[
  {
    "path": ".gitignore",
    "content": "assets/XVerseBench/animal/*\nassets/XVerseBench/object/*\n__pycache__\ncheckpoints/*\ngenerated_*\ntmp\n*.png"
  },
  {
    "path": ".gradio/certificate.pem",
    "content": "-----BEGIN CERTIFICATE-----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\n-----END CERTIFICATE-----\n"
  },
  {
    "path": "LICENCE",
    "content": "                                 Apache License\n                           Version 2.0, January 2004\n                        http://www.apache.org/licenses/\n\n   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n\n   1. Definitions.\n\n      \"License\" shall mean the terms and conditions for use, reproduction,\n      and distribution as defined by Sections 1 through 9 of this document.\n\n      \"Licensor\" shall mean the copyright owner or entity authorized by\n      the copyright owner that is granting the License.\n\n      \"Legal Entity\" shall mean the union of the acting entity and all\n      other entities that control, are controlled by, or are under common\n      control with that entity. For the purposes of this definition,\n      \"control\" means (i) the power, direct or indirect, to cause the\n      direction or management of such entity, whether by contract or\n      otherwise, or (ii) ownership of fifty percent (50%) or more of the\n      outstanding shares, or (iii) beneficial ownership of such entity.\n\n      \"You\" (or \"Your\") shall mean an individual or Legal Entity\n      exercising permissions granted by this License.\n\n      \"Source\" form shall mean the preferred form for making modifications,\n      including but not limited to software source code, documentation\n      source, and configuration files.\n\n      \"Object\" form shall mean any form resulting from mechanical\n      transformation or translation of a Source form, including but\n      not limited to compiled object code, generated documentation,\n      and conversions to other media types.\n\n      \"Work\" shall mean the work of authorship, whether in Source or\n      Object form, made available under the License, as indicated by a\n      copyright notice that is included in or attached to the work\n      (an example is provided in the Appendix below).\n\n      \"Derivative Works\" shall mean any work, whether in Source or Object\n      form, that is based on (or derived from) the Work and for which the\n      editorial revisions, annotations, elaborations, or other modifications\n      represent, as a whole, an original work of authorship. For the purposes\n      of this License, Derivative Works shall not include works that remain\n      separable from, or merely link (or bind by name) to the interfaces of,\n      the Work and Derivative Works thereof.\n\n      \"Contribution\" shall mean any work of authorship, including\n      the original version of the Work and any modifications or additions\n      to that Work or Derivative Works thereof, that is intentionally\n      submitted to Licensor for inclusion in the Work by the copyright owner\n      or by an individual or Legal Entity authorized to submit on behalf of\n      the copyright owner. For the purposes of this definition, \"submitted\"\n      means any form of electronic, verbal, or written communication sent\n      to the Licensor or its representatives, including but not limited to\n      communication on electronic mailing lists, source code control systems,\n      and issue tracking systems that are managed by, or on behalf of, the\n      Licensor for the purpose of discussing and improving the Work, but\n      excluding communication that is conspicuously marked or otherwise\n      designated in writing by the copyright owner as \"Not a Contribution.\"\n\n      \"Contributor\" shall mean Licensor and any individual or Legal Entity\n      on behalf of whom a Contribution has been received by Licensor and\n      subsequently incorporated within the Work.\n\n   2. Grant of Copyright License. Subject to the terms and conditions of\n      this License, each Contributor hereby grants to You a perpetual,\n      worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n      copyright license to reproduce, prepare Derivative Works of,\n      publicly display, publicly perform, sublicense, and distribute the\n      Work and such Derivative Works in Source or Object form.\n\n   3. Grant of Patent License. Subject to the terms and conditions of\n      this License, each Contributor hereby grants to You a perpetual,\n      worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n      (except as stated in this section) patent license to make, have made,\n      use, offer to sell, sell, import, and otherwise transfer the Work,\n      where such license applies only to those patent claims licensable\n      by such Contributor that are necessarily infringed by their\n      Contribution(s) alone or by combination of their Contribution(s)\n      with the Work to which such Contribution(s) was submitted. If You\n      institute patent litigation against any entity (including a\n      cross-claim or counterclaim in a lawsuit) alleging that the Work\n      or a Contribution incorporated within the Work constitutes direct\n      or contributory patent infringement, then any patent licenses\n      granted to You under this License for that Work shall terminate\n      as of the date such litigation is filed.\n\n   4. Redistribution. You may reproduce and distribute copies of the\n      Work or Derivative Works thereof in any medium, with or without\n      modifications, and in Source or Object form, provided that You\n      meet the following conditions:\n\n      (a) You must give any other recipients of the Work or\n          Derivative Works a copy of this License; and\n\n      (b) You must cause any modified files to carry prominent notices\n          stating that You changed the files; and\n\n      (c) You must retain, in the Source form of any Derivative Works\n          that You distribute, all copyright, patent, trademark, and\n          attribution notices from the Source form of the Work,\n          excluding those notices that do not pertain to any part of\n          the Derivative Works; and\n\n      (d) If the Work includes a \"NOTICE\" text file as part of its\n          distribution, then any Derivative Works that You distribute must\n          include a readable copy of the attribution notices contained\n          within such NOTICE file, excluding those notices that do not\n          pertain to any part of the Derivative Works, in at least one\n          of the following places: within a NOTICE text file distributed\n          as part of the Derivative Works; within the Source form or\n          documentation, if provided along with the Derivative Works; or,\n          within a display generated by the Derivative Works, if and\n          wherever such third-party notices normally appear. The contents\n          of the NOTICE file are for informational purposes only and\n          do not modify the License. You may add Your own attribution\n          notices within Derivative Works that You distribute, alongside\n          or as an addendum to the NOTICE text from the Work, provided\n          that such additional attribution notices cannot be construed\n          as modifying the License.\n\n      You may add Your own copyright statement to Your modifications and\n      may provide additional or different license terms and conditions\n      for use, reproduction, or distribution of Your modifications, or\n      for any such Derivative Works as a whole, provided Your use,\n      reproduction, and distribution of the Work otherwise complies with\n      the conditions stated in this License.\n\n   5. Submission of Contributions. Unless You explicitly state otherwise,\n      any Contribution intentionally submitted for inclusion in the Work\n      by You to the Licensor shall be under the terms and conditions of\n      this License, without any additional terms or conditions.\n      Notwithstanding the above, nothing herein shall supersede or modify\n      the terms of any separate license agreement you may have executed\n      with Licensor regarding such Contributions.\n\n   6. Trademarks. This License does not grant permission to use the trade\n      names, trademarks, service marks, or product names of the Licensor,\n      except as required for reasonable and customary use in describing the\n      origin of the Work and reproducing the content of the NOTICE file.\n\n   7. Disclaimer of Warranty. Unless required by applicable law or\n      agreed to in writing, Licensor provides the Work (and each\n      Contributor provides its Contributions) on an \"AS IS\" BASIS,\n      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or\n      implied, including, without limitation, any warranties or conditions\n      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A\n      PARTICULAR PURPOSE. You are solely responsible for determining the\n      appropriateness of using or redistributing the Work and assume any\n      risks associated with Your exercise of permissions under this License.\n\n   8. Limitation of Liability. In no event and under no legal theory,\n      whether in tort (including negligence), contract, or otherwise,\n      unless required by applicable law (such as deliberate and grossly\n      negligent acts) or agreed to in writing, shall any Contributor be\n      liable to You for damages, including any direct, indirect, special,\n      incidental, or consequential damages of any character arising as a\n      result of this License or out of the use or inability to use the\n      Work (including but not limited to damages for loss of goodwill,\n      work stoppage, computer failure or malfunction, or any and all\n      other commercial damages or losses), even if such Contributor\n      has been advised of the possibility of such damages.\n\n   9. Accepting Warranty or Additional Liability. While redistributing\n      the Work or Derivative Works thereof, You may choose to offer,\n      and charge a fee for, acceptance of support, warranty, indemnity,\n      or other liability obligations and/or rights consistent with this\n      License. However, in accepting such obligations, You may act only\n      on Your own behalf and on Your sole responsibility, not on behalf\n      of any other Contributor, and only if You agree to indemnify,\n      defend, and hold each Contributor harmless for any liability\n      incurred by, or claims asserted against, such Contributor by reason\n      of your accepting any such warranty or additional liability.\n\n   END OF TERMS AND CONDITIONS\n\n   APPENDIX: How to apply the Apache License to your work.\n\n      To apply the Apache License to your work, attach the following\n      boilerplate notice, with the fields enclosed by brackets \"[]\"\n      replaced with your own identifying information. (Don't include\n      the brackets!)  The text should be enclosed in the appropriate\n      comment syntax for the file format. We also recommend that a\n      file or class name and description of purpose be included on the\n      same \"printed page\" as the copyright notice for easier\n      identification within third-party archives.\n\n   Copyright [yyyy] [name of copyright owner]\n\n   Licensed under the Apache License, Version 2.0 (the \"License\");\n   you may not use this file except in compliance with the License.\n   You may obtain a copy of the License at\n\n       http://www.apache.org/licenses/LICENSE-2.0\n\n   Unless required by applicable law or agreed to in writing, software\n   distributed under the License is distributed on an \"AS IS\" BASIS,\n   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n   See the License for the specific language governing permissions and\n   limitations under the License.\n"
  },
  {
    "path": "README.md",
    "content": "# XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation\n\n<p align=\"center\">\n    <a href=\"https://arxiv.org/abs/2506.21416\">\n            <img alt=\"Build\" src=\"https://img.shields.io/badge/arXiv%20paper-2506.21416-b31b1b.svg\">\n    </a>\n    <a href=\"https://bytedance.github.io/XVerse/\">\n        <img alt=\"Project Page\" src=\"https://img.shields.io/badge/Project-Page-blue\">\n    </a>\n    <a href=\"https://github.com/bytedance/XVerse/tree/main/assets\">\n        <img alt=\"Build\" src=\"https://img.shields.io/badge/XVerseBench-Dataset-green\">\n    </a>\n    <a href=\"https://huggingface.co/ByteDance/XVerse\">\n        <img alt=\"Build\" src=\"https://img.shields.io/badge/🤗-HF%20Model-yellow\">\n    </a>    \n    <a href=\"https://huggingface.co/spaces/ByteDance/XVerse\">\n        <img alt=\"Build\" src=\"https://img.shields.io/badge/🤗-HF%20Demo-yellow\">\n    </a>\n</p>\n\n## 🔥 News\n- **2025.9.19**: 🎉 Congratulations! XVerse has been accepted by NeurIPS 2025! 🎉\n- **2025.7.18**: Supports quantized diffusion models, and add group offload to run the XVerse model in 16GB VRAM.\n- **2025.7.10**: Release huggingface space demo.\n- **2025.7.8**: Supports low VRAM inference, can run the XVerse model in 24GB VRAM.\n- **2025.6.26**: The code has been released!\n\n![XVerse's capability in single/multi-subject personalization and semantic attribute control (pose, style, lighting)](sample/first_page.png)\n\n## 📖 Introduction\n\n**XVerse** introduces a novel approach to multi-subject image synthesis, offering **precise and independent control over individual subjects** without disrupting the overall image latents or features. We achieve this by transforming reference images into offsets for token-specific text-stream modulation.\n\nThis innovation enables high-fidelity, editable image generation where you can robustly control both **individual subject characteristics** (identity) and their **semantic attributes**. XVerse significantly enhances capabilities for personalized and complex scene generation.\n\n## ⚡️ Quick Start\n\n### Requirements and Installation\n\nFirst, install the necessary dependencies:\n\n```bash\n# Create a conda environment named XVerse with Python version 3.10.16\nconda create -n XVerse python=3.10.16 -y\n# Activate the XVerse environment\nconda activate XVerse\n# Install the correct version of pytorch (According to your machine)\npip install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/cu124\n# Use pip to install the dependencies specified in requirements.txt\npip install -r requirements.txt\n# Install flash-attn\npip install flash-attn==2.7.4.post1 --no-build-isolation\n# Update version of httpx\npip install httpx==0.23.3\n```\n\nNext, download the required checkpoints:\n```bash\ncd checkpoints\nbash ./download_ckpts.sh\ncd ..\n```\n**Important**: You'll also need to download the face recognition model `model_ir_se50.pth` from [InsightFace_Pytorch](https://github.com/TreB1eN/InsightFace_Pytorch) and place it directly into the `./checkpoints/` folder.\n\nAfter that, you can export the model paths as environment variables. This step ensures that the subsequent inference scripts can locate the necessary models correctly:\n``` bash\nexport FLORENCE2_MODEL_PATH=\"./checkpoints/Florence-2-large\"\nexport SAM2_MODEL_PATH=\"./checkpoints/sam2.1_hiera_large.pt\"\nexport FACE_ID_MODEL_PATH=\"./checkpoints/model_ir_se50.pth\"\nexport CLIP_MODEL_PATH=\"./checkpoints/clip-vit-large-patch14\"\nexport FLUX_MODEL_PATH=\"./checkpoints/FLUX.1-dev\"\nexport DPG_VQA_MODEL_PATH=\"./checkpoints/mplug_visual-question-answering_coco_large_en\"\nexport DINO_MODEL_PATH=\"./checkpoints/dino-vits16\"\n```\n\n### Local Gradio Demo\n\nTo run the interactive Gradio demo locally, execute the following command:\n```bash\npython run_gradio.py\n```\n\n#### Input Settings Explained\nThe Gradio demo provides several parameters to control your image generation process:\n* **Prompt**: The textual description guiding the image generation.\n* **Generated Height/Width**: Use the sliders to set the shape of the output image.\n* **Weight_id/ip**: Adjust these weight parameters. Higher values generally lead to better subject consistency but might slightly impact the naturalness of the generated image.\n* **latent_lora_scale and vae_lora_scale**: Control the LoRA scale. Similar to Weight_id/ip, larger LoRA values can improve subject consistency but may reduce image naturalness.\n* **vae_skip_iter_before and vae_skip_iter_after**: Configure VAE skip iterations. Skipping more steps can result in better naturalness but might compromise subject consistency.\n\n#### Input Images\n\nThe demo provides detailed control over your input images:\n\n* **Expand Panel**: Click \"Input Image X\" to reveal the options for each image.\n* **Upload Image**: Click \"Image X\" to upload your desired reference image.\n* **Image Description**: Enter a description in the \"Caption X\" input box. You can also click \"Auto Caption\" to generate a description automatically.\n* **Detection & Segmentation**: Click \"Det & Seg\" to perform detection and segmentation on the uploaded image.\n* **Crop Face**: Use \"Crop Face\" to automatically crop the face from the image.\n* **ID Checkbox**: Check or uncheck \"ID or not\" to determine whether to use ID-related weights for that specific input image.\n\n> **⚠️ Important Usage Notes:**\n>\n> * **Prompt Construction**: The main text prompt **MUST** include the exact text you entered in the `Image Description` field for each active image. **Generation will fail if this description is missing from the prompt.**\n>     * *Example*: If you upload two images and set their descriptions as \"a man with red hair\" (for Image 1) and \"a woman with blue eyes\" (for Image 2), your main prompt might be: \"A `a man with red hair` walking beside `a woman with blue eyes` in a park.\"\n>     * You can then write your main prompt simply as: \"`ENT1` walking beside `ENT2` in a park.\" The code will **automatically replace** these placeholders with the full description text before generation.\n> * **Active Images**: Only images in **expanded** (un-collapsed) panels will be fed into the model. Collapsed image panels are ignored.\n\n### Inference with Single Sample\n\nTo perform inference on a single sample, run the following command. You can customize the image generation by adjusting the parameters such as the prompt, seed, and output size:\n```bash\npython inference_single_sample.py --prompt \"ENT1 wearing a tiny hat\" --seed 42 --cond_size 256 --target_height 768 --target_width 768 --weight_id 3 --weight_ip 5 --latent_lora_scale 0.85 --vae_lora_scale 1.3 --vae_skip_iter_s1 0.05 --vae_skip_iter_s2 0.8 --images \"sample/hamster.jpg\" --captions \"a hamster\" --idips false --save_path \"generated_image_1.png\" --num_images 1\n```\n\nFor inference with multiple condition images, use the command below. This allows you to incorporate multiple reference images into the generation process. Make sure to match the number of --images, --captions, and --ids values:\n```bash\npython inference_single_sample.py --prompt \"ENT1, and ENT2 standing together in a park.\" --seed 42 --cond_size 256 --target_height 768 --target_width 768 --weight_id 2 --weight_ip 5 --latent_lora_scale 0.85 --vae_lora_scale 1.3 --vae_skip_iter_s1 0.05 --vae_skip_iter_s2 0.8 --images \"sample/woman.jpg\" \"sample/girl.jpg\" --captions \"a woman\" \"a girl\" --idips true true --save_path \"generated_image_2.png\" --num_images 1\n```\n\n## ⚡️ Low-VRAM Inference\n\n### Offload Modules to CPU\n\n- During inference with a single sample or running gradio demo, you can enable low VRAM mode by adding the parameter `--use_low_vram True` or `--use_lower_vram True`. \n- `use_low_vram` allows you to perform inference with up to two conditional images on a GPU equipped with 24GB of VRAM.\n- `use_lower_vram` allows you to perform inference with up to three conditional images on a GPU equipped with 16GB of VRAM. \n- Note that CPU offload significantly reduces inference speed and should only be enabled when necessary.\n\n### Quantized Diffusion Models\n\n- You can download the quantized model from [here](https://huggingface.co/collections/diffusers/flux-quantized-checkpoints-682c951aebd378a2462984a0) into the checkpoints folder‌. Using the bnb-nf4 quantized model, you can run inference with a single condition on 32GB of VRAM, or perform inference with three conditions on 24GB of VRAM by enabling the CPU offloading feature. You need to modify the `FLUX_MODEL_PATH` environment variable and add the parameter `--dit_quant None`.\n- You can also download the GGUF quantized model from [here](https://huggingface.co/city96/FLUX.1-dev-gguf) into the checkpoints folder‌. Using this GGUF quantized model, you can perform two-condition inference with 32GB of video memory, or achieve four-condition-based inference in a 24GB video memory environment by enabling the CPU offloading feature. You can run the inference using the following commands:\n```bash\nexport FLUX_TRANSFORMERS_PATH=\"./checkpoints/FLUX.1-dev-gguf/flux1-dev-Q3_K_S.gguf\"\nexport FLUX_MODEL_PATH=\"./checkpoints/FLUX.1-dev\"\npython inference_single_sample.py --prompt \"ENT1, and ENT2 standing together in a park.\" --seed 42 --cond_size 256 --target_height 768 --target_width 768 --weight_id 3 --weight_ip 5 --latent_lora_scale 0.7 --vae_lora_scale 1.2 --vae_skip_iter_s1 0.05 --vae_skip_iter_s2 0.8 --images \"sample/woman.jpg\" \"sample/girl.jpg\" --captions \"a woman\" \"a girl\" --idips true true --save_path \"generated_image_2-GGUF.png\" --num_images 1 --dit_quant GGUF\n```\n**Note**: Quantized models may degrade the model's performance to some extent, and parameters like `weight_id`, `weight_ip`, and `lora_scale` may need to be re-adjusted.\n\n## Inference with XVerseBench\n\n![XVerseBench](sample/XVerseBench.png)\n\nFirst, please download XVerseBench according to the contents in the `assets` folder. Then, when running inference, please execute the following command:\n```bash\nbash ./eval/eval_scripts/run_eval.sh\n```\nThe script will automatically evaluate the model on the XVerseBench dataset and save the results in the `./results` folder.\n\n## 📌 ToDo\n\n- [x] Release github repo.\n- [x] Release arXiv paper.\n- [x] Release model checkpoints.\n- [x] Release inference data: XVerseBench.\n- [x] Release inference code for XVerseBench.\n- [x] Release inference code for gradio demo.\n- [x] Release inference code for single sample.\n- [x] Support inference in consumer-grade GPUs.\n- [x] Release huggingface space demo.\n- [x] Support quantized diffusion models.\n- [ ] Release Benchmark Leaderboard.\n- [ ] Release ComfyUI implementation.\n\n## License\n    \nThe code in this project is licensed under Apache 2.0; the dataset is licensed under CC0, subject to the intellctual property owned by Bytedance. Meanwhile, the dataset is adapted from [dreambench++](https://dreambenchplus.github.io/), you should also comply with the license of dreambench++.\n\n## Acknowledgments\nWe sincerely thank Alex Nasa for deploying the Hugging Face demo with the FLUX.1-schnell model. You can experience this online demo by clicking [here](https://huggingface.co/spaces/alexnasa/XVerse).\n    \n##  Citation\nIf XVerse is helpful, please help to ⭐ the repo.\n\nIf you find this project useful for your research, please consider citing our paper:\n```bibtex\n@article{chen2025xverse,\n  title={XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation},\n  author={Chen, Bowen and Zhao, Mengyi and Sun, Haomiao and Chen, Li and Wang, Xu and Du, Kang and Wu, Xinglong},\n  journal={arXiv preprint arXiv:2506.21416},\n  year={2025}\n\n\n}\n"
  },
  {
    "path": "assets/ReadMe.md",
    "content": "# Install of XVerseBench\n\nExisting controlled image generation benchmarks often focus on either maintaining identity or object appearance consistency, rarely encompassing datasets that rigorously test both aspects. To comprehensively assess the models' single-subject and multi-subject conditional generation and editing capabilities, we constructed a new benchmark by merging and curating data from DreamBench++ and some generated human images.\n\nOur resulting benchmark XVerseBench comprises 20 distinct human identities, 74 unique objects, and 45 different animal species/individuals. To thoroughly evaluate model effectiveness in subject-driven generation tasks, we developed test sets specifically for single-subject, dual-subject, and triple-subject control scenarios. This benchmark includes 300 unique test prompts covering diverse combinations of humans, objects, and animals. \n\n<p align=\"center\">\n  <img src=\"../sample/XVerseBench.png\" alt=\"XVerseBench\">\n</p>\n<p align=\"center\"><strong>Figure 1. XVerseBench</strong></p>\n\nThe above figure shows more detail information and samples for each categories. For evaluation, we employ a suite of metrics to quantify different aspects of generation quality and control fidelity: including DPG score to assess the model's editing capability, Face ID similarity and DINOv2 similarity to assess the model's preservation of human identity and objects, and Aesthetic Score to measure to evaluate the aesthetics of the generated image. XVerseBench aims to provide a more challenging and holistic evaluation framework for state-of-the-art multi-subject controllable text-to-image generation models.\n\n## Usage\n\n1. Download **DreamBench++** from [https://dreambenchplus.github.io/](https://dreambenchplus.github.io/) and place it into the `data/DreamBench++` directory.\n2. Run the following command to rename and segementate the images:\n   ```bash\n   python assets/rename.py\n   python assets/segmentation_sample.py\n   ```\n\n## Citation\nIf XVerseBench is helpful, please help to ⭐ the repo.\n\nIf you find this project useful for your research, please consider citing our paper:\n```bibtex\n@article{chen2025xverse,\n  title={XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation},\n  author={Chen, Bowen and Zhao, Mengyi and Sun, Haomiao and Chen, Li and Wang, Xu and Du, Kang and Wu, Xinglong},\n  journal={arXiv preprint arXiv:2506.21416},\n  year={2025}\n}\n```\n\n\n> Disclaimer：\n>\n> Your access to and use of this dataset are at your own risk. We do not guarantee the accuracy of this dataset. The dataset is provided “as is” and we make no warranty or representation to you with respect to it and we expressly disclaim, and hereby expressly waive, all warranties, express, implied, statutory or otherwise. This includes, without limitation, warranties of quality, performance, merchantability or fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable.\n> \n> In no event will we be liable to you on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this public license or use of the licensed material.\n>\n> The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.\n\n"
  },
  {
    "path": "assets/crop_faces.py",
    "content": "import os\nimport face_recognition\nfrom PIL import Image, ImageOps\nimport numpy as np\n\ndef detect_and_crop_faces(input_dir, output_dir):\n    # 确保输出目录存在\n    if not os.path.exists(output_dir):\n        os.makedirs(output_dir)\n\n    # 遍历输入目录中的所有文件\n    for filename in os.listdir(input_dir):\n        if filename.lower().endswith(('.png', '.jpg', '.jpeg')):\n            input_path = os.path.join(input_dir, filename)\n            output_path = os.path.join(output_dir, filename.replace('.png', '.jpg'))\n\n            # 加载图像并处理透明背景\n            image = Image.open(input_path).convert(\"RGBA\")\n            background = Image.new(\"RGBA\", image.size, \"WHITE\")\n            alpha_composite = Image.alpha_composite(background, image).convert(\"RGB\")\n\n            # 添加白色边缘，这里 padding 设为 10 像素，可按需调整\n            padded_image = ImageOps.expand(alpha_composite, border=10, fill='white')\n\n            # 尝试不同尺度的图像检测\n            scales = [0.6, 0.4, 0.2]\n            face_locations = []\n            for scale in scales:\n                resized_image = padded_image.resize((int(padded_image.width * scale), int(padded_image.height * scale)), Image.LANCZOS)\n                image_np = np.array(resized_image)\n                # Use the cnn model for detection\n                face_locations = face_recognition.face_locations(image_np, model=\"cnn\")\n                if face_locations:\n                    # Adjust the detected face positions to the original image size\n                    face_locations = [(int(top / scale), int(right / scale), int(bottom / scale), int(left / scale)) for top, right, bottom, left in face_locations]\n                    break\n\n            if face_locations:\n                # 假设第一个检测到的人脸是需要裁剪的\n                top, right, bottom, left = face_locations[0]\n                height = bottom - top\n                width = right - left\n\n                # 计算扩充后的区域\n                new_top = max(0, int(top - height * 0.3))\n                new_bottom = min(np.array(padded_image).shape[0], int(bottom + height * 0.3))\n                new_left = max(0, int(left - width * 0.3))\n                new_right = min(np.array(padded_image).shape[1], int(right + width * 0.3))\n\n                face_image = np.array(padded_image)[new_top:new_bottom, new_left:new_right]\n                # 将 NumPy 数组转换为 PIL 图像\n                face_pil = Image.fromarray(face_image)\n                # 保存裁剪后的人脸图像\n                face_pil.save(output_path)\n                print(f\"已裁剪并保存: {output_path}\")\n            else:\n                print(f\"未在 {input_path} 中检测到人脸\")\n\nif __name__ == \"__main__\":\n    input_directory = \"/mnt/bn/yg-butterfly-algo/personal/sunhm/code/XVerse/assets/XVerseBench_seg/human_seg\"\n    output_directory = \"/mnt/bn/yg-butterfly-algo/personal/sunhm/code/XVerse/assets/XVerseBench_seg/human\"\n    detect_and_crop_faces(input_directory, output_directory)\n"
  },
  {
    "path": "assets/rename.py",
    "content": "import os\nimport shutil\n\nsplit = [(\"live_subject/animal\", \"animal\"), (\"object\", \"object\")]\n\n# 定义目录路径\ncaption_dir_base = './data/DreamBench_plus/captions'\nimage_dir_base = './data/DreamBench_plus/images'\nnew_image_dir_base = './data/XVerseBench_rename'\n\nfor s, ts in split:\n    caption_dir = os.path.join(caption_dir_base, s)\n    image_dir = os.path.join(image_dir_base, s)\n    new_image_dir = os.path.join(new_image_dir_base, ts)\n\n    # 创建新的目标目录（如果不存在）\n    if not os.path.exists(new_image_dir):\n        os.makedirs(new_image_dir)\n\n    # 获取所有 caption 文件\n    caption_files = sorted([f for f in os.listdir(caption_dir) if f.endswith('.txt')])\n\n    for caption_file in caption_files:\n        # 提取索引\n        index = os.path.splitext(caption_file)[0]\n        # 构建 caption 文件完整路径\n        caption_file_path = os.path.join(caption_dir, caption_file)\n        # 构建对应的图片文件路径\n        image_file_name = f'{index}.jpg'\n        image_file_path = os.path.join(image_dir, image_file_name)\n\n        # 检查图片文件是否存在\n        if os.path.exists(image_file_path):\n            # 读取 caption 文件内容\n            with open(caption_file_path, 'r', encoding='utf-8') as f:\n                caption = f.read().split('\\n')[0].strip()\n\n            # 生成新的文件名\n            new_file_name = f'{index}_{caption}.jpg'\n            new_file_path_in_new_dir = os.path.join(new_image_dir, new_file_name)\n\n            # 移动并重命名文件\n            shutil.copy2(image_file_path, new_file_path_in_new_dir)\n            print(f'文件 {image_file_path} 已移动并重命名为 {new_file_path_in_new_dir}')\n        else:\n            print(f'未找到对应的图片文件: {image_file_path}')\n\n\nold_human_index = ['00', '05', '06', '09', '12', '13', '14', '16', '17']\n\n# 新增的文件映射\nnew_files = [\n    \"object/65_anime space ranger.jpg\", \"object/66_anime girl.jpg\", \"object/67_pixelated warrior.jpg\",\n    \"object/68_anime girl.jpg\", \"object/69_anime samurai.jpg\", \"object/70_anime girl.jpg\",\n    \"object/71_anime Spider-Man.jpg\", \"object/72_Avatar.jpg\", \"object/73_anime man.jpg\"\n]\n\n# 新增复制文件的代码\nfor old_human_index, new_file in zip(old_human_index, new_files):\n    # 构建原始图片文件路径\n    original_image_path = os.path.join(image_dir_base, \"live_subject/human\", f\"{old_human_index}.jpg\")\n    # 构建新的图片文件路径\n    new_image_path = os.path.join(new_image_dir_base, new_file)\n    \n    # 创建新文件的目录（如果不存在）\n    new_image_dir = os.path.dirname(new_image_path)\n    if not os.path.exists(new_image_dir):\n        os.makedirs(new_image_dir)\n    \n    # 检查原始图片文件是否存在\n    if os.path.exists(original_image_path):\n        # 复制文件\n        shutil.copy2(original_image_path, new_image_path)\n        print(f'文件 {original_image_path} 已复制到 {new_image_path}')\n    else:\n        print(f'未找到对应的图片文件: {original_image_path}')"
  },
  {
    "path": "assets/segmentation.py",
    "content": "from src.utils.data_utils import get_train_config, image_grid, pil2tensor, json_dump, pad_to_square, cv2pil, merge_bboxes\nfrom eval.tools.florence_sam import ObjectDetector\nimport torch\nimport os\nfrom PIL import Image  # 补充导入 Image 模块\nimport numpy as np\n\ndef merge_instances(orig_img, indices, ins_bboxes, ins_images):\n    orig_image_width, orig_image_height = orig_img.width, orig_img.height\n    final_img = Image.new(\"RGB\", (orig_image_width, orig_image_height), color=(255, 255, 255))\n    bboxes = []\n    for i in indices:\n        bbox = np.array(ins_bboxes[i], dtype=int).tolist()\n        bboxes.append(bbox)\n        \n        img = cv2pil(ins_images[i])\n        mask = (np.array(img)[..., :3] != 255).any(axis=-1)\n        mask = Image.fromarray(mask.astype(np.uint8) * 255, mode='L')\n        final_img.paste(img, (bbox[0], bbox[1]), mask)\n    \n    bbox = merge_bboxes(bboxes)\n    img = final_img.crop(bbox)\n    return img, bbox\n\ndtype = torch.bfloat16\ndevice = \"cuda\"\ndetector = ObjectDetector(device)\ndef det_seg_img(image, label):\n    if isinstance(image, str):\n        image = Image.open(image).convert(\"RGB\")\n    instance_result_dict = detector.get_multiple_instances(image, label, min_size=image.size[0]//20)\n    indices = list(range(len(instance_result_dict[\"instance_images\"])))\n    ins, bbox = merge_instances(image, indices, instance_result_dict[\"instance_bboxes\"], instance_result_dict[\"instance_images\"])\n    return ins\n\ndef segment_images_in_folder(input_folder, output_folder):\n    \"\"\"\n    对输入文件夹内所有图像进行分割，并将结果保存到输出文件夹。\n\n    :param input_folder: 输入图像文件夹路径\n    :param output_folder: 输出分割结果的文件夹路径\n    \"\"\"\n    # 确保输出文件夹存在\n    os.makedirs(output_folder, exist_ok=True)\n\n    # 遍历输入文件夹及其子文件夹内的所有文件\n    for root, _, filenames in os.walk(input_folder):\n        for filename in filenames:\n            # 检查是否为图像文件\n            if filename.lower().endswith(('.png', '.jpg', '.jpeg')):\n                file_path = os.path.join(root, filename)\n                try:\n                    # 从文件名中提取标签，假设文件名格式为 \"数字_标签.png\"\n                    label = filename.split('_')[-1].rsplit('.', 1)[0].strip()\n                    # 进行图像分割\n                    segmentation_result = det_seg_img(file_path, label)\n                    # 构建输出文件路径，保持原文件名\n                    relative_path = os.path.relpath(root, input_folder)\n                    output_subfolder = os.path.join(output_folder, relative_path)\n                    os.makedirs(output_subfolder, exist_ok=True)\n                    output_path = os.path.join(output_subfolder, filename)\n                    # 保存分割结果\n                    if isinstance(segmentation_result, Image.Image):\n                        segmentation_result.save(output_path)\n                    else:\n                        # 假设 segmentation_result 是可转换为 PIL Image 的对象\n                        Image.fromarray(segmentation_result).save(output_path)\n                except Exception as e:\n                    print(f\"处理文件 {file_path} 时出错: {e}\")\n\n\n# 使用示例\nif __name__ == \"__main__\":\n    input_folder = \"./assets/XverseBench_rename\"\n    output_folder = \"./assets/XVerseBench\"\n    segment_images_in_folder(input_folder, output_folder)\n"
  },
  {
    "path": "eval/eval_scripts/run_eval_multi.sh",
    "content": "export config_path=\"./train/config/XVerse_config_INF.yaml\"\nexport model_checkpoint=\"./checkpoints/XVerse\"\nexport target_size=768\nexport condition_size=256\nexport test_list_name=\"XVerseBench_multi\"\nexport save_name=\"./eval/XVerseBench_multi\"\n\nports=(`echo $METIS_WORKER_0_PORT | tr ',' ' '`)\nport=${ports[-1]}\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_gen_split_idip \\\n    --config_name \"$config_path\" \\\n    --model_path \"$model_checkpoint\" \\\n    --target_size \"$target_size\" \\\n    --condition_size \"$condition_size\" \\\n    --save_name \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_dpg_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_aes_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_face_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_sam-dino_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\npython \\\n    -m eval.tools.log_scores \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n"
  },
  {
    "path": "eval/eval_scripts/run_eval_single.sh",
    "content": "export config_path=\"./train/config/XVerse_config_INF.yaml\"\nexport model_checkpoint=\"./checkpoints/XVerse\"\nexport target_size=768\nexport condition_size=256\nexport test_list_name=\"XVerseBench_single\"\nexport save_name=\"./eval/XVerseBench_singleidip\"\n\nports=(`echo $METIS_WORKER_0_PORT | tr ',' ' '`)\nport=${ports[-1]}\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_gen_split_idip \\\n    --config_name \"$config_path\" \\\n    --model_path \"$model_checkpoint\" \\\n    --target_size \"$target_size\" \\\n    --condition_size \"$condition_size\" \\\n    --save_name \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_dpg_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_aes_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_face_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\naccelerate launch \\\n    --main_process_port $port \\\n    -m eval.tools.idip_sam-dino_score \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n\npython \\\n    -m eval.tools.log_scores \\\n    --input_dir \"$save_name\" \\\n    --test_list_name \"$test_list_name\"\n"
  },
  {
    "path": "eval/grounded_sam/florence2/config.json",
    "content": "{\n  \"_name_or_path\": \"florence2\",\n  \"architectures\": [\n    \"Florence2ForConditionalGeneration\"\n  ],\n  \"auto_map\": {\n    \"AutoConfig\": \"configuration_florence2.Florence2Config\",\n    \"AutoModelForCausalLM\": \"modeling_florence2.Florence2ForConditionalGeneration\"\n  },\n  \"bos_token_id\": 0,\n  \"eos_token_id\": 2,\n  \"ignore_index\": -100,\n  \"model_type\": \"florence2\",\n  \"pad_token_id\": 1,\n  \"projection_dim\": 1024,\n  \"text_config\": {\n      \"vocab_size\": 51289,\n      \"activation_dropout\": 0.1,\n      \"activation_function\": \"gelu\",\n      \"add_bias_logits\": false,\n      \"add_final_layer_norm\": false,\n      \"attention_dropout\": 0.1,\n      \"bos_token_id\": 0,\n      \"classif_dropout\": 0.1,\n      \"classifier_dropout\": 0.0,\n      \"d_model\": 1024,\n      \"decoder_attention_heads\": 16,\n      \"decoder_ffn_dim\": 4096,\n      \"decoder_layerdrop\": 0.0,\n      \"decoder_layers\": 12,\n      \"decoder_start_token_id\": 2,\n      \"dropout\": 0.1,\n      \"early_stopping\": true,\n      \"encoder_attention_heads\": 16,\n      \"encoder_ffn_dim\": 4096,\n      \"encoder_layerdrop\": 0.0,\n      \"encoder_layers\": 12,\n      \"eos_token_id\": 2,\n      \"forced_eos_token_id\": 2,\n      \"forced_bos_token_id\": 0,\n      \"gradient_checkpointing\": false,\n      \"init_std\": 0.02,\n      \"is_encoder_decoder\": true,\n      \"label2id\": {\n        \"LABEL_0\": 0,\n        \"LABEL_1\": 1,\n        \"LABEL_2\": 2\n      },\n      \"max_position_embeddings\": 1024,\n      \"no_repeat_ngram_size\": 3,\n      \"normalize_before\": false,\n      \"num_hidden_layers\": 12,\n      \"pad_token_id\": 1,\n      \"scale_embedding\": false,\n      \"num_beams\": 3\n  },\n  \"vision_config\": {\n    \"model_type\": \"davit\",\n    \"drop_path_rate\": 0.1,  \n    \"patch_size\": [7, 3, 3, 3],  \n    \"patch_stride\": [4, 2, 2, 2],  \n    \"patch_padding\": [3, 1, 1, 1],  \n    \"patch_prenorm\": [false, true, true, true],  \n    \"enable_checkpoint\": false,  \n    \"dim_embed\": [256, 512, 1024, 2048],  \n    \"num_heads\": [8, 16, 32, 64],  \n    \"num_groups\": [8, 16, 32, 64],  \n    \"depths\": [1, 1, 9, 1],  \n    \"window_size\": 12,\n    \"projection_dim\": 1024,\n    \"visual_temporal_embedding\": {\n        \"type\": \"COSINE\",\n        \"max_temporal_embeddings\": 100\n    },\n    \"image_pos_embed\": {\n        \"type\": \"learned_abs_2d\",\n        \"max_pos_embeddings\": 50\n    },\n    \"image_feature_source\": [\"spatial_avg_pool\", \"temporal_avg_pool\"]\n  },\n  \"vocab_size\": 51289,\n  \"torch_dtype\": \"float16\",\n  \"transformers_version\": \"4.41.0.dev0\",\n  \"is_encoder_decoder\": true\n}"
  },
  {
    "path": "eval/grounded_sam/florence2/configuration_florence2.py",
    "content": "# coding=utf-8\n# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\nimport warnings\n\"\"\" Florence-2 configuration\"\"\"\n\nfrom typing import Optional\n\nfrom transformers import AutoConfig\nfrom transformers.configuration_utils import PretrainedConfig\nfrom transformers.utils import logging\n\nlogger = logging.get_logger(__name__)\n\nclass Florence2VisionConfig(PretrainedConfig):\n    r\"\"\"\n    This is the configuration class to store the configuration of a [`Florence2VisionModel`]. It is used to instantiate a Florence2VisionModel\n    according to the specified arguments, defining the model architecture. Instantiating a configuration with the \n    defaults will yield a similar configuration to that of the Florence2VisionModel architecture.\n\n    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the\n    documentation from [`PretrainedConfig`] for more information.\n\n    Args:\n        drop_path_rate (`float`, *optional*, defaults to 0.1):\n            The dropout rate of the drop path layer.\n        patch_size (`List[int]`, *optional*, defaults to [7, 3, 3, 3]):\n            The patch size of the image.\n        patch_stride (`List[int]`, *optional*, defaults to [4, 2, 2, 2]):\n            The patch stride of the image.\n        patch_padding (`List[int]`, *optional*, defaults to [3, 1, 1, 1]):\n            The patch padding of the image.\n        patch_prenorm (`List[bool]`, *optional*, defaults to [false, true, true, true]):\n            Whether to apply layer normalization before the patch embedding layer.\n        enable_checkpoint (`bool`, *optional*, defaults to False):\n            Whether to enable checkpointing.\n        dim_embed (`List[int]`, *optional*, defaults to [256, 512, 1024, 2048]):\n            The dimension of the embedding layer.\n        num_heads (`List[int]`, *optional*, defaults to [8, 16, 32, 64]):\n            The number of attention heads.\n        num_groups (`List[int]`, *optional*, defaults to [8, 16, 32, 64]):\n            The number of groups.\n        depths (`List[int]`, *optional*, defaults to [1, 1, 9, 1]):\n            The depth of the model.\n        window_size (`int`, *optional*, defaults to 12):\n            The window size of the model.\n        projection_dim (`int`, *optional*, defaults to 1024):\n            The dimension of the projection layer.\n        visual_temporal_embedding (`dict`, *optional*):\n            The configuration of the visual temporal embedding.\n        image_pos_embed (`dict`, *optional*):\n            The configuration of the image position embedding.\n        image_feature_source (`List[str]`, *optional*, defaults to [\"spatial_avg_pool\", \"temporal_avg_pool\"]):\n            The source of the image feature.\n    Example:\n\n    ```python\n    >>> from transformers import Florence2VisionConfig, Florence2VisionModel\n\n    >>> # Initializing a Florence2 Vision style configuration\n    >>> configuration = Florence2VisionConfig()\n\n    >>> # Initializing a model (with random weights)\n    >>> model = Florence2VisionModel(configuration)\n\n    >>> # Accessing the model configuration\n    >>> configuration = model.config\n    ```\"\"\"\n\n    model_type = \"florence2_vision\"\n    keys_to_ignore_at_inference = [\"past_key_values\"]\n\n    def __init__(\n        self,\n        drop_path_rate=0.1,\n        patch_size=[7, 3, 3, 3],\n        patch_stride=[4, 2, 2, 2],\n        patch_padding=[3, 1, 1, 1],\n        patch_prenorm=[False, True, True, True],\n        enable_checkpoint=False,\n        dim_embed=[256, 512, 1024, 2048],\n        num_heads=[8, 16, 32, 64],\n        num_groups=[8, 16, 32, 64],\n        depths=[1, 1, 9, 1],\n        window_size=12,\n        projection_dim=1024,\n        visual_temporal_embedding=None,\n        image_pos_embed=None,\n        image_feature_source=[\"spatial_avg_pool\", \"temporal_avg_pool\"],\n        **kwargs,\n    ):\n        self.drop_path_rate = drop_path_rate\n        self.patch_size = patch_size\n        self.patch_stride = patch_stride\n        self.patch_padding = patch_padding\n        self.patch_prenorm = patch_prenorm\n        self.enable_checkpoint = enable_checkpoint\n        self.dim_embed = dim_embed\n        self.num_heads = num_heads\n        self.num_groups = num_groups\n        self.depths = depths\n        self.window_size = window_size\n        self.projection_dim = projection_dim\n        self.visual_temporal_embedding = visual_temporal_embedding\n        self.image_pos_embed = image_pos_embed\n        self.image_feature_source = image_feature_source\n\n        super().__init__(**kwargs)\n\n\n\nclass Florence2LanguageConfig(PretrainedConfig):\n    r\"\"\"\n    This is the configuration class to store the configuration of a [`Florence2LanguagePreTrainedModel`]. It is used to instantiate a BART\n    model according to the specified arguments, defining the model architecture. Instantiating a configuration with the\n    defaults will yield a similar configuration to that of the BART\n    [facebook/bart-large](https://huggingface.co/facebook/bart-large) architecture.\n\n    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the\n    documentation from [`PretrainedConfig`] for more information.\n\n\n    Args:\n        vocab_size (`int`, *optional*, defaults to 51289):\n            Vocabulary size of the Florence2Language model. Defines the number of different tokens that can be represented by the\n            `inputs_ids` passed when calling [`Florence2LanguageModel`].\n        d_model (`int`, *optional*, defaults to 1024):\n            Dimensionality of the layers and the pooler layer.\n        encoder_layers (`int`, *optional*, defaults to 12):\n            Number of encoder layers.\n        decoder_layers (`int`, *optional*, defaults to 12):\n            Number of decoder layers.\n        encoder_attention_heads (`int`, *optional*, defaults to 16):\n            Number of attention heads for each attention layer in the Transformer encoder.\n        decoder_attention_heads (`int`, *optional*, defaults to 16):\n            Number of attention heads for each attention layer in the Transformer decoder.\n        decoder_ffn_dim (`int`, *optional*, defaults to 4096):\n            Dimensionality of the \"intermediate\" (often named feed-forward) layer in decoder.\n        encoder_ffn_dim (`int`, *optional*, defaults to 4096):\n            Dimensionality of the \"intermediate\" (often named feed-forward) layer in decoder.\n        activation_function (`str` or `function`, *optional*, defaults to `\"gelu\"`):\n            The non-linear activation function (function or string) in the encoder and pooler. If string, `\"gelu\"`,\n            `\"relu\"`, `\"silu\"` and `\"gelu_new\"` are supported.\n        dropout (`float`, *optional*, defaults to 0.1):\n            The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.\n        attention_dropout (`float`, *optional*, defaults to 0.0):\n            The dropout ratio for the attention probabilities.\n        activation_dropout (`float`, *optional*, defaults to 0.0):\n            The dropout ratio for activations inside the fully connected layer.\n        classifier_dropout (`float`, *optional*, defaults to 0.0):\n            The dropout ratio for classifier.\n        max_position_embeddings (`int`, *optional*, defaults to 1024):\n            The maximum sequence length that this model might ever be used with. Typically set this to something large\n            just in case (e.g., 512 or 1024 or 2048).\n        init_std (`float`, *optional*, defaults to 0.02):\n            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.\n        encoder_layerdrop (`float`, *optional*, defaults to 0.0):\n            The LayerDrop probability for the encoder. See the [LayerDrop paper](see https://arxiv.org/abs/1909.11556)\n            for more details.\n        decoder_layerdrop (`float`, *optional*, defaults to 0.0):\n            The LayerDrop probability for the decoder. See the [LayerDrop paper](see https://arxiv.org/abs/1909.11556)\n            for more details.\n        scale_embedding (`bool`, *optional*, defaults to `False`):\n            Scale embeddings by diving by sqrt(d_model).\n        use_cache (`bool`, *optional*, defaults to `True`):\n            Whether or not the model should return the last key/values attentions (not used by all models).\n        num_labels (`int`, *optional*, defaults to 3):\n            The number of labels to use in [`Florence2LanguageForSequenceClassification`].\n        forced_eos_token_id (`int`, *optional*, defaults to 2):\n            The id of the token to force as the last generated token when `max_length` is reached. Usually set to\n            `eos_token_id`.\n\n    Example:\n\n    ```python\n    >>> from transformers import Florence2LanguageConfig, Florence2LanguageModel\n\n    >>> # Initializing a Florence2 Language style configuration\n    >>> configuration = Florence2LanguageConfig()\n\n    >>> # Initializing a model (with random weights)\n    >>> model = Florence2LangaugeModel(configuration)\n\n    >>> # Accessing the model configuration\n    >>> configuration = model.config\n    ```\"\"\"\n\n    model_type = \"florence2_language\"\n    keys_to_ignore_at_inference = [\"past_key_values\"]\n    attribute_map = {\"num_attention_heads\": \"encoder_attention_heads\", \"hidden_size\": \"d_model\"}\n\n    def __init__(\n        self,\n        vocab_size=51289,\n        max_position_embeddings=1024,\n        encoder_layers=12,\n        encoder_ffn_dim=4096,\n        encoder_attention_heads=16,\n        decoder_layers=12,\n        decoder_ffn_dim=4096,\n        decoder_attention_heads=16,\n        encoder_layerdrop=0.0,\n        decoder_layerdrop=0.0,\n        activation_function=\"gelu\",\n        d_model=1024,\n        dropout=0.1,\n        attention_dropout=0.0,\n        activation_dropout=0.0,\n        init_std=0.02,\n        classifier_dropout=0.0,\n        scale_embedding=False,\n        use_cache=True,\n        num_labels=3,\n        pad_token_id=1,\n        bos_token_id=0,\n        eos_token_id=2,\n        is_encoder_decoder=True,\n        decoder_start_token_id=2,\n        forced_eos_token_id=2,\n        **kwargs,\n    ):\n        self.vocab_size = vocab_size\n        self.max_position_embeddings = max_position_embeddings\n        self.d_model = d_model\n        self.encoder_ffn_dim = encoder_ffn_dim\n        self.encoder_layers = encoder_layers\n        self.encoder_attention_heads = encoder_attention_heads\n        self.decoder_ffn_dim = decoder_ffn_dim\n        self.decoder_layers = decoder_layers\n        self.decoder_attention_heads = decoder_attention_heads\n        self.dropout = dropout\n        self.attention_dropout = attention_dropout\n        self.activation_dropout = activation_dropout\n        self.activation_function = activation_function\n        self.init_std = init_std\n        self.encoder_layerdrop = encoder_layerdrop\n        self.decoder_layerdrop = decoder_layerdrop\n        self.classifier_dropout = classifier_dropout\n        self.use_cache = use_cache\n        self.num_hidden_layers = encoder_layers\n        self.scale_embedding = scale_embedding  # scale factor will be sqrt(d_model) if True\n\n        super().__init__(\n            num_labels=num_labels,\n            pad_token_id=pad_token_id,\n            bos_token_id=bos_token_id,\n            eos_token_id=eos_token_id,\n            is_encoder_decoder=is_encoder_decoder,\n            decoder_start_token_id=decoder_start_token_id,\n            forced_eos_token_id=forced_eos_token_id,\n            **kwargs,\n        )\n\n        # ensure backward compatibility for BART CNN models\n        if self.forced_bos_token_id is None and kwargs.get(\"force_bos_token_to_be_generated\", False):\n            self.forced_bos_token_id = self.bos_token_id\n            warnings.warn(\n                f\"Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. \"\n                \"The config can simply be saved and uploaded again to be fixed.\"\n            )\n\nclass Florence2Config(PretrainedConfig):\n    r\"\"\"\n    This is the configuration class to store the configuration of a [`Florence2ForConditionalGeneration`]. It is used to instantiate an\n    Florence-2 model according to the specified arguments, defining the model architecture. \n\n    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the\n    documentation from [`PretrainedConfig`] for more information.\n\n    Args:\n        vision_config (`Florence2VisionConfig`,  *optional*):\n            Custom vision config or dict\n        text_config (`Union[AutoConfig, dict]`, *optional*):\n            The config object of the text backbone. \n        ignore_index (`int`, *optional*, defaults to -100):\n            The ignore index for the loss function.\n        vocab_size (`int`, *optional*, defaults to 51289):\n            Vocabulary size of the Florence2model. Defines the number of different tokens that can be represented by the\n            `inputs_ids` passed when calling [`~Florence2ForConditionalGeneration`]\n        projection_dim (`int`, *optional*, defaults to 1024):\n            Dimension of the multimodal projection space.\n\n    Example:\n\n    ```python\n    >>> from transformers import Florence2ForConditionalGeneration, Florence2Config, CLIPVisionConfig, BartConfig\n\n    >>> # Initializing a clip-like vision config\n    >>> vision_config = CLIPVisionConfig()\n\n    >>> # Initializing a Bart config\n    >>> text_config = BartConfig()\n\n    >>> # Initializing a Florence-2 configuration\n    >>> configuration = Florence2Config(vision_config, text_config)\n\n    >>> # Initializing a model from the florence-2 configuration\n    >>> model = Florence2ForConditionalGeneration(configuration)\n\n    >>> # Accessing the model configuration\n    >>> configuration = model.config\n    ```\"\"\"\n\n    model_type = \"florence2\"\n    is_composition = False\n\n    def __init__(\n        self,\n        vision_config=None,\n        text_config=None,\n        ignore_index=-100,\n        vocab_size=51289,\n        projection_dim=1024,\n        **kwargs,\n    ):\n        self.ignore_index = ignore_index\n        self.vocab_size = vocab_size\n        self.projection_dim = projection_dim\n        if vision_config is not None:\n            vision_config = PretrainedConfig(**vision_config)\n        self.vision_config = vision_config\n        self.vocab_size = self.vocab_size\n\n        self.text_config = text_config\n        if text_config is not None:\n            self.text_config = Florence2LanguageConfig(**text_config)\n\n\n        super().__init__(**kwargs)\n\n"
  },
  {
    "path": "eval/grounded_sam/florence2/generation_config.json",
    "content": "{\n    \"num_beams\": 3,\n    \"early_stopping\": false\n}"
  },
  {
    "path": "eval/grounded_sam/florence2/modeling_florence2.py",
    "content": "# coding=utf-8\n# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n\"\"\" PyTorch Florence-2 model.\"\"\"\nfrom dataclasses import dataclass\nfrom typing import List, Optional, Tuple, Union\n\nimport math\nimport torch\nimport torch.utils.checkpoint\nfrom torch import nn\nimport torch.nn.functional as F\nimport torch.utils.checkpoint as checkpoint\nfrom torch.nn import CrossEntropyLoss \nfrom collections import OrderedDict\nfrom einops import rearrange\nfrom timm.models.layers import DropPath, trunc_normal_\n\nfrom transformers.modeling_utils import PreTrainedModel\nfrom transformers.generation.utils import GenerationMixin\nfrom transformers.utils import (\n    ModelOutput,\n    add_start_docstrings,\n    add_start_docstrings_to_model_forward,\n    is_flash_attn_2_available,\n    logging,\n    replace_return_docstrings,\n    is_flash_attn_2_available,\n    is_flash_attn_greater_or_equal_2_10,\n)\nfrom .configuration_florence2 import Florence2Config \nfrom .configuration_florence2 import Florence2LanguageConfig\nfrom .configuration_florence2 import Florence2VisionConfig\n\n\nfrom transformers.activations import ACT2FN\nfrom transformers.modeling_attn_mask_utils import (\n    _prepare_4d_attention_mask,\n    _prepare_4d_attention_mask_for_sdpa,\n    _prepare_4d_causal_attention_mask,\n    _prepare_4d_causal_attention_mask_for_sdpa,\n)\nfrom transformers.modeling_outputs import (\n    BaseModelOutput,\n    BaseModelOutputWithPastAndCrossAttentions,\n    Seq2SeqLMOutput,\n    Seq2SeqModelOutput,\n)\n\n\nif is_flash_attn_2_available():\n    from flash_attn.bert_padding import index_first_axis, pad_input, unpad_input  # noqa\n\nlogger = logging.get_logger(__name__)\n\n_CONFIG_FOR_DOC = \"Florence2Config\"\n\nclass LearnedAbsolutePositionEmbedding2D(nn.Module):\n    \"\"\"\n    This module learns positional embeddings up to a fixed maximum size.\n    \"\"\"\n\n    def __init__(self, embedding_dim=256, num_pos=50):\n        super().__init__()\n        self.row_embeddings = nn.Embedding(num_pos, embedding_dim // 2)\n        self.column_embeddings = nn.Embedding(num_pos, embedding_dim - (embedding_dim // 2))\n\n    def forward(self, pixel_values):\n        \"\"\"\n        pixel_values: (batch_size, height, width, num_channels) \n        returns: (batch_size, height, width, embedding_dim * 2)\n        \"\"\"\n        if len(pixel_values.shape) != 4:\n            raise ValueError('pixel_values must be a 4D tensor')\n        height, width = pixel_values.shape[1:3]\n        width_values = torch.arange(width, device=pixel_values.device)\n        height_values = torch.arange(height, device=pixel_values.device)\n        x_emb = self.column_embeddings(width_values)\n        y_emb = self.row_embeddings(height_values)\n        # (height, width, embedding_dim * 2)\n        pos = torch.cat([x_emb.unsqueeze(0).repeat(height, 1, 1), y_emb.unsqueeze(1).repeat(1, width, 1)], dim=-1)\n        # (embedding_dim * 2, height, width)\n        pos = pos.permute(2, 0, 1)\n        pos = pos.unsqueeze(0)\n        # (batch_size, embedding_dim * 2, height, width)\n        pos = pos.repeat(pixel_values.shape[0], 1, 1, 1)\n        # (batch_size, height, width, embedding_dim * 2)\n        pos = pos.permute(0, 2, 3, 1)\n        return pos\n\nclass PositionalEmbeddingCosine1D(nn.Module):\n    \"\"\"\n    This class implements a very simple positional encoding. It follows closely\n    the encoder from the link below:\n    https://pytorch.org/tutorials/beginner/translation_transformer.html\n\n    Args:\n        embed_dim: The dimension of the embeddings.\n        dropout_prob: The dropout probability.\n        max_seq_len: The maximum length to precompute the positional encodings.\n    \"\"\"\n    def __init__(\n            self,\n            embed_dim: int = 512,\n            max_seq_len: int = 1024) -> None:\n        super(PositionalEmbeddingCosine1D, self).__init__()\n        self.embed_dim = embed_dim\n        self.max_seq_len = max_seq_len\n        # Generate the sinusoidal arrays.\n        factor = math.log(10000)\n        denominator = torch.exp(\n            -factor * torch.arange(0, self.embed_dim, 2) / self.embed_dim)\n        # Matrix where rows correspond to a positional embedding as a function\n        # of the position index (i.e., the row index).\n        frequencies = \\\n            torch.arange(0, self.max_seq_len) \\\n            .reshape(self.max_seq_len, 1) * denominator\n        pos_idx_to_embed = torch.zeros((self.max_seq_len, self.embed_dim))\n        # Populate uneven entries.\n        pos_idx_to_embed[:, 0::2] = torch.sin(frequencies)\n        pos_idx_to_embed[:, 1::2] = torch.cos(frequencies)\n        # Save the positional embeddings in a constant buffer.\n        self.register_buffer(\"pos_idx_to_embed\", pos_idx_to_embed)\n\n    def forward(self, seq_embeds: torch.Tensor) -> torch.Tensor:\n        \"\"\"\n        Args:\n            seq_embeds: The sequence embeddings in order. Allowed size:\n                1. [T, D], where T is the length of the sequence, and D is the\n                frame embedding dimension.\n                2. [B, T, D], where B is the batch size and T and D are the\n                same as above.\n\n        Returns a tensor of with the same dimensions as the input: i.e.,\n        [1, T, D] or [T, D].\n        \"\"\"\n        shape_len = len(seq_embeds.shape)\n        assert 2 <= shape_len <= 3\n        len_seq = seq_embeds.size(-2)\n        assert len_seq <= self.max_seq_len\n        pos_embeds = self.pos_idx_to_embed[0:seq_embeds.size(-2), :]\n        # Adapt pre-computed positional embeddings to the input.\n        if shape_len == 3:\n            pos_embeds = pos_embeds.view(\n                (1, pos_embeds.size(0), pos_embeds.size(1)))\n        return pos_embeds\n\n\nclass LearnedAbsolutePositionEmbedding1D(nn.Module):\n    \"\"\"\n    Learnable absolute positional embeddings for 1D sequences.\n\n    Args:\n        embed_dim: The dimension of the embeddings.\n        max_seq_len: The maximum length to precompute the positional encodings.\n    \"\"\"\n    def __init__(\n            self,\n            embedding_dim: int = 512,\n            num_pos: int = 1024) -> None:\n        super(LearnedAbsolutePositionEmbedding1D, self).__init__()\n        self.embeddings = nn.Embedding(num_pos, embedding_dim)\n        self.num_pos = num_pos\n\n    def forward(self, seq_embeds: torch.Tensor) -> torch.Tensor:\n        \"\"\"\n        Args:\n            seq_embeds: The sequence embeddings in order. Allowed size:\n                1. [T, D], where T is the length of the sequence, and D is the\n                frame embedding dimension.\n                2. [B, T, D], where B is the batch size and T and D are the\n                same as above.\n\n        Returns a tensor of with the same dimensions as the input: i.e.,\n        [1, T, D] or [T, D].\n        \"\"\"\n        shape_len = len(seq_embeds.shape)\n        assert 2 <= shape_len <= 3\n        len_seq = seq_embeds.size(-2)\n        assert len_seq <= self.num_pos\n        # [T, D]\n        pos_embeds = self.embeddings(torch.arange(len_seq).to(seq_embeds.device))\n        # Adapt pre-computed positional embeddings to the input.\n        if shape_len == 3:\n            pos_embeds = pos_embeds.view(\n                (1, pos_embeds.size(0), pos_embeds.size(1)))\n        return pos_embeds\n\n\n\nclass MySequential(nn.Sequential):\n    def forward(self, *inputs):\n        for module in self._modules.values():\n            if type(inputs) == tuple:\n                inputs = module(*inputs)\n            else:\n                inputs = module(inputs)\n        return inputs\n\n\nclass PreNorm(nn.Module):\n    def __init__(self, norm, fn, drop_path=None):\n        super().__init__()\n        self.norm = norm\n        self.fn = fn\n        self.drop_path = drop_path\n\n    def forward(self, x, *args, **kwargs):\n        shortcut = x\n        if self.norm != None:\n            x, size = self.fn(self.norm(x), *args, **kwargs)\n        else:\n            x, size = self.fn(x, *args, **kwargs)\n\n        if self.drop_path:\n            x = self.drop_path(x)\n\n        x = shortcut + x\n\n        return x, size\n\n\nclass Mlp(nn.Module):\n    def __init__(\n        self,\n        in_features,\n        hidden_features=None,\n        out_features=None,\n        act_layer=nn.GELU,\n    ):\n        super().__init__()\n        out_features = out_features or in_features\n        hidden_features = hidden_features or in_features\n        self.net = nn.Sequential(OrderedDict([\n            (\"fc1\", nn.Linear(in_features, hidden_features)),\n            (\"act\", act_layer()),\n            (\"fc2\", nn.Linear(hidden_features, out_features))\n        ]))\n\n    def forward(self, x, size):\n        return self.net(x), size\n\n\nclass DepthWiseConv2d(nn.Module):\n    def __init__(\n        self,\n        dim_in,\n        kernel_size,\n        padding,\n        stride,\n        bias=True,\n    ):\n        super().__init__()\n        self.dw = nn.Conv2d(\n            dim_in, dim_in,\n            kernel_size=kernel_size,\n            padding=padding,\n            groups=dim_in,\n            stride=stride,\n            bias=bias\n        )\n\n    def forward(self, x, size):\n        B, N, C = x.shape\n        H, W = size\n        assert N == H * W\n\n        x = self.dw(x.transpose(1, 2).view(B, C, H, W))\n        size = (x.size(-2), x.size(-1))\n        x = x.flatten(2).transpose(1, 2)\n        return x, size\n\n\nclass ConvEmbed(nn.Module):\n    \"\"\" Image to Patch Embedding\n    \"\"\"\n\n    def __init__(\n        self,\n        patch_size=7,\n        in_chans=3,\n        embed_dim=64,\n        stride=4,\n        padding=2,\n        norm_layer=None,\n        pre_norm=True\n    ):\n        super().__init__()\n        self.patch_size = patch_size\n\n        self.proj = nn.Conv2d(\n            in_chans, embed_dim,\n            kernel_size=patch_size,\n            stride=stride,\n            padding=padding\n        )\n\n        dim_norm = in_chans if pre_norm else embed_dim\n        self.norm = norm_layer(dim_norm) if norm_layer else None\n\n        self.pre_norm = pre_norm\n\n    def forward(self, x, size):\n        H, W = size\n        if len(x.size()) == 3:\n            if self.norm and self.pre_norm:\n                x = self.norm(x)\n            x = rearrange(\n                x, 'b (h w) c -> b c h w',\n                h=H, w=W\n            )\n\n        x = self.proj(x)\n\n        _, _, H, W = x.shape\n        x = rearrange(x, 'b c h w -> b (h w) c')\n        if self.norm and not self.pre_norm:\n            x = self.norm(x)\n\n        return x, (H, W)\n\n\nclass ChannelAttention(nn.Module):\n\n    def __init__(self, dim, groups=8, qkv_bias=True):\n        super().__init__()\n\n        self.groups = groups\n        self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias)\n        self.proj = nn.Linear(dim, dim)\n\n    def forward(self, x, size):\n        B, N, C = x.shape\n\n        qkv = self.qkv(x).reshape(B, N, 3, self.groups, C // self.groups).permute(2, 0, 3, 1, 4)\n        q, k, v = qkv[0], qkv[1], qkv[2]\n\n        q = q * (float(N) ** -0.5)\n        attention = q.transpose(-1, -2) @ k\n        attention = attention.softmax(dim=-1)\n        x = (attention @ v.transpose(-1, -2)).transpose(-1, -2)\n        x = x.transpose(1, 2).reshape(B, N, C)\n        x = self.proj(x)\n        return x, size\n\n\nclass ChannelBlock(nn.Module):\n\n    def __init__(self, dim, groups, mlp_ratio=4., qkv_bias=True,\n                 drop_path_rate=0., act_layer=nn.GELU, norm_layer=nn.LayerNorm,\n                 conv_at_attn=True, conv_at_ffn=True):\n        super().__init__()\n\n        drop_path = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity()\n\n        self.conv1 = PreNorm(None, DepthWiseConv2d(dim, 3, 1, 1)) if conv_at_attn else None\n        self.channel_attn = PreNorm(\n            norm_layer(dim),\n            ChannelAttention(dim, groups=groups, qkv_bias=qkv_bias),\n            drop_path\n        )\n        self.conv2 = PreNorm(None, DepthWiseConv2d(dim, 3, 1, 1)) if conv_at_ffn else None\n        self.ffn = PreNorm(\n            norm_layer(dim),\n            Mlp(in_features=dim, hidden_features=int(dim*mlp_ratio), act_layer=act_layer),\n            drop_path\n        )\n\n    def forward(self, x, size):\n        if self.conv1:\n            x, size = self.conv1(x, size)\n        x, size = self.channel_attn(x, size)\n\n        if self.conv2:\n            x, size = self.conv2(x, size)\n        x, size = self.ffn(x, size)\n\n        return x, size\n\n\ndef window_partition(x, window_size: int):\n    B, H, W, C = x.shape\n    x = x.view(B, H // window_size, window_size, W // window_size, window_size, C)\n    windows = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, window_size, window_size, C)\n    return windows\n\n\ndef window_reverse(windows, batch_size: int, window_size: int, H: int, W: int):\n    B = batch_size \n    # this will cause onnx conversion failed for dynamic axis, because treated as constant\n    # int(windows.shape[0] / (H * W / window_size / window_size)) \n    x = windows.view(B, H // window_size, W // window_size, window_size, window_size, -1)\n    x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, H, W, -1)\n    return x\n\n\nclass WindowAttention(nn.Module):\n    def __init__(self, dim, num_heads, window_size, qkv_bias=True):\n\n        super().__init__()\n        self.dim = dim\n        self.window_size = window_size\n        self.num_heads = num_heads\n        head_dim = dim // num_heads\n        self.scale = float(head_dim) ** -0.5\n\n        self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias)\n        self.proj = nn.Linear(dim, dim)\n\n        self.softmax = nn.Softmax(dim=-1)\n\n    def forward(self, x, size):\n\n        H, W = size\n        B, L, C = x.shape\n        assert L == H * W, \"input feature has wrong size\"\n\n        x = x.view(B, H, W, C)\n\n        pad_l = pad_t = 0\n        pad_r = (self.window_size - W % self.window_size) % self.window_size\n        pad_b = (self.window_size - H % self.window_size) % self.window_size\n        x = F.pad(x, (0, 0, pad_l, pad_r, pad_t, pad_b))\n        _, Hp, Wp, _ = x.shape\n\n        x = window_partition(x, self.window_size)\n        x = x.view(-1, self.window_size * self.window_size, C)\n\n        # W-MSA/SW-MSA\n        # attn_windows = self.attn(x_windows)\n\n        B_, N, C = x.shape\n        qkv = self.qkv(x).reshape(B_, N, 3, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4)\n        q, k, v = qkv[0], qkv[1], qkv[2]\n\n        q = q * self.scale\n        attn = (q @ k.transpose(-2, -1))\n        attn = self.softmax(attn)\n\n        x = (attn @ v).transpose(1, 2).reshape(B_, N, C)\n        x = self.proj(x)\n\n        # merge windows\n        x = x.view(\n            -1, self.window_size, self.window_size, C\n        )\n        x = window_reverse(x, B, self.window_size, Hp, Wp)\n\n        if pad_r > 0 or pad_b > 0:\n            x = x[:, :H, :W, :].contiguous()\n\n        x = x.view(B, H * W, C)\n\n        return x, size\n\n\nclass SpatialBlock(nn.Module):\n\n    def __init__(self, dim, num_heads, window_size,\n                 mlp_ratio=4., qkv_bias=True, drop_path_rate=0., act_layer=nn.GELU,\n                 norm_layer=nn.LayerNorm, conv_at_attn=True, conv_at_ffn=True):\n        super().__init__()\n\n        drop_path = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity()\n\n        self.conv1 = PreNorm(None, DepthWiseConv2d(dim, 3, 1, 1)) if conv_at_attn else None\n        self.window_attn = PreNorm(\n            norm_layer(dim),\n            WindowAttention(dim, num_heads, window_size, qkv_bias=qkv_bias),\n            drop_path\n        )\n        self.conv2 = PreNorm(None, DepthWiseConv2d(dim, 3, 1, 1)) if conv_at_ffn else None\n        self.ffn = PreNorm(\n            norm_layer(dim),\n            Mlp(in_features=dim, hidden_features=int(dim*mlp_ratio), act_layer=act_layer),\n            drop_path\n        )\n\n    def forward(self, x, size):\n        if self.conv1:\n            x, size = self.conv1(x, size)\n        x, size = self.window_attn(x, size)\n\n        if self.conv2:\n            x, size = self.conv2(x, size)\n        x, size = self.ffn(x, size)\n        return x, size\n\n\nclass DaViT(nn.Module):\n    \"\"\" DaViT: Dual-Attention Transformer\n\n    Args:\n        in_chans (int): Number of input image channels. Default: 3.\n        num_classes (int): Number of classes for classification head. Default: 1000.\n        patch_size (tuple(int)): Patch size of convolution in different stages. Default: (7, 2, 2, 2).\n        patch_stride (tuple(int)): Patch stride of convolution in different stages. Default: (4, 2, 2, 2).\n        patch_padding (tuple(int)): Patch padding of convolution in different stages. Default: (3, 0, 0, 0).\n        patch_prenorm (tuple(bool)): If True, perform norm before convlution layer. Default: (True, False, False, False).\n        embed_dims (tuple(int)): Patch embedding dimension in different stages. Default: (64, 128, 192, 256).\n        num_heads (tuple(int)): Number of spatial attention heads in different stages. Default: (4, 8, 12, 16).\n        num_groups (tuple(int)): Number of channel groups in different stages. Default: (4, 8, 12, 16).\n        window_size (int): Window size. Default: 7.\n        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. Default: 4.\n        qkv_bias (bool): If True, add a learnable bias to query, key, value. Default: True.\n        drop_path_rate (float): Stochastic depth rate. Default: 0.1.\n        norm_layer (nn.Module): Normalization layer. Default: nn.LayerNorm.\n        enable_checkpoint (bool): If True, enable checkpointing. Default: False.\n        conv_at_attn (bool): If True, performe depthwise convolution before attention layer. Default: True.\n        conv_at_ffn (bool): If True, performe depthwise convolution before ffn layer. Default: True.\n    \"\"\"\n\n    def __init__(\n        self,\n        in_chans=3,\n        num_classes=1000,\n        depths=(1, 1, 3, 1),\n        patch_size=(7, 2, 2, 2),\n        patch_stride=(4, 2, 2, 2),\n        patch_padding=(3, 0, 0, 0),\n        patch_prenorm=(False, False, False, False),\n        embed_dims=(64, 128, 192, 256),\n        num_heads=(3, 6, 12, 24),\n        num_groups=(3, 6, 12, 24),\n        window_size=7,\n        mlp_ratio=4.,\n        qkv_bias=True,\n        drop_path_rate=0.1,\n        norm_layer=nn.LayerNorm,\n        enable_checkpoint=False,\n        conv_at_attn=True,\n        conv_at_ffn=True,\n     ):\n        super().__init__()\n\n        self.num_classes = num_classes\n        self.embed_dims = embed_dims\n        self.num_heads = num_heads\n        self.num_groups = num_groups\n        self.num_stages = len(self.embed_dims)\n        self.enable_checkpoint = enable_checkpoint\n        assert self.num_stages == len(self.num_heads) == len(self.num_groups)\n\n        num_stages = len(embed_dims)\n        dpr = [x.item() for x in torch.linspace(0, drop_path_rate, sum(depths)*2)]\n\n        depth_offset = 0\n        convs = []\n        blocks = []\n        for i in range(num_stages):\n            conv_embed = ConvEmbed(\n                patch_size=patch_size[i],\n                stride=patch_stride[i],\n                padding=patch_padding[i],\n                in_chans=in_chans if i == 0 else self.embed_dims[i - 1],\n                embed_dim=self.embed_dims[i],\n                norm_layer=norm_layer,\n                pre_norm=patch_prenorm[i]\n            )\n            convs.append(conv_embed)\n\n            block = MySequential(\n                *[\n                    MySequential(OrderedDict([\n                        (\n                            'spatial_block', SpatialBlock(\n                                embed_dims[i],\n                                num_heads[i],\n                                window_size,\n                                drop_path_rate=dpr[depth_offset+j*2],\n                                qkv_bias=qkv_bias,\n                                mlp_ratio=mlp_ratio,\n                                conv_at_attn=conv_at_attn,\n                                conv_at_ffn=conv_at_ffn,\n                            )\n                        ),\n                        (\n                            'channel_block', ChannelBlock(\n                                embed_dims[i],\n                                num_groups[i],\n                                drop_path_rate=dpr[depth_offset+j*2+1],\n                                qkv_bias=qkv_bias,\n                                mlp_ratio=mlp_ratio,\n                                conv_at_attn=conv_at_attn,\n                                conv_at_ffn=conv_at_ffn,\n                            )\n                        )\n                    ])) for j in range(depths[i])\n                ]\n            )\n            blocks.append(block)\n            depth_offset += depths[i]*2\n\n        self.convs = nn.ModuleList(convs)\n        self.blocks = nn.ModuleList(blocks)\n\n        self.norms = norm_layer(self.embed_dims[-1])\n        self.avgpool = nn.AdaptiveAvgPool1d(1)\n        self.head = nn.Linear(self.embed_dims[-1], num_classes) if num_classes > 0 else nn.Identity()\n\n        self.apply(self._init_weights)\n\n    @property\n    def dim_out(self):\n        return self.embed_dims[-1]\n\n    def _init_weights(self, m):\n        if isinstance(m, nn.Linear):\n            trunc_normal_(m.weight, std=0.02)\n            if m.bias is not None:\n                nn.init.constant_(m.bias, 0)\n        elif isinstance(m, nn.Conv2d):\n            nn.init.normal_(m.weight, std=0.02)\n            for name, _ in m.named_parameters():\n                if name in ['bias']:\n                    nn.init.constant_(m.bias, 0)\n        elif isinstance(m, nn.LayerNorm):\n            nn.init.constant_(m.weight, 1.0)\n            nn.init.constant_(m.bias, 0)\n        elif isinstance(m, nn.BatchNorm2d):\n            nn.init.constant_(m.weight, 1.0)\n            nn.init.constant_(m.bias, 0)\n\n    def forward_features_unpool(self, x):\n        \"\"\"\n        forward until avg pooling \n        Args:\n            x (_type_): input image tensor\n        \"\"\"\n        input_size = (x.size(2), x.size(3))\n        for conv, block in zip(self.convs, self.blocks):\n            x, input_size = conv(x, input_size)\n            if self.enable_checkpoint:\n                x, input_size = checkpoint.checkpoint(block, x, input_size)\n            else:\n                x, input_size = block(x, input_size)\n        return x\n\n    def forward_features(self, x):\n        x = self.forward_features_unpool(x)\n\n        # (batch_size, num_tokens, token_dim)\n        x = self.avgpool(x.transpose(1, 2))\n        # (batch_size, 1, num_tokens)\n        x = torch.flatten(x, 1)\n        x = self.norms(x)\n\n        return x\n\n    def forward(self, x):\n        x = self.forward_features(x)\n        x = self.head(x)\n        return x\n    \n    @classmethod\n    def from_config(cls, config):\n        return cls(\n            depths=config.depths,\n            embed_dims=config.dim_embed,\n            num_heads=config.num_heads,\n            num_groups=config.num_groups,\n            patch_size=config.patch_size,\n            patch_stride=config.patch_stride,\n            patch_padding=config.patch_padding,\n            patch_prenorm=config.patch_prenorm,\n            drop_path_rate=config.drop_path_rate,\n            window_size=config.window_size,\n        )\n\n\n\n\nif is_flash_attn_2_available():\n    from flash_attn import flash_attn_func, flash_attn_varlen_func\n    from flash_attn.bert_padding import index_first_axis, pad_input, unpad_input  # noqa\n\n# Copied from transformers.models.llama.modeling_llama._get_unpad_data\ndef _get_unpad_data(attention_mask):\n    seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)\n    indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten()\n    max_seqlen_in_batch = seqlens_in_batch.max().item()\n    cu_seqlens = F.pad(torch.cumsum(seqlens_in_batch, dim=0, dtype=torch.int32), (1, 0))\n    return (\n        indices,\n        cu_seqlens,\n        max_seqlen_in_batch,\n    )\n\n\ndef shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):\n    \"\"\"\n    Shift input ids one token to the right.\n    \"\"\"\n    shifted_input_ids = input_ids.new_zeros(input_ids.shape)\n    shifted_input_ids[:, 1:] = input_ids[:, :-1].clone()\n    shifted_input_ids[:, 0] = decoder_start_token_id\n\n    if pad_token_id is None:\n        raise ValueError(\"self.model.config.pad_token_id has to be defined.\")\n    # replace possible -100 values in labels by `pad_token_id`\n    shifted_input_ids.masked_fill_(shifted_input_ids == -100, pad_token_id)\n\n    return shifted_input_ids\n\n\nclass Florence2LearnedPositionalEmbedding(nn.Embedding):\n    \"\"\"\n    This module learns positional embeddings up to a fixed maximum size.\n    \"\"\"\n\n    def __init__(self, num_embeddings: int, embedding_dim: int):\n        # Florence2 is set up so that if padding_idx is specified then offset the embedding ids by 2\n        # and adjust num_embeddings appropriately. Other models don't have this hack\n        self.offset = 2\n        super().__init__(num_embeddings + self.offset, embedding_dim)\n\n    def forward(self, input_ids: torch.Tensor, past_key_values_length: int = 0):\n        \"\"\"`input_ids' shape is expected to be [bsz x seqlen].\"\"\"\n\n        bsz, seq_len = input_ids.shape[:2]\n        positions = torch.arange(\n            past_key_values_length, past_key_values_length + seq_len, dtype=torch.long, device=self.weight.device\n        ).expand(bsz, -1)\n\n        return super().forward(positions + self.offset)\n\n\nclass Florence2ScaledWordEmbedding(nn.Embedding):\n    \"\"\"\n    This module overrides nn.Embeddings' forward by multiplying with embeddings scale.\n    \"\"\"\n\n    def __init__(self, num_embeddings: int, embedding_dim: int, padding_idx: int, embed_scale: Optional[float] = 1.0):\n        super().__init__(num_embeddings, embedding_dim, padding_idx)\n        self.embed_scale = embed_scale\n\n    def forward(self, input_ids: torch.Tensor):\n        return super().forward(input_ids) * self.embed_scale\n\n\nclass Florence2Attention(nn.Module):\n    \"\"\"Multi-headed attention from 'Attention Is All You Need' paper\"\"\"\n\n    def __init__(\n        self,\n        embed_dim: int,\n        num_heads: int,\n        dropout: float = 0.0,\n        is_decoder: bool = False,\n        bias: bool = True,\n        is_causal: bool = False,\n        config: Optional[Florence2LanguageConfig] = None,\n    ):\n        super().__init__()\n        self.embed_dim = embed_dim\n        self.num_heads = num_heads\n        self.dropout = dropout\n        self.head_dim = embed_dim // num_heads\n        self.config = config\n\n        if (self.head_dim * num_heads) != self.embed_dim:\n            raise ValueError(\n                f\"embed_dim must be divisible by num_heads (got `embed_dim`: {self.embed_dim}\"\n                f\" and `num_heads`: {num_heads}).\"\n            )\n        self.scaling = self.head_dim**-0.5\n        self.is_decoder = is_decoder\n        self.is_causal = is_causal\n\n        self.k_proj = nn.Linear(embed_dim, embed_dim, bias=bias)\n        self.v_proj = nn.Linear(embed_dim, embed_dim, bias=bias)\n        self.q_proj = nn.Linear(embed_dim, embed_dim, bias=bias)\n        self.out_proj = nn.Linear(embed_dim, embed_dim, bias=bias)\n\n    def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):\n        return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous()\n\n    def forward(\n        self,\n        hidden_states: torch.Tensor,\n        key_value_states: Optional[torch.Tensor] = None,\n        past_key_value: Optional[Tuple[torch.Tensor]] = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        layer_head_mask: Optional[torch.Tensor] = None,\n        output_attentions: bool = False,\n    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:\n        \"\"\"Input shape: Batch x Time x Channel\"\"\"\n\n        # if key_value_states are provided this layer is used as a cross-attention layer\n        # for the decoder\n        is_cross_attention = key_value_states is not None\n\n        bsz, tgt_len, _ = hidden_states.size()\n\n        # get query proj\n        query_states = self.q_proj(hidden_states) * self.scaling\n        # get key, value proj\n        # `past_key_value[0].shape[2] == key_value_states.shape[1]`\n        # is checking that the `sequence_length` of the `past_key_value` is the same as\n        # the provided `key_value_states` to support prefix tuning\n        if (\n            is_cross_attention\n            and past_key_value is not None\n            and past_key_value[0].shape[2] == key_value_states.shape[1]\n        ):\n            # reuse k,v, cross_attentions\n            key_states = past_key_value[0]\n            value_states = past_key_value[1]\n        elif is_cross_attention:\n            # cross_attentions\n            key_states = self._shape(self.k_proj(key_value_states), -1, bsz)\n            value_states = self._shape(self.v_proj(key_value_states), -1, bsz)\n        elif past_key_value is not None:\n            # reuse k, v, self_attention\n            key_states = self._shape(self.k_proj(hidden_states), -1, bsz)\n            value_states = self._shape(self.v_proj(hidden_states), -1, bsz)\n            key_states = torch.cat([past_key_value[0], key_states], dim=2)\n            value_states = torch.cat([past_key_value[1], value_states], dim=2)\n        else:\n            # self_attention\n            key_states = self._shape(self.k_proj(hidden_states), -1, bsz)\n            value_states = self._shape(self.v_proj(hidden_states), -1, bsz)\n\n        if self.is_decoder:\n            # if cross_attention save Tuple(torch.Tensor, torch.Tensor) of all cross attention key/value_states.\n            # Further calls to cross_attention layer can then reuse all cross-attention\n            # key/value_states (first \"if\" case)\n            # if uni-directional self-attention (decoder) save Tuple(torch.Tensor, torch.Tensor) of\n            # all previous decoder key/value_states. Further calls to uni-directional self-attention\n            # can concat previous decoder key/value_states to current projected key/value_states (third \"elif\" case)\n            # if encoder bi-directional self-attention `past_key_value` is always `None`\n            past_key_value = (key_states, value_states)\n\n        proj_shape = (bsz * self.num_heads, -1, self.head_dim)\n        query_states = self._shape(query_states, tgt_len, bsz).view(*proj_shape)\n        key_states = key_states.reshape(*proj_shape)\n        value_states = value_states.reshape(*proj_shape)\n\n        src_len = key_states.size(1)\n        attn_weights = torch.bmm(query_states, key_states.transpose(1, 2))\n\n        if attn_weights.size() != (bsz * self.num_heads, tgt_len, src_len):\n            raise ValueError(\n                f\"Attention weights should be of size {(bsz * self.num_heads, tgt_len, src_len)}, but is\"\n                f\" {attn_weights.size()}\"\n            )\n\n        if attention_mask is not None:\n            if attention_mask.size() != (bsz, 1, tgt_len, src_len):\n                raise ValueError(\n                    f\"Attention mask should be of size {(bsz, 1, tgt_len, src_len)}, but is {attention_mask.size()}\"\n                )\n            attn_weights = attn_weights.view(bsz, self.num_heads, tgt_len, src_len) + attention_mask\n            attn_weights = attn_weights.view(bsz * self.num_heads, tgt_len, src_len)\n\n        attn_weights = nn.functional.softmax(attn_weights, dim=-1)\n\n        if layer_head_mask is not None:\n            if layer_head_mask.size() != (self.num_heads,):\n                raise ValueError(\n                    f\"Head mask for a single layer should be of size {(self.num_heads,)}, but is\"\n                    f\" {layer_head_mask.size()}\"\n                )\n            attn_weights = layer_head_mask.view(1, -1, 1, 1) * attn_weights.view(bsz, self.num_heads, tgt_len, src_len)\n            attn_weights = attn_weights.view(bsz * self.num_heads, tgt_len, src_len)\n\n        if output_attentions:\n            # this operation is a bit awkward, but it's required to\n            # make sure that attn_weights keeps its gradient.\n            # In order to do so, attn_weights have to be reshaped\n            # twice and have to be reused in the following\n            attn_weights_reshaped = attn_weights.view(bsz, self.num_heads, tgt_len, src_len)\n            attn_weights = attn_weights_reshaped.view(bsz * self.num_heads, tgt_len, src_len)\n        else:\n            attn_weights_reshaped = None\n\n        attn_probs = nn.functional.dropout(attn_weights, p=self.dropout, training=self.training)\n\n        attn_output = torch.bmm(attn_probs, value_states)\n\n        if attn_output.size() != (bsz * self.num_heads, tgt_len, self.head_dim):\n            raise ValueError(\n                f\"`attn_output` should be of size {(bsz * self.num_heads, tgt_len, self.head_dim)}, but is\"\n                f\" {attn_output.size()}\"\n            )\n\n        attn_output = attn_output.view(bsz, self.num_heads, tgt_len, self.head_dim)\n        attn_output = attn_output.transpose(1, 2)\n\n        # Use the `embed_dim` from the config (stored in the class) rather than `hidden_state` because `attn_output` can be\n        # partitioned across GPUs when using tensor-parallelism.\n        attn_output = attn_output.reshape(bsz, tgt_len, self.embed_dim)\n\n        attn_output = self.out_proj(attn_output)\n\n        return attn_output, attn_weights_reshaped, past_key_value\n\n\nclass Florence2FlashAttention2(Florence2Attention):\n    \"\"\"\n    Florence2 flash attention module. This module inherits from `Florence2Attention` as the weights of the module stays\n    untouched. The only required change would be on the forward pass where it needs to correctly call the public API of\n    flash attention and deal with padding tokens in case the input contains any of them.\n    \"\"\"\n\n    # Copied from transformers.models.llama.modeling_llama.LlamaFlashAttention2.__init__\n    def __init__(self, *args, **kwargs):\n        super().__init__(*args, **kwargs)\n\n        # TODO: Should be removed once Flash Attention for RoCm is bumped to 2.1.\n        # flash_attn<2.1 generates top-left aligned causal mask, while what is needed here is bottom-right alignement, that was made default for flash_attn>=2.1. This attribute is used to handle this difference. Reference: https://github.com/Dao-AILab/flash-attention/releases/tag/v2.1.0.\n        # Beware that with flash_attn<2.1, using q_seqlen != k_seqlen (except for the case q_seqlen == 1) produces a wrong mask (top-left).\n        self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal_2_10()\n\n    def _reshape(self, tensor: torch.Tensor, seq_len: int, bsz: int):\n        return tensor.view(bsz, seq_len, self.num_heads, self.head_dim)\n\n    def forward(\n        self,\n        hidden_states: torch.Tensor,\n        key_value_states: Optional[torch.Tensor] = None,\n        past_key_value: Optional[Tuple[torch.Tensor]] = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        layer_head_mask: Optional[torch.Tensor] = None,\n        output_attentions: bool = False,\n    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:\n        # Florence2FlashAttention2 attention does not support output_attentions\n        if output_attentions:\n            raise ValueError(\"Florence2FlashAttention2 attention does not support output_attentions\")\n\n        # if key_value_states are provided this layer is used as a cross-attention layer\n        # for the decoder\n        is_cross_attention = key_value_states is not None\n\n        bsz, q_len, _ = hidden_states.size()\n\n        # get query proj\n        query_states = self._reshape(self.q_proj(hidden_states), -1, bsz)\n        # get key, value proj\n        # `past_key_value[0].shape[2] == key_value_states.shape[1]`\n        # is checking that the `sequence_length` of the `past_key_value` is the same as\n        # the provided `key_value_states` to support prefix tuning\n        if (\n            is_cross_attention\n            and past_key_value is not None\n            and past_key_value[0].shape[2] == key_value_states.shape[1]\n        ):\n            # reuse k,v, cross_attentions\n            key_states = past_key_value[0].transpose(1, 2)\n            value_states = past_key_value[1].transpose(1, 2)\n        elif is_cross_attention:\n            # cross_attentions\n            key_states = self._reshape(self.k_proj(key_value_states), -1, bsz)\n            value_states = self._reshape(self.v_proj(key_value_states), -1, bsz)\n        elif past_key_value is not None:\n            # reuse k, v, self_attention\n            key_states = self._reshape(self.k_proj(hidden_states), -1, bsz)\n            value_states = self._reshape(self.v_proj(hidden_states), -1, bsz)\n            key_states = torch.cat([past_key_value[0].transpose(1, 2), key_states], dim=1)\n            value_states = torch.cat([past_key_value[1].transpose(1, 2), value_states], dim=1)\n        else:\n            # self_attention\n            key_states = self._reshape(self.k_proj(hidden_states), -1, bsz)\n            value_states = self._reshape(self.v_proj(hidden_states), -1, bsz)\n\n        if self.is_decoder:\n            # if cross_attention save Tuple(torch.Tensor, torch.Tensor) of all cross attention key/value_states.\n            # Further calls to cross_attention layer can then reuse all cross-attention\n            # key/value_states (first \"if\" case)\n            # if uni-directional self-attention (decoder) save Tuple(torch.Tensor, torch.Tensor) of\n            # all previous decoder key/value_states. Further calls to uni-directional self-attention\n            # can concat previous decoder key/value_states to current projected key/value_states (third \"elif\" case)\n            # if encoder bi-directional self-attention `past_key_value` is always `None`\n            past_key_value = (key_states.transpose(1, 2), value_states.transpose(1, 2))\n\n        kv_seq_len = key_states.shape[-2]\n        if past_key_value is not None:\n            kv_seq_len += past_key_value[0].shape[-2]\n\n        # In PEFT, usually we cast the layer norms in float32 for training stability reasons\n        # therefore the input hidden states gets silently casted in float32. Hence, we need\n        # cast them back in the correct dtype just to be sure everything works as expected.\n        # This might slowdown training & inference so it is recommended to not cast the LayerNorms\n        # in fp32. (LlamaRMSNorm handles it correctly)\n\n        input_dtype = query_states.dtype\n        if input_dtype == torch.float32:\n            if torch.is_autocast_enabled():\n                target_dtype = torch.get_autocast_gpu_dtype()\n            # Handle the case where the model is quantized\n            elif hasattr(self.config, \"_pre_quantization_dtype\"):\n                target_dtype = self.config._pre_quantization_dtype\n            else:\n                target_dtype = self.q_proj.weight.dtype\n\n            logger.warning_once(\n                f\"The input hidden states seems to be silently casted in float32, this might be related to\"\n                f\" the fact you have upcasted embedding or layer norm layers in float32. We will cast back the input in\"\n                f\" {target_dtype}.\"\n            )\n\n            query_states = query_states.to(target_dtype)\n            key_states = key_states.to(target_dtype)\n            value_states = value_states.to(target_dtype)\n\n        attn_output = self._flash_attention_forward(\n            query_states, key_states, value_states, attention_mask, q_len, dropout=self.dropout\n        )\n\n        attn_output = attn_output.reshape(bsz, q_len, -1)\n        attn_output = self.out_proj(attn_output)\n\n        if not output_attentions:\n            attn_weights = None\n\n        return attn_output, attn_weights, past_key_value\n\n    # Copied from transformers.models.llama.modeling_llama.LlamaFlashAttention2._flash_attention_forward\n    def _flash_attention_forward(\n        self, query_states, key_states, value_states, attention_mask, query_length, dropout=0.0, softmax_scale=None\n    ):\n        \"\"\"\n        Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token\n        first unpad the input, then computes the attention scores and pad the final attention scores.\n\n        Args:\n            query_states (`torch.Tensor`):\n                Input query states to be passed to Flash Attention API\n            key_states (`torch.Tensor`):\n                Input key states to be passed to Flash Attention API\n            value_states (`torch.Tensor`):\n                Input value states to be passed to Flash Attention API\n            attention_mask (`torch.Tensor`):\n                The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the\n                position of padding tokens and 1 for the position of non-padding tokens.\n            dropout (`float`):\n                Attention dropout\n            softmax_scale (`float`, *optional*):\n                The scaling of QK^T before applying softmax. Default to 1 / sqrt(head_dim)\n        \"\"\"\n        if not self._flash_attn_uses_top_left_mask:\n            causal = self.is_causal\n        else:\n            # TODO: Remove the `query_length != 1` check once Flash Attention for RoCm is bumped to 2.1. For details, please see the comment in LlamaFlashAttention2 __init__.\n            causal = self.is_causal and query_length != 1\n\n        # Contains at least one padding token in the sequence\n        if attention_mask is not None:\n            batch_size = query_states.shape[0]\n            query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = self._upad_input(\n                query_states, key_states, value_states, attention_mask, query_length\n            )\n\n            cu_seqlens_q, cu_seqlens_k = cu_seq_lens\n            max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens\n\n            attn_output_unpad = flash_attn_varlen_func(\n                query_states,\n                key_states,\n                value_states,\n                cu_seqlens_q=cu_seqlens_q,\n                cu_seqlens_k=cu_seqlens_k,\n                max_seqlen_q=max_seqlen_in_batch_q,\n                max_seqlen_k=max_seqlen_in_batch_k,\n                dropout_p=dropout,\n                softmax_scale=softmax_scale,\n                causal=causal,\n            )\n\n            attn_output = pad_input(attn_output_unpad, indices_q, batch_size, query_length)\n        else:\n            attn_output = flash_attn_func(\n                query_states, key_states, value_states, dropout, softmax_scale=softmax_scale, causal=causal\n            )\n\n        return attn_output\n\n    # Copied from transformers.models.llama.modeling_llama.LlamaFlashAttention2._upad_input\n    def _upad_input(self, query_layer, key_layer, value_layer, attention_mask, query_length):\n        indices_k, cu_seqlens_k, max_seqlen_in_batch_k = _get_unpad_data(attention_mask)\n        batch_size, kv_seq_len, num_key_value_heads, head_dim = key_layer.shape\n\n        key_layer = index_first_axis(\n            key_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k\n        )\n        value_layer = index_first_axis(\n            value_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k\n        )\n        if query_length == kv_seq_len:\n            query_layer = index_first_axis(\n                query_layer.reshape(batch_size * kv_seq_len, self.num_heads, head_dim), indices_k\n            )\n            cu_seqlens_q = cu_seqlens_k\n            max_seqlen_in_batch_q = max_seqlen_in_batch_k\n            indices_q = indices_k\n        elif query_length == 1:\n            max_seqlen_in_batch_q = 1\n            cu_seqlens_q = torch.arange(\n                batch_size + 1, dtype=torch.int32, device=query_layer.device\n            )  # There is a memcpy here, that is very bad.\n            indices_q = cu_seqlens_q[:-1]\n            query_layer = query_layer.squeeze(1)\n        else:\n            # The -q_len: slice assumes left padding.\n            attention_mask = attention_mask[:, -query_length:]\n            query_layer, indices_q, cu_seqlens_q, max_seqlen_in_batch_q = unpad_input(query_layer, attention_mask)\n\n        return (\n            query_layer,\n            key_layer,\n            value_layer,\n            indices_q,\n            (cu_seqlens_q, cu_seqlens_k),\n            (max_seqlen_in_batch_q, max_seqlen_in_batch_k),\n        )\n\n\nclass Florence2SdpaAttention(Florence2Attention):\n    def forward(\n        self,\n        hidden_states: torch.Tensor,\n        key_value_states: Optional[torch.Tensor] = None,\n        past_key_value: Optional[Tuple[torch.Tensor]] = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        layer_head_mask: Optional[torch.Tensor] = None,\n        output_attentions: bool = False,\n    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:\n        \"\"\"Input shape: Batch x Time x Channel\"\"\"\n        if output_attentions or layer_head_mask is not None:\n            # TODO: Improve this warning with e.g. `model.config._attn_implementation = \"manual\"` once this is implemented.\n            logger.warning_once(\n                \"Florence2Model is using Florence2SdpaAttention, but `torch.nn.functional.scaled_dot_product_attention` does not support `output_attentions=True` or `layer_head_mask` not None. Falling back to the manual attention\"\n                ' implementation, but specifying the manual implementation will be required from Transformers version v5.0.0 onwards. This warning can be removed using the argument `attn_implementation=\"eager\"` when loading the model.'\n            )\n            return super().forward(\n                hidden_states,\n                key_value_states=key_value_states,\n                past_key_value=past_key_value,\n                attention_mask=attention_mask,\n                layer_head_mask=layer_head_mask,\n                output_attentions=output_attentions,\n            )\n\n        # if key_value_states are provided this layer is used as a cross-attention layer\n        # for the decoder\n        is_cross_attention = key_value_states is not None\n\n        bsz, tgt_len, _ = hidden_states.size()\n\n        # get query proj\n        query_states = self.q_proj(hidden_states)\n        # get key, value proj\n        # `past_key_value[0].shape[2] == key_value_states.shape[1]`\n        # is checking that the `sequence_length` of the `past_key_value` is the same as\n        # the provided `key_value_states` to support prefix tuning\n        if (\n            is_cross_attention\n            and past_key_value is not None\n            and past_key_value[0].shape[2] == key_value_states.shape[1]\n        ):\n            # reuse k,v, cross_attentions\n            key_states = past_key_value[0]\n            value_states = past_key_value[1]\n        elif is_cross_attention:\n            # cross_attentions\n            key_states = self._shape(self.k_proj(key_value_states), -1, bsz)\n            value_states = self._shape(self.v_proj(key_value_states), -1, bsz)\n        elif past_key_value is not None:\n            # reuse k, v, self_attention\n            key_states = self._shape(self.k_proj(hidden_states), -1, bsz)\n            value_states = self._shape(self.v_proj(hidden_states), -1, bsz)\n            key_states = torch.cat([past_key_value[0], key_states], dim=2)\n            value_states = torch.cat([past_key_value[1], value_states], dim=2)\n        else:\n            # self_attention\n            key_states = self._shape(self.k_proj(hidden_states), -1, bsz)\n            value_states = self._shape(self.v_proj(hidden_states), -1, bsz)\n\n        if self.is_decoder:\n            # if cross_attention save Tuple(torch.Tensor, torch.Tensor) of all cross attention key/value_states.\n            # Further calls to cross_attention layer can then reuse all cross-attention\n            # key/value_states (first \"if\" case)\n            # if uni-directional self-attention (decoder) save Tuple(torch.Tensor, torch.Tensor) of\n            # all previous decoder key/value_states. Further calls to uni-directional self-attention\n            # can concat previous decoder key/value_states to current projected key/value_states (third \"elif\" case)\n            # if encoder bi-directional self-attention `past_key_value` is always `None`\n            past_key_value = (key_states, value_states)\n\n        query_states = self._shape(query_states, tgt_len, bsz)\n\n        # We dispatch to SDPA's Flash Attention or Efficient kernels via this `is_causal` if statement instead of an inline conditional assignment\n        # in SDPA to support both torch.compile's dynamic shapes and full graph options. An inline conditional prevents dynamic shapes from compiling.\n        # The tgt_len > 1 is necessary to match with AttentionMaskConverter.to_causal_4d that does not create a causal mask in case tgt_len == 1.\n        is_causal = True if self.is_causal and attention_mask is None and tgt_len > 1 else False\n\n        # NOTE: SDPA with memory-efficient backend is currently (torch==2.1.2) bugged when using non-contiguous inputs and a custom attn_mask,\n        # but we are fine here as `_shape` do call `.contiguous()`. Reference: https://github.com/pytorch/pytorch/issues/112577\n        attn_output = torch.nn.functional.scaled_dot_product_attention(\n            query_states,\n            key_states,\n            value_states,\n            attn_mask=attention_mask,\n            dropout_p=self.dropout if self.training else 0.0,\n            is_causal=is_causal,\n        )\n\n        if attn_output.size() != (bsz, self.num_heads, tgt_len, self.head_dim):\n            raise ValueError(\n                f\"`attn_output` should be of size {(bsz, self.num_heads, tgt_len, self.head_dim)}, but is\"\n                f\" {attn_output.size()}\"\n            )\n\n        attn_output = attn_output.transpose(1, 2)\n\n        # Use the `embed_dim` from the config (stored in the class) rather than `hidden_state` because `attn_output` can be\n        # partitioned across GPUs when using tensor-parallelism.\n        attn_output = attn_output.reshape(bsz, tgt_len, self.embed_dim)\n\n        attn_output = self.out_proj(attn_output)\n\n        return attn_output, None, past_key_value\n\n\nFLORENCE2_ATTENTION_CLASSES = {\n    \"eager\": Florence2Attention,\n    \"sdpa\": Florence2SdpaAttention,\n    \"flash_attention_2\": Florence2FlashAttention2,\n}\n\n\nclass Florence2EncoderLayer(nn.Module):\n    def __init__(self, config: Florence2LanguageConfig):\n        super().__init__()\n        self.embed_dim = config.d_model\n\n        self.self_attn = FLORENCE2_ATTENTION_CLASSES[config._attn_implementation](\n            embed_dim=self.embed_dim,\n            num_heads=config.encoder_attention_heads,\n            dropout=config.attention_dropout,\n            config=config,\n        )\n        self.self_attn_layer_norm = nn.LayerNorm(self.embed_dim)\n        self.dropout = config.dropout\n        self.activation_fn = ACT2FN[config.activation_function]\n        self.activation_dropout = config.activation_dropout\n        self.fc1 = nn.Linear(self.embed_dim, config.encoder_ffn_dim)\n        self.fc2 = nn.Linear(config.encoder_ffn_dim, self.embed_dim)\n        self.final_layer_norm = nn.LayerNorm(self.embed_dim)\n\n    def forward(\n        self,\n        hidden_states: torch.FloatTensor,\n        attention_mask: torch.FloatTensor,\n        layer_head_mask: torch.FloatTensor,\n        output_attentions: Optional[bool] = False,\n    ) -> Tuple[torch.FloatTensor, Optional[torch.FloatTensor]]:\n        \"\"\"\n        Args:\n            hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`\n            attention_mask (`torch.FloatTensor`): attention mask of size\n                `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.\n            layer_head_mask (`torch.FloatTensor`): mask for attention heads in a given layer of size\n                `(encoder_attention_heads,)`.\n            output_attentions (`bool`, *optional*):\n                Whether or not to return the attentions tensors of all attention layers. See `attentions` under\n                returned tensors for more detail.\n        \"\"\"\n        residual = hidden_states\n        hidden_states, attn_weights, _ = self.self_attn(\n            hidden_states=hidden_states,\n            attention_mask=attention_mask,\n            layer_head_mask=layer_head_mask,\n            output_attentions=output_attentions,\n        )\n        hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)\n        hidden_states = residual + hidden_states\n        hidden_states = self.self_attn_layer_norm(hidden_states)\n\n        residual = hidden_states\n        hidden_states = self.activation_fn(self.fc1(hidden_states))\n        hidden_states = nn.functional.dropout(hidden_states, p=self.activation_dropout, training=self.training)\n        hidden_states = self.fc2(hidden_states)\n        hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)\n        hidden_states = residual + hidden_states\n        hidden_states = self.final_layer_norm(hidden_states)\n\n        if hidden_states.dtype == torch.float16 and (\n            torch.isinf(hidden_states).any() or torch.isnan(hidden_states).any()\n        ):\n            clamp_value = torch.finfo(hidden_states.dtype).max - 1000\n            hidden_states = torch.clamp(hidden_states, min=-clamp_value, max=clamp_value)\n\n        outputs = (hidden_states,)\n\n        if output_attentions:\n            outputs += (attn_weights,)\n\n        return outputs\n\n\nclass Florence2DecoderLayer(nn.Module):\n    def __init__(self, config: Florence2LanguageConfig):\n        super().__init__()\n        self.embed_dim = config.d_model\n\n        self.self_attn = FLORENCE2_ATTENTION_CLASSES[config._attn_implementation](\n            embed_dim=self.embed_dim,\n            num_heads=config.decoder_attention_heads,\n            dropout=config.attention_dropout,\n            is_decoder=True,\n            is_causal=True,\n            config=config,\n        )\n        self.dropout = config.dropout\n        self.activation_fn = ACT2FN[config.activation_function]\n        self.activation_dropout = config.activation_dropout\n\n        self.self_attn_layer_norm = nn.LayerNorm(self.embed_dim)\n        self.encoder_attn = FLORENCE2_ATTENTION_CLASSES[config._attn_implementation](\n            self.embed_dim,\n            config.decoder_attention_heads,\n            dropout=config.attention_dropout,\n            is_decoder=True,\n            config=config,\n        )\n        self.encoder_attn_layer_norm = nn.LayerNorm(self.embed_dim)\n        self.fc1 = nn.Linear(self.embed_dim, config.decoder_ffn_dim)\n        self.fc2 = nn.Linear(config.decoder_ffn_dim, self.embed_dim)\n        self.final_layer_norm = nn.LayerNorm(self.embed_dim)\n\n    def forward(\n        self,\n        hidden_states: torch.Tensor,\n        attention_mask: Optional[torch.Tensor] = None,\n        encoder_hidden_states: Optional[torch.Tensor] = None,\n        encoder_attention_mask: Optional[torch.Tensor] = None,\n        layer_head_mask: Optional[torch.Tensor] = None,\n        cross_attn_layer_head_mask: Optional[torch.Tensor] = None,\n        past_key_value: Optional[Tuple[torch.Tensor]] = None,\n        output_attentions: Optional[bool] = False,\n        use_cache: Optional[bool] = True,\n    ) -> Tuple[torch.FloatTensor, Optional[Tuple[torch.FloatTensor, torch.FloatTensor]]]:\n        \"\"\"\n        Args:\n            hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`\n            attention_mask (`torch.FloatTensor`): attention mask of size\n                `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.\n            encoder_hidden_states (`torch.FloatTensor`):\n                cross attention input to the layer of shape `(batch, seq_len, embed_dim)`\n            encoder_attention_mask (`torch.FloatTensor`): encoder attention mask of size\n                `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.\n            layer_head_mask (`torch.FloatTensor`): mask for attention heads in a given layer of size\n                `(encoder_attention_heads,)`.\n            cross_attn_layer_head_mask (`torch.FloatTensor`): mask for cross-attention heads in a given layer of\n                size `(decoder_attention_heads,)`.\n            past_key_value (`Tuple(torch.FloatTensor)`): cached past key and value projection states\n            output_attentions (`bool`, *optional*):\n                Whether or not to return the attentions tensors of all attention layers. See `attentions` under\n                returned tensors for more detail.\n        \"\"\"\n        residual = hidden_states\n\n        # Self Attention\n        # decoder uni-directional self-attention cached key/values tuple is at positions 1,2\n        self_attn_past_key_value = past_key_value[:2] if past_key_value is not None else None\n        # add present self-attn cache to positions 1,2 of present_key_value tuple\n        hidden_states, self_attn_weights, present_key_value = self.self_attn(\n            hidden_states=hidden_states,\n            past_key_value=self_attn_past_key_value,\n            attention_mask=attention_mask,\n            layer_head_mask=layer_head_mask,\n            output_attentions=output_attentions,\n        )\n        hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)\n        hidden_states = residual + hidden_states\n        hidden_states = self.self_attn_layer_norm(hidden_states)\n\n        # Cross-Attention Block\n        cross_attn_present_key_value = None\n        cross_attn_weights = None\n        if encoder_hidden_states is not None:\n            residual = hidden_states\n\n            # cross_attn cached key/values tuple is at positions 3,4 of present_key_value tuple\n            cross_attn_past_key_value = past_key_value[-2:] if past_key_value is not None else None\n            hidden_states, cross_attn_weights, cross_attn_present_key_value = self.encoder_attn(\n                hidden_states=hidden_states,\n                key_value_states=encoder_hidden_states,\n                attention_mask=encoder_attention_mask,\n                layer_head_mask=cross_attn_layer_head_mask,\n                past_key_value=cross_attn_past_key_value,\n                output_attentions=output_attentions,\n            )\n            hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)\n            hidden_states = residual + hidden_states\n            hidden_states = self.encoder_attn_layer_norm(hidden_states)\n\n            # add cross-attn to positions 3,4 of present_key_value tuple\n            present_key_value = present_key_value + cross_attn_present_key_value\n\n        # Fully Connected\n        residual = hidden_states\n        hidden_states = self.activation_fn(self.fc1(hidden_states))\n        hidden_states = nn.functional.dropout(hidden_states, p=self.activation_dropout, training=self.training)\n        hidden_states = self.fc2(hidden_states)\n        hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)\n        hidden_states = residual + hidden_states\n        hidden_states = self.final_layer_norm(hidden_states)\n\n        outputs = (hidden_states,)\n\n        if output_attentions:\n            outputs += (self_attn_weights, cross_attn_weights)\n\n        if use_cache:\n            outputs += (present_key_value,)\n\n        return outputs\n\n\n\nclass Florence2LanguagePreTrainedModel(PreTrainedModel):\n    config_class = Florence2LanguageConfig\n    base_model_prefix = \"model\"\n    supports_gradient_checkpointing = True\n    _keys_to_ignore_on_load_unexpected = [\"encoder.version\", \"decoder.version\"]\n    _no_split_modules = [r\"Florence2EncoderLayer\", r\"Florence2DecoderLayer\"]\n    _skip_keys_device_placement = \"past_key_values\"\n    _supports_flash_attn_2 = True\n    _supports_sdpa = True\n\n    def _init_weights(self, module):\n        std = self.config.init_std\n        if isinstance(module, nn.Linear):\n            module.weight.data.normal_(mean=0.0, std=std)\n            if module.bias is not None:\n                module.bias.data.zero_()\n        elif isinstance(module, nn.Embedding):\n            module.weight.data.normal_(mean=0.0, std=std)\n            if module.padding_idx is not None:\n                module.weight.data[module.padding_idx].zero_()\n\n    @property\n    def dummy_inputs(self):\n        pad_token = self.config.pad_token_id\n        input_ids = torch.tensor([[0, 6, 10, 4, 2], [0, 8, 12, 2, pad_token]], device=self.device)\n        dummy_inputs = {\n            \"attention_mask\": input_ids.ne(pad_token),\n            \"input_ids\": input_ids,\n        }\n        return dummy_inputs\n\n\nclass Florence2Encoder(Florence2LanguagePreTrainedModel):\n    \"\"\"\n    Transformer encoder consisting of *config.encoder_layers* self attention layers. Each layer is a\n    [`Florence2EncoderLayer`].\n\n    Args:\n        config: Florence2LanguageConfig\n        embed_tokens (nn.Embedding): output embedding\n    \"\"\"\n\n    def __init__(self, config: Florence2LanguageConfig, embed_tokens: Optional[nn.Embedding] = None):\n        super().__init__(config)\n\n        self.dropout = config.dropout\n        self.layerdrop = config.encoder_layerdrop\n\n        embed_dim = config.d_model\n        self.padding_idx = config.pad_token_id\n        self.max_source_positions = config.max_position_embeddings\n        embed_scale = math.sqrt(embed_dim) if config.scale_embedding else 1.0\n\n        self.embed_tokens = Florence2ScaledWordEmbedding(\n            config.vocab_size, embed_dim, self.padding_idx, embed_scale=embed_scale\n        )\n\n        if embed_tokens is not None:\n            self.embed_tokens.weight = embed_tokens.weight\n\n        self.embed_positions = Florence2LearnedPositionalEmbedding(\n            config.max_position_embeddings,\n            embed_dim,\n        )\n        self.layers = nn.ModuleList([Florence2EncoderLayer(config) for _ in range(config.encoder_layers)])\n        self._use_flash_attention_2 = config._attn_implementation == \"flash_attention_2\"\n        self._use_sdpa = config._attn_implementation == \"sdpa\"\n        self.layernorm_embedding = nn.LayerNorm(embed_dim)\n\n        self.gradient_checkpointing = False\n        # Initialize weights and apply final processing\n        self.post_init()\n\n    def get_input_embeddings(self):\n        return self.embed_tokens\n\n    def set_input_embeddings(self, value):\n        self.embed_tokens = value\n\n    def forward(\n        self,\n        input_ids: torch.LongTensor = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        head_mask: Optional[torch.Tensor] = None,\n        inputs_embeds: Optional[torch.FloatTensor] = None,\n        output_attentions: Optional[bool] = None,\n        output_hidden_states: Optional[bool] = None,\n        return_dict: Optional[bool] = None,\n    ) -> Union[Tuple, BaseModelOutput]:\n        r\"\"\"\n        Args:\n            input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):\n                Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you\n                provide it.\n\n                Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and\n                [`PreTrainedTokenizer.__call__`] for details.\n\n                [What are input IDs?](../glossary#input-ids)\n            attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):\n                Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:\n\n                - 1 for tokens that are **not masked**,\n                - 0 for tokens that are **masked**.\n\n                [What are attention masks?](../glossary#attention-mask)\n            head_mask (`torch.Tensor` of shape `(encoder_layers, encoder_attention_heads)`, *optional*):\n                Mask to nullify selected heads of the attention modules. Mask values selected in `[0, 1]`:\n\n                - 1 indicates the head is **not masked**,\n                - 0 indicates the head is **masked**.\n\n            inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):\n                Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation.\n                This is useful if you want more control over how to convert `input_ids` indices into associated vectors\n                than the model's internal embedding lookup matrix.\n            output_attentions (`bool`, *optional*):\n                Whether or not to return the attentions tensors of all attention layers. See `attentions` under\n                returned tensors for more detail.\n            output_hidden_states (`bool`, *optional*):\n                Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors\n                for more detail.\n            return_dict (`bool`, *optional*):\n                Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.\n        \"\"\"\n        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions\n        output_hidden_states = (\n            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states\n        )\n        return_dict = return_dict if return_dict is not None else self.config.use_return_dict\n\n        # retrieve input_ids and inputs_embeds\n        if input_ids is not None and inputs_embeds is not None:\n            raise ValueError(\"You cannot specify both input_ids and inputs_embeds at the same time\")\n        elif input_ids is not None:\n            input = input_ids\n            input_ids = input_ids.view(-1, input_ids.shape[-1])\n        elif inputs_embeds is not None:\n            input = inputs_embeds[:, :, -1]\n        else:\n            raise ValueError(\"You have to specify either input_ids or inputs_embeds\")\n\n        if inputs_embeds is None:\n            inputs_embeds = self.embed_tokens(input_ids)\n\n        embed_pos = self.embed_positions(input)\n        embed_pos = embed_pos.to(inputs_embeds.device)\n\n        hidden_states = inputs_embeds + embed_pos\n        hidden_states = self.layernorm_embedding(hidden_states)\n        hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)\n\n        # expand attention_mask\n        if attention_mask is not None:\n            if self._use_flash_attention_2:\n                attention_mask = attention_mask if 0 in attention_mask else None\n            elif self._use_sdpa and head_mask is None and not output_attentions:\n                # output_attentions=True & head_mask can not be supported when using SDPA, fall back to\n                # the manual implementation that requires a 4D causal mask in all cases.\n                # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]\n                attention_mask = _prepare_4d_attention_mask_for_sdpa(attention_mask, inputs_embeds.dtype)\n            else:\n                # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]\n                attention_mask = _prepare_4d_attention_mask(attention_mask, inputs_embeds.dtype)\n\n        encoder_states = () if output_hidden_states else None\n        all_attentions = () if output_attentions else None\n\n        # check if head_mask has a correct number of layers specified if desired\n        if head_mask is not None:\n            if head_mask.size()[0] != (len(self.layers)):\n                raise ValueError(\n                    f\"The head_mask should be specified for {len(self.layers)} layers, but it is for\"\n                    f\" {head_mask.size()[0]}.\"\n                )\n\n        for idx, encoder_layer in enumerate(self.layers):\n            if output_hidden_states:\n                encoder_states = encoder_states + (hidden_states,)\n            # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description)\n            to_drop = False\n            if self.training:\n                dropout_probability = torch.rand([])\n                if dropout_probability < self.layerdrop:  # skip the layer\n                    to_drop = True\n\n            if to_drop:\n                layer_outputs = (None, None)\n            else:\n                if self.gradient_checkpointing and self.training:\n                    layer_outputs = self._gradient_checkpointing_func(\n                        encoder_layer.__call__,\n                        hidden_states,\n                        attention_mask,\n                        (head_mask[idx] if head_mask is not None else None),\n                        output_attentions,\n                    )\n                else:\n                    layer_outputs = encoder_layer(\n                        hidden_states,\n                        attention_mask,\n                        layer_head_mask=(head_mask[idx] if head_mask is not None else None),\n                        output_attentions=output_attentions,\n                    )\n\n                hidden_states = layer_outputs[0]\n\n            if output_attentions:\n                all_attentions = all_attentions + (layer_outputs[1],)\n\n        if output_hidden_states:\n            encoder_states = encoder_states + (hidden_states,)\n\n        if not return_dict:\n            return tuple(v for v in [hidden_states, encoder_states, all_attentions] if v is not None)\n        return BaseModelOutput(\n            last_hidden_state=hidden_states, hidden_states=encoder_states, attentions=all_attentions\n        )\n\n\nclass Florence2Decoder(Florence2LanguagePreTrainedModel):\n    \"\"\"\n    Transformer decoder consisting of *config.decoder_layers* layers. Each layer is a [`Florence2DecoderLayer`]\n\n    Args:\n        config: Florence2LanguageConfig\n        embed_tokens (nn.Embedding): output embedding\n    \"\"\"\n\n    def __init__(self, config: Florence2LanguageConfig, embed_tokens: Optional[nn.Embedding] = None):\n        super().__init__(config)\n        self.dropout = config.dropout\n        self.layerdrop = config.decoder_layerdrop\n        self.padding_idx = config.pad_token_id\n        self.max_target_positions = config.max_position_embeddings\n        embed_scale = math.sqrt(config.d_model) if config.scale_embedding else 1.0\n\n        self.embed_tokens = Florence2ScaledWordEmbedding(\n            config.vocab_size, config.d_model, self.padding_idx, embed_scale=embed_scale\n        )\n\n        if embed_tokens is not None:\n            self.embed_tokens.weight = embed_tokens.weight\n\n        self.embed_positions = Florence2LearnedPositionalEmbedding(\n            config.max_position_embeddings,\n            config.d_model,\n        )\n        self.layers = nn.ModuleList([Florence2DecoderLayer(config) for _ in range(config.decoder_layers)])\n        self._use_flash_attention_2 = config._attn_implementation == \"flash_attention_2\"\n        self._use_sdpa = config._attn_implementation == \"sdpa\"\n\n        self.layernorm_embedding = nn.LayerNorm(config.d_model)\n\n        self.gradient_checkpointing = False\n        # Initialize weights and apply final processing\n        self.post_init()\n\n    def get_input_embeddings(self):\n        return self.embed_tokens\n\n    def set_input_embeddings(self, value):\n        self.embed_tokens = value\n\n    def forward(\n        self,\n        input_ids: torch.LongTensor = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        encoder_hidden_states: Optional[torch.FloatTensor] = None,\n        encoder_attention_mask: Optional[torch.LongTensor] = None,\n        head_mask: Optional[torch.Tensor] = None,\n        cross_attn_head_mask: Optional[torch.Tensor] = None,\n        past_key_values: Optional[List[torch.FloatTensor]] = None,\n        inputs_embeds: Optional[torch.FloatTensor] = None,\n        use_cache: Optional[bool] = None,\n        output_attentions: Optional[bool] = None,\n        output_hidden_states: Optional[bool] = None,\n        return_dict: Optional[bool] = None,\n    ) -> Union[Tuple, BaseModelOutputWithPastAndCrossAttentions]:\n        r\"\"\"\n        Args:\n            input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):\n                Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you\n                provide it.\n\n                Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and\n                [`PreTrainedTokenizer.__call__`] for details.\n\n                [What are input IDs?](../glossary#input-ids)\n            attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):\n                Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:\n\n                - 1 for tokens that are **not masked**,\n                - 0 for tokens that are **masked**.\n\n                [What are attention masks?](../glossary#attention-mask)\n            encoder_hidden_states (`torch.FloatTensor` of shape `(batch_size, encoder_sequence_length, hidden_size)`, *optional*):\n                Sequence of hidden-states at the output of the last layer of the encoder. Used in the cross-attention\n                of the decoder.\n            encoder_attention_mask (`torch.LongTensor` of shape `(batch_size, encoder_sequence_length)`, *optional*):\n                Mask to avoid performing cross-attention on padding tokens indices of encoder input_ids. Mask values\n                selected in `[0, 1]`:\n\n                - 1 for tokens that are **not masked**,\n                - 0 for tokens that are **masked**.\n\n                [What are attention masks?](../glossary#attention-mask)\n            head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):\n                Mask to nullify selected heads of the attention modules. Mask values selected in `[0, 1]`:\n\n                - 1 indicates the head is **not masked**,\n                - 0 indicates the head is **masked**.\n\n            cross_attn_head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):\n                Mask to nullify selected heads of the cross-attention modules in the decoder to avoid performing\n                cross-attention on hidden heads. Mask values selected in `[0, 1]`:\n\n                - 1 indicates the head is **not masked**,\n                - 0 indicates the head is **masked**.\n\n            past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or when `config.use_cache=True`):\n                Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of\n                shape `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of\n                shape `(batch_size, num_heads, encoder_sequence_length, embed_size_per_head)`.\n\n                Contains pre-computed hidden-states (key and values in the self-attention blocks and in the\n                cross-attention blocks) that can be used (see `past_key_values` input) to speed up sequential decoding.\n\n                If `past_key_values` are used, the user can optionally input only the last `decoder_input_ids` (those\n                that don't have their past key value states given to this model) of shape `(batch_size, 1)` instead of\n                all `decoder_input_ids` of shape `(batch_size, sequence_length)`.\n            inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):\n                Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation.\n                This is useful if you want more control over how to convert `input_ids` indices into associated vectors\n                than the model's internal embedding lookup matrix.\n            output_attentions (`bool`, *optional*):\n                Whether or not to return the attentions tensors of all attention layers. See `attentions` under\n                returned tensors for more detail.\n            output_hidden_states (`bool`, *optional*):\n                Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors\n                for more detail.\n            return_dict (`bool`, *optional*):\n                Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.\n        \"\"\"\n        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions\n        output_hidden_states = (\n            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states\n        )\n        use_cache = use_cache if use_cache is not None else self.config.use_cache\n        return_dict = return_dict if return_dict is not None else self.config.use_return_dict\n\n        # retrieve input_ids and inputs_embeds\n        if input_ids is not None and inputs_embeds is not None:\n            raise ValueError(\"You cannot specify both decoder_input_ids and decoder_inputs_embeds at the same time\")\n        elif input_ids is not None:\n            input = input_ids\n            input_shape = input.shape\n            input_ids = input_ids.view(-1, input_shape[-1])\n        elif inputs_embeds is not None:\n            input_shape = inputs_embeds.size()[:-1]\n            input = inputs_embeds[:, :, -1]\n        else:\n            raise ValueError(\"You have to specify either decoder_input_ids or decoder_inputs_embeds\")\n\n        # past_key_values_length\n        past_key_values_length = past_key_values[0][0].shape[2] if past_key_values is not None else 0\n\n        if inputs_embeds is None:\n            inputs_embeds = self.embed_tokens(input)\n\n        if self._use_flash_attention_2:\n            # 2d mask is passed through the layers\n            attention_mask = attention_mask if (attention_mask is not None and 0 in attention_mask) else None\n        elif self._use_sdpa and not output_attentions and cross_attn_head_mask is None:\n            # output_attentions=True & cross_attn_head_mask can not be supported when using SDPA, and we fall back on\n            # the manual implementation that requires a 4D causal mask in all cases.\n            attention_mask = _prepare_4d_causal_attention_mask_for_sdpa(\n                attention_mask,\n                input_shape,\n                inputs_embeds,\n                past_key_values_length,\n            )\n        else:\n            # 4d mask is passed through the layers\n            attention_mask = _prepare_4d_causal_attention_mask(\n                attention_mask, input_shape, inputs_embeds, past_key_values_length\n            )\n\n        # expand encoder attention mask\n        if encoder_hidden_states is not None and encoder_attention_mask is not None:\n            if self._use_flash_attention_2:\n                encoder_attention_mask = encoder_attention_mask if 0 in encoder_attention_mask else None\n            elif self._use_sdpa and cross_attn_head_mask is None and not output_attentions:\n                # output_attentions=True & cross_attn_head_mask can not be supported when using SDPA, and we fall back on\n                # the manual implementation that requires a 4D causal mask in all cases.\n                # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]\n                encoder_attention_mask = _prepare_4d_attention_mask_for_sdpa(\n                    encoder_attention_mask,\n                    inputs_embeds.dtype,\n                    tgt_len=input_shape[-1],\n                )\n            else:\n                # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]\n                encoder_attention_mask = _prepare_4d_attention_mask(\n                    encoder_attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]\n                )\n\n        # embed positions\n        positions = self.embed_positions(input, past_key_values_length)\n        positions = positions.to(inputs_embeds.device)\n\n        hidden_states = inputs_embeds + positions\n        hidden_states = self.layernorm_embedding(hidden_states)\n\n        hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)\n\n        if self.gradient_checkpointing and self.training:\n            if use_cache:\n                logger.warning_once(\n                    \"`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...\"\n                )\n                use_cache = False\n\n        # decoder layers\n        all_hidden_states = () if output_hidden_states else None\n        all_self_attns = () if output_attentions else None\n        all_cross_attentions = () if (output_attentions and encoder_hidden_states is not None) else None\n        next_decoder_cache = () if use_cache else None\n\n        # check if head_mask/cross_attn_head_mask has a correct number of layers specified if desired\n        for attn_mask, mask_name in zip([head_mask, cross_attn_head_mask], [\"head_mask\", \"cross_attn_head_mask\"]):\n            if attn_mask is not None:\n                if attn_mask.size()[0] != (len(self.layers)):\n                    raise ValueError(\n                        f\"The `{mask_name}` should be specified for {len(self.layers)} layers, but it is for\"\n                        f\" {head_mask.size()[0]}.\"\n                    )\n\n        for idx, decoder_layer in enumerate(self.layers):\n            # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description)\n            if output_hidden_states:\n                all_hidden_states += (hidden_states,)\n            if self.training:\n                dropout_probability = torch.rand([])\n                if dropout_probability < self.layerdrop:\n                    continue\n\n            past_key_value = past_key_values[idx] if past_key_values is not None else None\n\n            if self.gradient_checkpointing and self.training:\n                layer_outputs = self._gradient_checkpointing_func(\n                    decoder_layer.__call__,\n                    hidden_states,\n                    attention_mask,\n                    encoder_hidden_states,\n                    encoder_attention_mask,\n                    head_mask[idx] if head_mask is not None else None,\n                    cross_attn_head_mask[idx] if cross_attn_head_mask is not None else None,\n                    None,\n                    output_attentions,\n                    use_cache,\n                )\n            else:\n                layer_outputs = decoder_layer(\n                    hidden_states,\n                    attention_mask=attention_mask,\n                    encoder_hidden_states=encoder_hidden_states,\n                    encoder_attention_mask=encoder_attention_mask,\n                    layer_head_mask=(head_mask[idx] if head_mask is not None else None),\n                    cross_attn_layer_head_mask=(\n                        cross_attn_head_mask[idx] if cross_attn_head_mask is not None else None\n                    ),\n                    past_key_value=past_key_value,\n                    output_attentions=output_attentions,\n                    use_cache=use_cache,\n                )\n            hidden_states = layer_outputs[0]\n\n            if use_cache:\n                next_decoder_cache += (layer_outputs[3 if output_attentions else 1],)\n\n            if output_attentions:\n                all_self_attns += (layer_outputs[1],)\n\n                if encoder_hidden_states is not None:\n                    all_cross_attentions += (layer_outputs[2],)\n\n        # add hidden states from the last decoder layer\n        if output_hidden_states:\n            all_hidden_states += (hidden_states,)\n\n        next_cache = next_decoder_cache if use_cache else None\n        if not return_dict:\n            return tuple(\n                v\n                for v in [hidden_states, next_cache, all_hidden_states, all_self_attns, all_cross_attentions]\n                if v is not None\n            )\n        return BaseModelOutputWithPastAndCrossAttentions(\n            last_hidden_state=hidden_states,\n            past_key_values=next_cache,\n            hidden_states=all_hidden_states,\n            attentions=all_self_attns,\n            cross_attentions=all_cross_attentions,\n        )\n\n\nclass Florence2LanguageModel(Florence2LanguagePreTrainedModel):\n    _tied_weights_keys = [\"encoder.embed_tokens.weight\", \"decoder.embed_tokens.weight\"]\n\n    def __init__(self, config: Florence2LanguageConfig):\n        super().__init__(config)\n\n        padding_idx, vocab_size = config.pad_token_id, config.vocab_size\n        self.shared = nn.Embedding(vocab_size, config.d_model, padding_idx)\n\n        self.encoder = Florence2Encoder(config, self.shared)\n        self.decoder = Florence2Decoder(config, self.shared)\n\n        # Initialize weights and apply final processing\n        self.post_init()\n\n    def _tie_weights(self):\n        if self.config.tie_word_embeddings:\n            self._tie_or_clone_weights(self.encoder.embed_tokens, self.shared)\n            self._tie_or_clone_weights(self.decoder.embed_tokens, self.shared)\n\n    def get_input_embeddings(self):\n        return self.shared\n\n    def set_input_embeddings(self, value):\n        self.shared = value\n        self.encoder.embed_tokens = self.shared\n        self.decoder.embed_tokens = self.shared\n\n    def get_encoder(self):\n        return self.encoder\n\n    def get_decoder(self):\n        return self.decoder\n\n    def forward(\n        self,\n        input_ids: torch.LongTensor = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        decoder_input_ids: Optional[torch.LongTensor] = None,\n        decoder_attention_mask: Optional[torch.LongTensor] = None,\n        head_mask: Optional[torch.Tensor] = None,\n        decoder_head_mask: Optional[torch.Tensor] = None,\n        cross_attn_head_mask: Optional[torch.Tensor] = None,\n        encoder_outputs: Optional[List[torch.FloatTensor]] = None,\n        past_key_values: Optional[List[torch.FloatTensor]] = None,\n        inputs_embeds: Optional[torch.FloatTensor] = None,\n        decoder_inputs_embeds: Optional[torch.FloatTensor] = None,\n        use_cache: Optional[bool] = None,\n        output_attentions: Optional[bool] = None,\n        output_hidden_states: Optional[bool] = None,\n        return_dict: Optional[bool] = None,\n    ) -> Union[Tuple, Seq2SeqModelOutput]:\n        # different to other models, Florence2 automatically creates decoder_input_ids from\n        # input_ids if no decoder_input_ids are provided\n        if decoder_input_ids is None and decoder_inputs_embeds is None:\n            if input_ids is None:\n                raise ValueError(\n                    \"If no `decoder_input_ids` or `decoder_inputs_embeds` are \"\n                    \"passed, `input_ids` cannot be `None`. Please pass either \"\n                    \"`input_ids` or `decoder_input_ids` or `decoder_inputs_embeds`.\"\n                )\n\n            decoder_input_ids = shift_tokens_right(\n                input_ids, self.config.pad_token_id, self.config.decoder_start_token_id\n            )\n\n        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions\n        output_hidden_states = (\n            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states\n        )\n        use_cache = use_cache if use_cache is not None else self.config.use_cache\n        return_dict = return_dict if return_dict is not None else self.config.use_return_dict\n\n        if encoder_outputs is None:\n            encoder_outputs = self.encoder(\n                input_ids=input_ids,\n                attention_mask=attention_mask,\n                head_mask=head_mask,\n                inputs_embeds=inputs_embeds,\n                output_attentions=output_attentions,\n                output_hidden_states=output_hidden_states,\n                return_dict=return_dict,\n            )\n        # If the user passed a tuple for encoder_outputs, we wrap it in a BaseModelOutput when return_dict=True\n        elif return_dict and not isinstance(encoder_outputs, BaseModelOutput):\n            encoder_outputs = BaseModelOutput(\n                last_hidden_state=encoder_outputs[0],\n                hidden_states=encoder_outputs[1] if len(encoder_outputs) > 1 else None,\n                attentions=encoder_outputs[2] if len(encoder_outputs) > 2 else None,\n            )\n\n        # decoder outputs consists of (dec_features, past_key_value, dec_hidden, dec_attn)\n        decoder_outputs = self.decoder(\n            input_ids=decoder_input_ids,\n            attention_mask=decoder_attention_mask,\n            encoder_hidden_states=encoder_outputs[0],\n            encoder_attention_mask=attention_mask,\n            head_mask=decoder_head_mask,\n            cross_attn_head_mask=cross_attn_head_mask,\n            past_key_values=past_key_values,\n            inputs_embeds=decoder_inputs_embeds,\n            use_cache=use_cache,\n            output_attentions=output_attentions,\n            output_hidden_states=output_hidden_states,\n            return_dict=return_dict,\n        )\n\n        if not return_dict:\n            return decoder_outputs + encoder_outputs\n\n        return Seq2SeqModelOutput(\n            last_hidden_state=decoder_outputs.last_hidden_state,\n            past_key_values=decoder_outputs.past_key_values,\n            decoder_hidden_states=decoder_outputs.hidden_states,\n            decoder_attentions=decoder_outputs.attentions,\n            cross_attentions=decoder_outputs.cross_attentions,\n            encoder_last_hidden_state=encoder_outputs.last_hidden_state,\n            encoder_hidden_states=encoder_outputs.hidden_states,\n            encoder_attentions=encoder_outputs.attentions,\n        )\n\n\nclass Florence2LanguageForConditionalGeneration(Florence2LanguagePreTrainedModel, GenerationMixin):\n    base_model_prefix = \"model\"\n    _tied_weights_keys = [\"encoder.embed_tokens.weight\", \"decoder.embed_tokens.weight\", \"lm_head.weight\"]\n    _keys_to_ignore_on_load_missing = [\"final_logits_bias\"]\n\n    def __init__(self, config: Florence2LanguageConfig):\n        super().__init__(config)\n        self.model = Florence2LanguageModel(config)\n        self.register_buffer(\"final_logits_bias\", torch.zeros((1, self.model.shared.num_embeddings)))\n        self.lm_head = nn.Linear(config.d_model, self.model.shared.num_embeddings, bias=False)\n\n        # Initialize weights and apply final processing\n        self.post_init()\n\n    def get_encoder(self):\n        return self.model.get_encoder()\n\n    def get_decoder(self):\n        return self.model.get_decoder()\n\n    def resize_token_embeddings(self, new_num_tokens: int, pad_to_multiple_of: Optional[int] = None) -> nn.Embedding:\n        new_embeddings = super().resize_token_embeddings(new_num_tokens, pad_to_multiple_of)\n        self._resize_final_logits_bias(new_embeddings.weight.shape[0])\n        return new_embeddings\n\n    def _resize_final_logits_bias(self, new_num_tokens: int) -> None:\n        old_num_tokens = self.final_logits_bias.shape[-1]\n        if new_num_tokens <= old_num_tokens:\n            new_bias = self.final_logits_bias[:, :new_num_tokens]\n        else:\n            extra_bias = torch.zeros((1, new_num_tokens - old_num_tokens), device=self.final_logits_bias.device)\n            new_bias = torch.cat([self.final_logits_bias, extra_bias], dim=1)\n        self.register_buffer(\"final_logits_bias\", new_bias)\n\n    def get_output_embeddings(self):\n        return self.lm_head\n\n    def set_output_embeddings(self, new_embeddings):\n        self.lm_head = new_embeddings\n\n    def forward(\n        self,\n        input_ids: torch.LongTensor = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        decoder_input_ids: Optional[torch.LongTensor] = None,\n        decoder_attention_mask: Optional[torch.LongTensor] = None,\n        head_mask: Optional[torch.Tensor] = None,\n        decoder_head_mask: Optional[torch.Tensor] = None,\n        cross_attn_head_mask: Optional[torch.Tensor] = None,\n        encoder_outputs: Optional[List[torch.FloatTensor]] = None,\n        past_key_values: Optional[List[torch.FloatTensor]] = None,\n        inputs_embeds: Optional[torch.FloatTensor] = None,\n        decoder_inputs_embeds: Optional[torch.FloatTensor] = None,\n        labels: Optional[torch.LongTensor] = None,\n        use_cache: Optional[bool] = None,\n        output_attentions: Optional[bool] = None,\n        output_hidden_states: Optional[bool] = None,\n        return_dict: Optional[bool] = None,\n    ) -> Union[Tuple, Seq2SeqLMOutput]:\n        r\"\"\"\n        labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):\n            Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,\n            config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored\n            (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`.\n\n        Returns:\n        \"\"\"\n        return_dict = return_dict if return_dict is not None else self.config.use_return_dict\n\n        if labels is not None:\n            if use_cache:\n                logger.warning(\"The `use_cache` argument is changed to `False` since `labels` is provided.\")\n            use_cache = False\n            if decoder_input_ids is None and decoder_inputs_embeds is None:\n                decoder_input_ids = shift_tokens_right(\n                    labels, self.config.pad_token_id, self.config.decoder_start_token_id\n                )\n\n        outputs = self.model(\n            input_ids,\n            attention_mask=attention_mask,\n            decoder_input_ids=decoder_input_ids,\n            encoder_outputs=encoder_outputs,\n            decoder_attention_mask=decoder_attention_mask,\n            head_mask=head_mask,\n            decoder_head_mask=decoder_head_mask,\n            cross_attn_head_mask=cross_attn_head_mask,\n            past_key_values=past_key_values,\n            inputs_embeds=inputs_embeds,\n            decoder_inputs_embeds=decoder_inputs_embeds,\n            use_cache=use_cache,\n            output_attentions=output_attentions,\n            output_hidden_states=output_hidden_states,\n            return_dict=return_dict,\n        )\n\n        lm_logits = self.lm_head(outputs[0])\n        lm_logits = lm_logits + self.final_logits_bias.to(lm_logits.device)\n\n        masked_lm_loss = None\n        if labels is not None:\n            labels = labels.to(lm_logits.device)\n            loss_fct = CrossEntropyLoss()\n            masked_lm_loss = loss_fct(lm_logits.view(-1, self.config.vocab_size), labels.view(-1))\n\n        if not return_dict:\n            output = (lm_logits,) + outputs[1:]\n            return ((masked_lm_loss,) + output) if masked_lm_loss is not None else output\n\n        return Seq2SeqLMOutput(\n            loss=masked_lm_loss,\n            logits=lm_logits,\n            past_key_values=outputs.past_key_values,\n            decoder_hidden_states=outputs.decoder_hidden_states,\n            decoder_attentions=outputs.decoder_attentions,\n            cross_attentions=outputs.cross_attentions,\n            encoder_last_hidden_state=outputs.encoder_last_hidden_state,\n            encoder_hidden_states=outputs.encoder_hidden_states,\n            encoder_attentions=outputs.encoder_attentions,\n        )\n\n    def prepare_inputs_for_generation(\n        self,\n        decoder_input_ids,\n        past_key_values=None,\n        attention_mask=None,\n        decoder_attention_mask=None,\n        head_mask=None,\n        decoder_head_mask=None,\n        cross_attn_head_mask=None,\n        use_cache=None,\n        encoder_outputs=None,\n        **kwargs,\n    ):\n        # cut decoder_input_ids if past_key_values is used\n        if past_key_values is not None:\n            past_length = past_key_values[0][0].shape[2]\n\n            # Some generation methods already pass only the last input ID\n            if decoder_input_ids.shape[1] > past_length:\n                remove_prefix_length = past_length\n            else:\n                # Default to old behavior: keep only final ID\n                remove_prefix_length = decoder_input_ids.shape[1] - 1\n\n            decoder_input_ids = decoder_input_ids[:, remove_prefix_length:]\n\n        return {\n            \"input_ids\": None,  # encoder_outputs is defined. input_ids not needed\n            \"encoder_outputs\": encoder_outputs,\n            \"past_key_values\": past_key_values,\n            \"decoder_input_ids\": decoder_input_ids,\n            \"attention_mask\": attention_mask,\n            \"decoder_attention_mask\": decoder_attention_mask,\n            \"head_mask\": head_mask,\n            \"decoder_head_mask\": decoder_head_mask,\n            \"cross_attn_head_mask\": cross_attn_head_mask,\n            \"use_cache\": use_cache,  # change this to avoid caching (presumably for debugging)\n        }\n\n    def prepare_decoder_input_ids_from_labels(self, labels: torch.Tensor):\n        return shift_tokens_right(labels, self.config.pad_token_id, self.config.decoder_start_token_id)\n\n    @staticmethod\n    def _reorder_cache(past_key_values, beam_idx):\n        reordered_past = ()\n        for layer_past in past_key_values:\n            # cached cross_attention states don't have to be reordered -> they are always the same\n            reordered_past += (\n                tuple(past_state.index_select(0, beam_idx.to(past_state.device)) for past_state in layer_past[:2])\n                + layer_past[2:],\n            )\n        return reordered_past\n\n@dataclass\nclass Florence2Seq2SeqLMOutput(ModelOutput):\n    \"\"\"\n    Base class for Florence-2 model's outputs that also contains : pre-computed hidden states that can speed up sequential\n    decoding.\n\n    Args:\n        loss (`torch.FloatTensor` of shape `(1,)`, *optional*, returned when `labels` is provided):\n            Language modeling loss.\n        logits (`torch.FloatTensor` of shape `(batch_size, sequence_length, config.vocab_size)`):\n            Prediction scores of the language modeling head (scores for each vocabulary token before SoftMax).\n        last_hidden_state (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`):\n            Sequence of hidden-states at the output of the last layer of the decoder of the model.\n\n            If `past_key_values` is used only the last hidden-state of the sequences of shape `(batch_size, 1,\n            hidden_size)` is output.\n        past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or when `config.use_cache=True`):\n            Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of shape\n            `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape\n            `(batch_size, num_heads, encoder_sequence_length, embed_size_per_head)`.\n\n            Contains pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention\n            blocks) that can be used (see `past_key_values` input) to speed up sequential decoding.\n        decoder_hidden_states (`tuple(torch.FloatTensor)`, *optional*, returned when `output_hidden_states=True` is passed or when `config.output_hidden_states=True`):\n            Tuple of `torch.FloatTensor` (one for the output of the embeddings, if the model has an embedding layer, +\n            one for the output of each layer) of shape `(batch_size, sequence_length, hidden_size)`.\n\n            Hidden-states of the decoder at the output of each layer plus the optional initial embedding outputs.\n        decoder_attentions (`tuple(torch.FloatTensor)`, *optional*, returned when `output_attentions=True` is passed or when `config.output_attentions=True`):\n            Tuple of `torch.FloatTensor` (one for each layer) of shape `(batch_size, num_heads, sequence_length,\n            sequence_length)`.\n\n            Attentions weights of the decoder, after the attention softmax, used to compute the weighted average in the\n            self-attention heads.\n        cross_attentions (`tuple(torch.FloatTensor)`, *optional*, returned when `output_attentions=True` is passed or when `config.output_attentions=True`):\n            Tuple of `torch.FloatTensor` (one for each layer) of shape `(batch_size, num_heads, sequence_length,\n            sequence_length)`.\n\n            Attentions weights of the decoder's cross-attention layer, after the attention softmax, used to compute the\n            weighted average in the cross-attention heads.\n        encoder_last_hidden_state (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):\n            Sequence of hidden-states at the output of the last layer of the encoder of the model.\n        encoder_hidden_states (`tuple(torch.FloatTensor)`, *optional*, returned when `output_hidden_states=True` is passed or when `config.output_hidden_states=True`):\n            Tuple of `torch.FloatTensor` (one for the output of the embeddings, if the model has an embedding layer, +\n            one for the output of each layer) of shape `(batch_size, sequence_length, hidden_size)`.\n\n            Hidden-states of the encoder at the output of each layer plus the optional initial embedding outputs.\n        encoder_attentions (`tuple(torch.FloatTensor)`, *optional*, returned when `output_attentions=True` is passed or when `config.output_attentions=True`):\n            Tuple of `torch.FloatTensor` (one for each layer) of shape `(batch_size, num_heads, sequence_length,\n            sequence_length)`.\n\n            Attentions weights of the encoder, after the attention softmax, used to compute the weighted average in the\n            self-attention heads.\n        image_hidden_states (`tuple(torch.FloatTensor)`, *optional*):\n            Tuple of `torch.FloatTensor` (one for the output of the image embeddings, `(batch_size,\n            num_image_tokens, hidden_size)`.\n\n            image_hidden_states of the model produced by the vision encoder\n    \"\"\"\n    loss: Optional[torch.FloatTensor] = None\n    logits: torch.FloatTensor = None\n    last_hidden_state: torch.FloatTensor = None\n    past_key_values: Optional[Tuple[Tuple[torch.FloatTensor]]] = None\n    decoder_hidden_states: Optional[Tuple[torch.FloatTensor, ...]] = None\n    decoder_attentions: Optional[Tuple[torch.FloatTensor, ...]] = None\n    cross_attentions: Optional[Tuple[torch.FloatTensor, ...]] = None\n    encoder_last_hidden_state: Optional[torch.FloatTensor] = None\n    encoder_hidden_states: Optional[Tuple[torch.FloatTensor, ...]] = None\n    encoder_attentions: Optional[Tuple[torch.FloatTensor, ...]] = None\n    image_hidden_states: Optional[Tuple[torch.FloatTensor, ...]] = None\n\n\nFLORENCE2_START_DOCSTRING = r\"\"\"\n    This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the\n    library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads\n    etc.)\n\n    This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass.\n    Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage\n    and behavior.\n\n    Parameters:\n        config ([`Florence2Config`] or [`Florence2VisionConfig`]):\n            Model configuration class with all the parameters of the model. Initializing with a config file does not\n            load the weights associated with the model, only the configuration. Check out the\n            [`~PreTrainedModel.from_pretrained`] method to load the model weights.\n\"\"\"\n\n\n@add_start_docstrings(\n    \"The bare Florence-2 Model outputting raw hidden-states without any specific head on top.\",\n    FLORENCE2_START_DOCSTRING,\n)\nclass Florence2PreTrainedModel(PreTrainedModel):\n    config_class = Florence2Config\n    base_model_prefix = \"model\"\n    supports_gradient_checkpointing = True\n    _skip_keys_device_placement = \"past_key_values\"\n\n    @property\n    def _supports_flash_attn_2(self):\n        \"\"\"\n        Retrieve language_model's attribute to check whether the model supports\n        Flash Attention 2 or not.\n        \"\"\"\n        return self.language_model._supports_flash_attn_2\n\n    @property\n    def _supports_sdpa(self):\n        \"\"\"\n        Retrieve language_model's attribute to check whether the model supports\n        SDPA or not.\n        \"\"\"\n        return self.language_model._supports_sdpa\n\n\nFLORENCE2_INPUTS_DOCSTRING = r\"\"\"\n    Args:\n        input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):\n            Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide\n            it.\n\n            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and\n            [`PreTrainedTokenizer.__call__`] for details.\n\n            [What are input IDs?](../glossary#input-ids)\n        pixel_values (`torch.FloatTensor` of shape `(batch_size, num_channels, image_size, image_size)):\n            The tensors corresponding to the input images. Pixel values can be obtained using\n            [`AutoImageProcessor`]. See [`CLIPImageProcessor.__call__`] for details ([]`Florence2Processor`] uses\n            [`CLIPImageProcessor`] for processing images).\n        attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):\n            Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:\n\n            - 1 for tokens that are **not masked**,\n            - 0 for tokens that are **masked**.\n\n            [What are attention masks?](../glossary#attention-mask)\n\n            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and\n            [`PreTrainedTokenizer.__call__`] for details.\n\n            If `past_key_values` is used, optionally only the last `decoder_input_ids` have to be input (see\n            `past_key_values`).\n\n            If you want to change padding behavior, you should read [`modeling_opt._prepare_decoder_attention_mask`]\n            and modify to your needs. See diagram 1 in [the paper](https://arxiv.org/abs/1910.13461) for more\n            information on the default strategy.\n\n            - 1 indicates the head is **not masked**,\n            - 0 indicates the head is **masked**.\n        position_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):\n            Indices of positions of each input sequence tokens in the position embeddings. Selected in the range `[0,\n            config.n_positions - 1]`. [What are position IDs?](../glossary#position-ids)\n        past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or when `config.use_cache=True`):\n            Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of shape\n            `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape\n            `(batch_size, num_heads, encoder_sequence_length, embed_size_per_head)`.\n\n            Contains pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention\n            blocks) that can be used (see `past_key_values` input) to speed up sequential decoding.\n\n            If `past_key_values` are used, the user can optionally input only the last `decoder_input_ids` (those that\n            don't have their past key value states given to this model) of shape `(batch_size, 1)` instead of all\n            `decoder_input_ids` of shape `(batch_size, sequence_length)`.\n        inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):\n            Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This\n            is useful if you want more control over how to convert `input_ids` indices into associated vectors than the\n            model's internal embedding lookup matrix.\n        use_cache (`bool`, *optional*):\n            If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see\n            `past_key_values`).\n        output_attentions (`bool`, *optional*):\n            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned\n            tensors for more detail.\n        output_hidden_states (`bool`, *optional*):\n            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for\n            more detail.\n        return_dict (`bool`, *optional*):\n            Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.\n\"\"\"\n\n@add_start_docstrings(\n    \"\"\"The FLORENCE2 vision model without any head\"\"\",\n    FLORENCE2_START_DOCSTRING,\n)\nclass Florence2VisionModel(Florence2PreTrainedModel):\n    def __init__(self, config: Florence2VisionConfig):\n        super().__init__(config)\n        assert config.model_type == 'davit', 'only DaViT is supported for now'\n        self.vision_tower = DaViT.from_config(config=config)\n\n        self.post_init()\n    \n    def forward(self, pixel_values):\n        if len(pixel_values.shape) == 4:\n            x = self.vision_tower.forward_features_unpool(pixel_values)\n        else:\n            raise ValueError(f'invalid image shape {pixel_values.shape}')\n        return x\n\n\n@add_start_docstrings(\n    \"\"\"The FLORENCE2 vision model with projection layer\"\"\",\n    FLORENCE2_START_DOCSTRING,\n)\nclass Florence2VisionModelWithProjection(Florence2PreTrainedModel):\n    def __init__(self, config: Florence2VisionConfig):\n        super().__init__(config)\n        assert config.model_type == 'davit', 'only DaViT is supported for now'\n        self.vision_tower = DaViT.from_config(config=config)\n\n        self._build_image_projection_layers(config)\n\n        self.post_init()\n    \n    def _build_image_projection_layers(self, config):\n        image_dim_out = config.dim_embed[-1]\n        dim_projection = config.projection_dim\n        self.image_projection = nn.Parameter(\n            torch.empty(image_dim_out, dim_projection)\n        )\n        self.image_proj_norm = nn.LayerNorm(dim_projection)\n        image_pos_embed_config = config.image_pos_embed\n        if image_pos_embed_config['type'] == 'learned_abs_2d':\n            self.image_pos_embed = LearnedAbsolutePositionEmbedding2D(\n                embedding_dim=image_dim_out,\n                num_pos=image_pos_embed_config['max_pos_embeddings']\n            )\n        else:\n            raise NotImplementedError('Not implemented yet')\n\n        self.image_feature_source = config.image_feature_source\n\n        # temporal embedding\n        visual_temporal_embedding_config = config.visual_temporal_embedding\n        if visual_temporal_embedding_config['type'] == 'COSINE':\n            self.visual_temporal_embed = PositionalEmbeddingCosine1D(\n                embed_dim=image_dim_out,\n                max_seq_len=visual_temporal_embedding_config['max_temporal_embeddings']\n            )\n        else:\n            raise NotImplementedError('Not implemented yet')\n\n    def forward(self, pixel_values):\n        if len(pixel_values.shape) == 4:\n            batch_size, C, H, W = pixel_values.shape\n            T = 1\n            x = self.vision_tower.forward_features_unpool(pixel_values)\n        else:\n            raise ValueError(f'invalid image shape {pixel_values.shape}')\n        \n        if self.image_pos_embed is not None:\n            x = x.view(batch_size * T, -1, x.shape[-1])\n            num_tokens = x.shape[-2]\n            h, w = int(num_tokens ** 0.5), int(num_tokens ** 0.5)\n            assert h * w == num_tokens, 'only support square feature maps for now'\n            x = x.view(batch_size * T, h, w, x.shape[-1])\n            pos_embed = self.image_pos_embed(x)\n            x = x + pos_embed\n            x = x.view(batch_size, T * h*w, x.shape[-1])\n\n        if self.visual_temporal_embed is not None:\n            visual_temporal_embed = self.visual_temporal_embed(x.view(batch_size, T, -1, x.shape[-1])[:, :, 0])\n            x = x.view(batch_size, T, -1, x.shape[-1]) + visual_temporal_embed.view(1, T, 1, x.shape[-1])\n\n        x_feat_dict = {}\n\n        spatial_avg_pool_x = x.view(batch_size, T, -1, x.shape[-1]).mean(dim=2)\n        x_feat_dict['spatial_avg_pool'] = spatial_avg_pool_x\n\n        temporal_avg_pool_x = x.view(batch_size, T, -1, x.shape[-1]).mean(dim=1)\n        x_feat_dict['temporal_avg_pool'] = temporal_avg_pool_x\n\n        x = x.view(batch_size, T, -1, x.shape[-1])[:, -1]\n        x_feat_dict['last_frame'] = x\n\n        new_x = []\n        for _image_feature_source in self.image_feature_source:\n            if _image_feature_source not in x_feat_dict:\n                raise ValueError('invalid image feature source: {}'.format(_image_feature_source))\n            new_x.append(x_feat_dict[_image_feature_source])\n\n        x = torch.cat(new_x, dim=1)\n\n        x = x @ self.image_projection\n        x = self.image_proj_norm(x)\n\n\n        return x\n\n\n\n@add_start_docstrings(\n    \"\"\"The FLORENCE2 model which consists of a vision backbone and a language model.\"\"\",\n    FLORENCE2_START_DOCSTRING,\n)\nclass Florence2ForConditionalGeneration(Florence2PreTrainedModel):\n    def __init__(self, config: Florence2Config):\n        super().__init__(config)\n        assert config.vision_config.model_type == 'davit', 'only DaViT is supported for now'\n        self.vision_tower = DaViT.from_config(config=config.vision_config)\n        # remove unused layers \n        del self.vision_tower.head\n        del self.vision_tower.norms\n\n        self.vocab_size = config.vocab_size\n        self._attn_implementation = config._attn_implementation\n        self._build_image_projection_layers(config)\n\n        language_model = Florence2LanguageForConditionalGeneration(config=config.text_config)\n\n        if language_model._tied_weights_keys is not None:\n            self._tied_weights_keys = [f\"language_model.{k}\" for k in language_model._tied_weights_keys]\n        self.language_model = language_model\n\n        self.pad_token_id = self.config.pad_token_id if self.config.pad_token_id is not None else -1\n        self.post_init()\n    \n    def _build_image_projection_layers(self, config):\n        image_dim_out = config.vision_config.dim_embed[-1]\n        dim_projection = config.vision_config.projection_dim\n        self.image_projection = nn.Parameter(\n            torch.empty(image_dim_out, dim_projection)\n        )\n        self.image_proj_norm = nn.LayerNorm(dim_projection)\n        image_pos_embed_config = config.vision_config.image_pos_embed\n        if image_pos_embed_config['type'] == 'learned_abs_2d':\n            self.image_pos_embed = LearnedAbsolutePositionEmbedding2D(\n                embedding_dim=image_dim_out,\n                num_pos=image_pos_embed_config['max_pos_embeddings']\n            )\n        else:\n            raise NotImplementedError('Not implemented yet')\n\n        self.image_feature_source = config.vision_config.image_feature_source\n\n        # temporal embedding\n        visual_temporal_embedding_config = config.vision_config.visual_temporal_embedding\n        if visual_temporal_embedding_config['type'] == 'COSINE':\n            self.visual_temporal_embed = PositionalEmbeddingCosine1D(\n                embed_dim=image_dim_out,\n                max_seq_len=visual_temporal_embedding_config['max_temporal_embeddings']\n            )\n        else:\n            raise NotImplementedError('Not implemented yet')\n\n    def get_encoder(self):\n        return self.language_model.get_encoder()\n\n    def get_decoder(self):\n        return self.language_model.get_decoder()\n\n    def get_input_embeddings(self):\n        return self.language_model.get_input_embeddings()\n\n    def resize_token_embeddings(self, new_num_tokens: Optional[int] = None, pad_to_multiple_of=None) -> nn.Embedding:\n        model_embeds = self.language_model.resize_token_embeddings(new_num_tokens, pad_to_multiple_of)\n        # update vocab size\n        self.config.text_config.vocab_size = model_embeds.num_embeddings\n        self.config.vocab_size = model_embeds.num_embeddings\n        self.vocab_size = model_embeds.num_embeddings\n        return model_embeds\n    \n    def _encode_image(self, pixel_values):\n        if len(pixel_values.shape) == 4:\n            batch_size, C, H, W = pixel_values.shape\n            T = 1\n            x = self.vision_tower.forward_features_unpool(pixel_values)\n        else:\n            raise ValueError(f'invalid image shape {pixel_values.shape}')\n        \n        if self.image_pos_embed is not None:\n            x = x.view(batch_size * T, -1, x.shape[-1])\n            num_tokens = x.shape[-2]\n            h, w = int(num_tokens ** 0.5), int(num_tokens ** 0.5)\n            assert h * w == num_tokens, 'only support square feature maps for now'\n            x = x.view(batch_size * T, h, w, x.shape[-1])\n            pos_embed = self.image_pos_embed(x)\n            x = x + pos_embed\n            x = x.view(batch_size, T * h*w, x.shape[-1])\n\n        if self.visual_temporal_embed is not None:\n            visual_temporal_embed = self.visual_temporal_embed(x.view(batch_size, T, -1, x.shape[-1])[:, :, 0])\n            x = x.view(batch_size, T, -1, x.shape[-1]) + visual_temporal_embed.view(1, T, 1, x.shape[-1])\n\n        x_feat_dict = {}\n\n        spatial_avg_pool_x = x.view(batch_size, T, -1, x.shape[-1]).mean(dim=2)\n        x_feat_dict['spatial_avg_pool'] = spatial_avg_pool_x\n\n        temporal_avg_pool_x = x.view(batch_size, T, -1, x.shape[-1]).mean(dim=1)\n        x_feat_dict['temporal_avg_pool'] = temporal_avg_pool_x\n\n        x = x.view(batch_size, T, -1, x.shape[-1])[:, -1]\n        x_feat_dict['last_frame'] = x\n\n        new_x = []\n        for _image_feature_source in self.image_feature_source:\n            if _image_feature_source not in x_feat_dict:\n                raise ValueError('invalid image feature source: {}'.format(_image_feature_source))\n            new_x.append(x_feat_dict[_image_feature_source])\n\n        x = torch.cat(new_x, dim=1)\n\n        x = x @ self.image_projection\n        x = self.image_proj_norm(x)\n\n        return x \n\n    def _merge_input_ids_with_image_features(\n        self, image_features, inputs_embeds \n    ):\n        batch_size, image_token_length = image_features.size()[:-1]\n        device = image_features.device\n        image_attention_mask = torch.ones(batch_size, image_token_length, device=device)\n\n        # task_prefix_embeds: [batch_size, padded_context_length, hidden_size]\n        # task_prefix_attention_mask: [batch_size, context_length]\n        if inputs_embeds is None:\n            return image_features, image_attention_mask\n\n        task_prefix_embeds = inputs_embeds\n        task_prefix_attention_mask = torch.ones(batch_size, task_prefix_embeds.size(1), device=device)\n\n        if len(task_prefix_attention_mask.shape) == 3:\n            task_prefix_attention_mask = task_prefix_attention_mask[:, 0]\n\n        # concat [image embeds, task prefix embeds]\n        inputs_embeds = torch.cat([image_features, task_prefix_embeds], dim=1)\n        attention_mask = torch.cat([image_attention_mask, task_prefix_attention_mask], dim=1)\n\n        return inputs_embeds, attention_mask\n\n\n    @add_start_docstrings_to_model_forward(FLORENCE2_INPUTS_DOCSTRING)\n    @replace_return_docstrings(output_type=Florence2Seq2SeqLMOutput, config_class=_CONFIG_FOR_DOC)\n    def forward(\n        self,\n        input_ids: torch.LongTensor = None,\n        pixel_values: torch.FloatTensor = None,\n        attention_mask: Optional[torch.Tensor] = None,\n        decoder_input_ids: Optional[torch.LongTensor] = None,\n        decoder_attention_mask: Optional[torch.LongTensor] = None,\n        head_mask: Optional[torch.Tensor] = None,\n        decoder_head_mask: Optional[torch.Tensor] = None,\n        cross_attn_head_mask: Optional[torch.Tensor] = None,\n        encoder_outputs: Optional[List[torch.FloatTensor]] = None,\n        past_key_values: Optional[List[torch.FloatTensor]] = None,\n        inputs_embeds: Optional[torch.FloatTensor] = None,\n        decoder_inputs_embeds: Optional[torch.FloatTensor] = None,\n        labels: Optional[torch.LongTensor] = None,\n        use_cache: Optional[bool] = None,\n        output_attentions: Optional[bool] = None,\n        output_hidden_states: Optional[bool] = None,\n        return_dict: Optional[bool] = None,\n    ) -> Union[Tuple, Florence2Seq2SeqLMOutput]:\n        r\"\"\"\n        Args:\n            labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):\n                Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,\n                config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored\n                (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`.\n\n        Returns:\n\n        Example:\n\n        ```python\n        >>> from PIL import Image\n        >>> import requests\n        >>> from transformers import AutoProcessor, Florence2ForConditionalGeneration\n\n        >>> model = Florence2ForConditionalGeneration.from_pretrained(\"microsoft/Florence-2-large\")\n        >>> processor = AutoProcessor.from_pretrained(\"microsoft/Florence-2-large\")\n\n        >>> prompt = \"<CAPTION>\"\n        >>> url = \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg\"\n        >>> image = Image.open(requests.get(url, stream=True).raw)\n\n        >>> inputs = processor(text=prompt, images=image, return_tensors=\"pt\")\n\n        >>> # Generate\n        >>> generate_ids = model.generate(**inputs, max_length=100)\n        >>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]\n        \"A green car parked in front of a yellow building.\"\n        ```\"\"\"\n        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions\n        output_hidden_states = (\n            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states\n        )\n        return_dict = return_dict if return_dict is not None else self.config.use_return_dict\n\n        image_features = None\n        if inputs_embeds is None:\n            # 1. Extra the input embeddings\n            if input_ids is not None:\n                inputs_embeds = self.get_input_embeddings()(input_ids)\n            # 2. Merge text and images\n            if pixel_values is not None:\n                # (batch_size, num_image_tokens, hidden_size)\n                image_features = self._encode_image(pixel_values)\n                inputs_embeds, attention_mask = self._merge_input_ids_with_image_features(image_features, inputs_embeds)\n\n        if inputs_embeds is not None:\n            attention_mask = attention_mask.to(inputs_embeds.dtype)\n        outputs = self.language_model(\n            attention_mask=attention_mask,\n            labels=labels,\n            inputs_embeds=inputs_embeds,\n            decoder_input_ids=decoder_input_ids,\n            encoder_outputs=encoder_outputs,\n            decoder_attention_mask=decoder_attention_mask,\n            head_mask=head_mask,\n            decoder_head_mask=decoder_head_mask,\n            cross_attn_head_mask=cross_attn_head_mask,\n            past_key_values=past_key_values,\n            decoder_inputs_embeds=decoder_inputs_embeds,\n            use_cache=use_cache,\n            output_attentions=output_attentions,\n            output_hidden_states=output_hidden_states,\n            return_dict=return_dict,\n        )\n\n        logits = outputs.logits\n        logits = logits.float()\n        loss = outputs.loss\n        if not return_dict:\n            output = (logits,) + outputs[1:]\n            return (loss,) + output if loss is not None else output\n\n        return Florence2Seq2SeqLMOutput(\n            loss=loss,\n            logits=logits,\n            past_key_values=outputs.past_key_values,\n            decoder_hidden_states=outputs.decoder_hidden_states,\n            decoder_attentions=outputs.decoder_attentions,\n            cross_attentions=outputs.cross_attentions,\n            encoder_last_hidden_state=outputs.encoder_last_hidden_state,\n            encoder_hidden_states=outputs.encoder_hidden_states,\n            encoder_attentions=outputs.encoder_attentions,\n            image_hidden_states=image_features\n        )\n\n    def generate(\n        self,\n        input_ids, \n        inputs_embeds=None,\n        pixel_values=None,\n        **kwargs\n        ):\n\n        if inputs_embeds is None:\n            # 1. Extra the input embeddings\n            if input_ids is not None:\n                inputs_embeds = self.get_input_embeddings()(input_ids)\n            # 2. Merge text and images\n            if pixel_values is not None:\n                image_features = self._encode_image(pixel_values)\n                inputs_embeds, attention_mask = self._merge_input_ids_with_image_features(image_features, inputs_embeds)\n        \n        return self.language_model.generate(\n            input_ids=None,\n            inputs_embeds=inputs_embeds,\n            **kwargs\n        )\n\n    def prepare_inputs_for_generation(\n        self,\n        decoder_input_ids,\n        past_key_values=None,\n        attention_mask=None,\n        pixel_values=None,\n        decoder_attention_mask=None,\n        head_mask=None,\n        decoder_head_mask=None,\n        cross_attn_head_mask=None,\n        use_cache=None,\n        encoder_outputs=None,\n        **kwargs,\n    ):\n        # cut decoder_input_ids if past_key_values is used\n        if past_key_values is not None:\n            past_length = past_key_values[0][0].shape[2]\n\n            # Some generation methods already pass only the last input ID\n            if decoder_input_ids.shape[1] > past_length:\n                remove_prefix_length = past_length\n            else:\n                # Default to old behavior: keep only final ID\n                remove_prefix_length = decoder_input_ids.shape[1] - 1\n\n            decoder_input_ids = decoder_input_ids[:, remove_prefix_length:]\n        \n        return {\n            \"input_ids\": None,  # encoder_outputs is defined. input_ids not needed\n            \"encoder_outputs\": encoder_outputs,\n            \"past_key_values\": past_key_values,\n            \"decoder_input_ids\": decoder_input_ids,\n            \"attention_mask\": attention_mask,\n            \"pixel_values\": pixel_values,\n            \"decoder_attention_mask\": decoder_attention_mask,\n            \"head_mask\": head_mask,\n            \"decoder_head_mask\": decoder_head_mask,\n            \"cross_attn_head_mask\": cross_attn_head_mask,\n            \"use_cache\": use_cache,  # change this to avoid caching (presumably for debugging)\n        }\n    \n    def prepare_decoder_input_ids_from_labels(self, labels: torch.Tensor):\n        return self.language_model.shift_tokens_right(labels)\n\n    def _reorder_cache(self, *args, **kwargs):\n        return self.language_model._reorder_cache(*args, **kwargs)"
  },
  {
    "path": "eval/grounded_sam/florence2/preprocessor_config.json",
    "content": "{\n  \"auto_map\": {\n    \"AutoProcessor\": \"processing_florence2.Florence2Processor\"\n   },\n  \"_valid_processor_keys\": [\n    \"images\",\n    \"do_resize\",\n    \"size\",\n    \"resample\",\n    \"do_rescale\",\n    \"rescale_factor\",\n    \"do_normalize\",\n    \"image_mean\",\n    \"image_std\",\n    \"return_tensors\",\n    \"data_format\",\n    \"input_data_format\",\n    \"do_convert_rgb\"\n  ],\n  \"do_convert_rgb\": null,\n  \"do_normalize\": true,\n  \"do_rescale\": true,\n  \"do_resize\": true,\n  \"do_center_crop\": false,\n  \"image_processor_type\": \"CLIPImageProcessor\",\n  \"image_seq_length\": 577,\n  \"image_mean\": [0.485, 0.456, 0.406],\n  \"image_std\":  [0.229, 0.224, 0.225],\n  \"processor_class\": \"Florence2Processor\",\n  \"resample\": 3,\n  \"size\": {\n    \"height\": 768,\n    \"width\":768 \n  },\n  \"crop_size\": {\n    \"height\": 768,\n    \"width\": 768\n  }\n}"
  },
  {
    "path": "eval/grounded_sam/florence2/processing_florence2.py",
    "content": "# coding=utf-8\n# Copyright 2024 Microsoft and The HuggingFace Inc. team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\"\"\"\nProcessor class for Florence-2.\n\"\"\"\n\nimport re\nimport logging\nfrom typing import List, Optional, Union\nimport numpy as np\nimport math\n\nimport torch\n\nfrom transformers.feature_extraction_utils import BatchFeature\nfrom transformers.image_utils import ImageInput, is_valid_image\nfrom transformers.processing_utils import ProcessorMixin\nfrom transformers.tokenization_utils_base import (\n    PaddingStrategy,\n    PreTokenizedInput,\n    TextInput,\n    TruncationStrategy,\n)\nfrom transformers import BartTokenizer, BartTokenizerFast\nfrom transformers.utils import TensorType\n\n\nlogger = logging.getLogger(__name__)\n\n# Copied from transformers.models.idefics2.processing_idefics2.is_url\ndef is_url(val) -> bool:\n    return isinstance(val, str) and val.startswith(\"http\")\n\n# Copied from transformers.models.idefics2.processing_idefics2.is_image_or_image_url\ndef is_image_or_image_url(elem):\n    return is_url(elem) or is_valid_image(elem)\n\n\ndef _is_str_or_image(elem):\n    return isinstance(elem, (str)) or is_image_or_image_url(elem)\n\n\nclass Florence2Processor(ProcessorMixin):\n    r\"\"\"\n    Constructs a Florence2 processor which wraps a Florence2 image processor and a Florence2 tokenizer into a single processor.\n\n    [`Florence2Processor`] offers all the functionalities of [`CLIPImageProcessor`] and [`BartTokenizerFast`]. See the\n    [`~Florence2Processor.__call__`] and [`~Florence2Processor.decode`] for more information.\n\n    Args:\n        image_processor ([`CLIPImageProcessor`], *optional*):\n            The image processor is a required input.\n        tokenizer ([`BartTokenizerFast`], *optional*):\n            The tokenizer is a required input.\n    \"\"\"\n\n    attributes = [\"image_processor\", \"tokenizer\"]\n    image_processor_class = \"CLIPImageProcessor\"\n    tokenizer_class = (\"BartTokenizer\", \"BartTokenizerFast\")\n\n    def __init__(\n        self,\n        image_processor=None,\n        tokenizer=None,\n    ):\n        if image_processor is None:\n            raise ValueError(\"You need to specify an `image_processor`.\")\n        if tokenizer is None:\n            raise ValueError(\"You need to specify a `tokenizer`.\")\n        if not hasattr(image_processor, \"image_seq_length\"):\n            raise ValueError(\"Image processor is missing an `image_seq_length` attribute.\")\n\n        self.image_seq_length = image_processor.image_seq_length\n\n        tokens_to_add = {\n                'additional_special_tokens': \\\n                    tokenizer.additional_special_tokens + \\\n                    ['<od>', '</od>', '<ocr>', '</ocr>'] + \\\n                    [f'<loc_{x}>' for x in range(1000)] + \\\n                    ['<cap>', '</cap>', '<ncap>', '</ncap>','<dcap>', '</dcap>', '<grounding>', '</grounding>', '<seg>', '</seg>', '<sep>', '<region_cap>', '</region_cap>', '<region_to_desciption>', '</region_to_desciption>', '<proposal>', '</proposal>', '<poly>', '</poly>', '<and>']\n            }\n        tokenizer.add_special_tokens(tokens_to_add)\n\n        self.tasks_answer_post_processing_type = {\n            '<OCR>': 'pure_text',\n            '<OCR_WITH_REGION>': 'ocr',\n            '<CAPTION>': 'pure_text',\n            '<DETAILED_CAPTION>': 'pure_text',\n            '<MORE_DETAILED_CAPTION>': 'pure_text',\n            '<OD>': 'description_with_bboxes',\n            '<DENSE_REGION_CAPTION>': 'description_with_bboxes',\n            '<CAPTION_TO_PHRASE_GROUNDING>': \"phrase_grounding\",\n            '<REFERRING_EXPRESSION_SEGMENTATION>': 'polygons',\n            '<REGION_TO_SEGMENTATION>': 'polygons',\n            '<OPEN_VOCABULARY_DETECTION>': 'description_with_bboxes_or_polygons',\n            '<REGION_TO_CATEGORY>': 'pure_text',\n            '<REGION_TO_DESCRIPTION>': 'pure_text',\n            '<REGION_TO_OCR>': 'pure_text',\n            '<REGION_PROPOSAL>': 'bboxes'\n        }\n\n        self.task_prompts_without_inputs = {\n            '<OCR>': 'What is the text in the image?',\n            '<OCR_WITH_REGION>': 'What is the text in the image, with regions?',\n            '<CAPTION>': 'What does the image describe?',\n            '<DETAILED_CAPTION>': 'Describe in detail what is shown in the image.',\n            '<MORE_DETAILED_CAPTION>': 'Describe with a paragraph what is shown in the image.',\n            '<OD>': 'Locate the objects with category name in the image.',\n            '<DENSE_REGION_CAPTION>': 'Locate the objects in the image, with their descriptions.',\n            '<REGION_PROPOSAL>': 'Locate the region proposals in the image.'\n        }\n\n        self.task_prompts_with_input = {\n            '<CAPTION_TO_PHRASE_GROUNDING>': \"Locate the phrases in the caption: {input}\",\n            '<REFERRING_EXPRESSION_SEGMENTATION>': 'Locate {input} in the image with mask',\n            '<REGION_TO_SEGMENTATION>': 'What is the polygon mask of region {input}',\n            '<OPEN_VOCABULARY_DETECTION>': 'Locate {input} in the image.',\n            '<REGION_TO_CATEGORY>': 'What is the region {input}?',\n            '<REGION_TO_DESCRIPTION>': 'What does the region {input} describe?',\n            '<REGION_TO_OCR>': 'What text is in the region {input}?',\n        }\n\n        self.post_processor = Florence2PostProcesser(tokenizer=tokenizer)\n\n\n        super().__init__(image_processor, tokenizer)\n    \n    def _construct_prompts(self, text):\n        # replace the task tokens with the task prompts if task token is in the text\n        prompts = []\n        for _text in text:\n            # 1. fixed task prompts without additional inputs\n            for task_token, task_prompt in self.task_prompts_without_inputs.items():\n                if task_token in _text:\n                    assert _text == task_token, f\"Task token {task_token} should be the only token in the text.\"\n                    _text = task_prompt\n                    break\n            # 2. task prompts with additional inputs \n            for task_token, task_prompt in self.task_prompts_with_input.items():\n                if task_token in _text:\n                    _text = task_prompt.format(input=_text.replace(task_token, ''))\n                    break\n            prompts.append(_text)\n        return prompts\n\n    def __call__(\n        self,\n        text: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None,\n        images: ImageInput = None,\n        tokenize_newline_separately: bool = True,\n        padding: Union[bool, str, PaddingStrategy] = False,\n        truncation: Union[bool, str, TruncationStrategy] = None,\n        max_length=None,\n        return_tensors: Optional[Union[str, TensorType]] = TensorType.PYTORCH,\n        do_resize: bool = None,\n        do_normalize: bool = None,\n        image_mean: Optional[Union[float, List[float]]] = None,\n        image_std: Optional[Union[float, List[float]]] = None,\n        data_format: Optional[\"ChannelDimension\"] = \"channels_first\",  # noqa: F821\n        input_data_format: Optional[\n            Union[str, \"ChannelDimension\"]  # noqa: F821\n        ] = None,\n        resample: \"PILImageResampling\" = None,  # noqa: F821\n        do_convert_rgb: bool = None,\n        do_thumbnail: bool = None,\n        do_align_long_axis: bool = None,\n        do_rescale: bool = None,\n    ) -> BatchFeature:\n        \"\"\"\n        Main method to prepare for the model one or several sequences(s) and image(s). This method forwards the `text`\n        and `kwargs` arguments to BartTokenizerFast's [`~BartTokenizerFast.__call__`] if `text` is not `None` to encode\n        the text. To prepare the image(s), this method forwards the `images` and `kwrags` arguments to\n        CLIPImageProcessor's [`~CLIPImageProcessor.__call__`] if `images` is not `None`. Please refer to the doctsring\n        of the above two methods for more information.\n\n        Args:\n            text (`str`, `List[str]`, `List[List[str]]`):\n                The sequence or batch of sequences to be encoded. Each sequence can be a string or a list of strings\n                (pretokenized string). If the sequences are provided as list of strings (pretokenized), you must set\n                `is_split_into_words=True` (to lift the ambiguity with a batch of sequences).\n            images (`PIL.Image.Image`, `np.ndarray`, `torch.Tensor`, `List[PIL.Image.Image]`, `List[np.ndarray]`, `List[torch.Tensor]`):\n                The image or batch of images to be prepared. Each image can be a PIL image, NumPy array or PyTorch\n                tensor. In case of a NumPy array/PyTorch tensor, each image should be of shape (C, H, W), where C is a\n                number of channels, H and W are image height and width.\n            tokenize_newline_separately (`bool`, defaults to `True`):\n                Adds a separately tokenized '\\n' at the end of the prompt.\n            padding (`bool`, `str` or [`~utils.PaddingStrategy`], *optional*, defaults to `False`):\n                Select a strategy to pad the returned sequences (according to the model's padding side and padding\n                index) among:\n                - `True` or `'longest'`: Pad to the longest sequence in the batch (or no padding if only a single\n                  sequence if provided).\n                - `'max_length'`: Pad to a maximum length specified with the argument `max_length` or to the maximum\n                  acceptable input length for the model if that argument is not provided.\n                - `False` or `'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of different\n                  lengths).\n            max_length (`int`, *optional*):\n                Maximum length of the returned list and optionally padding length (see above).\n            truncation (`bool`, *optional*):\n                Activates truncation to cut input sequences longer than `max_length` to `max_length`.\n            return_tensors (`str` or [`~utils.TensorType`], *optional*):\n                If set, will return tensors of a particular framework. Acceptable values are:\n\n                - `'tf'`: Return TensorFlow `tf.constant` objects.\n                - `'pt'`: Return PyTorch `torch.Tensor` objects.\n                - `'np'`: Return NumPy `np.ndarray` objects.\n                - `'jax'`: Return JAX `jnp.ndarray` objects.\n\n        Returns:\n            [`BatchFeature`]: A [`BatchFeature`] with the following fields:\n\n            - **input_ids** -- List of token ids to be fed to a model. Returned when `text` is not `None`. If `suffix`\n              is provided, the `input_ids` will also contain the suffix input ids.\n            - **attention_mask** -- List of indices specifying which tokens should be attended to by the model (when\n              `return_attention_mask=True` or if *\"attention_mask\"* is in `self.model_input_names` and if `text` is not\n              `None`).\n            - **pixel_values** -- Pixel values to be fed to a model. Returned when `images` is not `None`.\n            - **labels** -- Labels compatible with training if `suffix` is not None\n        \"\"\"\n\n        return_token_type_ids = False\n\n        if images is None:\n            raise ValueError(\"`images` are expected as arguments to a `Florence2Processor` instance.\")\n        if text is None:\n            logger.warning_once(\n                \"You are using Florence-2 without a text prompt.\"\n            )\n            text = \"\"\n\n        if isinstance(text, List) and isinstance(images, List):\n            if len(images) < len(text):\n                raise ValueError(\n                    f\"Received {len(images)} images for {len(text)} prompts. Each prompt should be associated with an image.\"\n                )\n        if _is_str_or_image(text):\n            text = [text]\n        elif isinstance(text, list) and _is_str_or_image(text[0]):\n            pass\n\n        pixel_values = self.image_processor(\n            images,\n            do_resize=do_resize,\n            do_normalize=do_normalize,\n            return_tensors=return_tensors,\n            image_mean=image_mean,\n            image_std=image_std,\n            input_data_format=input_data_format,\n            data_format=data_format,\n            resample=resample,\n            do_convert_rgb=do_convert_rgb,\n        )[\"pixel_values\"]\n\n        if max_length is not None:\n            max_length -= self.image_seq_length  # max_length has to account for the image tokens\n\n        text = self._construct_prompts(text)\n\n        inputs = self.tokenizer(\n            text,\n            return_tensors=return_tensors,\n            padding=padding,\n            max_length=max_length,\n            truncation=truncation,\n            return_token_type_ids=return_token_type_ids,\n        )\n\n        return_data = {**inputs, \"pixel_values\": pixel_values}\n\n        if return_token_type_ids:\n            labels = inputs[\"input_ids\"].masked_fill(inputs[\"token_type_ids\"] == 0, -100)\n            return_data.update({\"labels\": labels})\n        return BatchFeature(data=return_data)\n\n    # Copied from transformers.models.clip.processing_clip.CLIPProcessor.batch_decode with CLIP->Florence2\n    def batch_decode(self, *args, **kwargs):\n        \"\"\"\n        This method forwards all its arguments to BartTokenizerFast's [`~PreTrainedTokenizer.batch_decode`]. Please\n        refer to the docstring of this method for more information.\n        \"\"\"\n        return self.tokenizer.batch_decode(*args, **kwargs)\n\n    # Copied from transformers.models.clip.processing_clip.CLIPProcessor.decode with CLIP->Florence2\n    def decode(self, *args, **kwargs):\n        \"\"\"\n        This method forwards all its arguments to BartTokenizerFast's [`~PreTrainedTokenizer.decode`]. Please refer to\n        the docstring of this method for more information.\n        \"\"\"\n        return self.tokenizer.decode(*args, **kwargs)\n\n    @property\n    # Copied from transformers.models.clip.processing_clip.CLIPProcessor.model_input_names with CLIP->Florence2\n    def model_input_names(self):\n        tokenizer_input_names = self.tokenizer.model_input_names\n        image_processor_input_names = self.image_processor.model_input_names\n        return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))\n\n    def post_process_generation(self, text=None, sequence=None, transition_beam_score=None, task=None, image_size=None):\n        \"\"\"\n        Post-process the output of the model to each of the task outputs.\n\n        Args:\n            text (`str`): The text to post-process.\n            task (`str`): The task to post-process the text for.\n            image_size (`Tuple[int, int]`): The size of the image. height x width.\n        \"\"\"\n\n        task_answer_post_processing_type = self.tasks_answer_post_processing_type.get(task, 'pure_text')\n        task_answer = self.post_processor(\n            text=text,\n            sequence=sequence,\n            transition_beam_score=transition_beam_score,\n            image_size=image_size,\n            parse_tasks=task_answer_post_processing_type,\n        )[task_answer_post_processing_type]\n\n        if task_answer_post_processing_type == 'pure_text':\n            final_answer = task_answer\n            # remove the special tokens\n            final_answer = final_answer.replace('<s>', '').replace('</s>', '')\n        elif task_answer_post_processing_type in ['od', 'description_with_bboxes', 'bboxes']:\n            od_instances = task_answer\n            bboxes_od = [_od_instance['bbox'] for _od_instance in od_instances]\n            labels_od = [str(_od_instance['cat_name']) for _od_instance in od_instances]\n            final_answer = {'bboxes': bboxes_od, 'labels': labels_od}\n            if len(od_instances) and 'score' in od_instances[0]:\n                scores_od = [_od_instance['score'] for _od_instance in od_instances]\n                final_answer['scores'] = scores_od\n        elif task_answer_post_processing_type in ['ocr']:\n            bboxes = [_od_instance['quad_box'] for _od_instance in task_answer]\n            labels = [str(_od_instance['text']) for _od_instance in task_answer]\n            final_answer = {'quad_boxes': bboxes, 'labels': labels}\n        elif task_answer_post_processing_type in ['phrase_grounding']:\n            bboxes = []\n            labels = []\n            for _grounded_phrase in task_answer:\n                for _bbox in _grounded_phrase['bbox']:\n                    bboxes.append(_bbox)\n                    labels.append(_grounded_phrase['cat_name'])\n            final_answer = {'bboxes': bboxes, 'labels': labels}\n        elif task_answer_post_processing_type in ['description_with_polygons', 'polygons']:\n            labels = []\n            polygons = []\n            for result in task_answer:\n                label = result['cat_name']\n                _polygons = result['polygons']\n                labels.append(label)\n                polygons.append(_polygons)\n            final_answer = {'polygons': polygons, 'labels': labels}\n        elif task_answer_post_processing_type in ['description_with_bboxes_or_polygons']:\n            bboxes = []\n            bboxes_labels = []\n            polygons = []\n            polygons_labels = []\n            for result in task_answer:\n                label = result['cat_name']\n                if 'polygons' in result:\n                    _polygons = result['polygons']\n                    polygons.append(_polygons)\n                    polygons_labels.append(label)\n                else:\n                    _bbox = result['bbox']\n                    bboxes.append(_bbox)\n                    bboxes_labels.append(label)\n            final_answer = {'bboxes': bboxes, 'bboxes_labels': bboxes_labels, 'polygons': polygons, 'polygons_labels': polygons_labels}\n        else:\n            raise ValueError('Unknown task answer post processing type: {}'.format(task_answer_post_processing_type))\n\n        final_answer = {\n            task: final_answer}\n        return final_answer \n\nclass BoxQuantizer(object):\n    def __init__(self, mode, bins):\n        self.mode = mode\n        self.bins = bins\n\n    def quantize(self, boxes: torch.Tensor, size):\n        bins_w, bins_h = self.bins  # Quantization bins.\n        size_w, size_h = size       # Original image size.\n        size_per_bin_w = size_w / bins_w\n        size_per_bin_h = size_h / bins_h\n        xmin, ymin, xmax, ymax = boxes.split(1, dim=-1)  # Shape: 4 * [N, 1].\n\n        if self.mode == 'floor':\n            quantized_xmin = (\n                xmin / size_per_bin_w).floor().clamp(0, bins_w - 1)\n            quantized_ymin = (\n                ymin / size_per_bin_h).floor().clamp(0, bins_h - 1)\n            quantized_xmax = (\n                xmax / size_per_bin_w).floor().clamp(0, bins_w - 1)\n            quantized_ymax = (\n                ymax / size_per_bin_h).floor().clamp(0, bins_h - 1)\n\n        elif self.mode == 'round':\n            raise NotImplementedError()\n\n        else:\n            raise ValueError('Incorrect quantization type.')\n\n        quantized_boxes = torch.cat(\n            (quantized_xmin, quantized_ymin, quantized_xmax, quantized_ymax), dim=-1\n        ).int()\n\n        return quantized_boxes\n\n    def dequantize(self, boxes: torch.Tensor, size):\n        bins_w, bins_h = self.bins  # Quantization bins.\n        size_w, size_h = size       # Original image size.\n        size_per_bin_w = size_w / bins_w\n        size_per_bin_h = size_h / bins_h\n        xmin, ymin, xmax, ymax = boxes.split(1, dim=-1)  # Shape: 4 * [N, 1].\n\n        if self.mode == 'floor':\n            # Add 0.5 to use the center position of the bin as the coordinate.\n            dequantized_xmin = (xmin + 0.5) * size_per_bin_w\n            dequantized_ymin = (ymin + 0.5) * size_per_bin_h\n            dequantized_xmax = (xmax + 0.5) * size_per_bin_w\n            dequantized_ymax = (ymax + 0.5) * size_per_bin_h\n\n        elif self.mode == 'round':\n            raise NotImplementedError()\n\n        else:\n            raise ValueError('Incorrect quantization type.')\n\n        dequantized_boxes = torch.cat(\n            (dequantized_xmin, dequantized_ymin,\n             dequantized_xmax, dequantized_ymax), dim=-1\n        )\n\n        return dequantized_boxes\n\n\nclass CoordinatesQuantizer(object):\n    \"\"\"\n    Quantize coornidates (Nx2)\n    \"\"\"\n\n    def __init__(self, mode, bins):\n        self.mode = mode\n        self.bins = bins\n\n    def quantize(self, coordinates: torch.Tensor, size):\n        bins_w, bins_h = self.bins  # Quantization bins.\n        size_w, size_h = size       # Original image size.\n        size_per_bin_w = size_w / bins_w\n        size_per_bin_h = size_h / bins_h\n        assert coordinates.shape[-1] == 2, 'coordinates should be shape (N, 2)'\n        x, y = coordinates.split(1, dim=-1)  # Shape: 4 * [N, 1].\n\n        if self.mode == 'floor':\n            quantized_x = (x / size_per_bin_w).floor().clamp(0, bins_w - 1)\n            quantized_y = (y / size_per_bin_h).floor().clamp(0, bins_h - 1)\n\n        elif self.mode == 'round':\n            raise NotImplementedError()\n\n        else:\n            raise ValueError('Incorrect quantization type.')\n\n        quantized_coordinates = torch.cat(\n            (quantized_x, quantized_y), dim=-1\n        ).int()\n\n        return quantized_coordinates\n\n    def dequantize(self, coordinates: torch.Tensor, size):\n        bins_w, bins_h = self.bins  # Quantization bins.\n        size_w, size_h = size       # Original image size.\n        size_per_bin_w = size_w / bins_w\n        size_per_bin_h = size_h / bins_h\n        assert coordinates.shape[-1] == 2, 'coordinates should be shape (N, 2)'\n        x, y = coordinates.split(1, dim=-1)  # Shape: 4 * [N, 1].\n\n        if self.mode == 'floor':\n            # Add 0.5 to use the center position of the bin as the coordinate.\n            dequantized_x = (x + 0.5) * size_per_bin_w\n            dequantized_y = (y + 0.5) * size_per_bin_h\n\n        elif self.mode == 'round':\n            raise NotImplementedError()\n\n        else:\n            raise ValueError('Incorrect quantization type.')\n\n        dequantized_coordinates = torch.cat(\n            (dequantized_x, dequantized_y), dim=-1\n        )\n\n        return dequantized_coordinates\n\n\nclass Florence2PostProcesser(object):\n    r\"\"\"\n    Florence-2 post process for converting text prediction to various tasks results. \n\n    Args:\n        config: A dict of configs.\n        tokenizer: A tokenizer for decoding text to spans.\n        sample config:\n            UNIFIED_POST_PROCESS:\n                # commom configs\n                NUM_BBOX_HEIGHT_BINS: 1000\n                NUM_BBOX_WIDTH_BINS: 1000\n                COORDINATES_HEIGHT_BINS: 1000\n                COORDINATES_WIDTH_BINS: 1000\n                # task specific configs, override the common configs\n                PRASE_TASKS:\n                    - TASK_NAME: 'video_dense_caption'\n                      PATTERN: 'r<time_(\\d+)><time_(\\d+)>([a-zA-Z0-9 ]+)'\n                      SCORE_MODE: 'avg_cat_name_scores'\n                      NUM_BINS: 100\n                    - TASK_NAME: 'od'\n                      PATTERN: 'r<loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)>([a-zA-Z0-9 ]+)'\n                      SCORE_MODE: 'avg_cat_name_scores'\n\n    Returns:\n        parsed_dict (dict): A dict of parsed results.\n    \"\"\"\n    def __init__(\n        self,\n        tokenizer=None\n    ):\n        parse_tasks = []\n        parse_task_configs = {}\n        config = self._create_default_config()\n        for task in config['PARSE_TASKS']:\n            parse_tasks.append(task['TASK_NAME'])\n            parse_task_configs[task['TASK_NAME']] = task\n\n        self.config = config\n        self.parse_tasks = parse_tasks\n        self.parse_tasks_configs = parse_task_configs\n\n        self.tokenizer =  tokenizer\n        if self.tokenizer is not None:\n            self.all_special_tokens = set(self.tokenizer.all_special_tokens)\n\n        self.init_quantizers()\n        self.black_list_of_phrase_grounding = self._create_black_list_of_phrase_grounding()\n\n    def _create_black_list_of_phrase_grounding(self):\n        black_list = {}\n\n        if 'phrase_grounding' in self.parse_tasks and self.parse_tasks_configs['phrase_grounding']['FILTER_BY_BLACK_LIST']:\n            black_list =  set(\n                ['it', 'I', 'me', 'mine',\n                 'you', 'your', 'yours',\n                 'he', 'him', 'his',\n                 'she', 'her', 'hers',\n                 'they', 'them', 'their', 'theirs',\n                 'one', 'oneself',\n                 'we', 'us', 'our', 'ours',\n                 'you', 'your', 'yours',\n                 'they', 'them', 'their', 'theirs',\n                 'mine', 'yours', 'his', 'hers', 'its',\n                 'ours', 'yours', 'theirs',\n                 'myself', 'yourself', 'himself', 'herself', 'itself',\n                 'ourselves', 'yourselves', 'themselves',\n                 'this', 'that',\n                 'these', 'those',\n                 'who', 'whom', 'whose', 'which', 'what',\n                 'who', 'whom', 'whose', 'which', 'that',\n                 'all', 'another', 'any', 'anybody', 'anyone', 'anything',\n                 'each', 'everybody', 'everyone', 'everything',\n                 'few', 'many', 'nobody', 'none', 'one', 'several',\n                 'some', 'somebody', 'someone', 'something',\n                 'each other', 'one another',\n                 'myself', 'yourself', 'himself', 'herself', 'itself',\n                 'ourselves', 'yourselves', 'themselves',\n                 'the image', 'image', 'images', 'the', 'a', 'an', 'a group',\n                 'other objects', 'lots', 'a set',\n                 ]\n            )\n\n        return black_list\n    \n    def _create_default_config(self):\n        config = {\n            'NUM_BBOX_HEIGHT_BINS': 1000,\n            'NUM_BBOX_WIDTH_BINS': 1000,\n            'BOX_QUANTIZATION_MODE': 'floor',\n            'COORDINATES_HEIGHT_BINS': 1000,\n            'COORDINATES_WIDTH_BINS': 1000,\n            'COORDINATES_QUANTIZATION_MODE': 'floor',\n            'PARSE_TASKS': [\n                {\n                    'TASK_NAME': 'od',\n                    'PATTERN': r'([a-zA-Z0-9 ]+)<loc_(\\\\d+)><loc_(\\\\d+)><loc_(\\\\d+)><loc_(\\\\d+)>',\n                    'SCORE_MODE': 'avg_loc_scores'\n                },\n                {\n                    'TASK_NAME': 'ocr',\n                    'PATTERN':  r'(.+?)<loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)>',\n                    'AREA_THRESHOLD': 0.00\n                },\n                {\n                    'TASK_NAME': 'phrase_grounding',\n                    'FILTER_BY_BLACK_LIST': True\n                },\n                {\n                    'TASK_NAME': 'pure_text',\n                },\n                {\n                    'TASK_NAME': 'description_with_bboxes',\n                    'SCORE_MODE': 'avg_loc_scores'\n                },\n                {\n                    'TASK_NAME': 'description_with_polygons',\n                },\n                {\n                    'TASK_NAME': 'polygons',\n                },\n                {\n                    'TASK_NAME': 'bboxes',\n                },\n                {\n                    'TASK_NAME': 'description_with_bboxes_or_polygons',\n                }\n            ]\n        }\n\n        return config\n\n    def init_quantizers(self):\n        # we have box_quantizer (od, grounding) and coordinates_quantizer (ocr, referring_segmentation)\n        num_bbox_height_bins = self.config.get('NUM_BBOX_HEIGHT_BINS', 1000)\n        num_bbox_width_bins = self.config.get('NUM_BBOX_WIDTH_BINS', 1000)\n        box_quantization_mode = self.config.get('BOX_QUANTIZATION_MODE', 'floor')\n        self.box_quantizer = BoxQuantizer(\n            box_quantization_mode,\n            (num_bbox_width_bins, num_bbox_height_bins),\n        )\n        \n        num_bbox_height_bins = self.config['COORDINATES_HEIGHT_BINS'] if 'COORDINATES_HEIGHT_BINS' in self.config else self.config.get('NUM_BBOX_HEIGHT_BINS', 1000)\n        num_bbox_width_bins = self.config['COORDINATES_WIDTH_BINS'] if 'COORDINATES_WIDTH_BINS' in self.config else self.config.get('NUM_BBOX_WIDTH_BINS', 1000)\n        box_quantization_mode = self.config.get('COORDINATES_QUANTIZATION_MODE') if 'COORDINATES_QUANTIZATION_MODE' in self.config else self.config.get('BOX_QUANTIZATION_MODE', 'floor')\n        self.coordinates_quantizer = CoordinatesQuantizer(\n            box_quantization_mode,\n            (num_bbox_width_bins, num_bbox_height_bins),\n        )\n\n    def decode_with_spans(self, tokenizer, token_ids):\n        filtered_tokens = tokenizer.convert_ids_to_tokens(\n            token_ids, skip_special_tokens=False)\n        assert len(filtered_tokens) == len(token_ids)\n        sub_texts = []\n        for token in filtered_tokens:\n            if token in self.all_special_tokens:\n                sub_texts.append(token)\n            else:\n                if isinstance(tokenizer, (BartTokenizer, BartTokenizerFast)):\n                    sub_text = tokenizer.convert_tokens_to_string([token])\n                else:\n                    raise ValueError(f'type {type(tokenizer)} not supported')\n                sub_texts.append(sub_text)\n\n        text = ''\n        spans = []\n        for sub_text in sub_texts:\n            span = (len(text), len(text) + len(sub_text))  # [start index, end index).\n            text += sub_text\n            spans.append(span)\n        return text, spans\n\n    def parse_od_from_text_and_spans(\n        self,\n        text,\n        pattern,\n        image_size,\n        phrase_centric=False\n    ):\n        parsed = list(re.finditer(pattern, text))\n\n        instances = []\n        for i in range(len(parsed)):\n            # Prepare instance.\n            instance = {}\n\n            if phrase_centric:\n                bbox_bins = [int(parsed[i].group(j)) for j in range(2, 6)]\n            else:\n                bbox_bins = [int(parsed[i].group(j)) for j in range(1, 5)]\n            instance['bbox'] = self.box_quantizer.dequantize(\n                boxes=torch.tensor(bbox_bins),\n                size=image_size\n            ).tolist()  \n\n            if phrase_centric:\n                instance['cat_name'] = parsed[i].group(1).lower().strip()\n            else:\n                instance['cat_name'] = parsed[i].group(5).lower().strip()\n            instances.append(instance)\n\n        return instances\n\n    def parse_ocr_from_text_and_spans(self, \n                                     text, \n                                     pattern, \n                                     image_size,\n                                     area_threshold=-1.0,\n        ):\n        bboxes = []\n        labels = []\n        text = text.replace('<s>', '')\n        # ocr with regions\n        parsed = re.findall(pattern, text)\n        instances = []\n        image_width, image_height = image_size\n\n        for ocr_line in parsed:\n            ocr_content = ocr_line[0]\n            quad_box = ocr_line[1:]\n            quad_box = [int(i) for i in quad_box]\n            quad_box = self.coordinates_quantizer.dequantize(\n                torch.tensor(np.array(quad_box).reshape(-1, 2)),\n                size=image_size\n            ).reshape(-1).tolist()\n\n            if area_threshold > 0:\n                x_coords = [i for i in quad_box[0::2]]\n                y_coords = [i for i in quad_box[1::2]]\n\n                # apply the Shoelace formula\n                area = 0.5 * abs(sum(x_coords[i] * y_coords[i + 1] - x_coords[i + 1] * y_coords[i] for i in range(4 - 1)))\n\n                if area < (image_width * image_height) * area_threshold:\n                    continue\n\n            bboxes.append(quad_box)\n            labels.append(ocr_content)\n            instances.append({\n                'quad_box': quad_box,\n                'text': ocr_content,\n            })\n        return instances\n\n    def parse_phrase_grounding_from_text_and_spans(self, text, pattern, image_size):\n        # ignore <s> </s> and <pad>\n        cur_span = 0\n        if text.startswith('<s>'):   \n            cur_span += 3\n\n        text = text.replace('<s>', '')\n        text = text.replace('</s>', '')\n        text = text.replace('<pad>', '')\n\n        pattern = r\"([^<]+(?:<loc_\\d+>){4,})\"\n        phrases = re.findall(pattern, text)\n    \n        # pattern should be text pattern and od pattern\n        pattern = r'^\\s*(.*?)(?=<od>|</od>|<box>|</box>|<bbox>|</bbox>|<loc_)'\n        box_pattern = r'<loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)>'\n\n        instances = []\n        for pharse_text in phrases:\n            phrase_text_strip = pharse_text.replace('<ground>', '', 1)\n            phrase_text_strip = pharse_text.replace('<obj>', '', 1)\n\n            if phrase_text_strip == '':\n                cur_span += len(pharse_text)\n                continue\n\n            # Prepare instance.\n            instance = {}\n\n            # parse phrase, get string \n            phrase = re.search(pattern, phrase_text_strip)\n            if phrase is None:\n                cur_span += len(pharse_text)\n                continue\n\n            # parse bboxes by box_pattern\n            bboxes_parsed = list(re.finditer(box_pattern, pharse_text))\n            if len(bboxes_parsed) == 0:\n                cur_span += len(pharse_text)\n                continue\n\n            phrase = phrase.group()\n            # remove leading and trailing spaces\n            phrase = phrase.strip()\n\n            if phrase in self.black_list_of_phrase_grounding:\n                cur_span += len(pharse_text)\n                continue\n\n            # a list of list \n            bbox_bins = [[int(_bboxes_parsed.group(j)) for j in range(1, 5)] for _bboxes_parsed in bboxes_parsed]\n            instance['bbox'] = self.box_quantizer.dequantize(\n                boxes=torch.tensor(bbox_bins),\n                size=image_size\n            ).tolist()  \n\n            # exclude non-ascii characters\n            phrase = phrase.encode('ascii',errors='ignore').decode('ascii')\n            instance['cat_name'] = phrase\n\n            instances.append(instance)\n\n        return instances\n\n    def parse_description_with_bboxes_from_text_and_spans(\n            self, \n            text, \n            spans=None,\n            scores=None,\n            score_mode=None,\n            pattern=None, \n            image_size=None, \n            allow_empty_phrase=False\n        ):\n        def find_matched_token_indices(cur_span, token_spans):\n            inds = []\n            for i, token_span in enumerate(token_spans):\n                if not (token_span[1] <= cur_span[0] or token_span[0] >= cur_span[1]):\n                    inds.append(i)\n            return inds\n\n        cur_span = 0\n        if text.startswith('<s>'):   \n            cur_span += 3\n\n        text = text.replace('<s>', '')\n        text = text.replace('</s>', '')\n        text = text.replace('<pad>', '')\n\n        if allow_empty_phrase:\n            pattern = rf\"(?:(?:<loc_\\d+>){{4,}})\"\n        else:\n            pattern = r\"([^<]+(?:<loc_\\d+>){4,})\"\n        phrases = re.findall(pattern, text)\n    \n        # pattern should be text pattern and od pattern\n        pattern = r'^\\s*(.*?)(?=<od>|</od>|<box>|</box>|<bbox>|</bbox>|<loc_)'\n        box_pattern = r'<loc_(\\d+)><loc_(\\d+)><loc_(\\d+)><loc_(\\d+)>'\n\n        instances = []\n        for pharse_text in phrases:\n            phrase_text_strip = pharse_text.replace('<ground>', '', 1)\n            phrase_text_strip = pharse_text.replace('<obj>', '', 1)\n\n            if phrase_text_strip == '' and not allow_empty_phrase:\n                cur_span += len(pharse_text)\n                continue\n\n            # parse phrase, get string \n            phrase = re.search(pattern, phrase_text_strip)\n            if phrase is None:\n                cur_span += len(pharse_text)\n                continue\n\n            phrase_span = phrase.span()\n            phrase = phrase.group()\n            # remove leading and trailing spaces\n            phrase = phrase.strip()\n\n            # parse bboxes by box_pattern\n            bboxes_parsed = list(re.finditer(box_pattern, pharse_text))\n            if len(bboxes_parsed) == 0:\n                cur_span += len(pharse_text)\n                continue\n\n            # a list of list \n            bbox_bins = [[int(_bboxes_parsed.group(j)) for j in range(1, 5)] for _bboxes_parsed in bboxes_parsed]\n\n            bboxes = self.box_quantizer.dequantize(\n                boxes=torch.tensor(bbox_bins),\n                size=image_size\n            ).tolist()  \n\n            if score_mode == 'avg_loc_scores':\n                if spans is None or scores is None:\n                    all_scores = None\n                else:\n                    bbox_end_spans = [_bboxes_parsed.span(0) for _bboxes_parsed in bboxes_parsed]\n                    all_scores = []\n                    for _spans in bbox_end_spans:\n                        token_inds = find_matched_token_indices((_spans[0] + cur_span, _spans[1]+ cur_span), spans)\n                        loc_scores = [scores[token_i] for token_i in token_inds]\n                        score = sum(loc_scores) / len(loc_scores)\n                        all_scores.append(score)\n            elif score_mode == 'avg_cat_name_scores': \n                if spans is None or scores is None:\n                    all_scores = None\n                else:\n                    cat_name_token_inds = find_matched_token_indices((phrase_span[0] + cur_span, phrase_span[1]+cur_span), spans)\n                    cat_name_scores = [scores[token_i] for token_i in cat_name_token_inds]\n                    score = sum(cat_name_scores) / len(cat_name_scores)\n                    all_scores = [score] * len(bboxes)\n            elif score_mode is None:\n                all_scores = None\n            else:\n                raise ValueError('Unknown score mode: {}'.format(score_mode))\n\n            phrase = phrase.encode('ascii',errors='ignore').decode('ascii')\n            for _idx, _bboxes in enumerate(bboxes):\n                # Prepare instance.\n                instance = {}\n                instance['bbox'] = _bboxes\n                # exclude non-ascii characters\n                instance['cat_name'] = phrase\n                if all_scores is not None:\n                    instance['score'] = math.exp(all_scores[_idx])\n                instances.append(instance)\n            \n            cur_span += len(pharse_text)\n\n        return instances\n\n    def parse_description_with_polygons_from_text_and_spans(self, text, pattern, image_size, \n                                                            allow_empty_phrase=False,\n                                                            polygon_sep_token='<sep>',\n                                                            polygon_start_token='<poly>',\n                                                            polygon_end_token='</poly>',\n                                                            with_box_at_start=False,\n                                                            ):\n        \n        # ref_seg format: '<expression><x1><y1><x2><y2><><><sep><><><><>'\n        # ignore <s> </s> and <pad>\n\n        text = text.replace('<s>', '')\n        text = text.replace('</s>', '')\n        text = text.replace('<pad>', '')\n\n        if allow_empty_phrase:\n            pattern = rf\"(?:(?:<loc_\\d+>|{re.escape(polygon_sep_token)}|{re.escape(polygon_start_token)}|{re.escape(polygon_end_token)}){{4,}})\"\n        else:\n            # [^<]+: This part matches one or more characters that are not the < symbol. \n            # The ^ inside the square brackets [] is a negation, meaning it matches anything except <.\n            #\n            pattern = rf\"([^<]+(?:<loc_\\d+>|{re.escape(polygon_sep_token)}|{re.escape(polygon_start_token)}|{re.escape(polygon_end_token)}){{4,}})\"\n        phrases = re.findall(pattern, text)\n\n        phrase_string_pattern = r'^\\s*(.*?)(?=<od>|</od>|<box>|</box>|<bbox>|</bbox>|<loc_|<poly>)'\n        box_pattern =  rf'((?:<loc_\\d+>)+)(?:{re.escape(polygon_sep_token)}|$)'\n\n        # one polygons instance is separated by polygon_start_token and polygon_end_token\n        polygons_instance_pattern = rf'{re.escape(polygon_start_token)}(.*?){re.escape(polygon_end_token)}'\n    \n        instances = []\n        for phrase_text in phrases:\n\n            # exclude loc_\\d+>\n            # need to get span if want to include category score\n            phrase_text_strip = re.sub(r'^loc_\\d+>', '', phrase_text, count=1)\n\n            # phrase = phrase.replace('<poly>', '')\n            # phrase = phrase.replace('poly>', '')\n\n            if phrase_text_strip == '' and not allow_empty_phrase:\n                continue\n\n\n            # parse phrase, get string \n            phrase = re.search(phrase_string_pattern, phrase_text_strip)\n            if phrase is None:\n                continue\n            phrase = phrase.group()\n            # remove leading and trailing spaces\n            phrase = phrase.strip()\n\n            # parse bboxes by box_pattern\n\n            # split by polygon_start_token and polygon_end_token first using polygons_instance_pattern\n            if polygon_start_token in phrase_text and polygon_end_token in phrase_text:\n                polygons_instances_parsed = list(re.finditer(polygons_instance_pattern, phrase_text))\n            else:\n                polygons_instances_parsed = [phrase_text]\n\n            for _polygons_instances_parsed in polygons_instances_parsed:\n                # Prepare instance.\n                instance = {}\n\n                # polygons_parsed= list(re.finditer(box_pattern, phrase_text))\n                if isinstance(_polygons_instances_parsed, str): \n                    polygons_parsed= list(re.finditer(box_pattern, _polygons_instances_parsed))\n                else:\n                    polygons_parsed= list(re.finditer(box_pattern, _polygons_instances_parsed.group(1)))\n                if len(polygons_parsed) == 0:\n                    continue\n\n                # a list of list (polygon)\n                bbox = []\n                polygons = []\n                for _polygon_parsed in polygons_parsed:\n                    # group 1: whole <loc_\\d+>...</loc_\\d+>\n                    _polygon = _polygon_parsed.group(1)\n                    # parse into list of int\n                    _polygon = [int(_loc_parsed.group(1)) for _loc_parsed in re.finditer(r'<loc_(\\d+)>', _polygon)]\n                    if with_box_at_start and len(bbox) == 0:\n                        if len(_polygon) > 4:\n                            # no valid bbox prediction\n                            bbox = _polygon[:4]\n                            _polygon = _polygon[4:]\n                        else:\n                            bbox = [0, 0, 0, 0]\n                    # abandon last element if is not paired \n                    if len(_polygon) % 2 == 1:\n                        _polygon = _polygon[:-1]\n                    \n                    # reshape into (n, 2)\n                    _polygon = self.coordinates_quantizer.dequantize(\n                        torch.tensor(np.array(_polygon).reshape(-1, 2)),\n                        size=image_size\n                    ).reshape(-1).tolist()\n                    # reshape back\n                    polygons.append(_polygon)\n\n                instance['cat_name'] = phrase\n                instance['polygons'] = polygons\n                if len(bbox) != 0:\n                    instance['bbox'] = self.box_quantizer.dequantize(\n                        boxes=torch.tensor([bbox]),\n                        size=image_size\n                    ).tolist()[0]  \n\n                instances.append(instance)\n\n        return instances\n\n    def __call__(\n        self,\n        text=None,\n        sequence=None,\n        transition_beam_score=None,\n        image_size=None,\n        parse_tasks=None,\n    ):\n        \"\"\"\n        Args:\n            text: model outputs\n            image_size: (width, height)\n            parse_tasks: a list of tasks to parse, if None, parse all tasks.\n\n        \"\"\"\n        if parse_tasks is not None:\n            if isinstance(parse_tasks, str):\n                parse_tasks = [parse_tasks]\n            for _parse_task in parse_tasks:\n                assert _parse_task in self.parse_tasks, f'parse task {_parse_task} not supported'\n        \n        # sequence or text should be provided \n        assert sequence is not None or text is not None, 'sequence or text should be provided'\n        assert sequence is None or text is None, 'only one of sequence and text should be provided'\n\n        if sequence is not None:\n            sequence = sequence.tolist()[1:]\n            text, spans = self.decode_with_spans(self.tokenizer, sequence)\n            if transition_beam_score is not None:\n                transition_beam_score = transition_beam_score.tolist()\n                assert len(sequence) == len(transition_beam_score)\n        else:\n            spans = None\n            transition_beam_score = None\n\n        parsed_dict = {\n            'text': text\n        }\n\n        for task in self.parse_tasks:\n            if parse_tasks is not None and task not in parse_tasks:\n                continue\n\n            pattern = self.parse_tasks_configs[task].get('PATTERN', None)\n            score_mode = self.parse_tasks_configs[task].get('SCORE_MODE', None)\n\n            if task == 'ocr':\n                instances = self.parse_ocr_from_text_and_spans(\n                    text,\n                    pattern=pattern,\n                    image_size=image_size,\n                    area_threshold=self.parse_tasks_configs[task].get('AREA_THRESHOLD', 0.0),\n                )\n                parsed_dict['ocr'] = instances\n            elif task == 'phrase_grounding':\n                instances = self.parse_phrase_grounding_from_text_and_spans( \n                    text,\n                    pattern=pattern,\n                    image_size=image_size,\n                )\n                parsed_dict['phrase_grounding'] = instances\n            elif task == 'pure_text':\n                parsed_dict['pure_text'] = text \n            elif task == 'description_with_bboxes':\n                instances = self.parse_description_with_bboxes_from_text_and_spans( \n                    text,\n                    spans=spans,\n                    scores=transition_beam_score,\n                    score_mode=score_mode,\n                    pattern=pattern,\n                    image_size=image_size,\n                )\n                parsed_dict['description_with_bboxes'] = instances\n            elif task == 'description_with_polygons':\n                instances = self.parse_description_with_polygons_from_text_and_spans( \n                    text,\n                    pattern=pattern,\n                    image_size=image_size,\n                )\n                parsed_dict['description_with_polygons'] = instances\n            elif task == 'polygons':\n                instances = self.parse_description_with_polygons_from_text_and_spans( \n                    text,\n                    pattern=pattern,\n                    image_size=image_size,\n                    allow_empty_phrase=True,\n                )\n                parsed_dict['polygons'] = instances\n            elif task == 'bboxes':\n                instances = self.parse_description_with_bboxes_from_text_and_spans( \n                    text,\n                    pattern=pattern,\n                    image_size=image_size,\n                    allow_empty_phrase=True,\n                )\n                parsed_dict['bboxes'] = instances\n            elif task == 'description_with_bboxes_or_polygons':\n                if '<poly>' in text:\n                    # only support either polygons or bboxes, not both at the same time\n                    instances = self.parse_description_with_polygons_from_text_and_spans( \n                        text,\n                        pattern=pattern,\n                        image_size=image_size,\n                    )\n                else:\n                    instances = self.parse_description_with_bboxes_from_text_and_spans( \n                        text,\n                        pattern=pattern,\n                        image_size=image_size,\n                    )\n                parsed_dict['description_with_bboxes_or_polygons'] = instances\n            else:\n                raise ValueError(\"task {} is not supported\".format(task))\n\n        return parsed_dict"
  },
  {
    "path": "eval/grounded_sam/florence2/tokenizer.json",
    "content": "{\"version\":\"1.0\",\"truncation\":null,\"padding\":null,\"added_tokens\":[{\"id\":0,\"special\":true,\"content\":\"<s>\",\"single_word\":false,\"lstrip\":false,\"rstrip\":false,\"normalized\":true},{\"id\":1,\"special\":true,\"content\":\"<pad>\",\"single_word\":false,\"lstrip\":false,\"rstrip\":false,\"normalized\":true},{\"id\":2,\"special\":true,\"content\":\"</s>\",\"single_word\":false,\"lstrip\":false,\"rstrip\":false,\"normalized\":true},{\"id\":3,\"special\":true,\"content\":\"<unk>\",\"single_word\":false,\"lstrip\":false,\"rstrip\":false,\"normalized\":true},{\"id\":50264,\"special\":true,\"content\":\"<mask>\",\"single_word\":false,\"lstrip\":true,\"rstrip\":false,\"normalized\":true}],\"normalizer\":null,\"pre_tokenizer\":{\"type\":\"ByteLevel\",\"add_prefix_space\":false,\"trim_offsets\":true},\"post_processor\":{\"type\":\"RobertaProcessing\",\"sep\":[\"</s>\",2],\"cls\":[\"<s>\",0],\"trim_offsets\":true,\"add_prefix_space\":false},\"decoder\":{\"type\":\"ByteLevel\",\"add_prefix_space\":true,\"trim_offsets\":true},\"model\":{\"dropout\":null,\"unk_token\":null,\"continuing_subword_prefix\":\"\",\"end_of_word_suffix\":\"\",\"fuse_unk\":false,\"vocab\":{\"<s>\":0,\"<pad>\":1,\"</s>\":2,\"<unk>\":3,\".\":4,\"Ġthe\":5,\",\":6,\"Ġto\":7,\"Ġand\":8,\"Ġof\":9,\"Ġa\":10,\"Ġin\":11,\"-\":12,\"Ġfor\":13,\"Ġthat\":14,\"Ġon\":15,\"Ġis\":16,\"âĢ\":17,\"'s\":18,\"Ġwith\":19,\"ĠThe\":20,\"Ġwas\":21,\"Ġ\\\"\":22,\"Ġat\":23,\"Ġit\":24,\"Ġas\":25,\"Ġsaid\":26,\"Ļ\":27,\"Ġbe\":28,\"s\":29,\"Ġby\":30,\"Ġfrom\":31,\"Ġare\":32,\"Ġhave\":33,\"Ġhas\":34,\":\":35,\"Ġ(\":36,\"Ġhe\":37,\"ĠI\":38,\"Ġhis\":39,\"Ġwill\":40,\"Ġan\":41,\"Ġthis\":42,\")\":43,\"ĠâĢ\":44,\"Ġnot\":45,\"Ŀ\":46,\"Ġyou\":47,\"ľ\":48,\"Ġtheir\":49,\"Ġor\":50,\"Ġthey\":51,\"Ġwe\":52,\"Ġbut\":53,\"Ġwho\":54,\"Ġmore\":55,\"Ġhad\":56,\"Ġbeen\":57,\"Ġwere\":58,\"Ġabout\":59,\",\\\"\":60,\"Ġwhich\":61,\"Ġup\":62,\"Ġits\":63,\"Ġcan\":64,\"Ġone\":65,\"Ġout\":66,\"Ġalso\":67,\"Ġ$\":68,\"Ġher\":69,\"Ġall\":70,\"Ġafter\":71,\".\\\"\":72,\"/\":73,\"Ġwould\":74,\"'t\":75,\"Ġyear\":76,\"Ġwhen\":77,\"Ġfirst\":78,\"Ġshe\":79,\"Ġtwo\":80,\"Ġover\":81,\"Ġpeople\":82,\"ĠA\":83,\"Ġour\":84,\"ĠIt\":85,\"Ġtime\":86,\"Ġthan\":87,\"Ġinto\":88,\"Ġthere\":89,\"t\":90,\"ĠHe\":91,\"Ġnew\":92,\"ĠâĢĶ\":93,\"Ġlast\":94,\"Ġjust\":95,\"ĠIn\":96,\"Ġother\":97,\"Ġso\":98,\"Ġwhat\":99,\"I\":100,\"Ġlike\":101,\"a\":102,\"Ġsome\":103,\"S\":104,\"Ã«\":105,\"Ġthem\":106,\"Ġyears\":107,\"'\":108,\"Ġdo\":109,\"Ġyour\":110,\"Ġ-\":111,\"Ġ1\":112,\"\\\"\":113,\"Ġif\":114,\"Ġcould\":115,\"?\":116,\"Ġno\":117,\"i\":118,\"m\":119,\"Ġget\":120,\"ĠU\":121,\"Ġnow\":122,\"Ġhim\":123,\"Ġback\":124,\"ĠBut\":125,\"ĠâĢĵ\":126,\"Ġmy\":127,\"Ġ'\":128,\"Ġonly\":129,\"Ġthree\":130,\";\":131,\"Ġ2\":132,\"The\":133,\"1\":134,\"Ġpercent\":135,\"Ġagainst\":136,\"Ġbefore\":137,\"Ġcompany\":138,\"o\":139,\"ĠTrump\":140,\"Ġhow\":141,\"Ġbecause\":142,\"Ġany\":143,\"Ġmost\":144,\"Ġbeing\":145,\"Ġmake\":146,\"Ġwhere\":147,\"Ġduring\":148,\"Ġthrough\":149,\"Ġwhile\":150,\"000\":151,\"ĠThis\":152,\"Ġmillion\":153,\"ing\":154,\"Ġ3\":155,\"Ġmade\":156,\"Ġwell\":157,\"Ġ10\":158,\"Ġdown\":159,\"Ġoff\":160,\"Ġsays\":161,\"Ġme\":162,\"ĠB\":163,\"Ġgoing\":164,\"Ġteam\":165,\"ĠWe\":166,\"Ġthose\":167,\"Ġgovernment\":168,\"Ġway\":169,\"We\":170,\"Ġmany\":171,\"Ġthen\":172,\"Ġwork\":173,\"Ġtold\":174,\"com\":175,\"2\":176,\"Ġgame\":177,\"ĠAnd\":178,\"in\":179,\"year\":180,\"Ġp\":181,\"Ġvery\":182,\"Ġday\":183,\"Ġhome\":184,\"Ġtake\":185,\"Ġweek\":186,\"Ġsince\":187,\"ĠNew\":188,\"Ġmay\":189,\"Ġeven\":190,\"Ġseason\":191,\"Ġsee\":192,\"Ġ2017\":193,\"Ġstate\":194,\"Ġ5\":195,\"ed\":196,\"Ġshould\":197,\"Ġaround\":198,\"Ġ2018\":199,\"Ġsecond\":200,\"Ġus\":201,\"Ġstill\":202,\"Ġmuch\":203,\"Ġ4\":204,\"Ġgood\":205,\"Ġthink\":206,\"%\":207,\"ĠS\":208,\"Ġthese\":209,\"Ġmarket\":210,\"ĠD\":211,\"th\":212,\"Ġgo\":213,\"'re\":214,\"Ġsuch\":215,\"Ġknow\":216,\"Ġincluding\":217,\"Ġdon\":218,\"y\":219,\"Ġnext\":220,\"ĠP\":221,\"Ġdid\":222,\"Ġunder\":223,\"Ġsay\":224,\"en\":225,\"ĠL\":226,\"Ġbetween\":227,\"Ġper\":228,\"ĠK\":229,\"ĠC\":230,\"Ġ6\":231,\"Ġworld\":232,\"Ġpart\":233,\"ĠN\":234,\"Ġright\":235,\"Ġwant\":236,\"Ġfour\":237,\"),\":238,\"Ġhigh\":239,\"Ġneed\":240,\"re\":241,\"e\":242,\"It\":243,\"Ġhelp\":244,\"5\":245,\"3\":246,\"Ġcountry\":247,\"ĠR\":248,\"Ġpolice\":249,\"A\":250,\"Ġlong\":251,\"ĠThey\":252,\"Ġend\":253,\"er\":254,\"ĠT\":255,\"ĠM\":256,\"u\":257,\"Ġboth\":258,\"Ġhere\":259,\"an\":260,\"on\":261,\"Ġ7\":262,\"Ġde\":263,\"ĠShe\":264,\"Ġbusiness\":265,\"Ġreport\":266,\"j\":267,\"ers\":268,\"Ġreally\":269,\"ĠPresident\":270,\"ar\":271,\"ĠG\":272,\"ĠFriday\":273,\"ĠF\":274,\"Ġbest\":275,\"Ġsame\":276,\"Ġanother\":277,\"Ġset\":278,\"old\":279,\"ĠThat\":280,\"as\":281,\"n\":282,\"Ġcome\":283,\"Ġfamily\":284,\"Ġpublic\":285,\"ĠFor\":286,\"ĠAs\":287,\"0\":288,\"ĠH\":289,\"Ġ8\":290,\"Ġ20\":291,\"Ġfive\":292,\"es\":293,\"ĠTuesday\":294,\"Ġn\":295,\"ĠThursday\":296,\"Ġquarter\":297,\"h\":298,\"Ġtop\":299,\"Ġgot\":300,\"Ġlife\":301,\"ĠMonday\":302,\"Ġfound\":303,\"Ġuse\":304,\"ĠW\":305,\"4\":306,\"ĠWednesday\":307,\"Ġown\":308,\"Ġaccording\":309,\"Ġplay\":310,\"Ġshow\":311,\"ĠSt\":312,\"Ġman\":313,\"Ġleft\":314,\"ĠUnited\":315,\"Ġ12\":316,\"Ġplace\":317,\"ĠIf\":318,\"Ġlot\":319,\"Ġformer\":320,\"Ġ0\":321,\").\":322,\"Ġsupport\":323,\"ie\":324,\"Ġbillion\":325,\"Ġt\":326,\"Ġshares\":327,\"!\":328,\"z\":329,\"k\":330,\"ĠState\":331,\"Ġpoints\":332,\"Ġgroup\":333,\"Ġschool\":334,\"Ġinformation\":335,\"Ġ2016\":336,\"al\":337,\"r\":338,\"Ġwin\":339,\"Ġnews\":340,\"Ġused\":341,\"Ġput\":342,\"Ġcity\":343,\"ĠJ\":344,\"ĠThere\":345,\"Ġnumber\":346,\"C\":347,\"'ve\":348,\"Ġeach\":349,\"Ġtoo\":350,\"Ġwon\":351,\"ly\":352,\"Ġmonth\":353,\"is\":354,\"Ġadded\":355,\"Ġlook\":356,\"Ġbetter\":357,\"Ġevery\":358,\"Ġ&\":359,\"Ġdays\":360,\"Ġ9\":361,\"Ġtook\":362,\"Ġnight\":363,\"Ġe\":364,\"Ġ11\":365,\"os\":366,\"Ġfew\":367,\"or\":368,\"ĠNorth\":369,\"ĠYou\":370,\"Ġthird\":371,\"Ġgreat\":372,\"Ġcalled\":373,\"ĠOn\":374,\"Ġpast\":375,\"Ġcame\":376,\"Ġmonths\":377,\"ĠSaturday\":378,\"Ġ15\":379,\"Ġbig\":380,\"ĠE\":381,\"ĠUS\":382,\"Ġthings\":383,\"ĠO\":384,\"Ġd\":385,\"Ġstart\":386,\"B\":387,\"Ġstock\":388,\"Ġ30\":389,\"Ġwomen\":390,\"ĠSouth\":391,\"ĠMay\":392,\"Ġnever\":393,\"Ġpresident\":394,\"ĠSunday\":395,\"Ġwithout\":396,\"man\":397,\"8\":398,\"Ġdidn\":399,\"Ġlocal\":400,\"6\":401,\"Ġsomething\":402,\"Ġcase\":403,\"ĠAll\":404,\"it\":405,\"7\":406,\"ĠSo\":407,\"Ġchildren\":408,\"Ġaway\":409,\"Ġlittle\":410,\"Ġsix\":411,\"ĠCity\":412,\"ĠCounty\":413,\"Ġdata\":414,\"at\":415,\"Ġalready\":416,\"d\":417,\"Ġmoney\":418,\"Ġearly\":419,\"Ġacross\":420,\"Ġexpected\":421,\"Ġrun\":422,\"Ġlater\":423,\"am\":424,\"Ġprice\":425,\"Ġgames\":426,\"ĠMr\":427,\"b\":428,\"Ġmight\":429,\"Ġdifferent\":430,\"Ġreported\":431,\"Ġdeal\":432,\"Ġmedia\":433,\"Ġgrowth\":434,\"Ġcommunity\":435,\"ĠChina\":436,\"'m\":437,\"c\":438,\"Ġwent\":439,\"ĠNo\":440,\"Ġable\":441,\"Ġmaking\":442,\"Ġarea\":443,\"Ġfar\":444,\"Ġstatement\":445,\"ĠHouse\":446,\"Ġworking\":447,\"M\":448,\"Ġk\":449,\"Ġseen\":450,\"Ġcompanies\":451,\"Ġtoday\":452,\"Ġmembers\":453,\"Ġuntil\":454,\"Ġfull\":455,\"Ġagain\":456,\"Ġhalf\":457,\"Ġshare\":458,\"le\":459,\"Ġalways\":460,\"Ġcourt\":461,\"l\":462,\"and\":463,\"Ġchange\":464,\"Ġfind\":465,\"9\":466,\"Ġsystem\":467,\"ĠV\":468,\"ĠYork\":469,\"ĠAmerican\":470,\"Ġhead\":471,\"Ġplayers\":472,\"Ġdoes\":473,\"Ġhealth\":474,\"Ġm\":475,\"Ġpower\":476,\"Ġpoint\":477,\"Ġhit\":478,\"Ġ.\":479,\"Ġ--\":480,\"Ġfree\":481,\".,\":482,\"Ġlead\":483,\"Ġseveral\":484,\"Ġrecent\":485,\"Ġcall\":486,\"N\":487,\"Ġlaw\":488,\"Ġkeep\":489,\"Ġopen\":490,\"ĠNews\":491,\"Ġgive\":492,\"ia\":493,\"ĠMarch\":494,\"D\":495,\"ĠNational\":496,\"ĠAt\":497,\"Ġtimes\":498,\"Ġfuture\":499,\"R\":500,\"Ġ14\":501,\"ĠJune\":502,\"Ġofficials\":503,\"Ġ18\":504,\"Ġimportant\":505,\"f\":506,\"Ġfinal\":507,\"Ġ13\":508,\"ĠOne\":509,\"P\":510,\"Ġfollowing\":511,\"Ġcar\":512,\"Ġleast\":513,\"Ġwater\":514,\"Ġevent\":515,\"Ġline\":516,\"Ġmove\":517,\"Ġservices\":518,\"Ġhaving\":519,\"ĠWhen\":520,\"Ġstudents\":521,\"ĠPolice\":522,\"el\":523,\"Ġam\":524,\"ĠZ\":525,\"Ġside\":526,\"Ġstory\":527,\"Ġdue\":528,\"Ġmeeting\":529,\"K\":530,\"Ġmust\":531,\"ĠStates\":532,\"Ġlikely\":533,\"G\":534,\"Ġcontinue\":535,\"Ġago\":536,\"Ġparty\":537,\"Ġmajor\":538,\"Ġindustry\":539,\"Ġless\":540,\"30\":541,\"Ġun\":542,\"Ġhard\":543,\"Ġservice\":544,\"Ġ16\":545,\"Ġlooking\":546,\"Ġheld\":547,\"ve\":548,\"Ġwhether\":549,\"ĠJuly\":550,\"Ġtaken\":551,\"Ġalong\":552,\"Ġasked\":553,\"Ġstarted\":554,\"Ġbecome\":555,\"Ġforward\":556,\"Ġresearch\":557,\"Ġoffice\":558,\"Ġpolitical\":559,\"to\":560,\"Ġtogether\":561,\"Ġgetting\":562,\"Ġplan\":563,\"Ġ25\":564,\"T\":565,\"Ġamong\":566,\"Ġcoming\":567,\"Ġdecision\":568,\"Ġvideo\":569,\"Ġ2015\":570,\"g\":571,\"ĠAfter\":572,\"Ġsecurity\":573,\"L\":574,\"Ġcare\":575,\"Ġgiven\":576,\"Ġavailable\":577,\"âĢĶ\":578,\"Ġs\":579,\"ĠWest\":580,\"'ll\":581,\"Ġpay\":582,\"Ġnear\":583,\"Ġsaying\":584,\"Ġannounced\":585,\"Ġprogram\":586,\"ĠApril\":587,\"Ġreal\":588,\"ĠUniversity\":589,\"ĠWith\":590,\"AP\":591,\"Ġsocial\":592,\"Ġclose\":593,\"et\":594,\"Ġcurrent\":595,\"Ġwhy\":596,\"F\":597,\"ĠTo\":598,\"ĠTwitter\":599,\"Ġthough\":600,\"Ġ17\":601,\"Ġtaking\":602,\"ĠInc\":603,\"Ġmen\":604,\"w\":605,\"Ġcomes\":606,\"ley\":607,\"Ġdoing\":608,\"Ġprocess\":609,\"ĠJohn\":610,\"ch\":611,\"00\":612,\"Ġfinancial\":613,\"Ġlow\":614,\"Ġenough\":615,\"ĠWhile\":616,\"Ġfurther\":617,\"Ġpost\":618,\"Ġfeel\":619,\"st\":620,\"Ġperson\":621,\"ĠFacebook\":622,\"ĠWorld\":623,\"Ġwithin\":624,\"ad\":625,\"Ġdone\":626,\"the\":627,\"Ġlate\":628,\"Ġtax\":629,\"Ġdoesn\":630,\"Ġthing\":631,\"Ġnational\":632,\"Ġjob\":633,\"Ġusing\":634,\"ĠHowever\":635,\"ic\":636,\"Ġcampaign\":637,\"Ġrecord\":638,\"Ġbehind\":639,\"://\":640,\"ĠDepartment\":641,\"p\":642,\"Ġothers\":643,\"ĠJanuary\":644,\"Ġorder\":645,\"Ġ[\":646,\"Ġsales\":647,\"Ġyet\":648,\"Ä\":649,\"Ġsmall\":650,\"Ġseries\":651,\"Ġface\":652,\"ĠWhat\":653,\"Ġ50\":654,\"Ġever\":655,\"Ġearlier\":656,\"Ġlove\":657,\"up\":658,\"Ġrights\":659,\"ĠAn\":660,\"ist\":661,\"Ġmorning\":662,\"ĠWashington\":663,\"Ġyoung\":664,\"Ġlatest\":665,\"ĠIndia\":666,\"Ġtrying\":667,\"Ġfire\":668,\"Ġled\":669,\"Ġstrong\":670,\"Ġreturn\":671,\"Ġlevel\":672,\"O\":673,\"Ġaverage\":674,\"Ġperiod\":675,\"Ġexperience\":676,\"ak\":677,\"Ġpossible\":678,\"Ġbelieve\":679,\"Ġinclude\":680,\"Ġoil\":681,\"Ġrecently\":682,\"Ġonce\":683,\"Ġknown\":684,\"Ġlost\":685,\"Ġsure\":686,\"us\":687,\"Ġweeks\":688,\"Ġfood\":689,\"Ġreports\":690,\"Ġrating\":691,\"ĠMinister\":692,\"Ġwoman\":693,\"Ġprovide\":694,\"Ġproject\":695,\"Ġissue\":696,\"Ġlive\":697,\"10\":698,\"Ġclear\":699,\"he\":700,\"Ġcost\":701,\"Ġplayed\":702,\"Ġreleased\":703,\"Ġcoach\":704,\"v\":705,\"Ġ24\":706,\"Ġseven\":707,\"Ġplans\":708,\"Ġdevelopment\":709,\"ur\":710,\"ĺ\":711,\"Ġincrease\":712,\"This\":713,\"Ġpolicy\":714,\"Ġcent\":715,\"Ġbased\":716,\"E\":717,\"il\":718,\"ĠDecember\":719,\"Ġglobal\":720,\"Ġtrade\":721,\"Ġhours\":722,\"Ġhigher\":723,\"Ġgoal\":724,\"H\":725,\"ĠAl\":726,\"Ġ100\":727,\"Ġminutes\":728,\"Ġelection\":729,\"ĠAmerica\":730,\"Ġrate\":731,\"ĠCh\":732,\"Ġ21\":733,\"...\":734,\"ĠWhite\":735,\"Ġdirector\":736,\"Ġposition\":737,\"Ġshot\":738,\"Ġlarge\":739,\"Ġc\":740,\"Ġb\":741,\"]\":742,\"Ġissues\":743,\"Ġdeath\":744,\"Ġbuilding\":745,\"Ġtotal\":746,\"Ġoften\":747,\"Ġv\":748,\"Ġcountries\":749,\"Ġhistory\":750,\"Ġoutside\":751,\"Ġfederal\":752,\"Ġ19\":753,\"Ġfact\":754,\"ĠHigh\":755,\"Ġcareer\":756,\"im\":757,\"Ġinternational\":758,\"ĠNovember\":759,\"Ġfront\":760,\"Ġkind\":761,\"Ġkey\":762,\"ra\":763,\"ĠSan\":764,\"Ġshort\":765,\"Ġname\":766,\"ĠAccording\":767,\"Ġcourse\":768,\"Ġre\":769,\"Ġwanted\":770,\"W\":771,\"ĠSeptember\":772,\"Ġinterest\":773,\"Ġrole\":774,\"Ġresults\":775,\"Ġeconomic\":776,\"Ġ2014\":777,\"Ġchance\":778,\"ĠOctober\":779,\"Ġspecial\":780,\"Ġofficial\":781,\"Ġneeds\":782,\"um\":783,\"Ġl\":784,\"Ġproducts\":785,\"Ġnon\":786,\"Ġ@\":787,\"ĠBank\":788,\"Ġahead\":789,\"Ġhouse\":790,\"U\":791,\"Ġboard\":792,\"Ġold\":793,\"Ġsaw\":794,\"Ġlower\":795,\"ĠEuropean\":796,\"Ġcontrol\":797,\"ĠRussia\":798,\"Ġeight\":799,\"Ġrelease\":800,\"Ġpotential\":801,\"Ġthought\":802,\"Ġinvestigation\":803,\"Ġonline\":804,\"based\":805,\"Ġtechnology\":806,\"ĠDonald\":807,\"id\":808,\"Ġbody\":809,\"Ġrisk\":810,\"ian\":811,\"Ġcapital\":812,\"Ġstaff\":813,\"Ġaction\":814,\"ĠLeague\":815,\"Ġplaying\":816,\"Ġmakes\":817,\"Ġalmost\":818,\"Ġperformance\":819,\"Ġ22\":820,\"Ġg\":821,\"Ġfilm\":822,\"Ġnearly\":823,\"ĠCenter\":824,\"Ġvisit\":825,\"ĠGroup\":826,\"Ġbank\":827,\"Ġbit\":828,\"Ġreceived\":829,\"ĠAugust\":830,\"Ġmilitary\":831,\"ĠHis\":832,\"ine\":833,\"Ġchief\":834,\"ĠSchool\":835,\"Ġbring\":836,\"ĠCourt\":837,\"Ġ(@\":838,\"Ġmeans\":839,\"ĠSh\":840,\"Ġfans\":841,\"Ġse\":842,\"Ġ40\":843,\"20\":844,\"\\\".\":845,\"V\":846,\"Ġcut\":847,\"Ġkilled\":848,\"Ġ#\":849,\"Ġprices\":850,\"Ġgave\":851,\"ĠStreet\":852,\"ir\":853,\"ĠY\":854,\"Ġcurrently\":855,\"Ġf\":856,\"ay\":857,\"ne\":858,\"te\":859,\"Ġtry\":860,\"ĠPark\":861,\"ĥ\":862,\"J\":863,\"Ġquestion\":864,\"Ġhand\":865,\"Ġeconomy\":866,\"Ġinvestors\":867,\"able\":868,\"Ġplayer\":869,\"ĠBy\":870,\"ĠDavid\":871,\"Ġloss\":872,\"ab\":873,\"Ġbelow\":874,\"Ġwrote\":875,\"co\":876,\"ate\":877,\"Ġrunning\":878,\"un\":879,\"Ġbegan\":880,\"Ġsingle\":881,\"Ġfield\":882,\"Ġ23\":883,\"Ġleader\":884,\"Ġw\":885,\"ĠCalifornia\":886,\"Ġfourth\":887,\"Ġactually\":888,\"Ġlist\":889,\"ll\":890,\"Ġcouple\":891,\"Ġstudy\":892,\"Ġteams\":893,\"He\":894,\"ah\":895,\"ĠCanada\":896,\"Ġla\":897,\"Ġresult\":898,\"Ġaccess\":899,\"Ġvote\":900,\"ĠMore\":901,\"ĠFebruary\":902,\"Ġrevenue\":903,\"Ġoffer\":904,\"Ġlet\":905,\"ier\":906,\"Ġbuy\":907,\"Ġattack\":908,\"Ġblack\":909,\"Ġr\":910,\"Ġareas\":911,\"Ġstop\":912,\"Ġimpact\":913,\"Ġmatch\":914,\"Ġinvestment\":915,\"Ġcustomers\":916,\"Ġleaders\":917,\"ies\":918,\"Ġmember\":919,\"Ġchild\":920,\"Ġroad\":921,\"ul\":922,\"Ġvalue\":923,\"Ġshows\":924,\"ĠDr\":925,\"ĠDe\":926,\"ant\":927,\"ĠLondon\":928,\"Ġroom\":929,\"Ġmusic\":930,\"Ġproduction\":931,\"Ġanything\":932,\"Ġfirm\":933,\"Ġbiggest\":934,\"Ġair\":935,\"Ġproblem\":936,\"Ġgeneral\":937,\"Ġwasn\":938,\"Ġi\":939,\"Ġprivate\":940,\"Ġespecially\":941,\"Ġadministration\":942,\"Ġadditional\":943,\"ĠCo\":944,\"Ġopportunity\":945,\"Ġhold\":946,\"&\":947,\"Ġmatter\":948,\"Ġsenior\":949,\"Ġclub\":950,\"Ġsomeone\":951,\"ĠÃ\":952,\"ĠEast\":953,\"Ġ2019\":954,\".'\":955,\"Ġneeded\":956,\"ĠJames\":957,\"time\":958,\"Ġhowever\":959,\"Ġeverything\":960,\"Ġeveryone\":961,\"Ġdied\":962,\"Ġinvolved\":963,\"Ġfriends\":964,\"Ġisn\":965,\"Ġworth\":966,\"ik\":967,\"ĠCup\":968,\"Ġshowed\":969,\"There\":970,\"Ġ28\":971,\"Ġmeet\":972,\"Ġ26\":973,\"Ġ27\":974,\"Y\":975,\"Ġregion\":976,\"ĠPress\":977,\"ĠNow\":978,\"Ġson\":979,\"Ġspace\":980,\"Ġleading\":981,\"Ġstates\":982,\"Ġweekend\":983,\"ĠÂ£\":984,\"Ġmother\":985,\"Ġprevious\":986,\"ĠUK\":987,\"ĠMichael\":988,\"Ġleave\":989,\"est\":990,\"em\":991,\"Ġz\":992,\"ĠSome\":993,\"ors\":994,\"out\":995,\"15\":996,\"Ġwar\":997,\"Ġwebsite\":998,\"Ġstar\":999,\"X\":1000,\"ro\":1001,\"Ġtarget\":1002,\"Ġhimself\":1003,\"Ġturn\":1004,\"ĠEurope\":1005,\"Ġworked\":1006,\"Ġenergy\":1007,\"Ġscored\":1008,\"Ġ*\":1009,\"Ġsoon\":1010,\"Ġball\":1011,\"ĠTV\":1012,\"Ġannual\":1013,\"Ġ2013\":1014,\"Ġrace\":1015,\"ĠInternational\":1016,\"'d\":1017,\"ĠMarket\":1018,\"Ġconference\":1019,\"io\":1020,\"Ġo\":1021,\"Ġchanges\":1022,\"ig\":1023,\"Ġofficers\":1024,\"Ġinside\":1025,\"Ġform\":1026,\"Ġpublished\":1027,\"Ġphone\":1028,\"Ġco\":1029,\"Ġlegal\":1030,\"Ġexecutive\":1031,\"Ġfight\":1032,\"ings\":1033,\"Ġhope\":1034,\"Ġsummer\":1035,\"Ġofficer\":1036,\"Ġfootball\":1037,\"Ġproperty\":1038,\"@\":1039,\"Ġbook\":1040,\"Ġparents\":1041,\"Ġcosts\":1042,\"ac\":1043,\"Ġmanager\":1044,\"Ġcreate\":1045,\"Ġage\":1046,\"Ġemail\":1047,\"Ġmarkets\":1048,\"Ġmain\":1049,\"Ġhuman\":1050,\"Ġsent\":1051,\"Ġmanagement\":1052,\"ĠDay\":1053,\"ton\":1054,\"Ġcash\":1055,\"Ġfocus\":1056,\"Ġexpect\":1057,\"Ġtraining\":1058,\"Ġbecame\":1059,\"Ġwhose\":1060,\"Ġevents\":1061,\"Ġround\":1062,\"ĠLe\":1063,\"Ġfell\":1064,\"Ġabove\":1065,\"Ġanalysts\":1066,\"Ġtalk\":1067,\"Ġsituation\":1068,\"ri\":1069,\"ated\":1070,\"ke\":1071,\"Ġwants\":1072,\"ag\":1073,\"Ġlives\":1074,\"om\":1075,\"Ġal\":1076,\"Ġdemand\":1077,\"Ġsafety\":1078,\"Ġrest\":1079,\"ĠCouncil\":1080,\"Ġpersonal\":1081,\"Ġsite\":1082,\"ĠRussian\":1083,\"Ġmid\":1084,\"Ġnothing\":1085,\"Ġwhole\":1086,\"Ġbill\":1087,\"Ġsold\":1088,\"ĠBritish\":1089,\"se\":1090,\"Ġremain\":1091,\"12\":1092,\"Ġforeign\":1093,\"Ġshooting\":1094,\"Ġstay\":1095,\"50\":1096,\"ang\":1097,\"Ġhospital\":1098,\"Ġbad\":1099,\"Ġaddress\":1100,\"ĠKorea\":1101,\"Ġhappened\":1102,\"Ġcharges\":1103,\"Ġwhite\":1104,\"Ġ31\":1105,\"If\":1106,\"Ġearnings\":1107,\"Ġbreak\":1108,\"Ġlight\":1109,\"Ġterms\":1110,\"ĠChinese\":1111,\"ĠSenate\":1112,\"ana\":1113,\"Ġidea\":1114,\"ap\":1115,\"of\":1116,\"Ġnine\":1117,\"Ġcompared\":1118,\"Ġbuild\":1119,\"ard\":1120,\"In\":1121,\"Ġsimilar\":1122,\"Ġgas\":1123,\"Ġvictory\":1124,\"Ġ2012\":1125,\"Ġdebt\":1126,\"ĠMar\":1127,\"Ġarrested\":1128,\"Ġcomment\":1129,\"Ġincreased\":1130,\"Ġmedical\":1131,\"Ġ29\":1132,\"ĠJan\":1133,\"Ġgroups\":1134,\"Ġdespite\":1135,\"Ġfall\":1136,\"Ġtell\":1137,\"Ġworkers\":1138,\"Ġtown\":1139,\"Ã©\":1140,\"Ġwife\":1141,\"Ġquestions\":1142,\"Ġcontinued\":1143,\"Ġheart\":1144,\"Ġmet\":1145,\"Ġbrought\":1146,\"Ġhelped\":1147,\"ĠCongress\":1148,\"Ġstep\":1149,\"Ġfather\":1150,\"Ġmoment\":1151,\"Ġproduct\":1152,\"Ġprobably\":1153,\"Ġlargest\":1154,\"Ġvehicle\":1155,\"ĠEngland\":1156,\"Ġallow\":1157,\"Ġstarting\":1158,\"Ġkids\":1159,\"Ġincident\":1160,\"Ġnet\":1161,\"Ġrates\":1162,\"ĠRead\":1163,\"Ġpressure\":1164,\"Ġincluded\":1165,\"Ġread\":1166,\"Ġissued\":1167,\"ol\":1168,\"Ġeither\":1169,\"Ġefforts\":1170,\"Ġincludes\":1171,\"ĠRepublican\":1172,\"ish\":1173,\"âĢ¦\":1174,\"Ġgoals\":1175,\"aj\":1176,\"Ġen\":1177,\"x\":1178,\"Ġraised\":1179,\"au\":1180,\"Ġlonger\":1181,\"ut\":1182,\"Ġwatch\":1183,\"ĠTexas\":1184,\"You\":1185,\"Ġrange\":1186,\"nd\":1187,\"Ġfunds\":1188,\"Ġremains\":1189,\"ĠMark\":1190,\"Ġ60\":1191,\"Ġque\":1192,\"sh\":1193,\"Ġinterview\":1194,\"Ġrather\":1195,\"Ġresidents\":1196,\"Ġgrowing\":1197,\"Ġpre\":1198,\"Ġpaid\":1199,\"Ġcases\":1200,\"ĠReuters\":1201,\"Ġdifficult\":1202,\"Ġsign\":1203,\"ĠGoogle\":1204,\"Ġhttps\":1205,\"ĠPaul\":1206,\"Ġliving\":1207,\"day\":1208,\"ĠQ\":1209,\"iz\":1210,\"ĠRed\":1211,\"Ġland\":1212,\"They\":1213,\"ĠRoad\":1214,\"_\":1215,\"ĠThese\":1216,\"Ġview\":1217,\"Ġagency\":1218,\"Ġreason\":1219,\"Ġallowed\":1220,\"ĠAustralia\":1221,\"az\":1222,\"ĠRe\":1223,\"Ġturned\":1224,\"11\":1225,\"Ġnation\":1226,\"Ġready\":1227,\"Ġpress\":1228,\"Ġbudget\":1229,\"Ġdaily\":1230,\"ĠChief\":1231,\"Ġfamilies\":1232,\"Ġsignificant\":1233,\"ĠFirst\":1234,\"Ġthemselves\":1235,\"Ġj\":1236,\"Ġruns\":1237,\"Ġaccused\":1238,\"Ġtakes\":1239,\"Ġspent\":1240,\"Ġvia\":1241,\"ot\":1242,\"ina\":1243,\"25\":1244,\"land\":1245,\"Ġexample\":1246,\"Ġauthorities\":1247,\"Ġdate\":1248,\"Ġended\":1249,\"all\":1250,\"Reuters\":1251,\"Ġbusinesses\":1252,\"ans\":1253,\"Ġdetails\":1254,\"Ġground\":1255,\"Ġpretty\":1256,\"ĠApple\":1257,\"ation\":1258,\"ĠSmith\":1259,\"ĠCompany\":1260,\"ĠFlorida\":1261,\"Ġdrug\":1262,\"Ġresponse\":1263,\"one\":1264,\"Ġeducation\":1265,\"Ġmean\":1266,\"Ġleague\":1267,\"Ġanyone\":1268,\"Ġminister\":1269,\"Ġtitle\":1270,\"Ġadding\":1271,\"Ġproblems\":1272,\"Ġopening\":1273,\"Ġconditions\":1274,\"Ġred\":1275,\"Ġdecided\":1276,\"Å\":1277,\"Ġposted\":1278,\"term\":1279,\"Ġamount\":1280,\"ĠEU\":1281,\"Ġsuccess\":1282,\"Ġevidence\":1283,\"ĠObama\":1284,\"Ġaddition\":1285,\"Ġprovided\":1286,\"ĠLos\":1287,\"Ġagreement\":1288,\"Ġstage\":1289,\"ens\":1290,\"Ġrelationship\":1291,\"ĠGeneral\":1292,\"Ġsector\":1293,\"Ġstudent\":1294,\"ating\":1295,\"Ġtest\":1296,\"\\\",\":1297,\"Ġwinning\":1298,\"Ġfelt\":1299,\"Ġsource\":1300,\"Z\":1301,\"Ġseems\":1302,\"Ġcause\":1303,\"Ġschools\":1304,\"Ġdrive\":1305,\"Ġensure\":1306,\"Ġhuge\":1307,\"ĠMy\":1308,\"ĠHealth\":1309,\"Ġscene\":1310,\"Ġgiving\":1311,\"Ġcenter\":1312,\"Ġpositive\":1313,\"Ġyards\":1314,\"Ġjobs\":1315,\"Ġaccount\":1316,\"Ġheard\":1317,\"Ġquality\":1318,\"Ġways\":1319,\"Ġimmediately\":1320,\"Ġemployees\":1321,\"are\":1322,\"Ġpass\":1323,\"ĠCEO\":1324,\"Ġreceive\":1325,\"Ġlooks\":1326,\"ĠAfrica\":1327,\"Ġthroughout\":1328,\"led\":1329,\"Ġrelated\":1330,\"Ġsell\":1331,\"ĠUnion\":1332,\"ĠPhoto\":1333,\"ter\":1334,\"Ġquickly\":1335,\"ĠHow\":1336,\"Ġvarious\":1337,\"Ġreach\":1338,\"Ġpick\":1339,\"Ġcharged\":1340,\"Ġquite\":1341,\"ent\":1342,\"q\":1343,\"ins\":1344,\"Ġphoto\":1345,\"Ġunderstand\":1346,\"ĠâĢ¢\":1347,\"Ġreached\":1348,\"Ġtrack\":1349,\"uk\":1350,\"Ġeffort\":1351,\"ville\":1352,\"Ġcentral\":1353,\"Ġdaughter\":1354,\"Ġcontract\":1355,\"Ġinjury\":1356,\"Ġopened\":1357,\"Ġ($\":1358,\"Ġstraight\":1359,\"17\":1360,\"Ġcredit\":1361,\"ĠIndian\":1362,\"Ġsexual\":1363,\"Ġworks\":1364,\"Ġeasy\":1365,\"18\":1366,\"Ġclosed\":1367,\"Ġh\":1368,\"Ġhappen\":1369,\"Ġforce\":1370,\"ler\":1371,\"Ġhappy\":1372,\"Ġshared\":1373,\"Ġoverall\":1374,\"Ġmoving\":1375,\"á\":1376,\"Ġprojects\":1377,\"ĠBlack\":1378,\"Ġconcerns\":1379,\"Ġclass\":1380,\"Ġtried\":1381,\"Ġappeared\":1382,\"Ġcontent\":1383,\"ĠDistrict\":1384,\"Ġterm\":1385,\"Ġinstead\":1386,\"ĠOffice\":1387,\"Ġcontinues\":1388,\"Ġlevels\":1389,\"Ġafternoon\":1390,\"Ġfund\":1391,\"Ġsale\":1392,\"Ġdriver\":1393,\"Ġask\":1394,\"Ġcannot\":1395,\"ner\":1396,\"end\":1397,\"ĠHere\":1398,\"field\":1399,\"Ġstore\":1400,\"www\":1401,\"Ġcertain\":1402,\"Ġself\":1403,\"Ġdollar\":1404,\"ĠHer\":1405,\"Ġpopular\":1406,\"Ġfollow\":1407,\"Ġspending\":1408,\"by\":1409,\"Ġmoved\":1410,\"Ġgoes\":1411,\"Ġcreated\":1412,\"Ġstand\":1413,\"Ġoperations\":1414,\"Ġlooked\":1415,\"Ġtreatment\":1416,\"ov\":1417,\"Ġdistrict\":1418,\"Ġsigned\":1419,\"Ġhands\":1420,\"Ġmodel\":1421,\"ĠAngeles\":1422,\"Ġy\":1423,\"Ġborder\":1424,\"Ġincome\":1425,\"ĠLast\":1426,\"Ġcharge\":1427,\"Ġdriving\":1428,\"ĠJapan\":1429,\"Ġrise\":1430,\"Ġtalks\":1431,\"Ġfollowed\":1432,\"Ġpreviously\":1433,\"Ġusers\":1434,\"Ġfunding\":1435,\"ĠJohnson\":1436,\"Ġ\":1437,\"ou\":1438,\"ai\":1439,\"Ġnamed\":1440,\"Ġfriend\":1441,\"ĠNov\":1442,\"Ġdefense\":1443,\"ĠBritain\":1444,\"Ġentire\":1445,\"Ġtrading\":1446,\"Ġfailed\":1447,\"ĠEl\":1448,\"Ġclaims\":1449,\"Ġcomments\":1450,\"Ġbeat\":1451,\"ib\":1452,\"Ġbasis\":1453,\"ĠJones\":1454,\"Ġpresent\":1455,\"ĠBe\":1456,\"Ġdouble\":1457,\"Ġrose\":1458,\"ite\":1459,\"Ġability\":1460,\"Ġoriginal\":1461,\"Ġdead\":1462,\"ĠCommission\":1463,\"ĠMe\":1464,\"Ġcompetition\":1465,\"Ġ2011\":1466,\"Ġknew\":1467,\"Ġmaterial\":1468,\"av\":1469,\"ĠFrance\":1470,\"Ġscore\":1471,\"Ġsense\":1472,\"Ġserious\":1473,\"Ġconfirmed\":1474,\"Ġanti\":1475,\"Ġviolence\":1476,\"Ġimprove\":1477,\"son\":1478,\"Ã³\":1479,\"ĠAP\":1480,\"Ġsh\":1481,\"Ġhost\":1482,\"ĠMike\":1483,\"Ġpatients\":1484,\"ĠNFL\":1485,\"Ġcrisis\":1486,\"Ġrevealed\":1487,\"ach\":1488,\"ĠPrime\":1489,\"Ġbuilt\":1490,\"ĠNot\":1491,\"Ġrules\":1492,\"Ġelse\":1493,\"Ġdepartment\":1494,\"Ġitself\":1495,\"ise\":1496,\"500\":1497,\"Ġcomplete\":1498,\"ion\":1499,\"Ġtrial\":1500,\"ĠBay\":1501,\"ĠDec\":1502,\"Ġattention\":1503,\"Ġtravel\":1504,\"ĠCentral\":1505,\"ry\":1506,\"Ġagreed\":1507,\"Ġmind\":1508,\"ĠMc\":1509,\"Ġ70\":1510,\"Ġcontact\":1511,\"ari\":1512,\"ĠTimes\":1513,\"Ġspot\":1514,\"ĠFrench\":1515,\"Ġgets\":1516,\"op\":1517,\"Ġbrand\":1518,\"Ġcalls\":1519,\"Ġbanks\":1520,\"Ġdesign\":1521,\"Ġsafe\":1522,\"Ġoffers\":1523,\"Ġpractice\":1524,\"ĠOf\":1525,\"Ã¡\":1526,\"ling\":1527,\"Ġtrue\":1528,\"off\":1529,\"Ġnumbers\":1530,\"Ġfun\":1531,\"Ġlearn\":1532,\"Ġmultiple\":1533,\"ĠIs\":1534,\"res\":1535,\"als\":1536,\"Ġcommon\":1537,\"ized\":1538,\"Ġchallenge\":1539,\"Ġcommittee\":1540,\"ĠOur\":1541,\"Ġbase\":1542,\"ani\":1543,\"ĠAssociation\":1544,\"ung\":1545,\"Ġnetwork\":1546,\"ĠBrown\":1547,\"Ġapproach\":1548,\"16\":1549,\"Ġfinished\":1550,\"Ġreview\":1551,\"Ġrequired\":1552,\"Ġapp\":1553,\"ĠMan\":1554,\"ĠâĢ¦\":1555,\"twitter\":1556,\"ĠDemocratic\":1557,\"13\":1558,\"Ġevening\":1559,\"ĠTom\":1560,\"Ã¤\":1561,\"ĠAssociated\":1562,\"ĠCanadian\":1563,\"Ġcollege\":1564,\"Ġspokesman\":1565,\"Ġarticle\":1566,\"Ġtowards\":1567,\"ĠChicago\":1568,\"Ġmovie\":1569,\"14\":1570,\"ity\":1571,\"Ġforces\":1572,\"ĠChris\":1573,\"ĠDemocrats\":1574,\"Ġfeatures\":1575,\"Ġhearing\":1576,\"ĠX\":1577,\"ĠAlso\":1578,\"Ġmessage\":1579,\"age\":1580,\"Ġnoted\":1581,\"ĠSuper\":1582,\"Ġthousands\":1583,\"aw\":1584,\"ĠBill\":1585,\"ĠAr\":1586,\"ĠLa\":1587,\"ip\":1588,\"Ġ/\":1589,\"ĠDuring\":1590,\"Ġnote\":1591,\".)\":1592,\"Ġwrong\":1593,\"if\":1594,\"Ġpassed\":1595,\"ĠTwo\":1596,\"Ġdie\":1597,\",'\":1598,\"ĠDon\":1599,\"ĠGermany\":1600,\"Ġletter\":1601,\"Ġdescribed\":1602,\"ĠIran\":1603,\"ĠWilliams\":1604,\"Ġparticularly\":1605,\"Ġadd\":1606,\"Ġconversation\":1607,\"ĠSe\":1608,\"Ġhighest\":1609,\"be\":1610,\"Ġhomes\":1611,\"Ġsports\":1612,\"Ġgone\":1613,\"ĠAd\":1614,\"Ġel\":1615,\"Ġopportunities\":1616,\"Ġwords\":1617,\"Ġleaving\":1618,\"ĠChristmas\":1619,\"As\":1620,\"ĠGovernment\":1621,\"Ġsimply\":1622,\"Ġhusband\":1623,\"ĠResearch\":1624,\"ĠMexico\":1625,\"ates\":1626,\"ale\":1627,\"ĠGreen\":1628,\"$\":1629,\"od\":1630,\"ĠHall\":1631,\"Ġnatural\":1632,\"Ġoperating\":1633,\"les\":1634,\"ations\":1635,\"ĠKim\":1636,\"Ġgold\":1637,\"ok\":1638,\"Ġprovides\":1639,\"(\":1640,\"ell\":1641,\"Ġbegin\":1642,\"ĠParty\":1643,\"back\":1644,\"ĠAmazon\":1645,\"19\":1646,\"Ġmajority\":1647,\"ĠEven\":1648,\"Ġcheck\":1649,\"Ġweather\":1650,\"Ġorganization\":1651,\"Ġstories\":1652,\"ĠCar\":1653,\"Ġforced\":1654,\"ĠGeorge\":1655,\"Ġwalk\":1656,\"ong\":1657,\"Ġfiled\":1658,\"ĠJustice\":1659,\"Ġlaunched\":1660,\"Ġoffered\":1661,\"Ġwww\":1662,\"Ġconstruction\":1663,\"ĠBen\":1664,\"Ġserved\":1665,\"Ġ...\":1666,\"Ġparts\":1667,\"Ġcancer\":1668,\"Ġguys\":1669,\"Reporting\":1670,\"ash\":1671,\"less\":1672,\"Ġleadership\":1673,\"ĠCommittee\":1674,\"Ġregular\":1675,\"Ġcouncil\":1676,\"Ġcars\":1677,\"ĠDirector\":1678,\"Ġjudge\":1679,\"Ġvictims\":1680,\"ĠDaily\":1681,\"Ġkept\":1682,\"Ġeffect\":1683,\"Ġbeyond\":1684,\"pm\":1685,\"Ġtalking\":1686,\"Ġconsidered\":1687,\"ore\":1688,\"ĠAdvertisement\":1689,\"Ġst\":1690,\"ED\":1691,\"Ġmiddle\":1692,\"Ġraise\":1693,\"we\":1694,\"Ġclaimed\":1695,\"ino\":1696,\"Ġalleged\":1697,\"ĠPro\":1698,\"ĠScott\":1699,\"ĠOct\":1700,\"Ġconsider\":1701,\"ĠShare\":1702,\"Ġtraffic\":1703,\"ĠAfrican\":1704,\"Ġcouldn\":1705,\"Ġtoward\":1706,\"Ġsearch\":1707,\"But\":1708,\"Ġlaunch\":1709,\"Ġinjured\":1710,\"That\":1711,\"Ġalthough\":1712,\"Ġactivities\":1713,\"Ġchanged\":1714,\"Ġsources\":1715,\"Ġmissing\":1716,\"Ġu\":1717,\"Ġ35\":1718,\"Ġcover\":1719,\"ised\":1720,\"Ġ|\":1721,\"ow\":1722,\"ES\":1723,\"Ġdecades\":1724,\"ich\":1725,\"Ġcaused\":1726,\"Ġelections\":1727,\"ane\":1728,\"IS\":1729,\"Ġfeet\":1730,\"ĠBar\":1731,\"Ġversion\":1732,\"Ġgrow\":1733,\"Ġvehicles\":1734,\"Ġoptions\":1735,\"Ġindividual\":1736,\"Ġenvironment\":1737,\"ĠRobert\":1738,\"ĠValley\":1739,\"ĠFrom\":1740,\"per\":1741,\"ara\":1742,\"Ġsystems\":1743,\"Ġprotect\":1744,\"ĠKing\":1745,\"Ġinjuries\":1746,\"Ġfinally\":1747,\"Ġnuclear\":1748,\"40\":1749,\"Ġratio\":1750,\"Ġgun\":1751,\"ĠPakistan\":1752,\"ĠManagement\":1753,\"ĠAir\":1754,\"ce\":1755,\"Ġopposition\":1756,\"ment\":1757,\"ick\":1758,\"Ġpro\":1759,\"Ġact\":1760,\"Ġplatform\":1761,\"Ġlack\":1762,\"Ġpair\":1763,\"Ġ500\":1764,\"Ġcalling\":1765,\"ary\":1766,\"Ġprograms\":1767,\"Ġscheduled\":1768,\"Ġfast\":1769,\"Ġjoined\":1770,\"ĠWar\":1771,\"ĠEditing\":1772,\"ĠSince\":1773,\"ĠRyan\":1774,\"ĠMac\":1775,\"ĠBig\":1776,\"ĠLake\":1777,\"Ġdigital\":1778,\"When\":1779,\"ue\":1780,\"Ġassets\":1781,\"Ġseeing\":1782,\"ĠAct\":1783,\"Ġpartner\":1784,\"ĠBoard\":1785,\"Ġbeginning\":1786,\"Ġsupply\":1787,\"Ġmiles\":1788,\"Ġprison\":1789,\"ons\":1790,\"ĠAmericans\":1791,\"ub\":1792,\"ĠOr\":1793,\"me\":1794,\"Ġbenefits\":1795,\"Ġbenefit\":1796,\"Ġmeasures\":1797,\"Ġhear\":1798,\"Ġparties\":1799,\"Ġsuccessful\":1800,\"ĠJust\":1801,\"Ġvictim\":1802,\"Ġblock\":1803,\"Ġlimited\":1804,\"Ġtrip\":1805,\"ĠPeople\":1806,\"Ġserve\":1807,\"Ġart\":1808,\"ism\":1809,\"Ġwide\":1810,\"ĠSch\":1811,\"Ġ80\":1812,\"ĠThomas\":1813,\"Ġ90\":1814,\"Ġstocks\":1815,\"Ġgirl\":1816,\"ĠAsia\":1817,\"Ġseeking\":1818,\"Ġcertainly\":1819,\"ĠServices\":1820,\"ĠCollege\":1821,\"Ġcommunities\":1822,\"Ġextra\":1823,\"Ġ2010\":1824,\"ness\":1825,\"Ġholding\":1826,\"ous\":1827,\"Ġtough\":1828,\"ade\":1829,\"Ġmobile\":1830,\"Ġowns\":1831,\"ĠDo\":1832,\"ĠFire\":1833,\"Ġspoke\":1834,\"Ġreturned\":1835,\"Ġsize\":1836,\"Ġcriminal\":1837,\"ĠInstagram\":1838,\"Ġoffering\":1839,\"ĠGod\":1840,\"ĠService\":1841,\"Ġpage\":1842,\"her\":1843,\"Ġdeep\":1844,\"wood\":1845,\"Ġcrime\":1846,\"ĠSports\":1847,\"ile\":1848,\"ĠGlobal\":1849,\"Ġproposed\":1850,\"ain\":1851,\"Ġsession\":1852,\"ĠFederal\":1853,\"ĠSyria\":1854,\"Ġch\":1855,\"Ġthreat\":1856,\"Ġallegations\":1857,\"ĠRepublicans\":1858,\"ĠGerman\":1859,\"Ġstrategy\":1860,\"Ġcommercial\":1861,\"ING\":1862,\"ĠSecretary\":1863,\"Q\":1864,\"Ġreporters\":1865,\"100\":1866,\"ĠCapital\":1867,\"ĠBoth\":1868,\"ĠPost\":1869,\"ĠIsrael\":1870,\"Ġsave\":1871,\"ts\":1872,\"ill\":1873,\"Ġdrop\":1874,\"Ġreserved\":1875,\"ĠMany\":1876,\"Ġavoid\":1877,\"Ġ200\":1878,\"iv\":1879,\"Ġdamage\":1880,\"Ġcondition\":1881,\"Ġdropped\":1882,\"Ġdoor\":1883,\"Ġplanning\":1884,\"ire\":1885,\"Ġcard\":1886,\"Ġdesigned\":1887,\"Ġreduce\":1888,\"AN\":1889,\"ĠUn\":1890,\"ford\":1891,\"ĠThen\":1892,\"Ġpic\":1893,\"ĠCopyright\":1894,\"Ġrain\":1895,\"ĠMartin\":1896,\"Ġdomestic\":1897,\"45\":1898,\"ge\":1899,\"Ġmurder\":1900,\"Ġspeech\":1901,\"line\":1902,\"Ġhelping\":1903,\"Ġplanned\":1904,\"Ġfeature\":1905,\"ud\":1906,\"Ġtype\":1907,\"ham\":1908,\"ĠPublic\":1909,\"ja\":1910,\"Ġinsurance\":1911,\"Ġattacks\":1912,\"ĠCorp\":1913,\"Ġforecast\":1914,\"Ġresources\":1915,\"ma\":1916,\"?\\\"\":1917,\"ĠAm\":1918,\"ĠSept\":1919,\"Ġpush\":1920,\"Ġattorney\":1921,\"23\":1922,\"Ġemergency\":1923,\"Ġwinner\":1924,\"Ġblood\":1925,\"Ġnorth\":1926,\"ĠFeb\":1927,\"Ġbaby\":1928,\"Ġfloor\":1929,\"Ġspend\":1930,\"Ġex\":1931,\"Ġdollars\":1932,\"Ġunit\":1933,\"ĠHill\":1934,\"Ġder\":1935,\"ĠAbout\":1936,\"Ġalone\":1937,\"ization\":1938,\"Ġpresidential\":1939,\"Ġactivity\":1940,\"ĠTHE\":1941,\"ee\":1942,\"ber\":1943,\"ĠOther\":1944,\"Ġowner\":1945,\"Ġhour\":1946,\"Ġcities\":1947,\"Ġanswer\":1948,\"ide\":1949,\"Ġfully\":1950,\"ek\":1951,\"ists\":1952,\"Ġcoverage\":1953,\"Ġvs\":1954,\"Ġfigure\":1955,\"Ġpopulation\":1956,\"org\":1957,\"Ġsnow\":1958,\"Ġbecoming\":1959,\"ĠSam\":1960,\"ĠCarolina\":1961,\"Ġjoin\":1962,\"Ġprofit\":1963,\"Ġitems\":1964,\"Ġindex\":1965,\"Ġanalysis\":1966,\"Ġtournament\":1967,\"Ġstake\":1968,\"Ġperfect\":1969,\"way\":1970,\"Ġband\":1971,\"Ġgirls\":1972,\"Ġoption\":1973,\"Ġplays\":1974,\"oc\":1975,\"Ġproviding\":1976,\"ÃŃ\":1977,\"24\":1978,\"Ġwouldn\":1979,\"Ġones\":1980,\"Ġdeclined\":1981,\"Ġwritten\":1982,\"Ġvoters\":1983,\"Ġcandidate\":1984,\"Ġsuspect\":1985,\"Ġpolicies\":1986,\"Ġpeace\":1987,\"ast\":1988,\"Ġparticular\":1989,\"for\":1990,\"Ġhopes\":1991,\"Ġstation\":1992,\"ĠMost\":1993,\"Ġspeak\":1994,\"ĠRiver\":1995,\"Ġasking\":1996,\"Ġstatements\":1997,\"Ġfifth\":1998,\"ha\":1999,\"ĠNigeria\":2000,\"af\":2001,\"Ġexplained\":2002,\"Ġbar\":2003,\"Ġhousing\":2004,\"ĠSanta\":2005,\"Ġidentified\":2006,\"Ġsimple\":2007,\"Ġcritical\":2008,\"ĠClub\":2009,\"ĠSecurity\":2010,\"ĠLike\":2011,\"Ġstarts\":2012,\"art\":2013,\"Ġstreet\":2014,\"Ġreality\":2015,\"Ġheavy\":2016,\"Ġprogress\":2017,\"Ġshowing\":2018,\"Ġchallenges\":2019,\"Ġban\":2020,\"Ġcommitted\":2021,\"35\":2022,\"»\":2023,\"Ġdirectly\":2024,\"Ġaren\":2025,\"Ġclaim\":2026,\"ĠWestern\":2027,\"ind\":2028,\"Ġgives\":2029,\"ĠSaudi\":2030,\"Ġchoice\":2031,\"ĠTh\":2032,\"Ġapproved\":2033,\"Ġlocated\":2034,\"Ġarrived\":2035,\"22\":2036,\"Ġcaught\":2037,\"Ġprofessional\":2038,\"Ġmissed\":2039,\"Ġculture\":2040,\"ĠYear\":2041,\"ĠOhio\":2042,\"ĠLtd\":2043,\"ĠAnother\":2044,\"Ġseem\":2045,\"Ġbelieves\":2046,\"Ġbelieved\":2047,\"Ġcharacter\":2048,\"ĠAug\":2049,\"red\":2050,\"Ġfine\":2051,\"Ġprior\":2052,\"Ġthinking\":2053,\"Ġhttp\":2054,\"Ġ+\":2055,\"Ġzone\":2056,\"Ġputting\":2057,\"Ġcrash\":2058,\"ĠAustralian\":2059,\"ĠAb\":2060,\"Ġfocused\":2061,\"ĠREUTERS\":2062,\"ĠFox\":2063,\"ĠSp\":2064,\"Ġtraditional\":2065,\"Ġanalyst\":2066,\"Ġwait\":2067,\"IT\":2068,\"Ġrequest\":2069,\"ru\":2070,\"ians\":2071,\"ize\":2072,\"Ġfinish\":2073,\"Ġlaws\":2074,\"Ġran\":2075,\"ER\":2076,\"Ġsouth\":2077,\"Ġspeed\":2078,\"Ġmovement\":2079,\"Ġassault\":2080,\"Ġexchange\":2081,\"Ġappear\":2082,\"ĠSun\":2083,\"Ġle\":2084,\"Ġmaybe\":2085,\"Ġlosing\":2086,\"Ġsubject\":2087,\"ive\":2088,\"mer\":2089,\"ĠBusiness\":2090,\"ĠBl\":2091,\"Ġappears\":2092,\"Ġadvantage\":2093,\"ĠLee\":2094,\"ada\":2095,\"ĠUnder\":2096,\"Ġprevent\":2097,\"Ġrespect\":2098,\"Ġsex\":2099,\"Ġcentre\":2100,\"ĠJoe\":2101,\"ado\":2102,\"Ġtable\":2103,\"Ġequipment\":2104,\"Ġfair\":2105,\"Ġtour\":2106,\"Ġ32\":2107,\"ĠFinancial\":2108,\"Ġcounty\":2109,\"Ġdevices\":2110,\"Ġcustomer\":2111,\"Ġinfrastructure\":2112,\"Ġexpectations\":2113,\"Ġfacing\":2114,\"Ġupon\":2115,\"Ġcross\":2116,\"ĠOpen\":2117,\"AL\":2118,\"Ġquick\":2119,\"Ġattempt\":2120,\"Ġcompleted\":2121,\"Ġfacility\":2122,\"Ġconfidence\":2123,\"ĠSupreme\":2124,\"Ġpiece\":2125,\"our\":2126,\"Ġplaces\":2127,\"Ġsometimes\":2128,\"Ġpoor\":2129,\"Ġstorm\":2130,\"Ġhot\":2131,\"Ġaffected\":2132,\"na\":2133,\"Ġabuse\":2134,\"ĠMs\":2135,\"Ġword\":2136,\"over\":2137,\"Ġbrother\":2138,\"Ġnecessary\":2139,\"Ġeventually\":2140,\"ĠStar\":2141,\"Ġsend\":2142,\"Ġboy\":2143,\"ĠRs\":2144,\"Ġremember\":2145,\"21\":2146,\"Ġclimate\":2147,\"Ġcapacity\":2148,\"Ġresponsible\":2149,\"ĠMatt\":2150,\"month\":2151,\"Ġsuffered\":2152,\"%.\":2153,\"og\":2154,\"ĠPeter\":2155,\"Ġ,\":2156,\"Ġfeeling\":2157,\"ze\":2158,\"Ġbuying\":2159,\"oy\":2160,\"ij\":2161,\"Ġbought\":2162,\"Ġactions\":2163,\"Ġowned\":2164,\"Ġ___\":2165,\"Ġphysical\":2166,\"Ġspecific\":2167,\"Ġbattle\":2168,\"ĠEnergy\":2169,\"Ġpicture\":2170,\"Ġactive\":2171,\"Ġindividuals\":2172,\"Ġguy\":2173,\"Ġregional\":2174,\"Ġbond\":2175,\"ows\":2176,\"ĠToronto\":2177,\"Ġrule\":2178,\"Ġdevelop\":2179,\"Ġcrowd\":2180,\"Ġguilty\":2181,\"Ġfemale\":2182,\"Ġselling\":2183,\"ĠFollow\":2184,\"Ġmyself\":2185,\"ata\":2186,\"Ġdevice\":2187,\"Ġreasons\":2188,\"Ġrecords\":2189,\"Ġfighting\":2190,\"ON\":2191,\"ities\":2192,\"ĠHome\":2193,\"Ġstatus\":2194,\"Ġplant\":2195,\"Ġdrugs\":2196,\"ĠChurch\":2197,\"Ġcompletely\":2198,\"Ġdisease\":2199,\"Ġhighly\":2200,\"ĠParis\":2201,\"Ġdecade\":2202,\"Ġowners\":2203,\"Ġwall\":2204,\"Ġcamp\":2205,\"ĠSteve\":2206,\"Ġreporting\":2207,\"Ġearned\":2208,\"ĠImages\":2209,\"Ġexisting\":2210,\"ĠSen\":2211,\"Ġconcern\":2212,\"Ġhundreds\":2213,\"Ġsong\":2214,\"Ġknows\":2215,\"Ġunique\":2216,\"Ġlose\":2217,\"ĠKh\":2218,\"Ġapproximately\":2219,\"Ġhaven\":2220,\"Ġpark\":2221,\"Ġindependent\":2222,\"ĠAlthough\":2223,\"ĠAndrew\":2224,\"Ġpaper\":2225,\"Ġdeveloped\":2226,\"Ġrising\":2227,\"Ġdirect\":2228,\"Ġpurchase\":2229,\"Ġexactly\":2230,\"Ġq\":2231,\"Ġmassive\":2232,\"Ġbox\":2233,\"Ġchampion\":2234,\"ĠClinton\":2235,\"Ġvoice\":2236,\"Ġarrest\":2237,\"ĠKorean\":2238,\"Ġlearning\":2239,\"ĠVirginia\":2240,\"Ġsa\":2241,\"Ġpar\":2242,\"Ġchairman\":2243,\"Ġagencies\":2244,\"Ġhealthy\":2245,\"ĠThose\":2246,\"Ġpowerful\":2247,\"Ġ45\":2248,\"Ġdifference\":2249,\"ĠJackson\":2250,\"Ġenforcement\":2251,\"Ġdividend\":2252,\"qu\":2253,\"Ġenjoy\":2254,\"Ġruling\":2255,\"Ġongoing\":2256,\"Ġsoftware\":2257,\"ks\":2258,\"Ġlocation\":2259,\"Ġmostly\":2260,\"Ġcandidates\":2261,\"men\":2262,\"Ġbroke\":2263,\"What\":2264,\"ĠBr\":2265,\"Ġ2008\":2266,\"Ġconsumer\":2267,\"Ġdiscuss\":2268,\"Ġdi\":2269,\"Ġprimary\":2270,\"ĠEn\":2271,\"Ġgreen\":2272,\"Ġconcerned\":2273,\"Ġimage\":2274,\"ĠPremier\":2275,\"ĠMeanwhile\":2276,\"Ġfired\":2277,\"ĠBoston\":2278,\"ann\":2279,\"Ġcamera\":2280,\"Ġtraded\":2281,\"Ġhasn\":2282,\"Ġexcited\":2283,\"Ġincreasing\":2284,\"ĠDespite\":2285,\"Ġcitizens\":2286,\"Ġeuro\":2287,\"Ġreportedly\":2288,\"Ġminute\":2289,\"ĠWill\":2290,\"ĠLLC\":2291,\"Ġsp\":2292,\"ĠMichigan\":2293,\"Ġstopped\":2294,\"Ġeye\":2295,\"Ġdenied\":2296,\"Ġmodern\":2297,\"ĠWall\":2298,\"Ġdefinitely\":2299,\"point\":2300,\"Ġlines\":2301,\"Ġpolitics\":2302,\"Ġhotel\":2303,\"Ġretail\":2304,\"Ġstated\":2305,\"ĠOver\":2306,\"Ġgrew\":2307,\"Ġbroadcast\":2308,\"Ġlegislation\":2309,\"Ġfresh\":2310,\"Ġbid\":2311,\"Ġmanaged\":2312,\"Ġsociety\":2313,\"Ġscoring\":2314,\"ĠGet\":2315,\"Ġintelligence\":2316,\"Ġholiday\":2317,\"Ġgovernor\":2318,\"Ġestimated\":2319,\"Ġexperts\":2320,\"ĠJeff\":2321,\"Ġstruck\":2322,\"Ġhits\":2323,\"Ġcarry\":2324,\"Ġplaced\":2325,\"Ġstores\":2326,\"Ġexpressed\":2327,\"Ġvalued\":2328,\"Ġad\":2329,\"Ġtwice\":2330,\"ala\":2331,\"Ġdisplay\":2332,\"Ġusually\":2333,\"Ġresponded\":2334,\"Ġdog\":2335,\"AS\":2336,\"ĠFed\":2337,\"Ġ2009\":2338,\"Ġdocuments\":2339,\"Ġnormal\":2340,\"Ġtrain\":2341,\"Ġfl\":2342,\"Ġshown\":2343,\"ĠEd\":2344,\"Ġsort\":2345,\"Ġallegedly\":2346,\"Ġshots\":2347,\"ka\":2348,\"Ġaccounts\":2349,\"Ġyesterday\":2350,\"Ġcreating\":2351,\"Ġchurch\":2352,\"Ġbus\":2353,\"Ġaward\":2354,\"Ġequity\":2355,\"Ġphotos\":2356,\"Ġ33\":2357,\"Ġfiscal\":2358,\"je\":2359,\"Ġconsumers\":2360,\"ĠManchester\":2361,\"no\":2362,\"ĠKevin\":2363,\"Ġgain\":2364,\"Ġcorporate\":2365,\"Ġcivil\":2366,\"ĠMiddle\":2367,\"ally\":2368,\"Ġsound\":2369,\"ĠEnglish\":2370,\"IC\":2371,\"Ġwinds\":2372,\"Ġworst\":2373,\"ĠGrand\":2374,\"Ġeffective\":2375,\"ĠIsland\":2376,\"Ġdrivers\":2377,\"Ġfan\":2378,\"pe\":2379,\"Ġsides\":2380,\"ĠGo\":2381,\"Ġclean\":2382,\"âĢĵ\":2383,\"Ġtelevision\":2384,\"ĠJr\":2385,\"Ġallows\":2386,\"My\":2387,\"Ġgreater\":2388,\"ance\":2389,\"Ġdecisions\":2390,\"Ġrestaurant\":2391,\"ĠHospital\":2392,\"ĠTr\":2393,\"Ġbalance\":2394,\"Ġmph\":2395,\"Ġkeeping\":2396,\"Ġseconds\":2397,\"Ġweapons\":2398,\"ert\":2399,\"Ġpain\":2400,\"ass\":2401,\"Ġsteps\":2402,\"ger\":2403,\"ĠBrexit\":2404,\"Ġremaining\":2405,\"Ġbringing\":2406,\"ure\":2407,\"Ġweight\":2408,\"And\":2409,\"Ġwriting\":2410,\"Photo\":2411,\"ĠChristian\":2412,\"ob\":2413,\"Ġsport\":2414,\"Ġfigures\":2415,\"Ġtrust\":2416,\"Ġskills\":2417,\"Ġseat\":2418,\"Ġfaces\":2419,\"ck\":2420,\"Ġborn\":2421,\"Ġsuper\":2422,\"Ġfuel\":2423,\"Ġdel\":2424,\"Ġmeant\":2425,\"ica\":2426,\"Ġjustice\":2427,\"Ġspring\":2428,\"Ġkilling\":2429,\"Ġnegative\":2430,\"ĠRichard\":2431,\"Ġund\":2432,\"Ġfactors\":2433,\"Ġsigns\":2434,\"Ġlearned\":2435,\"ĠGame\":2436,\"Ġaudience\":2437,\"Ġdeliver\":2438,\"Ġillegal\":2439,\"Ġblue\":2440,\"Ġscreen\":2441,\"Ġremained\":2442,\"Ġannouncement\":2443,\"IN\":2444,\"Ġwaiting\":2445,\"Ġthanks\":2446,\"Ġimmigration\":2447,\"ĠFBI\":2448,\"Ġwarned\":2449,\"Ġmeasure\":2450,\"Ġdraw\":2451,\"Ġpositions\":2452,\"Ġdebut\":2453,\"ĠMedia\":2454,\"Ġallowing\":2455,\"air\":2456,\"hen\":2457,\"Ġmark\":2458,\"ys\":2459,\"Ġprepared\":2460,\"ĠVegas\":2461,\"ep\":2462,\"ice\":2463,\"2018\":2464,\"Ġdefensive\":2465,\"60\":2466,\"ĠBeach\":2467,\"Ġpulled\":2468,\"£\":2469,\"Ġlawyer\":2470,\"Ġcast\":2471,\"Ġsolution\":2472,\"Ġeyes\":2473,\"Ġmarketing\":2474,\"ĠFoundation\":2475,\"Ġrisks\":2476,\"ĠToday\":2477,\"za\":2478,\"Ġdraft\":2479,\"Ġice\":2480,\"26\":2481,\"ĠHar\":2482,\"ĠExecutive\":2483,\"Ġtruck\":2484,\"ions\":2485,\"ĠYour\":2486,\"ĠIreland\":2487,\"ĠJim\":2488,\"Ġha\":2489,\"Ġfear\":2490,\"Ġ36\":2491,\"UR\":2492,\"ĠFord\":2493,\"Ġwatching\":2494,\"ien\":2495,\"Ġstyle\":2496,\"ĠGood\":2497,\"Ġwearing\":2498,\"ĠHouston\":2499,\"Ġonto\":2500,\"Ġboost\":2501,\"Ġapplication\":2502,\"ĠDan\":2503,\"Ġspread\":2504,\"ĠDavis\":2505,\"Ġstrike\":2506,\"els\":2507,\"Ġwind\":2508,\"Ġinterested\":2509,\"Ġguard\":2510,\"Ġmission\":2511,\"Ġyourself\":2512,\"Ġoperation\":2513,\"Ġlarger\":2514,\"She\":2515,\"Ġseasons\":2516,\"28\":2517,\"27\":2518,\"Ġrespond\":2519,\"ci\":2520,\"ĠCentre\":2521,\"Our\":2522,\"Ġnames\":2523,\"Ġflight\":2524,\"Ġquarterback\":2525,\"Ġstandard\":2526,\"so\":2527,\"Ġsuggested\":2528,\"ĠMal\":2529,\"Ġolder\":2530,\"ini\":2531,\"Ġperhaps\":2532,\"ont\":2533,\"ĠInstitute\":2534,\"Ġmillions\":2535,\"Ġmental\":2536,\"ÃĤ\":2537,\"ga\":2538,\"Ġclients\":2539,\"Ġplease\":2540,\"Ġloan\":2541,\"Ġaware\":2542,\"ft\":2543,\"int\":2544,\"75\":2545,\"05\":2546,\"AY\":2547,\"ĠOut\":2548,\"Ġhair\":2549,\"ied\":2550,\"Ġseemed\":2551,\"ene\":2552,\"ty\":2553,\"NYSE\":2554,\"Ġoffensive\":2555,\"Ġtaxes\":2556,\"Ġinitial\":2557,\"ren\":2558,\"Ġseparate\":2559,\"la\":2560,\"ĠMiami\":2561,\"AC\":2562,\"Ġclearly\":2563,\"Ġfit\":2564,\"ĠCoast\":2565,\"Ġfirms\":2566,\"Ġpartners\":2567,\"Ġupcoming\":2568,\"Ġcold\":2569,\"Ġproposal\":2570,\"AT\":2571,\"Ġshut\":2572,\"ĠCommunity\":2573,\"Ġnature\":2574,\"ĠSal\":2575,\"Ġbottom\":2576,\"ting\":2577,\"ĠClick\":2578,\"Ġnice\":2579,\"ets\":2580,\"Ġhurt\":2581,\"itt\":2582,\"ama\":2583,\"Ġcarried\":2584,\"ĠCon\":2585,\"rd\":2586,\"Ġestate\":2587,\"ĠLas\":2588,\"ĠLaw\":2589,\"ng\":2590,\"Ġprotection\":2591,\"Ġproduce\":2592,\"Ġcurrency\":2593,\"Ġhappens\":2594,\"ĠPer\":2595,\"ney\":2596,\"ĠLong\":2597,\"Ġfellow\":2598,\"Ġcuts\":2599,\"Ġreading\":2600,\"ano\":2601,\"Ġproud\":2602,\"ost\":2603,\"ĠUN\":2604,\"ĠArizona\":2605,\"AD\":2606,\"Ġhelps\":2607,\"Ġwinter\":2608,\"Ġfinding\":2609,\"ĠGold\":2610,\"att\":2611,\"ĠWhy\":2612,\"Ġbasketball\":2613,\"lin\":2614,\"ĠCan\":2615,\"ĠBowl\":2616,\"ial\":2617,\"ĠAlex\":2618,\"200\":2619,\"AM\":2620,\"Ġpresence\":2621,\"Ġproduced\":2622,\"Ġdeveloping\":2623,\"Ġregarding\":2624,\"Ġdebate\":2625,\"Ġvice\":2626,\"ĠItaly\":2627,\"Ġsu\":2628,\"its\":2629,\"ator\":2630,\"Ġ34\":2631,\"Ġcomplex\":2632,\"Ġpresented\":2633,\"Ġresearchers\":2634,\"Ġslow\":2635,\"ya\":2636,\"Ġsanctions\":2637,\"Ġloved\":2638,\"Ġseek\":2639,\"Ġresponsibility\":2640,\"Ġadmitted\":2641,\"Ġalbum\":2642,\"Ġsolutions\":2643,\"Ġfacilities\":2644,\"ett\":2645,\"ĠGu\":2646,\"ĠWell\":2647,\"Ġlawmakers\":2648,\"Ġmiss\":2649,\"ful\":2650,\"ĠNick\":2651,\"'.\":2652,\"Ġfeels\":2653,\"Ġprime\":2654,\"Ġknowledge\":2655,\"Ġdeals\":2656,\"ĠTaylor\":2657,\"Ġsurvey\":2658,\"ĠFrancisco\":2659,\"Ġjoint\":2660,\"Ġwhom\":2661,\"Ġsit\":2662,\"01\":2663,\"Ġtr\":2664,\"Ġorganizations\":2665,\"ĠAvenue\":2666,\"ĠTheir\":2667,\"ĠTim\":2668,\"Ġrally\":2669,\"game\":2670,\"Ġbigger\":2671,\"Ġlawsuit\":2672,\"Ġrecorded\":2673,\"Ġfavorite\":2674,\"yard\":2675,\"Ġtransaction\":2676,\"Ġqu\":2677,\"oh\":2678,\"Ġinteresting\":2679,\"Ġinflation\":2680,\"ath\":2681,\"Ġstuff\":2682,\"Ġindustrial\":2683,\"ico\":2684,\"TS\":2685,\"Ġspeaking\":2686,\"Ġlosses\":2687,\"ID\":2688,\"ĠStadium\":2689,\"Ġstars\":2690,\"ĠWomen\":2691,\"ĠBlue\":2692,\"Ġwins\":2693,\"Ġdes\":2694,\"Ġcompetitive\":2695,\"ters\":2696,\"Ġpounds\":2697,\"Ġdirection\":2698,\"Ġinnings\":2699,\"ĠBest\":2700,\"Ġactor\":2701,\"Ġdangerous\":2702,\"Ġrequire\":2703,\"Ġplus\":2704,\"Ġsolid\":2705,\"Ġgeneration\":2706,\"Ġstrength\":2707,\"ĠMary\":2708,\"For\":2709,\"Ġplenty\":2710,\"ĠTeam\":2711,\"Ġinfluence\":2712,\"Ġfaced\":2713,\"Ġes\":2714,\"ĠIslamic\":2715,\"let\":2716,\"ĠDevelopment\":2717,\"Ġpath\":2718,\"Ġyouth\":2719,\"Ġcommitment\":2720,\"Ġbeautiful\":2721,\"ĠJack\":2722,\"ort\":2723,\"Ġten\":2724,\"Ġattend\":2725,\"ars\":2726,\"Ã³n\":2727,\"Ġviews\":2728,\"Ġeuros\":2729,\"Ġauthor\":2730,\"Ġcore\":2731,\"Ġsupporters\":2732,\"ĠiPhone\":2733,\"Ġfashion\":2734,\"Ġsmaller\":2735,\"Ġelected\":2736,\"Ġuniversity\":2737,\"Ġpicked\":2738,\"wa\":2739,\"Ġordered\":2740,\"ĠSc\":2741,\"ĠÅ\":2742,\"Ġlargely\":2743,\"+\":2744,\"ĠAttorney\":2745,\"Ġpaying\":2746,\"AR\":2747,\"Ġconnection\":2748,\"Ġsetting\":2749,\"Ġna\":2750,\"ĠRock\":2751,\"Ġrecovery\":2752,\"ew\":2753,\"Ġserving\":2754,\"Ġsurprise\":2755,\"Ġoccurred\":2756,\"Ġdivision\":2757,\"Ġtelling\":2758,\"Ġmargin\":2759,\"Ġ2020\":2760,\"Ġsister\":2761,\"ĠNBA\":2762,\"Ġvoted\":2763,\"Ġcon\":2764,\"By\":2765,\"Ġ49\":2766,\"Ġfoot\":2767,\"Ã¼\":2768,\"ĠTurkey\":2769,\"Ġamazing\":2770,\"Ġcombined\":2771,\"Ġappearance\":2772,\"Ġeasily\":2773,\"DAY\":2774,\"Ġnotes\":2775,\"ĠStart\":2776,\"Ġlanguage\":2777,\"Ġextremely\":2778,\"Ġcloudy\":2779,\"ĠLet\":2780,\"Ġdelivered\":2781,\"Ġimproved\":2782,\"Ġcollection\":2783,\"ĠPM\":2784,\"Ġestimates\":2785,\"Ġboys\":2786,\"izing\":2787,\"Ġtext\":2788,\"Ġcloser\":2789,\"Ġprotest\":2790,\"Ġprovince\":2791,\"Ġshop\":2792,\"Ġsmart\":2793,\"de\":2794,\"ĠSheriff\":2795,\"EN\":2796,\"Ġcorner\":2797,\"Ġpanel\":2798,\"Ġbooks\":2799,\"Ġsupported\":2800,\"Ġmentioned\":2801,\"ver\":2802,\"ĠMinistry\":2803,\"ĠPrince\":2804,\"ĠUSA\":2805,\"Ġreceiving\":2806,\"Ġchoose\":2807,\"ĠIN\":2808,\"ĠSpain\":2809,\"Ġsection\":2810,\"Ġconsidering\":2811,\"ĠCor\":2812,\"Ġwish\":2813,\"Ġwelcome\":2814,\"ĠConference\":2815,\"ere\":2816,\"ĠOfficer\":2817,\"Ġhoping\":2818,\"Ġportfolio\":2819,\"Ġstandards\":2820,\"Ġgrand\":2821,\"ĠReal\":2822,\"Ġsecure\":2823,\"ĠCorporation\":2824,\"ĠRep\":2825,\"ĠKelly\":2826,\"Ġstreets\":2827,\"Ġsitting\":2828,\"Ġslightly\":2829,\"ĠInvestment\":2830,\"99\":2831,\"ond\":2832,\"Ġunits\":2833,\"Ġvotes\":2834,\"Ġsegment\":2835,\"Ġchampionship\":2836,\"Ġsquad\":2837,\"iting\":2838,\"ron\":2839,\"®\":2840,\"Ġem\":2841,\"Ġtouch\":2842,\"Ġ38\":2843,\"Ġceremony\":2844,\"Ġdecide\":2845,\"Ġapproval\":2846,\"So\":2847,\"ĠPort\":2848,\"Ġsub\":2849,\"Ġsc\":2850,\"Ġrep\":2851,\"ĠWeek\":2852,\"Ġupper\":2853,\"Ġagree\":2854,\"ny\":2855,\"Ġmatches\":2856,\"ics\":2857,\"Ġtweeted\":2858,\"Ġheat\":2859,\"ĠGreat\":2860,\"Ġpenalty\":2861,\"Ġmass\":2862,\"Ġalongside\":2863,\"Ġherself\":2864,\"berg\":2865,\"Ġscience\":2866,\"Ġentered\":2867,\"Ġappeal\":2868,\"ĠPr\":2869,\"Ġfile\":2870,\"che\":2871,\"ĠReport\":2872,\"ĠThree\":2873,\"ĠNorthern\":2874,\"ĠJordan\":2875,\"Ġamid\":2876,\"Ġpace\":2877,\"Ġjail\":2878,\"Ġfinance\":2879,\"ĠYoung\":2880,\"32\":2881,\"Ġwilling\":2882,\"Ġconduct\":2883,\"ĠPar\":2884,\"Ġestablished\":2885,\"Ġreturns\":2886,\"Ġaid\":2887,\"Ġinternet\":2888,\"IA\":2889,\"29\":2890,\"Ġmeetings\":2891,\"Ġwarning\":2892,\"ĠCl\":2893,\"Ġcampus\":2894,\"Most\":2895,\"ĠFund\":2896,\"ĠWilliam\":2897,\"ĠJapanese\":2898,\"Ġconsensus\":2899,\"Ġbrain\":2900,\"!\\\"\":2901,\"Ġpoll\":2902,\"Ġtech\":2903,\"Ġtrend\":2904,\"Ġpotentially\":2905,\"Ġreduced\":2906,\"ĠShow\":2907,\"Ġ37\":2908,\"Ġhappening\":2909,\"ĠBrazil\":2910,\"pl\":2911,\"ĠCal\":2912,\"Ġcovered\":2913,\"Ġenter\":2914,\"TV\":2915,\"Ġcatch\":2916,\"foot\":2917,\"Ġunion\":2918,\"Ġexpansion\":2919,\"ĠSingapore\":2920,\"ĠDetroit\":2921,\"Ġattended\":2922,\"ats\":2923,\"Ġnewspaper\":2924,\"ĠDivision\":2925,\"news\":2926,\"Ġcap\":2927,\"Ġremoved\":2928,\"Ġ48\":2929,\"ĠRoyal\":2930,\"Ġwindow\":2931,\"Ġparking\":2932,\"Ġdark\":2933,\"Ġstanding\":2934,\"Ġupdate\":2935,\"Ġagent\":2936,\"Ġtransfer\":2937,\"ĠArmy\":2938,\"Ġuses\":2939,\"80\":2940,\"ĠTe\":2941,\"Ġintroduced\":2942,\"Ġmale\":2943,\"ĠSouthern\":2944,\"Ġratings\":2945,\"Ġisland\":2946,\"ĠMiller\":2947,\"Ġteachers\":2948,\"Ġadvice\":2949,\"Ġfamiliar\":2950,\"uf\":2951,\"Ġsought\":2952,\"Ġpor\":2953,\"ĠEric\":2954,\"Ġda\":2955,\"Ġideas\":2956,\"uh\":2957,\"Ġsixth\":2958,\"Ġtalent\":2959,\"ĠImage\":2960,\"ering\":2961,\"run\":2962,\"ments\":2963,\"Ġconducted\":2964,\"300\":2965,\"Ġurged\":2966,\"Ġdiscovered\":2967,\"Ġpl\":2968,\"Ġunderstanding\":2969,\"Ġoffense\":2970,\"Ġsecretary\":2971,\"Ġsk\":2972,\"Ġloans\":2973,\"ĠGr\":2974,\"Ġapplications\":2975,\"Ġcrude\":2976,\"go\":2977,\"ĠInstead\":2978,\"Ġopinion\":2979,\"Ġdoubt\":2980,\"ey\":2981,\"Ġdis\":2982,\"31\":2983,\"Ġexperienced\":2984,\"Ġleg\":2985,\"ĠCleveland\":2986,\"ven\":2987,\"Ġfailure\":2988,\"market\":2989,\"ack\":2990,\"Ġdecline\":2991,\"Ġchanging\":2992,\"Ġ300\":2993,\"Ġdefence\":2994,\"ĠBrian\":2995,\"Ġdelivery\":2996,\"Ġmarried\":2997,\"Ġdeclared\":2998,\"Ġpull\":2999,\"Ġlimit\":3000,\"ĠMORE\":3001,\"Ġdefeat\":3002,\"Ġexpand\":3003,\"ĠColorado\":3004,\"ĠRob\":3005,\"iss\":3006,\"Ġworse\":3007,\"Ġperform\":3008,\"ising\":3009,\"Ġ2007\":3010,\"ĠDel\":3011,\"Ġsurgery\":3012,\"Ġeasier\":3013,\"Ġmaintain\":3014,\"ĠEx\":3015,\"Ġtied\":3016,\"Ġeast\":3017,\"Ġuser\":3018,\"ola\":3019,\"Ġprogramme\":3020,\"Ġmanufacturing\":3021,\"Ġhitting\":3022,\"Ġx\":3023,\"Ġskin\":3024,\"Ġartist\":3025,\"Ġtells\":3026,\"Ġnearby\":3027,\"ĠDaniel\":3028,\"ĠPower\":3029,\"Ġdetermined\":3030,\"Ġactual\":3031,\"Ġtreated\":3032,\"Ġlived\":3033,\"Ġcomputer\":3034,\"Ġcool\":3035,\"oo\":3036,\"ĠPl\":3037,\"Ġeffects\":3038,\"Ġenvironmental\":3039,\"ĠMorgan\":3040,\"Ġflow\":3041,\"Ġachieve\":3042,\"ĠBell\":3043,\"Ġtesting\":3044,\"ĠBob\":3045,\"Ġwhatever\":3046,\"ĠBecause\":3047,\"US\":3048,\"ĠHollywood\":3049,\"Ġconflict\":3050,\"Ġwalking\":3051,\"ĠJudge\":3052,\"ĠAlabama\":3053,\"Ġaircraft\":3054,\"Ġte\":3055,\"well\":3056,\"Ġgoods\":3057,\"Ġidentify\":3058,\"Ġassociated\":3059,\"ĠVer\":3060,\"ĠEducation\":3061,\"Ġairport\":3062,\"IL\":3063,\"Ġfalling\":3064,\"Ġgiant\":3065,\"ĠMa\":3066,\"ĠMedical\":3067,\"Ġride\":3068,\"Ġden\":3069,\"º\":3070,\"ĠJose\":3071,\"Ġwest\":3072,\"ĠPacific\":3073,\"Ġvisitors\":3074,\"ĠWatch\":3075,\"ĠNations\":3076,\"Ġgains\":3077,\"Ġschedule\":3078,\"34\":3079,\"ĠExchange\":3080,\"Ġpayments\":3081,\"ĠII\":3082,\"70\":3083,\"No\":3084,\"ĠSyrian\":3085,\"ĠAdam\":3086,\"Ġne\":3087,\"Ġpartnership\":3088,\"Ġbl\":3089,\"ĠGeorgia\":3090,\"Ġsites\":3091,\"Ġmodels\":3092,\"Ġdegree\":3093,\"Ġdetermine\":3094,\"ĠWilson\":3095,\"Ġcontest\":3096,\"Ġprofessor\":3097,\"ĠChelsea\":3098,\"Ġmeaning\":3099,\"ĠGames\":3100,\"ĠTrust\":3101,\"ĠAsian\":3102,\"33\":3103,\"Ġlink\":3104,\"ĠUp\":3105,\"Ġholds\":3106,\"ĠTop\":3107,\"ĠItalian\":3108,\"ord\":3109,\"ĠKansas\":3110,\"Ġfarmers\":3111,\"Ġextended\":3112,\"Ġbirth\":3113,\"Ġreform\":3114,\"Ġrelations\":3115,\"Ġwrite\":3116,\"Ġsupporting\":3117,\"55\":3118,\"ita\":3119,\"Ġnotice\":3120,\"ster\":3121,\"Ġanimals\":3122,\"ĠJersey\":3123,\"Ġarm\":3124,\"ĠForeign\":3125,\"ĠLife\":3126,\"Ġtruly\":3127,\"ĠOnce\":3128,\"ĠMayor\":3129,\"ĠFree\":3130,\"ĠAgency\":3131,\"ĠWood\":3132,\"Ġpassing\":3133,\"DA\":3134,\"Ġ52\":3135,\"Ġmoves\":3136,\"Ġcom\":3137,\"house\":3138,\"ĠIts\":3139,\"Ġmarijuana\":3140,\"ines\":3141,\"Ġveteran\":3142,\"Ġvariety\":3143,\"ki\":3144,\"ff\":3145,\"amb\":3146,\"Ġlisted\":3147,\"Ġpushed\":3148,\"Ġvolume\":3149,\"Ġincreasingly\":3150,\"Ġkick\":3151,\"Ġrock\":3152,\"ank\":3153,\"Ġfees\":3154,\"Ġenable\":3155,\"Ġimages\":3156,\"Ġtruth\":3157,\"Ġministry\":3158,\"Ġrare\":3159,\"ĠDallas\":3160,\"ĠMinnesota\":3161,\"Ġcontributed\":3162,\"ĠCharles\":3163,\"Ġpercentage\":3164,\"Ġtechnical\":3165,\"ĠApp\":3166,\"Ġassistant\":3167,\"Ġinterests\":3168,\"Ġimmediate\":3169,\"38\":3170,\"ĠTown\":3171,\"Ġclosing\":3172,\"ĠAnthony\":3173,\"Ġsouthern\":3174,\"ase\":3175,\"ĠPutin\":3176,\"ĠForce\":3177,\"ba\":3178,\"Ġrefused\":3179,\"ĠStill\":3180,\"ix\":3181,\"ĠCol\":3182,\"Ġmaterials\":3183,\"Ġstructure\":3184,\"Ġdriven\":3185,\"Ġpatient\":3186,\"Ġbroken\":3187,\"Ġradio\":3188,\"Ġscale\":3189,\"Ġreplace\":3190,\"Ġ39\":3191,\"ĠLand\":3192,\"Ġdeputy\":3193,\"und\":3194,\"Ġcolor\":3195,\"OS\":3196,\"Ġroads\":3197,\"Ġcorruption\":3198,\"ĠRose\":3199,\"Ġemployee\":3200,\"ĠWater\":3201,\"Ġseats\":3202,\"Ġwalked\":3203,\"ec\":3204,\"Ġcents\":3205,\"Ġchain\":3206,\"Ġpayment\":3207,\"ĠAndroid\":3208,\"eb\":3209,\"Ġcommission\":3210,\"Ġthrow\":3211,\"Ġcount\":3212,\"Ġaccident\":3213,\"Ġexpensive\":3214,\"ered\":3215,\"ĠYes\":3216,\"ĠLouis\":3217,\"Ġstudies\":3218,\"Ġinvestigating\":3219,\"Ġcentury\":3220,\"Ġdiscussion\":3221,\"Ġinter\":3222,\"DAQ\":3223,\"ĠBefore\":3224,\"Ġinitially\":3225,\"*\":3226,\"Ġinvestments\":3227,\"Ġmulti\":3228,\"Ġtight\":3229,\"Ġconfident\":3230,\"Ġcounter\":3231,\"ĠQu\":3232,\"Ġgovernments\":3233,\"Ġarmed\":3234,\"Ġsuit\":3235,\"Ġrow\":3236,\"Ġlocations\":3237,\"Ġepisode\":3238,\"itch\":3239,\"Ġyounger\":3240,\"Ġfestival\":3241,\"Ġpitch\":3242,\"ĠOF\":3243,\"Ġtalked\":3244,\"ca\":3245,\"Ġprotests\":3246,\"Ġtargets\":3247,\"90\":3248,\"Ġoriginally\":3249,\"Ġsinger\":3250,\"Ġjourney\":3251,\"ug\":3252,\"Ġapply\":3253,\"Ġteacher\":3254,\"Ġchances\":3255,\"):\":3256,\"Ġdeaths\":3257,\"isation\":3258,\"ĠStephen\":3259,\"Ġcode\":3260,\"ĠChampionship\":3261,\"ĠJason\":3262,\"ĠAT\":3263,\"Ġaccept\":3264,\"ĠSeries\":3265,\"Ġvalues\":3266,\"Ġbed\":3267,\"ĠHarry\":3268,\"Ġflat\":3269,\"Ġtools\":3270,\"Ġpublicly\":3271,\"37\":3272,\"Ġpointed\":3273,\"ĠGolden\":3274,\"ps\":3275,\"Ġunable\":3276,\"ants\":3277,\"Ġestimate\":3278,\"Ġwarm\":3279,\"Ġbasic\":3280,\"ern\":3281,\"Ġraising\":3282,\"ĠRelated\":3283,\"Ġultimately\":3284,\"Ġnorthern\":3285,\"Ġplane\":3286,\"ĠVice\":3287,\"ĠRaj\":3288,\"ĠJustin\":3289,\"anc\":3290,\"Ġbrings\":3291,\"ĠArt\":3292,\"OT\":3293,\"Ġshift\":3294,\"ĠBBC\":3295,\"ĠSu\":3296,\"BS\":3297,\"Ġbag\":3298,\"Ġdoctor\":3299,\"Ġfill\":3300,\"Ġdowntown\":3301,\"Ġpossibility\":3302,\"ĠAg\":3303,\"Ġest\":3304,\"44\":3305,\"Ġstruggling\":3306,\"Ġlinked\":3307,\"Ġtickets\":3308,\"ĠJay\":3309,\"ĠCall\":3310,\"Ġstands\":3311,\"Ġwedding\":3312,\"Ġresident\":3313,\"eng\":3314,\"Ġleads\":3315,\"Ġadvance\":3316,\"ĠAtlanta\":3317,\"Ġtie\":3318,\"Ġadvanced\":3319,\"pt\":3320,\"burg\":3321,\"ĠEarlier\":3322,\"ĠSw\":3323,\"ĠZealand\":3324,\"Ġexercise\":3325,\"ĠAM\":3326,\"Ġaffect\":3327,\"Ġpossession\":3328,\"Ġinvolving\":3329,\"Ġ42\":3330,\"Ġwriter\":3331,\"ĠBeijing\":3332,\"Ġdoctors\":3333,\"Ġobviously\":3334,\"Ġer\":3335,\"ĠOlympic\":3336,\"Ġ75\":3337,\"ĠKhan\":3338,\"ĠFort\":3339,\"app\":3340,\"like\":3341,\"Ġsea\":3342,\"ock\":3343,\"Ġmix\":3344,\"ĠIraq\":3345,\"ĠMuslim\":3346,\"ĠFinally\":3347,\"Ġcontinuing\":3348,\"Ġpr\":3349,\"ĠKe\":3350,\"ĠJoseph\":3351,\"Ġexpects\":3352,\"Ġinstitutions\":3353,\"Ġconservative\":3354,\"own\":3355,\"ĠChairman\":3356,\"Ġreturning\":3357,\".-\":3358,\"Ġstood\":3359,\"Ġvision\":3360,\"ess\":3361,\"Ġadults\":3362,\"Ġyield\":3363,\"Ġprove\":3364,\"Ġorders\":3365,\"Ġdream\":3366,\"36\":3367,\"related\":3368,\"Ġsl\":3369,\"Ġeverybody\":3370,\"ui\":3371,\"Ġrepresents\":3372,\"Ġdiscussed\":3373,\"Ġbecomes\":3374,\"Ġvillage\":3375,\"CC\":3376,\"Ġnegotiations\":3377,\"ĠPhiladelphia\":3378,\"Ġcelebrate\":3379,\"Ġfarm\":3380,\"Ã§\":3381,\"Ġregistered\":3382,\"ĠGovernor\":3383,\"OL\":3384,\"ĠMon\":3385,\"Ġfiling\":3386,\"04\":3387,\"SE\":3388,\"ĠAssembly\":3389,\"Ġactress\":3390,\"Ġsi\":3391,\"Ġthank\":3392,\"Ġheading\":3393,\"ĠWho\":3394,\"Ġfamous\":3395,\"Ġconsecutive\":3396,\"Ġmarriage\":3397,\"ette\":3398,\"NAS\":3399,\"acks\":3400,\"ĠPlease\":3401,\"ĠDiego\":3402,\"Ġbaseball\":3403,\"ĠMoore\":3404,\"Ġties\":3405,\"Ġcarrying\":3406,\"que\":3407,\"Ġturning\":3408,\"ĠMcC\":3409,\"ĠKen\":3410,\"OR\":3411,\"ĠStock\":3412,\"Ġbuildings\":3413,\"49\":3414,\"ĠVan\":3415,\"39\":3416,\"ĠSeattle\":3417,\"Ġwild\":3418,\"Ġcrew\":3419,\"Ġroute\":3420,\"ĠTime\":3421,\"Ġtonight\":3422,\"Ġmoments\":3423,\"Ġvideos\":3424,\"Ġinternal\":3425,\"ĠLiverpool\":3426,\"port\":3427,\"Ġchair\":3428,\"Ġrival\":3429,\"ĠScotland\":3430,\"round\":3431,\"ith\":3432,\"Ġbreaking\":3433,\"Ġvoting\":3434,\"ically\":3435,\"Ġproducer\":3436,\"ĠLove\":3437,\"Ġremove\":3438,\"PA\":3439,\"Ġasset\":3440,\"Ġrequires\":3441,\"Ġsigning\":3442,\"ages\":3443,\"Ġimpressive\":3444,\"ĠIrish\":3445,\"Ġauthority\":3446,\"Ġruled\":3447,\"Ġaimed\":3448,\"Ġcaptain\":3449,\"AG\":3450,\"Ġplants\":3451,\"ĠAnderson\":3452,\"ĠSpanish\":3453,\"Ġbanking\":3454,\"Ġthreats\":3455,\"Ġsuspended\":3456,\"Ġtests\":3457,\"Ġreligious\":3458,\"Ġelectric\":3459,\"ĠREAD\":3460,\"Ġstrategic\":3461,\"Ġsplit\":3462,\"ex\":3463,\"Ġpractices\":3464,\"ĠIsraeli\":3465,\"ĠArabia\":3466,\"ĠMoscow\":3467,\"Ġfranchise\":3468,\"Ġcustody\":3469,\"ĠOld\":3470,\"Ġrequirements\":3471,\"Ġquarterly\":3472,\"Ġcomfortable\":3473,\"Ġcrimes\":3474,\"Ġheaded\":3475,\"Ġnewsletter\":3476,\"Ġanimal\":3477,\"Ġregulations\":3478,\"long\":3479,\"ĠCNN\":3480,\"Ġassists\":3481,\"Ġshopping\":3482,\"ĠGov\":3483,\"ĠSecurities\":3484,\"Ġassistance\":3485,\"Ġnor\":3486,\"Ġrelatively\":3487,\"Ġincreases\":3488,\"Ġgenerally\":3489,\"Ġ55\":3490,\"Ġgained\":3491,\"Ġ41\":3492,\"Ġpictures\":3493,\"gan\":3494,\"Ġpop\":3495,\"Ġupdates\":3496,\"ĠRepublic\":3497,\"Ġrebounds\":3498,\"ĠPatrick\":3499,\"Ġrelief\":3500,\"Ġacting\":3501,\"ĠFestival\":3502,\"Ġ2006\":3503,\"Ġboss\":3504,\"Ġtypes\":3505,\"65\":3506,\"ĠYet\":3507,\"Ġpurpose\":3508,\"ning\":3509,\"Ġmatters\":3510,\"Ġcompete\":3511,\"ball\":3512,\"ĠRam\":3513,\"Ġsw\":3514,\"ĠFollowing\":3515,\"ĠBush\":3516,\"Ġtroops\":3517,\"Ġsupposed\":3518,\"Ġfreedom\":3519,\"Ġfeatured\":3520,\"Ġstorage\":3521,\"ĠInformation\":3522,\"ĠHong\":3523,\"Ġgolf\":3524,\"Ġagents\":3525,\"Ġfraud\":3526,\"Ġminimum\":3527,\"Ġartists\":3528,\"Ġeat\":3529,\"high\":3530,\"ĠFormer\":3531,\"ĠKong\":3532,\"ĠJosh\":3533,\"ĠDelhi\":3534,\"Ġshowers\":3535,\"ĠAcademy\":3536,\"Ġapartment\":3537,\"Ġvan\":3538,\"Ġfish\":3539,\"oe\":3540,\"Ġfilms\":3541,\"ĠBo\":3542,\"Ġedge\":3543,\"Ġpossibly\":3544,\"Ġtweet\":3545,\"09\":3546,\"Ġresolution\":3547,\"jo\":3548,\"Ġkill\":3549,\"Ġ44\":3550,\"Ġcell\":3551,\"Ġscheme\":3552,\"Ġth\":3553,\"Ġbonds\":3554,\"Ġentry\":3555,\"Ġsecret\":3556,\"Ġ43\":3557,\"Ġending\":3558,\"Ġweren\":3559,\"ĠCredit\":3560,\"ĠLive\":3561,\"Ġretired\":3562,\"Ġmachine\":3563,\"Ġsummit\":3564,\"Ġsharing\":3565,\"Ġacquired\":3566,\"Ġera\":3567,\"Ġwear\":3568,\"ical\":3569,\"07\":3570,\"Ġexciting\":3571,\"li\":3572,\"BC\":3573,\"ĠSocial\":3574,\"Ġhistoric\":3575,\"ĠChe\":3576,\"ĠLewis\":3577,\"ira\":3578,\"Ġstolen\":3579,\"ĠSpeaking\":3580,\"Ġsleep\":3581,\"Ġspokeswoman\":3582,\"week\":3583,\"Ġpurchased\":3584,\"Ġimportance\":3585,\"EC\":3586,\"Ġends\":3587,\"Ġdress\":3588,\"Ġparliament\":3589,\"ĠCruz\":3590,\"Ġcards\":3591,\"hi\":3592,\"ĠEmail\":3593,\"Ġrepresent\":3594,\"Ġbrands\":3595,\"ĠSenior\":3596,\"Ġparticipants\":3597,\"Ġfly\":3598,\"Ġidentity\":3599,\"ĠHam\":3600,\"ĠSky\":3601,\"ĳ\":3602,\"SA\":3603,\"Ġpromised\":3604,\"Ġtrouble\":3605,\"Ġsuffering\":3606,\"Ġleaves\":3607,\"Ġsuggest\":3608,\"Sh\":3609,\"Ġbusy\":3610,\"Ġproperties\":3611,\"Ġworldwide\":3612,\"Ġcloud\":3613,\"ĠSEC\":3614,\"Ġclosely\":3615,\"Ġmanage\":3616,\"Ġnumerous\":3617,\"Ġbackground\":3618,\"ĠExpress\":3619,\"Ġ65\":3620,\"ĠTony\":3621,\"ĠMadrid\":3622,\"ev\":3623,\"der\":3624,\"Ġsignificantly\":3625,\"Ġalternative\":3626,\"Ġship\":3627,\"head\":3628,\"ators\":3629,\"Ġdinner\":3630,\"ax\":3631,\"SC\":3632,\"Ġcriticism\":3633,\"ĠMah\":3634,\"ĠMin\":3635,\"rie\":3636,\"ĠTour\":3637,\"Ġbench\":3638,\"Ġadds\":3639,\"Ġseriously\":3640,\"star\":3641,\"ĠJournal\":3642,\"ĠDi\":3643,\"ali\":3644,\"Ġsentence\":3645,\"ĠSeveral\":3646,\"Ġmayor\":3647,\"ati\":3648,\"Ġsuggests\":3649,\"Ġbehavior\":3650,\"Ġstronger\":3651,\"ĠFood\":3652,\"Ġclient\":3653,\"not\":3654,\"ĠPrice\":3655,\"Ġtargeted\":3656,\"ĠSingh\":3657,\"ĠNetwork\":3658,\"Ġprosecutors\":3659,\"Ġdirected\":3660,\"ĠDemocrat\":3661,\"bl\":3662,\"ues\":3663,\"ĠFamily\":3664,\"Ġconnected\":3665,\"ĠChampions\":3666,\"Ġroughly\":3667,\"Ġabsolutely\":3668,\"08\":3669,\"Ġpassengers\":3670,\"Ã¶\":3671,\"ĠSpecial\":3672,\"Ġcoast\":3673,\"Ġcomplaint\":3674,\"Ġ400\":3675,\"ĠEm\":3676,\"ves\":3677,\"Ġdogs\":3678,\"Ġhandle\":3679,\"Ġotherwise\":3680,\"Ġsees\":3681,\"Ġticket\":3682,\"ĠAward\":3683,\"All\":3684,\"Ġtask\":3685,\"Ġsongs\":3686,\"ĠAmong\":3687,\"Ġdedicated\":3688,\"Ġsteel\":3689,\"looking\":3690,\"Ġshortly\":3691,\"Ġtackle\":3692,\"ative\":3693,\"Ġminor\":3694,\"Ã¢\":3695,\"Ġprovider\":3696,\"vers\":3697,\"use\":3698,\"ives\":3699,\"Ġtypically\":3700,\"Ġarms\":3701,\"ĠAnt\":3702,\"ĠIS\":3703,\"Ġjump\":3704,\"ĠÂ©\":3705,\"47\":3706,\"aff\":3707,\"Ġmonthly\":3708,\"ĠMicrosoft\":3709,\"ĠCBS\":3710,\"Ġthreatened\":3711,\"Ġhonor\":3712,\"ĠMo\":3713,\"42\":3714,\"Ġinning\":3715,\"Ġpool\":3716,\"Ġhealthcare\":3717,\"ĠStory\":3718,\"ĠTennessee\":3719,\"Ġpromote\":3720,\"EL\":3721,\"Ġemotional\":3722,\"Ġpe\":3723,\"Ġfactor\":3724,\"Ġinvestigators\":3725,\"Ľ\":3726,\"ĠBack\":3727,\"ĠProject\":3728,\"Ġcu\":3729,\"side\":3730,\"Ġmessages\":3731,\"TH\":3732,\"eg\":3733,\"Ġexperiences\":3734,\"Ġcausing\":3735,\"Ġjoining\":3736,\"Ġpackage\":3737,\"Ġbodies\":3738,\"Ġlots\":3739,\"ĠHarris\":3740,\"Ġcl\":3741,\"ĠInternet\":3742,\"free\":3743,\"Ġperformed\":3744,\"Ġpieces\":3745,\"buy\":3746,\"Ġcaption\":3747,\"Ġweb\":3748,\"Ġcontracts\":3749,\"At\":3750,\"Ġattempted\":3751,\"Ġunlikely\":3752,\"Ġclick\":3753,\"Ġinvest\":3754,\"IM\":3755,\"ĠView\":3756,\"Ġneighborhood\":3757,\"Ġring\":3758,\"ĠFour\":3759,\"ail\":3760,\"46\":3761,\"One\":3762,\"Ġnative\":3763,\"CH\":3764,\"OM\":3765,\"Ġalcohol\":3766,\"ĠVal\":3767,\"Ġcharacters\":3768,\"ĠPat\":3769,\"Ġpoliticians\":3770,\"ĠMag\":3771,\"Ġbegins\":3772,\"ĠAk\":3773,\"Ġlos\":3774,\"Ġpersonnel\":3775,\"Ġenjoyed\":3776,\"ĠTechnology\":3777,\"Ġsun\":3778,\"ĠIT\":3779,\"Ġdocument\":3780,\"Ġdeficit\":3781,\"Ġcoalition\":3782,\"Ġmemory\":3783,\"Ġpushing\":3784,\"any\":3785,\"ified\":3786,\"Ġfounder\":3787,\"Ġ2000\":3788,\"2017\":3789,\"Ġvisited\":3790,\"ĠThough\":3791,\"ph\":3792,\"Ġsoft\":3793,\"Ġflag\":3794,\"Ġmom\":3795,\"inch\":3796,\"ĠSamsung\":3797,\"Ġapps\":3798,\"Ġtouchdown\":3799,\"ĠCare\":3800,\"ĠMrs\":3801,\"Ġredistributed\":3802,\"Ġencourage\":3803,\"ched\":3804,\"Ġtend\":3805,\"Ġregions\":3806,\"pp\":3807,\"IP\":3808,\"br\":3809,\"ush\":3810,\"Ġargued\":3811,\"Ġjunior\":3812,\"BA\":3813,\"Ġsevere\":3814,\"ĠNIGHT\":3815,\"Ġdef\":3816,\"Ġsurrounding\":3817,\"48\":3818,\"Ġengine\":3819,\"Ġfilled\":3820,\"Ġseventh\":3821,\"Ġbattery\":3822,\"ĠAllen\":3823,\"Ġguidance\":3824,\"Ġroll\":3825,\"Ġrural\":3826,\"Ġexpert\":3827,\"Ġconvicted\":3828,\"Ġlikes\":3829,\"ĠRo\":3830,\"Ġgrown\":3831,\"Ġretirement\":3832,\"Ġintended\":3833,\"Ġmis\":3834,\"Ġarmy\":3835,\"Ġdance\":3836,\"ĠThank\":3837,\"Ġent\":3838,\"Ġoutlook\":3839,\"Ġpara\":3840,\"Ġdry\":3841,\"ĠTO\":3842,\"era\":3843,\"Ġwaste\":3844,\"Ġfaster\":3845,\"ĠEagles\":3846,\"TA\":3847,\"ĠFrank\":3848,\"Ã\":3849,\"LE\":3850,\"ura\":3851,\"ko\":3852,\"ao\":3853,\"Ġdistribution\":3854,\"Ġimprovement\":3855,\"Ġplayoff\":3856,\"Ġacquisition\":3857,\"ĠCH\":3858,\"Ġtomorrow\":3859,\"Ġstruggle\":3860,\"ĠHuman\":3861,\"Ġnewly\":3862,\"oon\":3863,\"ĠNe\":3864,\"con\":3865,\"sc\":3866,\"Ġunless\":3867,\"Ġtransition\":3868,\"ten\":3869,\"ĠInter\":3870,\"Ġequal\":3871,\"Ġrec\":3872,\"Ġappointed\":3873,\"Ġwake\":3874,\"ĠEarth\":3875,\"ose\":3876,\"ĠEastern\":3877,\"Ġsoldiers\":3878,\"ĠParliament\":3879,\"Ġsets\":3880,\"Ġattempts\":3881,\"ĠIllinois\":3882,\"Ġrevenues\":3883,\"ĠWil\":3884,\"Ġheads\":3885,\"Ġprepare\":3886,\"Ġpriority\":3887,\"PS\":3888,\"ĠJo\":3889,\"ĠNBC\":3890,\"Ġtherefore\":3891,\"yn\":3892,\"Ġinitiative\":3893,\"ct\":3894,\"Ġcoffee\":3895,\"ĠFair\":3896,\"43\":3897,\"den\":3898,\"form\":3899,\"ova\":3900,\"Ġappropriate\":3901,\"ĠPlay\":3902,\"Ġaccepted\":3903,\"Ġcreative\":3904,\"Ġfollows\":3905,\"Ġrescue\":3906,\"Ġtree\":3907,\"With\":3908,\"ĠNetflix\":3909,\"ĠFootball\":3910,\"Ġsurprised\":3911,\"Ġlowest\":3912,\"800\":3913,\"amp\":3914,\"Ġworried\":3915,\"mar\":3916,\"ran\":3917,\"Ġvisiting\":3918,\"Ġselected\":3919,\"ĠMusic\":3920,\"ĠAnn\":3921,\"Ġexplain\":3922,\"ging\":3923,\"Ġwidely\":3924,\"Ġsquare\":3925,\"Ġtrends\":3926,\"Ġimproving\":3927,\"ĠHead\":3928,\"ĠQueen\":3929,\"ĠSociety\":3930,\"Ġcutting\":3931,\"ĠGOP\":3932,\"03\":3933,\"',\":3934,\"ET\":3935,\"ĠDrive\":3936,\"oll\":3937,\"ato\":3938,\"ĠSea\":3939,\"Ġjury\":3940,\"ĠRights\":3941,\"Ġinvestor\":3942,\"ĠABC\":3943,\"Ġtool\":3944,\"ĠAre\":3945,\"Ġrejected\":3946,\"Ġemerging\":3947,\"Ġcounts\":3948,\"Ġnations\":3949,\"Ġfalse\":3950,\"Ġtreat\":3951,\"va\":3952,\"Ġweak\":3953,\"ĠHighway\":3954,\"down\":3955,\"Ġstruggled\":3956,\"ĠMP\":3957,\"Ġguests\":3958,\"Ġgender\":3959,\"Ġhouses\":3960,\"rit\":3961,\"ĠWild\":3962,\"Ġstreak\":3963,\"uc\":3964,\"ĠReserve\":3965,\"ĠRatings\":3966,\"alt\":3967,\"Ġgreatest\":3968,\"Ġlawyers\":3969,\"Ġreaching\":3970,\"Ġtemperatures\":3971,\"To\":3972,\"Ġoutstanding\":3973,\"Ġpasses\":3974,\"Ġfaith\":3975,\"inc\":3976,\"Ġcr\":3977,\"Ġinformed\":3978,\"oz\":3979,\"Ġtrees\":3980,\"Ġsending\":3981,\"Ġ150\":3982,\"bo\":3983,\"Ġwine\":3984,\"ros\":3985,\"Ġsuspected\":3986,\"Ġrepeatedly\":3987,\"Ġhat\":3988,\"Ġshape\":3989,\"ĠWh\":3990,\"Ġassist\":3991,\"Ġstress\":3992,\"Ġfeed\":3993,\"ark\":3994,\"ored\":3995,\"Ġwatched\":3996,\"Ġincredible\":3997,\"cl\":3998,\"nt\":3999,\"Ġentertainment\":4000,\"ih\":4001,\"Ġbeauty\":4002,\"Ġbi\":4003,\"ĠLocal\":4004,\"Ġsat\":4005,\"41\":4006,\"Ġbroad\":4007,\"Ġheavily\":4008,\"Ġengaged\":4009,\"Ġspecifically\":4010,\"ĠMen\":4011,\"ĠRoss\":4012,\"Ġ2005\":4013,\"ST\":4014,\"95\":4015,\"Ġdownload\":4016,\"400\":4017,\"Ġsentenced\":4018,\"ĠCatholic\":4019,\"ĠOklahoma\":4020,\"Ġthrew\":4021,\"Ġworry\":4022,\"Ġimp\":4023,\"Ġdrove\":4024,\"Ġcolleagues\":4025,\"Ġagenda\":4026,\"64\":4027,\"ĠEach\":4028,\"Ġfee\":4029,\"New\":4030,\"ium\":4031,\"Ġspokesperson\":4032,\"Ġbills\":4033,\"Ġ47\":4034,\"ĠAfghanistan\":4035,\"Ġinvited\":4036,\"ĠYouTube\":4037,\"Ġanniversary\":4038,\"Ġdozen\":4039,\"ram\":4040,\"ĠOnly\":4041,\"Ġemployment\":4042,\"Getty\":4043,\"Ġgap\":4044,\"Ġsweet\":4045,\"ĠLittle\":4046,\"Ġinf\":4047,\"ying\":4048,\"Ġglass\":4049,\"Ġclasses\":4050,\"Ġcoal\":4051,\"ĠSub\":4052,\"Ġduty\":4053,\"CA\":4054,\"Ġcoaches\":4055,\"Â\":4056,\"anna\":4057,\"ĠSk\":4058,\"Ġ46\":4059,\"ison\":4060,\"ille\":4061,\"ĠST\":4062,\"ric\":4063,\"Ġparticipate\":4064,\"Ġequ\":4065,\"Ġrich\":4066,\"Ġrespectively\":4067,\"Ġexpenses\":4068,\"Ġcombination\":4069,\"right\":4070,\"Ġshareholders\":4071,\"Ġturns\":4072,\"Ġearn\":4073,\"Ġ51\":4074,\"ured\":4075,\"Ġdrink\":4076,\"ĠKar\":4077,\"ĠShares\":4078,\"ĠMid\":4079,\"ĠGetty\":4080,\"Ġbridge\":4081,\"lo\":4082,\"Ġinspired\":4083,\"Ġsurface\":4084,\"Ġgift\":4085,\"ence\":4086,\"Ġchallenging\":4087,\"Ġoffices\":4088,\"Ġsuspects\":4089,\"ĠFinance\":4090,\"Ġab\":4091,\"bound\":4092,\"Ġmomentum\":4093,\"Ġbacked\":4094,\"Ġparent\":4095,\"Ġcrucial\":4096,\"ave\":4097,\"Ġdealing\":4098,\"Ġregulatory\":4099,\"Ġapparently\":4100,\"ĠMat\":4101,\"Ġapart\":4102,\"Ġport\":4103,\"ole\":4104,\"Ġbeach\":4105,\"Ġcultural\":4106,\"Ġinstitutional\":4107,\"Ġbeating\":4108,\"ĠIowa\":4109,\"ĠAli\":4110,\"67\":4111,\"Ġje\":4112,\"ays\":4113,\"Ġweekly\":4114,\"Ġbirthday\":4115,\"Ġpipeline\":4116,\"Ġknee\":4117,\"Ġsolar\":4118,\"ĠPe\":4119,\"Ġcategory\":4120,\"ĠArea\":4121,\"ky\":4122,\"ures\":4123,\"06\":4124,\"ĠBall\":4125,\"Ġsemi\":4126,\"ĠHamilton\":4127,\"hip\":4128,\"ĠPh\":4129,\"ĠNext\":4130,\"Ġathletes\":4131,\"ii\":4132,\"Ġmovies\":4133,\"han\":4134,\"net\":4135,\"Ġplastic\":4136,\"Ġbehalf\":4137,\"gen\":4138,\"Ġfindings\":4139,\"Ġstretch\":4140,\"ĠSa\":4141,\"Ġofficially\":4142,\"ĠSarah\":4143,\"Ġprivacy\":4144,\"ĠMad\":4145,\"Ġnone\":4146,\"gh\":4147,\"On\":4148,\"Ġdrama\":4149,\"ĠFl\":4150,\"ika\":4151,\"ĠArsenal\":4152,\"Ġviolent\":4153,\"UN\":4154,\"called\":4155,\"59\":4156,\"Ġhate\":4157,\"Ġrelationships\":4158,\"Ġgranted\":4159,\"ĠJon\":4160,\"Ġlisten\":4161,\"season\":4162,\"Ġfewer\":4163,\"GA\":4164,\"ĠLabour\":4165,\"Ġremarks\":4166,\"ĠJonathan\":4167,\"ĠRos\":4168,\"sey\":4169,\"ĠOntario\":4170,\"ĠThompson\":4171,\"ĠNight\":4172,\"Ġranked\":4173,\"ĠUkraine\":4174,\"Ġimmigrants\":4175,\"Ġdegrees\":4176,\"ĠGe\":4177,\"Ġlabor\":4178,\"umb\":4179,\"ĠYORK\":4180,\"Ġallies\":4181,\"sp\":4182,\"hed\":4183,\"sw\":4184,\"Ġtariffs\":4185,\"SP\":4186,\"Ġclassic\":4187,\"Ġawards\":4188,\"ents\":4189,\"Ġfix\":4190,\"Ġsoccer\":4191,\"Ġconcert\":4192,\"ust\":4193,\"Ġadult\":4194,\"Ġoutput\":4195,\"Ġmanaging\":4196,\"02\":4197,\"Ġpromise\":4198,\"Ġawareness\":4199,\"Ġgross\":4200,\"Ġentering\":4201,\"Ġpo\":4202,\"oj\":4203,\"Ġmetal\":4204,\"Ġexit\":4205,\"Ġexcellent\":4206,\"Ġclubs\":4207,\"hold\":4208,\"Ġreplaced\":4209,\"ĠClass\":4210,\"Ġscientists\":4211,\"Ġprimarily\":4212,\"ĠMer\":4213,\"Ã£o\":4214,\"Ġcircumstances\":4215,\"ades\":4216,\"Ġsupplies\":4217,\"aker\":4218,\"ĠSand\":4219,\"Ġscandal\":4220,\"Ġsettlement\":4221,\"ĠWisconsin\":4222,\"ĠWarriors\":4223,\"ĠAustin\":4224,\"Ġjournalists\":4225,\"ening\":4226,\"Ġreflect\":4227,\"ĠBuy\":4228,\"ĠAwards\":4229,\"Ġselection\":4230,\"ĠBel\":4231,\"bury\":4232,\"Ġtechnologies\":4233,\"%,\":4234,\"ime\":4235,\"ĠÄ\":4236,\"ĠAdministration\":4237,\"Ġchannel\":4238,\"Star\":4239,\"Ġtransport\":4240,\"Ġawarded\":4241,\"ena\":4242,\"Ġmotor\":4243,\"orn\":4244,\"kin\":4245,\"Ġfeaturing\":4246,\"Ġphones\":4247,\"ĠAND\":4248,\"Ġrelevant\":4249,\"ĠSee\":4250,\"Ġwinners\":4251,\"Ġdad\":4252,\"ĠSource\":4253,\"ĠCheck\":4254,\"aut\":4255,\"ĠFar\":4256,\"Ġopponents\":4257,\"Ġoutcome\":4258,\"Ġdoors\":4259,\"Ġsuicide\":4260,\"ima\":4261,\"Ġjumped\":4262,\"Ġperspective\":4263,\"Ġtransportation\":4264,\"Ġthinks\":4265,\"ĠMor\":4266,\"Ġdeadline\":4267,\"Ġ53\":4268,\"ĠDeputy\":4269,\"ery\":4270,\"Ġdetailed\":4271,\"uch\":4272,\"ĠBur\":4273,\"Ġtrades\":4274,\"ĠGreg\":4275,\"Ġzero\":4276,\"erson\":4277,\"ĠChildren\":4278,\"Ġdu\":4279,\"66\":4280,\"Ġmixed\":4281,\"ĠBarack\":4282,\"54\":4283,\"Ġterritory\":4284,\"Ġac\":4285,\"Ġconcept\":4286,\"ĠAdd\":4287,\"Ġourselves\":4288,\"Ġreaction\":4289,\"ĠSydney\":4290,\"ink\":4291,\"Ġconsistent\":4292,\"Ġboat\":4293,\"room\":4294,\"Ġdozens\":4295,\"Ġeffectively\":4296,\"but\":4297,\"Ġmotion\":4298,\"Ġalive\":4299,\"ĠKey\":4300,\"weight\":4301,\"Ġexports\":4302,\"Ġoperate\":4303,\"Ġregime\":4304,\"ĠAuthority\":4305,\"och\":4306,\"ĠCR\":4307,\"leg\":4308,\"Ġforget\":4309,\"American\":4310,\"bs\":4311,\"Ġthoughts\":4312,\"ĠSign\":4313,\"ĠPatriots\":4314,\"Ġbrief\":4315,\"ĠOregon\":4316,\"ĠBal\":4317,\"Ġmine\":4318,\"Ġciting\":4319,\"Ġmagazine\":4320,\"more\":4321,\"ERS\":4322,\"ĠBer\":4323,\"ua\":4324,\"ox\":4325,\"ĠMain\":4326,\"Ġinstance\":4327,\"tr\":4328,\"Ġrestaurants\":4329,\"ora\":4330,\"Ġharassment\":4331,\"\\\",\\\"\":4332,\"Ł\":4333,\"Ġsilver\":4334,\"ĠMueller\":4335,\"ĠSenator\":4336,\"ĠEvery\":4337,\"Ġfootage\":4338,\"ms\":4339,\"Ġopposed\":4340,\"ĠLink\":4341,\"Ġver\":4342,\"Ġpleased\":4343,\"ame\":4344,\"ending\":4345,\"Ġrivals\":4346,\"ida\":4347,\"ike\":4348,\"ta\":4349,\"ĠCook\":4350,\"Ġheadquarters\":4351,\"ear\":4352,\"Ġaggressive\":4353,\"Ġcourts\":4354,\"ĠMuseum\":4355,\"Ġim\":4356,\"ĠHoldings\":4357,\"Ġcommunication\":4358,\"Ġphase\":4359,\"yl\":4360,\"Ġpowers\":4361,\"Ġproved\":4362,\"Ġcarbon\":4363,\"Ġaside\":4364,\"ĠOlympics\":4365,\"Ġgathered\":4366,\"ĠPennsylvania\":4367,\"Ġsmartphone\":4368,\"ĠMet\":4369,\"ĠHurricane\":4370,\"Ġprotected\":4371,\"Ġcommunications\":4372,\"Ġemerged\":4373,\"Ġaim\":4374,\"Ġstable\":4375,\"ides\":4376,\"GB\":4377,\"Ġentirely\":4378,\"Ġmissile\":4379,\"ĠGen\":4380,\"Ġunclear\":4381,\"Ġelectricity\":4382,\"ology\":4383,\"away\":4384,\"Ġlicense\":4385,\"ĠPittsburgh\":4386,\"Ġcameras\":4387,\"Ġmusical\":4388,\"Ġmanagers\":4389,\"57\":4390,\"Ġscores\":4391,\"Ġprofile\":4392,\"hel\":4393,\"¼\":4394,\"Ġshouldn\":4395,\"RA\":4396,\");\":4397,\"Ġpermanent\":4398,\"ome\":4399,\"Ġet\":4400,\"Ġmar\":4401,\"Ġfavor\":4402,\"Ġmaker\":4403,\"Ġdiscussions\":4404,\"ory\":4405,\"Ġsharp\":4406,\"Ġpleaded\":4407,\"Ġpassenger\":4408,\"quarter\":4409,\"Ġdem\":4410,\"Ġversus\":4411,\"Ġmainly\":4412,\"Ġeighth\":4413,\"ĠAirport\":4414,\"ĠCross\":4415,\"million\":4416,\"ĠNas\":4417,\"Ġcited\":4418,\"56\":4419,\"Ġyes\":4420,\"ĠBelow\":4421,\"arn\":4422,\"ĠTurkish\":4423,\"ĠSl\":4424,\"Ġstepped\":4425,\"Ġproducers\":4426,\"Ġovernight\":4427,\"Ġsounds\":4428,\"52\":4429,\"Ġ64\":4430,\"Ġ54\":4431,\"58\":4432,\"ĠClark\":4433,\"ĠRick\":4434,\"Ġgr\":4435,\"ĠMont\":4436,\"Ġbeer\":4437,\"une\":4438,\"Ġreporter\":4439,\"Ġcharity\":4440,\"Ġeating\":4441,\"Ġextend\":4442,\"Ġguess\":4443,\"NA\":4444,\"Ġhedge\":4445,\"Ġencouraged\":4446,\"owned\":4447,\"ĠMel\":4448,\"ĠKentucky\":4449,\"ace\":4450,\"Ġlineup\":4451,\"Ġhosts\":4452,\"Ġcapable\":4453,\"PR\":4454,\"ĠArts\":4455,\"Ġcontroversial\":4456,\"Ġhosted\":4457,\"ries\":4458,\"Ġroster\":4459,\"Ġfixed\":4460,\"ĠWalker\":4461,\"ged\":4462,\"Ġdisaster\":4463,\"Ġdispute\":4464,\"ĠDenver\":4465,\"ĠTrade\":4466,\"ute\":4467,\"ese\":4468,\"cy\":4469,\"Ġgrant\":4470,\"ĠMax\":4471,\"Ġdistance\":4472,\"isc\":4473,\"Ġeditor\":4474,\"ĠDave\":4475,\"Ġperformances\":4476,\"Ġlay\":4477,\"Ġvulnerable\":4478,\"ĠMurray\":4479,\"ĠâĤ¬\":4480,\"Ġmining\":4481,\"Ġ2004\":4482,\"level\":4483,\"ability\":4484,\"Ġauto\":4485,\"Ġfake\":4486,\"Ġattacked\":4487,\"ona\":4488,\"ups\":4489,\"ened\":4490,\"Ġfallen\":4491,\"Ġstations\":4492,\"ĠContact\":4493,\"itz\":4494,\"Ġincidents\":4495,\"Ġcomplaints\":4496,\"Ġoperates\":4497,\"Ġrefugees\":4498,\"Ġessential\":4499,\"ĠTest\":4500,\"Ġdemands\":4501,\"Ġroles\":4502,\"yr\":4503,\"Ġacts\":4504,\"Ġusual\":4505,\"ring\":4506,\"Ġhanded\":4507,\"ĠMatthew\":4508,\"hour\":4509,\"Ġindustries\":4510,\"Ġshoot\":4511,\"ĠAuthorities\":4512,\"Ġprobe\":4513,\"ĠUtah\":4514,\"ĠRBI\":4515,\"ĠAD\":4516,\"Ġprospect\":4517,\"outs\":4518,\"ĠUber\":4519,\"Ġbright\":4520,\"Ġmention\":4521,\"Ġsavings\":4522,\"ĠMiss\":4523,\"ONDON\":4524,\"Ġ1990\":4525,\"arm\":4526,\"ĠTen\":4527,\"These\":4528,\"Ġexplains\":4529,\"minute\":4530,\"85\":4531,\"Ġmaximum\":4532,\"Ġro\":4533,\"Ġrookie\":4534,\"Ġstudio\":4535,\"ĠCam\":4536,\"ĠGal\":4537,\"Ġdefend\":4538,\"hand\":4539,\"53\":4540,\"ĠOil\":4541,\"Ġserves\":4542,\"Ġsn\":4543,\"ios\":4544,\"ĠDefense\":4545,\"AB\":4546,\"Ġhired\":4547,\"Ġsupports\":4548,\"Ġpremium\":4549,\"ef\":4550,\"Ġfailing\":4551,\"ĠIndiana\":4552,\"Ġexp\":4553,\"Ġobjective\":4554,\"Ġaffordable\":4555,\"ĠCom\":4556,\"ĠThanks\":4557,\"Ġanywhere\":4558,\"Ġconfirm\":4559,\"ited\":4560,\"Ġrepresenting\":4561,\"Ġwitness\":4562,\"69\":4563,\"Ġclaiming\":4564,\"Ġviolation\":4565,\"Ġhistorical\":4566,\"med\":4567,\"Ġpreparing\":4568,\"ĠTech\":4569,\"Ġposts\":4570,\"OC\":4571,\"ĠGraham\":4572,\"ĠGl\":4573,\"ĠLions\":4574,\"ales\":4575,\"ĠID\":4576,\"Ġcorrect\":4577,\"ĠAntonio\":4578,\"Ġadvertising\":4579,\"Ġeastern\":4580,\"OW\":4581,\"Ġholdings\":4582,\"Ġpolls\":4583,\"ĠSH\":4584,\"Ġexecutives\":4585,\"ĠJewish\":4586,\"ĠGary\":4587,\"Ġprize\":4588,\"ĠCommissioner\":4589,\"Ġcells\":4590,\"ify\":4591,\"Ġlunch\":4592,\"Ġdemocracy\":4593,\"ĠEr\":4594,\"Ġregularly\":4595,\"Ġresulted\":4596,\"ĠAve\":4597,\"ĠPartners\":4598,\"Ġrewritten\":4599,\"Ġlo\":4600,\"Ġcooperation\":4601,\"ĠGulf\":4602,\"Ġsmoke\":4603,\"ĠMemorial\":4604,\"Ġwave\":4605,\"Ġfears\":4606,\"Ġkid\":4607,\"ĠGiants\":4608,\"Ġrecovered\":4609,\"row\":4610,\"ĠRadio\":4611,\"ĠBarcelona\":4612,\"Ġwonderful\":4613,\"ĠDow\":4614,\"Ġstream\":4615,\"ĠSimon\":4616,\"Ġdetail\":4617,\"Ġvolunteers\":4618,\"ĠInd\":4619,\"Ġforms\":4620,\"mann\":4621,\"ĠRay\":4622,\"oor\":4623,\"ĠTake\":4624,\"Ġrepresented\":4625,\"het\":4626,\"Ġblow\":4627,\"aged\":4628,\"RE\":4629,\"ĠMissouri\":4630,\"Ġcovering\":4631,\"Ġprofits\":4632,\"Ġconcluded\":4633,\"Ġthus\":4634,\"ĠColumbia\":4635,\"ode\":4636,\"ĠZimbabwe\":4637,\"Ġdisclosed\":4638,\"Ġlifted\":4639,\"ĠSean\":4640,\"ĠHarvey\":4641,\"ĠPlus\":4642,\"ces\":4643,\"ĠGreece\":4644,\"ĠLady\":4645,\"Ġdelay\":4646,\"Ġkitchen\":4647,\"ĠIndex\":4648,\"Ġbear\":4649,\"Ġputs\":4650,\"new\":4651,\"88\":4652,\"ĠAsh\":4653,\"Å¡\":4654,\"Ġperforming\":4655,\"law\":4656,\"ĠPart\":4657,\"Ġindicated\":4658,\"Ġannounce\":4659,\"Ġcompensation\":4660,\"Ġka\":4661,\"ĠScience\":4662,\"ris\":4663,\"Ġrecommendations\":4664,\"ĠSecond\":4665,\"Ġlights\":4666,\"Ġtemporary\":4667,\"urs\":4668,\"Ġwestern\":4669,\"stone\":4670,\"68\":4671,\"ĠDisney\":4672,\"Ġplayoffs\":4673,\"Ġjudges\":4674,\"Ġengineering\":4675,\"ĠPen\":4676,\"ĠPal\":4677,\"Ġobvious\":4678,\"ĠBridge\":4679,\"ĠEnd\":4680,\"ĠArab\":4681,\"Ġexcept\":4682,\"Ġhole\":4683,\"class\":4684,\"Ġcauses\":4685,\"Ġconnect\":4686,\"ĠAI\":4687,\"An\":4688,\"Ġchose\":4689,\"ĠElizabeth\":4690,\"min\":4691,\"Ġproper\":4692,\"ĠNHL\":4693,\"Ġraces\":4694,\"Ġinnovation\":4695,\"Ġsugar\":4696,\"600\":4697,\"ĠModi\":4698,\"illa\":4699,\"Ġtrillion\":4700,\"ĠSar\":4701,\"ĠAffairs\":4702,\"Ġimpossible\":4703,\"Ġguide\":4704,\"Ġcaptured\":4705,\"ĠSales\":4706,\"Ġspecies\":4707,\"51\":4708,\"Ġar\":4709,\"Ġmaster\":4710,\"Ġstayed\":4711,\"iro\":4712,\"ĠEconomic\":4713,\"Ġvast\":4714,\"ili\":4715,\"Ġpet\":4716,\"ye\":4717,\"77\":4718,\"Ġkeeps\":4719,\"ĠPhil\":4720,\"ĠEPS\":4721,\"ĠRegional\":4722,\"Ġsectors\":4723,\"Ġdesire\":4724,\"ĠStanley\":4725,\"¾\":4726,\"Ġunknown\":4727,\"Ġpot\":4728,\"ĠPR\":4729,\"Ġknowing\":4730,\"Ġflying\":4731,\"ĠTreasury\":4732,\"iers\":4733,\"enn\":4734,\"ably\":4735,\"Ġsick\":4736,\"Ġmanner\":4737,\"Ġmanufacturers\":4738,\"Ġchampions\":4739,\"gy\":4740,\"Part\":4741,\"ister\":4742,\"ĠMountain\":4743,\"Ġimagine\":4744,\"Ġportion\":4745,\"ĠCamp\":4746,\"Ġchemical\":4747,\"ible\":4748,\"ĠAnaly\":4749,\"ĠBureau\":4750,\"Ġpm\":4751,\"Ġupdated\":4752,\"Ġetc\":4753,\"ĠField\":4754,\"iles\":4755,\"Ġobtained\":4756,\"Ġstick\":4757,\"Ġcat\":4758,\"har\":4759,\"Ġmarked\":4760,\"Ġmedium\":4761,\"ĠDes\":4762,\"People\":4763,\"Ġwealth\":4764,\"ores\":4765,\"ĠBaltimore\":4766,\"Ġtip\":4767,\"Ġdismissed\":4768,\"ĠVictoria\":4769,\"ĠBrad\":4770,\"Ch\":4771,\"Ġ56\":4772,\"Ġstadium\":4773,\"eth\":4774,\"Ġthunder\":4775,\"Ġtested\":4776,\"Ġdrawn\":4777,\"Ġcounsel\":4778,\"ld\":4779,\"Ġspirit\":4780,\"uss\":4781,\"Ġtheme\":4782,\"my\":4783,\"Ġnecessarily\":4784,\"Ġelements\":4785,\"Ġcollected\":4786,\"ĠRes\":4787,\"ĠMaryland\":4788,\"ĠEnter\":4789,\"Ġfounded\":4790,\"ae\":4791,\"Ġpilot\":4792,\"Ġshoulder\":4793,\"PC\":4794,\"Ġargument\":4795,\"Ġyen\":4796,\"Ġreceiver\":4797,\"Ġharm\":4798,\"ĠET\":4799,\"Ġprotesters\":4800,\"Ġ72\":4801,\"ĠAaron\":4802,\"Ġed\":4803,\"Ġexpecting\":4804,\"\\\":\\\"\":4805,\"Ġbike\":4806,\"Äĩ\":4807,\"Ġluxury\":4808,\"half\":4809,\"ĠBarbara\":4810,\"Ġfoundation\":4811,\"Ġill\":4812,\"Ġsubmitted\":4813,\"Ġdeeply\":4814,\"Ġhospitals\":4815,\"ĠBJP\":4816,\"Ġshock\":4817,\"Ġplatforms\":4818,\"Ġsummary\":4819,\"ĠWhere\":4820,\"Ġcelebration\":4821,\"iff\":4822,\"Ġveterans\":4823,\"Ġachieved\":4824,\"fl\":4825,\"Ġactivists\":4826,\"ĠManager\":4827,\"Ġformal\":4828,\"Ġformed\":4829,\"Ġinvestigate\":4830,\"ĠKyle\":4831,\"Ġ:\":4832,\"ĠRa\":4833,\"ovic\":4834,\"Ġdrinking\":4835,\"Ġnetworks\":4836,\"ĠAlexander\":4837,\"ĠOs\":4838,\"Ġ)\":4839,\"Ġbomb\":4840,\"Ġrecalled\":4841,\"ito\":4842,\"ient\":4843,\"Ġrepresentatives\":4844,\"ĠChrist\":4845,\"ĠWay\":4846,\"Ġdeadly\":4847,\"Ġinvesting\":4848,\"ĠRussell\":4849,\"Ġconsumption\":4850,\"Ġharder\":4851,\"Ġbail\":4852,\"Ġcritics\":4853,\"Ġdanger\":4854,\"Ġdrew\":4855,\"ĠSol\":4856,\"Ġcopyright\":4857,\"ĠHenry\":4858,\"Ġbuyers\":4859,\"Ġresidential\":4860,\"Ġmaintenance\":4861,\"pr\":4862,\"Ġmarks\":4863,\"Ġages\":4864,\"Ġcovers\":4865,\"Ġton\":4866,\"Ġtitles\":4867,\"ĠPS\":4868,\"ĠEvans\":4869,\"Ġmigrants\":4870,\"Ġflights\":4871,\"Ġmonitoring\":4872,\"Ġaddressed\":4873,\"Ġvital\":4874,\"Ġcontrolled\":4875,\"Ġweapon\":4876,\"Ġinches\":4877,\"Ġreduction\":4878,\"Ġurban\":4879,\"Ġcoaching\":4880,\"Ġreducing\":4881,\"ila\":4882,\"Ġrealize\":4883,\"Ġmeat\":4884,\"Ġref\":4885,\"Ġoverseas\":4886,\"Ġblame\":4887,\"Ġterrorist\":4888,\"Ġstuck\":4889,\"ĠUs\":4890,\"esh\":4891,\"pro\":4892,\"Ġ58\":4893,\"ough\":4894,\"Ġexposure\":4895,\"ĠAbu\":4896,\"state\":4897,\"Ġproviders\":4898,\"Ġfore\":4899,\"Ġjet\":4900,\"bar\":4901,\"Ġownership\":4902,\"ret\":4903,\"Ġupset\":4904,\"Ġfacts\":4905,\"Ġpurchasing\":4906,\"Ġreforms\":4907,\"Ġriver\":4908,\"Ġsomebody\":4909,\"Ġguest\":4910,\"iy\":4911,\"Ġauction\":4912,\"ĠReading\":4913,\"Ġconsequences\":4914,\"Ġrepresentative\":4915,\"Ġappointment\":4916,\"add\":4917,\"Ġcollaboration\":4918,\"ĠTesla\":4919,\"ĠCohen\":4920,\"Ġengagement\":4921,\"Ġspeaks\":4922,\"EST\":4923,\"Ġexposed\":4924,\"Ġmaintained\":4925,\"rs\":4926,\"Ġdating\":4927,\"ĠProgram\":4928,\"board\":4929,\"Ġracing\":4930,\"Ġpension\":4931,\"ign\":4932,\"iti\":4933,\"ĠFive\":4934,\"Ġextensive\":4935,\"ĠHa\":4936,\"ĠPoint\":4937,\"ĠMexican\":4938,\"Ġexpanded\":4939,\"Ġtotally\":4940,\"Ġinvestigations\":4941,\"ĠOrleans\":4942,\"Ġcycle\":4943,\"ĠESPN\":4944,\"ifying\":4945,\"Ġcup\":4946,\"ĠAz\":4947,\"ĠInvestors\":4948,\"Ġengage\":4949,\"reg\":4950,\"Ġfought\":4951,\"Ġterrorism\":4952,\"Ġblocked\":4953,\"ĠOK\":4954,\"Äį\":4955,\"72\":4956,\"Ġdestroyed\":4957,\"«\":4958,\"Ġstaying\":4959,\"Ġafford\":4960,\"Ġappearances\":4961,\"ĠHills\":4962,\"Ġcrore\":4963,\"Ġstrategies\":4964,\"Ġtips\":4965,\"ĠSm\":4966,\"ĠFr\":4967,\"Ġbanned\":4968,\"ĠSon\":4969,\"ask\":4970,\"Ġlimits\":4971,\"Ġrecognition\":4972,\"Ġeligible\":4973,\"ĠGar\":4974,\"Ġvolatility\":4975,\"Ġlaid\":4976,\"nes\":4977,\"Ġgrade\":4978,\"ĠRE\":4979,\"ĠHart\":4980,\"Ġ57\":4981,\"oma\":4982,\"Ġuncertainty\":4983,\"Ġrecognized\":4984,\"ĠPC\":4985,\"Ġchosen\":4986,\"uz\":4987,\"Ġadviser\":4988,\"una\":4989,\"Ġassessment\":4990,\"Ġreveal\":4991,\"mo\":4992,\"After\":4993,\"ĠBro\":4994,\"ĠOff\":4995,\"Ġpeak\":4996,\"Ġreferred\":4997,\"ĠSC\":4998,\"Ġ2003\":4999,\"ification\":5000,\"Ġshutdown\":5001,\"ĠOfficials\":5002,\"ias\":5003,\"Ġextreme\":5004,\"Ġflood\":5005,\"Ġhockey\":5006,\"Ġwage\":5007,\"ĠNet\":5008,\"Ġdamaged\":5009,\"Ġreplacement\":5010,\"ĠMaria\":5011,\"Ġcreation\":5012,\"Ġguns\":5013,\"aci\":5014,\"Ġworker\":5015,\"do\":5016,\"Ġviewers\":5017,\"Ġseed\":5018,\"sts\":5019,\"Ġtouchdowns\":5020,\"Ġmistake\":5021,\"ray\":5022,\"ull\":5023,\"Ġpricing\":5024,\"Ġstrongly\":5025,\"Ġaims\":5026,\"ĠNavy\":5027,\"ĠEgypt\":5028,\"ker\":5029,\"Ġve\":5030,\"ĠSteven\":5031,\"Ġres\":5032,\"ational\":5033,\"Ġrequests\":5034,\"Ġemissions\":5035,\"ĠArena\":5036,\"uma\":5037,\"ĠAtlantic\":5038,\"hr\":5039,\"ĠAFP\":5040,\"ĠSquare\":5041,\"Ġcontribute\":5042,\"Ġfunction\":5043,\"Ġdec\":5044,\"ĠNelson\":5045,\"89\":5046,\"Ġreferendum\":5047,\"ĠPre\":5048,\"Ġapplied\":5049,\"ĠGMT\":5050,\"ĠIranian\":5051,\"ĠNigerian\":5052,\"ĠAny\":5053,\"NG\":5054,\"Ġacknowledged\":5055,\"Ġreferring\":5056,\"Ġventure\":5057,\"Ġimports\":5058,\"Ġblog\":5059,\"Ġfutures\":5060,\"OU\":5061,\"ĠUFC\":5062,\"Ġneither\":5063,\"Ġextension\":5064,\"hes\":5065,\"ĠMed\":5066,\"76\":5067,\"Ġsustainable\":5068,\"ains\":5069,\"Ġreputation\":5070,\"ĠVancouver\":5071,\"Ġbasically\":5072,\"acy\":5073,\"Ġsad\":5074,\"ĠFrancis\":5075,\"ĠKennedy\":5076,\"ĠNevada\":5077,\"ĠLu\":5078,\"ras\":5079,\"ĠAv\":5080,\"Ġrear\":5081,\"ĠHo\":5082,\"Ġproperly\":5083,\"abe\":5084,\"ĠHotel\":5085,\"Ġopinions\":5086,\"under\":5087,\"ĠStation\":5088,\"ĠFOR\":5089,\"ops\":5090,\"Ġadopted\":5091,\"ĠSwiss\":5092,\"ĠCountry\":5093,\"ĠTer\":5094,\"ĠAndy\":5095,\"Me\":5096,\"ĠCooper\":5097,\"ĠTigers\":5098,\"ĠCreek\":5099,\"Ġgay\":5100,\"iner\":5101,\"ĠAN\":5102,\"Ġbird\":5103,\"lla\":5104,\"ĠKate\":5105,\"ĠPet\":5106,\"ni\":5107,\"Ġprospects\":5108,\"ater\":5109,\"ites\":5110,\"Ġescape\":5111,\"lam\":5112,\"ake\":5113,\"Ġ1980\":5114,\"ĠLag\":5115,\"Ġsuccessfully\":5116,\"Ġdistricts\":5117,\"Ġministers\":5118,\"aries\":5119,\"Ġframe\":5120,\"ĠON\":5121,\"ĠEuro\":5122,\"ĠMarkets\":5123,\"Ġregister\":5124,\"Ġdefeated\":5125,\"Ġdevelopments\":5126,\"Ġninth\":5127,\"Ġquiet\":5128,\"Ġgenerated\":5129,\"Ġvaluable\":5130,\"Ġrecommended\":5131,\"ĠTheatre\":5132,\"ĠCap\":5133,\"bed\":5134,\"Ġreference\":5135,\"Ġease\":5136,\"oring\":5137,\"Ġ66\":5138,\"Ġimprovements\":5139,\"Ġelsewhere\":5140,\"ĠHillary\":5141,\"Ġdefender\":5142,\"ĠRight\":5143,\"zy\":5144,\"Ġcomprehensive\":5145,\"Ġspotted\":5146,\"ĠOakland\":5147,\"ĠOk\":5148,\"ĠSystem\":5149,\"ique\":5150,\"Ġpersons\":5151,\"Ġexist\":5152,\"Ġbroader\":5153,\"Ġclinical\":5154,\"Ġ2001\":5155,\"oul\":5156,\"Ġsecurities\":5157,\"ghan\":5158,\"Ġshelter\":5159,\"ero\":5160,\"ATED\":5161,\"Ġhosting\":5162,\"Ġselect\":5163,\"ĠKavanaugh\":5164,\"Ġrestrictions\":5165,\"osa\":5166,\"Ġyields\":5167,\"ĠLA\":5168,\"Ġ59\":5169,\"Ġwonder\":5170,\"Ġabsence\":5171,\"Ã¼r\":5172,\"ÅĤ\":5173,\"DP\":5174,\"Ġelectronic\":5175,\"Ġillegally\":5176,\"Ġmicro\":5177,\"ĠNEW\":5178,\"Ġhall\":5179,\"Ġaged\":5180,\"Ġtemperature\":5181,\"cast\":5182,\"atic\":5183,\"Ġlegacy\":5184,\"Ġaffairs\":5185,\"ji\":5186,\"ĠResources\":5187,\"Ġgang\":5188,\"winning\":5189,\"Ġattending\":5190,\"aro\":5191,\"Ġfriendly\":5192,\"aine\":5193,\"Ġcannabis\":5194,\"Ġairline\":5195,\"Ġnoting\":5196,\"Ġprofessionals\":5197,\"ĠFREE\":5198,\"RC\":5199,\"Ġfinancing\":5200,\"Ġindependence\":5201,\"ved\":5202,\"Ġresulting\":5203,\"Ġsteady\":5204,\"ĠWinter\":5205,\"uring\":5206,\"Ġhoped\":5207,\"98\":5208,\"Ġpresentation\":5209,\"aya\":5210,\"Ġrated\":5211,\"osh\":5212,\"ĠAnalysis\":5213,\"=\":5214,\"Ġdonations\":5215,\"IR\":5216,\"Ġcombat\":5217,\"ĠHoward\":5218,\"anda\":5219,\"79\":5220,\"Ġinvested\":5221,\"Ġexpanding\":5222,\"omb\":5223,\"ress\":5224,\"ble\":5225,\"Ġjournalist\":5226,\"ĠWoods\":5227,\"Ġcenters\":5228,\"ott\":5229,\"Ġstreaming\":5230,\"Ġterror\":5231,\"Ġsustained\":5232,\"ĠWWE\":5233,\"pre\":5234,\"ÅŁ\":5235,\"ait\":5236,\"Ġarrival\":5237,\"Ġresidence\":5238,\"Ġextent\":5239,\"Ġarrive\":5240,\"Ġ2002\":5241,\"Ġestablish\":5242,\"74\":5243,\"ĠArgentina\":5244,\"ĠDem\":5245,\"inn\":5246,\"aud\":5247,\"ĠNCAA\":5248,\"Ġquestioned\":5249,\"Ġballot\":5250,\"Ġmin\":5251,\"Ġlandscape\":5252,\"Ġhorse\":5253,\"Ġopponent\":5254,\"iel\":5255,\"Ġprompted\":5256,\"atory\":5257,\"Ġlift\":5258,\"Ġassociation\":5259,\"cher\":5260,\"Ġdefending\":5261,\"Ġtiny\":5262,\"Ġpoverty\":5263,\"ĠSafety\":5264,\"Ġpetition\":5265,\"ĠLimited\":5266,\"ĠCA\":5267,\"FC\":5268,\"Ãł\":5269,\"oni\":5270,\"Ġmonitor\":5271,\"ÃŃa\":5272,\"MA\":5273,\"Ġanswers\":5274,\"ĠMitchell\":5275,\"Ġbo\":5276,\"ĠShah\":5277,\"Ġsm\":5278,\"Ġmedal\":5279,\"ĠCivil\":5280,\"Ġrecognize\":5281,\"key\":5282,\"Ġpregnant\":5283,\"Ġspots\":5284,\"ante\":5285,\"Ġacademic\":5286,\"Ġinitiatives\":5287,\"Ġsecured\":5288,\"ĠCL\":5289,\"ils\":5290,\"Ġanticipated\":5291,\"Ġinvolvement\":5292,\"ĠMake\":5293,\"Ġinsisted\":5294,\"ĠWales\":5295,\"Ġclothing\":5296,\"Ġtracks\":5297,\"Ġsymptoms\":5298,\"Ġplate\":5299,\"ĠNY\":5300,\"Ġretailers\":5301,\"ĠPan\":5302,\"Ġfled\":5303,\"Ġquoted\":5304,\"Ġsaved\":5305,\"ĠCarter\":5306,\"Ġteaching\":5307,\"ĠTokyo\":5308,\"ĠCr\":5309,\"ĠSix\":5310,\"ĠPicture\":5311,\"Ġrecover\":5312,\"Ġcomedy\":5313,\"ree\":5314,\"Ġstrikes\":5315,\"ĠSanders\":5316,\"sel\":5317,\"Ġgraduate\":5318,\"Ġpending\":5319,\"St\":5320,\"Ġwarrant\":5321,\"Ġhonest\":5322,\"ĠGM\":5323,\"Ġnoticed\":5324,\"ĠGalaxy\":5325,\"ider\":5326,\"Ġproposals\":5327,\"Ġwore\":5328,\"Ġindeed\":5329,\"EM\":5330,\"ĠChannel\":5331,\"ances\":5332,\"ĠBrady\":5333,\"86\":5334,\"Ġgotten\":5335,\"Ġthrowing\":5336,\"ĠLeader\":5337,\"ĠVideo\":5338,\"71\":5339,\"Ġwelcomed\":5340,\"NEW\":5341,\"Ġfairly\":5342,\"Ġpromises\":5343,\"ĠSilver\":5344,\"Ġrape\":5345,\"Ġopener\":5346,\"ares\":5347,\"ĠSir\":5348,\"making\":5349,\"Ġcur\":5350,\"Ġrooms\":5351,\"73\":5352,\"Ġamounts\":5353,\"ĠIndustry\":5354,\"ĠDar\":5355,\"Ġ62\":5356,\"ted\":5357,\"Ġabroad\":5358,\"ĠMaybe\":5359,\"Ġreaders\":5360,\"oke\":5361,\"Ġpublication\":5362,\"ĠJean\":5363,\"Ġoperator\":5364,\"ĠHaving\":5365,\"ĠMil\":5366,\"life\":5367,\"Ġgenerate\":5368,\"ĠCraig\":5369,\"ĠMass\":5370,\"ĠBh\":5371,\"Ġrequested\":5372,\"Ġcrazy\":5373,\"ĠSpace\":5374,\"Ġcopy\":5375,\"Ġexport\":5376,\"Ġcontext\":5377,\"Ġbr\":5378,\"62\":5379,\"ĠRobinson\":5380,\"Ġcyber\":5381,\"ENT\":5382,\"BI\":5383,\"arg\":5384,\"Ġspeaker\":5385,\"Ġdramatic\":5386,\"ĠOl\":5387,\"ĠMill\":5388,\"Ġtrained\":5389,\"Ġediting\":5390,\"Ġsalary\":5391,\"Ġdirectors\":5392,\"Ġexplore\":5393,\"Ġlucky\":5394,\"Ġprominent\":5395,\"Ġbrothers\":5396,\"Ġneck\":5397,\"icht\":5398,\"ĠWatson\":5399,\"born\":5400,\"Ġproven\":5401,\"Ġprincipal\":5402,\"Ġedition\":5403,\"Ed\":5404,\"Ġswitch\":5405,\"maker\":5406,\"Ġrelative\":5407,\"mi\":5408,\"ĠBruce\":5409,\"ho\":5410,\"ĠScottish\":5411,\"water\":5412,\"ĠSport\":5413,\"ĠKings\":5414,\"ĠCollins\":5415,\"adi\":5416,\"Ġcelebrated\":5417,\"Ġclothes\":5418,\"Ġsunny\":5419,\"ĠCharlotte\":5420,\"ees\":5421,\"Ġscenes\":5422,\"ĠData\":5423,\"Ġwounded\":5424,\"Ġunusual\":5425,\"Ġrealized\":5426,\"ĠPlan\":5427,\"ĠTrans\":5428,\"ĠFC\":5429,\"Ġletters\":5430,\"Ġalerts\":5431,\"ĠWarren\":5432,\"DS\":5433,\"oss\":5434,\"pping\":5435,\"Ġsuspension\":5436,\"Ġbenchmark\":5437,\"ĠAcc\":5438,\"Ġalert\":5439,\"Ġpassion\":5440,\"ĠEst\":5441,\"Ġlatter\":5442,\"Ġstability\":5443,\"Ġarts\":5444,\"Ġpursue\":5445,\"ĠSeason\":5446,\"Ġfields\":5447,\"Ġmethod\":5448,\"63\":5449,\"Ġfolks\":5450,\"Ġexclusive\":5451,\"Ġcrews\":5452,\"Ġsessions\":5453,\"ĠMajor\":5454,\"ĠMount\":5455,\"Ġmap\":5456,\"Ġ=\":5457,\"Ġsituations\":5458,\"ĠBerlin\":5459,\"rey\":5460,\"Ġdates\":5461,\"Ġsheet\":5462,\"ĠLo\":5463,\"Ġfighters\":5464,\"ĠMart\":5465,\"Ġatmosphere\":5466,\"Ġillness\":5467,\"Ġcompeting\":5468,\"ĠChristopher\":5469,\"ĠRoy\":5470,\"mm\":5471,\"iano\":5472,\"Ġge\":5473,\"ĠRams\":5474,\"Ġconversations\":5475,\"ĠPa\":5476,\"ĠTel\":5477,\"Ġappreciate\":5478,\"78\":5479,\"ĠTotal\":5480,\"low\":5481,\"ĠStone\":5482,\"Ġopposite\":5483,\"Ġbarrel\":5484,\"Ġdevelopers\":5485,\"Ġexpress\":5486,\"Ġhighs\":5487,\"which\":5488,\"par\":5489,\"ĠVietnam\":5490,\"Ġblocks\":5491,\"Ġrecording\":5492,\"Ġadjusted\":5493,\"Ġret\":5494,\"ĠAR\":5495,\"Ġmilitants\":5496,\"Ġinnovative\":5497,\"ĠGhana\":5498,\"FR\":5499,\"Ġfantastic\":5500,\"Ġmortgage\":5501,\"ando\":5502,\"ĠLane\":5503,\"ises\":5504,\"ĠÂ\":5505,\"Ġhomeless\":5506,\"ĠKal\":5507,\"Ġapproached\":5508,\"Ġrounds\":5509,\"Ġmargins\":5510,\"ament\":5511,\"ĠMotor\":5512,\"Ġencouraging\":5513,\"ÂŃ\":5514,\"uru\":5515,\"Ġhandling\":5516,\"ĠMassachusetts\":5517,\"Ġplanet\":5518,\"ĠSpring\":5519,\"ĠBon\":5520,\"gu\":5521,\"Beat\":5522,\"Ġdrawing\":5523,\"ĠPhoenix\":5524,\"very\":5525,\"aid\":5526,\"ĠSte\":5527,\"ĠEntertainment\":5528,\"ĠRon\":5529,\"Ġassigned\":5530,\"ĠSA\":5531,\"News\":5532,\"Ġinterviews\":5533,\"ĠOh\":5534,\"media\":5535,\"vel\":5536,\"Ġpermission\":5537,\"Ġtransactions\":5538,\"Ġtraders\":5539,\"Ġsolo\":5540,\"Ġprovincial\":5541,\"Ġsuggesting\":5542,\"¡\":5543,\"Ġdiverse\":5544,\"Ġ67\":5545,\"Ġranks\":5546,\"ĠFre\":5547,\"Ġfavourite\":5548,\"Ġ63\":5549,\"Ġdifferences\":5550,\"Ġtargeting\":5551,\"Ġactors\":5552,\"Ġ76\":5553,\"icated\":5554,\"Ġcollect\":5555,\"akes\":5556,\"war\":5557,\"Ġcontained\":5558,\"ches\":5559,\"Ġlibrary\":5560,\"Ġsegments\":5561,\"ĠLine\":5562,\"Ãª\":5563,\"ual\":5564,\"Ġbags\":5565,\"Ġfactory\":5566,\"Ġear\":5567,\"Ġsomewhat\":5568,\"Ġrail\":5569,\"ĠUP\":5570,\"ula\":5571,\"ĠNiger\":5572,\"Ġlas\":5573,\"Ġimplementation\":5574,\"Ġemails\":5575,\"kel\":5576,\"wing\":5577,\"Ġadvised\":5578,\"--\":5579,\"istic\":5580,\"Ġdepth\":5581,\"Ġshoes\":5582,\"ĠJennifer\":5583,\"Ġvenue\":5584,\"Ġcontain\":5585,\"Ġhighlights\":5586,\"Ġcapabilities\":5587,\"Ġprocesses\":5588,\"Ġtradition\":5589,\"Ġcontacted\":5590,\"Ġproducing\":5591,\"Ġtrail\":5592,\"rem\":5593,\"Ġ600\":5594,\"Ġ68\":5595,\"AA\":5596,\"ĠBa\":5597,\"ĠSuch\":5598,\"ĠTyler\":5599,\"ipp\":5600,\"Ġsurvived\":5601,\"ami\":5602,\"ĠContinue\":5603,\"Ġcapture\":5604,\"bi\":5605,\"61\":5606,\"96\":5607,\"Ġthreatening\":5608,\"Ġkeen\":5609,\"dale\":5610,\"Ġtrailer\":5611,\"Ġstages\":5612,\"ĠGordon\":5613,\"Ġfinishing\":5614,\"Ġlegislative\":5615,\"Ġuseful\":5616,\"ĠGreek\":5617,\"ald\":5618,\"Ġgrounds\":5619,\"ĠDu\":5620,\"storms\":5621,\"ills\":5622,\"Ġexpense\":5623,\"Ġdetained\":5624,\"Today\":5625,\"Ġdiet\":5626,\"Ġwood\":5627,\"ĠCameron\":5628,\"Ġthrown\":5629,\"Ġcricket\":5630,\"Ġideal\":5631,\"with\":5632,\"Ġteammates\":5633,\"ours\":5634,\"Ġprojected\":5635,\"Ġpersonally\":5636,\"ĠBoy\":5637,\"rom\":5638,\"ĠPhilippines\":5639,\"win\":5640,\"ges\":5641,\"Ġcounties\":5642,\"ĠBaker\":5643,\"Ġprosecutor\":5644,\"Ġroof\":5645,\"met\":5646,\"Ġpartly\":5647,\"ĠMoon\":5648,\"eman\":5649,\"Ġfocusing\":5650,\"Ġfishing\":5651,\"than\":5652,\"ĠJeremy\":5653,\"ĠBad\":5654,\"ais\":5655,\"Ġcontrols\":5656,\"Ġtonnes\":5657,\"Ġshall\":5658,\"Ġ61\":5659,\"Ġgathering\":5660,\"ĠERA\":5661,\"Ġpresidency\":5662,\"Ġ85\":5663,\"ĠGas\":5664,\"Ġscenario\":5665,\"Ġquarters\":5666,\"Ġang\":5667,\"Ġsettled\":5668,\"ĠCommerce\":5669,\"Ġanybody\":5670,\"Ġgarden\":5671,\"ĠLibrary\":5672,\"Ġbet\":5673,\"Ġtopic\":5674,\"olo\":5675,\"Ġintense\":5676,\"87\":5677,\"Ġlinks\":5678,\"Ġmed\":5679,\"ĠAG\":5680,\"Ġflooding\":5681,\"ĠMurphy\":5682,\"PM\":5683,\"Ġfinds\":5684,\"Ġsensitive\":5685,\"pped\":5686,\"Ġcompletion\":5687,\"Ġminority\":5688,\"Ġvon\":5689,\"Ġstriking\":5690,\"rich\":5691,\"Ġbars\":5692,\"Ġefficient\":5693,\"Ġcontributions\":5694,\"Ġvisits\":5695,\"Ġattract\":5696,\"ĠMalaysia\":5697,\"ĠREL\":5698,\"Ġopens\":5699,\"Ġessentially\":5700,\"Ġreasonable\":5701,\"Ġsentiment\":5702,\"ĠMelbourne\":5703,\"Ġfitness\":5704,\"Ġfrequently\":5705,\"ĠRangers\":5706,\"Ġmuseum\":5707,\"ĠDNA\":5708,\"Ġcontrast\":5709,\"ĠAdams\":5710,\"ĠWin\":5711,\"Ġfalls\":5712,\"Ġimposed\":5713,\"250\":5714,\"ood\":5715,\"ĠRio\":5716,\"Ġchoices\":5717,\"Ġyellow\":5718,\"rin\":5719,\"ben\":5720,\"ĠStaff\":5721,\"ĠIndonesia\":5722,\"Ġcarries\":5723,\"Ġtourism\":5724,\"UM\":5725,\"ĠOrange\":5726,\"sell\":5727,\"Ġresolve\":5728,\"ĠMumbai\":5729,\"Ġpan\":5730,\"Ġimplement\":5731,\"Ġmidfielder\":5732,\"OP\":5733,\"Ġtensions\":5734,\"Ġ800\":5735,\"ĠLord\":5736,\"ĠLight\":5737,\"Ġlies\":5738,\"Ã©s\":5739,\"Ġparticipation\":5740,\"Ġtries\":5741,\"Ġsheriff\":5742,\"degree\":5743,\"Ġcongressional\":5744,\"Ġmode\":5745,\"Ġregulation\":5746,\"ĠJacob\":5747,\"ĠCrown\":5748,\"Ġbowl\":5749,\"ĠMississippi\":5750,\"Ġtheft\":5751,\"ĠKingdom\":5752,\"Ġresort\":5753,\"Ġroyal\":5754,\"Ġunemployment\":5755,\"PP\":5756,\"Ġnomination\":5757,\"ĠTR\":5758,\"Ġbehaviour\":5759,\"bank\":5760,\"ĠForest\":5761,\"WASHINGTON\":5762,\"ĠOthers\":5763,\"Ġslowly\":5764,\"Ġmenu\":5765,\"vo\":5766,\"ĠSy\":5767,\"ĠMetro\":5768,\"ĠLisa\":5769,\"Ġregistration\":5770,\"While\":5771,\"ĠJesus\":5772,\"Ġ250\":5773,\"Ġprocessing\":5774,\"Ġmonetary\":5775,\"ape\":5776,\"ener\":5777,\"ĠSystems\":5778,\"Ġdisappointed\":5779,\"Ġprint\":5780,\"uy\":5781,\"ħ\":5782,\"Ġdemanding\":5783,\"Ġincredibly\":5784,\"play\":5785,\"Ġsurveillance\":5786,\"ĠStandard\":5787,\"Ġperiods\":5788,\"Ġwrites\":5789,\"ĠLuke\":5790,\"ĠPalestinian\":5791,\"Ġwalks\":5792,\"Ġriding\":5793,\"Ġwaters\":5794,\"ĠSox\":5795,\"Ġtraveling\":5796,\"Ġtap\":5797,\"Ġorganized\":5798,\"Ġresource\":5799,\"Ġangry\":5800,\"Ġtiming\":5801,\"Ġempty\":5802,\"Ġmilk\":5803,\"Ġtherapy\":5804,\"ĠBrandon\":5805,\"mon\":5806,\"Ġnationwide\":5807,\"Ġnovel\":5808,\"ĠStorm\":5809,\"iet\":5810,\"ĠBre\":5811,\"Ġbegun\":5812,\"Ġdiplomatic\":5813,\"Ġads\":5814,\"ĠDC\":5815,\"ĠOb\":5816,\"ĠMontreal\":5817,\"ĠDown\":5818,\"ĠMilwaukee\":5819,\"Ġmeal\":5820,\"ĠPuerto\":5821,\"ĠMas\":5822,\"Ġjoy\":5823,\"Ġdeparture\":5824,\"ĠWright\":5825,\"Ġspoken\":5826,\"style\":5827,\"ĠAction\":5828,\"ĠComey\":5829,\"Ġdelivering\":5830,\"Ġtoll\":5831,\"Ġmidnight\":5832,\"ĠRevenue\":5833,\"Ġfiring\":5834,\"Ġstunning\":5835,\"Ġkicked\":5836,\"ĠOttawa\":5837,\"Ġefficiency\":5838,\"ĠLincoln\":5839,\"Ġtaste\":5840,\"ez\":5841,\"ĠWeather\":5842,\"ĠMorning\":5843,\"Ġhadn\":5844,\"Ġdiversity\":5845,\"ily\":5846,\"ĠAy\":5847,\"Ġargue\":5848,\"Ġerror\":5849,\"Ġtaught\":5850,\"Ġche\":5851,\"Ġoccasion\":5852,\"Ġinc\":5853,\"ĠOrlando\":5854,\"ĠOnline\":5855,\"Ġlegs\":5856,\"ĠNation\":5857,\"uck\":5858,\"Ġwidespread\":5859,\"ĠOcean\":5860,\"Ġconstantly\":5861,\"ĠLatin\":5862,\"Ġcomfort\":5863,\"Ġrely\":5864,\"uff\":5865,\"ĠCard\":5866,\"aring\":5867,\"Ġhumans\":5868,\"ĠThomson\":5869,\"aka\":5870,\"BIT\":5871,\"ĠReview\":5872,\"po\":5873,\"Ãº\":5874,\"Ġtrucks\":5875,\"Ġforecasts\":5876,\"view\":5877,\"Ġlongtime\":5878,\"ĠConstitution\":5879,\"Ġreserves\":5880,\"bit\":5881,\"Ġstressed\":5882,\"Ġcontribution\":5883,\"Ġchicken\":5884,\"ĠDE\":5885,\"Ġfat\":5886,\"ĠOscar\":5887,\"Ġcriticized\":5888,\"Ġtestimony\":5889,\"Ġapparent\":5890,\"Ġconstant\":5891,\"Ġcabinet\":5892,\"ĠDuke\":5893,\"Ġaspects\":5894,\"lic\":5895,\"ĠVol\":5896,\"Ġwing\":5897,\"Ġreb\":5898,\"ĠSessions\":5899,\"ĠSmart\":5900,\"car\":5901,\"ĠIm\":5902,\"Ġoperational\":5903,\"Ġregulators\":5904,\"ĠJimmy\":5905,\"eter\":5906,\"Ġnobody\":5907,\"ĠMarc\":5908,\"Ġliterally\":5909,\"Ġresistance\":5910,\"ĠKam\":5911,\"Ġsexually\":5912,\"Ġ69\":5913,\"uth\":5914,\"Ġviewed\":5915,\"Ġpicks\":5916,\"Ġdin\":5917,\"Ġtalented\":5918,\"Ġtennis\":5919,\"Ġstrengthen\":5920,\"Ġgl\":5921,\"ĠProtection\":5922,\"Ġinstalled\":5923,\"ways\":5924,\"ĠCampbell\":5925,\"ĠPortland\":5926,\"Ġintent\":5927,\"ĠPalace\":5928,\"Ġsecondary\":5929,\"Ġlocked\":5930,\"ĠPA\":5931,\"Ġlanded\":5932,\"Ġlength\":5933,\"Ġboosted\":5934,\"Ġpurchases\":5935,\"Ġcommand\":5936,\"ĠAsked\":5937,\"Ġspaces\":5938,\"Ġiconic\":5939,\"Ġrecommend\":5940,\"Ġduties\":5941,\"Ġseized\":5942,\"Ġdelayed\":5943,\"FA\":5944,\"AND\":5945,\"daq\":5946,\"Ġhiring\":5947,\"Ġoccur\":5948,\"DC\":5949,\"ĠMus\":5950,\"Ġag\":5951,\"Ġhopefully\":5952,\"ĠPenn\":5953,\"ards\":5954,\"Ġstriker\":5955,\"Ġrent\":5956,\"ĠTy\":5957,\"ĠBuffalo\":5958,\"ĠKy\":5959,\"Ġhike\":5960,\"pper\":5961,\"Ġ120\":5962,\"Ġop\":5963,\"Ġwheel\":5964,\"ĠIan\":5965,\"Ġchart\":5966,\"tt\":5967,\"Ġvolunteer\":5968,\"IG\":5969,\"person\":5970,\"ight\":5971,\"ĠBook\":5972,\"unt\":5973,\"ĠTechnologies\":5974,\"Now\":5975,\"Ġfavour\":5976,\"ĠGh\":5977,\"ĠQatar\":5978,\"ĠDutch\":5979,\"ĠGrant\":5980,\"ĠBan\":5981,\"rel\":5982,\"Ġagreements\":5983,\"Ġeducational\":5984,\"worth\":5985,\"ĠWard\":5986,\"700\":5987,\"Ġanymore\":5988,\"Ġrepair\":5989,\"Ġoperators\":5990,\"ĠLi\":5991,\"ots\":5992,\"ĠLouisiana\":5993,\"ĠWhether\":5994,\"Ġodds\":5995,\"Ġnoon\":5996,\"ĠStr\":5997,\"Ġfail\":5998,\"iser\":5999,\"Ġforever\":6000,\"Ġrecall\":6001,\"ĠPo\":6002,\"ĠHot\":6003,\"Ġdesigner\":6004,\"ido\":6005,\"LL\":6006,\"ĠControl\":6007,\"Ġsurvive\":6008,\"iam\":6009,\"Ġorganisation\":6010,\"ĠWork\":6011,\"Ġwider\":6012,\"Ġtank\":6013,\"work\":6014,\"ĠAS\":6015,\"Ġposting\":6016,\"Ġsuddenly\":6017,\"MC\":6018,\"ĠAL\":6019,\"ĠProfessor\":6020,\"ĠCoach\":6021,\"Ġrushed\":6022,\"Ġafraid\":6023,\"Ġactivist\":6024,\"that\":6025,\"ĠFilm\":6026,\"Ġbacking\":6027,\"Ġhousehold\":6028,\"Ġsignal\":6029,\"Ġaccurate\":6030,\"str\":6031,\"ĠThread\":6032,\"ĠBears\":6033,\"ATION\":6034,\"ĠAlliance\":6035,\"ĠMcDonald\":6036,\"ĠVenezuela\":6037,\"ogg\":6038,\"ĠWindows\":6039,\"makers\":6040,\"Ġutility\":6041,\"Ġrapidly\":6042,\"Ġattractive\":6043,\"Ġpa\":6044,\"ĠLarry\":6045,\"Ġmisconduct\":6046,\"Ġfreshman\":6047,\"Ġqualified\":6048,\"Ġcleared\":6049,\"Ġcrashed\":6050,\"Ġparticipating\":6051,\"Ġpages\":6052,\"Ġhighlight\":6053,\"Ġdialogue\":6054,\"ĠAlberta\":6055,\"Ġca\":6056,\"Ġwitnesses\":6057,\"ables\":6058,\"Ġfollowers\":6059,\"Ġensuring\":6060,\"Ġpromoting\":6061,\"Ġsearching\":6062,\"Ġremote\":6063,\"Ġclash\":6064,\"Ġfirefighters\":6065,\"Ġteen\":6066,\"ĠPlace\":6067,\"ĠNote\":6068,\"Ġregardless\":6069,\"ult\":6070,\"oney\":6071,\"ander\":6072,\"ional\":6073,\"ining\":6074,\"Ġdemanded\":6075,\"ĠCommunications\":6076,\"Ġconsideration\":6077,\"TC\":6078,\"ĠSoutheast\":6079,\"aga\":6080,\"ĠGarden\":6081,\"inger\":6082,\"ht\":6083,\"Ġbranch\":6084,\"Ġmouth\":6085,\"Ġaudio\":6086,\"Ġraw\":6087,\"Ġcoordinator\":6088,\"Ġexact\":6089,\"ĠHan\":6090,\"Ġdelays\":6091,\"ĠWal\":6092,\"ĠWells\":6093,\"Ġng\":6094,\"Ġhandful\":6095,\"Ġgirlfriend\":6096,\"Ġtypical\":6097,\"ĠWayne\":6098,\"ĠFranklin\":6099,\"Ġconstitutional\":6100,\"ĠChance\":6101,\"Ġblamed\":6102,\"rim\":6103,\"Ġpreliminary\":6104,\"Ġlie\":6105,\"da\":6106,\"ĠCapitol\":6107,\"Ġroutine\":6108,\"ĠNASA\":6109,\"Ġtre\":6110,\"ĠGolf\":6111,\"Ġsight\":6112,\"ĠDer\":6113,\"Ġreserve\":6114,\"150\":6115,\"Ġspeculation\":6116,\"Ġcompetitors\":6117,\"ĠMacron\":6118,\"ony\":6119,\"Ġovertime\":6120,\"Ġ71\":6121,\"Ġdepending\":6122,\"ĠWarner\":6123,\"Ġaccusations\":6124,\"ius\":6125,\"Ġpredicted\":6126,\"ĠCharlie\":6127,\"Ġeverywhere\":6128,\"Ġcable\":6129,\"ĠSaint\":6130,\"ĠRegion\":6131,\"Ġhero\":6132,\"ĠEmb\":6133,\"Ġkinds\":6134,\"Ġstarter\":6135,\"Ġsolve\":6136,\"ĠGuard\":6137,\"Ġloves\":6138,\"ĠDouglas\":6139,\"Ġfunded\":6140,\"ĠBrent\":6141,\"ĠAnyone\":6142,\"Ġsubstantial\":6143,\"ĠMarine\":6144,\"ĠMichelle\":6145,\"Ġcelebrating\":6146,\"Ġoffset\":6147,\"Ġbutton\":6148,\"gg\":6149,\"Ġmedicine\":6150,\"uri\":6151,\"Ġsomewhere\":6152,\"PD\":6153,\"Ġmon\":6154,\"Ġfires\":6155,\"final\":6156,\"oth\":6157,\"ined\":6158,\"Ġunderway\":6159,\"Ġmistakes\":6160,\"Ġgrateful\":6161,\"Ġcheap\":6162,\"È\":6163,\"Ġ95\":6164,\"Ġviolations\":6165,\"arr\":6166,\"Ġsurprising\":6167,\"Ġob\":6168,\"ĠNATO\":6169,\"Ġcontroversy\":6170,\"ĠSweden\":6171,\"Ġfuneral\":6172,\"Ġreviews\":6173,\"Ġpromotion\":6174,\"TY\":6175,\"Ġliberal\":6176,\"Ġpromising\":6177,\"ĠSP\":6178,\"How\":6179,\"Ġmemories\":6180,\"Ġbreast\":6181,\"zi\":6182,\"ights\":6183,\"Ġpattern\":6184,\"Ġoutdoor\":6185,\"ĠMu\":6186,\"Ġrush\":6187,\"ĠTheresa\":6188,\"ĠPol\":6189,\"Ġdescribe\":6190,\"ĠBand\":6191,\"ĠStewart\":6192,\"Ġ1999\":6193,\"ĠRaiders\":6194,\"mp\":6195,\"Ġprocedures\":6196,\"Ġplot\":6197,\"Ġhire\":6198,\"used\":6199,\"Ġ1970\":6200,\"Ġpicking\":6201,\"ĠSim\":6202,\"Ġregard\":6203,\"inal\":6204,\"backs\":6205,\"ĠHard\":6206,\"ĠLow\":6207,\"ĠAc\":6208,\"Is\":6209,\"Ġguarantee\":6210,\"ĠGiven\":6211,\"Ġbeta\":6212,\"ĠTre\":6213,\"Ġtrans\":6214,\"Ġretailer\":6215,\"Ġpurposes\":6216,\"ĠHol\":6217,\"Ġenjoying\":6218,\"Ġbrown\":6219,\"ĠPerry\":6220,\"Ġplea\":6221,\"MS\":6222,\"ĠDakota\":6223,\"ĠParker\":6224,\"Ġcommit\":6225,\"ĠLawrence\":6226,\"ĠMorris\":6227,\"ended\":6228,\"Ġvirtual\":6229,\"ÃĹ\":6230,\"Ġfruit\":6231,\"84\":6232,\"ĠHas\":6233,\"ishing\":6234,\"Ġdominated\":6235,\"ĠFA\":6236,\"Ġchannels\":6237,\"Ġunderstood\":6238,\"Ġcitizen\":6239,\"Ġchecks\":6240,\"ĠKenya\":6241,\"Ġdisabled\":6242,\"SD\":6243,\"Ġprotecting\":6244,\"Ġtweets\":6245,\"Ġsparked\":6246,\"ĠCO\":6247,\"§\":6248,\"ori\":6249,\"ĠGDP\":6250,\"ĠSer\":6251,\"ĠVisit\":6252,\"ĠMS\":6253,\"Ġbarely\":6254,\"Ġsand\":6255,\"Ġap\":6256,\"aging\":6257,\"Ġrel\":6258,\"ĠPerhaps\":6259,\"ĠMourinho\":6260,\"ĠJets\":6261,\"Ġdisclosure\":6262,\"Ġhighlighted\":6263,\"Ġimplemented\":6264,\"Ġcompliance\":6265,\"ĠAB\":6266,\"ĠAssistant\":6267,\"ĠCape\":6268,\"Ġfunny\":6269,\"Ġleverage\":6270,\"Ġmachines\":6271,\"Ġranging\":6272,\"Ġfastest\":6273,\"ĠRoberts\":6274,\"ĠPolicy\":6275,\"gar\":6276,\"Ġcollapse\":6277,\"ĠThrough\":6278,\"Ġrobbery\":6279,\"ĠHay\":6280,\"Ġelite\":6281,\"ĠDigital\":6282,\"ĠFun\":6283,\"ĠAlan\":6284,\"ement\":6285,\"Ġmit\":6286,\"Ġspin\":6287,\"Ġlistening\":6288,\"ĠDoug\":6289,\"ĠSaints\":6290,\"Ġinterior\":6291,\"Ġenhance\":6292,\"ĠCardinals\":6293,\"ever\":6294,\"Ġrobust\":6295,\"Ġinform\":6296,\"Ġsuffer\":6297,\"book\":6298,\"ĠMuslims\":6299,\"Ġagriculture\":6300,\"Ġkm\":6301,\"Ġdivers\":6302,\"Ã±\":6303,\"ĠReg\":6304,\"Ġequivalent\":6305,\"Ġcraft\":6306,\"Ġsettle\":6307,\"Ġcontains\":6308,\"ĠMack\":6309,\"ĠDis\":6310,\"ĠFore\":6311,\"ĠSudan\":6312,\"ĠMail\":6313,\"ĠBrooklyn\":6314,\"izer\":6315,\"bn\":6316,\"Ġhundred\":6317,\"Ġexhibition\":6318,\"ĠHave\":6319,\"vin\":6320,\"Ġcivilians\":6321,\"ĠCincinnati\":6322,\"Some\":6323,\"ĠSE\":6324,\"Ġbat\":6325,\"ĠIns\":6326,\"Ġcalm\":6327,\"Ġtone\":6328,\"Ġnormally\":6329,\"Ġseeks\":6330,\"ĠAss\":6331,\"Ġmembership\":6332,\"Ġannually\":6333,\"Ġemployers\":6334,\"CO\":6335,\"Ġcomplicated\":6336,\"Ġheadlines\":6337,\"ĠLabor\":6338,\"Ġlifestyle\":6339,\"ĠRen\":6340,\"ĠRich\":6341,\"cent\":6342,\"ude\":6343,\"Ġawesome\":6344,\"Ġpaint\":6345,\"Ġrolling\":6346,\"Ġwalls\":6347,\"Ġlab\":6348,\"Ġtourists\":6349,\"care\":6350,\"Ġgear\":6351,\"izz\":6352,\"Ġcream\":6353,\"ĠTro\":6354,\"ices\":6355,\"Ġpack\":6356,\"Ġdiseases\":6357,\"ĠSpeaker\":6358,\"ĠOfficers\":6359,\"Ġsky\":6360,\"83\":6361,\"ĠBE\":6362,\"Ġcategories\":6363,\"Ġindicate\":6364,\"Ġru\":6365,\"ĠSony\":6366,\"ĠDun\":6367,\"ocks\":6368,\"Ġconcrete\":6369,\"ĠMadison\":6370,\"ĠSab\":6371,\"IV\":6372,\"Ġobserved\":6373,\"ria\":6374,\"Ġinterim\":6375,\"Ġencounter\":6376,\"ista\":6377,\"Ġanger\":6378,\"Ġrapid\":6379,\"mail\":6380,\"Ġdestination\":6381,\"ĩ\":6382,\"Ġbreaks\":6383,\"rell\":6384,\"ĠChase\":6385,\"Ġattorneys\":6386,\"Ġrolled\":6387,\"ĠSprings\":6388,\"ĠVillage\":6389,\"TO\":6390,\"HS\":6391,\"Ġcampaigns\":6392,\"ologist\":6393,\"ĠTax\":6394,\"ĠIII\":6395,\"Ġteach\":6396,\"Ġprovision\":6397,\"Ġrem\":6398,\"Ġshirt\":6399,\"Ġdeployed\":6400,\"Ġguidelines\":6401,\"Ġav\":6402,\"zer\":6403,\"Ġrushing\":6404,\"94\":6405,\"place\":6406,\"Man\":6407,\"Ġdivided\":6408,\"ĠGun\":6409,\"Ġwindows\":6410,\"Ġcomponents\":6411,\"aba\":6412,\"ĠSwitzerland\":6413,\"election\":6414,\"ĠTampa\":6415,\"ĠAri\":6416,\"Ã¡s\":6417,\"Ġhighway\":6418,\"Ġacres\":6419,\"Ġcrown\":6420,\"known\":6421,\"Ġinquiry\":6422,\"url\":6423,\"Ġexpertise\":6424,\"Ġpraised\":6425,\"yer\":6426,\"Ġconclusion\":6427,\"Ġabortion\":6428,\"Ġlady\":6429,\"Ġtribute\":6430,\"Ġunveiled\":6431,\"Ġbeaten\":6432,\"TE\":6433,\"ĠMot\":6434,\"unk\":6435,\"Ġtriple\":6436,\"Ġforcing\":6437,\"ĠTickets\":6438,\"uit\":6439,\"Ġiron\":6440,\"Ġscientific\":6441,\"ĠIP\":6442,\"Ġdiagnosed\":6443,\"Ġocean\":6444,\"wide\":6445,\"ĠCowboys\":6446,\"LC\":6447,\"Ġmethods\":6448,\"ĠFind\":6449,\"ĠDean\":6450,\"Ġfundamental\":6451,\"ĠGill\":6452,\"Ġfeelings\":6453,\"IO\":6454,\"hu\":6455,\"Ġfeedback\":6456,\"ote\":6457,\"Ġduo\":6458,\"fully\":6459,\"get\":6460,\"Ġproof\":6461,\"story\":6462,\"Ġlongest\":6463,\"Ġshops\":6464,\"ĠJong\":6465,\"ĠCro\":6466,\"ĠHawaii\":6467,\"91\":6468,\"ĠJake\":6469,\"ĠSusan\":6470,\"Ġsubmit\":6471,\"rav\":6472,\"Ġmodest\":6473,\"Ġlit\":6474,\"Ġattempting\":6475,\"Ġsits\":6476,\"Ġaddressing\":6477,\"93\":6478,\"ĠBi\":6479,\"Ġlying\":6480,\"ĠOrganization\":6481,\"ĠOak\":6482,\"oli\":6483,\"Ġfatal\":6484,\"Ġmountain\":6485,\"val\":6486,\"lu\":6487,\"ĠMaine\":6488,\"Ġcharging\":6489,\"Ġresigned\":6490,\"illo\":6491,\"Ġrecommendation\":6492,\"party\":6493,\"ĠWeb\":6494,\"ĠPanthers\":6495,\"Ġnoise\":6496,\"ĠBrussels\":6497,\"awa\":6498,\"Ġambassador\":6499,\"Ġaccessible\":6500,\"ĠCalgary\":6501,\"idd\":6502,\"ĠAirlines\":6503,\"gr\":6504,\"Ġnu\":6505,\"roy\":6506,\"ĠMars\":6507,\"ĠPoland\":6508,\"ĠJerry\":6509,\"ados\":6510,\"ĠRico\":6511,\"ĠMir\":6512,\"ĠFin\":6513,\"ious\":6514,\"Ġpacked\":6515,\"Ġinsider\":6516,\"President\":6517,\"ĠBull\":6518,\"ĠYemen\":6519,\"ĠConnecticut\":6520,\"Ġ73\":6521,\"Ġdepartments\":6522,\"Ġorganic\":6523,\"ĠSummer\":6524,\"ĠBet\":6525,\"ste\":6526,\"zo\":6527,\"rat\":6528,\"Ġalliance\":6529,\"Ġintervention\":6530,\"wan\":6531,\"ĠOR\":6532,\"Ġdefined\":6533,\"ĠÃł\":6534,\"ĠChiefs\":6535,\"Ġknocked\":6536,\"ared\":6537,\"Ġholes\":6538,\"Ġpulling\":6539,\"ĠTodd\":6540,\"ĠJamie\":6541,\"ĠSher\":6542,\"Ġsignature\":6543,\"ĠSur\":6544,\"Ġgym\":6545,\"ĠVladimir\":6546,\"ĠThailand\":6547,\"Ġgaming\":6548,\"Ġsaving\":6549,\"ceive\":6550,\"82\":6551,\"ĠBern\":6552,\"ĠDid\":6553,\"Ġhardware\":6554,\"ished\":6555,\"Ġconspiracy\":6556,\"ANS\":6557,\"ĠIntelligence\":6558,\"Ġassembly\":6559,\"Ġ101\":6560,\"Ġconcise\":6561,\"ĠManhattan\":6562,\"Ġbelief\":6563,\"Ġsurge\":6564,\"Ġdeserve\":6565,\"Ġconsistently\":6566,\"ĠNor\":6567,\"okes\":6568,\"ðŁ\":6569,\"ME\":6570,\"ĠAsset\":6571,\"Ġsubstance\":6572,\"Ġprefer\":6573,\"Ġburning\":6574,\"ĠNik\":6575,\"ook\":6576,\"ĠPinterest\":6577,\"Ġboyfriend\":6578,\"ĠHal\":6579,\"ĠMerkel\":6580,\"Ġintroduce\":6581,\"ĠLinkedIn\":6582,\"ĠFull\":6583,\"ĠFarm\":6584,\"Ġchildhood\":6585,\"ĠTransportation\":6586,\"Ġterrible\":6587,\"du\":6588,\"Ġintention\":6589,\"Ġseemingly\":6590,\"elle\":6591,\"Ġfoods\":6592,\"Ġtitled\":6593,\"Ġdual\":6594,\"Ġimport\":6595,\"Ġdeveloper\":6596,\"UL\":6597,\"ington\":6598,\"ĠDelta\":6599,\"?'\":6600,\"iness\":6601,\"Ġquit\":6602,\"ĠGarcia\":6603,\"ĠSri\":6604,\"Ġhip\":6605,\"ĠBrazilian\":6606,\"elt\":6607,\"ively\":6608,\"Ġstructures\":6609,\"Ġlabour\":6610,\"Ġneighbors\":6611,\"Ġtill\":6612,\"Ġsoil\":6613,\"Ġdropping\":6614,\"Ġnominee\":6615,\"Ġmeets\":6616,\"92\":6617,\"rant\":6618,\"isa\":6619,\"Ġluck\":6620,\"aa\":6621,\"jet\":6622,\"ĠTor\":6623,\"ĠCrime\":6624,\"Ġlane\":6625,\"Ġflu\":6626,\"Ġlaunching\":6627,\"ĠAutom\":6628,\"aks\":6629,\"Ġuniversities\":6630,\"Ġpollution\":6631,\"ĠAdvis\":6632,\"ĠMall\":6633,\"ls\":6634,\"Ġdeeper\":6635,\"Ġrepeated\":6636,\"Ġmeanwhile\":6637,\"Ġchip\":6638,\"Ġoutlets\":6639,\"Ġliked\":6640,\"Ġsal\":6641,\"Ġwelfare\":6642,\"ago\":6643,\"Ġmakers\":6644,\"ving\":6645,\"fer\":6646,\"Ġovercome\":6647,\"mb\":6648,\"Ġshocked\":6649,\"akers\":6650,\"Ġnonprofit\":6651,\"Ġdonated\":6652,\"eral\":6653,\"Ġresume\":6654,\"Ġlogo\":6655,\"Ġsubscription\":6656,\"Ġ74\":6657,\"ela\":6658,\"Ġaspect\":6659,\"html\":6660,\"Ġsorry\":6661,\"Ġupgrade\":6662,\"Ġstance\":6663,\"Ġfr\":6664,\"Ġpapers\":6665,\"Ġattacking\":6666,\"Ġmeaningful\":6667,\"81\":6668,\"ĠWeinstein\":6669,\"Ġcreates\":6670,\"Ġhonour\":6671,\"ĠReply\":6672,\"oph\":6673,\"Ġmarch\":6674,\"Ġsmile\":6675,\"Ġcomparison\":6676,\"will\":6677,\"ĠSanchez\":6678,\"Ġvoter\":6679,\"Ġtheory\":6680,\"Ġequally\":6681,\"ĠRoger\":6682,\"Ġperfectly\":6683,\"Ġlanding\":6684,\"Ġbillions\":6685,\"ĠBloomberg\":6686,\"Ġpermit\":6687,\"Ġfinals\":6688,\"Ġracial\":6689,\"Ġpregnancy\":6690,\"iled\":6691,\"ĠFederation\":6692,\"Ġforest\":6693,\"Ġtag\":6694,\"aul\":6695,\"Ġdrinks\":6696,\"Ġ(\\\"\":6697,\"ĠMobile\":6698,\"Ġtouched\":6699,\"Ġclock\":6700,\"Ġreg\":6701,\"Ġasylum\":6702,\"igan\":6703,\"Ġsenator\":6704,\"Ġ99\":6705,\"ĠKumar\":6706,\"Ġskill\":6707,\"Ġ1998\":6708,\"pa\":6709,\"ĠAf\":6710,\"Ġmood\":6711,\"ston\":6712,\"Ġhang\":6713,\"ĠMPs\":6714,\"Please\":6715,\"ĠEve\":6716,\"Ġdocumentary\":6717,\"Ġpersonality\":6718,\"ĠCast\":6719,\"Ġdiscount\":6720,\"bing\":6721,\"ĠBoeing\":6722,\"Ġdepend\":6723,\"Ġcrossing\":6724,\"EX\":6725,\"Ġsucceed\":6726,\"Ġhumanitarian\":6727,\"ĠMuhammad\":6728,\"Ġwages\":6729,\"Ġcolumn\":6730,\"Ġexternal\":6731,\"Ġstatistics\":6732,\"ĠTODAY\":6733,\"Ġtrips\":6734,\"Ġta\":6735,\"Ġpenalties\":6736,\"Ġwriters\":6737,\"Ġshipping\":6738,\"ĠIndians\":6739,\"Ġsalt\":6740,\"ĠIndustrial\":6741,\"ĠYankees\":6742,\"ĠDen\":6743,\"Ġrough\":6744,\"Ġbarrels\":6745,\"ĠHor\":6746,\"bert\":6747,\"ĠDep\":6748,\"Ġresign\":6749,\"97\":6750,\"Ġballs\":6751,\"ĠJun\":6752,\"ĠBab\":6753,\"Ġassociate\":6754,\"Ġstring\":6755,\"Ġhub\":6756,\"Ġorgan\":6757,\"ĠMarshall\":6758,\"ĠFIFA\":6759,\"ĠMun\":6760,\"ency\":6761,\"research\":6762,\"Ġpeers\":6763,\"Ġtall\":6764,\"ĠGoldman\":6765,\"Don\":6766,\"Ġparade\":6767,\"Ġparks\":6768,\"Ġdet\":6769,\"Ġdisappointing\":6770,\"Ġreflects\":6771,\"ĠLakers\":6772,\"Ġfiles\":6773,\"Ġrelatives\":6774,\"ĠUSD\":6775,\"ĠArticle\":6776,\"Ġcustom\":6777,\"ĠCarlos\":6778,\"Ġtracking\":6779,\"Ġmaintaining\":6780,\"ĠCur\":6781,\"ardo\":6782,\"ĠSkip\":6783,\"Ġattitude\":6784,\"Just\":6785,\"Ġinstitution\":6786,\"Ġnarrow\":6787,\"Ġsnap\":6788,\"Ġenterprise\":6789,\"Ġdrives\":6790,\"Ġ77\":6791,\"Ġcrop\":6792,\"Ġvirus\":6793,\"Ġcelebrity\":6794,\"Ġeconomies\":6795,\"ued\":6796,\"Ġsum\":6797,\"ĠDubai\":6798,\"ĠInsurance\":6799,\"Ĺ\":6800,\"ury\":6801,\"ĠUnfortunately\":6802,\"Ġclosure\":6803,\"ota\":6804,\"ĠPhilip\":6805,\"oms\":6806,\"Ġinvestigated\":6807,\"Ġgenerations\":6808,\"ĠETF\":6809,\"ĠKeith\":6810,\"ĠLater\":6811,\"isk\":6812,\"Ġpreferred\":6813,\"Ġdefault\":6814,\"Ġtowns\":6815,\"ĠRod\":6816,\"ĠDie\":6817,\"Ġintegrated\":6818,\"Ġacquiring\":6819,\"Ġvoices\":6820,\"Ġser\":6821,\"Ġpresents\":6822,\"ĠBR\":6823,\"ĠEmergency\":6824,\"Ġreligion\":6825,\"HA\":6826,\"Ġresponding\":6827,\"ĠThings\":6828,\"Ġbeef\":6829,\"ĠWithout\":6830,\"urd\":6831,\"ĠCarl\":6832,\"Ġadministrative\":6833,\"ĠWhich\":6834,\"Ġchallenged\":6835,\"Ġcooking\":6836,\"ivid\":6837,\"ĠFer\":6838,\"Ġtremendous\":6839,\"ĠTerry\":6840,\"iri\":6841,\"CS\":6842,\"ĠJunior\":6843,\"ĠReddit\":6844,\"Ġtea\":6845,\"Ġaccounting\":6846,\"lan\":6847,\"Ġdetention\":6848,\"Ġreplied\":6849,\"SI\":6850,\"ĠHel\":6851,\"ns\":6852,\"ĠProf\":6853,\"Ġramp\":6854,\"ĠConservative\":6855,\"Ġattendance\":6856,\"Ġspecialist\":6857,\"ĠFinal\":6858,\"Ġadvertisement\":6859,\"Ġacquire\":6860,\"ĠWhatsApp\":6861,\"Ġworkforce\":6862,\"ĠCalif\":6863,\"Ġspeakers\":6864,\"ĠEPA\":6865,\"Ġconviction\":6866,\"hire\":6867,\"ĠFisher\":6868,\"ĠIntel\":6869,\"Ġbin\":6870,\"ĠWas\":6871,\"Ġearth\":6872,\"vi\":6873,\"Ġhurricane\":6874,\"Ġholidays\":6875,\"Ġassume\":6876,\"Ġinvolve\":6877,\"Ġdynamic\":6878,\"ĠGre\":6879,\"Ġitem\":6880,\"Ġpound\":6881,\"Ġanxiety\":6882,\"ĠPrint\":6883,\"rop\":6884,\"Ġautomatically\":6885,\"Ġdiscrimination\":6886,\"ĠLam\":6887,\"ĠColl\":6888,\"Ġimpressed\":6889,\"Ġinvolves\":6890,\"ĠLes\":6891,\"ĠTri\":6892,\"ĠLook\":6893,\"ĠiOS\":6894,\"Ġgrab\":6895,\"ĠAngel\":6896,\"Ġstops\":6897,\"ĠPay\":6898,\"ĠECB\":6899,\"Ġbunch\":6900,\"Ġletting\":6901,\"ele\":6902,\"ĠAdditionally\":6903,\"Ġboards\":6904,\"NC\":6905,\"Ġtragedy\":6906,\"Ġpink\":6907,\"Ġgonna\":6908,\"ones\":6909,\"Ġrev\":6910,\"ĠIndependent\":6911,\"ĠCambridge\":6912,\"ĠPence\":6913,\"Ġprosecution\":6914,\"Ġdeputies\":6915,\"ĠAhmed\":6916,\"Ġlows\":6917,\"ĠAmy\":6918,\"ĠBuilding\":6919,\"mark\":6920,\"Ġsmooth\":6921,\"Ġsole\":6922,\"Ġwanting\":6923,\"ĠHeart\":6924,\"Ġobtain\":6925,\"ĠBus\":6926,\"Ġexchanges\":6927,\"friendly\":6928,\"Ġlabel\":6929,\"elect\":6930,\"ĠCompanies\":6931,\"owing\":6932,\"ĠCB\":6933,\"RI\":6934,\"ĠMaster\":6935,\"Ġliquid\":6936,\"ĠDanny\":6937,\"Ġproceeds\":6938,\"ĠLaura\":6939,\"card\":6940,\"Ġtears\":6941,\"Ġexploration\":6942,\"Ġdepression\":6943,\"ken\":6944,\"ĠFe\":6945,\"Ġlending\":6946,\"ĠYouth\":6947,\"ality\":6948,\"NS\":6949,\"Ġmoon\":6950,\"ĠTaiwan\":6951,\"Ġstruggles\":6952,\"Ġdiscovery\":6953,\"Ġqualify\":6954,\"Ġwireless\":6955,\"alia\":6956,\"Ġwitnessed\":6957,\"Ġheight\":6958,\"ĠGuy\":6959,\"left\":6960,\"KE\":6961,\"Ġfoul\":6962,\"ĠMohammed\":6963,\"Ġgrass\":6964,\"ĠNon\":6965,\"Ġswim\":6966,\"Ġbrilliant\":6967,\"you\":6968,\"ĠFlynn\":6969,\"Ġsinging\":6970,\"eria\":6971,\"UT\":6972,\"ĠMcCain\":6973,\"ĠSep\":6974,\"ĠWars\":6975,\"Ġburden\":6976,\"Ġpas\":6977,\"Ġabandoned\":6978,\"Ġint\":6979,\"ĠTurner\":6980,\"Ġcollective\":6981,\"ĠEnvironmental\":6982,\"ĠStudents\":6983,\"Ġofferings\":6984,\"Ġresignation\":6985,\"Ġexplosion\":6986,\"ĠKoh\":6987,\"ager\":6988,\"Ġthrows\":6989,\"Ġasks\":6990,\"light\":6991,\"Ġanyway\":6992,\"Ġyard\":6993,\"Ġcarrier\":6994,\"Ġwaves\":6995,\"backed\":6996,\"TR\":6997,\"oud\":6998,\"Ġbreach\":6999,\"Ġdated\":7000,\"Ġdressed\":7001,\"ĠDodgers\":7002,\"oles\":7003,\"Ġ78\":7004,\"Ġreads\":7005,\"Ġpredict\":7006,\"ĠJerusalem\":7007,\"ĠPT\":7008,\"Ġcrack\":7009,\"yan\":7010,\"Ġnights\":7011,\"eline\":7012,\"Ġconvinced\":7013,\"Ġlock\":7014,\"Ġcarefully\":7015,\"ĠMercedes\":7016,\"Ġultimate\":7017,\"Ġdist\":7018,\"Ġslight\":7019,\"ĠEdwards\":7020,\"Ġswing\":7021,\"iling\":7022,\"Ġknife\":7023,\"ĠNashville\":7024,\"IF\":7025,\"inder\":7026,\"udd\":7027,\"Ġsenators\":7028,\"ĠFurther\":7029,\"ĠXi\":7030,\"Ġstr\":7031,\"ĠOd\":7032,\"days\":7033,\"Ġcomm\":7034,\"Ġverdict\":7035,\"Ġconfirmation\":7036,\"king\":7037,\"ĠCS\":7038,\"Ġadvocates\":7039,\"Ġpride\":7040,\"Ġmemorial\":7041,\"ams\":7042,\"erman\":7043,\"Ġteenager\":7044,\"ĠNeil\":7045,\"uts\":7046,\"Ġsoul\":7047,\"see\":7048,\"post\":7049,\"Ġchest\":7050,\"fire\":7051,\"ĠLynch\":7052,\"Ġpeaceful\":7053,\"OND\":7054,\"ĠIndustries\":7055,\"ĠJuan\":7056,\"Ġrestore\":7057,\"Ġreliable\":7058,\"ming\":7059,\"agan\":7060,\"Source\":7061,\"ĠCabinet\":7062,\"Ġremarkable\":7063,\"ĠTrudeau\":7064,\"ĠEs\":7065,\"Ġintegrity\":7066,\"ove\":7067,\"fe\":7068,\"Ġproceedings\":7069,\"Ġconnections\":7070,\"Ġunprecedented\":7071,\"ĠGlen\":7072,\"ux\":7073,\"Ġearning\":7074,\"Ġingredients\":7075,\"Ġnominated\":7076,\"ĠBangladesh\":7077,\"made\":7078,\"Ġlessons\":7079,\"Ġbreakfast\":7080,\"ĠRelations\":7081,\"Ġloose\":7082,\"Al\":7083,\"Ġupgraded\":7084,\"ral\":7085,\"ĠPage\":7086,\"oto\":7087,\"ĠQueensland\":7088,\"Ġprocedure\":7089,\"ĠSmall\":7090,\"Ġrespective\":7091,\"Ġpictured\":7092,\"ĠBas\":7093,\"Ġpreparation\":7094,\"ĠMyanmar\":7095,\"Ġdonation\":7096,\"Ġvisible\":7097,\"iest\":7098,\"ĠBroadway\":7099,\"rick\":7100,\"ĠSchools\":7101,\"Ġarrests\":7102,\"ĠJessica\":7103,\"ĠBengal\":7104,\"Ġhell\":7105,\"Ġannouncing\":7106,\"Ġmail\":7107,\"ĠMcG\":7108,\"two\":7109,\"rest\":7110,\"OD\":7111,\"ĠBradley\":7112,\"Ġdoubled\":7113,\"Ġpledged\":7114,\"Ġcomeback\":7115,\"Ġextraordinary\":7116,\"Ġslide\":7117,\"Ġassess\":7118,\"Ġagricultural\":7119,\"ĠKay\":7120,\"Ġvendors\":7121,\"Ġnarrative\":7122,\"Ġreviewed\":7123,\"ĠPass\":7124,\"Ġinspiration\":7125,\"ĠHunter\":7126,\"Ġcalendar\":7127,\"ĠDiamond\":7128,\"Ġremoval\":7129,\"ners\":7130,\"ĠKap\":7131,\"Ġconsent\":7132,\"Ġvisual\":7133,\"Ġcheese\":7134,\"ĠTher\":7135,\"ĠFR\":7136,\"ĠShanghai\":7137,\"iah\":7138,\"ĠCole\":7139,\"AK\":7140,\"Ġranking\":7141,\"Ġcook\":7142,\"Ġhalftime\":7143,\"ĠStars\":7144,\"Ġroutes\":7145,\"aim\":7146,\"Ġestablishment\":7147,\"ĠMug\":7148,\"Ġsurvivors\":7149,\"urg\":7150,\"ĠBrett\":7151,\"Ġunexpected\":7152,\"ained\":7153,\"Ġrarely\":7154,\"ĠGall\":7155,\"Ġadvocate\":7156,\"ĠNad\":7157,\"Ġ911\":7158,\"Ġracist\":7159,\"erer\":7160,\"ĠRev\":7161,\"ĠSection\":7162,\"Ġhelpful\":7163,\"CT\":7164,\"agg\":7165,\"Ġgovernance\":7166,\"Ġfelony\":7167,\"Ġoptimistic\":7168,\"Ġelectoral\":7169,\"EG\":7170,\"town\":7171,\"Ġdaughters\":7172,\"Ġanswered\":7173,\"Ġthin\":7174,\"ĠClassic\":7175,\"Ġshareholder\":7176,\"ĠBlake\":7177,\"ĠFla\":7178,\"Ġparliamentary\":7179,\"dy\":7180,\"Ġcommented\":7181,\"Ġtri\":7182,\"Ġglobe\":7183,\"Ġmandate\":7184,\"Ġslipped\":7185,\"ĠTower\":7186,\"Ġoperated\":7187,\"gers\":7188,\"Ġassured\":7189,\"ĠMartinez\":7190,\"Ġdesigns\":7191,\"ĠModel\":7192,\"Ġstakeholders\":7193,\"Ġdefended\":7194,\"Ġseniors\":7195,\"Ġvacation\":7196,\"Ġglobally\":7197,\"ump\":7198,\"Not\":7199,\"Ġclip\":7200,\"Ġarticles\":7201,\"BR\":7202,\"km\":7203,\"ĠFront\":7204,\"PL\":7205,\"Ġadoption\":7206,\"Ġsudden\":7207,\"Ġframework\":7208,\"Ġhanging\":7209,\"gl\":7210,\"ĠSel\":7211,\"Ġmoderate\":7212,\"Ġreverse\":7213,\"income\":7214,\"cor\":7215,\"ĠGB\":7216,\"Ġphysically\":7217,\"Ġtransparency\":7218,\"ĠElectric\":7219,\"Ġrefugee\":7220,\"profile\":7221,\"iva\":7222,\"ately\":7223,\"ĠAC\":7224,\"Ġtransferred\":7225,\"Ġaffair\":7226,\"ĠAlaska\":7227,\"oria\":7228,\"ĠChange\":7229,\"Ġrepeat\":7230,\"Ġscreening\":7231,\"ender\":7232,\"ĠCas\":7233,\"ĠDav\":7234,\"Ġfocuses\":7235,\"Ġcommissioner\":7236,\"Ġupside\":7237,\"ĠKeep\":7238,\"ĠBlues\":7239,\"ently\":7240,\"Ġaut\":7241,\"Ġexperiencing\":7242,\"aman\":7243,\"Ġapprove\":7244,\"Ġmile\":7245,\"Ġcheaper\":7246,\"ĠWind\":7247,\"ĠStore\":7248,\"Ġgrabbed\":7249,\"Ġsons\":7250,\"Ġfighter\":7251,\"Ġum\":7252,\"ĠBased\":7253,\"don\":7254,\"Ġconstitution\":7255,\"finals\":7256,\"act\":7257,\"¢\":7258,\"Ġmill\":7259,\"Ġorganisations\":7260,\"ĠToyota\":7261,\"Ġyuan\":7262,\"Ġterrorists\":7263,\"Ġforth\":7264,\"Ġavailability\":7265,\"Ġentrance\":7266,\"Ġvolumes\":7267,\"Ġmult\":7268,\"plus\":7269,\"ĠColumbus\":7270,\"ĠSummit\":7271,\"Ġbabies\":7272,\"ĠMur\":7273,\"ĠGray\":7274,\"ĠChar\":7275,\"ĠButler\":7276,\"Ġpose\":7277,\"ĠNatural\":7278,\"ĠAtt\":7279,\"Ġdecrease\":7280,\"Ġtens\":7281,\"kt\":7282,\"Ġminds\":7283,\"Ġimpacted\":7284,\"Ġchapter\":7285,\"ĠOp\":7286,\"ĠHarrison\":7287,\"ĠRodriguez\":7288,\"Ġethnic\":7289,\"Ġtravelling\":7290,\"ĠBond\":7291,\"ader\":7292,\"core\":7293,\"Ġgallery\":7294,\"founder\":7295,\"ĠVill\":7296,\"Ġdecent\":7297,\"ĠHistory\":7298,\"ĠInt\":7299,\"ĠNa\":7300,\"ĠHad\":7301,\"Ġmainstream\":7302,\"ĠTs\":7303,\"Ġbottle\":7304,\"sen\":7305,\"Ġrecession\":7306,\"Ġsophomore\":7307,\"Ġsilence\":7308,\"cc\":7309,\"Ġqualifying\":7310,\"Ġcomplained\":7311,\"ĠRad\":7312,\"Ġactively\":7313,\"Ġbacks\":7314,\"ĠMusk\":7315,\"Ġcareful\":7316,\"Ġmeals\":7317,\"ĠDor\":7318,\"Ġmess\":7319,\"ĠBelgium\":7320,\"Ġke\":7321,\"ĠLopez\":7322,\"Ġbow\":7323,\"Ġhelicopter\":7324,\"was\":7325,\"Ġstone\":7326,\"kins\":7327,\"Ġunlike\":7328,\"Ġcollision\":7329,\"ĠAlt\":7330,\"HP\":7331,\"ĠMason\":7332,\"has\":7333,\"Ġclimbed\":7334,\"Ġindication\":7335,\"Ġhotels\":7336,\"Ġloud\":7337,\"ĠMilan\":7338,\"kes\":7339,\"Ġbadly\":7340,\"Ġtrials\":7341,\"Ġimpacts\":7342,\"ĠJane\":7343,\"Ġcrossed\":7344,\"Ġdiscussing\":7345,\"ĠSM\":7346,\"Ġpopularity\":7347,\"ĠWant\":7348,\"fall\":7349,\"Ġartificial\":7350,\"ĠBu\":7351,\"akh\":7352,\"Ġdominant\":7353,\"gov\":7354,\"Ġpremier\":7355,\"Ġexecution\":7356,\"gate\":7357,\"Ġswimming\":7358,\"Ġchat\":7359,\"Ġdevastating\":7360,\"acking\":7361,\"Ġreception\":7362,\"urt\":7363,\"Ġtheater\":7364,\"Ġgather\":7365,\"Ġtear\":7366,\"uro\":7367,\"Ġdemocratic\":7368,\"Ġrebels\":7369,\"Ġlifetime\":7370,\"Ġradical\":7371,\"uan\":7372,\"Ġtechniques\":7373,\"ache\":7374,\"ior\":7375,\"Ġcamps\":7376,\"Ġtelephone\":7377,\"ĠDublin\":7378,\"ĠBrand\":7379,\"ĠMarcus\":7380,\"aun\":7381,\"ĠRec\":7382,\"Ġ82\":7383,\"ban\":7384,\"Ġsafely\":7385,\"aku\":7386,\"aki\":7387,\"Ġbankruptcy\":7388,\"FF\":7389,\"Ġformat\":7390,\"Ġattached\":7391,\"ĠFame\":7392,\"ĠEdward\":7393,\"Ġmerger\":7394,\"ĠRepresentatives\":7395,\"izes\":7396,\"Ġhidden\":7397,\"Ġval\":7398,\"zz\":7399,\"Ġexcess\":7400,\"Ġscope\":7401,\"Ġdivorce\":7402,\"Ġburn\":7403,\"Ġrequirement\":7404,\"BB\":7405,\"ĠHand\":7406,\"Ġcons\":7407,\"Ġrisen\":7408,\"Ġtwitter\":7409,\"Ġoffseason\":7410,\"ĠSometimes\":7411,\"ĠInf\":7412,\"ĠAng\":7413,\"uer\":7414,\"report\":7415,\"Ġdreams\":7416,\"Ġ700\":7417,\"ips\":7418,\"ĠDream\":7419,\"Ġgifts\":7420,\"Ġsomehow\":7421,\"ĠTur\":7422,\"ĠRachel\":7423,\"can\":7424,\"Ġlog\":7425,\"ĠMedicaid\":7426,\"Ġles\":7427,\"Ġtired\":7428,\"ĠArkansas\":7429,\"Ġliquidity\":7430,\"ĠPhillips\":7431,\"ĠBTC\":7432,\"Ġhide\":7433,\"Ġpun\":7434,\"ĠRun\":7435,\"lyn\":7436,\"ĠUC\":7437,\"ĠDesign\":7438,\"ĠDev\":7439,\"Ġvaluation\":7440,\"Ġreveals\":7441,\"ĠChild\":7442,\"other\":7443,\"Ġposed\":7444,\"lee\":7445,\"Ġships\":7446,\"ĠTrue\":7447,\"Ġdescribes\":7448,\"Ġrunner\":7449,\"bro\":7450,\"Ġankle\":7451,\"Ġod\":7452,\"ĠAnnual\":7453,\"CL\":7454,\"Ġoverhaul\":7455,\"ned\":7456,\"Ġbold\":7457,\"Ġmo\":7458,\"ĠFalls\":7459,\"Ġemployed\":7460,\"ĠGro\":7461,\"Ġflash\":7462,\"ĠTD\":7463,\"Ġnervous\":7464,\"Ġintegration\":7465,\"Ġsmartphones\":7466,\"Ġmovements\":7467,\"nie\":7468,\"ition\":7469,\"ĠThird\":7470,\"Ģ\":7471,\"Ġmetres\":7472,\"Ġeconomist\":7473,\"omp\":7474,\"Ġteens\":7475,\"Ġeveryday\":7476,\"Ġinterviewed\":7477,\"Ġbriefly\":7478,\"],\":7479,\"uke\":7480,\"ĠFOX\":7481,\"Ġunderlying\":7482,\"ĠLuc\":7483,\"Ġcourses\":7484,\"ss\":7485,\"amed\":7486,\"°\":7487,\"ju\":7488,\"ĠBanks\":7489,\"Ġoutfit\":7490,\"illing\":7491,\"Ġtrafficking\":7492,\"Ġurging\":7493,\"Ġbelt\":7494,\"Ġrid\":7495,\"CP\":7496,\"Ġelderly\":7497,\"ĠGrowth\":7498,\"Ã¡n\":7499,\"ĠSn\":7500,\"Ġsurrounded\":7501,\"Ġsisters\":7502,\"ĠIslam\":7503,\"Ġsynd\":7504,\"ĠCosta\":7505,\"di\":7506,\"ĠKl\":7507,\"Ġmanufacturer\":7508,\"holders\":7509,\"Ġelement\":7510,\"Ġload\":7511,\"Ġbooked\":7512,\"Ġaccompanied\":7513,\"ĠChamber\":7514,\"Ġbriefing\":7515,\"Oh\":7516,\"imi\":7517,\"ĠDefence\":7518,\"ĠCurrently\":7519,\"aking\":7520,\"Ġhandled\":7521,\"ĠCD\":7522,\"ĠBenjamin\":7523,\"Ġpocket\":7524,\"ĠKashmir\":7525,\"Ġlighting\":7526,\"aps\":7527,\"Ġ1997\":7528,\"ech\":7529,\"Ġaddiction\":7530,\"Ġbases\":7531,\"Ġpriorities\":7532,\"Ġhardly\":7533,\"ĠQuebec\":7534,\"ĠEarn\":7535,\"IES\":7536,\"ĠZach\":7537,\"ĠAlong\":7538,\"MI\":7539,\"Ġins\":7540,\"ĠRogers\":7541,\"ĠKan\":7542,\"ĠFuture\":7543,\"Ġtriggered\":7544,\"ĠUnit\":7545,\"Ġweighed\":7546,\"Ġpointing\":7547,\"Ġchocolate\":7548,\"ĠBrowns\":7549,\"ĠISIS\":7550,\"Ġgoalkeeper\":7551,\"Ġsaves\":7552,\"ĠAndre\":7553,\"burn\":7554,\"ĠCont\":7555,\"ĠNetherlands\":7556,\"Ġpolitically\":7557,\"ĠAshley\":7558,\"ĠWhit\":7559,\"aded\":7560,\"PH\":7561,\"Ġborders\":7562,\"ORE\":7563,\"Ġally\":7564,\"Trump\":7565,\"istan\":7566,\"ĠHunt\":7567,\"ĠCancer\":7568,\"ĠGrace\":7569,\"ĠTottenham\":7570,\"Ġ1960\":7571,\"ĠMarg\":7572,\"ĠBryan\":7573,\"ĠAgain\":7574,\"acing\":7575,\"Ġarguments\":7576,\"ĠSouthwest\":7577,\"Ġvocal\":7578,\"Ġjudgment\":7579,\"Ġengaging\":7580,\"Ġadopt\":7581,\"Ġrental\":7582,\"Ġlinebacker\":7583,\"ĠKardashian\":7584,\"Ġepisodes\":7585,\"..\":7586,\"Ġunt\":7587,\"Ġvowed\":7588,\"Ġ79\":7589,\"ule\":7590,\"Ġtransit\":7591,\"Ġoffshore\":7592,\"Ġsuppliers\":7593,\"Ġarguing\":7594,\"Ġsatellite\":7595,\"ĠLind\":7596,\"ĠTaliban\":7597,\"Buy\":7598,\"ĠCaribbean\":7599,\"ĠBarry\":7600,\"Ġauthors\":7601,\"ĠWolf\":7602,\"Ġviewing\":7603,\"ĠCubs\":7604,\"From\":7605,\"Ġ%\":7606,\"Ġcurrencies\":7607,\"Why\":7608,\"ĠBroncos\":7609,\"Ġtrick\":7610,\"Ġdiesel\":7611,\"ĠLiberal\":7612,\"FL\":7613,\"Ġtopics\":7614,\"Ġretain\":7615,\"ĠLiberty\":7616,\"Ġacquisitions\":7617,\"ced\":7618,\"Ġfre\":7619,\"Ġfleet\":7620,\"Ġcopper\":7621,\"ĠPot\":7622,\"jen\":7623,\"ĠElliott\":7624,\"ĠPyongyang\":7625,\"Ġobject\":7626,\"ĠUse\":7627,\"Ġmutual\":7628,\"MP\":7629,\"Ġev\":7630,\"Ġdeny\":7631,\"ĠEveryone\":7632,\"lling\":7633,\"Ġpays\":7634,\"Ġdrought\":7635,\"Ġcorn\":7636,\"Ġworkplace\":7637,\"rig\":7638,\"ĠMn\":7639,\"Ġadvisory\":7640,\"ĠCat\":7641,\"Ġchronic\":7642,\"ĠSteelers\":7643,\"Ġboxes\":7644,\"ĠNap\":7645,\"Ġdemonstrated\":7646,\"ĠTournament\":7647,\"Ġsymbol\":7648,\"ĠAfghan\":7649,\"ĠTan\":7650,\"ired\":7651,\"ĠEv\":7652,\"ĠConsumer\":7653,\"Ġmoral\":7654,\"ĠAdditional\":7655,\"Ġwebsites\":7656,\"Ġoccasions\":7657,\"Ġfate\":7658,\"Ġpitcher\":7659,\"Ġtaxpayers\":7660,\"Ġdeemed\":7661,\"ĠLibya\":7662,\"Ġpriced\":7663,\"Ġdistributed\":7664,\"ĠForum\":7665,\"Ġrice\":7666,\"Ġbloc\":7667,\"Ġprovisions\":7668,\"agh\":7669,\"Ġpen\":7670,\"Ġattracted\":7671,\"ĠEdmonton\":7672,\"Ġthousand\":7673,\"Ġpainting\":7674,\"Ġil\":7675,\"Ġcourtesy\":7676,\"Ġeliminate\":7677,\"Ġacc\":7678,\"Ġmeters\":7679,\"Ġreflected\":7680,\"Ġcomponent\":7681,\"Every\":7682,\"Ġsells\":7683,\"Ġfault\":7684,\"Ġburned\":7685,\"ĠKirk\":7686,\"ĠAnna\":7687,\"Ġappeals\":7688,\"Ġeggs\":7689,\"Ġfrequent\":7690,\"Ġtrigger\":7691,\"Ġrevised\":7692,\"ĠAngela\":7693,\"Ġ81\":7694,\"Ġsingles\":7695,\"Ġviral\":7696,\"Ġworries\":7697,\"ĠShould\":7698,\"profit\":7699,\"Ġraises\":7700,\"ĠBryant\":7701,\"ĠProduct\":7702,\"Ġtenure\":7703,\"Ġdiabetes\":7704,\"Ġcolour\":7705,\"azz\":7706,\"ĠGirls\":7707,\"Ġpractical\":7708,\"Ġblind\":7709,\"ancing\":7710,\"pictured\":7711,\"Ġfinale\":7712,\"ĠElection\":7713,\"Ġathletic\":7714,\"Ġpromoted\":7715,\"Ġflowers\":7716,\"Ġtrains\":7717,\"ario\":7718,\"Ġsufficient\":7719,\"IE\":7720,\"Ġexamples\":7721,\"Ġshed\":7722,\"Ġbirds\":7723,\"Ġchaos\":7724,\"Ġwound\":7725,\"Ġrocket\":7726,\"Ġwet\":7727,\"Ġsample\":7728,\"ĠNag\":7729,\"ĠOliver\":7730,\"Ġscrutiny\":7731,\"ĠSeven\":7732,\"ĠRoman\":7733,\"ĠFred\":7734,\"Ġweird\":7735,\"ĠTam\":7736,\"ĠSupport\":7737,\"ĠNathan\":7738,\"Ġstudying\":7739,\"Ġintroduction\":7740,\"Ġtons\":7741,\"cer\":7742,\"aus\":7743,\"ION\":7744,\"Ġcritic\":7745,\"ĠAh\":7746,\"alo\":7747,\"pur\":7748,\"Ġstorms\":7749,\"ĠMission\":7750,\"Ġcredits\":7751,\"Ġgrants\":7752,\"Ġcomp\":7753,\"Ġhearts\":7754,\"part\":7755,\"Ġpin\":7756,\"Ġsubsequent\":7757,\"Ġmad\":7758,\"ĠSacramento\":7759,\"woman\":7760,\"from\":7761,\"Ġoutcomes\":7762,\"Ġoldest\":7763,\"Ġdesperate\":7764,\"ĠTal\":7765,\"ĠDJ\":7766,\"ward\":7767,\"Ġaudiences\":7768,\"Ġimportantly\":7769,\"ĠEmily\":7770,\"sk\":7771,\"ĠHeat\":7772,\"ĠType\":7773,\"ĠPeace\":7774,\"Ġsuspicious\":7775,\"aly\":7776,\"ĠGET\":7777,\"ĠCAP\":7778,\"dis\":7779,\"ĠIraqi\":7780,\"ĠReed\":7781,\"Ġstrange\":7782,\"ĠParent\":7783,\"900\":7784,\"Ġglad\":7785,\"ĠTroy\":7786,\"ĠShort\":7787,\"Ġheritage\":7788,\"Ġarriving\":7789,\"ingly\":7790,\"Ġtransformation\":7791,\"Ġlease\":7792,\"Ġcollapsed\":7793,\"cha\":7794,\"ĠPatrol\":7795,\"Ġcomputers\":7796,\"Ġprinciples\":7797,\"Ġsporting\":7798,\"ĠHughes\":7799,\"mile\":7800,\"ĠCit\":7801,\"Ġdrilling\":7802,\"ĠBox\":7803,\"ÃŁ\":7804,\"bre\":7805,\"ĠOverall\":7806,\"Ġopioid\":7807,\"Ġdelighted\":7808,\"Ġhonored\":7809,\"ĠCold\":7810,\"Ġunions\":7811,\"ĠCou\":7812,\"ĠCircuit\":7813,\"Ġblast\":7814,\"sson\":7815,\"ĠHernandez\":7816,\"ĠLooking\":7817,\"Ġlegally\":7818,\"ĠWalmart\":7819,\"bridge\":7820,\"Ġmat\":7821,\"rad\":7822,\"ids\":7823,\"Ġdining\":7824,\"Ġrebound\":7825,\"abad\":7826,\"ĠRom\":7827,\"Ġimpose\":7828,\"ĠAlpha\":7829,\"ĠWeekly\":7830,\"TER\":7831,\"ĠJam\":7832,\"Ġabsolute\":7833,\"Ġinventory\":7834,\"ĠBilly\":7835,\"ĠKaren\":7836,\"ĠFriends\":7837,\"ĠCent\":7838,\"ĠVikings\":7839,\"ĠMuch\":7840,\"cell\":7841,\"ads\":7842,\"Ġph\":7843,\"Ġkiller\":7844,\"ĠMembers\":7845,\"Ġshooter\":7846,\"ĠInvestigators\":7847,\"ĠJoshua\":7848,\"Ġparticipated\":7849,\"Ġinnocent\":7850,\"ĠRichmond\":7851,\"itor\":7852,\"ĠDal\":7853,\"ĠOperator\":7854,\"Ġmakeup\":7855,\"Ġconf\":7856,\"ĠNEWS\":7857,\"ĠDef\":7858,\"Ġchase\":7859,\"ĠCost\":7860,\"mont\":7861,\"\\\":\":7862,\"Ġarrangements\":7863,\"stein\":7864,\"Ġretire\":7865,\"ĠLuis\":7866,\"Ġrenewed\":7867,\"ĠTownship\":7868,\"Ġchecked\":7869,\"arts\":7870,\"ĠCash\":7871,\"Ġcentres\":7872,\"chers\":7873,\"ĠSolutions\":7874,\"Ġlegend\":7875,\"ige\":7876,\"most\":7877,\"osed\":7878,\"ĠPor\":7879,\"Ġpremiere\":7880,\"FS\":7881,\"Ġmissiles\":7882,\"ĠLang\":7883,\"Ġsing\":7884,\"best\":7885,\"Ġtail\":7886,\"Ġriders\":7887,\"Picture\":7888,\"zen\":7889,\"ĠKent\":7890,\"Ġtransform\":7891,\"Ġwildlife\":7892,\"Ġsmoking\":7893,\"Ġpreseason\":7894,\"ĠLucas\":7895,\"ĠAnne\":7896,\"owski\":7897,\"Ġtape\":7898,\"Ġdisplayed\":7899,\"Ġforum\":7900,\"Ġanonymity\":7901,\"ĠIndianapolis\":7902,\"hips\":7903,\"acc\":7904,\"ĠMoreover\":7905,\"lers\":7906,\"area\":7907,\"ĠIndeed\":7908,\"Ġconducting\":7909,\"Ġinfection\":7910,\"Ġdealt\":7911,\"OB\":7912,\"asing\":7913,\"ĠGaza\":7914,\"itter\":7915,\"ĠKa\":7916,\"Ġhopeful\":7917,\"ĠSnow\":7918,\"Ġentitled\":7919,\"Ġaffecting\":7920,\"Ġeager\":7921,\"Ġcircle\":7922,\"Ġlaugh\":7923,\"ĠProsecutors\":7924,\"ĠDur\":7925,\"Ġbarriers\":7926,\"ĠPoll\":7927,\"oun\":7928,\"ĠPalm\":7929,\"chi\":7930,\"Ġsamples\":7931,\"Ġcompromise\":7932,\"atter\":7933,\"Ġenormous\":7934,\"ĠÃ©\":7935,\"coming\":7936,\"ĠPharmaceutical\":7937,\"Ġrank\":7938,\"Let\":7939,\"Ġtransgender\":7940,\"ĠCloud\":7941,\"FO\":7942,\"ĠBor\":7943,\"Ġbonus\":7944,\"Ġordinary\":7945,\"ĠPres\":7946,\"ĠHIV\":7947,\"ires\":7948,\"OSE\":7949,\"Ġdancing\":7950,\"ĠHD\":7951,\"Ġversions\":7952,\"Ġ88\":7953,\"rate\":7954,\"Ġtackles\":7955,\"Ġknock\":7956,\"ĠEmma\":7957,\"Ġmotivated\":7958,\"ĠBennett\":7959,\"ĠBurn\":7960,\"Ġgrid\":7961,\"Ġembrace\":7962,\"ĠSpurs\":7963,\"Ġflows\":7964,\"ĠGer\":7965,\"Ġsponsored\":7966,\"Ġsurvival\":7967,\"ching\":7968,\"Ġ1995\":7969,\"Ġreward\":7970,\"Ġdepends\":7971,\"Ġpostseason\":7972,\"Ġloaded\":7973,\"Ġneutral\":7974,\"ĠPop\":7975,\"BL\":7976,\"Ġrevolution\":7977,\"ĠFreedom\":7978,\"Ġrecovering\":7979,\"Ġrequiring\":7980,\"ALL\":7981,\"ARE\":7982,\"Ġmini\":7983,\"lt\":7984,\"ĠFDA\":7985,\"Ġcarpet\":7986,\"ĠPrior\":7987,\"Ġadmission\":7988,\"ĠEver\":7989,\"ĠTribune\":7990,\"ĠRonaldo\":7991,\"Ġthick\":7992,\"Ġlanes\":7993,\"Ġ84\":7994,\"ĠMemphis\":7995,\"Ġopt\":7996,\"BO\":7997,\"Ġfaculty\":7998,\"ĠChad\":7999,\"ĠSUV\":8000,\"ĠHen\":8001,\"Ġeste\":8002,\"ĠHu\":8003,\"ĠAgriculture\":8004,\"store\":8005,\"ĠDrug\":8006,\"inter\":8007,\"Ġ1996\":8008,\"ident\":8009,\"Ġbackup\":8010,\"ĠHonda\":8011,\"ĠHope\":8012,\"oes\":8013,\"ums\":8014,\"amer\":8015,\"Ġbreath\":8016,\"Ġ110\":8017,\"Ġjoke\":8018,\"ĠAld\":8019,\"Ġwondering\":8020,\"ĠAssad\":8021,\"ĠRem\":8022,\"Ġfundraising\":8023,\"pot\":8024,\"Ã¨\":8025,\"Ġquestioning\":8026,\"Ġpent\":8027,\"ĠMoney\":8028,\"ĠMedicine\":8029,\"wick\":8030,\"ĠKnights\":8031,\"Ġbatting\":8032,\"ĠMos\":8033,\"Ġdesignated\":8034,\"isse\":8035,\"Ġspotlight\":8036,\"Ġlake\":8037,\"Ġcaution\":8038,\"Ġinmates\":8039,\"Ġlap\":8040,\"CE\":8041,\"ĠJavascript\":8042,\"ĠDeutsche\":8043,\"ĠFargo\":8044,\"Ġguaranteed\":8045,\"borough\":8046,\"Ġfunctions\":8047,\"ĠElementary\":8048,\"ĠChuck\":8049,\"Ġpitched\":8050,\"ĠKrist\":8051,\"Ġsteal\":8052,\"Ġchips\":8053,\"Ġalarm\":8054,\"Ġbeloved\":8055,\"scale\":8056,\"Ġassaulted\":8057,\"ĠPentagon\":8058,\"Ġtemporarily\":8059,\"Ġ93\":8060,\"Ġ>\":8061,\"ĠPortugal\":8062,\"ti\":8063,\"HL\":8064,\"Ġdecreased\":8065,\"Ġexistence\":8066,\"Ġisolated\":8067,\"Ġdeposit\":8068,\"Ġstudied\":8069,\"\\\")\":8070,\"Ġtrophy\":8071,\"ĠBrooks\":8072,\"Ġbattling\":8073,\"Ġweaker\":8074,\"ĠPrivate\":8075,\"ĠAccess\":8076,\"Ġvirtually\":8077,\"Ġshortage\":8078,\"Ġgaining\":8079,\"Ġbathroom\":8080,\"TON\":8081,\"Ġconcerning\":8082,\"Ġengineer\":8083,\"Ġbread\":8084,\"Ġdemonstrate\":8085,\"ĠDh\":8086,\"Ġhorses\":8087,\"Ġintersection\":8088,\"Ġcolors\":8089,\"Ġdelegation\":8090,\"Ġnotable\":8091,\"Ġwithdrawal\":8092,\"ĠDennis\":8093,\"Ġlocally\":8094,\"Ġcoastal\":8095,\"Ġcomply\":8096,\"ĠMoh\":8097,\"ĠAlbert\":8098,\"Ġclosest\":8099,\"ĠCITY\":8100,\"Ġ83\":8101,\"Ġcancelled\":8102,\"ĠðŁ\":8103,\"Ġsharply\":8104,\"RS\":8105,\"Ġproductivity\":8106,\"Ġbasket\":8107,\"SS\":8108,\"Ġadmit\":8109,\"ool\":8110,\"ination\":8111,\"ĠBB\":8112,\"Ġsur\":8113,\"ĠSteel\":8114,\"ĠTed\":8115,\"ĠPac\":8116,\"Ġpatterns\":8117,\"Ġlisting\":8118,\"Ġreplacing\":8119,\"ĠPradesh\":8120,\"Ġroots\":8121,\"Ġbroker\":8122,\"ĠWriting\":8123,\"Ġsued\":8124,\"Ġorganised\":8125,\"ĠThanksgiving\":8126,\"ĠNOT\":8127,\"Ġjournalism\":8128,\"uel\":8129,\"Ġkilometers\":8130,\"Ġhunt\":8131,\"berry\":8132,\"ĠMother\":8133,\"Ġlegitimate\":8134,\"Ġinput\":8135,\"ĠRel\":8136,\"ĠGuardian\":8137,\"Ar\":8138,\"Ġtransported\":8139,\"Ġbedroom\":8140,\"ashing\":8141,\"Ġbats\":8142,\"Ġcleaning\":8143,\"Ġwrapped\":8144,\"Pacific\":8145,\"Ġfence\":8146,\"Ġtestified\":8147,\"Ġ1994\":8148,\"Ġinterference\":8149,\"Ġmatching\":8150,\"Ġexpression\":8151,\"eta\":8152,\"ĠSpencer\":8153,\"Ġstrategist\":8154,\"who\":8155,\"Ġvictories\":8156,\"Ġ2022\":8157,\"Ġstakes\":8158,\"Ġbuses\":8159,\"ĠHousing\":8160,\"Ġeditorial\":8161,\"Ġ86\":8162,\"ĠBishop\":8163,\"Ġfrustrated\":8164,\"Ġappearing\":8165,\"http\":8166,\"IGHT\":8167,\"Ġmemo\":8168,\"Ġinsiders\":8169,\"Even\":8170,\"Ġclassroom\":8171,\"Ġchef\":8172,\"aining\":8173,\"].\":8174,\"ĠMcD\":8175,\"Ġ87\":8176,\"ĠPunjab\":8177,\"Ġancient\":8178,\"Ġresolved\":8179,\"Ġdying\":8180,\"Ġdestruction\":8181,\"Ġgoverning\":8182,\"Ġrestructuring\":8183,\"ĠPick\":8184,\"Ġmunicipal\":8185,\"Ġengines\":8186,\"ĠHudson\":8187,\"Æ\":8188,\"Ġrepeal\":8189,\"standing\":8190,\"Ġbound\":8191,\"ĠOS\":8192,\"ĠCommonwealth\":8193,\"Ġdescription\":8194,\"Ġhouseholds\":8195,\"Ġmal\":8196,\"Ġstopping\":8197,\"equ\":8198,\"Ġregulator\":8199,\"Ġcontaining\":8200,\"Ġremoving\":8201,\"Ġwithdraw\":8202,\"Ġburied\":8203,\"Ġlists\":8204,\"ĠGil\":8205,\"Ġlowered\":8206,\"Ġformally\":8207,\"ĠRound\":8208,\"asi\":8209,\"¥\":8210,\"lett\":8211,\"Ġprogressive\":8212,\"ĠFalcons\":8213,\"ĠRaw\":8214,\"gun\":8215,\"Ġcontributing\":8216,\"Ġhunting\":8217,\"Ġvalid\":8218,\"Ġexception\":8219,\"ĠPlayers\":8220,\"ĠTra\":8221,\"Ġracism\":8222,\"hing\":8223,\"chen\":8224,\"Ġdifferently\":8225,\"Ġchampionships\":8226,\"ĠEng\":8227,\"ĠNO\":8228,\"ĠAuto\":8229,\"ĠErdogan\":8230,\"iding\":8231,\"Ġwarming\":8232,\"Ġcivilian\":8233,\"ĠDam\":8234,\"Ġfantasy\":8235,\"ĠNav\":8236,\"itions\":8237,\"ĠDrew\":8238,\"ĠNancy\":8239,\"Ġtrapped\":8240,\"ĠRussians\":8241,\"ĠIC\":8242,\"Ġflexibility\":8243,\"ular\":8244,\"Ġviolated\":8245,\"ipped\":8246,\"Ġgarage\":8247,\"ĠDeep\":8248,\"Ġpraise\":8249,\"ĠLab\":8250,\"ĠPlayer\":8251,\"Ġjudicial\":8252,\"Ġdonate\":8253,\"Ġseparated\":8254,\"Ġreleases\":8255,\"nik\":8256,\"Ġexplanation\":8257,\"aph\":8258,\"Ġloyal\":8259,\"Ġstrongest\":8260,\"ĠShar\":8261,\"Ġrescued\":8262,\"Ġambitious\":8263,\"Ġclimb\":8264,\"Ġscared\":8265,\"Ġignored\":8266,\"cut\":8267,\"Ġstole\":8268,\"Ġweakness\":8269,\"ĠRidge\":8270,\"oa\":8271,\"LA\":8272,\"Ġdep\":8273,\"ĠPowell\":8274,\"Do\":8275,\"Ġprotein\":8276,\"Ġreiterated\":8277,\"ĠCox\":8278,\"aling\":8279,\"ĠUnlike\":8280,\"ĠKane\":8281,\"ĠMcConnell\":8282,\"Ġshowcase\":8283,\"Ġuniform\":8284,\"ower\":8285,\"Ġdiscover\":8286,\"stop\":8287,\"ipper\":8288,\"Ġtreatments\":8289,\"Ġgrocery\":8290,\"Ġsubscribers\":8291,\"lock\":8292,\"ple\":8293,\"Ġflew\":8294,\"ania\":8295,\"Ġstepping\":8296,\"ĠSoviet\":8297,\"Ġconsultant\":8298,\"ags\":8299,\"ĠLim\":8300,\"Ġ91\":8301,\"ĠCode\":8302,\"ports\":8303,\"box\":8304,\"Ġlakh\":8305,\"Ġreminder\":8306,\"ym\":8307,\"ĠTravis\":8308,\"Ġpure\":8309,\"now\":8310,\"ĠVR\":8311,\"Ġachievement\":8312,\"ĠEmirates\":8313,\"ĠThunder\":8314,\"Ġmerely\":8315,\"ĠCa\":8316,\"ĠAverage\":8317,\"ĠDa\":8318,\"Ġtopped\":8319,\"ĠCurry\":8320,\"Ġchemicals\":8321,\"Ġamendment\":8322,\"ĠBorder\":8323,\"ĠBat\":8324,\"Ġ130\":8325,\"Ġprogramming\":8326,\"Ġtele\":8327,\"ĠKarl\":8328,\"Ġaveraged\":8329,\"ĠSpe\":8330,\"world\":8331,\"PG\":8332,\"Ġfights\":8333,\"ĠPrincess\":8334,\"ĠCIA\":8335,\"ĠAbe\":8336,\"Ġacted\":8337,\"only\":8338,\"Ġinsight\":8339,\"Ġathlete\":8340,\"ĠTar\":8341,\"commerce\":8342,\"Ġaveraging\":8343,\"cr\":8344,\"ĠPalestinians\":8345,\"Well\":8346,\"Ġbull\":8347,\"Ġchoosing\":8348,\"Ġsurely\":8349,\"ĠSecret\":8350,\"Ġteammate\":8351,\"ĠAmendment\":8352,\"ĠBirmingham\":8353,\"Ġexcitement\":8354,\"strong\":8355,\"ĠSin\":8356,\"Ġdamages\":8357,\"rated\":8358,\"Ġrankings\":8359,\"Ġconservation\":8360,\"home\":8361,\"erm\":8362,\"ield\":8363,\"Ġdisorder\":8364,\"acher\":8365,\"Ġnaturally\":8366,\"atur\":8367,\"Ġpackages\":8368,\"Ġapproaches\":8369,\"icks\":8370,\"ourn\":8371,\"Ġodd\":8372,\"Ġshore\":8373,\"ĠBeing\":8374,\"Ġmagic\":8375,\"Ġtourist\":8376,\"largest\":8377,\"Ġwhenever\":8378,\"Ġlenders\":8379,\"Ġegg\":8380,\"ĠChair\":8381,\"Ġlets\":8382,\"Ġwarnings\":8383,\"į\":8384,\"Ġpol\":8385,\"Ġdrag\":8386,\"ĠAmb\":8387,\"ĠCle\":8388,\"ĠLouisville\":8389,\"ĠShaw\":8390,\"lands\":8391,\"Ġanthem\":8392,\"ĠTrail\":8393,\"Ġaccepting\":8394,\"anger\":8395,\"good\":8396,\"ĠBroad\":8397,\"ĠLebanon\":8398,\"ĠMillion\":8399,\"ĠHenderson\":8400,\"Ġwh\":8401,\"Ġdust\":8402,\"Ġ92\":8403,\"ĠMend\":8404,\"Ġchecking\":8405,\"ĠCow\":8406,\"sized\":8407,\"Ġautomatic\":8408,\"Ġcelebrates\":8409,\"Ġarena\":8410,\"Ġfinger\":8411,\"ĠHarvard\":8412,\"Ġfrustration\":8413,\"Ġstrict\":8414,\"Ġpreserve\":8415,\"Ġsleeping\":8416,\"Ġconverted\":8417,\"Ġinsights\":8418,\"Ġtra\":8419,\"Ġjailed\":8420,\"Ġchamber\":8421,\"Ġtoxic\":8422,\"ading\":8423,\"ĠTriple\":8424,\"grade\":8425,\"ĠRest\":8426,\"ĠHoly\":8427,\"oper\":8428,\"Ġdesk\":8429,\"Ġmatchup\":8430,\"Ġsteep\":8431,\"ĠGot\":8432,\"lay\":8433,\"ĠCab\":8434,\"aked\":8435,\"ĠFoster\":8436,\"Ġrunners\":8437,\"ĠNA\":8438,\"Ġdestroy\":8439,\"Ġsupportive\":8440,\"ĠRacing\":8441,\"Ġtrademark\":8442,\"Ġjacket\":8443,\"Ġhorror\":8444,\"ĠAle\":8445,\"Ġass\":8446,\"Ġsch\":8447,\"abb\":8448,\"Ġplanes\":8449,\"Ġimpression\":8450,\"ĠEarly\":8451,\"ĠPompe\":8452,\"Ġking\":8453,\"Ġsilent\":8454,\"ĠCuba\":8455,\"Ġmedication\":8456,\"ences\":8457,\"list\":8458,\"ailing\":8459,\"WA\":8460,\"ella\":8461,\"Ġprop\":8462,\"Ġhalt\":8463,\"Ġslowing\":8464,\"ĠFoods\":8465,\"Ġanonymous\":8466,\"kh\":8467,\"Ġtraveled\":8468,\"Ġcommunicate\":8469,\"Ġter\":8470,\"ĠHockey\":8471,\"ĠRobin\":8472,\"Ġswept\":8473,\"Ġclinic\":8474,\"ration\":8475,\"len\":8476,\"Ġau\":8477,\"Ġcareers\":8478,\"ĠSound\":8479,\"Ġaddresses\":8480,\"China\":8481,\"ĠSr\":8482,\"Ġexhibit\":8483,\"ĠMotors\":8484,\"ĠIl\":8485,\"Ġinstall\":8486,\"ĠOkay\":8487,\"Ġ>>\":8488,\"hood\":8489,\"stand\":8490,\"Ġaudit\":8491,\"Ġcake\":8492,\"Ġflames\":8493,\"bel\":8494,\"ĠMust\":8495,\"ĠManafort\":8496,\"Ġcommodity\":8497,\"night\":8498,\"ĠRoom\":8499,\"ĠLanka\":8500,\"Ġcommander\":8501,\"ln\":8502,\"Ġdatabase\":8503,\"ĠSet\":8504,\"Ġgraduated\":8505,\"ĠTarget\":8506,\"Ġoutbreak\":8507,\"rou\":8508,\"ĠPope\":8509,\"ĠEqu\":8510,\"Ġpolling\":8511,\"Ġdig\":8512,\"Ġbrutal\":8513,\"ĠBarn\":8514,\"Ġdefinition\":8515,\"Ġpit\":8516,\"Ġpickup\":8517,\"ĠBitcoin\":8518,\"ĠReid\":8519,\"Ġloving\":8520,\"ĠHerald\":8521,\"ĠCanadians\":8522,\"Ġneighbor\":8523,\"Ġdies\":8524,\"ione\":8525,\"ĠRef\":8526,\"big\":8527,\"Ġguards\":8528,\"including\":8529,\"ente\":8530,\"Ġpartially\":8531,\"Image\":8532,\"Ġbulk\":8533,\"Ġslot\":8534,\"ĠNorthwest\":8535,\"ĠBarclays\":8536,\"Ġairlines\":8537,\"iver\":8538,\"isi\":8539,\"Ġsubsidiary\":8540,\"Ġcont\":8541,\"ĠDaniels\":8542,\"Ġscript\":8543,\"Ġunfair\":8544,\"Ġscreens\":8545,\"Ġprof\":8546,\"ĠIrma\":8547,\"Ġ1992\":8548,\"Ġmandatory\":8549,\"ĠSant\":8550,\"Ġsuspicion\":8551,\"NES\":8552,\"ĠLauren\":8553,\"igen\":8554,\"Ġprevention\":8555,\"Ġtension\":8556,\"ema\":8557,\"Ġtasks\":8558,\"Ġshake\":8559,\"Ġexplosive\":8560,\"Ġaffects\":8561,\"Ġmum\":8562,\"ĠDog\":8563,\"rer\":8564,\"Ġopted\":8565,\"Ġtrio\":8566,\"Ġlesson\":8567,\"Ġautomotive\":8568,\"where\":8569,\"ĠMontgomery\":8570,\"Ġcouples\":8571,\"Ġ89\":8572,\"AF\":8573,\"Ġinfo\":8574,\"ĠForm\":8575,\"Ġspectrum\":8576,\"Ġbands\":8577,\"Ġokay\":8578,\"Ġstroke\":8579,\"ĠNetanyahu\":8580,\"Ġwealthy\":8581,\"ĠAround\":8582,\"ĠGlenn\":8583,\"sec\":8584,\"there\":8585,\"ickets\":8586,\"ĠBudget\":8587,\"ĠBMW\":8588,\"Ġflagship\":8589,\"rier\":8590,\"Ġpodcast\":8591,\"Ġpursuing\":8592,\"Ġpos\":8593,\"ĠIslands\":8594,\"ĠUrban\":8595,\"page\":8596,\"Ġemotions\":8597,\"ided\":8598,\"Ġdividends\":8599,\"Ġboom\":8600,\"Ġaccusing\":8601,\"ird\":8602,\"ĠNam\":8603,\"ava\":8604,\"Ġwishes\":8605,\"ĠNy\":8606,\"ĠStanford\":8607,\"Ġcriteria\":8608,\"ĠJews\":8609,\"Ġengineers\":8610,\"Ġaccuracy\":8611,\"Ġdisplays\":8612,\"Ġdeserves\":8613,\"ridge\":8614,\"omm\":8615,\"aur\":8616,\"Ġdramatically\":8617,\"Ġunity\":8618,\"speed\":8619,\"Ġdeclining\":8620,\"Ġpermits\":8621,\"ĠKn\":8622,\"Ġconsulting\":8623,\"aux\":8624,\"ATE\":8625,\"ĠWat\":8626,\"ĠEditor\":8627,\"sy\":8628,\"urn\":8629,\"ĠUsing\":8630,\"asc\":8631,\"ital\":8632,\"Ġcre\":8633,\"quality\":8634,\"Ġce\":8635,\"Ġenemy\":8636,\"Ġoffence\":8637,\"icket\":8638,\"ĠDick\":8639,\"ĠTH\":8640,\"ĠChampionships\":8641,\"Ġoverwhelming\":8642,\"rib\":8643,\"ku\":8644,\"rap\":8645,\"Ġhomer\":8646,\"acion\":8647,\"member\":8648,\"erv\":8649,\"aney\":8650,\"MB\":8651,\"eded\":8652,\"Ġpunishment\":8653,\"Ġnegotiate\":8654,\"ĠFile\":8655,\"stream\":8656,\"ĠHur\":8657,\"Ġnose\":8658,\"ĠFab\":8659,\"iter\":8660,\"Ġpainful\":8661,\"ITY\":8662,\"eren\":8663,\"Ġcollecting\":8664,\"Additional\":8665,\"Ġentrepreneurs\":8666,\"bal\":8667,\"Ġexploring\":8668,\"Ġguitar\":8669,\"Ġpartnerships\":8670,\"Ġfurniture\":8671,\"Ġauthorized\":8672,\"Ġeasing\":8673,\"shirt\":8674,\"ĠGross\":8675,\"Ġpolitician\":8676,\"ĠSimpson\":8677,\"Ġdrone\":8678,\"ĠKatie\":8679,\"Ġprofitability\":8680,\"ĠNHS\":8681,\"ĠSierra\":8682,\"ĠNorway\":8683,\"ASHINGTON\":8684,\"ific\":8685,\"Ġcondemned\":8686,\"team\":8687,\"ĠNebraska\":8688,\"Ġthrilled\":8689,\"iller\":8690,\"Ġpatrol\":8691,\"ĠWR\":8692,\"orm\":8693,\"Ġspectacular\":8694,\"ĠKnight\":8695,\"ĠTravel\":8696,\"nam\":8697,\"Ġmuscle\":8698,\"ĠRain\":8699,\"ĠColombia\":8700,\"Ġnursing\":8701,\"Ġmigration\":8702,\"ĠMitch\":8703,\"Ġreleasing\":8704,\"ĠBesides\":8705,\"ĠMul\":8706,\"Ġheadline\":8707,\"Ġcontemporary\":8708,\"Ġdev\":8709,\"ĠChan\":8710,\"Ġindicates\":8711,\"ĠAp\":8712,\"ĠLt\":8713,\"ĠMarvel\":8714,\"Ġremembered\":8715,\"Â®\":8716,\"ĠForces\":8717,\"ĠColin\":8718,\"ĠGabriel\":8719,\"Ġobjects\":8720,\"ĠRHP\":8721,\"kar\":8722,\"ĠKo\":8723,\"Ġsignals\":8724,\"Ġinner\":8725,\"real\":8726,\"RO\":8727,\"Ġromantic\":8728,\"cat\":8729,\"ĠKel\":8730,\"Ġgut\":8731,\"ĠBoys\":8732,\"Ġyoungest\":8733,\"ĠCeltics\":8734,\"Ġslated\":8735,\"Ġremind\":8736,\"Ġproductive\":8737,\"set\":8738,\"Co\":8739,\"ĠBailey\":8740,\"Ġrenewable\":8741,\"ĠCarson\":8742,\"ĠDj\":8743,\"ĠKos\":8744,\"Ġurge\":8745,\"Ġfin\":8746,\"Ġpursuit\":8747,\"ĠCON\":8748,\"ĠChapter\":8749,\"Ġpal\":8750,\"Ġgate\":8751,\"ĠPackers\":8752,\"ĠReports\":8753,\"ĠRugby\":8754,\"ĠMasters\":8755,\"MO\":8756,\"Ġ98\":8757,\"Ġcatches\":8758,\"ĠAgreement\":8759,\"ĠTillerson\":8760,\"ĠIce\":8761,\"Ġrumors\":8762,\"ĠLeonard\":8763,\"ĠDolphins\":8764,\"ĠLP\":8765,\"top\":8766,\"ĠCrist\":8767,\"ĠHon\":8768,\"Ġblaze\":8769,\"Ġrhetoric\":8770,\"ands\":8771,\"ady\":8772,\"David\":8773,\"igh\":8774,\"Ġbuzz\":8775,\"ĠStrong\":8776,\"Ġshocking\":8777,\"ĠRh\":8778,\"Ġnegotiating\":8779,\"Ġtender\":8780,\"ĠJohnny\":8781,\"ĠMario\":8782,\"Ġ97\":8783,\"ĠHeritage\":8784,\"Ġexists\":8785,\"Ġprayers\":8786,\"Ġlengthy\":8787,\"Ġsafer\":8788,\"ĠHalloween\":8789,\"ĠJared\":8790,\"ĠConnect\":8791,\"Ġbump\":8792,\"Ġstrain\":8793,\"Ġfilling\":8794,\"Ġtrauma\":8795,\"Ġcompleting\":8796,\"cht\":8797,\"Ġkillings\":8798,\"anne\":8799,\"GE\":8800,\"ĠRescue\":8801,\"Ġdealers\":8802,\"Ġlocals\":8803,\"ĠVictor\":8804,\"Ġtragic\":8805,\"Ġdelivers\":8806,\"orts\":8807,\"Ġrugby\":8808,\"Ġinstallation\":8809,\"asa\":8810,\"ĠBart\":8811,\"Ġjournal\":8812,\"school\":8813,\"ĠCome\":8814,\"ĠVeterans\":8815,\"Sun\":8816,\"Ġcrowds\":8817,\"Ġtransparent\":8818,\"Ġimplications\":8819,\"ĠHuawei\":8820,\"sex\":8821,\"Ġrallied\":8822,\"Ġresponses\":8823,\"Ġdebris\":8824,\"Ġconvention\":8825,\"Ġmothers\":8826,\"BE\":8827,\"ĠRoute\":8828,\"Ġrebel\":8829,\"ĠEmmanuel\":8830,\"aster\":8831,\"Ġunderstands\":8832,\"pound\":8833,\"ĠCastle\":8834,\"Ġ2021\":8835,\"rik\":8836,\"ĠGR\":8837,\"Ġconvince\":8838,\"ault\":8839,\"Ġpassionate\":8840,\"ĠSciences\":8841,\"Ġarrives\":8842,\"idad\":8843,\"Ġcelebrities\":8844,\"ends\":8845,\"ĠFans\":8846,\"Ġdish\":8847,\"ĠCorps\":8848,\"hat\":8849,\"Ġemployer\":8850,\"ĠHy\":8851,\"Ġpowered\":8852,\"Ġgrandmother\":8853,\"ĠFL\":8854,\"oured\":8855,\"VE\":8856,\"ĠInst\":8857,\"ĠPerez\":8858,\"Ġtune\":8859,\"Ġcitizenship\":8860,\"Ġignore\":8861,\"Ġdoubles\":8862,\"IB\":8863,\"Ġprogrammes\":8864,\"inda\":8865,\"Ġentities\":8866,\"ĠInterior\":8867,\"Ġprompting\":8868,\"Ġwire\":8869,\"Ġtheatre\":8870,\"%)\":8871,\"Ġheels\":8872,\"ĠJu\":8873,\"Ġdeposits\":8874,\"Ġtrash\":8875,\"mond\":8876,\"she\":8877,\"iana\":8878,\"Ġislands\":8879,\"ĠTommy\":8880,\"Ġpub\":8881,\"Ġdiscipline\":8882,\"ĠSW\":8883,\"Ġmusicians\":8884,\"Ġembassy\":8885,\"ĠQB\":8886,\"hander\":8887,\"UES\":8888,\"ĠFerguson\":8889,\"Ġblocking\":8890,\"ahn\":8891,\"Ġfines\":8892,\"Ġtactics\":8893,\"Ġbullet\":8894,\"Ġequipped\":8895,\"Ġescaped\":8896,\"ĠSil\":8897,\"ĠPack\":8898,\"ĠAthletic\":8899,\"ĠMic\":8900,\"ĠDoes\":8901,\"ĠCarr\":8902,\"ĠChargers\":8903,\"ĠKyl\":8904,\"Ġzones\":8905,\"µ\":8906,\"iki\":8907,\"Ġgreatly\":8908,\"ĠMD\":8909,\"Ġimmigrant\":8910,\"ĠConstruction\":8911,\"ĠBorn\":8912,\"iment\":8913,\"ĠWade\":8914,\"Ġvisa\":8915,\"Ġgenuine\":8916,\"Ġelectronics\":8917,\"ĠSat\":8918,\"Ġsponsors\":8919,\"ĠMontana\":8920,\"Ġspell\":8921,\"ĠSachs\":8922,\"ĠEt\":8923,\"Ġfoster\":8924,\"Ġlocker\":8925,\"Ġexplaining\":8926,\"ĠAge\":8927,\"Ġgunman\":8928,\"Ġsauce\":8929,\"Ġcry\":8930,\"Ġstimulus\":8931,\"Ġarray\":8932,\"Ġcompare\":8933,\"Ġboats\":8934,\"Ġext\":8935,\"iders\":8936,\"ĠAst\":8937,\"ĠParks\":8938,\"ester\":8939,\"Ġ94\":8940,\"Ġrelating\":8941,\"Ġvegetables\":8942,\"Ġaccountable\":8943,\"Ġhyper\":8944,\"ĠWim\":8945,\"Ġnewest\":8946,\"ĠRome\":8947,\"ĠChancellor\":8948,\"CBS\":8949,\"Ġbusinessman\":8950,\"ĠDelaware\":8951,\"Ġlands\":8952,\"court\":8953,\"aria\":8954,\"Ġapproaching\":8955,\"cker\":8956,\"ĠSalt\":8957,\"ĠMak\":8958,\"Ġtreating\":8959,\"Ġsubsequently\":8960,\"ĠEll\":8961,\"xton\":8962,\"Ġ180\":8963,\"Ġdetermination\":8964,\"ĠSalman\":8965,\"ĠJoel\":8966,\"Ġclassified\":8967,\"Ġspan\":8968,\"Ġearthquake\":8969,\"ranked\":8970,\"Ġ96\":8971,\"ĠTiger\":8972,\"Ġadvocacy\":8973,\"mit\":8974,\"Ġcolleges\":8975,\"ĠYeah\":8976,\"ĠCaptain\":8977,\"Ġorange\":8978,\"Ġprojections\":8979,\"Ġelectrical\":8980,\"ĠMA\":8981,\"olog\":8982,\"ĠNewcastle\":8983,\"oppers\":8984,\"Ġrepresentation\":8985,\"Ġlawsuits\":8986,\"just\":8987,\"aced\":8988,\"ĠRace\":8989,\"ĠAqu\":8990,\"ĠBills\":8991,\"Ġexclusively\":8992,\"ĠProfile\":8993,\"Ġhometown\":8994,\"ĠStan\":8995,\"Ġstarring\":8996,\"Ġdeciding\":8997,\"ĠRating\":8998,\"ĠMedicare\":8999,\"ĠTransport\":9000,\"Ġmystery\":9001,\"ĠTa\":9002,\"ĠPad\":9003,\"ĠSwedish\":9004,\"ĠCarroll\":9005,\"about\":9006,\"Ġtorn\":9007,\"Ġnurse\":9008,\"NE\":9009,\"Ġwaited\":9010,\"ĠJeffrey\":9011,\"ĠUntil\":9012,\"Ġbone\":9013,\"ĠBobby\":9014,\"Ġpronounced\":9015,\"Ġpharmaceutical\":9016,\"ĠGallery\":9017,\"ĠMatch\":9018,\"Ġeconomists\":9019,\"ĠMarketing\":9020,\"face\":9021,\"ĠPetroleum\":9022,\"ories\":9023,\"ĠMets\":9024,\"ĠCore\":9025,\"billion\":9026,\"Ġexamination\":9027,\"ĠPorter\":9028,\"2016\":9029,\"Ġgolden\":9030,\"Ġsem\":9031,\"ĠDuterte\":9032,\"ĠJefferson\":9033,\"ĠTehran\":9034,\"ĠLeicester\":9035,\"ĠDA\":9036,\"Ġadapt\":9037,\"ĠDame\":9038,\"ĠRic\":9039,\"Ġunchanged\":9040,\"ect\":9041,\"Ġsections\":9042,\"kg\":9043,\"igned\":9044,\"Ġfilings\":9045,\"Ġreact\":9046,\"Ġurgent\":9047,\"Ġvessels\":9048,\"Ġspark\":9049,\"Ġbutter\":9050,\"ĠCons\":9051,\"Ġstating\":9052,\"Ġcorporations\":9053,\"ĠHus\":9054,\"Ġdamaging\":9055,\"raw\":9056,\"Ġequality\":9057,\"Two\":9058,\"ĠMills\":9059,\"iu\":9060,\"Ġobligation\":9061,\"ĠBrook\":9062,\"arian\":9063,\"Re\":9064,\"Ġphotographs\":9065,\"Ġepic\":9066,\"ĠStudent\":9067,\"ĠTherefore\":9068,\"Ġgod\":9069,\"ĠFILE\":9070,\"iqu\":9071,\"Ġdescribing\":9072,\"Ġproceed\":9073,\"Ġcas\":9074,\"ĠKat\":9075,\"ĠBra\":9076,\"Ġadequate\":9077,\"Ġpassage\":9078,\"Ġthanked\":9079,\"USA\":9080,\"ĠNeither\":9081,\"ĠLegislature\":9082,\"Ġfinances\":9083,\"Ġinst\":9084,\"ĵ\":9085,\"ĠAngels\":9086,\"Ġvet\":9087,\"ĠDead\":9088,\"Ex\":9089,\"Ġkicks\":9090,\"force\":9091,\"Ġsoy\":9092,\"ĠWindsor\":9093,\"Ġenhanced\":9094,\"Ġ1993\":9095,\"ĠCzech\":9096,\"Ġgradually\":9097,\"ĠMagic\":9098,\"Ġshadow\":9099,\"Ġneighborhoods\":9100,\"ĠRivers\":9101,\"Ġrapper\":9102,\"ĠGirl\":9103,\"ĠRot\":9104,\"Ġcrackdown\":9105,\"fish\":9106,\"Ġpreventing\":9107,\"Ġproduces\":9108,\"ĠMi\":9109,\"Ġnotified\":9110,\"Ġunderground\":9111,\"WE\":9112,\"Ġadmits\":9113,\"Ġboxing\":9114,\"Ġrefer\":9115,\"Ġcommitments\":9116,\"ĠWoman\":9117,\"Ġdenies\":9118,\"col\":9119,\"ĠSide\":9120,\"Ġambulance\":9121,\"ĠRodgers\":9122,\"Ġaftermath\":9123,\"Ġdeck\":9124,\"irmed\":9125,\"Ġerrors\":9126,\"ĠConvention\":9127,\"Ġcurb\":9128,\"ĠShop\":9129,\"ĠThai\":9130,\"Ġma\":9131,\"Ġrespected\":9132,\"ĠMVP\":9133,\"Ġborrowing\":9134,\"Ġcruise\":9135,\"ĠSure\":9136,\"Ġsentencing\":9137,\"ĠObamacare\":9138,\"ĠIr\":9139,\"ĠSale\":9140,\"ĠPete\":9141,\"Ġopenly\":9142,\"Ġstartup\":9143,\"rock\":9144,\"Ġcargo\":9145,\"Ġtelecom\":9146,\"ĠDownload\":9147,\"Ġextending\":9148,\"ĠCurrent\":9149,\"Ġcompetitions\":9150,\"ĠKids\":9151,\"Ġshy\":9152,\"ĠKerry\":9153,\"ĠNever\":9154,\"ĠDevils\":9155,\"Ġprim\":9156,\"Con\":9157,\"Ġcurve\":9158,\"Ġassumed\":9159,\"Ġadjust\":9160,\"Ġimmune\":9161,\"UE\":9162,\"ĠUr\":9163,\"Ġconventional\":9164,\"Ġgrandchildren\":9165,\"ĠBol\":9166,\"Ad\":9167,\"ĠMaduro\":9168,\"fi\":9169,\"ĠUAE\":9170,\"ĠOrgan\":9171,\"Ġindicating\":9172,\"iem\":9173,\"ĠAgainst\":9174,\"ĠAmbassador\":9175,\"ĠSeoul\":9176,\"Ġcriminals\":9177,\"how\":9178,\"put\":9179,\"Ġreminded\":9180,\"Ġparked\":9181,\"lich\":9182,\"Ġcontinent\":9183,\"Ġmatched\":9184,\"ĠNicole\":9185,\"Ġgenetic\":9186,\"Ġhumanity\":9187,\"ĠTem\":9188,\"Ġindicator\":9189,\"Ġvessel\":9190,\"Ġdefendant\":9191,\"ĠGriffin\":9192,\"jan\":9193,\"Ġvend\":9194,\"boro\":9195,\"Ġbrokerage\":9196,\"ĠFall\":9197,\"Ġmere\":9198,\"VILLE\":9199,\"Ġlasted\":9200,\"ĠMind\":9201,\"Ġpatch\":9202,\"ĠInsider\":9203,\"ĠComm\":9204,\"Ġtechnique\":9205,\"ĠIM\":9206,\"ĠCavaliers\":9207,\"Ġshame\":9208,\"Ġmil\":9209,\"oot\":9210,\"irt\":9211,\"Ġcop\":9212,\"ĠLeon\":9213,\"Ġfrozen\":9214,\"Ġslip\":9215,\"pton\":9216,\"Ġpanels\":9217,\"Ġpitching\":9218,\"Ġleather\":9219,\"ĠLogan\":9220,\"ĠNearly\":9221,\"urch\":9222,\"Ġinstructions\":9223,\"ĠRow\":9224,\"ĠKurdish\":9225,\"this\":9226,\"Ġlegendary\":9227,\"su\":9228,\"Ġstabbed\":9229,\"sters\":9230,\"Ġteenage\":9231,\"def\":9232,\"Ġoversight\":9233,\"Ġvolatile\":9234,\"Ġtransmission\":9235,\"ĠSgt\":9236,\"ĠIndigenous\":9237,\"ĠOxford\":9238,\"ĠCasey\":9239,\"Ġcor\":9240,\"Ġsalaries\":9241,\"Ġsponsor\":9242,\"Ġprescription\":9243,\"mat\":9244,\"ĠLeeds\":9245,\"ĠPakistani\":9246,\"Ġevil\":9247,\"Ġtables\":9248,\"ĠAbdul\":9249,\"Ġexpectation\":9250,\"Ġlegislature\":9251,\"ĠLin\":9252,\"¹\":9253,\"Ġcontractor\":9254,\"Ġshifting\":9255,\"Ġgenerous\":9256,\"ĠEddie\":9257,\"Ġpuck\":9258,\"utt\":9259,\"Ġdubbed\":9260,\"Ġnowhere\":9261,\"Ġbetting\":9262,\"Ġdisclose\":9263,\"Ĥ\":9264,\"ĠFashion\":9265,\"ĠHarper\":9266,\"handed\":9267,\"isha\":9268,\"ĠReds\":9269,\"Ġachievements\":9270,\"ume\":9271,\"Ġshootings\":9272,\"Ġadvisers\":9273,\"ĠEaster\":9274,\"Ġinternationally\":9275,\"ĠWi\":9276,\"ĠGandhi\":9277,\"ĠChristians\":9278,\"Ġrecruiting\":9279,\"Ġexperiment\":9280,\"Ġsol\":9281,\"Ġdifficulties\":9282,\"Ġinfluential\":9283,\"Ġhybrid\":9284,\"Ġformation\":9285,\"ĠBoulevard\":9286,\"Ġflags\":9287,\"Ġformula\":9288,\"front\":9289,\"Ġinclusion\":9290,\"ĠNone\":9291,\"ICE\":9292,\"Ġfilming\":9293,\"ĠLou\":9294,\"ĠReynolds\":9295,\"Ġpump\":9296,\"Ġexceptional\":9297,\"ANG\":9298,\"ĠCorporate\":9299,\"SAN\":9300,\"ĠHealthcare\":9301,\"ĠUkrainian\":9302,\"aron\":9303,\"Ġpants\":9304,\"Ġdrops\":9305,\"ete\":9306,\"ĠStudies\":9307,\"Ġwounds\":9308,\"END\":9309,\"Ġshower\":9310,\"Ġreviewing\":9311,\"ĠGreater\":9312,\"ĠÂ»\":9313,\"itors\":9314,\"alled\":9315,\"Ġsqu\":9316,\"ĠRonald\":9317,\"ĠInv\":9318,\"Ġtougher\":9319,\"Ġbalanced\":9320,\"Ġlined\":9321,\"Ġprinciple\":9322,\"Ġ1950\":9323,\"Ġleak\":9324,\"Be\":9325,\"Ġcircuit\":9326,\"Ġunfortunate\":9327,\"ĠGran\":9328,\"ĠFish\":9329,\"Ġfriendship\":9330,\"asp\":9331,\"OO\":9332,\"Ġobligations\":9333,\"Ġcoup\":9334,\"OK\":9335,\"Ġbreakdown\":9336,\"Ġhook\":9337,\"Ġresearcher\":9338,\"inated\":9339,\"ĠMarie\":9340,\"ĠGab\":9341,\"ĠWA\":9342,\"quez\":9343,\"General\":9344,\"ĠSwift\":9345,\"Ġgust\":9346,\"ĠCarol\":9347,\"ĠCentury\":9348,\"ĠOPEC\":9349,\"ĠRd\":9350,\"ĠCop\":9351,\"Ġsubjects\":9352,\"ĠComments\":9353,\"ases\":9354,\"Ġrelation\":9355,\"ĠEnvironment\":9356,\"ı\":9357,\"Ġgasoline\":9358,\"ĠLog\":9359,\"Ġicon\":9360,\"Ġprofitable\":9361,\"ĠRetail\":9362,\"ANC\":9363,\"Ġappealing\":9364,\"Ġvillages\":9365,\"Ġpizza\":9366,\"Ġmall\":9367,\"Ġtower\":9368,\"ĠLinda\":9369,\"Ġaccomplished\":9370,\"Ġpod\":9371,\"Ġleaked\":9372,\"ĠWed\":9373,\"Ġmer\":9374,\"Ġopposing\":9375,\"!'\":9376,\"Ġstomach\":9377,\"Ġrevealing\":9378,\"Ġho\":9379,\"DF\":9380,\"ĠSterling\":9381,\"Ġsolely\":9382,\"Ġpres\":9383,\"ĠCy\":9384,\"ĠLatest\":9385,\"ĠPitt\":9386,\"ĠThink\":9387,\"Ġcapability\":9388,\"aled\":9389,\"Ġexecuted\":9390,\"alling\":9391,\"ĠSilva\":9392,\"Ġrestricted\":9393,\"Ġdeclaration\":9394,\"Ġkilometres\":9395,\"rol\":9396,\"Ġidentifying\":9397,\"Ġdonors\":9398,\"vent\":9399,\"Ġcostly\":9400,\"ense\":9401,\"ĠSeeking\":9402,\"OURCE\":9403,\"iving\":9404,\"Ġplacing\":9405,\"tech\":9406,\"Ġbottles\":9407,\"writer\":9408,\"ĠSeahawks\":9409,\"oming\":9410,\"ĠArthur\":9411,\"ously\":9412,\"bin\":9413,\"ĠVa\":9414,\"Ġbias\":9415,\"Ġliability\":9416,\"ift\":9417,\"rak\":9418,\"aves\":9419,\"Ġcautious\":9420,\"ĠPrize\":9421,\"iley\":9422,\"ĠSharma\":9423,\"global\":9424,\"Ġwars\":9425,\"sm\":9426,\"ĠRemember\":9427,\"wind\":9428,\"ĠRichardson\":9429,\"ĠSum\":9430,\"ĠVincent\":9431,\"ĠRice\":9432,\"inf\":9433,\"Ġconsultation\":9434,\"range\":9435,\"Ġbacteria\":9436,\"Ġarchitecture\":9437,\"Ġpole\":9438,\"ĠMach\":9439,\"Ġcattle\":9440,\"Ġabused\":9441,\"being\":9442,\"ĠHERE\":9443,\"Ġfame\":9444,\"Ġhearings\":9445,\"ĠBrit\":9446,\"Ġjoins\":9447,\"ĠMcGregor\":9448,\"Ġoppose\":9449,\"Ġcheer\":9450,\"itting\":9451,\"imes\":9452,\"Ġusage\":9453,\"Ġstint\":9454,\"Ġoutlet\":9455,\"Ġshoppers\":9456,\"ĠBaptist\":9457,\"Ġinappropriate\":9458,\"ĠALSO\":9459,\"Ġstealing\":9460,\"Ġpledge\":9461,\"ĠRan\":9462,\"Ġphotographer\":9463,\"Ġprevented\":9464,\"Ġ01\":9465,\"ĠEngineering\":9466,\"ĠProducts\":9467,\"Ġuniverse\":9468,\"ĠMcCarthy\":9469,\"¿\":9470,\"graded\":9471,\"Ġinspection\":9472,\"Ġind\":9473,\"Fi\":9474,\"aren\":9475,\"Ġprotections\":9476,\"Ġsorts\":9477,\"ĠWorks\":9478,\"Ġbillionaire\":9479,\"ĠGay\":9480,\"ĠiPad\":9481,\"IX\":9482,\"Ġdefendants\":9483,\"band\":9484,\"Ġfarms\":9485,\"Ġhom\":9486,\"gal\":9487,\"iant\":9488,\"Ġnortheast\":9489,\"ĠJoint\":9490,\"Ġcanceled\":9491,\"Ġtoys\":9492,\"Ġrein\":9493,\"ĠTumblr\":9494,\"pees\":9495,\"ĠAut\":9496,\"Police\":9497,\"Ġaide\":9498,\"Ġachieving\":9499,\"Ġmund\":9500,\"ĠCommercial\":9501,\"first\":9502,\"Ġanticipate\":9503,\"iac\":9504,\"Ġprobation\":9505,\"hem\":9506,\"Ġports\":9507,\"ĠKer\":9508,\"Ġsupplier\":9509,\"ĠFather\":9510,\"ĠAnti\":9511,\"ashed\":9512,\"ĠTable\":9513,\"bledon\":9514,\"Ġunf\":9515,\"ĠRash\":9516,\"ĠLeBron\":9517,\"Car\":9518,\"bu\":9519,\"ĠDerek\":9520,\"Ġaccounted\":9521,\"ĠPri\":9522,\"nings\":9523,\"Ġreceives\":9524,\"lev\":9525,\"Ġbilateral\":9526,\"ĠList\":9527,\"ĠLG\":9528,\"ĠJazz\":9529,\"Ġrestored\":9530,\"Ġbattles\":9531,\"ials\":9532,\"Ġoccupied\":9533,\"Ġrepairs\":9534,\"Ġradar\":9535,\"ĠMLB\":9536,\"ĠNC\":9537,\"Ġflexible\":9538,\"ĠCommand\":9539,\"Ġcoat\":9540,\"ĠVir\":9541,\"ĠColts\":9542,\"ĠBC\":9543,\"Ġtwin\":9544,\"Ġprisoners\":9545,\"Ġslowed\":9546,\"hop\":9547,\"ĠInn\":9548,\"Ġconflicts\":9549,\"Ġmeasured\":9550,\"Ġautonomous\":9551,\"ĠBow\":9552,\"Ġdisc\":9553,\"inson\":9554,\"ĠSche\":9555,\"aire\":9556,\"ĠSU\":9557,\"ĠPeterson\":9558,\"Ġdrafted\":9559,\"ĠPelosi\":9560,\"ĠSoon\":9561,\"Ġmechanism\":9562,\"Ġaccountability\":9563,\"ĠNortheast\":9564,\"Ġfo\":9565,\"Ġanalytics\":9566,\"ĠEverything\":9567,\"Ġperceived\":9568,\"bers\":9569,\"Ġcelebrations\":9570,\"Ġinstruments\":9571,\"Ġstrip\":9572,\"ĠJuventus\":9573,\"Ġunfortunately\":9574,\"ĠGA\":9575,\"Ġwrestling\":9576,\"Ġstatue\":9577,\"vis\":9578,\"five\":9579,\"Ġmarine\":9580,\"ĠSamuel\":9581,\"Ġresponsibilities\":9582,\"hill\":9583,\"Ġrecruit\":9584,\"Ġreferee\":9585,\"ĠRail\":9586,\"ĠEagle\":9587,\"ĠCongressional\":9588,\"Ġbreathing\":9589,\"Ġbass\":9590,\"hit\":9591,\"Ġspreading\":9592,\"Ġevacuated\":9593,\"Ġintellectual\":9594,\"Ġsovereign\":9595,\"ocked\":9596,\"Ġslammed\":9597,\"Ġformerly\":9598,\"Ġarch\":9599,\"Ġdifficulty\":9600,\"ĠAFC\":9601,\"ĠFresh\":9602,\"Ġinvite\":9603,\"oner\":9604,\"ĠMich\":9605,\"Ġpitches\":9606,\"stock\":9607,\"Ġinitiated\":9608,\"ĠKu\":9609,\"ĠFlorence\":9610,\"yd\":9611,\"ĠFast\":9612,\"Ġmusician\":9613,\"ĠChile\":9614,\"anga\":9615,\"Ġdairy\":9616,\"Ġcontractors\":9617,\"ador\":9618,\"ĠPlanning\":9619,\"Ġultra\":9620,\"Ġprayer\":9621,\"Ġsuggestions\":9622,\"ĠEk\":9623,\"Ġrandom\":9624,\"ĠSullivan\":9625,\"Ġsensor\":9626,\"Ġhomicide\":9627,\"ĠIncome\":9628,\"Ġsettings\":9629,\"Ġacknowledge\":9630,\"ĠStay\":9631,\"Ġterminal\":9632,\"Ġ1991\":9633,\"West\":9634,\"hard\":9635,\"arc\":9636,\"Ġcombine\":9637,\"Ġprivately\":9638,\"Ġbarrier\":9639,\"Ġmedian\":9640,\"Ġwhereas\":9641,\"ĠTitans\":9642,\"Ġincentives\":9643,\"Ġhistorically\":9644,\"Ġindictment\":9645,\"Ġhiding\":9646,\"ĠPDT\":9647,\"Ġrebuild\":9648,\"hol\":9649,\"Ġpour\":9650,\"Ġairports\":9651,\"ĠEdinburgh\":9652,\"Ġappoint\":9653,\"ĠJul\":9654,\"Ġconfusion\":9655,\"Ġdam\":9656,\"ork\":9657,\"Ġcalculated\":9658,\"Ġhood\":9659,\"ĠTemple\":9660,\"ĠYorkshire\":9661,\"EP\":9662,\"ented\":9663,\"Ġapology\":9664,\"awi\":9665,\"Ġfacilitate\":9666,\"ĠSheffield\":9667,\"Ġrides\":9668,\"Ġcompelling\":9669,\"ĠGonzalez\":9670,\"roll\":9671,\"ONG\":9672,\"UP\":9673,\"ĠAj\":9674,\"pen\":9675,\"ĠVar\":9676,\"ĠIPO\":9677,\"ĠAnimal\":9678,\"Ġshifted\":9679,\"Ġ140\":9680,\"Ġtobacco\":9681,\"El\":9682,\"ild\":9683,\"Ġuncertain\":9684,\"Un\":9685,\"Ġcaps\":9686,\"Ġrecreational\":9687,\"ĠTu\":9688,\"Ġenc\":9689,\"More\":9690,\"iko\":9691,\"ĠEverton\":9692,\"ĠWalk\":9693,\"Ġmurdered\":9694,\"Ġpur\":9695,\"Ġdivisions\":9696,\"ivo\":9697,\"Ġfarming\":9698,\"Ġcourage\":9699,\"ped\":9700,\"Ġcrying\":9701,\"Ġattributed\":9702,\"Ã©e\":9703,\"Ġimplementing\":9704,\"ĠWang\":9705,\"Ġspeeds\":9706,\"alk\":9707,\"aming\":9708,\"eries\":9709,\"Ġavoided\":9710,\"ĠMessi\":9711,\"Ġconsiderable\":9712,\"rt\":9713,\"Ġinauguration\":9714,\"ĠPH\":9715,\"Ġsoldier\":9716,\"Ġore\":9717,\"ollywood\":9718,\"otive\":9719,\"ĠAuburn\":9720,\"ĠSav\":9721,\"ĠPut\":9722,\"Ġemphasis\":9723,\"Ġaf\":9724,\"owed\":9725,\"Ġdiagnosis\":9726,\"Ġcart\":9727,\"Ġassisted\":9728,\"ĠOrder\":9729,\"ĠEstate\":9730,\"Ġintends\":9731,\"ĠCommon\":9732,\"Ġadventure\":9733,\"Ġbeliefs\":9734,\"Ġlasting\":9735,\"cel\":9736,\"Ġdeployment\":9737,\"tra\":9738,\"ĠStories\":9739,\"Ġquote\":9740,\"Ġfeared\":9741,\"Ġconvenience\":9742,\"Ġoptimism\":9743,\"Ġscientist\":9744,\"ĠEnterprise\":9745,\"ĠRex\":9746,\"ĠFel\":9747,\"Ġposes\":9748,\"Ġroot\":9749,\"Ġevacuation\":9750,\"Ġpresidents\":9751,\"ĠRather\":9752,\"Ġgrave\":9753,\"ĠHeights\":9754,\"Ġjumping\":9755,\"driven\":9756,\"Ġaluminum\":9757,\"Ġholders\":9758,\"Ġboot\":9759,\"iber\":9760,\"Ġprecious\":9761,\"uation\":9762,\"FP\":9763,\"uses\":9764,\"Ġcommentary\":9765,\"Ġadvances\":9766,\"ĠNissan\":9767,\"Ġbronze\":9768,\"Ġinspire\":9769,\"Ġstarters\":9770,\"ĠEvan\":9771,\"rah\":9772,\"body\":9773,\"Ġcrops\":9774,\"Ġseeds\":9775,\"Ġharsh\":9776,\"ĠHomeland\":9777,\"Ġenabled\":9778,\"ological\":9779,\"Ġworkshop\":9780,\"Ġchains\":9781,\"amps\":9782,\"Ġamongst\":9783,\"ĠBear\":9784,\"Ġcertified\":9785,\"ĠJulie\":9786,\"Ġmountains\":9787,\"VA\":9788,\"Ġfed\":9789,\"Ġbuyer\":9790,\"ahl\":9791,\"ĠBos\":9792,\"ĠCrystal\":9793,\"Ġquest\":9794,\"ĠStein\":9795,\"Ġacceptable\":9796,\"Ġunbeaten\":9797,\"iring\":9798,\"ural\":9799,\"Ġuncomfortable\":9800,\"Ġpartial\":9801,\"Ġsacrifice\":9802,\"ĠGrande\":9803,\"Ġarrangement\":9804,\"Ġpackaging\":9805,\"screen\":9806,\"Ġmirror\":9807,\"Ġsweep\":9808,\"Ġconnecting\":9809,\"Ġpanic\":9810,\"ĠJacksonville\":9811,\"ĠKremlin\":9812,\"Ġorigin\":9813,\"Brien\":9814,\"Ġnorthwest\":9815,\"Ġcarriers\":9816,\"ĠRiley\":9817,\"Ġaud\":9818,\"Ġappreciation\":9819,\"Ġeliminated\":9820,\"ĠAnalyst\":9821,\"CR\":9822,\"Ġfirearm\":9823,\"Ġaccommodate\":9824,\"Ġstructural\":9825,\"Ġappealed\":9826,\"Ġcharter\":9827,\"ressing\":9828,\"Ġalike\":9829,\"white\":9830,\"Ġslowdown\":9831,\"Ġweigh\":9832,\"ĠPalmer\":9833,\"ound\":9834,\"ĠConn\":9835,\"Ġbranches\":9836,\"Ġace\":9837,\"Ġinsists\":9838,\"yo\":9839,\"ĠLynn\":9840,\"ĠCC\":9841,\"ĠWithin\":9842,\"Ġcoll\":9843,\"Ġsustain\":9844,\"Ġemerge\":9845,\"ĠBattle\":9846,\"VER\":9847,\"Ġaviation\":9848,\"Ġenables\":9849,\"ĠProduction\":9850,\"ĠGrove\":9851,\"Ġnationally\":9852,\"ĠBaldwin\":9853,\"rent\":9854,\"Ġfirearms\":9855,\"irm\":9856,\"Ġconsiders\":9857,\"ĠCosby\":9858,\"ĠMcK\":9859,\"ĠEnt\":9860,\"Ġincumbent\":9861,\"iance\":9862,\"Ġgiants\":9863,\"Ġkan\":9864,\"Ġminimal\":9865,\"ivity\":9866,\"ĠSay\":9867,\"ĠNass\":9868,\"Ġlovely\":9869,\"ĠFurthermore\":9870,\"Ġdisplaced\":9871,\"Ġcontacts\":9872,\"NY\":9873,\"Ġtechnological\":9874,\"ancy\":9875,\"Ġant\":9876,\"ope\":9877,\"ĠFY\":9878,\"Ġfavorable\":9879,\"ĠVirgin\":9880,\"Ġcasual\":9881,\"ĠLat\":9882,\"Ġpopulations\":9883,\"Ġromance\":9884,\"Ġforgotten\":9885,\"Ġfleeing\":9886,\"Ġspecialty\":9887,\"Ġdrill\":9888,\"Ġapplying\":9889,\"Ġcocaine\":9890,\"rea\":9891,\"Ġheroin\":9892,\"Ġsweeping\":9893,\"ĠMaj\":9894,\"Ġtroubled\":9895,\"Ġcolleague\":9896,\"Ġedged\":9897,\"omes\":9898,\"ĠHappy\":9899,\"Â´\":9900,\"Ġmilitant\":9901,\"boy\":9902,\"aver\":9903,\"Yes\":9904,\"llo\":9905,\"Ġsupporter\":9906,\"ĠSubscribe\":9907,\"ĠBird\":9908,\"ĠGibson\":9909,\"Ġhill\":9910,\"Ġnewspapers\":9911,\"ĠPHOTO\":9912,\"Ġouting\":9913,\"Ġdefine\":9914,\"Ġann\":9915,\"Ġrobot\":9916,\"Ġregret\":9917,\"ĠCould\":9918,\"raz\":9919,\"Ġceiling\":9920,\"Ġorganizers\":9921,\"ĠTw\":9922,\"Ġcriticised\":9923,\"ĠJoh\":9924,\"ĠJe\":9925,\"ĠBulls\":9926,\"Ġteeth\":9927,\"ĠRanch\":9928,\"ĠAndrea\":9929,\"Ġconservatives\":9930,\"Ġmag\":9931,\"vey\":9932,\"Ġpredecessor\":9933,\"ĠJPMorgan\":9934,\"Ġdraws\":9935,\"umber\":9936,\"Ġvaccine\":9937,\"ĠDas\":9938,\"Ġdisappeared\":9939,\"ĠIron\":9940,\"Ġlitigation\":9941,\"vert\":9942,\"Ġbelong\":9943,\"ĠRet\":9944,\"owers\":9945,\"rain\":9946,\"controlled\":9947,\"ĠKil\":9948,\"Ġrehab\":9949,\"ĠAustria\":9950,\"Ġprivilege\":9951,\"Ġbounce\":9952,\"Ġbout\":9953,\"ĠIslamist\":9954,\"Ġtaxi\":9955,\"ody\":9956,\".'\\\"\":9957,\"Ġdos\":9958,\"shire\":9959,\"Ġaccidents\":9960,\"Ġdemonstration\":9961,\"His\":9962,\"ĠBO\":9963,\"ĠICE\":9964,\"van\":9965,\"File\":9966,\"ĠManning\":9967,\"ounded\":9968,\"Ġdirections\":9969,\"lled\":9970,\"Ġoffences\":9971,\"Ġlaptop\":9972,\"ĠUniversal\":9973,\"Ġmilestone\":9974,\"ĠNarendra\":9975,\"Ġnotion\":9976,\"Ġuns\":9977,\"ĠLower\":9978,\"Ġmidfield\":9979,\"Ġoutper\":9980,\"trans\":9981,\"ĠJa\":9982,\"three\":9983,\"Adds\":9984,\"Ġpressures\":9985,\"Ġprohibited\":9986,\"Ġutilities\":9987,\"Ġbes\":9988,\"ĠReporter\":9989,\"Ġcommodities\":9990,\"leton\":9991,\"Ġslower\":9992,\"EE\":9993,\"auer\":9994,\"Ġtablet\":9995,\"sl\":9996,\"iously\":9997,\"Ġaiming\":9998,\"eland\":9999,\"ĠNEXT\":10000,\"tered\":10001,\"IVE\":10002,\"onic\":10003,\"May\":10004,\"ĠMilitary\":10005,\"Mark\":10006,\"Ġlender\":10007,\"mate\":10008,\"Ġaboard\":10009,\"they\":10010,\"Ġrespondents\":10011,\"Ġconversion\":10012,\"Ġsecuring\":10013,\"Ġentity\":10014,\"ĠHarbor\":10015,\"ĠCu\":10016,\"Ġcats\":10017,\"ĠACC\":10018,\"ĠIbrahim\":10019,\"GL\":10020,\"Ġinvitation\":10021,\"Ġcond\":10022,\"ĠRecords\":10023,\"ĠAdrian\":10024,\"Ġbrave\":10025,\"Ġmineral\":10026,\"Ġsooner\":10027,\"Ġsatisfied\":10028,\"Ġpets\":10029,\"Ġnotably\":10030,\"Ä±\":10031,\"Ġmarking\":10032,\"ĠRO\":10033,\"ĠHaw\":10034,\"ĠVis\":10035,\"Ġmarketplace\":10036,\"ĠNat\":10037,\"ĠForward\":10038,\"ĠLeft\":10039,\"Ġaggravated\":10040,\"ĠClose\":10041,\"acey\":10042,\"Ġlandmark\":10043,\"Ġdisruption\":10044,\"ĠChallenge\":10045,\"ĠDays\":10046,\"ĠCoun\":10047,\"ahan\":10048,\"Ġaides\":10049,\"South\":10050,\"ĠDylan\":10051,\"ĠRavens\":10052,\"ĠNature\":10053,\"lli\":10054,\"Ġdiplomats\":10055,\"350\":10056,\"ĠDrake\":10057,\"tag\":10058,\"Ġlicensed\":10059,\"ĠDenmark\":10060,\"Ġcancel\":10061,\"Ġinstant\":10062,\"DI\":10063,\"Ġpunch\":10064,\"ĠJenkins\":10065,\"Ġstrengthening\":10066,\"des\":10067,\"-$\":10068,\"Ġallegation\":10069,\"Ġsizes\":10070,\"iza\":10071,\"Ġmentally\":10072,\"ĠResidents\":10073,\"acked\":10074,\"Ġsensors\":10075,\",'\\\"\":10076,\"illion\":10077,\"ĠChampion\":10078,\"Ġexcessive\":10079,\"Ġhum\":10080,\"ĠComp\":10081,\"rend\":10082,\"ĠLakes\":10083,\"Ġburst\":10084,\"Ġtrainer\":10085,\"Ġclearing\":10086,\"ĠSilicon\":10087,\"Ġ350\":10088,\"DE\":10089,\"ĠGates\":10090,\"ĠHorn\":10091,\"ests\":10092,\"ĠCourtesy\":10093,\"Ġbipartisan\":10094,\"Ġhabits\":10095,\"ĠAlexa\":10096,\"walk\":10097,\"Ġsnapped\":10098,\"ĠEight\":10099,\"itis\":10100,\"zel\":10101,\"Ġcustoms\":10102,\"Ġsouthwest\":10103,\"Ġvary\":10104,\"Because\":10105,\"Ġpayout\":10106,\"Ġaccelerate\":10107,\"ĠBarr\":10108,\"tu\":10109,\"Ġfined\":10110,\"cost\":10111,\"ĠTheater\":10112,\"ĠCorbyn\":10113,\"Ġstem\":10114,\"Ġundermine\":10115,\".;\":10116,\"Ġstays\":10117,\"Ġbreakthrough\":10118,\"Ġturnover\":10119,\"hot\":10120,\"Ġtriumph\":10121,\"Ġpainted\":10122,\"ĠWinnipeg\":10123,\"ĠKas\":10124,\"ĠStuart\":10125,\"irk\":10126,\"Am\":10127,\"Ġtrusted\":10128,\"aze\":10129,\"ĠLate\":10130,\"Ġaccessories\":10131,\"Ġmemorable\":10132,\"ĠFool\":10133,\"Ġrotation\":10134,\"ĠBulldogs\":10135,\"ĠChen\":10136,\"Ġpoised\":10137,\"ĠMonte\":10138,\"ĠClarke\":10139,\"leading\":10140,\"Ġvenues\":10141,\"Ġbeneficial\":10142,\"ĠLiam\":10143,\"ĠBrothers\":10144,\"ĠNeed\":10145,\"Ġconc\":10146,\"olly\":10147,\"ĠJulian\":10148,\"ogue\":10149,\"Ġfounding\":10150,\"Ġsidelines\":10151,\"Ġdeclare\":10152,\"ĠMember\":10153,\"Ġexamine\":10154,\"abs\":10155,\"Ġboundaries\":10156,\"ĠBrisbane\":10157,\"Ġlaunches\":10158,\"lor\":10159,\"ĠGa\":10160,\"Ġthr\":10161,\"expected\":10162,\"wal\":10163,\"ĠBarnes\":10164,\"Ġclashes\":10165,\"content\":10166,\"ĠClemson\":10167,\"iger\":10168,\"Mar\":10169,\"Ġaccord\":10170,\"Ġsoutheast\":10171,\"ģ\":10172,\"ĠStarbucks\":10173,\"osing\":10174,\"Ġseasonal\":10175,\"icking\":10176,\"Ġloyalty\":10177,\"Ġtent\":10178,\"ĠDy\":10179,\"Ġevident\":10180,\"Ġlobby\":10181,\"Ġtours\":10182,\"Ġbombing\":10183,\"uations\":10184,\"Ġrises\":10185,\"Ġdemonstrations\":10186,\"ĠWATCH\":10187,\"pin\":10188,\"Ġdeb\":10189,\"ĠDraft\":10190,\"rog\":10191,\"Ġseal\":10192,\"ĠPerformance\":10193,\"ĠLGBT\":10194,\"Ġsed\":10195,\"Ġgig\":10196,\"nan\":10197,\"Ġrainfall\":10198,\"Ġfabric\":10199,\"Ġmanages\":10200,\"Ġlifting\":10201,\"ĠMagazine\":10202,\"ĠCriminal\":10203,\"Ġhikes\":10204,\"Ġcatching\":10205,\"Ġ1989\":10206,\"OG\":10207,\"Ġdisappointment\":10208,\"Ġir\":10209,\"ĠEV\":10210,\"stown\":10211,\"pass\":10212,\"120\":10213,\"Ġmedals\":10214,\"ĠSimmons\":10215,\"Ġinaugural\":10216,\"ĠCorn\":10217,\"Ġmotorcycle\":10218,\"lets\":10219,\"ĠSkype\":10220,\"Ã©t\":10221,\"Ġscary\":10222,\"opp\":10223,\"thirds\":10224,\"ĠMohamed\":10225,\"Ġteenagers\":10226,\"ANK\":10227,\"Ġserver\":10228,\"Ġouts\":10229,\"Ġdishes\":10230,\"four\":10231,\"dr\":10232,\"ĠOt\":10233,\"ĠSandy\":10234,\"ĠShane\":10235,\"orters\":10236,\"SH\":10237,\"Ġtouching\":10238,\"ĠNike\":10239,\"ĠHBO\":10240,\"driving\":10241,\"Ġplug\":10242,\"ĠBaseball\":10243,\"eling\":10244,\"hn\":10245,\"ulate\":10246,\"eed\":10247,\"ĠChristine\":10248,\"ĠGlobe\":10249,\"Ġethics\":10250,\"ĠTrevor\":10251,\"iya\":10252,\"Ġ360\":10253,\"Ġawaiting\":10254,\"Ġcounterpart\":10255,\"Ġsubsidies\":10256,\"pointers\":10257,\"Ġspy\":10258,\"ILL\":10259,\"Ġtakeover\":10260,\"ĠBeyond\":10261,\"Ġsurprisingly\":10262,\"TION\":10263,\"ĠSong\":10264,\"Ġni\":10265,\"Ġcommonly\":10266,\"Ġjack\":10267,\"Ġsubstitute\":10268,\"ews\":10269,\"Ġrecalls\":10270,\"ĠCommons\":10271,\"Ġsin\":10272,\"del\":10273,\"ĠMod\":10274,\"Ġpressing\":10275,\"ĠTelevision\":10276,\"ĠInside\":10277,\"ª\":10278,\"Ġbacklash\":10279,\"Ġcredible\":10280,\"ĠJenner\":10281,\"ĠPu\":10282,\"ĠStevens\":10283,\"ĠWE\":10284,\"Last\":10285,\"Ġinsurers\":10286,\"ĠJoin\":10287,\"bled\":10288,\"digit\":10289,\"Ġflooded\":10290,\"ĠShore\":10291,\"ĠTrophy\":10292,\"zing\":10293,\"ĠImmigration\":10294,\"Ġsuperior\":10295,\"IAN\":10296,\"Ġcasino\":10297,\"Ġenabling\":10298,\"Ġmeantime\":10299,\"Ġperformers\":10300,\"Ġproportion\":10301,\"Ġlawmaker\":10302,\"ĠConf\":10303,\"Ġconvert\":10304,\"Ġfarmer\":10305,\"Ġbu\":10306,\"ĠGE\":10307,\"ĠRepresentative\":10308,\"ĠBannon\":10309,\"ĠHelp\":10310,\"PT\":10311,\"formed\":10312,\"ĠSuperintendent\":10313,\"Ġfrustrating\":10314,\"ĠRegister\":10315,\"ĠPolitical\":10316,\"Ġboots\":10317,\"ĠRu\":10318,\"ĠSha\":10319,\"Ġinstrument\":10320,\"tor\":10321,\"ĠBelt\":10322,\"ĠWalsh\":10323,\"Ġrecipe\":10324,\"ilt\":10325,\"ĠClean\":10326,\"iors\":10327,\"Ġtwenty\":10328,\"iler\":10329,\"nder\":10330,\"Ġwinger\":10331,\"Ġwheat\":10332,\"ĠAviation\":10333,\"Ġcorrupt\":10334,\"Ġconnectivity\":10335,\"ĠVen\":10336,\"order\":10337,\"esc\":10338,\"break\":10339,\"Ġmetals\":10340,\"Ġtraditionally\":10341,\"Ġbell\":10342,\"Ġviolating\":10343,\"rough\":10344,\"Ġintroducing\":10345,\"Ġguided\":10346,\"ĠMol\":10347,\"Ġdesert\":10348,\"ĠBree\":10349,\"Le\":10350,\"ĠZone\":10351,\"ĠGlass\":10352,\"ĠEUR\":10353,\"ĠYahoo\":10354,\"Ġlaps\":10355,\"Ġdiffer\":10356,\"ĠHold\":10357,\"Ġtimely\":10358,\"Ġsuccessor\":10359,\"Ġcomic\":10360,\"Ġbears\":10361,\"Ġlicence\":10362,\"Ġreject\":10363,\"Ġsophisticated\":10364,\"Too\":10365,\"Ġobjectives\":10366,\"ĠId\":10367,\"urers\":10368,\"Ġraid\":10369,\"COM\":10370,\"Ġelect\":10371,\"ĠHampshire\":10372,\"Ġlens\":10373,\"Ġdesigners\":10374,\"Ġpresently\":10375,\"ĠRCMP\":10376,\"ĠEgyptian\":10377,\"ĠWalter\":10378,\"ĠWallace\":10379,\"Ġ2025\":10380,\"utics\":10381,\"ried\":10382,\"Ġrefuse\":10383,\"Ġsiblings\":10384,\"ĠNothing\":10385,\"Ġdressing\":10386,\"Ġnerve\":10387,\"AST\":10388,\"Ġuncertainties\":10389,\"Ġtale\":10390,\"ĠTalk\":10391,\"Ġissuing\":10392,\"shot\":10393,\"ĠTak\":10394,\"Ġacid\":10395,\"ĠNintendo\":10396,\"Ġwash\":10397,\"pd\":10398,\"ĠClaire\":10399,\"ĠScot\":10400,\"Ġsuits\":10401,\"ĠBayern\":10402,\"gest\":10403,\"Ġapplicable\":10404,\"Ġinteraction\":10405,\"ĠEnforcement\":10406,\"ĠRohingya\":10407,\"Ġjan\":10408,\"Ġunited\":10409,\"ĠCoalition\":10410,\"Ġlegislators\":10411,\"Ġdetectives\":10412,\"ĠSing\":10413,\"ĠBetween\":10414,\"ĠPoly\":10415,\"pool\":10416,\"mal\":10417,\"Ġreply\":10418,\"Ġschemes\":10419,\"ĠHolmes\":10420,\"ĠSenators\":10421,\"ĠVerizon\":10422,\"Ġwelcoming\":10423,\"ĠCricket\":10424,\"ĠMarco\":10425,\"ĠYears\":10426,\"ĠLiving\":10427,\"Ġcounterparts\":10428,\"ĠParadise\":10429,\"ĠTrad\":10430,\"#\":10431,\"iw\":10432,\"ĠSoccer\":10433,\"umbled\":10434,\"Ġdeceased\":10435,\"heim\":10436,\"Ġevaluation\":10437,\"Ġwrap\":10438,\"Ġmild\":10439,\"aji\":10440,\"ĠUCLA\":10441,\"ĠNative\":10442,\"president\":10443,\"ĠXbox\":10444,\"Ġenterprises\":10445,\"ĠSlam\":10446,\"oga\":10447,\"Rock\":10448,\"piece\":10449,\"ĠColeman\":10450,\"Ġcomparable\":10451,\"uba\":10452,\"Ġprovinces\":10453,\"ĠFormula\":10454,\"ipt\":10455,\"Ã´\":10456,\"Ġtick\":10457,\"ĠIMF\":10458,\"anch\":10459,\"atta\":10460,\"rew\":10461,\"However\":10462,\"LS\":10463,\"etta\":10464,\"ĠCustoms\":10465,\"SU\":10466,\"Ġpublishing\":10467,\"Ġinch\":10468,\"Ġkills\":10469,\"¤\":10470,\"ĠSus\":10471,\"ĠBeth\":10472,\"Ġsteam\":10473,\"jpg\":10474,\"pointer\":10475,\"Ġturnovers\":10476,\"Ġpowder\":10477,\"ĠUSB\":10478,\"ĠWildlife\":10479,\"ĠDirect\":10480,\"atively\":10481,\"ĠFerrari\":10482,\"Ġpleasure\":10483,\"ĠMatthews\":10484,\"Ġski\":10485,\"ography\":10486,\"ĠVermont\":10487,\"ĠMargaret\":10488,\"ĠMunich\":10489,\"Ġlayer\":10490,\"ĠProperty\":10491,\"Ġeconomics\":10492,\"ĠCrew\":10493,\"UK\":10494,\"Ġunnecessary\":10495,\"ĠGlasgow\":10496,\"Ġsealed\":10497,\"Ġclarity\":10498,\"Ġsurplus\":10499,\"ĠCanyon\":10500,\"ĠApart\":10501,\"Ġacceptance\":10502,\"ĠEllis\":10503,\"uster\":10504,\"rid\":10505,\"ĠHawks\":10506,\"Ġstatewide\":10507,\"Ġthreaten\":10508,\"ĠJail\":10509,\"Ġinclusive\":10510,\"Ġmud\":10511,\"Ġpat\":10512,\"Ġbitter\":10513,\"Ġalternatives\":10514,\"Ġaffiliate\":10515,\"Ġevaluate\":10516,\"ĠBaby\":10517,\"Ġperception\":10518,\"tim\":10519,\"Ġrefusing\":10520,\"Ġgrey\":10521,\"Ġarguably\":10522,\"Ġfirmly\":10523,\"ĠDark\":10524,\"Ġexcuse\":10525,\"ĠRaymond\":10526,\"Ġballots\":10527,\"inton\":10528,\"Ġ125\":10529,\"ĠCatherine\":10530,\"Ġsacks\":10531,\"ĠDeb\":10532,\"Ġworkout\":10533,\"web\":10534,\"Ġbatteries\":10535,\"breaking\":10536,\"ML\":10537,\"Ġunacceptable\":10538,\"ĠValentine\":10539,\"ĠYOU\":10540,\"ĠRT\":10541,\"Ġjurisdiction\":10542,\"Ġexamined\":10543,\"strom\":10544,\"ĠPocket\":10545,\"Ġcement\":10546,\"Ġuniversal\":10547,\"ĠOz\":10548,\"Ġkit\":10549,\"Ġchurches\":10550,\"Ġsuburban\":10551,\"ĠKushner\":10552,\"ĠDavidson\":10553,\"Sports\":10554,\"email\":10555,\"Ġrealistic\":10556,\"Ġintend\":10557,\"ĠGrey\":10558,\",''\":10559,\"Ġscholarship\":10560,\"Ġphilosophy\":10561,\"Ġwheels\":10562,\"Ġmotivation\":10563,\"eway\":10564,\"match\":10565,\"ĠDate\":10566,\"John\":10567,\"Ġcontrolling\":10568,\"750\":10569,\"aven\":10570,\"Ġfilmed\":10571,\"Ġ160\":10572,\"ĠBrock\":10573,\"ĠDetails\":10574,\"Ġlogistics\":10575,\"Ġassumptions\":10576,\"ĠStep\":10577,\"Ġfails\":10578,\"ĠNotre\":10579,\"Ġjuice\":10580,\"Ġcounting\":10581,\"Ġphotograph\":10582,\"Ġfortunate\":10583,\"Ġestablishing\":10584,\"ĠNJ\":10585,\"ĠWorkers\":10586,\"ĠQuinn\":10587,\"ĠHeather\":10588,\"Ġtimeline\":10589,\"Ġimported\":10590,\"ĠNASCAR\":10591,\"Ġexercises\":10592,\"Ġsearched\":10593,\"ĠRalph\":10594,\"alf\":10595,\"Ġgene\":10596,\"Ġdependent\":10597,\"Ã©n\":10598,\"iate\":10599,\"ĠBristol\":10600,\"Ġhung\":10601,\"Ġtropical\":10602,\"Ġintensity\":10603,\"ĠIdaho\":10604,\"ĠMull\":10605,\"Ġsuite\":10606,\"Ġblockchain\":10607,\"cz\":10608,\"ovich\":10609,\"Ġworn\":10610,\"ĠLE\":10611,\"AV\":10612,\"emi\":10613,\"Ġidentification\":10614,\"Ġtunnel\":10615,\"ĠARE\":10616,\"ĠArm\":10617,\"Ġoutrage\":10618,\"Ġtwist\":10619,\"uka\":10620,\"ĠGra\":10621,\"Ġjets\":10622,\"ĠThus\":10623,\"Ġcompound\":10624,\"Ġfinancially\":10625,\"2019\":10626,\"asse\":10627,\"Ġspare\":10628,\"ĠNoah\":10629,\"ĠMade\":10630,\"ĠMom\":10631,\"Ġphenomenon\":10632,\"Ġnurses\":10633,\"Ġoutlined\":10634,\"Ġpolit\":10635,\"ĠCarm\":10636,\"Ġleagues\":10637,\"Ġmath\":10638,\"Ġmodified\":10639,\"Ġwillingness\":10640,\"ĠAmanda\":10641,\"Ġgrandfather\":10642,\"Of\":10643,\"DR\":10644,\"Ġdip\":10645,\"ĠRAM\":10646,\"ĠChristie\":10647,\"Ġargues\":10648,\"ĠEX\":10649,\"ĠNine\":10650,\"ĠScroll\":10651,\"ĠTHIS\":10652,\"Pro\":10653,\"Ġkeys\":10654,\"Ġprocessor\":10655,\"Ġscam\":10656,\"ĠTraining\":10657,\"Ġhoney\":10658,\"Ĵ\":10659,\"Ġfacebook\":10660,\"ĠLegal\":10661,\"Ġaging\":10662,\"Ġspiritual\":10663,\"ĠHost\":10664,\"Ġlung\":10665,\"ĠUSC\":10666,\"Ġdirt\":10667,\"Ġfe\":10668,\"after\":10669,\"ĠDiana\":10670,\"Ġounce\":10671,\"date\":10672,\"ĠFinals\":10673,\"Ķ\":10674,\"Ġthorough\":10675,\"Ġviable\":10676,\"Ġanytime\":10677,\"Ġfost\":10678,\"orter\":10679,\"ware\":10680,\"ĠHolland\":10681,\"ĠMand\":10682,\"ĠSend\":10683,\"2013\":10684,\"ĠVolkswagen\":10685,\"Ġsuitable\":10686,\"ifies\":10687,\"Ġcomedian\":10688,\"Ġneighbours\":10689,\"ĠKnow\":10690,\"Ġcurious\":10691,\"ĠTwenty\":10692,\"ĠPrevention\":10693,\"ĠStephanie\":10694,\"Ġpilots\":10695,\"Ġstored\":10696,\"Ġdire\":10697,\"Ġfits\":10698,\"ision\":10699,\"ĠShell\":10700,\"Ġshifts\":10701,\"Ġpepper\":10702,\"Ġattendees\":10703,\"ĠName\":10704,\"hers\":10705,\"rip\":10706,\"Ġwatchdog\":10707,\"andy\":10708,\"Ġbio\":10709,\"Ġpublisher\":10710,\"powered\":10711,\"ĠCM\":10712,\"rian\":10713,\"ĠRand\":10714,\"wise\":10715,\"ĠJesse\":10716,\"Ġladies\":10717,\"ĠMetropolitan\":10718,\"ĠMicro\":10719,\"Ġkicking\":10720,\"Ġmeg\":10721,\"Ġclouds\":10722,\"Ġtrim\":10723,\"wear\":10724,\"ĠML\":10725,\"Ġconsists\":10726,\"Ġrig\":10727,\"Ġhonestly\":10728,\"GS\":10729,\"ĠNicholas\":10730,\"Ġcope\":10731,\"Ġpublish\":10732,\"working\":10733,\"bur\":10734,\"ĠNar\":10735,\"olds\":10736,\"aja\":10737,\"ĠSad\":10738,\"Ġclicking\":10739,\"Ġbids\":10740,\"ĠZuckerberg\":10741,\"Ġ900\":10742,\"Ġexam\":10743,\"ivers\":10744,\"Ġpray\":10745,\"Ġreader\":10746,\"ĠSeth\":10747,\"inem\":10748,\"Ġconfront\":10749,\"stra\":10750,\"AW\":10751,\"ĠGian\":10752,\"Ġaccordance\":10753,\"Ġinteract\":10754,\"ĠSharks\":10755,\"Ġfireworks\":10756,\"gment\":10757,\"illy\":10758,\"Ġconst\":10759,\"ARY\":10760,\"Ġprizes\":10761,\"Ġshoulders\":10762,\"Ġaccessed\":10763,\"Ġecosystem\":10764,\"Ġlicensing\":10765,\"La\":10766,\"Ġdedication\":10767,\"ĠdÃ©\":10768,\"Ġyouths\":10769,\"lem\":10770,\"Ġtoy\":10771,\"ĠProm\":10772,\"ounding\":10773,\"rod\":10774,\"Ġ1000\":10775,\"ishes\":10776,\"Over\":10777,\"Ġgaps\":10778,\"Ġmissions\":10779,\"Ġrailway\":10780,\"Day\":10781,\"orp\":10782,\"ĠSchumer\":10783,\"Ġeclipse\":10784,\"Ġshell\":10785,\"ĠBY\":10786,\"Many\":10787,\"ĠRecord\":10788,\"Ġdrunk\":10789,\"ayan\":10790,\"Ġsuggestion\":10791,\"Ġdefenders\":10792,\"ĠNewton\":10793,\"Ġdisputes\":10794,\"Ġevolution\":10795,\"Ġcredibility\":10796,\"ĠTenn\":10797,\"Ġplain\":10798,\"size\":10799,\"cont\":10800,\"Ġlone\":10801,\"Ġfingers\":10802,\"BUR\":10803,\"ĠInvestigation\":10804,\"ĠQualcomm\":10805,\"var\":10806,\"Ġcountless\":10807,\"ĠRebecca\":10808,\"½\":10809,\"abi\":10810,\"Ġreflecting\":10811,\"ĠTurn\":10812,\"Ġinteractive\":10813,\"Ġincentive\":10814,\"second\":10815,\"offs\":10816,\"ĠBerkeley\":10817,\"ĠTexans\":10818,\"Ġheated\":10819,\"Ġscorer\":10820,\"ĠSharif\":10821,\"Ġmigrant\":10822,\"west\":10823,\"ĠHoliday\":10824,\"Ġwrist\":10825,\"Ġchairs\":10826,\"Ġrecommends\":10827,\"ĠWildcats\":10828,\"ĠPed\":10829,\"ĠQuarter\":10830,\"ĠIV\":10831,\"ĠArch\":10832,\"Ġstandings\":10833,\"Ġbombs\":10834,\"Ġcapped\":10835,\"Can\":10836,\"Ġcaring\":10837,\"ĠLah\":10838,\"lim\":10839,\"Ġdragged\":10840,\"ĠBeat\":10841,\"DB\":10842,\"Ġaired\":10843,\"Ġjeans\":10844,\"action\":10845,\"Ġgenerating\":10846,\"ĠGir\":10847,\"risk\":10848,\"lon\":10849,\"stage\":10850,\"âĤ¬\":10851,\"earing\":10852,\"ĠTogether\":10853,\"Ġreun\":10854,\"ĠCorey\":10855,\"ĠBak\":10856,\"Ġprestigious\":10857,\"Ġapplicants\":10858,\"here\":10859,\"ĠMattis\":10860,\"Ġridiculous\":10861,\"ĠLess\":10862,\"Ġrains\":10863,\"Ġpresenting\":10864,\"anti\":10865,\"Ġdisabilities\":10866,\"Ġapartments\":10867,\"storm\":10868,\"ĠHem\":10869,\"Ġhabit\":10870,\"ĠRuth\":10871,\"ĠNPR\":10872,\"nut\":10873,\"Ġappreciated\":10874,\"Ġseparation\":10875,\"uda\":10876,\"Ġminus\":10877,\"ĠPhotos\":10878,\"Ġblew\":10879,\"ĠVoice\":10880,\"Ġrallies\":10881,\"Ġfond\":10882,\"ĠTaking\":10883,\"yt\":10884,\"FE\":10885,\"ĠTory\":10886,\"ressed\":10887,\"ĠLy\":10888,\"Ġrocks\":10889,\"ĠRah\":10890,\"Ġelementary\":10891,\"nis\":10892,\"ĠPresidential\":10893,\"Ġnutrition\":10894,\"Ġbaseman\":10895,\"Ġsuperstar\":10896,\"ĠWa\":10897,\"lar\":10898,\"Ġstaged\":10899,\"ĠLearn\":10900,\"Ġbroadcaster\":10901,\"Ġboasts\":10902,\"Ġdoubts\":10903,\"rum\":10904,\"Ġbare\":10905,\"cap\":10906,\"Ġclimbing\":10907,\"ĠSelect\":10908,\"ĠCant\":10909,\"ĠNord\":10910,\"ĠBeck\":10911,\"ĠKad\":10912,\"ello\":10913,\"Ġenforce\":10914,\"ĠZe\":10915,\"ked\":10916,\"elly\":10917,\"ĠLED\":10918,\"ĠOperations\":10919,\"ĠLuk\":10920,\"Ġcertificate\":10921,\"Ġdeter\":10922,\"Ġspill\":10923,\"Ġgrain\":10924,\"league\":10925,\"Up\":10926,\"ĠKid\":10927,\"using\":10928,\"ĠJays\":10929,\"Ġoccasionally\":10930,\"ĠMI\":10931,\"yes\":10932,\"Ġdetect\":10933,\"Ġpropaganda\":10934,\"Ġneighboring\":10935,\"sub\":10936,\"avan\":10937,\"ĠAstros\":10938,\"oti\":10939,\"threatening\":10940,\"Ġshorter\":10941,\"INGS\":10942,\"Ġfeeding\":10943,\"Ġelevated\":10944,\"ĠWenger\":10945,\"Ġundergo\":10946,\"Ġpsychological\":10947,\"Ġautom\":10948,\"NP\":10949,\"anks\":10950,\"ĠNokia\":10951,\"Ġdrones\":10952,\"Ġrecognised\":10953,\"Ġheroes\":10954,\"agen\":10955,\"Ġparole\":10956,\"ĠBah\":10957,\"Ġhomeowners\":10958,\"ĠSweet\":10959,\"Ġinstances\":10960,\"ĠParish\":10961,\"ĠSL\":10962,\"Ġunw\":10963,\"Ġdelicious\":10964,\"¯\":10965,\"ĠInvestments\":10966,\"ĠPhilippine\":10967,\"inos\":10968,\"Ġmes\":10969,\"Ġbite\":10970,\"Ġcornerback\":10971,\"ĠHat\":10972,\"Ġdeserved\":10973,\"ologists\":10974,\"[\":10975,\"Ġwrongdoing\":10976,\"ĠTrent\":10977,\"ĠVe\":10978,\"ĠDeal\":10979,\"Mr\":10980,\"Ġovers\":10981,\"Ġhonors\":10982,\"ĠITV\":10983,\"Ġpayroll\":10984,\"Ġconfused\":10985,\"Ġelaborate\":10986,\"ange\":10987,\"World\":10988,\"ĠResort\":10989,\"ilia\":10990,\"ĠKr\":10991,\"Ġconclude\":10992,\"First\":10993,\"ĠDR\":10994,\"Ġpeer\":10995,\"Ġrunway\":10996,\"ĠPotter\":10997,\"cons\":10998,\"bad\":10999,\"si\":11000,\"ĠClimate\":11001,\"ĠHoll\":11002,\"Ġweighing\":11003,\"Ġepidemic\":11004,\"ĠBible\":11005,\"Ġhon\":11006,\"Ġrenew\":11007,\"Ġgambling\":11008,\"ĠNationals\":11009,\"itable\":11010,\"ĠOutlook\":11011,\"Ġreactions\":11012,\"ĠCos\":11013,\"ĠDana\":11014,\"India\":11015,\"ĠAirbus\":11016,\"power\":11017,\"watch\":11018,\"Ġstyles\":11019,\"Ġordinance\":11020,\"Ġcam\":11021,\"Ġinvent\":11022,\"ĠDurant\":11023,\"Ġexchanged\":11024,\"Ġyoga\":11025,\"ĠMichel\":11026,\"ĠWyoming\":11027,\"ĠPhase\":11028,\"ĠHannah\":11029,\"Ġtem\":11030,\"Ġfare\":11031,\"omer\":11032,\"Ġtrails\":11033,\"Ġquietly\":11034,\"ĠFourth\":11035,\"Ġwise\":11036,\"Ġappetite\":11037,\"Ġpedestrian\":11038,\"Ġfierce\":11039,\"hin\":11040,\"ako\":11041,\"Ġvacant\":11042,\"Ġdynamics\":11043,\"Ġbust\":11044,\"ĠGT\":11045,\"century\":11046,\"Ġpermitted\":11047,\"Ġfog\":11048,\"Ġrecruitment\":11049,\"ĠDue\":11050,\"Ġbro\":11051,\"Ġsil\":11052,\"ĠOpp\":11053,\"Ġphrase\":11054,\"ĠChip\":11055,\"ĠBase\":11056,\"Ġjazz\":11057,\"Ġenemies\":11058,\"Ġremainder\":11059,\"bles\":11060,\"Ġ105\":11061,\"ĠGur\":11062,\"Ġretiring\":11063,\"ĠCour\":11064,\"ĠSi\":11065,\"Ġinevitable\":11066,\"ĠAdvisory\":11067,\"ĠCampaign\":11068,\"ĠPeninsula\":11069,\"base\":11070,\"Ġjustify\":11071,\"inen\":11072,\"North\":11073,\"Ġfreezing\":11074,\"Ġphotography\":11075,\"Ġappointments\":11076,\"ĠTree\":11077,\"Os\":11078,\"Ġdivide\":11079,\"ĠMMA\":11080,\"Ġdeclines\":11081,\"ĠAbbott\":11082,\"ACH\":11083,\"ĠJah\":11084,\"Ġspr\":11085,\"Ġskilled\":11086,\"ĠTry\":11087,\"ANT\":11088,\"ael\":11089,\"ĠMcN\":11090,\"Ġtariff\":11091,\"generation\":11092,\"ĠMans\":11093,\"Or\":11094,\"Ġraped\":11095,\"Ġdisability\":11096,\"Ġnominations\":11097,\"Ġhappiness\":11098,\"ĠLSU\":11099,\"ĠInterstate\":11100,\"ĠDance\":11101,\"ĠMaking\":11102,\"Ġbailout\":11103,\"oro\":11104,\"ĠObviously\":11105,\"Ġinbox\":11106,\"football\":11107,\"hy\":11108,\"ĠCase\":11109,\"Ġentertaining\":11110,\"Ġhardest\":11111,\"ĠOpposition\":11112,\"Ġflip\":11113,\"ĠPirates\":11114,\"anu\":11115,\"ĠKlopp\":11116,\"Ġballistic\":11117,\"Ġprinted\":11118,\"ĠNFC\":11119,\"UST\":11120,\"Ġglasses\":11121,\"Ġrum\":11122,\"ĠDuncan\":11123,\"hal\":11124,\"Ġpreview\":11125,\"BER\":11126,\"dec\":11127,\"Ġsustainability\":11128,\"Ġaff\":11129,\"Ġhungry\":11130,\"service\":11131,\"avi\":11132,\"Ġsometime\":11133,\"Ġmod\":11134,\"ĠLib\":11135,\"oko\":11136,\"Ġfundraiser\":11137,\"Ġcrowded\":11138,\"mates\":11139,\"Ġcreativity\":11140,\"ĠHell\":11141,\"Ġtreaty\":11142,\"ĠSoftware\":11143,\"ĠRandy\":11144,\"ĠPolish\":11145,\"sa\":11146,\"ardi\":11147,\"Ġcab\":11148,\"ĠCamera\":11149,\"Ġlicenses\":11150,\"Ġ1988\":11151,\"Ġcontinuous\":11152,\"Ġpaired\":11153,\"Ġtally\":11154,\"Ġgrip\":11155,\"cho\":11156,\"Ġsurged\":11157,\"Ġpodium\":11158,\"Ġcontrary\":11159,\"SL\":11160,\"ĠResearchers\":11161,\"cing\":11162,\"Ġmi\":11163,\"Ġdisputed\":11164,\"Ġgrades\":11165,\"Ġseverely\":11166,\"ĠMcL\":11167,\"ondo\":11168,\"Ġshelters\":11169,\"Ġdomain\":11170,\"ĠSwitch\":11171,\"Ġtestify\":11172,\"case\":11173,\"omet\":11174,\"atch\":11175,\"ĠAff\":11176,\"Ġcasting\":11177,\"berger\":11178,\"Ġintimate\":11179,\"erc\":11180,\"plan\":11181,\"ĠPast\":11182,\"ĠUt\":11183,\"Ġapologized\":11184,\"ĠDet\":11185,\"alle\":11186,\"Ġwhilst\":11187,\"Ġpel\":11188,\"Ġexecute\":11189,\"Ġharmful\":11190,\"ĠRB\":11191,\"onda\":11192,\"ĠFul\":11193,\"II\":11194,\"Those\":11195,\"Ġcryptocurrency\":11196,\"Ġrealise\":11197,\"ĠAthens\":11198,\"ĠApplication\":11199,\"ORD\":11200,\"Ġmidst\":11201,\"ĠSem\":11202,\"Ġmessaging\":11203,\"Ġcousin\":11204,\"ĠMarsh\":11205,\"ĠAlmost\":11206,\"uto\":11207,\"wire\":11208,\"ĠManaging\":11209,\"Ġsends\":11210,\"ĠDerby\":11211,\"Ġpad\":11212,\"Ġdevoted\":11213,\"ĠWorking\":11214,\"ĠWestminster\":11215,\"Ġdirty\":11216,\"ements\":11217,\"ĠLew\":11218,\"door\":11219,\"Ġadvisor\":11220,\"ival\":11221,\"Ġsubscribe\":11222,\"Ġcredited\":11223,\"Ġpressed\":11224,\"Ġbrick\":11225,\"Ġrehabilitation\":11226,\"Ġ\\\"[\":11227,\"erry\":11228,\"Ġtransformed\":11229,\"arp\":11230,\"Ġreceivers\":11231,\"ĠFan\":11232,\"ĠKris\":11233,\"ĠCharlottesville\":11234,\"Ġste\":11235,\"Ġconstructed\":11236,\"Ġbroadly\":11237,\"ĠBetter\":11238,\"ĠJanet\":11239,\"Ġenthusiasm\":11240,\"ĠIrving\":11241,\"ĠConst\":11242,\"Everyone\":11243,\"agn\":11244,\"ĠCrawford\":11245,\"Ġregards\":11246,\"ĠBurns\":11247,\"Ġjokes\":11248,\"erg\":11249,\"ARD\":11250,\"apped\":11251,\"Ġtravelled\":11252,\"ĠPoor\":11253,\"ĠHolly\":11254,\"Ġcontainer\":11255,\"Ġinfected\":11256,\"Ġlean\":11257,\"ĠWould\":11258,\"Ġmagnitude\":11259,\"ĠDou\":11260,\"minded\":11261,\"Ġpastor\":11262,\"Ġwherever\":11263,\"ulation\":11264,\"Ġ1986\":11265,\"ĠMegan\":11266,\"Ġgraphic\":11267,\"Ġtalents\":11268,\"Ġkn\":11269,\"ĠEC\":11270,\"ĠMcM\":11271,\"ĠKon\":11272,\"eni\":11273,\"ĠEsc\":11274,\"inas\":11275,\"ĠNom\":11276,\"Ġchasing\":11277,\"arl\":11278,\"ĠHungary\":11279,\"Ġmainland\":11280,\"ĠDist\":11281,\"utes\":11282,\"Ġrubber\":11283,\"iat\":11284,\"ĠMorrison\":11285,\"ushing\":11286,\"iny\":11287,\"Ġcopies\":11288,\"ĠFat\":11289,\"agged\":11290,\"Ġfloating\":11291,\"ĠCurtis\":11292,\"Ġfatally\":11293,\"ĠManuel\":11294,\"Ġgraduates\":11295,\"nar\":11296,\"ĠKenny\":11297,\"Ġretreat\":11298,\"Ġretro\":11299,\"ĠPierre\":11300,\"listed\":11301,\"ĠDale\":11302,\"ding\":11303,\"Ġintentions\":11304,\"Ġsentences\":11305,\"ĠSere\":11306,\"Ġinvasion\":11307,\"Ġpremiums\":11308,\"ĠGardner\":11309,\"Ġshipments\":11310,\"Ġcol\":11311,\"bell\":11312,\"ilo\":11313,\"Ġworthy\":11314,\"Ġinterceptions\":11315,\"Ġcomplain\":11316,\"icle\":11317,\"ĠTah\":11318,\"ĠMt\":11319,\"ĠSyracuse\":11320,\"Since\":11321,\"aches\":11322,\"ĠCand\":11323,\"Ġinteractions\":11324,\"ĠShawn\":11325,\"nc\":11326,\"Ġtheaters\":11327,\"ART\":11328,\"Th\":11329,\"Ġalter\":11330,\"aley\":11331,\"imo\":11332,\"Ġresponders\":11333,\"kan\":11334,\"ĠDarren\":11335,\"Ġdeliveries\":11336,\"PI\":11337,\"125\":11338,\"Ġlaughing\":11339,\"ĠPatterson\":11340,\"Ġinfections\":11341,\"Ġtur\":11342,\"130\":11343,\"Ġhackers\":11344,\"Ġwarn\":11345,\"Ġfreeze\":11346,\"Ġscreaming\":11347,\"ĠEcho\":11348,\"ĠDom\":11349,\"MAN\":11350,\"ĠJoy\":11351,\"Ġbeneath\":11352,\"ĠHalf\":11353,\"Ġpatent\":11354,\"Ġugly\":11355,\"Ġlip\":11356,\"Ġnominees\":11357,\"ĠGrade\":11358,\"Ġinfluenced\":11359,\"Ġabilities\":11360,\"Ġlimiting\":11361,\"Ġsmell\":11362,\"Ġesc\":11363,\"ĠBernard\":11364,\"cs\":11365,\"ĠMyers\":11366,\"oted\":11367,\"Black\":11368,\"Ġlim\":11369,\"Ġsworn\":11370,\"ĠBlair\":11371,\"anes\":11372,\"ĠEvent\":11373,\"Ġmature\":11374,\"Ġpositioned\":11375,\"Ġerupted\":11376,\"grand\":11377,\"ĠTell\":11378,\"Ġbackdrop\":11379,\"Ġyeah\":11380,\"ĠClear\":11381,\"Ġsignificance\":11382,\"Ġpatience\":11383,\"ĠWing\":11384,\"Ġhorrible\":11385,\"Ġdeploy\":11386,\"ipe\":11387,\"Ġbitcoin\":11388,\"Ġcommitting\":11389,\"Ġdismiss\":11390,\"ĠBlood\":11391,\"ĠMeyer\":11392,\"selling\":11393,\"Ġregarded\":11394,\"Ġlottery\":11395,\"ĠLuther\":11396,\"Ġpipe\":11397,\"Ġcro\":11398,\"ĠANC\":11399,\"ĠSolar\":11400,\"Ġsimilarly\":11401,\"Ġham\":11402,\"ĠHonor\":11403,\"tar\":11404,\"gin\":11405,\"ĠArmstrong\":11406,\"Ġbrowser\":11407,\"agon\":11408,\"via\":11409,\"Ġentries\":11410,\"Ġinfl\":11411,\"Ġgraduation\":11412,\"Ġalleges\":11413,\"ĠLoading\":11414,\"Ġsuperb\":11415,\"ially\":11416,\"Ġadministrator\":11417,\"uls\":11418,\"Ġartistic\":11419,\"ĠANGEL\":11420,\"ĠBang\":11421,\"Ġfossil\":11422,\"¨\":11423,\"Ġpoly\":11424,\"ĠGuardiola\":11425,\"ĠPerth\":11426,\"Ġeducate\":11427,\"Cl\":11428,\"Ġcommittees\":11429,\"Ġforthcoming\":11430,\"Ġadjustments\":11431,\"count\":11432,\"Ġincoming\":11433,\"brook\":11434,\"ĠMinneapolis\":11435,\"Ġgown\":11436,\"ĠCroatia\":11437,\"host\":11438,\"Ġcompetitor\":11439,\"Ġlyrics\":11440,\"Ġbelonging\":11441,\"ĠFrances\":11442,\"ĠHaley\":11443,\"ĠBruins\":11444,\"Ġmask\":11445,\"ĠPv\":11446,\"dollar\":11447,\"Ġbowling\":11448,\"Ġjewelry\":11449,\"ĠJulia\":11450,\"Ġbroadband\":11451,\"ĠBhar\":11452,\"ĠArmed\":11453,\"vy\":11454,\"government\":11455,\"kov\":11456,\"Ġpremises\":11457,\"Ġjersey\":11458,\"Ġapplies\":11459,\"ĠFreeman\":11460,\"Ġgrows\":11461,\"ĠEquity\":11462,\"Ġmaterially\":11463,\"Ġfigured\":11464,\"ience\":11465,\"Ġmajors\":11466,\"ĠYe\":11467,\"ĠHey\":11468,\"oned\":11469,\"aping\":11470,\"Ġtoilet\":11471,\"ĠConnor\":11472,\"Ġavoiding\":11473,\"pos\":11474,\"Once\":11475,\"ĠRockets\":11476,\"ĠSnapchat\":11477,\"Go\":11478,\"Ġsolidarity\":11479,\"ĠAffordable\":11480,\"Ġdial\":11481,\"ĠOmar\":11482,\"xt\":11483,\"ĠVatican\":11484,\"anta\":11485,\"ĠSuperior\":11486,\"Ġbeaches\":11487,\"ĠKi\":11488,\"Ã¥\":11489,\"KY\":11490,\"Ġgro\":11491,\"ĠEmpire\":11492,\"Ġoccurs\":11493,\"Ġjoked\":11494,\"Ġquotes\":11495,\"ĠSaskatchewan\":11496,\"pert\":11497,\"Ġmaintains\":11498,\"olt\":11499,\"Ġupgrades\":11500,\"ĠCho\":11501,\"ĠAlexis\":11502,\"ĠHundreds\":11503,\"ĠBud\":11504,\"Ġcenturies\":11505,\"ĠInvestor\":11506,\"ĠGomez\":11507,\"Ġconceded\":11508,\"Ġexpressing\":11509,\"ĠIBM\":11510,\"Ġadvancing\":11511,\"ĠDollar\":11512,\"jer\":11513,\"Ġexceed\":11514,\"author\":11515,\"rist\":11516,\"seat\":11517,\"ĠPrimary\":11518,\"ĠForbes\":11519,\"ĠAlzheimer\":11520,\"Ġdevastated\":11521,\"Ġawful\":11522,\"ĠStudio\":11523,\"Ġbullpen\":11524,\"Ġmobility\":11525,\"Ġanalyze\":11526,\"lie\":11527,\"AFP\":11528,\"iche\":11529,\"ĠRoyals\":11530,\"Ġcoupled\":11531,\"Ġdug\":11532,\"ĠRing\":11533,\"Ġenvironments\":11534,\"national\":11535,\"ĠCongo\":11536,\"Ġalleging\":11537,\"wn\":11538,\"ulating\":11539,\"Ġur\":11540,\"Ġreaches\":11541,\"ĠPine\":11542,\"Ġthreshold\":11543,\"Ġtournaments\":11544,\"Ġheating\":11545,\"ĠGard\":11546,\"ĠHamas\":11547,\"ĠÂ«\":11548,\"ĠHolding\":11549,\"Ġpossibilities\":11550,\"ĠHassan\":11551,\"ĠMohammad\":11552,\"Ġoffenders\":11553,\"Ġautomated\":11554,\"Ġrealised\":11555,\"ouse\":11556,\"building\":11557,\"ĠDub\":11558,\"ĠGeneva\":11559,\"Ġfacial\":11560,\"ĠRestaurant\":11561,\"ĠNg\":11562,\"Ġtot\":11563,\"Ġgrace\":11564,\"ĠCP\":11565,\"Ġposter\":11566,\"hart\":11567,\"ĠNi\":11568,\"Ġreaff\":11569,\"Ġprov\":11570,\"Ġ111\":11571,\"ĠAid\":11572,\"Ġscrap\":11573,\"izers\":11574,\"ogen\":11575,\"Ġtissue\":11576,\"Ġvibrant\":11577,\"Ġrider\":11578,\"CD\":11579,\"ĠKitchen\":11580,\"Ġgenre\":11581,\"¬\":11582,\"depth\":11583,\"kind\":11584,\"Ġendorsed\":11585,\"Ġsimultaneously\":11586,\"Ġintern\":11587,\"ĠDrag\":11588,\"Ġembraced\":11589,\"Ġcounted\":11590,\"uj\":11591,\"ĠOg\":11592,\"Ġphysician\":11593,\"ĠIR\":11594,\"IST\":11595,\"ĠKir\":11596,\"Ġhacking\":11597,\"ĠSources\":11598,\"astic\":11599,\"growing\":11600,\"ĠWake\":11601,\"Ġhint\":11602,\"Ġcompiled\":11603,\"Ġreign\":11604,\"Ġcinema\":11605,\"Ġboosting\":11606,\"Ġaccommodation\":11607,\"ĠEuropa\":11608,\"Ġsubsidiaries\":11609,\"Ġclosures\":11610,\"ĠBil\":11611,\"ĠBou\":11612,\"wh\":11613,\"ĠAw\":11614,\"FT\":11615,\"hole\":11616,\"ĠNova\":11617,\"ĠNSW\":11618,\"Ġrap\":11619,\"Ġencourages\":11620,\"GR\":11621,\"ds\":11622,\"ĠMuk\":11623,\"ĠSurvey\":11624,\"ĠReagan\":11625,\"oning\":11626,\"Ġneighbouring\":11627,\"ĠMcCl\":11628,\"acht\":11629,\"Ġfinishes\":11630,\"ĠEsp\":11631,\"pat\":11632,\"Ġdestinations\":11633,\"ĠWagner\":11634,\"Ġconfronted\":11635,\"square\":11636,\"Ġpie\":11637,\"brand\":11638,\"hl\":11639,\"Ġabsent\":11640,\"Ġsurf\":11641,\"Ġrifle\":11642,\"ĠSS\":11643,\"ĠDeath\":11644,\"wich\":11645,\"Ġbeds\":11646,\"ĠLock\":11647,\"ĠAgu\":11648,\"atives\":11649,\"jee\":11650,\"Ġoral\":11651,\"Ġbudgets\":11652,\"Ġinspiring\":11653,\"IONS\":11654,\"works\":11655,\"Ġspirits\":11656,\"Ġcabin\":11657,\"Ġsatisfaction\":11658,\"Ġvoluntary\":11659,\"ĠMunicipal\":11660,\"Ġdeportation\":11661,\"ĠWriter\":11662,\"ĠVI\":11663,\"VERTISEMENT\":11664,\"/.\":11665,\"ĠSouthampton\":11666,\"aces\":11667,\"ĠHelen\":11668,\"ĠHum\":11669,\"110\":11670,\"Ġgarbage\":11671,\"through\":11672,\"Ġkingdom\":11673,\"MT\":11674,\"augh\":11675,\"Ġbizarre\":11676,\"ĠStarting\":11677,\"Ġwooden\":11678,\"ĠProgress\":11679,\"iron\":11680,\"sten\":11681,\"ĠSergio\":11682,\"ĠHR\":11683,\"Ġturnout\":11684,\"ĠAmericas\":11685,\"ĠSara\":11686,\"Ġagrees\":11687,\"apper\":11688,\"Ġbra\":11689,\"Ġrecycling\":11690,\"oom\":11691,\"Ġflee\":11692,\"Ġdistinct\":11693,\"IAL\":11694,\"aha\":11695,\"Ġfever\":11696,\"ĠPartnership\":11697,\"ĠYu\":11698,\"ĠPixel\":11699,\"ĠBlock\":11700,\"ĠMelissa\":11701,\"igg\":11702,\"Ġdecides\":11703,\"ĠNorman\":11704,\"Ġmas\":11705,\"held\":11706,\"ĠPD\":11707,\"Ġsheer\":11708,\"ĠDim\":11709,\"ĠCass\":11710,\"Ġcolumnist\":11711,\"ĠBros\":11712,\"Ġturnaround\":11713,\"ĠValue\":11714,\"ĠBachelor\":11715,\"awn\":11716,\"Ġassignment\":11717,\"ested\":11718,\"ĠJudiciary\":11719,\"Ġdiamond\":11720,\"Ġmus\":11721,\"Ġindigenous\":11722,\"lines\":11723,\"Ġ1984\":11724,\"igroup\":11725,\"ict\":11726,\"ĠJaguars\":11727,\"Ġlun\":11728,\"Ġprofiles\":11729,\"Ġcomputing\":11730,\"ĠBelgian\":11731,\"ĠLloyd\":11732,\"ĠGoing\":11733,\"Ġdisp\":11734,\"Ġ1987\":11735,\"eder\":11736,\"ĠVin\":11737,\"Ġgovern\":11738,\"Ġblend\":11739,\"ĠSebastian\":11740,\"ĠMidwest\":11741,\"iga\":11742,\"Ġspl\":11743,\"Ġtopping\":11744,\"Ġnetworking\":11745,\"ĠEmer\":11746,\"Ġoxygen\":11747,\"ĠInterest\":11748,\"ĠMoy\":11749,\"Ġtrader\":11750,\"Ġbay\":11751,\"Ġsticking\":11752,\"ĠMovement\":11753,\"Ġbidding\":11754,\"tax\":11755,\"Ġacademy\":11756,\"ĠMO\":11757,\"ĠSpirit\":11758,\"Ġhealing\":11759,\"wen\":11760,\"ĠPrix\":11761,\"cal\":11762,\"ĠOperating\":11763,\"Ġinstantly\":11764,\"ĠTonight\":11765,\"Ġsacked\":11766,\"Ġautomation\":11767,\"umps\":11768,\"ĠNey\":11769,\"March\":11770,\"ĠBuck\":11771,\"Ġconcentration\":11772,\"Here\":11773,\"Ġtravelers\":11774,\"Ġprotective\":11775,\"ĠMoody\":11776,\"Ġentrepreneur\":11777,\"Ġfac\":11778,\"kowski\":11779,\"Ġpreparations\":11780,\"Ġdominate\":11781,\"Ġspray\":11782,\"Ġdisturbing\":11783,\"ĠFraser\":11784,\"ĠCody\":11785,\"ashi\":11786,\"ĠPel\":11787,\"Ġrisky\":11788,\"Ġawkward\":11789,\"ĠVA\":11790,\"ails\":11791,\"Ġangle\":11792,\"Ġundergoing\":11793,\"Ġalbums\":11794,\"Ġafterwards\":11795,\"ĠNaw\":11796,\"uge\":11797,\"enter\":11798,\"ĠSussex\":11799,\"ĠRecently\":11800,\"Ġlikelihood\":11801,\"large\":11802,\"Ġsnaps\":11803,\"ibr\":11804,\"ĠMalcolm\":11805,\"Ġcru\":11806,\"Ġaltogether\":11807,\"Ġsetup\":11808,\"Ġtorture\":11809,\"Ġfiber\":11810,\"Ġquarterbacks\":11811,\"ĠGetting\":11812,\"ipping\":11813,\"ĠNorwegian\":11814,\"ĠMiles\":11815,\"ĠArnold\":11816,\"ĠDisease\":11817,\"Ġtends\":11818,\"ife\":11819,\"ĠCaroline\":11820,\"Ġnavigate\":11821,\"Ġbrush\":11822,\"ĠAssociates\":11823,\"Ġbath\":11824,\"ĠCenters\":11825,\"ĠMC\":11826,\"Ġtaxpayer\":11827,\"comp\":11828,\"Ġaccomplish\":11829,\"ĠTraffic\":11830,\"ĠBru\":11831,\"Ġgreenhouse\":11832,\"ĠMalaysian\":11833,\"ĠPur\":11834,\"ased\":11835,\"ĠKnicks\":11836,\"aters\":11837,\"Ġalt\":11838,\"ICK\":11839,\"Ġcalculations\":11840,\"Ġmindset\":11841,\"unch\":11842,\"Ġgu\":11843,\"Ġsteadily\":11844,\"Ġfiction\":11845,\"ĠPap\":11846,\"forming\":11847,\"ĠActor\":11848,\"ĠBerry\":11849,\"imp\":11850,\"ĠUpper\":11851,\"Ġassessed\":11852,\"Ġlawn\":11853,\"ĠRoh\":11854,\"Ġclearance\":11855,\"funded\":11856,\"Ġpret\":11857,\"ĠHom\":11858,\"VS\":11859,\"ĠTourism\":11860,\"ĠRy\":11861,\"ĠGonz\":11862,\"ĠStudios\":11863,\"Ġanchor\":11864,\"Ġrecognise\":11865,\"Ġcooperate\":11866,\"enny\":11867,\"aza\":11868,\"ĠMeet\":11869,\"Ġeventual\":11870,\"SW\":11871,\"ĠCounsel\":11872,\"ĠSave\":11873,\"Ġlucrative\":11874,\"Ġslim\":11875,\"ĠGreens\":11876,\"Ġchemistry\":11877,\"ĠSheikh\":11878,\"Ġbridges\":11879,\"business\":11880,\"ĠSaf\":11881,\"ĠGy\":11882,\"Ġprotocol\":11883,\"Ġnephew\":11884,\"ĠBrands\":11885,\"ĠCulture\":11886,\"orship\":11887,\"Ġ(Â£\":11888,\"ĠDell\":11889,\"astics\":11890,\"Ġproving\":11891,\"ĠMann\":11892,\"aca\":11893,\"Ġindoor\":11894,\"ĠUganda\":11895,\"ĠRomney\":11896,\"ĠStage\":11897,\"Ġward\":11898,\"ĠAmber\":11899,\"haw\":11900,\"Ġtw\":11901,\"Ġbullying\":11902,\"ĠCAR\":11903,\"Ġassociates\":11904,\"ĠHopkins\":11905,\"Ġsuburb\":11906,\"Ġaggressively\":11907,\"Ġpostponed\":11908,\"Ġbas\":11909,\"Ġburglary\":11910,\"ĠFound\":11911,\"Ġfloors\":11912,\"Any\":11913,\"Ġjam\":11914,\"Ġvisibility\":11915,\"Ġbenefited\":11916,\"ĠAud\":11917,\"aying\":11918,\"iku\":11919,\"ĠPas\":11920,\"ĠGPS\":11921,\"ĠOwens\":11922,\"Ġreluctant\":11923,\"ĠOlivia\":11924,\"ols\":11925,\"Ġemotion\":11926,\"ĠHeavy\":11927,\"Ġhostile\":11928,\"Ġfavorites\":11929,\"Ġfeat\":11930,\"ĠCord\":11931,\"ĠGO\":11932,\"Ġindicted\":11933,\"idal\":11934,\"ĠIL\":11935,\"Ħ\":11936,\"acer\":11937,\"ICH\":11938,\"oda\":11939,\"Ġrecipients\":11940,\"Ġtribal\":11941,\"Ġresist\":11942,\"ĠCritics\":11943,\"Ġsang\":11944,\"ĠMath\":11945,\"ĠBrighton\":11946,\"ĠKw\":11947,\"Ġlimitations\":11948,\"Ġinterception\":11949,\"onde\":11950,\"ĠRobertson\":11951,\"Ġenjoys\":11952,\"site\":11953,\"Ġwings\":11954,\"ĠCeltic\":11955,\"Ġrelaxed\":11956,\"Share\":11957,\"Ġwarrants\":11958,\"oco\":11959,\"Ġcritically\":11960,\"GC\":11961,\"Ġcute\":11962,\"Ġlaying\":11963,\"itude\":11964,\"ĠMediterranean\":11965,\"Ġwatches\":11966,\"Ġdisagree\":11967,\"ĠReturn\":11968,\"ARC\":11969,\"people\":11970,\"Ġtwelve\":11971,\"Ġoverdose\":11972,\"ĠLot\":11973,\"ĠFROM\":11974,\"ĠPeters\":11975,\"Ġadministrators\":11976,\"Ġslam\":11977,\"jar\":11978,\"OH\":11979,\"ĠInitiative\":11980,\"Ġteamed\":11981,\"ĠMajority\":11982,\"June\":11983,\"ĠPlaza\":11984,\"lake\":11985,\"Ġglimpse\":11986,\"Ġrings\":11987,\"Ġos\":11988,\"Ġmentor\":11989,\"have\":11990,\"Ġlanguages\":11991,\"Ġuncle\":11992,\"agu\":11993,\"ĠWine\":11994,\"ĠCategory\":11995,\"ĠIng\":11996,\"Ġcontests\":11997,\"ĠRosen\":11998,\"ĠWhatever\":11999,\"Ġdenying\":12000,\"ean\":12001,\"Ġspec\":12002,\"Ġgrad\":12003,\"Ġtenants\":12004,\"show\":12005,\"ĠGregory\":12006,\"Ġcontention\":12007,\"Ġunanimously\":12008,\"ĠPin\":12009,\"fa\":12010,\"ĠPink\":12011,\"Ġswitched\":12012,\"acre\":12013,\"ĠTrading\":12014,\"VP\":12015,\"ĠMaple\":12016,\"Neill\":12017,\"Ġdiscounts\":12018,\"alls\":12019,\"Ġsounded\":12020,\"Ġrumours\":12021,\"ĠCre\":12022,\"hall\":12023,\"ĠTele\":12024,\"Ġthankful\":12025,\"Ġsurveyed\":12026,\"UB\":12027,\"Ġdignity\":12028,\"Ġnod\":12029,\"Ġmisleading\":12030,\"ĠTX\":12031,\"ĠBurke\":12032,\"Ġmounting\":12033,\"Ġskies\":12034,\"Ġbesides\":12035,\"ĠGarrett\":12036,\"tha\":12037,\"Ġintelligent\":12038,\"Ġtanks\":12039,\"apping\":12040,\"ĠRat\":12041,\"aint\":12042,\"Ġentertain\":12043,\"ĠAbdullah\":12044,\"Ġsink\":12045,\"ĠLan\":12046,\"ĠManufacturing\":12047,\"NFL\":12048,\"Ġthemes\":12049,\"ĠHaven\":12050,\"ĠDavies\":12051,\"ĠKerr\":12052,\"ĠLen\":12053,\"Ġcourtroom\":12054,\"Ġfailures\":12055,\"Ġlately\":12056,\"ĠElectronics\":12057,\"Ġgorgeous\":12058,\"Ġnotification\":12059,\"Ġ2030\":12060,\"aved\":12061,\"Ġdeer\":12062,\"economic\":12063,\"ĠStatistics\":12064,\"Ġconfrontation\":12065,\"Ġgovernors\":12066,\"ĠHaram\":12067,\"ĠLGBTQ\":12068,\"Ġprocessed\":12069,\"ĠDuchess\":12070,\"Ġdowns\":12071,\"Ġpork\":12072,\"Ġhumor\":12073,\"ocese\":12074,\"Ġneeding\":12075,\"Ġmidterm\":12076,\"ĠOval\":12077,\"Ġcorners\":12078,\"Ġtablets\":12079,\"eds\":12080,\"vere\":12081,\"Ġattacker\":12082,\"Paul\":12083,\"pee\":12084,\"ĠAlice\":12085,\"Ġrenowned\":12086,\"Ġ09\":12087,\"ocking\":12088,\"Ġcreditors\":12089,\"ĠPedro\":12090,\"ĠPhone\":12091,\"Ġsurveys\":12092,\"ĠWelsh\":12093,\"Ġcow\":12094,\"Ġbuilds\":12095,\"Ġ000\":12096,\"ĠAzerbaijan\":12097,\"ĠYad\":12098,\"Ġinfant\":12099,\"Ġmotorists\":12100,\"Ġpoorly\":12101,\"Ġmedications\":12102,\"Ġstupid\":12103,\"ĠCastro\":12104,\"user\":12105,\"antly\":12106,\"alty\":12107,\"ĠCond\":12108,\"issa\":12109,\"ĠIvan\":12110,\"Ġcostume\":12111,\"Ġ08\":12112,\"Ġhence\":12113,\"Ġdangers\":12114,\"Ġbullish\":12115,\"Life\":12116,\"Ġflavor\":12117,\"ĠCharleston\":12118,\"Ġbikes\":12119,\"Ġworkshops\":12120,\"Ġarranged\":12121,\"Ġcontender\":12122,\"Ġsequel\":12123,\"ĠPlant\":12124,\"Ġdonor\":12125,\"Ġfactories\":12126,\"rict\":12127,\"ellen\":12128,\"Ġrobots\":12129,\"ĠWor\":12130,\"ĠDirectors\":12131,\"ĠPeru\":12132,\"Ġqueen\":12133,\"ĠTimothy\":12134,\"ĠToo\":12135,\"Ġobservers\":12136,\"Ġears\":12137,\"Ġbel\":12138,\"link\":12139,\"uns\":12140,\"Ġhomers\":12141,\"Ġadjacent\":12142,\"Ġconfidential\":12143,\"Ġstunned\":12144,\"iden\":12145,\"illed\":12146,\"ESS\":12147,\"Ġconvenient\":12148,\"ĠLindsey\":12149,\"por\":12150,\"upp\":12151,\"Ġborrow\":12152,\"ĠAhmad\":12153,\"ORT\":12154,\"Ġrelate\":12155,\"ĠSelf\":12156,\"ĠVanguard\":12157,\"utter\":12158,\"ĠBranch\":12159,\"ĠBolton\":12160,\"bat\":12161,\"Ġoutright\":12162,\"fighters\":12163,\"ĠBed\":12164,\"Ġpes\":12165,\"inski\":12166,\"Ġgunshot\":12167,\"Ġprinting\":12168,\"ĠSent\":12169,\"vern\":12170,\"Ġharvest\":12171,\"Ġbubble\":12172,\"Ġrefund\":12173,\"Ġfuels\":12174,\"Ġdive\":12175,\"Ġdiplomat\":12176,\"Ġpile\":12177,\"ĠVery\":12178,\"rot\":12179,\"ĠSearch\":12180,\"ĠJoyce\":12181,\"ĠPruitt\":12182,\"ĠLevel\":12183,\"ĠBP\":12184,\"ĠLac\":12185,\"had\":12186,\"Ġexpenditure\":12187,\"ĠMadd\":12188,\"Ġpockets\":12189,\"ĠClippers\":12190,\"ĠDear\":12191,\"ĠGive\":12192,\"Ġhal\":12193,\"Ġvertical\":12194,\"Ġwholesale\":12195,\"what\":12196,\"ĠSpringfield\":12197,\"ayed\":12198,\"ĠSom\":12199,\"Ġsecrets\":12200,\"Ġcharts\":12201,\"iar\":12202,\"ibility\":12203,\"LAND\":12204,\"Ġbearing\":12205,\"Ġprom\":12206,\"Ġtab\":12207,\"Ġsheets\":12208,\"ĠGL\":12209,\"Ġendless\":12210,\"opening\":12211,\"ĠOwen\":12212,\"Ġunderneath\":12213,\"ĠErik\":12214,\"ĠDACA\":12215,\"Ġsteering\":12216,\"Ġfootprint\":12217,\"ĠRoma\":12218,\"ĠDucks\":12219,\"ĠEllen\":12220,\"ĠProfessional\":12221,\"ĠGardens\":12222,\"Ġgoalie\":12223,\"Ġshine\":12224,\"Ġturmoil\":12225,\"Ġhunger\":12226,\"ĠâĢĭ\":12227,\"active\":12228,\"hey\":12229,\"Ġblessed\":12230,\"ason\":12231,\"oping\":12232,\"ĠThousands\":12233,\"Ġdose\":12234,\"ĠLor\":12235,\"Ġevolved\":12236,\"Ġcharities\":12237,\"ĠPE\":12238,\"ĠRub\":12239,\"ws\":12240,\"Ġmist\":12241,\"ĠShen\":12242,\"Ġbiological\":12243,\"ĠTweet\":12244,\"Ġcollections\":12245,\"Ġsubstantially\":12246,\"inner\":12247,\"Ġbattled\":12248,\"ĠCong\":12249,\"Hold\":12250,\"wp\":12251,\"Ġwells\":12252,\"Ġsake\":12253,\"Ġunrest\":12254,\"ĠKurt\":12255,\"Ġripped\":12256,\"itation\":12257,\"Ġneighbourhood\":12258,\"Ġinv\":12259,\"Ġcad\":12260,\"ĠCuban\":12261,\"ĠWealth\":12262,\"Ġtuition\":12263,\"Ġdeclaring\":12264,\"sch\":12265,\"orne\":12266,\"Ġwondered\":12267,\"ĠChaff\":12268,\"Ġdealer\":12269,\"ĠNumber\":12270,\"Mobile\":12271,\"Ġscratch\":12272,\"Ġprepares\":12273,\"ĠSens\":12274,\"ĠIstanbul\":12275,\"ĠPanama\":12276,\"ĠCay\":12277,\"Ġallocation\":12278,\"itutional\":12279,\"Ġhar\":12280,\"ĠNazi\":12281,\"ĠSund\":12282,\"Ġwarehouse\":12283,\"Ġbackyard\":12284,\"ĠIll\":12285,\"Ġunlawful\":12286,\"ĠReform\":12287,\"Ġbasement\":12288,\"ĠHi\":12289,\"ĠPictures\":12290,\"Ġtransfers\":12291,\"ĠSell\":12292,\"Ġfluid\":12293,\"Ġambitions\":12294,\"wife\":12295,\"Ġintensive\":12296,\"Ġsteals\":12297,\"Ġfestive\":12298,\"ĠHayes\":12299,\"Ġrestoration\":12300,\"Ġbranded\":12301,\"Journal\":12302,\"Ġmacro\":12303,\"Ġconsole\":12304,\"ĠMelania\":12305,\"ĠRahul\":12306,\"Ġdisposal\":12307,\"Ġcult\":12308,\"Ġpetrol\":12309,\"Ġtires\":12310,\"Ġkidnapping\":12311,\"Ġ115\":12312,\"Ġswap\":12313,\"ĠSud\":12314,\"Ġblown\":12315,\"ĠHindu\":12316,\"ĠBeckham\":12317,\"ĠGul\":12318,\"Ġfixture\":12319,\"Ġwisdom\":12320,\"Ġmines\":12321,\"fort\":12322,\"Ġrivers\":12323,\"ĠCyber\":12324,\"Ġtouches\":12325,\"race\":12326,\"Ġrelax\":12327,\"Ġcrashes\":12328,\"Ġconstituency\":12329,\"Ġ1979\":12330,\"Ġbureau\":12331,\"Ġinterface\":12332,\"Ġdetected\":12333,\"ĠBio\":12334,\"Ġhighlighting\":12335,\"ames\":12336,\"Ġcorresponding\":12337,\"great\":12338,\"Ġgray\":12339,\"Ġadvantages\":12340,\"ĠME\":12341,\"ĠAbbas\":12342,\"Ġnaked\":12343,\"rington\":12344,\".),\":12345,\"ĠFace\":12346,\"third\":12347,\"Ġtranscript\":12348,\"ples\":12349,\"Good\":12350,\"ĠArctic\":12351,\"Ġtolerance\":12352,\"reat\":12353,\"green\":12354,\"ĠMik\":12355,\"Ġoutreach\":12356,\"Ġrolls\":12357,\"Ġgen\":12358,\"Ġsupplied\":12359,\"Ġguarantees\":12360,\"aug\":12361,\"Ġsemif\":12362,\"ounds\":12363,\"running\":12364,\"Ġfitting\":12365,\"ĠRisk\":12366,\"iveness\":12367,\"family\":12368,\"Ġti\":12369,\"ĠIsaac\":12370,\"Ġdump\":12371,\"ĠPatricia\":12372,\"Ġpassport\":12373,\"ĠRhode\":12374,\"Who\":12375,\"log\":12376,\"Ġstat\":12377,\"Ġrat\":12378,\"ango\":12379,\"SB\":12380,\"ĠMaur\":12381,\"Ġsmiling\":12382,\"Ġstrikeouts\":12383,\"Ġpupils\":12384,\"Ġcomplications\":12385,\"ĠAdvanced\":12386,\"ĠMonetary\":12387,\"ĠTall\":12388,\"ĠALL\":12389,\"Ġcontributor\":12390,\"ĠAdvertising\":12391,\"Ġhorrific\":12392,\"Ġcompeted\":12393,\"ĠKenneth\":12394,\"Ġhailed\":12395,\"Ġbones\":12396,\"Ġbolster\":12397,\"ĠBoss\":12398,\"Ġhospitalized\":12399,\"ĠTelegraph\":12400,\"ĠIndependence\":12401,\"Ġdr\":12402,\"ĠHang\":12403,\"Ġdocumented\":12404,\"Ġsubtle\":12405,\"invest\":12406,\"Ġbounced\":12407,\"ĠMAN\":12408,\"Ġprofession\":12409,\"Ń\":12410,\"Ġexcellence\":12411,\"ĠInspector\":12412,\"ĠBL\":12413,\"Ġdisrupt\":12414,\"ĠWinston\":12415,\"ĠCommunist\":12416,\"ĠSharon\":12417,\"Ġmechanical\":12418,\"Ġtreats\":12419,\"Ġdesperately\":12420,\"ĠIndy\":12421,\"ĠGi\":12422,\"ĠComposite\":12423,\"ĠHeath\":12424,\"aser\":12425,\"ĠCardiff\":12426,\"ilit\":12427,\"Ġeased\":12428,\"Ġprospective\":12429,\"Ġcommissioned\":12430,\"Ġtire\":12431,\"Ġalign\":12432,\"Ġgesture\":12433,\"Ġweakened\":12434,\"URE\":12435,\"SN\":12436,\"Ġnationals\":12437,\"Ġrelies\":12438,\"ĠIRS\":12439,\"ĠCount\":12440,\"Ġmedicines\":12441,\"Ġcongress\":12442,\"Ġstranger\":12443,\"Qu\":12444,\"lessly\":12445,\"ĠQueens\":12446,\"ĠAlleg\":12447,\"uing\":12448,\"ĠWy\":12449,\"ĠMiguel\":12450,\"idi\":12451,\"Ġcivic\":12452,\"ĠPetro\":12453,\"endo\":12454,\"Obviously\":12455,\"Ġreflection\":12456,\"ĠStop\":12457,\"ĠFitzgerald\":12458,\"placed\":12459,\"shore\":12460,\"Ġcorrectly\":12461,\"ĠNE\":12462,\"amy\":12463,\"ĠCT\":12464,\"some\":12465,\"ĠMb\":12466,\"oi\":12467,\"ĠHogan\":12468,\"ĠInnovation\":12469,\"ĠVilla\":12470,\"ĠCAN\":12471,\"ĠCemetery\":12472,\"into\":12473,\"Ġquestionable\":12474,\"Ġcreator\":12475,\"rug\":12476,\"Ġsemifinals\":12477,\"mission\":12478,\"Ġcle\":12479,\"ĠWaters\":12480,\"ĠNixon\":12481,\"ĠBT\":12482,\"Ġassuming\":12483,\"ĠJer\":12484,\"ĠClay\":12485,\"pack\":12486,\"ĠCool\":12487,\"may\":12488,\"Ġdecor\":12489,\"Ġspike\":12490,\"ĠSomalia\":12491,\"ĠKarn\":12492,\"ĠDamascus\":12493,\"Shares\":12494,\"Ġsus\":12495,\"ĠMoss\":12496,\"Ġ1985\":12497,\"Ġsuperintendent\":12498,\"ĠResults\":12499,\"Ġspends\":12500,\"prom\":12501,\"Ġshipped\":12502,\"Ġlaundering\":12503,\"ĠLeslie\":12504,\"Ġmeteor\":12505,\"Ġabandon\":12506,\"Ġdeliberately\":12507,\"ĠSentinel\":12508,\"Ġfascinating\":12509,\"Ġenrollment\":12510,\"ĠExperts\":12511,\"ĠSimilarly\":12512,\"ĠCuomo\":12513,\"bor\":12514,\"Ġune\":12515,\"neutral\":12516,\"Ġhamstring\":12517,\"Ġnegotiated\":12518,\"zes\":12519,\"ĠLeo\":12520,\"ĠDoctor\":12521,\"Ġcurriculum\":12522,\"ĠFocus\":12523,\"Ġtravels\":12524,\"Ġbeverage\":12525,\"ĠIncluding\":12526,\"tz\":12527,\"type\":12528,\"ĠRange\":12529,\"Ġfloods\":12530,\"Ġcoached\":12531,\"Ġdominance\":12532,\"letico\":12533,\"ĠRafael\":12534,\"Ġpredictions\":12535,\"Ġprosperity\":12536,\"ĠCav\":12537,\"Ġclinics\":12538,\"ĠBanking\":12539,\"ĠComing\":12540,\"ears\":12541,\"ĠKaepernick\":12542,\"ĠBlvd\":12543,\"Ġretained\":12544,\"isions\":12545,\"Ġko\":12546,\"Ġensemble\":12547,\"Ġprecise\":12548,\"Ġcompact\":12549,\"MD\":12550,\"ĠJet\":12551,\"ached\":12552,\"ĠTru\":12553,\"ĠBass\":12554,\"ĠIcon\":12555,\"Ġexcluding\":12556,\"sur\":12557,\"Ġconstruct\":12558,\"Ġvoiced\":12559,\"pan\":12560,\"Ġinability\":12561,\"Ġexc\":12562,\"Ġmate\":12563,\"Ġtrailing\":12564,\"Ġsuccessive\":12565,\"Ġbets\":12566,\"Ġgauge\":12567,\"Ġminorities\":12568,\"ĠIND\":12569,\"ĠVel\":12570,\"ĠGP\":12571,\"oid\":12572,\"bon\":12573,\"Ġpred\":12574,\"Ġdash\":12575,\"Ġperformer\":12576,\"Ġoccasional\":12577,\"aken\":12578,\"mes\":12579,\"America\":12580,\"Ġliver\":12581,\"Sp\":12582,\"Big\":12583,\"Ġwildfires\":12584,\"ĠJackie\":12585,\"ĠLed\":12586,\"ĠFinland\":12587,\"Ġjurors\":12588,\"olic\":12589,\"urance\":12590,\"ĠEdge\":12591,\"open\":12592,\"Ġscenarios\":12593,\"Ġglory\":12594,\"entry\":12595,\"ĠCoffee\":12596,\"rep\":12597,\"ĠChand\":12598,\"ĠVas\":12599,\"ĠIslamabad\":12600,\"Ġbur\":12601,\"ĠFle\":12602,\"ĠEdition\":12603,\"Ġshoe\":12604,\"ï¸ı\":12605,\"**\":12606,\"tle\":12607,\"ĠEb\":12608,\"keeping\":12609,\"ĠBasketball\":12610,\"ĠVon\":12611,\"ĠCF\":12612,\"MENT\":12613,\"amm\":12614,\"ĠFernando\":12615,\"Ġcompares\":12616,\"ĠDouble\":12617,\"Ġconvictions\":12618,\"Ġatop\":12619,\"Ġcops\":12620,\"Ġremembers\":12621,\"Ġlacking\":12622,\"dom\":12623,\"itate\":12624,\"ĠBeauty\":12625,\"Ġdevelops\":12626,\"ĠGor\":12627,\"Ġfunctional\":12628,\"ĠCOUNTY\":12629,\"ĠUpon\":12630,\"Ġsprint\":12631,\"Ġinjection\":12632,\"Ġminors\":12633,\"ĠTamil\":12634,\"ĠGat\":12635,\"101\":12636,\"ety\":12637,\"Ġdrum\":12638,\"Ġtasked\":12639,\"Ġpact\":12640,\"Ġ170\":12641,\"MR\":12642,\"ĠRamos\":12643,\"Ġcandy\":12644,\"Sc\":12645,\"iced\":12646,\"Ġsupermarket\":12647,\"Ġworrying\":12648,\"Ġsellers\":12649,\"ĠTag\":12650,\".:\":12651,\"Ġmixture\":12652,\"oting\":12653,\"Bl\":12654,\"ĠLl\":12655,\"ĠJal\":12656,\"ican\":12657,\"ĠBid\":12658,\"country\":12659,\"ĠStrategy\":12660,\"Ġadverse\":12661,\"Ġplunged\":12662,\"ĠMit\":12663,\"Ġstark\":12664,\"aton\":12665,\"Ġbooking\":12666,\"Tr\":12667,\"Ġcontainers\":12668,\"Ġvintage\":12669,\"ĠPit\":12670,\"Ġsurfaced\":12671,\"Ġindependently\":12672,\"Ġdetection\":12673,\"ĠBeyon\":12674,\"Ġcasualties\":12675,\"Ġstabbing\":12676,\"oved\":12677,\"Ġbarred\":12678,\"Ġthereby\":12679,\"Ġpartnered\":12680,\"Ġposing\":12681,\"ĠShannon\":12682,\"ĠChapel\":12683,\"Ġtechnically\":12684,\"uous\":12685,\"Â»\":12686,\"ometer\":12687,\"Ġwildfire\":12688,\"share\":12689,\"heart\":12690,\"Ġammunition\":12691,\"Ġthrive\":12692,\"ĠStre\":12693,\"GP\":12694,\"cÃ©\":12695,\"ĠMonaco\":12696,\"goal\":12697,\"ĠUm\":12698,\"ĠHSBC\":12699,\"ĠHilton\":12700,\"ĠViv\":12701,\"ĠKell\":12702,\"Ġdecisive\":12703,\"Ġmotive\":12704,\"amo\":12705,\"feld\":12706,\"ĠWH\":12707,\"iry\":12708,\"ulu\":12709,\"ĠSchneider\":12710,\"Ġcampaigning\":12711,\"Ġseparately\":12712,\"igo\":12713,\"ĠED\":12714,\"ĠRamirez\":12715,\"Ġmetro\":12716,\"ĠPatel\":12717,\"ĠChi\":12718,\"ĠAudi\":12719,\"Ġcharacteristics\":12720,\"Ġrestart\":12721,\"Ġkeyboard\":12722,\"ĠSD\":12723,\"his\":12724,\"biz\":12725,\"ĠSoft\":12726,\"ĠGrammy\":12727,\"Ġcontested\":12728,\"Ġweekends\":12729,\"Ġ112\":12730,\"Ġcycling\":12731,\"Ġhealthier\":12732,\"ija\":12733,\"Ġheader\":12734,\"Ġemploy\":12735,\"İ\":12736,\"Ġshortages\":12737,\"ĠAsk\":12738,\"ĠIvanka\":12739,\"Ġpartisan\":12740,\"Ġflowing\":12741,\"Ġcave\":12742,\"ENS\":12743,\"Ġups\":12744,\"read\":12745,\"ouch\":12746,\"Ġ102\":12747,\"Ġforming\":12748,\"bot\":12749,\"bie\":12750,\"Ġenrolled\":12751,\"Ġconcussion\":12752,\"Ġaffidavit\":12753,\"Ġmysterious\":12754,\"uries\":12755,\"ĠMang\":12756,\"Ġauthentic\":12757,\"Ġmetrics\":12758,\"ĠTwins\":12759,\"Ġprep\":12760,\"IJ\":12761,\"Ġdesired\":12762,\"ĠDiv\":12763,\"wall\":12764,\"ĠTab\":12765,\"Ġcompet\":12766,\"Ġrelied\":12767,\"Ġinequality\":12768,\"Ġmanual\":12769,\"ĠBucks\":12770,\"agging\":12771,\"Ġcorporation\":12772,\"Ġbanner\":12773,\"Ġgraphics\":12774,\"Ġaccurately\":12775,\"ĠMeeting\":12776,\"Ġconsult\":12777,\"ser\":12778,\"Ġprotesting\":12779,\"Ġhurting\":12780,\"omed\":12781,\"tes\":12782,\"Ġrode\":12783,\"Ġstartups\":12784,\"Ġhanding\":12785,\"ĠNest\":12786,\"Ġconsistency\":12787,\"anned\":12788,\"dem\":12789,\"ĠLyon\":12790,\"ĠCompetition\":12791,\"Ġtricky\":12792,\"Ġcos\":12793,\"ĠBengals\":12794,\"arry\":12795,\"Ġunderwent\":12796,\"ĠKit\":12797,\"à\":12798,\"uploads\":12799,\"Ġskate\":12800,\"Ġ''\":12801,\"Ġjun\":12802,\"ĠContent\":12803,\"focused\":12804,\"lat\":12805,\"ĠExp\":12806,\"ought\":12807,\"Ġnightmare\":12808,\"ĠExpect\":12809,\"Ġprecisely\":12810,\"ĠMonica\":12811,\"Ġlobbying\":12812,\"ĠChester\":12813,\"ĠInvest\":12814,\"Former\":12815,\"Ġimminent\":12816,\"ĠNL\":12817,\"Ġcomparing\":12818,\"ĠChes\":12819,\"ede\":12820,\"ĠNobel\":12821,\"mers\":12822,\"ĠKin\":12823,\"ĠBoko\":12824,\"ount\":12825,\"Ġthoroughly\":12826,\"Ġscattered\":12827,\"sharing\":12828,\"markets\":12829,\"ĠMis\":12830,\"Ġambition\":12831,\"Ġpreference\":12832,\"Ġeffectiveness\":12833,\"rio\":12834,\"Ġheavyweight\":12835,\"Ġovert\":12836,\"anya\":12837,\"ĠKanye\":12838,\"ishi\":12839,\"Ġrewards\":12840,\"uled\":12841,\"bach\":12842,\"Ġemphasized\":12843,\"Ġapologize\":12844,\"ĠRecent\":12845,\"!!\":12846,\"Ġanimated\":12847,\"ĠExxon\":12848,\"Ġfruits\":12849,\"Ġstripped\":12850,\"fold\":12851,\"ĠIndonesian\":12852,\"ller\":12853,\"Ġdementia\":12854,\"Ġkidney\":12855,\"Ġhalted\":12856,\"years\":12857,\"Ġconcerts\":12858,\"Ġrefers\":12859,\"ĠFri\":12860,\"Your\":12861,\"irl\":12862,\"Ġleap\":12863,\"jud\":12864,\"ĠHugh\":12865,\"ĠFO\":12866,\"Ġsore\":12867,\"Ġkil\":12868,\"ĠMate\":12869,\"cci\":12870,\"Ġsetback\":12871,\"Ġtightening\":12872,\"keeper\":12873,\"ĠAlbany\":12874,\"Ġpolicymakers\":12875,\"Ġdisorders\":12876,\"ĠCBC\":12877,\"ĠDiaz\":12878,\"Ġmaps\":12879,\"Ġroutinely\":12880,\"Ġverify\":12881,\"Ġbash\":12882,\"ĠJinping\":12883,\"Ġdisasters\":12884,\"ĠMonroe\":12885,\"ĠLouise\":12886,\"JP\":12887,\"ĠNevertheless\":12888,\"Ġconcessions\":12889,\"ĠPog\":12890,\"going\":12891,\"ĠFifth\":12892,\"ĠJill\":12893,\"ICT\":12894,\"ĠFM\":12895,\"ĠSugar\":12896,\"ĠBarb\":12897,\"Ġmidway\":12898,\"Ġtin\":12899,\"ĠPic\":12900,\"ĠPL\":12901,\"Ġleaks\":12902,\"Ġgrief\":12903,\"Ġtattoo\":12904,\"`\":12905,\"Ġment\":12906,\"ĠNu\":12907,\"Ġmarry\":12908,\"Ġdiving\":12909,\"Ġ1982\":12910,\"Ġcoin\":12911,\"ĠPoc\":12912,\"Ġstarred\":12913,\"ĠRiverside\":12914,\"Ġsidelined\":12915,\"Ġminers\":12916,\"STON\":12917,\"Ġbelongs\":12918,\"ĠSantos\":12919,\"ĠTechnical\":12920,\"aco\":12921,\"Ġadvise\":12922,\"Ġstreams\":12923,\"Ġcooler\":12924,\"ĠHE\":12925,\"Ġordering\":12926,\"ĠTask\":12927,\"ĠACT\":12928,\"ĠAnton\":12929,\"Ġcertification\":12930,\"ĠLeafs\":12931,\"ĠTS\":12932,\"ĠSerbia\":12933,\"azi\":12934,\"inks\":12935,\"ĠEST\":12936,\"Ġrelay\":12937,\"Â°\":12938,\"Ġdisappearance\":12939,\"ĠRomania\":12940,\"Ġoven\":12941,\"Ġowed\":12942,\"ĠStrip\":12943,\"ulated\":12944,\"UC\":12945,\"ITE\":12946,\"bling\":12947,\"Then\":12948,\"ppy\":12949,\"Ġunlimited\":12950,\"Ġcalories\":12951,\"Ġmerchandise\":12952,\"Ġblonde\":12953,\"ĠSpicer\":12954,\"performing\":12955,\"Ġimpl\":12956,\"Ġplates\":12957,\"Ġmosque\":12958,\"Ġdemon\":12959,\"Ġought\":12960,\"Ġdumped\":12961,\"Ġtracked\":12962,\"even\":12963,\"Ġstabil\":12964,\"imet\":12965,\"ĠLiga\":12966,\"ugh\":12967,\"ther\":12968,\"agar\":12969,\"Ġarchitect\":12970,\"Ġallocated\":12971,\"ĠJoey\":12972,\"Ġmarathon\":12973,\"master\":12974,\"ĠBert\":12975,\"Ġast\":12976,\"ĠEbola\":12977,\"ĠConservation\":12978,\"nic\":12979,\"Ġparallel\":12980,\"Ġinmate\":12981,\"Ġlocate\":12982,\"Ġdistribute\":12983,\"guard\":12984,\"Ġtackling\":12985,\"ential\":12986,\"Ġvi\":12987,\"Ġcups\":12988,\"Ġrhythm\":12989,\"Ġendured\":12990,\"ĠHub\":12991,\"ois\":12992,\"ĠLiberals\":12993,\"ĠRedskins\":12994,\"ĠEP\":12995,\"ĠKnox\":12996,\"fr\":12997,\"Ġmassacre\":12998,\"oka\":12999,\"Ġcompl\":13000,\"raft\":13001,\"ĠPublished\":13002,\"Ġattraction\":13003,\"ĠStephens\":13004,\"ility\":13005,\"ĠPul\":13006,\"ĠCapt\":13007,\"Ġexploded\":13008,\"Ġexceeded\":13009,\"lying\":13010,\"Ġcal\":13011,\"Mart\":13012,\"Ġpaintings\":13013,\"inate\":13014,\"ĠBrendan\":13015,\"Ġfortune\":13016,\"onductor\":13017,\"Ġphysicians\":13018,\"ĠStudy\":13019,\"ĠBul\":13020,\"ĠModern\":13021,\"HD\":13022,\"ĠBour\":13023,\"Ġtying\":13024,\"Ġ1967\":13025,\"Ġlighter\":13026,\"Ġtoss\":13027,\"inspired\":13028,\"Ġgreeted\":13029,\"Ġcycl\":13030,\"Ġverified\":13031,\"Ġmerit\":13032,\"sign\":13033,\"lder\":13034,\"Ġdebts\":13035,\"ĠSnyder\":13036,\"Ġamendments\":13037,\"Ġindicators\":13038,\"ĠDortmund\":13039,\"then\":13040,\"ĠListen\":13041,\"ĠFB\":13042,\"ref\":13043,\"ĠIoT\":13044,\"ĠBrewers\":13045,\"ĠLeadership\":13046,\"ĠNicolas\":13047,\"ĠBody\":13048,\"Ġsam\":13049,\"ĠAdvisor\":13050,\"Ġcord\":13051,\"Ġabuses\":13052,\"ĠPortuguese\":13053,\"Ġflown\":13054,\"VR\":13055,\"Ġconsumed\":13056,\"Ġreass\":13057,\"Ġalien\":13058,\"Ġrivalry\":13059,\"ĠREPORT\":13060,\"ĠRush\":13061,\"Ġdirecting\":13062,\"Ġsearches\":13063,\"ĠHP\":13064,\"ĠRoll\":13065,\"ĠFay\":13066,\"ĠClare\":13067,\"Ġhaul\":13068,\"Ġriot\":13069,\"Ġsettlements\":13070,\"Ġnorm\":13071,\"Ġaccelerated\":13072,\"ĠLok\":13073,\"Ġclever\":13074,\"Ġhyd\":13075,\"Ġstats\":13076,\"ĠHull\":13077,\"kers\":13078,\"Ġbuys\":13079,\"uter\":13080,\"Ġfue\":13081,\"https\":13082,\"UD\":13083,\"Ġisolation\":13084,\"Ġsuspend\":13085,\"ĠRules\":13086,\"ĠCircle\":13087,\"ĠHopefully\":13088,\"played\":13089,\"âĢ³\":13090,\"ĠPRE\":13091,\"sim\":13092,\"edd\":13093,\"ĠProperties\":13094,\"Ġbeans\":13095,\"Ġrevive\":13096,\"ĠBir\":13097,\"oug\":13098,\"Ġmob\":13099,\"Ġshowdown\":13100,\"iman\":13101,\"Ġpap\":13102,\"Ġvol\":13103,\"wu\":13104,\"Ġdiver\":13105,\"Ġpill\":13106,\"ĠMarlins\":13107,\"ĠLamar\":13108,\"Ġpersistent\":13109,\"Ġcondolences\":13110,\"ĠThor\":13111,\"Ab\":13112,\"Ġimpress\":13113,\"ĠRaptors\":13114,\"Ġreferences\":13115,\"Ġstiff\":13116,\"ĠBash\":13117,\"eding\":13118,\"Ġmurders\":13119,\"ĠGene\":13120,\"ĠManila\":13121,\"Ġbrokers\":13122,\"Ms\":13123,\"start\":13124,\"ĠDhabi\":13125,\"etz\":13126,\"Ġsubmission\":13127,\"ĠSchmidt\":13128,\"ĠPersonal\":13129,\"ĠBeverly\":13130,\"ĠMovie\":13131,\"ĠLamb\":13132,\"Ġplacement\":13133,\"Ġfolk\":13134,\"Ġfrequency\":13135,\"Ġplanted\":13136,\"Ġtwins\":13137,\"prov\":13138,\"rec\":13139,\"Ġpermanently\":13140,\"Ġcoordination\":13141,\"ĠCart\":13142,\"Ġobstacles\":13143,\"Ġliterature\":13144,\"Ġtu\":13145,\"Ġchill\":13146,\"ĠReserved\":13147,\"Ġlovers\":13148,\"ĠOutside\":13149,\"Ġslideshow\":13150,\"ĠGru\":13151,\"Ġty\":13152,\"Ġsalad\":13153,\"Ġlaboratory\":13154,\"ĠHolt\":13155,\"Ġ103\":13156,\"urb\":13157,\"ĠOrganisation\":13158,\"ĠAndrews\":13159,\"Ġrecipient\":13160,\"arch\":13161,\"Ġbleeding\":13162,\"ĠPand\":13163,\"Ġoverturned\":13164,\"Ġlistened\":13165,\"Ġclause\":13166,\"Ġnationalist\":13167,\"Ġresumed\":13168,\"ĠCout\":13169,\"ĠPride\":13170,\"Ġlayers\":13171,\"ĠBella\":13172,\"Ġreversed\":13173,\"Ġpriest\":13174,\"ĠFX\":13175,\"Ġalbeit\":13176,\"Ġhalfway\":13177,\"Ġcotton\":13178,\"ĠCarey\":13179,\"ĠTE\":13180,\"OCK\":13181,\"Ġbuck\":13182,\"ributes\":13183,\"ea\":13184,\"Ġfancy\":13185,\"ĠBuc\":13186,\"Ġbans\":13187,\"uters\":13188,\"Ġliabilities\":13189,\"ĠSou\":13190,\"ĠBernie\":13191,\"Ġintervene\":13192,\"food\":13193,\"ĠNDP\":13194,\"Ġinsist\":13195,\"Ġcontracted\":13196,\"hawk\":13197,\"),\\\"\":13198,\"ĠDawn\":13199,\"Ġmol\":13200,\"Ġcommissioners\":13201,\"Ġstranded\":13202,\"Ġoverwhelmed\":13203,\"Ġrecipes\":13204,\"Ġva\":13205,\"Ġrad\":13206,\"Ġscare\":13207,\"rez\":13208,\"Ġeliminating\":13209,\"Ġresc\":13210,\"ĠBreak\":13211,\"chn\":13212,\"Ġdelight\":13213,\"iot\":13214,\"Ġfreely\":13215,\"TI\":13216,\"ĠBluetooth\":13217,\"ĠMonth\":13218,\"ĠFlor\":13219,\"ĠFreddie\":13220,\"Ġtrailed\":13221,\"Ġinvestigative\":13222,\"Ġimposing\":13223,\"Ġattracting\":13224,\"awk\":13225,\"ĠSherman\":13226,\"Ġsucceeded\":13227,\"Ġvent\":13228,\"Ġreconciliation\":13229,\"ĠCel\":13230,\"ĠThroughout\":13231,\"ĠDowntown\":13232,\"ĠBrother\":13233,\"Ġtraditions\":13234,\"Ġmir\":13235,\"Ġstamp\":13236,\"tery\":13237,\"etti\":13238,\"isch\":13239,\"tic\":13240,\"Ġbanning\":13241,\"loss\":13242,\"ĠSpeedway\":13243,\"Ġstalled\":13244,\"ĠEN\":13245,\"ASH\":13246,\"thing\":13247,\"ĠAppeals\":13248,\"rac\":13249,\"Ġdistress\":13250,\"ĠConservatives\":13251,\"ĠPremium\":13252,\"usa\":13253,\"Ġslump\":13254,\"imm\":13255,\"ĠSupp\":13256,\"ĠWong\":13257,\"Ġdistant\":13258,\"Ġ104\":13259,\"Ġtide\":13260,\"ĠNorfolk\":13261,\"ĠYang\":13262,\"Ġsmashed\":13263,\"ĠBarrett\":13264,\"inho\":13265,\"Ġrobbed\":13266,\"ĠFarmers\":13267,\"filled\":13268,\"BT\":13269,\"Ġautumn\":13270,\"Ġtemple\":13271,\"ĠJacobs\":13272,\"Ġprecipitation\":13273,\"ĠHours\":13274,\"ĠFlight\":13275,\"Ġbeside\":13276,\"ĠOre\":13277,\"!)\":13278,\"ĠTurnbull\":13279,\"Ġpig\":13280,\"Ġcooling\":13281,\"Ġservers\":13282,\"oriented\":13283,\"Ġlocks\":13284,\"ĠSears\":13285,\"aving\":13286,\"ĠQuick\":13287,\"ĠGlob\":13288,\"ĠMining\":13289,\"Ġhorizon\":13290,\"arians\":13291,\"ĠOm\":13292,\"writing\":13293,\"Ġbelieving\":13294,\"Ġbon\":13295,\"Ġmounted\":13296,\"Ġpunt\":13297,\"ucci\":13298,\"uzz\":13299,\"cul\":13300,\"Ġkiss\":13301,\"ĠOnt\":13302,\"ĠCyprus\":13303,\"Ġrelying\":13304,\"Ġpiano\":13305,\"Ġcure\":13306,\"Ġcontinuously\":13307,\"ĠNobody\":13308,\"ĠBund\":13309,\"osis\":13310,\"ĠAurora\":13311,\"ĠBach\":13312,\"ĠKendall\":13313,\"Ġechoed\":13314,\"iable\":13315,\"Ġconscious\":13316,\"Ġmonster\":13317,\"omo\":13318,\"proof\":13319,\"ĠNate\":13320,\"Ġfilmmaker\":13321,\"ĠNaj\":13322,\"Ġvendor\":13323,\"ĠFoot\":13324,\"ĠChang\":13325,\"ĠFest\":13326,\"Ġselfie\":13327,\"Ġenters\":13328,\"ĠConor\":13329,\"ĠMosul\":13330,\"ĠWHAT\":13331,\"Ġwa\":13332,\"ĠGamb\":13333,\"osta\":13334,\"Ġcautioned\":13335,\"ĠTucker\":13336,\"ĠAirways\":13337,\"Ġvisitor\":13338,\"ĠÂ·\":13339,\"ĠRevolution\":13340,\"aching\":13341,\"Ġearliest\":13342,\"ĠQuality\":13343,\"Ġshorts\":13344,\"ube\":13345,\"ĠOperation\":13346,\"ĠSabha\":13347,\"Ġstrengths\":13348,\"ikes\":13349,\"Ġsexy\":13350,\"Ġrot\":13351,\"ibles\":13352,\"Ġcolours\":13353,\"THE\":13354,\"ailed\":13355,\"Ġwoke\":13356,\"ĠEmbassy\":13357,\"Ġinfamous\":13358,\"rov\":13359,\"State\":13360,\"âĢ¦.\":13361,\"Ġpond\":13362,\"Ġcapt\":13363,\"fore\":13364,\"De\":13365,\"Ġedited\":13366,\"self\":13367,\"Hey\":13368,\"Ġportrait\":13369,\"ĠManufact\":13370,\"ĠStand\":13371,\"Ġcontenders\":13372,\"':\":13373,\"acker\":13374,\"Ġwithdrawn\":13375,\"ĠBraves\":13376,\"ĠHosp\":13377,\"changing\":13378,\"ĠBag\":13379,\"Ġadjustment\":13380,\"ĠCousins\":13381,\"ĠAAP\":13382,\"Ġfi\":13383,\"Ġoutdoors\":13384,\"Ġlacked\":13385,\"BM\":13386,\"ĠWHO\":13387,\"ĠPST\":13388,\"ĠLuck\":13389,\"Ġassisting\":13390,\"ĠGround\":13391,\"ĠTeen\":13392,\"ĠOle\":13393,\"Ġembarrassing\":13394,\"ĠWalt\":13395,\"ĠVision\":13396,\"ĠFal\":13397,\"ĠZoo\":13398,\"ĠWorth\":13399,\"ĠFloyd\":13400,\"ĠGujarat\":13401,\"Ġtipped\":13402,\"Ġfam\":13403,\"ĠDad\":13404,\"Ġworship\":13405,\"Ġtyre\":13406,\"Ġrebuilding\":13407,\"Ġqualities\":13408,\"ĠLives\":13409,\"Ġbeats\":13410,\"Ġ450\":13411,\"Ġexisted\":13412,\"ĠGeorg\":13413,\"Ġpoured\":13414,\"rows\":13415,\"ĠOx\":13416,\"ĠSid\":13417,\"Ġmac\":13418,\"Ġteaches\":13419,\"ĠEli\":13420,\"alla\":13421,\"Ġdownside\":13422,\"ĠBend\":13423,\"non\":13424,\"ĠArmenia\":13425,\"Ġcultures\":13426,\"ĠMae\":13427,\"Ġduration\":13428,\"ĠAthletics\":13429,\"Ġjuvenile\":13430,\"Ġlid\":13431,\"Ġbankers\":13432,\"Ġoverview\":13433,\"wy\":13434,\"Ġorbit\":13435,\"Vs\":13436,\"because\":13437,\"Ps\":13438,\"ĠFran\":13439,\"Ġtouring\":13440,\"Ġwary\":13441,\"Ġ106\":13442,\"Ġlaser\":13443,\"ĠVij\":13444,\"âĦ¢\":13445,\"Ġsurrender\":13446,\"press\":13447,\"rees\":13448,\"NO\":13449,\"ĠShortly\":13450,\"ĠKor\":13451,\"edu\":13452,\"Ġhatred\":13453,\"Ġtee\":13454,\"Ġfamously\":13455,\"Ġkeeper\":13456,\"ND\":13457,\"Ġreduces\":13458,\"HC\":13459,\"Ġhay\":13460,\"Ġunnamed\":13461,\"ĠTes\":13462,\"Ġattackers\":13463,\"ĠFew\":13464,\"ĠRichards\":13465,\"Ġ1968\":13466,\"Ġspeeches\":13467,\"Ġcybersecurity\":13468,\"ĠInfrastructure\":13469,\"Ġ07\":13470,\"ENCE\":13471,\"uties\":13472,\"Ġanxious\":13473,\"ĠGang\":13474,\"Ġannouncements\":13475,\"lette\":13476,\"oret\":13477,\"ĠRockies\":13478,\"ĠEmployees\":13479,\"ĠThrones\":13480,\"Ġhugely\":13481,\"Ġclin\":13482,\"ĠHob\":13483,\"Ġfraction\":13484,\"ĠOfficial\":13485,\"ĠMariners\":13486,\"ĠElse\":13487,\"Ġsanctuary\":13488,\"ĠPhotograph\":13489,\"Ġreopen\":13490,\"lf\":13491,\"hm\":13492,\"vest\":13493,\"Ġspeeding\":13494,\"Ġtooth\":13495,\"ĠShi\":13496,\"ĠTitle\":13497,\"ĠMes\":13498,\"ĠJobs\":13499,\"fair\":13500,\"ĠDanish\":13501,\"ĠMalik\":13502,\"Ġlaughed\":13503,\"Ġnavy\":13504,\"ĠActress\":13505,\"ĠWilliamson\":13506,\"overs\":13507,\"Ġreckless\":13508,\"Ġjo\":13509,\"otic\":13510,\"Ġassaulting\":13511,\"Ġpri\":13512,\"ĠPi\":13513,\"Ġlesser\":13514,\"Ġtit\":13515,\"Ġdat\":13516,\"Ġnail\":13517,\"ĠMarathon\":13518,\"ĠGren\":13519,\"ĠDol\":13520,\"Ġjointly\":13521,\"Ġamended\":13522,\"mine\":13523,\"ĠBashar\":13524,\"ĠHyundai\":13525,\"Ġuncovered\":13526,\"Ġeducated\":13527,\"atti\":13528,\"pres\":13529,\"ĠBRE\":13530,\"Ġya\":13531,\"Bank\":13532,\"odd\":13533,\"lit\":13534,\"ĠLinks\":13535,\"Ġswitching\":13536,\"itte\":13537,\"ĠSind\":13538,\"erved\":13539,\"Ġ**\":13540,\"Ġpositively\":13541,\"Ġfrankly\":13542,\"Ġrevenge\":13543,\"ĠTrinity\":13544,\"ĠCDC\":13545,\"Ġthreatens\":13546,\"Ġhammer\":13547,\"NET\":13548,\"ĠMut\":13549,\"Ġsy\":13550,\"Ġunidentified\":13551,\"icken\":13552,\"Ġdrills\":13553,\"Ġtense\":13554,\"Ġforeigners\":13555,\"OST\":13556,\"Ġethical\":13557,\"ĠDurham\":13558,\"ĠQual\":13559,\"Ġterritories\":13560,\"Ġid\":13561,\"hor\":13562,\"enders\":13563,\"Mc\":13564,\"OV\":13565,\"percent\":13566,\"Ġdom\":13567,\"Ġupward\":13568,\"Ġamb\":13569,\"Ġvisas\":13570,\"zan\":13571,\"Ãĥ\":13572,\"Ġundocumented\":13573,\"Ġsuburbs\":13574,\"Ġhydro\":13575,\"ĠJob\":13576,\"ĠAdelaide\":13577,\"oya\":13578,\"ĠSR\":13579,\"ĠMick\":13580,\"Ġconsolidation\":13581,\"Ġemotionally\":13582,\"ĠHop\":13583,\"Her\":13584,\"Ġloses\":13585,\"ĠMoto\":13586,\"eled\":13587,\"Ġregulated\":13588,\"ental\":13589,\"Ġencountered\":13590,\"Ġhop\":13591,\"ĠTrafford\":13592,\"Ġsticks\":13593,\"Ġveto\":13594,\"Ġexpose\":13595,\"Ġstretched\":13596,\"fin\":13597,\"inance\":13598,\"chair\":13599,\"ĠGareth\":13600,\"ĠPil\":13601,\"ĠHammond\":13602,\"Ġserial\":13603,\"omy\":13604,\"Ġcellphone\":13605,\"ĠClara\":13606,\"Ġreacted\":13607,\"ĠNic\":13608,\"ĠHomes\":13609,\"ĠBroadcasting\":13610,\"ĠFut\":13611,\"ĠSupply\":13612,\"assing\":13613,\"ĠNewman\":13614,\"Ġcharitable\":13615,\"ĠClayton\":13616,\"Ġsovereignty\":13617,\"Ġconvincing\":13618,\"ĠPrincipal\":13619,\"ĠHigher\":13620,\"ĠCut\":13621,\"ĠCarrie\":13622,\"ĠSpot\":13623,\"Sometimes\":13624,\"ĠJar\":13625,\"ĠConsider\":13626,\"ieu\":13627,\"Ġrefinery\":13628,\"Ġbloody\":13629,\"wheel\":13630,\"Ġcryptocurrencies\":13631,\"Fund\":13632,\"ĠSunderland\":13633,\"ĠEvents\":13634,\"âĢĭ\":13635,\"Ġaccidentally\":13636,\"deep\":13637,\"Ġfranc\":13638,\"bec\":13639,\"ĠHartford\":13640,\"Ġstellar\":13641,\"wright\":13642,\"kick\":13643,\"UG\":13644,\"ĠBeast\":13645,\"Ġrefusal\":13646,\"ĠRoberto\":13647,\"ĠDixon\":13648,\"ĠDiane\":13649,\"name\":13650,\"asts\":13651,\"ĠCharter\":13652,\"Ġfueled\":13653,\"Ġcontents\":13654,\"Ġaccessing\":13655,\"Ġtroubles\":13656,\"Ġtops\":13657,\"Ġdebuted\":13658,\"icating\":13659,\"Ġinvestigator\":13660,\"Ġsubscribing\":13661,\"Ġcoordinated\":13662,\"ĠFil\":13663,\"six\":13664,\"teen\":13665,\"Ġwithdrew\":13666,\"ĠGilbert\":13667,\"Ġ1983\":13668,\"arsity\":13669,\"Ġimagination\":13670,\"Ġhandgun\":13671,\"ĠAlibaba\":13672,\"Ġbug\":13673,\"Ġ107\":13674,\"ĠCOMP\":13675,\"ĠSomething\":13676,\"Ġreliability\":13677,\"ĠFCC\":13678,\"ĠFowler\":13679,\"Ġsingled\":13680,\"nom\":13681,\"Ġknocking\":13682,\"Ġmeddling\":13683,\"Ġdetermining\":13684,\"reports\":13685,\"Ġshade\":13686,\"ĠSN\":13687,\"anto\":13688,\"Ġcomplaining\":13689,\"ĠNan\":13690,\"WS\":13691,\"Ġyoungsters\":13692,\"Il\":13693,\"ĠKaw\":13694,\"ĠProp\":13695,\"ĠCell\":13696,\"ĠHurricanes\":13697,\"Ġpublicity\":13698,\"ĠXin\":13699,\"rial\":13700,\"ICO\":13701,\"Ġsupervision\":13702,\"ĠSpotify\":13703,\"ĠNewport\":13704,\"Ġprince\":13705,\"anche\":13706,\"Ġsubscriber\":13707,\"ĠVic\":13708,\"ACT\":13709,\"ĠRaf\":13710,\"ĠActing\":13711,\"Ġcollusion\":13712,\"pet\":13713,\"isl\":13714,\"Ġcommerce\":13715,\"Health\":13716,\"ĠAbraham\":13717,\"pri\":13718,\"Ġlightweight\":13719,\"Ġinsurer\":13720,\"Like\":13721,\"Ġhelmet\":13722,\"Ġevac\":13723,\"look\":13724,\"ĠNaval\":13725,\"160\":13726,\"ĠFleet\":13727,\"vol\":13728,\"Ġexpired\":13729,\"ĠKlein\":13730,\"ĠEmmy\":13731,\"ABLE\":13732,\"ĠMorocco\":13733,\"ĠTrip\":13734,\"uted\":13735,\"Ġnos\":13736,\"ĠVista\":13737,\"mas\":13738,\"ĠRocky\":13739,\"ĠFlint\":13740,\"enberg\":13741,\"ĠBrow\":13742,\"Ġsignatures\":13743,\"Ġpolar\":13744,\"ajo\":13745,\"Ġendorsement\":13746,\"Ġreservations\":13747,\"LIN\":13748,\"anny\":13749,\"elli\":13750,\"last\":13751,\"Ġoversee\":13752,\"cm\":13753,\"ĠOilers\":13754,\"Are\":13755,\"Ġjudiciary\":13756,\"onte\":13757,\"ĠTrack\":13758,\"Ġsupervisor\":13759,\"erk\":13760,\"isher\":13761,\"Ġintact\":13762,\"Ġslid\":13763,\"icals\":13764,\"paid\":13765,\"ĠMAR\":13766,\"lement\":13767,\"ĠLiu\":13768,\"ĠLarge\":13769,\"ĠWings\":13770,\"pect\":13771,\"ĠRum\":13772,\"Ġanalyzed\":13773,\"Ġemploys\":13774,\"arte\":13775,\"ims\":13776,\"ĠEventually\":13777,\"Ġaffiliated\":13778,\"Ġhospitality\":13779,\"ĠSprint\":13780,\"Ġresolutions\":13781,\"Ġliquor\":13782,\"ĠNAFTA\":13783,\"ANY\":13784,\"Ġradiation\":13785,\"ĠProv\":13786,\"Ġpause\":13787,\"ĠTMZ\":13788,\"Ġelbow\":13789,\"Ġresilience\":13790,\"ĠParents\":13791,\"mus\":13792,\"ĠSafe\":13793,\"Ġinterpretation\":13794,\"Ġraced\":13795,\"IND\":13796,\"KR\":13797,\"Ġhinted\":13798,\"ĠErin\":13799,\"ĠBahrain\":13800,\"Ġcredentials\":13801,\"eless\":13802,\"Ġprocurement\":13803,\"ĠWebb\":13804,\"ĠLowe\":13805,\"ĠNak\":13806,\"ĠLearning\":13807,\"zh\":13808,\"Ġdipped\":13809,\"ĠSuite\":13810,\"Ġmisdemeanor\":13811,\"ALE\":13812,\"Ġstrengthened\":13813,\"ĠSophie\":13814,\"Ġconfirms\":13815,\"Ġrac\":13816,\"gey\":13817,\"Ġshootout\":13818,\"Ġble\":13819,\"Ġcircles\":13820,\"ĠChef\":13821,\"Ġcomprised\":13822,\"ĠSantiago\":13823,\"Ġfeud\":13824,\"beat\":13825,\"Ġstaffers\":13826,\"Ġacute\":13827,\"ski\":13828,\"Ġpolled\":13829,\"ĠKur\":13830,\"ĠJen\":13831,\"ĠUltimately\":13832,\"anded\":13833,\"ĠHoney\":13834,\"Ġannounces\":13835,\"Ġamateur\":13836,\"around\":13837,\"Ġfunctioning\":13838,\"group\":13839,\"ĠSqu\":13840,\"Where\":13841,\"Ġvoid\":13842,\"ĠSandra\":13843,\"isers\":13844,\"Ġhelicopters\":13845,\"ĠGym\":13846,\"ĠWol\":13847,\"mouth\":13848,\"Ġsubjected\":13849,\"ici\":13850,\"ually\":13851,\"ĠWash\":13852,\"ĠLindsay\":13853,\"ĠVers\":13854,\"Ġjumps\":13855,\"Ġneglect\":13856,\"ĠKuwait\":13857,\"fund\":13858,\"ĭ\":13859,\"ather\":13860,\"lly\":13861,\"ei\":13862,\"Although\":13863,\".''\":13864,\"Ġunhappy\":13865,\"Ġpills\":13866,\"Ġmagical\":13867,\"Ġdro\":13868,\"Ġinviting\":13869,\"ĠJohnston\":13870,\"oving\":13871,\"450\":13872,\"ĠMerc\":13873,\"Ġadmitting\":13874,\"Ġinsisting\":13875,\"ĠCru\":13876,\"ĠResource\":13877,\"oir\":13878,\"Ġcomplexity\":13879,\"ĠRoth\":13880,\"ĠCher\":13881,\"July\":13882,\"raf\":13883,\"Ġaggregate\":13884,\"Ġhelm\":13885,\"uclear\":13886,\"olan\":13887,\"Ġoffenses\":13888,\"ĠWolves\":13889,\"ĠFu\":13890,\"ĠPierce\":13891,\"Ġemailed\":13892,\"ĠStra\":13893,\"Ġpedestrians\":13894,\"ĠER\":13895,\"ĠConway\":13896,\"Ġblowing\":13897,\"CLOSE\":13898,\"hab\":13899,\"ĠGreene\":13900,\"Ġconfessed\":13901,\"ĠTorres\":13902,\"ĠHolocaust\":13903,\"Ġrepay\":13904,\"Ġdemonstrates\":13905,\"ĠPool\":13906,\"gent\":13907,\"Ġdeleted\":13908,\"Ġ$$\":13909,\"ĠSO\":13910,\"Ġdri\":13911,\"ĠNeg\":13912,\"ĠVP\":13913,\"ĠPF\":13914,\"ĠPrep\":13915,\"Ġorganizing\":13916,\"icker\":13917,\"Ġmanufactured\":13918,\"enson\":13919,\"adas\":13920,\"Ġwines\":13921,\"Ġmachinery\":13922,\"Ġspecialists\":13923,\"ĠDetective\":13924,\"ĠDL\":13925,\"Op\":13926,\"Ġquicker\":13927,\"ĠPenguins\":13928,\"Engine\":13929,\"zone\":13930,\"Ġsequence\":13931,\"ĠLost\":13932,\"Ġwarmer\":13933,\"ĠEthiopia\":13934,\"Ġaffirmed\":13935,\"fest\":13936,\"resses\":13937,\"Ġsoap\":13938,\"Ġbooth\":13939,\"Ġnotorious\":13940,\"amin\":13941,\"Ġpursued\":13942,\"ĠCer\":13943,\"ĠSB\":13944,\"Ġlivestock\":13945,\"Ġtrace\":13946,\"Ġrespects\":13947,\"arden\":13948,\"April\":13949,\"Ġ128\":13950,\"ĠSaid\":13951,\"ennial\":13952,\"Ġnamely\":13953,\"ĠBot\":13954,\"Ġ108\":13955,\"ĠLem\":13956,\"nell\":13957,\"Ġconfirming\":13958,\"Ġlogged\":13959,\"Ġprofound\":13960,\"elo\":13961,\"ĠChambers\":13962,\"RT\":13963,\"Ġnewer\":13964,\"Ġsideline\":13965,\"ĠCardinal\":13966,\"este\":13967,\"Ġnarrowly\":13968,\"Ġcompromised\":13969,\"Ġpolicing\":13970,\"Ġporn\":13971,\"Ġarc\":13972,\"Ġlearnt\":13973,\"INE\":13974,\"step\":13975,\"ĠDomin\":13976,\"Ġwaist\":13977,\"Ġboycott\":13978,\"mitted\":13979,\"iffs\":13980,\"ground\":13981,\"ĠMaterials\":13982,\"Ġceasefire\":13983,\"Right\":13984,\"ĠZen\":13985,\"estyle\":13986,\"Thank\":13987,\"ĠOnePlus\":13988,\"ĠMLS\":13989,\"Ġconstituents\":13990,\"oster\":13991,\"ĠProsecutor\":13992,\"Ġpriorit\":13993,\"ĠDebbie\":13994,\"ĠExpand\":13995,\"uv\":13996,\"Ġintegrate\":13997,\"Ġimmun\":13998,\"Ġdisciplinary\":13999,\"ĠImm\":14000,\"Ġja\":14001,\"Ġgardens\":14002,\"ĠHim\":14003,\"obe\":14004,\"Ġhitter\":14005,\"Ġbullets\":14006,\"Ġevolving\":14007,\"ĠScientists\":14008,\"Michael\":14009,\"ĠDO\":14010,\"Ġunbelievable\":14011,\"Ġlooming\":14012,\"Ġdownturn\":14013,\"Ġmentality\":14014,\"Ġreopened\":14015,\"Ġash\":14016,\"ĠChapman\":14017,\"Ġloop\":14018,\"ĠUT\":14019,\"ĠTier\":14020,\"Ġunaware\":14021,\"Ġgratitude\":14022,\"Ġperforms\":14023,\"olk\":14024,\"Ġ\\\"(\":14025,\"Ġlacks\":14026,\"Ġinstructed\":14027,\"ĠRecreation\":14028,\"sample\":14029,\"Ġrequesting\":14030,\"Canada\":14031,\"Ġsupposedly\":14032,\"ĠHardy\":14033,\"Ġholder\":14034,\"change\":14035,\"ĠDominic\":14036,\"ĠXavier\":14037,\"Ġlig\":14038,\"Ġcandid\":14039,\"ĠRab\":14040,\"Ġconferences\":14041,\"ĠBurton\":14042,\"Dr\":14043,\"Ġmunicipalities\":14044,\"Ġcrushed\":14045,\"Ġseekers\":14046,\"ĠCitizens\":14047,\"Ġheightened\":14048,\"ĠCasino\":14049,\"Ġdesktop\":14050,\"Ġwhoever\":14051,\"ĠImpact\":14052,\"Ġcocktail\":14053,\"Ġphilanthrop\":14054,\"ĠSAN\":14055,\"ĠPreston\":14056,\"Ġobesity\":14057,\"Ġrestrict\":14058,\"ĠKab\":14059,\"ĠProvidence\":14060,\"Ġscar\":14061,\"ĠChart\":14062,\"Ġbosses\":14063,\"ĠRate\":14064,\"Ġsav\":14065,\"pay\":14066,\"Ġtransplant\":14067,\"ĠNoble\":14068,\"child\":14069,\"Ġconclusions\":14070,\"FI\":14071,\"Ġsack\":14072,\"Ġexperimental\":14073,\"holder\":14074,\"oca\":14075,\"herty\":14076,\"ĠMT\":14077,\"Ġcatcher\":14078,\"LY\":14079,\"Ġgrams\":14080,\"reet\":14081,\"Ġadaptation\":14082,\"Ġhumble\":14083,\"Ġbot\":14084,\"Ġidentical\":14085,\"ication\":14086,\"ifer\":14087,\"ĠCrow\":14088,\"Ġregain\":14089,\"ĠLightning\":14090,\"Ġkg\":14091,\"Ġcomposed\":14092,\"Ġcorrespondent\":14093,\"Ġreunion\":14094,\"Ġobserve\":14095,\"Ġcomprising\":14096,\"Ġimpeachment\":14097,\"Ġresh\":14098,\"Ġlemon\":14099,\"ĠSnap\":14100,\"Ġproprietary\":14101,\"een\":14102,\"ourt\":14103,\"Ġdetective\":14104,\"Ġlabels\":14105,\"Ġcorridor\":14106,\"ĠClinic\":14107,\"Ġarra\":14108,\"ĠPearl\":14109,\"Ġinformal\":14110,\"ĠUnd\":14111,\"ĠVenezuelan\":14112,\"Ġpeninsula\":14113,\"Ġdefeating\":14114,\"Ġsyndrome\":14115,\"iere\":14116,\"Ġspite\":14117,\"bag\":14118,\"aran\":14119,\"Ġspecialized\":14120,\"ĠAA\":14121,\"ĠLyn\":14122,\"Ġinstrumental\":14123,\"Smith\":14124,\"Ġpivotal\":14125,\"Ġnightclub\":14126,\"ĠCob\":14127,\"Ġcolorful\":14128,\"Ġartwork\":14129,\"Ġ1981\":14130,\"Ġdawn\":14131,\"erville\":14132,\"uated\":14133,\"ief\":14134,\"Ġlinking\":14135,\"ĠOw\":14136,\"Ġappreci\":14137,\"Ġreductions\":14138,\"elling\":14139,\"Ġsalmon\":14140,\"bb\":14141,\"ĠPhillip\":14142,\"yle\":14143,\"Ġassure\":14144,\"Ġdiscretion\":14145,\"Ġefficiently\":14146,\"ĠMau\":14147,\"abil\":14148,\"Ġintentionally\":14149,\"Ġactivated\":14150,\"Ġimmense\":14151,\"ĠStrategic\":14152,\"Ġcheating\":14153,\"ĠTrend\":14154,\"ĠSamantha\":14155,\"Ġcomple\":14156,\"Ġhack\":14157,\"ĠSerie\":14158,\"ĠText\":14159,\"Ġstylish\":14160,\"ĠFaith\":14161,\"ĠGST\":14162,\"Ġexterior\":14163,\"Ġblessing\":14164,\"Ġblanket\":14165,\"Ġcooked\":14166,\"Ġretaliation\":14167,\"Ġtro\":14168,\"Ġshelves\":14169,\"rose\":14170,\"ĠGram\":14171,\"Ġsho\":14172,\"ĠArgentine\":14173,\"Ġclerk\":14174,\"specific\":14175,\"Ġagreeing\":14176,\"Ġstandout\":14177,\"black\":14178,\"Ġtrending\":14179,\"Ġviolate\":14180,\"Get\":14181,\"Ã±o\":14182,\"ĠOpt\":14183,\"ĠFrankfurt\":14184,\"ĠFranco\":14185,\"eness\":14186,\"Ġlining\":14187,\"Ġzoo\":14188,\"oil\":14189,\"lia\":14190,\"rab\":14191,\"Ġorganize\":14192,\"Ġwoods\":14193,\"Ġscan\":14194,\"Ġurgency\":14195,\"Ġoccurring\":14196,\"Ġreliance\":14197,\"Ġconcepts\":14198,\"Ġeligibility\":14199,\"0000\":14200,\"ĠBrief\":14201,\"Ġabusive\":14202,\"ĠBench\":14203,\"Ġrub\":14204,\"ĠDil\":14205,\"Ġmount\":14206,\"Ġmaturity\":14207,\"ĠNut\":14208,\"nee\":14209,\"enc\":14210,\"Ġgunfire\":14211,\"ĠKill\":14212,\"Ġgates\":14213,\"Ġflower\":14214,\"iol\":14215,\"Ġshaped\":14216,\"Ġundoubtedly\":14217,\"Ġbackgrounds\":14218,\"ĠComplex\":14219,\"\\\":{\\\"\":14220,\"Ġnaming\":14221,\"Ġmonument\":14222,\"Ġoh\":14223,\"Ġembedded\":14224,\"Ġbang\":14225,\"ĠKro\":14226,\"Ġaggression\":14227,\"ĠMits\":14228,\"During\":14229,\"ĠEp\":14230,\"iners\":14231,\"ĠAnaheim\":14232,\"Ġrom\":14233,\"Ġoutgoing\":14234,\"Ġfulfill\":14235,\"Ġreminds\":14236,\"Ġren\":14237,\"à¤\":14238,\"ĠSue\":14239,\"Ġrefresh\":14240,\"Ġlif\":14241,\"Ġfil\":14242,\"ĠLead\":14243,\"Ġregulate\":14244,\"ĠTeachers\":14245,\"Ġclarify\":14246,\"obs\":14247,\"Ġblasted\":14248,\"ĠAx\":14249,\"Ġflavors\":14250,\"Ġmega\":14251,\"Ġhurdles\":14252,\"Ġinspector\":14253,\"ĠSalvador\":14254,\"Ġprescribed\":14255,\"Ġrenovation\":14256,\"OUR\":14257,\"Ġutil\":14258,\"ĠBradford\":14259,\"Ġwasted\":14260,\"Ġlineman\":14261,\"Ġpalm\":14262,\"icate\":14263,\"Ġoverseeing\":14264,\"otted\":14265,\"ĠRapids\":14266,\"Ġjustified\":14267,\"aby\":14268,\"Ġextends\":14269,\"Ġoath\":14270,\"bow\":14271,\"ĠRivera\":14272,\"Jan\":14273,\"ĠImran\":14274,\"Ġforests\":14275,\"ĠShel\":14276,\"ĠBrun\":14277,\"Ġaerial\":14278,\"ĠNOW\":14279,\"PAR\":14280,\"Ġbeverages\":14281,\"ettel\":14282,\"Ġfragile\":14283,\"Ġcodes\":14284,\"Į\":14285,\"abel\":14286,\"Watch\":14287,\"road\":14288,\"Ġdismissal\":14289,\"ĠRosa\":14290,\"Ġcrunch\":14291,\"²\":14292,\"Ġinnovations\":14293,\"Ġhabitat\":14294,\"Ġforefront\":14295,\"ĠKoch\":14296,\"ĠChevrolet\":14297,\"Ġwheelchair\":14298,\"Ġconsiderably\":14299,\"Ġexpenditures\":14300,\"Ġtexts\":14301,\"Ġprompt\":14302,\"Ġskating\":14303,\"Ġpetroleum\":14304,\"ĠICC\":14305,\"Ġvit\":14306,\"fit\":14307,\"Ġprolonged\":14308,\"ĠLucy\":14309,\"Ġcho\":14310,\"Ġrocked\":14311,\"ĠBrom\":14312,\"Ġfreed\":14313,\"Ġyours\":14314,\"ĠEden\":14315,\"Ġmonitored\":14316,\"asted\":14317,\"Ġoversees\":14318,\"ieri\":14319,\"Ġideology\":14320,\"ĠFine\":14321,\"tering\":14322,\"Top\":14323,\"Ġdamp\":14324,\"uta\":14325,\"Ġlethal\":14326,\"Ġpurple\":14327,\"udge\":14328,\"ĠChemical\":14329,\"ĠPetersburg\":14330,\"Ġwarns\":14331,\"Ġcollectively\":14332,\"Ġâ\":14333,\"Ġplaintiffs\":14334,\"ĠBoris\":14335,\"Ġsheep\":14336,\"oves\":14337,\"ĠAuthor\":14338,\"Ġcampuses\":14339,\"Ġdestroying\":14340,\"Ġgloves\":14341,\"Ġcease\":14342,\"Ġdelegates\":14343,\"Ġpreceded\":14344,\"realDonaldTrump\":14345,\"Ġforwards\":14346,\"erton\":14347,\"ĠBuzzFeed\":14348,\"Ġoccupation\":14349,\"ĠLegion\":14350,\"Ġstir\":14351,\"Ġshale\":14352,\"Ġterrific\":14353,\"Ġnewborn\":14354,\"Ġstandoff\":14355,\"OWN\":14356,\"Ġmuscles\":14357,\"ĠHerman\":14358,\"ĠLiz\":14359,\"ĠExperience\":14360,\"ĠSuccess\":14361,\"ĠHispanic\":14362,\"ĠCCTV\":14363,\"Ġcomplement\":14364,\"ĠBing\":14365,\"Ġprem\":14366,\"ĠJohannes\":14367,\"Ġdent\":14368,\"itar\":14369,\"ĠHein\":14370,\"ĠNicola\":14371,\"Ġconcludes\":14372,\"ĠKhal\":14373,\"Ġparish\":14374,\"Ġshaking\":14375,\"ĠSchw\":14376,\"mod\":14377,\"ĠLil\":14378,\"Ã±a\":14379,\"ĠBog\":14380,\"ĠFight\":14381,\"Ġgre\":14382,\"Ġfel\":14383,\"Ġheal\":14384,\"err\":14385,\"TM\":14386,\"airo\":14387,\"health\":14388,\"Ġswings\":14389,\"Ġtier\":14390,\"anka\":14391,\"ribune\":14392,\"emouth\":14393,\"ĠBloom\":14394,\"Ġowing\":14395,\"Tech\":14396,\"Ġdough\":14397,\"Ġbatch\":14398,\"ĠLion\":14399,\"ĠZamb\":14400,\"Ġcrashing\":14401,\"ĠXL\":14402,\"ppers\":14403,\"ĠDoctors\":14404,\"ĠSor\":14405,\"video\":14406,\"Ġcigarettes\":14407,\"ĠBoxing\":14408,\"Ġconstitute\":14409,\"Ġconcentrate\":14410,\"ĠArmenian\":14411,\"Ġsemester\":14412,\"position\":14413,\"emic\":14414,\"ĠNYC\":14415,\"ĠCampus\":14416,\"Ġalternate\":14417,\"Ġexped\":14418,\"Ġpublishers\":14419,\"2015\":14420,\"Ġunanimous\":14421,\"ĠPrevious\":14422,\"Ġwellness\":14423,\"ĠCreative\":14424,\"edy\":14425,\"AGE\":14426,\"ĠCavs\":14427,\"Ġ1978\":14428,\"Ġfu\":14429,\"ĠTata\":14430,\"ĠChoice\":14431,\"Ġwoes\":14432,\"ĠCable\":14433,\"Ġ~\":14434,\"ĠGem\":14435,\"Ġconsolidated\":14436,\"ĠManitoba\":14437,\"Cloud\":14438,\"Ġrounded\":14439,\"ĠVentura\":14440,\"Ġshark\":14441,\"Ġdresses\":14442,\"Ġtraction\":14443,\"eda\":14444,\"Ġdiv\":14445,\"Ġdental\":14446,\"Wh\":14447,\"ĠGig\":14448,\"ĠBoyd\":14449,\"ĠTransit\":14450,\"Ġtelevised\":14451,\"SON\":14452,\"ĠVince\":14453,\"Ġcloses\":14454,\"apt\":14455,\"ĠWheeler\":14456,\"ĠTyson\":14457,\"Ġforensic\":14458,\"Ġpunished\":14459,\"Ġseas\":14460,\"Ġnavigation\":14461,\"Ġprecedent\":14462,\"Ġextremist\":14463,\"Ġcomposite\":14464,\"PO\":14465,\"Ġsurvivor\":14466,\"ĠVale\":14467,\"gars\":14468,\"HT\":14469,\"ĠRiyadh\":14470,\"Ġrevival\":14471,\"ĠPayne\":14472,\"Ġcollaborative\":14473,\"ĠCustomers\":14474,\"ĠPf\":14475,\"Ġproves\":14476,\"erve\":14477,\"Ġelev\":14478,\"ĠPaper\":14479,\"Ġchore\":14480,\"Ġthriller\":14481,\"Ġstraw\":14482,\"cock\":14483,\"Gu\":14484,\"Ġaligned\":14485,\"ĠChronicle\":14486,\"Ġshouting\":14487,\"Ġ1976\":14488,\"Ġlightning\":14489,\"Ġworlds\":14490,\"ĠOpening\":14491,\"enton\":14492,\"ĠAna\":14493,\"ĠGol\":14494,\"ĠTechn\":14495,\"lis\":14496,\"Ġorientation\":14497,\"ĠArri\":14498,\"ĠPG\":14499,\"ross\":14500,\"Ġsank\":14501,\"LOS\":14502,\"ĠAllison\":14503,\"Ġsmiles\":14504,\"USD\":14505,\"Ġkits\":14506,\"Bar\":14507,\"ĠBri\":14508,\"Ġounces\":14509,\"ĠNielsen\":14510,\"eno\":14511,\"Ġ109\":14512,\"Ġnorms\":14513,\"Ġskip\":14514,\"180\":14515,\"Ġmonitors\":14516,\"2012\":14517,\"Ġincorporate\":14518,\"Ġmechanisms\":14519,\"ĠHack\":14520,\"ĠBomb\":14521,\"ĠGavin\":14522,\"ĠNatalie\":14523,\"Ġdiscusses\":14524,\"Ġassembled\":14525,\"Ġcognitive\":14526,\"owner\":14527,\"Ġgenuinely\":14528,\"Ġdisappear\":14529,\"ĠAK\":14530,\"Ġstal\":14531,\"Ġsoup\":14532,\"ĠFinn\":14533,\"Ġcares\":14534,\"Ġfinest\":14535,\"Ġtuned\":14536,\"ende\":14537,\"ĠStefan\":14538,\"Ġaccompanying\":14539,\"Ã®\":14540,\"Maybe\":14541,\"Ġoffender\":14542,\"TT\":14543,\"Ġ212\":14544,\"Ġvolleyball\":14545,\"needed\":14546,\"Ġquo\":14547,\"Ġdim\":14548,\"ĠHistorical\":14549,\"ĠLance\":14550,\"gmail\":14551,\"ĠGate\":14552,\"Ġdemonstrators\":14553,\"Ġdy\":14554,\"cia\":14555,\"ĠSteele\":14556,\"ĠJoan\":14557,\"ĠKerala\":14558,\"KA\":14559,\"ĠElectoral\":14560,\"Ġpaths\":14561,\"Ã¸\":14562,\"Ne\":14563,\"Ġaccepts\":14564,\"Ġlowering\":14565,\"Ġportions\":14566,\"ĠValencia\":14567,\"Ġfestivals\":14568,\"Ġgeneric\":14569,\"usk\":14570,\"ĠVernon\":14571,\"ĠOrioles\":14572,\"Ġrenewal\":14573,\"Ġbelonged\":14574,\"Ġbreathe\":14575,\"Ġ220\":14576,\"Ġrecruited\":14577,\"Ġlogic\":14578,\"Ġrecreation\":14579,\"Ġverbal\":14580,\"ĠHaz\":14581,\"double\":14582,\"Ġfavourites\":14583,\"Ġfundamentals\":14584,\"ĠSoc\":14585,\"360\":14586,\"SO\":14587,\"Ġalerted\":14588,\"Ġbriefed\":14589,\"ĠBruno\":14590,\"Ġseating\":14591,\"Ġfreight\":14592,\"ĠAmer\":14593,\"Ġwished\":14594,\"table\":14595,\"growth\":14596,\"ĠWent\":14597,\"Ġhilarious\":14598,\"Ġthroat\":14599,\"bet\":14600,\"gon\":14601,\"Ġample\":14602,\"hee\":14603,\"ĠHood\":14604,\"ĠIceland\":14605,\"ĠAnkara\":14606,\"iang\":14607,\"Ġpracticing\":14608,\"azer\":14609,\"Ġleaf\":14610,\"Ġhottest\":14611,\"Ġmarginal\":14612,\"Ġrevelations\":14613,\"ĠPrices\":14614,\"ĠLar\":14615,\"times\":14616,\"Ġhandles\":14617,\"ĠNaz\":14618,\"Ġinstitute\":14619,\"Ġtranslate\":14620,\"ĠJP\":14621,\"Ġsoared\":14622,\"Ġconsume\":14623,\"ĠTap\":14624,\"ĠCelebrity\":14625,\"ĠMayweather\":14626,\"ĠOracle\":14627,\"Ġmor\":14628,\"ANA\":14629,\"Ġpaperwork\":14630,\"aste\":14631,\"Ġdil\":14632,\"Ġdecorated\":14633,\"Ġpromotional\":14634,\"ĠMerrill\":14635,\"Ġappliances\":14636,\"ĠCOP\":14637,\"Ġlips\":14638,\"ĠBrennan\":14639,\"ĠMile\":14640,\"ĠNetworks\":14641,\"ĠComment\":14642,\"ĠIb\":14643,\"ĠAgg\":14644,\"IDE\":14645,\"Ġinitiate\":14646,\"Ġknockout\":14647,\"Ġbargain\":14648,\"Ġaccordingly\":14649,\"bee\":14650,\"ĠGerald\":14651,\"Ġproblematic\":14652,\"Ġtrap\":14653,\"Ġfinalists\":14654,\"addy\":14655,\"would\":14656,\"Ġstrictly\":14657,\"ĠRamsey\":14658,\"Ġdownward\":14659,\"Ġextract\":14660,\"Ġfamed\":14661,\"ĠOUT\":14662,\"Ġinduct\":14663,\"ĠAuckland\":14664,\"Ġpoetry\":14665,\"mos\":14666,\"ĠGuinea\":14667,\"management\":14668,\"ohan\":14669,\"ĠGuide\":14670,\"aily\":14671,\"umping\":14672,\"Ġenacted\":14673,\"ĠEye\":14674,\"vision\":14675,\"umi\":14676,\"aped\":14677,\"Ġbicycle\":14678,\"ĠHouth\":14679,\"ĠNAS\":14680,\"Ġtapped\":14681,\"wer\":14682,\"otti\":14683,\"EA\":14684,\"Ġsurprises\":14685,\"ĠUpdate\":14686,\"ĠPun\":14687,\"ĠMiz\":14688,\"ĠOro\":14689,\"Ġcostumes\":14690,\"title\":14691,\"Ġsurviving\":14692,\"According\":14693,\"themed\":14694,\"ĠPeoples\":14695,\"Se\":14696,\"Ġassociations\":14697,\"hett\":14698,\"Time\":14699,\"Ġessay\":14700,\"Ġmu\":14701,\"ĠScore\":14702,\"ĠSpani\":14703,\"ĠSEE\":14704,\"Ġmales\":14705,\"Ġrage\":14706,\"EU\":14707,\"ĠYellow\":14708,\"rupt\":14709,\"Ġapparel\":14710,\"Ġsweat\":14711,\"Ġnearest\":14712,\"zman\":14713,\"Ġanticipation\":14714,\"Ġinjuring\":14715,\"Ġousted\":14716,\"chan\":14717,\"ĠAlert\":14718,\"Ġber\":14719,\"atal\":14720,\"Com\":14721,\"Ġ04\":14722,\"Ġafterward\":14723,\"edge\":14724,\"ĠBooker\":14725,\"lex\":14726,\"ĠWhole\":14727,\"Ġtoughest\":14728,\"ĠMaharashtra\":14729,\"lier\":14730,\"ĠTennis\":14731,\"Ġhandy\":14732,\"ĠMetal\":14733,\"ĠiTunes\":14734,\"ĠDiscovery\":14735,\"Ġcompassion\":14736,\"ĠLIVE\":14737,\"Ġeconomically\":14738,\"Ġendangered\":14739,\"GO\":14740,\"Ġmound\":14741,\"word\":14742,\"ĠTouch\":14743,\"ogo\":14744,\"Ġincomes\":14745,\"when\":14746,\"ĠAside\":14747,\"Ġscandals\":14748,\"Ġfunctionality\":14749,\"ĠAer\":14750,\"Ġcouncils\":14751,\"Ġdenial\":14752,\"140\":14753,\"Ġimplied\":14754,\"Ġoutfits\":14755,\"Ġsuited\":14756,\"Ġ1973\":14757,\"ĠPizza\":14758,\"Ġdebates\":14759,\"record\":14760,\"Ġhype\":14761,\"ĠRus\":14762,\"ĠRobbie\":14763,\"Ġtouted\":14764,\"ĠSharp\":14765,\"Ġbeings\":14766,\"Ġslavery\":14767,\"encies\":14768,\"ĠRooney\":14769,\"Ġnan\":14770,\"Ġraids\":14771,\"Ġinstructor\":14772,\"Market\":14773,\"Ġshook\":14774,\"Ġdeliberate\":14775,\"ĠNorthwestern\":14776,\"ĠEss\":14777,\"Ġwhatsoever\":14778,\"ĠConfederate\":14779,\"YS\":14780,\"ĠCameroon\":14781,\"ĠFlip\":14782,\"Yeah\":14783,\"Ġwashing\":14784,\"mand\":14785,\"ĠLex\":14786,\"Ġissuance\":14787,\"Ġniche\":14788,\"Ġfold\":14789,\"ĠWendy\":14790,\"Ġhy\":14791,\"Ġbucket\":14792,\"ĠVW\":14793,\"ĠCairo\":14794,\"ĠSK\":14795,\"ĠKang\":14796,\"Ġintake\":14797,\"Ġhills\":14798,\"anz\":14799,\"Â©\":14800,\"ugu\":14801,\"ĠFortunately\":14802,\"ĠMarqu\":14803,\"Ġimprisonment\":14804,\"oking\":14805,\"Ġdistributors\":14806,\"zie\":14807,\"Ġstip\":14808,\"ĠWire\":14809,\"Ġcouncillors\":14810,\"Ġsue\":14811,\"ĠRegardless\":14812,\"ĠEnc\":14813,\"Ġbaking\":14814,\"ĠVenture\":14815,\"Ġintriguing\":14816,\"Ġupheld\":14817,\"ĠActive\":14818,\"Ġgenes\":14819,\"ĠDawson\":14820,\"ĠPreviously\":14821,\"ĠRac\":14822,\"Ġmetric\":14823,\"Files\":14824,\"ĠiPhones\":14825,\"ĠWelcome\":14826,\"Ġburns\":14827,\"ĠScreen\":14828,\"ashes\":14829,\"ĠApr\":14830,\"Ġtheories\":14831,\"san\":14832,\"ĠRenault\":14833,\"ĠSinger\":14834,\"Ġfounders\":14835,\"Russian\":14836,\"ĠBelfast\":14837,\"Ġimagined\":14838,\"ĠPlanet\":14839,\"ĠCatalan\":14840,\"ĠRochester\":14841,\"Ġevolve\":14842,\"ĠOT\":14843,\"Ġpassword\":14844,\"Ġhomelessness\":14845,\"Ġbacklog\":14846,\"Ġpresenter\":14847,\"Ġfal\":14848,\"ISH\":14849,\"ĠEM\":14850,\"icked\":14851,\"Ġunlock\":14852,\"city\":14853,\"Ġnegotiation\":14854,\"Ġdancers\":14855,\"dan\":14856,\"ĠCOL\":14857,\"VC\":14858,\"boat\":14859,\"Ġoverly\":14860,\"deal\":14861,\"lander\":14862,\"Ġdiss\":14863,\"ICS\":14864,\"Ġfifty\":14865,\"Ġowe\":14866,\"Ġprisons\":14867,\"ifications\":14868,\"wo\":14869,\"ĠAu\":14870,\"Ġapiece\":14871,\"ĠCourtney\":14872,\"Ġ1975\":14873,\"Ġsurpass\":14874,\"Ġidentities\":14875,\"Ġintegral\":14876,\"Ġdocumentation\":14877,\"Ġelegant\":14878,\"ĠIg\":14879,\"Ġdear\":14880,\"Ġ113\":14881,\"ĠGupta\":14882,\"Ġcontentious\":14883,\"rish\":14884,\"Ġclues\":14885,\"Ġadditions\":14886,\"Ġep\":14887,\"rus\":14888,\"Ġcentered\":14889,\"ĠPhillies\":14890,\"father\":14891,\"Ġborough\":14892,\"Ġbuttons\":14893,\"Ġdeported\":14894,\"ĠREC\":14895,\"ĠAlready\":14896,\"eh\":14897,\"hur\":14898,\"Ġupbeat\":14899,\"omen\":14900,\"Ġdetailing\":14901,\"Ġwr\":14902,\"Ġvaried\":14903,\"ĠEconomics\":14904,\"Ġensures\":14905,\"ĠCivic\":14906,\"Ġunpaid\":14907,\"sold\":14908,\"ĠHil\":14909,\"ĠMult\":14910,\"ĠRising\":14911,\"ĠMini\":14912,\"Ġneuro\":14913,\"Ġpenal\":14914,\"Ġneighbour\":14915,\"ĠChavez\":14916,\"Ġjew\":14917,\"ĠVIP\":14918,\"Connor\":14919,\"ĠTalking\":14920,\"Ġcorrection\":14921,\"Ġstandpoint\":14922,\"roads\":14923,\"ĠWool\":14924,\"Ġverification\":14925,\"Ġmic\":14926,\"olf\":14927,\"Ġexemption\":14928,\"Ġfilter\":14929,\"Ġballoon\":14930,\"leases\":14931,\"ician\":14932,\"ĠSpr\":14933,\"Ġtoe\":14934,\"Ġunconstitutional\":14935,\"Ġmanslaughter\":14936,\"Ġtossed\":14937,\"ĠMeg\":14938,\"ATIONS\":14939,\"ACK\":14940,\"ĠRouge\":14941,\"ĠHansen\":14942,\"ĠHook\":14943,\"Out\":14944,\"ĠHorse\":14945,\"ĠBath\":14946,\"ĠAlways\":14947,\"Ġincorporated\":14948,\"Ġconjunction\":14949,\"ĠFit\":14950,\"Ġexamining\":14951,\"Ġwallet\":14952,\"Ġensured\":14953,\"Ġacclaimed\":14954,\"ippers\":14955,\"Ġbeneficiaries\":14956,\"Ġunexpectedly\":14957,\"Ġexploit\":14958,\"ĠWillie\":14959,\"Ġcomb\":14960,\"ĠWalton\":14961,\"rica\":14962,\"icky\":14963,\"Ġate\":14964,\"ĠPadres\":14965,\"Ġrib\":14966,\"Ġsnacks\":14967,\"ĠFernandez\":14968,\"ĠMachine\":14969,\"ction\":14970,\"Ġillnesses\":14971,\"ĠHoffman\":14972,\"ĠSpaceX\":14973,\"Ġju\":14974,\"Ġswift\":14975,\"Ġembark\":14976,\"ĠRailway\":14977,\"Ġmeasuring\":14978,\"agers\":14979,\"arsh\":14980,\"Ġessence\":14981,\"angle\":14982,\"Ġolive\":14983,\"ĠCommander\":14984,\"iggs\":14985,\"Ġrewarded\":14986,\"Ġdispatched\":14987,\"Ġplayground\":14988,\"Â½\":14989,\"ĠProgramme\":14990,\"Ġstudios\":14991,\"Ġskeptical\":14992,\"ĠOlymp\":14993,\"ĠKeys\":14994,\"ĠSunshine\":14995,\"amba\":14996,\"ĠDonna\":14997,\"Ġlightly\":14998,\"Ġobtaining\":14999,\"Ġpoisoning\":15000,\"Ġaz\":15001,\"Ġ1972\":15002,\"Ġunconscious\":15003,\"ECT\":15004,\"Ġlied\":15005,\"ĠKaz\":15006,\"Ġ06\":15007,\"ĠMoving\":15008,\"Ġnum\":15009,\"oral\":15010,\"Ġassessments\":15011,\"Ġscholarships\":15012,\"Ġevacuate\":15013,\"ĠSunni\":15014,\"Ġquake\":15015,\"Ġfort\":15016,\"ques\":15017,\"ĠAlonso\":15018,\"Ġthread\":15019,\"Ġsqueeze\":15020,\"arat\":15021,\"oly\":15022,\"ĠAlphabet\":15023,\"uting\":15024,\"icio\":15025,\"ĠRetirement\":15026,\"ither\":15027,\"Ġasleep\":15028,\"Ġpairs\":15029,\"Ġmanufacture\":15030,\"ĠHazard\":15031,\"Ġsidewalk\":15032,\"Ġwears\":15033,\"ĠCraft\":15034,\"emen\":15035,\"ieth\":15036,\"Ġbypass\":15037,\"ĠLancaster\":15038,\"Ġflour\":15039,\"charge\":15040,\"ĠCLICK\":15041,\"Ġpotatoes\":15042,\"ĠKarachi\":15043,\"Ġvalley\":15044,\"Ġsights\":15045,\"Ġfallout\":15046,\"ords\":15047,\"BN\":15048,\"Ġsunshine\":15049,\"Ġundertaken\":15050,\"Ġcontestants\":15051,\"Ġaccomplishments\":15052,\"Ġconditioning\":15053,\"Ġcel\":15054,\"ĠHalifax\":15055,\"Ġaccent\":15056,\"***\":15057,\"Ġpitchers\":15058,\"Ġadopting\":15059,\"Ġjustices\":15060,\"Ġrip\":15061,\"ince\":15062,\"Ġelimination\":15063,\"Ġaerospace\":15064,\"ĠBeer\":15065,\"ĠBasin\":15066,\"Ġunwanted\":15067,\"goers\":15068,\"isco\":15069,\"ĠTwin\":15070,\"ĠDesert\":15071,\"rix\":15072,\"Ġdarkness\":15073,\"ĠDunn\":15074,\"City\":15075,\"pop\":15076,\"Ġ1969\":15077,\"ataka\":15078,\"Ġtal\":15079,\"Ġautism\":15080,\"ĠMcLaren\":15081,\"ĠUEFA\":15082,\"Ġclassrooms\":15083,\"ĠLeave\":15084,\"Americans\":15085,\"las\":15086,\"Ġqui\":15087,\"Ġundefeated\":15088,\"otto\":15089,\"ĠNRA\":15090,\"ĠPorsche\":15091,\"Ġnuts\":15092,\"oys\":15093,\"ĠMethodist\":15094,\"Ġatt\":15095,\"Ġtweeting\":15096,\"children\":15097,\"eller\":15098,\"Ġinquiries\":15099,\"Ġmillennials\":15100,\"ĠWembley\":15101,\"INS\":15102,\"Ġautopsy\":15103,\"ĠElon\":15104,\"ĠHicks\":15105,\"ugg\":15106,\"Ġwreck\":15107,\"ĠComcast\":15108,\"Ġstones\":15109,\"public\":15110,\"ĠKem\":15111,\"bedroom\":15112,\"ļ\":15113,\"itated\":15114,\"Ġsemic\":15115,\"uman\":15116,\"Cal\":15117,\"ANN\":15118,\"ĠGaz\":15119,\"Ġundisclosed\":15120,\"ĠPlanned\":15121,\"ĠYale\":15122,\"ĠIST\":15123,\"lies\":15124,\"ĠStanding\":15125,\"Ġrelieved\":15126,\"EO\":15127,\"Ġgraduating\":15128,\"park\":15129,\"ĠâĢķ\":15130,\"Ġpensions\":15131,\"rave\":15132,\"ĠWonder\":15133,\"AZ\":15134,\"Ġcosting\":15135,\"Ġeditors\":15136,\"Ġtotaled\":15137,\"Ġspacecraft\":15138,\"meter\":15139,\"Ġ02\":15140,\"ĠNikki\":15141,\"sworth\":15142,\"ĠCrit\":15143,\"asha\":15144,\"Ġknees\":15145,\"Ġhats\":15146,\"uity\":15147,\"ĠPanther\":15148,\"Ġtan\":15149,\"ĠBuzz\":15150,\"ĠGlad\":15151,\"ĠPleasant\":15152,\"SM\":15153,\"Ġtricks\":15154,\"Ġplac\":15155,\"ĠDanielle\":15156,\"Ġours\":15157,\"Ġwashed\":15158,\"haven\":15159,\"Ġdrain\":15160,\"ĠUttar\":15161,\"Ġapple\":15162,\"Ġjunk\":15163,\"Ġturkey\":15164,\"ĠDug\":15165,\"Ġdiplomacy\":15166,\"Ġempire\":15167,\"Ġpinch\":15168,\"Ġferry\":15169,\"ĠDustin\":15170,\"Ġ03\":15171,\"Ġelder\":15172,\"Everything\":15173,\"ĠProgressive\":15174,\"ution\":15175,\"VI\":15176,\"dam\":15177,\"Ġlever\":15178,\"ĠAustralians\":15179,\"Ġconsequence\":15180,\"itan\":15181,\"Ġcondemn\":15182,\"Ġneg\":15183,\"ĠOverview\":15184,\"Ġsuccesses\":15185,\"Ġprobable\":15186,\"ĠMirror\":15187,\"mor\":15188,\"verse\":15189,\"Ġevaluating\":15190,\"ĠBes\":15191,\"Ġimm\":15192,\"Ġharness\":15193,\"Ġresilient\":15194,\"ĠBuild\":15195,\"Ġstraightforward\":15196,\"ADE\":15197,\"Ġgrandparents\":15198,\"Ġmarched\":15199,\"ĠKiev\":15200,\"Ġchiefs\":15201,\"oha\":15202,\"Ġvest\":15203,\"kn\":15204,\"enda\":15205,\"ĠSev\":15206,\"Ġbatters\":15207,\"ĠJos\":15208,\"ĠQue\":15209,\"ĠCourse\":15210,\"ĠCorner\":15211,\"ĠMess\":15212,\"Ġmourn\":15213,\"keepers\":15214,\"ĠRegina\":15215,\"Everybody\":15216,\"Ġtrajectory\":15217,\"Ġdefenseman\":15218,\"ĠArticles\":15219,\"Ġspur\":15220,\"ĠPhD\":15221,\"Ġpipes\":15222,\"Ġduck\":15223,\"Ġcombining\":15224,\"ĠHit\":15225,\"ĠGeorgetown\":15226,\"ĠBee\":15227,\"Cor\":15228,\"Ġcomposition\":15229,\"Ġconnects\":15230,\"ĠMARK\":15231,\"taker\":15232,\"Ġcertainty\":15233,\"Ġhefty\":15234,\"ĠHezbollah\":15235,\"ĠShip\":15236,\"Ġmalicious\":15237,\"AI\":15238,\"Ġbits\":15239,\"Ġstyl\":15240,\"Ġimpaired\":15241,\"ĠCBI\":15242,\"Despite\":15243,\"othe\":15244,\"ĠRyder\":15245,\"ĠAlf\":15246,\"ifa\":15247,\"Ind\":15248,\"Ġblaming\":15249,\"ĠToledo\":15250,\"EW\":15251,\"ĠEssex\":15252,\"iated\":15253,\"ĠAberdeen\":15254,\"ANCE\":15255,\"Ġpossess\":15256,\"Ġsuperhero\":15257,\"Ġoverhead\":15258,\"quet\":15259,\"ĠRicky\":15260,\"Ġdock\":15261,\"ĠTelecom\":15262,\"Ġshelf\":15263,\"³\":15264,\"Ġmaritime\":15265,\"Ġportrayed\":15266,\"ĠYesterday\":15267,\"Ġcollided\":15268,\"Ġcookies\":15269,\"ĠCul\":15270,\"Ġindexes\":15271,\"Ġnaval\":15272,\"oval\":15273,\"105\":15274,\"ĠWeber\":15275,\"chief\":15276,\"arma\":15277,\"ĠRey\":15278,\"Ġauditor\":15279,\"ĠMarion\":15280,\"ĠMartha\":15281,\"ĠSally\":15282,\"Ġsedan\":15283,\"ĠAlison\":15284,\"nce\":15285,\"Es\":15286,\"ĠParade\":15287,\"Ġpharmacy\":15288,\"ĠKre\":15289,\"loe\":15290,\"cks\":15291,\"Ġmitigate\":15292,\"Ġdesigning\":15293,\"Ġ2024\":15294,\"Ġportable\":15295,\"Ġimproves\":15296,\"ĠAMD\":15297,\"Ġexcluded\":15298,\"CON\":15299,\"ĠOscars\":15300,\"Ġfixtures\":15301,\"comb\":15302,\"ĠBerg\":15303,\"Ġbother\":15304,\"Ġboring\":15305,\"Ġobservation\":15306,\"ĠCad\":15307,\"Ġrecordings\":15308,\"ĠCultural\":15309,\"Ġweaken\":15310,\"Ġaccuse\":15311,\"ĠAbd\":15312,\"abor\":15313,\"115\":15314,\"uffle\":15315,\"Ġhighways\":15316,\"atham\":15317,\"empt\":15318,\"ĠDeer\":15319,\"ĠEDT\":15320,\"ĠWait\":15321,\"athan\":15322,\"Ġaccumulated\":15323,\"Ġguilt\":15324,\"Ġexempt\":15325,\"Ġdiluted\":15326,\"ĠJamal\":15327,\"Ġshit\":15328,\"cross\":15329,\"Ġeve\":15330,\"Ġshirts\":15331,\"Ġsatisfy\":15332,\"ĠPaulo\":15333,\"AH\":15334,\"sic\":15335,\"ĠChloe\":15336,\"ĠCities\":15337,\"ĠSwansea\":15338,\"Ġprecision\":15339,\"ĠTracy\":15340,\"ping\":15341,\"Ġcontinually\":15342,\"Ġdemographic\":15343,\"Ġcliff\":15344,\"Ġjaw\":15345,\"isted\":15346,\"ĠDevelop\":15347,\"ĠAJ\":15348,\"Ġaisle\":15349,\"ĠLionel\":15350,\"Ġpredominantly\":15351,\"Ġmel\":15352,\"Ġlifelong\":15353,\"hs\":15354,\"Ġshouted\":15355,\"lad\":15356,\"Ġdest\":15357,\"Ġpacks\":15358,\"ĠKath\":15359,\"ĠCruise\":15360,\"fired\":15361,\"oder\":15362,\"hua\":15363,\"Ġgoodbye\":15364,\"Ġinterfere\":15365,\"eca\":15366,\"ĠrÃ©\":15367,\"atum\":15368,\"itas\":15369,\"ĠLodge\":15370,\"ĠWald\":15371,\"Ġmidday\":15372,\"umble\":15373,\"asting\":15374,\"©\":15375,\"ĠLeg\":15376,\"ĠNepal\":15377,\"Ġchased\":15378,\"idge\":15379,\"Ġconv\":15380,\"Ġfraudulent\":15381,\"Ġopera\":15382,\"Ġshr\":15383,\"ĠUniverse\":15384,\"ĠJerome\":15385,\"Ġ1977\":15386,\"ĠDancing\":15387,\"ĠRS\":15388,\"±\":15389,\"eks\":15390,\"Ġchic\":15391,\"Ġpunish\":15392,\"Ġpropose\":15393,\"arin\":15394,\"ĠChop\":15395,\"ĠAhead\":15396,\"ĠGallagher\":15397,\"ĠBangkok\":15398,\"ĠShelby\":15399,\"ĠNS\":15400,\"Ġcheek\":15401,\"onia\":15402,\"Ġrelegation\":15403,\"ĠHind\":15404,\"ĠCory\":15405,\"Ġfingerprint\":15406,\"Ġstrive\":15407,\"Ġmm\":15408,\"igs\":15409,\"Ġholy\":15410,\"Ġfavored\":15411,\"ĠSomeone\":15412,\"ĠLatino\":15413,\"ĠPatt\":15414,\"Ġchallenger\":15415,\"ĠCotton\":15416,\"Sw\":15417,\"itten\":15418,\"ĠXI\":15419,\"ĠStat\":15420,\"ĠDIS\":15421,\"Ġautomakers\":15422,\"Ġevaluated\":15423,\"ĠArc\":15424,\"Ġpersuade\":15425,\"Af\":15426,\"Ġreunited\":15427,\"Ġabs\":15428,\"Ġbride\":15429,\"Ġpurely\":15430,\"uce\":15431,\"uded\":15432,\"Ġsettling\":15433,\"Ġlodged\":15434,\"Ġfixing\":15435,\"Ġsuccession\":15436,\"ĠAlfred\":15437,\"ĠAlvarez\":15438,\"mac\":15439,\"ĠFont\":15440,\"Ġcontra\":15441,\"affle\":15442,\"Ġcopied\":15443,\"Ġmasses\":15444,\"ĠElections\":15445,\"ĠThan\":15446,\"Ġsoaring\":15447,\"jay\":15448,\"Ġsuing\":15449,\"Ġconcentrated\":15450,\"Ġconvey\":15451,\"Ġ240\":15452,\"gs\":15453,\"ĠNeal\":15454,\"Ġnasty\":15455,\"ĠLB\":15456,\"odi\":15457,\"ĠSergei\":15458,\"Ġthumb\":15459,\"Ġservants\":15460,\"Ġrevelation\":15461,\"Ġdischarge\":15462,\"ĠBright\":15463,\"ĠBent\":15464,\"ĠChrysler\":15465,\"mill\":15466,\"ĠImagine\":15467,\"Ġreceptions\":15468,\"Ġpersonalities\":15469,\"Ġsilly\":15470,\"ĠLoc\":15471,\"ĠZero\":15472,\"HI\":15473,\"rice\":15474,\"Ġgar\":15475,\"far\":15476,\"enh\":15477,\"ĠBiden\":15478,\"ĠEntreprene\":15479,\"Ġassumption\":15480,\"Ġnicely\":15481,\"ĠEither\":15482,\"|\":15483,\"ĠNW\":15484,\"ĠKens\":15485,\"ĠNolan\":15486,\"Ġowning\":15487,\"atures\":15488,\"ĠPastor\":15489,\"ĠRegistration\":15490,\"Ġexperiments\":15491,\"Ġassurance\":15492,\"Ġhashtag\":15493,\"oint\":15494,\"ĠBin\":15495,\"Ġqualification\":15496,\"center\":15497,\"Ġausterity\":15498,\"ĠPers\":15499,\"Ġscoop\":15500,\"Ġpros\":15501,\"ĠFields\":15502,\"Ġfur\":15503,\"ĠJas\":15504,\"Ġplanting\":15505,\"security\":15506,\"ĠTrain\":15507,\"ĠKathy\":15508,\"demand\":15509,\"ĠLev\":15510,\"Ġtut\":15511,\"tier\":15512,\"QU\":15513,\"Ġexploitation\":15514,\"Ġignoring\":15515,\"ĠSex\":15516,\"Ġadapted\":15517,\"Ġdisastrous\":15518,\"Ġempower\":15519,\"Ġcreators\":15520,\"ĠLay\":15521,\"ĠDragon\":15522,\"ĠWyn\":15523,\"Ġ1974\":15524,\"acious\":15525,\"performance\":15526,\"ĠTiffany\":15527,\"isting\":15528,\"Ġindividually\":15529,\"ĠLeading\":15530,\"ĠSask\":15531,\"Ġcatastrophic\":15532,\"Ġpunched\":15533,\"ĠVienna\":15534,\"Ġsurgical\":15535,\"Gr\":15536,\"odo\":15537,\"Ġgem\":15538,\"ĠMinority\":15539,\"Ġmice\":15540,\"ĠHistoric\":15541,\"ĠKot\":15542,\"caster\":15543,\"Ġsuff\":15544,\"journal\":15545,\"Ġpresumably\":15546,\"ĠBit\":15547,\"inary\":15548,\"Ġbre\":15549,\"Ġenhancing\":15550,\"Ġgru\":15551,\"ĠRunning\":15552,\"hardt\":15553,\"Ġtroubling\":15554,\"Ġpumps\":15555,\"ĠProspect\":15556,\"etic\":15557,\"Ġmartial\":15558,\"Ġcouncillor\":15559,\"atra\":15560,\"ths\":15561,\"ĠSark\":15562,\"ĠChamp\":15563,\"scoring\":15564,\"ĠWel\":15565,\"rup\":15566,\"Ġterrifying\":15567,\"ĠCatch\":15568,\"Ġinspections\":15569,\"Ġpornography\":15570,\"bra\":15571,\"ĠKeeping\":15572,\"Ġbanker\":15573,\"angers\":15574,\"ĠCrimea\":15575,\"ĠDisclosure\":15576,\"iba\":15577,\"Ġturf\":15578,\"Ġschedules\":15579,\"ĠJorge\":15580,\"ĠAcross\":15581,\"Ġsolving\":15582,\"Ġsensation\":15583,\"ĠWW\":15584,\"cial\":15585,\"atz\":15586,\"Ġlion\":15587,\"Ġcertificates\":15588,\"itive\":15589,\"ĠWes\":15590,\"ĠPrison\":15591,\"ĠPlayStation\":15592,\"duty\":15593,\"Ġvariable\":15594,\"Ġstrangers\":15595,\"istrates\":15596,\"vs\":15597,\"Ġreigning\":15598,\"Ġsliding\":15599,\"ĠShin\":15600,\"Ġtelecommunications\":15601,\"Ġinstalling\":15602,\"Ġrecogn\":15603,\"Ġsubway\":15604,\"too\":15605,\"ĠMcKin\":15606,\"ĠStoke\":15607,\"Ġsensitivity\":15608,\"bas\":15609,\"Ġsan\":15610,\"Ġ(-\":15611,\"ĠSuarez\":15612,\"Ġaverages\":15613,\"ammu\":15614,\"ĠFen\":15615,\"Ġrefined\":15616,\"outh\":15617,\"Ġcob\":15618,\"ĠLaz\":15619,\"essa\":15620,\"Ġpositioning\":15621,\"Three\":15622,\"Ġoils\":15623,\"Ġassaults\":15624,\"Ġcompanion\":15625,\"ĠFlash\":15626,\"ĠMam\":15627,\"ĠTill\":15628,\"Ġblues\":15629,\"ĠJae\":15630,\"ĠPier\":15631,\"Ġbedrooms\":15632,\"ĠHawkins\":15633,\"ĠCornell\":15634,\"Ġanswering\":15635,\"Ġsec\":15636,\"Ġrecognizes\":15637,\"Red\":15638,\"ĠJamaica\":15639,\"Ġinsurgents\":15640,\"Ġbrace\":15641,\"Ġra\":15642,\"ĠTai\":15643,\"ocation\":15644,\"ignment\":15645,\"Ġreasonably\":15646,\"inating\":15647,\"Ġbonuses\":15648,\"Ġsandwich\":15649,\"Ġinadequate\":15650,\"Ġdelicate\":15651,\"Ġadorable\":15652,\"Ġpalace\":15653,\"Ġsmallest\":15654,\"Ġpractically\":15655,\"ĠCrosby\":15656,\"Ġlevy\":15657,\"Ġlend\":15658,\"boards\":15659,\"shaped\":15660,\"Ġvulnerability\":15661,\"ĠKelley\":15662,\"Ġsponsorship\":15663,\"ract\":15664,\"Ġslew\":15665,\"Ġfederation\":15666,\"ĠLal\":15667,\"acies\":15668,\"ĠFamilies\":15669,\"Ġproposing\":15670,\"Ġhyp\":15671,\"elected\":15672,\"inkle\":15673,\"ĠSays\":15674,\"ĠApollo\":15675,\"ĠWis\":15676,\"imer\":15677,\"Ġcombines\":15678,\"Ġtim\":15679,\"ĠQuestion\":15680,\"Ġborrowers\":15681,\"Ġswiftly\":15682,\"ĠMagn\":15683,\"Ġheadphones\":15684,\"Russia\":15685,\"Ġtongue\":15686,\"Ġbye\":15687,\"nn\":15688,\"Ġseller\":15689,\"ĠWord\":15690,\"Tom\":15691,\"ĠDevin\":15692,\"ĠSurrey\":15693,\"Ġquad\":15694,\"Ġcourthouse\":15695,\"gi\":15696,\"ĠGrill\":15697,\">\":15698,\"Ġrational\":15699,\"ĠFlames\":15700,\"ĠCham\":15701,\"Ġvacuum\":15702,\"ĠRays\":15703,\"Ġescalating\":15704,\"Ġouter\":15705,\"Ġstretches\":15706,\"ĠSpeed\":15707,\"Ġnegatively\":15708,\"Ġabsorb\":15709,\"ĠAustrian\":15710,\"Ġslice\":15711,\"ĠDiet\":15712,\"Ġbun\":15713,\"Ġtactical\":15714,\"ĠCBD\":15715,\"Ġedges\":15716,\"Ġnest\":15717,\"Ġstrained\":15718,\"ulates\":15719,\"ĠTina\":15720,\"Net\":15721,\"ķ\":15722,\"ĠGos\":15723,\"God\":15724,\"White\":15725,\"Ġproudly\":15726,\"usion\":15727,\"ĠArlington\":15728,\"ĠNear\":15729,\"ĠMaxwell\":15730,\"Ġbomber\":15731,\"Ġcared\":15732,\"Ġapprovals\":15733,\"Ġexams\":15734,\"ĠEconomy\":15735,\"Ġposters\":15736,\"ĠHampton\":15737,\"ĠPere\":15738,\"ĠContract\":15739,\"Ġhoused\":15740,\"Ġinstruction\":15741,\"ĠJess\":15742,\"Ġacre\":15743,\"Ġcongestion\":15744,\"ĠGener\":15745,\"Ġdioxide\":15746,\"Ġvar\":15747,\"ĠAlexandria\":15748,\"ĠSpider\":15749,\"Ġcoins\":15750,\"Ġ225\":15751,\"Ġterritorial\":15752,\"ĠSPD\":15753,\"Ġfloat\":15754,\"null\":15755,\"Ġcalculate\":15756,\"ĠDin\":15757,\"eto\":15758,\"Ġcows\":15759,\"Ġpunct\":15760,\"Ġexpire\":15761,\"Ġkidnapped\":15762,\"Ġcou\":15763,\"Ġattitudes\":15764,\"ĠLeh\":15765,\"ĠHero\":15766,\"ĠKabul\":15767,\"Ġcubic\":15768,\"Ġdigits\":15769,\"ĠRES\":15770,\"Ġpipelines\":15771,\"icide\":15772,\"ĠSingle\":15773,\"Ġhurts\":15774,\"ĠMaz\":15775,\"ĠPak\":15776,\"Ġslate\":15777,\"Ġmultimedia\":15778,\"ADA\":15779,\"Mexico\":15780,\"ĠRelease\":15781,\"chard\":15782,\"Ġgarlic\":15783,\"ĠFletcher\":15784,\"Ġaforementioned\":15785,\"Ġ05\":15786,\"ĠParkway\":15787,\"Ġfirefighter\":15788,\"Ġcounseling\":15789,\"utions\":15790,\"Cap\":15791,\"Ġconsultants\":15792,\"ĠMeh\":15793,\"ouring\":15794,\"ĠDI\":15795,\"mic\":15796,\"phones\":15797,\"Ġencounters\":15798,\"ĠHapp\":15799,\"Ġcartoon\":15800,\"flight\":15801,\"Ġundertake\":15802,\"ĠHans\":15803,\"Ġplunge\":15804,\"ĠParenthood\":15805,\"Ġkickoff\":15806,\"ĠCelsius\":15807,\"ĠRas\":15808,\"ĠDund\":15809,\"ounce\":15810,\"Ġpurse\":15811,\"Ġmortality\":15812,\"Ġbrains\":15813,\"Ġconglomerate\":15814,\"ĠObserver\":15815,\"ĠSector\":15816,\"ĠApparently\":15817,\"Ġblank\":15818,\"iston\":15819,\"Ġweighs\":15820,\"gro\":15821,\"ĠPaw\":15822,\"ĠCOM\":15823,\"ĠPurdue\":15824,\"Ġnetted\":15825,\"ĠLinux\":15826,\"Mike\":15827,\"Ġfaithful\":15828,\"Ġmagazines\":15829,\"Ġheadquartered\":15830,\"ĠIps\":15831,\"Ġindications\":15832,\"Look\":15833,\"ĠElite\":15834,\"Ġsupreme\":15835,\"Ġchunk\":15836,\"ĠSz\":15837,\"ĠVine\":15838,\"rise\":15839,\"ĠYas\":15840,\"general\":15841,\"ĠOpera\":15842,\"Ġpriests\":15843,\"Assad\":15844,\"Ġaunt\":15845,\"Ġwhopping\":15846,\"enzie\":15847,\"Ġvegan\":15848,\"Ġinflux\":15849,\"ĠConsult\":15850,\"Ġwaiver\":15851,\"Having\":15852,\"inning\":15853,\"Ġproximity\":15854,\"Ġclassical\":15855,\"ĠIslanders\":15856,\"Ġadvertisers\":15857,\"ĠCe\":15858,\"ĠSochi\":15859,\"Ġmemoir\":15860,\"ĠPlaying\":15861,\"yers\":15862,\"Ġstud\":15863,\"Ġobservations\":15864,\"Ġadmire\":15865,\"Ġhiking\":15866,\"Ġbatter\":15867,\"Ġconfusing\":15868,\"Ġprecaution\":15869,\"kil\":15870,\"clusive\":15871,\"opoulos\":15872,\"ĠWestbrook\":15873,\"ĠTanzania\":15874,\"ĠCedar\":15875,\"usted\":15876,\"Ġdestructive\":15877,\"ĠIndies\":15878,\"osi\":15879,\"ĠAmid\":15880,\"Ġintercepted\":15881,\"Ġpartnering\":15882,\"Ġsubstances\":15883,\"ĠSuns\":15884,\"Ġpromotes\":15885,\"bird\":15886,\"Gen\":15887,\"aper\":15888,\"ĠEy\":15889,\"Ġterrain\":15890,\"Ġ1930\":15891,\"zon\":15892,\"Ġbreed\":15893,\"broken\":15894,\"uchin\":15895,\"ĠPrim\":15896,\"ĠRoland\":15897,\"Ġfitted\":15898,\"Ġprotects\":15899,\"Ġ114\":15900,\"RP\":15901,\"Ġdisrupted\":15902,\"ĠBaylor\":15903,\"oren\":15904,\"ĠKeen\":15905,\"Ġmansion\":15906,\"Ġgrassroots\":15907,\"ĠVictory\":15908,\"Ġbarn\":15909,\"Ġdepreciation\":15910,\"oped\":15911,\"immer\":15912,\"Ġgarnered\":15913,\"ĠLip\":15914,\"ĠTob\":15915,\"Ġcreatures\":15916,\"ooter\":15917,\"Ġconsortium\":15918,\"obi\":15919,\"ĠMonster\":15920,\"arks\":15921,\"turn\":15922,\"Ġsketch\":15923,\"Ġpredicting\":15924,\"Ġminimize\":15925,\"ĠEthan\":15926,\"anson\":15927,\"ĠAdjusted\":15928,\"ĠHornets\":15929,\"ĠNZ\":15930,\"ĠKathleen\":15931,\"ĠKier\":15932,\"ĠMercury\":15933,\"Ġghost\":15934,\"Ġhaw\":15935,\"ĠDemand\":15936,\"ĠCollection\":15937,\"ĠFortune\":15938,\"Ġcruel\":15939,\"Ġfurious\":15940,\"ĠKun\":15941,\"ĠSalem\":15942,\"Ġunsuccessful\":15943,\"ĠLomb\":15944,\"ĠFury\":15945,\"ahi\":15946,\"Ġenthusiastic\":15947,\"Ġsurgeries\":15948,\"ACE\":15949,\"Ġroller\":15950,\"ĠStamford\":15951,\"Being\":15952,\"Dec\":15953,\"check\":15954,\"Ġaffection\":15955,\"Ġgifted\":15956,\"Ġenerg\":15957,\"Ġvarying\":15958,\"ĠCharl\":15959,\"Ġsolved\":15960,\"ĠNV\":15961,\"Ġlaptops\":15962,\"Ġkindness\":15963,\"mart\":15964,\"ĠPenny\":15965,\"Ġ116\":15966,\"ĠFeder\":15967,\"ĠCisco\":15968,\"Ġeducators\":15969,\"Ġminim\":15970,\"Ġgangs\":15971,\"Ġfestivities\":15972,\"ĠOriginal\":15973,\"yre\":15974,\"rying\":15975,\"Ġtighter\":15976,\"ĠMalta\":15977,\"Ġshield\":15978,\"interest\":15979,\"Ġbuoy\":15980,\"Ġsupplement\":15981,\"ĠSof\":15982,\"Ġok\":15983,\"Ġprosecuted\":15984,\"Ġinterventions\":15985,\"Ġseize\":15986,\"Ġcaravan\":15987,\"ĠCarlson\":15988,\"ĠEnterprises\":15989,\"ĠChristina\":15990,\"ĠWellington\":15991,\"Ġaltered\":15992,\"TP\":15993,\"Ġexpresses\":15994,\"Ġcomfortably\":15995,\"Ġstaffing\":15996,\"afa\":15997,\"itu\":15998,\"saving\":15999,\"Ġinflammation\":16000,\"hatt\":16001,\"ĠMiranda\":16002,\"icious\":16003,\"Ġgrabbing\":16004,\"ĠANY\":16005,\"Ġobjections\":16006,\"Ġdot\":16007,\"cle\":16008,\"Ġrelates\":16009,\"Ġtribe\":16010,\"Ġboarding\":16011,\"ĠEpisode\":16012,\"ĠEnjoy\":16013,\"arding\":16014,\"Ġathletics\":16015,\"Ġflies\":16016,\"Ġmortgages\":16017,\"ruct\":16018,\"Ġink\":16019,\"ĠKC\":16020,\"ĠSecondary\":16021,\"Ġfer\":16022,\"ĠQaeda\":16023,\"OA\":16024,\"Frank\":16025,\"track\":16026,\"ĠChandler\":16027,\"Ġenv\":16028,\"ĠLeaders\":16029,\"ĠKemp\":16030,\"Ġunsafe\":16031,\"sponsored\":16032,\"San\":16033,\"ĠUsers\":16034,\"PE\":16035,\"ĠAccount\":16036,\"otta\":16037,\"ĠMix\":16038,\"ĠCindy\":16039,\"En\":16040,\"Ġ175\":16041,\"Ġoverlooked\":16042,\"Ġpublications\":16043,\"Ġrewarding\":16044,\"Ġexplicit\":16045,\"Ġnotch\":16046,\"Ġspecifics\":16047,\"Ġdesignation\":16048,\"ĠAppeal\":16049,\"Ġcontingent\":16050,\"Ġcage\":16051,\"ĠKol\":16052,\"ĠJohns\":16053,\"ĠReach\":16054,\"ĠTin\":16055,\"ĠAfricans\":16056,\"Ġprec\":16057,\"ĠRural\":16058,\"ĠDw\":16059,\"Ġuphold\":16060,\"Ġsuffers\":16061,\"Ġweed\":16062,\"inst\":16063,\"Ġcancellation\":16064,\"ĠShaun\":16065,\"Ġleve\":16066,\"Ġdivisive\":16067,\"Ġhel\":16068,\"Ġfatigue\":16069,\"ĠSchwartz\":16070,\"ĠKirst\":16071,\"Ġarise\":16072,\"Ġgrandson\":16073,\"ĠLawson\":16074,\"Ġcollaborate\":16075,\"Ġparticipant\":16076,\"ĠBryce\":16077,\"Ġinfield\":16078,\"mid\":16079,\"Ġut\":16080,\"Ġnotices\":16081,\"Ġsneak\":16082,\"ĠPAR\":16083,\"Chris\":16084,\"Ġutilize\":16085,\"ĠByron\":16086,\"ĠZhang\":16087,\"PF\":16088,\"Ġoverwhelmingly\":16089,\"Ġvegetable\":16090,\"Ġabsurd\":16091,\"ĠChem\":16092,\"etime\":16093,\"Ġenvoy\":16094,\"Ġlover\":16095,\"length\":16096,\"Ġrevolutionary\":16097,\"ĠYam\":16098,\"Ġshutting\":16099,\"mt\":16100,\"super\":16101,\"ĠToby\":16102,\"ĠCoca\":16103,\"Ġproposition\":16104,\"Ġembracing\":16105,\"Ġversatile\":16106,\"ĠWalking\":16107,\"Ġillicit\":16108,\"Ġnude\":16109,\"Ġunpredictable\":16110,\"take\":16111,\"Ġgotta\":16112,\"ĠXiaomi\":16113,\"Ġinstit\":16114,\"ĠPep\":16115,\"ĠPearson\":16116,\"Ġrejection\":16117,\"stead\":16118,\"Ġmut\":16119,\"Ġoutspoken\":16120,\"ĠBaghdad\":16121,\"ĠFly\":16122,\"Ġwholly\":16123,\"ĠRM\":16124,\"ĠFa\":16125,\"Ġcleaner\":16126,\"frey\":16127,\"ĠHab\":16128,\"ĠLiber\":16129,\"Ġwhereabouts\":16130,\"Ġchefs\":16131,\"Ġalumni\":16132,\"Ġstopp\":16133,\"dd\":16134,\"forward\":16135,\"rast\":16136,\"ĠNash\":16137,\"ĠCort\":16138,\"Ġpotent\":16139,\"Ġmold\":16140,\"Ġdistinctive\":16141,\"chip\":16142,\"ĠBrunswick\":16143,\"Ġpopulist\":16144,\"Ġplagued\":16145,\"eka\":16146,\"ĠIOC\":16147,\"ugs\":16148,\"ĠDob\":16149,\"Ġmagn\":16150,\"asser\":16151,\"hew\":16152,\"Ġcapturing\":16153,\"oos\":16154,\"Ġcrystal\":16155,\"Ġalarming\":16156,\"Ġ135\":16157,\"iating\":16158,\"Ġnap\":16159,\"umar\":16160,\"ĠExpl\":16161,\"Ġupgrading\":16162,\"Ġdecl\":16163,\"Ġoverturn\":16164,\"ARK\":16165,\"linked\":16166,\"ĠContinued\":16167,\"Ġslumped\":16168,\"ĠGaga\":16169,\"iful\":16170,\"ĠPosted\":16171,\"ĠRecommended\":16172,\"Ġsnake\":16173,\"Ġexplosives\":16174,\"Ġhind\":16175,\"Ġcontempt\":16176,\"Ġmock\":16177,\"NBA\":16178,\"Ġstall\":16179,\"Ġorganisers\":16180,\"Ġingredient\":16181,\"Ġblockbuster\":16182,\"ĠStream\":16183,\"ĠLeah\":16184,\"Pic\":16185,\"Ġventures\":16186,\"oman\":16187,\"Ġweakening\":16188,\"Ġmaximize\":16189,\"Ġdigging\":16190,\"uez\":16191,\"Ġdistinction\":16192,\"ĠMali\":16193,\"Ġcontaminated\":16194,\"Ġhij\":16195,\"Ġcrafts\":16196,\"Fl\":16197,\"Ġcloset\":16198,\"ĠRapp\":16199,\"Ġtowers\":16200,\"Ġamenities\":16201,\"Ġopioids\":16202,\"Ġcontend\":16203,\"load\":16204,\"ĠJol\":16205,\"ĠBooks\":16206,\"Ġsim\":16207,\"Ġthrilling\":16208,\"Ġmeter\":16209,\"ĠMultiple\":16210,\"Ġarbitration\":16211,\"Ġcracked\":16212,\"Pl\":16213,\"Ġphotographers\":16214,\"Te\":16215,\"ĠSidd\":16216,\"Ġexplored\":16217,\"170\":16218,\"Ġpleasant\":16219,\"ĠCapitals\":16220,\"ĠRi\":16221,\"ĠRandall\":16222,\"overed\":16223,\"Ġchar\":16224,\"ĠEverybody\":16225,\"ĠPolitics\":16226,\"Ġmoisture\":16227,\"Ġthriving\":16228,\"ĠScotia\":16229,\"arded\":16230,\"imb\":16231,\"ĠFantasy\":16232,\"Ġcemetery\":16233,\"ĠPath\":16234,\"eur\":16235,\"ĠSec\":16236,\"ĠPlatform\":16237,\"Ġdeparted\":16238,\"ĠVIDEO\":16239,\"ĠPant\":16240,\"ĠSyn\":16241,\"Ġ230\":16242,\"bleacher\":16243,\"live\":16244,\"Ġprob\":16245,\"Ġgymn\":16246,\"Ġjudged\":16247,\"orns\":16248,\"Ġstemming\":16249,\"umbling\":16250,\"ĠHew\":16251,\"ĠCheryl\":16252,\"Ġconsciousness\":16253,\"cos\":16254,\"ĠTate\":16255,\"CNN\":16256,\"Ġrecognizing\":16257,\"meg\":16258,\"Ġpant\":16259,\"ulk\":16260,\"MM\":16261,\"ĠPrescott\":16262,\"ĠMarcel\":16263,\"anas\":16264,\"Ġhappier\":16265,\"mag\":16266,\"ĠLov\":16267,\"Ġspreads\":16268,\"ĠSample\":16269,\"Ġpopped\":16270,\"HR\":16271,\"ĠMitt\":16272,\"Ġ00\":16273,\"Ġlabeled\":16274,\"Ġaspirations\":16275,\"?)\":16276,\"Ġloads\":16277,\"ĠBritt\":16278,\"hurst\":16279,\"ĠTeams\":16280,\"Ġextremists\":16281,\"ĠClement\":16282,\"lings\":16283,\"shirts\":16284,\"cheon\":16285,\"ĠDEL\":16286,\"ĠLocation\":16287,\"Ġpresentations\":16288,\"ĠFalcon\":16289,\"Ġtoddler\":16290,\"kl\":16291,\"Ġprone\":16292,\"Ġcommemor\":16293,\"ĠStanton\":16294,\"201\":16295,\"Ġranges\":16296,\"Ġfielder\":16297,\"Ġattends\":16298,\"rade\":16299,\"Ġproactive\":16300,\"Ġhostage\":16301,\"ĠGriffith\":16302,\"ockey\":16303,\"ĠAdding\":16304,\"ĠAFL\":16305,\"gas\":16306,\"istics\":16307,\"Ġsurgeon\":16308,\"Ġtsunami\":16309,\"2014\":16310,\"Ġconstraints\":16311,\"cu\":16312,\"Ġsurrendered\":16313,\"azed\":16314,\"ĠAirbnb\":16315,\"650\":16316,\"zed\":16317,\"Ġinjustice\":16318,\"dog\":16319,\"full\":16320,\"ĠHear\":16321,\"Ġsprawling\":16322,\"Ġhomeland\":16323,\"ĠSG\":16324,\"anced\":16325,\"Ġpools\":16326,\"ĠCE\":16327,\"Ġbeers\":16328,\"AE\":16329,\"ĠJac\":16330,\"Ġrecurring\":16331,\"Writing\":16332,\"Ġgenius\":16333,\"ĠFrost\":16334,\"Ġgrounded\":16335,\"Ġallege\":16336,\"lessness\":16337,\"Ġjumper\":16338,\"Ġvicious\":16339,\"Ġsecretly\":16340,\"Ġhacked\":16341,\"ĠAmsterdam\":16342,\"ibu\":16343,\"Ġ1971\":16344,\"ĠRosenstein\":16345,\"nick\":16346,\"arge\":16347,\"Ġladder\":16348,\"elled\":16349,\"Ġsatellites\":16350,\"Ġassassination\":16351,\"ĠDepot\":16352,\"built\":16353,\"Ġunrelated\":16354,\"maid\":16355,\"ĠDod\":16356,\"ĠVanderbilt\":16357,\"Ġboundary\":16358,\"ĠStafford\":16359,\"ĠBry\":16360,\"Ġtribunal\":16361,\"Ġoutings\":16362,\"Ġquantity\":16363,\"imming\":16364,\"ĠBlacks\":16365,\"Br\":16366,\"eri\":16367,\"uffed\":16368,\"Ġexplicitly\":16369,\"ĠBieber\":16370,\"AKING\":16371,\"Ġphotographed\":16372,\"ĠPolit\":16373,\"Ġpremature\":16374,\"hered\":16375,\"ĠVi\":16376,\"Ġmarsh\":16377,\"casters\":16378,\"ĠKra\":16379,\"Ġdried\":16380,\"Ġcafe\":16381,\"eting\":16382,\"Ġshaping\":16383,\"aram\":16384,\"orf\":16385,\"Ġrichest\":16386,\"Ġhurricanes\":16387,\"Ġcommands\":16388,\"Gl\":16389,\"anth\":16390,\"Ġstunt\":16391,\"Ġyearly\":16392,\"Ġdefeats\":16393,\"Ġconsultancy\":16394,\"call\":16395,\"Ġlag\":16396,\"adh\":16397,\"ĠPalestine\":16398,\"Ġcustomized\":16399,\"ĠScar\":16400,\"ĠWesley\":16401,\"ready\":16402,\"Ġpersist\":16403,\"Ġpacking\":16404,\"ono\":16405,\"Ġdischarged\":16406,\"Ġpouring\":16407,\"sburg\":16408,\"Ġreconsider\":16409,\"ĠMethod\":16410,\"enez\":16411,\"cill\":16412,\"Ġsecular\":16413,\"pers\":16414,\"Ġple\":16415,\"ELS\":16416,\"ĠMine\":16417,\"Ġpushes\":16418,\"Us\":16419,\"Ġframes\":16420,\"ĠNets\":16421,\"ĠSiem\":16422,\"ĠHitler\":16423,\"kill\":16424,\"Ġrented\":16425,\"Ġcharm\":16426,\"Ġpulls\":16427,\"ĠTide\":16428,\"Ġinsufficient\":16429,\"itted\":16430,\"Care\":16431,\"iera\":16432,\"Ġcouch\":16433,\"aders\":16434,\"ext\":16435,\"ĠCitizen\":16436,\"Ġlogical\":16437,\"ĠMeadows\":16438,\"ĠDenis\":16439,\"ĠDrivers\":16440,\"Ġrepublic\":16441,\"Ġadvising\":16442,\"Ġparamedics\":16443,\"insky\":16444,\"illard\":16445,\"encia\":16446,\"Ġkh\":16447,\"Ġrh\":16448,\"Ġfinalized\":16449,\"Ġreins\":16450,\"ĠFarrell\":16451,\"Ġsteer\":16452,\"Ġproxy\":16453,\"unes\":16454,\"ĠSoul\":16455,\"ĠCopper\":16456,\"ĠKenyan\":16457,\"amped\":16458,\"conference\":16459,\"sted\":16460,\"ĠLon\":16461,\"Ġreplay\":16462,\"ĠBle\":16463,\"Ġvibe\":16464,\"Ġportfolios\":16465,\"sea\":16466,\"Ġbeautifully\":16467,\"Ġairs\":16468,\"ĠRap\":16469,\"ĠKatrina\":16470,\"Ġberth\":16471,\"gold\":16472,\"ĠIsaiah\":16473,\"iques\":16474,\"elson\":16475,\"Ġrelentless\":16476,\"ĠHighland\":16477,\"ĠPhilippe\":16478,\"ĠFol\":16479,\"Ġenduring\":16480,\"enz\":16481,\"Ġaer\":16482,\"icing\":16483,\"ĠHTC\":16484,\"Ġdoping\":16485,\"ĠAlb\":16486,\"Ġsom\":16487,\"icia\":16488,\"Ġcoroner\":16489,\"Ġdamn\":16490,\"Ġ119\":16491,\"Ġwiped\":16492,\"ĠAuditor\":16493,\"hern\":16494,\"ĠJew\":16495,\"endra\":16496,\"osp\":16497,\"ĠRory\":16498,\"Ġshapes\":16499,\"ĠPablo\":16500,\"Ġforemost\":16501,\"ĠHos\":16502,\"ĠCunningham\":16503,\"145\":16504,\"ĠRecovery\":16505,\"!!!\":16506,\"western\":16507,\"Ġimaging\":16508,\"ĠRookie\":16509,\"ĠMTV\":16510,\"Ġunc\":16511,\"ĠSporting\":16512,\"Ġpatrons\":16513,\"ĠCoverage\":16514,\"ĠObservatory\":16515,\"Ġfishermen\":16516,\"ĠProvince\":16517,\"ĠAston\":16518,\"ĠOsh\":16519,\"ĠWeekend\":16520,\"Ġrecruits\":16521,\"Ġdensity\":16522,\"FM\":16523,\"ĠGorsuch\":16524,\"ĠErie\":16525,\"lining\":16526,\"Ġshowcased\":16527,\"ĠRubio\":16528,\"Ġchaotic\":16529,\"Ġattractions\":16530,\"Ġhug\":16531,\"ĠHerbert\":16532,\"ĠRespond\":16533,\"Ġhappily\":16534,\"Ġtor\":16535,\"ĠOTHER\":16536,\"runner\":16537,\"ĠShakespeare\":16538,\"Ġstretching\":16539,\"ĠJudy\":16540,\"wyn\":16541,\"ĠCafe\":16542,\"Ġgreens\":16543,\"ĠHend\":16544,\"Ġglam\":16545,\"iation\":16546,\"ĠKingston\":16547,\"Ġincremental\":16548,\"Live\":16549,\"ĠBraun\":16550,\"USS\":16551,\"reb\":16552,\"Ġimperative\":16553,\"Ġsympathy\":16554,\"Ġrefuge\":16555,\"Ġadministered\":16556,\"rance\":16557,\"ĠLiberia\":16558,\"Ġmobil\":16559,\"heads\":16560,\"Ġinevitably\":16561,\"ĠEugene\":16562,\"ĠBerkshire\":16563,\"ĠHarbour\":16564,\"ĠTrends\":16565,\"TB\":16566,\"Ġdeficits\":16567,\"Ġlistings\":16568,\"Ġreadings\":16569,\"Ġtumor\":16570,\"Ġoffic\":16571,\"opy\":16572,\"Ġdistracted\":16573,\"Ġappropriately\":16574,\"ĠWillis\":16575,\"Ġskirt\":16576,\"ĠTea\":16577,\"Ġshades\":16578,\"Ġbargaining\":16579,\"Ġretention\":16580,\"ĠConcert\":16581,\"ĠMeteor\":16582,\"ĠCustom\":16583,\"Ġinputs\":16584,\"ĠSah\":16585,\"enta\":16586,\"Love\":16587,\"ĠBurg\":16588,\"ĠCynthia\":16589,\"ĠMoses\":16590,\"ubb\":16591,\"Ġpeoples\":16592,\"dh\":16593,\"ĠFro\":16594,\"bean\":16595,\"Ġcigarette\":16596,\"tta\":16597,\"umm\":16598,\"Ġphenomenal\":16599,\"Ġyelling\":16600,\"Ġinaug\":16601,\"Ġconven\":16602,\"ĠGore\":16603,\"request\":16604,\"Ġcolonial\":16605,\"ĠAleppo\":16606,\"Ġdemolition\":16607,\"Ġamounted\":16608,\"Ġstaggering\":16609,\"Ġclips\":16610,\"Ġinconsistent\":16611,\"ĠMilton\":16612,\"ĠWireless\":16613,\"ĠReno\":16614,\"ĠPerkins\":16615,\"Ġunusually\":16616,\"Ġmemor\":16617,\"Ġhectares\":16618,\"Ġlat\":16619,\"central\":16620,\"ĠDig\":16621,\"ĠMarina\":16622,\"ĠPartner\":16623,\"daily\":16624,\"your\":16625,\"Reilly\":16626,\"Ġpope\":16627,\"phy\":16628,\"Ġassessing\":16629,\"ĠRodrigo\":16630,\"wi\":16631,\"Ġcompatible\":16632,\"imate\":16633,\"Ġgentle\":16634,\"ĠRhodes\":16635,\"Brexit\":16636,\"ieve\":16637,\"Ġbreaches\":16638,\"Ġchopped\":16639,\"Ġcancers\":16640,\"VEL\":16641,\"Ġsluggish\":16642,\"ĠUltra\":16643,\"ĠUl\":16644,\"Ġcrises\":16645,\"ONE\":16646,\"ĠEquipment\":16647,\"Ġcater\":16648,\"Ġadjourn\":16649,\"Ġreadily\":16650,\"ĠRolling\":16651,\"ĠBott\":16652,\"inel\":16653,\"ĠRule\":16654,\"Ġgrind\":16655,\"ĠHussain\":16656,\"ussie\":16657,\"Ġdepressed\":16658,\"ĠImperial\":16659,\"ongo\":16660,\"Ġuniforms\":16661,\"Ġ117\":16662,\"Ġchambers\":16663,\"ĠDum\":16664,\"ifi\":16665,\"ĠBetty\":16666,\"ĠTA\":16667,\"Ġpromotions\":16668,\"itary\":16669,\"Ġcried\":16670,\"Ġbranding\":16671,\"ĠBahamas\":16672,\"ĠDat\":16673,\"Ġantibiotics\":16674,\"ĠAus\":16675,\"Ġumbrella\":16676,\"Ġgradual\":16677,\"Ġaltercation\":16678,\"Ġlure\":16679,\"ĠJakarta\":16680,\"Ġunified\":16681,\"chin\":16682,\"ettes\":16683,\"ĠRwanda\":16684,\"ulations\":16685,\"Ġbrink\":16686,\"Ġbroadcasting\":16687,\"ĠArtist\":16688,\"Ġrecon\":16689,\"Ġaqu\":16690,\"ĠServ\":16691,\"999\":16692,\"ĠParticipants\":16693,\"ĠVentures\":16694,\"fight\":16695,\"Ġactivism\":16696,\"Ġstructured\":16697,\"Ġportal\":16698,\"Ġtendency\":16699,\"ĠAssociate\":16700,\"Ġcalf\":16701,\"ĠOrd\":16702,\"ĠTi\":16703,\"ĠFrancois\":16704,\"uary\":16705,\"ĠVik\":16706,\"urchase\":16707,\"Ġfried\":16708,\"Ġbooming\":16709,\"Ġparticles\":16710,\"amas\":16711,\"INA\":16712,\"Super\":16713,\"supp\":16714,\"urring\":16715,\"ĠWatts\":16716,\"affer\":16717,\"ĠDEC\":16718,\"Ġroadway\":16719,\"border\":16720,\"Ġsequ\":16721,\"entially\":16722,\"ieg\":16723,\"Ġcamping\":16724,\"Ġ750\":16725,\"Ġcycles\":16726,\"ĠReese\":16727,\"ĠFellow\":16728,\"isters\":16729,\"ĠVehicle\":16730,\"kies\":16731,\"ĠJonas\":16732,\"Ġfoundations\":16733,\"ĠNigel\":16734,\"Ġstab\":16735,\"Ġcongressman\":16736,\"ĠWichita\":16737,\"antes\":16738,\"Ġprogression\":16739,\"Ġditch\":16740,\"lik\":16741,\"Ġsid\":16742,\"Ġele\":16743,\"ĠMund\":16744,\"Ġstairs\":16745,\"lete\":16746,\"Ġlingering\":16747,\"Ġsadly\":16748,\"Ġay\":16749,\"Em\":16750,\"Ġdeadliest\":16751,\"soon\":16752,\"Ġtangible\":16753,\"Ġabusing\":16754,\"Ġcomprises\":16755,\"vil\":16756,\"ĠBun\":16757,\"Ġdoubling\":16758,\"Ġcommun\":16759,\"Ġslogan\":16760,\"Ġloading\":16761,\"Ġshallow\":16762,\"Ġattributes\":16763,\"Che\":16764,\"Ġcheering\":16765,\"Ġrefuses\":16766,\"cam\":16767,\"bes\":16768,\"hon\":16769,\"ĠSpartans\":16770,\"cept\":16771,\"ĠComputer\":16772,\"ĠCanberra\":16773,\"ĠWARNING\":16774,\"Ġstuffed\":16775,\"block\":16776,\"ĠJennings\":16777,\"ĠAU\":16778,\"atin\":16779,\"Ġom\":16780,\"Ġbachelor\":16781,\"Ġprediction\":16782,\"ĠWinner\":16783,\"agne\":16784,\"Ġrob\":16785,\"ĠKatherine\":16786,\"Ġli\":16787,\"ĠHumph\":16788,\"ĠPEOPLE\":16789,\"IRO\":16790,\"Cola\":16791,\"Ġguitarist\":16792,\"isen\":16793,\"ĠHighlights\":16794,\"Ġwelcomes\":16795,\"Ġprisoner\":16796,\"Ġpsychology\":16797,\"Ġextradition\":16798,\"Ġrou\":16799,\"ĠLund\":16800,\"Ġthoughtful\":16801,\"RY\":16802,\"orman\":16803,\"Alex\":16804,\"Ġlaughter\":16805,\"Ġfumble\":16806,\"Ġsynthetic\":16807,\"Ġdigit\":16808,\"ĠRoc\":16809,\"ĠFactory\":16810,\"ellery\":16811,\"ishment\":16812,\"ilar\":16813,\"ĠEarl\":16814,\"ĠSutton\":16815,\"ĠJur\":16816,\"ĠAllan\":16817,\"ĠKoreans\":16818,\"uki\":16819,\"Ġculinary\":16820,\"PU\":16821,\"Stock\":16822,\"stars\":16823,\"ĠDayton\":16824,\"beck\":16825,\"Ġinstability\":16826,\"ĠBring\":16827,\"Ġbreeding\":16828,\"Ġmiracle\":16829,\"bons\":16830,\"Ġdonating\":16831,\"ĠKick\":16832,\"ĠSag\":16833,\"afi\":16834,\"Ġharassed\":16835,\"asm\":16836,\"Their\":16837,\"inity\":16838,\"Ġacademics\":16839,\"Ġstatute\":16840,\"ĠAmit\":16841,\"Ġpressured\":16842,\"east\":16843,\"\\\"),\":16844,\"iso\":16845,\"220\":16846,\"Ġairplane\":16847,\"ĠMcCabe\":16848,\"ctions\":16849,\"ĠMesa\":16850,\"Ġsensational\":16851,\"ĠFE\":16852,\"ĠNeigh\":16853,\"Ġbribery\":16854,\"Ġflaws\":16855,\"Ġfemales\":16856,\"Ġmisses\":16857,\"ĠColor\":16858,\"ĠVietnamese\":16859,\"ĠMental\":16860,\"Unfortunately\":16861,\"ĠPont\":16862,\"Ġ1940\":16863,\"dry\":16864,\"ĠGazette\":16865,\"ĠAns\":16866,\"Ġwhistle\":16867,\"Ġsymbolic\":16868,\"Ġpossessions\":16869,\"ĠDriver\":16870,\"Ġbracket\":16871,\"ĠReign\":16872,\"oji\":16873,\"Ġoct\":16874,\"Ġtube\":16875,\"ĠFelix\":16876,\"Ġtranslated\":16877,\"Ġpromptly\":16878,\"ĠErnest\":16879,\"arth\":16880,\"Ġdumb\":16881,\"Ġinfluences\":16882,\"taking\":16883,\"Ġprivat\":16884,\"erers\":16885,\"Ġmalware\":16886,\"Ġpredictable\":16887,\"Ġtighten\":16888,\"Ġheights\":16889,\"Ġfairness\":16890,\"facing\":16891,\"Ġrematch\":16892,\"Ġpoet\":16893,\"Ġfundamentally\":16894,\"Ġcoveted\":16895,\"Ġlivelihood\":16896,\"ĠABOUT\":16897,\"Ġsourced\":16898,\"Ġdeferred\":16899,\"Ġslashed\":16900,\"ĠSchultz\":16901,\"Ġtriggering\":16902,\"ĠShiv\":16903,\"Ġlithium\":16904,\"ahead\":16905,\"Ġleisure\":16906,\"Ġbackpack\":16907,\"ilateral\":16908,\"ĠNuclear\":16909,\"ĠLeone\":16910,\"ĠNice\":16911,\"Ġenthusiasts\":16912,\"September\":16913,\"Ġenroll\":16914,\"ĠWear\":16915,\"erey\":16916,\"angs\":16917,\"such\":16918,\"Ġunpopular\":16919,\"Ġdisciplined\":16920,\"Ġshrinking\":16921,\"ĠBrewing\":16922,\"ĠReally\":16923,\"Ġdirective\":16924,\"175\":16925,\"Ġnotifications\":16926,\"Ġfortunes\":16927,\"ĠHour\":16928,\"ĠGan\":16929,\"ĠChurchill\":16930,\"ĠDodge\":16931,\"ĠJeep\":16932,\"Ġsour\":16933,\"Ġderived\":16934,\"Ġft\":16935,\"riv\":16936,\"Ġlaundry\":16937,\"Ġfentanyl\":16938,\"ĠSioux\":16939,\"achi\":16940,\"workers\":16941,\"Ġworkload\":16942,\"rooms\":16943,\"ĠQU\":16944,\"ĠTruth\":16945,\"Ġdefenses\":16946,\"Ġdunk\":16947,\"Ĳ\":16948,\"Ġderby\":16949,\"ĠMotion\":16950,\"ĠMayo\":16951,\"ĠIke\":16952,\"Ġpreferences\":16953,\"Ġped\":16954,\"elman\":16955,\"moon\":16956,\"Ġshoots\":16957,\"ĠNoel\":16958,\"Ġmilit\":16959,\"ĠCambodia\":16960,\"ĠMLA\":16961,\"Ġhonoured\":16962,\"fast\":16963,\"Ġalgorithms\":16964,\"Ġstormed\":16965,\"NT\":16966,\"Benz\":16967,\"Ġvaccines\":16968,\"Ġmarching\":16969,\"Ġ118\":16970,\"ĠWilmington\":16971,\"GM\":16972,\"coin\":16973,\"Ġunderwater\":16974,\"ĠClearly\":16975,\"Ġorgans\":16976,\"mir\":16977,\"Ġdenounced\":16978,\"pless\":16979,\"imal\":16980,\"ĠKom\":16981,\"Ġfatalities\":16982,\"Ġyoungster\":16983,\"Ġthirty\":16984,\"Ġinternally\":16985,\"222\":16986,\"Ġdemonstrating\":16987,\"Ġbusiest\":16988,\"Ġperpetrators\":16989,\"Ġstun\":16990,\"Both\":16991,\"ĠMcCoy\":16992,\"gn\":16993,\"ĠDalton\":16994,\"ĠDAY\":16995,\"Ġsacred\":16996,\"Ġconsuming\":16997,\"Ġ(+\":16998,\"ĠPioneer\":16999,\"ĠApplications\":17000,\"ĠBolt\":17001,\"ĠBarkley\":17002,\"ĠExpo\":17003,\"ĠLore\":17004,\"ĠPrivacy\":17005,\"ĠHarley\":17006,\"Ġtractor\":17007,\"Ġtenth\":17008,\"ĠHaiti\":17009,\"ÃŃn\":17010,\"ĠTVs\":17011,\"ĠCathedral\":17012,\"Ġunite\":17013,\"Ġbinding\":17014,\"oks\":17015,\"ĠJenny\":17016,\"Ġcaller\":17017,\"ĠIngram\":17018,\"ĠPrairie\":17019,\"Ġrunoff\":17020,\"Ġasserted\":17021,\"icit\":17022,\"ĠSie\":17023,\"102\":17024,\"ĠMB\":17025,\"Ġobstruction\":17026,\"Ġgroom\":17027,\"Ġtolerate\":17028,\"Ġcans\":17029,\"forth\":17030,\"Ġvillain\":17031,\"Ġdefining\":17032,\"ĠFrenchman\":17033,\"otte\":17034,\"Ġcontr\":17035,\"clock\":17036,\"onder\":17037,\"Ġprolific\":17038,\"ĠElectronic\":17039,\"ĠSak\":17040,\"annie\":17041,\"ASS\":17042,\"Ġmultinational\":17043,\"Associated\":17044,\"IZ\":17045,\"ĠBelle\":17046,\"Ġmand\":17047,\"asis\":17048,\"Mac\":17049,\"Ġpretend\":17050,\"ĠCommunication\":17051,\"Ġheartbreaking\":17052,\"ĠShepherd\":17053,\"ĠBIG\":17054,\"mph\":17055,\"ĠShield\":17056,\"ĠLiv\":17057,\"ĠStatus\":17058,\"Ġbikini\":17059,\"Ġranch\":17060,\"Ġpeacefully\":17061,\"ITCH\":17062,\"bourne\":17063,\"ĠVariety\":17064,\"Ġstationed\":17065,\"Ġhed\":17066,\"Ġexhausted\":17067,\"Ġsurpassed\":17068,\"Ġcatalyst\":17069,\"Ġsmuggling\":17070,\"uating\":17071,\"Ġ123\":17072,\"Ġdup\":17073,\"ĠSul\":17074,\"conf\":17075,\"jit\":17076,\"Ġmaiden\":17077,\"asta\":17078,\"ĠCalvin\":17079,\"borne\":17080,\"Ġgrim\":17081,\"Ġtort\":17082,\"cott\":17083,\"olas\":17084,\"NR\":17085,\"Ġbreakout\":17086,\"ĠHun\":17087,\"ĠGuatemala\":17088,\"Ġhistorian\":17089,\"ĠLawyers\":17090,\"ĠDisplay\":17091,\"Ġobstruct\":17092,\"ĠOsborne\":17093,\"Ġtherapies\":17094,\"ĠAub\":17095,\"Ġinjunction\":17096,\"stroke\":17097,\"Ġseafood\":17098,\"Ġhazardous\":17099,\"ĠWolver\":17100,\"ĠViolence\":17101,\"ĠBillion\":17102,\"ĠLetter\":17103,\"ĠWorldwide\":17104,\"Real\":17105,\"Ġexpires\":17106,\"Ġflawed\":17107,\"European\":17108,\"Ġrigorous\":17109,\"ĠSimilar\":17110,\"ĠSurface\":17111,\"ĠEF\":17112,\"mys\":17113,\"ĠFunds\":17114,\"ographer\":17115,\"Ġtribes\":17116,\"Ġspouse\":17117,\"Ġunsure\":17118,\"aways\":17119,\"Ġtrainers\":17120,\"arie\":17121,\"ĠZar\":17122,\"ĠComedy\":17123,\"ĠLit\":17124,\"ĠNoon\":17125,\"Ġgallon\":17126,\"Ġconsulate\":17127,\"ĠBras\":17128,\"iology\":17129,\"onies\":17130,\"ĠBelichick\":17131,\"ĠRoot\":17132,\"ĠLux\":17133,\"ĠSed\":17134,\"ĠTos\":17135,\"Ġinherited\":17136,\"tw\":17137,\"Ġdeaf\":17138,\"Ġdriveway\":17139,\"jah\":17140,\"ĠScientific\":17141,\"ĠNottingham\":17142,\"both\":17143,\"awan\":17144,\"Ġnut\":17145,\"ĠLebanese\":17146,\"ĠAAA\":17147,\"ĠSuzuki\":17148,\"ĠBU\":17149,\"ells\":17150,\"Ġspecify\":17151,\"ĠNotes\":17152,\"Ġvoluntarily\":17153,\"ĠMolly\":17154,\"Ġoutskirts\":17155,\"Ġbehaviors\":17156,\"Ġmilitia\":17157,\"Ġsplash\":17158,\"Ġpersonalized\":17159,\"ĠFiat\":17160,\"ĠKind\":17161,\"ĠTruck\":17162,\"py\":17163,\"ĠWIN\":17164,\"dist\":17165,\"itational\":17166,\"APP\":17167,\"ĠPelicans\":17168,\"ĠGam\":17169,\"mel\":17170,\"Ġmandated\":17171,\"Ġbalances\":17172,\"ĠWizards\":17173,\"iary\":17174,\"ĠAvailable\":17175,\"Ġkay\":17176,\"jin\":17177,\"eyed\":17178,\"Ġsterling\":17179,\"Ġconcealed\":17180,\"ĠFedEx\":17181,\"ĠPO\":17182,\"ĠJacqu\":17183,\"anted\":17184,\"eme\":17185,\"ĠDefensive\":17186,\"manship\":17187,\"Ġreliever\":17188,\"Ġshortstop\":17189,\"Ġphot\":17190,\"ĠGain\":17191,\"ĠConcern\":17192,\"due\":17193,\"Ġalgorithm\":17194,\"fell\":17195,\"ĠMountains\":17196,\"icians\":17197,\"Ġhonoring\":17198,\"Ġuploaded\":17199,\"Ġtore\":17200,\"GH\":17201,\"orde\":17202,\"ĠCoin\":17203,\"ĠAven\":17204,\"Ġliterary\":17205,\"Before\":17206,\"Ġtactic\":17207,\"Ġsocially\":17208,\"ĠSik\":17209,\"Ġthermal\":17210,\"Ġhor\":17211,\"price\":17212,\"Ġrooted\":17213,\"arrow\":17214,\"Ġcirculating\":17215,\"Ġlaughs\":17216,\"ĠLines\":17217,\"lig\":17218,\"Ġjudgement\":17219,\"....\":17220,\"Ġsewer\":17221,\"Ġdancer\":17222,\"ĠPens\":17223,\"Ġsig\":17224,\"ische\":17225,\"wives\":17226,\"Ġgran\":17227,\"ĠBron\":17228,\"ĠHyde\":17229,\"yards\":17230,\"Ġcandidacy\":17231,\"Ġhey\":17232,\"Ġcontributors\":17233,\"ĠUpdated\":17234,\"Ġ190\":17235,\"Ġhalls\":17236,\"Ġemphas\":17237,\"ĠCherry\":17238,\"Ġrim\":17239,\"Ġbilled\":17240,\"Ġbaked\":17241,\"ĠPopular\":17242,\"lb\":17243,\"Ġgravity\":17244,\"Under\":17245,\"Ġreservation\":17246,\"organ\":17247,\"ĠPict\":17248,\"ĠWhitney\":17249,\"Ġonboard\":17250,\"NEY\":17251,\"ĠBreaking\":17252,\"Ġflagged\":17253,\"rar\":17254,\"ĠBasic\":17255,\"ĠDomestic\":17256,\"ĠPent\":17257,\"Ġvigilant\":17258,\"Ġzoning\":17259,\"Fire\":17260,\"Ġcorrected\":17261,\"isbury\":17262,\"ĠLaure\":17263,\"ĠDevon\":17264,\"print\":17265,\"ĠTopics\":17266,\"ĠFuel\":17267,\"Ġcirculation\":17268,\"ĠPratt\":17269,\"Ġskiing\":17270,\"Ġtornado\":17271,\"dep\":17272,\"ĠUnless\":17273,\"ifting\":17274,\"Ġfool\":17275,\"should\":17276,\"Ġinspectors\":17277,\"Ġprotested\":17278,\"Ġba\":17279,\"ussia\":17280,\"Ġspun\":17281,\"grass\":17282,\"phone\":17283,\"Ġpotato\":17284,\"ĠBehind\":17285,\"cil\":17286,\"Ġconcession\":17287,\"Ġapplause\":17288,\"ĠChin\":17289,\"Ġceremonies\":17290,\"pit\":17291,\"Ġtraumatic\":17292,\"Ġbasics\":17293,\"Ġparameters\":17294,\"ĠMoz\":17295,\"ĠAIDS\":17296,\"Ph\":17297,\"Ġjudging\":17298,\"Ġlecture\":17299,\"Ġmunicipality\":17300,\"Ġcardiac\":17301,\"ogan\":17302,\"pir\":17303,\"could\":17304,\"Channel\":17305,\"Ġshattered\":17306,\"ĠAV\":17307,\"continental\":17308,\"chie\":17309,\"ibi\":17310,\"ĠOy\":17311,\"Mon\":17312,\"ĠCN\":17313,\"WC\":17314,\"Ġdistributor\":17315,\"ĠSavannah\":17316,\"Ġcleaned\":17317,\"ĠFlores\":17318,\"Ġembarrassed\":17319,\"Ġclay\":17320,\"Ġvolcano\":17321,\"Ġstressful\":17322,\"Ġsummoned\":17323,\"ĠSeg\":17324,\"Ġstatistical\":17325,\"ĠShak\":17326,\"Ġadequately\":17327,\"worthy\":17328,\"fighting\":17329,\"alan\":17330,\"Ġnecessity\":17331,\"Ġresidency\":17332,\"Ġsober\":17333,\"arius\":17334,\"ĠTaj\":17335,\"mount\":17336,\"wards\":17337,\"Ġaesthetic\":17338,\"Coin\":17339,\"ĠDew\":17340,\"were\":17341,\"SK\":17342,\"Ġpowerhouse\":17343,\"Ġcleanup\":17344,\"ĠWITH\":17345,\"ĠHers\":17346,\"ĠRao\":17347,\"ĠFlyers\":17348,\"Ġdominating\":17349,\"issued\":17350,\"ĠMcGr\":17351,\"Ġinsurgency\":17352,\"Ġburial\":17353,\"ĠPlains\":17354,\"ensive\":17355,\"ĠPresent\":17356,\"Mo\":17357,\"Ġnerves\":17358,\"Ġsmoothly\":17359,\"staff\":17360,\"Ġrestoring\":17361,\"ĠGeneration\":17362,\"Ġcommuters\":17363,\"ĠLegend\":17364,\"ĠGad\":17365,\"lied\":17366,\"Ġissuer\":17367,\"ĠDozens\":17368,\"Ġphases\":17369,\"ĠWu\":17370,\"ĠTunisia\":17371,\"ĠPacers\":17372,\"Ġdur\":17373,\"ĠIG\":17374,\"annon\":17375,\"sided\":17376,\"Ġvo\":17377,\"ĠNI\":17378,\"Ġvitamin\":17379,\"Ġsoc\":17380,\"Ġimmunity\":17381,\"Ġgenerates\":17382,\"ĠMcGu\":17383,\"Ġexplores\":17384,\"Ġassistants\":17385,\"Ġstems\":17386,\"ushed\":17387,\"ĠZak\":17388,\"ĠOwners\":17389,\"Ġvariant\":17390,\"ardy\":17391,\"ĠNewark\":17392,\"ĠCatalonia\":17393,\"Ġautonomy\":17394,\"Ġgreet\":17395,\"Ġawait\":17396,\"ĠLuckily\":17397,\"ĠTicket\":17398,\"ĠSTOR\":17399,\"asy\":17400,\"Ġincorrect\":17401,\"Ġconsisting\":17402,\"Ġperspectives\":17403,\"ĠQuint\":17404,\"Ġtotaling\":17405,\"Ġnortheastern\":17406,\"Ġcharacterized\":17407,\"Ġsurfaces\":17408,\"nation\":17409,\"Ġprevents\":17410,\"ĠSho\":17411,\"Ġelectorate\":17412,\"Ġshortfall\":17413,\"chy\":17414,\"aws\":17415,\"ĠAddress\":17416,\"Ġdefensively\":17417,\"quel\":17418,\"chester\":17419,\"Ġterr\":17420,\"ahu\":17421,\"lined\":17422,\"ĠNev\":17423,\"unn\":17424,\"Def\":17425,\"pc\":17426,\"ĠSig\":17427,\"Ġnonetheless\":17428,\"ĠSundays\":17429,\"ĠBAS\":17430,\"Ġpolicemen\":17431,\"ĠGoal\":17432,\"apa\":17433,\"Ġrope\":17434,\"Ġoutage\":17435,\"ĠPaso\":17436,\"Ġsadness\":17437,\"ĠGrowing\":17438,\"ĠKyr\":17439,\"Ġale\":17440,\"ĠBreitbart\":17441,\"ĠVia\":17442,\"ĠBrig\":17443,\"idence\":17444,\"Ġ145\":17445,\"quire\":17446,\"Ġdistraction\":17447,\"ĠOdd\":17448,\"ĠSimply\":17449,\"ĠNin\":17450,\"Ġcompetent\":17451,\"ded\":17452,\"iper\":17453,\"ĠKaty\":17454,\"ĠSolomon\":17455,\"Ġfeeds\":17456,\"ĠMort\":17457,\"ĠRica\":17458,\"affe\":17459,\"Ġcooperating\":17460,\"Ġarrivals\":17461,\"Ġdelete\":17462,\"ĠAth\":17463,\"Ġtrustees\":17464,\"Ġtub\":17465,\"Ġsaga\":17466,\"otes\":17467,\"ĠCJ\":17468,\"Ġexited\":17469,\"stakes\":17470,\"Ġinflu\":17471,\"2000\":17472,\"ĠDonovan\":17473,\"ĠNur\":17474,\"Ġoutline\":17475,\"Ġaudition\":17476,\"oked\":17477,\"ĠJag\":17478,\"money\":17479,\"Ġcardiovascular\":17480,\"song\":17481,\"ĠOften\":17482,\"ĠGoff\":17483,\"ĠOaks\":17484,\"Will\":17485,\"acon\":17486,\"Ġ?\":17487,\"Har\":17488,\"ĠLambert\":17489,\"atoon\":17490,\"ĠAF\":17491,\"ĠMavericks\":17492,\"nia\":17493,\"ĠChennai\":17494,\"\\\"},\\\"\":17495,\"Ġpairing\":17496,\"mad\":17497,\"ause\":17498,\"ĠRide\":17499,\"111\":17500,\"ĠFallon\":17501,\"ĠHyder\":17502,\"ĠPiper\":17503,\"Ġfilmmakers\":17504,\"icon\":17505,\"ĠBeau\":17506,\"Ġbutt\":17507,\"lot\":17508,\"Ġrifles\":17509,\"Ġsunglasses\":17510,\"ĠTRA\":17511,\"Ġmagnetic\":17512,\"arty\":17513,\"ĠYo\":17514,\"ĠWeight\":17515,\"?!\":17516,\"ether\":17517,\"Ġaspir\":17518,\"Ġhunters\":17519,\"Ġcontamination\":17520,\"Ben\":17521,\"political\":17522,\"],\\\"\":17523,\"ĠBever\":17524,\"Ġmonuments\":17525,\"won\":17526,\"auc\":17527,\"Ġexpressions\":17528,\"Ġlakes\":17529,\"iao\":17530,\"abin\":17531,\"Ġpleading\":17532,\"Ġdiscounted\":17533,\"Ġdisappoint\":17534,\"ĠTW\":17535,\"craft\":17536,\"Ġsocieties\":17537,\"ĠAugusta\":17538,\"Ġbott\":17539,\"Ġmarker\":17540,\"ĠWrestling\":17541,\"CBC\":17542,\"athy\":17543,\"ĠAZ\":17544,\"Ġfabulous\":17545,\"valued\":17546,\"Ġoptical\":17547,\"Ġshaken\":17548,\"OSS\":17549,\"ĠImp\":17550,\"ĠAUD\":17551,\"inals\":17552,\"Ġrevital\":17553,\"Ġcontroller\":17554,\"Ġgrasp\":17555,\"uling\":17556,\"ĠFrederick\":17557,\"ague\":17558,\"bull\":17559,\"ĠLadies\":17560,\"Ġdisruptive\":17561,\"Ġbenefiting\":17562,\"Ġverge\":17563,\"ĠDak\":17564,\"Ġgrabs\":17565,\"ĠPAC\":17566,\"GN\":17567,\"ĠMcMahon\":17568,\"rob\":17569,\"ĠEspecially\":17570,\"ĠChrome\":17571,\"ĠBundesliga\":17572,\"104\":17573,\"Ġliberty\":17574,\"ĠSF\":17575,\"Ġvarieties\":17576,\"East\":17577,\"Ġgrowers\":17578,\"Ġsocialist\":17579,\"Ġunemployed\":17580,\"AMI\":17581,\"Ġtotals\":17582,\"ĠGib\":17583,\"Ġdefect\":17584,\"ĠOrtiz\":17585,\"ĠPerfect\":17586,\"Ġpraying\":17587,\"ISS\":17588,\"Ġul\":17589,\"Ġthrust\":17590,\"osc\":17591,\"ĠOtherwise\":17592,\"Ġobsessed\":17593,\"Ġ650\":17594,\"ĠWebsite\":17595,\"Ġspectators\":17596,\"ĠScout\":17597,\"ĠBoone\":17598,\"ĠDillon\":17599,\"Ġabortions\":17600,\"lect\":17601,\"utz\":17602,\"Ġvillagers\":17603,\"Ġaccelerating\":17604,\"Ġslap\":17605,\"Ġvague\":17606,\"Ġjurisdictions\":17607,\"League\":17608,\"ĠUruguay\":17609,\"Ġobstacle\":17610,\"Ġmanufactures\":17611,\"Ġcampaigned\":17612,\"ĠAdvance\":17613,\"ĠNort\":17614,\"emer\":17615,\"Ġ1964\":17616,\"Ġirre\":17617,\"Ġprog\":17618,\"ĠFeatured\":17619,\"Ġcommute\":17620,\"Ġhandset\":17621,\"akis\":17622,\"ĠArs\":17623,\"tail\":17624,\"iker\":17625,\"Ġcrafted\":17626,\"Ġupl\":17627,\"ĠMarcos\":17628,\"Looking\":17629,\"Ġseated\":17630,\"ĠBoat\":17631,\"Ġreadiness\":17632,\"ĠLLP\":17633,\"otechnology\":17634,\"facebook\":17635,\"ĠScouts\":17636,\"ĠEar\":17637,\"ĠAdv\":17638,\"ĠDemocracy\":17639,\"NI\":17640,\"oci\":17641,\"ĠSnapdragon\":17642,\"Saturday\":17643,\"ĠPra\":17644,\"ĠCoastal\":17645,\"ĠVoters\":17646,\"ĠLeigh\":17647,\"ohn\":17648,\"orry\":17649,\"Ġtechnicians\":17650,\"armed\":17651,\"Ġshrink\":17652,\"Ġspinning\":17653,\"agram\":17654,\"320\":17655,\"liner\":17656,\"ĠContest\":17657,\"ĠCountries\":17658,\"Ġfarewell\":17659,\"ĠCW\":17660,\"aris\":17661,\"Ġstorytelling\":17662,\"Ġpasser\":17663,\"Ġsailing\":17664,\"control\":17665,\"Ġdissent\":17666,\"ĠRih\":17667,\"Ġedit\":17668,\"Ġspoilers\":17669,\"itched\":17670,\"ĠBentley\":17671,\"Ġcant\":17672,\"mn\":17673,\"ĠMacy\":17674,\"Ġindefinitely\":17675,\"Ġvill\":17676,\"Ġmeth\":17677,\"ĠEL\":17678,\"Ġoptional\":17679,\"Ġremark\":17680,\"ĠVanessa\":17681,\"Ã£\":17682,\"Ġmasks\":17683,\"ĠProvincial\":17684,\"Ġculprit\":17685,\"ĠTol\":17686,\"Ġsnack\":17687,\"ĠInfinity\":17688,\"ĠPub\":17689,\"Ġbrakes\":17690,\"Ġclar\":17691,\"Ġinception\":17692,\"love\":17693,\"Ġwonders\":17694,\"Ġforged\":17695,\"ĠCEOs\":17696,\"Ġspecifications\":17697,\"irst\":17698,\"ension\":17699,\"ĠMarin\":17700,\"det\":17701,\"Ġordeal\":17702,\"ĠFeed\":17703,\"December\":17704,\"Ġstrokes\":17705,\"fect\":17706,\"orial\":17707,\"Ġshowcasing\":17708,\"Ġstack\":17709,\"UAL\":17710,\"ĠAlexandra\":17711,\"Ġpoison\":17712,\"ĠFry\":17713,\"ĠCars\":17714,\"Ġprototype\":17715,\"ĠUSDA\":17716,\"ĠIF\":17717,\"flows\":17718,\"Ġtailored\":17719,\"ĠGear\":17720,\"Ġmyth\":17721,\"Ġplatinum\":17722,\"seven\":17723,\"founded\":17724,\"encing\":17725,\"ĠTip\":17726,\"ĠMald\":17727,\"Ġgeopolitical\":17728,\"112\":17729,\"Ġenqu\":17730,\"ĠNR\":17731,\"ĠNadu\":17732,\"leen\":17733,\"ĠTat\":17734,\"Ġcolon\":17735,\"ĠSize\":17736,\"Ġvis\":17737,\"Ġbere\":17738,\"ĠAnnie\":17739,\"ĠWatkins\":17740,\"Ġpumping\":17741,\"cur\":17742,\"ĠBates\":17743,\"Ġslug\":17744,\"miss\":17745,\"Ġforecasting\":17746,\"source\":17747,\"Ġacknowledges\":17748,\"Ġprosecute\":17749,\"Ġtestament\":17750,\"Ġcum\":17751,\"ems\":17752,\"Ġsocks\":17753,\"ĠSame\":17754,\"Ġcompetitiveness\":17755,\"Ġdefinitive\":17756,\"Ġintensified\":17757,\"Ġsatisfying\":17758,\"Ġphysics\":17759,\"ĠHarden\":17760,\"Ġsubsidy\":17761,\"Men\":17762,\"ĠPaddock\":17763,\"Ġworkouts\":17764,\"ĠSaw\":17765,\"Ġcrisp\":17766,\"ĠBezos\":17767,\"ĠVote\":17768,\"Ġguiding\":17769,\"anged\":17770,\"Ġstaple\":17771,\"ŀ\":17772,\"ules\":17773,\"ĠAvengers\":17774,\"Ġoptim\":17775,\"ĠBuffett\":17776,\"Ġtimetable\":17777,\"oust\":17778,\"HE\":17779,\"ĠGrab\":17780,\"Have\":17781,\"cca\":17782,\"Ġwaived\":17783,\"Ġretaining\":17784,\"Ġaber\":17785,\"Ġoffline\":17786,\"Ġvigil\":17787,\"books\":17788,\"ĠRein\":17789,\"Ġacknowledging\":17790,\"ĠDoyle\":17791,\"Ġproteins\":17792,\"Ġmixing\":17793,\"ĠAlcohol\":17794,\"ĠJD\":17795,\"Ġsyn\":17796,\"Ġthieves\":17797,\"Ġhomemade\":17798,\"Ġfeminist\":17799,\"ĠRoosevelt\":17800,\"ĠCoal\":17801,\"Ġwishing\":17802,\"ĠSIGN\":17803,\"ĠLad\":17804,\"Ġempathy\":17805,\"ĠBrooke\":17806,\"ĠMash\":17807,\"inations\":17808,\"''\":17809,\"ulators\":17810,\"Ġdrastically\":17811,\"Ġfloral\":17812,\"ĠGuild\":17813,\"Ġundercover\":17814,\"ĠLaboratory\":17815,\"ĠRank\":17816,\"Ġrestraining\":17817,\"Ġparagraph\":17818,\"Ġpersona\":17819,\"ĠEmployment\":17820,\"ogs\":17821,\"ĠGw\":17822,\"ĠMedal\":17823,\"Ġwildly\":17824,\"fare\":17825,\"ĠCNBC\":17826,\"photo\":17827,\"Ġtransforming\":17828,\"Ġtermination\":17829,\"still\":17830,\"INT\":17831,\"Ġbal\":17832,\"ĠEconom\":17833,\"ĠLarson\":17834,\"Ġheck\":17835,\"Ġquantitative\":17836,\"Ġemergence\":17837,\"esta\":17838,\"Ġknot\":17839,\"Ġwhale\":17840,\"ĠðŁĺ\":17841,\"Ġperimeter\":17842,\"Ġempowerment\":17843,\"Ġmg\":17844,\"Ġrents\":17845,\"Ġrefreshing\":17846,\"Ġleasing\":17847,\"Ġpatents\":17848,\"andi\":17849,\"Ġfathers\":17850,\"Ġunse\":17851,\"Ġprocessors\":17852,\"Down\":17853,\"Ġreversal\":17854,\"veh\":17855,\"andal\":17856,\"ĠKov\":17857,\"Blue\":17858,\"Ġspecializes\":17859,\"Link\":17860,\"ĠConsidering\":17861,\"ĠEdmund\":17862,\"Ġneo\":17863,\"agger\":17864,\"rg\":17865,\"Ġseverity\":17866,\"Ġcour\":17867,\"RL\":17868,\"ĠTeresa\":17869,\"Ġgallons\":17870,\"Ġacquitted\":17871,\"Ġaccompl\":17872,\"Ġcracks\":17873,\"Ġsciences\":17874,\"Club\":17875,\"Ġpredicts\":17876,\"ĠVu\":17877,\"Ġhints\":17878,\"ĠZack\":17879,\"Ġrefurb\":17880,\"Ġdestabil\":17881,\"ĠSamar\":17882,\"ĠInfo\":17883,\"fs\":17884,\"Ġratios\":17885,\"Ġinherent\":17886,\"ĠContinental\":17887,\"Ġtreasure\":17888,\"Ġcaucus\":17889,\"Ġenact\":17890,\"orporated\":17891,\"ineries\":17892,\"Ġtastes\":17893,\"main\":17894,\"Ġsq\":17895,\"ickson\":17896,\"corruption\":17897,\"ulture\":17898,\"ĠGoodman\":17899,\"ĠLing\":17900,\"ĠSup\":17901,\"Ġexposing\":17902,\"immers\":17903,\"Ġresponds\":17904,\"heimer\":17905,\"Air\":17906,\"ĠFigures\":17907,\"Ġlongstanding\":17908,\"ĠAnalytics\":17909,\"Ġenforced\":17910,\"Ġnickname\":17911,\"Ġclinch\":17912,\"ĠCarpenter\":17913,\"ĠPharma\":17914,\"Ġconstructive\":17915,\"Ġgel\":17916,\"ĠSham\":17917,\"ĠTOP\":17918,\"ĠDerrick\":17919,\"Ã¶r\":17920,\"birds\":17921,\"ĠTong\":17922,\"ĠBatman\":17923,\"ĠRouhani\":17924,\"ĠOlive\":17925,\"ĠRiv\":17926,\"Ġdessert\":17927,\"Ġguides\":17928,\"Ġsag\":17929,\"Ġchemotherapy\":17930,\"Ġslept\":17931,\"ĠFranc\":17932,\"ĠDunk\":17933,\"writers\":17934,\"ĠÃĹ\":17935,\"Ġ401\":17936,\"Ġoutfielder\":17937,\"ĠHamburg\":17938,\"izu\":17939,\"Ġscr\":17940,\"Ġcomparisons\":17941,\"Ġwhites\":17942,\"Ġtraits\":17943,\"Ġcollateral\":17944,\"LEY\":17945,\"ideshow\":17946,\"Ġstatutory\":17947,\"Ġruin\":17948,\"Ġsituated\":17949,\"tem\":17950,\"Ġinject\":17951,\"rage\":17952,\"550\":17953,\"Ġfactions\":17954,\"ĠNaomi\":17955,\"cutting\":17956,\"Ġcommunicating\":17957,\"Ġrailroad\":17958,\"Ġsparking\":17959,\"Ġrespiratory\":17960,\"ĠWebster\":17961,\"ĠCarbon\":17962,\"Ġundertaking\":17963,\"Ġcomposer\":17964,\"ĠFigure\":17965,\"Ġspecified\":17966,\"Video\":17967,\"uber\":17968,\"Ġsexuality\":17969,\"lected\":17970,\"ĠBurger\":17971,\"ĠCards\":17972,\"SR\":17973,\"ĠLie\":17974,\"Ġrecount\":17975,\"Ġexceeding\":17976,\"Ġquoting\":17977,\"ĠJama\":17978,\"ĠVictorian\":17979,\"Ġsway\":17980,\"ĠGes\":17981,\"ĠSI\":17982,\"ĠKazakhstan\":17983,\"Ġaccusation\":17984,\"etr\":17985,\"Ah\":17986,\"Ġproc\":17987,\"Ġlamb\":17988,\"ĠMorales\":17989,\"ĠLily\":17990,\"Ġderail\":17991,\"Ġcontributes\":17992,\"iddle\":17993,\"ĠConcord\":17994,\"Ġelectr\":17995,\"Ġequip\":17996,\"Ġquantum\":17997,\"Ġthereafter\":17998,\"Ġarrange\":17999,\"Ġraided\":18000,\"ĠMove\":18001,\"ĠSang\":18002,\"ĠGaming\":18003,\"Ġbiology\":18004,\"ĠAmnesty\":18005,\"Ġdemise\":18006,\"ĠBarton\":18007,\"Ġqualifier\":18008,\"ANI\":18009,\"Ġundersc\":18010,\"Ġroyalty\":18011,\"ĠINC\":18012,\"Ġsne\":18013,\"ariat\":18014,\"ĠWan\":18015,\"Ġcluster\":18016,\"quin\":18017,\"Ġwhales\":18018,\"ĠFear\":18019,\"ĠBrew\":18020,\"Ġdeport\":18021,\"airs\":18022,\"Ġcensus\":18023,\"OUS\":18024,\"Ġrespectful\":18025,\"bone\":18026,\"Ġwaivers\":18027,\"friend\":18028,\"Ġsystemic\":18029,\"ĠDion\":18030,\"James\":18031,\"ĠAdmission\":18032,\"Ġstigma\":18033,\"ĠTIME\":18034,\"Ġunderpin\":18035,\"ĠWitnesses\":18036,\"Ġdigs\":18037,\"Ġgenocide\":18038,\"Ġstaging\":18039,\"rolled\":18040,\"Ġspecially\":18041,\"oop\":18042,\"Ġbaseline\":18043,\"ĠRF\":18044,\"avis\":18045,\"Ġvocals\":18046,\"COL\":18047,\"LD\":18048,\"Ġimpending\":18049,\"ĠCaldwell\":18050,\"Ġaluminium\":18051,\"Ġstra\":18052,\"ĠTayyip\":18053,\"Ġadmissions\":18054,\"falls\":18055,\"Ġrealizing\":18056,\"oen\":18057,\"ĠRV\":18058,\"ĠMog\":18059,\"Ġadvocating\":18060,\"ĠPepper\":18061,\"lived\":18062,\"ĠWick\":18063,\"Facebook\":18064,\"ĠSpect\":18065,\"Ġshout\":18066,\"Ġfractured\":18067,\"vet\":18068,\"Ġ1966\":18069,\"Ġcompensate\":18070,\"ĠVolume\":18071,\"Ġcategor\":18072,\"ĠHuntington\":18073,\"Free\":18074,\"OUGH\":18075,\"local\":18076,\"Sch\":18077,\"uti\":18078,\"Ġburger\":18079,\"Ġbush\":18080,\"Ġimpacting\":18081,\"Ġfrost\":18082,\"tti\":18083,\"ĠFresno\":18084,\"onz\":18085,\"shaw\":18086,\"ĠLibyan\":18087,\"Ġassert\":18088,\"ĠLegacy\":18089,\"ĠIE\":18090,\"ĠKinder\":18091,\"ĠHorizon\":18092,\"Ġtum\":18093,\"Ġsignaled\":18094,\"ĠFors\":18095,\"Ġspeedy\":18096,\"rang\":18097,\"ĠFT\":18098,\"Ġselecting\":18099,\"Ġpale\":18100,\"WD\":18101,\"Ġprobability\":18102,\"OUND\":18103,\"istrate\":18104,\"Ġsens\":18105,\"ocating\":18106,\"Ġinterpret\":18107,\"Ġpuzzle\":18108,\"Ġinland\":18109,\"Ġmanipulation\":18110,\"Sal\":18111,\"Ġfulfilling\":18112,\"ĠMcMaster\":18113,\"Make\":18114,\"jun\":18115,\"giving\":18116,\"ĠNiagara\":18117,\"Ġscholars\":18118,\"ALT\":18119,\"ĠSteam\":18120,\"omin\":18121,\"ĠSau\":18122,\"ĠDowning\":18123,\"Ġgy\":18124,\"ĠTit\":18125,\"ĠLav\":18126,\"ĠPepsi\":18127,\"Ġdumping\":18128,\"ĠDetect\":18129,\"ĠTDs\":18130,\"ĠKob\":18131,\"ĠSY\":18132,\"Ġpioneer\":18133,\"Ġ_\":18134,\"Ġclarified\":18135,\"ĠTests\":18136,\"opic\":18137,\"ĠMN\":18138,\"ĠBowman\":18139,\"umin\":18140,\"Ġwidow\":18141,\"Ġrallying\":18142,\"ĠPull\":18143,\"Ġprojection\":18144,\"Ġescalation\":18145,\"Ġlibraries\":18146,\"ĠFounder\":18147,\"ĠHugo\":18148,\"ĠStyle\":18149,\"Ġfreelance\":18150,\"Ġlisteners\":18151,\"Ġdiscovering\":18152,\"ĠPlans\":18153,\"Ġfranchises\":18154,\"ĠPam\":18155,\"Ġfarther\":18156,\"UI\":18157,\"opers\":18158,\"103\":18159,\"ublished\":18160,\"keys\":18161,\"aky\":18162,\"Ġinnov\":18163,\"¦\":18164,\"ĠDrum\":18165,\"Ġwraps\":18166,\"ĠCongressman\":18167,\"ĠVenus\":18168,\"fake\":18169,\"ĠBronx\":18170,\"ĠDinner\":18171,\"faced\":18172,\"Ġbackward\":18173,\"inge\":18174,\"Ġarsenal\":18175,\"ĠAce\":18176,\"uden\":18177,\"fre\":18178,\"Ġspa\":18179,\"ĠSaunders\":18180,\"ĠMatter\":18181,\"ĠSpons\":18182,\"Ġconsultations\":18183,\"ĠRuss\":18184,\"Ġsculpture\":18185,\"Ġuncommon\":18186,\"Nov\":18187,\"pg\":18188,\"otherapy\":18189,\"Ġgol\":18190,\"ĠBlazers\":18191,\"Ġadvises\":18192,\"ĠRegulatory\":18193,\"ĠBoyle\":18194,\"Äģ\":18195,\"Ġcuisine\":18196,\"Ġencouragement\":18197,\"yp\":18198,\"eny\":18199,\"ĠOrchestra\":18200,\"ĠChicken\":18201,\"Ġ1965\":18202,\"ĠPret\":18203,\"ĠCooperation\":18204,\"ĠDevices\":18205,\"ĠRodney\":18206,\"ĠHonduras\":18207,\"ĠEgg\":18208,\"Ġchurn\":18209,\"Ġclutch\":18210,\"ĠBernstein\":18211,\"Ġain\":18212,\"Ġformidable\":18213,\"ĠFacility\":18214,\"Ġpag\":18215,\"mons\":18216,\"bol\":18217,\"Ġliteracy\":18218,\"Ġsubmissions\":18219,\"ĠHulu\":18220,\"ĠConstitutional\":18221,\"ĠIsh\":18222,\"ĠPaula\":18223,\"olve\":18224,\"Ġabundance\":18225,\"ĠAla\":18226,\"ĠEcuador\":18227,\"Ġreconstruction\":18228,\"Ġcrush\":18229,\"reek\":18230,\"ĠÂŃ\":18231,\"ibo\":18232,\"Ġpracticed\":18233,\"Ġpac\":18234,\"rett\":18235,\"Ġpasta\":18236,\"Ġresp\":18237,\"ĠFlag\":18238,\"pal\":18239,\"Ġcommenting\":18240,\"Ġrecap\":18241,\"âĢĶâĢĶ\":18242,\"ĠToy\":18243,\"ĠMeredith\":18244,\"Ġreceipt\":18245,\"Ġseparating\":18246,\"ĠMap\":18247,\"Ġmogul\":18248,\"ĠBurlington\":18249,\"Ġger\":18250,\"Ġcoordinate\":18251,\"grad\":18252,\"Ġescalated\":18253,\"Ġproceeded\":18254,\"turned\":18255,\"Ġupt\":18256,\"hum\":18257,\"ĠWere\":18258,\"Whether\":18259,\"Ġenjoyable\":18260,\"energy\":18261,\"Ġprohibit\":18262,\"Ġhurdle\":18263,\"Ġdivorced\":18264,\"Ġcommentator\":18265,\"GT\":18266,\"ATH\":18267,\"Ġtravellers\":18268,\"Ġpopulated\":18269,\"ĠVo\":18270,\"ĠRebels\":18271,\"Ġspurred\":18272,\"Ġideological\":18273,\"Ġelephant\":18274,\"keyes\":18275,\"Pat\":18276,\"Ġlinger\":18277,\"Ġreps\":18278,\"Ġcocktails\":18279,\"ĠKristen\":18280,\"istically\":18281,\"Ġgunmen\":18282,\"Ġ1920\":18283,\"Ġquart\":18284,\"National\":18285,\"Ġexceptions\":18286,\"kat\":18287,\"priced\":18288,\"ĠHarold\":18289,\"ĠPistons\":18290,\"Ġcompounds\":18291,\"Ġmouse\":18292,\"Ġexhibits\":18293,\"ĠBurk\":18294,\"Ġclassmates\":18295,\"Ġcirculated\":18296,\"Ġattributable\":18297,\"ĠBaton\":18298,\"Ġorganizer\":18299,\"Ġdurable\":18300,\"Ġsingers\":18301,\"ĠOman\":18302,\"Ġhydrogen\":18303,\"Ġslash\":18304,\"Ġaccidental\":18305,\"ĠAbrams\":18306,\"KS\":18307,\"itty\":18308,\"Ġrust\":18309,\"Ġselections\":18310,\"porting\":18311,\"ĠEmanuel\":18312,\"XX\":18313,\"ĠThornton\":18314,\"Ġcolumns\":18315,\"Ġsentiments\":18316,\"fun\":18317,\"Ġplight\":18318,\"ĠSister\":18319,\"ĠMaggie\":18320,\"hya\":18321,\"Daniel\":18322,\"Ġplung\":18323,\"orio\":18324,\"ĠYorker\":18325,\"ĠSaturdays\":18326,\"Ġloc\":18327,\"aye\":18328,\"illon\":18329,\"ĠConsulting\":18330,\"pled\":18331,\"ĠZin\":18332,\"ĠFarms\":18333,\"ĠGiuliani\":18334,\"ĠMIN\":18335,\"ĠHanson\":18336,\"ĠComplete\":18337,\"ourke\":18338,\"oche\":18339,\"ĠJord\":18340,\"Ġprofessors\":18341,\"ĠWILL\":18342,\"ĠCron\":18343,\"Ġdorm\":18344,\"Ġcracking\":18345,\"tur\":18346,\"ORS\":18347,\"Ant\":18348,\"Ġdeduction\":18349,\"ĠSIM\":18350,\"igue\":18351,\"ĠValent\":18352,\"ĠEthereum\":18353,\"ĠSunny\":18354,\"ĠExtra\":18355,\"ivan\":18356,\"ĠFo\":18357,\"Ġleases\":18358,\"ibe\":18359,\"Ġ1800\":18360,\"Ġslapped\":18361,\"emaker\":18362,\"Ġfa\":18363,\"rien\":18364,\"ĠPeriod\":18365,\"ĠES\":18366,\"ĠBlu\":18367,\"Ġpreserving\":18368,\"Ġsmarter\":18369,\"mans\":18370,\"Ġgest\":18371,\"zu\":18372,\"nu\":18373,\"Ġdivest\":18374,\"roc\":18375,\"ĠFlood\":18376,\"Given\":18377,\"ĠNorton\":18378,\"Ġgranting\":18379,\"Ġdealings\":18380,\"Ġgeographic\":18381,\"esa\":18382,\"Ġcub\":18383,\"Ġcriticizing\":18384,\"ĠCub\":18385,\"Ġsurroundings\":18386,\"ĠInternal\":18387,\"Ġsle\":18388,\"Ġcrushing\":18389,\"ĠPP\":18390,\"izations\":18391,\"ĠAbdel\":18392,\"Joe\":18393,\"ĠVisitors\":18394,\"ĠCarly\":18395,\"INGTON\":18396,\"ĠGC\":18397,\"ĠWB\":18398,\"Ġgently\":18399,\"·\":18400,\"though\":18401,\"ĠAlto\":18402,\"Ġresting\":18403,\"ĠPerson\":18404,\"ĠTon\":18405,\"Ġbore\":18406,\"ĠClar\":18407,\"Ġmot\":18408,\"Ġbathrooms\":18409,\"ĠTypically\":18410,\"Ġdisconnect\":18411,\"Ġtightly\":18412,\"ĠHarvest\":18413,\"ĠHed\":18414,\"ĠGermans\":18415,\"atar\":18416,\"Ġkeynote\":18417,\"Ġimproper\":18418,\"fil\":18419,\"Ġintens\":18420,\"iev\":18421,\"Ġmedi\":18422,\"Ġtenant\":18423,\"Ġfootsteps\":18424,\"uli\":18425,\"Ġlegalization\":18426,\"106\":18427,\"ĠLexington\":18428,\"folio\":18429,\"ĠÂ½\":18430,\"ĠRita\":18431,\"Ġbattered\":18432,\"inka\":18433,\"ĠJavaScript\":18434,\"ĠMusical\":18435,\"ĠTalent\":18436,\"Ġlounge\":18437,\"Ġintimidation\":18438,\"ikh\":18439,\"ĠFam\":18440,\"Ġtherapeutic\":18441,\"Ġbalancing\":18442,\"Ġrocky\":18443,\"liners\":18444,\"ĠPredators\":18445,\"Ġregistering\":18446,\"Ġdiligence\":18447,\"ĠRover\":18448,\"ĠDot\":18449,\"Ġterminated\":18450,\"ĠEdu\":18451,\"Ġcharming\":18452,\"ĠPLAY\":18453,\"ĠFact\":18454,\"ĠCi\":18455,\").\\\"\":18456,\"ĠWrestle\":18457,\"hun\":18458,\"Ġopenings\":18459,\"Ġfou\":18460,\"Ġ126\":18461,\"spe\":18462,\"ĠAW\":18463,\"Ġbud\":18464,\"ĠTemper\":18465,\"ĠOrthodox\":18466,\"Ġprogressed\":18467,\"tre\":18468,\"Ġtasting\":18469,\"Ġscrutin\":18470,\"ĠLima\":18471,\"Ġlayout\":18472,\"Ġlitter\":18473,\"ijk\":18474,\"ĠParkinson\":18475,\"ĠAnfield\":18476,\"Ġdevelopmental\":18477,\"Ġheaven\":18478,\"ĠWoodward\":18479,\"index\":18480,\"Ġpistol\":18481,\"Ġreson\":18482,\"ĠWS\":18483,\"Ġemb\":18484,\"ĠLap\":18485,\"ĠPle\":18486,\"lington\":18487,\"ĠSit\":18488,\"Ġabruptly\":18489,\"ĠSenegal\":18490,\"ĠYates\":18491,\"aceutical\":18492,\"ĠJak\":18493,\"ĠHastings\":18494,\"iste\":18495,\"ĠDB\":18496,\"ĠAgent\":18497,\"Ġpreservation\":18498,\"ĠLank\":18499,\"ĠSuffolk\":18500,\"Ġboo\":18501,\"essed\":18502,\"Ġempowering\":18503,\"enne\":18504,\"Ġrecycled\":18505,\"Ġstrateg\":18506,\"Ġbrake\":18507,\"135\":18508,\"ĠStef\":18509,\"ĠFlake\":18510,\"ĠGregg\":18511,\"ĠRent\":18512,\"Ġinstallment\":18513,\"FW\":18514,\"ĠCran\":18515,\"obo\":18516,\"ml\":18517,\"ĠJade\":18518,\"Ġaccuses\":18519,\"ĠNvidia\":18520,\"Ġburg\":18521,\"High\":18522,\"Ġbothered\":18523,\"ĠBenn\":18524,\"Ġinterrupted\":18525,\"Ġtrek\":18526,\"Ġserv\":18527,\"Ġpatron\":18528,\"Ġdictator\":18529,\"owa\":18530,\"jad\":18531,\"ĠTulsa\":18532,\"Ġboil\":18533,\"Ġdisplaying\":18534,\"Ġcinem\":18535,\"awaited\":18536,\"¸\":18537,\"Ġreacts\":18538,\"ĠDee\":18539,\"ĠGron\":18540,\"igation\":18541,\"Ġservic\":18542,\"capt\":18543,\"Ġinsane\":18544,\"ĠVeteran\":18545,\"umen\":18546,\"End\":18547,\"ĠCream\":18548,\"Ġextremism\":18549,\"ĠMalone\":18550,\"Col\":18551,\"Ġsafeguard\":18552,\"Ġtomatoes\":18553,\"die\":18554,\"Ġchamp\":18555,\"zero\":18556,\"ĠPRES\":18557,\"Ġchoir\":18558,\"Ġpediatric\":18559,\"Ġprivileged\":18560,\"Ġdownstream\":18561,\"Business\":18562,\"ĠFighting\":18563,\"atable\":18564,\"Ġsums\":18565,\"Ġinsult\":18566,\"arten\":18567,\"ĠWikiLeaks\":18568,\"Ġpads\":18569,\"Ġretali\":18570,\"ĠHunts\":18571,\"Ġindie\":18572,\"ĠShields\":18573,\"ĠMortgage\":18574,\"oses\":18575,\"ampton\":18576,\"ĠVideos\":18577,\"ĠPER\":18578,\"itionally\":18579,\"ĠKimmel\":18580,\"sum\":18581,\"trade\":18582,\"acity\":18583,\"marked\":18584,\"ĠAngus\":18585,\"Ġtemper\":18586,\"Ġseizure\":18587,\"Ġfictional\":18588,\"utton\":18589,\"eva\":18590,\"Rs\":18591,\"Ġintra\":18592,\"ĠRequest\":18593,\"ppe\":18594,\"ĠeBay\":18595,\"ĠUSS\":18596,\"Ġ1500\":18597,\"Ġpossessing\":18598,\"Ġbacon\":18599,\"ĠSexual\":18600,\"ĠBuff\":18601,\"Ġslaughter\":18602,\"Ġjur\":18603,\"zhou\":18604,\"suit\":18605,\"ĠCha\":18606,\"ĠBuk\":18607,\"crime\":18608,\"ĠEasy\":18609,\"ĠChain\":18610,\"aq\":18611,\"ĠPall\":18612,\"flation\":18613,\"225\":18614,\"oup\":18615,\"109\":18616,\"ĠMcKenzie\":18617,\"Ġclearer\":18618,\"ĠDogs\":18619,\"oration\":18620,\"Ġsubs\":18621,\"Follow\":18622,\"ĠShirley\":18623,\"Ġadjusting\":18624,\"ĠEFF\":18625,\"Ġflipped\":18626,\"Ġconform\":18627,\"ĠLaurent\":18628,\"Ġcircular\":18629,\"ĠNOR\":18630,\"Ġmort\":18631,\"Ġtexture\":18632,\"avour\":18633,\"Ġflex\":18634,\"ĠHedge\":18635,\"ðŁĺ\":18636,\"Ġtrophies\":18637,\"ĠINV\":18638,\"Ġboast\":18639,\"ĠTyr\":18640,\"ĠNichols\":18641,\"ĠSpa\":18642,\"Ġcheered\":18643,\"Ġprey\":18644,\"reach\":18645,\"Ġbreached\":18646,\"ĠRegions\":18647,\"ĠLyft\":18648,\"ĠTul\":18649,\"ĠKore\":18650,\"Ġendure\":18651,\"ĠCover\":18652,\"\\\").\":18653,\"ĠSavage\":18654,\"Ã¨re\":18655,\"reens\":18656,\"Ġnic\":18657,\"sector\":18658,\"Ġweaknesses\":18659,\"Ġreboot\":18660,\"Ġ210\":18661,\"Ġimagery\":18662,\"ĠFrem\":18663,\"Ġclue\":18664,\"ĠLars\":18665,\"Ġfaction\":18666,\"hetic\":18667,\"Ġallied\":18668,\"ĠMarvin\":18669,\"Ġmethodology\":18670,\"ĠTN\":18671,\"Ġutter\":18672,\"Ġ270\":18673,\"ĠVolvo\":18674,\"oline\":18675,\"ĠACLU\":18676,\"Ġindirect\":18677,\"Ġminer\":18678,\"ĠBale\":18679,\"ĠStrange\":18680,\"ĠFuller\":18681,\"Ġexpelled\":18682,\"ĠTropical\":18683,\"Ġremotely\":18684,\"ĠTIM\":18685,\"Ġinnocence\":18686,\"Ġconfined\":18687,\"Ġfares\":18688,\"Ġprevalent\":18689,\"Ġdesp\":18690,\"House\":18691,\"azar\":18692,\"Ġgestures\":18693,\"ĠCES\":18694,\"ĠDM\":18695,\"eal\":18696,\"ĠÐ\":18697,\"Ġburnt\":18698,\"Ġframed\":18699,\"ĠDani\":18700,\"Ġhol\":18701,\"ĠCannes\":18702,\"ĠHayden\":18703,\"Ġwardrobe\":18704,\"ĠAssange\":18705,\"ĠSamp\":18706,\"bay\":18707,\"sky\":18708,\"ĠHence\":18709,\"ĠGrizzlies\":18710,\"rates\":18711,\"laws\":18712,\"ĠMandela\":18713,\"ĠHoover\":18714,\"rics\":18715,\"charged\":18716,\"Ġexclude\":18717,\"Ġpassive\":18718,\"Ġcontinuation\":18719,\"Ġblunt\":18720,\"Ġvac\":18721,\"ĠEmerging\":18722,\"rench\":18723,\"tv\":18724,\"ĠHollow\":18725,\"ĠOC\":18726,\"Ġadvisors\":18727,\"Ġrendered\":18728,\"ĠBernardino\":18729,\"ĠSupporters\":18730,\"ronic\":18731,\"Ġchancellor\":18732,\"Ġ1963\":18733,\"Ġuranium\":18734,\"Ġak\":18735,\"ĠOptions\":18736,\"ermott\":18737,\"ĠBerger\":18738,\"ibia\":18739,\"Ġexplosions\":18740,\"Ġimpairment\":18741,\"Ġhail\":18742,\"Ġalley\":18743,\"Ġcruelty\":18744,\"ĠClarence\":18745,\"Ġvariations\":18746,\"Ġrealm\":18747,\"Ġrenovations\":18748,\"ĠNorwich\":18749,\"Ġbelongings\":18750,\"Ġmerchants\":18751,\"ĠMinisters\":18752,\"ĠDodd\":18753,\"Ġviewer\":18754,\"Ġneutrality\":18755,\"quer\":18756,\"ĠPrinceton\":18757,\"dead\":18758,\"arest\":18759,\"GET\":18760,\"ĠCanadiens\":18761,\"ĠIgn\":18762,\"clear\":18763,\"Mal\":18764,\"ĠBridges\":18765,\"ĠHayward\":18766,\"Ġremarked\":18767,\"ingle\":18768,\"Ġsob\":18769,\"Ġdepart\":18770,\"beans\":18771,\"Ġpreserved\":18772,\"ĠFairfax\":18773,\"Ġforgot\":18774,\"ĠBeh\":18775,\"Rob\":18776,\"Ġcooperative\":18777,\"ullah\":18778,\"Ġmates\":18779,\"Ġrang\":18780,\"Ġthigh\":18781,\"Ġabducted\":18782,\"Ġchaired\":18783,\"ĠHearts\":18784,\"Ġidentifies\":18785,\"ĠBuckingham\":18786,\"ijn\":18787,\"ĠJab\":18788,\"Ġclashed\":18789,\"feed\":18790,\"sites\":18791,\"ĠCareer\":18792,\"exp\":18793,\"ĠBuccaneers\":18794,\"scape\":18795,\"Ġupdating\":18796,\"Ġintentional\":18797,\"ĠGuam\":18798,\"ĠBreakfast\":18799,\"ĠHag\":18800,\"Media\":18801,\"Ġtapping\":18802,\"Ġpics\":18803,\"Ġeaten\":18804,\"Ġpremise\":18805,\"Kim\":18806,\"ĠStorage\":18807,\"Ġextensively\":18808,\"Ġoutrageous\":18809,\"ĠSadly\":18810,\"Global\":18811,\"Â¢\":18812,\"leaning\":18813,\"CM\":18814,\"Ġeasiest\":18815,\"ument\":18816,\"Ġ122\":18817,\"Ġdaunting\":18818,\"ISE\":18819,\"Ġsunset\":18820,\"Ġreset\":18821,\"Ġbent\":18822,\"Trust\":18823,\"ĠCaleb\":18824,\"ĠRut\":18825,\"ĠBast\":18826,\"ETS\":18827,\"iencies\":18828,\"Ġpu\":18829,\"ature\":18830,\"Ġrealities\":18831,\"omi\":18832,\"Ġsoda\":18833,\"Ġunveil\":18834,\"ĠGoldberg\":18835,\"opes\":18836,\"Ġuprising\":18837,\"ĠMR\":18838,\"Ġendorse\":18839,\"Ġsail\":18840,\"Ġconverting\":18841,\"Ġglamorous\":18842,\"ĠHollande\":18843,\"108\":18844,\"isky\":18845,\"Ġcushion\":18846,\"240\":18847,\"Ġadventures\":18848,\"Ġantitrust\":18849,\"ĠStockholm\":18850,\"pace\":18851,\"ĠVald\":18852,\"ĠTransfer\":18853,\"ERT\":18854,\"ĠMcInt\":18855,\"Ġsurging\":18856,\"ogn\":18857,\"Ġlauded\":18858,\"ĠZam\":18859,\"ĠRough\":18860,\"TOR\":18861,\"Ġwed\":18862,\"Ġorigins\":18863,\"ĠEld\":18864,\"oso\":18865,\"Ġsupplying\":18866,\"ĠPetty\":18867,\"ĠTwe\":18868,\"ĠDenise\":18869,\"ĠBec\":18870,\"Ġbehave\":18871,\"Ġ121\":18872,\"estone\":18873,\"ĠBoulder\":18874,\"ĠBlackhawks\":18875,\"ĠWyatt\":18876,\"Ġfiguring\":18877,\"ĠDeborah\":18878,\"agi\":18879,\"significant\":18880,\"Ġasthma\":18881,\"Ġmessy\":18882,\"mpire\":18883,\"Ġax\":18884,\"Ġaspiring\":18885,\"ĠNH\":18886,\"ĠGina\":18887,\"heavy\":18888,\"ĠVick\":18889,\"ÃŃs\":18890,\"something\":18891,\"Ġbodily\":18892,\"Ġunauthorized\":18893,\"ĠActually\":18894,\"ĠOH\":18895,\"Ġmicrophone\":18896,\"allah\":18897,\"Ġrampant\":18898,\"Ġrelocated\":18899,\"Ġwidening\":18900,\"ĠCait\":18901,\"nel\":18902,\"ĠBlackBerry\":18903,\"Ġprofessionally\":18904,\"ĠInterestingly\":18905,\"Ġbarbecue\":18906,\"Ġresisting\":18907,\"ĠNunes\":18908,\"disc\":18909,\"Ġgroundbreaking\":18910,\"orable\":18911,\"ĠRegulation\":18912,\"Ġborrowed\":18913,\"Ġleaking\":18914,\"Ġlengths\":18915,\"Ġunveiling\":18916,\"houses\":18917,\"Ġ155\":18918,\"ĠBillboard\":18919,\"icion\":18920,\"Times\":18921,\"ĠZoe\":18922,\"ĠAbby\":18923,\"bus\":18924,\"ĠMinutes\":18925,\"ributed\":18926,\"Ġparap\":18927,\"Ġfertil\":18928,\"ABC\":18929,\"ĠIsle\":18930,\"Ġtherapist\":18931,\"Ġgubernatorial\":18932,\"ĠAust\":18933,\"ĠLoan\":18934,\"Bo\":18935,\"ĠNRL\":18936,\"rag\":18937,\"Clear\":18938,\"Ġrevision\":18939,\"Ġflesh\":18940,\"BD\":18941,\"iji\":18942,\"Ġproductions\":18943,\"Ġcoconut\":18944,\"ĠMcCorm\":18945,\"ĠDash\":18946,\"Ġgeography\":18947,\"hearted\":18948,\"Ġarson\":18949,\"Ġgoaltender\":18950,\"Ġbelly\":18951,\"Ġqualifications\":18952,\"ĠActiv\":18953,\"Ġhooked\":18954,\"ĠHungarian\":18955,\"Ġprotocols\":18956,\"inking\":18957,\"Ġfronts\":18958,\"ĠKuala\":18959,\"ĠToys\":18960,\"ĠFitness\":18961,\"Ġwarfare\":18962,\"Ġoutp\":18963,\"ĠQuestions\":18964,\"Ġwel\":18965,\"ĠShan\":18966,\"ĠMorton\":18967,\"ĠRomero\":18968,\"Ġglance\":18969,\"ĠTay\":18970,\"Ġsneakers\":18971,\"ĠSymphony\":18972,\"Ġinspect\":18973,\"enna\":18974,\"Nobody\":18975,\"Ġscrapped\":18976,\"ĠDeVos\":18977,\"ĠDominican\":18978,\"Ġplanets\":18979,\"anova\":18980,\"Ġnotify\":18981,\"Ġincurred\":18982,\"Ġunders\":18983,\"Ġdetainees\":18984,\"ĠMarriott\":18985,\"electric\":18986,\"ĠKes\":18987,\"union\":18988,\"ĠWatt\":18989,\"ATING\":18990,\"Ġslipping\":18991,\"Ġraft\":18992,\"Ġresisted\":18993,\"Ġcred\":18994,\"tern\":18995,\"Ġflurry\":18996,\"Line\":18997,\"Ġconsulted\":18998,\"Ġanalyzing\":18999,\"107\":19000,\"ĠWide\":19001,\"¶\":19002,\"human\":19003,\"ĠFEMA\":19004,\"Ġsmash\":19005,\"Ġcorps\":19006,\"Ġbarric\":19007,\"Ġcollar\":19008,\"ĠTB\":19009,\"without\":19010,\"ĠCanucks\":19011,\"Ġneedle\":19012,\"ĠSidney\":19013,\"ĠLauderdale\":19014,\"Ġglove\":19015,\"ilee\":19016,\"pic\":19017,\"Ġbenef\":19018,\"ĠHydro\":19019,\"ĠDisc\":19020,\"ĠArg\":19021,\"Ġtermin\":19022,\"Ġsympath\":19023,\"Ġpest\":19024,\"ĠCoff\":19025,\"Ġadvancement\":19026,\"social\":19027,\"pol\":19028,\"ĠEmails\":19029,\"Ġstacked\":19030,\"ibly\":19031,\"ĠAlbion\":19032,\"Ġfist\":19033,\"hero\":19034,\"ĠMarian\":19035,\"asia\":19036,\"Ġtownship\":19037,\"Ġslick\":19038,\"Ġmodeling\":19039,\"achers\":19040,\"ĠArgent\":19041,\"ĠSUN\":19042,\"arde\":19043,\"Ġpinned\":19044,\"Ġhitters\":19045,\"Ġdare\":19046,\"ictions\":19047,\"arily\":19048,\"Ġsting\":19049,\"Ġprimaries\":19050,\"appointed\":19051,\"Ġformats\":19052,\"Ġglitter\":19053,\"Ġpatches\":19054,\"Ġstrategically\":19055,\"Ġaka\":19056,\"Ġyielded\":19057,\"BY\":19058,\"Ġjeopard\":19059,\"ĠVand\":19060,\"Ġcrowned\":19061,\"Ġoccupants\":19062,\"Ġtanker\":19063,\"ĠVisa\":19064,\"Great\":19065,\"Ġseasoned\":19066,\"ĠAviv\":19067,\"Ġfiery\":19068,\"Ġderivatives\":19069,\"Ġdiverted\":19070,\"Ġacqu\":19071,\"Ġsandwiches\":19072,\"ĠLorenzo\":19073,\"Ġpardon\":19074,\"ĠBarber\":19075,\"ĠAgricultural\":19076,\"ĠPhilly\":19077,\"Ġregrets\":19078,\"ĠMillions\":19079,\"ĠFrazier\":19080,\"Ġtreasury\":19081,\"ĠKenn\":19082,\"Ġdestined\":19083,\"olved\":19084,\"Back\":19085,\"leader\":19086,\"lyss\":19087,\"ĠReyes\":19088,\"001\":19089,\"bags\":19090,\"ĠStandards\":19091,\"ĠExcellence\":19092,\"ĠMaid\":19093,\"ĠAnthem\":19094,\"FIELD\":19095,\"Ġrevived\":19096,\"ĠQuad\":19097,\"Ġdistinguished\":19098,\"Ġweighted\":19099,\"Ġritual\":19100,\"Ġinvites\":19101,\"wana\":19102,\"iture\":19103,\"ĠCI\":19104,\"ĠMAY\":19105,\"Ġunfairly\":19106,\"ĠKP\":19107,\"ĠMidlands\":19108,\"Ġmint\":19109,\"uers\":19110,\"Ġcatalog\":19111,\"arant\":19112,\"Ġlosers\":19113,\"Ġscheduling\":19114,\"esar\":19115,\"Ġtransferring\":19116,\"Ġbankrupt\":19117,\"Ġmethamphetamine\":19118,\"ĠEsk\":19119,\"ĠTreatment\":19120,\"ĠResponse\":19121,\"Ġhomework\":19122,\"ĠBald\":19123,\"Ġembarrassment\":19124,\"Ġpoorest\":19125,\"ĠPlatinum\":19126,\"ĠFac\":19127,\"Ġunleashed\":19128,\"Ġbrighter\":19129,\"002\":19130,\"Ġdisl\":19131,\"ĠLowry\":19132,\"ived\":19133,\"ĠDemon\":19134,\"ĠNonetheless\":19135,\"arro\":19136,\"ĠCONT\":19137,\"ifted\":19138,\"ĠFreder\":19139,\"isson\":19140,\"Ġrout\":19141,\"ARA\":19142,\"Ġswinging\":19143,\"Oct\":19144,\"Ġliable\":19145,\"Ġleaning\":19146,\"Ġlungs\":19147,\"380\":19148,\"ĠProcess\":19149,\"ĠCov\":19150,\"terrorism\":19151,\"Ġresistant\":19152,\"Ġpumped\":19153,\"Ġtripled\":19154,\"Semitism\":19155,\"ĠMia\":19156,\"Ġpenetration\":19157,\"ĠLutheran\":19158,\"BU\":19159,\"odes\":19160,\"Ġspanning\":19161,\"utch\":19162,\"Trans\":19163,\"ĠVolunteers\":19164,\"Ġpathway\":19165,\"Ġinfectious\":19166,\"Ġdrastic\":19167,\"ĠEngineers\":19168,\"Ġprincess\":19169,\"acts\":19170,\"usting\":19171,\"utive\":19172,\"achel\":19173,\"DO\":19174,\"Ġpave\":19175,\"ĠHerrera\":19176,\"Ġnearing\":19177,\"help\":19178,\"Ġembarked\":19179,\"Ġmodes\":19180,\"ĠDriving\":19181,\"Ġopting\":19182,\"Best\":19183,\"Ġbehavioral\":19184,\"Ġcables\":19185,\"App\":19186,\"otion\":19187,\"ĠExt\":19188,\"ĠSinclair\":19189,\"ĠInsp\":19190,\"Ġsinking\":19191,\"Next\":19192,\"ĠLumpur\":19193,\"ĠShadow\":19194,\"Donald\":19195,\"itals\":19196,\"Ġmentions\":19197,\"floor\":19198,\"Ġconsiderations\":19199,\"ĠSquad\":19200,\"ĠPlate\":19201,\"dos\":19202,\"Friday\":19203,\"Hopefully\":19204,\"arre\":19205,\"Ġalum\":19206,\"\\\":\\\"/\":19207,\"Ġfet\":19208,\"anza\":19209,\"Ġdign\":19210,\"ĠNguyen\":19211,\"ĠRutgers\":19212,\"ĠSew\":19213,\"Ġfilters\":19214,\"ofi\":19215,\"Ġunavailable\":19216,\"ranking\":19217,\"Ġrefining\":19218,\"ĠUNC\":19219,\"Ġmax\":19220,\"yll\":19221,\"Ġhandsome\":19222,\"Ġutterly\":19223,\"See\":19224,\"ĠStores\":19225,\"Ke\":19226,\"ĠAdvoc\":19227,\"ordon\":19228,\"umbles\":19229,\"Ġbugs\":19230,\"olar\":19231,\"ĠCork\":19232,\"Ġtoken\":19233,\"Ġauthorization\":19234,\"Ġconscience\":19235,\"Ġrepl\":19236,\"edi\":19237,\"owitz\":19238,\"iven\":19239,\"Ġlieu\":19240,\"Ġlifts\":19241,\"Lean\":19242,\"Ġmagnificent\":19243,\"ĠFilms\":19244,\"onents\":19245,\"Ġ***\":19246,\"Green\":19247,\"ĠAdvocate\":19248,\"ĠArrow\":19249,\"Ġblows\":19250,\"Ġexploited\":19251,\"fly\":19252,\"ĠAmar\":19253,\"ĠNOTICE\":19254,\"Ġsincere\":19255,\"found\":19256,\"ĠRud\":19257,\"Ġcy\":19258,\"ĠHeidi\":19259,\"Ġempowered\":19260,\"Ġweakest\":19261,\"ĠKru\":19262,\"Credit\":19263,\"aunted\":19264,\"Ġexotic\":19265,\"aning\":19266,\"Ġaw\":19267,\"ĠMulti\":19268,\"Ġanimation\":19269,\"850\":19270,\"ĠCounter\":19271,\"ĠNit\":19272,\"alli\":19273,\"Ġcapitalize\":19274,\"Ġexecuting\":19275,\"Ġdescent\":19276,\"ovi\":19277,\"ĠKimberly\":19278,\"headed\":19279,\"Ġmentioning\":19280,\")-\":19281,\"ĠSpecifically\":19282,\"ayette\":19283,\"ihad\":19284,\"ĠIss\":19285,\"Ġdisagreed\":19286,\"ĠKum\":19287,\"Ġurges\":19288,\"Ġpermitting\":19289,\"Ġpy\":19290,\"isp\":19291,\"Ġhygiene\":19292,\"Ġmourning\":19293,\"Ġcyclists\":19294,\"cats\":19295,\"FER\":19296,\"cycl\":19297,\"Ġnewcomers\":19298,\"Ġplead\":19299,\"Ġmend\":19300,\"secret\":19301,\"fan\":19302,\"Ġtranslates\":19303,\"unit\":19304,\"ĠTank\":19305,\"drive\":19306,\"ĠSite\":19307,\"Ġacceleration\":19308,\"ĠEnrique\":19309,\"ĠElaine\":19310,\"Ġstaring\":19311,\"Ġbackwards\":19312,\"Ġot\":19313,\"Ġvot\":19314,\"ĠHK\":19315,\"Ġfian\":19316,\"ĠLockheed\":19317,\"Ġmanifest\":19318,\"ĠZurich\":19319,\"pad\":19320,\"ĠRav\":19321,\"flow\":19322,\"Ġmoms\":19323,\"ĠSolid\":19324,\"ĠReady\":19325,\"aughlin\":19326,\"Ġreminding\":19327,\"ĠCOR\":19328,\"Ġoptimal\":19329,\"ĠCrisis\":19330,\"Ġcholesterol\":19331,\"ĠGerard\":19332,\"Ġfest\":19333,\"Ġsanction\":19334,\"Ġdragging\":19335,\"inent\":19336,\"ĠBravo\":19337,\"Ġamend\":19338,\"aval\":19339,\"Ġpoem\":19340,\"Ġinvasive\":19341,\"Ġlandsc\":19342,\"leigh\":19343,\"Ġheadache\":19344,\"ĠMuse\":19345,\"ĠTurning\":19346,\"girl\":19347,\"cess\":19348,\"Ġfalsely\":19349,\"Ġplaintiff\":19350,\"Ġheavier\":19351,\"Ġrumored\":19352,\"Ġeleven\":19353,\"ĠConsumers\":19354,\"ĠOriginally\":19355,\"ĠStatement\":19356,\"bors\":19357,\"Ġrevoked\":19358,\"ĠOmaha\":19359,\"Fox\":19360,\"ĠKle\":19361,\"Ġvault\":19362,\"Ġoutdated\":19363,\"umes\":19364,\"ĠArk\":19365,\"Ġapologised\":19366,\"Ġrockets\":19367,\"ĠMarines\":19368,\"Ġcaptures\":19369,\"ĠMW\":19370,\"ĠWalters\":19371,\"ĠFactor\":19372,\"Ġensuing\":19373,\"ĠSession\":19374,\"oons\":19375,\"Ġ132\":19376,\"gt\":19377,\"ĠPoints\":19378,\"Ġexhaust\":19379,\"ĠOsaka\":19380,\"heed\":19381,\"Ġhandic\":19382,\"amber\":19383,\"inging\":19384,\"Ġll\":19385,\"Ġescorted\":19386,\"Ġfloated\":19387,\"Ġmerge\":19388,\"Ġcompliment\":19389,\"ĠVC\":19390,\"Ġinsulin\":19391,\"ĠDebt\":19392,\"Ã§a\":19393,\"Ġpens\":19394,\"Ġassertion\":19395,\"Ġredevelopment\":19396,\"moderate\":19397,\"Ġleftist\":19398,\"ĠBA\":19399,\"Ġherd\":19400,\"Ġinsecurity\":19401,\"liter\":19402,\"Ġcommence\":19403,\"ĠCaucus\":19404,\"Ġnovels\":19405,\"ĠChevron\":19406,\"Ġerosion\":19407,\"ĠNicholson\":19408,\"ĠRoof\":19409,\"ĠVolunteer\":19410,\"Ġcompelled\":19411,\"Ġcongratulated\":19412,\"ĠPanel\":19413,\"Ġov\":19414,\"idelity\":19415,\"Ġspect\":19416,\"Ġbee\":19417,\"ĠAssistance\":19418,\"Ġterrified\":19419,\"iew\":19420,\"Ġweekday\":19421,\"ĠHiggins\":19422,\"special\":19423,\"ubs\":19424,\"anton\":19425,\"Ġbribes\":19426,\"Ġneat\":19427,\"ĠCliff\":19428,\"Ġdisqualified\":19429,\"ĠND\":19430,\"Ġvers\":19431,\"andra\":19432,\"Ġgraft\":19433,\"value\":19434,\"Ġportray\":19435,\"Ġdaytime\":19436,\"ksh\":19437,\"Ġconsist\":19438,\"Ġhonesty\":19439,\"ĠTimber\":19440,\"ĠNich\":19441,\"Ġinvented\":19442,\"ĠBuch\":19443,\"Ġskull\":19444,\"Ġtags\":19445,\"Ġ124\":19446,\"ighth\":19447,\"Ġrelaxing\":19448,\"Online\":19449,\"Ġsanctioned\":19450,\"Sport\":19451,\"ĠCove\":19452,\"Ġcomics\":19453,\"MW\":19454,\"AMA\":19455,\"mother\":19456,\"Home\":19457,\"ĠCustomer\":19458,\"Ġstrides\":19459,\"ĠWins\":19460,\"Ġrollout\":19461,\"ĠWeaver\":19462,\"Ġshuttle\":19463,\"Ġsteak\":19464,\"Ġglorious\":19465,\"ĠToll\":19466,\"Ġtrustee\":19467,\"Ġinstallations\":19468,\"ĠOpportunity\":19469,\"Ġoper\":19470,\"horse\":19471,\"Ġaided\":19472,\"irus\":19473,\"Ġsleek\":19474,\"Ġyelled\":19475,\"ĠSocialist\":19476,\"Ġapplaud\":19477,\"ĠWah\":19478,\"Ġdevote\":19479,\"Ġdh\":19480,\"Ġarchitectural\":19481,\"ĠMAC\":19482,\"centric\":19483,\"ĠSense\":19484,\"illas\":19485,\"ĠArchbishop\":19486,\"glass\":19487,\"Ġallowance\":19488,\"Ġbundle\":19489,\"andon\":19490,\"eight\":19491,\"ĠKare\":19492,\"haus\":19493,\"ĠAndreas\":19494,\"Ġdoll\":19495,\"RAM\":19496,\"Ġvolunteering\":19497,\"ĠRaleigh\":19498,\"Ġbees\":19499,\"Ġnickel\":19500,\"Ġgenerosity\":19501,\"Ġhomeowner\":19502,\"ĠLieutenant\":19503,\"Ġlandfall\":19504,\"ĠRenew\":19505,\"ĠGiving\":19506,\"ĠContribut\":19507,\"aret\":19508,\"ulf\":19509,\"Ġreinforce\":19510,\"ĠSalv\":19511,\"ĠVenice\":19512,\"Ġfreedoms\":19513,\"ĠTools\":19514,\"Ġ1962\":19515,\"ĠWarm\":19516,\"majority\":19517,\"Ġpleas\":19518,\"oding\":19519,\"plant\":19520,\"Ġtow\":19521,\"ĠBlanc\":19522,\"ĠPipeline\":19523,\"ĠMoor\":19524,\"Ġrefrain\":19525,\"ĠExplore\":19526,\"language\":19527,\"cers\":19528,\"ĠWT\":19529,\"sent\":19530,\"ĠNun\":19531,\"Ġplastics\":19532,\"acas\":19533,\"Ġdisruptions\":19534,\"Ġdiscomfort\":19535,\"enko\":19536,\"Ġimprisoned\":19537,\"Copyright\":19538,\"Ġmyriad\":19539,\"Ġparenting\":19540,\"Ġspree\":19541,\"NBC\":19542,\"Ġonion\":19543,\"ĠIsraelis\":19544,\"ĠRA\":19545,\"Ġrelocate\":19546,\"113\":19547,\"ĠHir\":19548,\"ĠDre\":19549,\"ĠDry\":19550,\"ĠONE\":19551,\"ĠAdministrator\":19552,\"Ġprints\":19553,\"ĠGret\":19554,\"Ġundergraduate\":19555,\"ĠLif\":19556,\"avers\":19557,\"ĠCarney\":19558,\"Ġapex\":19559,\"Ġlenses\":19560,\"Ġliberals\":19561,\"gb\":19562,\"ĠWhereas\":19563,\"Ġcountryside\":19564,\"amine\":19565,\"ĠTerminal\":19566,\"Ġintr\":19567,\"ĠTrey\":19568,\"ALS\":19569,\"Ġcontinental\":19570,\"Ġselfies\":19571,\"FILE\":19572,\"ĠUnity\":19573,\"Ġauthoritarian\":19574,\"Ġoriginated\":19575,\"ĠExcept\":19576,\"yna\":19577,\"Ġmonet\":19578,\"Ġundermining\":19579,\"ĠGS\":19580,\"pi\":19581,\"iq\":19582,\"Ġslides\":19583,\"ĠSummary\":19584,\"Ġpains\":19585,\"cluding\":19586,\"Ġequation\":19587,\"locked\":19588,\"Ġfraternity\":19589,\"Ġwithstand\":19590,\"Ġdevastation\":19591,\"Ġdemo\":19592,\"late\":19593,\"Ġpunches\":19594,\"Ġgeared\":19595,\"nen\":19596,\"ĠBowie\":19597,\"attle\":19598,\"Ġpolitic\":19599,\"ĠGle\":19600,\"mented\":19601,\"ĠCoordinator\":19602,\"Ġupwards\":19603,\"ĠMega\":19604,\"angled\":19605,\"Ġengineered\":19606,\"Ġluggage\":19607,\"ĠWen\":19608,\"ĠSergeant\":19609,\"Ġkindergarten\":19610,\"ĠPortsmouth\":19611,\"uddin\":19612,\"ket\":19613,\"oba\":19614,\"Ġoscill\":19615,\"esse\":19616,\"ĠOlson\":19617,\"ĠBorough\":19618,\"Ġsupplements\":19619,\"ĠEvening\":19620,\"ANE\":19621,\"Ġlava\":19622,\"Ġgearing\":19623,\"setting\":19624,\"urgical\":19625,\"asty\":19626,\"ĠDaytona\":19627,\"Ġbrewery\":19628,\"Ġpledges\":19629,\"rounder\":19630,\"ulous\":19631,\"ĠHancock\":19632,\"rex\":19633,\"Ġram\":19634,\"Ġproceeding\":19635,\"ĠMurdoch\":19636,\"Ġdowngrade\":19637,\"Ġstatues\":19638,\"Ġdebated\":19639,\"ĠSleep\":19640,\"Ġ144\":19641,\"ĠRuby\":19642,\"ĠFi\":19643,\"123\":19644,\"ĠArabic\":19645,\"Ġlasts\":19646,\"ĠIvy\":19647,\"ĠWid\":19648,\"rown\":19649,\"stick\":19650,\"?'\\\"\":19651,\"ĠSTEM\":19652,\"Ġsensible\":19653,\"htar\":19654,\"Ġharbor\":19655,\"Ġcra\":19656,\"ĠAlbum\":19657,\"ĠCarnival\":19658,\"Ġimplies\":19659,\"agement\":19660,\"ĠInitially\":19661,\"Ġchooses\":19662,\"Jeff\":19663,\"ĠHig\":19664,\"Ġtam\":19665,\"Ġlump\":19666,\"ucks\":19667,\"Ġrepatri\":19668,\"ĠMercy\":19669,\"zza\":19670,\"Ġ365\":19671,\"ĠRicardo\":19672,\"ogram\":19673,\"Ġundergone\":19674,\"system\":19675,\"Ġtel\":19676,\"ĠKee\":19677,\"ully\":19678,\"istas\":19679,\"Ġgrains\":19680,\"ĠTomorrow\":19681,\"ĠRC\":19682,\"ĠTurk\":19683,\"Ġfreshmen\":19684,\"ĠAway\":19685,\"ĠSach\":19686,\"ĠUltimate\":19687,\"Ġoffensively\":19688,\"ismo\":19689,\"Ġteaser\":19690,\"ĠJud\":19691,\"Ġlegitimacy\":19692,\"opt\":19693,\"ĠCobb\":19694,\"Ġrejecting\":19695,\"ĠSolo\":19696,\"ĠArcher\":19697,\"Ġsoutheastern\":19698,\"ĠPlain\":19699,\"ĠLoss\":19700,\"Ġminerals\":19701,\"ĠMari\":19702,\"Ġscrambling\":19703,\"ĠPeak\":19704,\"Ġhavoc\":19705,\"rings\":19706,\"Ġunofficial\":19707,\"ĠHaj\":19708,\"director\":19709,\"ĠCanal\":19710,\"ĠNSA\":19711,\"ĠEaton\":19712,\"ĠPART\":19713,\"ĠCommissioners\":19714,\"Ġwellbeing\":19715,\"resa\":19716,\"Ġunderstandable\":19717,\"dates\":19718,\"ĠSorry\":19719,\"Ġastonishing\":19720,\"Ġrevise\":19721,\"ĠEc\":19722,\"ĠLack\":19723,\"endi\":19724,\"endale\":19725,\"also\":19726,\"Ġcolder\":19727,\"Ġheel\":19728,\"Ġcellular\":19729,\"Conn\":19730,\"ĠThur\":19731,\"Ġmassage\":19732,\"olla\":19733,\"clus\":19734,\"Ġtoilets\":19735,\"ĠCelebr\":19736,\"Ġtackled\":19737,\"Ġchorus\":19738,\"ETA\":19739,\"anca\":19740,\"ĠOLED\":19741,\"Ġpunk\":19742,\"ĠBrain\":19743,\"ĠNuggets\":19744,\"Ġseamless\":19745,\"make\":19746,\"atted\":19747,\"ĠRog\":19748,\"ĠPatch\":19749,\"Ġruined\":19750,\"Ins\":19751,\"Ġconsolidate\":19752,\"Ġgospel\":19753,\"ĠCaption\":19754,\"Ġoverweight\":19755,\"Ġscreened\":19756,\"ĠKraft\":19757,\"ĠBain\":19758,\"breaker\":19759,\"ĠFeinstein\":19760,\"ĠDoc\":19761,\"Ġdeepest\":19762,\"ĠOL\":19763,\"Ġtunes\":19764,\"Ġrightly\":19765,\"ĠLanc\":19766,\"ĠBrotherhood\":19767,\"Ġpoultry\":19768,\"ĠPure\":19769,\"Ġstimulate\":19770,\"Ġdiscourse\":19771,\"ĠStark\":19772,\"Ġmuseums\":19773,\"ention\":19774,\"Ġtaxation\":19775,\"ĠAkron\":19776,\"ayer\":19777,\"ĠKirby\":19778,\"farm\":19779,\"oser\":19780,\"Ġcommend\":19781,\"Ġunarmed\":19782,\"ensions\":19783,\"Ġsuperst\":19784,\"Ġoceans\":19785,\"Ġmisuse\":19786,\"LO\":19787,\"ĠByrne\":19788,\"ĠMaritime\":19789,\"Ġdense\":19790,\"Ġexcuses\":19791,\"Ġsuppose\":19792,\"ĠMarks\":19793,\"Ġrainy\":19794,\"Ġreplicate\":19795,\"Ġboutique\":19796,\"ĠRenaissance\":19797,\"jas\":19798,\"icted\":19799,\"Ġreferenced\":19800,\"ĠTir\":19801,\"ĠHatch\":19802,\"ĠCry\":19803,\"ĠPayPal\":19804,\"Ġfulfil\":19805,\"ĠHawaiian\":19806,\"come\":19807,\"ĠThirty\":19808,\"Ġ260\":19809,\"ĠYak\":19810,\"Ġangles\":19811,\"Ġlandlord\":19812,\"Ġlavish\":19813,\"Women\":19814,\"ĠNT\":19815,\"Ġreinforced\":19816,\"Ġprevail\":19817,\"ĠCommunities\":19818,\"Ġfootwear\":19819,\"Ġassurances\":19820,\"Ġlb\":19821,\"Ġairing\":19822,\"Ġresorts\":19823,\"ĠFiji\":19824,\"ĠShay\":19825,\"Ġprevailing\":19826,\"many\":19827,\"Ġimpe\":19828,\"ĠDul\":19829,\"Ġsymbols\":19830,\"zb\":19831,\"ĠCere\":19832,\"Ġapplauded\":19833,\"Ġsoundtrack\":19834,\"Ġdrunken\":19835,\"ĠEuropeans\":19836,\"Ġherds\":19837,\"moving\":19838,\"WR\":19839,\"ĠHindi\":19840,\"Ġwaking\":19841,\"Jo\":19842,\"Andrew\":19843,\"rosse\":19844,\"ĠLegislative\":19845,\"Ġdisgrace\":19846,\"Nothing\":19847,\"ĠBulgaria\":19848,\"Ġhumidity\":19849,\"Ġtranslation\":19850,\"Ġmeasurements\":19851,\"Ġvying\":19852,\"ĠBrid\":19853,\"Max\":19854,\"Ġdir\":19855,\"unci\":19856,\"Ġdefines\":19857,\"Ġperfection\":19858,\"ancers\":19859,\"Matt\":19860,\"ĠShinzo\":19861,\"ĠPresidents\":19862,\"Ġginger\":19863,\"onna\":19864,\"existing\":19865,\"rika\":19866,\"enced\":19867,\"ĠBray\":19868,\"Ġgall\":19869,\"Ġdisrespect\":19870,\"ĠCumber\":19871,\"Ġcontestant\":19872,\"ucky\":19873,\"anticipated\":19874,\"abled\":19875,\"LLOW\":19876,\"Bel\":19877,\"ĠKear\":19878,\"Ġstoryline\":19879,\"Ġrigs\":19880,\"ĠScots\":19881,\"ĠChap\":19882,\"ĠThankfully\":19883,\"Ġcommunist\":19884,\"ĠAdviser\":19885,\"Ġregist\":19886,\"Ġannoying\":19887,\"ĠDVD\":19888,\"Ġethic\":19889,\"ĠFilipino\":19890,\"ĠAdidas\":19891,\"Ġbilling\":19892,\"Ġalleviate\":19893,\"Ġsmoked\":19894,\"Ġhazard\":19895,\"EV\":19896,\"Ag\":19897,\"baum\":19898,\"Ġdoses\":19899,\"Ġoutcry\":19900,\"Ġinclined\":19901,\"Ġpsychologist\":19902,\"itzer\":19903,\"January\":19904,\"Ġmornings\":19905,\"aught\":19906,\"Ġsurreal\":19907,\"ĠCannon\":19908,\"avy\":19909,\"ĠCris\":19910,\"cf\":19911,\"Ġinterpreted\":19912,\"Ġpersecution\":19913,\"vation\":19914,\"Ġupfront\":19915,\"ĠWaste\":19916,\"Ġmills\":19917,\"Ġbombings\":19918,\"ĠHeaven\":19919,\"ĠFlat\":19920,\"Ġboxer\":19921,\"Ġavenues\":19922,\"Invest\":19923,\"ĠZika\":19924,\"Ġbackstage\":19925,\"idas\":19926,\"eston\":19927,\"ead\":19928,\"Ġbishops\":19929,\"Ġrender\":19930,\"Ġfootballer\":19931,\"Ġspilled\":19932,\"Only\":19933,\"Ġsaddened\":19934,\"ĠAbove\":19935,\"inator\":19936,\"tro\":19937,\"onen\":19938,\"ĠAMC\":19939,\"Ġstringent\":19940,\"Ġfooting\":19941,\"ĠGhost\":19942,\"Ġtexting\":19943,\"ĠCPI\":19944,\"ĠUW\":19945,\"Ġaccol\":19946,\"iries\":19947,\"ĠFlex\":19948,\"ĠCarolyn\":19949,\"Andre\":19950,\"Ġsiege\":19951,\"Muslim\":19952,\"Ġautomobile\":19953,\"reci\":19954,\"Ġdean\":19955,\"atre\":19956,\"Ġwax\":19957,\"Ġwo\":19958,\"ĠDuffy\":19959,\"Ġfiance\":19960,\"Ġfib\":19961,\"Ġeagle\":19962,\"ĠCatal\":19963,\"Ġinfants\":19964,\"Ġsubmitting\":19965,\"Ġdownhill\":19966,\"Ġstaffer\":19967,\"ĠLights\":19968,\"Ġeater\":19969,\"ĠCaliforn\":19970,\"Ġsupervisors\":19971,\"ĠPy\":19972,\"Ġcondemnation\":19973,\"Ġsci\":19974,\"Ġhated\":19975,\"Ġtil\":19976,\"ĠLavrov\":19977,\"Ġsab\":19978,\"Ġmotors\":19979,\"Ġlogging\":19980,\"ĠOwn\":19981,\"Ġpi\":19982,\"Ġrepeating\":19983,\"ĠDOJ\":19984,\"enary\":19985,\"ĠChow\":19986,\"fat\":19987,\"Ġbalcony\":19988,\"orie\":19989,\"NING\":19990,\"ĠUnified\":19991,\"Neil\":19992,\"Bill\":19993,\"ĠSims\":19994,\"uten\":19995,\"LV\":19996,\"ĠEMS\":19997,\"Ġsip\":19998,\"Ġreplaces\":19999,\"ichi\":20000,\"ĠFig\":20001,\"ĠCharity\":20002,\"Ġpeek\":20003,\"Ġrack\":20004,\"Ġcousins\":20005,\"Ġresolving\":20006,\"Ġthrone\":20007,\"ĠEngine\":20008,\"ĠChak\":20009,\"Ġlamented\":20010,\"Ġwipe\":20011,\"Ġnutrients\":20012,\"ĠChat\":20013,\"AMP\":20014,\"ĠOprah\":20015,\"uming\":20016,\"serving\":20017,\"Ġfir\":20018,\"Ġlandlords\":20019,\"neck\":20020,\"Ġupload\":20021,\"Ġunspecified\":20022,\"Ġicy\":20023,\"´\":20024,\"Ġze\":20025,\"Ġprohibits\":20026,\"ĠFI\":20027,\"Res\":20028,\"ĠEff\":20029,\"hell\":20030,\"umbo\":20031,\"Ġreceipts\":20032,\"Ġoperatives\":20033,\"stant\":20034,\"Ġwives\":20035,\"ĠCinema\":20036,\"Ġnegligence\":20037,\"Ġgases\":20038,\"ĠLau\":20039,\"Ġbrew\":20040,\"August\":20041,\"never\":20042,\"Ġpenned\":20043,\"Ġincomplete\":20044,\"ĠZh\":20045,\"esi\":20046,\"Ġranged\":20047,\"apolis\":20048,\"Ġwithdrawing\":20049,\"ĠLevi\":20050,\"ĠLevy\":20051,\"ĠDaly\":20052,\"Ġdelaying\":20053,\"ĠMSNBC\":20054,\"ĠCyrus\":20055,\"ĠNutrition\":20056,\"NN\":20057,\"Ġwinding\":20058,\"Ġglow\":20059,\"ĠMY\":20060,\"Ġgoodwill\":20061,\"ĠMON\":20062,\"Ġslots\":20063,\"ĠNina\":20064,\"ĠFIR\":20065,\"ĠLTE\":20066,\"ĠInnov\":20067,\"dev\":20068,\"ctic\":20069,\"Ġanalyses\":20070,\"ĠBangalore\":20071,\"Ġtales\":20072,\"Ġovercame\":20073,\"ĠThurs\":20074,\"Ġcherry\":20075,\"ĠNou\":20076,\"ĠFlowers\":20077,\"1000\":20078,\"updated\":20079,\"rieve\":20080,\"ĠBeautiful\":20081,\"iak\":20082,\"Ġplayback\":20083,\"Ġheadset\":20084,\"Ġashamed\":20085,\"Min\":20086,\"Ġadm\":20087,\"ĠLucky\":20088,\"ĠTucson\":20089,\"Ġentirety\":20090,\"ranging\":20091,\"ĠVance\":20092,\"kered\":20093,\"image\":20094,\"ĠGord\":20095,\"War\":20096,\"Ġsimilarities\":20097,\"dig\":20098,\"ĠJude\":20099,\"Ġlonely\":20100,\"hra\":20101,\"ĠStaples\":20102,\"ĠACA\":20103,\"Ġmeasurement\":20104,\"Ġcooper\":20105,\"ATER\":20106,\"ĠMeng\":20107,\"Ġbarring\":20108,\"190\":20109,\"ĠBatt\":20110,\"Ġreproductive\":20111,\"ĠRowe\":20112,\"Ġsubsid\":20113,\"Ġslogans\":20114,\"ugar\":20115,\"ĠKeller\":20116,\"ingham\":20117,\"fuel\":20118,\"Ġhid\":20119,\"afe\":20120,\"Ġindul\":20121,\"cash\":20122,\"Ġstressing\":20123,\"ĠMIT\":20124,\"Ġtrump\":20125,\"ancer\":20126,\"ĠPes\":20127,\"ĠMint\":20128,\"Ġcrossover\":20129,\"ĠWeiss\":20130,\"ĠElvis\":20131,\"ĠPermanent\":20132,\"ĠKhalid\":20133,\"Ġunjust\":20134,\"Ġexceptionally\":20135,\"Ġfut\":20136,\"Ġavid\":20137,\"ĠEthics\":20138,\"Ġutilized\":20139,\"Ġfeasibility\":20140,\"Ġcatering\":20141,\"Press\":20142,\"wayne\":20143,\"October\":20144,\"Ġfavors\":20145,\"Ġobsession\":20146,\"Ġmelt\":20147,\"Ġmug\":20148,\"ĠMK\":20149,\"Ġapples\":20150,\"Ġvine\":20151,\"cliffe\":20152,\"Ġgrat\":20153,\"Ġspells\":20154,\"ounced\":20155,\"Ġdecree\":20156,\"issy\":20157,\"Team\":20158,\"Ġdeploying\":20159,\"Feb\":20160,\"Ġmiserable\":20161,\"Ġwat\":20162,\"ĠBust\":20163,\"ĠNorris\":20164,\"ĠTimberwolves\":20165,\"Ġangered\":20166,\"ĠArn\":20167,\"oft\":20168,\"rome\":20169,\"Ġadvertisements\":20170,\"onal\":20171,\"Ġnun\":20172,\"Ġtorque\":20173,\"Ġslave\":20174,\"Ġnonsense\":20175,\"Ġcoy\":20176,\"Ġcites\":20177,\"Game\":20178,\"Ġarchitects\":20179,\"playing\":20180,\"Ġgener\":20181,\"Ġsocio\":20182,\"Ġmeditation\":20183,\"Ġforgive\":20184,\"Ġsmiled\":20185,\"%),\":20186,\"Ġpers\":20187,\"ĠSoph\":20188,\"Ġoccupy\":20189,\"atton\":20190,\"Ġwitnessing\":20191,\"Ġapologise\":20192,\"Ġpredecessors\":20193,\"ĠCassidy\":20194,\"Ġtallied\":20195,\"NER\":20196,\"Ġtract\":20197,\"ĠHolder\":20198,\"ĠPav\":20199,\"Ġjackets\":20200,\"Mel\":20201,\"raud\":20202,\"Ġexercising\":20203,\"ĠChung\":20204,\"ĠAmin\":20205,\"athi\":20206,\"ĠMem\":20207,\"Ġracked\":20208,\"Ġcarved\":20209,\"ĠMickey\":20210,\"ĠLafayette\":20211,\"Ġgrill\":20212,\"ĠINFORMATION\":20213,\"usc\":20214,\"ĠPromotion\":20215,\"yson\":20216,\"istry\":20217,\"Ġfulfilled\":20218,\"Ġrestraint\":20219,\"Ġpopping\":20220,\"ĠSlater\":20221,\"Ġmercy\":20222,\"aden\":20223,\"Ġsubmarine\":20224,\"ĠBowling\":20225,\"dogs\":20226,\"ĠSwe\":20227,\"Ġnoticeable\":20228,\"Ġbis\":20229,\"ĠPremiership\":20230,\"Ġspat\":20231,\"ĠTow\":20232,\"ĠWand\":20233,\"Ġmechanics\":20234,\"while\":20235,\"ĠBenson\":20236,\"Ġmolecules\":20237,\"Ġcrosses\":20238,\"Ġrecalling\":20239,\"ĠCertainly\":20240,\"HAM\":20241,\"Ġsever\":20242,\"ĠRudy\":20243,\"ĠDUI\":20244,\"OLD\":20245,\"ĠTobacco\":20246,\"Ġsubdued\":20247,\"Ġquota\":20248,\"TF\":20249,\"Ġflats\":20250,\"Ġemphasize\":20251,\"Ġbelts\":20252,\"ĠOpinion\":20253,\"Ġpiled\":20254,\"ĠSpark\":20255,\"ĠElias\":20256,\"Ġclassification\":20257,\"ĠHands\":20258,\"ĠCV\":20259,\"Ġtoast\":20260,\"Ġcandle\":20261,\"atching\":20262,\"short\":20263,\"ĠDup\":20264,\"Ġult\":20265,\"bats\":20266,\"Ġmarketers\":20267,\"ĠAvery\":20268,\"ĠColbert\":20269,\"ĠIk\":20270,\"ĠVac\":20271,\"ĠJackets\":20272,\"Ġmerits\":20273,\"eli\":20274,\"PORT\":20275,\"Ġelevator\":20276,\"irming\":20277,\"effective\":20278,\"Ġgroceries\":20279,\"Ġhi\":20280,\"ĠINTER\":20281,\"ĠSAP\":20282,\"ĠNYPD\":20283,\"ĠKY\":20284,\"Ġangel\":20285,\"Ġspectacle\":20286,\"rÃ©\":20287,\"ĠRoche\":20288,\"Ġinsects\":20289,\"Ġcommenced\":20290,\"ĠFoley\":20291,\"Ġdarker\":20292,\"ĠUg\":20293,\"ĠMostly\":20294,\"Ġtermed\":20295,\"uci\":20296,\"ĠExec\":20297,\"ĠBrittany\":20298,\"Ġharmony\":20299,\"Ġadvocated\":20300,\"Ġparcel\":20301,\"ĠHots\":20302,\"Ġmonarch\":20303,\"ĠSiri\":20304,\"odge\":20305,\"ĠPag\":20306,\"Ġprogressing\":20307,\"grounds\":20308,\"Ġonstage\":20309,\"Ġwarmth\":20310,\"ĠWon\":20311,\"Ġviolates\":20312,\"ĠSaudis\":20313,\"Ġbumper\":20314,\"Ġpatrols\":20315,\"ĠBarron\":20316,\"Ġindoors\":20317,\"Ġtar\":20318,\"Each\":20319,\"Val\":20320,\"Ġapplicant\":20321,\"ĠCater\":20322,\"Ġclassics\":20323,\"ĠThreat\":20324,\"Ġwrapping\":20325,\"ĠIdlib\":20326,\"anking\":20327,\"Did\":20328,\"adia\":20329,\"ĠRig\":20330,\"ĠBram\":20331,\"ĠLaurie\":20332,\"ĠHair\":20333,\"ĠCannabis\":20334,\"Ġdaylight\":20335,\"ĠNorm\":20336,\"ĠRip\":20337,\"sin\":20338,\"unta\":20339,\"Pass\":20340,\"ĠAcad\":20341,\"ĠCummings\":20342,\"Ġtheirs\":20343,\"ĠDistribution\":20344,\"especially\":20345,\"Ġgrilled\":20346,\"Ġaffiliates\":20347,\"ĠVander\":20348,\"ĠCath\":20349,\"ĠProductions\":20350,\"ĠTrek\":20351,\"230\":20352,\"Ġcasinos\":20353,\"ĠCain\":20354,\"atu\":20355,\"idget\":20356,\"ĠWinds\":20357,\"Ġunanswered\":20358,\"Ġintercept\":20359,\"ĠMarty\":20360,\"Ġrefin\":20361,\"Ġlieutenant\":20362,\"cas\":20363,\"Chief\":20364,\"average\":20365,\"ilot\":20366,\"Ġscrimmage\":20367,\"ĠMud\":20368,\"speaking\":20369,\"ĠFranken\":20370,\"ĠTories\":20371,\"Ġabstract\":20372,\"awar\":20373,\"ĠTerms\":20374,\"dal\":20375,\"ĠFur\":20376,\"Ġhumour\":20377,\"rh\":20378,\"Ġsitu\":20379,\"aed\":20380,\"ĠFIN\":20381,\"Ġtranscripts\":20382,\"approved\":20383,\"ĠParsons\":20384,\"Ġpigs\":20385,\"Ġrepayment\":20386,\"ĠARM\":20387,\"ĠElliot\":20388,\"ĠLevine\":20389,\"Ġtagged\":20390,\"pun\":20391,\"ĠDwight\":20392,\"Ġconfiguration\":20393,\"sis\":20394,\"ĠAdult\":20395,\"Ġearthquakes\":20396,\"Ġcreature\":20397,\"ĠMRI\":20398,\"Ġmach\":20399,\"Ġprescriptions\":20400,\"cover\":20401,\"Ġministries\":20402,\"Ġinaccurate\":20403,\"ĠLabs\":20404,\"ĠMGM\":20405,\"Ġtomato\":20406,\"Ġeng\":20407,\"Ġopposes\":20408,\"owan\":20409,\"Ġmapping\":20410,\"Ġconsum\":20411,\"online\":20412,\"eters\":20413,\"code\":20414,\"Aug\":20415,\"Point\":20416,\"branded\":20417,\"pling\":20418,\"ĠCalder\":20419,\"Oper\":20420,\"ĠMiddles\":20421,\"Ġchampagne\":20422,\"ĠTues\":20423,\"Ġsampling\":20424,\"Ġenergetic\":20425,\"rano\":20426,\"ĠStyles\":20427,\"Ġneglected\":20428,\"ĠDamon\":20429,\"Ġendanger\":20430,\"Ġsouthwestern\":20431,\"ĠATM\":20432,\"ĠDuck\":20433,\"engers\":20434,\"Ġdan\":20435,\"yth\":20436,\"Ġbou\":20437,\"ĠDecl\":20438,\"Gold\":20439,\"Ġprojecting\":20440,\"Google\":20441,\"ĠHussein\":20442,\"Ġaccomplishment\":20443,\"itarian\":20444,\"Ġgossip\":20445,\"ĠRai\":20446,\"ril\":20447,\"ĠSke\":20448,\"Ġpsychiatric\":20449,\"ĠMacBook\":20450,\"ĠAdobe\":20451,\"ĠHodg\":20452,\"Ġaccompany\":20453,\"Ġadvertised\":20454,\"Ġreminiscent\":20455,\"Ġgeographical\":20456,\"Ġconvertible\":20457,\"IK\":20458,\"CTV\":20459,\"Ġcommunal\":20460,\"Ġchim\":20461,\"Ġselfish\":20462,\"Ġdrilled\":20463,\"Ġtortured\":20464,\"Ġblacks\":20465,\"noon\":20466,\"Ġmanifesto\":20467,\"ĠRichie\":20468,\"acco\":20469,\"Im\":20470,\"Ġdebit\":20471,\"ĠSNP\":20472,\"perfect\":20473,\"gard\":20474,\"ĠRatio\":20475,\"Ġstubborn\":20476,\"Ġaccumulation\":20477,\"Ġcongregation\":20478,\"Ġkissing\":20479,\"Ġkillers\":20480,\"ĠAbbey\":20481,\"von\":20482,\"ĠFuj\":20483,\"ĠIsabel\":20484,\"NB\":20485,\"ĠNish\":20486,\"ĠJulius\":20487,\"ĠZimmer\":20488,\"Ġuncover\":20489,\"dar\":20490,\"isle\":20491,\"ĠCompar\":20492,\"Ġcounselor\":20493,\"ĠSok\":20494,\"ĠCumm\":20495,\"ĠHip\":20496,\"Ġurgently\":20497,\"Ġrentals\":20498,\"Ġapproving\":20499,\"Ġirrigation\":20500,\"Ġprostate\":20501,\"ĠJudicial\":20502,\"ĠSubmit\":20503,\"ĠTanner\":20504,\"attack\":20505,\"emb\":20506,\"Ġreclaim\":20507,\"Ġec\":20508,\"Ġbrutality\":20509,\"Ġcommanding\":20510,\"Ġreasoning\":20511,\"Roy\":20512,\"ĠElect\":20513,\"ĠMobil\":20514,\"anding\":20515,\"Ġmirrors\":20516,\"Israel\":20517,\"Ġpavement\":20518,\"Ġoverdue\":20519,\"ĠMd\":20520,\"street\":20521,\"Ġthrill\":20522,\"pora\":20523,\"azon\":20524,\"Ġbrewing\":20525,\"enge\":20526,\"ĠDisaster\":20527,\"Ġbuilder\":20528,\"ods\":20529,\"utsch\":20530,\"Ġterminals\":20531,\"ĠBaird\":20532,\"enburg\":20533,\"Ġhast\":20534,\"Ġbrass\":20535,\"Ġparental\":20536,\"enture\":20537,\"ĠConduct\":20538,\"Ġexpands\":20539,\"luck\":20540,\"mur\":20541,\"ĠBj\":20542,\"Ġadministrations\":20543,\"ĠOlivier\":20544,\"oux\":20545,\"Ġnarrowed\":20546,\"winner\":20547,\"Ġmakeshift\":20548,\"ĠVAT\":20549,\"ĠJavier\":20550,\"-,\":20551,\"Ġsystematic\":20552,\"Ġenforcing\":20553,\"emin\":20554,\"ĠAudio\":20555,\"United\":20556,\"gener\":20557,\"ĠKara\":20558,\"ivas\":20559,\"ĠPretty\":20560,\"ĠLob\":20561,\"Ġpetitions\":20562,\"ĠMercer\":20563,\"ampa\":20564,\"product\":20565,\"Ġdistributing\":20566,\"Ġtunnels\":20567,\"Ġcondo\":20568,\"ĠRSS\":20569,\"ĠCarlo\":20570,\"Ġpumpkin\":20571,\"Ġsto\":20572,\"Ġassumes\":20573,\"oway\":20574,\"hiba\":20575,\"lection\":20576,\"Ġgam\":20577,\"ĠAires\":20578,\"Ġtransmitted\":20579,\"Ġtrousers\":20580,\"Ġcheers\":20581,\"ĠJensen\":20582,\"Ġemer\":20583,\"Ġsimpler\":20584,\"Ġcolored\":20585,\"ĠSustainable\":20586,\"Ġinstruct\":20587,\"Ġpoles\":20588,\"Ġsupervised\":20589,\"Ġinteg\":20590,\"ĠMoreno\":20591,\"boarding\":20592,\"igrant\":20593,\"ĠYoga\":20594,\"Ġenvironmentally\":20595,\"Ġsacrifices\":20596,\"Ġshores\":20597,\"Ġ127\":20598,\"Ġestranged\":20599,\"Ġintoxicated\":20600,\"Ġemergencies\":20601,\"ĠKosovo\":20602,\"yang\":20603,\"Ġfastball\":20604,\"Ġpackaged\":20605,\"LAN\":20606,\"Ġhurry\":20607,\"ĠManny\":20608,\"Ġporch\":20609,\"Ġcuriosity\":20610,\"ĠKend\":20611,\"thouse\":20612,\"ĠTou\":20613,\"mun\":20614,\"Ġwaving\":20615,\"Ġpasswords\":20616,\"ĠSwan\":20617,\"Ġprefers\":20618,\"ĠCorrections\":20619,\"aic\":20620,\"Ġejected\":20621,\"Ġdossier\":20622,\"ĠChal\":20623,\"Ġfacto\":20624,\"Ġspine\":20625,\"leck\":20626,\"Ġrestriction\":20627,\"Ġdisagreement\":20628,\"grown\":20629,\"ĠEdgar\":20630,\"Ġquantities\":20631,\"ĠRapid\":20632,\"Ġpals\":20633,\"Ġspared\":20634,\"Ġremarkably\":20635,\"ructure\":20636,\"Ġbackers\":20637,\"ĠGoals\":20638,\"cles\":20639,\"rolling\":20640,\"ĠBlasio\":20641,\"Ġorchestra\":20642,\"ologies\":20643,\"ĠRise\":20644,\"Power\":20645,\"Ġuptick\":20646,\"atha\":20647,\"ĠMob\":20648,\"Ġshotgun\":20649,\"downs\":20650,\"ĠBorg\":20651,\"Ġmorale\":20652,\"Call\":20653,\"wave\":20654,\"ĠDuc\":20655,\"Ġunwilling\":20656,\"oad\":20657,\"Ġbusinessmen\":20658,\"Ġrefriger\":20659,\"Ġgamers\":20660,\"Ġcele\":20661,\"Ġprecip\":20662,\"Ġrenegoti\":20663,\"OY\":20664,\"ĠPharm\":20665,\"Ġresponsive\":20666,\"Ġservant\":20667,\"eye\":20668,\"Ġraping\":20669,\"vas\":20670,\"Ġgroin\":20671,\"ĠMelvin\":20672,\"ĠKurds\":20673,\"Ġstricter\":20674,\"ĠMum\":20675,\"ients\":20676,\"Ġstandalone\":20677,\"Ġforums\":20678,\"Ġcommemorate\":20679,\"Far\":20680,\"ĠTelegram\":20681,\"Ġscreenings\":20682,\"ĠLeonardo\":20683,\"ighton\":20684,\"ĠDOWN\":20685,\"Ġmodule\":20686,\"Ġremedy\":20687,\"Ġ280\":20688,\"Su\":20689,\"ĠBecker\":20690,\"ĠGast\":20691,\"prem\":20692,\"ĠInto\":20693,\"oyle\":20694,\"114\":20695,\"Ġadhere\":20696,\"Report\":20697,\"ĠJaneiro\":20698,\"ĠKry\":20699,\"Pakistan\":20700,\"Ġrobotic\":20701,\"ande\":20702,\"Ġoverlooking\":20703,\"ĠTreaty\":20704,\"Ġrect\":20705,\"yne\":20706,\"Ġbattlefield\":20707,\"ĠGeoff\":20708,\"Ġearns\":20709,\"ĠMiner\":20710,\"Ġteased\":20711,\"Ġexemptions\":20712,\"Ġvacancy\":20713,\"oku\":20714,\"Ġvulnerabilities\":20715,\"ĠRou\":20716,\"Ġobserv\":20717,\"Ġoverlook\":20718,\"Ġcorrespond\":20719,\"Ġtheatrical\":20720,\"Ġrobotics\":20721,\"ĠCompl\":20722,\"ĠPasadena\":20723,\"laden\":20724,\"Ġvastly\":20725,\"olit\":20726,\"Ġjustification\":20727,\"Ġtampering\":20728,\"ĠSutherland\":20729,\"ĠMens\":20730,\"Ġinvisible\":20731,\"uren\":20732,\"ĠAshton\":20733,\"owl\":20734,\"Ġdisqual\":20735,\"ĠEva\":20736,\"Ġfriction\":20737,\"ĠIrvine\":20738,\"Ġaliens\":20739,\"ĠPension\":20740,\"ĠAssets\":20741,\"ĠBenedict\":20742,\"ittal\":20743,\"Ġsword\":20744,\"Ġunderwear\":20745,\"ĠFarmer\":20746,\"Ġtimber\":20747,\"Ġdependence\":20748,\"ĠTang\":20749,\"Ġ165\":20750,\"ĠNazis\":20751,\"Ġpunching\":20752,\"ĠGloria\":20753,\"usat\":20754,\"Ġluxurious\":20755,\"chuk\":20756,\"ĠCot\":20757,\"Ġregained\":20758,\"Ġreassure\":20759,\"Ġhello\":20760,\"Ġante\":20761,\"Ġnegotiators\":20762,\"Add\":20763,\"paced\":20764,\"Ã©r\":20765,\"Ġdemolished\":20766,\"Ann\":20767,\"joy\":20768,\"ĠJenna\":20769,\"Apple\":20770,\"Ġdisturbance\":20771,\"Ġcommissions\":20772,\"ĠPolitico\":20773,\"along\":20774,\"Ġnem\":20775,\"Ġauctions\":20776,\"ruck\":20777,\"ĠOD\":20778,\"ofer\":20779,\"Play\":20780,\"Ġcarn\":20781,\"vez\":20782,\"Ġtents\":20783,\"Ġcongratulate\":20784,\"ĠLiquid\":20785,\"ĠCoyotes\":20786,\"uku\":20787,\"ĠAllah\":20788,\"Ġbend\":20789,\"Ġcanvas\":20790,\"ĠClifford\":20791,\"Ġvolunteered\":20792,\"Luc\":20793,\"bp\":20794,\"ĠCensus\":20795,\"ĠShot\":20796,\"Ġanonymously\":20797,\"ĠAnglo\":20798,\"ĠBayer\":20799,\"ĠAber\":20800,\"ĠCorrectional\":20801,\"Ġhardship\":20802,\"ĠBuenos\":20803,\"ĠDaw\":20804,\"Ġbaskets\":20805,\"Ġupstairs\":20806,\"Ġmindful\":20807,\"ĠLCD\":20808,\"ĠBlackburn\":20809,\"ĠHale\":20810,\"477\":20811,\"Ġcircus\":20812,\"ĠDragons\":20813,\"Ġrubble\":20814,\"rb\":20815,\"Ġheadaches\":20816,\"aunt\":20817,\"itus\":20818,\"Ġscaled\":20819,\"ĠComic\":20820,\"asio\":20821,\"ĠNordic\":20822,\"Per\":20823,\"Ġbombers\":20824,\"ilitation\":20825,\"Ġindirectly\":20826,\"ĠHod\":20827,\"andan\":20828,\"operation\":20829,\"Ġpuppy\":20830,\"ĠMats\":20831,\"Ġstewards\":20832,\"roup\":20833,\"Ġmemorandum\":20834,\"Ġpatio\":20835,\"const\":20836,\"ĠBold\":20837,\"ĠKaiser\":20838,\"Following\":20839,\"Ġcompat\":20840,\"Ġsidewalks\":20841,\"ĠFitzpatrick\":20842,\"Ġsunlight\":20843,\"ĠLever\":20844,\"ĠBecky\":20845,\"icles\":20846,\"ĠProbably\":20847,\"Ġgarner\":20848,\"ĠTomas\":20849,\"Ġblankets\":20850,\"uga\":20851,\"jiang\":20852,\"Ġrevel\":20853,\"ĠHutch\":20854,\"llers\":20855,\"Ġtrimmed\":20856,\"ĠSTR\":20857,\"ĠKR\":20858,\"ĠPike\":20859,\"ĠASS\":20860,\"Bay\":20861,\"Ġdiagnostic\":20862,\"ĠSteph\":20863,\"Ġtoured\":20864,\"ĠAvoid\":20865,\"vic\":20866,\"Without\":20867,\"ĠClinical\":20868,\"Ġblo\":20869,\"undo\":20870,\"ĠBoise\":20871,\"Ġspeculated\":20872,\"ĠProt\":20873,\"vention\":20874,\"Ġscholar\":20875,\"ĠSta\":20876,\"Featured\":20877,\"ĠPrev\":20878,\"Ġpenny\":20879,\"ĠHath\":20880,\"rawn\":20881,\"Ġrenovated\":20882,\"ĠFried\":20883,\"itol\":20884,\"uddle\":20885,\"Ġinquest\":20886,\"Ġmetropolitan\":20887,\"lights\":20888,\"Ġtempo\":20889,\"onom\":20890,\"ĠImport\":20891,\"Asia\":20892,\"Ġowes\":20893,\"Ġmagistrate\":20894,\"ĠFriedman\":20895,\"Ġcontacting\":20896,\"Ġstrains\":20897,\"Ġhomage\":20898,\"Ġlent\":20899,\"ception\":20900,\"git\":20901,\"Ġlively\":20902,\"Ġscra\":20903,\"WW\":20904,\"Ã¶n\":20905,\"rill\":20906,\"Jack\":20907,\"ĠShank\":20908,\"iani\":20909,\"Ġdecreasing\":20910,\"MON\":20911,\"ĠSupervisor\":20912,\"ĠCats\":20913,\"ĠFusion\":20914,\"Ġracially\":20915,\"ĠTara\":20916,\"ĠPurchase\":20917,\"ĠRally\":20918,\"ĠGraph\":20919,\"ĠHello\":20920,\"hest\":20921,\"ĠVarg\":20922,\"Ġdrowned\":20923,\"ĠThu\":20924,\"ĠWet\":20925,\"ĠEug\":20926,\"Ġrainbow\":20927,\"Ġtelev\":20928,\"ĠAmir\":20929,\"Based\":20930,\"Ġcookie\":20931,\"uding\":20932,\"Ġcontracting\":20933,\"Ġobjected\":20934,\"Ġfork\":20935,\"acent\":20936,\"ĠTil\":20937,\"ĠLilly\":20938,\"ĠEur\":20939,\"Ġhormone\":20940,\"Ġnails\":20941,\"ĠFischer\":20942,\"Ġpier\":20943,\"EMENT\":20944,\"Ġeruption\":20945,\"visory\":20946,\"Ġspeculate\":20947,\"apan\":20948,\"ĠJub\":20949,\"ĠHuckabee\":20950,\"string\":20951,\"stay\":20952,\"Ġsustaining\":20953,\"VM\":20954,\"Ġpriv\":20955,\"Ġclos\":20956,\"Ġdownloaded\":20957,\"ĠIv\":20958,\"Ġfinanced\":20959,\"ĠSao\":20960,\"ĠEverett\":20961,\"rene\":20962,\"ĠWo\":20963,\"ĠPiet\":20964,\"Ġengulfed\":20965,\"Ġexiting\":20966,\"uni\":20967,\"horn\":20968,\"Ġgrav\":20969,\"ection\":20970,\"Ġdrainage\":20971,\"Ġfuelled\":20972,\"Ġorganizational\":20973,\"bike\":20974,\"ĠAreas\":20975,\"Ġpoliceman\":20976,\"ĠFirm\":20977,\"ĠSlide\":20978,\"Ġrand\":20979,\"ĠJedi\":20980,\"Ge\":20981,\"really\":20982,\"Manchester\":20983,\"ĠWise\":20984,\"parent\":20985,\"Ġlad\":20986,\"Ġurine\":20987,\"ĠColombian\":20988,\"geon\":20989,\"Ġ1961\":20990,\"Mania\":20991,\"Ġgraph\":20992,\"Ġcod\":20993,\"fred\":20994,\"Ġeffic\":20995,\"ĠGateway\":20996,\"asket\":20997,\"Ġdiminished\":20998,\"Mass\":20999,\"Ġ205\":21000,\"Long\":21001,\"Ġgranddaughter\":21002,\"Ġshining\":21003,\"Semitic\":21004,\"Ġarising\":21005,\"Ġ330\":21006,\"ĠDU\":21007,\"ĠZah\":21008,\"Ġexclusion\":21009,\"ĠClaus\":21010,\"Ġven\":21011,\"oine\":21012,\"ĠAPI\":21013,\"reve\":21014,\"Ġmilitias\":21015,\"Ġfro\":21016,\"Ġwaved\":21017,\"ĠLuxembourg\":21018,\"Ġdiamonds\":21019,\"Ġstabilize\":21020,\"Ġqueue\":21021,\"ĠSponsor\":21022,\"Ġeldest\":21023,\"ĠLud\":21024,\"Ġwasting\":21025,\"Ġdimension\":21026,\"Ġmotorcycles\":21027,\"ucker\":21028,\"ĠTav\":21029,\"Ġsupremacy\":21030,\"Take\":21031,\"ĠCPU\":21032,\"cup\":21033,\"Ġdisregard\":21034,\"Ġenvelope\":21035,\"ĠCah\":21036,\"Ġproposes\":21037,\"ĠMaurice\":21038,\"Ġhobby\":21039,\"Ġharmon\":21040,\"Ġribbon\":21041,\"ĠOrigin\":21042,\"Ġbuilders\":21043,\"Ġconj\":21044,\"Ġcert\":21045,\"eat\":21046,\"ĠStern\":21047,\"ulia\":21048,\"vals\":21049,\"cling\":21050,\"Ġprovocative\":21051,\"Ġsofter\":21052,\"Ġ1948\":21053,\"Ġremod\":21054,\"ĠSob\":21055,\"Ġmaxim\":21056,\"Ġblueprint\":21057,\"oit\":21058,\"ĠGarner\":21059,\"Ġfibre\":21060,\"search\":21061,\"ĠWrite\":21062,\"270\":21063,\"Ġclergy\":21064,\"ĠPalo\":21065,\"obile\":21066,\"Mad\":21067,\"Ġclown\":21068,\"Ġtraced\":21069,\"280\":21070,\"ĠAlberto\":21071,\"Ġdrums\":21072,\"ĠFridays\":21073,\"ĠStrat\":21074,\"stated\":21075,\"ĠStevenson\":21076,\"Pr\":21077,\"Ġboasted\":21078,\"ĠBrees\":21079,\"ĠDonn\":21080,\"ĠMaya\":21081,\"Ġrelieve\":21082,\"Ġ1080\":21083,\"Ġcheapest\":21084,\"Ġuniquely\":21085,\"Ġjungle\":21086,\"Ġprevalence\":21087,\"Ġoutfield\":21088,\"ĠMaps\":21089,\"Ġaccustomed\":21090,\"pac\":21091,\"Ġcombinations\":21092,\"ĠSoros\":21093,\"stad\":21094,\"Ġket\":21095,\"Ġdisgusting\":21096,\"ĠOFF\":21097,\"irs\":21098,\"Ġbiased\":21099,\"Ġpaved\":21100,\"iked\":21101,\"utterstock\":21102,\"ocal\":21103,\"Ġsurround\":21104,\"ĠGuang\":21105,\"Ġspear\":21106,\"ĠBellev\":21107,\"ortun\":21108,\"Rec\":21109,\"acho\":21110,\"Ġfrightening\":21111,\"Ġtyres\":21112,\"normal\":21113,\"ĠYan\":21114,\"ĠWarsaw\":21115,\"ĠBod\":21116,\"ourse\":21117,\"199\":21118,\"Ver\":21119,\"erent\":21120,\"Ġsparkling\":21121,\"Ġchanting\":21122,\"Ġ1945\":21123,\"Ġturbo\":21124,\"Ġhazards\":21125,\"IRE\":21126,\"ĠRonnie\":21127,\"Ġsplitting\":21128,\"ĠMatte\":21129,\"roph\":21130,\"Ġtended\":21131,\"Ġvandalism\":21132,\"alis\":21133,\"SY\":21134,\"Ġoversaw\":21135,\"Happy\":21136,\"ĠTC\":21137,\"275\":21138,\"Ġeco\":21139,\"ĠKers\":21140,\"Ġextensions\":21141,\"ĠFlan\":21142,\"ĠCena\":21143,\"ĠDowns\":21144,\"Ġdrummer\":21145,\"Ġawaited\":21146,\"ĠACL\":21147,\"Ġlegends\":21148,\"ĠRollins\":21149,\"hend\":21150,\"Ġdeparting\":21151,\"Ġtha\":21152,\"Ġunre\":21153,\".(\":21154,\"Ġfaded\":21155,\"Ġretirees\":21156,\"vid\":21157,\"Ġentrants\":21158,\"ĠStella\":21159,\"arer\":21160,\"Ġteaspoon\":21161,\"ĠSheridan\":21162,\"irc\":21163,\"ĠRelief\":21164,\"ĠButt\":21165,\"Ġris\":21166,\"Ġundermined\":21167,\"Ġsunk\":21168,\"Sam\":21169,\"kamp\":21170,\"riot\":21171,\"rating\":21172,\"Ġclubhouse\":21173,\"Ġpeaked\":21174,\"ĠSki\":21175,\"Ġairstrikes\":21176,\"Ġconce\":21177,\"ĠCPR\":21178,\"Ġesp\":21179,\"ĠWave\":21180,\"ĠColiseum\":21181,\"outheastern\":21182,\"Ġtrou\":21183,\"Ġfeather\":21184,\"ĠSoy\":21185,\"ĠBihar\":21186,\"Ġintervened\":21187,\"mits\":21188,\"colored\":21189,\"330\":21190,\"Ġprocession\":21191,\"apeake\":21192,\"itÃ©\":21193,\"riel\":21194,\"Ġmart\":21195,\"afer\":21196,\"ĠGuests\":21197,\"ĠPie\":21198,\"Ġshiny\":21199,\"ĠSixers\":21200,\"ĠRoads\":21201,\"Ġkicker\":21202,\"ĠCrimes\":21203,\"Ġfrontier\":21204,\"ansen\":21205,\"November\":21206,\"smith\":21207,\"ĠLaun\":21208,\"fried\":21209,\"weet\":21210,\"ĠGrass\":21211,\"Ġsanitation\":21212,\"ĠEat\":21213,\"ĠParts\":21214,\"ĠTun\":21215,\"amar\":21216,\"ĠJupiter\":21217,\"ĠFS\":21218,\"Ġunsc\":21219,\"ĠDone\":21220,\"Ġleveraging\":21221,\"Ġtucked\":21222,\"Ġineffective\":21223,\"Ġriots\":21224,\"wei\":21225,\"ĠAttend\":21226,\"Ġpertaining\":21227,\"amen\":21228,\"monds\":21229,\"Ġmism\":21230,\"serious\":21231,\"ĠViol\":21232,\"rous\":21233,\"Ġ129\":21234,\"uebl\":21235,\"umption\":21236,\"tri\":21237,\"ĠWedding\":21238,\"Ġtroopers\":21239,\"ĠTHR\":21240,\"olving\":21241,\"leys\":21242,\"Med\":21243,\"Ġseparatists\":21244,\"Ġimper\":21245,\"ĠFrontier\":21246,\"Ġwhit\":21247,\"ĠMutual\":21248,\"Ġrested\":21249,\"Ġunhealthy\":21250,\"gang\":21251,\"Ġresearching\":21252,\"ĠColonel\":21253,\"Ġaffordability\":21254,\"ĠRegarding\":21255,\"ĠWend\":21256,\"ĠMellon\":21257,\"Ġplots\":21258,\"Ġcanal\":21259,\"PER\":21260,\"ĠShopping\":21261,\"etry\":21262,\"Ġoccurrence\":21263,\"Ġgraves\":21264,\"BF\":21265,\"ĠKau\":21266,\"indust\":21267,\"Ġbeard\":21268,\"uate\":21269,\"ĠProdu\":21270,\"ĠSomali\":21271,\"ishers\":21272,\"ĠFell\":21273,\"ĠHutchinson\":21274,\"Ġhust\":21275,\"Ġillustration\":21276,\"Ġ//\":21277,\"Ġsharks\":21278,\"Ġcoincidence\":21279,\"Ġremake\":21280,\"Ġmural\":21281,\"course\":21282,\"ĠSultan\":21283,\"arse\":21284,\"Ġwhip\":21285,\"ĠPodcast\":21286,\"Ġtightened\":21287,\"Ġdenim\":21288,\"Ġlandfill\":21289,\"future\":21290,\"Ġsuperv\":21291,\"Hand\":21292,\"Ġpraising\":21293,\"ĠEly\":21294,\"ĠGust\":21295,\"ĠMayer\":21296,\"Ġorphan\":21297,\"Ġrepaired\":21298,\"ĠPir\":21299,\"Ġspiral\":21300,\"husband\":21301,\"ienne\":21302,\"iatric\":21303,\"Ġmarriages\":21304,\"Ġhorn\":21305,\"plain\":21306,\"ĠLum\":21307,\"ession\":21308,\"ĠFeatures\":21309,\"Ġbreakup\":21310,\"Ġentrepreneurship\":21311,\"rina\":21312,\"Ġembargo\":21313,\"Ġcapitalism\":21314,\"ĠMinor\":21315,\"Ġpromo\":21316,\"Ġexcel\":21317,\"Japan\":21318,\"Ġworsening\":21319,\"Ġstumbled\":21320,\"Ġpins\":21321,\"Ġswipe\":21322,\"Ġexile\":21323,\"Ġseparatist\":21324,\"ĠBian\":21325,\"Ġrelocation\":21326,\"Ġcommanders\":21327,\"Ġdowned\":21328,\"Ġblogger\":21329,\"packed\":21330,\"ĠSchn\":21331,\"Ġwaterfront\":21332,\"ĠYus\":21333,\"Ġnegotiator\":21334,\"Ġfavourable\":21335,\"Iran\":21336,\"oulder\":21337,\"Ġcance\":21338,\"Ġvind\":21339,\"angel\":21340,\"Ġauthenticity\":21341,\"Ġtowel\":21342,\"bul\":21343,\"ĠNeville\":21344,\"ĠBuddhist\":21345,\"fields\":21346,\"uly\":21347,\"Ġniece\":21348,\"Ġcorrections\":21349,\"Ġassignments\":21350,\"ĠSchl\":21351,\"Ġharmed\":21352,\"375\":21353,\"Ġwounding\":21354,\"ĠPosition\":21355,\"Ġsupermarkets\":21356,\"Ġdisclosures\":21357,\"Ġ185\":21358,\"esp\":21359,\"ĠMcCull\":21360,\"ĠMale\":21361,\"Ġsailors\":21362,\"mis\":21363,\"ĠSophia\":21364,\"Ġunfolded\":21365,\"owell\":21366,\"ĠScarborough\":21367,\"Ġentrepreneurial\":21368,\"118\":21369,\"ogy\":21370,\"ĠLikewise\":21371,\"Ġswung\":21372,\"Ġdrawings\":21373,\"Ġdrafting\":21374,\"ĠSimple\":21375,\"ĠFilip\":21376,\"arf\":21377,\"Ġfade\":21378,\"Ġmerged\":21379,\"ĠLeaf\":21380,\"sun\":21381,\"Ġflame\":21382,\"Ġindices\":21383,\"ĠCreate\":21384,\"ittle\":21385,\"ĠWer\":21386,\"ĠMond\":21387,\"Ġoz\":21388,\"ĠSmoke\":21389,\"Ġreplies\":21390,\"ĠDH\":21391,\"Ġjud\":21392,\"ĠFalk\":21393,\"Ġ---\":21394,\"Ġconstitutes\":21395,\"Ġtheat\":21396,\"119\":21397,\"Ġintermediate\":21398,\"vill\":21399,\"ĠGow\":21400,\"ĠHut\":21401,\"ł\":21402,\"155\":21403,\"ĠLocated\":21404,\"ĠDoor\":21405,\"Ġsliced\":21406,\"aru\":21407,\"Ġtearing\":21408,\"defense\":21409,\"oyer\":21410,\"Ġprodu\":21411,\"Ġseminar\":21412,\"asso\":21413,\"Ġpeaks\":21414,\"Ġconceal\":21415,\"Ġcrypto\":21416,\"Ġsetbacks\":21417,\"ĠAlicia\":21418,\"ĠFAA\":21419,\"Ġcontinuity\":21420,\"Ġcatastrophe\":21421,\"Ġbeg\":21422,\"Ġscales\":21423,\"apixel\":21424,\"Ġsalon\":21425,\"Ste\":21426,\"Ġlesbian\":21427,\"Ġanticip\":21428,\"Ġutilization\":21429,\"Ġchickens\":21430,\"Ġspinal\":21431,\"ĠJuliet\":21432,\"ĠFas\":21433,\"prising\":21434,\"ĠSalvation\":21435,\"Ġ138\":21436,\"Ġutilizing\":21437,\"âĢ¢\":21438,\"ĠMessenger\":21439,\"Ġrebellion\":21440,\"ĠAlexand\":21441,\"Ġinsect\":21442,\"Ġribs\":21443,\"ĠBild\":21444,\"Ġmonopoly\":21445,\"Queen\":21446,\"ĠNaples\":21447,\"Ġ133\":21448,\"Ġhourly\":21449,\"Ġego\":21450,\"Ġpencil\":21451,\"ĠPew\":21452,\"Ġdesirable\":21453,\"vant\":21454,\"ĠLAT\":21455,\"Ġperpet\":21456,\"lish\":21457,\"Ġ201\":21458,\"Ġdistances\":21459,\"Ġdistressed\":21460,\"Work\":21461,\"Ġtattoos\":21462,\"Ġstereotypes\":21463,\"istent\":21464,\"ĠCoral\":21465,\"fo\":21466,\"Ġpayable\":21467,\"Ġakin\":21468,\"ĠLis\":21469,\"ĠFinding\":21470,\"Ġsusceptible\":21471,\"ĠKiw\":21472,\"Ġforgiveness\":21473,\"ĠMoment\":21474,\"ĠDmitry\":21475,\"Ġrenov\":21476,\"Ġquint\":21477,\"ĠWaterloo\":21478,\"ĠReality\":21479,\"Ġstray\":21480,\"ĠBeaver\":21481,\"Ġbites\":21482,\"Ġelusive\":21483,\"Ġvirtue\":21484,\"Ġgadgets\":21485,\"Ġlandslide\":21486,\"ĠHealthy\":21487,\"Ġpits\":21488,\"Donnell\":21489,\"Ġirony\":21490,\"uct\":21491,\"Ġpractitioners\":21492,\"Ġreck\":21493,\"governmental\":21494,\"Ġatomic\":21495,\"Ġmotiv\":21496,\"Ġpolic\":21497,\"Ġcommunicated\":21498,\"ĠHS\":21499,\"Ġcriticize\":21500,\"Ġsynerg\":21501,\"Del\":21502,\"ĠRoe\":21503,\"Ġinspirational\":21504,\"ĠWarning\":21505,\"pel\":21506,\"Ġnevertheless\":21507,\"Ġdespair\":21508,\"Ġ(.\":21509,\"Ġfearing\":21510,\"Ġgrop\":21511,\"tree\":21512,\"Ġtrusts\":21513,\"Ġinterviewing\":21514,\"amic\":21515,\"Ġscor\":21516,\"ject\":21517,\"Another\":21518,\"pose\":21519,\"Ġdepicted\":21520,\"ĠPhotography\":21521,\"ĠLenovo\":21522,\"ĠEpic\":21523,\"ĠBoot\":21524,\"GI\":21525,\"enses\":21526,\"Class\":21527,\"arity\":21528,\"Ġservicing\":21529,\"ĠHann\":21530,\"Ġawe\":21531,\"Ġoverdoses\":21532,\"ĠFinnish\":21533,\"Ġpav\":21534,\"ĠPCs\":21535,\"SEC\":21536,\"ĠStro\":21537,\"Ġattracts\":21538,\"Ġapprehended\":21539,\"128\":21540,\"Ġunstable\":21541,\"ĠOutdoor\":21542,\"Ġcloth\":21543,\"ĠUlster\":21544,\"Ġvisually\":21545,\"Ġsculpt\":21546,\"Ġsufficiently\":21547,\"ĠKendrick\":21548,\"Ġengages\":21549,\"Ġknives\":21550,\"ĠGut\":21551,\"Ġarbit\":21552,\"osition\":21553,\"Ġemoji\":21554,\"Ġpinpoint\":21555,\"Ġremembering\":21556,\"rence\":21557,\"ĠVish\":21558,\"Ġimproperly\":21559,\"Ġranc\":21560,\"Ġupstream\":21561,\"Ġcheckpoint\":21562,\"Ġrash\":21563,\"eson\":21564,\"Ġtoes\":21565,\"260\":21566,\"Ġinvalid\":21567,\"Ġonions\":21568,\"Ġlashed\":21569,\"ĠDong\":21570,\"Ġprovisional\":21571,\"ĠFern\":21572,\"Ġirresponsible\":21573,\"actively\":21574,\"ĠKnown\":21575,\"Ġben\":21576,\"ĠBlank\":21577,\"Ġactresses\":21578,\"paying\":21579,\"Ġsyrup\":21580,\"isman\":21581,\"Ġeducating\":21582,\"Sunday\":21583,\"ifiable\":21584,\"Post\":21585,\"Ġcalculation\":21586,\"Ġhesitate\":21587,\"ĠIncreasing\":21588,\"Ġreeling\":21589,\"ĠDairy\":21590,\"ensing\":21591,\"Ġmaternity\":21592,\"Ø\":21593,\"./\":21594,\"ĠElm\":21595,\"Ġweddings\":21596,\"ĠYard\":21597,\"117\":21598,\"ĠRocket\":21599,\"OF\":21600,\"Ġtreasurer\":21601,\"Ġrattled\":21602,\"ĠDrop\":21603,\"arel\":21604,\"ĠFulton\":21605,\"ĠGiant\":21606,\"ĠFloor\":21607,\"Jet\":21608,\"ikk\":21609,\"ĠBucs\":21610,\"ostics\":21611,\"reme\":21612,\"ĠRouse\":21613,\"Ġdeliber\":21614,\"ĠEle\":21615,\"Ġconducts\":21616,\"ĠBlog\":21617,\"connected\":21618,\"Ġprayed\":21619,\"Ġcolourful\":21620,\"Ġaugmented\":21621,\"Ġbatted\":21622,\"Ġrelevance\":21623,\"ĠRomanian\":21624,\"acqu\":21625,\"ĠChel\":21626,\"ĠClo\":21627,\"ĠGraves\":21628,\"Ġchees\":21629,\"ĠGibbs\":21630,\"CLE\":21631,\"Ġfertility\":21632,\"Ġambul\":21633,\"Ġspecs\":21634,\"ĠIRA\":21635,\"ĠBooth\":21636,\"ithe\":21637,\"ĠPlayoff\":21638,\"ammed\":21639,\"Ġcollaborating\":21640,\"Ġlunar\":21641,\"Ġconfronting\":21642,\"Ġattribute\":21643,\"King\":21644,\"riz\":21645,\"Ġcasualty\":21646,\"acia\":21647,\"waters\":21648,\"Ġpaving\":21649,\"Ġcaregivers\":21650,\"nor\":21651,\"Ġreacting\":21652,\"ĠHash\":21653,\"Ġsqueezed\":21654,\"Ġexert\":21655,\"ĠMichele\":21656,\"ĠConc\":21657,\"ĠHep\":21658,\"Ġsewage\":21659,\"wart\":21660,\"GY\":21661,\"Ġdiscourage\":21662,\"ĠFir\":21663,\"Ġtextile\":21664,\"ĠSpice\":21665,\"ĠFah\":21666,\"Ġcomplainant\":21667,\"Ġinstinct\":21668,\"camp\":21669,\"ĠEdison\":21670,\"ĠVIDEOS\":21671,\"LM\":21672,\"ĠSands\":21673,\"About\":21674,\"Ġdisk\":21675,\"brid\":21676,\"Ġmuted\":21677,\"ACC\":21678,\"Ġwre\":21679,\"event\":21680,\"Ġicons\":21681,\"Express\":21682,\"udes\":21683,\"ĠBeatles\":21684,\"color\":21685,\"ĠHaas\":21686,\"ĠWolfe\":21687,\"ĠYOUR\":21688,\"Ġaccessibility\":21689,\"ĠCornwall\":21690,\"Ġing\":21691,\"Ġatrocities\":21692,\"weather\":21693,\"ĠDominion\":21694,\"ĠMIL\":21695,\"ĠLara\":21696,\"Ġunravel\":21697,\"Ġmaneuver\":21698,\"Ġfoam\":21699,\"ribe\":21700,\"CI\":21701,\"Ġcandles\":21702,\"acs\":21703,\")(\":21704,\"coon\":21705,\"ĠPurple\":21706,\"ĠGovernors\":21707,\"ĠKeystone\":21708,\"ĠYuk\":21709,\"file\":21710,\"Ġviol\":21711,\"gery\":21712,\"370\":21713,\"train\":21714,\"Ġgunshots\":21715,\"olin\":21716,\"Ġviruses\":21717,\"ĠTex\":21718,\"hours\":21719,\"Ġprev\":21720,\"ĠRid\":21721,\"ected\":21722,\"ĠVog\":21723,\"riers\":21724,\"Ġmurdering\":21725,\"ĠIz\":21726,\"Ġdeliberations\":21727,\"arming\":21728,\"unda\":21729,\"Ġrink\":21730,\"ĠDrugs\":21731,\"idered\":21732,\"Ġforge\":21733,\"Ġexpansive\":21734,\"VIEW\":21735,\"ĠBots\":21736,\"Ġswitches\":21737,\"KO\":21738,\"atten\":21739,\"Ġvariants\":21740,\"ĠVirtual\":21741,\"ĠCoch\":21742,\"yon\":21743,\"ĠKai\":21744,\"Ġbullied\":21745,\"iday\":21746,\"version\":21747,\"Ġlib\":21748,\"ĠCec\":21749,\"igated\":21750,\"ĠTRUMP\":21751,\"ĠPod\":21752,\"Ġtoppled\":21753,\"Ġeyeing\":21754,\"ĠPatients\":21755,\"techn\":21756,\"Ġhampered\":21757,\"Ġavert\":21758,\"ĠScheme\":21759,\"ĠCorm\":21760,\"Ġpony\":21761,\"Ġzoom\":21762,\"abo\":21763,\"Ġsleeves\":21764,\"lane\":21765,\"ĠLester\":21766,\"ĠDane\":21767,\"Ġcough\":21768,\"Ġsignings\":21769,\"HER\":21770,\"Ġsibling\":21771,\"Ġredemption\":21772,\"Ġstockp\":21773,\"ĠAlgeria\":21774,\"Ġpadd\":21775,\"ĠBrenda\":21776,\"uchi\":21777,\"Ġtransporting\":21778,\"Ġspeculative\":21779,\"ĠSek\":21780,\"abal\":21781,\"Ġshipment\":21782,\"oker\":21783,\"Ġwarranty\":21784,\"atan\":21785,\"Ġblister\":21786,\"ĠCelebration\":21787,\"Ġwal\":21788,\"Ġlac\":21789,\"Ġprioritize\":21790,\"ression\":21791,\"BP\":21792,\"Ġcollaborated\":21793,\"ĠNewsletter\":21794,\"ĠDamian\":21795,\"ĠResidential\":21796,\"Ġgra\":21797,\"Ġfeasible\":21798,\"ĠCrest\":21799,\"ĠBean\":21800,\"ĠSturgeon\":21801,\"ĠTale\":21802,\"ĠContin\":21803,\"ĠMush\":21804,\"Ġrocking\":21805,\"ĠMane\":21806,\"ĠHumane\":21807,\"resistant\":21808,\"ĠFra\":21809,\"highest\":21810,\"fts\":21811,\"Ġamassed\":21812,\"ĠPavilion\":21813,\"ĠSkin\":21814,\"Ġunfold\":21815,\"Ġresur\":21816,\"ĠPET\":21817,\"model\":21818,\"Ġemploying\":21819,\"Ġrude\":21820,\"Ġirrelevant\":21821,\"angu\":21822,\"Page\":21823,\"PN\":21824,\"igator\":21825,\"ĠReb\":21826,\"ĠArrest\":21827,\"ĠGund\":21828,\"Ġmalls\":21829,\"zhen\":21830,\"wed\":21831,\"Ġdaring\":21832,\"Ġfactual\":21833,\"ĠGent\":21834,\"Ġinforming\":21835,\"ĠStri\":21836,\"ĠLounge\":21837,\".]\":21838,\"ĠTribunal\":21839,\"ĠMoines\":21840,\"Ġshadows\":21841,\"generated\":21842,\"fulness\":21843,\"Ġheartfelt\":21844,\"ĠLivingston\":21845,\"ĠClerk\":21846,\"Ġnationalism\":21847,\"ĠMiche\":21848,\"balls\":21849,\"anos\":21850,\"agle\":21851,\"Ġprejudice\":21852,\"Ġevenly\":21853,\"Ġswearing\":21854,\"Ġexits\":21855,\"Ġcondemning\":21856,\"Ġvanilla\":21857,\"club\":21858,\"ĠFunding\":21859,\"ĠDover\":21860,\"Ġhots\":21861,\"Ġfres\":21862,\"Ġgoodness\":21863,\"ĠMcKay\":21864,\"Ġbulls\":21865,\"avia\":21866,\"129\":21867,\"Ġ1947\":21868,\"Ġdefamation\":21869,\"ĠMoran\":21870,\"irms\":21871,\"ĠFitz\":21872,\"ĠRossi\":21873,\"urated\":21874,\"Ġvariation\":21875,\"ĠBauer\":21876,\"ĠSchro\":21877,\"Ġcolony\":21878,\"ĠParliamentary\":21879,\"ikan\":21880,\"Ġstirring\":21881,\"ĠSheldon\":21882,\"Ġaccessory\":21883,\"ĠUtilities\":21884,\"Ġnab\":21885,\"Ġpract\":21886,\"Ġherein\":21887,\"ĠRole\":21888,\"ĠMant\":21889,\"Ġpharm\":21890,\"Ġ215\":21891,\"ĠNGO\":21892,\"ĠAnything\":21893,\"ĠMacedonia\":21894,\"Ġbree\":21895,\"ĠWTO\":21896,\"Chicago\":21897,\"ĠProtect\":21898,\"quarters\":21899,\"ĠGrassley\":21900,\"ĠInteractive\":21901,\"ĠInterview\":21902,\"Ġ550\":21903,\"Ġastronauts\":21904,\"Ġfreak\":21905,\"ĠIntegrated\":21906,\"Ġindict\":21907,\"Ġgenerators\":21908,\"acio\":21909,\"Kevin\":21910,\"Ġvaccination\":21911,\"Ġblockade\":21912,\"ĠSons\":21913,\"Ġcapita\":21914,\"ĠAnita\":21915,\"ĠExport\":21916,\"ĠNex\":21917,\"ĠAram\":21918,\"Ġzinc\":21919,\"Ġrevamped\":21920,\"Ġselective\":21921,\"Ġmanipulate\":21922,\"ĠBedford\":21923,\"ĠBattery\":21924,\"Ġqualifiers\":21925,\"lean\":21926,\"Ġscrew\":21927,\"film\":21928,\"ror\":21929,\"ĠEllison\":21930,\"ombo\":21931,\"ĠOst\":21932,\"165\":21933,\"Ġslaves\":21934,\"ĠPayton\":21935,\"Ġbarg\":21936,\"Ġrugged\":21937,\"ĠWinn\":21938,\"ĠHammer\":21939,\"ĠUPS\":21940,\"Euro\":21941,\"Ġunfamiliar\":21942,\"Ġdistract\":21943,\"Ġbuffer\":21944,\"ledge\":21945,\"Ġtrunk\":21946,\"Ġ320\":21947,\"122\":21948,\"Ġdilemma\":21949,\"Ġpra\":21950,\"Ġutmost\":21951,\"Ġcampaigners\":21952,\"icular\":21953,\"eful\":21954,\"ï¿½\":21955,\"ĠHQ\":21956,\"neau\":21957,\"Ġsir\":21958,\"test\":21959,\"Company\":21960,\"Ġrescind\":21961,\"ardon\":21962,\"MG\":21963,\"Gov\":21964,\"ĠRaz\":21965,\"Ġrod\":21966,\"fed\":21967,\"Ġpsych\":21968,\"Ġunin\":21969,\"ĠArbor\":21970,\"Ġnewcomer\":21971,\"ĠEdwin\":21972,\"raising\":21973,\"quist\":21974,\"Ġdiscoveries\":21975,\"Steve\":21976,\"Ġscramble\":21977,\"js\":21978,\"Ġacoustic\":21979,\"Ġdeterioration\":21980,\"Ġobserving\":21981,\"ĠWinning\":21982,\"ĠSaban\":21983,\"idy\":21984,\"Ġoverd\":21985,\"Ġscouting\":21986,\"Ġpunitive\":21987,\"ĠShelter\":21988,\"Ġmocked\":21989,\"Ġdreamed\":21990,\"Ġinvaluable\":21991,\"LP\":21992,\"standard\":21993,\"Ġrecounted\":21994,\"ĠSabres\":21995,\"points\":21996,\"Ġfringe\":21997,\"ĠBarker\":21998,\"alian\":21999,\"ĠPROV\":22000,\"Ġcartel\":22001,\"Ġovercrowd\":22002,\"tain\":22003,\"Year\":22004,\"ĠWelfare\":22005,\"ĠChr\":22006,\"Ġintroduces\":22007,\"ĠDoing\":22008,\"ĠGlover\":22009,\"Ġdeteriorating\":22010,\"Par\":22011,\"Ġattendant\":22012,\"ĠMold\":22013,\"ĠFlying\":22014,\"ovan\":22015,\"Ġoptimize\":22016,\"Ġchapters\":22017,\"Ġdull\":22018,\"gay\":22019,\"ĠATP\":22020,\"ĠKah\":22021,\"ainer\":22022,\"feet\":22023,\"Ġjoking\":22024,\"Ġdisadvantage\":22025,\"Rep\":22026,\"Ġtwisted\":22027,\"Ġslain\":22028,\"Ġcomprise\":22029,\"Ġrestricting\":22030,\"Ġdispos\":22031,\"Ġshaky\":22032,\"Ġembattled\":22033,\"owe\":22034,\"conscious\":22035,\"oken\":22036,\"Ġmistaken\":22037,\"ĠDra\":22038,\"Ġreservoir\":22039,\"Ġspate\":22040,\"Scott\":22041,\"avor\":22042,\"Ġqual\":22043,\"amel\":22044,\"hunt\":22045,\"ĠChevy\":22046,\"Ġclaw\":22047,\"Ġwitch\":22048,\"ĠZimmerman\":22049,\"arium\":22050,\"Ġrubbish\":22051,\"Ġstrings\":22052,\"Ġdoc\":22053,\"Ġplaque\":22054,\"ĠCyr\":22055,\"Ġflourish\":22056,\"Ġworthwhile\":22057,\"Ġbanners\":22058,\"ĠLemon\":22059,\"ĠRainbow\":22060,\"Ġconsisted\":22061,\"ĠHOW\":22062,\"Ñ\":22063,\"Ġblogs\":22064,\"CLUS\":22065,\"eely\":22066,\"Ġbeast\":22067,\"ĠMai\":22068,\"Ġhostility\":22069,\"eros\":22070,\"Ġforeseeable\":22071,\"ĠCorker\":22072,\"ĠWEEK\":22073,\"visors\":22074,\"ressive\":22075,\"ĠViktor\":22076,\"Ġbureaucracy\":22077,\"Ġ256\":22078,\"ĠFeel\":22079,\"ĠAdventure\":22080,\"Ġefficacy\":22081,\"ĠInstitution\":22082,\"ĠHarbaugh\":22083,\"ĠPractice\":22084,\"ĠChristianity\":22085,\"Thanks\":22086,\"Ġfridge\":22087,\"idel\":22088,\"Ġeff\":22089,\"Ġvein\":22090,\"terms\":22091,\"Ġignorance\":22092,\"Ġscream\":22093,\"Ġwit\":22094,\"ĠRousse\":22095,\"ĠWillow\":22096,\"Ġhallway\":22097,\"former\":22098,\"Ġshooters\":22099,\"ĠReporting\":22100,\"Ġgal\":22101,\"Ġsavvy\":22102,\"rand\":22103,\"Ġremed\":22104,\"ĠBaron\":22105,\"inar\":22106,\"Ġseizures\":22107,\"ĠThorn\":22108,\"ĠProtesters\":22109,\"ĠRevolutionary\":22110,\"think\":22111,\"ĠCabrera\":22112,\"Four\":22113,\"ĠRudd\":22114,\"Ġprost\":22115,\"ĠBottom\":22116,\"Port\":22117,\"nas\":22118,\"ifax\":22119,\"Wire\":22120,\"Ġtokens\":22121,\"antis\":22122,\"ĠSOU\":22123,\"ĠMilk\":22124,\"asters\":22125,\"Ġshrimp\":22126,\"Ġcakes\":22127,\"blue\":22128,\"ifty\":22129,\"View\":22130,\"adium\":22131,\"fen\":22132,\"zyk\":22133,\"ĠEmil\":22134,\"Ġdismay\":22135,\"Ġtilt\":22136,\"aska\":22137,\"Young\":22138,\"Ġpredators\":22139,\"Ġovershadowed\":22140,\"mitt\":22141,\"ĠSemin\":22142,\"ĠSchiff\":22143,\"ĠClarkson\":22144,\"212\":22145,\"210\":22146,\"Ġvanished\":22147,\"Ġmesh\":22148,\"ĠBurnett\":22149,\"ĠMent\":22150,\"ĠBlind\":22151,\"ĠPatriot\":22152,\"ĠVil\":22153,\"Ġflick\":22154,\"ĠTowns\":22155,\"ĠWhites\":22156,\"Ġspice\":22157,\"ĠMode\":22158,\"Ġnominate\":22159,\"Ġwrest\":22160,\"ĠAshes\":22161,\"Ġrows\":22162,\"ĠClint\":22163,\"Ġgentleman\":22164,\"utan\":22165,\"athlon\":22166,\"ĠIntermediate\":22167,\"hews\":22168,\"Ġoffended\":22169,\"ĠPaige\":22170,\"ĠFinch\":22171,\"ĠAboriginal\":22172,\"positive\":22173,\"Stop\":22174,\"Ġrenting\":22175,\"Ġ[âĢ¦]\":22176,\"ĠHert\":22177,\"Ġvegetation\":22178,\"apes\":22179,\"ĠCanon\":22180,\"appa\":22181,\"Ġabst\":22182,\"ĠKatz\":22183,\"Ġsurfing\":22184,\"aghan\":22185,\"ĠPresidency\":22186,\"Ġscaling\":22187,\"ĠSas\":22188,\"Ġpeanut\":22189,\"Ġrecommending\":22190,\"cious\":22191,\"endez\":22192,\"eker\":22193,\"ĠKamp\":22194,\"Ġsitcom\":22195,\"Ġcrust\":22196,\"women\":22197,\"ĠJes\":22198,\"ĠWhe\":22199,\"ĠWarwick\":22200,\"Ġepit\":22201,\"ĠAlc\":22202,\"Ġdictate\":22203,\"ĠSPORTS\":22204,\"ĠLanguage\":22205,\"Ġindicative\":22206,\"ĠMacDonald\":22207,\"Ġreorgan\":22208,\"Ġ`\":22209,\"ARS\":22210,\"Ġliberation\":22211,\"Ġbless\":22212,\"Ġreflective\":22213,\"Ġà¤\":22214,\"Ġdesires\":22215,\"ĠHank\":22216,\"ĠLaunch\":22217,\"Ġrotating\":22218,\"ĠStones\":22219,\"Ġcoordinating\":22220,\"ĠZeit\":22221,\"Ġskepticism\":22222,\"ĠAlam\":22223,\"ĠTrout\":22224,\"ĠSMS\":22225,\"ĠCrescent\":22226,\"ĠTeacher\":22227,\"Ġfury\":22228,\"Ġeyebrows\":22229,\"onga\":22230,\"ĠPilot\":22231,\"ĠRutherford\":22232,\"Ġinterstate\":22233,\"established\":22234,\"Ġbaggage\":22235,\"Ġ131\":22236,\"riks\":22237,\"mil\":22238,\"Ġneon\":22239,\"Ġqueer\":22240,\"ourced\":22241,\"ĠKash\":22242,\"ĠEleven\":22243,\"illes\":22244,\"ĠOpportun\":22245,\"Ġstre\":22246,\"Washington\":22247,\"ĠDifferent\":22248,\"Ġexempl\":22249,\"Ġboarded\":22250,\"Ġrogue\":22251,\"ĠDNC\":22252,\"rone\":22253,\"Ġreversing\":22254,\"nine\":22255,\"ĠIvory\":22256,\"itating\":22257,\"uve\":22258,\"Ġfracture\":22259,\"255\":22260,\"ĠAssessment\":22261,\"Ġsubjective\":22262,\"Ġfluct\":22263,\"ĠJaguar\":22264,\"Ġstride\":22265,\"Ġreapp\":22266,\"ĠGrow\":22267,\"against\":22268,\"ĠMedina\":22269,\"scenes\":22270,\"ĠNieto\":22271,\"Ġsou\":22272,\"ĠFleming\":22273,\"Ġnarcotics\":22274,\"ĠBere\":22275,\"ĠBub\":22276,\"ĠAck\":22277,\"Ġvinyl\":22278,\"ĠCopy\":22279,\"ĠGarland\":22280,\"ĠDuty\":22281,\"Ġinn\":22282,\"Ġmerchant\":22283,\"Ġactivate\":22284,\"Ġglowing\":22285,\"ettle\":22286,\"ĠBran\":22287,\"Ġsilk\":22288,\"anco\":22289,\"TL\":22290,\"ĠFurn\":22291,\"Ġwithheld\":22292,\"Ġpulse\":22293,\"ĠGU\":22294,\"BUS\":22295,\"ĠHyper\":22296,\"Ġpicnic\":22297,\"Ġpositives\":22298,\"ĠParamount\":22299,\"Ġ737\":22300,\"Ġenlisted\":22301,\"ĠValerie\":22302,\"false\":22303,\"ĠChocolate\":22304,\"ĠSTAR\":22305,\"Ġdescended\":22306,\"Ġtasty\":22307,\"ĠDaesh\":22308,\"ĠNed\":22309,\"Ġcomplimentary\":22310,\"Ġdepicting\":22311,\"ĠHavana\":22312,\"college\":22313,\"Ġtraces\":22314,\"Ġundue\":22315,\"ĠSisters\":22316,\"aum\":22317,\"ĠCourier\":22318,\"ĠOng\":22319,\"ĠSparks\":22320,\"ongs\":22321,\"ĠYong\":22322,\"URR\":22323,\"los\":22324,\"Ġhorsepower\":22325,\"confidence\":22326,\"ĠPett\":22327,\"ĠMeasure\":22328,\"Ġmarches\":22329,\"zig\":22330,\"ĠTOR\":22331,\"Ġexported\":22332,\"ĠRak\":22333,\"ĠInvestigations\":22334,\"Ġterminate\":22335,\"ĠTian\":22336,\"Ġmasters\":22337,\"ĠDS\":22338,\"Ġoutraged\":22339,\"ĠCups\":22340,\"ĠWeir\":22341,\"exec\":22342,\"Ġjourneys\":22343,\"Ġabide\":22344,\"Ġavail\":22345,\"ĠStreets\":22346,\"Ġfixes\":22347,\"Ġcocoa\":22348,\"Ġabundant\":22349,\"Ġhubs\":22350,\"mort\":22351,\"Ġrobberies\":22352,\"ĠBark\":22353,\"Ġprecautions\":22354,\"Ġhammered\":22355,\"ometric\":22356,\"mith\":22357,\"ĠMcCann\":22358,\"ĠJaw\":22359,\"ĠQuest\":22360,\"ĠMcF\":22361,\"Ġlob\":22362,\"Ġlegalized\":22363,\"Ġquirky\":22364,\"Ġtrailers\":22365,\"ĠIndividual\":22366,\"Ġcumulative\":22367,\"Ġenlarge\":22368,\"Ġconvoy\":22369,\"olen\":22370,\"got\":22371,\"landers\":22372,\"Ġscanner\":22373,\"Ġscans\":22374,\"ĠEg\":22375,\"prof\":22376,\"Ġhosp\":22377,\"ĠColo\":22378,\"Ġerr\":22379,\"Ġdeval\":22380,\"ĠUsually\":22381,\"Ġbul\":22382,\"ummy\":22383,\"Ġtandem\":22384,\"occupied\":22385,\"Ġmandates\":22386,\"ĠSwim\":22387,\"121\":22388,\"ussed\":22389,\"EF\":22390,\"Ġfries\":22391,\"Until\":22392,\"rc\":22393,\"Ġbadge\":22394,\"Ġstrips\":22395,\"Ġmagnet\":22396,\"Ġarchive\":22397,\"stan\":22398,\"ĠDeadline\":22399,\"Ġdisposable\":22400,\"Ġbob\":22401,\"Ġnorthwestern\":22402,\"Jul\":22403,\"ĠSAL\":22404,\"Ġinfluencing\":22405,\"Ġdevil\":22406,\"ĠEllie\":22407,\"cms\":22408,\"ingo\":22409,\"888\":22410,\"Ġcosmetic\":22411,\"Also\":22412,\"Ġyacht\":22413,\"Ġlazy\":22414,\"Ġmerc\":22415,\"Ġabsorbed\":22416,\"harm\":22417,\"116\":22418,\"Ġsubpoena\":22419,\"Ġcounters\":22420,\"ĠLori\":22421,\"Ġrandomly\":22422,\"nea\":22423,\"waves\":22424,\"Ġrelie\":22425,\"ĠKiss\":22426,\"Ġchassis\":22427,\"Ġbakery\":22428,\"Images\":22429,\"ĠHolden\":22430,\"Ġamazed\":22431,\"Ġalignment\":22432,\"ĠPowers\":22433,\"Ġlabelled\":22434,\"Ġstaunch\":22435,\"Ġsignaling\":22436,\"Ġsenate\":22437,\"Ġunconventional\":22438,\"ĠAlternative\":22439,\"Ġambassadors\":22440,\"ĠVPN\":22441,\"atics\":22442,\"Ġmosquito\":22443,\"ĠScholarship\":22444,\"Ġhelpless\":22445,\"alone\":22446,\"ZA\":22447,\"chel\":22448,\"Ġconstituencies\":22449,\"ĠCafÃ©\":22450,\"Ġhatch\":22451,\"ĠRupert\":22452,\"Ġrendering\":22453,\"Ġreinstated\":22454,\"Ġinterval\":22455,\"Texas\":22456,\"ĠAHL\":22457,\"February\":22458,\"review\":22459,\"Ġgle\":22460,\"Ġfals\":22461,\"Ġmarkers\":22462,\"Ġgovernmental\":22463,\"ĠPos\":22464,\"Ġarose\":22465,\"every\":22466,\"Ġrulings\":22467,\"obar\":22468,\"Govern\":22469,\"gren\":22470,\"isan\":22471,\"Ġmarketed\":22472,\"Click\":22473,\"Ġord\":22474,\"Ġballoons\":22475,\"asers\":22476,\"ĠHorton\":22477,\"pub\":22478,\"ĠAerospace\":22479,\"Ġflank\":22480,\"Ġmolecular\":22481,\"bour\":22482,\"nuts\":22483,\"Ġalliances\":22484,\"Ġbenchmarks\":22485,\"ocate\":22486,\"stadt\":22487,\"ĠGoodwin\":22488,\"lap\":22489,\"ĠFactors\":22490,\"Never\":22491,\"ĠNem\":22492,\"Ġroadside\":22493,\"orth\":22494,\"Ġexhibited\":22495,\"ĠPearce\":22496,\"ĠOlsen\":22497,\"Ġpostal\":22498,\"ĠLiberation\":22499,\"reen\":22500,\"mary\":22501,\"Ġropes\":22502,\"Ġlarg\":22503,\"Ġgob\":22504,\"boys\":22505,\"ĠSax\":22506,\"Ġreimbursement\":22507,\"ĠVie\":22508,\"ĠCatholics\":22509,\"ĠMartial\":22510,\"Ġpremiered\":22511,\"Ġawaits\":22512,\"ĠUnderstanding\":22513,\"ĠBelarus\":22514,\"ĠVor\":22515,\"ogi\":22516,\"iaz\":22517,\"Ġvictorious\":22518,\"Ġancestors\":22519,\"Ġwreckage\":22520,\"Ġoppression\":22521,\"ĠChildhood\":22522,\"Ġwidth\":22523,\"ĠPlymouth\":22524,\"ĠFifty\":22525,\"Ġoccupancy\":22526,\"etts\":22527,\"ĠFiscal\":22528,\"lifting\":22529,\"ĠTraditional\":22530,\"Ġnostalgia\":22531,\"Law\":22532,\"Ġlays\":22533,\"Ġarresting\":22534,\"Ġanticipating\":22535,\"Ġinsults\":22536,\"ĠExtension\":22537,\"Ġgenerator\":22538,\"ummer\":22539,\"Ġageing\":22540,\"Ġbouncing\":22541,\"ember\":22542,\"ĠWAR\":22543,\"ĠNico\":22544,\"ĠWow\":22545,\"ĠRaven\":22546,\"flower\":22547,\"ĠCrim\":22548,\"bh\":22549,\"Ġundo\":22550,\"Ġburgers\":22551,\"roud\":22552,\"ĠAtkinson\":22553,\"ĠYEAR\":22554,\"Ġpoorer\":22555,\"ICA\":22556,\"ĠSchedule\":22557,\"Ġstronghold\":22558,\"ĠMillennium\":22559,\"Ġ###\":22560,\"ilda\":22561,\"ĠGH\":22562,\"Ġupscale\":22563,\"aldi\":22564,\"ĠResolution\":22565,\"Ġswelling\":22566,\"Ġgrieving\":22567,\"ĠNile\":22568,\"ĠTig\":22569,\"ERY\":22570,\"ooth\":22571,\"BALL\":22572,\"Ġballet\":22573,\"Ġbucks\":22574,\"ĠUV\":22575,\"akin\":22576,\"Ġchilling\":22577,\"Ġdatabases\":22578,\"ĠGD\":22579,\"section\":22580,\"Ġhires\":22581,\"Ġmul\":22582,\"Ġsen\":22583,\"ĠTownsend\":22584,\"Ġinspected\":22585,\"ilic\":22586,\"Ġdiscriminatory\":22587,\"fol\":22588,\"Ġalcoholic\":22589,\"ĠHoff\":22590,\"Carl\":22591,\"Ġvicinity\":22592,\"lein\":22593,\"ĠEco\":22594,\"ĠGovern\":22595,\"Ġsecrecy\":22596,\"aned\":22597,\"ĠDUP\":22598,\"Ġ570\":22599,\"Ġsow\":22600,\"Ġstalls\":22601,\"Ġinsulting\":22602,\"ĠDT\":22603,\"Ġinforms\":22604,\"fitting\":22605,\"ĠDepending\":22606,\"ĠMelanie\":22607,\"ĠThom\":22608,\"path\":22609,\"Ġadmired\":22610,\"Peter\":22611,\"idents\":22612,\"ielding\":22613,\"ĠShanahan\":22614,\"TD\":22615,\"Things\":22616,\"sn\":22617,\"Ġconstituted\":22618,\"Ġ137\":22619,\"Ġderailed\":22620,\"ĠBonnie\":22621,\"Ġgraffiti\":22622,\"Ġearnest\":22623,\"Ġcompliant\":22624,\"blown\":22625,\"Ġalle\":22626,\"prise\":22627,\"Ġfocal\":22628,\"Ġgentlemen\":22629,\"ĠTalks\":22630,\"Ġpassports\":22631,\"Ġdeprived\":22632,\"Ġdude\":22633,\"ĠNath\":22634,\"Ġgoverned\":22635,\"Ġsac\":22636,\"Ġcastle\":22637,\"qv\":22638,\"Ġtolerated\":22639,\"ĠSci\":22640,\"close\":22641,\"ĠDynamics\":22642,\"Ġflashing\":22643,\"yk\":22644,\"ĠConsolid\":22645,\"Ġinherently\":22646,\"ĠForrest\":22647,\"Gene\":22648,\"Public\":22649,\"Ġloser\":22650,\"runners\":22651,\"Ġprudent\":22652,\"Ġpioneering\":22653,\"ĠHowe\":22654,\"ĠButter\":22655,\"ĠArabian\":22656,\"acha\":22657,\"ĠBBQ\":22658,\"ĠMineral\":22659,\"Ġdestiny\":22660,\"Ġretrieve\":22661,\"ĠBav\":22662,\"reth\":22663,\"oby\":22664,\"ĠGrid\":22665,\"Ġgrievances\":22666,\"ĠTips\":22667,\"Ġadamant\":22668,\"Ġdiets\":22669,\"Ġmilestones\":22670,\"Ġcollects\":22671,\"ĠLaboratories\":22672,\"ĠWC\":22673,\"Ġpostp\":22674,\"Ġdams\":22675,\"ĠOEM\":22676,\"Ġrumor\":22677,\"Ġlocking\":22678,\"Ġemission\":22679,\"Ġqueries\":22680,\"Jones\":22681,\"Ġlang\":22682,\"ĠAcqu\":22683,\"ĠMedium\":22684,\"ĠTreasurer\":22685,\"Sept\":22686,\"FB\":22687,\"Ġintegrating\":22688,\"Ġbolstered\":22689,\"Ġincorporating\":22690,\"encers\":22691,\"Ġirregularities\":22692,\"Ġnom\":22693,\"iod\":22694,\"ĠAi\":22695,\"Ġsor\":22696,\"anked\":22697,\"Ġrehears\":22698,\"fig\":22699,\"ĠBug\":22700,\"hoff\":22701,\"Ġtrooper\":22702,\"Ġgalaxy\":22703,\"amon\":22704,\"ĠAtlas\":22705,\"Ġsolicit\":22706,\"Ġsings\":22707,\"ĠInstructions\":22708,\"ĠMig\":22709,\"thinking\":22710,\"ĠCostco\":22711,\"Ġbreasts\":22712,\"Ġportraits\":22713,\"ĠCock\":22714,\"Ġsubscriptions\":22715,\"Ġpine\":22716,\"Ġhaunted\":22717,\"ĠMED\":22718,\"eer\":22719,\"ega\":22720,\"ĠZa\":22721,\"ENN\":22722,\"ĠWinners\":22723,\"aith\":22724,\"safe\":22725,\"Ġ143\":22726,\"ĠWeston\":22727,\"ĠLansing\":22728,\"ĠLaurel\":22729,\"ocrat\":22730,\"ograph\":22731,\"Ġmatchups\":22732,\"ĠFriend\":22733,\"Ġdigest\":22734,\"Ġdimensions\":22735,\"azing\":22736,\"Ġtipping\":22737,\"Ġenrich\":22738,\"gart\":22739,\"argo\":22740,\"Ġoutbreaks\":22741,\"Ġsalvage\":22742,\"ĠErica\":22743,\"Ġmodules\":22744,\"ĠPDF\":22745,\"ĠGoods\":22746,\"oots\":22747,\"2011\":22748,\"Ġinterrupt\":22749,\"Ġradi\":22750,\"ĠSimone\":22751,\"vell\":22752,\"ĠSV\":22753,\"extremely\":22754,\"Ġstadiums\":22755,\"ĠRox\":22756,\"Ġconflicting\":22757,\"Ġyouthful\":22758,\"ĠUM\":22759,\"series\":22760,\"Ġded\":22761,\"Ġfielding\":22762,\"Pre\":22763,\"itled\":22764,\"Ġstreamed\":22765,\"Ġapprentices\":22766,\"ĠAlec\":22767,\"ĠGap\":22768,\"ĠPrem\":22769,\"Ġleased\":22770,\"Ġdeepening\":22771,\"Ġbounds\":22772,\"Ġrethink\":22773,\"ĠVoting\":22774,\"ĠScha\":22775,\"blood\":22776,\"ĠReeves\":22777,\"Ġbells\":22778,\"Ġcollector\":22779,\"ĠCrimson\":22780,\"ĠWheat\":22781,\"207\":22782,\"ĠHB\":22783,\"ĠBCC\":22784,\"Ġsync\":22785,\"ĠAnders\":22786,\"Ġthanking\":22787,\"Ġlayoffs\":22788,\"Ġfoolish\":22789,\"Ġcustod\":22790,\"Ġelephants\":22791,\"Ġcorrelation\":22792,\"ĠHarding\":22793,\"ĠGPU\":22794,\"ĠBarnett\":22795,\"Ġol\":22796,\"Ġalarms\":22797,\"Ġfluctuations\":22798,\"shop\":22799,\"Ġcommentators\":22800,\"ĠAlpine\":22801,\"Ġmur\":22802,\"Ġbiotech\":22803,\"Ġunlocked\":22804,\"ouri\":22805,\"roe\":22806,\"ĠPayment\":22807,\"ĠPOL\":22808,\"ĠGuest\":22809,\"Ġphrases\":22810,\"ĠBuilt\":22811,\"erves\":22812,\"Ġnutritional\":22813,\"205\":22814,\"ourage\":22815,\"Related\":22816,\"Come\":22817,\"ĠSAT\":22818,\"Ġgatherings\":22819,\"Ġsquads\":22820,\"Ġorganising\":22821,\"Ġministerial\":22822,\"Ġkilomet\":22823,\"ĠJump\":22824,\"ĠStrength\":22825,\"ĠFerr\":22826,\"Ġillustrated\":22827,\"ĠOber\":22828,\"Ġextrad\":22829,\"Ġlimitation\":22830,\"idis\":22831,\"ĠMonths\":22832,\"ifts\":22833,\"Ġmotives\":22834,\"Ġmaternal\":22835,\"Ġbait\":22836,\"Ġadversity\":22837,\"Twitter\":22838,\"ĠUni\":22839,\"Ġgrappling\":22840,\"Ġbowls\":22841,\"ĠHib\":22842,\"ĠCopenhagen\":22843,\"Ġsergeant\":22844,\"Ġintro\":22845,\"Ġscrambled\":22846,\"ĠExc\":22847,\"Ġshowcases\":22848,\"Ġplotting\":22849,\"Ġsym\":22850,\"ĠNah\":22851,\"berries\":22852,\"itching\":22853,\"conn\":22854,\"istle\":22855,\"ĠBeginning\":22856,\"asley\":22857,\"ĠMeadow\":22858,\"ĠCra\":22859,\"Ġsupremacist\":22860,\"Ġsweats\":22861,\"production\":22862,\"innon\":22863,\"ovo\":22864,\"Ġscept\":22865,\"Ġdrowning\":22866,\"ĠEh\":22867,\"Ġdecorations\":22868,\"Ġsympathetic\":22869,\"raction\":22870,\"Ġ195\":22871,\"ripp\":22872,\"ĠNotice\":22873,\"charging\":22874,\"ĠDIY\":22875,\"ĠJin\":22876,\"Ġskinny\":22877,\"Ġmaj\":22878,\"Ġwhisk\":22879,\"Ġcongreg\":22880,\"RAL\":22881,\"Ġvolley\":22882,\"Ġestablishments\":22883,\"Ġcite\":22884,\"Miss\":22885,\"Int\":22886,\"iola\":22887,\"ĠBare\":22888,\"KING\":22889,\"ools\":22890,\"private\":22891,\"Ġflaw\":22892,\"Ġwires\":22893,\"Ġideals\":22894,\"oub\":22895,\"Ġ\\\"'\":22896,\"ĠCompet\":22897,\"ĠStatements\":22898,\"ĠHDR\":22899,\"rm\":22900,\"Ġbegging\":22901,\"uffs\":22902,\"Ġdispatch\":22903,\"Ġskipped\":22904,\"Ġlabs\":22905,\"hawks\":22906,\"Ġexpl\":22907,\"Ġpatriotic\":22908,\"ussions\":22909,\"Ġportrayal\":22910,\"ĠBudapest\":22911,\"ĠCod\":22912,\"Ġextingu\":22913,\"smart\":22914,\"Ġburdens\":22915,\"ĠDrama\":22916,\"Ġaltitude\":22917,\"Ġpursuant\":22918,\"à¥\":22919,\"atari\":22920,\"cot\":22921,\"Ġhotline\":22922,\"ooters\":22923,\"ĠRolls\":22924,\"Ġjeopardy\":22925,\"oids\":22926,\"Ġpageant\":22927,\"149\":22928,\"Ġdistinguish\":22929,\"support\":22930,\"ĠHighlands\":22931,\"ĠErnst\":22932,\"ĠHole\":22933,\"pering\":22934,\"ĠHasan\":22935,\"Ġrece\":22936,\"Ġirregular\":22937,\"Ġdisturbed\":22938,\"Ġcoupon\":22939,\"ĠElijah\":22940,\"oise\":22941,\"Ġfriendships\":22942,\"girlfriend\":22943,\"Ġrampage\":22944,\"arers\":22945,\"Ġdispens\":22946,\"assion\":22947,\"Ġtentative\":22948,\"ĠExploration\":22949,\"fashioned\":22950,\"ĠInstit\":22951,\"Ġthemed\":22952,\"ĠKurdistan\":22953,\"ĠCAL\":22954,\"ĠSweeney\":22955,\"Ġransom\":22956,\"Ġstamps\":22957,\"ĠSchwe\":22958,\"ĠLucia\":22959,\"124\":22960,\"omore\":22961,\"Ġmotivate\":22962,\"ĠWorcester\":22963,\"wald\":22964,\"CAR\":22965,\"iken\":22966,\"andro\":22967,\"ffic\":22968,\"ĠRehab\":22969,\"Ġgrou\":22970,\"Ġcontrollers\":22971,\"ĠHai\":22972,\"nz\":22973,\"Ġartillery\":22974,\"ĠMish\":22975,\"Ġregistry\":22976,\"Ġfrontman\":22977,\"ĠCharg\":22978,\"orneys\":22979,\"ĠPRESS\":22980,\"Ġperceptions\":22981,\"ĠMcGee\":22982,\"AU\":22983,\"mg\":22984,\"Off\":22985,\"ĠNGOs\":22986,\"chemical\":22987,\"Ġbrun\":22988,\"ĠHav\":22989,\"Ġlace\":22990,\"Ġ202\":22991,\"Ġdefer\":22992,\"Ġinjected\":22993,\"Ġgluten\":22994,\"ĠRin\":22995,\"ĠAvalanche\":22996,\"Ġcorpor\":22997,\"ĠPamela\":22998,\"Ġfills\":22999,\"ĠReve\":23000,\"ĠMonument\":23001,\"Ġnationalists\":23002,\"ĠIQ\":23003,\"adden\":23004,\"ĠLoop\":23005,\"Ġ134\":23006,\"Reg\":23007,\"click\":23008,\"bush\":23009,\"ĠKub\":23010,\"ipes\":23011,\"Ġtoggle\":23012,\"ĠRae\":23013,\"Ġburgl\":23014,\"Ġholistic\":23015,\"ronics\":23016,\"Ġprominence\":23017,\"jack\":23018,\"Ġfinan\":23019,\"icates\":23020,\"Ġvel\":23021,\"important\":23022,\"Thursday\":23023,\"chet\":23024,\"Ġrefunds\":23025,\"ĠElder\":23026,\"ĠOwner\":23027,\"Ġtakeaway\":23028,\"Pe\":23029,\"ĠToro\":23030,\"Tim\":23031,\"fix\":23032,\"before\":23033,\"ĠMotorola\":23034,\"Ġlev\":23035,\"Term\":23036,\"ĠSne\":23037,\"Ġmisinformation\":23038,\"ĠSinai\":23039,\"Ġnitrogen\":23040,\"Ġ203\":23041,\"Ġescaping\":23042,\"Ġjunction\":23043,\"ĠSantana\":23044,\"ĠYemeni\":23045,\"Ġwhipped\":23046,\"ĠStephenson\":23047,\"Ġattire\":23048,\"ĠBard\":23049,\"atically\":23050,\"ĠFaul\":23051,\"ĠSym\":23052,\"resh\":23053,\"ĠMG\":23054,\"Sub\":23055,\"ĠCarmen\":23056,\"Ġig\":23057,\"ĠSanford\":23058,\"ĠYa\":23059,\"cycle\":23060,\"Ġencryption\":23061,\"ĠScal\":23062,\"ĠChest\":23063,\"ĠMadonna\":23064,\"agin\":23065,\"ĠDHS\":23066,\"ĠCed\":23067,\"YR\":23068,\"Ġtruce\":23069,\"ĠBike\":23070,\"Ġfoes\":23071,\"ĠSlovakia\":23072,\"adal\":23073,\"Rain\":23074,\"OPE\":23075,\"Ġlockdown\":23076,\"Ġunilateral\":23077,\"Ġoverseen\":23078,\"Ġblames\":23079,\"Ġbarrage\":23080,\"aan\":23081,\"uds\":23082,\"ĠRust\":23083,\"ĠHC\":23084,\"cox\":23085,\"ĠAllied\":23086,\"ĠJosÃ©\":23087,\"pected\":23088,\"Ġunp\":23089,\"Ġsomeday\":23090,\"Ġdeductions\":23091,\"icial\":23092,\"ĠPRO\":23093,\"ĠIntern\":23094,\"Ġhemp\":23095,\"Ġkilograms\":23096,\"Ġnets\":23097,\"ĠBACK\":23098,\"early\":23099,\"outed\":23100,\"Ġrelegated\":23101,\"Ġ1958\":23102,\"ĠMustang\":23103,\"Ġgamble\":23104,\"Ġprostitution\":23105,\"ĠPapa\":23106,\"Ġinexpensive\":23107,\"GHz\":23108,\"Ġjerseys\":23109,\"Ġmisery\":23110,\"VIS\":23111,\"ĠRAW\":23112,\"Ġthri\":23113,\"Ġaffiliation\":23114,\"small\":23115,\"Ġflashed\":23116,\"Ġcoastline\":23117,\"Ġgard\":23118,\"Ġsv\":23119,\"Ġwaits\":23120,\"itton\":23121,\"London\":23122,\"Ġaccus\":23123,\"ĠCharge\":23124,\"Ġincub\":23125,\"Ġwanna\":23126,\"ĠAwareness\":23127,\"abies\":23128,\"ĠUh\":23129,\"Ġpersuaded\":23130,\"ĠThames\":23131,\"Ġcurated\":23132,\"Ī\":23133,\"Ġbrutally\":23134,\"Ġrooftop\":23135,\"Ġoy\":23136,\"Ġ1900\":23137,\"bery\":23138,\"Ġuphill\":23139,\"Ġinteracting\":23140,\"Ġchilly\":23141,\"ERE\":23142,\"Ġcapsule\":23143,\"ĠSaul\":23144,\"ocker\":23145,\"Ġdeserving\":23146,\"ĠBowen\":23147,\"ĠReaders\":23148,\"ĠWriters\":23149,\"Ġartifacts\":23150,\"ĠRanger\":23151,\"reau\":23152,\"Ġimperson\":23153,\"Ġhears\":23154,\"ĠMaher\":23155,\"neg\":23156,\"Ġmantra\":23157,\"Ġmull\":23158,\"Ġelders\":23159,\"ĠAmtrak\":23160,\"Ġspouses\":23161,\"ĠHak\":23162,\"Ġopenness\":23163,\"Ġprevailed\":23164,\"Ġfortnight\":23165,\"Pal\":23166,\"ride\":23167,\"Ġillustrate\":23168,\"dominated\":23169,\"trust\":23170,\"ī\":23171,\"ĠFemale\":23172,\"ĠSlim\":23173,\"Ġdesc\":23174,\"ĠKathryn\":23175,\"Ġdeepen\":23176,\"TAIN\":23177,\"eredith\":23178,\"Ġchanted\":23179,\"ĠHector\":23180,\"bread\":23181,\"ĠIsa\":23182,\"Ġvolcanic\":23183,\"Ġah\":23184,\"owners\":23185,\"aquin\":23186,\"Ġmelting\":23187,\"Ġpreschool\":23188,\"ocus\":23189,\"ĠMast\":23190,\"ĠMyr\":23191,\"Ġsuppress\":23192,\"Ġversatility\":23193,\"ĠNEC\":23194,\"Ġhoax\":23195,\"Ġmutually\":23196,\"ĠNeb\":23197,\"ĠWheel\":23198,\"kit\":23199,\"abl\":23200,\"again\":23201,\"ĠSonny\":23202,\"rift\":23203,\"Ġsweater\":23204,\"Ġinund\":23205,\"ĠTaco\":23206,\"ĠBout\":23207,\"Ġnonprofits\":23208,\"Ġmodify\":23209,\"Ġprofessionalism\":23210,\"ĠGould\":23211,\"ĠGuerrero\":23212,\"Ġterribly\":23213,\"ĠBenz\":23214,\"Ġcountered\":23215,\"Ġbean\":23216,\"ĠPhelps\":23217,\"Ġprowess\":23218,\"bc\":23219,\"Ġfeast\":23220,\"Ġ5000\":23221,\"Ġrevisit\":23222,\"Ġchin\":23223,\"agent\":23224,\"Ġtones\":23225,\"Ġextraction\":23226,\"ĠPosts\":23227,\"oin\":23228,\"Ġattain\":23229,\"Ġgardening\":23230,\"earned\":23231,\"ĠOtto\":23232,\"player\":23233,\"Ġscams\":23234,\"ĠHonolulu\":23235,\"ĠAppro\":23236,\"ĠHIGH\":23237,\"Ġdwell\":23238,\"Islam\":23239,\"leaders\":23240,\"Ġlegisl\":23241,\"expl\":23242,\"ĠChoi\":23243,\"Ġfrenzy\":23244,\"Ġcommercially\":23245,\"Ġlbs\":23246,\"Ġgateway\":23247,\"ĠAndersen\":23248,\"emia\":23249,\"lez\":23250,\"Ġresidences\":23251,\"office\":23252,\"ĠHelsinki\":23253,\"olia\":23254,\"Ġwolf\":23255,\"Ġstyling\":23256,\"ĠJunction\":23257,\"ĠPeyton\":23258,\"udo\":23259,\"ĠDorothy\":23260,\"Ġfreshly\":23261,\"ĠJulio\":23262,\"ĠSunset\":23263,\"ĠMadden\":23264,\"Ġissu\":23265,\"Ġsounding\":23266,\"sports\":23267,\"Ġmassively\":23268,\"ĠRahman\":23269,\"Ġpresided\":23270,\"Instead\":23271,\"Ġ136\":23272,\"ĠHowell\":23273,\"beit\":23274,\"Ġprosperous\":23275,\"Ġwrongly\":23276,\"ĠRaqqa\":23277,\"ĠCes\":23278,\"Ġbuddy\":23279,\"Ġchatting\":23280,\"Ġfencing\":23281,\"Ġtant\":23282,\"ocated\":23283,\"ALK\":23284,\"Ġsnapping\":23285,\"euro\":23286,\"Ryan\":23287,\"ĠRecogn\":23288,\"ucked\":23289,\"Ġpurported\":23290,\"ĠCann\":23291,\"Ġintimidating\":23292,\"Ġrulers\":23293,\"ĠMarse\":23294,\"Art\":23295,\"ĠAadhaar\":23296,\"Ġvows\":23297,\"Ġhunter\":23298,\"ourmet\":23299,\"ĠVarious\":23300,\"2009\":23301,\"anie\":23302,\"Ġcompassionate\":23303,\"ĠParking\":23304,\"Ġmalaria\":23305,\"Ġamnesty\":23306,\"Ġworsened\":23307,\"ĠTitan\":23308,\"Ġcrossings\":23309,\"drug\":23310,\"Ġaddicted\":23311,\"Ġremorse\":23312,\"ĠDestiny\":23313,\"Dear\":23314,\"Ġhur\":23315,\"Ġimplicated\":23316,\"Ġplayful\":23317,\"Ġripe\":23318,\"Ġsizable\":23319,\"Ġcrab\":23320,\"Ġliqu\":23321,\"Ġdrib\":23322,\"Ġcontraction\":23323,\"cro\":23324,\"ĠGus\":23325,\"Ġdoomed\":23326,\"Ġmog\":23327,\"ĠMonitor\":23328,\"Count\":23329,\"Ġsadd\":23330,\"Ġwrestler\":23331,\"Ġrestraints\":23332,\"Ġraging\":23333,\"185\":23334,\"Ġtapes\":23335,\"Ġmitigation\":23336,\"ocratic\":23337,\"Ġvib\":23338,\"ĠSnowden\":23339,\"aldo\":23340,\"Ġweights\":23341,\"Ġ1959\":23342,\"ucc\":23343,\"ĠCoc\":23344,\"Log\":23345,\"ĠStev\":23346,\"Ġdealership\":23347,\"Ġtrademarks\":23348,\"iru\":23349,\"Ġbeneficiary\":23350,\"Ġlegislator\":23351,\"Ġdeadlines\":23352,\"Ġcosmetics\":23353,\"ĠTammy\":23354,\"ĠCombined\":23355,\"Ġeducator\":23356,\"athon\":23357,\"Ġcombo\":23358,\"fu\":23359,\"appropriate\":23360,\"nington\":23361,\"ĠLiberties\":23362,\"missions\":23363,\"opard\":23364,\"ĠMondays\":23365,\"Ġfetch\":23366,\"Ġhers\":23367,\"jon\":23368,\"ukes\":23369,\"zek\":23370,\"Ġvetting\":23371,\"yet\":23372,\"Ġfacilitating\":23373,\"ĠStras\":23374,\"character\":23375,\"ĠHeads\":23376,\"Ġclim\":23377,\"ĠAlbuquerque\":23378,\"Ġbind\":23379,\"Ġconcluding\":23380,\"ĠBasically\":23381,\"rail\":23382,\"ĠTCU\":23383,\"ĠDepression\":23384,\"Ġhem\":23385,\"ĠHue\":23386,\"Ġpand\":23387,\"Ġscoreboard\":23388,\"Av\":23389,\"Ġidol\":23390,\"compl\":23391,\"Ġredesign\":23392,\"ĠJarrett\":23393,\"Ġfavoured\":23394,\"ĠINS\":23395,\"Ġpropelled\":23396,\"Ġevasion\":23397,\"Ġwidened\":23398,\"Ġwastewater\":23399,\"nard\":23400,\"responsive\":23401,\"Ġdemographics\":23402,\"engine\":23403,\"ĠBrewer\":23404,\"ĠBaxter\":23405,\"ront\":23406,\"ĠColon\":23407,\"Ġpromoter\":23408,\"Ġgenres\":23409,\"ovsky\":23410,\"build\":23411,\"urate\":23412,\"ĠCohn\":23413,\"design\":23414,\"Ġturbulent\":23415,\"Ġcurtain\":23416,\"310\":23417,\"ĠLamp\":23418,\"ĠBonds\":23419,\"church\":23420,\"Ġdeterrent\":23421,\"Ġdictatorship\":23422,\"acement\":23423,\"haul\":23424,\"Ġspir\":23425,\"Ġconceived\":23426,\"Ġstern\":23427,\"sit\":23428,\"Ġsingular\":23429,\"ĠYog\":23430,\"Ġconditional\":23431,\"Ġide\":23432,\"lund\":23433,\"Ġautop\":23434,\"ĠBEST\":23435,\"ĠJed\":23436,\"Ġrationale\":23437,\"Ġalarmed\":23438,\"Ġshovel\":23439,\"ĠProb\":23440,\"ĠMao\":23441,\"ĠBurgess\":23442,\"Ġ1953\":23443,\"above\":23444,\"ĠManson\":23445,\"Ġdismal\":23446,\"ĠFrankie\":23447,\"Ġtempted\":23448,\"Ġunderdog\":23449,\"ribing\":23450,\"ENCY\":23451,\"ĠDele\":23452,\"Las\":23453,\"places\":23454,\"Ġnotoriously\":23455,\"ĠAkin\":23456,\"Ġglut\":23457,\"Ġseamlessly\":23458,\"Ġrecess\":23459,\"written\":23460,\"ĠTJ\":23461,\"occ\":23462,\"ĠTerritory\":23463,\"ĠAIR\":23464,\"ĠDiagn\":23465,\"Ġvacancies\":23466,\"Ġcultivation\":23467,\"ĠAless\":23468,\"Ġrenamed\":23469,\"ĠMahmoud\":23470,\"bright\":23471,\"Ġvisibly\":23472,\"Ġnas\":23473,\"erred\":23474,\"ĠCarn\":23475,\"Ġtriggers\":23476,\"Ġpunishing\":23477,\"Ġluc\":23478,\"ĠBett\":23479,\"Ġbeam\":23480,\"ĠCheng\":23481,\"aina\":23482,\"Ġdetermines\":23483,\"ĠGerry\":23484,\"Ġshocks\":23485,\"Ġstainless\":23486,\"Ġdefects\":23487,\"ĠCinem\":23488,\"Ġtorrent\":23489,\"Ġresurgence\":23490,\"Ġcoral\":23491,\"Ġblitz\":23492,\"ĠGel\":23493,\"Ġstemmed\":23494,\"gur\":23495,\"Ġlymph\":23496,\"zzo\":23497,\"Ġspearheaded\":23498,\"Ġlicences\":23499,\"';\":23500,\"Ġarbitrary\":23501,\"ĠUzbek\":23502,\"Ġthief\":23503,\"reaching\":23504,\"Ġcand\":23505,\"ĠEA\":23506,\"ĠParaly\":23507,\"ĠEmerson\":23508,\"ĠSergey\":23509,\"ĠScher\":23510,\"ĠWr\":23511,\"rowing\":23512,\"Ġ3000\":23513,\"Ġmighty\":23514,\"elight\":23515,\"mAh\":23516,\"Ġcelebr\":23517,\"ĠConclusion\":23518,\"ĠCathy\":23519,\"Ġpolished\":23520,\"uddled\":23521,\"ewski\":23522,\"Ġfucking\":23523,\"Ġinterfering\":23524,\"Ġlandscapes\":23525,\"Ġfearful\":23526,\"ĠDetention\":23527,\"%).\":23528,\"ĠTT\":23529,\"Ġbleak\":23530,\"Ġindebted\":23531,\"Ġcheat\":23532,\"Ġconsolation\":23533,\"ĠPace\":23534,\"raine\":23535,\"Ġhonorary\":23536,\"420\":23537,\"Ġtechnician\":23538,\"ĠComprehensive\":23539,\"Ġfences\":23540,\"Ġwearable\":23541,\"ĠMarilyn\":23542,\"stru\":23543,\"Ġdrained\":23544,\"ĠGibraltar\":23545,\"lag\":23546,\"Ġdisorderly\":23547,\"Ġproclaimed\":23548,\"Ġcapacities\":23549,\"Ġretains\":23550,\"ĠVid\":23551,\"oshi\":23552,\"ĠEid\":23553,\"Ġanalytical\":23554,\"ominium\":23555,\"ĠExaminer\":23556,\"ĠNAACP\":23557,\"ocol\":23558,\"rev\":23559,\"ĠRim\":23560,\"ĠWoody\":23561,\"ĠMcKenna\":23562,\"ĠLennon\":23563,\"ĠEmploy\":23564,\"Fort\":23565,\"psy\":23566,\"Ġsphere\":23567,\"oday\":23568,\"ĠChick\":23569,\"ĠCompared\":23570,\"ĠIranians\":23571,\"ĠAccountability\":23572,\"itchie\":23573,\"ĠDickinson\":23574,\"Ġflock\":23575,\"Ġeclips\":23576,\"Ġnat\":23577,\"anke\":23578,\"ĠNeighborhood\":23579,\"Ġ141\":23580,\"Ġscarce\":23581,\"Ġcreations\":23582,\"lists\":23583,\"Ġuseless\":23584,\"Ġcriticisms\":23585,\"Ġruler\":23586,\"ĠHick\":23587,\"arya\":23588,\"worker\":23589,\"alam\":23590,\"Angelo\":23591,\"otle\":23592,\"Ġnewsletters\":23593,\"Ġerected\":23594,\"Ġzip\":23595,\"ĠBirthday\":23596,\"Ġdogged\":23597,\"Ġdanced\":23598,\"Ġconfession\":23599,\"Ġvomiting\":23600,\"ickers\":23601,\"Ġfox\":23602,\"Ġdeduct\":23603,\"Ġstresses\":23604,\"poll\":23605,\"ĠRadar\":23606,\"Ġengagements\":23607,\"Ġexaminer\":23608,\"Ġopportun\":23609,\"Ġlongevity\":23610,\"Ġbanana\":23611,\"carbon\":23612,\"uo\":23613,\"ĠLT\":23614,\"Ġsynagogue\":23615,\"Ġblackmail\":23616,\"INK\":23617,\"Ġfle\":23618,\"ĠGutierrez\":23619,\"Ġracket\":23620,\"Ġevenings\":23621,\"Ġdietary\":23622,\"ĠKok\":23623,\"Ġfaulty\":23624,\"Ġabandoning\":23625,\"ĠFlow\":23626,\"quest\":23627,\"estead\":23628,\"Ġbir\":23629,\"Ġsuicidal\":23630,\"ĠGift\":23631,\"ĠMissing\":23632,\"ĠMazda\":23633,\"ĠRib\":23634,\"ĠJourney\":23635,\"Ġconcede\":23636,\"Ġbrushed\":23637,\"Tw\":23638,\"andowski\":23639,\"ĠYun\":23640,\"Bride\":23641,\"zai\":23642,\"awatts\":23643,\"Ġcha\":23644,\"Ġspans\":23645,\"SF\":23646,\"Ġshells\":23647,\"planned\":23648,\"ĠGeographic\":23649,\"ĠVent\":23650,\"Ġfav\":23651,\"Ġinterrogation\":23652,\"Ġvaries\":23653,\"ĠPlat\":23654,\"operative\":23655,\"avid\":23656,\"Ġgreatness\":23657,\"ĠStrait\":23658,\"ĠSelling\":23659,\"Ġlawful\":23660,\"Ġlyn\":23661,\"Ġfunnel\":23662,\"Ġpundits\":23663,\"ties\":23664,\"Ġpneumonia\":23665,\"Ġcommencement\":23666,\"Ġbrisk\":23667,\"fires\":23668,\"ĠHTML\":23669,\"ĠSevent\":23670,\"Ġhistor\":23671,\"Ġ147\":23672,\"olls\":23673,\"Ġpian\":23674,\"Little\":23675,\"Ġcommercials\":23676,\"Ġdeteriorated\":23677,\"Ġbasin\":23678,\"Ġprohibition\":23679,\"Ġrestrictive\":23680,\"Ġtom\":23681,\"ĠPulse\":23682,\"vale\":23683,\"Ġmim\":23684,\"ĠLyons\":23685,\"ĠTrinidad\":23686,\"data\":23687,\"195\":23688,\"ĠPain\":23689,\"vor\":23690,\"ĠDirectorate\":23691,\"Wow\":23692,\"essential\":23693,\"Ġemerges\":23694,\"ĠDoors\":23695,\"Ġunde\":23696,\"Ġarchives\":23697,\"ĠIX\":23698,\"ĠAman\":23699,\"oric\":23700,\"ĠOper\":23701,\"nothing\":23702,\"Ġ142\":23703,\"igr\":23704,\"rust\":23705,\"ĠBYU\":23706,\"ĠBom\":23707,\"Ġrift\":23708,\"ĠAbs\":23709,\"ĠJenn\":23710,\"Ġrookies\":23711,\"hoe\":23712,\"Ġunderage\":23713,\"eden\":23714,\"Ġroasted\":23715,\"Ġenrol\":23716,\"Ġerased\":23717,\"Ġfreeway\":23718,\"Sil\":23719,\"Ġplanner\":23720,\"Ġconfess\":23721,\"ĠDual\":23722,\"ĠHeadquarters\":23723,\"bottom\":23724,\"Ġstatistic\":23725,\"ĠPush\":23726,\"Ġanim\":23727,\"ITT\":23728,\"Ġexecutions\":23729,\"Hub\":23730,\"ĠStick\":23731,\"Ġobscure\":23732,\"oven\":23733,\"Ġcoats\":23734,\"unc\":23735,\"Morning\":23736,\"Ġnit\":23737,\"mie\":23738,\"Ġcurves\":23739,\"gew\":23740,\"ĠAnniversary\":23741,\"members\":23742,\"ĠAbsolutely\":23743,\"Ġapt\":23744,\"otional\":23745,\"ĠGin\":23746,\"izo\":23747,\"Ġpretending\":23748,\"arak\":23749,\"Ġorganise\":23750,\"Ġroyalties\":23751,\"ĠCamden\":23752,\"Ġsausage\":23753,\"Inst\":23754,\"Ġchalk\":23755,\"ĠSurf\":23756,\"ĠSunrise\":23757,\"Ġmoder\":23758,\"aido\":23759,\"loving\":23760,\"lus\":23761,\"Ġoblig\":23762,\"Ġmotions\":23763,\"Ġclarification\":23764,\"ĠOM\":23765,\"Ġbishop\":23766,\"Ġexhibitions\":23767,\"ĠRifle\":23768,\"ĠPhot\":23769,\"ĠHM\":23770,\"ATIONAL\":23771,\"Ġwid\":23772,\"Ġreside\":23773,\"ĠPV\":23774,\"OOK\":23775,\"ĠTue\":23776,\"Ġ1200\":23777,\"Ġ1957\":23778,\"Ġespionage\":23779,\"ĠAPPLIC\":23780,\"Ġblasts\":23781,\"fter\":23782,\"Ġimmensely\":23783,\"ĠLots\":23784,\"Ġinflammatory\":23785,\"anging\":23786,\"Ġtumultuous\":23787,\"identified\":23788,\"Ġstead\":23789,\"ĠAch\":23790,\"Ãī\":23791,\"Ġbub\":23792,\"hler\":23793,\"olution\":23794,\"Ġshun\":23795,\"Ġnull\":23796,\"Ġunused\":23797,\"ĠObs\":23798,\"Ġinsol\":23799,\"ĠAttack\":23800,\"ertain\":23801,\"Ġdefiant\":23802,\"Through\":23803,\"ĠArmour\":23804,\"Ġsimulation\":23805,\"UCK\":23806,\"Ġinfluenza\":23807,\"Ġonset\":23808,\"Ġbored\":23809,\"Ġsouls\":23810,\"Ġreferees\":23811,\"Ġcollaborations\":23812,\"ĠLer\":23813,\"Ġcreepy\":23814,\"Ġanaly\":23815,\"ĠEffect\":23816,\"orting\":23817,\"Card\":23818,\"Ġdice\":23819,\"Ġharvesting\":23820,\"235\":23821,\"sty\":23822,\"ĠMcCartney\":23823,\"Ġsalute\":23824,\"UMP\":23825,\"Ġherb\":23826,\"ĠAbuse\":23827,\"ĠRamadan\":23828,\"Ġsuck\":23829,\"trained\":23830,\"ĠPhysical\":23831,\"iren\":23832,\"anches\":23833,\"erie\":23834,\"Ġhangs\":23835,\"Ġcataly\":23836,\"Ġintuitive\":23837,\"assi\":23838,\"Ġtechn\":23839,\"Ġjugg\":23840,\"Ġgameplay\":23841,\"Ġapolog\":23842,\"Ġfifteen\":23843,\"Ġgalleries\":23844,\"Ġoutlines\":23845,\"patient\":23846,\"ĠPotential\":23847,\"Ġethnicity\":23848,\"Ġharbour\":23849,\"Ġoverthrow\":23850,\"ĠLung\":23851,\"Ġwarehouses\":23852,\"ĠMonitoring\":23853,\"Ġmentors\":23854,\"Ġsized\":23855,\"Ġenvisioned\":23856,\"Ġgin\":23857,\"DT\":23858,\"Ġpropel\":23859,\"ĠKul\":23860,\"ference\":23861,\"estic\":23862,\"ĠLego\":23863,\"Ġdinners\":23864,\"ĠMoe\":23865,\"designed\":23866,\"ĠSusp\":23867,\"ĠBrick\":23868,\"qua\":23869,\"IDS\":23870,\"ĠBam\":23871,\"athe\":23872,\"Ġslices\":23873,\"Ġbottled\":23874,\"thy\":23875,\"producing\":23876,\"ĠTerror\":23877,\"professional\":23878,\"ĠKis\":23879,\"erto\":23880,\"ĠVehicles\":23881,\"Ġbeforehand\":23882,\"Ġdetrimental\":23883,\"weights\":23884,\"Ġallowances\":23885,\"Williams\":23886,\"ĠSyrians\":23887,\"ĠSto\":23888,\"Ġcozy\":23889,\"reditation\":23890,\"ensen\":23891,\"ĠSard\":23892,\"Ġroy\":23893,\"ooting\":23894,\"ĠReserv\":23895,\"ominated\":23896,\"emate\":23897,\"ĠTot\":23898,\"ĠCarnegie\":23899,\"ĠThib\":23900,\"ĠMarshal\":23901,\"Ġ152\":23902,\"Ġmayors\":23903,\"inery\":23904,\"ĠFiona\":23905,\"ĠCadillac\":23906,\"ivated\":23907,\"Ġeagerly\":23908,\"ĠOffensive\":23909,\"Ġastronaut\":23910,\"ĠVital\":23911,\"Ġcane\":23912,\"Ġquitting\":23913,\"ĠLone\":23914,\"Ġcensorship\":23915,\"ĠWelch\":23916,\"ĠUd\":23917,\"Ġmarquee\":23918,\"ĠDip\":23919,\"Ġwhereby\":23920,\"Ġtiger\":23921,\"gem\":23922,\"Ġconserv\":23923,\"Ġpresumed\":23924,\"ĠEntry\":23925,\"ffer\":23926,\"ĠProceed\":23927,\"Ġbrawl\":23928,\"ĠJaime\":23929,\"Ġecho\":23930,\"Ġadvancements\":23931,\"Ġtransitional\":23932,\"erick\":23933,\"Ġbully\":23934,\"anan\":23935,\"Ġreinvent\":23936,\"ĠLetters\":23937,\"Ġbricks\":23938,\"ĠSmy\":23939,\"Ġtowering\":23940,\"gging\":23941,\"299\":23942,\"orian\":23943,\"dimensional\":23944,\"ĠForty\":23945,\"ĠSinn\":23946,\"ushi\":23947,\"ĠSurveillance\":23948,\"enabled\":23949,\"ĠMous\":23950,\"ĠVive\":23951,\"Marcus\":23952,\"Ġvom\":23953,\"Ġcreek\":23954,\"Ġlime\":23955,\"Ġseismic\":23956,\"ĠFork\":23957,\"Ġembroiled\":23958,\"marks\":23959,\"Ġherald\":23960,\"ĠSonia\":23961,\"âĢ¦\\\"\":23962,\"wired\":23963,\"Ġobliged\":23964,\"ĠProjects\":23965,\"lde\":23966,\"ĠRiders\":23967,\"Ġovercoming\":23968,\"Mail\":23969,\"ĠLawn\":23970,\"ĠHawk\":23971,\"figure\":23972,\"ĠWritten\":23973,\"Ġens\":23974,\"Ġspacious\":23975,\"target\":23976,\"ĠRecep\":23977,\"ĠSAM\":23978,\"Ġentertained\":23979,\"Ġignited\":23980,\"ĠCENT\":23981,\"ogenic\":23982,\"Ġunatt\":23983,\"Ġexceeds\":23984,\"Ġ--------------------------------\":23985,\"Ġpillars\":23986,\"ĠBorders\":23987,\"ickey\":23988,\"Ġextinction\":23989,\"Ġviability\":23990,\"Ġtumors\":23991,\"ĠWilkinson\":23992,\"ĠKEY\":23993,\"Ġbins\":23994,\"ĠReported\":23995,\"Sm\":23996,\"ĠExclusive\":23997,\"ĠChilean\":23998,\"info\":23999,\"Ġwilderness\":24000,\"did\":24001,\"absolutely\":24002,\"pillar\":24003,\"Ġelites\":24004,\"ĠPreview\":24005,\"ixie\":24006,\"Mont\":24007,\"ribut\":24008,\"dream\":24009,\"Ġplanners\":24010,\"ĠSomerset\":24011,\"Ġenvis\":24012,\"ĠStall\":24013,\"Ġelevate\":24014,\"ographies\":24015,\"rama\":24016,\"Ha\":24017,\"Ġamidst\":24018,\"oho\":24019,\"Ġrejects\":24020,\"Jim\":24021,\"Ġmarginally\":24022,\"Ġusher\":24023,\"arez\":24024,\"ĠHawth\":24025,\"Ġsprink\":24026,\"ĠOffer\":24027,\"Ġanchored\":24028,\"ucking\":24029,\"ĠGarn\":24030,\"ĠConserv\":24031,\"Ġsocietal\":24032,\"Ġbrowsing\":24033,\"Ġbidder\":24034,\"burgh\":24035,\"ĠRunner\":24036,\"Ġtrendy\":24037,\"verts\":24038,\"imposed\":24039,\"ĠPatton\":24040,\"lements\":24041,\"Ġspicy\":24042,\"Ġswe\":24043,\"ĠStrike\":24044,\"Ġclam\":24045,\"ĠYankee\":24046,\"ĠKT\":24047,\"ĠGreenwood\":24048,\"ĠWays\":24049,\"Ġ2050\":24050,\"Ġattach\":24051,\"ĠShim\":24052,\"Ġmeltdown\":24053,\"Ġassemble\":24054,\"ĠUPDATE\":24055,\"Ġscout\":24056,\"Brown\":24057,\"ĠKobe\":24058,\"Ġpostpone\":24059,\"liness\":24060,\"allo\":24061,\"rief\":24062,\"ĠGerm\":24063,\"ĠFD\":24064,\"ĠReggie\":24065,\"ĠUnivers\":24066,\"ĠShepard\":24067,\"Ġcancell\":24068,\"ĠRomeo\":24069,\"ĠWarrior\":24070,\"ench\":24071,\"ifier\":24072,\"Ġprivileges\":24073,\"Ġsenses\":24074,\"Ġimpoverished\":24075,\"ĠPostal\":24076,\"encer\":24077,\"ĠConrad\":24078,\"Ġprinter\":24079,\"Ġinflicted\":24080,\"ĠGamble\":24081,\"ĠHeroes\":24082,\"132\":24083,\"Ġrevisions\":24084,\"Ġunsuccessfully\":24085,\"ĠHeisman\":24086,\"Ġstamped\":24087,\"inding\":24088,\"ĠLuna\":24089,\"Ġreinvest\":24090,\"ducers\":24091,\"ĠPassword\":24092,\"Leod\":24093,\"Ġcompounded\":24094,\"',\\\"\":24095,\"ogging\":24096,\"Ġprobing\":24097,\"ĠPBS\":24098,\"ĠMU\":24099,\"ĠWhenever\":24100,\"Ġsped\":24101,\"ĠCompetitive\":24102,\"isans\":24103,\"opa\":24104,\"Ġcleric\":24105,\"Ġvivid\":24106,\"à¸\":24107,\"126\":24108,\"Ġinconvenience\":24109,\"udi\":24110,\"Ġimmersive\":24111,\"Ġdiversion\":24112,\"Ġlogs\":24113,\"Ġspying\":24114,\"inct\":24115,\"Ġlitres\":24116,\"Ġmetallic\":24117,\"identally\":24118,\"FX\":24119,\"Ġloudly\":24120,\"Ġnursery\":24121,\"Ġcollectors\":24122,\"ĠKart\":24123,\"Ġescalate\":24124,\"Ġringing\":24125,\"Ġprocedural\":24126,\"Ġdisrupting\":24127,\"ĠEthiopian\":24128,\"ĠCFL\":24129,\"Ġillustrates\":24130,\"Ġperks\":24131,\"official\":24132,\"325\":24133,\"Ġmillennial\":24134,\"Ġbreadth\":24135,\"Ġmelted\":24136,\"Ġ850\":24137,\"ĠBake\":24138,\"donald\":24139,\"ĠGrac\":24140,\"Ġseeded\":24141,\"ĠDiscount\":24142,\"idates\":24143,\"Ġdrift\":24144,\"Ġcaptive\":24145,\"Ġseriousness\":24146,\"Ġrepercussions\":24147,\"Ġdisciplines\":24148,\"Ġthesis\":24149,\"Ġsleeve\":24150,\"ses\":24151,\"Monday\":24152,\"Ġthwart\":24153,\"ĠLic\":24154,\"Ġquadru\":24155,\"ĠPresbyterian\":24156,\"Ġreactors\":24157,\"ĠSuzanne\":24158,\"ewater\":24159,\"Ġlam\":24160,\"Ġbreastfeeding\":24161,\"Ġrats\":24162,\"ĠArtists\":24163,\"Ġdomestically\":24164,\"Ġdecom\":24165,\"ĠArms\":24166,\"basketball\":24167,\"Ġscrub\":24168,\"ĠTeddy\":24169,\"beh\":24170,\"ĠBetsy\":24171,\"ĠNursing\":24172,\"Ġdescriptions\":24173,\"127\":24174,\"gil\":24175,\"itional\":24176,\"Ġchampioned\":24177,\"ĠCalling\":24178,\"Ġrealization\":24179,\"ĠBuddy\":24180,\"hou\":24181,\"ĠDire\":24182,\"ĠHuff\":24183,\"Ġlipstick\":24184,\"Ray\":24185,\"Ġflare\":24186,\"belt\":24187,\"Ġbrightest\":24188,\"Ġmalfunction\":24189,\"ĠManor\":24190,\"Ġsaturated\":24191,\"rays\":24192,\"ĠDW\":24193,\"ixed\":24194,\"ĠSlovenia\":24195,\"seen\":24196,\"ĠCause\":24197,\"arios\":24198,\"ASE\":24199,\"Ġrend\":24200,\"ĠTBA\":24201,\"Ġlecturer\":24202,\"attering\":24203,\"Ġaffluent\":24204,\"CEO\":24205,\"Ġbreathtaking\":24206,\"ĠGiles\":24207,\"irth\":24208,\"ĠPhilips\":24209,\"Ġposture\":24210,\"ĠTSA\":24211,\"heit\":24212,\"Ġmenace\":24213,\"ricks\":24214,\"ĠAden\":24215,\"ĠReich\":24216,\"iggle\":24217,\"ĠShutterstock\":24218,\"Ġcourageous\":24219,\"edia\":24220,\"Staff\":24221,\"Ġdivert\":24222,\"ĠCir\":24223,\"Ġguessing\":24224,\"apers\":24225,\"ĠBritons\":24226,\"lÃ©\":24227,\"Ġconvened\":24228,\"ĠSerbian\":24229,\"Ġricher\":24230,\"Ġcock\":24231,\"Ġdeposited\":24232,\"company\":24233,\"Ġdelic\":24234,\"sensitive\":24235,\"tank\":24236,\"ĠPatty\":24237,\"mia\":24238,\"onomous\":24239,\"cn\":24240,\"Ġclamp\":24241,\"ĠAcademic\":24242,\"Ġprosecuting\":24243,\"ĠTransparency\":24244,\"Ġdeflation\":24245,\"Ġdashboard\":24246,\"ĠDress\":24247,\"Ġlin\":24248,\"mu\":24249,\"ĠGoodell\":24250,\"Ġlav\":24251,\"ĠTwelve\":24252,\"Ġflavour\":24253,\"Ġfiercely\":24254,\"Ġbloom\":24255,\"ĠHaf\":24256,\"ĠGrad\":24257,\"LET\":24258,\"ĠSeeing\":24259,\"oxide\":24260,\"Ġmenus\":24261,\"char\":24262,\"adoes\":24263,\"combe\":24264,\"Street\":24265,\"ĠRidley\":24266,\"Ġdepicts\":24267,\"ĠPred\":24268,\"ÑĢ\":24269,\"British\":24270,\"Ġbumps\":24271,\"Ġlamp\":24272,\"ĠDesmond\":24273,\"ĠPB\":24274,\"Ġfrag\":24275,\"tin\":24276,\"ĠSharing\":24277,\"Ġdesperation\":24278,\"Ġcommuter\":24279,\"igrants\":24280,\"ĠShapiro\":24281,\"Ġkinda\":24282,\"Ġimpartial\":24283,\"ĠJewel\":24284,\"Ġcongratulations\":24285,\"Ġcompost\":24286,\"Ġadmiration\":24287,\"Ġpaycheck\":24288,\"ĠAnonymous\":24289,\"enger\":24290,\"Mer\":24291,\"ĠGospel\":24292,\"ĠEth\":24293,\"ĠMH\":24294,\"Ġfem\":24295,\"ĠTrial\":24296,\"Ġdepths\":24297,\"ĠApplied\":24298,\"Ġgrit\":24299,\"Ġerase\":24300,\"sid\":24301,\"comm\":24302,\"}\":24303,\"Ġretreated\":24304,\"Ġanalysed\":24305,\"ĠRegular\":24306,\"ĠPesh\":24307,\"ICAL\":24308,\"pei\":24309,\"ĠReilly\":24310,\"ĠTrib\":24311,\"Ġbooths\":24312,\"Ġdrank\":24313,\"Ġcoma\":24314,\"Ġharvested\":24315,\"ĠCHAR\":24316,\"Ġbutterfly\":24317,\"Ġsailed\":24318,\"ĠDrink\":24319,\"eping\":24320,\"ATCH\":24321,\"ĠLegends\":24322,\"Ġinsured\":24323,\"Ġwholes\":24324,\"ĠBis\":24325,\"ĠShea\":24326,\"ighter\":24327,\"Ġsnakes\":24328,\"ĠGunn\":24329,\"ĠPoss\":24330,\"Ġdispar\":24331,\"Ġbombshell\":24332,\"Ġscanning\":24333,\"340\":24334,\"choice\":24335,\"cool\":24336,\"\\\"âĢĶ\":24337,\"ĠTheo\":24338,\"rine\":24339,\"ĠJacques\":24340,\"Ġdisadvantaged\":24341,\"Ġparamount\":24342,\"igate\":24343,\"stat\":24344,\"anski\":24345,\"Ġoutsourcing\":24346,\"Ġpopulous\":24347,\"Ġbinge\":24348,\"ĠOrganic\":24349,\"urban\":24350,\"Ġyogurt\":24351,\"Ġretweet\":24352,\"osen\":24353,\"cially\":24354,\"215\":24355,\"Ġeditions\":24356,\"Ġburgeoning\":24357,\"efully\":24358,\"ĠThousand\":24359,\"Ġreplacements\":24360,\"ĠAmazing\":24361,\"rator\":24362,\"icy\":24363,\"Ġintensify\":24364,\"Sen\":24365,\"ĠQuincy\":24366,\"powers\":24367,\"ĠAur\":24368,\"ĠZion\":24369,\"stal\":24370,\"Ġpillar\":24371,\"ĠErit\":24372,\"ĠPerform\":24373,\"aston\":24374,\"Eric\":24375,\"Ġunh\":24376,\"IFF\":24377,\"950\":24378,\"ĠEngineer\":24379,\"ĠLands\":24380,\"Ġdubious\":24381,\"fy\":24382,\"ĠWI\":24383,\"ĠSv\":24384,\"ĠHendricks\":24385,\"ĠKod\":24386,\"Ġoutlining\":24387,\"ĠCorrespond\":24388,\"amus\":24389,\"worst\":24390,\"arter\":24391,\"coni\":24392,\"Ġhierarchy\":24393,\"ĠTHAT\":24394,\"Ġexce\":24395,\"Ġrailways\":24396,\"Ġmasked\":24397,\"lene\":24398,\"Ġoutset\":24399,\"Ġavalanche\":24400,\"Ġnicknamed\":24401,\"Ġ702\":24402,\"Lee\":24403,\"Ġ139\":24404,\"ĠSixth\":24405,\"365\":24406,\"nda\":24407,\"Ġaccountant\":24408,\"Ġobese\":24409,\"Ġgrape\":24410,\"Ġimpunity\":24411,\"ĠYorkers\":24412,\"Ġguardian\":24413,\"icity\":24414,\"Ġcentrist\":24415,\"Ġwaterways\":24416,\"ursed\":24417,\"Ġhopeless\":24418,\"header\":24419,\"Ġtack\":24420,\"Ġric\":24421,\"umn\":24422,\"Ġvalve\":24423,\"Ġtread\":24424,\"ĠCST\":24425,\"Ġhepatitis\":24426,\"ctor\":24427,\"ĠRED\":24428,\"Ġsolitary\":24429,\"NW\":24430,\"Ġceremonial\":24431,\"Ġfoe\":24432,\"Ġling\":24433,\"Jason\":24434,\"ĠLisbon\":24435,\"Ġ1955\":24436,\"ĠHeller\":24437,\"Ġkin\":24438,\"essen\":24439,\"Ġturbines\":24440,\"shi\":24441,\"Ġlodge\":24442,\"Ġveterinary\":24443,\"ĠBoll\":24444,\"ĠConfederation\":24445,\"ĠJournalists\":24446,\"Ġtug\":24447,\"ĠStarr\":24448,\"Ġpiles\":24449,\"Way\":24450,\"adel\":24451,\"orean\":24452,\"Ġoft\":24453,\"Ġshortcomings\":24454,\"ĠSheila\":24455,\"Ġbackbone\":24456,\"III\":24457,\"ĠDarwin\":24458,\"ĠTunis\":24459,\"Ġsuspicions\":24460,\"Ġdisagreements\":24461,\"Ġ247\":24462,\"illery\":24463,\"'\\\"\":24464,\"Ġsegregation\":24465,\"ohl\":24466,\"Ġinstincts\":24467,\"ĠPoo\":24468,\"nih\":24469,\"parency\":24470,\"uddy\":24471,\"esting\":24472,\"asses\":24473,\"ĠIntroduction\":24474,\"ĠSirius\":24475,\"Local\":24476,\"orous\":24477,\"Ġrehearsal\":24478,\"Ġdemol\":24479,\"Ġtraffickers\":24480,\"Ġupsetting\":24481,\"Ġheir\":24482,\"death\":24483,\"ĠMoments\":24484,\"Los\":24485,\"Ġatmospheric\":24486,\"aints\":24487,\"ĠDianne\":24488,\"Ġlikewise\":24489,\"ĠMing\":24490,\"auga\":24491,\"Ġfirsthand\":24492,\"Ġnarratives\":24493,\"ĠAstron\":24494,\"ĠExtreme\":24495,\"Ġhorns\":24496,\"ĠSana\":24497,\"Ġrecapt\":24498,\"ĠMist\":24499,\"ĠRandolph\":24500,\"connect\":24501,\"Ġindecent\":24502,\"Ġforty\":24503,\"Ġjihadists\":24504,\"azes\":24505,\"Ġdread\":24506,\"Ġgrapes\":24507,\"Ġremoves\":24508,\"Ġscreamed\":24509,\"ĠCrus\":24510,\"ikers\":24511,\"Ġsnapshot\":24512,\"ĠCalls\":24513,\"Cons\":24514,\"Ġlettuce\":24515,\"ĠPig\":24516,\"urable\":24517,\"jured\":24518,\"ILY\":24519,\"ĠJessie\":24520,\".).\":24521,\"Pay\":24522,\"Tra\":24523,\"----------------\":24524,\"ĠUnits\":24525,\"ĠPlayboy\":24526,\"Ġarthritis\":24527,\"Ġafforded\":24528,\"insk\":24529,\"ĠFake\":24530,\"ĠLies\":24531,\"ĠBaltic\":24532,\"oyal\":24533,\"ĠVest\":24534,\"Ġrusher\":24535,\"Ġincorporates\":24536,\"ĠMM\":24537,\"ĠDru\":24538,\"ĠWare\":24539,\"ĠSammy\":24540,\"ĠGob\":24541,\"ĠRuk\":24542,\"Ġ146\":24543,\"ĠCrowd\":24544,\"Ġduel\":24545,\"irts\":24546,\"Ġsourcing\":24547,\"hp\":24548,\"ĠJava\":24549,\"bred\":24550,\"ĠRefer\":24551,\"Ġuninsured\":24552,\"Ġslope\":24553,\"256\":24554,\"Ġregulating\":24555,\"Ġfundra\":24556,\"Ġinserted\":24557,\"ĠNickel\":24558,\"ĠConsumption\":24559,\"ĠRomo\":24560,\"Atlantic\":24561,\"Ġenclave\":24562,\"Ġpegged\":24563,\"Ġdirects\":24564,\"mbudsman\":24565,\"ĠDES\":24566,\"Ob\":24567,\"Ġlimbs\":24568,\"Ġbury\":24569,\"ILA\":24570,\"Ġstew\":24571,\"Ġbreeze\":24572,\"Ġabrupt\":24573,\"ĠGott\":24574,\"ĠClaude\":24575,\"Ġgenetically\":24576,\"Ġrigid\":24577,\"ĠDudley\":24578,\"ĠNer\":24579,\"registered\":24580,\"Ġentrenched\":24581,\"Ġextortion\":24582,\"ĠNurs\":24583,\"Ġcontingency\":24584,\"etter\":24585,\"Ġrejo\":24586,\"Ġprotagonist\":24587,\"Ġcounselling\":24588,\"ĠVit\":24589,\"aware\":24590,\"ĠMonsanto\":24591,\"GG\":24592,\"Ġincarcerated\":24593,\"Ġabduction\":24594,\"Ġreferencing\":24595,\"Germany\":24596,\"uates\":24597,\"reck\":24598,\"Ġtram\":24599,\"Ġchron\":24600,\"Ġmish\":24601,\"ĠVes\":24602,\"ĠTire\":24603,\"Ġvandal\":24604,\"ĠCrazy\":24605,\"ĠLifetime\":24606,\"ĠSpectrum\":24607,\"celer\":24608,\"Ġmotto\":24609,\"hang\":24610,\"Ġblade\":24611,\"gel\":24612,\"Ġbiography\":24613,\"Ġallegiance\":24614,\"hod\":24615,\"hap\":24616,\"ptic\":24617,\"acle\":24618,\"ĠBlade\":24619,\"ĠBoh\":24620,\"Ġ149\":24621,\"Ġchang\":24622,\"Ġcanned\":24623,\"Ġfacilitated\":24624,\"actor\":24625,\"iologist\":24626,\"Ġrebuilt\":24627,\"Ġawake\":24628,\"Ġmayoral\":24629,\"ĠEuros\":24630,\"Ġdangerously\":24631,\"MK\":24632,\"Ġreplica\":24633,\"Ġcoinc\":24634,\"blog\":24635,\"ĠEra\":24636,\"Ġrelinqu\":24637,\"quite\":24638,\"ondon\":24639,\"rosso\":24640,\"tun\":24641,\"Ġtouchscreen\":24642,\"Ġpops\":24643,\"ousing\":24644,\"efficient\":24645,\"Ġ148\":24646,\"Ġconced\":24647,\"although\":24648,\"Ġ1956\":24649,\"Ġmortar\":24650,\"ĠCave\":24651,\"ĠJung\":24652,\"urer\":24653,\"Ġillusion\":24654,\"ĠBerman\":24655,\"intend\":24656,\"Ġcoping\":24657,\"Dem\":24658,\"tion\":24659,\"estation\":24660,\"ĠSounds\":24661,\"Ġnavigating\":24662,\"Ġsperm\":24663,\"Ġreligions\":24664,\"Ġfol\":24665,\"Ġheroic\":24666,\"FD\":24667,\"Ġhesitant\":24668,\"asure\":24669,\"Ġredeem\":24670,\"Adam\":24671,\"Ġfireplace\":24672,\"vertis\":24673,\"ĠSung\":24674,\"290\":24675,\"iland\":24676,\"ĠUpdates\":24677,\"OTUS\":24678,\"ĠPTSD\":24679,\"Ġhelmets\":24680,\"\\\"?\":24681,\"Ġslashing\":24682,\"Ġscouts\":24683,\"Ġspelling\":24684,\"ĠInitial\":24685,\"draw\":24686,\"Ġchallengers\":24687,\"Ġsupremacists\":24688,\"Ġpilgrims\":24689,\"Ġasc\":24690,\"ĠFill\":24691,\"ĠPau\":24692,\"Ġjewel\":24693,\"ĠMalt\":24694,\"icip\":24695,\"Ġinhabitants\":24696,\"Ġmetre\":24697,\"ahar\":24698,\"Comp\":24699,\"atches\":24700,\"inv\":24701,\"Ġcyclist\":24702,\"ĠQC\":24703,\"Ġmanually\":24704,\"ĠAnchorage\":24705,\"Ġdiscarded\":24706,\"Ġconsolid\":24707,\"Ġnavig\":24708,\"ĠAnimals\":24709,\"ĠPole\":24710,\"esson\":24711,\"Ġ1954\":24712,\"Ġsorted\":24713,\"Ġmadness\":24714,\"ĠBrigade\":24715,\"ĠGenesis\":24716,\"Ġdismissing\":24717,\"ĠPanasonic\":24718,\"Ġdizz\":24719,\"ĠEducational\":24720,\"ĠKO\":24721,\"ĠPill\":24722,\"ĠGIF\":24723,\"Ġbol\":24724,\"Ġwards\":24725,\"Ġcontroversies\":24726,\"Chinese\":24727,\"Ġantics\":24728,\"Ġreliant\":24729,\"ĠMoff\":24730,\"Ġethanol\":24731,\"Ġtorch\":24732,\"rights\":24733,\"ĠHabit\":24734,\"arton\":24735,\"rera\":24736,\"ĠSasha\":24737,\"abella\":24738,\"Ġproliferation\":24739,\"Ġsincerely\":24740,\"communication\":24741,\"ĠNay\":24742,\"ĠChattanooga\":24743,\"ounces\":24744,\"ĠNXT\":24745,\"ĠEmir\":24746,\"Ġmanipulated\":24747,\"Ġharassing\":24748,\"wat\":24749,\"Ġbouts\":24750,\"Book\":24751,\"Ġhovering\":24752,\"ĠScan\":24753,\"ship\":24754,\"ĠAngola\":24755,\"ĠLC\":24756,\"Ġruins\":24757,\"Ġsexist\":24758,\"zar\":24759,\"Ġpledging\":24760,\"ober\":24761,\"Ġembold\":24762,\"Ġobjection\":24763,\"Ġboasting\":24764,\"MIN\":24765,\"Ġherbs\":24766,\"Ġgears\":24767,\"ĠIc\":24768,\"stre\":24769,\"him\":24770,\"Ġhomicides\":24771,\"cki\":24772,\"castle\":24773,\"counter\":24774,\"ĠCAS\":24775,\"ĠReasons\":24776,\"ĠDeclaration\":24777,\"Ġsimplify\":24778,\"Ġfared\":24779,\"Ġescort\":24780,\"Ġkidn\":24781,\"ĠHamm\":24782,\"Ġnailed\":24783,\"Ġaccommodations\":24784,\"Ġmodifications\":24785,\"rible\":24786,\"Ġwool\":24787,\"EDIT\":24788,\"2010\":24789,\"Ġauthentication\":24790,\"Ġgoat\":24791,\"hom\":24792,\"Ġfederally\":24793,\"ĠRath\":24794,\"Ġspiked\":24795,\"Ġmisrepresent\":24796,\"Ġavenue\":24797,\"Ġbroadcasts\":24798,\"ĠEstonia\":24799,\"ennes\":24800,\"ĠMare\":24801,\"ption\":24802,\"ĠKag\":24803,\"Ġcircumstance\":24804,\"orrow\":24805,\"isons\":24806,\"ĠCollabor\":24807,\"Ġstroll\":24808,\"ĠCPS\":24809,\"soft\":24810,\"iral\":24811,\"apo\":24812,\"usky\":24813,\"poke\":24814,\"Ġwoo\":24815,\"ĠElena\":24816,\"ĠLastly\":24817,\"Ġlinemen\":24818,\"Canadian\":24819,\"ĠAnyway\":24820,\"Ġsubstantive\":24821,\"ĠCurt\":24822,\"Ġard\":24823,\"ĠYosh\":24824,\"ĠBuchanan\":24825,\"Ġrevolving\":24826,\"Ġspecials\":24827,\"Ġshrine\":24828,\"Ġlumber\":24829,\"Ġorchestrated\":24830,\"kie\":24831,\"azy\":24832,\"Ġexpiration\":24833,\"ĠDaryl\":24834,\"ĠPatri\":24835,\"better\":24836,\"2020\":24837,\"ĠFav\":24838,\"ĠOP\":24839,\"OTT\":24840,\"Ġflush\":24841,\"ĠSikh\":24842,\"Ġecosystems\":24843,\"ĠBET\":24844,\"eared\":24845,\"audio\":24846,\"ĠFahrenheit\":24847,\"police\":24848,\"Ġincarceration\":24849,\"Ġerupt\":24850,\"ĠDamien\":24851,\"ĠHague\":24852,\"ulz\":24853,\"ĠAgents\":24854,\"ĠBanner\":24855,\"Ġconductor\":24856,\"ĠAjax\":24857,\"arson\":24858,\"Ġrests\":24859,\"Ġeurozone\":24860,\"Ġfelon\":24861,\"Ġcurator\":24862,\"morning\":24863,\"Ġevidenced\":24864,\"ĠNeh\":24865,\"Ġmattress\":24866,\"Ġtast\":24867,\"Ġfueling\":24868,\"ĠOccup\":24869,\"Ġbake\":24870,\"ĠZac\":24871,\"meaning\":24872,\"Ill\":24873,\"ĠHau\":24874,\"ĠLaden\":24875,\"Ġbald\":24876,\"Mary\":24877,\"oky\":24878,\"atri\":24879,\"Ġtracker\":24880,\"OTA\":24881,\"catching\":24882,\"ĠUnderground\":24883,\"ĠHuffPost\":24884,\"ĠAtkins\":24885,\"oglu\":24886,\"Ġauthorised\":24887,\"Ġroutines\":24888,\"ĠHof\":24889,\"veland\":24890,\"Ġlangu\":24891,\"Ġprot\":24892,\"ĠHyd\":24893,\"integ\":24894,\"Ġbravery\":24895,\"Ġviolin\":24896,\"Ġdelightful\":24897,\"Ġticks\":24898,\"iton\":24899,\"Ġreap\":24900,\"Ġoversized\":24901,\"ĠPitch\":24902,\"Ġprized\":24903,\"Ġfusion\":24904,\"fact\":24905,\"acting\":24906,\"Ġfullback\":24907,\"Ġpolite\":24908,\"Ġswear\":24909,\"Ġconfiscated\":24910,\"ĠStud\":24911,\"Ġfielded\":24912,\"rito\":24913,\"covered\":24914,\"financial\":24915,\"bill\":24916,\"HK\":24917,\"OTOS\":24918,\"loaded\":24919,\"Ġmarble\":24920,\"ĠDiplom\":24921,\".âĢĶ\":24922,\"Ġeats\":24923,\"Ġbackfield\":24924,\"Ġtimeframe\":24925,\"Ġvegetarian\":24926,\"Ġswaps\":24927,\"ĠMines\":24928,\"igor\":24929,\"ĠLenn\":24930,\"ĠDP\":24931,\"ordered\":24932,\"ĠShark\":24933,\"Ġquant\":24934,\"erence\":24935,\"Ġashes\":24936,\"ĠBuckley\":24937,\"ophobia\":24938,\"Ġwarranted\":24939,\"Rose\":24940,\"Ġunreasonable\":24941,\"ĠJav\":24942,\"Ġpalette\":24943,\"Ġjoints\":24944,\"Ġadvent\":24945,\"Ġnoteworthy\":24946,\"ĠNicol\":24947,\"ĠChristensen\":24948,\"Ġplummeted\":24949,\"ayers\":24950,\"Ġdefends\":24951,\"Ġcontended\":24952,\"ĠCongratulations\":24953,\"kish\":24954,\"ĠHannity\":24955,\"Ġgroundwater\":24956,\"ĠKramer\":24957,\"Ġerect\":24958,\"Ġappet\":24959,\"ĠKardash\":24960,\"Ġexacerbated\":24961,\"Ġexplanations\":24962,\"vious\":24963,\"eport\":24964,\"---\":24965,\"icism\":24966,\"ĠNatasha\":24967,\"ĠGeoffrey\":24968,\"estro\":24969,\"Article\":24970,\"Ġincidence\":24971,\"Ġprovoked\":24972,\"elf\":24973,\"Ġinsistence\":24974,\"ĠOUR\":24975,\"Ġfertilizer\":24976,\"Ġstickers\":24977,\"ĠGators\":24978,\"ĠLanding\":24979,\"ĠDON\":24980,\"sta\":24981,\"ĠRobbins\":24982,\"Ġpixels\":24983,\"ĠHoy\":24984,\"imated\":24985,\"ĠÃī\":24986,\"â\":24987,\"Ġsimpl\":24988,\"Other\":24989,\"245\":24990,\"Ġforcibly\":24991,\"'.\\\"\":24992,\"Ġsmashing\":24993,\"Ġmosquitoes\":24994,\"Ġpaints\":24995,\"Ġdebating\":24996,\"enty\":24997,\"ĠIB\":24998,\"leaf\":24999,\"ĠDah\":25000,\"Ġreferral\":25001,\"pired\":25002,\"Ġbrunch\":25003,\"gie\":25004,\"Ġvict\":25005,\"ribute\":25006,\"Ġbloggers\":25007,\"Ġgum\":25008,\"ĠAdmiral\":25009,\"France\":25010,\"ĠPK\":25011,\"ĠSaturn\":25012,\"Ġinflated\":25013,\"WAR\":25014,\"Ġscenic\":25015,\"usal\":25016,\"their\":25017,\"Ġcontends\":25018,\"Ġpathways\":25019,\"inis\":25020,\"Ġawarding\":25021,\"Ġmisled\":25022,\"Ġeternal\":25023,\"Ġexaminations\":25024,\"Ġpoker\":25025,\"Ġsafest\":25026,\"Ġchildcare\":25027,\"aday\":25028,\"Ġpreceding\":25029,\"ĠCollective\":25030,\"Ġrespectable\":25031,\"ographical\":25032,\"Ġoak\":25033,\"00000\":25034,\"ĠCorridor\":25035,\"oran\":25036,\"133\":25037,\"Ġmushrooms\":25038,\"gaard\":25039,\"ĠOmega\":25040,\"ĠNaturally\":25041,\"anim\":25042,\"Ġcaptains\":25043,\"Ġtang\":25044,\"Ġlobbyists\":25045,\"ĠSug\":25046,\"Ġsucc\":25047,\"249\":25048,\"ENG\":25049,\"134\":25050,\"Ġsolic\":25051,\"ĠAdded\":25052,\"ĠSuicide\":25053,\"ĠFULL\":25054,\"ĠStrauss\":25055,\"ĠDiesel\":25056,\"Ġtempting\":25057,\"acist\":25058,\"ĠDelivery\":25059,\"Ġquiz\":25060,\"ĠPARK\":25061,\"Ġcollisions\":25062,\"Ġrestrained\":25063,\"purpose\":25064,\"ĠChanges\":25065,\"Ġabsentee\":25066,\"Ġprobes\":25067,\"hib\":25068,\"Ġcul\":25069,\"Ġpetty\":25070,\"Ġnecess\":25071,\"Ġcues\":25072,\"OME\":25073,\"Ġinadvertently\":25074,\"urity\":25075,\"ĠStuff\":25076,\"FG\":25077,\"Ġwrestlers\":25078,\"Ġpaste\":25079,\"ĠRoku\":25080,\"Ġcardboard\":25081,\"aires\":25082,\"Ġvariables\":25083,\"ĠSaras\":25084,\"ĠFif\":25085,\"Ġinvests\":25086,\"ĠDiscover\":25087,\"ĠFix\":25088,\"Thomas\":25089,\"ĠLunch\":25090,\"lv\":25091,\"camera\":25092,\"Step\":25093,\"Ġresumes\":25094,\"ĠSacred\":25095,\"ĠShooting\":25096,\"Ġnoble\":25097,\"Ġslopes\":25098,\"Ġont\":25099,\"Ġtwists\":25100,\"Very\":25101,\"Ġbigotry\":25102,\"ĠTib\":25103,\"Ġmos\":25104,\"Ġwarrior\":25105,\"Ġbroadcasters\":25106,\"Ġubiquitous\":25107,\"ameda\":25108,\"Ġchess\":25109,\"Special\":25110,\"Ġconver\":25111,\"Ġdeleg\":25112,\"endant\":25113,\"Ġfoil\":25114,\"Ġlush\":25115,\"Ġtaxed\":25116,\"Mag\":25117,\"ahs\":25118,\"Ġtablespoons\":25119,\"scription\":25120,\"clamation\":25121,\"ĠCertain\":25122,\"ĠDiversity\":25123,\"Ġhairst\":25124,\"ĠBrewery\":25125,\"Ġshedding\":25126,\"Cla\":25127,\"Ġpenis\":25128,\"ĠMurder\":25129,\"Park\":25130,\"uner\":25131,\"iments\":25132,\"ĠOVER\":25133,\"hus\":25134,\"Ġtabloid\":25135,\"Chart\":25136,\"Ġvouchers\":25137,\"ĠCoord\":25138,\"Ġmethane\":25139,\"ĠFisheries\":25140,\"ĠKham\":25141,\"includes\":25142,\"ĠSuperman\":25143,\"ensed\":25144,\"isure\":25145,\"Amazon\":25146,\"Ġvacated\":25147,\"heet\":25148,\"Ġroast\":25149,\"Ġlegalize\":25150,\"ĠTut\":25151,\"Ġsignage\":25152,\"init\":25153,\"Ġthefts\":25154,\"202\":25155,\"Ġstatic\":25156,\"Ġchants\":25157,\"Bob\":25158,\"Ġdiscretionary\":25159,\"Ġendurance\":25160,\"Ġcollegiate\":25161,\"Ġcorridors\":25162,\"Ġslack\":25163,\"ĠLash\":25164,\"Az\":25165,\"Series\":25166,\"Ġnonpartisan\":25167,\"ĠMcGill\":25168,\"Ġuneven\":25169,\"ulsive\":25170,\"eu\":25171,\"Ġpil\":25172,\"Ġfisheries\":25173,\"Ġonslaught\":25174,\"fiction\":25175,\"holding\":25176,\"Ġcheated\":25177,\"Ġtraumat\":25178,\"lasting\":25179,\"Ġmultitude\":25180,\"ĠThr\":25181,\"ĠBreast\":25182,\"Ġ1600\":25183,\"ĠMatth\":25184,\"Ġdiminish\":25185,\"ĠFTC\":25186,\"Ġgram\":25187,\"ĠResident\":25188,\"Ġfading\":25189,\"Ġmarginalized\":25190,\"ĠLite\":25191,\"ĠCarlton\":25192,\"Ġerad\":25193,\"Welcome\":25194,\"ĠFaw\":25195,\"iddy\":25196,\"Ġparticip\":25197,\"Ġcz\":25198,\"Ġtexted\":25199,\"Ġsuites\":25200,\"ĠForever\":25201,\"Ġrendition\":25202,\"rait\":25203,\"ĠPrague\":25204,\"Ġsponsoring\":25205,\"Ġcompos\":25206,\"ĠBeacon\":25207,\"144\":25208,\"Ġpupil\":25209,\"Ġintricate\":25210,\"Ġathleticism\":25211,\"Ġoptimization\":25212,\"Ġloot\":25213,\"polit\":25214,\"ĠOtt\":25215,\"Whatever\":25216,\"uno\":25217,\"ĠConstable\":25218,\"esville\":25219,\"Ġlookout\":25220,\"ĠAircraft\":25221,\"Ġspo\":25222,\"Ġcorrobor\":25223,\"Ġhiatus\":25224,\"ĠKnowing\":25225,\"ĠHamp\":25226,\"Ġspe\":25227,\"Ġstoring\":25228,\"Ġshakes\":25229,\"uran\":25230,\"Ġsickness\":25231,\"Ġliber\":25232,\"ĠAdministrative\":25233,\"Ġpleasing\":25234,\"ĠEqual\":25235,\"ĠConversation\":25236,\"Ġalgae\":25237,\"Ġlobbyist\":25238,\"ĠHelena\":25239,\"ptions\":25240,\"Ġfaire\":25241,\"ĠGone\":25242,\"ĠWiggins\":25243,\"Robert\":25244,\"Ġlistens\":25245,\"ĠDaisy\":25246,\"Ġsticky\":25247,\"sale\":25248,\"ĠMarijuana\":25249,\"ĠSSD\":25250,\"ĠTool\":25251,\"once\":25252,\"ĠHarmon\":25253,\"mobile\":25254,\"Ġdetain\":25255,\"Money\":25256,\"Ġflawless\":25257,\"forced\":25258,\"Ġguru\":25259,\"Ġairspace\":25260,\"ĠArchie\":25261,\"ĠGender\":25262,\"ĠMeat\":25263,\"abilities\":25264,\"ĠBD\":25265,\"Open\":25266,\"Ġoutsider\":25267,\"issue\":25268,\"Ġlearns\":25269,\"natural\":25270,\"Ġvinegar\":25271,\"ĠSUB\":25272,\"ĠRecon\":25273,\"blers\":25274,\"Ġsniff\":25275,\"Ġsuppression\":25276,\"Ġsaf\":25277,\"urger\":25278,\"Ġbunker\":25279,\"asaki\":25280,\"ĠSpartan\":25281,\"ĠTok\":25282,\"Ġrav\":25283,\"Ġfoc\":25284,\"Sean\":25285,\"etric\":25286,\"Ġballpark\":25287,\"ĠHerb\":25288,\"ĠBM\":25289,\"ĠPublishing\":25290,\"Ġroadmap\":25291,\"pered\":25292,\"Ġpredator\":25293,\"ĠBlockchain\":25294,\"Ġvalidity\":25295,\"ĠGlou\":25296,\"ĠYamaha\":25297,\"Ġadop\":25298,\"Ġswamp\":25299,\"Ġcomplied\":25300,\"Ky\":25301,\"Greg\":25302,\"casts\":25303,\"john\":25304,\"ĠBosnia\":25305,\"Ġcinematic\":25306,\"ĠTavern\":25307,\"Ġfrustrations\":25308,\"eryl\":25309,\"Ġfairy\":25310,\"UNCH\":25311,\"ĠTus\":25312,\"Corp\":25313,\"ĠNug\":25314,\"closed\":25315,\"Ġexercised\":25316,\"urden\":25317,\"Ġdigitally\":25318,\"137\":25319,\"ĠVictims\":25320,\"Ġreluctance\":25321,\"ELL\":25322,\"ĠTribe\":25323,\"chall\":25324,\"Ġwhiskey\":25325,\"ogl\":25326,\"Ġmater\":25327,\"ĠBac\":25328,\"Ġapartheid\":25329,\"ĠMBA\":25330,\"mot\":25331,\"ĠIre\":25332,\"Â®,\":25333,\"ĠChic\":25334,\"Ġtimed\":25335,\"ĠDome\":25336,\"efer\":25337,\"Ġobserver\":25338,\"unky\":25339,\"ĠKant\":25340,\"Ġundrafted\":25341,\"Ġsimplicity\":25342,\"onds\":25343,\"Ġstoked\":25344,\"Ġ1949\":25345,\"Ġransomware\":25346,\"ĠPow\":25347,\"ĠAngelo\":25348,\"ĠAmbrose\":25349,\"adjusted\":25350,\"Guard\":25351,\"138\":25352,\"ĠKaplan\":25353,\"stri\":25354,\"Ġcries\":25355,\"NF\":25356,\"atro\":25357,\"Ġavocado\":25358,\"illian\":25359,\"Ġsculptures\":25360,\"Ġelevation\":25361,\"Ġinspires\":25362,\"Ġgenerals\":25363,\"arb\":25364,\"chell\":25365,\"ĠJournalism\":25366,\"ĠHybrid\":25367,\"ĠCaller\":25368,\"vec\":25369,\"Lu\":25370,\"Ġresemble\":25371,\"bys\":25372,\"erving\":25373,\"antz\":25374,\"Ġwiden\":25375,\"vised\":25376,\"Ev\":25377,\"Ġdiagn\":25378,\"ĠMakes\":25379,\"Ġcer\":25380,\"ĠPats\":25381,\"single\":25382,\"sche\":25383,\"struct\":25384,\"Ġdissolved\":25385,\"Ġtimeout\":25386,\"Ġenhancement\":25387,\"CF\":25388,\"Ġindust\":25389,\"ĠDed\":25390,\"ĠZo\":25391,\"CB\":25392,\"Ġpesticides\":25393,\"ĠRubin\":25394,\"George\":25395,\"opal\":25396,\"Ġmotel\":25397,\"critical\":25398,\"Ġcollapsing\":25399,\"ĠShal\":25400,\"tex\":25401,\"Ġcomplementary\":25402,\"Ġoust\":25403,\"ĠFlu\":25404,\"Ġexporting\":25405,\"Ġdifferential\":25406,\"north\":25407,\"ĠFG\":25408,\"Ġspoon\":25409,\"sha\":25410,\"Ġdismantle\":25411,\"elta\":25412,\"Ġjar\":25413,\"space\":25414,\"Smart\":25415,\"mere\":25416,\"Ð\":25417,\"ĠGillespie\":25418,\"Lo\":25419,\"ĠMead\":25420,\"capacity\":25421,\"ĠIssue\":25422,\"050\":25423,\"ĠVall\":25424,\"Ġdisgr\":25425,\"Ġmeme\":25426,\"Ġpard\":25427,\"Ġcompensated\":25428,\"ĠKet\":25429,\"major\":25430,\"ĠBren\":25431,\"Ġheed\":25432,\"131\":25433,\"Ġcm\":25434,\"Ġdazzling\":25435,\"ĠCheese\":25436,\"Ġmonumental\":25437,\"Ġyielding\":25438,\"Read\":25439,\"Ġgrinding\":25440,\"Ang\":25441,\"Ġdefiance\":25442,\"Ġintimidated\":25443,\"Ġ310\":25444,\"Ġoutsiders\":25445,\"houn\":25446,\"Ma\":25447,\"ĸ\":25448,\"ĠForget\":25449,\"ĠSans\":25450,\"Ġunfolding\":25451,\"ĠSap\":25452,\"ĠLak\":25453,\"Ġsectarian\":25454,\"ĠDaddy\":25455,\"oxy\":25456,\"hitting\":25457,\"Ġdetectors\":25458,\"ĠRee\":25459,\"Ġbroaden\":25460,\"Ġslaying\":25461,\"Ġsuspending\":25462,\"Ġinvestig\":25463,\"Tuesday\":25464,\"Ġantibiotic\":25465,\"ĠShiite\":25466,\"igi\":25467,\"ĠExternal\":25468,\"ĠPhotographer\":25469,\"Ġerratic\":25470,\"NJ\":25471,\"ĠDock\":25472,\"Ġoutweigh\":25473,\"rants\":25474,\"Ġlobster\":25475,\"Ġreactor\":25476,\"Ġunrealistic\":25477,\"ĠAudrey\":25478,\"ĠYor\":25479,\"Anyone\":25480,\"Ġfraught\":25481,\"Ðµ\":25482,\"ĠWester\":25483,\"fc\":25484,\"ĠDunham\":25485,\"ĠLug\":25486,\"allow\":25487,\"139\":25488,\"Ġparity\":25489,\"Ġhorizontal\":25490,\"ijuana\":25491,\"Ġcivilization\":25492,\"ĠGins\":25493,\"Ġsmokers\":25494,\"ĠDiabetes\":25495,\"Five\":25496,\"ĠDG\":25497,\"Ġunderscores\":25498,\"Ġelabor\":25499,\"ĠLub\":25500,\"ĠDevil\":25501,\"Ġ154\":25502,\"ĠGuarant\":25503,\"ĠPandora\":25504,\"Ġexcav\":25505,\"Ġaccuser\":25506,\"Ġrevolt\":25507,\"Ġinstructors\":25508,\"Ġire\":25509,\"ographic\":25510,\"ĠCLE\":25511,\"Ġexpedition\":25512,\"ould\":25513,\"Ġstriving\":25514,\"south\":25515,\"onis\":25516,\"ĠSwed\":25517,\"MY\":25518,\"ĠLevin\":25519,\"Ġcarp\":25520,\"ĠArchitects\":25521,\"Ġ{\":25522,\"Ġcovert\":25523,\"Ġcooled\":25524,\"ĠStaten\":25525,\"Ġspecializing\":25526,\"ĠHazel\":25527,\"Ġlen\":25528,\"ighty\":25529,\"Ġbrilliantly\":25530,\"Phil\":25531,\"Ġlament\":25532,\"Australia\":25533,\"203\":25534,\"Ġticking\":25535,\"Ġadjud\":25536,\"Ġroommate\":25537,\"ĠSheet\":25538,\"capital\":25539,\"167\":25540,\"Ġendeavor\":25541,\"Ġaver\":25542,\"Ġdues\":25543,\"ĠCycl\":25544,\"oried\":25545,\"Va\":25546,\"loading\":25547,\"Ġpremie\":25548,\"Ġregimes\":25549,\"ĠAly\":25550,\"Ġperennial\":25551,\"Ġconsoles\":25552,\"Ġironic\":25553,\"ichael\":25554,\"Ġvigorously\":25555,\"Ġtransmit\":25556,\"gary\":25557,\"eking\":25558,\"Ġjails\":25559,\"ĠEpiscopal\":25560,\"eddy\":25561,\"Ġidle\":25562,\"Ġsafeguards\":25563,\"Ġdwindling\":25564,\"NOR\":25565,\"torn\":25566,\"ĠEvangel\":25567,\"ĠPlastic\":25568,\"ĠTerm\":25569,\"Ġforwarded\":25570,\"avage\":25571,\"Ġrefrigerator\":25572,\"arna\":25573,\"ĠGuinness\":25574,\"ĠCandy\":25575,\"Ġbotched\":25576,\"seller\":25577,\"Ġpul\":25578,\"grades\":25579,\"oshenko\":25580,\"earth\":25581,\"nette\":25582,\"Ġtraps\":25583,\"Ġtarn\":25584,\"Ġmilitar\":25585,\"ĠAriel\":25586,\"Ġtubes\":25587,\"ulo\":25588,\"Water\":25589,\"edin\":25590,\"Ġmarvel\":25591,\"chenko\":25592,\"ĠElk\":25593,\"spect\":25594,\"coe\":25595,\"ĠIllustrated\":25596,\"Ġruthless\":25597,\"etermined\":25598,\"Ġdys\":25599,\"Ġbreaching\":25600,\"gee\":25601,\"Nick\":25602,\"Ġcruiser\":25603,\"Ġciv\":25604,\"Ġdou\":25605,\"Ġ;\":25606,\"deb\":25607,\"ĠAsheville\":25608,\"Ġbiting\":25609,\"Ġyo\":25610,\"Courtesy\":25611,\"Ġroses\":25612,\"ĠConsequently\":25613,\"Ġrevis\":25614,\"Ġconfinement\":25615,\"next\":25616,\"produced\":25617,\"Ġmoratorium\":25618,\"Ġkne\":25619,\"eties\":25620,\"Ġplethora\":25621,\"Ġceleb\":25622,\"FIN\":25623,\"Ġdepartures\":25624,\"ĠWynne\":25625,\"abilia\":25626,\"ĠCourts\":25627,\"olis\":25628,\"Ġcereal\":25629,\"Ġblended\":25630,\"333\":25631,\"ĠLun\":25632,\"Ġrepe\":25633,\"Ġmathematics\":25634,\"Ġpharmacies\":25635,\"Center\":25636,\"Ġwhist\":25637,\"pine\":25638,\"Ġperm\":25639,\"Ġcustomary\":25640,\"Ġhormones\":25641,\"Ġcleansing\":25642,\"Ġconfidentiality\":25643,\"Ġmascot\":25644,\"Ġslippery\":25645,\"Ġmediation\":25646,\"Ġpodcasts\":25647,\"Ġcoating\":25648,\"Ġconveyed\":25649,\"Ġgir\":25650,\"ĠNurse\":25651,\"DM\":25652,\"Ġlured\":25653,\"orted\":25654,\"Ġolig\":25655,\"ritz\":25656,\"ĠINF\":25657,\"Ġtirelessly\":25658,\"Ġdoorstep\":25659,\"Ġtomb\":25660,\"Ġwithholding\":25661,\"irling\":25662,\"Ġhog\":25663,\"Ġ156\":25664,\"Ġgau\":25665,\"chem\":25666,\"raid\":25667,\"Ġtrolls\":25668,\"Ġ182\":25669,\"ĠColumb\":25670,\"Ġtissues\":25671,\"Ġnaive\":25672,\"Ġlect\":25673,\"Central\":25674,\"Sign\":25675,\"168\":25676,\"Ġbribe\":25677,\"ĠDoll\":25678,\"ĠTripoli\":25679,\"Ġfunk\":25680,\"Ġplaza\":25681,\"Ġmechanic\":25682,\"mem\":25683,\"Ġmonkey\":25684,\"grid\":25685,\"Ġtainted\":25686,\"ĠNicaragua\":25687,\"pelling\":25688,\"ĠXia\":25689,\"ammers\":25690,\"Ġorth\":25691,\"ICAN\":25692,\"Ġrant\":25693,\"Ġdiary\":25694,\"ĠHarrington\":25695,\"Ġimply\":25696,\"Qaeda\":25697,\"Ġworsen\":25698,\"Ġcrafting\":25699,\"ĠShir\":25700,\"Ġcoincided\":25701,\"Ġsnatched\":25702,\"ileen\":25703,\"sei\":25704,\"Ġsurgeons\":25705,\"directed\":25706,\"Ġcompulsory\":25707,\"Ġnowadays\":25708,\"ĠLI\":25709,\"ĠRebel\":25710,\"Ġlions\":25711,\"ĠJR\":25712,\"scar\":25713,\"ĠRespons\":25714,\"Ġscroll\":25715,\"ĠErd\":25716,\"iety\":25717,\"\\\";\":25718,\"ĠBone\":25719,\"ĠRumble\":25720,\"ĠKS\":25721,\"ĠLaur\":25722,\"kell\":25723,\"ĠBirds\":25724,\"agic\":25725,\"Ġsimmer\":25726,\"Ġrunaway\":25727,\"Ġ162\":25728,\"auna\":25729,\"Ġdialog\":25730,\"Ġlouder\":25731,\"esque\":25732,\"RR\":25733,\"Ġbloss\":25734,\"Ġcaliber\":25735,\"nery\":25736,\"Ġhauled\":25737,\"Ġbacterial\":25738,\"ĠVanity\":25739,\"ĠPrograms\":25740,\"omew\":25741,\"ĠMama\":25742,\"Ġarr\":25743,\"Ġdod\":25744,\"ĠJarvis\":25745,\"ĠFIRST\":25746,\"Ġinjections\":25747,\"ĠBallard\":25748,\"Ġmedically\":25749,\"angan\":25750,\"ĠNewfoundland\":25751,\"Ġfracking\":25752,\"Ġbast\":25753,\"outing\":25754,\"Ġmercury\":25755,\"Ġwatershed\":25756,\"ĠAmateur\":25757,\"Ġ153\":25758,\"escal\":25759,\"Ġpainter\":25760,\"creat\":25761,\"Ġperceive\":25762,\"Ġgent\":25763,\"attacks\":25764,\"worked\":25765,\"Ġimporting\":25766,\"Indian\":25767,\"Ġconvict\":25768,\"clad\":25769,\"Ġbudding\":25770,\"Ġambient\":25771,\"ĠWitness\":25772,\"letes\":25773,\"Ġbuffet\":25774,\"Ġneedles\":25775,\"Ġcoding\":25776,\"Ġchoke\":25777,\"Ġcorrespondence\":25778,\"Ġgods\":25779,\"Ġdances\":25780,\"Ġsteadfast\":25781,\"cert\":25782,\"Ġroaming\":25783,\"between\":25784,\"weak\":25785,\"Jer\":25786,\"jandro\":25787,\"Ġdiscouraged\":25788,\"Ġfruition\":25789,\"ĠØ\":25790,\"ĠKop\":25791,\"ULL\":25792,\"efe\":25793,\"imble\":25794,\"obb\":25795,\"ulla\":25796,\"Ġaccredited\":25797,\"Ġlectures\":25798,\"bil\":25799,\"why\":25800,\"Ġgreeting\":25801,\"ĠBoost\":25802,\"Ġmailed\":25803,\"Ġtroop\":25804,\"Ġfrig\":25805,\"Ġrese\":25806,\"Ġscratched\":25807,\"Stars\":25808,\"ĠRailroad\":25809,\"ĠIdol\":25810,\"Ġsuccumbed\":25811,\"ĠWeeks\":25812,\"ffe\":25813,\"Ġjihadist\":25814,\"ITION\":25815,\"Ġthreads\":25816,\"ĠGenerally\":25817,\"Ġmedieval\":25818,\"Ġquotas\":25819,\"ĠFerry\":25820,\"rique\":25821,\"Ġprod\":25822,\"ĠEduc\":25823,\"rive\":25824,\"Ġensued\":25825,\"Cy\":25826,\"Ġinfring\":25827,\"Ġprank\":25828,\"Ġfrontline\":25829,\"Ġcompletes\":25830,\"upe\":25831,\"Ġmanageable\":25832,\"Ġpoems\":25833,\"otten\":25834,\"igne\":25835,\"threat\":25836,\"ĠDri\":25837,\"ĠLINK\":25838,\"Calif\":25839,\"ĠDos\":25840,\"ulent\":25841,\"Ġaids\":25842,\"Ġslips\":25843,\"umped\":25844,\"Ġstyled\":25845,\"Ġdisproportionately\":25846,\"ĠDish\":25847,\"ĠUncle\":25848,\"andel\":25849,\"Ġrecharge\":25850,\"rators\":25851,\"ĠSPR\":25852,\"Ġguarded\":25853,\"ĠGreatest\":25854,\"ĠSkills\":25855,\"ĠNob\":25856,\"ĠDesk\":25857,\"ĠCros\":25858,\"Ġwrit\":25859,\"Ġquery\":25860,\"ORTS\":25861,\"Ġbundled\":25862,\"Ġgib\":25863,\"Ġeth\":25864,\"iesta\":25865,\"Ġevade\":25866,\"dict\":25867,\"straight\":25868,\"Met\":25869,\"present\":25870,\"Ġdiff\":25871,\"Ġdere\":25872,\"ĠSpl\":25873,\"Ġrepr\":25874,\"ĠBeard\":25875,\"Ġvain\":25876,\"Ġappointing\":25877,\"ĠVisual\":25878,\"caps\":25879,\"gado\":25880,\"ĠRican\":25881,\"ĠPose\":25882,\"endor\":25883,\"Ġ222\":25884,\"ĠLear\":25885,\"Ġconstructing\":25886,\"Dan\":25887,\"ĠSpears\":25888,\"ĠTherapy\":25889,\"pta\":25890,\"Ġrehabilit\":25891,\"Ġrisked\":25892,\"ĠGuer\":25893,\"HF\":25894,\"Ġ301\":25895,\"Ġliking\":25896,\"Ġmodular\":25897,\"eree\":25898,\"ĠMAT\":25899,\"ĠHomeless\":25900,\"Ġstove\":25901,\"erd\":25902,\"hash\":25903,\"ĠAchilles\":25904,\"ĠBeta\":25905,\"Ġincl\":25906,\"Ġgunned\":25907,\"ĠCrab\":25908,\"ĠMara\":25909,\"Ġinvaded\":25910,\"ulatory\":25911,\"ATA\":25912,\"angering\":25913,\"onso\":25914,\"Ġallocate\":25915,\"Ġgarment\":25916,\"itudes\":25917,\"ĠHuang\":25918,\"Ġstaples\":25919,\"ĠAlban\":25920,\"Ġtrough\":25921,\"Ġupright\":25922,\"tie\":25923,\"Ġexploits\":25924,\"ĠVaughan\":25925,\"ĠDarrell\":25926,\"Ġassortment\":25927,\"ĠChill\":25928,\"Ġlearners\":25929,\"aqu\":25930,\"Ġexplode\":25931,\"ĠChong\":25932,\"bt\":25933,\"opl\":25934,\"Ġaltern\":25935,\"Ġ151\":25936,\"fur\":25937,\"ULT\":25938,\"HOU\":25939,\"ĠMemory\":25940,\"Ġboosts\":25941,\"ynes\":25942,\"priv\":25943,\"Ġtimeless\":25944,\"Ġcurtail\":25945,\"ĠCary\":25946,\"ĠHud\":25947,\"Ġexclus\":25948,\"Ġ275\":25949,\"Ġfry\":25950,\"ĠVera\":25951,\"Ġdefied\":25952,\"ĠDust\":25953,\"Ġenvision\":25954,\"ĠPhilipp\":25955,\"Ġenhancements\":25956,\"ĠLIB\":25957,\"ggy\":25958,\"ĠAzure\":25959,\"esis\":25960,\"Ġcharismatic\":25961,\"Ġcoincide\":25962,\"inged\":25963,\"ĠChoose\":25964,\"Ġsizeable\":25965,\"136\":25966,\"Ġpronounce\":25967,\"ĠPositive\":25968,\"Ġideally\":25969,\"Ġechoes\":25970,\"Ġcottage\":25971,\"Ġencrypted\":25972,\"Prime\":25973,\"Ġá\":25974,\"Ġflashes\":25975,\"Group\":25976,\"Ġ501\":25977,\"heat\":25978,\"atility\":25979,\"ĠTesting\":25980,\"pex\":25981,\"WT\":25982,\"154\":25983,\"annah\":25984,\"Ġcompromising\":25985,\"Ġinactive\":25986,\"Ġdisparity\":25987,\"Ġgruesome\":25988,\"ĠFeather\":25989,\"ĠMandal\":25990,\"Ġthereof\":25991,\"ĠProducer\":25992,\"Ġprofiling\":25993,\"Ġlogistical\":25994,\"Ġcornerstone\":25995,\"ĠClaudia\":25996,\"Congress\":25997,\"ĠDill\":25998,\"ophone\":25999,\"Ġcameo\":26000,\"ĠCutler\":26001,\"Ġcraz\":26002,\"throw\":26003,\"ĠKasich\":26004,\"Ġexploiting\":26005,\"ĠSeas\":26006,\"agles\":26007,\"ĠGeological\":26008,\"ĠStub\":26009,\"ĠUps\":26010,\"MER\":26011,\"Ġmem\":26012,\"itution\":26013,\"Ġunderstandably\":26014,\"Ġcontractual\":26015,\"warming\":26016,\"qi\":26017,\"Sky\":26018,\"whelming\":26019,\"Ġcurse\":26020,\"ĠAren\":26021,\"Ġ265\":26022,\"ĠGree\":26023,\"Ġpresiding\":26024,\"Works\":26025,\"stones\":26026,\"Ġappalling\":26027,\"plex\":26028,\"dj\":26029,\"aunting\":26030,\"Ġimag\":26031,\"Ġsexism\":26032,\"ĠVert\":26033,\"ĠRag\":26034,\"ĠBliss\":26035,\"posium\":26036,\"div\":26037,\"Ġexperimenting\":26038,\"Ass\":26039,\"Lago\":26040,\"worthiness\":26041,\"ĠBerk\":26042,\"ĠDisneyland\":26043,\"Ġexaggerated\":26044,\"iliation\":26045,\"ĠFP\":26046,\"Ġprincipals\":26047,\"Miami\":26048,\"ropri\":26049,\"PLE\":26050,\"iona\":26051,\"ĠPokemon\":26052,\"apse\":26053,\"Ġbubbles\":26054,\"INC\":26055,\"ĠCaps\":26056,\"ĠBrowne\":26057,\"sing\":26058,\"ĠcafÃ©\":26059,\"Ġceilings\":26060,\"frame\":26061,\"ĠIrwin\":26062,\"ATS\":26063,\"dated\":26064,\"Ġprotester\":26065,\"Ġtaps\":26066,\"ĠOslo\":26067,\"Ù\":26068,\"Ġconcentrations\":26069,\"Ġdistributions\":26070,\"Ġglucose\":26071,\"ĠRudolph\":26072,\"Ġtowels\":26073,\"Ġâĸº\":26074,\"Ġneighbourhoods\":26075,\"Ġinduction\":26076,\"Ġglaring\":26077,\"Ġannexation\":26078,\"Ġunsustainable\":26079,\"ĠTend\":26080,\"Ġthumbs\":26081,\"iegel\":26082,\"cript\":26083,\"gor\":26084,\"closure\":26085,\"thought\":26086,\"Ġpaddle\":26087,\"Ġemulate\":26088,\"Ġdiameter\":26089,\"Ġtailor\":26090,\"ĠCorpor\":26091,\"icable\":26092,\"ĠPrin\":26093,\"Ġadminister\":26094,\"ĠJudd\":26095,\"ĠColleg\":26096,\"aund\":26097,\"ĠPond\":26098,\"ĠNOTE\":26099,\"Ġcombating\":26100,\"Ġinvention\":26101,\"ĠOculus\":26102,\"ĠRepl\":26103,\"iscal\":26104,\"Ġtrilogy\":26105,\"anian\":26106,\"ATT\":26107,\"ĠCoke\":26108,\"DL\":26109,\"ĠLup\":26110,\"living\":26111,\"Ġadvertise\":26112,\"ĠConnie\":26113,\"amping\":26114,\"Ġsung\":26115,\"ORY\":26116,\"ĠTet\":26117,\"Ġsplits\":26118,\"Ġreconnect\":26119,\"Ġlou\":26120,\"mut\":26121,\"ulator\":26122,\"Ġstrap\":26123,\"Ġswallow\":26124,\"rote\":26125,\"Ġexec\":26126,\"ffen\":26127,\"ĠCombine\":26128,\"ĠTreat\":26129,\"Ġsorrow\":26130,\"ĠNotably\":26131,\"ĠSever\":26132,\"rette\":26133,\"Ġwherein\":26134,\"Ġtransitioning\":26135,\"Ġtrout\":26136,\"Ġcockpit\":26137,\"Ġcrawl\":26138,\"Ġferv\":26139,\"Ġliquids\":26140,\"Ġtsp\":26141,\"atell\":26142,\"Ġmeasles\":26143,\"Ġjug\":26144,\"Ac\":26145,\"ĠKD\":26146,\"ĠMoose\":26147,\"Ġvans\":26148,\"chain\":26149,\"ĠPapua\":26150,\"plet\":26151,\"Wednesday\":26152,\"lynn\":26153,\"chery\":26154,\"budget\":26155,\"Tony\":26156,\"ĠBacon\":26157,\"Ġstirred\":26158,\"ĠSpecialist\":26159,\"Ġcounterfeit\":26160,\"Ð°\":26161,\"Ġdifferentiate\":26162,\"Ġmuscular\":26163,\"ĠTheodore\":26164,\"Ġlooms\":26165,\"ĠXX\":26166,\"ottage\":26167,\"Ġbenches\":26168,\"ĠMunicip\":26169,\"Po\":26170,\"ĠHeck\":26171,\"Ġscars\":26172,\"ĠNim\":26173,\"ÙĬ\":26174,\"ĠIngredients\":26175,\"Ġecological\":26176,\"ĠAWS\":26177,\"Ġdispose\":26178,\"Ġmattered\":26179,\"Ġ720\":26180,\"Ġpatriotism\":26181,\"ĠGrind\":26182,\"Ġcurved\":26183,\"opia\":26184,\"ĠLiqu\":26185,\"Ġevangelical\":26186,\"tto\":26187,\"ĠMaterial\":26188,\"ĠShowtime\":26189,\"ĠBS\":26190,\"Ġcheckpoints\":26191,\"Ġcrippling\":26192,\"ĠBalance\":26193,\"stress\":26194,\"bearing\":26195,\"Ġ216\":26196,\"ĠGuards\":26197,\"Ġlinebackers\":26198,\"Ġoffending\":26199,\"Ġsands\":26200,\"umbnail\":26201,\"atorial\":26202,\"Ġliberties\":26203,\"ĠGW\":26204,\"ĠPulitzer\":26205,\"ĠAlvin\":26206,\"ĠFAC\":26207,\"ĠStrategies\":26208,\"Ġreiter\":26209,\"ĠRestaur\":26210,\"ĠLithuania\":26211,\"ĠSwanson\":26212,\"terror\":26213,\"ĠMaurit\":26214,\"Ġparadise\":26215,\"zzle\":26216,\"owment\":26217,\"ĠWP\":26218,\"Ġsodium\":26219,\"Ġfuturistic\":26220,\"Ġdots\":26221,\"Anthony\":26222,\"Though\":26223,\"Ġstripes\":26224,\"Ġorig\":26225,\"ultz\":26226,\"Ġ340\":26227,\"KK\":26228,\"umer\":26229,\"ivery\":26230,\"Ġplacebo\":26231,\"Ġdemocrat\":26232,\"Ġsubmerged\":26233,\"ĠHidden\":26234,\"pieces\":26235,\"Ġasteroid\":26236,\"ĠGraphic\":26237,\"Ġadvert\":26238,\"sil\":26239,\"Ġdreaming\":26240,\"Ġnationality\":26241,\"Ġfostering\":26242,\"daughter\":26243,\"ĠSavings\":26244,\"Ġmischief\":26245,\"ĠClair\":26246,\"ĠBundy\":26247,\"Ġblatant\":26248,\"Ġtabs\":26249,\"qa\":26250,\"severe\":26251,\"attered\":26252,\"Ġgreed\":26253,\"Ġresembles\":26254,\"Ġnominal\":26255,\"Ġineligible\":26256,\"wealth\":26257,\"fax\":26258,\"payers\":26259,\"Ġdisplacement\":26260,\"itute\":26261,\"Ġunpleasant\":26262,\"ĠPom\":26263,\"lif\":26264,\"edo\":26265,\"ĠNP\":26266,\"Inter\":26267,\"Ġcohort\":26268,\"ĠStacy\":26269,\"ĠDai\":26270,\"Ġhistories\":26271,\"alin\":26272,\"273\":26273,\"Ġdram\":26274,\"ĠKand\":26275,\"Ġexpectancy\":26276,\"ansson\":26277,\"Ġlimbo\":26278,\"ĠPolar\":26279,\"Ġdivine\":26280,\"oused\":26281,\"Ġshel\":26282,\"ĠProblem\":26283,\"achment\":26284,\"Ġâĸł\":26285,\"shoot\":26286,\"antam\":26287,\"ĠHerz\":26288,\"Ġ157\":26289,\"Ġpreventive\":26290,\"keye\":26291,\"Sing\":26292,\"Ġcharacteristic\":26293,\"Ġcasually\":26294,\"ĠTaiwanese\":26295,\"md\":26296,\"ĠHubbard\":26297,\"imon\":26298,\"Ġsect\":26299,\"148\":26300,\"Ġmartyr\":26301,\"stud\":26302,\"Ġcongrat\":26303,\"ĠSWAT\":26304,\"ĠTheory\":26305,\"INAL\":26306,\"opping\":26307,\"ply\":26308,\"ĠKindle\":26309,\"uu\":26310,\"ĠLith\":26311,\"kaya\":26312,\"ĠActivity\":26313,\"uously\":26314,\"ĠJeb\":26315,\"tell\":26316,\"ĠSpin\":26317,\"ĠExplorer\":26318,\"Ġfolded\":26319,\"ĠCanterbury\":26320,\"ĠStur\":26321,\"Ġminiature\":26322,\"Ġmultif\":26323,\"ĠPressure\":26324,\"angling\":26325,\"ĠOverse\":26326,\"Ġresides\":26327,\"Ġimpressions\":26328,\"Ġauthored\":26329,\"265\":26330,\"Ġallergies\":26331,\"143\":26332,\"ĠJi\":26333,\"Ġsticker\":26334,\"ĠAccord\":26335,\"Ġcaste\":26336,\"Ġseparates\":26337,\"ĠFein\":26338,\"Daily\":26339,\"179\":26340,\"ĠScores\":26341,\"ĠAuction\":26342,\"hea\":26343,\"Ġdisclosing\":26344,\"ĠTacoma\":26345,\"Ġverse\":26346,\"ĠBeg\":26347,\"Ġfabrics\":26348,\"aez\":26349,\"Ġattachment\":26350,\"isy\":26351,\"Christ\":26352,\"Ġaddictive\":26353,\"Ġvir\":26354,\"Week\":26355,\"ĠPlum\":26356,\"croft\":26357,\"itivity\":26358,\"ĠExhibition\":26359,\"Ġbruised\":26360,\"Ġmimic\":26361,\"rers\":26362,\"Ġanal\":26363,\"Ġunintended\":26364,\"Ġpall\":26365,\"atts\":26366,\"ĠWarn\":26367,\"Ġslows\":26368,\"WH\":26369,\"Ġembro\":26370,\"nec\":26371,\"Ġ168\":26372,\"285\":26373,\"ologic\":26374,\"Ġhob\":26375,\"ĠPeel\":26376,\"Mill\":26377,\"eps\":26378,\"Ġrobbers\":26379,\"ĠDahl\":26380,\"semble\":26381,\"omics\":26382,\"toe\":26383,\"ĠLoch\":26384,\"Ġreproduction\":26385,\"ĠCullen\":26386,\"Ġimplants\":26387,\"Ġwow\":26388,\"ĠSTATE\":26389,\"vt\":26390,\"Ġdepleted\":26391,\"Ġbreweries\":26392,\"Ġhateful\":26393,\"Ġgast\":26394,\"Ġhollow\":26395,\"Ġradically\":26396,\"ographed\":26397,\"ĠFog\":26398,\"onian\":26399,\"ĠSequ\":26400,\"Ġdisrespectful\":26401,\"Dis\":26402,\"ĠExper\":26403,\"pron\":26404,\"ĠAmelia\":26405,\"ĠSage\":26406,\"bath\":26407,\"Ġtransformative\":26408,\"Ġtremendously\":26409,\"Ġpillow\":26410,\"ĠNormal\":26411,\"Cont\":26412,\"ĠMedic\":26413,\"educated\":26414,\"Ġredesigned\":26415,\"Ġkneeling\":26416,\"Ġinh\":26417,\"Ġroofs\":26418,\"Ġhandmade\":26419,\"Ġprotracted\":26420,\"ĠIsn\":26421,\"ĠCapacity\":26422,\"Ġsquash\":26423,\"ĠVega\":26424,\"Ġfats\":26425,\"ĠCertified\":26426,\"ointed\":26427,\"Ġpricey\":26428,\"ĠBasil\":26429,\"Ġfreezer\":26430,\"Ġscent\":26431,\"Ġpizz\":26432,\"ĠArd\":26433,\"Ġdistractions\":26434,\"Ġviolently\":26435,\"ĠHess\":26436,\"Ġfunc\":26437,\"Ġundert\":26438,\"Ġrejuven\":26439,\"Ġdisbelief\":26440,\"cluded\":26441,\"named\":26442,\"ĠFailure\":26443,\"kus\":26444,\"Ġhostages\":26445,\"ĠSahara\":26446,\"Ġ1944\":26447,\"Leary\":26448,\"ĠPrel\":26449,\"enza\":26450,\"ĠAlly\":26451,\"ĠKak\":26452,\"Ġcounselors\":26453,\"ĠGale\":26454,\"ĠHok\":26455,\"ĠSold\":26456,\"Ġhacker\":26457,\"Ġhun\":26458,\"Ġbung\":26459,\"Ġdeclares\":26460,\"Ġinfringement\":26461,\"OOD\":26462,\"Ġdoub\":26463,\"jam\":26464,\"Ġallergy\":26465,\"ĠShipping\":26466,\"Ġmedic\":26467,\"Ġaccommod\":26468,\"Ġdocumenting\":26469,\"Ġcompanions\":26470,\"Ġmodelling\":26471,\"Ġcarriage\":26472,\"ĠCherokee\":26473,\"Ġtresp\":26474,\"Ġtaxable\":26475,\"ĠActivities\":26476,\"ĠCrane\":26477,\"bots\":26478,\"ĠRusso\":26479,\"Ġstocked\":26480,\"ervation\":26481,\"Ġcoffin\":26482,\"aign\":26483,\"guards\":26484,\"Ġonwards\":26485,\"Ġfrank\":26486,\".*\":26487,\"unic\":26488,\"Ġcens\":26489,\"enic\":26490,\"ruit\":26491,\"rained\":26492,\"Ġadapting\":26493,\"aments\":26494,\"Ġstagnant\":26495,\"azaar\":26496,\"ĠHarlem\":26497,\"Ġ158\":26498,\"ysis\":26499,\"Ġbraking\":26500,\"Ġdipping\":26501,\"Ġclan\":26502,\"ĠShu\":26503,\"Ġprops\":26504,\"qualified\":26505,\"Ġmistakenly\":26506,\"ĠStalin\":26507,\"Ġaddicts\":26508,\"ĠCALL\":26509,\"ropolis\":26510,\"aten\":26511,\"pec\":26512,\"ĠDro\":26513,\"ĠFellowship\":26514,\"ĠSupporting\":26515,\"loc\":26516,\"uben\":26517,\"499\":26518,\"Bro\":26519,\"Ġpots\":26520,\"Ġchunks\":26521,\"wr\":26522,\"ĠColonial\":26523,\"ĠArchitecture\":26524,\"Ġconstrained\":26525,\"Ġenvelop\":26526,\"ĠIronically\":26527,\"aban\":26528,\"Ġapparatus\":26529,\"Ġcue\":26530,\"Ġborne\":26531,\"ĠRoz\":26532,\"ilton\":26533,\"Ġtheoretical\":26534,\"ĠWatching\":26535,\"Ġfuck\":26536,\"ĠSilk\":26537,\"ĠSTE\":26538,\"bler\":26539,\"ĠPOST\":26540,\"ĠUpton\":26541,\"Ġsummons\":26542,\"ĠCum\":26543,\"ĠKL\":26544,\"Ġrelaxation\":26545,\"ĠDuff\":26546,\"Ġincumb\":26547,\"ĠRedd\":26548,\"Ġstature\":26549,\"Ġcanv\":26550,\"added\":26551,\"Ġremedies\":26552,\"ĠISO\":26553,\"ĠDecker\":26554,\"Ġafloat\":26555,\"Ġstartling\":26556,\"ĠBethlehem\":26557,\"Ġrealizes\":26558,\"find\":26559,\"ĠAra\":26560,\"Ġphased\":26561,\"arov\":26562,\"Ġhalting\":26563,\"ĠWindow\":26564,\"Ġdentist\":26565,\"Ġtumble\":26566,\"Ġvalidation\":26567,\"Ġcarve\":26568,\"ĠIPS\":26569,\"Ġirrit\":26570,\"ĠEssential\":26571,\"Ġfluids\":26572,\"rons\":26573,\"Ġimplant\":26574,\"Ġnuisance\":26575,\"ĠShelley\":26576,\"ĠGemini\":26577,\"Ġpharmac\":26578,\"iction\":26579,\"Ġtaped\":26580,\"ĠGovernments\":26581,\"ruly\":26582,\"Ġscant\":26583,\"Ġprominently\":26584,\"Ġreim\":26585,\"unning\":26586,\"arted\":26587,\"ĠMatters\":26588,\"Ġ1918\":26589,\"ĠPros\":26590,\"atel\":26591,\"ĠBattalion\":26592,\"onduct\":26593,\"talk\":26594,\"ĠTinder\":26595,\"ĠInstant\":26596,\"ĠKern\":26597,\"Ġbuckets\":26598,\"ĠGroups\":26599,\"Ġmetaphor\":26600,\"cloud\":26601,\"ĠString\":26602,\"Ohio\":26603,\"Ġcaffeine\":26604,\"Old\":26605,\"Ġdefinite\":26606,\"ĠNikola\":26607,\"ĠLords\":26608,\"icol\":26609,\")?\":26610,\"Ġenjoyment\":26611,\"Ġfamine\":26612,\"Ġdefinitions\":26613,\"ĠJem\":26614,\"Check\":26615,\"Ġaiding\":26616,\"ĠMÃ©\":26617,\"Ġrenewables\":26618,\"Ġsightings\":26619,\"footed\":26620,\"Box\":26621,\"Ġgoats\":26622,\"Ġshack\":26623,\"AX\":26624,\"ĠMonk\":26625,\"ĠGraduate\":26626,\"Ġmeats\":26627,\"handle\":26628,\"147\":26629,\"rys\":26630,\"Ġunsub\":26631,\"Pont\":26632,\"uble\":26633,\"440\":26634,\"Ġeyel\":26635,\"thro\":26636,\"Ġcreep\":26637,\"^^^^\":26638,\"Ġpopcorn\":26639,\"Ġcompression\":26640,\"sal\":26641,\"ouf\":26642,\"Ġrepairing\":26643,\"Think\":26644,\"Ġdoubtful\":26645,\"ĠLooks\":26646,\"Ġtaller\":26647,\"Ġsul\":26648,\"sf\":26649,\"give\":26650,\"ĠGau\":26651,\"Ġrevered\":26652,\"EMBER\":26653,\"Ġsloppy\":26654,\"ersen\":26655,\"Ġvitamins\":26656,\"ĠImprovement\":26657,\"Ġprogresses\":26658,\"Ġdiploma\":26659,\"semb\":26660,\"ustain\":26661,\"Ġchant\":26662,\"Ġbumped\":26663,\"Ġsabotage\":26664,\"nant\":26665,\"Ġrabbit\":26666,\"Ġdividing\":26667,\"ĠDefender\":26668,\"Ġlik\":26669,\"Ġirrespective\":26670,\"cade\":26671,\"ĠSter\":26672,\"touch\":26673,\"EMA\":26674,\"Ġparted\":26675,\"ĠBAR\":26676,\"hung\":26677,\"Ġannoyed\":26678,\"Ġhinder\":26679,\"Ġexamines\":26680,\"oan\":26681,\"ĠBoe\":26682,\"Ġaggreg\":26683,\"ĠChu\":26684,\"ĠUCS\":26685,\"IGHTS\":26686,\"pez\":26687,\"ĠUNESCO\":26688,\"Ġwindshield\":26689,\"Martin\":26690,\"Ġwithhold\":26691,\"does\":26692,\"Ġbruising\":26693,\"Ġdeterior\":26694,\"bourg\":26695,\"ĠTowers\":26696,\"JD\":26697,\"England\":26698,\"Ġequivalents\":26699,\"Ġrazor\":26700,\"Ġreassuring\":26701,\"Ġident\":26702,\"Ġ208\":26703,\"reath\":26704,\"ceans\":26705,\"Ġpatrolling\":26706,\"eve\":26707,\"pots\":26708,\"itative\":26709,\"Ġsided\":26710,\"Ġsofa\":26711,\"Ġunborn\":26712,\"Ġaug\":26713,\"Ġperpetual\":26714,\"effect\":26715,\"represented\":26716,\"Ġrails\":26717,\"ĠSummers\":26718,\"ĠMOR\":26719,\"ĠSlow\":26720,\"ĠExpert\":26721,\"Ġshameful\":26722,\"Ġaudits\":26723,\"Sl\":26724,\"ĠBurr\":26725,\"adow\":26726,\"ĠWAY\":26727,\"anic\":26728,\"ĠIslamists\":26729,\"ĠStranger\":26730,\"pse\":26731,\"amaz\":26732,\"ĠPeggy\":26733,\"ĠSeventh\":26734,\"Ġscreenplay\":26735,\"ĠGriff\":26736,\"Ireland\":26737,\"142\":26738,\"Ġneural\":26739,\"ĠFernand\":26740,\"ainment\":26741,\"ĠMigration\":26742,\"ureen\":26743,\"ĠSCH\":26744,\"Sullivan\":26745,\"ĠWag\":26746,\"ĠREG\":26747,\"Ġ420\":26748,\"inky\":26749,\"ĠNewspaper\":26750,\"School\":26751,\"Ok\":26752,\"ĠKrishna\":26753,\"Ġ480\":26754,\"erald\":26755,\"Ġskipping\":26756,\"Ġharrowing\":26757,\"158\":26758,\"rogen\":26759,\"Ġbetrayal\":26760,\"Ġculmination\":26761,\"ĠCirc\":26762,\"Ġ211\":26763,\"stro\":26764,\"ĠTrace\":26765,\"Ġheaviest\":26766,\"td\":26767,\"ĠHenri\":26768,\"epend\":26769,\"RB\":26770,\"arella\":26771,\"umbai\":26772,\"Ġcrem\":26773,\"ĠDistribut\":26774,\"ruff\":26775,\"Ġscreams\":26776,\"Ġscathing\":26777,\"girls\":26778,\"Ġtiles\":26779,\"ĠEvil\":26780,\"usp\":26781,\"Ġknowledgeable\":26782,\"Ġrestitution\":26783,\"ĠWiFi\":26784,\"Ġitiner\":26785,\"exper\":26786,\"oris\":26787,\"ĠPokÃ©mon\":26788,\"iane\":26789,\"produ\":26790,\"ĠAchievement\":26791,\"Ġbrunt\":26792,\"ĠSurgery\":26793,\"Ġpragmatic\":26794,\"Ber\":26795,\"ĠKejriwal\":26796,\"cus\":26797,\"Ġconsensual\":26798,\"acet\":26799,\"ĠSecondly\":26800,\"Ġdivul\":26801,\"uca\":26802,\"Ġbusted\":26803,\"emies\":26804,\"ĠMou\":26805,\"Ġ217\":26806,\"Ġexcludes\":26807,\"ĠSamoa\":26808,\"Ġlofty\":26809,\"ĠSic\":26810,\"ĠRemem\":26811,\"dn\":26812,\"Ġeradicate\":26813,\"Ġpies\":26814,\"Ġscenery\":26815,\"ATTLE\":26816,\"ĠWAS\":26817,\"Ġinnovate\":26818,\"ĠEverest\":26819,\"Ġsynonymous\":26820,\"izen\":26821,\"Ġeuth\":26822,\"ĠFIA\":26823,\"ITIES\":26824,\"ĠSuddenly\":26825,\"Ġforay\":26826,\"pell\":26827,\"ÄŁ\":26828,\"licensed\":26829,\"Ġfra\":26830,\"Ġblasting\":26831,\"autical\":26832,\"ĠBlizzard\":26833,\"orer\":26834,\"Ġchili\":26835,\"ĠSylvia\":26836,\"except\":26837,\"tec\":26838,\"ĠResistance\":26839,\"young\":26840,\"usions\":26841,\"iotic\":26842,\"ĠDreams\":26843,\"ĠArchives\":26844,\"Ġunleash\":26845,\"ĠPract\":26846,\"Ġlikened\":26847,\"Ġga\":26848,\"Ġdisappearing\":26849,\"Ġunnoticed\":26850,\"Ġfrightened\":26851,\"arms\":26852,\"ĠCAD\":26853,\"Ġcoloured\":26854,\"ĠSigns\":26855,\"oing\":26856,\"Ġvodka\":26857,\"ruption\":26858,\"otions\":26859,\"isal\":26860,\"ĠBecome\":26861,\"Ġswoop\":26862,\"reating\":26863,\"Ġchoking\":26864,\"Ġunforgettable\":26865,\"258\":26866,\"packs\":26867,\"345\":26868,\"ĠAutumn\":26869,\"Ġther\":26870,\"399\":26871,\"ĠFaculty\":26872,\"Ġ1933\":26873,\"ĠNormally\":26874,\"orge\":26875,\"ĠTess\":26876,\"ĠChrom\":26877,\"Ġscripts\":26878,\"Ġbiking\":26879,\"Act\":26880,\"Ġgrazing\":26881,\"ĠLabrador\":26882,\"ĠLey\":26883,\"Ġwandering\":26884,\"Ġfend\":26885,\"ĠPolk\":26886,\"ĠKeane\":26887,\"ĠBeef\":26888,\"elope\":26889,\"ĠApproximately\":26890,\"Ġ1952\":26891,\"personal\":26892,\"Ġhistorians\":26893,\"ĠMcDonnell\":26894,\"must\":26895,\"LES\":26896,\"iking\":26897,\"Ġtherm\":26898,\"Ġhumane\":26899,\"Ġcrowdfunding\":26900,\"ĠBenefits\":26901,\"Land\":26902,\"Ġanalog\":26903,\"agency\":26904,\"ĠCrowley\":26905,\"Ġbirths\":26906,\"Ġobj\":26907,\"Ġfren\":26908,\"ĠSalmon\":26909,\"bies\":26910,\"Ġreve\":26911,\"216\":26912,\"Ġbetrayed\":26913,\"Ġinduced\":26914,\"acles\":26915,\"Ġtrad\":26916,\"Ġforgiven\":26917,\"Ġearners\":26918,\"208\":26919,\"Ġxen\":26920,\"Ġunle\":26921,\"Ġnecklace\":26922,\"Ġgravel\":26923,\"Ġsalads\":26924,\"Ġgrooming\":26925,\"California\":26926,\"Ġpossessed\":26927,\"Ġproclamation\":26928,\"Ġsequences\":26929,\"ream\":26930,\"FOX\":26931,\"arkin\":26932,\"ĠTRAN\":26933,\"Ġpurs\":26934,\"ĠLoans\":26935,\"Ġsacrificed\":26936,\"Ġiceberg\":26937,\"Phill\":26938,\"Ġgalvan\":26939,\"Ġsmugglers\":26940,\"formation\":26941,\"onson\":26942,\"ĠVaughn\":26943,\"Ġdoctrine\":26944,\"ĠEyes\":26945,\"Ġunmanned\":26946,\"states\":26947,\"Ġdetermin\":26948,\"almost\":26949,\"Ġeviction\":26950,\"Ġtid\":26951,\"ARR\":26952,\"Ġcooks\":26953,\"Bad\":26954,\"ĠCamb\":26955,\"Ġlinear\":26956,\"229\":26957,\"ĠCooke\":26958,\"ĠPurch\":26959,\"join\":26960,\"ĠCult\":26961,\"ĠRefugee\":26962,\"Ġslamming\":26963,\"ĠðŁĳ\":26964,\"Ġpedal\":26965,\"ĠVeronica\":26966,\"Ġlandowners\":26967,\"ĠYel\":26968,\"ĠWorkshop\":26969,\"antic\":26970,\"Ġdysfunction\":26971,\"Ġ229\":26972,\"Ġculturally\":26973,\"Ġinfuri\":26974,\"ĠEck\":26975,\"sem\":26976,\"Ġwired\":26977,\"ĠWerner\":26978,\"lov\":26979,\"ĠJasper\":26980,\"Ġvehemently\":26981,\"ĠSpy\":26982,\"lift\":26983,\"ĠNab\":26984,\"ĠPound\":26985,\"ĠHanna\":26986,\"Ġleveled\":26987,\"WOOD\":26988,\"tm\":26989,\"ĠKitt\":26990,\"Ġconve\":26991,\"nat\":26992,\"Ġjog\":26993,\"IVER\":26994,\"Ġmemes\":26995,\"Ġseaw\":26996,\"ector\":26997,\"Ġsprayed\":26998,\"Ġvaccinated\":26999,\"Europe\":27000,\"Ġmustard\":27001,\"ĠMahm\":27002,\"Ġ214\":27003,\"Research\":27004,\"iminary\":27005,\"Ġconcerted\":27006,\"Detroit\":27007,\"Ġkios\":27008,\"Ġplummet\":27009,\"Ġvisuals\":27010,\"247\":27011,\"Ġ228\":27012,\"development\":27013,\"ĠPascal\":27014,\"acial\":27015,\"ĠSeasons\":27016,\"ĠTL\":27017,\"480\":27018,\"ĠReader\":27019,\"Ġexpulsion\":27020,\"Ġchoked\":27021,\"Ġdevotion\":27022,\"ĠSTAT\":27023,\"urred\":27024,\"Ġfascinated\":27025,\"Ġstealth\":27026,\"NL\":27027,\"Ġbooster\":27028,\"Kat\":27029,\"ĠPriebus\":27030,\"Ġaux\":27031,\"ĠHate\":27032,\"ĠThing\":27033,\"Ġabnormal\":27034,\"Ġcalmly\":27035,\"Ġdedicate\":27036,\"cause\":27037,\"Ġisolate\":27038,\"ĠPai\":27039,\"Ġsuspensions\":27040,\"Ġpoisoned\":27041,\"ission\":27042,\"Ġprohibiting\":27043,\"353\":27044,\"banks\":27045,\"Ġkissed\":27046,\"ĠBegin\":27047,\"atis\":27048,\"LI\":27049,\"Ġshaft\":27050,\"ĠGuth\":27051,\"ĠBoo\":27052,\"Ġcinnamon\":27053,\"Ġverbally\":27054,\"ĠRabbi\":27055,\"Ġmonsters\":27056,\"done\":27057,\"ĠClyde\":27058,\"Ġspar\":27059,\"ĠCage\":27060,\"ĠPersons\":27061,\"305\":27062,\"ĠMons\":27063,\"Ġjealous\":27064,\"Ġswirling\":27065,\"know\":27066,\"Ġprote\":27067,\"Ġcruising\":27068,\"Ġduly\":27069,\"Ġchapel\":27070,\"Ġgroove\":27071,\"bps\":27072,\"ĠKelvin\":27073,\"iom\":27074,\"aer\":27075,\"bomb\":27076,\"Christian\":27077,\"Ġgigs\":27078,\"+.\":27079,\"ĠWei\":27080,\"Ġfarmland\":27081,\"otally\":27082,\"Ġequitable\":27083,\"ĠCBO\":27084,\"chool\":27085,\"amara\":27086,\"Ġwealthiest\":27087,\"ĠMeans\":27088,\"Ġ235\":27089,\"ĠUk\":27090,\"steps\":27091,\"raham\":27092,\"nerg\":27093,\"Ġclad\":27094,\"Ġsled\":27095,\"ĠMorrow\":27096,\"152\":27097,\"ĠRece\":27098,\"Ġplausible\":27099,\"Ġbisexual\":27100,\"artments\":27101,\"Ġveh\":27102,\"ĠLoft\":27103,\"bly\":27104,\"ĠCONC\":27105,\"automatic\":27106,\"Ġmasterpiece\":27107,\"ĠSpringer\":27108,\"Ġtendencies\":27109,\"Ro\":27110,\"Ġresentment\":27111,\"Ġadversely\":27112,\"Ġbandwidth\":27113,\"ĠDAV\":27114,\"Ġtun\":27115,\"Ġpuppies\":27116,\"ĠBundes\":27117,\"ĠHort\":27118,\"ĠGarfield\":27119,\"Ġenlist\":27120,\"Ġmont\":27121,\"gd\":27122,\"Ġrooting\":27123,\"Dream\":27124,\"Ġfulfillment\":27125,\"chal\":27126,\"182\":27127,\"prop\":27128,\"159\":27129,\"Ġcourtyard\":27130,\"iard\":27131,\"ĠSle\":27132,\"Ġoperative\":27133,\"Ġpublishes\":27134,\"ĠProposition\":27135,\"Ġcritique\":27136,\"Ġredist\":27137,\"wang\":27138,\"ĠNep\":27139,\"DD\":27140,\"Ġbonding\":27141,\"141\":27142,\"ĠAssault\":27143,\"-'\":27144,\"Ġlodging\":27145,\"itters\":27146,\"cigarettes\":27147,\"Ġ__\":27148,\"ĠLaf\":27149,\"GF\":27150,\"ĠAnat\":27151,\"ĠStephan\":27152,\"214\":27153,\"ĠKass\":27154,\"Ġviz\":27155,\"Ġpiling\":27156,\"Ġfugitive\":27157,\"ĠCurrency\":27158,\"ĠCrypto\":27159,\"Ġfaux\":27160,\"ĠPing\":27161,\"ĠLia\":27162,\"igl\":27163,\"Ġadversaries\":27164,\"ĠYPG\":27165,\"ĠComb\":27166,\"ĠYar\":27167,\"heny\":27168,\"Ġoverhe\":27169,\"Fest\":27170,\"emy\":27171,\"Ever\":27172,\"Ġ370\":27173,\"Ġsecretive\":27174,\"ĠSEN\":27175,\"ĠMEM\":27176,\"PRESS\":27177,\"ĠBirth\":27178,\"kos\":27179,\"Ġprecarious\":27180,\"irting\":27181,\"ĠUI\":27182,\"Ġoccupying\":27183,\"olute\":27184,\"Ġperiodic\":27185,\"eon\":27186,\"iens\":27187,\"ĠRH\":27188,\"Win\":27189,\"Ġplaybook\":27190,\"Ġexodus\":27191,\"ĠSkinner\":27192,\"Ġorderly\":27193,\"ĠVed\":27194,\"ouses\":27195,\"Ġescal\":27196,\"Ġbenign\":27197,\"Ġbots\":27198,\"ĠWhis\":27199,\"Ġappra\":27200,\"FOR\":27201,\"ĠChromebook\":27202,\"_____\":27203,\"990\":27204,\"athed\":27205,\"Ġspirited\":27206,\"illi\":27207,\"Ġbicycles\":27208,\"orse\":27209,\"ifestyle\":27210,\"orno\":27211,\"ĠDept\":27212,\"JA\":27213,\"Ġnausea\":27214,\"Ġpervasive\":27215,\"velop\":27216,\"commun\":27217,\"ĠUniversities\":27218,\"Ġremnants\":27219,\"Ġdisarm\":27220,\"ĠBoots\":27221,\"Ġprin\":27222,\"...\\\"\":27223,\"quila\":27224,\"Ġcautiously\":27225,\"uper\":27226,\"onto\":27227,\"din\":27228,\"Ġvelocity\":27229,\"Ġconspiring\":27230,\"ĠMX\":27231,\"Ġemphasizing\":27232,\"Ġâĸ\":27233,\"ĠStam\":27234,\"Ġspices\":27235,\"Ġairplanes\":27236,\"uty\":27237,\"culture\":27238,\"ĠPetr\":27239,\"Ġglor\":27240,\"ĠExcel\":27241,\"ĠSpeech\":27242,\"Ġharmless\":27243,\"ĠPend\":27244,\"ĠCrossing\":27245,\"ĠDocument\":27246,\"Ġramifications\":27247,\"ĠCroatian\":27248,\"ĠKiller\":27249,\"Ġmultim\":27250,\"Ġdiscontinued\":27251,\"Ġcherished\":27252,\"ĠMaker\":27253,\"aspers\":27254,\"ĠBlooming\":27255,\"ĠMata\":27256,\"offic\":27257,\"Ġsettlers\":27258,\"ĠPlenty\":27259,\"ĠInstitutes\":27260,\"ĠArpaio\":27261,\"Pool\":27262,\"ĠSubst\":27263,\"Ġ380\":27264,\"Ġdecidedly\":27265,\"ollah\":27266,\"Den\":27267,\"ĠJiang\":27268,\"ĠAmos\":27269,\"Grand\":27270,\"ĠTurns\":27271,\"meyer\":27272,\"Ġconducive\":27273,\"Ġpoignant\":27274,\"abortion\":27275,\"Ġnotebook\":27276,\"Ġshelling\":27277,\"common\":27278,\"ĠPavel\":27279,\"Ġhumid\":27280,\"Ġinappropriately\":27281,\"????\":27282,\"Ġsoar\":27283,\"Ġdynasty\":27284,\"Ġresearched\":27285,\"ĠYon\":27286,\"Ġmaple\":27287,\"Ġwedge\":27288,\"mass\":27289,\"ĠTM\":27290,\"USE\":27291,\"eln\":27292,\"Ġgloss\":27293,\"rigan\":27294,\"steen\":27295,\"ĠDeV\":27296,\"Ġdebacle\":27297,\"Christmas\":27298,\"Ġtweaks\":27299,\"grab\":27300,\"Ġprofoundly\":27301,\"Ġcampaigner\":27302,\"ĠSeal\":27303,\"Ġiteration\":27304,\"Ġsigh\":27305,\"Ġunfounded\":27306,\"Ġframing\":27307,\"Ġrecognizable\":27308,\"Ġseizing\":27309,\"legal\":27310,\"Ġproportions\":27311,\"omers\":27312,\"rek\":27313,\"Ġscreenshot\":27314,\"itsu\":27315,\"ĠOG\":27316,\"ĠYing\":27317,\"ĠMississ\":27318,\"295\":27319,\"Ġlandsl\":27320,\"Ġpsychiatrist\":27321,\"sov\":27322,\"arine\":27323,\"Ju\":27324,\"Ġflo\":27325,\"apple\":27326,\"hof\":27327,\"wig\":27328,\"ĠENT\":27329,\"Ġenthusiast\":27330,\"Such\":27331,\"ĠArtificial\":27332,\"happy\":27333,\"oton\":27334,\"ĠFram\":27335,\"ĠRemove\":27336,\"Ġsmear\":27337,\"Ġjer\":27338,\"Ġtopp\":27339,\"Ġimbalance\":27340,\"ĠWords\":27341,\"Ġcoffers\":27342,\"olina\":27343,\"Ġrigged\":27344,\"uction\":27345,\"idding\":27346,\"Ġdispensaries\":27347,\"Ġdermat\":27348,\"Ġshutter\":27349,\"idental\":27350,\"Ġcontinu\":27351,\"Ġhumility\":27352,\"Ġbulbs\":27353,\"Ġ207\":27354,\"lass\":27355,\"ĠBeirut\":27356,\"ĠUlt\":27357,\"urry\":27358,\"NEWS\":27359,\"Ġfeminine\":27360,\"Ġsimulated\":27361,\"Ġcharger\":27362,\"mom\":27363,\"ĠCreed\":27364,\"Ġwolves\":27365,\"essions\":27366,\"created\":27367,\"ifiers\":27368,\"Ġdissemin\":27369,\"ĠDarling\":27370,\"umann\":27371,\"Ġmarrying\":27372,\"Ġshred\":27373,\"avin\":27374,\"Ġbudgetary\":27375,\"Ġmedicinal\":27376,\"ulin\":27377,\"seys\":27378,\"agues\":27379,\"Ġextracted\":27380,\"ĠFlower\":27381,\"Ġcontinents\":27382,\"ĠWish\":27383,\"Ġdivides\":27384,\"ĠDing\":27385,\"Ġinsulation\":27386,\"respect\":27387,\"ĠABS\":27388,\"Ġreconcile\":27389,\"keep\":27390,\"ILD\":27391,\"Ġgenome\":27392,\"Ġ410\":27393,\"ĠSweep\":27394,\"Ġharass\":27395,\"Ġfrantic\":27396,\"ĠEE\":27397,\"dad\":27398,\"Ġaperture\":27399,\"rought\":27400,\"Ġhugs\":27401,\"Ġdrying\":27402,\"Ġoverrun\":27403,\"Space\":27404,\"Ġperiodically\":27405,\"Ġbrightness\":27406,\"atched\":27407,\"kee\":27408,\"ĠITS\":27409,\"ĠSpokane\":27410,\"ĠSeaf\":27411,\"Ġdesks\":27412,\"ĠEisen\":27413,\"ĠOPS\":27414,\"Ġcider\":27415,\"Ġacceler\":27416,\"ĠAthlet\":27417,\"2008\":27418,\"ĠGuid\":27419,\"ĠManip\":27420,\"Ġmould\":27421,\"Ġmisguided\":27422,\"Ġbrow\":27423,\"Ġmanagerial\":27424,\"Ġhugged\":27425,\"Ġfurnish\":27426,\"ĠHarmony\":27427,\"ĠHebrew\":27428,\"Ġtyph\":27429,\"Ġdecreases\":27430,\"Ġimpetus\":27431,\"Ġcontagious\":27432,\"Ġunch\":27433,\"209\":27434,\"Ġswell\":27435,\"ĠHuffington\":27436,\"Ġpubs\":27437,\"Ġadequ\":27438,\"amoto\":27439,\"rir\":27440,\"Ġpristine\":27441,\"Ġanx\":27442,\"ĠSecure\":27443,\"Ġenrichment\":27444,\"ĠVAL\":27445,\"Ġsummed\":27446,\"Ġconfidently\":27447,\"ĠProfit\":27448,\"ĠFrog\":27449,\"ĠLena\":27450,\"ĠFUN\":27451,\"Ġbruises\":27452,\"Ġuproar\":27453,\"coll\":27454,\"ĠImpro\":27455,\"Ġflair\":27456,\"146\":27457,\"ĠBrend\":27458,\"Ġ166\":27459,\"Ġenhances\":27460,\"ĠDent\":27461,\"Ġdegener\":27462,\"Ġproponents\":27463,\"ĠInspired\":27464,\"Ġramps\":27465,\"Ġwisely\":27466,\"Western\":27467,\"Ġtart\":27468,\"Ġsteered\":27469,\"Ġtreason\":27470,\"dropping\":27471,\"Ġtransc\":27472,\"ĠScarlett\":27473,\"ĠEzekiel\":27474,\"Ġpivot\":27475,\"esame\":27476,\"Show\":27477,\"Ġdiscontent\":27478,\"ĠJudith\":27479,\"ĠPutting\":27480,\"Ġblessings\":27481,\"Ġhardcore\":27482,\"Ġtray\":27483,\"Ġdiscern\":27484,\"oley\":27485,\"ouk\":27486,\"Ġwil\":27487,\"Ġintolerance\":27488,\"157\":27489,\"ĠRelative\":27490,\"ĠLynd\":27491,\"Ġwhistleblower\":27492,\"Ġincon\":27493,\"ĠTao\":27494,\"Ġindefinite\":27495,\"Ġguardians\":27496,\"Ġagon\":27497,\"ĠInstruments\":27498,\"Ġexistential\":27499,\"AAF\":27500,\"vind\":27501,\"Ġbrazen\":27502,\"condition\":27503,\"Ġratified\":27504,\"fam\":27505,\"ĠHin\":27506,\"ĠMichaels\":27507,\"204\":27508,\"ĠKats\":27509,\"ITS\":27510,\"ISON\":27511,\"prone\":27512,\"Ġboiling\":27513,\"Ġprolong\":27514,\"Ġnoticing\":27515,\"resident\":27516,\"brance\":27517,\"ĠFolk\":27518,\"Ġdesserts\":27519,\"uton\":27520,\"Web\":27521,\"ĠLongh\":27522,\"ĠReef\":27523,\"Going\":27524,\"ĠCarb\":27525,\"Sur\":27526,\"complete\":27527,\"ĠSloan\":27528,\"ĠClubs\":27529,\"ĠSadd\":27530,\"Ġshrugged\":27531,\"Ġedible\":27532,\"ĠTyp\":27533,\"thal\":27534,\"ĠRocks\":27535,\"ĠClive\":27536,\"Ġkidding\":27537,\"ĠCrom\":27538,\"ĠTurks\":27539,\"ĠWak\":27540,\"Ġeyewitness\":27541,\"ĠHass\":27542,\"collar\":27543,\"Ġsucceeding\":27544,\"Ġinsert\":27545,\"Ġ224\":27546,\"ĠBret\":27547,\"Ġneurological\":27548,\"Ġrewrite\":27549,\"imil\":27550,\"ultimate\":27551,\"ĠJeremiah\":27552,\"Ġliaison\":27553,\"Ġpedd\":27554,\"direct\":27555,\"ĠYi\":27556,\"ĠMAD\":27557,\"ĠOrion\":27558,\"oyd\":27559,\"ĠLOC\":27560,\"release\":27561,\"Ġinvestigates\":27562,\"ĠApache\":27563,\"Ã»\":27564,\"ĠVend\":27565,\"Ġcynical\":27566,\"ĠHelm\":27567,\"ĠMovies\":27568,\"tops\":27569,\"Ġsinister\":27570,\"Ġunparalleled\":27571,\"Ġspikes\":27572,\"Ġoverlap\":27573,\"enstein\":27574,\"Ġhypocrisy\":27575,\"Plus\":27576,\"Ġexpansions\":27577,\"Ġvow\":27578,\"Ġdetonated\":27579,\"Ġfellowship\":27580,\"Ġsolicitor\":27581,\"ĠNewtown\":27582,\"mony\":27583,\"ĠLod\":27584,\"ĠDevelopers\":27585,\"ateg\":27586,\"ibus\":27587,\"Ġcrumbling\":27588,\"ĠWein\":27589,\"ĠKlan\":27590,\"gio\":27591,\"ĠPhys\":27592,\"ĠAntarctica\":27593,\"368\":27594,\"Ġseam\":27595,\"Ġautomobiles\":27596,\"ĠTEAM\":27597,\"bern\":27598,\"Ġmanic\":27599,\"Ġsanct\":27600,\"Ġequals\":27601,\"Est\":27602,\"Ġincentiv\":27603,\"ĠHawking\":27604,\"nin\":27605,\"Ġresonate\":27606,\"bid\":27607,\"Ġtelescope\":27608,\"endon\":27609,\"ĠVacc\":27610,\"Ġregretted\":27611,\"Ġ1300\":27612,\"ĠForestry\":27613,\"BOOK\":27614,\"Ġgroundwork\":27615,\"Ġessays\":27616,\"ĠIndo\":27617,\"Pierre\":27618,\"ĠChau\":27619,\"Ġapologies\":27620,\"killers\":27621,\"ĠMoroccan\":27622,\"0001\":27623,\"336\":27624,\"Ra\":27625,\"Ġparcels\":27626,\"Ġleaned\":27627,\"Ġthankfully\":27628,\"ĠSplit\":27629,\"Ġlobbied\":27630,\"ĠDegree\":27631,\"Ġrisking\":27632,\"assy\":27633,\"Ġsupplemental\":27634,\"little\":27635,\"Ġeclectic\":27636,\"Ġ206\":27637,\"ealing\":27638,\"206\":27639,\"Ġrepo\":27640,\"Ġhose\":27641,\"ayn\":27642,\"lux\":27643,\"Ġbeliever\":27644,\"')\":27645,\"ĠHide\":27646,\"vance\":27647,\"ĠEinstein\":27648,\"Ġdepos\":27649,\"Ġfray\":27650,\"Ġki\":27651,\"Ġinternship\":27652,\"ĠHou\":27653,\"Vis\":27654,\"Ġstare\":27655,\"ĠBreed\":27656,\"option\":27657,\"Ġvisionary\":27658,\"Ġmins\":27659,\"Ġbitten\":27660,\"ancies\":27661,\"ĠShake\":27662,\"Ġtemplate\":27663,\"Ġliner\":27664,\"Ġmuster\":27665,\"appro\":27666,\"ĠMubarak\":27667,\"esty\":27668,\"mong\":27669,\"actory\":27670,\"Ġheadphone\":27671,\"ĠPrec\":27672,\"Ġwaive\":27673,\"Ron\":27674,\"ĠHearing\":27675,\"Ġimperfect\":27676,\"Ġsealing\":27677,\"Ġlocating\":27678,\"Ġculminated\":27679,\"chio\":27680,\"channel\":27681,\"lust\":27682,\"ĠLowell\":27683,\"woods\":27684,\"Ġsoak\":27685,\"Ġforbidden\":27686,\"Ġdetached\":27687,\"unct\":27688,\"ĠHunger\":27689,\"ĠPatient\":27690,\"ĠPolo\":27691,\"Saharan\":27692,\"Jon\":27693,\"athered\":27694,\"ĠSignal\":27695,\"Six\":27696,\"Ġstatistically\":27697,\"ITH\":27698,\"artment\":27699,\"ĠCU\":27700,\"Ġhates\":27701,\"qual\":27702,\"Ġcapitalist\":27703,\"ATES\":27704,\"ĠDesc\":27705,\"Ġhandcuffed\":27706,\"Ġindulge\":27707,\"ĠReligious\":27708,\"German\":27709,\"housing\":27710,\"Ġdismantling\":27711,\"Ġconventions\":27712,\"dain\":27713,\"chairs\":27714,\"Ġloos\":27715,\"Ġknowingly\":27716,\"Var\":27717,\"Ġhusbands\":27718,\"eez\":27719,\"asion\":27720,\"ĠIssa\":27721,\"Ġswollen\":27722,\"Ġ1946\":27723,\"Ġheadlined\":27724,\"Chelsea\":27725,\"Ġignorant\":27726,\"Ġperipheral\":27727,\"Note\":27728,\"Ġaxe\":27729,\"Ġnicotine\":27730,\"ĠSanctuary\":27731,\"Ġ1917\":27732,\"Ġwithdrawals\":27733,\"uits\":27734,\"Hot\":27735,\"Ġreimburse\":27736,\"probably\":27737,\"ĠAdapt\":27738,\"industrial\":27739,\"answer\":27740,\"orus\":27741,\"ĠMell\":27742,\"Talk\":27743,\"Ġcontemplating\":27744,\"omas\":27745,\"Ġtaxis\":27746,\"Ġencompasses\":27747,\"rations\":27748,\"ĠLatvia\":27749,\"Ġhumiliating\":27750,\"Ġloft\":27751,\"tight\":27752,\"rium\":27753,\"Ġlogin\":27754,\"ĠBulletin\":27755,\"Ġturtles\":27756,\"EAR\":27757,\"349\":27758,\"Radio\":27759,\"ĠBord\":27760,\"151\":27761,\"kk\":27762,\"pocket\":27763,\"Ġdove\":27764,\"348\":27765,\"Ġtemptation\":27766,\"ĠCoy\":27767,\"those\":27768,\"ĠDest\":27769,\"ishly\":27770,\"rn\":27771,\"Ġmammals\":27772,\"ĠTub\":27773,\"arial\":27774,\"ĠPersian\":27775,\"Ġdaddy\":27776,\"Zen\":27777,\"Ġps\":27778,\"Ġ]\":27779,\"Field\":27780,\"adiq\":27781,\"Ġmeaningless\":27782,\"Ġprimer\":27783,\"Ġ1942\":27784,\"Ġ!\":27785,\"625\":27786,\"Ġfashionable\":27787,\"ĠTheft\":27788,\"ĠHAVE\":27789,\"christ\":27790,\"Ġperil\":27791,\"Ġrepealing\":27792,\"Ġbuff\":27793,\"Ġodor\":27794,\"Ġstalking\":27795,\"ĠDems\":27796,\"iences\":27797,\"Ġunilaterally\":27798,\"odies\":27799,\"ĠQuite\":27800,\"Ġbloodshed\":27801,\"Ġinfect\":27802,\"Ġreminders\":27803,\"Ġchop\":27804,\"Ġevapor\":27805,\"877\":27806,\"Ġhorrified\":27807,\"ĠFruit\":27808,\"rams\":27809,\"Ġinsecure\":27810,\"cester\":27811,\"ĠNationwide\":27812,\"Ġmocking\":27813,\"Ret\":27814,\"Ġcomplying\":27815,\"sav\":27816,\"Ġali\":27817,\"Family\":27818,\"Ĩ\":27819,\"Ġdishonest\":27820,\"Ġincorrectly\":27821,\"LOAD\":27822,\"ĠGand\":27823,\"ourcing\":27824,\"obby\":27825,\"ĠPetersen\":27826,\"Something\":27827,\"Ġravaged\":27828,\"limited\":27829,\"Ġrituals\":27830,\"ĠKnowledge\":27831,\"ĠUtility\":27832,\"Ġdoom\":27833,\"Ġsheds\":27834,\"ĠGael\":27835,\"ĠMillennials\":27836,\"ĠMonthly\":27837,\"Ġdomination\":27838,\"Ġrapport\":27839,\"spot\":27840,\"ĠPrest\":27841,\"ĠHA\":27842,\"ushes\":27843,\"Ġtact\":27844,\"Richard\":27845,\"Ġgritty\":27846,\"Does\":27847,\"ĠTNT\":27848,\"Ġdownfall\":27849,\"Wood\":27850,\"ĠPrediction\":27851,\"ĠPour\":27852,\"ĠFraud\":27853,\"ĠSyndrome\":27854,\"166\":27855,\"Ġliteral\":27856,\"Ġaddict\":27857,\"ĠLoud\":27858,\"hens\":27859,\"ĠAccounts\":27860,\"distance\":27861,\"Ġclassmate\":27862,\"Ġsalv\":27863,\"Ġunlucky\":27864,\"Ġpartying\":27865,\"ĠKou\":27866,\"ĠSNAP\":27867,\"%-\":27868,\"Ġdelegate\":27869,\"Ġstrikers\":27870,\"ĠSlate\":27871,\"Ġarticulate\":27872,\"390\":27873,\"Ġinqu\":27874,\"Ġdiscredit\":27875,\"ĠPriv\":27876,\"ploy\":27877,\"ĠMarketplace\":27878,\"ĠTune\":27879,\"visor\":27880,\"Ġwrestle\":27881,\"Ġkindly\":27882,\"ĠCollect\":27883,\"Ġcirc\":27884,\"ĠRemain\":27885,\"Ġ192\":27886,\"contin\":27887,\"Ġ325\":27888,\"Ġsevered\":27889,\"isations\":27890,\"Ġmuddy\":27891,\"Ġtaxing\":27892,\"ĠRepresent\":27893,\"ĠSty\":27894,\"rology\":27895,\"ĠJudges\":27896,\"ĠBronze\":27897,\"ĠApplic\":27898,\"Ġarrow\":27899,\"consuming\":27900,\"ĠFeaturing\":27901,\"Ġspies\":27902,\"Ġnoises\":27903,\"ĠColony\":27904,\"lost\":27905,\"Ġopp\":27906,\"Ġdeem\":27907,\"ĠGarc\":27908,\"icent\":27909,\"ptroller\":27910,\"liest\":27911,\"Ġoutward\":27912,\"ĠUser\":27913,\"Ġintimidate\":27914,\"156\":27915,\"Ġjab\":27916,\"ANGE\":27917,\"Jay\":27918,\"ĠPoverty\":27919,\"ACA\":27920,\"Ġrife\":27921,\"Ġfaint\":27922,\"ĠAcceler\":27923,\"tall\":27924,\"ĠUNITED\":27925,\"ĠFighter\":27926,\"ĠGilmore\":27927,\"Ġsod\":27928,\"amura\":27929,\"Ġpredictive\":27930,\"Ġpolish\":27931,\"ĠDD\":27932,\"Ġfabricated\":27933,\"ĠDag\":27934,\"Ġfatty\":27935,\"Ġplague\":27936,\"Ġexhib\":27937,\"ĠAdvent\":27938,\"Ġ1941\":27939,\"ERSON\":27940,\"initely\":27941,\"Ġloneliness\":27942,\"ĠEquality\":27943,\"Ġuntrue\":27944,\"Ġonlook\":27945,\"Ġfragmented\":27946,\"ruce\":27947,\"Ġdistrust\":27948,\"Ġscal\":27949,\"ĠCors\":27950,\"Ġrobbing\":27951,\"cultural\":27952,\"clusion\":27953,\"ĠObi\":27954,\"sels\":27955,\"ĠEvidence\":27956,\"ĠSac\":27957,\"Ġfragments\":27958,\"Ġflipping\":27959,\"ĠRabbit\":27960,\"Ġdisproportionate\":27961,\"ĠCreat\":27962,\"Ġlabeling\":27963,\"ĠGri\":27964,\"Ġ161\":27965,\"ĠEditors\":27966,\"holm\":27967,\"adr\":27968,\"Ĭ\":27969,\"tailed\":27970,\"Ġrenters\":27971,\"Ġnoodles\":27972,\"Ġcompetence\":27973,\"Ġpanc\":27974,\"uration\":27975,\"Ġacids\":27976,\"Ġconfid\":27977,\"rival\":27978,\"AAA\":27979,\"kson\":27980,\"Ġrecreate\":27981,\"153\":27982,\"Ġ164\":27983,\"ĠOlympia\":27984,\"ĠUnlimited\":27985,\"ĠShock\":27986,\"ĠTeaching\":27987,\"ĠHouses\":27988,\"resso\":27989,\"ĠMaw\":27990,\"Ġreplen\":27991,\"Ġprotestors\":27992,\"bey\":27993,\"Ġsurve\":27994,\"Ġemphasizes\":27995,\"223\":27996,\"ĠEsther\":27997,\"ĠNikol\":27998,\"Ġprosecutions\":27999,\"ĠFreed\":28000,\"Ġposs\":28001,\"OTE\":28002,\"ĠPrayer\":28003,\"Ġsquarely\":28004,\"Ġtir\":28005,\"adv\":28006,\"Ġbogus\":28007,\"Ġwrongful\":28008,\"Ġembell\":28009,\"Ġseldom\":28010,\"Ġpossesses\":28011,\"Er\":28012,\"ĠAlternatively\":28013,\"Ġinstituted\":28014,\"rr\":28015,\"Ġvocational\":28016,\"eval\":28017,\"ĠComics\":28018,\"Ġstumbling\":28019,\"335\":28020,\"Ġdragon\":28021,\"vine\":28022,\"services\":28023,\"Ġcrit\":28024,\"irens\":28025,\"Ġlayered\":28026,\"orb\":28027,\"Ġdominates\":28028,\"ĠMarx\":28029,\"period\":28030,\"avering\":28031,\"Ġbrigade\":28032,\"Ġchem\":28033,\"ĠEvolution\":28034,\"ĠSuk\":28035,\"Ġ209\":28036,\"ĠMalk\":28037,\"Ġtallest\":28038,\"recogn\":28039,\"ĠCraw\":28040,\"Ġell\":28041,\"ĠCaesar\":28042,\"php\":28043,\"ĠSurvivors\":28044,\"sd\":28045,\"itsch\":28046,\"ambo\":28047,\"Ġashore\":28048,\"acular\":28049,\"rost\":28050,\"Ġmurderer\":28051,\"Ġcasts\":28052,\"ĠEconomist\":28053,\"ĠWeapons\":28054,\"Ġnostalgic\":28055,\"Skip\":28056,\"REAM\":28057,\"Pa\":28058,\"Ġjournals\":28059,\"ĠSitting\":28060,\"Union\":28061,\"Att\":28062,\"ĠMaxim\":28063,\"Ġpurportedly\":28064,\"Ġrespecting\":28065,\"ĠMAX\":28066,\"seed\":28067,\"Ġjuicy\":28068,\"ĠGallup\":28069,\"Ġmileage\":28070,\"adier\":28071,\"Ġbod\":28072,\"DER\":28073,\"Ġsummers\":28074,\"icult\":28075,\"ipl\":28076,\"ĠDeng\":28077,\"Ġsmells\":28078,\"Ġivory\":28079,\"Ġ255\":28080,\"Id\":28081,\"DEN\":28082,\"Ġ159\":28083,\"Due\":28084,\"ĠLighting\":28085,\"ĠSurely\":28086,\"Ġsund\":28087,\"ĠKessler\":28088,\"immigrant\":28089,\"Ġtragedies\":28090,\"ĠOxy\":28091,\"ĠFixed\":28092,\"ĠBalk\":28093,\"Ġoriented\":28094,\"pher\":28095,\"Ġkitchens\":28096,\"Ġhips\":28097,\"Ġtweak\":28098,\"Ġtuna\":28099,\"ĠCla\":28100,\"Ġdislike\":28101,\"ussy\":28102,\"Ġoutnumbered\":28103,\"Ġplumbing\":28104,\"Ġcogn\":28105,\"ĠThrow\":28106,\"ĠTER\":28107,\"urally\":28108,\"ĠMurd\":28109,\"Ġcreamy\":28110,\"Ġresiding\":28111,\"otics\":28112,\"Ġfingerprints\":28113,\"!,\":28114,\"Ġpaused\":28115,\"ĠMilo\":28116,\"Ġhomosexuality\":28117,\"Ġresponsibly\":28118,\"iop\":28119,\"UCT\":28120,\"Ġsucceeds\":28121,\"ĠCRE\":28122,\"ĠThatcher\":28123,\"Ġcurrents\":28124,\"Ġarises\":28125,\"Ġwaterproof\":28126,\"Ġamp\":28127,\"ĠClaims\":28128,\"177\":28129,\"Ġsubpoen\":28130,\"Ġvig\":28131,\"ĠNeuro\":28132,\"Ġblur\":28133,\"ĠPaint\":28134,\"campus\":28135,\"Ġtoughness\":28136,\"ĠButton\":28137,\"Neal\":28138,\"ĠDEN\":28139,\"ĠNir\":28140,\"ĠAxel\":28141,\"EEP\":28142,\"Ġpint\":28143,\"Ġagile\":28144,\"odor\":28145,\"Ġessentials\":28146,\"ĠMov\":28147,\"ĠVenezuel\":28148,\"Ġexchanging\":28149,\"ĠNegative\":28150,\"Mil\":28151,\"Key\":28152,\"Ġbuzzing\":28153,\"ĠStew\":28154,\"Ġrebuke\":28155,\"Ġdepl\":28156,\"ĠKoz\":28157,\"Ġ163\":28158,\"Ġshines\":28159,\"NZ\":28160,\"Ġcarnage\":28161,\"cases\":28162,\"Ġwarmed\":28163,\"ĠGreenwich\":28164,\"College\":28165,\"Ġneedy\":28166,\"301\":28167,\"ĠMÃ¼\":28168,\"culation\":28169,\"Ġ440\":28170,\"425\":28171,\"atories\":28172,\"Ġsatisfactory\":28173,\"ĠFib\":28174,\"ĠElim\":28175,\"developed\":28176,\"Ġvacations\":28177,\"Ġpeculiar\":28178,\"Ġvets\":28179,\"onest\":28180,\"ĠPug\":28181,\"Ġlifestyles\":28182,\"zzi\":28183,\"Ġprovoke\":28184,\"bah\":28185,\"arger\":28186,\"ĠVirt\":28187,\"Sales\":28188,\"annel\":28189,\"ĠMeth\":28190,\"ivating\":28191,\"Ġrevoke\":28192,\"ĠAgenda\":28193,\"ĠIch\":28194,\"Ġsensit\":28195,\"ĠAzerbai\":28196,\"ĠBombay\":28197,\"Ġuncon\":28198,\"river\":28199,\"Ġapr\":28200,\"actic\":28201,\"ĠSubaru\":28202,\"Ġbanquet\":28203,\"Ġcontradict\":28204,\"tek\":28205,\"Football\":28206,\"igent\":28207,\"Ġreintrodu\":28208,\"ĠInsight\":28209,\"Ġsystematically\":28210,\"Ġboun\":28211,\"ĠFishing\":28212,\"Ġstri\":28213,\"ĠOB\":28214,\"Ġstair\":28215,\"Wall\":28216,\"ĠAllow\":28217,\"Ġcaramel\":28218,\"169\":28219,\"Ġcafes\":28220,\"Ġcalcium\":28221,\"Ġ169\":28222,\"Ġportraying\":28223,\"Ġdiscriminate\":28224,\"Ġunrestricted\":28225,\"Ġmant\":28226,\"Ġscarcity\":28227,\"Ġfeminism\":28228,\"ĠJJ\":28229,\"ĠOversight\":28230,\"ĠCue\":28231,\"Ġinexperienced\":28232,\"Ġdrafts\":28233,\"Ġ1939\":28234,\"nm\":28235,\"forest\":28236,\"ĠHonour\":28237,\"Ġceramic\":28238,\"Ġdownstairs\":28239,\"Ġboon\":28240,\"Ġmorality\":28241,\"Ġhorrifying\":28242,\"Rad\":28243,\"justice\":28244,\"Ġmosques\":28245,\"Ġcurfew\":28246,\"Ġsurrogate\":28247,\"Ġreimb\":28248,\"enth\":28249,\"pressure\":28250,\"beam\":28251,\"Ġwhirlwind\":28252,\"ĠRecession\":28253,\"ĠTours\":28254,\"Ġclusters\":28255,\"ĠQuant\":28256,\"Jonathan\":28257,\"project\":28258,\"Ġ777\":28259,\"ĠNOAA\":28260,\"abis\":28261,\"Ġdeficiencies\":28262,\"Ġsuicides\":28263,\"Ġfoothold\":28264,\"ĠYah\":28265,\"imeter\":28266,\"URN\":28267,\"Ġcultivate\":28268,\"Ġnoisy\":28269,\"Ġ1951\":28270,\"Ġpressuring\":28271,\"ĠDeals\":28272,\"ĠProphet\":28273,\"ĠWikipedia\":28274,\"INESS\":28275,\"ĠShine\":28276,\"ĠCalled\":28277,\"ĠSole\":28278,\"ĠZhou\":28279,\"Ġasphalt\":28280,\"armac\":28281,\"ĠScorp\":28282,\"ĠUnknown\":28283,\"ĠPAT\":28284,\"Heart\":28285,\"Ġguessed\":28286,\"Ġsushi\":28287,\"Ġheartbeat\":28288,\"Ġconcent\":28289,\"eret\":28290,\"plin\":28291,\"Ġweeds\":28292,\"Ġbombed\":28293,\"ĠTerrorism\":28294,\"Rich\":28295,\"Ġblades\":28296,\"Ġhaunt\":28297,\"Ġstorefront\":28298,\"Ġthwarted\":28299,\"access\":28300,\"ĠLydia\":28301,\"LINE\":28302,\"Ġpregnancies\":28303,\"Ġripping\":28304,\"ĠBelieve\":28305,\"spoken\":28306,\"inian\":28307,\"sed\":28308,\"ĠBrass\":28309,\"econom\":28310,\"current\":28311,\"Ġvoc\":28312,\"Ġmodeled\":28313,\"Ġpeppers\":28314,\"otech\":28315,\"ĠOption\":28316,\"Connell\":28317,\"isel\":28318,\"Ġcompel\":28319,\"Ġjuveniles\":28320,\"ĠNET\":28321,\"ĠEXP\":28322,\"Ġparadigm\":28323,\"Des\":28324,\"Ġ204\":28325,\"employed\":28326,\"Ġdurability\":28327,\"Ġ245\":28328,\"Ġbillionaires\":28329,\"violent\":28330,\"ĠCooperative\":28331,\"TOP\":28332,\"ĠGarry\":28333,\"ĠSoldiers\":28334,\"Ġdared\":28335,\"Ġvoucher\":28336,\"Ġblends\":28337,\"gue\":28338,\"Ġadventurous\":28339,\"Ġorganisms\":28340,\"Ġgaze\":28341,\"Ġcrap\":28342,\"Coach\":28343,\"omon\":28344,\"ĠWheels\":28345,\"ĠGrayson\":28346,\"Ġrecy\":28347,\"grave\":28348,\"Ġallergic\":28349,\"Ġreef\":28350,\"Ġbeginnings\":28351,\"ĠRuff\":28352,\"Ġclout\":28353,\"structed\":28354,\"315\":28355,\"ĠGeorgian\":28356,\"say\":28357,\"Ġsprings\":28358,\"ĠAsus\":28359,\"Ġrepaid\":28360,\"ĠGuys\":28361,\"ticket\":28362,\"Ġunb\":28363,\"ĠCertificate\":28364,\"ĠSTORY\":28365,\"cin\":28366,\"Ġpassions\":28367,\"Ġmediocre\":28368,\"Ġlackluster\":28369,\"vernight\":28370,\"kids\":28371,\"ĠWife\":28372,\"politics\":28373,\"ĠHimal\":28374,\"oddy\":28375,\"ensus\":28376,\"ĠGustav\":28377,\"binding\":28378,\"ĠIndividuals\":28379,\"Ġmaize\":28380,\"Ġhoop\":28381,\"ĠChanging\":28382,\"Ġlessen\":28383,\"Ġarranging\":28384,\"ĠFukushima\":28385,\"ĠTrying\":28386,\"ĠMage\":28387,\"Ġskeleton\":28388,\"ĠTec\":28389,\"289\":28390,\"Ġrecl\":28391,\"ĠFIL\":28392,\"Gs\":28393,\"ĠOdyssey\":28394,\"ĠProcessing\":28395,\"ilion\":28396,\"Ġsubsidized\":28397,\"Ġabdomen\":28398,\"Ġanalyse\":28399,\"music\":28400,\"clean\":28401,\"Ġunfinished\":28402,\"Ġdownloads\":28403,\"Ġmorally\":28404,\"Ġ218\":28405,\"Ġtrib\":28406,\"Keep\":28407,\"ĠSER\":28408,\"FY\":28409,\"Ġaust\":28410,\"Ġdiscovers\":28411,\"ĠGROUP\":28412,\"ĠMachines\":28413,\"Ġeroded\":28414,\"Ġominous\":28415,\"Ġbrightly\":28416,\"IME\":28417,\"Ġwicked\":28418,\"ĠTrou\":28419,\"Ġvisions\":28420,\"Kay\":28421,\"reported\":28422,\"Ġbog\":28423,\"ĠQuin\":28424,\"ĠSigma\":28425,\"urned\":28426,\"ixon\":28427,\"Ġharming\":28428,\"Ġcheckout\":28429,\"inet\":28430,\"much\":28431,\"Ġcherish\":28432,\"ĠByrd\":28433,\"ĠSamson\":28434,\"WP\":28435,\"orders\":28436,\"boa\":28437,\"Ġbron\":28438,\"oki\":28439,\"ĠRR\":28440,\"Ġsuitcase\":28441,\"Ġfeathers\":28442,\"ĠChristy\":28443,\"Islamic\":28444,\"Ġamusement\":28445,\"ĠISS\":28446,\"intensive\":28447,\"Qaida\":28448,\"Ġneurons\":28449,\"Ġwagon\":28450,\"ĠTek\":28451,\"Ġdolls\":28452,\"ĠShoot\":28453,\"Ġunderestimate\":28454,\"Ġstreamlined\":28455,\"Ġfractures\":28456,\"Ġcathedral\":28457,\"Ġeliminates\":28458,\"helle\":28459,\"Ġcitrus\":28460,\"risis\":28461,\"Ġimpecc\":28462,\"istries\":28463,\"ĠHog\":28464,\"vote\":28465,\"pas\":28466,\"Ġassign\":28467,\"ĠSongs\":28468,\"ĠMiracle\":28469,\"kas\":28470,\"zynski\":28471,\"Ġcrane\":28472,\"Ġadulthood\":28473,\"ĠBenefit\":28474,\"ĠGrimes\":28475,\"Ġpayday\":28476,\"ablished\":28477,\"Ġcenterpiece\":28478,\"Ġhassle\":28479,\"ĠAppalachian\":28480,\"follow\":28481,\"Ġ290\":28482,\"ĠRL\":28483,\"ĠDoe\":28484,\"Ġacclaim\":28485,\"Ġlevied\":28486,\"Ġtossing\":28487,\"Ġcarrots\":28488,\"ĠDarius\":28489,\"161\":28490,\"Ġoffspring\":28491,\"ĠJury\":28492,\"ĠTPP\":28493,\"CAP\":28494,\"Ġenvironmentalists\":28495,\"Ġrays\":28496,\"267\":28497,\"Ser\":28498,\"Ġcaptivity\":28499,\"Ġappellate\":28500,\"ĠElectricity\":28501,\"ĠEnough\":28502,\"232\":28503,\"Ġfisher\":28504,\"Ġbrilliance\":28505,\"Ġpraises\":28506,\"aunch\":28507,\"Ġsolicitation\":28508,\"Ġadolescent\":28509,\"Ġinferior\":28510,\"checks\":28511,\"Set\":28512,\"Ġmutations\":28513,\"ĠLatinos\":28514,\"ĠLicense\":28515,\"ĠAme\":28516,\"hirt\":28517,\"ĠChun\":28518,\"Ġdeeds\":28519,\"ldon\":28520,\"Ġmammoth\":28521,\"Ġturtle\":28522,\"rule\":28523,\"Ken\":28524,\"Ġvoyage\":28525,\"gram\":28526,\"Ġconquer\":28527,\"Ġretaliate\":28528,\"ĠPJ\":28529,\"ĠViking\":28530,\"Ġsafegu\":28531,\"ordinary\":28532,\"ĠArbit\":28533,\"ĠDigest\":28534,\"Die\":28535,\"Ġbureaucratic\":28536,\"Ġhonorable\":28537,\"Ġcafeteria\":28538,\"ĠRAF\":28539,\"ĠPlaces\":28540,\"ĠKlu\":28541,\"Cam\":28542,\"ĠBiology\":28543,\"ĠCycling\":28544,\"imore\":28545,\"Ġstripping\":28546,\"Ġwarriors\":28547,\"Ġbursting\":28548,\"Ġlapse\":28549,\"Ġversa\":28550,\"Ġclicked\":28551,\"ogh\":28552,\"Ġ\\\"âĢ¦\":28553,\"Ġdiligently\":28554,\"ĠMiy\":28555,\"ĠCorpus\":28556,\"Ġredef\":28557,\"Ġ176\":28558,\"ĠInstrument\":28559,\"ĠOECD\":28560,\"Ġstro\":28561,\"Ġmicrowave\":28562,\"Santa\":28563,\"Ġpars\":28564,\"Social\":28565,\"iffe\":28566,\"itability\":28567,\"Equ\":28568,\"Ġnud\":28569,\"legged\":28570,\"ĠTud\":28571,\"lav\":28572,\"Ġinterpreter\":28573,\"alcohol\":28574,\"Ġimposition\":28575,\"Ġdwelling\":28576,\"Ġ1400\":28577,\"].\\\"\":28578,\"ĠIw\":28579,\"RM\":28580,\"Ġ555\":28581,\"Ġparalyzed\":28582,\"mind\":28583,\"rans\":28584,\"adin\":28585,\"French\":28586,\"Ġliar\":28587,\"Represent\":28588,\"Ġstrapped\":28589,\"orate\":28590,\"Ġrigging\":28591,\"Ġinterrog\":28592,\"Ġsparse\":28593,\"ento\":28594,\"ĠThem\":28595,\"Ġbaseless\":28596,\"Ġbuildup\":28597,\"Ġundecided\":28598,\"isms\":28599,\"Ġabduct\":28600,\"Ġflowed\":28601,\"Ġprestige\":28602,\"Ġhacks\":28603,\"Ġpanicked\":28604,\"Cast\":28605,\"ĠKrish\":28606,\"umat\":28607,\"Ġantique\":28608,\"Ġbitters\":28609,\"Ġentitlement\":28610,\"Ġstandby\":28611,\"Ten\":28612,\"said\":28613,\"ĠConditions\":28614,\"events\":28615,\"Ġobey\":28616,\"Ġshortest\":28617,\"etting\":28618,\"Ġconcentrating\":28619,\"ĠNeeds\":28620,\"234\":28621,\"Ġintrigued\":28622,\"enting\":28623,\"ĠXen\":28624,\"ĠAlger\":28625,\"seekers\":28626,\"anish\":28627,\"Ġ172\":28628,\"âĢĳ\":28629,\"Ġsilicon\":28630,\"Ġstandardized\":28631,\"ĠFountain\":28632,\"essel\":28633,\"Ġapproves\":28634,\"Ġsucked\":28635,\"gone\":28636,\"ĠBriggs\":28637,\"brother\":28638,\"Ġartisan\":28639,\"ĠContinuing\":28640,\"vir\":28641,\"Ġsubmarines\":28642,\"ĠInk\":28643,\"program\":28644,\"ĠNexus\":28645,\"ĠCoco\":28646,\"Ġconceptual\":28647,\"Ġmatt\":28648,\"aughters\":28649,\"Ġbaths\":28650,\"Ġbeaut\":28651,\"ĠEmerald\":28652,\"ĠParties\":28653,\"248\":28654,\"completely\":28655,\"esan\":28656,\"Ġdiarrhea\":28657,\"Ġ1100\":28658,\"borg\":28659,\"ĠBroken\":28660,\"Ġreiterate\":28661,\"Ġsorting\":28662,\"ONS\":28663,\"Ġ177\":28664,\"Ġadmin\":28665,\"ĠMandatory\":28666,\"Ġsymptom\":28667,\"Ġpaced\":28668,\"Remember\":28669,\"Ġabdominal\":28670,\"Ġswapped\":28671,\"Ġtransitions\":28672,\"IFA\":28673,\"pretty\":28674,\"ĠJC\":28675,\"Ġallotted\":28676,\"ĠShows\":28677,\"Arthur\":28678,\"Ġsoften\":28679,\"dozen\":28680,\"Mah\":28681,\"Ġextinguished\":28682,\"Ġreelection\":28683,\"Ġdeployments\":28684,\"Ġsturdy\":28685,\"Ġdownright\":28686,\"Ġjams\":28687,\"ĠOptim\":28688,\"Ġhumiliation\":28689,\"cd\":28690,\"Ġbunk\":28691,\"sie\":28692,\"NAT\":28693,\"ilies\":28694,\"Ġimplying\":28695,\"Ġ<\":28696,\"Ġhomepage\":28697,\"242\":28698,\"Ġey\":28699,\"Ġdict\":28700,\"Ġslender\":28701,\"Ġforehead\":28702,\"ĠCecil\":28703,\"Ġshrunk\":28704,\"ĠExit\":28705,\"Ġexpressly\":28706,\"Ġseals\":28707,\"ĠThiel\":28708,\"umni\":28709,\"Ġdamning\":28710,\"ĠVS\":28711,\"ulum\":28712,\"BBC\":28713,\"URES\":28714,\"Ġinhal\":28715,\"Ġfont\":28716,\"Ġworkplaces\":28717,\"ĠPUBLIC\":28718,\"ĠHorror\":28719,\"Bs\":28720,\"arta\":28721,\"ĠBread\":28722,\"Ġstret\":28723,\"Ġethos\":28724,\"Ġstabilized\":28725,\"Ġconvers\":28726,\"ĠInqu\":28727,\"Ġjudgments\":28728,\"ĠContemporary\":28729,\"221\":28730,\"Ġzombie\":28731,\"VD\":28732,\"Ġmisunderstanding\":28733,\"Ġspam\":28734,\"ĠPapers\":28735,\"Ġcrocod\":28736,\"ENA\":28737,\"ĠJuven\":28738,\"ĠAbram\":28739,\"Ġbursts\":28740,\"atto\":28741,\"Ġturbulence\":28742,\"tty\":28743,\"sexual\":28744,\"Ġwaning\":28745,\"community\":28746,\"Government\":28747,\"Ġtranspl\":28748,\"??\":28749,\"Getting\":28750,\"ĠRare\":28751,\"prime\":28752,\"Ġlooting\":28753,\"Ġvalidate\":28754,\"ĠCreating\":28755,\"ĠCorruption\":28756,\"Ġspit\":28757,\"ĠFavorite\":28758,\"Kar\":28759,\"Ġadaptive\":28760,\"ĠART\":28761,\"Ġtorso\":28762,\"ĠIdent\":28763,\"Ġsubdivision\":28764,\"azo\":28765,\"Ġconsequently\":28766,\"Ġrotate\":28767,\"ĠWit\":28768,\"Ġestab\":28769,\"managed\":28770,\"ĠBound\":28771,\"Ġskim\":28772,\"198\":28773,\"ĠCorona\":28774,\"ĠâĿ\":28775,\"Ġwording\":28776,\"buck\":28777,\"iph\":28778,\"patrick\":28779,\"Help\":28780,\"flying\":28781,\"Ġracer\":28782,\"Ġfisherman\":28783,\"____\":28784,\"ackers\":28785,\"Ġpersisted\":28786,\"Ġmyths\":28787,\"Ġgarn\":28788,\"ologue\":28789,\"ĠApprentice\":28790,\"Ġhereby\":28791,\"Ġvulgar\":28792,\"ĠGinger\":28793,\"Ġtrait\":28794,\"ĠIdea\":28795,\"Ġfigur\":28796,\"ĠSchwarzenegger\":28797,\"ĠSafari\":28798,\"178\":28799,\"ĠAsians\":28800,\"775\":28801,\"ĠTriangle\":28802,\"Ġdemons\":28803,\"ĠOv\":28804,\"Ġanime\":28805,\"Broad\":28806,\"Ġmolecule\":28807,\"Ġdeposition\":28808,\"Ġbiodiversity\":28809,\"modern\":28810,\"Ġwallets\":28811,\"NH\":28812,\"planes\":28813,\"rats\":28814,\"ĠSeed\":28815,\"Ġ174\":28816,\"umed\":28817,\"Ġtouting\":28818,\"gre\":28819,\"ĠSEAL\":28820,\"Ġperpetrator\":28821,\"ĠGerrard\":28822,\"Ġallocations\":28823,\"Ġworsh\":28824,\"payment\":28825,\"bett\":28826,\"ĠIssues\":28827,\"ennis\":28828,\"eering\":28829,\"ĠMV\":28830,\"yi\":28831,\"hak\":28832,\"Ġ167\":28833,\"Ġorchestr\":28834,\"224\":28835,\"Ġsup\":28836,\"Ġleukemia\":28837,\"osures\":28838,\"575\":28839,\"Ġnoticeably\":28840,\"Ġparamilitary\":28841,\"ĠTHERE\":28842,\"Ġwaged\":28843,\"igrated\":28844,\"Ġdocumentaries\":28845,\"Ġsenseless\":28846,\"Ġbark\":28847,\"Ġgenetics\":28848,\"ĠAlbania\":28849,\"ĠCrypt\":28850,\"ĠSEO\":28851,\"Ġnightly\":28852,\"Ġfaults\":28853,\"279\":28854,\"ĠFerdinand\":28855,\"ĠSylv\":28856,\"Ġcalam\":28857,\"ĠMuller\":28858,\"ĠSpielberg\":28859,\"Boy\":28860,\"ĠUrs\":28861,\"Ġrug\":28862,\"Ġcolonies\":28863,\"ĠFunk\":28864,\"Ġlyric\":28865,\"ĠATT\":28866,\"anni\":28867,\"ĠNB\":28868,\"Ġthorn\":28869,\"Ġpertinent\":28870,\"188\":28871,\"Ġpartic\":28872,\"Head\":28873,\"Pad\":28874,\"Palestinian\":28875,\"ĠBarg\":28876,\"anical\":28877,\"beaut\":28878,\"onge\":28879,\"Ġgigantic\":28880,\"travel\":28881,\"Ġdownloading\":28882,\"Contin\":28883,\"whe\":28884,\"plane\":28885,\"Wil\":28886,\"IDA\":28887,\"Ele\":28888,\"ĠPAL\":28889,\"Ġbeams\":28890,\"ĠProud\":28891,\"ramer\":28892,\"Ġindependents\":28893,\"Ġtranslator\":28894,\"ĠBrah\":28895,\"ĠTrooper\":28896,\"aylor\":28897,\"pson\":28898,\"Ġguise\":28899,\"Ġdiffering\":28900,\"Ġtopple\":28901,\"ichen\":28902,\"ĠSeymour\":28903,\"deg\":28904,\"ĠMixed\":28905,\"Ġinvoluntary\":28906,\"Ġcountdown\":28907,\"ĠNarc\":28908,\"ĠAdults\":28909,\"Ġcoaster\":28910,\"Ġ342\":28911,\"ĠAcquisition\":28912,\"mone\":28913,\"Ġpenchant\":28914,\"Brian\":28915,\"Gh\":28916,\"Pres\":28917,\"enei\":28918,\"Ġreefs\":28919,\"ĠMaver\":28920,\"Ġdevised\":28921,\"ĠIMP\":28922,\"vict\":28923,\"Ġagility\":28924,\"ĠPayments\":28925,\"respected\":28926,\"Ġtuning\":28927,\"ĠFACE\":28928,\"actions\":28929,\"Ġyell\":28930,\"ĠLeaving\":28931,\"Ġsnowy\":28932,\"Saudi\":28933,\"Ġformations\":28934,\"Ġairborne\":28935,\"Ġdeed\":28936,\"ooks\":28937,\"Ġnamesake\":28938,\"Ġpunishable\":28939,\"Ġagg\":28940,\"oths\":28941,\"ĠFamous\":28942,\"ĠDeposit\":28943,\"Ġinduce\":28944,\"189\":28945,\"Ġhesitation\":28946,\"ĠBrowse\":28947,\"ople\":28948,\"reys\":28949,\"henko\":28950,\"Ġsecretaries\":28951,\"Ġintersections\":28952,\"Ġdiminishing\":28953,\"ints\":28954,\"Ġ1934\":28955,\"ĠInvestigative\":28956,\"ĠMexicans\":28957,\"ĠMahar\":28958,\"ibur\":28959,\"Ġstocking\":28960,\"gross\":28961,\"Ġasbestos\":28962,\"Ġagitation\":28963,\"ĠBST\":28964,\"Overall\":28965,\"Ġheats\":28966,\"ĠSpan\":28967,\"Ġimped\":28968,\"Ġtrusting\":28969,\"Pet\":28970,\"Ġegregious\":28971,\"Ġcomedians\":28972,\"zin\":28973,\"WIN\":28974,\"Ġchats\":28975,\"Ġexploding\":28976,\"ĠTort\":28977,\"Ġembraces\":28978,\"Ġneut\":28979,\"verson\":28980,\"ouncing\":28981,\"ĠFiber\":28982,\"Ġbaker\":28983,\"Ġunstoppable\":28984,\"ĠDial\":28985,\"cars\":28986,\"Marc\":28987,\"164\":28988,\"volt\":28989,\"Ġceased\":28990,\"EFF\":28991,\"Ġpromoters\":28992,\"Ġcircuits\":28993,\"Ġexcise\":28994,\"Ġseminars\":28995,\"ĠTiny\":28996,\"ĠImportant\":28997,\"ĠTup\":28998,\"Ġoutburst\":28999,\"ĠSOC\":29000,\"ĠWWII\":29001,\"Ġmerging\":29002,\"highly\":29003,\"ĠGmail\":29004,\"ozy\":29005,\"ĠKB\":29006,\"Ġlaboratories\":29007,\"knit\":29008,\"ĠClosed\":29009,\"Ġsurrounds\":29010,\"ĠVet\":29011,\"Ġcere\":29012,\"vard\":29013,\"ĠDeadpool\":29014,\"text\":29015,\"Ġinfusion\":29016,\"Ġcuc\":29017,\"ĠAtl\":29018,\"Ġbustling\":29019,\"ĠSettings\":29020,\"Ġ193\":29021,\"ryan\":29022,\"184\":29023,\"186\":29024,\"Ġswat\":29025,\"rane\":29026,\"Ġepidem\":29027,\"lando\":29028,\"Ġtestifying\":29029,\"Ġmoistur\":29030,\"ĠTens\":29031,\"Ġexemplary\":29032,\"ĠPump\":29033,\"Ġforcefully\":29034,\"ĠFare\":29035,\"Ġcomplicate\":29036,\"Fe\":29037,\"Di\":29038,\"ĠThy\":29039,\"Ġcompartment\":29040,\"ĠFiesta\":29041,\"Would\":29042,\"fitted\":29043,\"Ġcull\":29044,\"Ġcomedic\":29045,\"cyl\":29046,\"Ġwhichever\":29047,\"stic\":29048,\"Ġ213\":29049,\"Ġspills\":29050,\"Ġplasma\":29051,\"Ġdisguise\":29052,\"ĠCompass\":29053,\"ĠImmun\":29054,\"Ġscarf\":29055,\"Ġdisperse\":29056,\"Ġreckon\":29057,\"ĠTaste\":29058,\"root\":29059,\"ĠGAME\":29060,\"xx\":29061,\"Ġhomophobic\":29062,\"Ġdimin\":29063,\"/#\":29064,\"Ġ178\":29065,\"Ġgems\":29066,\"lio\":29067,\"informed\":29068,\"ample\":29069,\"XT\":29070,\"Ġrepression\":29071,\"ĠTakes\":29072,\"Ġhabitats\":29073,\"Ġmountainous\":29074,\"ĠMcH\":29075,\"ENC\":29076,\"Mobil\":29077,\"Ġreel\":29078,\"ĠTI\":29079,\"Ġauthorize\":29080,\"ĠAccept\":29081,\"ĠMetall\":29082,\"CCC\":29083,\"Ġwetlands\":29084,\"ĠWitch\":29085,\"heading\":29086,\"Ġintervals\":29087,\"ĠWitt\":29088,\"hene\":29089,\"Ġcomforting\":29090,\"ollen\":29091,\"ERN\":29092,\"ooky\":29093,\"etch\":29094,\"Ġassailant\":29095,\"announced\":29096,\"elin\":29097,\"plate\":29098,\"920\":29099,\"eating\":29100,\"induced\":29101,\"ĠIgor\":29102,\"ĠAmph\":29103,\"Ġpatented\":29104,\"posing\":29105,\"Ġextraordinarily\":29106,\"Ġfearless\":29107,\"mortem\":29108,\"ĠDraw\":29109,\"ĠRend\":29110,\"Son\":29111,\"ridden\":29112,\"ĠAdvantage\":29113,\"Ġ305\":29114,\"Ġroared\":29115,\"Str\":29116,\"Ġradioactive\":29117,\"Ġslur\":29118,\"ĠRear\":29119,\"affles\":29120,\"ĠPon\":29121,\"Ġost\":29122,\"umbs\":29123,\"ĠSlack\":29124,\"athom\":29125,\"baby\":29126,\"213\":29127,\"ĠSpending\":29128,\"ĠAccordingly\":29129,\"Ġclocks\":29130,\"archs\":29131,\"Ġsmugg\":29132,\"Ġmastermind\":29133,\"ĠKlaus\":29134,\"alpha\":29135,\"Ġspoiled\":29136,\"264\":29137,\"Pod\":29138,\"Ġflared\":29139,\"Ġcomposure\":29140,\"ĠCAM\":29141,\"Ġrestruct\":29142,\"Ġtasted\":29143,\"ĠKimber\":29144,\"Ġupheaval\":29145,\"CHAR\":29146,\"ĠGeo\":29147,\"itations\":29148,\"Ġbegged\":29149,\"UX\":29150,\"Authorities\":29151,\"ĠEngel\":29152,\"ĠHOME\":29153,\"Ġratt\":29154,\"Ġquickest\":29155,\"475\":29156,\"ĠSting\":29157,\"ĠICO\":29158,\"yu\":29159,\"Ġdefy\":29160,\"Prince\":29161,\"cards\":29162,\"Ġovertake\":29163,\"Ġretrieved\":29164,\"ĠNavajo\":29165,\"Ġpastry\":29166,\"ĠLange\":29167,\"Ġentrusted\":29168,\"ĠCull\":29169,\"aler\":29170,\"Ġdinosaurs\":29171,\"Ġbragging\":29172,\"ĠAlley\":29173,\"meier\":29174,\"ĠAssuming\":29175,\"Ġana\":29176,\"omatic\":29177,\"Brend\":29178,\"acted\":29179,\"Ġexhaustive\":29180,\"Ġunfit\":29181,\"Several\":29182,\"gap\":29183,\"Ġtet\":29184,\"228\":29185,\"Sk\":29186,\"302\":29187,\"Ġdeflect\":29188,\"Ġ179\":29189,\"226\":29190,\"Ġadorned\":29191,\"ĠSpread\":29192,\"Ġthirds\":29193,\"ĠSemi\":29194,\"Ġdescend\":29195,\"Ġaccumulate\":29196,\"Ġflavours\":29197,\"Ġinvoked\":29198,\"ĠAnge\":29199,\"Ġprofess\":29200,\"unks\":29201,\"ĠKickstarter\":29202,\"ENTS\":29203,\"ĠRw\":29204,\"Ġchatter\":29205,\"ĠPOS\":29206,\"Ġcollaborators\":29207,\"ĠEW\":29208,\"ĠMarkus\":29209,\"Ġimpair\":29210,\"Ġbolt\":29211,\"Ġglue\":29212,\"Ġloosely\":29213,\"ĠSUM\":29214,\"Ġhydraulic\":29215,\"Ġpredatory\":29216,\"Charles\":29217,\"cond\":29218,\"Ġspawned\":29219,\"Fr\":29220,\"174\":29221,\"Ġtame\":29222,\"Ġaggrav\":29223,\"Ġchrist\":29224,\"true\":29225,\"ivable\":29226,\"Ġhen\":29227,\"ĠKut\":29228,\"Ġskyrocket\":29229,\"Ġeg\":29230,\"Ġveterinarian\":29231,\"ĠStats\":29232,\"Kit\":29233,\"Ġbiologist\":29234,\"Spe\":29235,\"Ġantenna\":29236,\"Ġsust\":29237,\"fill\":29238,\"Ġpayload\":29239,\"227\":29240,\"Ġlivestream\":29241,\"ORN\":29242,\"ĠAbel\":29243,\"Ġdeception\":29244,\"ussen\":29245,\"Britain\":29246,\"partisan\":29247,\"Ġbrowse\":29248,\"Ġmelan\":29249,\"172\":29250,\"ĠNumerous\":29251,\"ĠMansion\":29252,\"Ġassailants\":29253,\"Â£\":29254,\"olerance\":29255,\"Ġdirectives\":29256,\"ĠInteg\":29257,\"zers\":29258,\"Ġduct\":29259,\"ĠHonestly\":29260,\"ĠImmediately\":29261,\"ixty\":29262,\"Ġdiagnose\":29263,\"Ġimplication\":29264,\"ĠiPads\":29265,\"testers\":29266,\"riots\":29267,\"Ġrespons\":29268,\"XP\":29269,\"pes\":29270,\"875\":29271,\"Ġ199\":29272,\"ĠPoe\":29273,\"303\":29274,\"Ġailments\":29275,\"ĠCarrier\":29276,\"Ġeject\":29277,\"Ġrestroom\":29278,\"Drive\":29279,\"manufact\":29280,\"Ġcompens\":29281,\"Ġglossy\":29282,\"Ġrecovers\":29283,\"Ġthinner\":29284,\"Ġdescendants\":29285,\"antle\":29286,\"Beaut\":29287,\"competitive\":29288,\"ĠRobotics\":29289,\"Ġpretext\":29290,\"233\":29291,\"Ġflanked\":29292,\"ĠâĻ\":29293,\"Ġguts\":29294,\"Ġwee\":29295,\"Ġaccents\":29296,\"mc\":29297,\"Ġgrapp\":29298,\"ĠNathaniel\":29299,\"ĠMikhail\":29300,\"Ġobligated\":29301,\"Ġmanoeuv\":29302,\"Ġechoing\":29303,\"Ġ189\":29304,\"ĠDevice\":29305,\"isd\":29306,\"Ġloopholes\":29307,\"Ġbehold\":29308,\"ĠMerry\":29309,\"Ġfunn\":29310,\"Ġnuanced\":29311,\"667\":29312,\"ELY\":29313,\"ĠTasmania\":29314,\"ĠSaddam\":29315,\"Ġquizz\":29316,\"military\":29317,\"cient\":29318,\"Ġoutlaw\":29319,\"ĠAudit\":29320,\"ĠBoom\":29321,\"Ġcrim\":29322,\"asured\":29323,\"ĠApps\":29324,\"ĠKush\":29325,\"onica\":29326,\"Ġamput\":29327,\"signed\":29328,\"ĠMEN\":29329,\"ĠRosenberg\":29330,\"Ġvide\":29331,\"ĠDirection\":29332,\"Ġfountain\":29333,\"TW\":29334,\"ĠCARE\":29335,\"Ġreassured\":29336,\"Food\":29337,\"Ġdepressing\":29338,\"ĠWhilst\":29339,\"reatment\":29340,\"Ġspelled\":29341,\"Ġhipp\":29342,\"ĠPeach\":29343,\"hound\":29344,\"Harry\":29345,\"Ġcatalogue\":29346,\"ĠCommun\":29347,\"Ġnurture\":29348,\"rush\":29349,\"ĠPopulation\":29350,\"ĠNTS\":29351,\"ĠElectrical\":29352,\"rounded\":29353,\"Ġblending\":29354,\"Ġ223\":29355,\"alities\":29356,\"ilation\":29357,\"eas\":29358,\"estate\":29359,\"Ġnarrowing\":29360,\"ĠTreasure\":29361,\"192\":29362,\"Ġwhims\":29363,\"Ġrobber\":29364,\"Ġsoaked\":29365,\"nian\":29366,\"Ġcongest\":29367,\"ĠYosemite\":29368,\"notes\":29369,\"icer\":29370,\"ĠGuardians\":29371,\"ĠFrozen\":29372,\"Ġ187\":29373,\"Ġhandcuffs\":29374,\"Someone\":29375,\"Ġenshr\":29376,\"gency\":29377,\"ĠCube\":29378,\"Ġprinters\":29379,\"Ġundercut\":29380,\"ĠSolution\":29381,\"rosis\":29382,\"ĠHumanity\":29383,\"Ġsucks\":29384,\"ĠSick\":29385,\"Tax\":29386,\"Ġtablespoon\":29387,\"ĠTrin\":29388,\"ĠArchive\":29389,\"Mom\":29390,\"ĠSAY\":29391,\"Ġdrifting\":29392,\"ĠFarage\":29393,\"Ġforging\":29394,\"WM\":29395,\"ĠEleanor\":29396,\"USH\":29397,\"Ġemph\":29398,\"Ġcareless\":29399,\"Ġspew\":29400,\"Ġinsensitive\":29401,\"Ġawhile\":29402,\"Ġcit\":29403,\"opened\":29404,\"ĠFem\":29405,\"Ġvapor\":29406,\"Ġdownt\":29407,\"ylene\":29408,\"Ġclut\":29409,\"Ġculp\":29410,\"1990\":29411,\"Ġdisgruntled\":29412,\"Students\":29413,\"uttering\":29414,\"gyn\":29415,\"vre\":29416,\"Ġrapes\":29417,\"division\":29418,\"ĠCalendar\":29419,\"tal\":29420,\"icts\":29421,\"caliber\":29422,\"ĠFighters\":29423,\"ĠUnc\":29424,\"163\":29425,\"ĠRogue\":29426,\"Ġregistrations\":29427,\"Ġundermines\":29428,\"ĠPunch\":29429,\"Ġdramas\":29430,\"176\":29431,\"Ġslider\":29432,\"ĠFlore\":29433,\"Ø±\":29434,\"Ġbru\":29435,\"inelli\":29436,\"Ġdisparities\":29437,\"Ø§\":29438,\"Ġreferrals\":29439,\"ĠCharges\":29440,\"Ġbreeds\":29441,\"ĠMEP\":29442,\"288\":29443,\"Ġmouths\":29444,\"Ġsideways\":29445,\"Ġbelievers\":29446,\"ppard\":29447,\"Ġhotter\":29448,\"Ġunderestimated\":29449,\"Ġjelly\":29450,\"525\":29451,\"ĠCMS\":29452,\"ĠWeiner\":29453,\"Ġguarding\":29454,\"Ġampl\":29455,\"ĠKidd\":29456,\"UF\":29457,\"orient\":29458,\"max\":29459,\"Ash\":29460,\"Ġwander\":29461,\"Ġ..........\":29462,\"ĠDempsey\":29463,\"ĠToken\":29464,\"chat\":29465,\"Justin\":29466,\"equipped\":29467,\"ĠBI\":29468,\"Ġsins\":29469,\"Ġnond\":29470,\"ursion\":29471,\"Ġcoc\":29472,\"Ġmailing\":29473,\"ĠArchitect\":29474,\"Ġhaunting\":29475,\"Ġpont\":29476,\"Ġascertain\":29477,\"Ġwig\":29478,\"Ġskysc\":29479,\"Ġarg\":29480,\"ĠItalians\":29481,\"/?\":29482,\"Ġ----------------------------------------------------------------\":29483,\"ĠPrecision\":29484,\"EPA\":29485,\"Ġhotly\":29486,\"Ġcircumvent\":29487,\"ĠEcc\":29488,\"Ġmerch\":29489,\"akov\":29490,\"Ġunab\":29491,\"heres\":29492,\"Ġsubcommittee\":29493,\"ĠDiscuss\":29494,\"ĠChallenger\":29495,\"crafted\":29496,\"Ġcanine\":29497,\"osphere\":29498,\"Ġspider\":29499,\"Ġteachings\":29500,\"atos\":29501,\"Ġuniversally\":29502,\"Ġturbine\":29503,\"ĠLO\":29504,\"ĠMAG\":29505,\"Ġpassers\":29506,\"Ġroundup\":29507,\"Ġdenounce\":29508,\"ĠSpiegel\":29509,\"until\":29510,\"Ġshaved\":29511,\"Ġdisdain\":29512,\"Nazi\":29513,\"Ġnewfound\":29514,\"Ġspontaneous\":29515,\"Ġmash\":29516,\"ĠDispatch\":29517,\"Ġsunrise\":29518,\"ogged\":29519,\"Ġfuss\":29520,\"Ġeas\":29521,\"acci\":29522,\"ĠTarg\":29523,\"Ġhash\":29524,\"lict\":29525,\"Ġmisc\":29526,\"ĠSched\":29527,\"guy\":29528,\"linger\":29529,\"warm\":29530,\"ipel\":29531,\"ĠGork\":29532,\"Ġdispatcher\":29533,\"Ġ315\":29534,\"Ġfinely\":29535,\"Ġreliably\":29536,\"Ġrupt\":29537,\"Ġnegligent\":29538,\"Ġendorsements\":29539,\"ĠOrient\":29540,\"Ġelectro\":29541,\"haired\":29542,\"Ġphysique\":29543,\"wine\":29544,\"Ġadolescents\":29545,\"Ġ184\":29546,\"alth\":29547,\"Ġvalidated\":29548,\"izzard\":29549,\"ĠPeck\":29550,\"Ġemblem\":29551,\"status\":29552,\"ĠJungle\":29553,\"orius\":29554,\"Ġeccentric\":29555,\"Ġfolding\":29556,\"poor\":29557,\"ĠTHC\":29558,\"appers\":29559,\"Ġscripted\":29560,\"239\":29561,\"ĠPreferred\":29562,\"digital\":29563,\"Ġsharper\":29564,\"Ġportrays\":29565,\"rative\":29566,\"238\":29567,\"Ġ183\":29568,\"Ġuneasy\":29569,\"ĠRI\":29570,\"Ġvil\":29571,\"171\":29572,\"Ġspoil\":29573,\"ĠPricing\":29574,\"ĠHardware\":29575,\"Ġ188\":29576,\"Ġhorrendous\":29577,\"Ġostensibly\":29578,\"nah\":29579,\"Ġgadget\":29580,\"ADS\":29581,\"coat\":29582,\"Ġexhausting\":29583,\"Ġdraining\":29584,\"arate\":29585,\"ĠBulgarian\":29586,\"emo\":29587,\"Ġhier\":29588,\"Ġguitars\":29589,\"ieties\":29590,\"assed\":29591,\"ĠYaz\":29592,\"Ġaggress\":29593,\"ĠBG\":29594,\"vik\":29595,\"Ġneatly\":29596,\"Ġpixel\":29597,\"Ġintimacy\":29598,\"ĠRug\":29599,\"Ġ512\":29600,\"Ġnarrated\":29601,\"Ġmast\":29602,\"ĠNos\":29603,\"ĠHung\":29604,\"reciation\":29605,\"ĠChandra\":29606,\"Ġbios\":29607,\"ĠEnded\":29608,\"lique\":29609,\"ĠCambod\":29610,\"Ġworrisome\":29611,\"ĠEQ\":29612,\"Ġnovelist\":29613,\"ĠDynamic\":29614,\"ĠMIC\":29615,\"Ġdisposed\":29616,\"Ġbrackets\":29617,\"Ġhaircut\":29618,\"ĠLana\":29619,\"Ġlull\":29620,\"Ġbillboard\":29621,\"ĠReverend\":29622,\"ĠNAV\":29623,\"borgh\":29624,\"Ġadrenaline\":29625,\"Ġseeming\":29626,\"ĠPCB\":29627,\"ĠBridgewater\":29628,\"Ġsquirrel\":29629,\"262\":29630,\"write\":29631,\"Ġstabilization\":29632,\"wild\":29633,\"Ġsecession\":29634,\"Ġpacket\":29635,\"AMES\":29636,\"licted\":29637,\"Ġmalnutrition\":29638,\"claimed\":29639,\"Ġcharred\":29640,\"Ġtragically\":29641,\"Published\":29642,\"Ġrepealed\":29643,\"ĠSawyer\":29644,\"ĠMormon\":29645,\"resolution\":29646,\"ĠSaud\":29647,\"Henry\":29648,\"Ġdiscontin\":29649,\"Ġsnag\":29650,\"danger\":29651,\"Ġmixes\":29652,\"Ġupbringing\":29653,\"Ġlimb\":29654,\"ĠFantastic\":29655,\"Sim\":29656,\"ĠAugustine\":29657,\"ĠGreeks\":29658,\"cod\":29659,\"ĠHistorically\":29660,\"mire\":29661,\"register\":29662,\"ĠKund\":29663,\"Ġdebilitating\":29664,\"Chat\":29665,\"ĠTau\":29666,\"Ã¯\":29667,\"lower\":29668,\"pie\":29669,\"Ġ430\":29670,\"Ġnascent\":29671,\"Ġ375\":29672,\"Ġbum\":29673,\"WI\":29674,\"Netflix\":29675,\"whether\":29676,\"Ġdearly\":29677,\"eff\":29678,\"PRES\":29679,\"Ġlandmarks\":29680,\"Ġculminating\":29681,\"Ġmigrate\":29682,\"balanced\":29683,\"Ġregulars\":29684,\"Ġmodification\":29685,\"Ġdips\":29686,\"ĠRedmond\":29687,\"ationally\":29688,\"atsu\":29689,\"Ġphilosophical\":29690,\"Ġtyping\":29691,\"Ġunreal\":29692,\"Ġboiled\":29693,\"Ġblight\":29694,\"Ġdru\":29695,\"ĠGaddafi\":29696,\"Ġnour\":29697,\"Ġsequential\":29698,\"Ġaugment\":29699,\"ĠEuras\":29700,\"ĠWiley\":29701,\"endar\":29702,\"Ġacronym\":29703,\"esteem\":29704,\"ĠMajesty\":29705,\"Ġgrips\":29706,\"Ġobsolete\":29707,\"nos\":29708,\"Made\":29709,\"ogie\":29710,\"ĠLiver\":29711,\"ĠDonetsk\":29712,\"Ġdynam\":29713,\"tel\":29714,\"bring\":29715,\"Ġknit\":29716,\"Ġfirepower\":29717,\"Ġprepaid\":29718,\"ĠRaphael\":29719,\"Ġsensing\":29720,\"720\":29721,\"WN\":29722,\"Nor\":29723,\"puted\":29724,\"Ġbureaucrats\":29725,\"ĠAdjust\":29726,\"Ġintensely\":29727,\"Ġsunscreen\":29728,\"Ho\":29729,\"ĠYelp\":29730,\"ĠPU\":29731,\"ĠSerge\":29732,\"ĠCyp\":29733,\"ELF\":29734,\"ĠGuns\":29735,\"Ġteamwork\":29736,\"ĠBib\":29737,\"ĠMaintenance\":29738,\"perate\":29739,\"Ġwiping\":29740,\"Ġcharcoal\":29741,\"ordan\":29742,\"International\":29743,\"Ġbehaving\":29744,\"Ġsoftened\":29745,\"ĠIncreased\":29746,\"Ġunfl\":29747,\"470\":29748,\"Ġinformative\":29749,\"Ġnovelty\":29750,\"Ġavoidance\":29751,\"Ġteasing\":29752,\"matic\":29753,\"Ġmaid\":29754,\"ĠPell\":29755,\"Ġcounterterrorism\":29756,\"ĠGabe\":29757,\"ications\":29758,\"ĠConnection\":29759,\"ĠInquiry\":29760,\"isin\":29761,\"orama\":29762,\"Ġcorpse\":29763,\"Ġpractitioner\":29764,\"itto\":29765,\"UA\":29766,\"Ġforestry\":29767,\"Ġlic\":29768,\"Ġrevolves\":29769,\"Ġcalculating\":29770,\"Ġpuppet\":29771,\"ulously\":29772,\"ĠPebble\":29773,\"Dep\":29774,\"Ġupholding\":29775,\"Ġcarving\":29776,\"Ġwartime\":29777,\"Ġenvy\":29778,\"Ġencro\":29779,\"ĠPunk\":29780,\"ĠAdminist\":29781,\"ucha\":29782,\"Ġbattleground\":29783,\"Ġlol\":29784,\"uable\":29785,\"Ġunheard\":29786,\"ĠSpur\":29787,\"phony\":29788,\"Ġcarc\":29789,\"ĠSut\":29790,\"Ġpollutants\":29791,\"Cr\":29792,\"Ġvigorous\":29793,\"355\":29794,\"ĠMarriage\":29795,\"Ġstaffed\":29796,\"fecture\":29797,\"ĠArabs\":29798,\"supported\":29799,\"Ġmanpower\":29800,\"ĠSatellite\":29801,\"None\":29802,\"Ġqueues\":29803,\"Ġinsightful\":29804,\"Ġinterchange\":29805,\"Rel\":29806,\"Ġsolemn\":29807,\"Ġsmuggled\":29808,\"upt\":29809,\"Ġ171\":29810,\"Ġparallels\":29811,\"intelligence\":29812,\"punk\":29813,\"Ġrecycle\":29814,\"Ġdecorative\":29815,\"Ġshar\":29816,\"arrell\":29817,\"iances\":29818,\"ĠBolivia\":29819,\"Ġstrengthens\":29820,\"430\":29821,\"Ġhardships\":29822,\"Ġsignalling\":29823,\"Ġunthinkable\":29824,\"READ\":29825,\"Ġtad\":29826,\"picked\":29827,\"Ġarmor\":29828,\"Ġcores\":29829,\"ĠMatrix\":29830,\"Ġdj\":29831,\"Ġevolutionary\":29832,\"ĠBermuda\":29833,\"OE\":29834,\"organized\":29835,\"Ġrelentlessly\":29836,\"sol\":29837,\"ĠMamm\":29838,\"Ġpounding\":29839,\"Weather\":29840,\"Ġrab\":29841,\"Ġsweets\":29842,\"funding\":29843,\"ĠHUD\":29844,\"ĠSoldier\":29845,\"reed\":29846,\"released\":29847,\"Ġcontainment\":29848,\"alid\":29849,\"ĠNikon\":29850,\"Ġcervical\":29851,\"Ġign\":29852,\"Ġalias\":29853,\"Ġoptimized\":29854,\"Ġasserting\":29855,\"ĠAFTER\":29856,\"Ġflatt\":29857,\"Ġdinosaur\":29858,\"ĠRefugees\":29859,\"ĠAnch\":29860,\"Ġadjustable\":29861,\"Ġroaring\":29862,\"Ġpilgrimage\":29863,\"Ġcowboy\":29864,\"Ġentails\":29865,\"ractions\":29866,\"EY\":29867,\"undy\":29868,\"ĠKuh\":29869,\"inges\":29870,\"ĠTerra\":29871,\"ĠEscape\":29872,\"Ġrundown\":29873,\"Ġstriped\":29874,\"KN\":29875,\"ocations\":29876,\"IDENT\":29877,\"IGH\":29878,\"Ġavoids\":29879,\"Moh\":29880,\"ĠLS\":29881,\"lbs\":29882,\"ĠAttempt\":29883,\"Ġtriangle\":29884,\"Ġclimax\":29885,\"Ġhp\":29886,\"Ġallot\":29887,\"learning\":29888,\"ĠJFK\":29889,\"Justice\":29890,\"OUT\":29891,\"ĠHER\":29892,\"ĠLect\":29893,\"Ġtrench\":29894,\"edar\":29895,\"Ġreservoirs\":29896,\"uid\":29897,\"rf\":29898,\"162\":29899,\"Ġinterfered\":29900,\"Ġemit\":29901,\"these\":29902,\"444\":29903,\"ĠLeather\":29904,\"essing\":29905,\"ĠEighth\":29906,\"uckle\":29907,\"Breaking\":29908,\"Ġunresolved\":29909,\"Ġgoose\":29910,\"252\":29911,\"platform\":29912,\"atus\":29913,\"Ġcomplexion\":29914,\"ĠBUS\":29915,\"Ġstruct\":29916,\"middle\":29917,\"Sat\":29918,\"ĠWHERE\":29919,\"LB\":29920,\"redible\":29921,\"vered\":29922,\"Louis\":29923,\"ĠBaz\":29924,\"Eye\":29925,\"safety\":29926,\"Ġhypothetical\":29927,\"Ġbowel\":29928,\"Ġuntouched\":29929,\"312\":29930,\"ĠPric\":29931,\"Ġastounding\":29932,\"meet\":29933,\"Aaron\":29934,\"ĠWoo\":29935,\"236\":29936,\"ĠShape\":29937,\"Ġdrifted\":29938,\"Ġtile\":29939,\"ĠGrim\":29940,\"Ġundeniable\":29941,\"Ġ..\":29942,\"Ġradius\":29943,\"Ġovarian\":29944,\"ĠSeriously\":29945,\"verning\":29946,\"Ġassertions\":29947,\"oxic\":29948,\"231\":29949,\"ĠViz\":29950,\"Jackson\":29951,\"ĠSno\":29952,\"Ġboycot\":29953,\"okingly\":29954,\"ousse\":29955,\"proclaimed\":29956,\"Ġblazing\":29957,\"Ġinefficient\":29958,\"Ġfig\":29959,\"Ġbooze\":29960,\"259\":29961,\"agus\":29962,\"statement\":29963,\"Ġlocom\":29964,\"Ġtacos\":29965,\"Ġmemos\":29966,\"gender\":29967,\"ĠOrt\":29968,\"263\":29969,\"Ġintervening\":29970,\"Soc\":29971,\"University\":29972,\"ĠPis\":29973,\"ĠReturns\":29974,\"ĠPAN\":29975,\"Ġultrasound\":29976,\"Ġcoherent\":29977,\"tracking\":29978,\"rieved\":29979,\"383\":29980,\"Ġqualitative\":29981,\"uld\":29982,\"ĠGiovanni\":29983,\"Ġstorylines\":29984,\"Ġdarkest\":29985,\"Ġvelvet\":29986,\"RIP\":29987,\"Ġcompatibility\":29988,\"Ġtroll\":29989,\"CN\":29990,\"Found\":29991,\"ĠOu\":29992,\"Ġtease\":29993,\"Ġvested\":29994,\"Ġprovocation\":29995,\"Ġimprovised\":29996,\"Ġactivation\":29997,\"unte\":29998,\"ĠMonteneg\":29999,\"ĠJOHN\":30000,\"ĠReact\":30001,\"Ġpolluted\":30002,\"217\":30003,\"Ġmushroom\":30004,\"Ġdisconnected\":30005,\"ĠVoices\":30006,\"asu\":30007,\"Ġsensory\":30008,\"REE\":30009,\"Ġmonarchy\":30010,\"Ġ173\":30011,\"doing\":30012,\"involved\":30013,\"ĠJonah\":30014,\"Ġtoxins\":30015,\"Ġtv\":30016,\"Ġacademia\":30017,\"IQ\":30018,\"Mor\":30019,\"ĠStraight\":30020,\"ĠRN\":30021,\"ĠâĹı\":30022,\"Ġpear\":30023,\"187\":30024,\"Ġendeavors\":30025,\"ĠTurbo\":30026,\"Ġducks\":30027,\"ĠRamsay\":30028,\"Ġoutpatient\":30029,\"Ġcomprehend\":30030,\"UNE\":30031,\"Ġbriefings\":30032,\"total\":30033,\"Ġmigr\":30034,\"always\":30035,\"Ġmoot\":30036,\"ĠRider\":30037,\"Ġbiblical\":30038,\"Form\":30039,\"Ġcurry\":30040,\"Ġexquisite\":30041,\"385\":30042,\"244\":30043,\"Ġattendants\":30044,\"Ġcabinets\":30045,\"nton\":30046,\"Baby\":30047,\"Honestly\":30048,\"ĠFIRE\":30049,\"211\":30050,\"itech\":30051,\"ĠProsper\":30052,\"Ġchops\":30053,\"odic\":30054,\"Rod\":30055,\"job\":30056,\"orset\":30057,\"ĠAry\":30058,\"obic\":30059,\"ĠNil\":30060,\"isable\":30061,\"Ġorche\":30062,\"Ġtrivial\":30063,\"ĠZy\":30064,\"ĠXP\":30065,\"Ġendorsing\":30066,\"ĠLIM\":30067,\"adish\":30068,\"237\":30069,\"ĠLaws\":30070,\"heid\":30071,\"ĠSignature\":30072,\"ĠVern\":30073,\"ĠBland\":30074,\"ansk\":30075,\"Ġrepository\":30076,\"ĠPetra\":30077,\"Enter\":30078,\"Ġtruths\":30079,\"Ġbordering\":30080,\"Ġpenn\":30081,\"Ġsimplified\":30082,\"zn\":30083,\"ĠCree\":30084,\"Ġ181\":30085,\"Hi\":30086,\"ĠGreenberg\":30087,\"Ġprematurely\":30088,\"ĠSass\":30089,\"Ġwrecked\":30090,\"Ġheinous\":30091,\"415\":30092,\"Turn\":30093,\"zl\":30094,\"amental\":30095,\"ĠBraz\":30096,\"fing\":30097,\"ĠAngle\":30098,\"ĠPhantom\":30099,\"agra\":30100,\"ĠShack\":30101,\"Ġhomegrown\":30102,\"Ġalright\":30103,\"AME\":30104,\"ĠKN\":30105,\"Ġclicks\":30106,\"Ġmanned\":30107,\"ĠScope\":30108,\"Ġextras\":30109,\"Ġclinicians\":30110,\"321\":30111,\"African\":30112,\"Ġjuices\":30113,\"Ġrefere\":30114,\"****\":30115,\"ambling\":30116,\"since\":30117,\"Ġvoic\":30118,\"QB\":30119,\"ĠAtmospheric\":30120,\"Mat\":30121,\"Ġperpetrated\":30122,\"ĠSteps\":30123,\"Fit\":30124,\"Ġsilenced\":30125,\"Ġbonded\":30126,\"Ġquantify\":30127,\"Houston\":30128,\"ocracy\":30129,\"Ġfreeing\":30130,\"pipe\":30131,\"corn\":30132,\"rones\":30133,\"ooked\":30134,\"ĠSuz\":30135,\"Ġunaccount\":30136,\"196\":30137,\"Ġlogos\":30138,\"ĠFurious\":30139,\"ĠSpart\":30140,\"urst\":30141,\"itri\":30142,\"ĠZub\":30143,\"ĠActual\":30144,\"Ġslee\":30145,\"Ġgag\":30146,\"Ġmetabolism\":30147,\"ĠDesigned\":30148,\"Ġpedigree\":30149,\"Ġcoolest\":30150,\"âĿ\":30151,\"iuses\":30152,\"ĠYellowstone\":30153,\"Ġinformant\":30154,\"Ġushered\":30155,\"ĠGarg\":30156,\"thel\":30157,\"Hop\":30158,\"Ġrepetitive\":30159,\"flag\":30160,\"Ġunmarked\":30161,\"ĠBrave\":30162,\"Ġincur\":30163,\"reading\":30164,\"ppel\":30165,\"lah\":30166,\"ateurs\":30167,\"286\":30168,\"ĠAtomic\":30169,\"Ġappliance\":30170,\")'\":30171,\"traditional\":30172,\"Ġdads\":30173,\"Ġregimen\":30174,\"Ġinfrared\":30175,\"Ġdotted\":30176,\"Ġtails\":30177,\"Ġhorrors\":30178,\"uments\":30179,\"Ġdub\":30180,\"lighting\":30181,\"Ġunearthed\":30182,\"assisted\":30183,\"ĠSpiel\":30184,\"trial\":30185,\"Ġpersever\":30186,\"MAX\":30187,\"Ġicing\":30188,\"Energy\":30189,\"Ġ1943\":30190,\"move\":30191,\"Error\":30192,\"Ġliter\":30193,\"ĠCly\":30194,\"Ari\":30195,\"Ġgranite\":30196,\"Ġcropped\":30197,\"ĠRD\":30198,\"ĠREM\":30199,\"TX\":30200,\"Ġdispleasure\":30201,\"ĠComfort\":30202,\"Ġunsettling\":30203,\"Ġscratching\":30204,\"866\":30205,\"eton\":30206,\"560\":30207,\"Ġcommonplace\":30208,\"Ġreproduced\":30209,\"ggie\":30210,\"Ġschooling\":30211,\"Ġreprim\":30212,\"Ġdarling\":30213,\"huge\":30214,\"ĠDante\":30215,\"cp\":30216,\"heastern\":30217,\"Ġeduc\":30218,\"Digital\":30219,\"Ġwrath\":30220,\"Ġwatering\":30221,\"ĠTail\":30222,\"Ġdegradation\":30223,\"530\":30224,\"usive\":30225,\"ĠXu\":30226,\"ĠAH\":30227,\"Ġclassy\":30228,\"ĠSET\":30229,\"Ġcriminally\":30230,\"dependent\":30231,\"ĠAlps\":30232,\"Ġnotwithstanding\":30233,\"Ġfamiliarity\":30234,\"ĠAPP\":30235,\"aurus\":30236,\"gments\":30237,\"Mid\":30238,\"Ġepilepsy\":30239,\"Ġresemblance\":30240,\"brush\":30241,\"Ġ333\":30242,\"Ġliberated\":30243,\"ĠBeng\":30244,\"ĠLans\":30245,\"Ġtraff\":30246,\"ihu\":30247,\"establish\":30248,\"Ġcort\":30249,\"Rick\":30250,\"Ġplugged\":30251,\"onement\":30252,\"ĠAccounting\":30253,\"Ġreconstruct\":30254,\"Pop\":30255,\"Ġincapable\":30256,\"aho\":30257,\"ĠDexter\":30258,\"Ġpitted\":30259,\"Ġbathing\":30260,\"Ġdun\":30261,\"Ġexplor\":30262,\"ĠMidnight\":30263,\"Ġactiv\":30264,\"iann\":30265,\"likely\":30266,\"acons\":30267,\"owicz\":30268,\"Ġnegativity\":30269,\"Ġfreel\":30270,\"ewitness\":30271,\"Ġinj\":30272,\"Stephen\":30273,\"Ġshredded\":30274,\"Ġprepar\":30275,\"Script\":30276,\"Ġcorrectional\":30277,\"Ġcommits\":30278,\"hai\":30279,\"activity\":30280,\"Imp\":30281,\"Ġstumble\":30282,\"Ġcache\":30283,\"ĠPromise\":30284,\"Ġprecinct\":30285,\"Ġmulticultural\":30286,\"Ġsubstitutes\":30287,\"Ġshortened\":30288,\"ovable\":30289,\"Ġfasting\":30290,\"Ġinfused\":30291,\"Ġbulldo\":30292,\"alm\":30293,\"Ġadjoining\":30294,\"Ġmultiplayer\":30295,\"ĠAlien\":30296,\"Ġpund\":30297,\"ethyl\":30298,\"Ġbliss\":30299,\"ĠDecision\":30300,\"Ġbab\":30301,\"Ġangrily\":30302,\"another\":30303,\"oled\":30304,\"ainted\":30305,\"ĠPriest\":30306,\"Ġdraped\":30307,\"ĠPersonally\":30308,\"Ġstomp\":30309,\"ĠWolfgang\":30310,\"Ġoste\":30311,\"itches\":30312,\"Ġhoops\":30313,\"ĠJO\":30314,\"Ġsche\":30315,\"ĠZan\":30316,\"Ġcleans\":30317,\"Ġclimbs\":30318,\"Ġelectronically\":30319,\"243\":30320,\"ocy\":30321,\"gall\":30322,\"ĠREAL\":30323,\"Ġmurky\":30324,\"Ġmodernization\":30325,\"tub\":30326,\"Really\":30327,\"Ġlax\":30328,\"Ġdoubted\":30329,\"yden\":30330,\"ĠPrevent\":30331,\"UTERS\":30332,\"Ġoverride\":30333,\"ĠSAF\":30334,\"Ġcoun\":30335,\"Ġexcerpts\":30336,\"Ġmotivations\":30337,\"Ġdecency\":30338,\"Ġastronomers\":30339,\"orical\":30340,\"Ġaltering\":30341,\"Ġ232\":30342,\"described\":30343,\"omic\":30344,\"Ġexh\":30345,\"Ġknocks\":30346,\"ĠRiot\":30347,\"ĠPurs\":30348,\"equal\":30349,\"pleting\":30350,\"llan\":30351,\"ĠSOL\":30352,\"iator\":30353,\"ILE\":30354,\"ĠWM\":30355,\"Ġdefences\":30356,\"Ġforearm\":30357,\"Toronto\":30358,\"526\":30359,\"Ġacne\":30360,\"Ġthirteen\":30361,\"itiz\":30362,\"akable\":30363,\"charges\":30364,\"Ġinaction\":30365,\"Ġbred\":30366,\"Ġdeficiency\":30367,\"Ġintrigue\":30368,\"opoly\":30369,\"ĠCamer\":30370,\"ĠMelt\":30371,\"Ġunlawfully\":30372,\"Ġpenetrate\":30373,\"ĠUsed\":30374,\"ĠDirty\":30375,\"Ġexcerpt\":30376,\"ĠYen\":30377,\"ĠCARD\":30378,\"Ġcher\":30379,\"ĠChallenges\":30380,\"ieves\":30381,\"Ġambush\":30382,\"Data\":30383,\"eeks\":30384,\"Ġgiveaway\":30385,\"Ġpawn\":30386,\"Ġtransf\":30387,\"renched\":30388,\"Ġmoderately\":30389,\"Ġnumbered\":30390,\"ĠIntegrity\":30391,\"ĠHOU\":30392,\"ĠHDMI\":30393,\"Royal\":30394,\"LT\":30395,\"ĠDirk\":30396,\"izon\":30397,\"Ġ227\":30398,\"Ġdisagrees\":30399,\"ĠNinth\":30400,\"Ġincrement\":30401,\"ĠGlory\":30402,\"suff\":30403,\"Ġartery\":30404,\"ĠEmployee\":30405,\"bum\":30406,\"ĠEditorial\":30407,\"Kh\":30408,\"ĠPremiere\":30409,\"ĠWeld\":30410,\"ĠIncluded\":30411,\"Ġmathematical\":30412,\"Ġexponentially\":30413,\"Ġhandwritten\":30414,\"ĠMAS\":30415,\"Ġindiscrim\":30416,\"Ġnutrient\":30417,\"ĠSelection\":30418,\"Ġ219\":30419,\"hyd\":30420,\"Ġdeton\":30421,\"Ã¦\":30422,\"dark\":30423,\"ĠFidel\":30424,\"Ġmonkeys\":30425,\"Ġnutritious\":30426,\"Ġheadlights\":30427,\"oller\":30428,\"piring\":30429,\"ĠDefenders\":30430,\"Ġdrown\":30431,\"elong\":30432,\"Ġfloats\":30433,\"graduate\":30434,\"Ġprosper\":30435,\"ĠNamed\":30436,\"ĠEating\":30437,\"ECK\":30438,\"establishment\":30439,\"XM\":30440,\"Ġsoaking\":30441,\"278\":30442,\"Ġlistener\":30443,\"Ġsimultaneous\":30444,\"olutions\":30445,\"payer\":30446,\"Ġcustomize\":30447,\"ĠROCK\":30448,\"Ġaltar\":30449,\"ĠExercise\":30450,\"anky\":30451,\"ĠProfession\":30452,\"sever\":30453,\"ĠMerchant\":30454,\"RF\":30455,\"ĠCombat\":30456,\"Ġlegality\":30457,\"fledged\":30458,\"Ġdiapers\":30459,\"lves\":30460,\"Ġlur\":30461,\"Ġignores\":30462,\"ĠProtocol\":30463,\"Ġrepresentations\":30464,\"ĠBlumenthal\":30465,\"ĠLime\":30466,\"romptu\":30467,\"Ġbesieged\":30468,\"dl\":30469,\"Ġsighting\":30470,\"ĠParm\":30471,\"ĠServer\":30472,\"ĠBenghazi\":30473,\"estival\":30474,\"Ġplaylist\":30475,\"ĠUng\":30476,\"ĠQuantum\":30477,\"Ġcompromises\":30478,\"ĠSurvivor\":30479,\"ĠMobility\":30480,\"Ġbounty\":30481,\"ophers\":30482,\"ISA\":30483,\"need\":30484,\"uese\":30485,\"Ġorn\":30486,\"218\":30487,\"Ġ530\":30488,\"Ġbuddies\":30489,\"Ġagendas\":30490,\"ĠFeldman\":30491,\"ĠÃĸ\":30492,\"ĠBMC\":30493,\"ĠServe\":30494,\"Ent\":30495,\"ĠKH\":30496,\"ĠINT\":30497,\"Ġlittered\":30498,\"Ġvisitation\":30499,\"mist\":30500,\"Ġdupl\":30501,\"Ġrouted\":30502,\"ĠAmount\":30503,\"Dev\":30504,\"ĠConv\":30505,\"Ġslams\":30506,\"ĠVeterinary\":30507,\"bold\":30508,\"Ġ186\":30509,\"ĠDOT\":30510,\"builder\":30511,\"Ġdecay\":30512,\"ĠHemp\":30513,\"pelled\":30514,\"Ġmankind\":30515,\"Tonight\":30516,\"Ġeffortlessly\":30517,\"ĠBUT\":30518,\"Ġhostilities\":30519,\"formerly\":30520,\"alon\":30521,\"ĠCrash\":30522,\"humane\":30523,\"Ġmayhem\":30524,\"ĠBudd\":30525,\"Ġdisinformation\":30526,\"Ġ226\":30527,\"Ġprototypes\":30528,\"__\":30529,\"IVERS\":30530,\"izzy\":30531,\"ĠMight\":30532,\"ĠPip\":30533,\"pour\":30534,\"INO\":30535,\"ĠLL\":30536,\"Ġwiret\":30537,\"Ġresorted\":30538,\"ĠTanaka\":30539,\"ĠDOES\":30540,\"Earlier\":30541,\"HO\":30542,\"Ġmoniker\":30543,\"ĠFang\":30544,\"ĠHua\":30545,\"bered\":30546,\"adding\":30547,\"194\":30548,\"STR\":30549,\".\\\")\":30550,\"cop\":30551,\"ĠFlags\":30552,\"ĠColleges\":30553,\"ĠUz\":30554,\"Ġsparks\":30555,\"Ġparadox\":30556,\"Marie\":30557,\"Strong\":30558,\"Ġstrawberry\":30559,\"Ġnurturing\":30560,\"Ġfax\":30561,\"Tor\":30562,\"killer\":30563,\"burse\":30564,\"Ġattachments\":30565,\"Ġpup\":30566,\"Ġexhaustion\":30567,\"Ġwhisky\":30568,\"isu\":30569,\"ologically\":30570,\"iership\":30571,\"Ġlamps\":30572,\"Ġshuff\":30573,\"Ġcentralized\":30574,\"ĠNeedless\":30575,\"Ġgrenade\":30576,\"Ġrouter\":30577,\"Ġoptics\":30578,\"ivering\":30579,\"Ġpioneers\":30580,\"ĠHug\":30581,\"Ġhandguns\":30582,\"010\":30583,\"Ġbailed\":30584,\"uana\":30585,\"197\":30586,\"Ġdistorted\":30587,\"ĠEssentially\":30588,\"ĠSilent\":30589,\"Ġcomparative\":30590,\"Music\":30591,\"ĠMUS\":30592,\"Bur\":30593,\"ĠComet\":30594,\"ĠWinchester\":30595,\"IGN\":30596,\"Mod\":30597,\"ĠCandidate\":30598,\"Ġdysfunctional\":30599,\"ĠCeleb\":30600,\"Ġhitch\":30601,\"api\":30602,\"Ġidiot\":30603,\"Ġunsupported\":30604,\"gat\":30605,\"inker\":30606,\"Ġredevelop\":30607,\"Ġdwind\":30608,\"Ġforgetting\":30609,\"ĠRost\":30610,\"Ġremembrance\":30611,\"Na\":30612,\"mopolitan\":30613,\"Ġberries\":30614,\"Ġmarital\":30615,\"Vol\":30616,\"ĠClosing\":30617,\"ĠHindus\":30618,\"itism\":30619,\"Ġrover\":30620,\"Ġmysteries\":30621,\"ĠNig\":30622,\"ucing\":30623,\"Ġfabrication\":30624,\"Ġgarments\":30625,\"Ġwield\":30626,\"ĠCompton\":30627,\"357\":30628,\"Ġoxide\":30629,\"chron\":30630,\"ĠThought\":30631,\"Ġcomed\":30632,\"ĠEpstein\":30633,\"ĠBART\":30634,\"orative\":30635,\"ĠKahn\":30636,\"adan\":30637,\"APH\":30638,\"cum\":30639,\"Ġloophole\":30640,\"ĠGoPro\":30641,\"osit\":30642,\"Ġspecification\":30643,\"ĠAPR\":30644,\"Ġdrains\":30645,\"Ġconserve\":30646,\"ĠMorse\":30647,\"Ġcalorie\":30648,\"ĠCheney\":30649,\"station\":30650,\"Ġevangel\":30651,\"Ġspraying\":30652,\"lections\":30653,\"Ġenclosure\":30654,\"Ġcommanded\":30655,\"ĠOrganizations\":30656,\"Ġimb\":30657,\"mins\":30658,\"ĠTobias\":30659,\"Ve\":30660,\"ĠNau\":30661,\"183\":30662,\"ĠGuantanamo\":30663,\"173\":30664,\"Ġrequisite\":30665,\"Ġderivative\":30666,\"Ġpopulism\":30667,\"Ġcultivated\":30668,\"lord\":30669,\"uler\":30670,\"ĠDEA\":30671,\"inally\":30672,\"Ġdemonstr\":30673,\"trip\":30674,\"ĠFirefox\":30675,\"246\":30676,\"confirmed\":30677,\"Anne\":30678,\"Ġtamp\":30679,\"ĠHousehold\":30680,\"amous\":30681,\"Meet\":30682,\"Ġdashed\":30683,\"pire\":30684,\"Ġinex\":30685,\"Ġloosen\":30686,\"272\":30687,\"famous\":30688,\"ĠHeard\":30689,\"Ġhindsight\":30690,\"Ġdepot\":30691,\"ĠCutting\":30692,\"ĠMouse\":30693,\"Ġgeological\":30694,\"number\":30695,\"OUN\":30696,\".,\\\"\":30697,\"Ġmoderation\":30698,\"ĠUNHCR\":30699,\"Ġdomains\":30700,\"eco\":30701,\"Ġcrater\":30702,\"Ġ510\":30703,\"kid\":30704,\"Ġcylinders\":30705,\"ĠClasses\":30706,\"Kn\":30707,\"Ġcarcin\":30708,\"ĠHunting\":30709,\"irit\":30710,\"ARP\":30711,\"anting\":30712,\"ĠMarino\":30713,\"ĠRESP\":30714,\"ifle\":30715,\"Ġ239\":30716,\"fman\":30717,\"Ġtheoretically\":30718,\"Ġdistraught\":30719,\"Ġstaircase\":30720,\"Ġexpel\":30721,\"Ġlord\":30722,\"Ġbehaviours\":30723,\"Ġprescribing\":30724,\"ographs\":30725,\"ĠNewly\":30726,\"Ġpatiently\":30727,\"Ġskyline\":30728,\"udos\":30729,\"Ġrepertoire\":30730,\"Ġhover\":30731,\"mint\":30732,\"Ġclears\":30733,\"Ġkale\":30734,\"ĠSco\":30735,\"ĠCoulter\":30736,\"Ġpancreat\":30737,\"pu\":30738,\"995\":30739,\"Ġincompetent\":30740,\"2007\":30741,\"Ġgripping\":30742,\"enable\":30743,\"Ġreinforcing\":30744,\"ĠFee\":30745,\"education\":30746,\"ĠKuro\":30747,\"Ġbowed\":30748,\"Ġshave\":30749,\"ĠMean\":30750,\"xi\":30751,\"Ġinciting\":30752,\"atters\":30753,\"Ġecstatic\":30754,\"hog\":30755,\"Ġclauses\":30756,\"Ġsubt\":30757,\"Ġbehaved\":30758,\"tains\":30759,\"Liverpool\":30760,\"Ġstrives\":30761,\"ĠKev\":30762,\"ĠFramework\":30763,\"defined\":30764,\"Ġrecounts\":30765,\"array\":30766,\"tips\":30767,\"Ġartificially\":30768,\"fits\":30769,\"Clearly\":30770,\"mediate\":30771,\"Ġunseen\":30772,\"Ġthugs\":30773,\"ĠLent\":30774,\"Ġ1938\":30775,\"Ġgenital\":30776,\"ĠSonic\":30777,\"ĠWarehouse\":30778,\"pler\":30779,\"Ġunm\":30780,\"Ġpackets\":30781,\"ĠMET\":30782,\"ealous\":30783,\"ographers\":30784,\"Ġlabou\":30785,\"Core\":30786,\"+,\":30787,\"parable\":30788,\"Ġstrat\":30789,\"Ġinvitations\":30790,\"Ġsouven\":30791,\"Ġbillboards\":30792,\"ĠRegulations\":30793,\"Ġdwarf\":30794,\"Ġtoler\":30795,\"Ġprose\":30796,\"Ġestates\":30797,\"Ġmetabolic\":30798,\"ĠSuff\":30799,\"ĠFirstly\":30800,\"Ġpolio\":30801,\"Ġchick\":30802,\"ĠDaughter\":30803,\"Ġsubstant\":30804,\"ĠIdentity\":30805,\"umbers\":30806,\"ĠFacts\":30807,\"Ġfrust\":30808,\"Ġdissip\":30809,\"ĠDeck\":30810,\"Hy\":30811,\"ĠBirch\":30812,\"Ġhurled\":30813,\"democracy\":30814,\"nered\":30815,\"eper\":30816,\"Ġcerebral\":30817,\"181\":30818,\"Ġhalves\":30819,\"abit\":30820,\"balance\":30821,\"ĠTibet\":30822,\"Ġhandheld\":30823,\"ĠDough\":30824,\"Ġprogrammed\":30825,\"hw\":30826,\"Ġoutlawed\":30827,\"ĠSerious\":30828,\"Ġironically\":30829,\"Ġmanipulating\":30830,\")\\\"\":30831,\"juries\":30832,\"Ġfragrance\":30833,\"crete\":30834,\"ĠHHS\":30835,\"cience\":30836,\"Ġcosmic\":30837,\"Ġforeclosure\":30838,\"Ġpercentages\":30839,\"Bus\":30840,\"Ġenticing\":30841,\"extra\":30842,\"ĠShy\":30843,\"ĠÂ¥\":30844,\"Ġheadsets\":30845,\"imensional\":30846,\"Ġlux\":30847,\"Ġresidual\":30848,\"Ġmantle\":30849,\"ĠSJ\":30850,\"ĠPeaks\":30851,\"ĠFinger\":30852,\"Ġunfolds\":30853,\"anity\":30854,\"Ġresettlement\":30855,\"ĠWeak\":30856,\"ĠBeen\":30857,\"Ġ198\":30858,\"Ġangels\":30859,\"ĠFarn\":30860,\"peace\":30861,\"Ġcapac\":30862,\"Ġhue\":30863,\"Ġlust\":30864,\"traumatic\":30865,\"laun\":30866,\"Ġstrawberries\":30867,\"Ġherbal\":30868,\"Ġconversions\":30869,\"ĠHeld\":30870,\"Ġprescribe\":30871,\"Its\":30872,\"ĠDartmouth\":30873,\"Ġfashioned\":30874,\"460\":30875,\"BLE\":30876,\"international\":30877,\"Ġlumin\":30878,\"Ġplantation\":30879,\"ilde\":30880,\"490\":30881,\"Ġeuph\":30882,\"Ġdisgust\":30883,\"Ġaspire\":30884,\"medical\":30885,\"Ġsocialism\":30886,\"Ġdissolve\":30887,\"Wal\":30888,\"Ġadmittedly\":30889,\"Ġsewing\":30890,\"ĠAcer\":30891,\"Ġtul\":30892,\"Ġfacilit\":30893,\"Ġgrandma\":30894,\"ĠFeeling\":30895,\"Ġobst\":30896,\"ĠFranz\":30897,\"ĠPalin\":30898,\"ĠIncrease\":30899,\"gets\":30900,\"ĠImam\":30901,\"âĢİ\":30902,\"Ġcoincides\":30903,\"urrence\":30904,\"Ġlifes\":30905,\"Lab\":30906,\"Ham\":30907,\"angelo\":30908,\"Wild\":30909,\"Ġvetoed\":30910,\"Ġventilation\":30911,\"olid\":30912,\"Summer\":30913,\"Ġfacade\":30914,\"neys\":30915,\"ĠWOM\":30916,\"ĠBenny\":30917,\"ĠMarried\":30918,\"squ\":30919,\"ĠReflect\":30920,\"return\":30921,\"elia\":30922,\"olding\":30923,\"Ġrefine\":30924,\"ĠMadness\":30925,\"innacle\":30926,\"posts\":30927,\"287\":30928,\"fruit\":30929,\"274\":30930,\"icator\":30931,\"ĠVoy\":30932,\"Ġunsett\":30933,\"Ġfant\":30934,\"Ġtreaties\":30935,\"Ġcrystals\":30936,\"Ġhijacked\":30937,\"words\":30938,\"ĠReleased\":30939,\"Save\":30940,\"Ġcannon\":30941,\"Ġanomaly\":30942,\"Ġbeacon\":30943,\"Ġcrippled\":30944,\"Ġbundles\":30945,\"Ġuntreated\":30946,\"Ġhappiest\":30947,\"Ġgalaxies\":30948,\"Ġoccupational\":30949,\"416\":30950,\"Dar\":30951,\"Ġcrank\":30952,\"Ġappropriation\":30953,\"asking\":30954,\"mens\":30955,\"Ġdetector\":30956,\"Ġskewed\":30957,\"Ġpoke\":30958,\"254\":30959,\"Ġhypertension\":30960,\"apolog\":30961,\"Ġevaluations\":30962,\"blocks\":30963,\"Ġpow\":30964,\"GEN\":30965,\"Ġscalp\":30966,\"Ġarrogant\":30967,\"AIDS\":30968,\"ority\":30969,\"Ġredirect\":30970,\"Ġderogatory\":30971,\"Ġlateral\":30972,\"495\":30973,\"rolley\":30974,\"brew\":30975,\"Ġbabys\":30976,\"Ġmuff\":30977,\"ĠRequ\":30978,\"Ġdime\":30979,\"Ġwonderfully\":30980,\"Ġtreasures\":30981,\"ĠNES\":30982,\"Ġponds\":30983,\"Ġimpulse\":30984,\"Ġdetecting\":30985,\"Ġgrin\":30986,\"Ġbrid\":30987,\"Ġshoved\":30988,\"Ġpurge\":30989,\"irteen\":30990,\"OTHER\":30991,\"ÙĦ\":30992,\"irsch\":30993,\"ĠOcc\":30994,\"193\":30995,\"Ġfodder\":30996,\"wrote\":30997,\"meric\":30998,\"posal\":30999,\"Ġwinters\":31000,\"ĠJuice\":31001,\"hub\":31002,\"Ġcontrasting\":31003,\"Brazil\":31004,\"Ġflashy\":31005,\"uffer\":31006,\"technology\":31007,\"Children\":31008,\"Ġcatapult\":31009,\"owsky\":31010,\"ĠEclipse\":31011,\"abeth\":31012,\"ĠParticip\":31013,\"Ġlaud\":31014,\"ĠQuiet\":31015,\"Ġsimulations\":31016,\"Ġsacrificing\":31017,\"Ġpreaching\":31018,\"Ġvoicing\":31019,\"itizen\":31020,\"Ġgn\":31021,\"Ġsans\":31022,\"Ġ285\":31023,\"ĠRobot\":31024,\"Ġ1936\":31025,\"Ġsham\":31026,\"ĠKislyak\":31027,\"ĠGCC\":31028,\"tale\":31029,\"ĠShades\":31030,\"Ġsediment\":31031,\"Ġconveniently\":31032,\"Give\":31033,\"mounted\":31034,\"Ġpeel\":31035,\"Jun\":31036,\"ĠEisenhower\":31037,\"Ġdiplom\":31038,\"ĠPreservation\":31039,\"Ġaffirm\":31040,\"Ġtaboo\":31041,\"ĠGarr\":31042,\"ĠApply\":31043,\"prim\":31044,\"Ġausp\":31045,\"Ġtextbook\":31046,\"Ġforfeit\":31047,\"icides\":31048,\"Ġundis\":31049,\"DJ\":31050,\"Ġ\\\"...\":31051,\"ĠXperia\":31052,\"Ġfurry\":31053,\"Australian\":31054,\"Ġpreach\":31055,\"Ġparamed\":31056,\"Ġ196\":31057,\"agos\":31058,\"ĠRIP\":31059,\"Ġ408\":31060,\"ĠQuarterly\":31061,\"ĠQuentin\":31062,\"Ġdeft\":31063,\"ĠVlad\":31064,\"massive\":31065,\"apore\":31066,\"Ġquestionnaire\":31067,\"secution\":31068,\"ĠTunnel\":31069,\"ĠAssist\":31070,\"BILITY\":31071,\"everything\":31072,\"vich\":31073,\"Ġcomparatively\":31074,\"heng\":31075,\"ETH\":31076,\"ĠiPod\":31077,\"Ġinsurgent\":31078,\"Ġtestosterone\":31079,\"191\":31080,\"Ġmoons\":31081,\"Ġgripped\":31082,\"Ġstrang\":31083,\"pects\":31084,\"ĠSERVICE\":31085,\"Ġnumb\":31086,\"Ġmeasurable\":31087,\"Ġdismantled\":31088,\"Ġdepict\":31089,\"Ġretake\":31090,\"Light\":31091,\"Ġaquatic\":31092,\"useum\":31093,\"judicial\":31094,\"Ġ****\":31095,\"Ġrosters\":31096,\"certain\":31097,\"Ġhypothesis\":31098,\"2002\":31099,\"Snow\":31100,\"Ġpounded\":31101,\"ĠZel\":31102,\"ĠTrem\":31103,\"iversity\":31104,\"219\":31105,\"Jen\":31106,\"ĠAdventures\":31107,\"Ġcylinder\":31108,\"Ġbanging\":31109,\"Ġbalk\":31110,\"analy\":31111,\"ĠHust\":31112,\"ookie\":31113,\"ĠReturning\":31114,\"Ġpods\":31115,\"analysis\":31116,\"ĠTruman\":31117,\"Ġorg\":31118,\"Ġsar\":31119,\"Ġdred\":31120,\"ĠTelecommunications\":31121,\"ĠSven\":31122,\"carry\":31123,\"ĠLOVE\":31124,\"Ġparting\":31125,\"asar\":31126,\"utations\":31127,\"itic\":31128,\"Ġactu\":31129,\"Ġbananas\":31130,\"ĠNights\":31131,\"410\":31132,\"Still\":31133,\"Ġtweaked\":31134,\"went\":31135,\"Ġtoddlers\":31136,\"irted\":31137,\"Ġpaed\":31138,\"ĠWink\":31139,\"Ġviewpoint\":31140,\"ĠHelic\":31141,\"Ġhandshake\":31142,\"Ġpoaching\":31143,\"Ġrounding\":31144,\"268\":31145,\"ĠNVIDIA\":31146,\"Ġsquat\":31147,\"Ġtowed\":31148,\"Ġhandler\":31149,\"Ġconspir\":31150,\"Ġadditionally\":31151,\"CENT\":31152,\"ĠÃľ\":31153,\"article\":31154,\"ĠTough\":31155,\"NM\":31156,\"Rem\":31157,\"Ġstunts\":31158,\"ILS\":31159,\"ĠLM\":31160,\"Connect\":31161,\"ĠParagu\":31162,\"Ġcomplexities\":31163,\"Ġhugging\":31164,\"Ġabolish\":31165,\"ricting\":31166,\"ĠItems\":31167,\"Ġtemples\":31168,\"ĠSeat\":31169,\"ĠRubber\":31170,\"Ġindic\":31171,\"ĠVitamin\":31172,\"Ġcitations\":31173,\"Ġarmored\":31174,\"---------------\":31175,\"ĠNeo\":31176,\"ippy\":31177,\"Que\":31178,\"Ġrag\":31179,\"Ġlov\":31180,\"630\":31181,\"Ġadept\":31182,\"orbit\":31183,\"253\":31184,\"412\":31185,\"Ġbutterflies\":31186,\"Ġoutl\":31187,\"ĠCycle\":31188,\"Ġaesthetics\":31189,\"ĠTwitch\":31190,\"405\":31191,\"factor\":31192,\"ðŁĳ\":31193,\"ĠCircus\":31194,\"Posted\":31195,\"Ġintroductory\":31196,\"ĠStack\":31197,\"atoes\":31198,\"Ġfurn\":31199,\"ĠHond\":31200,\"Ġbipolar\":31201,\"ĠAging\":31202,\"inches\":31203,\"Ġincompetence\":31204,\"Ġaloud\":31205,\"Imagine\":31206,\"Ġsepar\":31207,\"Ġmanip\":31208,\"ophobic\":31209,\"inion\":31210,\"bek\":31211,\"Ġquer\":31212,\"ĠArmen\":31213,\"Ġhumorous\":31214,\"Ġmundane\":31215,\"Ġapologizing\":31216,\"Ġpioneered\":31217,\"Ġ303\":31218,\"282\":31219,\"Ġcalming\":31220,\"orious\":31221,\"760\":31222,\"Ġstitches\":31223,\"Ġthrottle\":31224,\"Ġspinach\":31225,\"urities\":31226,\"ĠCologne\":31227,\"Ġripple\":31228,\"Cs\":31229,\"Cent\":31230,\"Should\":31231,\"Ġaffinity\":31232,\"amount\":31233,\"ĠMISS\":31234,\"Ġsage\":31235,\"Ġamusing\":31236,\"Ġsnatch\":31237,\"clair\":31238,\"ĠGuess\":31239,\"bench\":31240,\"ĠMoj\":31241,\"nuclear\":31242,\"Ġfid\":31243,\"ĠVM\":31244,\"ĠGN\":31245,\"brainer\":31246,\"Ġcurled\":31247,\"Ġbushes\":31248,\"icably\":31249,\"Ġcreeping\":31250,\"Ġveil\":31251,\"ĠALS\":31252,\"ESPN\":31253,\"ulsion\":31254,\"ĠGTX\":31255,\"ĠANN\":31256,\"Ġcomplicit\":31257,\"assault\":31258,\"IOR\":31259,\"Ġpolymer\":31260,\"Ġestimating\":31261,\"277\":31262,\"alog\":31263,\"Ġglimps\":31264,\"Ġreinforces\":31265,\"Ġtextbooks\":31266,\"Ġdictated\":31267,\"ĠReyn\":31268,\"latable\":31269,\"ĠOrth\":31270,\"520\":31271,\"Ġtrickle\":31272,\"ĠWrong\":31273,\".[\":31274,\"ĠDesigner\":31275,\"304\":31276,\"ĠInner\":31277,\"Ġrave\":31278,\"ppa\":31279,\"ĠGim\":31280,\"Ġswath\":31281,\"Ġcarts\":31282,\"atlantic\":31283,\"Ġpersists\":31284,\"ĠDeveloper\":31285,\"Ġgoodies\":31286,\"isive\":31287,\"Inf\":31288,\"ĠSaving\":31289,\"loop\":31290,\"tions\":31291,\"Ġabusers\":31292,\"Ġclot\":31293,\"Ġmesmer\":31294,\"Ġdeg\":31295,\"Ġskirts\":31296,\"257\":31297,\"Ġunreliable\":31298,\"ĠCOMM\":31299,\"Ġ194\":31300,\"Ġfledgling\":31301,\"administ\":31302,\"Israeli\":31303,\"ĠBarbie\":31304,\"ĠJeanne\":31305,\"Ġgenerously\":31306,\"ĠStruct\":31307,\"ĠZap\":31308,\"Ġvetted\":31309,\"ĠViolet\":31310,\"Ġ),\":31311,\"Ġembarrass\":31312,\"bang\":31313,\"ĠProvider\":31314,\"getting\":31315,\"alg\":31316,\"Ġunconditional\":31317,\"ĠHulk\":31318,\"ĠWad\":31319,\"utation\":31320,\"Ġpointless\":31321,\"Ġdeprivation\":31322,\"Ġstarving\":31323,\"ĠImpossible\":31324,\"ĠStir\":31325,\"Ġknack\":31326,\"anse\":31327,\"Ġsecurely\":31328,\"Ġply\":31329,\"395\":31330,\"Pack\":31331,\"liv\":31332,\"Ġridden\":31333,\"alks\":31334,\"308\":31335,\"male\":31336,\"Ġbitterly\":31337,\"Ġirrational\":31338,\"Members\":31339,\"ported\":31340,\"qq\":31341,\"ractor\":31342,\"Ġinflict\":31343,\"ĠBoehner\":31344,\"Ġthickness\":31345,\"Ġdome\":31346,\"ĠInflu\":31347,\"Ġheap\":31348,\"Ġmirrored\":31349,\"Ġconstituent\":31350,\"Ġfertile\":31351,\"Ġvaping\":31352,\"266\":31353,\"riages\":31354,\"Ġembassies\":31355,\"Ġpersu\":31356,\"ĠMacArthur\":31357,\"issions\":31358,\"Main\":31359,\"aths\":31360,\"onne\":31361,\"circ\":31362,\"Ġsweating\":31363,\"quartered\":31364,\"Ġsax\":31365,\"Ġ540\":31366,\"Ġreputable\":31367,\"Ġsatire\":31368,\"Ġpastors\":31369,\"ventional\":31370,\"Mic\":31371,\"female\":31372,\"Ġpity\":31373,\"appropri\":31374,\"voc\":31375,\"hei\":31376,\"Ġimperial\":31377,\"Ġcorrective\":31378,\"Ġresent\":31379,\"Ġtempered\":31380,\"Ġdiffers\":31381,\"Hamilton\":31382,\"Ġsaddle\":31383,\"Ġgrenades\":31384,\"ĠQuart\":31385,\"onymous\":31386,\"til\":31387,\"Ġdepiction\":31388,\"Ġdisreg\":31389,\"Ġpetitioner\":31390,\"Ġfret\":31391,\"ĠEns\":31392,\"Emer\":31393,\"540\":31394,\"opathy\":31395,\"vertisements\":31396,\"Ġsketches\":31397,\"venth\":31398,\"Ġautomate\":31399,\"Ġjihad\":31400,\"iping\":31401,\"Ġtert\":31402,\"ĠSop\":31403,\"ships\":31404,\"Ġdeceptive\":31405,\"ĠPryor\":31406,\"ĠGorge\":31407,\"ĠMeridian\":31408,\"rero\":31409,\"affected\":31410,\"Ġlame\":31411,\"660\":31412,\"rub\":31413,\"Hello\":31414,\"ĠNumbers\":31415,\"269\":31416,\"Ġmarg\":31417,\"Fran\":31418,\"640\":31419,\"Ġcath\":31420,\"winter\":31421,\"ĠMosque\":31422,\"Ġreckoning\":31423,\"ĠImaging\":31424,\"Ġmutation\":31425,\"ĠMild\":31426,\"Ġkidnap\":31427,\"Ġnav\":31428,\"Ġferocious\":31429,\"Ġdusty\":31430,\"Cele\":31431,\"ĠFoss\":31432,\"Ġregrett\":31433,\"lymp\":31434,\"Ġcoli\":31435,\"Ġstereo\":31436,\"Ġforesee\":31437,\"alties\":31438,\"Ġresusc\":31439,\"Full\":31440,\"wash\":31441,\"ĠINST\":31442,\"ĠPars\":31443,\"Ġcoated\":31444,\"ĠHT\":31445,\"Ġdiscord\":31446,\"Ġreforming\":31447,\"CAN\":31448,\"Ġblink\":31449,\"Ġlubric\":31450,\"Ġmishand\":31451,\"ensible\":31452,\"existent\":31453,\"secondary\":31454,\"ĠDoesn\":31455,\"terrorist\":31456,\"Ġriff\":31457,\"custom\":31458,\"ĠDET\":31459,\"Ġreusable\":31460,\"ĠCRA\":31461,\"ĠScalia\":31462,\"Ġaccelerator\":31463,\"Ġpropag\":31464,\"ĠMID\":31465,\"ework\":31466,\"Ġlooted\":31467,\"oscope\":31468,\"eners\":31469,\"ruction\":31470,\"Ġbarr\":31471,\"Ġviewership\":31472,\"Ġlends\":31473,\"obil\":31474,\"ĠRoots\":31475,\"ĠCame\":31476,\"ibel\":31477,\"Ġglobalization\":31478,\"lab\":31479,\"information\":31480,\"Ġcoordin\":31481,\"Ġglitch\":31482,\"Ġworms\":31483,\"Ġslurs\":31484,\"Ġcontemplated\":31485,\"ĠPenal\":31486,\"Ġ191\":31487,\"Ġ221\":31488,\"Ġexposes\":31489,\"Ġ248\":31490,\"ĠASP\":31491,\"Ġdependency\":31492,\"urga\":31493,\"pdf\":31494,\"Ġvibr\":31495,\"clone\":31496,\"ossible\":31497,\"ĠUtt\":31498,\"serv\":31499,\"ĠLevant\":31500,\"maybe\":31501,\"MU\":31502,\"ĠLunar\":31503,\"Ġbystanders\":31504,\"Ġcapitals\":31505,\"Ġpreacher\":31506,\"thin\":31507,\"Ġunderscore\":31508,\"Ġ('\":31509,\"Ġmedd\":31510,\"Ġautobiography\":31511,\"Ġpersistence\":31512,\"Ġarming\":31513,\"Ġappalled\":31514,\"Ġcontradictory\":31515,\"Ġreciproc\":31516,\"Ġtakedown\":31517,\"tan\":31518,\"Ġnecessities\":31519,\"itans\":31520,\"ĠAlas\":31521,\"Ġsegregated\":31522,\"ĠResponsibility\":31523,\"ĠSHOW\":31524,\"ISIS\":31525,\"Ġpengu\":31526,\"Ġumb\":31527,\"ĠHO\":31528,\"HB\":31529,\"ĠChou\":31530,\"Ġalluded\":31531,\"Ġharms\":31532,\"bara\":31533,\"ĠWOR\":31534,\"Sorry\":31535,\"Ġstarvation\":31536,\"Ġspilling\":31537,\"Ġcarb\":31538,\"annis\":31539,\"ĠGarrison\":31540,\"Ġmillionaire\":31541,\"ifling\":31542,\"ĠCancel\":31543,\"Ġimprint\":31544,\"Ġborrower\":31545,\"455\":31546,\"ĠCic\":31547,\"Ġexposures\":31548,\"dest\":31549,\"Ġunn\":31550,\"Ġ802\":31551,\"Ġadherence\":31552,\"prints\":31553,\"Ġweary\":31554,\"Ġwaging\":31555,\"Ġ1937\":31556,\"ĠKepler\":31557,\"%;\":31558,\"Ġdefective\":31559,\"ĠReps\":31560,\"ĠGranted\":31561,\"Ġdisco\":31562,\"ĠRanking\":31563,\"erno\":31564,\"Ġarchaeological\":31565,\"sq\":31566,\"Ġcapit\":31567,\"Ġfleets\":31568,\"Ġinventor\":31569,\"iffin\":31570,\"Ġspotting\":31571,\"ĠSHARES\":31572,\"309\":31573,\"Hard\":31574,\"save\":31575,\"241\":31576,\"ĠThinking\":31577,\"XY\":31578,\"Ġhavens\":31579,\"Ġmessed\":31580,\"crop\":31581,\"Ġperme\":31582,\"Ġtimelines\":31583,\"ĠGarage\":31584,\"Ġplateau\":31585,\"together\":31586,\"fox\":31587,\"Ġfailings\":31588,\"ĠTight\":31589,\"ĠPhysics\":31590,\"ĠScholars\":31591,\"Ġpans\":31592,\"Fall\":31593,\"Ġhull\":31594,\"GER\":31595,\"Ġbourbon\":31596,\"ceived\":31597,\"Ġsteroids\":31598,\"Ġhamb\":31599,\"Ġinterpretations\":31600,\"Ġcush\":31601,\"Chair\":31602,\"Ġinformational\":31603,\"aryn\":31604,\"Ġwoven\":31605,\"Ġamen\":31606,\"Bre\":31607,\"Ġrefreshed\":31608,\"York\":31609,\"ĠBlast\":31610,\"Editor\":31611,\"Ġmotivating\":31612,\"ĠReason\":31613,\"Florida\":31614,\"Ġdreaded\":31615,\"Ġstationary\":31616,\"Ġbil\":31617,\"doors\":31618,\"Ġslightest\":31619,\"Ġcombustion\":31620,\"Ġfascination\":31621,\"Ġstraps\":31622,\"scribed\":31623,\"Ġexhibiting\":31624,\"Ġsimplest\":31625,\"Gar\":31626,\"Ġprogressives\":31627,\"claim\":31628,\"ocket\":31629,\"Ġexoner\":31630,\"ĠNETWORK\":31631,\"Brad\":31632,\"Ġ197\":31633,\"Ġnightmares\":31634,\"Ġillust\":31635,\"among\":31636,\"ĠGreenpeace\":31637,\"Ġoval\":31638,\"Ġblocker\":31639,\"3000\":31640,\"ĠMemor\":31641,\"Ġmids\":31642,\"Ġconfuse\":31643,\"YN\":31644,\"cow\":31645,\"Ġdispensary\":31646,\"telling\":31647,\"Ġentail\":31648,\"Ġneurolog\":31649,\"Ġbroth\":31650,\"Ġpron\":31651,\"ĠAnswer\":31652,\"thank\":31653,\"Ġintersect\":31654,\"Ġclinging\":31655,\"ĠKilling\":31656,\"Ġcohesion\":31657,\"Ġcategorized\":31658,\"Ġtangled\":31659,\"ĠASC\":31660,\"Arsenal\":31661,\"ĠAutomatic\":31662,\"580\":31663,\"sac\":31664,\"Ġshady\":31665,\"consumer\":31666,\"hetically\":31667,\"NV\":31668,\"Ġoverl\":31669,\"holes\":31670,\"ĠDonation\":31671,\"tera\":31672,\"score\":31673,\"library\":31674,\"Ġsmoother\":31675,\"Ġcoasts\":31676,\"Ġintercourse\":31677,\"Ġunfavorable\":31678,\"erb\":31679,\"Hel\":31680,\"Ġbiases\":31681,\"Ġinheritance\":31682,\"Ġsuppressed\":31683,\"ĠRecommend\":31684,\"iculture\":31685,\"ighting\":31686,\"inguished\":31687,\"idences\":31688,\"operated\":31689,\"Ġhors\":31690,\"Ġshrug\":31691,\"aila\":31692,\"ĠConsortium\":31693,\"Ġveins\":31694,\"uria\":31695,\"ĠSmithsonian\":31696,\"ĠAX\":31697,\")âĢĶ\":31698,\"given\":31699,\"JC\":31700,\"Ġreneg\":31701,\"Ġprincip\":31702,\"Ġextinct\":31703,\"Golden\":31704,\"ASON\":31705,\"Ġstatutes\":31706,\"292\":31707,\"ĠGOOD\":31708,\"ĠGreenland\":31709,\"ĠRasmussen\":31710,\"ATHER\":31711,\"Ġdeserted\":31712,\"ĠHitchcock\":31713,\"Ġqualifies\":31714,\"Ġdreadful\":31715,\"Ġsupers\":31716,\"Ġtendon\":31717,\"oter\":31718,\"ĠFate\":31719,\"Ġrestrooms\":31720,\"igating\":31721,\"Sher\":31722,\"Name\":31723,\"orph\":31724,\"ĠCritical\":31725,\"rox\":31726,\"Ġdefunct\":31727,\"Ġcanoe\":31728,\"Ġbiscuits\":31729,\"Ġwomb\":31730,\"808\":31731,\"istar\":31732,\"Ġroar\":31733,\"aundering\":31734,\"iewicz\":31735,\"ĠNM\":31736,\"ĠChamberlain\":31737,\"Ġ233\":31738,\"ĠCoat\":31739,\"Ġ999\":31740,\"aft\":31741,\"Ġlurking\":31742,\"ĠPist\":31743,\"Ġfollower\":31744,\"Ġcareg\":31745,\"ÙĨ\":31746,\"ĠThin\":31747,\"ZZ\":31748,\"ĠGI\":31749,\"ĠVintage\":31750,\"Ġpainstaking\":31751,\"Ġgloom\":31752,\"Ġtbsp\":31753,\"Ġwhim\":31754,\"ĠMask\":31755,\"rugged\":31756,\"Ġwritings\":31757,\"stantial\":31758,\"luence\":31759,\"ordable\":31760,\"akia\":31761,\"Ġassassinated\":31762,\"Wind\":31763,\"Ġdemeanor\":31764,\"Night\":31765,\"rape\":31766,\"ĠBringing\":31767,\"Ġshields\":31768,\"ĠAntarctic\":31769,\"Ġfruitful\":31770,\"ĠBuster\":31771,\"ĠLois\":31772,\"Ġ302\":31773,\"Style\":31774,\"ĠRIS\":31775,\"Ġdissatisfaction\":31776,\"ulp\":31777,\"ĠLaser\":31778,\"Ġdisposition\":31779,\"ĠAnk\":31780,\"Ġabsorbing\":31781,\"276\":31782,\"Ġvolcan\":31783,\"Ġleftover\":31784,\"yah\":31785,\"ĠVaj\":31786,\"Ġunsolved\":31787,\"oland\":31788,\"Ġstained\":31789,\"Ġpathetic\":31790,\"ylan\":31791,\"Ġknots\":31792,\"immigration\":31793,\"ieving\":31794,\"Coming\":31795,\"Commerce\":31796,\"ĠHurt\":31797,\"drawn\":31798,\"Ġaxis\":31799,\"Ġdye\":31800,\"ĠNora\":31801,\"ĠPortal\":31802,\"Ġsuspense\":31803,\"ĠExactly\":31804,\"Ġpowering\":31805,\"ĠClock\":31806,\"Ġdrawer\":31807,\"ĠSpike\":31808,\"Ġhallmark\":31809,\"aber\":31810,\"ĠTrainer\":31811,\"UV\":31812,\"Ġredundant\":31813,\"Tour\":31814,\"Ġdesignate\":31815,\"Ġredress\":31816,\"ĠUb\":31817,\"cake\":31818,\"oded\":31819,\"Ġkings\":31820,\"iates\":31821,\"Ġcoupons\":31822,\"Ġextremes\":31823,\"Elect\":31824,\"Ġcitation\":31825,\"Ġdirectory\":31826,\"Ġtranspired\":31827,\"cele\":31828,\"gence\":31829,\"5000\":31830,\"ostic\":31831,\"Ġraining\":31832,\"ĠSight\":31833,\"videos\":31834,\"phthal\":31835,\"llor\":31836,\"Ġappraisal\":31837,\"Ġdetox\":31838,\"Ġelecting\":31839,\"Ġordinances\":31840,\"Ġlifespan\":31841,\"Ref\":31842,\"Ġilluminated\":31843,\"Ġforfe\":31844,\"Making\":31845,\"ĠWorst\":31846,\"ĠTP\":31847,\"Ġfullest\":31848,\"ĠISIL\":31849,\"ĠRates\":31850,\"Ġyeast\":31851,\"sett\":31852,\"ĠYok\":31853,\"innie\":31854,\"edition\":31855,\"ĠGoldstein\":31856,\"Ġunaff\":31857,\"god\":31858,\"Ġzo\":31859,\"rums\":31860,\"Ġopaque\":31861,\"ĠHist\":31862,\"Yesterday\":31863,\"AMS\":31864,\"aband\":31865,\"005\":31866,\"illary\":31867,\"ĠSplash\":31868,\"Ġaccrued\":31869,\"Ell\":31870,\"Ġnominating\":31871,\"ĠBroadcast\":31872,\"ĠWhip\":31873,\"ARM\":31874,\"Ġunnecessarily\":31875,\"brown\":31876,\"429\":31877,\"ansky\":31878,\"Ġextravagant\":31879,\"Malley\":31880,\"wage\":31881,\"Ġexempted\":31882,\"Ġtypo\":31883,\"Ġesports\":31884,\"ĠStru\":31885,\"ĠPython\":31886,\"Ġsaint\":31887,\"ĠCSI\":31888,\"ĠPowder\":31889,\"Ġdisguised\":31890,\"ĠSubway\":31891,\"Ġprecursor\":31892,\"ĠWizard\":31893,\"Johnson\":31894,\"icas\":31895,\"Ġdefaults\":31896,\"!).\":31897,\"ebra\":31898,\"jected\":31899,\"Ġunaccompanied\":31900,\"HH\":31901,\"Ġproced\":31902,\"clinical\":31903,\"Ġmitigating\":31904,\"ĠSoup\":31905,\"ĠFunny\":31906,\"344\":31907,\"Hall\":31908,\"Ġscalable\":31909,\"Ġshimmer\":31910,\"Ġunderstatement\":31911,\"zeb\":31912,\"icus\":31913,\"Ġretract\":31914,\"IDER\":31915,\"ieft\":31916,\"iii\":31917,\"ĠEmperor\":31918,\"Ġvoltage\":31919,\"343\":31920,\"Rest\":31921,\"ĠButcher\":31922,\"Ġlaced\":31923,\"Ġsalty\":31924,\"Ġfourteen\":31925,\"Ġoxy\":31926,\"Ġraged\":31927,\"Ġforg\":31928,\"Ġcaveat\":31929,\"Ġponder\":31930,\"process\":31931,\"Ġghosts\":31932,\"ĠGoose\":31933,\"didn\":31934,\"stood\":31935,\"amation\":31936,\"Ġvillains\":31937,\"contract\":31938,\"Ġbooted\":31939,\"ĠDidn\":31940,\"ĠSalon\":31941,\"Ġlewd\":31942,\"ĠFritz\":31943,\"Ġorganis\":31944,\"Ġpuzzles\":31945,\"ĠRX\":31946,\"Ġcurtains\":31947,\"ĠPackage\":31948,\"Ġrebate\":31949,\"Ġspokes\":31950,\"Ġoccupant\":31951,\"Ġfooled\":31952,\"appy\":31953,\"Ġyourselves\":31954,\"Ġmaths\":31955,\"Ġ630\":31956,\"bos\":31957,\"ĠHeb\":31958,\"APS\":31959,\"Ġbulletin\":31960,\"Ġpests\":31961,\"Ġlum\":31962,\"ĠHAS\":31963,\"users\":31964,\"idated\":31965,\"Ġpalpable\":31966,\"ĠFeature\":31967,\"ĠPKK\":31968,\"Ġdetriment\":31969,\"Ġbamboo\":31970,\"Ġimmersed\":31971,\"ĠDud\":31972,\"Ġion\":31973,\"icc\":31974,\"ĠIris\":31975,\"ĠBeats\":31976,\"Ġimprobable\":31977,\"Ġfuner\":31978,\"Ġsprung\":31979,\"ĠLieberman\":31980,\"ĠSTA\":31981,\"venge\":31982,\"Ġtreacherous\":31983,\"Ġpreced\":31984,\"Ġsniper\":31985,\"ĠGOLD\":31986,\"ĠSUR\":31987,\"Nic\":31988,\"ĠROB\":31989,\"Camp\":31990,\"Ġhooks\":31991,\"oling\":31992,\"Ġbolst\":31993,\"339\":31994,\"heter\":31995,\"Ġbracelet\":31996,\"Ġbreat\":31997,\"307\":31998,\"ĠTrader\":31999,\"ĠPixar\":32000,\"hist\":32001,\"Ġmenacing\":32002,\"Ġgrizz\":32003,\"294\":32004,\"Ġillustrious\":32005,\"Ġtransact\":32006,\"Ġspoiler\":32007,\"ĠWORK\":32008,\"Road\":32009,\"Ġblackout\":32010,\"Ġencomp\":32011,\"proven\":32012,\"ĠFriendship\":32013,\"Ġentrances\":32014,\"Ġprofessions\":32015,\"Ġinsin\":32016,\"Ġrecorder\":32017,\"Ġformulation\":32018,\"govern\":32019,\"Ġpainfully\":32020,\"ĠRepe\":32021,\"eeds\":32022,\"cru\":32023,\"ĠDir\":32024,\"Ġtriumphant\":32025,\"Ġignition\":32026,\"xy\":32027,\"Ġintrusion\":32028,\"ĠEAR\":32029,\"RES\":32030,\"Ġration\":32031,\"ĠTaken\":32032,\"Ġcages\":32033,\"Ġpeg\":32034,\"Ġcommem\":32035,\"680\":32036,\"ĠRite\":32037,\"Ġfolder\":32038,\"Ġvertically\":32039,\"Ġcheeks\":32040,\"pick\":32041,\"Ġcrispy\":32042,\"Ġsqueezing\":32043,\"ĠBene\":32044,\"ĠTrailer\":32045,\"ĠKM\":32046,\"acceptable\":32047,\"ĠSetting\":32048,\"Ġsupernatural\":32049,\"ĠEz\":32050,\"Ġvenom\":32051,\"ĠFrey\":32052,\"Ġpulp\":32053,\"Had\":32054,\"centered\":32055,\"metics\":32056,\"Kent\":32057,\"ĠDOI\":32058,\"kr\":32059,\"ĠWHEN\":32060,\"Ġtakeoff\":32061,\"isf\":32062,\"uko\":32063,\"Ġquasi\":32064,\"Ġveggies\":32065,\"Ġpesticide\":32066,\"Ġstimulating\":32067,\"Ġacknowledgement\":32068,\"Ġattained\":32069,\"ĠBackground\":32070,\"281\":32071,\"317\":32072,\"ĠTrees\":32073,\"Ġdetractors\":32074,\"Ġannouncer\":32075,\"Ġjoyful\":32076,\"ĠElf\":32077,\"istration\":32078,\"phi\":32079,\"Ġprogressively\":32080,\"mini\":32081,\"Ġcontraception\":32082,\"asca\":32083,\"ishops\":32084,\"Ġmisunderstood\":32085,\"Ġinitiating\":32086,\"ĠConversely\":32087,\"338\":32088,\"080\":32089,\"idation\":32090,\"ĠGoes\":32091,\"Ġimprov\":32092,\"Ġswapping\":32093,\"Vict\":32094,\"Ġdevoid\":32095,\"fighter\":32096,\"ĠMori\":32097,\"Ġvoy\":32098,\"ĠElev\":32099,\"ĠAim\":32100,\"Ġtrustworthy\":32101,\"Leg\":32102,\"675\":32103,\"ĠPossible\":32104,\"Crunch\":32105,\"ĠRings\":32106,\"Ġphony\":32107,\"Ġbladder\":32108,\"ĠChall\":32109,\"Spot\":32110,\"oak\":32111,\"Was\":32112,\"ĠFAM\":32113,\"ĠAGA\":32114,\"ĠFifa\":32115,\"Ġenclosed\":32116,\"Ġanthrop\":32117,\"faith\":32118,\"ĠAux\":32119,\"Ġgracious\":32120,\"roller\":32121,\"Ġdowntime\":32122,\"swing\":32123,\"Ġcamouflage\":32124,\"ĠCosts\":32125,\"Ġliv\":32126,\"ricular\":32127,\"ĠUran\":32128,\"Ġdisapproval\":32129,\"Ġpropriet\":32130,\"bits\":32131,\"Ġmafia\":32132,\"ĠSCHOOL\":32133,\"ĠPrepar\":32134,\"button\":32135,\"Almost\":32136,\"Ġpastoral\":32137,\"ĠDove\":32138,\"Hol\":32139,\"Ġimposes\":32140,\"ĠDram\":32141,\"lys\":32142,\"ĠSAS\":32143,\"Ġwiring\":32144,\"271\":32145,\"ĠModels\":32146,\"Ġoutpost\":32147,\"etics\":32148,\"Ġinsulted\":32149,\"ĠMongolia\":32150,\"Ġoverth\":32151,\"Haw\":32152,\"ĠHomer\":32153,\"itta\":32154,\"raining\":32155,\"Ġevidently\":32156,\"raphic\":32157,\"impact\":32158,\"Ġfranch\":32159,\"Ġ2100\":32160,\"Ġapproximate\":32161,\"Ġcartoons\":32162,\"Ġbackups\":32163,\"umbing\":32164,\"Ġforceful\":32165,\"ĠShad\":32166,\"Ġsurges\":32167,\"Ġperf\":32168,\"Ġdele\":32169,\"Ġquieter\":32170,\"ĠHorowitz\":32171,\"ĠDX\":32172,\"anners\":32173,\"ĠNinja\":32174,\"ĠScript\":32175,\"ĠElise\":32176,\"collect\":32177,\"Ġgrading\":32178,\"ĠBethesda\":32179,\"Kids\":32180,\"ĠTelephone\":32181,\"Ġpreferring\":32182,\"Ġreconcil\":32183,\"Ġmango\":32184,\"ĠHail\":32185,\"ĠCitizenship\":32186,\"Master\":32187,\"cular\":32188,\"Ġstuffing\":32189,\"ĠAlive\":32190,\"ALLY\":32191,\"Ġchi\":32192,\"ĠDynam\":32193,\"ĠRosenthal\":32194,\"Ġpurity\":32195,\"Ġtemp\":32196,\"ĠHAL\":32197,\"employ\":32198,\"Ġplentiful\":32199,\"ĠComed\":32200,\"Ġstacks\":32201,\"ĠHuge\":32202,\"ĠOlder\":32203,\"Ġsclerosis\":32204,\"ONY\":32205,\"Ġfilmmaking\":32206,\"chance\":32207,\"Cry\":32208,\"Ġworkflow\":32209,\"ĠPersonnel\":32210,\"awed\":32211,\"ĠColumn\":32212,\"Ġuncomp\":32213,\"Ġdiscriminated\":32214,\"Ġpts\":32215,\"Ġallev\":32216,\"ĠKinn\":32217,\"meal\":32218,\"Ġnovice\":32219,\"Ġcrest\":32220,\"Ġhearty\":32221,\"Ġlowers\":32222,\"inqu\":32223,\"ĠPlayoffs\":32224,\"ĠHyp\":32225,\"Ġautos\":32226,\"Ġindec\":32227,\"Ġnighttime\":32228,\"Ġreflex\":32229,\"306\":32230,\"disciplinary\":32231,\"ophe\":32232,\"contact\":32233,\"Ġachievable\":32234,\"Ġslab\":32235,\"ĠMessage\":32236,\"ĠVMware\":32237,\"ĠDia\":32238,\"REG\":32239,\"Ġconfisc\":32240,\"ĠMechan\":32241,\"Ġphenomena\":32242,\"Ġsequencing\":32243,\"Ġshaming\":32244,\"Ġcompilation\":32245,\"ĠAges\":32246,\"Ġmastered\":32247,\"Ġagony\":32248,\"Ġrestrain\":32249,\"ĠLyme\":32250,\"Which\":32251,\"ĠBarney\":32252,\"ĠConcept\":32253,\"Ġsuperheroes\":32254,\"ĠPsychology\":32255,\"Ġreminis\":32256,\"violence\":32257,\"Lead\":32258,\"Da\":32259,\"VEN\":32260,\"ERC\":32261,\"ĠVoter\":32262,\"Ġbetray\":32263,\"Ġsavage\":32264,\"driver\":32265,\"IFT\":32266,\"Chain\":32267,\"angler\":32268,\"'-\":32269,\"lain\":32270,\"ĠRatt\":32271,\"bis\":32272,\"iverse\":32273,\"Ġdensely\":32274,\"Ġuncom\":32275,\"Ġunsuspecting\":32276,\"Ġstimulation\":32277,\"diff\":32278,\"Ġskins\":32279,\"ĠRiding\":32280,\"ategic\":32281,\"ĠUnderstand\":32282,\"occup\":32283,\"ĠCooking\":32284,\"Ġschizophrenia\":32285,\"ĠKoen\":32286,\"Ġcomrades\":32287,\"HY\":32288,\"Ġfab\":32289,\"ĠRowling\":32290,\"Allen\":32291,\"ĠJUL\":32292,\"Ġembryos\":32293,\"UU\":32294,\"ĠCAT\":32295,\"Ġtidy\":32296,\"finger\":32297,\"ĠCake\":32298,\"Ġrightfully\":32299,\"religious\":32300,\"Ġ407\":32301,\"Gal\":32302,\"408\":32303,\"Ġgrievance\":32304,\"Ġswallowed\":32305,\"251\":32306,\"283\":32307,\"ĠBarcl\":32308,\"opter\":32309,\"Ġpedoph\":32310,\"Ġcured\":32311,\"Ġestablishes\":32312,\"increasing\":32313,\"tics\":32314,\"articles\":32315,\"Ġunethical\":32316,\"authored\":32317,\"Ġanchors\":32318,\"ĠContra\":32319,\"Ġventured\":32320,\"ĠCoh\":32321,\"Ġpuff\":32322,\"heddar\":32323,\"Ġomission\":32324,\"Ġdich\":32325,\"ceed\":32326,\"Ġscares\":32327,\"Ġdoctoral\":32328,\"293\":32329,\"ĠUnt\":32330,\"Ġdop\":32331,\"ĠInjury\":32332,\"ificantly\":32333,\"ĠRift\":32334,\"ĠOrders\":32335,\"Ġmobilize\":32336,\"particularly\":32337,\"Ġchilled\":32338,\"Reports\":32339,\"redibly\":32340,\"ĠGuru\":32341,\"Ġvalleys\":32342,\"Ġtextures\":32343,\"Ġreuse\":32344,\"roit\":32345,\"unts\":32346,\"Ġirreversible\":32347,\"Ġwarships\":32348,\"Ġpus\":32349,\"Ġpeeled\":32350,\"Ġthirst\":32351,\"Ġgrapple\":32352,\"busters\":32353,\"Ġnort\":32354,\"ĠDates\":32355,\"Safe\":32356,\"Ġbirthplace\":32357,\"hemoth\":32358,\"Ġvile\":32359,\"Ġ306\":32360,\"Ram\":32361,\"activated\":32362,\"ĠAero\":32363,\"Ġbutcher\":32364,\"ĠKnock\":32365,\"Ġdisturb\":32366,\"Ġtotality\":32367,\"tted\":32368,\"Ġlegit\":32369,\"cking\":32370,\"nikov\":32371,\"Ġfavoring\":32372,\"lang\":32373,\"Ġrightful\":32374,\"orum\":32375,\"!!!!\":32376,\"ĠMinute\":32377,\"Ġpostings\":32378,\"Java\":32379,\"510\":32380,\"Ġmicrobes\":32381,\"Ġsixteen\":32382,\"entimes\":32383,\"Ġbulb\":32384,\"Ġgoalt\":32385,\"Ġhumiliated\":32386,\"ansom\":32387,\"roach\":32388,\"Ġgrouping\":32389,\"hari\":32390,\"Ġcler\":32391,\"Ġstared\":32392,\"ĠSymptoms\":32393,\"Ġbasil\":32394,\"Whenever\":32395,\"ĠWhoever\":32396,\"Oil\":32397,\"ĠJericho\":32398,\"ĠAlm\":32399,\"Pol\":32400,\"Hur\":32401,\"Ġupro\":32402,\"ĠSpo\":32403,\"hammer\":32404,\"Mur\":32405,\"ĠTorch\":32406,\"Ġfrequencies\":32407,\"ĠExpansion\":32408,\"Ġparalysis\":32409,\"igon\":32410,\"ĠSail\":32411,\"Ġsilently\":32412,\"Ġrevolver\":32413,\"Ġstockpile\":32414,\"Ġpessimistic\":32415,\"ESA\":32416,\"Ġdisclaim\":32417,\"Ġdemocracies\":32418,\"ĠTales\":32419,\"ĠAngry\":32420,\"ĠWhitman\":32421,\"ĠOri\":32422,\"Ġtransitioned\":32423,\"behind\":32424,\"ĠLAN\":32425,\"Ġcav\":32426,\"ĠJazeera\":32427,\"KC\":32428,\"ĠInspect\":32429,\"irty\":32430,\"ĠAin\":32431,\"ĠOrig\":32432,\"Ġobscene\":32433,\"Ġdormant\":32434,\"Ġharb\":32435,\"ĠWiz\":32436,\"ĠAdolf\":32437,\"Ġvic\":32438,\"Ġdenouncing\":32439,\"Ġye\":32440,\"aques\":32441,\"Ġomn\":32442,\"Ġassemblies\":32443,\"nosis\":32444,\"Ġadmon\":32445,\"Ġanguish\":32446,\"Ġvag\":32447,\"YE\":32448,\"ĠMacro\":32449,\"Ġrubbing\":32450,\"Ġreplicated\":32451,\"Moon\":32452,\"ĠGuitar\":32453,\"Ġcentimeters\":32454,\"amily\":32455,\"ĠAmes\":32456,\"Ġchlorine\":32457,\"Perhaps\":32458,\"Ġpartisans\":32459,\"soc\":32460,\"Ġvagina\":32461,\"Ġtrove\":32462,\"ĠYES\":32463,\"Ġtherapists\":32464,\"Ġnods\":32465,\"Ġhanged\":32466,\"Ġridge\":32467,\"Ġhaz\":32468,\"ĠmacOS\":32469,\"Ġske\":32470,\"ĠShia\":32471,\"Ġsteril\":32472,\"Ġalmond\":32473,\"ĠRockefeller\":32474,\"Ġintrinsic\":32475,\"Certainly\":32476,\"Ġsublime\":32477,\"Earn\":32478,\"abet\":32479,\"Ġframeworks\":32480,\"ogical\":32481,\"ilst\":32482,\"ipal\":32483,\"Ġrescuing\":32484,\"ĠWatergate\":32485,\"Ġ231\":32486,\"ĠNano\":32487,\"ighthouse\":32488,\"olph\":32489,\"Ġ312\":32490,\"Ġhealed\":32491,\"ĠTomb\":32492,\"Ġsubst\":32493,\"Ġsulph\":32494,\"ĠNewsp\":32495,\"ĠLama\":32496,\"venue\":32497,\"387\":32498,\"productive\":32499,\"ĠNEED\":32500,\"minus\":32501,\"ĠPages\":32502,\"cand\":32503,\"ĠClover\":32504,\"ĠForensic\":32505,\"ryn\":32506,\"ogle\":32507,\"ocr\":32508,\"Ġvaccinations\":32509,\"cies\":32510,\"ĠMek\":32511,\"Ġunaffected\":32512,\"Ġfetal\":32513,\"ĠDino\":32514,\"Ġhemisphere\":32515,\"Ġfroze\":32516,\"ĠPeg\":32517,\"Ġmicroscope\":32518,\"Ġmoderates\":32519,\"ĠGEN\":32520,\"ĠHawai\":32521,\"Ġstagn\":32522,\"Absolutely\":32523,\"practice\":32524,\"IBLE\":32525,\"cture\":32526,\"ĠAshe\":32527,\"Ġcondoms\":32528,\"Ġpoked\":32529,\"training\":32530,\"Ġintermedi\":32531,\"347\":32532,\"Ġcardinal\":32533,\"ĠSpoon\":32534,\"Ġsupp\":32535,\"Ġpreviews\":32536,\"Service\":32537,\"ĠBeam\":32538,\"Ġtranscend\":32539,\"Fresh\":32540,\"Sure\":32541,\"Ġ4000\":32542,\"idential\":32543,\"ĠCoinbase\":32544,\"Ġworkings\":32545,\"ĠPI\":32546,\"Ġpassionately\":32547,\"Ġdecisively\":32548,\"ĠInspection\":32549,\"Ġinvoke\":32550,\"Ġstain\":32551,\"Ġcleaners\":32552,\"Ġregulates\":32553,\"Ġshone\":32554,\"ĠEVERY\":32555,\"istance\":32556,\"map\":32557,\"Ġredu\":32558,\"Ġoccupies\":32559,\"Ġprocure\":32560,\"acket\":32561,\"roman\":32562,\"Ġilleg\":32563,\"Ġleaps\":32564,\"yond\":32565,\"Ġyarn\":32566,\"ĠLTD\":32567,\"ĠCONTR\":32568,\"ĠRestoration\":32569,\"ĠCDs\":32570,\"Ġdrinkers\":32571,\"ĠJordanian\":32572,\"Ġabl\":32573,\"Ġdisparate\":32574,\"Ġprimed\":32575,\"ĠFirearms\":32576,\"artz\":32577,\"Ġindispensable\":32578,\"Ter\":32579,\"Ġfright\":32580,\"Ġmarkedly\":32581,\"Ġroam\":32582,\"ĠJurassic\":32583,\"Ġfeder\":32584,\"Ġpepp\":32585,\"ĠDV\":32586,\"Ġpancakes\":32587,\"sweet\":32588,\"Ġunmatched\":32589,\"Ġassembling\":32590,\"Ultimately\":32591,\"Ġendeavour\":32592,\"Ġluckily\":32593,\"Ġbitch\":32594,\"Ġelegance\":32595,\"eers\":32596,\"drop\":32597,\"credit\":32598,\"Ġscourge\":32599,\"ĠMinimum\":32600,\"Ġimpatient\":32601,\"Ġhunted\":32602,\"ĠGoddard\":32603,\"Kal\":32604,\"Ġmined\":32605,\"Ġcalves\":32606,\"Ġ234\":32607,\"Ġplank\":32608,\"Ġinjecting\":32609,\"ĠKaufman\":32610,\"ĠCompliance\":32611,\"tone\":32612,\"Ġ345\":32613,\"Ġdazz\":32614,\"ĠClarks\":32615,\"Ġcomprehens\":32616,\"Ġpist\":32617,\"Ġrhythms\":32618,\"Ġreserv\":32619,\"337\":32620,\"ĠIDF\":32621,\"Ġshouts\":32622,\"midt\":32623,\"323\":32624,\"Ġsoothing\":32625,\"Ġadministr\":32626,\"Ġgloomy\":32627,\"Ġfutile\":32628,\"ĠProhibition\":32629,\"upon\":32630,\"ĠAnglic\":32631,\"seeking\":32632,\"Ġdodge\":32633,\"Ds\":32634,\"ĠGrants\":32635,\"editor\":32636,\"ĠInquis\":32637,\"Ġ1929\":32638,\"decl\":32639,\"ĠPorts\":32640,\"ĠCure\":32641,\"ĠDPRK\":32642,\"oct\":32643,\"Ġvocabulary\":32644,\"Ġcling\":32645,\"298\":32646,\"Ġpeac\":32647,\"Ġantibodies\":32648,\"dor\":32649,\"ĠWorse\":32650,\"Ġsmelled\":32651,\"Ġleash\":32652,\"MED\":32653,\"Ġdisinteg\":32654,\"Ġtruthful\":32655,\"Ġsalesman\":32656,\"Ġsquares\":32657,\"susp\":32658,\"Ġcraving\":32659,\"Ġwizard\":32660,\"moral\":32661,\"ĠQuÃ©\":32662,\"Anything\":32663,\"Ġfalsehood\":32664,\"ARI\":32665,\"Ġcoworkers\":32666,\"Ġthy\":32667,\"outher\":32668,\"Ġbrushing\":32669,\"ĠProtest\":32670,\"ĠMF\":32671,\"abba\":32672,\"lead\":32673,\"ĠExhibit\":32674,\"Ga\":32675,\"ĠFranks\":32676,\"Ġdictates\":32677,\"illegal\":32678,\"Ġrelayed\":32679,\"Ġploy\":32680,\"ĠØ§ÙĦ\":32681,\"ĠDocuments\":32682,\"Ġtint\":32683,\"ĠYuan\":32684,\"Ġdepended\":32685,\"Mir\":32686,\"ĠIntrodu\":32687,\"Ġrecourse\":32688,\"oqu\":32689,\"ĠTED\":32690,\"Ġdifferentiated\":32691,\"ĠWalls\":32692,\"Ġsentimental\":32693,\"Ġantis\":32694,\"retion\":32695,\"comes\":32696,\"ĠWORLD\":32697,\"Ġcoax\":32698,\"ĠTatt\":32699,\"ĠGingrich\":32700,\"2006\":32701,\"ĠBrut\":32702,\"Second\":32703,\"posed\":32704,\"shots\":32705,\"Ġ313\":32706,\"idian\":32707,\"alking\":32708,\"Ġdens\":32709,\"Ġgif\":32710,\"akings\":32711,\"Ġkeywords\":32712,\"Ġchast\":32713,\"Ġadversary\":32714,\"Ġnick\":32715,\"iasis\":32716,\"ĠLegisl\":32717,\"Ġcoff\":32718,\"ĠOriental\":32719,\"ĠMorg\":32720,\"ĠHAR\":32721,\"Ġlegalizing\":32722,\"Ġbanter\":32723,\"ĠTart\":32724,\"ĠTRI\":32725,\"Ġantagon\":32726,\"ĠGF\":32727,\"oler\":32728,\"ĠUFO\":32729,\"Therefore\":32730,\"ĠOsama\":32731,\"ĠStructure\":32732,\"apps\":32733,\"Ġpee\":32734,\"ĠSomehow\":32735,\"ĠOverwatch\":32736,\"ĠCasual\":32737,\"Ġdishon\":32738,\"SEE\":32739,\"ctive\":32740,\"andering\":32741,\"ĠTransformation\":32742,\"Andy\":32743,\"ĠFever\":32744,\"Ġspectator\":32745,\"Ġlash\":32746,\"Ġprotector\":32747,\"apy\":32748,\"Ġexhilar\":32749,\"aroo\":32750,\"Ġmamm\":32751,\"Ġbystand\":32752,\"acky\":32753,\"Ġdigestive\":32754,\"Ġamplified\":32755,\"Ġalpha\":32756,\"continue\":32757,\"Low\":32758,\"Ġdisgusted\":32759,\"356\":32760,\"script\":32761,\"Ġgenerational\":32762,\"ĠPassenger\":32763,\"sight\":32764,\"Ġcout\":32765,\"Ġhone\":32766,\"ulse\":32767,\"Ġignite\":32768,\"284\":32769,\"gow\":32770,\"Ġbinary\":32771,\"Ġincess\":32772,\"Review\":32773,\"607\":32774,\"ĠSurprise\":32775,\"Ġirritation\":32776,\"ĠBarth\":32777,\"ĠGum\":32778,\"Ġvideot\":32779,\"ĠFres\":32780,\"asons\":32781,\"Ġcollaborator\":32782,\"fal\":32783,\"ĠGon\":32784,\"Ġsettles\":32785,\"regular\":32786,\"Ġmiscarriage\":32787,\"cube\":32788,\"Ġsubord\":32789,\"ĠRegistered\":32790,\"Ġnotions\":32791,\"zzy\":32792,\"Ġrevert\":32793,\"OFF\":32794,\"Ġhasht\":32795,\"ĠPNG\":32796,\"Ġunimaginable\":32797,\"builders\":32798,\"Taylor\":32799,\"ĠPAY\":32800,\"Ġ).\":32801,\"Ġ238\":32802,\"ĠLAST\":32803,\"MAS\":32804,\"Ġillustrations\":32805,\"Ġparody\":32806,\"Ġdispersed\":32807,\"ĠRoses\":32808,\"Ġestimation\":32809,\"ĠGets\":32810,\"Patrick\":32811,\"CHA\":32812,\"Ġmisdem\":32813,\"agate\":32814,\"alter\":32815,\"Ġgeo\":32816,\"Ġenormously\":32817,\"Ġarrogance\":32818,\"Ġpert\":32819,\"Ġmeta\":32820,\"ĠJuno\":32821,\"iov\":32822,\"imov\":32823,\"Ġchores\":32824,\"acan\":32825,\"Paris\":32826,\"313\":32827,\"Lewis\":32828,\"Ġwillingly\":32829,\"ERA\":32830,\"Ġencaps\":32831,\"ilk\":32832,\"Ġnodes\":32833,\"Ġenzyme\":32834,\"want\":32835,\"Ġtolerant\":32836,\"Ġcondos\":32837,\"Ġasserts\":32838,\"Ġcanon\":32839,\"Ġscanned\":32840,\"bishop\":32841,\"Ġperched\":32842,\"util\":32843,\"ĠBonus\":32844,\"create\":32845,\"ĠFuk\":32846,\"Ġmotif\":32847,\"Ġcontemplate\":32848,\"ĠBEN\":32849,\"imir\":32850,\"Ġacadem\":32851,\"uvian\":32852,\"ĠIdeas\":32853,\"ĠCY\":32854,\"Ġants\":32855,\"Ġprostitutes\":32856,\"2005\":32857,\"Spring\":32858,\"ĠBarrel\":32859,\"ĠAunt\":32860,\"ĠLudwig\":32861,\"ĠHerm\":32862,\"PRO\":32863,\"obiles\":32864,\"rack\":32865,\"STER\":32866,\"ucket\":32867,\"Ġmun\":32868,\"Ġ419\":32869,\"ICES\":32870,\"Ġcardio\":32871,\"Ġtrenches\":32872,\"Nation\":32873,\"yahoo\":32874,\"Ġburd\":32875,\"Ġnost\":32876,\"Ġappropriations\":32877,\"ĠChili\":32878,\"Josh\":32879,\"GW\":32880,\"Ġoppressed\":32881,\"ĠBEFORE\":32882,\"Ġmurderous\":32883,\"Pen\":32884,\"achable\":32885,\"Ġrive\":32886,\"Ġculmin\":32887,\"Ġdefin\":32888,\"ĠMord\":32889,\"idate\":32890,\"ĠChim\":32891,\"ource\":32892,\"ĠElectro\":32893,\"orthy\":32894,\"Ġcalendars\":32895,\"regation\":32896,\"Ġretrospect\":32897,\"ĠTribal\":32898,\"ĠHes\":32899,\"Ġcran\":32900,\"Ġcreditor\":32901,\"Ġfibers\":32902,\"note\":32903,\"idays\":32904,\"ĠSebast\":32905,\"ĠKitty\":32906,\"Ġplainly\":32907,\"ĠLAPD\":32908,\"Ġtrumpet\":32909,\"ĠAppropriations\":32910,\"Hill\":32911,\"ĠVeget\":32912,\"296\":32913,\"lated\":32914,\"othes\":32915,\"ibrarian\":32916,\"Listen\":32917,\"nex\":32918,\"WHO\":32919,\"Ġshampoo\":32920,\"Ġclaimants\":32921,\"Ġisol\":32922,\"Ġunchecked\":32923,\"Ġmov\":32924,\"umo\":32925,\"ĠLens\":32926,\"Ġdiscreet\":32927,\"Ġrespectfully\":32928,\"Ġreclaimed\":32929,\"ĠHatt\":32930,\"thus\":32931,\"ĠFlo\":32932,\"Ġsumm\":32933,\"phas\":32934,\"ĠHaitian\":32935,\"Ġstrife\":32936,\"Ġabound\":32937,\"verted\":32938,\"Ġpatronage\":32939,\"449\":32940,\"Ġprelim\":32941,\"ĠZhu\":32942,\"ĠRevel\":32943,\"adic\":32944,\"Ġminded\":32945,\"ĠStability\":32946,\"Ġresembling\":32947,\"Ġvending\":32948,\"ischer\":32949,\"Ġkisses\":32950,\"Ġsuperiority\":32951,\"Ġinfinite\":32952,\"ISC\":32953,\"880\":32954,\"Ġappease\":32955,\"VO\":32956,\"404\":32957,\"ECH\":32958,\"gam\":32959,\"River\":32960,\"metal\":32961,\"determination\":32962,\"Cook\":32963,\"Ġbuds\":32964,\"Ġ(%)\":32965,\"ĠCreated\":32966,\"Ġstrut\":32967,\"Ġ425\":32968,\"Ġverte\":32969,\"ĠOrb\":32970,\"Ġweaving\":32971,\"261\":32972,\"Ġflyers\":32973,\"spons\":32974,\"ĠCovenant\":32975,\"570\":32976,\"Ġintangible\":32977,\"ĠBJ\":32978,\"ĠStead\":32979,\"ĠBrune\":32980,\"pain\":32981,\"independent\":32982,\"Ball\":32983,\"witch\":32984,\"ĠIon\":32985,\"Ġpupp\":32986,\"Cash\":32987,\"ĠConvert\":32988,\"Ġimpede\":32989,\"broad\":32990,\"onew\":32991,\"Ġsynergy\":32992,\"Ġcoined\":32993,\"620\":32994,\"ivalent\":32995,\"ĠInfect\":32996,\"ĠAqua\":32997,\"Together\":32998,\"ĠChemistry\":32999,\"ĠURL\":33000,\"ampion\":33001,\"Ġdeclarations\":33002,\"Ġaffirmative\":33003,\"umper\":33004,\"ĠTarant\":33005,\"Ġstereotype\":33006,\"Ġbookstore\":33007,\"incre\":33008,\"Ġchipset\":33009,\"Ġangst\":33010,\"Jose\":33011,\"laus\":33012,\"Ġheater\":33013,\"ipers\":33014,\"Ġeminent\":33015,\"hook\":33016,\"sticks\":33017,\"ĠCoul\":33018,\"Ġmildly\":33019,\"SG\":33020,\"Ġworm\":33021,\"Ġdisable\":33022,\"Ġperfume\":33023,\"ISTER\":33024,\"Ġgathers\":33025,\"ĠLotus\":33026,\"hyp\":33027,\"actus\":33028,\"Ġdistinctly\":33029,\"fifth\":33030,\"!),\":33031,\"ĠCrunch\":33032,\"Ġcohesive\":33033,\"Ġfortunately\":33034,\"Ġninety\":33035,\"Ġcartels\":33036,\"empl\":33037,\"Direct\":33038,\"Ġcommuting\":33039,\"ĠSX\":33040,\"ractive\":33041,\"Ġtranslating\":33042,\"ĠAQ\":33043,\"Ġslay\":33044,\"abuse\":33045,\"ĠProc\":33046,\"ĠCantor\":33047,\"ĠTas\":33048,\"Sir\":33049,\"Thom\":33050,\"ĠCHRIST\":33051,\"Ġreceptive\":33052,\"ĠCornel\":33053,\"Arab\":33054,\"Ġgrammar\":33055,\"Ġhandlers\":33056,\"Ġalloy\":33057,\"Ġthinly\":33058,\"adem\":33059,\"Ġproponent\":33060,\"ĠPVC\":33061,\"Ġstump\":33062,\"tom\":33063,\"rets\":33064,\"iciency\":33065,\"780\":33066,\"Ġ311\":33067,\"ĠClapper\":33068,\"ITAL\":33069,\"Ùħ\":33070,\"Ġnarrator\":33071,\"Ġblond\":33072,\"Ġintermittent\":33073,\"Ġcollabor\":33074,\"646\":33075,\"Ġmetast\":33076,\"Ġregeneration\":33077,\"ĠLegendary\":33078,\"Ġgenitals\":33079,\"Ġbartender\":33080,\"atson\":33081,\"Okay\":33082,\"Ġpassages\":33083,\"Ġsubstituted\":33084,\"orr\":33085,\"ALTH\":33086,\"Ġartic\":33087,\"Ġascent\":33088,\"Ġmatured\":33089,\"Ġterminology\":33090,\"served\":33091,\"ĠDeliver\":33092,\"Ġattic\":33093,\"anges\":33094,\"Ġrenaissance\":33095,\"Ġbleed\":33096,\"claimer\":33097,\"onse\":33098,\"Sec\":33099,\"Ġparticle\":33100,\"aneous\":33101,\"ateur\":33102,\"Ġzeal\":33103,\"ĠPets\":33104,\"Working\":33105,\"ĠRespect\":33106,\"Ġsermon\":33107,\"ĠProvided\":33108,\"Ġfilibuster\":33109,\"Ġabolished\":33110,\"reviewed\":33111,\"cription\":33112,\"Ġrevers\":33113,\"atered\":33114,\"435\":33115,\"Ġwhe\":33116,\"ometown\":33117,\"UFC\":33118,\"products\":33119,\"Winter\":33120,\"Ġ304\":33121,\"Ġsporadic\":33122,\"orough\":33123,\"EB\":33124,\"ĠAgric\":33125,\"ĠMTA\":33126,\"wic\":33127,\"Ġpowerless\":33128,\"Ġcarrot\":33129,\"ww\":33130,\"Ġabsorption\":33131,\"ĠTyphoon\":33132,\"Turkey\":33133,\"Ġproclaim\":33134,\"Ġhikers\":33135,\"Ġpractise\":33136,\"/$\":33137,\"Ġfingertips\":33138,\"Ġbaff\":33139,\"vu\":33140,\"Ġans\":33141,\"plug\":33142,\"Ġacquaintance\":33143,\"itement\":33144,\"ihar\":33145,\"Ġreluctantly\":33146,\"Ġforc\":33147,\"Ġguarant\":33148,\"ĠWanted\":33149,\"Walk\":33150,\"addle\":33151,\"unders\":33152,\"Fred\":33153,\"Ġtides\":33154,\"ĠBai\":33155,\"Ġcountering\":33156,\"raper\":33157,\"ursions\":33158,\"ĠFlav\":33159,\"pared\":33160,\"raised\":33161,\"Ñı\":33162,\"ĠDiff\":33163,\"Ġreload\":33164,\"ourses\":33165,\"ĠBurning\":33166,\"Ġwand\":33167,\"Ġledger\":33168,\"Ġcoughing\":33169,\"ĠLoren\":33170,\"Nazis\":33171,\"Ġcompile\":33172,\"Eight\":33173,\"icultural\":33174,\"yy\":33175,\"Ġ1932\":33176,\"Run\":33177,\"AIN\":33178,\"Ġattractiveness\":33179,\"ĠOmn\":33180,\"Ġconfer\":33181,\"compliance\":33182,\"Ġembed\":33183,\"Steven\":33184,\"2001\":33185,\"Ġdecre\":33186,\"Ġprompts\":33187,\"ĠHare\":33188,\"Ġleaping\":33189,\"Ġslaughtered\":33190,\"Ġforfeiture\":33191,\"342\":33192,\"Charl\":33193,\"CDC\":33194,\"ographically\":33195,\"Ġduplicate\":33196,\"Ġdistracting\":33197,\"examination\":33198,\"Ġpeas\":33199,\"Ġcatchy\":33200,\"Ġdives\":33201,\"ĠAda\":33202,\"Hay\":33203,\"Ġenthusiastically\":33204,\"Ġfunky\":33205,\"kay\":33206,\"EVA\":33207,\"Ġpsychologists\":33208,\"Ġancestry\":33209,\"iyah\":33210,\"ifter\":33211,\"nob\":33212,\"518\":33213,\"rouse\":33214,\"Ġchord\":33215,\"Ġcone\":33216,\"Ġbarracks\":33217,\"ĠRoyale\":33218,\"ĠIntegration\":33219,\"Ġtrolling\":33220,\"ĠSynt\":33221,\"andals\":33222,\"ĠGrain\":33223,\"ĠNeck\":33224,\"618\":33225,\"Ġrapist\":33226,\"pins\":33227,\"Ġwitty\":33228,\"Ġdehydration\":33229,\"arlane\":33230,\"Ġimmoral\":33231,\"Ġaccum\":33232,\"ĠMcAuliffe\":33233,\"slow\":33234,\"Ġinjust\":33235,\"Ġ1700\":33236,\"Ġcarbs\":33237,\"Ġintel\":33238,\"Non\":33239,\"isks\":33240,\"Tre\":33241,\"Ġinterviewer\":33242,\"sam\":33243,\"Ġdelve\":33244,\"Ġadmirable\":33245,\"ĠROM\":33246,\"ĠHispanics\":33247,\"Ġimpart\":33248,\"Ġunderrated\":33249,\"Ġvictimized\":33250,\"ĠPsych\":33251,\"ppings\":33252,\"Ġ610\":33253,\"pole\":33254,\"Ġdiner\":33255,\"ĠScale\":33256,\"Ġunforeseen\":33257,\"surprisingly\":33258,\"opus\":33259,\"ĠCOURT\":33260,\"Ġjuggling\":33261,\"ĠFacilities\":33262,\"Aid\":33263,\"ĠHPV\":33264,\"Ġcrawling\":33265,\"flu\":33266,\"etary\":33267,\"ĠHarriet\":33268,\"329\":33269,\"ĠSod\":33270,\"ĠBiological\":33271,\"birth\":33272,\"ribed\":33273,\"Ġpulses\":33274,\"396\":33275,\"eways\":33276,\"ĠAlma\":33277,\"nov\":33278,\"015\":33279,\"ricane\":33280,\"agna\":33281,\"Ak\":33282,\"ĠClaim\":33283,\"Ġpref\":33284,\"Ġinterfaces\":33285,\"ĠADHD\":33286,\"604\":33287,\"ZE\":33288,\"venture\":33289,\"Ġascend\":33290,\"ĠGou\":33291,\"Ġpriceless\":33292,\"redo\":33293,\"kw\":33294,\"Conf\":33295,\"Ġmah\":33296,\"Ġpoets\":33297,\"Ġstalk\":33298,\"Ġencamp\":33299,\"Ġhopped\":33300,\"Ġmelody\":33301,\"JECT\":33302,\"eming\":33303,\"Ġbewild\":33304,\"aternal\":33305,\"uchs\":33306,\"dit\":33307,\"ĠTransmission\":33308,\"Lake\":33309,\"Ġatoms\":33310,\"ĠThoughts\":33311,\"ilts\":33312,\"volume\":33313,\"Ġsocioeconomic\":33314,\"atisf\":33315,\"Ġnarr\":33316,\"zinski\":33317,\"ymes\":33318,\"episode\":33319,\"Ġinherit\":33320,\"Ġintending\":33321,\"Ġarenas\":33322,\"uras\":33323,\"burning\":33324,\"334\":33325,\"teenth\":33326,\"Ġsophistication\":33327,\"Ġscreenshots\":33328,\"Ġautistic\":33329,\"lip\":33330,\"paper\":33331,\"Ġmonopol\":33332,\"799\":33333,\"forms\":33334,\"ocrats\":33335,\"Ġpineapple\":33336,\"Ġbegs\":33337,\"Ġpersecuted\":33338,\"Ġsubscribed\":33339,\"Ġelic\":33340,\"ĠPRESIDENT\":33341,\"297\":33342,\"Ġpreferential\":33343,\"Ġpyramid\":33344,\"Ġconvergence\":33345,\"Ġwob\":33346,\"Project\":33347,\"ĠAluminum\":33348,\"ĠJPM\":33349,\"ĠBAT\":33350,\"Ġdolphins\":33351,\"018\":33352,\"healthy\":33353,\"ĠCG\":33354,\"ĠEffective\":33355,\"worm\":33356,\"ĠEas\":33357,\"olicited\":33358,\"ĠUSE\":33359,\"ĠCaval\":33360,\"Ġswirl\":33361,\"Ġspaghetti\":33362,\"Ġinward\":33363,\"Republican\":33364,\"Ġpublicized\":33365,\"Ġeconomical\":33366,\"Ġsalsa\":33367,\"ĠTitanic\":33368,\"dot\":33369,\"Ġcontro\":33370,\"ĠBangl\":33371,\"iban\":33372,\"ĠKlux\":33373,\"Ġhinges\":33374,\"610\":33375,\"Ġvalves\":33376,\"profits\":33377,\"Wonder\":33378,\"Ġorient\":33379,\"Ġsque\":33380,\"Ġprivatization\":33381,\"Obama\":33382,\"Thousands\":33383,\"ĠTasman\":33384,\"Ġmaze\":33385,\"eem\":33386,\"Ġsurvives\":33387,\"istant\":33388,\"Ġenriched\":33389,\"Ġencl\":33390,\"Ġcompliments\":33391,\"ĠShoes\":33392,\"Ġinsanity\":33393,\"consider\":33394,\"agog\":33395,\"Ġbaffled\":33396,\"ĠÂ°\":33397,\"ĠWordPress\":33398,\"qus\":33399,\"usual\":33400,\"stall\":33401,\"Deb\":33402,\"ĠRothschild\":33403,\"Ġesche\":33404,\"Ġsoph\":33405,\"Ġambiguous\":33406,\"negative\":33407,\"Ġdiscouraging\":33408,\"Alexander\":33409,\"319\":33410,\"Ġsummon\":33411,\"ipation\":33412,\"000000\":33413,\"Ġminimalist\":33414,\"Ġenraged\":33415,\"777\":33416,\"Ġplanetary\":33417,\"Ġthroughput\":33418,\"Ġtemperament\":33419,\"ĠNIC\":33420,\"ileged\":33421,\"minster\":33422,\"ĠPLEASE\":33423,\"Ġexagger\":33424,\"ĠDescription\":33425,\"Ġagitated\":33426,\"Ġimmortal\":33427,\"Ġrenders\":33428,\"Ġcharisma\":33429,\"sequ\":33430,\"Ġmajorities\":33431,\"Ġfreaking\":33432,\"ĠAdvice\":33433,\"Ġembodies\":33434,\"stable\":33435,\"Ġcustomization\":33436,\"started\":33437,\"ĠAutism\":33438,\"Ġparticipates\":33439,\"ĠUTC\":33440,\"Marco\":33441,\"Ġoddly\":33442,\"Ġantiqu\":33443,\"ĠPear\":33444,\"ĠFey\":33445,\"Ġcertify\":33446,\"Ġdisillusion\":33447,\"ĠPhysicians\":33448,\"obl\":33449,\"855\":33450,\"Ġelim\":33451,\"Ġ335\":33452,\"Ol\":33453,\"ĠSear\":33454,\"Ġnuances\":33455,\"past\":33456,\"Sa\":33457,\"ĠSlov\":33458,\"Ġfiltered\":33459,\"Ġanalogy\":33460,\"Ġformulate\":33461,\"Ġarmies\":33462,\"Ġpuls\":33463,\"fters\":33464,\"ilipp\":33465,\"ĠHOT\":33466,\"485\":33467,\"ĠAfghans\":33468,\"Ġtopical\":33469,\"ĠBunny\":33470,\"seeing\":33471,\"Ġeloqu\":33472,\"Ġkidneys\":33473,\"ĠDEM\":33474,\"pent\":33475,\"Ġhus\":33476,\"stores\":33477,\"ĠProtestant\":33478,\"Comm\":33479,\"label\":33480,\"Kings\":33481,\"ĠPurpose\":33482,\"âĢ¦..\":33483,\"Ġaccumulating\":33484,\"calling\":33485,\"Ġgiveaways\":33486,\"Ġpredicament\":33487,\"Ġtyp\":33488,\"Ġtraveler\":33489,\"003\":33490,\"impro\":33491,\"fac\":33492,\"Ġmapped\":33493,\"itious\":33494,\"Ġmasculinity\":33495,\"Ġtantal\":33496,\"ĠDJs\":33497,\"Ġviewpoints\":33498,\"Burn\":33499,\"ĠWii\":33500,\"pak\":33501,\"ĠEB\":33502,\"Ġhinge\":33503,\"Ġfacets\":33504,\"Ġphotographic\":33505,\"Ġcompiling\":33506,\"Ġdecks\":33507,\"Ġarticulated\":33508,\"Federal\":33509,\"crim\":33510,\"llah\":33511,\"Ġfiasco\":33512,\"ĠLIST\":33513,\"oute\":33514,\"ĠDraper\":33515,\"ĠLaos\":33516,\"Ġclimbers\":33517,\"raph\":33518,\"ĠDek\":33519,\"WAY\":33520,\"Ġgreets\":33521,\"Ġoppressive\":33522,\"otor\":33523,\"otiation\":33524,\"\\\":[\":33525,\"Record\":33526,\"mining\":33527,\"Town\":33528,\"Ġfavorably\":33529,\"ĠYoutube\":33530,\"William\":33531,\"Ġlan\":33532,\"âĢ²\":33533,\"ĠSpec\":33534,\"Ġtranquil\":33535,\"ĠClient\":33536,\"oln\":33537,\"celona\":33538,\"Ġrealistically\":33539,\"Ġmisplaced\":33540,\"ĠBie\":33541,\"bye\":33542,\"Yo\":33543,\"465\":33544,\"ĠMadagascar\":33545,\"oplan\":33546,\"arist\":33547,\"Ġconfines\":33548,\"Ġï\":33549,\"awks\":33550,\"Ġpiracy\":33551,\"Ġunwelcome\":33552,\"Intel\":33553,\"Ġparanoid\":33554,\"CLAIM\":33555,\"Ġblush\":33556,\"united\":33557,\"Ġmotivational\":33558,\"ĠVII\":33559,\"Ġdiabetic\":33560,\"Ġantiv\":33561,\"Ġdissect\":33562,\"Ġbestselling\":33563,\"Ġfluffy\":33564,\"ĠRemote\":33565,\"Ġvert\":33566,\"Correct\":33567,\"Ġcolossal\":33568,\"Ġcontrasts\":33569,\"Ġcirca\":33570,\"ĠDamage\":33571,\"Ġunrel\":33572,\"Ġdiscrepancy\":33573,\"ĠCIS\":33574,\"ĠCLASS\":33575,\"ilty\":33576,\"Ġsynopsis\":33577,\"emed\":33578,\"cakes\":33579,\"ibal\":33580,\"inea\":33581,\"ienced\":33582,\"Ġimplicit\":33583,\"ĠLOOK\":33584,\"Ġsilhouette\":33585,\"affiliated\":33586,\"ĠHalo\":33587,\"377\":33588,\"Ġlyr\":33589,\"ĠVide\":33590,\"herent\":33591,\"Ġbadges\":33592,\"plays\":33593,\"orea\":33594,\"Ġjammed\":33595,\"cancer\":33596,\"ĠYep\":33597,\"racted\":33598,\"ĠDisability\":33599,\"Ġfooth\":33600,\"friends\":33601,\"Ġbloated\":33602,\"Bet\":33603,\"ĠAntioch\":33604,\"Ġintrodu\":33605,\"Ġannexed\":33606,\"ivism\":33607,\"ĠFlickr\":33608,\"pants\":33609,\"Ġinterruption\":33610,\"645\":33611,\"ĠIly\":33612,\"ĠOss\":33613,\"ĠAMA\":33614,\"Ġpolitely\":33615,\"Ġnatives\":33616,\"Ġrushes\":33617,\"enges\":33618,\"ĠHarm\":33619,\"Ġdestroyer\":33620,\"ĠEstimates\":33621,\"Ġtransforms\":33622,\"Ġinvariably\":33623,\"Ġcac\":33624,\"iency\":33625,\"599\":33626,\"Ġconstitutionally\":33627,\"Ġrappers\":33628,\"ĠSettlement\":33629,\"icz\":33630,\"Ġhardened\":33631,\"citizens\":33632,\"Ġcircling\":33633,\"Ġtrapping\":33634,\"Ġguaranteeing\":33635,\"690\":33636,\"agher\":33637,\"Ġarcade\":33638,\"Ġfanc\":33639,\"Ġslapping\":33640,\"OPS\":33641,\"Ġmasse\":33642,\"Ġpudding\":33643,\"Jac\":33644,\"ĠGraphics\":33645,\"Ġuptake\":33646,\"?,\":33647,\"Fair\":33648,\"ĠSatan\":33649,\"uffy\":33650,\"ĠGuatem\":33651,\"ĠTransaction\":33652,\"Ġunlocking\":33653,\"ĠLINE\":33654,\"Ġapprehens\":33655,\"Ġglean\":33656,\"291\":33657,\"Ġexacerbate\":33658,\"ĠTrave\":33659,\"ĠTrop\":33660,\"Supp\":33661,\"Ġqueens\":33662,\"cart\":33663,\"Ġscrolling\":33664,\"Ġox\":33665,\"cone\":33666,\"Matthew\":33667,\"ĠDIRECT\":33668,\"Ġbacker\":33669,\"Ġthyroid\":33670,\"Sarah\":33671,\"ĠEDIT\":33672,\"ĠActivision\":33673,\"352\":33674,\"Ġreinforcements\":33675,\"Ġding\":33676,\"Ġplush\":33677,\"Ġpeanuts\":33678,\"ĠFant\":33679,\"ĠPediatrics\":33680,\"Ġaccommodating\":33681,\"ĠPractices\":33682,\"Answer\":33683,\"racial\":33684,\"ĠConstant\":33685,\"740\":33686,\"strength\":33687,\"apist\":33688,\"Ġsynthes\":33689,\"ĠLeap\":33690,\"ĠFabric\":33691,\"Ġbrainstorm\":33692,\"obia\":33693,\"Ġconception\":33694,\"Ġtuberculosis\":33695,\"Ġmajestic\":33696,\"ĠTitus\":33697,\"ĠTee\":33698,\"Ġlikeness\":33699,\"ĠSEA\":33700,\"lite\":33701,\"Ġ950\":33702,\"sufficient\":33703,\"Ġtrem\":33704,\"Ġharshly\":33705,\"Ġredacted\":33706,\"Ġwelding\":33707,\"Ġperplex\":33708,\"Ġpoetic\":33709,\"Ġinsignificant\":33710,\"Ġware\":33711,\"Ġwandered\":33712,\"Ġmete\":33713,\"ĠSTART\":33714,\"Ġweaponry\":33715,\"opsy\":33716,\"shadow\":33717,\"Ġobsc\":33718,\"hare\":33719,\"ĠOPEN\":33720,\"Ġdiligent\":33721,\"Girls\":33722,\"Ġinitials\":33723,\"Start\":33724,\"ĠBrookings\":33725,\"ombs\":33726,\"Ġlashes\":33727,\"essor\":33728,\"Ġgravy\":33729,\"ĠUbuntu\":33730,\"Tree\":33731,\"Ġ435\":33732,\"Ġcellar\":33733,\"Ġaquarium\":33734,\"ĠPodesta\":33735,\"361\":33736,\"ĠController\":33737,\"Ġeru\":33738,\"reasonable\":33739,\"Ġpermissions\":33740,\"725\":33741,\"Ġadministering\":33742,\"Ġflirt\":33743,\"Ġfleeting\":33744,\"asive\":33745,\"Ġsubcontract\":33746,\"Ġfascist\":33747,\"Ġcabbage\":33748,\"science\":33749,\"Ġboiler\":33750,\"ioned\":33751,\"Ġintegrates\":33752,\"Ġresidue\":33753,\"KEY\":33754,\"Ġwi\":33755,\"Ġsquared\":33756,\"Unless\":33757,\"Ġmute\":33758,\"ĠTuc\":33759,\"Ġverb\":33760,\"Gary\":33761,\"Ġexperimentation\":33762,\"fee\":33763,\"chini\":33764,\"Ġmarrow\":33765,\"ĠBalt\":33766,\"Ġnodded\":33767,\"tn\":33768,\"Ġmissionary\":33769,\"OTO\":33770,\"Ġoptimum\":33771,\"555\":33772,\"Ġwhipping\":33773,\"aunts\":33774,\"ĠScene\":33775,\"Ġcharacterize\":33776,\"Ġretrospective\":33777,\"Ġutilizes\":33778,\"Ġhastily\":33779,\"older\":33780,\"ĠPW\":33781,\"Ġsleepy\":33782,\"020\":33783,\"ĠAcid\":33784,\"Ġridiculously\":33785,\"Ġgigg\":33786,\"649\":33787,\"Ġcrus\":33788,\"ĠShame\":33789,\"ĠTorn\":33790,\"finding\":33791,\"IPS\":33792,\"Ġplat\":33793,\"ometers\":33794,\"Ġamphib\":33795,\"ellow\":33796,\"ĠSpecies\":33797,\"commercial\":33798,\"Ġvirgin\":33799,\"Ġdarn\":33800,\"Ġsorely\":33801,\"Ġrespondent\":33802,\"Ġray\":33803,\"ĠCONS\":33804,\"Ġunequivocally\":33805,\"server\":33806,\"Ġdrip\":33807,\"ĠRazor\":33808,\"Ban\":33809,\"ĠHMS\":33810,\"Ġhijab\":33811,\"ĠMuss\":33812,\"Ġsandy\":33813,\"Ġaversion\":33814,\"Ġoverarching\":33815,\"Ġultr\":33816,\"ĠIraqis\":33817,\"Ġuninterrupted\":33818,\"Ġrouting\":33819,\"Ġundone\":33820,\"independence\":33821,\"gra\":33822,\"ysics\":33823,\"inflammatory\":33824,\"cussion\":33825,\"ĠDefinitely\":33826,\"Ġelastic\":33827,\"peer\":33828,\"ĠGiov\":33829,\"ĠMandarin\":33830,\"Ġscratches\":33831,\"Ġphysicist\":33832,\"Ġbestowed\":33833,\"usually\":33834,\"OULD\":33835,\"igration\":33836,\"Human\":33837,\"Dead\":33838,\"osph\":33839,\"bott\":33840,\"doctoral\":33841,\"Ġbending\":33842,\"Ġconfigurations\":33843,\"psych\":33844,\"db\":33845,\"ĠUD\":33846,\"Ġarteries\":33847,\"orically\":33848,\"Ġblasphemy\":33849,\"jj\":33850,\"checking\":33851,\"adian\":33852,\"IRD\":33853,\"ĠDialogue\":33854,\"Ġshielded\":33855,\"ĠVox\":33856,\"Dave\":33857,\"Ġturb\":33858,\"ĠMassive\":33859,\"ĠBMI\":33860,\"ĠNF\":33861,\"uced\":33862,\"ickle\":33863,\"ishable\":33864,\"Ġembody\":33865,\"ÙĪ\":33866,\"Senior\":33867,\"ĠResult\":33868,\"try\":33869,\"egu\":33870,\"401\":33871,\"ĠLoyal\":33872,\"Ġperilous\":33873,\"Ġdissu\":33874,\"Ġmythology\":33875,\"ĠWax\":33876,\"Jesus\":33877,\"ĠMotorsport\":33878,\"Ġadvis\":33879,\"ĠAki\":33880,\"ISM\":33881,\"tested\":33882,\"Ġplag\":33883,\"Ġriches\":33884,\"ĠOCT\":33885,\"ĠLocke\":33886,\"BG\":33887,\"Ġ460\":33888,\"rawl\":33889,\"ĠTermin\":33890,\"Ġ295\":33891,\"Ġchopping\":33892,\"KT\":33893,\"Ġconverts\":33894,\"Ask\":33895,\"alse\":33896,\"ĠKeynes\":33897,\"Ġrefuted\":33898,\"Ġrabbits\":33899,\"Ġbilingual\":33900,\"urse\":33901,\"ĠSalad\":33902,\"odiac\":33903,\"Ġsolidly\":33904,\"Dam\":33905,\"Ġpp\":33906,\"rities\":33907,\"Rah\":33908,\"itness\":33909,\"Ġsixty\":33910,\"332\":33911,\"cold\":33912,\"Ġhindered\":33913,\"Ġclipped\":33914,\"Ġreceptor\":33915,\"ĠHoms\":33916,\"Ġdusk\":33917,\"Ġarchae\":33918,\"LR\":33919,\"Ġrods\":33920,\"Ġ257\":33921,\"ĠSith\":33922,\"ĠPumpkin\":33923,\"ellation\":33924,\"ĠWD\":33925,\"Ġdecriminal\":33926,\"Ġusable\":33927,\"Ġcheerful\":33928,\"ĠInform\":33929,\"Ġbrushes\":33930,\"vier\":33931,\"ĠBrush\":33932,\"590\":33933,\"boost\":33934,\"guided\":33935,\"ĠMJ\":33936,\"Ġsatirical\":33937,\"ortion\":33938,\"efficiency\":33939,\"Ġstrands\":33940,\"ĠWilde\":33941,\"Ġreproduce\":33942,\"verage\":33943,\"Ġlug\":33944,\"Ġhist\":33945,\"offer\":33946,\"Ġcollapses\":33947,\"Ġclerks\":33948,\"Ġairstrike\":33949,\"IPP\":33950,\"iscover\":33951,\"Ġnefarious\":33952,\"Ġstripe\":33953,\"Ġbona\":33954,\"ocon\":33955,\"Ġpunishments\":33956,\"ITED\":33957,\"ĠAltern\":33958,\"testing\":33959,\"Ġeerie\":33960,\"erous\":33961,\"Ġcaves\":33962,\"Ġcondemns\":33963,\"ĠDropbox\":33964,\"inese\":33965,\"axis\":33966,\"ĠRegistry\":33967,\"ĠMong\":33968,\"Ġbullies\":33969,\"Ġdocks\":33970,\"ĠAlter\":33971,\"rella\":33972,\"446\":33973,\"ĠDare\":33974,\"Ġvirtues\":33975,\"Ġdont\":33976,\"Value\":33977,\"ENE\":33978,\"received\":33979,\"Ġseaf\":33980,\"476\":33981,\"ilon\":33982,\"ĠKits\":33983,\"Ġrarity\":33984,\"Ġnurt\":33985,\"skin\":33986,\"ĠUL\":33987,\"ĠRegiment\":33988,\"terior\":33989,\"hate\":33990,\"ĠEstimated\":33991,\"ĠSilence\":33992,\"Ġorganism\":33993,\"ĠSigned\":33994,\"ĠIA\":33995,\"bite\":33996,\"Ġthicker\":33997,\"Ġeyeb\":33998,\"Ġjournalistic\":33999,\"ĠDisp\":34000,\"margin\":34001,\"Dri\":34002,\"Ġcomplexes\":34003,\"Ġimaginary\":34004,\"Ġrefuel\":34005,\"Ġmeticulous\":34006,\"Dub\":34007,\"Ġhaze\":34008,\"860\":34009,\"Ġproverbial\":34010,\"Ġozone\":34011,\"cale\":34012,\"resent\":34013,\"Ġdiscrete\":34014,\"boats\":34015,\"Ġ343\":34016,\"ĠRET\":34017,\"Ġsailor\":34018,\"hair\":34019,\"gear\":34020,\"Ġmalt\":34021,\"Ġpeach\":34022,\"ĠRabb\":34023,\"699\":34024,\"318\":34025,\"ĠVerge\":34026,\"Fin\":34027,\"ĠMighty\":34028,\"ierce\":34029,\"403\":34030,\"Ġdisenfranch\":34031,\"bass\":34032,\"nice\":34033,\"Ġsinks\":34034,\"ĠLaugh\":34035,\"367\":34036,\"ĠZur\":34037,\"Ġtravers\":34038,\"ĠMystery\":34039,\"onsense\":34040,\"ĠMonarch\":34041,\"Ġleapt\":34042,\"ergy\":34043,\"porate\":34044,\"display\":34045,\"ilet\":34046,\"Ġendemic\":34047,\"Bern\":34048,\"Ġpulmonary\":34049,\"Ġbroch\":34050,\"ĠManziel\":34051,\"Lyn\":34052,\"Repe\":34053,\"lda\":34054,\"hands\":34055,\"Ġtroublesome\":34056,\"Jordan\":34057,\"UTION\":34058,\"ĠALP\":34059,\"ĠLEG\":34060,\"Ġreconnaissance\":34061,\"ĠRNA\":34062,\"letters\":34063,\"ĠYounger\":34064,\"ĠLW\":34065,\"ĠSensor\":34066,\"388\":34067,\"Ġwielding\":34068,\"spr\":34069,\"Ġancestral\":34070,\"331\":34071,\"OTH\":34072,\"ĠAxis\":34073,\"irement\":34074,\"ĠCompact\":34075,\"voice\":34076,\"Ġpercussion\":34077,\"Ġendeav\":34078,\"Kate\":34079,\"ĠJACK\":34080,\"ĠMagnus\":34081,\"Ġinterconnected\":34082,\"ĠTraff\":34083,\"demon\":34084,\"Ġardent\":34085,\"ĠSomers\":34086,\"andum\":34087,\"346\":34088,\"heartedly\":34089,\"ayne\":34090,\"Design\":34091,\"melon\":34092,\"ĠCarib\":34093,\"Ġ1935\":34094,\"intention\":34095,\"cape\":34096,\"cend\":34097,\"organic\":34098,\"373\":34099,\"ĠRevival\":34100,\"ĠBLACK\":34101,\"Ġaspiration\":34102,\"yellow\":34103,\"bodied\":34104,\"Ġcrave\":34105,\"ĠIntelligent\":34106,\"ĠUnique\":34107,\"tab\":34108,\"386\":34109,\"ĠNess\":34110,\"Official\":34111,\"Stay\":34112,\"Ġcreat\":34113,\"iliary\":34114,\"rified\":34115,\"ĠPok\":34116,\"Ġabolition\":34117,\"Ka\":34118,\"ĠCourage\":34119,\"ĠDickens\":34120,\"rophic\":34121,\"ĠFAR\":34122,\"Ġfurnished\":34123,\".âĢĵ\":34124,\"rete\":34125,\"Ġvaginal\":34126,\"hner\":34127,\"ĠLONG\":34128,\"imates\":34129,\"ĠLiter\":34130,\"ĠMeasures\":34131,\"ĠBelg\":34132,\"\\\"-\":34133,\"ĠRaider\":34134,\"enario\":34135,\"rification\":34136,\"ĠFISA\":34137,\"ĠStab\":34138,\"Ġnar\":34139,\"mund\":34140,\"Tenn\":34141,\"Ġwakes\":34142,\"Ġcharg\":34143,\"okers\":34144,\"assment\":34145,\"Ġsiph\":34146,\"Ġludicrous\":34147,\"670\":34148,\"Ġcompositions\":34149,\"Ġpinnacle\":34150,\"ĠRankings\":34151,\"ĠTelescope\":34152,\"secure\":34153,\"Ġib\":34154,\"Ġaptly\":34155,\"paste\":34156,\"ĠJUST\":34157,\"RD\":34158,\"herry\":34159,\"sung\":34160,\"Ġmig\":34161,\"naires\":34162,\"Ġmigrated\":34163,\"Base\":34164,\"Ġamazingly\":34165,\"Ġunregulated\":34166,\"published\":34167,\"ĠPIT\":34168,\"ĠMissile\":34169,\"extreme\":34170,\"ĠAlone\":34171,\"skilled\":34172,\"ĠRamp\":34173,\"Ġcamer\":34174,\"Ġflyer\":34175,\"Ġbrewers\":34176,\"ĠReference\":34177,\"ĠMOV\":34178,\"ĠLep\":34179,\"Ġentitle\":34180,\"ivals\":34181,\"ĠPIN\":34182,\"Ġbatches\":34183,\"Ġunexplained\":34184,\"Ġenergies\":34185,\"Ġblurred\":34186,\"enged\":34187,\"orig\":34188,\"WF\":34189,\"olves\":34190,\"ĠPicks\":34191,\"ĠTwice\":34192,\"arranted\":34193,\"Ġmembrane\":34194,\"ĠMoonlight\":34195,\"Ġsulfur\":34196,\"Ġpurposely\":34197,\"Ġfumes\":34198,\"Ġ(#\":34199,\"onics\":34200,\"ivities\":34201,\"rollers\":34202,\"Ġflattering\":34203,\"felt\":34204,\"Ġintoxication\":34205,\"Bridge\":34206,\"ĠFallout\":34207,\"Ġcreatively\":34208,\"Ġpsychologically\":34209,\"Ġdespicable\":34210,\"gae\":34211,\"820\":34212,\"VERS\":34213,\"Ġtidal\":34214,\"Ġcarbohydrates\":34215,\"strip\":34216,\"Ġgravitational\":34217,\"Ġfeds\":34218,\"ĠZhao\":34219,\"legates\":34220,\"Ġ307\":34221,\"String\":34222,\"ĠRepair\":34223,\"Ġ1928\":34224,\"orses\":34225,\"atography\":34226,\"Boston\":34227,\"Ġasymm\":34228,\"ĠSomebody\":34229,\"Van\":34230,\"ĠSovereign\":34231,\"Ġnotoriety\":34232,\"Ġsimulate\":34233,\"ĠDiscussion\":34234,\"ĠTransition\":34235,\"Ġcopying\":34236,\"antage\":34237,\"ĠRodrig\":34238,\"Ġindifference\":34239,\"Ġ580\":34240,\"Ġastronomical\":34241,\"Ġscrews\":34242,\"840\":34243,\"inates\":34244,\"ĠStreaming\":34245,\"Ġentit\":34246,\"ĠLiterature\":34247,\"369\":34248,\"805\":34249,\"OTS\":34250,\"Ð¾\":34251,\"img\":34252,\"inness\":34253,\"Ġreverber\":34254,\"Ġpartition\":34255,\"Short\":34256,\"Ġmoist\":34257,\"Ġspoof\":34258,\"ĠDesire\":34259,\"orce\":34260,\"Ġcrammed\":34261,\"Ġunfor\":34262,\"Pan\":34263,\"ingen\":34264,\"Ġrelat\":34265,\"Mother\":34266,\"ĠGn\":34267,\"altern\":34268,\"Ġresurg\":34269,\"Ġcramped\":34270,\"ĠCitadel\":34271,\"Ġlaureate\":34272,\"Ġanalys\":34273,\"Ġnuns\":34274,\"ĠTie\":34275,\"activ\":34276,\"ĠSurprisingly\":34277,\"ĠProtective\":34278,\"ĠRedemption\":34279,\"Ġendlessly\":34280,\"Ġfists\":34281,\"spl\":34282,\"ĠKron\":34283,\"ĠExamples\":34284,\"Especially\":34285,\"Ġprejud\":34286,\"ĠSchwar\":34287,\"Ġ237\":34288,\"ĠPlants\":34289,\"ĠUNDER\":34290,\"Ġlasers\":34291,\"Ġsher\":34292,\"Ġgoddess\":34293,\"Ġwipes\":34294,\"409\":34295,\"ĠGTA\":34296,\"Ġhybrids\":34297,\"rowd\":34298,\"ĠMILL\":34299,\"ĠNUM\":34300,\"ĠGeek\":34301,\"ĠTWO\":34302,\"ĠTimbers\":34303,\"Ġresembled\":34304,\"ĠGRE\":34305,\"Bring\":34306,\"Ġcompressed\":34307,\"ĠOral\":34308,\"379\":34309,\"Ġwrench\":34310,\"LCS\":34311,\"Ġhomosexual\":34312,\"Kelly\":34313,\"Ġhump\":34314,\"ĠSicily\":34315,\"Ġperished\":34316,\"aos\":34317,\"doesn\":34318,\"scrib\":34319,\"Charlie\":34320,\"Ġshuffle\":34321,\"372\":34322,\"cedented\":34323,\"402\":34324,\"Ġtiers\":34325,\"Ġinteracted\":34326,\"ĠHG\":34327,\"ĠJere\":34328,\"ĠBRA\":34329,\"ĠDOC\":34330,\"things\":34331,\"Ġfaiths\":34332,\"Ġgirlfriends\":34333,\"Ġfortified\":34334,\"develop\":34335,\"ĠKus\":34336,\"iability\":34337,\"rase\":34338,\"iotics\":34339,\"ĠChern\":34340,\"boxes\":34341,\"abol\":34342,\"idan\":34343,\"emon\":34344,\"ĠJudaism\":34345,\"ĠSituation\":34346,\"ĠGrimm\":34347,\"Ġgou\":34348,\"ĠVictim\":34349,\"backer\":34350,\"Ġanimosity\":34351,\"ĠHorizons\":34352,\"ĠKazakh\":34353,\"Ġgrossly\":34354,\"ĠTac\":34355,\"yg\":34356,\"366\":34357,\"Ġcheaply\":34358,\"Ġformulated\":34359,\"ĠDangerous\":34360,\"offensive\":34361,\"Ġsauces\":34362,\"Ġkeyboards\":34363,\"666\":34364,\"Ġcanopy\":34365,\"Inc\":34366,\"astered\":34367,\"iesel\":34368,\"Ġadv\":34369,\"currency\":34370,\"Ġscapego\":34371,\"plings\":34372,\"ĠBDS\":34373,\"Ġstrangely\":34374,\"today\":34375,\"ĠEgyptians\":34376,\"Ġcoron\":34377,\"often\":34378,\"ĠTransformers\":34379,\"ĠAfterwards\":34380,\"reated\":34381,\"Ġpoisonous\":34382,\"Ġgeographically\":34383,\"Ġmell\":34384,\"Cross\":34385,\"Ġdeductible\":34386,\"ĠZionist\":34387,\"Ġcutter\":34388,\"ĠRP\":34389,\"ĠImag\":34390,\"Ġoverflow\":34391,\"358\":34392,\"ĠADD\":34393,\"bones\":34394,\"Ġflattened\":34395,\"ĠGREEN\":34396,\"Ġlaure\":34397,\"haps\":34398,\"ĠCellular\":34399,\"kens\":34400,\"363\":34401,\"ĠSmash\":34402,\"ĠSpeak\":34403,\"ĠMaiden\":34404,\"Ġgreedy\":34405,\"ĠManit\":34406,\"Ġfacet\":34407,\"ĠGPA\":34408,\"Ġracks\":34409,\"popular\":34410,\"322\":34411,\"ĠBars\":34412,\"avement\":34413,\"359\":34414,\"Ġpomp\":34415,\"Ġregisters\":34416,\"Fs\":34417,\"ĠLoving\":34418,\"ĠTaxi\":34419,\"concert\":34420,\"ĠArchae\":34421,\"Ġcurls\":34422,\"ĠSpit\":34423,\"ĠLIFE\":34424,\"Ġinvade\":34425,\"rolog\":34426,\"wreck\":34427,\"Ġconflicted\":34428,\"Ġ970\":34429,\"Ġexiled\":34430,\"Ġchew\":34431,\"udging\":34432,\"Ġexper\":34433,\"ĠFt\":34434,\"rius\":34435,\"ĠXer\":34436,\"~\":34437,\"Ġbandwagon\":34438,\"Fore\":34439,\"Cat\":34440,\"Ġoverflowing\":34441,\"Ġradios\":34442,\"Much\":34443,\"Ġfacilitates\":34444,\"ĠCaf\":34445,\"ĠQing\":34446,\"Use\":34447,\"Ġmang\":34448,\"Ġpissed\":34449,\"ĠOuter\":34450,\"within\":34451,\"ĠSchr\":34452,\"ĠSherlock\":34453,\"Ġ336\":34454,\"Ġcasc\":34455,\"chens\":34456,\"incent\":34457,\"Ġcultivating\":34458,\"ampions\":34459,\"Ġwasteful\":34460,\"adays\":34461,\"sets\":34462,\"ĠLF\":34463,\"watching\":34464,\"Ġabandonment\":34465,\"ĠJesuit\":34466,\"Ġlegislatures\":34467,\"regnancy\":34468,\"ĠColt\":34469,\"Ġinterns\":34470,\"Ġundertook\":34471,\"ĠIPA\":34472,\"ĠInstall\":34473,\"nsics\":34474,\"washer\":34475,\"Ġbeginners\":34476,\"ĠDiseases\":34477,\"Ġlimp\":34478,\"ĠESA\":34479,\"Basically\":34480,\"Ġprud\":34481,\"LED\":34482,\"Ġgrease\":34483,\"ousel\":34484,\"Ġrotten\":34485,\"ĠCele\":34486,\"facts\":34487,\"ĠLouie\":34488,\"ĠISI\":34489,\"481\":34490,\"Ġsett\":34491,\"Ġtoug\":34492,\"ĠReck\":34493,\"OUNT\":34494,\"ĠFou\":34495,\"Ġinhibitor\":34496,\"gru\":34497,\"bane\":34498,\"1980\":34499,\"ĠPanc\":34500,\"Ġsuperficial\":34501,\"Ġauthoritative\":34502,\"ĠVOL\":34503,\"790\":34504,\"Ġcrusade\":34505,\"airy\":34506,\"Ġemphatically\":34507,\"Ġflourishing\":34508,\"Ġ416\":34509,\"Ġheroine\":34510,\"inx\":34511,\"Ġanch\":34512,\"stretched\":34513,\"ĠRegener\":34514,\"ĠAncient\":34515,\"evaluate\":34516,\"Ġantibody\":34517,\"ĠEston\":34518,\"ĠAeg\":34519,\"Ġboldly\":34520,\"TN\":34521,\"ĠPercentage\":34522,\"Ġ747\":34523,\"Ġrapt\":34524,\"ĠEdited\":34525,\"Earth\":34526,\"phal\":34527,\"ĠXXX\":34528,\"arling\":34529,\"ĠReligion\":34530,\"Ġ503\":34531,\"forces\":34532,\"Ġendpoint\":34533,\"Miller\":34534,\"Ba\":34535,\"Ġdisappears\":34536,\"andre\":34537,\"Ġconnector\":34538,\"407\":34539,\"ĠTOUR\":34540,\"aura\":34541,\"ĠRazer\":34542,\"UPDATE\":34543,\"Ġcalib\":34544,\"original\":34545,\"ĠMonkey\":34546,\"Ir\":34547,\"Ġexacerb\":34548,\"killing\":34549,\"Ġforb\":34550,\"native\":34551,\"Ġpoking\":34552,\"Ġveiled\":34553,\"mails\":34554,\"Ġalphabet\":34555,\"Ġawkwardly\":34556,\"ĠNames\":34557,\"Ġspiders\":34558,\"ĠParam\":34559,\"ĠColour\":34560,\"Ġunification\":34561,\"ĠPione\":34562,\"Ġoffend\":34563,\"Ġscoff\":34564,\"ĠSAR\":34565,\"ĠBuildings\":34566,\"edes\":34567,\"ĠAke\":34568,\"Ġfirmware\":34569,\"Madison\":34570,\"policy\":34571,\"ĠComputing\":34572,\"ĠRW\":34573,\"Ġfluent\":34574,\"Ġdece\":34575,\"Ġswore\":34576,\"Ġrestaur\":34577,\"Ġpresses\":34578,\"ophon\":34579,\"Ġphilosopher\":34580,\"ften\":34581,\"Ġintruder\":34582,\"Ġleng\":34583,\"ĠCowboy\":34584,\"cled\":34585,\"Ġmeticulously\":34586,\"ĠPair\":34587,\"ĠEND\":34588,\"Ġcapsules\":34589,\"Ġauxiliary\":34590,\"Ġverses\":34591,\"Ġsheltered\":34592,\"Ġexplorer\":34593,\"ĠWolverine\":34594,\"auts\":34595,\"Ġinhibitors\":34596,\"ĠPeng\":34597,\"ĠValve\":34598,\"imar\":34599,\"Ġchuck\":34600,\"ĠRecording\":34601,\"Ġardu\":34602,\"Test\":34603,\"Ġinterven\":34604,\"Ġchrome\":34605,\"months\":34606,\"tap\":34607,\"ĠManz\":34608,\"format\":34609,\"ĠBalkans\":34610,\"Ġannex\":34611,\"uder\":34612,\"ĠAAC\":34613,\"Ġdisturbances\":34614,\"354\":34615,\"asms\":34616,\"ĠTad\":34617,\"puting\":34618,\"Ġfateful\":34619,\"imen\":34620,\"Ġaudi\":34621,\"ĠNewsweek\":34622,\"Around\":34623,\"Ġretribution\":34624,\"Ġsugars\":34625,\"Ġescapes\":34626,\"Ġlegitim\":34627,\"ĠProof\":34628,\"Ġmisogyn\":34629,\"cit\":34630,\"Ġclutching\":34631,\"exist\":34632,\"Ġrevol\":34633,\"Ġdiscs\":34634,\"discrimination\":34635,\"Ġstout\":34636,\"aline\":34637,\"ĠRandom\":34638,\"364\":34639,\"Ġapprehension\":34640,\"Ġmockery\":34641,\"Ġfossils\":34642,\"ĠStress\":34643,\"Ġbenefic\":34644,\"exc\":34645,\"lude\":34646,\"Small\":34647,\"Ġgh\":34648,\"Ġobserves\":34649,\"ĠSUP\":34650,\"Ġbrewer\":34651,\"ĠESP\":34652,\"Ġomitted\":34653,\"multiple\":34654,\"Ġminimizing\":34655,\"Ġtaco\":34656,\"Ġindifferent\":34657,\"medi\":34658,\"available\":34659,\"Ġ252\":34660,\"Ġsanity\":34661,\"ĠCookie\":34662,\"mostly\":34663,\"near\":34664,\"NASA\":34665,\"Ġlowly\":34666,\"seless\":34667,\"Ġobsess\":34668,\"itous\":34669,\"Dispatch\":34670,\"Ġcanyon\":34671,\"Ġbriefs\":34672,\"Say\":34673,\"ĠNato\":34674,\"ĠSpend\":34675,\"Ġ242\":34676,\"ĠEthernet\":34677,\"Ġmatte\":34678,\"ĠStim\":34679,\"hetics\":34680,\"Ġflourished\":34681,\"389\":34682,\"ĠMcA\":34683,\"695\":34684,\"Ġoverr\":34685,\"Ġtorment\":34686,\"Ġpirate\":34687,\"ĠJohann\":34688,\"roversial\":34689,\"ĠUnemployment\":34690,\"breakers\":34691,\"ĠMessages\":34692,\"tones\":34693,\"Ġtagging\":34694,\"Ġfrog\":34695,\"Jewish\":34696,\"Ġmessenger\":34697,\"Ġexasper\":34698,\"ernaut\":34699,\"Ġnarrower\":34700,\"ĠCatalyst\":34701,\"ĠSecrets\":34702,\"Ġadj\":34703,\"ĠFug\":34704,\"Ġaura\":34705,\"Ġtherape\":34706,\"mber\":34707,\"Ġcaliphate\":34708,\"Ġretreating\":34709,\"ĠComput\":34710,\"Ġburying\":34711,\"Ġail\":34712,\"Ġgriev\":34713,\"lins\":34714,\"825\":34715,\"tten\":34716,\"ifully\":34717,\"ĠTrials\":34718,\"igma\":34719,\"Ġ1914\":34720,\"Ġcoordinates\":34721,\"ocusing\":34722,\"ĠFeng\":34723,\"ĠWhale\":34724,\"Ġshorten\":34725,\"Ġcorrectness\":34726,\"evil\":34727,\"network\":34728,\"Ġreactive\":34729,\"assuming\":34730,\"ĠLaksh\":34731,\"games\":34732,\"Ġruining\":34733,\"excluding\":34734,\"annels\":34735,\"Âº\":34736,\"Ġrubbed\":34737,\"aleb\":34738,\"flex\":34739,\"iped\":34740,\"ĠLimit\":34741,\"allowed\":34742,\"ĠDMV\":34743,\"ĠLD\":34744,\"Ġstamina\":34745,\"conduct\":34746,\"Ġmislead\":34747,\"lib\":34748,\"ĠEminem\":34749,\"Ġpayoff\":34750,\"Ġkernel\":34751,\"Ġsweeps\":34752,\"Ġsonic\":34753,\"ĠKodi\":34754,\"unique\":34755,\"Ġsurrog\":34756,\"Michigan\":34757,\"Ġattest\":34758,\"Ġdummy\":34759,\"ĠStellar\":34760,\"ĠSquadron\":34761,\"ĠHait\":34762,\"ĠSpirits\":34763,\"605\":34764,\"ĠHemisphere\":34765,\"legram\":34766,\"ĠRack\":34767,\"opol\":34768,\"Ġfreshwater\":34769,\"cession\":34770,\"Ġabort\":34771,\"ĠLOG\":34772,\"Ġfuzzy\":34773,\"Ġcrystall\":34774,\"illation\":34775,\"ĠFreddy\":34776,\"Ġsalvation\":34777,\"Ġjuxtap\":34778,\"weekly\":34779,\"usha\":34780,\"456\":34781,\"Ġ660\":34782,\"ĠGlacier\":34783,\"Ġnegatives\":34784,\"Ġillegitimate\":34785,\"ĠProtein\":34786,\"Moore\":34787,\"Der\":34788,\"Ġinfancy\":34789,\"Again\":34790,\"ALD\":34791,\"Leon\":34792,\"ĠIdeally\":34793,\"fresh\":34794,\"730\":34795,\"Ġgamb\":34796,\"Ġscrewed\":34797,\"wow\":34798,\"Ġembodied\":34799,\"ĠCinderella\":34800,\"341\":34801,\"ĠPiano\":34802,\"Ġbroccoli\":34803,\"Ġmats\":34804,\"ĠZheng\":34805,\"cream\":34806,\"anut\":34807,\"ĠZig\":34808,\"Columb\":34809,\"ĠTibetan\":34810,\"Death\":34811,\"Ġstren\":34812,\"ĠVertical\":34813,\"Ġratification\":34814,\"Ġprincipally\":34815,\"ELD\":34816,\"Ġforbid\":34817,\"Ġamalg\":34818,\"blind\":34819,\"auri\":34820,\"stery\":34821,\"Ġbarley\":34822,\"FBI\":34823,\"ĠHex\":34824,\"925\":34825,\"Domin\":34826,\"oat\":34827,\"Ġswayed\":34828,\"ĠKKK\":34829,\"ĠTaxes\":34830,\"Ġker\":34831,\"eeper\":34832,\"ĠAwakens\":34833,\"ĠPix\":34834,\"ĠKING\":34835,\"dc\":34836,\"Ren\":34837,\"Ġlegitimately\":34838,\"ĠTriumph\":34839,\"ĠSites\":34840,\"ĠSai\":34841,\"tl\":34842,\"painted\":34843,\"ĠWaiting\":34844,\"starting\":34845,\"parents\":34846,\"ĠDuo\":34847,\"eele\":34848,\"upper\":34849,\"ĠInvestig\":34850,\"Ġeighteen\":34851,\"Ġcorrelated\":34852,\"ĠCascade\":34853,\"acca\":34854,\"ĠAlph\":34855,\"ĠPolic\":34856,\"ĠEVs\":34857,\"Ġworthless\":34858,\"ĠIndust\":34859,\"auld\":34860,\"ĠYiannopoulos\":34861,\"ĠEzra\":34862,\"Ġmorphed\":34863,\"Ġoriginating\":34864,\"mania\":34865,\"Ġsparing\":34866,\"Ġextrem\":34867,\"cre\":34868,\"ults\":34869,\"mare\":34870,\"classified\":34871,\"Ġparachute\":34872,\"Ġmistrust\":34873,\"ONT\":34874,\"Mind\":34875,\"Ġthru\":34876,\"707\":34877,\"ĠTwain\":34878,\"Ġmelodies\":34879,\"ĠDanger\":34880,\"ĠDPS\":34881,\"Ġderive\":34882,\"Ġdissolution\":34883,\"Ġchildbirth\":34884,\"Ġ415\":34885,\"fork\":34886,\"solid\":34887,\"loads\":34888,\"ĠCGI\":34889,\"378\":34890,\"ĠShed\":34891,\"Face\":34892,\"Ġcomet\":34893,\"iceps\":34894,\"ĠReduction\":34895,\"Fly\":34896,\"jp\":34897,\"ĠAnimation\":34898,\"Luke\":34899,\"Ġabiding\":34900,\"Ġdevise\":34901,\"ĠAe\":34902,\"Ġflux\":34903,\"Ġbras\":34904,\"Ġfracturing\":34905,\"Ġinventive\":34906,\"ĠGranger\":34907,\"Ġsap\":34908,\"inducing\":34909,\"Ġreviewers\":34910,\"Officers\":34911,\"ĠWHY\":34912,\"Ġamplify\":34913,\"Ġentr\":34914,\"Ġslit\":34915,\"457\":34916,\"Ġreformed\":34917,\"ĠPhi\":34918,\"Ġtempt\":34919,\"Ġcontradiction\":34920,\"585\":34921,\"ĠMaced\":34922,\"371\":34923,\"kinson\":34924,\"robe\":34925,\"ĠHunters\":34926,\"astern\":34927,\"criminal\":34928,\"jew\":34929,\"Ġdecentralized\":34930,\"bands\":34931,\"Ġavatar\":34932,\"ĠBarrier\":34933,\"Ġcharacterization\":34934,\"student\":34935,\"Ġgays\":34936,\"Ġspecialize\":34937,\"ĠJudging\":34938,\"Ġinitiation\":34939,\"Ġshove\":34940,\"Ġpirates\":34941,\"Ġfictitious\":34942,\"ĠPoker\":34943,\"ĠElsa\":34944,\"ĠTECH\":34945,\"handedly\":34946,\"Ġglued\":34947,\"Ġclinically\":34948,\"Ġinaccessible\":34949,\"Ġderegulation\":34950,\"Ġprohib\":34951,\"Ġdangling\":34952,\"Ġnoses\":34953,\"Ġstash\":34954,\"Ø§Ø\":34955,\"ESH\":34956,\"Ġmonstrous\":34957,\"Ġcrept\":34958,\"ĠCharm\":34959,\"Ġbeh\":34960,\"Ġshuts\":34961,\"Ġ236\":34962,\"imedia\":34963,\"445\":34964,\"Du\":34965,\"Ġafar\":34966,\"ĠRout\":34967,\"Ġflares\":34968,\"Utah\":34969,\"Ġ808\":34970,\"Ġjewels\":34971,\"2004\":34972,\"Ġrecal\":34973,\"Gas\":34974,\"ĠExcellent\":34975,\"Ġpitfalls\":34976,\"ĠDrawing\":34977,\"viously\":34978,\"angered\":34979,\"changes\":34980,\"Ġpasture\":34981,\"talking\":34982,\"Ġinequ\":34983,\"Ġbicycl\":34984,\"Cost\":34985,\"423\":34986,\"bard\":34987,\"Ġanterior\":34988,\"ecast\":34989,\"CHR\":34990,\"397\":34991,\"masters\":34992,\"706\":34993,\"ĠFinish\":34994,\"Yet\":34995,\"study\":34996,\"ĠCogn\":34997,\"Ġloaf\":34998,\"Ġspatial\":34999,\"ĠParad\":35000,\"batch\":35001,\"Ġvents\":35002,\"Ġspins\":35003,\"ĠAddiction\":35004,\"Ġcondone\":35005,\"Ġproble\":35006,\"English\":35007,\"ĠRomans\":35008,\"ĠSaying\":35009,\"ĠKling\":35010,\"Universal\":35011,\"ivist\":35012,\"Ġskirm\":35013,\"Ġ2500\":35014,\"Ġ263\":35015,\"aired\":35016,\"ĠMartian\":35017,\"ĠCompensation\":35018,\"lation\":35019,\"ĠSalam\":35020,\"LGBT\":35021,\"ĠDart\":35022,\"strike\":35023,\"vasive\":35024,\"ILLE\":35025,\"Ġimaginative\":35026,\"ĠEuph\":35027,\"Financial\":35028,\"Ġholog\":35029,\"orah\":35030,\"crit\":35031,\"ĠOswald\":35032,\"512\":35033,\"ĠUri\":35034,\"Ġdiscrepancies\":35035,\"Ġbeads\":35036,\"ĠShots\":35037,\"Mem\":35038,\"Ġhunts\":35039,\"Ġsubtly\":35040,\"Ġ470\":35041,\"ĠVigil\":35042,\"Ġsew\":35043,\"ĠBurma\":35044,\"igm\":35045,\"ighed\":35046,\"swe\":35047,\"Ġ251\":35048,\"Ġdeceit\":35049,\"Ġphysi\":35050,\"iflower\":35051,\"ĠCert\":35052,\"Ġchewing\":35053,\"rax\":35054,\"ĠMER\":35055,\"icient\":35056,\"Les\":35057,\"Ġ390\":35058,\"Ġperjury\":35059,\"Ġfiltering\":35060,\"770\":35061,\"Ġpoppy\":35062,\"Ġbland\":35063,\"ĠNasa\":35064,\"Ġorbiting\":35065,\"ĠRipple\":35066,\"otal\":35067,\"ĠRyu\":35068,\"ĠShap\":35069,\"ĠJian\":35070,\"Ġpiv\":35071,\"ĠNeptune\":35072,\"rary\":35073,\"Ġunavoidable\":35074,\"Ġguideline\":35075,\"Ġwaterfall\":35076,\"inators\":35077,\"ĠLogic\":35078,\"ĠPlug\":35079,\"role\":35080,\"Ġalterations\":35081,\"ĠSett\":35082,\"ĠFeld\":35083,\"Ġfreezes\":35084,\"Ġbedrock\":35085,\"ĠVIEW\":35086,\"ovation\":35087,\"Ġneedless\":35088,\"ĠIU\":35089,\"ignant\":35090,\"ĠConfeder\":35091,\"316\":35092,\"fine\":35093,\"Ġjars\":35094,\"gotten\":35095,\"Bron\":35096,\"Ġmindfulness\":35097,\"imating\":35098,\"Ġhysteria\":35099,\"Ġhurried\":35100,\"Ġinfantry\":35101,\"ĠNYU\":35102,\"tags\":35103,\"Penn\":35104,\"Ġtracing\":35105,\"ĠSwing\":35106,\"ĠIo\":35107,\"Ġreckoned\":35108,\"ĠRecall\":35109,\"ĠVersion\":35110,\"314\":35111,\"Ġecology\":35112,\"Ġarmoured\":35113,\"Ġresonance\":35114,\"970\":35115,\"Ġvigilance\":35116,\"Ġrede\":35117,\"ĠBohem\":35118,\"Ġchau\":35119,\"ĠDevi\":35120,\"Ġtru\":35121,\"))\":35122,\"Put\":35123,\"Ġflavored\":35124,\"ĠClown\":35125,\"Senate\":35126,\"ĠScandinavian\":35127,\"mable\":35128,\"Residents\":35129,\"ĠFranchise\":35130,\"Ġprecincts\":35131,\"Prem\":35132,\"ĠNeutral\":35133,\"coal\":35134,\"Ġdelinqu\":35135,\"Mus\":35136,\"UME\":35137,\"Ġtedious\":35138,\"roots\":35139,\"ĠCondition\":35140,\"ĠIntercept\":35141,\"017\":35142,\"itives\":35143,\"Ġdefinitively\":35144,\"Ġobliter\":35145,\"Ġclandestine\":35146,\"Ġstagnation\":35147,\"Ġblindness\":35148,\"abiding\":35149,\"Ġremix\":35150,\"feeding\":35151,\"Ġunrecogn\":35152,\"2003\":35153,\"960\":35154,\"381\":35155,\"Ġbulky\":35156,\"xia\":35157,\"ivered\":35158,\"inic\":35159,\"ĠSoci\":35160,\"ĠYards\":35161,\"Ġhides\":35162,\"Film\":35163,\"Ġtestim\":35164,\"Ġblacklist\":35165,\"Deep\":35166,\"Standard\":35167,\"ĠClash\":35168,\"Ġriddled\":35169,\"Ġdiseng\":35170,\"ĠTRE\":35171,\"ĠIDs\":35172,\"Ġmigrating\":35173,\"protect\":35174,\"Ġgraded\":35175,\"Ġvaguely\":35176,\"ĠCharacter\":35177,\"382\":35178,\"ĠMOD\":35179,\"Eng\":35180,\"Ġmobilized\":35181,\"Ġsincerity\":35182,\"Ġ317\":35183,\"sighted\":35184,\"ownt\":35185,\"ĠâĢİ\":35186,\"umpy\":35187,\"Ġitching\":35188,\"ĠVerd\":35189,\"cook\":35190,\"Ġsimulator\":35191,\"players\":35192,\"Early\":35193,\"infeld\":35194,\"Ġmaximizing\":35195,\"Philipp\":35196,\"ĠPhotoshop\":35197,\"Ġdestroys\":35198,\"Ġbefriend\":35199,\"Ġfilthy\":35200,\"ĠIncident\":35201,\"gha\":35202,\"Ġcomplicity\":35203,\"Ġmessing\":35204,\"YA\":35205,\"ĠNegro\":35206,\"adows\":35207,\"374\":35208,\"Ġpip\":35209,\"cean\":35210,\"Ġ1924\":35211,\"Sent\":35212,\"represent\":35213,\"Ġdeems\":35214,\"ĠRue\":35215,\"Ġtitanium\":35216,\"Ġmanners\":35217,\"âĢ¦âĢ¦\":35218,\"bare\":35219,\"Ġusur\":35220,\"mma\":35221,\"ĠPanda\":35222,\"ulus\":35223,\"ĠSlav\":35224,\"324\":35225,\"ĠMole\":35226,\"^\":35227,\"micro\":35228,\"foreign\":35229,\"lest\":35230,\"ocular\":35231,\"ĠUniv\":35232,\"ĠFrag\":35233,\"Ġshepherd\":35234,\"Ġelectron\":35235,\"ĠFSA\":35236,\"Ġunl\":35237,\"dose\":35238,\"Ġimmersion\":35239,\"ĠDeL\":35240,\"Ġbiomedical\":35241,\"Anna\":35242,\"Ġskillet\":35243,\"Ġrecre\":35244,\"Ġtrillions\":35245,\"voy\":35246,\"Ġnormalized\":35247,\"radio\":35248,\"cue\":35249,\"urbed\":35250,\"Ġthinkers\":35251,\"328\":35252,\"327\":35253,\"ĠForge\":35254,\"505\":35255,\"Ġunbearable\":35256,\"olini\":35257,\"Ġdisinfect\":35258,\"Ġshaving\":35259,\"Ġtoxicity\":35260,\"453\":35261,\"Ġheterosexual\":35262,\"Baltimore\":35263,\"Ġstool\":35264,\"lr\":35265,\"ĠMk\":35266,\"Ġantidote\":35267,\"Dark\":35268,\"810\":35269,\"Ġirritated\":35270,\"ĠSUPPORT\":35271,\"Chance\":35272,\"bent\":35273,\"ĠZelda\":35274,\"ĠPenguin\":35275,\"ifled\":35276,\"Ġarte\":35277,\"705\":35278,\"Ġcondol\":35279,\"izza\":35280,\"ĠCK\":35281,\"Ġprojector\":35282,\"ravings\":35283,\"Ġ1919\":35284,\"Ġburner\":35285,\"ĠSchwarz\":35286,\"Oregon\":35287,\"Ġridicule\":35288,\"Ġinstructional\":35289,\"Ġ\\\"#\":35290,\"ĠDign\":35291,\"Ġkitten\":35292,\"Ġconstit\":35293,\"iration\":35294,\"Speed\":35295,\"ecycle\":35296,\"ĠFalse\":35297,\"ĠDealer\":35298,\"Could\":35299,\"655\":35300,\"outside\":35301,\"Ġworldview\":35302,\"Ġ246\":35303,\"Ġspitting\":35304,\"595\":35305,\"MN\":35306,\"ĠComes\":35307,\"ingu\":35308,\"Ġenzymes\":35309,\"Ġcompass\":35310,\"Ġexclaimed\":35311,\"ĠMalays\":35312,\"Ġ1916\":35313,\"Ġcoloring\":35314,\"Ġrepeats\":35315,\"Ġsoils\":35316,\"Ġtrivia\":35317,\"ĠIsles\":35318,\"Const\":35319,\"ĠFiction\":35320,\"665\":35321,\"Ġcriminality\":35322,\"ĠZi\":35323,\"384\":35324,\"ĠWilderness\":35325,\"ĠCanary\":35326,\"ĠVs\":35327,\"Ð¸\":35328,\"ĠAPIs\":35329,\"Ġbehest\":35330,\"Ġeb\":35331,\"ĠHipp\":35332,\"Ġpreempt\":35333,\"Ġevoke\":35334,\"Ġinept\":35335,\"tele\":35336,\"447\":35337,\"ĠGarmin\":35338,\"Ġpursuits\":35339,\"351\":35340,\"ĠclichÃ©\":35341,\"ĠJihad\":35342,\"Ġ308\":35343,\"ĠSnake\":35344,\"ĠAnnounce\":35345,\"Nearly\":35346,\"!'\\\"\":35347,\"Ġ1927\":35348,\"saw\":35349,\"Ġabhor\":35350,\"Plan\":35351,\"rawled\":35352,\"ĠRiy\":35353,\"ensor\":35354,\"Fal\":35355,\"quick\":35356,\"odynamic\":35357,\"Ġsubstitution\":35358,\"Ġprovoking\":35359,\"Operation\":35360,\"rupulous\":35361,\"Ġsweetness\":35362,\"folk\":35363,\"ĠDefault\":35364,\"Ġstarved\":35365,\"ĠPrinting\":35366,\"urious\":35367,\"ĠTracker\":35368,\"them\":35369,\"Ġleth\":35370,\"Ġemptied\":35371,\"Ġfootprints\":35372,\"ilian\":35373,\"Ġbattalion\":35374,\"Ġprophet\":35375,\"Ġrailing\":35376,\"Ġhect\":35377,\"rouch\":35378,\"lees\":35379,\"Ġideologies\":35380,\"Ġ254\":35381,\"ĠGods\":35382,\"ĠAvalon\":35383,\"Ġfrontrunner\":35384,\"ĠPork\":35385,\"ĠPipe\":35386,\"Ġscaven\":35387,\"Ġming\":35388,\"Ġerg\":35389,\"Ġ520\":35390,\"Ġhatched\":35391,\"asant\":35392,\"ĠHI\":35393,\"Ġpend\":35394,\"Ġ288\":35395,\"Prom\":35396,\"achev\":35397,\"ĠEcology\":35398,\"enforcement\":35399,\"467\":35400,\"dule\":35401,\"Ġrealism\":35402,\"ĠTypes\":35403,\"USB\":35404,\"utra\":35405,\"ĠHiroshima\":35406,\"Ġcontradicted\":35407,\"393\":35408,\"ĠDSL\":35409,\"Ġtherein\":35410,\"ĠReconstruction\":35411,\"Ġ243\":35412,\"irled\":35413,\"479\":35414,\"ĠWhats\":35415,\"Currently\":35416,\"ĠPOWER\":35417,\"ĠHiro\":35418,\"ĠBreath\":35419,\"ĠYourself\":35420,\"Ġlantern\":35421,\"376\":35422,\"É\":35423,\"ĠHumans\":35424,\"Lady\":35425,\"Ġdissemination\":35426,\"ecake\":35427,\"ĠChao\":35428,\"flat\":35429,\"Ġinspecting\":35430,\"stration\":35431,\"Ġidentifiable\":35432,\"CV\":35433,\"ĠLobby\":35434,\"function\":35435,\"Roll\":35436,\"DIV\":35437,\"Tell\":35438,\"Ġfasc\":35439,\"ĠAOL\":35440,\"HM\":35441,\"Keefe\":35442,\"Ġporous\":35443,\"Ġsmoot\":35444,\"existence\":35445,\"ĠDeg\":35446,\"Ġdivor\":35447,\"isner\":35448,\"allas\":35449,\"Bloomberg\":35450,\"Ġdictators\":35451,\"ĠGeh\":35452,\"Ġsilicone\":35453,\"Ġdab\":35454,\"Ġmashed\":35455,\"Ġpric\":35456,\"might\":35457,\"ĠBLM\":35458,\"Ġpatriarch\":35459,\"Microsoft\":35460,\"ĠAds\":35461,\"Ġcoronary\":35462,\"ĠContrary\":35463,\"Ġdra\":35464,\"ĠStarted\":35465,\"Ġbuckle\":35466,\"lear\":35467,\"accept\":35468,\"Within\":35469,\"bd\":35470,\"interested\":35471,\"bia\":35472,\"POR\":35473,\"motion\":35474,\"ĠFounders\":35475,\"ĠCassandra\":35476,\"ĠPassion\":35477,\"Ġbehavioural\":35478,\"ĠHealing\":35479,\"Ġmarkings\":35480,\"Ġsnowball\":35481,\"Ġridiculed\":35482,\"phase\":35483,\"Ġunto\":35484,\"aque\":35485,\"uggets\":35486,\"Ġfrantically\":35487,\"Ġcoward\":35488,\"Ġinconvenient\":35489,\"Taking\":35490,\"Afee\":35491,\"Ġtwisting\":35492,\"930\":35493,\"ĠSieg\":35494,\"ĠGit\":35495,\"Ġcurs\":35496,\"ĠGlas\":35497,\"ĠSignificant\":35498,\"Ġachieves\":35499,\"Ġpreferably\":35500,\"Ġcondensed\":35501,\"Ġfetus\":35502,\"Ġunivers\":35503,\"Ġpse\":35504,\"Access\":35505,\"Ġintertwined\":35506,\"been\":35507,\"quit\":35508,\"ĠLEGO\":35509,\"Ġimagining\":35510,\"454\":35511,\"Ġplains\":35512,\"sequently\":35513,\"pull\":35514,\"Fast\":35515,\"Pot\":35516,\"yles\":35517,\"AIR\":35518,\"Ġblatantly\":35519,\"eki\":35520,\"ilated\":35521,\"ĠMembership\":35522,\"Ġ262\":35523,\"Ġ}\":35524,\"Ġexcavation\":35525,\"Ġethn\":35526,\"addin\":35527,\"Ġfoundational\":35528,\"ceptions\":35529,\"ĠViet\":35530,\"exempt\":35531,\"Ġmicrophones\":35532,\"Ġ244\":35533,\"778\":35534,\"Ġdwar\":35535,\"attery\":35536,\"502\":35537,\"ĠKik\":35538,\"Ġinspir\":35539,\"ĠMaximum\":35540,\"Ġvengeance\":35541,\"Ġetched\":35542,\"outine\":35543,\"552\":35544,\"Ġunicorn\":35545,\"gged\":35546,\".ï¿½\":35547,\"ĠBlackwell\":35548,\"ĠStatue\":35549,\"Ġdissidents\":35550,\"ĠKaine\":35551,\"Ġdeforestation\":35552,\"ĠScholar\":35553,\"Ġpleasantly\":35554,\"ÑĤ\":35555,\"398\":35556,\"ĠRUN\":35557,\"arent\":35558,\"Ġundeniably\":35559,\"Ġtechnologically\":35560,\"Ġconsciously\":35561,\"ĠEther\":35562,\"Ġproportional\":35563,\"Ġlaund\":35564,\"ĠRye\":35565,\"Ġambiguity\":35566,\"Ġunmist\":35567,\"Terror\":35568,\"ciplinary\":35569,\"ĠImproved\":35570,\"hesis\":35571,\"Ġcooker\":35572,\"elsen\":35573,\"Ġguerrilla\":35574,\"opped\":35575,\"ATURE\":35576,\"Ġrequ\":35577,\"Ġunprepared\":35578,\"Ġcamel\":35579,\"Ġfitt\":35580,\"Sex\":35581,\"edged\":35582,\"Ġrecurrent\":35583,\"ctuary\":35584,\"ĠCompare\":35585,\"ĠServing\":35586,\"Tri\":35587,\"Ġtransient\":35588,\"ĠBees\":35589,\"Ġcovenant\":35590,\"Ġfantasies\":35591,\"Ġespresso\":35592,\"draft\":35593,\"baugh\":35594,\"Ġdemocratically\":35595,\"ĠBans\":35596,\"ĠManual\":35597,\"ĠTurtle\":35598,\"ennett\":35599,\"achy\":35600,\"ĠClim\":35601,\"Ġdescending\":35602,\"Ġprow\":35603,\"Ġinconsistencies\":35604,\"Player\":35605,\"Ġoblivious\":35606,\"ĠWonderland\":35607,\"nav\":35608,\"aughter\":35609,\"Ġlod\":35610,\"Ġ403\":35611,\"ĠPolaris\":35612,\"ĠLeia\":35613,\"ĠInfantry\":35614,\"Sy\":35615,\"ĠMeter\":35616,\"Ġautoimmune\":35617,\"Ġdiagnoses\":35618,\"Ġtrespass\":35619,\"011\":35620,\"wrong\":35621,\"ĠGREAT\":35622,\"Ġtelescopes\":35623,\"shows\":35624,\"Pac\":35625,\"olation\":35626,\"Ġclerics\":35627,\"Ġdissenting\":35628,\"406\":35629,\"Ġetiquette\":35630,\"Ġdeterrence\":35631,\"765\":35632,\"Ġove\":35633,\"Has\":35634,\"Pak\":35635,\"à¤¾\":35636,\"ĠNec\":35637,\"Ġsociology\":35638,\"witz\":35639,\"Ġkittens\":35640,\"Ġcontinual\":35641,\"Ġoverlapping\":35642,\"Ġmonks\":35643,\"ĠMechanical\":35644,\"Captain\":35645,\"ocial\":35646,\"ĠFalling\":35647,\"ĠCorrection\":35648,\"ĠTrouble\":35649,\"Ġslog\":35650,\"Ġ253\":35651,\"Ġemanating\":35652,\"Ġwidest\":35653,\"PROV\":35654,\"Japanese\":35655,\"urat\":35656,\"Ġboxed\":35657,\"ĠCases\":35658,\"Ġjarring\":35659,\"Fix\":35660,\"'?\":35661,\"ĠStrateg\":35662,\"Republic\":35663,\"ovy\":35664,\"362\":35665,\"ĠMothers\":35666,\"Ġstreaks\":35667,\"Ġlocalized\":35668,\"ĠONLY\":35669,\"Ġeh\":35670,\"ĠObject\":35671,\"Ġstub\":35672,\"Fre\":35673,\"ĠScarlet\":35674,\"Ġmultip\":35675,\"ĠMaul\":35676,\"ĠProblems\":35677,\"cest\":35678,\"Ġmortal\":35679,\"Ġarche\":35680,\"ulet\":35681,\"Ġfuller\":35682,\"ĠGER\":35683,\"Si\":35684,\"mr\":35685,\"ĠPowerful\":35686,\"boxing\":35687,\"ĠPeer\":35688,\"Jean\":35689,\"ĠTF\":35690,\"Ġplural\":35691,\"optim\":35692,\"Jimmy\":35693,\"ĠFriendly\":35694,\"Mex\":35695,\"Ġdepri\":35696,\"PK\":35697,\"Ġwaitress\":35698,\"eph\":35699,\"arrass\":35700,\"ikawa\":35701,\"feel\":35702,\"Finally\":35703,\"fourth\":35704,\"394\":35705,\"conom\":35706,\"VT\":35707,\"Ġeleg\":35708,\"ivot\":35709,\"Ġharsher\":35710,\"ĠPepe\":35711,\"ĠImpl\":35712,\"Ġankles\":35713,\"idity\":35714,\"ĠPrepare\":35715,\"Rather\":35716,\"Ġconservatism\":35717,\"Ġunquestion\":35718,\"ribution\":35719,\"ĠPatent\":35720,\"ĠDeluxe\":35721,\"ĠAE\":35722,\"007\":35723,\"Ġprag\":35724,\"bg\":35725,\"Ġpalate\":35726,\"Ġintric\":35727,\"ossom\":35728,\"Ġspac\":35729,\"ĠSpotlight\":35730,\"Seven\":35731,\"amacare\":35732,\"ĠGotham\":35733,\"Ġencompass\":35734,\"Ġnicer\":35735,\"ĠLauder\":35736,\"Ġscaff\":35737,\"worn\":35738,\"442\":35739,\"Ġpropri\":35740,\"443\":35741,\"ĠCompos\":35742,\"ĠIniti\":35743,\"inth\":35744,\"Ġrehe\":35745,\"Prov\":35746,\"Ġgri\":35747,\"ossip\":35748,\"ĠModest\":35749,\"quiet\":35750,\"Ġwealthier\":35751,\"Ġ241\":35752,\"icum\":35753,\"Ġcommunism\":35754,\"Ġhelpers\":35755,\"Ġbellig\":35756,\"Ġ405\":35757,\"uttered\":35758,\"Ġbitterness\":35759,\"nl\":35760,\"474\":35761,\"Ġvitality\":35762,\"blank\":35763,\"ĠLeth\":35764,\"PAC\":35765,\"326\":35766,\"ĠNapoleon\":35767,\"Ġ299\":35768,\"ĠReviews\":35769,\"ĠSect\":35770,\"Ġstrongh\":35771,\"ĠTube\":35772,\"Ġwoodland\":35773,\"Ġhumming\":35774,\"411\":35775,\"Alpha\":35776,\"Ġundet\":35777,\"Ġmounts\":35778,\"Officials\":35779,\"igning\":35780,\"830\":35781,\"ĠStamp\":35782,\"ubby\":35783,\"424\":35784,\"Ġoutlandish\":35785,\"Ġjerk\":35786,\"Ġradiant\":35787,\"Ġcubes\":35788,\"Director\":35789,\"Ġatro\":35790,\"vous\":35791,\"Sab\":35792,\"Ġpretended\":35793,\"Ġ620\":35794,\"975\":35795,\"Sham\":35796,\"Ġpotassium\":35797,\"ĠAttention\":35798,\"gly\":35799,\"opens\":35800,\"ĠWorker\":35801,\"porter\":35802,\"Ġsplendid\":35803,\"embed\":35804,\"Je\":35805,\"ĠMeal\":35806,\"Ġsurname\":35807,\"Usually\":35808,\"Ġtimer\":35809,\"Ġweave\":35810,\"irin\":35811,\"ĠGenetics\":35812,\"ensual\":35813,\"Ġmerry\":35814,\"Ġapprehend\":35815,\"utsche\":35816,\"strate\":35817,\"Ġsupplementary\":35818,\"ĠRoundup\":35819,\"upid\":35820,\"Ġmiraculous\":35821,\"ĠHUN\":35822,\"Ġglaciers\":35823,\"weed\":35824,\"ĠSuggest\":35825,\"XL\":35826,\"authors\":35827,\"Ġbarking\":35828,\"ĠUKIP\":35829,\"leased\":35830,\"ĠRAD\":35831,\"Ġfide\":35832,\"Ġphen\":35833,\"Ġscanners\":35834,\"Parents\":35835,\"ĠBlaze\":35836,\"Ġtweaking\":35837,\"Ġelaborated\":35838,\"Ġsusp\":35839,\"iscovered\":35840,\"Ġthighs\":35841,\"Ġradicals\":35842,\"ULTS\":35843,\"aggressive\":35844,\"endants\":35845,\"Hon\":35846,\"Ġcorrecting\":35847,\"391\":35848,\"pps\":35849,\"ĠTerritories\":35850,\"Ġconferred\":35851,\"crazy\":35852,\"utor\":35853,\"ĠSurvival\":35854,\"Ġbrowsers\":35855,\"ĠConflict\":35856,\"pn\":35857,\"Ġdeprive\":35858,\"riage\":35859,\"ilan\":35860,\"à¦\":35861,\"949\":35862,\"Congratulations\":35863,\"radical\":35864,\"ĠHits\":35865,\"powerful\":35866,\"Ġcrypt\":35867,\"745\":35868,\"ĠRegistrar\":35869,\"ophile\":35870,\"ĠElement\":35871,\"cooked\":35872,\"ĠTwilight\":35873,\"Ġdemos\":35874,\"IER\":35875,\"Ġstricken\":35876,\"Magic\":35877,\"abby\":35878,\"ĠSack\":35879,\"ĠShrine\":35880,\"Nev\":35881,\"Probably\":35882,\"ĠWisdom\":35883,\"ulpt\":35884,\"opher\":35885,\"Ġcolonel\":35886,\"atl\":35887,\"Tem\":35888,\"kun\":35889,\"ĠIndie\":35890,\"Putin\":35891,\"jection\":35892,\"areth\":35893,\"ĠBullet\":35894,\"Ġsmartest\":35895,\"ĠEsper\":35896,\"Ġproficiency\":35897,\"Ġcessation\":35898,\"Ġmars\":35899,\"ĠDATA\":35900,\"sup\":35901,\"Ġostr\":35902,\"Jane\":35903,\"Ġpathogens\":35904,\"hd\":35905,\"ĠNK\":35906,\"Ġhorribly\":35907,\"regulated\":35908,\"Ġesteemed\":35909,\"ĠChinatown\":35910,\"Ġvibration\":35911,\"Ġoverboard\":35912,\"ĠRhod\":35913,\"Ġfeces\":35914,\"otation\":35915,\"Ġcryptic\":35916,\"Bal\":35917,\"OPER\":35918,\"Ġaffirmation\":35919,\"Ġmenstrual\":35920,\"Ġuntold\":35921,\"Ġanecdotes\":35922,\"ĠHOUSE\":35923,\"Ġcape\":35924,\"311\":35925,\"ittance\":35926,\"ĠRemy\":35927,\"ĠWaves\":35928,\"ĠCOVER\":35929,\"ordinate\":35930,\"Ġrestricts\":35931,\"Samsung\":35932,\"Ġplantations\":35933,\"olver\":35934,\"Better\":35935,\"ĠExplos\":35936,\"Ġnasal\":35937,\"ĠSyri\":35938,\"ĠPerl\":35939,\"Ġlatency\":35940,\"othermal\":35941,\"Sweet\":35942,\"ĠRyzen\":35943,\"ĠYuri\":35944,\"Ġsmack\":35945,\"Ġcrow\":35946,\"aniel\":35947,\"iological\":35948,\"Ġmonk\":35949,\"Ġtutorial\":35950,\"ĠAure\":35951,\"Ġcliffs\":35952,\"ameron\":35953,\"umers\":35954,\"ĠMour\":35955,\"Ġunorthodox\":35956,\"Ġgulf\":35957,\"Ġintrusive\":35958,\"ĠVIII\":35959,\"ĠFF\":35960,\"Ġenlarged\":35961,\"Ġspheres\":35962,\"ĠCheap\":35963,\"ĠAmend\":35964,\"Ġ::\":35965,\"Ġpacing\":35966,\"ĠStartup\":35967,\"ĠDating\":35968,\"racist\":35969,\"ĠDivine\":35970,\"Ġpollen\":35971,\"ĠMeaning\":35972,\"ĠLei\":35973,\"ĠMOT\":35974,\"ĠARC\":35975,\"legate\":35976,\"Ġbrav\":35977,\"Ross\":35978,\"redit\":35979,\"414\":35980,\"ringe\":35981,\"perhaps\":35982,\"SPA\":35983,\"Southern\":35984,\"Front\":35985,\"undrum\":35986,\"Ġassorted\":35987,\"ĠDawkins\":35988,\"ĠWrap\":35989,\"Ġconsequential\":35990,\"ĠFuji\":35991,\"458\":35992,\"Ġunst\":35993,\"Bon\":35994,\"acter\":35995,\"Trade\":35996,\"ingers\":35997,\"ĠClin\":35998,\"Ġstimul\":35999,\"arah\":36000,\"inois\":36001,\"urdy\":36002,\"Ġobsessive\":36003,\"Zone\":36004,\"Ġprimitive\":36005,\"unctions\":36006,\"Ġadapter\":36007,\"Ġassures\":36008,\"Daddy\":36009,\"Ġunsatisf\":36010,\"441\":36011,\"Ġ1910\":36012,\"Ġsecondly\":36013,\"truth\":36014,\"RED\":36015,\"040\":36016,\"Pope\":36017,\"venants\":36018,\"Ġestim\":36019,\"Ġhemorrh\":36020,\"Ġexcruciating\":36021,\"459\":36022,\"Ġboils\":36023,\"ieved\":36024,\"Storm\":36025,\"Ġmanifestation\":36026,\"Ġinsulated\":36027,\"fb\":36028,\"Ġclassify\":36029,\"Mbps\":36030,\"Ġinclination\":36031,\"Ġaur\":36032,\"Ġpolarized\":36033,\"Ġoccupations\":36034,\"Secretary\":36035,\"Ġcustomizable\":36036,\"scribe\":36037,\"Ġadjunct\":36038,\"Ġ1922\":36039,\"rived\":36040,\"ocative\":36041,\"Friends\":36042,\"Oak\":36043,\"Ġpsyche\":36044,\"Ġwrinkles\":36045,\"anthrop\":36046,\"Ġcoercion\":36047,\"enos\":36048,\"Ġvariability\":36049,\"hma\":36050,\"phot\":36051,\"ĠXander\":36052,\"ĠDiss\":36053,\"Ġtigers\":36054,\"ahoo\":36055,\"focus\":36056,\"rical\":36057,\"grow\":36058,\"Ġseminal\":36059,\"Ġdisciples\":36060,\"Cas\":36061,\"Hundreds\":36062,\"Ġscissors\":36063,\"correct\":36064,\"Ġfascism\":36065,\"imoto\":36066,\"Ġnudity\":36067,\"charg\":36068,\"Ġrusty\":36069,\"ĠLyndon\":36070,\"Ġanomalies\":36071,\"onial\":36072,\"ĠiCloud\":36073,\"Ġannoy\":36074,\"Ġdistortion\":36075,\"Lou\":36076,\"ĠGiul\":36077,\"eyes\":36078,\"870\":36079,\"uum\":36080,\"ĠUltr\":36081,\"Action\":36082,\"cigarette\":36083,\"igators\":36084,\"kj\":36085,\"Ġ323\":36086,\"uine\":36087,\"Score\":36088,\"Ġmans\":36089,\"Security\":36090,\"Ġarom\":36091,\"ĠBoards\":36092,\"Ġwrists\":36093,\"602\":36094,\"Ġastronomy\":36095,\"Ġresin\":36096,\"width\":36097,\")/\":36098,\"Ġconcurrent\":36099,\"unless\":36100,\"606\":36101,\"ĠMagnet\":36102,\"Ġauthorizing\":36103,\"ĠJunk\":36104,\"atical\":36105,\"Ġauthent\":36106,\"zac\":36107,\"413\":36108,\"ĠGrape\":36109,\"Ġcircled\":36110,\"Ġooz\":36111,\"Ġvisceral\":36112,\"ointment\":36113,\"Ġincendiary\":36114,\"ĠBourbon\":36115,\"Ġgimmick\":36116,\"vette\":36117,\"Stan\":36118,\"Ġdetachment\":36119,\"488\":36120,\"Ġmisogyny\":36121,\"Ġenlight\":36122,\"utic\":36123,\"Ġinquire\":36124,\"ĠBEL\":36125,\"ascular\":36126,\"ĠWasserman\":36127,\"Dallas\":36128,\"Ġconstellation\":36129,\"Ġdystopian\":36130,\"504\":36131,\"ĠOptical\":36132,\"Ġsilhou\":36133,\"Girl\":36134,\"ĠGong\":36135,\"ĠHighest\":36136,\"????????\":36137,\"Sav\":36138,\"ocity\":36139,\"leted\":36140,\"Ġattrition\":36141,\"ĠExpedition\":36142,\"ĠKilled\":36143,\"501\":36144,\"ONES\":36145,\"dat\":36146,\"Ġglyphosate\":36147,\"Ġplugs\":36148,\"Ġlact\":36149,\"Fla\":36150,\"fps\":36151,\"riger\":36152,\"Ġparagraphs\":36153,\"Ġinnate\":36154,\"ĠFoo\":36155,\"aternity\":36156,\"ĠGry\":36157,\"Ġoneself\":36158,\"642\":36159,\"Iowa\":36160,\"oodle\":36161,\"ĠCoconut\":36162,\"ĠChess\":36163,\"ommel\":36164,\"Ġmagnesium\":36165,\"Ġairliner\":36166,\"Ġexceedingly\":36167,\"ĠCreator\":36168,\"YouTube\":36169,\"Ġsleeper\":36170,\"Ġlonging\":36171,\"ĠPercy\":36172,\"Ġmatrix\":36173,\"Ġâľ\":36174,\"Ġbarren\":36175,\"Mrs\":36176,\"Ġinvading\":36177,\"Ġincom\":36178,\"Ġemperor\":36179,\"Ġip\":36180,\"irie\":36181,\"Ġpredictably\":36182,\"ĠBless\":36183,\"Ġsuperpower\":36184,\":-\":36185,\"Ġpropensity\":36186,\"easy\":36187,\"educ\":36188,\"ĠPolly\":36189,\"Ġcumbersome\":36190,\"Ġcollide\":36191,\"016\":36192,\"Ġtransports\":36193,\"Ġscraps\":36194,\"below\":36195,\"Ġhairs\":36196,\"mentation\":36197,\"Ġevolves\":36198,\"ĠFallen\":36199,\"Ġunsurprisingly\":36200,\"Ġcuff\":36201,\"Ġ249\":36202,\"mental\":36203,\"ĠCamel\":36204,\"Ġ337\":36205,\"Clinton\":36206,\"Ġdecad\":36207,\"ĠSTEP\":36208,\"ĠTestament\":36209,\"Ġirresistible\":36210,\"ĠACE\":36211,\"Ġhamm\":36212,\"ĠTerr\":36213,\"Ġcaul\":36214,\"iggins\":36215,\"Ġproficient\":36216,\"resp\":36217,\"Ġheirs\":36218,\"Ġ321\":36219,\"dress\":36220,\"ĠClothing\":36221,\"Ġ560\":36222,\"Ġ264\":36223,\"ĠRobb\":36224,\"Ġfrail\":36225,\"Ġoptimizing\":36226,\"615\":36227,\"ĠRefuge\":36228,\"rowth\":36229,\"washing\":36230,\"Ġgenders\":36231,\"indu\":36232,\"ĠNAT\":36233,\"Ġleans\":36234,\"Ġeyed\":36235,\"Ġhilar\":36236,\"vice\":36237,\"wolf\":36238,\"Ġfatig\":36239,\"ococ\":36240,\"ĠCarry\":36241,\"Community\":36242,\"Clark\":36243,\"itably\":36244,\"sv\":36245,\"448\":36246,\"Ġnumer\":36247,\"Ġ1925\":36248,\"ĠBehavioral\":36249,\"ĠScream\":36250,\"Ġgeek\":36251,\"rake\":36252,\"ĠTTC\":36253,\"Ġadditives\":36254,\"ĠBye\":36255,\"ylon\":36256,\"Ġfoliage\":36257,\"ateral\":36258,\"rapnel\":36259,\"Science\":36260,\"Ġrecollection\":36261,\"thening\":36262,\"ĠUbisoft\":36263,\"ĠLur\":36264,\"ĠOkinawa\":36265,\"ĠProvision\":36266,\"ferred\":36267,\"ĠGrounds\":36268,\"Ġhops\":36269,\"aterial\":36270,\"Ġacad\":36271,\"Ġengulf\":36272,\"ĠApex\":36273,\"frequency\":36274,\"relations\":36275,\"ĠCorvette\":36276,\"ĠRepeat\":36277,\"Ġanew\":36278,\"Ġhes\":36279,\"ĠLair\":36280,\"ĠPSP\":36281,\"foundation\":36282,\"Band\":36283,\"ĠPublisher\":36284,\"Ġreciprocal\":36285,\"Ġ287\":36286,\"Ġpir\":36287,\"Adams\":36288,\"Ġprostitute\":36289,\"ĠMecca\":36290,\"ectomy\":36291,\"Ġskew\":36292,\"ĠLol\":36293,\"Voice\":36294,\"ĠCalais\":36295,\"ISION\":36296,\"rue\":36297,\"Ġgaping\":36298,\"prot\":36299,\"Ġ6000\":36300,\"Ġtilted\":36301,\"Ġgoofy\":36302,\"Stand\":36303,\"Ġfellows\":36304,\"Ġcurly\":36305,\"ĠPOW\":36306,\"Ġlore\":36307,\"Ġinhabited\":36308,\"ĠIdentification\":36309,\"Metro\":36310,\"Ġdispel\":36311,\"Ġinvoking\":36312,\"Ġdeleting\":36313,\"Ġstigmat\":36314,\"ĠDalai\":36315,\"Ġequate\":36316,\"Ġmascara\":36317,\"endered\":36318,\"ĠNYT\":36319,\"ĠCommittees\":36320,\"rians\":36321,\"ĠOlympus\":36322,\"ĠQR\":36323,\"ĠDrinking\":36324,\"Ġbatt\":36325,\"andr\":36326,\"computer\":36327,\"Senator\":36328,\"ĠTwist\":36329,\"ĠNoise\":36330,\"Ġcheesy\":36331,\"Ġ1931\":36332,\"Ġtyranny\":36333,\"Ġnegligible\":36334,\"ĠBok\":36335,\"Ġwebpage\":36336,\"ĠHEAD\":36337,\"ĠNovel\":36338,\"Ġquarry\":36339,\"Ġexpressive\":36340,\"Ġforgiving\":36341,\"Among\":36342,\"asin\":36343,\"ĠSuc\":36344,\"Democrats\":36345,\"795\":36346,\"Ġaback\":36347,\"Â¨\":36348,\"ĠNeon\":36349,\"392\":36350,\"ĠRNC\":36351,\"ĠPROC\":36352,\"sein\":36353,\"Ros\":36354,\"Ġemot\":36355,\"ĠASA\":36356,\"ĠSeb\":36357,\"ĠExtended\":36358,\"atern\":36359,\"Ġpsychedelic\":36360,\"Fil\":36361,\"ĠOrwell\":36362,\"ĠSOS\":36363,\"Ġconceive\":36364,\"Ġhobbies\":36365,\"Ġspecimens\":36366,\"ĠTEXT\":36367,\"sometimes\":36368,\"Mario\":36369,\"orpor\":36370,\"ĠTemporary\":36371,\"Ġapocalypse\":36372,\"Ġcounterproductive\":36373,\"ĠQUEST\":36374,\"ĠCargo\":36375,\"Amb\":36376,\"Ġoptic\":36377,\"groups\":36378,\"Ġparanoia\":36379,\".?\":36380,\"sounding\":36381,\"mediately\":36382,\"System\":36383,\"ubi\":36384,\"Ġuttered\":36385,\"Ġgraphs\":36386,\"âĢĭâĢĭ\":36387,\"Ġscientifically\":36388,\"Ġbluntly\":36389,\"Ġhopping\":36390,\"Fun\":36391,\"ĠSUPER\":36392,\"Ġrobe\":36393,\"VB\":36394,\"ĠQuote\":36395,\"Ġincarnation\":36396,\"Ġtreadmill\":36397,\"Ġ1915\":36398,\"Ġbart\":36399,\"669\":36400,\"Ġhoc\":36401,\"Ġ309\":36402,\"Ġimprovis\":36403,\"Ġhut\":36404,\"Ġmixer\":36405,\"ĠCt\":36406,\"span\":36407,\"Ġwatered\":36408,\"Ġpatriot\":36409,\"Ġdehyd\":36410,\"laughs\":36411,\"ĠFancy\":36412,\"ĠVoc\":36413,\"Ġintellect\":36414,\"ĠTid\":36415,\"Ġnesting\":36416,\"Tel\":36417,\"Ġ()\":36418,\"letter\":36419,\"ĠSeems\":36420,\"Ops\":36421,\"ĠContents\":36422,\"ript\":36423,\"hani\":36424,\"Ġrecru\":36425,\"Ġpickups\":36426,\"repair\":36427,\"Throughout\":36428,\"bear\":36429,\"Ġconquered\":36430,\"656\":36431,\"Ġmalf\":36432,\"Ġordained\":36433,\"755\":36434,\"ĠReprodu\":36435,\"brain\":36436,\"ĠOuts\":36437,\"ĠWage\":36438,\"Ru\":36439,\"________\":36440,\"ĠLAW\":36441,\"ĠWass\":36442,\"Ġcomplication\":36443,\"Fri\":36444,\"Ġregener\":36445,\"Wait\":36446,\"577\":36447,\"Ġmisconception\":36448,\"Ġbombardment\":36449,\"Ġunloaded\":36450,\"Ġdictionary\":36451,\"IU\":36452,\"025\":36453,\"etically\":36454,\"ĠNarr\":36455,\"repe\":36456,\"Ġassigning\":36457,\"Rail\":36458,\"Ġnotebooks\":36459,\"Ġingest\":36460,\"Ġrpm\":36461,\"Ġalienated\":36462,\"ĠCredits\":36463,\"Ġindis\":36464,\"ĠGathering\":36465,\"aration\":36466,\"-+-+-+-+\":36467,\"Ġori\":36468,\"Ġsr\":36469,\"ndra\":36470,\"Ġlibertarian\":36471,\"Ġcoerced\":36472,\"ording\":36473,\"Ġtranqu\":36474,\"Ġelbows\":36475,\"549\":36476,\"Ġping\":36477,\"ĠRELE\":36478,\"ĠYanuk\":36479,\"Ġmaneuvers\":36480,\"ĠTrojan\":36481,\"IFIED\":36482,\"ĠViolent\":36483,\"è\":36484,\"Ġlest\":36485,\"Ġarrows\":36486,\"frog\":36487,\"anty\":36488,\"WB\":36489,\"ĠSeen\":36490,\"648\":36491,\"Ġclutter\":36492,\"ĠBender\":36493,\"Ġpessim\":36494,\"ĠTeg\":36495,\"Asian\":36496,\"IFIC\":36497,\"Ġexponential\":36498,\"Ġsponge\":36499,\"rite\":36500,\"ĠDAM\":36501,\"Ġtacit\":36502,\"ĠZoom\":36503,\"Ġolds\":36504,\"Ġonward\":36505,\"ĠSandwich\":36506,\"missible\":36507,\"isol\":36508,\"940\":36509,\"Ġinciner\":36510,\"ĠTrick\":36511,\"Ġawakening\":36512,\"Ġdart\":36513,\"ĠCouch\":36514,\"respons\":36515,\"ĠElephant\":36516,\"ĠPluto\":36517,\"ĠTags\":36518,\"itcher\":36519,\"644\":36520,\"702\":36521,\"Ġelectrons\":36522,\"ĠMyth\":36523,\"ĠAad\":36524,\"Danny\":36525,\"Ġcraw\":36526,\"ĠCertification\":36527,\"Ġtending\":36528,\"Ġpellets\":36529,\"Ġamused\":36530,\"ĠAuschwitz\":36531,\"ĠAppl\":36532,\"iris\":36533,\"ashion\":36534,\"walking\":36535,\"Ġabnorm\":36536,\"Cro\":36537,\"?:\":36538,\"ĠIcelandic\":36539,\"ĠAvailability\":36540,\"Ġcann\":36541,\"Opt\":36542,\"buster\":36543,\"ĠQuartz\":36544,\"Executive\":36545,\"tracks\":36546,\"igel\":36547,\"MIT\":36548,\"ĠTracking\":36549,\"Ġconditioned\":36550,\"Ġsampled\":36551,\"ĠGenius\":36552,\"Ġsubstit\":36553,\"ĠSiberia\":36554,\"Ġfrequ\":36555,\"historic\":36556,\"okin\":36557,\"OWS\":36558,\"1500\":36559,\"warts\":36560,\"ĠEtsy\":36561,\"licks\":36562,\"ĠSmooth\":36563,\"unity\":36564,\"515\":36565,\"Ġperk\":36566,\"aida\":36567,\"forts\":36568,\"ĠUA\":36569,\"RIC\":36570,\"Spain\":36571,\"ĠWired\":36572,\"cuts\":36573,\"Ġfurnace\":36574,\"ĠTOTAL\":36575,\"ĠTables\":36576,\"662\":36577,\"Fab\":36578,\"Ġquaint\":36579,\"ĠWorlds\":36580,\"ĠCabin\":36581,\"atche\":36582,\"List\":36583,\"ĠVO\":36584,\"Ġkeyword\":36585,\"Ġ258\":36586,\"Farm\":36587,\"timer\":36588,\"ĠVolt\":36589,\"Build\":36590,\"pressed\":36591,\"*,\":36592,\"Ġ324\":36593,\"aiman\":36594,\"TING\":36595,\"Ġsneaking\":36596,\"cery\":36597,\"Ġcrib\":36598,\"ĠIllust\":36599,\"later\":36600,\"Ġcompar\":36601,\"Ġpropulsion\":36602,\"647\":36603,\"ĠTrails\":36604,\"Ġperiphery\":36605,\"steel\":36606,\"Ġvividly\":36607,\"ĠConver\":36608,\"eatured\":36609,\"427\":36610,\"463\":36611,\"Ġapprox\":36612,\"spin\":36613,\"Ġconfigured\":36614,\"inside\":36615,\"razy\":36616,\"account\":36617,\"anye\":36618,\"riend\":36619,\"Ġbows\":36620,\"809\":36621,\"ĠDEF\":36622,\"ĠRez\":36623,\"Fans\":36624,\"ĠDF\":36625,\"Ġstains\":36626,\"ĠAtom\":36627,\"ĠConce\":36628,\"ĠTOM\":36629,\"ĠELECT\":36630,\"Ġdisappro\":36631,\"019\":36632,\"afia\":36633,\"ĠTemperature\":36634,\"Ġextracts\":36635,\"fab\":36636,\"Ġunsur\":36637,\"Ġseasoning\":36638,\"Ty\":36639,\"KB\":36640,\"Ġposit\":36641,\"Ġlocality\":36642,\"1200\":36643,\"cour\":36644,\"izons\":36645,\"hh\":36646,\"506\":36647,\"ĠDLC\":36648,\"iago\":36649,\"Ġcorpses\":36650,\"iddling\":36651,\"Mayor\":36652,\"Ġsimplistic\":36653,\"Ġlibel\":36654,\"Ġalmonds\":36655,\"Ġswast\":36656,\"Change\":36657,\"ĠJoker\":36658,\"MAR\":36659,\"ĠScully\":36660,\"Ġmailbox\":36661,\"VIDEO\":36662,\"ĠKyoto\":36663,\"esley\":36664,\"ĠIncredible\":36665,\"youtube\":36666,\"Ġinequalities\":36667,\"Ġbolts\":36668,\"Ġbothering\":36669,\"Ġattentive\":36670,\"ĠSparrow\":36671,\"Ġdiaper\":36672,\"Ġfanbase\":36673,\"Ġuncont\":36674,\"Ap\":36675,\"ĠQi\":36676,\"Price\":36677,\"471\":36678,\"Ġpearl\":36679,\"wid\":36680,\"899\":36681,\"ĠPony\":36682,\"casting\":36683,\"Ġinhabit\":36684,\"Ġunve\":36685,\"Ġinsur\":36686,\"ĠWee\":36687,\"658\":36688,\"Ġeffected\":36689,\"gger\":36690,\"Ġinstallments\":36691,\"imilar\":36692,\"FU\":36693,\"Ġinfertility\":36694,\"climate\":36695,\"HEAD\":36696,\"fashion\":36697,\"ĠTHEY\":36698,\"jc\":36699,\"Ġsatisf\":36700,\"ĠGuidelines\":36701,\"Ġinsure\":36702,\"ĠRSA\":36703,\"Ġvirt\":36704,\"Ġinterpre\":36705,\"Joshua\":36706,\"ĠShut\":36707,\"Ġtestimonies\":36708,\"Ñģ\":36709,\"untary\":36710,\"417\":36711,\"Ġbeck\":36712,\"ĠMilky\":36713,\"ç\":36714,\"Ġsequels\":36715,\"Ġ281\":36716,\"ĠRibbon\":36717,\"Ġroomm\":36718,\"Ġsynchron\":36719,\"452\":36720,\"Ġ1926\":36721,\"Ġhawk\":36722,\"ĠDisorder\":36723,\"Ġbackstory\":36724,\"ĠNum\":36725,\"Ġoverheard\":36726,\"technical\":36727,\"Jud\":36728,\"aii\":36729,\"Ġdecon\":36730,\"ĠRape\":36731,\"ĠWarrant\":36732,\"Ġpoop\":36733,\"spir\":36734,\"Country\":36735,\"Ġweld\":36736,\"Ġabuser\":36737,\"Ġ------\":36738,\"material\":36739,\"Ġpreserves\":36740,\"spring\":36741,\"Ġpuzzled\":36742,\"ĠDebate\":36743,\"Joseph\":36744,\"Ġ272\":36745,\"Blood\":36746,\"antry\":36747,\"Ġconverge\":36748,\"Ġimaginable\":36749,\"oward\":36750,\"545\":36751,\"Ġfug\":36752,\"Vision\":36753,\"075\":36754,\"Ġadoptive\":36755,\"Ġunknow\":36756,\"Stream\":36757,\"Ġaffili\":36758,\"ĠPUR\":36759,\"ĠWally\":36760,\"Ġgamer\":36761,\"Ġfart\":36762,\"stice\":36763,\"Ġcongen\":36764,\"Ð½\":36765,\"685\":36766,\"orst\":36767,\"ĠATF\":36768,\"Ġml\":36769,\"ĠMozilla\":36770,\"Ġcalmed\":36771,\"bage\":36772,\"ĠVault\":36773,\"arkable\":36774,\"ĠGuan\":36775,\"Ġclueless\":36776,\"umatic\":36777,\"Ġshameless\":36778,\"Ġpreached\":36779,\"Ġmisconceptions\":36780,\"Ġanthology\":36781,\"Ġbiomass\":36782,\"ĠPs\":36783,\"tails\":36784,\"Ġexcessively\":36785,\"Ġextr\":36786,\"Davis\":36787,\"Ġgrounding\":36788,\"Ġshortcuts\":36789,\"ĠShift\":36790,\"ĠRew\":36791,\"ĠIllum\":36792,\"Ġincite\":36793,\"sense\":36794,\"ĠScouting\":36795,\"otos\":36796,\"respond\":36797,\"Ġbeware\":36798,\"gran\":36799,\"ĠXV\":36800,\"JM\":36801,\"ĠSounders\":36802,\"Ġ276\":36803,\"Ġshockingly\":36804,\"Ġgastrointestinal\":36805,\"erences\":36806,\"df\":36807,\"ĠNG\":36808,\"Ġdiscredited\":36809,\"Ġdemoral\":36810,\"Ġgladly\":36811,\"Tal\":36812,\"ĠPredator\":36813,\"708\":36814,\"Ġdoi\":36815,\"Ġdecentral\":36816,\"illin\":36817,\"printed\":36818,\"Ġinflicting\":36819,\"ribes\":36820,\"Ġsupper\":36821,\"abc\":36822,\"Ġgraz\":36823,\"980\":36824,\"Bull\":36825,\"Ġmillionaires\":36826,\"Ġvanity\":36827,\"imony\":36828,\"Ġbiologists\":36829,\"Ġalternating\":36830,\"Ġsleeps\":36831,\"Force\":36832,\"ĠPrinc\":36833,\"ĠTransgender\":36834,\"Ġ314\":36835,\"ĠProvide\":36836,\"enthal\":36837,\"Ġplum\":36838,\"Ġresurrect\":36839,\"CW\":36840,\"Ġinjure\":36841,\"ĠPerspective\":36842,\"ĠBei\":36843,\"Ġrestless\":36844,\"aciously\":36845,\"Ġchlor\":36846,\"catch\":36847,\"ĠLuigi\":36848,\"Ġinconsistency\":36849,\"Ġwhiff\":36850,\"Arizona\":36851,\"ustration\":36852,\"ĠRaid\":36853,\"ĠDemons\":36854,\"ĠVita\":36855,\":\\\"\":36856,\"Ġmigraine\":36857,\"ĠHamb\":36858,\"Ġwidget\":36859,\"451\":36860,\"Ġrandomized\":36861,\"etchup\":36862,\"ĠParticularly\":36863,\"Ġdiced\":36864,\"Ġperfected\":36865,\"roid\":36866,\"710\":36867,\"Ġreflections\":36868,\"Ġantioxidants\":36869,\"ĠLabel\":36870,\"Ġ326\":36871,\"igious\":36872,\"ĠEucl\":36873,\"608\":36874,\"Ġstrand\":36875,\"ĠDirt\":36876,\"ĠLift\":36877,\"suits\":36878,\"ĠControls\":36879,\"RAW\":36880,\"Ġcowardly\":36881,\"ĠUmb\":36882,\"Growing\":36883,\"mington\":36884,\"Ġ339\":36885,\"ĠCommit\":36886,\"Ġnonviolent\":36887,\"Ġcontaminants\":36888,\"Ġacrylic\":36889,\"ĠMAP\":36890,\"Ġ269\":36891,\"Ġdegrading\":36892,\"Ġmiracles\":36893,\"ĠEstablishment\":36894,\"despite\":36895,\"cry\":36896,\"Ġpauses\":36897,\"Ġmythical\":36898,\"Ġtwenties\":36899,\"Actually\":36900,\"phan\":36901,\"recorded\":36902,\"Ġunwillingness\":36903,\"engineering\":36904,\"avored\":36905,\"Ġdevout\":36906,\"item\":36907,\"Ġbunny\":36908,\"ĠMerchants\":36909,\"Ġconsumes\":36910,\"508\":36911,\"Ġlex\":36912,\"ĠClause\":36913,\"Ġchecklist\":36914,\"Sus\":36915,\"uther\":36916,\".#\":36917,\"Bit\":36918,\"uay\":36919,\"bf\":36920,\"Ġpopulace\":36921,\"Ġ316\":36922,\"Ġcombust\":36923,\"Ġnano\":36924,\"Ġpopul\":36925,\"Indust\":36926,\"Ġcapitalists\":36927,\"ĠFiles\":36928,\"Bang\":36929,\"Ġkosher\":36930,\"atile\":36931,\"Ġincrim\":36932,\"OVER\":36933,\"Ġmelee\":36934,\"ymph\":36935,\"ĠPupp\":36936,\"evin\":36937,\"ĠMolecular\":36938,\"Ġmisinterpret\":36939,\"vc\":36940,\"olithic\":36941,\"ĠSimpsons\":36942,\"Ġshrew\":36943,\"Ġselectively\":36944,\"ĠDrain\":36945,\"mittedly\":36946,\"conservative\":36947,\"True\":36948,\"Using\":36949,\"562\":36950,\"apon\":36951,\"Ġapprentice\":36952,\"Mas\":36953,\"ĠBattlefield\":36954,\"Ġfing\":36955,\"Ġconcoct\":36956,\"ĠVIS\":36957,\"ĠHuss\":36958,\"Ġdetects\":36959,\"ĠFriedrich\":36960,\"Ġlatitude\":36961,\"Custom\":36962,\"ĠÙ\":36963,\"ĠBones\":36964,\"whose\":36965,\"Ġredirected\":36966,\"aligned\":36967,\"ĠNeighbor\":36968,\"ĠAmen\":36969,\"ĠMarble\":36970,\"Beyond\":36971,\"Ġbiomark\":36972,\"Ġerroneous\":36973,\"Atlanta\":36974,\"Ġmasturb\":36975,\"ĠAssoci\":36976,\"Albert\":36977,\"Ġcigar\":36978,\"ĠFraz\":36979,\"ethe\":36980,\"skinned\":36981,\"Ford\":36982,\"throp\":36983,\"Acc\":36984,\"Ġtricked\":36985,\"Ġoverwhelm\":36986,\"Ġimplements\":36987,\"ĠGeForce\":36988,\"Ġbounces\":36989,\"Ġmoderator\":36990,\"910\":36991,\"ĠButterfly\":36992,\"ĠIllegal\":36993,\"ĠSubject\":36994,\"RET\":36995,\"ĠFreeze\":36996,\"ĠNewt\":36997,\"Ġuterus\":36998,\"696\":36999,\"Ġ267\":37000,\"tk\":37001,\"Ġdodged\":37002,\"liam\":37003,\"Ġparasite\":37004,\"obal\":37005,\"ĠHubble\":37006,\"Ġtheology\":37007,\"âĢĶ\\\"\":37008,\"height\":37009,\"Ale\":37010,\"employment\":37011,\"ĠWallet\":37012,\"cessive\":37013,\"Ġ404\":37014,\"Ġsimilarity\":37015,\"zens\":37016,\"Ġdumps\":37017,\"Ġdepress\":37018,\"Ġlifeless\":37019,\"535\":37020,\"oard\":37021,\"Scotland\":37022,\"Ġbelievable\":37023,\"Ġcalculator\":37024,\"ĠNaked\":37025,\"Ġremission\":37026,\"Ġoranges\":37027,\"ĠSections\":37028,\"Ġentangled\":37029,\"Ġuncanny\":37030,\"Ġteaspoons\":37031,\"vr\":37032,\"ĠPorn\":37033,\"Organ\":37034,\"Ġbund\":37035,\"Doug\":37036,\"ĠGHz\":37037,\"Major\":37038,\"abus\":37039,\"Bell\":37040,\"avier\":37041,\"Ġimplanted\":37042,\"RON\":37043,\"Fle\":37044,\"462\":37045,\"509\":37046,\"Ġgoggles\":37047,\"Ġmanuscript\":37048,\"NOT\":37049,\"ĠCanaveral\":37050,\"ĠDID\":37051,\"Season\":37052,\"HAEL\":37053,\"Edge\":37054,\"appiness\":37055,\"DIS\":37056,\"Ġplotted\":37057,\"Ġwrought\":37058,\"Ġquarantine\":37059,\"Ġrearr\":37060,\"itage\":37061,\"Ġsocket\":37062,\"Ġbrig\":37063,\"Ġunbelievably\":37064,\"abytes\":37065,\"TG\":37066,\"Ġ444\":37067,\"ĠOffic\":37068,\"Ġacquaintances\":37069,\"ĠComparison\":37070,\"Nine\":37071,\"ĠFeast\":37072,\"758\":37073,\"YC\":37074,\"Ġfiner\":37075,\"ĠStrawberry\":37076,\"Ġeternity\":37077,\"liament\":37078,\"urrency\":37079,\"ĠCortana\":37080,\"ĠSabbath\":37081,\"Ġsprinkle\":37082,\"unker\":37083,\"ĠUE\":37084,\"flies\":37085,\"Ġblender\":37086,\"Ġacutely\":37087,\"emark\":37088,\"ĠAffect\":37089,\"Politics\":37090,\"Ġsane\":37091,\"Ġcorrosion\":37092,\"Ġspirituality\":37093,\"Ġredeemed\":37094,\"Ġingrained\":37095,\"manager\":37096,\"joined\":37097,\"ĠDumb\":37098,\"ĠHeight\":37099,\"Ġseventeen\":37100,\"Ġ640\":37101,\"Ġreviewer\":37102,\"Ġwallpaper\":37103,\"Ġnurs\":37104,\"Ġsubset\":37105,\"703\":37106,\"Ġsymbolism\":37107,\"Ġdudes\":37108,\"Ġmismatch\":37109,\"gans\":37110,\"please\":37111,\"ĠKE\":37112,\"Ġatom\":37113,\"004\":37114,\"ionic\":37115,\"Ġservings\":37116,\"Ġproxies\":37117,\"Ġtranscription\":37118,\"yx\":37119,\"bowl\":37120,\"iscovery\":37121,\"ĠScotch\":37122,\"brace\":37123,\"riter\":37124,\"ĠDesktop\":37125,\"Ġlimestone\":37126,\"æ\":37127,\"Neg\":37128,\"013\":37129,\"Ġformulas\":37130,\"Ġeval\":37131,\"Ġzombies\":37132,\"GU\":37133,\"ĠHermes\":37134,\"Ġbrist\":37135,\"Mand\":37136,\"Ġmastery\":37137,\"Ġgoverns\":37138,\"Ġconstrued\":37139,\"region\":37140,\"Ġemitted\":37141,\"Vice\":37142,\"060\":37143,\"Jennifer\":37144,\"mol\":37145,\"Ġjealousy\":37146,\"Ġingenuity\":37147,\"bug\":37148,\"olitical\":37149,\"Ġperce\":37150,\"ĠSapp\":37151,\"dim\":37152,\"utral\":37153,\"Ġinterrogated\":37154,\"Gate\":37155,\"Ġamber\":37156,\"911\":37157,\"ĠEveryday\":37158,\"ĠDDR\":37159,\"ĠBlades\":37160,\"Ġnifty\":37161,\"Ġmurderers\":37162,\"Ġpresumption\":37163,\"Pitt\":37164,\"Div\":37165,\"ĠDestination\":37166,\"having\":37167,\"Ġprolifer\":37168,\"Ġbreaker\":37169,\"ĠBW\":37170,\"Ġcourier\":37171,\"Try\":37172,\"ĠBUR\":37173,\"itized\":37174,\"Ġcompress\":37175,\"Ġrepetition\":37176,\"ĠTik\":37177,\"Ġdivergence\":37178,\"Ġcube\":37179,\"everyone\":37180,\"ĠPoles\":37181,\"418\":37182,\"ĠHighly\":37183,\"468\":37184,\"Jeremy\":37185,\"Ġcontradictions\":37186,\"Ġmanure\":37187,\"Sad\":37188,\"pletion\":37189,\"626\":37190,\"Ġ279\":37191,\"Ġfrivolous\":37192,\"ĠCanaan\":37193,\"olor\":37194,\"Ġincapac\":37195,\"ĠGentle\":37196,\"Ġinsomnia\":37197,\"ĠJing\":37198,\"688\":37199,\"ĠViews\":37200,\"Ġsyll\":37201,\"486\":37202,\"antom\":37203,\"Ġcog\":37204,\"aintain\":37205,\"ĠDVDs\":37206,\"Ġ318\":37207,\"archy\":37208,\"Ġreprodu\":37209,\"Ġconcedes\":37210,\"Brook\":37211,\"Ġinterpreting\":37212,\"Ġextracting\":37213,\"Ġess\":37214,\"uning\":37215,\"ĠMathematics\":37216,\"iably\":37217,\"Ġmultit\":37218,\"ĠActs\":37219,\"iliated\":37220,\"Foreign\":37221,\"Ġflaming\":37222,\"ĠCoup\":37223,\"Ġglitches\":37224,\"Ġdifferentiation\":37225,\"ihadi\":37226,\"ĠDrone\":37227,\"Ġincompatible\":37228,\"asher\":37229,\"documented\":37230,\"agons\":37231,\"wark\":37232,\"Ġshielding\":37233,\"ĠCorrect\":37234,\"romising\":37235,\"uned\":37236,\"Ġconduit\":37237,\"ĠDiablo\":37238,\"Ġbeginner\":37239,\"Ġarchived\":37240,\"smanship\":37241,\"ĠTBD\":37242,\"digy\":37243,\"Ġ322\":37244,\"Ġ268\":37245,\"ĠTears\":37246,\"ĠPriority\":37247,\"Italy\":37248,\"Ġ^\":37249,\"annot\":37250,\"different\":37251,\"Joy\":37252,\"Ġbreathed\":37253,\"heon\":37254,\"Ġracists\":37255,\"Ġvascular\":37256,\"Between\":37257,\"etition\":37258,\"ĠLikely\":37259,\"icans\":37260,\"529\":37261,\"ĠMonsters\":37262,\"agy\":37263,\"Orange\":37264,\"hide\":37265,\"SIM\":37266,\"Ġdeceive\":37267,\"ĠDAR\":37268,\"Ġshattering\":37269,\"Ġow\":37270,\"peak\":37271,\"Ġpreferable\":37272,\"Ġpiping\":37273,\"ĠLEDs\":37274,\"ĠCOMMUN\":37275,\"ĠConstruct\":37276,\"008\":37277,\"Ġdissatisfied\":37278,\"ĠKNOW\":37279,\"ĠFrame\":37280,\"ĠToast\":37281,\"Ġadore\":37282,\"history\":37283,\"Soviet\":37284,\"reporting\":37285,\"Ġ266\":37286,\"pract\":37287,\"ĠSauce\":37288,\"686\":37289,\"ievers\":37290,\"ĠDomain\":37291,\"ousand\":37292,\"768\":37293,\"Cos\":37294,\"609\":37295,\"432\":37296,\"Ġtransl\":37297,\"oof\":37298,\"Ġ292\":37299,\"Turkish\":37300,\"ĠPOLIT\":37301,\"Harris\":37302,\"bj\":37303,\"Ġrodents\":37304,\"556\":37305,\"Ġintellectuals\":37306,\"Ġinteroper\":37307,\"ixt\":37308,\"Ġunbiased\":37309,\"itia\":37310,\"Ġ504\":37311,\"Ġbuttocks\":37312,\"ĠFlam\":37313,\"Ġchrom\":37314,\"Ġ259\":37315,\"shock\":37316,\"ĠRJ\":37317,\"ĠLich\":37318,\"422\":37319,\"Ġcondom\":37320,\"phen\":37321,\"Ġvigilante\":37322,\"Ġowl\":37323,\"Ġdwellings\":37324,\"Ġarchaeologists\":37325,\"Ġ680\":37326,\"RAY\":37327,\"Ġ1921\":37328,\"Ġ625\":37329,\"ĠPLAN\":37330,\"alde\":37331,\"030\":37332,\"abbling\":37333,\"Wave\":37334,\"Ni\":37335,\"Ġfurthe\":37336,\"JS\":37337,\"Ġpsycho\":37338,\"ĠFranÃ§ois\":37339,\"Ġundergrad\":37340,\"Ġsuccessors\":37341,\"Ġpadded\":37342,\"introdu\":37343,\"Ġreasoned\":37344,\"Ġvas\":37345,\"creen\":37346,\"onsequ\":37347,\"starter\":37348,\"Court\":37349,\"ĠHIS\":37350,\"Ġplaster\":37351,\"Ġranger\":37352,\"Ġ298\":37353,\"esters\":37354,\"Ġglare\":37355,\"ype\":37356,\"Ġcompute\":37357,\"Ali\":37358,\"mallow\":37359,\"Ġmasculine\":37360,\"ĠExamination\":37361,\"improve\":37362,\"Ġdeclass\":37363,\"Ġdecoration\":37364,\"ĠFIG\":37365,\"abre\":37366,\"Ġstale\":37367,\"abling\":37368,\"ĠRusty\":37369,\"ĠASAP\":37370,\"Ġadjusts\":37371,\"Ġbluff\":37372,\"density\":37373,\"Ġdisse\":37374,\"Ġcensor\":37375,\"ervatives\":37376,\"Ġkettle\":37377,\"Ġskeptics\":37378,\"fd\":37379,\"Imm\":37380,\"461\":37381,\"Ġadvantageous\":37382,\"419\":37383,\"ĠPresents\":37384,\"482\":37385,\"ĠRewards\":37386,\"Ġovershadow\":37387,\"Alabama\":37388,\"ĠCPC\":37389,\"Ġsock\":37390,\"ĠChurches\":37391,\"hidden\":37392,\"Ġcringe\":37393,\"ĠHOR\":37394,\"PB\":37395,\"Pretty\":37396,\"Hong\":37397,\"?),\":37398,\"687\":37399,\"Ġgrocer\":37400,\"472\":37401,\"565\":37402,\"itent\":37403,\"Ġpartake\":37404,\"wait\":37405,\"usters\":37406,\"Ġcones\":37407,\"Ġconcurrently\":37408,\"Ġlevers\":37409,\"Ġaroma\":37410,\"ĠDrill\":37411,\"498\":37412,\"804\":37413,\"ithering\":37414,\"Ġ355\":37415,\"Ġlegion\":37416,\"Ġvitri\":37417,\"Ġcondu\":37418,\"Angel\":37419,\"OWER\":37420,\"Ġ{*\":37421,\"Simon\":37422,\"Ġsynthesis\":37423,\"ĠContainer\":37424,\"sheet\":37425,\"Bi\":37426,\"ĠRaspberry\":37427,\"Ġ328\":37428,\"anders\":37429,\"ĠBlossom\":37430,\"ĠFINAL\":37431,\"acid\":37432,\"Ġborderline\":37433,\"Aut\":37434,\"Ġoriginate\":37435,\"Ġtransm\":37436,\"Ġbuffalo\":37437,\"atial\":37438,\"ĠCraigslist\":37439,\"Ġcredential\":37440,\"Ġdisbanded\":37441,\"Ġunprotected\":37442,\"ĠZer\":37443,\"waukee\":37444,\"diagn\":37445,\"1999\":37446,\"doc\":37447,\"ellig\":37448,\"Ġwarheads\":37449,\"ĠADS\":37450,\"verified\":37451,\"ĠHAM\":37452,\"785\":37453,\"Cu\":37454,\"Ġenorm\":37455,\"ĠSkill\":37456,\"\\\\\":37457,\"Ġbashing\":37458,\"Ġloudspe\":37459,\"during\":37460,\"Ġdebunked\":37461,\"adequ\":37462,\"Ġuh\":37463,\"Feed\":37464,\"ificial\":37465,\"pred\":37466,\"ĠPassing\":37467,\"Kyle\":37468,\"enance\":37469,\"ĠMex\":37470,\"itect\":37471,\"Ġcavern\":37472,\"Ġtrop\":37473,\"ĠEliot\":37474,\"753\":37475,\"Ġencountering\":37476,\"Ġsulf\":37477,\"Always\":37478,\"ĠGest\":37479,\"Ġadditive\":37480,\"Ġ278\":37481,\"Ġloops\":37482,\"liberal\":37483,\"urion\":37484,\"ĠRefresh\":37485,\"ĠDynasty\":37486,\"Ġsweaty\":37487,\"Ġsails\":37488,\"protection\":37489,\"ĠRooms\":37490,\"ĠEXT\":37491,\"few\":37492,\"ĠPaid\":37493,\"Ġ377\":37494,\"Ġcolonialism\":37495,\"Ġchuckle\":37496,\"Ġarmour\":37497,\"Ġsoftly\":37498,\"661\":37499,\"Building\":37500,\"ĠAMER\":37501,\"Ġbabe\":37502,\"Ġshif\":37503,\"Sem\":37504,\"Ġdisembark\":37505,\"ĠSubstance\":37506,\"Stone\":37507,\"Ġdialect\":37508,\"ĠAph\":37509,\"Ġspreadsheet\":37510,\"ierra\":37511,\"Ġlineage\":37512,\"ĠCust\":37513,\"ĠBabe\":37514,\"Ġwra\":37515,\"ĠMafia\":37516,\"Ġflakes\":37517,\"ĠEVER\":37518,\"cong\":37519,\"ĠCreation\":37520,\"loo\":37521,\"ĠAmpl\":37522,\"ĠSpectre\":37523,\"012\":37524,\"geons\":37525,\"Ġswarm\":37526,\"ĠPale\":37527,\"ĠSeek\":37528,\"itures\":37529,\"Ġarri\":37530,\"Ġredistribution\":37531,\"campaign\":37532,\"ĠAbility\":37533,\"579\":37534,\"ournament\":37535,\"locks\":37536,\"Ġnests\":37537,\"ĠConstantine\":37538,\"Ġwhisper\":37539,\"Ġshrouded\":37540,\"changed\":37541,\"ĠEnhanced\":37542,\"Ġ920\":37543,\"Ġglob\":37544,\"Tam\":37545,\"Ġoutwe\":37546,\"Ġilliter\":37547,\"Ġsurg\":37548,\"Nap\":37549,\"ĠAerial\":37550,\"iferation\":37551,\"Egypt\":37552,\"ERO\":37553,\"Ġantip\":37554,\"environment\":37555,\"machine\":37556,\"Ġrupture\":37557,\"treatment\":37558,\"internal\":37559,\"Ġinfiltrate\":37560,\"Ġgratification\":37561,\"Uber\":37562,\"Ġunequal\":37563,\"Ġflav\":37564,\"Lord\":37565,\"tein\":37566,\"ĠLOT\":37567,\"Ġbullshit\":37568,\"Ġoriginals\":37569,\"Ġminced\":37570,\"Ġmultiply\":37571,\"ayson\":37572,\"Ġrecomm\":37573,\"Ġreceptors\":37574,\"Ġflashlight\":37575,\"Ġinhuman\":37576,\"Future\":37577,\"Ġpuzzling\":37578,\"Ġrouters\":37579,\"Ġuncontroll\":37580,\"responsible\":37581,\"Ġcellul\":37582,\"ĠTablet\":37583,\"Ġbolted\":37584,\"Ġpermissible\":37585,\"adra\":37586,\"picture\":37587,\"ODY\":37588,\"BRE\":37589,\"Iraq\":37590,\"Total\":37591,\"rising\":37592,\"Ġ273\":37593,\"nv\":37594,\"Ġ327\":37595,\"alysed\":37596,\"infect\":37597,\"Ġ1912\":37598,\"ĠVT\":37599,\"ĠLazarus\":37600,\"ictive\":37601,\"Bu\":37602,\"ĠNEVER\":37603,\"ĠCODE\":37604,\"ĠModified\":37605,\"fetched\":37606,\"ĠTrap\":37607,\"mob\":37608,\"Ġupkeep\":37609,\"WARD\":37610,\"Ġbrewed\":37611,\"Ġsaliva\":37612,\"Ġ1923\":37613,\"Ġsteroid\":37614,\"rather\":37615,\"ĠVER\":37616,\"Ġcontextual\":37617,\"Ont\":37618,\"ĠLSD\":37619,\"agine\":37620,\"Ġaudible\":37621,\"ĠMeta\":37622,\"erek\":37623,\"aults\":37624,\"ĠOttoman\":37625,\"ĠIncludes\":37626,\"Ġocc\":37627,\"678\":37628,\"ipple\":37629,\"Ġcontrasted\":37630,\"014\":37631,\"ĠLenin\":37632,\"Ġomega\":37633,\"885\":37634,\"civil\":37635,\"Ġoverload\":37636,\"},\\\"\":37637,\"Ġprogrammers\":37638,\"Ġgeometry\":37639,\"?).\":37640,\"shift\":37641,\"ĠClancy\":37642,\"nr\":37643,\"verb\":37644,\"Ġ760\":37645,\"Ġstaggered\":37646,\"Playing\":37647,\"ĠSmile\":37648,\"Ġcomplains\":37649,\"ĠSloven\":37650,\"Ġdisobedience\":37651,\"creator\":37652,\"Ġly\":37653,\"incoln\":37654,\"emp\":37655,\"Ġcrate\":37656,\"ĠPledge\":37657,\"ĠGPUs\":37658,\"protected\":37659,\"Vo\":37660,\"medium\":37661,\"Ġacet\":37662,\"603\":37663,\"478\":37664,\"469\":37665,\"Further\":37666,\"Ġsensed\":37667,\"Lock\":37668,\"Ġcrabs\":37669,\"ĠChains\":37670,\"ĠNEO\":37671,\"Ġexperimented\":37672,\"ĠRhythm\":37673,\"802\":37674,\"Ġhormonal\":37675,\"491\":37676,\"ĠMedian\":37677,\"Ġevaluates\":37678,\"ippi\":37679,\"Ġremovable\":37680,\"Ġvector\":37681,\"ilant\":37682,\"TERN\":37683,\"Ġpurch\":37684,\"ĠBind\":37685,\"athering\":37686,\"Ġcords\":37687,\"Lib\":37688,\"Ġdamned\":37689,\"orc\":37690,\"ĠEverywhere\":37691,\"Ġgorilla\":37692,\"ystem\":37693,\"fail\":37694,\"Ġecstasy\":37695,\"allion\":37696,\"Sea\":37697,\"Ġuploading\":37698,\"ĠSpecific\":37699,\"Ġreinforcement\":37700,\"cerned\":37701,\"ĠDollars\":37702,\"Twenty\":37703,\"OX\":37704,\"ADD\":37705,\"Ġbraces\":37706,\"Ġraven\":37707,\"Ġ1890\":37708,\"Ġcirculate\":37709,\"udden\":37710,\"Disney\":37711,\"ĠNope\":37712,\"ĠBagg\":37713,\"ĠBuddha\":37714,\"rael\":37715,\"urus\":37716,\"ĠKarma\":37717,\"Ġcurl\":37718,\"Ġflips\":37719,\"Ġbearer\":37720,\"Ġmisunderstand\":37721,\"Ġabras\":37722,\"ĠAssassin\":37723,\"Fact\":37724,\"Ġinterf\":37725,\"Ġvantage\":37726,\"ĠGenocide\":37727,\"Ġdeducted\":37728,\"Sep\":37729,\"McC\":37730,\"Jessica\":37731,\"ĠBackup\":37732,\"Ian\":37733,\"urnal\":37734,\"Ġlaborers\":37735,\"438\":37736,\"ĠContinuous\":37737,\"ĠNBN\":37738,\"Cool\":37739,\"mitting\":37740,\"ĠNormandy\":37741,\"Ġpurchaser\":37742,\"Ġacquainted\":37743,\"Ġblogging\":37744,\"route\":37745,\"marine\":37746,\"Ġstartled\":37747,\"6000\":37748,\"ĠRadical\":37749,\"kiss\":37750,\"ĠBlitz\":37751,\"express\":37752,\"Ġ601\":37753,\"hent\":37754,\"Ġtink\":37755,\"pires\":37756,\"launch\":37757,\"sg\":37758,\"ĠEffects\":37759,\"Ġstiffness\":37760,\"ĠAllies\":37761,\"Ġthirsty\":37762,\"Ġmyst\":37763,\"Ġlogger\":37764,\"Ġstances\":37765,\"ĠEvaluation\":37766,\"090\":37767,\"Ġproclaiming\":37768,\"Ġhypocritical\":37769,\"496\":37770,\"Ġcaus\":37771,\"ĠKappa\":37772,\"ĠLann\":37773,\"ĠScientist\":37774,\"Ġempath\":37775,\"etrical\":37776,\"lege\":37777,\"Hom\":37778,\"Aud\":37779,\"ĠColors\":37780,\"ĠStraw\":37781,\"each\":37782,\"ĠPatron\":37783,\"Ġnuance\":37784,\"send\":37785,\"ourney\":37786,\"ĠPhen\":37787,\"Ġamino\":37788,\"ĠSeconds\":37789,\"Sn\":37790,\"ĠCiv\":37791,\"Ġconglomer\":37792,\"Ġ411\":37793,\"versely\":37794,\"487\":37795,\"prises\":37796,\"Ġ277\":37797,\"necessary\":37798,\"Ġdope\":37799,\"Late\":37800,\"Ġrake\":37801,\"ĠBrigham\":37802,\"ogun\":37803,\"ĠSTATES\":37804,\"ĠGaal\":37805,\"Ġintellig\":37806,\"Ġglacier\":37807,\"destruct\":37808,\"ĠZucker\":37809,\"484\":37810,\"Ġ332\":37811,\"ĠArist\":37812,\"Ġprotagonists\":37813,\"Ġgraveyard\":37814,\"names\":37815,\"ĠPax\":37816,\"Ġthresholds\":37817,\"Seeing\":37818,\"Ġmunitions\":37819,\"Ġcontradicts\":37820,\"684\":37821,\"Ġ529\":37822,\"ĠConcent\":37823,\"ĠBlessed\":37824,\"Hz\":37825,\"Ġinhibit\":37826,\"Ġshenanigans\":37827,\"ĠSpear\":37828,\"Ġoverlay\":37829,\"ritis\":37830,\"ilus\":37831,\"Ġvariance\":37832,\"Ġoverpower\":37833,\"viol\":37834,\"erning\":37835,\"Ġpolarization\":37836,\"aito\":37837,\"GV\":37838,\"493\":37839,\"Keeping\":37840,\"Ġpaternity\":37841,\"ĠHappiness\":37842,\"oops\":37843,\"sb\":37844,\"xit\":37845,\"ophysical\":37846,\"Ġconclusive\":37847,\"Arch\":37848,\"Ġmiser\":37849,\"Ġsuffice\":37850,\"ĠStout\":37851,\"Ġhrs\":37852,\"643\":37853,\"Ġprincipled\":37854,\"azine\":37855,\"atorium\":37856,\"ĠFairy\":37857,\"Ġinfiltrated\":37858,\"ĠHier\":37859,\"ĠMIA\":37860,\"inders\":37861,\"Ġrebutt\":37862,\"Ġxx\":37863,\"Ġfeats\":37864,\"izzle\":37865,\"Ġ780\":37866,\"668\":37867,\"Ġrepressive\":37868,\"ĠYugoslavia\":37869,\"sole\":37870,\"704\":37871,\"ĠRPG\":37872,\"ĠTroll\":37873,\"packing\":37874,\"ĠDatabase\":37875,\"ĠVelvet\":37876,\"ĠRELEASE\":37877,\"ablish\":37878,\"smoking\":37879,\"ĠBottle\":37880,\"ĠFully\":37881,\"ĠLean\":37882,\"Ġobjectively\":37883,\"ĠFounding\":37884,\"ĠClassics\":37885,\"Ġmosaic\":37886,\"473\":37887,\"Ġrooft\":37888,\"Ġcentrally\":37889,\"Ġdismissive\":37890,\"Ġparasites\":37891,\"009\":37892,\"Ġcursed\":37893,\"Ġvex\":37894,\"Ġeconom\":37895,\"ĠBore\":37896,\"enery\":37897,\"ĠFundamental\":37898,\"ĠOmni\":37899,\"489\":37900,\"714\":37901,\"Ġforegoing\":37902,\"Ġfragment\":37903,\"oros\":37904,\"070\":37905,\"ĠFaust\":37906,\"Ġsucking\":37907,\"Ġnode\":37908,\"Ġrighteous\":37909,\"ĠPowered\":37910,\"426\":37911,\"HQ\":37912,\"Ġchronically\":37913,\"ĠBAL\":37914,\"Ġprest\":37915,\"Ġrapists\":37916,\"ĠRelationship\":37917,\"ĠCHR\":37918,\"Ġlinen\":37919,\"Ġnumerical\":37920,\"oters\":37921,\"Ġiterations\":37922,\"ttes\":37923,\"ĠENTER\":37924,\"Ġrabbi\":37925,\"Ġhoard\":37926,\"Ġmerciless\":37927,\"Ġrobes\":37928,\"ĠSpray\":37929,\"Ġadvers\":37930,\"ilantro\":37931,\"483\":37932,\"Ġfungus\":37933,\"Ġalcoholism\":37934,\"anasia\":37935,\"ĠCruiser\":37936,\"Ġmorals\":37937,\"cision\":37938,\"measures\":37939,\"Ġsabot\":37940,\"Ġrecol\":37941,\"ĠSaur\":37942,\"ĠError\":37943,\"Ġmysteriously\":37944,\"sle\":37945,\"Ġfeminists\":37946,\"Ð´\":37947,\"ackle\":37948,\"ĠMarxist\":37949,\"Ġselves\":37950,\"Ġdoorway\":37951,\"Ġdiscard\":37952,\"Ġbandits\":37953,\"ĠDive\":37954,\"ameless\":37955,\"TRY\":37956,\"Ġgull\":37957,\"Ġrepublican\":37958,\"sr\":37959,\"ĠDynamo\":37960,\"Ġembryo\":37961,\"MENTS\":37962,\"ĠLOW\":37963,\"Ġ319\":37964,\"Ġgly\":37965,\"Ġcowork\":37966,\"Coll\":37967,\"Ġcris\":37968,\"ĠBanana\":37969,\"reality\":37970,\"Ġmobilization\":37971,\"unal\":37972,\"Updated\":37973,\"Crew\":37974,\"ĠGideon\":37975,\"Ġvines\":37976,\"Ġknitting\":37977,\"Ġdag\":37978,\"ĠSurv\":37979,\"Ġvacc\":37980,\"Ġimpulses\":37981,\"Northern\":37982,\"Ġnanop\":37983,\"allows\":37984,\"UTH\":37985,\"Ġflashbacks\":37986,\"alsa\":37987,\"Ġ282\":37988,\"Ġtransmissions\":37989,\"ĠAlmighty\":37990,\"Office\":37991,\"ĠBride\":37992,\"ĠBeasts\":37993,\"othy\":37994,\"ĠClouds\":37995,\"ĠDyn\":37996,\"ĠJolly\":37997,\"District\":37998,\"Ġveget\":37999,\"Ġantit\":38000,\"ĠSmoking\":38001,\"hess\":38002,\"Ġcompose\":38003,\"Ġreligiously\":38004,\"ĠHY\":38005,\"Ġfluorescent\":38006,\"rame\":38007,\"ĠMeier\":38008,\"ĠSQ\":38009,\"benefit\":38010,\"Thirty\":38011,\"559\":38012,\"ĠCance\":38013,\"586\":38014,\"Ġgrouped\":38015,\"Ġphys\":38016,\"Ġrebellious\":38017,\"ĠBASE\":38018,\"chid\":38019,\"582\":38020,\"ĠLessons\":38021,\"ĠWonderful\":38022,\"ODE\":38023,\"uctions\":38024,\"Ġbarbaric\":38025,\"rahim\":38026,\"635\":38027,\"Ġcloves\":38028,\"ĠNIH\":38029,\"ossession\":38030,\"Employ\":38031,\"Ġliberate\":38032,\"Gro\":38033,\"Ġmagician\":38034,\"ountain\":38035,\"FORM\":38036,\"533\":38037,\"Ġunpredict\":38038,\"rity\":38039,\"Ġfaked\":38040,\"plets\":38041,\"ppelin\":38042,\"Living\":38043,\"Ġnearer\":38044,\"Ġsuperiors\":38045,\"Ur\":38046,\"Ġheroism\":38047,\"Ġbearded\":38048,\"006\":38049,\"Cole\":38050,\"1970\":38051,\"Ġsill\":38052,\"ĠReduce\":38053,\"OLOG\":38054,\"onel\":38055,\"Billy\":38056,\"ĠPainter\":38057,\"ansas\":38058,\"Ġintermediary\":38059,\"trump\":38060,\"ĠMith\":38061,\"otom\":38062,\"434\":38063,\"Ġterrit\":38064,\"Wa\":38065,\"Ġsuprem\":38066,\"Rh\":38067,\"liction\":38068,\"ĠDEAD\":38069,\"Ġbothers\":38070,\"503\":38071,\"Ġfrogs\":38072,\"Ġsprinkled\":38073,\"Ġnil\":38074,\"628\":38075,\"Private\":38076,\"ĠKGB\":38077,\"Ġoverriding\":38078,\"Ġdeceived\":38079,\"698\":38080,\"idium\":38081,\"Ġseeker\":38082,\"Final\":38083,\"Ġsubconscious\":38084,\"Ġwom\":38085,\"Ġcass\":38086,\"Ġchicks\":38087,\"Ġverifying\":38088,\"ective\":38089,\"inia\":38090,\"ĠDetection\":38091,\"MH\":38092,\"fortable\":38093,\"ĠISPs\":38094,\"Ġcrumble\":38095,\"ĠRecap\":38096,\"598\":38097,\"ummies\":38098,\"export\":38099,\"Irish\":38100,\"Ġlil\":38101,\"ĠRapt\":38102,\"ĠRIGHT\":38103,\"Ġanecdotal\":38104,\"Ġpiercing\":38105,\"deck\":38106,\"Liber\":38107,\"Books\":38108,\"Ġassassin\":38109,\"Tur\":38110,\"revolution\":38111,\"ĠSheep\":38112,\"ĠPublishers\":38113,\"EMS\":38114,\"iosis\":38115,\"finder\":38116,\"ĠCuriosity\":38117,\"ARB\":38118,\"ĠConvers\":38119,\"IVES\":38120,\"clave\":38121,\"ĠChaos\":38122,\"ĠMim\":38123,\"ĠCostume\":38124,\"Ġtwe\":38125,\"Ġintim\":38126,\"757\":38127,\"berto\":38128,\"Ġ261\":38129,\"VPN\":38130,\"cribed\":38131,\"ĠVerb\":38132,\"cb\":38133,\"Ġaxle\":38134,\"Ġsandwic\":38135,\"Ice\":38136,\"ĠThermal\":38137,\"654\":38138,\"709\":38139,\"ĠPact\":38140,\"ĠEnsure\":38141,\"izable\":38142,\"497\":38143,\"Ġbloodstream\":38144,\"Aw\":38145,\"Ġleakage\":38146,\"Ġalleg\":38147,\"ĠMelody\":38148,\"681\":38149,\"Austin\":38150,\"428\":38151,\"Ġsummarized\":38152,\"ĠDefendants\":38153,\"ĠVader\":38154,\"Ê\":38155,\"Ġ1880\":38156,\"Ġassemb\":38157,\"YOU\":38158,\"GREEN\":38159,\"jury\":38160,\"4000\":38161,\"Ġvenerable\":38162,\"Ġcomputational\":38163,\"Ġperpetuate\":38164,\"Ġtorpedo\":38165,\"Ġaborted\":38166,\"Ġrhetorical\":38167,\"ĠOvert\":38168,\"Ġacknowledgment\":38169,\"essment\":38170,\"ĠIGN\":38171,\"ĠSheen\":38172,\"571\":38173,\"Ġcontag\":38174,\"Ġcultiv\":38175,\"Ġspawn\":38176,\"mess\":38177,\"Dur\":38178,\"Ġvortex\":38179,\"ixties\":38180,\"ĠBlow\":38181,\"Sum\":38182,\"Åį\":38183,\"Rom\":38184,\"ĠRadeon\":38185,\"Fed\":38186,\"Ġameric\":38187,\"ĠAnth\":38188,\"Ġantic\":38189,\"Ġfortress\":38190,\"Cold\":38191,\"ĠPredict\":38192,\"Fake\":38193,\"Ġilluminate\":38194,\"Find\":38195,\"Ġintellectually\":38196,\"Ġgon\":38197,\"alker\":38198,\"Ġinvoice\":38199,\"IELD\":38200,\"Ġfools\":38201,\"ĠEnding\":38202,\"-(\":38203,\"Ġalk\":38204,\"ĠControlled\":38205,\"Ġpurposefully\":38206,\"ĠChronic\":38207,\"Ġrele\":38208,\"ĠOps\":38209,\"Party\":38210,\"ethnic\":38211,\"ĠSpecifications\":38212,\"ffee\":38213,\"ĠTeach\":38214,\"ulas\":38215,\"Ġenslaved\":38216,\"onomy\":38217,\"Ġtenets\":38218,\"Ġammonia\":38219,\"Ġ1913\":38220,\"Ġdripping\":38221,\"612\":38222,\"659\":38223,\"ĠSagan\":38224,\"Ġinaccur\":38225,\"Ġabol\":38226,\"ĠLIKE\":38227,\"Ġvisualization\":38228,\"learn\":38229,\"anon\":38230,\"cipline\":38231,\"Ġadaptations\":38232,\"Ġwaiter\":38233,\"nergy\":38234,\"507\":38235,\"ĠDK\":38236,\"YD\":38237,\"Ġpedest\":38238,\"Sense\":38239,\"ĠObst\":38240,\"Ġresurrection\":38241,\"ĠSPECIAL\":38242,\"Unlike\":38243,\"Ġlia\":38244,\"Ġpersuasive\":38245,\"iatrics\":38246,\"ONEY\":38247,\"esthetic\":38248,\"494\":38249,\"zik\":38250,\"Ġfract\":38251,\"ĠOutput\":38252,\"ĠBers\":38253,\"rozen\":38254,\"ĠRevis\":38255,\"Ġdraconian\":38256,\"Words\":38257,\"asions\":38258,\"ĠClintons\":38259,\"CU\":38260,\"History\":38261,\"Ġtwilight\":38262,\"iform\":38263,\"Ġdispl\":38264,\"progress\":38265,\"ĠIO\":38266,\"Ġcannibal\":38267,\"Michelle\":38268,\"Ġnerv\":38269,\"Ġcontexts\":38270,\"ĠHorses\":38271,\"Ġanatomy\":38272,\"ĠLegislation\":38273,\"ĠBloody\":38274,\"Ġunwittingly\":38275,\"Ġinquired\":38276,\"ĠZip\":38277,\"ĠDesigns\":38278,\"Ġirritating\":38279,\"Ġunison\":38280,\"ĠRG\":38281,\"aviour\":38282,\"Ġpseudo\":38283,\"ĠVenom\":38284,\"Ġobscured\":38285,\"Ġner\":38286,\"uked\":38287,\"ORGE\":38288,\"Ġmomentarily\":38289,\"olyn\":38290,\"Syrian\":38291,\"Ġmicroscopic\":38292,\"Ġmistress\":38293,\"Less\":38294,\"Ġawoke\":38295,\"Ġtutor\":38296,\"esome\":38297,\"ollar\":38298,\"egg\":38299,\"UTE\":38300,\"Buzz\":38301,\"Ġattainment\":38302,\"Ġdiscriminating\":38303,\"::\":38304,\"Ġ525\":38305,\"azard\":38306,\"ĠBrist\":38307,\"oras\":38308,\"Ġveterin\":38309,\"jing\":38310,\"idon\":38311,\"ĠAustral\":38312,\"arious\":38313,\"ĠGrav\":38314,\"anol\":38315,\"ĠQuran\":38316,\"Ġbleach\":38317,\"588\":38318,\"ĠOsw\":38319,\"Ġdiffered\":38320,\"typ\":38321,\"ĠSIL\":38322,\"failed\":38323,\"436\":38324,\"Ġpalms\":38325,\"ĠFail\":38326,\"idespread\":38327,\"Ġchap\":38328,\"ĠIMAGES\":38329,\"ACP\":38330,\"matched\":38331,\"Ġjaws\":38332,\"MHz\":38333,\"Nik\":38334,\"ĠHume\":38335,\"OSH\":38336,\"Ġpresume\":38337,\"secut\":38338,\"ĠDied\":38339,\"ĠBreat\":38340,\"gins\":38341,\"prison\":38342,\"ĠUR\":38343,\"ĠROS\":38344,\"isitions\":38345,\"Ġpelvic\":38346,\"exclusive\":38347,\"522\":38348,\"689\":38349,\"FN\":38350,\"Ġener\":38351,\"Ġdispers\":38352,\"Ġcohorts\":38353,\"shut\":38354,\"ĠLoad\":38355,\"needs\":38356,\"azaki\":38357,\"inoa\":38358,\"Inside\":38359,\"usra\":38360,\"ighters\":38361,\"Ġ271\":38362,\"Ġsubordinate\":38363,\"ĠHOL\":38364,\"ĠGlow\":38365,\"Ġincred\":38366,\"ĠMadame\":38367,\"Ġoats\":38368,\"Ġdeviation\":38369,\"ĠApproach\":38370,\"Ġnarc\":38371,\"bart\":38372,\"bole\":38373,\"ĠSHE\":38374,\"effects\":38375,\"ĠADA\":38376,\"Ġmuse\":38377,\"Squ\":38378,\"Ġneuroscience\":38379,\"ĠValues\":38380,\"engu\":38381,\"Ġdosage\":38382,\"Ġwhispers\":38383,\"Ġnaughty\":38384,\"ĠFarming\":38385,\"Recently\":38386,\"Ġrelapse\":38387,\"rentice\":38388,\"UGH\":38389,\"Ġdarkened\":38390,\"appings\":38391,\"ĠSlaughter\":38392,\"ĠAnim\":38393,\"Ġovertly\":38394,\"poses\":38395,\"Ġdeficient\":38396,\"Ġnecks\":38397,\"Iron\":38398,\"Ġphysiological\":38399,\"ĠLiang\":38400,\"Ġlear\":38401,\"Ġcelestial\":38402,\"Ġpistols\":38403,\"Ġeyebrow\":38404,\"915\":38405,\"ratch\":38406,\"cephal\":38407,\"ĠPSU\":38408,\"Ġphotograp\":38409,\"ĠGaul\":38410,\"Ġuncontrolled\":38411,\"ĠJoined\":38412,\"652\":38413,\"itory\":38414,\"Ġ274\":38415,\"GAN\":38416,\"imester\":38417,\"essional\":38418,\"Ø©\":38419,\"Ġuncons\":38420,\"THER\":38421,\"Ġpaternal\":38422,\"Zero\":38423,\"ugen\":38424,\"538\":38425,\"Ġende\":38426,\"Ġ505\":38427,\"movie\":38428,\"Lind\":38429,\"Ġscorn\":38430,\"ulty\":38431,\"Ġpesky\":38432,\"Ġ8000\":38433,\"677\":38434,\"Ġhomophobia\":38435,\"ranch\":38436,\"Ġnarciss\":38437,\"ĠVoyager\":38438,\"ĠHELP\":38439,\"528\":38440,\"edly\":38441,\"Ġdetract\":38442,\"Hope\":38443,\"787\":38444,\"ĠMerlin\":38445,\"Ġgrids\":38446,\"KI\":38447,\"Mu\":38448,\"ĠSelected\":38449,\"select\":38450,\"ĠModer\":38451,\"ĠFeet\":38452,\"Ġrename\":38453,\"intensity\":38454,\"Wilson\":38455,\"Ġ414\":38456,\"leave\":38457,\"Ready\":38458,\"intuitive\":38459,\"Ġmeager\":38460,\"Franc\":38461,\"DH\":38462,\"Ġrhy\":38463,\"ĠPillar\":38464,\"ĠDOE\":38465,\"minist\":38466,\"ĠGrave\":38467,\"isible\":38468,\"Ess\":38469,\"Ġempt\":38470,\"Ġpatched\":38471,\"ĠAbortion\":38472,\"rals\":38473,\"Ġdow\":38474,\"Ġcrawled\":38475,\"igrate\":38476,\"Virginia\":38477,\"Ġconting\":38478,\"Ġorphans\":38479,\"ĠCrimean\":38480,\"Ġdyn\":38481,\"Ġshadowy\":38482,\"sound\":38483,\"ailable\":38484,\"Ġ293\":38485,\"vm\":38486,\"Ġaccompanies\":38487,\"Meanwhile\":38488,\"JR\":38489,\"ĠDirections\":38490,\"Ġadolescence\":38491,\"Ġpenetrated\":38492,\"bars\":38493,\"Rev\":38494,\"Ta\":38495,\"ĠSkywalker\":38496,\"ĠFires\":38497,\"concept\":38498,\"ĠSIG\":38499,\"554\":38500,\"currently\":38501,\"Ġ----------------\":38502,\"ĠWHITE\":38503,\"767\":38504,\"rors\":38505,\"PDF\":38506,\"Ġcasing\":38507,\"673\":38508,\"Ġdisapprove\":38509,\"1800\":38510,\"ĠWeed\":38511,\"Ġinhib\":38512,\"Ġmorbid\":38513,\"433\":38514,\"Ġawfully\":38515,\"Ts\":38516,\"Maria\":38517,\"Ġillusions\":38518,\"Ġtotalitarian\":38519,\"ollo\":38520,\"Ġsuppl\":38521,\"Ġsarc\":38522,\"ĠRGB\":38523,\"Ġlauncher\":38524,\"Ġbadass\":38525,\"ĠSyd\":38526,\"Ġscrape\":38527,\"ĠCLA\":38528,\"Ġcircum\":38529,\"657\":38530,\"Ġnucleus\":38531,\"ĠUkip\":38532,\"Ġmodem\":38533,\"ĠJou\":38534,\"adders\":38535,\"Ġwiser\":38536,\"thereal\":38537,\"Ġdemocr\":38538,\"ĠInvalid\":38539,\"Mine\":38540,\"Ġmanifested\":38541,\"meat\":38542,\"MORE\":38543,\"Larry\":38544,\"acements\":38545,\"Ġspecimen\":38546,\"results\":38547,\"Ġswallowing\":38548,\"Ġpigeon\":38549,\"tons\":38550,\"ĠLose\":38551,\"Ġquartz\":38552,\"Ġintraven\":38553,\"Ġ412\":38554,\"alyst\":38555,\"Ġengraved\":38556,\"client\":38557,\"ĠADV\":38558,\"ĠShared\":38559,\"Ġrites\":38560,\"Ġhysterical\":38561,\"ĠHUM\":38562,\"Cow\":38563,\"orously\":38564,\"Ġpleasures\":38565,\"democratic\":38566,\"Ġamph\":38567,\"Ġnib\":38568,\"rieg\":38569,\"Ġcalculates\":38570,\"Ġfrying\":38571,\"favorite\":38572,\"Ġantim\":38573,\"ĠDoom\":38574,\"monitor\":38575,\"Want\":38576,\"Ġtemplates\":38577,\"558\":38578,\"iever\":38579,\"Photos\":38580,\",,\":38581,\"ĠSync\":38582,\"Ġconfronts\":38583,\"kept\":38584,\"dt\":38585,\"ĠERROR\":38586,\"ETF\":38587,\"578\":38588,\"Ġspor\":38589,\"718\":38590,\"ivation\":38591,\"ĠHaskell\":38592,\"Ca\":38593,\"Ġdick\":38594,\"Ġcivilized\":38595,\"Ġblah\":38596,\"enough\":38597,\"Ġoccup\":38598,\"Ġ334\":38599,\"antically\":38600,\"584\":38601,\"ĠDolphin\":38602,\"ĠStarts\":38603,\"Ġfanatic\":38604,\"Øª\":38605,\"imag\":38606,\"Ġmicrobial\":38607,\"freedom\":38608,\"cult\":38609,\"wra\":38610,\"Ġ423\":38611,\"RIPT\":38612,\"601\":38613,\"BTC\":38614,\"atmeal\":38615,\"653\":38616,\"agogue\":38617,\"Ġderives\":38618,\"Wolf\":38619,\"466\":38620,\"Susan\":38621,\"ĠPassage\":38622,\"ARDS\":38623,\"Guy\":38624,\"Council\":38625,\"Ġerotic\":38626,\"pure\":38627,\"ĠMemories\":38628,\"ĠWikileaks\":38629,\"elines\":38630,\"Ġanth\":38631,\"Capital\":38632,\"807\":38633,\"ĠEggs\":38634,\"cv\":38635,\"ctors\":38636,\"Ġshatter\":38637,\"Ġesteem\":38638,\"vity\":38639,\"ĠVulcan\":38640,\"effic\":38641,\"ĠBELOW\":38642,\"Ġplatoon\":38643,\"Commun\":38644,\"oustic\":38645,\"Amy\":38646,\"Freedom\":38647,\"ppo\":38648,\"Ja\":38649,\"ĠConan\":38650,\"Ġinsepar\":38651,\"scene\":38652,\"Ġurinary\":38653,\"gain\":38654,\"Hillary\":38655,\"ĠTAM\":38656,\"Hist\":38657,\"Ġmechan\":38658,\"ĠRobots\":38659,\"Leader\":38660,\"Ġcartridges\":38661,\"Ġwhistleblowers\":38662,\"ĠSPL\":38663,\"Labour\":38664,\"unction\":38665,\"Ġfaithfully\":38666,\"Ġcoarse\":38667,\"Ġsynth\":38668,\"ĠLV\":38669,\"Ġjustifying\":38670,\"439\":38671,\"Victoria\":38672,\"ĠProceedings\":38673,\"alogy\":38674,\"Ġmorph\":38675,\"Ġcove\":38676,\"Ġlaughable\":38677,\"ECA\":38678,\"Ġ670\":38679,\"aturated\":38680,\"ĠSouls\":38681,\"ĠSleeping\":38682,\"Ly\":38683,\"ĠRetro\":38684,\"Ġastroph\":38685,\"Ġseism\":38686,\"atherine\":38687,\"ĠHercules\":38688,\"Ġfuse\":38689,\"ĠHL\":38690,\"Ġunintentionally\":38691,\"ĠRÃ©\":38692,\"iery\":38693,\"Ġconco\":38694,\"Ġeras\":38695,\"recent\":38696,\"Ġlaunchers\":38697,\"ĠVolcano\":38698,\"ĠJace\":38699,\"Ġterminating\":38700,\"ĠIde\":38701,\"zee\":38702,\"asonic\":38703,\"itone\":38704,\"Ġnutshell\":38705,\"Ġbip\":38706,\"dies\":38707,\"Ġ286\":38708,\"Ġnood\":38709,\"ĠFathers\":38710,\"alys\":38711,\"Ġtheor\":38712,\"???\":38713,\"548\":38714,\"674\":38715,\"efined\":38716,\"806\":38717,\"âĻ\":38718,\"697\":38719,\"Ġdecap\":38720,\"ĠFN\":38721,\"Ġbureaucr\":38722,\"ĠGoat\":38723,\"ĠShang\":38724,\"Ġsemin\":38725,\"Ġthroats\":38726,\"Ġmoth\":38727,\"herer\":38728,\"Democratic\":38729,\"ixtures\":38730,\"impl\":38731,\"ĠLogo\":38732,\"ortunate\":38733,\"Ġclumsy\":38734,\"Ġinnocuous\":38735,\"ĠBlend\":38736,\"abulary\":38737,\"ĠFaces\":38738,\"Ġpornographic\":38739,\"px\":38740,\"Information\":38741,\"Ġfluoride\":38742,\"Ġatroc\":38743,\"Ġdelta\":38744,\"whatever\":38745,\"ossier\":38746,\"ĠNoir\":38747,\"ĠYao\":38748,\"551\":38749,\"undred\":38750,\"Ġmillennium\":38751,\"Ġferal\":38752,\"Ġconvinc\":38753,\"cano\":38754,\"imsy\":38755,\"angles\":38756,\"Ġsterile\":38757,\"ĠMenu\":38758,\"779\":38759,\"ĠCrack\":38760,\"Ġabundantly\":38761,\"ĠmL\":38762,\"Ġinfiltration\":38763,\"ĠDefinition\":38764,\"733\":38765,\"oubt\":38766,\"Ġorbital\":38767,\"Ġpiss\":38768,\"Ġbeet\":38769,\"679\":38770,\"Ġcounteract\":38771,\"ĠALE\":38772,\"ulative\":38773,\"crew\":38774,\"Ġliberating\":38775,\"ĠDull\":38776,\"Speaking\":38777,\"Sadly\":38778,\"Ġmisfortune\":38779,\"Ġdolphin\":38780,\"557\":38781,\"Ġbould\":38782,\"ĠTorah\":38783,\"ĠConfederacy\":38784,\"421\":38785,\"Ġorbits\":38786,\"ocused\":38787,\"beer\":38788,\"Rand\":38789,\"ĠORIG\":38790,\"Ġmuc\":38791,\"LER\":38792,\"ĠMisty\":38793,\"Ġinexpl\":38794,\"Ġreptiles\":38795,\"Ġaven\":38796,\"blocking\":38797,\"ĠPASS\":38798,\"Ġarisen\":38799,\"ĠMock\":38800,\"Ġops\":38801,\"Ġshin\":38802,\"524\":38803,\"Ġdigestion\":38804,\"Soft\":38805,\"irect\":38806,\"POL\":38807,\"ĠSpell\":38808,\"Level\":38809,\"Ġhex\":38810,\"Ġbitcoins\":38811,\"ĠHungry\":38812,\"VL\":38813,\"ĠRealm\":38814,\"RELATED\":38815,\"Delta\":38816,\"Pri\":38817,\"Ġrejoice\":38818,\"ĠLatter\":38819,\"LG\":38820,\"Ġstupidity\":38821,\"Ġdonkey\":38822,\"nova\":38823,\"Vill\":38824,\"Ġdecomp\":38825,\"Ġexternally\":38826,\"Ġsequest\":38827,\"815\":38828,\"Ġshortcut\":38829,\"riminal\":38830,\"Hun\":38831,\"EH\":38832,\"Ġregiment\":38833,\"Case\":38834,\"definition\":38835,\"Ġappendix\":38836,\"ĠPlayed\":38837,\"associated\":38838,\"izens\":38839,\"ĠVag\":38840,\"Ġflung\":38841,\"Ġfru\":38842,\"Ġcoil\":38843,\"________________________\":38844,\"Ġselects\":38845,\"Ġsolves\":38846,\"aea\":38847,\"985\":38848,\"Tomorrow\":38849,\"Ġsear\":38850,\"APE\":38851,\"492\":38852,\"Ġenlightened\":38853,\"Ġnonexistent\":38854,\"ĠPotato\":38855,\"Ghost\":38856,\"Ġrichness\":38857,\"ĠKarin\":38858,\"Ġfamilial\":38859,\"ĠJA\":38860,\"Regardless\":38861,\"Ġepis\":38862,\"GD\":38863,\"Ġinsanely\":38864,\"ĠPhill\":38865,\"Block\":38866,\"Finding\":38867,\"omal\":38868,\"Ġdecipher\":38869,\"ĠSwap\":38870,\"derived\":38871,\"ĠOFFIC\":38872,\"Support\":38873,\"Ġnylon\":38874,\"Ġexaggeration\":38875,\"Ġevangelicals\":38876,\"Ġbearings\":38877,\"587\":38878,\"Ġlocale\":38879,\"Ġpowerfully\":38880,\"Ġappropriated\":38881,\"itates\":38882,\"irlfriend\":38883,\"cule\":38884,\"ĠSomewhere\":38885,\"747\":38886,\"ĠInteresting\":38887,\"464\":38888,\"Ġelong\":38889,\"Ġdegrade\":38890,\"rafted\":38891,\"Ġtutorials\":38892,\"905\":38893,\"ĠIntervention\":38894,\"Ġuniqueness\":38895,\"Ġ284\":38896,\"Ġexplorers\":38897,\"Ġnucle\":38898,\"ĠMillenn\":38899,\"511\":38900,\"ĠReneg\":38901,\"Ġexecut\":38902,\"urai\":38903,\"leon\":38904,\"Ġdeserts\":38905,\"ĠCig\":38906,\"Ġsuggestive\":38907,\"instead\":38908,\"Ġlousy\":38909,\"Ġenigmatic\":38910,\"594\":38911,\"Know\":38912,\"rollment\":38913,\"ipher\":38914,\"Ġhumanities\":38915,\"Ġmodifying\":38916,\".....\":38917,\"Ġdegraded\":38918,\"Ġsuppressing\":38919,\"Ġeman\":38920,\"abouts\":38921,\"functional\":38922,\"ĠOU\":38923,\"ĠRelax\":38924,\"786\":38925,\"esses\":38926,\"ĠLogin\":38927,\"spec\":38928,\"ĠWWF\":38929,\"Ġ364\":38930,\"ĠIsis\":38931,\"Wisconsin\":38932,\"Ġequival\":38933,\"ĠCollector\":38934,\"ibilities\":38935,\"malink\":38936,\"acea\":38937,\"Ġchained\":38938,\"Ġarist\":38939,\"Ġdisadvantages\":38940,\"ĠBrus\":38941,\"limits\":38942,\"ĠDmit\":38943,\"544\":38944,\"ĠRecipe\":38945,\"Ġhabitual\":38946,\".):\":38947,\"ĠPRODUCT\":38948,\"772\":38949,\"Ġrept\":38950,\"Ġpathology\":38951,\"Ġresurrected\":38952,\"uders\":38953,\"Ġlingu\":38954,\"Ġdenomination\":38955,\"Ġfirewall\":38956,\"scient\":38957,\"Ġvaliant\":38958,\"Kansas\":38959,\"516\":38960,\"Ġcontemporaries\":38961,\"Roman\":38962,\"Ġaccompan\":38963,\"Ġantennas\":38964,\"ĠXan\":38965,\"Ġelectromagnetic\":38966,\"ĠNek\":38967,\"alien\":38968,\"indle\":38969,\"Ġgraphene\":38970,\"Ġgraceful\":38971,\"syn\":38972,\"ĠBosh\":38973,\"Ġ1908\":38974,\"Ġsuccumb\":38975,\"Technology\":38976,\"Ġtoxin\":38977,\"myra\":38978,\"essert\":38979,\"Hell\":38980,\"Gil\":38981,\"Ġdiarr\":38982,\"imeters\":38983,\"Ġexplo\":38984,\"Ġgeometric\":38985,\"ĠNavigation\":38986,\"cern\":38987,\"Ġprogrammer\":38988,\"oÄŁan\":38989,\"Ġdodging\":38990,\"ĠLU\":38991,\"573\":38992,\"inters\":38993,\"Ġserum\":38994,\"Ġuber\":38995,\"Ġmanga\":38996,\"762\":38997,\"ĠOccasionally\":38998,\"437\":38999,\"ĠTheme\":39000,\"Ġimmature\":39001,\"Ġactivating\":39002,\"ĠTruly\":39003,\"Ø¯\":39004,\"osion\":39005,\"Age\":39006,\"TIME\":39007,\"Silver\":39008,\"sand\":39009,\"ulnerable\":39010,\"Ġcram\":39011,\"Large\":39012,\"ĠAnger\":39013,\"icators\":39014,\"431\":39015,\"ĠHonest\":39016,\"zip\":39017,\"Ġdism\":39018,\"Ġfades\":39019,\"ĠPik\":39020,\"Ast\":39021,\"sequent\":39022,\"Ġunsigned\":39023,\"xious\":39024,\"creation\":39025,\"Ġ395\":39026,\"ottenham\":39027,\"Ġundesirable\":39028,\"ugal\":39029,\"ĠDivide\":39030,\"lp\":39031,\"563\":39032,\"ĠPOP\":39033,\"ĠCET\":39034,\"session\":39035,\"Ġoccurrences\":39036,\"chu\":39037,\"ĠACS\":39038,\"ĠProsecut\":39039,\"Ġhypnot\":39040,\"rely\":39041,\"ERG\":39042,\"Ven\":39043,\"Republicans\":39044,\"inez\":39045,\"ĠImplementation\":39046,\"Ġsprang\":39047,\"Ġobs\":39048,\"Defense\":39049,\"Ġunexpl\":39050,\"ĠPAGE\":39051,\"ĠTent\":39052,\"ĠNeurolog\":39053,\"Ġintuition\":39054,\"759\":39055,\"Ġterrestrial\":39056,\"Ġmorphine\":39057,\"Ġ.\\\"\":39058,\"ĠHydra\":39059,\"651\":39060,\"Ġneoliberal\":39061,\"683\":39062,\"Ġabnormalities\":39063,\"quant\":39064,\"Ġmonastery\":39065,\"jac\":39066,\"ĠReaction\":39067,\"Ġcontraceptive\":39068,\"ĠBalls\":39069,\"Ġapost\":39070,\"676\":39071,\"ĠHELL\":39072,\"approximately\":39073,\"Ġvibrations\":39074,\"COR\":39075,\"ĠCPUs\":39076,\"Ġcontin\":39077,\"Ġsemblance\":39078,\"Ġshorth\":39079,\"tip\":39080,\"ĠChips\":39081,\"makes\":39082,\"Ġprett\":39083,\"Ġconspicuous\":39084,\"ĠAmp\":39085,\"Ġvisualize\":39086,\"Hu\":39087,\"sorry\":39088,\"nai\":39089,\"ĠArcade\":39090,\"rimination\":39091,\"obin\":39092,\"Ġvampire\":39093,\"773\":39094,\"ĠCaucasus\":39095,\"Medic\":39096,\"ĠGitHub\":39097,\"ĠWicked\":39098,\"ĠFet\":39099,\"Krist\":39100,\"998\":39101,\"Ġfrontal\":39102,\"Ġ283\":39103,\"ndum\":39104,\"Ġidols\":39105,\"ĠMSG\":39106,\"ĠShuttle\":39107,\"ĠTowards\":39108,\"Ġsaturation\":39109,\"ĠÂ®\":39110,\"Ġcradle\":39111,\"eteen\":39112,\"Ġprejudices\":39113,\"separ\":39114,\"ĠSoda\":39115,\"ynam\":39116,\"Ġnause\":39117,\"Ġpenetrating\":39118,\"ĠVampire\":39119,\"Ġmole\":39120,\"Ġgoogle\":39121,\"earance\":39122,\"583\":39123,\"Ġdomin\":39124,\"727\":39125,\"Kind\":39126,\"Ġcust\":39127,\"manuel\":39128,\"ĠAstro\":39129,\"Roger\":39130,\"JO\":39131,\"killed\":39132,\"ĠDisapp\":39133,\"833\":39134,\"ĠEQU\":39135,\"Ġprecedence\":39136,\"mberg\":39137,\"641\":39138,\"ĠRoller\":39139,\"Ġspecifying\":39140,\"035\":39141,\"phil\":39142,\"Ġpowdered\":39143,\"Ġblot\":39144,\"Ġdeline\":39145,\"Bruce\":39146,\"536\":39147,\"Ġpim\":39148,\"leasing\":39149,\"vacc\":39150,\"RN\":39151,\"Ġspacing\":39152,\"Ġhangar\":39153,\"ĠPlot\":39154,\"537\":39155,\"legraph\":39156,\"596\":39157,\"Ġpolyg\":39158,\"doi\":39159,\"ĠNerd\":39160,\"installed\":39161,\"ĠSeeds\":39162,\"ĠPlays\":39163,\"ĠRomance\":39164,\"layer\":39165,\"Ġunsu\":39166,\"Ġcurric\":39167,\"Mi\":39168,\"restrial\":39169,\"ĠNiÃ±o\":39170,\"ĠProper\":39171,\"Ġpores\":39172,\"Giving\":39173,\"aeus\":39174,\"Middle\":39175,\"liber\":39176,\"Ġcombatants\":39177,\"ĠBulk\":39178,\"Ġ502\":39179,\"Ġstru\":39180,\"ĠLonely\":39181,\"Companies\":39182,\"inence\":39183,\"Autom\":39184,\"Ġfearsome\":39185,\"Ġsummar\":39186,\"Ġrotated\":39187,\"ĠPLA\":39188,\"ĠFAT\":39189,\"572\":39190,\"ĠSkies\":39191,\"iour\":39192,\"Ġintimately\":39193,\"amera\":39194,\"Ġ475\":39195,\"623\":39196,\"Ġirrig\":39197,\"Ġboosters\":39198,\"Ġtransmitting\":39199,\"DOWN\":39200,\"ĠAble\":39201,\"Ġfuriously\":39202,\"spirit\":39203,\"Ġgrun\":39204,\"Ġbible\":39205,\"ĠAdmir\":39206,\"ĠÂ§\":39207,\"ĠRaise\":39208,\"Ġflowering\":39209,\"uxe\":39210,\"ravis\":39211,\"urther\":39212,\"ĠScientology\":39213,\"pathy\":39214,\"Ġruth\":39215,\"Ġtempor\":39216,\"Ġwhispered\":39217,\"ogly\":39218,\"coord\":39219,\"chlor\":39220,\"processing\":39221,\"iott\":39222,\"ĠTY\":39223,\"wik\":39224,\"abolic\":39225,\"ĠUnable\":39226,\"ĠLiterary\":39227,\"ĠpH\":39228,\"Eastern\":39229,\"Craig\":39230,\"Fear\":39231,\"Ġinventions\":39232,\"ĠNost\":39233,\"Ġafflicted\":39234,\"ĠSwamp\":39235,\"INST\":39236,\"Jerry\":39237,\"Ġprope\":39238,\"ĠLancet\":39239,\"Ġrefres\":39240,\"ĠPrinciples\":39241,\"ĠLys\":39242,\"ERAL\":39243,\"addock\":39244,\"Ġcynicism\":39245,\"Ġmassacres\":39246,\"roo\":39247,\"Ġcollagen\":39248,\"Johnny\":39249,\"Keith\":39250,\"Italian\":39251,\"553\":39252,\"Dad\":39253,\"Neither\":39254,\"cler\":39255,\"ilers\":39256,\"Ġassass\":39257,\"Travel\":39258,\"672\":39259,\"Ġeaves\":39260,\"ATOR\":39261,\"Ġoily\":39262,\"581\":39263,\"ateful\":39264,\"728\":39265,\"Ġchiefly\":39266,\"tical\":39267,\"enes\":39268,\"ĠWouldn\":39269,\"ĠJacket\":39270,\"ĠSuit\":39271,\"Ġindustrialized\":39272,\"ĠNose\":39273,\"ĠSECTION\":39274,\"Ġredd\":39275,\"Ġcavity\":39276,\"Ġconn\":39277,\"Shield\":39278,\"Ġtongues\":39279,\"Ġsuccinct\":39280,\"views\":39281,\"ĠMUST\":39282,\"oliath\":39283,\"Ġlimitless\":39284,\"Ġapocalyptic\":39285,\"ĠAtlantis\":39286,\"DNA\":39287,\"ilded\":39288,\"ĠDresden\":39289,\"nit\":39290,\"Ġsubdiv\":39291,\"gressive\":39292,\"701\":39293,\"hops\":39294,\"alist\":39295,\"Ġunintentional\":39296,\"Ġpsychic\":39297,\"Ġcontrovers\":39298,\"Ġforeground\":39299,\"ĠnaÃ¯ve\":39300,\"Ġfolders\":39301,\"icist\":39302,\"Ġdrawbacks\":39303,\"ĠToxic\":39304,\"ophy\":39305,\"ĠMasonic\":39306,\"Ġcis\":39307,\"olated\":39308,\"Ġdepletion\":39309,\"Rap\":39310,\"692\":39311,\"Ġinver\":39312,\"ĠFAQ\":39313,\"Ġmeanings\":39314,\"Ġbisc\":39315,\"ĠRage\":39316,\"Ġresear\":39317,\"Ep\":39318,\"Ġunbeat\":39319,\"ĠComponents\":39320,\"bub\":39321,\"ĠInterface\":39322,\"Isa\":39323,\"ĠArgon\":39324,\"Ġdenomin\":39325,\"Ġmammal\":39326,\"519\":39327,\"Ġsizing\":39328,\"imbabwe\":39329,\"ĠReplacement\":39330,\"Georgia\":39331,\"ĠParticipation\":39332,\"Ġmelts\":39333,\"Ġfemin\":39334,\"514\":39335,\"Ġseams\":39336,\"513\":39337,\"ĠGaw\":39338,\"Ġbrood\":39339,\"Mit\":39340,\"Ġannoyance\":39341,\"Ġequilibrium\":39342,\"Ġpatri\":39343,\"Ġ338\":39344,\"561\":39345,\"mentioned\":39346,\"ĠVotes\":39347,\"Ġintoler\":39348,\"Ġstrikingly\":39349,\"Ġ352\":39350,\"Ġskeletal\":39351,\"616\":39352,\"isition\":39353,\"Ġfluor\":39354,\"provided\":39355,\"517\":39356,\"Ġclimates\":39357,\"Ġsensibilities\":39358,\"ĠFrequ\":39359,\"onite\":39360,\"Kenn\":39361,\"Ġmagnets\":39362,\"assis\":39363,\"Ġprerequisite\":39364,\"Ġ>>>\":39365,\"Ġscree\":39366,\"google\":39367,\"ĠMirage\":39368,\"Ġevict\":39369,\"Peace\":39370,\"Ġmissionaries\":39371,\"617\":39372,\"748\":39373,\"rient\":39374,\"ĠSTATS\":39375,\"Bird\":39376,\"ĠShiva\":39377,\"ĠBlessing\":39378,\"Ġredundancy\":39379,\"Ġphotoc\":39380,\"ĠOnes\":39381,\"754\":39382,\"alert\":39383,\"urous\":39384,\"Ġfolklore\":39385,\"ĠIdeal\":39386,\"sheets\":39387,\"according\":39388,\"Hor\":39389,\"Cle\":39390,\"ĠEdit\":39391,\"671\":39392,\"olitics\":39393,\"ĠESC\":39394,\"Ġparaly\":39395,\"Ġorgasm\":39396,\"speak\":39397,\"Ã°\":39398,\"Ġsneaky\":39399,\"Ġswords\":39400,\"Ġfandom\":39401,\"776\":39402,\"ĠScandinav\":39403,\"Ġdarts\":39404,\"546\":39405,\"cerpt\":39406,\"ĠGifts\":39407,\"Ġmagically\":39408,\"phys\":39409,\"Laughs\":39410,\"ĠSour\":39411,\"ources\":39412,\"789\":39413,\"ĠEps\":39414,\"ository\":39415,\"uality\":39416,\"literally\":39417,\"Ġheavens\":39418,\"FUL\":39419,\"Ġie\":39420,\"ĠISP\":39421,\"Ġwink\":39422,\"Ġweeping\":39423,\"Ġdocking\":39424,\"ACY\":39425,\"iece\":39426,\"Ġsignifies\":39427,\"guns\":39428,\"Sac\":39429,\"Leave\":39430,\"imation\":39431,\"Ġunex\":39432,\"uctive\":39433,\"ĠFees\":39434,\"ĠPortable\":39435,\"ĠInvestigator\":39436,\"pill\":39437,\"rehensible\":39438,\"Ġpotency\":39439,\"803\":39440,\"Ġembodiment\":39441,\"overty\":39442,\"shine\":39443,\"REL\":39444,\"ĠMPH\":39445,\"ĠPatriarch\":39446,\"Ġaspirin\":39447,\"Ġrinse\":39448,\"Ġinher\":39449,\"ograms\":39450,\"ĠTHREE\":39451,\"qt\":39452,\"ipples\":39453,\"Ġdehuman\":39454,\"Ġslander\":39455,\"Ġflora\":39456,\"brow\":39457,\"Ġblindly\":39458,\"ectar\":39459,\"endish\":39460,\"Ġpigment\":39461,\"cellent\":39462,\"Ġyells\":39463,\"ĠLust\":39464,\"ĠAttacks\":39465,\"ĠSyndicate\":39466,\"otin\":39467,\"gress\":39468,\"reenshot\":39469,\"picking\":39470,\"Ġacupuncture\":39471,\"images\":39472,\"glas\":39473,\"ĠPolicies\":39474,\"Ġintestinal\":39475,\"1998\":39476,\"ULE\":39477,\"runs\":39478,\"ĠNing\":39479,\"ĠAsuka\":39480,\"ĠSkull\":39481,\"Motor\":39482,\"Ġdefund\":39483,\"Ġattaching\":39484,\"ĠBAD\":39485,\"Ġquarrel\":39486,\"Child\":39487,\"Dog\":39488,\"issan\":39489,\"irmation\":39490,\"Ġinline\":39491,\"ĠLover\":39492,\"Ġcyan\":39493,\"entary\":39494,\"awareness\":39495,\"Ġtraveller\":39496,\"âĢĲ\":39497,\"Ġbeasts\":39498,\"Ġboobs\":39499,\"ĠDeadly\":39500,\"Ġplutonium\":39501,\"ĠIntellectual\":39502,\"Jam\":39503,\"Ġconsec\":39504,\"663\":39505,\"ĠVegan\":39506,\"Ġ331\":39507,\"uron\":39508,\"ĠHEL\":39509,\"reements\":39510,\"Ġclone\":39511,\"Ġoutputs\":39512,\"oult\":39513,\"ĠDOM\":39514,\"ĠNX\":39515,\"Ze\":39516,\"909\":39517,\"brate\":39518,\"arations\":39519,\"ĠJindal\":39520,\"Ġbooklet\":39521,\"amide\":39522,\"Ġscraping\":39523,\"Sol\":39524,\"Date\":39525,\"796\":39526,\"Ġfulf\":39527,\"Ġskeletons\":39528,\"Ġsaints\":39529,\"ĠCurious\":39530,\"Han\":39531,\"Ġrepud\":39532,\"osity\":39533,\"ĠGravity\":39534,\"Ġmetadata\":39535,\"Focus\":39536,\"Ġthrott\":39537,\"ĠProgramming\":39538,\"Break\":39539,\"erver\":39540,\"Ġknight\":39541,\"yrs\":39542,\"Ġ376\":39543,\"sat\":39544,\"auto\":39545,\"Ġbroom\":39546,\"Ġnerd\":39547,\"Political\":39548,\"022\":39549,\"-------------\":39550,\"oulos\":39551,\"Ġrelic\":39552,\"Ġenactment\":39553,\"rious\":39554,\"ĠUniform\":39555,\"Teen\":39556,\"Colorado\":39557,\"055\":39558,\"Ġangled\":39559,\"bolt\":39560,\"ĠNeander\":39561,\"ĠDism\":39562,\"thanks\":39563,\"Polit\":39564,\"ersion\":39565,\"dro\":39566,\"install\":39567,\"Jake\":39568,\"hz\":39569,\"Ġ770\":39570,\"ĠCommodore\":39571,\"lahoma\":39572,\"Ġshri\":39573,\"Ġ....\":39574,\"Ġ7000\":39575,\"scope\":39576,\"Ġgenesis\":39577,\"Ġresided\":39578,\"ĠRivals\":39579,\"Ġsarcastic\":39580,\"Ġelicit\":39581,\"Ġmultiplied\":39582,\"uitous\":39583,\"Ġoppress\":39584,\"ĠPROT\":39585,\"Ġperpetually\":39586,\"ĠAdds\":39587,\"Ġbuffers\":39588,\"Ġmush\":39589,\"Ġ354\":39590,\"Ġpresc\":39591,\"ĠKung\":39592,\"682\":39593,\"Education\":39594,\"Ġpled\":39595,\"bsp\":39596,\"Ġconfessions\":39597,\"Ġrevocation\":39598,\"Micro\":39599,\"ĠHobby\":39600,\"ĠFatal\":39601,\"STAR\":39602,\"Ġworkspace\":39603,\"Ġtransformations\":39604,\"Ġportals\":39605,\"orned\":39606,\"figured\":39607,\"Ġlinguistic\":39608,\"pperc\":39609,\"ergus\":39610,\"Fel\":39611,\"ĠIntent\":39612,\"Ġ289\":39613,\"Ġdelinquent\":39614,\"Ġhandwriting\":39615,\"Ġvap\":39616,\"576\":39617,\"redited\":39618,\"736\":39619,\"Ġpsychiatry\":39620,\"GMT\":39621,\"Ġdisingen\":39622,\"Ġcrou\":39623,\"801\":39624,\"Ġmalice\":39625,\"itutes\":39626,\"ĠTiff\":39627,\"Ġstink\":39628,\"574\":39629,\"Story\":39630,\"Modern\":39631,\"ĠGly\":39632,\"Jamie\":39633,\"Ġadvertis\":39634,\"Ġhiber\":39635,\"Ġinfiltr\":39636,\"Ġelector\":39637,\"rovers\":39638,\"ĠFist\":39639,\"peed\":39640,\"ĠClassical\":39641,\"592\":39642,\"Ġconscientious\":39643,\"Surv\":39644,\"Text\":39645,\"ĠDrunk\":39646,\"Ġsupplemented\":39647,\"THIS\":39648,\"Ġtimid\":39649,\"Ġstacking\":39650,\"rites\":39651,\"Ġrebirth\":39652,\"Ġbalcon\":39653,\"Ġyawn\":39654,\"rosc\":39655,\"axy\":39656,\"Hart\":39657,\"ĠOPER\":39658,\"996\":39659,\"Ġrabid\":39660,\"ĠTick\":39661,\"Ġgrinning\":39662,\"elfth\":39663,\"045\":39664,\"Ġjustifies\":39665,\"ĠPirate\":39666,\"ĠSalary\":39667,\"Ġmirac\":39668,\"613\":39669,\"inately\":39670,\"ĠLIN\":39671,\"Ġinadequ\":39672,\"NPR\":39673,\"iddled\":39674,\"storage\":39675,\"Ġseventy\":39676,\"onet\":39677,\"Ġgastro\":39678,\"FIR\":39679,\"Ġrodent\":39680,\"629\":39681,\"ĠInclude\":39682,\"ĠCategories\":39683,\"ĠLiterally\":39684,\"Ġpree\":39685,\"aunder\":39686,\"ĠLOL\":39687,\"694\":39688,\"Ġindef\":39689,\"Ped\":39690,\"Ġmenstru\":39691,\"Ġcensored\":39692,\"Ġconfigure\":39693,\"Ġoverest\":39694,\"igenous\":39695,\"Ġrectangular\":39696,\"ĠMIS\":39697,\"ĠMub\":39698,\"Ġwitches\":39699,\"izards\":39700,\"Ġobnoxious\":39701,\"ĠLoll\":39702,\"ĠSEM\":39703,\"Ġspiritually\":39704,\"Ġcoer\":39705,\"Ġmodesty\":39706,\"butt\":39707,\"Ġedits\":39708,\"ĠShall\":39709,\"sburgh\":39710,\"Ġ1911\":39711,\"Rex\":39712,\"manent\":39713,\"ĠLithuan\":39714,\"Ġpointers\":39715,\"ativity\":39716,\"retch\":39717,\"Ġcascade\":39718,\"ĠRagnarok\":39719,\"ĠPainting\":39720,\"ĠATL\":39721,\"Born\":39722,\"Ġpadding\":39723,\"whel\":39724,\"Ġgrotesque\":39725,\"Ġtheorists\":39726,\"forcer\":39727,\"ĠJinn\":39728,\"Ġrenal\":39729,\"jamin\":39730,\"ĠFEC\":39731,\".\\\"\\\"\":39732,\"redict\":39733,\"Ġoppos\":39734,\"opted\":39735,\"Sel\":39736,\"ipment\":39737,\"752\":39738,\"792\":39739,\"Pur\":39740,\"Ġvolt\":39741,\"Ġflap\":39742,\"ĠCASE\":39743,\"Ġdyed\":39744,\"orers\":39745,\"becca\":39746,\",.\":39747,\"ifice\":39748,\"ubes\":39749,\"Ġyr\":39750,\"DW\":39751,\"Ġalteration\":39752,\"ĠSimpl\":39753,\"Ġunequiv\":39754,\"756\":39755,\"Dou\":39756,\"Ġplunder\":39757,\"Ġcommons\":39758,\"Ġstag\":39759,\"ĠZeal\":39760,\"avanaugh\":39761,\"Self\":39762,\"none\":39763,\"EGIN\":39764,\"Ġflashback\":39765,\"VAL\":39766,\"Gab\":39767,\"ĠCapture\":39768,\"ĠBrilliant\":39769,\"ĠDisk\":39770,\"ĠMood\":39771,\"Ġhaun\":39772,\"Ġrotting\":39773,\"ĠCobra\":39774,\"Ġpsychopath\":39775,\"Ġhelper\":39776,\"Starting\":39777,\"ĠOrbit\":39778,\"Ġcaf\":39779,\"Half\":39780,\"Volume\":39781,\"aptop\":39782,\"ĠSaga\":39783,\"azor\":39784,\"593\":39785,\"774\":39786,\"ĠCaucasian\":39787,\"compan\":39788,\"ĠVERY\":39789,\"GES\":39790,\"Ġvomit\":39791,\"Ġdispro\":39792,\"ĠMechanics\":39793,\"Ġ385\":39794,\"Ġmystical\":39795,\"AFTA\":39796,\"Ġbacter\":39797,\"availability\":39798,\"Ġhairc\":39799,\"ĠVec\":39800,\"rypt\":39801,\"Ġmanipulative\":39802,\"shell\":39803,\"ĠWeird\":39804,\"jab\":39805,\"ĠByr\":39806,\"Bow\":39807,\"uin\":39808,\"Ġquot\":39809,\"MX\":39810,\"Ġ960\":39811,\"ĠSharia\":39812,\"ĠWeapon\":39813,\"ĠPowerPoint\":39814,\"Ġstitching\":39815,\"Ġconstraint\":39816,\"âľ\":39817,\"ulic\":39818,\"597\":39819,\"omedical\":39820,\"ĠSupplemental\":39821,\"ĠSurve\":39822,\"ĠSubcommittee\":39823,\"ĠDarkness\":39824,\"Ġpython\":39825,\"LU\":39826,\"Ġ402\":39827,\"ĠQuan\":39828,\"ĠModerate\":39829,\"clusively\":39830,\"Ġextrap\":39831,\"Ġlatt\":39832,\"ĠSTUD\":39833,\"oslav\":39834,\"Ġsymb\":39835,\"battle\":39836,\"flash\":39837,\"ĠDeploy\":39838,\"Ġmicrobiome\":39839,\"Ġingested\":39840,\"Ġdistort\":39841,\"Ġassimil\":39842,\"Ġmobs\":39843,\"illet\":39844,\"Gre\":39845,\"Ġ294\":39846,\"Ġforbids\":39847,\"ĠEfficiency\":39848,\"ĠClan\":39849,\"763\":39850,\"Ġdragons\":39851,\"States\":39852,\"ĠMAKE\":39853,\"ĠBOOK\":39854,\"ĠRuns\":39855,\"ĠUX\":39856,\"EED\":39857,\"Whoever\":39858,\"ionics\":39859,\"worldly\":39860,\"ĠMermaid\":39861,\"Ġbenz\":39862,\"Info\":39863,\"523\":39864,\"Ġbiod\":39865,\"ĠPoison\":39866,\"ceivable\":39867,\"Services\":39868,\"ATIVE\":39869,\"ĠItem\":39870,\"Ġdisav\":39871,\"Ġheter\":39872,\"Ġasteroids\":39873,\"ĠWooden\":39874,\"Ġelectroly\":39875,\"assadors\":39876,\"nance\":39877,\"reflect\":39878,\"Ġattent\":39879,\"iphany\":39880,\"Ġspaceship\":39881,\"Ġbegg\":39882,\"algia\":39883,\"Ax\":39884,\"Ġidiosyncr\":39885,\"Ġinserting\":39886,\"ĠCSS\":39887,\"ĠLET\":39888,\"ĠStrikes\":39889,\"ossibly\":39890,\"Exp\":39891,\"Opp\":39892,\"dden\":39893,\"Ġplayable\":39894,\"ĠJM\":39895,\"Ġlawfully\":39896,\"ĠBlink\":39897,\"Ġ413\":39898,\"Ġoverpowered\":39899,\"Ġcommenter\":39900,\"Track\":39901,\"Ġmethyl\":39902,\"Ġfermented\":39903,\"Ġinvaders\":39904,\"ĠMoves\":39905,\"Ġcommunicates\":39906,\"rint\":39907,\"ĠTray\":39908,\"jug\":39909,\"Ġsuperf\":39910,\"ochet\":39911,\"ĠJelly\":39912,\"Ġestrogen\":39913,\"Dom\":39914,\"mix\":39915,\"Gun\":39916,\"ochemistry\":39917,\"952\":39918,\"Ġovere\":39919,\"ĠPlaintiff\":39920,\"ĠPilgrim\":39921,\"ĠSERVICES\":39922,\"ĠExpend\":39923,\"ĠFRE\":39924,\"Ġsmelling\":39925,\"ĠSpaces\":39926,\"bris\":39927,\"Mission\":39928,\"Ġarter\":39929,\"Ġautonom\":39930,\"Lisa\":39931,\"ĠPercent\":39932,\"NK\":39933,\"ĠLimits\":39934,\"Ġ356\":39935,\"Recent\":39936,\"ĠSiberian\":39937,\"etermin\":39938,\"nets\":39939,\"ĠSword\":39940,\"essee\":39941,\"Ùĩ\":39942,\"icycle\":39943,\"Ġparas\":39944,\"Ġrud\":39945,\"Ġscrib\":39946,\"Ġ1860\":39947,\"Shop\":39948,\"orld\":39949,\"Ġpept\":39950,\"ENSE\":39951,\"Ġanimations\":39952,\"ership\":39953,\"Search\":39954,\"ĠUSSR\":39955,\"washed\":39956,\"Ġpromulg\":39957,\"Ġdetainee\":39958,\"Ġunderest\":39959,\"ĠAppropri\":39960,\"Left\":39961,\"Update\":39962,\"Wallet\":39963,\"idently\":39964,\"ĠBicycle\":39965,\"Ġgorge\":39966,\"abyte\":39967,\"ĠMinecraft\":39968,\"rike\":39969,\"997\":39970,\"Tesla\":39971,\"Often\":39972,\"ĠTHESE\":39973,\"Ġregression\":39974,\"Hen\":39975,\"Ġsnippets\":39976,\"irds\":39977,\"Ġprinces\":39978,\"Ġwastes\":39979,\"ĠWond\":39980,\"itimate\":39981,\"ĠMongol\":39982,\"ĠkW\":39983,\"Ġidiots\":39984,\"Ġforeigner\":39985,\"Upon\":39986,\"Ġbackdoor\":39987,\"umph\":39988,\"ĠSquirrel\":39989,\"Ġtyped\":39990,\"Ġblockers\":39991,\"Vote\":39992,\"ĠPossibly\":39993,\"geist\":39994,\"ĠTRANS\":39995,\"Ġtitan\":39996,\"VG\":39997,\"Ġmicrobi\":39998,\"Ġinteracts\":39999,\"Ġmasc\":40000,\"Ġfinite\":40001,\"Ġcutoff\":40002,\"ornings\":40003,\"Ġprototyp\":40004,\"Ġcompan\":40005,\"mology\":40006,\"ĠBOX\":40007,\"Cre\":40008,\"Bot\":40009,\"grading\":40010,\"PET\":40011,\"Ġinsidious\":40012,\"ĠFranch\":40013,\"orians\":40014,\"ĠAUT\":40015,\"ĠCrush\":40016,\"589\":40017,\"question\":40018,\"anguard\":40019,\"Ġabsurdity\":40020,\"?\\\",\":40021,\"Hum\":40022,\"Ġliberalism\":40023,\"Ġpostwar\":40024,\"Gener\":40025,\"Personally\":40026,\"889\":40027,\"Bul\":40028,\"Ġlighthouse\":40029,\"Ġ291\":40030,\"VK\":40031,\"ĠExposure\":40032,\"Ġsubtract\":40033,\"ometime\":40034,\"arbon\":40035,\"ĠThieves\":40036,\"anus\":40037,\"ĠLibertarian\":40038,\"Raw\":40039,\"Ġsolvent\":40040,\"Ġcorros\":40041,\"Ġsignific\":40042,\"Ġscholarly\":40043,\"024\":40044,\"Ġfetish\":40045,\"Ġlarvae\":40046,\"Ġcatast\":40047,\"Ġtraitor\":40048,\"ijing\":40049,\"Demand\":40050,\"math\":40051,\"Ġconceivable\":40052,\"either\":40053,\"acl\":40054,\"ĠArrows\":40055,\"627\":40056,\"ĠFrankenstein\":40057,\"entious\":40058,\"Ġimitation\":40059,\"amn\":40060,\"ĠSTOP\":40061,\"Ġcripp\":40062,\"zag\":40063,\"ĠZed\":40064,\"797\":40065,\"Along\":40066,\"Ġwont\":40067,\"Ġfolds\":40068,\"Shar\":40069,\"ĠCommentary\":40070,\"ĠLibraries\":40071,\"ĠThunderbolt\":40072,\"itud\":40073,\"Toy\":40074,\"Ġincidentally\":40075,\"ĠResp\":40076,\"Ġordinarily\":40077,\"Ġvanish\":40078,\"acterial\":40079,\"Minnesota\":40080,\"rank\":40081,\"614\":40082,\"ĠExam\":40083,\"Got\":40084,\"Ġsnipers\":40085,\"ETHOD\":40086,\"dirty\":40087,\"igsaw\":40088,\"Obs\":40089,\"ĠAuthors\":40090,\"Ġillustrating\":40091,\"782\":40092,\"864\":40093,\"Ġblinded\":40094,\"transfer\":40095,\"Ġspawning\":40096,\"ĠDiary\":40097,\"ĠDNS\":40098,\"CG\":40099,\"someone\":40100,\"Ġcruc\":40101,\"Morgan\":40102,\"Learn\":40103,\"API\":40104,\"toc\":40105,\"STAT\":40106,\"ĠFlame\":40107,\"aganda\":40108,\"ĠBenef\":40109,\"stuff\":40110,\"SEA\":40111,\"Ġincest\":40112,\"Normally\":40113,\"ĠRU\":40114,\"Ġarsenic\":40115,\"isine\":40116,\"ĠTG\":40117,\"Type\":40118,\"regn\":40119,\"Cass\":40120,\"Touch\":40121,\"Site\":40122,\"Ġpict\":40123,\"Ġcorrupted\":40124,\"729\":40125,\"Ġnineteen\":40126,\"Ġparaph\":40127,\"Ġtavern\":40128,\"Ġretard\":40129,\"ĠKaf\":40130,\"Ġcolleg\":40131,\"bucks\":40132,\"imum\":40133,\"ĠCandle\":40134,\"ĠMisc\":40135,\"ĠAwesome\":40136,\"edited\":40137,\"ĠDN\":40138,\"otomy\":40139,\"Ġdisclaimer\":40140,\"798\":40141,\"ĠGoodbye\":40142,\"ucle\":40143,\"atom\":40144,\"Judge\":40145,\"cipl\":40146,\"Ġinexplicable\":40147,\"iddler\":40148,\"781\":40149,\"Ġempirical\":40150,\"Veter\":40151,\"Ġascert\":40152,\"Ġaest\":40153,\"Ġlaz\":40154,\"binary\":40155,\"Ġ358\":40156,\"contained\":40157,\"Ġmultipl\":40158,\"ocado\":40159,\"Ġdelusional\":40160,\"Ġaeros\":40161,\"udence\":40162,\"Ġjargon\":40163,\"estine\":40164,\"Ġarbitrarily\":40165,\"Ġprick\":40166,\"BACK\":40167,\"amines\":40168,\"Mess\":40169,\"Knowing\":40170,\"ublic\":40171,\"ĠWarfare\":40172,\"Ġsignify\":40173,\"Ġfragmentation\":40174,\"Tex\":40175,\"Ġnin\":40176,\"Ġdise\":40177,\"882\":40178,\"hospital\":40179,\"volent\":40180,\"Need\":40181,\"Ġinfer\":40182,\"Sony\":40183,\"783\":40184,\"YING\":40185,\"Ġinfinity\":40186,\"ĠFortress\":40187,\"Ġmustache\":40188,\"Ġcorresponds\":40189,\"DX\":40190,\"Ġunmarried\":40191,\"ĠCruel\":40192,\"Ġ1901\":40193,\"Ġappropri\":40194,\"ZI\":40195,\"Ġphosph\":40196,\"901\":40197,\"IFE\":40198,\"Ġ347\":40199,\"Ġconvoluted\":40200,\"ĠApost\":40201,\"htm\":40202,\"Ġilluminating\":40203,\"568\":40204,\"Ġassassinate\":40205,\"Ġparam\":40206,\"Ġimpractical\":40207,\"cedes\":40208,\"ĠProcedure\":40209,\"ĠMouth\":40210,\"Battle\":40211,\"Ġ451\":40212,\"Sand\":40213,\"Ġcontamin\":40214,\"Hour\":40215,\"Cell\":40216,\"BIL\":40217,\"Ġprecon\":40218,\"ĠScor\":40219,\"Ġconfig\":40220,\"ĠMuscle\":40221,\"Ġhive\":40222,\"Ġunderworld\":40223,\"plement\":40224,\"Ġpostage\":40225,\"Ġinterpersonal\":40226,\"Ġpierced\":40227,\"Ġcharms\":40228,\"oscopic\":40229,\"ASC\":40230,\"ĠDex\":40231,\"render\":40232,\"png\":40233,\"Ġcritiques\":40234,\"992\":40235,\"ĠVinyl\":40236,\"Bear\":40237,\"idia\":40238,\"ĠTemp\":40239,\"Ġcyn\":40240,\"ĠBCE\":40241,\"Ġpatriarchal\":40242,\"Ġantagonist\":40243,\"ĠGMO\":40244,\"Ġunnatural\":40245,\"Race\":40246,\"imeo\":40247,\"ĠUkrainians\":40248,\"Train\":40249,\"Ġ329\":40250,\"ritten\":40251,\"igil\":40252,\"Lin\":40253,\"alus\":40254,\"*****\":40255,\"olded\":40256,\"ĠPegasus\":40257,\"Bas\":40258,\"photos\":40259,\"Ġ820\":40260,\"Ġsquadron\":40261,\"ESE\":40262,\"Ġ373\":40263,\"Uk\":40264,\"Lost\":40265,\"Store\":40266,\"ĠScenes\":40267,\"JJ\":40268,\"Ġlick\":40269,\"Tyler\":40270,\"cius\":40271,\"lishing\":40272,\"ocl\":40273,\"Ġassoci\":40274,\"ensitivity\":40275,\"entanyl\":40276,\"Rum\":40277,\"Ġ443\":40278,\"onding\":40279,\"Ġpedals\":40280,\"ĠPsychological\":40281,\"Ġthro\":40282,\"Network\":40283,\"591\":40284,\"Pick\":40285,\"Ġchords\":40286,\"ĠHound\":40287,\"entials\":40288,\"faces\":40289,\"ĠYin\":40290,\"ugi\":40291,\"bows\":40292,\"ĠForms\":40293,\"886\":40294,\"Ox\":40295,\"Ġ351\":40296,\"Ġmating\":40297,\"Ġchirop\":40298,\"916\":40299,\"Ġexpend\":40300,\"Ġusefulness\":40301,\"Marvel\":40302,\"ĠStretch\":40303,\"omez\":40304,\"ĠJS\":40305,\"Hal\":40306,\"fle\":40307,\"ĠCountdown\":40308,\"ĠLH\":40309,\"assian\":40310,\"vd\":40311,\"ĠTranscript\":40312,\"ĠExtrem\":40313,\"idine\":40314,\"ustainable\":40315,\"ederal\":40316,\"ĠOwl\":40317,\"Ġcreed\":40318,\"ĠGrateful\":40319,\"Ġprenatal\":40320,\"________________________________\":40321,\"ĠElements\":40322,\"âĢ¦)\":40323,\"nesia\":40324,\"ARGET\":40325,\"Ġboredom\":40326,\"Ġdepictions\":40327,\"verbal\":40328,\"ĠeSports\":40329,\"Laura\":40330,\"ilage\":40331,\"ĠGalactic\":40332,\"Investigators\":40333,\"Ġscattering\":40334,\"instein\":40335,\"ĠExperiment\":40336,\"ĠRecre\":40337,\"Ġregul\":40338,\"Ġrelent\":40339,\"STE\":40340,\"Ġslicing\":40341,\"igans\":40342,\"raped\":40343,\"ĠDeter\":40344,\"Ġsmoker\":40345,\"ĠWikimedia\":40346,\"pages\":40347,\"Ted\":40348,\"713\":40349,\"Ġpuberty\":40350,\"Ġhars\":40351,\"ĠStarter\":40352,\"patch\":40353,\"leeve\":40354,\"Ġ346\":40355,\"ĠAccessories\":40356,\"ventions\":40357,\"ĠSTAND\":40358,\"ĠUrug\":40359,\"ĠOccupy\":40360,\"Ġbinds\":40361,\"ĠBubble\":40362,\"Ġincorporation\":40363,\"Ġstereotypical\":40364,\"Ġgor\":40365,\"987\":40366,\"Ġevils\":40367,\"tower\":40368,\"Ġastronomer\":40369,\"Ble\":40370,\"ĠNid\":40371,\"ĠWidow\":40372,\"Ġpaw\":40373,\"Ġinnoc\":40374,\"ĠOWN\":40375,\"Ġtofu\":40376,\"drops\":40377,\"ĠEval\":40378,\"693\":40379,\"Collins\":40380,\"penter\":40381,\"ĠNib\":40382,\"Ġsmokes\":40383,\"Ġ1850\":40384,\"Ġtechno\":40385,\"oooo\":40386,\"ĠUnic\":40387,\"ĠKirin\":40388,\"\\\":[\\\"\":40389,\"Ġincrements\":40390,\"989\":40391,\"oodoo\":40392,\"ĠCyborg\":40393,\"Ġcures\":40394,\"ĠOW\":40395,\"ĠAnnex\":40396,\"behavior\":40397,\"/-\":40398,\"Ġbuggy\":40399,\"onent\":40400,\"Bey\":40401,\"Ġsummarize\":40402,\"putable\":40403,\"Ġfri\":40404,\"Gi\":40405,\"urances\":40406,\"ĠAppalach\":40407,\"Ġhegemony\":40408,\"ĠOrigins\":40409,\"Ġconnectors\":40410,\"ĠAST\":40411,\"object\":40412,\"ĠSlay\":40413,\"Arm\":40414,\"oston\":40415,\"ĠEVEN\":40416,\"Ġprophecy\":40417,\"Bright\":40418,\"ĠVector\":40419,\"Marg\":40420,\"omical\":40421,\"Holy\":40422,\"ĠRPM\":40423,\"ĠReceiver\":40424,\"Ġtracts\":40425,\"boss\":40426,\"Ġblurry\":40427,\"aspx\":40428,\"DES\":40429,\"Ġcess\":40430,\"ĠAster\":40431,\"anything\":40432,\"levard\":40433,\"unciation\":40434,\"jong\":40435,\"Ġiv\":40436,\"Common\":40437,\"ĠDistance\":40438,\"imus\":40439,\"outheast\":40440,\"Ġcir\":40441,\"ĠCato\":40442,\"Ġinscribed\":40443,\"ersed\":40444,\"Ġanarchy\":40445,\"Ġplagiar\":40446,\"Ġthug\":40447,\"Actor\":40448,\"ĠTant\":40449,\"Researchers\":40450,\"remember\":40451,\"Ġitch\":40452,\"Ġrefill\":40453,\"Ġsucker\":40454,\"ĠWANT\":40455,\"RAG\":40456,\"rencies\":40457,\"ĠTape\":40458,\"Ġattaches\":40459,\"nb\":40460,\"Tan\":40461,\"Ġappend\":40462,\"Ġalas\":40463,\"951\":40464,\"panel\":40465,\"Climate\":40466,\"icrobial\":40467,\"Brandon\":40468,\"ĠFreud\":40469,\"Ġfungi\":40470,\"Ġcommenters\":40471,\"ĠDelicious\":40472,\"Ġhitherto\":40473,\"conv\":40474,\"Ġchemist\":40475,\"Ġdenominations\":40476,\"ĠBehavior\":40477,\"comed\":40478,\"ĠLantern\":40479,\"ĠFloating\":40480,\"magic\":40481,\"ĠBarbar\":40482,\"bender\":40483,\"iliar\":40484,\"unny\":40485,\"Ġretracted\":40486,\"atars\":40487,\"ĠLovely\":40488,\"Ġinfinitely\":40489,\"Ġhumili\":40490,\"Ġinterestingly\":40491,\"Ġmunicip\":40492,\"ĠPanic\":40493,\"Ġcomprehension\":40494,\"ĠMassacre\":40495,\"Ġpersuasion\":40496,\"enf\":40497,\"Ġcoded\":40498,\"higher\":40499,\"chart\":40500,\"umbered\":40501,\"ĠIndigo\":40502,\"Ġthinker\":40503,\"Ġgoof\":40504,\"ĠPetition\":40505,\"fascist\":40506,\"absor\":40507,\"Ġassay\":40508,\"ĠClassification\":40509,\"Ġhalluc\":40510,\"speech\":40511,\"issues\":40512,\"Ġinexper\":40513,\"ĠLibre\":40514,\"Ġsling\":40515,\"zech\":40516,\"Ġpouch\":40517,\"ĠOffense\":40518,\"ĠHF\":40519,\"Fight\":40520,\"026\":40521,\"ĠTrident\":40522,\"fm\":40523,\"Ġintox\":40524,\"Ġ465\":40525,\"colonial\":40526,\"ovies\":40527,\"794\":40528,\"Techn\":40529,\"undreds\":40530,\"Ġchildish\":40531,\"arenthood\":40532,\"ĠShade\":40533,\"Host\":40534,\"Ġdirectional\":40535,\"reader\":40536,\"rimp\":40537,\"ĠEater\":40538,\"prep\":40539,\"Ġmeas\":40540,\"Ġlatch\":40541,\"inant\":40542,\"nels\":40543,\"finished\":40544,\"application\":40545,\"Board\":40546,\"Ġfiller\":40547,\"ivably\":40548,\"CAST\":40549,\"Ġstereotyp\":40550,\"Ġwarranties\":40551,\"ĠProbe\":40552,\"Ġspontaneously\":40553,\"Ġtropes\":40554,\"Meg\":40555,\"ĠHandling\":40556,\"hemer\":40557,\"986\":40558,\"ĠSly\":40559,\"plates\":40560,\"Ġmolten\":40561,\"ĠHIT\":40562,\"strings\":40563,\"Ġcentrif\":40564,\"ĠENG\":40565,\"Indeed\":40566,\"Ġ429\":40567,\"Ġsly\":40568,\"Ġ490\":40569,\"Ġhordes\":40570,\"boot\":40571,\"691\":40572,\"ihara\":40573,\"Ġsubversive\":40574,\"Russell\":40575,\"aceous\":40576,\"wk\":40577,\"Ġreverence\":40578,\"Ġingenious\":40579,\"holiday\":40580,\"eligible\":40581,\"ĠTactical\":40582,\"978\":40583,\"herence\":40584,\"Ġgimm\":40585,\"Ġarchaic\":40586,\"Ġadam\":40587,\"Ġ297\":40588,\"Father\":40589,\"ĠLerner\":40590,\"Ġhesitated\":40591,\"Safety\":40592,\"Ġawakened\":40593,\"ueller\":40594,\"Ġextrater\":40595,\"Ġmummy\":40596,\"ĠBuddhism\":40597,\"Ġ359\":40598,\"Ġlegions\":40599,\"Ġprehistoric\":40600,\"ancouver\":40601,\"Ġmelancholy\":40602,\"ĠEnemy\":40603,\"ĠSyl\":40604,\"ĠRobo\":40605,\"verting\":40606,\"ĠBullets\":40607,\"essler\":40608,\"Ġmarvelous\":40609,\"ĠBened\":40610,\"Ġsavior\":40611,\"omever\":40612,\"Bee\":40613,\"Ġrapp\":40614,\"Ġpredomin\":40615,\"ĠScripture\":40616,\"Ġsnapshots\":40617,\"Ġunrem\":40618,\"Ġsquid\":40619,\"ĠBuddh\":40620,\"ĠSantorum\":40621,\"Internet\":40622,\"avoid\":40623,\"Ġunamb\":40624,\"Ġ296\":40625,\"Ġnexus\":40626,\"Ġinterchangeable\":40627,\"ockets\":40628,\"Ġfoll\":40629,\"ĠOPT\":40630,\"023\":40631,\"Â²\":40632,\"Ġhereditary\":40633,\"Ġvape\":40634,\"=\\\"\":40635,\"1996\":40636,\"Ø³\":40637,\"Emergency\":40638,\"Ġneb\":40639,\"Ġisot\":40640,\"Ġdiam\":40641,\"stairs\":40642,\"ĠAppendix\":40643,\"venient\":40644,\"Ġinvol\":40645,\"Ġtheorist\":40646,\"Ġconqu\":40647,\"Mich\":40648,\"ĠSort\":40649,\"antasy\":40650,\"dating\":40651,\"771\":40652,\"Ġape\":40653,\"Ġindemn\":40654,\"ween\":40655,\"Games\":40656,\"ascal\":40657,\"Muslims\":40658,\"Ġleaflets\":40659,\"Ġtraverse\":40660,\"Ġtransgress\":40661,\"Ġflushed\":40662,\"893\":40663,\"lasses\":40664,\"obos\":40665,\"ooming\":40666,\"Ġtou\":40667,\"mast\":40668,\"âģ\":40669,\"751\":40670,\"Either\":40671,\"Ġgrate\":40672,\"urgy\":40673,\"Ġendowed\":40674,\"ĠRasm\":40675,\"Nat\":40676,\"odka\":40677,\"olon\":40678,\"iants\":40679,\"Ġsensations\":40680,\"Ġsituational\":40681,\"pox\":40682,\"Figure\":40683,\"Ġslime\":40684,\"Ġ421\":40685,\"ollow\":40686,\"Ġanesthesia\":40687,\"adult\":40688,\"ĠPiece\":40689,\"994\":40690,\"ĠAnalog\":40691,\"Iv\":40692,\"flo\":40693,\"Ġdomest\":40694,\"Ġcabal\":40695,\"Ġgarg\":40696,\"Ġrabb\":40697,\"REC\":40698,\"ISTORY\":40699,\"Friend\":40700,\"Ġancestor\":40701,\"ĠLets\":40702,\"Ġelf\":40703,\"Ġlobb\":40704,\"ĠAdren\":40705,\"silver\":40706,\"astical\":40707,\"Ġstitch\":40708,\"028\":40709,\"Hug\":40710,\"Ġmoss\":40711,\"ompl\":40712,\"Ġunob\":40713,\"883\":40714,\"Ġcortex\":40715,\"olutely\":40716,\"052\":40717,\"Seattle\":40718,\"restling\":40719,\"endment\":40720,\"Ġ366\":40721,\"ventus\":40722,\"ĠRated\":40723,\"ĠClever\":40724,\"Ġcloak\":40725,\"phrase\":40726,\"flake\":40727,\"Ġphilosophies\":40728,\"784\":40729,\"Ġskulls\":40730,\"wake\":40731,\"oru\":40732,\"ĠACTION\":40733,\"Ġcomprom\":40734,\"ĠManufacturer\":40735,\"ĠImprove\":40736,\"Ns\":40737,\"ĠRevenge\":40738,\"lords\":40739,\"Ġ417\":40740,\"iddles\":40741,\"Ġcondesc\":40742,\"tiny\":40743,\"Ġchloride\":40744,\"greg\":40745,\"ĠREST\":40746,\"subject\":40747,\"Ġundes\":40748,\"ftime\":40749,\"Ġbottleneck\":40750,\"ĠZombie\":40751,\"Ġhabitable\":40752,\"Ġcigars\":40753,\"Ġenlarg\":40754,\"icester\":40755,\"ðĿ\":40756,\"regulation\":40757,\"arters\":40758,\"Ġformulations\":40759,\"Ġadhesive\":40760,\"Ġ344\":40761,\"pod\":40762,\"etitive\":40763,\"Ġcontinuum\":40764,\"aghd\":40765,\"Ġ701\":40766,\"Ġdisband\":40767,\"Tu\":40768,\"Ġcivilisation\":40769,\"ĠPCI\":40770,\"Ġcrooked\":40771,\"ammy\":40772,\"Ġbrim\":40773,\"Jr\":40774,\"ĠBunker\":40775,\"plot\":40776,\"Ġwielded\":40777,\"Ġcaricature\":40778,\"ĠInfinite\":40779,\"piracy\":40780,\"aretz\":40781,\"Ġstares\":40782,\"incinnati\":40783,\"agents\":40784,\"ĠObamaCare\":40785,\"asuring\":40786,\"ansion\":40787,\"Ġastonished\":40788,\"iovascular\":40789,\"Bio\":40790,\"Ġadvisable\":40791,\"Ġsender\":40792,\"887\":40793,\"Led\":40794,\"DN\":40795,\"Ġaggregation\":40796,\"ĠInnocent\":40797,\"ĠTransactions\":40798,\"worms\":40799,\"ĠWorm\":40800,\"Ġ363\":40801,\"ĠBiblical\":40802,\"rared\":40803,\"Ġgazing\":40804,\"chant\":40805,\"Ġsubordinates\":40806,\"1600\":40807,\"actually\":40808,\"olition\":40809,\"ĠRTX\":40810,\"ĠPyramid\":40811,\"alph\":40812,\"ĠFPS\":40813,\"Ġerrone\":40814,\"ĠLR\":40815,\"Scientists\":40816,\"Ġincons\":40817,\"Ġbrittle\":40818,\"027\":40819,\"ĠBowser\":40820,\"Rub\":40821,\"links\":40822,\"ĠWik\":40823,\"ussion\":40824,\"Marsh\":40825,\"resents\":40826,\"Clean\":40827,\"Ġbrute\":40828,\"ĠInventory\":40829,\"1100\":40830,\"ĠATK\":40831,\"793\":40832,\"Ġcaveats\":40833,\"ĠKnot\":40834,\"IRT\":40835,\"ĠCanad\":40836,\"isma\":40837,\"entin\":40838,\"Own\":40839,\"Ġ455\":40840,\"Ġlesions\":40841,\"ĠAres\":40842,\"ĠKali\":40843,\"Ġpaws\":40844,\"Auto\":40845,\"Ġdiscrim\":40846,\"044\":40847,\"ĠCOUN\":40848,\"Ġ1905\":40849,\"Ġexperien\":40850,\"Ġ406\":40851,\"achelor\":40852,\"Ġscarcely\":40853,\"Ġsynchronized\":40854,\"Rat\":40855,\"Blake\":40856,\"Ġrewriting\":40857,\"Ġcannons\":40858,\"stem\":40859,\"Apparently\":40860,\"Ġleveling\":40861,\"?]\":40862,\"Ġfins\":40863,\"ĠTone\":40864,\"ogether\":40865,\"Sound\":40866,\"Ġmicrosc\":40867,\"ĠAsylum\":40868,\"Ġindividuality\":40869,\"Ġ432\":40870,\"lease\":40871,\"Chuck\":40872,\"Ġhating\":40873,\"Ġleftists\":40874,\"ĠPersonality\":40875,\"ĠBundle\":40876,\"Dutch\":40877,\"Ġtransformer\":40878,\"iami\":40879,\"ĠTradition\":40880,\"ĠRecipes\":40881,\"Ġdiscour\":40882,\"Viol\":40883,\"Ext\":40884,\"ĠOliv\":40885,\"ashington\":40886,\"Ġmillennia\":40887,\"Ġpsychiatrists\":40888,\"ĠTrilogy\":40889,\"inction\":40890,\"Ġdisliked\":40891,\"088\":40892,\"954\":40893,\"Ġoverloaded\":40894,\"Ġopium\":40895,\"acus\":40896,\"resources\":40897,\"mud\":40898,\"ometry\":40899,\"Hit\":40900,\"Ġguild\":40901,\"Ġabyss\":40902,\"884\":40903,\"ensity\":40904,\"ĠDifference\":40905,\"Electric\":40906,\"authent\":40907,\"Ġdownloadable\":40908,\"ellar\":40909,\"ĠSavior\":40910,\"ĠFRI\":40911,\"Ġ445\":40912,\"Ġincidental\":40913,\"Ġanalogue\":40914,\"ounters\":40915,\"ĠBuilder\":40916,\"Ġnarration\":40917,\"ategor\":40918,\"raise\":40919,\"Ġindoctr\":40920,\"Aren\":40921,\"Ġbaptism\":40922,\"Ġobe\":40923,\"Ġtubing\":40924,\"apsed\":40925,\"Fortunately\":40926,\"gered\":40927,\"Pict\":40928,\"Ġmastering\":40929,\"ĠHIM\":40930,\"ĠObesity\":40931,\"Ġornament\":40932,\"advant\":40933,\"ĠCous\":40934,\"032\":40935,\"cells\":40936,\"Ġpreclude\":40937,\"Ġanecdote\":40938,\"Ġpatriarchy\":40939,\"ĠSending\":40940,\"Pie\":40941,\"Ġdepressive\":40942,\"ĠEnds\":40943,\"712\":40944,\"zos\":40945,\"icka\":40946,\"Ġ1906\":40947,\"Anti\":40948,\"vana\":40949,\"ĠRestrict\":40950,\"Ġprotr\":40951,\"Ġusername\":40952,\"Ġparach\":40953,\"1997\":40954,\"imental\":40955,\"rower\":40956,\"carb\":40957,\"033\":40958,\"Ġobligatory\":40959,\"Ġwillful\":40960,\"Ġsnail\":40961,\"json\":40962,\"izarre\":40963,\"Ġmiscar\":40964,\"Ġdopamine\":40965,\"Ð»\":40966,\"Ġapplic\":40967,\"Ġnervously\":40968,\"YY\":40969,\"alez\":40970,\"ĠSoviets\":40971,\"ĠMister\":40972,\"Ġcrates\":40973,\"Ġheavenly\":40974,\"Ġdoct\":40975,\"048\":40976,\"Ġ2400\":40977,\"ivia\":40978,\"adies\":40979,\"Phone\":40980,\"asks\":40981,\"Ġperenn\":40982,\"Ġcomposing\":40983,\"Ġraiding\":40984,\"requent\":40985,\"ibli\":40986,\"ĠFeedback\":40987,\"cellaneous\":40988,\"ĠContracts\":40989,\"ĠCasting\":40990,\"vim\":40991,\"Cut\":40992,\"Ġabbrevi\":40993,\"Ġintest\":40994,\"ricted\":40995,\"969\":40996,\"nostic\":40997,\"Ġinverted\":40998,\"ĠEG\":40999,\"aiden\":41000,\"ĠClaud\":41001,\"ĠiP\":41002,\"urized\":41003,\"Emily\":41004,\"Ġ353\":41005,\"Ġ((\":41006,\"ammad\":41007,\"Reb\":41008,\"plom\":41009,\"YES\":41010,\"connection\":41011,\"ĠWra\":41012,\"ĠMerch\":41013,\"Ġether\":41014,\"Elizabeth\":41015,\"Chip\":41016,\"relevant\":41017,\"URA\":41018,\"Ġantioxidant\":41019,\"ĠChron\":41020,\"Ġtheological\":41021,\"HCR\":41022,\"ruits\":41023,\"Body\":41024,\"enezuel\":41025,\"Few\":41026,\"adder\":41027,\"Ġinducing\":41028,\"ĠDarth\":41029,\"Ġimplicitly\":41030,\"Ġoverfl\":41031,\"Ġrelics\":41032,\"Must\":41033,\"ĠAnswers\":41034,\"Ġretina\":41035,\"ĠSlowly\":41036,\"ĠShib\":41037,\"software\":41038,\"Ġ\\\"\\\"\":41039,\"hack\":41040,\"Apart\":41041,\"told\":41042,\"Ger\":41043,\"Civil\":41044,\"problem\":41045,\"Ġslang\":41046,\"Ġtactile\":41047,\"Ġtabl\":41048,\"ĠAscension\":41049,\"Ġhumankind\":41050,\"Howard\":41051,\"rescent\":41052,\"ĠReleases\":41053,\"arijuana\":41054,\"Christopher\":41055,\"ĠWarden\":41056,\"blogspot\":41057,\"ĠVari\":41058,\"idency\":41059,\"ĠHandler\":41060,\"Round\":41061,\"MJ\":41062,\"Ġrhyth\":41063,\"Tai\":41064,\"terson\":41065,\"Ġ,\\\"\":41066,\"portation\":41067,\"ĠOrbital\":41068,\"Ġfantas\":41069,\"Ġattribut\":41070,\"Ġdiagram\":41071,\"atech\":41072,\"1992\":41073,\"ibl\":41074,\"Woman\":41075,\"ternally\":41076,\"Days\":41077,\"Ġdebunk\":41078,\"ĠPhant\":41079,\"ĠOath\":41080,\"sharp\":41081,\"Ġclaws\":41082,\"Lots\":41083,\"Incre\":41084,\"Aff\":41085,\"hooting\":41086,\"rect\":41087,\"Ġaltru\":41088,\"Ġwors\":41089,\"Ġtho\":41090,\"Ġ349\":41091,\"clusions\":41092,\"Ġpseudonym\":41093,\"Bec\":41094,\"Ġphosphorus\":41095,\"ivic\":41096,\"Ġ348\":41097,\"otent\":41098,\"Ġub\":41099,\"Ġcoales\":41100,\"regate\":41101,\"Ġ1870\":41102,\"Ġglide\":41103,\"treated\":41104,\"ĠSymb\":41105,\"Ġenchant\":41106,\"Besides\":41107,\"stocks\":41108,\"Ġ388\":41109,\"--------------\":41110,\"interpret\":41111,\"ouple\":41112,\"Ġdrawback\":41113,\"ĠRevised\":41114,\"Ġanat\":41115,\"Ġpsychosis\":41116,\"Ø¨\":41117,\"Ġdiffuse\":41118,\"Ġaffidav\":41119,\"elve\":41120,\"amination\":41121,\"ĠTackle\":41122,\"hunter\":41123,\"env\":41124,\"Ġchests\":41125,\"Ġsubter\":41126,\"Ġconquest\":41127,\"Ġfidelity\":41128,\"Ġinfringing\":41129,\"opathic\":41130,\"ĠGrip\":41131,\"ĠKeyboard\":41132,\"Ġobjectionable\":41133,\"Ġmetabol\":41134,\"ĠGÃ¶\":41135,\"Room\":41136,\"...)\":41137,\"KEN\":41138,\"assic\":41139,\"Ġgeop\":41140,\"Tro\":41141,\"Ġcursing\":41142,\"Ġdile\":41143,\"Ġultraviolet\":41144,\"inarily\":41145,\"Ġdistilled\":41146,\"sect\":41147,\"ĠShooter\":41148,\"uckles\":41149,\"Ġdistortions\":41150,\"Map\":41151,\"Doctor\":41152,\"Ġinstalls\":41153,\"oire\":41154,\"Ġstarch\":41155,\"ociation\":41156,\"Lev\":41157,\"Ġscripture\":41158,\"Ġsalient\":41159,\"ilitating\":41160,\"wb\":41161,\"ĠSov\":41162,\"ĠDamn\":41163,\"Grey\":41164,\"Ġ980\":41165,\"Ġjung\":41166,\"Ġlicking\":41167,\"029\":41168,\"ĠDian\":41169,\"ĠBabylon\":41170,\"Ðº\":41171,\"ĠRomantic\":41172,\"Ġguesses\":41173,\"ĠFren\":41174,\"Generally\":41175,\"ultural\":41176,\"istence\":41177,\"Ġiniti\":41178,\"Ġ341\":41179,\"ĠSlave\":41180,\"ultan\":41181,\"ĠTrash\":41182,\"ĠEmpty\":41183,\"ĠHundred\":41184,\"ĠDirective\":41185,\"Anderson\":41186,\"Advertisement\":41187,\"RH\":41188,\"ĠOo\":41189,\"ĠHik\":41190,\"peg\":41191,\"Sup\":41192,\"ĠXT\":41193,\"Ġencrypt\":41194,\"selage\":41195,\"ĠThrone\":41196,\"Ġconsecut\":41197,\"Li\":41198,\"ĠVirus\":41199,\"ĠCookies\":41200,\"SHIP\":41201,\"Ġflavorful\":41202,\"odynamics\":41203,\"animal\":41204,\"spread\":41205,\"ĠIPCC\":41206,\"jobs\":41207,\"ernand\":41208,\"ĠHaunted\":41209,\"Ġintolerable\":41210,\"ĠLAR\":41211,\"ixtape\":41212,\"Ġneur\":41213,\"Ġcausal\":41214,\"ĠPsychiatry\":41215,\"ĠVim\":41216,\"Ġgenomic\":41217,\"duration\":41218,\"ĠUsername\":41219,\"ategy\":41220,\"Ġunic\":41221,\"ĠKILL\":41222,\"blooded\":41223,\"Ġcaucuses\":41224,\"ĠPOLITICO\":41225,\"Spanish\":41226,\"Ġobedience\":41227,\"Ġinconven\":41228,\"MAT\":41229,\"Ġbends\":41230,\"ĠImprovements\":41231,\"Ġrelig\":41232,\"ĠForth\":41233,\"ĠLumia\":41234,\"uces\":41235,\"Ġunim\":41236,\"ĠStatistical\":41237,\"kb\":41238,\"auntlet\":41239,\"ĠDisco\":41240,\"ĠInstruction\":41241,\"ooo\":41242,\"ĠDictionary\":41243,\"culated\":41244,\"Adv\":41245,\"ĠAvatar\":41246,\"ictional\":41247,\"Ġcentr\":41248,\"ifles\":41249,\"orks\":41250,\"skill\":41251,\"Ġlatex\":41252,\"ĠPagan\":41253,\"Ġdevast\":41254,\"Ġprol\":41255,\"896\":41256,\"Product\":41257,\"968\":41258,\"Ġfrench\":41259,\"083\":41260,\"ĠCluster\":41261,\"cloth\":41262,\"ĠFilter\":41263,\"ĠDisorders\":41264,\"etimes\":41265,\"Ġinstinctively\":41266,\"ĠBritann\":41267,\"Ġaft\":41268,\"ĠVict\":41269,\"Ġâĺħ\":41270,\"Ġperverse\":41271,\"Ġcontraceptives\":41272,\"ĠHannibal\":41273,\"escap\":41274,\"ĠApostle\":41275,\"ĠXiao\":41276,\"ĠMagnum\":41277,\"Ġphosphate\":41278,\"Ġ399\":41279,\"utable\":41280,\"Ġsten\":41281,\"Ġwearer\":41282,\"Ġsmug\":41283,\"ĠInfluence\":41284,\"Ġ384\":41285,\"Truth\":41286,\"struction\":41287,\"Ġmaniac\":41288,\"ĠMagnetic\":41289,\"ousands\":41290,\"Ġsemen\":41291,\"dir\":41292,\"ĠTornado\":41293,\"Ġexplos\":41294,\"1995\":41295,\"Xi\":41296,\"Steel\":41297,\"057\":41298,\"Barn\":41299,\"Fan\":41300,\"ĠChatt\":41301,\"Chem\":41302,\"ĠFold\":41303,\"bees\":41304,\"1080\":41305,\"ĠMaze\":41306,\"ierre\":41307,\"oeuv\":41308,\"Cand\":41309,\"odium\":41310,\"mmm\":41311,\"ereo\":41312,\"Ġreactionary\":41313,\"Ġacidic\":41314,\"ĠRemoval\":41315,\"Ġnont\":41316,\"031\":41317,\"ĠTerminator\":41318,\"ĠVendor\":41319,\"enemy\":41320,\"Ġreconstructed\":41321,\"ĠGalileo\":41322,\"Ġtesters\":41323,\"albeit\":41324,\"uminium\":41325,\"Ġrite\":41326,\"ĠInput\":41327,\"committee\":41328,\"Ġjour\":41329,\"gements\":41330,\"Ġgerm\":41331,\"Dick\":41332,\"ĠRequirements\":41333,\"omsday\":41334,\"Î\":41335,\"ISSION\":41336,\"Ġmolded\":41337,\"Ġrye\":41338,\"Attorney\":41339,\"population\":41340,\"Ġrepet\":41341,\"Sync\":41342,\"breaks\":41343,\"Ġbanished\":41344,\"Ġraspberry\":41345,\"Ġammo\":41346,\"Ġorthodox\":41347,\"Ġwebcam\":41348,\"ĠAsc\":41349,\"vl\":41350,\"1989\":41351,\"Ġdiscipl\":41352,\"Ġmoreover\":41353,\"Ġexplodes\":41354,\"1960\":41355,\"Ġpropositions\":41356,\"Protect\":41357,\"Ġsexes\":41358,\"physical\":41359,\"ĠAthena\":41360,\"ocent\":41361,\"ĠGothic\":41362,\"ĠRacial\":41363,\"istani\":41364,\"Ġhelium\":41365,\"ĠPresumably\":41366,\"Ġperman\":41367,\"becue\":41368,\"ĠHW\":41369,\"rued\":41370,\"ĠCNS\":41371,\"DEP\":41372,\"ĠManifest\":41373,\"2500\":41374,\"ĠMyst\":41375,\"Economic\":41376,\"Prot\":41377,\"Ġledge\":41378,\"Ġimitate\":41379,\"ĠTotally\":41380,\"ĠBeaut\":41381,\"OIL\":41382,\"Ġ1440\":41383,\"Moscow\":41384,\"ĠSets\":41385,\"merga\":41386,\"Ġlesbians\":41387,\"Walker\":41388,\"Move\":41389,\"ĠSOM\":41390,\"ĠPsy\":41391,\"strument\":41392,\"Ġiter\":41393,\"ĠTosh\":41394,\"oola\":41395,\"ĠAntiqu\":41396,\"ĠShining\":41397,\"Ġobservational\":41398,\"VW\":41399,\"rophe\":41400,\"034\":41401,\"Ġcontiguous\":41402,\"Ġstarve\":41403,\"sure\":41404,\"Ġnegate\":41405,\"Ġmindless\":41406,\"tf\":41407,\"Ġdownwards\":41408,\"046\":41409,\"riors\":41410,\"Ġreverted\":41411,\"ĠAthe\":41412,\"Bra\":41413,\"eah\":41414,\"Rachel\":41415,\"Hung\":41416,\"Join\":41417,\"ĠRaces\":41418,\"Ġmutant\":41419,\"Ġuncond\":41420,\"Ġusability\":41421,\"NESS\":41422,\"haust\":41423,\"036\":41424,\"Ġobscurity\":41425,\"Ġimperialism\":41426,\"Ġemitting\":41427,\"Ġideologically\":41428,\"ĠIro\":41429,\"erva\":41430,\"ĠIzzy\":41431,\"ĠLevels\":41432,\"onym\":41433,\"ĠConspiracy\":41434,\"ĠSapphire\":41435,\"Ul\":41436,\"Ġhuh\":41437,\"ochem\":41438,\"Ġbehaves\":41439,\"ĠMesh\":41440,\"Ark\":41441,\"Ġvec\":41442,\"ĠActions\":41443,\"Ġdistinguishing\":41444,\"ĠTsarnaev\":41445,\"ĠEndurance\":41446,\"ederation\":41447,\"itant\":41448,\"Ġstreetcar\":41449,\"041\":41450,\"ĠAval\":41451,\"ĠCompanion\":41452,\"ĠCartoon\":41453,\"Ġcalculus\":41454,\"993\":41455,\"eq\":41456,\"ĠVanilla\":41457,\"MAC\":41458,\"wolves\":41459,\"fg\":41460,\"Ġfermentation\":41461,\"Ġinformants\":41462,\"Ġsudo\":41463,\"Ġperipher\":41464,\"Ġindign\":41465,\"parts\":41466,\"detail\":41467,\"femin\":41468,\"blade\":41469,\"Ġinserts\":41470,\"Ġoffsets\":41471,\"Ġantidepressants\":41472,\"Ġphr\":41473,\"Ġresultant\":41474,\"biology\":41475,\"Ġacquies\":41476,\"UFF\":41477,\"****************\":41478,\"ĠPenalty\":41479,\"Ġrever\":41480,\"heric\":41481,\"ĠShadows\":41482,\"command\":41483,\"Ġreprint\":41484,\"089\":41485,\"empty\":41486,\"ĠTAG\":41487,\"stim\":41488,\"FK\":41489,\"Ġkins\":41490,\"uggle\":41491,\"imura\":41492,\"wit\":41493,\"Kill\":41494,\"Beck\":41495,\"Ocean\":41496,\"Ġlabyrinth\":41497,\"ĠNorse\":41498,\"IENCE\":41499,\"Ġ+++\":41500,\"DoS\":41501,\"gm\":41502,\"Ġbarbar\":41503,\"ĠCeres\":41504,\"Ġhashing\":41505,\"eworthy\":41506,\"Ġrecite\":41507,\"Ġelectrodes\":41508,\"Ġconformity\":41509,\"response\":41510,\"olate\":41511,\"Ġ357\":41512,\"Snap\":41513,\"Crime\":41514,\"Ġpointer\":41515,\"ĠTIT\":41516,\"Ġdistinctions\":41517,\"Ġ427\":41518,\"ĠÙĪ\":41519,\"abases\":41520,\"Mars\":41521,\"ĠSpiritual\":41522,\"Ġimpuls\":41523,\"Philadelphia\":41524,\"1994\":41525,\"Ġcunning\":41526,\"Ġfram\":41527,\"Ġinco\":41528,\"Ġomnip\":41529,\"imize\":41530,\"ervative\":41531,\"Gy\":41532,\"Drug\":41533,\"Ġcarniv\":41534,\"ĠSailor\":41535,\"download\":41536,\"ĠBeetle\":41537,\"ĠEarthqu\":41538,\"izontal\":41539,\"Alan\":41540,\"Nice\":41541,\"Prior\":41542,\"MAG\":41543,\"Ġautobi\":41544,\"ĠBrill\":41545,\"Ġpredominant\":41546,\"ĠMessiah\":41547,\"REM\":41548,\"ĠSlip\":41549,\"ĠWebs\":41550,\"ademic\":41551,\"<\":41552,\"ĠVessel\":41553,\"vari\":41554,\"Code\":41555,\"Ġbeetle\":41556,\"projects\":41557,\"BAT\":41558,\"Ġpsychotic\":41559,\"Ġunderside\":41560,\"Ġrefute\":41561,\"Considering\":41562,\"kees\":41563,\"wd\":41564,\"priority\":41565,\"Ġtwentieth\":41566,\"Ġatheist\":41567,\"amina\":41568,\"Ġeuphem\":41569,\"Ġtripod\":41570,\"ĠTrayvon\":41571,\"ĠNON\":41572,\"2200\":41573,\"ĠNPC\":41574,\"ependence\":41575,\"ĠMHz\":41576,\"ĠBung\":41577,\"Ġpane\":41578,\"Ġaboriginal\":41579,\"ĠPLUS\":41580,\"igers\":41581,\"ĠSexy\":41582,\"MF\":41583,\"Chall\":41584,\"Ay\":41585,\"ilingual\":41586,\"adj\":41587,\"Ġfrown\":41588,\"successful\":41589,\"stack\":41590,\"Ġic\":41591,\"ĠSeah\":41592,\"Ġconsequ\":41593,\"bugs\":41594,\"ĠScand\":41595,\"ĠCurve\":41596,\"Nob\":41597,\"ĠHoo\":41598,\"ĠKissinger\":41599,\"ĠTimeline\":41600,\"Ġmt\":41601,\"Description\":41602,\"YP\":41603,\"ĠInstallation\":41604,\"levision\":41605,\"Ġanthropology\":41606,\"itzerland\":41607,\"iaries\":41608,\"kward\":41609,\"robat\":41610,\"Ġcarbohydrate\":41611,\"Phot\":41612,\"Ð¾Ð\":41613,\"ĠSQL\":41614,\"Disc\":41615,\"Ġdataset\":41616,\"ynski\":41617,\"Ġfiat\":41618,\"ĠDres\":41619,\"ĠFavor\":41620,\"ĠHalls\":41621,\"Alt\":41622,\"PART\":41623,\"Spider\":41624,\"Ġdisabling\":41625,\"RG\":41626,\"Ward\":41627,\"aturation\":41628,\"Ġwillfully\":41629,\"Ġlockout\":41630,\"ĠShutdown\":41631,\"956\":41632,\"Ġcommunists\":41633,\"Against\":41634,\"Ore\":41635,\"ĠRik\":41636,\"ĠASD\":41637,\"ĠOnion\":41638,\"Ġparticulars\":41639,\"Analy\":41640,\"checked\":41641,\"selected\":41642,\"romy\":41643,\"ĠAkira\":41644,\"Ġcongr\":41645,\"Choice\":41646,\"Ġbos\":41647,\"organisms\":41648,\"Ġfrowned\":41649,\"Tok\":41650,\"Bir\":41651,\"ĠScrib\":41652,\"Ġrealms\":41653,\"Ġcoercive\":41654,\"1993\":41655,\"021\":41656,\"âĢĵâĢĵ\":41657,\"athetic\":41658,\"rior\":41659,\"Ġfolly\":41660,\"ĠAMERICA\":41661,\"Ġcassette\":41662,\"953\":41663,\"Ġabsorbs\":41664,\"043\":41665,\"quad\":41666,\"''.\":41667,\"ĠExtract\":41668,\"Ġ424\":41669,\"Whit\":41670,\"Dun\":41671,\"Ġexerted\":41672,\"Ġbrethren\":41673,\"ĠChronicles\":41674,\"eric\":41675,\"Mot\":41676,\"Ġendings\":41677,\"piration\":41678,\"Ġpredetermined\":41679,\"ĠAirl\":41680,\"Ġgasp\":41681,\"Ġ367\":41682,\"Ġexclaim\":41683,\"cation\":41684,\"sort\":41685,\"idden\":41686,\"missive\":41687,\"Ø¹\":41688,\"oice\":41689,\"same\":41690,\"Ott\":41691,\"Ġscatter\":41692,\"Flight\":41693,\"ĠTOD\":41694,\"Stra\":41695,\"amia\":41696,\"IZE\":41697,\"Ġcompressor\":41698,\"ixels\":41699,\"lethal\":41700,\"ĠExperimental\":41701,\"Ing\":41702,\"knife\":41703,\"Ġvanishing\":41704,\"ĠRequired\":41705,\"Stat\":41706,\"ĠPlex\":41707,\"spection\":41708,\"ĠBakr\":41709,\"Amazing\":41710,\"Ġbreaths\":41711,\"rots\":41712,\"OSP\":41713,\"Ġ840\":41714,\"Wars\":41715,\"OGR\":41716,\"Ġ372\":41717,\"ĠKhe\":41718,\"inous\":41719,\"lightly\":41720,\"ĠRounds\":41721,\"Ġrefinement\":41722,\"property\":41723,\"Ġmetaph\":41724,\"oultry\":41725,\"istor\":41726,\"Ġintestine\":41727,\"eus\":41728,\"ĠWilhelm\":41729,\"ĠBane\":41730,\"emption\":41731,\"oubtedly\":41732,\"ĠVirtue\":41733,\"'),\":41734,\"Ħ¢\":41735,\"Ġappar\":41736,\"ĠTranslation\":41737,\"Quite\":41738,\"Ġphysicists\":41739,\"Ġpriesthood\":41740,\"Ġallowable\":41741,\"Saint\":41742,\"OSED\":41743,\"bind\":41744,\"Ġtorches\":41745,\"osexual\":41746,\"Cruz\":41747,\"ertility\":41748,\"ĠAES\":41749,\"Ġascended\":41750,\"Ġmuzzle\":41751,\"Ġelectors\":41752,\"ĠKrug\":41753,\"Ġcc\":41754,\"classic\":41755,\"ĠMace\":41756,\"Å«\":41757,\"ĠâĢ¦\\\"\":41758,\"ĠTEST\":41759,\"gomery\":41760,\"Person\":41761,\"Ġtranslations\":41762,\"ĠDys\":41763,\"ĠConsent\":41764,\"Ġ361\":41765,\"alos\":41766,\"Ġallerg\":41767,\"ĠWast\":41768,\"ĠChecks\":41769,\"cerning\":41770,\"Ġlizard\":41771,\"Ġrevolutions\":41772,\"Ġtether\":41773,\"Ġminimized\":41774,\"ĠReverse\":41775,\"itely\":41776,\"iguous\":41777,\"athing\":41778,\"Flow\":41779,\"Moving\":41780,\"Ġ409\":41781,\"047\":41782,\"Ġsnug\":41783,\"Nich\":41784,\"Ġcartridge\":41785,\"YL\":41786,\"Ġforwarding\":41787,\"umerous\":41788,\"ĠAbedin\":41789,\"iolet\":41790,\"tick\":41791,\"ĠTransform\":41792,\"Grant\":41793,\"Ġsubtitles\":41794,\"ĠEmin\":41795,\"ghost\":41796,\"ĠKurd\":41797,\"Ġfireball\":41798,\"compatible\":41799,\"Ġprojectiles\":41800,\"amorph\":41801,\"ĠSatisf\":41802,\"Ġquirks\":41803,\"Ġrecept\":41804,\"spective\":41805,\"Ġgraphical\":41806,\"ĠPicard\":41807,\"ĠAuthent\":41808,\"ĠSponge\":41809,\"Army\":41810,\"ĠLumin\":41811,\"ĠSOME\":41812,\"Ġsolitude\":41813,\"ĠSHOULD\":41814,\"ĠFasc\":41815,\"opez\":41816,\"types\":41817,\"gallery\":41818,\"OLOGY\":41819,\"shake\":41820,\"Ġ369\":41821,\"Ġreused\":41822,\"Ġ378\":41823,\"Ġexorc\":41824,\"Ġdocs\":41825,\"Yu\":41826,\"ĠGOD\":41827,\"ocrine\":41828,\"location\":41829,\"fif\":41830,\"Grid\":41831,\"Ġpowd\":41832,\"Ġ'[\":41833,\"Ġposterior\":41834,\"Thompson\":41835,\"Table\":41836,\"oslov\":41837,\"ĠGoddess\":41838,\"odon\":41839,\"ĠSTD\":41840,\"Ġresponsiveness\":41841,\"stab\":41842,\"absolute\":41843,\"Enough\":41844,\"ĠEssence\":41845,\"ĠUpgrade\":41846,\"hematically\":41847,\"Subscribe\":41848,\"alsh\":41849,\"repl\":41850,\"Ġselector\":41851,\"ĠLength\":41852,\"Ġtemporal\":41853,\"Tele\":41854,\"ocalyptic\":41855,\"ĠDeaths\":41856,\"rl\":41857,\"Target\":41858,\"ĠOrn\":41859,\"ongh\":41860,\"Ġ1909\":41861,\"Quest\":41862,\"Place\":41863,\"ĠDisabled\":41864,\"Ġascending\":41865,\"giene\":41866,\"ĠMSI\":41867,\"ivil\":41868,\"Ġcaval\":41869,\"Ġintermitt\":41870,\"Ġsalts\":41871,\"Apr\":41872,\"059\":41873,\"ĠKeeper\":41874,\"emis\":41875,\"ĠEternal\":41876,\"SER\":41877,\"estones\":41878,\"Ġrudimentary\":41879,\"Ġpooled\":41880,\"ĠAlright\":41881,\"Ġdiagrams\":41882,\"ydia\":41883,\"Jacob\":41884,\"Ġarchitectures\":41885,\"ĠUSPS\":41886,\"Ġfootnote\":41887,\"ĠBrav\":41888,\"ĠLeopard\":41889,\"Ġvirtuous\":41890,\"ploma\":41891,\"ĠHIP\":41892,\"Ġhorizontally\":41893,\"olith\":41894,\"Prop\":41895,\"ĠApocalypse\":41896,\"Syria\":41897,\"ĠShowdown\":41898,\"constitutional\":41899,\"Independent\":41900,\"ĠMiliband\":41901,\"ĠTracks\":41902,\"adle\":41903,\"ĠESL\":41904,\"ĠFIGHT\":41905,\"Ġjohn\":41906,\"é\":41907,\"benef\":41908,\"eware\":41909,\"ĠTABLE\":41910,\"ĠVeg\":41911,\"ainers\":41912,\"Ġresolves\":41913,\"Warren\":41914,\"ĠRanked\":41915,\"possibly\":41916,\"bian\":41917,\"simple\":41918,\"Ġuniformly\":41919,\"ĠSlash\":41920,\"otton\":41921,\"ĠAbsent\":41922,\"agically\":41923,\"ĠPieces\":41924,\"Station\":41925,\"ĠBeware\":41926,\"ĠDiscrimination\":41927,\"Ġponies\":41928,\"Import\":41929,\"utory\":41930,\"ĠParas\":41931,\"Phoenix\":41932,\"Lat\":41933,\"UTC\":41934,\"push\":41935,\"astically\":41936,\"urrent\":41937,\"untarily\":41938,\"Ġparanormal\":41939,\"Ġglanced\":41940,\"Ġmanifestations\":41941,\"ĠNeuroscience\":41942,\"irgin\":41943,\"ROM\":41944,\"Ġ($)\":41945,\"Ġ379\":41946,\"missing\":41947,\"Ġmercenaries\":41948,\"Ġenumer\":41949,\"ĠShant\":41950,\"Ws\":41951,\"wered\":41952,\"Ġbuffs\":41953,\"ultane\":41954,\"ĠRohing\":41955,\"igger\":41956,\"Ring\":41957,\"Ġmanifests\":41958,\"Fat\":41959,\"ĠReduced\":41960,\"ĠMinerva\":41961,\"uart\":41962,\"ĠArmory\":41963,\"orange\":41964,\"igible\":41965,\"Ġphysiology\":41966,\"Ut\":41967,\"Ġparchment\":41968,\"ĠFired\":41969,\"trap\":41970,\"oggle\":41971,\"mson\":41972,\"ĠPoster\":41973,\"Ġbount\":41974,\"import\":41975,\"maximum\":41976,\"Ġ422\":41977,\"ĠFemin\":41978,\"Ġnodding\":41979,\"Ġinscription\":41980,\"Results\":41981,\"GRE\":41982,\"icative\":41983,\"Ġcognition\":41984,\"Ġions\":41985,\"ĠBite\":41986,\"Ġneutron\":41987,\"Ġduplication\":41988,\"ĠZIP\":41989,\"ĠQuit\":41990,\"Ġgrasping\":41991,\"ĠDaylight\":41992,\"Ġlayouts\":41993,\"CLA\":41994,\"reason\":41995,\"ĠHuh\":41996,\"Ġpige\":41997,\"ĠBomber\":41998,\"Produ\":41999,\"Ġgland\":42000,\"ĠAbsolute\":42001,\"writ\":42002,\"Ġmassac\":42003,\"Ġfixation\":42004,\"device\":42005,\"yz\":42006,\"ĠGOT\":42007,\"ĠDying\":42008,\"adjust\":42009,\"grain\":42010,\"Ġdeform\":42011,\"Ġtypew\":42012,\"Ġdagger\":42013,\"ĠTuring\":42014,\"ĠBucc\":42015,\"Heavy\":42016,\"Ġcommod\":42017,\"files\":42018,\"ogeneous\":42019,\"roth\":42020,\"Buff\":42021,\"Ġbookmark\":42022,\"porary\":42023,\"Medical\":42024,\"Um\":42025,\"Ġtranslucent\":42026,\"ĠAnxiety\":42027,\"ĠCorinthians\":42028,\"optional\":42029,\"PUT\":42030,\"Ġcrucifix\":42031,\"alloween\":42032,\"ĠVK\":42033,\"Ġblu\":42034,\"ĠCorinth\":42035,\"Mount\":42036,\"Ġmembranes\":42037,\"particip\":42038,\"Ġextraord\":42039,\"Ġstimulated\":42040,\"leneck\":42041,\"Ġspecifies\":42042,\"Sin\":42043,\"lash\":42044,\"Edited\":42045,\"Ġfused\":42046,\"Nin\":42047,\"ĠBungie\":42048,\"ĠTooth\":42049,\"WATCH\":42050,\"Nav\":42051,\"Initially\":42052,\"+)\":42053,\"ĠAncest\":42054,\"Ġtransmitter\":42055,\"ĠVolks\":42056,\"ezvous\":42057,\"ĠNirvana\":42058,\"ĠCald\":42059,\"font\":42060,\"Und\":42061,\"remlin\":42062,\"ichever\":42063,\"ĠHeal\":42064,\"shall\":42065,\"Ġattribution\":42066,\"authorized\":42067,\"ĠINTO\":42068,\"acteria\":42069,\"ĠTsu\":42070,\"ĠPlane\":42071,\"iphate\":42072,\"igraph\":42073,\"chev\":42074,\"Ġinverse\":42075,\"ifest\":42076,\"Players\":42077,\"!!\\\"\":42078,\"ĠContrast\":42079,\"1984\":42080,\"Ġsevent\":42081,\"colour\":42082,\"ĠRational\":42083,\"virtual\":42084,\"Ġfec\":42085,\"ĠETH\":42086,\"ĠPru\":42087,\"Õ\":42088,\"asma\":42089,\"Cur\":42090,\"Ġassigns\":42091,\"Ġridic\":42092,\"Todd\":42093,\"ulton\":42094,\"ĠDefendant\":42095,\"opsis\":42096,\"Ġpercentile\":42097,\"shr\":42098,\"wagen\":42099,\"Ġ368\":42100,\"SIGN\":42101,\"Screen\":42102,\"reprene\":42103,\"Ġerection\":42104,\"ĠFreak\":42105,\"ĠStard\":42106,\"stained\":42107,\"Ġcla\":42108,\"fet\":42109,\"ramids\":42110,\"QL\":42111,\"avorable\":42112,\"ĠTCP\":42113,\"nown\":42114,\"ulence\":42115,\"similar\":42116,\"Ġlinkage\":42117,\"ercise\":42118,\"Path\":42119,\"LECT\":42120,\"ĠCollections\":42121,\"ĠModule\":42122,\"Ġcs\":42123,\"Current\":42124,\"Ġmono\":42125,\"ĠAlv\":42126,\"ĠDude\":42127,\"Ġhypers\":42128,\"Ġ2600\":42129,\"surface\":42130,\"Ġpredictor\":42131,\"ĠColomb\":42132,\"Prof\":42133,\"anqu\":42134,\"natal\":42135,\"Ġadultery\":42136,\"ĠGenerations\":42137,\"clerosis\":42138,\"Ġ371\":42139,\"Ġenlightenment\":42140,\"onomic\":42141,\"Ġsatir\":42142,\"ĠBasics\":42143,\"Graham\":42144,\"ĠRove\":42145,\"Ġadul\":42146,\"Shut\":42147,\"ocious\":42148,\"Ġhandc\":42149,\"BW\":42150,\"ĠCognitive\":42151,\"visible\":42152,\"Ġinev\":42153,\"Ġ978\":42154,\"ĠSupported\":42155,\"Ġarrays\":42156,\"Ġalienation\":42157,\"Weight\":42158,\"ĠkWh\":42159,\"Ġwarped\":42160,\"Ġ386\":42161,\"lance\":42162,\"Ġherpes\":42163,\"ĠPHP\":42164,\"Ġclaimant\":42165,\"uitive\":42166,\"Ġpussy\":42167,\"Ġcorpus\":42168,\"ĠAo\":42169,\"Qual\":42170,\"ĠXVI\":42171,\"requ\":42172,\"Ġsympt\":42173,\"mination\":42174,\"Ġhairy\":42175,\"ĠBattles\":42176,\"owntown\":42177,\"Roberts\":42178,\"Ġnec\":42179,\"ablo\":42180,\"AMD\":42181,\"internet\":42182,\"Tar\":42183,\"direction\":42184,\"ouston\":42185,\"ĠGlock\":42186,\"ĠYanukovych\":42187,\"ogens\":42188,\"rogram\":42189,\"otype\":42190,\"ĠPt\":42191,\"tenance\":42192,\"Ġaromatic\":42193,\"oxin\":42194,\"Vert\":42195,\"Ġsociop\":42196,\"cible\":42197,\"Db\":42198,\"________________\":42199,\"Third\":42200,\"ĠShips\":42201,\"!.\":42202,\"expensive\":42203,\"WOR\":42204,\"primary\":42205,\"Ġ666\":42206,\"Ġdecaying\":42207,\"Ġclustered\":42208,\"Ġbeetles\":42209,\"ĠHogwarts\":42210,\"Ġheaders\":42211,\"ĠJudah\":42212,\"Ġscen\":42213,\"Ġcosmos\":42214,\"ĠGenetic\":42215,\"blems\":42216,\"Ġfeeble\":42217,\"NOW\":42218,\"NSA\":42219,\"Ġadminist\":42220,\"ĠDocker\":42221,\"portion\":42222,\"gression\":42223,\"Ġ1904\":42224,\"heard\":42225,\"Ġinhab\":42226,\"ĠLeaves\":42227,\"Ġcortisol\":42228,\"atinum\":42229,\"unknown\":42230,\"ĠObserv\":42231,\"ĠPhilosophy\":42232,\"Ide\":42233,\"Ġcopyrighted\":42234,\"surv\":42235,\"ĠLocations\":42236,\"Ġglands\":42237,\"ĠKnife\":42238,\"ĠEmber\":42239,\"ĠUnicorn\":42240,\"Ġhaste\":42241,\"Ġkinderg\":42242,\"ĠTerrit\":42243,\"ĠKoran\":42244,\"Ġaval\":42245,\"addon\":42246,\"ĠNero\":42247,\"\\\"]\":42248,\"Ġ392\":42249,\"comfort\":42250,\"Ġclothed\":42251,\"ashtra\":42252,\"mode\":42253,\"Ġ??\":42254,\"!\\\",\":42255,\"Ġknob\":42256,\"EMP\":42257,\"norm\":42258,\"ĠAgo\":42259,\"RECT\":42260,\"Denver\":42261,\"Ġ1907\":42262,\"ĠBombs\":42263,\"Sche\":42264,\"Ġtriangular\":42265,\"Ġperv\":42266,\"rises\":42267,\"Jes\":42268,\"Ġcalibration\":42269,\"Ġts\":42270,\"Same\":42271,\"ĠAxe\":42272,\"ĠMei\":42273,\"multi\":42274,\"Ġexerc\":42275,\"orney\":42276,\"Ware\":42277,\"abul\":42278,\"ĠFior\":42279,\"Eventually\":42280,\"ĠGrizz\":42281,\"Past\":42282,\"married\":42283,\"Ġscram\":42284,\"ĠCache\":42285,\"posure\":42286,\"Ġheav\":42287,\"ĠShirt\":42288,\"powder\":42289,\"complex\":42290,\"Doc\":42291,\"arus\":42292,\"Pi\":42293,\"Ġcurv\":42294,\"ĠTopic\":42295,\"Ġ.)\":42296,\"Ġwills\":42297,\"philis\":42298,\"gui\":42299,\"leground\":42300,\"Eth\":42301,\"Strike\":42302,\"Kid\":42303,\"Ġdelegated\":42304,\"Soon\":42305,\"Ġwast\":42306,\"gage\":42307,\"Ġprosecut\":42308,\"Ġ374\":42309,\"opolis\":42310,\"chest\":42311,\"ensation\":42312,\"Ġredes\":42313,\"Ġpresum\":42314,\"Portland\":42315,\"Ġannihil\":42316,\"yssey\":42317,\"Ġforks\":42318,\"Ġvitro\":42319,\"walker\":42320,\"ĠPsal\":42321,\"ĠStealth\":42322,\"Quick\":42323,\"ĠBaghd\":42324,\"ĠDrift\":42325,\"//\":42326,\"Ġinvincible\":42327,\"ĠGAM\":42328,\"Ġcastles\":42329,\"Ġbondage\":42330,\"ĠBalloon\":42331,\"Amid\":42332,\"individual\":42333,\"tis\":42334,\"ĠGuides\":42335,\"xe\":42336,\"Cong\":42337,\"URI\":42338,\"ĠHH\":42339,\"PHOTOS\":42340,\"ĠASIC\":42341,\"burst\":42342,\"ahon\":42343,\"ĠFIX\":42344,\"ilib\":42345,\"Ġ457\":42346,\"ĠLogged\":42347,\"à¹\":42348,\"Creat\":42349,\"inatory\":42350,\"column\":42351,\"ĠAugustus\":42352,\"suggest\":42353,\"pret\":42354,\"ĠParan\":42355,\"Ġsubsistence\":42356,\"wx\":42357,\"×\":42358,\"aleigh\":42359,\"dash\":42360,\"ĠMana\":42361,\"Ko\":42362,\"opausal\":42363,\"Ġbene\":42364,\"ĠSabb\":42365,\"ĠGhosts\":42366,\"Ġ1830\":42367,\"ĠHats\":42368,\"ĠHive\":42369,\"Perfect\":42370,\"Ġsocialists\":42371,\"Ġtumult\":42372,\"EGA\":42373,\"ĠNAME\":42374,\"Android\":42375,\"assembled\":42376,\"phis\":42377,\"Stage\":42378,\"Char\":42379,\"Double\":42380,\"Ġinsign\":42381,\"IED\":42382,\"perial\":42383,\"ĠEMP\":42384,\"mx\":42385,\"Ġskept\":42386,\"Ġwifi\":42387,\"Ġparad\":42388,\"ĠFrequency\":42389,\"Dist\":42390,\"nil\":42391,\"iots\":42392,\"å\":42393,\"Message\":42394,\"Furthermore\":42395,\"Ġhideous\":42396,\"ĠLDL\":42397,\"ĠFault\":42398,\"ĠDimensions\":42399,\"ĠImplement\":42400,\"fram\":42401,\"Ġamaz\":42402,\"ĠIndones\":42403,\"ĠTile\":42404,\"Ġlar\":42405,\"gc\":42406,\"Ġcorrelate\":42407,\"Ġensl\":42408,\"mite\":42409,\"Ġhomosexuals\":42410,\"Ġagric\":42411,\"8000\":42412,\"Ġcuring\":42413,\"rament\":42414,\"Ġrecons\":42415,\"ocene\":42416,\"ENTION\":42417,\"Ġcommunion\":42418,\"ĠFunction\":42419,\"iple\":42420,\"Ġredund\":42421,\"Ġcalibrated\":42422,\"Ġcontribut\":42423,\"ĠHuck\":42424,\"limit\":42425,\"ĠFedora\":42426,\"ĠTsuk\":42427,\"brates\":42428,\"Ġ1903\":42429,\"ozo\":42430,\"visual\":42431,\"ĠDiscipline\":42432,\"chains\":42433,\"ĠOCD\":42434,\"Ġexpended\":42435,\"0002\":42436,\"Ġsty\":42437,\"ĠNightmare\":42438,\"ĠReplace\":42439,\"ounty\":42440,\"fn\":42441,\"1900\":42442,\"ĠEpidem\":42443,\"ĠFW\":42444,\"Ġgul\":42445,\"ĠTomato\":42446,\"ĠPerse\":42447,\"wl\":42448,\"ĠFormation\":42449,\"Scan\":42450,\"cosystem\":42451,\"Brand\":42452,\"Ġ398\":42453,\"Ġcaptives\":42454,\"Ġ×\":42455,\"ESCO\":42456,\"ĠEnder\":42457,\"lesh\":42458,\"ĠAscend\":42459,\"poly\":42460,\"eous\":42461,\"Ġhyster\":42462,\"Murray\":42463,\"phe\":42464,\"Ġradiator\":42465,\"esthes\":42466,\"Ġopin\":42467,\"Ġconspic\":42468,\"intosh\":42469,\"Ġwitchcraft\":42470,\"ĠCFR\":42471,\"ussian\":42472,\"escent\":42473,\"locking\":42474,\"Ġnonsensical\":42475,\"uala\":42476,\"ĠSerial\":42477,\"1991\":42478,\"ĠCalm\":42479,\"containing\":42480,\"Ġstimulates\":42481,\"Ġ448\":42482,\"Pir\":42483,\"ĠâĨĴ\":42484,\"ĠDiver\":42485,\"Ġmanuscripts\":42486,\"ĠGaia\":42487,\"Ñĥ\":42488,\"Learning\":42489,\"Ġnipple\":42490,\"reads\":42491,\"Ġandroid\":42492,\"ĠMeditation\":42493,\"Ġincomprehensible\":42494,\"edded\":42495,\"Ġdescendant\":42496,\"ĠMorty\":42497,\"Luckily\":42498,\"ARCH\":42499,\"ausible\":42500,\"Dig\":42501,\"shared\":42502,\"ĠClip\":42503,\"Ġtrope\":42504,\"Ġnarcissistic\":42505,\"ventures\":42506,\"Ġcuriously\":42507,\"ĠCosmos\":42508,\"Aust\":42509,\"Lay\":42510,\"ĠShard\":42511,\"ĠRecorded\":42512,\"Ġ458\":42513,\"........\":42514,\"Ġperish\":42515,\"ĠExample\":42516,\"luent\":42517,\"Ġapes\":42518,\"ĠHitch\":42519,\"Ġholiest\":42520,\"Ġamplifier\":42521,\"minent\":42522,\"xxxxxxxx\":42523,\"inite\":42524,\"Ġgenomes\":42525,\"ĠGuilty\":42526,\"mult\":42527,\"Ġorc\":42528,\"Ġnipples\":42529,\"Side\":42530,\"Ġlogically\":42531,\"Ġdatasets\":42532,\"ĠTitanium\":42533,\"Ġrotor\":42534,\"undle\":42535,\"handled\":42536,\"nexpected\":42537,\"Ġdw\":42538,\"Ġdiagonal\":42539,\"ĠAnimated\":42540,\"Ġnumbering\":42541,\"Forest\":42542,\"ĠâĨ\":42543,\"Prin\":42544,\"Ġchemically\":42545,\"ĠGithub\":42546,\"Ġaph\":42547,\"ĠFaster\":42548,\"ĠTinker\":42549,\"ikini\":42550,\"Dest\":42551,\"dri\":42552,\"Manufact\":42553,\"isance\":42554,\"Return\":42555,\"Alert\":42556,\"elcome\":42557,\"ĠMMR\":42558,\"Ġresid\":42559,\"ĠLIC\":42560,\"Ġspecificity\":42561,\"zanne\":42562,\"Ġanyways\":42563,\"Ġ426\":42564,\"Scot\":42565,\"astery\":42566,\"Via\":42567,\"ĠBlocks\":42568,\"Ġactivates\":42569,\"Ġabstinence\":42570,\"Ġchronological\":42571,\"Soul\":42572,\"ĠSchne\":42573,\"Ġwatts\":42574,\"AUT\":42575,\"Ġcalcul\":42576,\"Simply\":42577,\"Emb\":42578,\"ceptive\":42579,\"ĠCatholicism\":42580,\"obook\":42581,\"ĠBits\":42582,\"ĠMbps\":42583,\"Ġindignation\":42584,\"Ġshorthand\":42585,\"Active\":42586,\"ĠLimbaugh\":42587,\"ĠCapcom\":42588,\"adesh\":42589,\"Ġclipping\":42590,\"ĠInstructor\":42591,\"Secret\":42592,\"___\":42593,\"Fer\":42594,\"rawling\":42595,\"ĠReward\":42596,\"Ġweep\":42597,\"Ġmotherboard\":42598,\"Above\":42599,\"metry\":42600,\"ĠPTS\":42601,\"Ġbombard\":42602,\"abetes\":42603,\".--\":42604,\"Lens\":42605,\"Comb\":42606,\"basic\":42607,\"ĠREALLY\":42608,\"Later\":42609,\"Ġ383\":42610,\"Ġpositional\":42611,\"olesc\":42612,\"Ġcrotch\":42613,\"ĠMDMA\":42614,\"requently\":42615,\"ĠPants\":42616,\"Ġ433\":42617,\"uctor\":42618,\"Ġillumination\":42619,\"ĠÙħ\":42620,\"ocrin\":42621,\"Ġpamph\":42622,\"atio\":42623,\"etc\":42624,\"Ġrestores\":42625,\"ĠProtector\":42626,\"Develop\":42627,\"ĠMew\":42628,\"trop\":42629,\"ĠSlayer\":42630,\"Ti\":42631,\"ĠNotwithstanding\":42632,\"Match\":42633,\"LIST\":42634,\"IDES\":42635,\"ĠThick\":42636,\"Ġdisks\":42637,\"Kin\":42638,\"Ġghetto\":42639,\"ĠObjects\":42640,\"Ġprism\":42641,\"ĠNether\":42642,\"Ġvul\":42643,\"iky\":42644,\"]:\":42645,\"ĠDetail\":42646,\"Ġfucked\":42647,\"!?\":42648,\"anium\":42649,\"Ġlords\":42650,\"ilities\":42651,\"ĠEthnic\":42652,\"static\":42653,\"$$\":42654,\"evidence\":42655,\"Ġmainline\":42656,\"Ġpeasant\":42657,\"ĠEnhance\":42658,\"ĠForced\":42659,\"virt\":42660,\"Ġii\":42661,\"Ġsymm\":42662,\"Ġconverter\":42663,\"ularity\":42664,\"Ġrepent\":42665,\"num\":42666,\"ĠScrew\":42667,\"ĠFTA\":42668,\"Ġmarines\":42669,\"hetto\":42670,\"blow\":42671,\"Ġado\":42672,\"ĠTypical\":42673,\"Ġoverw\":42674,\"ĠBerm\":42675,\"keley\":42676,\"Song\":42677,\"hao\":42678,\"valid\":42679,\"EXT\":42680,\"ĠProvides\":42681,\"âĺħâĺħ\":42682,\"ĠOdin\":42683,\"Shot\":42684,\"Ġgamma\":42685,\"Princ\":42686,\"asonry\":42687,\"ĠAccuracy\":42688,\"Ġcriterion\":42689,\"Ġdescriptive\":42690,\"Gall\":42691,\"gray\":42692,\"ĠCalcul\":42693,\"Ġaxes\":42694,\"ĠCommunists\":42695,\"ĠRebellion\":42696,\"Success\":42697,\"tg\":42698,\"Ġâĺ\":42699,\"Ġmultiplier\":42700,\"ravity\":42701,\"Thus\":42702,\"URL\":42703,\"Ġalternatively\":42704,\"duction\":42705,\"Ġsarcast\":42706,\"ĠCarth\":42707,\"ĠUSL\":42708,\"ĠInvisible\":42709,\"larg\":42710,\"pleted\":42711,\"pathic\":42712,\"Additionally\":42713,\"ĠCao\":42714,\"Ġlatent\":42715,\"ĠSurge\":42716,\"MEN\":42717,\"communications\":42718,\"ĠArray\":42719,\"Pink\":42720,\"commit\":42721,\"isodes\":42722,\"earcher\":42723,\"Ukraine\":42724,\"ĠAnthrop\":42725,\"incial\":42726,\"Ġquotations\":42727,\"adena\":42728,\"Ġwhining\":42729,\"Ġretri\":42730,\"ĠAssass\":42731,\"elligent\":42732,\"ĠPERSON\":42733,\"Py\":42734,\"Send\":42735,\"ĠâĪĴ\":42736,\"DON\":42737,\"Ġwatt\":42738,\"description\":42739,\"POS\":42740,\"Ġrepro\":42741,\"destroy\":42742,\"icidal\":42743,\"Ġmidrange\":42744,\"Ġinfographic\":42745,\"interesting\":42746,\"category\":42747,\"Flash\":42748,\"ĠInvasion\":42749,\"ĠExodus\":42750,\"restricted\":42751,\"Ġinference\":42752,\"dding\":42753,\"mingham\":42754,\"Ġcircumst\":42755,\"Wi\":42756,\"ĠHast\":42757,\"Ġsubjug\":42758,\"Ġwhispering\":42759,\"-.\":42760,\"Ġadren\":42761,\"ĠPattern\":42762,\"BOX\":42763,\"ĠEnhancement\":42764,\"Exc\":42765,\"ĠBucket\":42766,\"ĠGUN\":42767,\"deen\":42768,\"ĠHomo\":42769,\"1985\":42770,\"Ġclo\":42771,\"Ġsnippet\":42772,\"Ġ1896\":42773,\"TPP\":42774,\"Seg\":42775,\"success\":42776,\";\\\"\":42777,\"ĠMUCH\":42778,\"Author\":42779,\"Ġreplication\":42780,\"Ġhallucinations\":42781,\"Inv\":42782,\"ĠAware\":42783,\"ĠViper\":42784,\"kai\":42785,\"frames\":42786,\"ĠTHANK\":42787,\"ĠSHA\":42788,\"wordpress\":42789,\"Ġbc\":42790,\"CIA\":42791,\"arrison\":42792,\"Ġalloc\":42793,\"ĠAlz\":42794,\"letcher\":42795,\"ĠDaredevil\":42796,\"iversary\":42797,\"Ġmanuals\":42798,\"Catholic\":42799,\"feat\":42800,\"Ġkinetic\":42801,\"JB\":42802,\"yeah\":42803,\"ĠLDS\":42804,\"Ġppm\":42805,\"ĠADC\":42806,\"pring\":42807,\"cence\":42808,\"Ġclasp\":42809,\"Ġsetups\":42810,\"Ġdeity\":42811,\"ĠIndra\":42812,\"ĠWander\":42813,\"Ġantib\":42814,\"Otherwise\":42815,\"ombie\":42816,\"Bitcoin\":42817,\"ipop\":42818,\"expression\":42819,\"Animal\":42820,\"ĠResurrection\":42821,\"ĠMoral\":42822,\"ĠSDK\":42823,\"Ġwretched\":42824,\"ogenous\":42825,\"species\":42826,\"Ġchuckled\":42827,\"Thor\":42828,\"Ġ428\":42829,\"avery\":42830,\"ĠPry\":42831,\"asures\":42832,\"ĠErn\":42833,\"apor\":42834,\"Ġinnumerable\":42835,\"Ġbaptized\":42836,\"ĠExplosive\":42837,\"Ġelves\":42838,\"idges\":42839,\"ĠParadox\":42840,\"Close\":42841,\"aldehyde\":42842,\"construct\":42843,\"Ġvirginity\":42844,\"Poll\":42845,\"assin\":42846,\"Doctors\":42847,\"Pos\":42848,\"NECT\":42849,\"Moreover\":42850,\"Commercial\":42851,\"cknowled\":42852,\"1988\":42853,\"Ġquotation\":42854,\"marriage\":42855,\"ĠBapt\":42856,\"ĠSina\":42857,\"ĠGloves\":42858,\"gian\":42859,\"Ġconfounding\":42860,\"URRENT\":42861,\"Dean\":42862,\"Brew\":42863,\"thur\":42864,\"pty\":42865,\"immune\":42866,\"ĠSQU\":42867,\"Ġcounterfe\":42868,\"rider\":42869,\"Ġinferred\":42870,\"ĠDimension\":42871,\"ĠToad\":42872,\"Ġafterlife\":42873,\"ĠHERO\":42874,\"Indiana\":42875,\"seek\":42876,\"Ġdistinguishes\":42877,\"ĠQur\":42878,\"ĠMethods\":42879,\"combat\":42880,\"Ġcateg\":42881,\"ĠStruggle\":42882,\"teness\":42883,\"liquid\":42884,\"Ġblinking\":42885,\"ĠCONTIN\":42886,\"iae\":42887,\"Ġaerobic\":42888,\"Ġstrugg\":42889,\"Ġegalitarian\":42890,\"hello\":42891,\"orrect\":42892,\"ĠAbandon\":42893,\"Ġferment\":42894,\"Area\":42895,\"idem\":42896,\"ĠMania\":42897,\"Ġjs\":42898,\"ĠBALL\":42899,\"Running\":42900,\"Ġregenerate\":42901,\"iquid\":42902,\"Uh\":42903,\"Crystal\":42904,\"ĠItal\":42905,\"ĠHeavenly\":42906,\"Ð²\":42907,\"CRIPTION\":42908,\"Consumer\":42909,\"dust\":42910,\"amiliar\":42911,\"ĠRhino\":42912,\"Rocket\":42913,\"Ġreversible\":42914,\"kok\":42915,\"ĠSketch\":42916,\"Ġshotguns\":42917,\"apses\":42918,\"Ġdetach\":42919,\"ĠCells\":42920,\"artist\":42921,\"rily\":42922,\"ĠRestore\":42923,\"Scar\":42924,\"Ġevid\":42925,\"Ġspaced\":42926,\"ĠContributions\":42927,\"Ġ418\":42928,\"ĠMystic\":42929,\"Ġobfusc\":42930,\"Russ\":42931,\"wings\":42932,\"Pear\":42933,\"osite\":42934,\"Nusra\":42935,\"urations\":42936,\"ovie\":42937,\"icago\":42938,\"ĠConcepts\":42939,\"Ġstimuli\":42940,\"Ġaroused\":42941,\"aughty\":42942,\"Talking\":42943,\"ĠPrompt\":42944,\"Across\":42945,\"ĠPlaint\":42946,\"Ġbranching\":42947,\"Thankfully\":42948,\"Original\":42949,\"Esc\":42950,\"ĠTechnician\":42951,\"fleet\":42952,\"usher\":42953,\"Mos\":42954,\"livion\":42955,\"oenix\":42956,\"Ġhr\":42957,\"ibble\":42958,\"Ġindent\":42959,\"ĠFinished\":42960,\"Department\":42961,\"ĠINFO\":42962,\"Movie\":42963,\"++\":42964,\"THING\":42965,\"Ġtimers\":42966,\"rocket\":42967,\"Natural\":42968,\"lime\":42969,\"Ġangular\":42970,\"osure\":42971,\"Ġdynamically\":42972,\"Ġpacif\":42973,\"ĠProcessor\":42974,\"Ġdisgu\":42975,\"Ġmoderators\":42976,\"Ġceases\":42977,\"Ġinertia\":42978,\"Ġpaperback\":42979,\"yton\":42980,\"ĠHuma\":42981,\"Ġprohibitions\":42982,\"Ġgestation\":42983,\"Bomb\":42984,\"termin\":42985,\"Ġcaric\":42986,\"oS\":42987,\"tc\":42988,\"Cop\":42989,\"raved\":42990,\"Ġeighty\":42991,\"ĠEnable\":42992,\"Ġimplementations\":42993,\"Ġconquering\":42994,\"ĠFinder\":42995,\"window\":42996,\"Gra\":42997,\"Ġfonts\":42998,\"laughter\":42999,\"Ġcolonization\":43000,\"ĠDOD\":43001,\")!\":43002,\",)\":43003,\"ĠGeral\":43004,\"ĠSpoiler\":43005,\"ĠComponent\":43006,\"Ġgist\":43007,\"hiro\":43008,\"Ġlicens\":43009,\"nesses\":43010,\"Ġkarma\":43011,\"?\\\".\":43012,\"OPA\":43013,\"Ġsquats\":43014,\"ĠRAND\":43015,\"Ġorally\":43016,\"document\":43017,\"olars\":43018,\"Ġpresumptive\":43019,\"Pers\":43020,\"OAD\":43021,\"ufficient\":43022,\"LESS\":43023,\"Hidden\":43024,\"ORK\":43025,\"xs\":43026,\"Ġmathematician\":43027,\"ĠGloss\":43028,\"Ġannihilation\":43029,\"Ġmanifold\":43030,\"Ry\":43031,\"Thunder\":43032,\"Yan\":43033,\"Activ\":43034,\"Ġworldly\":43035,\"TED\":43036,\"marg\":43037,\"ĠStun\":43038,\"ryce\":43039,\"ĠVG\":43040,\"Isn\":43041,\"ĠCyn\":43042,\"Expl\":43043,\"IRED\":43044,\"Ġcompr\":43045,\"Ġindisc\":43046,\"Boss\":43047,\"()\":43048,\"berman\":43049,\"ĠBegins\":43050,\"ujah\":43051,\"ornia\":43052,\"hetical\":43053,\"Ġcivilizations\":43054,\"Ġfundamentalist\":43055,\"strap\":43056,\"Forward\":43057,\"ettlement\":43058,\"Ġprophetic\":43059,\"glers\":43060,\"bending\":43061,\"Terry\":43062,\"Ġidi\":43063,\"Ġtrunc\":43064,\"Ġcreeps\":43065,\"intel\":43066,\"switch\":43067,\"ailand\":43068,\"Ġinstaller\":43069,\"GOP\":43070,\"Ġ499\":43071,\"ĠParallel\":43072,\"Cru\":43073,\"Ġ\\\"@\":43074,\"Ġ396\":43075,\"ĠUnlock\":43076,\"Raven\":43077,\"Corn\":43078,\"Ġcircadian\":43079,\"Ġ********************************\":43080,\"iliate\":43081,\"ĠFunctional\":43082,\"Ġpronouns\":43083,\"ĠSatoshi\":43084,\"Ġstim\":43085,\"Gay\":43086,\"Iss\":43087,\"ĠThief\":43088,\"atellite\":43089,\"Ġshards\":43090,\"Ġphil\":43091,\"protein\":43092,\"Ġalters\":43093,\"Poor\":43094,\"Typically\":43095,\"KER\":43096,\"ociate\":43097,\"Ġemits\":43098,\"recy\":43099,\"Ġmechanically\":43100,\"Ġ...\\\"\":43101,\"nature\":43102,\"sys\":43103,\"ysc\":43104,\"Ġwavelengths\":43105,\"pattern\":43106,\"insured\":43107,\"Ġparasitic\":43108,\"ĠLCS\":43109,\"ĠPACs\":43110,\"Ġheals\":43111,\"ĠCCP\":43112,\"ĠHacker\":43113,\"Ġpsy\":43114,\"ĠBeans\":43115,\"Ġdemonic\":43116,\"JV\":43117,\"Ġatmosp\":43118,\"equality\":43119,\"Ġairst\":43120,\"Ġincarn\":43121,\"ynthesis\":43122,\"Ġequations\":43123,\"tch\":43124,\"ĠHUGE\":43125,\"ĠChanged\":43126,\"itatively\":43127,\"Job\":43128,\"gaming\":43129,\"Ġ1899\":43130,\"ĠMorsi\":43131,\"Ġconjecture\":43132,\"riad\":43133,\"Ġprimates\":43134,\"ĠArtemis\":43135,\"ĠThro\":43136,\"Ġbiologically\":43137,\"Church\":43138,\"topia\":43139,\"recomm\":43140,\"Ġgradient\":43141,\"Ġful\":43142,\"Ġbastard\":43143,\"CHO\":43144,\"IUM\":43145,\"sleep\":43146,\"Construction\":43147,\"raints\":43148,\"vable\":43149,\"ionage\":43150,\"Ġcomrade\":43151,\"Ġpopulate\":43152,\"Ġnerds\":43153,\"ĠXie\":43154,\"result\":43155,\"ĠImper\":43156,\"Ġpamphlet\":43157,\"Ku\":43158,\"Ġbackend\":43159,\"ificent\":43160,\"etus\":43161,\"Ġdisson\":43162,\"config\":43163,\"Ġsuc\":43164,\"Ġwavelength\":43165,\"external\":43166,\"owder\":43167,\"Ġpredis\":43168,\"eenth\":43169,\"Det\":43170,\"andem\":43171,\"Ġ1865\":43172,\"ĠDefeat\":43173,\"Individual\":43174,\"Ġretrieving\":43175,\"stories\":43176,\"Ġdesolate\":43177,\"Ġlett\":43178,\"Ġunpublished\":43179,\"Ġpassively\":43180,\"Ġdissertation\":43181,\"raits\":43182,\"abee\":43183,\"ĠResist\":43184,\"Robin\":43185,\"Ġbenevolent\":43186,\"blast\":43187,\"Offic\":43188,\"snap\":43189,\"vernment\":43190,\"Ġextermin\":43191,\"wt\":43192,\"bitious\":43193,\"hibited\":43194,\"Insp\":43195,\"posted\":43196,\"ĠYugoslav\":43197,\"rational\":43198,\"adapt\":43199,\"ĠAtari\":43200,\"Ġplugin\":43201,\"oglobin\":43202,\"efeated\":43203,\"ĠHRC\":43204,\"cko\":43205,\"ilver\":43206,\"ĠDestruction\":43207,\"gewater\":43208,\"ĠRadiation\":43209,\"Ġimprison\":43210,\"origin\":43211,\"antine\":43212,\"ĠPublication\":43213,\"Ġhealer\":43214,\"istered\":43215,\"ĠTHEIR\":43216,\"hazard\":43217,\"Contract\":43218,\"Ġmediated\":43219,\"Ġindexed\":43220,\"ĠSYSTEM\":43221,\"Labor\":43222,\"Blade\":43223,\"Ġyog\":43224,\"Champ\":43225,\"Gordon\":43226,\"IAS\":43227,\"Ġnineteenth\":43228,\"animous\":43229,\"begin\":43230,\"ĠHolo\":43231,\"Planet\":43232,\"udding\":43233,\"default\":43234,\"ĠOMG\":43235,\"Ġwond\":43236,\"wm\":43237,\"pend\":43238,\"Extreme\":43239,\"Ġinterstellar\":43240,\"ASED\":43241,\"ĠBerks\":43242,\"Ġprimal\":43243,\"Foot\":43244,\"Ġinadvert\":43245,\"amboo\":43246,\"ĠLeica\":43247,\"Events\":43248,\"ĠPigs\":43249,\"RAFT\":43250,\"ï\":43251,\"ĠGentleman\":43252,\"Multiple\":43253,\"ĠPsychiatric\":43254,\"Ġdespise\":43255,\"ĠZionism\":43256,\"ĠSSL\":43257,\"shit\":43258,\"Ġthreaded\":43259,\"Ġartifact\":43260,\"Ġmitochondrial\":43261,\"ĠLayer\":43262,\"inus\":43263,\"podcast\":43264,\"Ġawaken\":43265,\"Management\":43266,\"Ġdelusions\":43267,\"grey\":43268,\"Ġpseud\":43269,\"agonal\":43270,\"ĠHirosh\":43271,\"Georg\":43272,\"Dragon\":43273,\"Stack\":43274,\"ohm\":43275,\"Ġvener\":43276,\"Row\":43277,\"Ġsandbox\":43278,\"Ġblinding\":43279,\"razen\":43280,\"Ġ389\":43281,\"Ġcrappy\":43282,\"Ġlith\":43283,\"antha\":43284,\"Ġplurality\":43285,\"ĠDAC\":43286,\"inently\":43287,\"intage\":43288,\"Ġ1902\":43289,\"ĠDepend\":43290,\"Ġelapsed\":43291,\"==\":43292,\"ĠGenie\":43293,\"Bush\":43294,\"ĠPlanetary\":43295,\"Bah\":43296,\"ĠKira\":43297,\"emn\":43298,\"Month\":43299,\"allic\":43300,\"coded\":43301,\"VOL\":43302,\"Ġ[...]\":43303,\"ĠRampage\":43304,\"Ġ(*\":43305,\"Production\":43306,\"licts\":43307,\"Ġinoc\":43308,\"Cour\":43309,\"Ġspurious\":43310,\"Ġultras\":43311,\"ggles\":43312,\"Ġdelusion\":43313,\"ĠRacer\":43314,\"ĠPrism\":43315,\"FH\":43316,\"uppet\":43317,\"Ġcultured\":43318,\"Ġ436\":43319,\"aneously\":43320,\"Ø§ÙĦ\":43321,\"ĠMissions\":43322,\"monton\":43323,\"criptions\":43324,\"ificate\":43325,\"Cause\":43326,\"Ġ1898\":43327,\"ocaust\":43328,\"Ġbri\":43329,\"ĠShoals\":43330,\"ommod\":43331,\"alted\":43332,\"ogenesis\":43333,\"warn\":43334,\"illus\":43335,\"vv\":43336,\"Ġcontam\":43337,\"ĠLesbian\":43338,\"Ġcavalry\":43339,\"ĠPresence\":43340,\"rehens\":43341,\"tool\":43342,\"accessible\":43343,\"Ġ(~\":43344,\"ĠLicensed\":43345,\"Ġprophets\":43346,\"Ġboulder\":43347,\"mean\":43348,\"akura\":43349,\"Ġunres\":43350,\"ĠCinnamon\":43351,\"Leaks\":43352,\"........................\":43353,\"Contact\":43354,\"Ġassassins\":43355,\"ĠGreenwald\":43356,\"dk\":43357,\"amazon\":43358,\"Ġagreeable\":43359,\"ernandez\":43360,\"Easy\":43361,\"PLA\":43362,\"ĠBigfoot\":43363,\"Ġconvent\":43364,\"Ġempires\":43365,\"Ġ387\":43366,\"Ġgrasped\":43367,\"Ġruby\":43368,\"Ġreconc\":43369,\"Warning\":43370,\"atem\":43371,\"Ġretrieval\":43372,\"ĠFDR\":43373,\"ĠReaper\":43374,\"orem\":43375,\"ĠLuo\":43376,\"hig\":43377,\"ĠArmor\":43378,\"tp\":43379,\"ĠInterpret\":43380,\"Conservative\":43381,\"ĠSodium\":43382,\"Ġbead\":43383,\"Ġpropagate\":43384,\"claw\":43385,\"href\":43386,\"ĠPaste\":43387,\"Ġomit\":43388,\"Boost\":43389,\"Diamond\":43390,\"goo\":43391,\"Ġanomal\":43392,\"ĠDISTRICT\":43393,\"Greek\":43394,\"warning\":43395,\"Ġdespised\":43396,\"Karl\":43397,\"AGES\":43398,\"Ġserotonin\":43399,\"ESSION\":43400,\"_______\":43401,\"ĠCollider\":43402,\"auldron\":43403,\"Ġsquee\":43404,\"Control\":43405,\"ffield\":43406,\"cycles\":43407,\"Legal\":43408,\"xa\":43409,\"minimum\":43410,\"ĠGeneric\":43411,\"Circ\":43412,\"Â·\":43413,\"Behind\":43414,\"guide\":43415,\"Ground\":43416,\"roying\":43417,\"ĠGrail\":43418,\"Ġthee\":43419,\"Ġ9000\":43420,\"Batman\":43421,\"Brother\":43422,\"Ġnons\":43423,\"RW\":43424,\"saf\":43425,\"ĠCroat\":43426,\"tainment\":43427,\"sci\":43428,\"Ye\":43429,\"Range\":43430,\"Ey\":43431,\"perature\":43432,\"ĠDracula\":43433,\"oreal\":43434,\"Fighting\":43435,\"Ġreleg\":43436,\"Ġcoupling\":43437,\"Tracker\":43438,\"tyard\":43439,\"Mut\":43440,\"Military\":43441,\"lamm\":43442,\"ittens\":43443,\"ĠCRC\":43444,\"ĠXiang\":43445,\"Ġorthodoxy\":43446,\"ĠGoth\":43447,\"Ġalgorith\":43448,\"ĠAthen\":43449,\"Ġtyrann\":43450,\"ĠTorrent\":43451,\"IDs\":43452,\"ĠGENERAL\":43453,\"ĠASUS\":43454,\"rastructure\":43455,\"Faith\":43456,\"models\":43457,\"rentices\":43458,\"ĠCurse\":43459,\"Ġcalibr\":43460,\"attled\":43461,\"monary\":43462,\"Ġpenet\":43463,\"aclysm\":43464,\"album\":43465,\"Ġremnant\":43466,\"Ġfung\":43467,\"itiveness\":43468,\"thodox\":43469,\"Ġunlocks\":43470,\"Ġprobabilities\":43471,\"Ġster\":43472,\"Ġscrim\":43473,\"Ġanalytic\":43474,\"Urban\":43475,\"âĢĶâĢĶâĢĶâĢĶ\":43476,\"Craft\":43477,\"Ġbrut\":43478,\"1986\":43479,\"Section\":43480,\"raged\":43481,\"arij\":43482,\"Hero\":43483,\"ĠHebdo\":43484,\"ĠEmpress\":43485,\"Ġvivo\":43486,\"ĠPublications\":43487,\"Ġcannabinoids\":43488,\"arrett\":43489,\"Ġbounded\":43490,\"Ġquests\":43491,\"Ġomin\":43492,\"ĠRuler\":43493,\"ĠYue\":43494,\"ridges\":43495,\"Ġpeasants\":43496,\"ĠAlloy\":43497,\"Desk\":43498,\"ULAR\":43499,\"Ġthor\":43500,\"ĠOvers\":43501,\"ĠTome\":43502,\"mk\":43503,\"Ġ1050\":43504,\"Ġshroud\":43505,\"Ġdistribut\":43506,\"weapons\":43507,\"ĠAuthorization\":43508,\"ĠPoke\":43509,\"ĠAlternate\":43510,\"scan\":43511,\"artisan\":43512,\"ĠGems\":43513,\"ĠForums\":43514,\"atonin\":43515,\"viron\":43516,\"Rog\":43517,\"duct\":43518,\"Ġtabletop\":43519,\"crow\":43520,\"/)\":43521,\"ĠStainless\":43522,\"ottest\":43523,\"Ġreborn\":43524,\"anchez\":43525,\"cium\":43526,\"ĠNicarag\":43527,\"elfare\":43528,\"Ġupd\":43529,\"ritic\":43530,\"bm\":43531,\"Ġ608\":43532,\"ĠSlightly\":43533,\"ĠDrops\":43534,\"ISO\":43535,\"ĠiT\":43536,\"xiety\":43537,\"ĠGawker\":43538,\"omination\":43539,\"ĠReached\":43540,\"Student\":43541,\"Drop\":43542,\"MET\":43543,\"ĠKubrick\":43544,\"1950\":43545,\"ĠTuls\":43546,\"Ġcomputed\":43547,\"depending\":43548,\"ĠCosmetic\":43549,\"udget\":43550,\"Lex\":43551,\"icut\":43552,\"ĠDepth\":43553,\"Ġ1893\":43554,\"ahah\":43555,\"Ġath\":43556,\"fights\":43557,\"thia\":43558,\"Ġoccult\":43559,\"Wheel\":43560,\"ĠSega\":43561,\"Ġtheolog\":43562,\"reement\":43563,\")--\":43564,\"Ġunus\":43565,\"ĠGamma\":43566,\"Looks\":43567,\"Ġellipt\":43568,\"Ġairflow\":43569,\"ĠHimself\":43570,\"Ġpagan\":43571,\"ĠRei\":43572,\"Ġpilgr\":43573,\"ĠSubmission\":43574,\"Region\":43575,\"Ġinsertion\":43576,\"Ġsket\":43577,\"Ġsatisfies\":43578,\"ĠPixie\":43579,\"Ġcontempl\":43580,\"abbit\":43581,\"ĠReplay\":43582,\"ĠGalile\":43583,\"ĠGodzilla\":43584,\"Ġarithmetic\":43585,\"iasm\":43586,\"1987\":43587,\"ĠFeminist\":43588,\"Liter\":43589,\"ĠDisable\":43590,\"ouble\":43591,\"essors\":43592,\"Ġfors\":43593,\"Ġensu\":43594,\"Putting\":43595,\"ĠMSM\":43596,\"Cond\":43597,\"emade\":43598,\"Ġindistinguishable\":43599,\"Magn\":43600,\"Ġms\":43601,\"MAL\":43602,\"ĠBF\":43603,\"dm\":43604,\"iltration\":43605,\"irection\":43606,\"ĠSpir\":43607,\"Gb\":43608,\"ĠIbn\":43609,\"Abs\":43610,\"imens\":43611,\"RNA\":43612,\"============\":43613,\"Ġ655\":43614,\"ĠConversion\":43615,\"imilation\":43616,\"igion\":43617,\"ĠSomew\":43618,\"mL\":43619,\"Border\":43620,\"Ë\":43621,\"Factor\":43622,\"Number\":43623,\"Ġejac\":43624,\"Cho\":43625,\"Ġrighteousness\":43626,\"ĠPATH\":43627,\"ĠElys\":43628,\"ouched\":43629,\"Ġmultic\":43630,\"Ġfaculties\":43631,\"ĠEarthquake\":43632,\"ĠReferences\":43633,\"ensitive\":43634,\"Ġimpat\":43635,\"Ġ................\":43636,\"buff\":43637,\"Ġ1895\":43638,\"colo\":43639,\"Vi\":43640,\"Ġubiqu\":43641,\"ĠChev\":43642,\"Fish\":43643,\"ĠBlueprint\":43644,\"CHQ\":43645,\"Ġlinem\":43646,\"ĠFlavor\":43647,\"Ġcrimson\":43648,\"ĠAbstract\":43649,\"arette\":43650,\"plete\":43651,\"ranean\":43652,\"Dash\":43653,\"Ġdimensional\":43654,\"Cub\":43655,\"ttle\":43656,\"ĠDSM\":43657,\"Ġinstantaneous\":43658,\"esy\":43659,\"Ġepoch\":43660,\"Brit\":43661,\"ĠÎ\":43662,\"ECD\":43663,\"Ġwarp\":43664,\"obyl\":43665,\"ubric\":43666,\"Ġutilitarian\":43667,\"Ġsummarizes\":43668,\"letal\":43669,\"Ord\":43670,\"opath\":43671,\"tained\":43672,\"ghai\":43673,\"Ġwhis\":43674,\"insert\":43675,\"Ġphon\":43676,\"rils\":43677,\"Ġearthly\":43678,\"ĠAlic\":43679,\"ĠPCIe\":43680,\"Ġfurthermore\":43681,\"ocard\":43682,\"Ġuter\":43683,\"ĠAdmin\":43684,\"ographics\":43685,\"ĠConstantin\":43686,\"gravity\":43687,\"iPhone\":43688,\"Ġwasteland\":43689,\"Ġfps\":43690,\"Tip\":43691,\"Ġmurm\":43692,\"paces\":43693,\"ĠSamurai\":43694,\"ĠFOIA\":43695,\"ĠRadiant\":43696,\"ĠUnreal\":43697,\"Ġmicrow\":43698,\"usterity\":43699,\"zyme\":43700,\"itbart\":43701,\"metadata\":43702,\"Dat\":43703,\"ĠMoons\":43704,\"ĠProtestants\":43705,\"ungle\":43706,\"Ġvideog\":43707,\"pid\":43708,\"Ġdisple\":43709,\"aucus\":43710,\"Ġcoils\":43711,\"ĠDwar\":43712,\"fixed\":43713,\"Alice\":43714,\"Ġgarrison\":43715,\"ĠVelocity\":43716,\"ĠJehovah\":43717,\"Ġfascists\":43718,\"ĠCHO\":43719,\"jl\":43720,\"Ġmetaphors\":43721,\"ĠSiege\":43722,\"scientific\":43723,\"Ä«\":43724,\"Slow\":43725,\"hex\":43726,\"ĠBlaz\":43727,\"mediated\":43728,\"esthesia\":43729,\"ĠAvg\":43730,\"Ġbelie\":43731,\"Carter\":43732,\"Ġexposition\":43733,\"azeera\":43734,\"dial\":43735,\"Ġbask\":43736,\"Scale\":43737,\"Ġdisob\":43738,\"Ġgore\":43739,\"Ġhypocr\":43740,\"Ġphantom\":43741,\"ĠSynd\":43742,\"BLIC\":43743,\"pter\":43744,\"ĠScorpion\":43745,\"eor\":43746,\"ĠRecover\":43747,\"Ġsummoning\":43748,\"Ġorb\":43749,\"jump\":43750,\"Ġ768\":43751,\"ĠEnix\":43752,\"Spons\":43753,\",...\":43754,\"Wide\":43755,\"Ġparse\":43756,\"Ġdebtor\":43757,\"Ġpathological\":43758,\"Ġserpent\":43759,\"ĠFranÃ§\":43760,\"reetings\":43761,\"Ġdeletion\":43762,\"Ġvolunt\":43763,\"ĠNotification\":43764,\"liga\":43765,\"Disk\":43766,\"Account\":43767,\"1979\":43768,\"Ġsymmetry\":43769,\"ĠBearing\":43770,\"ĠABV\":43771,\"ĠORDER\":43772,\"rpm\":43773,\"ĠFuck\":43774,\"?!\\\"\":43775,\"mask\":43776,\"Grade\":43777,\"neath\":43778,\"ocom\":43779,\"Detect\":43780,\"ryption\":43781,\"ĠAura\":43782,\"Ġinert\":43783,\"PLAY\":43784,\"gres\":43785,\"INTON\":43786,\"Deal\":43787,\"fficient\":43788,\"ĠVoid\":43789,\"gement\":43790,\"Ġscorp\":43791,\"Ġreincarn\":43792,\"ĠVapor\":43793,\"Ġ1840\":43794,\"Yellow\":43795,\"......\":43796,\"Ġparameter\":43797,\"ĠDISTR\":43798,\"ĠForgotten\":43799,\"Eat\":43800,\"izational\":43801,\"Witness\":43802,\"ĠDupl\":43803,\"Ġdogma\":43804,\"Ġzipper\":43805,\"ĠZeus\":43806,\"mage\":43807,\"ormal\":43808,\"Ġ\\\".\":43809,\"Ġecc\":43810,\"ĠSlot\":43811,\"ĠRegist\":43812,\"Others\":43813,\"VID\":43814,\"Windows\":43815,\"Ġshitty\":43816,\"ĠLethal\":43817,\"Monster\":43818,\"ĠExpression\":43819,\"tx\":43820,\"ythm\":43821,\"Were\":43822,\"ivalry\":43823,\"atcher\":43824,\"ĠFormat\":43825,\"ĠPlasma\":43826,\"Phys\":43827,\"laugh\":43828,\"Fu\":43829,\"java\":43830,\"roma\":43831,\"ĠIncreases\":43832,\"Ġlicensee\":43833,\"Ġmystic\":43834,\"Ġproto\":43835,\"ĠLoki\":43836,\"forcing\":43837,\"hots\":43838,\"Ġ->\":43839,\"Outside\":43840,\"ĠEndless\":43841,\"Ġachie\":43842,\"ĠTurtles\":43843,\"Ġconvin\":43844,\"JUST\":43845,\"Ġimmobil\":43846,\"ĠCauses\":43847,\"Ġclich\":43848,\"xes\":43849,\"ffiti\":43850,\"Ġhypot\":43851,\"Bat\":43852,\"Ġbigot\":43853,\"Personal\":43854,\"ĠPharmac\":43855,\"Lot\":43856,\"VERT\":43857,\"Ġbapt\":43858,\"idelines\":43859,\"Ġprox\":43860,\"MAP\":43861,\"Spirit\":43862,\"ĠSlug\":43863,\"Ġebook\":43864,\"eches\":43865,\"ĠAndromeda\":43866,\"Ġceremon\":43867,\"1975\":43868,\"PRE\":43869,\"Ġasshole\":43870,\"linear\":43871,\"Nevertheless\":43872,\"Ġwillpower\":43873,\"azel\":43874,\"Fif\":43875,\"andise\":43876,\"Ġextravag\":43877,\"ĠBuffy\":43878,\"Ġcorrelations\":43879,\"ptr\":43880,\"Progress\":43881,\"shape\":43882,\"ĠSymbol\":43883,\"arag\":43884,\"ĠContext\":43885,\"ucer\":43886,\"1983\":43887,\"ĠMyster\":43888,\"Pain\":43889,\"Login\":43890,\"mbol\":43891,\"codes\":43892,\"RANT\":43893,\"Ġoverse\":43894,\"opot\":43895,\"STEM\":43896,\"enser\":43897,\"ĠCosmic\":43898,\"Spl\":43899,\"ritional\":43900,\"ĠPharaoh\":43901,\"ĠRemix\":43902,\"xon\":43903,\"ĠXII\":43904,\"Ġunman\":43905,\"Ġimmedi\":43906,\"Ġmonog\":43907,\"ĠLX\":43908,\"Ġabstraction\":43909,\"ocolate\":43910,\"ĠDonkey\":43911,\"Ġ!!\":43912,\"ĠLIA\":43913,\"shed\":43914,\"rules\":43915,\"Ġcalc\":43916,\"ĠAutob\":43917,\"anmar\":43918,\"eworks\":43919,\"notations\":43920,\"Ġtenancy\":43921,\"ĠPetraeus\":43922,\"dp\":43923,\"amphetamine\":43924,\"ĠCortex\":43925,\"rw\":43926,\"Ġprojectile\":43927,\"Ġintrinsically\":43928,\"Route\":43929,\"Ġnegoti\":43930,\"anuts\":43931,\"Analysis\":43932,\"redits\":43933,\"ĠGG\":43934,\"thread\":43935,\"ĠChosen\":43936,\"Years\":43937,\"otyp\":43938,\"ĠNCT\":43939,\"udic\":43940,\"ochemical\":43941,\"Neigh\":43942,\"Ġfishes\":43943,\"ĠFloat\":43944,\"Print\":43945,\"okia\":43946,\"Ġbarb\":43947,\"quote\":43948,\"Lew\":43949,\"Ġannoun\":43950,\"istors\":43951,\"Reading\":43952,\"ACTION\":43953,\"Ġintakes\":43954,\"ĠBeet\":43955,\"matter\":43956,\"Swe\":43957,\"Ther\":43958,\"Ġtyrant\":43959,\"ĠPsycho\":43960,\"ĠDestroy\":43961,\"Ġesoteric\":43962,\"Ġbiom\":43963,\"idious\":43964,\"Merc\":43965,\"hran\":43966,\"ĠBaal\":43967,\"seconds\":43968,\"Ġsuperhuman\":43969,\"ancel\":43970,\"Ġworshipped\":43971,\"Ġwebs\":43972,\"Ġviolet\":43973,\"ĠMetallic\":43974,\"eday\":43975,\"ordering\":43976,\"Nut\":43977,\"Ġconstructs\":43978,\"olescent\":43979,\"Unit\":43980,\"otypes\":43981,\"Ġembryonic\":43982,\"perm\":43983,\"Nature\":43984,\"ĠDecre\":43985,\"levant\":43986,\"Ġss\":43987,\"+(\":43988,\"ĠDoctrine\":43989,\"puters\":43990,\"Ġsaline\":43991,\"orsche\":43992,\"1111\":43993,\"values\":43994,\"Ġutopian\":43995,\"ĠBooster\":43996,\"Technical\":43997,\"ì\":43998,\"ĠLIMITED\":43999,\"nir\":44000,\"Ġclones\":44001,\"Performance\":44002,\"aple\":44003,\"Ġshudder\":44004,\"Ġcontempor\":44005,\"lator\":44006,\"ĠOops\":44007,\"Ġammon\":44008,\"Ġdavid\":44009,\"Ġbom\":44010,\"bish\":44011,\"Ġdetectable\":44012,\"Ġmultiplying\":44013,\"Ġreddit\":44014,\"Prim\":44015,\"Ġmedial\":44016,\"Ġsubstrate\":44017,\"ĠSanskrit\":44018,\"Spect\":44019,\"ĠMagical\":44020,\"Ġarcane\":44021,\"align\":44022,\"Ġ1861\":44023,\"Ġneocons\":44024,\"Ì\":44025,\"ĠBounty\":44026,\"ĠContinent\":44027,\"Ġhurd\":44028,\"alions\":44029,\"Ġgeneralized\":44030,\"ĠInsect\":44031,\"Ġsimul\":44032,\"actual\":44033,\"advert\":44034,\"ukong\":44035,\"Resp\":44036,\"ĠWarcraft\":44037,\"Hunter\":44038,\"hyper\":44039,\"ĠBreach\":44040,\"ught\":44041,\"Ġcomputation\":44042,\"react\":44043,\"Feel\":44044,\"ĠCheong\":44045,\"Ġslut\":44046,\"Ġgalactic\":44047,\"Ġtaunt\":44048,\"Enjoy\":44049,\"Ġreprinted\":44050,\"Word\":44051,\"ĠHandbook\":44052,\"amins\":44053,\"exit\":44054,\"Wo\":44055,\"Ġadherents\":44056,\"Counter\":44057,\"ĠNode\":44058,\"ĠTwisted\":44059,\"Ġgrinned\":44060,\"universal\":44061,\"ĠAmon\":44062,\"Ġaster\":44063,\"ĠEquip\":44064,\"!\\\".\":44065,\"Ġanalogous\":44066,\"rients\":44067,\"alky\":44068,\"ĠQian\":44069,\"Ġspont\":44070,\"docs\":44071,\"Ġcontemplation\":44072,\"Ġrevolutionaries\":44073,\"Ġpreset\":44074,\"ĠAmendments\":44075,\"Ġexecutes\":44076,\"ĠDuration\":44077,\"Ġcompulsion\":44078,\"Ġstagger\":44079,\"ynamic\":44080,\"blem\":44081,\"];\":44082,\"Higher\":44083,\"Balt\":44084,\"heast\":44085,\"Ġcorp\":44086,\"awei\":44087,\"Motion\":44088,\"Mis\":44089,\"Ġadventurer\":44090,\"eger\":44091,\"Ġarsen\":44092,\"ĠVoltage\":44093,\"ĠEVENTS\":44094,\"Salt\":44095,\"issance\":44096,\"DK\":44097,\"Ship\":44098,\"Ġunwitting\":44099,\"Ton\":44100,\"ĠPROGRAM\":44101,\"Ġtentacles\":44102,\"erness\":44103,\"thirst\":44104,\"Fig\":44105,\"fty\":44106,\"ĠTolkien\":44107,\"Sleep\":44108,\"ĠExplain\":44109,\"Pub\":44110,\"ĠBounce\":44111,\"ĠDemo\":44112,\"Ġ1897\":44113,\"ĠSPI\":44114,\"intern\":44115,\"********\":44116,\"ĠKills\":44117,\"ĠZombies\":44118,\"Single\":44119,\"ratom\":44120,\"ĠClaw\":44121,\"hid\":44122,\"asel\":44123,\"Shock\":44124,\"erential\":44125,\"Ġupgr\":44126,\"holy\":44127,\"Ġ\\\\\":44128,\"aghetti\":44129,\"Ġthence\":44130,\"genic\":44131,\"papers\":44132,\"1982\":44133,\"ravel\":44134,\"ĠUNIVERS\":44135,\"Charge\":44136,\"ĠDelay\":44137,\"ibrary\":44138,\"ĠHDD\":44139,\"olson\":44140,\"Ġenchanted\":44141,\"Wr\":44142,\"graph\":44143,\"Ġcorro\":44144,\"ept\":44145,\"etsu\":44146,\"ĠQin\":44147,\"Û\":44148,\"Ġantidepressant\":44149,\"ĠCerberus\":44150,\"Ġappe\":44151,\"ĠDEFENSE\":44152,\"Ġdysph\":44153,\"split\":44154,\"zilla\":44155,\"attr\":44156,\"Clar\":44157,\"Äĵ\":44158,\"hov\":44159,\"IRC\":44160,\"hibition\":44161,\"'/\":44162,\"ĠURLs\":44163,\"Draft\":44164,\"Prep\":44165,\"ĠLanguages\":44166,\"ĠTravels\":44167,\"ceiver\":44168,\"aturally\":44169,\"pair\":44170,\"ĠALWAYS\":44171,\"aaaa\":44172,\"ĠTenth\":44173,\"ĠNAD\":44174,\"Serv\":44175,\"ĠUID\":44176,\"cens\":44177,\"ĠLearned\":44178,\"Ġtraject\":44179,\"Ġmoaning\":44180,\"ĠNare\":44181,\"Ġingen\":44182,\"Ġsurn\":44183,\"Ġfloppy\":44184,\"breeding\":44185,\"uph\":44186,\"rossover\":44187,\"Understanding\":44188,\"Glass\":44189,\"Ġruntime\":44190,\"gp\":44191,\"Ġâľĵ\":44192,\"Ġcyt\":44193,\"bley\":44194,\"agall\":44195,\"Ġunworthy\":44196,\"otine\":44197,\"Ġchromosome\":44198,\"utters\":44199,\"ĠÂµ\":44200,\"Ġexpans\":44201,\"Ġdement\":44202,\"Ġinsurrection\":44203,\"Ġsurviv\":44204,\"genre\":44205,\"ospital\":44206,\"ĠPlato\":44207,\"ĠTrigger\":44208,\"selection\":44209,\"ilege\":44210,\"Ġsegreg\":44211,\"itizens\":44212,\"ĠRAID\":44213,\"Pure\":44214,\"hetti\":44215,\"ĠFailed\":44216,\"ĠCharacters\":44217,\"ĠCreep\":44218,\"akra\":44219,\"Ec\":44220,\"ĠAristotle\":44221,\"Lim\":44222,\"error\":44223,\"yrus\":44224,\"umably\":44225,\">>\":44226,\"Ġtsun\":44227,\"knowledge\":44228,\"Cert\":44229,\"bable\":44230,\"hesion\":44231,\"ĠProcedures\":44232,\"Ġmarkup\":44233,\"ideo\":44234,\"Ġrhet\":44235,\"ĠChapters\":44236,\"ĠChecking\":44237,\"mega\":44238,\"Ġphotons\":44239,\"required\":44240,\"Unknown\":44241,\"ĠDrawn\":44242,\"Ġvari\":44243,\"EEK\":44244,\"Ġcompuls\":44245,\"Ġcloning\":44246,\"ccoli\":44247,\"Ġ1070\":44248,\"Ġkindred\":44249,\"Ġdiscl\":44250,\"ĠCind\":44251,\"Collect\":44252,\"Ġchromosomes\":44253,\"phant\":44254,\"ĠKafka\":44255,\"Ġeverlasting\":44256,\"Ġmercenary\":44257,\"ĠHmm\":44258,\"----\":44259,\"riber\":44260,\"Ġdoubtless\":44261,\"Ġsusceptibility\":44262,\"beta\":44263,\"notice\":44264,\"Ġcrochet\":44265,\"Ġrespir\":44266,\"Ġphilosophers\":44267,\"ĠExtras\":44268,\"Ġseparat\":44269,\"shown\":44270,\"iblings\":44271,\"Hispanic\":44272,\"copy\":44273,\"Tang\":44274,\"Knight\":44275,\"Ġpursu\":44276,\"ĠAnime\":44277,\"Ġlipid\":44278,\"ggies\":44279,\"levels\":44280,\"phalt\":44281,\"ĠCompleted\":44282,\"bral\":44283,\"Ġcerv\":44284,\"ĠAfric\":44285,\"ĠPhar\":44286,\"Color\":44287,\"ogene\":44288,\"ĠCompan\":44289,\"memory\":44290,\"Dust\":44291,\"ĠXIV\":44292,\"ĠConsole\":44293,\"').\":44294,\"Ġ1888\":44295,\"byn\":44296,\"Ġpolygamy\":44297,\"Auth\":44298,\"BUT\":44299,\"istine\":44300,\"Ġsacr\":44301,\"Ġabsor\":44302,\"ijah\":44303,\"ĠNeural\":44304,\"olester\":44305,\"ql\":44306,\"Already\":44307,\"Creating\":44308,\"ĠStarg\":44309,\"ĠPhilos\":44310,\"Consider\":44311,\"Ġrepositories\":44312,\"cludes\":44313,\"ĠBuffer\":44314,\"ĠPerspect\":44315,\"Ġcomput\":44316,\"Stew\":44317,\"iamond\":44318,\"ĠJudgment\":44319,\"OVA\":44320,\"angible\":44321,\"Ġoxid\":44322,\"Ġepigen\":44323,\"Ġsidel\":44324,\"ĠEag\":44325,\"devices\":44326,\"icone\":44327,\"1920\":44328,\"atism\":44329,\"beard\":44330,\"ĠGujar\":44331,\"ĠPlaystation\":44332,\"Ġglances\":44333,\"ĠCOMPLE\":44334,\"VERTIS\":44335,\"ukemia\":44336,\"Edit\":44337,\"Tickets\":44338,\"Square\":44339,\"ĠSerpent\":44340,\"Ġtransporter\":44341,\"MQ\":44342,\"ĠMongo\":44343,\"1967\":44344,\"ibaba\":44345,\"Ġtimet\":44346,\"sylvania\":44347,\"Latin\":44348,\"osaurs\":44349,\"Ġhumanoid\":44350,\"Ġcannabinoid\":44351,\"Ġdisciple\":44352,\"Psych\":44353,\"Ġimpro\":44354,\"Ġmc\":44355,\"Raid\":44356,\"Letter\":44357,\"ificant\":44358,\"ĠPortug\":44359,\"ĠFreem\":44360,\"Ġappell\":44361,\"ĠMushroom\":44362,\"Ġclans\":44363,\"Ġsinful\":44364,\"Ġingestion\":44365,\"ĠDirectory\":44366,\"abetic\":44367,\"Ġantigen\":44368,\"Ġimagin\":44369,\"mitter\":44370,\"!!!!!\":44371,\"ĠDPR\":44372,\"leness\":44373,\"\\\":\\\"\\\",\\\"\":44374,\"ĠAUTHOR\":44375,\"Ġgrunt\":44376,\"Ġflickering\":44377,\"Cath\":44378,\"asury\":44379,\"Ġnozzle\":44380,\"Secure\":44381,\"Stre\":44382,\"ĠBIT\":44383,\"Ġdeviations\":44384,\"Professor\":44385,\"bilt\":44386,\"ĠConscious\":44387,\"Ġinterrupts\":44388,\"ĠMormons\":44389,\"ĠCutter\":44390,\"Bed\":44391,\"ipient\":44392,\"ĠGhostbusters\":44393,\"Cart\":44394,\"endas\":44395,\"ĠExecution\":44396,\"ycle\":44397,\"Ġwedd\":44398,\"Sold\":44399,\"Ġvanquished\":44400,\"Regarding\":44401,\"Depending\":44402,\"']\":44403,\"atron\":44404,\"oidal\":44405,\"Cube\":44406,\"Studio\":44407,\":/\":44408,\"ĠExplosion\":44409,\"activate\":44410,\"pport\":44411,\"fuck\":44412,\"Whe\":44413,\"Ġsmir\":44414,\"Ġwidgets\":44415,\"urses\":44416,\"izard\":44417,\")*\":44418,\"icho\":44419,\"ĠVersus\":44420,\"ĠIntroduced\":44421,\"osaurus\":44422,\"1977\":44423,\"forum\":44424,\"Gray\":44425,\"Program\":44426,\"righteous\":44427,\"endum\":44428,\"ĠScare\":44429,\"Ġresists\":44430,\"*)\":44431,\"ĠCombo\":44432,\"Ġsockets\":44433,\"Ġaston\":44434,\"LAB\":44435,\"Ġmutated\":44436,\"eworld\":44437,\"DEF\":44438,\"Trend\":44439,\"âĢĶ-\":44440,\"Ġpropagation\":44441,\"Ġemancipation\":44442,\"collection\":44443,\"ĠDifferences\":44444,\"Tweet\":44445,\"Ġmajesty\":44446,\")...\":44447,\"sylv\":44448,\"Ġadapters\":44449,\"Ġmilliseconds\":44450,\"Jews\":44451,\"ĠPatreon\":44452,\"phasis\":44453,\"ĠHTTP\":44454,\"onnaissance\":44455,\"ENDED\":44456,\"ĠIntro\":44457,\"qs\":44458,\"Ġsuperflu\":44459,\"*.\":44460,\"Ġminions\":44461,\"ĠStupid\":44462,\"Ġspecialization\":44463,\"ĠPikachu\":44464,\"Ġappellant\":44465,\"Training\":44466,\"circle\":44467,\"Interest\":44468,\"Ġfallacy\":44469,\"ĠDinosaur\":44470,\"ĠTHEM\":44471,\"Ġdirectories\":44472,\"Ġmasturbation\":44473,\"ĠStain\":44474,\"1978\":44475,\"odied\":44476,\"Ġexqu\":44477,\"ĠRats\":44478,\"swick\":44479,\"Ġemptiness\":44480,\"ĠXeon\":44481,\"Ġthereto\":44482,\"ĠEngels\":44483,\"ĠSupplement\":44484,\"Chan\":44485,\"Ġundead\":44486,\"ĠNoct\":44487,\"erest\":44488,\"ĠQuery\":44489,\"ĠSOLD\":44490,\"thritis\":44491,\"ĠEncounter\":44492,\"Ġvectors\":44493,\"Econom\":44494,\"Rogue\":44495,\"Ġgelatin\":44496,\"Rot\":44497,\"Flickr\":44498,\"Ġcaching\":44499,\"Ġloader\":44500,\"ĠELE\":44501,\"Ġcamoufl\":44502,\"Commission\":44503,\"Ġ1886\":44504,\"Ġcombos\":44505,\"ĠAwakening\":44506,\"Ġfeudal\":44507,\"Ġasses\":44508,\"ASY\":44509,\"atalie\":44510,\"Ġpanties\":44511,\"ĠMono\":44512,\"selves\":44513,\"Download\":44514,\"Ġvampires\":44515,\"------\":44516,\"ishop\":44517,\"User\":44518,\"Ġimperialist\":44519,\"ĠGOODMAN\":44520,\"1973\":44521,\"Vel\":44522,\"Struct\":44523,\"ĠUFOs\":44524,\"drivers\":44525,\"ĠOptional\":44526,\"uably\":44527,\"ĠPrinciple\":44528,\"verett\":44529,\"taining\":44530,\"Ġ1889\":44531,\"ĠCommunism\":44532,\"auder\":44533,\"Keys\":44534,\"lore\":44535,\"ĠMedieval\":44536,\"Hyd\":44537,\"weapon\":44538,\"Register\":44539,\"ĠHighlander\":44540,\"ĠRFC\":44541,\"Demon\":44542,\"ardless\":44543,\"ĠOrche\":44544,\"Kick\":44545,\"pixel\":44546,\"address\":44547,\"OUP\":44548,\"Brain\":44549,\"ĠMorph\":44550,\"bash\":44551,\"ĠANG\":44552,\"ĠIdle\":44553,\"ĠLucifer\":44554,\"Ġcorrelates\":44555,\"Ġgazed\":44556,\"colm\":44557,\"ĠKard\":44558,\"Solar\":44559,\"ĠVariable\":44560,\"ĠPACK\":44561,\"Ġfuzz\":44562,\"Ġanonym\":44563,\"ĠECO\":44564,\"feature\":44565,\"ĠEsports\":44566,\"ĠAnthropology\":44567,\"cise\":44568,\"manac\":44569,\"ĠSupports\":44570,\"rists\":44571,\"Quant\":44572,\"istical\":44573,\"çļĦ\":44574,\"Ġdexterity\":44575,\"monster\":44576,\"ordial\":44577,\"Mob\":44578,\"DEC\":44579,\"ĠConj\":44580,\"entric\":44581,\"1981\":44582,\"ECTION\":44583,\"ietal\":44584,\"ĠUses\":44585,\"ĠArmageddon\":44586,\"ĠCapitalism\":44587,\"Ub\":44588,\"iazep\":44589,\"helps\":44590,\"ouls\":44591,\"grim\":44592,\"ĠEthiop\":44593,\"tesy\":44594,\"Ġclipboard\":44595,\"Ġchimpanzees\":44596,\"PLIC\":44597,\"Sexual\":44598,\"wallet\":44599,\"ĠRect\":44600,\"ocytes\":44601,\"ĠHels\":44602,\"lace\":44603,\"Damn\":44604,\"Ġblasp\":44605,\"ildo\":44606,\"ĠRober\":44607,\"APD\":44608,\"ĠWCS\":44609,\"ippery\":44610,\"ellectual\":44611,\"Ġ$(\":44612,\"Ġuniverses\":44613,\"Ġholster\":44614,\"Ġshading\":44615,\"Ġinflic\":44616,\"else\":44617,\"ĠShiny\":44618,\"ĠAVG\":44619,\"Lower\":44620,\"ĠMayhem\":44621,\"Originally\":44622,\"Crypt\":44623,\"SHARE\":44624,\"ĠBeir\":44625,\"!:\":44626,\"Ġrepentance\":44627,\"WHAT\":44628,\".......\":44629,\"Ġauditory\":44630,\"aaa\":44631,\"ĠLoot\":44632,\"ciples\":44633,\"Ġcontem\":44634,\"Ġphoton\":44635,\"æľ\":44636,\"omach\":44637,\"ĠWhedon\":44638,\"ĠValid\":44639,\"asonable\":44640,\"pha\":44641,\"assad\":44642,\"ĠPse\":44643,\"Heat\":44644,\"Ġplugins\":44645,\"Ġclenched\":44646,\"ĠAmeric\":44647,\"transform\":44648,\"ĠEnh\":44649,\"agnetic\":44650,\"usalem\":44651,\"sych\":44652,\"Wed\":44653,\"replace\":44654,\"ĠKinect\":44655,\"shield\":44656,\"Sax\":44657,\"ividually\":44658,\"Ġfunctionally\":44659,\"Ġ:)\":44660,\"typically\":44661,\"Opening\":44662,\"Fa\":44663,\"ĠSELECT\":44664,\"Ġsamurai\":44665,\"Ġhorde\":44666,\"entle\":44667,\"sth\":44668,\"Changes\":44669,\"Pin\":44670,\"ithing\":44671,\"illance\":44672,\"ĠEmblem\":44673,\"ĠMicha\":44674,\"crypt\":44675,\"ĠObjective\":44676,\"ophys\":44677,\"Ġavg\":44678,\"poon\":44679,\"Ġreadable\":44680,\"ĠRx\":44681,\"allel\":44682,\"Sit\":44683,\"gom\":44684,\"ureau\":44685,\"ĠDoodle\":44686,\"Ġdungeon\":44687,\"($\":44688,\"Nintendo\":44689,\"\\\"],\\\"\":44690,\"Notes\":44691,\"Grab\":44692,\"Prosecutors\":44693,\"Advanced\":44694,\"Ġ1862\":44695,\"ĠVeter\":44696,\"Ġjurisd\":44697,\"ĠLauncher\":44698,\"Catal\":44699,\"udder\":44700,\"Ġresidues\":44701,\"Ġregress\":44702,\"ĠConquer\":44703,\"osal\":44704,\"ĠDice\":44705,\"************\":44706,\"braska\":44707,\"ipolar\":44708,\"Ġathe\":44709,\"bringing\":44710,\"Suddenly\":44711,\"ĠIEEE\":44712,\"verbs\":44713,\"Ġdelet\":44714,\"ipeg\":44715,\"Previous\":44716,\"]\\\"\":44717,\"Ġsidebar\":44718,\"illac\":44719,\"Property\":44720,\"Î±\":44721,\"REP\":44722,\"Ġauthenticated\":44723,\"gypt\":44724,\"uilding\":44725,\"ĠGing\":44726,\"Ġwart\":44727,\"Birth\":44728,\"Ġobedient\":44729,\"ĠXuan\":44730,\"ĠTYPE\":44731,\"Ġinhibits\":44732,\"1972\":44733,\"humans\":44734,\"IENT\":44735,\"Ġyoutube\":44736,\"Shortly\":44737,\"ophen\":44738,\"ĠWinc\":44739,\"ĠWrit\":44740,\"AUD\":44741,\"ĠHobbit\":44742,\"emphasis\":44743,\"ĠWonders\":44744,\"Ġtwitch\":44745,\"ĠProphe\":44746,\"Berry\":44747,\"ĠGinny\":44748,\"ĠBurst\":44749,\"ĠGenerator\":44750,\"Ġepile\":44751,\"ĠBalanced\":44752,\"GPU\":44753,\"maps\":44754,\"Ġneurotrans\":44755,\"ĠIRC\":44756,\"Ġ\\\"$\":44757,\"Create\":44758,\"Particip\":44759,\"ĠMarxism\":44760,\"Ġthou\":44761,\"ĠMortal\":44762,\"Ġï¿½\":44763,\"Ġninja\":44764,\"inburgh\":44765,\"Ġappro\":44766,\"ĠPistol\":44767,\"Jar\":44768,\"Ġprophes\":44769,\"classes\":44770,\"Ġanarchist\":44771,\"Ġextant\":44772,\"message\":44773,\"itaire\":44774,\"Ġ1863\":44775,\"ĠProl\":44776,\"Ġpropell\":44777,\"Ġimpossibility\":44778,\"Ġpropos\":44779,\"itamin\":44780,\"Rating\":44781,\"olphin\":44782,\"Ġmitochond\":44783,\"versions\":44784,\"Liberal\":44785,\"ishy\":44786,\"Ġspherical\":44787,\"ĠSurvive\":44788,\"FREE\":44789,\"rawler\":44790,\"Metal\":44791,\"ĠStarship\":44792,\"Ġ=================================================================\":44793,\"ĠDharma\":44794,\"ĠSeller\":44795,\"Ġwrapper\":44796,\"Experience\":44797,\"Integ\":44798,\"Customer\":44799,\"hammad\":44800,\"Ġunanim\":44801,\"Jenn\":44802,\"Ġschizophren\":44803,\"agree\":44804,\"ĠEVENT\":44805,\"Shell\":44806,\"Ġfractions\":44807,\"1968\":44808,\"Ġextermination\":44809,\"ĠSniper\":44810,\"Ġpronoun\":44811,\"ĠHitman\":44812,\"xp\":44813,\"resource\":44814,\"WIND\":44815,\"Ġhierarchical\":44816,\"Ġted\":44817,\"Changing\":44818,\"Ġplaus\":44819,\"Transform\":44820,\"Ġbicy\":44821,\"imentary\":44822,\"Fuck\":44823,\"Mini\":44824,\"Ġoverc\":44825,\"ĠOptimus\":44826,\"outer\":44827,\"helial\":44828,\"akening\":44829,\"fx\":44830,\"Ġnig\":44831,\"Ġ+/-\":44832,\"ĠVICE\":44833,\"Ġnm\":44834,\"1976\":44835,\"ĠRitual\":44836,\"ĠTyrann\":44837,\"Ġscriptures\":44838,\"inical\":44839,\"ĠNull\":44840,\"ourgeois\":44841,\"dra\":44842,\"Ġpious\":44843,\"Ġneuron\":44844,\"Ġcolonists\":44845,\"ĠNebula\":44846,\"apply\":44847,\"Sah\":44848,\"Marx\":44849,\"Ġhypotheses\":44850,\"notation\":44851,\"acists\":44852,\"Math\":44853,\"Manager\":44854,\"Library\":44855,\"audi\":44856,\"Ġmp\":44857,\"ergic\":44858,\"Ġwizards\":44859,\"fw\":44860,\"DVD\":44861,\"ĠScala\":44862,\"Different\":44863,\"ampoo\":44864,\"ĠDread\":44865,\"abbage\":44866,\"Rus\":44867,\"ĠDumbledore\":44868,\"keleton\":44869,\"elsh\":44870,\"esian\":44871,\"ĠCorsair\":44872,\"Tier\":44873,\"ĠCelest\":44874,\"Ġnoun\":44875,\"Ġlucid\":44876,\"requisites\":44877,\"Ġgenus\":44878,\"Event\":44879,\"1974\":44880,\"ĠSatanic\":44881,\"iox\":44882,\"ĠHandle\":44883,\"ĠDestroyer\":44884,\"Ġinvocation\":44885,\"ĠXD\":44886,\"modified\":44887,\"Gam\":44888,\"ĠRPC\":44889,\"Ġsubsystem\":44890,\"Compared\":44891,\"odan\":44892,\"ĠPassive\":44893,\"ĠHelmet\":44894,\"nutrition\":44895,\"riction\":44896,\"HOW\":44897,\"Jess\":44898,\"Ġpiston\":44899,\"imately\":44900,\"Ġhypoc\":44901,\"ĠCelestial\":44902,\"MRI\":44903,\"Ġcompiler\":44904,\"ĠBadge\":44905,\"ĠRevelation\":44906,\"Ġintrig\":44907,\"Grad\":44908,\"ĠSPACE\":44909,\"Poly\":44910,\"ĠVul\":44911,\"Ġtrembling\":44912,\"Ġindepend\":44913,\"doctor\":44914,\"Certain\":44915,\"emet\":44916,\"Password\":44917,\"Ġgasped\":44918,\"Ġpronunciation\":44919,\"Fuel\":44920,\"ĠSPEC\":44921,\"assets\":44922,\"Extra\":44923,\"Ġformatting\":44924,\"Ġmods\":44925,\"\\\"!\":44926,\"akedown\":44927,\"Ġcircuitry\":44928,\"ĠTRUE\":44929,\"ĠVeil\":44930,\"Ġsighed\":44931,\"Charg\":44932,\"eals\":44933,\"Ġworkaround\":44934,\"Ġank\":44935,\"ĠScrolls\":44936,\"Ġdiffusion\":44937,\"Ġamps\":44938,\"ĠTempest\":44939,\"adata\":44940,\"Ġphenomen\":44941,\"Ġ???\":44942,\"Ġpopup\":44943,\"Ġinhibition\":44944,\"Ġaliases\":44945,\"erity\":44946,\"agraph\":44947,\"Jew\":44948,\"Ġbec\":44949,\"Classic\":44950,\"comment\":44951,\"usable\":44952,\"rodu\":44953,\"ĠEnlightenment\":44954,\"Ġinvis\":44955,\"Ġbiochemical\":44956,\"latest\":44957,\"ĠGMOs\":44958,\"ĠSocialism\":44959,\"Ġpollut\":44960,\"Ġeluc\":44961,\"Js\":44962,\"orthern\":44963,\"PDATED\":44964,\"alyses\":44965,\"Experts\":44966,\"Blog\":44967,\"ĠDemocr\":44968,\"etooth\":44969,\"pause\":44970,\"âĢ¢âĢ¢\":44971,\"ĠShinji\":44972,\"Ġdystop\":44973,\"Sources\":44974,\"ĠBrach\":44975,\"np\":44976,\"ĠXY\":44977,\"Ġneurot\":44978,\"assembly\":44979,\"Ġbourgeois\":44980,\"ĠReson\":44981,\"ĠIDE\":44982,\"Ġrecoil\":44983,\"raq\":44984,\"ĠAvenger\":44985,\"Paper\":44986,\"UTF\":44987,\"ĠWrest\":44988,\"ĠSimulation\":44989,\"elaide\":44990,\"ĠDMCA\":44991,\"utm\":44992,\"1963\":44993,\"Ġarcs\":44994,\"Ġmaximal\":44995,\"Ġcyl\":44996,\"Ġphilosoph\":44997,\"enium\":44998,\"Ġrelativity\":44999,\"ĠMacintosh\":45000,\"Ġpneum\":45001,\"LOC\":45002,\"Ġgoddamn\":45003,\"SHA\":45004,\"Ġlocalization\":45005,\"ĠPHI\":45006,\"Ġhierarch\":45007,\"Ġatheists\":45008,\"Â±\":45009,\"Luck\":45010,\"ĠJugg\":45011,\"options\":45012,\"alore\":45013,\"Edward\":45014,\"Monitor\":45015,\"Ġneoc\":45016,\"numbered\":45017,\"Arc\":45018,\"ĠCodes\":45019,\"ĠHallow\":45020,\"olitan\":45021,\"sections\":45022,\"ĠEzek\":45023,\"Ġamy\":45024,\"task\":45025,\"ĠCLS\":45026,\"ĠValkyrie\":45027,\"Ġcircumference\":45028,\"amac\":45029,\"ĠNotting\":45030,\"Ġproverb\":45031,\"Spec\":45032,\"Ġelemental\":45033,\"ĠBitcoins\":45034,\"Except\":45035,\"Release\":45036,\"ADVERTISEMENT\":45037,\"Complete\":45038,\"phrine\":45039,\"Ġspores\":45040,\"random\":45041,\"neum\":45042,\"trigger\":45043,\"ocide\":45044,\"Ġlongitudinal\":45045,\"isec\":45046,\"peat\":45047,\"Ġprecept\":45048,\"Wing\":45049,\"ĠâĹ\":45050,\"otropic\":45051,\"mouse\":45052,\"ĠWitcher\":45053,\"ĠAppearance\":45054,\"ROR\":45055,\"Ġ||\":45056,\"aird\":45057,\"Blu\":45058,\"Ġincomp\":45059,\"ĠFirefly\":45060,\"update\":45061,\"Loc\":45062,\"Ġnihil\":45063,\"hesive\":45064,\"Quality\":45065,\"youtu\":45066,\"Seriously\":45067,\"Ġannot\":45068,\"ĠCoins\":45069,\"Visit\":45070,\"lc\":45071,\"----------\":45072,\"Ġdiction\":45073,\"Ġafore\":45074,\"Ġimmortality\":45075,\"ĠForbidden\":45076,\"Allah\":45077,\"ĠPartial\":45078,\"ĠGears\":45079,\"Ġtrance\":45080,\"Hat\":45081,\"irez\":45082,\"ĠSATA\":45083,\"Ġelectrode\":45084,\"ĠLinear\":45085,\"rikes\":45086,\"Ġderiv\":45087,\"ĠXue\":45088,\"Fine\":45089,\"ĠIgnore\":45090,\"desc\":45091,\"DOM\":45092,\"Simple\":45093,\"orescence\":45094,\"Previously\":45095,\"Ġcircumcision\":45096,\"Sphere\":45097,\"Ġrenown\":45098,\"SET\":45099,\"ilight\":45100,\"ĠByzantine\":45101,\"EXP\":45102,\"Ġwhine\":45103,\"Missing\":45104,\"Lt\":45105,\"Guide\":45106,\"Ġhippocampus\":45107,\"Ġwip\":45108,\"yrights\":45109,\"Ġsubmer\":45110,\"Maker\":45111,\"Switch\":45112,\"Ġspectral\":45113,\"nect\":45114,\"Ãį\":45115,\"Ġreven\":45116,\"WER\":45117,\"Adding\":45118,\"ĠCONTROL\":45119,\"asper\":45120,\"0000000\":45121,\"ynt\":45122,\"annabin\":45123,\"ĠAliens\":45124,\"ĠPCR\":45125,\"asketball\":45126,\"ricia\":45127,\"ĠUnch\":45128,\"Tap\":45129,\"Ġpracticable\":45130,\"ĠUsage\":45131,\"Ġsoluble\":45132,\"Scroll\":45133,\"Random\":45134,\"Ġmoan\":45135,\"ĠPuppet\":45136,\"Dim\":45137,\"Attack\":45138,\"Ġspears\":45139,\"Ġrectangle\":45140,\"Ġamuse\":45141,\"ĠDoct\":45142,\"reon\":45143,\"ĠReset\":45144,\"vag\":45145,\"unin\":45146,\"ĠBris\":45147,\"ĠSwarm\":45148,\"Model\":45149,\"Standing\":45150,\"Ġdenotes\":45151,\"{\":45152,\"ĠLizard\":45153,\"nesty\":45154,\"Ġwor\":45155,\"Ġamplification\":45156,\"ĠInferno\":45157,\"Cover\":45158,\"SAM\":45159,\"respective\":45160,\"Shift\":45161,\"Ġlibertarians\":45162,\"Runner\":45163,\"ĠRevelations\":45164,\"Spr\":45165,\"ĠCrusader\":45166,\"Ġcaffe\":45167,\"Patch\":45168,\"stros\":45169,\"ĠImmortal\":45170,\"Ġinsofar\":45171,\"itance\":45172,\"ĠValhalla\":45173,\"Ġradial\":45174,\"Beast\":45175,\"sync\":45176,\"Ġ--------\":45177,\"ĠPathfinder\":45178,\"iless\":45179,\"operator\":45180,\"Choose\":45181,\"Ġdecode\":45182,\"Ġvou\":45183,\"ĠMutant\":45184,\"ĠCVE\":45185,\"Female\":45186,\"Ġoxidation\":45187,\"inational\":45188,\"dB\":45189,\"Scope\":45190,\"Wan\":45191,\"ĠBought\":45192,\"ĠDietary\":45193,\"rotein\":45194,\"Present\":45195,\"aukee\":45196,\"Ġtotem\":45197,\"Ġsatur\":45198,\"wagon\":45199,\"Builder\":45200,\"ĠBulg\":45201,\"Ġsects\":45202,\"Flo\":45203,\"ombat\":45204,\"ĠHermione\":45205,\"aughs\":45206,\"Ġhydra\":45207,\"paren\":45208,\"ë\":45209,\"Whereas\":45210,\"tsky\":45211,\"Ġchall\":45212,\"WORK\":45213,\"opian\":45214,\"rican\":45215,\"vati\":45216,\"ĠHTTPS\":45217,\"Ġwrink\":45218,\"Ġthrob\":45219,\"habi\":45220,\"Ġiodine\":45221,\"omorph\":45222,\"ĠScion\":45223,\"Hunt\":45224,\"Written\":45225,\"iosity\":45226,\"ĠBrowser\":45227,\"Ġsinners\":45228,\"culosis\":45229,\"Ġunconsciously\":45230,\"0100\":45231,\"Ġanarchists\":45232,\"Pull\":45233,\"FFER\":45234,\"Ġpandemonium\":45235,\"matically\":45236,\"Rush\":45237,\"Ġpurified\":45238,\"ĠCyan\":45239,\"ĠDifficulty\":45240,\"Â«\":45241,\"Aside\":45242,\"oggles\":45243,\"untu\":45244,\"iege\":45245,\"iberal\":45246,\"ĠCOUR\":45247,\"eteenth\":45248,\"weeney\":45249,\"biased\":45250,\"ĠDecay\":45251,\"quart\":45252,\"alysis\":45253,\"Ġstere\":45254,\"ellect\":45255,\"Ġkernels\":45256,\"juven\":45257,\"ĠJPEG\":45258,\"indal\":45259,\"topic\":45260,\"Ġidentifier\":45261,\"åı\":45262,\"Ġepid\":45263,\"1969\":45264,\"Ġpoisons\":45265,\"sym\":45266,\"mop\":45267,\"LOCK\":45268,\"axe\":45269,\"cohol\":45270,\"ctory\":45271,\"Ġadject\":45272,\"Skin\":45273,\"ĠFract\":45274,\"ĠSHAR\":45275,\"echo\":45276,\"thood\":45277,\"Ġencoding\":45278,\"Ġrelational\":45279,\"Len\":45280,\"Bone\":45281,\"agara\":45282,\"uggish\":45283,\"ĠTanks\":45284,\"Stats\":45285,\"lihood\":45286,\"Mult\":45287,\"Graph\":45288,\"ĠCannot\":45289,\"ĠSpac\":45290,\"handler\":45291,\"ĠShit\":45292,\"Ġmorp\":45293,\"controller\":45294,\"udeau\":45295,\"Screenshot\":45296,\"Development\":45297,\"Gear\":45298,\"Ġtong\":45299,\"ĠColossus\":45300,\"rylic\":45301,\"STRUCT\":45302,\"capitalist\":45303,\"Ġsupplementation\":45304,\"Parts\":45305,\"pb\":45306,\"oppy\":45307,\"pite\":45308,\"processor\":45309,\"Ġexplanatory\":45310,\"Environmental\":45311,\"Compl\":45312,\"Gaming\":45313,\"arently\":45314,\"Ġconcess\":45315,\"Ġathlet\":45316,\"forestation\":45317,\"orsi\":45318,\"igmat\":45319,\"Ġencoded\":45320,\"misc\":45321,\"Ġproofs\":45322,\"ĠRevision\":45323,\"Ġmathematic\":45324,\"Ġconstitu\":45325,\"fficiency\":45326,\"Ġlightsaber\":45327,\"gz\":45328,\"erate\":45329,\"ournals\":45330,\"Comment\":45331,\"Ġpercept\":45332,\".\\\"[\":45333,\"ĠTechniques\":45334,\"coins\":45335,\"Shape\":45336,\"venant\":45337,\"ĠPrinted\":45338,\"Native\":45339,\"ĠGors\":45340,\"pecting\":45341,\"ĠDuel\":45342,\"Ġadmins\":45343,\"Flor\":45344,\"ĠDeus\":45345,\"cham\":45346,\"ĠRails\":45347,\"ceptor\":45348,\"naire\":45349,\"ĠSquid\":45350,\"ĠWarranty\":45351,\"SPEC\":45352,\"ensis\":45353,\"FUN\":45354,\"stellar\":45355,\"Select\":45356,\"llular\":45357,\"arget\":45358,\"ĠUncharted\":45359,\"Details\":45360,\"rison\":45361,\"Ġsyntax\":45362,\"chanted\":45363,\"Ġ-----\":45364,\"Ġthats\":45365,\"Registration\":45366,\"ĠSaber\":45367,\"ethical\":45368,\"Ġcryptography\":45369,\"atown\":45370,\"Ġdependencies\":45371,\"nw\":45372,\"Ġvehement\":45373,\"Ġrationality\":45374,\"ĠThou\":45375,\"Ġ----\":45376,\"rador\":45377,\"Ġenh\":45378,\"ĠCrate\":45379,\"STATE\":45380,\"/(\":45381,\"Ġdelim\":45382,\"CEPT\":45383,\"monkey\":45384,\"pai\":45385,\"uracy\":45386,\"Ġmortals\":45387,\"Sanders\":45388,\"ĠSeraph\":45389,\"-\\\"\":45390,\"1945\":45391,\"endix\":45392,\":'\":45393,\"ĠLegs\":45394,\"Exper\":45395,\"ĠKrypt\":45396,\"clinton\":45397,\"Ġuphe\":45398,\"Vers\":45399,\"Similarly\":45400,\"ressor\":45401,\"leans\":45402,\"LOG\":45403,\"cific\":45404,\"Ġ].\":45405,\"-)\":45406,\"resist\":45407,\"Pred\":45408,\"Latest\":45409,\"ilyn\":45410,\"Ġblob\":45411,\"Ġdevils\":45412,\"ĠIllusion\":45413,\"erella\":45414,\"Ġyak\":45415,\"method\":45416,\"Ġ698\":45417,\"Shadow\":45418,\"velt\":45419,\"Ġsomet\":45420,\"xc\":45421,\"Ġtriangles\":45422,\"netic\":45423,\"Calling\":45424,\"ĠDRM\":45425,\"Ġtriglycer\":45426,\"Ġinhibited\":45427,\"Ġnep\":45428,\"Ġalgebra\":45429,\"ascar\":45430,\"laim\":45431,\"Ġappl\":45432,\"1971\":45433,\"Bernie\":45434,\"Eh\":45435,\"Ġundefined\":45436,\"âĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶ\":45437,\"Sys\":45438,\"ournaments\":45439,\"Solid\":45440,\"Ġhep\":45441,\"ĠMales\":45442,\"Agent\":45443,\"Ġpsychedel\":45444,\"Wik\":45445,\"Ġdoctrines\":45446,\"rection\":45447,\"Compare\":45448,\"âĺ\":45449,\"Ġcertific\":45450,\"Ġsubstr\":45451,\"ĠCitation\":45452,\"ĠAFB\":45453,\"ĠBecame\":45454,\"Ġaristocracy\":45455,\"aryl\":45456,\"Ġanatomical\":45457,\"ocumented\":45458,\"ĠAssy\":45459,\"ĠFORM\":45460,\"Traditional\":45461,\"azines\":45462,\"Content\":45463,\"furt\":45464,\"Ġscripting\":45465,\"Ġcloaked\":45466,\"Ġunint\":45467,\"ĠCivilization\":45468,\"Desktop\":45469,\"ĠRagnar\":45470,\"Ġcurses\":45471,\"Ġobservable\":45472,\"ĠSpock\":45473,\"ĠPyr\":45474,\"Ġelectrom\":45475,\"ĠLump\":45476,\"oresc\":45477,\"ĠAttribution\":45478,\"egal\":45479,\"achusetts\":45480,\"Ġmarqu\":45481,\"âĻ¦\":45482,\"Ġcursor\":45483,\"ascist\":45484,\"1966\":45485,\"edit\":45486,\"lisher\":45487,\"ocyte\":45488,\"Writer\":45489,\"BILITIES\":45490,\"ĠUpload\":45491,\"Ġtreacher\":45492,\"Ġrecomb\":45493,\"Ġknights\":45494,\"Ġimmutable\":45495,\"ĠPly\":45496,\"Ġatten\":45497,\"ĠPassed\":45498,\"Flying\":45499,\"icipated\":45500,\"querade\":45501,\"ĠZot\":45502,\"CRE\":45503,\"ĠCursed\":45504,\"ickr\":45505,\"ĠDroid\":45506,\"thereum\":45507,\"Ġadjective\":45508,\"DIT\":45509,\"Ġtob\":45510,\"Ġinit\":45511,\"ĠPenet\":45512,\"Ġignor\":45513,\"Ġexalted\":45514,\"ĠDwell\":45515,\"assemb\":45516,\"Ġsentient\":45517,\"Ġ``\":45518,\"ĠGoo\":45519,\"Professional\":45520,\"othing\":45521,\"rupted\":45522,\"olics\":45523,\"ĠSetup\":45524,\"Thu\":45525,\"Campaign\":45526,\"Secondly\":45527,\"clipse\":45528,\"hibit\":45529,\"amate\":45530,\"SUP\":45531,\"ĠSuppose\":45532,\"submit\":45533,\"ĠDebian\":45534,\"Ġantid\":45535,\"Ġentert\":45536,\"ysical\":45537,\"ĠGladiator\":45538,\"ĠSTL\":45539,\"ĠBugs\":45540,\"ĠMech\":45541,\"ĠCoffin\":45542,\"itored\":45543,\"ICLE\":45544,\"Mist\":45545,\"Ġinfall\":45546,\"votes\":45547,\"actly\":45548,\"Occ\":45549,\"ĠConquest\":45550,\"alach\":45551,\"Ġintertw\":45552,\"reverse\":45553,\"amiya\":45554,\"icularly\":45555,\"edom\":45556,\"ĠLuxem\":45557,\"Fra\":45558,\"urrencies\":45559,\"Ġnobility\":45560,\"Tab\":45561,\"Beer\":45562,\"Ġ10000\":45563,\"Ġincor\":45564,\"Ġmelanch\":45565,\"Depth\":45566,\"Firstly\":45567,\"usr\":45568,\"ĠWiki\":45569,\"hhhh\":45570,\"ĠProxy\":45571,\"Ġantagonists\":45572,\"Ġtransistor\":45573,\"ĠRelic\":45574,\"ĠPrometheus\":45575,\"Ġ1280\":45576,\"Coun\":45577,\"ĠMedals\":45578,\"stats\":45579,\"Assembly\":45580,\"inished\":45581,\"cemic\":45582,\"Ġadventurers\":45583,\"Ġcd\":45584,\"Supporters\":45585,\"ĠYs\":45586,\"])\":45587,\"Ġneglig\":45588,\"Request\":45589,\"Ġwhore\":45590,\"Ġovercl\":45591,\"_-\":45592,\"partial\":45593,\"amd\":45594,\"Ġfructose\":45595,\"Ġdivid\":45596,\"Administ\":45597,\"amples\":45598,\"Boo\":45599,\"akery\":45600,\"owered\":45601,\"hester\":45602,\"Links\":45603,\"GROUND\":45604,\"ethy\":45605,\"Ġincarcer\":45606,\"Ġincap\":45607,\"Drag\":45608,\"ĠElastic\":45609,\"âĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶ\":45610,\"Ultra\":45611,\"AAAA\":45612,\"Order\":45613,\"ĠMysteries\":45614,\"Ġcanonical\":45615,\"Ign\":45616,\"Ġanimate\":45617,\"wegian\":45618,\"ggle\":45619,\"Hash\":45620,\"Arg\":45621,\"verty\":45622,\"Ġanalges\":45623,\"ouver\":45624,\"ittees\":45625,\"ĠAsgard\":45626,\"______\":45627,\"Mix\":45628,\"1964\":45629,\"Rate\":45630,\"Ġarousal\":45631,\"pheus\":45632,\"undai\":45633,\"hetamine\":45634,\"ĠMysterious\":45635,\"Alright\":45636,\"ĠHerod\":45637,\"riott\":45638,\"ĠAnarchy\":45639,\"ĠArche\":45640,\"Question\":45641,\"Chapter\":45642,\"Token\":45643,\"ĠSphere\":45644,\"Ġinduces\":45645,\"Audio\":45646,\"Normal\":45647,\"Ġprophe\":45648,\"ĠValiant\":45649,\"Tag\":45650,\"Relations\":45651,\"Ġblinked\":45652,\"onyms\":45653,\"ĠVortex\":45654,\"Ġdb\":45655,\"emonic\":45656,\"Phase\":45657,\"Ġkingdoms\":45658,\"Twe\":45659,\"ĠLORD\":45660,\"plementation\":45661,\"ĠConstantinople\":45662,\"helm\":45663,\"ĠFlesh\":45664,\"Ġthumbnail\":45665,\"ledged\":45666,\"ĠPROG\":45667,\"Ġdisbel\":45668,\"ĠLikes\":45669,\"ĠGamer\":45670,\"renches\":45671,\"hattan\":45672,\"Index\":45673,\"pecially\":45674,\"ĠJiu\":45675,\"Ġwhats\":45676,\"erion\":45677,\"xf\":45678,\"ĠPerception\":45679,\"Alien\":45680,\"Capt\":45681,\"ãĢĤ\":45682,\"joining\":45683,\"nesium\":45684,\"ĠSocrates\":45685,\"Icon\":45686,\"animate\":45687,\"ocalypse\":45688,\"ĠTactics\":45689,\"assador\":45690,\"Veh\":45691,\"src\":45692,\",-\":45693,\"Ġvisc\":45694,\"ĠDiscord\":45695,\"initial\":45696,\"atana\":45697,\"Size\":45698,\"Claim\":45699,\"ffect\":45700,\"iciary\":45701,\"Ġturret\":45702,\"reset\":45703,\"Ï\":45704,\"wrap\":45705,\"ulnerability\":45706,\"ĠInsert\":45707,\"Ġirrad\":45708,\"ognitive\":45709,\"clips\":45710,\"uncle\":45711,\"chemy\":45712,\"ottesville\":45713,\"Write\":45714,\"earances\":45715,\"1965\":45716,\"MIC\":45717,\"Ġmanag\":45718,\"Ġtelesc\":45719,\"Termin\":45720,\"Guest\":45721,\"Ġdenote\":45722,\"Failure\":45723,\"ograp\":45724,\"âĢķ\":45725,\"Ġscrolls\":45726,\"ĠArmored\":45727,\"Ġrecomp\":45728,\"Ġplaceholder\":45729,\"ĠISBN\":45730,\"ĠBelief\":45731,\"emporary\":45732,\"Asset\":45733,\"arcer\":45734,\"haar\":45735,\"assium\":45736,\"%:\":45737,\"ernal\":45738,\"ĠLv\":45739,\"atible\":45740,\"Pand\":45741,\"oubted\":45742,\"Lie\":45743,\"bial\":45744,\"STEP\":45745,\"Ġpresets\":45746,\"Ġstatist\":45747,\"Sund\":45748,\"reshold\":45749,\"endium\":45750,\"\\\");\":45751,\"Software\":45752,\"Ġbasal\":45753,\"ĠYose\":45754,\"Ġmortg\":45755,\"ocry\":45756,\"Ġsubreddit\":45757,\"omorphic\":45758,\"ĠLoaded\":45759,\"berra\":45760,\"vg\":45761,\"orkshire\":45762,\"ĠChrys\":45763,\"Repeat\":45764,\"ĠSimulator\":45765,\"rx\":45766,\"gex\":45767,\"Linux\":45768,\"ĠInstruct\":45769,\"irable\":45770,\"Ġmosquit\":45771,\"ĠManga\":45772,\"iOS\":45773,\"Ġsynt\":45774,\"Ġclitor\":45775,\"Ġlobe\":45776,\"ĠDelete\":45777,\"CVE\":45778,\"fortunately\":45779,\"Enc\":45780,\"vertising\":45781,\"Ġanten\":45782,\"Ġfif\":45783,\"Study\":45784,\"prev\":45785,\"ossus\":45786,\"Nar\":45787,\"Decl\":45788,\"erala\":45789,\"ĠPrototype\":45790,\"UGE\":45791,\"1001\":45792,\"Ġ---------\":45793,\"deals\":45794,\"odcast\":45795,\"TPS\":45796,\"Ġcodec\":45797,\"ittee\":45798,\"isexual\":45799,\"ĠBreaker\":45800,\"menu\":45801,\"ĠURI\":45802,\"('\":45803,\"ĠFiorina\":45804,\"ĠApostles\":45805,\"ĠWitches\":45806,\"raint\":45807,\"addafi\":45808,\"ersive\":45809,\"yrim\":45810,\"Ġmosa\":45811,\"Ġrog\":45812,\"Ear\":45813,\"âĺħ\":45814,\"Ġcaloric\":45815,\"matical\":45816,\"yrics\":45817,\"ĠKrugman\":45818,\"axter\":45819,\"1016\":45820,\"Ġsep\":45821,\"ĠExtend\":45822,\"ropolitan\":45823,\"thren\":45824,\"ologne\":45825,\"atomic\":45826,\"Naturally\":45827,\"Pros\":45828,\"gencies\":45829,\"akens\":45830,\"Male\":45831,\"Ġcausation\":45832,\"omnia\":45833,\"Comments\":45834,\"eeee\":45835,\"iquette\":45836,\"Ġcytok\":45837,\"ename\":45838,\"details\":45839,\"Ġdestruct\":45840,\"leep\":45841,\"ĠCavern\":45842,\"ĠInvention\":45843,\"ueless\":45844,\"Ġsubsection\":45845,\"outhern\":45846,\"metic\":45847,\"blogs\":45848,\"ĠPacks\":45849,\"ĠArduino\":45850,\"hhh\":45851,\"elligence\":45852,\"imity\":45853,\"ĠUltron\":45854,\"astrous\":45855,\"Ġbiome\":45856,\"ĠHover\":45857,\"Ġprivile\":45858,\"igham\":45859,\"apest\":45860,\"ĠYoshi\":45861,\"Artist\":45862,\".\\\",\":45863,\"gamer\":45864,\"Virgin\":45865,\"Tea\":45866,\"ĠDoomsday\":45867,\"ĠðŁĻĤ\":45868,\"terday\":45869,\"ĠCommando\":45870,\"ĠAchieve\":45871,\"chrom\":45872,\"Ġcryptographic\":45873,\"Ġrebell\":45874,\"Specifically\":45875,\"âĢ¦âĢ¦âĢ¦âĢ¦\":45876,\"ĠEternity\":45877,\"Ġemulation\":45878,\"ĠSERV\":45879,\"ĠMiscellaneous\":45880,\"ĠParticipant\":45881,\"duc\":45882,\"vp\":45883,\"ĠSparkle\":45884,\"ategories\":45885,\"Ġdecrypt\":45886,\"ĠGNOME\":45887,\"activation\":45888,\"Ġanarch\":45889,\"owler\":45890,\"adiator\":45891,\"itars\":45892,\"ĠTHEN\":45893,\")\\\",\":45894,\"åħ\":45895,\"Ġembod\":45896,\"vae\":45897,\"âĺĨ\":45898,\"Member\":45899,\"Ġrm\":45900,\"nyder\":45901,\"ĠLeviathan\":45902,\"Gaza\":45903,\"erenn\":45904,\"Chicken\":45905,\"ĠDefinitive\":45906,\"ĠBolshe\":45907,\"ĠJagu\":45908,\"gorith\":45909,\"loader\":45910,\"exe\":45911,\".........\":45912,\"ĠReceived\":45913,\"ĠProto\":45914,\"ĠLocked\":45915,\"Posts\":45916,\"ankind\":45917,\"Clock\":45918,\"ĠCLI\":45919,\"Throw\":45920,\"dL\":45921,\"epad\":45922,\"ĠAtmosp\":45923,\"Ġmk\":45924,\"ĠSteal\":45925,\"uple\":45926,\"reference\":45927,\"ĠGNU\":45928,\"adelphia\":45929,\"scripts\":45930,\"ilaterally\":45931,\"ĠMods\":45932,\"odus\":45933,\"ignty\":45934,\"REF\":45935,\"Ġhypothesized\":45936,\"issors\":45937,\"Ġanus\":45938,\"HUD\":45939,\"rices\":45940,\"Draw\":45941,\"Computer\":45942,\"Below\":45943,\"uthor\":45944,\"ĠTact\":45945,\"=$\":45946,\"00000000\":45947,\"Ġcaut\":45948,\"Sharp\":45949,\"depend\":45950,\"Ġtatt\":45951,\"Goal\":45952,\"Sounds\":45953,\"zona\":45954,\"anyon\":45955,\"ricanes\":45956,\"ĠUSAF\":45957,\"Jump\":45958,\"Bottom\":45959,\"etermination\":45960,\"ĠPles\":45961,\"Ġhypothes\":45962,\"Reference\":45963,\"Ġswall\":45964,\"Ġmaneu\":45965,\"rifice\":45966,\"ĠVeh\":45967,\"Ġtex\":45968,\"geoning\":45969,\"ĠâľĶ\":45970,\"Mach\":45971,\"eanor\":45972,\"%);\":45973,\"archives\":45974,\"Ġencyclopedia\":45975,\"ĠPreferences\":45976,\"damage\":45977,\"Done\":45978,\"Ġcoefficient\":45979,\"ĠCreatures\":45980,\"Ġital\":45981,\"ivari\":45982,\"Revolution\":45983,\"Ġnob\":45984,\"Diff\":45985,\"Ġabbre\":45986,\"Writ\":45987,\"ĠDOS\":45988,\"redd\":45989,\"Ġsplend\":45990,\"orest\":45991,\"flame\":45992,\"Ġdevs\":45993,\"Ġ==\":45994,\"ĠPuzzle\":45995,\"Ġgit\":45996,\"MOD\":45997,\"ĠArgument\":45998,\"ĠAbyss\":45999,\"Studies\":46000,\"ophob\":46001,\"uild\":46002,\"scill\":46003,\"fp\":46004,\"Ġplur\":46005,\"Delete\":46006,\"ĠFALSE\":46007,\"FIL\":46008,\"Ġmicrobiota\":46009,\"ĠIPv\":46010,\"Stud\":46011,\"ortal\":46012,\"ĠDivinity\":46013,\"ounter\":46014,\"ä¸\":46015,\"Naz\":46016,\"stals\":46017,\"ihilation\":46018,\"Ġpersecut\":46019,\"ĠPlanes\":46020,\"viation\":46021,\"Driver\":46022,\"ĠEEG\":46023,\"Unity\":46024,\"Premium\":46025,\"ĠSiren\":46026,\"ĠPaleo\":46027,\"earchers\":46028,\"Pract\":46029,\"Ö\":46030,\"VII\":46031,\"mosp\":46032,\"Ġidentifiers\":46033,\"Near\":46034,\"achu\":46035,\"Apps\":46036,\"tackle\":46037,\"COLOR\":46038,\"Ġperpendicular\":46039,\"viks\":46040,\"ecided\":46041,\"ĠDota\":46042,\"icons\":46043,\"Ġpsi\":46044,\"Brave\":46045,\"Ġunimagin\":46046,\"ĠATI\":46047,\"OOL\":46048,\"Gender\":46049,\"ĠSwords\":46050,\"oples\":46051,\"Rank\":46052,\"olphins\":46053,\"Ġdeities\":46054,\"ĠXIII\":46055,\"Ð¼\":46056,\"ĠKraken\":46057,\"ĠLEVEL\":46058,\"stasy\":46059,\"ĠBabel\":46060,\"Hours\":46061,\"Avoid\":46062,\"Mech\":46063,\"Multi\":46064,\"Ġect\":46065,\"Occup\":46066,\"panic\":46067,\"Ġmutants\":46068,\"Evidence\":46069,\"Tips\":46070,\"Ġvolts\":46071,\"Exit\":46072,\"xb\":46073,\"planet\":46074,\"avez\":46075,\"features\":46076,\")]\":46077,\"lol\":46078,\"ĠNeph\":46079,\"ĠSanct\":46080,\"Ġimpover\":46081,\"................................\":46082,\"Sty\":46083,\"Email\":46084,\"Torrent\":46085,\"Ġgluc\":46086,\"ĠSins\":46087,\"ĠIncarn\":46088,\"ĠWITHOUT\":46089,\"ĠPanzer\":46090,\"ĠAssignment\":46091,\"versible\":46092,\"Strange\":46093,\"ITNESS\":46094,\"incible\":46095,\"ZX\":46096,\"ĠMySQL\":46097,\"Ġconson\":46098,\"Ġoxidative\":46099,\"Machine\":46100,\"Impro\":46101,\"Parent\":46102,\"ĠMetroid\":46103,\"Educ\":46104,\"Ġdismant\":46105,\"dx\":46106,\"ĠPersona\":46107,\"ĠHDL\":46108,\"Americ\":46109,\"Users\":46110,\"Ġeighteenth\":46111,\"WARNING\":46112,\"ĠLists\":46113,\"ĠCanter\":46114,\"ĠTrotsky\":46115,\"Ġhaha\":46116,\"]'\":46117,\"ĠEncyclopedia\":46118,\"admin\":46119,\"ĠACTIONS\":46120,\"idav\":46121,\"Î¿\":46122,\"ĠFTP\":46123,\"Ġquar\":46124,\"ongyang\":46125,\"âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦\":46126,\"Ġsynchronization\":46127,\"DEM\":46128,\"riched\":46129,\"Ġnegro\":46130,\"Bench\":46131,\"Ġfilament\":46132,\"Ġdecoding\":46133,\"obj\":46134,\"Ġjoystick\":46135,\"Decre\":46136,\"ĠBolshevik\":46137,\"Virtual\":46138,\"ĠSacrament\":46139,\"xd\":46140,\"BILL\":46141,\"-+-+\":46142,\"Â¶\":46143,\"anchester\":46144,\"Pokemon\":46145,\"Ġslic\":46146,\"iameter\":46147,\"errilla\":46148,\"Exactly\":46149,\"\\\"'\":46150,\"getic\":46151,\"3333\":46152,\"solete\":46153,\"Ġincorpor\":46154,\"Ġio\":46155,\"------------\":46156,\"Ġantiquity\":46157,\"ATURES\":46158,\"Policy\":46159,\"oppable\":46160,\"Ġ=>\":46161,\"ODUCT\":46162,\"otide\":46163,\"Ú\":46164,\"Ġnormative\":46165,\"Fac\":46166,\"Ġshaman\":46167,\"element\":46168,\"Plex\":46169,\"INTER\":46170,\"etsk\":46171,\"ĠGauntlet\":46172,\"ĠBIOS\":46173,\"×ķ\":46174,\"riet\":46175,\"Rew\":46176,\"uristic\":46177,\"urches\":46178,\"ĠChomsky\":46179,\"ixir\":46180,\"package\":46181,\"Owner\":46182,\"Ġschematic\":46183,\"Assistant\":46184,\"Ġemanc\":46185,\"Ġarchetype\":46186,\"Initial\":46187,\"intent\":46188,\"Ġfilib\":46189,\"ispers\":46190,\"Flag\":46191,\"Tank\":46192,\"Ġinsurg\":46193,\"Ġapproximation\":46194,\"Ġsemantic\":46195,\"Ġsubtitle\":46196,\"Font\":46197,\"Ġintimid\":46198,\"Ġhath\":46199,\"tools\":46200,\"gob\":46201,\"Process\":46202,\"slave\":46203,\"ĠJUSTICE\":46204,\"âĻ¥\":46205,\"ĠHardcore\":46206,\"Discover\":46207,\"Ġexch\":46208,\"ptive\":46209,\"units\":46210,\"ĠDjango\":46211,\"itudinal\":46212,\"Ġpc\":46213,\"akespeare\":46214,\"ospace\":46215,\"Ġhorny\":46216,\"auth\":46217,\"ĠSkyrim\":46218,\"ENGTH\":46219,\"perors\":46220,\"ĠVulkan\":46221,\"Ġchimpan\":46222,\"Ġremem\":46223,\"Ġopacity\":46224,\"Ġ:(\":46225,\"ushima\":46226,\"Ġawoken\":46227,\"Ġsacrament\":46228,\"Beginning\":46229,\"escape\":46230,\"Anim\":46231,\"Ġadvant\":46232,\"ĠRequires\":46233,\"output\":46234,\"Ġdroid\":46235,\"Yep\":46236,\"rieving\":46237,\"Ġpt\":46238,\"ĠShotgun\":46239,\"ĠOsiris\":46240,\"disabled\":46241,\"ĠRadius\":46242,\"Medium\":46243,\"ĠScient\":46244,\"ĠRept\":46245,\"ymm\":46246,\"Ġcp\":46247,\"ĠLabyrinth\":46248,\"poral\":46249,\"Ġ'(\":46250,\"Hack\":46251,\"ĠTechnique\":46252,\"/,\":46253,\"Ġambig\":46254,\"Basic\":46255,\"Ġretrie\":46256,\"VICE\":46257,\"BIP\":46258,\"ragon\":46259,\"phies\":46260,\"uminum\":46261,\"ĠFei\":46262,\"lesi\":46263,\"Ġsemantics\":46264,\"ĠHz\":46265,\"ĠUnderworld\":46266,\"Ġendot\":46267,\"olesterol\":46268,\"ourning\":46269,\"Ġcaches\":46270,\"ĠYug\":46271,\"Legendary\":46272,\"ĠDocumentation\":46273,\"ĠSpiral\":46274,\"ĠClone\":46275,\"bnb\":46276,\"ĠâĶ\":46277,\"ustom\":46278,\"Mp\":46279,\"gettable\":46280,\"agonist\":46281,\"Ġneuronal\":46282,\"culus\":46283,\"enum\":46284,\"cules\":46285,\"Ġmuttered\":46286,\"ctica\":46287,\"necess\":46288,\"ĠSubtle\":46289,\"Ġsolder\":46290,\"Environment\":46291,\"oneliness\":46292,\"orage\":46293,\"âĢ¦.\\\"\":46294,\"nesota\":46295,\"agements\":46296,\"Ùİ\":46297,\"WHERE\":46298,\"ĠGDDR\":46299,\"Scient\":46300,\"ĠMulcair\":46301,\"ĠRena\":46302,\"________________________________________________________________\":46303,\"antics\":46304,\"Ġtorped\":46305,\"Brow\":46306,\"ossal\":46307,\"Category\":46308,\"Regular\":46309,\"remote\":46310,\"ãģ\":46311,\"ĠCoil\":46312,\"ritch\":46313,\"specified\":46314,\"Average\":46315,\"Ġfingert\":46316,\"entity\":46317,\"atibility\":46318,\"ampunk\":46319,\"ĠScriptures\":46320,\"Ġunequ\":46321,\"arettes\":46322,\"arching\":46323,\"Ġastron\":46324,\"Ġnumeric\":46325,\"ĠeBook\":46326,\"remove\":46327,\"onday\":46328,\"Ġmetaphysical\":46329,\"ĠGoku\":46330,\"Element\":46331,\"ĠRuin\":46332,\"Norm\":46333,\"Ġtox\":46334,\"puff\":46335,\"Ġharmonic\":46336,\"ĠAgility\":46337,\"ĠHearthstone\":46338,\"Ġmana\":46339,\"Points\":46340,\"Ġconduc\":46341,\"ĠPersia\":46342,\"-----\":46343,\"license\":46344,\"Application\":46345,\"assert\":46346,\"Reader\":46347,\"ĠSacrifice\":46348,\"float\":46349,\"inctions\":46350,\"byter\":46351,\"Ġfundament\":46352,\"\\\"âĢ¦\":46353,\"Fourth\":46354,\"Effective\":46355,\"ĠMeow\":46356,\"ĠErrors\":46357,\"ĠIcar\":46358,\"ĠMMO\":46359,\"Ġapostles\":46360,\"Ġfaintly\":46361,\"component\":46362,\"bably\":46363,\"uggage\":46364,\"ĠMPG\":46365,\"krit\":46366,\"container\":46367,\"ixture\":46368,\"ĠPOV\":46369,\"izabeth\":46370,\"onut\":46371,\"isdom\":46372,\"trace\":46373,\"ĠSDL\":46374,\"Interestingly\":46375,\"ĠExplan\":46376,\"lesiastical\":46377,\"ternal\":46378,\"Bug\":46379,\"Ġmetabolites\":46380,\"geries\":46381,\"Ġsupra\":46382,\"ĠMakoto\":46383,\"orget\":46384,\"racuse\":46385,\"][\":46386,\"ĠPrelude\":46387,\"peria\":46388,\"tube\":46389,\"ĠCatalog\":46390,\"ĠGoblin\":46391,\"QUEST\":46392,\"ĠINCLUD\":46393,\"ĠVERS\":46394,\"erguson\":46395,\"Ġcommandments\":46396,\"ĠUDP\":46397,\"itle\":46398,\"Î¹\":46399,\"domain\":46400,\"roximately\":46401,\"ĠTLS\":46402,\"ongevity\":46403,\"Ġmodulation\":46404,\"Ġdidnt\":46405,\"ĠCalories\":46406,\"Applications\":46407,\"ormon\":46408,\"Ġsd\":46409,\"dullah\":46410,\"Ġcous\":46411,\"ĠDARK\":46412,\"clip\":46413,\"ĠPsychiat\":46414,\"ĠTanz\":46415,\"ĠCharisma\":46416,\"ĠMerge\":46417,\"ĠKDE\":46418,\"requires\":46419,\"urdue\":46420,\"Ġdecimal\":46421,\"Ġâī¥\":46422,\"ĠAuth\":46423,\"ebted\":46424,\"ĠTempl\":46425,\"ĠâĢº\":46426,\"Ultimate\":46427,\"Ġmammalian\":46428,\"advertising\":46429,\"Ġdominion\":46430,\"Ġacron\":46431,\"ĠWem\":46432,\"ĠHeist\":46433,\"oiler\":46434,\"FLAG\":46435,\"ovember\":46436,\"Syn\":46437,\"Ġgodd\":46438,\"ĠPyth\":46439,\"Ġglyc\":46440,\"ĠHelpful\":46441,\"Ġgad\":46442,\"chedel\":46443,\"Similar\":46444,\"ĠÂ¶\":46445,\"Ġnp\":46446,\"ĠREPL\":46447,\"Fill\":46448,\"ĠSunder\":46449,\"etsy\":46450,\"ĠPAX\":46451,\"ĠFemales\":46452,\"ĠKingdoms\":46453,\"Ġwhistlebl\":46454,\"Hide\":46455,\"serial\":46456,\"ĠEnemies\":46457,\"ĠPeb\":46458,\"Ġpiety\":46459,\"ifact\":46460,\"esity\":46461,\"bsite\":46462,\"esides\":46463,\"Ġported\":46464,\"Ġamygdala\":46465,\"ĠGerr\":46466,\"afety\":46467,\"Ġadip\":46468,\"(\\\"\":46469,\"Ġcf\":46470,\"Ġurl\":46471,\"unia\":46472,\"icro\":46473,\"Austral\":46474,\"ĠConfig\":46475,\"accompanied\":46476,\"isite\":46477,\"Ġtextual\":46478,\"\\\">\":46479,\"Ġanecd\":46480,\"Ġ\\\",\":46481,\"angular\":46482,\"ĠUnicode\":46483,\"Proof\":46484,\"Ġmultiplication\":46485,\"Address\":46486,\"Ġbytes\":46487,\"lems\":46488,\"uterte\":46489,\"Episode\":46490,\"oshop\":46491,\"ritical\":46492,\"Adjust\":46493,\"argument\":46494,\"\\\\'\":46495,\"Rober\":46496,\"pection\":46497,\"Agg\":46498,\"äº\":46499,\"interrupted\":46500,\"ĠDebor\":46501,\"Ġlair\":46502,\"Various\":46503,\"isively\":46504,\"ĠStatic\":46505,\"ohyd\":46506,\"ĠEchoes\":46507,\"UID\":46508,\"raught\":46509,\"Bott\":46510,\"Ġapostle\":46511,\"ĠCentauri\":46512,\"oxicity\":46513,\"ibling\":46514,\"Ġparalle\":46515,\"inav\":46516,\"Crit\":46517,\"ĠTyph\":46518,\"Ġhig\":46519,\"ĠEDITION\":46520,\"Ġcoord\":46521,\"uish\":46522,\"sectional\":46523,\"inki\":46524,\"Title\":46525,\"anyahu\":46526,\"osterone\":46527,\"Ġdesper\":46528,\"ribly\":46529,\"Legend\":46530,\"afort\":46531,\"Org\":46532,\"Ġempir\":46533,\"ĠQuake\":46534,\"SSL\":46535,\"ioxide\":46536,\"åľ\":46537,\"Ġenz\":46538,\"urtle\":46539,\"BSD\":46540,\"Rust\":46541,\"ospels\":46542,\"Rare\":46543,\"Ġpartitions\":46544,\"Ġheresy\":46545,\"overy\":46546,\"Ġmonop\":46547,\"Pixel\":46548,\"odder\":46549,\"Option\":46550,\"withstanding\":46551,\"Transfer\":46552,\"Ġarrog\":46553,\"skip\":46554,\"ĠSSH\":46555,\"ĠSph\":46556,\"Ġcallback\":46557,\"PIN\":46558,\"Ġpdf\":46559,\"Ġplaint\":46560,\"cipled\":46561,\"reenshots\":46562,\"Ġparsing\":46563,\"::::::::\":46564,\"ioxid\":46565,\"Ġhereafter\":46566,\"ĠFunctions\":46567,\"ĠBulgar\":46568,\"Ġintu\":46569,\"DOC\":46570,\"Location\":46571,\"Hyper\":46572,\"ageddon\":46573,\"Evil\":46574,\"illions\":46575,\"Introduction\":46576,\"Physical\":46577,\"ĠLayout\":46578,\"âķ\":46579,\"------------------------\":46580,\"ĠRodham\":46581,\"ĠPatterns\":46582,\"Delivery\":46583,\"Ġdistur\":46584,\"ĠVolunte\":46585,\"ĠGUI\":46586,\"Ġclen\":46587,\"Ġinacc\":46588,\"ĠBallistic\":46589,\"ĠSprite\":46590,\"Privacy\":46591,\"theme\":46592,\"dump\":46593,\"ĠByte\":46594,\"ĠIncre\":46595,\"apult\":46596,\"ĠWrath\":46597,\"ensibly\":46598,\"NOTE\":46599,\"ounge\":46600,\"ustomed\":46601,\"ochond\":46602,\"ĠQt\":46603,\"Primary\":46604,\"Ġsidew\":46605,\"Root\":46606,\"gregation\":46607,\"SQL\":46608,\"ĠSOFTWARE\":46609,\"Gallery\":46610,\"ĠDungeon\":46611,\"ĠVengeance\":46612,\"->\":46613,\"steam\":46614,\"Ġfrivol\":46615,\"Ġpid\":46616,\"filter\":46617,\"Ġfacult\":46618,\"doms\":46619,\"Tool\":46620,\"1959\":46621,\"Ġprefix\":46622,\"Ġcomma\":46623,\"relative\":46624,\"Ġformatted\":46625,\"appropriately\":46626,\"Ġmd\":46627,\"xxx\":46628,\"ĠAuthentication\":46629,\"ĠWTC\":46630,\"Ġvulner\":46631,\"reditary\":46632,\"Steam\":46633,\"Tx\":46634,\"ĠGHC\":46635,\"Increased\":46636,\"forcement\":46637,\"ĠGuant\":46638,\"bernatorial\":46639,\"Entry\":46640,\"ĠWarp\":46641,\"ĠCreature\":46642,\"ĠAmmunition\":46643,\"Ġclust\":46644,\"ĠInher\":46645,\"Ġunbel\":46646,\"RGB\":46647,\"ĠMankind\":46648,\"ĠPlague\":46649,\"Ġ=================================\":46650,\"psc\":46651,\"Intern\":46652,\"tml\":46653,\"ĠCrusade\":46654,\"inflamm\":46655,\"Storage\":46656,\"token\":46657,\"inse\":46658,\"False\":46659,\"Adult\":46660,\"PokÃ©mon\":46661,\"PLIED\":46662,\"Ġglac\":46663,\"ĠDwarf\":46664,\"sequence\":46665,\"Ġmagnification\":46666,\"ĠIlluminati\":46667,\"hedral\":46668,\"param\":46669,\"regon\":46670,\".\\\",\\\"\":46671,\"Eva\":46672,\"igree\":46673,\"Object\":46674,\"Ġoptimizations\":46675,\"uador\":46676,\"mmmm\":46677,\"ullivan\":46678,\"Ġ[\\\"\":46679,\"ĠDusk\":46680,\"Ġtrig\":46681,\"Ġiss\":46682,\"Ġhypert\":46683,\"Ġperspect\":46684,\"Ġassum\":46685,\":,\":46686,\"Ġinterpol\":46687,\"Asked\":46688,\"Boot\":46689,\"LIB\":46690,\"Loading\":46691,\"Ident\":46692,\"upuncture\":46693,\"ioch\":46694,\"Ġprefrontal\":46695,\"delay\":46696,\"ĠPokÃ©\":46697,\"bestos\":46698,\"overe\":46699,\"Elf\":46700,\"eteria\":46701,\"ĠSneak\":46702,\"bians\":46703,\"ĠARTICLE\":46704,\"Xbox\":46705,\"encrypted\":46706,\"ync\":46707,\"ĠNietzsche\":46708,\"Nonetheless\":46709,\"ĠÂ±\":46710,\"ĠPrimal\":46711,\"ĠFlare\":46712,\"Ġconflic\":46713,\"ĠRune\":46714,\"Tes\":46715,\"cellence\":46716,\"Mega\":46717,\"ĠEntity\":46718,\"chrome\":46719,\"iatures\":46720,\"Ġuninstall\":46721,\"Winner\":46722,\"aimon\":46723,\"Ġhomebrew\":46724,\"Ruby\":46725,\"araoh\":46726,\"itime\":46727,\"Ġpotion\":46728,\"ĠAllows\":46729,\"ogyn\":46730,\"osuke\":46731,\"Limited\":46732,\"Ġmacros\":46733,\"ERROR\":46734,\"gling\":46735,\"Ġtodd\":46736,\"repre\":46737,\"ĠSakura\":46738,\"erker\":46739,\"items\":46740,\"FIG\":46741,\"ĠUnle\":46742,\"Ġhardness\":46743,\"Split\":46744,\"Ġarous\":46745,\"ocally\":46746,\"Ġì\":46747,\"ĠEVE\":46748,\"pleasant\":46749,\"ihil\":46750,\"ĠRouter\":46751,\"ĠLucius\":46752,\"readable\":46753,\"Ġtremb\":46754,\"Dro\":46755,\"Ġblaster\":46756,\"Ġbourgeoisie\":46757,\"NUM\":46758,\"Alternative\":46759,\"flags\":46760,\"GAME\":46761,\"ebook\":46762,\"ĠIPM\":46763,\"Ġcorrel\":46764,\"Setting\":46765,\"Frame\":46766,\"Ġatheism\":46767,\"Interested\":46768,\"Liquid\":46769,\"stanbul\":46770,\"Lv\":46771,\"Ġtits\":46772,\"Ġdc\":46773,\"×Ļ×\":46774,\"Ġdoctr\":46775,\"background\":46776,\"tsy\":46777,\"ĠCtrl\":46778,\"ĠCompatibility\":46779,\"idae\":46780,\"example\":46781,\"perture\":46782,\"Ġguid\":46783,\"ĠWinged\":46784,\"Command\":46785,\"ridor\":46786,\"bool\":46787,\"comments\":46788,\"ĠImmunity\":46789,\"Nit\":46790,\"Statement\":46791,\"Ġmanif\":46792,\"ĠIntake\":46793,\"Bloom\":46794,\"txt\":46795,\"context\":46796,\"input\":46797,\"achus\":46798,\"proc\":46799,\"Ñĭ\":46800,\"Ġdisemb\":46801,\"ospons\":46802,\"utical\":46803,\"ĠRender\":46804,\"Ironically\":46805,\"ursday\":46806,\"ĠExile\":46807,\"lishes\":46808,\"iets\":46809,\"orescent\":46810,\"cair\":46811,\"ĠSubjects\":46812,\"ĠDungeons\":46813,\"Ġiii\":46814,\"neapolis\":46815,\"ĠBlaster\":46816,\"Ġphp\":46817,\"ORED\":46818,\"ĠSLI\":46819,\"Ġelig\":46820,\"ĠIdentified\":46821,\"ĠBrawl\":46822,\"bytes\":46823,\"ĠCTR\":46824,\"Ġsched\":46825,\"Assuming\":46826,\"Bound\":46827,\"ĠMathemat\":46828,\"razil\":46829,\"ĠAstral\":46830,\"mble\":46831,\"untled\":46832,\"Ġmech\":46833,\"ĠDagger\":46834,\"ĠUseful\":46835,\"nesday\":46836,\"tarians\":46837,\"AMY\":46838,\"Camera\":46839,\"node\":46840,\"pict\":46841,\"ginx\":46842,\"Ġyea\":46843,\">>>>>>>>\":46844,\"paragraph\":46845,\"ĠSupplementary\":46846,\"9999\":46847,\"ĠAlchemist\":46848,\"uzzle\":46849,\"igun\":46850,\"ĠCalculator\":46851,\"ĠApplicant\":46852,\"hift\":46853,\"ĠGPL\":46854,\"Ġencode\":46855,\"Crash\":46856,\"ĠNutr\":46857,\"kHz\":46858,\"TABLE\":46859,\"intestinal\":46860,\"andom\":46861,\"archive\":46862,\"Ëľ\":46863,\"Registered\":46864,\"Questions\":46865,\"Remote\":46866,\"ethyst\":46867,\"Ġgren\":46868,\"ĠTexture\":46869,\"Ġseiz\":46870,\"Anyway\":46871,\"ĠVariant\":46872,\"ê\":46873,\"Adapt\":46874,\"ittered\":46875,\"meta\":46876,\"ambers\":46877,\"ĠRuins\":46878,\"ĠChimera\":46879,\"password\":46880,\"ĠReboot\":46881,\"Ġcaster\":46882,\"Ġamplitude\":46883,\"Position\":46884,\"Ġnotation\":46885,\"Ġsecretion\":46886,\"Excellent\":46887,\"delete\":46888,\"aminer\":46889,\"ä»\":46890,\"Exec\":46891,\"ĠKenobi\":46892,\"Interview\":46893,\"ontent\":46894,\"ospel\":46895,\"Ġtuber\":46896,\"CONT\":46897,\"roups\":46898,\"Ġemulator\":46899,\"Ġjava\":46900,\"0200\":46901,\"Ġnested\":46902,\"Ġfert\":46903,\")).\":46904,\"Dex\":46905,\"ĠSora\":46906,\"Ġpotions\":46907,\"ĠAnon\":46908,\"aah\":46909,\"Ġdunno\":46910,\"ĠÎ¼\":46911,\"Ġmethodological\":46912,\"itles\":46913,\"phia\":46914,\"Beg\":46915,\"Rules\":46916,\"ĠXML\":46917,\"Ġflask\":46918,\"ĠShogun\":46919,\"Ġ2048\":46920,\"atchewan\":46921,\"Ġfuckin\":46922,\"Built\":46923,\"Ġbour\":46924,\"Ġdisag\":46925,\"yss\":46926,\"ĠÏ\":46927,\"Spoiler\":46928,\"Wiki\":46929,\"Ġmorphology\":46930,\"Ġendors\":46931,\"Ġdungeons\":46932,\"dragon\":46933,\")),\":46934,\"Ġhous\":46935,\"Ġoverwhel\":46936,\"SAY\":46937,\"abwe\":46938,\"--------------------------------\":46939,\"Ġepist\":46940,\"Ġpalp\":46941,\"ĠExtensions\":46942,\"ĠMistress\":46943,\"ĠUkrain\":46944,\"================\":46945,\"edience\":46946,\"abama\":46947,\"ĠLua\":46948,\"ĠOffline\":46949,\"ĠKonami\":46950,\"unicip\":46951,\"ĠMachina\":46952,\"Specific\":46953,\"Ġpresupp\":46954,\"ĠGEAR\":46955,\"rition\":46956,\"rences\":46957,\"successfully\":46958,\"Ġ1024\":46959,\"Platform\":46960,\"}}\":46961,\"clude\":46962,\"roxy\":46963,\"Ġpromot\":46964,\"ĠAdapter\":46965,\"rocal\":46966,\"ĠMasquerade\":46967,\"Panel\":46968,\"Language\":46969,\"elsius\":46970,\"Push\":46971,\"abase\":46972,\"ĠdB\":46973,\"argon\":46974,\"ĠRemoved\":46975,\"amph\":46976,\"ĠWyr\":46977,\"Ġindisp\":46978,\"ĠOkin\":46979,\"aepernick\":46980,\"moil\":46981,\"Continue\":46982,\"00007\":46983,\"ĠJournals\":46984,\"TAG\":46985,\"ĠRemastered\":46986,\"Ġsymp\":46987,\"methyl\":46988,\"Overview\":46989,\"umeric\":46990,\"ĠCodex\":46991,\".$\":46992,\"ranged\":46993,\"Sym\":46994,\"ĠVerse\":46995,\"ĠEnabled\":46996,\"ĠFUCK\":46997,\"ĠHearth\":46998,\"Ġbrill\":46999,\"ĠChaser\":47000,\"Beh\":47001,\"ĠAlchemy\":47002,\"Oracle\":47003,\"roleum\":47004,\"ĠVoldemort\":47005,\"();\":47006,\"Ġcollaps\":47007,\"Visual\":47008,\"ĠAngular\":47009,\"ĠOsc\":47010,\"ichita\":47011,\"Ġcig\":47012,\"Ġtoolbar\":47013,\"ĠEnlight\":47014,\"ÑĮ\":47015,\"Îµ\":47016,\"aliation\":47017,\"ĠLovecraft\":47018,\"jri\":47019,\"ĠInterstellar\":47020,\"Ġdebugging\":47021,\"Ġparentheses\":47022,\"ĠInit\":47023,\"Located\":47024,\"Weak\":47025,\"ĠPvP\":47026,\"ĠCloak\":47027,\"uture\":47028,\"iths\":47029,\"asionally\":47030,\"FACE\":47031,\"Introdu\":47032,\"');\":47033,\"slot\":47034,\"aturday\":47035,\"ĠNiet\":47036,\"Ġpuzz\":47037,\"!!!!!!!!\":47038,\"folios\":47039,\"Ç\":47040,\"Ġverbs\":47041,\"ĠFrames\":47042,\"ĠAmbro\":47043,\"Ġmillisec\":47044,\"ĠRebell\":47045,\"ylum\":47046,\"PASS\":47047,\"ĠConfiguration\":47048,\"Î¼\":47049,\"brids\":47050,\"vantage\":47051,\"Ġ['\":47052,\"ĠScy\":47053,\"Benef\":47054,\"gradation\":47055,\"ĠOrc\":47056,\"Resources\":47057,\"Awesome\":47058,\"ĠMilitia\":47059,\"POST\":47060,\"Ġbinaries\":47061,\"Mode\":47062,\"Ġkb\":47063,\"ĠWARRANT\":47064,\"hemy\":47065,\"Desc\":47066,\"alion\":47067,\"Ġwiki\":47068,\"Ġcommer\":47069,\"Serial\":47070,\"ĠUncommon\":47071,\"ignore\":47072,\"Ġconstructor\":47073,\"ctl\":47074,\"Ġ):\":47075,\"ĠVerify\":47076,\"Notice\":47077,\"ĠRPGs\":47078,\"uckland\":47079,\"Ġincre\":47080,\"Pinterest\":47081,\"ĠDefinitions\":47082,\"iband\":47083,\"Ġtd\":47084,\"Ġsubscrib\":47085,\"Shin\":47086,\"ĠGadget\":47087,\"Document\":47088,\"å®\":47089,\"Requ\":47090,\"QUIRE\":47091,\"ĠQuadro\":47092,\"ĠUnix\":47093,\"Enlarge\":47094,\"thens\":47095,\"\\\"...\":47096,\"gebra\":47097,\"pload\":47098,\"alogue\":47099,\"vironments\":47100,\"Strength\":47101,\"ĠPID\":47102,\"ĠInvaders\":47103,\"HOME\":47104,\"Atl\":47105,\"ĠBlizz\":47106,\"ĠWidth\":47107,\"ĠOpenGL\":47108,\"zx\":47109,\"$,\":47110,\"Ġå\":47111,\"cig\":47112,\"lectic\":47113,\"relation\":47114,\"Ġfeas\":47115,\"undown\":47116,\"Said\":47117,\"Î½\":47118,\"ï¿½ï¿½\":47119,\"english\":47120,\"ĠTokens\":47121,\"ĠALEC\":47122,\"OOOO\":47123,\"isconsin\":47124,\"Ġconstants\":47125,\"ĠTemplar\":47126,\"Accept\":47127,\"Ġmascul\":47128,\"enegger\":47129,\"ampires\":47130,\"Rated\":47131,\"lua\":47132,\"ucl\":47133,\"ĠSequence\":47134,\"ĠNRS\":47135,\"STD\":47136,\"Cra\":47137,\"autions\":47138,\"ĠKernel\":47139,\"oleon\":47140,\"htaking\":47141,\"ancial\":47142,\"Pages\":47143,\"orthodox\":47144,\"ropy\":47145,\"EEE\":47146,\"Ġtranssexual\":47147,\"?????\":47148,\"Ġsurpr\":47149,\"arthy\":47150,\"ĠPsychic\":47151,\"Ġdorsal\":47152,\"cember\":47153,\"joice\":47154,\"/+\":47155,\"verend\":47156,\"uint\":47157,\"Ġderog\":47158,\"Subject\":47159,\"hemat\":47160,\"!]\":47161,\"Ġ);\":47162,\"Ġmeshes\":47163,\"Ġreperc\":47164,\"ĠTerran\":47165,\"åĪ\":47166,\"Load\":47167,\"å¹\":47168,\"ikarp\":47169,\"rompt\":47170,\"Ġgoblins\":47171,\"ĠShattered\":47172,\"tests\":47173,\"Spread\":47174,\"ĠNaruto\":47175,\"Ġpredic\":47176,\"Hyp\":47177,\"ĠArkham\":47178,\"ĠNASL\":47179,\"Material\":47180,\"Rule\":47181,\"raviolet\":47182,\"ĠKlingon\":47183,\"Memory\":47184,\"acers\":47185,\"Known\":47186,\"Important\":47187,\"ĠÎ±\":47188,\"Ġtraged\":47189,\"Ġshalt\":47190,\"Ġiso\":47191,\"ĠJSON\":47192,\"Instant\":47193,\"Ġpg\":47194,\"Ġexponent\":47195,\"formance\":47196,\"bitcoin\":47197,\"DOS\":47198,\"cheat\":47199,\"Ġrook\":47200,\"ĠBiol\":47201,\"noticed\":47202,\"Ġtwent\":47203,\"ĠRedux\":47204,\"ĠBorderlands\":47205,\"Supported\":47206,\"TRUMP\":47207,\"Ġturrets\":47208,\"include\":47209,\"Effect\":47210,\"Ġdisg\":47211,\"ophical\":47212,\"ĠFaction\":47213,\"wiki\":47214,\"Ġsrc\":47215,\"Laun\":47216,\"TIT\":47217,\"Ġorbs\":47218,\"Ġincompet\":47219,\"Ġdescriptor\":47220,\"ĠTrog\":47221,\"Contribut\":47222,\"ĠGodd\":47223,\"inances\":47224,\"Ult\":47225,\"lyak\":47226,\"âĢ¢âĢ¢âĢ¢âĢ¢\":47227,\"stitial\":47228,\"essim\":47229,\"Graphics\":47230,\"ubis\":47231,\"Ġegreg\":47232,\"DEV\":47233,\"Ġannotations\":47234,\"Yang\":47235,\"ĠDruid\":47236,\"ĠInquisition\":47237,\"ohydrate\":47238,\"Critical\":47239,\"æĸ\":47240,\"Sample\":47241,\"ĠPref\":47242,\"ĠUnleashed\":47243,\"ĠAccessed\":47244,\"Ġconceptions\":47245,\"Minor\":47246,\"pard\":47247,\"prus\":47248,\"Factory\":47249,\"thinkable\":47250,\"Ġexecutable\":47251,\"chapter\":47252,\"inyl\":47253,\"Display\":47254,\"ilater\":47255,\"Released\":47256,\"ĠDirectX\":47257,\"aneers\":47258,\"Ġ______\":47259,\"ĠHilbert\":47260,\"Options\":47261,\"Ġsorcery\":47262,\"esm\":47263,\"ÏĦ\":47264,\"Ġdescript\":47265,\"ĠTycoon\":47266,\"psons\":47267,\"Ġcov\":47268,\"Launch\":47269,\"ogeneity\":47270,\"Ġsacrific\":47271,\"ADRA\":47272,\"netflix\":47273,\"flix\":47274,\"usage\":47275,\"properties\":47276,\"attach\":47277,\"req\":47278,\"Resource\":47279,\"requisite\":47280,\"1007\":47281,\"ĠMIDI\":47282,\"ĠZoro\":47283,\"Tue\":47284,\"hower\":47285,\"dds\":47286,\"ynasty\":47287,\"headers\":47288,\"Ġdisproportion\":47289,\"omaly\":47290,\"Ġvim\":47291,\"inces\":47292,\"edient\":47293,\"ĠWraith\":47294,\"ilibrium\":47295,\"Hig\":47296,\"ĠFrie\":47297,\"Meat\":47298,\"ldom\":47299,\"KNOWN\":47300,\"orgetown\":47301,\"Improve\":47302,\"10000\":47303,\"Ġretarded\":47304,\"Disclaimer\":47305,\"Ġunfocused\":47306,\"ĠUnsure\":47307,\"ĠElixir\":47308,\"idth\":47309,\"atural\":47310,\"ĠErr\":47311,\"Critics\":47312,\"ĠBows\":47313,\"ifferent\":47314,\"proxy\":47315,\"Lic\":47316,\"aucas\":47317,\"rolet\":47318,\"ĠCoC\":47319,\"Ġdoesnt\":47320,\"phabet\":47321,\"Version\":47322,\"Ġhepat\":47323,\"gif\":47324,\"izophren\":47325,\"ãĥ»\":47326,\"ĠGutenberg\":47327,\"Î²\":47328,\"phans\":47329,\"Scene\":47330,\"Ġaccomp\":47331,\"ilings\":47332,\"rypted\":47333,\"aceae\":47334,\"arantine\":47335,\"heses\":47336,\"iasco\":47337,\"lopp\":47338,\"ĠGSL\":47339,\"disk\":47340,\"ãĢģ\":47341,\"0010\":47342,\"ĠOutbreak\":47343,\"Column\":47344,\"odox\":47345,\"atform\":47346,\"ĠThrust\":47347,\"ĠSVG\":47348,\"Enhanced\":47349,\"Â¯\":47350,\"Tools\":47351,\"rogens\":47352,\"xus\":47353,\"Available\":47354,\"zbollah\":47355,\"è¡\":47356,\"osate\":47357,\"usb\":47358,\"ordes\":47359,\"Matrix\":47360,\"ĠBlazing\":47361,\"ascus\":47362,\"ĠSovere\":47363,\"hement\":47364,\"*:\":47365,\"amaru\":47366,\"Ġparsed\":47367,\"Bonus\":47368,\"otrop\":47369,\"spell\":47370,\"ancock\":47371,\"ĠEnchant\":47372,\"vP\":47373,\"ĠReferred\":47374,\"Ġalot\":47375,\"ĠRuntime\":47376,\"ĠFn\":47377,\"CPU\":47378,\"ĠNicotine\":47379,\"External\":47380,\"ĠNightmares\":47381,\"Ġentropy\":47382,\"kB\":47383,\"ĠRealms\":47384,\"Ġ##\":47385,\"Ġsubmar\":47386,\"ĠSlime\":47387,\"itual\":47388,\"ĠBastard\":47389,\"Ġacknowled\":47390,\"Magazine\":47391,\"rendered\":47392,\"ircraft\":47393,\"CSS\":47394,\"Numbers\":47395,\"Pg\":47396,\"utenant\":47397,\"ĠPalest\":47398,\"ĠRoose\":47399,\"udicrous\":47400,\"anooga\":47401,\"Unt\":47402,\"Ġcapacitor\":47403,\"Ġschema\":47404,\"hematic\":47405,\"ĠPinball\":47406,\"endars\":47407,\"Ġ===\":47408,\"nsic\":47409,\"ipedia\":47410,\"Ġchromos\":47411,\"ĠmRNA\":47412,\"Ct\":47413,\"ĠPaladin\":47414,\"sonian\":47415,\"Ġæ\":47416,\"ajor\":47417,\"repeat\":47418,\"ortex\":47419,\"ĠHeroic\":47420,\"ĠHera\":47421,\"ociated\":47422,\"Ġdebug\":47423,\"osher\":47424,\"upiter\":47425,\"_.\":47426,\"Ġsys\":47427,\"ĠDownloads\":47428,\"','\":47429,\"Adventure\":47430,\"FORE\":47431,\"ocument\":47432,\"arning\":47433,\"Ġmiscon\":47434,\"vidia\":47435,\"Cod\":47436,\"ibraries\":47437,\"buffer\":47438,\"cdn\":47439,\"ĠModes\":47440,\"tarian\":47441,\"ĠPyro\":47442,\"ĠFixes\":47443,\"ĠâĪ\":47444,\"ĠCf\":47445,\"Testing\":47446,\"Byte\":47447,\"nants\":47448,\"oufl\":47449,\"ĠCipher\":47450,\"Aim\":47451,\"ĠAfgh\":47452,\"ĠStarCraft\":47453,\"intendent\":47454,\"akespe\":47455,\"Apply\":47456,\">>>\":47457,\"Lenin\":47458,\"ĠShaman\":47459,\"%\\\"\":47460,\"ĠFrenzy\":47461,\"illusion\":47462,\"===\":47463,\"Website\":47464,\"Allow\":47465,\"ĠBinary\":47466,\"ensable\":47467,\"ĠEmpires\":47468,\"Ġpromul\":47469,\"ormonal\":47470,\"ileaks\":47471,\"ĠAmmo\":47472,\"assies\":47473,\"atican\":47474,\"avior\":47475,\"ĠIter\":47476,\"1024\":47477,\"uesday\":47478,\"ĠAppears\":47479,\"achine\":47480,\"Problem\":47481,\"ousy\":47482,\"ramid\":47483,\"nox\":47484,\"Â·Â·\":47485,\"omething\":47486,\"ĠPurg\":47487,\"artney\":47488,\"Ġ0000\":47489,\"psey\":47490,\"Ġglutamate\":47491,\"ĠActivate\":47492,\"Repl\":47493,\"Priv\":47494,\"cyclop\":47495,\"ĠHispan\":47496,\"atsuki\":47497,\"Likewise\":47498,\"JOHN\":47499,\"POSE\":47500,\"pherd\":47501,\"schild\":47502,\"Ġsuffix\":47503,\"åĲ\":47504,\"Ġoptionally\":47505,\"ĠRecomm\":47506,\"ĠSpawn\":47507,\"ARDIS\":47508,\"Ġinconsist\":47509,\"Ġenglish\":47510,\"Beta\":47511,\"ĠContains\":47512,\"uddenly\":47513,\"Ġls\":47514,\"Dynamic\":47515,\"åĽ\":47516,\"Ġ{{\":47517,\"dq\":47518,\"Hmm\":47519,\"oliberal\":47520,\"ĠCarnage\":47521,\"ĠRebirth\":47522,\"incerity\":47523,\"Ġproletariat\":47524,\"ĠCrafting\":47525,\"Explore\":47526,\"Ġeld\":47527,\"ĠAnarch\":47528,\"Ġ(>\":47529,\"ĠClockwork\":47530,\"ĠProced\":47531,\"APTER\":47532,\"ĠSorcerer\":47533,\"âĶ\":47534,\"ĠSnape\":47535,\"elist\":47536,\"Balance\":47537,\"Tube\":47538,\"Ġ--------------------\":47539,\"Ġnostalg\":47540,\"ACTED\":47541,\"ĠVID\":47542,\"soever\":47543,\"ignt\":47544,\"Ġhypothal\":47545,\"ĠObj\":47546,\"igure\":47547,\"ĠElves\":47548,\"gorithm\":47549,\"Romney\":47550,\"idable\":47551,\"renheit\":47552,\"aptic\":47553,\"Ġnonex\":47554,\"Profile\":47555,\"Ġscient\":47556,\"ĠAchievements\":47557,\"ĠReload\":47558,\"Products\":47559,\"ampire\":47560,\"pread\":47561,\"ĠYamato\":47562,\"Thread\":47563,\"ĠFML\":47564,\"ĠForsaken\":47565,\"Statistics\":47566,\"Ġ([\":47567,\"utsu\":47568,\"nces\":47569,\"...?\":47570,\"upload\":47571,\"Typ\":47572,\"ĠReflex\":47573,\"Dial\":47574,\"Ġspawns\":47575,\"Server\":47576,\"Ġacquaint\":47577,\"iterranean\":47578,\"='\":47579,\"Device\":47580,\"×¨\":47581,\"ocaly\":47582,\"Remove\":47583,\"Ġ=====\":47584,\"Ġabdom\":47585,\"ideos\":47586,\"Dual\":47587,\"Fax\":47588,\"Ġbesie\":47589,\"ĠAdin\":47590,\"Ġdescrib\":47591,\"Ġiod\":47592,\"Limit\":47593,\"aunders\":47594,\"ĠAssassins\":47595,\"xxxx\":47596,\"ulner\":47597,\"Shipping\":47598,\"Item\":47599,\"fortune\":47600,\"Ġcipher\":47601,\"mA\":47602,\"acerb\":47603,\"ebus\":47604,\"Ġmodifiers\":47605,\"Added\":47606,\"prisingly\":47607,\"Dir\":47608,\"ĠArchangel\":47609,\"umbnails\":47610,\"Huh\":47611,\"ĠWARN\":47612,\"Role\":47613,\"usional\":47614,\"Ġcortical\":47615,\"ĠSCP\":47616,\"ĠException\":47617,\"ĠWarhammer\":47618,\")))\":47619,\"](\":47620,\"Ġsynaptic\":47621,\"Ġcached\":47622,\"archment\":47623,\"Ġtarg\":47624,\"Filter\":47625,\"ĠHades\":47626,\"Ġprinc\":47627,\"halla\":47628,\"ptoms\":47629,\"Ïģ\":47630,\"ructose\":47631,\"termination\":47632,\"Ġcompe\":47633,\"define\":47634,\"Ġprosec\":47635,\"require\":47636,\"ĠCorpse\":47637,\"Abstract\":47638,\"********************************\":47639,\"Used\":47640,\"ĠIbid\":47641,\"trak\":47642,\"ä¸Ń\":47643,\"ĠGABA\":47644,\"åĬ\":47645,\"ĠHegel\":47646,\"Jere\":47647,\"odore\":47648,\"í\":47649,\"namese\":47650,\"Origin\":47651,\"ĠMastery\":47652,\"gerald\":47653,\"Charges\":47654,\"--------------------\":47655,\"Forge\":47656,\"comings\":47657,\"åį\":47658,\"Ġ(&\":47659,\"Ġgrap\":47660,\"Mask\":47661,\"ĠGundam\":47662,\"generic\":47663,\"ĠMalf\":47664,\"raphics\":47665,\"Internal\":47666,\"ourge\":47667,\"Ġirresist\":47668,\"sterdam\":47669,\"Ġendogenous\":47670,\"Export\":47671,\"Ġë\":47672,\"poons\":47673,\"Ġabund\":47674,\"ĠQuantity\":47675,\"Issue\":47676,\"âĪĴ\":47677,\"cknow\":47678,\"Anonymous\":47679,\"ĠDRAG\":47680,\"Wikipedia\":47681,\"Ġsubdu\":47682,\"iverpool\":47683,\"apesh\":47684,\"Ability\":47685,\"ĠCentOS\":47686,\"iseum\":47687,\"lycer\":47688,\"Untitled\":47689,\"Ġlineback\":47690,\"Ġtomat\":47691,\"byte\":47692,\"tile\":47693,\"linux\":47694,\"Palest\":47695,\"canon\":47696,\"FAULT\":47697,\"ĠkHz\":47698,\"Ġhelic\":47699,\"ĠIGF\":47700,\"WARE\":47701,\"Feature\":47702,\"ĠGraveyard\":47703,\"ĠNemesis\":47704,\"akuya\":47705,\"inement\":47706,\"Ġwhence\":47707,\"ractical\":47708,\"Ping\":47709,\"tesque\":47710,\"scroll\":47711,\"espie\":47712,\"Ġasynchronous\":47713,\"ocre\":47714,\"Measure\":47715,\"morph\":47716,\"std\":47717,\"Settings\":47718,\"Course\":47719,\"Ġ],\":47720,\"Ïĥ\":47721,\"Documents\":47722,\"estern\":47723,\"Ġtf\":47724,\"Ġcircumcised\":47725,\"geant\":47726,\"Ġconject\":47727,\"ĠFolder\":47728,\"outube\":47729,\"ĠMedline\":47730,\"Status\":47731,\"ctr\":47732,\"anoia\":47733,\"ĠPowerShell\":47734,\"Chel\":47735,\"Loop\":47736,\"Ġresize\":47737,\"aphael\":47738,\"workshop\":47739,\"velength\":47740,\"hover\":47741,\"flush\":47742,\"ĠÎ²\":47743,\"Task\":47744,\"pedia\":47745,\"ptin\":47746,\"bidden\":47747,\"windows\":47748,\"ĠCaucas\":47749,\"aml\":47750,\"isoft\":47751,\"Ġrs\":47752,\"cgi\":47753,\"urrection\":47754,\"miah\":47755,\"ÏĤ\":47756,\"Ġplaythrough\":47757,\"Reddit\":47758,\"×ľ\":47759,\"Ġannotation\":47760,\"Ġnobles\":47761,\"seq\":47762,\"mares\":47763,\"Ġwik\":47764,\"foreseen\":47765,\"RPG\":47766,\"Ġreper\":47767,\"aredevil\":47768,\"arcity\":47769,\"/\\\"\":47770,\"Ġ});\":47771,\"Ġdiscont\":47772,\"ĠBinding\":47773,\"answered\":47774,\"Mesh\":47775,\"ĠMPEG\":47776,\"Ġperceptual\":47777,\"OTAL\":47778,\"ursive\":47779,\"ãģĦ\":47780,\"Ġplun\":47781,\"onential\":47782,\"ãĤ\":47783,\"ĠReloaded\":47784,\"iscopal\":47785,\"ĠDespair\":47786,\"FIX\":47787,\"Ġheterogeneity\":47788,\",[\":47789,\"ichick\":47790,\"DCS\":47791,\"Ġcooldown\":47792,\"................\":47793,\"Ġsomew\":47794,\"Battery\":47795,\"stract\":47796,\"Attempt\":47797,\"allery\":47798,\"ĠNept\":47799,\"Ġtac\":47800,\"ĠElemental\":47801,\"Function\":47802,\"Ġbindings\":47803,\"versive\":47804,\"ĠWarlock\":47805,\"Response\":47806,\"ĠNPCs\":47807,\"ollower\":47808,\"ĠReborn\":47809,\"Ġphenotype\":47810,\"uscript\":47811,\"Ġpecul\":47812,\"!/\":47813,\"Unique\":47814,\"ĠFreeBSD\":47815,\"ĠChero\":47816,\"Ġcolle\":47817,\"gently\":47818,\"Empty\":47819,\"rss\":47820,\"Ġdd\":47821,\"forge\":47822,\"ĠTraps\":47823,\"×Ķ\":47824,\"iblical\":47825,\"---------\":47826,\"uminati\":47827,\"login\":47828,\"asus\":47829,\"xual\":47830,\"ĠMiko\":47831,\"ĠDrac\":47832,\"ssh\":47833,\"Submit\":47834,\"ĠMultiplayer\":47835,\"leanor\":47836,\"Orig\":47837,\"anism\":47838,\"peror\":47839,\"ĠESV\":47840,\"Ġencour\":47841,\"å°\":47842,\"ĠPLoS\":47843,\"ĠCrusher\":47844,\"ocrates\":47845,\"ynchronous\":47846,\"Â§\":47847,\"ĠLuffy\":47848,\"Lastly\":47849,\"Ġdiffere\":47850,\"okane\":47851,\"Enh\":47852,\"ursor\":47853,\"Ġapopt\":47854,\"ĠTotem\":47855,\"ä½\":47856,\"Honest\":47857,\"xml\":47858,\"Created\":47859,\"Ġteleport\":47860,\"NRS\":47861,\"ccess\":47862,\"ilitary\":47863,\"ackets\":47864,\"Ġenchantment\":47865,\"ĠCunning\":47866,\"ortmund\":47867,\"Altern\":47868,\"Alternatively\":47869,\"ĠLuthor\":47870,\"Publisher\":47871,\"GBT\":47872,\"çĶ\":47873,\"Activity\":47874,\"Ġleptin\":47875,\"æĪ\":47876,\"ĠStarfleet\":47877,\"å¸\":47878,\"oooooooo\":47879,\"Ġlawy\":47880,\"Frag\":47881,\"×ª\":47882,\"yright\":47883,\"cookie\":47884,\"Finish\":47885,\"wikipedia\":47886,\"ĠAbilities\":47887,\"interface\":47888,\"Ġglared\":47889,\"Engineers\":47890,\"ĠAtk\":47891,\"oteric\":47892,\"Ġbyte\":47893,\"ossibility\":47894,\"Label\":47895,\"ĠCSV\":47896,\"Ġè\":47897,\"ĠOblivion\":47898,\"android\":47899,\"rehensive\":47900,\"ĠCommands\":47901,\"clud\":47902,\"ĠTutorial\":47903,\"retched\":47904,\"irlwind\":47905,\"conserv\":47906,\"ministic\":47907,\"void\":47908,\"ernels\":47909,\"alias\":47910,\"ĠDraco\":47911,\"desktop\":47912,\"ĠMormonism\":47913,\"oÄŁ\":47914,\"kef\":47915,\"Ġtimestamp\":47916,\"WAYS\":47917,\"ãģĹ\":47918,\"\\\"(\":47919,\"eneg\":47920,\"CHAT\":47921,\"Ġnpm\":47922,\"ĠGrenade\":47923,\"rongh\":47924,\"dinand\":47925,\"Definition\":47926,\"ĠInteger\":47927,\"Ġmodifier\":47928,\"Ġdex\":47929,\"ĠParameters\":47930,\"andestine\":47931,\"ĠSHALL\":47932,\"Purchase\":47933,\"enaries\":47934,\"Ġstarship\":47935,\"Armor\":47936,\"Skill\":47937,\"Ġlookup\":47938,\"verages\":47939,\"Minimum\":47940,\"ĠBleach\":47941,\"Ġdf\":47942,\"inosaur\":47943,\"ixel\":47944,\"Zip\":47945,\"temp\":47946,\"ruby\":47947,\"Fram\":47948,\"sword\":47949,\"Minecraft\":47950,\"strous\":47951,\"Client\":47952,\"ĠBarbarian\":47953,\"æĹ\":47954,\"USER\":47955,\"ĠMehran\":47956,\"axies\":47957,\"ermanent\":47958,\"ĠHeader\":47959,\"ablishment\":47960,\"hyde\":47961,\"Snake\":47962,\"ĠTelesc\":47963,\"Pocket\":47964,\"Ġ........\":47965,\"Destroy\":47966,\"Method\":47967,\"ĠZup\":47968,\"olulu\":47969,\"Ġunemploy\":47970,\"Temp\":47971,\"ĠExplicit\":47972,\"äºº\":47973,\"cache\":47974,\"innamon\":47975,\"Ġunavoid\":47976,\"Summary\":47977,\"Ġappre\":47978,\"Ġtaxp\":47979,\"XXX\":47980,\"ieval\":47981,\"ĠSummon\":47982,\"å¤\":47983,\"Lear\":47984,\"ibliography\":47985,\"CLASS\":47986,\"dimension\":47987,\"ĠHorde\":47988,\"Ġfilesystem\":47989,\"ĠQiao\":47990,\"obbies\":47991,\"DIR\":47992,\"Ġimpedance\":47993,\"éĩ\":47994,\"Names\":47995,\"ĠDrupal\":47996,\"Applic\":47997,\"imei\":47998,\"ynchron\":47999,\"Ire\":48000,\"ĠMinion\":48001,\"ĠHaste\":48002,\"ä¿\":48003,\"Ġ(=\":48004,\"LinkedIn\":48005,\"Maps\":48006,\"ifacts\":48007,\"Damage\":48008,\"odynam\":48009,\"ĠShroud\":48010,\"Ancient\":48011,\"enhagen\":48012,\"Tact\":48013,\"anship\":48014,\"aturdays\":48015,\"ãģ«\":48016,\"ikhail\":48017,\"ãģ®\":48018,\"framework\":48019,\"lication\":48020,\"âĢ¦]\":48021,\"Plug\":48022,\"ĠLilith\":48023,\"browser\":48024,\"offset\":48025,\"ĠJuda\":48026,\"ciating\":48027,\"console\":48028,\"Ġ=================\":48029,\"._\":48030,\"ĠPuzz\":48031,\"OPLE\":48032,\"erial\":48033,\"OHN\":48034,\"ĠGolem\":48035,\"ierrez\":48036,\"Ġ},\":48037,\"inition\":48038,\"insula\":48039,\"ĠEntered\":48040,\"greSQL\":48041,\"ĠFlask\":48042,\"ĠXCOM\":48043,\"fixes\":48044,\"ĠWeasley\":48045,\"arser\":48046,\"Ġrc\":48047,\"microsoft\":48048,\"HHHH\":48049,\"INFO\":48050,\"rehend\":48051,\"Ġpolymorph\":48052,\"Button\":48053,\"âī\":48054,\"QUI\":48055,\"twitch\":48056,\"jriwal\":48057,\"ĠSaiyan\":48058,\"Ġadherent\":48059,\"acters\":48060,\"arthed\":48061,\"âĢł\":48062,\"Ġfoss\":48063,\"ã\":48064,\"Quote\":48065,\"ependent\":48066,\"Ġhorr\":48067,\"UGC\":48068,\"Weiss\":48069,\"styles\":48070,\"advertisement\":48071,\"Credits\":48072,\"Lua\":48073,\"ĠUCH\":48074,\"Ġhorrend\":48075,\"Ġminion\":48076,\">,\":48077,\"ãĥ³\":48078,\"Ġinclud\":48079,\"Compar\":48080,\"Ġ[]\":48081,\"Ġ(<\":48082,\"Phones\":48083,\"paralleled\":48084,\"HTML\":48085,\"Ġ(%\":48086,\"raltar\":48087,\"Ġamd\":48088,\"Maximum\":48089,\"ĠSolitaire\":48090,\"SCP\":48091,\"ĠVaugh\":48092,\"ĠCLR\":48093,\"database\":48094,\"module\":48095,\"Ì¶\":48096,\"Capture\":48097,\"Window\":48098,\"ubuntu\":48099,\"Includes\":48100,\"ĠUriel\":48101,\"ORPG\":48102,\"Îº\":48103,\"âĪ\":48104,\"ä¸Ģ\":48105,\"Ġdexter\":48106,\"ĠGlac\":48107,\"slice\":48108,\"HAHAHAHA\":48109,\"\\\\\\\"\":48110,\"lations\":48111,\"ÙĲ\":48112,\"ĠAUTH\":48113,\"earch\":48114,\"ĠSocket\":48115,\"Character\":48116,\"Sort\":48117,\"Ġindist\":48118,\"/_\":48119,\"ĠAntar\":48120,\"ifix\":48121,\"Ġlich\":48122,\"variable\":48123,\"_(\":48124,\"Ġgui\":48125,\"Herm\":48126,\"elvet\":48127,\"è¯\":48128,\"Developer\":48129,\"Ġkcal\":48130,\"ciation\":48131,\"Transaction\":48132,\"Ġdocker\":48133,\"###\":48134,\"ĠVegeta\":48135,\"Result\":48136,\"ocamp\":48137,\"aughtered\":48138,\"Increase\":48139,\"aples\":48140,\"iannopoulos\":48141,\"zbek\":48142,\"estyles\":48143,\"emonium\":48144,\"è¿\":48145,\"ĠFANT\":48146,\"Reason\":48147,\"Elsewhere\":48148,\"\\\"\\\"\":48149,\"ĠArtifact\":48150,\"Authent\":48151,\"herical\":48152,\"Ġmembr\":48153,\"socket\":48154,\"Elsa\":48155,\"Condition\":48156,\"Ġlapt\":48157,\"Ġsorcerer\":48158,\"Layer\":48159,\"apters\":48160,\"Ġveter\":48161,\"Myth\":48162,\"ensical\":48163,\"ÏĢ\":48164,\"noxious\":48165,\"Ġunpre\":48166,\"Flags\":48167,\"OOOOOOOO\":48168,\"Ġincent\":48169,\"Combat\":48170,\"Session\":48171,\"Ġteleportation\":48172,\"éĢ\":48173,\"ortment\":48174,\"Admin\":48175,\"Fixed\":48176,\"×Ļ\":48177,\"Ġconfir\":48178,\"ãģŁ\":48179,\"morrow\":48180,\"osponsors\":48181,\"\\\\/\":48182,\"ictionary\":48183,\"Num\":48184,\"Ġquir\":48185,\"åº\":48186,\"à¨\":48187,\"Ġ<<\":48188,\"Attempts\":48189,\"ãģ§\":48190,\"Î»\":48191,\"Features\":48192,\"XXXX\":48193,\"Ġinflamm\":48194,\"VERSION\":48195,\"ortality\":48196,\"spawn\":48197,\"ratulations\":48198,\"Ġcharism\":48199,\"Ġ&&\":48200,\"Dialogue\":48201,\"luster\":48202,\"<<\":48203,\"args\":48204,\"redients\":48205,\"Ġpredicate\":48206,\"qqa\":48207,\"etheus\":48208,\"Ġ(!\":48209,\"Ġshowc\":48210,\"cmd\":48211,\"bringer\":48212,\"Ġcoh\":48213,\"Input\":48214,\"ĠFANTASY\":48215,\"Ġfict\":48216,\"Blocks\":48217,\"Install\":48218,\"vector\":48219,\"umblr\":48220,\"agnar\":48221,\"Array\":48222,\"Ġembry\":48223,\"Ġtheoret\":48224,\"Ġhref\":48225,\"irrel\":48226,\"irements\":48227,\"iations\":48228,\"Ġ(/\":48229,\"Thumbnail\":48230,\"Ġhashes\":48231,\"^^\":48232,\"Copy\":48233,\"Ġeq\":48234,\"translation\":48235,\"Favorite\":48236,\"Fail\":48237,\"Ġogre\":48238,\"isites\":48239,\"Merit\":48240,\"ãģ¦\":48241,\"DATA\":48242,\"rarily\":48243,\"igmatic\":48244,\"Sequ\":48245,\"Els\":48246,\"ãģª\":48247,\"lehem\":48248,\"requency\":48249,\"aughed\":48250,\"Ġdistingu\":48251,\"Ġartific\":48252,\"Ġdwarves\":48253,\"Í\":48254,\"resy\":48255,\"~~\":48256,\"sofar\":48257,\"ideon\":48258,\"ozyg\":48259,\"EEEE\":48260,\"ĠMelee\":48261,\"å¤§\":48262,\"tumblr\":48263,\"ssl\":48264,\"Wra\":48265,\"ONSORED\":48266,\"Ġvowel\":48267,\"},\":48268,\"Vari\":48269,\"cientious\":48270,\"Node\":48271,\"Ġsorce\":48272,\"========\":48273,\"perse\":48274,\"Detailed\":48275,\"isphere\":48276,\"Background\":48277,\"ĺħ\":48278,\"Redd\":48279,\"ìĿ\":48280,\"ãģ¨\":48281,\"ĠCTRL\":48282,\"Ġç\":48283,\"iculty\":48284,\"ername\":48285,\"Ġns\":48286,\"Deploy\":48287,\"Ġhapp\":48288,\"Ġ///\":48289,\"Begin\":48290,\"Ġgp\":48291,\"$.\":48292,\"Output\":48293,\"Suggest\":48294,\"×Ĳ\":48295,\"ĠToggle\":48296,\"Ġnutrit\":48297,\"Ġ\\\\\\\"\":48298,\"Ġpreval\":48299,\"Ġsubreddits\":48300,\"Menu\":48301,\"Amount\":48302,\"ĠWasteland\":48303,\"Ġsprites\":48304,\"Ġshader\":48305,\"Ġ;)\":48306,\"NAME\":48307,\"CLUD\":48308,\"Ġgoblin\":48309,\"Refer\":48310,\"ÙĴ\":48311,\"á¹\":48312,\"Improved\":48313,\"endiary\":48314,\"Ġassail\":48315,\"chieve\":48316,\"reply\":48317,\"Ġcontrad\":48318,\"cients\":48319,\"GROUP\":48320,\"Controller\":48321,\"omsky\":48322,\"chemist\":48323,\"packages\":48324,\"ombies\":48325,\"scl\":48326,\"Ġibn\":48327,\"çĽ\":48328,\":(\":48329,\"ĠMinotaur\":48330,\"niper\":48331,\"====\":48332,\"Ġsubsc\":48333,\"è¦\":48334,\"Ġinteger\":48335,\"Ġ\\\"-\":48336,\"Ġtheorem\":48337,\"utenberg\":48338,\"Trigger\":48339,\"github\":48340,\"ä¼\":48341,\"##\":48342,\"xtap\":48343,\"okÃ©\":48344,\"ilial\":48345,\"idepress\":48346,\":\\\\\":48347,\"Param\":48348,\"Correction\":48349,\"Ã¯ve\":48350,\"Chest\":48351,\"×©\":48352,\"ĠÏĦ\":48353,\"Ġrespawn\":48354,\"Ġrall\":48355,\"Ġcreatine\":48356,\"umsy\":48357,\"ĠTemplate\":48358,\"foo\":48359,\"query\":48360,\"Ġmanufact\":48361,\"Hardware\":48362,\"iframe\":48363,\"Ġ-------\":48364,\"Ġrecip\":48365,\"ĠAttributes\":48366,\"Ġforeskin\":48367,\"ãĤĭ\":48368,\"ãĥĦ\":48369,\"uania\":48370,\"................................................................\":48371,\"Ġphylogen\":48372,\"eaturing\":48373,\"Ġsprite\":48374,\"Ġinvari\":48375,\"DonaldTrump\":48376,\"({\":48377,\"ĠMalfoy\":48378,\"Gamer\":48379,\"ĠPlugin\":48380,\"Î³\":48381,\"Query\":48382,\"ĠPuzzles\":48383,\"inventory\":48384,\"trl\":48385,\"Insert\":48386,\"Ġawa\":48387,\"ĠWerewolf\":48388,\"Ġhorizont\":48389,\"×ŀ\":48390,\"Ġcunt\":48391,\"]]\":48392,\"ĠByz\":48393,\"Mouse\":48394,\"Ġ[[\":48395,\"ĠCthulhu\":48396,\"ĠDRAGON\":48397,\"Default\":48398,\"ĠPresbyter\":48399,\"Ġff\":48400,\"Ġorcs\":48401,\"Construct\":48402,\"ĠDebug\":48403,\"Ġ*/\":48404,\"×ĳ\":48405,\"Ġembr\":48406,\"License\":48407,\"css\":48408,\"incinn\":48409,\"Prosecut\":48410,\"Ġsugg\":48411,\"å¾\":48412,\"ĠUndead\":48413,\"æĿ\":48414,\"Ġfs\":48415,\"Ġthw\":48416,\"Vector\":48417,\"åĮ\":48418,\"settings\":48419,\"å¯\":48420,\"Ġssh\":48421,\"ĠConverted\":48422,\"ãĤĴ\":48423,\"risome\":48424,\"Ġagre\":48425,\"Collection\":48426,\"cmp\":48427,\"puter\":48428,\"alloc\":48429,\"Ġé\":48430,\"ascade\":48431,\"ĠSpells\":48432,\"Ġ:-)\":48433,\"Haunted\":48434,\"Ġadolesc\":48435,\"FORMATION\":48436,\"ĠImperium\":48437,\"ãĥ¼\":48438,\"Supplement\":48439,\"Render\":48440,\"Theme\":48441,\"ĠTorment\":48442,\"([\":48443,\"ëĭ\":48444,\"Ġhtml\":48445,\"Ġjuven\":48446,\"ĠSiber\":48447,\"Ġdaemon\":48448,\"ivariate\":48449,\"objects\":48450,\"negie\":48451,\"Ġindu\":48452,\"landish\":48453,\"Meta\":48454,\"Impl\":48455,\"Ġglyph\":48456,\"Ġ-->\":48457,\"Ġstreng\":48458,\"agascar\":48459,\"guyen\":48460,\"((\":48461,\")[\":48462,\"ĠNorn\":48463,\"Ġhippocamp\":48464,\"ĠÂ¯\":48465,\"îĢ\":48466,\"Connection\":48467,\"PATH\":48468,\"mbuds\":48469,\"ĠShards\":48470,\"Ġadvoc\":48471,\"Ġsimulac\":48472,\"âĸĳ\":48473,\"!?\\\"\":48474,\"ĠPotion\":48475,\"Ġamulet\":48476,\"ĠFnatic\":48477,\"Ġcryptoc\":48478,\"wav\":48479,\"radius\":48480,\"pkg\":48481,\"ĠMFT\":48482,\"æĢ\":48483,\"Ġtoile\":48484,\"Items\":48485,\"ifference\":48486,\"errors\":48487,\"ĠCelt\":48488,\"Ġunpop\":48489,\"ilogy\":48490,\"6666\":48491,\"hesda\":48492,\"Instruct\":48493,\"å·\":48494,\"Materials\":48495,\"ettings\":48496,\"Percent\":48497,\"Ġresistor\":48498,\"tymology\":48499,\"Ġdeprecated\":48500,\"Ġgrep\":48501,\"ĠWRITE\":48502,\"Ġtriv\":48503,\"Ġscrut\":48504,\"[/\":48505,\"anyl\":48506,\"skirts\":48507,\"MSN\":48508,\"ĠCodec\":48509,\"ecd\":48510,\"Anth\":48511,\"){\":48512,\"%]\":48513,\"veyard\":48514,\"aspberry\":48515,\"ãĢ\":48516,\"Reward\":48517,\"rha\":48518,\"Stretch\":48519,\"]-\":48520,\"Prev\":48521,\"Context\":48522,\"Ġlinux\":48523,\"HAHA\":48524,\"perties\":48525,\"ĠVIDE\":48526,\"Domain\":48527,\"Ġmurd\":48528,\"ĠLegions\":48529,\"apache\":48530,\"æŃ\":48531,\"Pause\":48532,\"Temperature\":48533,\"ufact\":48534,\"igslist\":48535,\"ĠRetrieved\":48536,\"èª\":48537,\"ãģĮ\":48538,\"Ingredients\":48539,\"ruary\":48540,\"dyl\":48541,\"Alias\":48542,\"ĠÎĶ\":48543,\"Ġinval\":48544,\"amsung\":48545,\"!--\":48546,\"olean\":48547,\"æī\":48548,\"ãģ¯\":48549,\"Ġcoefficients\":48550,\"ĠDHCP\":48551,\"âĨĴ\":48552,\"utonium\":48553,\":[\":48554,\"âĹ\":48555,\"cli\":48556,\"Container\":48557,\"å¼\":48558,\"nexus\":48559,\"SOURCE\":48560,\"Ò\":48561,\"=/\":48562,\"Ġmysql\":48563,\"ĠGained\":48564,\"Ġ/*\":48565,\"uncture\":48566,\"Ġstatically\":48567,\"âĸł\":48568,\"æĺ¯\":48569,\"æ°\":48570,\"estamp\":48571,\"Cache\":48572,\"ulkan\":48573,\"staking\":48574,\"apter\":48575,\"ãģ¾\":48576,\"ĠÎ¼g\":48577,\"Ġtremend\":48578,\"ĠPiercing\":48579,\"naissance\":48580,\"ĠHealer\":48581,\"Enabled\":48582,\"éģ\":48583,\"âĸ\":48584,\"ĠThumbnails\":48585,\"Ġhither\":48586,\"Format\":48587,\"utherland\":48588,\"íķ\":48589,\"Ġdestro\":48590,\"fff\":48591,\"execute\":48592,\"msg\":48593,\"romancer\":48594,\"ĠCanaver\":48595,\"ĠVaults\":48596,\"oided\":48597,\"iage\":48598,\"Ġimg\":48599,\"summary\":48600,\"]);\":48601,\"ĠABE\":48602,\"ĠGamergate\":48603,\"utherford\":48604,\"Ġoverwrite\":48605,\"enment\":48606,\"æķ\":48607,\"Ġsystemd\":48608,\"tif\":48609,\"]).\":48610,\"ãĤ¤\":48611,\"Widget\":48612,\"======\":48613,\"(-\":48614,\"Ġ\\\"+\":48615,\"ĠIncarnation\":48616,\"æĥ\":48617,\"ï¿½ï¿½ï¿½\":48618,\"GUI\":48619,\"èĥ\":48620,\"forums\":48621,\"Ġrunes\":48622,\"Ġâī¤\":48623,\"Ġdefic\":48624,\"Distance\":48625,\"directory\":48626,\"ĠHorus\":48627,\"iltr\":48628,\"ortium\":48629,\"Ġ./\":48630,\"bda\":48631,\"owship\":48632,\"ĠâĨĳ\":48633,\"}.\":48634,\"åĩ\":48635,\"1027\":48636,\"Weapons\":48637,\"lucent\":48638,\"Ġauth\":48639,\";;\":48640,\"Recommended\":48641,\"Ġsurv\":48642,\"Ġvm\":48643,\"ĠStronghold\":48644,\"Ġparan\":48645,\"ĠTrance\":48646,\"æĺ\":48647,\"Ġsovere\":48648,\"Ġcorrid\":48649,\"ĠPwr\":48650,\"Ġ[/\":48651,\"Ġseq\":48652,\"Population\":48653,\"Ġ[];\":48654,\"Ġreferen\":48655,\"ĠInstr\":48656,\"ĠStamina\":48657,\"kernel\":48658,\"Python\":48659,\"-+\":48660,\"Ġallele\":48661,\"éĽ\":48662,\"isode\":48663,\"ä¸į\":48664,\"otonin\":48665,\"modules\":48666,\"Notable\":48667,\"Spell\":48668,\"\\\\\\\\\":48669,\"Pref\":48670,\"Ġdatas\":48671,\"setup\":48672,\"Ġhapl\":48673,\"Height\":48674,\"åĭ\":48675,\"ãģ£\":48676,\"]),\":48677,\"Handle\":48678,\"umenthal\":48679,\"Package\":48680,\"Ġenthus\":48681,\"Ġunsus\":48682,\"Narr\":48683,\"Examples\":48684,\"FAQ\":48685,\"REDACTED\":48686,\"Ġnotor\":48687,\"Enable\":48688,\"Pattern\":48689,\"aeda\":48690,\">.\":48691,\"CHECK\":48692,\"Ġï¿½ï¿½ï¿½ï¿½\":48693,\"Ġ'.\":48694,\"Ġãĥ\":48695,\"append\":48696,\"ï¿½ï¿½ï¿½ï¿½\":48697,\"gemony\":48698,\"terness\":48699,\"ĠHaku\":48700,\"NVIDIA\":48701,\"queue\":48702,\"Bind\":48703,\"Ġneigh\":48704,\"armor\":48705,\"retty\":48706,\"LOD\":48707,\"plugins\":48708,\"Ġ/>\":48709,\"TYPE\":48710,\"Ġ4096\":48711,\"-------\":48712,\"Preview\":48713,\"FML\":48714,\"Ġproletarian\":48715,\"zees\":48716,\"enfranch\":48717,\"ãģĨ\":48718,\"Ctrl\":48719,\"Module\":48720,\"ĠSurviv\":48721,\"ĠStarcraft\":48722,\"rored\":48723,\"reddit\":48724,\"Ġrul\":48725,\"Ġtx\":48726,\"Ġmage\":48727,\"Sword\":48728,\"Ġ~/\":48729,\"Effects\":48730,\"éļ\":48731,\"ä¹\":48732,\"Sensor\":48733,\"Solution\":48734,\"ãģĻ\":48735,\"Arcade\":48736,\"Ġpredec\":48737,\"Values\":48738,\"Length\":48739,\"Ġfortun\":48740,\"ttp\":48741,\"\\\"[\":48742,\"tmp\":48743,\"ĠBerserker\":48744,\"åĨ\":48745,\"ositories\":48746,\"Ġcouncill\":48747,\"ffff\":48748,\"));\":48749,\"Recipe\":48750,\"ĠASCII\":48751,\"âĦ¢:\":48752,\"ä\":48753,\"Ġhorm\":48754,\"=>\":48755,\"sers\":48756,\"ãģĭ\":48757,\"Recommend\":48758,\"['\":48759,\"agame\":48760,\"Animation\":48761,\"aucuses\":48762,\"Discussion\":48763,\"Ġhelicop\":48764,\"å¿\":48765,\"Float\":48766,\"Component\":48767,\"instance\":48768,\"Ġfoo\":48769,\"localhost\":48770,\"=-\":48771,\"Offset\":48772,\"Psy\":48773,\"ĠGohan\":48774,\"buquerque\":48775,\"Ġdefe\":48776,\"chwitz\":48777,\"parse\":48778,\"Ġdors\":48779,\"Ġspons\":48780,\"Ġasync\":48781,\"agonists\":48782,\"Ġindo\":48783,\".>>\":48784,\"ĠDisciple\":48785,\"Ġfilename\":48786,\"rency\":48787,\"ĠDise\":48788,\"Ġ\\\"/\":48789,\"template\":48790,\"ãĤ¹\":48791,\"swers\":48792,\"Ġ++\":48793,\"Ġ[(\":48794,\"thora\":48795,\"ĠDepths\":48796,\"livious\":48797,\"Ġdisadvant\":48798,\"foundland\":48799,\"Upload\":48800,\"ĠÂ§Â§\":48801,\"Ġsophistic\":48802,\";}\":48803,\"izont\":48804,\"\\\"}\":48805,\"estial\":48806,\"Ranked\":48807,\"ĠOccupations\":48808,\"LEASE\":48809,\"ĠOgre\":48810,\"folder\":48811,\"Plot\":48812,\"farious\":48813,\"Ġsuscept\":48814,\"Types\":48815,\"Discuss\":48816,\"Ġ'/\":48817,\"æµ\":48818,\"earable\":48819,\"æ³\":48820,\"Tile\":48821,\"iatus\":48822,\"åŃ\":48823,\"Ġreperto\":48824,\"Helper\":48825,\"Returns\":48826,\"ä¸Ĭ\":48827,\"imaru\":48828,\"Ġreq\":48829,\"Ġdissatisf\":48830,\"multipl\":48831,\"}{\":48832,\"-[\":48833,\"itial\":48834,\"*/\":48835,\"Config\":48836,\"Example\":48837,\"ĠjQuery\":48838,\"Mods\":48839,\"ĠGPIO\":48840,\"Ġlaun\":48841,\"layout\":48842,\"cised\":48843,\"Ġ......\":48844,\"+++\":48845,\"prototype\":48846,\"Exception\":48847,\"Ġsubsections\":48848,\"Ġresemb\":48849,\"Ġâĩ\":48850,\"ĠPubMed\":48851,\"username\":48852,\"Ġaggro\":48853,\"éĥ\":48854,\"Ġ};\":48855,\"ĠMages\":48856,\"ryu\":48857,\"apons\":48858,\"Optional\":48859,\"ĠAncients\":48860,\"ãĤĬ\":48861,\"Quotes\":48862,\"oaded\":48863,\"Ġsuspic\":48864,\"inline\":48865,\"omial\":48866,\"ĠMahjong\":48867,\"auntlets\":48868,\"Ġanarchism\":48869,\"Ġsubclass\":48870,\"ĠMLG\":48871,\"...]\":48872,\"Dialog\":48873,\"uphem\":48874,\"Ġrecursive\":48875,\"7601\":48876,\"frac\":48877,\"Else\":48878,\"ĠSeverus\":48879,\"},{\\\"\":48880,\"ĠCLIENT\":48881,\"Ġjavascript\":48882,\"sama\":48883,\"ĠLearns\":48884,\"ãĤĤ\":48885,\"Upgrade\":48886,\"Listener\":48887,\"Ġsnipp\":48888,\"Ġrune\":48889,\"ĠTTL\":48890,\"ertation\":48891,\"olicy\":48892,\"=\\\"\\\"\":48893,\"«ĺ\":48894,\"Ġexpr\":48895,\"ovych\":48896,\"Ġãģ\":48897,\"_-_\":48898,\"munition\":48899,\"////\":48900,\"func\":48901,\">>>>\":48902,\"Provider\":48903,\"Ïī\":48904,\"BUG\":48905,\"Ġ[-\":48906,\"Ġarrang\":48907,\"merce\":48908,\"ãĥ\":48909,\"incarn\":48910,\"Valid\":48911,\"ĠAether\":48912,\"ãĤĵ\":48913,\"ĠUTF\":48914,\"ĠMonstrous\":48915,\"ãĤĮ\":48916,\"hedon\":48917,\"áµ\":48918,\":#\":48919,\"ĠFrieza\":48920,\"padding\":48921,\"Reviewer\":48922,\"Ġpsychiat\":48923,\"yrinth\":48924,\"ĠâĶĤ\":48925,\"hillary\":48926,\"Static\":48927,\"Newsletter\":48928,\"Avg\":48929,\"Ġfn\":48930,\"Topic\":48931,\"choes\":48932,\"Ġnewsp\":48933,\"á¸\":48934,\"Ġ[+\":48935,\"~~~~~~~~~~~~~~~~\":48936,\":]\":48937,\"apego\":48938,\"buf\":48939,\"Translation\":48940,\"ById\":48941,\"Ġmmol\":48942,\"ãĥ¼ãĥ\":48943,\"å½\":48944,\"ãĤī\":48945,\"Ġparser\":48946,\"ãĥª\":48947,\"`,\":48948,\"Lair\":48949,\")}\":48950,\"ypes\":48951,\"adobe\":48952,\"Ġancest\":48953,\"ernel\":48954,\"ĠNULL\":48955,\"ç«\":48956,\"anguages\":48957,\"Increases\":48958,\"æĦ\":48959,\"utorial\":48960,\"ithmetic\":48961,\"dll\":48962,\"ĠArcane\":48963,\"çī\":48964,\"Ġtc\":48965,\"urtles\":48966,\"èĪ\":48967,\"Bytes\":48968,\"Slot\":48969,\"ĠBahÃ¡\":48970,\"Weapon\":48971,\"widget\":48972,\"querque\":48973,\"Ġembodiments\":48974,\"å¥\":48975,\"WARN\":48976,\"swer\":48977,\"thumbnails\":48978,\"FFFF\":48979,\"inguishable\":48980,\"Ġâī\":48981,\"Ġ${\":48982,\"AAAAAAAA\":48983,\"Conclusion\":48984,\"ĻĤ\":48985,\"disable\":48986,\"Rect\":48987,\"Ġsubp\":48988,\"Ġ().\":48989,\"ĠDetected\":48990,\"èĢ\":48991,\"[]\":48992,\"Ġcoerc\":48993,\"ĠmM\":48994,\"recated\":48995,\"fusc\":48996,\"ĠSorce\":48997,\"çĶŁ\":48998,\").[\":48999,\"Ġ})\":49000,\"mobi\":49001,\"yip\":49002,\"Acknowled\":49003,\"ternity\":49004,\"iqueness\":49005,\"ython\":49006,\"><\":49007,\"Ġstd\":49008,\"Url\":49009,\"Ġnamespace\":49010,\"Ġtion\":49011,\"oother\":49012,\"Ó\":49013,\"Ġhemor\":49014,\"Ġrg\":49015,\"ventory\":49016,\"ãĤ¢\":49017,\"anamo\":49018,\"Socket\":49019,\"Topics\":49020,\"apeshifter\":49021,\"gnu\":49022,\"Ġdetrim\":49023,\"`.\":49024,\"romeda\":49025,\"çĲ\":49026,\"Ġlambda\":49027,\"Compan\":49028,\"Variable\":49029,\"Ġusb\":49030,\"ĠAdamant\":49031,\"ournal\":49032,\"Ġcovari\":49033,\"ãĥ©\":49034,\"éĸ\":49035,\"åİ\":49036,\"otaur\":49037,\"Ġ(),\":49038,\"Marginal\":49039,\"ãģı\":49040,\"Ġphysic\":49041,\"adeon\":49042,\"RESULTS\":49043,\"200000\":49044,\"ãģį\":49045,\"udeb\":49046,\"ãģĵ\":49047,\"COMPLE\":49048,\"Ġmsg\":49049,\"ghazi\":49050,\"/*\":49051,\"ĠDeity\":49052,\"Ġdisapp\":49053,\"Availability\":49054,\"Ġillum\":49055,\"à©\":49056,\"ptives\":49057,\",âĢĶ\":49058,\"chnology\":49059,\"Ġaccur\":49060,\"Ġapi\":49061,\"Obj\":49062,\"ãĤ«\":49063,\"ãĤ¸\":49064,\"ä¹ĭ\":49065,\"ËĪ\":49066,\"Ġtcp\":49067,\"Required\":49068,\".<\":49069,\"\\\".[\":49070,\"Ġ~/.\":49071,\"Ġobser\":49072,\"RFC\":49073,\"Ġintegers\":49074,\"åī\":49075,\"Installation\":49076,\"Ô\":49077,\"ó\":49078,\"csv\":49079,\"ãĥ«\":49080,\"ĠNoticed\":49081,\"âĸĵ\":49082,\"Tumblr\":49083,\"Reply\":49084,\"||\":49085,\"Ġconclud\":49086,\"Ġ))\":49087,\"ebin\":49088,\"sql\":49089,\"Closure\":49090,\"++++\":49091,\"],[\":49092,\"âĹı\":49093,\"Ġprolet\":49094,\"Ġ>=\":49095,\"estinal\":49096,\"Ġ[*\":49097,\"ĠInquisitor\":49098,\"Ġcmd\":49099,\"FINE\":49100,\"CRIP\":49101,\"Ġvertex\":49102,\"TeX\":49103,\"///\":49104,\"Ö¼\":49105,\"iscons\":49106,\"Ġmyster\":49107,\"Changed\":49108,\"timeout\":49109,\"irtual\":49110,\"Methods\":49111,\"Ġcerts\":49112,\"texture\":49113,\"Roaming\":49114,\"Proxy\":49115,\"Override\":49116,\"éĹ\":49117,\"utf\":49118,\"python\":49119,\"ĠRarity\":49120,\"ilitarian\":49121,\"çľ\":49122,\"().\":49123,\"æł\":49124,\"Ġbuf\":49125,\"åĳ\":49126,\"çķ\":49127,\"Ġ*.\":49128,\"umerable\":49129,\"~~~~\":49130,\"å¦\":49131,\"Ġsimultane\":49132,\"Ġjson\":49133,\"Requires\":49134,\"Ġperl\":49135,\"Interface\":49136,\"rupal\":49137,\"</\":49138,\"uilt\":49139,\"mercial\":49140,\"ĠPalestin\":49141,\"theless\":49142,\")=\":49143,\"Generic\":49144,\"&&\":49145,\"ALSE\":49146,\"Ġdebugger\":49147,\"paralle\":49148,\"acly\":49149,\"ĠScourge\":49150,\")].\":49151,\"Ġinstr\":49152,\"Ġ{}\":49153,\"]+\":49154,\"Ġdilig\":49155,\"åŃĲ\":49156,\"Ġcaptcha\":49157,\"kefeller\":49158,\"iosyncr\":49159,\"Ġchars\":49160,\"Ġinitialize\":49161,\"Width\":49162,\"Ġgithub\":49163,\"Ġinitialization\":49164,\"ĠGamerGate\":49165,\"ĠÃ¾\":49166,\"drm\":49167,\"slaught\":49168,\"Ġtiss\":49169,\".............\":49170,\"Ĥ¬\":49171,\"Ġplent\":49172,\"ãģķ\":49173,\"cfg\":49174,\"âĨ\":49175,\"Ġpokemon\":49176,\"\\\"],\":49177,\"Ġtyr\":49178,\"SELECT\":49179,\"othal\":49180,\"Tags\":49181,\"ĠMarketable\":49182,\"-----------\":49183,\"icter\":49184,\"irlf\":49185,\"ormons\":49186,\"Database\":49187,\"ĠãĤ\":49188,\"Ġ{\\\"\":49189,\"î\":49190,\"Handler\":49191,\"âĶĢ\":49192,\"$$$$\":49193,\"ĠJaune\":49194,\"ãĤ³\":49195,\"(),\":49196,\")+\":49197,\"--------\":49198,\"Ġshenan\":49199,\"Ġwelf\":49200,\"Ġ',\":49201,\"attribute\":49202,\"Uncommon\":49203,\"maxwell\":49204,\"Browser\":49205,\"ĠPastebin\":49206,\"uberty\":49207,\"debug\":49208,\"Ġmosqu\":49209,\"ĠBoolean\":49210,\"wcs\":49211,\"é£\":49212,\"/âĢĭ\":49213,\"çĦ\":49214,\"(){\":49215,\"////////////////////////////////\":49216,\"ĠGleaming\":49217,\"regor\":49218,\"ĠMercenary\":49219,\"ensional\":49220,\"mpeg\":49221,\"sudo\":49222,\"ãģ®å\":49223,\"iggurat\":49224,\"vironment\":49225,\"Directory\":49226,\"ĠDecoder\":49227,\"SPONSORED\":49228,\"intendo\":49229,\"Ġ<=\":49230,\"btn\":49231,\"ï¸\":49232,\"ä½ľ\":49233,\"paio\":49234,\"Tokens\":49235,\"ãĢį\":49236,\"params\":49237,\"Offline\":49238,\"Ġmetab\":49239,\"ĠLisp\":49240,\"anwhile\":49241,\">:\":49242,\"itialized\":49243,\"HTTP\":49244,\"Trivia\":49245,\"Sov\":49246,\"wrapper\":49247,\"={\":49248,\"ĠAzerb\":49249,\"aeper\":49250,\"Ġneighb\":49251,\"initions\":49252,\"Ġsts\":49253,\"ĠSasuke\":49254,\"#$\":49255,\"uliffe\":49256,\"æĸ¹\":49257,\"++++++++++++++++\":49258,\"ĠElven\":49259,\"ãģĤ\":49260,\"Ġartif\":49261,\"Folder\":49262,\"Ġà¨\":49263,\"åĤ\":49264,\"Ġphyl\":49265,\"uggest\":49266,\"blance\":49267,\"ãģł\":49268,\"Requirements\":49269,\"Usage\":49270,\"Ġinitialized\":49271,\"ãģ®æ\":49272,\"conservancy\":49273,\"ĠReincarn\":49274,\")|\":49275,\"Ġantioxid\":49276,\"ĠClicker\":49277,\"Ġunlaw\":49278,\"Ġ\\\\(\":49279,\"ãĥĪ\":49280,\"Ġ[*]\":49281,\"Characters\":49282,\"////////\":49283,\"ãĢĲ\":49284,\"ãĤ·\":49285,\"webkit\":49286,\"ãĢĳ\":49287,\"Ġxp\":49288,\"alkyrie\":49289,\"Console\":49290,\"());\":49291,\"ĠKorra\":49292,\"\\\"))\":49293,\"oooooooooooooooo\":49294,\"Timer\":49295,\"////////////////\":49296,\"yout\":49297,\"engeance\":49298,\"emetery\":49299,\"Ġmages\":49300,\"mods\":49301,\"Null\":49302,\"Ġphilos\":49303,\"ascript\":49304,\"Ġaddon\":49305,\"ĠâĸĪ\":49306,\"emale\":49307,\"----------------------------------------------------------------\":49308,\"Ġ\\\\\\\\\":49309,\"=[\":49310,\"ĠParables\":49311,\"ãĥĨ\":49312,\"VALUE\":49313,\"Ġ@@\":49314,\"Ġuint\":49315,\"${\":49316,\"cpp\":49317,\"%%\":49318,\"Ġ(âĪĴ\":49319,\"utils\":49320,\"prefix\":49321,\"å°Ĩ\":49322,\"ãĥŃ\":49323,\"Completed\":49324,\"Ġgoto\":49325,\"ãĤ¯\":49326,\"Winged\":49327,\"perty\":49328,\"[\\\"\":49329,\"ãĥİ\":49330,\"ĠScythe\":49331,\"Ġæľ\":49332,\"Ġ!=\":49333,\"Buffer\":49334,\"docker\":49335,\"ĠWATCHED\":49336,\"èĢħ\":49337,\"())\":49338,\"Ġdst\":49339,\"SIZE\":49340,\"ĠDemonic\":49341,\"Ġresil\":49342,\"ãĤ¿\":49343,\"Ġpione\":49344,\"cpu\":49345,\"++)\":49346,\"TEXT\":49347,\"Ġdiscrep\":49348,\"debian\":49349,\"quished\":49350,\"Ġacknow\":49351,\"Ġtrave\":49352,\"Ġgcc\":49353,\"Catalog\":49354,\"ctrl\":49355,\"ĠMoroc\":49356,\"Ġcpu\":49357,\"Ġ];\":49358,\"ĠSorceress\":49359,\"Introduced\":49360,\"Frames\":49361,\"Ġcondem\":49362,\"¶æ\":49363,\"~~~~~~~~\":49364,\"ĠEmacs\":49365,\"][/\":49366,\"Ġglim\":49367,\"Init\":49368,\"ĠPrimordial\":49369,\"ãĥĥ\":49370,\"Ġ+=\":49371,\"Ġblat\":49372,\"à¼\":49373,\"------------------------------------------------\":49374,\"gpu\":49375,\"ãĥĥãĥĪ\":49376,\"Ġxml\":49377,\"Ġboolean\":49378,\"References\":49379,\"Ġ?)\":49380,\"Ġsatell\":49381,\"Queue\":49382,\"Ġpestic\":49383,\"Ġ}}\":49384,\"Attribute\":49385,\"Ġdx\":49386,\"ĠDefin\":49387,\"Synopsis\":49388,\"..................\":49389,\"ãĥ¬\":49390,\"plugin\":49391,\"Disable\":49392,\"0000000000000000\":49393,\")\\\\\":49394,\"ĠIchigo\":49395,\"println\":49396,\"rontal\":49397,\"Setup\":49398,\"Ġï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½\":49399,\"å§\":49400,\"âĸº\":49401,\"ĠPengu\":49402,\"ailability\":49403,\"Duration\":49404,\"Timeout\":49405,\"ãĢĮ\":49406,\"Ġbehav\":49407,\"Reviewed\":49408,\"Ġtoget\":49409,\"\\\\.\":49410,\"lished\":49411,\"Ġthous\":49412,\"Ġperpend\":49413,\"ecause\":49414,\"Layout\":49415,\"è»\":49416,\"ĠDexterity\":49417,\"unsigned\":49418,\"+=\":49419,\"[[\":49420,\"ĠRunes\":49421,\"ãĤ¦\":49422,\"};\":49423,\"})\":49424,\"FTWARE\":49425,\"ength\":49426,\"milo\":49427,\"duino\":49428,\"å¤©\":49429,\"ĠClojure\":49430,\"ļé\":49431,\"ãĥ¥\":49432,\"gradient\":49433,\"Ġ\\\"\\\"\\\"\":49434,\"âĨĳ\":49435,\"@#\":49436,\"JSON\":49437,\"Ġproport\":49438,\"addr\":49439,\"});\":49440,\"ãĥĲ\":49441,\"ä¸ī\":49442,\"Ġtmp\":49443,\"å£\":49444,\"../\":49445,\"zsche\":49446,\"ĠâĪ¼\":49447,\"Entity\":49448,\"æ©Ł\":49449,\"ĠâĶľâĶĢâĶĢ\":49450,\"filename\":49451,\"{{\":49452,\"@@\":49453,\"ĠSeym\":49454,\"Ġ/**\":49455,\"ĠSummoner\":49456,\"Quantity\":49457,\"ç·\":49458,\"Attach\":49459,\"Ġbool\":49460,\"Texture\":49461,\"Ġopio\":49462,\".}\":49463,\"ãĥĭ\":49464,\"integer\":49465,\"Ġregex\":49466,\"Ġnomine\":49467,\"ription\":49468,\"ãģ®ç\":49469,\"ãĥķ\":49470,\"Ġsubparagraph\":49471,\"GGGG\":49472,\"Ġexplan\":49473,\"Header\":49474,\"Spawn\":49475,\"toggle\":49476,\"²¾\":49477,\"Abyss\":49478,\"expr\":49479,\"ĠZerg\":49480,\"ĠGrimoire\":49481,\"Contents\":49482,\"Instance\":49483,\"cyclopedia\":49484,\"ãĥĹ\":49485,\"ĠTakeru\":49486,\"=(\":49487,\"ä»£\":49488,\"\\\\)\":49489,\"Ġrgb\":49490,\"htt\":49491,\"bryce\":49492,\"Ġlivest\":49493,\"ĠAnnotations\":49494,\"âĶĢâĶĢâĶĢâĶĢâĶĢâĶĢâĶĢâĶĢ\":49495,\"berus\":49496,\"ntil\":49497,\"Ġskelet\":49498,\"callback\":49499,\"åħī\":49500,\"Joined\":49501,\"ãĤª\":49502,\"Ġargs\":49503,\"artifacts\":49504,\"Ġå¤\":49505,\"ÃĽ\":49506,\"ãĥŀ\":49507,\"Streamer\":49508,\"}\\\"\":49509,\"Ġunden\":49510,\"ãĥģ\":49511,\"Īè\":49512,\"ãĥ£\":49513,\"Ġ0004\":49514,\"Ġ\\\\'\":49515,\"ãĤ°\":49516,\"ĠCONFIG\":49517,\"Ġ#####\":49518,\"``\":49519,\"anguage\":49520,\"Ġ*)\":49521,\"Template\":49522,\"MODE\":49523,\"Ġ00000000\":49524,\"'';\":49525,\"></\":49526,\"å£«\":49527,\"essage\":49528,\"ntax\":49529,\"Cmd\":49530,\"ividual\":49531,\"Unix\":49532,\"è£\":49533,\"çĭ\":49534,\"ä½¿\":49535,\"():\":49536,\"ãĥī\":49537,\"gdala\":49538,\"etheless\":49539,\"ktop\":49540,\"ĠACPI\":49541,\"ãĥĸ\":49542,\"Ġsshd\":49543,\"Ġ000000\":49544,\"Ġchalleng\":49545,\"âĶĢâĶĢ\":49546,\"ĠFlavoring\":49547,\"çİĭ\":49548,\"Http\":49549,\"Ĭ±\":49550,\"Accessory\":49551,\"oldemort\":49552,\"ĠIzan\":49553,\"galitarian\":49554,\"ĠChocobo\":49555,\"edIn\":49556,\"++++++++\":49557,\"Ġprintf\":49558,\"çīĪ\":49559,\"izoph\":49560,\"ruciating\":49561,\"Ġenum\":49562,\",,,,\":49563,\"Ġpregn\":49564,\"sembly\":49565,\"Ġtherap\":49566,\"Ġingred\":49567,\"ãĤµ\":49568,\"Ġsql\":49569,\"(*\":49570,\"Appearance\":49571,\"ngth\":49572,\"invoke\":49573,\"ãĥĥãĤ¯\":49574,\"ctx\":49575,\"Ġdmg\":49576,\"Plugin\":49577,\"ãĥ¡\":49578,\"ulhu\":49579,\"ãĤ§\":49580,\"Ġwarr\":49581,\"Ġmetic\":49582,\"å¥³\":49583,\"Ġoun\":49584,\"ð\":49585,\"Ġtooltip\":49586,\"ãĤŃ\":49587,\"Ġvolunte\":49588,\"imgur\":49589,\"accompan\":49590,\"aterasu\":49591,\"olkien\":49592,\"ãĤº\":49593,\"Ġnodd\":49594,\"ĠMetatron\":49595,\"javascript\":49596,\"umbledore\":49597,\"ãĥł\":49598,\"--------------------------------------------------------\":49599,\"runtime\":49600,\"ĠLeban\":49601,\"Configuration\":49602,\"emort\":49603,\"(_\":49604,\"Connector\":49605,\"iosyn\":49606,\"reddits\":49607,\"Ġ\\\"%\":49608,\"Ġ[&\":49609,\"ĠSwordsman\":49610,\"ĠAwoken\":49611,\"Ġ;;\":49612,\"ãĥ¼ãĥ«\":49613,\"Ġ:=\":49614,\"ãĤ¹ãĥĪ\":49615,\"Ġcomr\":49616,\"Adapter\":49617,\"sbm\":49618,\"âķĲâķĲ\":49619,\"çļ\":49620,\"Loader\":49621,\"ãĥĵ\":49622,\"okemon\":49623,\"ãģ®é\":49624,\"-->\":49625,\"Ġlvl\":49626,\"Footnote\":49627,\"Iter\":49628,\"####\":49629,\"ãĥĳ\":49630,\"ĠCarbuncle\":49631,\"Ġ[+]\":49632,\"Ġmathemat\":49633,\"Allows\":49634,\"Ġ4090\":49635,\"Async\":49636,\"ģ«\":49637,\"Ļ½\":49638,\"))))\":49639,\"á½\":49640,\"Ġcx\":49641,\"Ġansw\":49642,\"{\\\"\":49643,\"ãĥŁ\":49644,\"addons\":49645,\"Filename\":49646,\"Appearances\":49647,\"ĠãĢĮ\":49648,\"Ġaddr\":49649,\"Ġcharact\":49650,\"glomer\":49651,\"Advertisements\":49652,\"Ġdracon\":49653,\"ĠFenrir\":49654,\"Ġ();\":49655,\"ĠCitiz\":49656,\"acebook\":49657,\"Ġparams\":49658,\"]=\":49659,\"Ġsubscript\":49660,\"Ġentreprene\":49661,\"tnc\":49662,\"iversal\":49663,\"Ġmillenn\":49664,\"ithub\":49665,\"/>\":49666,\"Ġ\\\"{\":49667,\"Frameworks\":49668,\"avorite\":49669,\"Ġ])\":49670,\"Constructed\":49671,\"fml\":49672,\"ãĥį\":49673,\"################################\":49674,\"-|\":49675,\"¥ŀ\":49676,\"Ġwithd\":49677,\"ĠCth\":49678,\"AppData\":49679,\"Msg\":49680,\":{\":49681,\"ãĤ¨\":49682,\"Ġtuple\":49683,\"ç¥ŀ\":49684,\"Ġintrins\":49685,\"ĠCooldown\":49686,\"ategory\":49687,\"^{\":49688,\"ãĥĬ\":49689,\"''''\":49690,\"çĶ°\":49691,\"ĠDEBUG\":49692,\"Ġcannabin\":49693,\"ocobo\":49694,\"Invalid\":49695,\"ãĥĢ\":49696,\"Compat\":49697,\"Ġ({\":49698,\"Removed\":49699,\"Ġconvol\":49700,\"}:\":49701,\"interstitial\":49702,\"Ġ</\":49703,\"Ġcontrace\":49704,\"uyomi\":49705,\"Callback\":49706,\"Parser\":49707,\"äºĶ\":49708,\"Versions\":49709,\"::::\":49710,\"Recomm\":49711,\"}\\\\\":49712,\"Ġ\\\"_\":49713,\"Debug\":49714,\"ĠAoE\":49715,\"atever\":49716,\"ĠTradable\":49717,\"Reloaded\":49718,\"ĠReincarnated\":49719,\"ĠStrongh\":49720,\">\\\"\":49721,\"initialized\":49722,\"Ġexting\":49723,\"PokÃ©\":49724,\"Parameters\":49725,\"¶ħ\":49726,\"########\":49727,\"NULL\":49728,\"ãĥĩ\":49729,\"groupon\":49730,\"\\\\-\":49731,\"ãĥı\":49732,\"ãĤ±\":49733,\"Ġsubsequ\":49734,\"ccording\":49735,\"ĠMODULE\":49736,\"ĠProtoss\":49737,\"\\\"},{\\\"\":49738,\"Ġ..............\":49739,\"Integer\":49740,\"endif\":49741,\"ãĥĻ\":49742,\"parser\":49743,\"lambda\":49744,\"Ġcarbohyd\":49745,\"ĠUnloaded\":49746,\"_{\":49747,\"âĸ¬âĸ¬\":49748,\"Ġdebian\":49749,\"]}\":49750,\"ãĤ¶\":49751,\"Parameter\":49752,\"ãĤ£\":49753,\"ãĤ»\":49754,\"Ġ$_\":49755,\"İĭ\":49756,\"Ġiterator\":49757,\"ãĤ¬\":49758,\"WINDOWS\":49759,\"CONCLUS\":49760,\"Ġ\\\"\\\\\":49761,\"umbn\":49762,\"(&\":49763,\"ãĥ©ãĥ³\":49764,\"usercontent\":49765,\"ometimes\":49766,\"METHOD\":49767,\"ãĥ¢\":49768,\"potion\":49769,\"ãĥ¯\":49770,\"everal\":49771,\"Ġweap\":49772,\"minecraft\":49773,\"================================\":49774,\"printf\":49775,\"ĠShinra\":49776,\"Ġreluct\":49777,\"\\\\\\\",\":49778,\"Runtime\":49779,\"xff\":49780,\"ĠAbyssal\":49781,\"akeru\":49782,\"Ġ\\\\(\\\\\":49783,\"\\\"/>\":49784,\"efficients\":49785,\"Ü\":49786,\"avascript\":49787,\"Ġbehavi\":49788,\"++;\":49789,\"=#\":49790,\"Attributes\":49791,\"âĵĺ\":49792,\"lvl\":49793,\"¬¼\":49794,\"/**\":49795,\"Gameplay\":49796,\"ĠLeilan\":49797,\">)\":49798,\"=\\\"/\":49799,\"Ġ));\":49800,\"ãĥĨãĤ£\":49801,\"ġ\":49802,\".</\":49803,\"Ġantidepress\":49804,\"Ġhtt\":49805,\"################\":49806,\"arnaev\":49807,\"ãĤ½\":49808,\"DERR\":49809,\"¥µ\":49810,\"âĸĪ\":49811,\"Ġ|--\":49812,\"Ġundermin\":49813,\"Ġ)))\":49814,\"ãĥĩãĤ£\":49815,\"awaru\":49816,\"\\\":[{\\\"\":49817,\"aution\":49818,\"ãĤ¤ãĥĪ\":49819,\"ô\":49820,\"ĠILCS\":49821,\"dfx\":49822,\"ĨĴ\":49823,\"âĸĴ\":49824,\"Ġcitiz\":49825,\"Ġ-=\":49826,\"ĠAllaah\":49827,\"Ġ(_\":49828,\"ĸļ\":49829,\"Ġ{\\\\\":49830,\"Ġsrf\":49831,\"ãĤ´\":49832,\"æŃ¦\":49833,\"»Ĵ\":49834,\"Ptr\":49835,\"'>\":49836,\"DEBUG\":49837,\"âĶģ\":49838,\"ãĢı\":49839,\"WithNo\":49840,\"Redditor\":49841,\"ĠâĶľ\":49842,\"Ġfmt\":49843,\"ãĢİ\":49844,\"Ġmsec\":49845,\"ĪĴ\":49846,\"eatures\":49847,\"itially\":49848,\"\\\"\\\"\\\"\":49849,\"ãĥ¼ãĤ¯\":49850,\"Textures\":49851,\"\\\"},\":49852,\"\\\"></\":49853,\"Ġenthusi\":49854,\"CHAPTER\":49855,\"Ġunbeliev\":49856,\"Ġearthqu\":49857,\"Ġ><\":49858,\"||||\":49859,\"ß\":49860,\"iterator\":49861,\"è£ħ\":49862,\"Ĥª\":49863,\"ojure\":49864,\"ãħĭãħĭ\":49865,\"ãĥ¼ãĥ³\":49866,\"Ġprintln\":49867,\"Ġ][\":49868,\"âĸĪâĸĪ\":49869,\"âķĲ\":49870,\"\\\\\\\":\":49871,\"senal\":49872,\"é¾į\":49873,\"é¾\":49874,\"Ġcryst\":49875,\"ãĥķãĤ¡\":49876,\"ĠCosponsors\":49877,\"ãĤ·ãĥ£\":49878,\"Magikarp\":49879,\"ĠMagicka\":49880,\"âĸĪâĸĪâĸĪâĸĪ\":49881,\",,,,,,,,\":49882,\"vertisement\":49883,\"âĶĢâĶĢâĶĢâĶĢ\":49884,\"ãĥķãĤ©\":49885,\"luaj\":49886,\"CLASSIFIED\":49887,\".''.\":49888,\"byss\":49889,\"Ġ{:\":49890,\"ĠNanto\":49891,\"Ġptr\":49892,\"Ġ%%\":49893,\"Ġteasp\":49894,\"[_\":49895,\"ãĥ¤\":49896,\"ħĭ\":49897,\"ŃĶ\":49898,\"Ġpci\":49899,\"Ġ\\\"<\":49900,\"GGGGGGGG\":49901,\"æĪ¦\":49902,\"--+\":49903,\"ãĤ®\":49904,\"Ġ())\":49905,\"âĸ¬\":49906,\"Ġsizeof\":49907,\"}}}\":49908,\";;;;;;;;\":49909,\">]\":49910,\"âĸĪâĸĪâĸĪâĸĪâĸĪâĸĪâĸĪâĸĪ\":49911,\"Vaults\":49912,\"Ġistg\":49913,\"Ġnewcom\":49914,\"=]\":49915,\"¿½\":49916,\"ĵĺ\":49917,\"{\\\\\":49918,\"Args\":49919,\"Ġexha\":49920,\"(\\\\\":49921,\"Ġunnecess\":49922,\"\\\"}],\\\"\":49923,\"ĠUNCLASSIFIED\":49924,\">(\":49925,\"ãĤ¢ãĥ«\":49926,\"æ©\":49927,\"70710\":49928,\"Ń·\":49929,\"ãĥ¼ãĥĨãĤ£\":49930,\"ĠSakuya\":49931,\"ãĥĥãĥī\":49932,\"ĠPyrrha\":49933,\"escription\":49934,\"VIDIA\":49935,\"================================================================\":49936,\"Ġlooph\":49937,\"=~\":49938,\"Ġcumbers\":49939,\"Ġ)]\":49940,\"govtrack\":49941,\"ĠãĤµ\":49942,\"Ġsubur\":49943,\"Þ\":49944,\"Ġâī¡\":49945,\"Interstitial\":49946,\"ãĥ¼ãĥĨ\":49947,\"Ġgobl\":49948,\"ãĥīãĥ©\":49949,\"oldown\":49950,\"ģĸ\":49951,\"Depths\":49952,\"Ġ());\":49953,\"Ġ._\":49954,\"20439\":49955,\"Ġç¥ŀ\":49956,\"ãģ®å®\":49957,\"ãĤ¼\":49958,\"Ġ$\\\\\":49959,\"âĹ¼\":49960,\"Ġencount\":49961,\"Ġ<!--\":49962,\"Ġeleph\":49963,\"\\\\\\\\\\\\\\\\\":49964,\"Ġmisunder\":49965,\"ahime\":49966,\"Ġattm\":49967,\"ĠCrossref\":49968,\"@@@@\":49969,\"ãħĭ\":49970,\"£ı\":49971,\"````\":49972,\"dylib\":49973,\"Ĥİ\":49974,\"Ġoccas\":49975,\"ãĥ´\":49976,\"ãĥĺ\":49977,\"ãĥ³ãĤ¸\":49978,\"Ġ+#\":49979,\"FINEST\":49980,\"Iterator\":49981,\"_>\":49982,\"hovah\":49983,\"éŃĶ\":49984,\"ãĤ¦ãĤ¹\":49985,\"aditional\":49986,\"@@@@@@@@\":49987,\"?ãĢį\":49988,\"âĸĢ\":49989,\"natureconservancy\":49990,\"=\\\"#\":49991,\"ĠCrossRef\":49992,\"ãĤ¡\":49993,\"ĠArchdemon\":49994,\"\\\"><\":49995,\"ãĥ¯ãĥ³\":49996,\"Ġendif\":49997,\"Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯\":49998,\"Ġtradem\":49999,\"\\\":-\":50000,\"ĠCLSID\":50001,\"ãĤ©\":50002,\"=\\\\\\\"\":50003,\"\\\\/\\\\/\":50004,\"Ġunintention\":50005,\"PDATE\":50006,\"Ġ``(\":50007,\"shapeshifter\":50008,\"Ġpractition\":50009,\"ikuman\":50010,\"Ý\":50011,\";;;;\":50012,\"ĠKinnikuman\":50013,\"Ġ(?,\":50014,\"@#&\":50015,\")=(\":50016,\")</\":50017,\"Ġ//[\":50018,\"=-=-\":50019,\"\\\":\\\"\\\"},{\\\"\":50020,\"é»Ĵ\":50021,\"\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\":50022,\"steamapps\":50023,\"=-=-=-=-=-=-=-=-\":50024,\">[\":50025,\"Initialized\":50026,\"ãĥīãĥ©ãĤ´ãĥ³\":50027,\"=-=-=-=-\":50028,\"ĠTsukuyomi\":50029,\"ertodd\":50030,\"Ġ+---\":50031,\"é¾įå\":50032,\"ãĥ´ãĤ¡\":50033,\"ortunately\":50034,\"TextColor\":50035,\"66666666\":50036,\"%%%%\":50037,\"ãĤ¨ãĥ«\":50038,\"taboola\":50039,\"ĠSkydragon\":50040,\"userc\":50041,\"Cooldown\":50042,\"Ġsidx\":50043,\"éĹĺ\":50044,\"FontSize\":50045,\"©¶æ\":50046,\"å§«\":50047,\"ÃĥÃĤ\":50048,\"âĸĦ\":50049,\"00200000\":50050,\"Â¯Â¯\":50051,\"âĸĳâĸĳ\":50052,\"\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\":50053,\"STDOUT\":50054,\"Buyable\":50055,\"Ġâĵĺ\":50056,\"SourceFile\":50057,\"Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯\":50058,\"ãģ®éŃĶ\":50059,\"ãĤ´ãĥ³\":50060,\"?????-\":50061,\"pmwiki\":50062,\"Â¯Â¯Â¯Â¯\":50063,\"TEXTURE\":50064,\"#$#$\":50065,\"ÃįÃį\":50066,\"EMOTE\":50067,\"\\\\<\":50068,\"dayName\":50069,\"Nitrome\":50070,\"ĠPsyNet\":50071,\";;;;;;;;;;;;\":50072,\"Ġè£ı\":50073,\"ĠisEnabled\":50074,\"76561\":50075,\"iHUD\":50076,\"ãĥĺãĥ©\":50077,\"*/(\":50078,\"Ġè£ıç\":50079,\"ÃĥÃĤÃĥÃĤ\":50080,\"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\":50081,\"ThumbnailImage\":50082,\"©¶æ¥µ\":50083,\"Ġ[|\":50084,\"displayText\":50085,\"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\":50086,\"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\":50087,\".ãĢį\":50088,\"ModLoader\":50089,\"oreAnd\":50090,\"ĠSmartstocks\":50091,\"cffff\":50092,\"À\":50093,\"Á\":50094,\"ñ\":50095,\"ò\":50096,\"õ\":50097,\"ö\":50098,\"÷\":50099,\"ø\":50100,\"ù\":50101,\"ú\":50102,\"û\":50103,\"ü\":50104,\"ý\":50105,\"þ\":50106,\"ÿ\":50107,\"Ā\":50108,\"ā\":50109,\"Ă\":50110,\"ă\":50111,\"Ą\":50112,\"ą\":50113,\"Ć\":50114,\"ć\":50115,\"Ĉ\":50116,\"ĉ\":50117,\"Ċ\":50118,\"ċ\":50119,\"Č\":50120,\"č\":50121,\"Ď\":50122,\"ď\":50123,\"Đ\":50124,\"đ\":50125,\"Ē\":50126,\"ē\":50127,\"Ĕ\":50128,\"ĕ\":50129,\"Ė\":50130,\"ė\":50131,\"Ę\":50132,\"ę\":50133,\"Ě\":50134,\"ě\":50135,\"Ĝ\":50136,\"ĝ\":50137,\"Ğ\":50138,\"ğ\":50139,\"ĊĊ\":50140,\"Âł\":50141,\"ÂłÂł\":50142,\"ĠÂł\":50143,\"ÂłÂłÂłÂł\":50144,\"ĠÂłĠÂł\":50145,\"wcsstore\":50146,\"ÂłÂłÂłÂłÂłÂłÂłÂł\":50147,\"ĠDragonbound\":50148,\"ĠguiActive\":50149,\"ĠÂłĠÂłĠÂłĠÂł\":50150,\"ļéĨĴ\":50151,\"Ġdavidjl\":50152,\"è¦ļéĨĴ\":50153,\"\\\"]=>\":50154,\"Ġ<-\":50155,\"ForgeModLoader\":50156,\"NetMessage\":50157,\"ItemImage\":50158,\"Ġè£ıè¦ļéĨĴ\":50159,\"PsyNetMessage\":50160,\"Ġ<[\":50161,\"ĠguiActiveUn\":50162,\"ĠguiName\":50163,\"ĠexternalTo\":50164,\"ĠunfocusedRange\":50165,\"ĠguiActiveUnfocused\":50166,\"ĠguiIcon\":50167,\"ĠexternalToEVA\":50168,\"ĠexternalToEVAOnly\":50169,\"reportprint\":50170,\"embedreportprint\":50171,\"cloneembedreportprint\":50172,\"rawdownload\":50173,\"rawdownloadcloneembedreportprint\":50174,\"SpaceEngineers\":50175,\"actionDate\":50176,\"ActionCode\":50177,\"externalActionCode\":50178,\"?????-?????-\":50179,\"MpServer\":50180,\"ĠBaseType\":50181,\"Ġgmaxwell\":50182,\"cffffcc\":50183,\"Ġ\\\"$:/\":50184,\"Ġ<@\":50185,\"ĸļå£«\":50186,\"é¾įåĸļå£«\":50187,\"ÂłÂłÂł\":50188,\"=~=~\":50189,\"ĠactionGroup\":50190,\"ĠItemLevel\":50191,\"Ġè£ıè\":50192,\">>\\\\\":50193,\"ĠattRot\":50194,\"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\":50195,\"ĠMechdragon\":50196,\"ĠRandomRedditor\":50197,\"ĠRandomRedditorWithNo\":50198,\"Ġdstg\":50199,\"Ġsqor\":50200,\"Ġpetertodd\":50201,\"StreamerBot\":50202,\"TPPStreamerBot\":50203,\"FactoryReloaded\":50204,\"ĠpartName\":50205,\"\\\\\\\">\":50206,\"catentry\":50207,\"ÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂł\":50208,\"ItemThumbnailImage\":50209,\"ĠUCHIJ\":50210,\"ĳå£«\":50211,\"ĠSetFontSize\":50212,\"Orderable\":50213,\"isSpecial\":50214,\"DeliveryDate\":50215,\"quickShip\":50216,\"quickShipAvailable\":50217,\"isSpecialOrderable\":50218,\"inventoryQuantity\":50219,\"channelAvailability\":50220,\"soType\":50221,\"soDeliveryDate\":50222,\"é¾įå¥\":50223,\"é¾įå¥ĳå£«\":50224,\"EStream\":50225,\"oreAndOnline\":50226,\"InstoreAndOnline\":50227,\"BuyableInstoreAndOnline\":50228,\"ĠTAMADRA\":50229,\"assetsadobe\":50230,\"Downloadha\":50231,\"ĠTheNitrome\":50232,\"ĠTheNitromeFan\":50233,\"GoldMagikarp\":50234,\"DragonMagazine\":50235,\"Ġ<+\":50236,\"ĠsrfN\":50237,\"ĠlargeDownload\":50238,\"ĠOkawaru\":50239,\"ĠsrfAttach\":50240,\"EStreamFrame\":50241,\"ãĤ¼ãĤ¦ãĤ¹\":50242,\"ĠSolidGoldMagikarp\":50243,\"ĊÂł\":50244,\"ĠSetTextColor\":50245,\"Ġfixme\":50246,\"ĠãĤµãĥ¼ãĥĨãĤ£\":50247,\"ĠãĤµãĥ¼ãĥĨãĤ£ãĥ¯ãĥ³\":50248,\"ĠÂłĠÂłĠÂłĠÂłĠÂłĠÂłĠÂłĠÂł\":50249,\"ĠAdinida\":50250,\"ItemTracker\":50251,\"ĠDevOnline\":50252,\"ĠÂłÂł\":50253,\"<?\":50254,\"*=-\":50255,\"ÃĽÃĽ\":50256,\"ĠEntityItem\":50257,\"EngineDebug\":50258,\"ĠstrutConnector\":50259,\"<|endoftext|>\":50260,\"madeupword0000\":50261,\"madeupword0001\":50262,\"madeupword0002\":50263,\"<mask>\":50264},\"merges\":[\"Ġ t\",\"Ġ a\",\"h e\",\"i n\",\"r e\",\"o n\",\"Ġt he\",\"e r\",\"Ġ s\",\"a t\",\"Ġ w\",\"Ġ o\",\"e n\",\"Ġ c\",\"i t\",\"i s\",\"a n\",\"o r\",\"e s\",\"Ġ b\",\"e d\",\"Ġ f\",\"in g\",\"Ġ p\",\"o u\",\"Ġa n\",\"a l\",\"a r\",\"Ġt o\",\"Ġ m\",\"Ġo f\",\"Ġ in\",\"Ġ d\",\"Ġ h\",\"Ġan d\",\"i c\",\"a s\",\"l e\",\"Ġt h\",\"i on\",\"o m\",\"l l\",\"en t\",\"Ġ n\",\"Ġ l\",\"s t\",\"Ġ re\",\"v e\",\"Ġ e\",\"r o\",\"l y\",\"Ġb e\",\"Ġ g\",\"Ġ T\",\"c t\",\"Ġ S\",\"i d\",\"o t\",\"Ġ I\",\"u t\",\"e t\",\"Ġ A\",\"Ġ is\",\"Ġ on\",\"i m\",\"a m\",\"o w\",\"a y\",\"a d\",\"s e\",\"Ġth at\",\"Ġ C\",\"i g\",\"Ġf or\",\"a c\",\"Ġ y\",\"v er\",\"u r\",\"Ġ u\",\"l d\",\"Ġs t\",\"Ġ M\",\"' s\",\"Ġ he\",\"Ġ it\",\"at ion\",\"it h\",\"i r\",\"c e\",\"Ġy ou\",\"i l\",\"Ġ B\",\"Ġw h\",\"o l\",\"Ġ P\",\"Ġw ith\",\"Ġ 1\",\"t er\",\"c h\",\"Ġa s\",\"Ġw e\",\"Ġ (\",\"n d\",\"i ll\",\"Ġ D\",\"i f\",\"Ġ 2\",\"a g\",\"er s\",\"k e\",\"Ġ \\\"\",\"Ġ H\",\"e m\",\"Ġc on\",\"Ġ W\",\"Ġ R\",\"he r\",\"Ġw as\",\"Ġ r\",\"o d\",\"Ġ F\",\"u l\",\"at e\",\"Ġa t\",\"r i\",\"p p\",\"o re\",\"ĠT he\",\"Ġs e\",\"u s\",\"Ġp ro\",\"Ġh a\",\"u m\",\"Ġa re\",\"Ġd e\",\"a in\",\"an d\",\"Ġo r\",\"ig h\",\"es t\",\"is t\",\"a b\",\"r om\",\"Ġ N\",\"t h\",\"Ġc om\",\"Ġ G\",\"u n\",\"o p\",\"0 0\",\"Ġ L\",\"Ġn ot\",\"es s\",\"Ġe x\",\"Ġ v\",\"re s\",\"Ġ E\",\"e w\",\"it y\",\"an t\",\"Ġb y\",\"e l\",\"o s\",\"or t\",\"o c\",\"q u\",\"Ġf rom\",\"Ġha ve\",\"Ġs u\",\"i ve\",\"ou ld\",\"Ġs h\",\"Ġth is\",\"n t\",\"r a\",\"p e\",\"igh t\",\"ar t\",\"m ent\",\"Ġa l\",\"u st\",\"en d\",\"- -\",\"al l\",\"Ġ O\",\"ac k\",\"Ġc h\",\"Ġ le\",\"i es\",\"re d\",\"ar d\",\"â Ģ\",\"ou t\",\"Ġ J\",\"Ġa b\",\"e ar\",\"i v\",\"al ly\",\"ou r\",\"o st\",\"g h\",\"p t\",\"Ġp l\",\"as t\",\"Ġc an\",\"a k\",\"om e\",\"u d\",\"T he\",\"Ġh is\",\"Ġd o\",\"Ġg o\",\"Ġh as\",\"g e\",\"' t\",\"Ġ U\",\"r ou\",\"Ġs a\",\"Ġ j\",\"Ġb ut\",\"Ġw or\",\"Ġa ll\",\"e ct\",\"Ġ k\",\"am e\",\"Ġw ill\",\"o k\",\"Ġw he\",\"Ġthe y\",\"id e\",\"0 1\",\"f f\",\"ic h\",\"p l\",\"t her\",\"Ġt r\",\". .\",\"Ġin t\",\"i e\",\"u re\",\"ag e\",\"Ġn e\",\"i al\",\"a p\",\"in e\",\"ic e\",\"Ġm e\",\"Ġo ut\",\"an s\",\"on e\",\"on g\",\"ion s\",\"Ġwh o\",\"Ġ K\",\"Ġu p\",\"Ġthe ir\",\"Ġa d\",\"Ġ 3\",\"Ġu s\",\"at ed\",\"ou s\",\"Ġm ore\",\"u e\",\"o g\",\"ĠS t\",\"in d\",\"i ke\",\"Ġs o\",\"im e\",\"p er\",\". \\\"\",\"b er\",\"i z\",\"a ct\",\"Ġon e\",\"Ġsa id\",\"Ġ -\",\"a re\",\"Ġyou r\",\"c c\",\"ĠT h\",\"Ġc l\",\"e p\",\"a ke\",\"ab le\",\"i p\",\"Ġcon t\",\"Ġwh ich\",\"i a\",\"Ġ im\",\"Ġab out\",\"Ġwe re\",\"ver y\",\"u b\",\"Ġh ad\",\"Ġ en\",\"Ġcom p\",\", \\\"\",\"ĠI n\",\"Ġu n\",\"Ġa g\",\"i re\",\"ac e\",\"a u\",\"ar y\",\"Ġw ould\",\"as s\",\"r y\",\"Ġ âĢ\",\"c l\",\"o ok\",\"e re\",\"s o\",\"Ġ V\",\"ig n\",\"i b\",\"Ġof f\",\"Ġt e\",\"v en\",\"Ġ Y\",\"i le\",\"o se\",\"it e\",\"or m\",\"Ġ2 01\",\"Ġre s\",\"Ġm an\",\"Ġp er\",\"Ġo ther\",\"or d\",\"ul t\",\"Ġbe en\",\"Ġl ike\",\"as e\",\"an ce\",\"k s\",\"ay s\",\"ow n\",\"en ce\",\"Ġd is\",\"ct ion\",\"Ġan y\",\"Ġa pp\",\"Ġs p\",\"in t\",\"res s\",\"ation s\",\"a il\",\"Ġ 4\",\"ic al\",\"Ġthe m\",\"Ġhe r\",\"ou nt\",\"ĠC h\",\"Ġa r\",\"Ġ if\",\"Ġthe re\",\"Ġp e\",\"Ġy ear\",\"a v\",\"Ġm y\",\"Ġs ome\",\"Ġwhe n\",\"ou gh\",\"ac h\",\"Ġth an\",\"r u\",\"on d\",\"ic k\",\"Ġo ver\",\"ve l\",\"Ġ qu\",\"Ċ Ċ\",\"Ġs c\",\"re at\",\"re e\",\"ĠI t\",\"ou nd\",\"p ort\",\"Ġal so\",\"Ġp art\",\"f ter\",\"Ġk n\",\"Ġbe c\",\"Ġt ime\",\"en s\",\"Ġ 5\",\"op le\",\"Ġwh at\",\"Ġn o\",\"d u\",\"m er\",\"an g\",\"Ġn ew\",\"-- --\",\"Ġg et\",\"or y\",\"it ion\",\"ing s\",\"Ġj ust\",\"Ġint o\",\"Ġ 0\",\"ent s\",\"o ve\",\"t e\",\"Ġpe ople\",\"Ġp re\",\"Ġit s\",\"Ġre c\",\"Ġt w\",\"i an\",\"ir st\",\"ar k\",\"or s\",\"Ġwor k\",\"ad e\",\"o b\",\"Ġs he\",\"Ġo ur\",\"w n\",\"in k\",\"l ic\",\"Ġ1 9\",\"ĠH e\",\"is h\",\"nd er\",\"au se\",\"Ġh im\",\"on s\",\"Ġ [\",\"Ġ ro\",\"f orm\",\"i ld\",\"at es\",\"ver s\",\"Ġon ly\",\"o ll\",\"Ġs pe\",\"c k\",\"e ll\",\"am p\",\"Ġa cc\",\"Ġb l\",\"i ous\",\"ur n\",\"f t\",\"o od\",\"Ġh ow\",\"he d\",\"Ġ '\",\"Ġa fter\",\"a w\",\"Ġat t\",\"o v\",\"n e\",\"Ġpl ay\",\"er v\",\"ic t\",\"Ġc ould\",\"it t\",\"Ġa m\",\"Ġf irst\",\"Ġ 6\",\"Ġa ct\",\"Ġ $\",\"e c\",\"h ing\",\"u al\",\"u ll\",\"Ġcom m\",\"o y\",\"o ld\",\"c es\",\"at er\",\"Ġf e\",\"Ġbe t\",\"w e\",\"if f\",\"Ġtw o\",\"oc k\",\"Ġb ack\",\") .\",\"id ent\",\"Ġu nder\",\"rou gh\",\"se l\",\"x t\",\"Ġm ay\",\"rou nd\",\"Ġp o\",\"p h\",\"is s\",\"Ġd es\",\"Ġm ost\",\"Ġd id\",\"Ġad d\",\"j ect\",\"Ġin c\",\"f ore\",\"Ġp ol\",\"on t\",\"Ġag ain\",\"cl ud\",\"ter n\",\"Ġkn ow\",\"Ġne ed\",\"Ġcon s\",\"Ġc o\",\"Ġ .\",\"Ġw ant\",\"Ġse e\",\"Ġ 7\",\"n ing\",\"i ew\",\"ĠTh is\",\"c ed\",\"Ġe ven\",\"Ġin d\",\"t y\",\"ĠW e\",\"at h\",\"Ġthe se\",\"Ġp r\",\"Ġu se\",\"Ġbec ause\",\"Ġf l\",\"n g\",\"Ġn ow\",\"ĠâĢ ĵ\",\"c om\",\"is e\",\"Ġm ake\",\"Ġthe n\",\"ow er\",\"Ġe very\",\"ĠU n\",\"Ġse c\",\"os s\",\"u ch\",\"Ġe m\",\"Ġ =\",\"ĠR e\",\"i ed\",\"r it\",\"Ġin v\",\"le ct\",\"Ġsu pp\",\"at ing\",\"Ġl ook\",\"m an\",\"pe ct\",\"Ġ 8\",\"ro w\",\"Ġb u\",\"Ġwhe re\",\"if ic\",\"Ġyear s\",\"i ly\",\"Ġd iff\",\"Ġsh ould\",\"Ġre m\",\"T h\",\"I n\",\"Ġe v\",\"d ay\",\"' re\",\"ri b\",\"Ġre l\",\"s s\",\"Ġde f\",\"Ġr ight\",\"Ġs y\",\") ,\",\"l es\",\"00 0\",\"he n\",\"Ġth rough\",\"ĠT r\",\"_ _\",\"Ġw ay\",\"Ġd on\",\"Ġ ,\",\"Ġ1 0\",\"as ed\",\"Ġas s\",\"ub lic\",\"Ġre g\",\"ĠA nd\",\"i x\",\"Ġ very\",\"Ġin clud\",\"ot her\",\"Ġim p\",\"ot h\",\"Ġsu b\",\"ĠâĢ Ķ\",\"Ġbe ing\",\"ar g\",\"ĠW h\",\"= =\",\"ib le\",\"Ġdo es\",\"an ge\",\"r am\",\"Ġ 9\",\"er t\",\"p s\",\"it ed\",\"ation al\",\"Ġb r\",\"Ġd own\",\"Ġman y\",\"ak ing\",\"Ġc all\",\"ur ing\",\"it ies\",\"Ġp h\",\"ic s\",\"al s\",\"Ġde c\",\"at ive\",\"en er\",\"Ġbe fore\",\"il ity\",\"Ġwe ll\",\"Ġm uch\",\"ers on\",\"Ġth ose\",\"Ġsu ch\",\"Ġ ke\",\"Ġ end\",\"ĠB ut\",\"as on\",\"t ing\",\"Ġl ong\",\"e f\",\"Ġth ink\",\"y s\",\"Ġbe l\",\"Ġs m\",\"it s\",\"a x\",\"Ġo wn\",\"Ġpro v\",\"Ġs et\",\"if e\",\"ment s\",\"b le\",\"w ard\",\"Ġsh ow\",\"Ġp res\",\"m s\",\"om et\",\"Ġo b\",\"Ġs ay\",\"ĠS h\",\"t s\",\"f ul\",\"Ġe ff\",\"Ġg u\",\"Ġin st\",\"u nd\",\"re n\",\"c ess\",\"Ġ ent\",\"ĠY ou\",\"Ġgo od\",\"Ġst art\",\"in ce\",\"Ġm ade\",\"t t\",\"st em\",\"ol og\",\"u p\",\"Ġ |\",\"um p\",\"Ġhe l\",\"ver n\",\"ul ar\",\"u ally\",\"Ġa c\",\"Ġm on\",\"Ġl ast\",\"Ġ2 00\",\"1 0\",\"Ġst ud\",\"u res\",\"ĠA r\",\"sel f\",\"ar s\",\"mer ic\",\"u es\",\"c y\",\"Ġm in\",\"oll ow\",\"Ġc ol\",\"i o\",\"Ġm od\",\"Ġc ount\",\"ĠC om\",\"he s\",\"Ġf in\",\"a ir\",\"i er\",\"âĢ Ķ\",\"re ad\",\"an k\",\"at ch\",\"e ver\",\"Ġst r\",\"Ġpo int\",\"or k\",\"ĠN ew\",\"Ġs ur\",\"o ol\",\"al k\",\"em ent\",\"Ġus ed\",\"ra ct\",\"we en\",\"Ġs ame\",\"ou n\",\"ĠA l\",\"c i\",\"Ġdiff ere\",\"Ġwh ile\",\"---- ----\",\"Ġg ame\",\"ce pt\",\"Ġs im\",\".. .\",\"Ġin ter\",\"e k\",\"Ġre port\",\"Ġpro du\",\"Ġst ill\",\"l ed\",\"a h\",\"Ġhe re\",\"Ġwor ld\",\"Ġth ough\",\"Ġn um\",\"ar ch\",\"im es\",\"al e\",\"ĠS e\",\"ĠI f\",\"/ /\",\"ĠL e\",\"Ġre t\",\"Ġre f\",\"Ġtr ans\",\"n er\",\"ut ion\",\"ter s\",\"Ġt ake\",\"ĠC l\",\"Ġcon f\",\"w ay\",\"a ve\",\"Ġgo ing\",\"Ġs l\",\"u g\",\"ĠA meric\",\"Ġspe c\",\"Ġh and\",\"Ġbet ween\",\"ist s\",\"ĠD e\",\"o ot\",\"I t\",\"Ġe ar\",\"Ġagain st\",\"Ġh igh\",\"g an\",\"a z\",\"at her\",\"Ġex p\",\"Ġo p\",\"Ġin s\",\"Ġg r\",\"Ġhel p\",\"Ġre qu\",\"et s\",\"in s\",\"ĠP ro\",\"is m\",\"Ġf ound\",\"l and\",\"at a\",\"us s\",\"am es\",\"Ġp erson\",\"Ġg reat\",\"p r\",\"Ġs ign\",\"ĠA n\",\"' ve\",\"Ġs omet\",\"Ġs er\",\"h ip\",\"Ġr un\",\"Ġ :\",\"Ġt er\",\"ire ct\",\"Ġf ollow\",\"Ġd et\",\"ic es\",\"Ġf ind\",\"1 2\",\"Ġm em\",\"Ġc r\",\"e red\",\"e x\",\"Ġex t\",\"ut h\",\"en se\",\"c o\",\"Ġte am\",\"v ing\",\"ou se\",\"as h\",\"at t\",\"v ed\",\"Ġsy stem\",\"ĠA s\",\"d er\",\"iv es\",\"m in\",\"Ġle ad\",\"ĠB l\",\"c ent\",\"Ġa round\",\"Ġgo vern\",\"Ġc ur\",\"vel op\",\"an y\",\"Ġc our\",\"al th\",\"ag es\",\"iz e\",\"Ġc ar\",\"od e\",\"Ġl aw\",\"Ġre ad\",\"' m\",\"c on\",\"Ġre al\",\"Ġsupp ort\",\"Ġ1 2\",\".. ..\",\"Ġre ally\",\"n ess\",\"Ġf act\",\"Ġd ay\",\"Ġb oth\",\"y ing\",\"Ġs erv\",\"ĠF or\",\"Ġth ree\",\"Ġw om\",\"Ġm ed\",\"od y\",\"ĠThe y\",\"5 0\",\"Ġex per\",\"t on\",\"Ġe ach\",\"ak es\",\"Ġc he\",\"Ġc re\",\"in es\",\"Ġre p\",\"1 9\",\"g g\",\"ill ion\",\"Ġg rou\",\"ut e\",\"i k\",\"W e\",\"g et\",\"E R\",\"Ġm et\",\"Ġs ays\",\"o x\",\"Ġd uring\",\"er n\",\"iz ed\",\"a red\",\"Ġf am\",\"ic ally\",\"Ġha pp\",\"ĠI s\",\"Ġch ar\",\"m ed\",\"v ent\",\"Ġg ener\",\"i ent\",\"p le\",\"i et\",\"re nt\",\"1 1\",\"v es\",\"pt ion\",\"Ġ2 0\",\"form ation\",\"Ġc or\",\"Ġoff ic\",\"ie ld\",\"Ġto o\",\"is ion\",\"Ġin f\",\"Ġ Z\",\"t he\",\"o ad\",\"Ġp ublic\",\"Ġpro g\",\"r ic\",\"* *\",\"Ġw ar\",\"Ġp ower\",\"v iew\",\"Ġf ew\",\"Ġl oc\",\"Ġdiffere nt\",\"Ġst ate\",\"Ġhe ad\",\"' ll\",\"Ġp oss\",\"Ġst at\",\"re t\",\"ant s\",\"Ġv al\",\"Ġis s\",\"Ġc le\",\"i vers\",\"an c\",\"Ġex pl\",\"Ġan other\",\"Ġ Q\",\"Ġa v\",\"th ing\",\"n ce\",\"W h\",\"Ġch ild\",\"Ġs ince\",\"i red\",\"l ess\",\"Ġl ife\",\"Ġde velop\",\"itt le\",\"Ġde p\",\"Ġp ass\",\"ã ĥ\",\"Ġt urn\",\"or n\",\"Th is\",\"b ers\",\"ro ss\",\"ĠA d\",\"Ġf r\",\"Ġres p\",\"Ġsec ond\",\"o h\",\"Ġ /\",\"Ġdis c\",\"Ġ &\",\"Ġsomet hing\",\"Ġcomp le\",\"Ġ ed\",\"Ġf il\",\"Ġmon th\",\"a j\",\"u c\",\"Ġgovern ment\",\"Ġwith out\",\"Ġle g\",\"Ġd ist\",\"Ġp ut\",\"Ġqu est\",\"an n\",\"Ġpro t\",\"2 0\",\"Ġne ver\",\"i ence\",\"Ġle vel\",\"Ġar t\",\"Ġth ings\",\"Ġm ight\",\"Ġeff ect\",\"Ġcont ro\",\"Ġc ent\",\"Ġ1 8\",\"Ġall ow\",\"Ġbel ie\",\"ch ool\",\"ot t\",\"Ġinc re\",\"Ġfe el\",\"Ġres ult\",\"Ġl ot\",\"Ġf un\",\"ot e\",\"Ġt y\",\"ere st\",\"Ġcont in\",\"Ġus ing\",\"Ġb ig\",\"2 01\",\"Ġas k\",\"Ġb est\",\"Ġ )\",\"I N\",\"Ġo pp\",\"3 0\",\"Ġnum ber\",\"in ess\",\"S t\",\"le ase\",\"Ġc a\",\"Ġm ust\",\"Ġd irect\",\"Ġg l\",\"Ġ <\",\"Ġop en\",\"Ġp ost\",\"Ġcom e\",\"Ġse em\",\"ord ing\",\"Ġwe ek\",\"ate ly\",\"it al\",\"Ġe l\",\"ri end\",\"Ġf ar\",\"Ġt ra\",\"in al\",\"Ġp ri\",\"ĠU S\",\"Ġpl ace\",\"Ġfor m\",\"Ġto ld\",\"\\\" :\",\"ain s\",\"at ure\",\"ĠTr ump\",\"Ġst and\",\"Ġ #\",\"id er\",\"ĠF r\",\"Ġne xt\",\"Ġs oc\",\"Ġp ur\",\"Ġle t\",\"Ġl ittle\",\"Ġh um\",\"Ġ i\",\"r on\",\"1 5\",\"Ġ1 5\",\"Ġcomm un\",\"Ġm ark\",\"ĠThe re\",\"Ġw r\",\"ĠTh at\",\"Ġin formation\",\"w ays\",\"Ġb us\",\"a pp\",\"Ġinv est\",\"m e\",\"Ġh ard\",\"ain ed\",\"e ad\",\"Ġim port\",\"Ġapp ro\",\"Ġt est\",\"Ġt ri\",\"Ġre st\",\"os ed\",\"Ġf ull\",\"Ġc are\",\"ĠS p\",\"Ġc ase\",\"O N\",\"Ġs k\",\"Ġl ess\",\"Ġ +\",\"Ġpart ic\",\"ĠP l\",\"ab ly\",\"u ck\",\"is hed\",\"ch n\",\"b e\",\"Ġl ist\",\"at or\",\"Ġto p\",\"Ġad v\",\"ĠB e\",\"ru ct\",\"Ġd em\",\"r ation\",\"l ing\",\"g y\",\"re en\",\"g er\",\"Ġh ome\",\"Ġle ft\",\"Ġbet ter\",\"Ġd ata\",\"Ġ1 1\",\"Ġatt ack\",\"Ġpro ble\",\"l ine\",\"ard s\",\"Ġbe h\",\"r al\",\"ĠH ow\",\"ĠS he\",\"ar ge\",\"Ġ --\",\": //\",\"Ġb ro\",\"ĠP h\",\"at s\",\"Ġbu ild\",\"w w\",\"id ed\",\"a im\",\"as es\",\"en cy\",\"Ġm ain\",\"in ed\",\"Ġinclud ing\",\"Ġ {\",\"Ġg ot\",\"Ġint erest\",\"Ġke ep\",\"Ġ X\",\"Ġe as\",\"ain ing\",\"Ġcl ass\",\"âĢ ¦\",\"ĠN o\",\"Ġv ar\",\"Ġsm all\",\"amp le\",\"A T\",\"Ġ ide\",\"ĠS o\",\"Ġre ce\",\"Ġpol it\",\"Ġm ov\",\"Ġpl an\",\"Ġper cent\",\"iv ing\",\"Ġc amp\",\"Ġp ay\",\"1 4\",\"s c\",\"is ed\",\"Ġu nt\",\"one y\",\"pl oy\",\"== ==\",\"Ġdid n\",\"ĠI nd\",\"el s\",\"ert ain\",\"Ġp os\",\"__ __\",\"i ver\",\"Ġpro cess\",\"Ġprog ram\",\"if ied\",\"ĠR ep\",\"1 6\",\"u ro\",\"olog y\",\"at ter\",\"in a\",\"Ġn ame\",\"ĠA ll\",\"Ġf our\",\"Ġret urn\",\"v ious\",\"b s\",\"Ġcall ed\",\"Ġm ove\",\"ĠS c\",\"ir d\",\"Ġgrou p\",\"Ġb re\",\"Ġm en\",\"Ġc ap\",\"t en\",\"e e\",\"Ġd ri\",\"le g\",\"he re\",\"uth or\",\"Ġp at\",\"Ġcur rent\",\"id es\",\"Ġp op\",\"t o\",\"ent ion\",\"Ġal ways\",\"Ġm il\",\"Ġwom en\",\"Ġ1 6\",\"Ġo ld\",\"iv en\",\"ra ph\",\"ĠO r\",\"r or\",\"ent ly\",\"Ġn ear\",\"ĠE x\",\"re am\",\"s h\",\"Ġ1 4\",\"Ġf ree\",\"iss ion\",\"st and\",\"ĠC on\",\"al ity\",\"us ed\",\"1 3\",\"Ġdes ign\",\"Ġch ange\",\"Ġch ang\",\"Ġb o\",\"Ġv is\",\"em ber\",\"Ġb ook\",\"read y\",\"Ġk ill\",\"2 5\",\"pp ed\",\"Ġa way\",\"Ġab le\",\"Ġcount ry\",\"Ġcon st\",\"ar n\",\"Ġor der\",\"A R\",\"i or\",\"i um\",\"or th\",\"1 8\",\"ail able\",\"Ġs w\",\"Ġm illion\",\"Ġ1 3\",\"at ic\",\"t ed\",\"ĠG o\",\"Ġo per\",\"en g\",\"Ġth ing\",\"aj or\",\"con om\",\"ĠCom m\",\"Ġwh y\",\"u red\",\"ur al\",\"Ġs chool\",\"b y\",\"ĠM ar\",\"Ġa ff\",\"Ġd ays\",\"Ġan n\",\"us h\",\"an e\",\"I f\",\"e g\",\"Ġpro f\",\"Ġhe alth\",\"ou th\",\"B ut\",\"ion al\",\". ,\",\"Ġs ol\",\"Ġal ready\",\"Ġ3 0\",\"Ġchar act\",\"H e\",\"Ġf riend\",\"E S\",\"i ans\",\"ic le\",\"' d\",\"ĠO n\",\"Ġle ast\",\"Ġp rom\",\"Ġd r\",\"Ġh ist\",\"it her\",\"Ġ est\",\"i qu\",\"1 7\",\"s on\",\"Ġte ll\",\"Ġt alk\",\"oh n\",\"o int\",\"le ction\",\"A N\",\"Ġunt il\",\"au gh\",\"Ġl ater\",\"Ġ ve\",\"Ġv iew\",\"end ing\",\"iv ed\",\"Ġwor d\",\"w are\",\"Ġc ost\",\"Ġen ough\",\"Ġg ive\",\"ĠUn ited\",\"Ġte chn\",\"are nt\",\"O R\",\"Ġp ar\",\"ĠD r\",\"Ġ201 6\",\"r ist\",\"er ing\",\"Ġ Â\",\"Ġl arge\",\"s ide\",\"ac y\",\"cc ess\",\"Ġw in\",\"Ġimport ant\",\"Ġ19 9\",\"Ġdoes n\",\"Ġ1 7\",\"Ġbus iness\",\"Ġcle ar\",\"Ġre se\",\"\\\" ,\",\"ur y\",\"Ġe qu\",\"as ter\",\"al f\",\"ĠAmeric an\",\"n ect\",\"Ġex pect\",\"ivers ity\",\"Ġo cc\",\"ĠF l\",\"Ġk ind\",\"Ġme an\",\"Ġp ast\",\"Ġde v\",\"Ġb as\",\"le t\",\"ra ft\",\"Ġor gan\",\"Ġde l\",\"Ġper form\",\"Ġst ory\",\"Ġse ason\",\"ĠC ol\",\"Ġcl aim\",\"Ġc ame\",\"Ġwith in\",\"Ġl ine\",\"Ġpro ject\",\"ĠA t\",\"Ġcontro l\",\"end ed\",\"ĠS y\",\"Ġa ir\",\"iz ation\",\"Ġ *\",\"le y\",\"Ġm oney\",\"id d\",\"Y ou\",\"f or\",\"Ġfam ily\",\"Ġm aking\",\"Ġb it\",\"Ġpol ice\",\"Ġhapp en\",\"Ġ vers\",\"on y\",\"u ff\",\"ĠW hen\",\"Ġs it\",\"ide o\",\"l f\",\"is on\",\"Ġsu re\",\"g in\",\"Ġapp ear\",\"Ġl ight\",\"Ġ es\",\"o f\",\"Ġw ater\",\"Ġt imes\",\"n ot\",\"Ġg row\",\"Ġcomp any\",\"ĠT e\",\"ow s\",\"Ġm ar\",\"our ce\",\"i ol\",\"ar m\",\"b r\",\"Ġex ample\",\"Ġcon c\",\"Ġf ore\",\"ĠT o\",\"p ro\",\"E N\",\"ri es\",\"Ġ2 5\",\"ĠC an\",\"ne y\",\"Ġact ually\",\"Ġe ver\",\"ur ity\",\"ak en\",\"ap s\",\"Ġt ax\",\"Ġm ajor\",\"am a\",\"Ġof ten\",\"er al\",\"Ġhum an\",\"Ġj ob\",\"is ter\",\"Ġav ailable\",\"oc r\",\"en n\",\"a id\",\"iv id\",\"Ġrec ord\",\"? \\\"\",\"Ġs ing\",\"ĠA m\",\"id ence\",\"Ġnew s\",\"st er\",\"Ġe conom\",\"Ġfollow ing\",\"ĠB r\",\"is ing\",\"Ġh our\",\"m ost\",\"um ent\",\"Ġse x\",\"Ġdes c\",\"Ġbec ome\",\"ĠE d\",\"Ġto ok\",\"Ġha ving\",\"Ġprodu ct\",\"a ult\",\"A s\",\"ar ing\",\"Ġme ans\",\"Ġh op\",\"un e\",\"Ġch o\",\"Ġc ertain\",\"Ġn on\",\"Ġde al\",\"2 4\",\"le ment\",\"oc i\",\"en e\",\"Ġs ide\",\"ĠP r\",\"ĠM ay\",\"Ġre ason\",\"u ed\",\"c hed\",\"ul ation\",\"Ġe lect\",\"Ġoffic ial\",\"Ġposs ible\",\"Ġh old\",\"and s\",\"ot s\",\"Ġc ity\",\"or ies\",\"Ġse ver\",\"Ġchild ren\",\"Ġon ce\",\"Ġact iv\",\"l er\",\"Ġn ight\",\"it ions\",\"ĠJ ohn\",\"a pe\",\"pl ay\",\"Ġd one\",\"Ġl im\",\"Ġwork ing\",\"ĠP res\",\"or ld\",\"e b\",\"ĠC o\",\"Ġb ody\",\"ail s\",\"ut es\",\"ĠM r\",\"Ġwhe ther\",\"Ġa uthor\",\"ro p\",\"Ġpro per\",\"Ġse en\",\") ;\",\"Ġf ac\",\"ĠS u\",\"Ġcon d\",\"it ing\",\"Ġcour se\",\"Ġ }\",\"-------- --------\",\"a ign\",\"Ġev ent\",\"Ġen g\",\"Ġp ot\",\"Ġin tern\",\"i am\",\"Ġsh ort\",\"em pt\",\"ã Ĥ\",\"ĠG od\",\"il ar\",\"8 0\",\"Ġor ig\",\"I S\",\"our n\",\"ab ility\",\"it ive\",\"Ġd am\",\"Ġ1 00\",\"Ġp ress\",\"Ġdo ing\",\"Ġprot ect\",\"r ing\",\"Ġthough t\",\"Ġquest ion\",\"re w\",\"ĠW ar\",\"Ġsever al\",\"ĠSt ate\",\"Ġg iven\",\"Ġf und\",\"ĠT w\",\"Ġw ent\",\"an ces\",\"w ork\",\"p or\",\"m y\",\"4 0\",\"Ġar g\",\"art ment\",\"ust om\",\"Ġpol ic\",\"Ġme et\",\"Ġc reat\",\"2 2\",\"ĠSt ates\",\"Ġg ames\",\"ra w\",\"ut ure\",\"Ġunder stand\",\"ur s\",\"ĠO b\",\"l ish\",\"s y\",\"Ġm akes\",\"Ġw on\",\"ag on\",\"Ġh tt\",\"Ġl ove\",\"ent ial\",\"Ġcomple te\",\"p ar\",\"ĠI m\",\"A L\",\"Ġacc ount\",\"Â ł\",\"ore d\",\"ver t\",\"Ġ ident\",\"Ġ201 5\",\"Ġother s\",\"ĠM in\",\"i ber\",\"ver age\",\"The re\",\"ition al\",\"d d\",\"Ġpro b\",\"Ġyou ng\",\"Ġal ong\",\"Ġacc ording\",\"Ġy et\",\"Ġmem bers\",\"ĠWh at\",\"o id\",\"ĠM an\",\"A nd\",\"Ġam ong\",\"a i\",\"Ġem ploy\",\"ĠR es\",\"Ġ >\",\"Ġinv ol\",\"Ġl ow\",\"a f\",\"ĠC ar\",\"Ġh ig\",\"ĠO ne\",\"ĠS ec\",\"in ation\",\"Ġlike ly\",\"Ġan t\",\"ag ed\",\"ĠR uss\",\"Ġb en\",\"Ġre le\",\"F or\",\"b ack\",\"ĠN ot\",\"Ġpres ident\",\"b all\",\"Ġacc ess\",\"ivid ual\",\"ĠD em\",\"ĠE uro\",\"6 0\",\"Ġkn own\",\"ir l\",\"ĠG r\",\"Ġear ly\",\"u se\",\"iet y\",\"âĢ ĵ\",\"Ġf ight\",\"Ġs ent\",\"Ġto day\",\"Ġmark et\",\"\\\" .\",\"Ġb ased\",\"Ġstr ong\",\"ur ther\",\"Ġde b\",\"m ber\",\"Ġproble m\",\"Ġde ath\",\"Ġsoc ial\",\"im ate\",\"A S\",\"ort un\",\"Ġcamp aign\",\"er y\",\"C h\",\"Ġe y\",\"i ally\",\"Ġm us\",\"w h\",\"p os\",\"Ġ er\",\"Ġsa f\",\"Ġmonth s\",\"ir on\",\"Ġv iol\",\"Ġf ive\",\"Ġst re\",\"Ġplay ers\",\"in c\",\"al d\",\"y ear\",\"a un\",\"Ġsu ccess\",\"Ġpres ent\",\"ere nce\",\"Ġ201 4\",\"Ġsu gg\",\"Ġpartic ular\",\"Ġtr y\",\"Ġsugg est\",\"ĠCh rist\",\"on es\",\"Ġpri v\",\"2 3\",\"Ġc rit\",\"Ġl and\",\"Ġloc al\",\"if y\",\"2 9\",\"Ġa ut\",\"E D\",\"ĠG u\",\"Ġm ult\",\"Ġpolit ical\",\"Ġask ed\",\"Ġfor mer\",\"it ter\",\"ri pt\",\"Ġcl ose\",\"Ġp ract\",\"ĠY ork\",\"Ġget ting\",\"Ġac ross\",\"Ġcom b\",\"Ġbelie ve\",\"Ġ z\",\"Ġto get\",\"Ġtoget her\",\"ĠC ent\",\"ir c\",\"Ġind ividual\",\"ĠM c\",\"2 7\",\"is k\",\"ĠE ng\",\"Ġf ace\",\"Ġ2 4\",\"Ġval ue\",\"Ġare a\",\"e v\",\"Ġw rit\",\"ĠPres ident\",\"Ġv ot\",\"Ġke y\",\"Ġm om\",\"p ut\",\"Ġany thing\",\"Ġexper ience\",\"att le\",\"Ġm ind\",\"a ff\",\"om m\",\"Ġf uture\",\"g ed\",\"Ġc ut\",\"Ġto t\",\"it ch\",\"Ġv ideo\",\"Ġinvest ig\",\"Ġn et\",\"ĠM y\",\"r ict\",\"i en\",\". )\",\"Ġimp ro\",\"th ough\",\"ward s\",\"Ġcon nect\",\"ĠM ed\",\"sel ves\",\"ens ive\",\"m b\",\"o ber\",\"at ors\",\"A n\",\"Ġ5 0\",\"Ġre du\",\"res ent\",\"Ġab ove\",\"Ġf re\",\"ĠEuro pe\",\"s w\",\"Ġam ount\",\"ĠA pp\",\"Ġe ither\",\"Ġmil it\",\"Ġan al\",\"Ġf ail\",\"ĠE n\",\"al es\",\"Ġspec ial\",\"Ġbl ack\",\"I T\",\"c her\",\"Ġlook ing\",\"Ġf ire\",\"y n\",\"Ġal most\",\"o on\",\"Ġstud y\",\"Ġm iss\",\"c hes\",\"ro wn\",\"Ġt re\",\"Ġcommun ity\",\"Ġmed ia\",\"Ġf ood\",\"Ġcom es\",\"ĠUn iversity\",\"Ġsing le\",\"Wh at\",\"u ly\",\"Ġh alf\",\"ag ue\",\"h od\",\"ĠRep ublic\",\"Ġstart ed\",\"Ġqu ick\",\"ot o\",\"b ook\",\"Ġiss ue\",\"it or\",\"Ġel se\",\"Ġcons ider\",\"2 6\",\"ro du\",\"Ġt aken\",\"2 8\",\"9 9\",\"ĠW ith\",\"Ġtr ue\",\"Ġw a\",\"Ġtr ad\",\"Ġag o\",\"Ġm ess\",\"ie f\",\"Ġadd ed\",\"o ke\",\"Ġb ad\",\"Ġf av\",\"3 3\",\"Ġsim ilar\",\"as k\",\"ĠD on\",\"Ġcharact er\",\"ort s\",\"ĠH ouse\",\"Ġreport ed\",\"Ġty pe\",\"v al\",\"i od\",\"ĠHow ever\",\"Ġt arg\",\"Ġent ire\",\"pp ing\",\"Ġhist ory\",\"Ġl ive\",\"ff ic\",\".... ....\",\"ed eral\",\"Ġtr ying\",\"Ġdisc uss\",\"ĠH ar\",\"ac es\",\"l ished\",\"Ġse lf\",\"os p\",\"re st\",\"Ġro om\",\"el t\",\"Ġf all\",\"ol ution\",\"Ġe t\",\"Ġ x\",\"Ġis n\",\"Ġide a\",\"b o\",\"Ġs ound\",\"ĠD ep\",\"Ġsome one\",\"ci ally\",\"ull y\",\"Ġf oc\",\"Ġob ject\",\"if t\",\"ap er\",\"Ġplay er\",\"Ġr ather\",\"Ġserv ice\",\"as hing\",\"ĠD o\",\"ĠP art\",\"ru g\",\"m on\",\"p ly\",\"Ġm or\",\"Ġnot hing\",\"Ġprov ide\",\"I C\",\"un g\",\"Ġpart y\",\"Ġex ist\",\"Ġm ag\",\"7 0\",\"Ġr ul\",\"Ġh ouse\",\"Ġbeh ind\",\"Ġhow ever\",\"ĠW orld\",\"Ġs um\",\"Ġapp lic\",\"Ġ ;\",\"Ġfun ction\",\"g r\",\"ĠP ol\",\"Ġfr ont\",\"2 00\",\"Ġser ies\",\"Ġt em\",\"Ġty p\",\"ill s\",\"Ġo pt\",\"Ġpoint s\",\"Ġbel ow\",\"itt ed\",\"Ġspec ific\",\"Ġ201 7\",\"um b\",\"Ġr a\",\"Ġpre vious\",\"Ġpre t\",\"re me\",\"Ġc ustom\",\"Ġcour t\",\"ĠM e\",\"Ġre pl\",\"Ġwho le\",\"g o\",\"c er\",\"Ġt reat\",\"ĠA ct\",\"Ġprob ably\",\"Ġle arn\",\"end er\",\"ĠA ss\",\"Ġvers ion\",\"n ow\",\"Ġche ck\",\"ĠC al\",\"R E\",\"min ist\",\"O n\",\"our ces\",\"Ġben ef\",\"Ġd oc\",\"Ġdet er\",\"Ġen c\",\"Ġsu per\",\"Ġadd ress\",\"Ġv ict\",\"Ġ201 3\",\"Ġme as\",\"t r\",\"Ġf ield\",\"W hen\",\"Ġsign ific\",\"u ge\",\"Ġfe at\",\"Ġcomm on\",\"l oad\",\"Ġbe gin\",\"Ġbr ing\",\"Ġa ction\",\"er man\",\"Ġdesc rib\",\"Ġind ust\",\"Ġwant ed\",\"ri ed\",\"m ing\",\"Ġatt empt\",\"4 5\",\"f er\",\"Ġd ue\",\"ress ion\",\"# #\",\"Ġsh all\",\"Ġs ix\",\"o o\",\"Ġst ep\",\"Ġp ub\",\"Ġhim self\",\"Ġ2 3\",\"Ġc op\",\"Ġd est\",\"Ġst op\",\"A C\",\"ib ility\",\"Ġl ab\",\"ic ult\",\"Ġhour s\",\"Ġcre ate\",\"Ġf urther\",\"ĠAmeric a\",\"ĠC ity\",\"Ġd ou\",\"he ad\",\"S T\",\"ĠN orth\",\"c ing\",\"Ġn ational\",\"u le\",\"ĠIn st\",\"Ġt aking\",\"ĠQ u\",\"ir t\",\"Ġre d\",\"Ġrese arch\",\"v iron\",\"ĠG e\",\"Ġbre ak\",\"an a\",\"Ġsp ace\",\"ater ial\",\"Ġrec ent\",\"ĠA b\",\"Ġgener al\",\"Ġh it\",\"Ġper iod\",\"Ġevery thing\",\"ive ly\",\"Ġph ys\",\"Ġsay ing\",\"an ks\",\"Ġc ou\",\"Ġc ult\",\"ac ed\",\"e al\",\"u ation\",\"Ġc oun\",\"l u\",\"Ġinclud e\",\"Ġpos ition\",\"ĠA fter\",\"ĠCan ad\",\"ĠE m\",\"Ġim m\",\"ĠR ed\",\"Ġp ick\",\"Ġcom pl\",\"Ġm atter\",\"re g\",\"e xt\",\"ang u\",\"is c\",\"o le\",\"a ut\",\"Ġcomp et\",\"e ed\",\"f ect\",\"Ġ2 1\",\"ĠS en\",\"ĠThe se\",\"as ing\",\"Ġcan not\",\"Ġin it\",\"Ġrel ations\",\"ac hed\",\"Ġb ar\",\"Ġ4 0\",\"ĠT H\",\"Ġ201 2\",\"Ġv ol\",\"Ġg round\",\"Ġsec urity\",\"Ġup d\",\"il t\",\"3 5\",\"Ġconc ern\",\"ĠJ ust\",\"Ġwh ite\",\"Ġseem s\",\"ĠH er\",\"pe cially\",\"i ents\",\"Ġann oun\",\"Ġf ig\",\"ight s\",\"Ġst ri\",\"l ike\",\"id s\",\"Ġs us\",\"Ġw atch\",\"Ġ â\",\"Ġw ind\",\"ĠC ont\",\"Ġit self\",\"Ġm ass\",\"A l\",\"y le\",\"iqu e\",\"ĠN ational\",\"Ġab s\",\"Ġp ack\",\"Ġout side\",\"Ġan im\",\"Ġp ain\",\"et er\",\"Ġman ag\",\"du ct\",\"og n\",\"Ġ ]\",\"ĠSe pt\",\"se c\",\"o ff\",\"ĠJ an\",\"Ġf oot\",\"ad es\",\"Ġth ird\",\"Ġm ot\",\"Ġev idence\",\"int on\",\"Ġth reat\",\"a pt\",\"pl es\",\"c le\",\"Ġl o\",\"Ġde cl\",\"Ġit em\",\"med i\",\"Ġrep resent\",\"om b\",\"am er\",\"Ġsignific ant\",\"og raph\",\"s u\",\"Ġc al\",\"i res\",\"00 00\",\"I D\",\"A M\",\"Ġsim ply\",\"Ġlong er\",\"Ġf ile\",\"O T\",\"c he\",\"S o\",\"ate g\",\"or g\",\"ĠH is\",\"Ġen er\",\"Ġd om\",\"Ġup on\",\"il i\",\"\\\": \\\"\",\"Ġthem selves\",\"Ġcom ing\",\"Ġqu ite\",\"Ġdiff icult\",\"ĠB ar\",\"il ities\",\"re l\",\"end s\",\"c ial\",\"6 4\",\"Ġwom an\",\"ra p\",\"y r\",\"Ġne cess\",\"ip s\",\"Ġte xt\",\"Ġrequ ire\",\"Ġmilit ary\",\"Ġre view\",\"Ġresp ons\",\"7 5\",\"Ġsub ject\",\"Ġinst ead\",\"Ġiss ues\",\"Ġg en\",\"\\\" ,\\\"\",\"Ġmin utes\",\"Ġwe ap\",\"r ay\",\"am ed\",\"t ime\",\"b l\",\"H ow\",\"Ġc ode\",\"ĠS m\",\"Ġhig her\",\"ĠSt e\",\"r is\",\"Ġp age\",\"Ġstud ents\",\"ĠIn tern\",\"Ġmet hod\",\"ĠA ug\",\"ĠP er\",\"ĠA g\",\"Ġpolic y\",\"ĠS w\",\"Ġex ec\",\"Ġac cept\",\"um e\",\"rib ut\",\"Ġword s\",\"Ġfin al\",\"Ġchang es\",\"ĠDem ocr\",\"Ġfriend s\",\"Ġres pect\",\"Ġe p\",\"Ġcomp an\",\"iv il\",\"Ġdam age\",\"** **\",\"og le\",\"viron ment\",\"Ġne g\",\"ent al\",\"Ġa p\",\"Ġtot al\",\"iv al\",\"! \\\"\",\"l im\",\"Ġneed s\",\"Ġag re\",\"Ġdevelop ment\",\"Ġa ge\",\"ip le\",\"2 1\",\"Ġresult s\",\"ĠA f\",\"S h\",\"Ġg un\",\"ĠOb ama\",\"ro ll\",\"Ġ @\",\"Ġright s\",\"ĠB rit\",\"Ġrun ning\",\"Ġwas n\",\"Ġp ort\",\"Ġr ate\",\"Ġpret ty\",\"Ġtarg et\",\"Ġsa w\",\"Ġc irc\",\"Ġwor ks\",\"ic ro\",\"al t\",\"o ver\",\"ww w\",\"Th at\",\"l ier\",\"Ġevery one\",\"ud e\",\"Ġp ie\",\"idd le\",\"ra el\",\"Ġr ad\",\"Ġbl ock\",\"Ġw alk\",\"T o\",\"ã ģ\",\"n es\",\"ĠA ust\",\"a ul\",\"ro te\",\"ĠS outh\",\"ess ion\",\"op h\",\"Ġshow s\",\"Ġs ite\",\"Ġj o\",\"Ġr isk\",\"cl us\",\"l t\",\"Ġin j\",\"id ing\",\"ĠS pe\",\"Ġch all\",\"ir m\",\"Ġ2 2\",\"itt ing\",\"st r\",\"Ġh y\",\"L E\",\"ke y\",\"Ġbe gan\",\"at ur\",\"ashing ton\",\"l am\",\"ĠD av\",\"b it\",\"Ġs ize\",\"ĠP ar\",\"3 8\",\"ourn al\",\"f ace\",\"Ġdec ision\",\"Ġl arg\",\"Ġj ud\",\"re ct\",\"Ġcontin ue\",\"ĠO ct\",\"ove red\",\"ĠI nt\",\"==== ====\",\"Ġp arent\",\"ĠW ill\",\"Ġeas y\",\"Ġd rug\",\"ang er\",\"Ġs ense\",\"Ġd i\",\"id ay\",\"Ġener gy\",\"ist ic\",\"Ġass oci\",\"ar ter\",\"ob al\",\"e ks\",\"ĠE l\",\"ur ch\",\"Ġg irl\",\"o e\",\"it le\",\"Ġ2 8\",\"ĠC he\",\"Ġrequ est\",\"Ġso on\",\"Ġh ost\",\"k y\",\"Ġst ates\",\"om es\",\"Ġm aterial\",\"le x\",\"Ġmom ent\",\"Ġan sw\",\"on se\",\"Ġes pecially\",\"Ġn orm\",\"Ġserv ices\",\"p ite\",\"r an\",\"Ġro le\",\"4 4\",\") :\",\"Ġc red\",\"C l\",\"____ ____\",\"Ġm at\",\"Ġl og\",\"ĠCl inton\",\"O U\",\"Ġoff ice\",\"Ġ2 6\",\"Ġch arg\",\"Ġtr ack\",\"m a\",\"Ġhe art\",\"Ġb all\",\"Ġperson al\",\"Ġbuild ing\",\"n a\",\"s et\",\"b ody\",\"ĠBl ack\",\"Ġincre ase\",\"itt en\",\"Ġneed ed\",\"3 6\",\"3 2\",\"= \\\"\",\"Ġl ost\",\"Ġbec ame\",\"Ġgrou ps\",\"ĠM us\",\"Ġw rote\",\"ĠP e\",\"Ġpro p\",\"j oy\",\"Ã ©\",\"ĠWh ite\",\"Ġde ad\",\". '\",\"Ġhtt p\",\"Ġwe bs\",\"O S\",\"Ġins ide\",\"Ġwr ong\",\"Ġstat ement\",\"Ġ ...\",\"y l\",\"Ġfil m\",\"Ġmus ic\",\"Ġsh are\",\"ific ation\",\"Ġre lease\",\"Ġfor ward\",\"Ġst ay\",\"Ġcomp ut\",\"it te\",\"s er\",\"Ġorig inal\",\"Ġc ard\",\"Ġc and\",\"Ġd iv\",\"at ural\",\"Ġfav or\",\"O M\",\"Ġc ases\",\"us es\",\"Ġse ction\",\"Ġle ave\",\"g ing\",\"ov ed\",\"ĠW ashington\",\"3 9\",\"ĠG l\",\"Ġrequ ired\",\"act ion\",\"ap an\",\"o or\",\"it er\",\"ĠK ing\",\"Ġcount ries\",\"ĠG erman\",\"ll ing\",\"Ġ2 7\",\"3 4\",\"Ġquest ions\",\"Ġpr im\",\"Ġc ell\",\"Ġsh oot\",\"Ġany one\",\"ĠW est\",\"Ġaff ect\",\"ep end\",\"Ġon line\",\"ĠIs rael\",\"ĠSept ember\",\"Ġab ility\",\"Ġcont ent\",\"is es\",\"Ġre ve\",\"Ġl aun\",\"Ġind ic\",\"Ġfor ce\",\"c ast\",\"Ġso ld\",\"av ing\",\"f l\",\"Ġso ft\",\"Ġcompan ies\",\"ce ed\",\"Ġart icle\",\"Ġa ud\",\"Ġre v\",\"Ġed uc\",\"Ġplay ing\",\"0 5\",\"Ġhe ld\",\"ct or\",\"Ġrele ased\",\"Ġf ederal\",\"3 7\",\"Ġad minist\",\"Ġinter view\",\"Ġinst all\",\"Ġrece ived\",\"Ġs ource\",\"u k\",\"P h\",\"Ġser ious\",\"Ġcre ated\",\"Ġc ause\",\"Ġim medi\",\"Ġdef in\",\"u el\",\"ĠDep artment\",\"ct ions\",\"ĠC our\",\"ĠN ow\",\"z e\",\"it es\",\"it ution\",\"Ġl ate\",\"Ġspe ak\",\"n ers\",\"Ġleg al\",\"ar i\",\"ĠC or\",\"Ġwe eks\",\"Ġmod el\",\"Ġp red\",\"Ġex act\",\"B C\",\"ĠB y\",\"IN G\",\"os ing\",\"Ġt akes\",\"Ġreg ard\",\"Ġopp ortun\",\"Ġpr ice\",\"Ġ19 8\",\"ĠA pr\",\"f ully\",\"Ġor d\",\"Ġproble ms\",\"ru ction\",\"h am\",\"ĠC ount\",\"le ge\",\"Ġlead ers\",\"E T\",\"le v\",\"Ġde ep\",\"olog ical\",\"es e\",\"h aps\",\"ĠS ome\",\"Ġp ers\",\"Ġcont ract\",\"Ġrelations hip\",\"s p\",\"ou d\",\"Ġb ase\",\"4 8\",\"m it\",\"A d\",\"anc ial\",\"Ġcons um\",\"Ġpot ential\",\"Ġl angu\",\"re m\",\"et h\",\"Ġrel ig\",\"ress ed\",\"6 6\",\"Ġl ink\",\"Ġl ower\",\"ay er\",\"ĠJ une\",\"Ġf em\",\"un t\",\"er c\",\"ur d\",\"Ġcont act\",\"Ġ ill\",\"Ġm other\",\"Ġest ab\",\"h tt\",\"ĠM arch\",\"ĠB ro\",\"ĠCh ina\",\"Ġ2 9\",\"Ġs qu\",\"Ġprov ided\",\"Ġa verage\",\"as ons\",\"Ġ201 1\",\"Ġex am\",\"l in\",\"5 5\",\"n ed\",\"Ġper fect\",\"Ġt ou\",\"al se\",\"u x\",\"Ġbu y\",\"Ġsh ot\",\"Ġcol lect\",\"Ġph ot\",\"Ġplay ed\",\"Ġsur pr\",\"Ġofficial s\",\"Ġsim ple\",\"av y\",\"Ġindust ry\",\"Ġhand s\",\"g round\",\"Ġp ull\",\"Ġr ound\",\"Ġus er\",\"Ġr ange\",\"u ary\",\"Ġpriv ate\",\"op s\",\"e es\",\"Ġw ays\",\"ĠM ich\",\"Ġve h\",\"Ġex cept\",\"Ġter ms\",\"im um\",\"pp er\",\"I ON\",\"ore s\",\"ĠDr agon\",\"ou l\",\"Ġd en\",\"Ġperform ance\",\"Ġb ill\",\"c il\",\"4 7\",\"Ġen vironment\",\"Ġex c\",\"ad d\",\"Ġwor th\",\"Ġp ict\",\"Ġch ance\",\"Ġ201 8\",\"b or\",\"Ġspe ed\",\"ict ion\",\"Ġal leg\",\"ĠJ apan\",\"at ory\",\"re et\",\"Ġm atch\",\"ĠI I\",\"Ġst ru\",\"ord er\",\"Ġst e\",\"Ġl iving\",\"Ġst ruct\",\"in o\",\"Ġse par\",\"her n\",\"Ġresp onse\",\"Ġen joy\",\"Ġv ia\",\"A D\",\"um ents\",\"ace book\",\"Ġmem ber\",\"ib r\",\"iz ing\",\"Ġto ol\",\"ĠM on\",\"ĠWh ile\",\"h ood\",\"ĠA ng\",\"ĠD ef\",\"Ġoff er\",\"T r\",\"a ur\",\"Ġturn ed\",\"ĠJ uly\",\"d own\",\"an ced\",\"Ġrec ently\",\"ĠE ar\",\"Ġc e\",\"ĠSt ar\",\"ĠC ong\",\"rough t\",\"Ġbl ood\",\"Ġhop e\",\"Ġcom ment\",\"ain t\",\"Ġar ri\",\"il es\",\"Ġpartic ip\",\"ough t\",\"ri ption\",\"0 8\",\"4 9\",\"Ġg ave\",\"Ġse lect\",\"Ġkill ed\",\"sy ch\",\"Ġgo es\",\"i j\",\"Ġc oll\",\"Ġimp act\",\"at ives\",\"ĠS er\",\"0 9\",\"ĠAug ust\",\"Ġb oy\",\"d e\",\"ĠD es\",\"Ġf elt\",\"U S\",\"Ġexpect ed\",\"Ġim age\",\"ĠM ark\",\"cc ording\",\"o ice\",\"E C\",\"ĠM ag\",\"en ed\",\"h old\",\"ĠP ost\",\"Ġpre vent\",\"N o\",\"Ġinvol ved\",\"Ġey es\",\"Ġquick ly\",\"A t\",\"un k\",\"Ġbeh av\",\"Ġ ur\",\"Ġl ed\",\"c ome\",\"e y\",\"Ġcand id\",\"Ġear lier\",\"Ġfoc us\",\"et y\",\"P ro\",\"led ge\",\"ix ed\",\"ill ed\",\"Ġpop ular\",\"A P\",\"Ġset t\",\"l ight\",\"Ġvar ious\",\"in ks\",\"Ġlevel s\",\"Ġro ad\",\"ell ig\",\"ab les\",\"he l\",\"itte e\",\"ĠG ener\",\"y pe\",\"Ġhe ard\",\"ic les\",\"Ġm is\",\"Ġus ers\",\"ĠS an\",\"Ġimpro ve\",\"Ġf ather\",\"Ġse arch\",\"The y\",\"v il\",\"Ġprof ess\",\"Ġkn ew\",\"Ġl oss\",\"Ġev ents\",\"6 5\",\"Ġb illion\",\"0 7\",\"0 2\",\"ĠNew s\",\"ĠA M\",\"Ġco ver\",\"w here\",\"ens ion\",\"Ġb ott\",\"Ġare as\",\"en ces\",\"op e\",\"ĠTw itter\",\"a el\",\"Ġget s\",\"ĠGo ogle\",\"Ġs n\",\"i ant\",\"Ġv ote\",\"Ġnear ly\",\"Ġinclud ed\",\"Ġrec ogn\",\"z z\",\"m m\",\"al ed\",\"Ġhappen ed\",\"0 4\",\"Ġh ot\",\"Ġwho se\",\"Ġc ivil\",\"Ġsu ff\",\"o es\",\"it iz\",\"ĠSy ri\",\"Ġresp ond\",\"Ġh on\",\"Ġfeat ures\",\"Ġeconom ic\",\"ĠApr il\",\"r im\",\"Ġtechn ology\",\"Ġo ption\",\"ag ing\",\"Ġpur ch\",\"R e\",\"Ġl at\",\"ch ie\",\"is l\",\"Ġrec omm\",\"u f\",\"Ġtr aining\",\"Ġeffect s\",\"Ġf ast\",\"Ġ201 0\",\"Ġocc ur\",\"Ġwebs ite\",\"Ġem ail\",\"Ġs ens\",\"e ch\",\"Ġo il\",\"Ġinf lu\",\"Ġcurrent ly\",\"ĠS ch\",\"ĠAd d\",\"Ġgo al\",\"Ġsc ient\",\"Ġcon v\",\"1 00\",\"em y\",\"Ġdec ided\",\"Ġtra vel\",\"Ġm ention\",\"L L\",\"0 3\",\"Ġe lection\",\"Ġph one\",\"Ġlook s\",\"Ġsit uation\",\"Ġc y\",\"Ġh or\",\"b ed\",\"ĠCour t\",\"a ily\",\"av es\",\"Ġqu ality\",\"ĠCom p\",\"w ise\",\"Ġt able\",\"Ġst aff\",\"ĠW ind\",\"et t\",\"Ġtri ed\",\"ide red\",\"Ġadd ition\",\"Ġb ox\",\"Ġl ack\",\"ar ily\",\"Ġw ide\",\"Ġm id\",\"Ġbo ard\",\"ys is\",\"Ġant i\",\"h a\",\"Ġd ig\",\"en ing\",\"Ġd ro\",\"C on\",\"6 8\",\"Ġsl ow\",\"b ased\",\"se qu\",\"Ġp ath\",\"E x\",\"ak er\",\"Ġwork ed\",\"Ġp en\",\"Ġeng ine\",\"Ġlook ed\",\"ĠSu per\",\"ĠS erv\",\"Ġvict im\",\"U n\",\"Ġproper ty\",\"Ġint rodu\",\"Ġexec ut\",\"ĠP M\",\"L e\",\"Ġcol or\",\"ĠM ore\",\"Ġ6 0\",\"Ġnet work\",\"Ġd ate\",\"c ul\",\"id ge\",\"Ġext ra\",\"3 1\",\"Ġs le\",\"6 7\",\"Ġw ond\",\"Ġreport s\",\"j ust\",\"ĠAust ral\",\"Ġcap ital\",\"Ġen s\",\"Ġcomm and\",\"Ġallow ed\",\"Ġpre p\",\"Ġca pt\",\"h ib\",\"Ġnum bers\",\"ch an\",\"Ġf air\",\"m p\",\"om s\",\"Ġre ach\",\"W ith\",\"t ain\",\"Ġbro ad\",\"Ġcou ple\",\"ec ause\",\"ly ing\",\"ĠF eb\",\"Ġsc reen\",\"Ġl ives\",\"Ġpri or\",\"ĠCong ress\",\"A r\",\"Ġappro ach\",\"Ġe mer\",\"ar ies\",\"ĠD is\",\"s erv\",\"ĠN e\",\"Ġbu ilt\",\"c ies\",\"Ġre pe\",\"Ġrul es\",\"for ce\",\"ĠP al\",\"Ġfin ancial\",\"Ġcons idered\",\"ĠCh ar\",\"n ces\",\"ĠI S\",\"Ġb rought\",\"Ġb i\",\"i ers\",\"ĠS im\",\"O P\",\"Ġproduct s\",\"Ġvis it\",\"Ġdoc ument\",\"Ġcon duct\",\"Ġcomplete ly\",\"in ing\",\"ĠCal if\",\"ib ly\",\"Ġwr itten\",\"ĠT V\",\"em ents\",\"Ġd raw\",\"O ne\",\"Ġpub lished\",\"Ġsec ret\",\"r ain\",\"he t\",\"ĠF acebook\",\"ond ay\",\"ĠU p\",\"Ġsex ual\",\"Ġth ous\",\"ĠP at\",\"Ġ ess\",\"Ġstand ard\",\"Ġar m\",\"g es\",\"ect ion\",\"Ġf ell\",\"Ġfore ign\",\"an i\",\"ĠFr iday\",\"Ġreg ular\",\"in ary\",\"Ġincre ased\",\"Ġus ually\",\"Ġdem on\",\"Ġd ark\",\"Ġadd itional\",\"ro l\",\"ĠO f\",\"Ġprodu ction\",\"! !\",\"und red\",\"Ġintern ational\",\"id ents\",\"ĠF ree\",\"rou p\",\"Ġr ace\",\"Ġm ach\",\"Ġh uge\",\"A ll\",\"le ar\",\"ove mber\",\"Ġto wn\",\"Ġatt ention\",\"ĠO ff\",\"y ond\",\"ĠThe n\",\"f ield\",\"Ġter ror\",\"ra z\",\"ĠB o\",\"Ġmeet ing\",\"ĠP ark\",\"Ġar rest\",\"Ġf ear\",\"Ġa w\",\"ĠV al\",\"or ing\",\"' ,\",\"Ġext reme\",\"ar r\",\"Ġwork ers\",\"A fter\",\"Ġ3 1\",\"n et\",\"am ent\",\"Ġdirect ly\",\"Ġpop ulation\",\"ub e\",\"ĠOct ober\",\"ĠI N\",\"ĠJan uary\",\"5 9\",\"ĠDav id\",\"Ġc ross\",\"ce mber\",\"ĠF irst\",\"Ġmess age\",\"ir it\",\"Ġn ation\",\"Ġp oll\",\"is ions\",\"Ġansw er\",\"n y\",\"is ode\",\"Ġcar ry\",\"ĠRuss ia\",\"Ġhe ar\",\"eng th\",\"ro y\",\"Ġn atural\",\"in ally\",\"Ġdo g\",\"m itted\",\"Ġtr ade\",\"Ġsub st\",\"Ġmult iple\",\"ĠAf ric\",\"Ġf ans\",\"Ġs ort\",\"Ġgl obal\",\"ic ation\",\"ĠW ed\",\"ar a\",\"Ġa chie\",\"Ġlangu age\",\"ve y\",\"Ġt al\",\"Ġnecess ary\",\"Ġdet ails\",\"Ġs en\",\"ĠS und\",\"ĠRe g\",\"ĠR ec\",\"0 6\",\"Ġs il\",\"ress ive\",\"Ġmed ical\",\"un ch\",\"orn ia\",\"Ġu nd\",\"f ort\",\"oc ks\",\"ĠM onday\",\"ues day\",\"c raft\",\"7 7\",\"ur t\",\"Ġ ver\",\"ĠH ill\",\"Ġrece ive\",\"Ġmor ning\",\"es tern\",\"Ġb ank\",\"Ġs at\",\"ir th\",\"ĠH igh\",\"Ġdev ice\",\"ĠTH E\",\"ĠCent er\",\"Ġsaf e\",\"Ġp le\",\"ĠCanad a\",\"Ġsystem s\",\"Ġass ist\",\"Ġsur v\",\"Ġb attle\",\"ĠS oc\",\"vert is\",\"S he\",\"Ġp aper\",\"Ġgrow th\",\"Ġc ast\",\"S c\",\"Ġpl ans\",\"ll ed\",\"Ġpart s\",\"Ġw all\",\"Ġmove ment\",\"Ġpract ice\",\"im ately\",\"Ġdis play\",\"Ġsomet imes\",\"om p\",\"ĠP aul\",\"ĠY es\",\"k ing\",\"5 8\",\"o ly\",\"Ġs on\",\"Ġav oid\",\"ok es\",\"ĠJ ew\",\"Ġto wards\",\"as c\",\"Ġ //\",\"ĠK ore\",\"Ġtalk ing\",\"Ġcor rect\",\"Ġsp ent\",\"ic ks\",\"i able\",\"e ared\",\"Ġter m\",\"Ġwant s\",\"om ing\",\"Ġ ut\",\"Ġdou b\",\"Ġfor ces\",\"Ġp lease\",\"6 9\",\"ĠN ovember\",\"at form\",\"ond on\",\"Ġon es\",\"Ġimmedi ately\",\"ĠRuss ian\",\"ĠM et\",\"Ġde g\",\"Ġparent s\",\"C H\",\"ĠAmeric ans\",\"al y\",\"ĠM od\",\"Ġsh own\",\"Ġcond itions\",\"Ġst uff\",\"Ġre b\",\"ĠY our\",\"Ġinclud es\",\"n own\",\"ĠS am\",\"Ġexper ien\",\"m ission\",\"ĠE ven\",\"augh t\",\"Ġannoun ced\",\"ĠRepublic an\",\"Ġdeter min\",\"Ġdescrib ed\",\"ĠCount y\",\"( )\",\"Ġdo or\",\"Ġchang ed\",\"Ġne igh\",\"ĠH ere\",\"Ġcle an\",\"Ġp an\",\"ĠDe cember\",\"ĠEurope an\",\"ir ing\",\"ap ter\",\"Ġcl ub\",\"ĠT uesday\",\"Ġp aid\",\"ĠN et\",\"Ġattack s\",\"Ġcharact ers\",\"Ġal one\",\"Ġdirect or\",\"d om\",\"Ġ3 5\",\"Ġl oad\",\"Ġr out\",\"ĠCalif ornia\",\"Ġfin ally\",\"Ġr ac\",\"Ġcont r\",\"Ġexact ly\",\"res h\",\"p ri\",\"ĠIs lam\",\"Ġn ature\",\"Ġcare er\",\"Ġlat est\",\"Ġcon vers\",\"ĠS l\",\"p ose\",\"ci ent\",\"ĠIn c\",\"iv ity\",\"8 8\",\"ĠA tt\",\"ĠM or\",\"nes day\",\"Ġwe ight\",\"k en\",\"Ġnot e\",\"Ġteam s\",\"Ġ \\\\\",\"air s\",\"ĠG reen\",\"Ġh undred\",\"on ent\",\"Ġstre ng\",\"Ġcons ist\",\"ic ated\",\"Ġreg ul\",\"Ġl ic\",\"ast ic\",\"Ġt en\",\"urs day\",\"ellig ence\",\"ous ly\",\"ĠU K\",\"B I\",\"Ġcost s\",\"Ġind epend\",\"ĠA P\",\"Ġnorm al\",\"Ġh om\",\"Ġob vious\",\"Ġs we\",\"Ġst ar\",\"Ġread y\",\"ac her\",\"Ġimp lement\",\"g est\",\"Ġs ong\",\"ĠG et\",\"ĠL ab\",\"Ġinterest ing\",\"us ing\",\"Ġg iving\",\"ĠSund ay\",\"Ġet c\",\"Ġm iddle\",\"Ġrem ember\",\"r ight\",\"os ition\",\"ut ions\",\"Ġm ax\",\"4 6\",\"Ġyour self\",\"Ġdem and\",\"Ġtreat ment\",\"Ġd anger\",\"ĠC ons\",\"Ġgu y\",\"ĠBrit ish\",\"Ġphys ical\",\"Ġrel ated\",\"Ġrem ain\",\"Ġcould n\",\"Ġref er\",\"Ġc itiz\",\"b ox\",\"EN T\",\"bo ard\",\"Ġin n\",\"I G\",\"er o\",\"ĠSt reet\",\"osp ital\",\"ren ch\",\"cher s\",\"Ġst ra\",\"O L\",\"ag er\",\"ĠA N\",\"Ġeas ily\",\"I A\",\"en ge\",\"in y\",\"Ġcl os\",\"ock ed\",\"Ġus es\",\"ĠC oun\",\"I m\",\"u ild\",\"? ?\",\"m ore\",\"Ġan g\",\"Ġwr ite\",\"ol ute\",\"5 7\",\"Ġlead er\",\"Ġread ing\",\"< /\",\"Ġaut om\",\"est s\",\"4 3\",\"Ġleg isl\",\"ĠG old\",\"Ġdesign ed\",\"ĠS T\",\"ĠLe g\",\"a res\",\"Ġbe aut\",\"ĠT ex\",\"Ġappear s\",\"Ġstru gg\",\"ĠR om\",\"Ġ 00\",\"Ġcho ice\",\"Ġparticular ly\",\"ĠF rom\",\"op er\",\"ĠL ondon\",\"ann ed\",\"Ġallow s\",\"ob ile\",\"Ġdiffere nce\",\"âĢ ¢\",\"ĠV iew\",\"ĠWed nesday\",\"Ġal though\",\"Ġrel ative\",\"Ġapplic ation\",\"ate ver\",\"Ġare n\",\"Ġmy self\",\"Ġim ag\",\"Ġdis e\",\"Ġsoc iety\",\"Ġfre qu\",\"ĠEng lish\",\"Ġpo or\",\"ĠD ay\",\"Ġwrit ing\",\"Ġse ven\",\"Ġstart ing\",\"Ġb ud\",\"Ġpr int\",\"ĠTr ans\",\"uf act\",\"ĠSt ud\",\"n ew\",\"Ġcr im\",\"Ġg ives\",\"Ġco ol\",\"a e\",\"i ance\",\"ĠGener al\",\"Ġthink ing\",\"Ġsa ve\",\"Ġlim ited\",\"ĠPart y\",\"Ġmean ing\",\"p en\",\"ow ers\",\"ĠJ ack\",\"E M\",\"Ġn ice\",\"ru pt\",\"Ġg as\",\"Ġe ight\",\"Ġfe et\",\"Ġeff ort\",\"Ġ ign\",\"ic it\",\"B l\",\"co in\",\"Ġop in\",\"Ġbr ain\",\"Wh ile\",\"he st\",\"ĠTh ursday\",\"Ġwould n\",\"augh ter\",\"Ġtou ch\",\"le ments\",\"Ġstud ies\",\"Ġcent er\",\"c ont\",\"or ge\",\"Ġcomput er\",\"Ġinvestig ation\",\"P l\",\"or ks\",\"Ġ200 8\",\"Ġincre asing\",\"Ġst ore\",\"Ġcom ments\",\"Ġb al\",\"m en\",\"Ġdo ll\",\"Ġl iber\",\"Ġw ife\",\"Ġlaw s\",\"atur day\",\"it ness\",\"Ġmod ern\",\"ĠS k\",\"Ġadminist ration\",\"Ġopportun ity\",\"Ġs al\",\"Ġpower ful\",\"M y\",\"Ġclaim s\",\"ĠEar th\",\"ord s\",\"Ġt itle\",\"Ġes c\",\"n ame\",\"N ot\",\"om en\",\"Ġbe yond\",\"Ġc amer\",\"Ġse ll\",\"it ute\",\"ear ch\",\"Ġapp l\",\"im ent\",\"4 2\",\"ĠAr t\",\"Ġun f\",\"Ġviol ence\",\"ur g\",\"ĠE ast\",\"Ġcomp ared\",\"Ġopt ions\",\"Ġthrough out\",\"Ġv s\",\"ig r\",\". [\",\"ac hes\",\"7 8\",\"Ġfil es\",\"F L\",\"E L\",\"ar ian\",\"ĠJ ames\",\"ĠA ir\",\"an ch\",\"Ġdet ail\",\"Ġpie ce\",\"P S\",\"Ġn amed\",\"Ġeduc ation\",\"Ġdri ve\",\"Ġitem s\",\"Ġstud ent\",\"ic ed\",\": :\",\"ic o\",\"Ġth row\",\"Ġsc ene\",\"Ġcomple x\",\"Ġ200 9\",\"Ġpre c\",\"ĠB re\",\"7 9\",\"Ġcon cept\",\"Ġstat us\",\"am ing\",\"Ġd ied\",\"Ġknow ledge\",\"Ġbegin ning\",\"O D\",\"ru ary\",\"Ġcertain ly\",\"Ġgu ys\",\"Ġsl ight\",\"in n\",\"ound s\",\"Ġf ine\",\"Ġf at\",\"ic ations\",\"Ġper haps\",\"ĠA nt\",\"Ġinc ome\",\"Ġhtt ps\",\"Ġmajor ity\",\"port s\",\"st on\",\"Ġgreat er\",\"Ġfe ed\",\"ent ially\",\"Ġsaf ety\",\"Ġun ique\",\"and om\",\"Ġg one\",\"Ġshow ed\",\"Ġhist or\",\"Ġcoun ter\",\"i us\",\"id a\",\"Ġlead ing\",\"i pe\",\"Ġs end\",\"ĠDon ald\",\"er ve\",\"Ġdef ense\",\"ines e\",\"Ġy es\",\"ĠF ire\",\"ĠMus lim\",\"ra q\",\"Ġcontin ued\",\"os h\",\"Ġprov ides\",\"Ġpr ison\",\"ĠP re\",\"Ġhapp y\",\"Ġeconom y\",\"Ġtr ust\",\"ag s\",\"ĠG ame\",\"Ġweap ons\",\"um an\",\"ĠC le\",\"it ation\",\"Ġanal ysis\",\"ĠT imes\",\"Ġsc ience\",\"- >\",\"Ġfig ure\",\"Ġdis app\",\"ent y\",\"Ġsoft ware\",\"Ġu lt\",\"Ġoffic ers\",\"N ew\",\"I s\",\"Ġrem ains\",\"ĠInd ia\",\"Ġp sych\",\"ri ef\",\"Ġc at\",\"es c\",\"Ġob serv\",\"Ġst age\",\"ĠD ark\",\"Ġent er\",\"ch ange\",\"Ġpass ed\",\"Ġdes pite\",\"ĠO ut\",\"Ġmov ie\",\"r s\",\"Ġv oice\",\"m ine\",\"ĠPl ay\",\"Ġto ward\",\"ĠT er\",\"Ġreg ion\",\"Ġval ues\",\"or ters\",\"Ġm ount\",\"Ġoffic er\",\"ĠO ther\",\"b an\",\"Ġh ous\",\"w ood\",\"ro om\",\"I V\",\"ĠS un\",\"se e\",\"ĠO ver\",\"ro g\",\"9 0\",\"Ġl ay\",\"ĠT ur\",\"a wn\",\"Ġpress ure\",\"ĠS ub\",\"Ġbook s\",\"ed om\",\"ĠS and\",\"A A\",\"ag o\",\"Ġre asons\",\"f ord\",\"Ġactiv ity\",\"U T\",\"N ow\",\"ĠSen ate\",\"ce ll\",\"n ight\",\"Ġcall s\",\"in ter\",\"Ġlet ter\",\"ĠR ob\",\"ĠJ e\",\"Ġcho ose\",\"ĠL aw\",\"G et\",\"B e\",\"Ġro b\",\"Ġtyp es\",\"Ġpl atform\",\"Ġqu arter\",\"R A\",\"ĠT ime\",\"Ġmay be\",\"ĠC r\",\"9 5\",\"p re\",\"Ġmov ing\",\"Ġl if\",\"Ġgo ld\",\"Ġs om\",\"Ġpat ients\",\"Ġtr uth\",\"ĠK e\",\"ur ance\",\"ant ly\",\"m ar\",\"Ġchar ge\",\"ĠG reat\",\"Ġce le\",\"---------------- ----------------\",\"Ġro ck\",\"ro id\",\"an cy\",\"Ġcred it\",\"a ud\",\"B y\",\"ĠE very\",\"Ġmov ed\",\"ing er\",\"rib ution\",\"Ġn ames\",\"Ġstra ight\",\"ĠHe alth\",\"ĠW ell\",\"Ġfe ature\",\"Ġr ule\",\"Ġsc he\",\"in ated\",\"ĠMich ael\",\"ber g\",\"4 1\",\"il ed\",\"b and\",\"Ġcl ick\",\"ĠAng el\",\"on ents\",\"Â Ń\",\"ĠI raq\",\"ĠS aturday\",\"Ġa ware\",\"p art\",\"Ġpat tern\",\"O W\",\"ĠL et\",\"Ġgr ad\",\"ign ed\",\"Ġassoci ated\",\"Ġst yle\",\"n o\",\"i ation\",\"a ith\",\"il ies\",\"Ġst ories\",\"ur ation\",\"Ġindividual s\",\"ĠâĢ ¦\",\"m iss\",\"ĠAss oci\",\"ish ing\",\"ab y\",\"Ġsum mer\",\"ĠB en\",\"Ġ3 2\",\"Ġar ch\",\"ut y\",\"ĠTex as\",\"h ol\",\"Ġfull y\",\"Ġm ill\",\"Ġfollow ed\",\"ĠB ill\",\"ĠInd ian\",\"ĠSec ret\",\"ĠB el\",\"ĠFeb ruary\",\"Ġjob s\",\"Ġseem ed\",\"ĠGo vern\",\"i pped\",\"Ġreal ity\",\"Ġl ines\",\"Ġp ark\",\"Ġmeas ure\",\"ĠO ur\",\"I M\",\"Ġbro ther\",\"Ġgrow ing\",\"Ġb an\",\"Ġest im\",\"Ġc ry\",\"ĠS chool\",\"Ġme chan\",\"ĠO F\",\"ĠWind ows\",\"Ġr ates\",\"ĠO h\",\"Ġpos itive\",\"Ġcult ure\",\"ist ics\",\"ic a\",\"Ġh ar\",\"y a\",\"ite ly\",\"i pp\",\"Ġm ap\",\"en cies\",\"ĠWill iam\",\"I I\",\"ak ers\",\"5 6\",\"ĠM art\",\"ĠR em\",\"Ġal tern\",\"it ude\",\"Ġco ach\",\"row d\",\"D on\",\"Ġk ids\",\"Ġj ournal\",\"Ġcor por\",\"Ġf alse\",\"Ġwe b\",\"Ġsle ep\",\"Ġcont ain\",\"Ġst o\",\"Ġb ed\",\"iver se\",\"ĠR ich\",\"ĠCh inese\",\"Ġp un\",\"Ġme ant\",\"k nown\",\"Ġnot ice\",\"Ġfavor ite\",\"a ven\",\"Ġcond ition\",\"Ġpur pose\",\") )\",\"Ġorgan ization\",\"Ġchall eng\",\"Ġman ufact\",\"Ġsus p\",\"ĠA c\",\"Ġcrit ic\",\"un es\",\"uc lear\",\"Ġm er\",\"vent ion\",\"Ġ8 0\",\"Ġm ist\",\"ĠU s\",\"ĠT or\",\"htt p\",\"ol f\",\"Ġlarg er\",\"Ġadv ant\",\"Ġrese ar\",\"Ġact ions\",\"m l\",\"Ġke pt\",\"Ġa im\",\", '\",\"c ol\",\"Ġbenef its\",\"if ying\",\"Ġact ual\",\"ĠIntern ational\",\"Ġveh icle\",\"Ġch ief\",\"Ġeff orts\",\"ĠLe ague\",\"ĠM ost\",\"Ġwa it\",\"Ġad ult\",\"Ġover all\",\"Ġspe ech\",\"Ġhigh ly\",\"Ġfem ale\",\"Ġer ror\",\"Ġeffect ive\",\"5 4\",\"Ġenc our\",\"w ell\",\"Ġfail ed\",\"Ġcons erv\",\"Ġprogram s\",\"Ġt rou\",\"Ġa head\",\"5 00\",\"vertis ement\",\"I P\",\"ĠF ound\",\"p ir\",\"Ġ %\",\"Ġcr ime\",\"and er\",\"Ġloc ation\",\"ĠI ran\",\"Ġbehav ior\",\"az ing\",\"Ġr are\",\"Ġem b\",\"Ġca used\",\"Ġsh ip\",\"Ġact ive\",\"Ġcont ribut\",\"Ġg reen\",\"Ġac qu\",\"Ġref lect\",\"ven ue\",\"Ġf irm\",\"Ġb irth\",\"] .\",\"Ġclear ly\",\"Ġem ot\",\"Ġag ency\",\"ri age\",\"Ġmem ory\",\"9 8\",\"S A\",\"ĠSe e\",\"ac ing\",\"C C\",\"Ġbig gest\",\"Ġr ap\",\"Ġbas ic\",\"Ġb and\",\"e at\",\"Ġsus pect\",\"ĠM ac\",\"Ġ9 0\",\"m ark\",\"ist an\",\"Ġsp read\",\"am s\",\"k i\",\"as y\",\"ra v\",\"ĠR ober\",\"Ġdemon str\",\"r ated\",\"Ġabs olute\",\"Ġpl aces\",\"Ġim pl\",\"ibr ary\",\"Ġc ards\",\"Ġdest roy\",\"Ġv irt\",\"ve re\",\"Ġapp eared\",\"y an\",\"p oint\",\"Ġbe g\",\"Ġtem per\",\"s pe\",\"ant ed\",\"ear s\",\"ĠD irect\",\"Ġl ength\",\"Ġbl og\",\"am b\",\"Ġint eg\",\"Ġres ources\",\"ac c\",\"if ul\",\"Ġsp ot\",\"Ġfor ced\",\"Ġthous ands\",\"ĠMin ister\",\"Ġqu al\",\"ĠF rench\",\"at ically\",\"Ġgener ally\",\"Ġdr ink\",\"Ġth us\",\"I L\",\"od es\",\"Ġappro pri\",\"ĠRe ad\",\"Ġwh om\",\"Ġey e\",\"Ġcol lege\",\"Ġ4 5\",\"ire ction\",\"Ġens ure\",\"Ġapp arent\",\"id ers\",\"Ġrelig ious\",\"Ġmin or\",\"ol ic\",\"Ġt ro\",\"ĠWh y\",\"rib ute\",\"m et\",\"Ġprim ary\",\"Ġdevelop ed\",\"Ġpe ace\",\"Ġsk in\",\"st e\",\"av a\",\"Ġbl ue\",\"Ġfam ilies\",\"Ġ ir\",\"Ġapp ly\",\"Ġin form\",\"ĠSm ith\",\"C T\",\"i i\",\"Ġlim it\",\"Ġres ist\",\"........ ........\",\"um n\",\"Ġconf lic\",\"Ġtw e\",\"ud d\",\"ĠT om\",\"Ġl iter\",\"qu e\",\"b on\",\"Ġha ir\",\"Ġevent ually\",\"Ġp us\",\"Ġhelp ed\",\"Ġag g\",\"or ney\",\"ĠApp le\",\"Ġf it\",\"ĠS ur\",\"Ġpre m\",\"Ġs ales\",\"Ġsecond s\",\"Ġstreng th\",\"Ġfeel ing\",\"¿ ½\",\"Ġt our\",\"Ġknow s\",\"o om\",\"Ġex erc\",\"Ġsom ew\",\"ï ¿½\",\"> >\",\"Ġsp okes\",\"Ġide as\",\"Ġreg ist\",\"so ft\",\"ĠD el\",\"ĠP C\",\"Ġpro pos\",\"Ġlaun ch\",\"Ġbott om\",\"T H\",\"ĠP lease\",\"v est\",\"it z\",\"ĠIn ter\",\"Ġsc ript\",\"Ġr at\",\"ar ning\",\"Ġ il\",\"ĠJ er\",\"ĠA re\",\"Ġwh atever\",\"ok en\",\"ci ence\",\"Ġmod e\",\"Ġag ree\",\"Ġs ources\",\"Ġinit ial\",\"Ġrest rict\",\"Ġwond er\",\"us ion\",\"## ##\",\"ĠS il\",\"vil le\",\"Ġb urn\",\"t w\",\"as ion\",\"ĠÂ £\",\"Ġn or\",\"u ing\",\"Ġre ached\",\"Ġs un\",\"Ġc ateg\",\"ig ration\",\"Ġc ook\",\"Ġprom ot\",\"Ġm ale\",\"Ġcl imate\",\"Ġf ix\",\"Ġalleg ed\",\"U R\",\"all ed\",\"Ġim ages\",\"C ont\",\"ot a\",\"Ġschool s\",\"i os\",\"Ġd rop\",\"Ġst ream\",\"ĠM o\",\"Ġprevious ly\",\"al ing\",\"Ġp et\",\"Ġdou ble\",\"Ġ( @\",\"ann el\",\"Ġdef ault\",\"t ies\",\"Ġr ank\",\"ĠD ec\",\"ĠCoun cil\",\"Ġweap on\",\"Ġst ock\",\"Ġanal y\",\"ĠSt r\",\"Ġpict ure\",\"ĠPol ice\",\"f erence\",\"Ġcent ury\",\"Ġcitiz ens\",\"Ġon to\",\"Ġexp and\",\"Ġhe ro\",\"ĠS ol\",\"Ġw ild\",\"Ġupd ate\",\"Ġcustom ers\",\"r ont\",\"d ef\",\"Ġl ik\",\"Ġcrim inal\",\"ĠChrist ian\",\"S P\",\"7 6\",\"Ġle aving\",\"Ġother wise\",\"ĠD ist\",\"Ġbas is\",\"5 2\",\"5 3\",\"ic ip\",\"ĠB er\",\"Ġrecomm end\",\"Ġfl oor\",\"Ġc rowd\",\"ol es\",\"Ġ7 0\",\"Ġcent ral\",\"ĠE v\",\"Ġd ream\",\"Ġdown load\",\"Ġconf ir\",\"ĠTh om\",\"Ġwind ow\",\"Ġhapp ens\",\"Ġun it\",\"Ġt end\",\"Ġs pl\",\"Ġbec omes\",\"Ġfight ing\",\"Ġpred ict\",\"ĠP ress\",\"ĠP ower\",\"Ġhe avy\",\"ak ed\",\"Ġf an\",\"or ter\",\"ate gy\",\"B A\",\"iz es\",\"Ġsp end\",\"H ere\",\"Ġ200 7\",\"Ġad op\",\"ĠH am\",\"Ġfoot ball\",\"ĠP ort\",\"od ay\",\"5 1\",\"amp ions\",\"Ġtrans fer\",\"h t\",\"Ġ3 8\",\"ter m\",\"ac ity\",\"Ġb ur\",\"] ,\",\"tern al\",\"r ig\",\"b ut\",\"Ġthere fore\",\"ĠB ecause\",\"res p\",\"re y\",\"Ġm ission\",\"S ome\",\"Ġnot ed\",\"Ġass um\",\"Ġdise ase\",\"Ġed it\",\"Ġprog ress\",\"r d\",\"ĠB rown\",\"oc al\",\"Ġadd ing\",\"Ġra ised\",\"ĠAn y\",\"Ġt ick\",\"Ġsee ing\",\"ĠPe ople\",\"Ġagre ement\",\"Ġser ver\",\"Ġw at\",\"Ġdeb ate\",\"Ġsupp osed\",\"il ing\",\"Ġlarg est\",\"Ġsuccess ful\",\"ĠP ri\",\"ĠDemocr atic\",\"Ġj ump\",\"ĠSyri a\",\"Ġown ers\",\"Ġoff ers\",\"Ġshoot ing\",\"Ġeff ic\",\"se y\",\"Ġha ven\",\"ver se\",\"te red\",\"ĠL ight\",\"im al\",\"ĠB ig\",\"Ġdef end\",\"Ġbe at\",\"Ġrecord s\",\"% )\",\"Ġsc en\",\"Ġemploy ees\",\"Ġdev ices\",\"he m\",\"Ġcom mer\",\"ĠM ex\",\"Ġbenef it\",\"ĠPro f\",\"Ġil leg\",\"Ġsur face\",\"ĠAl so\",\"Ġh arm\",\"ing ly\",\"w ide\",\"ĠA lex\",\"Ġsh ut\",\"ĠC ur\",\"Ġl ose\",\"p m\",\"Ġchall enge\",\"se mb\",\"Ġst ation\",\"Ġint elligence\",\"Ġacc ur\",\"ĠFl or\",\"Ġrequ ires\",\"ĠM al\",\"b um\",\"Ġh ospital\",\"Ġsp irit\",\"Ġoff ered\",\"Ġprodu ce\",\"ĠComm un\",\"Ġcreat ing\",\"Ġcr is\",\"s pect\",\"Ġend ed\",\"Ġd aily\",\"Ġvot ers\",\"land s\",\"i as\",\"i h\",\"on a\",\"Ġsm art\",\"ĠOff ice\",\"ĠL ord\",\"ri al\",\"ĠIntern et\",\"Ġcirc um\",\"Ġextreme ly\",\"' .\",\"Ġopin ion\",\"ĠM il\",\"Ġg ain\",\"B S\",\"ĠF in\",\"y p\",\"Ġuse ful\",\"Ġbud get\",\"Ġcom fort\",\"is f\",\"Ġback ground\",\"el ine\",\"Ġep isode\",\"Ġen emy\",\"Ġtri al\",\"Ġestab lish\",\"d ate\",\"ĠC ap\",\"Ġcontin ues\",\"Ġshow ing\",\"ĠUn ion\",\"w ith\",\"Ġpost ed\",\"ĠSy stem\",\"Ġe at\",\"ri an\",\"Ġr ise\",\"ĠGerman y\",\"il s\",\"Ġsign ed\",\"Ġv ill\",\"Ġgr and\",\"m or\",\"ĠEng land\",\"Ġproject s\",\"um ber\",\"Ġconf erence\",\"z a\",\"Ġrespons ible\",\"ĠAr ab\",\"Ġlearn ed\",\"âĢĶ âĢĶ\",\"i pping\",\"ĠGe orge\",\"O C\",\"Ġreturn ed\",\"ĠAustral ia\",\"Ġb rief\",\"Q u\",\"Ġbr and\",\"ill ing\",\"ab led\",\"Ġhig hest\",\"Ġtr ain\",\"ĠComm ission\",\"wh ile\",\"Ġn om\",\"cept ion\",\"Ġm ut\",\"ĠBl ue\",\"Ġinc ident\",\"v ant\",\"8 6\",\"ĠI D\",\"Ġn uclear\",\"7 4\",\"ĠL ike\",\"ĠR E\",\"ĠM icro\",\"l i\",\"m ail\",\"Ġcharg es\",\"8 9\",\"Ġad just\",\"ad o\",\"Ġear th\",\"N A\",\"Ġpr ices\",\"P A\",\"Ġd raft\",\"Ġrun s\",\"Ġcandid ate\",\"ens es\",\"Ġmanag ement\",\"ĠPh il\",\"ĠM iss\",\"Ġte ach\",\"g ram\",\"Ġunderstand ing\",\"a it\",\"ic ago\",\"A dd\",\"ĠE p\",\"sec ut\",\"Ġsepar ate\",\"Ġinst ance\",\"Ġe th\",\"Ġun less\",\"**** ****\",\"ĠF ore\",\"in ate\",\"Ġoper ations\",\"S p\",\"Ġf aith\",\"g ar\",\"ĠCh urch\",\"ron ic\",\"Ġconf ig\",\"os ure\",\"Ġactiv ities\",\"Ġtrad itional\",\"Ġ3 6\",\"Ġd irection\",\"Ġmach ine\",\"Ġsur round\",\"Ġp ush\",\"un ction\",\"ĠE U\",\"Ġeas ier\",\"Ġarg ument\",\"G B\",\"Ġm icro\",\"Ġsp ending\",\"iz ations\",\"Ġthe ory\",\"ad ow\",\"Ġcall ing\",\"ĠL ast\",\"Ġd er\",\"Ġinflu ence\",\"Ġcomm it\",\"Ġph oto\",\"Ġun c\",\"ist ry\",\"g n\",\"ast e\",\"ack s\",\"Ġdis p\",\"ad y\",\"d o\",\"ĠG ood\",\"Ġ `\",\"Ġw ish\",\"Ġreve aled\",\"Âł Âł\",\"l ig\",\"Ġen force\",\"ĠComm ittee\",\"Ġche m\",\"Ġmil es\",\"Ġinterest ed\",\"Ġsol ution\",\"ic y\",\"in ct\",\"Ġ- >\",\"ĠD et\",\"Ġrem oved\",\"Ġcomp ar\",\"e ah\",\"Ġpl ant\",\"ĠS ince\",\"Ġachie ve\",\"Ġadvant age\",\"Ġslight ly\",\"b ing\",\"Ġpl aced\",\"u nder\",\"201 5\",\"ĠM ad\",\"Ġt im\",\"os es\",\"Ġc ru\",\"ĠR ock\",\"Ġmost ly\",\"Ġneg ative\",\"Ġset ting\",\"Ġprodu ced\",\"Ġm ur\",\"Ġconnect ion\",\"ĠM er\",\"Ġdri ver\",\"Ġexecut ive\",\"Ġass ault\",\"Ġb orn\",\"ĠV er\",\"t ained\",\"Ġstruct ure\",\"Ġredu ce\",\"Ġdec ades\",\"Ġd ed\",\"u ke\",\"ĠM any\",\"idd en\",\"Ġle ague\",\"S e\",\"Ġjo in\",\"Ġdis co\",\"Ġd ie\",\"c ks\",\"act ions\",\"Ġass ess\",\"ag n\",\"Ġgo als\",\"our s\",\"I R\",\"Ġsen ior\",\"ill er\",\"m od\",\"ip ment\",\"oc ol\",\"u y\",\"ĠQ ue\",\"Ġpart ies\",\"ir gin\",\"Ġle arning\",\"it able\",\"Ġstre et\",\"Ġcamer a\",\"A pp\",\"Ġsk ills\",\"b re\",\"c ious\",\"Ġcele br\",\"ĠFr anc\",\"Ġexist ing\",\"Ġwill ing\",\"l or\",\"Ġ id\",\"ĠSp ace\",\"Ġcrit ical\",\"ĠL a\",\"ortun ately\",\"Ġser ve\",\"Ġc old\",\"Ġspec ies\",\"T S\",\"Ġanim als\",\"ĠB ay\",\"Ġold er\",\"ĠU nder\",\"est ic\",\"ĠT re\",\"Ġte acher\",\"Ġpre fer\",\"v is\",\"Ġth read\",\"ĠM att\",\"Ġmanag er\",\"ãĥ »\",\"Ġprofess ional\",\"ĠV ol\",\"Ġnot es\",\"The se\",\"ul a\",\"Ġf resh\",\"ent ed\",\"u zz\",\"ed y\",\"clus ion\",\"ĠR el\",\"Ġdoub t\",\"E O\",\"Ġopen ed\",\"ĠB it\",\"Ad vertisement\",\"Ġgu ess\",\"ĠU N\",\"Ġse qu\",\"Ġexpl ain\",\"ott en\",\"Ġatt ract\",\"ak s\",\"Ġstr ing\",\"Ġcont ext\",\"oss ible\",\"ĠRepublic ans\",\"Ġsol id\",\"Ġc ities\",\"Ġask ing\",\"Ġr andom\",\"u ps\",\"ur ies\",\"ar ant\",\"dd en\",\"g l\",\"ĠFlor ida\",\"Ġdep end\",\"ĠSc ott\",\"Ġ3 3\",\"Ġi T\",\"ic on\",\"Ġmention ed\",\"Ġ2 000\",\"Ġclaim ed\",\"Ġdefin itely\",\"ul f\",\"Ġc ore\",\"Ġopen ing\",\"ĠCon st\",\"wh ich\",\"ĠT ra\",\"A G\",\"7 2\",\"Ġbelie ved\",\"ad a\",\"Ġ4 8\",\"ĠSec urity\",\"yr ight\",\"ĠP et\",\"ĠL ou\",\"Ġhold ing\",\"======== ========\",\"Ġ ice\",\"Ġb row\",\"Ġauthor ities\",\"h ost\",\"w ord\",\"Ġsc ore\",\"ĠD iv\",\"Ġcell s\",\"Ġtrans l\",\"Ġneigh bor\",\"Ġrem ove\",\"u ct\",\"Ġdist rict\",\"ĠA ccording\",\"Ġwor se\",\"Ġconcern s\",\"Ġpresident ial\",\"Ġpolic ies\",\"ĠH all\",\"7 3\",\"Ġh us\",\"A Y\",\"Ġ200 6\",\"ĠJ ud\",\"Ġindepend ent\",\"ĠJust ice\",\"ili ar\",\"pr int\",\"igh ter\",\"Ġprotect ion\",\"z en\",\"Ġsu dden\",\"h ouse\",\"ĠJ es\",\"P R\",\"ĠIn f\",\"Ġb ul\",\"Ġ _\",\"ĠServ ice\",\"ĠP R\",\"Ġstr ategy\",\"ff ect\",\"Ġgirl s\",\"Ġmiss ing\",\"oy al\",\"ĠTe am\",\"ul ated\",\"Ġd at\",\"Ġpolit ics\",\"ab or\",\"A ccording\",\"Ġspe ll\",\"Ġg raph\",\"ort hern\",\"T C\",\"A b\",\"Ġlab or\",\"is her\",\"Ġk ick\",\"ĠiT unes\",\"Ġstep s\",\"pos es\",\"Ġsmall er\",\"E n\",\"ber t\",\"Ġro ll\",\"Ġresear chers\",\"Ġcl osed\",\"Ġtrans port\",\"Ġlaw y\",\"________ ________\",\"ĠCh icago\",\"Ġas pect\",\"Ġn one\",\"Ġmar riage\",\"9 6\",\"Ġe lements\",\"ĠF re\",\"ĠS al\",\"Ġd ram\",\"F C\",\"t op\",\"e qu\",\"Ġhe aring\",\"Ġsupport ed\",\"Ġtest ing\",\"co hol\",\"Ġmass ive\",\"Ġst ick\",\"Ġgu ard\",\"is co\",\"ph one\",\"F rom\",\"How ever\",\"Ġb order\",\"Ġcop y\",\"ograph y\",\"l ist\",\"7 1\",\"Ġown er\",\"cl ass\",\"ru it\",\"r ate\",\"ĠO nce\",\"Ġdig ital\",\"Ġt ask\",\"ER S\",\"Ġinc red\",\"t es\",\"+ +\",\"ĠFr ance\",\"Ġb reat\",\"ow l\",\"Ġiss ued\",\"ĠW estern\",\"Ġdet ect\",\"Ġpart ners\",\"Ġsh ared\",\"ĠC all\",\"Ġcan cer\",\"ac he\",\"rib e\",\"Ġexpl ained\",\"Ġhe at\",\"{ \\\"\",\"Ġinvest ment\",\"ĠB ook\",\"Ġw ood\",\"Ġtool s\",\"ĠAl though\",\"Ġbelie f\",\"Ġcris is\",\"Ġg e\",\"ĠM P\",\"Ġoper ation\",\"ty pe\",\"~ ~\",\"g a\",\"Ġcont ains\",\"ant a\",\"Ġexp ress\",\"ĠG roup\",\"ĠJ ournal\",\"k a\",\"Ġam b\",\"ĠUS A\",\"Ġfind ing\",\"Ġfund ing\",\"h ow\",\"Ġestab lished\",\"ide os\",\"Ġdeg ree\",\"Ġdanger ous\",\"ang ing\",\"Ġfre edom\",\"pp ort\",\"out hern\",\"Ġch urch\",\"Ġc atch\",\"ĠTw o\",\"Ġpres ence\",\"ĠGu ard\",\"U p\",\"Ġauthor ity\",\"ĠPro ject\",\"Ġbut ton\",\"Ġcon sequ\",\"Ġval id\",\"Ġwe ak\",\"Ġstart s\",\"Ġref erence\",\"ĠM em\",\"\\\" )\",\"U N\",\"or age\",\"ĠO pen\",\"Ġcol lection\",\"y m\",\"g ency\",\"Ġbeaut iful\",\"ro s\",\"Ġtell s\",\"Ġwa iting\",\"n el\",\"Ġprov iding\",\"ĠDemocr ats\",\"Ġd aughter\",\"Ġm aster\",\"Ġpur poses\",\"ĠJapan ese\",\"Ġequ al\",\"Ġturn s\",\"Ġdoc uments\",\"Ġwatch ing\",\"R es\",\"Ġr an\",\"201 4\",\"Ġre ject\",\"ĠKore a\",\"Ġvictim s\",\"Le vel\",\"ere nces\",\"Ġw itness\",\"Ġ3 4\",\"Ġre form\",\"com ing\",\"Ġocc up\",\"Ġc aught\",\"Ġtra ffic\",\"ad ing\",\"Ġmod els\",\"ar io\",\"Ġserv ed\",\"Ġb atter\",\"u ate\",\"ĠSecret ary\",\"Ġagre ed\",\"Ġtr uly\",\"yn am\",\"ĠR et\",\"Ġun its\",\"ĠRes earch\",\"h and\",\"az ine\",\"ĠM ike\",\"Ġvar iety\",\"ot al\",\"Ġam azing\",\"Ġconfir med\",\"Ġentire ly\",\"Ġpurch ase\",\"Ġe lement\",\"Ġc ash\",\"Ġdeter mine\",\"D e\",\"Ġc ars\",\"ĠW all\",\"â ĸ\",\"Ġview s\",\"Ġdrug s\",\"Ġdep artment\",\"ĠSt ep\",\"u it\",\"Ġ3 9\",\"as ure\",\"ĠCl ass\",\"Ġc overed\",\"ĠB ank\",\"Ġme re\",\"u ana\",\"Ġmult i\",\"Ġm ix\",\"Ġun like\",\"lev ision\",\"Ġsto pped\",\"Ġs em\",\"ĠG al\",\"ul es\",\"Ġwe l\",\"ĠJohn son\",\"l a\",\"Ġsk ill\",\"Ġbec oming\",\"ri e\",\"Ġappropri ate\",\"f e\",\"ell ow\",\"ĠPro t\",\"ul ate\",\"oc ation\",\"Ġweek end\",\"od ies\",\"Ġsit es\",\"Ġanim al\",\"ĠT im\",\"Ġsc ale\",\"Ġcharg ed\",\"Ġinst ruct\",\"ill a\",\"Ġmethod s\",\"Ġc ert\",\"Ġjud ge\",\"ĠH el\",\"Ġdoll ars\",\"Ġstand ing\",\"ĠS qu\",\"Ġdeb t\",\"l iam\",\"Ġdri ving\",\"ĠS um\",\"ĠEd ition\",\"Ġal bum\",\"and on\",\"I F\",\"ĠU k\",\"6 3\",\"ad er\",\"Ġcommer cial\",\"es h\",\"ĠGovern ment\",\"Ġdisc overed\",\"Ġout put\",\"ĠHill ary\",\"ĠCar ol\",\"Ġ200 5\",\"Ġab use\",\"anc ing\",\"Ġsw itch\",\"Ġann ual\",\"T w\",\"Ġst ated\",\"ag ement\",\"in ner\",\"Ġdem ocr\",\"Ġres idents\",\"Ġallow ing\",\"Ġfact ors\",\"od d\",\"Ġf uck\",\"em ies\",\"Ġoccur red\",\"ot i\",\"Ġn orth\",\"ĠP ublic\",\"Ġinj ury\",\"Ġins urance\",\"C L\",\"oll y\",\"ã Ģ\",\"Ġrepe ated\",\"Ġar ms\",\"ang ed\",\"Ġconst ruction\",\"Ġf le\",\"P U\",\"ic ians\",\"Ġfor ms\",\"ĠMc C\",\"ant ic\",\"Ġm ental\",\"p ire\",\"Ġequ ipment\",\"Ġf ant\",\"Ġdiscuss ion\",\"Ġregard ing\",\"k in\",\"ar p\",\"Ġch air\",\"og ue\",\"Ġpro ceed\",\"ĠI d\",\"O ur\",\"Ġmur der\",\"M an\",\"Ġ4 9\",\"as p\",\"Ġsupp ly\",\"Ġin put\",\"Ġwe alth\",\"liam ent\",\"Ġpro ced\",\"or ial\",\"ĠSt at\",\"ĠN FL\",\"hen s\",\"ĠInst itute\",\"Ġput ting\",\"ourn ament\",\"et ic\",\"Ġloc ated\",\"Ġk id\",\"er ia\",\"r un\",\"Ġpr inc\",\"Ġ !\",\"go ing\",\"ĠB et\",\"Ġcl ot\",\"Ġtell ing\",\"Ġprop osed\",\"i ot\",\"or ry\",\"Ġfund s\",\"g ment\",\"ĠL ife\",\"Ġb aby\",\"ĠB ack\",\"Ġsp oke\",\"Im age\",\"Ġear n\",\"ĠA T\",\"g u\",\"Ġex change\",\"ĠL in\",\"ov ing\",\"Ġp air\",\"M ore\",\"az on\",\"Ġarrest ed\",\"Ġkill ing\",\"c an\",\"ĠC ard\",\"y d\",\"Ġident ified\",\"Ġm obile\",\"Ġthan ks\",\"ony m\",\"ĠF orm\",\"Ġhundred s\",\"ĠCh ris\",\"ĠC at\",\"Ġtre nd\",\"h at\",\"ĠA v\",\"om an\",\"Ġelect ric\",\"ĠW il\",\"S E\",\"O f\",\"Ġrest aur\",\"ot ed\",\"Ġtr ig\",\"Ġn ine\",\"Ġb omb\",\"Wh y\",\"Â ¯\",\"Ġco verage\",\"Ġapp eal\",\"ĠRober t\",\"ĠS up\",\"Ġfin ished\",\"Ġfl ow\",\"Ġdel iver\",\"Ġcal cul\",\"Ġphot os\",\"Ġph il\",\"Ġpie ces\",\"Ġapp re\",\"k es\",\"Ġr ough\",\"D o\",\"Ġpart ner\",\"Ġconcern ed\",\"Ġ3 7\",\"ĠG en\",\"C ol\",\"ct ors\",\"Ġ= >\",\"st ate\",\"Ġsuggest ed\",\"ĠFor ce\",\"C E\",\"Ġher self\",\"ĠPl an\",\"w orks\",\"o oth\",\"ren cy\",\"Ġcor ner\",\"Ġhus band\",\"Ġintern et\",\"ĠA ut\",\"em s\",\"os en\",\"ĠAt l\",\"g en\",\"Ġbal ance\",\"6 2\",\"Ġsound s\",\"te xt\",\"Ġar r\",\"ov es\",\"Ġmill ions\",\"Ġrad io\",\"Ġsat isf\",\"ĠD am\",\"M r\",\"G o\",\"S pe\",\"Ġcomb at\",\"r ant\",\"ĠG ree\",\"Ġf uel\",\"Ġdist ance\",\"Ġtest s\",\"Ġdec re\",\"ĠE r\",\"Ġman aged\",\"D S\",\"Ġt it\",\"Ġmeas ures\",\"ĠL iber\",\"Ġatt end\",\"as hed\",\"ĠJ ose\",\"ĠN ight\",\"d it\",\"ĠN ov\",\"ĠE nd\",\"out s\",\"Ġgener ation\",\"Ġadv oc\",\"y th\",\"Ġconvers ation\",\"ĠS ky\",\"act ive\",\"ce l\",\"ri er\",\"ĠFr ank\",\"Ġg ender\",\"Ġcon cent\",\"Ġcar ried\",\"and a\",\"ĠV irgin\",\"Ġarri ved\",\"ic ide\",\"ad ed\",\"Ġfail ure\",\"Ġmin imum\",\"le ts\",\"Ġwor st\",\"Ġkeep ing\",\"Ġint ended\",\"Ġilleg al\",\"Ġsub sc\",\"Ġdetermin ed\",\"Ġtri p\",\"Y es\",\"Ġra ise\",\"Ġ ~\",\"Ġfeel s\",\"Ġpack age\",\"ĠJ o\",\"h i\",\"201 6\",\"re al\",\"Ġf ra\",\"Ġsy mb\",\"M e\",\"uck y\",\"p ret\",\"ĠK h\",\"ĠEd it\",\"ĠWe b\",\"em ic\",\"ĠCol or\",\"Ġjust ice\",\"I nt\",\"Ġfar m\",\"ck now\",\"\\\" >\",\"el ess\",\"Ġredu ced\",\"Ġ5 00\",\"x x\",\"ĠR ad\",\"ĠW ood\",\"Ġcl in\",\"Ġhy p\",\"il er\",\"ur a\",\"k ins\",\"8 5\",\"6 1\",\"ĠThe ir\",\"ĠM ary\",\"Ġs an\",\"Ġno vel\",\"ĠWh o\",\"Ġcap acity\",\"Ġimp ossible\",\"Ġpl ays\",\"Ġmin ister\",\"ij uana\",\"ic ate\",\"ĠS et\",\"Ġf ram\",\"Ġ ing\",\"Ġcommun ities\",\"ĠF BI\",\"it a\",\"Ġb on\",\"Ġstr ateg\",\"Ġinterest s\",\"l ock\",\"g ers\",\"m as\",\"ĠAN D\",\"Ġconflic t\",\"Ġrequire ments\",\"Ġs ac\",\"Ġoper ating\",\"in i\",\"rel ated\",\"Ġcomm itted\",\"Ġrelative ly\",\"Ġs outh\",\"Â¯ Â¯\",\"Ġaff ord\",\"Ġident ity\",\"Ġdec isions\",\"Ġacc used\",\"pl ace\",\"Ġvict ory\",\"o ch\",\"i at\",\"N ame\",\"C om\",\"t ion\",\"ed s\",\"Ġsee k\",\"Ġt ight\",\"ĠIm ages\",\"Ġinit i\",\"Ġhum ans\",\"Ġfam iliar\",\"Ġaud ience\",\"Ġintern al\",\"vent ure\",\"Ġs ides\",\"ĠT O\",\"Ġd im\",\"Ġcon clud\",\"Ġapp oint\",\"Ġenforce ment\",\"ĠJ im\",\"ĠAssoci ation\",\"Ġcircum st\",\"ĠCanad ian\",\"Ġjo ined\",\"Ġdiffere nces\",\"ĠL os\",\"Ġprot est\",\"Ġtw ice\",\"w in\",\"Ġgl ass\",\"ars h\",\"ĠAr my\",\"Ġexp ression\",\"Ġdec ide\",\"Ġplan ning\",\"an ia\",\"Ġhand le\",\"ĠMicro soft\",\"ĠN or\",\"Ġmax imum\",\"ĠRe v\",\"Ġse a\",\"Ġev al\",\"Ġhel ps\",\"re f\",\"Ġb ound\",\"Ġm outh\",\"Ġstand ards\",\"Ġcl im\",\"ĠC amp\",\"ĠF ox\",\"cl es\",\"Ġar my\",\"ĠTe chn\",\"ack ing\",\"x y\",\"S S\",\"Ġ4 2\",\"Ġbu g\",\"ĠUk rain\",\"ĠM ax\",\"ĠJ ones\",\"ĠSh ow\",\"l o\",\"Ġplan et\",\"Ġ7 5\",\"Ġwin ning\",\"Ġf aster\",\"Ġspe ct\",\"Ġbro ken\",\"T R\",\"Ġdef ined\",\"Ġhealth y\",\"Ġcompet ition\",\"htt ps\",\"ĠIs land\",\"ĠF e\",\"Ġannoun ce\",\"ĠC up\",\"ĠInst ead\",\"Ġcl ient\",\"Ġposs ibly\",\"se ction\",\"ock et\",\"l ook\",\"Ġfin ish\",\"Ġcre w\",\"Ġres erv\",\"Ġed itor\",\"Ġh ate\",\"Ġs ale\",\"Ġcontro vers\",\"Ġp ages\",\"w ing\",\"Ġnum er\",\"Ġopp osition\",\"Ġ200 4\",\"Ġref uge\",\"Ġfl ight\",\"Ġap art\",\"ĠL at\",\"A meric\",\"ĠAfric a\",\"Ġapplic ations\",\"ĠPal est\",\"ĠB ur\",\"Ġg ar\",\"ĠSoc ial\",\"Ġup gr\",\"Ġsh ape\",\"Ġspe aking\",\"ans ion\",\"a o\",\"ĠS n\",\"Ġwor ry\",\"ĠBrit ain\",\"P lease\",\"rou d\",\"Ġh un\",\"Ġintrodu ced\",\"Ġd iet\",\"I nd\",\"ĠSec ond\",\"Ġfun ctions\",\"ut s\",\"ĠE ach\",\"ĠJe ff\",\"Ġst ress\",\"Ġaccount s\",\"Ġgu arant\",\"ĠAn n\",\"ed ia\",\"Ġhon est\",\"Ġt ree\",\"ĠAfric an\",\"ĠB ush\",\"} ,\",\"Ġs ch\",\"ĠOn ly\",\"Ġf if\",\"ig an\",\"Ġexerc ise\",\"ĠEx p\",\"Ġscient ists\",\"Ġlegisl ation\",\"ĠW ork\",\"ĠS pr\",\"Ã Ĥ\",\"ĠH uman\",\"Ġ è\",\"Ġsur vey\",\"Ġr ich\",\"ri p\",\"Ġmain tain\",\"Ġfl o\",\"Ġleaders hip\",\"st ream\",\"ĠIslam ic\",\"Ġ 01\",\"ĠCol lege\",\"Ġmag ic\",\"ĠPr ime\",\"Ġfig ures\",\"201 7\",\"ind er\",\"x ual\",\"ĠDe ad\",\"Ġabsolute ly\",\"Ġfour th\",\"Ġpresent ed\",\"resp ond\",\"rib le\",\"Ġal cohol\",\"at o\",\"ĠD E\",\"por ary\",\"Ġgr ab\",\"Ġvar i\",\"Ġqu ant\",\"ĠPh oto\",\"Ġpl us\",\"r ick\",\"ar ks\",\"Ġaltern ative\",\"Ġp il\",\"Ġappro x\",\"th at\",\"Ġobject s\",\"ĠR o\",\"ĠAnd roid\",\"Ġsignificant ly\",\"ĠR oad\",\"k ay\",\"R ead\",\"av or\",\"Ġa cknow\",\"ĠH D\",\"ĠS ing\",\"O r\",\"ĠM ont\",\"Ġun s\",\"pro f\",\"Ġneg oti\",\"ĠAr ch\",\"ik i\",\"Ġte levision\",\"ĠJew ish\",\"Ġcomm ittee\",\"Ġmot or\",\"Ġappear ance\",\"Ġs itting\",\"Ġstri ke\",\"ĠD own\",\"com p\",\"ĠH ist\",\"Ġf old\",\"ac ement\",\"ĠLou is\",\"Ġbel ong\",\"ĠâĢ ¢\",\"Ġm ort\",\"Ġprep ared\",\"Ġ6 4\",\"ĠM aster\",\"Ġind eed\",\"ĠD en\",\"Ġre nt\",\"T A\",\"our ney\",\"ar c\",\"S u\",\"9 7\",\"Ġadv ice\",\"Ġchang ing\",\"Ġlist ed\",\"Ġlaun ched\",\"is ation\",\"ĠP eter\",\"is hes\",\"Ġl ived\",\"ĠM el\",\"ĠSup reme\",\"ĠF ederal\",\"Ġ) ;\",\"ruct ure\",\"Ġset s\",\"Ġphil os\",\"u ous\",\"ĠÂ ł\",\"Ġappl ied\",\"ĠN OT\",\"Ġhous ing\",\"ĠM ount\",\"Ġo dd\",\"Ġsu st\",\"D A\",\"ffic ient\",\"Ġ ?\",\"ol ved\",\"Ġp owers\",\"Ġth r\",\"Ġrem aining\",\"ĠW ater\",\"L C\",\"Ġca uses\",\"ãģ ®\",\"Ġman ner\",\"ad s\",\"Ġsuggest s\",\"Ġend s\",\"stand ing\",\"f ig\",\"ĠD un\",\"id th\",\"Ġg ay\",\"Ġter min\",\"ĠAngel es\",\"M S\",\"Ġscient ific\",\"Ġco al\",\"ap ers\",\"b ar\",\"ĠThom as\",\"Ġsy m\",\"ĠR un\",\"th is\",\"P C\",\"igr ants\",\"Ġmin ute\",\"ĠDist rict\",\"cell ent\",\"Ġle aves\",\"Ġcomple ted\",\"am in\",\"Ġfoc used\",\"Ġmon itor\",\"Ġveh icles\",\"M A\",\"ĠM ass\",\"ĠGr and\",\"Ġaffect ed\",\"itution al\",\"Ġconst ruct\",\"Ġfollow s\",\"Ġt on\",\"re ens\",\"Ġh omes\",\"ĠE xt\",\"ĠLe vel\",\"r ast\",\"ĠI r\",\"Ġel im\",\"Ġlarge ly\",\"ĠJ oe\",\"Ġvot es\",\"all s\",\"Ġbusiness es\",\"ĠFound ation\",\"ĠCent ral\",\"Ġy ards\",\"Ġmaterial s\",\"ul ner\",\"Ġgu ide\",\"Ġclos er\",\"um s\",\"Ġsp orts\",\"ed er\",\"J ust\",\"Ġtax es\",\"8 4\",\"ĠO ld\",\"Ġdec ade\",\"ol a\",\"Ġv ir\",\"Ġdro pped\",\"Ġdel ay\",\"it ect\",\"Ġsec ure\",\"ste in\",\"le vel\",\"Ġtre ated\",\"Ġfil ed\",\"ain e\",\"Ġv an\",\"Ġm ir\",\"Ġcol umn\",\"ict ed\",\"e per\",\"Ġro t\",\"Ġcons ult\",\"Ġent ry\",\"Ġmar ijuana\",\"ĠD ou\",\"Ġapparent ly\",\"ok ing\",\"clus ive\",\"Ġincre ases\",\"an o\",\"Ġspecific ally\",\"Ġte le\",\"ens ions\",\"Ġrelig ion\",\"ab ilities\",\"Ġfr ame\",\"ĠN ote\",\"ĠLe e\",\"Ġhelp ing\",\"Ġed ge\",\"ost on\",\"Ġorgan izations\",\"Ã ĥ\",\"ĠB oth\",\"hip s\",\"Ġbig ger\",\"Ġbo ost\",\"ĠSt and\",\"Ġro w\",\"ul s\",\"ab ase\",\"Ġr id\",\"L et\",\"are n\",\"ra ve\",\"Ġst ret\",\"P D\",\"Ġv ision\",\"Ġwe aring\",\"Ġappre ci\",\"Ġa ward\",\"ĠU se\",\"Ġfact or\",\"w ar\",\"ul ations\",\") (\",\"Ġg od\",\"Ġter rit\",\"Ġpar am\",\"ast s\",\"8 7\",\"Ġen emies\",\"ĠG ames\",\"F F\",\"Ġacc ident\",\"W ell\",\"ĠMart in\",\"T ER\",\"Ġat h\",\"ĠHe ll\",\"Ġfor g\",\"Ġve ter\",\"ĠMed ic\",\"f ree\",\"Ġst ars\",\"Ġexp ensive\",\"Ġac ad\",\"ra wn\",\"ĠW he\",\"Ġl ock\",\"Ġform at\",\"Ġsold iers\",\"s m\",\"Ġag ent\",\"Ġrespons ibility\",\"or a\",\"ĠS cience\",\"Ġrap id\",\"Ġt ough\",\"ĠJes us\",\"Ġbelie ves\",\"M L\",\"Ġwe ar\",\"le te\",\"Ãĥ ÃĤ\",\"ĠD ri\",\"Ġcomm ission\",\"ĠB ob\",\"O h\",\"ap ed\",\"Ġwar m\",\"ÃĥÃĤ ÃĥÃĤ\",\"Ġ200 3\",\"ort ion\",\"Ġhas n\",\"ust er\",\"Ġun ivers\",\"ĠI ll\",\"Ġk ing\",\"olog ies\",\"9 4\",\"ĠT em\",\"ĠM os\",\"Ġpat ient\",\"ĠMex ico\",\"ce an\",\"ĠDe ath\",\"ĠSand ers\",\"y ou\",\"ĠC ast\",\"ĠComp any\",\"pt y\",\"Ġhappen ing\",\"F P\",\"ĠB attle\",\"Ġb ought\",\"A m\",\"M od\",\"U s\",\"ut ers\",\"ĠC re\",\"ĠTh ose\",\"Ġ4 4\",\"is er\",\"Ġs oul\",\"ĠT op\",\"ĠHar ry\",\"ĠA w\",\"Ġse at\",\"ff ee\",\"Ġrev olution\",\"Ġ( \\\"\",\"ĠD uring\",\"et te\",\"Ġr ing\",\"Ġoff ensive\",\"Ġreturn s\",\"Ġv ideos\",\"Ġdis cl\",\"Ġfam ous\",\"en ced\",\"ĠS ign\",\"ĠR iver\",\"Ġ3 00\",\"P M\",\"ĠB us\",\"ĠC H\",\"Ġcandid ates\",\"ard en\",\"Ġpercent age\",\"Ġvis ual\",\"Ġthan k\",\"Ġtrou ble\",\"ner gy\",\"Ġ200 1\",\"Ġpro ve\",\"ash ion\",\"Ġen h\",\"ĠL ong\",\"U M\",\"Ġconnect ed\",\"Ġposs ibility\",\"O ver\",\"Ġexper t\",\"Ġl ibrary\",\"art s\",\"ĠDirect or\",\"Ġfell ow\",\"9 2\",\"ir ty\",\"Ġd ry\",\"Ġsign s\",\"ĠL ove\",\"Ġqu iet\",\"f oot\",\"Ġp ure\",\"ĠH un\",\"Ġf illed\",\"ph as\",\"ĠE lect\",\"end ment\",\"ĠEx pl\",\"Ġun able\",\"n s\",\"m o\",\"Ġv ast\",\"ob e\",\"Ġident ify\",\"app ing\",\"ĠCarol ina\",\"g ress\",\"Ġpro te\",\"Ġf ish\",\"Ġcircumst ances\",\"raz y\",\"ĠPh ot\",\"Ġb odies\",\"ĠM ur\",\"Ġdevelop ing\",\"ĠA R\",\"Ġexperien ced\",\"Ġsubst ant\",\"ĠBo ard\",\"es ome\",\"Ġdom estic\",\"Ġcomb ined\",\"ĠP ut\",\"Ġchem ical\",\"ĠCh ild\",\"Ġpo ol\",\"ĠC y\",\"Ġe gg\",\"c ons\",\"st ers\",\"Ġh urt\",\"Ġmark ets\",\"Ġconserv ative\",\"Ġsupp orters\",\"Ġag encies\",\"id el\",\"O b\",\"ur b\",\"Ġ4 3\",\"ĠDef ense\",\"y e\",\"ĠA p\",\"du le\",\"Ġtemper ature\",\"Ġconduct ed\",\"ĠCh ief\",\"Ġpull ed\",\"Ġf ol\",\"L ast\",\"ont o\",\"os is\",\"V ER\",\"D es\",\"ĠP an\",\"F irst\",\"Ġadv ance\",\"Ġlic ense\",\"r ors\",\"ĠJ on\",\"Ġimag ine\",\"Ġhe ll\",\"Ġf ixed\",\"Ġinc or\",\"os ite\",\"ĠL og\",\"ick en\",\"] :\",\"Ġsurpr ise\",\"h ab\",\"Ġc raft\",\"ol t\",\"ĠJ ul\",\"Ġd ial\",\"Ġrele vant\",\"Ġent ered\",\"Ġlead s\",\"ĠA D\",\"ĠCle an\",\"Ġpict ures\",\"ess or\",\"Ġal t\",\"Ġpay ing\",\"P er\",\"ĠMark et\",\"Ġupd ates\",\"am ily\",\"ĠT ype\",\"ĠH ome\",\"Ġ5 5\",\"semb ly\",\"rom e\",\"8 3\",\"Ġgreat est\",\"Ġhe ight\",\"Ġhe av\",\"ain ts\",\"Ġlist en\",\"as er\",\"ĠS H\",\"Ġcap able\",\"ac le\",\"Ġpers pect\",\"in ating\",\"Ġoff ering\",\"ry pt\",\"ĠDe velop\",\"ab in\",\"r c\",\"Ġbr ight\",\"al ty\",\"ar row\",\"Ġsupp l\",\"ind ing\",\"ack ed\",\"gy pt\",\"ĠAn other\",\"p g\",\"ĠVirgin ia\",\"ĠL u\",\"Ġpl anned\",\"Ġp it\",\"Ġswe et\",\"T ype\",\"ĠD i\",\"Ġtyp ically\",\"ĠFranc isco\",\"Ġpro spect\",\"ĠD an\",\"Ġte en\",\"re es\",\"Ġsc hed\",\"Ġh ol\",\"Ġsc r\",\"Ġlot s\",\"l ife\",\"Ġnews p\",\"Ġfor get\",\"ĠN one\",\"ĠM iddle\",\"ĠR yan\",\"ed d\",\"Ġse vere\",\"Ġsu it\",\"ll er\",\"9 3\",\"Ġcor respond\",\"Ġexpl os\",\"u ations\",\"Ġfl ag\",\"g ame\",\"r id\",\"Ġpr in\",\"ĠD ata\",\"Ġde ploy\",\"ĠEn ter\",\"su it\",\"gh an\",\"ĠM en\",\"Ġthough ts\",\"Ġmat ters\",\"Ġad apt\",\"ĠA ri\",\"Ġf ill\",\"Ġfor th\",\"Ġs am\",\"Ġ4 1\",\"Ġpay ment\",\"ĠH or\",\"Ġsp ring\",\"du c\",\"Ġl osing\",\"Ġbring ing\",\"F O\",\"al a\",\"Ġdist ribution\",\"he red\",\"b our\",\"ĠIsrael i\",\"om a\",\"Ġcomb ination\",\"Ġpl enty\",\"V E\",\"C an\",\"ĠH aw\",\"Ġper man\",\"ĠSpe cial\",\"Ġto w\",\"Ġsee king\",\"Ġexam ples\",\"Ġclass es\",\"c r\",\"Ġbe er\",\"Ġmov es\",\"ĠI P\",\"ĠK n\",\"Ġpan el\",\"E ven\",\"Ġproper ly\",\"Ġr is\",\"Ġpl ug\",\"Ġestim ated\",\"E very\",\"Ġdef ensive\",\"ag raph\",\"Ġpre gn\",\"Ġinst it\",\"ĠV ict\",\"Ġvol ume\",\"Ġpos itions\",\"Ġl inks\",\"ĠPro gram\",\"ĠWe ek\",\"ag ues\",\"Ġtrans form\",\"k er\",\"ĠC EO\",\"Ġc as\",\"Ġopp onent\",\"Ġtwe et\",\"ĠC ode\",\"Ġsh op\",\"Ġf ly\",\"Ġtal ks\",\"Ġb ag\",\"Ph one\",\"Ġa id\",\"Ġpl ants\",\"Ġ6 5\",\"Ġatt orney\",\"ar ters\",\"qu est\",\"ĠMag ic\",\"Ġbeg ins\",\"Ġmy ster\",\"Ġenvironment al\",\"Ġst orage\",\"N N\",\"Ġm arg\",\"Ġs ke\",\"Ġmet al\",\"ell y\",\"Ġord ered\",\"Ġrem ained\",\"Ġl oved\",\"Ġprom pt\",\"Ġupd ated\",\"Ġexper ts\",\"Ġwalk ing\",\"Ġan cient\",\"Ġperform ed\",\"AT E\",\"Ġne ither\",\"i ency\",\"Ġmanufact ure\",\"ĠP ak\",\"Ġselect ed\",\"Ġm ine\",\"Ġult imately\",\"Ġexpl an\",\"Ġlab el\",\"ĠServ ices\",\"ribut ed\",\"Tr ump\",\"Ġsy n\",\"ĠU lt\",\"S C\",\"Ġme at\",\"Ġg iant\",\"ĠW ars\",\"ĠO N\",\"Ġad m\",\"Ġinter pret\",\"Ġeven ing\",\"Ġev il\",\"ĠB oston\",\"ĠW ild\",\"Ġ Ã\",\"ĠBit coin\",\"ĠAm azon\",\"D r\",\"ĠIn formation\",\"Ġobvious ly\",\"Ġadv anced\",\"Ph oto\",\"ol ar\",\"Ġwe ather\",\"Ġsymb ol\",\"Ġso le\",\"Ġpot entially\",\"ost er\",\"Ġorig inally\",\"m un\",\"3 00\",\"az e\",\"ess ions\",\"Ġde ck\",\"Ġst ood\",\"Ġyou th\",\"ĠB ern\",\"R ep\",\"ĠT est\",\"Ġbas ically\",\"ot ic\",\"Ġinvol ve\",\"ol it\",\"ly n\",\"S ee\",\"Ġair craft\",\"Ġconf irm\",\"E W\",\"Ġmess ages\",\"ĠRich ard\",\"Ġk it\",\"Ġpro hib\",\"Ġv ulner\",\"is ters\",\"Ġexist ence\",\"Ġturn ing\",\"ĠS P\",\"Ġdes ire\",\"Ġfl at\",\"Ġm ent\",\"se ason\",\"ang es\",\"Ġneighbor hood\",\"ĠL ake\",\"AT ION\",\"Ġpoint ed\",\"b ur\",\"Ġinn ov\",\"uc ks\",\"U L\",\"Ġprofess or\",\"Ġexp ressed\",\"A B\",\"ic ious\",\"Ġ200 2\",\"ĠDe v\",\"Ġs ession\",\"Ġb are\",\"s en\",\"Ġdis s\",\"ĠC ath\",\"ĠP ass\",\"ĠP oint\",\"Ġdo ctor\",\"or row\",\"ail ed\",\"ĠR ub\",\"ĠD C\",\"ĠChar l\",\"p erson\",\"Ġwrit er\",\"igh ters\",\"ure au\",\"Ġob lig\",\"Ġrecord ed\",\"Ġbro ke\",\"Ġord ers\",\"il ty\",\"Ġmot ion\",\"in ity\",\"l aw\",\"ad ium\",\"Ġimm igration\",\"Ġcontr ast\",\"Ġb att\",\"Ġex cellent\",\"Ġtechn ical\",\"am i\",\"Ġt un\",\"Ġcl oud\",\"ĠY ear\",\"ge on\",\"Ġcre ation\",\"Ġstr ange\",\"Ġa uth\",\"Ġfor t\",\"b orn\",\"Ġext ent\",\"ĠT oday\",\"ĠCl ub\",\"Ġr ain\",\"Ġs ample\",\"Ġaccept ed\",\"Ġt act\",\"Ġf ired\",\"ĠS on\",\"Ġstand s\",\"Ġb oot\",\"Ġ4 7\",\"Ġstat ements\",\"Ġvers ions\",\"Ġse lling\",\"ound ed\",\"Ġ199 0\",\"Ġwere n\",\"ĠW atch\",\"Ġexper iment\",\"P ost\",\"Ġret ail\",\"ul ed\",\"In st\",\"un te\",\"ãĥ ¼\",\"Ġdep art\",\"Ġb ond\",\"i very\",\"om pl\",\"Ġre action\",\"ĠSyri an\",\"ĠP ac\",\"app ed\",\"ani el\",\"D P\",\"Ġres olution\",\"Ġre act\",\"Ġappro ved\",\"on om\",\"m ond\",\"ĠO ffic\",\"-- -\",\"Ġrepl ace\",\"Ġt ack\",\"Ġsp ort\",\"Ġch ain\",\"Ġemer gency\",\"r ad\",\"ĠPalest in\",\"Ġ4 6\",\"Ġautom atically\",\"Ġrout e\",\"Ġp al\",\"Ġb anks\",\"ĠPar is\",\"ĠMed ia\",\"ro ad\",\"ic ing\",\"i xt\",\"ist ed\",\"Ġg rew\",\"Ġco ord\",\"ĠW here\",\"om in\",\"Ġsub s\",\"ï¿½ ï¿½\",\"ĠÂ ±\",\"Ġcorpor ate\",\"Ġse lection\",\"n oon\",\"ĠRep ort\",\"c s\",\"clud ing\",\"ord ers\",\"anc he\",\"ĠIt s\",\"Ġslow ly\",\"ĠE gypt\",\"ĠA cc\",\"Ġcol le\",\"iqu es\",\"E X\",\"Ġattempt s\",\"ur l\",\"ĠC ross\",\"Ġfind ings\",\"ĠS C\",\"ĠO R\",\"Ġind ex\",\"ens ity\",\"ĠW ay\",\"ĠL and\",\"Ġsh ock\",\"d is\",\"Ġd ynam\",\"Ġc art\",\"m osp\",\"S ince\",\"i est\",\"ĠB oy\",\"Ġst orm\",\"ĠCont in\",\"201 3\",\"he w\",\"il it\",\"Ġess ential\",\"iqu id\",\"O ther\",\"ive red\",\"Ġreason able\",\"A ct\",\"Ġsub sequ\",\"ĠP ack\",\"ĠF ort\",\"Ġconsider ing\",\"Ġun iversity\",\"l og\",\"Ġmar ried\",\"Ġill ust\",\"ĠTr ue\",\"£ ı\",\"Ġnumer ous\",\"rast ructure\",\"Ġserious ly\",\"Ġrefer red\",\"u a\",\"Ġconsist ent\",\"on na\",\"ĠRe al\",\"ru ption\",\"ci ples\",\"Ġfact s\",\"9 1\",\"ot es\",\"er g\",\"The n\",\"Ġacc ompl\",\"N ote\",\"Ġre venue\",\"Ġpass ing\",\"Ġm al\",\"e en\",\"ĠY et\",\"Ġg ather\",\"ter day\",\"ew ork\",\"ĠA uthor\",\"P e\",\"Ġopt im\",\"Ġr ub\",\"Ġè £ı\",\"Ġun known\",\"st one\",\"Ġun ion\",\"ol ve\",\"Ġopportun ities\",\"Ġbrow ser\",\"ĠW al\",\"ĠC ost\",\"Ġreport ing\",\"st s\",\"p et\",\"Ġs and\",\"Ġsudden ly\",\"Ġsurpr ising\",\"ĠV R\",\"Ġsomew hat\",\"ĠB as\",\"ult ure\",\"iz z\",\"ĠC D\",\"Ġchalleng es\",\"Ġsett ings\",\"Ġexperien ces\",\"ĠF ull\",\"Ġcan n\",\"Ġrece iving\",\"ES T\",\"Ġj oint\",\"Ġcult ural\",\"Ġa st\",\"8 2\",\"as tern\",\"ce ived\",\"ĠC ru\",\"Ġb ull\",\"p ired\",\"am m\",\"Ġfac ing\",\"p ower\",\"Ġb oss\",\"ĠH ol\",\"Ġinst r\",\"Ġincreasing ly\",\"Ġsh ift\",\"Ġstre ets\",\"ĠWilliam s\",\"ab b\",\"Ġl ie\",\"Ġl augh\",\"ĠC a\",\"P L\",\"Ġadult s\",\"Ġcustom er\",\"Ġob tained\",\"Ġsupport ing\",\"ht ml\",\"f ire\",\"Ġdetail ed\",\"Ġpick ed\",\"ĠR ight\",\"ld er\",\"E E\",\"st ood\",\"ĠK im\",\"Ġw ire\",\"Ġs ight\",\"Ġdevelop ers\",\"Ġpers ons\",\"Ġs ad\",\"Ġc up\",\"Ġwar ning\",\"Ġboy s\",\"l ong\",\"Ġb ird\",\"f o\",\"Ġw al\",\"Ġobserv ed\",\"Ġz one\",\"iven ess\",\"Ġch annel\",\"c ript\",\"Ġref used\",\"ĠAg ain\",\"Ġsu c\",\"Ġspokes man\",\"ĠRe f\",\"r ite\",\"ou ston\",\"ãĥ ³\",\"ĠS her\",\"Ġact s\",\"ĠN ame\",\"Ġstrugg le\",\"ar ry\",\"omet imes\",\"Ġdisc rim\",\"H T\",\"Ġcateg ory\",\"Ġreal ize\",\"Ġemploy ee\",\"ĠAf ghan\",\"en ger\",\"Ġgun s\",\"ĠSte ve\",\"ĠM ot\",\"ĠO l\",\"ok ed\",\"Ġth ick\",\"Ġfair ly\",\"ill y\",\"Ġsur ve\",\"ĠM at\",\"we ight\",\"â Ķ\",\"Ġtro ops\",\"Ġag ents\",\"Ġbatter y\",\"Ġmot iv\",\"Ã ¡\",\"S ec\",\"d en\",\"o very\",\"L S\",\"Ġfl u\",\"Ġconf ident\",\"ĠO per\",\"Ġem pty\",\"Ġp hen\",\"Ġse ctor\",\"Ġexc ited\",\"Ġrem ote\",\"ap h\",\"o en\",\"Ġdestroy ed\",\"Ġmor al\",\"ĠH P\",\"ĠR on\",\"Ġd ress\",\"ĠB at\",\"Ġl it\",\"ĠM S\",\"Ġa f\",\"H L\",\"r um\",\"is ms\",\"Ġshould n\",\"Ġsym pt\",\"ĠTor onto\",\"het ic\",\"Ġcar bon\",\"Ġinstall ed\",\"Ġviol ent\",\"Ġsol ar\",\"j a\",\"Ġpract ices\",\"Ġr ide\",\"ĠP enn\",\"Ġimpro ved\",\"Ġaud io\",\"Ġbehav i\",\"ĠP S\",\"Ġe ating\",\"D ata\",\"ĠRe view\",\"p ass\",\"cl aim\",\"u ated\",\"ang ers\",\"c hen\",\"Ġproper ties\",\"Ġany where\",\"An other\",\"Ġbl ow\",\"ĠJack son\",\"Ġp roud\",\"Ġplan e\",\"l ines\",\"Ġsqu are\",\"Ġpro of\",\"ans as\",\"Ġtalk ed\",\"m akers\",\"Ġs ister\",\"Ġhold s\",\"Ġres ident\",\"Ġ= =\",\"Ġresist ance\",\"Ġspl it\",\"Ġpro secut\",\"Ġconf idence\",\"res ents\",\"Ġcut s\",\"Ġexcept ion\",\"Ġz ero\",\"Get ty\",\"Ġcop yright\",\"Ġtot ally\",\"orm al\",\"ific ations\",\"ĠAustral ian\",\"Ġs ick\",\"Ġ1 50\",\"Ġhouse hold\",\"Ġfe es\",\"Ġdri vers\",\"og en\",\"ĠN Y\",\"Ġnecess arily\",\"Ġregul ations\",\"ear ing\",\"s l\",\"Ġperspect ive\",\"c are\",\"ic ial\",\"H is\",\"Ġesc ape\",\"Ġsurpr ised\",\"ĠV an\",\"ur rent\",\"Ġv ac\",\"8 1\",\"ĠTh us\",\"Ġem phas\",\"ĠCh ampions\",\"ĠI ce\",\"Ġn arr\",\"Ġhead s\",\"Ġca using\",\"b el\",\"f ortunately\",\"ĠM a\",\"Ġtarg ets\",\"ci pl\",\"Ġafter noon\",\"Ġadd s\",\"ĠMay be\",\"ĠF our\",\"ess ed\",\"ple te\",\"Ġus ual\",\"ch o\",\"ing u\",\"Ġwith d\",\"ĠE nergy\",\"ĠE conom\",\"O O\",\"Ġart icles\",\"Ġinj ured\",\"Ġman age\",\"Ġexpl ains\",\"Ġdi agn\",\"R ec\",\"at ures\",\"Ġlink ed\",\"Ġdiscuss ed\",\"Ġexpl o\",\"Ġocc asion\",\"ath an\",\"Ġopp osite\",\"Ġfac es\",\"Ġden ied\",\"ĠK night\",\"Ġn ut\",\"Ġapprox imately\",\"Ġdisapp oint\",\"onym ous\",\"ĠB est\",\"ĠL o\",\"ĠH y\",\"ĠA ff\",\"Ġvot ing\",\"an while\",\"ĠII I\",\"Ġinstit utions\",\"ag ram\",\"ĠD aily\",\"Ġdr ag\",\"Ġnear by\",\"Ġgu ilty\",\"Ġcon ver\",\"P re\",\"s hip\",\"Ġre ward\",\"Ġphilos oph\",\"ĠS S\",\"u gh\",\"Ġapp s\",\"f riend\",\"Ġu pper\",\"Ġad vert\",\"Ġs now\",\"Ġfr ust\",\"Ġour selves\",\"F r\",\"ĠD ie\",\"amp ion\",\"Ġdis miss\",\"Ġc ere\",\"Ġsign al\",\"f rom\",\"Ġ ).\",\"Ġ5 2\",\"Ġcr imes\",\"it ors\",\"est ival\",\"use um\",\"Ġcoun cil\",\"ĠS aud\",\"M ay\",\"ĠG un\",\"ic ian\",\"et her\",\"Ġsu fficient\",\"ĠH en\",\"so le\",\"Ġhistor ical\",\"ĠF ar\",\"ĠT urn\",\"Ġp in\",\"Ġsuc ceed\",\"m at\",\"ly mp\",\"Ġtrad ition\",\"ĠO k\",\"Ġc ro\",\"Ġdesc ription\",\"al le\",\"Ġsk y\",\"T e\",\"Ġwide ly\",\"Ġw ave\",\"Ġdefin ition\",\"ĠJew s\",\"Ġcy cle\",\"Ġref ere\",\"Ġbr ings\",\"us al\",\"Ġal ive\",\"Ġfrequ ently\",\"Ġint ention\",\"ĠCont rol\",\"l v\",\"y stem\",\"Ġpriv acy\",\"g ent\",\"ren ce\",\"ĠQu est\",\"ĠChrist mas\",\"Ġr ail\",\"Ġco oper\",\"Ġtest ed\",\"ĠC apt\",\"as ks\",\"Ġcomfort able\",\"Ġdel ivered\",\"sc ape\",\"Ġdep th\",\"ĠG OP\",\"Ġwrit es\",\"Ġass ets\",\"Ġsa v\",\"im ents\",\"Ġtrans ition\",\"Ġart ist\",\"ĠL ook\",\"Ġl ob\",\"Ġcomp onents\",\"ar ity\",\"Ġwalk ed\",\"Ġro ot\",\"Ġparticip ants\",\"Ġnot iced\",\"Ġres c\",\"Ġn av\",\"ĠAd minist\",\"d a\",\"ut ral\",\"pl ate\",\"Ġimport ance\",\"Ġass ert\",\"ious ly\",\"c ription\",\"Ġinj uries\",\"ĠChe ck\",\"Ġregist ered\",\"Ġint ent\",\"Ġmiss ed\",\"ograph ic\",\"Ġsent ence\",\"oun ter\",\"Ġassist ance\",\"ev in\",\"Ġdat abase\",\"Ġbuild ings\",\"Ġclass ic\",\"Ġth inks\",\"ĠOh io\",\"P r\",\"ug g\",\"Ġfe e\",\"p an\",\"Ġeffect ively\",\"Ġfac ility\",\"Ġbe ar\",\"Ġch apter\",\"Ġdog s\",\"ĠCol umb\",\"Ġl atter\",\"it ial\",\"Ġad mitted\",\"T V\",\"ĠGe org\",\"Ġpost s\",\"\\\\ \\\\\",\"Ġlawy er\",\"Ġequ ival\",\"Ġm and\",\"Ġcontro lled\",\"ĠW alk\",\"ĠAnd rew\",\"Ġmen u\",\"am ental\",\"Ġprotect ed\",\"v a\",\"Ġadminist r\",\"or al\",\"Ġre in\",\"ĠS ar\",\"Ġamount s\",\"Ġn ative\",\"ĠM oon\",\"Ġrep resents\",\"Ġab andon\",\"Ġcarry ing\",\"Ġt ank\",\"m ary\",\"Ġdecl ared\",\"T ube\",\"Ġh at\",\"Ġpun ish\",\"el lect\",\"m es\",\"Ġun iverse\",\"ĠR od\",\"ph y\",\"Ġinf rastructure\",\"Ġ5 1\",\"Ġopp osed\",\"ow nt\",\"c a\",\"ĠM ake\",\"Ġhard ware\",\"Ġco ffee\",\"R el\",\"b al\",\"w orld\",\"ĠS af\",\"ĠSe a\",\"in als\",\"Ġown ed\",\"Ġh all\",\"ers ion\",\"Ġdescrib e\",\"ĠP ot\",\"Ġport ion\",\"Ġat mosp\",\"Ġgovern ments\",\"Ġdep ending\",\"Ġoff ense\",\"Ġtr ick\",\"aw a\",\"ĠL ine\",\"ĠV is\",\"ĠH ard\",\"ĠOr ig\",\"ĠCl ick\",\"Ġdes k\",\"ĠVal ley\",\"ĠS ov\",\"Ġmov ies\",\"Ġrem ark\",\"Ġm ail\",\"Ġcons cious\",\"Ġrul ing\",\"ĠR ights\",\"Ġmed ic\",\"he nt\",\"ĠW omen\",\"> <\",\"Ġrepl aced\",\"ĠP rem\",\"ĠTh anks\",\"Ġre new\",\"ĠB all\",\"if orm\",\"Ġsh ots\",\"C omm\",\"Ġar med\",\"Ġconst ant\",\"Ġt aste\",\"Ġreal ized\",\"Ġbu ff\",\"Ġm o\",\"Ġeffic ient\",\"M ost\",\"or ation\",\"if ies\",\"Ġcommun ication\",\"Ġfl ood\",\"Ġconsequ ences\",\"Ġany way\",\"ig g\",\"ĠG M\",\"ĠTh ank\",\"Ġ iron\",\"Ġev olution\",\"ĠC op\",\"tw itter\",\"Ġ9 5\",\"Ġrelationship s\",\"ad el\",\"ĠYou ng\",\"Ġpropos al\",\"ay ers\",\"uild ing\",\"ĠH ot\",\"OR E\",\"c os\",\"Ġcoll abor\",\"P G\",\"ax y\",\"Ġknow ing\",\"Ġsupport s\",\"ow ed\",\"Ġcontrol s\",\"Ġmere ly\",\"um er\",\"Ġath let\",\"Ġf ashion\",\"p ath\",\"Ġg ift\",\"Ġer a\",\"AN D\",\"Ġkind s\",\"ĠKore an\",\"Ġleg it\",\"ul ous\",\"Ġess entially\",\"Ġthe rap\",\"n ic\",\"Ġsuff ered\",\"Ġh ur\",\"Ġprom ise\",\"Ġex cess\",\"Ġover w\",\"Ġpr ime\",\"ĠH ouston\",\"er ry\",\"ĠM s\",\"R S\",\"201 2\",\"Ġst ores\",\"ĠO lymp\",\"Ġj ourney\",\"Al though\",\"S ub\",\"ĠE duc\",\"ĠCh apter\",\"Ġrequest s\",\"Ġconsum ers\",\"Ġt iny\",\"Ġis ol\",\"ĠF air\",\"b a\",\"ĠY OU\",\"Ġcr ash\",\"ce ler\",\"Ġemot ional\",\"Ġgood s\",\"Ġelect ed\",\"Ġmod er\",\"ĠLin ux\",\"Ġbl ocks\",\"Ġis land\",\"ĠSoc iety\",\"Ġelect ions\",\"Ġbroad cast\",\"Ġche ap\",\"Ġn ations\",\"Ġse asons\",\"4 00\",\"Ġwas te\",\"ĠS at\",\"Ġfield s\",\"em ploy\",\"Ġprof ile\",\"Ġauth ors\",\"AL L\",\"ĠG ra\",\"w est\",\"ĠT y\",\"Ġdeath s\",\"Ġv acc\",\"Ġfor med\",\"Ġd u\",\"Ġon going\",\"ĠMuslim s\",\"el f\",\"ig ure\",\"Ġass ume\",\"ĠUkrain e\",\"w ater\",\"Ġco ast\",\"Ġvot ed\",\"g or\",\"ĠA S\",\"ĠMich igan\",\"az a\",\"ĠAr m\",\"i ro\",\"Ġf lex\",\"as ters\",\"' '\",\"Ġwel come\",\"ar l\",\"Ġloc ations\",\"ig ation\",\"ĠF il\",\"Ġbu ying\",\"Ġarch itect\",\"Ġhard er\",\"ĠC ub\",\"Ġinter face\",\"Ġrestaur ant\",\"Ġdisco ver\",\"Ġex ceed\",\"Ġfav our\",\"ger y\",\"Ġd uty\",\"Ġp itch\",\"ad or\",\"ĠM ach\",\"b oy\",\"Ġrespond ed\",\"Ġext ended\",\"her s\",\"M any\",\"ra id\",\"if er\",\"ĠIn s\",\"S er\",\"Ġmed ium\",\"s he\",\"ĠS ports\",\"Ġmag azine\",\"ut ation\",\"Ġlim its\",\"ĠG all\",\"Ġex ternal\",\"raz il\",\"Ġyoung er\",\"t le\",\"Ġrem ind\",\"ĠC ON\",\"Ġimmedi ate\",\"Ġh idden\",\"Ġvol unte\",\"Ġsim pl\",\"od cast\",\"Ġph ase\",\"d r\",\"Ġpl ot\",\"Ġexp osure\",\"R I\",\"og rap\",\"v in\",\"an ish\",\"ĠAc ad\",\"ĠEng ine\",\"Ġexp ansion\",\"ĠP ay\",\"Y our\",\"Ġpus hed\",\"ĠE ll\",\"ĠHe ad\",\"Ġmarket ing\",\"ĠA C\",\"k et\",\"Ġh its\",\"Ġg ro\",\"ĠA ge\",\"ĠSc ot\",\"] [\",\"Ġst im\",\"Ġi Phone\",\"Ī Ĵ\",\"Ġn arrow\",\"ĠGet ty\",\"ĠTur key\",\"Ġperfect ly\",\"Ġen able\",\"ut ch\",\"Ġprec ise\",\"Ġreg ime\",\"Ġsh if\",\"Ġcomp ens\",\"g un\",\"d iv\",\"Ġch osen\",\"ĠK en\",\"An y\",\"Ġtre es\",\"Ġrecomm ended\",\"ĠR en\",\"u able\",\"ĠH T\",\"F ollow\",\"E G\",\"ĠH and\",\"ĠK enn\",\"Ġarg uments\",\"Ġex ists\",\"Ġb ike\",\"ĠCons erv\",\"Ġbre aking\",\"ĠG ar\",\"Ġc razy\",\"Ġvirt ual\",\"ay lor\",\"ix el\",\"Ġ19 80\",\"Ġper mission\",\"ĠSer ies\",\"Ġconsum er\",\"Ġclose ly\",\"c alled\",\"Ġ5 4\",\"Ġhop es\",\"Ġar ray\",\"ĠW in\",\"ĠLab our\",\"Ġsp ons\",\"ĠI re\",\"Ġp ow\",\"Ġread ers\",\"Ġemploy ment\",\"Ġcreat ure\",\"Ġresult ing\",\"Ġaccur ate\",\"Ġmom ents\",\"Ġarg ued\",\"Ġp ed\",\"D uring\",\"Ġ5 3\",\"ĠT al\",\"Ġs ought\",\"Ġsuff ering\",\"Ġ icon\",\"le e\",\"Ġ( $\",\"al ian\",\"Â °\",\"Ġp ra\",\"Ġbon us\",\"( \\\"\",\"k o\",\"Ġact ing\",\"D E\",\"f all\",\"Ġcompar ison\",\"Ġsm ooth\",\"ĠN AS\",\"u pp\",\"ĠJose ph\",\"ep ing\",\"ĠT ake\",\"ĠM id\",\"Ġs ending\",\"f ast\",\"ĠF all\",\"Ġdeal ing\",\"us er\",\"ĠOr gan\",\"C o\",\"Ġatt ached\",\"Ġse es\",\"% .\",\"Ġtyp ical\",\"AR T\",\"Ġfind s\",\"ĠAs ia\",\"um in\",\"ĠC ore\",\"ĠE nt\",\"in ent\",\"u ce\",\"ĠBl ood\",\"ĠN ever\",\"Ġem ails\",\"Ġhigh light\",\"Ġconf ront\",\"at us\",\"ut ed\",\"Ġun us\",\"Ġtop ic\",\"ĠAd am\",\"Ġb le\",\"at i\",\"Ġunder stood\",\"S et\",\"st ruct\",\"T P\",\"Ġm ob\",\"a a\",\"ĠSt art\",\"pect ed\",\"se ll\",\"Ġded icated\",\"ĠC A\",\"u an\",\"Ġsong s\",\"esc ription\",\"Ġte ch\",\"Ġr ape\",\"Ġas ide\",\"Ġgr ant\",\"Ġ5 6\",\"s ub\",\"Ġarg ue\",\"Ġcont aining\",\"Ġsche dule\",\"Ġliber al\",\"Ġpublic ly\",\"Ġheav ily\",\"ĠU t\",\"in er\",\"ĠS ection\",\"ĠC are\",\"we et\",\"l s\",\"D is\",\"âĶ Ģ\",\"ĠF ollow\",\"B ack\",\"ĠI T\",\"Ġb es\",\"j i\",\"ĠH it\",\"est ed\",\"Ġevery body\",\"ĠSw ed\",\"Ġfem in\",\"Ġfac ilities\",\"Ġcon ven\",\"C omp\",\"ĠO S\",\"c ore\",\"Ġan x\",\"Ġdiv ision\",\"ĠC am\",\"ĠSt an\",\"m ates\",\"Ġexpl ore\",\"pl om\",\"Ġsh ares\",\"pl oad\",\"an es\",\"Ġide al\",\"et ers\",\"ĠB ase\",\"Ġpl astic\",\"Ġdist inct\",\"ĠNet work\",\"ĠSe attle\",\"Ġtrad ing\",\"ens us\",\"int end\",\"Ġex hib\",\"Ġinit ially\",\"ĠF ood\",\"Ġthous and\",\"ĠBus iness\",\"act er\",\"Ġpar agraph\",\"Ġrough ly\",\"Ġw ww\",\"Ġcreat ive\",\"ĠCon f\",\"Ġconsum ption\",\"Ġfil ms\",\"ag an\",\"Ġob tain\",\"Ġt all\",\"Ġt or\",\"Ġacknow led\",\"Ġg rown\",\"al o\",\"K E\",\"Ġ4 00\",\"end ers\",\"t aining\",\"U G\",\"Ġsu icide\",\"Ġwat ched\",\"ĠL ist\",\"al i\",\"re hens\",\"Ġsurround ing\",\"Ġp ip\",\"Ġf lying\",\"ĠJ ava\",\"ord an\",\"Ġserv ing\",\"in ations\",\"p ost\",\"Ġsh o\",\"A v\",\"Ġj ail\",\"z y\",\"Ġ199 9\",\"Ġ< /\",\"Ġliter ally\",\"ĠS ir\",\"Ġexp osed\",\"Ġl ies\",\"st ar\",\"Ġb at\",\"Ġear ned\",\"ĠD ig\",\"Ġspec ified\",\"ĠSe ason\",\"Ġdeg rees\",\"Don ald\",\"Ġcent re\",\"Ġsh aring\",\"Ġwin ter\",\"ĠC O\",\"C he\",\"Ġ Î\",\"M P\",\"Ġun w\",\"Ġfew er\",\"ĠM ir\",\"Ġsomew here\",\"ĠK ey\",\"Ġattack ed\",\"ĠK ir\",\"Ġdom ain\",\"Ġstrong er\",\"Ġ9 9\",\"Ġpen alty\",\"I d\",\"Sc ript\",\"Ġdecl ined\",\"Ġne ck\",\"Ġfra ud\",\"Ġcur rency\",\"Ġr ising\",\"R C\",\"âĢ¦ âĢ¦\",\"H z\",\"Ġt ab\",\"Ġtal ent\",\"n am\",\"ĠN BA\",\"Ġvill age\",\"Ġleg s\",\"ĠN ext\",\"E d\",\"Ġac id\",\"Ġhy d\",\"8 00\",\"Ġinvol ving\",\"ĠIm age\",\"ĠBe fore\",\"F l\",\"Ġyes terday\",\"S ource\",\"Ġterror ist\",\"Ġsu p\",\"Ġsy nt\",\"ĠSaud i\",\"Ġw est\",\"Ġr u\",\"b urg\",\"Ġvis ible\",\"Ġstru ck\",\"r ison\",\"Ġaw esome\",\"Ġd rawn\",\"Ġansw ers\",\"ĠG irl\",\"ĠR am\",\"Ġthreat s\",\"Ġdef eat\",\"os it\",\"Ġv ent\",\"atur ally\",\"Americ an\",\"end a\",\"ĠH oly\",\"Ġr um\",\"% ,\",\"c ase\",\"ĠHist ory\",\"ĠYou Tube\",\"Ġsit uations\",\"ĠD NA\",\"S te\",\"Ġsa ved\",\"It em\",\"Ġrec ip\",\"olog ist\",\"Ġfac ed\",\"Ġel ig\",\"O nce\",\"ĠL i\",\"u h\",\"Ġmist ake\",\"ĠDiv ision\",\"ĠB ell\",\"Ġsympt oms\",\"Â ®\",\"Ġdom in\",\"Ġfall ing\",\"Ġend ing\",\"as hes\",\"Ġmat ches\",\"ĠOn line\",\"Ġexplan ation\",\"D ef\",\"red it\",\"Ġany more\",\"ĠT otal\",\"ĠF OR\",\"us hed\",\"Ġlet ters\",\"Ġris ks\",\"ĠO K\",\"Ġreported ly\",\": \\\\\",\"Ġpl ate\",\"Ġsubject s\",\"Ġattempt ed\",\"if ier\",\"ian a\",\"Ġunlike ly\",\"ĠTh ough\",\"um a\",\"ĠIn vest\",\"ĠPr in\",\"ic an\",\"ĠD ar\",\"ĠColor ado\",\"au g\",\"Ġve get\",\"a os\",\"ri a\",\"Ġshe l\",\"Ġmark ed\",\"Ġ( )\",\"Ġsp r\",\"p o\",\"ĠL ink\",\"Ġdef e\",\"ĠJ r\",\"Ġthem e\",\"Ġpass ion\",\"ĠP en\",\"Ġinf o\",\"iz er\",\"Ġsh it\",\"ĠC ivil\",\"ap se\",\"c re\",\"Ġpo ly\",\"Ġcomp onent\",\"ĠChar les\",\"ĠIre land\",\"ĠPro v\",\"Ġdo ctors\",\"Ġgr anted\",\"Ġpain t\",\"Ġhon or\",\"Ġsm oke\",\"Ġpay ments\",\"Ġprim arily\",\"ĠKing dom\",\"r ich\",\"ate ll\",\"Ġde als\",\"Ġsched uled\",\"Ġfund amental\",\"Ġprote in\",\"Ġnewsp aper\",\"Ġcl ients\",\"yth on\",\"ĠD ate\",\"h us\",\"Ġfeed back\",\"Ġstret ch\",\"Ġc ock\",\"Ġhot el\",\"ĠQue en\",\"Ġsu gar\",\"Ġj u\",\"Ġmil k\",\"Ġappro val\",\"ĠL ive\",\"Ġequival ent\",\"ef ully\",\"Ġins ert\",\"z ona\",\"Ġext ension\",\"d ri\",\"J ohn\",\"Ġacc omp\",\"S m\",\"ĠF und\",\"Ġconst antly\",\"Ġ` `\",\"Ġgener ated\",\"ĠA ction\",\"ĠP sych\",\"ĠT ri\",\"Ġrecogn ize\",\"Ġv ary\",\"ph a\",\"ĠR a\",\"d f\",\"et ch\",\"ĠSov iet\",\"Tw o\",\"Ġpattern s\",\"Ġprof ession\",\"an ing\",\"T ime\",\"ĠL im\",\"Ġcol ors\",\"ĠA z\",\"ĠT R\",\"Ġinf ect\",\"Ġphen omen\",\"Ġshe ll\",\"Al so\",\"Ġput s\",\"Ġdel ivery\",\"Ġbro wn\",\"Ġprocess ing\",\"Ġlight s\",\"ess age\",\"ĠBro ok\",\"ĠA ud\",\"l ation\",\"Ġindust rial\",\"L ike\",\"ĠB razil\",\"rou s\",\"ES S\",\"ĠL uc\",\"Ġsome how\",\"Ġ8 5\",\"Ġpro port\",\"Ġpolit icians\",\"Ġindic ate\",\"Ġh ole\",\"Ġtechn iques\",\"Ġcompet itive\",\"Ġph r\",\"Ġv o\",\"ist ent\",\"ĠD ream\",\"Ġcamp us\",\"Ġaspect s\",\"Ġhelp ful\",\"Ġsh ield\",\"or se\",\"Ġtrig ger\",\"m al\",\"Ġ5 8\",\"Ġt ort\",\"Ġperson ally\",\"Ġt ag\",\"Ġkeep s\",\"ĠV ideo\",\"Ġben ch\",\"Ġg ap\",\"a ire\",\"Ġe ast\",\"Ġrec overy\",\"per ial\",\"Ġprof it\",\"ĠM ic\",\"Ġ5 7\",\"Ġcol on\",\"Ġstrong ly\",\"st yle\",\"Ġalleg ations\",\"h an\",\"Ġrep orters\",\"j o\",\"r ine\",\"arg et\",\"and al\",\"Ġ0 3\",\"Ġfl ash\",\"tr ans\",\"Ġstr ict\",\"Ġpark ing\",\"ĠPak istan\",\"Ġl i\",\"Ġwe ird\",\"ĠE ric\",\"Ġreg ions\",\"ĠJ un\",\"Ġint ellect\",\"ĠW H\",\"od ing\",\"rib utes\",\"up id\",\"ĠT it\",\"Ġf inger\",\"or ia\",\"Ġe lev\",\"ĠF ield\",\"Ġcon clusion\",\"; ;\",\"Ġfeel ings\",\"Ġext ensive\",\"Ġm ixed\",\"Ġne uro\",\"v y\",\"Ġhar ass\",\"ĠC irc\",\"ou ch\",\"Ġterrit ory\",\"Ġsuccess fully\",\"M ar\",\"Ġing red\",\"Ġoverw hel\",\"Ġl ayer\",\"V iew\",\"Ġall ies\",\"ill ance\",\"ĠTh ree\",\"Ġb unch\",\"Ġnorm ally\",\"Ġnet works\",\"Ġsac r\",\"ĠC IA\",\"b les\",\"Ġch ose\",\"Ġopp onents\",\"Ġregard less\",\"Ġfr anch\",\"Ġpre f\",\"ĠP o\",\"Ġbr idge\",\"ann a\",\"ĠSil ver\",\"Ġw age\",\"p age\",\"ri or\",\"Ġrad ical\",\"ĠL ittle\",\"Ġman ip\",\"Ġsecret ary\",\"Ġg ang\",\"D R\",\"F A\",\"Ġdec ent\",\"ĠSp irit\",\"Ġun cle\",\"ĠDevelop ment\",\"Ġinvest ors\",\"Ġwall s\",\"Ġpub lish\",\"Ġgener ate\",\"iss ions\",\"c ar\",\"Ġprom ote\",\"Ġcut ting\",\"Ġche st\",\"Ġdrink ing\",\"Ġcollect ed\",\"Ġ7 2\",\"Ġhop ing\",\"Ġem br\",\"gor ith\",\"Ġwar ned\",\"Ġinstruct ions\",\"O G\",\"ĠD id\",\"ĠAg ency\",\"Ġg ear\",\"Ġcritic ism\",\"ĠF urther\",\"Ġut il\",\"ann y\",\"R ed\",\"Ġcoun sel\",\"ĠAs ian\",\"Ġredu ction\",\"p ool\",\"Ġteach ing\",\"Ġdeep ly\",\"i y\",\"Ġestim ates\",\"Ġcho ices\",\"Ġperman ent\",\"in em\",\"ke l\",\"Ġf asc\",\"p se\",\"f ile\",\"ĠL ow\",\"ĠP erson\",\"Ġt ournament\",\"st al\",\"Ġm el\",\"U ST\",\"ĠR ay\",\"az i\",\"V al\",\"Ġcont ained\",\"ĠH olly\",\"Ġw ake\",\"Ġreve al\",\"Ġprocess es\",\"ĠIS IS\",\"Ġ0 9\",\"Ġbl ind\",\"Ġste el\",\"ĠB ad\",\"Ġcare fully\",\"app y\",\"ro it\",\"Ġg aming\",\"Ġhous es\",\"ĠC oll\",\"Ġtr uck\",\"er m\",\"Ġsc ored\",\"Ġocc as\",\"ret urn\",\"b ound\",\"v ar\",\"Ġsh arp\",\"Ġaf raid\",\"ĠE X\",\"am ber\",\"c ific\",\"Ġsche me\",\"N C\",\"ĠPol it\",\"Ġdecl ine\",\"Ġ199 8\",\"Ġpus hing\",\"Ġposs ession\",\"Ġpriv ile\",\"Ġteacher s\",\"Ġy ield\",\"H A\",\"ĠDav is\",\"it led\",\"#### ####\",\"Ġr ig\",\"ĠD aniel\",\"ac on\",\"Ġh ide\",\"ut en\",\"Ġcolle agues\",\"Ġprin ciples\",\"Ġl oud\",\"Ġs in\",\"ĠDem on\",\"Ġst one\",\"Ġ0 2\",\"Ġt aught\",\"Ġter rible\",\"Ġst uck\",\"ĠPol icy\",\"te en\",\"Ġimplement ation\",\"ĠB BC\",\"ĠAP I\",\"Ġwhe el\",\"all as\",\"Ġch ampions\",\"ol ars\",\"play er\",\"Ġrepeated ly\",\"ĠSt ill\",\"Ġlik es\",\"ast y\",\"es ter\",\"ĠCath olic\",\"R L\",\"Ġb ath\",\"Ġno ise\",\"t itle\",\"Ġn orthern\",\"P art\",\"Ġmag n\",\"Ġf ab\",\"ĠAs h\",\"Ġdis pl\",\"Ġtick et\",\"Ġm urd\",\"Ġalong side\",\"ĠMus ic\",\"Ġr iver\",\"ĠSte el\",\"ĠC L\",\"ĠPl ayer\",\"ĠM ult\",\"ow ing\",\"re p\",\"s ize\",\"Ġt ur\",\"ĠGeorg ia\",\"isc al\",\"ra ction\",\"Ġc able\",\"Ġ5 9\",\"Ġw ins\",\"Ġup coming\",\"Ġsurv ive\",\"Ġins pired\",\"ĠEduc ation\",\"Ġstat istics\",\"ĠF oot\",\"iam i\",\"Ġy ellow\",\"ĠP age\",\". -\",\"ĠH as\",\"Ġur ban\",\"Ġa x\",\"es sel\",\"\\\\ \\\"\",\"Ġquarter back\",\"Ġreg ister\",\"ĠLab or\",\"Ġab ilities\",\"ĠF amily\",\"Ġvar iable\",\"ĠPr ice\",\"Ġcont em\",\"Ġth in\",\"ĠE qu\",\"d ata\",\"Ġg otten\",\"Ġconst it\",\"Ġas ks\",\"Ġt ail\",\"Ġexc iting\",\"ĠE ffect\",\"ĠSp anish\",\"Ġencour age\",\"ins on\",\"ĠA h\",\"Ġcommit ment\",\"C S\",\"Ġr ally\",\"Ġ: :\",\"Ġsubs id\",\"Ġsp in\",\"Ġcapt ured\",\"201 8\",\"Ġinn oc\",\"Ġalleged ly\",\"ĠC ome\",\"Ġart ists\",\"ĠN umber\",\"Ġelect ronic\",\"Ġreg ional\",\"ap es\",\"Ġw ra\",\"Ġmy th\",\"pr ise\",\"ĠM iller\",\"ĠC reat\",\"ĠEp isode\",\"b ell\",\"Ġdirect ed\",\"Ġext ract\",\"Ġs orry\",\"Ġv ice\",\"ag ger\",\"ĠSu pport\",\"Ġ6 6\",\"ĠI ron\",\"Ġwonder ful\",\"Ġg ra\",\"N et\",\"ion e\",\"E ng\",\"Ġsh ips\",\"ik es\",\"ĠK evin\",\"it ar\",\"Ġactiv ists\",\"tr ue\",\"ĠAri zona\",\"ent h\",\"ĠDes pite\",\"ĠS E\",\"Ġha bit\",\"ern el\",\"Ġin qu\",\"Ġab ortion\",\"Ġv oid\",\"Ġexpl icit\",\"Ġeng aged\",\"Ġang ry\",\"Ġr ating\",\"Ġfr ag\",\"b ro\",\"ick ing\",\"d ev\",\"Ġwor ried\",\"Ġob ser\",\"Ġap artment\",\"ĠG T\",\"Ġest ate\",\"ĠConst itution\",\"em on\",\"ĠS now\",\"Ġcount y\",\"Ġdis ag\",\"ĠStep hen\",\"Ġimm igrants\",\"w ind\",\"ĠN ations\",\"Ġfol ks\",\"O ut\",\"Ġg all\",\"Ġtarget ed\",\"Ġst ead\",\"ĠB on\",\"ĠL ib\",\"Ġinform ed\",\"Ġ12 0\",\"ch ain\",\"idel ines\",\"or ough\",\"Ġdri ven\",\"Ġregular ly\",\"Ġbas ket\",\"Ġprinc iple\",\"oc ument\",\"Ġst un\",\"ib ilities\",\"ĠRom an\",\"ĠAb out\",\"Ġal ert\",\"Ġdemocr acy\",\"Ġrepresent ed\",\"H S\",\"c ers\",\"p arent\",\"Ar t\",\"p ack\",\"Ġdi plom\",\"re ts\",\"ĠN O\",\"Ġcapt ure\",\"ĠAd v\",\"Ħ ¢\",\"Ġannounce ment\",\"ĠL ear\",\"Ġh ook\",\"Ġpur s\",\"ĠS uch\",\"ĠC amer\",\"Ġrefuge es\",\"ĠV e\",\"P ol\",\"Ġrecogn ized\",\"l ib\",\"Ġhad n\",\"A ss\",\"Ġpil ot\",\"us hing\",\"Ġreturn ing\",\"Ġtra il\",\"ĠSt one\",\"Ġrout ine\",\"Ġcour ts\",\"Ġdes per\",\"Ġfriend ly\",\"ĠIt aly\",\"Ġpl ed\",\"Ġbreat h\",\"Ġstud io\",\"N S\",\"Ġimp ressive\",\"ĠAfghan istan\",\"Ġf ing\",\"Ġd ownt\",\"ink ing\",\"ĠR og\",\"i ary\",\"col or\",\"se x\",\"ar on\",\"Ġf ault\",\"ĠN ick\",\"D own\",\"ĠR ose\",\"ĠS outhern\",\"X X\",\"is odes\",\"L ist\",\"6 00\",\"Ġout come\",\"er r\",\"Ġelse where\",\"Ġret ire\",\"Ġp ounds\",\"ĠGl obal\",\"Pe ople\",\"Ġcommun ications\",\"Ġlo an\",\"Ġrat io\",\"ĠEm pire\",\"Ġg onna\",\"Ġinv ent\",\"D F\",\"Ġ19 70\",\"ĠComm on\",\"p at\",\"Ġprom ised\",\"Ġd inner\",\"ĠH om\",\"Ġcreat es\",\"Ġoper ate\",\"ver ty\",\"ĠJ ordan\",\"et ime\",\"Ġsust ain\",\"R eg\",\"Ġincred ible\",\"im a\",\"Ġwar rant\",\"Ġm m\",\"A tt\",\"Ġlaw suit\",\"Ġreview s\",\"it ure\",\"ĠS ource\",\"l ights\",\"ĠF ord\",\"Ġ6 3\",\"g roup\",\"st ore\",\"Ġfeat ured\",\"Ġfore ver\",\"Ġpo verty\",\"ĠP op\",\"ĠC NN\",\"az z\",\"ab is\",\"ach ing\",\"Ġl aid\",\"ĠSu pp\",\"Ġfil ter\",\"en a\",\"ĠCommun ity\",\"Ġcreat ures\",\"u ction\",\"ĠR oyal\",\"Ġassoci ation\",\"ĠCon nect\",\"ĠBr ad\",\"âĸ Ī\",\"l ers\",\"the re\",\"ĠG i\",\"Ġval uable\",\"AC K\",\"ĠT aylor\",\"Ġl iquid\",\"ĠAtt orney\",\"ĠCar l\",\"ĠF inal\",\"ag a\",\"ĠWil son\",\"B ecause\",\"ĠProf essor\",\"ak a\",\"Ġincred ibly\",\"r ance\",\"! )\",\"R ef\",\"s k\",\"Ġsol utions\",\"Ġatmosp here\",\"Ġbl ame\",\"um es\",\"ĠN ob\",\"C A\",\"um ps\",\"r ical\",\"ĠPut in\",\"ĠD est\",\"or ic\",\"ĠP A\",\"Ġrespect ively\",\"w an\",\"Ġfif th\",\"â Ħ¢\",\"ĠC ry\",\"Ġgovern or\",\"res ident\",\"Ġpurch ased\",\"Ġh ack\",\"Ġint ense\",\"ob s\",\"Ġorig in\",\"Ġdef ine\",\"Ġcare ful\",\"** *\",\"Ġshould er\",\"Cl ick\",\"Ġt ied\",\"Ġdest ruction\",\"ou red\",\"Ġno body\",\"Ġh o\",\"ĠEx per\",\"Ġt ip\",\"\\\" ;\",\"Ġtechn ique\",\"Ġj ur\",\"ĠP ok\",\"b ow\",\"Ġleg end\",\"Ġacc ord\",\"Ġbus y\",\"ĠInt el\",\"Ġh ang\",\"ak i\",\". ]\",\"âĢĶâĢĶ âĢĶâĢĶ\",\"Ġsur gery\",\"Ġrep rodu\",\"Ġun iform\",\"Ġscen es\",\"c ode\",\"Ġ6 2\",\"l isher\",\"ĠH ave\",\"ph ia\",\"Ġcry pt\",\"Ġrec on\",\"Ġsc ream\",\"Ġadop ted\",\"Ġsc ores\",\"N e\",\"ĠIt alian\",\"in cluding\",\"B O\",\"Ġindic ated\",\"Ġent ertain\",\"G u\",\"T ext\",\"i el\",\"Ġtw enty\",\"Ġeng age\",\"off s\",\"ĠPac ific\",\"Ġsm ile\",\"Ġperson nel\",\"Ġto ler\",\"Ġdo ors\",\"Ġt one\",\"Ġmach ines\",\"Ġent ering\",\"ten ance\",\"C O\",\"ĠJer sey\",\"Ġfore st\",\"Ġhor se\",\"Ġcompl aint\",\"ĠSpr ing\",\"y o\",\"ĠPl us\",\"ed ing\",\"ĠRet urn\",\"qu arters\",\"ial s\",\"c ow\",\"Ġacad emic\",\"Ġf ruit\",\"Ġ199 6\",\"og ether\",\"Ġw ine\",\"Ġpur su\",\"ĠSte ven\",\"Ġlic ens\",\"Wh o\",\"Ġclot hes\",\"re ction\",\"Ġsqu ad\",\"Ġst able\",\"Ġr aw\",\"z ens\",\"St ar\",\"ut ies\",\"anc er\",\"Ġke ys\",\"ĠM u\",\"Ġcompl icated\",\"ig er\",\"ĠTe xt\",\"Ġabs or\",\"Ġ6 8\",\"Ġfun ny\",\"Ġrel ief\",\"ĠL ew\",\"ĠC ook\",\"Ġch art\",\"Ġdraw ing\",\"G E\",\"Ġmod ule\",\"ĠB ull\",\"I LL\",\"Ġs alt\",\"0000 0000\",\"il le\",\"Ġres ource\",\"aw ay\",\"adel phia\",\"ĠB ru\",\"Ġ6 7\",\"Ġsome body\",\"Ġparticip ate\",\"Ġro se\",\"we red\",\"Ġmus cle\",\"Ġcons ent\",\"Ġcontin uing\",\"ĠGuard ian\",\"ĠOr der\",\"reg on\",\"Ġre ar\",\"Ġprov ision\",\"Ġlik ed\",\"ri ent\",\"Ġb ra\",\"Tr ans\",\"Ġmeet ings\",\"Ġto x\",\"Ġcon vent\",\"Ġaut o\",\"Ġrec ording\",\"ĠSo ft\",\"00 1\",\"ĠR oll\",\"Ġprogram ming\",\"Ġp ic\",\"Ġprov ed\",\"Ġst ab\",\"ĠA st\",\"Ġca ption\",\"ul ating\",\"ĠAtt ack\",\"Ġnew ly\",\"Ġ199 7\",\"f r\",\"Ġdis cipl\",\"ĠGree k\",\"Ġed ition\",\"ĠDo es\",\"ĠB ox\",\"if le\",\"ack et\",\"Ġpass es\",\"Ġgu est\",\"Ġac celer\",\"it als\",\"U D\",\"Ġaut hent\",\"ĠR est\",\"ov al\",\"t a\",\"u ine\",\"Ġarm or\",\"ĠT own\",\"Ġcomp at\",\"Ġinc hes\",\"Des pite\",\"Ġass ign\",\"he rent\",\"Ġprep are\",\"ĠM eg\",\"oc key\",\"Ġdep ends\",\"Ġtrack s\",\"w atch\",\"Ġl ists\",\"ĠN orthern\",\"Ġal ter\",\"re c\",\"ĠE astern\",\"Ġcond em\",\"Ġevery where\",\"? '\",\"Ġaff ili\",\"Ġf ought\",\"\\\": {\\\"\",\"Ġm ac\",\"it arian\",\"Ġsc ope\",\"ĠA L\",\"aw s\",\"ar ms\",\"Ġqu e\",\"Ġenjoy ed\",\"nes ota\",\"Ġagg ressive\",\"ĠSt ory\",\"ĠI V\",\"Ġrec ipe\",\"Ġrare ly\",\"ĠMed ical\",\"val ue\",\"ang el\",\"ay ing\",\"omet hing\",\"Ġsub section\",\"Ġs outhern\",\"Ġfrequ ency\",\"re te\",\"roll ed\",\"ult s\",\"ĠN ic\",\"Ġbeh alf\",\"Ġsequ ence\",\"ab et\",\"Ġcontrovers ial\",\"Ġcomp rom\",\"Ġwork er\",\"Ġmain ly\",\"Ġal gorith\",\"ĠM ajor\",\"or ce\",\"g ender\",\"Ġorgan ized\",\"Ġf ake\",\"Ġconclud ed\",\"ĠE D\",\"ĠEx ec\",\"r age\",\"Ġch ances\",\"ber ry\",\"ĠTr ad\",\"Ġconfig uration\",\"Ġwithd raw\",\"Ġf ro\",\"ud es\",\"ĠBro ther\",\"ĠB rian\",\"Ġtri es\",\"Ġsam ples\",\"Ġb id\",\"ĠGold en\",\"Ġphot ograph\",\"if est\",\"ĠD O\",\"ĠPar liament\",\"******** ********\",\"R em\",\"Ġcont est\",\"Ġsign ing\",\"p x\",\"ĠZ eal\",\"âĶĢ âĶĢ\",\"E ar\",\"Ġex it\",\"Be fore\",\"ĠCor por\",\"n ull\",\"mon th\",\"Ġrac ial\",\"ott ed\",\"ĠV eg\",\"ĠRe uters\",\"Ġsw ord\",\"ps on\",\"ĠRom ney\",\"a ed\",\"Ġt rib\",\"Ġin ner\",\"Ġprot ocol\",\"ĠB i\",\"ĠM iami\",\"ever al\",\"p ress\",\"Ġsh ipping\",\"ĠAm endment\",\"ĠHow ard\",\"con nect\",\"ĠD isc\",\"ĠJ ac\",\"iam ond\",\"ĠThere fore\",\"s es\",\"ĠPrin cess\",\"ĠUS B\",\"ĠAn th\",\"Ġsurve illance\",\"Ġap olog\",\"Ġ6 1\",\"ow a\",\"Ġf ulf\",\"j s\",\"Ġl uck\",\"ust ed\",\"ĠÂ §\",\"n i\",\"Ġant icip\",\"em an\",\"Ġwin ner\",\"Ġsil ver\",\"ll a\",\"ic ity\",\"Ġunus ual\",\"Ġcr ack\",\"Ġt ies\",\"e z\",\"Ġpract ical\",\"Ġprov ince\",\"ĠPl ace\",\"Ġprior ity\",\"IC E\",\"Ġdescrib es\",\"Ġbr anch\",\"F orm\",\"ask a\",\"miss ions\",\"b i\",\"Ġp orn\",\"ĠTur k\",\"Ġent hus\",\"Ġf ighters\",\"Ġ0 8\",\"ĠDet roit\",\"Ġfound ation\",\"av id\",\"A re\",\"Ġjud gment\",\"cl ing\",\"Ġsol ve\",\"ĠDes ign\",\"W here\",\"hes is\",\"ĠT ro\",\"a fter\",\"Ġne utral\",\"ĠPalestin ian\",\"ĠHolly wood\",\"Ġadv is\",\"ĠN on\",\"y es\",\"ol is\",\"Ġrep utation\",\"Ġsm ell\",\"Ġb read\",\"ĠB ul\",\"ĠBe ach\",\"Ġclaim ing\",\"Ġgen etic\",\"Ġtechn ologies\",\"Ġupgr ade\",\"row s\",\"Ġdevelop er\",\"ĠJ osh\",\"ĠDis ney\",\"erv ed\",\"ip al\",\"Ġun ex\",\"Ġbare ly\",\"t hen\",\"ĠP ub\",\"Ġill ness\",\"et ary\",\"ĠB al\",\"Ġp atch\",\"Ġbut t\",\"Ġst upid\",\"ĠD og\",\"ĠD allas\",\"f ront\",\"ie ce\",\"Ġprot ests\",\"Ġch at\",\"oen ix\",\"Ġw ing\",\"Ġpar liament\",\"Ġ7 7\",\"ose xual\",\"Ġre nder\",\"pt ions\",\"ĠCo ast\",\"os a\",\"ĠG reg\",\"h op\",\"ĠMan agement\",\"Ġbit coin\",\"Ġrec over\",\"Ġincor por\",\"or ne\",\"ĠUs ing\",\"Ġpre ced\",\"Ġthreat ened\",\"Ġspirit ual\",\"ĠE vent\",\"ĠF red\",\"Ġadvert ising\",\"Ġimprove ments\",\"ĠC ustom\",\"Ġer rors\",\"Ġsens itive\",\"ĠN avy\",\"Ġcre am\",\"L ook\",\"Ġex clusive\",\"Ġcomp rehens\",\"Ġde leg\",\"Ġcon ce\",\"Ġrem em\",\"Ġstruct ures\",\"Ġst ored\",\"N D\",\"Ġ1 000\",\"U P\",\"ĠB udd\",\"A F\",\"w oman\",\"ĠAcad emy\",\"ð Ł\",\"se a\",\"Ġtem porary\",\"Ab out\",\"es ters\",\"Ġtick ets\",\"Ġposs ess\",\"in ch\",\"o z\",\"Ġl a\",\"Ġcontract s\",\"Ġun p\",\"Ġc ig\",\"ĠK at\",\"ult ural\",\"as m\",\"Ġmount ain\",\"ĠCapt ain\",\"St ep\",\"m aking\",\"ĠSp ain\",\"Ġequ ally\",\"Ġl ands\",\"at ers\",\"Ġreject ed\",\"er a\",\"im m\",\"ri x\",\"C D\",\"Ġtrans action\",\"g ener\",\"less ly\",\"Ġ| |\",\"Ġc os\",\"ĠHen ry\",\"Ġprov isions\",\"Ġg ained\",\"Ġdirect ory\",\"Ġra ising\",\"ĠS ep\",\"ol en\",\"ond er\",\"Ġcon sole\",\"in st\",\"Ġb om\",\"Ġunc ertain\",\"1 50\",\"ock ing\",\"Ġmeas ured\",\"Ġpl ain\",\"Ġse ats\",\"Ġd ict\",\"S L\",\"af e\",\"Ġest imate\",\"iz on\",\"at hered\",\"Ġcontribut ed\",\"Ġep isodes\",\"omm od\",\"G r\",\"AN T\",\"Ġ6 9\",\"G ener\",\"Ġ2 50\",\"vious ly\",\"rog en\",\"Ġterror ism\",\"Ġmove ments\",\"ent le\",\"oun ce\",\"ĠS oul\",\"Ġpre v\",\"ĠT able\",\"act s\",\"ri ors\",\"t ab\",\"Ġsuff er\",\"Ġn erv\",\"Ġmain stream\",\"ĠW olf\",\"Ġfranch ise\",\"b at\",\"Ġdem ands\",\"Ġag enda\",\"Ġdo zen\",\"Ġclin ical\",\"iz ard\",\"ĠO p\",\"t d\",\"Ġvis ited\",\"ĠPer haps\",\"Ġact or\",\"Ġde lic\",\"Ġcont ribute\",\"Ġin ject\",\"ĠE s\",\"ac co\",\"Ġlist ening\",\"Ġcon gress\",\"epend ent\",\"Ġprem ium\",\"Ġ7 6\",\"ĠIr ish\",\"Ġass igned\",\"ĠPh ys\",\"Ġworld wide\",\"Ġnarr ative\",\"ot ype\",\"m ont\",\"b ase\",\"ĠB owl\",\"ĠAdminist ration\",\"Ġrel ation\",\"ĠE V\",\"C P\",\"Ġco vers\",\"Ġ7 8\",\"Ġcert ific\",\"Ġgr ass\",\"Ġ0 4\",\"pir acy\",\"ir a\",\"Ġengine ering\",\"ĠM ars\",\"Ġun employ\",\"ĠFore ign\",\"st ract\",\"Ġv en\",\"Ġst eal\",\"Ġrepl ied\",\"Ġult imate\",\"Ġtit les\",\"d ated\",\"Ġj oy\",\"a us\",\"Ġhy per\",\"ak u\",\"Ġoffic ially\",\"ĠPro duct\",\"Ġdifficult y\",\"per or\",\"Ġresult ed\",\"rib ed\",\"l ink\",\"wh o\",\"~~ ~~\",\"ĠSpe ed\",\"ĠV iet\",\"W ind\",\"ĠBar ack\",\"Ġrestrict ions\",\"ĠSh are\",\"Ġ199 5\",\"ition ally\",\"Ġbeaut y\",\"op t\",\"Ġm aps\",\"ĠC R\",\"ĠN ation\",\"ĠCru z\",\"W ill\",\"Ġelectric ity\",\"Ġor g\",\"Ġb urd\",\"Ġviol ation\",\"Ġus age\",\"Ġper mit\",\"ĠCh ron\",\"ĠF ant\",\"Ġn aturally\",\"Ġ0 7\",\"Ġth rown\",\"ĠAw oken\",\"Ġal ien\",\"ĠHer o\",\"ĠK ent\",\"ĠR ick\",\"ri ke\",\"Ġp ace\",\"}, {\\\"\",\"G L\",\"Ġpo ison\",\"ĠT ower\",\"Ġform al\",\"al ysis\",\"Ġgen uine\",\"Ġk il\",\"a ver\",\"Ġproced ure\",\"ĠPro p\",\"intend o\",\"ĠM ain\",\"as ant\",\"Ġtr ained\",\"G ame\",\"ĠL oad\",\"ĠM A\",\"Ġcru cial\",\"Ġle ts\",\"ĠF R\",\"Ġch ampion\",\"1 01\",\"ĠCon ference\",\"Ġwrit ers\",\"Ġconnect ions\",\"Ġo kay\",\"ir ms\",\"ĠR and\",\"Ġenc ounter\",\"ĠB uff\",\"Ġachie ved\",\"Ġche cks\",\"isc ons\",\"Ġassist ant\",\"Ġwhen ever\",\"ĠA ccess\",\"ĠU r\",\"b in\",\"Ġcl ock\",\"is p\",\"op her\",\"Ġb orrow\",\"Ġm ad\",\"Ġperson ality\",\"on ly\",\"IS T\",\"ab ama\",\"Ġg ains\",\"Ġcommon ly\",\"Ġter r\",\"Ġhyp ot\",\"Ġre ly\",\"Ġt iss\",\"iscons in\",\"Ġrid ic\",\"f unction\",\"ĠO regon\",\"Ġun com\",\"r ating\",\"el and\",\"ĠN C\",\"Ġm oon\",\"ann on\",\"Ġvulner able\",\"ut ive\",\"ÂłÂł ÂłÂł\",\"ĠRad io\",\"Ġw estern\",\"se ct\",\"ĠT ony\",\"Ġocc urs\",\"ĠO s\",\"ĠH on\",\"Ã Ń\",\"Ġv essel\",\"ĠScot land\",\"Ġdiscrim ination\",\"Ġsubsequ ent\",\"st ring\",\"Ġfant asy\",\"ĠSh adow\",\"Ġtest im\",\"W E\",\"it i\",\"r as\",\"Ġbo at\",\"Ġmar ks\",\"Ġord inary\",\"Ġre n\",\"Ġrepresent ative\",\"Ġpet ition\",\"Ġ7 3\",\"Ġad venture\",\"Ġign ore\",\"ĠPhil adelphia\",\"ĠS av\",\"V P\",\"Ġfact ory\",\"Ġt asks\",\"Ġdep ression\",\"z ed\",\"................ ................\",\"ĠSt orm\",\"Ġc ogn\",\"Ġelig ible\",\"Ġredu cing\",\"v ia\",\"Ġ0 5\",\"Ġstri king\",\"Ġdoll ar\",\"h o\",\"O V\",\"Ġinstr ument\",\"Ġphilosoph y\",\"ĠMo ore\",\"ĠA venue\",\"Ġrul ed\",\"ĠFr ont\",\"IN E\",\"ĠM ah\",\"Ġscen ario\",\"ĠNAS A\",\"Ġen orm\",\"Ġdeb ut\",\"Ġte a\",\"T oday\",\"Ġabs ence\",\"S im\",\"Ġh am\",\"le ep\",\"Ġt ables\",\"ĠHe art\",\"M I\",\"K e\",\"re qu\",\"V D\",\"m ap\",\"Ġchair man\",\"Ġp ump\",\"Ġrapid ly\",\"v i\",\"Ġsubstant ial\",\"E P\",\"d es\",\"ch ant\",\"ili pp\",\"ĠS anta\",\"ri ers\",\"anche ster\",\"L oad\",\"ĠC ase\",\"Ġsa ving\",\"Ġ7 4\",\"ĠA FP\",\"er ning\",\"oun ced\",\"ĠMin nesota\",\"ĠW as\",\"Ġrec ru\",\"Ġassess ment\",\"ĠB ron\",\"U E\",\"Ġdynam ic\",\"Ġf urn\",\"ul ator\",\"Ġprop ag\",\"h igh\",\"Ġacc ommod\",\"Ġst ack\",\"ĠS us\",\"w rit\",\"Ġre ven\",\"ĠGod d\",\"ĠZeal and\",\"ab s\",\"Ġbr ut\",\"Ġper pet\",\"h ot\",\"Ġhard ly\",\"ĠB urn\",\"ãĤ ¹\",\"Ġst y\",\"Ġtrans actions\",\"Ġg ate\",\"Ġsc reens\",\"Ġsub mitted\",\"Ġ1 01\",\"Ġlangu ages\",\"ugh t\",\"em en\",\"Ġfall s\",\"Ġc oc\",\"Ĥ ¬\",\"Ġstri kes\",\"p a\",\"Ġdel iber\",\"ĠI M\",\"Ġrel ax\",\"ann els\",\"ĠSen ator\",\"Ġext rem\",\"Ġ} ,\",\"ĠDe b\",\"Ġbe ll\",\"Ġdis order\",\"c ut\",\"Ġi OS\",\"Ġl ocked\",\"Ġem issions\",\"Ġshort ly\",\"\\\" ]\",\"ĠJud ge\",\"ĠS ometimes\",\"Ġr ival\",\"Ġd ust\",\"Ġreach ing\",\"F ile\",\"Â¯Â¯ Â¯Â¯\",\"ino is\",\"ĠJ ason\",\"Ġs atell\",\"are t\",\"Ġst ations\",\"Ġag ric\",\"ĠTechn ology\",\"com es\",\"ĠUn fortunately\",\"ĠChild ren\",\"Ġappl ies\",\"ast ed\",\"Ġan ger\",\"ail ability\",\"ĠDam age\",\"Ġcomp are\",\"ĠStand ard\",\"Ġaim ed\",\"ĠB a\",\"angu age\",\"Ġreg ulation\",\"Ġj ury\",\"Ġair port\",\"Ġse ctions\",\"ĠPr ince\",\"em ed\",\"Ġmedic ine\",\"Ġh itting\",\"Ġsp ark\",\"ol ves\",\"Ġad s\",\"St ate\",\"Ġfood s\",\"Ġrepl acement\",\"Ġch icken\",\"Ġlow est\",\"Ġmind s\",\"Ġinvol ves\",\"u i\",\"Ġarr ang\",\"Ġproced ures\",\"ĠWh ich\",\"ivers ary\",\"Ġb ills\",\"Ġimprove ment\",\"Ġin ev\",\"Ġexpect ations\",\"Ġintellect ual\",\"Ġsp aces\",\"Ġmechan ism\",\"2 50\",\"bre ak\",\"ĠZ e\",\"ĠT enn\",\"ĠB alt\",\"Ġbar rel\",\"Ġstat ic\",\"man n\",\"Pol ice\",\"Ġt ips\",\"Ġhand ling\",\"c us\",\"od ed\",\"il ton\",\"ir y\",\"Ġjournal ists\",\"our se\",\"Ġcom ic\",\"Ġnom ine\",\"IT Y\",\"Ġvers us\",\"Ġlo op\",\"Ġsur f\",\"ĠInd ust\",\"ĠHun ter\",\"Ġbelief s\",\"is an\",\"Ġset up\",\"Ġbre w\",\"im age\",\"Ġcomput ers\",\"f ol\",\"} ,\\\"\",\"ĠMed al\",\"Ġtax p\",\"Ġdisplay ed\",\"Ġg rav\",\"Ġf iscal\",\"M on\",\"ĠMos cow\",\"ĠK ong\",\"ĠCent re\",\"Ġcamer as\",\"ĠMr s\",\"ĠH ay\",\"Ġa ver\",\"ĠK elly\",\"p y\",\"Ġrequire ment\",\"Ġent itled\",\"omb ie\",\"Ġsh adow\",\"ag ic\",\"ĠA k\",\"Ġel ite\",\"Ġdiv ided\",\"Ġhead ing\",\"Ġcop ies\",\"Ġloss es\",\"Ġv it\",\"k ed\",\"ĠB ry\",\"Ġan s\",\"ĠSte am\",\"Ġrep orter\",\"he im\",\"ĠIt em\",\"Ġsuper ior\",\"d on\",\"ere nt\",\"Ã ¶\",\"Ġtherap y\",\"Ġpe ak\",\"ĠMod el\",\"Ġl ying\",\"Ġg am\",\"z er\",\"r itten\",\"Ġrespons es\",\"Ġconsider ation\",\"ĠB ible\",\"Ġl oyal\",\"Ġinst ant\",\"Ġp m\",\"ĠFore st\",\"Ã ¼\",\"Ġext end\",\"Ġconv icted\",\"Ġfound er\",\"Ġconv in\",\"ĠO ak\",\"che ck\",\"Ġsch olars\",\"p ed\",\"Ġover se\",\"T op\",\"c ount\",\"ĠAr k\",\"Â ·\",\"Ġ0 6\",\"ĠL A\",\"m d\",\"ĠLat in\",\"im ental\",\"ĠC PU\",\"Ġsubst ance\",\"Ġminor ity\",\"Ġmanufact uring\",\"E r\",\"ocol ate\",\"Ġatt ended\",\"ĠMan ager\",\"r ations\",\"Ġappreci ate\",\"om y\",\"GB T\",\"id ency\",\"B L\",\"Ġguarant ee\",\"pos ition\",\"Ġo cean\",\"clud e\",\"Ġhead ed\",\"Ġt ape\",\"Ġlo ose\",\"Ġlog ic\",\"Ġpro ven\",\"Ġsp ir\",\"Ġad mit\",\"is a\",\"Ġinvestig ate\",\"Ġ199 4\",\"sy lv\",\"ĠL ost\",\"c est\",\"Ġ7 1\",\"Ġrequest ed\",\"Ġwind ows\",\"ĠPok Ã©\",\"ĠWith out\",\"M et\",\"Ġbehavi our\",\"Ġread er\",\"Ġh ung\",\"ĠKe ep\",\"Ġro les\",\"Ġimplement ed\",\"Ġbl ank\",\"Ġserv es\",\"ĠJ ay\",\"Ġc ited\",\"ĠF riend\",\"prof it\",\"ap on\",\"Ġrep air\",\"it em\",\"arr ass\",\"Ġcrit ics\",\"ad i\",\"ĠF ather\",\"Ġsh out\",\"Ġf ool\",\"Ġ8 8\",\"Ġprodu cing\",\"Ġl ib\",\"Ġround s\",\"Ġcirc le\",\"Ġpre par\",\"Ġsub mit\",\"Ġn ic\",\"mor row\",\"ãĥ «\",\"U nder\",\"Ġv ital\",\"ater n\",\"Ġpass word\",\"Ġpublic ation\",\"Ġprom inent\",\"Ġspeak s\",\"Ġb ars\",\"Ġde eper\",\"ĠM ill\",\"port ed\",\"Ġw id\",\"Ġbut ter\",\"Ġsm oking\",\"Ġindic ates\",\"K ey\",\"rop ri\",\"ĠF ile\",\"all ing\",\"ast ing\",\"ĠR us\",\"Ġad j\",\"Ġ7 9\",\"av al\",\"Ġpres um\",\"bur gh\",\"on ic\",\"Ġf ur\",\"Ġpoll s\",\"ik a\",\"Ġsecond ary\",\"Ġmon ster\",\"ig s\",\"ĠCur rent\",\"E vent\",\"Ġowners hip\",\"end ar\",\"Ġarri ve\",\"ĠT ax\",\"Ġn ull\",\"ĠPri v\",\"Ġth ro\",\"Ġk iss\",\"c at\",\"Ġup set\",\"ang le\",\"it ches\",\"ect or\",\"olog ists\",\"ĠGal axy\",\"Ġcor ruption\",\"Ġh int\",\"ent er\",\"ĠH ospital\",\"Ġgreat ly\",\"Ġbeg un\",\"es y\",\"Ġso il\",\"ĠAnt on\",\"Ġmain tenance\",\"ãĥ ©\",\"Ġdo zens\",\"Ġhuman ity\",\"ĠAl abama\",\"Ġr om\",\"w orth\",\"ap ing\",\"sylv ania\",\"l ah\",\"Ġg athered\",\"G A\",\"Ġattack ing\",\"f ound\",\"ĠSqu are\",\"Ġar bit\",\"ict ions\",\"ĠW isconsin\",\"Ġd ance\",\"ĠS aint\",\"arch y\",\"Ġbase ball\",\"Ġcontribut ions\",\"Ġliter ature\",\"Ġex ha\",\"per ty\",\"t est\",\"Ġb ab\",\"Ġcontain er\",\"let ter\",\"Ġfall en\",\"Ġwebs ites\",\"Ġbott le\",\"ĠS ac\",\"Ġbre ast\",\"ĠP L\",\"Ġveter an\",\"Ġinterview s\",\"ĠA le\",\"Ġb anned\",\"eng ers\",\"ĠRev olution\",\"in th\",\"Ġconc erning\",\"IV E\",\"Ġexp enses\",\"ĠMatt hew\",\"ĠColumb ia\",\"d s\",\"ist ance\",\"Ġent ity\",\".. .\\\"\",\"Ġrel iable\",\"Ġpar alle\",\"ĠChrist ians\",\"Ġopin ions\",\"Ġin du\",\"l ow\",\"Ġcompet e\",\"Ġth orough\",\"Ġemploy ed\",\"Ġestablish ment\",\"ig en\",\"ĠC ro\",\"Ġlawy ers\",\"ĠSt ation\",\"T E\",\"ĠL ind\",\"ĠP ur\",\"it ary\",\"Ġeffic iency\",\"âĢ Ĳ\",\"ĠL y\",\"Ġm ask\",\"Ġdis aster\",\"Ġag es\",\"ER E\",\"es is\",\"ĠH old\",\"Ġcas ual\",\"b led\",\"Ġen abled\",\"ĠEn vironment\",\"ĠInt elligence\",\"i per\",\"ĠM ap\",\"ĠB E\",\"Ġemer ged\",\"is dom\",\"Ġc abin\",\"Ġregist ration\",\"Ġfing ers\",\"Ġro ster\",\"Ġfram ework\",\"ĠDo ctor\",\"et ts\",\"Ġtransport ation\",\"Ġaware ness\",\"H er\",\"Ġattempt ing\",\"O ff\",\"ĠSt ore\",\"ÃĥÃĤÃĥÃĤ ÃĥÃĤÃĥÃĤ\",\"ĠK now\",\"Ġdef ence\",\"Ġsc an\",\"ĠT en\",\"ĠCh air\",\"ĠP H\",\"ĠAtl anta\",\"Ġfuck ing\",\"Ġans wered\",\"b n\",\"ĠK ar\",\"Ġcateg ories\",\"Ġr ational\",\"Ġc ust\",\"Ġrob ot\",\"Ġcorrect ly\",\"Ġg if\",\"Ġgraph ics\",\"m ic\",\"Ġground s\",\"ĠO pp\",\"i ate\",\"Ġdist ributed\",\"Ġsan ctions\",\"Ġchalleng ing\",\"ut o\",\"Ġingred ients\",\"Ġinv ited\",\"Ġfound ed\",\"ĠRe qu\",\"d ed\",\"Ġb owl\",\"Ġbrother s\",\"ĠH a\",\"I O\",\"Ġw ages\",\"im ore\",\"oc ial\",\"Ġse ed\",\"ative ly\",\"Ġaddress es\",\"ĠI owa\",\"ab eth\",\"Ġatt itude\",\"is d\",\"ch ild\",\"Ġm ole\",\"Ġdisco very\",\"y ard\",\"B r\",\"Ġ8 2\",\"Ġsuppl ies\",\"ell ing\",\"Ġdist ingu\",\"C R\",\"Ġre cept\",\"Ġ vert\",\"Ġsw im\",\"b ec\",\"d oor\",\"ĠY eah\",\"Ġg al\",\"Ġinter act\",\"ĠE SP\",\"ĠC S\",\"amp s\",\"Ġconvin ced\",\"Ġobject ive\",\"Ġdis h\",\"ĠPhot os\",\"l ad\",\"Ġdownt own\",\"o il\",\"in ction\",\"Ġto morrow\",\"ĠC OM\",\"Ġsurv ival\",\"sh ot\",\"Ġsett lement\",\"C ons\",\"ĠX box\",\"int erest\",\"ĠS M\",\"arg o\",\"en ess\",\"Ġeth nic\",\"b ered\",\"M in\",\"ĠT ok\",\"Ġinc ent\",\"ĠComm and\",\"Ġmain tained\",\"Ġbreak s\",\"br idge\",\"at ar\",\"ag g\",\"ĠF inally\",\"un icip\",\"ĠO nt\",\"le ft\",\"Ġrecogn ition\",\"Ġ* /\",\"ĠP ers\",\"Ġwe lf\",\"Ġaddress ed\",\"ĠK ansas\",\"Ġvir us\",\"Ġwhere as\",\"Ġp apers\",\"ram s\",\"ĠMin istry\",\"Ġple asure\",\"Ġacqu ired\",\"Ġd uration\",\"j pg\",\"Ġcal m\",\"ĠN HL\",\"Ġburn ing\",\"Ġfold er\",\"ick ed\",\"ĠP y\",\"ĠIll inois\",\"Cl ass\",\"ĠGodd ess\",\"Ġperform ing\",\"Ġwelf are\",\"j ar\",\"In ter\",\"Ġl in\",\"Ġenh ance\",\"Ġnot ion\",\"f are\",\"yp es\",\"ĠAre a\",\"Ġcann abis\",\"ĠDie go\",\"f s\",\"ĠM anchester\",\"com m\",\"in ite\",\"Ġcover ing\",\"ĠS ound\",\"Ġ19 60\",\"Ġ8 4\",\"e lect\",\"z ing\",\"Ġcitiz en\",\"Ġph ones\",\"Ġr aid\",\"Ġign ored\",\"ĠOb ject\",\"Ġu pload\",\"c ard\",\"Ġmod ified\",\"Ġroom s\",\"ia h\",\"r ange\",\"he ast\",\"ach us\",\"Ġsuggest ing\",\"âĢ ĭ\",\"gr ade\",\"E l\",\"Ġclot hing\",\"Ġr h\",\"ĠH an\",\"un ity\",\"en cing\",\"ĠAust in\",\"sec ution\",\"t ra\",\"d em\",\"ĠQ ual\",\"Ġhe aven\",\"Ġst ages\",\"Ġw edd\",\"pl us\",\"ific ial\",\"ĠIm m\",\"ĠH o\",\"iet ies\",\"Ġphr ase\",\"Ġbr ill\",\"act ory\",\"Ġprov iders\",\"Ġsil ence\",\"Ġa er\",\"ĠA I\",\"ĠAd venture\",\"Ġplatform s\",\"Ġdemonstr ated\",\"Ġinter f\",\"ing ton\",\"Ġr aces\",\"Ġgr ade\",\"ult ane\",\"ĠTh rough\",\"f alse\",\"Ġb ow\",\"ĠA B\",\"Ġfl avor\",\"Ġhistor ic\",\"g ov\",\"Ġcol our\",\"Ġview ed\",\"ĠEm ail\",\"el come\",\"Ġinter vention\",\"Ġd iversity\",\"Ġperiod s\",\"Ġre verse\",\"ĠV ery\",\"Ġqu ote\",\"ĠLe ft\",\"th rough\",\"Ġsc rew\",\"Ġland ing\",\"Ġp ill\",\"Ġw et\",\"Ġprot esters\",\"Ġrepe at\",\"av ed\",\"er k\",\"Ġsal ary\",\"ĠPenn sylvania\",\"St ill\",\"Ġmay or\",\"Ġkit chen\",\"Ġfeat uring\",\"ĠM useum\",\"ĠT ournament\",\"ĠF al\",\"Ġser vers\",\"U C\",\"Ġany body\",\"im g\",\"ĠTr ade\",\"ixt ure\",\"the less\",\"Ġfin ance\",\"Ġcl osing\",\"ĠPat ri\",\"i ac\",\"ab el\",\"Ġ> >\",\"or ous\",\"Ġf irms\",\"sc reen\",\"un a\",\"Ġemb arrass\",\"ul se\",\"Ġlet ting\",\"Ġth rew\",\"ile y\",\"Ġch annels\",\"l an\",\"ĠVeg as\",\"Ġse ar\",\"Ġfant astic\",\"ar re\",\"uzz le\",\"ĠD er\",\"Th ose\",\"Ġsw ing\",\"Ġshe et\",\"ind ex\",\"co ver\",\"og an\",\"Ġvari ables\",\"ĠTe ch\",\"Ġsp oken\",\"ac hel\",\"ĠD a\",\"ĠMount ain\",\"Ġload ed\",\"Ġfoot age\",\"vers ion\",\"Ġun l\",\"ĠPh oenix\",\"Ġthrow ing\",\"Ġf iring\",\"Ġtrack ing\",\"Ġw idth\",\"Ġstrugg ling\",\"ro oms\",\"ot ion\",\"Ġmonth ly\",\"ĠSer ver\",\"Ġegg s\",\"op en\",\"M C\",\"Ġ199 3\",\"Ġh ired\",\"Ġstay ed\",\"ĠAll en\",\"Ġst ro\",\"Ġ9 8\",\"st ep\",\"ĠTurk ish\",\"Ġfab ric\",\"ist ing\",\"ĠD om\",\"Ġd ates\",\"Ġpr on\",\"Ġbasket ball\",\"Ġl ucky\",\"ĠArab ia\",\"Ġassum ed\",\"est y\",\"Ġaff airs\",\"Ġgl ad\",\"ĠInd eed\",\"ĠF A\",\"ĠW ord\",\"Ġjo ining\",\"if ice\",\"p read\",\"ir ts\",\"ĠSe lect\",\"Ġpop ulations\",\"aw are\",\"Ġn ose\",\"Ġcompl aints\",\"st art\",\"Ġsc oring\",\"Th anks\",\"Ġmin ing\",\"Ġvisit ors\",\"S H\",\"Ġdam aged\",\"Ġcharacter istics\",\"ĠP ent\",\"D C\",\"Ġ8 3\",\"ĠS ix\",\"r ates\",\"Ġfl ags\",\"ĠB rew\",\"d og\",\"M ark\",\"// //\",\"Ġexec ution\",\"Ġj oke\",\"ph ones\",\"Ġtestim ony\",\"Ġob st\",\"Q L\",\"ĠC ut\",\"Ġstud ied\",\"ĠN intendo\",\"ick et\",\"ĠN BC\",\"Ġl ad\",\"ĠB ra\",\"ĠM oh\",\"Ġk ernel\",\"Ġoverwhel ming\",\"Ġag ed\",\"Ġapplic able\",\"ĠC ond\",\"Ġroad s\",\"ĠBl ock\",\"m ade\",\"od ge\",\"Ġcomm ands\",\"Ġoff ices\",\"vel and\",\"Ġt ut\",\"Ġrece iver\",\"ĠF ro\",\"Ġsho pping\",\"Ġi P\",\"ĠSt re\",\"ĠA BC\",\"Ġentertain ment\",\"ĠB ow\",\"ort ed\",\"M c\",\"Ġread s\",\"gr ad\",\"ĠCol lect\",\"Ġâ ĪĴ\",\"ĠCap ital\",\"eder ation\",\"Ġemploy er\",\"Ġinvolve ment\",\"Ġanx iety\",\"al ia\",\"Ġro of\",\"ĠAm ong\",\"ĠDemocr at\",\"Ġstat s\",\"ĠV ill\",\"Ġconst itutional\",\"Ġrefer ring\",\"itt y\",\"Ġtack le\",\"out ube\",\"Ġback ed\",\"ĠH ong\",\"ĠBro ad\",\"Ġe le\",\"ĠO tt\",\"Ġ199 2\",\"h our\",\"achus etts\",\"C al\",\"Ġdefe ated\",\"Ġ8 1\",\"es p\",\"Ġseem ingly\",\"w as\",\"ĠJ enn\",\"ĠK urd\",\"Ġg ene\",\"Ġdisc ount\",\"R et\",\"EC T\",\"( );\",\"Ġclub s\",\"Ġs id\",\"ĠM arsh\",\"Che ck\",\"Ġp p\",\"ĠE ag\",\"ides pread\",\"Ġbe ings\",\"F T\",\"Ġintrodu ction\",\"ĠCh ange\",\"AR D\",\"Ġ1 10\",\"ad ows\",\"ier ce\",\"Ġme al\",\"a uthor\",\"ĠB ang\",\"lah oma\",\"Ġr anks\",\"201 1\",\"?? ??\",\"m ax\",\"Ġcoll apse\",\"Ġop ens\",\"Ġe cho\",\"Ġs oph\",\"Ġrac ist\",\"Ġenorm ous\",\"Ġw aves\",\"Ġt ap\",\"Ġcomprehens ive\",\". --\",\"ĠR oy\",\"Ġfarm ers\",\"Rel ated\",\"a ired\",\"ron es\",\"ĠC rim\",\"Ġproport ion\",\"Ġdesign s\",\"Ġnegoti ations\",\"Ġvirt ually\",\"ĠBat man\",\"Ġwar n\",\"Ġlegit imate\",\"m ate\",\"Ġcon vention\",\", ,\",\"net ic\",\"ĠS D\",\"Ġconsist ently\",\"Ġcompens ation\",\"Ġpunish ment\",\"Ġy e\",\"Ġt ie\",\"ĠB ureau\",\"ir lf\",\"ĠB u\",\"ĠA ren\",\"ĠPh ilipp\",\"Ġkn ife\",\"Ġmem ories\",\"ĠR oss\",\"Ġang le\",\"Ġ8 6\",\"ĠTh under\",\"Ġre nd\",\"ĠT our\",\"Ġcount s\",\"s ung\",\"ĠIm p\",\"Ġeduc ational\",\"Ġaccess ible\",\"C OM\",\"Ġd rew\",\"y er\",\"G l\",\"am ine\",\"OR T\",\"O B\",\"I B\",\"m aster\",\"Ġtri als\",\"og y\",\"h ar\",\"ĠTr ust\",\"Ġprefer red\",\"irlf riend\",\"ĠN ev\",\"Ġb in\",\"Ġc ow\",\"P age\",\"Ġsign ature\",\"ĠB L\",\"7 00\",\"Ġret ired\",\"Ġby tes\",\"Ġneigh b\",\"ĠLeg end\",\"Ġdev ast\",\"Ġsuspect ed\",\"is ons\",\"ĠPokÃ© mon\",\"sc ale\",\"Ġcap abilities\",\"Ġre vel\",\"Ġche ese\",\"d y\",\"igr ant\",\"Ġfail ing\",\"b its\",\"ĠHer oes\",\"ĠG host\",\"ĠS cient\",\"Ġappoint ed\",\"ur i\",\"Ġinst itution\",\"Ġexpand ed\",\"g reg\",\"Ġmonitor ing\",\"Ġp odcast\",\"Ġcoal ition\",\"Ġ9 6\",\"J o\",\"Ġst olen\",\"ĠS ab\",\"Ġstop s\",\"Ġhol iday\",\"Ġint r\",\"C ar\",\"Bl ack\",\"ĠL GBT\",\"Ġwar ming\",\"ĠAnd erson\",\"Ġ8 9\",\"Ġprodu cer\",\"M ed\",\"Ġaccur acy\",\"ĠMar vel\",\"iz abeth\",\"ĠPat rick\",\"m ony\",\"Ġmin i\",\"ac les\",\"Ġover t\",\"the y\",\"Ġmembers hip\",\"ĠV en\",\"Ġex ch\",\"Ġrem oval\",\"ĠD ave\",\"T Y\",\"m ad\",\"ĠF ind\",\"Ġad equ\",\"Ġe c\",\"Ġte eth\",\"Ġemot ion\",\"Ġper m\",\"Ġsole ly\",\"d b\",\"Ġextra ord\",\"IG HT\",\"c al\",\"Ġgu idelines\",\"Ġd ying\",\"Ġsusp ended\",\"ĠPrem ier\",\"ĠAnth ony\",\"el ve\",\"Ġd ad\",\"ĠE th\",\"ĠFoot ball\",\"Ġabandon ed\",\"Ġ< <\",\"Ġm arch\",\"Ġhor ror\",\"âĢ¦ \\\"\",\"Ġchild hood\",\"Ġcampaign s\",\"Ġl unch\",\"ĠAl bert\",\"bl ock\",\"âĸĪ âĸĪ\",\"ound ing\",\"Ġb one\",\"or gan\",\"ad ers\",\"ĠFl ash\",\"ĠDri ve\",\"Ġton ight\",\"Ġw ars\",\"ĠF L\",\"Ġform ation\",\"con st\",\"New s\",\"Ġcom pe\",\"or ious\",\"ĠSt aff\",\"Ġdiscuss ions\",\"ĠProt ection\",\"ĠJ am\",\"Ġcrit eria\",\"Ġinstall ation\",\"Ġaccompl ish\",\"iz za\",\"Ġpub lisher\",\"Ġresc ue\",\"ĠT ry\",\"U LL\",\"ĠS om\",\"ĠH op\",\"ore t\",\"th s\",\"ord on\",\"Ġp ocket\",\"ĠIn v\",\"Down load\",\"ĠCr ime\",\"Ġb ene\",\"ĠGu ide\",\"ĠAs sembly\",\"Ġparam eters\",\"I E\",\"ĠAlex ander\",\"Ġconc ert\",\"ĠSc he\",\"Ġsh oes\",\"Ġvis iting\",\"Ġrec all\",\"Ġb ub\",\"Ġr ural\",\"Ġconc rete\",\"ĠR os\",\"N ext\",\"R uss\",\"Ġlo ans\",\"ĠSh ield\",\"Ġtre m\",\"hem at\",\"k g\",\"ĠHar ris\",\"is ition\",\"ĠM ove\",\"ĠF C\",\"Ġf ate\",\"ĠCh o\",\"Ġt ired\",\"Ġprinc ipal\",\"h ist\",\"ien ces\",\"ath y\",\"Ġse vent\",\"Ġm ood\",\"Ġstrateg ic\",\"Ġdise ases\",\"Ġfor um\",\"Ġtem por\",\"Ġhead quarters\",\"P ar\",\"ig e\",\"fl ix\",\"Ġgu itar\",\"Ġ9 4\",\"On ly\",\"Ġrele ases\",\"ro ph\",\"================ ================\",\"Ġ6 00\",\"ĠContin ue\",\"ig ate\",\"ĠC rit\",\"sy stem\",\"Ġdis abled\",\"Ġunex pected\",\"ith ub\",\"Ġuncle ar\",\"ĠE st\",\"Ġcontr ad\",\"Ġstrateg ies\",\"vent ures\",\"Ġpass age\",\"AM E\",\"Ġimpro ving\",\"Ġreve als\",\"Ġdecre ase\",\"ov a\",\"Ġann oy\",\"ĠSh ort\",\"ĠL ibrary\",\"Ġcy ber\",\"n ell\",\"ĠH ur\",\"ĠC B\",\"Ġphot ograp\",\"U I\",\"Ġs ed\",\"G e\",\"Ġ8 7\",\"Ġd iverse\",\"Ġencour aged\",\"Ġcons piracy\",\"Ġbird s\",\"Ġoper ator\",\"Ġhand ful\",\"Ġclass ified\",\"? )\",\"Ġdram atic\",\"Ġinvestig ators\",\"it o\",\"Ġw idespread\",\"ĠR oom\",\"-------------------------------- --------------------------------\",\"Ġcollect ive\",\"Ġjournal ist\",\"St ring\",\"Ġtemper atures\",\"il a\",\"Ġgu id\",\"Ġins pect\",\"Ġmiss ile\",\"ĠMay or\",\"Ġman ual\",\"Ġsim ultane\",\"Ġrat ings\",\"Ġsu ck\",\"Ġ9 7\",\"Ġunivers al\",\"Ġph arm\",\"Ġdis rupt\",\"ian o\",\"A V\",\"Ġf t\",\"Ġstat ist\",\"old s\",\"ĠWalk er\",\"ph p\",\"Ġunder t\",\"ĠL as\",\"ish op\",\"nt il\",\"res hold\",\"ĠWhe ther\",\"M s\",\"Ġden y\",\"ĠCl oud\",\"Ġprov ider\",\"Ġsurv iv\",\"ĠUp date\",\"h as\",\"Ġmist akes\",\"ch arge\",\"pl ed\",\"r ity\",\"Ġn ode\",\"ĠMass achusetts\",\"ool s\",\"lic ation\",\"Ġf ails\",\"em ale\",\"or i\",\"back s\",\"Ġsh irt\",\"Ġ' '\",\"ĠN AT\",\"Ġwat ers\",\"els on\",\"Ġe ase\",\"Ġsc ar\",\"Ġcont ents\",\"m ind\",\"Ġcont ribution\",\"Ġsh r\",\"Ġhand ed\",\"Ġst ability\",\"Ġtra ve\",\"E m\",\"Ġmir ror\",\"12 3\",\"Ġwe igh\",\"Ġf iction\",\"ou ver\",\"ist ant\",\"r ition\",\"ĠF ed\",\"Ġphys ically\",\"Ġst ake\",\"ĠArt icle\",\"ĠAr c\",\"ĠLew is\",\"ĠM ind\",\"Ġdemonstr ate\",\"Ġprof its\",\"v ision\",\"om ic\",\"ol id\",\"Ġbatt les\",\"Ġdri ves\",\"Ġeas tern\",\"ĠS ony\",\"!! !\",\"ar ation\",\"v ard\",\"ĠG L\",\"port ation\",\"Ġ9 2\",\"Ġlaw makers\",\"Ġprotect ing\",\"ĠE PA\",\"Ġy eah\",\"Ġsh ame\",\"ol ph\",\"e ven\",\"x it\",\"Ġatt ach\",\"Ġrepresent ing\",\"Ġob s\",\"ĠUt ah\",\"iff s\",\"ĠFre edom\",\"Ã ³\",\"A K\",\"Ġinc idents\",\"it age\",\"Ġview ers\",\"c d\",\"Ġm ouse\",\"Ġcl ar\",\"Ġaccord ance\",\"Ġb ot\",\"c or\",\"ĠSum mer\",\"he ld\",\"Ġinnoc ent\",\"Ġiniti ative\",\"ol s\",\"________________ ________________\",\"Ġsp ots\",\"p ace\",\"Ġconvent ional\",\"Ġcorpor ations\",\"Ġblock ed\",\"H D\",\"at tered\",\"Ġref ers\",\"Ġbu ck\",\"ĠDig ital\",\"12 0\",\"Ġtop ics\",\"T F\",\"Ä ģ\",\"br id\",\"re ement\",\"Ġunder lying\",\"ĠM ember\",\"Ġinvestig ating\",\"Ġpregn ancy\",\"Ġtouch down\",\"ĠB and\",\"ĠCall er\",\"Ġinst ances\",\"P P\",\"w a\",\"G ood\",\"Ġ199 1\",\"ĠC old\",\"Ġfear s\",\"Ġrem arks\",\"Ĩ Ĵ\",\"at al\",\"Ġm it\",\"Ġexper iments\",\"i pt\",\"Col or\",\"ind u\",\"Up date\",\"Ġ9 3\",\"A g\",\"Ġ å\",\"anc ouver\",\"B oth\",\"Ġjud ges\",\"Ob ject\",\"Ġst ere\",\"umb n\",\"Ġparticip ation\",\"ĠSt ars\",\"ĠJ ere\",\"Ġweek ly\",\"ĠB an\",\"Ġconvers ations\",\"ĠP itt\",\"u z\",\"ĠIndian a\",\"ĠK ick\",\"Ġinf ection\",\"Ġhero es\",\"Ġsett led\",\"Ġstri p\",\"Ġh al\",\"Ġd ump\",\"ĠS ci\",\"Ġl es\",\"Ġref erences\",\"ĠU RL\",\"ĠBr idge\",\"Ġwant ing\",\"For ce\",\"Ġex clus\",\"Me anwhile\",\"m n\",\"Ġg entle\",\"m aker\",\"sen al\",\"ĠG ro\",\"ou ri\",\"ĠR ain\",\"ĠAll iance\",\"Ġl ift\",\"el a\",\"S D\",\"ĠCle veland\",\"Ġrank ed\",\"Ġst adium\",\"Ġdead ly\",\"ä ¸\",\"Ġr iding\",\"ar ia\",\"ĠAr mor\",\"Ġdocument ation\",\"ĠGree ce\",\"ree k\",\"Ġl ens\",\"ĠS a\",\"Ġg ross\",\"ĠE mer\",\"ag ers\",\"ĠD ub\",\"ĠR h\",\"ĠAM D\",\"Ġarri val\",\"Ġdes ert\",\"Ġsupp lement\",\"ĠRes p\",\"Ġkn ee\",\"Ġmarg in\",\"f ont\",\"og g\",\"201 0\",\"ĠP ir\",\"ĠP rom\",\"iv als\",\"Ġint ake\",\"Ġdifferent ly\",\"ug s\",\"Ġb its\",\"clud ed\",\"Ġsearch ing\",\"ĠD u\",\"um ble\",\"Ġfunction al\",\"ĠBalt imore\",\"ĠC ould\",\"Ġdes ired\",\"Ġcirc uit\",\"ĠL yn\",\"ĠG O\",\"ĠF alse\",\"re pre\",\"' :\",\"alt ies\",\"Ġmin im\",\"Ġdro ve\",\"ĠSh ould\",\"Ġh ip\",\"Ġpro s\",\"Ġut ility\",\"ĠN ature\",\"ĠM ode\",\"P resident\",\"o pp\",\"r at\",\"form ance\",\"Ġconcent ration\",\"Ġf ont\",\"ĠB ud\",\"Ġam id\",\"Ġre vers\",\"ĠM L\",\"B ar\",\"Ġinter action\",\"Ġjur isd\",\"Ġspell s\",\"d ep\",\"f il\",\"Ġcivil ians\",\"ut ter\",\"ĠCo oper\",\"ĠBel ow\",\"Ġent rance\",\"Ġcon vert\",\"Ġcontrovers y\",\"ow ered\",\"Ġcontr ary\",\"Ġar c\",\"ĠExec utive\",\"ĠOffic er\",\"Ġpack ages\",\"Ġprog ressive\",\"w idth\",\"Ġreserv ed\",\"v ol\",\"ĠSam sung\",\"Ġprint ed\",\"Ġcent ers\",\"Ġintrodu ce\",\"ĠKenn edy\",\"Ġodd s\",\"Ġsure ly\",\"Ġindepend ence\",\"Ġpass engers\",\"repre ne\",\"ĠBe h\",\"Ġl oves\",\"ĠESP N\",\"Ġfac ilit\",\"Ġident ical\",\"Ġdo ct\",\"Ġpartners hip\",\"con f\",\"ĠH ide\",\"Ġconf used\",\"ĠC ow\",\"M en\",\"Ġw rest\",\"ĠIraq i\",\"Ġh oles\",\"ĠStud ies\",\"Ġpregn ant\",\"h ard\",\"Ġsign als\",\"I X\",\"Ġpull ing\",\"Ġgrad uate\",\"Ġnomine e\",\"D ate\",\"Ġper mitted\",\"Ġâ Ĥ¬\",\"ĠOk lahoma\",\"St art\",\"Ġauthor ized\",\"Ġal arm\",\"ĠC os\",\"v an\",\"Ġgener ations\",\"c ular\",\"Ġdr agon\",\"ĠSoft ware\",\"ĠEd ward\",\"Ġcontro ller\",\"S en\",\"ge red\",\"ĠV ik\",\"Ġappro ached\",\"Th ank\",\"Ġcan ce\",\"Ġform ula\",\"ĠSm all\",\"Ġweak ness\",\"Ġr amp\",\"it udes\",\"j ud\",\"Ġbrill iant\",\"Ġacc us\",\"s ource\",\"Ġ8 00\",\"ĠE vil\",\"S w\",\"Ġhom eless\",\"we ek\",\"i ens\",\"r ics\",\"ĠTh ird\",\"T O\",\"Ġorgan ic\",\"Ġpresent ation\",\"ag h\",\"ĠDown load\",\"v ation\",\"Ġas sembly\",\"or able\",\"hold ers\",\"ĠBern ie\",\"ĠHel p\",\"Ġt ong\",\"ĠF ight\",\"Ġbe ach\",\"B ook\",\"ĠL ic\",\"Ġr ush\",\"ĠR ound\",\"ou p\",\"ĠMar x\",\"Ġcalcul ated\",\"ĠDe vil\",\"ĠSar ah\",\"Ġoccasion ally\",\"Ġbul let\",\"Av ailable\",\"g ate\",\"Ġ9 1\",\"Ġh osp\",\"Ġprom ises\",\"ĠH IV\",\"ĠSt adium\",\"ĠSt ock\",\"ĠCorpor ation\",\"g age\",\"N G\",\"ĠC redit\",\"Ġs ne\",\"ib l\",\"Ġacc um\",\"s uch\",\"Ġterror ists\",\"Ġconscious ness\",\"ĠZ h\",\"Ġdram a\",\"ool a\",\"pir ation\",\"Ġlab our\",\"ĠN in\",\"Ġut ter\",\"Ġdemocr atic\",\"Ġass ass\",\"il ation\",\"Ġg est\",\"Ġab road\",\"Ġmet ab\",\"Ġs orts\",\"Ġfl av\",\"U B\",\"Ġm g\",\"ĠNot hing\",\"ĠO d\",\"Ġmus ical\",\"200 9\",\"Ġdro ps\",\"oc ated\",\"ater al\",\"0000 00\",\"Ġg re\",\"Ġequ ality\",\"Ġburd en\",\"Ġv ig\",\"ĠLe ader\",\"-------- ----\",\"Ġcere mony\",\"Ġf ighter\",\"Ġact ors\",\"Ġ æ\",\"am an\",\"F i\",\"Ġal ign\",\"put er\",\"Ġe lder\",\"ĠN SA\",\"Ġrepresent ation\",\"ĠOnt ario\",\"IT H\",\"usal em\",\"Ġharass ment\",\"itz er\",\"Ġsy mp\",\"Ġbox es\",\"ĠD R\",\"Ġman ifest\",\"at re\",\"Ġ ^\",\"Ġd ies\",\"le ton\",\"Ġmiss ions\",\"et he\",\"Ġres olve\",\"Ġfollow ers\",\"Ġas c\",\"Ġk m\",\"l ord\",\"am med\",\"Ġsil ent\",\"ĠAssoci ated\",\"Ġtim ing\",\"Ġprison ers\",\"ĠK ings\",\"ĠF ive\",\"Ġtow er\",\"Ġappro aches\",\"Ġprecise ly\",\"Ġb ureau\",\"ĠM other\",\"ĠI ss\",\"Ġkey board\",\"it ual\",\"Ġfund ed\",\"Ġstay ing\",\"Ġpsych ological\",\"Ġm ile\",\"ĠLe on\",\"ĠBar b\",\"w ill\",\"Ġw ider\",\"ĠAtl antic\",\"Ġt ill\",\"ĠR ome\",\"ro t\",\"Ġaccomp an\",\"Ġfl our\",\"ac o\",\"W orld\",\"ĠExp ress\",\"ĠY u\",\"C or\",\"Ġple ased\",\"part y\",\"Ġpoint ing\",\"Ġinf lation\",\"Ġro y\",\"Ġ ),\",\"ain er\",\"Ġwedd ing\",\"orm on\",\"Ġrequ iring\",\"Ġqual ified\",\"Ġse gment\",\"EN D\",\"Ġs izes\",\"e als\",\"Ġcor rupt\",\"ass ador\",\"Ġcele b\",\"Ġdream s\",\"ĠM ess\",\"Ġcheck ing\",\"ĠV ersion\",\"Ġprep aring\",\"Ġact ively\",\"ĠD iff\",\"Ġl ux\",\"ĠW inter\",\"act eria\",\"ĠN E\",\"Ġdep uty\",\"Ġtrans gender\",\"Ġsum mary\",\"Ġin her\",\"er ies\",\"ch ar\",\"ĠY an\",\"Ġkn ock\",\"ĠP ath\",\"Ġl ip\",\"roll er\",\"Ġimp ression\",\"Ġcelebr ate\",\"Ġsl ide\",\"Ġgu ests\",\"Ġcl ip\",\"F S\",\"Ġsav ings\",\"Ġcapt ain\",\"Ġleg acy\",\"ĠDen ver\",\"Ġw ounded\",\"tab oola\",\"AC T\",\"Ġpurs ue\",\"Ġo xy\",\"Ġ q\",\"Ġsem i\",\"ĠN eed\",\"ĠAff airs\",\"Ġob sc\",\"Ġcheck ed\",\"Ġd ual\",\"C ode\",\"ĠM D\",\"le m\",\"ult y\",\"ĠÂ ©\",\"ĠEl izabeth\",\"Ġcent uries\",\"ard ed\",\"s rc\",\"Ġev ident\",\"enn is\",\"at in\",\"Ġunemploy ment\",\"ĠMar io\",\"Ġint im\",\"Ch rist\",\"Ġbi ological\",\"Ġsold ier\",\"ĠAdd ed\",\"Ġm ath\",\"ĠG il\",\"Ġbi as\",\"Ġd ating\",\"ĠO cean\",\"Ġm ice\",\"M us\",\"h ire\",\"ĠT es\",\"Ser ver\",\"lim ited\",\"S ize\",\"Ġmet ers\",\"Ġrock et\",\"es see\",\"Ġcertific ate\",\"ĠIran ian\",\"AS S\",\"Ġgr id\",\"D ec\",\"Ġro lling\",\"com mun\",\"ĠSwed en\",\"b ury\",\"Ġtiss ue\",\"Ġrac ism\",\"ĠL ocal\",\"Ġmyster y\",\"Ġexam ine\",\"Ġst em\",\"Ġs its\",\"Ġhop ed\",\"ot ing\",\"Ġdial ogue\",\"Ġpers u\",\"W atch\",\"l ay\",\"M AN\",\"Ġch ronic\",\"ĠPort land\",\"mark et\",\"ĠS EC\",\"Ġparalle l\",\"Ġsc andal\",\"Ġcar ries\",\"Ġphenomen on\",\"h uman\",\"ack er\",\"ĠO x\",\"Ġretire ment\",\"tain ment\",\"ov ie\",\"ĠG ear\",\"Ġd uties\",\"Ġdo se\",\"Ġsc roll\",\"M B\",\"in f\",\"Ġsa uce\",\"Ġland scape\",\"red dit\",\"ĠChampions hip\",\"ĠRed dit\",\"al id\",\"Ġco in\",\"Ġover s\",\"Ġpost ing\",\"ab out\",\"Ġf el\",\"and y\",\"Ġb old\",\"Ġfocus ing\",\"e ffect\",\"G R\",\"Ġde emed\",\"Ġrecommend ations\",\"Ġste pped\",\"Ġvot er\",\"ĠDe ep\",\"ĠInst agram\",\"Ġmoder ate\",\"ĠMary land\",\"Ġrestrict ed\",\"ĠM B\",\"ĠCh all\",\"Ġto b\",\"Ġc ir\",\"ĠO cc\",\"ĠE ver\",\"Ġcoll aps\",\"IN FO\",\"= -\",\"ĠP ict\",\"ĠAcc ount\",\"n c\",\"Ġo ught\",\"Ġex port\",\"Ġdr unk\",\"( '\",\"Ġw ise\",\"ĠM ort\",\"ne cess\",\"Ġan cest\",\"ĠInc re\",\"Ġfrequ ent\",\"m ir\",\"Ġinterpret ation\",\"Ġdepend ent\",\"Ġco ins\",\"ĠB ol\",\"V ideo\",\"ĠJust in\",\"Ġfat al\",\"Ġcook ing\",\"Ġconf usion\",\"ip her\",\"Ġcust ody\",\"ĠMor gan\",\"om ach\",\"ĠGovern or\",\"Ġrestaur ants\",\"el ing\",\"Ġacknowled ged\",\"Ġthe r\",\"Ġgen es\",\"ch ing\",\"He y\",\"Ġtact ics\",\"ĠMex ican\",\"Ġv end\",\"Ġhe s\",\"qu er\",\"Ġnot ing\",\"ĠCamer on\",\"Ġtarget ing\",\"ro ck\",\"Ġcred its\",\"Ġemot ions\",\"Ġrepresent atives\",\"new s\",\"Ġlegisl ative\",\"Ġrem oving\",\"Ġtweet ed\",\"ĠCar ter\",\"ĠF ixed\",\"Ġfor cing\",\"Ġspeak er\",\"Ġm ales\",\"ĠViet nam\",\"l ined\",\"Ġconcept s\",\"Ġvo ices\",\"o ir\",\"ĠT rib\",\"W he\",\"ĠJer usalem\",\"ĠS ant\",\"Ġc ul\",\"Ġl ady\",\"ĠHaw ai\",\"Ġar ts\",\"ĠIn n\",\"ĠMach ine\",\"ĠEm peror\",\"Ġsl ot\",\"g ly\",\"ĠPro cess\",\"II I\",\"Ġathlet es\",\"ĠTem ple\",\"ĠRep resent\",\"Ġpres c\",\"Ġt ons\",\"Ġgold en\",\"Ġp unch\",\"ĠG R\",\"iver pool\",\"Ġen act\",\"Ġlob by\",\"Ġm os\",\"Ġpick ing\",\"Ġlif etime\",\"Ġcogn itive\",\"E ach\",\"z o\",\"Ġd ub\",\"Ġcons ists\",\"ol n\",\"Ġf estival\",\"am ous\",\"Ġint ellig\",\"w ords\",\"ĠSm art\",\"Ġde le\",\"Ġl apt\",\"Ġmag ical\",\"ĠS in\",\"b us\",\"ur ities\",\"igh th\",\"ĠRub y\",\"ĠS ure\",\"ol ving\",\"Ġj un\",\"O ST\",\"Ġimp osed\",\"Ġast ron\",\"Ġcor rel\",\"ĠN S\",\"ĠK it\",\"ĠF uture\",\"b urn\",\"Ġimm une\",\"oc us\",\"Ġcour ses\",\"ĠSt ring\",\"Ġle an\",\"Ġg host\",\"Ġout comes\",\"Ġexp ense\",\"Ġevery day\",\"Ġaccept able\",\"A h\",\"Ġequ ipped\",\"Ġor ange\",\"F R\",\"ĠD utch\",\"Th ough\",\"ĠR ank\",\"Q U\",\"ĠRober ts\",\"wh at\",\"re nd\",\"Ġdisapp ear\",\"Ġsp awn\",\"ĠL am\",\"o is\",\"Ġdes erve\",\"Ġmin imal\",\"Ġnerv ous\",\"ĠW ould\",\"Ġro ok\",\"ĠV ancouver\",\"Ġres ign\",\"sh ire\",\"ĠW orks\",\"ĠB uild\",\"Ġafford able\",\"ĠG ary\",\"ĠAren a\",\"Ġh anging\",\"Ġimpl ications\",\"ĠS ong\",\"Ġmain taining\",\"Ġgu ards\",\"C ON\",\"Ġder ived\",\"Ġexecut ed\",\"Ġthe ories\",\"Ġqu oted\",\"ĠAnd re\",\"og a\",\"sel ess\",\"in fo\",\"ĠBel g\",\"Ġt ears\",\"ĠSur v\",\"Ġbirth day\",\"ig ious\",\"im mer\",\"Ġspect rum\",\"Ġarchitect ure\",\"Ġrec ruit\",\"arm a\",\"T able\",\"Ġmon sters\",\"ĠG ov\",\"Ġdest ination\",\"Ġattract ive\",\"Ġf oss\",\"ĠMore over\",\"Ġpres ents\",\"TH E\",\"Ġrep ly\",\"pt on\",\"Ġc um\",\"Ġdel ight\",\"Ġaffect s\",\"Ġdon ations\",\"ĠT oy\",\"ĠH im\",\"M ENT\",\"Ġover come\",\"it ched\",\"ĠFant asy\",\"ĠH at\",\"ĠBe ast\",\"b ott\",\"Ġinvestig ations\",\"R un\",\"Ġhun ting\",\"d i\",\"f und\",\"Ġs essions\",\"est yle\",\"Ġport ray\",\"oid s\",\"Y eah\",\"Ġcommun icate\",\"Ġcom edy\",\"ĠY ang\",\"Ġbel t\",\"ĠMar ine\",\"Ġpredict ed\",\"Pl ay\",\"Ġimportant ly\",\"Ġremark able\",\"Ġelim inate\",\"D avid\",\"Ġb ind\",\"V ID\",\"Ġadvoc ates\",\"ĠG aza\",\"im p\",\"D B\",\"ĠN a\",\"ĠSim ilar\",\"I ES\",\"Ġchar ity\",\"v as\",\"m ath\",\"Ġâ ĸ\",\"ok er\",\"nd um\",\"Ġcap s\",\"ĠH al\",\"2 000\",\"e an\",\"Ġfle et\",\"Ġrec re\",\"R ight\",\"Ġsleep ing\",\"ij ing\",\"k ind\",\"Ġdesign ated\",\"Ã ¤\",\"Ġanim ation\",\"ke e\",\"ĠInt rodu\",\"Ġ/ >\",\"Ġdelay ed\",\"Ġtrem end\",\"Ġcur ious\",\"U se\",\"Ġle ct\",\"d am\",\"Ġinnov ation\",\"ĠPoint s\",\"Ġload ing\",\"Ġdisp ute\",\"ct ic\",\"ird s\",\"ĠB Y\",\"Ġn urs\",\"ĠVal ue\",\"ION S\",\"ĠH um\",\"Ġtem plate\",\"m ers\",\"Ġappear ances\",\"ĠEnter tainment\",\"Ġtransl ation\",\"Ġsa ke\",\"Ġbene ath\",\"Ġin hib\",\"Ġe uro\",\"abet es\",\"Ġstud ying\",\"ĠM as\",\"Ġper ceived\",\"Ġexam ined\",\"Ġe ager\",\"Ġco aches\",\"Ġim per\",\"ch i\",\"Ġprodu ces\",\"\\\" ).\",\"ĠEvery one\",\"Ġm unicip\",\"Ġg irlfriend\",\"Ġh ire\",\"ĠV ice\",\"Ġsu itable\",\"op y\",\"Ġin equ\",\"ĠD uke\",\"f ish\",\"f irst\",\"ĠO bs\",\"Ġinter ior\",\"ĠBru ce\",\"ĠR y\",\"Ġanal ys\",\"Ġconsider able\",\"Ġfore cast\",\"Ġf ert\",\"ors hip\",\"ĠD rug\",\"ĠA LL\",\": \\\"\",\"th ur\",\"ĠM ail\",\"Ġball ot\",\"Ġinst antly\",\"ĠCh annel\",\"Ġp icks\",\"Ġ198 9\",\"Ġt ent\",\"ol i\",\"Ġcivil ian\",\"b ling\",\"ell o\",\"b u\",\"Ġin ch\",\"Ġlog o\",\"Ġcooper ation\",\"Ġwal ks\",\"Ġinvest ments\",\"Ġimp rison\",\"ĠF estival\",\"ĠK y\",\"Ġleg ally\",\"Ġg ri\",\"ch arg\",\"S l\",\"Ġthreat ening\",\"du ction\",\"fl ow\",\"Ġdismiss ed\",\"ibr aries\",\"c ap\",\"e le\",\"ĠMc G\",\"ĠHar vard\",\"ĠConserv ative\",\"ĠC BS\",\"p ng\",\"Ġro ots\",\"ĠH aving\",\"umb led\",\"ĠF un\",\"\\\\ /\",\"ĠS earch\",\"ple x\",\"Ġdiscuss ing\",\"Ġcontin u\",\"ĠT ai\",\"ĠW ik\",\"F ree\",\"f it\",\"Ġref use\",\"Ġmanag ing\",\"Ġsy nd\",\"ip edia\",\"w alk\",\"Ġprofession als\",\"Ġguid ance\",\"Ġunivers ities\",\"Ġas semb\",\"unt u\",\"F inally\",\"AS E\",\"ĠAut o\",\"ĠH ad\",\"Ġann iversary\",\"L D\",\"ĠD ur\",\"ĠUlt imate\",\"ih ad\",\"pro duct\",\"Ġtrans it\",\"Ġrest ore\",\"Ġexpl aining\",\"Ġass et\",\"Ġtransfer red\",\"Ġbur st\",\"ap olis\",\"ĠMag azine\",\"ĠC ra\",\"ĠB R\",\"gg ed\",\"ĠH E\",\"M ich\",\"b et\",\"ĠL ady\",\"yl um\",\"erv es\",\"Ġme ets\",\"wh ite\",\"L og\",\"Ġcorrespond ing\",\"Ġins isted\",\"G G\",\"Ġsurround ed\",\"Ġt ens\",\"Ġl ane\",\"Ġco inc\",\"h ome\",\"Ġexist ed\",\"ect ed\",\"ĠDou ble\",\"lam m\",\"Ġske pt\",\"ex p\",\"Ġper ception\",\"ie v\",\"ĠBe ing\",\"o ft\",\"Ġadop t\",\". :\",\"] ;\",\"Wind ows\",\"Ġsatell ite\",\"AS H\",\"Ġinf ant\",\"d escription\",\"ĠMe anwhile\",\"c m\",\"oc a\",\"ĠT reat\",\"act or\",\"Ġtob acco\",\"ĠN orm\",\"em ption\",\"Ġfl esh\",\"Ġj e\",\"o op\",\"ĠHe aven\",\"Ġbe ating\",\"an im\",\"Ġgather ing\",\"Ġcult iv\",\"G O\",\"ab e\",\"ĠJon athan\",\"ĠSaf ety\",\"Ġbad ly\",\"pro t\",\"Ġcho osing\",\"Ġcontact ed\",\"Ġqu it\",\"Ġdist ur\",\"Ġst ir\",\"Ġto ken\",\"D et\",\"ĠP a\",\"Ġfunction ality\",\"00 3\",\"s ome\",\"Ġlimit ations\",\"Ġmet h\",\"b uild\",\"con fig\",\"N T\",\"re ll\",\"ble m\",\"ĠM om\",\"Ġveter ans\",\"ĠH u\",\"Ġtrend s\",\"are r\",\"ĠG iven\",\"ĠCa ption\",\"m ay\",\"AS T\",\"Ġwond ering\",\"ĠCl ark\",\"n ormal\",\"Ġsepar ated\",\"Ġdes p\",\"st ic\",\"b rew\",\"Ġrel ating\",\"ĠN ik\",\"ĠF arm\",\"Ġenthus i\",\"g ood\",\"d eb\",\"Ġactiv ist\",\"Ġm art\",\"Ġexplos ion\",\"ĠEconom ic\",\"L ink\",\"Ġins ight\",\"Ġconven ient\",\"Ġcounter part\",\"su pport\",\"ĠV irt\",\"ag en\",\"ĠTenn essee\",\"ĠSim on\",\"ĠA ward\",\"OC K\",\"ĠF igure\",\"Ġoverse as\",\"Ġpr ide\",\"ĠC as\",\"n ote\",\"m g\",\"C urrent\",\"Ġdispl ays\",\"cont ent\",\"Ġtravel ing\",\"Ġhosp itals\",\"ĠFin ancial\",\"ĠP ast\",\"Ġdefend ant\",\"Ġstream ing\",\"m ble\",\"ĠBer lin\",\"uk i\",\"Ġdist ribut\",\"Ġant ib\",\"Ġch ocolate\",\"ĠCast le\",\"Ġinter rupt\",\"ĠR ow\",\"Ġconvers ion\",\"Ġbug s\",\"ĠR ather\",\"li est\",\"L Y\",\"ĠJe an\",\"com mon\",\"ak h\",\"Ġ1 30\",\"ot ton\",\"ĠDe an\",\"Ġam endment\",\"Ġgame play\",\"ĠWar ren\",\"od a\",\"Ġhigh lights\",\"Ġir re\",\"ĠNAT O\",\"Ġball s\",\"Ġdemand ing\",\"U RE\",\"ĠL uke\",\"F igure\",\"st op\",\"on ia\",\"z one\",\"iz ers\",\"ĠW R\",\"Ġaward ed\",\"Ġregul atory\",\"ĠH art\",\"ĠS N\",\"pl ing\",\"Ġs our\",\"ĠP ixel\",\"us ive\",\"Ġf et\",\"ĠS ent\",\"Ġautom atic\",\"Ġf er\",\"vern ment\",\"ĠKh an\",\"T ON\",\"f ather\",\"Ġextraord inary\",\"th rop\",\"ĠP ython\",\"ĠG PU\",\"Ġsex ually\",\"Ġdesk top\",\"it ivity\",\"ĠAnton io\",\"Ġo rient\",\"Ġe ars\",\"ob by\",\"ous es\",\"vertis ements\",\"Ġmanufacture rs\",\"ic ient\",\"min ute\",\"Ġconv iction\",\"Ġg arden\",\"p ublic\",\"Ġsatisf ied\",\"f old\",\"O K\",\"Ġin hab\",\"ĠTh ink\",\"Ġprogram me\",\"Ġst omach\",\"Ġcoord in\",\"Ġh oly\",\"Ġth reshold\",\"Ġr het\",\"Ġser ial\",\"Ġemploy ers\",\"ĠEvery thing\",\"ra h\",\"Ġb other\",\"Ġbr ands\",\"Val ue\",\"ĠT ed\",\"ĠPlan et\",\"Ġp ink\",\"ĠFurther more\",\"s a\",\"P E\",\"re ck\",\"ĠUS D\",\"ot te\",\"Ġ& &\",\"Ġland ed\",\"g ets\",\"Ġprodu cers\",\"Ġhealth care\",\"Ġdomin ant\",\"Ġdest ro\",\"Ġam ended\",\"ch ron\",\"Ġf its\",\"ĠSy d\",\"ĠAuthor ity\",\"AT CH\",\"Ġfight s\",\"ĠL LC\",\"Ġ-- -\",\"ĠCor p\",\"Ġtox ic\",\"spe cific\",\"ĠC orn\",\"ĠChe l\",\"Ġtele phone\",\"ĠP ant\",\"Ġmyster ious\",\"aun ch\",\"od ox\",\"med ia\",\"Ġwitness es\",\"ag u\",\"Ġquestion ed\",\"ĠBre xit\",\"ĠRem ember\",\"ene z\",\"Ġend orse\",\"iat ric\",\"ĠId ent\",\"Ġridic ulous\",\"1 10\",\"Ġpr ayer\",\"Ġscient ist\",\"Ġ19 50\",\"ĠA qu\",\"Ġunder ground\",\"ĠU FC\",\"m are\",\"ĠL ater\",\"w ich\",\"Ġsubsc rib\",\"Ġhost s\",\"Ġer r\",\"Ġgr ants\",\"ant om\",\"Ġsum mon\",\"ear ly\",\"ĠC lear\",\"ĠPr im\",\"Ġsusp ension\",\"Ġguarant eed\",\"app er\",\"Ġr ice\",\"ĠSe an\",\"ĠSh in\",\"Ġrefere ndum\",\"Ġfl ed\",\"r ust\",\"Ġ3 60\",\"ter y\",\"Ġsh ocked\",\"B R\",\"ĠO il\",\"ĠAll ah\",\"Ġpart ly\",\"Ġign or\",\"Ġtrans mission\",\"Ġhom osexual\",\"ivers al\",\"Ġhop efully\",\"ãĤ ¤\",\"Ġless on\",\"L eg\",\"Ġ ..\",\"Y et\",\"t able\",\"app ropri\",\"re tt\",\"Ġbo ards\",\"Ġincor rect\",\"Ġb acteria\",\"ar u\",\"am ac\",\"Ġsn ap\",\".' \\\"\",\"Ġpar ad\",\"t em\",\"he art\",\"Ġav ailability\",\"Ġw isdom\",\"Ġ( +\",\"Ġpri est\",\"ĠÂł ĠÂł\",\"O pen\",\"Ġsp an\",\"Ġparam eter\",\"Ġconv ince\",\"Ġ( %)\",\"r ac\",\"Ġf o\",\"Ġsafe ly\",\"Ġconver ted\",\"ĠOlymp ic\",\"Ġres erve\",\"Ġhe aling\",\"ĠM ine\",\"M ax\",\"Ġin herent\",\"ĠGra ham\",\"Ġinteg rated\",\"D em\",\"Ġpip eline\",\"Ġapp lying\",\"Ġem bed\",\"ĠCharl ie\",\"Ġc ave\",\"200 8\",\"Ġcons ensus\",\"Ġre wards\",\"P al\",\"ĠHT ML\",\"Ġpopular ity\",\"look ing\",\"ĠSw ord\",\"ĠAr ts\",\"' )\",\"Ġelect ron\",\"clus ions\",\"Ġinteg rity\",\"Ġexclus ively\",\"Ġgr ace\",\"Ġtort ure\",\"Ġburn ed\",\"tw o\",\"Ġ18 0\",\"P rodu\",\"Ġent reprene\",\"raph ics\",\"Ġg ym\",\"ric ane\",\"ĠT am\",\"Ġadministr ative\",\"Ġmanufacture r\",\"Ġ vel\",\"ĠN i\",\"Ġisol ated\",\"ĠMedic ine\",\"Ġback up\",\"Ġpromot ing\",\"Ġcommand er\",\"Ġfle e\",\"ĠRus sell\",\"Ġforg otten\",\"ĠMiss ouri\",\"Ġres idence\",\"m ons\",\"Ġrese mb\",\"Ġw and\",\"Ġmeaning ful\",\"P T\",\"Ġb ol\",\"Ġhe lic\",\"Ġwealth y\",\"Ġr ifle\",\"str ong\",\"row ing\",\"pl an\",\"as ury\",\"âĢ¦ .\",\"Ġexpand ing\",\"ĠHam ilton\",\"Ġrece ives\",\"S I\",\"eat ures\",\"ĠAn im\",\"RE E\",\"P ut\",\"Ġbrief ly\",\"ri ve\",\"Ġstim ul\",\"Ġ`` (\",\"Ġ __\",\"Ġch ip\",\"Ġha z\",\"Ġpri ze\",\"ĠTh ings\",\"AC E\",\"ul in\",\"d ict\",\"ok u\",\"Ġassoci ate\",\"ock ets\",\"y outube\",\"St ory\",\"ateg ory\",\"Ġm ild\",\"ail ing\",\"ĠY e\",\"O rig\",\"ĠK a\",\"or ig\",\"Ġpropag anda\",\"Ġan onymous\",\"Ġstrugg led\",\"Ġout rage\",\"AT ED\",\"ĠBe ijing\",\"r ary\",\"Ġle ather\",\"Ġworld s\",\"Ġbroad er\",\"12 5\",\"id al\",\"ĠBet ter\",\"Ġt ear\",\"E xt\",\"Ġpropos als\",\"Ġit er\",\"ĠSqu ad\",\"Ġvol unt\",\"m i\",\"D id\",\"ĠP u\",\"p in\",\"Ġspeak ers\",\"Ġb orders\",\"Ġfig ured\",\"= '\",\"Ġsimultane ously\",\"aed a\",\"Ġcharg ing\",\"Ġur ged\",\"Ġcon j\",\"25 6\",\"ĠG ordon\",\"mer ce\",\"Ġdocument ary\",\"Sh are\",\"it ol\",\"ON E\",\"ĠG arden\",\"h att\",\"ĠThom pson\",\"ane ous\",\"ap ore\",\"Ġt anks\",\"Ġless ons\",\"tr ack\",\"Ġout standing\",\"Ġvolunte ers\",\"Ġsp ray\",\"Ġmanag ers\",\"l arge\",\"Ġcamp s\",\"Ġart ificial\",\"ĠR u\",\"Ġb ags\",\"th al\",\"Ġcompat ible\",\"ĠBl ade\",\"Ġf ed\",\"Ġarg ues\",\"F I\",\"Ġunf air\",\"Ġcor n\",\"Ġoff set\",\"Ġdirect ions\",\"Ġdisappoint ed\",\"ĠCon vention\",\"Ġview ing\",\"M E\",\"oc ity\",\"Ġtown s\",\"Ġlay ers\",\"Ġro lled\",\"Ġjump ed\",\"Ġatt ribute\",\"Ġun necess\",\"inc oln\",\"Ġsupp ose\",\"ĠNet her\",\"ch a\",\"Ġbur ied\",\"Ġsix th\",\"B en\",\"ress ing\",\"OU R\",\"Ġw ound\",\"Ġcy cl\",\"Ġmechan isms\",\"Ġcongress ional\",\"ĠE lement\",\"Ġagre ements\",\"Ġdec or\",\"Ġclos est\",\"ĠM it\",\"Go ogle\",\"} }\",\"Ġm ixture\",\"Ġflu id\",\"S ign\",\"ĠSch olar\",\"Ġp ist\",\"ask et\",\"ab ling\",\"Ġrac ing\",\"he ro\",\"ri el\",\"ass y\",\"Ġche aper\",\"b en\",\"Ġvert ical\",\"amac are\",\"ĠRead ing\",\"g ments\",\"Ġhelic op\",\"Ġsacr ifice\",\"ay a\",\"p aren\",\"V A\",\"ĠL es\",\"ĠStud io\",\"Ġviol ations\",\"ĠAn na\",\"ac er\",\"é ¾\",\"ĠR at\",\"ĠBe ck\",\"ĠD ick\",\"ĠA CT\",\"Ġcomp osition\",\"Ġtext ure\",\"ĠO wn\",\"Ġsmart phone\",\"ĠN A\",\"Ġfor b\",\"im port\",\"Ġdef ending\",\"il st\",\"re r\",\"Ġo h\",\"ĠJere my\",\"Ġbank ing\",\"cept ions\",\"Ġrespect ive\",\"/ .\",\"Ġdr inks\",\"ĠW i\",\"Ġb ands\",\"ĠL iverpool\",\"Ġg rip\",\"ĠB uy\",\"Ġopen ly\",\"Ġreview ed\",\"per t\",\"Ġver ify\",\"ĠCo le\",\"ĠW ales\",\"M O\",\"Ġun pre\",\"Ġshel ter\",\"ĠIm perial\",\"Ġgu i\",\"ĠD ak\",\"Ġsuggest ions\",\"Ġexplicit ly\",\"Ġsl ave\",\"Ġblock chain\",\"Ġcompet ing\",\"Ġprom ising\",\"S ON\",\"Ġsoc cer\",\"Ġconst itution\",\"4 29\",\"Ġdist ract\",\"ĠU ser\",\"es ides\",\"ĠMet hod\",\"ĠTok yo\",\"Ġaccompan ied\",\"Cl ient\",\"s ur\",\"al og\",\"Ġident ification\",\"Ġinv asion\",\"as ma\",\"Ġindust ries\",\"pp ers\",\"Ġsub tle\",\"ĠUn it\",\"n atural\",\"Ġsurv ived\",\"Ġfl aw\",\"ĺ ħ\",\"ĠH oll\",\"Ġdef icit\",\"Ġtut orial\",\"ĠCh ance\",\"Ġarg uing\",\"Ġcontem porary\",\"Ġinteg ration\",\"for ward\",\"Ġt um\",\"it is\",\"Ġh iding\",\"ĠD omin\",\"ĠT an\",\"ĠB uilding\",\"ĠV in\",\"Ġspokes person\",\"ĠNot es\",\"Ġemer ging\",\"Ġprepar ation\",\"Ġpro st\",\"Ġsuspect s\",\"Ġaut onom\",\"D escription\",\"Ġdeal t\",\"ĠP ear\",\"Ġstead y\",\"Ġdecre ased\",\"Ġso vere\",\"ĠCl in\",\"Ġgrad ually\",\"ors es\",\"ĠW AR\",\"S erv\",\"ãĤ ¢\",\"h r\",\"Ġd irty\",\"ĠB arn\",\"ĠB C\",\"Ġd il\",\"Ġcal endar\",\"Ġcompl iance\",\"Ġch amber\",\"b b\",\"Ġpass enger\",\"ate ful\",\"ĠT itle\",\"ĠSyd ney\",\"ĠG ot\",\"Ġdark ness\",\"Ġdef ect\",\"Ġpack ed\",\"ass ion\",\"Ġgod s\",\"Ġh arsh\",\"IC K\",\"le ans\",\"Ġalgorith m\",\"Ġoxy gen\",\"Ġvis its\",\"Ġbl ade\",\"Ġkil omet\",\"ĠKent ucky\",\"Ġkill er\",\"P ack\",\"enn y\",\"Ġdiv ine\",\"Ġnom ination\",\"be ing\",\"Ġeng ines\",\"Ġc ats\",\"Ġbuff er\",\"ĠPh ill\",\"Ġtra ff\",\"AG E\",\"Ġtong ue\",\"Ġrad iation\",\"ere r\",\"m em\",\"ĠExpl icit\",\"é¾ į\",\"Ġcou ples\",\"Ġphys ics\",\"ĠMc K\",\"Ġpolit ically\",\"aw ks\",\"ĠBl oom\",\"Ġwor ship\",\"e ger\",\"ut er\",\"ĠF O\",\"Ġmat hemat\",\"Ġsent enced\",\"Ġdis k\",\"ĠM arg\",\"Ġ/ *\",\"P I\",\"Ġoption al\",\"Ġbab ies\",\"Ġse eds\",\"ĠScott ish\",\"Ġth y\",\"] ]\",\"ĠHit ler\",\"P H\",\"ng th\",\"Ġrec overed\",\"ing e\",\"Ġpow der\",\"Ġl ips\",\"Ġdesign er\",\"Ġdis orders\",\"Ġcour age\",\"Ġch aos\",\"\\\" },{\\\"\",\"Ġcar rier\",\"b ably\",\"H igh\",\"ĠR T\",\"es ity\",\"l en\",\"Ġrout es\",\"u ating\",\"F il\",\"N OT\",\"w all\",\"s burgh\",\"Ġeng aging\",\"ĠJava Script\",\"ore r\",\"li hood\",\"Ġun ions\",\"ĠF ederation\",\"ĠTes la\",\"Ġcomple tion\",\"ĠT a\",\"Ġprivile ge\",\"ĠOr ange\",\"Ġne ur\",\"paren cy\",\"Ġb ones\",\"Ġtit led\",\"Ġprosecut ors\",\"ĠM E\",\"Ġengine er\",\"ĠUn iverse\",\"ĠH ig\",\"n ie\",\"o ard\",\"Ġheart s\",\"ĠG re\",\"uss ion\",\"Ġmin istry\",\"Ġpen et\",\"ĠN ut\",\"ĠO w\",\"ĠX P\",\"in stein\",\"Ġbul k\",\"S ystem\",\"ic ism\",\"ĠMarket able\",\"Ġpre val\",\"Ġpost er\",\"Ġatt ending\",\"ur able\",\"Ġlicens ed\",\"ĠG h\",\"et ry\",\"ĠTrad able\",\"Ġbl ast\",\"à ¤\",\"ĠTit an\",\"ell ed\",\"d ie\",\"H ave\",\"ĠFl ame\",\"Ġprof ound\",\"Ġparticip ating\",\"Ġan ime\",\"ĠE ss\",\"Ġspec ify\",\"Ġregard ed\",\"ĠSpe ll\",\"Ġs ons\",\"own ed\",\"Ġm erc\",\"Ġexper imental\",\"land o\",\"h s\",\"ĠDun geon\",\"in os\",\"Ġcomp ly\",\"ĠSystem s\",\"ar th\",\"Ġse ized\",\"l ocal\",\"ĠGirl s\",\"ud o\",\"on ed\",\"ĠF le\",\"Ġconstruct ed\",\"Ġhost ed\",\"Ġsc ared\",\"act ic\",\"ĠIs lands\",\"ĠM ORE\",\"Ġbl ess\",\"Ġblock ing\",\"Ġch ips\",\"Ġev ac\",\"P s\",\"Ġcorpor ation\",\"Ġo x\",\"Ġlight ing\",\"Ġneighb ors\",\"ĠU b\",\"ar o\",\"Ġbe ef\",\"ĠU ber\",\"F acebook\",\"ar med\",\"it ate\",\"ĠR ating\",\"ĠQu ick\",\"Ġoccup ied\",\"Ġaim s\",\"ĠAdd itionally\",\"ĠInt erest\",\"Ġdram atically\",\"Ġhe al\",\"Ġpain ting\",\"Ġengine ers\",\"M M\",\"ĠM ust\",\"Ġquant ity\",\"P aul\",\"Ġearn ings\",\"ĠPost s\",\"st ra\",\"ãĥ¼ ãĥ\",\"Ġst ance\",\"Ġdro pping\",\"sc ript\",\"Ġd ressed\",\"M ake\",\"Ġjust ify\",\"ĠL td\",\"Ġprompt ed\",\"Ġscr ut\",\"Ġspeed s\",\"ĠGi ants\",\"om er\",\"ĠEd itor\",\"Ġdescrib ing\",\"ĠL ie\",\"ment ed\",\"Ġnow here\",\"oc aly\",\"Ġinst ruction\",\"fort able\",\"Ġent ities\",\"Ġc m\",\"ĠN atural\",\"Ġinqu iry\",\"Ġpress ed\",\"iz ont\",\"for ced\",\"Ġra ises\",\"ĠNet flix\",\"ĠS ide\",\"Ġout er\",\"Ġamong st\",\"im s\",\"ows ki\",\"Ġclim b\",\"ne ver\",\"Ġcomb ine\",\"d ing\",\"Ġcomp r\",\"Ġsignific ance\",\"Ġremem bered\",\"ĠNev ada\",\"ĠT el\",\"ĠSc ar\",\"ĠWar riors\",\"ĠJ ane\",\"Ġcou p\",\"b as\",\"Ġtermin al\",\", -\",\"O H\",\"Ġt ension\",\"Ġw ings\",\"ĠMy ster\",\"ï¿½ï¿½ ï¿½ï¿½\",\"ĠUn like\",\"val id\",\"viron ments\",\"ĠAl i\",\"Ġn aked\",\"book s\",\"ĠM un\",\"ĠG ulf\",\"Ġd ensity\",\"Ġdim in\",\"Ġdesper ate\",\"Ġpres idency\",\"Ġ198 6\",\"h y\",\"IN D\",\"Ġun lock\",\"im ens\",\"Ġhand led\",\"ĠE b\",\"Ġdisapp eared\",\"Ġgen re\",\"Ġ198 8\",\"Ġdetermin ation\",\"St ream\",\"ik o\",\"ap ters\",\"Ġacknow ledge\",\"J an\",\"Ġcapital ism\",\"P at\",\"Ġ20 20\",\"Ġpain ful\",\"Ġcur ve\",\"Ġbom bs\",\"st orm\",\"ĠMet al\",\"en cer\",\"ĠF ig\",\"ĠA aron\",\"anc hes\",\"Ġins piration\",\"Ġexha ust\",\"t ains\",\"ash i\",\"Ġdesc ript\",\"Ġr itual\",\"ĠChel sea\",\"Ġpromot ion\",\"ĠH ung\",\"ĠW ard\",\"iv a\",\"ĠE T\",\"Ġto ss\",\"all ow\",\"ĠFranc is\",\"D ep\",\"Ġhapp iness\",\"ĠGl ass\",\"Ġbet a\",\"Ġstreng then\",\"N E\",\"o a\",\"Ġbutt ons\",\"ĠMur ray\",\"Ġkick ed\",\"Qu est\",\"ĠT alk\",\"ĠS everal\",\"ĠZ ero\",\"Ġdr one\",\"ul k\",\"Ġc am\",\"ĠM obile\",\"Ġprevent ing\",\"Ġret ro\",\"ĠA x\",\"Ġcru el\",\"Ġflo at\",\". ),\",\"Ġfil ing\",\"ĠGr ant\",\"ĠB or\",\"Ġr ib\",\"Ġchampions hip\",\"ĠM erc\",\"Ġsty les\",\"Ġc ake\",\"Ġbuild s\",\"ĠS elf\",\"io x\",\"Ġep ic\",\"oy d\",\"B el\",\"ĠSt ew\",\". (\",\"ah u\",\"ĠBe yond\",\"Ġout s\",\"Ġsol o\",\"ĠT ree\",\"Ġpres erve\",\"Ġt ub\",\"AR E\",\"ro c\",\"ĠIm pro\",\"ĠW right\",\"Ġbu nd\",\"Ġtr aged\",\"Ġoccas ional\",\"b ian\",\"Sec ond\",\"r ons\",\"Ġinter actions\",\"form ed\",\"s ing\",\"Ġown s\",\"Ġh ockey\",\"Gener al\",\"Ġlog ical\",\"Ġexp end\",\"Ġesc al\",\"ĠGr iff\",\"ĠC rown\",\"ĠRes erve\",\"Ġsto pping\",\"Ġexc use\",\"sec ond\",\"Ġoper ated\",\"Ġre aches\",\"ĠMal ays\",\"Ġpoll ution\",\"ĠBrook lyn\",\"Ġde lete\",\"Ġhas h\",\"Bl ock\",\"ah a\",\"âĢ ³\",\"Ġsh orter\",\"p iece\",\"> </\",\"Ġh orm\",\"ĠW at\",\"ĠBre ak\",\"Ġprohib ited\",\"Ġint ensity\",\"ĠAl an\",\"Ġli ability\",\"? !\",\"and ed\",\"Ġneigh bour\",\"ĠCol lection\",\"Ġf ires\",\"Ġrevolution ary\",\"f ly\",\"ĠOr leans\",\"Wh ite\",\"ĠW rit\",\"ĠD awn\",\"Ġsett le\",\"Ġexec ute\",\"B M\",\"Ġspokes woman\",\"Ġlif estyle\",\"Ġclick ing\",\"ĠK ill\",\"ĠLiber al\",\"ĠN azi\",\"Ġtra iler\",\"Ġmount ains\",\"Ġdam n\",\"z es\",\"p es\",\"Ġpress ing\",\"Ġb ail\",\"ĠOrgan ization\",\"Ġp ir\",\"Ġth irty\",\"Ġelect rical\",\"Ġ1 15\",\"ĠP oly\",\"ĠR ap\",\"ĠSt rike\",\"ĠC ann\",\"Ġdemand ed\",\"Ġback ing\",\"def ault\",\"spe ed\",\"ĠLeg isl\",\"Ġmother s\",\"ĠB ody\",\"Ġvar iation\",\"ced ented\",\"p owered\",\"le ading\",\"N ever\",\"Ġg rave\",\"ĠAnt i\",\"A W\",\"Ġinterview ed\",\"ĠG ab\",\"ĠF at\",\"Ġrook ie\",\"u u\",\"Ġdep os\",\"ix on\",\"Ġam pl\",\"ret ion\",\"ĠHe at\",\"Ġpeace ful\",\"S M\",\"ie ve\",\"Ġd iver\",\"ĠVict oria\",\"Ġm ic\",\"p df\",\"Ġst ating\",\"Ġl ung\",\"Ġcritic ized\",\"Ġvacc ine\",\"ĠLoad ing\",\"ur se\",\"T ake\",\"ĠFr an\",\"ĠS old\",\"ĠRob in\",\"Ġdetect ed\",\"ĠSc ript\",\"Ġadjust ed\",\"Ġsen ator\",\"Ġopp osing\",\"Er ror\",\"C ount\",\"Ġconflic ts\",\"Ġo w\",\"ĠAr gent\",\"Ġmatch ing\",\"h h\",\"ĠTre k\",\"st arter\",\"\\\" ),\",\"ĠA F\",\"od er\",\"xx xx\",\"ĠAl t\",\"ac re\",\"ĠP ick\",\"ĠSol ar\",\"ĠD al\",\"O ct\",\"ĠB att\",\"Ġs rc\",\"Ġeng agement\",\"Ġexecut ives\",\"Ġliber ty\",\"j ava\",\"Ġtal ented\",\"igen ous\",\"Ġcon secut\",\".. ...\",\"In fo\",\"Ġhor rible\",\"Ġsurprising ly\",\"f eed\",\"ic ating\",\"ĠL ED\",\"Ġfem ales\",\"St ation\",\"ell er\",\"ĠOak land\",\"Ġmechan ical\",\"i ology\",\"ĠV ar\",\"Ġrob ust\",\"ett ings\",\"ott a\",\"Ġthe oret\",\"Ġret ain\",\"k ward\",\"Ġd a\",\"Ġdeploy ed\",\"d el\",\"ĠAnd y\",\"Ġsubsc ribe\",\"we b\",\"Ġn a\",\"ĠMic hel\",\"Ġpart ially\",\"ĠCome y\",\"Ġc rown\",\"ĠM aj\",\"ĠBl u\",\"r ator\",\"D ay\",\"IN T\",\"Ġdocument ed\",\"ĠG DP\",\"g i\",\"che ll\",\"Ġbrut al\",\"ĠB ab\",\"st ration\",\"Ġthe ft\",\"Ġt ube\",\"@ @\",\"Ġqu ery\",\"ĠL incoln\",\"Ġpublish ing\",\"Ġw ore\",\"or ical\",\"Ġr ic\",\"Ġnot able\",\"Ġsubsequ ently\",\"ne x\",\"Ġobser ve\",\"ĠB oe\",\"Ġc odes\",\"m ain\",\"W H\",\"ĠS L\",\"Ġresident ial\",\"av an\",\"Ġm as\",\"are st\",\"ade on\",\"OU T\",\"Ġsoph istic\",\"ant e\",\"Ġc ens\",\"Ġ **\",\"Ġmort ality\",\"Ġyour s\",\"Ġoccas ions\",\"Ġrec alled\",\"ĠDri ver\",\"Ġv ocal\",\"Ġbath room\",\"Ġsh ops\",\"Ġcollabor ation\",\"ĠOb amacare\",\"ĠC ell\",\"Ch ar\",\"Su per\",\"C re\",\"Ġt ends\",\"Ġt orn\",\"Ġeconom ics\",\"a very\",\"ĠR aid\",\"ĠS em\",\"Ġshould ers\",\"Ġexpect ing\",\"Ġexam ination\",\"en ame\",\"ĠU I\",\"i ability\",\"ol as\",\"ĠAm b\",\"ĠD ra\",\"Ġmid field\",\"ĠI C\",\"Ġlay out\",\"Ġflo ating\",\"f i\",\"it ative\",\"Ġtremend ous\",\"Ġ Ð\",\"Ġab und\",\"W ork\",\"ĠLight ning\",\"Ġsimilar ly\",\"Ġconserv atives\",\"Ġpr ay\",\"B E\",\"iz arre\",\"Ġt empt\",\"Ġemphas is\",\"ĠMet ro\",\"Ġf ishing\",\"Ġmar ry\",\"ne g\",\"ĠStud y\",\"Ġrec k\",\"Ġdis pos\",\"on ing\",\"bs ite\",\"Ġsusp ic\",\"Ġmer ch\",\"ĠG ib\",\"ĠDes cription\",\"ĠD VD\",\"w he\",\"ĠY emen\",\"Ġen vironments\",\"oot ing\",\"ĠMod ern\",\"e u\",\"Ġreflect s\",\"Ġh oney\",\"Ġanaly st\",\"Ġg ut\",\"d ec\",\"A ction\",\"Ġhousehold s\",\"Ġst er\",\"Ġtem ple\",\"Ġreform s\",\"Ġfavour ite\",\"Ġdead line\",\"ĠL E\",\"Th ree\",\"ĠWith in\",\"A ug\",\"Ġnight s\",\"elt a\",\"Ġinv alid\",\"ĠEx change\",\"ĠDel hi\",\"w hen\",\"inc ome\",\"Ġ ðŁ\",\"Ġwire less\",\"sc ribe\",\"ist a\",\"Ġhost ile\",\"Ġall y\",\"Ġg ig\",\"Ġout lets\",\"ĠD or\",\"EM ENT\",\"Ġas h\",\"Ġab stract\",\"OR D\",\"ĠMot or\",\"Ġadv iser\",\"ist le\",\"Ġb ases\",\"Ġcourt esy\",\"Ġcross ing\",\"Ġcle ared\",\"Ġrefuge e\",\"cos ystem\",\"Ġthrow s\",\"f un\",\"bour ne\",\"d ays\",\"Ġdisag ree\",\"ĠN ative\",\"Ġreflect ed\",\"ĠF ast\",\"ĠY ellow\",\"ĠSing apore\",\"ĠR aven\",\"Ġembr ace\",\"ĠK u\",\"ĠC hen\",\"ĠEar ly\",\"Ġappoint ment\",\"ĠMin i\",\"it ement\",\"Ġpl acing\",\"Ġb icy\",\"S R\",\"Ġwh is\",\"S U\",\"Ġinvestig ated\",\"Ġphotograph s\",\"g ithub\",\"ĠBe at\",\"ĠR ing\",\"ig hed\",\"i ar\",\"Ġev olved\",\"eral d\",\"Ġd un\",\"Ġh ub\",\"I AL\",\"Ġencour aging\",\"ĠPr int\",\"ĠD ays\",\"Ġpro secution\",\"Ġp ants\",\"az y\",\"l ive\",\"Ġfoss il\",\"ĠJ u\",\"Ġro cks\",\"ud ge\",\"ĠR ace\",\"Ġg reet\",\"b ie\",\"Ġf illing\",\"ĠL en\",\"Ġdi abetes\",\"Ġfire arms\",\"um ing\",\"enez uel\",\"ĠB B\",\"Ġaccept ing\",\"AT H\",\"Ġres ort\",\"Ġh unt\",\"ri k\",\"uck er\",\"am ents\",\"Ġsust ained\",\"Ġcross ed\",\"Ġbreak fast\",\"Ġatt ributes\",\"lect ed\",\"at ile\",\"Ġv ibr\",\"ĠK al\",\"ars on\",\"op les\",\"Ġtou ched\",\"Ġdam ages\",\"Ġimp ressed\",\"ru p\",\"Ġan ch\",\"ĠAd ams\",\"H el\",\"ĠVict or\",\"Ġmount ed\",\"ĠC C\",\"Ġdelic ious\",\"sp an\",\"ell a\",\"Ġel abor\",\"am ples\",\"Ġdef ic\",\"Ġconstit u\",\"u ates\",\"ĠM ission\",\"ĠT her\",\"ĠMon ster\",\"b es\",\"Re uters\",\"ĠInd ones\",\"h ill\",\"mun ition\",\"Ġconfirm ation\",\"ĠCons ider\",\"ac ent\",\"Ġj et\",\"ĠEm ploy\",\"ĠGT X\",\"n an\",\"ĠSp ider\",\"Ġprocess or\",\"Ġpat ri\",\"ĠPent agon\",\"ĠRob inson\",\"Ġreal istic\",\"Ã ±\",\"Ġappear ing\",\"Ġp ipe\",\"om ed\",\"Ġf ru\",\"Ġaw ful\",\"Ġeval uation\",\"Ġintellig ent\",\"ĠC itiz\",\"Ġfund ra\",\"od ium\",\"Ġtwe ets\",\"Ġwor n\",\"pr ing\",\"Ġkid n\",\"Ġreb els\",\"ĠK am\",\"ĠNether lands\",\"ĠS W\",\"Ġacqu isition\",\"ĠM ale\",\"ãĥ ª\",\"omb ies\",\"Ġtrad em\",\"ĠStat us\",\"B re\",\"ĠTH IS\",\"Ġad verse\",\"ĠN EW\",\"s ign\",\"Ġorgan isation\",\"en c\",\"ĠHar per\",\"ap or\",\"ĠMem bers\",\"ĠPe ace\",\"ĠAir port\",\"ĠOther s\",\"Ġscr atch\",\"ĠP il\",\"Ġsens or\",\"Ġadop tion\",\"ĠHot el\",\"ĠDr ag\",\"Ġhonest ly\",\"Ġy ard\",\"ĠFor ces\",\"Ġpat ent\",\"Ġb ass\",\"Ġquiet ly\",\"Ġbreat hing\",\"Ġp ose\",\"i ors\",\"ĠJ ess\",\"st atic\",\"IT E\",\"O ffic\",\"Ġj ew\",\"w cs\",\"Ġ14 0\",\"Ġpre view\",\"ipp i\",\"Ġunf ortunately\",\"oke mon\",\"Ġh orn\",\"Ġre ass\",\"Ġpe er\",\"ock er\",\"Ġunt o\",\"ĠGr ay\",\"Ġclean ing\",\"Ġattract ed\",\"200 7\",\"P oint\",\"k ill\",\"ĠAg reement\",\"ur ches\",\"Ġhor r\",\"ĠMiss iss\",\"Ġworth y\",\"Ġfl owers\",\"t own\",\"d ll\",\"Ġre actions\",\"Ġde ce\",\"Ġindic ating\",\"M D\",\"Ġpre ference\",\"ĠM VP\",\"ess ional\",\"ĠT arget\",\"g ence\",\"ĠInd ians\",\"Ġm isc\",\"Ġfree ly\",\"Ġmus cles\",\"Ġline up\",\"Ġimpact s\",\"ous ing\",\"om i\",\"ac ular\",\"Ġcontro lling\",\"ag ine\",\"c ery\",\"he ll\",\"Ġrank ing\",\"ĠN ich\",\"ĠA ve\",\"12 8\",\"Ġhigh way\",\"Ġinc ons\",\"Ġb inding\",\"Ġstrugg les\",\"ĠPitt sburgh\",\"Ġgr ay\",\"r in\",\"Ġcom ics\",\"ĠS port\",\"Ġrel atives\",\"Ġfr ight\",\"Ġpro be\",\"ĠPort ug\",\"Ġv oc\",\"Ġt u\",\"ĠCor ps\",\"Ġposs ibilities\",\"Ġqual ify\",\"wcs store\",\"Ġl ibraries\",\"Ġm igrants\",\"Ġent ries\",\"Ġconsecut ive\",\"v als\",\"ĠChair man\",\"Ġh ill\",\"IM E\",\"ĠG ard\",\"Ġinequ ality\",\"f ox\",\"ĠS ave\",\"Ġc ort\",\"claim ed\",\"Ġtra its\",\"Ġp our\",\"Ġmiss iles\",\"Ġess ence\",\"Ġs ends\",\"Ġall iance\",\"Ġw ishes\",\"ĠChrist opher\",\"B ig\",\"N Y\",\"ĠJac ob\",\"s an\",\"ur red\",\"ĠS O\",\"ll y\",\"Ġadvoc ate\",\"ĠB ond\",\"Ġ\\\" /\",\"Us ing\",\"Ġdistrict s\",\"ĠG ate\",\"ĠB ir\",\"r idge\",\"ĠN az\",\"ĠR s\",\"bo ards\",\"ĠG a\",\"ĠRe agan\",\"Ġinflu enced\",\"1 000\",\"ap y\",\"Ġchalleng ed\",\"Ġb arg\",\"Ġfac ulty\",\"ĠF if\",\"Ġacqu ire\",\"A c\",\"Ġin sect\",\"Ġinstr uments\",\"Ġle af\",\"th odox\",\"M essage\",\"Ġt ale\",\"Ġthere by\",\"Ġtra p\",\"Ġstrong est\",\"ĠMil itary\",\"is ible\",\"Ġ198 4\",\"ethe less\",\"Ġflex ible\",\"Ġkill s\",\"Ġfin ishing\",\"ĠS ize\",\"Ġredu ces\",\"Ġep id\",\"Ġorient ation\",\"f ull\",\"Ġtr ace\",\"Ġl aser\",\"Ġopp ose\",\"Ġed iting\",\"Ġmoment um\",\"ä º\",\"sh ow\",\"V I\",\"ĠL ad\",\"Ġ198 5\",\"Ġmurd ered\",\"9 00\",\"ut her\",\"Ġprob ability\",\"ĠP oll\",\"Ġrel uct\",\"ĠChe m\",\"ĠMont real\",\"Ġadequ ate\",\"ĠPol and\",\"ĠSher iff\",\"um ph\",\"Ġo k\",\"Ġ 000\",\"Ġ\\\" [\",\"Ġoper ators\",\"ĠF er\",\"Ġmod es\",\"ĠE ve\",\"Ġdiscipl ine\",\"N ET\",\"H and\",\"Ġor al\",\"ĠW E\",\"em ail\",\"J P\",\"ĠPalestin ians\",\"Ġhe nce\",\"ĠL ess\",\"Ġover l\",\"d ig\",\"Ġintim id\",\"ĠCo al\",\"Ġr anging\",\"th a\",\"Ġdist ant\",\"Ġf ib\",\"ĠInd ex\",\"ĠW onder\",\"ĠP el\",\"hatt an\",\"ĠH ug\",\"Ã Ĺ\",\"ra it\",\"Ġwra pped\",\"ĠR PG\",\"Ġchemical s\",\"ĠM oney\",\"Ġfro zen\",\"Ġind irect\",\"ĠAgain st\",\"E nd\",\"Ġuncom fortable\",\"ĠGall ery\",\"ĠPost ed\",\"Ø §\",\"ond uct\",\"Ġconsequ ence\",\"Ġbit ter\",\"Ġ198 7\",\"p op\",\"Ġcount less\",\"ĠAl aska\",\"ff ff\",\"Ġdepart ure\",\"Ġref und\",\"ĠI an\",\"i ated\",\"Ġsee ks\",\"Ġmechan ics\",\"Ġjurisd iction\",\"lyn n\",\"Ġal ike\",\"ĠH unt\",\"ath on\",\"Ġres olved\",\"Ġc ache\",\"Ġdist inction\",\"d irect\",\"Ġenc ount\",\"ou b\",\"be at\",\"ĠCount ry\",\"se arch\",\"Ġcontin uous\",\"Ġmod est\",\"ĠR ail\",\"th ood\",\"1 30\",\"B UG\",\"Ġcrim inals\",\"Ġindic ation\",\"Ġencount ered\",\"l ast\",\"ĠW y\",\"Ġide ology\",\"ĠP DF\",\"sec urity\",\"] )\",\"ĠJim my\",\"ĠE N\",\"Ġh iring\",\"T em\",\"Ġp ig\",\"aun t\",\"ĠCry stal\",\"Ġpen alties\",\"Ġcap ability\",\"Ġp y\",\"Ġproduct ive\",\"Ġbal anced\",\"ĠGe Force\",\"cl ick\",\"olit an\",\"od s\",\"Ġafter wards\",\"Ġplay offs\",\"ĠG ill\",\"U ser\",\"Ġback s\",\"p ub\",\"t ag\",\"Ġabs urd\",\"p iring\",\"Ġc iting\",\"Ġtr illion\",\"Ġoblig ation\",\"Ġmax im\",\"ah oo\",\"c f\",\"um i\",\"ĠAl pha\",\"ĠN elson\",\"Ġpursu ant\",\"in itely\",\"Ġf ract\",\"ent ry\",\"ber y\",\"ĠTh or\",\"Add ed\",\"ĠD J\",\"ĠG ene\",\"Ġaw kward\",\"St ud\",\"Ġwal let\",\"ĠDiv ine\",\"ari os\",\"Ġrele asing\",\"Ġed ited\",\"Ġaccompl ished\",\"B est\",\"Ġed ges\",\"Ġplan es\",\"Ġfeed ing\",\"\\\" },\\\"\",\"Ġdiscl osure\",\"Ġgr ain\",\"air y\",\"o ons\",\"ern and\",\"V R\",\"Ġreason ably\",\"Ġdr um\",\"Ġpart ial\",\"Ġgraph ic\",\"Ġunpre cedented\",\"Ġadv ised\",\"M icro\",\"ĠAss ad\",\"point s\",\"sc ar\",\"ĠZ one\",\"tt es\",\"Ġ7 00\",\"v o\",\"ĠH amp\",\"Ġfix es\",\"Ġca ution\",\"Ġstr ings\",\"Ġpan els\",\"Ġle ak\",\"Ġpr icing\",\"row th\",\"ĠEr ror\",\"ĠS aints\",\"f ix\",\"Ġobserv ations\",\"ĠA bs\",\"Ġsuggest ion\",\"ĠUkrain ian\",\"Ġbar rier\",\"Ġpain ted\",\"B et\",\"im ir\",\"ĠS pect\",\"p ot\",\"orne ys\",\"Ġcomp ound\",\"Ġbe ars\",\"ĠR ush\",\"Ġlux ury\",\"S um\",\"Ġor bit\",\"ĠMar c\",\"Ġex empt\",\"ĠTra il\",\"ĠM O\",\"ĠH ans\",\"ĠWe apon\",\"oc used\",\"umin um\",\"ĠJer ry\",\"Ġb ust\",\"ĠA G\",\"ĠW iki\",\"Ġend less\",\"ĠV lad\",\"ĠB ah\",\"ĠR adeon\",\"ke ys\",\"ĠSur vey\",\"ĠV iol\",\"def ine\",\"le an\",\"Ġcomm od\",\"Ġreven ues\",\"Å į\",\"Ġfurn iture\",\"Ġcast ing\",\"Ġdiplom atic\",\"ĠPlay ers\",\"ĠK illed\",\"Ġmod ify\",\"Ġinnov ative\",\"ĠAb u\",\"n or\",\"Ġbond s\",\"Ġcoach ing\",\"M er\",\"Ġmod ules\",\"ĠPatri ots\",\"Ġenh anced\",\"Ġproceed ings\",\"Ġteam mates\",\"Ġ12 8\",\"ard o\",\"Ġcomprom ise\",\"ĠM uch\",\"Ġfle w\",\"ĠEd ge\",\"Ġunnecess ary\",\"Ġdoct rine\",\"re port\",\"ĠOr lando\",\"ĠProf ile\",\"Ġplay off\",\"friend ly\",\"Ġcompl ain\",\"ĠM C\",\"ĠO pt\",\"ĠG B\",\"Ġbeat en\",\"Ġg olf\",\"Ġpl acement\",\"B it\",\"Ġnews letter\",\"Ġ201 9\",\"vis or\",\"raw l\",\"ĠiP ad\",\"Ġact ed\",\"Ġju ice\",\"Ġdec ks\",\"P N\",\"su ccess\",\"ĠH alf\",\"Ġdele ted\",\"Ġsec rets\",\"Ġas ylum\",\"M art\",\"ĠAct iv\",\"ĠGu y\",\"ĠT s\",\"Ġd ys\",\"Ġassum ing\",\"Ġman a\",\"Ġsub ur\",\"Ġ12 5\",\"M edia\",\"AR Y\",\"r ide\",\"c p\",\"Ġdifficult ies\",\"Ġcollect ing\",\"Ġbank rupt\",\"n on\",\"Ġcomp osed\",\"Ġvol t\",\"Ġmilit ants\",\"Ġ> >>\",\"ĠM ormon\",\"t or\",\"Ġpartic les\",\"ĠB art\",\"ry ption\",\"Ġad min\",\"Ġsqu ee\",\"VID IA\",\"Ġcreat or\",\"iam eter\",\"ic ular\",\"N BC\",\"Ġgrab bed\",\"Ġn odd\",\"Ġr ated\",\"Ġrot ation\",\"Ġgr asp\",\"Ġexcess ive\",\"ĠE C\",\"ĠWh it\",\"Ġinvent ory\",\"ault s\",\"ĠF B\",\"Ġe cosystem\",\"Ġbill ions\",\"Ġvent ure\",\"n amed\",\"Ġdef ender\",\"out e\",\"Inst ead\",\"ir able\",\"W ar\",\"Ġassum ption\",\"Ġb ite\",\"Ġearth qu\",\"t ail\",\"sp ace\",\"Ġgif ts\",\"boy s\",\"Ġinev itable\",\"Ġstruct ural\",\"Ġbenef icial\",\"Ġcompe lling\",\"h ole\",\"erv ation\",\"Ġco at\",\"o j\",\"inc arn\",\"ĠY ears\",\"Ġdetermin ing\",\"Ġrhet oric\",\"Ġbound aries\",\"Ġwh ites\",\"A nt\",\"add y\",\") -\",\"ra ham\",\"eter min\",\"Ġhar vest\",\"ĠCon c\",\"Ġlapt op\",\"ĠM atch\",\"Ġenjoy ing\",\"cc a\",\"oll ar\",\"Ġtri ps\",\"Ġadd iction\",\"ĠS ak\",\"Ġpow ered\",\"Ġc ous\",\"ĠRuss ians\",\"ie re\",\"Ġret rie\",\"qu ality\",\"Ġdiff er\",\"Ġking dom\",\"ĠL aur\",\"ĠCap itol\",\"Ġcon clusions\",\"ĠAl tern\",\"ĠN av\",\"Ġtrans parent\",\"B ER\",\"G roup\",\"ĠCom plete\",\"Ġinf er\",\"Ġint rig\",\"Ġins ane\",\"R O\",\"oph ob\",\"is en\",\"qu al\",\"Mich ael\",\"Ġm useum\",\"ĠP ope\",\"Ġres et\",\"r ative\",\"f ive\",\"Ġagg reg\",\"itte es\",\"osit ory\",\"Ġcar b\",\"ĠRec ord\",\"Ġdec ides\",\"ĠF ix\",\"Ġexcept ions\",\"ĠCommission er\",\"un s\",\"ĠEnvironment al\",\"Ġlegend ary\",\"ist ence\",\"Ġtun nel\",\"k m\",\"Ġins ult\",\"Ġt roll\",\"Ġsh ake\",\"Ġdet ention\",\"qu es\",\"ĠCh rome\",\"ĠF iles\",\"Ġsub t\",\"Ġprospect s\",\"Ġpro l\",\"re nder\",\"pro of\",\"Ġperform ances\",\"St r\",\"Ġh ref\",\"ern ame\",\"Ġachieve ment\",\"Ġf ut\",\"F ull\",\"ĠLe ban\",\"go ogle\",\"ãĥ Ī\",\"amp a\",\"May be\",\"Ġproject ed\",\"ĠE mb\",\"Ġcol leg\",\"Ġa wards\",\"Ġâ Ķ\",\"G old\",\"ĠBl ake\",\"ĠR aj\",\"if ting\",\"Ġp ending\",\"Ġinst inct\",\"Ġdevelop ments\",\"Con nect\",\"ĠM and\",\"ĠW ITH\",\"ĠPhilipp ines\",\"prof ile\",\"Ġalt ogether\",\"ĠB und\",\"ĠT D\",\"oo oo\",\"amp ed\",\"ip h\",\"Ġste am\",\"Ġold est\",\"Ġdet ection\",\"ul pt\",\"Ġ ç\",\"ĠWay ne\",\"200 6\",\"f a\",\"Ġcir cles\",\"ĠF u\",\"Ġdon ors\",\"appropri ate\",\"ĠDak ota\",\"j amin\",\"Ġmotiv ated\",\"Ġpurch ases\",\"ĠLouis iana\",\"ĠS pl\",\"Ġgl obe\",\"Ġ10 5\",\"z ip\",\"c all\",\"Ġdepart ments\",\"Ġsustain able\",\"10 5\",\"ĠO P\",\"if iers\",\"Ġprevent ed\",\"Ġinc omp\",\"ĠComm ander\",\"Ġdom inated\",\"ĠÂ »\",\"Ġinvest ed\",\"Ġcomplex ity\",\"Ġin cl\",\"Ġens uring\",\"Ġreal m\",\"yn c\",\"ĠInd ependent\",\"r ained\",\"ĠJ en\",\"ĠFl ight\",\"Ġat he\",\"Ġspec ulation\",\"ĠT E\",\"oc ate\",\"t ic\",\"Ġpl aint\",\"her ry\",\"Ġto y\",\"Ġ1 11\",\"Ġpl ates\",\"st atus\",\"ĠIs a\",\"Ġdev oted\",\"C op\",\"ĠE S\",\"25 5\",\"ur rency\",\"M ain\",\"Ġsl aves\",\"Ġpe pper\",\"Ġqu otes\",\"Ġce iling\",\"ĠF ish\",\"Ġtrans formation\",\"Ġfra ction\",\"Ġadvant ages\",\"Ġto ile\",\"Ġstun ning\",\"Ġmo ist\",\"bre aking\",\"s i\",\"ĠL ocation\",\"ĠMed ium\",\"Ġtext s\",\"Ġu gly\",\"Ġb io\",\". âĢĶ\",\"ĠB ased\",\"Ġtr ains\",\"ĠW ing\",\"ĠAn cient\",\"ĠRec ords\",\"ĠH ope\",\"Spe cial\",\"ades h\",\"ob i\",\"[ /\",\"Ġtempor arily\",\"V er\",\"h u\",\"os er\",\"Ġover night\",\"Ġm amm\",\"ĠTre asury\",\"ĠV enezuel\",\"ĠMeg a\",\"Ġt ar\",\"Ġexpect s\",\"bl ack\",\"or ph\",\"\\\\\\\\ \\\\\\\\\",\"Ġaccept ance\",\"Ġrad ar\",\"s is\",\"Ġjun ior\",\"Ġfram es\",\"Ġobserv ation\",\"ac ies\",\"P ower\",\"ĠAdv anced\",\"M ag\",\"olog ically\",\"ĠMe chan\",\"Ġsent ences\",\"Ġanaly sts\",\"augh ters\",\"force ment\",\"Ġv ague\",\"Ġcl ause\",\"Ġdirect ors\",\"Ġeval uate\",\"Ġcabin et\",\"M att\",\"ĠClass ic\",\"A ng\",\"Ġcl er\",\"ĠB uck\",\"Ġresear cher\",\"Ġ16 0\",\"Ġpoor ly\",\"Ġexperien cing\",\"ĠP ed\",\"ĠMan hattan\",\"Ġfre ed\",\"Ġthem es\",\"ad vant\",\"Ġn in\",\"Ġpra ise\",\"10 4\",\"ĠLib ya\",\"b est\",\"Ġtrust ed\",\"Ġce ase\",\"Ġd ign\",\"D irect\",\"Ġbomb ing\",\"Ġm igration\",\"ĠSci ences\",\"Ġmunicip al\",\"ĠA verage\",\"Ġgl ory\",\"Ġreve aling\",\"Ġare na\",\"Ġuncertain ty\",\"Ġbattle field\",\"ia o\",\"G od\",\"Ġc inem\",\"ra pe\",\"el le\",\"ap ons\",\"Ġlist ing\",\"Ġwa ited\",\"Ġsp otted\",\"ke ley\",\"ĠAud io\",\"e or\",\"ard ing\",\"idd ing\",\"ig ma\",\"ĠN eg\",\"Ġl one\",\"Ġ ----\",\"ex e\",\"d eg\",\"Ġtrans f\",\"Ġwas h\",\"Ġsl avery\",\"Ġexpl oring\",\"ĠW W\",\"ats on\",\"Ġen cl\",\"l ies\",\"ĠC reek\",\"Ġwood en\",\"Man ager\",\"ĠBr and\",\"um my\",\"ĠAr thur\",\"Ġbureau cr\",\"Ġbl end\",\"ar ians\",\"F urther\",\"Ġsupposed ly\",\"Ġwind s\",\"Ġ19 79\",\"Ġgrav ity\",\"Ġanalys es\",\"ĠTra vel\",\"ĠV eter\",\"Ġd umb\",\"Ġaltern ate\",\"g al\",\"Ġconsum ed\",\"Ġeffect iveness\",\".' '\",\"Ġpath s\",\"ond a\",\"L A\",\"ĠStr ong\",\"Ġen ables\",\"Ġesc aped\",\"Ġ\\\" \\\"\",\"Ġ1 12\",\"Ġ198 3\",\"Ġsm iled\",\"Ġtend ency\",\"F ire\",\"Ġp ars\",\"ĠR oc\",\"Ġl ake\",\"Ġf itness\",\"ĠA th\",\"ĠH orn\",\"Ġh ier\",\"Ġimp ose\",\"m other\",\"Ġp ension\",\"ic ut\",\"bor ne\",\"ic iary\",\". _\",\"ĠS U\",\"Ġpol ar\",\"is y\",\"eng u\",\"itial ized\",\"AT A\",\"w rite\",\"Ġexerc ises\",\"ĠD iamond\",\"ot ypes\",\"Ġharm ful\",\"on z\",\"Ġprint ing\",\"st ory\",\"Ġexpert ise\",\"ĠG er\",\"Ġtraged y\",\"ĠF ly\",\"Ġd ivid\",\"amp ire\",\"st ock\",\"M em\",\"Ġre ign\",\"Ġun ve\",\"Ġam end\",\"ĠProp het\",\"Ġmut ual\",\"ĠF ac\",\"Ġrepl acing\",\"H ar\",\"ĠCirc uit\",\"Ġthro at\",\"ĠSh ot\",\"Ġbatter ies\",\"Ġto ll\",\"Ġaddress ing\",\"ĠMedic aid\",\"Ġp upp\",\"ĠN ar\",\"ol k\",\"Ġequ ity\",\"M R\",\"ĠHis pan\",\"ĠL arge\",\"m id\",\"D ev\",\"Ġexp ed\",\"Ġdem o\",\"ĠMarsh all\",\"erg us\",\"Ġf iber\",\"Ġdiv orce\",\"ĠCre ate\",\"Ġsl ower\",\"ĠPark er\",\"ĠStud ent\",\"ĠTr aining\",\"Ret urn\",\"ĠT ru\",\"Ġc ub\",\"ĠRe ached\",\"Ġpan ic\",\"Ġqu arters\",\"Ġre ct\",\"Ġtreat ing\",\"Ġr ats\",\"ĠChristian ity\",\"ol er\",\"Ġsac red\",\"Ġdecl are\",\"ul ative\",\"et ing\",\"Ġdeliver ing\",\"est one\",\"Ġt el\",\"ĠL arry\",\"Ġmet a\",\"ac cept\",\"art z\",\"ĠRog er\",\"hand ed\",\"Ġhead er\",\"Ġtra pped\",\"ĠCent ury\",\"Ġkn ocked\",\"ĠOx ford\",\"Ġsurviv ors\",\"b ot\",\"Ġdemon stration\",\"Ġd irt\",\"Ġass ists\",\"OM E\",\"ĠD raft\",\"ortun ate\",\"fol io\",\"pe red\",\"ust ers\",\"g t\",\"ĠL ock\",\"Ġjud icial\",\"ver ted\",\"Ġsec ured\",\"out ing\",\"ĠBook s\",\"Ġhost ing\",\"Ġlif ted\",\"l ength\",\"Ġj er\",\"Ġwhe els\",\"ĠR ange\",\"umbn ails\",\"Ġdiagn osis\",\"te ch\",\"ĠStew art\",\"ĠP ract\",\"Ġnation wide\",\"Ġde ar\",\"Ġoblig ations\",\"Ġgrow s\",\"Ġmand atory\",\"Ġsusp icious\",\"! '\",\"A pr\",\"G reat\",\"Ġmort gage\",\"Ġprosecut or\",\"Ġeditor ial\",\"ĠK r\",\"Ġprocess ed\",\"ung le\",\"Ġflex ibility\",\"Ear lier\",\"ĠC art\",\"ĠS ug\",\"Ġfoc uses\",\"Ġstart up\",\"Ġbre ach\",\"ĠT ob\",\"cy cle\",\"ãĢ Į\",\"ro se\",\"Ġb izarre\",\"ãĢ į\",\"Ġveget ables\",\"$ $\",\"Ġret reat\",\"osh i\",\"ĠSh op\",\"ĠG round\",\"ĠSt op\",\"ĠHawai i\",\"ĠA y\",\"Per haps\",\"ĠBe aut\",\"uff er\",\"enn a\",\"Ġproduct ivity\",\"F ixed\",\"cont rol\",\"Ġabs ent\",\"ĠCamp aign\",\"G reen\",\"Ġident ifying\",\"Ġreg ret\",\"Ġpromot ed\",\"ĠSe ven\",\"Ġer u\",\"ne ath\",\"aug hed\",\"ĠP in\",\"ĠL iving\",\"C ost\",\"om atic\",\"me ga\",\"ĠN ig\",\"oc y\",\"Ġin box\",\"Ġem pire\",\"Ġhor izont\",\"Ġbr anches\",\"Ġmet aph\",\"Act ive\",\"ed i\",\"ĠFil m\",\"ĠS omething\",\"Ġmod s\",\"inc ial\",\"ĠOrig inal\",\"G en\",\"Ġspir its\",\"Ġear ning\",\"H ist\",\"Ġr iders\",\"Ġsacr ific\",\"M T\",\"ĠV A\",\"ĠS alt\",\"Ġoccup ation\",\"ĠM i\",\"Ġdis g\",\"lic t\",\"Ġn it\",\"Ġn odes\",\"e em\",\"ĠP ier\",\"Ġhat red\",\"ps y\",\"ãĥ ī\",\"Ġthe ater\",\"Ġsophistic ated\",\"Ġdef ended\",\"Ġbes ides\",\"Ġthorough ly\",\"ĠMedic are\",\"Ġbl amed\",\"arent ly\",\"Ġcry ing\",\"F OR\",\"pri v\",\"Ġsing ing\",\"ĠI l\",\"Ġc ute\",\"o ided\",\"olit ical\",\"ĠNe uro\",\"å ¤\",\"Ġdon ation\",\"ĠEag les\",\"ĠG ive\",\"T om\",\"Ġsubstant ially\",\"ĠLic ense\",\"ĠJ a\",\"Ġg rey\",\"ĠAn imal\",\"ĠE R\",\"ĠU nd\",\"Ġke en\",\"Ġconclud e\",\"ĠMississ ippi\",\"Eng ine\",\"ĠStud ios\",\"P ress\",\"o vers\",\"ll ers\",\"Ġ3 50\",\"ĠR angers\",\"Ġr ou\",\"ert o\",\"E p\",\"iss a\",\"iv an\",\"Ġse al\",\"ĠReg ist\",\"dis play\",\"Ġwe aken\",\"u um\",\"ĠComm ons\",\"ĠS ay\",\"Ġcult ures\",\"Ġl aughed\",\"Ġsl ip\",\"Ġtreat ments\",\"iz able\",\"m art\",\"ĠR ice\",\"Ġbe ast\",\"Ġob esity\",\"ĠLa ure\",\"ig a\",\"Wh ich\",\"hold er\",\"Ġelder ly\",\"Ġp ays\",\"Ġcompl ained\",\"Ġc rop\",\"Ġpro c\",\"Ġexplos ive\",\"ĠF an\",\"ĠAr senal\",\"A uthor\",\"ef ul\",\"Ġme als\",\"Ġ( -\",\"id ays\",\"Ġimag ination\",\"Ġann ually\",\"Ġm s\",\"as ures\",\"H ead\",\"ik h\",\"m atic\",\"Ġboy friend\",\"ĠCom puter\",\"Ġb ump\",\"Ġsur ge\",\"ĠCra ig\",\"ĠKir k\",\"D el\",\"medi ate\",\"Ġscen arios\",\"ĠM ut\",\"ĠSt ream\",\"Ġcompet itors\",\"Ù Ħ\",\"ĠStan ford\",\"ĠRes ources\",\"az ed\",\"b age\",\"Ġorgan is\",\"ĠRe lease\",\"Ġsepar ately\",\"Ġha bits\",\"Ġmeasure ments\",\"ĠCl ose\",\"Ġaccomp any\",\"Ġg ly\",\"Ġt ang\",\"ĠR ou\",\"Ġplug in\",\"Ġcon vey\",\"ĠChall enge\",\"oot s\",\"j an\",\"Ġcur s\",\"ĠRel ations\",\"ke eper\",\"Ġapproach ing\",\"p ing\",\"Spe aking\",\"Ġarrang ement\",\"ĠV I\",\"are ttes\",\"Ġaffect ing\",\"Ġperm its\",\"b ecause\",\"Ġu seless\",\"ĠH us\",\"!! !!\",\"Ġdestro ying\",\"Un fortunately\",\"Ġfasc inating\",\"S em\",\"Ġelect oral\",\"Ġtrans parency\",\"ĠCh aos\",\"Ġvolunte er\",\"Ġstatist ical\",\"Ġactiv ated\",\"ro x\",\"We b\",\"H E\",\"ĠHamp shire\",\"is ive\",\"M ap\",\"Ġtr ash\",\"ĠLaw rence\",\"st ick\",\"C r\",\"Ġr ings\",\"EX T\",\"Ġoper ational\",\"op es\",\"D oes\",\"ĠEv ans\",\"Ġwitness ed\",\"P ort\",\"Ġlaunch ing\",\"ec onom\",\"w ear\",\"ĠPart icip\",\"um m\",\"cul es\",\"ĠR AM\",\"ĠT un\",\"Ġass ured\",\"Ġb inary\",\"Ġbet ray\",\"Ġexpl oration\",\"ĠF el\",\"Ġad mission\",\"it ated\",\"S y\",\"Ġav oided\",\"ĠSim ulator\",\"Ġcelebr ated\",\"ĠElect ric\",\"¥ ŀ\",\"Ġcl uster\",\"itzer land\",\"he alth\",\"L ine\",\"ĠN ash\",\"at on\",\"Ġsp are\",\"Ġenter prise\",\"ĠD IS\",\"clud es\",\"Ġfl ights\",\"Ġreg ards\",\"ĠÃ Ĺ\",\"h alf\",\"Ġtr ucks\",\"Ġcontact s\",\"Ġunc ons\",\"ĠCl imate\",\"Ġimm ense\",\"N EW\",\"oc c\",\"ect ive\",\"Ġemb od\",\"Ġpat rol\",\"Ġbes ide\",\"Ġv iable\",\"Ġcre ep\",\"Ġtrig gered\",\"ver ning\",\"Ġcompar able\",\"q l\",\"Ġg aining\",\"ass es\",\"Ġ( );\",\"ĠG rey\",\"ĠM LS\",\"s ized\",\"Ġpros per\",\"\\\" ?\",\"Ġpoll ing\",\"Ġsh ar\",\"ĠR C\",\"Ġfire arm\",\"or ient\",\"Ġf ence\",\"Ġvari ations\",\"g iving\",\"ĠP i\",\"osp el\",\"Ġpled ge\",\"Ġc ure\",\"Ġsp y\",\"Ġviol ated\",\"Ġr ushed\",\"Ġstro ke\",\"ĠBl og\",\"sel s\",\"ĠE c\",\",' '\",\"Ġp ale\",\"ĠColl ins\",\"ter ror\",\"ĠCanad ians\",\"Ġt une\",\"Ġlabor atory\",\"Ġn ons\",\"t arian\",\"Ġdis ability\",\"ĠG am\",\"Ġsing er\",\"al g\",\"ĠSen ior\",\"Ġtrad ed\",\"ĠWar rior\",\"Ġinf ring\",\"ĠFrank lin\",\"Ġstr ain\",\"ĠSwed ish\",\"Ġsevent h\",\"ĠB enn\",\"ĠT ell\",\"Ġsynd rome\",\"Ġwond ered\",\"id en\",\"++ ++\",\"ig o\",\"Ġpur ple\",\"Ġjournal ism\",\"Ġreb el\",\"Ġf u\",\"bl og\",\"Ġinv ite\",\"ren cies\",\"ĠCont act\",\"Is rael\",\"ĠCont ent\",\"Ġche er\",\"Ġbed room\",\"ĠEngine ering\",\"ĠQue ens\",\"Ġd well\",\"ĠPlay Station\",\"ĠD im\",\"ĠCol on\",\"l r\",\"Ġoper ates\",\"Ġmotiv ation\",\"US A\",\"ast ered\",\"C ore\",\"ĠTr uth\",\"ol o\",\"OS E\",\"ĠMem ory\",\"Ġpred ec\",\"Ġan arch\",\"Ġ19 20\",\"ĠY am\",\"Ã ¨\",\"b id\",\"Ġgr ateful\",\"Ġexc itement\",\"Ġtre asure\",\"Ġlong est\",\"ct ive\",\"Ġdes erves\",\"Ġreserv es\",\"Ġcop s\",\"ĠOtt awa\",\"ĠEgypt ian\",\"ank ed\",\"Ġart if\",\"Ġhypot hesis\",\": /\",\"Ġpurch asing\",\"Ġlove ly\",\"H P\",\"Ġdiv ide\",\"Ġstrict ly\",\"Ġquestion ing\",\"Ġtaxp ayers\",\"ĠJ oy\",\"Ġroll s\",\"ĠHe avy\",\"Ġp orts\",\"Ġmag netic\",\"Ġinf lamm\",\"Ġbr ush\",\"t ics\",\"â ĪĴ\",\"Ġbott les\",\"pp y\",\"Ġp add\",\"ãĤ ¯\",\"m illion\",\"Ġdevast ating\",\"Ġcomp iled\",\"Ġmed ication\",\"Ġtw elve\",\"ĠPer ry\",\"Sp ace\",\"im b\",\"y our\",\"Ġle aked\",\"ĠT ar\",\"Ġun ity\",\"Ġinfect ed\",\"Ġtravel ed\",\"ID E\",\"ĠMc Donald\",\"t xt\",\"ĠPr inc\",\"Ġinter ven\",\"ĠTai wan\",\"ĠP ow\",\"Ġbe aring\",\"ĠTh read\",\"Ġz ones\",\"iz ards\",\"un ks\",\"Ch apter\",\"ll or\",\"ĠÂ ·\",\"Ġw ounds\",\"Ġdisc retion\",\"Ġsucceed ed\",\"ik ing\",\"Ġicon ic\",\"C all\",\"Ġscreen ing\",\"ĠM is\",\"ict s\",\"Ġmin isters\",\"Ġsepar ation\",\"Pl ayer\",\"Ġb ip\",\"Ġbel oved\",\"Ġcount ing\",\"ĠE ye\",\"ar ound\",\"ing ing\",\"Ġtable t\",\"Ġoff ence\",\"in ance\",\"h ave\",\"ĠInf o\",\"ĠNin ja\",\"Ġprotect ive\",\"ĠC ass\",\"M ac\",\"ĠQual ity\",\"N orth\",\"Ġ ic\",\"ĠCub a\",\"ĠChron icle\",\"ĠPro perty\",\"Ġfast est\",\"ot os\",\"ĠG erm\",\"OW N\",\"Ġbo om\",\"ĠStan ley\",\"ergus on\",\"Ġcle ver\",\"Ġent ers\",\"m ode\",\"ter ior\",\"ĠS ens\",\"Ġlin ear\",\"AR K\",\"Ġcomp aring\",\"Ġpure ly\",\"Ġsaf er\",\"ĠPot ter\",\"Ġc ups\",\"R T\",\"Ġgl uc\",\"Ġatt ributed\",\"Ġdu pl\",\"ĠP ap\",\"Ġprec ious\",\"Ġp a\",\"iction ary\",\"ĠT ig\",\"ĠTo o\",\"ol utions\",\"st an\",\"Ġrob ots\",\"Ġlob b\",\"Ġstat ute\",\"Ġprevent ion\",\"w estern\",\"16 0\",\"ĠAct ive\",\"ĠMar ia\",\"h al\",\"N one\",\"ell ar\",\"ĠK B\",\"ĠPart ners\",\"ĠSing le\",\"ĠFollow ing\",\"ang o\",\"ac ious\",\"Ġth ou\",\"Ġk g\",\"Ġinflu ential\",\"ĠFriend s\",\"S ur\",\"ain ted\",\"Ġfor ums\",\"Ġst arter\",\"Ġcitizens hip\",\"ĠE lection\",\"on ge\",\"ot ation\",\"os ph\",\";; ;;\",\"ut ical\",\"p ur\",\"ere n\",\"Ġaccus ations\",\"bit ious\",\"ab bit\",\"ĠOr d\",\"Post ed\",\"ir k\",\"Ġsens itivity\",\"ic he\",\"ĠAm y\",\"ĠF ab\",\"Ġsum mit\",\"Ġped est\",\"Ġrub ber\",\"Ġagric ultural\",\"Ġcan cel\",\"A E\",\"Ġin aug\",\"Ġcont am\",\"Ġfirm ly\",\"i w\",\"st age\",\"ĠK an\",\"Ġt ier\",\"Ġinv ention\",\"Ġtransl ated\",\"ĠR ules\",\"B ox\",\"Tw itter\",\"ID S\",\"Ġp izza\",\"Ġdeb ug\",\"ĠD rop\",\"v s\",\"Ġh orses\",\"b ig\",\"Ġb oring\",\"Ġh ood\",\"ĠMcC ain\",\"at ched\",\"ĠBro s\",\"Ġsk ip\",\"Ġess ay\",\"st at\",\"ĠLeg ends\",\"Ġam munition\",\"au c\",\"Ġshoot er\",\"Ġun h\",\"Ġsuppl ied\",\"Ġgener ic\",\"ĠS K\",\"ib an\",\"yr ics\",\"Ġ25 5\",\"Ġclim bing\",\"Form er\",\"Ġfl ip\",\"Ġjump ing\",\"Ġfrust ration\",\"ĠTer ry\",\"Ġneighborhood s\",\"Ġmed ian\",\"be an\",\"Ġbr ains\",\"Follow ing\",\"Ġsh aped\",\"Ġdraw s\",\"Ġal tered\",\"J ack\",\"Ġrecip es\",\"Ġsk illed\",\"we alth\",\"ach i\",\"e lection\",\"Ġbehavi ors\",\"de als\",\"ĠU ntil\",\"F e\",\"Ġdecl aration\",\"mar ks\",\"ĠBet ween\",\"cel ona\",\"Ġres on\",\"Ġbub ble\",\"Am ong\",\"Ġim perial\",\"G S\",\"Ġfemin ist\",\"200 5\",\"ĠK yle\",\"Ġaccount ing\",\"ĠTe le\",\"ĠT yr\",\"Ġconnect ing\",\"Ġre hab\",\"ĠP red\",\"s im\",\"Ġmeant ime\",\"Ġphys ician\",\"M W\",\"ĠCamp bell\",\"ĠBr andon\",\"Ġcontribut ing\",\"ĠR ule\",\"ĠWe ight\",\"ĠN ap\",\"Ġinter active\",\"Ġv ag\",\"Ġhel met\",\"ĠCom b\",\"f our\",\"Ġsh ipped\",\"Ġcomple ting\",\"ĠP D\",\"PD ATE\",\"Ġspread ing\",\"Ġsc ary\",\"erv ing\",\"ĠG as\",\"Ġfr ank\",\"s chool\",\"Ġrom antic\",\"Ġstab il\",\"R ob\",\"Ġaccur ately\",\"Ġac ute\",\"ĠH ann\",\"Ġsymbol s\",\"Ġcivil ization\",\"ĠA W\",\"Ġlight ning\",\"Ġcons iders\",\"Ġven ue\",\"Ġ ×\",\"Ġo ven\",\"ĠS F\",\"h is\",\"Ġn u\",\"ĠLear n\",\"Ġpe oples\",\"Ġst d\",\"Ġsle e\",\"Ġs lic\",\"ĠStat istics\",\"Ġcor ners\",\"ĠB aker\",\"Ġ: )\",\"ment ation\",\"ol ver\",\"Ġlaugh ing\",\"ĠT odd\",\"ond e\",\"ĠH ills\",\"Ġn uts\",\"ĠW oman\",\"pl ane\",\"Ġl iver\",\"ĠIn side\",\"S orry\",\"Ġagre es\",\"Ġfund ament\",\"ĠF isher\",\"Ġa uction\",\"Ġthread s\",\"gl as\",\"ĠBas ic\",\"ĠN at\",\"Ġlack ing\",\"Ġceleb ration\",\"j u\",\"Ġs illy\",\"E uro\",\"Ġt att\",\"ight y\",\"cont rolled\",\"T est\",\"ĠSing h\",\"Ġr age\",\"Ġrh yth\",\"o ffic\",\"ĠPh antom\",\"Ġhead lines\",\"Ġrespond ing\",\"ĠMor ning\",\"Ġvit amin\",\"Ġboot s\",\"ĠS ite\",\"al in\",\"p i\",\"Ġvir al\",\"ĠU C\",\"D ER\",\"ĠSe x\",\"Ġst ocks\",\"c urrent\",\"Ġch urches\",\"ĠR are\",\"ĠMur phy\",\"Ġden ial\",\"ĠG aming\",\"Ġtou g\",\"Ġn ick\",\"Ġm akers\",\"ĠRon ald\",\"Ġgener ous\",\"ĠD oc\",\"ĠMor ris\",\"Ġtransform ed\",\"ĠN ormal\",\"Ġ10 4\",\"ĠKick starter\",\"ĠUp on\",\"On line\",\"ĠI RS\",\"Ġw rap\",\"Ġl oving\",\"Ġarri ves\",\"ĠD ue\",\"Ġhe ter\",\"ĠM ade\",\"Ġrent al\",\"Ġbelong s\",\"Ġatt orneys\",\"Ġcro ps\",\"Ġmat ched\",\"ul um\",\"ol ine\",\"10 9\",\"Ġdis par\",\"Ġbuy ers\",\"ĠCam bridge\",\"Ġeth ics\",\"rou ps\",\"Ġjust ified\",\"Ġmarg inal\",\"Ġrespect ed\",\"win ning\",\"Ġnodd ed\",\"ĠSer ge\",\"ĠForm er\",\"C raft\",\"######## ########\",\"ĠWar ner\",\"Ġd ash\",\"et e\",\"Ġent ert\",\"ĠE scape\",\"out heast\",\"Ġkn ees\",\"ĠB omb\",\"Ġr ug\",\"P ass\",\"Ġatt itudes\",\"go vernment\",\"ĠPri or\",\"Ġqual ities\",\"Ġnot ification\",\"ĠPh one\",\"l ie\",\"Ġanticip ated\",\"ĠCom bat\",\"ĠBar ry\",\"Ġ198 2\",\"Us ers\",\"on er\",\"Ġcomput ing\",\"ĠConnect icut\",\"Ġless er\",\"Ġpe ers\",\"ĠC u\",\"Ġtechn ically\",\"Ġsub mission\",\"ĠUn iversal\",\"Ġman ually\",\"our ge\",\"Ġrespond ents\",\"ĠB TC\",\"ĠH ost\",\"Ġf are\",\"ĠB ird\",\"Ġrece ipt\",\"al so\",\"Ġj ack\",\"Ġagric ulture\",\"Ġsk ull\",\"Ġ! =\",\"Ġpass ive\",\"ĠC I\",\"Ġsoc ieties\",\"Ġremind ed\",\"Ġinter ference\",\"B uy\",\"Ġâ ľ\",\"g on\",\"Ġscrut iny\",\"ĠW itch\",\"Ġconduct ing\",\"Ġ ãĥ\",\"Ġexch anges\",\"ĠMit chell\",\"Ġinhab it\",\"Ġtw ist\",\"B D\",\"Ġwhere ver\",\"group on\",\"Ġj okes\",\"ĠBen jamin\",\"ĠR andom\",\"fr ame\",\"ĠL ions\",\"Ġhighlight ed\",\"ĠArk ansas\",\"E nt\",\"Ġp ile\",\"Ġpre lim\",\"g s\",\"mind ed\",\"Ġfel ony\",\"ĠG A\",\"ĠL uck\",\"Ġpract ically\",\"ĠB os\",\"Ġact ress\",\"D am\",\"ĠB ou\",\"Ġvis a\",\"Ġembed ded\",\"Ġhy brid\",\"Ġear liest\",\"Ġsoon er\",\"s ocial\",\"ĠH A\",\"Ġste ep\",\"Ġdis advant\",\"Ġexplo it\",\"ĠE gg\",\"ĠUlt ra\",\"Ġnecess ity\",\"L ocal\",\"ie ge\",\"Ġd ated\",\"Ġmass es\",\"Ġsubsc ription\",\"pl ess\",\"Ġan onym\",\"Ġpresum ably\",\"Bl ue\",\"The ir\",\"asket ball\",\"ĠPhil ip\",\"Ġcom ed\",\"load ed\",\"r ane\",\"Ġref lection\",\"Ch ina\",\"Ġext ends\",\"Ġform ing\",\"Ġund ers\",\"200 1\",\"Ġgr at\",\"Ġconcent rations\",\"Ġins ulin\",\"Ġsec ular\",\"Ġwh ilst\",\"Ġwin ners\",\"Ad vertisements\",\"Ġdeliber ately\",\"ĠWork ing\",\"Ġs ink\",\"et ics\",\"d ale\",\"Ġmand ate\",\"Ġg ram\",\"Ġvac ation\",\"Ġwarn ings\",\"ri pp\",\"ĠTH AT\",\"Ġcomment ary\",\"Ġint u\",\"Ġa est\",\"Ġreason ing\",\"Ġbreak down\",\"ĠZ ombie\",\"Ġ-- >\",\"ĠPolit ical\",\"c ott\",\"Ġthr ust\",\"Ġtechn ological\",\"Ġdec iding\",\"Ġtraff icking\",\"L ong\",\"W elcome\",\"pr ising\",\"ĠCommun ications\",\"Ġend ors\",\"Ġsw ift\",\"Ġmetab ol\",\"co ins\",\"res a\",\"ĠHT TP\",\"Ġen roll\",\"ĠH appy\",\"us r\",\"int age\",\"Ġ[ \\\"\",\"u ably\",\"ĠM aterial\",\"Ġrepe al\",\"Se pt\",\"k h\",\"ĠMod i\",\"Ġunder neath\",\"ĠI L\",\"sh ore\",\"Ġdiagn osed\",\"ace utical\",\"Ġsh ower\",\"au x\",\"ĠSw itch\",\"ĠStre ngth\",\"Ġj ihad\",\"n ational\",\"Ġtra uma\",\"uss y\",\"on i\",\"Ġcons olid\",\"Ġcal ories\",\"ĠF lynn\",\"ag ged\",\"16 8\",\"ĠP ink\",\"Ġfulf ill\",\"Ġch ains\",\"Ġnot ably\",\"ĠA V\",\"L ife\",\"ĠCh uck\",\"m us\",\"ĠUr ban\",\"ĠH end\",\"Ġdep osit\",\"ĠS ad\",\"Ġaff air\",\"OR K\",\"ie val\",\"ĠF DA\",\"Ġt rop\",\"ĠOver all\",\"Ġvirt ue\",\"Ġsatisf action\",\"au nd\",\"Ġl un\",\"ĠSw itzerland\",\"ĠOper ation\",\"pro cess\",\"Ġsh ook\",\"Ġcount ies\",\"le ased\",\"ĠCharl otte\",\"1 12\",\"Ġtrans cript\",\"Ġre dd\",\"p ush\",\"ĠHe y\",\"ĠAn alysis\",\"[ \\\"\",\"Ġaltern atives\",\"ard less\",\"Ġele ph\",\"Ġpre jud\",\"ĠLe af\",\"H aving\",\"ĠH ub\",\"Ġexpress ions\",\"ĠVol ume\",\"Ġshock ing\",\"ĠRed s\",\"Ġread ily\",\"Ġplan ets\",\"ad ata\",\"Ġcollaps ed\",\"ĠMad rid\",\"Ġir rit\",\"i pper\",\"ĠEn c\",\"ĠW ire\",\"Ġbu zz\",\"ĠG P\",\"ash a\",\"Ġaccident ally\",\"ur u\",\"Ġfrust rated\",\"ĠS A\",\"Ġhung ry\",\"ĠH uff\",\"Ġlab els\",\"ant o\",\"ĠE P\",\"Ġbar riers\",\") |\",\"ĠBer keley\",\"ĠJ ets\",\"Ġp airs\",\"ĠL an\",\"J ames\",\"ĠB ear\",\"Ġhum or\",\"ĠLiber ty\",\"Ġmagn itude\",\"Ġag ing\",\"ĠM ason\",\"Ġfriends hip\",\"umb ling\",\"Ġemer ge\",\"Ġnewsp apers\",\"Ġam bitious\",\"ĠRich ards\",\"atern al\",\"Ġ198 1\",\"Ġcook ies\",\"Ġsc ulpt\",\"Ġpur suit\",\"L ocation\",\"Ġscript s\",\"p c\",\"Ġarrang ements\",\"Ġd iameter\",\"Ġl oses\",\"am ation\",\"Ġl iqu\",\"ĠJ ake\",\"aret te\",\"Ġunderstand s\",\"ĠZ en\",\"v m\",\"Ġappro ve\",\"Ġw ip\",\"Ġult ra\",\"Ġint end\",\"ĠD I\",\"asc ular\",\"Ġst ays\",\"ĠK or\",\"ĠK l\",\"Ġinvest ing\",\"L a\",\"Ġbelie ving\",\"b ad\",\"m outh\",\"Ġtaxp ayer\",\"ãĥ ĥ\",\"ĠQue bec\",\"Ġl ap\",\"ĠSw iss\",\"d rop\",\"Ġdr ain\",\"ir i\",\"et c\",\"ft en\",\"ĠN ex\",\"Ġst raw\",\"Ġscream ing\",\"Ġcount ed\",\"Ġdam aging\",\"Ġamb assador\",\"cent ury\",\"Ġpro x\",\"Ġarrest s\",\"u v\",\"il ateral\",\"ĠCh arg\",\"Ġpresc ribed\",\"Ġindepend ently\",\"Ġf ierce\",\"ĠB aby\",\"Ġb rave\",\"Ġsu its\",\"= >\",\"Ġbas eline\",\"ĠR ate\",\"Ġis lands\",\"Ġ( (\",\"g reen\",\"ix els\",\"Ġname ly\",\"ĠVill age\",\"th an\",\"am y\",\"V ersion\",\"g mail\",\"ential s\",\"ĠS ud\",\"ĠMel bourne\",\"Ġarri ving\",\"Ġquant um\",\"e ff\",\"rop olitan\",\"T ri\",\"Ġfun eral\",\"ĠI R\",\"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\",\"ĠC ob\",\"it ably\",\"Ġt urb\",\"Ġcomb o\",\"Re view\",\"Ġdeploy ment\",\"u ity\",\"ĠB ott\",\"Ġinv isible\",\"Ġrender ing\",\"Ġunl ocked\",\"Ġa qu\",\"ĠVlad imir\",\"Ġp ad\",\"ĠBr ain\",\"ĠLeg acy\",\"dr agon\",\"ĠKurd ish\",\"Ġsound ed\",\"Ġdet ained\",\"ĠD M\",\"g ary\",\"Ġd aughters\",\"Ġdistur bing\",\"uk a\",\"ĠPar ad\",\"Ġt ast\",\"Ġunf ortunate\",\"Ġu l\",\"em in\",\"Ġattend ance\",\"tr l\",\"Ġpar ks\",\"ĠMem orial\",\"ĠAl ice\",\"oth y\",\"gu ard\",\"ĠD ise\",\"ĠSh an\",\"ĠFor um\",\"R ich\",\"Ġshif ted\",\"ue z\",\"Ġl ighter\",\"ĠMag n\",\"Ġc od\",\"S ch\",\"ham mad\",\"P ub\",\"3 50\",\"ĠP okemon\",\"Ġprot otype\",\"Ġun re\",\"B ase\",\"ĠStud ents\",\"ĠRep ly\",\"ĠCommun ist\",\"Ġg au\",\"ĠTy ler\",\"I Z\",\"Ġparticip ated\",\"Ġsup rem\",\"ĠDet ails\",\"Ġvessel s\",\"ro d\",\"Ġt ribe\",\"ke ep\",\"Ġassum ptions\",\"Ġp ound\",\"Ġcr ude\",\"ĠAv ailable\",\"Ġswim ming\",\"Ġin clusion\",\"Ġadv ances\",\"c ulation\",\"Ġconserv ation\",\"Ġover d\",\"ĠBuff alo\",\"Art icle\",\"ed ge\",\"Ġaw a\",\"ĠMad ison\",\"Ġsid ew\",\"Ġcat ast\",\"ĠK rist\",\"uc le\",\"ĠHigh way\",\"ĠTer ror\",\"Ġactiv ation\",\"Ġuncons cious\",\"ĠSat an\",\"ĠSus an\",\"ill ery\",\"Ġarr anged\",\"i op\",\"Ġrum ors\",\"ur ring\",\"th ink\",\"ĠKe ith\",\"ĠK ind\",\"Ġavoid ing\",\"by n\",\"n ut\",\"ĠSpe aker\",\"r us\",\"n ames\",\"Ġgu ilt\",\"ĠOlymp ics\",\"Ġsa il\",\"ĠM es\",\"lev ant\",\"ĠColumb us\",\"a ft\",\"C ity\",\"S outh\",\"ĠHar vey\",\"ĠP un\",\"S everal\",\"Ġment ally\",\"Ġimp ress\",\"m ount\",\"ĠUb untu\",\"âĢĶâĢĶâĢĶâĢĶ âĢĶâĢĶâĢĶâĢĶ\",\"ĠSuper man\",\"ĠMP s\",\"Ġintent ions\",\"ĠR acing\",\"Ġlike lihood\",\"Ġ2 40\",\"T otal\",\"Ġto ys\",\"ĠW atson\",\"Ġur ge\",\"L ear\",\"ĠP aper\",\"Ġoccur ring\",\"ĠB eng\",\"ĠC ert\",\"Ġst ones\",\"T im\",\"ĠTw in\",\"z b\",\"ĠD ynam\",\"Ġpolit ician\",\"k ens\",\"ĠEnter prise\",\"UT ERS\",\"Ġab ol\",\"Ġref resh\",\"Ġarbit rary\",\"pe ction\",\"Ġtrou bles\",\"Ġ} );\",\"t v\",\"Ġpil ots\",\"Ġdist ribute\",\"Ġaud it\",\"Ġp ause\",\"orig inal\",\"Ġr ivals\",\"Â £\",\"F ig\",\"T L\",\"ab il\",\"ry ing\",\"L in\",\"ion ed\",\"l on\",\"Ġf ancy\",\"Ġcr ashed\",\"Ġt ract\",\"Ġshe d\",\"Ġcons ume\",\"B ased\",\"down load\",\"in it\",\"Ġvolt age\",\"Int rodu\",\"Ġcondem ned\",\"ĠFin ance\",\"res pect\",\"Ġex cluded\",\"Ġestablish ing\",\"her ic\",\"Ġher itage\",\"Ġspect acular\",\"Ġun st\",\"ĠSnow den\",\"ĠL ane\",\"S an\",\"Ġprotect ions\",\"st ruction\",\"inc inn\",\"Ġmac ro\",\"C ustom\",\"ios ity\",\"Ġes p\",\"Ġfunction ing\",\"Ġm ush\",\"Ġp uzzle\",\"Ġeth ical\",\"M al\",\"Ġgo verning\",\"ĠF erguson\",\"Ġrest ored\",\"Ġst ressed\",\"ĠCoun ter\",\"ĠK as\",\"cl ip\",\"AN S\",\"Ġse iz\",\"U K\",\"by ss\",\"old own\",\"ap i\",\"Ġperman ently\",\"oun ters\",\"W est\",\"Th rough\",\"L ight\",\"at oes\",\"Ġne at\",\"Ġc ord\",\"ure r\",\"Ġsevere ly\",\"ĠA ven\",\"Ġinter rog\",\"Ġtri ple\",\"G iven\",\"N umber\",\"Ġar ise\",\"Ġs her\",\"pl ant\",\"Ġfl ower\",\"ĠC ou\",\"Ġat e\",\"Ġnew er\",\"b ul\",\"Ġmean while\",\"ĠL air\",\"Ġadjust ment\",\"ĠCop yright\",\"Ġd ivers\",\"i ological\",\"Ġgam ers\",\"o at\",\"Ġhistor ically\",\"Ġanal og\",\"Ġlong time\",\"Ġpres cription\",\"ĠM ist\",\"ĠHy per\",\"ĠM aine\",\"ĠDe ity\",\"Ġmulti pl\",\"ĠRe incarn\",\"ĠH yd\",\"ĠP ic\",\"S il\",\"r ants\",\"ĠC ris\",\". ;\",\"( {\",\"epend ence\",\"Ġrec y\",\"ate ur\",\"Ġqu ad\",\"Ġgl ob\",\"Ġcon ced\",\"te am\",\"Ġcapital ist\",\"ĠL ot\",\"Ġroy al\",\"ĠCy ber\",\"Ġblack s\",\"met ic\",\"ri v\",\"ĠD anny\",\"Ġsp o\",\"ĠR O\",\"Ġanim ated\",\"rypt ed\",\"ĠDep uty\",\"Ġrend ered\",\"F E\",\"Ġstre ak\",\"Ġcloud s\",\"ĠDou g\",\"~~~~ ~~~~\",\"Ġdisc our\",\"ĠVe h\",\"Ġpsych ology\",\"ĠJ ourney\",\"Ġcry stal\",\"ĠFro st\",\"Ġsuspic ion\",\"Ġrel ate\",\"or us\",\"ĠC rypt\",\"ĠN VIDIA\",\"com ed\",\"ut ing\",\"incinn ati\",\"Ġvulner ability\",\"ost ic\",\"Ġisol ation\",\"Ġcool ing\",\"ĠCoal ition\",\"Ġ1 19\",\"F our\",\"ĠDe al\",\"Ġâ ī\",\"se mble\",\"ram ent\",\"ĠBar celona\",\"Ġ10 2\",\"Ġcoc aine\",\"ocaly pse\",\"F eb\",\"ogen ic\",\"Ġmut ation\",\"Ġcrypt oc\",\"ĠK el\",\"ĠG it\",\"a is\",\"Ġs isters\",\"AN K\",\"Ġactiv ate\",\"T er\",\"Ġd read\",\"yl on\",\"Ġprop ri\",\"A ust\",\"ĠDef ault\",\"Ġout door\",\"Ġshe er\",\"ce ive\",\"Ġg ently\",\"Ð ¾\",\"Pro gram\",\"Ġâ ĨĴ\",\"Ġve gan\",\"ĠCr us\",\"Ġrespons ibilities\",\"ĠH R\",\"OL D\",\"Ġprev ents\",\"Ġst iff\",\"ĠW ere\",\"Ġathlet ic\",\"ĠSc ore\",\"Ġ) :\",\"Ġcolumn s\",\"ĠL oc\",\"av ailable\",\"ĠF ram\",\"ĠS essions\",\"Ġcompan ion\",\"Ġpack s\",\"14 0\",\"ĠKn ights\",\"Ġf art\",\"Ġstream s\",\"Ġsh ore\",\"Ġapp eals\",\"ĠPer formance\",\"h aul\",\"ĠSt ra\",\"ĠN ag\",\"10 3\",\"ĠTrans portation\",\"B B\",\"E v\",\"z an\",\"P ublic\",\"Ġtw in\",\"uls ion\",\"M ult\",\"Ġelect ro\",\"Ġstat ue\",\"ation ally\",\"ĠN ort\",\"Ġins pection\",\"/ *\",\"ig ue\",\"Ġcomp assion\",\"ĠT ales\",\"ĠSte in\",\"ĠSc reen\",\"ĠB ug\",\"ĠL ion\",\"g irl\",\"Ġwithdraw al\",\"Ġobject ives\",\"Ġblood y\",\"Ġprelim inary\",\"Ġj acket\",\"Ġdim ensions\",\"ĠC ool\",\"ĠOcc up\",\"Ġw reck\",\"Ġdoub led\",\"ank ing\",\"Ġ19 75\",\"Ġglass es\",\"ĠW ang\",\"pro v\",\"P ath\",\"connect ed\",\"ĠMult i\",\"ĠNor way\",\"agon ist\",\"Ġfe ared\",\"Ġtouch ing\",\"Ġarg uably\",\"Â¯Â¯Â¯Â¯ Â¯Â¯Â¯Â¯\",\"ĠNC AA\",\"che m\",\"Ġsp at\",\"ĠW WE\",\"ĠC el\",\"ig ger\",\"Ġattack er\",\"ĠJo in\",\"ob ject\",\"ett a\",\"Ġelim inated\",\"d et\",\"Ġdest ruct\",\"ĠLuc as\",\"ct uary\",\"18 0\",\"ĠBr ady\",\"ĠBl ues\",\"B ay\",\"au kee\",\"Ġtim eline\",\"Ġdeleg ates\",\"w ritten\",\"uff icient\",\"Ġsh apes\",\"Cop yright\",\"ou ble\",\"serv ice\",\"Ġp ione\",\"Ġcolleg es\",\"Ġrow s\",\"Ġsp ite\",\"Ġassess ed\",\"3 60\",\"Ġle ase\",\"Ġconfident ial\",\"ck er\",\"ĠMan ning\",\"ĠV oice\",\"Ġse aled\",\"Ġcalcul ate\",\"N O\",\"ĠAss istant\",\"Ġteen ager\",\"ul ent\",\"ather ine\",\"Ġm ock\",\"Ġd iamond\",\"Ġf est\",\"Ġsw itched\",\"Ġres ume\",\"ĠPu erto\",\"Ġl anes\",\"ir ation\",\"ĠSimilar ly\",\"Ġro d\",\"ĠS el\",\"ĠPal ace\",\"ĠLim ited\",\"e ous\",\"Ġvar iant\",\"Ġw ard\",\"Ġ) )\",\"Sh ow\",\"OO K\",\"A lex\",\"ĠN ep\",\"br is\",\"ĠWik ipedia\",\"Ġexcept ional\",\"Ġman ages\",\"ĠD raw\",\"Ag ain\",\"Ġco pper\",\"ut t\",\"Ġex ports\",\"Ġport folio\",\"Ġelev ated\",\"R ated\",\"ĠOther wise\",\"ĠT act\",\"ĠShe l\",\"ĠT X\",\"\\\" âĢĶ\",\"Ġres ur\",\"ĠW a\",\"ven ant\",\"Ġmon etary\",\"pe ople\",\"E mail\",\"Ġfif ty\",\"ĠS weet\",\"ĠMalays ia\",\"Ġconf using\",\"ĠR io\",\"ud a\",\"uten ant\",\"\\\" );\",\"Ġpra ised\",\"Ġvol umes\",\"t urn\",\"Ġm ature\",\"Ġnon profit\",\"Ġpassion ate\",\"ĠPriv ate\",\"Ġ10 3\",\"Ġdesc end\",\"ç ¥ŀ\",\"uff y\",\"head ed\",\"Whe ther\",\"ri en\",\"ze ch\",\"be it\",\"Ġch rom\",\"ĠMc M\",\"Ġd ancing\",\"Ġe leg\",\"ĠNot iced\",\"11 5\",\"Ġadvoc acy\",\"ENT S\",\"amb ling\",\"ĠMin or\",\"ĠF inn\",\"Ġprior ities\",\"Ġthere of\",\"ĠSt age\",\"ĠRog ers\",\"Ġsubst itute\",\"ĠJ ar\",\"ĠJeff erson\",\"Ġlight ly\",\"10 2\",\"ĠL isa\",\"u its\",\"ys ical\",\"Ġshif ts\",\"Ġd rones\",\"Ġwork place\",\"Ġres id\",\"ens ed\",\"ah n\",\"Ġpref erences\",\"ser ver\",\"Ġdeb ates\",\"d oc\",\"ĠGod s\",\"Ġhelicop ter\",\"Ġhon our\",\"Ġconsider ably\",\"ed ed\",\"ĠF emale\",\"ĠAn ne\",\"Ġre un\",\"ĠF ace\",\"ĠHall ow\",\"ĠBud get\",\"Ġcondem n\",\"Ġt ender\",\"Pro f\",\"ocr atic\",\"ĠTurn er\",\"ĠAg ric\",\"Ġ19 76\",\"Ġa pt\",\"d isc\",\"ĠF ighter\",\"ĠA ur\",\"Ġgar bage\",\"in put\",\"ĠK arl\",\"ĠOl iver\",\"ĠL anguage\",\"k n\",\"N on\",\"ĠCl ar\",\"Ġtrad itions\",\"Ġad vertisement\",\"ĠS or\",\"Ġarch ive\",\"Ġvill ages\",\"7 50\",\"Ġimplement ing\",\"w aukee\",\"Ġdiet ary\",\"Ġswitch ing\",\"Rep ublic\",\"Ġvel ocity\",\"Ġc it\",\"ĠA wards\",\"Ġfin ancing\",\"Ġlast ed\",\") ]\",\"Ġrem inder\",\"P erson\",\"Ġprec ision\",\"Ġdesign ers\",\"ĠF ried\",\"ĠB order\",\"Ġtr agic\",\"Ġw ield\",\"Ġiniti atives\",\"ĠT ank\",\"w er\",\"Ġjo ins\",\"R o\",\"in ery\",\"Ġar row\",\"Ġgener ating\",\"found er\",\"Ġsear ches\",\"Ġrandom ly\",\"A ccess\",\"Ġb atch\",\"Ġp osed\",\"l at\",\"Ġpursu ing\",\"as a\",\"Ġtest ified\",\"form ing\",\"ĠSh ar\",\"w iki\",\"ĠE ither\",\"S ometimes\",\"Ġsen ators\",\"ĠJohn ny\",\"ĠTal iban\",\"ĠG PS\",\"\\\":\\\" /\",\"ãģ® å\",\"Ġanaly zed\",\"ĠRub io\",\"ĠMove ment\",\"op ard\",\"ii i\",\"St and\",\"f ight\",\"Ġign oring\",\"i ang\",\"ĠG N\",\"so ever\",\"ĠST AT\",\"Ġref using\",\"Ġswe at\",\"Ġb ay\",\"P ORT\",\"ir med\",\"ak y\",\"Ġdis pro\",\"Ġlabel ed\",\"Ġ10 8\",\"H ello\",\"Ġple asant\",\"ab a\",\"Ġtri umph\",\"Ġab oard\",\"Ġinc om\",\"ĠC row\",\"le tt\",\"Ġfol k\",\"Ġch ase\",\"` `\",\"ĠBr us\",\"Ġte ens\",\"c ue\",\"Ġter rain\",\"h yd\",\"il ight\",\"OR Y\",\"Su pport\",\"ew s\",\"ll i\",\"rain ts\",\"ĠC and\",\"Ġab used\",\"ach ment\",\"l arg\",\"B as\",\"ĠC ancer\",\"Ġ19 78\",\"Ġsupp orter\",\"ac cess\",\"ĠTer min\",\"ĠT ampa\",\"ĠAN Y\",\"Ġnew est\",\"ĠCrim inal\",\"ed u\",\"Ġ19 30\",\"Ġadm its\",\"Ġend e\",\"Ġfail ures\",\"ur ate\",\"ful ness\",\"cy cl\",\"ĠSub ject\",\"Ġinf inite\",\"th ree\",\"W A\",\"p it\",\"ĠInst all\",\"R ad\",\"ili ation\",\"G M\",\"Ġcontin ent\",\"Ġaccommod ate\",\"ĠCl ay\",\"Ġp up\",\"ĠF unction\",\"Ġham mer\",\"ĠAlbert a\",\"Ġrev ised\",\"Ġminor ities\",\"Ġmeasure ment\",\"Con nell\",\"Ġdis able\",\"ĠM ix\",\"In cre\",\"Ġfor k\",\"ĠR osen\",\"Ġimpl ies\",\"umb lr\",\"AN G\",\"Ġprote ins\",\"Ġagg ression\",\"Ġfacilit ate\",\"S N\",\"Ġilleg ally\",\"u er\",\"Ġacad em\",\"Ġp uzz\",\"ĠSh ift\",\"p ay\",\"oll o\",\"Ġaud iences\",\"B uild\",\"Ġno ble\",\"Ġsynt ax\",\"â ĺħ\",\"Ġbe am\",\"ĠB ed\",\"ĠA ld\",\"Ġorig ins\",\"v ideo\",\"Ġ19 77\",\"ĠAss ault\",\"Ġgar age\",\"Te am\",\"Ġver dict\",\"Ġd war\",\"ĠVirt ual\",\"e vent\",\"Ke ep\",\"Ġsent iment\",\"Ġwild life\",\"sh irt\",\"Ġb urg\",\"Ġrecommend ation\",\"rep resent\",\"Ġgall ery\",\"own ers\",\"Ġsch olar\",\"Ġconven ience\",\"ĠSw ift\",\"Ġconv inc\",\"C ap\",\"Ġwar fare\",\"ĠVis ual\",\"Ġconst itute\",\"Ġab ort\",\"ĠWe ather\",\"ĠLook ing\",\"ĠH em\",\"Ġmart ial\",\"Ġinc oming\",\"et ition\",\"Ġtoler ance\",\"ĠCre ated\",\"Ġfl ows\",\"ĠE lder\",\"Ġsoul s\",\"Ġf oul\",\"ĠP ain\",\"ĠC AN\",\"Ġ2 20\",\"b c\",\"he nd\",\"Ġgen ius\",\"R eal\",\"ĠW r\",\"omet er\",\"p ad\",\"Ġlim iting\",\"ĠS i\",\"ĠL ore\",\"ĠAd ventures\",\"Ġvar ied\",\"D isc\",\"f in\",\"ĠPerson al\",\"Ch ris\",\"Ġinv ented\",\"Ġd ive\",\"ĠR ise\",\"Ġo z\",\"ĠCom ics\",\"Ġexp ose\",\"ĠRe b\",\"let ters\",\"s ite\",\"im ated\",\"Ġh acking\",\"Ġeduc ated\",\"ĠNob ody\",\"Ġdep ri\",\"Ġincent ive\",\"ãĤ ·\",\"Ġovers ight\",\"Ġtrib es\",\"ĠBelg ium\",\"Ġlicens ing\",\"our t\",\"Produ ct\",\"ah l\",\"ĠG em\",\"Ġspecial ist\",\"Ġc ra\",\"ann ers\",\"ĠCor byn\",\"Ġ19 73\",\"RE AD\",\"Ġsum mar\",\"Ġover look\",\"ĠApp lication\",\"Ġin appropriate\",\"Ġdownload ed\",\"Q ue\",\"ĠB ears\",\"Ġth umb\",\"ĠChar acter\",\"ĠReincarn ated\",\"ĠS id\",\"Ġdemonstr ates\",\"s ky\",\"ĠBloom berg\",\"ĠAr ray\",\"ĠRes ults\",\"ĠFour th\",\"ĠED T\",\"ĠO scar\",\"c end\",\"Ġ10 6\",\"ĠN ULL\",\"ĠH ERE\",\"m atch\",\"ĠBr un\",\"Ġgluc ose\",\"ie g\",\"eg u\",\"Ġcert ified\",\"Ġrel ie\",\"Ġhuman itarian\",\"Ġpr ayers\",\"K ing\",\"Ġn an\",\"h ou\",\"10 8\",\"ul u\",\"Ġrenew able\",\"Ġdistingu ish\",\"Ġd ense\",\"ĠV ent\",\"ĠPack age\",\"ĠB oss\",\"Ġedit ors\",\"Ġm igr\",\"T ra\",\"ĠPet ers\",\"ĠAr ctic\",\"200 4\",\"ĠC ape\",\"Ġloc ally\",\"Ġlast ing\",\"Ġhand y\",\". ).\",\"P an\",\"ĠR ES\",\"Ind ex\",\"Ġt ensions\",\"Ġformer ly\",\"Ġide ological\",\"Ġsens ors\",\"Ġdeal ers\",\"Ġdef ines\",\"S k\",\"Ġproceed s\",\"Ġpro xy\",\"az ines\",\"ĠB ash\",\"ĠP ad\",\"ĠC raft\",\"eal ous\",\"Ġshe ets\",\"omet ry\",\"J une\",\"cl ock\",\"T T\",\"ĠThe atre\",\"ĠB uzz\",\"Ġch apters\",\"Ġmill enn\",\"Ġd ough\",\"ĠCongress ional\",\"Ġimag ined\",\"av ior\",\"Ġclin ic\",\"Ġ19 45\",\"Ġhold er\",\"ro ot\",\"oles ter\",\"Ġrest art\",\"B N\",\"ĠHam as\",\"ĠJ ob\",\"Ġor b\",\"Ġr am\",\"Ġdiscl ose\",\"Ġtransl ate\",\"Ġimm igrant\",\"Ġannoy ing\",\"Ġtreat y\",\"an ium\",\"ĠTe a\",\"ĠLeg ion\",\"Ġcrowd s\",\"ĠB ec\",\"ĠA er\",\"oh yd\",\"B ro\",\"Look ing\",\"Ġl bs\",\"Ġagg ress\",\"Ġse am\",\"Ġinter cept\",\"ĠM I\",\"mer cial\",\"act iv\",\"ĠC it\",\"Ġdim ension\",\"Ġconsist ency\",\"Ġr ushing\",\"ĠDou glas\",\"Ġtr im\",\"Inst all\",\"ick er\",\"Ġsh y\",\"10 6\",\"Ġment ions\",\"pe lled\",\"ĠT ak\",\"c ost\",\"Ġclass room\",\"Ġfort une\",\"dri ven\",\"Ġun le\",\"ĠWhe el\",\"Ġinvest or\",\"ĠM asters\",\"k it\",\"Ġassoci ations\",\"ĠEv olution\",\"op ing\",\"us cript\",\"Ġprov incial\",\"ĠWal ter\",\"av i\",\"S O\",\"Ġun limited\",\"Eng lish\",\"ĠC ards\",\"ĠEb ola\",\"ne red\",\"Ġreven ge\",\"Ġout right\",\"um per\",\"Ġf itting\",\"ĠSol id\",\"Ġform ally\",\"Ġproblem atic\",\"Ġhaz ard\",\"Ġenc ryption\",\"Ġstraight forward\",\"ĠA K\",\"Ġp se\",\"ĠOr b\",\"ĠCh amber\",\"ĠM ak\",\"Cont ents\",\"Ġloyal ty\",\"Ġl yrics\",\"ĠSy m\",\"Ġwel comed\",\"Ġcook ed\",\"Ġmon op\",\"Ġn urse\",\"Ġmis leading\",\"Ġe ternal\",\"Ġshif ting\",\"Ġ+ =\",\"V is\",\"Ġinst itutional\",\"ill ary\",\"Ġp ant\",\"VER T\",\"ĠA CC\",\"ĠEn h\",\"Ġinc on\",\"ĠRE UTERS\",\"Ġdon ated\",\"âĢ¦âĢ¦ âĢ¦âĢ¦\",\"In tern\",\"Ġexhib it\",\"Ġt ire\",\"ĠR ic\",\"ĠCh ampion\",\"ĠMu hammad\",\"N ING\",\"ĠSoc cer\",\"Ġmob ility\",\"Ġvary ing\",\"ĠM ovie\",\"Ġl ord\",\"o ak\",\"F ield\",\"Ġve ctor\",\"us ions\",\"Ġsc rap\",\"Ġen abling\",\"m ake\",\"T or\",\". *\",\"| |\",\"ĠWe bsite\",\"ĠN PC\",\"Ġsocial ist\",\"ĠBill y\",\"ĠAdd itional\",\"Ġc argo\",\"Ġfar ms\",\"ĠSo on\",\"ĠPri ze\",\"Ġmid night\",\"Ġ9 00\",\"se en\",\"ĠSp ot\",\"Ġshe ep\",\"Ġspons ored\",\"ĠH i\",\"ĠJ ump\",\"Ġ19 67\",\"Micro soft\",\"ĠAg ent\",\"Ġch arts\",\"d ir\",\"Ġadj acent\",\"Ġtr icks\",\"Ġman ga\",\"Ġex agger\",\"/ >\",\"foot ball\",\"ĠF CC\",\"G C\",\"ĠT ier\",\"and ra\",\"OU ND\",\"% ),\",\"Ġfru its\",\"V C\",\"ĠA A\",\"R ober\",\"Ġmid st\",\"â Ĺ\",\"ank a\",\"Ġlegisl ature\",\"ĠNe il\",\"Ġtour ists\",\"\\\" \\\"\",\"ĠWar ning\",\"ĠNever theless\",\"ĠOffic ial\",\"ĠWh atever\",\"Ġm old\",\"Ġdraft ed\",\"Ġsubst ances\",\"Ġbre ed\",\"Ġt ags\",\"ĠT ask\",\"Ġver b\",\"Ġmanufact ured\",\"com ments\",\"ĠPol ish\",\"Pro v\",\"Ġdetermin es\",\"Ob ama\",\"k ers\",\"Ġutter ly\",\"Ġse ct\",\"sc he\",\"ĠG ates\",\"ĠCh ap\",\"Ġal uminum\",\"Ġz ombie\",\"ĠT ouch\",\"ĠU P\",\"Ġsatisf y\",\"Ġpred omin\",\"asc ript\",\"Ġelabor ate\",\"Ġ19 68\",\"Ġmeas uring\",\"ĠV ari\",\"any ahu\",\"Ġs ir\",\"ul ates\",\"id ges\",\"ick ets\",\"ĠSp encer\",\"T M\",\"oub ted\",\"Ġpre y\",\"Ġinstall ing\",\"ĠC ab\",\"re ed\",\"re ated\",\"Su pp\",\"Ġwr ist\",\"ĠK erry\",\"10 7\",\"ĠK le\",\"ĠR achel\",\"Ġc otton\",\"ĠA RE\",\"ĠE le\",\"Cont rol\",\"Ġload s\",\"ĠD od\",\"an as\",\"b one\",\"Ġclass ical\",\"ĠReg ional\",\"ĠInt eg\",\"V M\",\"Ġdes ires\",\"Ġaut ism\",\"support ed\",\"ĠM essage\",\"Ġcomp act\",\"writ er\",\"Ġ10 9\",\"ĠHur ricane\",\"c ision\",\"Ġcy cles\",\"Ġdr ill\",\"Ġcolle ague\",\"Ġm aker\",\"G erman\",\"Ġmist aken\",\"S un\",\"ĠG ay\",\"Ġwhat soever\",\"Ġsell s\",\"ĠA irl\",\"l iv\",\"ĠO ption\",\"Ġsol ved\",\"Ġse ctors\",\"Ġhorizont al\",\"Ġequ ation\",\"ĠSk ill\",\"ĠB io\",\"g ement\",\"ĠSn ap\",\"ĠLeg al\",\"Ġtradem ark\",\"Ġmake up\",\"Ġassemb led\",\"Ġsa ves\",\"ĠHallow een\",\"ĠVer mont\",\"ĠFR OM\",\"Ġfar ming\",\"ĠP odcast\",\"accept able\",\"ĠHig her\",\"Ġas leep\",\"ull ivan\",\"Ġrefere n\",\"ĠLe v\",\"Ġbul lets\",\"ok o\",\"H C\",\"Ġst airs\",\"Ġmain tains\",\"ĠL ower\",\"ĠV i\",\"Ġmar ine\",\"Ġac res\",\"Ġcoordin ator\",\"ĠJ oh\",\"Ġcounterpart s\",\"ĠBrother s\",\"Ġind ict\",\"b ra\",\"Ġch unk\",\"Ġc ents\",\"H ome\",\"ĠMon th\",\"Ġaccording ly\",\"if les\",\"ĠGerm ans\",\"ĠSy n\",\"H ub\",\"Ġey eb\",\"âĶĢâĶĢ âĶĢâĶĢ\",\"Ġr anges\",\"ĠHoll and\",\"ĠRob ot\",\"f c\",\"M ike\",\"Ġpl asma\",\"Ġsw ap\",\"Ġath lete\",\"ĠR ams\",\",' \\\"\",\"Ġinfect ions\",\"Ġcor rid\",\"Ġv ib\",\"Ġpat ches\",\"Ġtradition ally\",\"Ġrevel ation\",\"Ġswe ep\",\"Ġgl ance\",\"Ġin ex\",\"200 3\",\"ĠR aw\",\"work ing\",\"os ures\",\"ĠD at\",\"ĠLyn ch\",\"Ġle verage\",\"ĠRe id\",\"Ġcorrel ation\",\"ian ces\",\"av ascript\",\"Ġrep ository\",\"ret ty\",\"Ġ19 72\",\"24 0\",\"Ġo un\",\"p ol\",\"ĠRe ed\",\"Ġtact ical\",\"is ite\",\"App le\",\"ĠQu inn\",\"Ġrap ed\",\"ill o\",\"Euro pe\",\"Ġalgorith ms\",\"ĠRod rig\",\"i u\",\"Ġill um\",\"Ġf ame\",\"Ġintrodu cing\",\"Ġdel ays\",\"ĠRaid ers\",\"Ġwh istle\",\"Ġnovel s\",\"ĠRe ally\",\"Ġder iv\",\"Ġpublic ations\",\"ĠNe ither\",\"ĠCom merce\",\"Ġa ston\",\"l anguage\",\"Not es\",\"ĠR oth\",\"ĠF ear\",\"Ġm ate\",\"Ġpar ade\",\"ĠQ B\",\"Ġman eu\",\"ĠC incinnati\",\"m itting\",\"Ġwa ist\",\"ĠR ew\",\"Ġdisc ont\",\"Ð °\",\"Ġst aring\",\"Ġal ias\",\"Ġsec urities\",\"Ġtoile t\",\"ĠJ edi\",\"Ġun law\",\"v ised\",\"//// ////\",\"] (\",\"ĠWe iss\",\"Ġpre st\",\"ĠComp an\",\"Ġmem o\",\"ĠGr ace\",\"J uly\",\"ĠEl ite\",\"cent er\",\"ĠSt ay\",\"Ġgal axy\",\"Ġto oth\",\"ĠS ettings\",\"Ġsubject ed\",\"ãĤ ¦\",\"Ġline back\",\"Ġretail ers\",\"ĠW ant\",\"Ġd angers\",\"A ir\",\"Ġvolunt ary\",\"ew ay\",\"Ġinterpret ed\",\"ot ine\",\"Ã §\",\"Ġp el\",\"Serv ice\",\"ĠEvent ually\",\"Ġcare ers\",\"Ġthreat en\",\"Ġmem or\",\"ĠBrad ley\",\"anc ies\",\"s n\",\"ĠUn known\",\"N ational\",\"Ġsh adows\",\"ail and\",\"ĠD ash\",\"Every one\",\"izz ard\",\"M arch\",\"= (\",\"Ġpull s\",\"Ġstr anger\",\"Ġback wards\",\"ĠBern ard\",\"imens ional\",\"Ġch ron\",\"Ġtheoret ical\",\"k top\",\"Ġw are\",\"ĠInvest ig\",\"ĠIn iti\",\"ĠOper ations\",\"o ven\",\"oc ide\",\"* /\",\"Ġfl ames\",\"ĠC ash\",\"sh it\",\"Ġc ab\",\"ĠAn aly\",\"ĠSe ah\",\"Ġdefin ing\",\"Ġorder ing\",\"Ġimm un\",\"Ġpers istent\",\"AC H\",\"Russ ian\",\"m ans\",\"Ġh ind\",\"Ġphot ography\",\"Â ©\",\"Ġh ug\",\"Ġ10 7\",\"ĠH ence\",\"i ots\",\"ude au\",\"Ġsubsid ies\",\"Ġroutine ly\",\"ĠDev ice\",\"it ic\",\"Ġdisg ust\",\"land er\",\"Ġ19 40\",\"Ġassign ment\",\"ĠB esides\",\"w ick\",\"ĠD ust\",\"us c\",\"struct ed\",\"11 1\",\"de velop\",\"Ġf ond\",\"Ġinter section\",\"Ġdign ity\",\"Ġcommission er\",\"With out\",\"re ach\",\"Ġcart oon\",\"Ġsc ales\",\"ãĥ Ń\",\"F IG\",\"Ġsurve ys\",\"ĠIndones ia\",\"Ġart work\",\"Ġun ch\",\"Ġcy cling\",\"un ct\",\"au er\",\"or ate\",\"ĠOb viously\",\"Ġcharacter ized\",\"fe ld\",\"Ġaff irm\",\"Ġinn ings\",\"Ġ é\",\"Ġal iens\",\"Ġcl oth\",\"et ooth\",\"ĠC ertain\",\"Â §\",\"Ġdig est\",\"k now\",\"ĠX L\",\"Ġpredict ions\",\"Ġd in\",\"W AR\",\"Ġafter math\",\"Ex ample\",\"ĠSu ccess\",\"ĠTh r\",\"IG N\",\"Ġmin er\",\"B us\",\"Ġcl arity\",\"heim er\",\"ĠO UT\",\"ĠS end\",\"ĠCirc le\",\"ĠD iet\",\"Ġpron ounced\",\"Ġcreat ors\",\"Ġearthqu ake\",\"atter y\",\"ge ons\",\"Ġo d\",\"Ġlay ing\",\"or p\",\"U lt\",\"pro ject\",\"Ġunder min\",\"Ġsequ el\",\"S am\",\"ĠDark ness\",\"Ġre ception\",\"b ull\",\"Y S\",\"ĠV ir\",\"Ġsequ ences\",\"ĠCo in\",\"Ġout fit\",\"ĠW ait\",\"1 19\",\"Ġdel ivers\",\".... ..\",\"Ġbl own\",\"ĠE sc\",\"ĠM ath\",\"per m\",\"ĠU l\",\"Ġgl im\",\"Ġfac ial\",\"Ġgreen house\",\"Ġto kens\",\"/ -\",\"ĠAnn ual\",\"ĠON E\",\"Ġteen age\",\"ĠPhys ical\",\"ĠL ang\",\"ĠC elt\",\"Ġsu ed\",\"ivid ually\",\"Ġpat ience\",\"ch air\",\"reg ular\",\"Ġa ug\",\"in v\",\"ex cept\",\"ĠL il\",\"Ġn est\",\"f d\",\"s um\",\"ĠCh ase\",\"Russ ia\",\"ĠJenn ifer\",\"Ġoff season\",\"Over all\",\"F ore\",\"Ġr iot\",\"A ud\",\"form er\",\"Ġdefend ers\",\"ĠC T\",\"iot ic\",\"rib ly\",\"Ġautom ated\",\"Ġpen is\",\"Ġins ist\",\"Ġdi agram\",\"ĠS QL\",\"ĠG arc\",\"Ġw itch\",\"cl ient\",\"ier ra\",\"am bers\",\"Ġrec ount\",\"f ar\",\"V ery\",\"oster one\",\"Ġappreci ated\",\"ĠPer fect\",\"S ection\",\"Ġd oses\",\"oca ust\",\"Ġcost ly\",\"Ġg rams\",\"ĠSh i\",\"Ġwrest ling\",\"Ġ19 71\",\"Ġtro phy\",\"Ġn erve\",\"ĠK az\",\"ĠExper ience\",\"Ġpled ged\",\"Ġplay back\",\"Ġcreat ivity\",\"by e\",\"Ġattack ers\",\"Ġhold ers\",\"ĠCo ach\",\"ĠPh D\",\"Ġtransf ers\",\"Ġcol ored\",\"ĠH indu\",\"Ġd rown\",\"Ġlist ened\",\"ĠW A\",\"ias m\",\"P O\",\"Ġappeal ing\",\"Ġdiscl osed\",\"ĠCh icken\",\"ag ging\",\"Ġple aded\",\"Ġnav igation\",\"ĠReturn s\",\"Ġ[ [\",\"R OR\",\"E A\",\"Ġphotograp her\",\"ĠR ider\",\"ipp ers\",\"Ġsl ice\",\"Ġe rect\",\"Ġhe d\",\"iss ance\",\"ĠVik ings\",\"ur ious\",\"Ġapp et\",\"oubted ly\",\"Ch ild\",\"Ġauthent ic\",\"o os\",\"ĠM aking\",\"Ġannoun cing\",\"Ġb od\",\"Ġmet er\",\"ĠN ine\",\"ĠR ogue\",\"Ġwork force\",\"Ġrenew ed\",\"Ġorganis ations\",\"ac s\",\"P LE\",\"Sh ort\",\"Ġcomp ounds\",\"ĠVis it\",\"Ġen velop\",\"ear th\",\"Ġsupport ive\",\"gg le\",\"ĠBrus sels\",\"ĠGu ild\",\"Cre ate\",\"RE L\",\"Ġaver aged\",\"Ġ19 69\",\"ri ages\",\"Ġlength y\",\"Ġforg ot\",\"O kay\",\"ĠE rd\",\"Ġdeal er\",\"Ġrec ession\",\"D D\",\"Ġdesper ately\",\"Ġhun ger\",\"Ġst icks\",\"Ġm ph\",\"ĠF aith\",\"Ġintention ally\",\"Ġdem ol\",\"ue ller\",\"ĠS ale\",\"Ġde bris\",\"s pring\",\"Ġle ap\",\">> >>\",\"Ġcontain ers\",\"se lling\",\"rane an\",\"atter ing\",\"Ġcomment ed\",\"ĠC M\",\"on ut\",\"Ġwood s\",\"es pecially\",\"Ġorgan ize\",\"iv ic\",\"ĠWood s\",\"ang a\",\"s qu\",\"Ġm aj\",\"am on\",\"Ġax is\",\"Ġ19 74\",\"ĠDen mark\",\"Ġwar rior\",\"ĠP and\",\"Ġout lined\",\"ĠB O\",\"ins ula\",\"z illa\",\"eb ook\",\"Ġd are\",\"Ġsear ched\",\"Ġnav igate\",\"S n\",\"writ ing\",\"Ġun ited\",\"J apan\",\"ĠHe brew\",\"Ġfl ame\",\"Ġrel ies\",\"Ġcatch ing\",\"ĠSh o\",\"Ġimprison ment\",\"Ġp ockets\",\"Ġclos ure\",\"ĠF am\",\"t im\",\"ade qu\",\"Act ivity\",\"Ġrecru iting\",\"ĠW ATCH\",\"ĠArgent ina\",\"d est\",\"Ġapolog ize\",\"or o\",\"Ġlack s\",\"Ġtun ed\",\"ĠGriff in\",\"Ġinf amous\",\"Ġcelebr ity\",\"ss on\",\"Ġ ----------------------------------------------------------------\",\"ĠIs is\",\"ĠDis play\",\"Ġcred ibility\",\"Ġeconom ies\",\"Ġhead line\",\"ĠCow boys\",\"Ġind ef\",\"Ġl ately\",\"Ġincent ives\",\"but ton\",\"ĠM ob\",\"A ut\",\"Ġres igned\",\"ĠO m\",\"c amp\",\"Ġprof iles\",\"Ġsche mes\",\"olph ins\",\"ay ed\",\"Cl inton\",\"en h\",\"ĠY ahoo\",\"Ġab st\",\"Ġan k\",\"su its\",\"Ġw ished\",\"ĠMar co\",\"udd en\",\"Ġsp here\",\"ĠB ishop\",\"Ġincorpor ated\",\"ĠPl ant\",\"11 4\",\"Ġh ated\",\"p ic\",\"Ġdon ate\",\"Ġl ined\",\"Ġbe ans\",\"Ġsteal ing\",\"Ġcost ume\",\"Ġsher iff\",\"Ġfor ty\",\"Ġint act\",\"Ġadapt ed\",\"Ġtrave lling\",\"b art\",\"Ġnice ly\",\"Ġdri ed\",\"Ġsc al\",\"os ity\",\"NOT E\",\"ĠB h\",\"ĠBron cos\",\"ĠI gn\",\"Ġint imate\",\"Ġchem istry\",\"Ġopt imal\",\"D eb\",\"ĠGener ation\",\"Ġ] ,\",\"ich i\",\"ĠW ii\",\"ĠYOU R\",\"vent ions\",\"W rite\",\"Ġpop ul\",\"un ning\",\"ĠW or\",\"V ol\",\"Ġqu een\",\"head s\",\"K K\",\"Ġanaly ze\",\"op ic\",\"ear chers\",\"Ġd ot\",\"leg raph\",\"ast ically\",\"Ġupgr ades\",\"Ġca res\",\"Ġext ending\",\"Ġfree ze\",\"Ġin ability\",\"Ġorg ans\",\"Ġpret end\",\"Ġout let\",\"11 3\",\"ol an\",\"ĠM all\",\"ul ing\",\"t alk\",\"Ġexpress ing\",\"ĠAl ways\",\"ĠBe gin\",\"f iles\",\"Ġlic enses\",\"% %\",\"ĠM itt\",\"Ġfil ters\",\"ĠMil waukee\",\"G N\",\"Ġunf old\",\"M o\",\"Ġnut rition\",\"pp o\",\"B o\",\"Ġfound ing\",\"Ġunder mine\",\"Ġeas iest\",\"ĠC zech\",\"ĠM ack\",\"Ġsexual ity\",\"ĠN ixon\",\"W in\",\"ĠAr n\",\"ĠK in\",\"ãĤ £\",\"ic er\",\"Ġfort un\",\"Ġsurf aces\",\"agh d\",\"Ġcar riers\",\"ĠP ART\",\"ĠT ib\",\"Ġinter val\",\"Ġfrust rating\",\"ĠSh ip\",\"ĠAr med\",\"ff e\",\"Ġbo ats\",\"ĠAb raham\",\"in is\",\"Ġsu ited\",\"th read\",\"i ov\",\"ab ul\",\"ĠVenezuel a\",\"Ġto m\",\"su per\",\"Ġcast le\",\"alth ough\",\"iox ide\",\"ec hes\",\"Ġevolution ary\",\"Ġnegoti ate\",\"Ġconfront ed\",\"Rem ember\",\"Ġ17 0\",\"S uch\",\"Ġ9 11\",\"m ult\",\"ĠA byss\",\"ur ry\",\"ke es\",\"spe c\",\"ĠBarb ara\",\"Ġbelong ing\",\"Ġvill ain\",\"ist ani\",\"Ġaccount able\",\"Ġport ions\",\"ĠDe cl\",\"U r\",\"ĠK ate\",\"g re\",\"Ġmag azines\",\"UC K\",\"Ġregul ate\",\"om on\",\"ĠAl most\",\"Ġover view\",\"Ġsc ram\",\"Ġl oot\",\"ĠF itz\",\"Ġcharacter istic\",\"ĠSn ake\",\"s ay\",\"ĠR ico\",\"Ġtra it\",\"ĠJo ined\",\"au cus\",\"Ġadapt ation\",\"ĠAirl ines\",\"Ġarch ae\",\"ĠI de\",\"Ġb ikes\",\"Ġliter ary\",\"Ġinflu ences\",\"ĠUs ed\",\"C reat\",\"Ġple a\",\"ĠDef ence\",\"ĠAss ass\",\"Ġp ond\",\"UL T\",\") \\\"\",\"Ġeval uated\",\"Ġob taining\",\"Ġdem ographic\",\"Ġvig il\",\"ale y\",\"Ġsp ouse\",\"ĠSeah awks\",\"resp ons\",\"ĠB elt\",\"um atic\",\"Ġr ises\",\"run ner\",\"ĠMichel le\",\"Ġpot ent\",\"r ace\",\"ĠP AC\",\"F ind\",\"olester ol\",\"IS S\",\"ĠIntrodu ced\",\"ress es\",\"ign ment\",\"O s\",\"ĠT u\",\"ĠDe x\",\"ic ides\",\"Ġspark ed\",\"ĠLaur a\",\"ĠBry ant\",\"Ġsm iling\",\"ĠNex us\",\"Ġdefend ants\",\"ĠCat al\",\"Ġdis hes\",\"sh aped\",\"Ġpro long\",\"m t\",\"( $\",\"ãĢ Ĥ\",\"Ġcalcul ations\",\"ĠS ame\",\"Ġp iv\",\"H H\",\"Ġcance lled\",\"Ġgr in\",\"Ġterrit ories\",\"ist ically\",\"C ome\",\"ĠP arent\",\"Pro ject\",\"Ġneg lig\",\"ĠPriv acy\",\"Ġam mo\",\"LE CT\",\"olute ly\",\"ĠEp ic\",\"Ġmis under\",\"w al\",\"Apr il\",\"m os\",\"path y\",\"ĠC arson\",\"Ġalbum s\",\"ĠE asy\",\"Ġpist ol\",\"< <\",\"Ġ\\\\ (\",\"t arget\",\"hel p\",\"Ġinter pre\",\"cons cious\",\"ĠH ousing\",\"ĠJ oint\",\"12 7\",\"Ġbe ers\",\"s cience\",\"ĠFire fox\",\"effect ive\",\"ĠC abin\",\"ĠO kay\",\"ĠApp lic\",\"Ġspace craft\",\"ĠS R\",\"ve t\",\"ĠStr ange\",\"S B\",\"Ġcor ps\",\"iber al\",\"e fficient\",\"Ġpreval ence\",\"Ġeconom ists\",\"11 8\",\"Th read\",\"ord able\",\"OD E\",\"ĠC ant\",\"=- =-\",\"if iable\",\"ĠA round\",\"Ġpo le\",\"Ġwilling ness\",\"CL A\",\"ĠK id\",\"Ġcomple ment\",\"Ġsc attered\",\"Ġin mates\",\"Ġble eding\",\"e very\",\"Ġque ue\",\"ĠTr ain\",\"Ġh ij\",\"Ġme lee\",\"ple ted\",\"Ġdig it\",\"Ġg em\",\"offic ial\",\"Ġlif ting\",\"Ð µ\",\"Re qu\",\"it utes\",\"Ġpack aging\",\"ĠWork ers\",\"h ran\",\"ĠLeban on\",\"ol esc\",\"Ġpun ished\",\"ĠJ uan\",\"Ġj am\",\"ĠD ocument\",\"Ġm apping\",\"ic ates\",\"Ġinev itably\",\"Ġvan illa\",\"ĠT on\",\"Ġwat ches\",\"Ġle agues\",\"Ġiniti ated\",\"deg ree\",\"port ion\",\"Ġrec alls\",\"Ġru in\",\"Ġm elt\",\"I AN\",\"Ġhe m\",\"Ex p\",\"Ġb aking\",\"ĠCol omb\",\"at ible\",\"Ġrad ius\",\"pl ug\",\"ĠI F\",\"et ically\",\"Ġf ict\",\"H ER\",\"ĠT ap\",\"atin um\",\"Ġin k\",\"Ġco h\",\"ĠW izard\",\"b oth\",\"te x\",\"Ġsp ends\",\"ĠCurrent ly\",\"ĠP it\",\"Ġneur ons\",\"ig nt\",\"Ġr all\",\"Ġbus es\",\"b uilding\",\"Ġadjust ments\",\"Ġc ried\",\"ibl ical\",\"att ed\",\"ĠZ ion\",\"ĠM atter\",\"Ġmed itation\",\"ĠD ennis\",\"Ġour s\",\"ĠT ab\",\"Ġrank ings\",\"ort al\",\"Ġad vers\",\"Ġsur render\",\"ĠG ob\",\"ci um\",\"om as\",\"im eter\",\"Ġmulti player\",\"Ġhero in\",\"Ġoptim istic\",\"Ġindic ator\",\"ĠBr ig\",\"Ġgro cery\",\"Ġapplic ant\",\"ĠRock et\",\"v id\",\"Ex ception\",\"p ent\",\"Ġorgan izing\",\"Ġenc ounters\",\"ĠT OD\",\"Ġjew el\",\"S ave\",\"ĠChrist ie\",\"Ġhe ating\",\"Ġl azy\",\"ĠC P\",\"Ġcous in\",\"Con fig\",\"Ġreg ener\",\"Ġne arest\",\"Ġachie ving\",\"EN S\",\"th row\",\"ĠRich mond\",\"ant le\",\"200 2\",\"Ġan ten\",\"b ird\",\"13 3\",\"Ġn arc\",\"r aint\",\"un ny\",\"ĠHispan ic\",\"ourn aments\",\"Ġprop he\",\"ĠTh ailand\",\"ĠT i\",\"Ġinject ion\",\"Ġinher it\",\"rav is\",\"Ġmed i\",\"Ġwho ever\",\"ĠDE BUG\",\"G P\",\"ĠH ud\",\"C ard\",\"p rom\",\"Ġp or\",\"Ġover head\",\"L aw\",\"Ġviol ate\",\"Ġhe ated\",\"Ġdescript ions\",\"Ġachieve ments\",\"ĠBe er\",\"ĠQu ant\",\"W as\",\"Ġe ighth\",\"ĠI v\",\"Ġspecial ized\",\"U PDATE\",\"ĠD elta\",\"P op\",\"J ul\",\"ĠAs k\",\"oph y\",\"Ġnews letters\",\"ĠT ool\",\"Ġg ard\",\"ĠConf eder\",\"ĠGM T\",\"ĠAb bott\",\"Ġimm unity\",\"ĠV M\",\"Is lam\",\"Ġimpl icit\",\"w d\",\"Ġ19 44\",\"rav ity\",\"omet ric\",\"Ġsurv iving\",\"ur ai\",\"ĠPr ison\",\"Ġr ust\",\"ĠSk etch\",\"Ġbe es\",\"ĠThe ory\",\"Ġmer it\",\"T ex\",\"ch at\",\"Ġm im\",\"Ġpast e\",\"ĠK och\",\"Ġignor ance\",\"ĠSh oot\",\"Ġbas ement\",\"Un ited\",\"ĠAd vis\",\"he ight\",\"Ġf oster\",\"Ġdet ain\",\"in formation\",\"Ġne ural\",\"' ;\",\"Ġprov es\",\"all ery\",\"Ġinv itation\",\"um bers\",\"Ġc attle\",\"Ġbicy cle\",\"z i\",\"Ġconsult ant\",\"Ġap ology\",\"ĠT iger\",\"Ġ12 3\",\"99 9\",\"Ġind ividually\",\"r t\",\"ig ion\",\"ĠBrazil ian\",\"Ġdist urb\",\"Ġentreprene urs\",\"Ġfore sts\",\"cer pt\",\"pl ates\",\"p her\",\"clip se\",\"Ġtw itter\",\"Ġac ids\",\"ograph ical\",\"h um\",\"ĠB ald\",\"if ully\",\"Ġcomp iler\",\"ĠD A\",\"Ġdon or\",\"as i\",\"Ġtrib al\",\"l ash\",\"ĠCon fig\",\"Ġapplic ants\",\"Ġsal aries\",\"13 5\",\"Put in\",\"ĠF ocus\",\"ir s\",\"Ġmisc onduct\",\"ĠH az\",\"Ġeat en\",\"M obile\",\"Mus lim\",\"ĠMar cus\",\"v iol\",\"Ġfavor able\",\"Ġst ub\",\"ad in\",\"ĠH ob\",\"Ġfaith ful\",\"Ġelectron ics\",\"Ġvac uum\",\"w ait\",\"back ed\",\"econom ic\",\"d ist\",\"Ġten ure\",\"Ġsince re\",\"ĠT ogether\",\"ĠW ave\",\"Ġprog ression\",\"Ġden ying\",\"Ġdist ress\",\"br aska\",\"th ird\",\"Ġmix ing\",\"Ġcolon ial\",\"Ġpriv ately\",\"Ġun rest\",\"atern ity\",\"Ġprem ises\",\"ant i\",\"greg ation\",\"Ġlic ence\",\"ĠH ind\",\"ĠSam uel\",\"Ġconvinc ing\",\"ĠA ce\",\"ĠR ust\",\"ĠNet anyahu\",\"Ġhand les\",\"ĠP atch\",\"orient ed\",\"ah o\",\"ĠG onz\",\"Ġhack ers\",\"claim er\",\"Ġcustom s\",\"ĠGr an\",\"f ighters\",\"Ġl uc\",\"Ġman uscript\",\"aren thood\",\"Ġdev il\",\"Ġwar riors\",\"Ġoff enders\",\"Will iam\",\"Ġhol idays\",\"Ġnight mare\",\"Ġle ver\",\"iff erent\",\"St at\",\"Ġexhib ition\",\"put ed\",\"ĠP ure\",\"Ġal pha\",\"Ġenthus iasm\",\"ĠRepresent atives\",\"E AR\",\"ĠT yp\",\"Ġwhe at\",\"ĠAl f\",\"Ġcor rection\",\"Ġev angel\",\"AT T\",\"M iss\",\"Ġs oup\",\"Ġimpl ied\",\"par am\",\"Ġsex y\",\"ĠL ux\",\"Ġrep ublic\",\"p atch\",\"ab lish\",\"Ġic ons\",\"Ġfather s\",\"ĠG ET\",\"ĠCar ib\",\"Ġregul ated\",\"ĠCo hen\",\"ĠBob by\",\"Ġn er\",\"Ġb ent\",\"vent ory\",\"ĠAl ong\",\"ĠE ST\",\"ĠWall ace\",\"Ġmurd ers\",\"r ise\",\"ke ll\",\"ĠCommon wealth\",\"Ġn asty\",\"et a\",\"ĠM IT\",\"Ġadminist ered\",\"Ġgenuine ly\",\"Ed itor\",\"n ick\",\"Ġhyd ro\",\"**************** ****************\",\"ĠB le\",\"Ġfin es\",\"Ġg orge\",\"aus ible\",\"r h\",\"Ġapp le\",\"ment ioned\",\"Ġro pe\",\"ot yp\",\"H R\",\"Ġdisappoint ing\",\"Ġc age\",\"n ik\",\"Ġdoub ts\",\"ĠF REE\",\"print s\",\"ĠM UST\",\"Ġvend ors\",\"ĠIn qu\",\"Ġliber als\",\"Ġcontract or\",\"Ġup side\",\"child ren\",\"Ġtrick y\",\"Ġregul ators\",\"charg ed\",\"l iter\",\"Ġ ***\",\"Ġreb ell\",\"l ang\",\"Ġloc als\",\"Ġphys icians\",\"Ġhe y\",\"ar se\",\"t m\",\"ĠLe x\",\"Ġbehavior al\",\"success ful\",\"F X\",\"Ġbr ick\",\"ov ic\",\"Ġcon form\",\"Ġreview ing\",\"Ġins ights\",\"Ġbi ology\",\"ĠRem ove\",\"ĠExt ra\",\"Ġcomm itting\",\"indu ced\",\"ignt y\",\"ig m\",\"Ġat omic\",\"Comm on\",\"ĠE M\",\"ĠP ere\",\"ĠIt ems\",\"e h\",\"Ġpres erved\",\"ĠH ood\",\"Ġprison er\",\"Ġbankrupt cy\",\"Ġg ren\",\"us hes\",\"Ġexplo itation\",\"Ġsign atures\",\"Ġfin an\",\"] ,\\\"\",\"ĠM R\",\"Ġme g\",\"rem lin\",\"Ġmusic ians\",\"Ġselect ing\",\"Ġexam ining\",\"IN K\",\"l ated\",\"H i\",\"Ġart ic\",\"Ġp ets\",\"Ġimp air\",\"ĠM AN\",\"Ġtable ts\",\"in clude\",\"R ange\",\"Ġca ut\",\"Ġlog s\",\"Ġmount ing\",\"Ġun aware\",\"Ġdynam ics\",\"ĠPalest ine\",\"ĠQu arter\",\"ĠPur ple\",\"Ġm a\",\"ĠIm port\",\"Ġcollect ions\",\"ci ation\",\"Ġsuccess or\",\"Ġcl one\",\"Ġaim ing\",\"Ġposs essed\",\"Ġstick ing\",\"Ġsh aking\",\"Ġloc ate\",\"ĠH ockey\",\"T urn\",\"17 0\",\"Ġfif teen\",\"ĠHar rison\",\"Ġcontinu ously\",\"ĠT C\",\"ĠVal ent\",\"ĠRes cue\",\"Ġby pass\",\"am ount\",\"Ġm ast\",\"Ġprotect s\",\"Ġart istic\",\"Ġsomet ime\",\"Ġsh oe\",\"Ġshout ed\",\"ific ant\",\"et itive\",\"ĠReg ister\",\"ĠJ in\",\"Ġconcent rated\",\"ling ton\",\"on ies\",\"Ġgener ator\",\"yr im\",\"ĠAr men\",\"Ġclear ing\",\"id o\",\"ĠT W\",\"al ph\",\"Ġlad ies\",\"H ard\",\"Ġdial og\",\"Ġinput s\",\"æ ľ\",\"Ġpos es\",\"Ġsl ots\",\"ĠPrem ium\",\"Ġle aks\",\"Ġboss es\",\"Ġ11 3\",\"c ourse\",\"A cc\",\"ĠNew ton\",\"ĠAust ria\",\"ĠM age\",\"Ġte aches\",\"ab ad\",\"Ġwe ars\",\"Ġc yl\",\"Ġcur se\",\"ĠS ales\",\"ĠW ings\",\"Ġp sy\",\"Ġg aps\",\"ĠIce land\",\"ĠP interest\",\"Ġland lord\",\"Ġdefin itions\",\"ĠK er\",\"Ġsufficient ly\",\"ĠP ence\",\"ĠArch itect\",\"Ġsur pass\",\"Ġ11 4\",\"Ġsuper hero\",\"ĠDise ase\",\"Ġpri ests\",\"ĠC ulture\",\"Ġdefin itive\",\"Ġsecret ly\",\"ĠD ance\",\"inst all\",\"ch ief\",\"ĠJess ica\",\"W ould\",\"Up dated\",\"Ġlock er\",\"ĠK ay\",\"Ġmem orial\",\"è ¦\",\"f at\",\"Ġdis gu\",\"Ġflav ors\",\"ĠBase ball\",\"ĠRes istance\",\"Ġk icks\",\"Ġen v\",\"Ġteen agers\",\"D ark\",\"ĠC AR\",\"Ġh alt\",\"ĠL G\",\"ĠGab riel\",\"Ġfe ver\",\"Ġs atur\",\"Ġm all\",\"Ġaffili ate\",\"ĠS leep\",\"ĠSpe cific\",\"ĠV el\",\"Ġj ar\",\"ĠSac red\",\"ĠEd wards\",\"ĠA CL\",\"Ġret ained\",\"ĠG iant\",\"Ġlim itation\",\"in ces\",\"Ġref usal\",\"ĠT ale\",\"ĠBut ler\",\"Ġacc idents\",\"ĠC SS\",\"Ġimport ed\",\"ĠCop y\",\"Î ±\",\"ER T\",\"z el\",\"Ġdiv isions\",\"h ots\",\"ĠAl b\",\"ĠD S\",\"Load er\",\"W ashington\",\"at isf\",\"ĠCreat ive\",\"\\\\ .\",\"ĠAut om\",\"red ict\",\"Ġrecept or\",\"ĠCarl os\",\"Met hod\",\"ok a\",\"Ġmal icious\",\"Ġste pping\",\", [\",\"ĠD ad\",\"Ġatt raction\",\"ĠEffect s\",\"ĠPir ate\",\"ĠC er\",\"ĠIndust ry\",\"ĠR ud\",\"Ġchar ter\",\"Ġd ining\",\"Ġins ists\",\"Ġconfig ure\",\"Ġ( #\",\"ĠSim ple\",\"ĠSc roll\",\"UT C\",\"17 5\",\"ĠK on\",\"Ġmarket place\",\"Ġ ãĤ\",\"Ġref res\",\"Ġg ates\",\"er red\",\"ĠP od\",\"Ġbeh ave\",\"Fr ank\",\"n ode\",\"Ġendors ed\",\"he tt\",\"as ive\",\"ĠHom eland\",\"Ġr ides\",\"ĠLe ave\",\"er ness\",\"Ġflood ing\",\"A FP\",\"Ġris en\",\"Ġcontin ually\",\"Ġun anim\",\"ĠCont ract\",\"ĠP as\",\"Ġgu ided\",\"ĠCh ile\",\"b d\",\"Ġsu cc\",\"pt ic\",\"Ġcomm ittees\",\"ĠL uther\",\"ĠAny one\",\"Ġs ab\",\"12 4\",\"Ġp ixel\",\"ĠB ak\",\"ĠT ag\",\"ĠBenn ett\",\"En ter\",\"sm all\",\"ĠPresident ial\",\"Ġp ul\",\"Ġcontr ace\",\"arch ive\",\"Ġcoast al\",\"ĠK ids\",\"19 2\",\"âĢ ²\",\"ick y\",\"ING TON\",\"Ġw olf\",\"ĠSt alin\",\"T ur\",\"id get\",\"am as\",\"ĠUn less\",\"Ġspons or\",\"Ġmor ph\",\"ĠCho ose\",\"Ġrun ner\",\"Ġun bel\",\"Ġm ud\",\"ĠMan a\",\"Ġdub bed\",\"Ġg odd\",\"ure rs\",\"wind ow\",\"Ġrel ied\",\"Ġcelebr ating\",\"os c\",\"Ġ13 5\",\"Ġlobb ying\",\"Ġincom plete\",\"Ġrestrict ion\",\"Ġinc ap\",\"it us\",\"Ġexpect ation\",\"ĠAp ollo\",\"Ġint ens\",\"Ġsyn c\",\"G H\",\"Ġmanip ulation\",\"B Y\",\"Ġspe ar\",\"Ġbre asts\",\"Ġvol can\",\"il ia\",\"M aterial\",\"Ġform ats\",\"ĠB ast\",\"Ġparliament ary\",\"Ġsn ake\",\"Ġserv ants\",\"ĠTr udeau\",\"ĠGr im\",\"ĠArab ic\",\"ĠSC P\",\"ĠBoy s\",\"st ation\",\"Ġprospect ive\",\"ord e\",\"in itialized\",\"Ġb ored\",\"AB LE\",\"Ġaccess ed\",\"Ġtax i\",\"ĠShe ll\",\"aid en\",\"urs ed\",\"in ates\",\"ĠIns urance\",\"ĠPet e\",\"Sept ember\",\"6 50\",\"Ġad ventures\",\"ĠCo ver\",\"Ġt ribute\",\"Ġsk etch\",\"Ġem power\",\"Ġ Ø\",\"ĠGl enn\",\"ĠD aw\",\"= \\\\\\\"\",\"ĠPolit ics\",\"Ġgu ides\",\"Ġd ioxide\",\"ĠG ore\",\"ĠBr ight\",\"ĠS ierra\",\"Ġval ued\",\"c ond\",\"Ġpo inter\",\"Se lect\",\"Ġrisk y\",\"Ġabsor b\",\"im ages\",\"Ġref uses\",\"Ġbon uses\",\"__ _\",\"Ġh ilar\",\"ĠF eatures\",\"2 20\",\"ĠCollect or\",\"F oot\",\"Ġ19 64\",\"cul us\",\"Ġd awn\",\"Ġwork out\",\"ĠL O\",\"Ġphilosoph ical\",\"ĠSand y\",\"ĠYou th\",\"Ġl iable\",\"A f\",\"bl ue\",\"Ġovert urn\",\"less ness\",\"ĠTrib une\",\"ĠIn g\",\"Ġfact ories\",\"Ġcat ches\",\"Ġpr one\",\"Ġmat rix\",\"Ġlog in\",\"Ġin acc\",\"Ġex ert\",\"s ys\",\"Ġneed le\",\"ĠQ ur\",\"Ġnot ified\",\"ould er\",\"t x\",\"Ġremind s\",\"Ġpublisher s\",\"Ġn ort\",\"Ġg it\",\"Ġfl ies\",\"ĠEm ily\",\"Ġflow ing\",\"ĠAl ien\",\"ĠStr ateg\",\"Ġhard est\",\"Ġmod ification\",\"AP I\",\"ĠM Y\",\"Ġcr ashes\",\"st airs\",\"n umber\",\"Ġur ging\",\"ch annel\",\"ĠFal con\",\"Ġinhabit ants\",\"Ġterr ifying\",\"Ġutil ize\",\"Ġban ner\",\"Ġcig arettes\",\"Ġsens es\",\"ĠHol mes\",\"Ġpract ition\",\"ĠPhill ips\",\"ott o\",\"Ġcomp ile\",\"Mod el\",\"ĠK o\",\"Ġ[ ]\",\"Americ ans\",\"ĠTer ms\",\"Ġmed ications\",\"ĠAn a\",\"Ġfundament ally\",\"ĠNot ice\",\"Ġwe aker\",\"Ġ 0000\",\"Ġgar lic\",\"Ġout break\",\"Ġeconom ist\",\"ĠB irth\",\"Ġobst acles\",\"ar cer\",\"ĠOr thodox\",\"Ġplace bo\",\"ĠC rew\",\"asp berry\",\"ĠAng els\",\"Ġdis charge\",\"Ġdestruct ive\",\"11 7\",\"ĠR ising\",\"Ġd airy\",\"l ate\",\"Ġcoll ision\",\"ĠTig ers\",\"ean or\",\"ocument ed\",\"ĠIn valid\",\"Ġd ont\",\"ĠL iter\",\"ĠV a\",\"Ġhyd rogen\",\"Ġvari ants\",\"ĠBrown s\",\"Ġ19 65\",\"Ġind igenous\",\"Ġtrad es\",\"Ġremain der\",\"Ġswe pt\",\"ĠImp act\",\"Ġred ist\",\"Ġun int\",\"grad uate\",\"ãĥ ķ\",\"ĠW ILL\",\"ãģ® ç\",\"ĠCrit ical\",\"Ġf isher\",\"Ġv icious\",\"Ġrevers ed\",\"Y ear\",\"ĠS ox\",\"Ġshoot ings\",\"Ġfil ming\",\"Ġtouchdown s\",\"ai res\",\"m el\",\"Ġgrand father\",\"Ġaffect ion\",\"ing le\",\"Ġover ly\",\"Add itional\",\"Ġsup reme\",\"ĠGr ad\",\"Ġsport ing\",\"Ġmer cy\",\"ĠBrook s\",\"ount y\",\"Ġperform s\",\"Ġtight ly\",\"Ġdem ons\",\"Ġkill ings\",\"Ġfact ion\",\"ĠNov a\",\"aut s\",\"Ġund oubtedly\",\"ar in\",\"Ġunder way\",\"ra k\",\"Ġl iv\",\"ĠReg ion\",\"Ġbrief ing\",\"s ers\",\"cl oud\",\"ĠM ik\",\"us p\",\"Ġpred iction\",\"az or\",\"Ġport able\",\"ĠG and\",\"Ġpresent ing\",\"Ġ10 80\",\"Â »\",\"ush i\",\"ĠSp ark\",\"there um\",\"Ġjust ification\",\"ĠN y\",\"Ġcontract ors\",\"ming ham\",\"ĠSt yle\",\"å ħ\",\"ĠChron icles\",\"ĠPict ure\",\"Ġprov ing\",\"Ġw ives\",\"set t\",\"Ġmole cules\",\"ĠFair y\",\"Ġconsist ing\",\"Ġp ier\",\"al one\",\"in ition\",\"Ġn ucle\",\"j son\",\"Ġg otta\",\"Ġmob il\",\"Ġver bal\",\"ar ium\",\"Ġmon ument\",\"uck ed\",\"Ġ25 6\",\"T ech\",\"mine craft\",\"ĠTr ack\",\"Ġt ile\",\"Ġcompat ibility\",\"as is\",\"Ġs add\",\"Ġinstruct ed\",\"ĠM ueller\",\"Ġle thal\",\"Ġhorm one\",\"Ġor che\",\"el se\",\"Ġske let\",\"Ġentert aining\",\"Ġminim ize\",\"ag ain\",\"Ġunder go\",\"Ġconst raints\",\"Ġcig arette\",\"ĠIslam ist\",\"Ġtravel s\",\"ĠPant hers\",\"l ings\",\"C are\",\"Ġlaw suits\",\"ur as\",\"Ġcry st\",\"Ġlow ered\",\"Ġaer ial\",\"Ġcomb inations\",\"Ġha un\",\"Ġch a\",\"Ġv ine\",\"Ġquant ities\",\"Ġlink ing\",\"b ank\",\"Ġso y\",\"B ill\",\"ĠAngel a\",\"Ġrecip ient\",\"ĠProt est\",\"Ġs ocket\",\"Ġsolid arity\",\"Ġâ Ĩ\",\"m ill\",\"Ġvar ies\",\"ĠPak istani\",\"Dr agon\",\"Ġun e\",\"Ġhor izon\",\"ÂłÂłÂłÂł ÂłÂłÂłÂł\",\"Ġprov inces\",\"Ġfrank ly\",\"Ġenact ed\",\"not es\",\"[ '\",\"Ġ19 2\",\"ocr acy\",\"Ġendorse ment\",\"Ġover time\",\"Tr ue\",\"L ab\",\"lic ted\",\"ĠD NC\",\"Ġbe ats\",\"ĠJam ie\",\"15 2\",\"ĠIN T\",\"Cont act\",\"Ġaccount ed\",\"h ash\",\"ĠPack ers\",\"p ires\",\"Ġles bian\",\"Ġamend ments\",\"Ġhop eful\",\"ĠFin land\",\"Ġspot light\",\"Ġconfig ured\",\"Ġtrou bled\",\"Ġg aze\",\"ĠCal gary\",\"Ġrel iability\",\"Ġins urg\",\"sw er\",\"b uy\",\"ĠSk in\",\"Ġp ixels\",\"Ġhand gun\",\"Ġpar as\",\"Ġcateg or\",\"ĠE L\",\"ĠRe x\",\"Ind eed\",\"Ġkind a\",\"Ġconj unction\",\"ĠBry an\",\"ĠMan ufact\",\"y ang\",\"Pl us\",\"S QL\",\"ish ment\",\"Ġdom inate\",\"Ġn ail\",\"Ġo ath\",\"Ġeru pt\",\"ĠF ine\",\"it bart\",\"ĠCh ip\",\"ĠAb d\",\"ĠN am\",\"Ġbuy er\",\"Ġdiss ent\",\"Le aks\",\"Cont in\",\"Ġr ider\",\"ĠSome one\",\"Ġill usion\",\"c in\",\"ĠBoe ing\",\"Ġin adequ\",\"ov ation\",\"i ants\",\"Ġreb uild\",\"4 50\",\"ĠDest iny\",\"S W\",\"ĠT ill\",\"H it\",\"ia z\",\"ĠBang l\",\"acher s\",\"ĠRe form\",\"Ġse gments\",\"Ġsystem atic\",\"d c\",\"ĠConserv atives\",\"Ġport al\",\"h or\",\"ĠDragon bound\",\"Ġdrag ged\",\"om o\",\"Ġthe e\",\"ad vert\",\"ĠRep orts\",\"ĠE t\",\"Ġbarrel s\",\"Aug ust\",\"Ġcompar isons\",\"Ġhe x\",\"Ġan throp\",\"\\\" [\",\"bor ough\",\"ab i\",\"Ġpict ured\",\"play ing\",\"ĠAdd ress\",\"ĠMir ror\",\"Sm ith\",\"Ġt ires\",\"ĠN PR\",\"AA AA\",\"Ġclass ification\",\"ĠTh an\",\"ĠH arm\",\"ĠR A\",\"Ġreject ion\",\"min ation\",\"Ġr anged\",\"ĠF alls\",\"D I\",\"H ost\",\"ãĤ ´\",\"ĠEx ample\",\"list ed\",\"th irds\",\"Ġsaf egu\",\"br and\",\"Ġprob able\",\"Can ada\",\"IT ION\",\"ĠQ aeda\",\"Ġch ick\",\"Ġimport s\",\"h it\",\"l oc\",\"W W\",\"Ġble w\",\"Ġany time\",\"Ġwh oles\",\"ik ed\",\"Ġcal culation\",\"cre ate\",\"ĠO ri\",\"Ġupgr aded\",\"Ġapp ar\",\"ut ory\",\"ĠM ol\",\"B rit\",\"ĠJ ong\",\"IN AL\",\"ĠStart ing\",\"Ġd ice\",\"urt le\",\"Ġre lying\",\"cl osure\",\"Ġprof itable\",\"Ġsl aughter\",\"ĠMan ual\",\"c aster\",\"Ġ\\\" $\",\"Ġfe ather\",\"ĠSim ply\",\"ie ves\",\"Ġdeter ior\",\"ĠPC I\",\"Ġst amp\",\"Ġfl aws\",\"Ġsh ade\",\"ham mer\",\"Ġpass port\",\"Ġcont ing\",\"am el\",\"Ġobser vers\",\"Ġneg lect\",\"ĠR B\",\"ĠBrother hood\",\"Ġskept ical\",\"f amily\",\"us k\",\"Ġemotion ally\",\"â Ļ\",\"ĠBet a\",\"ason able\",\"id ity\",\"ĠM ul\",\"Ġkick ing\",\"ĠC arm\",\"oll ah\",\"VERT IS\",\"ĠAt hen\",\"Ġlad der\",\"ĠBul let\",\"å £\",\"00 01\",\"ĠWild life\",\"ĠM ask\",\"ĠN an\",\"R ev\",\"Ġun acceptable\",\"leg al\",\"Ġcrowd ed\",\"ag i\",\"ĠC ox\",\"j e\",\"Ġmor ality\",\"Ġfu els\",\"Ġc ables\",\"Ġman kind\",\"ĠCarib bean\",\"Ġanch or\",\"Ġby te\",\"ĠO ften\",\"ĠO z\",\"Ġcraft ed\",\"Ġhistor ian\",\"ĠW u\",\"Ġtow ers\",\"ĠCitiz ens\",\"Ġhel m\",\"Ġcred entials\",\"Ġsing ular\",\"ĠJes se\",\"Ġtack les\",\"Ġcont empt\",\"Ġa fore\",\"ĠSh adows\",\"Ġn il\",\"Ġur gent\",\"app le\",\"bl ood\",\"Ġv on\",\"Ġoff line\",\"Ġbreat he\",\"Ġj umps\",\"Ġirre levant\",\"ox ic\",\"om al\",\"import ant\",\"J im\",\"Ġgl oves\",\"arm ing\",\"dep th\",\"Ġtal ents\",\"ook ie\",\"ĠS B\",\"Ġpal m\",\"uff s\",\"est a\",\"IG H\",\"Ġcan on\",\"ĠVer izon\",\"ĠP le\",\"Ġcou pled\",\"vel t\",\"Ġfundra ising\",\"ĠGet ting\",\"ĠD LC\",\"Ġmathemat ical\",\"ĠH S\",\"ĠCard inals\",\"te lling\",\"Ġspons ors\",\"Ġ Ï\",\"ĠBull s\",\"op tion\",\"Ġprop ose\",\"Ġmem orable\",\"Ġembr aced\",\"Ġdecl ining\",\"He alth\",\"ed a\",\"Ġ} ;\",\"Ġsp am\",\"m ile\",\"Ġpit cher\",\"ĠE ight\",\"Ġcar ing\",\"ut ic\",\"ro le\",\"Ġair line\",\"ernand ez\",\"ĠAth let\",\"Ġcert ification\",\"ux e\",\"rig er\",\"Ġem pir\",\"Ġsens ation\",\"Ġdis m\",\"Ġb olt\",\"Ġev olve\",\"H ouse\",\"Ġconsult ation\",\"ĠD uty\",\"Ġtou ches\",\"ĠN athan\",\"Ġf aint\",\"h ad\",\"\\\" (\",\"ĠCons umer\",\"ĠExt reme\",\"Ġ12 7\",\"ĠHer m\",\"ĠSac rament\",\"iz oph\",\"Ġanx ious\",\"ul ously\",\"Ġsoc ially\",\"ĠU TC\",\"Ġsol ving\",\"ĠLet ter\",\"Hist ory\",\"ed uc\",\"Pr ice\",\") );\",\"Ġrel oad\",\"am ic\",\"Ġp ork\",\"Ġdisc ourse\",\"Ġt ournaments\",\"ai ro\",\"ĠK ur\",\"ĠCost a\",\"Ġviol ating\",\"Ġinterf ere\",\"Ġrecre ational\",\"uff le\",\"Ġspe eches\",\"Ġneed ing\",\"Ġremem bers\",\"Ġcred ited\",\"n ia\",\"f ocused\",\"amer a\",\"Ġb ru\",\"um bs\",\"ĠCub an\",\"Ġpreced ing\",\"Ġnons ense\",\"ac ial\",\"Ġsmart phones\",\"ĠSt ories\",\"S ports\",\"ĠEmer gency\",\"oun cing\",\"ef ined\",\"Ġb er\",\"Ġconsult ing\",\"Ġm asters\",\"he astern\",\".\\\" [\",\"ĠRun ning\",\"Ġsus cept\",\"ĠF eng\",\"Americ a\",\"pr ises\",\"st itial\",\"ĠWeek ly\",\"ĠGreat er\",\"mod ules\",\"if ter\",\"G raphics\",\"ul er\",\"Ġwho lly\",\"Ġsupp ress\",\"Ġconce aled\",\"Ġhapp ily\",\"Ġaccept s\",\"ĠEn joy\",\"Ġr ivers\",\"ĠEx cept\",\"2 25\",\"ĠN HS\",\"ĠMc Connell\",\"Ġp ussy\",\"fer red\",\"ut able\",\"Ġatt ain\",\"Ġ> =\",\"Ġdepos its\",\"roph ic\",\"Ġnot orious\",\"ĠSh aw\",\"il itation\",\"Ġepid emic\",\"all ic\",\"Ġsmall est\",\"ov ich\",\"Ġaccess ories\",\"per ties\",\"Ġsur plus\",\"ĠMe ch\",\"Ġamb ig\",\"ĠImm igration\",\"Ġch im\",\"ev al\",\"Ġpract icing\",\"ĠMyster y\",\"Ġdom ains\",\"ĠSil icon\",\"app s\",\"Ġkilomet ers\",\"e a\",\"ĠSm ash\",\"Ġwarrant y\",\"Ġn ost\",\"s il\",\"re v\",\"J on\",\"ĠDub lin\",\"Ġtast es\",\"Ġb out\",\"g reat\",\"er ror\",\"Ġsw itches\",\"ĠB apt\",\"D O\",\"ok i\",\"Ġsour ced\",\"pro du\",\"Ġattach ment\",\"ĠIss ue\",\"ĠQuest ion\",\"Jo in\",\"Ġf itted\",\"Ġunlaw ful\",\"^ ^\",\"ere k\",\"Ġauthent ication\",\"Ġst ole\",\"Ġaccount ability\",\"l abel\",\"S earch\",\"Ġal beit\",\"atic an\",\"fund ed\",\"ĠAdd ing\",\"ĠI Q\",\"Ġsub mar\",\"l it\",\"a que\",\"ĠLear ning\",\"Ġint eger\",\"M aster\",\"ĠCh rom\",\"Ġprem ier\",\"O p\",\"ĠLi u\",\"Ġbl essed\",\"ĠGl obe\",\"ĠResp onse\",\"Ġlegit im\",\"ĠMer kel\",\"Ġdispos al\",\"Â ´\",\"Ġgau ge\",\"pe at\",\"Ġindu ced\",\"Ġquestion able\",\"arth y\",\"ĠV it\",\"ĠF eed\",\"U ntil\",\"U t\",\"worth y\",\"R Y\",\"ĠH erald\",\"ĠHam mer\",\"Ġmed al\",\"ĠR ivers\",\"ĠH ack\",\"Ġclar ify\",\"Ġtrack ed\",\"Ġautonom ous\",\"Ġten ant\",\"ĠQ atar\",\"er ie\",\"Ġgr im\",\"ĠMon itor\",\"Ġresist ant\",\"ĠSpe c\",\"ĠWell s\",\"N AS\",\"14 8\",\"Ġmin ers\",\"iot ics\",\"Ġmiss es\",\"11 6\",\"g ian\",\"g it\",\"ĠE yes\",\"p res\",\"Ġgrad uated\",\"Ġang el\",\"Ġsyn chron\",\"Ġefficient ly\",\"Ġtrans mitted\",\"H arry\",\"Ġglob ally\",\"EN CE\",\"ĠMont ana\",\"r aged\",\"ĠPre vention\",\"Ġp iss\",\"ĠL l\",\"Ġshe lf\",\"ĠB JP\",\"ĠTest ament\",\"ĠL ate\",\"ik er\",\"ĠH app\",\"ĠJul ian\",\"h all\",\"Ġsp ont\",\"Ġshut down\",\"Ġincons istent\",\"Ġsubscrib ers\",\"Ġske leton\",\"ĠNe braska\",\"Ġins pire\",\"ĠV oid\",\"F eed\",\"Ġang les\",\"ĠSpr ings\",\"Ġbench mark\",\"Ġvacc ines\",\"izoph ren\",\"se xual\",\"uff ed\",\"Ġsh ine\",\"ĠK ath\",\"Ġgest ure\",\"ine a\",\"Ġr ip\",\"Ġopp ression\",\"Ġcons cience\",\"b t\",\"ĠL um\",\"Ġinc idence\",\"ĠF a\",\"w r\",\"Ġmin eral\",\"ĠSp urs\",\"alk y\",\"Ġth under\",\"Ġop io\",\"Be ing\",\"ĠPal m\",\"Ġwas ted\",\"Ġl b\",\"i aries\",\"ĠIniti ative\",\"Ġcur ric\",\"Ġmark er\",\"ĠMc L\",\"Ġext ensions\",\"ĠP v\",\"ĠAr ms\",\"Ġoffer ings\",\"Ġdef enses\",\"Ġvend or\",\"Ġcontrad ict\",\"ĠCol in\",\"Ġredd it\",\"Ġper ipher\",\"12 2\",\"Ġs ins\",\"E dit\",\"IC T\",\"So ft\",\"ĠSh ah\",\"Ġadministr ator\",\"ĠT rip\",\"Ġporn ography\",\"Ġtu ition\",\"in ence\",\"ĠPro gress\",\"Ġcat alog\",\"Ġsu ite\",\"Ġh ike\",\"Ġreprodu ctive\",\"eng ine\",\"Ġd rought\",\"ĠNo ah\",\"Ġ2 30\",\"Ġd ude\",\"Ġrelax ed\",\"Ġpart ition\",\"Ġparticip ant\",\"Ġtel esc\",\"Ġfe as\",\"ĠF F\",\"own er\",\"Ġswe eping\",\"Ġl enses\",\"Ġmatch up\",\"ĠRe pl\",\"ourn als\",\"Ġcred ible\",\"Ġgrand mother\",\"Ġther mal\",\"Ġsubscrib ing\",\"Ġident ities\",\"col m\",\"U CT\",\"Ġreluct ant\",\"us ers\",\"ĠC ort\",\"Ġassist ed\",\"OS S\",\"ATION S\",\"IS H\",\"Ġpharm aceutical\",\"ic able\",\"ad ian\",\"ĠSon ic\",\"ĠF ury\",\"ĠM ong\",\"A H\",\"ĠPsych ology\",\"Ġph osph\",\"Ġtreat s\",\"Ń Ķ\",\"Ġstead ily\",\"ĠHell o\",\"Ġrel ates\",\"Ġcl ue\",\"Ex pl\",\"a uth\",\"Ġrev ision\",\"Ġe ld\",\"os ion\",\"Ġbr on\",\"14 4\",\"ri kes\",\"Ġmin es\",\"Ġblank et\",\"ĠF ail\",\"el ed\",\"ĠIm agine\",\"ĠPl anned\",\"a ic\",\"Re quest\",\"M ad\",\"ĠHor se\",\"ĠEag le\",\"Ġcap ac\",\"15 7\",\"Ġl ing\",\"ĠN ice\",\"ĠP arenthood\",\"min ster\",\"og s\",\"ens itive\",\"Not hing\",\"Ġcar n\",\"F in\",\"ĠP E\",\"Ġr ifles\",\"ĠL P\",\"S and\",\"Ġgui Active\",\"Ġtour ist\",\"C NN\",\"Ġunve iled\",\"Ġpredec essor\",\"} {\",\"u ber\",\"Ġoff shore\",\"Ġopt ical\",\"ĠR ot\",\"ĠPear l\",\"et on\",\"Ġst ared\",\"Ġfart her\",\"at ility\",\"cont in\",\"ĠG y\",\"ĠF oster\",\"ĠC oc\",\"ri ents\",\"Ġdesign ing\",\"ĠEconom y\",\"ON G\",\"W omen\",\"ĠN ancy\",\"er ver\",\"Ġmas cul\",\"Ġcasual ties\",\"Ġ2 25\",\"ĠS ullivan\",\"ĠCh oice\",\"Ġa ster\",\"w s\",\"Ġhot els\",\"Ġconsider ations\",\"Ġcou ch\",\"ĠSt rip\",\"ĠG n\",\"Ġmanip ulate\",\"l ied\",\"Ġsynt hetic\",\"Ġassault ed\",\"Ġoff enses\",\"ĠDra ke\",\"Ġim pe\",\"Oct ober\",\"ĠHer itage\",\"h l\",\"ĠBl air\",\"Un like\",\"Ġg rief\",\"Ġ4 50\",\"Ġopt ed\",\"Ġresign ation\",\"il o\",\"Ġver se\",\"ĠT omb\",\"Ġu pt\",\"Ġa ired\",\"ĠH ook\",\"ĠML B\",\"Ġassum es\",\"out ed\",\"ĠV ers\",\"Ġinfer ior\",\"Ġbund le\",\"ĠD NS\",\"ograp her\",\"Ġmult ip\",\"ĠSoul s\",\"Ġillust rated\",\"Ġtact ic\",\"Ġdress ing\",\"Ġdu o\",\"Con f\",\"Ġrel ent\",\"Ġc ant\",\"Ġscar ce\",\"Ġcand y\",\"ĠC F\",\"Ġaffili ated\",\"Ġspr int\",\"yl an\",\"ĠGarc ia\",\"Ġj unk\",\"Pr int\",\"ex ec\",\"C rit\",\"Ġport rait\",\"ir ies\",\"ĠOF F\",\"Ġdisp utes\",\"W R\",\"L ove\",\"ãģ Ħ\",\"ĠRe yn\",\"Ġh ipp\",\"op ath\",\"Ġflo ors\",\"ĠFe el\",\"Ġwor ries\",\"Ġsett lements\",\"ĠP os\",\"Ġmos que\",\"Ġfin als\",\"Ġcr ushed\",\"ĠPro bably\",\"ĠB ot\",\"ĠM ans\",\"ĠPer iod\",\"Ġsovere ignty\",\"Ġsell er\",\"Ġap ost\",\"Ġam ateur\",\"Ġd orm\",\"Ġconsum ing\",\"Ġarm our\",\"ĠRo ose\",\"Ġint ensive\",\"Ġelim inating\",\"ĠSun ni\",\"ĠAle ppo\",\"j in\",\"Ġadv ise\",\"p al\",\"ĠH alo\",\"Ġdes cent\",\"Ġsimpl er\",\"Ġbo oth\",\"ST R\",\"L ater\",\"ĠC ave\",\"== =\",\"Ġm ol\",\"Ġf ist\",\"Ġshot gun\",\"su pp\",\"Ġrob bery\",\"E ffect\",\"Ġobsc ure\",\"ĠProf essional\",\"Ġemb assy\",\"Ġmilit ant\",\"Ġinc arcer\",\"Ġgener ates\",\"Ġlaun ches\",\"Ġadministr ators\",\"Ġsh aft\",\"Ġcirc ular\",\"Ġfresh man\",\"ĠW es\",\"ĠJo el\",\"ĠD rew\",\"ĠDun can\",\"ĠApp arently\",\"s ight\",\"ĠIntern al\",\"ĠInd ividual\",\"ĠF E\",\"Ġb ore\",\"ĠM t\",\"Ġbroad ly\",\"ĠO ptions\",\"ount ain\",\"ip es\",\"ĠV ideos\",\"20 4\",\"Ġh ills\",\"Ġsim ulation\",\"Ġdisappoint ment\",\"it an\",\"ĠLabor atory\",\"Ġup ward\",\"Ġbound ary\",\"Ġdark er\",\"h art\",\"Ġdomin ance\",\"C ong\",\"ĠOr acle\",\"ĠL ords\",\"Ġscholars hip\",\"ĠVin cent\",\"ed e\",\"ĠR ah\",\"Ġencour ages\",\"ro v\",\"Ġqu o\",\"Ġprem ise\",\"ĠCris is\",\"ĠHol ocaust\",\"Ġrhyth m\",\"Ġmet ric\",\"cl ub\",\"Ġtransport ed\",\"Ġn od\",\"ĠP ist\",\"Ġancest ors\",\"ĠFred er\",\"th umbnails\",\"ĠC E\",\"ON D\",\"Ph il\",\"ven ge\",\"ĠProduct s\",\"cast le\",\"Ġqual ifying\",\"ĠK aren\",\"VERTIS EMENT\",\"Ġmight y\",\"Ġexplan ations\",\"Ġfix ing\",\"D i\",\"Ġdecl aring\",\"Ġanonym ity\",\"Ġju ven\",\"ĠN ord\",\"ĠDo om\",\"ĠAct ually\",\"O k\",\"ph is\",\"ĠDes ert\",\"Ġ11 6\",\"I K\",\"ĠF M\",\"Ġinc omes\",\"V EL\",\"ok ers\",\"Ġpe cul\",\"Ġlight weight\",\"g ue\",\"Ġacc ent\",\"Ġincre ment\",\"ĠCh an\",\"Ġcompl aining\",\"ĠB aghd\",\"Ġmidfield er\",\"Ġover haul\",\"Pro cess\",\"ĠH ollow\",\"ĠTit ans\",\"Sm all\",\"man uel\",\"ĠUn ity\",\"ĠEv ents\",\"S ty\",\"Ġdispro portion\",\"n esty\",\"en es\",\"ĠC od\",\"Ġdemonstr ations\",\"ĠCrim son\",\"ĠO H\",\"Ġen rolled\",\"Ġc el\",\"ĠBre tt\",\"Ġa ide\",\"Ġhe els\",\"Ġbroad band\",\"Ġmark ing\",\"Ġw izard\",\"ĠN J\",\"ĠChief s\",\"Ġingred ient\",\"Ġd ug\",\"ĠSh ut\",\"urch ase\",\"end or\",\"Ġfar mer\",\"ĠGold man\",\"12 9\",\"15 5\",\"Or der\",\"Ġl ion\",\"i ably\",\"Ġst ain\",\"ar ray\",\"ilit ary\",\"ĠFA Q\",\"Ġexpl oded\",\"ĠMcC arthy\",\"ĠT weet\",\"ĠG reens\",\"ek ing\",\"l n\",\"ens en\",\"Ġmotor cycle\",\"Ġpartic le\",\"Ġch olesterol\",\"B ron\",\"Ġst air\",\"Ġox id\",\"Ġdes irable\",\"ib les\",\"Ġthe or\",\"for cing\",\"Ġpromot ional\",\"ov o\",\"b oot\",\"ĠBon us\",\"raw ling\",\"Ġshort age\",\"ĠP sy\",\"Ġrecru ited\",\"Ġinf ants\",\"Ġtest osterone\",\"Ġded uct\",\"Ġdistinct ive\",\"Ġfirm ware\",\"bu ilt\",\"14 5\",\"Ġexpl ored\",\"Ġfact ions\",\"Ġv ide\",\"Ġtatt oo\",\"Ġfinan cially\",\"Ġfat igue\",\"Ġproceed ing\",\"const itutional\",\"Ġmis er\",\"Ġch airs\",\"gg ing\",\"ipp le\",\"Ġd ent\",\"Ġdis reg\",\"ç Ķ\",\"st ant\",\"ll o\",\"b ps\",\"aken ing\",\"Ġab normal\",\"ĠE RA\",\"å£ «\",\"ĠH BO\",\"ĠM AR\",\"Ġcon cess\",\"Ġserv ant\",\"Ġas pir\",\"l av\",\"ĠPan el\",\"am o\",\"Ġprec ip\",\"Ġrecord ings\",\"Ġproceed ed\",\"Ġcol ony\",\"ĠT ang\",\"ab lo\",\"Ġstri pped\",\"Le ft\",\"to o\",\"Ġpot atoes\",\"Ġfin est\",\"% ).\",\"Ġc rap\",\"ĠZ ach\",\"ab ases\",\"ĠG oth\",\"Ġbillion aire\",\"w olf\",\"Ġsan ction\",\"S K\",\"Ġlog ged\",\"P o\",\"ey ed\",\"un al\",\"Ġcr icket\",\"Ġarm ies\",\"Ġunc overed\",\"Cl oud\",\"Ã³ n\",\"Ġreb ounds\",\"Ġm es\",\"O per\",\"P ac\",\"Ġnation ally\",\"Ġinsert ed\",\"p ict\",\"Ġgovern ance\",\"Ð ¸\",\"Ġprivile ges\",\"G ET\",\"Ġfavor ites\",\"im ity\",\"Ġlo ver\",\"the m\",\"em pl\",\"Ġgorge ous\",\"An n\",\"Ġsl ipped\",\"Ġve to\",\"B ob\",\"Ġsl im\",\"u cc\",\"ĠF ame\",\"udden ly\",\"Ġden ies\",\"ĠM aur\",\"Ġdist ances\",\"Ġw anna\",\"t ar\",\"ĠS ER\",\"Ġâ Ī\",\"Ġle mon\",\"at hetic\",\"Ġlit eral\",\"Ġdistingu ished\",\"Ġansw ering\",\"G I\",\"Ġrelig ions\",\"ĠPhil os\",\"ĠL ay\",\"Ġcomp os\",\"ire ments\",\"ĠK os\",\"ine z\",\"roll ing\",\"Ġyoung est\",\"and ise\",\"ĠB orn\",\"Ġalt ar\",\"am ina\",\"ĠB oot\",\"v oc\",\"Ġdig ging\",\"Ġpress ures\",\"Ġl en\",\"26 4\",\"Ġassass ination\",\"ĠBir mingham\",\"ĠMy th\",\"Ġsovere ign\",\"ĠArt ist\",\"ĠPhot ograph\",\"Ġdep icted\",\"Ġdisp ens\",\"orth y\",\"Ġamb ul\",\"int eg\",\"ĠC ele\",\"ĠTib et\",\"Ġhier archy\",\"Ġc u\",\"Ġpre season\",\"ĠPet erson\",\"Ġcol ours\",\"Ġworry ing\",\"Ġback ers\",\"ĠPal mer\",\"ĠÎ ¼\",\"Ġcontribut or\",\"Ġhear ings\",\"Ġur ine\",\"Ġ Ù\",\"ourge ois\",\"Sim ilar\",\"ĠZ immer\",\"s omething\",\"ĠUS C\",\"Ġstrength s\",\"ĠF I\",\"Ġlog ging\",\"As ked\",\"ĠTh ai\",\"in qu\",\"ĠW alt\",\"Ġcrew s\",\"it ism\",\"3 01\",\"Ġshar ply\",\"um ed\",\"Ġred irect\",\"r ators\",\"In f\",\"ĠWe apons\",\"Ġte asp\",\"19 99\",\"L ive\",\"ĠEs pecially\",\"ĠS ter\",\"ĠVeter ans\",\"Ġint ro\",\"other apy\",\"Ġmal ware\",\"Ġbre eding\",\"Ġmole cular\",\"ĠR oute\",\"ĠCom ment\",\"oc hem\",\"Ġa in\",\"Se ason\",\"Ġlineback er\",\"Ä «\",\"ĠEconom ics\",\"es ar\",\"ĠL ives\",\"ĠEm ma\",\"Ġk in\",\"ĠTer rit\",\"Ġpl anted\",\"ot on\",\"ĠBut ter\",\"ĠSp ons\",\"P ER\",\"Ġdun geon\",\"Ġsymb olic\",\"Ġfil med\",\"Ġdi ets\",\"Ġconclud es\",\"Ġcertain ty\",\"ĠForm at\",\"Ġstr angers\",\"form at\",\"ĠPh ase\",\"Ġcop ied\",\"Ġmet res\",\"ld a\",\"ĠUs ers\",\"Ġdeliber ate\",\"Ġwas hed\",\"ĠL ance\",\"im ation\",\"Ġimpro per\",\"ĠGen esis\",\"ick r\",\"ĠK ush\",\"Ġreal ise\",\"Ġembarrass ing\",\"alk ing\",\"b ucks\",\"Ġver ified\",\"Ġout line\",\"year s\",\"ĠIn come\",\"20 2\",\"Ġz ombies\",\"F inal\",\"ĠMill enn\",\"Ġmod ifications\",\"ĠV ision\",\"ĠM oses\",\"ver b\",\"iter ranean\",\"ĠJ et\",\"Ġnav al\",\"ĠA gg\",\"Ġur l\",\"Ġvict ories\",\"Ġnon etheless\",\"Ġinj ust\",\"ĠF act\",\"ç ļ\",\"Ġins ufficient\",\"re view\",\"face book\",\"Ġnegoti ating\",\"Ġguarant ees\",\"im en\",\"uten berg\",\"Ġg ambling\",\"Ġcon gr\",\"Load ing\",\"Ġnever theless\",\"Ġpres idents\",\"ĠIndust rial\",\"Ġ11 8\",\"Ġp oured\",\"ĠT ory\",\"Ġ17 5\",\"Ġ: =\",\"Sc ott\",\"ange red\",\"T ok\",\"Ġorgan izers\",\"M at\",\"ĠG rowth\",\"Ġad ul\",\"Ġens ures\",\"Ġ11 7\",\"é¾į å\",\"Ġmass acre\",\"Ġgr ades\",\"be fore\",\"AD VERTISEMENT\",\"ĠSl ow\",\"ĠM MA\",\"âĢĶ \\\"\",\"ĠV atican\",\"Q aeda\",\"Ġo we\",\"66 66\",\"ĠS orry\",\"ĠGr ass\",\"Ġbackground s\",\"Ġexha usted\",\"Ġcl an\",\"Ġcomprom ised\",\"ĠE lf\",\"ĠIsa ac\",\"ens on\",\"In vest\",\"IF A\",\"Ġinterrupt ed\",\"ãĥī ãĥ©\",\"Ġtw isted\",\"ĠDrag ons\",\"M ode\",\"ĠK remlin\",\"Ġfert il\",\"he res\",\"ph an\",\"ĠN ode\",\"f ed\",\"ĠOr c\",\"Ġunw illing\",\"C ent\",\"Ġprior it\",\"Ġgrad uates\",\"Ġsubject ive\",\"Ġiss uing\",\"ĠL t\",\"Ġview er\",\"Ġw oke\",\"Th us\",\"bro ok\",\"Ġdep ressed\",\"Ġbr acket\",\"ĠG or\",\"ĠFight ing\",\"Ġstri ker\",\"Rep ort\",\"ĠPortug al\",\"Ġne o\",\"w ed\",\"19 9\",\"Ġflee ing\",\"sh adow\",\"ident ified\",\"US E\",\"Ste am\",\"Ġstret ched\",\"Ġrevel ations\",\"art ed\",\"ĠD w\",\"Ġalign ment\",\"est on\",\"ĠJ ared\",\"S ep\",\"Ġblog s\",\"up date\",\"g om\",\"r isk\",\"Ġcl ash\",\"ĠH our\",\"Ġrun time\",\"Ġunw anted\",\"Ġsc am\",\"Ġr ack\",\"Ġen light\",\"on est\",\"ĠF err\",\"Ġconv ictions\",\"Ġp iano\",\"Ġcirc ulation\",\"ĠW elcome\",\"Ġback lash\",\"ĠW ade\",\"Ġrece ivers\",\"ot ive\",\"J eff\",\"Ġnetwork ing\",\"ĠPre p\",\"ĠExpl orer\",\"Ġlect ure\",\"Ġupload ed\",\"ĠMe at\",\"B LE\",\"ĠNaz is\",\"ĠSy nd\",\"st ud\",\"ro ots\",\"ri ans\",\"Ġportray ed\",\"Ġ ??\",\"ĠBudd ha\",\"s un\",\"Rober t\",\"ĠCom plex\",\"Ġover see\",\"Ġste alth\",\"T itle\",\"ĠJ obs\",\"ĠK um\",\"Ġappreci ation\",\"ĠM OD\",\"Ġbas ics\",\"Ġcl ips\",\"Ġnurs ing\",\"Ġpropos ition\",\"Ġreal ised\",\"ĠNY C\",\"Ġall ocated\",\"ri um\",\"ar an\",\"ĠPro duction\",\"ĠV ote\",\"Ġsm ugg\",\"Ġhun ter\",\"az er\",\"ĠCh anges\",\"Ġfl uct\",\"y on\",\"Ar ray\",\"Ġk its\",\"W ater\",\"Ġuncom mon\",\"Ġrest ing\",\"ell s\",\"w ould\",\"Ġpurs ued\",\"Ġassert ion\",\"omet own\",\"ĠMos ul\",\"ĠPl atform\",\"io let\",\"Ġshare holders\",\"Ġtra ils\",\"P ay\",\"ĠEn forcement\",\"ty pes\",\"ĠAn onymous\",\"Ġsatisf ying\",\"il ogy\",\"Ġ( '\",\"w ave\",\"c ity\",\"Ste ve\",\"Ġconfront ation\",\"ĠE ld\",\"C apt\",\"ah an\",\"ht m\",\"ĠC trl\",\"ON S\",\"2 30\",\"if a\",\"hold ing\",\"Ġdelic ate\",\"Ġj aw\",\"ĠGo ing\",\"or um\",\"S al\",\"Ġd ull\",\"ĠB eth\",\"Ġpr isons\",\"Ġe go\",\"ĠEl sa\",\"avor ite\",\"ĠG ang\",\"ĠN uclear\",\"Ġsp ider\",\"ats u\",\"Ġsam pling\",\"Ġabsor bed\",\"ĠPh arm\",\"iet h\",\"Ġbuck et\",\"ĠRec omm\",\"O F\",\"ĠF actory\",\"AN CE\",\"Ġb acter\",\"H as\",\"ĠObs erv\",\"12 1\",\"Ġprem iere\",\"De velop\",\"Ġcur rencies\",\"C ast\",\"Ġaccompany ing\",\"ĠNash ville\",\"Ġfat ty\",\"ĠBre nd\",\"Ġloc ks\",\"Ġcent ered\",\"ĠU T\",\"augh s\",\"or ie\",\"ĠAff ordable\",\"v ance\",\"D L\",\"em et\",\"Ġthr one\",\"ĠBlu etooth\",\"Ġn aming\",\"if ts\",\"AD E\",\"Ġcorrect ed\",\"Ġprompt ly\",\"ĠST R\",\"Ġgen ome\",\"Ġcop e\",\"Ġval ley\",\"Ġround ed\",\"ĠK end\",\"al ion\",\"p ers\",\"Ġtour ism\",\"Ġst ark\",\"v l\",\"Ġblow ing\",\"ĠSche dule\",\"st d\",\"Ġunh appy\",\"Ġlit igation\",\"ced es\",\"Ġand roid\",\"Ġinteg ral\",\"ere rs\",\"ud ed\",\"t ax\",\"Ġre iter\",\"ĠMot ors\",\"oci ated\",\"Ġwond ers\",\"ĠAp ost\",\"uck ing\",\"ĠRoose velt\",\"f ram\",\"Ġyield s\",\"Ġconstit utes\",\"aw k\",\"Int erest\",\"Ġinter im\",\"Ġbreak through\",\"ĠC her\",\"Ġpro sec\",\"ĠD j\",\"ĠM T\",\"Res p\",\"ĠP T\",\"Ġs perm\",\"ed it\",\"B T\",\"Lin ux\",\"count ry\",\"le ague\",\"Ġd ick\",\"Ġo ct\",\"Ġinsert ing\",\"Ġsc ra\",\"ĠBrew ing\",\"Ġ19 66\",\"Ġrun ners\",\"Ġpl un\",\"id y\",\"ĠD ian\",\"Ġdys function\",\"Ġex clusion\",\"Ġdis gr\",\"Ġincorpor ate\",\"Ġrecon c\",\"Ġnom inated\",\"ĠAr cher\",\"d raw\",\"achel or\",\"Ġwrit ings\",\"Ġshall ow\",\"Ġh ast\",\"ĠB MW\",\"ĠR S\",\"Ġth igh\",\"Ġ19 63\",\"Ġl amb\",\"Ġfav ored\",\"ag le\",\"Ġcool er\",\"ĠH ours\",\"ĠG U\",\"ĠOrig in\",\"Ġglim pse\",\"---------------- ----\",\"L im\",\"Ġche ek\",\"Ġj ealous\",\"- '\",\"Ġhar ness\",\"ĠPo ison\",\"Ġdis abilities\",\"ne apolis\",\"Ġout look\",\"Ġnot ify\",\"ĠIndian apolis\",\"Ġab rupt\",\"ns ic\",\"Ġenc rypted\",\"Ġfor fe\",\"reat h\",\"Ġr abb\",\"Ġfound ations\",\"Ġcompl iment\",\"ĠInter view\",\"ĠS we\",\"Ġad olesc\",\"Ġmon itors\",\"ĠSacrament o\",\"Ġtime ly\",\"Ġcontem pl\",\"Ġposition ed\",\"Ġpost ers\",\"ph ies\",\"iov ascular\",\"v oid\",\"ĠFif th\",\"Ġinvestig ative\",\"OU N\",\"Ġinteg rate\",\"ĠIN C\",\"ish a\",\"ibl ings\",\"ĠRe quest\",\"ĠRodrig uez\",\"Ġsl ides\",\"ĠD X\",\"Ġfemin ism\",\"Ġdat as\",\"Ġb end\",\"ir us\",\"ĠNig eria\",\"F ox\",\"Ch ange\",\"Ġair plane\",\"ĠLad en\",\"Ġpublic ity\",\"ixt y\",\"Ġcommit ments\",\"Ġaggreg ate\",\"Ġdisplay ing\",\"ĠAr row\",\"Ġ12 2\",\"Ġrespect s\",\"and roid\",\"s ix\",\"ĠSh a\",\"Ġrest oration\",\") \\\\\",\"W S\",\"oy s\",\"Ġillust rate\",\"with out\",\"12 6\",\"ĠâĶ Ĥ\",\"Ġpick up\",\"n els\",\"Ġ ....\",\"f ood\",\"ĠF en\",\") ?\",\"Ġphenomen a\",\"Ġcompan ions\",\"ĠW rite\",\"Ġsp ill\",\"Ġbr idges\",\"ĠUp dated\",\"ĠF o\",\"Ġinsect s\",\"ASH INGTON\",\"Ġsc are\",\"il tr\",\"ĠZh ang\",\"Ġsever ity\",\"Ġind ul\",\"14 9\",\"ĠCo ffee\",\"Ġnorm s\",\"Ġp ulse\",\"ĠF T\",\"Ġhorr ific\",\"ĠDest roy\",\"ĠJ SON\",\"Ġo live\",\"Ġdiscuss es\",\"R est\",\"E lect\",\"ĠW inn\",\"ĠSurv iv\",\"ĠH ait\",\"S ure\",\"op ed\",\"Ġro oted\",\"ĠS ke\",\"ĠBron ze\",\"Ġl ol\",\"Def ault\",\"Ġcommod ity\",\"red ited\",\"Ġliber tarian\",\"Ġforb idden\",\"Ġgr an\",\"à ¨\",\"Ġl ag\",\"en z\",\"dri ve\",\"Ġmathemat ics\",\"Ġw ires\",\"Ġcrit ically\",\"Ġcarb ohyd\",\"ĠChance llor\",\"ĠEd die\",\"Ġban ning\",\"ĠF ri\",\"Ġcompl ications\",\"et ric\",\"ĠBangl adesh\",\"Ġband width\",\"St op\",\"ĠOrig inally\",\"Ġhalf way\",\"yn asty\",\"sh ine\",\"Ġt ales\",\"rit ies\",\"av ier\",\"Ġspin ning\",\"ĠWH O\",\"Ġneighbour hood\",\"b ach\",\"Ġcommer ce\",\"ĠS le\",\"B U\",\"Ġentreprene ur\",\"Ġpecul iar\",\"ĠCom ments\",\"f re\",\"3 20\",\"IC S\",\"Ġimag ery\",\"ĠCan on\",\"ĠElect ronic\",\"sh ort\",\"( (\",\"D ig\",\"Ġcomm em\",\"u ced\",\"Ġincl ined\",\"ĠSum mon\",\"Ġcl iff\",\"ĠMed iterranean\",\"Ġpo etry\",\"Ġprosper ity\",\"ĠRe ce\",\"Ġp ills\",\"m ember\",\"Ġfin ale\",\"un c\",\"ĠG ig\",\"ä ½\",\"Ġl od\",\"Ġback ward\",\"- +\",\"ĠFor ward\",\"Ġth ri\",\"s ure\",\"Ġso ap\",\"ĠF X\",\"R ES\",\"ĠSe xual\",\"oul os\",\"Ġfool ish\",\"Ġright eous\",\"Ġco ff\",\"terror ism\",\"ust ain\",\"ot er\",\"Ġab uses\",\"ne xt\",\"Ġab usive\",\"Ġthere after\",\"Ġprohib ition\",\"ĠS UP\",\"Ġd ip\",\"Ġr ipped\",\"Ġinher ited\",\"Ġb ats\",\"st ru\",\"G T\",\"Ġflaw ed\",\"ph abet\",\"Ġf og\",\"do ors\",\"Ġim aging\",\"Ġdig its\",\"ĠHung ary\",\"Ġar rog\",\"Ġteach ings\",\"Ġprotocol s\",\"ĠB anks\",\"à ¸\",\"p ound\",\"ĠC urt\",\".\\\" )\",\". /\",\"Ġex emption\",\"end ix\",\"ĠM ull\",\"Ġimpro ves\",\"ĠG amer\",\"d imensional\",\"I con\",\"ĠMarg aret\",\"St atus\",\"d ates\",\"Ġint ends\",\"Ġdep ict\",\"Ġpark ed\",\"J oe\",\"ĠMar ines\",\"chn ology\",\"! ).\",\"Ġjud ged\",\"Ġwe ights\",\"R ay\",\"Ġapart ments\",\"he ster\",\"Ġrein force\",\"Ġoff ender\",\"occ up\",\"Ġs ore\",\"e pt\",\"ĠPH P\",\"ĠB row\",\"Ġauthor ization\",\"ĠR isk\",\"ĠDel aware\",\"ĠQ U\",\"Ġnot ifications\",\"Ġsun light\",\"Ġex clude\",\"d at\",\"Ġm esh\",\"ĠSud an\",\"Ġbelong ed\",\"Ġsub way\",\"Ġno on\",\"ĠInter ior\",\"ol ics\",\"ĠL akers\",\"Ġc oding\",\"Dis claimer\",\"Cal if\",\"O ld\",\"Ġdis l\",\"???? ?\",\"Ġconfir ms\",\"Ġrecruit ment\",\"Ġhom icide\",\"Cons ider\",\"ĠJeff rey\",\"ft y\",\"} ;\",\"Ġobject ion\",\"do ing\",\"ĠLe o\",\"W ant\",\"Ġgl ow\",\"ĠClar ke\",\"ĠNorm an\",\"Ġver ification\",\"Ġpack et\",\"ĠForm ula\",\"Ġpl ag\",\"es ville\",\"Ġshout ing\",\"Ġo v\",\"ĠR EC\",\"ĠB ub\",\"Ġn inth\",\"Ġener g\",\"Ġvalid ity\",\"Ġup s\",\"j ack\",\"Ġneighbor ing\",\"ĠN ec\",\"ew orks\",\"ĠH ab\",\"are z\",\"Ġsp ine\",\"Ġevent ual\",\"ĠLe aders\",\"ĠC arn\",\"Ġprob ation\",\"Ġrom ance\",\"ms g\",\"ĠMechan ical\",\"ER Y\",\"R ock\",\"Ġpart isan\",\"N ode\",\"ass ets\",\"min ent\",\"Ġforeign ers\",\"Ġtest ify\",\"ĠUs ually\",\"l ords\",\"ĠG ren\",\"ĠPow ell\",\"BI L\",\"Ġs r\",\"Ġadd ict\",\"Ġshell s\",\"Ġs igh\",\"ĠY ale\",\"tern ity\",\"Ġ7 50\",\"E U\",\"ĠR ifle\",\"Ġpat ron\",\"em a\",\"ĠB annon\",\"an ity\",\"Ġtrop ical\",\"ĠV II\",\"c ross\",\"Every thing\",\"ĠIS O\",\"Ġhum ble\",\"ass ing\",\"ĠF IG\",\"Ġupd ating\",\"ys on\",\"Ġcal cium\",\"Ġcompet ent\",\"Ġste ering\",\"Pro t\",\"ĠS Y\",\"ĠFin als\",\"ĠR ug\",\"15 9\",\"13 7\",\"ĠG olf\",\"Ġ12 6\",\"Ġaccommod ation\",\"ĠHug hes\",\"Ġaest hetic\",\"art isan\",\"ĠTw ilight\",\"Ġpr ince\",\"ĠAgric ulture\",\"ĠDis co\",\"Ġpreced ent\",\"Ġtyp ing\",\"author ized\",\"O ption\",\"ĠA ub\",\"l ishes\",\"ach t\",\"m ag\",\"P eter\",\"ĠU FO\",\"mont on\",\"ĠL ith\",\"Ġa rom\",\"Ġsec uring\",\"Ġconf ined\",\"priv ate\",\"Ġsw ords\",\"Ġmark ers\",\"Ġmetab olic\",\"se lect\",\"ĠCur se\",\"ĠO t\",\"g ressive\",\"Ġinc umb\",\"ĠS aga\",\"Ġpr iced\",\"Ġclear ance\",\"Cont ent\",\"Ġdr illing\",\"Ġnot ices\",\"Ġb ourgeois\",\"Ġv est\",\"Ġcook ie\",\"ĠGuard ians\",\"ry s\",\"in yl\",\"Ġ12 4\",\"Ġpl ausible\",\"on gh\",\"ĠOd in\",\"Ġconcept ion\",\"ĠY uk\",\"ĠBaghd ad\",\"ĠFl ag\",\"Aust ral\",\"ĠI BM\",\"Ġintern ationally\",\"ĠWiki Leaks\",\"I ED\",\"Ġc yn\",\"Ġcho oses\",\"ĠP ill\",\"Ġcomb ining\",\"Ġrad i\",\"ĠMoh ammed\",\"def ense\",\"atch ing\",\"Sub ject\",\"ic iency\",\"Fr ame\",\"Ġ{ \\\"\",\"Ġche ss\",\"Ġtim er\",\"19 0\",\"Ġt in\",\"Ġord inance\",\"emet ery\",\"Ġacc using\",\"Ġnotice able\",\"Ġcent res\",\"Ġl id\",\"ĠM ills\",\"img ur\",\"Ġz oom\",\"erg ic\",\"Ġcomp ression\",\"pr im\",\"f ind\",\"Ġsur g\",\"Ġp and\",\"ĠK ee\",\"ĠCh ad\",\"cell ence\",\"oy le\",\"Ġsocial ism\",\"ĠT ravis\",\"ĠM Hz\",\"Ġgu ild\",\"ALL Y\",\"ĠSub scribe\",\"ĠRel ated\",\"Ġoccur rence\",\"itch ing\",\"Ġfict ional\",\"Ġcr ush\",\"ĠE A\",\"c od\",\"m ix\",\"ĠTri ple\",\"Ġretrie ve\",\"Ġstimul us\",\"Ġpsych iat\",\"ĠDo or\",\"Ġhomosexual ity\",\"Ġelement ary\",\"Ġcell ular\",\"id ian\",\"ĠL aun\",\"Ġintrig uing\",\"Ġfo am\",\"ĠB ass\",\"id i\",\"its u\",\"Ġass ure\",\"Ġcongr at\",\"Ġbusiness man\",\"ĠBo ost\",\"cl ose\",\"Ġl ied\",\"Ġsc iences\",\"ĠO mega\",\"ĠG raphics\",\"Ġ< =\",\"sp oken\",\"Ġconnect ivity\",\"S aturday\",\"ĠAven gers\",\"Ġto ggle\",\"Ġank le\",\"Ġnational ist\",\"mod el\",\"ĠP ool\",\"ophob ia\",\"V ar\",\"ĠM ons\",\"ator ies\",\"Ġaggress ively\",\"C lear\",\"For ge\",\"act ers\",\"Ġhed ge\",\"Ġpip es\",\"Ġbl unt\",\"Ġs q\",\"Ġremote ly\",\"W ed\",\"as ers\",\"Ġref riger\",\"Ġt iles\",\"Ġresc ued\",\"Ġcompr ised\",\"ins ky\",\"Ġman if\",\"avan augh\",\"Ġprol ifer\",\"Ġal igned\",\"x ml\",\"Ġtri v\",\"Ġcoord ination\",\"ĠP ER\",\"ĠQu ote\",\"13 4\",\"b f\",\"ĠS aw\",\"Ġtermin ation\",\"Ġ19 0\",\"Ġadd itions\",\"Ġtri o\",\"Ġproject ions\",\"Ġpositive ly\",\"Ġin clusive\",\"Ġmem br\",\"19 90\",\"old er\",\"Ġpract iced\",\"ink le\",\"Ar ch\",\"Ġstar ters\",\"ari us\",\"Ġinter mediate\",\"ĠBen ef\",\"ĠK iller\",\"Ġinter ventions\",\"ĠK il\",\"ĠF lying\",\"In v\",\"Ġprem ature\",\"Ġpsych iatric\",\"Ġind ie\",\"Ġcoll ar\",\"ĠRain bow\",\"af i\",\"Ġdis ruption\",\"ĠFO X\",\"cast ing\",\"Ġmis dem\",\"c ro\",\"Ġw ipe\",\"ard on\",\"Ġb ast\",\"ĠTom my\",\"ĠRepresent ative\",\"Ġbell y\",\"ĠP O\",\"ĠBre itbart\",\"13 2\",\"Ġmess aging\",\"Sh ould\",\"Ref erences\",\"ĠG RE\",\"ist ical\",\"L P\",\"ĠC av\",\"ĠC razy\",\"Ġintu itive\",\"ke eping\",\"ĠM oss\",\"Ġdiscont in\",\"ĠMod ule\",\"Ġun related\",\"ĠPract ice\",\"ĠTrans port\",\"Ġstatist ically\",\"orn s\",\"Ġs ized\",\"p u\",\"Ġca f\",\"ĠWorld s\",\"ĠRod gers\",\"ĠL un\",\"ĠCom ic\",\"l iving\",\"Ġc ared\",\"Ġclim bed\",\") {\",\"Ġconsist ed\",\"Ġmed ieval\",\"fol k\",\"Ġh acked\",\"Ġd ire\",\"ĠHerm ione\",\"Ġt ended\",\"ce ans\",\"D aniel\",\"w ent\",\"Ġlegisl ators\",\"Ġred es\",\"g ames\",\"Ġg n\",\"am iliar\",\"Ġ+ +\",\"gg y\",\"th reat\",\"Ġmag net\",\"Ġper ceive\",\"Ġz ip\",\"Ġindict ment\",\"Ġcrit ique\",\"g ard\",\"ĠSaf e\",\"ĠC ream\",\"Ġad vent\",\"ob a\",\"Ġv owed\",\"ous ands\",\"Ġsk i\",\"Ġabort ions\",\"u art\",\"Ġstun ned\",\"Ġadv ancing\",\"Ġlack ed\",\"Ġ\\\\ \\\"\",\"Ġsch izophren\",\"Ġeleg ant\",\"Ġconf erences\",\"Ġcance led\",\"ĠHud son\",\"ĠHop efully\",\"Ġtr ump\",\"Ġfrequ encies\",\"Ġmet eor\",\"ĠJun ior\",\"ĠFle et\",\"ĠMal colm\",\"ĠT ools\",\"Ġ ........\",\"Ġh obby\",\"ĠEurope ans\",\"Ġ15 00\",\"ĠInt o\",\"Ġs way\",\"ĠApp ro\",\"ĠCom pl\",\"Comm unity\",\"Ġt ide\",\"ĠSum mit\",\"ä »\",\"Ġinter vals\",\"ĠE ther\",\"Ġhabit at\",\"ĠSteven s\",\"lish ing\",\"ĠDom ain\",\"Ġtrig gers\",\"Ġch asing\",\"Ġchar m\",\"ĠFl ower\",\"it ored\",\"Ġbless ing\",\"Ġtext ures\",\"F ive\",\"Ġliqu or\",\"R P\",\"F IN\",\"Ġ19 62\",\"C AR\",\"Un known\",\"Ġres il\",\"ĠL ily\",\"Ġabund ance\",\"Ġpredict able\",\"r ar\",\"Ġbull shit\",\"le en\",\"che t\",\"M or\",\"M uch\",\"ä ¹\",\"Ġemphas ized\",\"Ġcr ust\",\"Ġprim itive\",\"Ġenjoy able\",\"ĠPict ures\",\"Ġteam mate\",\"pl er\",\"ĠT ol\",\"ĠK ane\",\"Ġsummon ed\",\"th y\",\"ram a\",\"ĠH onda\",\"Ġreal izing\",\"Ġquick er\",\"Ġconcent rate\",\"cle ar\",\"Ġ2 10\",\"ĠErd ogan\",\"ar is\",\"Ġrespond s\",\"ĠB I\",\"Ġelig ibility\",\"Ġpus hes\",\"ĠId aho\",\"Ġagg rav\",\"Ġru ins\",\"ur ations\",\"Ġb ans\",\"Ġan at\",\"sh are\",\"Ġgr ind\",\"h in\",\"um en\",\"Ġut ilities\",\"ĠYan kees\",\"Ġdat abases\",\"ĠD D\",\"Ġdispl aced\",\"Ġdepend encies\",\"Ġstim ulation\",\"h un\",\"h ouses\",\"ĠP retty\",\"ĠRaven s\",\"ĠTOD AY\",\"Ġassoci ates\",\"Ġthe rape\",\"cl ed\",\"Ġde er\",\"Ġrep airs\",\"rent ice\",\"Ġrecept ors\",\"Ġrem ed\",\"ĠC e\",\"Ġmar riages\",\"Ġball ots\",\"ĠSold ier\",\"Ġhilar ious\",\"op l\",\"13 8\",\"Ġinherent ly\",\"Ġignor ant\",\"Ġb ounce\",\"ĠE aster\",\"REL ATED\",\"ĠCur rency\",\"E V\",\"ãĥ ŀ\",\"ĠLe ad\",\"Ġdece ased\",\"B rien\",\"ĠMus k\",\"J S\",\"Ġmer ge\",\"heart ed\",\"c reat\",\"m itt\",\"m und\",\"ĠâĢ ĭ\",\"ĠB ag\",\"Ġproject ion\",\"Ġj ava\",\"ĠStand ards\",\"ĠLeon ard\",\"Ġcoc onut\",\"ĠPop ulation\",\"Ġtra ject\",\"Ġimp ly\",\"Ġcur iosity\",\"ĠD B\",\"ĠF resh\",\"ĠP or\",\"Ġheav ier\",\"ne ys\",\"gom ery\",\"Ġdes erved\",\"Ġphr ases\",\"ĠG C\",\"Ġye ast\",\"d esc\",\"De ath\",\"Ġreb oot\",\"Ġmet adata\",\"IC AL\",\"Ġrep ay\",\"ĠInd ependence\",\"Ġsubur ban\",\"ical s\",\"Ġat op\",\"Ġall ocation\",\"gener ation\",\"ĠG ram\",\"Ġmoist ure\",\"Ġp ine\",\"ĠLiber als\",\"Ġa ides\",\"Ġund erest\",\"ĠBer ry\",\"Ġcere mon\",\"3 70\",\"ast rous\",\"ĠPir ates\",\"Ġt ense\",\"ĠIndust ries\",\"ĠApp eals\",\"ĠN ear\",\"Ġè£ı ç\",\"Ġlo vers\",\"ĠC AP\",\"ĠC raw\",\"Ġg iants\",\"Ġeffic acy\",\"E lement\",\"ĠBeh avior\",\"ĠToy ota\",\"Ġint est\",\"P riv\",\"A I\",\"Ġmaneu ver\",\"Ġperfect ion\",\"Ġb ang\",\"p aper\",\"r ill\",\"Ge orge\",\"b order\",\"in ters\",\"ĠS eth\",\"Ġcl ues\",\"ĠLe vi\",\"ĠRe venue\",\"14 7\",\"Ġv apor\",\"Ġfortun ate\",\"Ġthreat ens\",\"Ġve t\",\"Ġdepend ency\",\"ers ed\",\"art icle\",\"ĠBl izzard\",\"Ġch lor\",\"Ġmin us\",\"ĠB ills\",\"Ġcryptoc urrency\",\"Ġmetabol ism\",\"ter ing\",\"Ġp estic\",\"step s\",\"ĠTre asure\",\"ract ed\",\"ĠConst ant\",\"Ġtem p\",\"13 9\",\"ĠDet ective\",\"ur ally\",\"Ġrecover ing\",\"Ġcort ex\",\"Ġ14 4\",\"cl osed\",\"Ġprejud ice\",\"aun ted\",\"Ġstorm s\",\"ĠN OW\",\"Ġmach inery\",\"Add ress\",\"Ġcompe lled\",\"27 0\",\"Ġdesp air\",\"b ane\",\"Ġveget able\",\"Ġbed s\",\"Lear n\",\"Ġcolor ful\",\"Ġsp ike\",\"Ġmarg ins\",\"Ġsymp athy\",\"Ġworks hop\",\"ĠC BC\",\"S at\",\"Ġburn s\",\"ĠG ender\",\"Ġ12 9\",\"ĠC able\",\"Ġdeb ts\",\"ĠThe resa\",\"Ġreflect ing\",\"Ġa irst\",\"Ġr im\",\"ram id\",\"Ġweakness es\",\"W rit\",\"ogg le\",\"t i\",\"ĠCh arge\",\"Ġwe ighed\",\"Ġ( .\",\"Ġl aughter\",\"Ġrou ter\",\"ĠDemocr acy\",\"D ear\",\"Ġhas ht\",\"Ġd y\",\"Ġhint s\",\"run ning\",\"Ġfin ishes\",\"ar us\",\"M ass\",\"res ult\",\"asc us\",\"Ġv intage\",\"Ġcon qu\",\"Ġwild ly\",\"ac ist\",\"Ġl ingu\",\"Ġprot agonist\",\"st rom\",\"te enth\",\"ĠSol o\",\"m ac\",\"f illed\",\"Ġre nown\",\"it ives\",\"Ġmot ive\",\"ĠAnt ar\",\"ĠM ann\",\"ĠAd just\",\"Ġrock ets\",\"Ġtrou bling\",\"e i\",\"Ġorgan isms\",\"ass is\",\"Christ ian\",\"Ġ14 5\",\"ĠH ass\",\"Ġsw all\",\"Ġw ax\",\"ĠSurv ival\",\"V S\",\"ĠM urd\",\"v d\",\"stand ard\",\"Ġdrag ons\",\"Ġacceler ation\",\"r ational\",\"f inal\",\"Ġp aired\",\"ĠE thereum\",\"Ġinterf aces\",\"Ġres ent\",\"Ġartif acts\",\"Å «\",\"are l\",\"Ġcompet itor\",\"ĠNich olas\",\"ĠSur face\",\"c pp\",\"ĠT ot\",\"Ġeconom ically\",\"Ġorgan ised\",\"Ġen forced\",\"in ho\",\"Ġvar ieties\",\"Ġab dom\",\"ĠBa iley\",\"id av\",\"ĠSal v\",\"p aid\",\"Ġalt itude\",\"ess ert\",\"ĠG utenberg\",\"are a\",\"op oulos\",\"Ġprofess ors\",\"igg s\",\"ĠF ate\",\"he y\",\"Ġ3 000\",\"D ist\",\"Ġtw ins\",\"c ill\",\"ĠM aps\",\"Ġtra ps\",\"Ġwe ed\",\"ĠK iss\",\"Ġy oga\",\"Ġrecip ients\",\"ĠWest minster\",\"Ġpool s\",\"ĠWal mart\",\"18 8\",\"ĠSchool s\",\"att ack\",\"ĠAR M\",\"par agraph\",\"W arning\",\"j l\",\"Ġself ish\",\"anche z\",\"ĠHe ights\",\"F re\",\"ĠS oph\",\"Ġ --------------------------------\",\"t ml\",\"33 3\",\"Ġraid s\",\"Ġsatell ites\",\"KE Y\",\"Ġlast s\",\"Ñ Ĥ\",\"In s\",\"ĠD ame\",\"Ġunp redict\",\"// /\",\"gh ai\",\"Ġart illery\",\"Ġcru ise\",\"Ġg el\",\"ĠCabin et\",\"Ġbl ows\",\"ĠE sp\",\"Ġprox imity\",\"ot he\",\"ĠSk ills\",\"ĠU pper\",\"ob o\",\"ĠN DP\",\"Ġenjoy s\",\"Ġrepe ating\",\"ĠConst ruction\",\"ĠQuest ions\",\"H illary\",\"Ġu int\",\"Ġprocess ors\",\"ĠGib son\",\"ĠMult iple\",\"q a\",\"ĠB om\",\"ĠM iles\",\"vent ional\",\"Ġhur ts\",\"s kin\",\"ĠA IDS\",\"Ġadvis ers\",\"ĠR oot\",\"Ġmethod ology\",\"ĠD ale\",\"Ġdet on\",\"ĠKnow ledge\",\"sequ ently\",\"Ġ12 1\",\"Ġconnect s\",\"C y\",\"ĠD anger\",\"Ġcontribut ors\",\"ĠB ent\",\"Ġbr ass\",\"ĠGun s\",\"int o\",\"ĠFort une\",\"Ġbro ker\",\"bal ance\",\"Ġlength s\",\"Ġv ic\",\"Ġaver aging\",\"Ġappropri ately\",\"ĠCamer a\",\"Ġsand wich\",\"ĠCD C\",\"Ġcoord inate\",\"Ġnav ig\",\"Ġgood ness\",\"l aim\",\"Ġbra ke\",\"Ġextrem ist\",\"ĠW ake\",\"ĠM end\",\"ĠT iny\",\"ĠC OL\",\"ĠR F\",\"ĠD ual\",\"ĠW ine\",\"C ase\",\"Ġref ined\",\"Ġl amp\",\"L ead\",\"Ġb apt\",\"ĠCar b\",\"ĠS add\",\"ĠMin neapolis\",\"PD F\",\"Ear ly\",\"ĠH idden\",\"I ts\",\"ĠT IME\",\"Ġp ap\",\"Ġcommission ed\",\"ĠF ew\",\"ĠCol ts\",\"ĠB ren\",\"Ġbot hered\",\"Ġlike wise\",\"Ex per\",\"ĠSch w\",\"c ry\",\"n n\",\"ĠM itch\",\"im on\",\"M G\",\"b m\",\"UM P\",\"r ays\",\"Ġregist ry\",\"Ġ2 70\",\"ach ine\",\"re lla\",\"ant ing\",\"00 000\",\"Ġru ined\",\"sp ot\",\"Ġt a\",\"Ġmaxim ize\",\"Ġincon ven\",\"D ead\",\"H uman\",\"En abled\",\"ĠMar ie\",\"Ġch ill\",\"ĠParad ise\",\"Ġstar ring\",\"ĠLat ino\",\"ĠProt ocol\",\"ĠE VER\",\"Ġsuppl iers\",\"m essage\",\"ĠBro ck\",\"Ġser um\",\"âĸĪâĸĪ âĸĪâĸĪ\",\"Ġen comp\",\"Ġamb ition\",\"ues e\",\"Ġar rows\",\"And rew\",\"Ġanten na\",\"Ġ19 61\",\"ĠB ark\",\"Ġb ool\",\"ãĤ ª\",\"ĠSt orage\",\"Ġrail way\",\"Ġtoug her\",\"ĠC ad\",\"Ġwas hing\",\"P y\",\"' ]\",\"em bed\",\"ĠMem phis\",\"ack le\",\"Ġfam ously\",\"ĠF ortunately\",\"ov ies\",\"Ġmind set\",\"Ġsne ak\",\"ĠD h\",\"RA W\",\"ĠSim pson\",\"Ġliv est\",\"Ġland mark\",\"Ġc ement\",\"L ow\",\"Ġthr illed\",\"ĠCour se\",\"in el\",\"Ġch uck\",\"id ate\",\"gl obal\",\"Ġwh it\",\"Ġ ï¿½\",\"ad ays\",\"s ki\",\"ĠS V\",\"Ġvir uses\",\"30 6\",\"ĠResp ons\",\"Ġthe aters\",\"ĠBr anch\",\"ĠGene va\",\"ĠM K\",\"Ġunbel iev\",\"Ġcommun ist\",\"Orig inal\",\"ĠRe ceived\",\"ĠTrans fer\",\"ĠAr g\",\"In put\",\"ĠStr ategy\",\"Ġpal ace\",\"the ning\",\"D ri\",\"Ġsent encing\",\"umbn ail\",\"Ġp ins\",\"re cy\",\"Ġs iblings\",\"Get ting\",\"ĠB U\",\"ĠNorth west\",\"Ġprolong ed\",\"ĠSak ura\",\"C omb\",\"ĠB our\",\"Ġinadequ ate\",\"ĠK ash\",\"Ġus ername\",\"ĠImpro ve\",\"Ġbatt ling\",\"ĠM AC\",\"Ġcurric ulum\",\"Ġs oda\",\"ĠC annon\",\"Ġsens ible\",\"sp ons\",\"De cember\",\"Ġw icked\",\"ĠP engu\",\"Ġdict ators\",\"ĠHe arts\",\"og yn\",\"Ġsimilar ities\",\"ĠSt ats\",\"Ġh ollow\",\"it ations\",\"\\\": [\",\"Ġh over\",\"ĠList en\",\"s ch\",\"S und\",\"Ġc ad\",\"ĠPar ks\",\"Ġl ur\",\"Ġhy pe\",\"ĠL em\",\"N AME\",\"is ure\",\"Fr iday\",\"Ġshoot s\",\"Ġclos es\",\"Ġd b\",\"ĠR idge\",\"ĠDiff erent\",\"Ġrepl ies\",\"ĠBroad way\",\"op ers\",\"Ġint oler\",\"ĠZe us\",\"akes pe\",\"Ġpropri etary\",\"Ġrequest ing\",\"Ġcontro llers\",\"ĠM IN\",\"im edia\",\"be cca\",\"Ġexp ans\",\"Ġoil s\",\"B ot\",\"ĠCh and\",\"Ġpr inter\",\"Ġto pped\",\"ĠP OL\",\"ĠEar lier\",\"S ocial\",\"av in\",\"Ġdecre ases\",\"ĠSe b\",\"Ġspecific ations\",\"ĠBl ast\",\"ĠK urt\",\"Ġfre el\",\"B rown\",\"Ġdil ig\",\"ro e\",\"ĠPro blem\",\"ĠQu ad\",\"Ġdecent ral\",\"ĠV ector\",\"an ut\",\"Ġplug ins\",\"ĠGreg ory\",\"Ġfuck ed\",\"el ines\",\"ĠAmb assador\",\"t ake\",\"Ġcle ans\",\"ong yang\",\"An onymous\",\"st ro\",\"\\\" }\",\"al ine\",\"ĠO dd\",\"ĠE ug\",\"2 16\",\"Ġbo il\",\"ĠP owers\",\"Ġnurs es\",\"Ob viously\",\"ĠTechn ical\",\"Ġexceed ed\",\"OR S\",\"Ġextrem ists\",\"Ġtr aces\",\"ex pl\",\"Ġcom r\",\"ĠS ach\",\") /\",\"Ġm asks\",\"Ġsc i\",\"B on\",\"Ġreg ression\",\"we gian\",\"Ġadvis or\",\"it ures\",\"ĠV o\",\"ex ample\",\"ĠInst ruct\",\"Ġs iege\",\"Ġredu ctions\",\"pt r\",\"Ġstat utory\",\"Ġrem oves\",\"Ġp uck\",\"red its\",\"Ġbe e\",\"Ġsal ad\",\"Ġpromot ions\",\"ĠJosh ua\",\"with standing\",\"ET H\",\"ĠCh a\",\"im us\",\"Ġexpend iture\",\"aun ting\",\"Ġdelight ed\",\"Ġ15 5\",\"be h\",\"Ġcar pet\",\"ĠSp art\",\"Ġj ungle\",\"l ists\",\"Ġbull ying\",\"ĠNob el\",\"ĠGl en\",\"Ġreferen ced\",\"Ġintrodu ces\",\"se in\",\"Ġcho pped\",\"gl ass\",\"ĠW rest\",\"Ġneutral ity\",\"Ġâ Ļ\",\"Ġinvestig ator\",\"Ġshel ves\",\"Ġun constitutional\",\"Ġreprodu ction\",\"Ġmer chant\",\"m ia\",\"Ġmet rics\",\"Ġexplos ives\",\"ĠSon ia\",\"Ġbod ily\",\"Ġthick ness\",\"Ġpredomin antly\",\"ĠAb ility\",\"Ġmon itored\",\"IC H\",\"Ġ] .\",\"ĠMart inez\",\"Ġvis ibility\",\"Ġqu eries\",\"Ġgen ocide\",\"ĠWar fare\",\"Qu ery\",\"Ġstud ios\",\"Ġemb ry\",\"Ġcorrid or\",\"Ġclean ed\",\"com plete\",\"ĠM H\",\"Ġenroll ment\",\"ING S\",\"Ġimpact ed\",\"Ġdis astrous\",\"ĠY un\",\"ĠCl aire\",\"ĠBas ically\",\"y t\",\"uster ity\",\"Ġindirect ly\",\"w ik\",\"Ġd od\",\"ĠCar r\",\"Ġam p\",\"Ġprohib it\",\"ĠIn itial\",\"ĠR d\",\"ij i\",\"Ġeduc ate\",\"c orn\",\"i ott\",\"ĠBeaut y\",\"Ġdetect ive\",\"ĠCon n\",\"s ince\",\"Ġst agger\",\"Ġob ese\",\"Ġb ree\",\"olog ic\",\"is se\",\"walk er\",\"Ġbl ades\",\"Ġlaw ful\",\"fun c\",\"ĠBeh ind\",\"Ġappet ite\",\"Ġ( *\",\"Ġt ennis\",\"Ġoff spring\",\"Ġj ets\",\"Ġstruct ured\",\"Ġafore mentioned\",\"N ov\",\"Ġsc aling\",\"f ill\",\"Ġst ew\",\"Ġcur b\",\"ĠStep han\",\"ed In\",\"S F\",\"ob ic\",\"é ŃĶ\",\"ou g\",\"ĠM M\",\"Ġgen etically\",\"ope z\",\"13 6\",\"Ġu mb\",\"anc ers\",\"Ġcoh ort\",\"Ġmerch andise\",\"Ġimp osing\",\"ĠLegisl ature\",\"ĠArch ive\",\"iv ia\",\"ĠN aval\",\"Ġoff ences\",\"Ġmir acle\",\"Ġsn apped\",\"Ġf oes\",\"Ġextensive ly\",\"ĠR af\",\"Ġc ater\",\"ed ience\",\"K it\",\"ĠB in\",\"Ġrecomm ends\",\"ĠC ities\",\"Ġrig id\",\"ĠRE AD\",\"ĠNob le\",\"ĠT ian\",\"Ġcertific ates\",\"ant is\",\"o iler\",\"ĠBudd hist\",\"d id\",\"Ġsurvey ed\",\"Ġdown ward\",\"Ġprint s\",\"ĠMot ion\",\"ron ics\",\"ĠS ans\",\"oss ibly\",\"u ctions\",\"Ġcolon ies\",\"ĠDan ish\",\"un it\",\"Ġsp oil\",\"Ġadvis ory\",\"ber ries\",\"Pl an\",\"Ġspecific ation\",\"op hers\",\"ĠRes ource\",\"Ġsh irts\",\"prising ly\",\"commun ications\",\"Ġtriv ial\",\"Ġmention ing\",\"ise xual\",\"Ġsupp lements\",\"Ġsuper vision\",\"B P\",\"v or\",\"Ġw it\",\"Ġco oldown\",\"Ġplaint iff\",\"ĠReview s\",\"ĠS ri\",\"ĠM int\",\"ĠSug ar\",\"Ġafter ward\",\"ĠPri est\",\"ĠInvest ment\",\"og ene\",\"ĠT aking\",\"Ġstretch ing\",\"Ġinflamm ation\",\"ĠTe hran\",\"Ġl ining\",\"Ġfree zing\",\"ĠEnt ity\",\"Ġins piring\",\"spe cial\",\"pr ice\",\"Ġsu e\",\"ĠP orter\",\"oun ge\",\"ET A\",\"ĠD erek\",\"ĠLu is\",\"u o\",\"ym ph\",\"Ġex terior\",\"ih il\",\"ĠAsh ley\",\"in ator\",\"Ġnut rients\",\"ĠTh rones\",\"Ġfin ances\",\"ĠIn spect\",\"Ġspe cially\",\"ĠRequ ired\",\"ĠP TS\",\"ĠViol ence\",\"oint ed\",\"sh ots\",\"Ġex cerpt\",\"co on\",\"IN S\",\"ĠG ri\",\"Ġrecogn ised\",\"We ek\",\"You ng\",\"Ġv om\",\"is le\",\"ĠCur ry\",\"ĠBudd h\",\"Ġnot ebook\",\"Ġd urable\",\"/ ?\",\"ĠG ad\",\"ĠP upp\",\"Ġforg ive\",\"p ark\",\"Ġpersonal ities\",\"an alysis\",\"cl amation\",\"Ġelev ator\",\"Ġware house\",\"ĠR ole\",\"un n\",\"Ġillust ration\",\"ĠSc an\",\"Ġatmosp heric\",\"Im port\",\"AN C\",\"rict ed\",\"f u\",\"01 0\",\"Ġar che\",\"Ġreward ed\",\"akespe are\",\"Ġintern ally\",\"ĠR BI\",\"alk er\",\"Ġeleph ant\",\"ow itz\",\"ĠP izza\",\"Ġbip artisan\",\"Ã© s\",\"Ġslow ed\",\"ĠSt ark\",\"Ġover ride\",\"OU S\",\"Ġ3 20\",\"undred s\",\"ĠDe ck\",\"ĠC ensus\",\"be e\",\"14 6\",\"ot or\",\"Ġ ip\",\"Ġu b\",\"oc ations\",\"ĠBut ton\",\"r ice\",\"Ġc ripp\",\"ff f\",\"Ġorig inated\",\"Ġoverwhel med\",\"app a\",\"Ġfore most\",\"âĢ ĳ\",\"ĠL EG\",\"re lease\",\"eat ured\",\"at ches\",\"Ġre ps\",\"Ġl ending\",\"ĠRe ference\",\"ĠCl ient\",\"16 5\",\"vent h\",\"Com plete\",\"ĠPat rol\",\"Ġsw orn\",\"c am\",\"Ġshut tle\",\"ĠR alph\",\"Ġh ometown\",\"- ,\",\"on al\",\"ĠB P\",\"å ı\",\"Ġpersu ade\",\"ĠAlex and\",\"Ġcomb ines\",\"Ġv ivid\",\"ĠL ag\",\"Ġenc oding\",\"Ġsal vation\",\"w en\",\"ĠRec overy\",\"i ya\",\"Un iversity\",\"ĠB iden\",\"Ġbud gets\",\"ĠTex ans\",\"f its\",\"Ġhon ored\",\"Ġp ython\",\"T D\",\"## #\",\"cl one\",\"Ġbl ink\",\"ĠL iquid\",\"Ġunemploy ed\",\"Ġcl ashes\",\"ĠCoun sel\",\"Ġdirect ing\",\"Ġpun ct\",\"ĠFal cons\",\"Ġsh ark\",\"ĠDam ascus\",\"Ġje ans\",\"Ġemb ark\",\"Ġse ize\",\"Ġup wards\",\"2 80\",\"ĠE z\",\"ĠAny thing\",\"Ġex otic\",\"l ower\",\"ĠCreat or\",\"ĠU m\",\"Ġsubur bs\",\"ber ger\",\"ĠW end\",\"Ġm int\",\"ĠX X\",\"ĠD ro\",\"Ġsuff ers\",\"Ġher b\",\"t ree\",\"Ġfrag ile\",\"Ġflood ed\",\"ĠAl cohol\",\"ole an\",\"ny der\",\"ĠK O\",\"F ram\",\"Ġ13 6\",\"Ġow ed\",\"ĠMe lee\",\"ĠH ash\",\"Ġwh isk\",\"Ġsu do\",\"r r\",\"Qu ick\",\"app ro\",\"Ġi i\",\"ĠEx amples\",\"he e\",\"Ġpromot es\",\"per ature\",\"k ar\",\"ĠHon or\",\"Ġs odium\",\"ĠL if\",\"ros so\",\"intend ent\",\"Ġcorrespond ent\",\"F ound\",\"sec ret\",\"Ġident ifies\",\"ag ne\",\"Ġl ou\",\"ĠP P\",\"Ġcoinc idence\",\"m ove\",\"Ġmilit ia\",\"Ġinf iltr\",\"ĠPrim ary\",\"Ġpitch ing\",\"ĠI b\",\"ĠGO OD\",\"ãĤ ¸\",\"ĠW izards\",\"ir al\",\"ĠVen us\",\"R R\",\"ĠâĢ ķ\",\"ĠCase y\",\"Ġsad ly\",\"Ġadm ire\",\"Ġembarrass ed\",\"c b\",\"M el\",\"Ġtub es\",\"Ġbeaut ifully\",\"ĠQueens land\",\"Bel ow\",\"re z\",\"qu et\",\"ple asant\",\"ĠÂ «\",\"C amp\",\"Ġdec isive\",\"19 98\",\"ĠL amb\",\"ut ton\",\"h n\",\"ĠJ agu\",\"au nder\",\"ĠC ord\",\"Ġcl erk\",\"Ġca ffe\",\"Ġwip ed\",\"Ġre im\",\"ĠMount ains\",\"Ġimprison ed\",\"Ġdevelop s\",\"ĠP ra\",\"Ġmodel ing\",\"Any one\",\"ance l\",\"ĠS it\",\"Ġshield s\",\"Ġl awn\",\"Ġcard iovascular\",\"Ġdemonstr ating\",\"Ġpar se\",\"ĠIsrael is\",\"Ġeuro s\",\"14 3\",\"Ġgl orious\",\"ins ki\",\"ec d\",\"Ġcondition ing\",\"Ġhel pless\",\"Ġmicro sc\",\"ĠHar bor\",\"Ġst akes\",\"Ġ2 60\",\"Ġun equ\",\"ĠFl oyd\",\"Ġd amp\",\"Ġappar atus\",\"ĠLaw s\",\"Ġcoun ters\",\"Ġindu ce\",\"at able\",\"ĠAh med\",\"Ġsl am\",\"N ovember\",\"Ġpers ist\",\"Ġim minent\",\"Ã¡ n\",\"Ġsh red\",\"Ġph ases\",\"ĠEd monton\",\"ĠArm strong\",\"ĠMe et\",\"ĠK itty\",\"Ñ Ģ\",\"c irc\",\"ĠAd ult\",\"Ġa rose\",\"ĠX en\",\"D an\",\"g ow\",\"Ġsuper f\",\"ĠAd mir\",\"Ġend ure\",\"Ġkey word\",\"yr us\",\"Ġy arn\",\"Ġpath way\",\"ĠHop kins\",\"mid t\",\"Ġcens orship\",\"d ependent\",\"Ġinstruct or\",\"S ources\",\"Ġto e\",\"Ġball oon\",\"N ob\",\"Ġsw ear\",\"ĠCast ro\",\"Ġgl oss\",\"ĠK avanaugh\",\"Ġremark ably\",\"Ph otos\",\"ĠN om\",\"ĠS outheast\",\"y ers\",\"Ġvalid ation\",\"Ġcann on\",\"ĠVict ory\",\"ĠPier re\",\"Ġcaut ious\",\"Aud io\",\"Ġf etch\",\"ĠG ift\",\"ĠH yp\",\"Ġrem edy\",\"Z E\",\"Ġsc ent\",\"Ġbe ard\",\"ĠR ut\",\"- \\\"\",\"Ġpat ents\",\"H y\",\"Ġun just\",\"Ġpot ato\",\"Ġforth coming\",\"Ġche f\",\"ĠR ift\",\"aff e\",\"ĠR OM\",\"ĠL aunch\",\"Ġp ads\",\"ĠNe o\",\"Ġon set\",\"Ġsquee ze\",\"s afe\",\"Ġpref ix\",\"ĠT M\",\"ĠN early\",\"ĠClin ical\",\"ĠM ental\",\"ot iation\",\"ĠUn ic\",\"ant ry\",\"ĠC ir\",\"Ġep it\",\"Ã ¦\",\"Ġextract ed\",\"verse ly\",\"ri ad\",\"Ġstr ains\",\"Ġto ps\",\"Ġpo em\",\"ĠRand y\",\"ĠMap le\",\"TH ER\",\"up iter\",\"ĠSS D\",\"ļ é\",\"Ġun con\",\"per ing\",\"Ġsle pt\",\"in ers\",\"Ġunder water\",\"ĠEv idence\",\"g one\",\"20 5\",\"Ġhistor ians\",\"Ġsynt hesis\",\"Ġf rog\",\"b asketball\",\"Ġvibr ant\",\"Ġsub ord\",\"Ġ3 65\",\"ĠD ial\",\"Ġcooper ate\",\"HA HA\",\"Ġgreet ed\",\"15 8\",\"Ġj azz\",\"Ġinto x\",\"ĠWalk ing\",\"Ġsuper visor\",\"ĠF usion\",\"ĠMer cedes\",\"s end\",\"H am\",\"s d\",\"n l\",\"Ġtour s\",\"ĠF IFA\",\"Ġcul p\",\"g d\",\"30 4\",\"Ġple as\",\"Ġillust rates\",\"ĠColomb ia\",\"Ġhighlight ing\",\"ĠSum mary\",\"Ġexp osing\",\"ĠD ru\",\"Ġir ony\",\"r itional\",\"ĠCar roll\",\"ĠEll is\",\"P ict\",\"ĠR apt\",\"Ġad apter\",\"Ġun m\",\"Ġcor pse\",\"Ġceleb rities\",\"D en\",\"at um\",\"ĠAp ocalypse\",\"ĠW ag\",\"lin ing\",\"Ġhorm ones\",\"R ub\",\"ĠX i\",\"ĠV aults\",\"20 8\",\"alky rie\",\"inos aur\",\"Ġfeed s\",\"v ity\",\"Ġdefe ating\",\"W ait\",\"Ġemphas ize\",\"ĠSteel ers\",\"yr inth\",\"le ys\",\"ĠWhe never\",\"Current ly\",\"ĠCl ock\",\"Ġcollect ively\",\"any on\",\"ĠJ P\",\"Ġment ality\",\"Ġdownload s\",\"Ġsurround ings\",\"ĠBarn es\",\"Ġflags hip\",\"Ġindic ators\",\"Ġgra pp\",\"Jan uary\",\"ĠElement al\",\"ĠAthen a\",\"ib al\",\"Ġs ights\",\"Ġcap ita\",\"ĠTreat y\",\"Ġvo iced\",\"ĠG az\",\"let te\",\"Ġy a\",\"Ġexp ired\",\"Leg end\",\"H ot\",\"n ature\",\"Ġunst able\",\"Ġ2 80\",\"Ã º\",\"Com ment\",\"AL E\",\"Ġquest s\",\"Ġhand ler\",\"n is\",\"Ġvers atile\",\"Ġconce al\",\"enge ance\",\"ĠInter active\",\"Ġobs essed\",\"ĠDog s\",\"Ġcr acked\",\"S ound\",\"s v\",\"ĠD ylan\",\"ro ads\",\"f x\",\"ĠCath olics\",\"ĠH ag\",\"Ġsl ammed\",\"Ġgl owing\",\"s ale\",\"Ġtiss ues\",\"ĠCh i\",\"ne e\",\"Ġc her\",\"s ic\",\"ur rection\",\"Ġb acon\",\"ul atory\",\") .\\\"\",\"Ġir regular\",\"FOR M\",\"ass ed\",\"Ġintention al\",\"Ġcompens ate\",\"ĠSpe aking\",\"ĠS ets\",\"15 3\",\"Ġconvent ions\",\"b ands\",\"em ade\",\"Ġe cc\",\"ĠWin ston\",\"ĠAssass in\",\"ĠBelg ian\",\"Ġdepend ence\",\"Ġnic he\",\"Ġb ark\",\"ĠJ azz\",\"Ġdisadvant age\",\"Ġgas oline\",\"Ġ16 5\",\"çļ Ħ\",\"ess a\",\"mod ule\",\"ang ular\",\"O Y\",\"ĠTreat ment\",\"it as\",\"ol ation\",\"ĠArn old\",\"Ġfe ud\",\"ĠN est\",\"Ġthe atre\",\"ew ater\",\"Ġmin ors\",\"olic y\",\"ĠH aven\",\"div ision\",\"Ġtr unk\",\"F ar\",\"ĠP ull\",\"Ġcapt uring\",\"Ġ18 00\",\"ĠTe en\",\"Ġex empl\",\"Ġclin ics\",\"ĠB urg\",\"Ġsubst it\",\"Ġpay load\",\"ĠL av\",\"ĠT roy\",\"ĠW itness\",\"Ġfrag ments\",\"Ġpass words\",\"Ġg ospel\",\"ĠG in\",\"Ġten ants\",\"ol ith\",\"S ix\",\"Pre vious\",\"ĠAg es\",\"ĠDar win\",\"Ġbl at\",\"Ġem pathy\",\"sm ith\",\"b ag\",\"ĠE cho\",\"ĠC amb\",\"ĠM add\",\"ĠB oo\",\"Ġred e\",\"ĠBurn ing\",\"Ġsmooth ly\",\"ĠAd rian\",\"ĠV ampire\",\"ĠMon sters\",\"ste am\",\"Sty le\",\"M a\",\"re a\",\"ĠD war\",\"aly st\",\"urs or\",\"Ġelim ination\",\"Ġcrypt o\",\"ch t\",\"ĠE ternal\",\"âĢ¦ ]\",\"ĠS orce\",\"I ll\",\"N ER\",\"Ġu h\",\"Con clusion\",\"w age\",\"Ġresp ir\",\"Ġrem inis\",\"het ical\",\"Ġg y\",\"Ġutil ized\",\"ic idal\",\"Ġ19 00\",\"Ġhun ters\",\"ĠSw an\",\"ĠRe act\",\"Ġvis itor\",\"ĠThanks giving\",\"30 8\",\"Post s\",\"Ġh ips\",\"19 97\",\"om ers\",\"Ġkn ocking\",\"ĠVeh icle\",\"Ġt il\",\"Ġ13 8\",\"Ġm i\",\"ĠInvest igation\",\"ĠKen ya\",\"Ġcas ino\",\"Ġmot ives\",\"Ġreg ain\",\"re x\",\"Ġweek ends\",\"Ġstab bed\",\"bor o\",\"Ġexplo ited\",\"ĠHA VE\",\"ĠTe levision\",\"c ock\",\"Ġprepar ations\",\"Ġende av\",\"ĠRem ote\",\"ĠM aker\",\"ĠPro du\",\"ĠEv an\",\"Ġinform ational\",\"ĠLouis ville\",\"15 4\",\"ĠDream s\",\"Ġpl ots\",\"ĠRun ner\",\"Ġhur ting\",\"Ġacad emy\",\"ĠMont gomery\",\"n m\",\"ĠL anc\",\"ĠAl z\",\"2 10\",\"el ong\",\"Ġretail er\",\"Ġar ising\",\"Ġrebell ion\",\"Ġbl onde\",\"play ed\",\"Ġinstrument al\",\"C ross\",\"Ġret ention\",\"Ġtherape utic\",\"Ġse as\",\"Ġinfant ry\",\"ĠCl int\",\"Ġprompt ing\",\"Ġbit ch\",\"Ġst ems\",\"ĠK ra\",\"Ġthe sis\",\"ĠB og\",\"ru ed\",\"Ġk ings\",\"Ġcl ay\",\"ific ent\",\"ĠY ES\",\"ĠTh ing\",\"ĠCub s\",\"vey ard\",\"els h\",\"in arily\",\"ĠE y\",\"ĠRoll ing\",\"Ġev olving\",\"Ind ia\",\"Ġrecogn izes\",\"Ġgrad uation\",\"is ers\",\"Ġfert ility\",\"ĠMil an\",\"Comm and\",\"Ġbox ing\",\"Ġ19 43\",\"Ġgl uten\",\"ĠEm ir\",\"Ġid ol\",\"Ġcon ceived\",\"ĠCre ation\",\"Mer it\",\"udd y\",\"uss ions\",\"ĠLie utenant\",\"iet al\",\"Ġunch anged\",\"ĠSc ale\",\"ĠCrime a\",\"ball s\",\"ator ial\",\"Ġdepth s\",\"Ġempir ical\",\"Ġtrans m\",\"Ġuns afe\",\"miss ible\",\"com fort\",\"15 6\",\"Ġmechan ic\",\"00 2\",\"l ins\",\"Ġsm oked\",\"P os\",\"Ġslow ing\",\"Ġl av\",\"Tex as\",\"Ġche ating\",\"ĠMet ropolitan\",\"eth yl\",\"Ġdiscover ing\",\"as se\",\"Ġpen cil\",\"ĠPy ongyang\",\"Ġclos et\",\"ĠShe et\",\"ĠEnt ry\",\"ou stic\",\"Ġmy st\",\"er ate\",\"ari at\",\"Ġminer als\",\"Ġmusic ian\",\"ĠP ul\",\"ĠM az\",\"24 9\",\"Ġper missions\",\"Ġ iv\",\"en ary\",\"ick ers\",\"ĠB ing\",\"he a\",\"en able\",\"Ġgri ev\",\"Ġassert ed\",\"ĠColon el\",\"Ġaff idav\",\"w o\",\"Ġse ated\",\"ĠR ide\",\"Ġpaint ings\",\"ĠP ix\",\"Ġ13 7\",\"ish i\",\"umb ai\",\"g otten\",\"ĠEar l\",\"Ġin ning\",\"Ġc ensus\",\"Ġtrave lled\",\"ĠCons ult\",\"18 5\",\"b ind\",\"Ġsimpl icity\",\"Ġoverlook ed\",\"ĠHelp ful\",\"Ġmon key\",\"Ġoverwhelming ly\",\"Bl ood\",\"ĠFl int\",\"ĠJ ama\",\"ĠPres ent\",\"ĠR age\",\"ĠT A\",\"pt ive\",\"Ġturn out\",\"w ald\",\"ĠD olphins\",\"ĠV PN\",\"Ġon ion\",\"Ġcraft ing\",\"m ma\",\"ĠMerc ury\",\"Ġarr ange\",\"Ġalert s\",\"ĠO T\",\"zb ollah\",\"Ġg ases\",\"ĠRichards on\",\"s al\",\"l ar\",\"Ġfro st\",\"Ġlower ing\",\"Ġacc laim\",\"Ġstart ups\",\"ĠG ain\",\"ess ment\",\"Ġguard ian\",\"äº º\",\"ĠP ie\",\"ĠL inks\",\"Ġmer its\",\"Ġaw ake\",\"Ġparent al\",\"Ġexceed s\",\"Ġid le\",\"ĠPil ot\",\"Ġe Bay\",\"ĠAc cept\",\"ipe g\",\"C am\",\"ĠK ot\",\"Ġtrad ers\",\"olit ics\",\"unk er\",\"ĠP ale\",\"os i\",\"an mar\",\"Ġ19 47\",\"ĠF ell\",\"est ial\",\"it ating\",\"G F\",\"ĠS r\",\"if ted\",\"Ġconnect or\",\"ĠB one\",\"ill es\",\"2 60\",\"h ma\",\"Ġoverl ap\",\"ĠGit Hub\",\"Ġclean er\",\"ĠBapt ist\",\"ĠW AS\",\"Ġlung s\",\"Ñ ģ\",\"ĠB UT\",\"Ġc ite\",\"Ġpit ched\",\"reat ment\",\"Ġtro phies\",\"ĠN u\",\"38 6\",\"ĠPr ide\",\"Ġattend ees\",\"[ ]\",\"17 9\",\"Ġspat ial\",\"Ġpri zes\",\"ĠRel igion\",\"Ġshow case\",\"ĠC ategory\",\"vid ia\",\"T arget\",\"Pro perty\",\"? ,\",\"Ġf usion\",\"p ie\",\"ĠU CLA\",\"Ġsound track\",\"Ġprin cess\",\"ĠC aval\",\"sh ould\",\"Ġlim bs\",\"Back ground\",\"Ġlone ly\",\"Ġc ores\",\"ĠT ail\",\"she et\",\"Ġ13 2\",\"R a\",\"ãĤ «\",\"ĠB olt\",\"Ġbook ed\",\"Ġadmin ister\",\"Ġequ als\",\"w y\",\"Ġobserv ing\",\"ĠBar on\",\"ĠAd obe\",\"Ġv irgin\",\"ĠSocial ist\",\"M ove\",\"gh azi\",\"ĠLind a\",\"2 12\",\"Ġbre wing\",\"Ġmerch ants\",\"bur se\",\"Ġdiv or\",\"Ġmet als\",\"ĠN er\",\"Ġsum s\",\"ĠEn emy\",\"Ġen vision\",\"Ġgrant ing\",\"ĠH oney\",\"ĠSk yrim\",\"Ġsoc io\",\"gr aded\",\"Ġselect ive\",\"W ASHINGTON\",\"Ġ19 48\",\"ĠSir ius\",\"ĠG ross\",\"act ivity\",\"ĠI van\",\"Ġfur ious\",\"BS D\",\"ĠPre vious\",\"Ġrespons ive\",\"Ġchar itable\",\"Ġle aning\",\"ĠP ew\",\"Ġviol ates\",\"\\\\\\\\\\\\\\\\ \\\\\\\\\\\\\\\\\",\"ĠCom ing\",\"w ire\",\"Ġpo et\",\"Ġres olutions\",\"comm and\",\"ĠPortug uese\",\"Ġnick name\",\"Ġde af\",\"Feb ruary\",\"Ġrecogn ise\",\"Ġentire ty\",\"Ġseason al\",\"pl aced\",\"ĠTe legraph\",\"Ġmicro phone\",\"our ing\",\"Ġgr ains\",\"Ġgovern ed\",\"Ġpost p\",\"ĠW aters\",\"in ement\",\"Ġund ocumented\",\"ĠCom cast\",\"Ġf ox\",\"Ġassault s\",\"re on\",\"man y\",\"ĠJen kins\",\"ĠAny way\",\"Ġassess ments\",\"Ġdown s\",\"ĠM ouse\",\"Ġsuper b\",\"k t\",\"ĠD ow\",\"Ġtax ation\",\"4 01\",\"Ġsm iles\",\"Ġundert aken\",\"Ġex h\",\"Ġenthusi astic\",\"Ġtw ent\",\"Ġgovernment al\",\"Ġautonom y\",\"ĠTechn ologies\",\"ĠCh ain\",\"Ġpreval ent\",\"f b\",\"Ġnic otine\",\"og ram\",\"j ob\",\"Ġawa iting\",\"ĠMen u\",\"Ġdep uties\",\"k ov\",\"ish ops\",\"But ton\",\"ĠShan ghai\",\"Ġdies el\",\"ĠD uck\",\"R yan\",\"ĠPC s\",\"N F\",\"j ury\",\"ent e\",\"Ġinacc urate\",\"edd y\",\"Wh atever\",\"Ġshow c\",\"ĠN ad\",\"od us\",\"et r\",\"Ġplaint iffs\",\"ĠW OR\",\"ĠAss ange\",\"Ġpriv at\",\"Ġpremium s\",\"Ġt am\",\"UR L\",\"Ġel ites\",\"ĠR anger\",\"otten ham\",\"ĠH off\",\"ĠAt hens\",\"Ġdefin ite\",\"Ġs ighed\",\"Ġeven ly\",\"2 11\",\"ĠAm ber\",\"ak ia\",\"Ġmail ing\",\"Ġcr ashing\",\"ĠConfeder ate\",\"ru gged\",\"W al\",\"ĠDep ths\",\"Ġjuven ile\",\"Ġreact or\",\"Introdu ction\",\"ĠDel uxe\",\"19 95\",\"ĠS anchez\",\"ĠM ead\",\"iv able\",\": -\",\"ĠPlan ning\",\"ĠT rap\",\"qu in\",\"ĠProt ect\",\"ve red\",\"In formation\",\"Ġkid ney\",\"inn amon\",\"l as\",\"Ġpolic ing\",\"Ġtoler ate\",\"ĠQ i\",\"Ġbi ased\",\"F ort\",\"ĠK i\",\"s ave\",\"Ġprivile ged\",\"Ġbe asts\",\"ĠGl as\",\"ĠC inem\",\"Ġcome back\",\"Sund ay\",\"Ġext inction\",\"h ops\",\"Ġtrans mit\",\"Ġdoub les\",\"ĠFl at\",\"16 7\",\"Ġdis puted\",\"Ġinjust ice\",\"f oo\",\"V ict\",\"role um\",\"ĠJul ie\",\"Con text\",\"ĠR arity\",\"iss ue\",\"Comp onent\",\"Ġcounsel ing\",\"an ne\",\"d ark\",\"Ġobject ions\",\"u ilt\",\"Ġg ast\",\"Ġpl ac\",\"Ġun used\",\"ãĥ ĩ\",\"ĠT rial\",\"ĠJ as\",\"hed ral\",\"ob b\",\"Ġtempor al\",\"ĠPR O\",\"ĠN W\",\"ĠAnn iversary\",\"L arge\",\"Ġther m\",\"Ġd avid\",\"Ġsystem ic\",\"ĠSh ir\",\"m ut\",\"ĠNe pt\",\"add ress\",\"Ġscan ning\",\"Ġunderstand able\",\"Ġcan vas\",\"C at\",\"ĠZ oo\",\"Ġang els\",\"L O\",\"ĠStat ement\",\"ĠS ig\",\"ov able\",\"ĠA way\",\"sh aring\",\"ocr ats\",\"st ated\",\"Ġweigh ing\",\"N or\",\"w ild\",\"B ey\",\"Ġaston ishing\",\"ĠReyn olds\",\"Ġop ener\",\"Ġtrain er\",\"Ġsurg ical\",\"p n\",\"Ġadjust ing\",\"whe el\",\"Ġf rown\",\"erv ative\",\"Ġsusp end\",\"With in\",\"te in\",\"Ġobst acle\",\"Ġliber ties\",\"ym es\",\"Ġur anium\",\"ans om\",\"an ol\",\"ub a\",\"ĠL oss\",\"Ġa rous\",\"ĠHend erson\",\"W ow\",\"s pl\",\"c ur\",\"ĠÂ Ń\",\"Ġtheir s\",\"Dam age\",\"Ġdownload ing\",\"Ġdisc ern\",\"ĠSt o\",\"ĠFl a\",\"Ġh ath\",\"ĠA j\",\"Ġun pleasant\",\"Europe an\",\"exp ensive\",\"Ġscreens hot\",\"ĠU V\",\"Ġall ied\",\"ĠPers ian\",\"Ġmonop oly\",\"Ġat om\",\"ĠReds kins\",\"\\\"> <\",\"Ġcan cell\",\"Ġcinem a\",\"13 1\",\"f air\",\"ĠAlf red\",\"Ġd uck\",\"arg s\",\"22 3\",\"ĠIS I\",\"Ġsign aling\",\"in ar\",\"Ġlaugh s\",\"Ġfor wards\",\"Ġreck less\",\"Ġlisten ers\",\"at ivity\",\"Ġvast ly\",\"n ant\",\"L ess\",\"ĠHun ting\",\"ĠScient ific\",\"IT ED\",\"Ġkn ight\",\"ĠH TC\",\"us a\",\"t mp\",\"Ġr ude\",\"ĠLegend ary\",\"Ġar ises\",\"B ad\",\"ĠCl aim\",\"pe g\",\"Ġreal ities\",\"Th ink\",\"ĠÂ °\",\"Ġro de\",\"Ġstri ve\",\"Ġan ecd\",\"Ġshort s\",\"Ġhypot hes\",\"Ġcoord inated\",\"ĠGand hi\",\"ĠF PS\",\"R ED\",\"Ġsuscept ible\",\"Ġshr ink\",\"ĠCh art\",\"Hel p\",\"Ġ ion\",\"de ep\",\"rib es\",\"ĠK ai\",\"ĠCustom er\",\"Sum mary\",\"Ġc ough\",\"w ife\",\"Ġl end\",\"Ġposition ing\",\"Ġlot tery\",\"ĠC anyon\",\"Ġf ade\",\"Ġbron ze\",\"ĠKenn y\",\"Ġbo asts\",\"ĠEnh anced\",\"rec ord\",\"Ġemer gence\",\"Ġa kin\",\"ĠB ert\",\"it ous\",\"âĸ ĳ\",\"Ġst ip\",\"Ġexch anged\",\"om ore\",\"als h\",\"Ġreserv oir\",\"Ġstand point\",\"W M\",\"Ġiniti ate\",\"Ġdec ay\",\"Ġbrew ery\",\"Ġter ribly\",\"Ġmort al\",\"lev ard\",\"Ġrev is\",\"N I\",\"el o\",\"Ġconf ess\",\"ĠMS NBC\",\"Ġsub missions\",\"Cont roller\",\"Ġ20 2\",\"ĠR uth\",\"} );\",\"ĠAz ure\",\"Ġ .\\\"\",\"20 6\",\"ĠMarket ing\",\"Ġl aund\",\"ien cies\",\"Ġrenown ed\",\"ĠT rou\",\"ĠN GO\",\"ble ms\",\"Ġterr ified\",\"Ġwar ns\",\"Ġper t\",\"Ġuns ure\",\"4 80\",\"ale z\",\"ult z\",\"ĠOut side\",\"Ġst yl\",\"ĠUnder ground\",\"Ġp anc\",\"Ġd ictionary\",\"Ġf oe\",\"rim inal\",\"ĠNor wegian\",\"Ġj ailed\",\"Ġm aternal\",\"Ã© e\",\"ĠLu cy\",\"c op\",\"Ch o\",\"Ġuns igned\",\"ĠZe lda\",\"ĠIns ider\",\"ĠContin ued\",\"Ġ13 3\",\"ĠNar uto\",\"ĠMajor ity\",\"16 9\",\"ĠW o\",\"ãĤ ĵ\",\"Ġpast or\",\"Ġinform al\",\"Ð ½\",\"an throp\",\"jo in\",\"ãģ Ĺ\",\"it ational\",\"N P\",\"ĠWrit ing\",\"f n\",\"ĠB ever\",\"19 5\",\"Ġy elling\",\"Ġdr astically\",\"Ġe ject\",\"Ġne ut\",\"Ġth rive\",\"ĠFre qu\",\"ou x\",\"Ġpossess es\",\"ĠSen ators\",\"ĠD ES\",\"ĠSh akespeare\",\"ĠFran co\",\"ĠL B\",\"uch i\",\"Ġinc arn\",\"Ġfound ers\",\"F unction\",\"Ġbright ness\",\"ĠB T\",\"Ġwh ale\",\"ĠThe ater\",\"m ass\",\"ĠD oll\",\"S omething\",\"Ġecho ed\",\"ĠHe x\",\"c rit\",\"af ia\",\"Ġgodd ess\",\"Ġele ven\",\"ĠPre view\",\"ĠAur ora\",\"Ġ4 01\",\"uls ive\",\"ĠLog an\",\"in burgh\",\"ĠCent ers\",\"ĠON LY\",\"ĠA id\",\"Ġparad ox\",\"Ġh urd\",\"ĠL C\",\"D ue\",\"c ourt\",\"Ġoff ended\",\"Ġeval uating\",\"ĠMatthew s\",\"Ġto mb\",\"Ġpay roll\",\"Ġextra ction\",\"ĠH ands\",\"if i\",\"Ġsuper natural\",\"ĠCOM M\",\"] =\",\"dog s\",\"Ġ5 12\",\"ĠMe eting\",\"Rich ard\",\"ĠMax imum\",\"Ġide als\",\"Th ings\",\"m and\",\"ĠReg ardless\",\"Ġhum ili\",\"b uffer\",\"L ittle\",\"ĠD ani\",\"ĠN ak\",\"Ġliber ation\",\"ĠA be\",\"ĠO L\",\"Ġstuff ed\",\"ac a\",\"ind a\",\"raph ic\",\"Ġmos qu\",\"Ġcampaign ing\",\"Ġoccup y\",\"S qu\",\"r ina\",\"ĠW el\",\"ĠV S\",\"Ġphys ic\",\"Ġp uls\",\"r int\",\"oad ed\",\"ET F\",\"ĠArch ives\",\"Ġven ues\",\"h ner\",\"ĠTur bo\",\"Ġl ust\",\"Ġappeal ed\",\"que z\",\"il ib\",\"ĠTim othy\",\"Ġo mn\",\"d ro\",\"Ġobs ession\",\"ĠSav age\",\"19 96\",\"Gl obal\",\"J es\",\"2 14\",\"Ġsl iding\",\"Ġdisapp ro\",\"ĠMag ical\",\"Ġvolunt arily\",\"g b\",\"ane y\",\"Ġprop het\",\"ĠRe in\",\"ĠJul ia\",\"ĠW orth\",\"aur us\",\"Ġb ounds\",\"ie u\",\")) )\",\"Ġcro re\",\"ĠCitiz en\",\"S ky\",\"Ġcolumn ist\",\"Ġseek ers\",\"ond o\",\"IS A\",\"ĠL ength\",\"Ġnost alg\",\"Ġnew com\",\"Ġdet rim\",\"ent ric\",\"3 75\",\"ĠG E\",\"Ġaut op\",\"Ġacadem ics\",\"App Data\",\"ĠS hen\",\"Ġid iot\",\"ĠTrans it\",\"Ġteasp oon\",\"W il\",\"K O\",\"ĠCom edy\",\"> ,\",\"Ġpop ulated\",\"W D\",\"Ġp igs\",\"ĠO culus\",\"Ġsymp athetic\",\"Ġmar athon\",\"19 8\",\"Ġseiz ure\",\"s ided\",\"Ġd op\",\"irt ual\",\"L and\",\"ĠFl oor\",\"osa urs\",\"... ]\",\"Ġl os\",\"Ġsubsid iary\",\"E Y\",\"ĠPart s\",\"ĠSt ef\",\"ĠJud iciary\",\"Ġ13 4\",\"Ġmir rors\",\"Ġk et\",\"t imes\",\"Ġneuro log\",\"Ġc av\",\"ĠGu est\",\"Ġtum or\",\"sc ill\",\"ĠLl oyd\",\"E st\",\"Ġcle arer\",\"Ġstere otypes\",\"Ġd ur\",\"not hing\",\"Red dit\",\"Ġnegoti ated\",\"---------------- --------\",\"23 5\",\"Ġfl own\",\"ĠSe oul\",\"ĠRes ident\",\"ĠS CH\",\"Ġdisappear ance\",\"ĠV ince\",\"g rown\",\"Ġgrab s\",\"r il\",\"ĠInf inite\",\"ĠTw enty\",\"Ġpedest rian\",\"Ġjer sey\",\"ĠF ur\",\"ĠInf inity\",\"ĠEll iott\",\"Ġment or\",\"Ġmor ally\",\"Ġob ey\",\"sec ure\",\"iff e\",\"Ġantib iotics\",\"ang led\",\"ĠFre eman\",\"ĠIntrodu ction\",\"J un\",\"Ġm arsh\",\"ic ans\",\"ĠEV ENTS\",\"och ond\",\"W all\",\"icult y\",\"Ġmisdem eanor\",\"Ġl y\",\"Th omas\",\"ĠRes olution\",\"Ġanim ations\",\"ĠD ry\",\"Ġinter course\",\"ĠNew castle\",\"ĠH og\",\"ĠEqu ipment\",\"17 7\",\"Ġterrit orial\",\"Ġarch ives\",\"20 3\",\"Fil ter\",\"ĠMun ich\",\"Ġcommand ed\",\"ĠW and\",\"Ġpit ches\",\"ĠCro at\",\"Ġrat ios\",\"ĠM its\",\"Ġaccum ulated\",\"ĠSpecific ally\",\"Ġgentle man\",\"acer b\",\"Ġp enn\",\"Ġa ka\",\"ĠF uk\",\"Ġinterven e\",\"ĠRef uge\",\"ĠAlz heimer\",\"Ġsuccess ion\",\"oh an\",\"d oes\",\"L ord\",\"Ġsepar at\",\"Ġcorrespond ence\",\"Ġsh iny\",\"P rior\",\"Ġs ulf\",\"Ġmiser able\",\"Ġded ication\",\"( ).\",\"Ġspecial ists\",\"Ġdefect s\",\"ĠC ult\",\"ĠX ia\",\"Ġje opard\",\"ĠO re\",\"Ab ility\",\"Ġle ar\",\"Ġamb itions\",\"ĠB MI\",\"ĠArab s\",\"Ġ19 42\",\"Ġpres ervation\",\"ific ate\",\"Ġash amed\",\"l oss\",\"ĠRest aur\",\"Ġrese mble\",\"Ġen rich\",\"ĠK N\",\"ĠCl an\",\"fl oat\",\"Ġplay able\",\"IT T\",\"Ġharm ony\",\"arr ison\",\"ĠWe instein\",\"w ere\",\"Ġpoison ing\",\"ĠCom put\",\"ĠWord Press\",\"m ajor\",\"ĠVal ve\",\"F an\",\"ĠTh row\",\"ĠRom ans\",\"ĠDep ression\",\"ad os\",\"Ġtort ured\",\"Ġbal ancing\",\"bott om\",\"Ġacqu iring\",\"ĠMon te\",\"ard i\",\"Ġa ura\",\"Ġ# #\",\"ĠStand ing\",\"ĠAtl as\",\"C F\",\"Ġintr ins\",\"ĠBen ghazi\",\"Ġcamp ing\",\"Ġt apped\",\"bl ade\",\"st rous\",\"ĠR abb\",\"ĠW ritten\",\"t ip\",\"ĠNe igh\",\"ster dam\",\"ĠAll ow\",\"ĠHe aling\",\"ĠR hod\",\"n um\",\"Ġcaffe ine\",\"ĠPer cent\",\"Ġbo o\",\"Ġapp les\",\"30 5\",\"Ġwel coming\",\"Ġappl aud\",\"Ġa usterity\",\"Â ±\",\"ĠRe ality\",\"ef e\",\"å ®\",\"Ġsu cks\",\"Ġtab s\",\"ĠPay Pal\",\"Ġback pack\",\"Ġgif ted\",\"abul ary\",\"ĠSc out\",\"ir teen\",\"Ġch in\",\"Ġo mitted\",\"Ġnegative ly\",\"Ġaccess ing\",\"ĠE arn\",\"Ġambul ance\",\"Ġhead phones\",\"Ġ20 5\",\"ĠRef resh\",\"p resident\",\"ĠKit chen\",\"ĠEnt ered\",\"ĠS nyder\",\"00 5\",\"om ical\",\"Ġborrow ed\",\"ĠN em\",\"Ġav iation\",\"Ġst all\",\"rim ination\",\"Ġuniform s\",\"it ime\",\"ĠSim mons\",\"ener gy\",\"ab lished\",\"y y\",\"qual ified\",\"Ġrall ies\",\"ĠSt uart\",\"fl ight\",\"Ġgang s\",\"r ag\",\"Ġv ault\",\"lu x\",\"ĠCom par\",\"Ġdesign ation\",\"20 9\",\"ĠJ os\",\"d ollar\",\"z ero\",\"Ġwell s\",\"30 3\",\"Ġconstitu ents\",\"Ġhe ck\",\"Ġc ows\",\"Ġcommand ers\",\"Ġdifferent ial\",\"ĠC atherine\",\"29 9\",\"Ġval ve\",\"Ġbr ace\",\"Ġperspect ives\",\"c ert\",\"f act\",\"icular ly\",\"ĠMc N\",\"pl anes\",\"Ġint ric\",\"Ġpe as\",\"ov an\",\"Ġtoss ed\",\"ret ch\",\"ĠL opez\",\"Ġunf amiliar\",\"de ath\",\"ĠA part\",\"ĠCh ang\",\"Ġrelie ved\",\"rop he\",\"Ġair ports\",\"Ġfre ak\",\"ut il\",\"M ill\",\"ĠCh in\",\"ĠOw en\",\"m ale\",\"ĠBro ken\",\"ĠWind s\",\"ro b\",\"r ising\",\"Ġfire fighters\",\"Ġauthor itarian\",\"Ġ14 8\",\"Bit coin\",\"ex ternal\",\"Ġbrow sers\",\"iche ver\",\"or ian\",\"Ġun b\",\"Ġpo ke\",\"ĠZ ot\",\"M id\",\"ĠPop ular\",\"Ġco vert\",\"Ġcont ributes\",\"Ġ6 50\",\"Ġcont ention\",\"G ate\",\"Ġcons oles\",\"Ġchrom os\",\"ĠI X\",\"Ġvis ually\",\"ĠE isen\",\"Ġjewel ry\",\"Ġdeleg ation\",\"Ġacceler ate\",\"ĠR iley\",\"Ġsl ope\",\"Ġind oor\",\"it ially\",\"Ġhuge ly\",\"Ġtun nels\",\"Ġfin ed\",\"Ġdirect ive\",\"Ġfore head\",\"ustom ed\",\"Ġsk ate\",\"Mus ic\",\"g as\",\"Ġrecogn izing\",\"am bo\",\"Ġover weight\",\"ĠGr ade\",\"Ù Ĭ\",\"Ġsound ing\",\"Ġlock ing\",\"ĠR EM\",\"St ore\",\"Ġexc av\",\"ĠLike wise\",\"ĠL ights\",\"Ġel bow\",\"ĠSupp ly\",\"w ic\",\"Ġhands ome\",\"19 94\",\"C oll\",\"Ġadequ ately\",\"ĠAssoci ate\",\"Ġstri ps\",\"Ġcrack down\",\"Ġmar vel\",\"ĠK un\",\"Ġpass ages\",\"@@ @@\",\"ĠT all\",\"Ġthought ful\",\"names e\",\"Ġprost itution\",\"bus iness\",\"Ġball istic\",\"person al\",\"c ig\",\"iz ational\",\"R ound\",\"ĠÂłĠÂł ĠÂłĠÂł\",\"ĠCole man\",\"Ġadm itting\",\"ĠPl ug\",\"Ġbit coins\",\"ĠSu z\",\"Ġfair ness\",\"Ġsupp lier\",\"Ġcatast rophic\",\"ĠHel en\",\"o qu\",\"M arc\",\"ĠArt icles\",\"g ie\",\"Ġend angered\",\"Ġdest iny\",\"ĠVol t\",\"ol ia\",\"ax is\",\"Ġche at\",\"Ġun ified\",\"IC O\",\"qu ote\",\"30 2\",\"ĠS ed\",\"Ġsupp ression\",\"Ġanaly zing\",\"Ġsqu at\",\"Ġfig uring\",\"Ġcoordin ates\",\"Ġch unks\",\"Ġ19 46\",\"Ġsub p\",\"Ġw iki\",\"ĠFor bes\",\"ĠJ upiter\",\"ĠE rik\",\"im er\",\"ĠCom mercial\",\"\\\\ )\",\"Ġlegitim acy\",\"Ġd ental\",\"ĠMe an\",\"Ġdefic its\",\"5 50\",\"Orig inally\",\"ĠHor ror\",\"Ġcontam ination\",\"ll ah\",\"Ġconf isc\",\"ĠCl are\",\"T B\",\"ĠF ailed\",\"an ed\",\"Ġrul er\",\"ĠCont roller\",\"Ġfemin ists\",\"F ix\",\"g ay\",\"20 7\",\"Ġr abbit\",\"Th ird\",\"ownt own\",\"Ġgl ue\",\"Ġvol atile\",\"Ġsh ining\",\"Ġf oll\",\"Ġimp aired\",\"Ġsup ers\",\"æ Ī\",\"Ġcl utch\",\"ļé ĨĴ\",\"Ġpro let\",\"Ġ( !\",\"Ġy elled\",\"ĠK iev\",\"ĠEr n\",\"ĠSh ock\",\"K B\",\"Ġsit uated\",\"qu ery\",\"ĠN as\",\"Ġan nex\",\"char acter\",\"ĠHol iday\",\"Ġautom ation\",\"ĠJ ill\",\"ĠRem astered\",\"Ġl inem\",\"Ġwild erness\",\"ĠHor izon\",\"ĠGu inea\",\"A Z\",\"Ġmain land\",\"Ġsec recy\",\"LE ASE\",\"Ġp unk\",\"ĠProv ince\",\"( ),\",\"Spe ed\",\"Ġhand ing\",\"ĠSeb ast\",\"S ir\",\"r ase\",\"Ġj ournals\",\"Ġcon gest\",\"ĠT ut\",\"ir rel\",\"Ġschizophren ia\",\"Ġmis ogyn\",\"health y\",\"I ron\",\"Ġreact ed\",\"- $\",\"25 2\",\"Ġpl ural\",\"Ġpl um\",\"Ġbarg ain\",\"Ġground ed\",\"f inder\",\"Ġdis se\",\"ĠL az\",\"O OD\",\"Ġat roc\",\"F actory\",\"Ġmin ions\",\"Ġo ri\",\"ĠB rave\",\"ĠP RE\",\"ĠMy anmar\",\"ĠH od\",\"Ġexped ition\",\"Ġexpl ode\",\"ĠCo ord\",\"Ġext r\",\"ĠB rief\",\"ĠAD HD\",\"Ġhard core\",\"feed ing\",\"Ġd ile\",\"ĠF ruit\",\"Ġvacc ination\",\"ĠM ao\",\"osp here\",\"Ġcont ests\",\"- |\",\"Ġf ren\",\"isp here\",\"R om\",\"ĠSh arp\",\"ĠTre nd\",\"Ġdis connect\",\"âĢ¢ âĢ¢\",\"Ġper secution\",\"Ear th\",\"Ġhealth ier\",\"38 4\",\"Ġc ob\",\"ĠTr inity\",\"OW S\",\"AN N\",\"Ġspecial ty\",\"Ġg ru\",\"Ġcooper ative\",\"wh y\",\"Start ing\",\"ĠIss ues\",\"st re\",\"ens or\",\"Ġ18 5\",\"Ad v\",\"! ?\",\"ĠRe vel\",\"em ia\",\"ĠH ulk\",\"Ġcelebr ations\",\"ĠS ou\",\"ra ud\",\"ĠKle in\",\"Ġun real\",\"con text\",\"Ġpartners hips\",\"Ġadop ting\",\"t ical\",\"Ġspl ash\",\"ĠHe zbollah\",\"c ategory\",\"cycl op\",\"xt on\",\"ĠD ot\",\"urd y\",\"t z\",\"Ġenvelop e\",\"ĠN L\",\"â ķ\",\"Ġwhere in\",\"Spe c\",\"18 4\",\"Ġte lev\",\"al iation\",\"Ġmyth s\",\"å °\",\"Ġrig orous\",\"Ġcommun icating\",\"Ġobser ver\",\"Ġre he\",\"ĠW ash\",\"Ġapolog ized\",\"ĠT in\",\"Ġexpend itures\",\"work ers\",\"d ocument\",\"Ġhes itate\",\"ĠLen in\",\"Ġunpredict able\",\"Ġrenew al\",\"cl er\",\"ok ia\",\"ĠCON T\",\"Ġpost season\",\"Tok ens\",\"Ġex acerb\",\"Ġbet ting\",\"Ġ14 7\",\"Ġelev ation\",\"W ood\",\"ĠSol omon\",\"19 4\",\"00 4\",\"out put\",\"Ġredu nd\",\"ĠM umbai\",\"Ġp H\",\"Ġreprodu ce\",\"ĠD uration\",\"MA X\",\"Ġb og\",\"C BS\",\"ĠBal ance\",\"ĠS gt\",\"ĠRec ent\",\"Ġc d\",\"Ġpo pped\",\"Ġincomp et\",\"pro p\",\"ay an\",\"g uy\",\"Pac ific\",\"Ġty r\",\"Ġ{ {\",\"ĠMy stic\",\"ĠD ana\",\"Ġmast urb\",\"Ġge ometry\",\"Ã ¢\",\"ĠCor rect\",\"Ġtraject ory\",\"Ġdistract ed\",\"Ġf oo\",\"ĠW elsh\",\"L uc\",\"m ith\",\"Ġrug by\",\"Ġrespir atory\",\"Ġtri angle\",\"Ġ2 15\",\"Ġunder graduate\",\"ĠSuper ior\",\"ch anging\",\"_ -\",\"Ġright ly\",\"Ġrefere e\",\"Ġluc rative\",\"Ġun authorized\",\"Ġresemb les\",\"ĠGN U\",\"ĠDer by\",\"Ġpath ways\",\"ĠL ed\",\"Ġend urance\",\"Ġst int\",\"Ġcollect or\",\"F ast\",\"Ġd ots\",\"Ġnational s\",\"ĠSec urities\",\"Ġwh ip\",\"Par am\",\"Ġlearn s\",\"M agic\",\"Ġdetail ing\",\"m oon\",\"Ġbroadcast ing\",\"Ġb aked\",\"26 5\",\"hol m\",\"ĠS ah\",\"ĠHus sein\",\"ĠCourt esy\",\"17 4\",\"Ġ14 6\",\"Ġge ographic\",\"pe ace\",\"Ġjud ging\",\"ĠS tern\",\"B ur\",\"Ġstory line\",\"G un\",\"ĠSt ick\",\"24 5\",\"30 7\",\"ãĤ´ ãĥ³\",\"ĠAdminist rator\",\"Ġbur nt\",\"Ġp ave\",\"ch oes\",\"Ex ec\",\"Ġcamp uses\",\"Res ult\",\"Ġmut ations\",\"ĠCh arter\",\"Ġcapt ures\",\"Ġcomp ares\",\"Ġbad ge\",\"S cient\",\"Ġer ad\",\"ier y\",\"o i\",\"ett es\",\"ĠE state\",\"Ġst rap\",\"Ġproud ly\",\"Ġf ried\",\"Ġwithd rawn\",\"ĠV oy\",\"ph ony\",\"It ems\",\"ĠP ierce\",\"b ard\",\"Ġann otation\",\"ant on\",\"ill on\",\"Im pro\",\"... )\",\"Ġhapp ier\",\"---- --\",\"ad just\",\"Ġstaff ers\",\"Ġactiv ism\",\"Ġper f\",\"Ġal right\",\"N eed\",\"Ġcomm ence\",\"Ġopio id\",\"ĠAm anda\",\"E s\",\"ĠP ars\",\"ĠK aw\",\"W orks\",\"24 8\",\"Ġind o\",\"t c\",\"end ant\",\"ĠM oto\",\"Ġlegal ization\",\"OT E\",\"Ġtask ed\",\"Ġt sp\",\"ĠACT IONS\",\"16 6\",\"Ġrefres hing\",\"ĠN R\",\"ĠPere z\",\"Ġinfring ement\",\"S Y\",\"List en\",\"in ning\",\"k u\",\"Ġrot ate\",\"pro gram\",\"ar ah\",\"Des ign\",\"Ġ( Â£\",\"Ġst oring\",\"Ġwar rants\",\"Ġjud gement\",\"ĠB rist\",\"us ually\",\"ph oto\",\"ĠR an\",\"ĠP ine\",\"Ġoutrage ous\",\"ĠValent ine\",\"lu ence\",\"ĠEvery body\",\"Al tern\",\"Ġrele vance\",\"Ġtermin ated\",\"Ġd essert\",\"Ġfulf illed\",\"Ġprosecut ed\",\"ĠW ords\",\"Ġm igrant\",\"Ġcultiv ation\",\"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\",\"idel ity\",\"ĠV ern\",\"ĠLog in\",\"Ġmetaph or\",\"ĠT ip\",\"Ġrecru its\",\"ĠP ig\",\"rib ing\",\"Ġenthusi asts\",\"ex per\",\"Ġfright ening\",\"ĠH air\",\"ans on\",\"str ate\",\"Ġh i\",\"He ight\",\"Ġown ing\",\"n one\",\"Ġdis like\",\"Ġkn ives\",\"pher d\",\"Ġloud ly\",\"ĠAP Is\",\"Dis play\",\"ĠL ac\",\"ĠUS S\",\"ab l\",\"ver ages\",\"J ew\",\"Ġ17 2\",\"ĠHist orical\",\"at oon\",\"ĠPhys ics\",\"in tern\",\"Ġwarm th\",\"Ġto pp\",\"D M\",\"Ġgun man\",\"Ġem peror\",\"od i\",\"ãĥ £\",\"in atory\",\"ĠR ib\",\"Ġ13 1\",\"ĠSat urn\",\"ĠSh ining\",\"Ġw aking\",\"Qu otes\",\"Ġcomed ian\",\"en berg\",\"Â ½\",\"Ġbelie vers\",\"Ġpaper work\",\"c ustom\",\"Ġle v\",\"Ġl ament\",\"Ġpour ing\",\"22 2\",\"p olitical\",\"ĠSupp lement\",\"m aid\",\"Ġcruel ty\",\"Ġt read\",\"ys ics\",\"A w\",\"rit es\",\"Ġmod ifier\",\"ĠP osition\",\"Ad am\",\"l b\",\"ub s\",\"Ġimper fect\",\"Ġcl usters\",\"ĠEngine er\",\"ĠC herry\",\"Ġinaug uration\",\"ĠS au\",\"Ġembod iment\",\"ĠUn cle\",\"Ġover r\",\"Ġexplos ions\",\"c ule\",\"ĠPrinc eton\",\"ĠAndre a\",\"Ġincorrect ly\",\"Ġearn est\",\"Ġpil gr\",\"ĠS print\",\"Ġslee ve\",\"Ġhe ars\",\"ĠAm azing\",\"Ġbrow sing\",\"ag in\",\"Ġhom eland\",\"Ġha w\",\"Ġd iving\",\"ist ered\",\"17 8\",\"Ġbarg aining\",\"ĠArc ade\",\"Ġdeleg ate\",\"ters on\",\"................................ ................................\",\"ĠJackson ville\",\"27 5\",\"Ġst agn\",\"Ġad am\",\"ĠSher man\",\"C B\",\"Ġsub urb\",\"ĠFood s\",\"Ġconver ting\",\"ĠAr ist\",\"Ġch ambers\",\"l ove\",\"Ġam ino\",\"ĠG an\",\"Ġmad ness\",\"m c\",\"ĠUS E\",\"def ined\",\"Ġul tr\",\"ind ust\",\"Ġw olves\",\"l ance\",\"Add itionally\",\"Ġcr acks\",\"as ia\",\"ĠRe ason\",\"ĠP ump\",\"Ġaccident al\",\"ĠL aser\",\"ĠR id\",\"Ġinitial ized\",\"ell i\",\"Ġun named\",\"Ġn oun\",\"ĠPass ed\",\"Ġhost age\",\"ĠEth iop\",\"sh irts\",\"Ġun rel\",\"ĠEmb assy\",\"Ġ19 41\",\"Ġat oms\",\"Ġpur ported\",\"16 4\",\"ĠF i\",\"Ġgall ons\",\"ĠMon ica\",\"Ġp g\",\"en ment\",\"Ġsort ed\",\"ĠG ospel\",\"Ġhe ights\",\"Ġtr aced\",\"Ġunder going\",\"She ll\",\"Ġs acks\",\"Ġproport ions\",\"Ġhall uc\",\"F ont\",\"ac et\",\"Ġwar mer\",\"ĠIN TER\",\"Ġgrab bing\",\"Pl ug\",\"Ġreal ization\",\"ĠBur ke\",\"Ġen chant\",\"AT ER\",\"ĠSe ed\",\"Ġabund ant\",\"F M\",\"Ġc ivic\",\"V s\",\"is i\",\"Ġv ow\",\"Ġre per\",\"ĠPartners hip\",\"Ġpenet ration\",\"Ġax e\",\"Ġsh attered\",\"ĠZ ombies\",\"Ġv inyl\",\"ĠAl ert\",\"e on\",\"Ġoblig ed\",\"ĠIll ust\",\"ĠPl aza\",\"ĠFront ier\",\"Ġdavid jl\",\"ĠSer ial\",\"ĠH av\",\"ĠNut rition\",\"B i\",\"Ġâĸ Ī\",\"ĠJ ays\",\"lin ux\",\"Ġhur ry\",\"Ġv oy\",\"Ġhop eless\",\"ĠSte alth\",\"Ġ ãģ\",\"ess ors\",\"tt le\",\"b org\",\"ĠSaf ari\",\"f ell\",\"Ġw ary\",\"d ue\",\"ĠAb ove\",\"H a\",\"E LL\",\"Ġnot or\",\"ĠW on\",\"T oo\",\"Ġoccup ations\",\"Ġposs essions\",\"Ġinv iting\",\"Ġpred ators\",\"Ġacceler ated\",\"Ġ15 7\",\"uter te\",\"ĠC ube\",\"e ast\",\"acc ount\",\"G ive\",\"Ġtrans plant\",\"red ients\",\"id able\",\"Ġscreens hots\",\"ĠG und\",\"ĠF S\",\"Ġtravel ers\",\"Ġsens ory\",\"ĠF iat\",\"ĠRock ets\",\"İ ĭ\",\"_ {\",\"F riend\",\"Ġchar ming\",\"AL S\",\"Ġenjoy ment\",\"m ph\",\"Ġ5 000\",\"ĠRE G\",\"Ù Ĩ\",\"b ia\",\"Ġcomp ilation\",\"ro st\",\"ĠV P\",\"ĠSch ne\",\"201 9\",\"Ġcop ying\",\"M ORE\",\"ĠFl ore\",\"f alls\",\"2 15\",\"t otal\",\"Ġdis ciples\",\"d ouble\",\"Ġexceed ing\",\"Ġsm ashed\",\"Ġconcept ual\",\"ĠRom ania\",\"ĠB rent\",\"ĠI CE\",\"ĠT ou\",\"Ġg rap\",\"Ġn ails\",\"18 9\",\"ãĥ ĺ\",\"Ġproc ure\",\"e ur\",\"Ġconfir ming\",\"ĠC ec\",\"aw i\",\"ĠEd en\",\"Ġn g\",\"Ġengine ered\",\"at ics\",\"Ġhook ed\",\"Ġdisgust ing\",\"ĠMur der\",\"ãĤ ¿\",\"L ibrary\",\"Ġ16 8\",\"Al most\",\"hem atic\",\"Men u\",\"ĠNot re\",\"ĠJ ur\",\"Ġkidn apped\",\"Ġhack er\",\"ĠJ ade\",\"Ġcreep y\",\"Ġdraw ings\",\"ĠSpons or\",\"Ġcycl ists\",\"ĠGob lin\",\"Ġoptim ized\",\"Ġst aged\",\"ĠMc D\",\"bet ween\",\"A ge\",\"en o\",\"S ex\",\"ĠW ide\",\"n ings\",\"av is\",\"Ġincap able\",\"ĠK ob\",\"Ġreward ing\",\"ĠL one\",\"oles cent\",\"Ġcontract ed\",\"Ġstick y\",\"J ose\",\"B all\",\"f est\",\"ĠIn put\",\"ĠRec ently\",\"Ġto mat\",\"squ are\",\"App lication\",\"Ġnit rogen\",\"Ġdupl icate\",\"ĠRec on\",\"ĠD ear\",\"L ondon\",\"Ġint ra\",\"Ġd ock\",\"Ġout reach\",\"ĠM illion\",\"Ġmamm als\",\"am pton\",\"V AL\",\"Ġsn aps\",\"Ġd os\",\"ĠWh ole\",\"ĠRead y\",\"T ry\",\"ĠWinn ipeg\",\"ear ance\",\"Ġinc urred\",\"ren ched\",\"ĠNS W\",\"il ot\",\"rain e\",\"Ġc ube\",\"g ot\",\"Ġrun way\",\"etermin ed\",\"ĠHaw ks\",\"Ġsurviv or\",\"ĠW ish\",\"ĠD in\",\"ĠDE F\",\"ĠV ault\",\"18 7\",\"Ġmush rooms\",\"Ġcris p\",\"be y\",\"ĠDisco very\",\"Ġdevelopment al\",\"Ġparad igm\",\"Ġcha otic\",\"ĠT su\",\"Ġ3 33\",\"b ons\",\"Ġbacter ial\",\"Ġcomm its\",\"Ġcos mic\",\"Ġme ga\",\"oc ative\",\"ĠP aint\",\"ophob ic\",\"Ġv ain\",\"Ġcar ved\",\"ĠTh ief\",\"ĠG ul\",\"ows hip\",\"Ġc ites\",\"ĠEd inburgh\",\"Ġdimin ished\",\"Ġacknowled ges\",\"ĠK ills\",\"Ġmic row\",\"ĠHer a\",\"Ġsen iors\",\"Ġwhere by\",\"H op\",\"at ron\",\"Ġun available\",\"ĠN ate\",\"Ġ4 80\",\"Ġsl ated\",\"ĠRe becca\",\"ĠB attery\",\"Ġgram mar\",\"Ġhead set\",\"Ġcurs or\",\"Ġex cluding\",\"any e\",\"aunder ing\",\"eb in\",\"Ġfeas ible\",\"ĠPub lishing\",\"ĠLab s\",\"ĠCl iff\",\"ĠFerr ari\",\"Ġp ac\",\"vis ible\",\"mark ed\",\"pe ll\",\"Ġpol ite\",\"Ġstagger ing\",\"ĠGal actic\",\"Ġsuper st\",\"Ġpar an\",\"ĠOffic ers\",\"ãĢ ģ\",\"Ġspecific s\",\"ul us\",\"23 9\",\"ĠP aste\",\"AM P\",\"ĠPan ama\",\"ĠDe lete\",\"angu ard\",\"rest rial\",\"Ġhero ic\",\"ĠD y\",\"Ø§ ÙĦ\",\"Ġincumb ent\",\"Ġcr unch\",\"t ro\",\"Ġsc oop\",\"Ġblog ger\",\"Ġsell ers\",\"ure n\",\"Ġmedic ines\",\"ĠC aps\",\"ĠAnim ation\",\"ox y\",\"Ġout ward\",\"Ġinqu iries\",\"22 9\",\"Ġpsych ologist\",\"ĠS ask\",\"ev il\",\"Ġcontam inated\",\"ãĤ ¨\",\"he rence\",\"Ġbrand ed\",\"ĠAbd ul\",\"z h\",\"Ġparagraph s\",\"Ġmin s\",\"Ġcor related\",\"er b\",\"Ġimp art\",\"Ġmil estone\",\"ĠSol utions\",\"ot le\",\"Ġunder cover\",\"Ġmar ched\",\"ĠCharg ers\",\"f ax\",\"ĠSec rets\",\"Ġr uth\",\"we ather\",\"Ġfemin ine\",\"Ġsh am\",\"Ġprest igious\",\"igg ins\",\"Ġs ung\",\"hist ory\",\"ett le\",\"gg ie\",\"Ġout dated\",\"ol and\",\"Ġper ceptions\",\"ĠS ession\",\"ĠDod gers\",\"u j\",\"ĠE ND\",\"D oc\",\"Ġdefic iency\",\"Gr and\",\"ĠJ oker\",\"Ġretro spect\",\"Ġdiagn ostic\",\"Ġharm less\",\"Ġro gue\",\"ĠA val\",\"E qu\",\"Ġtrans c\",\"ĠRoberts on\",\"ĠDep ending\",\"ĠBurn s\",\"iv o\",\"Ġhost ility\",\"F eatures\",\"ĵ ĺ\",\"Ġdis comfort\",\"ĠL CD\",\"spec ified\",\"ĠEx pect\",\"3 40\",\"Ġimper ative\",\"ĠReg ular\",\"Ch inese\",\"Ġstate wide\",\"Ġsy mm\",\"Ġlo ops\",\"Ġaut umn\",\"N ick\",\"Ġsh aping\",\"Ġqu ot\",\"Ġc herry\",\"ĠCross ref\",\"è¦ ļéĨĴ\",\"Stand ard\",\"he ed\",\"ĠD ell\",\"ĠViet namese\",\"Ġo st\",\"ĠV alkyrie\",\"O A\",\"Ass ad\",\"Ġreb ound\",\"ĠTra ffic\",\"pl aces\",\"æ ĺ\",\"ĠB uc\",\"17 2\",\"Ġshel ters\",\"Ġins isting\",\"ĠCertain ly\",\"ĠKenn eth\",\"ĠT CP\",\"Ġpen al\",\"ĠRe play\",\"he ard\",\"Ġdial ect\",\"iz a\",\"ĠF Y\",\"it cher\",\"ĠD L\",\"Ġspir al\",\"Ġquarterback s\",\"Ġh ull\",\"Ġgo ogle\",\"Ġto dd\",\"ĠSter ling\",\"ĠPl ate\",\"Ġsp ying\",\"mb ol\",\"ĠReal m\",\"ĠPro ced\",\"ĠCr ash\",\"Ġtermin ate\",\"Ġprotest ing\",\"C enter\",\"gu ided\",\"Ġun cover\",\"Ġboy cott\",\"Ġreal izes\",\"s ound\",\"Ġpret ending\",\"ĠV as\",\"19 80\",\"Ġfram ed\",\"Ġ13 9\",\"Ġdesc ended\",\"Ġrehab ilitation\",\"Ġborrow ing\",\"ĠB uch\",\"Ġbl ur\",\"R on\",\"ĠFro zen\",\"en za\",\"Ch ief\",\"ĠP oor\",\"Ġtransl ates\",\"M IN\",\"Ġ2 12\",\"J ECT\",\"Ġerupt ed\",\"Ġsuccess es\",\"S EC\",\"Ġpl ague\",\"Ġg ems\",\"d oms\",\"Ġstret ches\",\"ĠSp y\",\"Ġstory telling\",\"C redit\",\"ĠP ush\",\"Ġtra ction\",\"Ġin effective\",\"ĠL una\",\"Ġt apes\",\"Ġanaly tics\",\"erc ise\",\"Ġprogram mes\",\"ĠCar bon\",\"Ġbeh old\",\"he avy\",\"ĠConserv ation\",\"ĠF IR\",\"Ġs ack\",\"ter min\",\"ric ks\",\"Ġhous ed\",\"Ġunus ually\",\"I ce\",\"Ġexecut ing\",\"ĠMor oc\",\"ed ay\",\"Ġed itions\",\"Ġsm arter\",\"ĠB A\",\"Ġout law\",\"Ġvan ished\",\"ib a\",\"AL SE\",\"ĠSil va\",\"23 8\",\"C ould\",\"Ġphilos opher\",\"Ġevac uated\",\"Sec ret\",\"14 2\",\"Ġvis as\",\"ãĤ ¬\",\"ĠM alt\",\"ĠClear ly\",\"ĠN iger\",\"ĠC airo\",\"ĠF ist\",\"3 80\",\"ĠX ML\",\"aut o\",\"it ant\",\"Ġrein forced\",\"Rec ord\",\"ĠSurviv or\",\"G Hz\",\"Ġscrew s\",\"parent s\",\"Ġo ceans\",\"ma res\",\"Ġbra kes\",\"vas ive\",\"Ġhell o\",\"ĠS IM\",\"rim p\",\"Ġo re\",\"ĠArm our\",\"24 7\",\"Ġterr ific\",\"Ġt ones\",\"14 1\",\"ĠMin utes\",\"Ep isode\",\"Ġcur ves\",\"Ġinflamm atory\",\"Ġbat ting\",\"ĠBeaut iful\",\"L ay\",\"Ġunp op\",\"v able\",\"Ġr iots\",\"ĠTact ics\",\"b augh\",\"ĠC ock\",\"Ġorg asm\",\"ĠS as\",\"Ġconstruct or\",\"et z\",\"G ov\",\"Ġant agon\",\"Ġthe at\",\"Ġde eds\",\"ha o\",\"c uts\",\"ĠMc Cl\",\"Ġu m\",\"ĠScient ists\",\"Ġgrass roots\",\"ys sey\",\"\\\"] =>\",\"Ġsurf aced\",\"Ġsh ades\",\"Ġneighb ours\",\"Ġad vertis\",\"oy a\",\"Ġmer ged\",\"Up on\",\"Ġg ad\",\"Ġanticip ate\",\"Any way\",\"Ġsl ogan\",\"Ġdis respect\",\"I ran\",\"ĠT B\",\"act ed\",\"Ġsubp oen\",\"medi ately\",\"OO OO\",\"Ġwa iver\",\"Ġvulner abilities\",\"ott esville\",\"ĠHuff ington\",\"J osh\",\"ĠD H\",\"M onday\",\"ĠEll en\",\"K now\",\"x on\",\"it ems\",\"22 8\",\"Ġf ills\",\"ĠN ike\",\"Ġcum ulative\",\"and als\",\"I r\",\"Ġ ì\",\"Ġfr iction\",\"ig ator\",\"Ġsc ans\",\"ĠVi enna\",\"ld om\",\"Ġperform ers\",\"P rim\",\"Ġb idding\",\"M ur\",\"Ġlean ed\",\"ĠPri x\",\"al ks\",\"Ġ[ âĢ¦]\",\"ĠTw itch\",\"ĠDevelop er\",\"ĠG ir\",\"Ġcall back\",\"Ab stract\",\"Ġacc ustomed\",\"Ġfreed oms\",\"ĠP G\",\"ur acy\",\"Ġl ump\",\"is man\",\",, ,,\",\"19 92\",\"ĠR ED\",\"Ġwor m\",\"M atch\",\"ĠPl atinum\",\"I J\",\"ĠOwn er\",\"Tri via\",\"com pl\",\"Ġnew born\",\"Ġfant as\",\"O wn\",\"Ġ19 59\",\"Ġsymp ath\",\"Ġub iqu\",\"Ġoutput s\",\"Ġal lev\",\"Ġpr ag\",\"K evin\",\"Ġfav ors\",\"Ġbur ial\",\"Ġn urt\",\"so lete\",\"c ache\",\"Ġ15 6\",\"Ġunl ocks\",\"te chn\",\"M aking\",\"Ġcon quer\",\"ad ic\",\"æ ĸ\",\"Ġel f\",\"Ġelect orate\",\"ĠKurd s\",\"ĠSt ack\",\"ĠSam urai\",\"Ġâ ĺħ\",\"Ġ{ }\",\"ĠS aid\",\"ĠFall out\",\"Ġkind ness\",\"ĠCustom s\",\"ĠBou levard\",\"Ġhelicop ters\",\"ot ics\",\"ĠVe get\",\"com ment\",\"Ġcritic ised\",\"Ġpol ished\",\"ĠRem ix\",\"ĠC ultural\",\"Ġrec ons\",\"Ġdo i\",\"at em\",\"Sc reen\",\"Ġbar red\",\"Com ments\",\"ĠGener ally\",\"Ġsl ap\",\"7 20\",\"V ari\",\"p ine\",\"Ġem pt\",\"Ġh ats\",\"ĠPlay ing\",\"l ab\",\"a verage\",\"form s\",\"ĠC otton\",\"Ġcan s\",\"ĠD ON\",\"ĠSom alia\",\"C rypt\",\"ĠIncre ases\",\"E ver\",\"mod ern\",\"Ġsur geon\",\"3 000\",\"Ġrandom ized\",\"================================ ================================\",\"B ern\",\"im pl\",\"ĠC OR\",\"Ġpro claim\",\"th ouse\",\"Ġto es\",\"Ġam ple\",\"Ġpres erving\",\"Ġdis bel\",\"gr and\",\"B esides\",\"Ġsil k\",\"ĠPat tern\",\"h m\",\"Ġenter prises\",\"Ġaffidav it\",\"ĠAdvis ory\",\"Ġadvert ised\",\"ĠRel igious\",\"se ctions\",\"psy ch\",\"ĠField s\",\"aw ays\",\"Ġhasht ag\",\"ĠNight mare\",\"Ġv ampire\",\"Ġfore nsic\",\"rosso ver\",\"n ar\",\"Ġn avy\",\"Ġvac ant\",\"ĠD uel\",\"Ġhall way\",\"Ġface book\",\"ident ally\",\"ĠN RA\",\"Ġm att\",\"Ġhur ricane\",\"ĠKir by\",\"ĠP uzzle\",\"Ġsk irt\",\"ou st\",\"du llah\",\"Ġanal ogy\",\"in ion\",\"Ġtomat oes\",\"ĠN V\",\"ĠPe ak\",\"ĠMe yer\",\"Ġappoint ments\",\"Ġm asc\",\"Ġal ley\",\"re hend\",\"Ġchar ities\",\"Ġund o\",\"Ġdest inations\",\"ĠTest ing\",\"\\\"> </\",\"Ġdest ined\",\"Ġimp lements\",\"ĠHar old\",\"RE CT\",\"Ġoptim ization\",\"Ġkilomet res\",\"Ġc md\",\"Ġimpair ment\",\"Ġun successful\",\"Ġswift ly\",\"ĠGlas gow\",\"art en\",\"ĠSh ares\",\"ĠAn swer\",\"ĠAl bum\",\"Ġnut ritional\",\"ãĥ ĸ\",\"ĠF ut\",\"Ġbl oc\",\"ĠN FC\",\"Ġwholes ale\",\"ĠC W\",\"Ġneg lected\",\"Ġlaun cher\",\"Ġannounce ments\",\"OU LD\",\"com b\",\"Ġrot ating\",\"Ġrest s\",\"ĠT icket\",\"ched el\",\"L ou\",\"ĠV ic\",\"Ġ\\\" '\",\"Ġtem plates\",\"Ġrepl aces\",\"Ar c\",\":: ::\",\"ĠGil bert\",\"Ġillness es\",\"Ġsched ules\",\"Ġheter osexual\",\"L INE\",\"Ġhere in\",\"Ġco erc\",\"Ġdecre asing\",\"Ġde portation\",\"s udo\",\"ĠInd igenous\",\"Ġweigh s\",\"Al ong\",\"' );\",\"ĠBeng als\",\"70 7\",\"Ġjoint s\",\"ver ts\",\"Ġ14 9\",\"na ire\",\"Ġsimpl est\",\"Ġl ore\",\"10 80\",\"f iction\",\"ĠDat abase\",\"Ġreserv ation\",\"Ġs ou\",\"Ġsan ctuary\",\"aud io\",\"ap le\",\"Ġveget arian\",\"Ġanticip ation\",\"m icro\",\"Ġend uring\",\"Ġdepart ed\",\"Ġsidew alk\",\"Ġprohib its\",\"ĠF ont\",\"Ġcomp ute\",\"ĠS ect\",\"Ġ15 8\",\"B attle\",\"Ġbom ber\",\"Ġdist raction\",\"Ġend ured\",\"Ġpractition ers\",\"Ġdistur bed\",\"Ġdr ank\",\"ord ered\",\"Ġsurpr ises\",\"se at\",\"Sec urity\",\"ĠW isdom\",\"og o\",\"Ġsub paragraph\",\"ĠPen insula\",\"ĠOrig ins\",\"ire n\",\"ĠP av\",\"igg le\",\"Ġgrat itude\",\"ĠG ravity\",\"over ty\",\"im an\",\"ct r\",\"ĠCa esar\",\"c ould\",\"g em\",\"Ġsk ies\",\"Ġch amp\",\"Ġagree ing\",\"F amily\",\"D iv\",\"17 6\",\"Ġmess y\",\"um ption\",\"F ederal\",\"ern o\",\"ĠCh at\",\"Bey ond\",\"Ġdev ote\",\"ĠW alsh\",\"Ġdump ed\",\"Ġaccum ulation\",\"st ad\",\"hib ition\",\"Ġsm okers\",\"Ġinspect or\",\"F rench\",\"iss an\",\"ĠV ita\",\"Ġresearch ing\",\"R AM\",\"ĠCelt ics\",\"Ġcl oak\",\"ĠTer ra\",\"M ary\",\"so ld\",\"ĠD OM\",\"mod s\",\"Int el\",\"Ġmult itude\",\"ĠImpro ved\",\"Ġrel iance\",\"Ġartif act\",\"Ġalarm ing\",\"P rom\",\"h on\",\"T ION\",\"med ium\",\"Ġref lex\",\"ĠEx cel\",\"Ġweaken ed\",\"16 3\",\"2 24\",\"Ġcost umes\",\"Ġunique ly\",\"Ġs orrow\",\"Ġm ansion\",\"w p\",\"Ġsal v\",\"ĠGro ve\",\"bs p\",\"ĠSn iper\",\"ĠSh ipping\",\"ĠP OW\",\"Ġund is\",\"Ġbrand ing\",\"G irl\",\"ĠAh mad\",\"ĠL akes\",\"ĠCore y\",\"Ġinherit ance\",\"ener y\",\"Ġpack ing\",\"ĠP rest\",\"D est\",\"F W\",\"Ġregul ator\",\"l ocked\",\"Ġcont ested\",\"ĠMel issa\",\"ĠD uc\",\"Ġunpop ular\",\"Ġst acked\",\"Ġ19 17\",\"Ġyear ly\",\"Ġst are\",\"Ġassess ing\",\"Ã ¸\",\"Ġbe verages\",\"Ġcompet itions\",\"Ġstreng thening\",\"al ong\",\"ĠL ud\",\"Ġmel ted\",\"stan bul\",\"Ġb ounty\",\"EN C\",\"ĠL ands\",\"Ġdecl ares\",\"Ġcustom ize\",\"Ġcomp osite\",\"ãĥ ¬\",\"C M\",\"ograph ics\",\"ĠTem p\",\"Ġcont ender\",\"Ġins ign\",\"ĠL AN\",\"Ġdis asters\",\"ins pired\",\"Ġjud gments\",\"ustain able\",\"urs ion\",\"Ġvar iance\",\"ĠUlt imately\",\"Ġ --------\",\"u ador\",\"ĠR X\",\"Ġmel ting\",\"ĠExt ended\",\"ĠT we\",\"M ajor\",\"ĠB il\",\"Ġsy rup\",\"qu ick\",\"ĠHold er\",\"Ġinnoc ence\",\"U LE\",\"ĠM ight\",\"99 99\",\"Ġf al\",\"Ġcontinu ity\",\"Ġ19 53\",\"ĠB S\",\"st ill\",\"L at\",\"ĠAb use\",\"Ġun supported\",\"xxxx xxxx\",\"Ġinst itute\",\"Ġfrag ment\",\"ĠP ep\",\"W estern\",\"ĠC ause\",\"ĠFr ag\",\"ĠAr s\",\"à ¥\",\"ast ics\",\"Ġb ishop\",\"Ġcross es\",\"Ġ15 4\",\"ĠUp grade\",\"Ġmit igate\",\"ĠRay mond\",\"Mod s\",\"Ġtom ato\",\"Ġst umbled\",\"Ġdiff ers\",\"In itial\",\"ĠR aspberry\",\"Ġign ores\",\"Ġt ant\",\"Ã ł\",\"Ġrel ay\",\"Ġb isexual\",\"Ġconf ession\",\"Ġd ement\",\"in as\",\"ĠHe ather\",\"pl atform\",\"dri ving\",\"bour g\",\"ĠM ush\",\"Ġhy ster\",\"Det ails\",\"Ġdr ift\",\"ĠW ald\",\"ĠLuck ily\",\"or f\",\"Ġexp ire\",\"ĠP unch\",\"zy me\",\"g old\",\"Ġunp aid\",\"ĠT rent\",\"Ġun armed\",\"Ġill icit\",\"ĠT ottenham\",\"Ġsm ash\",\"Intern ational\",\"ink er\",\"Ġst ing\",\"ĠSadd am\",\"ĠAR T\",\"Ġtruth s\",\"b irth\",\"Ġso ber\",\"ĠN it\",\"Ġ ib\",\"Ġus able\",\"Ġst acks\",\"ĠSy lv\",\"Ġnort heast\",\"Ġdom ination\",\"ĠM our\",\"EN SE\",\"ĠMe asure\",\"Ġprogram mer\",\"Ġ< -\",\"18 2\",\"ĠCond ition\",\"Ġback yard\",\"ir ling\",\"ĠJ eb\",\"ĠCre ed\",\"ĠH ang\",\"ĠCOM P\",\"F ER\",\"ĠIs h\",\"Ġdetect ives\",\"------------ ---\",\"ĠMess enger\",\"Ġlo oph\",\"Ġgate way\",\"15 1\",\"ĠMaterial s\",\"ĠD T\",\"Ġdo omed\",\"od o\",\"Ġslic es\",\"Ġemail ed\",\"ĠPer l\",\"Ġren ov\",\"UT H\",\"ody nam\",\"ĠSouth west\",\"get ic\",\"ĠT PP\",\"Ġoptim ism\",\"ĠT ow\",\"ul ators\",\"prot ected\",\"y les\",\"Â «\",\"Ġex ile\",\"en v\",\"P rop\",\"ĠZimmer man\",\"Ù İ\",\"C a\",\"om aly\",\"ãĥ Ĩ\",\"Ġrail road\",\"L ee\",\"23 2\",\"Ġrepl icate\",\"Ġcomfort ably\",\"act ly\",\"Ġr av\",\"Ġtelesc ope\",\"Ġhonest y\",\"ĠPe pper\",\"ĠBr ing\",\"Ġric hest\",\"Ġout doors\",\"Ġh alls\",\"Ġcont end\",\"IS E\",\"Ġsub mitting\",\"Ġna ive\",\"ar ations\",\"Ġ14 3\",\"Ġpo ised\",\"respons ible\",\"Ġsoc ks\",\"ĠSk ull\",\"Quest ion\",\"Ġdiscover ies\",\"Jo ined\",\"ĠEn emies\",\"ĠWire less\",\"ĠRe venge\",\"Ġpuzz les\",\"Ġce ased\",\"29 0\",\"cript ions\",\"ĠCon sole\",\"Ġbo iling\",\"Ġdisc rep\",\"Ġded uction\",\"Ġar senal\",\"XX XX\",\"ĠAm sterdam\",\"rox imately\",\"ĠSh ane\",\"Ġpos ing\",\"ĠACL U\",\"ĠCompan ies\",\"Ġthe ology\",\"ĠU g\",\"qu arter\",\"ĠH ank\",\"Co in\",\"ĠL v\",\"Ġalleg ation\",\"ĠAv oid\",\"Ġindef initely\",\"Ġcommod ities\",\"Ġbr ig\",\"ĠMan it\",\"Ġt enth\",\"met hod\",\"ĠKn icks\",\"ĠâĢ İ\",\"Ġinv oked\",\"D ial\",\"AR A\",\"Ġc aucus\",\"22 7\",\"ĠJ ab\",\"Ġoun ces\",\"b ay\",\"Ġbud dy\",\"f an\",\"23 4\",\"ĠH il\",\"ad h\",\"ĠT Y\",\"ĠIN D\",\"Ġ19 39\",\"Ġiter ation\",\"ĠGonz alez\",\"ĠV ert\",\"ĠI O\",\"em b\",\"re ra\",\"en ch\",\"ĠRequ irements\",\"ĠW ins\",\"Ġlivest ock\",\"h ours\",\"\\\" âĢ¦\",\"b ral\",\"M arg\",\"ĠD one\",\"Ġwas ting\",\"ing ed\",\"g roups\",\"Ġw ishing\",\"ĠT umblr\",\"Ġt apping\",\"Ġnational ism\",\"ĠB yr\",\"Ġsqu ares\",\"ĠAct ions\",\"ãĥ ¥\",\"In side\",\"deb ug\",\"Ġapp end\",\"Ġstub born\",\"ĠC ind\",\"T ell\",\"Ġt earing\",\"ĠRe y\",\"or c\",\"ĠDay ton\",\"ĠN H\",\"ĠMad ness\",\"Ch arl\",\"ĠMor rison\",\"fil ter\",\"Ġacc use\",\"Ġ. /\",\"Ġtor rent\",\"Ġdecl ines\",\"g allery\",\"M ine\",\"Ġneg otiation\",\"ĠBash ar\",\"op ia\",\"19 93\",\"em ort\",\"ĠNo vel\",\"ĠF ang\",\"ers ive\",\"ĠInst ant\",\"Ġroll er\",\"A round\",\"ĠElect ions\",\"G ames\",\"Ġin expensive\",\"Ġwor s\",\"Ġv ul\",\"ĠH ole\",\"Ġunbeliev able\",\"Ġn ause\",\"Ġent r\",\"bo at\",\"ĠST E\",\"Ġbus h\",\"ĠHass an\",\"Ġw o\",\"Ġpa used\",\"ĠM ig\",\"l ived\",\"Ġsc out\",\"Ġl ith\",\"Pub lished\",\"du ino\",\"c ool\",\"Ġcirc ulating\",\"id as\",\"ĠP am\",\"viol ent\",\"ĠCraw ford\",\"udd le\",\"ĠLet ters\",\"Gu ard\",\"mor ph\",\"Ġwand ering\",\"Ġsoph omore\",\"Ġque er\",\"ĠBl ind\",\"r ue\",\"ĠMar riage\",\"D om\",\"Ġpadd ing\",\"Ġfold ers\",\"Ġmeaning less\",\"Ġcandid acy\",\"af ort\",\"Ġwhistle bl\",\"ĠIdent ified\",\"Ġcig ar\",\"Ġh id\",\"ĠDub ai\",\"Ġpost ure\",\"Ġh iking\",\"ĠTermin al\",\"Legend ary\",\"ĠT P\",\"ĠAT K\",\"ĠStar bucks\",\"ĠR iot\",\"19 91\",\"ĠBott om\",\"e ffic\",\"ĠEug ene\",\"ĠWy oming\",\"ĠRock y\",\"Ġsal mon\",\"Ġmet ro\",\"Ġb ilateral\",\"Ġcelebr ates\",\"L ength\",\"b illion\",\"B at\",\"Ġre leg\",\"Ġpse udo\",\"D T\",\"ĠRh ode\",\"P arent\",\"ple tion\",\"Ġatt ribut\",\"Ġtun ing\",\"ĠNOT E\",\"ĠRe bel\",\"ic us\",\"F und\",\"Ġcock tail\",\"Ġ5 01\",\"Ġsp oon\",\"Ġbrut ality\",\"Ġun ite\",\"Ġmicro bi\",\"ĠRe ich\",\"pos itive\",\"Ġam azed\",\"ĠN T\",\"D esc\",\"ECT ION\",\"Ġfalse ly\",\"ĠHigh lander\",\"ĠC rist\",\"ĠVictor ian\",\"Ġdistribut ions\",\"the ir\",\"ĠE instein\",\"Ġp od\",\"Ġepid em\",\"Ġhe ap\",\"ĠR anch\",\"Ġan them\",\"Ġre app\",\"ĠAub urn\",\"Ġconc urrent\",\"ĠThrough out\",\"ĠP OST\",\"â ĺ\",\"Ġhom emade\",\"k ick\",\"B eg\",\"Ġch assis\",\"c ounter\",\"Ġmer ger\",\"Ġl aps\",\"2 17\",\"un ion\",\"ĠTr igger\",\"Ġdeb ated\",\"Ġsil ently\",\"Ġrest raint\",\"B al\",\"0000 000\",\"Ġform idable\",\"ĠFil ip\",\"Ġsacrific es\",\"F ood\",\"Ġdwar f\",\"ĠSe qu\",\"in ian\",\"More over\",\"Ġtang ible\",\"ops is\",\"ĠMine craft\",\"ĠRegist ration\",\"o an\",\"Ġrepresent ations\",\"Ġth irst\",\"Ġcor p\",\"ire ment\",\"M ade\",\"l oe\",\"> \\\"\",\"c ats\",\"* .\",\"Ġgest ures\",\"gener al\",\"Le ague\",\"Ġpack ets\",\"ĠInspect or\",\"ĠBer g\",\"Ġfraud ulent\",\"Ġcritic ize\",\"F un\",\"Ġbl aming\",\"nd ra\",\"Ġsl ash\",\"ĠE ston\",\"Ġpropos ing\",\"Ġwh ales\",\"Ġtherap ist\",\"Ġsub set\",\"Ġle isure\",\"EL D\",\"ĠC VE\",\"ĠAct ivity\",\"Ġcul min\",\"sh op\",\"ĠD AY\",\"is cher\",\"ĠAdmir al\",\"ĠAtt acks\",\"Ġ19 58\",\"Ġmem oir\",\"Ġfold ed\",\"Ġsex ist\",\"Ġ15 3\",\"ĠL I\",\"Ġread ings\",\"Ġembarrass ment\",\"ĠEmploy ment\",\"w art\",\"ch in\",\"Ġcontin uation\",\"l ia\",\"Rec ently\",\"Ġd uel\",\"Ġevac uation\",\"ĠKash mir\",\"Ġdis position\",\"ĠR ig\",\"Ġbol ts\",\"Ġins urers\",\"4 67\",\"M ex\",\"Ġret aliation\",\"Ġmis ery\",\"Ġunre asonable\",\"r aining\",\"I mm\",\"ĠP U\",\"em er\",\"Ġgen ital\",\"ãĤ ³\",\"ĠC andy\",\"Ġon ions\",\"ĠP att\",\"lin er\",\"Ġconced ed\",\"Ġf a\",\"Ġfor c\",\"ĠH ernandez\",\"ĠGe off\",\"deb ian\",\"ĠTe ams\",\"Ġc ries\",\"Ġhome owners\",\"23 7\",\"A BC\",\"Ġst itch\",\"Ġstat istic\",\"Ġhead ers\",\"ĠBi ology\",\"Ġmot ors\",\"ĠG EN\",\"ĠL ip\",\"Ġh ates\",\"Ġhe el\",\"S elf\",\"i pl\",\"ED IT\",\"ort ing\",\"Ġann ot\",\"ĠSpe ech\",\"old emort\",\"ĠJ avascript\",\"ĠLe Bron\",\"Ġfoot print\",\"Ġf n\",\"Ġseiz ures\",\"n as\",\"h ide\",\"Ġ19 54\",\"ĠBe e\",\"ĠDecl aration\",\"ĠKat ie\",\"Ġreserv ations\",\"N R\",\"f emale\",\"Ġsatur ated\",\"Ġb iblical\",\"Ġtroll s\",\"Dev ice\",\"ph otos\",\"Ġdr ums\",\"ãĥīãĥ© ãĤ´ãĥ³\",\"N ight\",\"f ighter\",\"ĠH ak\",\"ri ber\",\"Ġc ush\",\"Ġdiscipl inary\",\"ba um\",\"ĠG H\",\"ĠSch midt\",\"ilib rium\",\"Ġs ixty\",\"ĠKush ner\",\"ro ts\",\"Ġp und\",\"ĠR ac\",\"Ġspr ings\",\"Ġcon ve\",\"Bus iness\",\"F all\",\"Ġqual ifications\",\"Ġvers es\",\"Ġnarc iss\",\"ĠK oh\",\"ĠW ow\",\"ĠCharl ottesville\",\"ed o\",\"Ġinterrog ation\",\"ĠW ool\",\"36 5\",\"B rian\",\"Ġâľ ĵ\",\"Ġalleg es\",\"ond s\",\"id ation\",\"ĠJack ie\",\"y u\",\"Ġl akes\",\"Ġworth while\",\"Ġcryst als\",\"ĠJud a\",\"Ġcomp rehend\",\"Ġfl ush\",\"Ġabsor ption\",\"ĠO C\",\"Ġfright ened\",\"ĠCh ocolate\",\"Mart in\",\"Ġbu ys\",\"Ġbu cks\",\"Ġapp ell\",\"ĠChampions hips\",\"Ġlist ener\",\"ĠDef ensive\",\"Ġc z\",\"ud s\",\"ĠM ate\",\"Ġre play\",\"Ġdecor ated\",\"Ġs unk\",\"ĠV IP\",\"ĠAn k\",\"Ġ19 5\",\"aa aa\",\"Nob ody\",\"ĠMil k\",\"ĠG ur\",\"ĠM k\",\"ĠS ara\",\"Ġse ating\",\"ĠW id\",\"Tr ack\",\"Ġemploy s\",\"Ġgig antic\",\"AP P\",\"ãĤ §\",\"in ventory\",\"Ġtow el\",\"at che\",\"l asting\",\"ĠT L\",\"Ġlat ency\",\"Ġkn e\",\"B er\",\"me aning\",\"Ġup held\",\"Ġplay ground\",\"Ġm ant\",\"S ide\",\"Ġstere o\",\"Ġnorth west\",\"Ġexception ally\",\"Ġr ays\",\"Ġrec urring\",\"D rive\",\"Ġup right\",\"Ġab duct\",\"ĠMar athon\",\"Ġgood bye\",\"Ġal phabet\",\"h p\",\"Ġcourt room\",\"ring ton\",\"ot hing\",\"T ag\",\"Ġdiplom ats\",\"Ġbar bar\",\"ĠAqu a\",\"18 3\",\"33 33\",\"Ġmat urity\",\"Ġinst ability\",\"ĠAp ache\",\"Ġ= ==\",\"Ġfast ing\",\"ĠGr id\",\"Mod Loader\",\"Ġ15 2\",\"A bs\",\"ĠOper ating\",\"ett i\",\"Ġacqu aint\",\"Don nell\",\"ĠK em\",\"ĠFor ge\",\"Ġarm ored\",\"M il\",\"Ġphilos ophers\",\"in vest\",\"Pl ayers\",\"â Ī\",\"Ġmy riad\",\"Ġcomr ades\",\"R ot\",\"Ġremember ing\",\"Ġcorrespond s\",\"Ġprogram mers\",\"ĠLyn n\",\"Ġo lig\",\"Ġco herent\",\"yn chron\",\"ĠChem ical\",\"Ġj ugg\",\"p air\",\"post s\",\"E ye\",\"ĠIn ner\",\"Ġsem ester\",\"ott est\",\"ĠEmir ates\",\"ric anes\",\"or ously\",\"m its\",\"ĠW is\",\"Ġd odge\",\"l ocation\",\"Ġf aded\",\"Am azon\",\"ĠPro ceed\",\"ĠIN FO\",\"j ournal\",\"ĠTru ck\",\"T en\",\"Ġ2 17\",\"Ġstat utes\",\"m obile\",\"ĠT ypes\",\"Rec omm\",\"b uster\",\"pe x\",\"Ġleg ends\",\"Ġhead ache\",\"f aced\",\"ĠWi Fi\",\"if ty\",\"ĠH ER\",\"Ġcirc uits\",\"ER ROR\",\"22 6\",\"ol in\",\"Ġcyl inder\",\"osp ace\",\"ik ers\",\"P rem\",\"Qu ant\",\"Ġconflic ting\",\"Ġslight est\",\"Ġfor ged\",\"ion age\",\"Step hen\",\"ĠK ub\",\"ĠOpp ortun\",\"ĠHe al\",\"Ġbl o\",\"Ġrul ers\",\"Ġh uh\",\"Ġsubmar ine\",\"f y\",\"ass er\",\"Ġallow ance\",\"ĠKas ich\",\"ĠT as\",\"ĠAustral ians\",\"Forge ModLoader\",\"ĠâĨ ĳ\",\"ĠMat rix\",\"am ins\",\"Ġ12 00\",\"ĠAc qu\",\"23 6\",\"D ocument\",\"ĠBre aking\",\"19 3\",\"ĠSub st\",\"ĠRoll er\",\"ĠPro perties\",\"ĠN I\",\"t ier\",\"Ġcr ushing\",\"Ġadvoc ating\",\"Further more\",\"keep ers\",\"Ġsex ism\",\"x d\",\"Ġcall er\",\"ĠS ense\",\"chie ve\",\"ĠT F\",\"Ġfuel ed\",\"Ġreminis cent\",\"Ġobs ess\",\"ur st\",\"Ġup hold\",\"ĠF ans\",\"het ics\",\"Ġâ Ĺ\",\"ĠB ath\",\"Ġbe verage\",\"Ġo scill\",\"25 4\",\"Ġpol es\",\"Ġgrad ual\",\"Ġex ting\",\"ĠS uff\",\"ĠS uddenly\",\"Ġlik ing\",\"Ġ19 49\",\"un ciation\",\"am ination\",\"ĠO mar\",\"ĠL V\",\"ĠCon sequently\",\"Ġsynt hes\",\"ĠG IF\",\"Ġp ains\",\"Ġinteract ing\",\"u ously\",\"inc re\",\"Ġrum or\",\"ĠScient ology\",\"19 7\",\"ĠZ ig\",\"Ġspe lling\",\"ĠA SS\",\"Ġexting u\",\"ms on\",\"Ġg h\",\"Ġremark ed\",\"ĠStrateg ic\",\"ĠM ON\",\"å ¥\",\"g ae\",\"ĠWH AT\",\"E ric\",\"ĠCamp us\",\"Ġmeth ane\",\"Ġimag in\",\"J UST\",\"ĠAl m\",\"X T\",\"i q\",\"ĠR SS\",\"Ġwrong doing\",\"att a\",\"Ġbig ot\",\"Ġdemonstr ators\",\"ĠCal vin\",\"ĠV illa\",\"Ġmembr ane\",\"ĠAw esome\",\"Ġbenef ic\",\"26 8\",\"Ġmagn ificent\",\"ĠL ots\",\"G reg\",\"ĠBor is\",\"Ġdetain ees\",\"ĠH erman\",\"Ġwhis pered\",\"Ġa we\",\"Prof essor\",\"fund ing\",\"Ġphys iological\",\"ĠDest ruction\",\"Ġlim b\",\"Ġmanip ulated\",\"Ġbub bles\",\"Ġpse ud\",\"Ġhyd ra\",\"ĠBrist ol\",\"Ġst ellar\",\"ĠExp ansion\",\"ĠK ell\",\"ĠInterest ingly\",\"Ġm ans\",\"Ġdrag ging\",\"Ġec ological\",\"ĠF it\",\"Ġg ent\",\"Ġbenef ited\",\"ĠHait i\",\"Ġpoly g\",\"ãĥ İ\",\"Ġ20 30\",\"Ġpro w\",\"Ġrecon struction\",\"Ġwas t\",\"Ġpsych ic\",\"ĠGree ks\",\"Hand ler\",\"16 2\",\"ĠP ulse\",\"Ġsol icit\",\"Ġsy s\",\"Ġinflu x\",\"ĠG entle\",\"per cent\",\"Ġprolifer ation\",\"Ġtax able\",\"Ġdisreg ard\",\"Ġesc aping\",\"Ġg inger\",\"Ġwith stand\",\"Ġdevast ated\",\"ĠD ew\",\"ser ies\",\"Ġinject ed\",\"ela ide\",\"Ġturn over\",\"he at\",\"Ļ Ĥ\",\"H appy\",\"ĠSil ent\",\"ãĤ Ń\",\"iv ism\",\"Ġir rational\",\"AM A\",\"Ġre ef\",\"r ub\",\"Ġ16 2\",\"Ġbank ers\",\"ĠEth ics\",\"v v\",\"Ġcritic isms\",\"K n\",\"18 6\",\"M ovie\",\"ĠT ories\",\"Ġno od\",\"Ġdist ortion\",\"F alse\",\"od ore\",\"Ġt asty\",\"Res earch\",\"ĠU ID\",\"- )\",\"Ġdivor ced\",\"ĠM U\",\"ĠHay es\",\"ĠIs n\",\"ian i\",\"ĠH Q\",\"Ġ\\\" #\",\"ign ant\",\"Ġtra umatic\",\"ĠL ing\",\"H un\",\"Ġsab ot\",\"on line\",\"r andom\",\"Ġren amed\",\"ra red\",\"K A\",\"d ead\",\"Ã© t\",\"ĠAss istance\",\"Ġse af\",\"++++ ++++\",\"Ġse ldom\",\"ĠWeb b\",\"Ġbo olean\",\"u let\",\"Ġref rain\",\"ĠDI Y\",\"ru le\",\"Ġshut ting\",\"Ġutil izing\",\"load ing\",\"ĠPar am\",\"co al\",\"oot er\",\"Ġattract ing\",\"ĠD ol\",\"Ġher s\",\"ag netic\",\"ĠRe ach\",\"im o\",\"Ġdisc arded\",\"ĠP ip\",\"01 5\",\"Ã¼ r\",\"Ġm ug\",\"Im agine\",\"C OL\",\"Ġcurs ed\",\"ĠSh ows\",\"ĠCurt is\",\"ĠSach s\",\"spe aking\",\"ĠV ista\",\"ĠFram ework\",\"ong o\",\"Ġsub reddit\",\"Ġcr us\",\"ĠO val\",\"R ow\",\"g rowing\",\"Ġinstall ment\",\"Ġgl ac\",\"ĠAdv ance\",\"EC K\",\"ĠLGBT Q\",\"LE Y\",\"Ġac et\",\"Ġsuccess ive\",\"ĠNic ole\",\"Ġ19 57\",\"Qu ote\",\"Ġcircumst ance\",\"ack ets\",\"Ġ14 2\",\"ort ium\",\"Ġguess ed\",\"ĠFr ame\",\"Ġperpet rators\",\"ĠAv iation\",\"ĠBen ch\",\"Ġhand c\",\"A p\",\"Ġ19 56\",\"25 9\",\"r and\",\"Net Message\",\"d in\",\"urt les\",\"h ig\",\"ĠV III\",\"ff iti\",\"ĠSw ords\",\"b ial\",\"Ġkidn apping\",\"dev ice\",\"Ġb arn\",\"ĠEl i\",\"auc as\",\"S end\",\"Con structed\",\"ĠÂ ½\",\"Ġneed les\",\"Ġad vertisements\",\"Ġv ou\",\"Ġexhib ited\",\"ĠFort ress\",\"As k\",\"B erry\",\"TY PE\",\"Ġcan cers\",\"ump ing\",\"ĠTerrit ory\",\"Ġpr ud\",\"Ġn as\",\"Ġathe ist\",\"Ġbal ances\",\"ãģ Ł\",\"ĠSh awn\",\"& &\",\"Ġland sc\",\"ĠR GB\",\"Ġpet ty\",\"Ġex cellence\",\"Ġtransl ations\",\"Ġpar cel\",\"ĠChe v\",\"E ast\",\"ĠOut put\",\"im i\",\"Ġamb ient\",\"ĠTh reat\",\"Ġvill ains\",\"Ġ5 50\",\"IC A\",\"Ġtall er\",\"Ġle aking\",\"c up\",\"Ġpol ish\",\"Ġinfect ious\",\"ĠK C\",\"Ġ@ @\",\"back ground\",\"Ġbureaucr acy\",\"ĠS ai\",\"un less\",\"it ious\",\"ĠSky pe\",\"At l\",\"ID ENT\",\"00 8\",\"Ġhyp ocr\",\"Ġpit chers\",\"Ġguess ing\",\"ĠF INAL\",\"Bet ween\",\"Ġvill agers\",\"Ġ25 2\",\"f ashion\",\"ĠTun is\",\"Be h\",\"ĠEx c\",\"ĠM ID\",\"28 8\",\"ĠHas kell\",\"19 6\",\"ĠN OR\",\"Ġspec s\",\"Ġinv ari\",\"Ġgl ut\",\"ĠC ars\",\"Ġimp ulse\",\"Ġhon ors\",\"g el\",\"Ġjurisd ictions\",\"ĠBund le\",\"ul as\",\"Calif ornia\",\"ĠIncre ase\",\"Ġp ear\",\"Ġsing les\",\"Ġc ues\",\"Ġunder went\",\"ĠW S\",\"Ġexagger ated\",\"Ġdub ious\",\"Ġfl ashing\",\"L OG\",\") ].\",\"J ournal\",\"t g\",\"V an\",\"ĠI stanbul\",\"ĠIn sp\",\"ĠFrank en\",\"D raw\",\"Ġsad ness\",\"Ġiron ic\",\"ĠF ry\",\"x c\",\"Ġ16 4\",\"is ch\",\"W ay\",\"ĠProtest ant\",\"h orn\",\"Ġun aff\",\"ĠV iv\",\"ill as\",\"ĠProduct ions\",\"ĠH ogan\",\"Ġper imeter\",\"ĠS isters\",\"Ġspont aneous\",\"Ġdown side\",\"Ġdescend ants\",\"Ġor n\",\"w orm\",\"Japan ese\",\"Ġ19 55\",\"Ġ15 1\",\"ĠDo ing\",\"els en\",\"umb les\",\"Ġrad ically\",\"ĠDr um\",\"ĠB ach\",\"Ġli abilities\",\"ĠO B\",\"ĠElement ary\",\"Ġmem e\",\"yn es\",\"Ġfinger print\",\"ĠGr ab\",\"Ġundert ake\",\"Mem bers\",\"ĠRead er\",\"ĠSim s\",\"g od\",\"Ġhypot hetical\",\"s cient\",\"ĠA J\",\"Ġchar ism\",\"Ġad missions\",\"ĠMiss ile\",\"tr ade\",\"Ġexerc ising\",\"ĠBack ground\",\"W ritten\",\"Ġvoc als\",\"whe ther\",\"Ġv i\",\"ĠW inner\",\"Ġl itter\",\"ĠSh ooting\",\"ST EM\",\"ãĤ ¡\",\"ĠA FL\",\"Ġvari ability\",\"Ġe ats\",\"ĠD PS\",\"b row\",\"Ġeleph ants\",\"Ġstr at\",\"Ġ Å\",\"Ġsett lers\",\"Matt hew\",\"Ġin advert\",\"H I\",\"ĠIM F\",\"ĠGo al\",\"Ġnerv es\",\"John son\",\"ey e\",\"ablish ment\",\"Th ursday\",\"BIL ITY\",\"H ad\",\"am oto\",\"het amine\",\"ep s\",\"Ġmit ochond\",\"Ġcomp ressed\",\"ĠTre vor\",\"ĠAnim als\",\"T ool\",\"L ock\",\"Ġtwe ak\",\"Ġpin ch\",\"Ġcancell ation\",\"P ot\",\"Ġfoc al\",\"ĠAst ron\",\"17 3\",\"ĠA SC\",\"ĠO THER\",\"umn i\",\"Ġdem ise\",\"d l\",\"Ù ħ\",\"Sem itism\",\"Ġcr acking\",\"Ġcollabor ative\",\"Ġexpl ores\",\"s ql\",\"Ġher bs\",\"Ġconfig urations\",\"m is\",\"ĠRes ult\",\"ace y\",\"ĠSm oke\",\"Ġsan ct\",\"el ia\",\"Ġdeg ener\",\"Ġdeep est\",\"Ġscream ed\",\"Ġn ap\",\"Soft ware\",\"ĠST AR\",\"E F\",\"ĠX in\",\"spons ored\",\"mans hip\",\"23 3\",\"Ġprim aries\",\"Ġfilter ing\",\"Ġas semble\",\"m il\",\"ĠMy ers\",\"b ows\",\"Ġpun ched\",\"M ic\",\"Ġinnov ations\",\"Ġfun c\",\"and o\",\"Ġfr acking\",\"ĠV ul\",\"Ð¾ Ð\",\"osh op\",\"ĠIm mun\",\"Ġsett ling\",\"Ġadolesc ents\",\"Ġreb uilding\",\"Ġtransform ing\",\"Ġpar ole\",\"Ġhar bor\",\"Ġbook ing\",\"ot ional\",\"onge vity\",\"ĠY o\",\"b ug\",\"Ġemer ges\",\"ĠMethod s\",\"ĠCh u\",\"P res\",\"ĠDun geons\",\"Ġtra iling\",\"ĠR um\",\"ĠH ugh\",\"å¤ ©\",\"ĠE ra\",\"ĠBatt les\",\"Res ults\",\"ĠTr ading\",\"Ġvers a\",\"c ss\",\"ax ies\",\"he et\",\"Ġgre ed\",\"19 89\",\"Ġgard ens\",\"Ġconting ent\",\"P ark\",\"ĠLeaf s\",\"h ook\",\"ro be\",\"Ġdiplom acy\",\"ĠF uel\",\"ĠInv asion\",\"Ġupgr ading\",\"M ale\",\"Ġe lic\",\"Ġrelent less\",\"ĠCo venant\",\"ap esh\",\"ĠT rop\",\"T y\",\"pro duction\",\"art y\",\"Ġpun ches\",\"ak o\",\"cyclop edia\",\"ĠR abbit\",\"ĠHD MI\",\"Ġ14 1\",\"Ġf oil\",\"Item Image\",\"ĠF G\",\"Ġimplement ations\",\"ĠP om\",\"ixt ures\",\"Ġaw ait\",\"Ġ3 30\",\"am us\",\"Ġumb rella\",\"Ġfore see\",\"se par\",\"Ġcircum cision\",\"Ġperipher al\",\"S ay\",\"ĠExper t\",\"In c\",\"Ġwithd rew\",\"ĠAnd ers\",\"f ried\",\"Ġradio active\",\"ĠOp ening\",\"Ġboard ing\",\"ĠN D\",\"Ġover throw\",\"Act iv\",\"W P\",\"ĠAct s\",\"× Ļ\",\"Ġmot ions\",\"v ic\",\"ĠM ighty\",\"ĠDef ender\",\"a er\",\"Ġthank ful\",\"ĠK illing\",\"ĠBr is\",\"mo il\",\"Ġpredict ing\",\"26 6\",\"ch oice\",\"Ġkill ers\",\"Ġinc ub\",\"ĠChe st\",\"ather ing\",\"Ġpro claimed\",\"fl ower\",\"oss om\",\"umbled ore\",\"ĠCy cling\",\"ĠOccup y\",\"AG ES\",\"P en\",\"ĠY ug\",\"Ġpack aged\",\"Ġheight ened\",\"c ot\",\"st ack\",\"C ond\",\"Ġst amps\",\"m age\",\"Ġpersu aded\",\"Ġens l\",\"ĠCard inal\",\"Ġsol itary\",\"Ġpossess ing\",\"ĠC ork\",\"Ġev id\",\"ĠT ay\",\"Ġbl ues\",\"Ġextrem ism\",\"Ġlun ar\",\"Ġcl own\",\"Te chn\",\"Ġfest ivals\",\"ĠPv P\",\"ĠL ar\",\"Ġconsequ ently\",\"p resent\",\"Ġsom eday\",\"ç İĭ\",\"ĠMet eor\",\"Ġtour ing\",\"c ulture\",\"Ġbe aches\",\"S hip\",\"c ause\",\"ĠFl ood\",\"ãĥ ¯\",\"Ġpur ity\",\"th ose\",\"Ġem ission\",\"b olt\",\"Ġch ord\",\"ĠScript ure\",\"L u\",\"Ġ$ {\",\"cre ated\",\"Other s\",\"25 8\",\"Ġelement al\",\"Ġannoy ed\",\"ĠA E\",\"d an\",\"ĠS ag\",\"Res earchers\",\"Ġfair y\",\"âĢĵ âĢĵ\",\"======== ====\",\"Sm art\",\"GG GG\",\"Ġskelet ons\",\"Ġpup ils\",\"link ed\",\"Ġur gency\",\"en abled\",\"ĠF uck\",\"Ġcoun cill\",\"r ab\",\"U AL\",\"T I\",\"Ġlif es\",\"Ġconf essed\",\"B ug\",\"Ġharm on\",\"ĠCON FIG\",\"ĠNe utral\",\"D ouble\",\"Ġst aple\",\"ĠSH A\",\"Brit ish\",\"ĠSN P\",\"AT OR\",\"oc o\",\"Ġswing ing\",\"ge x\",\"ole on\",\"pl ain\",\"ĠMiss ing\",\"ĠTro phy\",\"v ari\",\"ran ch\",\"Ġ3 01\",\"4 40\",\"00000000 00000000\",\"Ġrest oring\",\"Ġha ul\",\"uc ing\",\"ner g\",\"Ġfut ures\",\"Ġstrateg ist\",\"quest ion\",\"Ġlater al\",\"ĠB ard\",\"Ġs or\",\"ĠRhod es\",\"ĠD owntown\",\"????? -\",\"ĠL it\",\"ĠB ened\",\"Ġco il\",\"st reet\",\"ĠPort al\",\"FI LE\",\"ĠG ru\",\"* ,\",\"23 1\",\"ne um\",\"Ġsuck ed\",\"Ġr apper\",\"Ġtend encies\",\"ĠLaure n\",\"cell aneous\",\"26 7\",\"Ġbrow se\",\"Ġover c\",\"head er\",\"o ise\",\"Ġbe et\",\"ĠG le\",\"St ay\",\"Ġm um\",\"Ġtyp ed\",\"Ġdiscount s\",\"T alk\",\"ĠO g\",\"ex isting\",\"ĠS ell\",\"u ph\",\"C I\",\"ĠAust rian\",\"ĠW arm\",\"Ġdismiss al\",\"Ġaver ages\",\"c amera\",\"Ġalleg iance\",\"L AN\",\"=\\\" #\",\"Ġcomment ators\",\"ĠSet ting\",\"ĠMid west\",\"Ġpharm ac\",\"ĠEX P\",\"Ġstain less\",\"Ch icago\",\"Ġt an\",\"24 4\",\"Ġcountry side\",\"ĠV ac\",\"29 5\",\"Ġpin ned\",\"Ġcr ises\",\"Ġstandard ized\",\"T ask\",\"ĠJ ail\",\"ĠD ocker\",\"col ored\",\"f orth\",\"\\\" },\",\"Ġpat rons\",\"Ġsp ice\",\"Ġm ourn\",\"ĠM ood\",\"Ġlaund ry\",\"Ġequ ip\",\"ĠM ole\",\"y ll\",\"ĠTH C\",\"n ation\",\"ĠSher lock\",\"Ġiss u\",\"ĠK re\",\"ĠAmeric as\",\"ĠA AA\",\"Ġsystem atically\",\"Ġcont ra\",\"ĠS ally\",\"Ġrational e\",\"Ġcar riage\",\"Ġpe aks\",\"Ġcontrad iction\",\"ens ation\",\"ĠFail ure\",\"Ġpro ps\",\"Ġnames pace\",\"Ġc ove\",\"field s\",\"ãĤ ĭ\",\"Ġw ool\",\"ĠC atch\",\"Ġpresum ed\",\"ĠD iana\",\"r agon\",\"ig i\",\"Ġh amm\",\"Ġst unt\",\"ĠG UI\",\"ĠObserv atory\",\"ĠSh ore\",\"Ġsmell s\",\"ann ah\",\"Ġcock pit\",\"ĠD uterte\",\"8 50\",\"Ġopp ressed\",\"bre aker\",\"ĠCont ribut\",\"ĠPer u\",\"ĠMons anto\",\"ĠAtt empt\",\"Ġcommand ing\",\"Ġfr idge\",\"ĠR in\",\"ĠChe ss\",\"ual ity\",\"Ġo l\",\"Republic an\",\"ĠGl ory\",\"ĠW IN\",\".... ...\",\"ag ent\",\"read ing\",\"Ġin h\",\"J ones\",\"Ġcl icks\",\"al an\",\"Ġ[ ];\",\"ĠMaj esty\",\"ĠC ed\",\"op us\",\"ate l\",\"Ã ª\",\"AR C\",\"ĠEc uador\",\"ãĥ ł\",\"ĠK uro\",\"Ġritual s\",\"Ġcapt ive\",\"Ġoun ce\",\"Ġdisag reement\",\"Ġsl og\",\"f uel\",\"P et\",\"M ail\",\"Ġexerc ised\",\"Ġsol ic\",\"Ġrain fall\",\"Ġdev otion\",\"ĠAss essment\",\"Ġrob otic\",\"opt ions\",\"ĠR P\",\"ĠFam ilies\",\"ĠFl ames\",\"Ġassign ments\",\"00 7\",\"aked own\",\"Ġvoc abulary\",\"Re illy\",\"Ġc aval\",\"g ars\",\"Ġsupp ressed\",\"ĠS ET\",\"ĠJohn s\",\"Ġwar p\",\"bro ken\",\"Ġstat ues\",\"Ġadvoc ated\",\"Ġ2 75\",\"Ġper il\",\"om orph\",\"ĠF emin\",\"per fect\",\"Ġh atch\",\"L ib\",\"5 12\",\"Ġlif elong\",\"3 13\",\"Ġche eks\",\"Ġnum bered\",\"ĠM ug\",\"B ody\",\"ra vel\",\"We ight\",\"ĠJ ak\",\"ĠHe ath\",\"Ġkiss ing\",\"ĠJ UST\",\"Ġw aving\",\"u pload\",\"Ġins ider\",\"ĠPro gressive\",\"ĠFil ter\",\"tt a\",\"ĠBe am\",\"Ġviol ently\",\"ip ation\",\"Ġskept icism\",\"Ġ19 18\",\"ĠAnn ie\",\"ĠS I\",\"Ġgen etics\",\"Ġon board\",\"at l\",\"ĠFried man\",\"ĠB ri\",\"cept ive\",\"Ġpir ate\",\"ĠRep orter\",\"27 8\",\"Ġmyth ology\",\"Ġe clipse\",\"Ġsk ins\",\"Ġgly ph\",\"ing ham\",\"F iles\",\"C our\",\"w omen\",\"Ġreg imes\",\"Ġphotograp hed\",\"K at\",\"ĠMA X\",\"Offic ials\",\"Ġunexpected ly\",\"Ġimpress ions\",\"F ront\",\";;;; ;;;;\",\"Ġsuprem acy\",\"Ġs ang\",\"Ġaggrav ated\",\"Ġabrupt ly\",\"ĠS ector\",\"Ġexc uses\",\"Ġcost ing\",\"ide press\",\"St ack\",\"ĠR NA\",\"ob il\",\"Ġghost s\",\"ld on\",\"at ibility\",\"Top ics\",\"Ġreim burse\",\"ĠH M\",\"ĠDe g\",\"Ġth ief\",\"y et\",\"ogen esis\",\"le aning\",\"ĠK ol\",\"ĠB asketball\",\"Ġf i\",\"ĠSee ing\",\"Ġrecy cling\",\"Ġ[ -\",\"Cong ress\",\"Ġlect ures\",\"P sy\",\"Ġne p\",\"Ġm aid\",\"Ġori ented\",\"A X\",\"Ġrespect ful\",\"re ne\",\"fl ush\",\"ĠUn loaded\",\"re quest\",\"gr id\",\"ĠAltern atively\",\"ĠHug o\",\"Ġdec ree\",\"ĠBuddh ism\",\"and um\",\"And roid\",\"ĠCong o\",\"ĠJoy ce\",\"Ġacknowled ging\",\"hes ive\",\"ĠTom orrow\",\"ĠH iro\",\"th ren\",\"ĠM aced\",\"Ġho ax\",\"ĠIncre ased\",\"ĠPr adesh\",\"W ild\",\"____ __\",\"16 1\",\"Ġa unt\",\"Ġdistribut ing\",\"ĠT ucker\",\"ĠSS L\",\"ĠW olves\",\"B uilding\",\"ou lt\",\"ĠLu o\",\"ĠY as\",\"ĠSp ir\",\"ĠSh ape\",\"ĠCamb od\",\"ĠIP v\",\"Ġm l\",\"Ġext rad\",\"39 0\",\"ĠPenn y\",\"d ream\",\"Ġstation ed\",\"opt ional\",\"ew orthy\",\". </\",\"Ġundert aking\",\"Ġchick ens\",\"Ġstimul i\",\"ĠEl se\",\"ig ators\",\"ĠBegin ning\",\"ct ory\",\"Ġprep ares\",\"Ġdel ta\",\"Ġvic inity\",\"t ool\",\"Ġworks hops\",\"M Hz\",\"Ġaccus ation\",\"Ġhist ories\",\"rop olis\",\"ĠChurch ill\",\"Ġne on\",\"Ġb aff\",\"d ies\",\"may be\",\"Ġè£ı è¦ļéĨĴ\",\"Ġsympt om\",\"EC H\",\"ĠMan uel\",\"Ġban ana\",\"ĠH B\",\"Ġ ****\",\"ĠKore ans\",\"c oll\",\"F B\",\"Ġpr aying\",\"ĠCann ot\",\"ĠM ile\",\"Ġembr acing\",\"ĠSil k\",\"39 3\",\"ot ers\",\"F D\",\"Ġday light\",\"al ias\",\"ĠBrig ade\",\"ĠHann ah\",\"Ġcler gy\",\"Ġs outheast\",\"Ġalcohol ic\",\"Ġpropos es\",\"liv ion\",\"Ġcalcul ating\",\"Ġstim ulate\",\"Ġspl itting\",\"e ight\",\"ĠInd y\",\"pl ays\",\"ĠP ik\",\"Ġdom est\",\"Ġforg iveness\",\"ĠR ings\",\"pat ient\",\"kins on\",\"M ont\",\"ig ible\",\"; \\\"\",\"Ġperiod ically\",\"amm ad\",\"ĠBr itt\",\"p ard\",\"Ġarbit ration\",\"ĠSchne ider\",\"ĠCorpor ate\",\"ĠMay a\",\"Ġsn akes\",\"a um\",\"Ġbl asted\",\"Ġmyster ies\",\"Ġrev ive\",\"oc amp\",\"ĠD odge\",\"ĠOper a\",\"27 9\",\"Ġor phan\",\"Ġspec ifies\",\"ĠM ets\",\"D uration\",\"H en\",\"Ġfire works\",\"Ġprosec ute\",\"ĠTill erson\",\"d p\",\"us age\",\"l iness\",\"ĠDeb ian\",\"Ġ2 24\",\"ris es\",\"ĠIn fect\",\"at ra\",\"ĠR R\",\"ĠL or\",\"d iff\",\"ĠCharl eston\",\"Ġac oustic\",\"Ġam use\",\"3 30\",\"Ġc er\",\"ĠT ac\",\"Ġ[ +\",\"Ġcard iac\",\"ĠRestaur ant\",\"er gy\",\"Ġf uzz\",\"Ġbit es\",\"Ġhazard ous\",\"Ġbr ighter\",\"r ans\",\"ĠStephan ie\",\"ext ra\",\"RE T\",\"ĠChrist ine\",\"ĠS ue\",\"stat ement\",\"Ġbol ster\",\"Ġant it\",\"Rad io\",\"B IT\",\"ãĤ °\",\"Ġvis ions\",\"ĠCon cept\",\"Ġin line\",\"ĠPhilos ophy\",\"is ans\",\"ĠIr ving\",\"Ã £\",\"t aking\",\"Ġincons ist\",\"ĠKum ar\",\"Ġl ig\",\"ĠSch umer\",\"ĠReg ulations\",\"ĠH z\",\"th ro\",\"ĠV oldemort\",\"ĠM ED\",\"ĠFreder ick\",\"P ad\",\"22 1\",\"Ġalleg ing\",\"ĠCommun ication\",\"Ġ16 7\",\"Ġforecast s\",\"Ġsp iders\",\"Or gan\",\"ĠParticip ants\",\"ĠO ps\",\"des ign\",\"Cl ose\",\"Ġfact o\",\"Ġbom bers\",\"res istant\",\"ateg ories\",\"S chool\",\"Ġhom ework\",\"Ġcor ro\",\"T uesday\",\"ĠBrend an\",\"ĠM X\",\"ĠT S\",\"ĠSt ri\",\"Ġstake holders\",\"ĠMillenn ium\",\"Ġtransfer ring\",\"J ud\",\"Ġt ac\",\"Ġ16 00\",\"ĠSD K\",\"r b\",\"Ġinterpret ations\",\"ĠS G\",\"Ġup stairs\",\"ĠHar vest\",\"Ġvag ina\",\"Ġing est\",\"x f\",\"ĠOr ion\",\"ĠJoe y\",\"Ġsand wic\",\"Ġimm ortal\",\"Ġfl ipped\",\"ort ex\",\"threat ening\",\"Ġsn iper\",\"Ġconver ts\",\"Ġinstall ations\",\"ĠBul gar\",\"ors che\",\"m ails\",\"Ġl ure\",\"Ġnarrow ly\",\"Ġgren ade\",\"ĠG ing\",\"Ġunder wear\",\"------------ --\",\"Ġch ased\",\"ĠV AL\",\"Ġparent ing\",\"ĠH amb\",\"ĠBl az\",\"Ġanarch ist\",\"ĠMed ian\",\"ĠProgram s\",\"Î ½\",\"Ġob j\",\"ĠN okia\",\"orm an\",\"an qu\",\"at ism\",\"op a\",\"Ġfulf illing\",\"Ġpupp y\",\"Ġent it\",\"ĠSebast ian\",\"Ġshoot ers\",\"Ġric her\",\"è ¡\",\"Ġtempt ed\",\"ĠAT T\",\"ĠC V\",\"Ġto re\",\"Res ource\",\"ĠDevil s\",\"40 8\",\"in ational\",\"Ġass urance\",\"ĠDar ren\",\"Ġwh ichever\",\"pos ure\",\"Ġf ury\",\"St ock\",\"Ġunivers ally\",\"resp onse\",\"Ġo ak\",\"Ġwork load\",\"ĠCor ner\",\"ee le\",\"\\\" ...\",\"Ġdepri ved\",\"k owski\",\"Ġcast s\",\"Ġaffili ation\",\"ĠA ch\",\"ĠAs ked\",\"at he\",\"Ġl act\",\"ĠTh u\",\"r m\",\"Ġair lines\",\"Ġnot ions\",\"Form at\",\"ĠF AA\",\"ãĥ Ĭ\",\"dri ver\",\"Ġtrans cend\",\"S ettings\",\"ĠPro secut\",\"Ġsp inal\",\"Ġdefault s\",\"F K\",\"Ġpref ers\",\"rend ered\",\"th us\",\"fil m\",\"Ġt iger\",\"ĠSp icer\",\"rec ogn\",\"ĠRug by\",\"Net work\",\"Ġp ity\",\"Ġcomp artment\",\"c asters\",\"ĠMon roe\",\"Ġ7 20\",\"Ġcorrect ions\",\"Ġdop amine\",\"ĠA Z\",\"C ut\",\"Ġro omm\",\"Ġspec ulate\",\"H ash\",\"Ġrestrict ive\",\"11 11\",\"red ible\",\"on el\",\"Ġramp ant\",\"re ported\",\"ĠSu ite\",\"ĠMin imum\",\"al ys\",\"az ard\",\"lo op\",\"Ġl ent\",\"sh a\",\"Ġv andal\",\"men u\",\"ĠBoe hner\",\"Ġnarr atives\",\"Ġauthent icity\",\"26 9\",\"an ic\",\"d uty\",\"28 5\",\"Ġthank ed\",\"Ġbetray ed\",\"l ift\",\"Ġsouth west\",\"ĠDex ter\",\"ĠB od\",\"Ġkey words\",\"A verage\",\"D IS\",\"Ġethnic ity\",\"! ),\",\"ĠNational s\",\"á ¹\",\"ĠT ah\",\"iox id\",\"Ġwid get\",\"Ġpast a\",\"Ġbill ing\",\"Ġtr ilogy\",\"ĠL ines\",\"Ġsn iff\",\"Ġnep hew\",\"L ate\",\"Ġprinc ip\",\"ĠLo op\",\"ĠMarx ist\",\"Ġdiss olved\",\"Ġcontext s\",\"ĠAm ount\",\"ĠSp ike\",\"Ġtot als\",\"Ġorgan izer\",\"Ġup rising\",\"s hips\",\"Y Y\",\"ĠNort heast\",\"m oney\",\"grad ation\",\"Ġgoal keeper\",\"ĠH ear\",\"Ġste ak\",\"ĠBuzz Feed\",\"Ġsole mn\",\"ĠSc and\",\"Ġpo pping\",\"Ġad here\",\"ĠAl leg\",\"by te\",\"ĠW olver\",\"Ġun in\",\"Ġrec ol\",\"it ud\",\"Ġmim ic\",\"ib us\",\"Ġpredict s\",\"ĠKee per\",\"i ating\",\"Ġde ception\",\"Ġlear nt\",\"Ġdi ary\",\"Ġcond itional\",\"Ġre lic\",\"Ġinv oke\",\"ien ced\",\"å Ī\",\"ĠP ont\",\"Ġcell phone\",\"Ġspeed ing\",\"Ġtack ling\",\"Ġn ude\",\"op ened\",\"ĠMan afort\",\"Ġ19 52\",\"Ġmaj ors\",\"ĠSil ence\",\"Ġlog istics\",\"Ġweight ed\",\"ĠPsych iat\",\"\\\": [\\\"\",\"Ġsick ness\",\"Ġdivid ends\",\"z on\",\"Re lease\",\"ĠKe ys\",\"ĠI ch\",\"Ġen z\",\"ĠF ernand\",\"ĠÎ ±\",\"Ġmean ings\",\"Ġp enny\",\"Ġst ern\",\"Ġl ar\",\"ĠPub lished\",\"Ġback drop\",\"K im\",\"ĠSy nt\",\"Ġdeb uted\",\"w m\",\"ĠIs le\",\"Ġregul ating\",\"ott i\",\"ĠSch olars\",\"ices ter\",\"ĠChe f\",\"Ġpop s\",\"ĠLaun cher\",\"ĠVar ious\",\"Ġcomment ing\",\"os lav\",\"enz ie\",\"Ġrival ry\",\"â Ĥ¬\",\"Re ally\",\"Ġor c\",\"Ġbe an\",\"ĠJud y\",\"Not ice\",\"ĠB ike\",\"? ]\",\"Ġrent ed\",\"st en\",\"Ġfore front\",\"ĠBald win\",\"Ġyield ed\",\"t ails\",\"Pr ime\",\"ĠS ources\",\"ic ator\",\"Se an\",\"Ġmarch ing\",\"Out put\",\"ĠJ ungle\",\"Ġres ide\",\"zz le\",\"ĠAndrew s\",\"Ġtor que\",\"Bas ic\",\"Act ually\",\"st rap\",\"p enter\",\"Ġexam s\",\"ĠY a\",\"Ġ15 9\",\"ĠDec ision\",\"Ġr ansom\",\"ete enth\",\"ens ing\",\"2 13\",\"Ġsun set\",\"40 4\",\"ĠRap id\",\"ĠHe in\",\"ĠAb original\",\"Ġorgan ism\",\"ĠS ever\",\"Ġcl a\",\"aj i\",\"Sim ple\",\"ĠFl avor\",\"ĠE val\",\"pr us\",\"Ġch orus\",\"D AY\",\"Ġden ounced\",\"Ġbi ography\",\"ĠTurn bull\",\"Rec ent\",\"N ormal\",\"lect ions\",\"W ord\",\"Ġf erry\",\"ĠWag ner\",\"h om\",\"Un it\",\"Ġsuper market\",\"ĠS ith\",\"Ġnomine es\",\"Ġdictators hip\",\"idd ler\",\"Ġannoun ces\",\"ĠThe m\",\"ĠNept une\",\"Ġde ity\",\"ĠY i\",\"Ġmon arch\",\"AR R\",\"Ġinv aded\",\"ĠH ok\",\"unt ary\",\"C ertain\",\"eg a\",\"Ġk idding\",\"ĠReg ulation\",\"Ġtr ay\",\"Ġphotograp hers\",\"ĠArc ane\",\"Ġdis charged\",\"Ġevangel ical\",\"Ġinter change\",\"Ġfilm maker\",\"ĠEnd less\",\"Ġ29 0\",\"ĠSalv ador\",\"AS Y\",\"ĠSign al\",\"Ġwr ath\",\"â ľ\",\"l ot\",\"' /\",\"Ġproject ile\",\"Ġemploy ing\",\"ĠInter face\",\"19 1\",\"atell ite\",\"ĠR ath\",\"pack age\",\"Ġindic ations\",\"J ason\",\"Ġarg s\",\"ĠG Hz\",\"Ġt ilt\",\"n ants\",\"w on\",\"ãĤ µ\",\"red d\",\"res cent\",\"ĠCal endar\",\"Ġmod ular\",\"Ġassist ing\",\"Ġred eem\",\"ĠBe an\",\"Ġwor sh\",\"Ġdecentral ized\",\") ...\",\"37 7\",\"Ġarr ays\",\"Ġaccomplish ments\",\"Î ¿\",\"d ot\",\"Ġmut ually\",\"Ġob struct\",\"Ġmis represent\",\"ore st\",\"ion ic\",\"ru ce\",\"% ;\",\"Ġknow ingly\",\"port ing\",\"in ently\",\"A ri\",\"ĠSch ultz\",\"D a\",\"ĠC ere\",\"Ġob solete\",\"ħ ĭ\",\"g ive\",\"Ġb ait\",\"Ġen larg\",\"Ne ill\",\"Ġ19 33\",\"Ġrecons ider\",\"ĠSerge ant\",\"ĠDian e\",\"ĠC ogn\",\"ĠI con\",\"P osition\",\"Ġf ost\",\"Ġstir ring\",\"se ven\",\"ĠSpace X\",\"ugg ets\",\"Ġmed d\",\"G al\",\"ĠS ister\",\"B oy\",\"Ġtrigger ing\",\"T aking\",\"Ġscream s\",\"Ġca usal\",\"Ġaw aken\",\"Ar m\",\"29 7\",\"Ġdisp atched\",\"ĠF ALSE\",\"Ġorgan izational\",\"ĠT ong\",\"Ġdile mma\",\"d emon\",\"S pl\",\"Ġhook s\",\"ud ing\",\"Ġvalid ate\",\"Ġpot ion\",\"Ġcl aw\",\"Ġburg l\",\"Ġqu ir\",\"AC A\",\"ĠBren nan\",\"Ġdur ability\",\"Ġbomb ings\",\"ĠWind ow\",\"Ġculp rit\",\"3 25\",\"There fore\",\"umb ered\",\"per formance\",\"w arts\",\"Ġen forcing\",\"ĠBl ow\",\"Ġre print\",\"if ax\",\"al pha\",\"Ġsin ister\",\"Ġbur ger\",\"fight ing\",\"Sc ore\",\"ĠSt ones\",\"i em\",\"40 5\",\"che my\",\"Ġvine gar\",\"n om\",\"Ġprev ailing\",\"ĠLat est\",\"Â ¶\",\"Ġb a\",\"ĠWrit er\",\"Ġ17 7\",\"ĠCon way\",\"Ġcollect s\",\"Ġquant itative\",\"Ġhor rors\",\"og ens\",\"ĠSl ov\",\"Ġl ays\",\"h aw\",\"ĠSl ash\",\"Ġnight club\",\"ĠDav ies\",\"Ġbr ide\",\"ĠScar let\",\"y mm\",\"ĠApplic ations\",\"vel ength\",\"Ġrev ival\",\"Ġsoft ly\",\"Ġz oo\",\"ita ire\",\"C ur\",\"Ġelect rom\",\"Ġplant ing\",\"OT O\",\"ĠE lements\",\"Ġsw allow\",\"por ter\",\"Ġlapt ops\",\"Ġpe anut\",\"Ġlobby ists\",\"Î ²\",\"Pan el\",\"ĠJo an\",\"im il\",\"t nc\",\"Ġresist ed\",\"Ġout we\",\"Ġret aining\",\"at ri\",\"Ġpo orer\",\"ĠSyri ans\",\"ĠHam mond\",\"Ġwe ld\",\"ud er\",\"top ic\",\"ĠT T\",\"ric ia\",\"Ġth ieves\",\"L ic\",\"ĠG ust\",\"ĠW ays\",\"are th\",\"24 3\",\"Ġbroad caster\",\"sh ield\",\"ass ium\",\"ub le\",\"Ġairst rikes\",\"on so\",\"Ġped al\",\"Ġcollect ors\",\"ĠV ander\",\"ĠMes a\",\"Ġdict ator\",\"Ġd ir\",\"ent on\",\"c art\",\"sc ore\",\"ad der\",\"C ry\",\"Ġs sh\",\"gg er\",\"Ġdrunk en\",\"ĠG S\",\"ĠSe at\",\"Ġcorner back\",\"Ġsk ipped\",\"ĠRes earchers\",\"ĠAud i\",\"Ref erence\",\"Ġhaun ted\",\"Ã «\",\"ĠClin ic\",\"c z\",\"Ġp s\",\"ĠPal adin\",\"ĠRec ipe\",\"Ġst igma\",\"opp y\",\"Ġmon keys\",\"ĠHaw k\",\"S ad\",\"\\\" />\",\"ĠWorks hop\",\"ĠRet ail\",\"ĠAv atar\",\"6 25\",\"N a\",\"ĠV C\",\"ĠSec ure\",\"M Y\",\"19 88\",\"oss ip\",\"Ġpro state\",\"Ġund en\",\"Ġg amer\",\"ĠCont ents\",\"ĠWar hammer\",\"ĠSent inel\",\"3 10\",\"Ġse gregation\",\"ĠF lex\",\"ĠM AY\",\"Ġdr ills\",\"ĠDrug s\",\"Islam ic\",\"Ġsp ur\",\"Ġca fe\",\"Ġimag inary\",\"Ġgu iding\",\"Ġsw ings\",\"ĠThe me\",\"ob y\",\"Ġn ud\",\"Ġbe gging\",\"Ġstr ongh\",\"Ġreject ing\",\"Ġpedest rians\",\"ĠPro spect\",\"R are\",\"s le\",\"Ġconcess ions\",\"ĠConst itutional\",\"Ġbe ams\",\"Ġfib ers\",\"p oon\",\"Ġinstinct s\",\"pro perty\",\"ĠB IG\",\"Sand ers\",\"im ates\",\"Ġco ating\",\"Ġcorps es\",\"ĠTR UE\",\"check ed\",\"Ġ16 6\",\"A sh\",\"ĠJ S\",\"ĠF iction\",\"Ġcommun al\",\"Ġener getic\",\"oooo oooo\",\"Ġnow adays\",\"IL D\",\"ib o\",\"ĠSU V\",\"R en\",\"Ġdwell ing\",\"Sil ver\",\"Ġt ally\",\"ĠM oving\",\"Ġcow ard\",\"Ġgener als\",\"Ġhorn s\",\"Ġcirc ulated\",\"Ġrob bed\",\"ĠUn limited\",\"Ġharass ed\",\"Ġinhib it\",\"Ġcomp oser\",\"ĠSpot ify\",\"Ġspread s\",\"3 64\",\"Ġsu icidal\",\"Ġno ises\",\"ĠSt ur\",\"Ġs aga\",\"ĠK ag\",\"is o\",\"Ġtheoret ically\",\"M oney\",\"Ġsimilar ity\",\"Ġslic ed\",\"ut ils\",\"ing es\",\"\\\" -\",\"Ġan th\",\"Ġimp ed\",\"Mod ule\",\"Through out\",\"Ġmen us\",\"comm ittee\",\"and i\",\"ob j\",\"in av\",\"f ired\",\"ĠAb dullah\",\"Ġund ead\",\"Ġfont s\",\"H old\",\"EN G\",\"Ġsustain ability\",\"Ġfl ick\",\"Ġr azor\",\"ĠF est\",\"ĠChar acters\",\"Ġword ing\",\"Ġpopul ist\",\"Ġcritic izing\",\"Ġm use\",\"v ine\",\"Ġcard board\",\"Ġkind ly\",\"Ġfr inge\",\"ĠThe ft\",\"icult ural\",\"Ġgovern ors\",\"Ġ ï¿½ï¿½ï¿½ï¿½\",\"Ġ16 3\",\"Ġtime out\",\"ĠA uth\",\"Child ren\",\"A U\",\"Ġred emption\",\"ĠAl ger\",\"Ġ19 14\",\"Ġw aved\",\"Ġastron auts\",\"og rams\",\"Ġsw amp\",\"ĠFinn ish\",\"Ġcand le\",\"Ġton nes\",\"ut m\",\"Ġr ay\",\"Ġsp un\",\"Ġfear ful\",\"art icles\",\"Ġca us\",\"or ically\",\"ĠRequ ires\",\"ĠG ol\",\"Ġpop e\",\"Ġinaug ural\",\"Ġg le\",\"AD A\",\"ĠIS IL\",\"ĠOff ensive\",\"Ġwatch dog\",\"Ġbal con\",\"ent ity\",\"ĠH oo\",\"Ġgall on\",\"AC C\",\"Ġdoub ling\",\"Ġimpl ication\",\"ĠS ight\",\"Ġdoct r\",\"---- ---\",\"Ġ\\\\ \\\\\",\"Ġm alt\",\"R oll\",\"Ġâī ¥\",\"Ġrec ap\",\"add ing\",\"u ces\",\"ĠB end\",\"fig ure\",\"Ġtur key\",\"Ġsoc ietal\",\"ĠT ickets\",\"Ġcommer cially\",\"Ġsp icy\",\"Ġ2 16\",\"ĠR amp\",\"Ġsuperior ity\",\"Ã ¯\",\"ĠTr acker\",\"C arl\",\"ĠC oy\",\"ĠPatri ot\",\"Ġconsult ed\",\"Ġlist ings\",\"Ġsle w\",\"reens hot\",\"ĠG one\",\"Ġ[ ...]\",\"30 9\",\"Ġh ottest\",\"Ø ±\",\"Ġrock y\",\"ĠD iaz\",\"Ġmass age\",\"Ġpar aly\",\"Ġp ony\",\"A z\",\"Ġcart ridge\",\"ĠN Z\",\"Ġsn ack\",\"ĠLam ar\",\"ple ment\",\"ĠLes lie\",\"Ġm ater\",\"Ġsn ipp\",\"24 6\",\"Ġjoint ly\",\"ĠBris bane\",\"ĠiP od\",\"Ġpump ing\",\"Ġgo at\",\"ĠSh aron\",\"eal ing\",\"Ġcor on\",\"Ġan omal\",\"rah im\",\"ĠConnect ion\",\"Ġsculpt ure\",\"Ġsched uling\",\"ĠD addy\",\"at hing\",\"Ġeyeb rows\",\"Ġcur ved\",\"Ġsent iments\",\"Ġdraft ing\",\"D rop\",\"( [\",\"Ġnom inal\",\"ĠLeaders hip\",\"ĠG row\",\"Ġ17 6\",\"Ġconstruct ive\",\"iv ation\",\"Ġcorrupt ed\",\"ger ald\",\"ĠC ros\",\"ĠChe ster\",\"ĠL ap\",\"ãģ ª\",\"OT H\",\"D ATA\",\"Ġal mond\",\"pro bably\",\"I mp\",\"Ġfe ast\",\"ĠWar craft\",\"F lor\",\"Ġcheck point\",\"Ġtrans cription\",\"Ġ20 4\",\"Ġtwe aks\",\"Ġrel ieve\",\"S cience\",\"Ġperform er\",\"Z one\",\"Ġtur moil\",\"ig ated\",\"hib it\",\"ĠC afe\",\"the med\",\"Ġflu or\",\"ben ch\",\"Ġde com\",\"ĠU nt\",\"ĠBar rett\",\"ĠF acts\",\"Ġt asting\",\"ĠPTS D\",\"ĠSe al\",\"ĠJuda ism\",\"ĠDynam ic\",\"ĠC ors\",\"V e\",\"ĠM ing\",\"ĠTrans form\",\"v on\",\"ĠDef enders\",\"ĠTact ical\",\"ĠV on\",\"ĠUn ivers\",\"Ġdist orted\",\"ĠB reath\",\"?' \\\"\",\"Ġag on\",\"ĠDead ly\",\"Ġl an\",\"ĠCy cle\",\"orn ed\",\"Ġrel iably\",\"Ġgl or\",\"ĠMon key\",\"ãĥ ¡\",\"Ġad ren\",\"Ġmicrow ave\",\"ĠAl ban\",\"irc raft\",\"dig it\",\"sm art\",\"ĠD read\",\"Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯ Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯\",\"{ {\",\"ĠRoc hester\",\"Ġsimpl ified\",\"Ġinf licted\",\"Ġtake over\",\"Ġyour selves\",\"ad itional\",\"Ġmus cular\",\"K S\",\"Ġing en\",\"T ax\",\"ĠFe ature\",\"27 7\",\"Ġcru c\",\"Ġcr ate\",\"Ġun identified\",\"Ġacclaim ed\",\"ĠM anga\",\"ĠFr ances\",\"ĠNep al\",\"ĠG erald\",\"ĠKu wait\",\"Ġsl ain\",\"ĠHe b\",\"ĠG oku\",\"ãģ® æ\",\"28 6\",\"M rs\",\"ĠC ody\",\"ĠSan ctuary\",\"01 6\",\"Ġdism ant\",\"Ġdatas et\",\"ĠH ond\",\"b uck\",\"ĠPat terson\",\"Ġpal ette\",\"ĠG D\",\"ic ol\",\"ĠL odge\",\"Ġplanet ary\",\"ak in\",\"ĠRegist ered\",\"ab we\",\"ĠPeters burg\",\"Ġha iled\",\"ĠP iece\",\"S che\",\"ĠDO J\",\"Ġen umer\",\"18 1\",\"ĠObs erver\",\"ĠB old\",\"f ounded\",\"com merce\",\"Ġexplo its\",\"ĠF inding\",\"UR N\",\"ĠS ne\",\"ĠAc id\",\"ay ette\",\"ĠVal ues\",\"Ġdr astic\",\"Ġarchitect ural\",\"Ġ\\\" .\",\"× ķ\",\"ump ed\",\"Ġwra pping\",\"Ġwid ow\",\"ĠSl ayer\",\"l ace\",\"on ce\",\"German y\",\"av oid\",\"Ġtem ples\",\"P AR\",\"Ã ´\",\"ĠLuc ifer\",\"ĠFl ickr\",\"l ov\",\"for ces\",\"Ġsc outing\",\"Ġlou der\",\"tes y\",\"Ġbefore hand\",\"Ä ĵ\",\"ĠNe on\",\"ĠW ol\",\"ĠTyp ically\",\"ĠPolit ico\",\"-+ -+\",\"Ġbuild er\",\"Ġder ive\",\"K ill\",\"Ġp oker\",\"Ġambig uous\",\"Ġlif ts\",\"Ġcy t\",\"Ġrib s\",\"ood le\",\"ĠS ounds\",\"h air\",\"ĠSynd rome\",\"t f\",\"Ġproport ional\",\"u id\",\"Ġper taining\",\"ĠKind le\",\"ĠNeg ro\",\"Ġreiter ated\",\"ĠTon ight\",\"oth s\",\"ĠCorn ell\",\"Ġo wing\",\"Ġ20 8\",\"elf are\",\"oc ating\",\"ĠB irds\",\"Sub scribe\",\"Ġess ays\",\"Ġburd ens\",\"Ġillust rations\",\"ar ious\",\"ER AL\",\"ĠCal cul\",\"Ġx en\",\"ĠLink edIn\",\"ĠJ ung\",\"Ġredes ign\",\"Con nor\",\"29 6\",\"Ġrevers al\",\"ĠAd elaide\",\"ĠL L\",\"Ġs inking\",\"Ġg um\",\"US H\",\"c apt\",\"ĠGr imm\",\"Ġfoot steps\",\"ĠCB D\",\"isp ers\",\"Ġpro se\",\"Wed nesday\",\"ĠM ovies\",\"ed in\",\"Ġoverturn ed\",\"Ġcontent ious\",\"US B\",\"~~~~~~~~ ~~~~~~~~\",\"ĠCo pper\",\"Ġpoint less\",\"N V\",\"val ues\",\"olph in\",\"d ain\",\"Ġdepos ited\",\"ĠG W\",\"Ġpreced ed\",\"ĠCl a\",\"ĠGo lem\",\"ĠN im\",\"ĠÎ ²\",\"ĠEngine ers\",\"m iddle\",\"Ġfl att\",\"oper ative\",\"Ġcouncil s\",\"imb abwe\",\"el in\",\"Ġstress ful\",\"ĠL D\",\"Ġres h\",\"l ake\",\"Ġwheel chair\",\"ĠAltern ative\",\"Ġoptim ize\",\"oper ation\",\"Ġpe ek\",\"Ġones elf\",\"ig il\",\"Ġtrans itions\",\"op athy\",\"bl ank\",\"Ġ16 9\",\"17 1\",\"________________________________ ________________________________\",\"Ġl aundering\",\"En c\",\"ĠD EC\",\"Ġwork outs\",\"Ġsp ikes\",\"Ġdin osaurs\",\"Ġdiscrim inatory\",\"P ool\",\"R ather\",\"38 5\",\"R NA\",\"tes ters\",\"et o\",\"ĠIdent ity\",\"Ġve in\",\"ĠBur ton\",\"Ġarc ade\",\"4 20\",\"Ult imately\",\"ĠSad ly\",\"Ã °\",\"p ill\",\"Ġcub ic\",\"ĠSpect rum\",\"the se\",\"st ates\",\"Ġun official\",\"h awks\",\"ĠEVER Y\",\"Ġrain bow\",\"Ġincarcer ation\",\"and ing\",\"Ġsy ll\",\"ĠEver ton\",\"Ġ17 9\",\"ĠSer bia\",\"Ġ18 9\",\"m eter\",\"ĠMic key\",\"Ġant iqu\",\"Ġfact ual\",\"ne ck\",\"ĠN are\",\"n orm\",\"m ust\",\"Ġhigh ways\",\"Ġgl am\",\"Ġdivid ing\",\"ĠSquad ron\",\"ĠMar tha\",\"Ġbirth s\",\"C over\",\"//////// ////////\",\"ĠW ong\",\"Ph ot\",\"ĠA LS\",\"ri o\",\"ĠNon etheless\",\"ĠL emon\",\"Ġ20 6\",\"ĠE E\",\"Ġderiv ative\",\"ĠWW II\",\"v ote\",\"Ġthere in\",\"Ġsepar ating\",\"44 6\",\"sy nc\",\"ĠStre ets\",\"Ġr att\",\"Ġmunicip ality\",\"ĠShort ly\",\"Ġmon k\",\") ,\\\"\",\"Ġscr ub\",\"Ġoper atives\",\"Ne ither\",\"Pl ace\",\"ĠLim it\",\"F emale\",\"ĠAct or\",\"Char acter\",\"Ġconstit uted\",\"35 7\",\"Ġprotest ed\",\"ĠSt raw\",\"ĠHe ight\",\"ild a\",\"ĠTy ph\",\"Ġflood s\",\"Ġcos metic\",\"W AY\",\"pert ure\",\"up on\",\"t ons\",\"ess ing\",\"ĠP ocket\",\"Ġro oft\",\"ĠC aucas\",\"Ġant idepress\",\"Ġincomp atible\",\"EC D\",\"Ġoper a\",\"ĠCont est\",\"Ġgener ators\",\"l ime\",\"Def ense\",\"19 87\",\"for um\",\"Ġsav age\",\"ĠHung arian\",\"n z\",\"Ġmet allic\",\"Ġex pelled\",\"Ġres idency\",\"Ġdress es\",\"66 6\",\"ĠC lement\",\"f ires\",\"C ategory\",\"Ġge ek\",\"al is\",\"Ġc emetery\",\"educ ated\",\"Ġc rawl\",\"ĠUn able\",\"ĠT yson\",\"ak is\",\"Ġp ardon\",\"ĠW ra\",\"Ġstrengthen ed\",\"ĠF ors\",\"33 5\",\"ĠH C\",\"ĠM ond\",\"Ġvisual s\",\"ĠBeat les\",\"ett lement\",\"Ġ ï\",\"g ro\",\"Ġb ash\",\"Ġpo orest\",\"Ġex cel\",\"Ġaspir ations\",\"ĠM unicip\",\"ens ible\",\"Ġceremon ies\",\"Ġintimid ation\",\"ĠCON TR\",\"be ck\",\"ĠK ap\",\"as u\",\"Ġtradem arks\",\"ĠS ew\",\"ĠComp etition\",\"net work\",\"ĠAr ri\",\"ĠT et\",\"Ro aming\",\"W C\",\"D at\",\"Ġso b\",\"Ġpair ing\",\"Ġoverd ose\",\"SA Y\",\"ab er\",\"Ġrev olt\",\"ĠF ah\",\"act ing\",\"e q\",\"est ation\",\"F ight\",\"ĠMar ks\",\"27 3\",\"Ġ17 8\",\"R aw\",\"ãģ ĭ\",\"34 9\",\"bl ocks\",\"Ġver ge\",\"est ine\",\"ĠPod esta\",\"Ġinv asive\",\"Ġprofound ly\",\"ĠA o\",\"e ach\",\"Ġl est\",\"inter pret\",\"Ġshr inking\",\"Ġerr one\",\"Ġche es\",\"ly s\",\"ĠI vy\",\"ĠDirect ory\",\"Ġhint ed\",\"V ICE\",\"Ġcontact ing\",\"ĠG ent\",\"he i\",\"Ġlabel ing\",\"Ġmerc ury\",\"ĠL ite\",\"Ġexp ires\",\"Ġdest abil\",\"rit is\",\"c u\",\"Ġfeather s\",\"Ġste er\",\"Ġprogram med\",\"ĠV ader\",\"Go ing\",\"ĠE lim\",\"Ġy o\",\"ĠMic he\",\"Ġ20 3\",\"Ġslee ves\",\"Ġb ully\",\"ĠHum ans\",\"36 8\",\"Ġcomp ress\",\"ĠBan ner\",\"AR S\",\"Ġa while\",\"Ġcal ib\",\"Ġspons orship\",\"ĠDiff iculty\",\"ĠP apers\",\"Ġident ifier\",\"} .\",\"Ġy og\",\"ĠSh ia\",\"Ġclean up\",\"Ġvib e\",\"int rodu\",\"im ming\",\"Austral ia\",\"Ġout lines\",\"ĠY outube\",\"tr ain\",\"ĠM akes\",\"Ġde ported\",\"Ġcent r\",\"ĠD ug\",\"ĠB oulder\",\"ĠBuff y\",\"Ġinj unction\",\"ĠHar ley\",\"ĠG roups\",\"ĠD umbledore\",\"ĠCl ara\",\"Ġ\\\" -\",\"Ġsacrific ed\",\"ep h\",\"Sh adow\",\"ib ling\",\"Ġfreel ance\",\"Ġevident ly\",\"ph al\",\"Ġret ains\",\"M ir\",\"Ġfin ite\",\"d ar\",\"ĠC ous\",\"Ġrep aired\",\"Ġperiod ic\",\"Ġchampions hips\",\"Ġaster oid\",\"bl ind\",\"Ġexpress ly\",\"ĠAst ros\",\"Ġsc aled\",\"Ġge ographical\",\"ĠRap ids\",\"En joy\",\"Ġel astic\",\"ĠMoh amed\",\"Mark et\",\"be gin\",\"Ġdisco vers\",\"Ġtele communications\",\"Ġscan ner\",\"Ġen large\",\"Ġsh arks\",\"Ġpsy chedel\",\"ĠRou ge\",\"Ġsnap shot\",\"is ine\",\"X P\",\"Ġpestic ides\",\"ĠL SD\",\"ĠDist ribution\",\"re ally\",\"Ġde gradation\",\"Ġdisgu ise\",\"Ġbi om\",\"ĠEX T\",\"Ġequ ations\",\"Ġhaz ards\",\"ĠComp ared\",\") *\",\"Ġvirt ues\",\"Ġeld ers\",\"Ġenh ancing\",\"ĠAc ross\",\"er os\",\"ang ling\",\"Ġcomb ust\",\"ucc i\",\"Ġconc ussion\",\"Ġcontrace ption\",\"ĠK ang\",\"Ġexpress es\",\"Ġa ux\",\"ĠP ione\",\"Ġexhib its\",\"Deb ug\",\"OT AL\",\"ĠAl ready\",\"ĠWheel er\",\"Ġexp ands\",\"? :\",\"Ġreconc iliation\",\"Ġpir ates\",\"Ġpur se\",\"Ġdiscour age\",\"Ġspect acle\",\"R ank\",\"Ġwra ps\",\"ĠTh ought\",\"Ġimp ending\",\"O pp\",\"ĠAng lo\",\"ĠE UR\",\"Ġscrew ed\",\"ret ched\",\"Ġencour agement\",\"mod els\",\"Ġconf use\",\"mm m\",\"ĠVit amin\",\"âĸĳ âĸĳ\",\"C ru\",\"Ġkn ights\",\"Ġdisc ard\",\"Ġb ishops\",\"ĠW ear\",\"ĠGar rett\",\"k an\",\"ãĥ Ł\",\"Ġmascul ine\",\"cap ital\",\"ĠA us\",\"Ġfat ally\",\"th anks\",\"ĠA U\",\"ĠG ut\",\"12 00\",\"Ġ 00000000\",\"Ġsur rog\",\"ĠBI OS\",\"ra its\",\"ĠWat ts\",\"Ġresur rection\",\"ĠElect oral\",\"ĠT ips\",\"4 000\",\"Ġnut rient\",\"Ġdepict ing\",\"Ġspr ink\",\"Ġm uff\",\"ĠL IM\",\"ĠS ample\",\"ps c\",\"ib i\",\"gener ated\",\"Ġspec imens\",\"Ġdiss atisf\",\"Ġtail ored\",\"Ġhold ings\",\"ĠMonth ly\",\"ĠE at\",\"po ons\",\"Ġne c\",\"ĠC age\",\"ĠLot us\",\"ĠLan tern\",\"Ġfront ier\",\"Ġp ensions\",\"Ġj oked\",\"ĠHard y\",\"=-=- =-=-\",\"r ade\",\"U ID\",\"Ġr ails\",\"Ġem it\",\"Ġsl ate\",\"Ġsm ug\",\"Ġsp it\",\"ĠCall s\",\"ĠJac obs\",\"f eat\",\"ĠU E\",\"Ġrest ruct\",\"Ġregener ation\",\"Ġenerg ies\",\"ĠCon nor\",\"OH N\",\"ĠChe ese\",\"Ġg er\",\"Ġresur rect\",\"man agement\",\"N W\",\"Ġpres ently\",\"ĠBru ins\",\"M ember\",\"ĠM ang\",\"id an\",\"Ġboost ing\",\"w yn\",\"+ .\",\"requ isite\",\"ĠNY PD\",\"ĠMe gan\",\"ĠCond itions\",\"Ġp ics\",\"nes ium\",\"ĠR ash\",\"Ġ17 4\",\"ĠD ucks\",\"Ġemb ro\",\"z u\",\"on ian\",\"rel igious\",\"Ġc raz\",\"ĠAC A\",\"ĠZ ucker\",\"EM A\",\"ĠPro s\",\"We apon\",\"ĠKn ox\",\"ĠAr duino\",\"Ġst ove\",\"Ġheaven s\",\"ĠP urchase\",\"Ġher d\",\"Ġfundra iser\",\"Dig ital\",\"5 000\",\"Ġprop onents\",\"/ âĢĭ\",\"Ġj elly\",\"ĠVis a\",\"Ġmon ks\",\"Ġadvance ment\",\"ĠW er\",\"Ġ18 7\",\"e us\",\"ert ility\",\"Ġfet al\",\"Ġ19 36\",\"L o\",\"Ġout fits\",\"Ġstair case\",\"b omb\",\"Ġcustom ized\",\"cl air\",\"T ree\",\"Ġm apped\",\"ĠConsider ing\",\"ĠTor res\",\"Ġmeth yl\",\"Ġapprox imate\",\"Ġdo om\",\"ĠHans en\",\"Ġc rossover\",\"Ġstand alone\",\"ä ¼\",\"Ġinv ites\",\"Ġgra veyard\",\"Ġh p\",\"Donald Trump\",\"Ġesc ort\",\"G ar\",\"Ġpredec essors\",\"Ġh ay\",\"Ġen zyme\",\"ĠStra ight\",\"vis ors\",\"I ng\",\"ane ously\",\"ĠApp lied\",\"Ġf ec\",\"ĠDur ant\",\"Ġout spoken\",\"or b\",\"Ġz eal\",\"Ġdisgr ace\",\"' ).\",\"ĠChe ng\",\"28 9\",\"ĠRen a\",\"ĠSu icide\",\"29 4\",\"Ġout raged\",\"ĠNew man\",\"ĠN vidia\",\"ĠA ber\",\"ĠB ers\",\"Ġrecre ation\",\"Wind ow\",\"ĠD P\",\"x e\",\"Ġped oph\",\"Ġfall out\",\"ambo o\",\"Ġpresent ations\",\"ĠApp s\",\"Ġh tml\",\"3 45\",\"ĠX XX\",\"Ġrub bing\",\"ĠLe ather\",\"Ġhum idity\",\"se ys\",\"est ablished\",\"ĠUn its\",\"64 6\",\"Ġrespect able\",\"A uto\",\"Ġthri ving\",\"ĠInn ovation\",\"ang s\",\"Ext ra\",\"reg ulation\",\"29 8\",\"p ick\",\"Ex amples\",\"ĠC J\",\"Att ack\",\"Ġdr acon\",\"L T\",\"Ġstick er\",\"re rs\",\"Ġsun ny\",\"I ss\",\"reg ulated\",\"d im\",\"ĠAb stract\",\"Ġhus bands\",\"Off ice\",\"om ination\",\"it ars\",\"AN GE\",\"asc al\",\"ĠK ris\",\"ĠInf antry\",\"Ġm alf\",\"ĠA the\",\"ĠR ally\",\"bal anced\",\"................ ........\",\"OU P\",\"Ġmole cule\",\"met ics\",\"ĠSpl it\",\"ĠInstruct ions\",\"ĠN ights\",\"c ards\",\"Ġt ug\",\"Ġcon e\",\"å Ń\",\"Ġt x\",\"ĠDisc ussion\",\"Ġcatast rophe\",\"pp e\",\"g io\",\"Ġcommun ism\",\"Ġhal ted\",\"ĠGu ant\",\"cle an\",\"ĠSc hed\",\"ĠK anye\",\"Ġw ander\",\"ĠSer iously\",\"Ġ18 8\",\"enn ial\",\"f ollow\",\"product ive\",\"ĠFl ow\",\"ĠS ail\",\"Ġc raw\",\"Ġsim ulations\",\"or u\",\"ang les\",\"ĠN olan\",\"Ġmen stru\",\"4 70\",\"Ġ20 7\",\"aj a\",\"Ġcas ually\",\"board ing\",\"Ġ2 22\",\"ov y\",\"ĠN umbers\",\"um at\",\"O E\",\"28 7\",\"ĠCle mson\",\"Ġcert s\",\"Ġsl id\",\"ĠT ribe\",\"Ġto ast\",\"Ġfort unes\",\"Ġf als\",\"ĠComm ittees\",\"Ġg p\",\"Ġf iery\",\"ĠN ets\",\"ĠAn ime\",\"Pack age\",\"ĠComp are\",\"l aughter\",\"in fect\",\"Ġatroc ities\",\"Ġjust ices\",\"Ġins ults\",\"ĠVern on\",\"Ġsh aken\",\"Ġperson a\",\"est amp\",\"36 7\",\"br ain\",\"Ġexperiment ing\",\"K en\",\"ĠElect ronics\",\"Ġ16 1\",\"dom ain\",\"Ġgraph ical\",\"b ishop\",\"Ġwho pping\",\"ĠEv angel\",\"Ġadvertis ers\",\"ĠSpe ar\",\"Ġb ids\",\"Ġdestro ys\",\"ut z\",\"Ġunders c\",\"ĠAD D\",\"Ġan ts\",\"ĠC um\",\"ipp les\",\"ĠF ill\",\"Ġgl anced\",\"Ġind icted\",\"ĠE ff\",\"Ġmis con\",\"ĠDes ktop\",\"Ġab ide\",\"ãĥ Ģ\",\"ĠI o\",\"ĠC oul\",\"Ġcaps ule\",\"ĠCh rys\",\"M ON\",\"Ġund es\",\"ĠI RA\",\"Ġc itation\",\"Ġdict ate\",\"ĠNet works\",\"ĠConf lict\",\"ĠSt uff\",\"x a\",\"is ec\",\"ĠChem istry\",\"Ġquarter ly\",\"William s\",\"an an\",\"O pt\",\"ĠAlexand ria\",\"out heastern\",\"ĠSpring field\",\"ĠBlack s\",\"Ġge ography\",\"24 2\",\"Ġut most\",\"ĠEx xon\",\"ab outs\",\"E VA\",\"ĠEn able\",\"ĠBar r\",\"Ġdisag reed\",\"ĠCy prus\",\"Ġdement ia\",\"Ġlab s\",\"Ġubiqu itous\",\"ĠLO VE\",\"Ġconsolid ated\",\"s r\",\"Ġcream y\",\"ĠTim ber\",\"Reg ardless\",\"ĠCert ificate\",\"Ġ\\\" ...\",\"ogen ous\",\"Capt ain\",\"Ġinsult ing\",\"ĠSor os\",\"ĠInst r\",\"ĠBulgar ia\",\"bet ter\",\"Ġsuck ing\",\"ĠDavid son\",\"at z\",\"Ġcoll ateral\",\"g if\",\"Ġplag ued\",\"ĠC ancel\",\"ĠGard ner\",\"R B\",\"Ġsix teen\",\"Rem ove\",\"ur istic\",\"c ook\",\"R od\",\"Ġcompr ising\",\"f le\",\") âĢĶ\",\"ĠVik ing\",\"g rowth\",\"agon al\",\"Ġsr f\",\"af ety\",\"m ot\",\"N early\",\"st own\",\"ĠF actor\",\"Ġautom obile\",\"Ġproced ural\",\"m ask\",\"amp ires\",\"Ġdisapp ears\",\"j ab\",\"3 15\",\"Ġ19 51\",\"ne eded\",\"Ġd aring\",\"le ader\",\"Ġp odium\",\"Ġun healthy\",\"Ġm und\",\"Ġpy ramid\",\"oc re\",\"Ġkiss ed\",\"Ġdream ed\",\"ĠFant astic\",\"ĠG ly\",\"å Ĭ\",\"Ġgreat ness\",\"Ġsp ices\",\"Ġmet ropolitan\",\"Ġcomp uls\",\"i ets\",\"101 6\",\"ĠSh am\",\"ĠP yr\",\"fl ies\",\"ĠMid night\",\"Ġswall owed\",\"Ġgen res\",\"ĠL ucky\",\"ĠRew ards\",\"Ġdisp atch\",\"ĠI PA\",\"ĠApp ly\",\"Ġa ven\",\"al ities\",\"3 12\",\"th ings\",\"Ġ( ).\",\"Ġm ates\",\"ĠS z\",\"ĠC OP\",\"ol ate\",\"O FF\",\"Ġre charge\",\"c aps\",\"ĠYork er\",\"ic one\",\"Ġgal axies\",\"ile aks\",\"D ave\",\"ĠP uzz\",\"ĠCelt ic\",\"ĠA FC\",\"27 6\",\"ĠS ons\",\"Ġaffirm ative\",\"H or\",\"Ġtutorial s\",\"ĠC ITY\",\"ĠR osa\",\"ĠExt ension\",\"Ser ies\",\"Ġf ats\",\"Ġr ab\",\"l is\",\"Ġun ic\",\"Ġe ve\",\"ĠSp in\",\"Ġadul thood\",\"ty p\",\"Ġsect arian\",\"Ġcheck out\",\"ĠCy cl\",\"S ingle\",\"Ġmart yr\",\"Ġch illing\",\"88 8\",\"ou fl\",\"Ġ] ;\",\"Ġcongest ion\",\"m k\",\"ĠWhere as\",\"Ġ19 38\",\"ur rencies\",\"er ion\",\"Ġbo ast\",\"ĠPat ients\",\"Ġch ap\",\"ĠB D\",\"real DonaldTrump\",\"Ġexam ines\",\"h ov\",\"Ġstart ling\",\"ĠBab ylon\",\"w id\",\"om ew\",\"br ance\",\"ĠOd yssey\",\"w ig\",\"Ġtor ch\",\"ĠV ox\",\"ĠMo z\",\"ĠT roll\",\"ĠAn s\",\"Similar ly\",\"ĠF ul\",\"00 6\",\"Un less\",\"ĠAl one\",\"st ead\",\"ĠPub lisher\",\"r ights\",\"t u\",\"ĠDoes n\",\"Ġprofession ally\",\"Ġcl o\",\"ic z\",\"Ġste als\",\"Ġ á\",\"19 86\",\"Ġst urdy\",\"ĠJoh ann\",\"Ġmed als\",\"Ġfil ings\",\"ĠFr aser\",\"d one\",\"Ġmult inational\",\"Ġf eder\",\"Ġworth less\",\"Ġp est\",\"Yes terday\",\"ank ind\",\"Ġg ays\",\"Ġb orne\",\"ĠP OS\",\"Pict ure\",\"Ġpercent ages\",\"25 1\",\"r ame\",\"Ġpot ions\",\"AM D\",\"ĠLeban ese\",\"Ġr ang\",\"ĠL SU\",\"ong s\",\"Ġpen insula\",\"ĠCl ause\",\"AL K\",\"oh a\",\"ĠMac Book\",\"Ġunanim ous\",\"Ġl enders\",\"Ġhang s\",\"Ġfranch ises\",\"ore rs\",\"ĠUp dates\",\"Ġisol ate\",\"and ro\",\"S oon\",\"Ġdisrupt ive\",\"ĠSur ve\",\"Ġst itches\",\"ĠSc orp\",\"ĠDomin ion\",\"Ġsupp lying\",\"Ar g\",\"Ġtur ret\",\"ĠL uk\",\"Ġbr ackets\",\"* )\",\"ĠRevolution ary\",\"ĠHon est\",\"Ġnot icing\",\"ĠSh annon\",\"Ġafford ed\",\"Ġth a\",\"ĠJan et\",\"! --\",\"ĠNare ndra\",\"ĠPl ot\",\"H ol\",\"se ver\",\"e enth\",\"Ġobst ruction\",\"Ġ10 24\",\"st aff\",\"j as\",\"or get\",\"sc enes\",\"l aughs\",\"ĠF argo\",\"cr ime\",\"Ġorche str\",\"Ġde let\",\"ili ary\",\"rie ved\",\"Ġmilit ar\",\"ĠGreen e\",\"âĹ ı\",\"ãģ ¦\",\"ĠGu ards\",\"Ġunle ashed\",\"ĠWe ber\",\"Ġadjust able\",\"Ġcal iber\",\"Ġmotiv ations\",\"ĠÃ ł\",\"m Ah\",\"ĠL anka\",\"hand le\",\"Ġp ent\",\"ĠR av\",\"ĠAng ular\",\"ĠK au\",\"umb ing\",\"Ġphil anthrop\",\"Ġde hyd\",\"Ġtox icity\",\"e er\",\"ĠY ORK\",\"w itz\",\"å ¼\",\"ĠI E\",\"commun ity\",\"ĠA H\",\"Ġret ali\",\"Ġmass ively\",\"ĠDani els\",\"ĠD EL\",\"Ġcar cin\",\"Ur l\",\"Ġrout ing\",\"ĠNPC s\",\"ĠR AF\",\"ry ce\",\"Ġwa ived\",\"ĠGu atem\",\"Every body\",\"Ġco venant\",\"Ġ17 3\",\"Ġrelax ing\",\"Ġqu art\",\"al most\",\"Ġguard ed\",\"ĠSold iers\",\"ĠPL AY\",\"Ġout going\",\"L AND\",\"Ġre write\",\"ĠM OV\",\"ĠIm per\",\"ĠS olution\",\"Ġphenomen al\",\"Ġl ongevity\",\"Ġimp at\",\"ĠN issan\",\"ir ie\",\"Ġod or\",\"ĠZ ar\",\"ok s\",\"Ġmilit ias\",\"ĠSP EC\",\"Ġtoler ated\",\"ars er\",\"ĠBrad ford\",\"+ ,\",\"Ġsur real\",\"s f\",\"Can adian\",\"Ġresemb lance\",\"Ġcarbohyd rate\",\"VI EW\",\"Ġaccess ory\",\"me al\",\"larg est\",\"ieg el\",\"Some one\",\"Ġtoug hest\",\"os o\",\"Ġfun nel\",\"Ġcondemn ation\",\"lu ent\",\"Ġw ired\",\"ĠSun set\",\"Jes us\",\"ĠP ST\",\"ĠP ages\",\"ĠTy coon\",\"ĠP F\",\"Ġselect ions\",\"Ġ à¤\",\"part isan\",\"Ġhigh s\",\"ĠR une\",\"Ġcraft s\",\"le ad\",\"ĠParent s\",\"Ġre claim\",\"ek er\",\"ĠAll ied\",\"ae per\",\"Ġlo oming\",\"Ġbenefic iaries\",\"ĠH ull\",\"Stud ents\",\"Jew ish\",\"d j\",\"Ġp act\",\"tem plate\",\"ĠOffic ials\",\"ĠBay lor\",\"Ġhe mp\",\"Ġyouth s\",\"ĠLevel s\",\"ĠX iao\",\"ĠC hes\",\"Ġende avor\",\"ĠRem oved\",\"Ġhipp ocamp\",\"H ell\",\"ãĤ Ĭ\",\"80 5\",\"Ġd inosaur\",\"ĠWr ath\",\"ĠIndones ian\",\"Ġcalcul ator\",\"ĠD ictionary\",\"Ġ4 20\",\"ĠM AG\",\"( _\",\"! ,\",\"t arians\",\"Ġrestrict ing\",\"rac use\",\"Ġweek day\",\"OU NT\",\"Ġsh rugged\",\"leg round\",\"Ġb ald\",\"ĠDo ctors\",\"Ġt outed\",\"ĠMax well\",\"Ġ2 14\",\"Ġdiplom at\",\"Ġrep ression\",\"Ġconstitu ency\",\"v ice\",\"r anked\",\"ĠNap oleon\",\"g ang\",\"ĠFore ver\",\"t un\",\"Ġbul b\",\"ĠPD T\",\"ĠC isco\",\"V EN\",\"Ġres umed\",\"Ste ven\",\"ĠManit oba\",\"Ġfab ulous\",\"ĠAg ents\",\"19 84\",\"Ġam using\",\"ĠMyster ies\",\"Ġor thodox\",\"fl oor\",\"Ġquestion naire\",\"Ġpenet rate\",\"Ġfilm makers\",\"ĠUn c\",\"Ġst amped\",\"Ġth irteen\",\"Ġout field\",\"Ġforward ed\",\"Ġapp ra\",\"Ġa ided\",\"t ry\",\"Ġunf ocused\",\"ĠL iz\",\"ĠWend y\",\"ĠSc ene\",\"Ch arg\",\"Ġreject s\",\"Ġleft ist\",\"ĠProv idence\",\"ĠBr id\",\"reg n\",\"Ġprophe cy\",\"ĠL IVE\",\"4 99\",\"Ġfor ge\",\"ĠF ML\",\"Ġintrins ic\",\"ĠF rog\",\"Ġw ont\",\"ĠH olt\",\"Ġfam ed\",\"CL US\",\"aeper nick\",\"ĠH ate\",\"ĠC ay\",\"Ġregister ing\",\"ort ality\",\"rop y\",\"ocaly ptic\",\"a an\",\"n av\",\"Ġfasc ist\",\"IF IED\",\"Ġimpl icated\",\"ĠRes ort\",\"ĠChand ler\",\"ĠBr ick\",\"P in\",\"ys c\",\"Us age\",\"ĠHel m\",\"us ra\",\"âĺħ âĺħ\",\"ĠAb bas\",\"Ġunanim ously\",\"Ġke eper\",\"Ġadd icted\",\"?? ?\",\"Ġhelm ets\",\"Ġant ioxid\",\"aps ed\",\"80 8\",\"gi ene\",\"Ġwa its\",\"Ġmin ion\",\"ra ved\",\"ĠP orsche\",\"Ġdream ing\",\"Ġ17 1\",\"ĠC ain\",\"Ġun for\",\"ass o\",\"ĠConfig uration\",\"k un\",\"hard t\",\"Ġn ested\",\"ĠL DS\",\"L ES\",\"Ġt ying\",\"en os\",\"Ġc ue\",\"ĠMar qu\",\"sk irts\",\"Ġclick ed\",\"Ġexp iration\",\"ĠAccording ly\",\"ĠW C\",\"Ġbless ings\",\"Ġaddict ive\",\"ĠN arr\",\"y x\",\"ĠJagu ars\",\"Ġrent s\",\"ĠS iber\",\"Ġt ipped\",\"ous se\",\"ĠFitz gerald\",\"Ġhier arch\",\"out ine\",\"Ġwa velength\",\"> .\",\"ch id\",\"ĠProcess ing\",\"/ +\",\"r anking\",\"E asy\",\"ĠConst ruct\",\"Ġt et\",\"ins ured\",\"H UD\",\"Ġqu oting\",\"Ġcommun icated\",\"in x\",\"Ġin mate\",\"Ġerect ed\",\"ĠAbs olutely\",\"ĠSure ly\",\"Ġun im\",\"ĠThr one\",\"he id\",\"Ġcl aws\",\"Ġsuper star\",\"ĠL enn\",\"ĠWh is\",\"U k\",\"ab ol\",\"Ġsk et\",\"ĠN iet\",\"Ġper ks\",\"Ġaff inity\",\"Ġopen ings\",\"phas is\",\"Ġdiscrim inate\",\"T ip\",\"v c\",\"Ġgr inding\",\"ĠJenn y\",\"Ġast hma\",\"hol es\",\"ĠHom er\",\"Ġreg isters\",\"ĠGl ad\",\"Ġcre ations\",\"Ġlith ium\",\"Ġappl ause\",\"unt il\",\"Just ice\",\"ĠTur ks\",\"Ġsc andals\",\"Ġb ake\",\"t ank\",\"M ech\",\"ĠMe ans\",\"ĠM aid\",\"Republic ans\",\"is al\",\"wind ows\",\"ĠSant os\",\"Ġveget ation\",\"33 8\",\"t ri\",\"Ġfl ux\",\"ins ert\",\"Ġclar ified\",\"Ġmort g\",\"ĠCh im\",\"ĠT ort\",\"Ġdiscl aim\",\"met al\",\"ĠAs ide\",\"Ġindu ction\",\"Ġinf l\",\"Ġathe ists\",\"amp h\",\"Ġe ther\",\"ĠV ital\",\"ĠBu ilt\",\"M ind\",\"Ġweapon ry\",\"S ET\",\"Ġ18 6\",\"ad min\",\"g am\",\"cont ract\",\"af a\",\"Ġderiv atives\",\"Ġsn acks\",\"Ġch urn\",\"E conom\",\"Ġca pped\",\"ĠUnder standing\",\"ĠH ers\",\"ĠI z\",\"Ġd uct\",\"I ENT\",\"augh ty\",\"Ġâľ Ķ\",\"ĠN P\",\"Ġsa iling\",\"In itialized\",\"Ġt ed\",\"Ġreact ors\",\"ĠL omb\",\"Ġcho ke\",\"ĠW orm\",\"Ġadm iration\",\"Ġsw ung\",\"ens ibly\",\"Ġr ash\",\"ĠGo als\",\"ĠImport ant\",\"Sh ot\",\"ĠR as\",\"Ġtrain ers\",\"ĠB un\",\"Work ing\",\"Ġhar med\",\"ĠPand ora\",\"ĠL TE\",\"Ġmush room\",\"ĠCH AR\",\"ĠF ee\",\"ĠM oy\",\"B orn\",\"ol iberal\",\"ĠMart ial\",\"Ġgentle men\",\"Ġling ering\",\"Offic ial\",\"Ġgra ffiti\",\"ĠN ames\",\"D er\",\"Ġqu int\",\"ist rate\",\"aze era\",\"ĠNOT ICE\",\"ĠFlore nce\",\"Ġpay able\",\"Ġdep icts\",\"ĠSpe cies\",\"He art\",\"âĶĢâĶĢâĶĢâĶĢ âĶĢâĶĢâĶĢâĶĢ\",\"Ġencl osed\",\"Incre ases\",\"D aily\",\"ĠL is\",\"Ġenact ment\",\"ĠB acon\",\"ĠSt eele\",\"dem and\",\"Ġ18 3\",\"Ġmouth s\",\"Ġstr anded\",\"Ġenhance ment\",\"01 1\",\"ĠWh ats\",\"Ġhe aled\",\"en y\",\"ĠR ab\",\"Ġ3 40\",\"ĠLab yrinth\",\"ro ach\",\"ĠY osh\",\"ĠCl ippers\",\"Ġconcert s\",\"Intern et\",\"35 5\",\"Ġstick ers\",\"Ġter med\",\"ĠAx e\",\"Ġgrand parents\",\"Fr ance\",\"ĠCl im\",\"ĠU h\",\"ul ic\",\"Ġthr ill\",\"cent ric\",\"ĠOver view\",\"ĠCond uct\",\"Ġsubstant ive\",\"Ġ18 2\",\"m ur\",\"Ġstr ay\",\"ĠCo ff\",\"Ġrep etitive\",\"ĠFor gotten\",\"Ġqual ification\",\"ew itness\",\"ĠZ imbabwe\",\"Ġsim ulated\",\"ĠJ D\",\"25 3\",\"ĠW are\",\"Ġun sc\",\"T imes\",\"Ġsum mons\",\"Ġdis connected\",\"Ġ18 4\",\"ci us\",\"ĠGu jar\",\"od ka\",\"Ġer ase\",\"ĠTob acco\",\"elect ed\",\"Ġun cont\",\"ĠShe pard\",\"ĠL amp\",\"Ġalert ed\",\"Ġoper ative\",\"arn a\",\"u int\",\"Ġneglig ence\",\"ac ements\",\"Ġsup ra\",\"Ġprev ail\",\"ĠSh ark\",\"Ġbel ts\",\"ãģ «\",\"Ġt ighter\",\"Engine ers\",\"Ġin active\",\"Ġexp onent\",\"ĠWill ie\",\"a ples\",\"Ġhe ir\",\"ĠH its\",\"ian n\",\"ĠS ays\",\"Ġcurrent s\",\"ĠBeng al\",\"Ġar ist\",\"B uffer\",\"Ġbree ze\",\"ĠWes ley\",\"Col a\",\"Ġpron oun\",\"Ġde ed\",\"ĠK ling\",\"Ġof t\",\"Ġinf lict\",\"Ġpun ishing\",\"Ġn m\",\"ik u\",\"OD UCT\",\"01 4\",\"Ġsubsid y\",\"ĠDE A\",\"ĠHer bert\",\"ĠJ al\",\"B ank\",\"Ġdef erred\",\"Ġship ment\",\"B ott\",\"Ġal le\",\"b earing\",\"HT ML\",\"Off line\",\"Ġ2 13\",\"Ġscroll ing\",\"Ġsc anned\",\"ĠLib yan\",\"ĠT OP\",\"ch rom\",\"d t\",\"col umn\",\"Psy NetMessage\",\"Z ero\",\"Ġtor so\",\"0 50\",\"âķ Ĳ\",\"Ġimp erson\",\"ĠSchw artz\",\"ud ic\",\"Ġpiss ed\",\"ĠS app\",\"25 7\",\"ĠIS Ps\",\"og l\",\"Ġsuper vised\",\"Ġad olescent\",\"Ġatt ained\",\"ĠDel ivery\",\"ĠB unny\",\"Ġ19 37\",\"Ġmini ature\",\"Ġo s\",\"Ġ3 70\",\"60 8\",\"ĠMour inho\",\"Ġinn ate\",\"Ġtem po\",\"ĠN M\",\"ĠFall en\",\"00 9\",\"Ġprov ocative\",\"Stream er\",\"ĠBened ict\",\"ĠBol she\",\"Ġt urtle\",\"ĠPC B\",\"ĠEqu al\",\"Direct or\",\"ĠR end\",\"Ġflu ids\",\"Author ities\",\"Ġcous ins\",\"requ ency\",\"ĠNeigh bor\",\"s ets\",\"sh ared\",\"Char les\",\"pass word\",\"Ġg ears\",\"Ġ2 11\",\"ĠHard ware\",\"ri ka\",\"Ġup stream\",\"H om\",\"Ġdisproportion ately\",\"iv ities\",\"Ġund efined\",\"Ġelect rons\",\"Ġcommem or\",\"Event ually\",\"Ġ> <\",\"Ġir responsible\",\"2 18\",\"ĠRe leased\",\"ĠO VER\",\"ĠI GN\",\"ĠB read\",\"st ellar\",\"ĠS age\",\"tt ed\",\"dam age\",\"ed ition\",\"ĠPre c\",\"Ġl ime\",\"Ġconf inement\",\"Ġcal orie\",\"we apon\",\"Ġdiff ering\",\"ĠS ina\",\"m ys\",\"am d\",\"Ġintric ate\",\"k k\",\"ĠP AT\",\"Ã£ o\",\"st ones\",\"lin ks\",\"Ġr anch\",\"Sem itic\",\"Ġdifferent iate\",\"ĠS inger\",\"occup ied\",\"Ġfort ress\",\"c md\",\"Ġinter ception\",\"ĠAnk ara\",\"Ġre pt\",\"ĠSol itaire\",\"Ġrem ake\",\"p red\",\"Ġd ared\",\"aut ions\",\"ĠB ACK\",\"Run ning\",\"Ġdebug ging\",\"Ġgraph s\",\"3 99\",\"ĠNig el\",\"Ġb un\",\"Ġpill ow\",\"Ġprog ressed\",\"fashion ed\",\"Ġob edience\",\"ER N\",\"Ġrehe ars\",\"C ell\",\"t l\",\"S her\",\"Ġher ald\",\"ĠPay ment\",\"ĠC ory\",\"ĠDe pt\",\"Ġrep ent\",\"ĠWe ak\",\"uck land\",\"Ġple asing\",\"Ġshort ages\",\"Ġjur ors\",\"ĠK ab\",\"q qa\",\"Ant i\",\"Ġw ow\",\"ĠRC MP\",\"Ġt sun\",\"ĠS ic\",\"Ġcomp rises\",\"Ġsp ies\",\"Ġprec inct\",\"n u\",\"Ġur ges\",\"Ġtim ed\",\"Ġstrip es\",\"ĠB oots\",\"Ġy en\",\"Adv anced\",\"Ġdisc rete\",\"ĠArch angel\",\"employ ment\",\"D iff\",\"Ġmon uments\",\"Ġ20 9\",\"work er\",\"Ġ19 6\",\"ĠI g\",\"utter stock\",\"T PS\",\"J ac\",\"Ġhomeless ness\",\"Ġcomment ator\",\"Ġrac ially\",\"f ing\",\"se ed\",\"E le\",\"ell ation\",\"Ġeth anol\",\"Ġpar ish\",\"ĠD ong\",\"ĠAw akening\",\"Ġdev iation\",\"ĠB earing\",\"ĠTsu k\",\"Ġrec ess\",\"Ġl ymph\",\"ĠCann abis\",\"å ľ\",\"ĠNEW S\",\"Ġd ra\",\"ĠStef an\",\"ĠWr ong\",\"ĠS AM\",\"Ġloose ly\",\"Ġinterpre ter\",\"ĠPl ain\",\"Go vernment\",\"Ġbigot ry\",\"Ġgren ades\",\"ave z\",\"pict ured\",\"Ġmand ated\",\"ĠMon k\",\"ĠPed ro\",\"Ġl ava\",\"27 4\",\"Ġcyn ical\",\"ĠScroll s\",\"l ocks\",\"M p\",\"Ġcon gregation\",\"orn ings\",\"ph il\",\"ĠI bid\",\"Ġf erv\",\"Ġdisapp earing\",\"Ġarrog ant\",\"sy n\",\"ĠMa ver\",\"ĠSu it\",\"24 1\",\"Ġab bre\",\"ack ers\",\"P a\",\"ĠY el\",\"Whe never\",\"Ġ23 5\",\"ĠV ine\",\"ĠAn at\",\"Ġext inct\",\"LE T\",\"Ġexecut able\",\"V ERS\",\"ox ide\",\"D NA\",\"ĠP rel\",\"Ġresent ment\",\"Ġcompr ise\",\"ĠAv iv\",\"Ġinter ceptions\",\"Ġprol ific\",\"IN A\",\"ĠEr in\",\"though t\",\"2 19\",\"ĠPsychiat ry\",\"un ky\",\"chem ist\",\"H o\",\"ĠMcC oy\",\"Ġbr icks\",\"L os\",\"ri ly\",\"ĠUS SR\",\"Ġr ud\",\"Ġl aud\",\"ĠW ise\",\"ĠEmer ald\",\"Ġrev ived\",\"Ġdam ned\",\"ĠRep air\",\"id em\",\"ct ica\",\"Ġpatri arch\",\"ĠN urs\",\"me g\",\"Ġcheap est\",\"re ements\",\"empt y\",\"ĠCele br\",\"Ġdepri vation\",\"ch anted\",\"ĠTh umbnails\",\"E nergy\",\"ĠEth an\",\"ĠQ ing\",\"Ġopp oses\",\"W IND\",\"v ik\",\"ĠM au\",\"ĠS UB\",\"66 7\",\"G RE\",\"ĠVol unte\",\"nt on\",\"C ook\",\"å Ĳ\",\"es que\",\"Ġplum met\",\"Ġsu ing\",\"Ġpron ounce\",\"Ġresist ing\",\"ĠF ishing\",\"ĠTri als\",\"Ġy ell\",\"Ġ3 10\",\"Ġin duct\",\"Ġpersonal ized\",\"oft en\",\"R eb\",\"EM BER\",\"Ġview point\",\"Ġexist ential\",\"() )\",\"rem ove\",\"MENT S\",\"l asses\",\"Ġev apor\",\"Ġa isle\",\"met a\",\"Ġreflect ive\",\"Ġentit lement\",\"Ġdev ised\",\"mus ic\",\"asc ade\",\"Ġwind ing\",\"off set\",\"Ġaccess ibility\",\"ke red\",\"Bet ter\",\"ĠJohn ston\",\"th inking\",\"S now\",\"ĠCroat ia\",\"ĠAt omic\",\"27 1\",\"34 8\",\"Ġtext book\",\"ĠSix th\",\"Ġ Ø§ÙĦ\",\"Ġsl ider\",\"ĠBur ger\",\"b ol\",\"S ync\",\"Ġgrand children\",\"Ġc erv\",\"+ )\",\"Ġe ternity\",\"Ġtweet ing\",\"Ġspec ulative\",\"Ġpiv otal\",\"ĠW P\",\"ĠT ER\",\"ynam ic\",\"Ġu pl\",\"ĠC ats\",\"per haps\",\"Ġclass mates\",\"Ġblat ant\",\"' -\",\"Ġl akh\",\"ant ine\",\"ĠB org\",\"i om\",\"/ (\",\"ĠAthlet ic\",\"Ġs ar\",\"OT A\",\"ĠHoff man\",\"Never theless\",\"Ġad orable\",\"Ġspawn ed\",\"Ass ociated\",\"ĠDom estic\",\"Ġimpl ant\",\"ĠLux em\",\"ĠK ens\",\"Ġp umps\",\"ĠS AT\",\"Att ributes\",\"50 9\",\"av our\",\"Ġcentral ized\",\"ĠT N\",\"Ġfresh ly\",\"ĠA chieve\",\"Ġouts iders\",\"her ty\",\"ĠRe e\",\"ĠT owers\",\"ĠD art\",\"ak able\",\"Ġm p\",\"ĠHeaven ly\",\"Ġr ipe\",\"ĠCarol ine\",\"ry an\",\"Ġclass ics\",\"Ġret iring\",\"Ġ2 28\",\"Ġa h\",\"Ġdeal ings\",\"Ġpunch ing\",\"ĠChap man\",\"O ptions\",\"max well\",\"vol ume\",\"Ġst al\",\"Ġex ported\",\"ĠQu ite\",\"Ġnumer ical\",\"B urn\",\"F act\",\"ĠKey stone\",\"Ġtrend ing\",\"Ġalter ing\",\"ĠAfric ans\",\"47 8\",\"ĠM N\",\"ĠKn ock\",\"Ġtempt ation\",\"Ġprest ige\",\"Over view\",\"ĠTrad itional\",\"ĠBah rain\",\"Priv ate\",\"ĠH OU\",\"Ġbar r\",\"ĠT at\",\"C ube\",\"US D\",\"ĠGrand e\",\"ĠG at\",\"ĠFl o\",\"Ġres ides\",\"Ġind ec\",\"vol ent\",\"Ġperpet ual\",\"ub es\",\"Ġworld view\",\"ĠQuant um\",\"Ġfil tered\",\"Ġen su\",\"orget own\",\"ERS ON\",\"ĠM ild\",\"37 9\",\"OT T\",\"Ã ¥\",\"Ġvit amins\",\"Ġrib bon\",\"Ġsincere ly\",\"ĠH in\",\"Ġeight een\",\"Ġcontradict ory\",\"Ġgl aring\",\"Ġexpect ancy\",\"Ġcons pir\",\"Ġmon strous\",\"Ġ3 80\",\"re ci\",\"Ġhand ic\",\"Ġpump ed\",\"Ġindic ative\",\"Ġr app\",\"Ġav ail\",\"ĠLEG O\",\"ĠMar ijuana\",\"19 85\",\"ert on\",\"Ġtwent ieth\",\"################ ################\",\"ĠSw amp\",\"Ġval uation\",\"Ġaffili ates\",\"adjust ed\",\"ĠFac ility\",\"26 2\",\"Ġenz ymes\",\"itud inal\",\"Ġimp rint\",\"S ite\",\"Ġinstall er\",\"ĠT RA\",\"m ology\",\"lin ear\",\"ĠCollect ive\",\"ig ating\",\"ĠT oken\",\"Ġspec ulated\",\"K N\",\"ĠC ly\",\"or ity\",\"Ġdef er\",\"Ġinspect ors\",\"appro ved\",\"R M\",\"ĠSun s\",\"Ġinform ing\",\"ĠSy racuse\",\"ib li\",\"7 65\",\"Ġgl ove\",\"Ġauthor ize\",\"âĢ¦âĢ¦âĢ¦âĢ¦ âĢ¦âĢ¦âĢ¦âĢ¦\",\"ĠCru ise\",\"Ġcontract ing\",\"she ll\",\"IF E\",\"ĠJew el\",\"p ract\",\"ĠPhot oshop\",\"ĠKnow ing\",\"h arm\",\"Ġattract ions\",\"ad an\",\"et us\",\"01 8\",\"w agen\",\"Al t\",\"Ġmultip ly\",\"Ġequ ilibrium\",\": {\",\"ĠF ighters\",\"ĠEd gar\",\"Ġfour teen\",\"Go vern\",\"Ġmis use\",\"Ġab using\",\"Ġancest ry\",\"ram er\",\"64 4\",\"Ġwor ms\",\"Ġthick er\",\"ĠComb ine\",\"Ġpeas ants\",\"Ġv ind\",\"Ġcon quest\",\"Ġm ocked\",\"Ġc innamon\",\"ĠC ald\",\"ĠGall up\",\"Ġavoid ance\",\"Ġincarn ation\",\"ĠStr at\",\"Ġt asted\",\"ent a\",\"ĠN eal\",\"p ared\",\"Ġtermin ology\",\"ject ion\",\"Scient ists\",\"ĠIN S\",\"ĠDe e\",\"Ġdirect ories\",\"R oad\",\"ĠSh ap\",\"br ight\",\"ĠDirect ors\",\"ĠCol umn\",\"Ġb ob\",\"Ġprefer ably\",\"Ġgl itch\",\"f urt\",\"Ġe g\",\"id is\",\"C BC\",\"Ġsur rendered\",\"Ġtest ament\",\"33 6\",\"ug gest\",\"ĠN il\",\"an other\",\"Ġpat hetic\",\"ĠDon na\",\"Ġ2 18\",\"ĠA very\",\"Ġwhis key\",\"Ġf ixture\",\"ĠCon quest\",\"Ġbet s\",\"O cc\",\"ĠLe icester\",\"] .\\\"\",\"Ġ) );\",\"Ġfl ashes\",\"45 6\",\"Ġmask ed\",\"ge bra\",\"Ġcomput ed\",\"che l\",\"aud er\",\"Ġdefe ats\",\"ĠLiber ation\",\"ĠOs ama\",\"ĠV ive\",\"Ch anges\",\"Ch annel\",\"Ġtar iffs\",\"Ġm age\",\"ĠS ax\",\"Ġinadvert ently\",\"ĠC RE\",\"ĠRe aper\",\"ink y\",\"gr ading\",\"Ġstere otyp\",\"Ġcur l\",\"ĠF ANT\",\"Ġfram eworks\",\"M om\",\"ĠAn ch\",\"Ġflav our\",\"car bon\",\"Ġperm itting\",\"let cher\",\"ĠMo zilla\",\"ĠPark ing\",\"ĠCh amp\",\"Sc roll\",\"Ġmurd erer\",\"Ġrest ed\",\"Ġow es\",\"ĠP oss\",\"AD D\",\"IF F\",\"res olution\",\"ĠMin ing\",\"Ġcompar ative\",\"D im\",\"Ġneighbour ing\",\"ĠA ST\",\"ĠT oxic\",\"Ġbi ases\",\"Ġgun fire\",\"ur ous\",\"ĠMom ent\",\"19 83\",\"Ġper vasive\",\"tt p\",\"ĠNorm ally\",\"r ir\",\"S arah\",\"ĠAlb any\",\"Ġun sett\",\"ĠS MS\",\"ip ers\",\"l ayer\",\"ĠWh ites\",\"up le\",\"Ġtur bo\",\"ĠLe eds\",\"Ġthat s\",\"ĠMin er\",\"M ER\",\"ĠRe ign\",\"Ġper me\",\"ĠBl itz\",\"Ġ19 34\",\"Ġintimid ating\",\"t ube\",\"Ġecc entric\",\"ab olic\",\"box es\",\"ĠAssoci ates\",\"v otes\",\"Ġsim ulate\",\"um bo\",\"aster y\",\"Ġship ments\",\"FF FF\",\"an th\",\"Ġseason ed\",\"Ġexperiment ation\",\"âĸ ł\",\"law s\",\"Me et\",\"idd les\",\"ant ics\",\"R ating\",\"IS IS\",\"h ift\",\"Ġfront s\",\"b uf\",\"01 7\",\"Ġun att\",\"ĠD il\",\"le ases\",\"ĠGard ens\",\"77 7\",\"t ouch\",\"ve ll\",\"45 8\",\"Ġ= ====\",\"s aving\",\"Ġer osion\",\"ĠQu in\",\"Ġearn s\",\"Ġaccomplish ment\",\"ĠWe i\",\"Ġ< [\",\"____ _\",\"Ġir rig\",\"ĠT eddy\",\"Ġconqu ered\",\"ĠArm ored\",\"Ġassert s\",\"Ġmanip ulating\",\"r Ã©\",\"Ġtranscript s\",\"G allery\",\"Ġplot ting\",\"Ne il\",\"Ġbetray al\",\"load er\",\"ĠS ul\",\"Ġdispl acement\",\"Ġroy alty\",\"ĠW I\",\"he it\",\"ĠDev ices\",\"alle l\",\"Ġmunicipal ities\",\"Ġcan al\",\"St ars\",\"ĠU AE\",\"Ġ\\\" âĢ¦\",\"ĠC U\",\"ab ove\",\"Ġreson ance\",\"ĠguiActive Un\",\"add ed\",\"ĠBra ves\",\"ĠI bn\",\"Ġhere by\",\"ĠB RE\",\"Ġshare holder\",\"ĠH ir\",\"ĠJ i\",\"Ġstrange ly\",\"Ġadm ired\",\"Ġpl ight\",\"Ġb achelor\",\"ĠP ole\",\"cipl inary\",\"T ony\",\"ĠArmen ian\",\"Ġun man\",\"ĠZion ist\",\"St age\",\"isco ver\",\"Ġautom otive\",\"Ġs idelines\",\"Ġsl ick\",\"ĠRena issance\",\"ĠF UN\",\"Im ages\",\"ĠH aj\",\"Ġp ing\",\"Ġshort cut\",\"ĠBl vd\",\"ĠLook s\",\"Ġbur sts\",\"Ġcl amp\",\"Ġm ish\",\"Ġsort ing\",\"Ġpatri ot\",\"Ġcorrect ness\",\"ĠScand inav\",\"ĠCaval iers\",\"p ython\",\"az ar\",\"Ġ3 75\",\"ĠJa une\",\"40 9\",\"Ġdetrim ental\",\"Ġstab bing\",\"Ġpoison ed\",\"Ġf ountain\",\"oc ent\",\"or st\",\"ĠMar i\",\"Ġr ains\",\"ĠO vers\",\"ĠInst itution\",\"ud get\",\"AM Y\",\"t ale\",\"ĠK R\",\"ĠPr ices\",\"Ġhead aches\",\"Ġlands l\",\"ĠA ura\",\"Bon us\",\"ĠZ hao\",\"ĠH ip\",\"Ġhop s\",\"ĠKurd istan\",\"Ġexplo iting\",\"ry n\",\"Ġhypocr isy\",\"op ening\",\"Ġgun shot\",\"Ġw ed\",\"inter stitial\",\"Inter stitial\",\"Ġam en\",\"Bre aking\",\"Ġmarket ed\",\"W ire\",\"ĠC rowd\",\"Contin ue\",\"ĠK nown\",\"ĠEffect ive\",\"ore an\",\"iz ons\",\"Jose ph\",\"Ġescal ation\",\"us ername\",\"Ġcur tain\",\"AT ES\",\"ĠP AR\",\"ĠM iy\",\"Ġcounter fe\",\"l ene\",\"Ġcont enders\",\"d aily\",\"ĠAs c\",\"ĠPhill ip\",\"most ly\",\"Ġfil ename\",\"he ne\",\"Ġresemb ling\",\"Ġst aging\",\"ĠCh loe\",\"Ġw iring\",\"H on\",\"ĠRen ew\",\"ott age\",\"ĠHy brid\",\"m uch\",\"Ġstro kes\",\"Ġpolicy makers\",\"AP TER\",\"ĠArk ham\",\"pl ot\",\"Ġassist ants\",\"Ġde port\",\"ĠSe ga\",\"Ġinflu enza\",\"ĠC ursed\",\"ĠK obe\",\"Ġskin ny\",\"Prov ider\",\"ĠR ip\",\"Ġincrement al\",\"product s\",\"B F\",\"Ġd ome\",\"ĠC redits\",\"Ġlos ers\",\"int s\",\"ĠBet ty\",\"ĠTal ent\",\"ĠD AM\",\"L v\",\"E ss\",\"Ġd ens\",\"tem p\",\"J udge\",\"od ic\",\"Ġ' (\",\"UR ES\",\"ets k\",\"V O\",\"Ġretrie ved\",\"Ġarchitect s\",\"Ù ĩ\",\"Ġeth ic\",\"ĠSecond ary\",\"st ocks\",\"ad ia\",\"Ġ3 25\",\"ĠOp inion\",\"Ġsimultane ous\",\"Ġd izz\",\"ul p\",\"Ġsmugg ling\",\"ipp ery\",\"R andom\",\"f acing\",\"ĠD as\",\"Ġstock p\",\"Ġdiscl osures\",\"po inter\",\"Ġcor al\",\"ĠSe lection\",\"ĠP ike\",\"ival ent\",\"Ġruth less\",\"ĠR im\",\"Ġensu ing\",\"ĠExper iment\",\"Ġcongress man\",\"Ġbelie ver\",\"Ġun specified\",\"ĠM ord\",\"Ġknowledge able\",\"ĠV ERY\",\"T X\",\"Ġstra ps\",\"Ġtur f\",\"apesh ifter\",\"Ġmar ital\",\"Ġfl ock\",\"ãģ Ĩ\",\"26 3\",\"AM ES\",\"ĠOpp osition\",\"Ġtre asures\",\"ĠG OD\",\"Ġmodel ed\",\"ĠWOR LD\",\"Ġ( [\",\"ĠUs age\",\"H F\",\"Ġ$ (\",\"uss ed\",\"Ġpione er\",\"E ight\",\"par se\",\"b read\",\"rit z\",\"ĠMir anda\",\"ĠK ant\",\"++ )\",\"ore n\",\"Ġprov oked\",\"Ġbre eds\",\"ĠIn cludes\",\"ĠPast ebin\",\"ĠFl ip\",\"J ava\",\"Ġbr ink\",\"Ġrum ored\",\"Ġun seen\",\"Ġgar nered\",\"ĠDef in\",\"al ted\",\"Ġtatt oos\",\"Ġhes itation\",\"is itions\",\"ĠWe aver\",\"ĠReport ing\",\"Ġtherap ies\",\"Ġconsult ants\",\"Ġresid ual\",\"ĠMal i\",\"ĠRom a\",\"i ago\",\"ĠRes idents\",\"ub i\",\"Ġremed ies\",\"Ġadapt ive\",\"ĠAl ive\",\"ĠBar cl\",\"Ġwal lets\",\"c rypt\",\"etermin ation\",\"ĠPel osi\",\"Ġsl ipping\",\"oton in\",\"Ġall iances\",\"pat rick\",\"ir is\",\"Ġor th\",\"ĠPer kins\",\"ĠDe V\",\"ĠG ets\",\"Ġdry ing\",\"ge e\",\"fore st\",\"ĠFor get\",\"ore m\",\"33 9\",\"Ġvague ly\",\"ĠD ion\",\"ĠP orn\",\"ĠH OW\",\"Ġp neum\",\"Ġrub ble\",\"ĠT aste\",\"enc ia\",\"ĠG el\",\"Ġd st\",\"Ġ24 5\",\"ĠMoroc co\",\"inf lamm\",\"ĠTw ins\",\"Ġb ots\",\"d aughter\",\"ĠB alk\",\"Ġbre thren\",\"Ġlog os\",\"Ġgo bl\",\"f ps\",\"Ġsub division\",\"Ġp awn\",\"Ġsquee zed\",\"Ġmor ale\",\"ĠD W\",\"' \\\"\",\"Ġkn ot\",\"ook y\",\"Ġdiv isive\",\"Ġboost ed\",\"ch y\",\"ãĥ Ĳ\",\"if act\",\"Ġnewcom ers\",\"ĠWrest ling\",\"Ġsc outs\",\"w olves\",\"R at\",\"Ġnin eteenth\",\"ĠOs borne\",\"St ats\",\"Ġem powered\",\"Ġpsych opath\",\"ĠO EM\",\"ugg age\",\"ĠP K\",\"ĠMoh ammad\",\"P ak\",\"Ġanarch ists\",\"ĠExt ract\",\"est hes\",\"ĠStock holm\",\"l oo\",\"ĠG raph\",\"Ġdeploy ing\",\"ĠStr anger\",\"ĠM old\",\"Ġstaff er\",\"Ġdiscount ed\",\"uck le\",\"ple ase\",\"ĠLand ing\",\"ÃŃ a\",\"Ġ19 3\",\"Ġan te\",\"Ġrep etition\",\"Ġ+ /-\",\"Ġpar ody\",\"Ġlive ly\",\"AA A\",\"ĠHor us\",\"Ġp its\",\"ind ers\",\"L OC\",\"ĠVen ice\",\"40 6\",\"ĠDis cover\",\"â Ĩ\",\"ellect ual\",\"Ġp ens\",\"Ġey el\",\"ig uous\",\"Im pl\",\"Ġj oking\",\"Ġinv al\",\"ĠBel fast\",\"Ġcredit ors\",\"ĠSky walker\",\"ov sky\",\"Ġcease fire\",\"Ġse als\",\"is oft\",\") ).\",\"ĠFel ix\",\"IT S\",\"Ġt resp\",\"ĠBlock chain\",\"ew are\",\"ĠSch war\",\"en ne\",\"mount ed\",\"ĠBe acon\",\"les h\",\"Ġimmense ly\",\"Ġche ering\",\"Em ploy\",\"sc ene\",\"ish ly\",\"atche wan\",\"ĠNic olas\",\"Ġdr ained\",\"ĠEx it\",\"ĠAz erb\",\"j un\",\"Ġflo ated\",\"u ania\",\"De ep\",\"Ġsuper v\",\"Ġmyst ical\",\"ĠD ollar\",\"ĠApost le\",\"ĠR EL\",\"ĠProv ided\",\"ĠB ucks\",\"ãĥ ´\",\"cut ting\",\"Ġenhance ments\",\"ĠPengu ins\",\"ĠIsa iah\",\"Ġj erk\",\"ĠW yn\",\"Ġst alled\",\"Ġcryptoc urrencies\",\"ĠR oland\",\"sing le\",\"Ġl umin\",\"ĠF ellow\",\"ĠCap acity\",\"ĠKaz akh\",\"W N\",\"Ġfin anced\",\"38 9\",\"Ġt id\",\"Ġcoll usion\",\"ĠMy r\",\"î Ģ\",\"Sen ator\",\"Ġped iatric\",\"Ġneat ly\",\"Ġsandwic hes\",\"ĠArchitect ure\",\"Ġt ucked\",\"Ġbalcon y\",\"Ġearthqu akes\",\"qu ire\",\"F uture\",\"Ġhe fty\",\"é Ĺ\",\"Ġspecial izes\",\"Ġstress es\",\"Ġs ender\",\"Ġmisunder standing\",\"Ġep ile\",\"Ġprov oke\",\"ĠCol ors\",\"Ġdis may\",\"uk o\",\"[ _\",\"58 6\",\"ne utral\",\"Ġdon ating\",\"ĠRand all\",\"Mult i\",\"Ġconvenient ly\",\"ĠS ung\",\"ĠC oca\",\"Ġt ents\",\"ĠAc celer\",\"Ġpart nered\",\"27 2\",\"ir ming\",\"ĠB AS\",\"s ometimes\",\"Ġobject ed\",\"ub ric\",\"p osed\",\"LC S\",\"gr ass\",\"Ġattribut able\",\"V IS\",\"Israel i\",\"Ġrepe ats\",\"ĠR M\",\"v ag\",\"ut a\",\"in ous\",\"Ġin ert\",\"ĠMig uel\",\"æ Ń\",\"ĠHawai ian\",\"B oard\",\"Ġart ific\",\"ĠAzerb ai\",\"as io\",\"ĠR ent\",\"A IN\",\"Ġappl iances\",\"Ġnational ity\",\"Ġass hole\",\"ĠN eb\",\"Ġnot ch\",\"h ani\",\"ĠBr ide\",\"Av ailability\",\"Ġintercept ed\",\"Ġcontin ental\",\"Ġsw elling\",\"ĠPers pect\",\"b ies\",\". <\",\"ith metic\",\"ĠL ara\",\"Ġtempt ing\",\"add r\",\"Ġoversee ing\",\"cl ad\",\"ĠD V\",\"ĠGing rich\",\"Ġm un\",\"ĠApp ropri\",\"Ġalter ations\",\"ĠPat reon\",\"Ġha voc\",\"Ġdiscipl ines\",\"Ġnotor iously\",\"aku ya\",\"ier i\",\"? ).\",\"ĠW ent\",\"Ġsil icon\",\"Ġtre mb\",\"Cont ainer\",\"K nown\",\"Ġmort ar\",\"est e\",\"ick a\",\"Ar thur\",\"ĠPre viously\",\"ĠMart y\",\"Ġsp arse\",\"g ins\",\"Ġin ward\",\"ĠParticip ant\",\"C opy\",\"ĠM isc\",\"Ġantib iotic\",\"ĠRet ro\",\"Ġel usive\",\"Ġass ail\",\"ĠBatt alion\",\"ĠB ought\",\"Ġdimin ish\",\"ĠEuro pa\",\"s ession\",\"ĠDanger ous\",\"ies el\",\"Ġdisbel ief\",\"Ġbl asts\",\"ext reme\",\"ĠBoy d\",\"ĠProject s\",\"ĠGu ys\",\"Ġunder gone\",\"Ġgr ill\",\"ĠDw ight\",\"Ġ19 7\",\"US ER\",\"Ġfiles ystem\",\"Ġcl ocks\",\"T aylor\",\"Ġwra pper\",\"Ġfold ing\",\"ous and\",\"ĠPhilipp ine\",\"ATION AL\",\"ĠPer th\",\"Ġas hes\",\"Ġaccum ulate\",\"ĠGate way\",\"Sh op\",\"orks hire\",\"H an\",\"ĠBar rel\",\"ĠLe h\",\"ĠX V\",\"Ġwh im\",\"Ġrep o\",\"ĠC G\",\"ĠM am\",\"Ġincorpor ating\",\"Ġbail out\",\"Ġlingu istic\",\"Ġdis integ\",\"C LE\",\"Ġcinem atic\",\"ĠF iber\",\"S yn\",\"il ion\",\"ĠCom pos\",\"c hens\",\"Ġne oc\",\"Ġbo iled\",\"F INE\",\"on o\",\"un cle\",\"ik en\",\"ĠB M\",\"Î ¹\",\"Ġreceipt s\",\"Ġdisp osed\",\"ĠTh irty\",\"ĠR ough\",\"ĠA BS\",\"Ġnot withstanding\",\"oll en\",\"# $\",\"Ġunrel iable\",\"Ġbl oom\",\"Ġmedi ocre\",\"Ġtr am\",\"ĠTas man\",\"Ġsh akes\",\"Ġmanifest o\",\"ĠM W\",\"Ġsatisf actory\",\"Ġsh ores\",\"Ġcomput ation\",\"Ġassert ions\",\"orm ons\",\"ar ag\",\"ab it\",\"Dem ocrats\",\"ĠL oot\",\"ĠVol ks\",\"ha ired\",\"Ġgrav itational\",\"S ing\",\"ĠM iz\",\"Ġthro ttle\",\"Ġtyr anny\",\"ĠView s\",\"Ġrob ber\",\"ĠMinor ity\",\"Ġsh rine\",\"sc ope\",\"pur pose\",\"Ġnucle us\",\"our cing\",\"ĠUS DA\",\"ĠD HS\",\"w ra\",\"ĠBow ie\",\"Sc ale\",\"ĠB EL\",\"x i\",\"I ter\",\"Ġ( ),\",\"w right\",\"Ġsail ors\",\"ous ed\",\"NAS A\",\"ĠPro of\",\"ĠMin eral\",\"t oken\",\"ĠF D\",\"R ew\",\"Ġe ll\",\"6 30\",\"Ġchance llor\",\"ĠG os\",\"Ġamount ed\",\"ĠRec re\",\"ome z\",\"ĠOpt im\",\"ĠOl ive\",\"Ġtrack er\",\"ow ler\",\"ĠUn ique\",\"R oot\",\"Ġmar itime\",\"ĠQur an\",\"ĠAd apt\",\"Ġecosystem s\",\"ĠRe peat\",\"ĠS oy\",\"ĠI MP\",\"Ġgrad uating\",\"and em\",\"P ur\",\"ĠRes et\",\"ĠTr ick\",\"ĠPh illy\",\"ĠT ue\",\"ĠMalays ian\",\"Ġclim ax\",\"Ġb ury\",\"Ġcons pic\",\"ĠSouth ampton\",\"ĠFl owers\",\"Ġesc orted\",\"ĠEduc ational\",\"ĠI RC\",\"Ġbrut ally\",\"e ating\",\"Ġpill ar\",\"ĠS ang\",\"ĠJ ude\",\"ar ling\",\"ĠAm nesty\",\"Ġrem inding\",\"ĠAdminist rative\",\"hes da\",\"Ġfl ashed\",\"ĠP BS\",\"per ate\",\"fe ature\",\"Ġsw ipe\",\"Ġgra ves\",\"oult ry\",\"26 1\",\"bre aks\",\"ĠGu er\",\"Ġsh rimp\",\"ĠV oting\",\"qu ist\",\"Ġanaly tical\",\"Ġtables poons\",\"ĠS OU\",\"Ġresear ched\",\"Ġdisrupt ed\",\"Ġj our\",\"Ġrepl ica\",\"Ġcart oons\",\"b ians\",\"} )\",\"c opy\",\"G ot\",\"ou ched\",\"P UT\",\"Ġsw arm\",\"not ations\",\"s aid\",\"Ġreb uilt\",\"Ġcollabor ate\",\"Ġr aging\",\"Ġn ar\",\"Ġdem ographics\",\"ĠD DR\",\"Ġdist rust\",\"oss ier\",\"ĠK ro\",\"Ġpump kin\",\"Ġreg rets\",\"Ġfatal ities\",\"ĠL ens\",\"ĠO le\",\"p d\",\"Ġpupp et\",\"ĠOut look\",\"ĠSt am\",\"O l\",\"F air\",\"U U\",\"Ġre written\",\"Ä ±\",\"Ġfasc inated\",\"Ġve ctors\",\"Ġtrib unal\",\"u ay\",\"ĠM ats\",\"ĠCo ins\",\"[ [\",\"Ġ18 1\",\"Ġrend ers\",\"ĠK aepernick\",\"Ġesp ionage\",\"Ġsum m\",\"Ġd itch\",\"Acc ount\",\"Ġspread sheet\",\"Ġmut ant\",\"p ast\",\"40 7\",\"Ġd ye\",\"Ġinit iation\",\"Ġ4 000\",\"Ġpunish able\",\"Ġth inner\",\"ĠKh al\",\"Ġinter medi\",\"D un\",\"ĠGoth am\",\"Ġeager ly\",\"Ġvag inal\",\"p owers\",\"V W\",\"ĠWATCH ED\",\"Ġpred ator\",\"ams ung\",\"Ġdispar ity\",\"Ġ[ *\",\"Ġam ph\",\"Ġout skirts\",\"ĠSpir its\",\"Ġskelet al\",\"Ð »\",\"ĠR ear\",\"Ġissu ance\",\"ĠLog ic\",\"re leased\",\"Z Z\",\"ĠB ound\",\"Ent ry\",\"Ġex its\",\"is ol\",\"ĠFound er\",\"Ġw re\",\"ĠGreen land\",\"ĠM MO\",\"t aker\",\"IN C\",\"ãģ ¾\",\"Ġhour ly\",\"hen ko\",\"Ġfantas ies\",\"Ġdis ob\",\"Ġdemol ition\",\"ãĥ ĭ\",\"Ġen listed\",\"rat ulations\",\"Ġmis guided\",\"Ġens ured\",\"Ġdiscour aged\",\"m ort\",\"Ġfl ank\",\"Ġc ess\",\"Ġreact s\",\"ĠS ere\",\"s ensitive\",\"ĠSer pent\",\"ass ad\",\"Ġ24 7\",\"Ġcalm ly\",\"b usters\",\"Ġble ed\",\"ĠSt ro\",\"Ġamuse ment\",\"ĠAntar ctica\",\"Ġs cept\",\"ĠG aw\",\"a q\",\"ason ic\",\"Ġsp rawling\",\"n ative\",\"atur ated\",\"ĠBattle field\",\"IV ERS\",\"E B\",\"ĠG ems\",\"ĠNorth western\",\"ĠFil ms\",\"ĠAut omatic\",\"Ġappre hend\",\"ãģ ¨\",\"Ġgui Name\",\"Ġback end\",\"Ġevid enced\",\"ge ant\",\"01 2\",\"ĠS iege\",\"Ġexternal To\",\"Ġunfocused Range\",\"ĠguiActiveUn focused\",\"Ġgui Icon\",\"ĠexternalTo EVA\",\"ĠexternalToEVA Only\",\"F ri\",\"ch ard\",\"en aries\",\"Ġchief s\",\"Ġc f\",\"ĠH UD\",\"Ġcorro bor\",\"Ġd B\",\"ĠT aken\",\"ĠPat ricia\",\"ra il\",\"ĠCh arm\",\"ĠLiber tarian\",\"rie ve\",\"Person al\",\"ĠO UR\",\"ger ies\",\"Ġdump ing\",\"Ġneurolog ical\",\"it imate\",\"ĠClint ons\",\"raft ed\",\"ĠM olly\",\"Ġtermin als\",\"reg ister\",\"Ġfl are\",\"Ġenc oded\",\"Ġautop sy\",\"p el\",\"m achine\",\"Ġexempt ions\",\"ĠRoy als\",\"d istance\",\"Ġdraft s\",\"Ġl ame\",\"ĠC unning\",\"Ġsp ouses\",\"ĠMark ets\",\"ĠCar rier\",\"Ġimp lying\",\"ĠY ak\",\"s id\",\"Ġl oser\",\"Ġvigil ant\",\"Ġimpe achment\",\"Ġaug mented\",\"ĠEmploy ees\",\"Ġunint ended\",\"tern ally\",\"ĠW att\",\"Ġrecogn izable\",\"ess im\",\"æ Ŀ\",\"Ġco ated\",\"r ha\",\"Ġlie utenant\",\"ĠLegisl ation\",\"pub lished\",\"44 4\",\"01 3\",\"Ġide ally\",\"ĠPass word\",\"Ġsimpl ify\",\"ĠMet a\",\"ĠM RI\",\"Ġple ading\",\"organ ized\",\"hand ler\",\"Ġun ravel\",\"cor rect\",\"Ġ icy\",\"Ġparan oid\",\"Ġpass er\",\"Ġinspect ions\",\"of er\",\"ĠHealth care\",\"28 3\",\"ĠBr ut\",\"iol a\",\"for ge\",\"ĠMed ieval\",\"MS N\",\"ie vers\",\"ĠProgram ming\",\"å ī\",\"Ġ2 23\",\"m u\",\"ĠC LE\",\"ug a\",\"Ġsho ppers\",\"Ġinform ative\",\"ĠPl ans\",\"Ġsupplement ation\",\"ĠT ests\",\"ty ard\",\"ocy tes\",\"ĠVeg a\",\"ĠGujar at\",\"erman ent\",\"Ex cept\",\"ĠL OT\",\"all a\",\"ĠC umm\",\"ĠO sw\",\"Ġven om\",\"ĠDeb t\",\"ĠD OWN\",\"Ġreun ion\",\"Ġm uc\",\"ĠRel ief\",\"Ġge op\",\"ĠðŁ ĺ\",\"al ogue\",\"An th\",\"ech o\",\"Ġcor ros\",\"Ġrepl ication\",\"ĠBl azing\",\"ĠD aughter\",\"Ġinf lic\",\"ĠLind sey\",\"Ù Ī\",\"28 4\",\"Ex it\",\"Ġgl oom\",\"TA IN\",\"Ġundermin ing\",\"Ġadv ising\",\"h idden\",\"Ġover flow\",\"Ġg or\",\"urd ue\",\"Ġe choes\",\"enh agen\",\"Ġimp uls\",\"d rug\",\"c ash\",\"Ġas ync\",\"Ġmir ac\",\"at ts\",\"p unk\",\"Ġpiv ot\",\"ĠLegisl ative\",\"Ġblog gers\",\"ĠCl aw\",\"s burg\",\"d yl\",\"ĠRecomm end\",\"Ġver te\",\"Ġprohib iting\",\"ĠPant her\",\"Jon athan\",\"Ġo min\",\"Ġhate ful\",\"28 1\",\"ĠOr che\",\"ĠMurd och\",\"down s\",\"Ġas ymm\",\"G ER\",\"Al ways\",\"Ġinform s\",\"ĠW M\",\"ĠP ony\",\"ĠApp endix\",\"ĠAr lington\",\"J am\",\"Ġmedic inal\",\"ĠS lam\",\"IT IES\",\"Ġre aff\",\"ĠR i\",\"F G\",\"S pring\",\"b ool\",\"Ġthigh s\",\"Ġmark ings\",\"ĠRa qqa\",\"ĠL ak\",\"p oll\",\"ts ky\",\"ĠMort y\",\"ĠDef inition\",\"Ġdeb unk\",\"end ered\",\"ĠLe one\",\"a vers\",\"Ġmortg ages\",\"App arently\",\"N ic\",\"ha us\",\"ĠTh ousands\",\"au ld\",\"Ġm ash\",\"sh oot\",\"Ġdi arr\",\"Ġconscious ly\",\"H ero\",\"e as\",\"ĠN aturally\",\"ĠDestroy er\",\"Ġdash board\",\"serv ices\",\"R og\",\"Ġmillenn ials\",\"Ġinv ade\",\"- (\",\"Ġcomm issions\",\"ĠA uckland\",\"Ġbroadcast s\",\"Ġfront al\",\"Ġcr ank\",\"ĠHist oric\",\"Ġrum ours\",\"CT V\",\"Ġster il\",\"Ġboost er\",\"rock et\",\"ãĤ ¼\",\"ut sche\",\"ĠP I\",\"Ġ2 33\",\"ĠProdu cer\",\"ĠAnaly tics\",\"Ġinval uable\",\"Ġunint ention\",\"ĠC Y\",\"Ġscrut in\",\"Ġg igg\",\"Ġeng ulf\",\"Ġprolet ariat\",\"Ġh acks\",\"ĠH ew\",\"ar ak\",\"ĠSl ime\",\"ield ing\",\"ag her\",\"ĠEll iot\",\"Ġtele com\",\"Ġ2 19\",\"ult an\",\"ĠAr bor\",\"ĠSc outs\",\"B an\",\"Ġlifes pan\",\"Ġbl asp\",\"38 8\",\"Ġjud iciary\",\"ĠContin ental\",\"ask ing\",\"Mc C\",\"L ED\",\"Ġbag gage\",\"ĠSorce rer\",\"Ġrem nants\",\"ĠGriff ith\",\"ets u\",\"ĠSub aru\",\"ĠPerson ality\",\"des igned\",\"ush ima\",\"agn ar\",\"Ġrec oil\",\"Ġpass ions\",\"\\\\ \\\":\",\"Ġte e\",\"Ġabol ition\",\"ĠCreat ing\",\"j ac\",\"Ġ19 4\",\"01 9\",\"Ġpill ars\",\"ric hed\",\"/ \\\"\",\"t k\",\"Ġlive lihood\",\"Ġro asted\",\"ah on\",\"ĠH utch\",\"ass ert\",\"Ġdivid end\",\"Ġkn it\",\"Ġd aunting\",\"Ġdisturb ance\",\"Ġsh ale\",\"Ġcultiv ated\",\"Ġrefriger ator\",\"L B\",\"ĠN ET\",\"Ġcommercial s\",\"Ġthink ers\",\"45 5\",\"Ġch op\",\"B road\",\"Ġsuspic ions\",\"Ġtag ged\",\"l ifting\",\"Ġsty lish\",\"ĠShield s\",\"Short ly\",\"Ġt ails\",\"A uth\",\"ST E\",\"ĠG AME\",\"Ġse ism\",\"ĠK is\",\"olog ne\",\"Ġcow ork\",\"Ġforc ibly\",\"Ġthy roid\",\"ĠP B\",\"AN E\",\"mar ried\",\"h orse\",\"Ġpoly mer\",\"ĠCh al\",\"od or\",\"DE BUG\",\"ĠCon text\",\"Ġbl iss\",\"Ġpin point\",\"ĠMat hemat\",\"leg ram\",\"ĠWeek end\",\"Ġlab elled\",\"Ġb art\",\"it les\",\"Ġest rogen\",\"âĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶ âĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶ\",\"\\\" '\",\"Ġvis ibly\",\"Ġouts ider\",\"aid a\",\"Are a\",\"Ġdisse min\",\"Ġdish onest\",\"ĠCl osed\",\"ĠBullet in\",\"ĠRam sey\",\"sw ord\",\"ĠX I\",\"our ced\",\"S ame\",\"34 6\",\"ĠRe pe\",\"ĠK ou\",\"c ake\",\"em is\",\"C ache\",\"ĠMe aning\",\"ĠEn light\",\"onom y\",\"Ġmanifest ation\",\"sw orth\",\"J ay\",\"Ġch ore\",\"Ã¶ r\",\"D ream\",\"Ġsanction ed\",\"Ġcult urally\",\"ĠA ra\",\"N av\",\"Ġthe ological\",\"Ġstr ut\",\"ĠV O\",\"ĠHand book\",\"Ġconstruct ing\",\"ĠÂ ¶\",\"ĠBenef its\",\"ĠPsych ological\",\"s ac\",\"å ¸\",\"p olicy\",\"ĠMat ters\",\"ĠReport ed\",\"ĠBy te\",\"Ġvit ro\",\"ĠM aiden\",\"Ġl am\",\"ĠJenn ings\",\"Ġgar ment\",\"ĠRut gers\",\"ĠStaff ord\",\"ĠWell ington\",\"Ġinter mitt\",\"Ġn pm\",\"Ġord eal\",\"Ġplug ged\",\"o oming\",\"in ished\",\"fram ework\",\"Ġtim ber\",\"Ġc ass\",\"Ġ8 50\",\"il ess\",\"ĠRed ux\",\"7 68\",\"St re\",\"Ġsurpass ed\",\"w hel\",\"Ġparalle ls\",\"Ġve il\",\"ĠG I\",\"ĠR EST\",\"Ġread iness\",\"s ort\",\"Ġmod ifying\",\"ĠSl ate\",\"ru ff\",\"Ġmar ble\",\"Ġinf rared\",\"Ġaud itor\",\"ĠFANT ASY\",\"ĠP overty\",\"ĠS PD\",\"Ġ\\\" (\",\"K y\",\"RA Y\",\"Ġexecut ions\",\"ĠBever ly\",\"ĠMarx ism\",\"ĠBur st\",\"ĠK ali\",\"est ones\",\"Clear ly\",\"E ll\",\"ãģ §\",\"ĠProceed ings\",\"T oken\",\"IF IC\",\"Ã± a\",\"Cent ral\",\"ĠH aley\",\"ĠD rama\",\"Ġform ations\",\"OR N\",\"Book s\",\"Ġdom inating\",\"ĠFly ers\",\"ĠCompan ion\",\"Ġdiscipl ined\",\"ĠYug oslav\",\"ĠSpell s\",\"Ġv engeance\",\"Ġland lords\",\"L en\",\"ĠO gre\",\"ano ia\",\"Ġpier cing\",\"Ġcon greg\",\"Ġscore r\",\"ob ia\",\"Ġnic kel\",\"ĠLear ns\",\"Ġre jo\",\"Ġmaster piece\",\"Fl ash\",\"Ġinhab ited\",\"ĠOpen GL\",\"ĠD ud\",\"ĠI CO\",\"Ġar ter\",\"Ġpl ur\",\"Ġmaster y\",\"Ġlong standing\",\"st ed\",\"Ġw ines\",\"Ġtelev ised\",\"ĠSh rine\",\"ĠBay ern\",\"Ġâ ĵĺ\",\"Ġencl osure\",\"j ohn\",\"Ġprophe ts\",\"ĠRes urrection\",\"ĠOrd ers\",\"Ġun even\",\"r als\",\"Ġd wind\",\"ĠL ah\",\"ĠSl oven\",\"37 8\",\"Ġins istence\",\"aff le\",\"ĠCl one\",\"Ġhard ship\",\"ĠCongress man\",\"Ġple ad\",\"Ġreview ers\",\"Ġc ured\",\"Ġ19 35\",\"as ley\",\"f ake\",\"ĠTh inking\",\"yd ia\",\"P ART\",\"ĠD ota\",\"o it\",\"Ġwh ipped\",\"Ġb ouncing\",\"ĠHispan ics\",\"com ings\",\"Ġcann abin\",\"ĠCh ambers\",\"ĠZ ack\",\"Option al\",\"Ġco ats\",\"Ġprow ess\",\"ĠNort on\",\"Ġplain ly\",\"Ġfre ight\",\"Ġinhib ition\",\"Ġcl am\",\"Ġ30 3\",\"ke f\",\"ale igh\",\"L uke\",\"Ġpsych o\",\"ator ium\",\"M ED\",\"Ġtreat ies\",\"Ġind isc\",\"Ġd c\",\"OP S\",\"Ġresil ient\",\"ĠInter state\",\"Ġsl ack\",\"Ġmund ane\",\"Ġestab lishes\",\"35 9\",\"Ġstr ained\",\"Ġn ond\",\"S us\",\"Ġcast e\",\"ar ate\",\"ie ving\",\"Ġunfair ly\",\"Ġpars er\",\"on ial\",\"urs ive\",\"V ia\",\"ĠOtt o\",\"ĠAuthor ities\",\"stro ke\",\"K R\",\"ĠMer cy\",\"Ġfurn ished\",\"Ġout set\",\"Ġmet ic\",\"19 82\",\"olith ic\",\"ĠT ent\",\"og ical\",\"ĠA ircraft\",\"Ġh ides\",\"ĠBec ame\",\"Ġeduc ators\",\"re aching\",\"Ġvol atility\",\"Ġtodd ler\",\"ĠNAS CAR\",\"ĠTw elve\",\"ĠHigh lights\",\"Ġgra pe\",\"Ġspl its\",\"Ġpe asant\",\"Ġre neg\",\"ĠMS I\",\"Tem p\",\"st ars\",\"Ġtre k\",\"ĠHy de\",\"b inding\",\"Ġreal ism\",\"Ġox ide\",\"ĠH os\",\"Ġmount s\",\"Ġbit ing\",\"Ġcollaps ing\",\"Ġpost al\",\"Ġmuse ums\",\"Ġdet ached\",\"Ġrespect ing\",\"Ġmonop ol\",\"Ġwork flow\",\"ĠC ake\",\"Tem plate\",\"ĠOrgan isation\",\"Ġpers istence\",\"36 9\",\"C oming\",\"B rad\",\"Ġredund ant\",\"ĠG TA\",\"Ġb ending\",\"Ġrev oked\",\"Ġoff ending\",\"Ġfram ing\",\"Ġprint f\",\"Comm un\",\"mem bers\",\"Out side\",\"Ġconst rued\",\"Ġc oded\",\"F ORE\",\"Ġch ast\",\"Ch at\",\"Ind ian\",\"ĠY ard\",\"? !\\\"\",\"ĠP orts\",\"ĠX avier\",\"ĠR ET\",\"' .\\\"\",\"ĠBo at\",\"iv ated\",\"ich t\",\"umer able\",\"D s\",\"ĠDun n\",\"Ġcoff in\",\"Ġsecure ly\",\"ĠRapt ors\",\"ĠB es\",\"Install ation\",\"Ġin ception\",\"ĠHealth y\",\"end ants\",\"Ġpsych ologists\",\"ĠShe ikh\",\"c ultural\",\"ĠBlack Berry\",\"sh ift\",\"F red\",\"oc he\",\"Ġc akes\",\"ĠS EO\",\"ĠG ian\",\"ĠAs ians\",\"og ging\",\"e lement\",\"Ġpund its\",\"ĠV augh\",\"ĠG avin\",\"Ġh itter\",\"Ġdrown ed\",\"Ġch alk\",\"ĠZ ika\",\"Ġmeas les\",\"80 2\",\"âĢ¦ ..\",\"ĠAW S\",\"] \\\"\",\"Ġdist ort\",\"ĠM ast\",\"Ġantib odies\",\"ĠM ash\",\"Mem ory\",\"ĠUg anda\",\"ĠPro b\",\"Ġvom iting\",\"ĠTurn s\",\"Ġoccup ying\",\"Ġev asion\",\"ĠTher apy\",\"Ġprom o\",\"Ġelect r\",\"Ġblue print\",\"ĠD re\",\"pr iced\",\"ĠDep ot\",\"Ġallev iate\",\"ĠSom ali\",\"m arg\",\"n ine\",\"Ġnostalg ia\",\"ĠShe pherd\",\"Ġcaval ry\",\"Ġtor ped\",\"ĠBlood y\",\"x b\",\"Ġs ank\",\"Ġgo alt\",\"report print\",\"embed reportprint\",\"clone embedreportprint\",\"ĠIn itially\",\"ĠF ischer\",\"Ġnot eworthy\",\"c ern\",\"Ġin efficient\",\"raw download\",\"rawdownload cloneembedreportprint\",\"c ation\",\"ĠD ynasty\",\"l ag\",\"D ES\",\"Ġdistinct ly\",\"ĠEston ia\",\"Ġopen ness\",\"Ġg ossip\",\"ru ck\",\"W idth\",\"ĠIb rahim\",\"Ġpet roleum\",\"Ġav atar\",\"ĠH ed\",\"ath a\",\"ĠHog warts\",\"Ġc aves\",\"67 8\",\"Ġsafegu ard\",\"ĠM og\",\"iss on\",\"ĠDur ham\",\"sl aught\",\"ĠGrad uate\",\"Ġsub conscious\",\"ĠEx cellent\",\"ĠD um\",\"---- -\",\"Ġp iles\",\"ĠW ORK\",\"ĠG arn\",\"ĠF ol\",\"ĠAT M\",\"Ġavoid s\",\"ĠT ul\",\"Ġble ak\",\"EL Y\",\"iv ist\",\"light ly\",\"P ers\",\"ĠD ob\",\"ĠL S\",\"Ġins anity\",\"Î µ\",\"atal ie\",\"En large\",\"Ġtw ists\",\"Ġfault y\",\"Ġpir acy\",\"Ġimp over\",\"Ġrug ged\",\"ĠF ashion\",\"Ġs ands\",\"' ?\",\"sw ick\",\"Ġn atives\",\"Ġhe n\",\"ĠNo ise\",\"ãĥ Ĺ\",\"Ġg reens\",\"Ġfree zer\",\"Ġd ynasty\",\"ĠFather s\",\"ĠNew ark\",\"Ġarchae ological\",\"Ġo t\",\"ob ar\",\"Ġblock ade\",\"Ġall erg\",\"L V\",\"Ġdeb it\",\"ĠR FC\",\"ĠMil ton\",\"ĠPress ure\",\"Ġwill ingly\",\"Ġdisproportion ate\",\"Ġopp ressive\",\"Ġdiamond s\",\"Ġbelong ings\",\"19 70\",\"Ġbell s\",\"Ġimperial ism\",\"Ġ2 27\",\"Ġexpl oding\",\"ĠE clipse\",\"Ġ19 19\",\"Ġr ant\",\"Ġnom inations\",\"34 7\",\"Ġpeace fully\",\"ric a\",\"ĠF UCK\",\"Ġvib ration\",\"mal ink\",\"Ġro pes\",\"ĠIv anka\",\"ĠBrew ery\",\"ĠBook er\",\"ĠOw ens\",\"go ers\",\"Serv ices\",\"ĠSn ape\",\"Ġ19 1\",\"39 5\",\"Ġ2 99\",\"just ice\",\"Ġb ri\",\"Ġdisc s\",\"Ġprom inently\",\"Ġvul gar\",\"Ġsk ipping\",\"l ves\",\"Ġtsun ami\",\"37 4\",\"ĠU rug\",\"ĠE id\",\"rec ated\",\"p hen\",\"Ġfault s\",\"ĠStart ed\",\"9 50\",\"Ġp i\",\"Ġdetect or\",\"Ġbast ard\",\"Ġvalid ated\",\"Space Engineers\",\"OUR CE\",\"Ġ( ~\",\"Ġuns ur\",\"Ġaff irmed\",\"Ġfasc ism\",\"Ġres olving\",\"ĠCh avez\",\"ĠC yn\",\"Ġdet ract\",\"L ost\",\"Ġrig ged\",\"Ġhom age\",\"ĠBrun o\",\"55 5\",\"ec a\",\"Ġpress es\",\"Ġhum our\",\"Ġsp acing\",\"Ġ' /\",\"olk ien\",\"C oun\",\"OP ER\",\"T re\",\"S on\",\"ĠCambod ia\",\"ier re\",\"m ong\",\"o zy\",\"Ġliquid ity\",\"ĠSov iets\",\"ĠFernand o\",\"Ġ2 29\",\"Ġsl ug\",\"ĠCatal an\",\"elect ric\",\"Ġsc enery\",\"ĠH earth\",\"Ġconst rained\",\"Ġgoal ie\",\"ĠGu idelines\",\"ĠAm mo\",\"ĠPear son\",\"Ġtax ed\",\"Ġfet us\",\"Resp onse\",\"ĠAlex is\",\"th ia\",\"G uy\",\"Ġrecon struct\",\"Ġextrem es\",\"Ġconclud ing\",\"ĠP eg\",\"ook s\",\"Ġded uctions\",\"R ose\",\"Ġground breaking\",\"ĠT arg\",\"ãĥ ģ\",\"ĠRe ve\",\"res ource\",\"Ġmo ons\",\"Ġelectrom agnetic\",\"Ġamid st\",\"ĠVik tor\",\"N ESS\",\"B ACK\",\"Ġcomm ute\",\"ĠAna heim\",\"Ġfluct uations\",\"6 40\",\"Ġnood les\",\"ĠCop enhagen\",\"ĠT ide\",\"ĠGri zz\",\"ĠS EE\",\"Ġpip elines\",\"Ġsc ars\",\"end o\",\"ag us\",\"ĠE TF\",\"/ #\",\"ĠBec ome\",\"44 8\",\"Ġvis c\",\"ĠRecomm ended\",\"Ġj umper\",\"Ġcogn ition\",\"Ġassass in\",\"Ġwitness ing\",\"ĠSet up\",\"Ġl ac\",\"v im\",\"IS M\",\"p ages\",\"SS L\",\"35 8\",\"Ġad ject\",\"indust rial\",\"l ore\",\"cher y\",\"Ġgl itter\",\"Ġc alf\",\"Flor ida\",\"Ġspoil ers\",\"Ġsucceed s\",\"Ġch anting\",\"Ġslog ans\",\"ĠTr acy\",\"Vis it\",\"rol ogy\",\"Ġm ornings\",\"Ġline age\",\"Ġs ip\",\"Ġintense ly\",\"Ġflour ish\",\"ĠSle eping\",\"ĠF em\",\"or por\",\"ĠK lan\",\"ĠDar th\",\"h ack\",\"ĠNi elsen\",\"Ġtum ors\",\"Ġprocure ment\",\"ĠY orkshire\",\"Ġra ided\",\"K Y\",\"An na\",\"Ġ// [\",\"ĠDis order\",\"ĠMust ang\",\"ĠW en\",\"ĠTry ing\",\"s q\",\"Ġdeliver ies\",\"Ġshut ter\",\"Ġcere bral\",\"Ġbip olar\",\"ĠC N\",\"l ass\",\"j et\",\"Ġdeb ating\",\"> :\",\"Ġe agle\",\"gr ades\",\"ĠD ixon\",\"UG C\",\"M AS\",\"ĠDr aco\",\"ĠMach ines\",\"aff er\",\"Ġem an\",\"Â ²\",\"pr on\",\"ĠG ym\",\"Ġcompar atively\",\"ĠTrib unal\",\"PR O\",\"Ġle x\",\"Ġfert ile\",\"Ġdep ressing\",\"Ġsuperf icial\",\"ess ential\",\"ĠHun ters\",\"g p\",\"Ġprom inence\",\"L iber\",\"ĠAn cest\",\"ote chnology\",\"Ġm ocking\",\"ĠTra ff\",\"ĸ ļ\",\"Med ium\",\"I raq\",\"Ġpsychiat rist\",\"Quant ity\",\"ĠL ect\",\"Ġno isy\",\"5 20\",\"G Y\",\"Ġsl apped\",\"ĠM TV\",\"Ġpar a\",\"p ull\",\"Mult iple\",\"as her\",\"Ġn our\",\"ĠSe g\",\"Spe ll\",\"v ous\",\"ord ial\",\"Sen ior\",\"ĠGold berg\",\"ĠPl asma\",\"ne ed\",\"Ġmess enger\",\"ere t\",\"Ġteam ed\",\"Ġliter acy\",\"ĠLe ah\",\"ĠD oyle\",\"Ġem itted\",\"U X\",\"Ġev ade\",\"Ġm aze\",\"Ġwrong ly\",\"ĠL ars\",\"Ġstere otype\",\"Ġpled ges\",\"Ġarom a\",\"ĠM ET\",\"Ġac re\",\"ĠO D\",\"Ġf f\",\"Ġbrew eries\",\"ĠH ilton\",\"und le\",\"ĠK ak\",\"ĠThank fully\",\"ĠCan ucks\",\"in ctions\",\"ĠApp ears\",\"Ġco er\",\"Ġundermin ed\",\"ro vers\",\"And re\",\"Ġbl aze\",\"um ers\",\"Ġfam ine\",\"amp hetamine\",\"ulk an\",\"Am ount\",\"Ġdesper ation\",\"wik ipedia\",\"develop ment\",\"ĠCor inth\",\"uss ia\",\"Jack son\",\"L I\",\"N ative\",\"R s\",\"Oh io\",\"ĠKath leen\",\"F ortunately\",\"Ġattend ant\",\"ĠPre ferred\",\"ĠDid n\",\"ĠV s\",\"M is\",\"Ġrespond ent\",\"Ġb oun\",\"st able\",\"Ġp aved\",\"Ġunex pl\",\"ĠChe ney\",\"L M\",\"ĠC ull\",\"bl own\",\"Ġconfront ing\",\"oc ese\",\"serv ing\",\"W i\",\"ĠLith uania\",\"ann i\",\"Ġst alk\",\"h d\",\"Ġv ener\",\"AP H\",\"ynchron ous\",\"UR R\",\"um ably\",\"hist oric\",\"H alf\",\"H ay\",\"Ġresil ience\",\"spe ction\",\"Ġabandon ing\",\"O bs\",\"ĠDeb bie\",\"Ġgrad ient\",\"ĠPl aint\",\"ĠCan al\",\"AR CH\",\"Ġexpans ive\",\"Ġfun g\",\"Ġb ounced\",\"U nd\",\"Ġprec autions\",\"Ġclar ification\",\"Ġd agger\",\"Ġgri ps\",\"ĠÂ µ\",\"ĠRiver a\",\"ĠUnd ead\",\"is ites\",\"ĠFIR ST\",\"Ã± o\",\"aud i\",\"Ġhost ages\",\"Ġcompl iant\",\"Ġal umni\",\"Se ven\",\"Ġcyber security\",\"e ither\",\"Col lect\",\"Ġinvari ably\",\"ĠS oci\",\"Ġlaw maker\",\"Ġa le\",\"ĠPerson ally\",\"N azi\",\"Ġcustom ization\",\"ĠPro c\",\"ĠSask atchewan\",\"eat uring\",\"Ġsp ared\",\"Ġdiscontin ued\",\"Ġcomput ational\",\"ĠMotor ola\",\"Ġsuprem acist\",\"government al\",\"Ġparad ise\",\"ĠDown ing\",\"ĠNik on\",\"Ġcat alyst\",\"ber ra\",\"Tor onto\",\"8 75\",\"bet a\",\"ĠMac ron\",\"Ġunreal istic\",\"ve ctor\",\"ĠVeh icles\",\"it iveness\",\"ĠR V\",\"ĠCol bert\",\"s in\",\"o ji\",\"ent in\",\"ĠKr ish\",\"hell o\",\"ff ield\",\"ok y\",\"ĠT ate\",\"Ġmap le\",\"Ġa ids\",\"chem ical\",\"33 4\",\"n uts\",\"ĠWar p\",\"Ġx x\",\"ĠRob b\",\"umer ous\",\"_- _\",\"ft ime\",\"ĠV W\",\"Ġw inger\",\"ĠD ome\",\"t ools\",\"ĠP V\",\"ĠGe orgetown\",\"Ġg eared\",\"Ġjihad ists\",\"Ġc p\",\"Ġster oids\",\"M other\",\"cler osis\",\"ĠDR M\",\"nes ia\",\"Ġl inger\",\"Ġimm ersive\",\"ĠC OUN\",\"Ġoutwe igh\",\"ens ual\",\"B and\",\"Ġtransform s\",\"mat ched\",\"ps ons\",\"ĠJud icial\",\"f actor\",\"Ġrefer ral\",\"Ġodd ly\",\"ĠW enger\",\"B ring\",\"ĠB ows\",\"60 2\",\"IC LE\",\"Ġl ions\",\"ĠAcad emic\",\"ĠTh orn\",\"ĠRa ider\",\"kef eller\",\"St orage\",\"L ower\",\"ĠOr t\",\"ĠEqu ality\",\"AL T\",\"ĠS OC\",\"T ypes\",\"Ġl yn\",\"ĠAss et\",\"co at\",\"TP P\",\"C VE\",\"ĠPione er\",\"app lication\",\"Mod ern\",\"ĠH K\",\"En vironment\",\"Al right\",\"R ain\",\"IP P\",\"ĠShi ite\",\"Ġm ound\",\"ĠAb ilities\",\"cond ition\",\"St aff\",\"Ġcompet ence\",\"ĠM oor\",\"ĠDi ablo\",\"Ġwith held\",\"Ġost ensibly\",\"ĠB rom\",\"Ġms g\",\"Ġden omin\",\"ĠRef erences\",\"ĠF P\",\"Ġplun ged\",\"Ġp amph\",\"m oving\",\"cent ral\",\"Ġdown right\",\"Ġf ading\",\"T al\",\"T yp\",\"ĠTh y\",\"uk es\",\"it he\",\"Ġo ve\",\"Ġbatt led\",\"Ġseaf ood\",\"Ġfig ur\",\"ĠR D\",\"c rop\",\"Ġsqu ads\",\"{ \\\\\",\"à ¹\",\"ĠE h\",\"Ġinterview ing\",\"ĠQ in\",\"Ġas piring\",\"PL IC\",\"Ġcla uses\",\"ĠG ast\",\"ĠN ir\",\"Ġl uggage\",\"Ġh ose\",\"Ġsystem d\",\"Ġdesc ending\",\"ĠRev ised\",\"ĠR ails\",\"al ign\",\"70 9\",\"33 7\",\"Ġf ug\",\"charg ing\",\"t ags\",\"Ġut er\",\"k ish\",\"WAR NING\",\"49 0\",\"prof its\",\"Ġvoy age\",\"Ġa ce\",\"ĠV anguard\",\"ĠT anks\",\"ĠM uk\",\"Ġ2 26\",\"S afe\",\"Ar mor\",\"Ġvolcan ic\",\"Ġwom b\",\"ĠM IL\",\"Ġbegin ner\",\"ĠRec ogn\",\"ĠA AP\",\"PL AY\",\") !\",\"Ġdetect ing\",\"c n\",\"Ġbre aches\",\"Bas ically\",\"ĠP ag\",\"ĠMunicip al\",\"ĠInd ie\",\"ĠL af\",\"ĠDis able\",\"ĠOl son\",\"Ġrest rained\",\"Ġrul ings\",\"Ġhum ane\",\"ev ents\",\"ĠCinem a\",\"display Text\",\"ĠH atch\",\"action Date\",\"onna issance\",\"Ġassault ing\",\"ĠL ug\",\"CH AT\",\"Ġvig orous\",\"ĠPer se\",\"Ġintoler ance\",\"ĠSnap chat\",\"ĠSh arks\",\"Ġd ummy\",\"ĠDi agn\",\"ĠGu itar\",\"im eters\",\"40 3\",\"RE G\",\"A x\",\"Ġsepar ates\",\"ĠMah m\",\"Ġt v\",\"j ah\",\"O OL\",\"C irc\",\"ĠWinds or\",\"uss ian\",\"Ġintu ition\",\"Ġdis dain\",\"ĠDon ovan\",\"Ġ2 21\",\"E mb\",\"Ġcondem ning\",\"Ġgener osity\",\"zz y\",\"Ġpant ies\",\"ĠPre vent\",\"Action Code\",\"AN A\",\"34 2\",\"external ActionCode\",\"Ġspec ifying\",\"Ġcryst all\",\"J ere\",\"Ġru pt\",\"ĠApp rentice\",\"Ġprof iling\",\"Ð º\",\"St rike\",\"Ġsid eline\",\"Ġoblig ated\",\"Ġocc ult\",\"Ġbureaucr atic\",\"ant ically\",\"rupt ed\",\"neg ative\",\"ĠEthiop ia\",\"ĠC ivic\",\"Ġins iders\",\"el igible\",\"ĠTV s\",\"ĠB AR\",\"ĠT I\",\"i ologist\",\"ĠA IR\",\"Ġsubstit uted\",\"Ar ab\",\"ĠS aul\",\"ĠY og\",\"p rem\",\"Ġbuild ers\",\"Ġstation ary\",\"Ġdoubt ful\",\"Ġvig orously\",\"Ġthr illing\",\"Ph ysical\",\"ĠCare y\",\"ĠHyd ra\",\"geon ing\",\"ĠS ly\",\"y ton\",\"Ġborrow ers\",\"ĠPark inson\",\"Ġ ë\",\"ĠJama ica\",\"Ġsat ir\",\"Ġinsurg ents\",\"ĠF irm\",\"Ġis ot\",\"ĠK arn\",\"our ning\",\"ak ens\",\"doc s\",\"l ittle\",\"ĠMon aco\",\"CL ASS\",\"Tur key\",\"L y\",\"ĠCon an\",\"ass ic\",\"Ġstar red\",\"ĠPac ers\",\"et ies\",\"Ġt ipping\",\"M oon\",\"ĠR w\",\"s ame\",\"Ġcav ity\",\"Ġgo of\",\"ĠZ o\",\"Sh ock\",\"um mer\",\"Ġemphas izes\",\"Ġreg rett\",\"Ġnovel ty\",\"Ġen vy\",\"ĠPass ive\",\"r w\",\"50 5\",\"Ġind ifferent\",\"ĠR ica\",\"ĠHim self\",\"ĠFred die\",\"Ġad ip\",\"ä¸ Ģ\",\"Ġbreak out\",\"Ġhur ried\",\"ĠHu ang\",\"ĠD isk\",\"Ġro aming\",\"?????- ?????-\",\"U V\",\"ĠRick y\",\"ĠS igma\",\"Ġmarginal ized\",\"Ġed its\",\"Ġ30 4\",\"mem ory\",\"Ġspec imen\",\"29 3\",\"ãģ ¯\",\"Ġvert ically\",\"Ġaud ition\",\"ĠHe ck\",\"Ġc aster\",\"ĠHold ings\",\"ad al\",\"ĠC ron\",\"ĠL iam\",\"Ġdef lect\",\"P ick\",\"ĠDeb ug\",\"RE F\",\"Ġvers atility\",\"ot hes\",\"class ified\",\"ĠMah ar\",\"ĠH ort\",\"C ounter\",\"st asy\",\"not iced\",\"33 1\",\"ĠSh im\",\"f uck\",\"ĠB ie\",\"Ġair ing\",\"ĠPro tein\",\"ĠHold ing\",\"Ġspect ators\",\"ili ated\",\"ĠThat cher\",\"n osis\",\"ãĥ¼ ãĥ³\",\"Te le\",\"B oston\",\"ĠTem pl\",\"st ay\",\"Ġdecl arations\",\"47 9\",\"Vol ume\",\"ĠDesign er\",\"ĠOver watch\",\"id ae\",\"Ġon wards\",\"Ġn ets\",\"ĠMan ila\",\"part icularly\",\"Ġpolit ic\",\"o other\",\"Ġport raits\",\"Ġpave ment\",\"c ffff\",\"Ġs aints\",\"Ġbegin ners\",\"ES PN\",\"Ġshort comings\",\"âķĲ âķĲ\",\"Ġcom et\",\"ĠOrgan ic\",\"qu el\",\"Ġhospital ized\",\"Bre ak\",\"Ġpe el\",\"dyl ib\",\"asp x\",\"ur ances\",\"ĠT IM\",\"P g\",\"Ġread able\",\"ĠMal ik\",\"Ġm uzzle\",\"Ġbench marks\",\"d al\",\"ĠV acc\",\"ĠH icks\",\"60 9\",\"ĠB iblical\",\"he ng\",\"Ġover load\",\"ĠCivil ization\",\"Ġimm oral\",\"Ġf ries\",\"ãĤ Ĵ\",\"Ġreprodu ced\",\"Ġform ulation\",\"j ug\",\"ire z\",\"g ear\",\"Ġco ached\",\"Mp Server\",\"ĠS J\",\"ĠK w\",\"In it\",\"d eal\",\"ĠO ro\",\"ĠL oki\",\"ĠSong s\",\"Ġ23 2\",\"ĠLou ise\",\"asion ally\",\"Ġunc ond\",\"olly wood\",\"Ġprogress ives\",\"ĠEn ough\",\"ĠDo e\",\"Ġwreck age\",\"Ġbr ushed\",\"ĠBase Type\",\"Ġz oning\",\"ish able\",\"het ically\",\"ĠC aucus\",\"ĠH ue\",\"Ġk arma\",\"ĠSport ing\",\"Ġtrad er\",\"Ġseem ing\",\"ĠCapt ure\",\"4 30\",\"b ish\",\"Ġt unes\",\"Ġindo ors\",\"ĠSp here\",\"ĠD ancing\",\"TER N\",\"Ġno b\",\"ĠG ST\",\"m aps\",\"Ġpe ppers\",\"F it\",\"Ġoverse es\",\"ĠRabb i\",\"ĠR uler\",\"vert ising\",\"off ice\",\"xx x\",\"Ġra ft\",\"Ch anged\",\"Ġtext books\",\"L inks\",\"ĠO mn\",\"ãĢ ĳ\",\"Ġinconven ience\",\"ĠDon etsk\",\"= ~\",\"Ġimplicit ly\",\"Ġboost s\",\"ĠB ones\",\"ĠBo om\",\"Cour tesy\",\"Ġsens ational\",\"AN Y\",\"Ġgre edy\",\"ed en\",\"Ġinex per\",\"ĠL er\",\"ĠV ale\",\"Ġtight en\",\"ĠE AR\",\"ĠN um\",\"Ġancest or\",\"S ent\",\"ĠH orde\",\"urg ical\",\"all ah\",\"Ġsa p\",\"amb a\",\"ĠSp read\",\"tw itch\",\"Ġgrand son\",\"Ġfract ure\",\"Ġmoder ator\",\"ĠSe venth\",\"ĠRe verse\",\"Ġestim ation\",\"Cho ose\",\"Ġpar ach\",\"Ġbar ric\",\"ãĢ Ĳ\",\"Ġcomp ass\",\"Ġall ergic\",\"âĢ ķ\",\"OT HER\",\"err illa\",\"Ġw agon\",\"Ġz inc\",\"Ġrub bed\",\"ĠFull er\",\"ĠLuxem bourg\",\"ĠHoo ver\",\"Ġli ar\",\"ĠEven ing\",\"ĠCob b\",\"est eem\",\"Ġselect or\",\"ĠB rawl\",\"is ance\",\"ĠE k\",\"Ġtro op\",\"Ġg uts\",\"ĠApp eal\",\"ĠTibet an\",\"Ġrout ines\",\"ĠM ent\",\"Ġsummar ized\",\"steam apps\",\"Ġtr anqu\",\"Ġ19 29\",\"or an\",\"ĠAut hent\",\"Ġg maxwell\",\"Ġappre hens\",\"Ġpo ems\",\"Ġsa usage\",\"ĠWeb ster\",\"ur us\",\"Ġthem ed\",\"Ġl ounge\",\"Ġcharg er\",\"Sp oiler\",\"Ġsp illed\",\"h og\",\"ĠSu nder\",\"ĠA in\",\"ĠAng ry\",\"Ġdis qual\",\"ĠFrequ ency\",\"ĠEther net\",\"Ġhel per\",\"Per cent\",\"Ġhorr ifying\",\"Ġa il\",\"ĠAll an\",\"EE E\",\"ĠCross ing\",\"44 9\",\"Ġh olog\",\"ĠPuzz les\",\"ĠGo es\",\"eren n\",\"60 4\",\"ãģ ı\",\"ĠRaf ael\",\"Ġatt en\",\"ĠE manuel\",\"Ġup ro\",\"ĠSus p\",\"P sych\",\"ĠTr ainer\",\"ĠN ES\",\"ĠHun ts\",\"bec ue\",\"Ġcounsel or\",\"R ule\",\"Ġtox ins\",\"Ġb anners\",\"r ifice\",\"Ġgreet ing\",\"Ġfren zy\",\"Ġall ocate\",\"Ġ* )\",\"ex pr\",\"50 3\",\"ĠCh ick\",\"ĠT orn\",\"Ġconsolid ation\",\"ĠF letcher\",\"sw itch\",\"fr ac\",\"cl ips\",\"ĠMcK in\",\"ĠLun ar\",\"Mon th\",\"IT CH\",\"Ġscholar ly\",\"rap ed\",\"39 8\",\"Ġ19 10\",\"Ġe greg\",\"Ġin secure\",\"Ġvict orious\",\"cffff cc\",\"Ġsing led\",\"Ġel ves\",\"ĠW ond\",\"bur st\",\"Ġcam oufl\",\"ĠBL ACK\",\"Ġcondition ed\",\"ç ī\",\"ans wered\",\"Ġcompuls ory\",\"asc ist\",\"Ġpodcast s\",\"ĠFrank furt\",\"bn b\",\"Ġne oliberal\",\"ĠKey board\",\"ĠBel le\",\"w arm\",\"Ġtrust s\",\"Ġins ured\",\"ĠBu cc\",\"us able\",\"60 7\",\"ĠPl ains\",\"Ġ18 90\",\"Ġsabot age\",\"Ġlod ged\",\"f elt\",\"Ġg a\",\"ĠN arc\",\"ĠSal em\",\"Ġsevent y\",\"ĠBl ank\",\"p ocket\",\"Ġwhis per\",\"Ġm ating\",\"om ics\",\"ĠSal man\",\"ĠK ad\",\"Ġan gered\",\"Ġcoll isions\",\"Ġextraord inarily\",\"Ġcoerc ion\",\"G host\",\"b irds\",\"è Ģ\",\"k ok\",\"Ġper missible\",\"avor able\",\"Ġpo inters\",\"Ġdiss ip\",\"ac i\",\"Ġtheat rical\",\"ĠCos mic\",\"Ġforget ting\",\"Ġfinal ized\",\"å¤ §\",\"y out\",\"l ibrary\",\"Ġbo oming\",\"ĠBel ieve\",\"ĠTe acher\",\"ĠL iv\",\"ĠGOOD MAN\",\"ĠDomin ican\",\"OR ED\",\"ĠPart ies\",\"Ġprecip itation\",\"ĠSl ot\",\"R oy\",\"ĠComb ined\",\"Ġinteg rating\",\"Ġch rome\",\"Ġintest inal\",\"ĠRe bell\",\"Ġmatch ups\",\"Ġblock buster\",\"ĠLore n\",\"ĠLe vy\",\"Ġpre aching\",\"ĠS ending\",\"ĠPur pose\",\"ra x\",\"f if\",\"Ġauthor itative\",\"ĠP ET\",\"ast ical\",\"Ġdish on\",\"Ġchat ting\",\"Ġ\\\"$ :/\",\"Connect ion\",\"Ġrecre ate\",\"Ġdel inqu\",\"Ġbro th\",\"ĠD irty\",\"ĠAd min\",\"z man\",\"Ġscholars hips\",\"Ġ25 3\",\"cont act\",\"als a\",\"7 67\",\"c reen\",\"abb age\",\"Ġ19 15\",\"Ġbl ended\",\"Ġal armed\",\"L anguage\",\"35 6\",\"Ġbl ends\",\"ĠCh anged\",\"W olf\",\"Ġhe pat\",\"Creat ing\",\"Ġper secut\",\"Ġsweet ness\",\"art e\",\"Ġforfe iture\",\"ĠRober to\",\"im pro\",\"N FL\",\"ĠMag net\",\"Det ailed\",\"Ġinsign ificant\",\"ĠPOL IT\",\"ĠBB Q\",\"ĠC PS\",\"Ġse aw\",\"amin er\",\"m L\",\"end if\",\"f inals\",\"Ġ26 5\",\"u ish\",\"Ġ} )\",\"ĠPro blems\",\"Ġem blem\",\"Ġserious ness\",\"Ġpars ing\",\"Ġsubst itution\",\"Ġpress ured\",\"Ġrecy cled\",\"ale b\",\"Rub y\",\"Ġprof iciency\",\"Dri ver\",\"ĠW ester\",\": '\",\"AF TA\",\"Ġm antle\",\"ĠClay ton\",\"fl ag\",\"Ġpractition er\",\"c overed\",\"ĠSt ruct\",\"add afi\",\"4 25\",\"ĠTown ship\",\"ĠHyd ro\",\"Lou is\",\"34 3\",\"Ġcond o\",\"ĠT ao\",\"Ġutil ization\",\"Ġnause a\",\"ĠDem s\",\"rid ges\",\"p ause\",\"Ġform ulas\",\"Ġchall enger\",\"37 6\",\"Ġdefect ive\",\"ĠRail way\",\"ĠPub Med\",\"Ġyog urt\",\"l bs\",\"ĠNor folk\",\"OP E\",\"ĠMood y\",\"Ġdistribut or\",\"Ġscroll s\",\"Ġextract s\",\"St an\",\"Ġv iability\",\"Ġexp oses\",\"Ġstar vation\",\"ĠStep s\",\"ĠD odd\",\"f ew\",\"ST D\",\"33 2\",\"Ġclos ures\",\"Ġcomplement ary\",\"ĠS asha\",\"ump y\",\"Ġmon et\",\"Ġartic ulate\",\"ĠDo ct\",\"k iller\",\"Ġsc rim\",\"Ġ2 64\",\"Ġprost itutes\",\"Ġse vered\",\"Ġattach ments\",\"Ġcool ed\",\"L ev\",\"ĠF alk\",\"f ail\",\"Ġpolic eman\",\"ĠD ag\",\"Ġpray ed\",\"ĠK ernel\",\"Ġcl ut\",\"Ġc ath\",\"Ġan omaly\",\"St orm\",\"em aker\",\"ĠBreak fast\",\"ul i\",\"o ire\",\"J J\",\"h z\",\"Oper ation\",\"ĠS ick\",\"35 4\",\"ĠGuatem ala\",\"R ate\",\"Ġexp osures\",\"f aces\",\"ĠArch ae\",\"ra f\",\"ĠM ia\",\"Ġ20 25\",\"Ġop aque\",\"Ġdisgu ised\",\"ĠHead quarters\",\"S ah\",\"Ġp ots\",\"9 78\",\"ĠM alf\",\"Ġfrown ed\",\"Ġpoison ous\",\"ĠCon vers\",\"ee ks\",\"Ġcr ab\",\".\\\" \\\"\",\"Ġtre ason\",\"Ġr anc\",\"Ġescal ating\",\"Ġwar r\",\"Ġmob s\",\"Ġl amps\",\"ĠSun shine\",\"ĠBrun swick\",\"Ph ones\",\"Ġspe lled\",\"ĠSk ip\",\"Ġ20 50\",\"Ġ19 11\",\"ĠPl uto\",\"ĠAm end\",\"Ġme ats\",\"38 7\",\"Ġst omp\",\"ĠZh ou\",\"ĠLevi athan\",\"ĠHaz ard\",\"ad v\",\"ĠOr well\",\"Ġal oud\",\"Ġb umper\",\"ĠAn arch\",\"ub untu\",\"ĠSer ious\",\"f itting\",\"ĠOption al\",\"ĠCec il\",\"RE AM\",\"Ġser otonin\",\"Ġcultiv ate\",\"ag ogue\",\"} \\\\\",\"Ġmos ques\",\"ĠSun ny\",\"Ġre active\",\"rev olution\",\"ĠL up\",\"ĠFed ora\",\"Ġdefense man\",\"ĠV ID\",\"ist ine\",\"Ġdrown ing\",\"ĠBroad casting\",\"Ġthr iller\",\"ĠS cy\",\"Ġacceler ating\",\"Ġdirect s\",\"od ied\",\"b ike\",\"d uration\",\"Ġpain fully\",\"R edd\",\"Ġproduct ions\",\"Ġg ag\",\"Ġwh ist\",\"Ġs ock\",\"Ġinf initely\",\"ĠConc ern\",\"ĠCit adel\",\"Ġlie u\",\"Ġcand les\",\"ogene ous\",\"arg er\",\"Ġheaven ly\",\"inflamm atory\",\"Per formance\",\"C s\",\"ruct ose\",\"az aki\",\"Ġp essim\",\"Ġinf erence\",\"Ġpow d\",\"ĠZ oe\",\"Ġpain ts\",\"Ġd azz\",\"pt a\",\"-------- ---\",\"Ġins pir\",\"ĠExper imental\",\"ĠKn ife\",\"reg or\",\"b ors\",\"Ġshow ers\",\"rom eda\",\"Ġs aint\",\"Ġben ign\",\"ĠJ iang\",\"Ġenvision ed\",\"Ġsh roud\",\"IF T\",\"H O\",\"Ġsh uff\",\"ĠI CC\",\"Ġse greg\",\"Ġrevis it\",\"ighth ouse\",\"L i\",\"Ġsub strate\",\"ĠSe as\",\"ĠRew ard\",\"ĠH ep\",\"ĠBr ass\",\"s bm\",\"Ġelim inates\",\"Ġst amina\",\"ĠV AT\",\"ĠLo an\",\"Ġconst raint\",\"Ġappropri ated\",\"Ġp es\",\"ĠA LE\",\"r anging\",\"Ġ40 4\",\"39 2\",\"Ġintellectual s\",\"ach u\",\"Ġrestruct uring\",\"ĠLe vin\",\"Ġrun es\",\"Ġdelight ful\",\"Ġcarbohyd rates\",\"ĠMod els\",\"ĠExp o\",\"Ġtransport ing\",\"all oc\",\"Ġring ing\",\"S amsung\",\"Ġscarce ly\",\"ĠURL s\",\"ĠM AS\",\"Ġprot otypes\",\"Ġnarr ator\",\"ĠCPU s\",\"cd n\",\"ĠBart on\",\"Ġdecided ly\",\"ĠSh u\",\"ix ir\",\"oc ious\",\"ĠMy st\",\"N intendo\",\"Ġre use\",\"Ġforg iven\",\"F ew\",\"in ical\",\"n at\",\"Ġseam less\",\"ĠEv a\",\"ĠE VE\",\"ĠJ O\",\"land ers\",\"Ġso fter\",\"neg ie\",\"Ġtrans ient\",\"Ġorb ital\",\"Ġfulf il\",\"ĠK om\",\"Hop efully\",\"Ġdynam ically\",\"ĠHun ger\",\"å Ľ\",\"ĠArmen ia\",\"el man\",\"ber to\",\"Ġp ige\",\"ĠID s\",\"lim it\",\"Ġve ins\",\"Ġso aring\",\"p acks\",\"Gold en\",\"ĠCr ab\",\"ist or\",\"ĠR PM\",\"Ġ$ $\",\"g ression\",\"Ġjihad ist\",\"Ġgam ble\",\"Ġcare g\",\"Ġinf lated\",\"F ace\",\"ĠFire arms\",\"ĠEm manuel\",\"â Ŀ\",\"Ġsh ocks\",\"gr ab\",\"Ġspl end\",\"ĠHP V\",\"ab ortion\",\"Ab ove\",\"Ent ity\",\"play ers\",\"Ġcomm enced\",\"ul ence\",\"Ġfulfill ment\",\"Ġembod iments\",\"ĠW elfare\",\"Ġha il\",\"Ġ< @\",\"tt en\",\"Ġcat cher\",\"ĠJ azeera\",\"Ġvolcan o\",\"Ġstabil ize\",\"ĠHand ler\",\"Ġintens ified\",\"ĠAb rams\",\"Ġhum iliation\",\"p aced\",\"60 5\",\"ĠCent OS\",\"Spe cific\",\"Ġhe ed\",\"ĠC AM\",\"ĠGal ile\",\"D ie\",\"Ġabol ished\",\"ĠThom son\",\"ĠTe achers\",\"ĠW ass\",\"j ong\",\"ĠIS BN\",\"ĠAll ies\",\"sh ake\",\"å ·\",\"v ict\",\"How ard\",\"Ġde em\",\"Ġexceed ingly\",\"ĠSmart stocks\",\"ib e\",\"Ġdoor way\",\"Ġcompet ed\",\"ig mat\",\"Ġnational ists\",\"Ġg room\",\"ĠKe en\",\"Ġdispos able\",\"de cl\",\"ĠT olkien\",\"ĠSche me\",\"Ġb iod\",\"Ġav id\",\"ĠEl on\",\"ag ar\",\"ĠT SA\",\"R oman\",\"Ġartific ially\",\"Ġadvis ors\",\"X L\",\"ĠInf erno\",\"36 6\",\"Ġted ious\",\"ĠPhot ography\",\"ĠCar rie\",\"Ġtro pe\",\"ĠSand ra\",\"Ġdec imal\",\"Que en\",\"ĠGund am\",\"ĠO M\",\"ote ch\",\"N BA\",\"Ġ19 32\",\"Ġent renched\",\"ĠMar ion\",\"Ġfr aternity\",\"Lab our\",\"Hen ry\",\"Ġlat itude\",\"E ither\",\"Ġenh ances\",\"ĠPot ential\",\"Ġsh ines\",\"id ad\",\"Ġbread th\",\"Ġcapac ities\",\"ĠðŁ ĻĤ\",\"ĠBron x\",\"Ġsex es\",\"Ġdifferent iation\",\"Ġheavy weight\",\"ĠT aj\",\"d ra\",\"Ġmigr ate\",\"Ġexhaust ion\",\"ĠR UN\",\"els ius\",\"ĠCu omo\",\"Ġgu itars\",\"Ġcl ones\",\"ĠSom ew\",\"ĠP ry\",\"------------ -\",\"Ġwarr anted\",\"cy cles\",\"Ġsalv age\",\"Ġdis ks\",\"R ANT\",\"ĠNGO s\",\"ĠMart ian\",\"\\\":[ {\\\"\",\"Ġadd icts\",\"oj ure\",\"il let\",\"Ġamazing ly\",\"art ments\",\"p ixel\",\"ĠGPU s\",\"Lay out\",\"è £\",\"ĠTam il\",\"ĠBas il\",\"Ġimpart ial\",\"ĠSt ructure\",\"f ork\",\"b ryce\",\"Ġr idge\",\"ĠHamb urg\",\"ri ous\",\"Ġbl itz\",\"cig arettes\",\"Ġcan ned\",\"40 2\",\"Ġiron ically\",\"Ġcompassion ate\",\"ĠHaw kins\",\". #\",\"ĠCat hedral\",\"Ġrall ied\",\"in ternal\",\"Ġqu ota\",\"st akes\",\"T EXT\",\"m om\",\"Ġcomple tes\",\"Ġ23 8\",\"Ġsh rug\",\"ãĥ ĳ\",\"ĠN inth\",\"Ġrev ise\",\"ĠProv ider\",\"Ġtre acher\",\"Ġqu asi\",\"ĠPR ES\",\"Ġdep osition\",\"Ġconfidential ity\",\"iss ors\",\"Ġim balance\",\"Ġspan ning\",\"Ġang ular\",\"ĠC ul\",\"commun ication\",\"ĠNor a\",\"ĠGen ius\",\"op ter\",\"Ġs acked\",\"Sp ot\",\"Ġfine ly\",\"ĠCH R\",\"28 2\",\"w aves\",\"Pal est\",\"ĠRo hing\",\"N L\",\"è ¿\",\"Ġsh itty\",\"ĠSc alia\",\"4 75\",\"Pro gress\",\"Ġreferen cing\",\"Ġclass rooms\",\"ab ee\",\"Ġs od\",\"hes ion\",\"70 8\",\"ĠZucker berg\",\"ĠFin ish\",\"ĠScot ia\",\"ĠSav ior\",\"ĠInstall ation\",\"an tha\",\"( -\",\"Ġ30 2\",\"ĠP unk\",\"Ġcr ater\",\"yout u\",\"Ġro ast\",\"Ġinflu encing\",\"Ġd up\",\"ĠJ R\",\"ĠG rav\",\"Ġstat ure\",\"Ġbath rooms\",\"A side\",\"W iki\",\"me an\",\"ĠZ ak\",\"ĠOn es\",\"ĠN ath\",\"Ġhyper t\",\"Ġcommence ment\",\"C ivil\",\"Ġmoder ately\",\"Ġdistribut ors\",\"Ġbreast feeding\",\"Ġ9 80\",\"ĠS ik\",\"ĠC ig\",\"ĠAM ER\",\"R IP\",\"ĠCare er\",\"ust ing\",\"Ġmess ed\",\"Ġe h\",\"ĠJ ensen\",\"/ $\",\"Ġblack mail\",\"Ġconvers ions\",\"Ġscientific ally\",\"Ġmant ra\",\"p aying\",\"Ġiv ory\",\"ĠCour ts\",\"OU GH\",\"aunt let\",\"Ser ial\",\"B row\",\"ĠH undreds\",\"3 23\",\"Ġpe e\",\"Ġlin ux\",\"Ġsub mer\",\"ĠPrinc ipal\",\"48 5\",\"ĠD SL\",\"ĠCous ins\",\"Ġdoctr ines\",\"ĠAthlet ics\",\"Ġ3 15\",\"ĠK arma\",\"Ġatt ent\",\"ur ger\",\"Ġpresc ribe\",\"Ġenc aps\",\"ĠC ame\",\"Ġsecret ive\",\"ĠCr imes\",\"d n\",\"C lean\",\"ĠEgypt ians\",\"ĠCar penter\",\"Ġ ll\",\"H um\",\"ĠMil o\",\"Ġcapital ists\",\"Ġbrief ed\",\"T we\",\"ĠBas in\",\"elve t\",\"M os\",\"Ġplun ge\",\"ĠKa iser\",\"ĠFu j\",\"ill in\",\"Ġsafegu ards\",\"Ġo ste\",\"ĠOpportun ity\",\"ĠM afia\",\"ĠCall ing\",\"ap a\",\"ur ban\",\"br ush\",\"ill ard\",\"c Ã©\",\"int elligence\",\"ĠL ob\",\"ĠDru id\",\"Ġsm oother\",\"Ġfoot ing\",\"Ġmotor ists\",\"arc ity\",\"Ġmascul inity\",\"Ġm ism\",\"Ġabdom inal\",\"ĠTa vern\",\"ĠR oh\",\"Ġesc apes\",\"s igned\",\"Anth ony\",\"Ġsacrific ing\",\"Ġintim acy\",\"Ġan terior\",\"ĠK od\",\"Ġmot if\",\"Ġg raz\",\"Ġvisual ization\",\"Ġguitar ist\",\"ĠTro tsky\",\"m agic\",\"D ar\",\"ĠMor i\",\"Ġw ards\",\"Ġtoile ts\",\"l est\",\"Ġtele port\",\"ĠSund ays\",\"ĠPl at\",\"ET S\",\"Ġe Sports\",\"Pat rick\",\"ĠK atherine\",\"en ko\",\"Ġhas sle\",\"ĠM ick\",\"gg les\",\"Ġh ob\",\"aint ain\",\"Ġair borne\",\"Ġsp ans\",\"Ġch ili\",\"Ġa perture\",\"Ġvolunte ered\",\"ĠInc ident\",\"ĠF res\",\"ĠVeter an\",\"augh tered\",\"ing o\",\"Ġun insured\",\"CL OSE\",\"Ġf use\",\"Ġer otic\",\"Ġadvert ise\",\"ra ising\",\"Text ure\",\"Ġatt ends\",\"ĠRE AL\",\"udd led\",\"Ġsm oot\",\"Ġ30 5\",\"ĠWill is\",\"Ġbl ond\",\"An alysis\",\"ĠV T\",\"on ica\",\"Ġstrongh old\",\"R F\",\"N M\",\". >>\",\"Ġprosper ous\",\"Ġbo asted\",\"29 2\",\"ĠManufact uring\",\"PR ESS\",\"g ren\",\"Ġpharm acy\",\"ĠRoc kefeller\",\"k ai\",\"Ġth umbs\",\"ĠH ut\",\"Ġmother board\",\"Ġguard ians\",\"ĠAl ter\",\"ll ular\",\"Ġsh ack\",\"Ġwise ly\",\"Ġback bone\",\"erv a\",\"Ġsu icides\",\"ĠMcG regor\",\"ij ah\",\"E mer\",\"ĠB rav\",\"Ġdesign ate\",\"P OST\",\"produ ced\",\"Ġcleans ing\",\"irl wind\",\"ex istent\",\"ĠHum ph\",\"ĠPay ne\",\"Ġv ested\",\"Å ¡\",\"Ġstring ent\",\"ion a\",\"Ġuns ub\",\"Ġsum med\",\"ĠHer cules\",\"sub ject\",\"ĠR agnar\",\"ĠN os\",\"Ġcharacter ization\",\"Ġsav vy\",\"ĠDaw son\",\"ĠCas ino\",\"Ġf ri\",\"ĠBar rier\",\"Ġmis information\",\"Ġins ulation\",\"Ġcorrid ors\",\"Ġair planes\",\"ĠNo ct\",\"ah i\",\"Ġ19 16\",\"k b\",\"arm ac\",\"Ġsh un\",\"Ġsche ma\",\"Ġhorr ified\",\"Ġ23 9\",\"aund ers\",\"N B\",\"i ates\",\"er ity\",\"ĠSh ard\",\"Ġr arity\",\"Ġgroup ed\",\"ĠGh ana\",\"again st\",\"ĠBi ological\",\"ĠA ware\",\"ow ell\",\"Ï Ħ\",\"ĠBe au\",\"sh aw\",\"H ack\",\"ĠJul ius\",\"US S\",\"ol son\",\"aun a\",\"c ru\",\"ĠMaur ice\",\"ĠI k\",\"Ġsequ encing\",\"Ġradical s\",\"Ġ( ?,\",\"v irtual\",\"Ġany ways\",\"Ġreper c\",\"Ġhand lers\",\"Ġhes itant\",\"é ĥ\",\"ĠM F\",\"ple mentation\",\"ass ociated\",\"Ġcampaign ed\",\"ĠY ue\",\"ut ations\",\"ĠY oga\",\"Ġsim mer\",\"Ġro ds\",\"Ġmel ody\",\"Ġconv oy\",\"v ideos\",\"Ġscreen ed\",\"N eg\",\"ochem ical\",\"Ġ( ))\",\"Ġultr as\",\"Ġant ip\",\"ĠIsland ers\",\"70 4\",\"Ġfet ish\",\"Ġridic ulously\",\"ĠK art\",\"Ġmitochond rial\",\"Ġinterf ering\",\"Build er\",\"Ġover fl\",\"Ġac ne\",\"ĠM ud\",\"ĠK err\",\"f lex\",\"ĠPost al\",\"ĠBalt ic\",\"47 7\",\"ĠPers ons\",\"our age\",\"H B\",\"ĠM use\",\"ĠImm ortal\",\"ĠDri ving\",\"Ġpet itions\",\"Ġsubsc ript\",\"Ġs orce\",\"ĠProcess or\",\"ut on\",\"S ony\",\"Ġph on\",\"Ġr aced\",\"ĠAnth rop\",\"Ġday time\",\"ĠEx ercise\",\"Add ing\",\"Ġeng ages\",\"ĠQual comm\",\"Ġmir acles\",\"Ġmem es\",\"ĠDr ink\",\"ĠOri oles\",\"Ġhair s\",\"ĠPol ar\",\"ath om\",\"Ġsl ippery\",\"ĠR emy\",\"Ġcar amel\",\"ĠY EAR\",\"Ġal k\",\"I gn\",\"a ution\",\"ĠMer lin\",\"ĠC ran\",\"Ġap ologies\",\"Ġ4 10\",\"Ġout ing\",\"ĠMem ories\",\"app ointed\",\"Ġcount ered\",\"u ld\",\"pos ing\",\"Ġfire wall\",\"ĠW ast\",\"ĠW et\",\"work ed\",\"se ller\",\"Ġrepe aled\",\"ere o\",\"ass uming\",\"BL IC\",\"m ite\",\"ĠCEO s\",\"ĠChap el\",\"ellig ent\",\"________________ ________\",\"D og\",\"Ġw art\",\"Ġsubsc riber\",\"s ports\",\"Ġbe gged\",\"ĠM V\",\"Ġsem if\",\"eth ical\",\"Ġpre ach\",\"Ġrev ital\",\"Ġpun itive\",\"Ġshort cuts\",\"Ġinstit uted\",\"ĠWars aw\",\"Ġabdom en\",\"ĠK ING\",\"Ġsuper intendent\",\"Ġf ry\",\"ĠGe o\",\"T OR\",\"Ġcontrad ictions\",\"apt ic\",\"Ġlandsc apes\",\"b ugs\",\"Ġcl ust\",\"Ġvol ley\",\"c ribed\",\"Ġt andem\",\"Ġrob es\",\"WH AT\",\"Ġpromot er\",\"Ġel oqu\",\"review ed\",\"ĠD K\",\"ĠPl ato\",\"Ġf ps\",\"T ank\",\"ĠDer rick\",\"Ġpriorit ize\",\"as per\",\"ĠHond uras\",\"ĠCom pleted\",\"ne c\",\"Ġm og\",\"n ir\",\"ĠMay o\",\"DE F\",\"st all\",\"in ness\",\"ĠVolks wagen\",\"Ġprec aution\",\"ĠM ell\",\"i ak\",\"ist ries\",\"Ġ24 8\",\"Ġoverl apping\",\"Sen ate\",\"ĠEnh ance\",\"res y\",\"rac ial\",\"OR TS\",\"ĠM ormons\",\"Str ong\",\"ĠCo ch\",\"Mex ico\",\"ĠMad uro\",\"Ġj ars\",\"Ġcan e\",\"W ik\",\"oll a\",\"iff erence\",\"Ġphysic ist\",\"ĠMag gie\",\"Ġ28 5\",\"Ġdep iction\",\"ĠMcL aren\",\"J u\",\"Ġsl ows\",\"Ġcommission ers\",\"ĠWill ow\",\"ĠExpl os\",\"hov ah\",\"Ġtechn ician\",\"Ġhom icides\",\"ĠFl av\",\"ĠTr uman\",\"Ġ100 00\",\"u ctor\",\"Ġsh ader\",\"News letter\",\"45 7\",\"Ġre ver\",\"Ġhard ened\",\"Ġwhere abouts\",\"Ġrede velop\",\"Ġcar bs\",\"Ġtra vers\",\"Ġsqu irrel\",\"Ġfoll ower\",\"Ġs ings\",\"50 8\",\"Ġrabb its\",\"emon ium\",\"Ġdocument ing\",\"Ġmisunder stood\",\") '\",\"R ick\",\"gg ies\",\"Ġprem ie\",\"Ġsk ating\",\"Ġpass ports\",\"Ġf ists\",\"aged don\",\"H aw\",\"AC P\",\"0 80\",\"ĠThough ts\",\"ĠCarl son\",\"Ġpriest hood\",\"h ua\",\"Ġdun geons\",\"ĠLo ans\",\"Ġant is\",\"Ġfamiliar ity\",\"ĠS abb\",\"op al\",\"ĠIn k\",\"st rike\",\"Ġc ram\",\"Ġlegal ized\",\"Ġcu isine\",\"Ġfib re\",\"Tra vel\",\"ĠMon ument\",\"OD Y\",\"eth y\",\"Ġinter state\",\"ĠP UR\",\"em porary\",\"ĠArab ian\",\"develop ed\",\"Ġsadd le\",\"Ġg ithub\",\"ĠOff er\",\"ĠIS P\",\"ro let\",\"ĠSUP ER\",\"ĠDen is\",\"Ġmultipl ier\",\"Ġstir red\",\"Interest ingly\",\"Ġcustom ary\",\"Ġbill ed\",\"he x\",\"Ġmultipl ied\",\"Ġfl ipping\",\"ĠCros by\",\"Ġfundament als\",\"ia e\",\"ĠPlay ed\",\"ĠAt om\",\"am azon\",\"ĠFl am\",\"ee z\",\"activ ated\",\"Ġtables poon\",\"Ġliberal ism\",\"ĠPal in\",\"ĠP atel\",\"N um\",\"ĠT AM\",\"Ġs urn\",\"ĠRel oaded\",\"Ġco ined\",\"\\\" ],\",\"ĠCl ash\",\"ĠAg u\",\"Ġprag matic\",\"ĠActiv ate\",\"Ġ8 02\",\"Ġtrail ers\",\"Ġsil hou\",\"Ġprob es\",\"Ġcirc us\",\"ĠB ain\",\"ĠLind say\",\"ĠAb bey\",\"Del ivery\",\"Ġconcess ion\",\"Ġgast ro\",\"ĠSpr ite\",\"Ä Ł\",\"and el\",\"Ġg imm\",\"Ġaut obi\",\"ĠT urtle\",\"Ġwonder fully\",\"ĠHar am\",\"ĠWorld wide\",\"ĠHand le\",\"Ġtheor ists\",\"Ġsle ek\",\"ĠZh u\",\"ograph ically\",\"EG A\",\"ĠOwn ers\",\"ath s\",\"ĠAntar ctic\",\"n atal\",\"=\\\" \\\"\",\"fl ags\",\"`` ``\",\"Ġs ul\",\"K h\",\"Ġpot assium\",\"Ġlinem an\",\"Ġcere al\",\"ĠSe asons\",\"Ġ20 22\",\"Ġmat hematic\",\"Ġastron omers\",\"prof essional\",\"Ġf ares\",\"cknow led\",\"Ġch i\",\"Ġyoung sters\",\"Ġmistaken ly\",\"Ġhem isphere\",\"ĠDiv inity\",\"r one\",\"Ġ\\\" ,\",\"r ings\",\"Ġattract s\",\"v ana\",\"å ¹\",\"C AP\",\"Ġplay list\",\"Ġpor ch\",\"ãģ £\",\"Ġincorpor ates\",\"Ġso ak\",\"Ġassert ing\",\"ĠTerror ism\",\"ĠP ablo\",\"J a\",\"ces ter\",\"Ġfear ing\",\"ĠPr ayer\",\"Ġescal ated\",\"G W\",\"Ġro be\",\"ĠBright on\",\"ac ists\",\"ĠSym phony\",\"ĠDwar f\",\"ĠPar ade\",\"ĠLe go\",\"Ġinex pl\",\"Ġl ords\",\"le af\",\"RA G\",\"l iber\",\"Ġcig ars\",\"ĠJe hovah\",\"60 6\",\"WIND OWS\",\"ĠLiber ia\",\"eb us\",\"He avy\",\"Ġl ubric\",\"ĠR W\",\"angu ages\",\"Ġnarrow ed\",\"com puter\",\"ĠE mber\",\"Ġmurder ing\",\"Ġdown stream\",\"ĠT uls\",\"ĠT ables\",\"Top ic\",\"ĠAcc uracy\",\"= /\",\"l ost\",\"ĠRe i\",\"Ġprogress es\",\"b ear\",\"Ġestablish ments\",\"Just in\",\"ĠPe ach\",\"ĠG omez\",\"å ¿\",\"ĠTri angle\",\"Id ent\",\"ĠH ive\",\"Res ources\",\"Ġmix es\",\"ĠAss uming\",\"M u\",\"Ġhyp oc\",\"Ġs ane\",\"ĠW an\",\"id ious\",\"Su ccess\",\"Ġ io\",\"Ang el\",\"Ġdanger ously\",\"ĠCreat ure\",\"W ORK\",\": [\",\"ĠKat rina\",\"List ener\",\"M iller\",\"ĠId lib\",\"h ang\",\"Ġcircum vent\",\"h ref\",\"Ġcel estial\",\"ĠWe eks\",\"ĠP ug\",\"ĠDal ton\",\"Ġsubpoen a\",\"uk u\",\"Ġpers isted\",\"pe i\",\"old ing\",\"ĠDoc uments\",\"ĠH ast\",\"ĠC ENT\",\"Ġprim er\",\"Ġsyn onymous\",\"Ġn ib\",\"om bs\",\"Ġnot ation\",\"ĠD ish\",\"ĠAt mosp\",\"Ġforb id\",\"ĠAN G\",\"pat tern\",\"l os\",\"Ġproject iles\",\"b rown\",\".\\\" ,\",\"ĠVen om\",\"Ġfierce ly\",\"ub lished\",\"ĠU ran\",\"ĠNic arag\",\"4 10\",\"ĠC AL\",\"OT OS\",\"ĠMir acle\",\"ĠEn chant\",\"Ġguard ing\",\"app end\",\"Att ach\",\"Ġlevel ed\",\"Ġcond oms\",\"ih ilation\",\"64 9\",\"Ġnight mares\",\"ĠTHE Y\",\"ĠST ART\",\"ĠK inn\",\"Ġroomm ate\",\"Ġhy giene\",\"o pping\",\"J ob\",\"Ġl vl\",\"ĠV ER\",\"ĠKe eping\",\"ab etic\",\"Ġformat ting\",\"eral a\",\"Ġrev isions\",\"Ġres urg\",\"T el\",\"ĠGood man\",\"35 3\",\"p od\",\"Ġind isp\",\"ĠTrans lation\",\"Ġg own\",\"ĠM und\",\"Ġc is\",\"Ġby stand\",\"col lect\",\"ĠPun jab\",\"act ively\",\"ĠG amb\",\"te ll\",\"Ġimport ing\",\"g encies\",\"Ġloc om\",\"ĠBr ill\",\"H oly\",\"ĠBer ger\",\"Ġshow down\",\"Ġrespond ers\",\"IL Y\",\"Ġt akedown\",\"le ted\",\"Ġmat tered\",\"Ġpredict ive\",\"Ġover lay\",\"G PU\",\"ĠV ick\",\"Ġconvey ed\",\"T ab\",\"pe er\",\"Sc an\",\"Ġdefensive ly\",\"v ae\",\"Ġappro ving\",\"Ġt iers\",\"ĠV ia\",\"quer ade\",\"ĠSaud is\",\"Ġdemol ished\",\"ĠProp he\",\"Ġmon o\",\"Ġhospital ity\",\"H AM\",\"ĠAri el\",\"M OD\",\"ĠTor ah\",\"Ġbl ah\",\"ĠBel arus\",\"erent ial\",\"ĠT uc\",\"Ġbank er\",\"39 7\",\"Ġmosqu it\",\"ĠScient ist\",\"ĠMus ical\",\"Ġh ust\",\"Sh ift\",\"Ġtor ment\",\"Ġstand off\",\"E duc\",\"ĠF og\",\"Ġampl ifier\",\"Sh ape\",\"Inst ance\",\"ĠCrit ics\",\"Ġda emon\",\"H ouston\",\"Ġmatt ress\",\"ĠID F\",\"Ġobsc ene\",\"ĠA mer\",\"hett i\",\"Ġcomp iling\",\"35 2\",\"vere tt\",\"ĠRed uction\",\"ist ration\",\"ĠBl essed\",\"ĠB achelor\",\"3 16\",\"Ġpr ank\",\"ĠVul can\",\"dd ing\",\"Ġm ourning\",\"ĠQu int\",\"ĠBl aster\",\"test ing\",\"Ġsed iment\",\">> >\",\"ĠE ternity\",\"ĠWH ERE\",\"ĠM aze\",\"Ġreact ing\",\"ĠAl v\",\"oms day\",\"ĠC RA\",\"Ġtransl ator\",\"Ġbog us\",\"at u\",\"We bsite\",\"oll s\",\"Ġbapt ism\",\"Ġs ibling\",\"ĠAut umn\",\"ve z\",\"ãģ® é\",\"gu ards\",\"Ge org\",\"assad ors\",\"ĠFre ud\",\"Ġcontin ents\",\"ĠReg istry\",\"Bern ie\",\"ĸļ å£«\",\"Ġtoler ant\",\"ĠU W\",\"Ġhor ribly\",\"99 5\",\"ĠMID I\",\"Ġimpat ient\",\"oc ado\",\"er i\",\"ĠWor st\",\"ĠNor ris\",\"ĠTalk ing\",\"Ġdef ends\",\"ens able\",\"Ġ20 21\",\"Ġanat omy\",\"L ew\",\"Ġdraw er\",\"ĠCan berra\",\"Ġpatri otic\",\"é¾įå ĸļå£«\",\"ĠAv g\",\"AR M\",\"Ġundis closed\",\"Ġfare well\",\"45 9\",\"b able\",\"ĠAll ison\",\"OL OG\",\"Ġcon co\",\"t ight\",\"ĠAC PI\",\"ĠM ines\",\"l ich\",\"ĠâĶ ľ\",\"represent ed\",\"200 000\",\"Ġenthusi ast\",\"OT S\",\"b il\",\"ĠIng redients\",\"Ġinvent or\",\"ĠMy SQL\",\"ÂłÂł Âł\",\"ĠAB OUT\",\"with in\",\"Ġm k\",\"B ul\",\"ĠF ake\",\"Ġdracon ian\",\"W a\",\"hel m\",\"ĠTer ran\",\"erv ille\",\"Ġcommon place\",\"SI ZE\",\"Ġ\\\" <\",\"re place\",\"ograph s\",\"ĠSE LECT\",\"inc ible\",\"ĠMost ly\",\"ĠShe ffield\",\"ĠID E\",\"ugg le\",\"Ġcit ations\",\"h urst\",\"ĠUn ix\",\"Ġunle ash\",\"ĠP iper\",\"ĠN ano\",\"Ġsucc umb\",\"Ġreluct ance\",\"Ġ25 00\",\"ĠMer chant\",\"Ġwire t\",\"Ġcomb os\",\"ĠBirth day\",\"Ġchar coal\",\"ĠU PS\",\"ĠFair fax\",\"Ġdrive way\",\"ĠT ek\",\"ĠP itch\",\"ove re\",\"Ġtechn icians\",\"ĠAct ual\",\"fl ation\",\"ĠF iscal\",\"ĠEm pty\",\"an amo\",\"Ġmag nesium\",\"Ġsl ut\",\"Ġgrow ers\",\"Invest igators\",\"( ):\",\"ĠS atellite\",\"ĠKe ynes\",\"miss ive\",\"l ane\",\"Ġb orough\",\"3 44\",\"ĠTE AM\",\"ĠBet hesda\",\"C V\",\"h ower\",\"ĠR AD\",\"Ġch ant\",\"ĠR iy\",\"Ġcompos itions\",\"Ġmild ly\",\"Ġmedd ling\",\"Ġag ility\",\"ane ers\",\"5 01\",\"Ġsyn th\",\"ling er\",\"29 1\",\"Ġex claimed\",\"Part y\",\"Ġcont amin\",\"ĠMan or\",\"ĠResp ond\",\"Ġpra ising\",\"Ġman ners\",\"fle et\",\"Sum mer\",\"ĠLy nd\",\"ĠDef initely\",\"gr im\",\"Ġbow ling\",\"st ri\",\"ç Ľ\",\"y nt\",\"Ġmand ates\",\"D IV\",\"Ġreconc ile\",\"view s\",\"ĠDam on\",\"vet te\",\"F lo\",\"ĠGreat est\",\"il on\",\"ic ia\",\"Ġportray al\",\"Ġcush ion\",\"50 4\",\"19 79\",\"oss al\",\"App lic\",\"sc ription\",\"Ġmit igation\",\"AT S\",\"p ac\",\"Ġer ased\",\"Ġdefic iencies\",\"ĠHolland e\",\"ĠX u\",\"Ġb red\",\"Ġpregn ancies\",\"f emin\",\"Ġem ph\",\"Ġpl anners\",\"Ġout per\",\"utter ing\",\"Ġperpet rator\",\"Ġm otto\",\"ĠEll ison\",\"ĠNE VER\",\"Ġadmitted ly\",\"AR I\",\"ĠAzerbai jan\",\"Ġmill isec\",\"Ġcombust ion\",\"ĠBott le\",\"ĠL und\",\"ĠP s\",\"ĠD ress\",\"Ġfabric ated\",\"Ġbat tered\",\"Ġs idel\",\"ĠNot ting\",\"Fore ign\",\"ĠJer ome\",\"0 20\",\"ĠAr bit\",\"Ġkn ots\",\"ĠR IGHT\",\"M oving\",\"ãģ Ļ\",\"Ġsur geries\",\"Ġcour thouse\",\"Ġm astered\",\"Ġhover ing\",\"ĠBr an\",\"ĠAl ison\",\"Ġsaf est\",\"m ilitary\",\"Ġbull ied\",\"Ġbar rage\",\"Read er\",\"ES E\",\"ĠGe ographic\",\"T ools\",\"3 14\",\"ĠGe ek\",\"ro th\",\"gl ers\",\"ĠF IN\",\"Ï ģ\",\"ĠA ston\",\"al tern\",\"48 8\",\"Ġveter in\",\"G amer\",\"Ġint el\",\"ren ches\",\"Sh ield\",\"Ġam nesty\",\"ĠB har\",\"Ġp iled\",\"Ġhonor able\",\"ĠInst itutes\",\"Ġso aked\",\"Ġcom a\",\"ĠE FF\",\"34 1\",\"by tes\",\"ĠG mail\",\"le in\",\"ĠCanad iens\",\"m aterial\",\"I l\",\"Ġinstruct ors\",\"ĠK Y\",\"Ġconce ive\",\"ub b\",\"ĠP ossible\",\"Ġeas ing\",\"ĠChrist ina\",\"Ġcar ic\",\"ĠHD R\",\"R OM\",\"Ġsho vel\",\"de lete\",\"Ġp uff\",\"ĠCh anging\",\"Ġseam lessly\",\"Att ribute\",\"Ġacqu isitions\",\"ak ery\",\"ĠE F\",\"Ġaut istic\",\"ĠT akes\",\"ĠPow der\",\"ĠSt ir\",\"5 10\",\"ĠBub ble\",\"sett ings\",\"ĠF owler\",\"Ġmust ard\",\"Ġmore over\",\"Ġcopyright ed\",\"ĠLED s\",\"15 00\",\"æ ī\",\"ĠH IS\",\"en f\",\"Ġcust od\",\"ĠH uck\",\"G i\",\"Ġim g\",\"An swer\",\"C t\",\"j ay\",\"ĠInf rastructure\",\"Ġfeder ally\",\"L oc\",\"Ġmicro bes\",\"Ġover run\",\"dd s\",\"ot ent\",\"adi ator\",\">>>> >>>>\",\"Ġtorn ado\",\"Ġadj ud\",\"Ġintrig ued\",\"Ġs i\",\"ĠRevel ation\",\"pro gress\",\"Ġburgl ary\",\"ĠSai yan\",\"ĠK athy\",\"Ġser pent\",\"ĠAndre as\",\"Ġcomp el\",\"ess ler\",\"ĠPl astic\",\"ĠAd vent\",\"ĠPos itive\",\"ĠQ t\",\"ĠHind us\",\"reg istered\",\"ular ity\",\"Ġrighteous ness\",\"Ġdemon ic\",\"u itive\",\"ĠB DS\",\"ĠGre gg\",\"c ia\",\"ĠCrus ade\",\"ĠSina i\",\"W ARE\",\"+ (\",\"Ġme ll\",\"Ġder ail\",\"y ards\",\"A st\",\"Ġnotice ably\",\"ĠO ber\",\"R am\",\"Ġun noticed\",\"Ġse q\",\"av age\",\"T s\",\"Ġ6 40\",\"Ġconced e\",\"Ġ] )\",\"F ill\",\"Ġcapt ivity\",\"ĠImprove ment\",\"ĠCrus ader\",\"ara oh\",\"M AP\",\"æ Ĺ\",\"Ġstr ide\",\"al ways\",\"F ly\",\"N it\",\"Ġal gae\",\"ĠCook ing\",\"ĠDo ors\",\"Mal ley\",\"Ġpolic emen\",\"ãģ į\",\"Ġastron aut\",\"access ible\",\"49 5\",\"ĠR AW\",\"cl iffe\",\"udic rous\",\"Ġdep ended\",\"al ach\",\"Ġvent ures\",\"ra ke\",\"Ġt its\",\"ĠH ou\",\"Ġcond om\",\"ormon al\",\"Ġind ent\",\"Ġupload ing\",\"Foot note\",\"Import ant\",\"Ġ27 1\",\"Ġmind ful\",\"Ġcont ends\",\"C ra\",\"Ġcal ibr\",\"ĠO ECD\",\"plug in\",\"F at\",\"ĠIS S\",\"ĠDynam ics\",\"ans en\",\"68 6\",\"' ),\",\"Ġsp rite\",\"Ġhand held\",\"ĠH ipp\",\"=~ =~\",\"Tr ust\",\"Ġsem antics\",\"ĠBund es\",\"ĠRen o\",\"ĠLiter ature\",\"s ense\",\"G ary\",\"ĠA eg\",\"ĠTr in\",\"EE K\",\"Ġcler ic\",\"ĠSS H\",\"Ġch rist\",\"Ġinv ading\",\"ib u\",\"Ġen um\",\"aur a\",\"Ġal lege\",\"ĠInc redible\",\"B BC\",\"Ġth ru\",\"Ġsa iled\",\"Ġem ulate\",\"Ġin security\",\"Ġc rou\",\"Ġaccommod ations\",\"Ġincompet ent\",\"Ġsl ips\",\"ĠEarth qu\",\"s ama\",\"IL LE\",\"Ġi Phones\",\"as aki\",\"Ġby e\",\"Ġar d\",\"Ġext ras\",\"Ġsl aughtered\",\"Ġcrowd funding\",\"res so\",\"Ġfil ib\",\"ĠER ROR\",\"ĠT LS\",\"e gg\",\"ĠIt al\",\"Ġen list\",\"ĠCatal onia\",\"ĠSc ots\",\"Ġser geant\",\"Ġdiss olve\",\"N H\",\"Ġstand ings\",\"ri que\",\"I Q\",\"Ġbenef iciary\",\"Ġaqu arium\",\"You Tube\",\"ĠPower Shell\",\"Ġbright est\",\"ĠWar rant\",\"S old\",\"Writ ing\",\"Ġbegin nings\",\"ĠRes erved\",\"ĠLatin os\",\"head ing\",\"Ġ4 40\",\"Ġrooft op\",\"AT ING\",\"Ġ3 90\",\"VP N\",\"G s\",\"k ernel\",\"turn ed\",\"Ġprefer able\",\"Ġturn overs\",\"ĠH els\",\"S a\",\"ĠShin ji\",\"ve h\",\"ĠMOD ULE\",\"V iol\",\"Ġex iting\",\"Ġj ab\",\"ĠVan illa\",\"Ġac ron\",\"ĠG ap\",\"ber n\",\"A k\",\"ĠMc Gu\",\"Ġend lessly\",\"ĠFar age\",\"ĠNo el\",\"V a\",\"M K\",\"Ġbr ute\",\"ĠK ru\",\"ĠES V\",\"ĠOl ivia\",\"âĢ ł\",\"ĠK af\",\"Ġtrust ing\",\"Ġh ots\",\"3 24\",\"Ġmal aria\",\"Ġj son\",\"Ġp ounding\",\"ort ment\",\"Count ry\",\"Ġpostp oned\",\"Ġunequ iv\",\"? ),\",\"ĠRo oney\",\"udd ing\",\"ĠLe ap\",\"ur rence\",\"sh apeshifter\",\"ĠH AS\",\"os ate\",\"Ġca vern\",\"Ġconserv atism\",\"ĠB AD\",\"Ġmile age\",\"Ġarrest ing\",\"V aults\",\"Ġmix er\",\"Dem ocratic\",\"ĠB enson\",\"Ġauth ored\",\"8 000\",\"Ġpro active\",\"ĠSpirit ual\",\"t re\",\"Ġincarcer ated\",\"ĠS ort\",\"Ġpe aked\",\"Ġwield ing\",\"re ciation\",\"×Ļ ×\",\"P atch\",\"ĠEm my\",\"Ġex qu\",\"tt o\",\"ĠRat io\",\"ĠP icks\",\"ĠG ry\",\"ph ant\",\"Ġf ret\",\"Ġeth n\",\"Ġarch ived\",\"% -\",\"c ases\",\"ĠBl aze\",\"Ġim b\",\"c v\",\"y ss\",\"im ony\",\"Ġcount down\",\"Ġaw akening\",\"ĠTunis ia\",\"ĠRe fer\",\"ĠM J\",\"Ġun natural\",\"ĠCar negie\",\"iz en\",\"ĠN uggets\",\"he ss\",\"Ġev ils\",\"64 7\",\"Ġintrodu ctory\",\"l oving\",\"ĠMcM ahon\",\"Ġambig uity\",\"L abel\",\"ĠAlm ighty\",\"Ġcolor ing\",\"ĠCl aus\",\"set ting\",\"N ULL\",\"ĠF avorite\",\"ĠS IG\",\"> (\",\"ĠSh iva\",\"ĠMay er\",\"Ġstorm ed\",\"ĠCo verage\",\"we apons\",\"igh am\",\"Ġun answered\",\"Ġle ve\",\"Ġc oy\",\"c as\",\"b ags\",\"as ured\",\"Se attle\",\"ĠSant orum\",\"ser ious\",\"Ġcourage ous\",\"ĠS oup\",\"Ġconfisc ated\",\"Ġ// /\",\"Ġuncon ventional\",\"Ġmom s\",\"ĠRohing ya\",\"ĠOrche stra\",\"ĠPot ion\",\"Ġdisc redit\",\"ĠF IL\",\"f ixed\",\"ĠDe er\",\"do i\",\"ĠDim ension\",\"Ġbureaucr ats\",\"et een\",\"Ġaction Group\",\"oh m\",\"Ġb umps\",\"ĠUt ility\",\"Ġsubmar ines\",\"ren heit\",\"re search\",\"ĠShap iro\",\"Ġsket ches\",\"Ġde ceptive\",\"ĠV il\",\"es ame\",\"ĠEss entially\",\"Ġramp age\",\"isk y\",\"Ġmut tered\",\"th ritis\",\"Ġ23 6\",\"f et\",\"b ars\",\"Ġpup il\",\"ĠTh ou\",\"o S\",\"s ong\",\"Ġfract ured\",\"Ġre vert\",\"pict ure\",\"Ġcrit erion\",\"us her\",\"Ġreperc ussions\",\"ĠV intage\",\"ĠSuper intendent\",\"Offic ers\",\"Ġflag ged\",\"Ġbl ames\",\"Ġin verse\",\"ograp hers\",\"Ġmakes hift\",\"Ġdev oid\",\"Ġfoss ils\",\"ĠArist otle\",\"ĠFund s\",\"Ġde pleted\",\"ĠFl u\",\"ĠY uan\",\"Ġw oes\",\"Ġlip id\",\"Ġsit u\",\"requ isites\",\"Ġfurn ish\",\"ĠSam ar\",\"Ġshame ful\",\"Ġadverse ly\",\"Ġad ept\",\"Ġrem orse\",\"Ġmurder ous\",\"uck les\",\"ĠE SL\",\"Ġ3 14\",\"s ent\",\"Ġred ef\",\"ĠC ache\",\"ĠP urs\",\"ig ans\",\"Ġ4 60\",\"Ġpres criptions\",\"Ġf res\",\"F uck\",\"ocr ates\",\"Tw enty\",\"ĠWe ird\",\"ĠT oggle\",\"ĠC alled\",\"itiz ens\",\"Ġp oultry\",\"Ġharvest ing\",\"ãĤ¦ ãĤ¹\",\"Bott om\",\"Ġcaution ed\",\"t n\",\"39 6\",\"ĠNik ki\",\"Ġeval uations\",\"Ġharass ing\",\"Ġbind ings\",\"ĠMon etary\",\"Ġhit ters\",\"Ġadvers ary\",\"un ts\",\"Ġset back\",\"Ġenc rypt\",\"ĠC ait\",\"Ġl ows\",\"eng es\",\"ĠN orn\",\"Ġbul bs\",\"Ġbott led\",\"ĠVoy ager\",\"3 17\",\"Ġsp heres\",\"p olitics\",\"Ġsubt ract\",\"Ġsens ations\",\"Ġapp alling\",\"Ġ3 16\",\"Ġenvironment ally\",\"ĠST EM\",\"Ġpub lishes\",\"5 60\",\"Ġdilig ence\",\"48 4\",\"Ġadv ises\",\"Ġpet rol\",\"Ġimag ining\",\"Ġpatrol s\",\"ĠInt eger\",\"ĠAs hes\",\"act us\",\"ĠRad iant\",\"ĠL T\",\"it ability\",\"ht aking\",\"Set ting\",\"Ġnu anced\",\"ĠRe ef\",\"ĠDevelop ers\",\"N i\",\"pie ces\",\"99 0\",\"Lic ense\",\"Ġlow ers\",\"ĠOtt oman\",\"3 27\",\"oo o\",\"Ġqu itting\",\"mark ets\",\"Beh ind\",\"Ġbas in\",\"Ġdoc s\",\"an ie\",\"fl ash\",\"ct l\",\"Ġcivil ized\",\"ĠFuk ushima\",\"\\\"] ,\\\"\",\"ĠK S\",\"ĠHonest ly\",\"ar at\",\"Ġconstruct s\",\"ĠL ans\",\"ĠD ire\",\"ĠLI KE\",\"ĠTrou ble\",\"Ġwith holding\",\"ĠOb livion\",\"Ġsan ity\",\"any a\",\"Con st\",\"Ġgro cer\",\"ĠC elsius\",\"Ġrecount ed\",\"ĠW ife\",\"B order\",\"ate red\",\"h appy\",\"Ġspo iler\",\"Ġlog ically\",\"H all\",\"Ġsucceed ing\",\"Ġpoly morph\",\"Ġax es\",\"ĠShot gun\",\"ĠS lim\",\"ĠPrin ciples\",\"ĠL eth\",\"art a\",\"Ġsc or\",\"Sc reenshot\",\"Ġrelax ation\",\"#$ #$\",\"Ġdeter rent\",\"idd y\",\"Ġpower less\",\"Ġles bians\",\"Ġch ords\",\"ĠEd ited\",\"se lected\",\"Ġseparat ists\",\"000 2\",\"Ġair space\",\"Ġturn around\",\"Ġc unning\",\"P ATH\",\"P oly\",\"Ġbomb ed\",\"Ġt ion\",\"x s\",\"Ġwith hold\",\"Ġw aged\",\"ĠLiber ties\",\"Fl ag\",\"Ġcomfort ing\",\"45 4\",\"ĠI ris\",\"are rs\",\"Ġr ag\",\"Ġrel ocated\",\"ĠGu arant\",\"Ġstrateg ically\",\"Ġgam ma\",\"uber ty\",\"ĠLock heed\",\"g res\",\"Ġgr illed\",\"ĠLow e\",\"st ats\",\"ĠR ocks\",\"Ġsens ing\",\"Ġrent ing\",\"ĠGe ological\",\"Ø§ Ø\",\"ot rop\",\"Ġse w\",\"Ġimproper ly\",\"48 6\",\"Ġâĸ ł\",\"Ġstar ving\",\"ĠB j\",\"Disc ussion\",\"3 28\",\"ĠCom bo\",\"ĠFix es\",\"N AT\",\"Ġstri ving\",\"th ora\",\"Ġharvest ed\",\"ĠP ing\",\"Ġplay ful\",\"Ġaven ues\",\"Ġoccup ational\",\"Ġw akes\",\"ĠCou rier\",\"Ġdrum mer\",\"ĠBrow ser\",\"ĠH outh\",\"it u\",\"Ġapp arel\",\"p aste\",\"Ġhun ted\",\"ĠSecond ly\",\"l ain\",\"X Y\",\"ĠP IN\",\"ic ons\",\"Ġcock tails\",\"Ġs izable\",\"Ġhurd les\",\"est inal\",\"ĠRecre ation\",\"Ġe co\",\"64 8\",\"ĠD ied\",\"m int\",\"Ġfinger prints\",\"Ġdis pose\",\"ĠBos nia\",\"ts y\",\"22 00\",\"Ġins pected\",\"ĠF ou\",\"Ġf uss\",\"Ġamb ush\",\"ĠR ak\",\"Ġmanif ested\",\"Pro secut\",\"Ġsuff ice\",\"ren ces\",\"Ġcompens ated\",\"ĠC yrus\",\"Ġgen us\",\"ĠWolver ine\",\"ĠTrend s\",\"Ġh ikes\",\"ĠSe en\",\"Ġen rol\",\"C old\",\"Ġpol itely\",\"ĠSl av\",\"ĠRu pert\",\"Ġey ewitness\",\"ĠAl to\",\"Ġun comp\",\"Ġposter ior\",\"M ust\",\"ĠHer z\",\"Ġprogress ively\",\"Ġ23 4\",\"Ġind ifference\",\"ĠCunning ham\",\"Ġacadem ia\",\"Ġse wer\",\"Ġast ounding\",\"ĠA ES\",\"r ather\",\"Ġeld est\",\"Ġclim bs\",\"ĠAdd s\",\"Ġout cry\",\"Ġcont ag\",\"ĠH ouses\",\"Ġpe pt\",\"ĠMel ania\",\"interest ed\",\"ĠU CH\",\"ĠR oots\",\"ĠHub bard\",\"ĠT BD\",\"ĠRoman ian\",\"fil ename\",\"St one\",\"ĠIm pl\",\"Ġchromos ome\",\"C le\",\"d x\",\"Ġscram bled\",\"ĠP t\",\"Ġ24 2\",\"OP LE\",\"Ġtremend ously\",\"St reet\",\"Ġcra ving\",\"Ġbund led\",\"ĠR G\",\"p ipe\",\"Ġinj uring\",\"Ġarc ane\",\"Part icip\",\"ĠHero ic\",\"st y\",\"Ġto pping\",\"ĠTemp est\",\"rent ices\",\"b h\",\"Ġpar anoia\",\"ĠUnic ode\",\"Ġegreg ious\",\"Ġ\\\\ '\",\"ĠOsw ald\",\"Ġgra vel\",\"ĠSim psons\",\"Ġbl and\",\"ĠGuant anamo\",\"Writ er\",\"lin ers\",\"ĠD ice\",\"J C\",\"Ġpar ity\",\"Ġs ided\",\"Ġ23 7\",\"ĠPyr rha\",\"at ters\",\"d k\",\"F ine\",\"comp an\",\"Ġform ulated\",\"ĠId ol\",\"il ers\",\"hem oth\",\"ĠF av\",\"Ġintr usion\",\"Ġcar rots\",\"ĠL ayer\",\"ĠH acker\",\"Ġ ----------------\",\"Ġmoder ation\",\"é ģ\",\"oc oc\",\"Ġcharacter ize\",\"ĠTe resa\",\"Ġsocio economic\",\"Ġper k\",\"ĠParticip ation\",\"tr aining\",\"ĠPaul o\",\"ph ys\",\"Ġtrust worthy\",\"Ġembod ied\",\"ĠMer ch\",\"c urrency\",\"ĠPrior ity\",\"Ġte asing\",\"Ġabsor bing\",\"Ġunf inished\",\"ĠCompar ison\",\"Ġdis ple\",\"writ ers\",\"Ġprofess ions\",\"ĠPengu in\",\"Ġang rily\",\"ĠL INK\",\"68 8\",\"ĠCor respond\",\"Ġprev ailed\",\"Ġcart el\",\"l p\",\"as ms\",\"ĠRed emption\",\"ĠIslam ists\",\"effect s\",\"d ose\",\"ĠL atter\",\"ĠHal ifax\",\"Ġv as\",\"ĠTop ics\",\"ĠN amed\",\"advert ising\",\"zz a\",\"IC ES\",\"Ġret arded\",\"ach able\",\"ĠPupp et\",\"ĠItem Level\",\"Ġret ract\",\"Ġident ifiable\",\"A aron\",\"ĠB uster\",\"s ol\",\"hel le\",\"as semb\",\"H ope\",\"r anged\",\"B a\",\"ĠP urch\",\"é Ģ\",\"ĠSir i\",\"Ġarri vals\",\"Ġ19 12\",\"Ġshort ened\",\"Ġ3 12\",\"Ġdiscrep ancy\",\"ĠTem perature\",\"ĠWal ton\",\"Ġkind erg\",\"p olit\",\"Ġrem ix\",\"Ġconnect ors\",\"ãĥĺ ãĥ©\",\"ĠKazakh stan\",\"dom inated\",\"Ġsu gars\",\"im ble\",\"ĠPan ic\",\"ĠDem and\",\"ĠCol ony\",\"on en\",\"ĠM ER\",\"7 75\",\"ur ia\",\"aza ar\",\"ĠDeg ree\",\"P ri\",\"Ġsun shine\",\"Ġ25 1\",\"Ġpsychedel ic\",\"Ġdigit ally\",\"ĠBra un\",\"Ġsh immer\",\"Ġsh ave\",\"ĠTel esc\",\"ĠAst ral\",\"ĠVenezuel an\",\"ĠO G\",\"Ġc rawling\",\"Int eg\",\"ĠFe ather\",\"Ġunfold ing\",\"Ġappropri ation\",\"Ġè£ı è\",\"ĠMob ility\",\"ĠN ey\",\"- .\",\"b ilt\",\"L IN\",\"ĠT ube\",\"ĠCon versely\",\"Ġkey boards\",\"ĠC ao\",\"Ġover th\",\"Ġla ure\",\">> \\\\\",\"ĠV iper\",\"ach a\",\"Off set\",\"ĠR aleigh\",\"ĠJ ae\",\"J ordan\",\"j p\",\"Ġtotal itarian\",\"Connect or\",\"Ġobserv es\",\"ĠSpart an\",\"ĠIm mediately\",\"ĠSc al\",\"C ool\",\"Ġt aps\",\"Ġro ar\",\"P ast\",\"Ġch ars\",\"ĠB ender\",\"ĠShe ldon\",\"Ġpain ter\",\"Ġbe acon\",\"ĠCreat ures\",\"Ġdownt urn\",\"Ġh inder\",\"ĠAnd romeda\",\"Ã Ľ\",\"cc oli\",\"ĠF itness\",\"et rical\",\"Ġutil izes\",\"Ġsen ate\",\"Ġen semble\",\"Ġche ers\",\"T W\",\"Ġaff luent\",\"k il\",\"ry lic\",\"ord ering\",\"Com puter\",\"Ġgru esome\",\"ost ics\",\"ĠUb isoft\",\"ĠKel ley\",\"Ġw rench\",\"Ġbourgeois ie\",\"IB LE\",\"ĠPrest on\",\"w orn\",\"ar ist\",\"reat ing\",\"Ġst ained\",\"ar ine\",\"Ġsl ime\",\"EN N\",\"Ġche sts\",\"Ġground water\",\"ann ot\",\"ĠTr ay\",\"ĠLoc ke\",\"ĠC TR\",\"Ġd udes\",\"ĠEx ternal\",\"ĠDec oder\",\"Ġpar amed\",\"ĠMed line\",\"80 9\",\"ĠD inner\",\"rup al\",\"g z\",\"ĠG um\",\"ĠDem o\",\"j ee\",\"Ġd h\",\"ber man\",\"arch s\",\"Ġen qu\",\"ĠEp stein\",\"Ġdevast ation\",\"Ġfriends hips\",\"ĠAr d\",\"Ġ23 1\",\"ĠRub in\",\"ĠDist ance\",\"Ġsp urred\",\"Ġd ossier\",\"Ġover looking\",\"\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\",\"Fore st\",\"ĠCom es\",\"\\\\ \\\",\",\"ĠIran ians\",\"Ġf ixtures\",\"L aughs\",\"Ġcur ry\",\"ĠKing ston\",\"Ġsqu ash\",\"Ġcat alogue\",\"Ġabnormal ities\",\"Ġdigest ive\",\".... .....\",\"Ġsubord inate\",\"og ly\",\"Ġ24 9\",\"M iddle\",\"Ġmass ac\",\"Ġburg ers\",\"Ġdown stairs\",\"Ġ19 31\",\"39 4\",\"ĠV G\",\"Ġl asers\",\"ĠS ikh\",\"ĠAlex a\",\"der ived\",\"Ġcycl ist\",\"ãģ® éŃĶ\",\"onel iness\",\"!!!! !!!!\",\"Ġbuff s\",\"leg ate\",\"Ġrap ing\",\"Ġrecomm ending\",\"ro red\",\"Ġmult icultural\",\"un ique\",\"Ġbusiness men\",\"Ġune asy\",\"ĠM AP\",\"Ġdisp ersed\",\"cipl ine\",\"J ess\",\"ĠK erala\",\"å §\",\"Ġabst raction\",\"Sur v\",\"U h\",\"Ġprin ters\",\"ij a\",\"ow der\",\"Ġanalog ous\",\"ĠA SP\",\"af er\",\"Ġunfold ed\",\"Ġlevel ing\",\"Ġbre ached\",\"ĠH earing\",\"Ġn at\",\"Ġtransl ating\",\"crit ical\",\"Ġant agonist\",\"ĠYes terday\",\"Ġfuzz y\",\"w ash\",\"m ere\",\"Ġbe wild\",\"ĠM ae\",\"V irgin\",\"ph rase\",\"Ġsign aled\",\"ĠH IGH\",\"Ġprot ester\",\"Ġgar ner\",\"unk nown\",\"Ġk ay\",\"Ġabduct ed\",\"Ġst alking\",\"am n\",\"Ġdes erving\",\"ĠR iv\",\"ĠJ orge\",\"Ġscratch ing\",\"ĠS aving\",\"ip ing\",\"Ġte ase\",\"Ġmission ary\",\"ĠMor row\",\"T IME\",\"P resent\",\"Ġchem otherapy\",\"tern ess\",\"ĠH omes\",\"ĠP urdue\",\"Ġst aunch\",\"ĠWhit ney\",\"ĠTH ERE\",\"Î ¼\",\"iat us\",\"ĠErn est\",\"ĠDe ploy\",\"Ġcove ted\",\"F ML\",\"ĠDial ogue\",\"Ġex ited\",\"f ruit\",\"Ġner d\",\"\\\":\\\" \\\",\\\"\",\"Ġv ivo\",\"ru ly\",\"4 60\",\"ĠAm en\",\"rehens ible\",\"Ġâ ĺ\",\"D IR\",\"Ġad herence\",\"Ġche w\",\"ĠCo ke\",\"ĠSerge i\",\"dig ital\",\"ĠNe ck\",\"g ently\",\"enth al\",\"/ )\",\"Ġwe ary\",\"Ġgu ise\",\"ĠConc ord\",\"ĠOn ion\",\"at cher\",\"Ġb inge\",\"ĠDirect ive\",\"Ġman ned\",\"ans k\",\"Ġill usions\",\"Ġbillion aires\",\"38 3\",\"oly n\",\"odynam ic\",\"ĠWhe at\",\"ĠA lic\",\"Ġcol oured\",\"ĠN AFTA\",\"ab o\",\"Ġmac ros\",\"ind ependent\",\"s weet\",\"Ġsp ac\",\"ĠK abul\",\"Ġ Ä\",\"em e\",\"Ġdict ated\",\"Ġsh outs\",\"= {\",\"Ġr ipping\",\"ĠSh ay\",\"ĠCr icket\",\"direct ed\",\"Ġanalys ed\",\"ĠWAR RANT\",\"ag ons\",\"ĠBlaz ers\",\"Ġche ered\",\"Ġar ithmetic\",\"ĠTan z\",\"37 3\",\"ĠFl ags\",\"Ġ29 5\",\"Ġw itches\",\"ĠIn cluded\",\"ĠG ained\",\"ĠBl ades\",\"G am\",\"ĠSam antha\",\"ĠAtl antis\",\"ĠPr att\",\"Ġspo iled\",\"ĠI B\",\"ĠRam irez\",\"Pro bably\",\"re ro\",\"ĠN g\",\"ĠWar lock\",\"t p\",\"Ġover he\",\"Ġadministr ations\",\"Ġt int\",\"Ġreg iment\",\"Ġpist ols\",\"Ġblank ets\",\"Ġep ist\",\"Ġbowl s\",\"Ġhydra ulic\",\"Ġde an\",\"Ġj ung\",\"Ġasc end\",\"70 5\",\"ĠSant iago\",\"Ã ®\",\"Ġun avoid\",\"ĠSh aman\",\"re b\",\"Ġstem ming\",\"99 8\",\"ĠM G\",\"st icks\",\"esthes ia\",\"ER O\",\"Ġmor bid\",\"ĠGr ill\",\"ĠP oe\",\"any l\",\"Ġdele ting\",\"ĠSurve illance\",\"Ġdirect ives\",\"Ġiter ations\",\"ĠR ox\",\"ĠMil ky\",\"F ather\",\"Ġpat ented\",\"44 7\",\"Ġprec ursor\",\"Ġm aiden\",\"ĠP hen\",\"ĠVe gan\",\"ĠPat ent\",\"K elly\",\"Redd itor\",\"Ġn ods\",\"Ġvent ilation\",\"ĠSchwar z\",\"Ġw izards\",\"Ġomin ous\",\"ĠHe ads\",\"ĠB G\",\"Ġl umber\",\"ĠSp iel\",\"Ġis Enabled\",\"Ġancest ral\",\"ĠSh ips\",\"Ġwrest ler\",\"ph i\",\"Ġy uan\",\"ĠRebell ion\",\"Ġice berg\",\"Ġmag ically\",\"Ġdivers ion\",\"ar ro\",\"yth m\",\"ĠR iders\",\"ĠRob bie\",\"ĠK ara\",\"ĠMain tenance\",\"ĠHer b\",\"Ġhar ms\",\"p acked\",\"ĠFe instein\",\"Ġmarry ing\",\"Ġbl ending\",\"ĠR ates\",\"Ġ18 80\",\"Ġwr ink\",\"ĠUn ch\",\"ĠTor ch\",\"desc ribed\",\"Ġhuman oid\",\"ilit ating\",\"ĠCon v\",\"ĠFe ld\",\"IGH TS\",\"Ġwhistlebl ower\",\"ort mund\",\"ets y\",\"arre tt\",\"ĠMon o\",\"ĠI ke\",\"ĠC NBC\",\"ĠW AY\",\"ĠMD MA\",\"ĠIndividual s\",\"Ġsupplement al\",\"Ġpower house\",\"ĠSt ru\",\"F ocus\",\"aph ael\",\"ĠCol leg\",\"att i\",\"Z A\",\"Ġp erenn\",\"ĠSign ature\",\"ĠRod ney\",\"Ġcub es\",\"idd led\",\"ĠD ante\",\"ĠIN V\",\"iling ual\",\"ĠC th\",\"Ġso fa\",\"Ġintimid ate\",\"ĠR oe\",\"ĠDi plom\",\"ĠCount ries\",\"ays on\",\"Ġextrad ition\",\"Ġdis abling\",\"ĠCard iff\",\"Ġmemor andum\",\"ĠTr ace\",\"Ġ?? ?\",\"se ctor\",\"ĠRou hani\",\"ĠY ates\",\"ĠFree ze\",\"Ġbl adder\",\"M otor\",\"ĠProm ise\",\"ant asy\",\"Ġforesee able\",\"ĠC ologne\",\"cont ainer\",\"ĠTre es\",\"ĠG ors\",\"ĠSin clair\",\"Ġbar ring\",\"key e\",\"Ġsl ashed\",\"ĠStat istical\",\"é ĩ\",\"Ġâĸ º\",\"All ows\",\"Ġhum ility\",\"Ġdr illed\",\"ĠF urn\",\"44 3\",\"Ġse wage\",\"Ġhome page\",\"Ġcour tyard\",\"Ġv ile\",\"Ġsubsid iaries\",\"aj o\",\"direct ory\",\"Ġam mon\",\"V ers\",\"charg es\",\"Ġ} }\",\"ĠCh ains\",\"Ġ24 6\",\"n ob\",\"Ġper cept\",\"Ġg rit\",\"Ġfisher men\",\"ĠIraq is\",\"ĠDIS TR\",\"ĠF ULL\",\"ĠEval uation\",\"g raph\",\"at ial\",\"Ġcooper ating\",\"Ġmel an\",\"Ġenlight ened\",\"Ġal i\",\"t ailed\",\"Ġsal ute\",\"Ġweak est\",\"ĠBull dogs\",\"U A\",\"ĠAll oy\",\"Ġsem en\",\"oc ene\",\"ĠWilliam son\",\"s pr\",\", âĢĶ\",\"ĠG F\",\"itt ens\",\"Be at\",\"ĠJ unk\",\"iph ate\",\"ĠFarm ers\",\"ĠBit coins\",\"ig ers\",\"d h\",\"ĠL oyal\",\"p ayer\",\"Ġentert ained\",\"Ġpenn ed\",\"Ġcoup on\",\"Que ue\",\"Ġweaken ing\",\"c arry\",\"Ġunderest imate\",\"Ġshoot out\",\"Ġcharism atic\",\"ĠProced ure\",\"Ġprud ent\",\"in ances\",\"Ġric hes\",\"Ġcort ical\",\"Ġstr ides\",\"Ġd rib\",\"ĠOil ers\",\"5 40\",\"ĠPer form\",\"ĠBang kok\",\"Ġe uth\",\"S ER\",\"Ġsimpl istic\",\"t ops\",\"camp aign\",\"Q uality\",\"Ġimpover ished\",\"ĠEisen hower\",\"Ġaug ment\",\"ĠH arden\",\"Ġinterven ed\",\"Ġlist ens\",\"ĠK ok\",\"Ġs age\",\"Ġrub bish\",\"ĠD ed\",\"Ġm ull\",\"pe lling\",\"Ġvide ot\",\"Produ ction\",\"D J\",\"m iah\",\"Ġadapt ations\",\"Ġmed ically\",\"Ġboard ed\",\"Ġarrog ance\",\"Ġscra pped\",\"Ġopp ress\",\"FORM ATION\",\"Ġj unction\",\"4 15\",\"EE EE\",\"S kill\",\"Ġsub du\",\"ĠSug gest\",\"ĠP ett\",\"Ġle tt\",\"ĠMan ip\",\"ĠC af\",\"ĠCooper ation\",\"T her\",\"Ġreg ained\",\"¶ æ\",\"ref lect\",\"Ġth ugs\",\"ĠShel by\",\"Ġdict ates\",\"ĠWe iner\",\"ĠH ale\",\"Ġbatt leground\",\"s child\",\"Ġcond ol\",\"h unt\",\"osit ories\",\"Ġacc uses\",\"Fil ename\",\"Ġsh ri\",\"Ġmotiv ate\",\"Ġreflect ions\",\"N ull\",\"ĠL obby\",\"¥ µ\",\"ĠS ATA\",\"ĠBack up\",\"Ñ ĥ\",\"n in\",\"ĠCor rection\",\"Ġju icy\",\"ut ra\",\"ĠP ric\",\"Ġrest raining\",\"ĠAir bnb\",\"ĠAr rest\",\"Ġappropri ations\",\"Ġsl opes\",\"Ġmans laughter\",\"Ġwork ings\",\"ĠH uss\",\"ĠF rey\",\"Le ave\",\"ĠHarm ony\",\"ĠF eder\",\"Ġ4 30\",\"Ġt rench\",\"Ġglad ly\",\"Ġbull pen\",\"ĠG au\",\"b ones\",\"Ġgro ove\",\"Ġpre text\",\"ã ħĭ\",\"Ġtransm itter\",\"ĠComp onent\",\"Ġunder age\",\"ĠEm pires\",\"T ile\",\"Ġo y\",\"ĠMar vin\",\"ĠC AS\",\"Ġbl oss\",\"Ġrepl icated\",\"ĠMar iners\",\"Marc us\",\"ĠBl ocks\",\"Ġliber ated\",\"Ġbutter fly\",\"Fe el\",\"Ġfer mentation\",\"Ġyou tube\",\"Ġoff end\",\"ĠTer m\",\"res ist\",\"Ġcess ation\",\"Ġinsurg ency\",\"Ġb ir\",\"ĠRa ise\",\"59 5\",\"Ġhypothes es\",\"50 2\",\"Ġpl aque\",\"ocr at\",\"Ġjack ets\",\"ĠHuff Post\",\"am ong\",\"Ġconf er\",\"48 7\",\"ĠL illy\",\"Ġadapt ing\",\"ĠF ay\",\"Ġsh oved\",\"ve c\",\"Ġref ine\",\"Ġg on\",\"Ġgun men\",\"z ai\",\"ĠShut tle\",\"ĠI zan\",\"Ġ19 13\",\"Ġple thora\",\"Â· Â·\",\"Ġ5 10\",\"Ġp uberty\",\"Ġ24 1\",\"ĠWe alth\",\"ĠAl ma\",\"ĠM EM\",\"ĠAd ults\",\"C as\",\"pr ison\",\"R ace\",\"Ġwater proof\",\"Ġathlet icism\",\"Ġcapital ize\",\"ĠJu ice\",\"Ġillum inated\",\"ĠP ascal\",\"Ġirrit ation\",\"ĠWitness es\",\"ad le\",\"ĠAst ro\",\"Ġf ax\",\"ĠEl vis\",\"Prim ary\",\"ĠL ich\",\"ĠEl ves\",\"Ġres iding\",\"Ġst umble\",\"3 19\",\"ĠP KK\",\"Ġadvers aries\",\"D OS\",\"ĠR itual\",\"Ġsm ear\",\"Ġar son\",\"ident al\",\"Ġsc ant\",\"Ġmon archy\",\"Ġhal ftime\",\"Ġresid ue\",\"Ġind ign\",\"ĠSh aun\",\"ĠEl m\",\"aur i\",\"A ff\",\"W ATCH\",\"ĠLy on\",\"hel ps\",\"36 1\",\"Ġlobby ist\",\"Ġdimin ishing\",\"Ġout breaks\",\"Ġgo ats\",\"f avorite\",\"ĠN ah\",\"son ian\",\"ĠBo oster\",\"Ġsand box\",\"ĠF are\",\"ĠMalt a\",\"Ġatt Rot\",\"ĠM OR\",\"ld e\",\"Ġnavig ating\",\"T ouch\",\"Ġunt rue\",\"ĠDis aster\",\"Ġl udicrous\",\"Pass word\",\"ĠJ FK\",\"blog spot\",\"4 16\",\"ĠUN DER\",\"ern al\",\"Ġdelay ing\",\"T OP\",\"Ġimpl ants\",\"ĠAV G\",\"ĠH uge\",\"att r\",\"Ġjournal istic\",\"ĠPe yton\",\"ĠI A\",\"R ap\",\"go al\",\"ĠProgram me\",\"Ġsm ashing\",\"w ives\",\"print ln\",\"ĠPl ague\",\"in us\",\"EE P\",\"Ġcru iser\",\"ĠPar ish\",\"umin ium\",\"Ġoccup ants\",\"ĠJ ihad\",\"m op\",\"Ġp int\",\"Ġhe ct\",\"ĠMe cca\",\"direct or\",\"ĠFund ing\",\"ĠM ixed\",\"Ġst ag\",\"T ier\",\"Ġg ust\",\"Ġbright ly\",\"ors i\",\"Ġup hill\",\"R D\",\"Ġles ions\",\"ĠBund y\",\"liv ious\",\"Ġbi ologist\",\"ĠFac ulty\",\"ĠAuthor ization\",\"Ġ24 4\",\"All ow\",\"ï ¸\",\"ĠGi ul\",\"Ġpert inent\",\"ot aur\",\"es se\",\"ĠRo of\",\"Ġunman ned\",\"35 1\",\"ĠSh ak\",\"ĠO rient\",\"Ġend anger\",\"D ir\",\"Ġrepl en\",\"ed ient\",\"Ġtail or\",\"Ġgad gets\",\"Ġaud ible\",\"âĺ Ĩ\",\"N ice\",\"Ġbomb ard\",\"ĠR ape\",\"Ġdef iance\",\"ĠTW O\",\"ĠFilip ino\",\"Ġunaff ected\",\"erv atives\",\"Ġso ared\",\"ĠBol ton\",\"Ġcomprom ising\",\"ĠBrew ers\",\"R AL\",\"ĠA HL\",\"icy cle\",\"Ġv ampires\",\"Ġdi pped\",\"oy er\",\"ĠX III\",\"Ġsidew ays\",\"ĠW aste\",\"ĠD iss\",\"ĠâĶľ âĶĢâĶĢ\",\"$ .\",\"Ġhabit ats\",\"ĠBe ef\",\"tr uth\",\"tr ained\",\"spl it\",\"R us\",\"And y\",\"ĠB ram\",\"RE P\",\"p id\",\"è£ ħ\",\"ĠMut ant\",\"An im\",\"ĠMar ina\",\"Ġfut ile\",\"hig hest\",\"f requency\",\"Ġepile psy\",\"Ġcop ing\",\"Ġconc ise\",\"Ġtr acing\",\"ĠS UN\",\"pan el\",\"ĠSoph ie\",\"ĠCrow ley\",\"ĠAd olf\",\"ĠShoot er\",\"Ġsh aky\",\"ĠI G\",\"ĠL ies\",\"ĠBar ber\",\"p kg\",\"Ġupt ake\",\"Ġpred atory\",\"UL TS\",\"/ **\",\"Ġintox icated\",\"ĠWest brook\",\"od der\",\"he ment\",\"Ġbas eman\",\"AP D\",\"st orage\",\"ĠFif ty\",\"ed itor\",\"G EN\",\"UT ION\",\"ir ting\",\"Ġse wing\",\"r ift\",\"Ġag ony\",\"ĠS ands\",\"Ġ25 4\",\"C ash\",\"Ġl odge\",\"Ġp unt\",\"N atural\",\"ĠIde as\",\"Ġerrone ous\",\"ĠSens or\",\"ĠHann ity\",\"Ġ19 21\",\"Ġm ould\",\"ĠG on\",\"kay a\",\"Ġanonym ously\",\"ĠK EY\",\"Ġsim ulator\",\"W inter\",\"Ġstream ed\",\"50 7\",\"? \\\",\",\"Ġte ased\",\"Ġco efficient\",\"Ġwart ime\",\"ĠTH R\",\"' '.\",\"ĠBank ing\",\"mp ire\",\"Ġf andom\",\"Ġl ia\",\"G a\",\"Ġdown hill\",\"Ġinterpre ting\",\"Ind ividual\",\"N orm\",\"Ġjealous y\",\"bit coin\",\"Ġple asures\",\"ĠToy s\",\"ĠChev rolet\",\"ĠAd visor\",\"IZ E\",\"Ġrecept ions\",\"70 6\",\"C ro\",\"Ġ26 2\",\"Ġcit rus\",\"ir u\",\"Review er\",\"ject ed\",\"U ES\",\"an z\",\"19 81\",\"ĠWork er\",\"Ġcompl ied\",\"ores cent\",\"contin ental\",\"T on\",\"ĠPr ism\",\"ĠShe ep\",\"Ġ28 8\",\"n ox\",\"ĠV og\",\"O rd\",\"Ġreal ms\",\"te k\",\"Ġirrig ation\",\"Ġbicy cles\",\"Ġelectron ically\",\"p oly\",\"t all\",\"() );\",\"Ġaest hetics\",\"ĠInteg rated\",\"Expl ore\",\"Ġd unk\",\"47 6\",\"p ain\",\"ĠJac ques\",\"ĠD mit\",\"Fram es\",\"Ġreun ited\",\"Ġhum id\",\"D ro\",\"P olitical\",\"Ġyouth ful\",\"Ġent ails\",\"Ġmosqu ito\",\"36 3\",\"spe cies\",\"Ġcoord inating\",\"ĠMay hem\",\"ĠMagn us\",\"M ount\",\"Impro ved\",\"ĠST ATE\",\"ATT LE\",\"Ġflow ed\",\"Ġtack led\",\"Ġfashion ed\",\"Ġre organ\",\"iv ari\",\"f inger\",\"Ġreluct antly\",\"et ting\",\"ĠV and\",\"you ng\",\"ĠGar land\",\"Ġpresum ption\",\"Ġamen ities\",\"ĠPle asant\",\"on ential\",\"ĠO xy\",\"Ġmor als\",\"ĠY ah\",\"Read y\",\"Sim on\",\"En h\",\"D emon\",\"Ġcl ich\",\"Mon itor\",\"ĠD U\",\"Ġwel comes\",\"Ġstand out\",\"Ġdread ful\",\"Ġban anas\",\"Ġball oons\",\"h ooting\",\"bas ic\",\"Ġsuff ix\",\"Ġd uly\",\"can o\",\"Ch ain\",\"at os\",\"Ġgeop olitical\",\"Ġ( &\",\"ĠGem ini\",\"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\",\"Ġacqu itted\",\"L uck\",\"prot ect\",\"10 24\",\"Ġsc arcity\",\"Ġmind fulness\",\"ec ided\",\"D N\",\"pr ime\",\"ĠPres idents\",\"ĠVID EO\",\"Ġ( âĪĴ\",\"add ock\",\"N OR\",\"ĠP ru\",\"p un\",\"ĠL OL\",\")) ))\",\"ĠL iqu\",\"ĠS AS\",\"Ġsty ling\",\"Ġpunish ments\",\"Ġnum b\",\"Ġasc ertain\",\"ĠRock ies\",\"f lu\",\"Th umbnail\",\"Ġperpet rated\",\"ĠSem i\",\"Ġdis arm\",\"ĠOld er\",\"ĠEx ception\",\"Ġexponent ially\",\"ĠCommun ities\",\"Ġabol ish\",\"ĠPart ner\",\"pt oms\",\"Ġ7 77\",\"ĠFo ley\",\"ĠC ases\",\"Ġgre ase\",\"ĠReb irth\",\"G round\",\"Ġ; )\",\"ĠDoct rine\",\"ik ini\",\"Y e\",\"ĠBl ossom\",\"Ġpers ists\",\"b ill\",\"Ġinf usion\",\"Ġbud dies\",\"9 11\",\"ĠPat ient\",\"Ġdem os\",\"Ġacquaint ance\",\"ĠP aw\",\"at ari\",\"Ġx ml\",\"Ġfasc ination\",\"ĠSer ve\",\"Ï Ĥ\",\"br anded\",\"Ġa z\",\"Return s\",\"Ġover shadow\",\"Ġro am\",\"Ġspeed y\",\"n umbered\",\"hel ial\",\"Ġdisc iple\",\"Ġass urances\",\"g iven\",\"pect ing\",\"ĠN atalie\",\"çĶ °\",\"Ġmosquit oes\",\"rote in\",\"Ġnumer ic\",\"Ġindepend ents\",\"Ġtrans itional\",\"Ġreaction ary\",\"ĠMech dragon\",\"do ctor\",\"Ġshort est\",\"Ġsequ ential\",\"ĠB ac\",\"ĠAccount s\",\"ãģ Į\",\"ach y\",\"ract ive\",\"ĠReg iment\",\"Ġbreat htaking\",\"ffic iency\",\"ĠB ates\",\"Ġ3 11\",\"Ġward robe\",\"ft s\",\"ĠBer k\",\"Sim ply\",\"ĠRivers ide\",\"iver ing\",\"ident ial\",\"lu cent\",\"Ġen riched\",\"ĠCon ver\",\"ĠG iving\",\"ãĥ Ļ\",\"Ġlegal ize\",\"ĠF TC\",\"Ġfre aking\",\"M ix\",\"Ġter restrial\",\"es ian\",\"ci ents\",\"W ing\",\"LO AD\",\"Ġled ge\",\"ĠViol ent\",\"ĠMet all\",\"Ġ30 8\",\"Ġs outheastern\",\"hett o\",\"M eat\",\"Ġslow down\",\"Ġret reated\",\"Jere my\",\"end as\",\"**** *\",\"er ic\",\"Ġre ins\",\"opp able\",\"ĠHuman ity\",\"ear ances\",\"rig an\",\"C amera\",\"Ġwa ivers\",\"s oc\",\"Ġalter ation\",\"trans form\",\"ĠC emetery\",\"50 6\",\"Ġindef inite\",\"Ġstim ulating\",\"y g\",\"60 3\",\"ĠS op\",\"Ġdescript ive\",\"Ph ase\",\"ĠEd mund\",\"Ġpneum onia\",\"vent us\",\"A mb\",\"Ġlabor atories\",\"ĠEx clusive\",\"ug ar\",\"W ere\",\"Ġmalf unction\",\"Ġhomosexual s\",\"Ġ---- ---\",\"un i\",\"Ġturb ines\",\"ĠEqu ity\",\"D u\",\"Ġmind ed\",\"ĠR H\",\"ĠBlack hawks\",\"Ġfe ats\",\"Ġ17 00\",\"re pl\",\"36 2\",\"lad en\",\"Ġindisp ensable\",\"ly ss\",\"tt i\",\"Ġre el\",\"Ġdiver ted\",\"Ġlik eness\",\"Ġsubscript ions\",\"Ġfing ert\",\"Ġfil thy\",\"dest ruct\",\"d raft\",\"ĠBernard ino\",\"l aunch\",\"Ġper plex\",\"ĠS UM\",\"car b\",\"Ġswe ater\",\"ĠVent ure\",\"ĠJ ag\",\"ĠCele b\",\"ĠV oters\",\"Ġstead fast\",\"Ġathlet ics\",\"ĠHans on\",\"ĠDr ac\",\"Tr acker\",\"Ġcomm end\",\"ĠPres idency\",\"ĠD ID\",\"in formed\",\"Ġweb page\",\"P retty\",\"Ġforce fully\",\"ãĥĥ ãĤ¯\",\"Ġrel ocation\",\"Ġsat ire\",\"â ī\",\"ĠSunder land\",\"æ Ħ\",\"V oice\",\"???? ????\",\"Ġinform ant\",\"Ġbow el\",\"ĠUn iform\",\"Ġ ...\\\"\",\"Ġpur ge\",\"Ġpic nic\",\"ĠU mb\",\"ĠU PDATE\",\"ĠSapp hire\",\"ĠSt all\",\"le arn\",\"Ġobject ively\",\"Ġob liter\",\"Ġlooph ole\",\"Ġjour neys\",\"Ġo mission\",\"Pro s\",\"ĠSid ney\",\"pl oma\",\"Ġspray ed\",\"Ġg uru\",\"Ġtra itor\",\"Ġtim et\",\"Ġsn apping\",\"ĠSe vent\",\"urn al\",\"ĠUk ip\",\"Ġb owed\",\"por al\",\"l iberal\",\"R os\",\"Quest ions\",\"i OS\",\"Ġsummar ize\",\"ST AT\",\"Ġ18 50\",\"ap est\",\"Ġl ender\",\"ĠVari able\",\"br inging\",\"ĠL ORD\",\", )\",\"Ġcollaps es\",\"x iety\",\"ĠN ed\",\"Y D\",\"ĠSch a\",\"Ġantib ody\",\"Ġdis band\",\"y re\",\"ill usion\",\"Ġro ver\",\"s hed\",\"ĠHiro sh\",\"cc i\",\"Ġcal am\",\"ĠMort on\",\"P interest\",\"Ġ19 28\",\"ĠE uras\",\"ord es\",\"Ġf ences\",\"ĠIn ventory\",\"ĠVal encia\",\"ĠU d\",\"ĠT iff\",\"Ġsqu e\",\"Ġqu otation\",\"Ġtroubles ome\",\"er ker\",\"QU EST\",\"ĠKing doms\",\"s outh\",\"Ġle vy\",\"Pr ince\",\"ĠSt ing\",\"Ġnick named\",\"Ġapp e\",\"Ġphot ographic\",\"Ġcorp us\",\"re ference\",\"ĠT rog\",\"U nt\",\") =(\",\"ĠLat via\",\"Ġactiv ating\",\"Ġlicense e\",\"Ġdispar ities\",\"ĠNews letter\",\"ãĥĥ ãĥĪ\",\"Ġfree ing\",\"ĠJe ep\",\"ĠPer ception\",\"ins k\",\"Ġsil icone\",\"ĠHay den\",\"Le an\",\"ĠSuz uki\",\"ibr arian\",\"66 8\",\"Ġsp or\",\"Ġcorrel ations\",\"ag hetti\",\"Ġtu ber\",\"ĠIP CC\",\"il us\",\"ĠV u\",\"Ġwealth iest\",\"ĠCarb uncle\",\"an za\",\"Ġfool ed\",\"ĠZ ur\",\"Ġd addy\",\"ran o\",\"il ian\",\"Ġknock out\",\"f man\",\"requ ired\",\"ĠWik ileaks\",\"ĠD uffy\",\"ON T\",\"Ġins ol\",\"ĠObject s\",\"Ġb ou\",\"ĠNord ic\",\"ĠIns ert\",\"sc an\",\"Ġd ancers\",\"Ġid iots\",\"major ity\",\"ĠNev ille\",\"ĠFree BSD\",\"Ġt art\",\"pan ic\",\"69 0\",\"Ġcoc oa\",\"Ġsam pled\",\"Ġlook up\",\"Ind ust\",\"Ġinject ions\",\"gen re\",\"Ġa u\",\"Ġroad way\",\"Ġgen itals\",\"K ind\",\"ĠEx aminer\",\"ĠY az\",\"F resh\",\"Ġpar alysis\",\"ĠAl uminum\",\"Ġre ap\",\"ok Ã©\",\"Ġsl oppy\",\"ĠTun nel\",\"pos ium\",\"ner y\",\"en ic\",\"Ġher bal\",\"ĠOut er\",\"ĠBuild er\",\"Ġinc ur\",\"Ġide ologies\",\"Ġback ups\",\"cons uming\",\"ĠDet ect\",\"de ck\",\"ĠKN OW\",\"ĠG ret\",\"ĠM IC\",\"Ġtough ness\",\"ĠEx hibit\",\"Ġh ive\",\"L es\",\"ĠSCH OOL\",\"ĠAt ari\",\"ald e\",\"ĠN ull\",\"and estine\",\"m ouse\",\"Ġbrig ade\",\"48 9\",\"Ġrev ol\",\"ĠLaw son\",\"ĠW ah\",\"op oly\",\"eb ted\",\"ĠS aunders\",\"Ġ3 13\",\"ĠW inc\",\"Ġtab oo\",\"ĠHel met\",\"Ġw edge\",\"ch ip\",\"ĠT ina\",\"b g\",\"Ġinf uri\",\"r n\",\"Ġanomal ies\",\"ĠSy nc\",\"ĠEx am\",\"ĠComm it\",\"ĠDi ary\",\"ĠALS O\",\"ĠDe bor\",\"omed ical\",\"Ġcomprehens ion\",\"6 55\",\"Ġempower ing\",\"Ġ ire\",\"Ġju ices\",\"ĠE TH\",\"ĠBox ing\",\"=\\\" /\",\"Ġfacilit ated\",\"p oke\",\"ĠPars ons\",\"ĠMod er\",\"tra vel\",\"Ġcivil izations\",\"Ġliber tarians\",\"Ġrun e\",\"ĠCl arks\",\"at hed\",\"Ġcampaign ers\",\"ĠDis patch\",\"ĠFah renheit\",\"ĠCap com\",\"-------- --\",\"Ġl ace\",\"Ġdr aining\",\"Ġl iner\",\"ĠArt ificial\",\"Ã© n\",\"t ask\",\"] ).\",\"ĠGM O\",\"ĠOper ator\",\"ord inary\",\"ĠInf luence\",\"ĠU ps\",\"Ġpot ency\",\"uss en\",\"osp ons\",\"ĠSw im\",\"ĠDead line\",\"Un ity\",\"Ġcul inary\",\"Ġenlight enment\",\"Ġwe arer\",\"Ġmin ed\",\"Ġp ly\",\"Ġinc est\",\"ĠDVD s\",\"W alk\",\"B TC\",\"Tr ade\",\"Ġdev al\",\"ib and\",\"ĠOvers ight\",\"Palest inian\",\"Ġd art\",\"Ġm ul\",\"L R\",\"Ġrem ovable\",\"ĠReal ms\",\"ì Ŀ\",\"Ġmisc ar\",\"ĠV ulkan\",\"68 5\",\"Ã¨ re\",\"ĠS ap\",\"Ġmer ging\",\"ĠCar ly\",\"che ster\",\"Ġbr isk\",\"Ġlux urious\",\"ĠGener ator\",\"Ġbit terness\",\"Ġed ible\",\"Ġ24 3\",\"T G\",\"Ġrect angle\",\"With No\",\"bel ow\",\"J enn\",\"Ġdark est\",\"Ġh itch\",\"Ġdos age\",\"Ġsc aven\",\"ĠK eller\",\"ĠIllust rated\",\"Certain ly\",\"ĠMaver icks\",\"Marg inal\",\"Ġdiarr hea\",\"Ġenorm ously\",\"Ġ9 99\",\"sh r\",\"qu art\",\"Ġadam ant\",\"ĠM ew\",\"Ġren ovation\",\"Ġcerv ical\",\"ĠPercent age\",\"en ers\",\"ĠKim ber\",\"Ġflo ats\",\"Ġde x\",\"ĠW itcher\",\"ĠSwan sea\",\"d m\",\"Ġsal ty\",\"y ellow\",\"Ġca pe\",\"ĠDr ain\",\"ĠPaul a\",\"ĠTol edo\",\"les i\",\"Mag azine\",\"ĠW ick\",\"ĠM n\",\"ĠA ck\",\"ĠR iding\",\"AS ON\",\"Ġhom ophobic\",\"AR P\",\"Ġwand ered\",\"C PU\",\"ood oo\",\"ĠP ipe\",\"Ġtight ening\",\"ĠBut t\",\"3 18\",\"Ġdesert ed\",\"S ession\",\"Ġfacilit ating\",\"J ump\",\"Ġemer gencies\",\"OW ER\",\"Ġexhaust ive\",\"ĠAF TER\",\"Ġheart beat\",\"ĠLab el\",\"ack y\",\"ĠCert ified\",\"ilt ration\",\"Z e\",\"ĠU tt\",\"Ġ13 00\",\"Ġpres ume\",\"ĠDis p\",\"Ġsur ged\",\"Ġdoll s\",\"Col umb\",\"Ġchim pan\",\"ĠR azor\",\"Ġt icks\",\"Ġcouncill or\",\"Ġpilgr image\",\"ĠReb els\",\"ĠQ C\",\"ĠA uction\",\"x ia\",\"ik k\",\"b red\",\"Ġinsert ion\",\"Ġco arse\",\"d B\",\"SE E\",\"ĠZ ap\",\"ĠF oo\",\"Ġcontem por\",\"ĠQuarter ly\",\"ot ions\",\"ĠAl chemist\",\"ĠT rey\",\"ĠDu o\",\"S weet\",\"80 4\",\"ĠGi ov\",\"Ġfun n\",\"N in\",\"h off\",\"Ġram ifications\",\"Ġ19 22\",\"ĠExper ts\",\"az es\",\"Ġgar ments\",\"ar ial\",\"ĠN ab\",\"Ġ25 7\",\"ĠV ed\",\"Ġhum orous\",\"ĠPom pe\",\"Ġn ylon\",\"Ġlur king\",\"ĠSerge y\",\"ĠMatt is\",\"Ġmisogyn y\",\"ĠComp onents\",\"ĠWatch ing\",\"ĠF olk\",\"ract ical\",\"B ush\",\"Ġt aped\",\"Ġgroup ing\",\"Ġbe ads\",\"Ġ20 48\",\"Ġcon du\",\"quer que\",\"Read ing\",\"Ġgriev ances\",\"Ult ra\",\"Ġend point\",\"H ig\",\"ĠSt atic\",\"ĠScar borough\",\"L ua\",\"ĠMess i\",\"a qu\",\"ĠPsy Net\",\"ĠR udd\",\"Ġa venue\",\"v p\",\"J er\",\"Ġsh ady\",\"ĠRes ist\",\"ĠArt emis\",\"Ġcare less\",\"Ġbro kers\",\"Ġtemper ament\",\"Ġ5 20\",\"T ags\",\"ĠTurn ing\",\"Ġut tered\",\"Ġp edd\",\"Ġimpro vised\",\"Ġ: (\",\"Ġtab l\",\"Ġpl ains\",\"16 00\",\"press ure\",\"ĠEss ence\",\"marg in\",\"friend s\",\"ĠRest oration\",\"Ġpoll ut\",\"ĠPok er\",\"ĠAugust ine\",\"ĠC IS\",\"ĠSE AL\",\"or ama\",\"Ġth wart\",\"se ek\",\"Ġp agan\",\"Â º\",\"cp u\",\"Ġg arn\",\"Ġass ortment\",\"ĠI LCS\",\"t ower\",\"Recomm ended\",\"Ġun born\",\"ĠRandom Redditor\",\"ĠRandomRedditor WithNo\",\"Ġparaly zed\",\"Ġeru ption\",\"Ġinter sect\",\"ĠSt oke\",\"ĠS co\",\"B ind\",\"å ¾\",\"ĠP NG\",\"ĠNeg ative\",\"ĠNO AA\",\"Le on\",\"Ġall oy\",\"ĠL ama\",\"ĠD iversity\",\"5 75\",\"Ġunderest imated\",\"ĠSc or\",\"Ġm ural\",\"Ġb usted\",\"so on\",\"l if\",\"Ġnone x\",\"Ġall ergy\",\"ĠUnder world\",\"ĠR ays\",\"ĠBl asio\",\"Ġh rs\",\"ĠD ir\",\"Ġ3 27\",\"by ter\",\"Ġrepl acements\",\"Ġactiv ates\",\"ri ved\",\"M H\",\"Ġp ans\",\"ĠH I\",\"Ġlong itudinal\",\"Ġnu isance\",\"al er\",\"Ġsw ell\",\"ĠS igned\",\"s ci\",\"ĠIs les\",\"ĠA GA\",\"Ġdef iant\",\"Ġson ic\",\"oc on\",\"K C\",\"ĠA im\",\"t ie\",\"ah ah\",\"Ġm L\",\"D X\",\"Ġb isc\",\"ĠBill board\",\"ĠSY STEM\",\"NE Y\",\"ga ard\",\"Ġdist ressed\",\"former ly\",\"Al an\",\"Ġche fs\",\"Ġopt ics\",\"ĠC omet\",\"ĠAM C\",\"Ġredes igned\",\"irm ation\",\"Ġsight ings\",\"38 2\",\"3 11\",\"ĠW B\",\"Ġcont raction\",\"ĠT OTAL\",\"D ual\",\"Ġstart led\",\"Ġunderstand ably\",\"Ġsung lasses\",\"ETH OD\",\"Ġd ocker\",\"Ġsurf ing\",\"ĠH EL\",\"ĠSl ack\",\"ton es\",\"Ġsh alt\",\"Vis ual\",\"49 8\",\"Dep artment\",\"c ussion\",\"Ġunrest ricted\",\"Ġt ad\",\"Ġre name\",\"employ ed\",\"Ġeduc ating\",\"Ġgrin ned\",\"bed room\",\"ĠActiv ities\",\"ĠV elvet\",\"ĠSW AT\",\"Ġsh uffle\",\"ig or\",\"Ġsatur ation\",\"F inding\",\"c ream\",\"ic ter\",\"Ġv odka\",\"tr acking\",\"te c\",\"Ġfore ground\",\"iest a\",\"Ġve hement\",\"ĠEC B\",\"ĠT ie\",\"E y\",\"Ġt urtles\",\"ĠRail road\",\"ĠKat z\",\"ĠFram es\",\"Ġmen ace\",\"ĠFell owship\",\"ĠEss ential\",\"ugg ish\",\"Ġdri p\",\"ch witz\",\"ĠKy oto\",\"s b\",\"ĠN ina\",\"Param eter\",\"Ġal arms\",\"ĠCl aud\",\"Ġpione ering\",\"Ġchief ly\",\"ĠSc ream\",\"Col lection\",\"Ġthank fully\",\"ĠRonald o\",\"åŃ Ĳ\",\"st rip\",\"ĠDisney land\",\"com mercial\",\"See ing\",\"S oul\",\"Ġevac uate\",\"Ġc iv\",\"ĠAs he\",\"Ġdiv ides\",\"ĠD agger\",\"rehens ive\",\"Ġber ries\",\"ĠD F\",\"Ġs ushi\",\"Ġplur ality\",\"W I\",\"Ġdisadvant aged\",\"Ġbatt alion\",\"ob iles\",\"45 1\",\"Ġcl ing\",\"Ġunden iable\",\"ĠL ounge\",\"Ġha unt\",\"p he\",\"Ġquant ify\",\"Ġdiff ered\",\"Ġ[* ]\",\"ĠV iz\",\"c um\",\"sl ave\",\"Ġvide og\",\"Ġqu ar\",\"Ġbund les\",\"ĠAl onso\",\"t ackle\",\"Ġneur onal\",\"Ġlandsl ide\",\"conf irmed\",\"ĠDep th\",\"Ġrenew ables\",\"B ear\",\"ĠMaced onia\",\"Ġjer seys\",\"Ġb unk\",\"ĠSp awn\",\"ĠControl s\",\"ĠBuch anan\",\"Ġrobot ics\",\"Ġemphas izing\",\"ĠTut orial\",\"h yp\",\"ist on\",\"Ġmonument al\",\"æ °\",\"ĠCar ry\",\"Ġt bsp\",\"en ance\",\"H ill\",\"art hed\",\"Ġro tten\",\"De an\",\"Ġtw isting\",\"Ġgood will\",\"Ġimm ersion\",\"L iving\",\"Ġbr ushes\",\"ĠC GI\",\"ĠAt k\",\"tr aditional\",\"Ġph antom\",\"ĠSt amina\",\"Ġexpans ions\",\"ĠMar in\",\"Ġembark ed\",\"ĠE g\",\"int estinal\",\"ĠPE OPLE\",\"ĠBo oth\",\"ĠApp alach\",\"Ġreleg ated\",\"V T\",\"M IT\",\"Ġmust er\",\"Ġwithdraw ing\",\"Ġmicrosc ope\",\"ĠG athering\",\"ĠC rescent\",\"ĠArgent ine\",\"ĠDec re\",\"ĠDomin ic\",\"Ġbud s\",\"ant age\",\"ĠI on\",\"Ġwid ened\",\"ONS ORED\",\"ĠGl oves\",\"iann opoulos\",\"raz en\",\"fe el\",\"Ġrepay ment\",\"Ġhind sight\",\"ĠRE ALLY\",\"ĠPist ol\",\"ĠBra h\",\"Ġwat ts\",\"Ġsurv ives\",\"Ġfl urry\",\"iss y\",\"Al ert\",\"ĠUrug uay\",\"Ph oenix\",\"S low\",\"ĠG rave\",\"ĠF ir\",\"Ġmanage able\",\"Ġtar iff\",\"ĠU DP\",\"ĠPist ons\",\"ĠNiger ian\",\"Ġstrike outs\",\"Ġcos metics\",\"whel ming\",\"f ab\",\"c ape\",\"pro xy\",\"Ġre think\",\"Ġover coming\",\"sim ple\",\"Ġw oo\",\"Ġdistract ing\",\"ĠSt anton\",\"ĠTuls a\",\"ĠD ock\",\"65 9\",\"Ġdisc ord\",\"ĠEm acs\",\"ĠV es\",\"ĠR OB\",\"Ġreass uring\",\"Ġcons ortium\",\"Muslim s\",\"3 21\",\"Ġprompt s\",\"se i\",\"ĠH itch\",\"imp osed\",\"ĠF ool\",\"Ġindisc rim\",\"wr ong\",\"bu querque\",\"D avis\",\"! ]\",\"Ġtim eless\",\"ĠNE ED\",\"Ġpestic ide\",\"Ġrally ing\",\"ĠCal der\",\"Ġå ¤\",\"Ġx p\",\"ĠUn le\",\"ĠEx port\",\"lu aj\",\"B uff\",\") </\",\"B oot\",\"ĠChrys ler\",\"or ative\",\"M ess\",\"Ġneglig ible\",\"ert odd\",\"ĠMush room\",\"ĠG ale\",\"g c\",\"ĠCos by\",\"ĠR ural\",\"rit ical\",\"B ell\",\"Ġturb ine\",\"00 200000\",\"Ġlegit imately\",\"ĠAnim ated\",\"T ED\",\"ĠThe odore\",\"c onduct\",\"ĠH ier\",\"Ġcounterfe it\",\"ĠAlger ia\",\"Ġun beat\",\"cont roller\",\"Ġun res\",\"Ġscram bling\",\"ĠFall on\",\"T es\",\"Ġam ber\",\"Ġroy alties\",\"ĠShel ter\",\"ĠL ester\",\"Ġclass ify\",\"Rem ote\",\"Ġun heard\",\"Ġcontrovers ies\",\"Ġenrich ment\",\"ĠYan kee\",\"g amer\",\"Ġpl atinum\",\"Ġec ology\",\"ĠS ark\",\"Ġunt ouched\",\"Ġsuper visors\",\"Ġ\\\" %\",\"Ġf ooth\",\"Ġcomm ons\",\"Ġnarc otics\",\"Ġind ices\",\"ĠP ly\",\"Ġaddition ally\",\"ĠGaw ker\",\"ĠE Q\",\"Pl aying\",\"Ġcave at\",\"ĠAbs olute\",\"oss us\",\"B aby\",\"Ġr ation\",\"Ġres in\",\"Ġcalib ration\",\"ĠNew port\",\"Ġkn ocks\",\"v t\",\"Ġcomp ost\",\"Sc ene\",\"Ġsar cast\",\"Ġkiss es\",\"Ġn s\",\"all i\",\"ĠMar cel\",\"ĠP iet\",\"iat rics\",\"Ġsurround s\",\"ĠRep rodu\",\"ĠPhill ies\",\"Ġuncertain ties\",\"ĠE ur\",\"ĠRom ance\",\"ĠH ath\",\"ĠNeed s\",\"ĠCl oak\",\"Ġcre m\",\"que ue\",\"Ġ3 55\",\"Ġup front\",\"] );\",\"Ġrecip roc\",\"Ġ19 27\",\"Ġ11 00\",\"ut su\",\"Ġdep ressive\",\"ow ment\",\"F ans\",\"Ġme ch\",\"Ġann ihil\",\"Ġcounter terrorism\",\"ĠFig ures\",\"b old\",\"ĠMo ines\",\"ĠDri vers\",\"Ġmanuscript s\",\"ĠCrypt o\",\"Ġhyp not\",\"redd its\",\"Ġprosec utions\",\"Ġdiver t\",\"CR IP\",\"ĠB ene\",\"ĠRe ggie\",\"Ġtax ing\",\"ĠMor ales\",\"ent ing\",\"t ur\",\"sign ificant\",\"ĠPR OV\",\"Ġstr ands\",\"Ġp ouch\",\"ĠR ookie\",\"» Ĵ\",\"Ġnic er\",\"he my\",\"h w\",\"EC A\",\"Ġintimid ated\",\"Ġstr icter\",\"Ġmicro bial\",\"det ails\",\"Ġv ows\",\"Ġqu ake\",\"hh hh\",\"Ġrein vent\",\"U b\",\"Ġrel inqu\",\"ĠBuff ett\",\"lic ensed\",\"itte red\",\"ĠPic ard\",\"Ġche wing\",\"u cl\",\"organ ic\",\"Ġlocal ized\",\"ĠEconom ist\",\"Ġacqu ainted\",\"Def inition\",\"s ed\",\"Crit ics\",\"Ġc c\",\"45 3\",\"38 1\",\"Ġfell ows\",\"Ġcheck points\",\"0 25\",\"Ġre election\",\"Ġmed iated\",\"ĠK DE\",\"Ġhurd le\",\"Ġtext ing\",\"Per fect\",\"Ġtrust ees\",\"fect ure\",\"Ġd ich\",\"mon ary\",\"Ġdist inctions\",\"Ġ14 00\",\"Ġus her\",\"Ġparas ites\",\"ĠSh aring\",\"ĠV im\",\"Ġbar becue\",\"ĠMin isters\",\"ere lla\",\"Ġe b\",\"Ġm c\",\"ĠSome how\",\"ĠIn sect\",\"ch anges\",\"b road\",\"ĠBy z\",\"Ġgrap es\",\"66 9\",\"Ġ= ================\",\"Ġass imil\",\"Ġhaun ting\",\"Ġfire power\",\"Ġdef amation\",\"em phasis\",\"Ġcomp ose\",\"Ġallerg ies\",\"Ġstr ang\",\"roll ers\",\"b ang\",\"Ġbrew ers\",\"ron gh\",\"ri ot\",\"p oor\",\"c old\",\"S ample\",\"Ġbu oy\",\"0 40\",\"ĠCourt ney\",\"Ġ26 8\",\"ĠWed ding\",\"70 2\",\"Ġobsess ive\",\"Ġbra king\",\"ĠL al\",\"an ical\",\"å ¦\",\"at en\",\"Con struction\",\"Ġclin ically\",\"iers hip\",\"N ames\",\"ĠDisc uss\",\"ĠRam os\",\"Ġloc ale\",\"ĠAgric ultural\",\"En able\",\"Ġhorse power\",\"ent ure\",\"P ref\",\"C ourt\",\"Ġstaff ing\",\"Ġfut uristic\",\"dri vers\",\"ĠMarket place\",\"æĪ ¦\",\"Friend s\",\"Ġdam ning\",\"ĠCustom ers\",\"Ġwe eds\",\"ĠM ai\",\"Ġag ile\",\"ĠT att\",\"ic ent\",\"R anked\",\"cro ft\",\"ĠKat y\",\"Ext reme\",\"Ġcar ve\",\"ĠR over\",\"ĠBy ron\",\"37 2\",\"Ġconduct s\",\"r atch\",\"it ia\",\"ĠPump kin\",\"Sad ly\",\"Rel oaded\",\"P olicy\",\"Ġl ick\",\"pe ak\",\"is ks\",\"ĠCD s\",\"ĠEn cyclopedia\",\"in itial\",\"C os\",\"ĠAware ness\",\"ĠD ram\",\"$$ $$\",\"Ġr iff\",\"Ġscript ure\",\"run ners\",\"Ġbo iler\",\"ons on\",\"o in\",\"Ġham string\",\"Ġcat aly\",\"ĠArch bishop\",\"ch all\",\"Ġf aux\",\"ok in\",\"local host\",\"ĠN AME\",\"ad obe\",\"S AN\",\"am ate\",\"Ġscram ble\",\"Ġcar c\",\"ĠMan ifest\",\"ĠCed ar\",\"ĠSer gio\",\"l ater\",\"ff er\",\"Ġgrapp ling\",\"ĠDe utsche\",\"agon ists\",\"ĠNew sp\",\"Ġpret ended\",\"arch ment\",\"Ġcur ated\",\"Ġhead phone\",\"ĠUn common\",\"ĠS IGN\",\"A gent\",\"Ġdead lines\",\"Ġhorizont ally\",\"ĠM AT\",\"ĠSum mers\",\"Ġord ained\",\"ĠLast ly\",\"ĠKend all\",\"Ġfr ig\",\"ĠMach ina\",\"ĠWater loo\",\"ĠMex icans\",\"Ġprotect or\",\"Ġgl are\",\"} \\\"\",\"Prem ium\",\"Ġr ift\",\"ĠTelesc ope\",\"Met al\",\"Ġrec apt\",\"Ġ; ;\",\"Ġincl ination\",\"Ġimp oses\",\"ing en\",\"^ {\",\"Ġh aste\",\"Ġd olphins\",\"Ġcomm uters\",\"pl anned\",\"c ong\",\"m x\",\"ĠU pload\",\"Ġext rap\",\"ĠTuc son\",\"ĠExpl oration\",\"efe ated\",\"Ġsl ender\",\"70 3\",\"ĠB uk\",\"is el\",\"Ġcompet itiveness\",\"ch lor\",\"ĠP ermanent\",\"ĠE verett\",\"ĠSpecial ist\",\"ĠS OL\",\"Ġcy an\",\"ĠEx actly\",\"U F\",\"ĠL IFE\",\"ary l\",\"on et\",\"ĠEmploy ee\",\"aw ed\",\"ĠRat ings\",\"Ġextra vag\",\"ul hu\",\"ĠPl ane\",\"Ġelev ate\",\"ĠCoord inator\",\"ĠWat kins\",\"Ġex cludes\",\"Ġsent ient\",\"Ġep och\",\"Ġall oc\",\"Pre viously\",\"ĠSh y\",\"ĠSlov akia\",\"L OCK\",\"Ġmarked ly\",\"Ġkn ob\",\"Ġadventure rs\",\"ĠBe en\",\"ĠCost s\",\"amm ers\",\"Ġon slaught\",\"ĠSupport ed\",\"ĠT au\",\"ik arp\",\"ĠS overe\",\"ĠHam pton\",\"ãĤ ī\",\"Pre v\",\"ĠW orse\",\"Ġc ottage\",\"ĠH ades\",\"le z\",\"b owl\",\"Ġfrag rance\",\"ĠL ok\",\"EM OTE\",\"ĠPet ro\",\"Ġ19 25\",\"ĠP end\",\"produ cing\",\"Ġrel ocate\",\"v ati\",\"p ole\",\"Ġsem in\",\"ĠN UM\",\"Ġrock ed\",\"b uff\",\"b ly\",\"Rep ly\",\"ĠH ai\",\"Ġartic ulated\",\"ĠIslam abad\",\"66 5\",\"ĠClaim s\",\"Des ktop\",\"Ġtrust ee\",\"Ġscript ing\",\"ĠS ob\",\"ĠAs ylum\",\"STD OUT\",\"ĠCl own\",\"ĠD ortmund\",\"ĠDev on\",\"l ite\",\"ĠMar ble\",\"Ġb unker\",\"Ġcre st\",\"Ġarous al\",\"ĠS ears\",\"ĠBudd y\",\"ered ith\",\"ĠP olly\",\"Ġdec ode\",\"ĠV ish\",\"ĠRef lect\",\"an on\",\"Ġrefund s\",\"imm ers\",\"H M\",\"Ġwip ing\",\"Ġpuzz led\",\"Ġmat te\",\"un o\",\"P ierre\",\") ),\",\"Ġt ainted\",\"Ġsymbol ism\",\"ĠF raz\",\"Ġprotest ors\",\"ethe us\",\"%% %%\",\"W ra\",\"Ġl ax\",\"ad em\",\"atur ation\",\"ãĥ ĵ\",\"ĠTra iler\",\"ĠE NG\",\"ĠBows er\",\"Ġatt m\",\"D ur\",\"80 7\",\"Ġsid x\",\"Ġc ider\",\"ĠA ffect\",\"Ġw oven\",\"ĠBark er\",\"ben ef\",\"Ġdst g\",\"ĠRy u\",\"> [\",\"Ġsq or\",\"S audi\",\"Ġis tg\",\"Ġindul ge\",\"pro c\",\"Ġdisg usted\",\"Ġcomp ounded\",\"Ġn em\",\"Ġschool ing\",\"ĠC ure\",\"process ing\",\"S ol\",\"Ġpro verb\",\"it ized\",\"ĠAlv arez\",\"Ġscar f\",\"Ġrect angular\",\"re ve\",\"Ġh ormonal\",\"ĠSt ress\",\"itiz en\",\"Ġ4 25\",\"girl s\",\"ĠNo ir\",\"ĠR app\",\"Ġmar ches\",\"ch urch\",\"ĠUs es\",\"Ġ40 5\",\"ĠBer m\",\"Ġord inances\",\"ĠJud gment\",\"Charg es\",\"ĠZ in\",\"Ġdust y\",\"Ġstraw berries\",\"Ġper ce\",\"ĠTh ur\",\"ĠDebor ah\",\"net flix\",\"ĠLam bert\",\"Ġam used\",\"ĠGu ang\",\"Y OU\",\"R GB\",\"ĠC CTV\",\"Ġf iat\",\"r ang\",\"Ġf ederation\",\"ĠM ant\",\"ĠB ust\",\"ĠM are\",\"respect ive\",\"ĠM igration\",\"ĠB IT\",\"59 0\",\"Ġpatriot ism\",\"Ġout lining\",\"reg ion\",\"ĠJos Ã©\",\"Ġbl asting\",\"ĠEz ra\",\"B s\",\"Ġundermin es\",\"ĠSm ooth\",\"Ġcl ashed\",\"rad io\",\"Ġtransition ing\",\"ĠBucc aneers\",\"ĠOw l\",\"Ġplug s\",\"Ġh iatus\",\"ĠPin ball\",\"Ġm ig\",\"ĠNut r\",\"ĠWolf e\",\"Ġinteg ers\",\"Ġor bits\",\"ĠEd win\",\"ĠDirect X\",\"b ite\",\"Ġbl azing\",\"v r\",\"Ed ge\",\"ĠP ID\",\"ex it\",\"ĠCom ed\",\"ĠPath finder\",\"ĠGu id\",\"ĠSign s\",\"ĠZ er\",\"ĠAg enda\",\"Ġreimburse ment\",\"M esh\",\"i Phone\",\"ĠMar cos\",\"ĠS ites\",\"h ate\",\"en burg\",\"Ġs ockets\",\"p end\",\"Bat man\",\"v ir\",\"ĠSH OW\",\"Ġprovision al\",\"con n\",\"ĠDeath s\",\"AT IVE\",\"Pro file\",\"sy m\",\"J A\",\"Ġnin ja\",\"inst alled\",\"id ates\",\"eb ra\",\"ĠOm aha\",\"Ġse izing\",\"ĠBe asts\",\"Ġsal ts\",\"M ission\",\"Gener ally\",\"ĠTr ilogy\",\"he on\",\"leg ates\",\"Ġd ime\",\"Ġf aire\",\"par able\",\"G raph\",\"Ġtotal ing\",\"Ġdiagram s\",\"ĠYan uk\",\"ple t\",\"ĠMe h\",\"Ġmyth ical\",\"ĠStep hens\",\"aut ical\",\"ochem istry\",\"Ġkil ograms\",\"Ġel bows\",\"anc ock\",\"ĠB CE\",\"ĠPr ague\",\"Ġimpro v\",\"ĠDev in\",\"Ġ\\\" \\\\\",\"par alle\",\"Ġsuprem acists\",\"ĠB illion\",\"Ġreg imen\",\"inn acle\",\"Ġrequ isite\",\"ang an\",\"ĠBur lington\",\"ain ment\",\"ĠObject ive\",\"oms ky\",\"G V\",\"Ġun ilateral\",\"Ġt c\",\"Ġh ires\",\"ment al\",\"Ġinvol untary\",\"Ġtrans pl\",\"ĠASC II\",\"Â ¨\",\"Ev ents\",\"Ġdoub ted\",\"ĠKa plan\",\"ĠCour age\",\"ig on\",\"ĠMan aging\",\"ĠT art\",\"Ġfalse hood\",\"ĠV iolet\",\"Ġair s\",\"Ġfertil izer\",\"Brit ain\",\"Ġaqu atic\",\"ou f\",\"W ords\",\"ĠHart ford\",\"Ġeven ings\",\"ĠV engeance\",\"qu ite\",\"G all\",\"ĠP ret\",\"Ġp df\",\"ĠL M\",\"ĠSo chi\",\"ĠInter cept\",\"9 20\",\"Ġprofit ability\",\"ĠId le\",\"ĠMac Donald\",\"ĠEst ablishment\",\"um sy\",\"Ġgather ings\",\"ĠN aj\",\"Charl ie\",\"Ġas cent\",\"ĠProt ector\",\"Ġal gebra\",\"Ġbi os\",\"for ums\",\"EL S\",\"Introdu ced\",\"Ġ3 35\",\"Ġastron omy\",\"Cont ribut\",\"ĠPol ic\",\"Pl atform\",\"Ġcontain ment\",\"w rap\",\"Ġcoron ary\",\"ĠJ elly\",\"man ager\",\"Ġheart breaking\",\"c air\",\"ĠChe ro\",\"c gi\",\"Med ical\",\"ĠAccount ability\",\"! !\\\"\",\"oph ile\",\"Ġpsych otic\",\"ĠRest rict\",\"Ġequ itable\",\"iss ues\",\"Ġ19 05\",\"ĠN ek\",\"c ised\",\"ĠTr acking\",\"Ġo zone\",\"Ġcook er\",\"ros is\",\"Ġre open\",\"Ġinf inity\",\"ĠPharm aceutical\",\"ens ional\",\"Att empt\",\"ĠR ory\",\"Mar co\",\"Ġawa its\",\"H OW\",\"t reated\",\"Ġbol st\",\"Ġreve red\",\"Ġp ods\",\"opp ers\",\"00 10\",\"Ġampl itude\",\"ric an\",\"SP ONSORED\",\"Ġtrou sers\",\"Ġhal ves\",\"ĠK aine\",\"ĠCut ler\",\"ĠA UTH\",\"Ġsplend id\",\"Ġprevent ive\",\"ĠDud ley\",\"if acts\",\"umin ati\",\"ĠY in\",\"Ġad mon\",\"ĠV ag\",\"Ġin verted\",\"Ġhast ily\",\"ĠH ague\",\"L yn\",\"Ġled ger\",\"Ġastron omical\",\"get ting\",\"Ġcirc a\",\"ĠC ic\",\"ĠTenn is\",\"Lim ited\",\"Ġd ru\",\"ĠBY U\",\"Ġtrave llers\",\"Ġp ane\",\"ĠInt ro\",\"Ġpatient ly\",\"Ġa iding\",\"Ġlo os\",\"ĠT ough\",\"Ġ29 3\",\"Ġconsum es\",\"Source File\",\"Ġ\\\"\\\" \\\"\",\"Ġbond ing\",\"Ġtil ted\",\"Ġmenstru al\",\"ĠCel estial\",\"UL AR\",\"Plug in\",\"Ġrisk ing\",\"N az\",\"ĠRiy adh\",\"Ġacc redited\",\"Ġsk irm\",\"é Ľ\",\"Ġexam iner\",\"Ġmess ing\",\"Ġnear ing\",\"ĠC hern\",\"ĠBeck ham\",\"Ġsw apped\",\"Ġgo ose\",\"K ay\",\"Ġlo fty\",\"ĠWal let\",\"Ġ[ '\",\"Ġap ocalypse\",\"Ġb amboo\",\"ĠSP ACE\",\"ĠEl ena\",\"Ġ30 6\",\"ac ons\",\"Ġtight ened\",\"Ġadolesc ence\",\"Ġrain y\",\"Ġvandal ism\",\"ĠNew town\",\"Ġcon ject\",\"c akes\",\"Ġche ated\",\"Ġmoder ators\",\"par ams\",\"E FF\",\"Ġdece it\",\"ĠST L\",\"ĠTanz ania\",\"ĠR I\",\"Ġ19 23\",\"ĠEx ile\",\"the l\",\"Ġthe olog\",\"Ġquir ky\",\"ĠIr vine\",\"Ġneed y\",\"or is\",\"U m\",\"K a\",\"Ġmail box\",\"3 22\",\"Ġb os\",\"ĠPet ra\",\"K ING\",\"Ġenlarg ed\",\"O ften\",\"Ġbad ass\",\"Ġ3 43\",\"ĠPl aces\",\"ĠC AD\",\"Ġpr istine\",\"Ġinterven ing\",\"d irection\",\"Ġl az\",\"ĠD SM\",\"Ġproject ing\",\"ĠF unk\",\"ag og\",\"pay ment\",\"n ov\",\"Ġch atter\",\"AR B\",\"Ġexam inations\",\"ĠHouse hold\",\"ĠG us\",\"F ord\",\"4 14\",\"B oss\",\"Ġmy stic\",\"Ġle aps\",\"ĠB av\",\"ul z\",\"b udget\",\"Foot ball\",\"Ġsubsid ized\",\"Ġfirst hand\",\"Ġcoinc ide\",\"oc ular\",\"Con n\",\"ĠColl abor\",\"Ġfool s\",\"am ura\",\"ah ar\",\"r ists\",\"Ġsw ollen\",\"Ġexp ended\",\"ĠP au\",\"s up\",\"Ġsp ar\",\"Ġkey note\",\"s uff\",\"Ġunequ al\",\"Ġprogress ing\",\"str ings\",\"ĠGamer gate\",\"Dis ney\",\"ĠEle ven\",\"om nia\",\"Ġscript ed\",\"Ġear ners\",\"bro ther\",\"ĠEn abled\",\"æ ³\",\"Ġlar vae\",\"ĠL OC\",\"m ess\",\"Wil son\",\"ĠTem plate\",\"success fully\",\"Ġparam ount\",\"Ġcamoufl age\",\"Ġbind s\",\"ĠQu iet\",\"ĠSh utterstock\",\"r ush\",\"Ġmasc ot\",\"fort une\",\"ĠCol t\",\"ĠBe yon\",\"hab i\",\"Ġha irc\",\"Ġ26 7\",\"ĠDe us\",\"Ġtw itch\",\"Ġconcent rating\",\"Ġn ipples\",\"c ible\",\"Ġg ir\",\"N Z\",\"M ath\",\"n ih\",\"Requ ired\",\"Ġp onder\",\"ĠS AN\",\"Ġwedd ings\",\"Ġl oneliness\",\"N ES\",\"ĠMah jong\",\"69 5\",\"add le\",\"ĠGar ner\",\"ĠC OUR\",\"Br idge\",\"Ġsp ree\",\"ĠCald well\",\"Ġbri bery\",\"Ġï¿½ï¿½ï¿½ï¿½ ï¿½ï¿½ï¿½ï¿½\",\"plug ins\",\"Ġr acket\",\"Ġchamp agne\",\"vers ible\",\"V ote\",\"Ġmod ifiers\",\"May or\",\"6 80\",\"Ġassemb lies\",\"ĠS ultan\",\"ĠN ing\",\"ĠLad ies\",\"Ġsulf ur\",\"Ġor bs\",\"Ġ---- -\",\"____ ___\",\"ĠJournal ism\",\"Ġes ports\",\"Ġl ush\",\"Ġh ue\",\"Ġspect ral\",\"H onest\",\"ãĥ ı\",\"Ġbus hes\",\"Ġrein forcement\",\"Ġre opened\",\"ĠWhe els\",\"ĠM org\",\"rie ving\",\"Ġaux iliary\",\"Ġj Query\",\"ĠB AT\",\"tes que\",\"Ġver tex\",\"p ure\",\"f rey\",\"ãĤ º\",\"d os\",\"Ġty ph\",\"Ġc ull\",\"Ġe q\",\"Ġdec on\",\"Ġtoss ing\",\"Ġdispar ate\",\"ĠBr igham\",\"print f\",\"led ged\",\"Ġsu nd\",\"Ġco zy\",\"Ġhepat itis\",\"per forming\",\"Ġav al\",\"ĠG G\",\"f uture\",\"Ġpet ertodd\",\"ĠKos ovo\",\"Ġmagn ets\",\"Al ready\",\"ĠEd ison\",\"ĠCe res\",\"ĠRA ID\",\"Ġbrill iance\",\"57 6\",\"Ġder ives\",\"Ġhypert ension\",\"ĠÎ Ķ\",\"Ġlamb da\",\"Ġfl air\",\"Ġmission aries\",\"Ġrap es\",\"ĠSt arter\",\"ĠMon ths\",\"Ġdef y\",\"Ġseism ic\",\"ĠR aphael\",\"Ġeuro zone\",\"65 6\",\"z sche\",\"Ġscr atched\",\"Ġb ows\",\"ĠLenn on\",\"ĠGa ia\",\"Ġdri pping\",\"f acts\",\"A le\",\"Ġfrog s\",\"ĠBre ast\",\"ogene ity\",\"ĠProsecut or\",\"Ġampl ified\",\"ĠHod g\",\"ĠF n\",\"Th ousands\",\"ĠNI H\",\"ĠMonitor ing\",\"FT WARE\",\"ĠPri ebus\",\"ĠG rowing\",\"hun ter\",\"Ġdiagn ose\",\"ĠM ald\",\"ĠL R\",\"Ġcrown ed\",\"Ġburst ing\",\"Ġdiss olution\",\"j avascript\",\"Ġuseful ness\",\"ĠExec ution\",\": (\",\"ĠIv ory\",\"a ah\",\"Ġpersecut ed\",\"viol ence\",\"ist as\",\"ĠCr ate\",\"Ġimpuls es\",\"ĠSp ani\",\"ed es\",\"Hand le\",\"ĠZ erg\",\"think able\",\"Last ly\",\"Ġspont aneously\",\"Ġinconven ient\",\"Ġdismiss ing\",\"Ġpl otted\",\"Ġeight y\",\"Ġ7 37\",\"r ish\",\"ĠThor nton\",\"ath am\",\"Ġsit com\",\"V en\",\"Rec ipe\",\"t el\",\"l und\",\"Ġcle ars\",\"ĠSas uke\",\"Ġ25 8\",\"Ġopt ing\",\"Ġen raged\",\"est hetic\",\"ĠA e\",\"uch s\",\"Pre p\",\"Fl ow\",\"Ġrun off\",\"ĠE ating\",\"ĠG iles\",\"ĠAct ing\",\"res ources\",\"ib aba\",\"Ġr pm\",\"Ġske wed\",\"ĠBl anc\",\"ĠS akuya\",\"Ġhot ter\",\"Ġ19 24\",\"op ian\",\"ck o\",\"Ġcr umbling\",\"Ġcapt ains\",\"ĠAppropri ations\",\"le aders\",\"dro pping\",\"an uts\",\"Ġrevers ing\",\"ĠP ose\",\"ĠS ek\",\"Sc ot\",\"ĠIde a\",\"c ise\",\"ĠSloven ia\",\"Ġ3 17\",\"Do ctor\",\"Ġcro cod\",\"ald i\",\"Se a\",\"ĠFar rell\",\"Ġmerc enaries\",\"ĠR NC\",\"ĠGu ess\",\"Ġp acing\",\"M achine\",\"Streamer Bot\",\"ĠChar ity\",\"Ġ29 8\",\"Ġcann ons\",\"ĠTob y\",\"TPP StreamerBot\",\"ĠPass ion\",\"cf g\",\"Th om\",\"Ġbad ges\",\"ĠBern stein\",\". âĢĵ\",\"ĠP OP\",\"ĠCon j\",\"Ġinitial ization\",\"Ġbiod iversity\",\"D ub\",\"Ġfeud al\",\"Ġdisclaim er\",\"Ġc row\",\"Ġign ition\",\"ar f\",\"S HA\",\"Ġk Hz\",\"h azard\",\"ĠArt ists\",\"oe uv\",\"67 9\",\"ĠRud y\",\"N ine\",\"ĠRam adan\",\"å ½\",\"itt o\",\"Ġadren aline\",\"C ert\",\"Ġsmell ed\",\"Ġimp unity\",\"Ġag endas\",\"ĠRe born\",\"ĠCon cent\",\"ĠSe ems\",\"Ġo mega\",\"ĠDust in\",\"Ġback er\",\"ĠSau ce\",\"ĠBoy le\",\"W IN\",\"Ġsp ins\",\"Ġpa uses\",\"u pt\",\"Ġshred ded\",\"Ġstra pped\",\"ĠCor ruption\",\"Ġscr atches\",\"Ġn i\",\"Ġatt ire\",\"ĠS AF\",\"Factory Reloaded\",\"ĠI PS\",\"Ġ( %\",\"Ġsem inar\",\"f ocus\",\"c ivil\",\"Ġ18 60\",\"int osh\",\"Ġcontin ual\",\"Ġabbre vi\",\"ĠS ok\",\"oc obo\",\"X M\",\"Ġfr antic\",\"Ġunavoid able\",\"Ġar tery\",\"Ġannot ations\",\"b ath\",\"Cl imate\",\"Ġd ors\",\"ĠSl ide\",\"co ord\",\"ĠRel oad\",\"ĠL DL\",\"ĠLove craft\",\"Ġunim agin\",\"Ġresemb led\",\"Ġbarr acks\",\"n p\",\"Ġsurrog ate\",\"Ġcategor ized\",\"ãĤ ©\",\"Ġvacc inated\",\"Ġdrain age\",\"Ġind ist\",\"ĠWhats App\",\"Ġ18 70\",\"oler ance\",\"inv oke\",\"am orph\",\"Ġrecon nect\",\"Ġem anc\",\"Ġblind ness\",\"Ġ12 80\",\"intern et\",\"c ollar\",\"Ġalt ru\",\"Ġab yss\",\"ĠT RI\",\"65 7\",\"Ġinf used\",\"HE AD\",\"Ġforest ry\",\"ĠWood y\",\"ĠC i\",\"w i\",\"s am\",\"78 4\",\"hol iday\",\"Ġmog ul\",\"ĠF ees\",\"ĠD EN\",\"In ternal\",\"ur bed\",\"f usc\",\"at om\",\"ĠIll usion\",\"Ġpoll ed\",\"Ġfl ap\",\"Ġco ax\",\"L GBT\",\"An aly\",\"ĠSect ions\",\"ĠCalif orn\",\"em n\",\"Ġh ither\",\"ĠN IGHT\",\"Ġn ailed\",\"ĠPip eline\",\"39 1\",\"o of\",\"ĠPr imal\",\"vere nd\",\"Ġsl ashing\",\"Ġret ri\",\"avi our\",\"Ġdepart ing\",\"g il\",\"IS C\",\"Ġmid way\",\"Ġultras ound\",\"Ġbeh aving\",\"ĠT ara\",\"class es\",\"V irtual\",\"ĠColon ial\",\"Ġstri pping\",\"Ġorchestr ated\",\"ĠGra ves\",\"45 2\",\"ĠIron ically\",\"ĠWrit ers\",\"Ġl ends\",\"ĠMan z\",\"Ġra ven\",\"Ġoxid ative\",\"Ġ26 6\",\"EL F\",\"act ually\",\"asc ar\",\"D raft\",\"Ġfavour able\",\"Ġhumili ating\",\"Ġf idelity\",\"ĠH of\",\"ĠX uan\",\"49 6\",\"Ġlay ered\",\"at is\",\"79 0\",\"Ġpay check\",\"it on\",\"K ar\",\"ĠVM ware\",\"ĠFar mer\",\"Ġserv ic\",\"gl omer\",\"Ġsl ump\",\"ĠFab ric\",\"ĠD OC\",\"est ing\",\"Ġreass ure\",\"Ġph yl\",\"v olt\",\"it ory\",\"R ules\",\"Ġoxid ation\",\"Ġpri zed\",\"Ġmist ress\",\"ĠDj ango\",\"WAR N\",\"å ĳ\",\"Ġenc ode\",\"ĠFeed back\",\"Ġstupid ity\",\"I an\",\"ĠYugoslav ia\",\"× ¨\",\"ac l\",\"UT E\",\"19 77\",\"Ġqual ifies\",\"Ġpuls es\",\"pret ty\",\"Ġfro ze\",\"Ġs s\",\"Iter ator\",\"Ġur gently\",\"Ġm ailed\",\"ĠCh am\",\"Ġsust aining\",\"Ġbas il\",\"Ġpupp ies\",\"il ant\",\"ĠP LEASE\",\"l ap\",\"ace ous\",\"F ear\",\"ĠMaster y\",\"aut omatic\",\"ĠT AG\",\"Ġant im\",\"ag les\",\"47 3\",\"fram es\",\"Ġwh ispers\",\"ĠWho ever\",\"Ġbra very\",\"ĠUK IP\",\"ract ions\",\"\\\"\\\" \\\"\",\"Ġt ame\",\"Ġpart ed\",\"every thing\",\"CON T\",\"Ġind ebted\",\"Ġadd r\",\"re k\",\"IR ED\",\"Ġem inent\",\"cl inton\",\"Ġo usted\",\"Ġreview er\",\"Ġmelt down\",\"Ġre arr\",\"ĠY ao\",\"the real\",\"aby te\",\"Ġst umbling\",\"Ġbat ches\",\"Ġ25 9\",\"Ġcontrace ptive\",\"Ġprost itute\",\"ens is\",\"De cl\",\"ĠSt rikes\",\"M ilitary\",\"ĠO ath\",\"v acc\",\"pp ings\",\"05 2\",\"Ġpart Name\",\"amp ing\",\"Rep orts\",\"K I\",\"CH R\",\"Ġsubt ly\",\"sw ers\",\"Bl ake\",\"us ual\",\"Ġcontest ants\",\"Ġcart ridges\",\"ĠGRE AT\",\"Ġbl ush\",\"ĠâĢ º\",\"47 2\",\"Ġreason ed\",\"ãĥ ¤\",\"paralle led\",\"Ġd yn\",\"ag ate\",\"Ġnight ly\",\"å Ĩ\",\"55 6\",\"Ġsem antic\",\"ĠAdv oc\",\"Ġ !!\",\"Ġdisag rees\",\"ĠB W\",\"V eh\",\"Ġharm ing\",\"Ġembr aces\",\"Ġstri ves\",\"Ġin land\",\"ĠK ard\",\"Ġhe ats\",\"ĠGin ny\",\"ut an\",\"ern aut\",\"yl ene\",\"ĠE lev\",\"J D\",\"Ġh ars\",\"ĠStar r\",\"Ġsk ysc\",\"Ġcollabor ators\",\"Us ually\",\"Ġrev olutions\",\"ĠSTAT S\",\"Ġdism antle\",\"Ġconfident ly\",\"Ġkin etic\",\"Al i\",\"Ġpercent ile\",\"Ġextract ing\",\"ill ian\",\"est ead\",\"Ġphysic ists\",\"ĠMarsh al\",\"Ġfell owship\",\"Ġd ashed\",\"ĠU R\",\"ĠSi oux\",\"ĠComp act\",\"am ide\",\"P ython\",\"ĠLe igh\",\"ĠPharm ac\",\"ist rates\",\"her ical\",\"Ġf ue\",\"ĠE min\",\"Ġ( {\",\"ĠNeighbor hood\",\"Ġdisrupt ing\",\"ĠD up\",\"Ġg land\",\"ĠSe v\",\"ĠMar ian\",\"arg on\",\"ĠD und\",\"Ġ< !--\",\"Ġstr and\",\"Ġstadium s\",\"z os\",\"Ġpsych osis\",\"ĠR ack\",\"Ġbrilliant ly\",\"ï¸ ı\",\"Ġsubmer ged\",\"ĠInst it\",\"ĠCh ow\",\"Ġc ages\",\"ĠH ats\",\"ĠU rs\",\"Ġdil uted\",\"us at\",\"ien ne\",\"ĠMembers hip\",\"ĠBur k\",\"Ġ ie\",\"Ġarche type\",\"D rug\",\"ult on\",\"ĠSp ock\",\"ĠMcK ay\",\"ĠDep end\",\"F eatured\",\"S oc\",\"19 78\",\"ĠB ere\",\"Ġrelent lessly\",\"Ġcripp ling\",\"Ġar thritis\",\"çĶ Ł\",\"ĠTrop ical\",\"ĠBul g\",\"ĠCher yl\",\"Ġadm irable\",\"Ġsub title\",\"Over ride\",\"Ġorig inating\",\"ĠC CP\",\"Ġsw ore\",\"ĠSo le\",\"ĠDis orders\",\"3 29\",\"Ġprocess ion\",\"Ġref urb\",\"Ġimm ersed\",\"requ ently\",\"Ġskept ics\",\"Ġcer amic\",\"m itter\",\"en stein\",\"b elt\",\"ĠT IT\",\"b idden\",\"Ġf ir\",\"m ist\",\"> ]\",\"Ġwe ave\",\"ĠParad ox\",\"Ġentr usted\",\"ĠBarcl ays\",\"Ġnovel ist\",\"og ie\",\"80 6\",\"Ġnin ety\",\"Ġdisag reements\",\"@@@@ @@@@\",\"ĠAus chwitz\",\"c ars\",\"ĠL ET\",\"t ub\",\"arant ine\",\"P OS\",\"Ġback story\",\"Ġcheer ful\",\"ĠR ag\",\"ek a\",\"bi ased\",\"Ġinexper ienced\",\"ak ra\",\"ĠW itt\",\"t an\",\"Ġrap ist\",\"Ġplate au\",\"ch al\",\"ĠInqu is\",\"exp ression\",\"Ġc ipher\",\"Ġsh aving\",\"add en\",\"re ly\",\"( \\\\\",\"ism a\",\"ĠReg ulatory\",\"CH AR\",\"ily n\",\"N VIDIA\",\"G U\",\"Ġmur m\",\"la us\",\"Christ opher\",\"Ġcontract ual\",\"ĠPro xy\",\"ĠJa ime\",\"ĠMethod ist\",\"Ġstew ards\",\"st a\",\"per ia\",\"Ġphys iology\",\"Ġbump ed\",\"Ġf ructose\",\"Austral ian\",\"ĠMet allic\",\"ĠMas querade\",\"ar b\",\"Ġprom ul\",\"Ġdown fall\",\"Ġbut cher\",\"Ġb our\",\"ĠIN FORMATION\",\"ĠB is\",\"pect s\",\"ad ena\",\"Ġcontempl ating\",\"ar oo\",\"cent ered\",\"ĠPe aks\",\"Us ed\",\"Ġmod em\",\"Ġg enders\",\"Ġ8 000\",\"37 1\",\"Ġm aternity\",\"ĠR az\",\"Ġrock ing\",\"Ġhandgun s\",\"ĠD ACA\",\"Aut om\",\"ĠN ile\",\"Ġtum ult\",\"ĠBenef it\",\"ĠAppro ach\",\"works hop\",\"ĠLe aving\",\"G er\",\"inst ead\",\"Ġvibr ations\",\"Ġrep ositories\",\"49 7\",\"ĠA unt\",\"ĠJ ub\",\"ĠExp edition\",\"Al pha\",\"Ġs ans\",\"Ġoverd ue\",\"Ġoverc rowd\",\"Ġlegisl atures\",\"Ġp aternal\",\"ĠLeon ardo\",\"Ġexp ressive\",\"Ġdistract ions\",\"Ġsil enced\",\"tr ust\",\"Ġb iking\",\"Ġ5 60\",\"Ġpropri et\",\"Ġimp osition\",\"Ġcon glomer\",\"Ġ= ================================================================\",\"ĠTe aching\",\"ĠY ose\",\"int ensive\",\"T own\",\"Ġtroll ing\",\"ĠGr ac\",\"ĠAS US\",\"Y o\",\"Ġspecial s\",\"ĠNep h\",\"ĠGod zilla\",\"Dat abase\",\"ĠHe gel\",\"Ġ27 2\",\"19 76\",\"ĠGl oria\",\"Ġdis emb\",\"ĠInvestig ations\",\"ĠB ane\",\"ag ements\",\"St range\",\"Ġtre asury\",\"ĠPl ays\",\"Ġundes irable\",\"Ġwid ening\",\"Ġverb ally\",\"Ġinf ancy\",\"Ġcut ter\",\"f ml\",\"Ġ21 00\",\"prot otype\",\"f ine\",\"Ġdec riminal\",\"Ġdysfunction al\",\"Ġbes ie\",\"ĠErn st\",\"z eb\",\"Ġnort heastern\",\"Ġa ust\",\"por ate\",\"ĠMar lins\",\"Ġsegreg ated\",\"ew orld\",\"ĠMa her\",\"Ġtra verse\",\"Ġmon astery\",\"ur gy\",\"G ear\",\"s and\",\"Com pl\",\"ĠE MP\",\"Ġpl ent\",\"ĠMer cer\",\"Ġ27 6\",\"TA BLE\",\"Config uration\",\"H undreds\",\"Ġpr ic\",\"Ġcollabor ating\",\"ĠPar amount\",\"ĠCumm ings\",\"Ġ( <\",\"Ġrecord er\",\"Ġfl ats\",\"Ġ4 16\",\"wh ose\",\"Font Size\",\"ĠOr bit\",\"Y R\",\"Ġwr ists\",\"Ġb akery\",\") }\",\"ĠB ounty\",\"ĠLanc aster\",\"Ġend ings\",\"acc ording\",\"ĠSal am\",\"e asy\",\"75 5\",\"ĠBur r\",\"ĠBarn ett\",\"onom ous\",\"Un ion\",\"Ġpreced ence\",\"ĠScholars hip\",\"ĠU X\",\"Ġroll out\",\"Ġbo on\",\"al m\",\"ĠCan ter\",\"æ µ\",\"Ġround ing\",\"Ġcl ad\",\"Ġv ap\",\"ĠF eatured\",\"is ations\",\"Ġ5 40\",\"pol ice\",\"Ġunsett ling\",\"Ġdr ifting\",\"ĠLum ia\",\"ĠObama Care\",\"ĠF avor\",\"Hy per\",\"ĠRoth schild\",\"ĠMil iband\",\"an aly\",\"ĠJul iet\",\"H u\",\"Ġrec alling\",\"a head\",\"69 6\",\"Ġunf avorable\",\"Ġd ances\",\"O x\",\"Ġleg ality\",\"Ġ40 3\",\"rom ancer\",\"Ġinqu ire\",\"ĠM oves\",\"\\\\ \\\">\",\"ĠVari ant\",\"ĠMess iah\",\"ĠL CS\",\"ĠBah Ã¡\",\"75 6\",\"Ġeyeb row\",\"ĠÂ ¥\",\"ĠMc F\",\"ĠFort y\",\"M as\",\"Ġpan icked\",\"Ġtransform ations\",\"q q\",\"Ġrev olves\",\"ring e\",\"ĠA i\",\"ax e\",\"Ġon ward\",\"ĠC FR\",\"ĠB are\",\"log in\",\"Ġliqu ids\",\"Ġde comp\",\"second ary\",\"il an\",\"ĠCon vert\",\"ami ya\",\"Ġprosecut ing\",\"Ġâī ¡\",\"ĠYork ers\",\"ĠByr ne\",\"sl ow\",\"aw ei\",\"J ean\",\"Ġ26 9\",\"ĠSky dragon\",\"Ġ Ã©\",\"ĠNicarag ua\",\"ĠHuck abee\",\"ĠHigh ly\",\"Ġamph ib\",\"ĠPast or\",\"ĠL ets\",\"Ġbl urred\",\"Ġvisc eral\",\"ĠC BO\",\"Ġcollabor ated\",\"z ig\",\"Leg al\",\"Ġapart heid\",\"Ġbr id\",\"Ġpres et\",\"ĠD ET\",\"ĠAM A\",\"× Ķ\",\"arch ing\",\"auc uses\",\"build er\",\"Ġpo etic\",\"Ġem ulator\",\"ĠMole cular\",\"Ġhon oring\",\"ise um\",\"Ġtract or\",\"ĠCl uster\",\"ĠCal m\",\"ared evil\",\"Ġsidew alks\",\"Ġviol in\",\"Ġgeneral ized\",\"ĠAle c\",\"Ġemb argo\",\"Ġfast ball\",\"ĠHT TPS\",\"ĠL ack\",\"ĠCh ill\",\"ri ver\",\"C hel\",\"ĠSw arm\",\"ĠLev ine\",\"ro ying\",\"L aunch\",\"Ġkick er\",\"Ġadd itive\",\"ĠDe als\",\"W idget\",\"cont aining\",\"Ġescal ate\",\"ĠOP EN\",\"Ġtwe aked\",\"Ġst ash\",\"Ġsp arks\",\"ĠEs sex\",\"ĠE cc\",\"Ġconv ict\",\"Ġblog ging\",\"I ER\",\"ĠH L\",\"Ġmurd erers\",\"75 9\",\"ĠH ib\",\"Ġde pl\",\"ĠJ ord\",\"S ac\",\"Ġdis sect\",\"ĠHow e\",\"os her\",\"Ġcustom izable\",\"ĠFran z\",\"Ġat ro\",\"Ä ĩ\",\"Ġ000 4\",\"Ġout post\",\"R oss\",\"Ġglyph osate\",\"ĠHast ings\",\"ĠBE FORE\",\"Ġsh ove\",\"o pped\",\"ĠSc ala\",\"Ġam ulet\",\"an ian\",\"Ġexacerb ated\",\"Ġe ater\",\"47 1\",\"UM E\",\"Ġpul p\",\"izont al\",\"ĠZ am\",\"ĠAT I\",\"imm une\",\"aby tes\",\"Ġunnecess arily\",\"ĠC AT\",\"ĠAx is\",\"Ġvisual ize\",\"Ã ī\",\"ĠRad ical\",\"f m\",\"Doc uments\",\"ĠFor rest\",\"Ġcontext ual\",\"ĠSy mbol\",\"Ġtent ative\",\"ĠDO ES\",\"ĠGood s\",\"Ġintermitt ent\",\"} :\",\"medi ated\",\"Ġridic ule\",\"Ġathe ism\",\"Ġpath ogens\",\"ĠM um\",\"Ġre introdu\",\"Ġ30 7\",\"i HUD\",\"Ġflash light\",\"Ġsw earing\",\"Ġp engu\",\"B u\",\"Ġrot ated\",\"ĠCr ane\",\"Ġ() );\",\"Ġfashion able\",\"Ġendors ing\",\"46 3\",\") [\",\"Ġingest ion\",\"Ġcook s\",\"Ġ9 50\",\"ot omy\",\"ĠIm am\",\"Ġk a\",\"Ġte aser\",\"ĠGhost s\",\"ĠãĤ µ\",\"19 69\",\"Ï ĥ\",\"ub by\",\"Ġconver ter\",\"zan ne\",\"end e\",\"ĠPre par\",\"ĠNic kel\",\"ĠChim era\",\"h im\",\"ĠTyr ann\",\"ĠSabb ath\",\"ĠNich ols\",\"Ġra pt\",\"ih ar\",\"Ġshe lling\",\"Ġillum inate\",\"Ġdent ist\",\"ut or\",\"ĠInteg ration\",\"Ġwh ims\",\"ĠLiter ary\",\"Be aut\",\"Ġp archment\",\"ag ara\",\"Br and\",\"Ġder og\",\"âĢ¦ )\",\"ĠNor se\",\"Ġunw itting\",\"Ġc uc\",\"Ġborder line\",\"Ġupset ting\",\"Ġrec ourse\",\"Ġd raped\",\"ĠRad ar\",\"Ġcold er\",\"ĠPep si\",\"im inary\",\"], [\",\"65 8\",\"V i\",\"ĠF rem\",\"ĠP es\",\"Ġveter inary\",\"ĠT ED\",\"ĠEp idem\",\"n ova\",\"k id\",\"Ġdev out\",\"o ct\",\"j ad\",\"M oh\",\"ĠP AY\",\"Ġge ometric\",\"Ġ3 23\",\"Ġcircum ference\",\"ich ick\",\"19 75\",\"ĠY uri\",\"ĠSh all\",\"ĠH over\",\"un in\",\"S pr\",\"Ġg raft\",\"ĠHapp iness\",\"Ġdisadvant ages\",\"att acks\",\"Ġhub s\",\"ĠStar Craft\",\"é ĸ\",\"Ġgall eries\",\"ĠKor ra\",\"Ġgrocer ies\",\"ĠGors uch\",\"Ġrap ists\",\"Ġfun gi\",\"ĠTyph oon\",\"V ector\",\"ĠEm press\",\"b attle\",\"4 68\",\"Ġparas ite\",\"ĠBom ber\",\"S G\",\"ex ist\",\"ĠP f\",\"Ġun se\",\"Ġsurge ons\",\"B irth\",\"ĠUn sure\",\"ĠPrint ed\",\"ĠBehavior al\",\"ĠA ster\",\"Pak istan\",\"Ġun ethical\",\"Ġs v\",\"ĠIo T\",\"Ġlay outs\",\"P ain\",\"Ġconst ants\",\"ĠL W\",\"ĠB ake\",\"Ġtow els\",\"Ġdeterior ation\",\"ĠBol ivia\",\"Ġblind ed\",\"ĠW arden\",\"ĠMist ress\",\"Ġon stage\",\"Ġcl ans\",\"ĠB EST\",\"19 60\",\"Ġant ique\",\"Ġrhet orical\",\"ĠPer cy\",\"ĠRw anda\",\", .\",\"B ruce\",\"Ġtra umat\",\"ĠParliament ary\",\"Ġfoot note\",\"id ia\",\"ĠLear ned\",\"se eking\",\"gen ic\",\"Ġdim ensional\",\"H ide\",\"èĢ ħ\",\"Ġintrig ue\",\"in se\",\"Ġle ases\",\"Ġapp rentices\",\"w ashing\",\"Ġ19 26\",\"V ILLE\",\"Ġsw oop\",\"s cl\",\"Ġbed rooms\",\"on ics\",\"ĠCr unch\",\"comp atible\",\"Ġincap ac\",\"ĠYemen i\",\"ash tra\",\"z hou\",\"d anger\",\"Ġmanifest ations\",\"ĠDem ons\",\"AA F\",\"Secret ary\",\"ACT ED\",\"L OD\",\"Ġam y\",\"ra per\",\"eth nic\",\"4 17\",\"Ġpos itives\",\"Ġ27 3\",\"ĠRefuge es\",\"Ġus b\",\"ĠV ald\",\"odd y\",\"ĠMahm oud\",\"As ia\",\"Ġskull s\",\"ĠEx odus\",\"ĠComp et\",\"ĠL IC\",\"ĠM ansion\",\"ĠA me\",\"Ġconsolid ate\",\"storm s\",\"ont ent\",\"99 6\",\"Ġcl en\",\"Ġm ummy\",\"fl at\",\"75 8\",\"ĠV OL\",\"oter ic\",\"n en\",\"ĠMin ute\",\"S ov\",\"Ġfin er\",\"R h\",\"ly cer\",\"Ġreinforce ments\",\"ĠJohann es\",\"ĠGall agher\",\"Ġgym n\",\"S uddenly\",\"Ġext ortion\",\"k r\",\"i ator\",\"T a\",\"Ġhippocamp us\",\"N PR\",\"ĠComput ing\",\"Ġsquare ly\",\"Ġmod elling\",\"ĠFor ums\",\"ĠL isp\",\"ĠKrish na\",\"Ġ3 24\",\"Ġr ushes\",\"Ġens ued\",\"Ġcre eping\",\"on te\",\"n ai\",\"il ater\",\"ĠHorn ets\",\"Ġob livious\",\"IN ST\",\"55 9\",\"Ġjeopard y\",\"Ġdistingu ishing\",\"j ured\",\"Ġbeg s\",\"sim ilar\",\"ph ot\",\"5 30\",\"ĠPark way\",\"Ġs inks\",\"ĠHearth stone\",\"ib ur\",\"ĠBat on\",\"Av oid\",\"Ġd ancer\",\"Ġmag istrate\",\"ary n\",\"Ġdisturb ances\",\"ĠRom ero\",\"Ġpar aph\",\"Ġmis chief\",\"âĸ ĵ\",\"ĠSh aria\",\"Ġur inary\",\"r oute\",\"iv as\",\"f itted\",\"Ġeject ed\",\"ĠAl buquerque\",\"Ġ4 70\",\"Ġirrit ated\",\"ĠZ ip\",\"ĠB iol\",\"Ã į\",\"Ġden ounce\",\"Ġbin aries\",\"ĠVer se\",\"Ġopp os\",\"ĠKend rick\",\"ĠG PL\",\"Ġsp ew\",\"ĠEl ijah\",\"ĠE as\",\"Ġdr ifted\",\"so far\",\"Ġannoy ance\",\"ĠB ET\",\"47 4\",\"ĠSt rongh\",\"it ates\",\"ĠCogn itive\",\"oph one\",\"ĠIdent ification\",\"ocr ine\",\"connect ion\",\"Ġbox er\",\"ĠAS D\",\"ĠAre as\",\"Y ang\",\"t ch\",\"ull ah\",\"Ġdece ive\",\"Comb at\",\"ep isode\",\"cre te\",\"W itness\",\"Ġcondol ences\",\"ht ar\",\"Ġhe als\",\"Ġbuck ets\",\"ĠLA W\",\"B lu\",\"Ġsl ab\",\"ĠOR DER\",\"oc l\",\"att on\",\"ĠSteven son\",\"ĠG inger\",\"ĠFriend ly\",\"ĠVander bilt\",\"sp irit\",\"ig l\",\"ĠReg arding\",\"ĠPR OG\",\"Ġse aling\",\"start ing\",\"Ġcard inal\",\"ĠV ec\",\"ĠBe ir\",\"Ġmillisec onds\",\"we ak\",\"per se\",\"Ġster ile\",\"ĠCont emporary\",\"ĠPh ant\",\"ĠCl o\",\"Ġout p\",\"Ġex iled\",\"Ġ27 7\",\"Ġself ie\",\"Ġman ic\",\"Ġn ano\",\"ter ms\",\"Alex ander\",\"Ġres olves\",\"Ġmillenn ia\",\"Ġexpl odes\",\"Ġconst ellation\",\"Ġadul tery\",\"m otion\",\"D OC\",\"Ġbroad casters\",\"Ġkinderg arten\",\"ĠMay weather\",\"ĠE co\",\"ich o\",\"Ġ28 7\",\"l aun\",\"Ġm ute\",\"Ġdisc reet\",\"Ġpres chool\",\"Ġpre empt\",\"De lete\",\"ĠFre ed\",\"P i\",\"H K\",\"Ġblock er\",\"ĠC umber\",\"Ġw rought\",\"d ating\",\"Ġins urer\",\"Ġquot as\",\"Ġpre ached\",\"Ġev iction\",\"ĠReg ina\",\"ĠP ens\",\"Ġsevent een\",\"ĠN ass\",\"D ick\",\"Ġfold s\",\"Ġd otted\",\"ĠA ad\",\"Un iversal\",\"Ġp izz\",\"ĠG uru\",\"Ġso ils\",\"Ġno vice\",\"ĠNe ander\",\"Ġst ool\",\"Ġdeton ated\",\"ĠPik achu\",\"ĠMass ive\",\"IV ER\",\"ĠAb del\",\"Ġsubdu ed\",\"Ġtall est\",\"Ġprec arious\",\"Ġa y\",\"r ification\",\"ĠOb j\",\"c ale\",\"Ġun question\",\"cul osis\",\"ad as\",\"igr ated\",\"D ays\",\"Ġque ens\",\"ĠGaz ette\",\"ĠCol our\",\"ĠBow man\",\"ĠJ J\",\"Ã¯ ve\",\"Ġdomin ates\",\"Stud ent\",\"Ġm u\",\"Ġback log\",\"ĠElect ro\",\"Tr uth\",\"48 3\",\"Ġcond ensed\",\"r ules\",\"ĠCons piracy\",\"Ġacron ym\",\"hand led\",\"ĠMat te\",\"j ri\",\"ĠImp ossible\",\"l ude\",\"cre ation\",\"Ġwar med\",\"ĠSl ave\",\"Ġmis led\",\"Ġfer ment\",\"ĠK ah\",\"ink i\",\"ke leton\",\"cy l\",\"ĠKar in\",\"Hun ter\",\"Reg ister\",\"ĠSur rey\",\"Ġst ares\",\"ĠW idth\",\"ĠN ay\",\"ĠSk i\",\"Ġblack list\",\"uck et\",\"Ġexp ulsion\",\"im et\",\"Ġret weet\",\"vant age\",\"Fe ature\",\"Ġtro opers\",\"Ġhom ers\",\"9 69\",\"Ġconting ency\",\"ĠW TC\",\"ĠBrew er\",\"fore ign\",\"W are\",\"S olar\",\"Ġund ue\",\"RE C\",\"ulner able\",\"path ic\",\"ĠBo ise\",\"Ġ3 22\",\"Ġarous ed\",\"ĠY ing\",\"ä¸ į\",\"uel ess\",\"Ġp as\",\"Ġmor p\",\"Ġfl oral\",\"Ex press\",\"ud ging\",\"k B\",\"ĠGr anted\",\"Ø ¯\",\"ĠMich a\",\"ĠGoth ic\",\"ĠSPEC IAL\",\"ĠRic ardo\",\"F ran\",\"Ġadminister ing\",\"6 20\",\"por a\",\"ĠÂ ®\",\"Ġcomprom ises\",\"Ġb itten\",\"Ac cept\",\"Th irty\",\"Ð ²\",\"Ġmater ially\",\"ĠTer r\",\"ig matic\",\"ch ains\",\"Ġdo ve\",\"stad t\",\"Mar vel\",\"FA ULT\",\"Ġwind shield\",\"Ġ3 36\",\"ad ier\",\"Ġsw apping\",\"Ġflaw less\",\"ĠPred ator\",\"ĠMiche le\",\"Ġprop ulsion\",\"ĠPsych ic\",\"Ġassign ing\",\"Ġfabric ation\",\"Ġbar ley\",\"l ust\",\"Ġtow ering\",\"Ġalter cation\",\"ĠBent ley\",\"Sp here\",\"Ġtun a\",\"ĠClass es\",\"Fre edom\",\"un er\",\"L ady\",\"v oice\",\"Ġcool est\",\"or r\",\"Ġpal p\",\"$ {\",\"Ġhyster ia\",\"ĠMet atron\",\"p ants\",\"Ġspawn ing\",\"Exper ts\",\"ĠInvest ors\",\"ĠAn archy\",\"Ġshr unk\",\"ĠVict im\",\"Ġ28 9\",\"Ġec stasy\",\"ĠB inding\",\"58 5\",\"ĠMel ody\",\"57 8\",\"ot ally\",\"ĠE tsy\",\"lig a\",\"Ġapplaud ed\",\"Ġswe ating\",\"Ġredist ributed\",\"Ġpop corn\",\"Ġsem inal\",\"f ur\",\"ĠNeuro science\",\"R and\",\"ĠO st\",\"ĠMadd en\",\"ĠIncre asing\",\"ĠDaw kins\",\"ĠSub way\",\"Ġar sen\",\"cons erv\",\"B UR\",\"Ġsp iked\",\"ĠLy ft\",\"ĠImper ium\",\"ĠDrop box\",\"Ġfav oured\",\"Ġencomp asses\",\"gh ost\",\"Ġins pires\",\"Ġbur geoning\",\"ĠY oshi\",\"ĠVert ical\",\"ĠAud itor\",\"Ġint ending\",\"Ġfilib uster\",\"Bl oom\",\"f ac\",\"ĠCav s\",\"ign ing\",\"Ġcowork ers\",\"ĠBarb arian\",\"rem ember\",\"FL AG\",\"Ġaudit ory\",\"ason ry\",\"Col lege\",\"Ġmut ed\",\"gem ony\",\"ob in\",\"ĠPsych o\",\"9 68\",\"Ġlav ish\",\"Ġhierarch ical\",\"ĠDr one\",\"ou k\",\"Ġcripp led\",\"ĠMax im\",\"Sl ot\",\"Ġqu iz\",\"ĠV id\",\"if ling\",\"Ġarchae ologists\",\"Ġabandon ment\",\"d ial\",\"le on\",\"ĠF as\",\"T ed\",\"Ġr aspberry\",\"Ġmaneu vers\",\"Ġbehavi ours\",\"Ġins ure\",\"Ġrem od\",\"Sw itch\",\"h oe\",\"Ġsp aced\",\"Ġafford ability\",\"ĠF ern\",\"not ation\",\"ĠBal anced\",\"Ġoccup ies\",\"en vironment\",\"Ġneck lace\",\"Ġsed an\",\"F U\",\"ĠBrav o\",\"Ġab users\",\"ĠAn ita\",\"met adata\",\"ĠG ithub\",\"ait o\",\"ĠF aster\",\"ĠWass erman\",\"ĠF lesh\",\"Ġth orn\",\"r arily\",\"ĠMer ry\",\"w ine\",\"Ġpopul ace\",\"ĠL ann\",\"Ġrepair ing\",\"Ġpsy che\",\"Ġmod ulation\",\"aw aru\",\"âĢĭ âĢĭ\",\"ari j\",\"Ġdecor ations\",\"Ġapolog ise\",\"ĠG arg\",\"app ly\",\"Ġgive away\",\"ĠFl an\",\"ĠWy att\",\"U ber\",\"Ġauthor ised\",\"ĠMor al\",\"HAHA HAHA\",\"activ ate\",\"Ġtorped o\",\"ĠF AR\",\"Ġam assed\",\"ĠA ram\",\"ark in\",\"ĠVict ims\",\"st ab\",\"Ġo m\",\"ĠE CO\",\"Ġopio ids\",\"Ġpurpose ly\",\"ĠV est\",\"Ġer g\",\"at an\",\"ĠSur gery\",\"Ġcorrect ing\",\"ĠOrt iz\",\"ĠBe et\",\"Ġrev oke\",\"Ġfre eway\",\"ĠH iggins\",\"F ail\",\"ĠFar ms\",\"ĠAT P\",\"h ound\",\"Ġp oking\",\"ĠCommun ists\",\"mon ster\",\"iment ary\",\"Ġunlock ing\",\"Ġunf it\",\"we ed\",\"en ario\",\"at ical\",\"ĠEnlight enment\",\"ĠN G\",\"ĠComp ensation\",\"de en\",\"ĠWid ow\",\"ĠCind y\",\"ĠAfter wards\",\"Ġ6 000\",\"ikh ail\",\"ag ically\",\"Ġrat ified\",\"Ġcasual ty\",\"H OME\",\"p sey\",\"f ee\",\"Ġspark ling\",\"Ġd Ã©\",\"Ġconcert ed\",\"C atal\",\"Ġcomp lying\",\"ĠA res\",\"ĠD ent\",\"Sh ut\",\"Ġsk im\",\"ad minist\",\"Ġhost ilities\",\"ĠG ins\",\"Ġ6 08\",\"Ġm uddy\",\"ĠMc Int\",\"ĠDec ay\",\"5 25\",\"Ġconspic uous\",\"ĠEx posure\",\"Ġresc ind\",\"Ġwear able\",\"Ġ3 28\",\"our met\",\"ah s\",\"ĠRob ots\",\"Ġe clips\",\"inst ance\",\"ĠRE PORT\",\"ĠApp l\",\"0 30\",\"ĠSk ies\",\"01 00\",\"Ġfall acy\",\"S ocket\",\"ĠRece iver\",\"Ġsol ves\",\"ĠButter fly\",\"ĠSho pping\",\"ĠFI RE\",\"65 4\",\"Med ic\",\"Ġsing ers\",\"ĠNeed less\",\"'' ''\",\"isher s\",\"ĠD ive\",\"58 8\",\"Ġselect ively\",\"Ġcl umsy\",\"88 9\",\"Ġpurch aser\",\"ear ned\",\"ard y\",\"Ġbenef iting\",\"eng lish\",\"Ġyield ing\",\"ĠP our\",\"Ġspin ach\",\"Ġdel ve\",\"ĠC rom\",\"6 10\",\"Ġexport ing\",\"ĠMA KE\",\"Ġ26 3\",\"Ġg rop\",\"Ġenv oy\",\"ĠInqu iry\",\"ĠLu igi\",\"d ry\",\"ĠT uring\",\"Thumbnail Image\",\"ĠVar iety\",\"Ġfac et\",\"Ġfl uffy\",\"Ġexcerpt s\",\"Ġsh orth\",\"ĠOl sen\",\"CL UD\",\"Ġrel iant\",\"ĠUN C\",\"T our\",\"Ġbat hing\",\"Comp any\",\"Ġglobal ization\",\"P red\",\"ĠMalf oy\",\"Ġh oc\",\"j am\",\"craft ed\",\"ĠBond s\",\"ĠKiss inger\",\"Eng land\",\"Ġorder ly\",\"cat entry\",\"Ġ26 1\",\"Ġexch anging\",\"ĠInt ent\",\"ĠAmend ments\",\"D OM\",\"Ġst out\",\"ÂłÂłÂłÂłÂłÂłÂłÂł ÂłÂłÂłÂłÂłÂłÂłÂł\",\"ĠAir bus\",\"Ġ27 8\",\"hy de\",\"P oll\",\"Item ThumbnailImage\",\"Ġlooph oles\",\"ĠPill ar\",\"Ġexpl or\",\"St retch\",\"A part\",\"Ġun married\",\"Lim it\",\"ĠTransform ers\",\"Ġintellect ually\",\"unct ure\",\"18 00\",\"Ġd arn\",\"B razil\",\"Ġleft over\",\"ber us\",\"f red\",\"Mine craft\",\"3 26\",\"ĠForm s\",\"Ġproof s\",\"ĠDes igned\",\"Ġindex es\",\"ĠSupp ose\",\"EM S\",\"ĠL oving\",\"ĠBon nie\",\"im ating\",\"OT US\",\"Ġconduct or\",\"Ġbehav ed\",\"ĠF ren\",\"Ġsy nerg\",\"Ġmillenn ium\",\"Ġcater ing\",\"ĠL auder\",\"W r\",\"ĠY iannopoulos\",\"ĠAT F\",\"Ġensl aved\",\"Ġawaken ed\",\"D VD\",\"ĠED ITION\",\"ĠConc ert\",\"ĠChall enger\",\"ĠH aku\",\"umer ic\",\"Ġdep recated\",\"ĠSH AR\",\"4 12\",\"Ġdy stop\",\"Ġtremb ling\",\"Ġdread ed\",\"ĠSp ac\",\"p adding\",\"Re pl\",\"ĠG arrison\",\"M ini\",\"Ġun paralleled\",\"am ar\",\"URR ENT\",\"w reck\",\"c ertain\",\"t al\",\"ĠC LS\",\"app ings\",\"Ġsens ed\",\"Ġf encing\",\"ĠPas o\",\"ĠDes k\",\"Ġsc off\",\"Ġcontem plate\",\"ĠL iga\",\"l iquid\",\"75 7\",\"Ġapp rentice\",\"ĠUCH IJ\",\"5 70\",\"ĠTh ousand\",\"ĠIll um\",\"Ġchampion ed\",\"ãĤ Į\",\"Ġelect ors\",\"Ġ3 98\",\"ĠH ancock\",\"round ed\",\"ĠJ OHN\",\"Ġuns atisf\",\"Ġqual ifier\",\"ĠGad get\",\"EN E\",\"Ġdead liest\",\"ĠPl ants\",\"Ġ ions\",\"Ġacc ents\",\"Ġtwe aking\",\"Ġsh aved\",\"F REE\",\"ĠCh aser\",\"Again st\",\"9 60\",\"Ġmeth amphetamine\",\"Ġnormal ized\",\"Ġ$ \\\\\",\"ĠPre cision\",\"ĠGu am\",\"Ġch oked\",\"ĠX II\",\"ĠCast ing\",\"Tor rent\",\"Ġscal p\",\"ĠJagu ar\",\"w it\",\"Ġsem ic\",\"ix ie\",\"ĠG ould\",\"Ġconf ines\",\"N usra\",\"ĠL on\",\"ĠJ ugg\",\"y cle\",\"ĠCod ec\",\"E gypt\",\"Ġrest rain\",\"ĠAl iens\",\"Ġch oking\",\"ĠD unk\",\"ĠBell a\",\"ab c\",\"Ġsl ang\",\"Ġneuro trans\",\"s av\",\"Ġempower ment\",\"â ĨĴ\",\"Ġclim bers\",\"ĠM im\",\"ĠF ra\",\"ros se\",\"Cap ital\",\"ĠCth ulhu\",\"Inter face\",\"Ġprof icient\",\"ĠIN TO\",\"Ġ3 18\",\"ront al\",\"5 80\",\"ĠDes pair\",\"K enn\",\"Ġscrim mage\",\"ĠCo at\",\"as ions\",\"Ġwall paper\",\"ĠJ ol\",\"Ġresurg ence\",\"Ġant iv\",\"ĠB alls\",\"² ¾\",\"Ġbuff ers\",\"Ġsub system\",\"ĠSt ellar\",\"ĠL ung\",\"A IDS\",\"Ġerad icate\",\"Ġblat antly\",\"Ġbehav es\",\"ĠN un\",\"Ġant ics\",\"ex port\",\"DE V\",\"w b\",\"Ġph p\",\"ĠInteg rity\",\"Ġexplore r\",\"Ġrev olving\",\"auth ored\",\"g ans\",\"Ġbas k\",\"Ġas ynchronous\",\"å į\",\"TH ING\",\"69 8\",\"G ene\",\"ĠR acer\",\"ĠN ico\",\"iss ued\",\"Ġser mon\",\"p ossibly\",\"Ġsize of\",\"Ġentrepreneur ial\",\"ox in\",\"ĠMin erva\",\"Ġpl atoon\",\"n os\",\"ri ks\",\"A UT\",\"ĠAval anche\",\"ĠDes c\",\"ĳ å£«\",\"ĠP oc\",\"Ġconf erred\",\"Î »\",\"Ġpat ched\",\"F BI\",\"66 2\",\"Ġfract ures\",\"Ġdetect s\",\"Ġded icate\",\"Ġconstitu ent\",\"Ġcos mos\",\"W T\",\"Ġswe ats\",\"Ġspr ung\",\"b ara\",\"s olid\",\"Ġuns us\",\"Ġbul ky\",\"ĠPhilipp e\",\"ĠFen rir\",\"Ġtherap ists\",\"ore al\",\"^^ ^^\",\"Ġtotal ed\",\"Ġboo ze\",\"ĠR PC\",\"Prosecut ors\",\"Ġdis eng\",\"ĠSh ared\",\"Ġmotor cycles\",\"Ġinvent ions\",\"Ġlett uce\",\"ĠMer ge\",\"ĠJ C\",\"Ġspiritual ity\",\"ĠWAR NING\",\"Ġunl ucky\",\"ĠT ess\",\"Ġtong ues\",\"ĠD UI\",\"T umblr\",\"Ġle ans\",\"Ġinv aders\",\"Ġcan opy\",\"ĠHur ricanes\",\"ĠB ret\",\"ĠAP PLIC\",\"id ine\",\"ick le\",\"Reg arding\",\"Ġve ggies\",\"Ġe jac\",\"ju ven\",\"F ish\",\"D EM\",\"ĠD ino\",\"Th row\",\"ĠCheck ing\",\"be ard\",\"( &\",\"Ġj ails\",\"Ġh r\",\"trans fer\",\"iv ating\",\"Ġfle ets\",\"ĠIm ag\",\"ĠMc Donnell\",\"Ġsnipp et\",\"Is a\",\"ĠCh att\",\"ĠSt ain\",\"ĠSet FontSize\",\"ĠO y\",\"ĠMathemat ics\",\"49 4\",\"Ġelectro ly\",\"ĠG ott\",\"ĠBr as\",\"B OOK\",\"ĠF inger\",\"d ump\",\"Ġmut ants\",\"Ġrent als\",\"Ġinter tw\",\"Ġc reek\",\"ail a\",\"Bro ther\",\"ĠDisc ord\",\"pe e\",\"raw ler\",\"Ġcar p\",\"Ġ27 9\",\"ãĤ· ãĥ£\",\"rel ations\",\"Ġcontr asts\",\"Col umn\",\"Ġrec onnaissance\",\"Ġun know\",\"Ġl ooting\",\"Ġregul ates\",\"Ġopt imum\",\"ĠChero kee\",\"ĠA ry\",\"Lat est\",\"Ġroad side\",\"Ġd anced\",\"ĠUnic orn\",\"A cknowled\",\"Ġuncont roll\",\"ĠM US\",\"at io\",\"ch ance\",\"ha ven\",\"VAL UE\",\"Ġfavour ites\",\"Ġceremon ial\",\"b inary\",\"pe ed\",\"wood s\",\"EM P\",\"Ġv ascular\",\"Ġcontempl ated\",\"Ġbar ren\",\"ĠL IST\",\"Y ellow\",\"ospons ors\",\"Ġwhisk y\",\"ĠM amm\",\"ĠDeV os\",\"min imum\",\"H ung\",\"44 2\",\"P ic\",\"ĠSnap dragon\",\"77 6\",\"Ġcar ving\",\"Ġund ecided\",\"Ġadvantage ous\",\"Ġpal ms\",\"ĠA Q\",\"Ġst arch\",\"L oop\",\"Ġpadd le\",\"Ġfl aming\",\"ĠHor izons\",\"An imation\",\"bo ost\",\"Ġprob abilities\",\"ĠM ish\",\"Ġex odus\",\"ĠEditor ial\",\"Ġfung us\",\"Ġdissent ing\",\"ĠDel icious\",\"rog ram\",\"ĠD yn\",\"d isk\",\"t om\",\"Ġfab rics\",\"ĠC ove\",\"ĠB ans\",\"Ġsoft en\",\"ĠCON S\",\"Ġin eligible\",\"Ġestim ating\",\"ĠLex ington\",\"pract ice\",\"of i\",\"Ġshe dding\",\"ĠN ope\",\"Ġbreat hed\",\"ĠCorinth ians\",\"y ne\",\"ek i\",\"B ull\",\"Ġatt aching\",\"reens hots\",\"Ġanaly se\",\"ĠK appa\",\"Ġuns ustainable\",\"Ġinter pol\",\"ank y\",\"he mer\",\"Ġprot agonists\",\"Ġform atted\",\"ĠBry ce\",\"ĠAch illes\",\"ĠAb edin\",\"sh ock\",\"Ġb um\",\"b os\",\"qu a\",\"ĠW arn\",\"q t\",\"ĠDi abetes\",\"8 64\",\"ĠIn visible\",\"Ġvan ish\",\"Ġtrans mitting\",\"Ġmur ky\",\"ĠFe i\",\"Ġawa ited\",\"ĠJur assic\",\"umm ies\",\"Ġmen acing\",\"g all\",\"C ath\",\"B uilt\",\"ild o\",\"ĠV otes\",\"Ġon t\",\"Ġmun itions\",\"ĠFre em\",\"ÃŃ n\",\"Ġdec ency\",\"lo pp\",\"ie ved\",\"ĠG ord\",\"Ġun thinkable\",\"ĠNews week\",\"Ġ3 21\",\"He at\",\"Ġpresent er\",\"ji ang\",\"Ġpl ank\",\"ĠAval on\",\"Ġben z\",\"ĠR out\",\"Ġslam ming\",\"ĠD ai\",\"ou ter\",\"ĠCook ie\",\"ĠAlic ia\",\"ge y\",\"Ġvan ity\",\"Ġow l\",\"á µ\",\"t ested\",\"ĠAw akens\",\"Ġcan v\",\"Ġblind ly\",\"ĠRid ley\",\"ĠEm ails\",\"Requ ires\",\"ĠSer bian\",\"ograp hed\",\"if rame\",\"eter ia\",\"Ġaltern ating\",\"qu iet\",\"Ġsoc iology\",\"ĠUn lock\",\"ĠCommun ism\",\"Ġo ps\",\"Ġatt ribution\",\"Ġab duction\",\"ĠAb ram\",\"Ġsidel ined\",\"ĠB OOK\",\"Ġref ining\",\"ĠFe eling\",\"ĠOs lo\",\"ĠPru itt\",\"r ack\",\"ang ible\",\"Ġcaut iously\",\"ĠM ARK\",\"eed s\",\"M ouse\",\"ĠStep h\",\"ĠP air\",\"S ab\",\"99 7\",\"ĠBa al\",\"B ec\",\"Ġcomm a\",\"ĠP all\",\"ĠG ael\",\"Ġmisunder stand\",\"ĠP esh\",\"Order able\",\"Ġdis mal\",\"ĠSh iny\",\"% \\\"\",\"Ġreal istically\",\"Ġpat io\",\"ĠG w\",\"ĠVirt ue\",\"Ġexhaust ing\",\"wh atever\",\"oph ys\",\"y ip\",\"4 18\",\"Ad just\",\"ĠWa iting\",\"ess on\",\"ĠMaz da\",\"ĠDo zens\",\"Ġstream lined\",\"Ġincompet ence\",\"ĠM eth\",\"Ġeth os\",\"ON ES\",\"Ġincent iv\",\"Ġgr itty\",\"ĠBut cher\",\"Head er\",\"Ġexp onential\",\"Ã Ł\",\"Ġcorrel ate\",\"Ġcons ensual\",\"s ounding\",\"R ing\",\"Orig in\",\"Ġcon clusive\",\"fe et\",\"ac ly\",\"ĠF ernandez\",\"Buy able\",\"Ġd ucks\",\"aunt lets\",\"Ġel ong\",\"Ġ28 6\",\"Ġsim ul\",\"G as\",\"ĠK irst\",\"Ġprot r\",\"ĠRob o\",\"ĠAo E\",\"op ol\",\"Ġpsych ologically\",\"sp in\",\"ilater ally\",\"ĠCon rad\",\"W ave\",\"44 1\",\"ĠAd vertisement\",\"ĠHarm on\",\"ĠOri ental\",\"is Special\",\"Ġpresum ptive\",\"Ġw il\",\"ĠK ier\",\"ne a\",\"Ġp pm\",\"Ġhar bour\",\"ĠW ired\",\"comp any\",\"Ġcor oner\",\"atur days\",\"ĠP roud\",\"ĠN EXT\",\"ĠFl ake\",\"val ued\",\"ce iver\",\"Ġfra ught\",\"Ġc asing\",\"Ġrun away\",\"Ġg in\",\"ĠLaure nt\",\"ĠHar lem\",\"ĠCur iosity\",\"qu ished\",\"Ġneuro science\",\"ĠH ulu\",\"Ġborrow er\",\"Ġpetition er\",\"ĠCo oldown\",\"W ARD\",\"Ġinv oking\",\"conf idence\",\"For ward\",\"Ġst s\",\"pop ulation\",\"Delivery Date\",\"Fil m\",\"ĠC ov\",\"quick Ship\",\"quickShip Available\",\"prim ary\",\"isSpecial Orderable\",\"inventory Quantity\",\"channel Availability\",\"BO X\",\"ĠMulti player\",\"ĠJen ner\",\"77 8\",\"ĠM d\",\"Ġ~ /.\",\"M N\",\"Ġchild ish\",\"Ġantioxid ant\",\"ĠChrom ebook\",\"Ġ27 4\",\"Ġscreen play\",\"Ġadvent urous\",\"ĠRelations hip\",\"respons ive\",\"ming ton\",\"Ġcorner stone\",\"ĠF ey\",\"F IR\",\"Ġrook ies\",\"ĠF eaturing\",\"Ġorig inate\",\"Ġelectro des\",\"ant es\",\"Ġscript ures\",\"Ġgl ued\",\"Ġdiscont ent\",\"Ġaff licted\",\"lay out\",\"B rave\",\"Ġm osa\",\"ĠQuant ity\",\"ĠH ik\",\"w inner\",\"H ours\",\"Ġent ail\",\"ĠCell s\",\"olog ue\",\"Ġv il\",\"Ġpre acher\",\"Ġdecor ative\",\"d ifferent\",\"Ġprejud ices\",\"ĠSm oking\",\"ĠNotting ham\",\"so Type\",\"Ġrhyth ms\",\"ĠAl ph\",\"bl ast\",\"Ste el\",\"ĠDaniel le\",\"Ġstr ife\",\"Ġrem atch\",\"so DeliveryDate\",\"ĠF ork\",\"t rip\",\"ol ulu\",\"hes es\",\"C G\",\"ĠPOLIT ICO\",\"ost a\",\"ĠDr ift\",\"é¾įå ¥\",\"é¾įå¥ ĳå£«\",\"Ġvet ting\",\"ĠJin ping\",\"ĠRec ession\",\"Min or\",\"ĠF raud\",\"enf ranch\",\"Ġconven ed\",\"ĠNA ACP\",\"ĠMill ions\",\"ĠFarm ing\",\"ĠW oo\",\"ĠFl are\",\"rit o\",\"imm igrant\",\"Ġvac ancy\",\"ĠHE AD\",\"ĠV aj\",\"eg al\",\"ĠV igil\",\"Stud y\",\"Ġru ining\",\"Ġr acks\",\"Ġhe ater\",\"ĠRand olph\",\"ĠBr ush\",\"ĠT ir\",\"Ø ¨\",\"Ġc ov\",\"% ]\",\"Ġrecount s\",\"ĠO PT\",\"ĠM elt\",\"Ġtr uce\",\"Ġcas inos\",\"Ġcrus ade\",\"Ġcarn age\",\"Ġstri pe\",\"ĠK yl\",\"Text ures\",\"Ġ6 98\",\"Ġpro clamation\",\"Ġgood ies\",\"Ġ........ ..\",\"pro claimed\",\"P olit\",\"Ġtop ical\",\"Ġspecial ize\",\"ĠA min\",\"g m\",\"Ġanch ored\",\"Ġbear ings\",\"s ample\",\"ĠHigh land\",\"ĠAut ism\",\"Ġmerc enary\",\"Ġinterview er\",\"L ER\",\"ĠSom ers\",\"Ġembry o\",\"ĠAss y\",\"Ġ28 1\",\"ĠEd iting\",\"ĠCh osen\",\"6 60\",\"Ġp ci\",\"ĠThunder bolt\",\"BI LL\",\"Ġchuck led\",\"jri wal\",\"h of\",\"Ġearth ly\",\"() {\",\"ind ependence\",\"Ġdisp ers\",\"ĠV endor\",\"ĠG areth\",\"Ġp als\",\"P enn\",\"ĠSub mit\",\"ic um\",\"Th u\",\"Ġcl andestine\",\"Ġcann ibal\",\"ĠCl erk\",\"E Stream\",\"gal itarian\",\"âĻ ¥\",\"g ew\",\"Ġhor rend\",\"ĠL ov\",\"ĠRe action\",\"ocr in\",\"Class ic\",\"Ġecho ing\",\"Ġdiscl osing\",\"ĠIns ight\",\"og un\",\"ĠInc arn\",\"upload s\",\"pp erc\",\"guy en\",\"Ġ19 01\",\"ĠB ars\",\"68 7\",\"Ġb ribes\",\"ĠFres no\",\"ur at\",\"ĠRe ese\",\"Ġintr usive\",\"Ġgri pping\",\"ĠBlue print\",\"ĠR asm\",\"un ia\",\"man aged\",\"ĠHeb do\",\"Ġ3 45\",\"Ġdec oding\",\"Ġpo ets\",\"Ġj aws\",\"ĠF IGHT\",\"am eless\",\"ĠMead ows\",\"ĠHar baugh\",\"Inter view\",\"ĠH osp\",\"ĠB RA\",\"Ġdelet ion\",\"m ob\",\"W alker\",\"ĠMoon light\",\"ĠJ ed\",\"ĠSoph ia\",\"Ġus ur\",\"Ġfortun ately\",\"ĠPut ting\",\"ĠF old\",\"Ġsan itation\",\"Ġpart isans\",\"IS ON\",\"B ow\",\"ĠCON C\",\"ĠRed uced\",\"ĠS utton\",\"Ġtouch screen\",\"Ġembry os\",\"âĢ¢âĢ¢ âĢ¢âĢ¢\",\"ĠK rug\",\"com bat\",\"ĠPet roleum\",\"Ġam d\",\"ĠCos mos\",\"Ġpresc ribing\",\"Ġconform ity\",\"ours es\",\"Ġplent iful\",\"Ġdis illusion\",\"ĠEc ology\",\"itt al\",\"Ġf anc\",\"Ġassass inated\",\"regn ancy\",\"Ġperenn ial\",\"ĠBul lets\",\"Ġst ale\",\"Ġc ached\",\"ĠJud ith\",\"ĠDise ases\",\"All en\",\"Ġl as\",\"Ġsh ards\",\"ĠSu arez\",\"ĠFriend ship\",\"inter face\",\"ĠSupp orters\",\"add ons\",\"46 2\",\"ĠIm ran\",\"ĠW im\",\"Ġnew found\",\"ĠM b\",\"An imal\",\"Ġd arling\",\"and e\",\"Ġrh y\",\"ĠTw isted\",\"pos al\",\"yn ski\",\"Var ious\",\"× ľ\",\"ĠK iw\",\"uy omi\",\"Ġwell being\",\"ĠL au\",\"an os\",\"Ġunm ist\",\"Ġmac OS\",\"Ġrest room\",\"ĠOl iv\",\"ĠAir ways\",\"Ġtimet able\",\"9 80\",\"Ġrad ios\",\"v oy\",\"ias co\",\"Ġcloud y\",\"ĠDraw ing\",\"Any thing\",\"Sy ria\",\"ĠH ert\",\"st aking\",\"Ġun checked\",\"Ġb razen\",\"ĠN RS\",\"69 7\",\"onom ic\",\"est ablish\",\"Ġl eng\",\"Ġdi agonal\",\"ĠF ior\",\"L air\",\"ĠSt ard\",\"Ġdef icient\",\"jo ining\",\"be am\",\"Ġomn ip\",\"Ġbl ender\",\"Ġsun rise\",\"Mo ore\",\"ĠF ault\",\"ĠCost ume\",\"ĠM ub\",\"Fl ags\",\"an se\",\"Ġpay out\",\"ĠGovern ors\",\"ĠD illon\",\"ĠBan ana\",\"N ar\",\"Ġtra iled\",\"Ġimperial ist\",\"um ann\",\"ats uki\",\"4 35\",\"ĠRoad s\",\"Ġsl ur\",\"ĠIde ally\",\"Ġt renches\",\"C trl\",\"Ġmir rored\",\"ĠZ el\",\"ĠC rest\",\"Comp at\",\"ĠRoll s\",\"sc rib\",\"ĠTra ils\",\"omet ers\",\"w inter\",\"Ġimm ortality\",\"il ated\",\"Ġcontrad icts\",\"un iversal\",\"ill ions\",\"ĠM ama\",\"opt im\",\"AT URE\",\"Ġge o\",\"et ter\",\"ĠCar lo\",\"4 24\",\"Ġcanon ical\",\"ĠStrongh old\",\"n ear\",\"Ġperf ume\",\"Ġorche stra\",\"od iac\",\"Ġup he\",\"Ġreign ing\",\"vers ive\",\"Ġc aucuses\",\"ĠD EM\",\"Ġinsult ed\",\"Ġ---- --\",\"ĠCr ush\",\"Ġroot ing\",\"ĠWra ith\",\"Ġwh ore\",\"Ġto fu\",\"C md\",\"ĠB ree\",\"Ġ$ _\",\"Ġr ive\",\"ĠAd vertising\",\"Ġw att\",\"ĠH O\",\"Ġpersu asive\",\"ĠParam eters\",\"Ġobserv ational\",\"ĠN CT\",\"ĠMo j\",\"ĠSal on\",\"Ġtr unc\",\"Ġexqu isite\",\"ĠMar a\",\"Ġpo op\",\"ĠAN N\",\"Ex c\",\"ĠWonder ful\",\"ĠT aco\",\"Ġhome owner\",\"ĠSmith sonian\",\"orpor ated\",\"mm mm\",\"Ġlo af\",\"ĠYam ato\",\"ĠInd o\",\"Ġcl inging\",\"Ã¡ s\",\"Ġimm utable\",\"h ub\",\"Or ange\",\"Ġfingert ips\",\"ĠWood en\",\"ĠK idd\",\"ĠJ PM\",\"ĠDam n\",\"C ow\",\"c odes\",\"48 2\",\"Ġiniti ating\",\"ĠEl k\",\"ĠCut ting\",\"Ġabsent ee\",\"ĠV ance\",\"ĠLil ith\",\"G UI\",\"Ġobsc ured\",\"Ġdwar ves\",\"ĠCh op\",\"ĠB oko\",\"Val ues\",\"Ġmult imedia\",\"Ġbrew ed\",\"Reg ular\",\"CRIP TION\",\"ĠMort al\",\"Ġa pex\",\"Ġtravel er\",\"Ġbo ils\",\"Ġspray ing\",\"Rep resent\",\"ĠStars hip\",\"4 28\",\"Ġdisappro val\",\"Ġshadow y\",\"Ġlament ed\",\"ĠRe place\",\"ĠFran Ã§\",\"67 7\",\"d or\",\"Ġunst oppable\",\"Ġcoh orts\",\"gy n\",\"ĠClass ics\",\"ĠAm ph\",\"Ġsl uggish\",\"ĠAdd iction\",\"ĠPad res\",\"Ġins cription\",\"Ġin human\",\"min us\",\"ĠJere miah\",\"at ars\",\"Ter ror\",\"ĠT os\",\"ĠSh arma\",\"ast a\",\"c atch\",\"Ġpl umbing\",\"ĠTim bers\",\"Sh ar\",\"H al\",\"ĠO sc\",\"Ġcou pling\",\"hum ans\",\"Ġsp onge\",\"Ġid ols\",\"ĠSp a\",\"ĠAdv ocate\",\"ĠBe ats\",\"lu a\",\"Ġtick ing\",\"Ġload er\",\"ĠG ron\",\"8 10\",\"Ġstim ulated\",\"Ġside bar\",\"ĠManufact urer\",\"ore And\",\"19 73\",\"Ġpra ises\",\"ĠFl ores\",\"dis able\",\"ĠElect rical\",\"ra ise\",\"E th\",\"Ġmigr ated\",\"Ġlect urer\",\"K ids\",\"ĠCa vern\",\"Ġk ettle\",\"Ġgly c\",\"ĠMand ela\",\"ĠF ully\",\"å§ «\",\"FIN EST\",\"Ġsquee zing\",\"ĠRy der\",\"amp oo\",\"oreAnd Online\",\"Inst oreAndOnline\",\"Buyable InstoreAndOnline\",\"Ġcommem orate\",\"ĠRamp age\",\"Aust in\",\"ĠSh roud\",\"ĠRu ins\",\"9 15\",\"ĠK H\",\"Ġwater front\",\"ĠE SC\",\"b aby\",\"ĠC out\",\"ĠEm blem\",\"Ġequival ents\",\"49 2\",\"Un ique\",\"ĠNiet zsche\",\"brow ser\",\"Ġim itation\",\"ĠWere wolf\",\"ĠKir in\",\"ac as\",\"' ,\\\"\",\"ĠÃ ¾\",\"Review ed\",\"Ġc unt\",\"Ġvo ic\",\"ĠLen ovo\",\"Ġbond ed\",\"48 1\",\"Ġinhib itors\",\"Ġendeav ors\",\"ĠHav ana\",\"ĠSt out\",\"ĠJ olly\",\"A ctor\",\"*/ (\",\"Ġoccur rences\",\"ĠT ens\",\"Incre ased\",\"ĠACT ION\",\"Ġ ãĢĮ\",\"ĠRank ings\",\"ĠB reat\",\"Ġ30 9\",\"D ou\",\"Ġimpact ing\",\"ĠDuc hess\",\"pre fix\",\"Q B\",\"Ġsummon ing\",\"Ġbest owed\",\"ĠKe pler\",\"ĠPOW ER\",\"c ube\",\"ĠK its\",\"ĠG rip\",\"Ġop ium\",\"Ġrep utable\",\"t oc\",\"ich ael\",\"ĠR ipple\",\"Ġcaf Ã©\",\"ĠZ oom\",\"ĠBur ma\",\"Ġwa ive\",\"Ġst alls\",\"Ġdem eanor\",\"inc erity\",\"Ġfluor ide\",\"ĠSH OULD\",\"Par is\",\"Ġlong ing\",\"Ġpl at\",\"Ġgross ly\",\"Ġbull s\",\"Ġshowc asing\",\"ex pected\",\"ĠG addafi\",\"engine ering\",\"Re peat\",\"ĠK ut\",\"Ġconce ivable\",\"Ġtrim med\",\"osc ope\",\"ĠCand idate\",\"ĠT ears\",\"rol og\",\"Lew is\",\"S UP\",\"Ġroad map\",\"Ġsal iva\",\"Ġtrump et\",\"Jim my\",\"Ġmirac ulous\",\"Ġcolon ization\",\"Ġam put\",\"ĠGN OME\",\"ate ch\",\"D ifferent\",\"ĠE LE\",\"ĠGovern ments\",\"ĠA head\",\"ãħĭ ãħĭ\",\"word press\",\"L IB\",\"ĠIn clude\",\"ĠDor othy\",\"0 45\",\"ĠColomb ian\",\"Ġle ased\",\"88 4\",\"Ġde grading\",\"ĠDa isy\",\"i ations\",\"Ġbapt ized\",\"Ġsurn ame\",\"co x\",\"Ġblink ed\",\"ãĥ ¢\",\"Ġpoll en\",\"Ġder mat\",\"Ġre gex\",\"ĠNich olson\",\"ĠE ater\",\"ç ľ\",\"rad or\",\"Ġnarrow er\",\"Ġhur ricanes\",\"Ġhalluc inations\",\"r idden\",\"ISS ION\",\"ĠFire fly\",\"Ġattain ment\",\"Ġnom inate\",\"Ġav ocado\",\"ĠM eredith\",\"Ġt s\",\"Ġreve rence\",\"Ġe uph\",\"Ġcr ates\",\"ĠT EXT\",\"Ġ4 43\",\"Ġ3 19\",\"J SON\",\"iqu ette\",\"Ġshort stop\",\"ic key\",\"Ġpro pelled\",\"Ġap i\",\"ĠTh ieves\",\"77 9\",\"Ġovers aw\",\"Ġcol i\",\"ĠNic ola\",\"Ġover cl\",\"ik awa\",\"ĠC yr\",\"Ġ38 4\",\"78 9\",\"ĠAll ows\",\"10 27\",\"Det roit\",\"TR Y\",\"set up\",\"ĠSocial ism\",\"Sov iet\",\"s usp\",\"ĠAP R\",\"ĠShut down\",\"Ġal uminium\",\"zb ek\",\"ĠL over\",\"GGGG GGGG\",\"Ġdemocr acies\",\"Ġ19 08\",\"ĠMer rill\",\"ĠFranco is\",\"gd ala\",\"Ġtraff ickers\",\"ĠT il\",\"ĠGo at\",\"Ġsp ed\",\"ĠRes erv\",\"Ġpro d\",\"55 2\",\"Ġc ac\",\"ĠUn iv\",\"ĠSch we\",\"Ġsw irling\",\"ĠWild erness\",\"ĠEgg s\",\"Ġsadd ened\",\"Ġarch aic\",\"H yd\",\"Ġexcess ively\",\"B RE\",\"Ġaer ospace\",\"ĠVo ices\",\"Cra ig\",\"Ġign ited\",\"In itially\",\"ĠMc A\",\"Ġhand set\",\"Ġreform ing\",\"Ġfrust rations\",\"ĠDead pool\",\"ĠBel ichick\",\"ract or\",\"ĠRagnar ok\",\"ĠD rupal\",\"ĠApp roximately\",\"19 20\",\"ĠHub ble\",\"arm or\",\"ĠSar as\",\"ĠJon as\",\"Ġnostalg ic\",\"Ġfeas ibility\",\"Sah aran\",\"Ġorb iting\",\"Ġ9 70\",\"R u\",\"Ġsh in\",\"ĠInvestig ators\",\"Ġinconsist encies\",\"ĠP AN\",\"B G\",\"Ġgraz ing\",\"Ġdetect ors\",\"ĠStart up\",\"ĠFun ny\",\"ĠNa omi\",\"Consider ing\",\"Ġh og\",\"ut f\",\"ce mic\",\"Ġfort ified\",\"ĠFun ctions\",\"Ġcod ec\",\"nut rition\",\"H at\",\"\\\" !\",\"micro soft\",\"55 8\",\"ĠTh in\",\"ĠA CE\",\"Al ias\",\"ĠO PS\",\"p apers\",\"P K\",\"ãĢ İ\",\"Ġimpro bable\",\"N orthern\",\"equ al\",\"Ġlook out\",\"Ġty res\",\"ĠMod ified\",\"ĠK op\",\"Abs olutely\",\"Ġbuild up\",\"sil ver\",\"Ġaud i\",\"Ġgro tesque\",\"ĠSab er\",\"ĠPres byter\",\"ON Y\",\"Ġglac iers\",\"ĠSho als\",\"ĠK ass\",\"ĠH RC\",\"ĠNic ol\",\"ĠL unch\",\"ĠF oss\",\"âĸ Ĵ\",\"AD RA\",\"ĠOne Plus\",\"o ing\",\"ground s\",\"Ġincident al\",\"Ġdatas ets\",\"68 9\",\"ĠClarks on\",\"Ġassemb ling\",\"ĠCorrect ions\",\"Ġdrink ers\",\"Ġqual ifiers\",\"Ġle ash\",\"Ġunf ounded\",\"ĠH undred\",\"Ġkick off\",\"T i\",\"Ġrecon cil\",\"ĠGr ants\",\"ĠCompl iance\",\"ĠDexter ity\",\"Ġ19 06\",\"w arn\",\"D allas\",\"Max imum\",\"n ard\",\"av ia\",\"be aut\",\"ens itivity\",\"tr ace\",\"Ġpione ers\",\"ĠF ract\",\"ãĢ ı\",\"Ġpre cept\",\"Ġgloss y\",\"ĠI EEE\",\"Ac ross\",\"Ġ6 80\",\"S leep\",\"che on\",\"Ġsatir ical\",\"ĠMin otaur\",\"ĠCla ude\",\"Ġr Ã©\",\"ape go\",\"Ġcar rot\",\"ĠSem in\",\"ino a\",\"Ġz o\",\"Ind ependent\",\"Ġdiagn oses\",\"ĠC ue\",\"M AR\",\"Ġrend ition\",\"ĠK ik\",\"Ġpath ology\",\"Ġselect s\",\"Link edIn\",\"Ġass ay\",\"ĠD res\",\"Ġtext ual\",\"post ed\",\"IT AL\",\"ĠM aul\",\"N eal\",\"Ġinter connected\",\"Ġerr atic\",\"ĠVir us\",\"Ġ5 30\",\"Ġenvironmental ists\",\"ĠP helps\",\"Ġeng agements\",\"ĠIN ST\",\"Ġeconom ical\",\"nox ious\",\"Ġg earing\",\"izz y\",\"Ġfavor ably\",\"ĠMcG ill\",\"T erm\",\"Ġh anged\",\"Ġball park\",\"ĠRe yes\",\"Ġbe ware\",\"ĠP sal\",\"ĠMass acre\",\"q i\",\"Ġin accessible\",\"acly sm\",\"Ġfr ay\",\"ill ac\",\"Ġbitter ly\",\"ĠCert ification\",\"Mich igan\",\"Ġir respective\",\"al ore\",\"Em pty\",\"Ġendorse ments\",\"Ġund et\",\"f g\",\"equ ipped\",\"Ġmerc iless\",\"ĠC ust\",\"Ġimm ature\",\"Ġvou cher\",\"ĠBlack well\",\"Ñ ı\",\"h awk\",\"dis ciplinary\",\"ile e\",\"ĠMak oto\",\"ĠD ude\",\"ãĥĩ ãĤ£\",\"Y ears\",\"Ġin ver\",\"Ġsh aman\",\"ĠY ong\",\"ip el\",\"ell en\",\"ĠCath y\",\"br ids\",\"Ġs arc\",\"65 1\",\"N ear\",\"Ġground work\",\"Ġam az\",\"Ġ4 15\",\"ĠHunting ton\",\"hew s\",\"ĠB ung\",\"Ġarbit rarily\",\"ĠW it\",\"ĠAl berto\",\"Ġdis qualified\",\"best os\",\"46 1\",\"Ġp c\",\"Ġ28 4\",\"ro bat\",\"Rob in\",\"Ġh ugs\",\"ĠTrans ition\",\"ĠOcc asionally\",\"Ġ3 26\",\"ĠWh ilst\",\"ĠLe y\",\"Ġspaces hip\",\"cs v\",\"Ġun successfully\",\"ĠA u\",\"le ck\",\"ĠWing ed\",\"ĠGrizz lies\",\". ï¿½\",\"Ġne arer\",\"ĠSorce ress\",\"ĠInd igo\",\"El se\",\"8 40\",\"let es\",\"Co ach\",\"Ġup bringing\",\"ĠK es\",\"Ġseparat ist\",\"Ġrac ists\",\"Ġch ained\",\"Ġabst inence\",\"lear ning\",\"Ġrein stated\",\"Ġsymm etry\",\"Ġremind ers\",\"ĠChe vy\",\"Ġm ont\",\"Ġexempl ary\",\"ĠT OR\",\"Z X\",\"Ġqual itative\",\"ĠSt amp\",\"ĠSav annah\",\"ĠRoss i\",\"Ġp aed\",\"Ġdispens aries\",\"ĠWall s\",\"ĠCh ronic\",\"Ġcompliment ary\",\"ĠBeir ut\",\"Ġ+ ---\",\"igs list\",\"Ġcrypt ographic\",\"mas ters\",\"ĠCap itals\",\"Ġmax imal\",\"Ġent ropy\",\"Point s\",\"Ġcombat ants\",\"l ip\",\"ĠGl ob\",\"ĠB MC\",\"ph ase\",\"th ank\",\"HT TP\",\"Ġcomm uter\",\"Ġ\\\\( \\\\\",\".. /\",\"ĠReg ener\",\"ĠDO I\",\"ĠActiv ision\",\"Ġsl it\",\"os al\",\"RE M\",\"Ġch ants\",\"Y u\",\"Ke ys\",\"Bre xit\",\"ĠFor ced\",\"Ari zona\",\"Ġsquad ron\",\"IS O\",\"ĠMal one\",\"Ġ3 38\",\"Ġcontrast ing\",\"Ġt idal\",\"Ġlib el\",\"Ġimpl anted\",\"Ġupro ar\",\"ĠC ater\",\"Ġpropos itions\",\"M anchester\",\"ĠEuro s\",\"it amin\",\"G il\",\"ĠEl ven\",\"ĠSe ek\",\"ĠB ai\",\"Ġredevelop ment\",\"ĠTown s\",\"ĠL ub\",\"! \\\",\",\"al on\",\"K rist\",\"Ġmeas urable\",\"Ġimagin able\",\"Ġapost les\",\"Y N\",\"7 60\",\"Ġster oid\",\"Ġspecific ity\",\"ĠL ocated\",\"ĠBeck er\",\"ĠE du\",\"ĠDiet ary\",\"uts ch\",\"ĠMar ilyn\",\"Ġbl ister\",\"ĠM EP\",\"ĠK oz\",\"ĠC MS\",\"y ahoo\",\"ĠCar ney\",\"Ġbo asting\",\"ĠC aleb\",\"By te\",\"read s\",\"ad en\",\"Pro blem\",\"ĠWood ward\",\"S we\",\"S up\",\"ĠK GB\",\"Set up\",\"Ġtac it\",\"Ġret ribution\",\"Ġd ues\",\"ĠM Ã¼\",\". ?\",\"ä¸ Ń\",\"p ots\",\"Ġcame o\",\"ĠP AL\",\"educ ation\",\"A my\",\"like ly\",\"g ling\",\"Ġconstitution ally\",\"ĠHam m\",\"ĠSpe ak\",\"Ġwid gets\",\"br ate\",\"Ġcra ppy\",\"ĠI ter\",\"Ġanticip ating\",\"ĠB out\",\"P ixel\",\"ĠY ep\",\"ĠLaur ie\",\"Ġh ut\",\"Ġbullet in\",\"ĠSal vation\",\"Ġch ats\",\"ear able\",\"Honest ly\",\"AL TH\",\"onse qu\",\"c ult\",\"isco very\",\"ovy ch\",\"Ġse lves\",\"ĠSat oshi\",\"S ounds\",\"Ġconver gence\",\"ĠRosen berg\",\"19 74\",\"Ġnas al\",\"Ġfull est\",\"Ġfer ocious\",\"x us\",\"ist e\",\"AM S\",\"Ġlobb ied\",\"Ġso othing\",\"ĠGun n\",\"t oday\",\"0 24\",\"Ġinspir ational\",\"ĠN BN\",\"p b\",\"g ewater\",\"or ah\",\"all owed\",\"ĠCol iseum\",\"Ġspecial izing\",\"Ġinsane ly\",\"ĠT ape\",\"del ay\",\"Ġt arn\",\"ĠP ound\",\"Ġmel anch\",\"Ġdeploy ments\",\"il and\",\"Ġless en\",\"Ġfur ry\",\"ĠUE FA\",\"Ġblood shed\",\"ĠMe ier\",\"ither ing\",\"Ġhe irs\",\"ĠJ aw\",\"ax ter\",\"ĠPublic ations\",\"Ġal ters\",\"int ention\",\"ĠWinc hester\",\"d etermination\",\"ĠLif etime\",\"th in\",\"Mon ster\",\"7 80\",\"Ġapprox imation\",\"Ġsuper markets\",\"ĠSecond s\",\"or os\",\"h uge\",\"Ġb ribe\",\"ĠLIM ITED\",\"un ed\",\"Ġmis interpret\",\"ĠIn jury\",\"Ġ3 67\",\"Ġthreshold s\",\"ĠCarn ival\",\"Ġgastro intestinal\",\"Ġguid eline\",\"Ġde ceived\",\"f eatures\",\"Ġpurported ly\",\"ĠRon nie\",\"ĠNew t\",\"Ġsp acious\",\"as us\",\"Ġsuperhero es\",\"ĠCyn thia\",\"le gged\",\"k amp\",\"ch io\",\"Ġth umbnail\",\"ĠShir ley\",\"ill ation\",\"Ġshe ds\",\"ĠZ y\",\"E PA\",\"Ġdam s\",\"Ġy awn\",\"n ah\",\"ĠPe ggy\",\"ĠE rie\",\"ĠJu ventus\",\"ĠF ountain\",\"r x\",\"don ald\",\"al bum\",\"ĠComp rehensive\",\"Ġc aching\",\"ĠU z\",\"ulner ability\",\"ĠPrinc iple\",\"ĠJ ian\",\"ing ers\",\"cast s\",\"ĠOs iris\",\"ch art\",\"t ile\",\"ĠTiff any\",\"ĠPatt on\",\"ĠWh ip\",\"Ġovers ized\",\"J e\",\"ĠCind erella\",\"ĠB orders\",\"ĠDa esh\",\"M ah\",\"Ġdog ma\",\"Ġcommun ists\",\"v u\",\"Coun cil\",\"Ġfresh water\",\"Ġw ounding\",\"Ġdeb acle\",\"Ġyoung ster\",\"Ġthread ed\",\"ĠB ots\",\"ĠSav ings\",\"ãģ Ĥ\",\"ol ing\",\"oh o\",\"Ġillum ination\",\"M RI\",\"Ġlo osen\",\"tr ump\",\"ag ency\",\"ur ion\",\"Ġmoment arily\",\"ĠCh un\",\"ĠBud apest\",\"ĠAl ley\",\"D isk\",\"Ġaston ished\",\"ĠCon quer\",\"ĠAccount ing\",\"h aving\",\"ĠWe in\",\"ĠAl right\",\"Ġrev olver\",\"Ġdel usion\",\"Ġrelic s\",\"Ġad herent\",\"qu ant\",\"Ġhand made\",\"or io\",\"Ġcomb ating\",\"c oded\",\"Ġquad ru\",\"re th\",\"N ik\",\"ĠTrib al\",\"ĠMyster ious\",\"Ġin hal\",\"ĠWin ning\",\"ĠClass ification\",\"ch anged\",\"Ġun ab\",\"Ġsc orn\",\"icip ated\",\"w l\",\"ond uctor\",\"Ġrein forcing\",\"ĠChild hood\",\"an ova\",\"Ġadventure r\",\"Ġdoctor al\",\"ĠStrateg ies\",\"Ġengulf ed\",\"ĠEnc ounter\",\"Ġl ashes\",\"Crit ical\",\"ric ular\",\"ĠU TF\",\"oci ation\",\"check ing\",\"ĠConsult ing\",\"Run time\",\"per iod\",\"ĠAs gard\",\"Ġdist illed\",\"ĠPas adena\",\"ĠD ying\",\"ĠCOUN TY\",\"Ġgran ite\",\"Ġsm ack\",\"Ġparach ute\",\"ĠS UR\",\"Virgin ia\",\"ĠF urious\",\"78 7\",\"ĠO kin\",\"Ġcam el\",\"ĠM bps\",\"19 72\",\"ĠCh ao\",\"ĠC yan\",\"j oice\",\"ef er\",\"ĠW rap\",\"ĠDeb ate\",\"S eg\",\"Ġfore arm\",\"ĠIgn ore\",\"Ġtim estamp\",\"Ġprob ing\",\"ĠNo on\",\"ĠGra il\",\"f en\",\"Ġdorm ant\",\"ĠFirst ly\",\"ĠE ighth\",\"ĠH UN\",\"ĠDes ire\",\"or as\",\"Girl s\",\"ĠDes mond\",\"z ar\",\"am ines\",\"O AD\",\"exec ute\",\"Ġbo obs\",\"ĠAT L\",\"_ (\",\"Chel sea\",\"Ġmasturb ation\",\"ĠCo C\",\"Ġdestroy er\",\"ĠCh omsky\",\"Ġsc atter\",\"ĠAss ets\",\"79 6\",\"ĠC argo\",\"Ġrecept ive\",\"ĠSc ope\",\"Ġmarket ers\",\"Ġlaun chers\",\"Ġax le\",\"ĠSE A\",\"se q\",\"ĠM off\",\"f inding\",\"ĠGib bs\",\"Georg ia\",\"extreme ly\",\"N J\",\"Ġlab orers\",\"st als\",\"Ġmed iation\",\"ĠH edge\",\"at own\",\"Ġi od\",\"des pite\",\"v ill\",\"J ane\",\"ex istence\",\"Ġcoinc ided\",\"ĠUt ilities\",\"ĠChe ap\",\"Ġlog istical\",\"Ġcul mination\",\"ĠNic otine\",\"p ak\",\"F older\",\"Ġrod ents\",\"st uff\",\"Ġlaw fully\",\"Ġreper to\",\"io ch\",\"j j\",\"Dial ogue\",\"HH HH\",\"lic tion\",\"Look s\",\"Ġ29 7\",\"Ġtur rets\",\"ĠAb andon\",\"Ġinc ess\",\"ĠTraff ord\",\"Ġcur led\",\"Ġprefer ring\",\"Ġprivat ization\",\"Ġir resist\",\"ĠP anda\",\"ĠSh ake\",\"ĠMc Gr\",\"ãĥ Ħ\",\"und ers\",\"Ġdiscrim inated\",\"Ġbart ender\",\"I LE\",\"Atl antic\",\"Ġprop ensity\",\"ĠW iz\",\"ĠG im\",\"con ference\",\"Ġrein forces\",\"G h\",\"w agon\",\"Ġe erie\",\"F al\",\"Ġhug ged\",\"rac ist\",\"R IC\",\"F u\",\"Ġf iller\",\"ĠSt ub\",\"Ġeng raved\",\"ĠWrest le\",\"Ġimagin ative\",\"ĠPe er\",\"ĠFact ors\",\"an us\",\"ĠDrac ula\",\"mon itor\",\"Ġrou ters\",\"ib ia\",\"ĠBoo lean\",\"end ale\",\"ĠSl aughter\",\"ĠSh ack\",\"R FC\",\"ĠSpiel berg\",\"S ax\",\"ĠPH OTO\",\"ĠCl over\",\"ĠR ae\",\"Dep ending\",\"ĠMem or\",\"ar am\",\"Ġpier ced\",\"Ġcur tains\",\"v ale\",\"ĠInqu isition\",\"ĠP oke\",\"Ġforecast ing\",\"Ġcompl ains\",\"S ense\",\"ĠHer mes\",\"isc overed\",\"Ġb ible\",\"ĠMor ph\",\"Ġg erm\",\"78 5\",\"D ON\",\"Ġcon gen\",\"Ġcr ane\",\"ĠD PR\",\"Ġrespect fully\",\"R oom\",\"ĠN aw\",\"ĠDal ai\",\"re ason\",\"ĠAng us\",\"Educ ation\",\"ĠTitan ic\",\"Ë ľ\",\"Ġo val\",\"un ited\",\"Ġthird s\",\"Ġmoist ur\",\"ĠC PC\",\"M iami\",\"Ġtent acles\",\"ĠPol aris\",\"ex c\",\"ex clusive\",\"ĠPra irie\",\"Ġcol ossal\",\"ĠBl end\",\"sur prisingly\",\"ÃŃ s\",\"Ġindo ctr\",\"Ġbas al\",\"ĠMP EG\",\"und o\",\"Spl it\",\"Develop ment\",\"Ġlan tern\",\"19 71\",\"Ġprov ocation\",\"Ġang uish\",\"ĠB ind\",\"ĠLe ia\",\"duc ers\",\"ipp y\",\"conserv ancy\",\"Ġinitial ize\",\"ĠTw ice\",\"ĠSu k\",\"Ġpred ic\",\"Ġdi ploma\",\"Ġsoc iop\",\"Ing redients\",\"Ġhamm ered\",\"ĠIr ma\",\"Q aida\",\"Ġglim ps\",\"ĠB ian\",\"Ġst acking\",\"Ġf end\",\"gov track\",\"Ġun n\",\"dem ocratic\",\"ig ree\",\"Ġ5 80\",\"Ġ29 4\",\"Ġstraw berry\",\"ID ER\",\"Ġcher ished\",\"ĠH ots\",\"Ġinfer red\",\"Ġ8 08\",\"ĠS ocrates\",\"O regon\",\"ĠR oses\",\"ĠFO IA\",\"Ġins ensitive\",\"Ġ40 8\",\"Recomm end\",\"ĠSh ine\",\"Ġpain staking\",\"UG E\",\"ĠHell er\",\"ĠEnter prises\",\"I OR\",\"ad j\",\"N RS\",\"L G\",\"Ġalien ated\",\"Ġacknowled gement\",\"ĠA UD\",\"ĠRen eg\",\"Ġvou chers\",\"Ġ9 60\",\"Ġm oot\",\"ĠDim ensions\",\"Ġc abbage\",\"B right\",\"g at\",\"ĠK lu\",\"Ġlat ent\",\"Ġz e\",\"ĠM eng\",\"Ġdis perse\",\"Ġpand emonium\",\"H Q\",\"Ġvirt uous\",\"ĠLoc ations\",\"ee per\",\"prov ided\",\"Ġse ams\",\"ĠW T\",\"iz o\",\"PR OV\",\"Ġtit anium\",\"Ġrecol lection\",\"Ġcr an\",\"Ġ7 80\",\"ĠN F\",\"49 1\",\"64 2\",\"p acking\",\"59 8\",\"text ure\",\"Sp ider\",\"fre edom\",\"cipl ed\",\"ĠTAM ADRA\",\"âĻ ¦\",\"aut hent\",\"ĠW ANT\",\"r ified\",\"Ġr ites\",\"Ġuter us\",\"k iss\",\"Ġâī ¤\",\"Ġsk illet\",\"Ġdis enfranch\",\"ĠGa al\",\"Comp an\",\"Ġage ing\",\"gu ide\",\"B alt\",\"Ġiter ator\",\"Ġdiscretion ary\",\"t ips\",\"Ġprim ates\",\"ĠTechn ique\",\"ĠPay ments\",\"az el\",\"ĠR OCK\",\"stant ial\",\"0 60\",\"Ġd mg\",\"ĠJack ets\",\"ĠPlay off\",\"Ġnurs ery\",\"ĠSy mb\",\"art on\",\"Ġannex ation\",\"Color ado\",\"Ġco ils\",\"ĠSh oes\",\"âĦ¢ :\",\"ĠRo z\",\"COM PLE\",\"ĠEve rest\",\"ĠTri umph\",\"J oy\",\"G rid\",\"à ¼\",\"process or\",\"ĠPros per\",\"ĠSever us\",\"ĠSelect ed\",\"r g\",\"ĠTay yip\",\"St ra\",\"Ġski ing\",\"Ġ? )\",\"Ġpe g\",\"Tes la\",\"Ġtime frame\",\"Ġmaster mind\",\"ĠN B\",\"scient ific\",\"ĠSh it\",\"gener ic\",\"IN TER\",\"N UM\",\"Ġst roll\",\"ĠEn ix\",\"ĠM MR\",\"ĠE MS\",\"m ovie\",\"Ĥ ª\",\"Ġminim izing\",\"idd ling\",\"Ġilleg itimate\",\"Ġprot otyp\",\"Ġpremature ly\",\"Ġmanual s\",\"obb ies\",\"ĠCass idy\",\"D EC\",\"des ktop\",\"Ġaer os\",\"Ġscreen ings\",\"Ġdeb ilitating\",\"ĠGr ind\",\"nature conservancy\",\"Ġf ades\",\"ter mination\",\"assets adobe\",\"F actor\",\"Ġdefinitive ly\",\"P okÃ©\",\"ap ult\",\"ĠLaf ayette\",\"C orn\",\"ĠCor al\",\"Ġstagn ant\",\"T ue\",\"Ġdissatisf action\",\"G ender\",\"Ġkid neys\",\"ĠG ow\",\"ĠDef eat\",\"ĠAsh ton\",\"Ġcart els\",\"Ġfore closure\",\"ĠExpl ore\",\"stre ngth\",\"ot in\",\"Ġveterin arian\",\"Ġf umble\",\"Ġpar ap\",\"ĠSt rait\",\"r ils\",\"Ġpr ick\",\"ĠBerm uda\",\"ĠAm munition\",\"skin ned\",\"Ġab ound\",\"ĠB raz\",\"Ġshar per\",\"ĠAsc ension\",\"Ġ9 78\",\"Ġpreview s\",\"Ġcommun ion\",\"ĠX Y\",\"Ġph ony\",\"Ġnewcom er\",\"Ġ3 32\",\".\\\" ,\\\"\",\"Ġredist ribution\",\"Prot ect\",\"ĠSo f\",\"K al\",\"Ġlip stick\",\"w orst\",\"Ġtang led\",\"Ġretrospect ive\",\"int eger\",\"Ġvolunte ering\",\"Ġ19 07\",\"Ġ --------------------\",\"ic hen\",\"Ġunve iling\",\"Ġsen seless\",\"Ġfisher ies\",\"\\\\ -\",\"Ġh inges\",\"Ġcalcul us\",\"My th\",\"Ġund efeated\",\"Ġoptim izations\",\"Ġdep ress\",\"Ġbill board\",\"ĠY ad\",\"ĠPy ramid\",\"Is n\",\"I de\",\"Ġleg ion\",\"ĠK ramer\",\"ent anyl\",\"Ġpenet rating\",\"ĠHaw th\",\"ĠPR ODUCT\",\"ĠGer ard\",\"ĠP act\",\"ĠIn cluding\",\"ĠEl ias\",\"ĠEl aine\",\"vis ual\",\"Ġhum ming\",\"Ġcond esc\",\"ĠF asc\",\"ä¸ Ĭ\",\"Ġe galitarian\",\"Ġdev s\",\"ĠD ahl\",\"O ps\",\"D H\",\"ĠB ounce\",\"id ated\",\"ald o\",\"Ġrepublic an\",\"Ġh amb\",\"ĠS ett\",\"ograph ies\",\"CH APTER\",\"Ġtrans sexual\",\"Ġsky rocket\",\"ans wer\",\"Ġmark up\",\"Ø ª\",\"Ġhero ine\",\"Comp are\",\"ĠT av\",\"Be ast\",\"Ġsuccess ors\",\"Ġna Ã¯ve\",\"ĠBuck ley\",\"st ress\",\"me at\",\"Ġdownload able\",\"Ġindex ed\",\"Ġsc aff\",\"ĠL ump\",\"ĠHom o\",\"Stud io\",\"In sp\",\"Ġr acked\",\"far ious\",\"ĠPet ty\",\"Ex ternal\",\"Ġ19 09\",\"W ars\",\"com mit\",\"put ers\",\"Ġun ob\",\"ĠEr r\",\"ĠE G\",\"ĠAl am\",\"ĠSiber ia\",\"ĠAtmosp heric\",\"IS TER\",\"ĠSatan ic\",\"trans lation\",\"ĠL oud\",\"tra umatic\",\"l ique\",\"Ġreson ate\",\"ĠWel ch\",\"Ġspark ing\",\"ĠT OM\",\"t one\",\"Ġout l\",\"Ġhandc uffed\",\"ĠSer ie\",\"8 01\",\"Ġland marks\",\"ĠRee ves\",\"Ġsoft ened\",\"Ġdazz ling\",\"ĠW anted\",\"month s\",\"Mag ikarp\",\"Ġunt reated\",\"ĠBed ford\",\"M i\",\"ĠDynam o\",\"O re\",\"79 5\",\"Ġwrong ful\",\"Ġl ured\",\"Ġcort isol\",\"Ġve x\",\"d rawn\",\"ile t\",\"Download ha\",\"ĠF action\",\"Ġlab yrinth\",\"Ġhij acked\",\"w aters\",\"er ick\",\"Ġsuper iors\",\"ĠRow ling\",\"ĠGu inness\",\"Ġt d\",\"99 2\",\"Ġune arthed\",\"Ġcentr if\",\"Ġsham eless\",\"P od\",\"ĠF ib\",\"Ġ icing\",\"Ġpredict or\",\"Ġ29 2\",\"fore station\",\"con struct\",\"C and\",\"@ #\",\"Ġag itated\",\"Ġre pr\",\"OV A\",\"Ġkn itting\",\"ĠLim a\",\"Ġf odder\",\"68 4\",\"ĠPerson a\",\"k l\",\"7 01\",\"Ġbreak up\",\"á ¸\",\"Ġapp alled\",\"Ġantidepress ants\",\"ĠSus sex\",\"Har ris\",\"ĠTher mal\",\"ee ee\",\"U pload\",\"Ġg ulf\",\"Ġdoor step\",\"ĠSh ank\",\"L U\",\"ĠM EN\",\"ĠP ond\",\"s orry\",\"Ġmis fortune\",\"n ance\",\"Ġb ona\",\"M ut\",\"Ġde graded\",\"ĠL OG\",\"ĠN ess\",\"an imal\",\"Ġa version\",\"und own\",\"Ġsupplement ed\",\"ĠC ups\",\"Ġ50 4\",\"Ġdep rive\",\"ĠSpark le\",\"Å Ĥ\",\"ĠMed itation\",\"auth ors\",\"ĠSab an\",\"ĠN aked\",\"air d\",\"ĠMand arin\",\"ĠScript ures\",\"ĠPerson nel\",\"ĠMahar ashtra\",\"Ġ19 03\",\"ĠP ai\",\"ĠMir age\",\"omb at\",\"Access ory\",\"Ġfrag mented\",\"T ogether\",\"Ġbelie vable\",\"ĠGl adiator\",\"al igned\",\"ĠSl ug\",\"M AT\",\"Ġconvert ible\",\"ĠBour bon\",\"amer on\",\"ĠRe hab\",\"nt ax\",\"Ġpowd ered\",\"pill ar\",\"Ġsm oker\",\"ĠMans on\",\"ĠB F\",\"5 11\",\"ĠGood ell\",\"ĠD AR\",\"m ud\",\"g art\",\"Ġob edient\",\"ĠTrans mission\",\"ĠDon ation\",\"8 80\",\"Ġbother ing\",\"Material s\",\"ãĤ ±\",\"dest roy\",\"Ġfore going\",\"Ġanarch ism\",\"ĠK ry\",\"ice ps\",\"Ġl ittered\",\"ĠSch iff\",\"Ġanecd otal\",\"un its\",\"Ġf ian\",\"ĠSt im\",\"ĠS OME\",\"ĠInv aders\",\"Ġbehaviour al\",\"ĠVent ures\",\"Ġsub lime\",\"Ġfru ition\",\"ĠPen alty\",\"Ġcorros ion\",\"¶ ħ\",\"Ġlik ened\",\"Ġbesie ged\",\"ween ey\",\"ĠCre ep\",\"Ġlinem en\",\"mult i\",\"ic ably\",\"ud der\",\"Ġvital ity\",\"Ġshort fall\",\"ĠP ants\",\"ap ist\",\"H idden\",\"ĠDro ps\",\"med ical\",\"Ġpron unciation\",\"ĠN RL\",\"Ġinsight ful\",\"J V\",\"ĠBe ard\",\"ĠCh ou\",\"Ġchar ms\",\"Ġb ins\",\"Ġamb assadors\",\"ĠS aturdays\",\"Ġinhib itor\",\"ĠFr anch\",\"6 01\",\"', '\",\"ĠCon or\",\"art ney\",\"ĠX peria\",\"g rave\",\"be es\",\"ĠProtest ants\",\"Ġso aking\",\"ĠM andal\",\"Ġph ased\",\"Ġ6 60\",\"Ġsc ams\",\"Ġbuzz ing\",\"ĠItal ians\",\"ĠLoren zo\",\"ĠJ A\",\"Ġhes itated\",\"Ġcl iffs\",\"ĠG OT\",\"ingu ishable\",\"Ġk o\",\"Ġinter ruption\",\"Z ip\",\"Lear ning\",\"Ġundersc ores\",\"ĠBl ink\",\"K u\",\"57 9\",\"ĠAut ob\",\"I RE\",\"Ġwater ing\",\"Ġpast ry\",\"8 20\",\"Ġvision ary\",\"ĠTempl ar\",\"awa ited\",\"Ġpist on\",\"Ġant id\",\"current ly\",\"Ġp ard\",\"Ġw aging\",\"Ġnob ility\",\"ĠY us\",\"Ġinject ing\",\"f aith\",\"ĠP ASS\",\"å º\",\"Ġret ake\",\"ĠPR OC\",\"Ġcat hedral\",\"b ash\",\"Ġwrest lers\",\"Ġpartner ing\",\"Ġn oses\",\"Ġ3 58\",\"Trans form\",\"am en\",\"Ġb outs\",\"ĠId eal\",\"ĠConstant in\",\"Ġse p\",\"ĠMon arch\",\"att en\",\"ĠPe oples\",\"mod ified\",\"Ġmor atorium\",\"Ġpen chant\",\"Ġoffensive ly\",\"Ġprox ies\",\"ok ane\",\"ĠTaiwan ese\",\"ĠP oo\",\"ĠH OME\",\"us ional\",\"Ġver bs\",\"ĠO man\",\"vis ory\",\"Ġpersu asion\",\"Ġmult it\",\"Ġsc issors\",\"G ay\",\"ow ay\",\"oph ysical\",\"l us\",\"gn u\",\"Ġap ocalyptic\",\"Ġabsurd ity\",\"Ġplay book\",\"Ġautobi ography\",\"I UM\",\"Ġsne aking\",\"ĠSim ulation\",\"pp s\",\"ell ery\",\"Plan et\",\"Ġright fully\",\"Ġn iece\",\"ĠN EC\",\"ĠIP O\",\"ĠDis closure\",\"lean or\",\"ous y\",\"ST ER\",\"Ġ28 2\",\"Cru z\",\"Ch all\",\"64 3\",\"ĠSurv ive\",\"ĠF atal\",\"ĠAm id\",\"ap o\",\"We apons\",\"D EN\",\"7 70\",\"ĠGreen wald\",\"Ġlin en\",\"al os\",\"Ġpollut ants\",\"ĠPCI e\",\"k at\",\"Ġp aw\",\"ĠK raft\",\"C hem\",\"ĠTermin ator\",\"Ġre incarn\",\"Ġ] [\",\"ĠSe eds\",\"Ġsilhou ette\",\"ĠSt ores\",\"Ġgro oming\",\"ĠD irection\",\"ĠIs abel\",\"ĠBr idges\",\"ðŁ ĳ\",\"E ED\",\"ĠM orsi\",\"Ġval ves\",\"ĠRank ed\",\"ĠPh arma\",\"ĠOrgan izations\",\"Ġpenet rated\",\"ĠRod ham\",\"ĠProt oss\",\"Ġove rest\",\"Ġex asper\",\"ĠT J\",\"Ġ 000000\",\"Ġtrick le\",\"Ġbour bon\",\"WH O\",\"Ġw retched\",\"Ġmicrosc opic\",\"Ġcheck list\",\"Ġad orned\",\"R oyal\",\"Ad minist\",\"ĠRet irement\",\"ĠHig hest\",\"We ather\",\"ile ge\",\"Ġincre ments\",\"ĠC osponsors\",\"Ġmas se\",\"ĠS inn\",\"r f\",\"Ġh ordes\",\"as sembly\",\"75 4\",\"ĠNat asha\",\"ĠTY PE\",\"ĠGEN ERAL\",\"Ġarr anging\",\"Ġ40 7\",\"l ator\",\"Ġg lean\",\"Ġdisc redited\",\"Ġclin icians\",\"UN E\",\"Ġachie ves\",\"ĠEm erson\",\"com plex\",\"= [\",\"Ġprincip ally\",\"Ġfra il\",\"p icked\",\"Ġthan king\",\"Ġre cl\",\"ĠL AST\",\"Ġsupp ressing\",\"il ic\",\"Ġantidepress ant\",\"ĠLis bon\",\"Ġth or\",\"Ġsp a\",\"Ġking doms\",\"ĠPear ce\",\"em o\",\"Ġpl ung\",\"Ġdiv est\",\"Ġ ********************************\",\"b is\",\"osp els\",\"ad r\",\"Sp irit\",\"hall a\",\"P ink\",\"end ez\",\"Ġresurrect ed\",\"esc ape\",\"ĠRosen stein\",\"Ġge ological\",\"Ġnecess ities\",\"Ġcarn iv\",\"ĠE lys\",\"ĠBar ney\",\"Ġ29 6\",\"dig y\",\"ST ON\",\"D OWN\",\"Ġmil estones\",\"Ġk er\",\"Ġdismant ling\",\"Ġre prim\",\"Ġcross ings\",\"19 45\",\"Ġpatri archy\",\"Ġblasp hemy\",\"Ġ3 59\",\"met ry\",\"ĠOb esity\",\"ĠDiff erences\",\"bl ocking\",\"ãĥķ ãĤ¡\",\"ich ita\",\"ĠSab ha\",\"ph alt\",\"ĠCol o\",\"ual a\",\"effic ients\",\"ĠMed ina\",\"con sole\",\"55 7\",\"ĠHann ibal\",\"ĠHab it\",\"ĠF ever\",\"Ġthen ce\",\"Ġsyn agogue\",\"Ġessential s\",\"Ġw ink\",\"ĠTr ader\",\"ID A\",\"ĠSp oiler\",\"ĠIceland ic\",\"ĠHay ward\",\"Ġpe ac\",\"Ġmal ice\",\"Ġflash back\",\"Ġth w\",\"Ġlay offs\",\"L iquid\",\"Ġtro oper\",\"Ġh inge\",\"ĠRead ers\",\"Ph ill\",\"ĠB auer\",\"Cre ated\",\"Ġaud its\",\"ac compan\",\"Ġunsus pecting\",\"ier a\",\"6666 6666\",\"Ġbro ch\",\"Ġapprehend ed\",\"ĠM alk\",\"cer ning\",\"ĠCod ex\",\"O VER\",\"M arsh\",\"ĠD eng\",\"ĠExp ression\",\"Ġdisrespect ful\",\"Ġasc ending\",\"t ests\",\"ĠPlaint iff\",\"ster y\",\"ĠAl ibaba\",\"din and\",\"ĠDem psey\",\"Applic ations\",\"mor al\",\"Ġthrough put\",\"Ġquar rel\",\"Ġm ills\",\"Ġhe mor\",\"ĠC ASE\",\"terror ist\",\"st im\",\"ifest yle\",\"ro zen\",\"CE PT\",\"Ar k\",\"u ci\",\"lect ic\",\"Ġirrit ating\",\"she ets\",\"A y\",\"Ġrede emed\",\"Ġhorn y\",\"ĠTe ach\",\"ĠS ear\",\"dem ocracy\",\"4 65\",\"ĠRest ore\",\"Ġstand by\",\"ĠP is\",\"iff in\",\"Ġsleep y\",\"Ġextr ater\",\"Ġcompl iments\",\"Fram eworks\",\"Ġinstall s\",\"Ġb anging\",\"sur face\",\"found land\",\"Ġmetaph ysical\",\"Ġ28 3\",\"oul s\",\"dev ices\",\"Ar gs\",\"ĠSac rifice\",\"ĠMcC orm\",\"es on\",\"Cons ervative\",\"ĠM ikhail\",\"see ing\",\"is ively\",\"ĠRo oms\",\"ĠGener ic\",\"Ġenthusi astically\",\"Ġgri pped\",\"Ġcomed ic\",\"ĠElectric ity\",\"Ġgu errilla\",\"Ġdec oration\",\"ĠPerspect ive\",\"Ġconsult ations\",\"Ġun amb\",\"Ġplag iar\",\"Ġmagic ian\",\"Ġe rection\",\"ĠTour ism\",\"or ied\",\"ro xy\",\"11 00\",\"T am\",\"Ī è\",\"Î ³\",\"× ª\",\"ĠPred ators\",\"Nit rome\",\"Ġtelesc opes\",\"project s\",\"Ġun protected\",\"Ġst ocked\",\"ĠEnt reprene\",\"nex pected\",\"Ġwast ewater\",\"V ill\",\"Ġint imately\",\"Ġi Cloud\",\"ĠConst able\",\"Ġspo of\",\"Ġne farious\",\"Ġfin s\",\"Ġcens or\",\"ĠMod es\",\"ĠEs per\",\"ar bon\",\"Ġinter sections\",\"Ġlaud ed\",\"Ġphys i\",\"Ġgener ously\",\"ĠThe Nitrome\",\"ĠTheNitrome Fan\",\"Ġar isen\",\"ĠÙ Ī\",\"Ġg lands\",\"ĠPav ilion\",\"ĠGu pta\",\"Ġuniform ly\",\"Ġr amps\",\"ri et\",\"ĠWH EN\",\"ĠVan essa\",\"Ġrout ed\",\"Ġlim p\",\"ĠC PI\",\"p ter\",\"int uitive\",\"Ġv aping\",\"Ġexperiment ed\",\"ĠOlymp us\",\"ĠAm on\",\"Ġsight ing\",\"Ġinfiltr ate\",\"ĠGentle man\",\"Ġsign ings\",\"ĠMe ow\",\"ĠNav igation\",\"che cks\",\"4 33\",\"Ġel apsed\",\"ĠBulg arian\",\"esp ie\",\"ĠS OM\",\"d uring\",\"Ġsp ills\",\"anc a\",\"ĠPly mouth\",\"M AL\",\"Ġdomest ically\",\"ĠWater gate\",\"ĠF AM\",\"k illed\",\"ed ited\",\"ĠYour self\",\"Ġsynchron ization\",\"ĠPract ices\",\"ST EP\",\"Ġgen omes\",\"ĠQ R\",\"not ice\",\"Ġloc ating\",\"z in\",\"Ġ3 29\",\"al cohol\",\"Ġk itten\",\"V o\",\"Ġr inse\",\"Ġgrapp le\",\"ĠSc rew\",\"ĠD ul\",\"A IR\",\"Ġle asing\",\"ĠCaf Ã©\",\"Ġro ses\",\"ĠRes pect\",\"Ġmis lead\",\"Ġperfect ed\",\"Ġnud ity\",\"Ġnon partisan\",\"ĠCons umption\",\"Report ing\",\"Ġnu ances\",\"Ġdeduct ible\",\"ĠSh ots\",\"Ġ3 77\",\"Ġæ ľ\",\"ano oga\",\"Ben ef\",\"ĠB am\",\"ĠS amp\",\"if ix\",\"Ġgal van\",\"ĠMed als\",\"rad ius\",\"Ġno bles\",\"Ġe aves\",\"igr ate\",\"K T\",\"ĠHar bour\",\"u ers\",\"Ġrisk ed\",\"re q\",\"Ġneuro t\",\"get table\",\"ain a\",\"Rom ney\",\"Ġunder pin\",\"Ġlo ft\",\"ĠSub committee\",\"ĠMong ol\",\"b iz\",\"Ġmanif ests\",\"ass isted\",\"ĠG aga\",\"Ġsy nergy\",\"Ġreligious ly\",\"ĠPre f\",\"ĠG erry\",\"T AG\",\"ĠCho i\",\"4 66\",\"beh ind\",\"ĠO u\",\"Gold Magikarp\",\"Ġhemor rh\",\"R iver\",\"Ġtend on\",\"Ġinj ure\",\"ĠF iona\",\"Ġp ag\",\"Ġag itation\",\"|| ||\",\"ur an\",\"ĠE SA\",\"Ġest eem\",\"Ġdod ging\",\"Ġ4 12\",\"r ss\",\"Ġce ases\",\"ex cluding\",\"Ġint akes\",\"Ġinsert s\",\"Ġemb old\",\"ĠO ral\",\"up uncture\",\"4 11\",\"ĠUn ified\",\"ĠDe le\",\"Ġfurn ace\",\"ĠCoy otes\",\"ĠBr ach\",\"L abor\",\"Ġhand shake\",\"Ġbru ises\",\"Gr ade\",\"éĹ ĺ\",\"ĠGram my\",\"ile en\",\"St ates\",\"ĠScandinav ian\",\"ĠKard ash\",\"8 66\",\"Ġeffort lessly\",\"ĠDI RECT\",\"ĠTH EN\",\"ĠMe i\",\"ert ation\",\"19 68\",\"Ġgro in\",\"w itch\",\"Requ irements\",\"98 5\",\"Ġroof s\",\"Ġest ates\",\"ĠH F\",\"Ġha ha\",\"Ġdense ly\",\"ĠO CT\",\"Ġpl astics\",\"Ġincident ally\",\"ĠTr acks\",\"ĠTax es\",\"Ġch anted\",\"Ġforce ful\",\"ĠBie ber\",\"ĠK ahn\",\"K ent\",\"ĠC ot\",\"lic ts\",\"F ed\",\"Ġhide ous\",\"ĠVer d\",\"ĠSynd icate\",\"ĠIl legal\",\"J et\",\"ĠD AV\",\"re asonable\",\"c rew\",\"Ġfundamental ist\",\"Ġtruth ful\",\"ĠJ ing\",\"Ġl il\",\"Ġdown ed\",\"Ġen chanted\",\"ĠPolic ies\",\"ĠMcM aster\",\"ĠH are\",\"ides how\",\"Ġpar ams\",\"en cers\",\"gorith m\",\"Ġallow ances\",\"Ġturb ulent\",\"Ġcomplex ities\",\"ĠK T\",\"Ġ3 37\",\"ĠGen etic\",\"F UN\",\"D oug\",\"t ick\",\"Ġg igs\",\"ument hal\",\"Ġpatriarch al\",\"Ġcal c\",\", ...\",\"Ġc out\",\"ĠGu an\",\"Ġpath ological\",\"ĠR ivals\",\"Ġunder rated\",\"Ġflu orescent\",\"ĠJ iu\",\"arna ev\",\"ĠQu an\",\"Ġ4 29\",\"Ġ à¨\",\"M ario\",\"Con struct\",\"ĠC itation\",\"ĠR acial\",\"ĠR SA\",\"ĠF idel\",\"Ġ3 95\",\"Person ally\",\"C ause\",\"Ã »\",\"rad ical\",\"in en\",\"Ġvehement ly\",\"ĠPap a\",\"Ġintern ship\",\"Ġfl akes\",\"ĠRe ck\",\"Luck ily\",\"B ra\",\"20 20\",\"rav ings\",\"R N\",\"W onder\",\"Ser iously\",\"Ġre usable\",\"Ġpoll uted\",\"ĠP eng\",\"le igh\",\"ind le\",\"Ġcircuit ry\",\"ĠMad onna\",\"ĠB ART\",\"Res idents\",\"att ribute\",\"Phil adelphia\",\"Cl ub\",\"Ġplan ner\",\"Ġfr antically\",\"Ġfaith fully\",\"ĠTerrit ories\",\"ĠL AT\",\"ĠAnders en\",\"an u\",\"ĠP ARK\",\"ĠS ora\",\"i age\",\"ĠPlay offs\",\"ĠG CC\",\"4 27\",\"Ġab norm\",\"ĠL ever\",\"Ġdisob edience\",\"As ync\",\"ĠShe a\",\"V ert\",\"Ġsk irts\",\"ĠSaw yer\",\"x p\",\"Ġwors ening\",\"Ġsc apego\",\"ĠAng le\",\"oth al\",\"Ġtro ve\",\"ĠSt y\",\"ĠN guyen\",\"mar ine\",\"ide on\",\"Dep ths\",\"Bl og\",\"ĠIll uminati\",\"Ġtract s\",\"Ġorgan ise\",\"Ġo str\",\"F s\",\"Ġlever aging\",\"ĠD aredevil\",\"as ar\",\"Ġl ang\",\"Ġex termin\",\"urs ions\",\"ĠRom o\",\"ãĤ¤ ãĥĪ\",\"Ġcont ended\",\"Ġencounter ing\",\"ĠTable t\",\"ĠAltern ate\",\"sk ill\",\"Ġswe ets\",\"Ġco hesive\",\"cap acity\",\"Ġrep ud\",\"Ġl izard\",\"ro o\",\"Ġpilgr ims\",\"ĠR uff\",\"ĠInstr ument\",\"ĠLog o\",\"uit ous\",\"E H\",\"Ġsales man\",\"Ġank les\",\"L ed\",\"ĠPat ty\",\"ud os\",\"Own er\",\"Ġdiscrep ancies\",\"k j\",\"M U\",\"Ġuncond itional\",\"Dragon Magazine\",\"i ard\",\"O ak\",\"ĠConvers ation\",\"be er\",\"ĠOs aka\",\"D elta\",\"us ky\",\"Ġsecret ion\",\"Ġpl aza\",\"Ġm ing\",\"Ġde pletion\",\"ĠM ous\",\"ĠI TS\",\"ĠH imal\",\"ĠFle ming\",\"Ġcyt ok\",\"ĠH ick\",\"Ġbat ters\",\"ĠInt ellectual\",\"6 75\",\"Ã© r\",\"IS ION\",\"ĠQu entin\",\"ĠCh apters\",\"ih adi\",\"Ġco aster\",\"WAY S\",\"ĠL izard\",\"ĠY or\",\"and ering\",\"S kin\",\"ha ust\",\"ab by\",\"Ġportray ing\",\"Ġwield ed\",\"d ash\",\"Ġprop onent\",\"Ġr ipple\",\"Ġgrap hene\",\"Ġfly er\",\"Ġrec urrent\",\"Ġdev ils\",\"Ġwater fall\",\"æĺ ¯\",\"go o\",\"Text Color\",\"Ġtam pering\",\"IV ES\",\"TR UMP\",\"ĠAb el\",\"ĠS AL\",\"ĠHend ricks\",\"ĠLu cius\",\"b ots\",\"Ġ40 96\",\"IST ORY\",\"Gu est\",\"ĠN X\",\"in ant\",\"Ben z\",\"ĠLoad ed\",\"ĠCle ver\",\"t reatment\",\"Ġta vern\",\"Ġ3 39\",\"ĠT NT\",\"ific antly\",\"Tem perature\",\"F el\",\"Ġunder world\",\"ĠJud ges\",\"Ġ< +\",\"Ġst ump\",\"Ġoccup ancy\",\"Ġab er\",\"ĠF inder\",\") \\\",\",\"ĠN unes\",\"res et\",\"in et\",\"ect omy\",\"Ġwell ness\",\"ĠP eb\",\"quart ered\",\"and an\",\"Ġneg atives\",\"ĠTh iel\",\"ĠCl ip\",\"ĠL TD\",\"Ġbl ight\",\"Ġreperto ire\",\"K yle\",\"Ġqu er\",\"ĠC es\",\"Ġha pl\",\"98 9\",\"ĠTh ames\",\"isc opal\",\"Des k\",\"ivari ate\",\"ĠEx cellence\",\"found ation\",\"Ġâ ĩ\",\"X i\",\"Ġmyster iously\",\"esty les\",\"Ġper ish\",\"ĠEng els\",\"ĠDE AD\",\"09 0\",\"}} }\",\"ĠUn real\",\"Ġrest less\",\"ID ES\",\"orth odox\",\"ĠInter mediate\",\"Ġdin ners\",\"ĠTr out\",\"ĠSe ym\",\"ĠHall s\",\"og ged\",\"Ġtraged ies\",\"Ġdid nt\",\"67 6\",\"Ġail ments\",\"Ġobserv able\",\"ĠV ide\",\"ad apt\",\"ĠD usk\",\"Ġprofessional ism\",\"ĠPres cott\",\"ĠInd ies\",\"p ox\",\"ĠMe hran\",\"W ide\",\"Ġend emic\",\"ĠPar an\",\"B ird\",\"Ġped als\",\"ĠI U\",\"ĠAdam ant\",\"ĠH urt\",\"Ġcorrel ates\",\"urd en\",\"Ġspons oring\",\"cl imate\",\"ĠUnivers ities\",\"ĠK not\",\"enn es\",\"ĠDam ian\",\"ĠAx el\",\"S port\",\"Ġbar b\",\"ĠS no\",\"sh own\",\"ste en\",\"ud ence\",\"Ġnon violent\",\"Ġhom ophobia\",\"Ġbiom ass\",\"ĠDet ail\",\"Ġsrf N\",\"ĠT une\",\"accompan ied\",\"I ENCE\",\"Al bert\",\"ĠMong o\",\"z x\",\"ĠCer berus\",\"or bit\",\"c ens\",\"Ġsl ay\",\"SH ARE\",\"H Y\",\"Ġb rawl\",\"ĠPro be\",\"Ġnonex istent\",\"ĠClare nce\",\"ĠBlack burn\",\"Ġport als\",\"ĠR ita\",\"ĠRem ain\",\"ĠLe vant\",\"Ġtrick ed\",\"ĠF erry\",\"aver ing\",\"ĠStraw berry\",\"ĠAn swers\",\"Ġhorrend ous\",\"ĠA man\",\"Supp lement\",\"ĠT oad\",\"Ġpe eled\",\"Ġman oeuv\",\"ĠU zbek\",\"mond s\",\"ĠH ector\",\"Ġ40 2\",\"pe es\",\"fix es\",\"Ġd j\",\"Ġres umes\",\"Ġaccount ant\",\"Ġadvers ity\",\"Ġham pered\",\"ĠL arson\",\"Ġd oping\",\"part s\",\"H ur\",\"Ġbe arded\",\"Ġy r\",\"ĠPlug in\",\"å¥ ³\",\"Ġ/ **\",\"rol ley\",\"Ġwaters hed\",\"ĠSub mission\",\"if lower\",\"AS C\",\"Ġcho ir\",\"Ġsculpt ures\",\"m A\",\"incre asing\",\"ai i\",\"Ġsne akers\",\"Ġconfront s\",\"ĠEle phant\",\"ĠEl ixir\",\"Ġrec al\",\"ĠT TL\",\"w idget\",\"ĠW ax\",\"ĠGr ayson\",\"Ġha irst\",\"Ġhumili ated\",\"ĠWAR N\",\"app iness\",\"ĠT TC\",\"F uel\",\"Ġpol io\",\"Ġcomplex es\",\"Ġbab e\",\"ĠX IV\",\"P F\",\"). [\",\"P arts\",\"Ġ4 35\",\"M eg\",\"ĠY ards\",\"ĠAL P\",\"Ġy ells\",\"Ġprin ces\",\"Ġbull ies\",\"ĠCapital ism\",\"ex empt\",\"FA Q\",\"ĠSp onge\",\"ĠAl a\",\"Ġpleas antly\",\"Ġbu f\",\"Ġden ote\",\"Ġunp ublished\",\"Ġkne eling\",\"asc a\",\"Ġl apse\",\"al ien\",\"99 4\",\"Ġrefere es\",\"ĠLaw yers\",\"S anta\",\"Ġpuzz ling\",\"ĠProm etheus\",\"ĠPh araoh\",\"ĠDel ay\",\"Ġfacilit ates\",\"ĠC ES\",\"Ġjew els\",\"Ġbook let\",\"ond ing\",\"Ġpolar ization\",\"ĠMor an\",\"ĠSal ad\",\"ĠS OS\",\"ĠAdv ice\",\"PH OTOS\",\"IC AN\",\"iat ures\",\"ex press\",\"ĠWonder land\",\"ĠC ODE\",\"ĠCL ASS\",\"9 75\",\"Ġg rep\",\"ĠD iesel\",\"ĠGl ac\",\"! ?\\\"\",\"Ġr m\",\"o ine\",\"disc rimination\",\"ĠN urse\",\"m allow\",\"Ġv ortex\",\"ĠCons ortium\",\"Ġlarge Download\",\"stra ight\",\"augh lin\",\"G rad\",\"Ġpublic ized\",\"ĠW aves\",\"ĠRed d\",\"Ġfest ivities\",\"ĠM ane\",\"ar ov\",\"Ġfleet ing\",\"ĠDr unk\",\"ug en\",\"C ele\",\"Ġchromos omes\",\"ĠD OT\",\"-+-+ -+-+\",\"Ġbus iest\",\"ĠBe aver\",\"Sy rian\",\"ĠK yr\",\"k as\",\"ĠCross Ref\",\"19 50\",\"76 01\",\"Ġrepe aling\",\"ĠWin ners\",\"ĠMac ro\",\"ĠD OD\",\"bl ance\",\"S ort\",\"64 1\",\"Ġmet re\",\"ĠD irk\",\"Ġgo ggles\",\"Ġdraw backs\",\"Ġcomplain ant\",\"Ġauthor izing\",\"Ġantit rust\",\"oper ated\",\"Ġm ah\",\"Ġexagger ation\",\"Am azing\",\"ĠSer aph\",\"Ġha ze\",\"w ow\",\"Ġextingu ished\",\"Ġcan yon\",\"ĠB osh\",\"Ġv ents\",\"Ġsc rape\",\"Cor rect\",\"4 26\",\"Ġav g\",\"Dem and\",\"ĠâĪ ¼\",\"Ġmicrobi ota\",\"\\\"} ],\\\"\",\"ĠSt ev\",\"B io\",\"ĠPlan es\",\"Ġsuggest ive\",\"Ġdec ipher\",\"ĠRefuge e\",\"ĠKe jriwal\",\"ĠGreen peace\",\"Ġdecl ass\",\"ĠSound ers\",\"Ġth o\",\"Ġdec rypt\",\"Ġbr ushing\",\"ĠJane iro\",\"ip op\",\"S i\",\"8 77\",\"ĠGeoff rey\",\"Ġc pu\",\"ĠHaz el\",\"Ġview points\",\"Ġcris py\",\"ĠNot ification\",\"Ġsold er\",\"ĠMod est\",\"ĠHem isphere\",\"Ġcass ette\",\"in cludes\",\"Ġident ifiers\",\"ĠC ALL\",\"in cent\",\"T odd\",\"ĠSwe ep\",\"Ġ3 34\",\"b oss\",\"Ġsm ir\",\"gin x\",\"Ġtown ship\",\"Ġg rieving\",\"ĠMos que\",\"Net flix\",\"AS ED\",\"ĠMillenn ials\",\"oc om\",\"19 67\",\"Ġbold ly\",\"s leep\",\"Ġes che\",\"arij uana\",\"Ġsw irl\",\"ĠPen al\",\"Ġneglig ent\",\"ĠStephen son\",\"K ER\",\"ĠZ oro\",\"ris is\",\"Ġlocal ization\",\"ĠSeym our\",\"ĠAng lic\",\"red itation\",\"prot ection\",\"ĠPa ige\",\"Ġo mit\",\"ĠR ousse\",\"ĠT ub\",\"Ġinv itations\",\"t ty\",\"Ġm oss\",\"ph ysical\",\"C redits\",\"Ġan archy\",\"Ġchild care\",\"Ġl ull\",\"ĠM ek\",\"ĠL anguages\",\"lat est\",\"ĠSan ford\",\"Ġus ability\",\"Ġdiff use\",\"ĠD ATA\",\"Ġsp rites\",\"ĠVeget a\",\"ĠProm otion\",\"ãĥ¼ ãĤ¯\",\"rict ing\",\"z ee\",\"Tur kish\",\"ĠTD s\",\"pro ven\",\"57 1\",\"Ġsmug glers\",\"707 10\",\"Ġreform ed\",\"ĠLo is\",\"Ġun fl\",\"ĠWITH OUT\",\"ĠReturn ing\",\"ann ie\",\"ĠTom as\",\"Fr anc\",\"ĠProf it\",\"ĠSER V\",\"ĠR umble\",\"ik uman\",\"es an\",\"Ġt esters\",\"Ġgad get\",\"Ġbrace let\",\"ĠF SA\",\"comp onent\",\"Ġparamed ics\",\"Ġj an\",\"ĠRem em\",\"ĠSk inner\",\"Ġl ov\",\"ĠQu ake\",\"rom a\",\"Ġfl ask\",\"Pr inc\",\"Ġover power\",\"Ġlod ging\",\"ĠK KK\",\"ret te\",\"Ġabsor bs\",\"w rote\",\"Ġ ,\\\"\",\"K ings\",\"ĠH ail\",\"ĠFall ing\",\"xt ap\",\"ĠHel ena\",\"ire ns\",\"L arry\",\"Ġpamph let\",\"ĠC PR\",\"G ro\",\"ĠHirosh ima\",\"Ġhol istic\",\"\\\". [\",\"Ġdet achment\",\"Ġas pire\",\"Ġcompl icit\",\"ĠGreen wood\",\"Ġresp awn\",\"ĠSt upid\",\"ĠFin ished\",\"f al\",\"b ass\",\"Ġab hor\",\"Ġmock ery\",\"ĠFe ast\",\"VID EO\",\"Ġcon sec\",\"ĠHung ry\",\"P ull\",\"ĠH ust\",\"it ance\",\"? ãĢį\",\") --\",\"ĠPar allel\",\"con v\",\"4 69\",\"ha ar\",\"w ant\",\"P aper\",\"m ins\",\"ĠTor o\",\"ĠTR UMP\",\"ĠR ai\",\"D W\",\"ĠW icked\",\"ĠL ep\",\"Ġfun ky\",\"Ġdetrim ent\",\"ios is\",\"ache v\",\"Ġde grade\",\"im ilation\",\"Ġret ard\",\"Ġfrag mentation\",\"Ġcow boy\",\"ĠY PG\",\"ĠH AL\",\"Parent s\",\"ĠS ieg\",\"ĠStra uss\",\"ĠRub ber\",\"× Ĳ\",\"Fr ag\",\"Ġp t\",\"Ġoption ally\",\"ĠZ IP\",\"ĠTrans cript\",\"ĠD well\",\"88 2\",\"M erc\",\"ĠM OT\",\"ãĥ¯ ãĥ³\",\"Ġhun ts\",\"Ġexec utes\",\"In cludes\",\"Ġacid ic\",\"ĠRespons ibility\",\"ĠD umb\",\"we i\",\"And erson\",\"ĠJas per\",\"ight on\",\"abs olutely\",\"Ad ult\",\"Ġpl under\",\"Mor ning\",\"ĠT ours\",\"ĠD ane\",\"Î º\",\"ĠT EST\",\"ĠG ina\",\"Ġcan ine\",\"aw an\",\"Ġsocial ists\",\"ĠS oda\",\"Ġimp etus\",\"ĠSupplement ary\",\"oli ath\",\"ĠKinn ikuman\",\"mitted ly\",\"second s\",\"Ġorganis ers\",\"Ġdocument aries\",\"Vari able\",\"GRE EN\",\"Ġres orts\",\"Ġbr agging\",\"Ġ3 68\",\"Art ist\",\"w k\",\"bl ers\",\"Un common\",\"ĠRet rieved\",\"Ġhect ares\",\"Ġtox in\",\"r ank\",\"Ġfaith s\",\"ĠG raphic\",\"Ġve c\",\"ĠL IA\",\"Af rican\",\"Ġard ent\",\"end iary\",\"L ake\",\"ĠD OS\",\"cient ious\",\"ĠOk awaru\",\"ĠAll y\",\"ĠTim eline\",\"D ash\",\"ĠI c\",\"contin ue\",\"Ġt idy\",\"Ġinstinct ively\",\"ĠP ossibly\",\"ĠOut door\",\"ĠWould n\",\"Ġl ich\",\"ĠBr ay\",\"ĠA X\",\"ĠÃ ī\",\"Ġ+ #\",\"\\\\ '\",\"Direct ory\",\"ab iding\",\"Ġf eral\",\"ic ative\",\"but t\",\"Ġper verse\",\"S alt\",\"Ġwar ped\",\"Ġnin eteen\",\"Ġcabin ets\",\"Ġsrf Attach\",\"ĠSl oan\",\"Ġpower ing\",\"reg ation\",\"F light\",\"se vere\",\"Ġst ren\",\"Ġc og\",\"ap ache\",\"Ġâ Ŀ\",\"Ġcaf eteria\",\"p aces\",\"ĠGrim oire\",\"uton ium\",\"Ġr aining\",\"Ġcir cling\",\"Ġlineback ers\",\"c redit\",\"Ġrep atri\",\"ĠCam den\",\"lic ense\",\"Ġly ric\",\"Ġdescript or\",\"Ġval leys\",\"Ġre q\",\"Ġback stage\",\"ĠPro hibition\",\"ĠK et\",\"Op ening\",\"S ym\",\"æĸ ¹\",\"Ġserv ings\",\"Ġoverse en\",\"Ġaster oids\",\"ĠMod s\",\"ĠSpr inger\",\"ĠCont ainer\",\"è »\",\"ĠM ens\",\"Ġmult im\",\"Ġfire fighter\",\"pe c\",\"Ġchlor ine\",\"Ð ¼\",\"end i\",\"Ġsp aring\",\"Ġpolyg amy\",\"ĠR N\",\"ĠP ell\",\"Ġt igers\",\"Ġflash y\",\"ĠMad ame\",\"S word\",\"Ġpref rontal\",\"Ġpre requisite\",\"uc a\",\"Ġw ifi\",\"Ġmiscon ception\",\"Ġharsh ly\",\"ĠStream ing\",\"ot om\",\"ĠGiul iani\",\"foot ed\",\"Ġtub ing\",\"ind ividual\",\"z ek\",\"n uclear\",\"m ol\",\"Ġright ful\",\"49 3\",\"Ġspecial ization\",\"Ġpassion ately\",\"ĠVel ocity\",\"ĠAv ailability\",\"T enn\",\"Ġl atch\",\"ĠSome body\",\"Ġhel ium\",\"cl aw\",\"Ġdi pping\",\"XX X\",\"Ġinter personal\",\"7 10\",\"Ġsub ter\",\"Ġbi ologists\",\"ĠLight ing\",\"Ġopt ic\",\"Ġden im\",\"end on\",\"ĠC orm\",\"Ġ3 41\",\"ĠC oup\",\"Ġfear less\",\"Ġal ot\",\"ĠCliff ord\",\"ĠRun time\",\"ĠProv ision\",\"up dated\",\"lene ck\",\"Ġneur on\",\"Ġgrad ing\",\"ĠC t\",\"sequ ence\",\"in ia\",\"con cept\",\"Ġro aring\",\"ri val\",\"ĠCaucas ian\",\"Ġmon og\",\"key es\",\"Ġappell ate\",\"Ġlia ison\",\"EStream Frame\",\"ĠPl um\",\"! .\",\"Ġsp herical\",\"Ġper ished\",\"Ġbl ot\",\"Ġben ches\",\"Ġ4 11\",\"Ġpione ered\",\"Ġhur led\",\"Jenn ifer\",\"ĠYose mite\",\"Ch air\",\"Ġreef s\",\"Ġelect or\",\"ĠAnt hem\",\"65 2\",\"Ġun install\",\"Ġimp ede\",\"Ġbl inking\",\"Ġgot o\",\"Dec re\",\"A ren\",\"Ġstabil ization\",\"ĠDis abled\",\"ĠYanuk ovych\",\"Ġoutlaw ed\",\"ĠVent ura\",\"ten ess\",\"Ġplant ation\",\"Ġy acht\",\"ĠHu awei\",\"Ġsol vent\",\"Ġgr acious\",\"Ġcur iously\",\"Ġcapac itor\",\"Ġc x\",\"ĠRef lex\",\"Ph ys\",\"ĠC f\",\"pt in\",\"cons ervative\",\"Ġinv ocation\",\"c our\",\"F N\",\"ĠNew ly\",\"H our\",\"As ian\",\"ĠLe ading\",\"ĠAer ospace\",\"An ne\",\"Ġpre natal\",\"Ġdeterior ating\",\"H CR\",\"ĠNorm andy\",\"ol ini\",\"ĠAm bro\",\"9 10\",\"Ġset backs\",\"ĠT RE\",\"Ġs ig\",\"ĠSc ourge\",\"59 7\",\"79 8\",\"Game play\",\"Ġm sec\",\"M X\",\"Ġprice y\",\"ĠL LP\",\"aker u\",\"Ġover arching\",\"ĠB ale\",\"Ġworld ly\",\"Cl ark\",\"Ġscen ic\",\"Ġdisl iked\",\"ĠCont rolled\",\"T ickets\",\"ĠE W\",\"ab ies\",\"ĠPl enty\",\"Non etheless\",\"Ġart isan\",\"Trans fer\",\"ĠF amous\",\"Ġinf ield\",\"ble y\",\"Ġunres olved\",\"ĠML A\",\"ãĤ Ĥ\",\"Cor rection\",\"Ġdemocr at\",\"ĠMore no\",\"ro cal\",\"il ings\",\"Ġsail or\",\"Ġr ife\",\"h ung\",\"Ġtrop es\",\"Ġsn atched\",\"ĠL IN\",\"ĠB ib\",\"ES A\",\"ĠPre v\",\"ĠCam el\",\"run time\",\"Ġob noxious\",\"4 37\",\"Ġsum mers\",\"Ġunexpl ained\",\"ĠWal ters\",\"cal iber\",\"Ġg ull\",\"ĠEnd urance\",\"ä½ ľ\",\"Ġ3 47\",\"Ir ish\",\"Ġaer obic\",\"Ġcr amped\",\"ĠHon olulu\",\"à ©\",\"us erc\",\"ec ast\",\"AC Y\",\"ĠQu ery\",\"ãĤ¹ ãĥĪ\",\"Bet a\",\"Ġsuscept ibility\",\"ĠSh iv\",\"ĠLim baugh\",\"ĠÃ ĸ\",\"ĠN XT\",\"ĠM uss\",\"ĠBrit ons\",\"ES CO\",\"EG IN\",\"Ġ% %\",\"Ġsec ession\",\"ĠPat ron\",\"ĠLu a\",\"n aires\",\"ĠJPM organ\",\"us b\",\"ocy te\",\"Ġcouncill ors\",\"ĠLi ang\",\"f arm\",\"Ġnerv ously\",\"Ġattract iveness\",\"ĠK ov\",\"j ump\",\"Pl ot\",\"Ġst ains\",\"ĠStat ue\",\"ĠApost les\",\"he ter\",\"ĠSUP PORT\",\"Ġoverwhel m\",\"Y ES\",\"Ġ29 1\",\"d ensity\",\"Ġtra pping\",\"M it\",\"Ġf ide\",\"ĠPam ela\",\"atl antic\",\"Dam n\",\"Ġp ts\",\"OP A\",\"Ġserv icing\",\"Ġoverfl owing\",\"ul o\",\"ĠE rit\",\"t icket\",\"light ing\",\"ĠH mm\",\"ãĥ¼ ãĥ«\",\"im oto\",\"Ġchuck le\",\"4 23\",\"ãģ ķ\",\"sh ape\",\"Ġque ues\",\"Ġanch ors\",\"ãĤ¼ ãĤ¦ãĤ¹\",\"F er\",\"Ġaw oke\",\"Ġ6 66\",\"h ands\",\"Ġdiver gence\",\"Ġ50 5\",\"T ips\",\"Ġdep ot\",\"Ġske w\",\"ĠDel iver\",\"op ot\",\"Ġdiv ul\",\"ĠE B\",\"uns igned\",\"ĠUn i\",\"X box\",\"Ġfor ks\",\"Ġ7 02\",\"å ¯\",\"Ġpromot ers\",\"ĠV apor\",\"Ġlev ied\",\"sl ot\",\"Ġpig ment\",\"Ġcyl inders\",\"C RE\",\"Ġsn atch\",\"Ġperpet ually\",\"Ġl icking\",\"ĠFe et\",\"ĠKra ken\",\"ĠHold en\",\"ĠCLS ID\",\"m r\",\"Ġproject or\",\"Ġden otes\",\"Ġchap el\",\"ĠTor rent\",\"b ler\",\"R oute\",\"ĠDef endant\",\"ĠPublisher s\",\"ĠM ales\",\"ĠInn ov\",\"ĠAg ility\",\"rit er\",\"ty mology\",\"st ores\",\"L ind\",\"Ġf olly\",\"ĠZur ich\",\"B le\",\"Ġnurt ure\",\"Ġcoast line\",\"uch in\",\"D omin\",\"Ġfri vol\",\"ĠCons olid\",\"res ults\",\"M J\",\"Ġphyl ogen\",\"Ġha uled\",\"ĠW iley\",\"ĠJess ie\",\"ĠPrep are\",\"ĠE ps\",\"Ġtreasure r\",\"I AS\",\"Ġcolon ists\",\"Ġin und\",\"ĠWW F\",\"ĠCon verted\",\"6 000\",\"out side\",\"ĠApp earance\",\"ĠRel ic\",\"ĠM ister\",\"s aw\",\"Ġresult ant\",\"Ġadject ive\",\"ĠLaure l\",\"ĠHind i\",\"b da\",\"Pe ace\",\"Ġreb irth\",\"Ġmembr anes\",\"Ġforward ing\",\"Ġcoll ided\",\"ĠCar olyn\",\"K ansas\",\"5 99\",\"ĠSolid GoldMagikarp\",\"Be ck\",\"Ġstress ing\",\"ĠGo o\",\"ĠCooper ative\",\"Ġf s\",\"ĠAr chie\",\"L iter\",\"ĠK lopp\",\"J erry\",\"Ġfoot wear\",\"War ren\",\"Ġsc ree\",\"h are\",\"Under standing\",\"P ed\",\"Ġanth ology\",\"ĠAnn ounce\",\"M ega\",\"Ġflu ent\",\"Ġbond age\",\"ĠDisc ount\",\"il ial\",\"C art\",\"ĠNight mares\",\"Sh am\",\"ĠB oll\",\"uss ie\",\"H ttp\",\"Atl anta\",\"Ġun recogn\",\"ĠB id\",\"Ġunder grad\",\"Ġforg iving\",\"ĠGl over\",\"AAAA AAAA\",\"4 45\",\"V G\",\"pa io\",\"kill ers\",\"Ġrespons ibly\",\"Ġmobil ize\",\"Ġeffect ed\",\"ĠL umin\",\"Ġk ale\",\"Ġinfring ing\",\"ann ounced\",\"Ġf itt\",\"b atch\",\"ĠT ackle\",\"ĠL ime\",\"ĠAP P\",\"uke mia\",\"Ġrub y\",\"Ġex oner\",\"ĠCas ual\",\"0 70\",\"Ġpel vic\",\"Ġautom ate\",\"ĠK ear\",\"ĠCoast al\",\"Ġcre ed\",\"Ġbored om\",\"ĠSt un\",\"ri ott\",\"Ĥ İ\",\"Ġregener ate\",\"Ġcomed ians\",\"ĠOP ER\",\"Sp ons\",\"id ium\",\"on is\",\"L ocated\",\"05 7\",\"Ġsusp ense\",\"ĠD ating\",\"C ass\",\"Ġneoc ons\",\"ĠShin zo\",\"Ġaw oken\",\"ch rist\",\"ĠMess ages\",\"att led\",\"ĠSpr ay\",\"ĠSp ice\",\"C W\",\"Ġshield ing\",\"ĠG aul\",\"Am id\",\"Ġparam ilitary\",\"Ġmult if\",\"ĠTan ner\",\"il k\",\"Ġgodd amn\",\"g ements\",\"Ġbe friend\",\"m obi\",\"Ġ3 88\",\"fold er\",\"acc a\",\"Ġins in\",\"g ap\",\"N ev\",\"fif th\",\"Ġpsychiat ry\",\"b anks\",\"TH IS\",\"Ġhar b\",\"ac qu\",\"Ġfac ade\",\"ĠPower Point\",\"80 3\",\"Ġbl uff\",\"Sh ares\",\"Ġfavor ing\",\"El izabeth\",\"Ãį Ãį\",\"Ġr anger\",\"77 2\",\"ĠAr che\",\"h ak\",\"ĠGen etics\",\"ĠF EMA\",\"Ġev olves\",\"Ġest e\",\"ĠP ets\",\"ĠM Ã©\",\"ĠInterest ing\",\"ĠCanter bury\",\"ch apter\",\"ĠStar fleet\",\"Sp anish\",\"Ġdraw back\",\"ĠNor wich\",\"9 70\",\"n orth\",\"ag anda\",\"Ġtransform ative\",\"ram ids\",\"bi ology\",\"ad ay\",\"Ġpropag ation\",\"ĠGam ma\",\"ĠDen ise\",\"ĠCalcul ator\",\"ent imes\",\"ĠB ett\",\"Ġapp endix\",\"ĠHD D\",\"AK ING\",\"Ġst igmat\",\"Ġhol ster\",\"Ġord inarily\",\"Ch ance\",\"ĠCont rary\",\"Ġad hesive\",\"Ġgather s\",\"6 12\",\"re au\",\"ony ms\",\"ew ays\",\"Ġindu ces\",\"Ġinterchange able\",\"se m\",\"Wh it\",\"Ġtr ance\",\"Ġincorpor ation\",\"ĠExt ras\",\"Fin ancial\",\"Ġawkward ly\",\"ĠStur geon\",\"ĠH Y\",\"Norm ally\",\"ĠEnd ing\",\"ĠAss ist\",\"enc rypted\",\"Ġsub jug\",\"Ġn os\",\"Ġfan atic\",\"C ub\",\"C U\",\"?\\\" .\",\"Ġirre versible\",\"å Ĥ\",\"03 1\",\"ĠH AR\",\"sp read\",\"ul ia\",\"= $\",\"Sc ope\",\"L ots\",\"Ġlif estyles\",\"ol on\",\"Ġf eds\",\"Ġcongrat ulate\",\"web kit\",\"Ġindist inguishable\",\"ĠSw ing\",\"Ġcommand ments\",\"qu ila\",\"ab ella\",\"m ethyl\",\"ann abin\",\"Ġo vere\",\"Ġlob ster\",\"ĠQU EST\",\"ĠCONT IN\",\"bern atorial\",\":::: ::::\",\"ĠTra ve\",\"ĠSam oa\",\"AN I\",\"75 2\",\"Ð ´\",\"userc ontent\",\"ĠMod erate\",\"y eah\",\"ĠK itt\",\"Ġwe e\",\"Ġstuff ing\",\"ĠInter vention\",\"ĠD ign\",\"Ġware houses\",\"ĠF iji\",\"Ġpel lets\",\"Ġtake away\",\"ĠT ABLE\",\"ĠClass ical\",\"col lection\",\"Ġland fall\",\"ĠMus cle\",\"Ġsett les\",\"ĠAD V\",\"Ġ3 44\",\"L aura\",\"Ġf ared\",\"ĠPart ial\",\"4 36\",\"oss ibility\",\"ĠD aly\",\"ĠT arant\",\"ĠFu ji\",\"am l\",\"c ence\",\"55 1\",\"ĠProced ures\",\"ĠO CD\",\"ĠU D\",\"t in\",\"Q UI\",\"ach o\",\"4 38\",\"Ġgl itches\",\"Ġenchant ment\",\"Ġcalcul ates\",\"IR O\",\"ĠH ua\",\"alys es\",\"ĠL ift\",\"um o\",\"Ġle apt\",\"Ġhypothes ized\",\"ĠGust av\",\"it ans\",\"VERS ION\",\"æ ł\",\"Rog er\",\"Ġr and\",\"ĠAd apter\",\"Ġ3 31\",\"ĠPet ition\",\"k ies\",\"M ars\",\"Ġunder cut\",\"ze es\",\"ĠLy ons\",\"ĠDH CP\",\"Miss ing\",\"Ġretire es\",\"Ġins idious\",\"el i\",\"> )\",\". ãĢį\",\"Ġfinal ists\",\"ĠA ure\",\"Ġacc user\",\"Ġwas tes\",\"ĠY s\",\"ĠL ori\",\"Ġconstitu encies\",\"Ġsupp er\",\"Ġmay hem\",\"or ange\",\"Ġmis placed\",\"Ġmanager ial\",\"Ġex ce\",\"ĠCL I\",\"Ġprim al\",\"ĠL ent\",\"Cry stal\",\"h over\",\"ĠN TS\",\"end um\",\"Ġd w\",\"ĠAl c\",\"n ostic\",\"Ġpres erves\",\"ĠTs arnaev\",\"Ġtri pled\",\"rel ative\",\"Arc ade\",\"k illing\",\"ĠW EEK\",\"ĠH anna\",\"D ust\",\"Com pleted\",\"ģ «\",\"Ġappro ves\",\"ĠSur f\",\"ĠLuther an\",\"ven ants\",\"Ġrobber ies\",\"we ights\",\"soft ware\",\"at ana\",\"ug al\",\"Ġgrav y\",\"ĠC ance\",\"OLOG Y\",\"ly ak\",\"Ton ight\",\"Ġunve il\",\"Ġ19 04\",\"ĠMin ion\",\"ent ious\",\"st ice\",\"pack ages\",\"ĠG EAR\",\"Ġg ol\",\"ĠHutch inson\",\"ĠProf ession\",\"ĠG UN\",\"ĠDiff erence\",\"ĠTsuk uyomi\",\"ĠLes bian\",\"6 70\",\"Ġfug itive\",\"ĠPlan etary\",\"-------------------------------- ------------------------\",\"Ġacc rued\",\"Ġch icks\",\"Ġsto pp\",\"Ġblock ers\",\"C od\",\"Ġcomment ers\",\"ĠSomew here\",\"ĠPhot ographer\",\"the me\",\"Ġmay oral\",\"w u\",\"Ġanten nas\",\"Ġrev amped\",\"ĠSubject s\",\"it Ã©\",\"im ura\",\"Ġentr ances\",\"liter ally\",\"Ġten ets\",\"ĠO MG\",\"ĠMP H\",\"ĠDon key\",\"ĠOff ense\",\"Ġ\\\" +\",\"Sn ap\",\"ĠAF B\",\"Ġan imate\",\"ĠS od\",\"His panic\",\"Ġinconsist ency\",\"D b\",\"F Y\",\"Ex port\",\"Ġa pe\",\"Ġpear l\",\"ib el\",\"ĠPAC s\",\"Ġ{ \\\\\",\"Ġact u\",\"ĠHS BC\",\"camp us\",\"Ġpay off\",\"Ġde ities\",\"ĠN ato\",\"ou ple\",\"Ġcens ored\",\"ĠCl ojure\",\"Ġconf ounding\",\"en i\",\"Ġreck on\",\"op he\",\"Ġspot ting\",\"Ġsign ifies\",\"Ġprop el\",\"Ġfest ive\",\"S uggest\",\"Ġpled ging\",\"ĠB erman\",\"Ġrebell ious\",\"Ġovershadow ed\",\"Ġinfiltr ated\",\"j obs\",\"67 2\",\"Ġscal able\",\"Ġdomin ion\",\"ĠNew foundland\",\"ĠMead ow\",\"Ġpart itions\",\"AM I\",\"Ġsupplement ary\",\"str ument\",\"Ġhair y\",\"Ġperpet uate\",\"Ġnuts hell\",\"ĠPot ato\",\"ĠHob bit\",\"Ġcur ses\",\"Flo at\",\"Ġquiet er\",\"Ġfuel ing\",\"Ġcaps ules\",\"ĠL ust\",\"ĠH aunted\",\"Exec utive\",\"Ġchild birth\",\"G re\",\"Ġrad iant\",\"å İ\",\"Ġm alls\",\"Ġin ept\",\"ĠWarrant y\",\"Ġspect ator\",\"E h\",\"t hens\",\"Ġculmin ating\",\"æ ©\",\"ary a\",\"ãĤ ®\",\"ilit arian\",\"ĠOR IG\",\"ĠSp ending\",\"pt ives\",\"ĠS iren\",\"ĠRec ording\",\"ay ne\",\"Ġv im\",\"Ġspr ang\",\"T ang\",\"ĠM FT\",\"mor ning\",\"ĠWe ed\",\"m peg\",\"cess ion\",\"ĠCh ung\",\"7 30\",\"w arning\",\"56 2\",\"handed ly\",\"P oor\",\"P olitics\",\": #\",\"Ġp ian\",\"Ġfec es\",\"ĠDocument ation\",\"Ġban ished\",\"Ġ3 99\",\"ĠAR C\",\"Ġhe inous\",\"J ake\",\"ĠAm ir\",\"way ne\",\"v re\",\"os henko\",\"Ġnotebook s\",\"Ġfound ational\",\"Ġmarvel ous\",\"ixt ape\",\"Ġwithdraw als\",\"Ġh orde\",\"ĠD habi\",\"is able\",\"ĠK D\",\"Ġcontag ious\",\"ĠD ip\",\"ĠAr rows\",\"Ġpronoun s\",\"Ġmorph ine\",\"ĠB US\",\"68 2\",\"Ġk osher\",\"fin ished\",\"ĠInstr uments\",\"Ġf used\",\"yd en\",\"ĠSal mon\",\"F ab\",\"aff ected\",\"K EN\",\"C ENT\",\"Dom ain\",\"Ġpoke mon\",\"ĠDr inking\",\"G rowing\",\"ĠInvestig ative\",\"ĠA ether\",\"em i\",\"Ġtabl oid\",\"Ġrep ro\",\"ĠNot withstanding\",\"ĠBers erker\",\"Ġdram as\",\"Ġclich Ã©\",\"Ġb ung\",\"ĠU RI\",\"ĠD os\",\"0 44\",\"Ġpast ors\",\"Ġl s\",\"Ġac rylic\",\"aun ts\",\"Ed ward\",\"Ġmajor ities\",\"B ang\",\"Ġfield ing\",\"ĠRepl acement\",\"ĠAl chemy\",\"pp ard\",\"ĠRome o\",\"ĠSan ct\",\"ĠLav rov\",\"ib ble\",\"Inst ruct\",\"Ġimp ractical\",\"ĠPlay boy\",\"ce phal\",\"Ġsw aps\",\"Ġk an\",\"ĠThe o\",\"Ġillust rating\",\"Ġdismant led\",\"ĠTrans gender\",\"ĠG uth\",\"UG H\",\"Ġtriumph ant\",\"Ġencomp ass\",\"Ġbook mark\",\"udd in\",\"j er\",\"Ġpred icate\",\"ES H\",\"Ġwhen ce\",\"ĠAB E\",\"Ġnon profits\",\"Se qu\",\"Ġdi abetic\",\"Ġp end\",\"Ġheart felt\",\"sh i\",\"Ġinter acts\",\"ĠTele com\",\"Ġbombard ment\",\"dep ending\",\"ĠLow ry\",\"ĠAd mission\",\"ĠBl ooming\",\"ust ration\",\"ene gger\",\"B rew\",\"Ġmol ten\",\"ĠNer d\",\"P IN\",\"âĸ Ģ\",\"ave ment\",\"Ġtou red\",\"Ġco efficients\",\"ĠTray von\",\"ans son\",\"Ġsand y\",\"t old\",\"fl ows\",\"Ġpop ulous\",\"ĠT inder\",\"ĠBl iss\",\"R achel\",\"Min imum\",\"Ġcontest ant\",\"ĠRed uce\",\"ĠMor se\",\"ĠGrass ley\",\"ĠClick er\",\"Ġexp r\",\"Ġs incerity\",\"Ġmar qu\",\"Ġelic it\",\"ĠPro position\",\"ĠDemon ic\",\"Ġtac os\",\"G reek\",\"Ġpost war\",\"Ġin sofar\",\"ĠP ork\",\"Ġ35 2\",\"doctor al\",\"walk ing\",\"Ġmid term\",\"ĠSam my\",\"sight ed\",\"ĠTR ANS\",\"ic i\",\"AL D\",\"ĠUS L\",\"ĠF ISA\",\"ĠAm pl\",\"ĠAlex andra\",\"ine lli\",\"Tr ain\",\"Ġsign ify\",\"ĠVers us\",\"Ġob fusc\",\"Ġk h\",\"Ġagg ro\",\"ĠRen ault\",\"Ġ3 48\",\"5 18\",\"ox icity\",\"0 22\",\"ĠTw ist\",\"Ġgoof y\",\"D ynamic\",\"Ġbrief ings\",\"m ight\",\"8 99\",\"Ġderog atory\",\"T ro\",\"Ġfor ging\",\"ĠKor an\",\"ĠMar ried\",\"ĠBuc s\",\"Ġpal ate\",\"ĠCon version\",\"m able\",\"4 13\",\"Ġ( _\",\"Ġs iph\",\"ĠN EO\",\"col lege\",\"Ġmarg inally\",\"Ġfl irt\",\"ĠTra ps\",\"ĠP ace\",\"é »Ĵ\",\"Ġgoalt ender\",\"Ġforb ids\",\"Ġcler ks\",\"ĠT ant\",\"ĠRobb ins\",\"ĠPrint ing\",\"Ġpremie red\",\"Ġmagn ification\",\"ĠT G\",\"ĠR ouse\",\"ĠM ock\",\"odynam ics\",\"Ġpre clude\",\"ism o\",\"ĠPul itzer\",\"Ġaval anche\",\"ĠK odi\",\"rib une\",\"ĠL ena\",\"Elect ric\",\"Ġref inery\",\"Ġend owed\",\"Ġcounsel ors\",\"Ġd olphin\",\"ĠM ith\",\"Ġarm oured\",\"hib ited\",\"Beg in\",\"ĠP W\",\"O il\",\"ĠV or\",\"ĠShar if\",\"ĠFraz ier\",\"est ate\",\"Ġj ams\",\"Pro xy\",\"Ġband its\",\"ĠPresbyter ian\",\"ĠPrem iere\",\"t iny\",\"ĠCru el\",\"Test ing\",\"Ġhom er\",\"ĠV ERS\",\"ĠPro l\",\"ĠDep osit\",\"ĠCoff in\",\"Ġsemin ars\",\"Ġs ql\",\"ĠDef endants\",\"Altern atively\",\"ĠR ats\",\"ç «\",\"ethy st\",\"' >\",\"Ġiss uer\",\"58 9\",\"Ġch aired\",\"ĠAccess ories\",\"man ent\",\"Ġmar row\",\"ĠPrim ordial\",\"C N\",\"Ġlimit less\",\"ĠCarn age\",\"Ġund rafted\",\"q v\",\"IN ESS\",\"on ew\",\"Ġco hesion\",\"98 7\",\"Ġne cks\",\"Ġfootball er\",\"ĠG ER\",\"Ġdetect able\",\"ĠSupport ing\",\"ĠCS V\",\"oc ally\",\"k Hz\",\"Ġund e\",\"Ġsh one\",\"Ġbud ding\",\"tra k\",\"Stand ing\",\"ĠStar craft\",\"ĠKem p\",\"Ben ch\",\"Ġthw arted\",\"ĠGround s\",\"ath i\",\"L isa\",\"Dial og\",\"ĠS X\",\"V ision\",\"Ġingen ious\",\"Ù Ĳ\",\"Ġfost ering\",\"ĠZ a\",\"ĠIn gram\",\"Ġ\\\" @\",\"N aturally\",\"6 16\",\"0 35\",\"ĠF AC\",\"H mm\",\"55 4\",\"Ġacceler ator\",\"ĠV end\",\"Ġsun screen\",\"Ġtuber culosis\",\"rav iolet\",\"ĠFunction al\",\"ĠEr rors\",\"ed ar\",\"19 66\",\"ĠSpect re\",\"ĠRec ipes\",\"88 5\",\"ĠM ankind\",\"L iverpool\",\"Ġ| --\",\"Ġsubst itutes\",\"ĠX T\",\"w ired\",\"Ġinc o\",\"ĠAf gh\",\"E va\",\"ic c\",\"S ong\",\"K night\",\"Ġdilig ently\",\"ĠBroad cast\",\"A id\",\"Ġaf ar\",\"ĠH MS\",\"aton in\",\"ĠGr ateful\",\"Ġfire place\",\"ĠOm ni\",\"e uro\",\"ĠF RE\",\"ĠSh ib\",\"ĠDig est\",\"t oggle\",\"Ġheads ets\",\"Ġdiff usion\",\"ĠSqu irrel\",\"ĠF N\",\"Ġdark ened\",\"out her\",\"Ġsleep s\",\"ĠX er\",\"gun s\",\"Ġset ups\",\"Ġpars ed\",\"Ġmamm oth\",\"ĠCur ious\",\"g ob\",\"ĠFitz patrick\",\"ĠEm il\",\"im ov\",\"........ .....\",\"ĠB enny\",\"Second ly\",\"Ġheart y\",\"Ġcons on\",\"st ained\",\"Ġgal actic\",\"cl ave\",\"Ġplummet ed\",\"Ġp ests\",\"Ġsw at\",\"Ġrefer rals\",\"ĠLion el\",\"h oly\",\"Ġunder dog\",\"ĠSl ater\",\"ĠProv ide\",\"ĠAm ar\",\"ress or\",\"å Į\",\"ong a\",\"Ġtim id\",\"Ġp iety\",\"ĠD ek\",\"Ġsur ging\",\"az o\",\"Ġ6 10\",\"Ġdes ks\",\"ĠSp okane\",\"ĠAn field\",\"Ġwars hips\",\"ĠCob ra\",\"Ġar ming\",\"clus ively\",\"ĠBad ge\",\"ag ascar\",\"ĠPR ESS\",\"ĠMcK enzie\",\"ĠFer dinand\",\"burn ing\",\"Af ee\",\"Ġtyr ann\",\"ĠI w\",\"ĠBo one\",\"100 7\",\"ĠRe pt\",\"Ċ Âł\",\"Ġcar avan\",\"ĠD ill\",\"ĠBundes liga\",\"Ch uck\",\"Ġheal er\",\"ãĥ¼ãĥ Ĩ\",\"ĠH obby\",\"Ġneg ate\",\"Ġcrit iques\",\"section al\",\"mop olitan\",\"Ġd x\",\"Ġouts ourcing\",\"ĠC ipher\",\"t ap\",\"Sh arp\",\"Ġup beat\",\"Ġhang ar\",\"Ġcru ising\",\"ĠNi agara\",\"Ġ3 42\",\"ill us\",\"ĠS v\",\"Ġsubt itles\",\"Ġsqu ared\",\"Ġbook store\",\"Ġrevolution aries\",\"ĠCarl ton\",\"ab al\",\"Ut ah\",\"Ġdesp ise\",\"ĠU M\",\"cons ider\",\"aid o\",\"Ġc arts\",\"ĠT urtles\",\"Tr aining\",\"Ġhonor ary\",\"Â ¢\",\"Ġtri angles\",\"4 22\",\"Ġreprint ed\",\"Ġgrace ful\",\"ĠMong olia\",\"Ġdisrupt ions\",\"ĠB oh\",\"Ġ3 49\",\"Ġdr ains\",\"Ġcons ulate\",\"Ġb ends\",\"Ġm afia\",\"ur on\",\"ĠF ulton\",\"m isc\",\"Ġren al\",\"Ġin action\",\"ck ing\",\"Ġphot ons\",\"Ġbru ised\",\"ĠC odes\",\"og i\",\"Ġn ests\",\"ĠLove ly\",\"ĠLib re\",\"ĠD aryl\",\"Ġ# ##\",\"S ys\",\". ,\\\"\",\"Ġfree zes\",\"est ablishment\",\"and owski\",\"Ġcum bers\",\"ĠSt arg\",\"ĠBom bs\",\"Ġleg ions\",\"Ġhand writing\",\"Ġgr un\",\"ĠC ah\",\"sequ ent\",\"Ġm oth\",\"ĠMS M\",\"Ins ert\",\"F if\",\"Ġmot el\",\"Ġdex ter\",\"ĠB ild\",\"hearted ly\",\"Ġpro pe\",\"ĠText ure\",\"ĠJ unction\",\"ynt hesis\",\"oc ard\",\"ĠVer a\",\"ĠBar th\",\"ĠÎ¼ g\",\"Ġl ashed\",\"Ġ35 1\",\"ĠZ amb\",\"ĠSt aples\",\"ĠCort ex\",\"ĠCork er\",\"Ġcontinu um\",\"ĠWR ITE\",\"unt a\",\"rid or\",\"Ġde ems\",\"0 33\",\"ĠG OLD\",\"p as\",\"Ġrep ressive\",\"ãĥĨ ãĤ£\",\"Ġbaff led\",\"Sc ar\",\"Ġc rave\",\"Ġ ______\",\"Ġentrepreneurs hip\",\"ĠDirector ate\",\"Ġ' [\",\"Ġv ines\",\"Ġasc ended\",\"ĠGR OUP\",\"ĠGood bye\",\"Ġdo gged\",\"ãĥ´ ãĤ¡\",\"Man ufact\",\"Ġunimagin able\",\"ri ots\",\"ier rez\",\"Ġrel ativity\",\"ĠCraft ing\",\"ra ught\",\"ud en\",\"c ookie\",\"Ġassass ins\",\"Ġdissatisf ied\",\"ac ci\",\"Ġcondu it\",\"Sp read\",\"ĠR ican\",\"n ice\",\"izz le\",\"Ġsc ares\",\"ĠWH Y\",\"ph ans\",\"5 35\",\"Ġprot racted\",\"ĠKrist en\",\"5 36\",\"ĠSc rib\",\"ĠNe h\",\"Ġtwent ies\",\"Ġpredic ament\",\"Ġhandc uffs\",\"Ġfruit ful\",\"ĠU L\",\"ĠLud wig\",\"Ġatt est\",\"ĠBre aker\",\"Ġbi ologically\",\"ĠDeal er\",\"Ġrenov ations\",\"f w\",\"ess en\",\"Al ice\",\"ĠHen ri\",\"Ġun ilaterally\",\"ĠS idd\",\"h ai\",\"ĠSt retch\",\"S ales\",\"Ġcumbers ome\",\"ĠJ avier\",\"Ġtrend y\",\"Ġrot ting\",\"ĠChall enges\",\"Ġscra ps\",\"Ġfac ets\",\"ĠVer onica\",\"ĠVer ge\",\"ĠS ana\",\"Al ien\",\"ĠR ih\",\"Ġrad ial\",\"ect ar\",\"Ġ6 30\",\"cl i\",\"Mar ie\",\"Ġwild fire\",\"ĠCat o\",\"h ander\",\"Ġwait ress\",\"Ġch ops\",\"ĠS ECTION\",\"Ġblunt ly\",\"ĠCat alog\",\"n ian\",\"stud y\",\"Ġpat rolling\",\"ĠT enth\",\"nex us\",\"ĠN ON\",\"op sy\",\"Ġsc athing\",\"s ie\",\"Ġdeterior ated\",\"V B\",\"Naz is\",\"Ġdep ictions\",\"Ġauthent icated\",\"ĠCon ce\",\"k rit\",\"Ġpromul g\",\"ĠL ONG\",\"U FC\",\"ĠVis itors\",\"ĠRec all\",\"Ġrehab ilit\",\"ĠSL I\",\"Ġglac ier\",\"ĠB ite\",\"Ġ50 3\",\"Ġvom it\",\"Ġfer mented\",\"ĠKh alid\",\"Ġgrad ed\",\"ĠMag icka\",\"ĠIch igo\",\"power ful\",\"ic ators\",\"75 3\",\"Ġsh rew\",\"Ġ35 6\",\"Ġlegal izing\",\"Ġall otted\",\"ĠArch demon\",\"ith ing\",\"igg urat\",\"V OL\",\"Le od\",\"Ġo ily\",\"Ġindu cing\",\"Ġamy gdala\",\"Ġadm ins\",\"ĠAcqu isition\",\"C AN\",\"Ġsche matic\",\"Ġmo an\",\"ĠCamer oon\",\"Ġt ink\",\"Ġmer ry\",\"Ġbutter flies\",\"ĠGo ff\",\"Ġworks pace\",\"ĠCor ona\",\"Ġj avascript\",\"ĠD olphin\",\"ĠCant or\",\"4 64\",\"to e\",\"AP S\",\"ĠAg ing\",\"Ġpadd ed\",\"ĠZ heng\",\"ĠHe ld\",\"Ġest ranged\",\"Ġ7 70\",\". }\",\"ĠDun ham\",\"Ġsm okes\",\"Ġcap itals\",\"und ai\",\"Sh in\",\"ĠFound ing\",\"Ġent itle\",\"Ġcenter piece\",\"D iscover\",\"Ġthere to\",\"al ert\",\"ĠN ou\",\"ĠAnaly st\",\"l c\",\"F H\",\"FI ELD\",\"ĠP OV\",\"gr ay\",\"Ġar cs\",\"ĠH OT\",\"Ġr s\",\"Ġoblig atory\",\"ĠArchitect s\",\"ĠS ven\",\"ĠF EC\",\"0 200\",\"Christ mas\",\"ĠAlban ia\",\"rat om\",\"58 7\",\"Ġhard ships\",\"Ġaut os\",\"ĠCharg es\",\"Ġap es\",\"Ġ3 76\",\"wal let\",\"Ġintox ication\",\"Ġgobl in\",\"Ġ5 70\",\"++++++++ ++++++++\",\"ĠYel p\",\"ĠMag netic\",\"ĠBr iggs\",\"R ail\",\"Ġspawn s\",\"ĠW iggins\",\"Ġshowc ased\",\"Ġres orted\",\"ub en\",\"Ġwh ipping\",\"Ġim itate\",\"Ġdigest ion\",\"ĠUS PS\",\"ĠG est\",\"Ġye a\",\"ĠT ight\",\"ind al\",\"ic as\",\"` .\",\"C AST\",\"'' ;\",\"ĠF et\",\"opath ic\",\"In valid\",\"Ġregrett ed\",\"Ġbro ccoli\",\"ĠSc ores\",\"e ve\",\"Ġpost ings\",\"Ġaccum ulating\",\"Ġneed less\",\"elf th\",\"Ġmay ors\",\"Ġsc rib\",\"Ġanecd otes\",\"Ġbot ched\",\"ĠRib bon\",\"ĠConstant ine\",\"i uses\",\"ess es\",\"Ġdev ise\",\"Comp ared\",\"Ġp udding\",\"Ġg arg\",\"Ġev oke\",\"79 7\",\"Ġdet ox\",\"9 09\",\"ĠPie ces\",\"ĠMcC artney\",\"Ġmet ast\",\"ĠK rypt\",\"P OR\",\"Ġt ending\",\"ĠMerch ants\",\"Pro of\",\"ĠV arg\",\"ĠPort able\",\"ãĥ¼ãĥĨ ãĤ£\",\"B rain\",\"25 00\",\"Ġfol iage\",\"Ø ¹\",\"Ġment ors\",\"ĠA ires\",\"Ġminimal ist\",\"Ġing ested\",\"ĠTro jan\",\"ĠQ ian\",\"inv olved\",\"0 27\",\"Ġer oded\",\"RA FT\",\"Ġbl urry\",\"M ob\",\"Ġbuff et\",\"ĠFn atic\",\"ae a\",\"KN OWN\",\"ĠIn it\",\"s afety\",\"en um\",\"ACT ION\",\"ĠCrus her\",\"ĠD ates\",\"Ġ ................\",\"c alling\",\"ak ov\",\"Ġvent ured\",\"Ġ5 55\",\"au ga\",\"H art\",\"ĠA ero\",\"M AC\",\"Ġthin ly\",\"Ġar ra\",\"ST ATE\",\"ild e\",\"ĠJac qu\",\"ĠFem ales\",\"Ġthe orem\",\"Ġ3 46\",\"Ġsmart est\",\"ĠPU BLIC\",\"ĠK ron\",\"ĠB its\",\"ĠV essel\",\"ĠTele phone\",\"Ġdec ap\",\"Ġadj unct\",\"ĠS EN\",\"mer ga\",\"Ġred acted\",\"Ġpre historic\",\"Ġexplan atory\",\"ĠRun s\",\"ĠUtt ar\",\"ĠM anny\",\"ĠAUTH OR\",\"ĠUnle ashed\",\"ĠBow ling\",\"be ans\",\"79 3\",\"Ġunivers es\",\"Ġsens it\",\"ĠK ung\",\"re peat\",\"ctr l\",\"Ġp aced\",\"Ġfull er\",\"Cl ock\",\"Ġrec omb\",\"ĠF aul\",\"ĠB unker\",\"Ġpool ed\",\"Ġan a\",\"ĠM outh\",\"LL OW\",\"hum ane\",\"Ġbull do\",\"ĠMicha els\",\"f am\",\"Ġwreck ed\",\"Ġport rays\",\"ĠWh ale\",\"ĠH es\",\"Ġguess es\",\"ĠBrow se\",\"ĠL APD\",\"Ġconsequ ential\",\"ĠInn ocent\",\"ĠD RAG\",\"Ġtrans gress\",\"ĠO aks\",\"Ġtri via\",\"ĠRes on\",\"ĠA DS\",\"-- +\",\"ĠT oll\",\"Ġgrasp ing\",\"ĠTHE M\",\"ĠT ags\",\"ĠCon clusion\",\"Ġpract icable\",\"Ġho op\",\"Ġunintention ally\",\"Ġign ite\",\"ĠM ov\",\"ur ized\",\"le hem\",\"Ter min\",\"Ġcolour ful\",\"ĠLin ear\",\"ĠEll ie\",\"G y\",\"Ġman power\",\"Ġj s\",\"Ġem oji\",\"ĠSHAR ES\",\"_ .\",\"0000 7\",\"Ġsophistic ation\",\"Ġunders core\",\"Ġpract ise\",\"Ġbl ob\",\"op ens\",\"Uk raine\",\"Ke eping\",\"Y C\",\"J R\",\"ult imate\",\"Cl aim\",\"Ġautom obiles\",\"99 3\",\"ste el\",\"Ġpart ing\",\"ĠL ank\",\"... ?\",\"Ġ38 5\",\"Ġremem brance\",\"Ġe ased\",\"Ġcov ari\",\"ĠS ind\",\"Effect ive\",\"Ġdisse mination\",\"ĠMo ose\",\"ĠCl apper\",\"br ates\",\"App ly\",\"Ġinv is\",\"Ġwors ened\",\"âĢĶ -\",\"Ġlegisl ator\",\"ĠL ol\",\"ĠRow e\",\"Ġdealers hip\",\"um ar\",\"id ences\",\"Ġinvestig ates\",\"Ġc ascade\",\"Ġbid der\",\"ĠB EN\",\"Iron ically\",\"Ġpres iding\",\"Ġd ing\",\"Ġcontrad icted\",\"Ġshut s\",\"ĠF IX\",\"Ġ3 66\",\"Dist rict\",\"Ġsin ful\",\"ĠChar isma\",\"o ops\",\"Ġtot ality\",\"Ġrest itution\",\"ĠOpt imus\",\"ĠD ah\",\"Ġcl ueless\",\"urn ed\",\"Ġnut rit\",\"Ġland owners\",\"Ġfl ushed\",\"Ġbroad en\",\"m ie\",\"Ġprint ln\",\"Ġn ig\",\"ĠCorp us\",\"J en\",\"Ġprot o\",\"ĠWik imedia\",\"ĠPal o\",\"C OR\",\"Ġstory lines\",\"Ġevangel icals\",\"ĠDar rell\",\"Ġrot or\",\"ĠH W\",\"sk illed\",\"ery l\",\"Ġbe gg\",\"ĠBl umenthal\",\"Ġwe aving\",\"Ġdown wards\",\"ĠJack et\",\"ĠANG EL\",\"Te chnology\",\"Ġes oteric\",\"alde hyde\",\"Ġfur iously\",\"Ġforeign er\",\"We ak\",\"CH O\",\"ĠH ound\",\"Exper ience\",\"ĠPlay station\",\"ĠM IA\",\"ĠU ng\",\"cl oth\",\"ag all\",\"Ġcal ming\",\"iz ens\",\"St ruct\",\"ĠW itches\",\"ĠCeleb ration\",\"Ġ........ ......\",\"pt roller\",\"ĠTC U\",\"Ġb unny\",\"ãĥ į\",\"ut orial\",\"Ġup scale\",\"ĠSt a\",\"ĠCol ossus\",\"Ġchlor ide\",\"ĠZ ac\",\"ĠRe asons\",\"ĠBrook ings\",\"ĠWH ITE\",\"][ /\",\"ĠL ose\",\"9 05\",\"Ġunders ide\",\"ern els\",\"Ġv ape\",\"do zen\",\"upp et\",\"ĠST OP\",\"mat ical\",\"ĠStat ements\",\"hed dar\",\"P AC\",\"Custom er\",\"Ġmem os\",\"ĠP J\",\"end ars\",\"ĠLim its\",\"l augh\",\"Ġstabil ized\",\"ĠALE C\",\"Y A\",\"Up grade\",\"al am\",\"Ġtechn o\",\"Ġan ew\",\"fore seen\",\"Ġcolleg iate\",\"ĠPy ro\",\"ĠD ism\",\"Ġfront line\",\"Ġammon ia\",\"I U\",\"Qu ite\",\"John ny\",\"ass in\",\"G OP\",\"ĠSt yles\",\"ĠSovere ign\",\"acter ial\",\"5 49\",\"ĠR IP\",\"ĠL ists\",\"Ġ3 64\",\"ĠRece p\",\"s ocket\",\"ĠByr d\",\"ĠCand le\",\"An cient\",\"Ġappell ant\",\"en forcement\",\"ace a\",\"ans ki\",\"Ġold s\",\"88 6\",\"Ġsl urs\",\"Ġem pires\",\"Ġbuck le\",\"Ġalien ation\",\"ĠAber deen\",\"Ġunic orn\",\"Ġoverr iding\",\"ĠL X\",\"pp a\",\"Ġdesp ised\",\"ĠB ugs\",\"ĠB ST\",\"S outhern\",\"5 33\",\"Ġhall mark\",\"ĠPost er\",\"Ġstem med\",\"Ġprincip als\",\"ĠT ECH\",\"ĠSand wich\",\"It aly\",\"Ġche esy\",\"ĠSet TextColor\",\"ĠProt ective\",\"ĠC ohn\",\"J O\",\"apt op\",\"Re ason\",\"Lead er\",\"ĠUnder stand\",\"ĠFr idays\",\"ĠContin uous\",\"Ġcl ipping\",\"ĠR ye\",\"Ġber th\",\"tim er\",\"ann is\",\"re act\",\"Ġbuff alo\",\"ĠPar as\",\"Ġ6 55\",\"Ġpres ided\",\"ĠSun rise\",\"Ġve ts\",\"Ġcl oves\",\"ĠMcC ull\",\"Stre ngth\",\"G AN\",\"Ġill iter\",\"ĠPric ing\",\"l Ã©\",\"Ġresist or\",\"Ġbr un\",\"ĠSuff olk\",\"Ñ ĭ\",\"ĠL iver\",\"Re leased\",\"Ġwhat s\",\"8 60\",\"ĠMe asures\",\"Ġden ouncing\",\"ĠRy zen\",\"Ġsou ven\",\"Ġcareg ivers\",\"ch ini\",\"ĠScar lett\",\"Ġt rough\",\"Cong ratulations\",\"Ġtax is\",\"ĠTrad ition\",\"j it\",\"Ġtable top\",\"Ġhither to\",\"Ġdis information\",\"off ensive\",\"h ra\",\"ĠDISTR ICT\",\"Ġcompl icate\",\"chen ko\",\"ĠRecon struction\",\"Ġpalp able\",\"Ġa usp\",\"Ġ4 28\",\"Ġshowc ases\",\"ĠPublic ation\",\"know ledge\",\"inn on\",\"4 19\",\"Ġretri eval\",\"and ers\",\"Ġref ute\",\"Ġinqu ired\",\"g ur\",\"Ġneg ativity\",\"Ġcons erve\",\"Ġafter life\",\"Ġpres upp\",\"ĠGill espie\",\"Ġm t\",\"ĠD N\",\"T ap\",\"Ġper pend\",\"ĠS my\",\"does n\",\"Ġsp illing\",\"Ġhyp ers\",\"K ate\",\"Â® ,\",\"ke pt\",\"ĠP owered\",\"Ġj a\",\"ĠK lux\",\"ard e\",\"ab an\",\"Ġ4 44\",\"Ġflatt ened\",\"ĠImprove ments\",\"urg a\",\"ĠK und\",\"Ġins cribed\",\"Ġfac ult\",\"Ġunpre pared\",\"ĠCons umers\",\"Ġsatisf ies\",\"Ġpul monary\",\"Ġinf iltration\",\"Ġex ternally\",\"Ġcongrat ulations\",\"ag han\",\"Ġair liner\",\"Ġfl ung\",\"Ġfly ers\",\"G D\",\"Ġsnipp ets\",\"Ġrec ursive\",\"Ġmaster ing\",\"L ex\",\"Ġovert ly\",\"v g\",\"Ġluck ily\",\"Ġenc ro\",\"ĠLanc et\",\"ĠAbyss al\",\"function al\",\"Ġs ow\",\"Ġsqu id\",\"Ġnar ration\",\"Ġn aughty\",\"ĠHon our\",\"ĠSpart ans\",\"Ġsh atter\",\"ĠTac oma\",\"ĠCal ories\",\"ĠR aces\",\"Sub mit\",\"Ġpurpose fully\",\"w av\",\"ĠY ok\",\"F est\",\"ĠG err\",\"Met ro\",\"Ġit iner\",\"f amous\",\"Ġ\\\" {\",\"in line\",\"was her\",\"Iss ue\",\"ĠCL IENT\",\"oz o\",\"Vers ions\",\"7 25\",\"ĠGl ock\",\"Ġshield ed\",\"ĠPC R\",\"ENC Y\",\"ĠWe ld\",\"ĠSim pl\",\"Ġredirect ed\",\"ĠK ham\",\"Ġ( >\",\"Ġlab ou\",\"Ġdi apers\",\"ss l\",\"Ġcell ar\",\"organ isms\",\"ore sc\",\"ĠBer ks\",\"did n\",\"Sh ipping\",\"C hest\",\"Ġund one\",\"Ġmillion aire\",\"Ġc ords\",\"ĠYoung er\",\"appropri ately\",\"Ġsequ els\",\"u ve\",\"ant icipated\",\"Ġle wd\",\"ĠSh irt\",\"ĠDmit ry\",\"V eter\",\"Ġsl aying\",\"ĠY ar\",\"Ġcompl ication\",\"I owa\",\"ĠEric a\",\"ĠBL M\",\"g irlfriend\",\"b odied\",\"6 26\",\"19 63\",\"Ġintermedi ary\",\"Ġcons olation\",\"M ask\",\"ĠSi em\",\"ow an\",\"Beg inning\",\"Ġfix me\",\"Ġculmin ated\",\"Ġcon duc\",\"ĠVolunte er\",\"Ġpos itional\",\"Ġgre ets\",\"ĠDefin itions\",\"Ġthink er\",\"Ġingen uity\",\"Ġfresh men\",\"ĠMom ents\",\"Ġ35 7\",\"ate urs\",\"ĠFed Ex\",\"s g\",\"69 4\",\"Ġdwind ling\",\"ĠBO X\",\"sel age\",\"Ġt mp\",\"Ġst en\",\"ĠS ut\",\"Ġneighbourhood s\",\"Ġclass mate\",\"f ledged\",\"Ġleft ists\",\"Ġclim ates\",\"ATH ER\",\"ĠScy the\",\"ul iffe\",\"Ġs ag\",\"Ġho pped\",\"ĠF t\",\"ĠE ck\",\"ĠC K\",\"ĠDo omsday\",\"k ids\",\"Ġgas ped\",\"Ġmon iker\",\"ĠL od\",\"ĠC FL\",\"t ions\",\"r ums\",\"fol ios\",\"Ġm d\",\"Ġunc anny\",\"Ġtrans ports\",\"ĠLab rador\",\"Ġrail ways\",\"Ġappl iance\",\"ĠCTR L\",\"æ Ģ\",\"Pop ulation\",\"ĠConfeder acy\",\"Ġunb earable\",\"Ġdors al\",\"ĠIn form\",\"op ted\",\"ĠK ILL\",\"Mar x\",\"Ġhypoc ritical\",\"q us\",\"ĠN umerous\",\"ĠGeorg ian\",\"ĠAmbro se\",\"ĠL och\",\"Ġgu bernatorial\",\"ĠX eon\",\"ĠSupp orts\",\"ens er\",\"ee ly\",\"ĠAven ger\",\"19 65\",\"Ar my\",\"Ġju xtap\",\"Ġcho pping\",\"ĠSpl ash\",\"ĠS ustainable\",\"ĠFin ch\",\"Ġ18 61\",\"ict ive\",\"at meal\",\"ĠG ohan\",\"Ġlights aber\",\"ĠG PA\",\"ug u\",\"ĠRE PL\",\"vari able\",\"Ġher pes\",\"Ġdesert s\",\"ac iously\",\"Ġsitu ational\",\"week ly\",\"ob l\",\"Ġtext ile\",\"ĠCorn wall\",\"Ġcontrace ptives\",\"ĠA ke\",\"] -\",\"ä¹ ĭ\",\": ,\",\"ĠW em\",\"ĠB ihar\",\"Ġ' .\",\"Ġbe re\",\"Ġanal ogue\",\"ĠCook ies\",\"Ġtake off\",\"Whe el\",\"Ġmaj estic\",\"Ġcomm uting\",\"0 23\",\"ĠCor pse\",\"ass ment\",\"min i\",\"Ġgor illa\",\"ĠAl as\",\"ere e\",\"Ġacquaint ances\",\"ĠAd vantage\",\"Ġspirit ually\",\"Ġey ed\",\"pm wiki\",\"ĠE nder\",\"Ġtrans lucent\",\"Ġnight time\",\"ĠIM AGES\",\"5 45\",\"ĠK amp\",\"ĠFre ak\",\"Ġ ig\",\"Port land\",\"4 32\",\"ĠM ata\",\"Ġmar ines\",\"Ġh ors\",\"ater asu\",\"ĠAtt ribution\",\"Ġ-------- -\",\"Ġk ins\",\"ĠBEL OW\",\"++ +\",\"Ġre eling\",\"ol ed\",\"Ġcl utter\",\"ĠRel ative\",\"Ġ4 27\",\"B US\",\"Ġa vert\",\"ĠChe ong\",\"ĠA ble\",\"ĠPry or\",\"Develop er\",\"Ġen cyclopedia\",\"ĠUSA F\",\"ĠG arry\",\"Sp ain\",\"Bl ocks\",\"Ġexp osition\",\"ĠGamer Gate\",\"W OR\",\"Ġstockp ile\",\"Ġclot hed\",\"ĠT one\",\"ĠR ue\",\"t umblr\",\"Ġtreacher ous\",\"Ġf rying\",\"Ñ Į\",\"ĠS ph\",\"Ġrest raints\",\"Ġemb odies\",\"ĠG es\",\"S afety\",\"Ġnegoti ators\",\"min ing\",\"ĠAppalach ian\",\"L OS\",\"ĠJenn a\",\"Ġpass ers\",\"ç ĭ\",\"sn ap\",\"Ġshort en\",\"creat or\",\"Ġinn umerable\",\"uther land\",\"67 4\",\"ĠW OM\",\"ĠAs cend\",\"ĠArm ory\",\"ĠTrans action\",\"K ick\",\"Ġsuit case\",\"day Name\",\"Ġwaste ful\",\"mar riage\",\"ĠMcC abe\",\"ite ch\",\"ĠO ss\",\"Cl osure\",\"ĠTreasure r\",\"Ġindec ent\",\"ĠD ull\",\"Ġresid ences\",\"19 59\",\"ĠS ettlement\",\"Ham ilton\",\"Ġself ies\",\"ĠRank ing\",\"ĠBark ley\",\"ĠB ore\",\"ĠW CS\",\"ĠMar itime\",\"ĠH uh\",\"ĠForest ry\",\"Ġcultiv ating\",\"ĠBall ard\",\"Ġg arrison\",\"ĠSD L\",\"9 30\",\"Ġnas cent\",\"Ġirresist ible\",\"Ġaw fully\",\"\\\\/ \\\\/\",\"Ġequ ate\",\"Ġanthrop ology\",\"ĠSylv ia\",\"Ġintest ine\",\"Ġinnoc uous\",\"cess ive\",\"ag ra\",\"ĠMet roid\",\"G rant\",\"8 55\",\"ģ ĸ\",\"Ġ\\\" _\",\"ãĥĥ ãĥī\",\"Ġappra isal\",\"ĠFred dy\",\"04 6\",\"Ġ40 6\",\"Ġ18 30\",\"Ġd ocking\",\"St atic\",\"Ġp ont\",\"ĠVolt age\",\"ĠSt ead\",\"ĠMort gage\",\"ĠJon ah\",\"Y L\",\"CLASS IFIED\",\"Ġas bestos\",\"nik ov\",\"Ġcoll agen\",\"ĠOrb ital\",\"P ocket\",\"7 99\",\"Ġhy brids\",\"inc hes\",\"Ġinv oice\",\"und y\",\"Ġinequ alities\",\"T rend\",\"w ashed\",\"B ALL\",\"Ġluc id\",\"ĠComment ary\",\"Ġw itty\",\"Br andon\",\"Ġbru ising\",\"Ġ6 20\",\"es cent\",\"box ing\",\"P OL\",\"Ġ3 78\",\"R ect\",\"Ġlic ences\",\"ĠMcG ee\",\"p ressed\",\"D anny\",\"Ġj ammed\",\"ord inate\",\"Ġle th\",\"Ġdistingu ishes\",\"ĠYam aha\",\"IL S\",\"ĠH ume\",\"ĠC ategories\",\"Rober ts\",\"Ch art\",\"Ġbeet le\",\"ĠGra veyard\",\"Ġ($ )\",\"o ÄŁ\",\"Ġtw ilight\",\"are lla\",\"á ½\",\"Ġbooth s\",\"ĠH HS\",\"ĠFeld man\",\"Ġexcav ation\",\"Ġphilosoph ies\",\"at ography\",\"ĠGar age\",\"te chnology\",\"Ġunfor gettable\",\"Ġver ifying\",\"Ġsubord inates\",\"E ls\",\"Ġne b\",\"G aming\",\"EN A\",\"ĠAchieve ment\",\"it ters\",\"ĠG abe\",\"Ġd umps\",\"for cer\",\"Ġpo ignant\",\"ĠM BA\",\"ĠHe idi\",\"ime i\",\"Ġm ages\",\"Ġliber ate\",\"Ġcircum cised\",\"ĠMer maid\",\"ĠMat th\",\"t ogether\",\"ĠW ichita\",\"Ġstore front\",\"ĠAd in\",\"V II\",\"Four th\",\"Ġexplore rs\",\"W ER\",\"Not able\",\"Bro ok\",\"m ens\",\"F aith\",\"-------- -\",\"ĠJ ou\",\"¬ ¼\",\"Ġpine apple\",\"Ġam alg\",\"el n\",\"ark able\",\"ĠãĤµ ãĥ¼ãĥĨãĤ£\",\"ĠãĤµãĥ¼ãĥĨãĤ£ ãĥ¯ãĥ³\",\"Ġov arian\",\"ĠE choes\",\"Ġhairc ut\",\"Ġp av\",\"Ġch illed\",\"anas ia\",\"Ġsty led\",\"Ġd ab\",\"ni per\",\"Ġminister ial\",\"ĠD UP\",\"T an\",\"Ġsul ph\",\"ĠD eter\",\"ĠBo hem\",\"od an\",\"Ġeduc ator\",\"â ĵĺ\",\"sp ir\",\"Ch icken\",\"ĠE leanor\",\"Ġqu i\",\"Ġheav iest\",\"Ġgrasp ed\",\"U RA\",\"Ġcro oked\",\"Jess ica\",\"pro blem\",\"Ġpred etermined\",\"Ġman iac\",\"Ġbreath s\",\"ĠLauder dale\",\"Ġh obbies\",\"y z\",\"Cr ime\",\"Ġcharism a\",\"d L\",\"Ġle aping\",\"Ġk ittens\",\"Ang elo\",\"ĠJ ACK\",\"ĠSu zanne\",\"Ġhal ting\",\"ENT ION\",\"Ġswall owing\",\"ĠEarthqu ake\",\"Ġeight eenth\",\"ĠN IC\",\"ĠIN F\",\"ĠCons cious\",\"Ġparticular s\",\"circ le\",\"7 40\",\"Ġbene volent\",\"Ġ7 47\",\"Ġ4 90\",\"Ġr undown\",\"ĠVal erie\",\"ĠB UR\",\"Ġcivil isation\",\"ĠS chn\",\"W B\",\"ot ide\",\"intern ational\",\"Ġj ohn\",\"Ġ19 02\",\"Ġpe anuts\",\"Ġflav ored\",\"k us\",\"Ġro ared\",\"Ġcut off\",\"é £\",\"Ġorn ament\",\"Ġarchitect ures\",\"Ġ3 69\",\"ol or\",\"ĠWild e\",\"ĠC RC\",\"ĠAdjust ed\",\"Ġprov oking\",\"land ish\",\"Ġrational ity\",\"Ġjust ifies\",\"Ġdisp el\",\"Ġa meric\",\"ĠPol es\",\"Ø ©\",\"Ġen vis\",\"ĠD oodle\",\"ä½ ¿\",\"igs aw\",\"auld ron\",\"Techn ical\",\"T een\",\"up hem\",\"ĠX iang\",\"Ġdetract ors\",\"ĠZ i\",\"ĠJournal ists\",\"Ġconduc ive\",\"ĠVolunte ers\",\"Ġs d\",\"Know ing\",\"Ġtrans missions\",\"ĠPL AN\",\"ĠL IB\",\"Ġall uded\",\"Ġob e\",\"Ġd ope\",\"ĠGold stein\",\"Ġwavelength s\",\"ĠDest ination\",\"nd a\",\"ug i\",\"Ġattent ive\",\"ĠLe an\",\"ral tar\",\"Ġman g\",\"mb uds\",\"ak ings\",\"b ender\",\"Ġacc ol\",\"Ġcraw led\",\"N OW\",\"Min nesota\",\"Ġflour ished\",\"ĠZ up\",\"ĠSuper visor\",\"ĠOliv ier\",\"Ex cellent\",\"Ġwid en\",\"D one\",\"Ġw ig\",\"Ġmiscon ceptions\",\"Cor p\",\"W an\",\"Ġvener able\",\"ĠNot ably\",\"ĠKling on\",\"an imate\",\"Bo ost\",\"ĠS AY\",\"miss ing\",\"ibli ography\",\"mel on\",\"Ġpay day\",\"Ø ³\",\"bo le\",\"Ġve iled\",\"ĠAl phabet\",\"It alian\",\"Ġever lasting\",\"ĠR IS\",\"ĠC ree\",\"rom pt\",\"Ġh ating\",\"Ġgrin ning\",\"Ġge ographically\",\"OS H\",\"Ġwe eping\",\"ĠÂłĠÂłĠÂłĠÂł ĠÂłĠÂłĠÂłĠÂł\",\"Ġimpe cc\",\"Let ter\",\"Ġblo ated\",\"PL A\",\"ĠFe in\",\"Ġper sever\",\"Th under\",\"Ġa ur\",\"ĠR L\",\"Ġpit falls\",\"âĸ º\",\"Ġpredomin ant\",\"Ġ5 25\",\"7 18\",\"AP E\",\"7 14\",\"Ġfarm land\",\"ĠQ iao\",\"Ġv iolet\",\"ĠBah amas\",\"Ġinflic ting\",\"ĠE fficiency\",\"Ġhome brew\",\"Ġundert ook\",\"Ġcur ly\",\"ĠHard ing\",\"man ia\",\"59 6\",\"Ġtem pered\",\"Ġhar rowing\",\"ĠP ledge\",\"ĠFranken stein\",\"è ª\",\"M otion\",\"Ġpredict ably\",\"ĠExpl osion\",\"oc using\",\"er d\",\"col o\",\"FF ER\",\"Ġback field\",\"ĠV IDE\",\"ue bl\",\"N arr\",\"ĠArg ument\",\"Ġgen omic\",\"Ġbout ique\",\"Ġbatt ed\",\"ĠB inary\",\"Ġg amb\",\"ĠRh ythm\",\"67 3\",\"Ġa float\",\"ĠOlymp ia\",\"Y ING\",\"Ġend if\",\"is in\",\"Ġwin ters\",\"Ġsc attering\",\"I v\",\"D istance\",\"Ġtr u\",\"ĠCom fort\",\"Ġne xus\",\"Ġair flow\",\"ĠByz antine\",\"p ayers\",\"con i\",\"ĠB etsy\",\"D eal\",\"ĠN ug\",\"ĠContin ent\",\"red ibly\",\"Ġoptim izing\",\"al beit\",\"Ġec static\",\"ĠPro to\",\"ç ·\",\"iv ot\",\"âĸ Ħ\",\"em p\",\"rou nder\",\"Ġcl out\",\"ĠI ST\",\"66 3\",\"ĠDoll ars\",\"ĠD AC\",\"Ġsubsc ribed\",\"Ġrehears al\",\"Ġam ps\",\"ĠSh ang\",\"es m\",\"Ġspr inkle\",\"Ġassail ant\",\"ĠO o\",\"ĠCoin base\",\"T act\",\"Ġret ina\",\"Ġn uns\",\"R ON\",\"att o\",\"Ġj ug\",\"ĠSV G\",\"Ġb ikini\",\"ĠFI LE\",\"ĠFound ers\",\"ep ort\",\"ĠK P\",\"Ġrest ores\",\"ĠTh ick\",\"Ġash ore\",\"Ġappro vals\",\"R ender\",\"M AG\",\"G raham\",\"ĠCort ana\",\"ãĥ³ ãĤ¸\",\"ss h\",\"or ians\",\"ars ity\",\"ĠInsp ired\",\"u pper\",\"Ġsign alling\",\"Ġreb uke\",\"Ġfl ares\",\"Ġdownt ime\",\"Stud ies\",\"Ġstagn ation\",\"ĠSequ ence\",\"Ġgr unt\",\"Ġass ures\",\"ĠPL A\",\"59 2\",\"Ġintra ven\",\"d epend\",\"Sus an\",\"ĠManz iel\",\"Man ia\",\"Cont ract\",\"Ġsl ams\",\"Ġcult ured\",\"Ġcred itor\",\"L IST\",\"ĠH UM\",\"ĠChatt anooga\",\"serv ed\",\"Ġclo aked\",\"ĠF TP\",\"p owder\",\"ĠSt ella\",\"uct ive\",\"Ġcheap ly\",\"ĠMU CH\",\"ĠGalile o\",\"Ġsu ites\",\"spe ech\",\"Ġdeliber ations\",\"ĠCh ips\",\"« ĺ\",\"Bal ance\",\"ĠWyn ne\",\"ĠAk ron\",\"Ass et\",\"Ġhon oured\",\"Ġed ged\",\"Like wise\",\"anim ous\",\"ĠW age\",\"ĠEz ek\",\"ad vertisement\",\"ĠRT X\",\"ĠM AD\",\"Ġmigr ating\",\"ĠS QU\",\"Ġ4 75\",\"Ed ited\",\"Ġshorth and\",\"ĠBas ics\",\"Ġcro tch\",\"ĠEV EN\",\"Ġv m\",\"effic iency\",\"Ġcal ves\",\"ĠF rie\",\"ĠBrill iant\",\"Ġstri kers\",\"Ġrepent ance\",\"Ġarter ies\",\"r l\",\"B ed\",\"h ap\",\"Ġcrypt ography\",\"ĠSab res\",\"Ġ4 14\",\"vi ks\",\"ih ara\",\"aps es\",\"T alking\",\"Ġintertw ined\",\"Ġdoc ks\",\"Ġalle le\",\"ĠArt ifact\",\"ĠH IM\",\"t orn\",\"ç ķ\",\"Ġop acity\",\"ĠE ly\",\"os uke\",\"Ġn ipple\",\"Ġhand written\",\"ĠV K\",\"ĠChamber lain\",\"ĠLa os\",\"ig raph\",\"g row\",\"Ġtr illions\",\"Ġdescend ant\",\"ĠSail or\",\"as uring\",\"Ġce ilings\",\"ĠWare house\",\"f lying\",\"ĠGl ow\",\"Ġn ont\",\"Ġmiscar riage\",\"Ġrig s\",\"Ġmin istries\",\"Ġelabor ated\",\"Ġdel usional\",\"ĠHum ane\",\"Ġ3 79\",\"n ets\",\"Ġblack out\",\"add ers\",\"Ġn p\",\"ĠT ire\",\"ro sc\",\"Ġsub div\",\"Ġlink age\",\"Ġchron ological\",\"ĠHER O\",\"Ġres ettlement\",\"ĠVin yl\",\"Ġpast oral\",\"ĠMob il\",\"ĠBar bar\",\"Co oldown\",\"ĠF ritz\",\"c riminal\",\"re pe\",\"Ġbell ig\",\"ĠBre ed\",\"Ġ4 18\",\"Ġsem blance\",\"ij k\",\"Ġcur tail\",\"Ġclin ch\",\"cont ained\",\"ĠProm pt\",\"ast on\",\"Ġw i\",\"Ġpursu its\",\"5 15\",\"ĠGl oss\",\"Ġfl ips\",\"Ġcoup ons\",\"Ġcl oning\",\"ĠLike ly\",\"Rem oved\",\"ĠQu artz\",\"r ices\",\"ĠSpe ars\",\"Ġp ious\",\"Ġdep reciation\",\"ĠD are\",\"oun ces\",\"am az\",\"O nt\",\"Ġp innacle\",\"d ocker\",\"0 26\",\"ĠW yr\",\"ĠPro per\",\"Ë Ī\",\"n il\",\"By tes\",\"Ġseek er\",\"t rial\",\"Ġunf olds\",\"ĠMar se\",\"Ġextravag ant\",\"ĠSurviv ors\",\"RED ACTED\",\"ĠSpeed way\",\"ĠCra igslist\",\"sub mit\",\"ĠGener ations\",\"Ġup holding\",\"Ġblood stream\",\"ĠMiss ions\",\"ĠL awn\",\"Ġlim bo\",\"ene i\",\"H uh\",\"ĠWild cats\",\"pre p\",\"ĠMark us\",\"ĠFor bidden\",\"rit ic\",\"IN O\",\"Ġexhib iting\",\"requ ent\",\"ch uk\",\"Ġhabit ual\",\"ĠComp atibility\",\"Dr ag\",\"RIP T\",\"uj ah\",\"GR OUND\",\"Ġdelinqu ent\",\"Ġburn er\",\"Ġcontempor aries\",\"Ġgimm ick\",\"load s\",\"Ġno zzle\",\"p odcast\",\"ĠW ak\",\"ĠStat en\",\"ĠK uh\",\"ãģ ĵ\",\"inter rupted\",\"Ġinv incible\",\"ĠBurn ett\",\"cig arette\",\"ĠPeb ble\",\"ĠTem porary\",\"ĠMar ino\",\"58 2\",\"Ġwast eland\",\"ident ly\",\"T x\",\"Ġr ite\",\"ĠPan asonic\",\"ĠM iddles\",\"ĠHort on\",\"ae us\",\"Ġc uring\",\"Ġm ats\",\"Ġadj ourn\",\"Ġfears ome\",\"pe z\",\"bo ats\",\"Ġpro pell\",\"Ġconflic ted\",\"ĠAng er\",\"Ġinsurg ent\",\"K arl\",\"Ġco ales\",\"Ġsouth western\",\"Ġdis su\",\"ĠO vert\",\"******** ****\",\"Ġbox ed\",\"ĠBr une\",\"aa a\",\"Ġgard ening\",\"ĠEng el\",\"tr acks\",\"Ġpur ified\",\"Ġplace holder\",\"ĠL ikes\",\"Ġd an\",\"G ab\",\"Ġe ct\",\"ĠF aw\",\"ĠEl iot\",\"Ġ' ,\",\"otrop ic\",\"ĠRu in\",\"hed on\",\"Ġca ul\",\"Ġa ft\",\"ĠCad illac\",\"gh a\",\"ass ian\",\"ud eb\",\"ĠT ick\",\"Ġadjust s\",\"AR GET\",\"5 37\",\"isc he\",\"ant y\",\"ĠFried rich\",\"ĠBl izz\",\"ĠA OL\",\"Camp aign\",\"Ġmamm al\",\"ĠVe il\",\"ĠK ev\",\"ĠMaur it\",\"ĠDam ien\",\"N ation\",\"E astern\",\"Ġ{ :\",\"Ġ= ================================\",\"Ġstereotyp ical\",\"Ġatt ic\",\"ĠCy borg\",\"requ ire\",\"Ġaward ing\",\"ĠPap ua\",\"bt n\",\"b ent\",\"B oo\",\"Ġ( =\",\"ĠX ander\",\"ĠSomers et\",\"Ġcatch y\",\"Ġcert ify\",\"STR UCT\",\"Ġit al\",\"Ġt ides\",\"ĠBr ands\",\"G ray\",\"comp etitive\",\"Ġcur ator\",\"ĠD G\",\"omin ium\",\"ĠGM Os\",\"ci ating\",\"ĠCarm en\",\"ow ard\",\"Balt imore\",\"Ġr gb\",\"C u\",\"Ġwip es\",\"spe ll\",\"IT NESS\",\"Ġsummar izes\",\"ĠRe vis\",\"Ġwhistlebl owers\",\"ĠBre ach\",\"Ġcro chet\",\"k os\",\"ews ki\",\"Ġrep et\",\"Ġcrim son\",\"ĠKar achi\",\"read able\",\"dim ension\",\"ĠI gor\",\"ild ed\",\"ĠZ ed\",\"ĠKe ane\",\"ĠCos metic\",\"DE P\",\"Ġretreat ing\",\"ĠU A\",\"ens ical\",\"Ġd usk\",\"ĠDick ens\",\"Ġaren as\",\"ĠPass age\",\"level s\",\"Ġcur v\",\"P ope\",\"Ġch ores\",\"ĠEl ise\",\"ĠComp ass\",\"b ub\",\"Ġmamm alian\",\"ĠSans krit\",\"ĠAN C\",\"ĠCr ack\",\"Q ual\",\"L aun\",\"amp unk\",\"Ġlearn ers\",\"Ġglam orous\",\"Ġfur the\",\"erm ott\",\"c and\",\"Gener ic\",\"Ġnarr ated\",\"Ġdisorder ly\",\"ĠTrans actions\",\"ĠDet ention\",\"ĠR oku\",\"Ä į\",\"Ġunder statement\",\"ĠS aur\",\"ĠRodrig o\",\"ĠAS AP\",\"S in\",\"Ġre joice\",\"Method s\",\"Ġelectro de\",\"Ġworsh ipped\",\"Ġid i\",\"ĠPhys icians\",\"Ġpop up\",\"Ġde ft\",\"ĠRem oval\",\"ĠBu enos\",\"ver bs\",\"Ġfun k\",\"ush a\",\"rict ion\",\"ore a\",\"ĠBang alore\",\"ĠKen obi\",\"zz i\",\"Ġnorm ative\",\"Ġgobl ins\",\"Ġcaf es\",\"ĠUN CLASSIFIED\",\"ĠF ired\",\"S IGN\",\"Ġs clerosis\",\"ĠV oter\",\"ĠSon ny\",\"ĠExt end\",\"ĠEV s\",\"Ar senal\",\"Ġp si\",\"Ġwid est\",\"ĠT us\",\"Ġlo oms\",\"Ġjust ifying\",\"ĠGr anger\",\"è ¯\",\"Ref er\",\"58 3\",\"Ġflour ishing\",\"ab re\",\"Ġr ave\",\"ĠCont ra\",\"Ġ18 98\",\"Add s\",\"Ġf ul\",\"ĠCo oke\",\"some one\",\"= #\",\"67 1\",\"Ġy ak\",\"Ġar te\",\"ĠMis cellaneous\",\"ĠDet ection\",\"ĠCl ancy\",\"â ģ\",\"ass ies\",\"Ġval iant\",\"ĠFemin ist\",\"cor ruption\",\"V el\",\"P ear\",\"Ġsucc inct\",\"Ġquick est\",\"k w\",\"Ġsp itting\",\"ĠL ibraries\",\"åħ ī\",\"ant z\",\"D ad\",\"ĠSpec ifications\",\"rup ulous\",\"and r\",\"RES ULTS\",\"Ġsnow ball\",\"Ġpred is\",\"ĠB axter\",\"ĠNurs ing\",\"ĠCh aff\",\"s we\",\"Ġout age\",\"Ġnest ing\",\"Ġnotor iety\",\"tr igger\",\"on ite\",\"j on\",\"Ġf ou\",\"ook ed\",\"ĠCelebr ity\",\"re ality\",\"Ġfat ig\",\"Ġhug ging\",\"Ġbother s\",\"ĠPan zer\",\"ĠCh andra\",\"fig ured\",\"Ġvol ts\",\"ĠCloud s\",\"Ġfee ble\",\"ĠCur ve\",\"ĠAs us\",\"78 6\",\"abs or\",\"ĠV ICE\",\"ĠH ess\",\"Ġmanufact ures\",\"Ġgri zz\",\"ĠPower ful\",\"ac id\",\"Ġsub sections\",\"ĠKrug man\",\"ĠAl ps\",\"is u\",\"Ġsequ est\",\"ĠUlt ron\",\"ĠT inker\",\"ĠGo ose\",\"Ġmism atch\",\"Att orney\",\"Ġmorph ology\",\"ĠSix ers\",\"ut tered\",\"ĠE LECT\",\"gr an\",\"Rus sell\",\"ĠG SL\",\"Ġfort night\",\"Ġ. )\",\"Ġapost le\",\"pr one\",\"el ist\",\"Unt itled\",\"ĠIm plementation\",\"ist ors\",\"Ġtank er\",\"Ġpl ush\",\"Ġattend ants\",\"ĠT ik\",\"ĠGreen wich\",\"ĠY on\",\"ĠSP L\",\"cell s\",\"unt led\",\"S olution\",\"ĠQu Ã©\",\"Ġvac ated\",\"Ġupt ick\",\"ĠMer idian\",\"æ ĥ\",\"ĠDr ill\",\"9 25\",\"58 4\",\"Ġrenov ated\",\"ĠKub rick\",\"zy k\",\"Ġl ousy\",\"pp el\",\"ohyd rate\",\"ĠI zzy\",\"lesi astical\",\"CC C\",\"ĠAj ax\",\"Ġad apters\",\"ĠPetra eus\",\"Ġaffirm ation\",\"ĠST OR\",\"le ms\",\"ad oes\",\"ĠConstantin ople\",\"Ġp onies\",\"Ġl ighthouse\",\"Ġadherent s\",\"ĠBre es\",\"omorph ic\",\"Fight ing\",\"Ġpl aster\",\"ĠP VC\",\"ĠOb st\",\"Ġdear ly\",\"ĠTo oth\",\"icks on\",\"Ġsh aming\",\"P lex\",\"A gg\",\"ĠâĢ¦ \\\"\",\"Ġsub reddits\",\"Ġpige on\",\"ĠResident ial\",\"ĠPass ing\",\"Ġl um\",\"ĠP ension\",\"Ġpessim istic\",\"Ġ4 32\",\"z inski\",\"c ade\",\"0 75\",\"Ġapolog ised\",\"iy ah\",\"Put ting\",\"Ġgloom y\",\"ĠLy me\",\"=-=-=-=- =-=-=-=-\",\"ĠT ome\",\"ĠPsych iatric\",\"ĠH IT\",\"c ms\",\"ap olog\",\"Ġbreak er\",\"Ġdeep en\",\"Ġtheor ist\",\"ĠHigh lands\",\"Ġb aker\",\"Ġst aples\",\"Ġinterf ered\",\"ĠAb ortion\",\"jo ined\",\"ch u\",\"Ġform ulate\",\"Ġvacc inations\",\"Ġban ter\",\"phe us\",\"Ġoutfield er\",\"ĠM eter\",\"Ġ# ####\",\"Ġ18 95\",\"Ġnarrow ing\",\"ĠST ORY\",\"f p\",\"ĠC ST\",\"ign ore\",\"Ġproclaim ing\",\"ĠR U\",\"ĠB ALL\",\"yn a\",\"65 3\",\"Ġpos it\",\"P RE\",\"59 4\",\"ĠRegist rar\",\"ĠPil grim\",\"ic io\",\"Ġpre tt\",\"Ġlif eless\",\"Ġ__ _\",\"Ne igh\",\"ĠCh urches\",\"orn o\",\"Ġor cs\",\"Ġkind red\",\"ĠAud it\",\"Ġmillenn ial\",\"ĠPers ia\",\"g ravity\",\"ĠDis ability\",\"ĠD ARK\",\"W s\",\"od on\",\"Ġgrand daughter\",\"ĠBro oke\",\"ĠA DA\",\"ER A\",\"Ġpick ups\",\"ĠWil kinson\",\"ĠSh ards\",\"ĠN K\",\"Ġexp el\",\"ĠKis lyak\",\"Ġj argon\",\"Ġpolar ized\",\"ian e\",\"Pub lisher\",\"Ġreb utt\",\"Ġapprehens ion\",\"ĠK essler\",\"Ġpr ism\",\"F UL\",\"19 64\",\"ĠL oll\",\"ä ¿\",\"le thal\",\"Å Ł\",\"Ġg hetto\",\"Ġb oulder\",\"ĠSlow ly\",\"ĠOsc ars\",\"ĠInst ruction\",\"ĠUl tr\",\"ĠM oe\",\"N ich\",\"ĠP ATH\",\"( *\",\"ĠRE LEASE\",\"un ing\",\"rou se\",\"en eg\",\"Ġre imb\",\"ĠDet ected\",\"Do S\",\"Ġster ling\",\"Ġaggreg ation\",\"ĠLone ly\",\"ĠAtt end\",\"hig her\",\"Ġairst rike\",\"ks on\",\"SE LECT\",\"Ġdef lation\",\"ĠHer rera\",\"C ole\",\"rit ch\",\"Ġadvis able\",\"F ax\",\"Ġwork around\",\"Ġp id\",\"mort em\",\"ers en\",\"Ġtyp o\",\"Ġal um\",\"78 2\",\"ĠJam al\",\"script s\",\"Ġcapt ives\",\"ĠPres ence\",\"ĠLie berman\",\"angel o\",\"Ġalcohol ism\",\"ass i\",\"Ġrec ite\",\"Ġgap ing\",\"Ġbask ets\",\"ĠG ou\",\"Brow ser\",\"ne au\",\"Ġcorrect ive\",\"und a\",\"sc oring\",\"ĠX D\",\"Ġfil ament\",\"Ġdeep ening\",\"ĠStain less\",\"Int eger\",\"Ġbu ggy\",\"Ġten ancy\",\"ĠMub arak\",\"Ġt uple\",\"ĠD roid\",\"ĠS itting\",\"Ġforfe it\",\"ĠRasm ussen\",\"ixt ies\",\"es i\",\"ĠKim mel\",\"Ġmetic ulously\",\"Ġap opt\",\"ĠS eller\",\"08 8\",\"ec ake\",\"hem atically\",\"T N\",\"Ġmind less\",\"Ġdig s\",\"ĠAcc ord\",\"ons ense\",\"em ing\",\"br ace\",\"Ġe Book\",\"ĠDist ribut\",\"ĠInvest ments\",\"w t\",\"] ),\",\"beh avior\",\"56 3\",\"Ġbl inding\",\"ĠPro testers\",\"top ia\",\"Ġreb orn\",\"ĠKel vin\",\"ĠDo ver\",\"ĠD airy\",\"ĠOut s\",\"Ġ[ /\",\"Ï Ģ\",\"b p\",\"ĠVan ity\",\"ĠRec ap\",\"ĠHOU SE\",\"ĠF ACE\",\"Ġ4 22\",\"69 2\",\"ĠAnt ioch\",\"cook ed\",\"Ġcoll ide\",\"Ġa pr\",\"Ġsle eper\",\"ĠJar vis\",\"Ġalternative ly\",\"ĠLe aves\",\"ĠM aw\",\"Ġantiqu ity\",\"ĠAdin ida\",\"Ġab user\",\"PokÃ© mon\",\"Ġass orted\",\"ĠRev ision\",\"ĠP iano\",\"ĠG ideon\",\"O cean\",\"Ġsal on\",\"Ġbust ling\",\"ogn itive\",\"ĠRah man\",\"Ġwa iter\",\"Ġpres ets\",\"ĠO sh\",\"ĠG HC\",\"oper ator\",\"Ġrept iles\",\"Ġ4 13\",\"ĠG arr\",\"ĠCh ak\",\"Ġhas hes\",\"Ġfail ings\",\"Ġfolk lore\",\"Ġab l\",\"ĠC ena\",\"ĠMac Arthur\",\"ĠCOUR T\",\"Ġperipher y\",\"app ers\",\"Ġreck oned\",\"ĠInf lu\",\"ĠC ET\",\"Ġ3 72\",\"ĠDefin itive\",\"ass ault\",\"4 21\",\"Ġreservoir s\",\"Ġd ives\",\"ĠCo il\",\"DA Q\",\"Ġvivid ly\",\"ĠR J\",\"ĠBel lev\",\"Ġec lectic\",\"ĠShow down\",\"ĠK M\",\"ip ed\",\"reet ings\",\"ĠAs uka\",\"L iberal\",\"ĠÏ Ħ\",\"Ġbystand ers\",\"ĠGood win\",\"uk ong\",\"S it\",\"ĠT rem\",\"Ġcrim inally\",\"ĠCirc us\",\"ch rome\",\"88 7\",\"Ġnan op\",\"ĠOb i\",\"ĠL OW\",\"o gh\",\"ĠAuth ors\",\"ob yl\",\"Ur ban\",\"Ġt i\",\"ĠWe ir\",\"t rap\",\"ag y\",\"Ġparent heses\",\"Ġout numbered\",\"Ġcounter productive\",\"ĠTob ias\",\"ub is\",\"P arser\",\"ST AR\",\"Ġsyn aptic\",\"ĠG ears\",\"Ġh iber\",\"Ġdebunk ed\",\"Ġex alted\",\"aw atts\",\"H OU\",\"Ch urch\",\"ĠPix ie\",\"ĠU ri\",\"ĠForm ation\",\"ĠPred iction\",\"C EO\",\"Ġthro tt\",\"ĠBrit ann\",\"ĠMad agascar\",\"ë ĭ\",\"Ġbill boards\",\"ĠRPG s\",\"ĠBe es\",\"complete ly\",\"F IL\",\"Ġdoes nt\",\"ĠGreen berg\",\"re ys\",\"Ġsl ing\",\"Ġempt ied\",\"ĠPix ar\",\"ĠDh arma\",\"l uck\",\"ingu ished\",\"Ġend ot\",\"Ġbab ys\",\"05 9\",\"che st\",\"r ats\",\"Ġr idden\",\"Ġbeet les\",\"Ġillum inating\",\"Ġfict itious\",\"ĠProv incial\",\"Ġ7 68\",\"Ġshe pherd\",\"ĠR ender\",\"Ġ18 96\",\"C rew\",\"Ġmold ed\",\"ĠXia omi\",\"ĠSp iral\",\"Ġdel im\",\"Ġorgan ising\",\"Ġho ops\",\"ĠBe i\",\"z hen\",\"Ġfuck in\",\"Ġdec ad\",\"Ġun biased\",\"am my\",\"sw ing\",\"Ġsmugg led\",\"Ġk ios\",\"ĠP ERSON\",\"ĠInquis itor\",\"Ġsnow y\",\"Ġscrap ing\",\"ĠBurg ess\",\"P tr\",\"ag ame\",\"R W\",\"Ġdro id\",\"ĠL ys\",\"ĠCass andra\",\"Jac ob\",\"Ġ35 4\",\"Ġpast ure\",\"Ġfr anc\",\"ĠScot ch\",\"ĠEnd s\",\"ĠI GF\",\"def inition\",\"Ġhyster ical\",\"ĠBrown e\",\"77 1\",\"Ġmobil ization\",\"æ ķ\",\"iqu eness\",\"Th or\",\"Ġspear headed\",\"Ġembro iled\",\"Ġconject ure\",\"jud icial\",\"Ch oice\",\"Ġpaper back\",\"P ir\",\"Ġrec overs\",\"ĠSur ge\",\"ĠSh ogun\",\"ĠPed iatrics\",\"ãģ ł\",\"Ġsweep s\",\"ĠLabor atories\",\"ĠP acks\",\"al us\",\"add in\",\"Ġhead lights\",\"g ra\",\"Ev idence\",\"COL OR\",\"Ad min\",\"Ĭ ±\",\"Ġconco ct\",\"s ufficient\",\"Ġun marked\",\"Ġrich ness\",\"Ġdiss ertation\",\"Ġseason ing\",\"Ġg ib\",\"ĠM ages\",\"un ctions\",\"ĠN id\",\"che at\",\"ĠTM Z\",\"c itizens\",\"ĠCatholic ism\",\"n b\",\"Ġdisemb ark\",\"ĠPROG RAM\",\"a ques\",\"Ty ler\",\"Or g\",\"ĠSl ay\",\"ĠN ero\",\"ĠTown send\",\"IN TON\",\"te le\",\"Ġmes mer\",\"9 01\",\"Ġfire ball\",\"ev idence\",\"aff iliated\",\"ĠFrench man\",\"ĠAugust a\",\"0 21\",\"Ġs led\",\"Ġre used\",\"ĠImmun ity\",\"Ġwrest le\",\"assemb led\",\"Mar ia\",\"Ġgun shots\",\"ĠBarb ie\",\"Ġcannabin oids\",\"ĠTo ast\",\"ĠK inder\",\"IR D\",\"Ġre juven\",\"Ġg ore\",\"Ġrupt ure\",\"Ġbre aching\",\"ĠCart oon\",\"Ġ4 55\",\"ĠPale o\",\"6 14\",\"Ġspe ars\",\"ĠAm es\",\"ab us\",\"Mad ison\",\"GR OUP\",\"Ġab orted\",\"y ah\",\"Ġfel on\",\"Ġcaus ation\",\"Ġprep aid\",\"Ġp itted\",\"op lan\",\"ĠShel ley\",\"ĠRus so\",\"ĠP agan\",\"Ġwill fully\",\"ĠCan aver\",\"und rum\",\"ĠSal ary\",\"ĠAr paio\",\"read er\",\"ĠR ational\",\"ĠOver se\",\"ĠCa uses\",\"Ġ* .\",\"Ġw ob\",\"Ke ith\",\"ĠCons ent\",\"man ac\",\"77 3\",\"6 23\",\"Ġfate ful\",\"et imes\",\"Ġspir ited\",\"ĠD ys\",\"Ġhe gemony\",\"Ġboy cot\",\"ĠEn rique\",\"em outh\",\"Ġtim elines\",\"ĠSah ara\",\"ĠRel ax\",\"ĠQuin cy\",\"ĠLess ons\",\"ĠE QU\",\"SE A\",\"N K\",\"ĠCost co\",\"Incre ase\",\"Ġmotiv ating\",\"ĠCh ong\",\"am aru\",\"ĠDiv ide\",\"Ġped igree\",\"ĠTasman ia\",\"ĠPrel ude\",\"L as\",\"9 40\",\"57 4\",\"Ġch au\",\"ĠSp iegel\",\"un ic\",\"-- >\",\"ĠPhil ips\",\"ĠKaf ka\",\"Ġuphe aval\",\"Ġsent imental\",\"Ġsa x\",\"ĠAk ira\",\"ser ial\",\"Mat rix\",\"Ġelect ing\",\"Ġcomment er\",\"ĠNeb ula\",\"ple ts\",\"ĠNad u\",\"ĠAd ren\",\"Ġen shr\",\"ĠR AND\",\"fin ancial\",\"ĠCly de\",\"uther ford\",\"Ġsign age\",\"Ġde line\",\"Ġphosph ate\",\"rovers ial\",\"f ascist\",\"ĠV all\",\"ĠBeth lehem\",\"Ġfor s\",\"Ġeng lish\",\"S olid\",\"N ature\",\"Ġv a\",\"ĠGu ests\",\"Ġtant al\",\"Ġauto immune\",\";;;;;;;; ;;;;\",\"ĠTot ally\",\"ĠO v\",\"Ġdef ences\",\"ĠCoc onut\",\"Ġtranqu il\",\"Ġpl oy\",\"Ġflav ours\",\"ĠFl ask\",\"ãĤ¨ ãĥ«\",\"ĠWest on\",\"ĠVol vo\",\"8 70\",\"Ġmicro phones\",\"ver bal\",\"R PG\",\"Ġi ii\",\"; }\",\"0 28\",\"Ġhead lined\",\"Ġprim ed\",\"Ġho ard\",\"ĠSh ad\",\"ĠEN TER\",\"Ġtri angular\",\"Ġcap it\",\"l ik\",\"ĠAn cients\",\"Ġl ash\",\"Ġconv ol\",\"Ġcolon el\",\"en emy\",\"G ra\",\"Ġpub s\",\"ut ters\",\"Ġassign s\",\"ĠPen et\",\"ĠMon strous\",\"ĠBow en\",\"il ver\",\"H aunted\",\"ĠD ing\",\"start ed\",\"pl in\",\"Ġcontamin ants\",\"ĠDO E\",\"ff en\",\"ĠTechn ician\",\"R y\",\"Ġrob bers\",\"Ġhot line\",\"ĠGuard iola\",\"ĠKau fman\",\"row er\",\"ĠDres den\",\"ĠAl pine\",\"E lf\",\"Ġf mt\",\"ĠS ard\",\"urs es\",\"g pu\",\"Un ix\",\"Ġunequiv ocally\",\"ĠCitizens hip\",\"qu ad\",\"m ire\",\"ĠS weeney\",\"B attery\",\"6 15\",\"Ġpanc akes\",\"Ġo ats\",\"M aps\",\"ĠCont rast\",\"mbuds man\",\"ĠE PS\",\"Ġsub committee\",\"Ġsour cing\",\"Ġs izing\",\"ĠBuff er\",\"ĠMand atory\",\"Ġmoder ates\",\"ĠPattern s\",\"ĠCh ocobo\",\"ĠZ an\",\"ĠSTAT ES\",\"ĠJud ging\",\"ĠIn her\",\"* :\",\"Ġb il\",\"ĠY en\",\"Ġexh ilar\",\"oll ower\",\"z ers\",\"Ġsn ug\",\"max imum\",\"Ġdesp icable\",\"ĠP ACK\",\"ĠAn nex\",\"Ġsarcast ic\",\"Ġlate x\",\"Ġt amp\",\"ĠS ao\",\"b ah\",\"ĠRe verend\",\"ĠChin atown\",\"ĠA UT\",\"d ocumented\",\"ĠGA BA\",\"ĠCan aan\",\"ĠÙ ħ\",\"Ġgovern s\",\"pre v\",\"E sc\",\"ĠEst imates\",\"OS P\",\"Ġendeav our\",\"ĠCl osing\",\"omet ime\",\"every one\",\"Ġwor sen\",\"Ġsc anners\",\"Ġdev iations\",\"ĠRobot ics\",\"ĠCom pton\",\"Ġsorce rer\",\"Ġend ogenous\",\"Ġem ulation\",\"ĠPier cing\",\"ĠA ph\",\"ĠS ocket\",\"Ġb ould\",\"ĠO U\",\"ĠBorder lands\",\"Ġ18 63\",\"G ordon\",\"ĠW TO\",\"Ġrestrict s\",\"Ġmosa ic\",\"Ġmel odies\",\"ç Ħ\",\"T ar\",\"Ġdis son\",\"ĠProv ides\",\"Ġ ......\",\"b ek\",\"F IX\",\"Ġbro om\",\"ans hip\",\"Do ctors\",\"Ġner ds\",\"ĠReg ions\",\"na issance\",\"Ġmet e\",\"Ġcre pt\",\"pl ings\",\"Ġgirlfriend s\",\"kn it\",\"ig ent\",\"ow e\",\"Ġus hered\",\"ĠB az\",\"M obil\",\"4 34\",\"ĠPres ents\",\"orig in\",\"Ġins omnia\",\"ĠA ux\",\"4 39\",\"ĠCh ili\",\"irs ch\",\"G AME\",\"Ġgest ation\",\"alg ia\",\"rom ising\",\"$ ,\",\"c row\",\"ĠIn spection\",\"at omic\",\"Rel ations\",\"J OHN\",\"rom an\",\"ĠClock work\",\"ĠBak r\",\"m one\",\"M ET\",\"Ġthirst y\",\"Ġb c\",\"Ġfacult ies\",\"R um\",\"Ġnu ance\",\"ĠD arius\",\"ple ting\",\"fter s\",\"etch up\",\"Reg istration\",\"ĠK E\",\"R ah\",\"Ġpref erential\",\"ĠL ash\",\"ĠH H\",\"Val id\",\"ĠN AV\",\"Ġstar ve\",\"ĠG ong\",\"z ynski\",\"ĠAct ress\",\"Ġw ik\",\"Ġun accompanied\",\"lv l\",\"Br ide\",\"AD S\",\"ĠCommand o\",\"ĠVaugh n\",\"Wal let\",\"Ġho pping\",\"ĠV ie\",\"Ġcave ats\",\"Ġal as\",\"if led\",\"ab use\",\"66 1\",\"Ġib n\",\"Ġg ul\",\"Ġrob bing\",\"t il\",\"IL A\",\"Ġmit igating\",\"Ġapt ly\",\"Ġty rant\",\"Ġmid day\",\"ĠGil more\",\"ĠDe cker\",\"ĠÂ§ Â§\",\"part ial\",\"Ex actly\",\"Ġphen otype\",\"Ġ[+ ]\",\"ĠP lex\",\"ĠI ps\",\"vers ions\",\"Ġe book\",\"Ġch ic\",\"g ross\",\"\\\":\\\" \\\"},{\\\"\",\"ĠSur prisingly\",\"M organ\",\"Ġresid ues\",\"ĠConf ederation\",\"in feld\",\"Ġl yr\",\"mod erate\",\"Ġperpend icular\",\"V K\",\"Ġsynchron ized\",\"Ġrefres hed\",\"Ġad ore\",\"ĠTor ment\",\"ol ina\",\"Ġ26 00\",\"Item Tracker\",\"Ġp ies\",\"ĠF AT\",\"ĠR HP\",\"0 48\",\"ĠRES P\",\"ĠB J\",\"all ows\",\"P and\",\"Ġunw elcome\",\"ĠV oc\",\"ĠBast ard\",\"ĠO W\",\"ĠL AR\",\"ĠHeal er\",\"Environment al\",\"ĠKen yan\",\"ĠTr ance\",\"ĠP ats\",\"Ġali ases\",\"ĠGar field\",\"Ġcampaign er\",\"Ġadvance ments\",\"ĠOkin awa\",\"ĠC oh\",\"ows ky\",\"Ġstar ved\",\"Ġsize able\",\"Ġ: -)\",\"Ġm RNA\",\"Ġsusp ensions\",\"ist ar\",\"Scot land\",\"Pr in\",\"-------------------------------- ----------------\",\"Ġ50 2\",\"Ġteasp oons\",\"Ġ10 50\",\"Ġcoerc ive\",\"ĠMason ic\",\"edd ed\",\"ĠPass enger\",\"Ġl att\",\"Ġbr aces\",\"ĠSt eal\",\"ĠNY T\",\"ĠK ats\",\"ĠCel est\",\"ae z\",\"T u\",\"ĠCoul ter\",\"ðŁ ĺ\",\"Fl ickr\",\"ĠWil mington\",\"ith s\",\"++ ;\",\"Ġv ending\",\"Ġneg ro\",\"ĠPh i\",\"ĠYellow stone\",\"Call back\",\"Ġsh ampoo\",\"ĠSh ades\",\"w at\",\"Ġsuper human\",\"Ġridic uled\",\"Ġhol iest\",\"om bo\",\"Ġintern s\",\"Ġh one\",\"ĠPar agu\",\"UR I\",\"Ġd angling\",\"ãĤ »\",\"so v\",\"ict ional\",\"av ailability\",\"Ġrev ocation\",\"Ġd ow\",\"in ic\",\"ĠTHE IR\",\"Ġis o\",\"Ġout ings\",\"ĠLeth al\",\"Ġ) ))\",\"Ġinacc ur\",\"Ġout landish\",\"Ġan us\",\"let ico\",\"id on\",\"l ol\",\"Ġun regulated\",\"Ġsuccumb ed\",\"Ġc uff\",\"ĠWast eland\",\"let al\",\"Ġsub str\",\"Ġcoff ers\",\"Ġautom akers\",\"ov i\",\"ĠX ue\",\"ĠDayton a\",\"Ġjar ring\",\"Ġf umes\",\"Ġdisband ed\",\"z ik\",\"itt on\",\"Ġstriking ly\",\"Ġsp ores\",\"Ad apter\",\".) :\",\"ĠLynd on\",\"ival ry\",\"Ġor ally\",\"Ġtumult uous\",\"Ġdisple asure\",\"Ġcon es\",\"or rect\",\"Ġappe ase\",\"Ġder by\",\"ĠTrip oli\",\"ĠAl ess\",\"Ġp oked\",\"ĠGu ilty\",\"v P\",\"En ough\",\"Ġorig inals\",\"6 99\",\"Ġrabb i\",\"Ġproverb ial\",\"Ġpostp one\",\"el ope\",\"ĠMist y\",\"Ġstaff ed\",\"ĠUn employment\",\"redit ary\",\"Ġdilig ent\",\"re comm\",\"me asures\",\"as in\",\"8 25\",\"Ġpond s\",\"Ġmm ol\",\"ĠS AR\",\"ĠC ARE\",\"Ġ3 71\",\"Ġclen ched\",\"ĠCors air\",\"Ġcaric ature\",\"z n\",\"att ach\",\"ĠSch ro\",\"spe ak\",\"p ainted\",\"ĠS uc\",\"ĠE NT\",\"Ġcell ul\",\"ĠP aid\",\"di agn\",\"WH ERE\",\"Ġtext ed\",\"B arn\",\"Ġret racted\",\"ĠRe ferred\",\"S av\",\"Ġup keep\",\"Ġwork places\",\"ĠTok ens\",\"Ġampl ify\",\"cl inical\",\"Ġmult ic\",\"mber g\",\"Ġconvol uted\",\"Reg ion\",\"5 65\",\"ĠTop ic\",\"Ġsn ail\",\"Ġsal ine\",\"Ġins urrection\",\"ĠPet r\",\"f orts\",\"B AT\",\"ĠNav ajo\",\"Ġrud imentary\",\"ĠLak sh\",\"OND ON\",\"Me asure\",\"Ġtransform er\",\"ĠGodd ard\",\"Ġcoinc ides\",\"ir in\",\"R ex\",\"ĠB ok\",\"qu it\",\"Ġshotgun s\",\"Ġprolet arian\",\"Ġsc orp\",\"ĠAd a\",\"5 14\",\"Ġsl ander\",\"record ed\",\"Ġemb ell\",\"ris ome\",\"Ġapolog izing\",\"ĠMul cair\",\"ĠGib raltar\",\"Cl a\",\"Ġall ot\",\"ĠAtt ention\",\"Ġ4 33\",\"le ave\",\"Ġwh ine\",\"ĠIss a\",\"ĠFa ust\",\"ĠBar ron\",\"hen y\",\"Ġvictim ized\",\"J ews\",\"Ġnurt uring\",\"ett el\",\"W inged\",\"ĠSub tle\",\"Ġflavor ful\",\"ĠRep s\",\"eng ed\",\"call back\",\"Ġdirection al\",\"Ġcl asp\",\"ĠDirect ions\",\"plan et\",\"icult ure\",\"Hel per\",\"ic ion\",\"ac ia\",\"Ġç ¥ŀ\",\"Ġsur ges\",\"Ġcan oe\",\"ĠPrem iership\",\"be en\",\"Ġdef ied\",\"ĠTro oper\",\"Ġtrip od\",\"Ġgas p\",\"ĠE uph\",\"ĠAd s\",\"vern ight\",\"high ly\",\"R ole\",\"Ġent angled\",\"ĠZe it\",\"6 18\",\"ĠRust y\",\"Ġhaven s\",\"ĠVaugh an\",\"HA EL\",\"ĠSER VICE\",\"/ ,\",\"Ġstr icken\",\"Ġdel usions\",\"Ġb is\",\"ĠH af\",\"Ġgrat ification\",\"Ġent icing\",\"UN CH\",\"Ad ams\",\"ĠOL ED\",\"ĠBeet le\",\"Ġ18 99\",\"ĠSO FTWARE\",\"ateg or\",\"V L\",\"ĠTot em\",\"ĠG ators\",\"AT URES\",\"Ġimped ance\",\"Reg istered\",\"ĠC ary\",\"ĠAer ial\",\"on ne\",\"en ium\",\"Ġd red\",\"ĠBe g\",\"Ġconcurrent ly\",\"Ġsuper power\",\"ĠX an\",\"j ew\",\"imes ter\",\"ĠDick inson\",\"âĶ ģ\",\"F la\",\"Ġp ree\",\"ĠRoll ins\",\"© ¶æ\",\"Ġden omination\",\"ĠL ana\",\"5 16\",\"Ġinc iting\",\"sc ribed\",\"j uries\",\"ĠWond ers\",\"app roximately\",\"Ġsusp ending\",\"Ġmountain ous\",\"ĠL augh\",\"oid al\",\"N s\",\"Det ect\",\") =\",\"ĠL uthor\",\"ĠSchwarz enegger\",\"ĠMull er\",\"ĠDev i\",\"ec ycle\",\"J ar\",\"6 13\",\"ĠL ongh\",\"B ah\",\"ĠSP ORTS\",\"n w\",\"Ġref inement\",\"Ġwater ways\",\"Ġd iner\",\"Bl ade\",\"68 3\",\"F ac\",\"Ġinitial s\",\"Ġro g\",\"Ġparan ormal\",\"B UT\",\"Ġ[ (\",\"ĠSw anson\",\"ĠM esh\",\"âĸ ¬\",\"Impro ve\",\"ĠRad iation\",\"ĠEst her\",\"ĠE sk\",\"ĠA ly\",\"ik y\",\"Ġir rad\",\"ĠBuck ingham\",\"Ġref ill\",\"Ġ. _\",\"Re pe\",\"CON CLUS\",\"Ġdifferent iated\",\"Ġchi rop\",\"ĠAt kins\",\"Pat tern\",\"Ġexc ise\",\"Ġcab al\",\"N SA\",\"ĠST A\",\"ĠS IL\",\"ĠPar aly\",\"Ġr ye\",\"ĠHow ell\",\"ĠCount down\",\"ness es\",\"alys ed\",\"Ġres ize\",\"ãĤ ½\",\"Ġbudget ary\",\"ĠStr as\",\"w ang\",\"Ġap iece\",\"Ġprecinct s\",\"Ġpe ach\",\"Ġsky line\",\"Ġ35 3\",\"pop ular\",\"App earances\",\"ĠMechan ics\",\"ĠDev Online\",\"S ullivan\",\"Z en\",\"Ġp u\",\"op olis\",\"5 44\",\"Ġde form\",\"Ġcounter act\",\"ĠL ange\",\"Ġ4 17\",\"Con sole\",\"77 4\",\"Ġnodd ing\",\"Ġpopul ism\",\"Ġhe p\",\"Ġcoun selling\",\"compl iance\",\"U FF\",\"Ġunden iably\",\"Ġrail ing\",\"ĠHor owitz\",\"ĠSim one\",\"ĠBung ie\",\"Ġa k\",\"ĠTal ks\",\"x ff\",\"fl ake\",\"Cr ash\",\"Ġsweat y\",\"Ġban quet\",\"ĠOFF IC\",\"Ġinvent ive\",\"Ġastron omer\",\"ĠStam ford\",\"ĠSc are\",\"ĠGRE EN\",\"olic ited\",\"Ġr usher\",\"Ġcent rist\",\"ight ing\",\"Ġsub class\",\"Ġdis av\",\"Ġdef und\",\"ĠN anto\",\"oci ate\",\"m ast\",\"Ġpac if\",\"Ġm end\",\"e ers\",\"imm igration\",\"ESS ION\",\"Ġnumber ing\",\"Ġlaugh able\",\"ĠEnd ed\",\"v iation\",\"em ark\",\"P itt\",\"Ġmetic ulous\",\"ĠL F\",\"Ġcongrat ulated\",\"ĠBir ch\",\"Ġsway ed\",\"Ġsemif inals\",\"Ġhum ankind\",\"m atter\",\"ĠEqu ip\",\"opa usal\",\"S aid\",\"ĠLay out\",\"Ġvo icing\",\"Ġth ug\",\"Ġporn ographic\",\"I PS\",\"Ġmo aning\",\"Ġgriev ance\",\"Ġconf essions\",\"esc al\",\"TEXT URE\",\"Aut hent\",\"os aurus\",\"P urchase\",\"Ġreleg ation\",\"al ter\",\"ĠÂł Âł\",\"Ġr iddled\",\"Ġo gre\",\"ĠLow ell\",\"Occ up\",\"E at\",\"ĠHy der\",\"ĠAdvis er\",\"Com merce\",\"H unt\",\"ĠOr th\",\"ĠComp etitive\",\"ĠCL A\",\"CD C\",\"Ġsal ads\",\"F le\",\"Ġindustrial ized\",\"` ,\",\"ĠO WN\",\"Ġbec k\",\"ĠPart icularly\",\"oub t\",\"Ġm M\",\"ĠHuss ain\",\"ĠChen nai\",\"Ġ9 20\",\"Ġappoint ing\",\"ĠCull en\",\",,,, ,,,,\",\"Ġp ores\",\"ver ified\",\"Ġbi ochemical\",\"em ate\",\"Ġcoward ly\",\"ĠHels inki\",\"ĠEthiop ian\",\"S OURCE\",\"ER C\",\"est ro\",\"Ġbi otech\",\"ĠS our\",\"Ġbrew er\",\"Bloom berg\",\"Ġintens ify\",\"Gl ass\",\"an co\",\"ĠF DR\",\"gre SQL\",\"ĠF ires\",\"©¶æ ¥µ\",\"ec o\",\"100 1\",\"ĠHom eless\",\"Ġinstant aneous\",\"ĠH aste\",\"ig el\",\"D iamond\",\"Ġp aving\",\"Ġland fill\",\"Ġd ads\",\"h oun\",\": ]\",\"Ġinc endiary\",\"ĠLiving ston\",\"ĠHil bert\",\"ĠChe cks\",\"st yles\",\"in ators\",\"ĠCl ive\",\"ph rine\",\"Ġchimpan zees\",\"Ġp all\",\"ĠJ M\",\"ĠAad haar\",\"ð Ŀ\",\"Ġachie vable\",\"dis abled\",\"P ET\",\"OOOO OOOO\",\"M ot\",\"Ġint angible\",\"Ġbal let\",\"ĠWe bs\",\"ĠEst imated\",\"Effect s\",\"Ġb ailed\",\"Josh ua\",\"Ġturb ulence\",\"Ġoccup ant\",\"ĠDay light\",\"Ġ36 1\",\"me et\",\"Ġstat ically\",\"Ġon look\",\"Ġk i\",\"il legal\",\"Ġvel vet\",\"Ġdehyd ration\",\"Ġacqu ies\",\"ĠRe z\",\"ak ura\",\"ĠU pton\",\"at ro\",\"Ġincomp rehensible\",\"Ġback door\",\"ĠRh ino\",\"7 27\",\"Ġmath s\",\") +\",\"Ġhe resy\",\"Ġd f\",\"ĠRoc he\",\"ĠL ydia\",\"Ġpanc reat\",\"re ply\",\"arre ll\",\"Ġsolicit ation\",\"Ġcirc adian\",\"BI P\",\"Ġfor ay\",\"Ġcrypt ic\",\"iz u\",\"ime o\",\"ĠTom ato\",\"ĠH oms\",\"ex amination\",\"Ġqu arry\",\"ĠVal iant\",\"ĠJer icho\",\"ĠIN CLUD\",\"Ġ18 40\",\"5 19\",\"Ġres ists\",\"Ġsnap shots\",\"ĠSp ur\",\"ĠAnt iqu\",\"Log in\",\"Ġbest selling\",\"Ġant ic\",\"ĠS utherland\",\"ãĤ¢ ãĥ«\",\"Ġ~ /\",\"ĠP arm\",\"è ĥ\",\"P ages\",\"int ensity\",\"Ġimm obil\",\"Ġ18 65\",\"zz o\",\"Ġn ifty\",\"Ġf entanyl\",\"ĠPres ervation\",\"op hen\",\"Ġd arts\",\"ĠD inosaur\",\"po inters\",\"ĠR ite\",\"s uggest\",\"aware ness\",\"ĠSher idan\",\"Ġst ances\",\"Ġsor cery\",\"Ġper jury\",\"ĠNik ola\",\"ie ver\",\"Ġf iance\",\"ĠJordan ian\",\"ĠBall oon\",\"Ġn ab\",\"Ġk b\",\"Ġhuman ities\",\"ĠTan aka\",\"hill ary\",\"Ġconsult ancy\",\"ĠZ ub\",\"Ġrem ission\",\"Ġconf id\",\"CH Q\",\"ĠF ug\",\"Ġimpro vis\",\"Y ep\",\"/ _\",\"Ġunwilling ness\",\"Ġport folios\",\"05 5\",\"ĠInstruct or\",\"aim an\",\"Ġclaim ants\",\"M bps\",\"ĠBy e\",\"re ceived\",\"T weet\",\"Ġind emn\",\"ri z\",\"am ara\",\"N at\",\"Ġeval uates\",\"ĠL ur\",\"ep ad\",\"FO X\",\"ĠTh ro\",\"Ġrust y\",\"Ġbed rock\",\"ĠOp rah\",\"J B\",\"Ġmanip ulative\",\"Ġwill ful\",\"Ġrel apse\",\"Ġext ant\",\"The me\",\"S ensor\",\"ĠSt ability\",\"go vern\",\"Ġpo ppy\",\"Ġkn ack\",\"Ġins ulated\",\"ĠT ile\",\"ĠExt rem\",\"Ġunt old\",\"Ġconver ge\",\"Ġref uel\",\"ig roup\",\"Ġdistort ions\",\"Ġrav aged\",\"Ġmechan ically\",\"ĠRe illy\",\"ĠN ose\",\"ĠIncarn ation\",\"ĠBeck y\",\"abb ling\",\"Ġt aco\",\"Ġr ake\",\"Ġmelanch oly\",\"Ġillust rious\",\"ĠDart mouth\",\"Gu ide\",\"ĠR azer\",\"ĠBen z\",\"Ult imate\",\"ĠSur prise\",\"Ġpage ant\",\"off er\",\"Who ever\",\"Ġw iser\",\"Ġchem ist\",\"ĠHE LL\",\"ĠBul k\",\"Ġpl utonium\",\"ĠCO VER\",\"Ö ¼\",\"f ailed\",\"Ġtire lessly\",\"Ġinf ertility\",\"ĠTr ident\",\"ĠShow time\",\"ĠC iv\",\"V ice\",\"requ ires\",\"itt ance\",\"Ġun controlled\",\"interest ing\",\"56 1\",\"Ġinnov ate\",\"ateg ic\",\"L ie\",\"ĠS elling\",\"U l\",\"Ġsav ior\",\"ĠT osh\",\"Ġsw ast\",\"P ASS\",\"Ġr ink\",\"Ġcard io\",\"ĠI ro\",\"ud i\",\"Ġv antage\",\"Ġv ans\",\"ĠNi Ã±o\",\"+ =\",\"Ġpropag ate\",\"< ?\",\"Ġmethod ological\",\"204 39\",\"Ġtrig lycer\",\"Ġing rained\",\"ĠAn notations\",\"arr anted\",\"6 17\",\"ĠS odium\",\"ĠA AC\",\"techn ical\",\"mult ipl\",\"Ġ3 73\",\"å ĭ\",\"Ġdec isively\",\"Ġboost ers\",\"Ġdessert s\",\"ĠGren ade\",\"Ġtest ifying\",\"ĠSc ully\",\"ID s\",\"Ġlock down\",\"ĠSc her\",\"ĠR Ã©\",\"ĠWhit man\",\"ĠRams ay\",\"rem ote\",\"Ġh ikers\",\"ĠHy undai\",\"Ġcons cientious\",\"Ġcler ics\",\"ĠSiber ian\",\"ut i\",\"is bury\",\"Ġrel ayed\",\"Ġqu artz\",\"ĠC BI\",\"seek ers\",\"ull a\",\"Ġweld ing\",\"ĠSh al\",\"ble acher\",\"T ai\",\"ĠSam son\",\"Ġt umble\",\"ĠInvest or\",\"Ġsub contract\",\"ĠShin ra\",\"ow icz\",\"j andro\",\"d ad\",\"Ġtermin ating\",\"ĠNe ural\",\"ä» £\",\"Ġleak age\",\"ĠMid lands\",\"ĠCaucas us\",\"í ķ\",\"c it\",\"ll an\",\"iv ably\",\"ĠAlb ion\",\"Ġ4 57\",\"Ġregist rations\",\"Ġcomr ade\",\"Ġclip board\",\"0 47\",\"Ġdiscour aging\",\"ĠO ops\",\"Ad apt\",\"Ġem path\",\"n v\",\"ĠPR OT\",\"ĠDon n\",\"ĠP ax\",\"ĠB ayer\",\"t is\",\"Squ are\",\"Ġfoot prints\",\"part icip\",\"ĠChile an\",\"B rend\",\"ind ucing\",\"M agn\",\"Ġclub house\",\"ĠMagn um\",\"Ġenc amp\",\"ĠEth nic\",\"uch a\",\"ere y\",\"Ġw atered\",\"ĠCal ais\",\"Ġcomplex ion\",\"Ġsect s\",\"Ġren ters\",\"Ġbr as\",\"oÄŁ an\",\"Time out\",\"Man agement\",\"Ġinf ographic\",\"P okemon\",\"Cl ar\",\"Ġloc ality\",\"Ġfl ora\",\"as el\",\"P ont\",\"Ġpop ulate\",\"ĠO ng\",\"Ġsubs istence\",\"Ġa uctions\",\"ĠMcA uliffe\",\"ĠL OOK\",\"br inger\",\"Ġtit an\",\"Ġmanif old\",\"ĠâĹ ı\",\"Ġcalibr ated\",\"Ġcal iphate\",\"ĠSH E\",\"ĠCommission ers\",\"ce ivable\",\"j c\",\"W inner\",\"5 24\",\"Ġcond one\",\"Other wise\",\"Ġp iling\",\"Ġem body\",\"ĠCrime an\",\"ut ics\",\"ĠEx hibition\",\"Ġ4 26\",\"e ering\",\"Ġv ying\",\"ĠH UGE\",\"* =-\",\"Ġprin cipled\",\"à ¦\",\"Ġquir ks\",\"ĠEdit ors\",\"put ing\",\"G ES\",\"ĠF TA\",\"à¤ ¾\",\"add on\",\"ĠH AM\",\"ĠFrie za\",\"W oman\",\". $\",\"Ġc rib\",\"ĠHer od\",\"Ġtim ers\",\"ĠSp aces\",\"ĠMac intosh\",\"at aka\",\"Ġgl ide\",\"Ġsmell ing\",\"ĠB AL\",\"Ġun su\",\"Ġcond os\",\"Ġbicy cl\",\"ĠRev ival\",\"55 3\",\"Ġjugg ling\",\"H ug\",\"ĠKardash ian\",\"ĠBalk ans\",\"mult iple\",\"Ġnutrit ious\",\"oc ry\",\"19 00\",\"Ġinteg rates\",\"Ġad joining\",\"ĠF older\",\"roll ment\",\"ven ient\",\"Ġu ber\",\"y i\",\"Ġwh iff\",\"ĠJu ven\",\"ĠB orough\",\"net te\",\"Ġb ilingual\",\"ĠSp arks\",\"ph thal\",\"man ufact\",\"Ġt outing\",\"ĠPH I\",\"Ke efe\",\"Rew ard\",\"Ġinf all\",\"ĠTem per\",\"typ ically\",\"ĠNik ol\",\"Ġregular s\",\"Ġpseud onym\",\"Ġexhib itions\",\"Ġbl aster\",\"Ġ40 9\",\"w arming\",\"Ġrever ber\",\"Ġrecip rocal\",\"Ġ6 70\",\"ip ient\",\"b ett\",\"ĠBe gins\",\"Ġit ching\",\"ĠPh ar\",\"Ass uming\",\"Ġem itting\",\"ĠML G\",\"Ġbirth place\",\"Ġt aunt\",\"ĠL uffy\",\"ĠAm it\",\"Ġcir cled\",\"ĠN ost\",\"enn ett\",\"Ġde forestation\",\"ĠHist orically\",\"ĠEvery day\",\"Ġovert ake\",\"79 2\",\"Ġn un\",\"ĠLuc ia\",\"Ġaccompan ies\",\"ĠSe eking\",\"ĠTr ash\",\"an ism\",\"R ogue\",\"Ġnorth western\",\"ĠSupplement al\",\"ĠNY U\",\"ĠF RI\",\"ĠSat isf\",\"x es\",\"5 17\",\"Ġreass ured\",\"Ġspor adic\",\"Ġ7 01\",\"Ġmed ial\",\"Ġcannabin oid\",\"Ġbarbar ic\",\"Ġep is\",\"ĠExplos ive\",\"ĠD ough\",\"Ġuns olved\",\"Support ed\",\"Ġacknowled gment\",\"sp awn\",\"Ġkit chens\",\"Ġ- =\",\"talk ing\",\"ic ist\",\"ĠPeg asus\",\"ĠPS U\",\"Ġphot on\",\"ĠAuthent ication\",\"R G\",\"@# &\",\"76 2\",\"ĠCl air\",\"Ġdi aper\",\"Ġbr ist\",\"ĠProsecut ors\",\"ĠJ em\",\"6 28\",\"ĠEvery where\",\"ĠJean ne\",\"equ ality\",\"ãĥ© ãĥ³\",\"object s\",\"ĠPel icans\",\"Ġ39 2\",\"Ġbl u\",\"b ys\",\"ĠA go\",\"Ġinstruction al\",\"Ġdiscrim inating\",\"ĠTR AN\",\"ĠCorn el\",\"ag os\",\"Ġty re\",\"Ġas piration\",\"ĠBrid gewater\",\"\\\": -\",\"! \\\".\",\"ĠEn s\",\"ĠCoc o\",\"P ie\",\"Ġdet ach\",\"ĠC ouch\",\"Ġphys ique\",\"ĠOccup ations\",\"osc opic\",\"en ough\",\"B uzz\",\"App earance\",\"Y P\",\"Ġrac er\",\"Ġcompl icity\",\"r pm\",\"T oy\",\"Ġinterrupt s\",\"ĠCat alyst\",\"Ġut ilitarian\",\"imp act\",\"Ġsp aghetti\",\"Ġp orous\",\"Ġeste emed\",\"Ġinc iner\",\"ĠI OC\",\"7 48\",\"Ġesp resso\",\"ĠSm ile\",\"abil ia\",\"6 35\",\"Ġmathematic ian\",\"Ġ4 24\",\"ĠK L\",\"ĠH IP\",\"Ġover heard\",\"ĠT ud\",\"ĠT ec\",\"Ġqu izz\",\"Ġfl attering\",\"Ġcon n\",\"âĢ İ\",\"Ġatt aches\",\"ĠR OS\",\"ĠAC S\",\"Ġt cp\",\"ĠSh ame\",\"sk ip\",\"res pected\",\"ĠTrin idad\",\"gr ain\",\"Ġfooth old\",\"ĠUnch arted\",\"ĠJul io\",\"z l\",\"av ored\",\"ĠAn xiety\",\"er rors\",\"ĠCent auri\",\"its ch\",\"D addy\",\"Ġclutch ing\",\"ĠIm plement\",\"ĠGut ierrez\",\"Ġ7 60\",\"Ġtele portation\",\"end ra\",\"Ġrevers ible\",\"st ros\",\"Ad venture\",\"08 3\",\"Ġliber ating\",\"Ġas phalt\",\"ĠSp end\",\"AR DS\",\"im sy\",\"PR ES\",\"ĠEmer ging\",\"Ġwild fires\",\"Ġtechn ologically\",\"Ġem its\",\"ĠART ICLE\",\"Ġirregular ities\",\"Ġcher ish\",\"çī Ī\",\"Ġst ink\",\"ĠR ost\",\"Econom ic\",\"Ġcough ing\",\"ĠMcC ann\",\"pro perties\",\"ilant ro\",\"Ġreneg oti\",\"Trans lation\",\"Ġin quest\",\"ĠGra pe\",\"oot ers\",\"gu i\",\"ĠSwords man\",\"ace ae\",\"h itting\",\"Ġr c\",\"Ġexert ed\",\"ĠS AP\",\"it ent\",\"Ġperil ous\",\"Ġobsc urity\",\"Ġassass inate\",\"Ġab original\",\"Ġresc uing\",\"ĠSh attered\",\"lock ing\",\"all ion\",\"Ch anging\",\"ĠHar rington\",\"ĠB ord\",\"ĠAfgh ans\",\"Jam ie\",\"aret z\",\"ĠAugust us\",\"Ġ38 6\",\"8 30\",\"Ġj og\",\"ok ingly\",\"Tr igger\",\"ĠH OR\",\"Stat istics\",\"Ġviewers hip\",\"Ġadd itives\",\"h ur\",\"Ġmaxim izing\",\"ĠR ove\",\"ĠLou ie\",\"ĠBuck et\",\"ĠCHR IST\",\"ou sel\",\"Ġstre aks\",\"ir ted\",\"Ġt ert\",\"Ġcolonial ism\",\"Ġbur ying\",\"y k\",\"Cond ition\",\"ĠDPR K\",\"By Id\",\"75 1\",\"âĹ ¼\",\"Ġwor risome\",\"Ġvoc ational\",\"sl ice\",\"Ġsa ils\",\"ĠCorrection al\",\"95 4\",\"Ġt ul\",\"K id\",\"l uster\",\"Ġfam ilial\",\"ĠSp it\",\"ĠEp iscopal\",\"Specific ally\",\"ĠVol cano\",\"run s\",\"q s\",\"Ġve tted\",\"Ġcram med\",\"t rop\",\"here r\",\"Thank fully\",\"Ġper cussion\",\"Ġor anges\",\"Ġround up\",\"Ġ4 99\",\"x ious\",\"Char acters\",\"ĠZion ism\",\"ĠR ao\",\"ÃĽ ÃĽ\",\"W F\",\"Ġunintention al\",\"ONE Y\",\"Gr ab\",\"Com mercial\",\"Ġglut amate\",\"ĠMcK enna\",\"ru ciating\",\"ning ton\",\"ih u\",\"Ch an\",\"ĠSw ap\",\"Ġleaf lets\",\"Ġfunction ally\",\"er ous\",\"F arm\",\"Ġcal oric\",\"ĠLiter ally\",\"con cert\",\"Ġshe nan\",\"Ġrep aid\",\"ey es\",\"Ġbas hing\",\"ĠG orge\",\"Ġcollabor ations\",\"Ġun account\",\"itch ie\",\"Ġteam work\",\"pp elin\",\"Ġpip ing\",\"Ġmin ced\",\"Ġd iam\",\"ri eg\",\"Ġmasc ara\",\"Ġsuck er\",\"ĠMo ons\",\"App s\",\"ĠPe ck\",\"Ġper v\",\"ĠFl oat\",\"o ley\",\"ĠN ish\",\"im ize\",\"Ġarom atic\",\"u in\",\"end ish\",\"! /\",\"ĠB icycle\",\"ĠAS IC\",\"ile ged\",\"ĠQuad ro\",\"ios yn\",\"Ġlock out\",\"ĠW ink\",\"SP EC\",\"Attempt s\",\"Ġseed ed\",\"red o\",\"ias is\",\"Ġsn ag\",\"ãĥķ ãĤ©\",\"ãĤ ¶\",\"Ġground ing\",\"Ġrelie ver\",\"Ġfrivol ous\",\"ĠG ifts\",\"ĠF aces\",\"Es pecially\",\"Ġmicrobi ome\",\"im ag\",\"ĠSch l\",\"ĠP les\",\"ĠBle ach\",\"ĠIr win\",\"ĠE aton\",\"ĠDisc iple\",\"Ġmultipl ication\",\"Ġcoer ced\",\"Ġ4 19\",\"st h\",\"E vil\",\"B omb\",\"Ġex orc\",\"Ġstag gered\",\"L ESS\",\"Ġinert ia\",\"ĠED IT\",\"Ġgo b\",\"Tr aditional\",\"Ġclass y\",\"Lear y\",\"ĠP AGE\",\"yr s\",\"Ġtrans porter\",\"Ġmat ured\",\"Ġhij ab\",\"Ġbi ome\",\"Where as\",\"Ġex termination\",\"ĠT ues\",\"ĠT akeru\",\"ĠAud rey\",\"er ial\",\"ĠAd en\",\"aff les\",\"Ġnarciss istic\",\"ĠB aird\",\"UT F\",\"I re\",\"ĠCon nie\",\"Ch amp\",\"Ġwhis pering\",\"ĠH att\",\"D K\",\"Ġdis infect\",\"Ġdeduct ed\",\"Ġpart ake\",\"Ġdown grade\",\"ĠEs ports\",\"ĠContin uing\",\"Ġdemocr atically\",\"icro bial\",\"itt a\",\"Ġlim estone\",\"Ġexempt ed\",\"ĠFren zy\",\"H erm\",\"7 28\",\"Ġfled gling\",\"Met a\",\"765 61\",\"69 3\",\"% :\",\"w ake\",\"5 26\",\"ĠDis cipline\",\"Ġvirgin ity\",\"ĠLeg ions\",\"ĠFrank ie\",\"int ent\",\"Ġrest rooms\",\"ĠRou ter\",\"da q\",\"Ġobjection able\",\"âĨ ĳ\",\"w ark\",\"ĠRah ul\",\"g ain\",\"activ ation\",\"abs olute\",\"ĠAccess ed\",\"Ġ24 00\",\"ogg les\",\"Ġsecond ly\",\"ĠDEF ENSE\",\"Ġpost age\",\"wra pper\",\"sh arp\",\"7 29\",\"Ġcommun icates\",\"Ġadd on\",\"ĠMil itia\",\"H ong\",\"Ġsl umped\",\"ĠJP EG\",\"ĠI car\",\"ad ish\",\"68 1\",\"Ġmaj esty\",\"ĠWolf gang\",\"ĠEl astic\",\"u per\",\"Ġv iz\",\"Ġunconscious ly\",\"ĠST D\",\"ĠS ass\",\"Ġflower ing\",\"ĠHel ic\",\"ĠDra per\",\"ĠAm ateur\",\"Ġman ure\",\"Ġdis ingen\",\"ĠLe i\",\"br ing\",\"9 49\",\"Ġinhib ited\",\"Ġhead quartered\",\"Ġen igmatic\",\"ï¿½ï¿½ ï¿½\",\"Ġred ress\",\"R H\",\"Ġratt led\",\"Ġd iction\",\"l io\",\"ĠT BA\",\"ĠSN AP\",\"C alling\",\"Ġfasc ists\",\"ĠD ove\",\"iew icz\",\"0 36\",\"Ġco asts\",\"ĠR ect\",\"Ġ) ]\",\"L ot\",\"6 29\",\"ĠS EM\",\"ĠPeters en\",\"ĠExpl ain\",\"ĠBo ards\",\"ĠBe zos\",\"ĠJ ournals\",\"Ġ20 24\",\"p arser\",\"Ġmist rust\",\"Ġgr ate\",\"ĠL ocked\",\"bo a\",\"S aint\",\"g aming\",\"Ġvow el\",\"in ately\",\"bl ow\",\"All ah\",\"Ġun matched\",\"Ġb ordering\",\"ĠExp end\",\"n r\",\"Or acle\",\"rou ch\",\"Ġcont iguous\",\"ac us\",\"Ġdist raught\",\"58 1\",\"Ġanat omical\",\"O X\",\"ap ixel\",\"8 33\",\"ĠPL US\",\"Ġres usc\",\"Ġab iding\",\"57 3\",\"Ġvac ancies\",\"Em ily\",\"Ġhyp othal\",\"ĠWer ner\",\"ĠWe e\",\"ĠDJ s\",\"5 13\",\"Ġwitch craft\",\"Ġac upuncture\",\"ent ary\",\"benef it\",\"Product s\",\"ĠP SP\",\"ĠMP G\",\"ĠJ inn\",\"ĠJ arrett\",\"Ġ4 45\",\"ĠIm aging\",\"ĠP yth\",\"Fin ish\",\"Ġte x\",\"Ġjuven iles\",\"Ġhero ism\",\"Ġdoubt less\",\"ĠA ki\",\"ĠT end\",\"ĠPatri arch\",\"Ġbit ters\",\"ĠTele communications\",\"it atively\",\"ag na\",\"Ġr g\",\"ĠS OLD\",\"Ġcomp ulsion\",\"ĠN asa\",\"ĠKath ryn\",\"Ġmillion aires\",\"Ġintrins ically\",\"Ġbolst ered\",\"time out\",\"fl o\",\"Ġtut or\",\"p our\",\"Stat ement\",\"Ġ{ *\",\"ĠRud olph\",\"ĠKimber ly\",\"rog ens\",\"adi q\",\"] +\",\"Ġindign ation\",\"Ġfract uring\",\"ĠRe leases\",\"ĠGr ain\",\"pro tein\",\"L ago\",\"Ġvac ations\",\"Ġboot ed\",\"ĠTH REE\",\"ĠH G\",\"oresc ence\",\"Ġt f\",\"Ġso ar\",\"iosyn cr\",\"Ġgl ances\",\"ĠSp oon\",\"ĠJ ury\",\"ĠCow boy\",\"Ġcreat ively\",\"Hig her\",\"Ġsolic itor\",\"Ġhaw k\",\"ac io\",\"89 6\",\"Ġsuperf lu\",\"Ġbombs hell\",\"ct ure\",\"Ġbroker age\",\"Ġraid ing\",\"Ġf rench\",\"Ġang led\",\"Trans action\",\"ĠGen ocide\",\"u pe\",\"ĠHait ian\",\"57 2\",\"! :\",\"Ġunwitting ly\",\"iter ator\",\"sc roll\",\"Ġtall ied\",\"Ġbi omedical\",\"ĠC ARD\",\"Ġe uphem\",\"Ġbrain storm\",\"a quin\",\"K o\",\"Mic helle\",\"ĠR unes\",\"ĠBall istic\",\"ud ers\",\"Ġmod esty\",\"ĠiP ads\",\"ĠEzek iel\",\"Y E\",\"Ġstars hip\",\"Ġpower fully\",\"Ġper l\",\"ĠSh ade\",\"ĠQu art\",\"ĠE EG\",\"Ġfisher man\",\"OS ED\",\"ĠTyp ical\",\"df x\",\"Ġmes hes\",\"Ġet ched\",\"worth iness\",\"Ġtopp led\",\"Ġ3 96\",\"or ius\",\"We iss\",\"Ġmy sql\",\"ĠVal halla\",\"Ù Ĵ\",\"le asing\",\"Ġrec omp\",\"rap nel\",\"S el\",\"04 3\",\"Ġder ailed\",\"ĠGu ides\",\"IR T\",\"Ġde human\",\"ĠBritt any\",\"\\\" ))\",\"Ġex claim\",\"Ġb alk\",\"Ġ8 40\",\"CLA IM\",\"int el\",\"L AB\",\"Ġpe gged\",\"Ġast roph\",\"sm oking\",\"Ġrig ging\",\"Ġfix ation\",\"Ġcat apult\",\"ins ide\",\"ĠC ascade\",\"ĠBolshe vik\",\"G aza\",\"Dep th\",\"Ġloud spe\",\"Ġalmond s\",\"me yer\",\"l eness\",\"j en\",\"f resh\",\"Ġunbeat en\",\"ĠSqu id\",\"ĠPres umably\",\"Tim er\",\"B W\",\"Ġro sters\",\"Ġell ipt\",\"ĠHar riet\",\"dat abase\",\"ĠMut ual\",\"ĠComm odore\",\"uk ed\",\"kn ife\",\"ĠCOMM UN\",\"h ya\",\"Ġmel ts\",\"arch ives\",\"Ġrat ification\",\"Ġmultip lying\",\"Ġinter oper\",\"Ġasc ert\",\"w ings\",\"ver ting\",\"ĠScorp ion\",\"ay e\",\"ĠPorts mouth\",\"ĠM TA\",\"n it\",\"iaz ep\",\"Ġqu arantine\",\"Ġslides how\",\"Ġcent imeters\",\"Ġsyn opsis\",\"Ġsp ate\",\"th irst\",\"Ġnom inating\",\"ĠMel vin\",\"Pre view\",\"Ġthro b\",\"Ġgener ational\",\"ĠRad ius\",\"rest ling\",\"put able\",\"aw ar\",\"N ECT\",\"Ġunlaw fully\",\"ĠRevel ations\",\"Wik ipedia\",\"sur v\",\"Ġeye ing\",\"ij n\",\"ĠF W\",\"Ġbr unt\",\"Ġinter stellar\",\"Ġcl itor\",\"ĠCroat ian\",\"ĠCh ic\",\"ev a\",\"ĠDis app\",\"ĠA kin\",\"iner ies\",\"d ust\",\"Interest ed\",\"Ġgen esis\",\"ĠE ucl\",\"Ã¶ n\",\"p icking\",\"Ġmut ated\",\"Ġdisappro ve\",\"ĠHD L\",\"Ġ6 25\",\"Ì ¶\",\"c ancer\",\"Ġsqu ats\",\"Ġle vers\",\"Disc uss\",\"= ]\",\"D ex\",\"ĠVIDE OS\",\"A UD\",\"Ġtrans act\",\"ĠKin ect\",\"ĠK uala\",\"ĠC yp\",\"7 47\",\"Ġsh attering\",\"Ġarsen ic\",\"ĠInt ake\",\"ĠAngel o\",\"ĠQu it\",\"ĠK he\",\"Ġ18 93\",\"M aker\",\"0 29\",\"ĠPain ting\",\"Dis able\",\"9 16\",\"Ġanal ges\",\"Ġtact ile\",\"Ġprop hes\",\"Ġd iced\",\"ĠTravel s\",\"ĠHe ader\",\"ĠClub s\",\"Ass istant\",\"Ġinc rim\",\"Ġd ips\",\"Ġcruc ifix\",\"ĠShan ahan\",\"ĠInter pret\",\"Ġ40 90\",\"al ogy\",\"abb a\",\"Ġsimul ac\",\"hus band\",\"S IM\",\"Ġrecy cle\",\"uc er\",\"ed ged\",\"Ġre naissance\",\"ĠBomb ay\",\"Cath olic\",\"ĠL INE\",\"ĠCl othing\",\"re ports\",\"Ġpl aus\",\"Ġd ag\",\"ĠM ace\",\"Z I\",\"Ġintr uder\",\"ĠVeter inary\",\"g ru\",\"Ġsne aky\",\"ĠS ie\",\"ĠC innamon\",\"P OSE\",\"Ġcou rier\",\"ĠC NS\",\"Ġemanc ipation\",\"s it\",\"Ġplay through\",\"ĠFac ilities\",\"v irt\",\"ĠG auntlet\",\"Thom pson\",\"Ġunbeliev ably\",\"Param eters\",\"Ġst itching\",\"ign e\",\"ĠTH ESE\",\"Priv acy\",\"Ġshenan igans\",\"Ġvit ri\",\"ĠVal id\",\"59 1\",\"Ń ·\",\"ĠProt otype\",\"ink a\",\"SC P\",\"ĠT id\",\"è Ī\",\"old ed\",\"Ġindividual ity\",\"Ġbark ing\",\"Ġm ars\",\"ĠW D\",\"Ġ8 20\",\"Ġt ir\",\"Ġsl apping\",\"Ġdisgr untled\",\"ĠAng ola\",\"ri us\",\"ĠTorn ado\",\"ĠTh urs\",\"Ġcapt cha\",\"Ġang st\",\"ĠP og\",\"ĠAssass ins\",\"ĠAd idas\",\"Ġjoy ful\",\"Ġwh ining\",\"Emer gency\",\"Ġphosph orus\",\"Ġatt rition\",\"oph on\",\"ĠTimber wolves\",\"ĠJ ah\",\"ĠBr inging\",\"ĠW ad\",\"ĠEn sure\",\"oh l\",\"ĠX ie\",\"omm el\",\"c mp\",\"Ġz ipper\",\"Ġrel at\",\"ĠCor ridor\",\"m ilo\",\"T ING\",\"Av g\",\"Ġcro pped\",\"] }\",\"Ġr aged\",\"ĠLump ur\",\"ĠGuer rero\",\"our ke\",\"N ut\",\"Ġoff sets\",\"og lu\",\"dr m\",\"Ġmort als\",\"lat able\",\"Ġdismiss ive\",\"ä¸ ī\",\"Ġthro ats\",\"Ġchips et\",\"ĠSpot light\",\"Catal og\",\"art ist\",\"G b\",\"Ġch illy\",\"Ġst oked\",\"Ġ3 74\",\"W ard\",\"L atin\",\"Ġf iasco\",\"Ġble ach\",\"Ġb rav\",\"Enh anced\",\"Ġin oc\",\"ĠFior ina\",\"_ >\",\"Ġle ukemia\",\"Ġel uc\",\"Ġannoun cer\",\"ĠLith uan\",\"ĠArm ageddon\",\"å ĩ\",\"Len in\",\"ĠR uk\",\"Ġpe pp\",\"ĠRom antic\",\"ĠP IT\",\"ĠInter stellar\",\"ĠAt kinson\",\"R aid\",\"J s\",\"Go al\",\"C ourse\",\"Ġvan ishing\",\"es ley\",\"ĠR ounds\",\"Els a\",\"59 3\",\"Ġredund ancy\",\"ĠST AND\",\"Ġprop hetic\",\"Ġhabit able\",\"ry u\",\"Ġfaint ly\",\"M ODE\",\"Ġfl anked\",\"IR C\",\"Aw esome\",\"Ġsp urious\",\"ĠZ ah\",\"ĠMS G\",\"Ġsh ading\",\"Ġmotiv ational\",\"ĠSant ana\",\"ĠS PR\",\"Ġexc ruciating\",\"om ial\",\"ĠM iko\",\"ĠLe opard\",\"A byss\",\"Ġ[ |\",\"d irty\",\"Ġbath s\",\"Ġdem oral\",\"and re\",\"P B\",\"Ġun ification\",\"Ġsac rament\",\"Ġ[ &\",\"Ġpric eless\",\"Ġgel atin\",\"Ġeman ating\",\"ĠAll aah\",\"98 6\",\"Ġout burst\",\"Ġer as\",\"ĠX VI\",\"ĠSP I\",\"O tt\",\"ĠLaz arus\",\"PL IED\",\"F lying\",\"blog s\",\"W isconsin\",\"R aven\",\"Ġreb ate\",\"Ġcreep s\",\"ĠSp an\",\"ĠPain ter\",\"ĠKir a\",\"ĠAm os\",\"ĠCor vette\",\"Cons umer\",\"ĠRec over\",\"ck i\",\"Ġpes ky\",\"ĠIn vention\",\"Compan ies\",\"Ġchalleng ers\",\"ad emic\",\"ĠUkrain ians\",\"ĠNeuro log\",\"ĠFors aken\",\"Ġent rants\",\"Ġemb attled\",\"Ġdef unct\",\"ĠGlac ier\",\"Ġpo isons\",\"ĠH orses\",\"m akes\",\"ĠD irt\",\"Ġ4 23\",\"hh h\",\"ĠTrans formation\",\"QUI RE\",\"................ ..\",\"Ġtrave ller\",\"ĠSe xy\",\"ĠK ern\",\"ip olar\",\"Ġransom ware\",\"oooooooo oooooooo\",\"E c\",\"rub y\",\"Prof essional\",\"ĠOut break\",\"arg ument\",\"G rey\",\"ĠFif a\",\"ĠCH O\",\"ĠFOR M\",\"ĠAm trak\",\"- [\",\"Ġcr adle\",\"Ġantioxid ants\",\"ãģ®å ®\",\"7 36\",\"ĠNAS L\",\"ĠContribut ions\",\"Ind iana\",\"ĠST EP\",\"C SS\",\"Ġsal ient\",\"Ġall ocations\",\"yr ights\",\"Ġm ashed\",\"ĠCut ter\",\"Sex ual\",\"Ġp ounded\",\"Ġfan base\",\"Ġc asc\",\"ĠTrans parency\",\"Ġanaly tic\",\"ĠSummon er\",\"× ŀ\",\"ĠAD C\",\"det ail\",\"Ġvan quished\",\"Ġcr abs\",\"ar ie\",\"Dest roy\",\"ĠS ack\",\"Ġtrans istor\",\"Al abama\",\"ĠK oen\",\"ĠFisher ies\",\"c one\",\"Ġannex ed\",\"ĠM GM\",\"es a\",\"Ġf aked\",\"ĠCong ratulations\",\"Ġhind ered\",\"Ġcorrection al\",\"ĠI TV\",\"lee ve\",\"Ġin appropriately\",\"lic ks\",\"Ġtresp ass\",\"Ġp aws\",\"Ġnegoti ator\",\"ĠChrist ensen\",\"lim its\",\"ĠDian ne\",\"Ġeleg ance\",\"ĠContract s\",\"an ke\",\"Ob j\",\"Ġvigil ance\",\"Ġcast les\",\"ĠN AD\",\"ĠHol o\",\"Ġemph atically\",\"ĠTit us\",\"ĠServ ing\",\"ĠRich ie\",\"ĠP igs\",\"5 68\",\"Ġanim osity\",\"ĠAtt ributes\",\"ĠU riel\",\"M Q\",\"my ra\",\"ĠApplic ant\",\"Ġpsychiat rists\",\"ĠV ij\",\"ĠAb by\",\"ag ree\",\"P ush\",\"Ġk Wh\",\"hib a\",\"Ġinc ite\",\"ĠWe asley\",\"ĠTax i\",\"minist ic\",\"hy per\",\"ĠF arn\",\"Ġ6 01\",\"ĠNation wide\",\"F ake\",\"95 2\",\"Ġma ize\",\"Ġinteract ed\",\"Ġtransition ed\",\"Ġparas itic\",\"Ġharm onic\",\"Ġdec aying\",\"Ġbas eless\",\"ns ics\",\"Ġtrans pired\",\"Ġabund antly\",\"ĠFore nsic\",\"Ġtread mill\",\"ĠJ av\",\"ab and\",\"Ġssh d\",\"Ġfront man\",\"ĠJak arta\",\"oll er\",\"dro ps\",\"ĠSERV ICES\",\"rompt u\",\"oph ical\",\"h ospital\",\"bled on\",\"6 45\",\"Ġmid range\",\"ĠEV ENT\",\"cul ated\",\"raw led\",\"Ġper ched\",\"Ġover board\",\"ĠPe el\",\"ĠP wr\",\"ĠCar th\",\"ĠCOM PLE\",\"co e\",\"sh all\",\"Ġdeter rence\",\"M ETHOD\",\"ĠAbs ent\",\"M EN\",\"Ġs ill\",\"ĠLE VEL\",\"Y ork\",\"Ġsin ners\",\"ĠOP EC\",\"ĠN ur\",\"ĠDesign s\",\"se lection\",\"Ġunw orthy\",\"CH A\",\"Ġstreng thens\",\"88 3\",\"ed ly\",\"Ġslic ing\",\"Ġmal nutrition\",\"Ġfilm making\",\"ĠPol k\",\"ur ated\",\"Ġ4 21\",\"bre akers\",\"!' \\\"\",\"Ġwet lands\",\"ĠDisc rimination\",\"Ġallow able\",\"Ġste ered\",\"ĠSic ily\",\"S AM\",\"Ġmust ache\",\"Ġm ids\",\"Ġcl ipped\",\"Ġcirc ulate\",\"Ġbr ittle\",\"ĠBuild ings\",\"ra ised\",\"ĠRound up\",\"Ġwealth ier\",\"Ġoverw rite\",\"Ġover powered\",\"ĠGerr ard\",\"s ites\",\"PD ATED\",\"Ġacute ly\",\"ĠGam ble\",\"Ġp im\",\"ĠK us\",\"Typ ically\",\"De ploy\",\"ĠMoroc can\",\"p otion\",\"com be\",\"Ġvigil ante\",\"Ġ36 3\",\"St ew\",\"ĠB agg\",\"Ġres ided\",\"ĠSp o\",\"Ġrem nant\",\"Ġempt iness\",\"br ainer\",\"Ġout patient\",\"pri ority\",\"Ġle ptin\",\"ĠPay ton\",\"ĠGle aming\",\"ĠS hed\",\"ĠPol o\",\"ĠMormon ism\",\"rest ricted\",\"arl ane\",\"w x\",\"Ġcreat ine\",\"ĠAn on\",\"ĠST UD\",\"ĠJ UL\",\"ĠT ee\",\"5 28\",\"08 9\",\"Ġhat ched\",\"Dis patch\",\"ĠCompos ite\",\"Ġ45 1\",\"p uff\",\"ĠX COM\",\"ĠOr n\",\"ĠTH ANK\",\"END ED\",\"ĠAshe ville\",\"ĠÃ ľ\",\"Ġman go\",\"ĠS lightly\",\"world ly\",\"ĠW ander\",\"ĠExp and\",\"ĠCh r\",\"M ist\",\"Ġorthodox y\",\"ĠUN ESCO\",\"reg ate\",\"Else where\",\"k ie\",\"ir led\",\"Ġtopp le\",\"Ġadopt ive\",\"ĠLeg s\",\"d ress\",\"ĠS agan\",\"b are\",\"ĠGl ou\",\"Cr unch\",\"Ġhelp ers\",\"Ġchron ically\",\"ĠH uma\",\"1 0000\",\"Ġaccommod ating\",\"äº Ķ\",\"Ġwrink les\",\"Ġdod ged\",\"four th\",\"Ġpre con\",\"Ġcompress or\",\"ĠK are\",\"Ġev ict\",\"ĠWar wick\",\"im ar\",\"Ġmodern ization\",\"Ġband wagon\",\"Ġref uted\",\"Ġnet ted\",\"ĠNa ples\",\"ĠGen ie\",\"per ors\",\"Ġfield ed\",\"Ġde re\",\"ĠPar ables\",\"le es\",\"Ġtr out\",\"asp ers\",\"Ġn ihil\",\"Ġhapp iest\",\"Ġflo ppy\",\"ĠLo ft\",\"ĠHe ard\",\"Ġun ison\",\"Ġl ug\",\"ĠRed mond\",\"class ic\",\"Supp orters\",\"SH IP\",\"G MT\",\"Ġfue lled\",\"ç Ĳ\",\"Ġd d\",\"ĠEmin em\",\"Ġ18 97\",\"NY SE\",\"Ġsecret aries\",\"ĠF IA\",\"ĠCanaver al\",\"F avorite\",\"Ġp omp\",\"Ġdetain ee\",\"ers hip\",\"aim on\",\"i our\",\"ĠA pex\",\"Ġplant ations\",\"am ia\",\"ac ion\",\"R ust\",\"Ġtow ed\",\"ĠTru ly\",\"5 77\",\"Ġshel tered\",\"r ider\",\"W o\",\"Ġl air\",\"ĠInt elligent\",\"impro ve\",\"m atically\",\"Ġet iquette\",\"ad ra\",\"all o\",\"ĠJun o\",\"any thing\",\"ĠStru ggle\",\"ĠPred ict\",\"ĠGr imes\",\"ĠAMER ICA\",\"ct x\",\"ĠSit uation\",\"W OOD\",\"Ġsol uble\",\"me ier\",\"Ġintoler able\",\"ang ering\",\"Ġun interrupted\",\"Ġtool tip\",\"Ġinterrog ated\",\"Ġgun ned\",\"ĠSne ak\",\"æŃ ¦\",\"Ġt ether\",\"Ġcr umble\",\"L ens\",\"Ġclust ered\",\"ĠSy l\",\"ĠHas an\",\"Ġdystop ian\",\"w ana\",\"Ġjoy stick\",\"ĠTh ib\",\"amm u\",\"Tom orrow\",\"5 46\",\"Ġoverc ame\",\"Ġminim ized\",\"cept or\",\"Run ner\",\"ENG TH\",\"ĠBrend a\",\"ĠAchieve ments\",\"Ġtor ches\",\"Ġrapp ort\",\"ĠInvestig ator\",\"ĠHand ling\",\"rel ation\",\"g rey\",\"8 15\",\"Ġk cal\",\"ĠComm ands\",\"d q\",\"Ġcur ls\",\"Ġbe arer\",\"Ġcyn icism\",\"it ri\",\"ĠUse ful\",\"B ee\",\"D CS\",\"Ġab ras\",\"P ract\",\"BIL ITIES\",\"7 12\",\"Ġdebug ger\",\"Ġdebt or\",\"ĠL ia\",\"ĠK ers\",\"Ġexacerb ate\",\"ĠSt acy\",\"ĠB land\",\"ĠSc enes\",\"Ġbranch ing\",\"âĸĪâĸĪâĸĪâĸĪ âĸĪâĸĪâĸĪâĸĪ\",\"ape ake\",\"Ġs alsa\",\"Ġmish and\",\"ĠKon ami\",\"ĠN ib\",\"Ġanecd ote\",\"Ġagree able\",\"Ï ī\",\"ĠNath aniel\",\"ĠHe isman\",\"ĠB eware\",\"Ġ18 86\",\"spect ive\",\"69 1\",\"5 22\",\"Ġinhib its\",\"Ġhas hing\",\"Ġ18 89\",\"å° Ĩ\",\"v ich\",\"P ure\",\"Ġsolid ly\",\"Ġaspir in\",\"im aru\",\"Ġstreet car\",\"ĠU CS\",\"ĠJ udd\",\"Ġflash backs\",\"p ins\",\"Ġ14 40\",\"ĠUN HCR\",\"ĠSym ptoms\",\"T IT\",\"5 38\",\"F ra\",\"% );\",\"Ġo oz\",\"Ġcur few\",\"Ġcal med\",\"Ġparticip ates\",\"Te X\",\"Ġnons ensical\",\"Ġfull back\",\"ĠDe L\",\"mon key\",\"h ari\",\"Ġmetabol ites\",\"Ġloot ed\",\"ĠAL WAYS\",\"ĠB CC\",\"L t\",\"oc het\",\"B one\",\"Ġveto ed\",\"Ġg cc\",\"ĠCL ICK\",\"Ġ18 88\",\"s af\",\"Ġstiff ness\",\"Ġlow ly\",\"ĠGe h\",\"vers on\",\"ors et\",\"Ġun foreseen\",\"Ġan esthesia\",\"ĠOpt ical\",\"Ġrecon structed\",\"ĠT up\",\"sh ows\",\"NEW S\",\"ĠNewsp aper\",\"ĠA SA\",\"ter a\",\"N umbers\",\"Ġinexpl icable\",\"× ĳ\",\"Ġhard ness\",\"unt arily\",\"ĠA cer\",\"grad ient\",\"ARD IS\",\"Ġwood land\",\"Ġmetaph ors\",\"ĠWem bley\",\"ĠPa vel\",\"phil is\",\"Ġre writing\",\"Ġpercept ual\",\"Ġ10 70\",\"worm s\",\"ĠDown s\",\"Ġunsur prisingly\",\"Ġtag ging\",\"fl ame\",\"Ġlit res\",\"Ġboun ces\",\"ĠB abe\",\"sh ut\",\"Ġoverd oses\",\"ĠShe ila\",\"ĠCh au\",\"ĠBl ess\",\"Capt ure\",\"ĠSign ificant\",\"ĠSc ion\",\"Ġ38 9\",\"ĠMc H\",\"ĠTitan ium\",\"ĠMe al\",\"amed a\",\"ag ents\",\"agg ressive\",\"B illy\",\"76 3\",\"ĠS aying\",\"DER R\",\"it one\",\"Coll ins\",\"B ound\",\"Ġbol ted\",\"ĠDM CA\",\"95 3\",\"Ġun iqueness\",\"Ġep igen\",\"un ci\",\"ant am\",\"Ġreck oning\",\"ch airs\",\"OG R\",\"ĠSen egal\",\"Ġ18 62\",\"re levant\",\"ĠÂ ¯\",\"Ġpharm acies\",\"ĠG eral\",\"v ier\",\"Y an\",\"OR PG\",\"Ġrab id\",\"b ending\",\"ĠUN ITED\",\"Ġ4 65\",\"As sembly\",\"Ġwe ep\",\"Ġbe hest\",\"ĠMother s\",\"ĠJ ace\",\"h id\",\"Ġwh irlwind\",\"ĠUN IVERS\",\"Ġut opian\",\"Ġkidn ap\",\"Ph ilipp\",\"K in\",\"89 3\",\"Ġlivest ream\",\"ĠM ISS\",\"Ġsub versive\",\"ĠTechn iques\",\"ĠJUST ICE\",\"ĠB ASE\",\"Ġ38 7\",\"Ġassail ants\",\"ĠHard core\",\"Ġsprink led\",\"ĠP se\",\"é ļ\",\"print ed\",\"ĠH au\",\"OR GE\",\"ĠT OUR\",\"Ġl aced\",\"Ġit ch\",\"G iving\",\"Ġport ed\",\"78 1\",\"//////////////// ////////////////\",\"bre eding\",\"Ġlog ger\",\"ĠH OL\",\"inn ie\",\"First ly\",\"Ġembry onic\",\"Ġdeleg ated\",\"p ai\",\"O IL\",\"Ġcentr ally\",\"ĠR x\",\"ĠSc outing\",\"D utch\",\"Ġhe reditary\",\"ĠCru iser\",\"s at\",\"5 29\",\"ĠMar riott\",\"other mal\",\"Ġprohib itions\",\"E arn\",\"ĠSt ab\",\"ĠColleg es\",\"ĠBel ief\",\"st retched\",\"ĠL H\",\"ĠEntity Item\",\"C IA\",\"Ġun rem\",\"Ġlaure ate\",\"Ġdenomin ations\",\"sum mary\",\"h ler\",\"S pect\",\"ĠK laus\",\"ĠBe ans\",\"Ġins ur\",\"ĠPA X\",\"Ġfield er\",\"ĠV et\",\"ĠSp arrow\",\"z ie\",\"ĠS Q\",\"ĠMond ays\",\"ĠOff line\",\"ĠLer ner\",\"ĠExt ensions\",\"Ire land\",\"Ġpatron age\",\"Ġcontrast ed\",\"ĠMan ia\",\"h irt\",\"Mos cow\",\"Ġcondem ns\",\"ĠAn ge\",\"Ġcomp osing\",\"ĠPe pe\",\"ĠP addock\",\"Ġheter ogeneity\",\"Ġide ologically\",\"Ġf ishes\",\"Ġcur sing\",\"ĠR utherford\",\"ĠFlo ating\",\"ĠAm elia\",\"Te a\",\"Syn opsis\",\"Ġstun ts\",\"Ġbe ad\",\"Ġstock ing\",\"ĠM ILL\",\"ob ook\",\"mass ive\",\"\\\\ <\",\"Ġh ump\",\"ĠPref erences\",\"Engine Debug\",\"ge ist\",\"ĠNiet o\",\"ome ver\",\"ish y\",\"eval uate\",\"col onial\",\"Altern ative\",\"ĠGo Pro\",\"ĠV ortex\",\"ĠNET WORK\",\"ans ky\",\"Sec ure\",\"ĠTh rust\",\"Sn ake\",\"Ġparcel s\",\"Ġsam urai\",\"Ġactress es\",\"N ap\",\"M F\",\"ifer ation\",\"Be er\",\"5 23\",\"ĠI ly\",\"oint ment\",\"P ing\",\"Ġstri ped\",\"ĠMell on\",\"oss ession\",\"Ġneut ron\",\"end ium\",\"Ġa ph\",\"ĠFlav oring\",\"Ġ38 3\",\"Ġrespons iveness\",\"ĠJ indal\",\"ĠHitch cock\",\"Den ver\",\"ĠDRAG ON\",\"sm anship\",\"ĠDu pl\",\"Ġs ly\",\"Ġweb cam\",\"ĠTw ain\",\"ĠDar ling\",\"ili ate\",\"cons umer\",\"D IT\",\"Ġnames ake\",\"Ġun orthodox\",\"Ġfun er\",\"ĠPL oS\",\"ĠCONTR OL\",\"ozy g\",\"ogl obin\",\"F ACE\",\"ER G\",\"ĠD ia\",\"ĠF iesta\",\"ce le\",\"0 34\",\"Ġencl ave\",\"âĸ¬ âĸ¬\",\"on ement\",\"al ist\",\"M and\",\"Ġhome grown\",\"ĠF ancy\",\"Ġconcept ions\",\"ĠCont ains\",\"ure en\",\"Ġreiter ate\",\"Ġme ager\",\"Ġinstall ments\",\"Sp awn\",\"6 27\",\"Ġphot oc\",\"ĠCab rera\",\"ĠRos enthal\",\"ĠLans ing\",\"is ner\",\"Ġinvest s\",\"ĠUFO s\",\"EX P\",\"Hard ware\",\"Ġtr agically\",\"Ġconced es\",\"ie ft\",\"ch am\",\"bor gh\",\"ĠSch r\",\"ĠMel anie\",\"ĠH oy\",\"Ġvisit ation\",\"Ġid iosyncr\",\"Ġfract ions\",\"Ġfore skin\",\"ob os\",\"Ġpo aching\",\"ĠVI EW\",\"Ġstimul ates\",\"ĠG ork\",\"can on\",\"M IC\",\"ĠNem esis\",\"ĠInd ra\",\"ĠDM V\",\"Ġ5 29\",\"Ġinspect ing\",\"Ġgrand ma\",\"ĠW hedon\",\"ĠSh ant\",\"ĠP urg\",\"ik an\",\"ĠT eg\",\"ĠCL R\",\"z ac\",\"Vict oria\",\"ĠVer ify\",\"ion ics\",\"Ġpart ying\",\"ĠM ou\",\"col our\",\"Ġtestim onies\",\"l ations\",\"Ġpress uring\",\"hi ro\",\"ac ers\",\"Ġf id\",\"ang ler\",\"ĠCS I\",\"Ġhere after\",\"Ġdiss idents\",\"report ing\",\"iph any\",\"che v\",\"Ġsol itude\",\"Ġl obe\",\"Ġind is\",\"Ġcred ential\",\"re cent\",\"ad ult\",\"ĠNir vana\",\"ĠFranch ise\",\"L ayer\",\"H yp\",\"ĠBerks hire\",\"Ġwill s\",\"t if\",\"Ġtot em\",\"ĠJud ah\",\"rep air\",\"Inst ant\",\"5 48\",\"Ġemb assies\",\"Ġbott leneck\",\"Ġb ount\",\"Ġtyp ew\",\"ĠAl vin\",\"j ing\",\"im ilar\",\"R ush\",\"Ġbr im\",\"ĠHEL P\",\"A im\",\"] '\",\"Ġpass ively\",\"Ġbound ed\",\"ĠR ated\",\"Ġcriminal ity\",\"Ġbiom ark\",\"Ġdisp atcher\",\"ĠTow ards\",\"Ġ+ ++\",\"right eous\",\"f rog\",\"ĠP anc\",\"C arter\",\"0 32\",\"æ© Ł\",\"Ġult raviolet\",\"ĠLic ensed\",\"ĠT ata\",\"ĠBl essing\",\"ĠG AM\",\"Ġchem ically\",\"ĠSe af\",\"ĠRE LE\",\"ĠMerc enary\",\"capital ist\",\"Ġform ulations\",\"Ġann ihilation\",\"ĠVer b\",\"ĠAr gon\",\"Ġun loaded\",\"Ġmorp hed\",\"Ġconqu ering\",\"back er\",\"I ELD\",\"Ġtheft s\",\"Ġfront runner\",\"ĠRoy ale\",\"ĠFund amental\",\"el ight\",\"C hip\",\"necess ary\",\"ay n\",\"ĠSl ip\",\"Ġ4 48\",\"cern ed\",\"P ause\",\"Ġshock ingly\",\"ĠAB V\",\"Ġcomp osure\",\"7 33\",\"ĠMotors port\",\"ah ime\",\"Mur ray\",\"M ach\",\"Ġgr ids\",\"Ġdeb ian\",\"Ġfurther more\",\"Ġdexter ity\",\"ĠCollect ions\",\"os lov\",\"il age\",\"b j\",\"ĠMont eneg\",\"Ġstrut Connector\",\"Ġmassac res\",\"Ġbrief s\",\"fet ched\",\"uv ian\",\"ol ition\",\"Fail ure\",\"emon ic\",\"Ġfl ared\",\"Ġclaim ant\",\"Ġc ures\",\"Ġgive aways\",\"ĠSubst ance\",\"al ions\",\"Ġcr inge\",\"ĠK ul\",\"Ġarist ocracy\",\"ĠUl ster\",\"ol ated\",\"h ousing\",\"ĠM IS\",\"Ġgl ared\",\"ĠWil helm\",\"ne eds\",\"lam bda\",\"build ers\",\"ĠV IS\",\"Ġradi ator\",\"ĠGhost busters\",\"Ġ4 36\",\"act ual\",\"Ġher ds\",\"Ã§ a\",\"watch ing\",\"Ġcounter ing\",\"Ch arge\",\"Ġchar red\",\"Ġwar heads\",\"Ġiod ine\",\"ĠM acy\",\"04 1\",\"Ġdepart ures\",\"ĠS ins\",\"Ġdy ed\",\"ĠConcept s\",\"g ado\",\"7 13\",\"Ġquot ations\",\"Ġg ist\",\"ĠChrist y\",\"Ġant igen\",\"ĠHem p\",\"ĠD rawn\",\"ĠB arg\",\"ez vous\",\"Ġp aternity\",\"Ġar du\",\"ĠAnch orage\",\"ĠR ik\",\"Ġover loaded\",\"ĠUs ername\",\"ĠTam my\",\"ĠN au\",\"ĠCell ular\",\"Ġw aning\",\"Ġrod ent\",\"ĠWor cester\",\"il ts\",\"ĠT ad\",\"Ġdwell ings\",\"Ġbull ish\",\"4 31\",\"Ġretali ate\",\"Ġmig raine\",\"ĠChev ron\",\"CH ECK\",\"Ġdon key\",\"c rim\",\"SP A\",\"ĠAn alog\",\"Ġmarqu ee\",\"ĠHa as\",\"B ir\",\"ĠGD DR\",\"ĠDownload s\",\"Ġwill power\",\"ĠFor th\",\"ĠRecord ed\",\"Ġimp ossibility\",\"ĠLog ged\",\"ĠFr anks\",\"ĠR att\",\"in itions\",\"Ġclean ers\",\"Ġsore ly\",\"Ġflick ering\",\"ĠEx amination\",\"c atching\",\"allow een\",\"Ms g\",\"Ġdun no\",\"F a\",\"Ġdys ph\",\"c razy\",\".' '.\",\"Ġmain line\",\"Ġc s\",\"Ġp tr\",\"ĠW ally\",\"ig un\",\"95 1\",\"ĠBig foot\",\"f ights\",\"Ġretrie ving\",\"J r\",\"Ġdupl ication\",\"ĠExpl an\",\"Ġrel ational\",\"Ġqu aint\",\"Ġbisc uits\",\"Ġad o\",\"Ġsh udder\",\"Ġantid ote\",\"blood ed\",\"ks h\",\"Ġsa uces\",\"Ġrein vest\",\"Ġdispens ary\",\"ĠD iver\",\"Ġ9 000\",\"stud ent\",\"Ġin separ\",\"esc ap\",\"Ġtodd lers\",\"ĠGP IO\",\"ĠAss ignment\",\"head ers\",\"Ġlack luster\",\"Ġab ack\",\"95 6\",\"Ġtool bar\",\"7 45\",\"Ġo ust\",\"Ġcontempl ation\",\"ĠPRES IDENT\",\"Ġ4 58\",\"==== ==\",\"Ġguarantee ing\",\"ĠHe ist\",\"ĠCann es\",\"Ļ ½\",\"Ġcollabor ator\",\"ĠAm p\",\"Ġg ou\",\"ĠSH ALL\",\"st ories\",\"78 3\",\"Ġmobil ized\",\"Ġbro od\",\"ĠL U\",\"ĠðŁ ĳ\",\"Ġref in\",\"ĠAnthrop ology\",\"v ind\",\"ill i\",\"Ġwarrant ies\",\"ĠB abel\",\"Ġsw ath\",\"Ġc aches\",\"Ġantagon ists\",\"art ifacts\",\"Ġhot ly\",\"ĠSt arts\",\"ĠG Ã¶\",\"z ag\",\"!! !!!\",\"Ġsc ourge\",\"Ġcons piring\",\"ru its\",\"re verse\",\"ĠShe en\",\"ĠJes uit\",\"ĠGiov anni\",\"ad ies\",\"Ġbutt ocks\",\"ear cher\",\"ac an\",\"Ġvolley ball\",\"Ġshroud ed\",\"Ġscore board\",\"b ats\",\"ĠI PM\",\"Ġass es\",\"Ġde regulation\",\"ĠTe legram\",\"ĠReb oot\",\"Ġ7 000\",\"ĠCan ary\",\"Ġk ernels\",\"ĠFranÃ§ ois\",\"ĠD uff\",\"ĠP on\",\"ĠLe ica\",\"ĠGar min\",\"Ġor phans\",\"ĠClaud ia\",\"Ġcal endars\",\"ĠLe ilan\",\"ent o\",\"R ocket\",\"Ġbr unch\",\"ĠHaw king\",\"ain ers\",\"Ġsens ibilities\",\"Ġk W\",\"ĠK and\",\"Ġre claimed\",\"Ġinteresting ly\",\"× ©\",\"rom y\",\"J M\",\"ĠEnhance ment\",\"b ush\",\"Sk ip\",\"Ġrapp ers\",\"Ġg azing\",\"p edia\",\"ath lon\",\"Rev olution\",\"Ġsn ipers\",\"Ġre verted\",\"Ġconglomer ate\",\"T erry\",\"79 4\",\"Ġhars her\",\"Ġdes olate\",\"ĠHit man\",\"Comm ission\",\"Ġ( /\",\"âĢ¦ .\\\"\",\"Com par\",\"Ġampl ification\",\"om inated\",\"Ġreg ress\",\"ĠColl ider\",\"Ġinform ants\",\"Ġg azed\"]}}"
  },
  {
    "path": "eval/grounded_sam/florence2/tokenizer_config.json",
    "content": "{\n    \"model_max_length\": 1024\n}\n\n"
  },
  {
    "path": "eval/grounded_sam/florence2/vocab.json",
    "content": "{\n    \"<s>\": 0,\n    \"<pad>\": 1,\n    \"</s>\": 2,\n    \"<unk>\": 3,\n    \".\": 4,\n    \"Ġthe\": 5,\n    \",\": 6,\n    \"Ġto\": 7,\n    \"Ġand\": 8,\n    \"Ġof\": 9,\n    \"Ġa\": 10,\n    \"Ġin\": 11,\n    \"-\": 12,\n    \"Ġfor\": 13,\n    \"Ġthat\": 14,\n    \"Ġon\": 15,\n    \"Ġis\": 16,\n    \"âĢ\": 17,\n    \"'s\": 18,\n    \"Ġwith\": 19,\n    \"ĠThe\": 20,\n    \"Ġwas\": 21,\n    \"Ġ\\\"\": 22,\n    \"Ġat\": 23,\n    \"Ġit\": 24,\n    \"Ġas\": 25,\n    \"Ġsaid\": 26,\n    \"Ļ\": 27,\n    \"Ġbe\": 28,\n    \"s\": 29,\n    \"Ġby\": 30,\n    \"Ġfrom\": 31,\n    \"Ġare\": 32,\n    \"Ġhave\": 33,\n    \"Ġhas\": 34,\n    \":\": 35,\n    \"Ġ(\": 36,\n    \"Ġhe\": 37,\n    \"ĠI\": 38,\n    \"Ġhis\": 39,\n    \"Ġwill\": 40,\n    \"Ġan\": 41,\n    \"Ġthis\": 42,\n    \")\": 43,\n    \"ĠâĢ\": 44,\n    \"Ġnot\": 45,\n    \"Ŀ\": 46,\n    \"Ġyou\": 47,\n    \"ľ\": 48,\n    \"Ġtheir\": 49,\n    \"Ġor\": 50,\n    \"Ġthey\": 51,\n    \"Ġwe\": 52,\n    \"Ġbut\": 53,\n    \"Ġwho\": 54,\n    \"Ġmore\": 55,\n    \"Ġhad\": 56,\n    \"Ġbeen\": 57,\n    \"Ġwere\": 58,\n    \"Ġabout\": 59,\n    \",\\\"\": 60,\n    \"Ġwhich\": 61,\n    \"Ġup\": 62,\n    \"Ġits\": 63,\n    \"Ġcan\": 64,\n    \"Ġone\": 65,\n    \"Ġout\": 66,\n    \"Ġalso\": 67,\n    \"Ġ$\": 68,\n    \"Ġher\": 69,\n    \"Ġall\": 70,\n    \"Ġafter\": 71,\n    \".\\\"\": 72,\n    \"/\": 73,\n    \"Ġwould\": 74,\n    \"'t\": 75,\n    \"Ġyear\": 76,\n    \"Ġwhen\": 77,\n    \"Ġfirst\": 78,\n    \"Ġshe\": 79,\n    \"Ġtwo\": 80,\n    \"Ġover\": 81,\n    \"Ġpeople\": 82,\n    \"ĠA\": 83,\n    \"Ġour\": 84,\n    \"ĠIt\": 85,\n    \"Ġtime\": 86,\n    \"Ġthan\": 87,\n    \"Ġinto\": 88,\n    \"Ġthere\": 89,\n    \"t\": 90,\n    \"ĠHe\": 91,\n    \"Ġnew\": 92,\n    \"ĠâĢĶ\": 93,\n    \"Ġlast\": 94,\n    \"Ġjust\": 95,\n    \"ĠIn\": 96,\n    \"Ġother\": 97,\n    \"Ġso\": 98,\n    \"Ġwhat\": 99,\n    \"I\": 100,\n    \"Ġlike\": 101,\n    \"a\": 102,\n    \"Ġsome\": 103,\n    \"S\": 104,\n    \"Ã«\": 105,\n    \"Ġthem\": 106,\n    \"Ġyears\": 107,\n    \"'\": 108,\n    \"Ġdo\": 109,\n    \"Ġyour\": 110,\n    \"Ġ-\": 111,\n    \"Ġ1\": 112,\n    \"\\\"\": 113,\n    \"Ġif\": 114,\n    \"Ġcould\": 115,\n    \"?\": 116,\n    \"Ġno\": 117,\n    \"i\": 118,\n    \"m\": 119,\n    \"Ġget\": 120,\n    \"ĠU\": 121,\n    \"Ġnow\": 122,\n    \"Ġhim\": 123,\n    \"Ġback\": 124,\n    \"ĠBut\": 125,\n    \"ĠâĢĵ\": 126,\n    \"Ġmy\": 127,\n    \"Ġ'\": 128,\n    \"Ġonly\": 129,\n    \"Ġthree\": 130,\n    \";\": 131,\n    \"Ġ2\": 132,\n    \"The\": 133,\n    \"1\": 134,\n    \"Ġpercent\": 135,\n    \"Ġagainst\": 136,\n    \"Ġbefore\": 137,\n    \"Ġcompany\": 138,\n    \"o\": 139,\n    \"ĠTrump\": 140,\n    \"Ġhow\": 141,\n    \"Ġbecause\": 142,\n    \"Ġany\": 143,\n    \"Ġmost\": 144,\n    \"Ġbeing\": 145,\n    \"Ġmake\": 146,\n    \"Ġwhere\": 147,\n    \"Ġduring\": 148,\n    \"Ġthrough\": 149,\n    \"Ġwhile\": 150,\n    \"000\": 151,\n    \"ĠThis\": 152,\n    \"Ġmillion\": 153,\n    \"ing\": 154,\n    \"Ġ3\": 155,\n    \"Ġmade\": 156,\n    \"Ġwell\": 157,\n    \"Ġ10\": 158,\n    \"Ġdown\": 159,\n    \"Ġoff\": 160,\n    \"Ġsays\": 161,\n    \"Ġme\": 162,\n    \"ĠB\": 163,\n    \"Ġgoing\": 164,\n    \"Ġteam\": 165,\n    \"ĠWe\": 166,\n    \"Ġthose\": 167,\n    \"Ġgovernment\": 168,\n    \"Ġway\": 169,\n    \"We\": 170,\n    \"Ġmany\": 171,\n    \"Ġthen\": 172,\n    \"Ġwork\": 173,\n    \"Ġtold\": 174,\n    \"com\": 175,\n    \"2\": 176,\n    \"Ġgame\": 177,\n    \"ĠAnd\": 178,\n    \"in\": 179,\n    \"year\": 180,\n    \"Ġp\": 181,\n    \"Ġvery\": 182,\n    \"Ġday\": 183,\n    \"Ġhome\": 184,\n    \"Ġtake\": 185,\n    \"Ġweek\": 186,\n    \"Ġsince\": 187,\n    \"ĠNew\": 188,\n    \"Ġmay\": 189,\n    \"Ġeven\": 190,\n    \"Ġseason\": 191,\n    \"Ġsee\": 192,\n    \"Ġ2017\": 193,\n    \"Ġstate\": 194,\n    \"Ġ5\": 195,\n    \"ed\": 196,\n    \"Ġshould\": 197,\n    \"Ġaround\": 198,\n    \"Ġ2018\": 199,\n    \"Ġsecond\": 200,\n    \"Ġus\": 201,\n    \"Ġstill\": 202,\n    \"Ġmuch\": 203,\n    \"Ġ4\": 204,\n    \"Ġgood\": 205,\n    \"Ġthink\": 206,\n    \"%\": 207,\n    \"ĠS\": 208,\n    \"Ġthese\": 209,\n    \"Ġmarket\": 210,\n    \"ĠD\": 211,\n    \"th\": 212,\n    \"Ġgo\": 213,\n    \"'re\": 214,\n    \"Ġsuch\": 215,\n    \"Ġknow\": 216,\n    \"Ġincluding\": 217,\n    \"Ġdon\": 218,\n    \"y\": 219,\n    \"Ġnext\": 220,\n    \"ĠP\": 221,\n    \"Ġdid\": 222,\n    \"Ġunder\": 223,\n    \"Ġsay\": 224,\n    \"en\": 225,\n    \"ĠL\": 226,\n    \"Ġbetween\": 227,\n    \"Ġper\": 228,\n    \"ĠK\": 229,\n    \"ĠC\": 230,\n    \"Ġ6\": 231,\n    \"Ġworld\": 232,\n    \"Ġpart\": 233,\n    \"ĠN\": 234,\n    \"Ġright\": 235,\n    \"Ġwant\": 236,\n    \"Ġfour\": 237,\n    \"),\": 238,\n    \"Ġhigh\": 239,\n    \"Ġneed\": 240,\n    \"re\": 241,\n    \"e\": 242,\n    \"It\": 243,\n    \"Ġhelp\": 244,\n    \"5\": 245,\n    \"3\": 246,\n    \"Ġcountry\": 247,\n    \"ĠR\": 248,\n    \"Ġpolice\": 249,\n    \"A\": 250,\n    \"Ġlong\": 251,\n    \"ĠThey\": 252,\n    \"Ġend\": 253,\n    \"er\": 254,\n    \"ĠT\": 255,\n    \"ĠM\": 256,\n    \"u\": 257,\n    \"Ġboth\": 258,\n    \"Ġhere\": 259,\n    \"an\": 260,\n    \"on\": 261,\n    \"Ġ7\": 262,\n    \"Ġde\": 263,\n    \"ĠShe\": 264,\n    \"Ġbusiness\": 265,\n    \"Ġreport\": 266,\n    \"j\": 267,\n    \"ers\": 268,\n    \"Ġreally\": 269,\n    \"ĠPresident\": 270,\n    \"ar\": 271,\n    \"ĠG\": 272,\n    \"ĠFriday\": 273,\n    \"ĠF\": 274,\n    \"Ġbest\": 275,\n    \"Ġsame\": 276,\n    \"Ġanother\": 277,\n    \"Ġset\": 278,\n    \"old\": 279,\n    \"ĠThat\": 280,\n    \"as\": 281,\n    \"n\": 282,\n    \"Ġcome\": 283,\n    \"Ġfamily\": 284,\n    \"Ġpublic\": 285,\n    \"ĠFor\": 286,\n    \"ĠAs\": 287,\n    \"0\": 288,\n    \"ĠH\": 289,\n    \"Ġ8\": 290,\n    \"Ġ20\": 291,\n    \"Ġfive\": 292,\n    \"es\": 293,\n    \"ĠTuesday\": 294,\n    \"Ġn\": 295,\n    \"ĠThursday\": 296,\n    \"Ġquarter\": 297,\n    \"h\": 298,\n    \"Ġtop\": 299,\n    \"Ġgot\": 300,\n    \"Ġlife\": 301,\n    \"ĠMonday\": 302,\n    \"Ġfound\": 303,\n    \"Ġuse\": 304,\n    \"ĠW\": 305,\n    \"4\": 306,\n    \"ĠWednesday\": 307,\n    \"Ġown\": 308,\n    \"Ġaccording\": 309,\n    \"Ġplay\": 310,\n    \"Ġshow\": 311,\n    \"ĠSt\": 312,\n    \"Ġman\": 313,\n    \"Ġleft\": 314,\n    \"ĠUnited\": 315,\n    \"Ġ12\": 316,\n    \"Ġplace\": 317,\n    \"ĠIf\": 318,\n    \"Ġlot\": 319,\n    \"Ġformer\": 320,\n    \"Ġ0\": 321,\n    \").\": 322,\n    \"Ġsupport\": 323,\n    \"ie\": 324,\n    \"Ġbillion\": 325,\n    \"Ġt\": 326,\n    \"Ġshares\": 327,\n    \"!\": 328,\n    \"z\": 329,\n    \"k\": 330,\n    \"ĠState\": 331,\n    \"Ġpoints\": 332,\n    \"Ġgroup\": 333,\n    \"Ġschool\": 334,\n    \"Ġinformation\": 335,\n    \"Ġ2016\": 336,\n    \"al\": 337,\n    \"r\": 338,\n    \"Ġwin\": 339,\n    \"Ġnews\": 340,\n    \"Ġused\": 341,\n    \"Ġput\": 342,\n    \"Ġcity\": 343,\n    \"ĠJ\": 344,\n    \"ĠThere\": 345,\n    \"Ġnumber\": 346,\n    \"C\": 347,\n    \"'ve\": 348,\n    \"Ġeach\": 349,\n    \"Ġtoo\": 350,\n    \"Ġwon\": 351,\n    \"ly\": 352,\n    \"Ġmonth\": 353,\n    \"is\": 354,\n    \"Ġadded\": 355,\n    \"Ġlook\": 356,\n    \"Ġbetter\": 357,\n    \"Ġevery\": 358,\n    \"Ġ&\": 359,\n    \"Ġdays\": 360,\n    \"Ġ9\": 361,\n    \"Ġtook\": 362,\n    \"Ġnight\": 363,\n    \"Ġe\": 364,\n    \"Ġ11\": 365,\n    \"os\": 366,\n    \"Ġfew\": 367,\n    \"or\": 368,\n    \"ĠNorth\": 369,\n    \"ĠYou\": 370,\n    \"Ġthird\": 371,\n    \"Ġgreat\": 372,\n    \"Ġcalled\": 373,\n    \"ĠOn\": 374,\n    \"Ġpast\": 375,\n    \"Ġcame\": 376,\n    \"Ġmonths\": 377,\n    \"ĠSaturday\": 378,\n    \"Ġ15\": 379,\n    \"Ġbig\": 380,\n    \"ĠE\": 381,\n    \"ĠUS\": 382,\n    \"Ġthings\": 383,\n    \"ĠO\": 384,\n    \"Ġd\": 385,\n    \"Ġstart\": 386,\n    \"B\": 387,\n    \"Ġstock\": 388,\n    \"Ġ30\": 389,\n    \"Ġwomen\": 390,\n    \"ĠSouth\": 391,\n    \"ĠMay\": 392,\n    \"Ġnever\": 393,\n    \"Ġpresident\": 394,\n    \"ĠSunday\": 395,\n    \"Ġwithout\": 396,\n    \"man\": 397,\n    \"8\": 398,\n    \"Ġdidn\": 399,\n    \"Ġlocal\": 400,\n    \"6\": 401,\n    \"Ġsomething\": 402,\n    \"Ġcase\": 403,\n    \"ĠAll\": 404,\n    \"it\": 405,\n    \"7\": 406,\n    \"ĠSo\": 407,\n    \"Ġchildren\": 408,\n    \"Ġaway\": 409,\n    \"Ġlittle\": 410,\n    \"Ġsix\": 411,\n    \"ĠCity\": 412,\n    \"ĠCounty\": 413,\n    \"Ġdata\": 414,\n    \"at\": 415,\n    \"Ġalready\": 416,\n    \"d\": 417,\n    \"Ġmoney\": 418,\n    \"Ġearly\": 419,\n    \"Ġacross\": 420,\n    \"Ġexpected\": 421,\n    \"Ġrun\": 422,\n    \"Ġlater\": 423,\n    \"am\": 424,\n    \"Ġprice\": 425,\n    \"Ġgames\": 426,\n    \"ĠMr\": 427,\n    \"b\": 428,\n    \"Ġmight\": 429,\n    \"Ġdifferent\": 430,\n    \"Ġreported\": 431,\n    \"Ġdeal\": 432,\n    \"Ġmedia\": 433,\n    \"Ġgrowth\": 434,\n    \"Ġcommunity\": 435,\n    \"ĠChina\": 436,\n    \"'m\": 437,\n    \"c\": 438,\n    \"Ġwent\": 439,\n    \"ĠNo\": 440,\n    \"Ġable\": 441,\n    \"Ġmaking\": 442,\n    \"Ġarea\": 443,\n    \"Ġfar\": 444,\n    \"Ġstatement\": 445,\n    \"ĠHouse\": 446,\n    \"Ġworking\": 447,\n    \"M\": 448,\n    \"Ġk\": 449,\n    \"Ġseen\": 450,\n    \"Ġcompanies\": 451,\n    \"Ġtoday\": 452,\n    \"Ġmembers\": 453,\n    \"Ġuntil\": 454,\n    \"Ġfull\": 455,\n    \"Ġagain\": 456,\n    \"Ġhalf\": 457,\n    \"Ġshare\": 458,\n    \"le\": 459,\n    \"Ġalways\": 460,\n    \"Ġcourt\": 461,\n    \"l\": 462,\n    \"and\": 463,\n    \"Ġchange\": 464,\n    \"Ġfind\": 465,\n    \"9\": 466,\n    \"Ġsystem\": 467,\n    \"ĠV\": 468,\n    \"ĠYork\": 469,\n    \"ĠAmerican\": 470,\n    \"Ġhead\": 471,\n    \"Ġplayers\": 472,\n    \"Ġdoes\": 473,\n    \"Ġhealth\": 474,\n    \"Ġm\": 475,\n    \"Ġpower\": 476,\n    \"Ġpoint\": 477,\n    \"Ġhit\": 478,\n    \"Ġ.\": 479,\n    \"Ġ--\": 480,\n    \"Ġfree\": 481,\n    \".,\": 482,\n    \"Ġlead\": 483,\n    \"Ġseveral\": 484,\n    \"Ġrecent\": 485,\n    \"Ġcall\": 486,\n    \"N\": 487,\n    \"Ġlaw\": 488,\n    \"Ġkeep\": 489,\n    \"Ġopen\": 490,\n    \"ĠNews\": 491,\n    \"Ġgive\": 492,\n    \"ia\": 493,\n    \"ĠMarch\": 494,\n    \"D\": 495,\n    \"ĠNational\": 496,\n    \"ĠAt\": 497,\n    \"Ġtimes\": 498,\n    \"Ġfuture\": 499,\n    \"R\": 500,\n    \"Ġ14\": 501,\n    \"ĠJune\": 502,\n    \"Ġofficials\": 503,\n    \"Ġ18\": 504,\n    \"Ġimportant\": 505,\n    \"f\": 506,\n    \"Ġfinal\": 507,\n    \"Ġ13\": 508,\n    \"ĠOne\": 509,\n    \"P\": 510,\n    \"Ġfollowing\": 511,\n    \"Ġcar\": 512,\n    \"Ġleast\": 513,\n    \"Ġwater\": 514,\n    \"Ġevent\": 515,\n    \"Ġline\": 516,\n    \"Ġmove\": 517,\n    \"Ġservices\": 518,\n    \"Ġhaving\": 519,\n    \"ĠWhen\": 520,\n    \"Ġstudents\": 521,\n    \"ĠPolice\": 522,\n    \"el\": 523,\n    \"Ġam\": 524,\n    \"ĠZ\": 525,\n    \"Ġside\": 526,\n    \"Ġstory\": 527,\n    \"Ġdue\": 528,\n    \"Ġmeeting\": 529,\n    \"K\": 530,\n    \"Ġmust\": 531,\n    \"ĠStates\": 532,\n    \"Ġlikely\": 533,\n    \"G\": 534,\n    \"Ġcontinue\": 535,\n    \"Ġago\": 536,\n    \"Ġparty\": 537,\n    \"Ġmajor\": 538,\n    \"Ġindustry\": 539,\n    \"Ġless\": 540,\n    \"30\": 541,\n    \"Ġun\": 542,\n    \"Ġhard\": 543,\n    \"Ġservice\": 544,\n    \"Ġ16\": 545,\n    \"Ġlooking\": 546,\n    \"Ġheld\": 547,\n    \"ve\": 548,\n    \"Ġwhether\": 549,\n    \"ĠJuly\": 550,\n    \"Ġtaken\": 551,\n    \"Ġalong\": 552,\n    \"Ġasked\": 553,\n    \"Ġstarted\": 554,\n    \"Ġbecome\": 555,\n    \"Ġforward\": 556,\n    \"Ġresearch\": 557,\n    \"Ġoffice\": 558,\n    \"Ġpolitical\": 559,\n    \"to\": 560,\n    \"Ġtogether\": 561,\n    \"Ġgetting\": 562,\n    \"Ġplan\": 563,\n    \"Ġ25\": 564,\n    \"T\": 565,\n    \"Ġamong\": 566,\n    \"Ġcoming\": 567,\n    \"Ġdecision\": 568,\n    \"Ġvideo\": 569,\n    \"Ġ2015\": 570,\n    \"g\": 571,\n    \"ĠAfter\": 572,\n    \"Ġsecurity\": 573,\n    \"L\": 574,\n    \"Ġcare\": 575,\n    \"Ġgiven\": 576,\n    \"Ġavailable\": 577,\n    \"âĢĶ\": 578,\n    \"Ġs\": 579,\n    \"ĠWest\": 580,\n    \"'ll\": 581,\n    \"Ġpay\": 582,\n    \"Ġnear\": 583,\n    \"Ġsaying\": 584,\n    \"Ġannounced\": 585,\n    \"Ġprogram\": 586,\n    \"ĠApril\": 587,\n    \"Ġreal\": 588,\n    \"ĠUniversity\": 589,\n    \"ĠWith\": 590,\n    \"AP\": 591,\n    \"Ġsocial\": 592,\n    \"Ġclose\": 593,\n    \"et\": 594,\n    \"Ġcurrent\": 595,\n    \"Ġwhy\": 596,\n    \"F\": 597,\n    \"ĠTo\": 598,\n    \"ĠTwitter\": 599,\n    \"Ġthough\": 600,\n    \"Ġ17\": 601,\n    \"Ġtaking\": 602,\n    \"ĠInc\": 603,\n    \"Ġmen\": 604,\n    \"w\": 605,\n    \"Ġcomes\": 606,\n    \"ley\": 607,\n    \"Ġdoing\": 608,\n    \"Ġprocess\": 609,\n    \"ĠJohn\": 610,\n    \"ch\": 611,\n    \"00\": 612,\n    \"Ġfinancial\": 613,\n    \"Ġlow\": 614,\n    \"Ġenough\": 615,\n    \"ĠWhile\": 616,\n    \"Ġfurther\": 617,\n    \"Ġpost\": 618,\n    \"Ġfeel\": 619,\n    \"st\": 620,\n    \"Ġperson\": 621,\n    \"ĠFacebook\": 622,\n    \"ĠWorld\": 623,\n    \"Ġwithin\": 624,\n    \"ad\": 625,\n    \"Ġdone\": 626,\n    \"the\": 627,\n    \"Ġlate\": 628,\n    \"Ġtax\": 629,\n    \"Ġdoesn\": 630,\n    \"Ġthing\": 631,\n    \"Ġnational\": 632,\n    \"Ġjob\": 633,\n    \"Ġusing\": 634,\n    \"ĠHowever\": 635,\n    \"ic\": 636,\n    \"Ġcampaign\": 637,\n    \"Ġrecord\": 638,\n    \"Ġbehind\": 639,\n    \"://\": 640,\n    \"ĠDepartment\": 641,\n    \"p\": 642,\n    \"Ġothers\": 643,\n    \"ĠJanuary\": 644,\n    \"Ġorder\": 645,\n    \"Ġ[\": 646,\n    \"Ġsales\": 647,\n    \"Ġyet\": 648,\n    \"Ä\": 649,\n    \"Ġsmall\": 650,\n    \"Ġseries\": 651,\n    \"Ġface\": 652,\n    \"ĠWhat\": 653,\n    \"Ġ50\": 654,\n    \"Ġever\": 655,\n    \"Ġearlier\": 656,\n    \"Ġlove\": 657,\n    \"up\": 658,\n    \"Ġrights\": 659,\n    \"ĠAn\": 660,\n    \"ist\": 661,\n    \"Ġmorning\": 662,\n    \"ĠWashington\": 663,\n    \"Ġyoung\": 664,\n    \"Ġlatest\": 665,\n    \"ĠIndia\": 666,\n    \"Ġtrying\": 667,\n    \"Ġfire\": 668,\n    \"Ġled\": 669,\n    \"Ġstrong\": 670,\n    \"Ġreturn\": 671,\n    \"Ġlevel\": 672,\n    \"O\": 673,\n    \"Ġaverage\": 674,\n    \"Ġperiod\": 675,\n    \"Ġexperience\": 676,\n    \"ak\": 677,\n    \"Ġpossible\": 678,\n    \"Ġbelieve\": 679,\n    \"Ġinclude\": 680,\n    \"Ġoil\": 681,\n    \"Ġrecently\": 682,\n    \"Ġonce\": 683,\n    \"Ġknown\": 684,\n    \"Ġlost\": 685,\n    \"Ġsure\": 686,\n    \"us\": 687,\n    \"Ġweeks\": 688,\n    \"Ġfood\": 689,\n    \"Ġreports\": 690,\n    \"Ġrating\": 691,\n    \"ĠMinister\": 692,\n    \"Ġwoman\": 693,\n    \"Ġprovide\": 694,\n    \"Ġproject\": 695,\n    \"Ġissue\": 696,\n    \"Ġlive\": 697,\n    \"10\": 698,\n    \"Ġclear\": 699,\n    \"he\": 700,\n    \"Ġcost\": 701,\n    \"Ġplayed\": 702,\n    \"Ġreleased\": 703,\n    \"Ġcoach\": 704,\n    \"v\": 705,\n    \"Ġ24\": 706,\n    \"Ġseven\": 707,\n    \"Ġplans\": 708,\n    \"Ġdevelopment\": 709,\n    \"ur\": 710,\n    \"ĺ\": 711,\n    \"Ġincrease\": 712,\n    \"This\": 713,\n    \"Ġpolicy\": 714,\n    \"Ġcent\": 715,\n    \"Ġbased\": 716,\n    \"E\": 717,\n    \"il\": 718,\n    \"ĠDecember\": 719,\n    \"Ġglobal\": 720,\n    \"Ġtrade\": 721,\n    \"Ġhours\": 722,\n    \"Ġhigher\": 723,\n    \"Ġgoal\": 724,\n    \"H\": 725,\n    \"ĠAl\": 726,\n    \"Ġ100\": 727,\n    \"Ġminutes\": 728,\n    \"Ġelection\": 729,\n    \"ĠAmerica\": 730,\n    \"Ġrate\": 731,\n    \"ĠCh\": 732,\n    \"Ġ21\": 733,\n    \"...\": 734,\n    \"ĠWhite\": 735,\n    \"Ġdirector\": 736,\n    \"Ġposition\": 737,\n    \"Ġshot\": 738,\n    \"Ġlarge\": 739,\n    \"Ġc\": 740,\n    \"Ġb\": 741,\n    \"]\": 742,\n    \"Ġissues\": 743,\n    \"Ġdeath\": 744,\n    \"Ġbuilding\": 745,\n    \"Ġtotal\": 746,\n    \"Ġoften\": 747,\n    \"Ġv\": 748,\n    \"Ġcountries\": 749,\n    \"Ġhistory\": 750,\n    \"Ġoutside\": 751,\n    \"Ġfederal\": 752,\n    \"Ġ19\": 753,\n    \"Ġfact\": 754,\n    \"ĠHigh\": 755,\n    \"Ġcareer\": 756,\n    \"im\": 757,\n    \"Ġinternational\": 758,\n    \"ĠNovember\": 759,\n    \"Ġfront\": 760,\n    \"Ġkind\": 761,\n    \"Ġkey\": 762,\n    \"ra\": 763,\n    \"ĠSan\": 764,\n    \"Ġshort\": 765,\n    \"Ġname\": 766,\n    \"ĠAccording\": 767,\n    \"Ġcourse\": 768,\n    \"Ġre\": 769,\n    \"Ġwanted\": 770,\n    \"W\": 771,\n    \"ĠSeptember\": 772,\n    \"Ġinterest\": 773,\n    \"Ġrole\": 774,\n    \"Ġresults\": 775,\n    \"Ġeconomic\": 776,\n    \"Ġ2014\": 777,\n    \"Ġchance\": 778,\n    \"ĠOctober\": 779,\n    \"Ġspecial\": 780,\n    \"Ġofficial\": 781,\n    \"Ġneeds\": 782,\n    \"um\": 783,\n    \"Ġl\": 784,\n    \"Ġproducts\": 785,\n    \"Ġnon\": 786,\n    \"Ġ@\": 787,\n    \"ĠBank\": 788,\n    \"Ġahead\": 789,\n    \"Ġhouse\": 790,\n    \"U\": 791,\n    \"Ġboard\": 792,\n    \"Ġold\": 793,\n    \"Ġsaw\": 794,\n    \"Ġlower\": 795,\n    \"ĠEuropean\": 796,\n    \"Ġcontrol\": 797,\n    \"ĠRussia\": 798,\n    \"Ġeight\": 799,\n    \"Ġrelease\": 800,\n    \"Ġpotential\": 801,\n    \"Ġthought\": 802,\n    \"Ġinvestigation\": 803,\n    \"Ġonline\": 804,\n    \"based\": 805,\n    \"Ġtechnology\": 806,\n    \"ĠDonald\": 807,\n    \"id\": 808,\n    \"Ġbody\": 809,\n    \"Ġrisk\": 810,\n    \"ian\": 811,\n    \"Ġcapital\": 812,\n    \"Ġstaff\": 813,\n    \"Ġaction\": 814,\n    \"ĠLeague\": 815,\n    \"Ġplaying\": 816,\n    \"Ġmakes\": 817,\n    \"Ġalmost\": 818,\n    \"Ġperformance\": 819,\n    \"Ġ22\": 820,\n    \"Ġg\": 821,\n    \"Ġfilm\": 822,\n    \"Ġnearly\": 823,\n    \"ĠCenter\": 824,\n    \"Ġvisit\": 825,\n    \"ĠGroup\": 826,\n    \"Ġbank\": 827,\n    \"Ġbit\": 828,\n    \"Ġreceived\": 829,\n    \"ĠAugust\": 830,\n    \"Ġmilitary\": 831,\n    \"ĠHis\": 832,\n    \"ine\": 833,\n    \"Ġchief\": 834,\n    \"ĠSchool\": 835,\n    \"Ġbring\": 836,\n    \"ĠCourt\": 837,\n    \"Ġ(@\": 838,\n    \"Ġmeans\": 839,\n    \"ĠSh\": 840,\n    \"Ġfans\": 841,\n    \"Ġse\": 842,\n    \"Ġ40\": 843,\n    \"20\": 844,\n    \"\\\".\": 845,\n    \"V\": 846,\n    \"Ġcut\": 847,\n    \"Ġkilled\": 848,\n    \"Ġ#\": 849,\n    \"Ġprices\": 850,\n    \"Ġgave\": 851,\n    \"ĠStreet\": 852,\n    \"ir\": 853,\n    \"ĠY\": 854,\n    \"Ġcurrently\": 855,\n    \"Ġf\": 856,\n    \"ay\": 857,\n    \"ne\": 858,\n    \"te\": 859,\n    \"Ġtry\": 860,\n    \"ĠPark\": 861,\n    \"ĥ\": 862,\n    \"J\": 863,\n    \"Ġquestion\": 864,\n    \"Ġhand\": 865,\n    \"Ġeconomy\": 866,\n    \"Ġinvestors\": 867,\n    \"able\": 868,\n    \"Ġplayer\": 869,\n    \"ĠBy\": 870,\n    \"ĠDavid\": 871,\n    \"Ġloss\": 872,\n    \"ab\": 873,\n    \"Ġbelow\": 874,\n    \"Ġwrote\": 875,\n    \"co\": 876,\n    \"ate\": 877,\n    \"Ġrunning\": 878,\n    \"un\": 879,\n    \"Ġbegan\": 880,\n    \"Ġsingle\": 881,\n    \"Ġfield\": 882,\n    \"Ġ23\": 883,\n    \"Ġleader\": 884,\n    \"Ġw\": 885,\n    \"ĠCalifornia\": 886,\n    \"Ġfourth\": 887,\n    \"Ġactually\": 888,\n    \"Ġlist\": 889,\n    \"ll\": 890,\n    \"Ġcouple\": 891,\n    \"Ġstudy\": 892,\n    \"Ġteams\": 893,\n    \"He\": 894,\n    \"ah\": 895,\n    \"ĠCanada\": 896,\n    \"Ġla\": 897,\n    \"Ġresult\": 898,\n    \"Ġaccess\": 899,\n    \"Ġvote\": 900,\n    \"ĠMore\": 901,\n    \"ĠFebruary\": 902,\n    \"Ġrevenue\": 903,\n    \"Ġoffer\": 904,\n    \"Ġlet\": 905,\n    \"ier\": 906,\n    \"Ġbuy\": 907,\n    \"Ġattack\": 908,\n    \"Ġblack\": 909,\n    \"Ġr\": 910,\n    \"Ġareas\": 911,\n    \"Ġstop\": 912,\n    \"Ġimpact\": 913,\n    \"Ġmatch\": 914,\n    \"Ġinvestment\": 915,\n    \"Ġcustomers\": 916,\n    \"Ġleaders\": 917,\n    \"ies\": 918,\n    \"Ġmember\": 919,\n    \"Ġchild\": 920,\n    \"Ġroad\": 921,\n    \"ul\": 922,\n    \"Ġvalue\": 923,\n    \"Ġshows\": 924,\n    \"ĠDr\": 925,\n    \"ĠDe\": 926,\n    \"ant\": 927,\n    \"ĠLondon\": 928,\n    \"Ġroom\": 929,\n    \"Ġmusic\": 930,\n    \"Ġproduction\": 931,\n    \"Ġanything\": 932,\n    \"Ġfirm\": 933,\n    \"Ġbiggest\": 934,\n    \"Ġair\": 935,\n    \"Ġproblem\": 936,\n    \"Ġgeneral\": 937,\n    \"Ġwasn\": 938,\n    \"Ġi\": 939,\n    \"Ġprivate\": 940,\n    \"Ġespecially\": 941,\n    \"Ġadministration\": 942,\n    \"Ġadditional\": 943,\n    \"ĠCo\": 944,\n    \"Ġopportunity\": 945,\n    \"Ġhold\": 946,\n    \"&\": 947,\n    \"Ġmatter\": 948,\n    \"Ġsenior\": 949,\n    \"Ġclub\": 950,\n    \"Ġsomeone\": 951,\n    \"ĠÃ\": 952,\n    \"ĠEast\": 953,\n    \"Ġ2019\": 954,\n    \".'\": 955,\n    \"Ġneeded\": 956,\n    \"ĠJames\": 957,\n    \"time\": 958,\n    \"Ġhowever\": 959,\n    \"Ġeverything\": 960,\n    \"Ġeveryone\": 961,\n    \"Ġdied\": 962,\n    \"Ġinvolved\": 963,\n    \"Ġfriends\": 964,\n    \"Ġisn\": 965,\n    \"Ġworth\": 966,\n    \"ik\": 967,\n    \"ĠCup\": 968,\n    \"Ġshowed\": 969,\n    \"There\": 970,\n    \"Ġ28\": 971,\n    \"Ġmeet\": 972,\n    \"Ġ26\": 973,\n    \"Ġ27\": 974,\n    \"Y\": 975,\n    \"Ġregion\": 976,\n    \"ĠPress\": 977,\n    \"ĠNow\": 978,\n    \"Ġson\": 979,\n    \"Ġspace\": 980,\n    \"Ġleading\": 981,\n    \"Ġstates\": 982,\n    \"Ġweekend\": 983,\n    \"ĠÂ£\": 984,\n    \"Ġmother\": 985,\n    \"Ġprevious\": 986,\n    \"ĠUK\": 987,\n    \"ĠMichael\": 988,\n    \"Ġleave\": 989,\n    \"est\": 990,\n    \"em\": 991,\n    \"Ġz\": 992,\n    \"ĠSome\": 993,\n    \"ors\": 994,\n    \"out\": 995,\n    \"15\": 996,\n    \"Ġwar\": 997,\n    \"Ġwebsite\": 998,\n    \"Ġstar\": 999,\n    \"X\": 1000,\n    \"ro\": 1001,\n    \"Ġtarget\": 1002,\n    \"Ġhimself\": 1003,\n    \"Ġturn\": 1004,\n    \"ĠEurope\": 1005,\n    \"Ġworked\": 1006,\n    \"Ġenergy\": 1007,\n    \"Ġscored\": 1008,\n    \"Ġ*\": 1009,\n    \"Ġsoon\": 1010,\n    \"Ġball\": 1011,\n    \"ĠTV\": 1012,\n    \"Ġannual\": 1013,\n    \"Ġ2013\": 1014,\n    \"Ġrace\": 1015,\n    \"ĠInternational\": 1016,\n    \"'d\": 1017,\n    \"ĠMarket\": 1018,\n    \"Ġconference\": 1019,\n    \"io\": 1020,\n    \"Ġo\": 1021,\n    \"Ġchanges\": 1022,\n    \"ig\": 1023,\n    \"Ġofficers\": 1024,\n    \"Ġinside\": 1025,\n    \"Ġform\": 1026,\n    \"Ġpublished\": 1027,\n    \"Ġphone\": 1028,\n    \"Ġco\": 1029,\n    \"Ġlegal\": 1030,\n    \"Ġexecutive\": 1031,\n    \"Ġfight\": 1032,\n    \"ings\": 1033,\n    \"Ġhope\": 1034,\n    \"Ġsummer\": 1035,\n    \"Ġofficer\": 1036,\n    \"Ġfootball\": 1037,\n    \"Ġproperty\": 1038,\n    \"@\": 1039,\n    \"Ġbook\": 1040,\n    \"Ġparents\": 1041,\n    \"Ġcosts\": 1042,\n    \"ac\": 1043,\n    \"Ġmanager\": 1044,\n    \"Ġcreate\": 1045,\n    \"Ġage\": 1046,\n    \"Ġemail\": 1047,\n    \"Ġmarkets\": 1048,\n    \"Ġmain\": 1049,\n    \"Ġhuman\": 1050,\n    \"Ġsent\": 1051,\n    \"Ġmanagement\": 1052,\n    \"ĠDay\": 1053,\n    \"ton\": 1054,\n    \"Ġcash\": 1055,\n    \"Ġfocus\": 1056,\n    \"Ġexpect\": 1057,\n    \"Ġtraining\": 1058,\n    \"Ġbecame\": 1059,\n    \"Ġwhose\": 1060,\n    \"Ġevents\": 1061,\n    \"Ġround\": 1062,\n    \"ĠLe\": 1063,\n    \"Ġfell\": 1064,\n    \"Ġabove\": 1065,\n    \"Ġanalysts\": 1066,\n    \"Ġtalk\": 1067,\n    \"Ġsituation\": 1068,\n    \"ri\": 1069,\n    \"ated\": 1070,\n    \"ke\": 1071,\n    \"Ġwants\": 1072,\n    \"ag\": 1073,\n    \"Ġlives\": 1074,\n    \"om\": 1075,\n    \"Ġal\": 1076,\n    \"Ġdemand\": 1077,\n    \"Ġsafety\": 1078,\n    \"Ġrest\": 1079,\n    \"ĠCouncil\": 1080,\n    \"Ġpersonal\": 1081,\n    \"Ġsite\": 1082,\n    \"ĠRussian\": 1083,\n    \"Ġmid\": 1084,\n    \"Ġnothing\": 1085,\n    \"Ġwhole\": 1086,\n    \"Ġbill\": 1087,\n    \"Ġsold\": 1088,\n    \"ĠBritish\": 1089,\n    \"se\": 1090,\n    \"Ġremain\": 1091,\n    \"12\": 1092,\n    \"Ġforeign\": 1093,\n    \"Ġshooting\": 1094,\n    \"Ġstay\": 1095,\n    \"50\": 1096,\n    \"ang\": 1097,\n    \"Ġhospital\": 1098,\n    \"Ġbad\": 1099,\n    \"Ġaddress\": 1100,\n    \"ĠKorea\": 1101,\n    \"Ġhappened\": 1102,\n    \"Ġcharges\": 1103,\n    \"Ġwhite\": 1104,\n    \"Ġ31\": 1105,\n    \"If\": 1106,\n    \"Ġearnings\": 1107,\n    \"Ġbreak\": 1108,\n    \"Ġlight\": 1109,\n    \"Ġterms\": 1110,\n    \"ĠChinese\": 1111,\n    \"ĠSenate\": 1112,\n    \"ana\": 1113,\n    \"Ġidea\": 1114,\n    \"ap\": 1115,\n    \"of\": 1116,\n    \"Ġnine\": 1117,\n    \"Ġcompared\": 1118,\n    \"Ġbuild\": 1119,\n    \"ard\": 1120,\n    \"In\": 1121,\n    \"Ġsimilar\": 1122,\n    \"Ġgas\": 1123,\n    \"Ġvictory\": 1124,\n    \"Ġ2012\": 1125,\n    \"Ġdebt\": 1126,\n    \"ĠMar\": 1127,\n    \"Ġarrested\": 1128,\n    \"Ġcomment\": 1129,\n    \"Ġincreased\": 1130,\n    \"Ġmedical\": 1131,\n    \"Ġ29\": 1132,\n    \"ĠJan\": 1133,\n    \"Ġgroups\": 1134,\n    \"Ġdespite\": 1135,\n    \"Ġfall\": 1136,\n    \"Ġtell\": 1137,\n    \"Ġworkers\": 1138,\n    \"Ġtown\": 1139,\n    \"Ã©\": 1140,\n    \"Ġwife\": 1141,\n    \"Ġquestions\": 1142,\n    \"Ġcontinued\": 1143,\n    \"Ġheart\": 1144,\n    \"Ġmet\": 1145,\n    \"Ġbrought\": 1146,\n    \"Ġhelped\": 1147,\n    \"ĠCongress\": 1148,\n    \"Ġstep\": 1149,\n    \"Ġfather\": 1150,\n    \"Ġmoment\": 1151,\n    \"Ġproduct\": 1152,\n    \"Ġprobably\": 1153,\n    \"Ġlargest\": 1154,\n    \"Ġvehicle\": 1155,\n    \"ĠEngland\": 1156,\n    \"Ġallow\": 1157,\n    \"Ġstarting\": 1158,\n    \"Ġkids\": 1159,\n    \"Ġincident\": 1160,\n    \"Ġnet\": 1161,\n    \"Ġrates\": 1162,\n    \"ĠRead\": 1163,\n    \"Ġpressure\": 1164,\n    \"Ġincluded\": 1165,\n    \"Ġread\": 1166,\n    \"Ġissued\": 1167,\n    \"ol\": 1168,\n    \"Ġeither\": 1169,\n    \"Ġefforts\": 1170,\n    \"Ġincludes\": 1171,\n    \"ĠRepublican\": 1172,\n    \"ish\": 1173,\n    \"âĢ¦\": 1174,\n    \"Ġgoals\": 1175,\n    \"aj\": 1176,\n    \"Ġen\": 1177,\n    \"x\": 1178,\n    \"Ġraised\": 1179,\n    \"au\": 1180,\n    \"Ġlonger\": 1181,\n    \"ut\": 1182,\n    \"Ġwatch\": 1183,\n    \"ĠTexas\": 1184,\n    \"You\": 1185,\n    \"Ġrange\": 1186,\n    \"nd\": 1187,\n    \"Ġfunds\": 1188,\n    \"Ġremains\": 1189,\n    \"ĠMark\": 1190,\n    \"Ġ60\": 1191,\n    \"Ġque\": 1192,\n    \"sh\": 1193,\n    \"Ġinterview\": 1194,\n    \"Ġrather\": 1195,\n    \"Ġresidents\": 1196,\n    \"Ġgrowing\": 1197,\n    \"Ġpre\": 1198,\n    \"Ġpaid\": 1199,\n    \"Ġcases\": 1200,\n    \"ĠReuters\": 1201,\n    \"Ġdifficult\": 1202,\n    \"Ġsign\": 1203,\n    \"ĠGoogle\": 1204,\n    \"Ġhttps\": 1205,\n    \"ĠPaul\": 1206,\n    \"Ġliving\": 1207,\n    \"day\": 1208,\n    \"ĠQ\": 1209,\n    \"iz\": 1210,\n    \"ĠRed\": 1211,\n    \"Ġland\": 1212,\n    \"They\": 1213,\n    \"ĠRoad\": 1214,\n    \"_\": 1215,\n    \"ĠThese\": 1216,\n    \"Ġview\": 1217,\n    \"Ġagency\": 1218,\n    \"Ġreason\": 1219,\n    \"Ġallowed\": 1220,\n    \"ĠAustralia\": 1221,\n    \"az\": 1222,\n    \"ĠRe\": 1223,\n    \"Ġturned\": 1224,\n    \"11\": 1225,\n    \"Ġnation\": 1226,\n    \"Ġready\": 1227,\n    \"Ġpress\": 1228,\n    \"Ġbudget\": 1229,\n    \"Ġdaily\": 1230,\n    \"ĠChief\": 1231,\n    \"Ġfamilies\": 1232,\n    \"Ġsignificant\": 1233,\n    \"ĠFirst\": 1234,\n    \"Ġthemselves\": 1235,\n    \"Ġj\": 1236,\n    \"Ġruns\": 1237,\n    \"Ġaccused\": 1238,\n    \"Ġtakes\": 1239,\n    \"Ġspent\": 1240,\n    \"Ġvia\": 1241,\n    \"ot\": 1242,\n    \"ina\": 1243,\n    \"25\": 1244,\n    \"land\": 1245,\n    \"Ġexample\": 1246,\n    \"Ġauthorities\": 1247,\n    \"Ġdate\": 1248,\n    \"Ġended\": 1249,\n    \"all\": 1250,\n    \"Reuters\": 1251,\n    \"Ġbusinesses\": 1252,\n    \"ans\": 1253,\n    \"Ġdetails\": 1254,\n    \"Ġground\": 1255,\n    \"Ġpretty\": 1256,\n    \"ĠApple\": 1257,\n    \"ation\": 1258,\n    \"ĠSmith\": 1259,\n    \"ĠCompany\": 1260,\n    \"ĠFlorida\": 1261,\n    \"Ġdrug\": 1262,\n    \"Ġresponse\": 1263,\n    \"one\": 1264,\n    \"Ġeducation\": 1265,\n    \"Ġmean\": 1266,\n    \"Ġleague\": 1267,\n    \"Ġanyone\": 1268,\n    \"Ġminister\": 1269,\n    \"Ġtitle\": 1270,\n    \"Ġadding\": 1271,\n    \"Ġproblems\": 1272,\n    \"Ġopening\": 1273,\n    \"Ġconditions\": 1274,\n    \"Ġred\": 1275,\n    \"Ġdecided\": 1276,\n    \"Å\": 1277,\n    \"Ġposted\": 1278,\n    \"term\": 1279,\n    \"Ġamount\": 1280,\n    \"ĠEU\": 1281,\n    \"Ġsuccess\": 1282,\n    \"Ġevidence\": 1283,\n    \"ĠObama\": 1284,\n    \"Ġaddition\": 1285,\n    \"Ġprovided\": 1286,\n    \"ĠLos\": 1287,\n    \"Ġagreement\": 1288,\n    \"Ġstage\": 1289,\n    \"ens\": 1290,\n    \"Ġrelationship\": 1291,\n    \"ĠGeneral\": 1292,\n    \"Ġsector\": 1293,\n    \"Ġstudent\": 1294,\n    \"ating\": 1295,\n    \"Ġtest\": 1296,\n    \"\\\",\": 1297,\n    \"Ġwinning\": 1298,\n    \"Ġfelt\": 1299,\n    \"Ġsource\": 1300,\n    \"Z\": 1301,\n    \"Ġseems\": 1302,\n    \"Ġcause\": 1303,\n    \"Ġschools\": 1304,\n    \"Ġdrive\": 1305,\n    \"Ġensure\": 1306,\n    \"Ġhuge\": 1307,\n    \"ĠMy\": 1308,\n    \"ĠHealth\": 1309,\n    \"Ġscene\": 1310,\n    \"Ġgiving\": 1311,\n    \"Ġcenter\": 1312,\n    \"Ġpositive\": 1313,\n    \"Ġyards\": 1314,\n    \"Ġjobs\": 1315,\n    \"Ġaccount\": 1316,\n    \"Ġheard\": 1317,\n    \"Ġquality\": 1318,\n    \"Ġways\": 1319,\n    \"Ġimmediately\": 1320,\n    \"Ġemployees\": 1321,\n    \"are\": 1322,\n    \"Ġpass\": 1323,\n    \"ĠCEO\": 1324,\n    \"Ġreceive\": 1325,\n    \"Ġlooks\": 1326,\n    \"ĠAfrica\": 1327,\n    \"Ġthroughout\": 1328,\n    \"led\": 1329,\n    \"Ġrelated\": 1330,\n    \"Ġsell\": 1331,\n    \"ĠUnion\": 1332,\n    \"ĠPhoto\": 1333,\n    \"ter\": 1334,\n    \"Ġquickly\": 1335,\n    \"ĠHow\": 1336,\n    \"Ġvarious\": 1337,\n    \"Ġreach\": 1338,\n    \"Ġpick\": 1339,\n    \"Ġcharged\": 1340,\n    \"Ġquite\": 1341,\n    \"ent\": 1342,\n    \"q\": 1343,\n    \"ins\": 1344,\n    \"Ġphoto\": 1345,\n    \"Ġunderstand\": 1346,\n    \"ĠâĢ¢\": 1347,\n    \"Ġreached\": 1348,\n    \"Ġtrack\": 1349,\n    \"uk\": 1350,\n    \"Ġeffort\": 1351,\n    \"ville\": 1352,\n    \"Ġcentral\": 1353,\n    \"Ġdaughter\": 1354,\n    \"Ġcontract\": 1355,\n    \"Ġinjury\": 1356,\n    \"Ġopened\": 1357,\n    \"Ġ($\": 1358,\n    \"Ġstraight\": 1359,\n    \"17\": 1360,\n    \"Ġcredit\": 1361,\n    \"ĠIndian\": 1362,\n    \"Ġsexual\": 1363,\n    \"Ġworks\": 1364,\n    \"Ġeasy\": 1365,\n    \"18\": 1366,\n    \"Ġclosed\": 1367,\n    \"Ġh\": 1368,\n    \"Ġhappen\": 1369,\n    \"Ġforce\": 1370,\n    \"ler\": 1371,\n    \"Ġhappy\": 1372,\n    \"Ġshared\": 1373,\n    \"Ġoverall\": 1374,\n    \"Ġmoving\": 1375,\n    \"á\": 1376,\n    \"Ġprojects\": 1377,\n    \"ĠBlack\": 1378,\n    \"Ġconcerns\": 1379,\n    \"Ġclass\": 1380,\n    \"Ġtried\": 1381,\n    \"Ġappeared\": 1382,\n    \"Ġcontent\": 1383,\n    \"ĠDistrict\": 1384,\n    \"Ġterm\": 1385,\n    \"Ġinstead\": 1386,\n    \"ĠOffice\": 1387,\n    \"Ġcontinues\": 1388,\n    \"Ġlevels\": 1389,\n    \"Ġafternoon\": 1390,\n    \"Ġfund\": 1391,\n    \"Ġsale\": 1392,\n    \"Ġdriver\": 1393,\n    \"Ġask\": 1394,\n    \"Ġcannot\": 1395,\n    \"ner\": 1396,\n    \"end\": 1397,\n    \"ĠHere\": 1398,\n    \"field\": 1399,\n    \"Ġstore\": 1400,\n    \"www\": 1401,\n    \"Ġcertain\": 1402,\n    \"Ġself\": 1403,\n    \"Ġdollar\": 1404,\n    \"ĠHer\": 1405,\n    \"Ġpopular\": 1406,\n    \"Ġfollow\": 1407,\n    \"Ġspending\": 1408,\n    \"by\": 1409,\n    \"Ġmoved\": 1410,\n    \"Ġgoes\": 1411,\n    \"Ġcreated\": 1412,\n    \"Ġstand\": 1413,\n    \"Ġoperations\": 1414,\n    \"Ġlooked\": 1415,\n    \"Ġtreatment\": 1416,\n    \"ov\": 1417,\n    \"Ġdistrict\": 1418,\n    \"Ġsigned\": 1419,\n    \"Ġhands\": 1420,\n    \"Ġmodel\": 1421,\n    \"ĠAngeles\": 1422,\n    \"Ġy\": 1423,\n    \"Ġborder\": 1424,\n    \"Ġincome\": 1425,\n    \"ĠLast\": 1426,\n    \"Ġcharge\": 1427,\n    \"Ġdriving\": 1428,\n    \"ĠJapan\": 1429,\n    \"Ġrise\": 1430,\n    \"Ġtalks\": 1431,\n    \"Ġfollowed\": 1432,\n    \"Ġpreviously\": 1433,\n    \"Ġusers\": 1434,\n    \"Ġfunding\": 1435,\n    \"ĠJohnson\": 1436,\n    \"Ġ\": 1437,\n    \"ou\": 1438,\n    \"ai\": 1439,\n    \"Ġnamed\": 1440,\n    \"Ġfriend\": 1441,\n    \"ĠNov\": 1442,\n    \"Ġdefense\": 1443,\n    \"ĠBritain\": 1444,\n    \"Ġentire\": 1445,\n    \"Ġtrading\": 1446,\n    \"Ġfailed\": 1447,\n    \"ĠEl\": 1448,\n    \"Ġclaims\": 1449,\n    \"Ġcomments\": 1450,\n    \"Ġbeat\": 1451,\n    \"ib\": 1452,\n    \"Ġbasis\": 1453,\n    \"ĠJones\": 1454,\n    \"Ġpresent\": 1455,\n    \"ĠBe\": 1456,\n    \"Ġdouble\": 1457,\n    \"Ġrose\": 1458,\n    \"ite\": 1459,\n    \"Ġability\": 1460,\n    \"Ġoriginal\": 1461,\n    \"Ġdead\": 1462,\n    \"ĠCommission\": 1463,\n    \"ĠMe\": 1464,\n    \"Ġcompetition\": 1465,\n    \"Ġ2011\": 1466,\n    \"Ġknew\": 1467,\n    \"Ġmaterial\": 1468,\n    \"av\": 1469,\n    \"ĠFrance\": 1470,\n    \"Ġscore\": 1471,\n    \"Ġsense\": 1472,\n    \"Ġserious\": 1473,\n    \"Ġconfirmed\": 1474,\n    \"Ġanti\": 1475,\n    \"Ġviolence\": 1476,\n    \"Ġimprove\": 1477,\n    \"son\": 1478,\n    \"Ã³\": 1479,\n    \"ĠAP\": 1480,\n    \"Ġsh\": 1481,\n    \"Ġhost\": 1482,\n    \"ĠMike\": 1483,\n    \"Ġpatients\": 1484,\n    \"ĠNFL\": 1485,\n    \"Ġcrisis\": 1486,\n    \"Ġrevealed\": 1487,\n    \"ach\": 1488,\n    \"ĠPrime\": 1489,\n    \"Ġbuilt\": 1490,\n    \"ĠNot\": 1491,\n    \"Ġrules\": 1492,\n    \"Ġelse\": 1493,\n    \"Ġdepartment\": 1494,\n    \"Ġitself\": 1495,\n    \"ise\": 1496,\n    \"500\": 1497,\n    \"Ġcomplete\": 1498,\n    \"ion\": 1499,\n    \"Ġtrial\": 1500,\n    \"ĠBay\": 1501,\n    \"ĠDec\": 1502,\n    \"Ġattention\": 1503,\n    \"Ġtravel\": 1504,\n    \"ĠCentral\": 1505,\n    \"ry\": 1506,\n    \"Ġagreed\": 1507,\n    \"Ġmind\": 1508,\n    \"ĠMc\": 1509,\n    \"Ġ70\": 1510,\n    \"Ġcontact\": 1511,\n    \"ari\": 1512,\n    \"ĠTimes\": 1513,\n    \"Ġspot\": 1514,\n    \"ĠFrench\": 1515,\n    \"Ġgets\": 1516,\n    \"op\": 1517,\n    \"Ġbrand\": 1518,\n    \"Ġcalls\": 1519,\n    \"Ġbanks\": 1520,\n    \"Ġdesign\": 1521,\n    \"Ġsafe\": 1522,\n    \"Ġoffers\": 1523,\n    \"Ġpractice\": 1524,\n    \"ĠOf\": 1525,\n    \"Ã¡\": 1526,\n    \"ling\": 1527,\n    \"Ġtrue\": 1528,\n    \"off\": 1529,\n    \"Ġnumbers\": 1530,\n    \"Ġfun\": 1531,\n    \"Ġlearn\": 1532,\n    \"Ġmultiple\": 1533,\n    \"ĠIs\": 1534,\n    \"res\": 1535,\n    \"als\": 1536,\n    \"Ġcommon\": 1537,\n    \"ized\": 1538,\n    \"Ġchallenge\": 1539,\n    \"Ġcommittee\": 1540,\n    \"ĠOur\": 1541,\n    \"Ġbase\": 1542,\n    \"ani\": 1543,\n    \"ĠAssociation\": 1544,\n    \"ung\": 1545,\n    \"Ġnetwork\": 1546,\n    \"ĠBrown\": 1547,\n    \"Ġapproach\": 1548,\n    \"16\": 1549,\n    \"Ġfinished\": 1550,\n    \"Ġreview\": 1551,\n    \"Ġrequired\": 1552,\n    \"Ġapp\": 1553,\n    \"ĠMan\": 1554,\n    \"ĠâĢ¦\": 1555,\n    \"twitter\": 1556,\n    \"ĠDemocratic\": 1557,\n    \"13\": 1558,\n    \"Ġevening\": 1559,\n    \"ĠTom\": 1560,\n    \"Ã¤\": 1561,\n    \"ĠAssociated\": 1562,\n    \"ĠCanadian\": 1563,\n    \"Ġcollege\": 1564,\n    \"Ġspokesman\": 1565,\n    \"Ġarticle\": 1566,\n    \"Ġtowards\": 1567,\n    \"ĠChicago\": 1568,\n    \"Ġmovie\": 1569,\n    \"14\": 1570,\n    \"ity\": 1571,\n    \"Ġforces\": 1572,\n    \"ĠChris\": 1573,\n    \"ĠDemocrats\": 1574,\n    \"Ġfeatures\": 1575,\n    \"Ġhearing\": 1576,\n    \"ĠX\": 1577,\n    \"ĠAlso\": 1578,\n    \"Ġmessage\": 1579,\n    \"age\": 1580,\n    \"Ġnoted\": 1581,\n    \"ĠSuper\": 1582,\n    \"Ġthousands\": 1583,\n    \"aw\": 1584,\n    \"ĠBill\": 1585,\n    \"ĠAr\": 1586,\n    \"ĠLa\": 1587,\n    \"ip\": 1588,\n    \"Ġ/\": 1589,\n    \"ĠDuring\": 1590,\n    \"Ġnote\": 1591,\n    \".)\": 1592,\n    \"Ġwrong\": 1593,\n    \"if\": 1594,\n    \"Ġpassed\": 1595,\n    \"ĠTwo\": 1596,\n    \"Ġdie\": 1597,\n    \",'\": 1598,\n    \"ĠDon\": 1599,\n    \"ĠGermany\": 1600,\n    \"Ġletter\": 1601,\n    \"Ġdescribed\": 1602,\n    \"ĠIran\": 1603,\n    \"ĠWilliams\": 1604,\n    \"Ġparticularly\": 1605,\n    \"Ġadd\": 1606,\n    \"Ġconversation\": 1607,\n    \"ĠSe\": 1608,\n    \"Ġhighest\": 1609,\n    \"be\": 1610,\n    \"Ġhomes\": 1611,\n    \"Ġsports\": 1612,\n    \"Ġgone\": 1613,\n    \"ĠAd\": 1614,\n    \"Ġel\": 1615,\n    \"Ġopportunities\": 1616,\n    \"Ġwords\": 1617,\n    \"Ġleaving\": 1618,\n    \"ĠChristmas\": 1619,\n    \"As\": 1620,\n    \"ĠGovernment\": 1621,\n    \"Ġsimply\": 1622,\n    \"Ġhusband\": 1623,\n    \"ĠResearch\": 1624,\n    \"ĠMexico\": 1625,\n    \"ates\": 1626,\n    \"ale\": 1627,\n    \"ĠGreen\": 1628,\n    \"$\": 1629,\n    \"od\": 1630,\n    \"ĠHall\": 1631,\n    \"Ġnatural\": 1632,\n    \"Ġoperating\": 1633,\n    \"les\": 1634,\n    \"ations\": 1635,\n    \"ĠKim\": 1636,\n    \"Ġgold\": 1637,\n    \"ok\": 1638,\n    \"Ġprovides\": 1639,\n    \"(\": 1640,\n    \"ell\": 1641,\n    \"Ġbegin\": 1642,\n    \"ĠParty\": 1643,\n    \"back\": 1644,\n    \"ĠAmazon\": 1645,\n    \"19\": 1646,\n    \"Ġmajority\": 1647,\n    \"ĠEven\": 1648,\n    \"Ġcheck\": 1649,\n    \"Ġweather\": 1650,\n    \"Ġorganization\": 1651,\n    \"Ġstories\": 1652,\n    \"ĠCar\": 1653,\n    \"Ġforced\": 1654,\n    \"ĠGeorge\": 1655,\n    \"Ġwalk\": 1656,\n    \"ong\": 1657,\n    \"Ġfiled\": 1658,\n    \"ĠJustice\": 1659,\n    \"Ġlaunched\": 1660,\n    \"Ġoffered\": 1661,\n    \"Ġwww\": 1662,\n    \"Ġconstruction\": 1663,\n    \"ĠBen\": 1664,\n    \"Ġserved\": 1665,\n    \"Ġ...\": 1666,\n    \"Ġparts\": 1667,\n    \"Ġcancer\": 1668,\n    \"Ġguys\": 1669,\n    \"Reporting\": 1670,\n    \"ash\": 1671,\n    \"less\": 1672,\n    \"Ġleadership\": 1673,\n    \"ĠCommittee\": 1674,\n    \"Ġregular\": 1675,\n    \"Ġcouncil\": 1676,\n    \"Ġcars\": 1677,\n    \"ĠDirector\": 1678,\n    \"Ġjudge\": 1679,\n    \"Ġvictims\": 1680,\n    \"ĠDaily\": 1681,\n    \"Ġkept\": 1682,\n    \"Ġeffect\": 1683,\n    \"Ġbeyond\": 1684,\n    \"pm\": 1685,\n    \"Ġtalking\": 1686,\n    \"Ġconsidered\": 1687,\n    \"ore\": 1688,\n    \"ĠAdvertisement\": 1689,\n    \"Ġst\": 1690,\n    \"ED\": 1691,\n    \"Ġmiddle\": 1692,\n    \"Ġraise\": 1693,\n    \"we\": 1694,\n    \"Ġclaimed\": 1695,\n    \"ino\": 1696,\n    \"Ġalleged\": 1697,\n    \"ĠPro\": 1698,\n    \"ĠScott\": 1699,\n    \"ĠOct\": 1700,\n    \"Ġconsider\": 1701,\n    \"ĠShare\": 1702,\n    \"Ġtraffic\": 1703,\n    \"ĠAfrican\": 1704,\n    \"Ġcouldn\": 1705,\n    \"Ġtoward\": 1706,\n    \"Ġsearch\": 1707,\n    \"But\": 1708,\n    \"Ġlaunch\": 1709,\n    \"Ġinjured\": 1710,\n    \"That\": 1711,\n    \"Ġalthough\": 1712,\n    \"Ġactivities\": 1713,\n    \"Ġchanged\": 1714,\n    \"Ġsources\": 1715,\n    \"Ġmissing\": 1716,\n    \"Ġu\": 1717,\n    \"Ġ35\": 1718,\n    \"Ġcover\": 1719,\n    \"ised\": 1720,\n    \"Ġ|\": 1721,\n    \"ow\": 1722,\n    \"ES\": 1723,\n    \"Ġdecades\": 1724,\n    \"ich\": 1725,\n    \"Ġcaused\": 1726,\n    \"Ġelections\": 1727,\n    \"ane\": 1728,\n    \"IS\": 1729,\n    \"Ġfeet\": 1730,\n    \"ĠBar\": 1731,\n    \"Ġversion\": 1732,\n    \"Ġgrow\": 1733,\n    \"Ġvehicles\": 1734,\n    \"Ġoptions\": 1735,\n    \"Ġindividual\": 1736,\n    \"Ġenvironment\": 1737,\n    \"ĠRobert\": 1738,\n    \"ĠValley\": 1739,\n    \"ĠFrom\": 1740,\n    \"per\": 1741,\n    \"ara\": 1742,\n    \"Ġsystems\": 1743,\n    \"Ġprotect\": 1744,\n    \"ĠKing\": 1745,\n    \"Ġinjuries\": 1746,\n    \"Ġfinally\": 1747,\n    \"Ġnuclear\": 1748,\n    \"40\": 1749,\n    \"Ġratio\": 1750,\n    \"Ġgun\": 1751,\n    \"ĠPakistan\": 1752,\n    \"ĠManagement\": 1753,\n    \"ĠAir\": 1754,\n    \"ce\": 1755,\n    \"Ġopposition\": 1756,\n    \"ment\": 1757,\n    \"ick\": 1758,\n    \"Ġpro\": 1759,\n    \"Ġact\": 1760,\n    \"Ġplatform\": 1761,\n    \"Ġlack\": 1762,\n    \"Ġpair\": 1763,\n    \"Ġ500\": 1764,\n    \"Ġcalling\": 1765,\n    \"ary\": 1766,\n    \"Ġprograms\": 1767,\n    \"Ġscheduled\": 1768,\n    \"Ġfast\": 1769,\n    \"Ġjoined\": 1770,\n    \"ĠWar\": 1771,\n    \"ĠEditing\": 1772,\n    \"ĠSince\": 1773,\n    \"ĠRyan\": 1774,\n    \"ĠMac\": 1775,\n    \"ĠBig\": 1776,\n    \"ĠLake\": 1777,\n    \"Ġdigital\": 1778,\n    \"When\": 1779,\n    \"ue\": 1780,\n    \"Ġassets\": 1781,\n    \"Ġseeing\": 1782,\n    \"ĠAct\": 1783,\n    \"Ġpartner\": 1784,\n    \"ĠBoard\": 1785,\n    \"Ġbeginning\": 1786,\n    \"Ġsupply\": 1787,\n    \"Ġmiles\": 1788,\n    \"Ġprison\": 1789,\n    \"ons\": 1790,\n    \"ĠAmericans\": 1791,\n    \"ub\": 1792,\n    \"ĠOr\": 1793,\n    \"me\": 1794,\n    \"Ġbenefits\": 1795,\n    \"Ġbenefit\": 1796,\n    \"Ġmeasures\": 1797,\n    \"Ġhear\": 1798,\n    \"Ġparties\": 1799,\n    \"Ġsuccessful\": 1800,\n    \"ĠJust\": 1801,\n    \"Ġvictim\": 1802,\n    \"Ġblock\": 1803,\n    \"Ġlimited\": 1804,\n    \"Ġtrip\": 1805,\n    \"ĠPeople\": 1806,\n    \"Ġserve\": 1807,\n    \"Ġart\": 1808,\n    \"ism\": 1809,\n    \"Ġwide\": 1810,\n    \"ĠSch\": 1811,\n    \"Ġ80\": 1812,\n    \"ĠThomas\": 1813,\n    \"Ġ90\": 1814,\n    \"Ġstocks\": 1815,\n    \"Ġgirl\": 1816,\n    \"ĠAsia\": 1817,\n    \"Ġseeking\": 1818,\n    \"Ġcertainly\": 1819,\n    \"ĠServices\": 1820,\n    \"ĠCollege\": 1821,\n    \"Ġcommunities\": 1822,\n    \"Ġextra\": 1823,\n    \"Ġ2010\": 1824,\n    \"ness\": 1825,\n    \"Ġholding\": 1826,\n    \"ous\": 1827,\n    \"Ġtough\": 1828,\n    \"ade\": 1829,\n    \"Ġmobile\": 1830,\n    \"Ġowns\": 1831,\n    \"ĠDo\": 1832,\n    \"ĠFire\": 1833,\n    \"Ġspoke\": 1834,\n    \"Ġreturned\": 1835,\n    \"Ġsize\": 1836,\n    \"Ġcriminal\": 1837,\n    \"ĠInstagram\": 1838,\n    \"Ġoffering\": 1839,\n    \"ĠGod\": 1840,\n    \"ĠService\": 1841,\n    \"Ġpage\": 1842,\n    \"her\": 1843,\n    \"Ġdeep\": 1844,\n    \"wood\": 1845,\n    \"Ġcrime\": 1846,\n    \"ĠSports\": 1847,\n    \"ile\": 1848,\n    \"ĠGlobal\": 1849,\n    \"Ġproposed\": 1850,\n    \"ain\": 1851,\n    \"Ġsession\": 1852,\n    \"ĠFederal\": 1853,\n    \"ĠSyria\": 1854,\n    \"Ġch\": 1855,\n    \"Ġthreat\": 1856,\n    \"Ġallegations\": 1857,\n    \"ĠRepublicans\": 1858,\n    \"ĠGerman\": 1859,\n    \"Ġstrategy\": 1860,\n    \"Ġcommercial\": 1861,\n    \"ING\": 1862,\n    \"ĠSecretary\": 1863,\n    \"Q\": 1864,\n    \"Ġreporters\": 1865,\n    \"100\": 1866,\n    \"ĠCapital\": 1867,\n    \"ĠBoth\": 1868,\n    \"ĠPost\": 1869,\n    \"ĠIsrael\": 1870,\n    \"Ġsave\": 1871,\n    \"ts\": 1872,\n    \"ill\": 1873,\n    \"Ġdrop\": 1874,\n    \"Ġreserved\": 1875,\n    \"ĠMany\": 1876,\n    \"Ġavoid\": 1877,\n    \"Ġ200\": 1878,\n    \"iv\": 1879,\n    \"Ġdamage\": 1880,\n    \"Ġcondition\": 1881,\n    \"Ġdropped\": 1882,\n    \"Ġdoor\": 1883,\n    \"Ġplanning\": 1884,\n    \"ire\": 1885,\n    \"Ġcard\": 1886,\n    \"Ġdesigned\": 1887,\n    \"Ġreduce\": 1888,\n    \"AN\": 1889,\n    \"ĠUn\": 1890,\n    \"ford\": 1891,\n    \"ĠThen\": 1892,\n    \"Ġpic\": 1893,\n    \"ĠCopyright\": 1894,\n    \"Ġrain\": 1895,\n    \"ĠMartin\": 1896,\n    \"Ġdomestic\": 1897,\n    \"45\": 1898,\n    \"ge\": 1899,\n    \"Ġmurder\": 1900,\n    \"Ġspeech\": 1901,\n    \"line\": 1902,\n    \"Ġhelping\": 1903,\n    \"Ġplanned\": 1904,\n    \"Ġfeature\": 1905,\n    \"ud\": 1906,\n    \"Ġtype\": 1907,\n    \"ham\": 1908,\n    \"ĠPublic\": 1909,\n    \"ja\": 1910,\n    \"Ġinsurance\": 1911,\n    \"Ġattacks\": 1912,\n    \"ĠCorp\": 1913,\n    \"Ġforecast\": 1914,\n    \"Ġresources\": 1915,\n    \"ma\": 1916,\n    \"?\\\"\": 1917,\n    \"ĠAm\": 1918,\n    \"ĠSept\": 1919,\n    \"Ġpush\": 1920,\n    \"Ġattorney\": 1921,\n    \"23\": 1922,\n    \"Ġemergency\": 1923,\n    \"Ġwinner\": 1924,\n    \"Ġblood\": 1925,\n    \"Ġnorth\": 1926,\n    \"ĠFeb\": 1927,\n    \"Ġbaby\": 1928,\n    \"Ġfloor\": 1929,\n    \"Ġspend\": 1930,\n    \"Ġex\": 1931,\n    \"Ġdollars\": 1932,\n    \"Ġunit\": 1933,\n    \"ĠHill\": 1934,\n    \"Ġder\": 1935,\n    \"ĠAbout\": 1936,\n    \"Ġalone\": 1937,\n    \"ization\": 1938,\n    \"Ġpresidential\": 1939,\n    \"Ġactivity\": 1940,\n    \"ĠTHE\": 1941,\n    \"ee\": 1942,\n    \"ber\": 1943,\n    \"ĠOther\": 1944,\n    \"Ġowner\": 1945,\n    \"Ġhour\": 1946,\n    \"Ġcities\": 1947,\n    \"Ġanswer\": 1948,\n    \"ide\": 1949,\n    \"Ġfully\": 1950,\n    \"ek\": 1951,\n    \"ists\": 1952,\n    \"Ġcoverage\": 1953,\n    \"Ġvs\": 1954,\n    \"Ġfigure\": 1955,\n    \"Ġpopulation\": 1956,\n    \"org\": 1957,\n    \"Ġsnow\": 1958,\n    \"Ġbecoming\": 1959,\n    \"ĠSam\": 1960,\n    \"ĠCarolina\": 1961,\n    \"Ġjoin\": 1962,\n    \"Ġprofit\": 1963,\n    \"Ġitems\": 1964,\n    \"Ġindex\": 1965,\n    \"Ġanalysis\": 1966,\n    \"Ġtournament\": 1967,\n    \"Ġstake\": 1968,\n    \"Ġperfect\": 1969,\n    \"way\": 1970,\n    \"Ġband\": 1971,\n    \"Ġgirls\": 1972,\n    \"Ġoption\": 1973,\n    \"Ġplays\": 1974,\n    \"oc\": 1975,\n    \"Ġproviding\": 1976,\n    \"ÃŃ\": 1977,\n    \"24\": 1978,\n    \"Ġwouldn\": 1979,\n    \"Ġones\": 1980,\n    \"Ġdeclined\": 1981,\n    \"Ġwritten\": 1982,\n    \"Ġvoters\": 1983,\n    \"Ġcandidate\": 1984,\n    \"Ġsuspect\": 1985,\n    \"Ġpolicies\": 1986,\n    \"Ġpeace\": 1987,\n    \"ast\": 1988,\n    \"Ġparticular\": 1989,\n    \"for\": 1990,\n    \"Ġhopes\": 1991,\n    \"Ġstation\": 1992,\n    \"ĠMost\": 1993,\n    \"Ġspeak\": 1994,\n    \"ĠRiver\": 1995,\n    \"Ġasking\": 1996,\n    \"Ġstatements\": 1997,\n    \"Ġfifth\": 1998,\n    \"ha\": 1999,\n    \"ĠNigeria\": 2000,\n    \"af\": 2001,\n    \"Ġexplained\": 2002,\n    \"Ġbar\": 2003,\n    \"Ġhousing\": 2004,\n    \"ĠSanta\": 2005,\n    \"Ġidentified\": 2006,\n    \"Ġsimple\": 2007,\n    \"Ġcritical\": 2008,\n    \"ĠClub\": 2009,\n    \"ĠSecurity\": 2010,\n    \"ĠLike\": 2011,\n    \"Ġstarts\": 2012,\n    \"art\": 2013,\n    \"Ġstreet\": 2014,\n    \"Ġreality\": 2015,\n    \"Ġheavy\": 2016,\n    \"Ġprogress\": 2017,\n    \"Ġshowing\": 2018,\n    \"Ġchallenges\": 2019,\n    \"Ġban\": 2020,\n    \"Ġcommitted\": 2021,\n    \"35\": 2022,\n    \"»\": 2023,\n    \"Ġdirectly\": 2024,\n    \"Ġaren\": 2025,\n    \"Ġclaim\": 2026,\n    \"ĠWestern\": 2027,\n    \"ind\": 2028,\n    \"Ġgives\": 2029,\n    \"ĠSaudi\": 2030,\n    \"Ġchoice\": 2031,\n    \"ĠTh\": 2032,\n    \"Ġapproved\": 2033,\n    \"Ġlocated\": 2034,\n    \"Ġarrived\": 2035,\n    \"22\": 2036,\n    \"Ġcaught\": 2037,\n    \"Ġprofessional\": 2038,\n    \"Ġmissed\": 2039,\n    \"Ġculture\": 2040,\n    \"ĠYear\": 2041,\n    \"ĠOhio\": 2042,\n    \"ĠLtd\": 2043,\n    \"ĠAnother\": 2044,\n    \"Ġseem\": 2045,\n    \"Ġbelieves\": 2046,\n    \"Ġbelieved\": 2047,\n    \"Ġcharacter\": 2048,\n    \"ĠAug\": 2049,\n    \"red\": 2050,\n    \"Ġfine\": 2051,\n    \"Ġprior\": 2052,\n    \"Ġthinking\": 2053,\n    \"Ġhttp\": 2054,\n    \"Ġ+\": 2055,\n    \"Ġzone\": 2056,\n    \"Ġputting\": 2057,\n    \"Ġcrash\": 2058,\n    \"ĠAustralian\": 2059,\n    \"ĠAb\": 2060,\n    \"Ġfocused\": 2061,\n    \"ĠREUTERS\": 2062,\n    \"ĠFox\": 2063,\n    \"ĠSp\": 2064,\n    \"Ġtraditional\": 2065,\n    \"Ġanalyst\": 2066,\n    \"Ġwait\": 2067,\n    \"IT\": 2068,\n    \"Ġrequest\": 2069,\n    \"ru\": 2070,\n    \"ians\": 2071,\n    \"ize\": 2072,\n    \"Ġfinish\": 2073,\n    \"Ġlaws\": 2074,\n    \"Ġran\": 2075,\n    \"ER\": 2076,\n    \"Ġsouth\": 2077,\n    \"Ġspeed\": 2078,\n    \"Ġmovement\": 2079,\n    \"Ġassault\": 2080,\n    \"Ġexchange\": 2081,\n    \"Ġappear\": 2082,\n    \"ĠSun\": 2083,\n    \"Ġle\": 2084,\n    \"Ġmaybe\": 2085,\n    \"Ġlosing\": 2086,\n    \"Ġsubject\": 2087,\n    \"ive\": 2088,\n    \"mer\": 2089,\n    \"ĠBusiness\": 2090,\n    \"ĠBl\": 2091,\n    \"Ġappears\": 2092,\n    \"Ġadvantage\": 2093,\n    \"ĠLee\": 2094,\n    \"ada\": 2095,\n    \"ĠUnder\": 2096,\n    \"Ġprevent\": 2097,\n    \"Ġrespect\": 2098,\n    \"Ġsex\": 2099,\n    \"Ġcentre\": 2100,\n    \"ĠJoe\": 2101,\n    \"ado\": 2102,\n    \"Ġtable\": 2103,\n    \"Ġequipment\": 2104,\n    \"Ġfair\": 2105,\n    \"Ġtour\": 2106,\n    \"Ġ32\": 2107,\n    \"ĠFinancial\": 2108,\n    \"Ġcounty\": 2109,\n    \"Ġdevices\": 2110,\n    \"Ġcustomer\": 2111,\n    \"Ġinfrastructure\": 2112,\n    \"Ġexpectations\": 2113,\n    \"Ġfacing\": 2114,\n    \"Ġupon\": 2115,\n    \"Ġcross\": 2116,\n    \"ĠOpen\": 2117,\n    \"AL\": 2118,\n    \"Ġquick\": 2119,\n    \"Ġattempt\": 2120,\n    \"Ġcompleted\": 2121,\n    \"Ġfacility\": 2122,\n    \"Ġconfidence\": 2123,\n    \"ĠSupreme\": 2124,\n    \"Ġpiece\": 2125,\n    \"our\": 2126,\n    \"Ġplaces\": 2127,\n    \"Ġsometimes\": 2128,\n    \"Ġpoor\": 2129,\n    \"Ġstorm\": 2130,\n    \"Ġhot\": 2131,\n    \"Ġaffected\": 2132,\n    \"na\": 2133,\n    \"Ġabuse\": 2134,\n    \"ĠMs\": 2135,\n    \"Ġword\": 2136,\n    \"over\": 2137,\n    \"Ġbrother\": 2138,\n    \"Ġnecessary\": 2139,\n    \"Ġeventually\": 2140,\n    \"ĠStar\": 2141,\n    \"Ġsend\": 2142,\n    \"Ġboy\": 2143,\n    \"ĠRs\": 2144,\n    \"Ġremember\": 2145,\n    \"21\": 2146,\n    \"Ġclimate\": 2147,\n    \"Ġcapacity\": 2148,\n    \"Ġresponsible\": 2149,\n    \"ĠMatt\": 2150,\n    \"month\": 2151,\n    \"Ġsuffered\": 2152,\n    \"%.\": 2153,\n    \"og\": 2154,\n    \"ĠPeter\": 2155,\n    \"Ġ,\": 2156,\n    \"Ġfeeling\": 2157,\n    \"ze\": 2158,\n    \"Ġbuying\": 2159,\n    \"oy\": 2160,\n    \"ij\": 2161,\n    \"Ġbought\": 2162,\n    \"Ġactions\": 2163,\n    \"Ġowned\": 2164,\n    \"Ġ___\": 2165,\n    \"Ġphysical\": 2166,\n    \"Ġspecific\": 2167,\n    \"Ġbattle\": 2168,\n    \"ĠEnergy\": 2169,\n    \"Ġpicture\": 2170,\n    \"Ġactive\": 2171,\n    \"Ġindividuals\": 2172,\n    \"Ġguy\": 2173,\n    \"Ġregional\": 2174,\n    \"Ġbond\": 2175,\n    \"ows\": 2176,\n    \"ĠToronto\": 2177,\n    \"Ġrule\": 2178,\n    \"Ġdevelop\": 2179,\n    \"Ġcrowd\": 2180,\n    \"Ġguilty\": 2181,\n    \"Ġfemale\": 2182,\n    \"Ġselling\": 2183,\n    \"ĠFollow\": 2184,\n    \"Ġmyself\": 2185,\n    \"ata\": 2186,\n    \"Ġdevice\": 2187,\n    \"Ġreasons\": 2188,\n    \"Ġrecords\": 2189,\n    \"Ġfighting\": 2190,\n    \"ON\": 2191,\n    \"ities\": 2192,\n    \"ĠHome\": 2193,\n    \"Ġstatus\": 2194,\n    \"Ġplant\": 2195,\n    \"Ġdrugs\": 2196,\n    \"ĠChurch\": 2197,\n    \"Ġcompletely\": 2198,\n    \"Ġdisease\": 2199,\n    \"Ġhighly\": 2200,\n    \"ĠParis\": 2201,\n    \"Ġdecade\": 2202,\n    \"Ġowners\": 2203,\n    \"Ġwall\": 2204,\n    \"Ġcamp\": 2205,\n    \"ĠSteve\": 2206,\n    \"Ġreporting\": 2207,\n    \"Ġearned\": 2208,\n    \"ĠImages\": 2209,\n    \"Ġexisting\": 2210,\n    \"ĠSen\": 2211,\n    \"Ġconcern\": 2212,\n    \"Ġhundreds\": 2213,\n    \"Ġsong\": 2214,\n    \"Ġknows\": 2215,\n    \"Ġunique\": 2216,\n    \"Ġlose\": 2217,\n    \"ĠKh\": 2218,\n    \"Ġapproximately\": 2219,\n    \"Ġhaven\": 2220,\n    \"Ġpark\": 2221,\n    \"Ġindependent\": 2222,\n    \"ĠAlthough\": 2223,\n    \"ĠAndrew\": 2224,\n    \"Ġpaper\": 2225,\n    \"Ġdeveloped\": 2226,\n    \"Ġrising\": 2227,\n    \"Ġdirect\": 2228,\n    \"Ġpurchase\": 2229,\n    \"Ġexactly\": 2230,\n    \"Ġq\": 2231,\n    \"Ġmassive\": 2232,\n    \"Ġbox\": 2233,\n    \"Ġchampion\": 2234,\n    \"ĠClinton\": 2235,\n    \"Ġvoice\": 2236,\n    \"Ġarrest\": 2237,\n    \"ĠKorean\": 2238,\n    \"Ġlearning\": 2239,\n    \"ĠVirginia\": 2240,\n    \"Ġsa\": 2241,\n    \"Ġpar\": 2242,\n    \"Ġchairman\": 2243,\n    \"Ġagencies\": 2244,\n    \"Ġhealthy\": 2245,\n    \"ĠThose\": 2246,\n    \"Ġpowerful\": 2247,\n    \"Ġ45\": 2248,\n    \"Ġdifference\": 2249,\n    \"ĠJackson\": 2250,\n    \"Ġenforcement\": 2251,\n    \"Ġdividend\": 2252,\n    \"qu\": 2253,\n    \"Ġenjoy\": 2254,\n    \"Ġruling\": 2255,\n    \"Ġongoing\": 2256,\n    \"Ġsoftware\": 2257,\n    \"ks\": 2258,\n    \"Ġlocation\": 2259,\n    \"Ġmostly\": 2260,\n    \"Ġcandidates\": 2261,\n    \"men\": 2262,\n    \"Ġbroke\": 2263,\n    \"What\": 2264,\n    \"ĠBr\": 2265,\n    \"Ġ2008\": 2266,\n    \"Ġconsumer\": 2267,\n    \"Ġdiscuss\": 2268,\n    \"Ġdi\": 2269,\n    \"Ġprimary\": 2270,\n    \"ĠEn\": 2271,\n    \"Ġgreen\": 2272,\n    \"Ġconcerned\": 2273,\n    \"Ġimage\": 2274,\n    \"ĠPremier\": 2275,\n    \"ĠMeanwhile\": 2276,\n    \"Ġfired\": 2277,\n    \"ĠBoston\": 2278,\n    \"ann\": 2279,\n    \"Ġcamera\": 2280,\n    \"Ġtraded\": 2281,\n    \"Ġhasn\": 2282,\n    \"Ġexcited\": 2283,\n    \"Ġincreasing\": 2284,\n    \"ĠDespite\": 2285,\n    \"Ġcitizens\": 2286,\n    \"Ġeuro\": 2287,\n    \"Ġreportedly\": 2288,\n    \"Ġminute\": 2289,\n    \"ĠWill\": 2290,\n    \"ĠLLC\": 2291,\n    \"Ġsp\": 2292,\n    \"ĠMichigan\": 2293,\n    \"Ġstopped\": 2294,\n    \"Ġeye\": 2295,\n    \"Ġdenied\": 2296,\n    \"Ġmodern\": 2297,\n    \"ĠWall\": 2298,\n    \"Ġdefinitely\": 2299,\n    \"point\": 2300,\n    \"Ġlines\": 2301,\n    \"Ġpolitics\": 2302,\n    \"Ġhotel\": 2303,\n    \"Ġretail\": 2304,\n    \"Ġstated\": 2305,\n    \"ĠOver\": 2306,\n    \"Ġgrew\": 2307,\n    \"Ġbroadcast\": 2308,\n    \"Ġlegislation\": 2309,\n    \"Ġfresh\": 2310,\n    \"Ġbid\": 2311,\n    \"Ġmanaged\": 2312,\n    \"Ġsociety\": 2313,\n    \"Ġscoring\": 2314,\n    \"ĠGet\": 2315,\n    \"Ġintelligence\": 2316,\n    \"Ġholiday\": 2317,\n    \"Ġgovernor\": 2318,\n    \"Ġestimated\": 2319,\n    \"Ġexperts\": 2320,\n    \"ĠJeff\": 2321,\n    \"Ġstruck\": 2322,\n    \"Ġhits\": 2323,\n    \"Ġcarry\": 2324,\n    \"Ġplaced\": 2325,\n    \"Ġstores\": 2326,\n    \"Ġexpressed\": 2327,\n    \"Ġvalued\": 2328,\n    \"Ġad\": 2329,\n    \"Ġtwice\": 2330,\n    \"ala\": 2331,\n    \"Ġdisplay\": 2332,\n    \"Ġusually\": 2333,\n    \"Ġresponded\": 2334,\n    \"Ġdog\": 2335,\n    \"AS\": 2336,\n    \"ĠFed\": 2337,\n    \"Ġ2009\": 2338,\n    \"Ġdocuments\": 2339,\n    \"Ġnormal\": 2340,\n    \"Ġtrain\": 2341,\n    \"Ġfl\": 2342,\n    \"Ġshown\": 2343,\n    \"ĠEd\": 2344,\n    \"Ġsort\": 2345,\n    \"Ġallegedly\": 2346,\n    \"Ġshots\": 2347,\n    \"ka\": 2348,\n    \"Ġaccounts\": 2349,\n    \"Ġyesterday\": 2350,\n    \"Ġcreating\": 2351,\n    \"Ġchurch\": 2352,\n    \"Ġbus\": 2353,\n    \"Ġaward\": 2354,\n    \"Ġequity\": 2355,\n    \"Ġphotos\": 2356,\n    \"Ġ33\": 2357,\n    \"Ġfiscal\": 2358,\n    \"je\": 2359,\n    \"Ġconsumers\": 2360,\n    \"ĠManchester\": 2361,\n    \"no\": 2362,\n    \"ĠKevin\": 2363,\n    \"Ġgain\": 2364,\n    \"Ġcorporate\": 2365,\n    \"Ġcivil\": 2366,\n    \"ĠMiddle\": 2367,\n    \"ally\": 2368,\n    \"Ġsound\": 2369,\n    \"ĠEnglish\": 2370,\n    \"IC\": 2371,\n    \"Ġwinds\": 2372,\n    \"Ġworst\": 2373,\n    \"ĠGrand\": 2374,\n    \"Ġeffective\": 2375,\n    \"ĠIsland\": 2376,\n    \"Ġdrivers\": 2377,\n    \"Ġfan\": 2378,\n    \"pe\": 2379,\n    \"Ġsides\": 2380,\n    \"ĠGo\": 2381,\n    \"Ġclean\": 2382,\n    \"âĢĵ\": 2383,\n    \"Ġtelevision\": 2384,\n    \"ĠJr\": 2385,\n    \"Ġallows\": 2386,\n    \"My\": 2387,\n    \"Ġgreater\": 2388,\n    \"ance\": 2389,\n    \"Ġdecisions\": 2390,\n    \"Ġrestaurant\": 2391,\n    \"ĠHospital\": 2392,\n    \"ĠTr\": 2393,\n    \"Ġbalance\": 2394,\n    \"Ġmph\": 2395,\n    \"Ġkeeping\": 2396,\n    \"Ġseconds\": 2397,\n    \"Ġweapons\": 2398,\n    \"ert\": 2399,\n    \"Ġpain\": 2400,\n    \"ass\": 2401,\n    \"Ġsteps\": 2402,\n    \"ger\": 2403,\n    \"ĠBrexit\": 2404,\n    \"Ġremaining\": 2405,\n    \"Ġbringing\": 2406,\n    \"ure\": 2407,\n    \"Ġweight\": 2408,\n    \"And\": 2409,\n    \"Ġwriting\": 2410,\n    \"Photo\": 2411,\n    \"ĠChristian\": 2412,\n    \"ob\": 2413,\n    \"Ġsport\": 2414,\n    \"Ġfigures\": 2415,\n    \"Ġtrust\": 2416,\n    \"Ġskills\": 2417,\n    \"Ġseat\": 2418,\n    \"Ġfaces\": 2419,\n    \"ck\": 2420,\n    \"Ġborn\": 2421,\n    \"Ġsuper\": 2422,\n    \"Ġfuel\": 2423,\n    \"Ġdel\": 2424,\n    \"Ġmeant\": 2425,\n    \"ica\": 2426,\n    \"Ġjustice\": 2427,\n    \"Ġspring\": 2428,\n    \"Ġkilling\": 2429,\n    \"Ġnegative\": 2430,\n    \"ĠRichard\": 2431,\n    \"Ġund\": 2432,\n    \"Ġfactors\": 2433,\n    \"Ġsigns\": 2434,\n    \"Ġlearned\": 2435,\n    \"ĠGame\": 2436,\n    \"Ġaudience\": 2437,\n    \"Ġdeliver\": 2438,\n    \"Ġillegal\": 2439,\n    \"Ġblue\": 2440,\n    \"Ġscreen\": 2441,\n    \"Ġremained\": 2442,\n    \"Ġannouncement\": 2443,\n    \"IN\": 2444,\n    \"Ġwaiting\": 2445,\n    \"Ġthanks\": 2446,\n    \"Ġimmigration\": 2447,\n    \"ĠFBI\": 2448,\n    \"Ġwarned\": 2449,\n    \"Ġmeasure\": 2450,\n    \"Ġdraw\": 2451,\n    \"Ġpositions\": 2452,\n    \"Ġdebut\": 2453,\n    \"ĠMedia\": 2454,\n    \"Ġallowing\": 2455,\n    \"air\": 2456,\n    \"hen\": 2457,\n    \"Ġmark\": 2458,\n    \"ys\": 2459,\n    \"Ġprepared\": 2460,\n    \"ĠVegas\": 2461,\n    \"ep\": 2462,\n    \"ice\": 2463,\n    \"2018\": 2464,\n    \"Ġdefensive\": 2465,\n    \"60\": 2466,\n    \"ĠBeach\": 2467,\n    \"Ġpulled\": 2468,\n    \"£\": 2469,\n    \"Ġlawyer\": 2470,\n    \"Ġcast\": 2471,\n    \"Ġsolution\": 2472,\n    \"Ġeyes\": 2473,\n    \"Ġmarketing\": 2474,\n    \"ĠFoundation\": 2475,\n    \"Ġrisks\": 2476,\n    \"ĠToday\": 2477,\n    \"za\": 2478,\n    \"Ġdraft\": 2479,\n    \"Ġice\": 2480,\n    \"26\": 2481,\n    \"ĠHar\": 2482,\n    \"ĠExecutive\": 2483,\n    \"Ġtruck\": 2484,\n    \"ions\": 2485,\n    \"ĠYour\": 2486,\n    \"ĠIreland\": 2487,\n    \"ĠJim\": 2488,\n    \"Ġha\": 2489,\n    \"Ġfear\": 2490,\n    \"Ġ36\": 2491,\n    \"UR\": 2492,\n    \"ĠFord\": 2493,\n    \"Ġwatching\": 2494,\n    \"ien\": 2495,\n    \"Ġstyle\": 2496,\n    \"ĠGood\": 2497,\n    \"Ġwearing\": 2498,\n    \"ĠHouston\": 2499,\n    \"Ġonto\": 2500,\n    \"Ġboost\": 2501,\n    \"Ġapplication\": 2502,\n    \"ĠDan\": 2503,\n    \"Ġspread\": 2504,\n    \"ĠDavis\": 2505,\n    \"Ġstrike\": 2506,\n    \"els\": 2507,\n    \"Ġwind\": 2508,\n    \"Ġinterested\": 2509,\n    \"Ġguard\": 2510,\n    \"Ġmission\": 2511,\n    \"Ġyourself\": 2512,\n    \"Ġoperation\": 2513,\n    \"Ġlarger\": 2514,\n    \"She\": 2515,\n    \"Ġseasons\": 2516,\n    \"28\": 2517,\n    \"27\": 2518,\n    \"Ġrespond\": 2519,\n    \"ci\": 2520,\n    \"ĠCentre\": 2521,\n    \"Our\": 2522,\n    \"Ġnames\": 2523,\n    \"Ġflight\": 2524,\n    \"Ġquarterback\": 2525,\n    \"Ġstandard\": 2526,\n    \"so\": 2527,\n    \"Ġsuggested\": 2528,\n    \"ĠMal\": 2529,\n    \"Ġolder\": 2530,\n    \"ini\": 2531,\n    \"Ġperhaps\": 2532,\n    \"ont\": 2533,\n    \"ĠInstitute\": 2534,\n    \"Ġmillions\": 2535,\n    \"Ġmental\": 2536,\n    \"ÃĤ\": 2537,\n    \"ga\": 2538,\n    \"Ġclients\": 2539,\n    \"Ġplease\": 2540,\n    \"Ġloan\": 2541,\n    \"Ġaware\": 2542,\n    \"ft\": 2543,\n    \"int\": 2544,\n    \"75\": 2545,\n    \"05\": 2546,\n    \"AY\": 2547,\n    \"ĠOut\": 2548,\n    \"Ġhair\": 2549,\n    \"ied\": 2550,\n    \"Ġseemed\": 2551,\n    \"ene\": 2552,\n    \"ty\": 2553,\n    \"NYSE\": 2554,\n    \"Ġoffensive\": 2555,\n    \"Ġtaxes\": 2556,\n    \"Ġinitial\": 2557,\n    \"ren\": 2558,\n    \"Ġseparate\": 2559,\n    \"la\": 2560,\n    \"ĠMiami\": 2561,\n    \"AC\": 2562,\n    \"Ġclearly\": 2563,\n    \"Ġfit\": 2564,\n    \"ĠCoast\": 2565,\n    \"Ġfirms\": 2566,\n    \"Ġpartners\": 2567,\n    \"Ġupcoming\": 2568,\n    \"Ġcold\": 2569,\n    \"Ġproposal\": 2570,\n    \"AT\": 2571,\n    \"Ġshut\": 2572,\n    \"ĠCommunity\": 2573,\n    \"Ġnature\": 2574,\n    \"ĠSal\": 2575,\n    \"Ġbottom\": 2576,\n    \"ting\": 2577,\n    \"ĠClick\": 2578,\n    \"Ġnice\": 2579,\n    \"ets\": 2580,\n    \"Ġhurt\": 2581,\n    \"itt\": 2582,\n    \"ama\": 2583,\n    \"Ġcarried\": 2584,\n    \"ĠCon\": 2585,\n    \"rd\": 2586,\n    \"Ġestate\": 2587,\n    \"ĠLas\": 2588,\n    \"ĠLaw\": 2589,\n    \"ng\": 2590,\n    \"Ġprotection\": 2591,\n    \"Ġproduce\": 2592,\n    \"Ġcurrency\": 2593,\n    \"Ġhappens\": 2594,\n    \"ĠPer\": 2595,\n    \"ney\": 2596,\n    \"ĠLong\": 2597,\n    \"Ġfellow\": 2598,\n    \"Ġcuts\": 2599,\n    \"Ġreading\": 2600,\n    \"ano\": 2601,\n    \"Ġproud\": 2602,\n    \"ost\": 2603,\n    \"ĠUN\": 2604,\n    \"ĠArizona\": 2605,\n    \"AD\": 2606,\n    \"Ġhelps\": 2607,\n    \"Ġwinter\": 2608,\n    \"Ġfinding\": 2609,\n    \"ĠGold\": 2610,\n    \"att\": 2611,\n    \"ĠWhy\": 2612,\n    \"Ġbasketball\": 2613,\n    \"lin\": 2614,\n    \"ĠCan\": 2615,\n    \"ĠBowl\": 2616,\n    \"ial\": 2617,\n    \"ĠAlex\": 2618,\n    \"200\": 2619,\n    \"AM\": 2620,\n    \"Ġpresence\": 2621,\n    \"Ġproduced\": 2622,\n    \"Ġdeveloping\": 2623,\n    \"Ġregarding\": 2624,\n    \"Ġdebate\": 2625,\n    \"Ġvice\": 2626,\n    \"ĠItaly\": 2627,\n    \"Ġsu\": 2628,\n    \"its\": 2629,\n    \"ator\": 2630,\n    \"Ġ34\": 2631,\n    \"Ġcomplex\": 2632,\n    \"Ġpresented\": 2633,\n    \"Ġresearchers\": 2634,\n    \"Ġslow\": 2635,\n    \"ya\": 2636,\n    \"Ġsanctions\": 2637,\n    \"Ġloved\": 2638,\n    \"Ġseek\": 2639,\n    \"Ġresponsibility\": 2640,\n    \"Ġadmitted\": 2641,\n    \"Ġalbum\": 2642,\n    \"Ġsolutions\": 2643,\n    \"Ġfacilities\": 2644,\n    \"ett\": 2645,\n    \"ĠGu\": 2646,\n    \"ĠWell\": 2647,\n    \"Ġlawmakers\": 2648,\n    \"Ġmiss\": 2649,\n    \"ful\": 2650,\n    \"ĠNick\": 2651,\n    \"'.\": 2652,\n    \"Ġfeels\": 2653,\n    \"Ġprime\": 2654,\n    \"Ġknowledge\": 2655,\n    \"Ġdeals\": 2656,\n    \"ĠTaylor\": 2657,\n    \"Ġsurvey\": 2658,\n    \"ĠFrancisco\": 2659,\n    \"Ġjoint\": 2660,\n    \"Ġwhom\": 2661,\n    \"Ġsit\": 2662,\n    \"01\": 2663,\n    \"Ġtr\": 2664,\n    \"Ġorganizations\": 2665,\n    \"ĠAvenue\": 2666,\n    \"ĠTheir\": 2667,\n    \"ĠTim\": 2668,\n    \"Ġrally\": 2669,\n    \"game\": 2670,\n    \"Ġbigger\": 2671,\n    \"Ġlawsuit\": 2672,\n    \"Ġrecorded\": 2673,\n    \"Ġfavorite\": 2674,\n    \"yard\": 2675,\n    \"Ġtransaction\": 2676,\n    \"Ġqu\": 2677,\n    \"oh\": 2678,\n    \"Ġinteresting\": 2679,\n    \"Ġinflation\": 2680,\n    \"ath\": 2681,\n    \"Ġstuff\": 2682,\n    \"Ġindustrial\": 2683,\n    \"ico\": 2684,\n    \"TS\": 2685,\n    \"Ġspeaking\": 2686,\n    \"Ġlosses\": 2687,\n    \"ID\": 2688,\n    \"ĠStadium\": 2689,\n    \"Ġstars\": 2690,\n    \"ĠWomen\": 2691,\n    \"ĠBlue\": 2692,\n    \"Ġwins\": 2693,\n    \"Ġdes\": 2694,\n    \"Ġcompetitive\": 2695,\n    \"ters\": 2696,\n    \"Ġpounds\": 2697,\n    \"Ġdirection\": 2698,\n    \"Ġinnings\": 2699,\n    \"ĠBest\": 2700,\n    \"Ġactor\": 2701,\n    \"Ġdangerous\": 2702,\n    \"Ġrequire\": 2703,\n    \"Ġplus\": 2704,\n    \"Ġsolid\": 2705,\n    \"Ġgeneration\": 2706,\n    \"Ġstrength\": 2707,\n    \"ĠMary\": 2708,\n    \"For\": 2709,\n    \"Ġplenty\": 2710,\n    \"ĠTeam\": 2711,\n    \"Ġinfluence\": 2712,\n    \"Ġfaced\": 2713,\n    \"Ġes\": 2714,\n    \"ĠIslamic\": 2715,\n    \"let\": 2716,\n    \"ĠDevelopment\": 2717,\n    \"Ġpath\": 2718,\n    \"Ġyouth\": 2719,\n    \"Ġcommitment\": 2720,\n    \"Ġbeautiful\": 2721,\n    \"ĠJack\": 2722,\n    \"ort\": 2723,\n    \"Ġten\": 2724,\n    \"Ġattend\": 2725,\n    \"ars\": 2726,\n    \"Ã³n\": 2727,\n    \"Ġviews\": 2728,\n    \"Ġeuros\": 2729,\n    \"Ġauthor\": 2730,\n    \"Ġcore\": 2731,\n    \"Ġsupporters\": 2732,\n    \"ĠiPhone\": 2733,\n    \"Ġfashion\": 2734,\n    \"Ġsmaller\": 2735,\n    \"Ġelected\": 2736,\n    \"Ġuniversity\": 2737,\n    \"Ġpicked\": 2738,\n    \"wa\": 2739,\n    \"Ġordered\": 2740,\n    \"ĠSc\": 2741,\n    \"ĠÅ\": 2742,\n    \"Ġlargely\": 2743,\n    \"+\": 2744,\n    \"ĠAttorney\": 2745,\n    \"Ġpaying\": 2746,\n    \"AR\": 2747,\n    \"Ġconnection\": 2748,\n    \"Ġsetting\": 2749,\n    \"Ġna\": 2750,\n    \"ĠRock\": 2751,\n    \"Ġrecovery\": 2752,\n    \"ew\": 2753,\n    \"Ġserving\": 2754,\n    \"Ġsurprise\": 2755,\n    \"Ġoccurred\": 2756,\n    \"Ġdivision\": 2757,\n    \"Ġtelling\": 2758,\n    \"Ġmargin\": 2759,\n    \"Ġ2020\": 2760,\n    \"Ġsister\": 2761,\n    \"ĠNBA\": 2762,\n    \"Ġvoted\": 2763,\n    \"Ġcon\": 2764,\n    \"By\": 2765,\n    \"Ġ49\": 2766,\n    \"Ġfoot\": 2767,\n    \"Ã¼\": 2768,\n    \"ĠTurkey\": 2769,\n    \"Ġamazing\": 2770,\n    \"Ġcombined\": 2771,\n    \"Ġappearance\": 2772,\n    \"Ġeasily\": 2773,\n    \"DAY\": 2774,\n    \"Ġnotes\": 2775,\n    \"ĠStart\": 2776,\n    \"Ġlanguage\": 2777,\n    \"Ġextremely\": 2778,\n    \"Ġcloudy\": 2779,\n    \"ĠLet\": 2780,\n    \"Ġdelivered\": 2781,\n    \"Ġimproved\": 2782,\n    \"Ġcollection\": 2783,\n    \"ĠPM\": 2784,\n    \"Ġestimates\": 2785,\n    \"Ġboys\": 2786,\n    \"izing\": 2787,\n    \"Ġtext\": 2788,\n    \"Ġcloser\": 2789,\n    \"Ġprotest\": 2790,\n    \"Ġprovince\": 2791,\n    \"Ġshop\": 2792,\n    \"Ġsmart\": 2793,\n    \"de\": 2794,\n    \"ĠSheriff\": 2795,\n    \"EN\": 2796,\n    \"Ġcorner\": 2797,\n    \"Ġpanel\": 2798,\n    \"Ġbooks\": 2799,\n    \"Ġsupported\": 2800,\n    \"Ġmentioned\": 2801,\n    \"ver\": 2802,\n    \"ĠMinistry\": 2803,\n    \"ĠPrince\": 2804,\n    \"ĠUSA\": 2805,\n    \"Ġreceiving\": 2806,\n    \"Ġchoose\": 2807,\n    \"ĠIN\": 2808,\n    \"ĠSpain\": 2809,\n    \"Ġsection\": 2810,\n    \"Ġconsidering\": 2811,\n    \"ĠCor\": 2812,\n    \"Ġwish\": 2813,\n    \"Ġwelcome\": 2814,\n    \"ĠConference\": 2815,\n    \"ere\": 2816,\n    \"ĠOfficer\": 2817,\n    \"Ġhoping\": 2818,\n    \"Ġportfolio\": 2819,\n    \"Ġstandards\": 2820,\n    \"Ġgrand\": 2821,\n    \"ĠReal\": 2822,\n    \"Ġsecure\": 2823,\n    \"ĠCorporation\": 2824,\n    \"ĠRep\": 2825,\n    \"ĠKelly\": 2826,\n    \"Ġstreets\": 2827,\n    \"Ġsitting\": 2828,\n    \"Ġslightly\": 2829,\n    \"ĠInvestment\": 2830,\n    \"99\": 2831,\n    \"ond\": 2832,\n    \"Ġunits\": 2833,\n    \"Ġvotes\": 2834,\n    \"Ġsegment\": 2835,\n    \"Ġchampionship\": 2836,\n    \"Ġsquad\": 2837,\n    \"iting\": 2838,\n    \"ron\": 2839,\n    \"®\": 2840,\n    \"Ġem\": 2841,\n    \"Ġtouch\": 2842,\n    \"Ġ38\": 2843,\n    \"Ġceremony\": 2844,\n    \"Ġdecide\": 2845,\n    \"Ġapproval\": 2846,\n    \"So\": 2847,\n    \"ĠPort\": 2848,\n    \"Ġsub\": 2849,\n    \"Ġsc\": 2850,\n    \"Ġrep\": 2851,\n    \"ĠWeek\": 2852,\n    \"Ġupper\": 2853,\n    \"Ġagree\": 2854,\n    \"ny\": 2855,\n    \"Ġmatches\": 2856,\n    \"ics\": 2857,\n    \"Ġtweeted\": 2858,\n    \"Ġheat\": 2859,\n    \"ĠGreat\": 2860,\n    \"Ġpenalty\": 2861,\n    \"Ġmass\": 2862,\n    \"Ġalongside\": 2863,\n    \"Ġherself\": 2864,\n    \"berg\": 2865,\n    \"Ġscience\": 2866,\n    \"Ġentered\": 2867,\n    \"Ġappeal\": 2868,\n    \"ĠPr\": 2869,\n    \"Ġfile\": 2870,\n    \"che\": 2871,\n    \"ĠReport\": 2872,\n    \"ĠThree\": 2873,\n    \"ĠNorthern\": 2874,\n    \"ĠJordan\": 2875,\n    \"Ġamid\": 2876,\n    \"Ġpace\": 2877,\n    \"Ġjail\": 2878,\n    \"Ġfinance\": 2879,\n    \"ĠYoung\": 2880,\n    \"32\": 2881,\n    \"Ġwilling\": 2882,\n    \"Ġconduct\": 2883,\n    \"ĠPar\": 2884,\n    \"Ġestablished\": 2885,\n    \"Ġreturns\": 2886,\n    \"Ġaid\": 2887,\n    \"Ġinternet\": 2888,\n    \"IA\": 2889,\n    \"29\": 2890,\n    \"Ġmeetings\": 2891,\n    \"Ġwarning\": 2892,\n    \"ĠCl\": 2893,\n    \"Ġcampus\": 2894,\n    \"Most\": 2895,\n    \"ĠFund\": 2896,\n    \"ĠWilliam\": 2897,\n    \"ĠJapanese\": 2898,\n    \"Ġconsensus\": 2899,\n    \"Ġbrain\": 2900,\n    \"!\\\"\": 2901,\n    \"Ġpoll\": 2902,\n    \"Ġtech\": 2903,\n    \"Ġtrend\": 2904,\n    \"Ġpotentially\": 2905,\n    \"Ġreduced\": 2906,\n    \"ĠShow\": 2907,\n    \"Ġ37\": 2908,\n    \"Ġhappening\": 2909,\n    \"ĠBrazil\": 2910,\n    \"pl\": 2911,\n    \"ĠCal\": 2912,\n    \"Ġcovered\": 2913,\n    \"Ġenter\": 2914,\n    \"TV\": 2915,\n    \"Ġcatch\": 2916,\n    \"foot\": 2917,\n    \"Ġunion\": 2918,\n    \"Ġexpansion\": 2919,\n    \"ĠSingapore\": 2920,\n    \"ĠDetroit\": 2921,\n    \"Ġattended\": 2922,\n    \"ats\": 2923,\n    \"Ġnewspaper\": 2924,\n    \"ĠDivision\": 2925,\n    \"news\": 2926,\n    \"Ġcap\": 2927,\n    \"Ġremoved\": 2928,\n    \"Ġ48\": 2929,\n    \"ĠRoyal\": 2930,\n    \"Ġwindow\": 2931,\n    \"Ġparking\": 2932,\n    \"Ġdark\": 2933,\n    \"Ġstanding\": 2934,\n    \"Ġupdate\": 2935,\n    \"Ġagent\": 2936,\n    \"Ġtransfer\": 2937,\n    \"ĠArmy\": 2938,\n    \"Ġuses\": 2939,\n    \"80\": 2940,\n    \"ĠTe\": 2941,\n    \"Ġintroduced\": 2942,\n    \"Ġmale\": 2943,\n    \"ĠSouthern\": 2944,\n    \"Ġratings\": 2945,\n    \"Ġisland\": 2946,\n    \"ĠMiller\": 2947,\n    \"Ġteachers\": 2948,\n    \"Ġadvice\": 2949,\n    \"Ġfamiliar\": 2950,\n    \"uf\": 2951,\n    \"Ġsought\": 2952,\n    \"Ġpor\": 2953,\n    \"ĠEric\": 2954,\n    \"Ġda\": 2955,\n    \"Ġideas\": 2956,\n    \"uh\": 2957,\n    \"Ġsixth\": 2958,\n    \"Ġtalent\": 2959,\n    \"ĠImage\": 2960,\n    \"ering\": 2961,\n    \"run\": 2962,\n    \"ments\": 2963,\n    \"Ġconducted\": 2964,\n    \"300\": 2965,\n    \"Ġurged\": 2966,\n    \"Ġdiscovered\": 2967,\n    \"Ġpl\": 2968,\n    \"Ġunderstanding\": 2969,\n    \"Ġoffense\": 2970,\n    \"Ġsecretary\": 2971,\n    \"Ġsk\": 2972,\n    \"Ġloans\": 2973,\n    \"ĠGr\": 2974,\n    \"Ġapplications\": 2975,\n    \"Ġcrude\": 2976,\n    \"go\": 2977,\n    \"ĠInstead\": 2978,\n    \"Ġopinion\": 2979,\n    \"Ġdoubt\": 2980,\n    \"ey\": 2981,\n    \"Ġdis\": 2982,\n    \"31\": 2983,\n    \"Ġexperienced\": 2984,\n    \"Ġleg\": 2985,\n    \"ĠCleveland\": 2986,\n    \"ven\": 2987,\n    \"Ġfailure\": 2988,\n    \"market\": 2989,\n    \"ack\": 2990,\n    \"Ġdecline\": 2991,\n    \"Ġchanging\": 2992,\n    \"Ġ300\": 2993,\n    \"Ġdefence\": 2994,\n    \"ĠBrian\": 2995,\n    \"Ġdelivery\": 2996,\n    \"Ġmarried\": 2997,\n    \"Ġdeclared\": 2998,\n    \"Ġpull\": 2999,\n    \"Ġlimit\": 3000,\n    \"ĠMORE\": 3001,\n    \"Ġdefeat\": 3002,\n    \"Ġexpand\": 3003,\n    \"ĠColorado\": 3004,\n    \"ĠRob\": 3005,\n    \"iss\": 3006,\n    \"Ġworse\": 3007,\n    \"Ġperform\": 3008,\n    \"ising\": 3009,\n    \"Ġ2007\": 3010,\n    \"ĠDel\": 3011,\n    \"Ġsurgery\": 3012,\n    \"Ġeasier\": 3013,\n    \"Ġmaintain\": 3014,\n    \"ĠEx\": 3015,\n    \"Ġtied\": 3016,\n    \"Ġeast\": 3017,\n    \"Ġuser\": 3018,\n    \"ola\": 3019,\n    \"Ġprogramme\": 3020,\n    \"Ġmanufacturing\": 3021,\n    \"Ġhitting\": 3022,\n    \"Ġx\": 3023,\n    \"Ġskin\": 3024,\n    \"Ġartist\": 3025,\n    \"Ġtells\": 3026,\n    \"Ġnearby\": 3027,\n    \"ĠDaniel\": 3028,\n    \"ĠPower\": 3029,\n    \"Ġdetermined\": 3030,\n    \"Ġactual\": 3031,\n    \"Ġtreated\": 3032,\n    \"Ġlived\": 3033,\n    \"Ġcomputer\": 3034,\n    \"Ġcool\": 3035,\n    \"oo\": 3036,\n    \"ĠPl\": 3037,\n    \"Ġeffects\": 3038,\n    \"Ġenvironmental\": 3039,\n    \"ĠMorgan\": 3040,\n    \"Ġflow\": 3041,\n    \"Ġachieve\": 3042,\n    \"ĠBell\": 3043,\n    \"Ġtesting\": 3044,\n    \"ĠBob\": 3045,\n    \"Ġwhatever\": 3046,\n    \"ĠBecause\": 3047,\n    \"US\": 3048,\n    \"ĠHollywood\": 3049,\n    \"Ġconflict\": 3050,\n    \"Ġwalking\": 3051,\n    \"ĠJudge\": 3052,\n    \"ĠAlabama\": 3053,\n    \"Ġaircraft\": 3054,\n    \"Ġte\": 3055,\n    \"well\": 3056,\n    \"Ġgoods\": 3057,\n    \"Ġidentify\": 3058,\n    \"Ġassociated\": 3059,\n    \"ĠVer\": 3060,\n    \"ĠEducation\": 3061,\n    \"Ġairport\": 3062,\n    \"IL\": 3063,\n    \"Ġfalling\": 3064,\n    \"Ġgiant\": 3065,\n    \"ĠMa\": 3066,\n    \"ĠMedical\": 3067,\n    \"Ġride\": 3068,\n    \"Ġden\": 3069,\n    \"º\": 3070,\n    \"ĠJose\": 3071,\n    \"Ġwest\": 3072,\n    \"ĠPacific\": 3073,\n    \"Ġvisitors\": 3074,\n    \"ĠWatch\": 3075,\n    \"ĠNations\": 3076,\n    \"Ġgains\": 3077,\n    \"Ġschedule\": 3078,\n    \"34\": 3079,\n    \"ĠExchange\": 3080,\n    \"Ġpayments\": 3081,\n    \"ĠII\": 3082,\n    \"70\": 3083,\n    \"No\": 3084,\n    \"ĠSyrian\": 3085,\n    \"ĠAdam\": 3086,\n    \"Ġne\": 3087,\n    \"Ġpartnership\": 3088,\n    \"Ġbl\": 3089,\n    \"ĠGeorgia\": 3090,\n    \"Ġsites\": 3091,\n    \"Ġmodels\": 3092,\n    \"Ġdegree\": 3093,\n    \"Ġdetermine\": 3094,\n    \"ĠWilson\": 3095,\n    \"Ġcontest\": 3096,\n    \"Ġprofessor\": 3097,\n    \"ĠChelsea\": 3098,\n    \"Ġmeaning\": 3099,\n    \"ĠGames\": 3100,\n    \"ĠTrust\": 3101,\n    \"ĠAsian\": 3102,\n    \"33\": 3103,\n    \"Ġlink\": 3104,\n    \"ĠUp\": 3105,\n    \"Ġholds\": 3106,\n    \"ĠTop\": 3107,\n    \"ĠItalian\": 3108,\n    \"ord\": 3109,\n    \"ĠKansas\": 3110,\n    \"Ġfarmers\": 3111,\n    \"Ġextended\": 3112,\n    \"Ġbirth\": 3113,\n    \"Ġreform\": 3114,\n    \"Ġrelations\": 3115,\n    \"Ġwrite\": 3116,\n    \"Ġsupporting\": 3117,\n    \"55\": 3118,\n    \"ita\": 3119,\n    \"Ġnotice\": 3120,\n    \"ster\": 3121,\n    \"Ġanimals\": 3122,\n    \"ĠJersey\": 3123,\n    \"Ġarm\": 3124,\n    \"ĠForeign\": 3125,\n    \"ĠLife\": 3126,\n    \"Ġtruly\": 3127,\n    \"ĠOnce\": 3128,\n    \"ĠMayor\": 3129,\n    \"ĠFree\": 3130,\n    \"ĠAgency\": 3131,\n    \"ĠWood\": 3132,\n    \"Ġpassing\": 3133,\n    \"DA\": 3134,\n    \"Ġ52\": 3135,\n    \"Ġmoves\": 3136,\n    \"Ġcom\": 3137,\n    \"house\": 3138,\n    \"ĠIts\": 3139,\n    \"Ġmarijuana\": 3140,\n    \"ines\": 3141,\n    \"Ġveteran\": 3142,\n    \"Ġvariety\": 3143,\n    \"ki\": 3144,\n    \"ff\": 3145,\n    \"amb\": 3146,\n    \"Ġlisted\": 3147,\n    \"Ġpushed\": 3148,\n    \"Ġvolume\": 3149,\n    \"Ġincreasingly\": 3150,\n    \"Ġkick\": 3151,\n    \"Ġrock\": 3152,\n    \"ank\": 3153,\n    \"Ġfees\": 3154,\n    \"Ġenable\": 3155,\n    \"Ġimages\": 3156,\n    \"Ġtruth\": 3157,\n    \"Ġministry\": 3158,\n    \"Ġrare\": 3159,\n    \"ĠDallas\": 3160,\n    \"ĠMinnesota\": 3161,\n    \"Ġcontributed\": 3162,\n    \"ĠCharles\": 3163,\n    \"Ġpercentage\": 3164,\n    \"Ġtechnical\": 3165,\n    \"ĠApp\": 3166,\n    \"Ġassistant\": 3167,\n    \"Ġinterests\": 3168,\n    \"Ġimmediate\": 3169,\n    \"38\": 3170,\n    \"ĠTown\": 3171,\n    \"Ġclosing\": 3172,\n    \"ĠAnthony\": 3173,\n    \"Ġsouthern\": 3174,\n    \"ase\": 3175,\n    \"ĠPutin\": 3176,\n    \"ĠForce\": 3177,\n    \"ba\": 3178,\n    \"Ġrefused\": 3179,\n    \"ĠStill\": 3180,\n    \"ix\": 3181,\n    \"ĠCol\": 3182,\n    \"Ġmaterials\": 3183,\n    \"Ġstructure\": 3184,\n    \"Ġdriven\": 3185,\n    \"Ġpatient\": 3186,\n    \"Ġbroken\": 3187,\n    \"Ġradio\": 3188,\n    \"Ġscale\": 3189,\n    \"Ġreplace\": 3190,\n    \"Ġ39\": 3191,\n    \"ĠLand\": 3192,\n    \"Ġdeputy\": 3193,\n    \"und\": 3194,\n    \"Ġcolor\": 3195,\n    \"OS\": 3196,\n    \"Ġroads\": 3197,\n    \"Ġcorruption\": 3198,\n    \"ĠRose\": 3199,\n    \"Ġemployee\": 3200,\n    \"ĠWater\": 3201,\n    \"Ġseats\": 3202,\n    \"Ġwalked\": 3203,\n    \"ec\": 3204,\n    \"Ġcents\": 3205,\n    \"Ġchain\": 3206,\n    \"Ġpayment\": 3207,\n    \"ĠAndroid\": 3208,\n    \"eb\": 3209,\n    \"Ġcommission\": 3210,\n    \"Ġthrow\": 3211,\n    \"Ġcount\": 3212,\n    \"Ġaccident\": 3213,\n    \"Ġexpensive\": 3214,\n    \"ered\": 3215,\n    \"ĠYes\": 3216,\n    \"ĠLouis\": 3217,\n    \"Ġstudies\": 3218,\n    \"Ġinvestigating\": 3219,\n    \"Ġcentury\": 3220,\n    \"Ġdiscussion\": 3221,\n    \"Ġinter\": 3222,\n    \"DAQ\": 3223,\n    \"ĠBefore\": 3224,\n    \"Ġinitially\": 3225,\n    \"*\": 3226,\n    \"Ġinvestments\": 3227,\n    \"Ġmulti\": 3228,\n    \"Ġtight\": 3229,\n    \"Ġconfident\": 3230,\n    \"Ġcounter\": 3231,\n    \"ĠQu\": 3232,\n    \"Ġgovernments\": 3233,\n    \"Ġarmed\": 3234,\n    \"Ġsuit\": 3235,\n    \"Ġrow\": 3236,\n    \"Ġlocations\": 3237,\n    \"Ġepisode\": 3238,\n    \"itch\": 3239,\n    \"Ġyounger\": 3240,\n    \"Ġfestival\": 3241,\n    \"Ġpitch\": 3242,\n    \"ĠOF\": 3243,\n    \"Ġtalked\": 3244,\n    \"ca\": 3245,\n    \"Ġprotests\": 3246,\n    \"Ġtargets\": 3247,\n    \"90\": 3248,\n    \"Ġoriginally\": 3249,\n    \"Ġsinger\": 3250,\n    \"Ġjourney\": 3251,\n    \"ug\": 3252,\n    \"Ġapply\": 3253,\n    \"Ġteacher\": 3254,\n    \"Ġchances\": 3255,\n    \"):\": 3256,\n    \"Ġdeaths\": 3257,\n    \"isation\": 3258,\n    \"ĠStephen\": 3259,\n    \"Ġcode\": 3260,\n    \"ĠChampionship\": 3261,\n    \"ĠJason\": 3262,\n    \"ĠAT\": 3263,\n    \"Ġaccept\": 3264,\n    \"ĠSeries\": 3265,\n    \"Ġvalues\": 3266,\n    \"Ġbed\": 3267,\n    \"ĠHarry\": 3268,\n    \"Ġflat\": 3269,\n    \"Ġtools\": 3270,\n    \"Ġpublicly\": 3271,\n    \"37\": 3272,\n    \"Ġpointed\": 3273,\n    \"ĠGolden\": 3274,\n    \"ps\": 3275,\n    \"Ġunable\": 3276,\n    \"ants\": 3277,\n    \"Ġestimate\": 3278,\n    \"Ġwarm\": 3279,\n    \"Ġbasic\": 3280,\n    \"ern\": 3281,\n    \"Ġraising\": 3282,\n    \"ĠRelated\": 3283,\n    \"Ġultimately\": 3284,\n    \"Ġnorthern\": 3285,\n    \"Ġplane\": 3286,\n    \"ĠVice\": 3287,\n    \"ĠRaj\": 3288,\n    \"ĠJustin\": 3289,\n    \"anc\": 3290,\n    \"Ġbrings\": 3291,\n    \"ĠArt\": 3292,\n    \"OT\": 3293,\n    \"Ġshift\": 3294,\n    \"ĠBBC\": 3295,\n    \"ĠSu\": 3296,\n    \"BS\": 3297,\n    \"Ġbag\": 3298,\n    \"Ġdoctor\": 3299,\n    \"Ġfill\": 3300,\n    \"Ġdowntown\": 3301,\n    \"Ġpossibility\": 3302,\n    \"ĠAg\": 3303,\n    \"Ġest\": 3304,\n    \"44\": 3305,\n    \"Ġstruggling\": 3306,\n    \"Ġlinked\": 3307,\n    \"Ġtickets\": 3308,\n    \"ĠJay\": 3309,\n    \"ĠCall\": 3310,\n    \"Ġstands\": 3311,\n    \"Ġwedding\": 3312,\n    \"Ġresident\": 3313,\n    \"eng\": 3314,\n    \"Ġleads\": 3315,\n    \"Ġadvance\": 3316,\n    \"ĠAtlanta\": 3317,\n    \"Ġtie\": 3318,\n    \"Ġadvanced\": 3319,\n    \"pt\": 3320,\n    \"burg\": 3321,\n    \"ĠEarlier\": 3322,\n    \"ĠSw\": 3323,\n    \"ĠZealand\": 3324,\n    \"Ġexercise\": 3325,\n    \"ĠAM\": 3326,\n    \"Ġaffect\": 3327,\n    \"Ġpossession\": 3328,\n    \"Ġinvolving\": 3329,\n    \"Ġ42\": 3330,\n    \"Ġwriter\": 3331,\n    \"ĠBeijing\": 3332,\n    \"Ġdoctors\": 3333,\n    \"Ġobviously\": 3334,\n    \"Ġer\": 3335,\n    \"ĠOlympic\": 3336,\n    \"Ġ75\": 3337,\n    \"ĠKhan\": 3338,\n    \"ĠFort\": 3339,\n    \"app\": 3340,\n    \"like\": 3341,\n    \"Ġsea\": 3342,\n    \"ock\": 3343,\n    \"Ġmix\": 3344,\n    \"ĠIraq\": 3345,\n    \"ĠMuslim\": 3346,\n    \"ĠFinally\": 3347,\n    \"Ġcontinuing\": 3348,\n    \"Ġpr\": 3349,\n    \"ĠKe\": 3350,\n    \"ĠJoseph\": 3351,\n    \"Ġexpects\": 3352,\n    \"Ġinstitutions\": 3353,\n    \"Ġconservative\": 3354,\n    \"own\": 3355,\n    \"ĠChairman\": 3356,\n    \"Ġreturning\": 3357,\n    \".-\": 3358,\n    \"Ġstood\": 3359,\n    \"Ġvision\": 3360,\n    \"ess\": 3361,\n    \"Ġadults\": 3362,\n    \"Ġyield\": 3363,\n    \"Ġprove\": 3364,\n    \"Ġorders\": 3365,\n    \"Ġdream\": 3366,\n    \"36\": 3367,\n    \"related\": 3368,\n    \"Ġsl\": 3369,\n    \"Ġeverybody\": 3370,\n    \"ui\": 3371,\n    \"Ġrepresents\": 3372,\n    \"Ġdiscussed\": 3373,\n    \"Ġbecomes\": 3374,\n    \"Ġvillage\": 3375,\n    \"CC\": 3376,\n    \"Ġnegotiations\": 3377,\n    \"ĠPhiladelphia\": 3378,\n    \"Ġcelebrate\": 3379,\n    \"Ġfarm\": 3380,\n    \"Ã§\": 3381,\n    \"Ġregistered\": 3382,\n    \"ĠGovernor\": 3383,\n    \"OL\": 3384,\n    \"ĠMon\": 3385,\n    \"Ġfiling\": 3386,\n    \"04\": 3387,\n    \"SE\": 3388,\n    \"ĠAssembly\": 3389,\n    \"Ġactress\": 3390,\n    \"Ġsi\": 3391,\n    \"Ġthank\": 3392,\n    \"Ġheading\": 3393,\n    \"ĠWho\": 3394,\n    \"Ġfamous\": 3395,\n    \"Ġconsecutive\": 3396,\n    \"Ġmarriage\": 3397,\n    \"ette\": 3398,\n    \"NAS\": 3399,\n    \"acks\": 3400,\n    \"ĠPlease\": 3401,\n    \"ĠDiego\": 3402,\n    \"Ġbaseball\": 3403,\n    \"ĠMoore\": 3404,\n    \"Ġties\": 3405,\n    \"Ġcarrying\": 3406,\n    \"que\": 3407,\n    \"Ġturning\": 3408,\n    \"ĠMcC\": 3409,\n    \"ĠKen\": 3410,\n    \"OR\": 3411,\n    \"ĠStock\": 3412,\n    \"Ġbuildings\": 3413,\n    \"49\": 3414,\n    \"ĠVan\": 3415,\n    \"39\": 3416,\n    \"ĠSeattle\": 3417,\n    \"Ġwild\": 3418,\n    \"Ġcrew\": 3419,\n    \"Ġroute\": 3420,\n    \"ĠTime\": 3421,\n    \"Ġtonight\": 3422,\n    \"Ġmoments\": 3423,\n    \"Ġvideos\": 3424,\n    \"Ġinternal\": 3425,\n    \"ĠLiverpool\": 3426,\n    \"port\": 3427,\n    \"Ġchair\": 3428,\n    \"Ġrival\": 3429,\n    \"ĠScotland\": 3430,\n    \"round\": 3431,\n    \"ith\": 3432,\n    \"Ġbreaking\": 3433,\n    \"Ġvoting\": 3434,\n    \"ically\": 3435,\n    \"Ġproducer\": 3436,\n    \"ĠLove\": 3437,\n    \"Ġremove\": 3438,\n    \"PA\": 3439,\n    \"Ġasset\": 3440,\n    \"Ġrequires\": 3441,\n    \"Ġsigning\": 3442,\n    \"ages\": 3443,\n    \"Ġimpressive\": 3444,\n    \"ĠIrish\": 3445,\n    \"Ġauthority\": 3446,\n    \"Ġruled\": 3447,\n    \"Ġaimed\": 3448,\n    \"Ġcaptain\": 3449,\n    \"AG\": 3450,\n    \"Ġplants\": 3451,\n    \"ĠAnderson\": 3452,\n    \"ĠSpanish\": 3453,\n    \"Ġbanking\": 3454,\n    \"Ġthreats\": 3455,\n    \"Ġsuspended\": 3456,\n    \"Ġtests\": 3457,\n    \"Ġreligious\": 3458,\n    \"Ġelectric\": 3459,\n    \"ĠREAD\": 3460,\n    \"Ġstrategic\": 3461,\n    \"Ġsplit\": 3462,\n    \"ex\": 3463,\n    \"Ġpractices\": 3464,\n    \"ĠIsraeli\": 3465,\n    \"ĠArabia\": 3466,\n    \"ĠMoscow\": 3467,\n    \"Ġfranchise\": 3468,\n    \"Ġcustody\": 3469,\n    \"ĠOld\": 3470,\n    \"Ġrequirements\": 3471,\n    \"Ġquarterly\": 3472,\n    \"Ġcomfortable\": 3473,\n    \"Ġcrimes\": 3474,\n    \"Ġheaded\": 3475,\n    \"Ġnewsletter\": 3476,\n    \"Ġanimal\": 3477,\n    \"Ġregulations\": 3478,\n    \"long\": 3479,\n    \"ĠCNN\": 3480,\n    \"Ġassists\": 3481,\n    \"Ġshopping\": 3482,\n    \"ĠGov\": 3483,\n    \"ĠSecurities\": 3484,\n    \"Ġassistance\": 3485,\n    \"Ġnor\": 3486,\n    \"Ġrelatively\": 3487,\n    \"Ġincreases\": 3488,\n    \"Ġgenerally\": 3489,\n    \"Ġ55\": 3490,\n    \"Ġgained\": 3491,\n    \"Ġ41\": 3492,\n    \"Ġpictures\": 3493,\n    \"gan\": 3494,\n    \"Ġpop\": 3495,\n    \"Ġupdates\": 3496,\n    \"ĠRepublic\": 3497,\n    \"Ġrebounds\": 3498,\n    \"ĠPatrick\": 3499,\n    \"Ġrelief\": 3500,\n    \"Ġacting\": 3501,\n    \"ĠFestival\": 3502,\n    \"Ġ2006\": 3503,\n    \"Ġboss\": 3504,\n    \"Ġtypes\": 3505,\n    \"65\": 3506,\n    \"ĠYet\": 3507,\n    \"Ġpurpose\": 3508,\n    \"ning\": 3509,\n    \"Ġmatters\": 3510,\n    \"Ġcompete\": 3511,\n    \"ball\": 3512,\n    \"ĠRam\": 3513,\n    \"Ġsw\": 3514,\n    \"ĠFollowing\": 3515,\n    \"ĠBush\": 3516,\n    \"Ġtroops\": 3517,\n    \"Ġsupposed\": 3518,\n    \"Ġfreedom\": 3519,\n    \"Ġfeatured\": 3520,\n    \"Ġstorage\": 3521,\n    \"ĠInformation\": 3522,\n    \"ĠHong\": 3523,\n    \"Ġgolf\": 3524,\n    \"Ġagents\": 3525,\n    \"Ġfraud\": 3526,\n    \"Ġminimum\": 3527,\n    \"Ġartists\": 3528,\n    \"Ġeat\": 3529,\n    \"high\": 3530,\n    \"ĠFormer\": 3531,\n    \"ĠKong\": 3532,\n    \"ĠJosh\": 3533,\n    \"ĠDelhi\": 3534,\n    \"Ġshowers\": 3535,\n    \"ĠAcademy\": 3536,\n    \"Ġapartment\": 3537,\n    \"Ġvan\": 3538,\n    \"Ġfish\": 3539,\n    \"oe\": 3540,\n    \"Ġfilms\": 3541,\n    \"ĠBo\": 3542,\n    \"Ġedge\": 3543,\n    \"Ġpossibly\": 3544,\n    \"Ġtweet\": 3545,\n    \"09\": 3546,\n    \"Ġresolution\": 3547,\n    \"jo\": 3548,\n    \"Ġkill\": 3549,\n    \"Ġ44\": 3550,\n    \"Ġcell\": 3551,\n    \"Ġscheme\": 3552,\n    \"Ġth\": 3553,\n    \"Ġbonds\": 3554,\n    \"Ġentry\": 3555,\n    \"Ġsecret\": 3556,\n    \"Ġ43\": 3557,\n    \"Ġending\": 3558,\n    \"Ġweren\": 3559,\n    \"ĠCredit\": 3560,\n    \"ĠLive\": 3561,\n    \"Ġretired\": 3562,\n    \"Ġmachine\": 3563,\n    \"Ġsummit\": 3564,\n    \"Ġsharing\": 3565,\n    \"Ġacquired\": 3566,\n    \"Ġera\": 3567,\n    \"Ġwear\": 3568,\n    \"ical\": 3569,\n    \"07\": 3570,\n    \"Ġexciting\": 3571,\n    \"li\": 3572,\n    \"BC\": 3573,\n    \"ĠSocial\": 3574,\n    \"Ġhistoric\": 3575,\n    \"ĠChe\": 3576,\n    \"ĠLewis\": 3577,\n    \"ira\": 3578,\n    \"Ġstolen\": 3579,\n    \"ĠSpeaking\": 3580,\n    \"Ġsleep\": 3581,\n    \"Ġspokeswoman\": 3582,\n    \"week\": 3583,\n    \"Ġpurchased\": 3584,\n    \"Ġimportance\": 3585,\n    \"EC\": 3586,\n    \"Ġends\": 3587,\n    \"Ġdress\": 3588,\n    \"Ġparliament\": 3589,\n    \"ĠCruz\": 3590,\n    \"Ġcards\": 3591,\n    \"hi\": 3592,\n    \"ĠEmail\": 3593,\n    \"Ġrepresent\": 3594,\n    \"Ġbrands\": 3595,\n    \"ĠSenior\": 3596,\n    \"Ġparticipants\": 3597,\n    \"Ġfly\": 3598,\n    \"Ġidentity\": 3599,\n    \"ĠHam\": 3600,\n    \"ĠSky\": 3601,\n    \"ĳ\": 3602,\n    \"SA\": 3603,\n    \"Ġpromised\": 3604,\n    \"Ġtrouble\": 3605,\n    \"Ġsuffering\": 3606,\n    \"Ġleaves\": 3607,\n    \"Ġsuggest\": 3608,\n    \"Sh\": 3609,\n    \"Ġbusy\": 3610,\n    \"Ġproperties\": 3611,\n    \"Ġworldwide\": 3612,\n    \"Ġcloud\": 3613,\n    \"ĠSEC\": 3614,\n    \"Ġclosely\": 3615,\n    \"Ġmanage\": 3616,\n    \"Ġnumerous\": 3617,\n    \"Ġbackground\": 3618,\n    \"ĠExpress\": 3619,\n    \"Ġ65\": 3620,\n    \"ĠTony\": 3621,\n    \"ĠMadrid\": 3622,\n    \"ev\": 3623,\n    \"der\": 3624,\n    \"Ġsignificantly\": 3625,\n    \"Ġalternative\": 3626,\n    \"Ġship\": 3627,\n    \"head\": 3628,\n    \"ators\": 3629,\n    \"Ġdinner\": 3630,\n    \"ax\": 3631,\n    \"SC\": 3632,\n    \"Ġcriticism\": 3633,\n    \"ĠMah\": 3634,\n    \"ĠMin\": 3635,\n    \"rie\": 3636,\n    \"ĠTour\": 3637,\n    \"Ġbench\": 3638,\n    \"Ġadds\": 3639,\n    \"Ġseriously\": 3640,\n    \"star\": 3641,\n    \"ĠJournal\": 3642,\n    \"ĠDi\": 3643,\n    \"ali\": 3644,\n    \"Ġsentence\": 3645,\n    \"ĠSeveral\": 3646,\n    \"Ġmayor\": 3647,\n    \"ati\": 3648,\n    \"Ġsuggests\": 3649,\n    \"Ġbehavior\": 3650,\n    \"Ġstronger\": 3651,\n    \"ĠFood\": 3652,\n    \"Ġclient\": 3653,\n    \"not\": 3654,\n    \"ĠPrice\": 3655,\n    \"Ġtargeted\": 3656,\n    \"ĠSingh\": 3657,\n    \"ĠNetwork\": 3658,\n    \"Ġprosecutors\": 3659,\n    \"Ġdirected\": 3660,\n    \"ĠDemocrat\": 3661,\n    \"bl\": 3662,\n    \"ues\": 3663,\n    \"ĠFamily\": 3664,\n    \"Ġconnected\": 3665,\n    \"ĠChampions\": 3666,\n    \"Ġroughly\": 3667,\n    \"Ġabsolutely\": 3668,\n    \"08\": 3669,\n    \"Ġpassengers\": 3670,\n    \"Ã¶\": 3671,\n    \"ĠSpecial\": 3672,\n    \"Ġcoast\": 3673,\n    \"Ġcomplaint\": 3674,\n    \"Ġ400\": 3675,\n    \"ĠEm\": 3676,\n    \"ves\": 3677,\n    \"Ġdogs\": 3678,\n    \"Ġhandle\": 3679,\n    \"Ġotherwise\": 3680,\n    \"Ġsees\": 3681,\n    \"Ġticket\": 3682,\n    \"ĠAward\": 3683,\n    \"All\": 3684,\n    \"Ġtask\": 3685,\n    \"Ġsongs\": 3686,\n    \"ĠAmong\": 3687,\n    \"Ġdedicated\": 3688,\n    \"Ġsteel\": 3689,\n    \"looking\": 3690,\n    \"Ġshortly\": 3691,\n    \"Ġtackle\": 3692,\n    \"ative\": 3693,\n    \"Ġminor\": 3694,\n    \"Ã¢\": 3695,\n    \"Ġprovider\": 3696,\n    \"vers\": 3697,\n    \"use\": 3698,\n    \"ives\": 3699,\n    \"Ġtypically\": 3700,\n    \"Ġarms\": 3701,\n    \"ĠAnt\": 3702,\n    \"ĠIS\": 3703,\n    \"Ġjump\": 3704,\n    \"ĠÂ©\": 3705,\n    \"47\": 3706,\n    \"aff\": 3707,\n    \"Ġmonthly\": 3708,\n    \"ĠMicrosoft\": 3709,\n    \"ĠCBS\": 3710,\n    \"Ġthreatened\": 3711,\n    \"Ġhonor\": 3712,\n    \"ĠMo\": 3713,\n    \"42\": 3714,\n    \"Ġinning\": 3715,\n    \"Ġpool\": 3716,\n    \"Ġhealthcare\": 3717,\n    \"ĠStory\": 3718,\n    \"ĠTennessee\": 3719,\n    \"Ġpromote\": 3720,\n    \"EL\": 3721,\n    \"Ġemotional\": 3722,\n    \"Ġpe\": 3723,\n    \"Ġfactor\": 3724,\n    \"Ġinvestigators\": 3725,\n    \"Ľ\": 3726,\n    \"ĠBack\": 3727,\n    \"ĠProject\": 3728,\n    \"Ġcu\": 3729,\n    \"side\": 3730,\n    \"Ġmessages\": 3731,\n    \"TH\": 3732,\n    \"eg\": 3733,\n    \"Ġexperiences\": 3734,\n    \"Ġcausing\": 3735,\n    \"Ġjoining\": 3736,\n    \"Ġpackage\": 3737,\n    \"Ġbodies\": 3738,\n    \"Ġlots\": 3739,\n    \"ĠHarris\": 3740,\n    \"Ġcl\": 3741,\n    \"ĠInternet\": 3742,\n    \"free\": 3743,\n    \"Ġperformed\": 3744,\n    \"Ġpieces\": 3745,\n    \"buy\": 3746,\n    \"Ġcaption\": 3747,\n    \"Ġweb\": 3748,\n    \"Ġcontracts\": 3749,\n    \"At\": 3750,\n    \"Ġattempted\": 3751,\n    \"Ġunlikely\": 3752,\n    \"Ġclick\": 3753,\n    \"Ġinvest\": 3754,\n    \"IM\": 3755,\n    \"ĠView\": 3756,\n    \"Ġneighborhood\": 3757,\n    \"Ġring\": 3758,\n    \"ĠFour\": 3759,\n    \"ail\": 3760,\n    \"46\": 3761,\n    \"One\": 3762,\n    \"Ġnative\": 3763,\n    \"CH\": 3764,\n    \"OM\": 3765,\n    \"Ġalcohol\": 3766,\n    \"ĠVal\": 3767,\n    \"Ġcharacters\": 3768,\n    \"ĠPat\": 3769,\n    \"Ġpoliticians\": 3770,\n    \"ĠMag\": 3771,\n    \"Ġbegins\": 3772,\n    \"ĠAk\": 3773,\n    \"Ġlos\": 3774,\n    \"Ġpersonnel\": 3775,\n    \"Ġenjoyed\": 3776,\n    \"ĠTechnology\": 3777,\n    \"Ġsun\": 3778,\n    \"ĠIT\": 3779,\n    \"Ġdocument\": 3780,\n    \"Ġdeficit\": 3781,\n    \"Ġcoalition\": 3782,\n    \"Ġmemory\": 3783,\n    \"Ġpushing\": 3784,\n    \"any\": 3785,\n    \"ified\": 3786,\n    \"Ġfounder\": 3787,\n    \"Ġ2000\": 3788,\n    \"2017\": 3789,\n    \"Ġvisited\": 3790,\n    \"ĠThough\": 3791,\n    \"ph\": 3792,\n    \"Ġsoft\": 3793,\n    \"Ġflag\": 3794,\n    \"Ġmom\": 3795,\n    \"inch\": 3796,\n    \"ĠSamsung\": 3797,\n    \"Ġapps\": 3798,\n    \"Ġtouchdown\": 3799,\n    \"ĠCare\": 3800,\n    \"ĠMrs\": 3801,\n    \"Ġredistributed\": 3802,\n    \"Ġencourage\": 3803,\n    \"ched\": 3804,\n    \"Ġtend\": 3805,\n    \"Ġregions\": 3806,\n    \"pp\": 3807,\n    \"IP\": 3808,\n    \"br\": 3809,\n    \"ush\": 3810,\n    \"Ġargued\": 3811,\n    \"Ġjunior\": 3812,\n    \"BA\": 3813,\n    \"Ġsevere\": 3814,\n    \"ĠNIGHT\": 3815,\n    \"Ġdef\": 3816,\n    \"Ġsurrounding\": 3817,\n    \"48\": 3818,\n    \"Ġengine\": 3819,\n    \"Ġfilled\": 3820,\n    \"Ġseventh\": 3821,\n    \"Ġbattery\": 3822,\n    \"ĠAllen\": 3823,\n    \"Ġguidance\": 3824,\n    \"Ġroll\": 3825,\n    \"Ġrural\": 3826,\n    \"Ġexpert\": 3827,\n    \"Ġconvicted\": 3828,\n    \"Ġlikes\": 3829,\n    \"ĠRo\": 3830,\n    \"Ġgrown\": 3831,\n    \"Ġretirement\": 3832,\n    \"Ġintended\": 3833,\n    \"Ġmis\": 3834,\n    \"Ġarmy\": 3835,\n    \"Ġdance\": 3836,\n    \"ĠThank\": 3837,\n    \"Ġent\": 3838,\n    \"Ġoutlook\": 3839,\n    \"Ġpara\": 3840,\n    \"Ġdry\": 3841,\n    \"ĠTO\": 3842,\n    \"era\": 3843,\n    \"Ġwaste\": 3844,\n    \"Ġfaster\": 3845,\n    \"ĠEagles\": 3846,\n    \"TA\": 3847,\n    \"ĠFrank\": 3848,\n    \"Ã\": 3849,\n    \"LE\": 3850,\n    \"ura\": 3851,\n    \"ko\": 3852,\n    \"ao\": 3853,\n    \"Ġdistribution\": 3854,\n    \"Ġimprovement\": 3855,\n    \"Ġplayoff\": 3856,\n    \"Ġacquisition\": 3857,\n    \"ĠCH\": 3858,\n    \"Ġtomorrow\": 3859,\n    \"Ġstruggle\": 3860,\n    \"ĠHuman\": 3861,\n    \"Ġnewly\": 3862,\n    \"oon\": 3863,\n    \"ĠNe\": 3864,\n    \"con\": 3865,\n    \"sc\": 3866,\n    \"Ġunless\": 3867,\n    \"Ġtransition\": 3868,\n    \"ten\": 3869,\n    \"ĠInter\": 3870,\n    \"Ġequal\": 3871,\n    \"Ġrec\": 3872,\n    \"Ġappointed\": 3873,\n    \"Ġwake\": 3874,\n    \"ĠEarth\": 3875,\n    \"ose\": 3876,\n    \"ĠEastern\": 3877,\n    \"Ġsoldiers\": 3878,\n    \"ĠParliament\": 3879,\n    \"Ġsets\": 3880,\n    \"Ġattempts\": 3881,\n    \"ĠIllinois\": 3882,\n    \"Ġrevenues\": 3883,\n    \"ĠWil\": 3884,\n    \"Ġheads\": 3885,\n    \"Ġprepare\": 3886,\n    \"Ġpriority\": 3887,\n    \"PS\": 3888,\n    \"ĠJo\": 3889,\n    \"ĠNBC\": 3890,\n    \"Ġtherefore\": 3891,\n    \"yn\": 3892,\n    \"Ġinitiative\": 3893,\n    \"ct\": 3894,\n    \"Ġcoffee\": 3895,\n    \"ĠFair\": 3896,\n    \"43\": 3897,\n    \"den\": 3898,\n    \"form\": 3899,\n    \"ova\": 3900,\n    \"Ġappropriate\": 3901,\n    \"ĠPlay\": 3902,\n    \"Ġaccepted\": 3903,\n    \"Ġcreative\": 3904,\n    \"Ġfollows\": 3905,\n    \"Ġrescue\": 3906,\n    \"Ġtree\": 3907,\n    \"With\": 3908,\n    \"ĠNetflix\": 3909,\n    \"ĠFootball\": 3910,\n    \"Ġsurprised\": 3911,\n    \"Ġlowest\": 3912,\n    \"800\": 3913,\n    \"amp\": 3914,\n    \"Ġworried\": 3915,\n    \"mar\": 3916,\n    \"ran\": 3917,\n    \"Ġvisiting\": 3918,\n    \"Ġselected\": 3919,\n    \"ĠMusic\": 3920,\n    \"ĠAnn\": 3921,\n    \"Ġexplain\": 3922,\n    \"ging\": 3923,\n    \"Ġwidely\": 3924,\n    \"Ġsquare\": 3925,\n    \"Ġtrends\": 3926,\n    \"Ġimproving\": 3927,\n    \"ĠHead\": 3928,\n    \"ĠQueen\": 3929,\n    \"ĠSociety\": 3930,\n    \"Ġcutting\": 3931,\n    \"ĠGOP\": 3932,\n    \"03\": 3933,\n    \"',\": 3934,\n    \"ET\": 3935,\n    \"ĠDrive\": 3936,\n    \"oll\": 3937,\n    \"ato\": 3938,\n    \"ĠSea\": 3939,\n    \"Ġjury\": 3940,\n    \"ĠRights\": 3941,\n    \"Ġinvestor\": 3942,\n    \"ĠABC\": 3943,\n    \"Ġtool\": 3944,\n    \"ĠAre\": 3945,\n    \"Ġrejected\": 3946,\n    \"Ġemerging\": 3947,\n    \"Ġcounts\": 3948,\n    \"Ġnations\": 3949,\n    \"Ġfalse\": 3950,\n    \"Ġtreat\": 3951,\n    \"va\": 3952,\n    \"Ġweak\": 3953,\n    \"ĠHighway\": 3954,\n    \"down\": 3955,\n    \"Ġstruggled\": 3956,\n    \"ĠMP\": 3957,\n    \"Ġguests\": 3958,\n    \"Ġgender\": 3959,\n    \"Ġhouses\": 3960,\n    \"rit\": 3961,\n    \"ĠWild\": 3962,\n    \"Ġstreak\": 3963,\n    \"uc\": 3964,\n    \"ĠReserve\": 3965,\n    \"ĠRatings\": 3966,\n    \"alt\": 3967,\n    \"Ġgreatest\": 3968,\n    \"Ġlawyers\": 3969,\n    \"Ġreaching\": 3970,\n    \"Ġtemperatures\": 3971,\n    \"To\": 3972,\n    \"Ġoutstanding\": 3973,\n    \"Ġpasses\": 3974,\n    \"Ġfaith\": 3975,\n    \"inc\": 3976,\n    \"Ġcr\": 3977,\n    \"Ġinformed\": 3978,\n    \"oz\": 3979,\n    \"Ġtrees\": 3980,\n    \"Ġsending\": 3981,\n    \"Ġ150\": 3982,\n    \"bo\": 3983,\n    \"Ġwine\": 3984,\n    \"ros\": 3985,\n    \"Ġsuspected\": 3986,\n    \"Ġrepeatedly\": 3987,\n    \"Ġhat\": 3988,\n    \"Ġshape\": 3989,\n    \"ĠWh\": 3990,\n    \"Ġassist\": 3991,\n    \"Ġstress\": 3992,\n    \"Ġfeed\": 3993,\n    \"ark\": 3994,\n    \"ored\": 3995,\n    \"Ġwatched\": 3996,\n    \"Ġincredible\": 3997,\n    \"cl\": 3998,\n    \"nt\": 3999,\n    \"Ġentertainment\": 4000,\n    \"ih\": 4001,\n    \"Ġbeauty\": 4002,\n    \"Ġbi\": 4003,\n    \"ĠLocal\": 4004,\n    \"Ġsat\": 4005,\n    \"41\": 4006,\n    \"Ġbroad\": 4007,\n    \"Ġheavily\": 4008,\n    \"Ġengaged\": 4009,\n    \"Ġspecifically\": 4010,\n    \"ĠMen\": 4011,\n    \"ĠRoss\": 4012,\n    \"Ġ2005\": 4013,\n    \"ST\": 4014,\n    \"95\": 4015,\n    \"Ġdownload\": 4016,\n    \"400\": 4017,\n    \"Ġsentenced\": 4018,\n    \"ĠCatholic\": 4019,\n    \"ĠOklahoma\": 4020,\n    \"Ġthrew\": 4021,\n    \"Ġworry\": 4022,\n    \"Ġimp\": 4023,\n    \"Ġdrove\": 4024,\n    \"Ġcolleagues\": 4025,\n    \"Ġagenda\": 4026,\n    \"64\": 4027,\n    \"ĠEach\": 4028,\n    \"Ġfee\": 4029,\n    \"New\": 4030,\n    \"ium\": 4031,\n    \"Ġspokesperson\": 4032,\n    \"Ġbills\": 4033,\n    \"Ġ47\": 4034,\n    \"ĠAfghanistan\": 4035,\n    \"Ġinvited\": 4036,\n    \"ĠYouTube\": 4037,\n    \"Ġanniversary\": 4038,\n    \"Ġdozen\": 4039,\n    \"ram\": 4040,\n    \"ĠOnly\": 4041,\n    \"Ġemployment\": 4042,\n    \"Getty\": 4043,\n    \"Ġgap\": 4044,\n    \"Ġsweet\": 4045,\n    \"ĠLittle\": 4046,\n    \"Ġinf\": 4047,\n    \"ying\": 4048,\n    \"Ġglass\": 4049,\n    \"Ġclasses\": 4050,\n    \"Ġcoal\": 4051,\n    \"ĠSub\": 4052,\n    \"Ġduty\": 4053,\n    \"CA\": 4054,\n    \"Ġcoaches\": 4055,\n    \"Â\": 4056,\n    \"anna\": 4057,\n    \"ĠSk\": 4058,\n    \"Ġ46\": 4059,\n    \"ison\": 4060,\n    \"ille\": 4061,\n    \"ĠST\": 4062,\n    \"ric\": 4063,\n    \"Ġparticipate\": 4064,\n    \"Ġequ\": 4065,\n    \"Ġrich\": 4066,\n    \"Ġrespectively\": 4067,\n    \"Ġexpenses\": 4068,\n    \"Ġcombination\": 4069,\n    \"right\": 4070,\n    \"Ġshareholders\": 4071,\n    \"Ġturns\": 4072,\n    \"Ġearn\": 4073,\n    \"Ġ51\": 4074,\n    \"ured\": 4075,\n    \"Ġdrink\": 4076,\n    \"ĠKar\": 4077,\n    \"ĠShares\": 4078,\n    \"ĠMid\": 4079,\n    \"ĠGetty\": 4080,\n    \"Ġbridge\": 4081,\n    \"lo\": 4082,\n    \"Ġinspired\": 4083,\n    \"Ġsurface\": 4084,\n    \"Ġgift\": 4085,\n    \"ence\": 4086,\n    \"Ġchallenging\": 4087,\n    \"Ġoffices\": 4088,\n    \"Ġsuspects\": 4089,\n    \"ĠFinance\": 4090,\n    \"Ġab\": 4091,\n    \"bound\": 4092,\n    \"Ġmomentum\": 4093,\n    \"Ġbacked\": 4094,\n    \"Ġparent\": 4095,\n    \"Ġcrucial\": 4096,\n    \"ave\": 4097,\n    \"Ġdealing\": 4098,\n    \"Ġregulatory\": 4099,\n    \"Ġapparently\": 4100,\n    \"ĠMat\": 4101,\n    \"Ġapart\": 4102,\n    \"Ġport\": 4103,\n    \"ole\": 4104,\n    \"Ġbeach\": 4105,\n    \"Ġcultural\": 4106,\n    \"Ġinstitutional\": 4107,\n    \"Ġbeating\": 4108,\n    \"ĠIowa\": 4109,\n    \"ĠAli\": 4110,\n    \"67\": 4111,\n    \"Ġje\": 4112,\n    \"ays\": 4113,\n    \"Ġweekly\": 4114,\n    \"Ġbirthday\": 4115,\n    \"Ġpipeline\": 4116,\n    \"Ġknee\": 4117,\n    \"Ġsolar\": 4118,\n    \"ĠPe\": 4119,\n    \"Ġcategory\": 4120,\n    \"ĠArea\": 4121,\n    \"ky\": 4122,\n    \"ures\": 4123,\n    \"06\": 4124,\n    \"ĠBall\": 4125,\n    \"Ġsemi\": 4126,\n    \"ĠHamilton\": 4127,\n    \"hip\": 4128,\n    \"ĠPh\": 4129,\n    \"ĠNext\": 4130,\n    \"Ġathletes\": 4131,\n    \"ii\": 4132,\n    \"Ġmovies\": 4133,\n    \"han\": 4134,\n    \"net\": 4135,\n    \"Ġplastic\": 4136,\n    \"Ġbehalf\": 4137,\n    \"gen\": 4138,\n    \"Ġfindings\": 4139,\n    \"Ġstretch\": 4140,\n    \"ĠSa\": 4141,\n    \"Ġofficially\": 4142,\n    \"ĠSarah\": 4143,\n    \"Ġprivacy\": 4144,\n    \"ĠMad\": 4145,\n    \"Ġnone\": 4146,\n    \"gh\": 4147,\n    \"On\": 4148,\n    \"Ġdrama\": 4149,\n    \"ĠFl\": 4150,\n    \"ika\": 4151,\n    \"ĠArsenal\": 4152,\n    \"Ġviolent\": 4153,\n    \"UN\": 4154,\n    \"called\": 4155,\n    \"59\": 4156,\n    \"Ġhate\": 4157,\n    \"Ġrelationships\": 4158,\n    \"Ġgranted\": 4159,\n    \"ĠJon\": 4160,\n    \"Ġlisten\": 4161,\n    \"season\": 4162,\n    \"Ġfewer\": 4163,\n    \"GA\": 4164,\n    \"ĠLabour\": 4165,\n    \"Ġremarks\": 4166,\n    \"ĠJonathan\": 4167,\n    \"ĠRos\": 4168,\n    \"sey\": 4169,\n    \"ĠOntario\": 4170,\n    \"ĠThompson\": 4171,\n    \"ĠNight\": 4172,\n    \"Ġranked\": 4173,\n    \"ĠUkraine\": 4174,\n    \"Ġimmigrants\": 4175,\n    \"Ġdegrees\": 4176,\n    \"ĠGe\": 4177,\n    \"Ġlabor\": 4178,\n    \"umb\": 4179,\n    \"ĠYORK\": 4180,\n    \"Ġallies\": 4181,\n    \"sp\": 4182,\n    \"hed\": 4183,\n    \"sw\": 4184,\n    \"Ġtariffs\": 4185,\n    \"SP\": 4186,\n    \"Ġclassic\": 4187,\n    \"Ġawards\": 4188,\n    \"ents\": 4189,\n    \"Ġfix\": 4190,\n    \"Ġsoccer\": 4191,\n    \"Ġconcert\": 4192,\n    \"ust\": 4193,\n    \"Ġadult\": 4194,\n    \"Ġoutput\": 4195,\n    \"Ġmanaging\": 4196,\n    \"02\": 4197,\n    \"Ġpromise\": 4198,\n    \"Ġawareness\": 4199,\n    \"Ġgross\": 4200,\n    \"Ġentering\": 4201,\n    \"Ġpo\": 4202,\n    \"oj\": 4203,\n    \"Ġmetal\": 4204,\n    \"Ġexit\": 4205,\n    \"Ġexcellent\": 4206,\n    \"Ġclubs\": 4207,\n    \"hold\": 4208,\n    \"Ġreplaced\": 4209,\n    \"ĠClass\": 4210,\n    \"Ġscientists\": 4211,\n    \"Ġprimarily\": 4212,\n    \"ĠMer\": 4213,\n    \"Ã£o\": 4214,\n    \"Ġcircumstances\": 4215,\n    \"ades\": 4216,\n    \"Ġsupplies\": 4217,\n    \"aker\": 4218,\n    \"ĠSand\": 4219,\n    \"Ġscandal\": 4220,\n    \"Ġsettlement\": 4221,\n    \"ĠWisconsin\": 4222,\n    \"ĠWarriors\": 4223,\n    \"ĠAustin\": 4224,\n    \"Ġjournalists\": 4225,\n    \"ening\": 4226,\n    \"Ġreflect\": 4227,\n    \"ĠBuy\": 4228,\n    \"ĠAwards\": 4229,\n    \"Ġselection\": 4230,\n    \"ĠBel\": 4231,\n    \"bury\": 4232,\n    \"Ġtechnologies\": 4233,\n    \"%,\": 4234,\n    \"ime\": 4235,\n    \"ĠÄ\": 4236,\n    \"ĠAdministration\": 4237,\n    \"Ġchannel\": 4238,\n    \"Star\": 4239,\n    \"Ġtransport\": 4240,\n    \"Ġawarded\": 4241,\n    \"ena\": 4242,\n    \"Ġmotor\": 4243,\n    \"orn\": 4244,\n    \"kin\": 4245,\n    \"Ġfeaturing\": 4246,\n    \"Ġphones\": 4247,\n    \"ĠAND\": 4248,\n    \"Ġrelevant\": 4249,\n    \"ĠSee\": 4250,\n    \"Ġwinners\": 4251,\n    \"Ġdad\": 4252,\n    \"ĠSource\": 4253,\n    \"ĠCheck\": 4254,\n    \"aut\": 4255,\n    \"ĠFar\": 4256,\n    \"Ġopponents\": 4257,\n    \"Ġoutcome\": 4258,\n    \"Ġdoors\": 4259,\n    \"Ġsuicide\": 4260,\n    \"ima\": 4261,\n    \"Ġjumped\": 4262,\n    \"Ġperspective\": 4263,\n    \"Ġtransportation\": 4264,\n    \"Ġthinks\": 4265,\n    \"ĠMor\": 4266,\n    \"Ġdeadline\": 4267,\n    \"Ġ53\": 4268,\n    \"ĠDeputy\": 4269,\n    \"ery\": 4270,\n    \"Ġdetailed\": 4271,\n    \"uch\": 4272,\n    \"ĠBur\": 4273,\n    \"Ġtrades\": 4274,\n    \"ĠGreg\": 4275,\n    \"Ġzero\": 4276,\n    \"erson\": 4277,\n    \"ĠChildren\": 4278,\n    \"Ġdu\": 4279,\n    \"66\": 4280,\n    \"Ġmixed\": 4281,\n    \"ĠBarack\": 4282,\n    \"54\": 4283,\n    \"Ġterritory\": 4284,\n    \"Ġac\": 4285,\n    \"Ġconcept\": 4286,\n    \"ĠAdd\": 4287,\n    \"Ġourselves\": 4288,\n    \"Ġreaction\": 4289,\n    \"ĠSydney\": 4290,\n    \"ink\": 4291,\n    \"Ġconsistent\": 4292,\n    \"Ġboat\": 4293,\n    \"room\": 4294,\n    \"Ġdozens\": 4295,\n    \"Ġeffectively\": 4296,\n    \"but\": 4297,\n    \"Ġmotion\": 4298,\n    \"Ġalive\": 4299,\n    \"ĠKey\": 4300,\n    \"weight\": 4301,\n    \"Ġexports\": 4302,\n    \"Ġoperate\": 4303,\n    \"Ġregime\": 4304,\n    \"ĠAuthority\": 4305,\n    \"och\": 4306,\n    \"ĠCR\": 4307,\n    \"leg\": 4308,\n    \"Ġforget\": 4309,\n    \"American\": 4310,\n    \"bs\": 4311,\n    \"Ġthoughts\": 4312,\n    \"ĠSign\": 4313,\n    \"ĠPatriots\": 4314,\n    \"Ġbrief\": 4315,\n    \"ĠOregon\": 4316,\n    \"ĠBal\": 4317,\n    \"Ġmine\": 4318,\n    \"Ġciting\": 4319,\n    \"Ġmagazine\": 4320,\n    \"more\": 4321,\n    \"ERS\": 4322,\n    \"ĠBer\": 4323,\n    \"ua\": 4324,\n    \"ox\": 4325,\n    \"ĠMain\": 4326,\n    \"Ġinstance\": 4327,\n    \"tr\": 4328,\n    \"Ġrestaurants\": 4329,\n    \"ora\": 4330,\n    \"Ġharassment\": 4331,\n    \"\\\",\\\"\": 4332,\n    \"Ł\": 4333,\n    \"Ġsilver\": 4334,\n    \"ĠMueller\": 4335,\n    \"ĠSenator\": 4336,\n    \"ĠEvery\": 4337,\n    \"Ġfootage\": 4338,\n    \"ms\": 4339,\n    \"Ġopposed\": 4340,\n    \"ĠLink\": 4341,\n    \"Ġver\": 4342,\n    \"Ġpleased\": 4343,\n    \"ame\": 4344,\n    \"ending\": 4345,\n    \"Ġrivals\": 4346,\n    \"ida\": 4347,\n    \"ike\": 4348,\n    \"ta\": 4349,\n    \"ĠCook\": 4350,\n    \"Ġheadquarters\": 4351,\n    \"ear\": 4352,\n    \"Ġaggressive\": 4353,\n    \"Ġcourts\": 4354,\n    \"ĠMuseum\": 4355,\n    \"Ġim\": 4356,\n    \"ĠHoldings\": 4357,\n    \"Ġcommunication\": 4358,\n    \"Ġphase\": 4359,\n    \"yl\": 4360,\n    \"Ġpowers\": 4361,\n    \"Ġproved\": 4362,\n    \"Ġcarbon\": 4363,\n    \"Ġaside\": 4364,\n    \"ĠOlympics\": 4365,\n    \"Ġgathered\": 4366,\n    \"ĠPennsylvania\": 4367,\n    \"Ġsmartphone\": 4368,\n    \"ĠMet\": 4369,\n    \"ĠHurricane\": 4370,\n    \"Ġprotected\": 4371,\n    \"Ġcommunications\": 4372,\n    \"Ġemerged\": 4373,\n    \"Ġaim\": 4374,\n    \"Ġstable\": 4375,\n    \"ides\": 4376,\n    \"GB\": 4377,\n    \"Ġentirely\": 4378,\n    \"Ġmissile\": 4379,\n    \"ĠGen\": 4380,\n    \"Ġunclear\": 4381,\n    \"Ġelectricity\": 4382,\n    \"ology\": 4383,\n    \"away\": 4384,\n    \"Ġlicense\": 4385,\n    \"ĠPittsburgh\": 4386,\n    \"Ġcameras\": 4387,\n    \"Ġmusical\": 4388,\n    \"Ġmanagers\": 4389,\n    \"57\": 4390,\n    \"Ġscores\": 4391,\n    \"Ġprofile\": 4392,\n    \"hel\": 4393,\n    \"¼\": 4394,\n    \"Ġshouldn\": 4395,\n    \"RA\": 4396,\n    \");\": 4397,\n    \"Ġpermanent\": 4398,\n    \"ome\": 4399,\n    \"Ġet\": 4400,\n    \"Ġmar\": 4401,\n    \"Ġfavor\": 4402,\n    \"Ġmaker\": 4403,\n    \"Ġdiscussions\": 4404,\n    \"ory\": 4405,\n    \"Ġsharp\": 4406,\n    \"Ġpleaded\": 4407,\n    \"Ġpassenger\": 4408,\n    \"quarter\": 4409,\n    \"Ġdem\": 4410,\n    \"Ġversus\": 4411,\n    \"Ġmainly\": 4412,\n    \"Ġeighth\": 4413,\n    \"ĠAirport\": 4414,\n    \"ĠCross\": 4415,\n    \"million\": 4416,\n    \"ĠNas\": 4417,\n    \"Ġcited\": 4418,\n    \"56\": 4419,\n    \"Ġyes\": 4420,\n    \"ĠBelow\": 4421,\n    \"arn\": 4422,\n    \"ĠTurkish\": 4423,\n    \"ĠSl\": 4424,\n    \"Ġstepped\": 4425,\n    \"Ġproducers\": 4426,\n    \"Ġovernight\": 4427,\n    \"Ġsounds\": 4428,\n    \"52\": 4429,\n    \"Ġ64\": 4430,\n    \"Ġ54\": 4431,\n    \"58\": 4432,\n    \"ĠClark\": 4433,\n    \"ĠRick\": 4434,\n    \"Ġgr\": 4435,\n    \"ĠMont\": 4436,\n    \"Ġbeer\": 4437,\n    \"une\": 4438,\n    \"Ġreporter\": 4439,\n    \"Ġcharity\": 4440,\n    \"Ġeating\": 4441,\n    \"Ġextend\": 4442,\n    \"Ġguess\": 4443,\n    \"NA\": 4444,\n    \"Ġhedge\": 4445,\n    \"Ġencouraged\": 4446,\n    \"owned\": 4447,\n    \"ĠMel\": 4448,\n    \"ĠKentucky\": 4449,\n    \"ace\": 4450,\n    \"Ġlineup\": 4451,\n    \"Ġhosts\": 4452,\n    \"Ġcapable\": 4453,\n    \"PR\": 4454,\n    \"ĠArts\": 4455,\n    \"Ġcontroversial\": 4456,\n    \"Ġhosted\": 4457,\n    \"ries\": 4458,\n    \"Ġroster\": 4459,\n    \"Ġfixed\": 4460,\n    \"ĠWalker\": 4461,\n    \"ged\": 4462,\n    \"Ġdisaster\": 4463,\n    \"Ġdispute\": 4464,\n    \"ĠDenver\": 4465,\n    \"ĠTrade\": 4466,\n    \"ute\": 4467,\n    \"ese\": 4468,\n    \"cy\": 4469,\n    \"Ġgrant\": 4470,\n    \"ĠMax\": 4471,\n    \"Ġdistance\": 4472,\n    \"isc\": 4473,\n    \"Ġeditor\": 4474,\n    \"ĠDave\": 4475,\n    \"Ġperformances\": 4476,\n    \"Ġlay\": 4477,\n    \"Ġvulnerable\": 4478,\n    \"ĠMurray\": 4479,\n    \"ĠâĤ¬\": 4480,\n    \"Ġmining\": 4481,\n    \"Ġ2004\": 4482,\n    \"level\": 4483,\n    \"ability\": 4484,\n    \"Ġauto\": 4485,\n    \"Ġfake\": 4486,\n    \"Ġattacked\": 4487,\n    \"ona\": 4488,\n    \"ups\": 4489,\n    \"ened\": 4490,\n    \"Ġfallen\": 4491,\n    \"Ġstations\": 4492,\n    \"ĠContact\": 4493,\n    \"itz\": 4494,\n    \"Ġincidents\": 4495,\n    \"Ġcomplaints\": 4496,\n    \"Ġoperates\": 4497,\n    \"Ġrefugees\": 4498,\n    \"Ġessential\": 4499,\n    \"ĠTest\": 4500,\n    \"Ġdemands\": 4501,\n    \"Ġroles\": 4502,\n    \"yr\": 4503,\n    \"Ġacts\": 4504,\n    \"Ġusual\": 4505,\n    \"ring\": 4506,\n    \"Ġhanded\": 4507,\n    \"ĠMatthew\": 4508,\n    \"hour\": 4509,\n    \"Ġindustries\": 4510,\n    \"Ġshoot\": 4511,\n    \"ĠAuthorities\": 4512,\n    \"Ġprobe\": 4513,\n    \"ĠUtah\": 4514,\n    \"ĠRBI\": 4515,\n    \"ĠAD\": 4516,\n    \"Ġprospect\": 4517,\n    \"outs\": 4518,\n    \"ĠUber\": 4519,\n    \"Ġbright\": 4520,\n    \"Ġmention\": 4521,\n    \"Ġsavings\": 4522,\n    \"ĠMiss\": 4523,\n    \"ONDON\": 4524,\n    \"Ġ1990\": 4525,\n    \"arm\": 4526,\n    \"ĠTen\": 4527,\n    \"These\": 4528,\n    \"Ġexplains\": 4529,\n    \"minute\": 4530,\n    \"85\": 4531,\n    \"Ġmaximum\": 4532,\n    \"Ġro\": 4533,\n    \"Ġrookie\": 4534,\n    \"Ġstudio\": 4535,\n    \"ĠCam\": 4536,\n    \"ĠGal\": 4537,\n    \"Ġdefend\": 4538,\n    \"hand\": 4539,\n    \"53\": 4540,\n    \"ĠOil\": 4541,\n    \"Ġserves\": 4542,\n    \"Ġsn\": 4543,\n    \"ios\": 4544,\n    \"ĠDefense\": 4545,\n    \"AB\": 4546,\n    \"Ġhired\": 4547,\n    \"Ġsupports\": 4548,\n    \"Ġpremium\": 4549,\n    \"ef\": 4550,\n    \"Ġfailing\": 4551,\n    \"ĠIndiana\": 4552,\n    \"Ġexp\": 4553,\n    \"Ġobjective\": 4554,\n    \"Ġaffordable\": 4555,\n    \"ĠCom\": 4556,\n    \"ĠThanks\": 4557,\n    \"Ġanywhere\": 4558,\n    \"Ġconfirm\": 4559,\n    \"ited\": 4560,\n    \"Ġrepresenting\": 4561,\n    \"Ġwitness\": 4562,\n    \"69\": 4563,\n    \"Ġclaiming\": 4564,\n    \"Ġviolation\": 4565,\n    \"Ġhistorical\": 4566,\n    \"med\": 4567,\n    \"Ġpreparing\": 4568,\n    \"ĠTech\": 4569,\n    \"Ġposts\": 4570,\n    \"OC\": 4571,\n    \"ĠGraham\": 4572,\n    \"ĠGl\": 4573,\n    \"ĠLions\": 4574,\n    \"ales\": 4575,\n    \"ĠID\": 4576,\n    \"Ġcorrect\": 4577,\n    \"ĠAntonio\": 4578,\n    \"Ġadvertising\": 4579,\n    \"Ġeastern\": 4580,\n    \"OW\": 4581,\n    \"Ġholdings\": 4582,\n    \"Ġpolls\": 4583,\n    \"ĠSH\": 4584,\n    \"Ġexecutives\": 4585,\n    \"ĠJewish\": 4586,\n    \"ĠGary\": 4587,\n    \"Ġprize\": 4588,\n    \"ĠCommissioner\": 4589,\n    \"Ġcells\": 4590,\n    \"ify\": 4591,\n    \"Ġlunch\": 4592,\n    \"Ġdemocracy\": 4593,\n    \"ĠEr\": 4594,\n    \"Ġregularly\": 4595,\n    \"Ġresulted\": 4596,\n    \"ĠAve\": 4597,\n    \"ĠPartners\": 4598,\n    \"Ġrewritten\": 4599,\n    \"Ġlo\": 4600,\n    \"Ġcooperation\": 4601,\n    \"ĠGulf\": 4602,\n    \"Ġsmoke\": 4603,\n    \"ĠMemorial\": 4604,\n    \"Ġwave\": 4605,\n    \"Ġfears\": 4606,\n    \"Ġkid\": 4607,\n    \"ĠGiants\": 4608,\n    \"Ġrecovered\": 4609,\n    \"row\": 4610,\n    \"ĠRadio\": 4611,\n    \"ĠBarcelona\": 4612,\n    \"Ġwonderful\": 4613,\n    \"ĠDow\": 4614,\n    \"Ġstream\": 4615,\n    \"ĠSimon\": 4616,\n    \"Ġdetail\": 4617,\n    \"Ġvolunteers\": 4618,\n    \"ĠInd\": 4619,\n    \"Ġforms\": 4620,\n    \"mann\": 4621,\n    \"ĠRay\": 4622,\n    \"oor\": 4623,\n    \"ĠTake\": 4624,\n    \"Ġrepresented\": 4625,\n    \"het\": 4626,\n    \"Ġblow\": 4627,\n    \"aged\": 4628,\n    \"RE\": 4629,\n    \"ĠMissouri\": 4630,\n    \"Ġcovering\": 4631,\n    \"Ġprofits\": 4632,\n    \"Ġconcluded\": 4633,\n    \"Ġthus\": 4634,\n    \"ĠColumbia\": 4635,\n    \"ode\": 4636,\n    \"ĠZimbabwe\": 4637,\n    \"Ġdisclosed\": 4638,\n    \"Ġlifted\": 4639,\n    \"ĠSean\": 4640,\n    \"ĠHarvey\": 4641,\n    \"ĠPlus\": 4642,\n    \"ces\": 4643,\n    \"ĠGreece\": 4644,\n    \"ĠLady\": 4645,\n    \"Ġdelay\": 4646,\n    \"Ġkitchen\": 4647,\n    \"ĠIndex\": 4648,\n    \"Ġbear\": 4649,\n    \"Ġputs\": 4650,\n    \"new\": 4651,\n    \"88\": 4652,\n    \"ĠAsh\": 4653,\n    \"Å¡\": 4654,\n    \"Ġperforming\": 4655,\n    \"law\": 4656,\n    \"ĠPart\": 4657,\n    \"Ġindicated\": 4658,\n    \"Ġannounce\": 4659,\n    \"Ġcompensation\": 4660,\n    \"Ġka\": 4661,\n    \"ĠScience\": 4662,\n    \"ris\": 4663,\n    \"Ġrecommendations\": 4664,\n    \"ĠSecond\": 4665,\n    \"Ġlights\": 4666,\n    \"Ġtemporary\": 4667,\n    \"urs\": 4668,\n    \"Ġwestern\": 4669,\n    \"stone\": 4670,\n    \"68\": 4671,\n    \"ĠDisney\": 4672,\n    \"Ġplayoffs\": 4673,\n    \"Ġjudges\": 4674,\n    \"Ġengineering\": 4675,\n    \"ĠPen\": 4676,\n    \"ĠPal\": 4677,\n    \"Ġobvious\": 4678,\n    \"ĠBridge\": 4679,\n    \"ĠEnd\": 4680,\n    \"ĠArab\": 4681,\n    \"Ġexcept\": 4682,\n    \"Ġhole\": 4683,\n    \"class\": 4684,\n    \"Ġcauses\": 4685,\n    \"Ġconnect\": 4686,\n    \"ĠAI\": 4687,\n    \"An\": 4688,\n    \"Ġchose\": 4689,\n    \"ĠElizabeth\": 4690,\n    \"min\": 4691,\n    \"Ġproper\": 4692,\n    \"ĠNHL\": 4693,\n    \"Ġraces\": 4694,\n    \"Ġinnovation\": 4695,\n    \"Ġsugar\": 4696,\n    \"600\": 4697,\n    \"ĠModi\": 4698,\n    \"illa\": 4699,\n    \"Ġtrillion\": 4700,\n    \"ĠSar\": 4701,\n    \"ĠAffairs\": 4702,\n    \"Ġimpossible\": 4703,\n    \"Ġguide\": 4704,\n    \"Ġcaptured\": 4705,\n    \"ĠSales\": 4706,\n    \"Ġspecies\": 4707,\n    \"51\": 4708,\n    \"Ġar\": 4709,\n    \"Ġmaster\": 4710,\n    \"Ġstayed\": 4711,\n    \"iro\": 4712,\n    \"ĠEconomic\": 4713,\n    \"Ġvast\": 4714,\n    \"ili\": 4715,\n    \"Ġpet\": 4716,\n    \"ye\": 4717,\n    \"77\": 4718,\n    \"Ġkeeps\": 4719,\n    \"ĠPhil\": 4720,\n    \"ĠEPS\": 4721,\n    \"ĠRegional\": 4722,\n    \"Ġsectors\": 4723,\n    \"Ġdesire\": 4724,\n    \"ĠStanley\": 4725,\n    \"¾\": 4726,\n    \"Ġunknown\": 4727,\n    \"Ġpot\": 4728,\n    \"ĠPR\": 4729,\n    \"Ġknowing\": 4730,\n    \"Ġflying\": 4731,\n    \"ĠTreasury\": 4732,\n    \"iers\": 4733,\n    \"enn\": 4734,\n    \"ably\": 4735,\n    \"Ġsick\": 4736,\n    \"Ġmanner\": 4737,\n    \"Ġmanufacturers\": 4738,\n    \"Ġchampions\": 4739,\n    \"gy\": 4740,\n    \"Part\": 4741,\n    \"ister\": 4742,\n    \"ĠMountain\": 4743,\n    \"Ġimagine\": 4744,\n    \"Ġportion\": 4745,\n    \"ĠCamp\": 4746,\n    \"Ġchemical\": 4747,\n    \"ible\": 4748,\n    \"ĠAnaly\": 4749,\n    \"ĠBureau\": 4750,\n    \"Ġpm\": 4751,\n    \"Ġupdated\": 4752,\n    \"Ġetc\": 4753,\n    \"ĠField\": 4754,\n    \"iles\": 4755,\n    \"Ġobtained\": 4756,\n    \"Ġstick\": 4757,\n    \"Ġcat\": 4758,\n    \"har\": 4759,\n    \"Ġmarked\": 4760,\n    \"Ġmedium\": 4761,\n    \"ĠDes\": 4762,\n    \"People\": 4763,\n    \"Ġwealth\": 4764,\n    \"ores\": 4765,\n    \"ĠBaltimore\": 4766,\n    \"Ġtip\": 4767,\n    \"Ġdismissed\": 4768,\n    \"ĠVictoria\": 4769,\n    \"ĠBrad\": 4770,\n    \"Ch\": 4771,\n    \"Ġ56\": 4772,\n    \"Ġstadium\": 4773,\n    \"eth\": 4774,\n    \"Ġthunder\": 4775,\n    \"Ġtested\": 4776,\n    \"Ġdrawn\": 4777,\n    \"Ġcounsel\": 4778,\n    \"ld\": 4779,\n    \"Ġspirit\": 4780,\n    \"uss\": 4781,\n    \"Ġtheme\": 4782,\n    \"my\": 4783,\n    \"Ġnecessarily\": 4784,\n    \"Ġelements\": 4785,\n    \"Ġcollected\": 4786,\n    \"ĠRes\": 4787,\n    \"ĠMaryland\": 4788,\n    \"ĠEnter\": 4789,\n    \"Ġfounded\": 4790,\n    \"ae\": 4791,\n    \"Ġpilot\": 4792,\n    \"Ġshoulder\": 4793,\n    \"PC\": 4794,\n    \"Ġargument\": 4795,\n    \"Ġyen\": 4796,\n    \"Ġreceiver\": 4797,\n    \"Ġharm\": 4798,\n    \"ĠET\": 4799,\n    \"Ġprotesters\": 4800,\n    \"Ġ72\": 4801,\n    \"ĠAaron\": 4802,\n    \"Ġed\": 4803,\n    \"Ġexpecting\": 4804,\n    \"\\\":\\\"\": 4805,\n    \"Ġbike\": 4806,\n    \"Äĩ\": 4807,\n    \"Ġluxury\": 4808,\n    \"half\": 4809,\n    \"ĠBarbara\": 4810,\n    \"Ġfoundation\": 4811,\n    \"Ġill\": 4812,\n    \"Ġsubmitted\": 4813,\n    \"Ġdeeply\": 4814,\n    \"Ġhospitals\": 4815,\n    \"ĠBJP\": 4816,\n    \"Ġshock\": 4817,\n    \"Ġplatforms\": 4818,\n    \"Ġsummary\": 4819,\n    \"ĠWhere\": 4820,\n    \"Ġcelebration\": 4821,\n    \"iff\": 4822,\n    \"Ġveterans\": 4823,\n    \"Ġachieved\": 4824,\n    \"fl\": 4825,\n    \"Ġactivists\": 4826,\n    \"ĠManager\": 4827,\n    \"Ġformal\": 4828,\n    \"Ġformed\": 4829,\n    \"Ġinvestigate\": 4830,\n    \"ĠKyle\": 4831,\n    \"Ġ:\": 4832,\n    \"ĠRa\": 4833,\n    \"ovic\": 4834,\n    \"Ġdrinking\": 4835,\n    \"Ġnetworks\": 4836,\n    \"ĠAlexander\": 4837,\n    \"ĠOs\": 4838,\n    \"Ġ)\": 4839,\n    \"Ġbomb\": 4840,\n    \"Ġrecalled\": 4841,\n    \"ito\": 4842,\n    \"ient\": 4843,\n    \"Ġrepresentatives\": 4844,\n    \"ĠChrist\": 4845,\n    \"ĠWay\": 4846,\n    \"Ġdeadly\": 4847,\n    \"Ġinvesting\": 4848,\n    \"ĠRussell\": 4849,\n    \"Ġconsumption\": 4850,\n    \"Ġharder\": 4851,\n    \"Ġbail\": 4852,\n    \"Ġcritics\": 4853,\n    \"Ġdanger\": 4854,\n    \"Ġdrew\": 4855,\n    \"ĠSol\": 4856,\n    \"Ġcopyright\": 4857,\n    \"ĠHenry\": 4858,\n    \"Ġbuyers\": 4859,\n    \"Ġresidential\": 4860,\n    \"Ġmaintenance\": 4861,\n    \"pr\": 4862,\n    \"Ġmarks\": 4863,\n    \"Ġages\": 4864,\n    \"Ġcovers\": 4865,\n    \"Ġton\": 4866,\n    \"Ġtitles\": 4867,\n    \"ĠPS\": 4868,\n    \"ĠEvans\": 4869,\n    \"Ġmigrants\": 4870,\n    \"Ġflights\": 4871,\n    \"Ġmonitoring\": 4872,\n    \"Ġaddressed\": 4873,\n    \"Ġvital\": 4874,\n    \"Ġcontrolled\": 4875,\n    \"Ġweapon\": 4876,\n    \"Ġinches\": 4877,\n    \"Ġreduction\": 4878,\n    \"Ġurban\": 4879,\n    \"Ġcoaching\": 4880,\n    \"Ġreducing\": 4881,\n    \"ila\": 4882,\n    \"Ġrealize\": 4883,\n    \"Ġmeat\": 4884,\n    \"Ġref\": 4885,\n    \"Ġoverseas\": 4886,\n    \"Ġblame\": 4887,\n    \"Ġterrorist\": 4888,\n    \"Ġstuck\": 4889,\n    \"ĠUs\": 4890,\n    \"esh\": 4891,\n    \"pro\": 4892,\n    \"Ġ58\": 4893,\n    \"ough\": 4894,\n    \"Ġexposure\": 4895,\n    \"ĠAbu\": 4896,\n    \"state\": 4897,\n    \"Ġproviders\": 4898,\n    \"Ġfore\": 4899,\n    \"Ġjet\": 4900,\n    \"bar\": 4901,\n    \"Ġownership\": 4902,\n    \"ret\": 4903,\n    \"Ġupset\": 4904,\n    \"Ġfacts\": 4905,\n    \"Ġpurchasing\": 4906,\n    \"Ġreforms\": 4907,\n    \"Ġriver\": 4908,\n    \"Ġsomebody\": 4909,\n    \"Ġguest\": 4910,\n    \"iy\": 4911,\n    \"Ġauction\": 4912,\n    \"ĠReading\": 4913,\n    \"Ġconsequences\": 4914,\n    \"Ġrepresentative\": 4915,\n    \"Ġappointment\": 4916,\n    \"add\": 4917,\n    \"Ġcollaboration\": 4918,\n    \"ĠTesla\": 4919,\n    \"ĠCohen\": 4920,\n    \"Ġengagement\": 4921,\n    \"Ġspeaks\": 4922,\n    \"EST\": 4923,\n    \"Ġexposed\": 4924,\n    \"Ġmaintained\": 4925,\n    \"rs\": 4926,\n    \"Ġdating\": 4927,\n    \"ĠProgram\": 4928,\n    \"board\": 4929,\n    \"Ġracing\": 4930,\n    \"Ġpension\": 4931,\n    \"ign\": 4932,\n    \"iti\": 4933,\n    \"ĠFive\": 4934,\n    \"Ġextensive\": 4935,\n    \"ĠHa\": 4936,\n    \"ĠPoint\": 4937,\n    \"ĠMexican\": 4938,\n    \"Ġexpanded\": 4939,\n    \"Ġtotally\": 4940,\n    \"Ġinvestigations\": 4941,\n    \"ĠOrleans\": 4942,\n    \"Ġcycle\": 4943,\n    \"ĠESPN\": 4944,\n    \"ifying\": 4945,\n    \"Ġcup\": 4946,\n    \"ĠAz\": 4947,\n    \"ĠInvestors\": 4948,\n    \"Ġengage\": 4949,\n    \"reg\": 4950,\n    \"Ġfought\": 4951,\n    \"Ġterrorism\": 4952,\n    \"Ġblocked\": 4953,\n    \"ĠOK\": 4954,\n    \"Äį\": 4955,\n    \"72\": 4956,\n    \"Ġdestroyed\": 4957,\n    \"«\": 4958,\n    \"Ġstaying\": 4959,\n    \"Ġafford\": 4960,\n    \"Ġappearances\": 4961,\n    \"ĠHills\": 4962,\n    \"Ġcrore\": 4963,\n    \"Ġstrategies\": 4964,\n    \"Ġtips\": 4965,\n    \"ĠSm\": 4966,\n    \"ĠFr\": 4967,\n    \"Ġbanned\": 4968,\n    \"ĠSon\": 4969,\n    \"ask\": 4970,\n    \"Ġlimits\": 4971,\n    \"Ġrecognition\": 4972,\n    \"Ġeligible\": 4973,\n    \"ĠGar\": 4974,\n    \"Ġvolatility\": 4975,\n    \"Ġlaid\": 4976,\n    \"nes\": 4977,\n    \"Ġgrade\": 4978,\n    \"ĠRE\": 4979,\n    \"ĠHart\": 4980,\n    \"Ġ57\": 4981,\n    \"oma\": 4982,\n    \"Ġuncertainty\": 4983,\n    \"Ġrecognized\": 4984,\n    \"ĠPC\": 4985,\n    \"Ġchosen\": 4986,\n    \"uz\": 4987,\n    \"Ġadviser\": 4988,\n    \"una\": 4989,\n    \"Ġassessment\": 4990,\n    \"Ġreveal\": 4991,\n    \"mo\": 4992,\n    \"After\": 4993,\n    \"ĠBro\": 4994,\n    \"ĠOff\": 4995,\n    \"Ġpeak\": 4996,\n    \"Ġreferred\": 4997,\n    \"ĠSC\": 4998,\n    \"Ġ2003\": 4999,\n    \"ification\": 5000,\n    \"Ġshutdown\": 5001,\n    \"ĠOfficials\": 5002,\n    \"ias\": 5003,\n    \"Ġextreme\": 5004,\n    \"Ġflood\": 5005,\n    \"Ġhockey\": 5006,\n    \"Ġwage\": 5007,\n    \"ĠNet\": 5008,\n    \"Ġdamaged\": 5009,\n    \"Ġreplacement\": 5010,\n    \"ĠMaria\": 5011,\n    \"Ġcreation\": 5012,\n    \"Ġguns\": 5013,\n    \"aci\": 5014,\n    \"Ġworker\": 5015,\n    \"do\": 5016,\n    \"Ġviewers\": 5017,\n    \"Ġseed\": 5018,\n    \"sts\": 5019,\n    \"Ġtouchdowns\": 5020,\n    \"Ġmistake\": 5021,\n    \"ray\": 5022,\n    \"ull\": 5023,\n    \"Ġpricing\": 5024,\n    \"Ġstrongly\": 5025,\n    \"Ġaims\": 5026,\n    \"ĠNavy\": 5027,\n    \"ĠEgypt\": 5028,\n    \"ker\": 5029,\n    \"Ġve\": 5030,\n    \"ĠSteven\": 5031,\n    \"Ġres\": 5032,\n    \"ational\": 5033,\n    \"Ġrequests\": 5034,\n    \"Ġemissions\": 5035,\n    \"ĠArena\": 5036,\n    \"uma\": 5037,\n    \"ĠAtlantic\": 5038,\n    \"hr\": 5039,\n    \"ĠAFP\": 5040,\n    \"ĠSquare\": 5041,\n    \"Ġcontribute\": 5042,\n    \"Ġfunction\": 5043,\n    \"Ġdec\": 5044,\n    \"ĠNelson\": 5045,\n    \"89\": 5046,\n    \"Ġreferendum\": 5047,\n    \"ĠPre\": 5048,\n    \"Ġapplied\": 5049,\n    \"ĠGMT\": 5050,\n    \"ĠIranian\": 5051,\n    \"ĠNigerian\": 5052,\n    \"ĠAny\": 5053,\n    \"NG\": 5054,\n    \"Ġacknowledged\": 5055,\n    \"Ġreferring\": 5056,\n    \"Ġventure\": 5057,\n    \"Ġimports\": 5058,\n    \"Ġblog\": 5059,\n    \"Ġfutures\": 5060,\n    \"OU\": 5061,\n    \"ĠUFC\": 5062,\n    \"Ġneither\": 5063,\n    \"Ġextension\": 5064,\n    \"hes\": 5065,\n    \"ĠMed\": 5066,\n    \"76\": 5067,\n    \"Ġsustainable\": 5068,\n    \"ains\": 5069,\n    \"Ġreputation\": 5070,\n    \"ĠVancouver\": 5071,\n    \"Ġbasically\": 5072,\n    \"acy\": 5073,\n    \"Ġsad\": 5074,\n    \"ĠFrancis\": 5075,\n    \"ĠKennedy\": 5076,\n    \"ĠNevada\": 5077,\n    \"ĠLu\": 5078,\n    \"ras\": 5079,\n    \"ĠAv\": 5080,\n    \"Ġrear\": 5081,\n    \"ĠHo\": 5082,\n    \"Ġproperly\": 5083,\n    \"abe\": 5084,\n    \"ĠHotel\": 5085,\n    \"Ġopinions\": 5086,\n    \"under\": 5087,\n    \"ĠStation\": 5088,\n    \"ĠFOR\": 5089,\n    \"ops\": 5090,\n    \"Ġadopted\": 5091,\n    \"ĠSwiss\": 5092,\n    \"ĠCountry\": 5093,\n    \"ĠTer\": 5094,\n    \"ĠAndy\": 5095,\n    \"Me\": 5096,\n    \"ĠCooper\": 5097,\n    \"ĠTigers\": 5098,\n    \"ĠCreek\": 5099,\n    \"Ġgay\": 5100,\n    \"iner\": 5101,\n    \"ĠAN\": 5102,\n    \"Ġbird\": 5103,\n    \"lla\": 5104,\n    \"ĠKate\": 5105,\n    \"ĠPet\": 5106,\n    \"ni\": 5107,\n    \"Ġprospects\": 5108,\n    \"ater\": 5109,\n    \"ites\": 5110,\n    \"Ġescape\": 5111,\n    \"lam\": 5112,\n    \"ake\": 5113,\n    \"Ġ1980\": 5114,\n    \"ĠLag\": 5115,\n    \"Ġsuccessfully\": 5116,\n    \"Ġdistricts\": 5117,\n    \"Ġministers\": 5118,\n    \"aries\": 5119,\n    \"Ġframe\": 5120,\n    \"ĠON\": 5121,\n    \"ĠEuro\": 5122,\n    \"ĠMarkets\": 5123,\n    \"Ġregister\": 5124,\n    \"Ġdefeated\": 5125,\n    \"Ġdevelopments\": 5126,\n    \"Ġninth\": 5127,\n    \"Ġquiet\": 5128,\n    \"Ġgenerated\": 5129,\n    \"Ġvaluable\": 5130,\n    \"Ġrecommended\": 5131,\n    \"ĠTheatre\": 5132,\n    \"ĠCap\": 5133,\n    \"bed\": 5134,\n    \"Ġreference\": 5135,\n    \"Ġease\": 5136,\n    \"oring\": 5137,\n    \"Ġ66\": 5138,\n    \"Ġimprovements\": 5139,\n    \"Ġelsewhere\": 5140,\n    \"ĠHillary\": 5141,\n    \"Ġdefender\": 5142,\n    \"ĠRight\": 5143,\n    \"zy\": 5144,\n    \"Ġcomprehensive\": 5145,\n    \"Ġspotted\": 5146,\n    \"ĠOakland\": 5147,\n    \"ĠOk\": 5148,\n    \"ĠSystem\": 5149,\n    \"ique\": 5150,\n    \"Ġpersons\": 5151,\n    \"Ġexist\": 5152,\n    \"Ġbroader\": 5153,\n    \"Ġclinical\": 5154,\n    \"Ġ2001\": 5155,\n    \"oul\": 5156,\n    \"Ġsecurities\": 5157,\n    \"ghan\": 5158,\n    \"Ġshelter\": 5159,\n    \"ero\": 5160,\n    \"ATED\": 5161,\n    \"Ġhosting\": 5162,\n    \"Ġselect\": 5163,\n    \"ĠKavanaugh\": 5164,\n    \"Ġrestrictions\": 5165,\n    \"osa\": 5166,\n    \"Ġyields\": 5167,\n    \"ĠLA\": 5168,\n    \"Ġ59\": 5169,\n    \"Ġwonder\": 5170,\n    \"Ġabsence\": 5171,\n    \"Ã¼r\": 5172,\n    \"ÅĤ\": 5173,\n    \"DP\": 5174,\n    \"Ġelectronic\": 5175,\n    \"Ġillegally\": 5176,\n    \"Ġmicro\": 5177,\n    \"ĠNEW\": 5178,\n    \"Ġhall\": 5179,\n    \"Ġaged\": 5180,\n    \"Ġtemperature\": 5181,\n    \"cast\": 5182,\n    \"atic\": 5183,\n    \"Ġlegacy\": 5184,\n    \"Ġaffairs\": 5185,\n    \"ji\": 5186,\n    \"ĠResources\": 5187,\n    \"Ġgang\": 5188,\n    \"winning\": 5189,\n    \"Ġattending\": 5190,\n    \"aro\": 5191,\n    \"Ġfriendly\": 5192,\n    \"aine\": 5193,\n    \"Ġcannabis\": 5194,\n    \"Ġairline\": 5195,\n    \"Ġnoting\": 5196,\n    \"Ġprofessionals\": 5197,\n    \"ĠFREE\": 5198,\n    \"RC\": 5199,\n    \"Ġfinancing\": 5200,\n    \"Ġindependence\": 5201,\n    \"ved\": 5202,\n    \"Ġresulting\": 5203,\n    \"Ġsteady\": 5204,\n    \"ĠWinter\": 5205,\n    \"uring\": 5206,\n    \"Ġhoped\": 5207,\n    \"98\": 5208,\n    \"Ġpresentation\": 5209,\n    \"aya\": 5210,\n    \"Ġrated\": 5211,\n    \"osh\": 5212,\n    \"ĠAnalysis\": 5213,\n    \"=\": 5214,\n    \"Ġdonations\": 5215,\n    \"IR\": 5216,\n    \"Ġcombat\": 5217,\n    \"ĠHoward\": 5218,\n    \"anda\": 5219,\n    \"79\": 5220,\n    \"Ġinvested\": 5221,\n    \"Ġexpanding\": 5222,\n    \"omb\": 5223,\n    \"ress\": 5224,\n    \"ble\": 5225,\n    \"Ġjournalist\": 5226,\n    \"ĠWoods\": 5227,\n    \"Ġcenters\": 5228,\n    \"ott\": 5229,\n    \"Ġstreaming\": 5230,\n    \"Ġterror\": 5231,\n    \"Ġsustained\": 5232,\n    \"ĠWWE\": 5233,\n    \"pre\": 5234,\n    \"ÅŁ\": 5235,\n    \"ait\": 5236,\n    \"Ġarrival\": 5237,\n    \"Ġresidence\": 5238,\n    \"Ġextent\": 5239,\n    \"Ġarrive\": 5240,\n    \"Ġ2002\": 5241,\n    \"Ġestablish\": 5242,\n    \"74\": 5243,\n    \"ĠArgentina\": 5244,\n    \"ĠDem\": 5245,\n    \"inn\": 5246,\n    \"aud\": 5247,\n    \"ĠNCAA\": 5248,\n    \"Ġquestioned\": 5249,\n    \"Ġballot\": 5250,\n    \"Ġmin\": 5251,\n    \"Ġlandscape\": 5252,\n    \"Ġhorse\": 5253,\n    \"Ġopponent\": 5254,\n    \"iel\": 5255,\n    \"Ġprompted\": 5256,\n    \"atory\": 5257,\n    \"Ġlift\": 5258,\n    \"Ġassociation\": 5259,\n    \"cher\": 5260,\n    \"Ġdefending\": 5261,\n    \"Ġtiny\": 5262,\n    \"Ġpoverty\": 5263,\n    \"ĠSafety\": 5264,\n    \"Ġpetition\": 5265,\n    \"ĠLimited\": 5266,\n    \"ĠCA\": 5267,\n    \"FC\": 5268,\n    \"Ãł\": 5269,\n    \"oni\": 5270,\n    \"Ġmonitor\": 5271,\n    \"ÃŃa\": 5272,\n    \"MA\": 5273,\n    \"Ġanswers\": 5274,\n    \"ĠMitchell\": 5275,\n    \"Ġbo\": 5276,\n    \"ĠShah\": 5277,\n    \"Ġsm\": 5278,\n    \"Ġmedal\": 5279,\n    \"ĠCivil\": 5280,\n    \"Ġrecognize\": 5281,\n    \"key\": 5282,\n    \"Ġpregnant\": 5283,\n    \"Ġspots\": 5284,\n    \"ante\": 5285,\n    \"Ġacademic\": 5286,\n    \"Ġinitiatives\": 5287,\n    \"Ġsecured\": 5288,\n    \"ĠCL\": 5289,\n    \"ils\": 5290,\n    \"Ġanticipated\": 5291,\n    \"Ġinvolvement\": 5292,\n    \"ĠMake\": 5293,\n    \"Ġinsisted\": 5294,\n    \"ĠWales\": 5295,\n    \"Ġclothing\": 5296,\n    \"Ġtracks\": 5297,\n    \"Ġsymptoms\": 5298,\n    \"Ġplate\": 5299,\n    \"ĠNY\": 5300,\n    \"Ġretailers\": 5301,\n    \"ĠPan\": 5302,\n    \"Ġfled\": 5303,\n    \"Ġquoted\": 5304,\n    \"Ġsaved\": 5305,\n    \"ĠCarter\": 5306,\n    \"Ġteaching\": 5307,\n    \"ĠTokyo\": 5308,\n    \"ĠCr\": 5309,\n    \"ĠSix\": 5310,\n    \"ĠPicture\": 5311,\n    \"Ġrecover\": 5312,\n    \"Ġcomedy\": 5313,\n    \"ree\": 5314,\n    \"Ġstrikes\": 5315,\n    \"ĠSanders\": 5316,\n    \"sel\": 5317,\n    \"Ġgraduate\": 5318,\n    \"Ġpending\": 5319,\n    \"St\": 5320,\n    \"Ġwarrant\": 5321,\n    \"Ġhonest\": 5322,\n    \"ĠGM\": 5323,\n    \"Ġnoticed\": 5324,\n    \"ĠGalaxy\": 5325,\n    \"ider\": 5326,\n    \"Ġproposals\": 5327,\n    \"Ġwore\": 5328,\n    \"Ġindeed\": 5329,\n    \"EM\": 5330,\n    \"ĠChannel\": 5331,\n    \"ances\": 5332,\n    \"ĠBrady\": 5333,\n    \"86\": 5334,\n    \"Ġgotten\": 5335,\n    \"Ġthrowing\": 5336,\n    \"ĠLeader\": 5337,\n    \"ĠVideo\": 5338,\n    \"71\": 5339,\n    \"Ġwelcomed\": 5340,\n    \"NEW\": 5341,\n    \"Ġfairly\": 5342,\n    \"Ġpromises\": 5343,\n    \"ĠSilver\": 5344,\n    \"Ġrape\": 5345,\n    \"Ġopener\": 5346,\n    \"ares\": 5347,\n    \"ĠSir\": 5348,\n    \"making\": 5349,\n    \"Ġcur\": 5350,\n    \"Ġrooms\": 5351,\n    \"73\": 5352,\n    \"Ġamounts\": 5353,\n    \"ĠIndustry\": 5354,\n    \"ĠDar\": 5355,\n    \"Ġ62\": 5356,\n    \"ted\": 5357,\n    \"Ġabroad\": 5358,\n    \"ĠMaybe\": 5359,\n    \"Ġreaders\": 5360,\n    \"oke\": 5361,\n    \"Ġpublication\": 5362,\n    \"ĠJean\": 5363,\n    \"Ġoperator\": 5364,\n    \"ĠHaving\": 5365,\n    \"ĠMil\": 5366,\n    \"life\": 5367,\n    \"Ġgenerate\": 5368,\n    \"ĠCraig\": 5369,\n    \"ĠMass\": 5370,\n    \"ĠBh\": 5371,\n    \"Ġrequested\": 5372,\n    \"Ġcrazy\": 5373,\n    \"ĠSpace\": 5374,\n    \"Ġcopy\": 5375,\n    \"Ġexport\": 5376,\n    \"Ġcontext\": 5377,\n    \"Ġbr\": 5378,\n    \"62\": 5379,\n    \"ĠRobinson\": 5380,\n    \"Ġcyber\": 5381,\n    \"ENT\": 5382,\n    \"BI\": 5383,\n    \"arg\": 5384,\n    \"Ġspeaker\": 5385,\n    \"Ġdramatic\": 5386,\n    \"ĠOl\": 5387,\n    \"ĠMill\": 5388,\n    \"Ġtrained\": 5389,\n    \"Ġediting\": 5390,\n    \"Ġsalary\": 5391,\n    \"Ġdirectors\": 5392,\n    \"Ġexplore\": 5393,\n    \"Ġlucky\": 5394,\n    \"Ġprominent\": 5395,\n    \"Ġbrothers\": 5396,\n    \"Ġneck\": 5397,\n    \"icht\": 5398,\n    \"ĠWatson\": 5399,\n    \"born\": 5400,\n    \"Ġproven\": 5401,\n    \"Ġprincipal\": 5402,\n    \"Ġedition\": 5403,\n    \"Ed\": 5404,\n    \"Ġswitch\": 5405,\n    \"maker\": 5406,\n    \"Ġrelative\": 5407,\n    \"mi\": 5408,\n    \"ĠBruce\": 5409,\n    \"ho\": 5410,\n    \"ĠScottish\": 5411,\n    \"water\": 5412,\n    \"ĠSport\": 5413,\n    \"ĠKings\": 5414,\n    \"ĠCollins\": 5415,\n    \"adi\": 5416,\n    \"Ġcelebrated\": 5417,\n    \"Ġclothes\": 5418,\n    \"Ġsunny\": 5419,\n    \"ĠCharlotte\": 5420,\n    \"ees\": 5421,\n    \"Ġscenes\": 5422,\n    \"ĠData\": 5423,\n    \"Ġwounded\": 5424,\n    \"Ġunusual\": 5425,\n    \"Ġrealized\": 5426,\n    \"ĠPlan\": 5427,\n    \"ĠTrans\": 5428,\n    \"ĠFC\": 5429,\n    \"Ġletters\": 5430,\n    \"Ġalerts\": 5431,\n    \"ĠWarren\": 5432,\n    \"DS\": 5433,\n    \"oss\": 5434,\n    \"pping\": 5435,\n    \"Ġsuspension\": 5436,\n    \"Ġbenchmark\": 5437,\n    \"ĠAcc\": 5438,\n    \"Ġalert\": 5439,\n    \"Ġpassion\": 5440,\n    \"ĠEst\": 5441,\n    \"Ġlatter\": 5442,\n    \"Ġstability\": 5443,\n    \"Ġarts\": 5444,\n    \"Ġpursue\": 5445,\n    \"ĠSeason\": 5446,\n    \"Ġfields\": 5447,\n    \"Ġmethod\": 5448,\n    \"63\": 5449,\n    \"Ġfolks\": 5450,\n    \"Ġexclusive\": 5451,\n    \"Ġcrews\": 5452,\n    \"Ġsessions\": 5453,\n    \"ĠMajor\": 5454,\n    \"ĠMount\": 5455,\n    \"Ġmap\": 5456,\n    \"Ġ=\": 5457,\n    \"Ġsituations\": 5458,\n    \"ĠBerlin\": 5459,\n    \"rey\": 5460,\n    \"Ġdates\": 5461,\n    \"Ġsheet\": 5462,\n    \"ĠLo\": 5463,\n    \"Ġfighters\": 5464,\n    \"ĠMart\": 5465,\n    \"Ġatmosphere\": 5466,\n    \"Ġillness\": 5467,\n    \"Ġcompeting\": 5468,\n    \"ĠChristopher\": 5469,\n    \"ĠRoy\": 5470,\n    \"mm\": 5471,\n    \"iano\": 5472,\n    \"Ġge\": 5473,\n    \"ĠRams\": 5474,\n    \"Ġconversations\": 5475,\n    \"ĠPa\": 5476,\n    \"ĠTel\": 5477,\n    \"Ġappreciate\": 5478,\n    \"78\": 5479,\n    \"ĠTotal\": 5480,\n    \"low\": 5481,\n    \"ĠStone\": 5482,\n    \"Ġopposite\": 5483,\n    \"Ġbarrel\": 5484,\n    \"Ġdevelopers\": 5485,\n    \"Ġexpress\": 5486,\n    \"Ġhighs\": 5487,\n    \"which\": 5488,\n    \"par\": 5489,\n    \"ĠVietnam\": 5490,\n    \"Ġblocks\": 5491,\n    \"Ġrecording\": 5492,\n    \"Ġadjusted\": 5493,\n    \"Ġret\": 5494,\n    \"ĠAR\": 5495,\n    \"Ġmilitants\": 5496,\n    \"Ġinnovative\": 5497,\n    \"ĠGhana\": 5498,\n    \"FR\": 5499,\n    \"Ġfantastic\": 5500,\n    \"Ġmortgage\": 5501,\n    \"ando\": 5502,\n    \"ĠLane\": 5503,\n    \"ises\": 5504,\n    \"ĠÂ\": 5505,\n    \"Ġhomeless\": 5506,\n    \"ĠKal\": 5507,\n    \"Ġapproached\": 5508,\n    \"Ġrounds\": 5509,\n    \"Ġmargins\": 5510,\n    \"ament\": 5511,\n    \"ĠMotor\": 5512,\n    \"Ġencouraging\": 5513,\n    \"ÂŃ\": 5514,\n    \"uru\": 5515,\n    \"Ġhandling\": 5516,\n    \"ĠMassachusetts\": 5517,\n    \"Ġplanet\": 5518,\n    \"ĠSpring\": 5519,\n    \"ĠBon\": 5520,\n    \"gu\": 5521,\n    \"Beat\": 5522,\n    \"Ġdrawing\": 5523,\n    \"ĠPhoenix\": 5524,\n    \"very\": 5525,\n    \"aid\": 5526,\n    \"ĠSte\": 5527,\n    \"ĠEntertainment\": 5528,\n    \"ĠRon\": 5529,\n    \"Ġassigned\": 5530,\n    \"ĠSA\": 5531,\n    \"News\": 5532,\n    \"Ġinterviews\": 5533,\n    \"ĠOh\": 5534,\n    \"media\": 5535,\n    \"vel\": 5536,\n    \"Ġpermission\": 5537,\n    \"Ġtransactions\": 5538,\n    \"Ġtraders\": 5539,\n    \"Ġsolo\": 5540,\n    \"Ġprovincial\": 5541,\n    \"Ġsuggesting\": 5542,\n    \"¡\": 5543,\n    \"Ġdiverse\": 5544,\n    \"Ġ67\": 5545,\n    \"Ġranks\": 5546,\n    \"ĠFre\": 5547,\n    \"Ġfavourite\": 5548,\n    \"Ġ63\": 5549,\n    \"Ġdifferences\": 5550,\n    \"Ġtargeting\": 5551,\n    \"Ġactors\": 5552,\n    \"Ġ76\": 5553,\n    \"icated\": 5554,\n    \"Ġcollect\": 5555,\n    \"akes\": 5556,\n    \"war\": 5557,\n    \"Ġcontained\": 5558,\n    \"ches\": 5559,\n    \"Ġlibrary\": 5560,\n    \"Ġsegments\": 5561,\n    \"ĠLine\": 5562,\n    \"Ãª\": 5563,\n    \"ual\": 5564,\n    \"Ġbags\": 5565,\n    \"Ġfactory\": 5566,\n    \"Ġear\": 5567,\n    \"Ġsomewhat\": 5568,\n    \"Ġrail\": 5569,\n    \"ĠUP\": 5570,\n    \"ula\": 5571,\n    \"ĠNiger\": 5572,\n    \"Ġlas\": 5573,\n    \"Ġimplementation\": 5574,\n    \"Ġemails\": 5575,\n    \"kel\": 5576,\n    \"wing\": 5577,\n    \"Ġadvised\": 5578,\n    \"--\": 5579,\n    \"istic\": 5580,\n    \"Ġdepth\": 5581,\n    \"Ġshoes\": 5582,\n    \"ĠJennifer\": 5583,\n    \"Ġvenue\": 5584,\n    \"Ġcontain\": 5585,\n    \"Ġhighlights\": 5586,\n    \"Ġcapabilities\": 5587,\n    \"Ġprocesses\": 5588,\n    \"Ġtradition\": 5589,\n    \"Ġcontacted\": 5590,\n    \"Ġproducing\": 5591,\n    \"Ġtrail\": 5592,\n    \"rem\": 5593,\n    \"Ġ600\": 5594,\n    \"Ġ68\": 5595,\n    \"AA\": 5596,\n    \"ĠBa\": 5597,\n    \"ĠSuch\": 5598,\n    \"ĠTyler\": 5599,\n    \"ipp\": 5600,\n    \"Ġsurvived\": 5601,\n    \"ami\": 5602,\n    \"ĠContinue\": 5603,\n    \"Ġcapture\": 5604,\n    \"bi\": 5605,\n    \"61\": 5606,\n    \"96\": 5607,\n    \"Ġthreatening\": 5608,\n    \"Ġkeen\": 5609,\n    \"dale\": 5610,\n    \"Ġtrailer\": 5611,\n    \"Ġstages\": 5612,\n    \"ĠGordon\": 5613,\n    \"Ġfinishing\": 5614,\n    \"Ġlegislative\": 5615,\n    \"Ġuseful\": 5616,\n    \"ĠGreek\": 5617,\n    \"ald\": 5618,\n    \"Ġgrounds\": 5619,\n    \"ĠDu\": 5620,\n    \"storms\": 5621,\n    \"ills\": 5622,\n    \"Ġexpense\": 5623,\n    \"Ġdetained\": 5624,\n    \"Today\": 5625,\n    \"Ġdiet\": 5626,\n    \"Ġwood\": 5627,\n    \"ĠCameron\": 5628,\n    \"Ġthrown\": 5629,\n    \"Ġcricket\": 5630,\n    \"Ġideal\": 5631,\n    \"with\": 5632,\n    \"Ġteammates\": 5633,\n    \"ours\": 5634,\n    \"Ġprojected\": 5635,\n    \"Ġpersonally\": 5636,\n    \"ĠBoy\": 5637,\n    \"rom\": 5638,\n    \"ĠPhilippines\": 5639,\n    \"win\": 5640,\n    \"ges\": 5641,\n    \"Ġcounties\": 5642,\n    \"ĠBaker\": 5643,\n    \"Ġprosecutor\": 5644,\n    \"Ġroof\": 5645,\n    \"met\": 5646,\n    \"Ġpartly\": 5647,\n    \"ĠMoon\": 5648,\n    \"eman\": 5649,\n    \"Ġfocusing\": 5650,\n    \"Ġfishing\": 5651,\n    \"than\": 5652,\n    \"ĠJeremy\": 5653,\n    \"ĠBad\": 5654,\n    \"ais\": 5655,\n    \"Ġcontrols\": 5656,\n    \"Ġtonnes\": 5657,\n    \"Ġshall\": 5658,\n    \"Ġ61\": 5659,\n    \"Ġgathering\": 5660,\n    \"ĠERA\": 5661,\n    \"Ġpresidency\": 5662,\n    \"Ġ85\": 5663,\n    \"ĠGas\": 5664,\n    \"Ġscenario\": 5665,\n    \"Ġquarters\": 5666,\n    \"Ġang\": 5667,\n    \"Ġsettled\": 5668,\n    \"ĠCommerce\": 5669,\n    \"Ġanybody\": 5670,\n    \"Ġgarden\": 5671,\n    \"ĠLibrary\": 5672,\n    \"Ġbet\": 5673,\n    \"Ġtopic\": 5674,\n    \"olo\": 5675,\n    \"Ġintense\": 5676,\n    \"87\": 5677,\n    \"Ġlinks\": 5678,\n    \"Ġmed\": 5679,\n    \"ĠAG\": 5680,\n    \"Ġflooding\": 5681,\n    \"ĠMurphy\": 5682,\n    \"PM\": 5683,\n    \"Ġfinds\": 5684,\n    \"Ġsensitive\": 5685,\n    \"pped\": 5686,\n    \"Ġcompletion\": 5687,\n    \"Ġminority\": 5688,\n    \"Ġvon\": 5689,\n    \"Ġstriking\": 5690,\n    \"rich\": 5691,\n    \"Ġbars\": 5692,\n    \"Ġefficient\": 5693,\n    \"Ġcontributions\": 5694,\n    \"Ġvisits\": 5695,\n    \"Ġattract\": 5696,\n    \"ĠMalaysia\": 5697,\n    \"ĠREL\": 5698,\n    \"Ġopens\": 5699,\n    \"Ġessentially\": 5700,\n    \"Ġreasonable\": 5701,\n    \"Ġsentiment\": 5702,\n    \"ĠMelbourne\": 5703,\n    \"Ġfitness\": 5704,\n    \"Ġfrequently\": 5705,\n    \"ĠRangers\": 5706,\n    \"Ġmuseum\": 5707,\n    \"ĠDNA\": 5708,\n    \"Ġcontrast\": 5709,\n    \"ĠAdams\": 5710,\n    \"ĠWin\": 5711,\n    \"Ġfalls\": 5712,\n    \"Ġimposed\": 5713,\n    \"250\": 5714,\n    \"ood\": 5715,\n    \"ĠRio\": 5716,\n    \"Ġchoices\": 5717,\n    \"Ġyellow\": 5718,\n    \"rin\": 5719,\n    \"ben\": 5720,\n    \"ĠStaff\": 5721,\n    \"ĠIndonesia\": 5722,\n    \"Ġcarries\": 5723,\n    \"Ġtourism\": 5724,\n    \"UM\": 5725,\n    \"ĠOrange\": 5726,\n    \"sell\": 5727,\n    \"Ġresolve\": 5728,\n    \"ĠMumbai\": 5729,\n    \"Ġpan\": 5730,\n    \"Ġimplement\": 5731,\n    \"Ġmidfielder\": 5732,\n    \"OP\": 5733,\n    \"Ġtensions\": 5734,\n    \"Ġ800\": 5735,\n    \"ĠLord\": 5736,\n    \"ĠLight\": 5737,\n    \"Ġlies\": 5738,\n    \"Ã©s\": 5739,\n    \"Ġparticipation\": 5740,\n    \"Ġtries\": 5741,\n    \"Ġsheriff\": 5742,\n    \"degree\": 5743,\n    \"Ġcongressional\": 5744,\n    \"Ġmode\": 5745,\n    \"Ġregulation\": 5746,\n    \"ĠJacob\": 5747,\n    \"ĠCrown\": 5748,\n    \"Ġbowl\": 5749,\n    \"ĠMississippi\": 5750,\n    \"Ġtheft\": 5751,\n    \"ĠKingdom\": 5752,\n    \"Ġresort\": 5753,\n    \"Ġroyal\": 5754,\n    \"Ġunemployment\": 5755,\n    \"PP\": 5756,\n    \"Ġnomination\": 5757,\n    \"ĠTR\": 5758,\n    \"Ġbehaviour\": 5759,\n    \"bank\": 5760,\n    \"ĠForest\": 5761,\n    \"WASHINGTON\": 5762,\n    \"ĠOthers\": 5763,\n    \"Ġslowly\": 5764,\n    \"Ġmenu\": 5765,\n    \"vo\": 5766,\n    \"ĠSy\": 5767,\n    \"ĠMetro\": 5768,\n    \"ĠLisa\": 5769,\n    \"Ġregistration\": 5770,\n    \"While\": 5771,\n    \"ĠJesus\": 5772,\n    \"Ġ250\": 5773,\n    \"Ġprocessing\": 5774,\n    \"Ġmonetary\": 5775,\n    \"ape\": 5776,\n    \"ener\": 5777,\n    \"ĠSystems\": 5778,\n    \"Ġdisappointed\": 5779,\n    \"Ġprint\": 5780,\n    \"uy\": 5781,\n    \"ħ\": 5782,\n    \"Ġdemanding\": 5783,\n    \"Ġincredibly\": 5784,\n    \"play\": 5785,\n    \"Ġsurveillance\": 5786,\n    \"ĠStandard\": 5787,\n    \"Ġperiods\": 5788,\n    \"Ġwrites\": 5789,\n    \"ĠLuke\": 5790,\n    \"ĠPalestinian\": 5791,\n    \"Ġwalks\": 5792,\n    \"Ġriding\": 5793,\n    \"Ġwaters\": 5794,\n    \"ĠSox\": 5795,\n    \"Ġtraveling\": 5796,\n    \"Ġtap\": 5797,\n    \"Ġorganized\": 5798,\n    \"Ġresource\": 5799,\n    \"Ġangry\": 5800,\n    \"Ġtiming\": 5801,\n    \"Ġempty\": 5802,\n    \"Ġmilk\": 5803,\n    \"Ġtherapy\": 5804,\n    \"ĠBrandon\": 5805,\n    \"mon\": 5806,\n    \"Ġnationwide\": 5807,\n    \"Ġnovel\": 5808,\n    \"ĠStorm\": 5809,\n    \"iet\": 5810,\n    \"ĠBre\": 5811,\n    \"Ġbegun\": 5812,\n    \"Ġdiplomatic\": 5813,\n    \"Ġads\": 5814,\n    \"ĠDC\": 5815,\n    \"ĠOb\": 5816,\n    \"ĠMontreal\": 5817,\n    \"ĠDown\": 5818,\n    \"ĠMilwaukee\": 5819,\n    \"Ġmeal\": 5820,\n    \"ĠPuerto\": 5821,\n    \"ĠMas\": 5822,\n    \"Ġjoy\": 5823,\n    \"Ġdeparture\": 5824,\n    \"ĠWright\": 5825,\n    \"Ġspoken\": 5826,\n    \"style\": 5827,\n    \"ĠAction\": 5828,\n    \"ĠComey\": 5829,\n    \"Ġdelivering\": 5830,\n    \"Ġtoll\": 5831,\n    \"Ġmidnight\": 5832,\n    \"ĠRevenue\": 5833,\n    \"Ġfiring\": 5834,\n    \"Ġstunning\": 5835,\n    \"Ġkicked\": 5836,\n    \"ĠOttawa\": 5837,\n    \"Ġefficiency\": 5838,\n    \"ĠLincoln\": 5839,\n    \"Ġtaste\": 5840,\n    \"ez\": 5841,\n    \"ĠWeather\": 5842,\n    \"ĠMorning\": 5843,\n    \"Ġhadn\": 5844,\n    \"Ġdiversity\": 5845,\n    \"ily\": 5846,\n    \"ĠAy\": 5847,\n    \"Ġargue\": 5848,\n    \"Ġerror\": 5849,\n    \"Ġtaught\": 5850,\n    \"Ġche\": 5851,\n    \"Ġoccasion\": 5852,\n    \"Ġinc\": 5853,\n    \"ĠOrlando\": 5854,\n    \"ĠOnline\": 5855,\n    \"Ġlegs\": 5856,\n    \"ĠNation\": 5857,\n    \"uck\": 5858,\n    \"Ġwidespread\": 5859,\n    \"ĠOcean\": 5860,\n    \"Ġconstantly\": 5861,\n    \"ĠLatin\": 5862,\n    \"Ġcomfort\": 5863,\n    \"Ġrely\": 5864,\n    \"uff\": 5865,\n    \"ĠCard\": 5866,\n    \"aring\": 5867,\n    \"Ġhumans\": 5868,\n    \"ĠThomson\": 5869,\n    \"aka\": 5870,\n    \"BIT\": 5871,\n    \"ĠReview\": 5872,\n    \"po\": 5873,\n    \"Ãº\": 5874,\n    \"Ġtrucks\": 5875,\n    \"Ġforecasts\": 5876,\n    \"view\": 5877,\n    \"Ġlongtime\": 5878,\n    \"ĠConstitution\": 5879,\n    \"Ġreserves\": 5880,\n    \"bit\": 5881,\n    \"Ġstressed\": 5882,\n    \"Ġcontribution\": 5883,\n    \"Ġchicken\": 5884,\n    \"ĠDE\": 5885,\n    \"Ġfat\": 5886,\n    \"ĠOscar\": 5887,\n    \"Ġcriticized\": 5888,\n    \"Ġtestimony\": 5889,\n    \"Ġapparent\": 5890,\n    \"Ġconstant\": 5891,\n    \"Ġcabinet\": 5892,\n    \"ĠDuke\": 5893,\n    \"Ġaspects\": 5894,\n    \"lic\": 5895,\n    \"ĠVol\": 5896,\n    \"Ġwing\": 5897,\n    \"Ġreb\": 5898,\n    \"ĠSessions\": 5899,\n    \"ĠSmart\": 5900,\n    \"car\": 5901,\n    \"ĠIm\": 5902,\n    \"Ġoperational\": 5903,\n    \"Ġregulators\": 5904,\n    \"ĠJimmy\": 5905,\n    \"eter\": 5906,\n    \"Ġnobody\": 5907,\n    \"ĠMarc\": 5908,\n    \"Ġliterally\": 5909,\n    \"Ġresistance\": 5910,\n    \"ĠKam\": 5911,\n    \"Ġsexually\": 5912,\n    \"Ġ69\": 5913,\n    \"uth\": 5914,\n    \"Ġviewed\": 5915,\n    \"Ġpicks\": 5916,\n    \"Ġdin\": 5917,\n    \"Ġtalented\": 5918,\n    \"Ġtennis\": 5919,\n    \"Ġstrengthen\": 5920,\n    \"Ġgl\": 5921,\n    \"ĠProtection\": 5922,\n    \"Ġinstalled\": 5923,\n    \"ways\": 5924,\n    \"ĠCampbell\": 5925,\n    \"ĠPortland\": 5926,\n    \"Ġintent\": 5927,\n    \"ĠPalace\": 5928,\n    \"Ġsecondary\": 5929,\n    \"Ġlocked\": 5930,\n    \"ĠPA\": 5931,\n    \"Ġlanded\": 5932,\n    \"Ġlength\": 5933,\n    \"Ġboosted\": 5934,\n    \"Ġpurchases\": 5935,\n    \"Ġcommand\": 5936,\n    \"ĠAsked\": 5937,\n    \"Ġspaces\": 5938,\n    \"Ġiconic\": 5939,\n    \"Ġrecommend\": 5940,\n    \"Ġduties\": 5941,\n    \"Ġseized\": 5942,\n    \"Ġdelayed\": 5943,\n    \"FA\": 5944,\n    \"AND\": 5945,\n    \"daq\": 5946,\n    \"Ġhiring\": 5947,\n    \"Ġoccur\": 5948,\n    \"DC\": 5949,\n    \"ĠMus\": 5950,\n    \"Ġag\": 5951,\n    \"Ġhopefully\": 5952,\n    \"ĠPenn\": 5953,\n    \"ards\": 5954,\n    \"Ġstriker\": 5955,\n    \"Ġrent\": 5956,\n    \"ĠTy\": 5957,\n    \"ĠBuffalo\": 5958,\n    \"ĠKy\": 5959,\n    \"Ġhike\": 5960,\n    \"pper\": 5961,\n    \"Ġ120\": 5962,\n    \"Ġop\": 5963,\n    \"Ġwheel\": 5964,\n    \"ĠIan\": 5965,\n    \"Ġchart\": 5966,\n    \"tt\": 5967,\n    \"Ġvolunteer\": 5968,\n    \"IG\": 5969,\n    \"person\": 5970,\n    \"ight\": 5971,\n    \"ĠBook\": 5972,\n    \"unt\": 5973,\n    \"ĠTechnologies\": 5974,\n    \"Now\": 5975,\n    \"Ġfavour\": 5976,\n    \"ĠGh\": 5977,\n    \"ĠQatar\": 5978,\n    \"ĠDutch\": 5979,\n    \"ĠGrant\": 5980,\n    \"ĠBan\": 5981,\n    \"rel\": 5982,\n    \"Ġagreements\": 5983,\n    \"Ġeducational\": 5984,\n    \"worth\": 5985,\n    \"ĠWard\": 5986,\n    \"700\": 5987,\n    \"Ġanymore\": 5988,\n    \"Ġrepair\": 5989,\n    \"Ġoperators\": 5990,\n    \"ĠLi\": 5991,\n    \"ots\": 5992,\n    \"ĠLouisiana\": 5993,\n    \"ĠWhether\": 5994,\n    \"Ġodds\": 5995,\n    \"Ġnoon\": 5996,\n    \"ĠStr\": 5997,\n    \"Ġfail\": 5998,\n    \"iser\": 5999,\n    \"Ġforever\": 6000,\n    \"Ġrecall\": 6001,\n    \"ĠPo\": 6002,\n    \"ĠHot\": 6003,\n    \"Ġdesigner\": 6004,\n    \"ido\": 6005,\n    \"LL\": 6006,\n    \"ĠControl\": 6007,\n    \"Ġsurvive\": 6008,\n    \"iam\": 6009,\n    \"Ġorganisation\": 6010,\n    \"ĠWork\": 6011,\n    \"Ġwider\": 6012,\n    \"Ġtank\": 6013,\n    \"work\": 6014,\n    \"ĠAS\": 6015,\n    \"Ġposting\": 6016,\n    \"Ġsuddenly\": 6017,\n    \"MC\": 6018,\n    \"ĠAL\": 6019,\n    \"ĠProfessor\": 6020,\n    \"ĠCoach\": 6021,\n    \"Ġrushed\": 6022,\n    \"Ġafraid\": 6023,\n    \"Ġactivist\": 6024,\n    \"that\": 6025,\n    \"ĠFilm\": 6026,\n    \"Ġbacking\": 6027,\n    \"Ġhousehold\": 6028,\n    \"Ġsignal\": 6029,\n    \"Ġaccurate\": 6030,\n    \"str\": 6031,\n    \"ĠThread\": 6032,\n    \"ĠBears\": 6033,\n    \"ATION\": 6034,\n    \"ĠAlliance\": 6035,\n    \"ĠMcDonald\": 6036,\n    \"ĠVenezuela\": 6037,\n    \"ogg\": 6038,\n    \"ĠWindows\": 6039,\n    \"makers\": 6040,\n    \"Ġutility\": 6041,\n    \"Ġrapidly\": 6042,\n    \"Ġattractive\": 6043,\n    \"Ġpa\": 6044,\n    \"ĠLarry\": 6045,\n    \"Ġmisconduct\": 6046,\n    \"Ġfreshman\": 6047,\n    \"Ġqualified\": 6048,\n    \"Ġcleared\": 6049,\n    \"Ġcrashed\": 6050,\n    \"Ġparticipating\": 6051,\n    \"Ġpages\": 6052,\n    \"Ġhighlight\": 6053,\n    \"Ġdialogue\": 6054,\n    \"ĠAlberta\": 6055,\n    \"Ġca\": 6056,\n    \"Ġwitnesses\": 6057,\n    \"ables\": 6058,\n    \"Ġfollowers\": 6059,\n    \"Ġensuring\": 6060,\n    \"Ġpromoting\": 6061,\n    \"Ġsearching\": 6062,\n    \"Ġremote\": 6063,\n    \"Ġclash\": 6064,\n    \"Ġfirefighters\": 6065,\n    \"Ġteen\": 6066,\n    \"ĠPlace\": 6067,\n    \"ĠNote\": 6068,\n    \"Ġregardless\": 6069,\n    \"ult\": 6070,\n    \"oney\": 6071,\n    \"ander\": 6072,\n    \"ional\": 6073,\n    \"ining\": 6074,\n    \"Ġdemanded\": 6075,\n    \"ĠCommunications\": 6076,\n    \"Ġconsideration\": 6077,\n    \"TC\": 6078,\n    \"ĠSoutheast\": 6079,\n    \"aga\": 6080,\n    \"ĠGarden\": 6081,\n    \"inger\": 6082,\n    \"ht\": 6083,\n    \"Ġbranch\": 6084,\n    \"Ġmouth\": 6085,\n    \"Ġaudio\": 6086,\n    \"Ġraw\": 6087,\n    \"Ġcoordinator\": 6088,\n    \"Ġexact\": 6089,\n    \"ĠHan\": 6090,\n    \"Ġdelays\": 6091,\n    \"ĠWal\": 6092,\n    \"ĠWells\": 6093,\n    \"Ġng\": 6094,\n    \"Ġhandful\": 6095,\n    \"Ġgirlfriend\": 6096,\n    \"Ġtypical\": 6097,\n    \"ĠWayne\": 6098,\n    \"ĠFranklin\": 6099,\n    \"Ġconstitutional\": 6100,\n    \"ĠChance\": 6101,\n    \"Ġblamed\": 6102,\n    \"rim\": 6103,\n    \"Ġpreliminary\": 6104,\n    \"Ġlie\": 6105,\n    \"da\": 6106,\n    \"ĠCapitol\": 6107,\n    \"Ġroutine\": 6108,\n    \"ĠNASA\": 6109,\n    \"Ġtre\": 6110,\n    \"ĠGolf\": 6111,\n    \"Ġsight\": 6112,\n    \"ĠDer\": 6113,\n    \"Ġreserve\": 6114,\n    \"150\": 6115,\n    \"Ġspeculation\": 6116,\n    \"Ġcompetitors\": 6117,\n    \"ĠMacron\": 6118,\n    \"ony\": 6119,\n    \"Ġovertime\": 6120,\n    \"Ġ71\": 6121,\n    \"Ġdepending\": 6122,\n    \"ĠWarner\": 6123,\n    \"Ġaccusations\": 6124,\n    \"ius\": 6125,\n    \"Ġpredicted\": 6126,\n    \"ĠCharlie\": 6127,\n    \"Ġeverywhere\": 6128,\n    \"Ġcable\": 6129,\n    \"ĠSaint\": 6130,\n    \"ĠRegion\": 6131,\n    \"Ġhero\": 6132,\n    \"ĠEmb\": 6133,\n    \"Ġkinds\": 6134,\n    \"Ġstarter\": 6135,\n    \"Ġsolve\": 6136,\n    \"ĠGuard\": 6137,\n    \"Ġloves\": 6138,\n    \"ĠDouglas\": 6139,\n    \"Ġfunded\": 6140,\n    \"ĠBrent\": 6141,\n    \"ĠAnyone\": 6142,\n    \"Ġsubstantial\": 6143,\n    \"ĠMarine\": 6144,\n    \"ĠMichelle\": 6145,\n    \"Ġcelebrating\": 6146,\n    \"Ġoffset\": 6147,\n    \"Ġbutton\": 6148,\n    \"gg\": 6149,\n    \"Ġmedicine\": 6150,\n    \"uri\": 6151,\n    \"Ġsomewhere\": 6152,\n    \"PD\": 6153,\n    \"Ġmon\": 6154,\n    \"Ġfires\": 6155,\n    \"final\": 6156,\n    \"oth\": 6157,\n    \"ined\": 6158,\n    \"Ġunderway\": 6159,\n    \"Ġmistakes\": 6160,\n    \"Ġgrateful\": 6161,\n    \"Ġcheap\": 6162,\n    \"È\": 6163,\n    \"Ġ95\": 6164,\n    \"Ġviolations\": 6165,\n    \"arr\": 6166,\n    \"Ġsurprising\": 6167,\n    \"Ġob\": 6168,\n    \"ĠNATO\": 6169,\n    \"Ġcontroversy\": 6170,\n    \"ĠSweden\": 6171,\n    \"Ġfuneral\": 6172,\n    \"Ġreviews\": 6173,\n    \"Ġpromotion\": 6174,\n    \"TY\": 6175,\n    \"Ġliberal\": 6176,\n    \"Ġpromising\": 6177,\n    \"ĠSP\": 6178,\n    \"How\": 6179,\n    \"Ġmemories\": 6180,\n    \"Ġbreast\": 6181,\n    \"zi\": 6182,\n    \"ights\": 6183,\n    \"Ġpattern\": 6184,\n    \"Ġoutdoor\": 6185,\n    \"ĠMu\": 6186,\n    \"Ġrush\": 6187,\n    \"ĠTheresa\": 6188,\n    \"ĠPol\": 6189,\n    \"Ġdescribe\": 6190,\n    \"ĠBand\": 6191,\n    \"ĠStewart\": 6192,\n    \"Ġ1999\": 6193,\n    \"ĠRaiders\": 6194,\n    \"mp\": 6195,\n    \"Ġprocedures\": 6196,\n    \"Ġplot\": 6197,\n    \"Ġhire\": 6198,\n    \"used\": 6199,\n    \"Ġ1970\": 6200,\n    \"Ġpicking\": 6201,\n    \"ĠSim\": 6202,\n    \"Ġregard\": 6203,\n    \"inal\": 6204,\n    \"backs\": 6205,\n    \"ĠHard\": 6206,\n    \"ĠLow\": 6207,\n    \"ĠAc\": 6208,\n    \"Is\": 6209,\n    \"Ġguarantee\": 6210,\n    \"ĠGiven\": 6211,\n    \"Ġbeta\": 6212,\n    \"ĠTre\": 6213,\n    \"Ġtrans\": 6214,\n    \"Ġretailer\": 6215,\n    \"Ġpurposes\": 6216,\n    \"ĠHol\": 6217,\n    \"Ġenjoying\": 6218,\n    \"Ġbrown\": 6219,\n    \"ĠPerry\": 6220,\n    \"Ġplea\": 6221,\n    \"MS\": 6222,\n    \"ĠDakota\": 6223,\n    \"ĠParker\": 6224,\n    \"Ġcommit\": 6225,\n    \"ĠLawrence\": 6226,\n    \"ĠMorris\": 6227,\n    \"ended\": 6228,\n    \"Ġvirtual\": 6229,\n    \"ÃĹ\": 6230,\n    \"Ġfruit\": 6231,\n    \"84\": 6232,\n    \"ĠHas\": 6233,\n    \"ishing\": 6234,\n    \"Ġdominated\": 6235,\n    \"ĠFA\": 6236,\n    \"Ġchannels\": 6237,\n    \"Ġunderstood\": 6238,\n    \"Ġcitizen\": 6239,\n    \"Ġchecks\": 6240,\n    \"ĠKenya\": 6241,\n    \"Ġdisabled\": 6242,\n    \"SD\": 6243,\n    \"Ġprotecting\": 6244,\n    \"Ġtweets\": 6245,\n    \"Ġsparked\": 6246,\n    \"ĠCO\": 6247,\n    \"§\": 6248,\n    \"ori\": 6249,\n    \"ĠGDP\": 6250,\n    \"ĠSer\": 6251,\n    \"ĠVisit\": 6252,\n    \"ĠMS\": 6253,\n    \"Ġbarely\": 6254,\n    \"Ġsand\": 6255,\n    \"Ġap\": 6256,\n    \"aging\": 6257,\n    \"Ġrel\": 6258,\n    \"ĠPerhaps\": 6259,\n    \"ĠMourinho\": 6260,\n    \"ĠJets\": 6261,\n    \"Ġdisclosure\": 6262,\n    \"Ġhighlighted\": 6263,\n    \"Ġimplemented\": 6264,\n    \"Ġcompliance\": 6265,\n    \"ĠAB\": 6266,\n    \"ĠAssistant\": 6267,\n    \"ĠCape\": 6268,\n    \"Ġfunny\": 6269,\n    \"Ġleverage\": 6270,\n    \"Ġmachines\": 6271,\n    \"Ġranging\": 6272,\n    \"Ġfastest\": 6273,\n    \"ĠRoberts\": 6274,\n    \"ĠPolicy\": 6275,\n    \"gar\": 6276,\n    \"Ġcollapse\": 6277,\n    \"ĠThrough\": 6278,\n    \"Ġrobbery\": 6279,\n    \"ĠHay\": 6280,\n    \"Ġelite\": 6281,\n    \"ĠDigital\": 6282,\n    \"ĠFun\": 6283,\n    \"ĠAlan\": 6284,\n    \"ement\": 6285,\n    \"Ġmit\": 6286,\n    \"Ġspin\": 6287,\n    \"Ġlistening\": 6288,\n    \"ĠDoug\": 6289,\n    \"ĠSaints\": 6290,\n    \"Ġinterior\": 6291,\n    \"Ġenhance\": 6292,\n    \"ĠCardinals\": 6293,\n    \"ever\": 6294,\n    \"Ġrobust\": 6295,\n    \"Ġinform\": 6296,\n    \"Ġsuffer\": 6297,\n    \"book\": 6298,\n    \"ĠMuslims\": 6299,\n    \"Ġagriculture\": 6300,\n    \"Ġkm\": 6301,\n    \"Ġdivers\": 6302,\n    \"Ã±\": 6303,\n    \"ĠReg\": 6304,\n    \"Ġequivalent\": 6305,\n    \"Ġcraft\": 6306,\n    \"Ġsettle\": 6307,\n    \"Ġcontains\": 6308,\n    \"ĠMack\": 6309,\n    \"ĠDis\": 6310,\n    \"ĠFore\": 6311,\n    \"ĠSudan\": 6312,\n    \"ĠMail\": 6313,\n    \"ĠBrooklyn\": 6314,\n    \"izer\": 6315,\n    \"bn\": 6316,\n    \"Ġhundred\": 6317,\n    \"Ġexhibition\": 6318,\n    \"ĠHave\": 6319,\n    \"vin\": 6320,\n    \"Ġcivilians\": 6321,\n    \"ĠCincinnati\": 6322,\n    \"Some\": 6323,\n    \"ĠSE\": 6324,\n    \"Ġbat\": 6325,\n    \"ĠIns\": 6326,\n    \"Ġcalm\": 6327,\n    \"Ġtone\": 6328,\n    \"Ġnormally\": 6329,\n    \"Ġseeks\": 6330,\n    \"ĠAss\": 6331,\n    \"Ġmembership\": 6332,\n    \"Ġannually\": 6333,\n    \"Ġemployers\": 6334,\n    \"CO\": 6335,\n    \"Ġcomplicated\": 6336,\n    \"Ġheadlines\": 6337,\n    \"ĠLabor\": 6338,\n    \"Ġlifestyle\": 6339,\n    \"ĠRen\": 6340,\n    \"ĠRich\": 6341,\n    \"cent\": 6342,\n    \"ude\": 6343,\n    \"Ġawesome\": 6344,\n    \"Ġpaint\": 6345,\n    \"Ġrolling\": 6346,\n    \"Ġwalls\": 6347,\n    \"Ġlab\": 6348,\n    \"Ġtourists\": 6349,\n    \"care\": 6350,\n    \"Ġgear\": 6351,\n    \"izz\": 6352,\n    \"Ġcream\": 6353,\n    \"ĠTro\": 6354,\n    \"ices\": 6355,\n    \"Ġpack\": 6356,\n    \"Ġdiseases\": 6357,\n    \"ĠSpeaker\": 6358,\n    \"ĠOfficers\": 6359,\n    \"Ġsky\": 6360,\n    \"83\": 6361,\n    \"ĠBE\": 6362,\n    \"Ġcategories\": 6363,\n    \"Ġindicate\": 6364,\n    \"Ġru\": 6365,\n    \"ĠSony\": 6366,\n    \"ĠDun\": 6367,\n    \"ocks\": 6368,\n    \"Ġconcrete\": 6369,\n    \"ĠMadison\": 6370,\n    \"ĠSab\": 6371,\n    \"IV\": 6372,\n    \"Ġobserved\": 6373,\n    \"ria\": 6374,\n    \"Ġinterim\": 6375,\n    \"Ġencounter\": 6376,\n    \"ista\": 6377,\n    \"Ġanger\": 6378,\n    \"Ġrapid\": 6379,\n    \"mail\": 6380,\n    \"Ġdestination\": 6381,\n    \"ĩ\": 6382,\n    \"Ġbreaks\": 6383,\n    \"rell\": 6384,\n    \"ĠChase\": 6385,\n    \"Ġattorneys\": 6386,\n    \"Ġrolled\": 6387,\n    \"ĠSprings\": 6388,\n    \"ĠVillage\": 6389,\n    \"TO\": 6390,\n    \"HS\": 6391,\n    \"Ġcampaigns\": 6392,\n    \"ologist\": 6393,\n    \"ĠTax\": 6394,\n    \"ĠIII\": 6395,\n    \"Ġteach\": 6396,\n    \"Ġprovision\": 6397,\n    \"Ġrem\": 6398,\n    \"Ġshirt\": 6399,\n    \"Ġdeployed\": 6400,\n    \"Ġguidelines\": 6401,\n    \"Ġav\": 6402,\n    \"zer\": 6403,\n    \"Ġrushing\": 6404,\n    \"94\": 6405,\n    \"place\": 6406,\n    \"Man\": 6407,\n    \"Ġdivided\": 6408,\n    \"ĠGun\": 6409,\n    \"Ġwindows\": 6410,\n    \"Ġcomponents\": 6411,\n    \"aba\": 6412,\n    \"ĠSwitzerland\": 6413,\n    \"election\": 6414,\n    \"ĠTampa\": 6415,\n    \"ĠAri\": 6416,\n    \"Ã¡s\": 6417,\n    \"Ġhighway\": 6418,\n    \"Ġacres\": 6419,\n    \"Ġcrown\": 6420,\n    \"known\": 6421,\n    \"Ġinquiry\": 6422,\n    \"url\": 6423,\n    \"Ġexpertise\": 6424,\n    \"Ġpraised\": 6425,\n    \"yer\": 6426,\n    \"Ġconclusion\": 6427,\n    \"Ġabortion\": 6428,\n    \"Ġlady\": 6429,\n    \"Ġtribute\": 6430,\n    \"Ġunveiled\": 6431,\n    \"Ġbeaten\": 6432,\n    \"TE\": 6433,\n    \"ĠMot\": 6434,\n    \"unk\": 6435,\n    \"Ġtriple\": 6436,\n    \"Ġforcing\": 6437,\n    \"ĠTickets\": 6438,\n    \"uit\": 6439,\n    \"Ġiron\": 6440,\n    \"Ġscientific\": 6441,\n    \"ĠIP\": 6442,\n    \"Ġdiagnosed\": 6443,\n    \"Ġocean\": 6444,\n    \"wide\": 6445,\n    \"ĠCowboys\": 6446,\n    \"LC\": 6447,\n    \"Ġmethods\": 6448,\n    \"ĠFind\": 6449,\n    \"ĠDean\": 6450,\n    \"Ġfundamental\": 6451,\n    \"ĠGill\": 6452,\n    \"Ġfeelings\": 6453,\n    \"IO\": 6454,\n    \"hu\": 6455,\n    \"Ġfeedback\": 6456,\n    \"ote\": 6457,\n    \"Ġduo\": 6458,\n    \"fully\": 6459,\n    \"get\": 6460,\n    \"Ġproof\": 6461,\n    \"story\": 6462,\n    \"Ġlongest\": 6463,\n    \"Ġshops\": 6464,\n    \"ĠJong\": 6465,\n    \"ĠCro\": 6466,\n    \"ĠHawaii\": 6467,\n    \"91\": 6468,\n    \"ĠJake\": 6469,\n    \"ĠSusan\": 6470,\n    \"Ġsubmit\": 6471,\n    \"rav\": 6472,\n    \"Ġmodest\": 6473,\n    \"Ġlit\": 6474,\n    \"Ġattempting\": 6475,\n    \"Ġsits\": 6476,\n    \"Ġaddressing\": 6477,\n    \"93\": 6478,\n    \"ĠBi\": 6479,\n    \"Ġlying\": 6480,\n    \"ĠOrganization\": 6481,\n    \"ĠOak\": 6482,\n    \"oli\": 6483,\n    \"Ġfatal\": 6484,\n    \"Ġmountain\": 6485,\n    \"val\": 6486,\n    \"lu\": 6487,\n    \"ĠMaine\": 6488,\n    \"Ġcharging\": 6489,\n    \"Ġresigned\": 6490,\n    \"illo\": 6491,\n    \"Ġrecommendation\": 6492,\n    \"party\": 6493,\n    \"ĠWeb\": 6494,\n    \"ĠPanthers\": 6495,\n    \"Ġnoise\": 6496,\n    \"ĠBrussels\": 6497,\n    \"awa\": 6498,\n    \"Ġambassador\": 6499,\n    \"Ġaccessible\": 6500,\n    \"ĠCalgary\": 6501,\n    \"idd\": 6502,\n    \"ĠAirlines\": 6503,\n    \"gr\": 6504,\n    \"Ġnu\": 6505,\n    \"roy\": 6506,\n    \"ĠMars\": 6507,\n    \"ĠPoland\": 6508,\n    \"ĠJerry\": 6509,\n    \"ados\": 6510,\n    \"ĠRico\": 6511,\n    \"ĠMir\": 6512,\n    \"ĠFin\": 6513,\n    \"ious\": 6514,\n    \"Ġpacked\": 6515,\n    \"Ġinsider\": 6516,\n    \"President\": 6517,\n    \"ĠBull\": 6518,\n    \"ĠYemen\": 6519,\n    \"ĠConnecticut\": 6520,\n    \"Ġ73\": 6521,\n    \"Ġdepartments\": 6522,\n    \"Ġorganic\": 6523,\n    \"ĠSummer\": 6524,\n    \"ĠBet\": 6525,\n    \"ste\": 6526,\n    \"zo\": 6527,\n    \"rat\": 6528,\n    \"Ġalliance\": 6529,\n    \"Ġintervention\": 6530,\n    \"wan\": 6531,\n    \"ĠOR\": 6532,\n    \"Ġdefined\": 6533,\n    \"ĠÃł\": 6534,\n    \"ĠChiefs\": 6535,\n    \"Ġknocked\": 6536,\n    \"ared\": 6537,\n    \"Ġholes\": 6538,\n    \"Ġpulling\": 6539,\n    \"ĠTodd\": 6540,\n    \"ĠJamie\": 6541,\n    \"ĠSher\": 6542,\n    \"Ġsignature\": 6543,\n    \"ĠSur\": 6544,\n    \"Ġgym\": 6545,\n    \"ĠVladimir\": 6546,\n    \"ĠThailand\": 6547,\n    \"Ġgaming\": 6548,\n    \"Ġsaving\": 6549,\n    \"ceive\": 6550,\n    \"82\": 6551,\n    \"ĠBern\": 6552,\n    \"ĠDid\": 6553,\n    \"Ġhardware\": 6554,\n    \"ished\": 6555,\n    \"Ġconspiracy\": 6556,\n    \"ANS\": 6557,\n    \"ĠIntelligence\": 6558,\n    \"Ġassembly\": 6559,\n    \"Ġ101\": 6560,\n    \"Ġconcise\": 6561,\n    \"ĠManhattan\": 6562,\n    \"Ġbelief\": 6563,\n    \"Ġsurge\": 6564,\n    \"Ġdeserve\": 6565,\n    \"Ġconsistently\": 6566,\n    \"ĠNor\": 6567,\n    \"okes\": 6568,\n    \"ðŁ\": 6569,\n    \"ME\": 6570,\n    \"ĠAsset\": 6571,\n    \"Ġsubstance\": 6572,\n    \"Ġprefer\": 6573,\n    \"Ġburning\": 6574,\n    \"ĠNik\": 6575,\n    \"ook\": 6576,\n    \"ĠPinterest\": 6577,\n    \"Ġboyfriend\": 6578,\n    \"ĠHal\": 6579,\n    \"ĠMerkel\": 6580,\n    \"Ġintroduce\": 6581,\n    \"ĠLinkedIn\": 6582,\n    \"ĠFull\": 6583,\n    \"ĠFarm\": 6584,\n    \"Ġchildhood\": 6585,\n    \"ĠTransportation\": 6586,\n    \"Ġterrible\": 6587,\n    \"du\": 6588,\n    \"Ġintention\": 6589,\n    \"Ġseemingly\": 6590,\n    \"elle\": 6591,\n    \"Ġfoods\": 6592,\n    \"Ġtitled\": 6593,\n    \"Ġdual\": 6594,\n    \"Ġimport\": 6595,\n    \"Ġdeveloper\": 6596,\n    \"UL\": 6597,\n    \"ington\": 6598,\n    \"ĠDelta\": 6599,\n    \"?'\": 6600,\n    \"iness\": 6601,\n    \"Ġquit\": 6602,\n    \"ĠGarcia\": 6603,\n    \"ĠSri\": 6604,\n    \"Ġhip\": 6605,\n    \"ĠBrazilian\": 6606,\n    \"elt\": 6607,\n    \"ively\": 6608,\n    \"Ġstructures\": 6609,\n    \"Ġlabour\": 6610,\n    \"Ġneighbors\": 6611,\n    \"Ġtill\": 6612,\n    \"Ġsoil\": 6613,\n    \"Ġdropping\": 6614,\n    \"Ġnominee\": 6615,\n    \"Ġmeets\": 6616,\n    \"92\": 6617,\n    \"rant\": 6618,\n    \"isa\": 6619,\n    \"Ġluck\": 6620,\n    \"aa\": 6621,\n    \"jet\": 6622,\n    \"ĠTor\": 6623,\n    \"ĠCrime\": 6624,\n    \"Ġlane\": 6625,\n    \"Ġflu\": 6626,\n    \"Ġlaunching\": 6627,\n    \"ĠAutom\": 6628,\n    \"aks\": 6629,\n    \"Ġuniversities\": 6630,\n    \"Ġpollution\": 6631,\n    \"ĠAdvis\": 6632,\n    \"ĠMall\": 6633,\n    \"ls\": 6634,\n    \"Ġdeeper\": 6635,\n    \"Ġrepeated\": 6636,\n    \"Ġmeanwhile\": 6637,\n    \"Ġchip\": 6638,\n    \"Ġoutlets\": 6639,\n    \"Ġliked\": 6640,\n    \"Ġsal\": 6641,\n    \"Ġwelfare\": 6642,\n    \"ago\": 6643,\n    \"Ġmakers\": 6644,\n    \"ving\": 6645,\n    \"fer\": 6646,\n    \"Ġovercome\": 6647,\n    \"mb\": 6648,\n    \"Ġshocked\": 6649,\n    \"akers\": 6650,\n    \"Ġnonprofit\": 6651,\n    \"Ġdonated\": 6652,\n    \"eral\": 6653,\n    \"Ġresume\": 6654,\n    \"Ġlogo\": 6655,\n    \"Ġsubscription\": 6656,\n    \"Ġ74\": 6657,\n    \"ela\": 6658,\n    \"Ġaspect\": 6659,\n    \"html\": 6660,\n    \"Ġsorry\": 6661,\n    \"Ġupgrade\": 6662,\n    \"Ġstance\": 6663,\n    \"Ġfr\": 6664,\n    \"Ġpapers\": 6665,\n    \"Ġattacking\": 6666,\n    \"Ġmeaningful\": 6667,\n    \"81\": 6668,\n    \"ĠWeinstein\": 6669,\n    \"Ġcreates\": 6670,\n    \"Ġhonour\": 6671,\n    \"ĠReply\": 6672,\n    \"oph\": 6673,\n    \"Ġmarch\": 6674,\n    \"Ġsmile\": 6675,\n    \"Ġcomparison\": 6676,\n    \"will\": 6677,\n    \"ĠSanchez\": 6678,\n    \"Ġvoter\": 6679,\n    \"Ġtheory\": 6680,\n    \"Ġequally\": 6681,\n    \"ĠRoger\": 6682,\n    \"Ġperfectly\": 6683,\n    \"Ġlanding\": 6684,\n    \"Ġbillions\": 6685,\n    \"ĠBloomberg\": 6686,\n    \"Ġpermit\": 6687,\n    \"Ġfinals\": 6688,\n    \"Ġracial\": 6689,\n    \"Ġpregnancy\": 6690,\n    \"iled\": 6691,\n    \"ĠFederation\": 6692,\n    \"Ġforest\": 6693,\n    \"Ġtag\": 6694,\n    \"aul\": 6695,\n    \"Ġdrinks\": 6696,\n    \"Ġ(\\\"\": 6697,\n    \"ĠMobile\": 6698,\n    \"Ġtouched\": 6699,\n    \"Ġclock\": 6700,\n    \"Ġreg\": 6701,\n    \"Ġasylum\": 6702,\n    \"igan\": 6703,\n    \"Ġsenator\": 6704,\n    \"Ġ99\": 6705,\n    \"ĠKumar\": 6706,\n    \"Ġskill\": 6707,\n    \"Ġ1998\": 6708,\n    \"pa\": 6709,\n    \"ĠAf\": 6710,\n    \"Ġmood\": 6711,\n    \"ston\": 6712,\n    \"Ġhang\": 6713,\n    \"ĠMPs\": 6714,\n    \"Please\": 6715,\n    \"ĠEve\": 6716,\n    \"Ġdocumentary\": 6717,\n    \"Ġpersonality\": 6718,\n    \"ĠCast\": 6719,\n    \"Ġdiscount\": 6720,\n    \"bing\": 6721,\n    \"ĠBoeing\": 6722,\n    \"Ġdepend\": 6723,\n    \"Ġcrossing\": 6724,\n    \"EX\": 6725,\n    \"Ġsucceed\": 6726,\n    \"Ġhumanitarian\": 6727,\n    \"ĠMuhammad\": 6728,\n    \"Ġwages\": 6729,\n    \"Ġcolumn\": 6730,\n    \"Ġexternal\": 6731,\n    \"Ġstatistics\": 6732,\n    \"ĠTODAY\": 6733,\n    \"Ġtrips\": 6734,\n    \"Ġta\": 6735,\n    \"Ġpenalties\": 6736,\n    \"Ġwriters\": 6737,\n    \"Ġshipping\": 6738,\n    \"ĠIndians\": 6739,\n    \"Ġsalt\": 6740,\n    \"ĠIndustrial\": 6741,\n    \"ĠYankees\": 6742,\n    \"ĠDen\": 6743,\n    \"Ġrough\": 6744,\n    \"Ġbarrels\": 6745,\n    \"ĠHor\": 6746,\n    \"bert\": 6747,\n    \"ĠDep\": 6748,\n    \"Ġresign\": 6749,\n    \"97\": 6750,\n    \"Ġballs\": 6751,\n    \"ĠJun\": 6752,\n    \"ĠBab\": 6753,\n    \"Ġassociate\": 6754,\n    \"Ġstring\": 6755,\n    \"Ġhub\": 6756,\n    \"Ġorgan\": 6757,\n    \"ĠMarshall\": 6758,\n    \"ĠFIFA\": 6759,\n    \"ĠMun\": 6760,\n    \"ency\": 6761,\n    \"research\": 6762,\n    \"Ġpeers\": 6763,\n    \"Ġtall\": 6764,\n    \"ĠGoldman\": 6765,\n    \"Don\": 6766,\n    \"Ġparade\": 6767,\n    \"Ġparks\": 6768,\n    \"Ġdet\": 6769,\n    \"Ġdisappointing\": 6770,\n    \"Ġreflects\": 6771,\n    \"ĠLakers\": 6772,\n    \"Ġfiles\": 6773,\n    \"Ġrelatives\": 6774,\n    \"ĠUSD\": 6775,\n    \"ĠArticle\": 6776,\n    \"Ġcustom\": 6777,\n    \"ĠCarlos\": 6778,\n    \"Ġtracking\": 6779,\n    \"Ġmaintaining\": 6780,\n    \"ĠCur\": 6781,\n    \"ardo\": 6782,\n    \"ĠSkip\": 6783,\n    \"Ġattitude\": 6784,\n    \"Just\": 6785,\n    \"Ġinstitution\": 6786,\n    \"Ġnarrow\": 6787,\n    \"Ġsnap\": 6788,\n    \"Ġenterprise\": 6789,\n    \"Ġdrives\": 6790,\n    \"Ġ77\": 6791,\n    \"Ġcrop\": 6792,\n    \"Ġvirus\": 6793,\n    \"Ġcelebrity\": 6794,\n    \"Ġeconomies\": 6795,\n    \"ued\": 6796,\n    \"Ġsum\": 6797,\n    \"ĠDubai\": 6798,\n    \"ĠInsurance\": 6799,\n    \"Ĺ\": 6800,\n    \"ury\": 6801,\n    \"ĠUnfortunately\": 6802,\n    \"Ġclosure\": 6803,\n    \"ota\": 6804,\n    \"ĠPhilip\": 6805,\n    \"oms\": 6806,\n    \"Ġinvestigated\": 6807,\n    \"Ġgenerations\": 6808,\n    \"ĠETF\": 6809,\n    \"ĠKeith\": 6810,\n    \"ĠLater\": 6811,\n    \"isk\": 6812,\n    \"Ġpreferred\": 6813,\n    \"Ġdefault\": 6814,\n    \"Ġtowns\": 6815,\n    \"ĠRod\": 6816,\n    \"ĠDie\": 6817,\n    \"Ġintegrated\": 6818,\n    \"Ġacquiring\": 6819,\n    \"Ġvoices\": 6820,\n    \"Ġser\": 6821,\n    \"Ġpresents\": 6822,\n    \"ĠBR\": 6823,\n    \"ĠEmergency\": 6824,\n    \"Ġreligion\": 6825,\n    \"HA\": 6826,\n    \"Ġresponding\": 6827,\n    \"ĠThings\": 6828,\n    \"Ġbeef\": 6829,\n    \"ĠWithout\": 6830,\n    \"urd\": 6831,\n    \"ĠCarl\": 6832,\n    \"Ġadministrative\": 6833,\n    \"ĠWhich\": 6834,\n    \"Ġchallenged\": 6835,\n    \"Ġcooking\": 6836,\n    \"ivid\": 6837,\n    \"ĠFer\": 6838,\n    \"Ġtremendous\": 6839,\n    \"ĠTerry\": 6840,\n    \"iri\": 6841,\n    \"CS\": 6842,\n    \"ĠJunior\": 6843,\n    \"ĠReddit\": 6844,\n    \"Ġtea\": 6845,\n    \"Ġaccounting\": 6846,\n    \"lan\": 6847,\n    \"Ġdetention\": 6848,\n    \"Ġreplied\": 6849,\n    \"SI\": 6850,\n    \"ĠHel\": 6851,\n    \"ns\": 6852,\n    \"ĠProf\": 6853,\n    \"Ġramp\": 6854,\n    \"ĠConservative\": 6855,\n    \"Ġattendance\": 6856,\n    \"Ġspecialist\": 6857,\n    \"ĠFinal\": 6858,\n    \"Ġadvertisement\": 6859,\n    \"Ġacquire\": 6860,\n    \"ĠWhatsApp\": 6861,\n    \"Ġworkforce\": 6862,\n    \"ĠCalif\": 6863,\n    \"Ġspeakers\": 6864,\n    \"ĠEPA\": 6865,\n    \"Ġconviction\": 6866,\n    \"hire\": 6867,\n    \"ĠFisher\": 6868,\n    \"ĠIntel\": 6869,\n    \"Ġbin\": 6870,\n    \"ĠWas\": 6871,\n    \"Ġearth\": 6872,\n    \"vi\": 6873,\n    \"Ġhurricane\": 6874,\n    \"Ġholidays\": 6875,\n    \"Ġassume\": 6876,\n    \"Ġinvolve\": 6877,\n    \"Ġdynamic\": 6878,\n    \"ĠGre\": 6879,\n    \"Ġitem\": 6880,\n    \"Ġpound\": 6881,\n    \"Ġanxiety\": 6882,\n    \"ĠPrint\": 6883,\n    \"rop\": 6884,\n    \"Ġautomatically\": 6885,\n    \"Ġdiscrimination\": 6886,\n    \"ĠLam\": 6887,\n    \"ĠColl\": 6888,\n    \"Ġimpressed\": 6889,\n    \"Ġinvolves\": 6890,\n    \"ĠLes\": 6891,\n    \"ĠTri\": 6892,\n    \"ĠLook\": 6893,\n    \"ĠiOS\": 6894,\n    \"Ġgrab\": 6895,\n    \"ĠAngel\": 6896,\n    \"Ġstops\": 6897,\n    \"ĠPay\": 6898,\n    \"ĠECB\": 6899,\n    \"Ġbunch\": 6900,\n    \"Ġletting\": 6901,\n    \"ele\": 6902,\n    \"ĠAdditionally\": 6903,\n    \"Ġboards\": 6904,\n    \"NC\": 6905,\n    \"Ġtragedy\": 6906,\n    \"Ġpink\": 6907,\n    \"Ġgonna\": 6908,\n    \"ones\": 6909,\n    \"Ġrev\": 6910,\n    \"ĠIndependent\": 6911,\n    \"ĠCambridge\": 6912,\n    \"ĠPence\": 6913,\n    \"Ġprosecution\": 6914,\n    \"Ġdeputies\": 6915,\n    \"ĠAhmed\": 6916,\n    \"Ġlows\": 6917,\n    \"ĠAmy\": 6918,\n    \"ĠBuilding\": 6919,\n    \"mark\": 6920,\n    \"Ġsmooth\": 6921,\n    \"Ġsole\": 6922,\n    \"Ġwanting\": 6923,\n    \"ĠHeart\": 6924,\n    \"Ġobtain\": 6925,\n    \"ĠBus\": 6926,\n    \"Ġexchanges\": 6927,\n    \"friendly\": 6928,\n    \"Ġlabel\": 6929,\n    \"elect\": 6930,\n    \"ĠCompanies\": 6931,\n    \"owing\": 6932,\n    \"ĠCB\": 6933,\n    \"RI\": 6934,\n    \"ĠMaster\": 6935,\n    \"Ġliquid\": 6936,\n    \"ĠDanny\": 6937,\n    \"Ġproceeds\": 6938,\n    \"ĠLaura\": 6939,\n    \"card\": 6940,\n    \"Ġtears\": 6941,\n    \"Ġexploration\": 6942,\n    \"Ġdepression\": 6943,\n    \"ken\": 6944,\n    \"ĠFe\": 6945,\n    \"Ġlending\": 6946,\n    \"ĠYouth\": 6947,\n    \"ality\": 6948,\n    \"NS\": 6949,\n    \"Ġmoon\": 6950,\n    \"ĠTaiwan\": 6951,\n    \"Ġstruggles\": 6952,\n    \"Ġdiscovery\": 6953,\n    \"Ġqualify\": 6954,\n    \"Ġwireless\": 6955,\n    \"alia\": 6956,\n    \"Ġwitnessed\": 6957,\n    \"Ġheight\": 6958,\n    \"ĠGuy\": 6959,\n    \"left\": 6960,\n    \"KE\": 6961,\n    \"Ġfoul\": 6962,\n    \"ĠMohammed\": 6963,\n    \"Ġgrass\": 6964,\n    \"ĠNon\": 6965,\n    \"Ġswim\": 6966,\n    \"Ġbrilliant\": 6967,\n    \"you\": 6968,\n    \"ĠFlynn\": 6969,\n    \"Ġsinging\": 6970,\n    \"eria\": 6971,\n    \"UT\": 6972,\n    \"ĠMcCain\": 6973,\n    \"ĠSep\": 6974,\n    \"ĠWars\": 6975,\n    \"Ġburden\": 6976,\n    \"Ġpas\": 6977,\n    \"Ġabandoned\": 6978,\n    \"Ġint\": 6979,\n    \"ĠTurner\": 6980,\n    \"Ġcollective\": 6981,\n    \"ĠEnvironmental\": 6982,\n    \"ĠStudents\": 6983,\n    \"Ġofferings\": 6984,\n    \"Ġresignation\": 6985,\n    \"Ġexplosion\": 6986,\n    \"ĠKoh\": 6987,\n    \"ager\": 6988,\n    \"Ġthrows\": 6989,\n    \"Ġasks\": 6990,\n    \"light\": 6991,\n    \"Ġanyway\": 6992,\n    \"Ġyard\": 6993,\n    \"Ġcarrier\": 6994,\n    \"Ġwaves\": 6995,\n    \"backed\": 6996,\n    \"TR\": 6997,\n    \"oud\": 6998,\n    \"Ġbreach\": 6999,\n    \"Ġdated\": 7000,\n    \"Ġdressed\": 7001,\n    \"ĠDodgers\": 7002,\n    \"oles\": 7003,\n    \"Ġ78\": 7004,\n    \"Ġreads\": 7005,\n    \"Ġpredict\": 7006,\n    \"ĠJerusalem\": 7007,\n    \"ĠPT\": 7008,\n    \"Ġcrack\": 7009,\n    \"yan\": 7010,\n    \"Ġnights\": 7011,\n    \"eline\": 7012,\n    \"Ġconvinced\": 7013,\n    \"Ġlock\": 7014,\n    \"Ġcarefully\": 7015,\n    \"ĠMercedes\": 7016,\n    \"Ġultimate\": 7017,\n    \"Ġdist\": 7018,\n    \"Ġslight\": 7019,\n    \"ĠEdwards\": 7020,\n    \"Ġswing\": 7021,\n    \"iling\": 7022,\n    \"Ġknife\": 7023,\n    \"ĠNashville\": 7024,\n    \"IF\": 7025,\n    \"inder\": 7026,\n    \"udd\": 7027,\n    \"Ġsenators\": 7028,\n    \"ĠFurther\": 7029,\n    \"ĠXi\": 7030,\n    \"Ġstr\": 7031,\n    \"ĠOd\": 7032,\n    \"days\": 7033,\n    \"Ġcomm\": 7034,\n    \"Ġverdict\": 7035,\n    \"Ġconfirmation\": 7036,\n    \"king\": 7037,\n    \"ĠCS\": 7038,\n    \"Ġadvocates\": 7039,\n    \"Ġpride\": 7040,\n    \"Ġmemorial\": 7041,\n    \"ams\": 7042,\n    \"erman\": 7043,\n    \"Ġteenager\": 7044,\n    \"ĠNeil\": 7045,\n    \"uts\": 7046,\n    \"Ġsoul\": 7047,\n    \"see\": 7048,\n    \"post\": 7049,\n    \"Ġchest\": 7050,\n    \"fire\": 7051,\n    \"ĠLynch\": 7052,\n    \"Ġpeaceful\": 7053,\n    \"OND\": 7054,\n    \"ĠIndustries\": 7055,\n    \"ĠJuan\": 7056,\n    \"Ġrestore\": 7057,\n    \"Ġreliable\": 7058,\n    \"ming\": 7059,\n    \"agan\": 7060,\n    \"Source\": 7061,\n    \"ĠCabinet\": 7062,\n    \"Ġremarkable\": 7063,\n    \"ĠTrudeau\": 7064,\n    \"ĠEs\": 7065,\n    \"Ġintegrity\": 7066,\n    \"ove\": 7067,\n    \"fe\": 7068,\n    \"Ġproceedings\": 7069,\n    \"Ġconnections\": 7070,\n    \"Ġunprecedented\": 7071,\n    \"ĠGlen\": 7072,\n    \"ux\": 7073,\n    \"Ġearning\": 7074,\n    \"Ġingredients\": 7075,\n    \"Ġnominated\": 7076,\n    \"ĠBangladesh\": 7077,\n    \"made\": 7078,\n    \"Ġlessons\": 7079,\n    \"Ġbreakfast\": 7080,\n    \"ĠRelations\": 7081,\n    \"Ġloose\": 7082,\n    \"Al\": 7083,\n    \"Ġupgraded\": 7084,\n    \"ral\": 7085,\n    \"ĠPage\": 7086,\n    \"oto\": 7087,\n    \"ĠQueensland\": 7088,\n    \"Ġprocedure\": 7089,\n    \"ĠSmall\": 7090,\n    \"Ġrespective\": 7091,\n    \"Ġpictured\": 7092,\n    \"ĠBas\": 7093,\n    \"Ġpreparation\": 7094,\n    \"ĠMyanmar\": 7095,\n    \"Ġdonation\": 7096,\n    \"Ġvisible\": 7097,\n    \"iest\": 7098,\n    \"ĠBroadway\": 7099,\n    \"rick\": 7100,\n    \"ĠSchools\": 7101,\n    \"Ġarrests\": 7102,\n    \"ĠJessica\": 7103,\n    \"ĠBengal\": 7104,\n    \"Ġhell\": 7105,\n    \"Ġannouncing\": 7106,\n    \"Ġmail\": 7107,\n    \"ĠMcG\": 7108,\n    \"two\": 7109,\n    \"rest\": 7110,\n    \"OD\": 7111,\n    \"ĠBradley\": 7112,\n    \"Ġdoubled\": 7113,\n    \"Ġpledged\": 7114,\n    \"Ġcomeback\": 7115,\n    \"Ġextraordinary\": 7116,\n    \"Ġslide\": 7117,\n    \"Ġassess\": 7118,\n    \"Ġagricultural\": 7119,\n    \"ĠKay\": 7120,\n    \"Ġvendors\": 7121,\n    \"Ġnarrative\": 7122,\n    \"Ġreviewed\": 7123,\n    \"ĠPass\": 7124,\n    \"Ġinspiration\": 7125,\n    \"ĠHunter\": 7126,\n    \"Ġcalendar\": 7127,\n    \"ĠDiamond\": 7128,\n    \"Ġremoval\": 7129,\n    \"ners\": 7130,\n    \"ĠKap\": 7131,\n    \"Ġconsent\": 7132,\n    \"Ġvisual\": 7133,\n    \"Ġcheese\": 7134,\n    \"ĠTher\": 7135,\n    \"ĠFR\": 7136,\n    \"ĠShanghai\": 7137,\n    \"iah\": 7138,\n    \"ĠCole\": 7139,\n    \"AK\": 7140,\n    \"Ġranking\": 7141,\n    \"Ġcook\": 7142,\n    \"Ġhalftime\": 7143,\n    \"ĠStars\": 7144,\n    \"Ġroutes\": 7145,\n    \"aim\": 7146,\n    \"Ġestablishment\": 7147,\n    \"ĠMug\": 7148,\n    \"Ġsurvivors\": 7149,\n    \"urg\": 7150,\n    \"ĠBrett\": 7151,\n    \"Ġunexpected\": 7152,\n    \"ained\": 7153,\n    \"Ġrarely\": 7154,\n    \"ĠGall\": 7155,\n    \"Ġadvocate\": 7156,\n    \"ĠNad\": 7157,\n    \"Ġ911\": 7158,\n    \"Ġracist\": 7159,\n    \"erer\": 7160,\n    \"ĠRev\": 7161,\n    \"ĠSection\": 7162,\n    \"Ġhelpful\": 7163,\n    \"CT\": 7164,\n    \"agg\": 7165,\n    \"Ġgovernance\": 7166,\n    \"Ġfelony\": 7167,\n    \"Ġoptimistic\": 7168,\n    \"Ġelectoral\": 7169,\n    \"EG\": 7170,\n    \"town\": 7171,\n    \"Ġdaughters\": 7172,\n    \"Ġanswered\": 7173,\n    \"Ġthin\": 7174,\n    \"ĠClassic\": 7175,\n    \"Ġshareholder\": 7176,\n    \"ĠBlake\": 7177,\n    \"ĠFla\": 7178,\n    \"Ġparliamentary\": 7179,\n    \"dy\": 7180,\n    \"Ġcommented\": 7181,\n    \"Ġtri\": 7182,\n    \"Ġglobe\": 7183,\n    \"Ġmandate\": 7184,\n    \"Ġslipped\": 7185,\n    \"ĠTower\": 7186,\n    \"Ġoperated\": 7187,\n    \"gers\": 7188,\n    \"Ġassured\": 7189,\n    \"ĠMartinez\": 7190,\n    \"Ġdesigns\": 7191,\n    \"ĠModel\": 7192,\n    \"Ġstakeholders\": 7193,\n    \"Ġdefended\": 7194,\n    \"Ġseniors\": 7195,\n    \"Ġvacation\": 7196,\n    \"Ġglobally\": 7197,\n    \"ump\": 7198,\n    \"Not\": 7199,\n    \"Ġclip\": 7200,\n    \"Ġarticles\": 7201,\n    \"BR\": 7202,\n    \"km\": 7203,\n    \"ĠFront\": 7204,\n    \"PL\": 7205,\n    \"Ġadoption\": 7206,\n    \"Ġsudden\": 7207,\n    \"Ġframework\": 7208,\n    \"Ġhanging\": 7209,\n    \"gl\": 7210,\n    \"ĠSel\": 7211,\n    \"Ġmoderate\": 7212,\n    \"Ġreverse\": 7213,\n    \"income\": 7214,\n    \"cor\": 7215,\n    \"ĠGB\": 7216,\n    \"Ġphysically\": 7217,\n    \"Ġtransparency\": 7218,\n    \"ĠElectric\": 7219,\n    \"Ġrefugee\": 7220,\n    \"profile\": 7221,\n    \"iva\": 7222,\n    \"ately\": 7223,\n    \"ĠAC\": 7224,\n    \"Ġtransferred\": 7225,\n    \"Ġaffair\": 7226,\n    \"ĠAlaska\": 7227,\n    \"oria\": 7228,\n    \"ĠChange\": 7229,\n    \"Ġrepeat\": 7230,\n    \"Ġscreening\": 7231,\n    \"ender\": 7232,\n    \"ĠCas\": 7233,\n    \"ĠDav\": 7234,\n    \"Ġfocuses\": 7235,\n    \"Ġcommissioner\": 7236,\n    \"Ġupside\": 7237,\n    \"ĠKeep\": 7238,\n    \"ĠBlues\": 7239,\n    \"ently\": 7240,\n    \"Ġaut\": 7241,\n    \"Ġexperiencing\": 7242,\n    \"aman\": 7243,\n    \"Ġapprove\": 7244,\n    \"Ġmile\": 7245,\n    \"Ġcheaper\": 7246,\n    \"ĠWind\": 7247,\n    \"ĠStore\": 7248,\n    \"Ġgrabbed\": 7249,\n    \"Ġsons\": 7250,\n    \"Ġfighter\": 7251,\n    \"Ġum\": 7252,\n    \"ĠBased\": 7253,\n    \"don\": 7254,\n    \"Ġconstitution\": 7255,\n    \"finals\": 7256,\n    \"act\": 7257,\n    \"¢\": 7258,\n    \"Ġmill\": 7259,\n    \"Ġorganisations\": 7260,\n    \"ĠToyota\": 7261,\n    \"Ġyuan\": 7262,\n    \"Ġterrorists\": 7263,\n    \"Ġforth\": 7264,\n    \"Ġavailability\": 7265,\n    \"Ġentrance\": 7266,\n    \"Ġvolumes\": 7267,\n    \"Ġmult\": 7268,\n    \"plus\": 7269,\n    \"ĠColumbus\": 7270,\n    \"ĠSummit\": 7271,\n    \"Ġbabies\": 7272,\n    \"ĠMur\": 7273,\n    \"ĠGray\": 7274,\n    \"ĠChar\": 7275,\n    \"ĠButler\": 7276,\n    \"Ġpose\": 7277,\n    \"ĠNatural\": 7278,\n    \"ĠAtt\": 7279,\n    \"Ġdecrease\": 7280,\n    \"Ġtens\": 7281,\n    \"kt\": 7282,\n    \"Ġminds\": 7283,\n    \"Ġimpacted\": 7284,\n    \"Ġchapter\": 7285,\n    \"ĠOp\": 7286,\n    \"ĠHarrison\": 7287,\n    \"ĠRodriguez\": 7288,\n    \"Ġethnic\": 7289,\n    \"Ġtravelling\": 7290,\n    \"ĠBond\": 7291,\n    \"ader\": 7292,\n    \"core\": 7293,\n    \"Ġgallery\": 7294,\n    \"founder\": 7295,\n    \"ĠVill\": 7296,\n    \"Ġdecent\": 7297,\n    \"ĠHistory\": 7298,\n    \"ĠInt\": 7299,\n    \"ĠNa\": 7300,\n    \"ĠHad\": 7301,\n    \"Ġmainstream\": 7302,\n    \"ĠTs\": 7303,\n    \"Ġbottle\": 7304,\n    \"sen\": 7305,\n    \"Ġrecession\": 7306,\n    \"Ġsophomore\": 7307,\n    \"Ġsilence\": 7308,\n    \"cc\": 7309,\n    \"Ġqualifying\": 7310,\n    \"Ġcomplained\": 7311,\n    \"ĠRad\": 7312,\n    \"Ġactively\": 7313,\n    \"Ġbacks\": 7314,\n    \"ĠMusk\": 7315,\n    \"Ġcareful\": 7316,\n    \"Ġmeals\": 7317,\n    \"ĠDor\": 7318,\n    \"Ġmess\": 7319,\n    \"ĠBelgium\": 7320,\n    \"Ġke\": 7321,\n    \"ĠLopez\": 7322,\n    \"Ġbow\": 7323,\n    \"Ġhelicopter\": 7324,\n    \"was\": 7325,\n    \"Ġstone\": 7326,\n    \"kins\": 7327,\n    \"Ġunlike\": 7328,\n    \"Ġcollision\": 7329,\n    \"ĠAlt\": 7330,\n    \"HP\": 7331,\n    \"ĠMason\": 7332,\n    \"has\": 7333,\n    \"Ġclimbed\": 7334,\n    \"Ġindication\": 7335,\n    \"Ġhotels\": 7336,\n    \"Ġloud\": 7337,\n    \"ĠMilan\": 7338,\n    \"kes\": 7339,\n    \"Ġbadly\": 7340,\n    \"Ġtrials\": 7341,\n    \"Ġimpacts\": 7342,\n    \"ĠJane\": 7343,\n    \"Ġcrossed\": 7344,\n    \"Ġdiscussing\": 7345,\n    \"ĠSM\": 7346,\n    \"Ġpopularity\": 7347,\n    \"ĠWant\": 7348,\n    \"fall\": 7349,\n    \"Ġartificial\": 7350,\n    \"ĠBu\": 7351,\n    \"akh\": 7352,\n    \"Ġdominant\": 7353,\n    \"gov\": 7354,\n    \"Ġpremier\": 7355,\n    \"Ġexecution\": 7356,\n    \"gate\": 7357,\n    \"Ġswimming\": 7358,\n    \"Ġchat\": 7359,\n    \"Ġdevastating\": 7360,\n    \"acking\": 7361,\n    \"Ġreception\": 7362,\n    \"urt\": 7363,\n    \"Ġtheater\": 7364,\n    \"Ġgather\": 7365,\n    \"Ġtear\": 7366,\n    \"uro\": 7367,\n    \"Ġdemocratic\": 7368,\n    \"Ġrebels\": 7369,\n    \"Ġlifetime\": 7370,\n    \"Ġradical\": 7371,\n    \"uan\": 7372,\n    \"Ġtechniques\": 7373,\n    \"ache\": 7374,\n    \"ior\": 7375,\n    \"Ġcamps\": 7376,\n    \"Ġtelephone\": 7377,\n    \"ĠDublin\": 7378,\n    \"ĠBrand\": 7379,\n    \"ĠMarcus\": 7380,\n    \"aun\": 7381,\n    \"ĠRec\": 7382,\n    \"Ġ82\": 7383,\n    \"ban\": 7384,\n    \"Ġsafely\": 7385,\n    \"aku\": 7386,\n    \"aki\": 7387,\n    \"Ġbankruptcy\": 7388,\n    \"FF\": 7389,\n    \"Ġformat\": 7390,\n    \"Ġattached\": 7391,\n    \"ĠFame\": 7392,\n    \"ĠEdward\": 7393,\n    \"Ġmerger\": 7394,\n    \"ĠRepresentatives\": 7395,\n    \"izes\": 7396,\n    \"Ġhidden\": 7397,\n    \"Ġval\": 7398,\n    \"zz\": 7399,\n    \"Ġexcess\": 7400,\n    \"Ġscope\": 7401,\n    \"Ġdivorce\": 7402,\n    \"Ġburn\": 7403,\n    \"Ġrequirement\": 7404,\n    \"BB\": 7405,\n    \"ĠHand\": 7406,\n    \"Ġcons\": 7407,\n    \"Ġrisen\": 7408,\n    \"Ġtwitter\": 7409,\n    \"Ġoffseason\": 7410,\n    \"ĠSometimes\": 7411,\n    \"ĠInf\": 7412,\n    \"ĠAng\": 7413,\n    \"uer\": 7414,\n    \"report\": 7415,\n    \"Ġdreams\": 7416,\n    \"Ġ700\": 7417,\n    \"ips\": 7418,\n    \"ĠDream\": 7419,\n    \"Ġgifts\": 7420,\n    \"Ġsomehow\": 7421,\n    \"ĠTur\": 7422,\n    \"ĠRachel\": 7423,\n    \"can\": 7424,\n    \"Ġlog\": 7425,\n    \"ĠMedicaid\": 7426,\n    \"Ġles\": 7427,\n    \"Ġtired\": 7428,\n    \"ĠArkansas\": 7429,\n    \"Ġliquidity\": 7430,\n    \"ĠPhillips\": 7431,\n    \"ĠBTC\": 7432,\n    \"Ġhide\": 7433,\n    \"Ġpun\": 7434,\n    \"ĠRun\": 7435,\n    \"lyn\": 7436,\n    \"ĠUC\": 7437,\n    \"ĠDesign\": 7438,\n    \"ĠDev\": 7439,\n    \"Ġvaluation\": 7440,\n    \"Ġreveals\": 7441,\n    \"ĠChild\": 7442,\n    \"other\": 7443,\n    \"Ġposed\": 7444,\n    \"lee\": 7445,\n    \"Ġships\": 7446,\n    \"ĠTrue\": 7447,\n    \"Ġdescribes\": 7448,\n    \"Ġrunner\": 7449,\n    \"bro\": 7450,\n    \"Ġankle\": 7451,\n    \"Ġod\": 7452,\n    \"ĠAnnual\": 7453,\n    \"CL\": 7454,\n    \"Ġoverhaul\": 7455,\n    \"ned\": 7456,\n    \"Ġbold\": 7457,\n    \"Ġmo\": 7458,\n    \"ĠFalls\": 7459,\n    \"Ġemployed\": 7460,\n    \"ĠGro\": 7461,\n    \"Ġflash\": 7462,\n    \"ĠTD\": 7463,\n    \"Ġnervous\": 7464,\n    \"Ġintegration\": 7465,\n    \"Ġsmartphones\": 7466,\n    \"Ġmovements\": 7467,\n    \"nie\": 7468,\n    \"ition\": 7469,\n    \"ĠThird\": 7470,\n    \"Ģ\": 7471,\n    \"Ġmetres\": 7472,\n    \"Ġeconomist\": 7473,\n    \"omp\": 7474,\n    \"Ġteens\": 7475,\n    \"Ġeveryday\": 7476,\n    \"Ġinterviewed\": 7477,\n    \"Ġbriefly\": 7478,\n    \"],\": 7479,\n    \"uke\": 7480,\n    \"ĠFOX\": 7481,\n    \"Ġunderlying\": 7482,\n    \"ĠLuc\": 7483,\n    \"Ġcourses\": 7484,\n    \"ss\": 7485,\n    \"amed\": 7486,\n    \"°\": 7487,\n    \"ju\": 7488,\n    \"ĠBanks\": 7489,\n    \"Ġoutfit\": 7490,\n    \"illing\": 7491,\n    \"Ġtrafficking\": 7492,\n    \"Ġurging\": 7493,\n    \"Ġbelt\": 7494,\n    \"Ġrid\": 7495,\n    \"CP\": 7496,\n    \"Ġelderly\": 7497,\n    \"ĠGrowth\": 7498,\n    \"Ã¡n\": 7499,\n    \"ĠSn\": 7500,\n    \"Ġsurrounded\": 7501,\n    \"Ġsisters\": 7502,\n    \"ĠIslam\": 7503,\n    \"Ġsynd\": 7504,\n    \"ĠCosta\": 7505,\n    \"di\": 7506,\n    \"ĠKl\": 7507,\n    \"Ġmanufacturer\": 7508,\n    \"holders\": 7509,\n    \"Ġelement\": 7510,\n    \"Ġload\": 7511,\n    \"Ġbooked\": 7512,\n    \"Ġaccompanied\": 7513,\n    \"ĠChamber\": 7514,\n    \"Ġbriefing\": 7515,\n    \"Oh\": 7516,\n    \"imi\": 7517,\n    \"ĠDefence\": 7518,\n    \"ĠCurrently\": 7519,\n    \"aking\": 7520,\n    \"Ġhandled\": 7521,\n    \"ĠCD\": 7522,\n    \"ĠBenjamin\": 7523,\n    \"Ġpocket\": 7524,\n    \"ĠKashmir\": 7525,\n    \"Ġlighting\": 7526,\n    \"aps\": 7527,\n    \"Ġ1997\": 7528,\n    \"ech\": 7529,\n    \"Ġaddiction\": 7530,\n    \"Ġbases\": 7531,\n    \"Ġpriorities\": 7532,\n    \"Ġhardly\": 7533,\n    \"ĠQuebec\": 7534,\n    \"ĠEarn\": 7535,\n    \"IES\": 7536,\n    \"ĠZach\": 7537,\n    \"ĠAlong\": 7538,\n    \"MI\": 7539,\n    \"Ġins\": 7540,\n    \"ĠRogers\": 7541,\n    \"ĠKan\": 7542,\n    \"ĠFuture\": 7543,\n    \"Ġtriggered\": 7544,\n    \"ĠUnit\": 7545,\n    \"Ġweighed\": 7546,\n    \"Ġpointing\": 7547,\n    \"Ġchocolate\": 7548,\n    \"ĠBrowns\": 7549,\n    \"ĠISIS\": 7550,\n    \"Ġgoalkeeper\": 7551,\n    \"Ġsaves\": 7552,\n    \"ĠAndre\": 7553,\n    \"burn\": 7554,\n    \"ĠCont\": 7555,\n    \"ĠNetherlands\": 7556,\n    \"Ġpolitically\": 7557,\n    \"ĠAshley\": 7558,\n    \"ĠWhit\": 7559,\n    \"aded\": 7560,\n    \"PH\": 7561,\n    \"Ġborders\": 7562,\n    \"ORE\": 7563,\n    \"Ġally\": 7564,\n    \"Trump\": 7565,\n    \"istan\": 7566,\n    \"ĠHunt\": 7567,\n    \"ĠCancer\": 7568,\n    \"ĠGrace\": 7569,\n    \"ĠTottenham\": 7570,\n    \"Ġ1960\": 7571,\n    \"ĠMarg\": 7572,\n    \"ĠBryan\": 7573,\n    \"ĠAgain\": 7574,\n    \"acing\": 7575,\n    \"Ġarguments\": 7576,\n    \"ĠSouthwest\": 7577,\n    \"Ġvocal\": 7578,\n    \"Ġjudgment\": 7579,\n    \"Ġengaging\": 7580,\n    \"Ġadopt\": 7581,\n    \"Ġrental\": 7582,\n    \"Ġlinebacker\": 7583,\n    \"ĠKardashian\": 7584,\n    \"Ġepisodes\": 7585,\n    \"..\": 7586,\n    \"Ġunt\": 7587,\n    \"Ġvowed\": 7588,\n    \"Ġ79\": 7589,\n    \"ule\": 7590,\n    \"Ġtransit\": 7591,\n    \"Ġoffshore\": 7592,\n    \"Ġsuppliers\": 7593,\n    \"Ġarguing\": 7594,\n    \"Ġsatellite\": 7595,\n    \"ĠLind\": 7596,\n    \"ĠTaliban\": 7597,\n    \"Buy\": 7598,\n    \"ĠCaribbean\": 7599,\n    \"ĠBarry\": 7600,\n    \"Ġauthors\": 7601,\n    \"ĠWolf\": 7602,\n    \"Ġviewing\": 7603,\n    \"ĠCubs\": 7604,\n    \"From\": 7605,\n    \"Ġ%\": 7606,\n    \"Ġcurrencies\": 7607,\n    \"Why\": 7608,\n    \"ĠBroncos\": 7609,\n    \"Ġtrick\": 7610,\n    \"Ġdiesel\": 7611,\n    \"ĠLiberal\": 7612,\n    \"FL\": 7613,\n    \"Ġtopics\": 7614,\n    \"Ġretain\": 7615,\n    \"ĠLiberty\": 7616,\n    \"Ġacquisitions\": 7617,\n    \"ced\": 7618,\n    \"Ġfre\": 7619,\n    \"Ġfleet\": 7620,\n    \"Ġcopper\": 7621,\n    \"ĠPot\": 7622,\n    \"jen\": 7623,\n    \"ĠElliott\": 7624,\n    \"ĠPyongyang\": 7625,\n    \"Ġobject\": 7626,\n    \"ĠUse\": 7627,\n    \"Ġmutual\": 7628,\n    \"MP\": 7629,\n    \"Ġev\": 7630,\n    \"Ġdeny\": 7631,\n    \"ĠEveryone\": 7632,\n    \"lling\": 7633,\n    \"Ġpays\": 7634,\n    \"Ġdrought\": 7635,\n    \"Ġcorn\": 7636,\n    \"Ġworkplace\": 7637,\n    \"rig\": 7638,\n    \"ĠMn\": 7639,\n    \"Ġadvisory\": 7640,\n    \"ĠCat\": 7641,\n    \"Ġchronic\": 7642,\n    \"ĠSteelers\": 7643,\n    \"Ġboxes\": 7644,\n    \"ĠNap\": 7645,\n    \"Ġdemonstrated\": 7646,\n    \"ĠTournament\": 7647,\n    \"Ġsymbol\": 7648,\n    \"ĠAfghan\": 7649,\n    \"ĠTan\": 7650,\n    \"ired\": 7651,\n    \"ĠEv\": 7652,\n    \"ĠConsumer\": 7653,\n    \"Ġmoral\": 7654,\n    \"ĠAdditional\": 7655,\n    \"Ġwebsites\": 7656,\n    \"Ġoccasions\": 7657,\n    \"Ġfate\": 7658,\n    \"Ġpitcher\": 7659,\n    \"Ġtaxpayers\": 7660,\n    \"Ġdeemed\": 7661,\n    \"ĠLibya\": 7662,\n    \"Ġpriced\": 7663,\n    \"Ġdistributed\": 7664,\n    \"ĠForum\": 7665,\n    \"Ġrice\": 7666,\n    \"Ġbloc\": 7667,\n    \"Ġprovisions\": 7668,\n    \"agh\": 7669,\n    \"Ġpen\": 7670,\n    \"Ġattracted\": 7671,\n    \"ĠEdmonton\": 7672,\n    \"Ġthousand\": 7673,\n    \"Ġpainting\": 7674,\n    \"Ġil\": 7675,\n    \"Ġcourtesy\": 7676,\n    \"Ġeliminate\": 7677,\n    \"Ġacc\": 7678,\n    \"Ġmeters\": 7679,\n    \"Ġreflected\": 7680,\n    \"Ġcomponent\": 7681,\n    \"Every\": 7682,\n    \"Ġsells\": 7683,\n    \"Ġfault\": 7684,\n    \"Ġburned\": 7685,\n    \"ĠKirk\": 7686,\n    \"ĠAnna\": 7687,\n    \"Ġappeals\": 7688,\n    \"Ġeggs\": 7689,\n    \"Ġfrequent\": 7690,\n    \"Ġtrigger\": 7691,\n    \"Ġrevised\": 7692,\n    \"ĠAngela\": 7693,\n    \"Ġ81\": 7694,\n    \"Ġsingles\": 7695,\n    \"Ġviral\": 7696,\n    \"Ġworries\": 7697,\n    \"ĠShould\": 7698,\n    \"profit\": 7699,\n    \"Ġraises\": 7700,\n    \"ĠBryant\": 7701,\n    \"ĠProduct\": 7702,\n    \"Ġtenure\": 7703,\n    \"Ġdiabetes\": 7704,\n    \"Ġcolour\": 7705,\n    \"azz\": 7706,\n    \"ĠGirls\": 7707,\n    \"Ġpractical\": 7708,\n    \"Ġblind\": 7709,\n    \"ancing\": 7710,\n    \"pictured\": 7711,\n    \"Ġfinale\": 7712,\n    \"ĠElection\": 7713,\n    \"Ġathletic\": 7714,\n    \"Ġpromoted\": 7715,\n    \"Ġflowers\": 7716,\n    \"Ġtrains\": 7717,\n    \"ario\": 7718,\n    \"Ġsufficient\": 7719,\n    \"IE\": 7720,\n    \"Ġexamples\": 7721,\n    \"Ġshed\": 7722,\n    \"Ġbirds\": 7723,\n    \"Ġchaos\": 7724,\n    \"Ġwound\": 7725,\n    \"Ġrocket\": 7726,\n    \"Ġwet\": 7727,\n    \"Ġsample\": 7728,\n    \"ĠNag\": 7729,\n    \"ĠOliver\": 7730,\n    \"Ġscrutiny\": 7731,\n    \"ĠSeven\": 7732,\n    \"ĠRoman\": 7733,\n    \"ĠFred\": 7734,\n    \"Ġweird\": 7735,\n    \"ĠTam\": 7736,\n    \"ĠSupport\": 7737,\n    \"ĠNathan\": 7738,\n    \"Ġstudying\": 7739,\n    \"Ġintroduction\": 7740,\n    \"Ġtons\": 7741,\n    \"cer\": 7742,\n    \"aus\": 7743,\n    \"ION\": 7744,\n    \"Ġcritic\": 7745,\n    \"ĠAh\": 7746,\n    \"alo\": 7747,\n    \"pur\": 7748,\n    \"Ġstorms\": 7749,\n    \"ĠMission\": 7750,\n    \"Ġcredits\": 7751,\n    \"Ġgrants\": 7752,\n    \"Ġcomp\": 7753,\n    \"Ġhearts\": 7754,\n    \"part\": 7755,\n    \"Ġpin\": 7756,\n    \"Ġsubsequent\": 7757,\n    \"Ġmad\": 7758,\n    \"ĠSacramento\": 7759,\n    \"woman\": 7760,\n    \"from\": 7761,\n    \"Ġoutcomes\": 7762,\n    \"Ġoldest\": 7763,\n    \"Ġdesperate\": 7764,\n    \"ĠTal\": 7765,\n    \"ĠDJ\": 7766,\n    \"ward\": 7767,\n    \"Ġaudiences\": 7768,\n    \"Ġimportantly\": 7769,\n    \"ĠEmily\": 7770,\n    \"sk\": 7771,\n    \"ĠHeat\": 7772,\n    \"ĠType\": 7773,\n    \"ĠPeace\": 7774,\n    \"Ġsuspicious\": 7775,\n    \"aly\": 7776,\n    \"ĠGET\": 7777,\n    \"ĠCAP\": 7778,\n    \"dis\": 7779,\n    \"ĠIraqi\": 7780,\n    \"ĠReed\": 7781,\n    \"Ġstrange\": 7782,\n    \"ĠParent\": 7783,\n    \"900\": 7784,\n    \"Ġglad\": 7785,\n    \"ĠTroy\": 7786,\n    \"ĠShort\": 7787,\n    \"Ġheritage\": 7788,\n    \"Ġarriving\": 7789,\n    \"ingly\": 7790,\n    \"Ġtransformation\": 7791,\n    \"Ġlease\": 7792,\n    \"Ġcollapsed\": 7793,\n    \"cha\": 7794,\n    \"ĠPatrol\": 7795,\n    \"Ġcomputers\": 7796,\n    \"Ġprinciples\": 7797,\n    \"Ġsporting\": 7798,\n    \"ĠHughes\": 7799,\n    \"mile\": 7800,\n    \"ĠCit\": 7801,\n    \"Ġdrilling\": 7802,\n    \"ĠBox\": 7803,\n    \"ÃŁ\": 7804,\n    \"bre\": 7805,\n    \"ĠOverall\": 7806,\n    \"Ġopioid\": 7807,\n    \"Ġdelighted\": 7808,\n    \"Ġhonored\": 7809,\n    \"ĠCold\": 7810,\n    \"Ġunions\": 7811,\n    \"ĠCou\": 7812,\n    \"ĠCircuit\": 7813,\n    \"Ġblast\": 7814,\n    \"sson\": 7815,\n    \"ĠHernandez\": 7816,\n    \"ĠLooking\": 7817,\n    \"Ġlegally\": 7818,\n    \"ĠWalmart\": 7819,\n    \"bridge\": 7820,\n    \"Ġmat\": 7821,\n    \"rad\": 7822,\n    \"ids\": 7823,\n    \"Ġdining\": 7824,\n    \"Ġrebound\": 7825,\n    \"abad\": 7826,\n    \"ĠRom\": 7827,\n    \"Ġimpose\": 7828,\n    \"ĠAlpha\": 7829,\n    \"ĠWeekly\": 7830,\n    \"TER\": 7831,\n    \"ĠJam\": 7832,\n    \"Ġabsolute\": 7833,\n    \"Ġinventory\": 7834,\n    \"ĠBilly\": 7835,\n    \"ĠKaren\": 7836,\n    \"ĠFriends\": 7837,\n    \"ĠCent\": 7838,\n    \"ĠVikings\": 7839,\n    \"ĠMuch\": 7840,\n    \"cell\": 7841,\n    \"ads\": 7842,\n    \"Ġph\": 7843,\n    \"Ġkiller\": 7844,\n    \"ĠMembers\": 7845,\n    \"Ġshooter\": 7846,\n    \"ĠInvestigators\": 7847,\n    \"ĠJoshua\": 7848,\n    \"Ġparticipated\": 7849,\n    \"Ġinnocent\": 7850,\n    \"ĠRichmond\": 7851,\n    \"itor\": 7852,\n    \"ĠDal\": 7853,\n    \"ĠOperator\": 7854,\n    \"Ġmakeup\": 7855,\n    \"Ġconf\": 7856,\n    \"ĠNEWS\": 7857,\n    \"ĠDef\": 7858,\n    \"Ġchase\": 7859,\n    \"ĠCost\": 7860,\n    \"mont\": 7861,\n    \"\\\":\": 7862,\n    \"Ġarrangements\": 7863,\n    \"stein\": 7864,\n    \"Ġretire\": 7865,\n    \"ĠLuis\": 7866,\n    \"Ġrenewed\": 7867,\n    \"ĠTownship\": 7868,\n    \"Ġchecked\": 7869,\n    \"arts\": 7870,\n    \"ĠCash\": 7871,\n    \"Ġcentres\": 7872,\n    \"chers\": 7873,\n    \"ĠSolutions\": 7874,\n    \"Ġlegend\": 7875,\n    \"ige\": 7876,\n    \"most\": 7877,\n    \"osed\": 7878,\n    \"ĠPor\": 7879,\n    \"Ġpremiere\": 7880,\n    \"FS\": 7881,\n    \"Ġmissiles\": 7882,\n    \"ĠLang\": 7883,\n    \"Ġsing\": 7884,\n    \"best\": 7885,\n    \"Ġtail\": 7886,\n    \"Ġriders\": 7887,\n    \"Picture\": 7888,\n    \"zen\": 7889,\n    \"ĠKent\": 7890,\n    \"Ġtransform\": 7891,\n    \"Ġwildlife\": 7892,\n    \"Ġsmoking\": 7893,\n    \"Ġpreseason\": 7894,\n    \"ĠLucas\": 7895,\n    \"ĠAnne\": 7896,\n    \"owski\": 7897,\n    \"Ġtape\": 7898,\n    \"Ġdisplayed\": 7899,\n    \"Ġforum\": 7900,\n    \"Ġanonymity\": 7901,\n    \"ĠIndianapolis\": 7902,\n    \"hips\": 7903,\n    \"acc\": 7904,\n    \"ĠMoreover\": 7905,\n    \"lers\": 7906,\n    \"area\": 7907,\n    \"ĠIndeed\": 7908,\n    \"Ġconducting\": 7909,\n    \"Ġinfection\": 7910,\n    \"Ġdealt\": 7911,\n    \"OB\": 7912,\n    \"asing\": 7913,\n    \"ĠGaza\": 7914,\n    \"itter\": 7915,\n    \"ĠKa\": 7916,\n    \"Ġhopeful\": 7917,\n    \"ĠSnow\": 7918,\n    \"Ġentitled\": 7919,\n    \"Ġaffecting\": 7920,\n    \"Ġeager\": 7921,\n    \"Ġcircle\": 7922,\n    \"Ġlaugh\": 7923,\n    \"ĠProsecutors\": 7924,\n    \"ĠDur\": 7925,\n    \"Ġbarriers\": 7926,\n    \"ĠPoll\": 7927,\n    \"oun\": 7928,\n    \"ĠPalm\": 7929,\n    \"chi\": 7930,\n    \"Ġsamples\": 7931,\n    \"Ġcompromise\": 7932,\n    \"atter\": 7933,\n    \"Ġenormous\": 7934,\n    \"ĠÃ©\": 7935,\n    \"coming\": 7936,\n    \"ĠPharmaceutical\": 7937,\n    \"Ġrank\": 7938,\n    \"Let\": 7939,\n    \"Ġtransgender\": 7940,\n    \"ĠCloud\": 7941,\n    \"FO\": 7942,\n    \"ĠBor\": 7943,\n    \"Ġbonus\": 7944,\n    \"Ġordinary\": 7945,\n    \"ĠPres\": 7946,\n    \"ĠHIV\": 7947,\n    \"ires\": 7948,\n    \"OSE\": 7949,\n    \"Ġdancing\": 7950,\n    \"ĠHD\": 7951,\n    \"Ġversions\": 7952,\n    \"Ġ88\": 7953,\n    \"rate\": 7954,\n    \"Ġtackles\": 7955,\n    \"Ġknock\": 7956,\n    \"ĠEmma\": 7957,\n    \"Ġmotivated\": 7958,\n    \"ĠBennett\": 7959,\n    \"ĠBurn\": 7960,\n    \"Ġgrid\": 7961,\n    \"Ġembrace\": 7962,\n    \"ĠSpurs\": 7963,\n    \"Ġflows\": 7964,\n    \"ĠGer\": 7965,\n    \"Ġsponsored\": 7966,\n    \"Ġsurvival\": 7967,\n    \"ching\": 7968,\n    \"Ġ1995\": 7969,\n    \"Ġreward\": 7970,\n    \"Ġdepends\": 7971,\n    \"Ġpostseason\": 7972,\n    \"Ġloaded\": 7973,\n    \"Ġneutral\": 7974,\n    \"ĠPop\": 7975,\n    \"BL\": 7976,\n    \"Ġrevolution\": 7977,\n    \"ĠFreedom\": 7978,\n    \"Ġrecovering\": 7979,\n    \"Ġrequiring\": 7980,\n    \"ALL\": 7981,\n    \"ARE\": 7982,\n    \"Ġmini\": 7983,\n    \"lt\": 7984,\n    \"ĠFDA\": 7985,\n    \"Ġcarpet\": 7986,\n    \"ĠPrior\": 7987,\n    \"Ġadmission\": 7988,\n    \"ĠEver\": 7989,\n    \"ĠTribune\": 7990,\n    \"ĠRonaldo\": 7991,\n    \"Ġthick\": 7992,\n    \"Ġlanes\": 7993,\n    \"Ġ84\": 7994,\n    \"ĠMemphis\": 7995,\n    \"Ġopt\": 7996,\n    \"BO\": 7997,\n    \"Ġfaculty\": 7998,\n    \"ĠChad\": 7999,\n    \"ĠSUV\": 8000,\n    \"ĠHen\": 8001,\n    \"Ġeste\": 8002,\n    \"ĠHu\": 8003,\n    \"ĠAgriculture\": 8004,\n    \"store\": 8005,\n    \"ĠDrug\": 8006,\n    \"inter\": 8007,\n    \"Ġ1996\": 8008,\n    \"ident\": 8009,\n    \"Ġbackup\": 8010,\n    \"ĠHonda\": 8011,\n    \"ĠHope\": 8012,\n    \"oes\": 8013,\n    \"ums\": 8014,\n    \"amer\": 8015,\n    \"Ġbreath\": 8016,\n    \"Ġ110\": 8017,\n    \"Ġjoke\": 8018,\n    \"ĠAld\": 8019,\n    \"Ġwondering\": 8020,\n    \"ĠAssad\": 8021,\n    \"ĠRem\": 8022,\n    \"Ġfundraising\": 8023,\n    \"pot\": 8024,\n    \"Ã¨\": 8025,\n    \"Ġquestioning\": 8026,\n    \"Ġpent\": 8027,\n    \"ĠMoney\": 8028,\n    \"ĠMedicine\": 8029,\n    \"wick\": 8030,\n    \"ĠKnights\": 8031,\n    \"Ġbatting\": 8032,\n    \"ĠMos\": 8033,\n    \"Ġdesignated\": 8034,\n    \"isse\": 8035,\n    \"Ġspotlight\": 8036,\n    \"Ġlake\": 8037,\n    \"Ġcaution\": 8038,\n    \"Ġinmates\": 8039,\n    \"Ġlap\": 8040,\n    \"CE\": 8041,\n    \"ĠJavascript\": 8042,\n    \"ĠDeutsche\": 8043,\n    \"ĠFargo\": 8044,\n    \"Ġguaranteed\": 8045,\n    \"borough\": 8046,\n    \"Ġfunctions\": 8047,\n    \"ĠElementary\": 8048,\n    \"ĠChuck\": 8049,\n    \"Ġpitched\": 8050,\n    \"ĠKrist\": 8051,\n    \"Ġsteal\": 8052,\n    \"Ġchips\": 8053,\n    \"Ġalarm\": 8054,\n    \"Ġbeloved\": 8055,\n    \"scale\": 8056,\n    \"Ġassaulted\": 8057,\n    \"ĠPentagon\": 8058,\n    \"Ġtemporarily\": 8059,\n    \"Ġ93\": 8060,\n    \"Ġ>\": 8061,\n    \"ĠPortugal\": 8062,\n    \"ti\": 8063,\n    \"HL\": 8064,\n    \"Ġdecreased\": 8065,\n    \"Ġexistence\": 8066,\n    \"Ġisolated\": 8067,\n    \"Ġdeposit\": 8068,\n    \"Ġstudied\": 8069,\n    \"\\\")\": 8070,\n    \"Ġtrophy\": 8071,\n    \"ĠBrooks\": 8072,\n    \"Ġbattling\": 8073,\n    \"Ġweaker\": 8074,\n    \"ĠPrivate\": 8075,\n    \"ĠAccess\": 8076,\n    \"Ġvirtually\": 8077,\n    \"Ġshortage\": 8078,\n    \"Ġgaining\": 8079,\n    \"Ġbathroom\": 8080,\n    \"TON\": 8081,\n    \"Ġconcerning\": 8082,\n    \"Ġengineer\": 8083,\n    \"Ġbread\": 8084,\n    \"Ġdemonstrate\": 8085,\n    \"ĠDh\": 8086,\n    \"Ġhorses\": 8087,\n    \"Ġintersection\": 8088,\n    \"Ġcolors\": 8089,\n    \"Ġdelegation\": 8090,\n    \"Ġnotable\": 8091,\n    \"Ġwithdrawal\": 8092,\n    \"ĠDennis\": 8093,\n    \"Ġlocally\": 8094,\n    \"Ġcoastal\": 8095,\n    \"Ġcomply\": 8096,\n    \"ĠMoh\": 8097,\n    \"ĠAlbert\": 8098,\n    \"Ġclosest\": 8099,\n    \"ĠCITY\": 8100,\n    \"Ġ83\": 8101,\n    \"Ġcancelled\": 8102,\n    \"ĠðŁ\": 8103,\n    \"Ġsharply\": 8104,\n    \"RS\": 8105,\n    \"Ġproductivity\": 8106,\n    \"Ġbasket\": 8107,\n    \"SS\": 8108,\n    \"Ġadmit\": 8109,\n    \"ool\": 8110,\n    \"ination\": 8111,\n    \"ĠBB\": 8112,\n    \"Ġsur\": 8113,\n    \"ĠSteel\": 8114,\n    \"ĠTed\": 8115,\n    \"ĠPac\": 8116,\n    \"Ġpatterns\": 8117,\n    \"Ġlisting\": 8118,\n    \"Ġreplacing\": 8119,\n    \"ĠPradesh\": 8120,\n    \"Ġroots\": 8121,\n    \"Ġbroker\": 8122,\n    \"ĠWriting\": 8123,\n    \"Ġsued\": 8124,\n    \"Ġorganised\": 8125,\n    \"ĠThanksgiving\": 8126,\n    \"ĠNOT\": 8127,\n    \"Ġjournalism\": 8128,\n    \"uel\": 8129,\n    \"Ġkilometers\": 8130,\n    \"Ġhunt\": 8131,\n    \"berry\": 8132,\n    \"ĠMother\": 8133,\n    \"Ġlegitimate\": 8134,\n    \"Ġinput\": 8135,\n    \"ĠRel\": 8136,\n    \"ĠGuardian\": 8137,\n    \"Ar\": 8138,\n    \"Ġtransported\": 8139,\n    \"Ġbedroom\": 8140,\n    \"ashing\": 8141,\n    \"Ġbats\": 8142,\n    \"Ġcleaning\": 8143,\n    \"Ġwrapped\": 8144,\n    \"Pacific\": 8145,\n    \"Ġfence\": 8146,\n    \"Ġtestified\": 8147,\n    \"Ġ1994\": 8148,\n    \"Ġinterference\": 8149,\n    \"Ġmatching\": 8150,\n    \"Ġexpression\": 8151,\n    \"eta\": 8152,\n    \"ĠSpencer\": 8153,\n    \"Ġstrategist\": 8154,\n    \"who\": 8155,\n    \"Ġvictories\": 8156,\n    \"Ġ2022\": 8157,\n    \"Ġstakes\": 8158,\n    \"Ġbuses\": 8159,\n    \"ĠHousing\": 8160,\n    \"Ġeditorial\": 8161,\n    \"Ġ86\": 8162,\n    \"ĠBishop\": 8163,\n    \"Ġfrustrated\": 8164,\n    \"Ġappearing\": 8165,\n    \"http\": 8166,\n    \"IGHT\": 8167,\n    \"Ġmemo\": 8168,\n    \"Ġinsiders\": 8169,\n    \"Even\": 8170,\n    \"Ġclassroom\": 8171,\n    \"Ġchef\": 8172,\n    \"aining\": 8173,\n    \"].\": 8174,\n    \"ĠMcD\": 8175,\n    \"Ġ87\": 8176,\n    \"ĠPunjab\": 8177,\n    \"Ġancient\": 8178,\n    \"Ġresolved\": 8179,\n    \"Ġdying\": 8180,\n    \"Ġdestruction\": 8181,\n    \"Ġgoverning\": 8182,\n    \"Ġrestructuring\": 8183,\n    \"ĠPick\": 8184,\n    \"Ġmunicipal\": 8185,\n    \"Ġengines\": 8186,\n    \"ĠHudson\": 8187,\n    \"Æ\": 8188,\n    \"Ġrepeal\": 8189,\n    \"standing\": 8190,\n    \"Ġbound\": 8191,\n    \"ĠOS\": 8192,\n    \"ĠCommonwealth\": 8193,\n    \"Ġdescription\": 8194,\n    \"Ġhouseholds\": 8195,\n    \"Ġmal\": 8196,\n    \"Ġstopping\": 8197,\n    \"equ\": 8198,\n    \"Ġregulator\": 8199,\n    \"Ġcontaining\": 8200,\n    \"Ġremoving\": 8201,\n    \"Ġwithdraw\": 8202,\n    \"Ġburied\": 8203,\n    \"Ġlists\": 8204,\n    \"ĠGil\": 8205,\n    \"Ġlowered\": 8206,\n    \"Ġformally\": 8207,\n    \"ĠRound\": 8208,\n    \"asi\": 8209,\n    \"¥\": 8210,\n    \"lett\": 8211,\n    \"Ġprogressive\": 8212,\n    \"ĠFalcons\": 8213,\n    \"ĠRaw\": 8214,\n    \"gun\": 8215,\n    \"Ġcontributing\": 8216,\n    \"Ġhunting\": 8217,\n    \"Ġvalid\": 8218,\n    \"Ġexception\": 8219,\n    \"ĠPlayers\": 8220,\n    \"ĠTra\": 8221,\n    \"Ġracism\": 8222,\n    \"hing\": 8223,\n    \"chen\": 8224,\n    \"Ġdifferently\": 8225,\n    \"Ġchampionships\": 8226,\n    \"ĠEng\": 8227,\n    \"ĠNO\": 8228,\n    \"ĠAuto\": 8229,\n    \"ĠErdogan\": 8230,\n    \"iding\": 8231,\n    \"Ġwarming\": 8232,\n    \"Ġcivilian\": 8233,\n    \"ĠDam\": 8234,\n    \"Ġfantasy\": 8235,\n    \"ĠNav\": 8236,\n    \"itions\": 8237,\n    \"ĠDrew\": 8238,\n    \"ĠNancy\": 8239,\n    \"Ġtrapped\": 8240,\n    \"ĠRussians\": 8241,\n    \"ĠIC\": 8242,\n    \"Ġflexibility\": 8243,\n    \"ular\": 8244,\n    \"Ġviolated\": 8245,\n    \"ipped\": 8246,\n    \"Ġgarage\": 8247,\n    \"ĠDeep\": 8248,\n    \"Ġpraise\": 8249,\n    \"ĠLab\": 8250,\n    \"ĠPlayer\": 8251,\n    \"Ġjudicial\": 8252,\n    \"Ġdonate\": 8253,\n    \"Ġseparated\": 8254,\n    \"Ġreleases\": 8255,\n    \"nik\": 8256,\n    \"Ġexplanation\": 8257,\n    \"aph\": 8258,\n    \"Ġloyal\": 8259,\n    \"Ġstrongest\": 8260,\n    \"ĠShar\": 8261,\n    \"Ġrescued\": 8262,\n    \"Ġambitious\": 8263,\n    \"Ġclimb\": 8264,\n    \"Ġscared\": 8265,\n    \"Ġignored\": 8266,\n    \"cut\": 8267,\n    \"Ġstole\": 8268,\n    \"Ġweakness\": 8269,\n    \"ĠRidge\": 8270,\n    \"oa\": 8271,\n    \"LA\": 8272,\n    \"Ġdep\": 8273,\n    \"ĠPowell\": 8274,\n    \"Do\": 8275,\n    \"Ġprotein\": 8276,\n    \"Ġreiterated\": 8277,\n    \"ĠCox\": 8278,\n    \"aling\": 8279,\n    \"ĠUnlike\": 8280,\n    \"ĠKane\": 8281,\n    \"ĠMcConnell\": 8282,\n    \"Ġshowcase\": 8283,\n    \"Ġuniform\": 8284,\n    \"ower\": 8285,\n    \"Ġdiscover\": 8286,\n    \"stop\": 8287,\n    \"ipper\": 8288,\n    \"Ġtreatments\": 8289,\n    \"Ġgrocery\": 8290,\n    \"Ġsubscribers\": 8291,\n    \"lock\": 8292,\n    \"ple\": 8293,\n    \"Ġflew\": 8294,\n    \"ania\": 8295,\n    \"Ġstepping\": 8296,\n    \"ĠSoviet\": 8297,\n    \"Ġconsultant\": 8298,\n    \"ags\": 8299,\n    \"ĠLim\": 8300,\n    \"Ġ91\": 8301,\n    \"ĠCode\": 8302,\n    \"ports\": 8303,\n    \"box\": 8304,\n    \"Ġlakh\": 8305,\n    \"Ġreminder\": 8306,\n    \"ym\": 8307,\n    \"ĠTravis\": 8308,\n    \"Ġpure\": 8309,\n    \"now\": 8310,\n    \"ĠVR\": 8311,\n    \"Ġachievement\": 8312,\n    \"ĠEmirates\": 8313,\n    \"ĠThunder\": 8314,\n    \"Ġmerely\": 8315,\n    \"ĠCa\": 8316,\n    \"ĠAverage\": 8317,\n    \"ĠDa\": 8318,\n    \"Ġtopped\": 8319,\n    \"ĠCurry\": 8320,\n    \"Ġchemicals\": 8321,\n    \"Ġamendment\": 8322,\n    \"ĠBorder\": 8323,\n    \"ĠBat\": 8324,\n    \"Ġ130\": 8325,\n    \"Ġprogramming\": 8326,\n    \"Ġtele\": 8327,\n    \"ĠKarl\": 8328,\n    \"Ġaveraged\": 8329,\n    \"ĠSpe\": 8330,\n    \"world\": 8331,\n    \"PG\": 8332,\n    \"Ġfights\": 8333,\n    \"ĠPrincess\": 8334,\n    \"ĠCIA\": 8335,\n    \"ĠAbe\": 8336,\n    \"Ġacted\": 8337,\n    \"only\": 8338,\n    \"Ġinsight\": 8339,\n    \"Ġathlete\": 8340,\n    \"ĠTar\": 8341,\n    \"commerce\": 8342,\n    \"Ġaveraging\": 8343,\n    \"cr\": 8344,\n    \"ĠPalestinians\": 8345,\n    \"Well\": 8346,\n    \"Ġbull\": 8347,\n    \"Ġchoosing\": 8348,\n    \"Ġsurely\": 8349,\n    \"ĠSecret\": 8350,\n    \"Ġteammate\": 8351,\n    \"ĠAmendment\": 8352,\n    \"ĠBirmingham\": 8353,\n    \"Ġexcitement\": 8354,\n    \"strong\": 8355,\n    \"ĠSin\": 8356,\n    \"Ġdamages\": 8357,\n    \"rated\": 8358,\n    \"Ġrankings\": 8359,\n    \"Ġconservation\": 8360,\n    \"home\": 8361,\n    \"erm\": 8362,\n    \"ield\": 8363,\n    \"Ġdisorder\": 8364,\n    \"acher\": 8365,\n    \"Ġnaturally\": 8366,\n    \"atur\": 8367,\n    \"Ġpackages\": 8368,\n    \"Ġapproaches\": 8369,\n    \"icks\": 8370,\n    \"ourn\": 8371,\n    \"Ġodd\": 8372,\n    \"Ġshore\": 8373,\n    \"ĠBeing\": 8374,\n    \"Ġmagic\": 8375,\n    \"Ġtourist\": 8376,\n    \"largest\": 8377,\n    \"Ġwhenever\": 8378,\n    \"Ġlenders\": 8379,\n    \"Ġegg\": 8380,\n    \"ĠChair\": 8381,\n    \"Ġlets\": 8382,\n    \"Ġwarnings\": 8383,\n    \"į\": 8384,\n    \"Ġpol\": 8385,\n    \"Ġdrag\": 8386,\n    \"ĠAmb\": 8387,\n    \"ĠCle\": 8388,\n    \"ĠLouisville\": 8389,\n    \"ĠShaw\": 8390,\n    \"lands\": 8391,\n    \"Ġanthem\": 8392,\n    \"ĠTrail\": 8393,\n    \"Ġaccepting\": 8394,\n    \"anger\": 8395,\n    \"good\": 8396,\n    \"ĠBroad\": 8397,\n    \"ĠLebanon\": 8398,\n    \"ĠMillion\": 8399,\n    \"ĠHenderson\": 8400,\n    \"Ġwh\": 8401,\n    \"Ġdust\": 8402,\n    \"Ġ92\": 8403,\n    \"ĠMend\": 8404,\n    \"Ġchecking\": 8405,\n    \"ĠCow\": 8406,\n    \"sized\": 8407,\n    \"Ġautomatic\": 8408,\n    \"Ġcelebrates\": 8409,\n    \"Ġarena\": 8410,\n    \"Ġfinger\": 8411,\n    \"ĠHarvard\": 8412,\n    \"Ġfrustration\": 8413,\n    \"Ġstrict\": 8414,\n    \"Ġpreserve\": 8415,\n    \"Ġsleeping\": 8416,\n    \"Ġconverted\": 8417,\n    \"Ġinsights\": 8418,\n    \"Ġtra\": 8419,\n    \"Ġjailed\": 8420,\n    \"Ġchamber\": 8421,\n    \"Ġtoxic\": 8422,\n    \"ading\": 8423,\n    \"ĠTriple\": 8424,\n    \"grade\": 8425,\n    \"ĠRest\": 8426,\n    \"ĠHoly\": 8427,\n    \"oper\": 8428,\n    \"Ġdesk\": 8429,\n    \"Ġmatchup\": 8430,\n    \"Ġsteep\": 8431,\n    \"ĠGot\": 8432,\n    \"lay\": 8433,\n    \"ĠCab\": 8434,\n    \"aked\": 8435,\n    \"ĠFoster\": 8436,\n    \"Ġrunners\": 8437,\n    \"ĠNA\": 8438,\n    \"Ġdestroy\": 8439,\n    \"Ġsupportive\": 8440,\n    \"ĠRacing\": 8441,\n    \"Ġtrademark\": 8442,\n    \"Ġjacket\": 8443,\n    \"Ġhorror\": 8444,\n    \"ĠAle\": 8445,\n    \"Ġass\": 8446,\n    \"Ġsch\": 8447,\n    \"abb\": 8448,\n    \"Ġplanes\": 8449,\n    \"Ġimpression\": 8450,\n    \"ĠEarly\": 8451,\n    \"ĠPompe\": 8452,\n    \"Ġking\": 8453,\n    \"Ġsilent\": 8454,\n    \"ĠCuba\": 8455,\n    \"Ġmedication\": 8456,\n    \"ences\": 8457,\n    \"list\": 8458,\n    \"ailing\": 8459,\n    \"WA\": 8460,\n    \"ella\": 8461,\n    \"Ġprop\": 8462,\n    \"Ġhalt\": 8463,\n    \"Ġslowing\": 8464,\n    \"ĠFoods\": 8465,\n    \"Ġanonymous\": 8466,\n    \"kh\": 8467,\n    \"Ġtraveled\": 8468,\n    \"Ġcommunicate\": 8469,\n    \"Ġter\": 8470,\n    \"ĠHockey\": 8471,\n    \"ĠRobin\": 8472,\n    \"Ġswept\": 8473,\n    \"Ġclinic\": 8474,\n    \"ration\": 8475,\n    \"len\": 8476,\n    \"Ġau\": 8477,\n    \"Ġcareers\": 8478,\n    \"ĠSound\": 8479,\n    \"Ġaddresses\": 8480,\n    \"China\": 8481,\n    \"ĠSr\": 8482,\n    \"Ġexhibit\": 8483,\n    \"ĠMotors\": 8484,\n    \"ĠIl\": 8485,\n    \"Ġinstall\": 8486,\n    \"ĠOkay\": 8487,\n    \"Ġ>>\": 8488,\n    \"hood\": 8489,\n    \"stand\": 8490,\n    \"Ġaudit\": 8491,\n    \"Ġcake\": 8492,\n    \"Ġflames\": 8493,\n    \"bel\": 8494,\n    \"ĠMust\": 8495,\n    \"ĠManafort\": 8496,\n    \"Ġcommodity\": 8497,\n    \"night\": 8498,\n    \"ĠRoom\": 8499,\n    \"ĠLanka\": 8500,\n    \"Ġcommander\": 8501,\n    \"ln\": 8502,\n    \"Ġdatabase\": 8503,\n    \"ĠSet\": 8504,\n    \"Ġgraduated\": 8505,\n    \"ĠTarget\": 8506,\n    \"Ġoutbreak\": 8507,\n    \"rou\": 8508,\n    \"ĠPope\": 8509,\n    \"ĠEqu\": 8510,\n    \"Ġpolling\": 8511,\n    \"Ġdig\": 8512,\n    \"Ġbrutal\": 8513,\n    \"ĠBarn\": 8514,\n    \"Ġdefinition\": 8515,\n    \"Ġpit\": 8516,\n    \"Ġpickup\": 8517,\n    \"ĠBitcoin\": 8518,\n    \"ĠReid\": 8519,\n    \"Ġloving\": 8520,\n    \"ĠHerald\": 8521,\n    \"ĠCanadians\": 8522,\n    \"Ġneighbor\": 8523,\n    \"Ġdies\": 8524,\n    \"ione\": 8525,\n    \"ĠRef\": 8526,\n    \"big\": 8527,\n    \"Ġguards\": 8528,\n    \"including\": 8529,\n    \"ente\": 8530,\n    \"Ġpartially\": 8531,\n    \"Image\": 8532,\n    \"Ġbulk\": 8533,\n    \"Ġslot\": 8534,\n    \"ĠNorthwest\": 8535,\n    \"ĠBarclays\": 8536,\n    \"Ġairlines\": 8537,\n    \"iver\": 8538,\n    \"isi\": 8539,\n    \"Ġsubsidiary\": 8540,\n    \"Ġcont\": 8541,\n    \"ĠDaniels\": 8542,\n    \"Ġscript\": 8543,\n    \"Ġunfair\": 8544,\n    \"Ġscreens\": 8545,\n    \"Ġprof\": 8546,\n    \"ĠIrma\": 8547,\n    \"Ġ1992\": 8548,\n    \"Ġmandatory\": 8549,\n    \"ĠSant\": 8550,\n    \"Ġsuspicion\": 8551,\n    \"NES\": 8552,\n    \"ĠLauren\": 8553,\n    \"igen\": 8554,\n    \"Ġprevention\": 8555,\n    \"Ġtension\": 8556,\n    \"ema\": 8557,\n    \"Ġtasks\": 8558,\n    \"Ġshake\": 8559,\n    \"Ġexplosive\": 8560,\n    \"Ġaffects\": 8561,\n    \"Ġmum\": 8562,\n    \"ĠDog\": 8563,\n    \"rer\": 8564,\n    \"Ġopted\": 8565,\n    \"Ġtrio\": 8566,\n    \"Ġlesson\": 8567,\n    \"Ġautomotive\": 8568,\n    \"where\": 8569,\n    \"ĠMontgomery\": 8570,\n    \"Ġcouples\": 8571,\n    \"Ġ89\": 8572,\n    \"AF\": 8573,\n    \"Ġinfo\": 8574,\n    \"ĠForm\": 8575,\n    \"Ġspectrum\": 8576,\n    \"Ġbands\": 8577,\n    \"Ġokay\": 8578,\n    \"Ġstroke\": 8579,\n    \"ĠNetanyahu\": 8580,\n    \"Ġwealthy\": 8581,\n    \"ĠAround\": 8582,\n    \"ĠGlenn\": 8583,\n    \"sec\": 8584,\n    \"there\": 8585,\n    \"ickets\": 8586,\n    \"ĠBudget\": 8587,\n    \"ĠBMW\": 8588,\n    \"Ġflagship\": 8589,\n    \"rier\": 8590,\n    \"Ġpodcast\": 8591,\n    \"Ġpursuing\": 8592,\n    \"Ġpos\": 8593,\n    \"ĠIslands\": 8594,\n    \"ĠUrban\": 8595,\n    \"page\": 8596,\n    \"Ġemotions\": 8597,\n    \"ided\": 8598,\n    \"Ġdividends\": 8599,\n    \"Ġboom\": 8600,\n    \"Ġaccusing\": 8601,\n    \"ird\": 8602,\n    \"ĠNam\": 8603,\n    \"ava\": 8604,\n    \"Ġwishes\": 8605,\n    \"ĠNy\": 8606,\n    \"ĠStanford\": 8607,\n    \"Ġcriteria\": 8608,\n    \"ĠJews\": 8609,\n    \"Ġengineers\": 8610,\n    \"Ġaccuracy\": 8611,\n    \"Ġdisplays\": 8612,\n    \"Ġdeserves\": 8613,\n    \"ridge\": 8614,\n    \"omm\": 8615,\n    \"aur\": 8616,\n    \"Ġdramatically\": 8617,\n    \"Ġunity\": 8618,\n    \"speed\": 8619,\n    \"Ġdeclining\": 8620,\n    \"Ġpermits\": 8621,\n    \"ĠKn\": 8622,\n    \"Ġconsulting\": 8623,\n    \"aux\": 8624,\n    \"ATE\": 8625,\n    \"ĠWat\": 8626,\n    \"ĠEditor\": 8627,\n    \"sy\": 8628,\n    \"urn\": 8629,\n    \"ĠUsing\": 8630,\n    \"asc\": 8631,\n    \"ital\": 8632,\n    \"Ġcre\": 8633,\n    \"quality\": 8634,\n    \"Ġce\": 8635,\n    \"Ġenemy\": 8636,\n    \"Ġoffence\": 8637,\n    \"icket\": 8638,\n    \"ĠDick\": 8639,\n    \"ĠTH\": 8640,\n    \"ĠChampionships\": 8641,\n    \"Ġoverwhelming\": 8642,\n    \"rib\": 8643,\n    \"ku\": 8644,\n    \"rap\": 8645,\n    \"Ġhomer\": 8646,\n    \"acion\": 8647,\n    \"member\": 8648,\n    \"erv\": 8649,\n    \"aney\": 8650,\n    \"MB\": 8651,\n    \"eded\": 8652,\n    \"Ġpunishment\": 8653,\n    \"Ġnegotiate\": 8654,\n    \"ĠFile\": 8655,\n    \"stream\": 8656,\n    \"ĠHur\": 8657,\n    \"Ġnose\": 8658,\n    \"ĠFab\": 8659,\n    \"iter\": 8660,\n    \"Ġpainful\": 8661,\n    \"ITY\": 8662,\n    \"eren\": 8663,\n    \"Ġcollecting\": 8664,\n    \"Additional\": 8665,\n    \"Ġentrepreneurs\": 8666,\n    \"bal\": 8667,\n    \"Ġexploring\": 8668,\n    \"Ġguitar\": 8669,\n    \"Ġpartnerships\": 8670,\n    \"Ġfurniture\": 8671,\n    \"Ġauthorized\": 8672,\n    \"Ġeasing\": 8673,\n    \"shirt\": 8674,\n    \"ĠGross\": 8675,\n    \"Ġpolitician\": 8676,\n    \"ĠSimpson\": 8677,\n    \"Ġdrone\": 8678,\n    \"ĠKatie\": 8679,\n    \"Ġprofitability\": 8680,\n    \"ĠNHS\": 8681,\n    \"ĠSierra\": 8682,\n    \"ĠNorway\": 8683,\n    \"ASHINGTON\": 8684,\n    \"ific\": 8685,\n    \"Ġcondemned\": 8686,\n    \"team\": 8687,\n    \"ĠNebraska\": 8688,\n    \"Ġthrilled\": 8689,\n    \"iller\": 8690,\n    \"Ġpatrol\": 8691,\n    \"ĠWR\": 8692,\n    \"orm\": 8693,\n    \"Ġspectacular\": 8694,\n    \"ĠKnight\": 8695,\n    \"ĠTravel\": 8696,\n    \"nam\": 8697,\n    \"Ġmuscle\": 8698,\n    \"ĠRain\": 8699,\n    \"ĠColombia\": 8700,\n    \"Ġnursing\": 8701,\n    \"Ġmigration\": 8702,\n    \"ĠMitch\": 8703,\n    \"Ġreleasing\": 8704,\n    \"ĠBesides\": 8705,\n    \"ĠMul\": 8706,\n    \"Ġheadline\": 8707,\n    \"Ġcontemporary\": 8708,\n    \"Ġdev\": 8709,\n    \"ĠChan\": 8710,\n    \"Ġindicates\": 8711,\n    \"ĠAp\": 8712,\n    \"ĠLt\": 8713,\n    \"ĠMarvel\": 8714,\n    \"Ġremembered\": 8715,\n    \"Â®\": 8716,\n    \"ĠForces\": 8717,\n    \"ĠColin\": 8718,\n    \"ĠGabriel\": 8719,\n    \"Ġobjects\": 8720,\n    \"ĠRHP\": 8721,\n    \"kar\": 8722,\n    \"ĠKo\": 8723,\n    \"Ġsignals\": 8724,\n    \"Ġinner\": 8725,\n    \"real\": 8726,\n    \"RO\": 8727,\n    \"Ġromantic\": 8728,\n    \"cat\": 8729,\n    \"ĠKel\": 8730,\n    \"Ġgut\": 8731,\n    \"ĠBoys\": 8732,\n    \"Ġyoungest\": 8733,\n    \"ĠCeltics\": 8734,\n    \"Ġslated\": 8735,\n    \"Ġremind\": 8736,\n    \"Ġproductive\": 8737,\n    \"set\": 8738,\n    \"Co\": 8739,\n    \"ĠBailey\": 8740,\n    \"Ġrenewable\": 8741,\n    \"ĠCarson\": 8742,\n    \"ĠDj\": 8743,\n    \"ĠKos\": 8744,\n    \"Ġurge\": 8745,\n    \"Ġfin\": 8746,\n    \"Ġpursuit\": 8747,\n    \"ĠCON\": 8748,\n    \"ĠChapter\": 8749,\n    \"Ġpal\": 8750,\n    \"Ġgate\": 8751,\n    \"ĠPackers\": 8752,\n    \"ĠReports\": 8753,\n    \"ĠRugby\": 8754,\n    \"ĠMasters\": 8755,\n    \"MO\": 8756,\n    \"Ġ98\": 8757,\n    \"Ġcatches\": 8758,\n    \"ĠAgreement\": 8759,\n    \"ĠTillerson\": 8760,\n    \"ĠIce\": 8761,\n    \"Ġrumors\": 8762,\n    \"ĠLeonard\": 8763,\n    \"ĠDolphins\": 8764,\n    \"ĠLP\": 8765,\n    \"top\": 8766,\n    \"ĠCrist\": 8767,\n    \"ĠHon\": 8768,\n    \"Ġblaze\": 8769,\n    \"Ġrhetoric\": 8770,\n    \"ands\": 8771,\n    \"ady\": 8772,\n    \"David\": 8773,\n    \"igh\": 8774,\n    \"Ġbuzz\": 8775,\n    \"ĠStrong\": 8776,\n    \"Ġshocking\": 8777,\n    \"ĠRh\": 8778,\n    \"Ġnegotiating\": 8779,\n    \"Ġtender\": 8780,\n    \"ĠJohnny\": 8781,\n    \"ĠMario\": 8782,\n    \"Ġ97\": 8783,\n    \"ĠHeritage\": 8784,\n    \"Ġexists\": 8785,\n    \"Ġprayers\": 8786,\n    \"Ġlengthy\": 8787,\n    \"Ġsafer\": 8788,\n    \"ĠHalloween\": 8789,\n    \"ĠJared\": 8790,\n    \"ĠConnect\": 8791,\n    \"Ġbump\": 8792,\n    \"Ġstrain\": 8793,\n    \"Ġfilling\": 8794,\n    \"Ġtrauma\": 8795,\n    \"Ġcompleting\": 8796,\n    \"cht\": 8797,\n    \"Ġkillings\": 8798,\n    \"anne\": 8799,\n    \"GE\": 8800,\n    \"ĠRescue\": 8801,\n    \"Ġdealers\": 8802,\n    \"Ġlocals\": 8803,\n    \"ĠVictor\": 8804,\n    \"Ġtragic\": 8805,\n    \"Ġdelivers\": 8806,\n    \"orts\": 8807,\n    \"Ġrugby\": 8808,\n    \"Ġinstallation\": 8809,\n    \"asa\": 8810,\n    \"ĠBart\": 8811,\n    \"Ġjournal\": 8812,\n    \"school\": 8813,\n    \"ĠCome\": 8814,\n    \"ĠVeterans\": 8815,\n    \"Sun\": 8816,\n    \"Ġcrowds\": 8817,\n    \"Ġtransparent\": 8818,\n    \"Ġimplications\": 8819,\n    \"ĠHuawei\": 8820,\n    \"sex\": 8821,\n    \"Ġrallied\": 8822,\n    \"Ġresponses\": 8823,\n    \"Ġdebris\": 8824,\n    \"Ġconvention\": 8825,\n    \"Ġmothers\": 8826,\n    \"BE\": 8827,\n    \"ĠRoute\": 8828,\n    \"Ġrebel\": 8829,\n    \"ĠEmmanuel\": 8830,\n    \"aster\": 8831,\n    \"Ġunderstands\": 8832,\n    \"pound\": 8833,\n    \"ĠCastle\": 8834,\n    \"Ġ2021\": 8835,\n    \"rik\": 8836,\n    \"ĠGR\": 8837,\n    \"Ġconvince\": 8838,\n    \"ault\": 8839,\n    \"Ġpassionate\": 8840,\n    \"ĠSciences\": 8841,\n    \"Ġarrives\": 8842,\n    \"idad\": 8843,\n    \"Ġcelebrities\": 8844,\n    \"ends\": 8845,\n    \"ĠFans\": 8846,\n    \"Ġdish\": 8847,\n    \"ĠCorps\": 8848,\n    \"hat\": 8849,\n    \"Ġemployer\": 8850,\n    \"ĠHy\": 8851,\n    \"Ġpowered\": 8852,\n    \"Ġgrandmother\": 8853,\n    \"ĠFL\": 8854,\n    \"oured\": 8855,\n    \"VE\": 8856,\n    \"ĠInst\": 8857,\n    \"ĠPerez\": 8858,\n    \"Ġtune\": 8859,\n    \"Ġcitizenship\": 8860,\n    \"Ġignore\": 8861,\n    \"Ġdoubles\": 8862,\n    \"IB\": 8863,\n    \"Ġprogrammes\": 8864,\n    \"inda\": 8865,\n    \"Ġentities\": 8866,\n    \"ĠInterior\": 8867,\n    \"Ġprompting\": 8868,\n    \"Ġwire\": 8869,\n    \"Ġtheatre\": 8870,\n    \"%)\": 8871,\n    \"Ġheels\": 8872,\n    \"ĠJu\": 8873,\n    \"Ġdeposits\": 8874,\n    \"Ġtrash\": 8875,\n    \"mond\": 8876,\n    \"she\": 8877,\n    \"iana\": 8878,\n    \"Ġislands\": 8879,\n    \"ĠTommy\": 8880,\n    \"Ġpub\": 8881,\n    \"Ġdiscipline\": 8882,\n    \"ĠSW\": 8883,\n    \"Ġmusicians\": 8884,\n    \"Ġembassy\": 8885,\n    \"ĠQB\": 8886,\n    \"hander\": 8887,\n    \"UES\": 8888,\n    \"ĠFerguson\": 8889,\n    \"Ġblocking\": 8890,\n    \"ahn\": 8891,\n    \"Ġfines\": 8892,\n    \"Ġtactics\": 8893,\n    \"Ġbullet\": 8894,\n    \"Ġequipped\": 8895,\n    \"Ġescaped\": 8896,\n    \"ĠSil\": 8897,\n    \"ĠPack\": 8898,\n    \"ĠAthletic\": 8899,\n    \"ĠMic\": 8900,\n    \"ĠDoes\": 8901,\n    \"ĠCarr\": 8902,\n    \"ĠChargers\": 8903,\n    \"ĠKyl\": 8904,\n    \"Ġzones\": 8905,\n    \"µ\": 8906,\n    \"iki\": 8907,\n    \"Ġgreatly\": 8908,\n    \"ĠMD\": 8909,\n    \"Ġimmigrant\": 8910,\n    \"ĠConstruction\": 8911,\n    \"ĠBorn\": 8912,\n    \"iment\": 8913,\n    \"ĠWade\": 8914,\n    \"Ġvisa\": 8915,\n    \"Ġgenuine\": 8916,\n    \"Ġelectronics\": 8917,\n    \"ĠSat\": 8918,\n    \"Ġsponsors\": 8919,\n    \"ĠMontana\": 8920,\n    \"Ġspell\": 8921,\n    \"ĠSachs\": 8922,\n    \"ĠEt\": 8923,\n    \"Ġfoster\": 8924,\n    \"Ġlocker\": 8925,\n    \"Ġexplaining\": 8926,\n    \"ĠAge\": 8927,\n    \"Ġgunman\": 8928,\n    \"Ġsauce\": 8929,\n    \"Ġcry\": 8930,\n    \"Ġstimulus\": 8931,\n    \"Ġarray\": 8932,\n    \"Ġcompare\": 8933,\n    \"Ġboats\": 8934,\n    \"Ġext\": 8935,\n    \"iders\": 8936,\n    \"ĠAst\": 8937,\n    \"ĠParks\": 8938,\n    \"ester\": 8939,\n    \"Ġ94\": 8940,\n    \"Ġrelating\": 8941,\n    \"Ġvegetables\": 8942,\n    \"Ġaccountable\": 8943,\n    \"Ġhyper\": 8944,\n    \"ĠWim\": 8945,\n    \"Ġnewest\": 8946,\n    \"ĠRome\": 8947,\n    \"ĠChancellor\": 8948,\n    \"CBS\": 8949,\n    \"Ġbusinessman\": 8950,\n    \"ĠDelaware\": 8951,\n    \"Ġlands\": 8952,\n    \"court\": 8953,\n    \"aria\": 8954,\n    \"Ġapproaching\": 8955,\n    \"cker\": 8956,\n    \"ĠSalt\": 8957,\n    \"ĠMak\": 8958,\n    \"Ġtreating\": 8959,\n    \"Ġsubsequently\": 8960,\n    \"ĠEll\": 8961,\n    \"xton\": 8962,\n    \"Ġ180\": 8963,\n    \"Ġdetermination\": 8964,\n    \"ĠSalman\": 8965,\n    \"ĠJoel\": 8966,\n    \"Ġclassified\": 8967,\n    \"Ġspan\": 8968,\n    \"Ġearthquake\": 8969,\n    \"ranked\": 8970,\n    \"Ġ96\": 8971,\n    \"ĠTiger\": 8972,\n    \"Ġadvocacy\": 8973,\n    \"mit\": 8974,\n    \"Ġcolleges\": 8975,\n    \"ĠYeah\": 8976,\n    \"ĠCaptain\": 8977,\n    \"Ġorange\": 8978,\n    \"Ġprojections\": 8979,\n    \"Ġelectrical\": 8980,\n    \"ĠMA\": 8981,\n    \"olog\": 8982,\n    \"ĠNewcastle\": 8983,\n    \"oppers\": 8984,\n    \"Ġrepresentation\": 8985,\n    \"Ġlawsuits\": 8986,\n    \"just\": 8987,\n    \"aced\": 8988,\n    \"ĠRace\": 8989,\n    \"ĠAqu\": 8990,\n    \"ĠBills\": 8991,\n    \"Ġexclusively\": 8992,\n    \"ĠProfile\": 8993,\n    \"Ġhometown\": 8994,\n    \"ĠStan\": 8995,\n    \"Ġstarring\": 8996,\n    \"Ġdeciding\": 8997,\n    \"ĠRating\": 8998,\n    \"ĠMedicare\": 8999,\n    \"ĠTransport\": 9000,\n    \"Ġmystery\": 9001,\n    \"ĠTa\": 9002,\n    \"ĠPad\": 9003,\n    \"ĠSwedish\": 9004,\n    \"ĠCarroll\": 9005,\n    \"about\": 9006,\n    \"Ġtorn\": 9007,\n    \"Ġnurse\": 9008,\n    \"NE\": 9009,\n    \"Ġwaited\": 9010,\n    \"ĠJeffrey\": 9011,\n    \"ĠUntil\": 9012,\n    \"Ġbone\": 9013,\n    \"ĠBobby\": 9014,\n    \"Ġpronounced\": 9015,\n    \"Ġpharmaceutical\": 9016,\n    \"ĠGallery\": 9017,\n    \"ĠMatch\": 9018,\n    \"Ġeconomists\": 9019,\n    \"ĠMarketing\": 9020,\n    \"face\": 9021,\n    \"ĠPetroleum\": 9022,\n    \"ories\": 9023,\n    \"ĠMets\": 9024,\n    \"ĠCore\": 9025,\n    \"billion\": 9026,\n    \"Ġexamination\": 9027,\n    \"ĠPorter\": 9028,\n    \"2016\": 9029,\n    \"Ġgolden\": 9030,\n    \"Ġsem\": 9031,\n    \"ĠDuterte\": 9032,\n    \"ĠJefferson\": 9033,\n    \"ĠTehran\": 9034,\n    \"ĠLeicester\": 9035,\n    \"ĠDA\": 9036,\n    \"Ġadapt\": 9037,\n    \"ĠDame\": 9038,\n    \"ĠRic\": 9039,\n    \"Ġunchanged\": 9040,\n    \"ect\": 9041,\n    \"Ġsections\": 9042,\n    \"kg\": 9043,\n    \"igned\": 9044,\n    \"Ġfilings\": 9045,\n    \"Ġreact\": 9046,\n    \"Ġurgent\": 9047,\n    \"Ġvessels\": 9048,\n    \"Ġspark\": 9049,\n    \"Ġbutter\": 9050,\n    \"ĠCons\": 9051,\n    \"Ġstating\": 9052,\n    \"Ġcorporations\": 9053,\n    \"ĠHus\": 9054,\n    \"Ġdamaging\": 9055,\n    \"raw\": 9056,\n    \"Ġequality\": 9057,\n    \"Two\": 9058,\n    \"ĠMills\": 9059,\n    \"iu\": 9060,\n    \"Ġobligation\": 9061,\n    \"ĠBrook\": 9062,\n    \"arian\": 9063,\n    \"Re\": 9064,\n    \"Ġphotographs\": 9065,\n    \"Ġepic\": 9066,\n    \"ĠStudent\": 9067,\n    \"ĠTherefore\": 9068,\n    \"Ġgod\": 9069,\n    \"ĠFILE\": 9070,\n    \"iqu\": 9071,\n    \"Ġdescribing\": 9072,\n    \"Ġproceed\": 9073,\n    \"Ġcas\": 9074,\n    \"ĠKat\": 9075,\n    \"ĠBra\": 9076,\n    \"Ġadequate\": 9077,\n    \"Ġpassage\": 9078,\n    \"Ġthanked\": 9079,\n    \"USA\": 9080,\n    \"ĠNeither\": 9081,\n    \"ĠLegislature\": 9082,\n    \"Ġfinances\": 9083,\n    \"Ġinst\": 9084,\n    \"ĵ\": 9085,\n    \"ĠAngels\": 9086,\n    \"Ġvet\": 9087,\n    \"ĠDead\": 9088,\n    \"Ex\": 9089,\n    \"Ġkicks\": 9090,\n    \"force\": 9091,\n    \"Ġsoy\": 9092,\n    \"ĠWindsor\": 9093,\n    \"Ġenhanced\": 9094,\n    \"Ġ1993\": 9095,\n    \"ĠCzech\": 9096,\n    \"Ġgradually\": 9097,\n    \"ĠMagic\": 9098,\n    \"Ġshadow\": 9099,\n    \"Ġneighborhoods\": 9100,\n    \"ĠRivers\": 9101,\n    \"Ġrapper\": 9102,\n    \"ĠGirl\": 9103,\n    \"ĠRot\": 9104,\n    \"Ġcrackdown\": 9105,\n    \"fish\": 9106,\n    \"Ġpreventing\": 9107,\n    \"Ġproduces\": 9108,\n    \"ĠMi\": 9109,\n    \"Ġnotified\": 9110,\n    \"Ġunderground\": 9111,\n    \"WE\": 9112,\n    \"Ġadmits\": 9113,\n    \"Ġboxing\": 9114,\n    \"Ġrefer\": 9115,\n    \"Ġcommitments\": 9116,\n    \"ĠWoman\": 9117,\n    \"Ġdenies\": 9118,\n    \"col\": 9119,\n    \"ĠSide\": 9120,\n    \"Ġambulance\": 9121,\n    \"ĠRodgers\": 9122,\n    \"Ġaftermath\": 9123,\n    \"Ġdeck\": 9124,\n    \"irmed\": 9125,\n    \"Ġerrors\": 9126,\n    \"ĠConvention\": 9127,\n    \"Ġcurb\": 9128,\n    \"ĠShop\": 9129,\n    \"ĠThai\": 9130,\n    \"Ġma\": 9131,\n    \"Ġrespected\": 9132,\n    \"ĠMVP\": 9133,\n    \"Ġborrowing\": 9134,\n    \"Ġcruise\": 9135,\n    \"ĠSure\": 9136,\n    \"Ġsentencing\": 9137,\n    \"ĠObamacare\": 9138,\n    \"ĠIr\": 9139,\n    \"ĠSale\": 9140,\n    \"ĠPete\": 9141,\n    \"Ġopenly\": 9142,\n    \"Ġstartup\": 9143,\n    \"rock\": 9144,\n    \"Ġcargo\": 9145,\n    \"Ġtelecom\": 9146,\n    \"ĠDownload\": 9147,\n    \"Ġextending\": 9148,\n    \"ĠCurrent\": 9149,\n    \"Ġcompetitions\": 9150,\n    \"ĠKids\": 9151,\n    \"Ġshy\": 9152,\n    \"ĠKerry\": 9153,\n    \"ĠNever\": 9154,\n    \"ĠDevils\": 9155,\n    \"Ġprim\": 9156,\n    \"Con\": 9157,\n    \"Ġcurve\": 9158,\n    \"Ġassumed\": 9159,\n    \"Ġadjust\": 9160,\n    \"Ġimmune\": 9161,\n    \"UE\": 9162,\n    \"ĠUr\": 9163,\n    \"Ġconventional\": 9164,\n    \"Ġgrandchildren\": 9165,\n    \"ĠBol\": 9166,\n    \"Ad\": 9167,\n    \"ĠMaduro\": 9168,\n    \"fi\": 9169,\n    \"ĠUAE\": 9170,\n    \"ĠOrgan\": 9171,\n    \"Ġindicating\": 9172,\n    \"iem\": 9173,\n    \"ĠAgainst\": 9174,\n    \"ĠAmbassador\": 9175,\n    \"ĠSeoul\": 9176,\n    \"Ġcriminals\": 9177,\n    \"how\": 9178,\n    \"put\": 9179,\n    \"Ġreminded\": 9180,\n    \"Ġparked\": 9181,\n    \"lich\": 9182,\n    \"Ġcontinent\": 9183,\n    \"Ġmatched\": 9184,\n    \"ĠNicole\": 9185,\n    \"Ġgenetic\": 9186,\n    \"Ġhumanity\": 9187,\n    \"ĠTem\": 9188,\n    \"Ġindicator\": 9189,\n    \"Ġvessel\": 9190,\n    \"Ġdefendant\": 9191,\n    \"ĠGriffin\": 9192,\n    \"jan\": 9193,\n    \"Ġvend\": 9194,\n    \"boro\": 9195,\n    \"Ġbrokerage\": 9196,\n    \"ĠFall\": 9197,\n    \"Ġmere\": 9198,\n    \"VILLE\": 9199,\n    \"Ġlasted\": 9200,\n    \"ĠMind\": 9201,\n    \"Ġpatch\": 9202,\n    \"ĠInsider\": 9203,\n    \"ĠComm\": 9204,\n    \"Ġtechnique\": 9205,\n    \"ĠIM\": 9206,\n    \"ĠCavaliers\": 9207,\n    \"Ġshame\": 9208,\n    \"Ġmil\": 9209,\n    \"oot\": 9210,\n    \"irt\": 9211,\n    \"Ġcop\": 9212,\n    \"ĠLeon\": 9213,\n    \"Ġfrozen\": 9214,\n    \"Ġslip\": 9215,\n    \"pton\": 9216,\n    \"Ġpanels\": 9217,\n    \"Ġpitching\": 9218,\n    \"Ġleather\": 9219,\n    \"ĠLogan\": 9220,\n    \"ĠNearly\": 9221,\n    \"urch\": 9222,\n    \"Ġinstructions\": 9223,\n    \"ĠRow\": 9224,\n    \"ĠKurdish\": 9225,\n    \"this\": 9226,\n    \"Ġlegendary\": 9227,\n    \"su\": 9228,\n    \"Ġstabbed\": 9229,\n    \"sters\": 9230,\n    \"Ġteenage\": 9231,\n    \"def\": 9232,\n    \"Ġoversight\": 9233,\n    \"Ġvolatile\": 9234,\n    \"Ġtransmission\": 9235,\n    \"ĠSgt\": 9236,\n    \"ĠIndigenous\": 9237,\n    \"ĠOxford\": 9238,\n    \"ĠCasey\": 9239,\n    \"Ġcor\": 9240,\n    \"Ġsalaries\": 9241,\n    \"Ġsponsor\": 9242,\n    \"Ġprescription\": 9243,\n    \"mat\": 9244,\n    \"ĠLeeds\": 9245,\n    \"ĠPakistani\": 9246,\n    \"Ġevil\": 9247,\n    \"Ġtables\": 9248,\n    \"ĠAbdul\": 9249,\n    \"Ġexpectation\": 9250,\n    \"Ġlegislature\": 9251,\n    \"ĠLin\": 9252,\n    \"¹\": 9253,\n    \"Ġcontractor\": 9254,\n    \"Ġshifting\": 9255,\n    \"Ġgenerous\": 9256,\n    \"ĠEddie\": 9257,\n    \"Ġpuck\": 9258,\n    \"utt\": 9259,\n    \"Ġdubbed\": 9260,\n    \"Ġnowhere\": 9261,\n    \"Ġbetting\": 9262,\n    \"Ġdisclose\": 9263,\n    \"Ĥ\": 9264,\n    \"ĠFashion\": 9265,\n    \"ĠHarper\": 9266,\n    \"handed\": 9267,\n    \"isha\": 9268,\n    \"ĠReds\": 9269,\n    \"Ġachievements\": 9270,\n    \"ume\": 9271,\n    \"Ġshootings\": 9272,\n    \"Ġadvisers\": 9273,\n    \"ĠEaster\": 9274,\n    \"Ġinternationally\": 9275,\n    \"ĠWi\": 9276,\n    \"ĠGandhi\": 9277,\n    \"ĠChristians\": 9278,\n    \"Ġrecruiting\": 9279,\n    \"Ġexperiment\": 9280,\n    \"Ġsol\": 9281,\n    \"Ġdifficulties\": 9282,\n    \"Ġinfluential\": 9283,\n    \"Ġhybrid\": 9284,\n    \"Ġformation\": 9285,\n    \"ĠBoulevard\": 9286,\n    \"Ġflags\": 9287,\n    \"Ġformula\": 9288,\n    \"front\": 9289,\n    \"Ġinclusion\": 9290,\n    \"ĠNone\": 9291,\n    \"ICE\": 9292,\n    \"Ġfilming\": 9293,\n    \"ĠLou\": 9294,\n    \"ĠReynolds\": 9295,\n    \"Ġpump\": 9296,\n    \"Ġexceptional\": 9297,\n    \"ANG\": 9298,\n    \"ĠCorporate\": 9299,\n    \"SAN\": 9300,\n    \"ĠHealthcare\": 9301,\n    \"ĠUkrainian\": 9302,\n    \"aron\": 9303,\n    \"Ġpants\": 9304,\n    \"Ġdrops\": 9305,\n    \"ete\": 9306,\n    \"ĠStudies\": 9307,\n    \"Ġwounds\": 9308,\n    \"END\": 9309,\n    \"Ġshower\": 9310,\n    \"Ġreviewing\": 9311,\n    \"ĠGreater\": 9312,\n    \"ĠÂ»\": 9313,\n    \"itors\": 9314,\n    \"alled\": 9315,\n    \"Ġsqu\": 9316,\n    \"ĠRonald\": 9317,\n    \"ĠInv\": 9318,\n    \"Ġtougher\": 9319,\n    \"Ġbalanced\": 9320,\n    \"Ġlined\": 9321,\n    \"Ġprinciple\": 9322,\n    \"Ġ1950\": 9323,\n    \"Ġleak\": 9324,\n    \"Be\": 9325,\n    \"Ġcircuit\": 9326,\n    \"Ġunfortunate\": 9327,\n    \"ĠGran\": 9328,\n    \"ĠFish\": 9329,\n    \"Ġfriendship\": 9330,\n    \"asp\": 9331,\n    \"OO\": 9332,\n    \"Ġobligations\": 9333,\n    \"Ġcoup\": 9334,\n    \"OK\": 9335,\n    \"Ġbreakdown\": 9336,\n    \"Ġhook\": 9337,\n    \"Ġresearcher\": 9338,\n    \"inated\": 9339,\n    \"ĠMarie\": 9340,\n    \"ĠGab\": 9341,\n    \"ĠWA\": 9342,\n    \"quez\": 9343,\n    \"General\": 9344,\n    \"ĠSwift\": 9345,\n    \"Ġgust\": 9346,\n    \"ĠCarol\": 9347,\n    \"ĠCentury\": 9348,\n    \"ĠOPEC\": 9349,\n    \"ĠRd\": 9350,\n    \"ĠCop\": 9351,\n    \"Ġsubjects\": 9352,\n    \"ĠComments\": 9353,\n    \"ases\": 9354,\n    \"Ġrelation\": 9355,\n    \"ĠEnvironment\": 9356,\n    \"ı\": 9357,\n    \"Ġgasoline\": 9358,\n    \"ĠLog\": 9359,\n    \"Ġicon\": 9360,\n    \"Ġprofitable\": 9361,\n    \"ĠRetail\": 9362,\n    \"ANC\": 9363,\n    \"Ġappealing\": 9364,\n    \"Ġvillages\": 9365,\n    \"Ġpizza\": 9366,\n    \"Ġmall\": 9367,\n    \"Ġtower\": 9368,\n    \"ĠLinda\": 9369,\n    \"Ġaccomplished\": 9370,\n    \"Ġpod\": 9371,\n    \"Ġleaked\": 9372,\n    \"ĠWed\": 9373,\n    \"Ġmer\": 9374,\n    \"Ġopposing\": 9375,\n    \"!'\": 9376,\n    \"Ġstomach\": 9377,\n    \"Ġrevealing\": 9378,\n    \"Ġho\": 9379,\n    \"DF\": 9380,\n    \"ĠSterling\": 9381,\n    \"Ġsolely\": 9382,\n    \"Ġpres\": 9383,\n    \"ĠCy\": 9384,\n    \"ĠLatest\": 9385,\n    \"ĠPitt\": 9386,\n    \"ĠThink\": 9387,\n    \"Ġcapability\": 9388,\n    \"aled\": 9389,\n    \"Ġexecuted\": 9390,\n    \"alling\": 9391,\n    \"ĠSilva\": 9392,\n    \"Ġrestricted\": 9393,\n    \"Ġdeclaration\": 9394,\n    \"Ġkilometres\": 9395,\n    \"rol\": 9396,\n    \"Ġidentifying\": 9397,\n    \"Ġdonors\": 9398,\n    \"vent\": 9399,\n    \"Ġcostly\": 9400,\n    \"ense\": 9401,\n    \"ĠSeeking\": 9402,\n    \"OURCE\": 9403,\n    \"iving\": 9404,\n    \"Ġplacing\": 9405,\n    \"tech\": 9406,\n    \"Ġbottles\": 9407,\n    \"writer\": 9408,\n    \"ĠSeahawks\": 9409,\n    \"oming\": 9410,\n    \"ĠArthur\": 9411,\n    \"ously\": 9412,\n    \"bin\": 9413,\n    \"ĠVa\": 9414,\n    \"Ġbias\": 9415,\n    \"Ġliability\": 9416,\n    \"ift\": 9417,\n    \"rak\": 9418,\n    \"aves\": 9419,\n    \"Ġcautious\": 9420,\n    \"ĠPrize\": 9421,\n    \"iley\": 9422,\n    \"ĠSharma\": 9423,\n    \"global\": 9424,\n    \"Ġwars\": 9425,\n    \"sm\": 9426,\n    \"ĠRemember\": 9427,\n    \"wind\": 9428,\n    \"ĠRichardson\": 9429,\n    \"ĠSum\": 9430,\n    \"ĠVincent\": 9431,\n    \"ĠRice\": 9432,\n    \"inf\": 9433,\n    \"Ġconsultation\": 9434,\n    \"range\": 9435,\n    \"Ġbacteria\": 9436,\n    \"Ġarchitecture\": 9437,\n    \"Ġpole\": 9438,\n    \"ĠMach\": 9439,\n    \"Ġcattle\": 9440,\n    \"Ġabused\": 9441,\n    \"being\": 9442,\n    \"ĠHERE\": 9443,\n    \"Ġfame\": 9444,\n    \"Ġhearings\": 9445,\n    \"ĠBrit\": 9446,\n    \"Ġjoins\": 9447,\n    \"ĠMcGregor\": 9448,\n    \"Ġoppose\": 9449,\n    \"Ġcheer\": 9450,\n    \"itting\": 9451,\n    \"imes\": 9452,\n    \"Ġusage\": 9453,\n    \"Ġstint\": 9454,\n    \"Ġoutlet\": 9455,\n    \"Ġshoppers\": 9456,\n    \"ĠBaptist\": 9457,\n    \"Ġinappropriate\": 9458,\n    \"ĠALSO\": 9459,\n    \"Ġstealing\": 9460,\n    \"Ġpledge\": 9461,\n    \"ĠRan\": 9462,\n    \"Ġphotographer\": 9463,\n    \"Ġprevented\": 9464,\n    \"Ġ01\": 9465,\n    \"ĠEngineering\": 9466,\n    \"ĠProducts\": 9467,\n    \"Ġuniverse\": 9468,\n    \"ĠMcCarthy\": 9469,\n    \"¿\": 9470,\n    \"graded\": 9471,\n    \"Ġinspection\": 9472,\n    \"Ġind\": 9473,\n    \"Fi\": 9474,\n    \"aren\": 9475,\n    \"Ġprotections\": 9476,\n    \"Ġsorts\": 9477,\n    \"ĠWorks\": 9478,\n    \"Ġbillionaire\": 9479,\n    \"ĠGay\": 9480,\n    \"ĠiPad\": 9481,\n    \"IX\": 9482,\n    \"Ġdefendants\": 9483,\n    \"band\": 9484,\n    \"Ġfarms\": 9485,\n    \"Ġhom\": 9486,\n    \"gal\": 9487,\n    \"iant\": 9488,\n    \"Ġnortheast\": 9489,\n    \"ĠJoint\": 9490,\n    \"Ġcanceled\": 9491,\n    \"Ġtoys\": 9492,\n    \"Ġrein\": 9493,\n    \"ĠTumblr\": 9494,\n    \"pees\": 9495,\n    \"ĠAut\": 9496,\n    \"Police\": 9497,\n    \"Ġaide\": 9498,\n    \"Ġachieving\": 9499,\n    \"Ġmund\": 9500,\n    \"ĠCommercial\": 9501,\n    \"first\": 9502,\n    \"Ġanticipate\": 9503,\n    \"iac\": 9504,\n    \"Ġprobation\": 9505,\n    \"hem\": 9506,\n    \"Ġports\": 9507,\n    \"ĠKer\": 9508,\n    \"Ġsupplier\": 9509,\n    \"ĠFather\": 9510,\n    \"ĠAnti\": 9511,\n    \"ashed\": 9512,\n    \"ĠTable\": 9513,\n    \"bledon\": 9514,\n    \"Ġunf\": 9515,\n    \"ĠRash\": 9516,\n    \"ĠLeBron\": 9517,\n    \"Car\": 9518,\n    \"bu\": 9519,\n    \"ĠDerek\": 9520,\n    \"Ġaccounted\": 9521,\n    \"ĠPri\": 9522,\n    \"nings\": 9523,\n    \"Ġreceives\": 9524,\n    \"lev\": 9525,\n    \"Ġbilateral\": 9526,\n    \"ĠList\": 9527,\n    \"ĠLG\": 9528,\n    \"ĠJazz\": 9529,\n    \"Ġrestored\": 9530,\n    \"Ġbattles\": 9531,\n    \"ials\": 9532,\n    \"Ġoccupied\": 9533,\n    \"Ġrepairs\": 9534,\n    \"Ġradar\": 9535,\n    \"ĠMLB\": 9536,\n    \"ĠNC\": 9537,\n    \"Ġflexible\": 9538,\n    \"ĠCommand\": 9539,\n    \"Ġcoat\": 9540,\n    \"ĠVir\": 9541,\n    \"ĠColts\": 9542,\n    \"ĠBC\": 9543,\n    \"Ġtwin\": 9544,\n    \"Ġprisoners\": 9545,\n    \"Ġslowed\": 9546,\n    \"hop\": 9547,\n    \"ĠInn\": 9548,\n    \"Ġconflicts\": 9549,\n    \"Ġmeasured\": 9550,\n    \"Ġautonomous\": 9551,\n    \"ĠBow\": 9552,\n    \"Ġdisc\": 9553,\n    \"inson\": 9554,\n    \"ĠSche\": 9555,\n    \"aire\": 9556,\n    \"ĠSU\": 9557,\n    \"ĠPeterson\": 9558,\n    \"Ġdrafted\": 9559,\n    \"ĠPelosi\": 9560,\n    \"ĠSoon\": 9561,\n    \"Ġmechanism\": 9562,\n    \"Ġaccountability\": 9563,\n    \"ĠNortheast\": 9564,\n    \"Ġfo\": 9565,\n    \"Ġanalytics\": 9566,\n    \"ĠEverything\": 9567,\n    \"Ġperceived\": 9568,\n    \"bers\": 9569,\n    \"Ġcelebrations\": 9570,\n    \"Ġinstruments\": 9571,\n    \"Ġstrip\": 9572,\n    \"ĠJuventus\": 9573,\n    \"Ġunfortunately\": 9574,\n    \"ĠGA\": 9575,\n    \"Ġwrestling\": 9576,\n    \"Ġstatue\": 9577,\n    \"vis\": 9578,\n    \"five\": 9579,\n    \"Ġmarine\": 9580,\n    \"ĠSamuel\": 9581,\n    \"Ġresponsibilities\": 9582,\n    \"hill\": 9583,\n    \"Ġrecruit\": 9584,\n    \"Ġreferee\": 9585,\n    \"ĠRail\": 9586,\n    \"ĠEagle\": 9587,\n    \"ĠCongressional\": 9588,\n    \"Ġbreathing\": 9589,\n    \"Ġbass\": 9590,\n    \"hit\": 9591,\n    \"Ġspreading\": 9592,\n    \"Ġevacuated\": 9593,\n    \"Ġintellectual\": 9594,\n    \"Ġsovereign\": 9595,\n    \"ocked\": 9596,\n    \"Ġslammed\": 9597,\n    \"Ġformerly\": 9598,\n    \"Ġarch\": 9599,\n    \"Ġdifficulty\": 9600,\n    \"ĠAFC\": 9601,\n    \"ĠFresh\": 9602,\n    \"Ġinvite\": 9603,\n    \"oner\": 9604,\n    \"ĠMich\": 9605,\n    \"Ġpitches\": 9606,\n    \"stock\": 9607,\n    \"Ġinitiated\": 9608,\n    \"ĠKu\": 9609,\n    \"ĠFlorence\": 9610,\n    \"yd\": 9611,\n    \"ĠFast\": 9612,\n    \"Ġmusician\": 9613,\n    \"ĠChile\": 9614,\n    \"anga\": 9615,\n    \"Ġdairy\": 9616,\n    \"Ġcontractors\": 9617,\n    \"ador\": 9618,\n    \"ĠPlanning\": 9619,\n    \"Ġultra\": 9620,\n    \"Ġprayer\": 9621,\n    \"Ġsuggestions\": 9622,\n    \"ĠEk\": 9623,\n    \"Ġrandom\": 9624,\n    \"ĠSullivan\": 9625,\n    \"Ġsensor\": 9626,\n    \"Ġhomicide\": 9627,\n    \"ĠIncome\": 9628,\n    \"Ġsettings\": 9629,\n    \"Ġacknowledge\": 9630,\n    \"ĠStay\": 9631,\n    \"Ġterminal\": 9632,\n    \"Ġ1991\": 9633,\n    \"West\": 9634,\n    \"hard\": 9635,\n    \"arc\": 9636,\n    \"Ġcombine\": 9637,\n    \"Ġprivately\": 9638,\n    \"Ġbarrier\": 9639,\n    \"Ġmedian\": 9640,\n    \"Ġwhereas\": 9641,\n    \"ĠTitans\": 9642,\n    \"Ġincentives\": 9643,\n    \"Ġhistorically\": 9644,\n    \"Ġindictment\": 9645,\n    \"Ġhiding\": 9646,\n    \"ĠPDT\": 9647,\n    \"Ġrebuild\": 9648,\n    \"hol\": 9649,\n    \"Ġpour\": 9650,\n    \"Ġairports\": 9651,\n    \"ĠEdinburgh\": 9652,\n    \"Ġappoint\": 9653,\n    \"ĠJul\": 9654,\n    \"Ġconfusion\": 9655,\n    \"Ġdam\": 9656,\n    \"ork\": 9657,\n    \"Ġcalculated\": 9658,\n    \"Ġhood\": 9659,\n    \"ĠTemple\": 9660,\n    \"ĠYorkshire\": 9661,\n    \"EP\": 9662,\n    \"ented\": 9663,\n    \"Ġapology\": 9664,\n    \"awi\": 9665,\n    \"Ġfacilitate\": 9666,\n    \"ĠSheffield\": 9667,\n    \"Ġrides\": 9668,\n    \"Ġcompelling\": 9669,\n    \"ĠGonzalez\": 9670,\n    \"roll\": 9671,\n    \"ONG\": 9672,\n    \"UP\": 9673,\n    \"ĠAj\": 9674,\n    \"pen\": 9675,\n    \"ĠVar\": 9676,\n    \"ĠIPO\": 9677,\n    \"ĠAnimal\": 9678,\n    \"Ġshifted\": 9679,\n    \"Ġ140\": 9680,\n    \"Ġtobacco\": 9681,\n    \"El\": 9682,\n    \"ild\": 9683,\n    \"Ġuncertain\": 9684,\n    \"Un\": 9685,\n    \"Ġcaps\": 9686,\n    \"Ġrecreational\": 9687,\n    \"ĠTu\": 9688,\n    \"Ġenc\": 9689,\n    \"More\": 9690,\n    \"iko\": 9691,\n    \"ĠEverton\": 9692,\n    \"ĠWalk\": 9693,\n    \"Ġmurdered\": 9694,\n    \"Ġpur\": 9695,\n    \"Ġdivisions\": 9696,\n    \"ivo\": 9697,\n    \"Ġfarming\": 9698,\n    \"Ġcourage\": 9699,\n    \"ped\": 9700,\n    \"Ġcrying\": 9701,\n    \"Ġattributed\": 9702,\n    \"Ã©e\": 9703,\n    \"Ġimplementing\": 9704,\n    \"ĠWang\": 9705,\n    \"Ġspeeds\": 9706,\n    \"alk\": 9707,\n    \"aming\": 9708,\n    \"eries\": 9709,\n    \"Ġavoided\": 9710,\n    \"ĠMessi\": 9711,\n    \"Ġconsiderable\": 9712,\n    \"rt\": 9713,\n    \"Ġinauguration\": 9714,\n    \"ĠPH\": 9715,\n    \"Ġsoldier\": 9716,\n    \"Ġore\": 9717,\n    \"ollywood\": 9718,\n    \"otive\": 9719,\n    \"ĠAuburn\": 9720,\n    \"ĠSav\": 9721,\n    \"ĠPut\": 9722,\n    \"Ġemphasis\": 9723,\n    \"Ġaf\": 9724,\n    \"owed\": 9725,\n    \"Ġdiagnosis\": 9726,\n    \"Ġcart\": 9727,\n    \"Ġassisted\": 9728,\n    \"ĠOrder\": 9729,\n    \"ĠEstate\": 9730,\n    \"Ġintends\": 9731,\n    \"ĠCommon\": 9732,\n    \"Ġadventure\": 9733,\n    \"Ġbeliefs\": 9734,\n    \"Ġlasting\": 9735,\n    \"cel\": 9736,\n    \"Ġdeployment\": 9737,\n    \"tra\": 9738,\n    \"ĠStories\": 9739,\n    \"Ġquote\": 9740,\n    \"Ġfeared\": 9741,\n    \"Ġconvenience\": 9742,\n    \"Ġoptimism\": 9743,\n    \"Ġscientist\": 9744,\n    \"ĠEnterprise\": 9745,\n    \"ĠRex\": 9746,\n    \"ĠFel\": 9747,\n    \"Ġposes\": 9748,\n    \"Ġroot\": 9749,\n    \"Ġevacuation\": 9750,\n    \"Ġpresidents\": 9751,\n    \"ĠRather\": 9752,\n    \"Ġgrave\": 9753,\n    \"ĠHeights\": 9754,\n    \"Ġjumping\": 9755,\n    \"driven\": 9756,\n    \"Ġaluminum\": 9757,\n    \"Ġholders\": 9758,\n    \"Ġboot\": 9759,\n    \"iber\": 9760,\n    \"Ġprecious\": 9761,\n    \"uation\": 9762,\n    \"FP\": 9763,\n    \"uses\": 9764,\n    \"Ġcommentary\": 9765,\n    \"Ġadvances\": 9766,\n    \"ĠNissan\": 9767,\n    \"Ġbronze\": 9768,\n    \"Ġinspire\": 9769,\n    \"Ġstarters\": 9770,\n    \"ĠEvan\": 9771,\n    \"rah\": 9772,\n    \"body\": 9773,\n    \"Ġcrops\": 9774,\n    \"Ġseeds\": 9775,\n    \"Ġharsh\": 9776,\n    \"ĠHomeland\": 9777,\n    \"Ġenabled\": 9778,\n    \"ological\": 9779,\n    \"Ġworkshop\": 9780,\n    \"Ġchains\": 9781,\n    \"amps\": 9782,\n    \"Ġamongst\": 9783,\n    \"ĠBear\": 9784,\n    \"Ġcertified\": 9785,\n    \"ĠJulie\": 9786,\n    \"Ġmountains\": 9787,\n    \"VA\": 9788,\n    \"Ġfed\": 9789,\n    \"Ġbuyer\": 9790,\n    \"ahl\": 9791,\n    \"ĠBos\": 9792,\n    \"ĠCrystal\": 9793,\n    \"Ġquest\": 9794,\n    \"ĠStein\": 9795,\n    \"Ġacceptable\": 9796,\n    \"Ġunbeaten\": 9797,\n    \"iring\": 9798,\n    \"ural\": 9799,\n    \"Ġuncomfortable\": 9800,\n    \"Ġpartial\": 9801,\n    \"Ġsacrifice\": 9802,\n    \"ĠGrande\": 9803,\n    \"Ġarrangement\": 9804,\n    \"Ġpackaging\": 9805,\n    \"screen\": 9806,\n    \"Ġmirror\": 9807,\n    \"Ġsweep\": 9808,\n    \"Ġconnecting\": 9809,\n    \"Ġpanic\": 9810,\n    \"ĠJacksonville\": 9811,\n    \"ĠKremlin\": 9812,\n    \"Ġorigin\": 9813,\n    \"Brien\": 9814,\n    \"Ġnorthwest\": 9815,\n    \"Ġcarriers\": 9816,\n    \"ĠRiley\": 9817,\n    \"Ġaud\": 9818,\n    \"Ġappreciation\": 9819,\n    \"Ġeliminated\": 9820,\n    \"ĠAnalyst\": 9821,\n    \"CR\": 9822,\n    \"Ġfirearm\": 9823,\n    \"Ġaccommodate\": 9824,\n    \"Ġstructural\": 9825,\n    \"Ġappealed\": 9826,\n    \"Ġcharter\": 9827,\n    \"ressing\": 9828,\n    \"Ġalike\": 9829,\n    \"white\": 9830,\n    \"Ġslowdown\": 9831,\n    \"Ġweigh\": 9832,\n    \"ĠPalmer\": 9833,\n    \"ound\": 9834,\n    \"ĠConn\": 9835,\n    \"Ġbranches\": 9836,\n    \"Ġace\": 9837,\n    \"Ġinsists\": 9838,\n    \"yo\": 9839,\n    \"ĠLynn\": 9840,\n    \"ĠCC\": 9841,\n    \"ĠWithin\": 9842,\n    \"Ġcoll\": 9843,\n    \"Ġsustain\": 9844,\n    \"Ġemerge\": 9845,\n    \"ĠBattle\": 9846,\n    \"VER\": 9847,\n    \"Ġaviation\": 9848,\n    \"Ġenables\": 9849,\n    \"ĠProduction\": 9850,\n    \"ĠGrove\": 9851,\n    \"Ġnationally\": 9852,\n    \"ĠBaldwin\": 9853,\n    \"rent\": 9854,\n    \"Ġfirearms\": 9855,\n    \"irm\": 9856,\n    \"Ġconsiders\": 9857,\n    \"ĠCosby\": 9858,\n    \"ĠMcK\": 9859,\n    \"ĠEnt\": 9860,\n    \"Ġincumbent\": 9861,\n    \"iance\": 9862,\n    \"Ġgiants\": 9863,\n    \"Ġkan\": 9864,\n    \"Ġminimal\": 9865,\n    \"ivity\": 9866,\n    \"ĠSay\": 9867,\n    \"ĠNass\": 9868,\n    \"Ġlovely\": 9869,\n    \"ĠFurthermore\": 9870,\n    \"Ġdisplaced\": 9871,\n    \"Ġcontacts\": 9872,\n    \"NY\": 9873,\n    \"Ġtechnological\": 9874,\n    \"ancy\": 9875,\n    \"Ġant\": 9876,\n    \"ope\": 9877,\n    \"ĠFY\": 9878,\n    \"Ġfavorable\": 9879,\n    \"ĠVirgin\": 9880,\n    \"Ġcasual\": 9881,\n    \"ĠLat\": 9882,\n    \"Ġpopulations\": 9883,\n    \"Ġromance\": 9884,\n    \"Ġforgotten\": 9885,\n    \"Ġfleeing\": 9886,\n    \"Ġspecialty\": 9887,\n    \"Ġdrill\": 9888,\n    \"Ġapplying\": 9889,\n    \"Ġcocaine\": 9890,\n    \"rea\": 9891,\n    \"Ġheroin\": 9892,\n    \"Ġsweeping\": 9893,\n    \"ĠMaj\": 9894,\n    \"Ġtroubled\": 9895,\n    \"Ġcolleague\": 9896,\n    \"Ġedged\": 9897,\n    \"omes\": 9898,\n    \"ĠHappy\": 9899,\n    \"Â´\": 9900,\n    \"Ġmilitant\": 9901,\n    \"boy\": 9902,\n    \"aver\": 9903,\n    \"Yes\": 9904,\n    \"llo\": 9905,\n    \"Ġsupporter\": 9906,\n    \"ĠSubscribe\": 9907,\n    \"ĠBird\": 9908,\n    \"ĠGibson\": 9909,\n    \"Ġhill\": 9910,\n    \"Ġnewspapers\": 9911,\n    \"ĠPHOTO\": 9912,\n    \"Ġouting\": 9913,\n    \"Ġdefine\": 9914,\n    \"Ġann\": 9915,\n    \"Ġrobot\": 9916,\n    \"Ġregret\": 9917,\n    \"ĠCould\": 9918,\n    \"raz\": 9919,\n    \"Ġceiling\": 9920,\n    \"Ġorganizers\": 9921,\n    \"ĠTw\": 9922,\n    \"Ġcriticised\": 9923,\n    \"ĠJoh\": 9924,\n    \"ĠJe\": 9925,\n    \"ĠBulls\": 9926,\n    \"Ġteeth\": 9927,\n    \"ĠRanch\": 9928,\n    \"ĠAndrea\": 9929,\n    \"Ġconservatives\": 9930,\n    \"Ġmag\": 9931,\n    \"vey\": 9932,\n    \"Ġpredecessor\": 9933,\n    \"ĠJPMorgan\": 9934,\n    \"Ġdraws\": 9935,\n    \"umber\": 9936,\n    \"Ġvaccine\": 9937,\n    \"ĠDas\": 9938,\n    \"Ġdisappeared\": 9939,\n    \"ĠIron\": 9940,\n    \"Ġlitigation\": 9941,\n    \"vert\": 9942,\n    \"Ġbelong\": 9943,\n    \"ĠRet\": 9944,\n    \"owers\": 9945,\n    \"rain\": 9946,\n    \"controlled\": 9947,\n    \"ĠKil\": 9948,\n    \"Ġrehab\": 9949,\n    \"ĠAustria\": 9950,\n    \"Ġprivilege\": 9951,\n    \"Ġbounce\": 9952,\n    \"Ġbout\": 9953,\n    \"ĠIslamist\": 9954,\n    \"Ġtaxi\": 9955,\n    \"ody\": 9956,\n    \".'\\\"\": 9957,\n    \"Ġdos\": 9958,\n    \"shire\": 9959,\n    \"Ġaccidents\": 9960,\n    \"Ġdemonstration\": 9961,\n    \"His\": 9962,\n    \"ĠBO\": 9963,\n    \"ĠICE\": 9964,\n    \"van\": 9965,\n    \"File\": 9966,\n    \"ĠManning\": 9967,\n    \"ounded\": 9968,\n    \"Ġdirections\": 9969,\n    \"lled\": 9970,\n    \"Ġoffences\": 9971,\n    \"Ġlaptop\": 9972,\n    \"ĠUniversal\": 9973,\n    \"Ġmilestone\": 9974,\n    \"ĠNarendra\": 9975,\n    \"Ġnotion\": 9976,\n    \"Ġuns\": 9977,\n    \"ĠLower\": 9978,\n    \"Ġmidfield\": 9979,\n    \"Ġoutper\": 9980,\n    \"trans\": 9981,\n    \"ĠJa\": 9982,\n    \"three\": 9983,\n    \"Adds\": 9984,\n    \"Ġpressures\": 9985,\n    \"Ġprohibited\": 9986,\n    \"Ġutilities\": 9987,\n    \"Ġbes\": 9988,\n    \"ĠReporter\": 9989,\n    \"Ġcommodities\": 9990,\n    \"leton\": 9991,\n    \"Ġslower\": 9992,\n    \"EE\": 9993,\n    \"auer\": 9994,\n    \"Ġtablet\": 9995,\n    \"sl\": 9996,\n    \"iously\": 9997,\n    \"Ġaiming\": 9998,\n    \"eland\": 9999,\n    \"ĠNEXT\": 10000,\n    \"tered\": 10001,\n    \"IVE\": 10002,\n    \"onic\": 10003,\n    \"May\": 10004,\n    \"ĠMilitary\": 10005,\n    \"Mark\": 10006,\n    \"Ġlender\": 10007,\n    \"mate\": 10008,\n    \"Ġaboard\": 10009,\n    \"they\": 10010,\n    \"Ġrespondents\": 10011,\n    \"Ġconversion\": 10012,\n    \"Ġsecuring\": 10013,\n    \"Ġentity\": 10014,\n    \"ĠHarbor\": 10015,\n    \"ĠCu\": 10016,\n    \"Ġcats\": 10017,\n    \"ĠACC\": 10018,\n    \"ĠIbrahim\": 10019,\n    \"GL\": 10020,\n    \"Ġinvitation\": 10021,\n    \"Ġcond\": 10022,\n    \"ĠRecords\": 10023,\n    \"ĠAdrian\": 10024,\n    \"Ġbrave\": 10025,\n    \"Ġmineral\": 10026,\n    \"Ġsooner\": 10027,\n    \"Ġsatisfied\": 10028,\n    \"Ġpets\": 10029,\n    \"Ġnotably\": 10030,\n    \"Ä±\": 10031,\n    \"Ġmarking\": 10032,\n    \"ĠRO\": 10033,\n    \"ĠHaw\": 10034,\n    \"ĠVis\": 10035,\n    \"Ġmarketplace\": 10036,\n    \"ĠNat\": 10037,\n    \"ĠForward\": 10038,\n    \"ĠLeft\": 10039,\n    \"Ġaggravated\": 10040,\n    \"ĠClose\": 10041,\n    \"acey\": 10042,\n    \"Ġlandmark\": 10043,\n    \"Ġdisruption\": 10044,\n    \"ĠChallenge\": 10045,\n    \"ĠDays\": 10046,\n    \"ĠCoun\": 10047,\n    \"ahan\": 10048,\n    \"Ġaides\": 10049,\n    \"South\": 10050,\n    \"ĠDylan\": 10051,\n    \"ĠRavens\": 10052,\n    \"ĠNature\": 10053,\n    \"lli\": 10054,\n    \"Ġdiplomats\": 10055,\n    \"350\": 10056,\n    \"ĠDrake\": 10057,\n    \"tag\": 10058,\n    \"Ġlicensed\": 10059,\n    \"ĠDenmark\": 10060,\n    \"Ġcancel\": 10061,\n    \"Ġinstant\": 10062,\n    \"DI\": 10063,\n    \"Ġpunch\": 10064,\n    \"ĠJenkins\": 10065,\n    \"Ġstrengthening\": 10066,\n    \"des\": 10067,\n    \"-$\": 10068,\n    \"Ġallegation\": 10069,\n    \"Ġsizes\": 10070,\n    \"iza\": 10071,\n    \"Ġmentally\": 10072,\n    \"ĠResidents\": 10073,\n    \"acked\": 10074,\n    \"Ġsensors\": 10075,\n    \",'\\\"\": 10076,\n    \"illion\": 10077,\n    \"ĠChampion\": 10078,\n    \"Ġexcessive\": 10079,\n    \"Ġhum\": 10080,\n    \"ĠComp\": 10081,\n    \"rend\": 10082,\n    \"ĠLakes\": 10083,\n    \"Ġburst\": 10084,\n    \"Ġtrainer\": 10085,\n    \"Ġclearing\": 10086,\n    \"ĠSilicon\": 10087,\n    \"Ġ350\": 10088,\n    \"DE\": 10089,\n    \"ĠGates\": 10090,\n    \"ĠHorn\": 10091,\n    \"ests\": 10092,\n    \"ĠCourtesy\": 10093,\n    \"Ġbipartisan\": 10094,\n    \"Ġhabits\": 10095,\n    \"ĠAlexa\": 10096,\n    \"walk\": 10097,\n    \"Ġsnapped\": 10098,\n    \"ĠEight\": 10099,\n    \"itis\": 10100,\n    \"zel\": 10101,\n    \"Ġcustoms\": 10102,\n    \"Ġsouthwest\": 10103,\n    \"Ġvary\": 10104,\n    \"Because\": 10105,\n    \"Ġpayout\": 10106,\n    \"Ġaccelerate\": 10107,\n    \"ĠBarr\": 10108,\n    \"tu\": 10109,\n    \"Ġfined\": 10110,\n    \"cost\": 10111,\n    \"ĠTheater\": 10112,\n    \"ĠCorbyn\": 10113,\n    \"Ġstem\": 10114,\n    \"Ġundermine\": 10115,\n    \".;\": 10116,\n    \"Ġstays\": 10117,\n    \"Ġbreakthrough\": 10118,\n    \"Ġturnover\": 10119,\n    \"hot\": 10120,\n    \"Ġtriumph\": 10121,\n    \"Ġpainted\": 10122,\n    \"ĠWinnipeg\": 10123,\n    \"ĠKas\": 10124,\n    \"ĠStuart\": 10125,\n    \"irk\": 10126,\n    \"Am\": 10127,\n    \"Ġtrusted\": 10128,\n    \"aze\": 10129,\n    \"ĠLate\": 10130,\n    \"Ġaccessories\": 10131,\n    \"Ġmemorable\": 10132,\n    \"ĠFool\": 10133,\n    \"Ġrotation\": 10134,\n    \"ĠBulldogs\": 10135,\n    \"ĠChen\": 10136,\n    \"Ġpoised\": 10137,\n    \"ĠMonte\": 10138,\n    \"ĠClarke\": 10139,\n    \"leading\": 10140,\n    \"Ġvenues\": 10141,\n    \"Ġbeneficial\": 10142,\n    \"ĠLiam\": 10143,\n    \"ĠBrothers\": 10144,\n    \"ĠNeed\": 10145,\n    \"Ġconc\": 10146,\n    \"olly\": 10147,\n    \"ĠJulian\": 10148,\n    \"ogue\": 10149,\n    \"Ġfounding\": 10150,\n    \"Ġsidelines\": 10151,\n    \"Ġdeclare\": 10152,\n    \"ĠMember\": 10153,\n    \"Ġexamine\": 10154,\n    \"abs\": 10155,\n    \"Ġboundaries\": 10156,\n    \"ĠBrisbane\": 10157,\n    \"Ġlaunches\": 10158,\n    \"lor\": 10159,\n    \"ĠGa\": 10160,\n    \"Ġthr\": 10161,\n    \"expected\": 10162,\n    \"wal\": 10163,\n    \"ĠBarnes\": 10164,\n    \"Ġclashes\": 10165,\n    \"content\": 10166,\n    \"ĠClemson\": 10167,\n    \"iger\": 10168,\n    \"Mar\": 10169,\n    \"Ġaccord\": 10170,\n    \"Ġsoutheast\": 10171,\n    \"ģ\": 10172,\n    \"ĠStarbucks\": 10173,\n    \"osing\": 10174,\n    \"Ġseasonal\": 10175,\n    \"icking\": 10176,\n    \"Ġloyalty\": 10177,\n    \"Ġtent\": 10178,\n    \"ĠDy\": 10179,\n    \"Ġevident\": 10180,\n    \"Ġlobby\": 10181,\n    \"Ġtours\": 10182,\n    \"Ġbombing\": 10183,\n    \"uations\": 10184,\n    \"Ġrises\": 10185,\n    \"Ġdemonstrations\": 10186,\n    \"ĠWATCH\": 10187,\n    \"pin\": 10188,\n    \"Ġdeb\": 10189,\n    \"ĠDraft\": 10190,\n    \"rog\": 10191,\n    \"Ġseal\": 10192,\n    \"ĠPerformance\": 10193,\n    \"ĠLGBT\": 10194,\n    \"Ġsed\": 10195,\n    \"Ġgig\": 10196,\n    \"nan\": 10197,\n    \"Ġrainfall\": 10198,\n    \"Ġfabric\": 10199,\n    \"Ġmanages\": 10200,\n    \"Ġlifting\": 10201,\n    \"ĠMagazine\": 10202,\n    \"ĠCriminal\": 10203,\n    \"Ġhikes\": 10204,\n    \"Ġcatching\": 10205,\n    \"Ġ1989\": 10206,\n    \"OG\": 10207,\n    \"Ġdisappointment\": 10208,\n    \"Ġir\": 10209,\n    \"ĠEV\": 10210,\n    \"stown\": 10211,\n    \"pass\": 10212,\n    \"120\": 10213,\n    \"Ġmedals\": 10214,\n    \"ĠSimmons\": 10215,\n    \"Ġinaugural\": 10216,\n    \"ĠCorn\": 10217,\n    \"Ġmotorcycle\": 10218,\n    \"lets\": 10219,\n    \"ĠSkype\": 10220,\n    \"Ã©t\": 10221,\n    \"Ġscary\": 10222,\n    \"opp\": 10223,\n    \"thirds\": 10224,\n    \"ĠMohamed\": 10225,\n    \"Ġteenagers\": 10226,\n    \"ANK\": 10227,\n    \"Ġserver\": 10228,\n    \"Ġouts\": 10229,\n    \"Ġdishes\": 10230,\n    \"four\": 10231,\n    \"dr\": 10232,\n    \"ĠOt\": 10233,\n    \"ĠSandy\": 10234,\n    \"ĠShane\": 10235,\n    \"orters\": 10236,\n    \"SH\": 10237,\n    \"Ġtouching\": 10238,\n    \"ĠNike\": 10239,\n    \"ĠHBO\": 10240,\n    \"driving\": 10241,\n    \"Ġplug\": 10242,\n    \"ĠBaseball\": 10243,\n    \"eling\": 10244,\n    \"hn\": 10245,\n    \"ulate\": 10246,\n    \"eed\": 10247,\n    \"ĠChristine\": 10248,\n    \"ĠGlobe\": 10249,\n    \"Ġethics\": 10250,\n    \"ĠTrevor\": 10251,\n    \"iya\": 10252,\n    \"Ġ360\": 10253,\n    \"Ġawaiting\": 10254,\n    \"Ġcounterpart\": 10255,\n    \"Ġsubsidies\": 10256,\n    \"pointers\": 10257,\n    \"Ġspy\": 10258,\n    \"ILL\": 10259,\n    \"Ġtakeover\": 10260,\n    \"ĠBeyond\": 10261,\n    \"Ġsurprisingly\": 10262,\n    \"TION\": 10263,\n    \"ĠSong\": 10264,\n    \"Ġni\": 10265,\n    \"Ġcommonly\": 10266,\n    \"Ġjack\": 10267,\n    \"Ġsubstitute\": 10268,\n    \"ews\": 10269,\n    \"Ġrecalls\": 10270,\n    \"ĠCommons\": 10271,\n    \"Ġsin\": 10272,\n    \"del\": 10273,\n    \"ĠMod\": 10274,\n    \"Ġpressing\": 10275,\n    \"ĠTelevision\": 10276,\n    \"ĠInside\": 10277,\n    \"ª\": 10278,\n    \"Ġbacklash\": 10279,\n    \"Ġcredible\": 10280,\n    \"ĠJenner\": 10281,\n    \"ĠPu\": 10282,\n    \"ĠStevens\": 10283,\n    \"ĠWE\": 10284,\n    \"Last\": 10285,\n    \"Ġinsurers\": 10286,\n    \"ĠJoin\": 10287,\n    \"bled\": 10288,\n    \"digit\": 10289,\n    \"Ġflooded\": 10290,\n    \"ĠShore\": 10291,\n    \"ĠTrophy\": 10292,\n    \"zing\": 10293,\n    \"ĠImmigration\": 10294,\n    \"Ġsuperior\": 10295,\n    \"IAN\": 10296,\n    \"Ġcasino\": 10297,\n    \"Ġenabling\": 10298,\n    \"Ġmeantime\": 10299,\n    \"Ġperformers\": 10300,\n    \"Ġproportion\": 10301,\n    \"Ġlawmaker\": 10302,\n    \"ĠConf\": 10303,\n    \"Ġconvert\": 10304,\n    \"Ġfarmer\": 10305,\n    \"Ġbu\": 10306,\n    \"ĠGE\": 10307,\n    \"ĠRepresentative\": 10308,\n    \"ĠBannon\": 10309,\n    \"ĠHelp\": 10310,\n    \"PT\": 10311,\n    \"formed\": 10312,\n    \"ĠSuperintendent\": 10313,\n    \"Ġfrustrating\": 10314,\n    \"ĠRegister\": 10315,\n    \"ĠPolitical\": 10316,\n    \"Ġboots\": 10317,\n    \"ĠRu\": 10318,\n    \"ĠSha\": 10319,\n    \"Ġinstrument\": 10320,\n    \"tor\": 10321,\n    \"ĠBelt\": 10322,\n    \"ĠWalsh\": 10323,\n    \"Ġrecipe\": 10324,\n    \"ilt\": 10325,\n    \"ĠClean\": 10326,\n    \"iors\": 10327,\n    \"Ġtwenty\": 10328,\n    \"iler\": 10329,\n    \"nder\": 10330,\n    \"Ġwinger\": 10331,\n    \"Ġwheat\": 10332,\n    \"ĠAviation\": 10333,\n    \"Ġcorrupt\": 10334,\n    \"Ġconnectivity\": 10335,\n    \"ĠVen\": 10336,\n    \"order\": 10337,\n    \"esc\": 10338,\n    \"break\": 10339,\n    \"Ġmetals\": 10340,\n    \"Ġtraditionally\": 10341,\n    \"Ġbell\": 10342,\n    \"Ġviolating\": 10343,\n    \"rough\": 10344,\n    \"Ġintroducing\": 10345,\n    \"Ġguided\": 10346,\n    \"ĠMol\": 10347,\n    \"Ġdesert\": 10348,\n    \"ĠBree\": 10349,\n    \"Le\": 10350,\n    \"ĠZone\": 10351,\n    \"ĠGlass\": 10352,\n    \"ĠEUR\": 10353,\n    \"ĠYahoo\": 10354,\n    \"Ġlaps\": 10355,\n    \"Ġdiffer\": 10356,\n    \"ĠHold\": 10357,\n    \"Ġtimely\": 10358,\n    \"Ġsuccessor\": 10359,\n    \"Ġcomic\": 10360,\n    \"Ġbears\": 10361,\n    \"Ġlicence\": 10362,\n    \"Ġreject\": 10363,\n    \"Ġsophisticated\": 10364,\n    \"Too\": 10365,\n    \"Ġobjectives\": 10366,\n    \"ĠId\": 10367,\n    \"urers\": 10368,\n    \"Ġraid\": 10369,\n    \"COM\": 10370,\n    \"Ġelect\": 10371,\n    \"ĠHampshire\": 10372,\n    \"Ġlens\": 10373,\n    \"Ġdesigners\": 10374,\n    \"Ġpresently\": 10375,\n    \"ĠRCMP\": 10376,\n    \"ĠEgyptian\": 10377,\n    \"ĠWalter\": 10378,\n    \"ĠWallace\": 10379,\n    \"Ġ2025\": 10380,\n    \"utics\": 10381,\n    \"ried\": 10382,\n    \"Ġrefuse\": 10383,\n    \"Ġsiblings\": 10384,\n    \"ĠNothing\": 10385,\n    \"Ġdressing\": 10386,\n    \"Ġnerve\": 10387,\n    \"AST\": 10388,\n    \"Ġuncertainties\": 10389,\n    \"Ġtale\": 10390,\n    \"ĠTalk\": 10391,\n    \"Ġissuing\": 10392,\n    \"shot\": 10393,\n    \"ĠTak\": 10394,\n    \"Ġacid\": 10395,\n    \"ĠNintendo\": 10396,\n    \"Ġwash\": 10397,\n    \"pd\": 10398,\n    \"ĠClaire\": 10399,\n    \"ĠScot\": 10400,\n    \"Ġsuits\": 10401,\n    \"ĠBayern\": 10402,\n    \"gest\": 10403,\n    \"Ġapplicable\": 10404,\n    \"Ġinteraction\": 10405,\n    \"ĠEnforcement\": 10406,\n    \"ĠRohingya\": 10407,\n    \"Ġjan\": 10408,\n    \"Ġunited\": 10409,\n    \"ĠCoalition\": 10410,\n    \"Ġlegislators\": 10411,\n    \"Ġdetectives\": 10412,\n    \"ĠSing\": 10413,\n    \"ĠBetween\": 10414,\n    \"ĠPoly\": 10415,\n    \"pool\": 10416,\n    \"mal\": 10417,\n    \"Ġreply\": 10418,\n    \"Ġschemes\": 10419,\n    \"ĠHolmes\": 10420,\n    \"ĠSenators\": 10421,\n    \"ĠVerizon\": 10422,\n    \"Ġwelcoming\": 10423,\n    \"ĠCricket\": 10424,\n    \"ĠMarco\": 10425,\n    \"ĠYears\": 10426,\n    \"ĠLiving\": 10427,\n    \"Ġcounterparts\": 10428,\n    \"ĠParadise\": 10429,\n    \"ĠTrad\": 10430,\n    \"#\": 10431,\n    \"iw\": 10432,\n    \"ĠSoccer\": 10433,\n    \"umbled\": 10434,\n    \"Ġdeceased\": 10435,\n    \"heim\": 10436,\n    \"Ġevaluation\": 10437,\n    \"Ġwrap\": 10438,\n    \"Ġmild\": 10439,\n    \"aji\": 10440,\n    \"ĠUCLA\": 10441,\n    \"ĠNative\": 10442,\n    \"president\": 10443,\n    \"ĠXbox\": 10444,\n    \"Ġenterprises\": 10445,\n    \"ĠSlam\": 10446,\n    \"oga\": 10447,\n    \"Rock\": 10448,\n    \"piece\": 10449,\n    \"ĠColeman\": 10450,\n    \"Ġcomparable\": 10451,\n    \"uba\": 10452,\n    \"Ġprovinces\": 10453,\n    \"ĠFormula\": 10454,\n    \"ipt\": 10455,\n    \"Ã´\": 10456,\n    \"Ġtick\": 10457,\n    \"ĠIMF\": 10458,\n    \"anch\": 10459,\n    \"atta\": 10460,\n    \"rew\": 10461,\n    \"However\": 10462,\n    \"LS\": 10463,\n    \"etta\": 10464,\n    \"ĠCustoms\": 10465,\n    \"SU\": 10466,\n    \"Ġpublishing\": 10467,\n    \"Ġinch\": 10468,\n    \"Ġkills\": 10469,\n    \"¤\": 10470,\n    \"ĠSus\": 10471,\n    \"ĠBeth\": 10472,\n    \"Ġsteam\": 10473,\n    \"jpg\": 10474,\n    \"pointer\": 10475,\n    \"Ġturnovers\": 10476,\n    \"Ġpowder\": 10477,\n    \"ĠUSB\": 10478,\n    \"ĠWildlife\": 10479,\n    \"ĠDirect\": 10480,\n    \"atively\": 10481,\n    \"ĠFerrari\": 10482,\n    \"Ġpleasure\": 10483,\n    \"ĠMatthews\": 10484,\n    \"Ġski\": 10485,\n    \"ography\": 10486,\n    \"ĠVermont\": 10487,\n    \"ĠMargaret\": 10488,\n    \"ĠMunich\": 10489,\n    \"Ġlayer\": 10490,\n    \"ĠProperty\": 10491,\n    \"Ġeconomics\": 10492,\n    \"ĠCrew\": 10493,\n    \"UK\": 10494,\n    \"Ġunnecessary\": 10495,\n    \"ĠGlasgow\": 10496,\n    \"Ġsealed\": 10497,\n    \"Ġclarity\": 10498,\n    \"Ġsurplus\": 10499,\n    \"ĠCanyon\": 10500,\n    \"ĠApart\": 10501,\n    \"Ġacceptance\": 10502,\n    \"ĠEllis\": 10503,\n    \"uster\": 10504,\n    \"rid\": 10505,\n    \"ĠHawks\": 10506,\n    \"Ġstatewide\": 10507,\n    \"Ġthreaten\": 10508,\n    \"ĠJail\": 10509,\n    \"Ġinclusive\": 10510,\n    \"Ġmud\": 10511,\n    \"Ġpat\": 10512,\n    \"Ġbitter\": 10513,\n    \"Ġalternatives\": 10514,\n    \"Ġaffiliate\": 10515,\n    \"Ġevaluate\": 10516,\n    \"ĠBaby\": 10517,\n    \"Ġperception\": 10518,\n    \"tim\": 10519,\n    \"Ġrefusing\": 10520,\n    \"Ġgrey\": 10521,\n    \"Ġarguably\": 10522,\n    \"Ġfirmly\": 10523,\n    \"ĠDark\": 10524,\n    \"Ġexcuse\": 10525,\n    \"ĠRaymond\": 10526,\n    \"Ġballots\": 10527,\n    \"inton\": 10528,\n    \"Ġ125\": 10529,\n    \"ĠCatherine\": 10530,\n    \"Ġsacks\": 10531,\n    \"ĠDeb\": 10532,\n    \"Ġworkout\": 10533,\n    \"web\": 10534,\n    \"Ġbatteries\": 10535,\n    \"breaking\": 10536,\n    \"ML\": 10537,\n    \"Ġunacceptable\": 10538,\n    \"ĠValentine\": 10539,\n    \"ĠYOU\": 10540,\n    \"ĠRT\": 10541,\n    \"Ġjurisdiction\": 10542,\n    \"Ġexamined\": 10543,\n    \"strom\": 10544,\n    \"ĠPocket\": 10545,\n    \"Ġcement\": 10546,\n    \"Ġuniversal\": 10547,\n    \"ĠOz\": 10548,\n    \"Ġkit\": 10549,\n    \"Ġchurches\": 10550,\n    \"Ġsuburban\": 10551,\n    \"ĠKushner\": 10552,\n    \"ĠDavidson\": 10553,\n    \"Sports\": 10554,\n    \"email\": 10555,\n    \"Ġrealistic\": 10556,\n    \"Ġintend\": 10557,\n    \"ĠGrey\": 10558,\n    \",''\": 10559,\n    \"Ġscholarship\": 10560,\n    \"Ġphilosophy\": 10561,\n    \"Ġwheels\": 10562,\n    \"Ġmotivation\": 10563,\n    \"eway\": 10564,\n    \"match\": 10565,\n    \"ĠDate\": 10566,\n    \"John\": 10567,\n    \"Ġcontrolling\": 10568,\n    \"750\": 10569,\n    \"aven\": 10570,\n    \"Ġfilmed\": 10571,\n    \"Ġ160\": 10572,\n    \"ĠBrock\": 10573,\n    \"ĠDetails\": 10574,\n    \"Ġlogistics\": 10575,\n    \"Ġassumptions\": 10576,\n    \"ĠStep\": 10577,\n    \"Ġfails\": 10578,\n    \"ĠNotre\": 10579,\n    \"Ġjuice\": 10580,\n    \"Ġcounting\": 10581,\n    \"Ġphotograph\": 10582,\n    \"Ġfortunate\": 10583,\n    \"Ġestablishing\": 10584,\n    \"ĠNJ\": 10585,\n    \"ĠWorkers\": 10586,\n    \"ĠQuinn\": 10587,\n    \"ĠHeather\": 10588,\n    \"Ġtimeline\": 10589,\n    \"Ġimported\": 10590,\n    \"ĠNASCAR\": 10591,\n    \"Ġexercises\": 10592,\n    \"Ġsearched\": 10593,\n    \"ĠRalph\": 10594,\n    \"alf\": 10595,\n    \"Ġgene\": 10596,\n    \"Ġdependent\": 10597,\n    \"Ã©n\": 10598,\n    \"iate\": 10599,\n    \"ĠBristol\": 10600,\n    \"Ġhung\": 10601,\n    \"Ġtropical\": 10602,\n    \"Ġintensity\": 10603,\n    \"ĠIdaho\": 10604,\n    \"ĠMull\": 10605,\n    \"Ġsuite\": 10606,\n    \"Ġblockchain\": 10607,\n    \"cz\": 10608,\n    \"ovich\": 10609,\n    \"Ġworn\": 10610,\n    \"ĠLE\": 10611,\n    \"AV\": 10612,\n    \"emi\": 10613,\n    \"Ġidentification\": 10614,\n    \"Ġtunnel\": 10615,\n    \"ĠARE\": 10616,\n    \"ĠArm\": 10617,\n    \"Ġoutrage\": 10618,\n    \"Ġtwist\": 10619,\n    \"uka\": 10620,\n    \"ĠGra\": 10621,\n    \"Ġjets\": 10622,\n    \"ĠThus\": 10623,\n    \"Ġcompound\": 10624,\n    \"Ġfinancially\": 10625,\n    \"2019\": 10626,\n    \"asse\": 10627,\n    \"Ġspare\": 10628,\n    \"ĠNoah\": 10629,\n    \"ĠMade\": 10630,\n    \"ĠMom\": 10631,\n    \"Ġphenomenon\": 10632,\n    \"Ġnurses\": 10633,\n    \"Ġoutlined\": 10634,\n    \"Ġpolit\": 10635,\n    \"ĠCarm\": 10636,\n    \"Ġleagues\": 10637,\n    \"Ġmath\": 10638,\n    \"Ġmodified\": 10639,\n    \"Ġwillingness\": 10640,\n    \"ĠAmanda\": 10641,\n    \"Ġgrandfather\": 10642,\n    \"Of\": 10643,\n    \"DR\": 10644,\n    \"Ġdip\": 10645,\n    \"ĠRAM\": 10646,\n    \"ĠChristie\": 10647,\n    \"Ġargues\": 10648,\n    \"ĠEX\": 10649,\n    \"ĠNine\": 10650,\n    \"ĠScroll\": 10651,\n    \"ĠTHIS\": 10652,\n    \"Pro\": 10653,\n    \"Ġkeys\": 10654,\n    \"Ġprocessor\": 10655,\n    \"Ġscam\": 10656,\n    \"ĠTraining\": 10657,\n    \"Ġhoney\": 10658,\n    \"Ĵ\": 10659,\n    \"Ġfacebook\": 10660,\n    \"ĠLegal\": 10661,\n    \"Ġaging\": 10662,\n    \"Ġspiritual\": 10663,\n    \"ĠHost\": 10664,\n    \"Ġlung\": 10665,\n    \"ĠUSC\": 10666,\n    \"Ġdirt\": 10667,\n    \"Ġfe\": 10668,\n    \"after\": 10669,\n    \"ĠDiana\": 10670,\n    \"Ġounce\": 10671,\n    \"date\": 10672,\n    \"ĠFinals\": 10673,\n    \"Ķ\": 10674,\n    \"Ġthorough\": 10675,\n    \"Ġviable\": 10676,\n    \"Ġanytime\": 10677,\n    \"Ġfost\": 10678,\n    \"orter\": 10679,\n    \"ware\": 10680,\n    \"ĠHolland\": 10681,\n    \"ĠMand\": 10682,\n    \"ĠSend\": 10683,\n    \"2013\": 10684,\n    \"ĠVolkswagen\": 10685,\n    \"Ġsuitable\": 10686,\n    \"ifies\": 10687,\n    \"Ġcomedian\": 10688,\n    \"Ġneighbours\": 10689,\n    \"ĠKnow\": 10690,\n    \"Ġcurious\": 10691,\n    \"ĠTwenty\": 10692,\n    \"ĠPrevention\": 10693,\n    \"ĠStephanie\": 10694,\n    \"Ġpilots\": 10695,\n    \"Ġstored\": 10696,\n    \"Ġdire\": 10697,\n    \"Ġfits\": 10698,\n    \"ision\": 10699,\n    \"ĠShell\": 10700,\n    \"Ġshifts\": 10701,\n    \"Ġpepper\": 10702,\n    \"Ġattendees\": 10703,\n    \"ĠName\": 10704,\n    \"hers\": 10705,\n    \"rip\": 10706,\n    \"Ġwatchdog\": 10707,\n    \"andy\": 10708,\n    \"Ġbio\": 10709,\n    \"Ġpublisher\": 10710,\n    \"powered\": 10711,\n    \"ĠCM\": 10712,\n    \"rian\": 10713,\n    \"ĠRand\": 10714,\n    \"wise\": 10715,\n    \"ĠJesse\": 10716,\n    \"Ġladies\": 10717,\n    \"ĠMetropolitan\": 10718,\n    \"ĠMicro\": 10719,\n    \"Ġkicking\": 10720,\n    \"Ġmeg\": 10721,\n    \"Ġclouds\": 10722,\n    \"Ġtrim\": 10723,\n    \"wear\": 10724,\n    \"ĠML\": 10725,\n    \"Ġconsists\": 10726,\n    \"Ġrig\": 10727,\n    \"Ġhonestly\": 10728,\n    \"GS\": 10729,\n    \"ĠNicholas\": 10730,\n    \"Ġcope\": 10731,\n    \"Ġpublish\": 10732,\n    \"working\": 10733,\n    \"bur\": 10734,\n    \"ĠNar\": 10735,\n    \"olds\": 10736,\n    \"aja\": 10737,\n    \"ĠSad\": 10738,\n    \"Ġclicking\": 10739,\n    \"Ġbids\": 10740,\n    \"ĠZuckerberg\": 10741,\n    \"Ġ900\": 10742,\n    \"Ġexam\": 10743,\n    \"ivers\": 10744,\n    \"Ġpray\": 10745,\n    \"Ġreader\": 10746,\n    \"ĠSeth\": 10747,\n    \"inem\": 10748,\n    \"Ġconfront\": 10749,\n    \"stra\": 10750,\n    \"AW\": 10751,\n    \"ĠGian\": 10752,\n    \"Ġaccordance\": 10753,\n    \"Ġinteract\": 10754,\n    \"ĠSharks\": 10755,\n    \"Ġfireworks\": 10756,\n    \"gment\": 10757,\n    \"illy\": 10758,\n    \"Ġconst\": 10759,\n    \"ARY\": 10760,\n    \"Ġprizes\": 10761,\n    \"Ġshoulders\": 10762,\n    \"Ġaccessed\": 10763,\n    \"Ġecosystem\": 10764,\n    \"Ġlicensing\": 10765,\n    \"La\": 10766,\n    \"Ġdedication\": 10767,\n    \"ĠdÃ©\": 10768,\n    \"Ġyouths\": 10769,\n    \"lem\": 10770,\n    \"Ġtoy\": 10771,\n    \"ĠProm\": 10772,\n    \"ounding\": 10773,\n    \"rod\": 10774,\n    \"Ġ1000\": 10775,\n    \"ishes\": 10776,\n    \"Over\": 10777,\n    \"Ġgaps\": 10778,\n    \"Ġmissions\": 10779,\n    \"Ġrailway\": 10780,\n    \"Day\": 10781,\n    \"orp\": 10782,\n    \"ĠSchumer\": 10783,\n    \"Ġeclipse\": 10784,\n    \"Ġshell\": 10785,\n    \"ĠBY\": 10786,\n    \"Many\": 10787,\n    \"ĠRecord\": 10788,\n    \"Ġdrunk\": 10789,\n    \"ayan\": 10790,\n    \"Ġsuggestion\": 10791,\n    \"Ġdefenders\": 10792,\n    \"ĠNewton\": 10793,\n    \"Ġdisputes\": 10794,\n    \"Ġevolution\": 10795,\n    \"Ġcredibility\": 10796,\n    \"ĠTenn\": 10797,\n    \"Ġplain\": 10798,\n    \"size\": 10799,\n    \"cont\": 10800,\n    \"Ġlone\": 10801,\n    \"Ġfingers\": 10802,\n    \"BUR\": 10803,\n    \"ĠInvestigation\": 10804,\n    \"ĠQualcomm\": 10805,\n    \"var\": 10806,\n    \"Ġcountless\": 10807,\n    \"ĠRebecca\": 10808,\n    \"½\": 10809,\n    \"abi\": 10810,\n    \"Ġreflecting\": 10811,\n    \"ĠTurn\": 10812,\n    \"Ġinteractive\": 10813,\n    \"Ġincentive\": 10814,\n    \"second\": 10815,\n    \"offs\": 10816,\n    \"ĠBerkeley\": 10817,\n    \"ĠTexans\": 10818,\n    \"Ġheated\": 10819,\n    \"Ġscorer\": 10820,\n    \"ĠSharif\": 10821,\n    \"Ġmigrant\": 10822,\n    \"west\": 10823,\n    \"ĠHoliday\": 10824,\n    \"Ġwrist\": 10825,\n    \"Ġchairs\": 10826,\n    \"Ġrecommends\": 10827,\n    \"ĠWildcats\": 10828,\n    \"ĠPed\": 10829,\n    \"ĠQuarter\": 10830,\n    \"ĠIV\": 10831,\n    \"ĠArch\": 10832,\n    \"Ġstandings\": 10833,\n    \"Ġbombs\": 10834,\n    \"Ġcapped\": 10835,\n    \"Can\": 10836,\n    \"Ġcaring\": 10837,\n    \"ĠLah\": 10838,\n    \"lim\": 10839,\n    \"Ġdragged\": 10840,\n    \"ĠBeat\": 10841,\n    \"DB\": 10842,\n    \"Ġaired\": 10843,\n    \"Ġjeans\": 10844,\n    \"action\": 10845,\n    \"Ġgenerating\": 10846,\n    \"ĠGir\": 10847,\n    \"risk\": 10848,\n    \"lon\": 10849,\n    \"stage\": 10850,\n    \"âĤ¬\": 10851,\n    \"earing\": 10852,\n    \"ĠTogether\": 10853,\n    \"Ġreun\": 10854,\n    \"ĠCorey\": 10855,\n    \"ĠBak\": 10856,\n    \"Ġprestigious\": 10857,\n    \"Ġapplicants\": 10858,\n    \"here\": 10859,\n    \"ĠMattis\": 10860,\n    \"Ġridiculous\": 10861,\n    \"ĠLess\": 10862,\n    \"Ġrains\": 10863,\n    \"Ġpresenting\": 10864,\n    \"anti\": 10865,\n    \"Ġdisabilities\": 10866,\n    \"Ġapartments\": 10867,\n    \"storm\": 10868,\n    \"ĠHem\": 10869,\n    \"Ġhabit\": 10870,\n    \"ĠRuth\": 10871,\n    \"ĠNPR\": 10872,\n    \"nut\": 10873,\n    \"Ġappreciated\": 10874,\n    \"Ġseparation\": 10875,\n    \"uda\": 10876,\n    \"Ġminus\": 10877,\n    \"ĠPhotos\": 10878,\n    \"Ġblew\": 10879,\n    \"ĠVoice\": 10880,\n    \"Ġrallies\": 10881,\n    \"Ġfond\": 10882,\n    \"ĠTaking\": 10883,\n    \"yt\": 10884,\n    \"FE\": 10885,\n    \"ĠTory\": 10886,\n    \"ressed\": 10887,\n    \"ĠLy\": 10888,\n    \"Ġrocks\": 10889,\n    \"ĠRah\": 10890,\n    \"Ġelementary\": 10891,\n    \"nis\": 10892,\n    \"ĠPresidential\": 10893,\n    \"Ġnutrition\": 10894,\n    \"Ġbaseman\": 10895,\n    \"Ġsuperstar\": 10896,\n    \"ĠWa\": 10897,\n    \"lar\": 10898,\n    \"Ġstaged\": 10899,\n    \"ĠLearn\": 10900,\n    \"Ġbroadcaster\": 10901,\n    \"Ġboasts\": 10902,\n    \"Ġdoubts\": 10903,\n    \"rum\": 10904,\n    \"Ġbare\": 10905,\n    \"cap\": 10906,\n    \"Ġclimbing\": 10907,\n    \"ĠSelect\": 10908,\n    \"ĠCant\": 10909,\n    \"ĠNord\": 10910,\n    \"ĠBeck\": 10911,\n    \"ĠKad\": 10912,\n    \"ello\": 10913,\n    \"Ġenforce\": 10914,\n    \"ĠZe\": 10915,\n    \"ked\": 10916,\n    \"elly\": 10917,\n    \"ĠLED\": 10918,\n    \"ĠOperations\": 10919,\n    \"ĠLuk\": 10920,\n    \"Ġcertificate\": 10921,\n    \"Ġdeter\": 10922,\n    \"Ġspill\": 10923,\n    \"Ġgrain\": 10924,\n    \"league\": 10925,\n    \"Up\": 10926,\n    \"ĠKid\": 10927,\n    \"using\": 10928,\n    \"ĠJays\": 10929,\n    \"Ġoccasionally\": 10930,\n    \"ĠMI\": 10931,\n    \"yes\": 10932,\n    \"Ġdetect\": 10933,\n    \"Ġpropaganda\": 10934,\n    \"Ġneighboring\": 10935,\n    \"sub\": 10936,\n    \"avan\": 10937,\n    \"ĠAstros\": 10938,\n    \"oti\": 10939,\n    \"threatening\": 10940,\n    \"Ġshorter\": 10941,\n    \"INGS\": 10942,\n    \"Ġfeeding\": 10943,\n    \"Ġelevated\": 10944,\n    \"ĠWenger\": 10945,\n    \"Ġundergo\": 10946,\n    \"Ġpsychological\": 10947,\n    \"Ġautom\": 10948,\n    \"NP\": 10949,\n    \"anks\": 10950,\n    \"ĠNokia\": 10951,\n    \"Ġdrones\": 10952,\n    \"Ġrecognised\": 10953,\n    \"Ġheroes\": 10954,\n    \"agen\": 10955,\n    \"Ġparole\": 10956,\n    \"ĠBah\": 10957,\n    \"Ġhomeowners\": 10958,\n    \"ĠSweet\": 10959,\n    \"Ġinstances\": 10960,\n    \"ĠParish\": 10961,\n    \"ĠSL\": 10962,\n    \"Ġunw\": 10963,\n    \"Ġdelicious\": 10964,\n    \"¯\": 10965,\n    \"ĠInvestments\": 10966,\n    \"ĠPhilippine\": 10967,\n    \"inos\": 10968,\n    \"Ġmes\": 10969,\n    \"Ġbite\": 10970,\n    \"Ġcornerback\": 10971,\n    \"ĠHat\": 10972,\n    \"Ġdeserved\": 10973,\n    \"ologists\": 10974,\n    \"[\": 10975,\n    \"Ġwrongdoing\": 10976,\n    \"ĠTrent\": 10977,\n    \"ĠVe\": 10978,\n    \"ĠDeal\": 10979,\n    \"Mr\": 10980,\n    \"Ġovers\": 10981,\n    \"Ġhonors\": 10982,\n    \"ĠITV\": 10983,\n    \"Ġpayroll\": 10984,\n    \"Ġconfused\": 10985,\n    \"Ġelaborate\": 10986,\n    \"ange\": 10987,\n    \"World\": 10988,\n    \"ĠResort\": 10989,\n    \"ilia\": 10990,\n    \"ĠKr\": 10991,\n    \"Ġconclude\": 10992,\n    \"First\": 10993,\n    \"ĠDR\": 10994,\n    \"Ġpeer\": 10995,\n    \"Ġrunway\": 10996,\n    \"ĠPotter\": 10997,\n    \"cons\": 10998,\n    \"bad\": 10999,\n    \"si\": 11000,\n    \"ĠClimate\": 11001,\n    \"ĠHoll\": 11002,\n    \"Ġweighing\": 11003,\n    \"Ġepidemic\": 11004,\n    \"ĠBible\": 11005,\n    \"Ġhon\": 11006,\n    \"Ġrenew\": 11007,\n    \"Ġgambling\": 11008,\n    \"ĠNationals\": 11009,\n    \"itable\": 11010,\n    \"ĠOutlook\": 11011,\n    \"Ġreactions\": 11012,\n    \"ĠCos\": 11013,\n    \"ĠDana\": 11014,\n    \"India\": 11015,\n    \"ĠAirbus\": 11016,\n    \"power\": 11017,\n    \"watch\": 11018,\n    \"Ġstyles\": 11019,\n    \"Ġordinance\": 11020,\n    \"Ġcam\": 11021,\n    \"Ġinvent\": 11022,\n    \"ĠDurant\": 11023,\n    \"Ġexchanged\": 11024,\n    \"Ġyoga\": 11025,\n    \"ĠMichel\": 11026,\n    \"ĠWyoming\": 11027,\n    \"ĠPhase\": 11028,\n    \"ĠHannah\": 11029,\n    \"Ġtem\": 11030,\n    \"Ġfare\": 11031,\n    \"omer\": 11032,\n    \"Ġtrails\": 11033,\n    \"Ġquietly\": 11034,\n    \"ĠFourth\": 11035,\n    \"Ġwise\": 11036,\n    \"Ġappetite\": 11037,\n    \"Ġpedestrian\": 11038,\n    \"Ġfierce\": 11039,\n    \"hin\": 11040,\n    \"ako\": 11041,\n    \"Ġvacant\": 11042,\n    \"Ġdynamics\": 11043,\n    \"Ġbust\": 11044,\n    \"ĠGT\": 11045,\n    \"century\": 11046,\n    \"Ġpermitted\": 11047,\n    \"Ġfog\": 11048,\n    \"Ġrecruitment\": 11049,\n    \"ĠDue\": 11050,\n    \"Ġbro\": 11051,\n    \"Ġsil\": 11052,\n    \"ĠOpp\": 11053,\n    \"Ġphrase\": 11054,\n    \"ĠChip\": 11055,\n    \"ĠBase\": 11056,\n    \"Ġjazz\": 11057,\n    \"Ġenemies\": 11058,\n    \"Ġremainder\": 11059,\n    \"bles\": 11060,\n    \"Ġ105\": 11061,\n    \"ĠGur\": 11062,\n    \"Ġretiring\": 11063,\n    \"ĠCour\": 11064,\n    \"ĠSi\": 11065,\n    \"Ġinevitable\": 11066,\n    \"ĠAdvisory\": 11067,\n    \"ĠCampaign\": 11068,\n    \"ĠPeninsula\": 11069,\n    \"base\": 11070,\n    \"Ġjustify\": 11071,\n    \"inen\": 11072,\n    \"North\": 11073,\n    \"Ġfreezing\": 11074,\n    \"Ġphotography\": 11075,\n    \"Ġappointments\": 11076,\n    \"ĠTree\": 11077,\n    \"Os\": 11078,\n    \"Ġdivide\": 11079,\n    \"ĠMMA\": 11080,\n    \"Ġdeclines\": 11081,\n    \"ĠAbbott\": 11082,\n    \"ACH\": 11083,\n    \"ĠJah\": 11084,\n    \"Ġspr\": 11085,\n    \"Ġskilled\": 11086,\n    \"ĠTry\": 11087,\n    \"ANT\": 11088,\n    \"ael\": 11089,\n    \"ĠMcN\": 11090,\n    \"Ġtariff\": 11091,\n    \"generation\": 11092,\n    \"ĠMans\": 11093,\n    \"Or\": 11094,\n    \"Ġraped\": 11095,\n    \"Ġdisability\": 11096,\n    \"Ġnominations\": 11097,\n    \"Ġhappiness\": 11098,\n    \"ĠLSU\": 11099,\n    \"ĠInterstate\": 11100,\n    \"ĠDance\": 11101,\n    \"ĠMaking\": 11102,\n    \"Ġbailout\": 11103,\n    \"oro\": 11104,\n    \"ĠObviously\": 11105,\n    \"Ġinbox\": 11106,\n    \"football\": 11107,\n    \"hy\": 11108,\n    \"ĠCase\": 11109,\n    \"Ġentertaining\": 11110,\n    \"Ġhardest\": 11111,\n    \"ĠOpposition\": 11112,\n    \"Ġflip\": 11113,\n    \"ĠPirates\": 11114,\n    \"anu\": 11115,\n    \"ĠKlopp\": 11116,\n    \"Ġballistic\": 11117,\n    \"Ġprinted\": 11118,\n    \"ĠNFC\": 11119,\n    \"UST\": 11120,\n    \"Ġglasses\": 11121,\n    \"Ġrum\": 11122,\n    \"ĠDuncan\": 11123,\n    \"hal\": 11124,\n    \"Ġpreview\": 11125,\n    \"BER\": 11126,\n    \"dec\": 11127,\n    \"Ġsustainability\": 11128,\n    \"Ġaff\": 11129,\n    \"Ġhungry\": 11130,\n    \"service\": 11131,\n    \"avi\": 11132,\n    \"Ġsometime\": 11133,\n    \"Ġmod\": 11134,\n    \"ĠLib\": 11135,\n    \"oko\": 11136,\n    \"Ġfundraiser\": 11137,\n    \"Ġcrowded\": 11138,\n    \"mates\": 11139,\n    \"Ġcreativity\": 11140,\n    \"ĠHell\": 11141,\n    \"Ġtreaty\": 11142,\n    \"ĠSoftware\": 11143,\n    \"ĠRandy\": 11144,\n    \"ĠPolish\": 11145,\n    \"sa\": 11146,\n    \"ardi\": 11147,\n    \"Ġcab\": 11148,\n    \"ĠCamera\": 11149,\n    \"Ġlicenses\": 11150,\n    \"Ġ1988\": 11151,\n    \"Ġcontinuous\": 11152,\n    \"Ġpaired\": 11153,\n    \"Ġtally\": 11154,\n    \"Ġgrip\": 11155,\n    \"cho\": 11156,\n    \"Ġsurged\": 11157,\n    \"Ġpodium\": 11158,\n    \"Ġcontrary\": 11159,\n    \"SL\": 11160,\n    \"ĠResearchers\": 11161,\n    \"cing\": 11162,\n    \"Ġmi\": 11163,\n    \"Ġdisputed\": 11164,\n    \"Ġgrades\": 11165,\n    \"Ġseverely\": 11166,\n    \"ĠMcL\": 11167,\n    \"ondo\": 11168,\n    \"Ġshelters\": 11169,\n    \"Ġdomain\": 11170,\n    \"ĠSwitch\": 11171,\n    \"Ġtestify\": 11172,\n    \"case\": 11173,\n    \"omet\": 11174,\n    \"atch\": 11175,\n    \"ĠAff\": 11176,\n    \"Ġcasting\": 11177,\n    \"berger\": 11178,\n    \"Ġintimate\": 11179,\n    \"erc\": 11180,\n    \"plan\": 11181,\n    \"ĠPast\": 11182,\n    \"ĠUt\": 11183,\n    \"Ġapologized\": 11184,\n    \"ĠDet\": 11185,\n    \"alle\": 11186,\n    \"Ġwhilst\": 11187,\n    \"Ġpel\": 11188,\n    \"Ġexecute\": 11189,\n    \"Ġharmful\": 11190,\n    \"ĠRB\": 11191,\n    \"onda\": 11192,\n    \"ĠFul\": 11193,\n    \"II\": 11194,\n    \"Those\": 11195,\n    \"Ġcryptocurrency\": 11196,\n    \"Ġrealise\": 11197,\n    \"ĠAthens\": 11198,\n    \"ĠApplication\": 11199,\n    \"ORD\": 11200,\n    \"Ġmidst\": 11201,\n    \"ĠSem\": 11202,\n    \"Ġmessaging\": 11203,\n    \"Ġcousin\": 11204,\n    \"ĠMarsh\": 11205,\n    \"ĠAlmost\": 11206,\n    \"uto\": 11207,\n    \"wire\": 11208,\n    \"ĠManaging\": 11209,\n    \"Ġsends\": 11210,\n    \"ĠDerby\": 11211,\n    \"Ġpad\": 11212,\n    \"Ġdevoted\": 11213,\n    \"ĠWorking\": 11214,\n    \"ĠWestminster\": 11215,\n    \"Ġdirty\": 11216,\n    \"ements\": 11217,\n    \"ĠLew\": 11218,\n    \"door\": 11219,\n    \"Ġadvisor\": 11220,\n    \"ival\": 11221,\n    \"Ġsubscribe\": 11222,\n    \"Ġcredited\": 11223,\n    \"Ġpressed\": 11224,\n    \"Ġbrick\": 11225,\n    \"Ġrehabilitation\": 11226,\n    \"Ġ\\\"[\": 11227,\n    \"erry\": 11228,\n    \"Ġtransformed\": 11229,\n    \"arp\": 11230,\n    \"Ġreceivers\": 11231,\n    \"ĠFan\": 11232,\n    \"ĠKris\": 11233,\n    \"ĠCharlottesville\": 11234,\n    \"Ġste\": 11235,\n    \"Ġconstructed\": 11236,\n    \"Ġbroadly\": 11237,\n    \"ĠBetter\": 11238,\n    \"ĠJanet\": 11239,\n    \"Ġenthusiasm\": 11240,\n    \"ĠIrving\": 11241,\n    \"ĠConst\": 11242,\n    \"Everyone\": 11243,\n    \"agn\": 11244,\n    \"ĠCrawford\": 11245,\n    \"Ġregards\": 11246,\n    \"ĠBurns\": 11247,\n    \"Ġjokes\": 11248,\n    \"erg\": 11249,\n    \"ARD\": 11250,\n    \"apped\": 11251,\n    \"Ġtravelled\": 11252,\n    \"ĠPoor\": 11253,\n    \"ĠHolly\": 11254,\n    \"Ġcontainer\": 11255,\n    \"Ġinfected\": 11256,\n    \"Ġlean\": 11257,\n    \"ĠWould\": 11258,\n    \"Ġmagnitude\": 11259,\n    \"ĠDou\": 11260,\n    \"minded\": 11261,\n    \"Ġpastor\": 11262,\n    \"Ġwherever\": 11263,\n    \"ulation\": 11264,\n    \"Ġ1986\": 11265,\n    \"ĠMegan\": 11266,\n    \"Ġgraphic\": 11267,\n    \"Ġtalents\": 11268,\n    \"Ġkn\": 11269,\n    \"ĠEC\": 11270,\n    \"ĠMcM\": 11271,\n    \"ĠKon\": 11272,\n    \"eni\": 11273,\n    \"ĠEsc\": 11274,\n    \"inas\": 11275,\n    \"ĠNom\": 11276,\n    \"Ġchasing\": 11277,\n    \"arl\": 11278,\n    \"ĠHungary\": 11279,\n    \"Ġmainland\": 11280,\n    \"ĠDist\": 11281,\n    \"utes\": 11282,\n    \"Ġrubber\": 11283,\n    \"iat\": 11284,\n    \"ĠMorrison\": 11285,\n    \"ushing\": 11286,\n    \"iny\": 11287,\n    \"Ġcopies\": 11288,\n    \"ĠFat\": 11289,\n    \"agged\": 11290,\n    \"Ġfloating\": 11291,\n    \"ĠCurtis\": 11292,\n    \"Ġfatally\": 11293,\n    \"ĠManuel\": 11294,\n    \"Ġgraduates\": 11295,\n    \"nar\": 11296,\n    \"ĠKenny\": 11297,\n    \"Ġretreat\": 11298,\n    \"Ġretro\": 11299,\n    \"ĠPierre\": 11300,\n    \"listed\": 11301,\n    \"ĠDale\": 11302,\n    \"ding\": 11303,\n    \"Ġintentions\": 11304,\n    \"Ġsentences\": 11305,\n    \"ĠSere\": 11306,\n    \"Ġinvasion\": 11307,\n    \"Ġpremiums\": 11308,\n    \"ĠGardner\": 11309,\n    \"Ġshipments\": 11310,\n    \"Ġcol\": 11311,\n    \"bell\": 11312,\n    \"ilo\": 11313,\n    \"Ġworthy\": 11314,\n    \"Ġinterceptions\": 11315,\n    \"Ġcomplain\": 11316,\n    \"icle\": 11317,\n    \"ĠTah\": 11318,\n    \"ĠMt\": 11319,\n    \"ĠSyracuse\": 11320,\n    \"Since\": 11321,\n    \"aches\": 11322,\n    \"ĠCand\": 11323,\n    \"Ġinteractions\": 11324,\n    \"ĠShawn\": 11325,\n    \"nc\": 11326,\n    \"Ġtheaters\": 11327,\n    \"ART\": 11328,\n    \"Th\": 11329,\n    \"Ġalter\": 11330,\n    \"aley\": 11331,\n    \"imo\": 11332,\n    \"Ġresponders\": 11333,\n    \"kan\": 11334,\n    \"ĠDarren\": 11335,\n    \"Ġdeliveries\": 11336,\n    \"PI\": 11337,\n    \"125\": 11338,\n    \"Ġlaughing\": 11339,\n    \"ĠPatterson\": 11340,\n    \"Ġinfections\": 11341,\n    \"Ġtur\": 11342,\n    \"130\": 11343,\n    \"Ġhackers\": 11344,\n    \"Ġwarn\": 11345,\n    \"Ġfreeze\": 11346,\n    \"Ġscreaming\": 11347,\n    \"ĠEcho\": 11348,\n    \"ĠDom\": 11349,\n    \"MAN\": 11350,\n    \"ĠJoy\": 11351,\n    \"Ġbeneath\": 11352,\n    \"ĠHalf\": 11353,\n    \"Ġpatent\": 11354,\n    \"Ġugly\": 11355,\n    \"Ġlip\": 11356,\n    \"Ġnominees\": 11357,\n    \"ĠGrade\": 11358,\n    \"Ġinfluenced\": 11359,\n    \"Ġabilities\": 11360,\n    \"Ġlimiting\": 11361,\n    \"Ġsmell\": 11362,\n    \"Ġesc\": 11363,\n    \"ĠBernard\": 11364,\n    \"cs\": 11365,\n    \"ĠMyers\": 11366,\n    \"oted\": 11367,\n    \"Black\": 11368,\n    \"Ġlim\": 11369,\n    \"Ġsworn\": 11370,\n    \"ĠBlair\": 11371,\n    \"anes\": 11372,\n    \"ĠEvent\": 11373,\n    \"Ġmature\": 11374,\n    \"Ġpositioned\": 11375,\n    \"Ġerupted\": 11376,\n    \"grand\": 11377,\n    \"ĠTell\": 11378,\n    \"Ġbackdrop\": 11379,\n    \"Ġyeah\": 11380,\n    \"ĠClear\": 11381,\n    \"Ġsignificance\": 11382,\n    \"Ġpatience\": 11383,\n    \"ĠWing\": 11384,\n    \"Ġhorrible\": 11385,\n    \"Ġdeploy\": 11386,\n    \"ipe\": 11387,\n    \"Ġbitcoin\": 11388,\n    \"Ġcommitting\": 11389,\n    \"Ġdismiss\": 11390,\n    \"ĠBlood\": 11391,\n    \"ĠMeyer\": 11392,\n    \"selling\": 11393,\n    \"Ġregarded\": 11394,\n    \"Ġlottery\": 11395,\n    \"ĠLuther\": 11396,\n    \"Ġpipe\": 11397,\n    \"Ġcro\": 11398,\n    \"ĠANC\": 11399,\n    \"ĠSolar\": 11400,\n    \"Ġsimilarly\": 11401,\n    \"Ġham\": 11402,\n    \"ĠHonor\": 11403,\n    \"tar\": 11404,\n    \"gin\": 11405,\n    \"ĠArmstrong\": 11406,\n    \"Ġbrowser\": 11407,\n    \"agon\": 11408,\n    \"via\": 11409,\n    \"Ġentries\": 11410,\n    \"Ġinfl\": 11411,\n    \"Ġgraduation\": 11412,\n    \"Ġalleges\": 11413,\n    \"ĠLoading\": 11414,\n    \"Ġsuperb\": 11415,\n    \"ially\": 11416,\n    \"Ġadministrator\": 11417,\n    \"uls\": 11418,\n    \"Ġartistic\": 11419,\n    \"ĠANGEL\": 11420,\n    \"ĠBang\": 11421,\n    \"Ġfossil\": 11422,\n    \"¨\": 11423,\n    \"Ġpoly\": 11424,\n    \"ĠGuardiola\": 11425,\n    \"ĠPerth\": 11426,\n    \"Ġeducate\": 11427,\n    \"Cl\": 11428,\n    \"Ġcommittees\": 11429,\n    \"Ġforthcoming\": 11430,\n    \"Ġadjustments\": 11431,\n    \"count\": 11432,\n    \"Ġincoming\": 11433,\n    \"brook\": 11434,\n    \"ĠMinneapolis\": 11435,\n    \"Ġgown\": 11436,\n    \"ĠCroatia\": 11437,\n    \"host\": 11438,\n    \"Ġcompetitor\": 11439,\n    \"Ġlyrics\": 11440,\n    \"Ġbelonging\": 11441,\n    \"ĠFrances\": 11442,\n    \"ĠHaley\": 11443,\n    \"ĠBruins\": 11444,\n    \"Ġmask\": 11445,\n    \"ĠPv\": 11446,\n    \"dollar\": 11447,\n    \"Ġbowling\": 11448,\n    \"Ġjewelry\": 11449,\n    \"ĠJulia\": 11450,\n    \"Ġbroadband\": 11451,\n    \"ĠBhar\": 11452,\n    \"ĠArmed\": 11453,\n    \"vy\": 11454,\n    \"government\": 11455,\n    \"kov\": 11456,\n    \"Ġpremises\": 11457,\n    \"Ġjersey\": 11458,\n    \"Ġapplies\": 11459,\n    \"ĠFreeman\": 11460,\n    \"Ġgrows\": 11461,\n    \"ĠEquity\": 11462,\n    \"Ġmaterially\": 11463,\n    \"Ġfigured\": 11464,\n    \"ience\": 11465,\n    \"Ġmajors\": 11466,\n    \"ĠYe\": 11467,\n    \"ĠHey\": 11468,\n    \"oned\": 11469,\n    \"aping\": 11470,\n    \"Ġtoilet\": 11471,\n    \"ĠConnor\": 11472,\n    \"Ġavoiding\": 11473,\n    \"pos\": 11474,\n    \"Once\": 11475,\n    \"ĠRockets\": 11476,\n    \"ĠSnapchat\": 11477,\n    \"Go\": 11478,\n    \"Ġsolidarity\": 11479,\n    \"ĠAffordable\": 11480,\n    \"Ġdial\": 11481,\n    \"ĠOmar\": 11482,\n    \"xt\": 11483,\n    \"ĠVatican\": 11484,\n    \"anta\": 11485,\n    \"ĠSuperior\": 11486,\n    \"Ġbeaches\": 11487,\n    \"ĠKi\": 11488,\n    \"Ã¥\": 11489,\n    \"KY\": 11490,\n    \"Ġgro\": 11491,\n    \"ĠEmpire\": 11492,\n    \"Ġoccurs\": 11493,\n    \"Ġjoked\": 11494,\n    \"Ġquotes\": 11495,\n    \"ĠSaskatchewan\": 11496,\n    \"pert\": 11497,\n    \"Ġmaintains\": 11498,\n    \"olt\": 11499,\n    \"Ġupgrades\": 11500,\n    \"ĠCho\": 11501,\n    \"ĠAlexis\": 11502,\n    \"ĠHundreds\": 11503,\n    \"ĠBud\": 11504,\n    \"Ġcenturies\": 11505,\n    \"ĠInvestor\": 11506,\n    \"ĠGomez\": 11507,\n    \"Ġconceded\": 11508,\n    \"Ġexpressing\": 11509,\n    \"ĠIBM\": 11510,\n    \"Ġadvancing\": 11511,\n    \"ĠDollar\": 11512,\n    \"jer\": 11513,\n    \"Ġexceed\": 11514,\n    \"author\": 11515,\n    \"rist\": 11516,\n    \"seat\": 11517,\n    \"ĠPrimary\": 11518,\n    \"ĠForbes\": 11519,\n    \"ĠAlzheimer\": 11520,\n    \"Ġdevastated\": 11521,\n    \"Ġawful\": 11522,\n    \"ĠStudio\": 11523,\n    \"Ġbullpen\": 11524,\n    \"Ġmobility\": 11525,\n    \"Ġanalyze\": 11526,\n    \"lie\": 11527,\n    \"AFP\": 11528,\n    \"iche\": 11529,\n    \"ĠRoyals\": 11530,\n    \"Ġcoupled\": 11531,\n    \"Ġdug\": 11532,\n    \"ĠRing\": 11533,\n    \"Ġenvironments\": 11534,\n    \"national\": 11535,\n    \"ĠCongo\": 11536,\n    \"Ġalleging\": 11537,\n    \"wn\": 11538,\n    \"ulating\": 11539,\n    \"Ġur\": 11540,\n    \"Ġreaches\": 11541,\n    \"ĠPine\": 11542,\n    \"Ġthreshold\": 11543,\n    \"Ġtournaments\": 11544,\n    \"Ġheating\": 11545,\n    \"ĠGard\": 11546,\n    \"ĠHamas\": 11547,\n    \"ĠÂ«\": 11548,\n    \"ĠHolding\": 11549,\n    \"Ġpossibilities\": 11550,\n    \"ĠHassan\": 11551,\n    \"ĠMohammad\": 11552,\n    \"Ġoffenders\": 11553,\n    \"Ġautomated\": 11554,\n    \"Ġrealised\": 11555,\n    \"ouse\": 11556,\n    \"building\": 11557,\n    \"ĠDub\": 11558,\n    \"ĠGeneva\": 11559,\n    \"Ġfacial\": 11560,\n    \"ĠRestaurant\": 11561,\n    \"ĠNg\": 11562,\n    \"Ġtot\": 11563,\n    \"Ġgrace\": 11564,\n    \"ĠCP\": 11565,\n    \"Ġposter\": 11566,\n    \"hart\": 11567,\n    \"ĠNi\": 11568,\n    \"Ġreaff\": 11569,\n    \"Ġprov\": 11570,\n    \"Ġ111\": 11571,\n    \"ĠAid\": 11572,\n    \"Ġscrap\": 11573,\n    \"izers\": 11574,\n    \"ogen\": 11575,\n    \"Ġtissue\": 11576,\n    \"Ġvibrant\": 11577,\n    \"Ġrider\": 11578,\n    \"CD\": 11579,\n    \"ĠKitchen\": 11580,\n    \"Ġgenre\": 11581,\n    \"¬\": 11582,\n    \"depth\": 11583,\n    \"kind\": 11584,\n    \"Ġendorsed\": 11585,\n    \"Ġsimultaneously\": 11586,\n    \"Ġintern\": 11587,\n    \"ĠDrag\": 11588,\n    \"Ġembraced\": 11589,\n    \"Ġcounted\": 11590,\n    \"uj\": 11591,\n    \"ĠOg\": 11592,\n    \"Ġphysician\": 11593,\n    \"ĠIR\": 11594,\n    \"IST\": 11595,\n    \"ĠKir\": 11596,\n    \"Ġhacking\": 11597,\n    \"ĠSources\": 11598,\n    \"astic\": 11599,\n    \"growing\": 11600,\n    \"ĠWake\": 11601,\n    \"Ġhint\": 11602,\n    \"Ġcompiled\": 11603,\n    \"Ġreign\": 11604,\n    \"Ġcinema\": 11605,\n    \"Ġboosting\": 11606,\n    \"Ġaccommodation\": 11607,\n    \"ĠEuropa\": 11608,\n    \"Ġsubsidiaries\": 11609,\n    \"Ġclosures\": 11610,\n    \"ĠBil\": 11611,\n    \"ĠBou\": 11612,\n    \"wh\": 11613,\n    \"ĠAw\": 11614,\n    \"FT\": 11615,\n    \"hole\": 11616,\n    \"ĠNova\": 11617,\n    \"ĠNSW\": 11618,\n    \"Ġrap\": 11619,\n    \"Ġencourages\": 11620,\n    \"GR\": 11621,\n    \"ds\": 11622,\n    \"ĠMuk\": 11623,\n    \"ĠSurvey\": 11624,\n    \"ĠReagan\": 11625,\n    \"oning\": 11626,\n    \"Ġneighbouring\": 11627,\n    \"ĠMcCl\": 11628,\n    \"acht\": 11629,\n    \"Ġfinishes\": 11630,\n    \"ĠEsp\": 11631,\n    \"pat\": 11632,\n    \"Ġdestinations\": 11633,\n    \"ĠWagner\": 11634,\n    \"Ġconfronted\": 11635,\n    \"square\": 11636,\n    \"Ġpie\": 11637,\n    \"brand\": 11638,\n    \"hl\": 11639,\n    \"Ġabsent\": 11640,\n    \"Ġsurf\": 11641,\n    \"Ġrifle\": 11642,\n    \"ĠSS\": 11643,\n    \"ĠDeath\": 11644,\n    \"wich\": 11645,\n    \"Ġbeds\": 11646,\n    \"ĠLock\": 11647,\n    \"ĠAgu\": 11648,\n    \"atives\": 11649,\n    \"jee\": 11650,\n    \"Ġoral\": 11651,\n    \"Ġbudgets\": 11652,\n    \"Ġinspiring\": 11653,\n    \"IONS\": 11654,\n    \"works\": 11655,\n    \"Ġspirits\": 11656,\n    \"Ġcabin\": 11657,\n    \"Ġsatisfaction\": 11658,\n    \"Ġvoluntary\": 11659,\n    \"ĠMunicipal\": 11660,\n    \"Ġdeportation\": 11661,\n    \"ĠWriter\": 11662,\n    \"ĠVI\": 11663,\n    \"VERTISEMENT\": 11664,\n    \"/.\": 11665,\n    \"ĠSouthampton\": 11666,\n    \"aces\": 11667,\n    \"ĠHelen\": 11668,\n    \"ĠHum\": 11669,\n    \"110\": 11670,\n    \"Ġgarbage\": 11671,\n    \"through\": 11672,\n    \"Ġkingdom\": 11673,\n    \"MT\": 11674,\n    \"augh\": 11675,\n    \"Ġbizarre\": 11676,\n    \"ĠStarting\": 11677,\n    \"Ġwooden\": 11678,\n    \"ĠProgress\": 11679,\n    \"iron\": 11680,\n    \"sten\": 11681,\n    \"ĠSergio\": 11682,\n    \"ĠHR\": 11683,\n    \"Ġturnout\": 11684,\n    \"ĠAmericas\": 11685,\n    \"ĠSara\": 11686,\n    \"Ġagrees\": 11687,\n    \"apper\": 11688,\n    \"Ġbra\": 11689,\n    \"Ġrecycling\": 11690,\n    \"oom\": 11691,\n    \"Ġflee\": 11692,\n    \"Ġdistinct\": 11693,\n    \"IAL\": 11694,\n    \"aha\": 11695,\n    \"Ġfever\": 11696,\n    \"ĠPartnership\": 11697,\n    \"ĠYu\": 11698,\n    \"ĠPixel\": 11699,\n    \"ĠBlock\": 11700,\n    \"ĠMelissa\": 11701,\n    \"igg\": 11702,\n    \"Ġdecides\": 11703,\n    \"ĠNorman\": 11704,\n    \"Ġmas\": 11705,\n    \"held\": 11706,\n    \"ĠPD\": 11707,\n    \"Ġsheer\": 11708,\n    \"ĠDim\": 11709,\n    \"ĠCass\": 11710,\n    \"Ġcolumnist\": 11711,\n    \"ĠBros\": 11712,\n    \"Ġturnaround\": 11713,\n    \"ĠValue\": 11714,\n    \"ĠBachelor\": 11715,\n    \"awn\": 11716,\n    \"Ġassignment\": 11717,\n    \"ested\": 11718,\n    \"ĠJudiciary\": 11719,\n    \"Ġdiamond\": 11720,\n    \"Ġmus\": 11721,\n    \"Ġindigenous\": 11722,\n    \"lines\": 11723,\n    \"Ġ1984\": 11724,\n    \"igroup\": 11725,\n    \"ict\": 11726,\n    \"ĠJaguars\": 11727,\n    \"Ġlun\": 11728,\n    \"Ġprofiles\": 11729,\n    \"Ġcomputing\": 11730,\n    \"ĠBelgian\": 11731,\n    \"ĠLloyd\": 11732,\n    \"ĠGoing\": 11733,\n    \"Ġdisp\": 11734,\n    \"Ġ1987\": 11735,\n    \"eder\": 11736,\n    \"ĠVin\": 11737,\n    \"Ġgovern\": 11738,\n    \"Ġblend\": 11739,\n    \"ĠSebastian\": 11740,\n    \"ĠMidwest\": 11741,\n    \"iga\": 11742,\n    \"Ġspl\": 11743,\n    \"Ġtopping\": 11744,\n    \"Ġnetworking\": 11745,\n    \"ĠEmer\": 11746,\n    \"Ġoxygen\": 11747,\n    \"ĠInterest\": 11748,\n    \"ĠMoy\": 11749,\n    \"Ġtrader\": 11750,\n    \"Ġbay\": 11751,\n    \"Ġsticking\": 11752,\n    \"ĠMovement\": 11753,\n    \"Ġbidding\": 11754,\n    \"tax\": 11755,\n    \"Ġacademy\": 11756,\n    \"ĠMO\": 11757,\n    \"ĠSpirit\": 11758,\n    \"Ġhealing\": 11759,\n    \"wen\": 11760,\n    \"ĠPrix\": 11761,\n    \"cal\": 11762,\n    \"ĠOperating\": 11763,\n    \"Ġinstantly\": 11764,\n    \"ĠTonight\": 11765,\n    \"Ġsacked\": 11766,\n    \"Ġautomation\": 11767,\n    \"umps\": 11768,\n    \"ĠNey\": 11769,\n    \"March\": 11770,\n    \"ĠBuck\": 11771,\n    \"Ġconcentration\": 11772,\n    \"Here\": 11773,\n    \"Ġtravelers\": 11774,\n    \"Ġprotective\": 11775,\n    \"ĠMoody\": 11776,\n    \"Ġentrepreneur\": 11777,\n    \"Ġfac\": 11778,\n    \"kowski\": 11779,\n    \"Ġpreparations\": 11780,\n    \"Ġdominate\": 11781,\n    \"Ġspray\": 11782,\n    \"Ġdisturbing\": 11783,\n    \"ĠFraser\": 11784,\n    \"ĠCody\": 11785,\n    \"ashi\": 11786,\n    \"ĠPel\": 11787,\n    \"Ġrisky\": 11788,\n    \"Ġawkward\": 11789,\n    \"ĠVA\": 11790,\n    \"ails\": 11791,\n    \"Ġangle\": 11792,\n    \"Ġundergoing\": 11793,\n    \"Ġalbums\": 11794,\n    \"Ġafterwards\": 11795,\n    \"ĠNaw\": 11796,\n    \"uge\": 11797,\n    \"enter\": 11798,\n    \"ĠSussex\": 11799,\n    \"ĠRecently\": 11800,\n    \"Ġlikelihood\": 11801,\n    \"large\": 11802,\n    \"Ġsnaps\": 11803,\n    \"ibr\": 11804,\n    \"ĠMalcolm\": 11805,\n    \"Ġcru\": 11806,\n    \"Ġaltogether\": 11807,\n    \"Ġsetup\": 11808,\n    \"Ġtorture\": 11809,\n    \"Ġfiber\": 11810,\n    \"Ġquarterbacks\": 11811,\n    \"ĠGetting\": 11812,\n    \"ipping\": 11813,\n    \"ĠNorwegian\": 11814,\n    \"ĠMiles\": 11815,\n    \"ĠArnold\": 11816,\n    \"ĠDisease\": 11817,\n    \"Ġtends\": 11818,\n    \"ife\": 11819,\n    \"ĠCaroline\": 11820,\n    \"Ġnavigate\": 11821,\n    \"Ġbrush\": 11822,\n    \"ĠAssociates\": 11823,\n    \"Ġbath\": 11824,\n    \"ĠCenters\": 11825,\n    \"ĠMC\": 11826,\n    \"Ġtaxpayer\": 11827,\n    \"comp\": 11828,\n    \"Ġaccomplish\": 11829,\n    \"ĠTraffic\": 11830,\n    \"ĠBru\": 11831,\n    \"Ġgreenhouse\": 11832,\n    \"ĠMalaysian\": 11833,\n    \"ĠPur\": 11834,\n    \"ased\": 11835,\n    \"ĠKnicks\": 11836,\n    \"aters\": 11837,\n    \"Ġalt\": 11838,\n    \"ICK\": 11839,\n    \"Ġcalculations\": 11840,\n    \"Ġmindset\": 11841,\n    \"unch\": 11842,\n    \"Ġgu\": 11843,\n    \"Ġsteadily\": 11844,\n    \"Ġfiction\": 11845,\n    \"ĠPap\": 11846,\n    \"forming\": 11847,\n    \"ĠActor\": 11848,\n    \"ĠBerry\": 11849,\n    \"imp\": 11850,\n    \"ĠUpper\": 11851,\n    \"Ġassessed\": 11852,\n    \"Ġlawn\": 11853,\n    \"ĠRoh\": 11854,\n    \"Ġclearance\": 11855,\n    \"funded\": 11856,\n    \"Ġpret\": 11857,\n    \"ĠHom\": 11858,\n    \"VS\": 11859,\n    \"ĠTourism\": 11860,\n    \"ĠRy\": 11861,\n    \"ĠGonz\": 11862,\n    \"ĠStudios\": 11863,\n    \"Ġanchor\": 11864,\n    \"Ġrecognise\": 11865,\n    \"Ġcooperate\": 11866,\n    \"enny\": 11867,\n    \"aza\": 11868,\n    \"ĠMeet\": 11869,\n    \"Ġeventual\": 11870,\n    \"SW\": 11871,\n    \"ĠCounsel\": 11872,\n    \"ĠSave\": 11873,\n    \"Ġlucrative\": 11874,\n    \"Ġslim\": 11875,\n    \"ĠGreens\": 11876,\n    \"Ġchemistry\": 11877,\n    \"ĠSheikh\": 11878,\n    \"Ġbridges\": 11879,\n    \"business\": 11880,\n    \"ĠSaf\": 11881,\n    \"ĠGy\": 11882,\n    \"Ġprotocol\": 11883,\n    \"Ġnephew\": 11884,\n    \"ĠBrands\": 11885,\n    \"ĠCulture\": 11886,\n    \"orship\": 11887,\n    \"Ġ(Â£\": 11888,\n    \"ĠDell\": 11889,\n    \"astics\": 11890,\n    \"Ġproving\": 11891,\n    \"ĠMann\": 11892,\n    \"aca\": 11893,\n    \"Ġindoor\": 11894,\n    \"ĠUganda\": 11895,\n    \"ĠRomney\": 11896,\n    \"ĠStage\": 11897,\n    \"Ġward\": 11898,\n    \"ĠAmber\": 11899,\n    \"haw\": 11900,\n    \"Ġtw\": 11901,\n    \"Ġbullying\": 11902,\n    \"ĠCAR\": 11903,\n    \"Ġassociates\": 11904,\n    \"ĠHopkins\": 11905,\n    \"Ġsuburb\": 11906,\n    \"Ġaggressively\": 11907,\n    \"Ġpostponed\": 11908,\n    \"Ġbas\": 11909,\n    \"Ġburglary\": 11910,\n    \"ĠFound\": 11911,\n    \"Ġfloors\": 11912,\n    \"Any\": 11913,\n    \"Ġjam\": 11914,\n    \"Ġvisibility\": 11915,\n    \"Ġbenefited\": 11916,\n    \"ĠAud\": 11917,\n    \"aying\": 11918,\n    \"iku\": 11919,\n    \"ĠPas\": 11920,\n    \"ĠGPS\": 11921,\n    \"ĠOwens\": 11922,\n    \"Ġreluctant\": 11923,\n    \"ĠOlivia\": 11924,\n    \"ols\": 11925,\n    \"Ġemotion\": 11926,\n    \"ĠHeavy\": 11927,\n    \"Ġhostile\": 11928,\n    \"Ġfavorites\": 11929,\n    \"Ġfeat\": 11930,\n    \"ĠCord\": 11931,\n    \"ĠGO\": 11932,\n    \"Ġindicted\": 11933,\n    \"idal\": 11934,\n    \"ĠIL\": 11935,\n    \"Ħ\": 11936,\n    \"acer\": 11937,\n    \"ICH\": 11938,\n    \"oda\": 11939,\n    \"Ġrecipients\": 11940,\n    \"Ġtribal\": 11941,\n    \"Ġresist\": 11942,\n    \"ĠCritics\": 11943,\n    \"Ġsang\": 11944,\n    \"ĠMath\": 11945,\n    \"ĠBrighton\": 11946,\n    \"ĠKw\": 11947,\n    \"Ġlimitations\": 11948,\n    \"Ġinterception\": 11949,\n    \"onde\": 11950,\n    \"ĠRobertson\": 11951,\n    \"Ġenjoys\": 11952,\n    \"site\": 11953,\n    \"Ġwings\": 11954,\n    \"ĠCeltic\": 11955,\n    \"Ġrelaxed\": 11956,\n    \"Share\": 11957,\n    \"Ġwarrants\": 11958,\n    \"oco\": 11959,\n    \"Ġcritically\": 11960,\n    \"GC\": 11961,\n    \"Ġcute\": 11962,\n    \"Ġlaying\": 11963,\n    \"itude\": 11964,\n    \"ĠMediterranean\": 11965,\n    \"Ġwatches\": 11966,\n    \"Ġdisagree\": 11967,\n    \"ĠReturn\": 11968,\n    \"ARC\": 11969,\n    \"people\": 11970,\n    \"Ġtwelve\": 11971,\n    \"Ġoverdose\": 11972,\n    \"ĠLot\": 11973,\n    \"ĠFROM\": 11974,\n    \"ĠPeters\": 11975,\n    \"Ġadministrators\": 11976,\n    \"Ġslam\": 11977,\n    \"jar\": 11978,\n    \"OH\": 11979,\n    \"ĠInitiative\": 11980,\n    \"Ġteamed\": 11981,\n    \"ĠMajority\": 11982,\n    \"June\": 11983,\n    \"ĠPlaza\": 11984,\n    \"lake\": 11985,\n    \"Ġglimpse\": 11986,\n    \"Ġrings\": 11987,\n    \"Ġos\": 11988,\n    \"Ġmentor\": 11989,\n    \"have\": 11990,\n    \"Ġlanguages\": 11991,\n    \"Ġuncle\": 11992,\n    \"agu\": 11993,\n    \"ĠWine\": 11994,\n    \"ĠCategory\": 11995,\n    \"ĠIng\": 11996,\n    \"Ġcontests\": 11997,\n    \"ĠRosen\": 11998,\n    \"ĠWhatever\": 11999,\n    \"Ġdenying\": 12000,\n    \"ean\": 12001,\n    \"Ġspec\": 12002,\n    \"Ġgrad\": 12003,\n    \"Ġtenants\": 12004,\n    \"show\": 12005,\n    \"ĠGregory\": 12006,\n    \"Ġcontention\": 12007,\n    \"Ġunanimously\": 12008,\n    \"ĠPin\": 12009,\n    \"fa\": 12010,\n    \"ĠPink\": 12011,\n    \"Ġswitched\": 12012,\n    \"acre\": 12013,\n    \"ĠTrading\": 12014,\n    \"VP\": 12015,\n    \"ĠMaple\": 12016,\n    \"Neill\": 12017,\n    \"Ġdiscounts\": 12018,\n    \"alls\": 12019,\n    \"Ġsounded\": 12020,\n    \"Ġrumours\": 12021,\n    \"ĠCre\": 12022,\n    \"hall\": 12023,\n    \"ĠTele\": 12024,\n    \"Ġthankful\": 12025,\n    \"Ġsurveyed\": 12026,\n    \"UB\": 12027,\n    \"Ġdignity\": 12028,\n    \"Ġnod\": 12029,\n    \"Ġmisleading\": 12030,\n    \"ĠTX\": 12031,\n    \"ĠBurke\": 12032,\n    \"Ġmounting\": 12033,\n    \"Ġskies\": 12034,\n    \"Ġbesides\": 12035,\n    \"ĠGarrett\": 12036,\n    \"tha\": 12037,\n    \"Ġintelligent\": 12038,\n    \"Ġtanks\": 12039,\n    \"apping\": 12040,\n    \"ĠRat\": 12041,\n    \"aint\": 12042,\n    \"Ġentertain\": 12043,\n    \"ĠAbdullah\": 12044,\n    \"Ġsink\": 12045,\n    \"ĠLan\": 12046,\n    \"ĠManufacturing\": 12047,\n    \"NFL\": 12048,\n    \"Ġthemes\": 12049,\n    \"ĠHaven\": 12050,\n    \"ĠDavies\": 12051,\n    \"ĠKerr\": 12052,\n    \"ĠLen\": 12053,\n    \"Ġcourtroom\": 12054,\n    \"Ġfailures\": 12055,\n    \"Ġlately\": 12056,\n    \"ĠElectronics\": 12057,\n    \"Ġgorgeous\": 12058,\n    \"Ġnotification\": 12059,\n    \"Ġ2030\": 12060,\n    \"aved\": 12061,\n    \"Ġdeer\": 12062,\n    \"economic\": 12063,\n    \"ĠStatistics\": 12064,\n    \"Ġconfrontation\": 12065,\n    \"Ġgovernors\": 12066,\n    \"ĠHaram\": 12067,\n    \"ĠLGBTQ\": 12068,\n    \"Ġprocessed\": 12069,\n    \"ĠDuchess\": 12070,\n    \"Ġdowns\": 12071,\n    \"Ġpork\": 12072,\n    \"Ġhumor\": 12073,\n    \"ocese\": 12074,\n    \"Ġneeding\": 12075,\n    \"Ġmidterm\": 12076,\n    \"ĠOval\": 12077,\n    \"Ġcorners\": 12078,\n    \"Ġtablets\": 12079,\n    \"eds\": 12080,\n    \"vere\": 12081,\n    \"Ġattacker\": 12082,\n    \"Paul\": 12083,\n    \"pee\": 12084,\n    \"ĠAlice\": 12085,\n    \"Ġrenowned\": 12086,\n    \"Ġ09\": 12087,\n    \"ocking\": 12088,\n    \"Ġcreditors\": 12089,\n    \"ĠPedro\": 12090,\n    \"ĠPhone\": 12091,\n    \"Ġsurveys\": 12092,\n    \"ĠWelsh\": 12093,\n    \"Ġcow\": 12094,\n    \"Ġbuilds\": 12095,\n    \"Ġ000\": 12096,\n    \"ĠAzerbaijan\": 12097,\n    \"ĠYad\": 12098,\n    \"Ġinfant\": 12099,\n    \"Ġmotorists\": 12100,\n    \"Ġpoorly\": 12101,\n    \"Ġmedications\": 12102,\n    \"Ġstupid\": 12103,\n    \"ĠCastro\": 12104,\n    \"user\": 12105,\n    \"antly\": 12106,\n    \"alty\": 12107,\n    \"ĠCond\": 12108,\n    \"issa\": 12109,\n    \"ĠIvan\": 12110,\n    \"Ġcostume\": 12111,\n    \"Ġ08\": 12112,\n    \"Ġhence\": 12113,\n    \"Ġdangers\": 12114,\n    \"Ġbullish\": 12115,\n    \"Life\": 12116,\n    \"Ġflavor\": 12117,\n    \"ĠCharleston\": 12118,\n    \"Ġbikes\": 12119,\n    \"Ġworkshops\": 12120,\n    \"Ġarranged\": 12121,\n    \"Ġcontender\": 12122,\n    \"Ġsequel\": 12123,\n    \"ĠPlant\": 12124,\n    \"Ġdonor\": 12125,\n    \"Ġfactories\": 12126,\n    \"rict\": 12127,\n    \"ellen\": 12128,\n    \"Ġrobots\": 12129,\n    \"ĠWor\": 12130,\n    \"ĠDirectors\": 12131,\n    \"ĠPeru\": 12132,\n    \"Ġqueen\": 12133,\n    \"ĠTimothy\": 12134,\n    \"ĠToo\": 12135,\n    \"Ġobservers\": 12136,\n    \"Ġears\": 12137,\n    \"Ġbel\": 12138,\n    \"link\": 12139,\n    \"uns\": 12140,\n    \"Ġhomers\": 12141,\n    \"Ġadjacent\": 12142,\n    \"Ġconfidential\": 12143,\n    \"Ġstunned\": 12144,\n    \"iden\": 12145,\n    \"illed\": 12146,\n    \"ESS\": 12147,\n    \"Ġconvenient\": 12148,\n    \"ĠLindsey\": 12149,\n    \"por\": 12150,\n    \"upp\": 12151,\n    \"Ġborrow\": 12152,\n    \"ĠAhmad\": 12153,\n    \"ORT\": 12154,\n    \"Ġrelate\": 12155,\n    \"ĠSelf\": 12156,\n    \"ĠVanguard\": 12157,\n    \"utter\": 12158,\n    \"ĠBranch\": 12159,\n    \"ĠBolton\": 12160,\n    \"bat\": 12161,\n    \"Ġoutright\": 12162,\n    \"fighters\": 12163,\n    \"ĠBed\": 12164,\n    \"Ġpes\": 12165,\n    \"inski\": 12166,\n    \"Ġgunshot\": 12167,\n    \"Ġprinting\": 12168,\n    \"ĠSent\": 12169,\n    \"vern\": 12170,\n    \"Ġharvest\": 12171,\n    \"Ġbubble\": 12172,\n    \"Ġrefund\": 12173,\n    \"Ġfuels\": 12174,\n    \"Ġdive\": 12175,\n    \"Ġdiplomat\": 12176,\n    \"Ġpile\": 12177,\n    \"ĠVery\": 12178,\n    \"rot\": 12179,\n    \"ĠSearch\": 12180,\n    \"ĠJoyce\": 12181,\n    \"ĠPruitt\": 12182,\n    \"ĠLevel\": 12183,\n    \"ĠBP\": 12184,\n    \"ĠLac\": 12185,\n    \"had\": 12186,\n    \"Ġexpenditure\": 12187,\n    \"ĠMadd\": 12188,\n    \"Ġpockets\": 12189,\n    \"ĠClippers\": 12190,\n    \"ĠDear\": 12191,\n    \"ĠGive\": 12192,\n    \"Ġhal\": 12193,\n    \"Ġvertical\": 12194,\n    \"Ġwholesale\": 12195,\n    \"what\": 12196,\n    \"ĠSpringfield\": 12197,\n    \"ayed\": 12198,\n    \"ĠSom\": 12199,\n    \"Ġsecrets\": 12200,\n    \"Ġcharts\": 12201,\n    \"iar\": 12202,\n    \"ibility\": 12203,\n    \"LAND\": 12204,\n    \"Ġbearing\": 12205,\n    \"Ġprom\": 12206,\n    \"Ġtab\": 12207,\n    \"Ġsheets\": 12208,\n    \"ĠGL\": 12209,\n    \"Ġendless\": 12210,\n    \"opening\": 12211,\n    \"ĠOwen\": 12212,\n    \"Ġunderneath\": 12213,\n    \"ĠErik\": 12214,\n    \"ĠDACA\": 12215,\n    \"Ġsteering\": 12216,\n    \"Ġfootprint\": 12217,\n    \"ĠRoma\": 12218,\n    \"ĠDucks\": 12219,\n    \"ĠEllen\": 12220,\n    \"ĠProfessional\": 12221,\n    \"ĠGardens\": 12222,\n    \"Ġgoalie\": 12223,\n    \"Ġshine\": 12224,\n    \"Ġturmoil\": 12225,\n    \"Ġhunger\": 12226,\n    \"ĠâĢĭ\": 12227,\n    \"active\": 12228,\n    \"hey\": 12229,\n    \"Ġblessed\": 12230,\n    \"ason\": 12231,\n    \"oping\": 12232,\n    \"ĠThousands\": 12233,\n    \"Ġdose\": 12234,\n    \"ĠLor\": 12235,\n    \"Ġevolved\": 12236,\n    \"Ġcharities\": 12237,\n    \"ĠPE\": 12238,\n    \"ĠRub\": 12239,\n    \"ws\": 12240,\n    \"Ġmist\": 12241,\n    \"ĠShen\": 12242,\n    \"Ġbiological\": 12243,\n    \"ĠTweet\": 12244,\n    \"Ġcollections\": 12245,\n    \"Ġsubstantially\": 12246,\n    \"inner\": 12247,\n    \"Ġbattled\": 12248,\n    \"ĠCong\": 12249,\n    \"Hold\": 12250,\n    \"wp\": 12251,\n    \"Ġwells\": 12252,\n    \"Ġsake\": 12253,\n    \"Ġunrest\": 12254,\n    \"ĠKurt\": 12255,\n    \"Ġripped\": 12256,\n    \"itation\": 12257,\n    \"Ġneighbourhood\": 12258,\n    \"Ġinv\": 12259,\n    \"Ġcad\": 12260,\n    \"ĠCuban\": 12261,\n    \"ĠWealth\": 12262,\n    \"Ġtuition\": 12263,\n    \"Ġdeclaring\": 12264,\n    \"sch\": 12265,\n    \"orne\": 12266,\n    \"Ġwondered\": 12267,\n    \"ĠChaff\": 12268,\n    \"Ġdealer\": 12269,\n    \"ĠNumber\": 12270,\n    \"Mobile\": 12271,\n    \"Ġscratch\": 12272,\n    \"Ġprepares\": 12273,\n    \"ĠSens\": 12274,\n    \"ĠIstanbul\": 12275,\n    \"ĠPanama\": 12276,\n    \"ĠCay\": 12277,\n    \"Ġallocation\": 12278,\n    \"itutional\": 12279,\n    \"Ġhar\": 12280,\n    \"ĠNazi\": 12281,\n    \"ĠSund\": 12282,\n    \"Ġwarehouse\": 12283,\n    \"Ġbackyard\": 12284,\n    \"ĠIll\": 12285,\n    \"Ġunlawful\": 12286,\n    \"ĠReform\": 12287,\n    \"Ġbasement\": 12288,\n    \"ĠHi\": 12289,\n    \"ĠPictures\": 12290,\n    \"Ġtransfers\": 12291,\n    \"ĠSell\": 12292,\n    \"Ġfluid\": 12293,\n    \"Ġambitions\": 12294,\n    \"wife\": 12295,\n    \"Ġintensive\": 12296,\n    \"Ġsteals\": 12297,\n    \"Ġfestive\": 12298,\n    \"ĠHayes\": 12299,\n    \"Ġrestoration\": 12300,\n    \"Ġbranded\": 12301,\n    \"Journal\": 12302,\n    \"Ġmacro\": 12303,\n    \"Ġconsole\": 12304,\n    \"ĠMelania\": 12305,\n    \"ĠRahul\": 12306,\n    \"Ġdisposal\": 12307,\n    \"Ġcult\": 12308,\n    \"Ġpetrol\": 12309,\n    \"Ġtires\": 12310,\n    \"Ġkidnapping\": 12311,\n    \"Ġ115\": 12312,\n    \"Ġswap\": 12313,\n    \"ĠSud\": 12314,\n    \"Ġblown\": 12315,\n    \"ĠHindu\": 12316,\n    \"ĠBeckham\": 12317,\n    \"ĠGul\": 12318,\n    \"Ġfixture\": 12319,\n    \"Ġwisdom\": 12320,\n    \"Ġmines\": 12321,\n    \"fort\": 12322,\n    \"Ġrivers\": 12323,\n    \"ĠCyber\": 12324,\n    \"Ġtouches\": 12325,\n    \"race\": 12326,\n    \"Ġrelax\": 12327,\n    \"Ġcrashes\": 12328,\n    \"Ġconstituency\": 12329,\n    \"Ġ1979\": 12330,\n    \"Ġbureau\": 12331,\n    \"Ġinterface\": 12332,\n    \"Ġdetected\": 12333,\n    \"ĠBio\": 12334,\n    \"Ġhighlighting\": 12335,\n    \"ames\": 12336,\n    \"Ġcorresponding\": 12337,\n    \"great\": 12338,\n    \"Ġgray\": 12339,\n    \"Ġadvantages\": 12340,\n    \"ĠME\": 12341,\n    \"ĠAbbas\": 12342,\n    \"Ġnaked\": 12343,\n    \"rington\": 12344,\n    \".),\": 12345,\n    \"ĠFace\": 12346,\n    \"third\": 12347,\n    \"Ġtranscript\": 12348,\n    \"ples\": 12349,\n    \"Good\": 12350,\n    \"ĠArctic\": 12351,\n    \"Ġtolerance\": 12352,\n    \"reat\": 12353,\n    \"green\": 12354,\n    \"ĠMik\": 12355,\n    \"Ġoutreach\": 12356,\n    \"Ġrolls\": 12357,\n    \"Ġgen\": 12358,\n    \"Ġsupplied\": 12359,\n    \"Ġguarantees\": 12360,\n    \"aug\": 12361,\n    \"Ġsemif\": 12362,\n    \"ounds\": 12363,\n    \"running\": 12364,\n    \"Ġfitting\": 12365,\n    \"ĠRisk\": 12366,\n    \"iveness\": 12367,\n    \"family\": 12368,\n    \"Ġti\": 12369,\n    \"ĠIsaac\": 12370,\n    \"Ġdump\": 12371,\n    \"ĠPatricia\": 12372,\n    \"Ġpassport\": 12373,\n    \"ĠRhode\": 12374,\n    \"Who\": 12375,\n    \"log\": 12376,\n    \"Ġstat\": 12377,\n    \"Ġrat\": 12378,\n    \"ango\": 12379,\n    \"SB\": 12380,\n    \"ĠMaur\": 12381,\n    \"Ġsmiling\": 12382,\n    \"Ġstrikeouts\": 12383,\n    \"Ġpupils\": 12384,\n    \"Ġcomplications\": 12385,\n    \"ĠAdvanced\": 12386,\n    \"ĠMonetary\": 12387,\n    \"ĠTall\": 12388,\n    \"ĠALL\": 12389,\n    \"Ġcontributor\": 12390,\n    \"ĠAdvertising\": 12391,\n    \"Ġhorrific\": 12392,\n    \"Ġcompeted\": 12393,\n    \"ĠKenneth\": 12394,\n    \"Ġhailed\": 12395,\n    \"Ġbones\": 12396,\n    \"Ġbolster\": 12397,\n    \"ĠBoss\": 12398,\n    \"Ġhospitalized\": 12399,\n    \"ĠTelegraph\": 12400,\n    \"ĠIndependence\": 12401,\n    \"Ġdr\": 12402,\n    \"ĠHang\": 12403,\n    \"Ġdocumented\": 12404,\n    \"Ġsubtle\": 12405,\n    \"invest\": 12406,\n    \"Ġbounced\": 12407,\n    \"ĠMAN\": 12408,\n    \"Ġprofession\": 12409,\n    \"Ń\": 12410,\n    \"Ġexcellence\": 12411,\n    \"ĠInspector\": 12412,\n    \"ĠBL\": 12413,\n    \"Ġdisrupt\": 12414,\n    \"ĠWinston\": 12415,\n    \"ĠCommunist\": 12416,\n    \"ĠSharon\": 12417,\n    \"Ġmechanical\": 12418,\n    \"Ġtreats\": 12419,\n    \"Ġdesperately\": 12420,\n    \"ĠIndy\": 12421,\n    \"ĠGi\": 12422,\n    \"ĠComposite\": 12423,\n    \"ĠHeath\": 12424,\n    \"aser\": 12425,\n    \"ĠCardiff\": 12426,\n    \"ilit\": 12427,\n    \"Ġeased\": 12428,\n    \"Ġprospective\": 12429,\n    \"Ġcommissioned\": 12430,\n    \"Ġtire\": 12431,\n    \"Ġalign\": 12432,\n    \"Ġgesture\": 12433,\n    \"Ġweakened\": 12434,\n    \"URE\": 12435,\n    \"SN\": 12436,\n    \"Ġnationals\": 12437,\n    \"Ġrelies\": 12438,\n    \"ĠIRS\": 12439,\n    \"ĠCount\": 12440,\n    \"Ġmedicines\": 12441,\n    \"Ġcongress\": 12442,\n    \"Ġstranger\": 12443,\n    \"Qu\": 12444,\n    \"lessly\": 12445,\n    \"ĠQueens\": 12446,\n    \"ĠAlleg\": 12447,\n    \"uing\": 12448,\n    \"ĠWy\": 12449,\n    \"ĠMiguel\": 12450,\n    \"idi\": 12451,\n    \"Ġcivic\": 12452,\n    \"ĠPetro\": 12453,\n    \"endo\": 12454,\n    \"Obviously\": 12455,\n    \"Ġreflection\": 12456,\n    \"ĠStop\": 12457,\n    \"ĠFitzgerald\": 12458,\n    \"placed\": 12459,\n    \"shore\": 12460,\n    \"Ġcorrectly\": 12461,\n    \"ĠNE\": 12462,\n    \"amy\": 12463,\n    \"ĠCT\": 12464,\n    \"some\": 12465,\n    \"ĠMb\": 12466,\n    \"oi\": 12467,\n    \"ĠHogan\": 12468,\n    \"ĠInnovation\": 12469,\n    \"ĠVilla\": 12470,\n    \"ĠCAN\": 12471,\n    \"ĠCemetery\": 12472,\n    \"into\": 12473,\n    \"Ġquestionable\": 12474,\n    \"Ġcreator\": 12475,\n    \"rug\": 12476,\n    \"Ġsemifinals\": 12477,\n    \"mission\": 12478,\n    \"Ġcle\": 12479,\n    \"ĠWaters\": 12480,\n    \"ĠNixon\": 12481,\n    \"ĠBT\": 12482,\n    \"Ġassuming\": 12483,\n    \"ĠJer\": 12484,\n    \"ĠClay\": 12485,\n    \"pack\": 12486,\n    \"ĠCool\": 12487,\n    \"may\": 12488,\n    \"Ġdecor\": 12489,\n    \"Ġspike\": 12490,\n    \"ĠSomalia\": 12491,\n    \"ĠKarn\": 12492,\n    \"ĠDamascus\": 12493,\n    \"Shares\": 12494,\n    \"Ġsus\": 12495,\n    \"ĠMoss\": 12496,\n    \"Ġ1985\": 12497,\n    \"Ġsuperintendent\": 12498,\n    \"ĠResults\": 12499,\n    \"Ġspends\": 12500,\n    \"prom\": 12501,\n    \"Ġshipped\": 12502,\n    \"Ġlaundering\": 12503,\n    \"ĠLeslie\": 12504,\n    \"Ġmeteor\": 12505,\n    \"Ġabandon\": 12506,\n    \"Ġdeliberately\": 12507,\n    \"ĠSentinel\": 12508,\n    \"Ġfascinating\": 12509,\n    \"Ġenrollment\": 12510,\n    \"ĠExperts\": 12511,\n    \"ĠSimilarly\": 12512,\n    \"ĠCuomo\": 12513,\n    \"bor\": 12514,\n    \"Ġune\": 12515,\n    \"neutral\": 12516,\n    \"Ġhamstring\": 12517,\n    \"Ġnegotiated\": 12518,\n    \"zes\": 12519,\n    \"ĠLeo\": 12520,\n    \"ĠDoctor\": 12521,\n    \"Ġcurriculum\": 12522,\n    \"ĠFocus\": 12523,\n    \"Ġtravels\": 12524,\n    \"Ġbeverage\": 12525,\n    \"ĠIncluding\": 12526,\n    \"tz\": 12527,\n    \"type\": 12528,\n    \"ĠRange\": 12529,\n    \"Ġfloods\": 12530,\n    \"Ġcoached\": 12531,\n    \"Ġdominance\": 12532,\n    \"letico\": 12533,\n    \"ĠRafael\": 12534,\n    \"Ġpredictions\": 12535,\n    \"Ġprosperity\": 12536,\n    \"ĠCav\": 12537,\n    \"Ġclinics\": 12538,\n    \"ĠBanking\": 12539,\n    \"ĠComing\": 12540,\n    \"ears\": 12541,\n    \"ĠKaepernick\": 12542,\n    \"ĠBlvd\": 12543,\n    \"Ġretained\": 12544,\n    \"isions\": 12545,\n    \"Ġko\": 12546,\n    \"Ġensemble\": 12547,\n    \"Ġprecise\": 12548,\n    \"Ġcompact\": 12549,\n    \"MD\": 12550,\n    \"ĠJet\": 12551,\n    \"ached\": 12552,\n    \"ĠTru\": 12553,\n    \"ĠBass\": 12554,\n    \"ĠIcon\": 12555,\n    \"Ġexcluding\": 12556,\n    \"sur\": 12557,\n    \"Ġconstruct\": 12558,\n    \"Ġvoiced\": 12559,\n    \"pan\": 12560,\n    \"Ġinability\": 12561,\n    \"Ġexc\": 12562,\n    \"Ġmate\": 12563,\n    \"Ġtrailing\": 12564,\n    \"Ġsuccessive\": 12565,\n    \"Ġbets\": 12566,\n    \"Ġgauge\": 12567,\n    \"Ġminorities\": 12568,\n    \"ĠIND\": 12569,\n    \"ĠVel\": 12570,\n    \"ĠGP\": 12571,\n    \"oid\": 12572,\n    \"bon\": 12573,\n    \"Ġpred\": 12574,\n    \"Ġdash\": 12575,\n    \"Ġperformer\": 12576,\n    \"Ġoccasional\": 12577,\n    \"aken\": 12578,\n    \"mes\": 12579,\n    \"America\": 12580,\n    \"Ġliver\": 12581,\n    \"Sp\": 12582,\n    \"Big\": 12583,\n    \"Ġwildfires\": 12584,\n    \"ĠJackie\": 12585,\n    \"ĠLed\": 12586,\n    \"ĠFinland\": 12587,\n    \"Ġjurors\": 12588,\n    \"olic\": 12589,\n    \"urance\": 12590,\n    \"ĠEdge\": 12591,\n    \"open\": 12592,\n    \"Ġscenarios\": 12593,\n    \"Ġglory\": 12594,\n    \"entry\": 12595,\n    \"ĠCoffee\": 12596,\n    \"rep\": 12597,\n    \"ĠChand\": 12598,\n    \"ĠVas\": 12599,\n    \"ĠIslamabad\": 12600,\n    \"Ġbur\": 12601,\n    \"ĠFle\": 12602,\n    \"ĠEdition\": 12603,\n    \"Ġshoe\": 12604,\n    \"ï¸ı\": 12605,\n    \"**\": 12606,\n    \"tle\": 12607,\n    \"ĠEb\": 12608,\n    \"keeping\": 12609,\n    \"ĠBasketball\": 12610,\n    \"ĠVon\": 12611,\n    \"ĠCF\": 12612,\n    \"MENT\": 12613,\n    \"amm\": 12614,\n    \"ĠFernando\": 12615,\n    \"Ġcompares\": 12616,\n    \"ĠDouble\": 12617,\n    \"Ġconvictions\": 12618,\n    \"Ġatop\": 12619,\n    \"Ġcops\": 12620,\n    \"Ġremembers\": 12621,\n    \"Ġlacking\": 12622,\n    \"dom\": 12623,\n    \"itate\": 12624,\n    \"ĠBeauty\": 12625,\n    \"Ġdevelops\": 12626,\n    \"ĠGor\": 12627,\n    \"Ġfunctional\": 12628,\n    \"ĠCOUNTY\": 12629,\n    \"ĠUpon\": 12630,\n    \"Ġsprint\": 12631,\n    \"Ġinjection\": 12632,\n    \"Ġminors\": 12633,\n    \"ĠTamil\": 12634,\n    \"ĠGat\": 12635,\n    \"101\": 12636,\n    \"ety\": 12637,\n    \"Ġdrum\": 12638,\n    \"Ġtasked\": 12639,\n    \"Ġpact\": 12640,\n    \"Ġ170\": 12641,\n    \"MR\": 12642,\n    \"ĠRamos\": 12643,\n    \"Ġcandy\": 12644,\n    \"Sc\": 12645,\n    \"iced\": 12646,\n    \"Ġsupermarket\": 12647,\n    \"Ġworrying\": 12648,\n    \"Ġsellers\": 12649,\n    \"ĠTag\": 12650,\n    \".:\": 12651,\n    \"Ġmixture\": 12652,\n    \"oting\": 12653,\n    \"Bl\": 12654,\n    \"ĠLl\": 12655,\n    \"ĠJal\": 12656,\n    \"ican\": 12657,\n    \"ĠBid\": 12658,\n    \"country\": 12659,\n    \"ĠStrategy\": 12660,\n    \"Ġadverse\": 12661,\n    \"Ġplunged\": 12662,\n    \"ĠMit\": 12663,\n    \"Ġstark\": 12664,\n    \"aton\": 12665,\n    \"Ġbooking\": 12666,\n    \"Tr\": 12667,\n    \"Ġcontainers\": 12668,\n    \"Ġvintage\": 12669,\n    \"ĠPit\": 12670,\n    \"Ġsurfaced\": 12671,\n    \"Ġindependently\": 12672,\n    \"Ġdetection\": 12673,\n    \"ĠBeyon\": 12674,\n    \"Ġcasualties\": 12675,\n    \"Ġstabbing\": 12676,\n    \"oved\": 12677,\n    \"Ġbarred\": 12678,\n    \"Ġthereby\": 12679,\n    \"Ġpartnered\": 12680,\n    \"Ġposing\": 12681,\n    \"ĠShannon\": 12682,\n    \"ĠChapel\": 12683,\n    \"Ġtechnically\": 12684,\n    \"uous\": 12685,\n    \"Â»\": 12686,\n    \"ometer\": 12687,\n    \"Ġwildfire\": 12688,\n    \"share\": 12689,\n    \"heart\": 12690,\n    \"Ġammunition\": 12691,\n    \"Ġthrive\": 12692,\n    \"ĠStre\": 12693,\n    \"GP\": 12694,\n    \"cÃ©\": 12695,\n    \"ĠMonaco\": 12696,\n    \"goal\": 12697,\n    \"ĠUm\": 12698,\n    \"ĠHSBC\": 12699,\n    \"ĠHilton\": 12700,\n    \"ĠViv\": 12701,\n    \"ĠKell\": 12702,\n    \"Ġdecisive\": 12703,\n    \"Ġmotive\": 12704,\n    \"amo\": 12705,\n    \"feld\": 12706,\n    \"ĠWH\": 12707,\n    \"iry\": 12708,\n    \"ulu\": 12709,\n    \"ĠSchneider\": 12710,\n    \"Ġcampaigning\": 12711,\n    \"Ġseparately\": 12712,\n    \"igo\": 12713,\n    \"ĠED\": 12714,\n    \"ĠRamirez\": 12715,\n    \"Ġmetro\": 12716,\n    \"ĠPatel\": 12717,\n    \"ĠChi\": 12718,\n    \"ĠAudi\": 12719,\n    \"Ġcharacteristics\": 12720,\n    \"Ġrestart\": 12721,\n    \"Ġkeyboard\": 12722,\n    \"ĠSD\": 12723,\n    \"his\": 12724,\n    \"biz\": 12725,\n    \"ĠSoft\": 12726,\n    \"ĠGrammy\": 12727,\n    \"Ġcontested\": 12728,\n    \"Ġweekends\": 12729,\n    \"Ġ112\": 12730,\n    \"Ġcycling\": 12731,\n    \"Ġhealthier\": 12732,\n    \"ija\": 12733,\n    \"Ġheader\": 12734,\n    \"Ġemploy\": 12735,\n    \"İ\": 12736,\n    \"Ġshortages\": 12737,\n    \"ĠAsk\": 12738,\n    \"ĠIvanka\": 12739,\n    \"Ġpartisan\": 12740,\n    \"Ġflowing\": 12741,\n    \"Ġcave\": 12742,\n    \"ENS\": 12743,\n    \"Ġups\": 12744,\n    \"read\": 12745,\n    \"ouch\": 12746,\n    \"Ġ102\": 12747,\n    \"Ġforming\": 12748,\n    \"bot\": 12749,\n    \"bie\": 12750,\n    \"Ġenrolled\": 12751,\n    \"Ġconcussion\": 12752,\n    \"Ġaffidavit\": 12753,\n    \"Ġmysterious\": 12754,\n    \"uries\": 12755,\n    \"ĠMang\": 12756,\n    \"Ġauthentic\": 12757,\n    \"Ġmetrics\": 12758,\n    \"ĠTwins\": 12759,\n    \"Ġprep\": 12760,\n    \"IJ\": 12761,\n    \"Ġdesired\": 12762,\n    \"ĠDiv\": 12763,\n    \"wall\": 12764,\n    \"ĠTab\": 12765,\n    \"Ġcompet\": 12766,\n    \"Ġrelied\": 12767,\n    \"Ġinequality\": 12768,\n    \"Ġmanual\": 12769,\n    \"ĠBucks\": 12770,\n    \"agging\": 12771,\n    \"Ġcorporation\": 12772,\n    \"Ġbanner\": 12773,\n    \"Ġgraphics\": 12774,\n    \"Ġaccurately\": 12775,\n    \"ĠMeeting\": 12776,\n    \"Ġconsult\": 12777,\n    \"ser\": 12778,\n    \"Ġprotesting\": 12779,\n    \"Ġhurting\": 12780,\n    \"omed\": 12781,\n    \"tes\": 12782,\n    \"Ġrode\": 12783,\n    \"Ġstartups\": 12784,\n    \"Ġhanding\": 12785,\n    \"ĠNest\": 12786,\n    \"Ġconsistency\": 12787,\n    \"anned\": 12788,\n    \"dem\": 12789,\n    \"ĠLyon\": 12790,\n    \"ĠCompetition\": 12791,\n    \"Ġtricky\": 12792,\n    \"Ġcos\": 12793,\n    \"ĠBengals\": 12794,\n    \"arry\": 12795,\n    \"Ġunderwent\": 12796,\n    \"ĠKit\": 12797,\n    \"à\": 12798,\n    \"uploads\": 12799,\n    \"Ġskate\": 12800,\n    \"Ġ''\": 12801,\n    \"Ġjun\": 12802,\n    \"ĠContent\": 12803,\n    \"focused\": 12804,\n    \"lat\": 12805,\n    \"ĠExp\": 12806,\n    \"ought\": 12807,\n    \"Ġnightmare\": 12808,\n    \"ĠExpect\": 12809,\n    \"Ġprecisely\": 12810,\n    \"ĠMonica\": 12811,\n    \"Ġlobbying\": 12812,\n    \"ĠChester\": 12813,\n    \"ĠInvest\": 12814,\n    \"Former\": 12815,\n    \"Ġimminent\": 12816,\n    \"ĠNL\": 12817,\n    \"Ġcomparing\": 12818,\n    \"ĠChes\": 12819,\n    \"ede\": 12820,\n    \"ĠNobel\": 12821,\n    \"mers\": 12822,\n    \"ĠKin\": 12823,\n    \"ĠBoko\": 12824,\n    \"ount\": 12825,\n    \"Ġthoroughly\": 12826,\n    \"Ġscattered\": 12827,\n    \"sharing\": 12828,\n    \"markets\": 12829,\n    \"ĠMis\": 12830,\n    \"Ġambition\": 12831,\n    \"Ġpreference\": 12832,\n    \"Ġeffectiveness\": 12833,\n    \"rio\": 12834,\n    \"Ġheavyweight\": 12835,\n    \"Ġovert\": 12836,\n    \"anya\": 12837,\n    \"ĠKanye\": 12838,\n    \"ishi\": 12839,\n    \"Ġrewards\": 12840,\n    \"uled\": 12841,\n    \"bach\": 12842,\n    \"Ġemphasized\": 12843,\n    \"Ġapologize\": 12844,\n    \"ĠRecent\": 12845,\n    \"!!\": 12846,\n    \"Ġanimated\": 12847,\n    \"ĠExxon\": 12848,\n    \"Ġfruits\": 12849,\n    \"Ġstripped\": 12850,\n    \"fold\": 12851,\n    \"ĠIndonesian\": 12852,\n    \"ller\": 12853,\n    \"Ġdementia\": 12854,\n    \"Ġkidney\": 12855,\n    \"Ġhalted\": 12856,\n    \"years\": 12857,\n    \"Ġconcerts\": 12858,\n    \"Ġrefers\": 12859,\n    \"ĠFri\": 12860,\n    \"Your\": 12861,\n    \"irl\": 12862,\n    \"Ġleap\": 12863,\n    \"jud\": 12864,\n    \"ĠHugh\": 12865,\n    \"ĠFO\": 12866,\n    \"Ġsore\": 12867,\n    \"Ġkil\": 12868,\n    \"ĠMate\": 12869,\n    \"cci\": 12870,\n    \"Ġsetback\": 12871,\n    \"Ġtightening\": 12872,\n    \"keeper\": 12873,\n    \"ĠAlbany\": 12874,\n    \"Ġpolicymakers\": 12875,\n    \"Ġdisorders\": 12876,\n    \"ĠCBC\": 12877,\n    \"ĠDiaz\": 12878,\n    \"Ġmaps\": 12879,\n    \"Ġroutinely\": 12880,\n    \"Ġverify\": 12881,\n    \"Ġbash\": 12882,\n    \"ĠJinping\": 12883,\n    \"Ġdisasters\": 12884,\n    \"ĠMonroe\": 12885,\n    \"ĠLouise\": 12886,\n    \"JP\": 12887,\n    \"ĠNevertheless\": 12888,\n    \"Ġconcessions\": 12889,\n    \"ĠPog\": 12890,\n    \"going\": 12891,\n    \"ĠFifth\": 12892,\n    \"ĠJill\": 12893,\n    \"ICT\": 12894,\n    \"ĠFM\": 12895,\n    \"ĠSugar\": 12896,\n    \"ĠBarb\": 12897,\n    \"Ġmidway\": 12898,\n    \"Ġtin\": 12899,\n    \"ĠPic\": 12900,\n    \"ĠPL\": 12901,\n    \"Ġleaks\": 12902,\n    \"Ġgrief\": 12903,\n    \"Ġtattoo\": 12904,\n    \"`\": 12905,\n    \"Ġment\": 12906,\n    \"ĠNu\": 12907,\n    \"Ġmarry\": 12908,\n    \"Ġdiving\": 12909,\n    \"Ġ1982\": 12910,\n    \"Ġcoin\": 12911,\n    \"ĠPoc\": 12912,\n    \"Ġstarred\": 12913,\n    \"ĠRiverside\": 12914,\n    \"Ġsidelined\": 12915,\n    \"Ġminers\": 12916,\n    \"STON\": 12917,\n    \"Ġbelongs\": 12918,\n    \"ĠSantos\": 12919,\n    \"ĠTechnical\": 12920,\n    \"aco\": 12921,\n    \"Ġadvise\": 12922,\n    \"Ġstreams\": 12923,\n    \"Ġcooler\": 12924,\n    \"ĠHE\": 12925,\n    \"Ġordering\": 12926,\n    \"ĠTask\": 12927,\n    \"ĠACT\": 12928,\n    \"ĠAnton\": 12929,\n    \"Ġcertification\": 12930,\n    \"ĠLeafs\": 12931,\n    \"ĠTS\": 12932,\n    \"ĠSerbia\": 12933,\n    \"azi\": 12934,\n    \"inks\": 12935,\n    \"ĠEST\": 12936,\n    \"Ġrelay\": 12937,\n    \"Â°\": 12938,\n    \"Ġdisappearance\": 12939,\n    \"ĠRomania\": 12940,\n    \"Ġoven\": 12941,\n    \"Ġowed\": 12942,\n    \"ĠStrip\": 12943,\n    \"ulated\": 12944,\n    \"UC\": 12945,\n    \"ITE\": 12946,\n    \"bling\": 12947,\n    \"Then\": 12948,\n    \"ppy\": 12949,\n    \"Ġunlimited\": 12950,\n    \"Ġcalories\": 12951,\n    \"Ġmerchandise\": 12952,\n    \"Ġblonde\": 12953,\n    \"ĠSpicer\": 12954,\n    \"performing\": 12955,\n    \"Ġimpl\": 12956,\n    \"Ġplates\": 12957,\n    \"Ġmosque\": 12958,\n    \"Ġdemon\": 12959,\n    \"Ġought\": 12960,\n    \"Ġdumped\": 12961,\n    \"Ġtracked\": 12962,\n    \"even\": 12963,\n    \"Ġstabil\": 12964,\n    \"imet\": 12965,\n    \"ĠLiga\": 12966,\n    \"ugh\": 12967,\n    \"ther\": 12968,\n    \"agar\": 12969,\n    \"Ġarchitect\": 12970,\n    \"Ġallocated\": 12971,\n    \"ĠJoey\": 12972,\n    \"Ġmarathon\": 12973,\n    \"master\": 12974,\n    \"ĠBert\": 12975,\n    \"Ġast\": 12976,\n    \"ĠEbola\": 12977,\n    \"ĠConservation\": 12978,\n    \"nic\": 12979,\n    \"Ġparallel\": 12980,\n    \"Ġinmate\": 12981,\n    \"Ġlocate\": 12982,\n    \"Ġdistribute\": 12983,\n    \"guard\": 12984,\n    \"Ġtackling\": 12985,\n    \"ential\": 12986,\n    \"Ġvi\": 12987,\n    \"Ġcups\": 12988,\n    \"Ġrhythm\": 12989,\n    \"Ġendured\": 12990,\n    \"ĠHub\": 12991,\n    \"ois\": 12992,\n    \"ĠLiberals\": 12993,\n    \"ĠRedskins\": 12994,\n    \"ĠEP\": 12995,\n    \"ĠKnox\": 12996,\n    \"fr\": 12997,\n    \"Ġmassacre\": 12998,\n    \"oka\": 12999,\n    \"Ġcompl\": 13000,\n    \"raft\": 13001,\n    \"ĠPublished\": 13002,\n    \"Ġattraction\": 13003,\n    \"ĠStephens\": 13004,\n    \"ility\": 13005,\n    \"ĠPul\": 13006,\n    \"ĠCapt\": 13007,\n    \"Ġexploded\": 13008,\n    \"Ġexceeded\": 13009,\n    \"lying\": 13010,\n    \"Ġcal\": 13011,\n    \"Mart\": 13012,\n    \"Ġpaintings\": 13013,\n    \"inate\": 13014,\n    \"ĠBrendan\": 13015,\n    \"Ġfortune\": 13016,\n    \"onductor\": 13017,\n    \"Ġphysicians\": 13018,\n    \"ĠStudy\": 13019,\n    \"ĠBul\": 13020,\n    \"ĠModern\": 13021,\n    \"HD\": 13022,\n    \"ĠBour\": 13023,\n    \"Ġtying\": 13024,\n    \"Ġ1967\": 13025,\n    \"Ġlighter\": 13026,\n    \"Ġtoss\": 13027,\n    \"inspired\": 13028,\n    \"Ġgreeted\": 13029,\n    \"Ġcycl\": 13030,\n    \"Ġverified\": 13031,\n    \"Ġmerit\": 13032,\n    \"sign\": 13033,\n    \"lder\": 13034,\n    \"Ġdebts\": 13035,\n    \"ĠSnyder\": 13036,\n    \"Ġamendments\": 13037,\n    \"Ġindicators\": 13038,\n    \"ĠDortmund\": 13039,\n    \"then\": 13040,\n    \"ĠListen\": 13041,\n    \"ĠFB\": 13042,\n    \"ref\": 13043,\n    \"ĠIoT\": 13044,\n    \"ĠBrewers\": 13045,\n    \"ĠLeadership\": 13046,\n    \"ĠNicolas\": 13047,\n    \"ĠBody\": 13048,\n    \"Ġsam\": 13049,\n    \"ĠAdvisor\": 13050,\n    \"Ġcord\": 13051,\n    \"Ġabuses\": 13052,\n    \"ĠPortuguese\": 13053,\n    \"Ġflown\": 13054,\n    \"VR\": 13055,\n    \"Ġconsumed\": 13056,\n    \"Ġreass\": 13057,\n    \"Ġalien\": 13058,\n    \"Ġrivalry\": 13059,\n    \"ĠREPORT\": 13060,\n    \"ĠRush\": 13061,\n    \"Ġdirecting\": 13062,\n    \"Ġsearches\": 13063,\n    \"ĠHP\": 13064,\n    \"ĠRoll\": 13065,\n    \"ĠFay\": 13066,\n    \"ĠClare\": 13067,\n    \"Ġhaul\": 13068,\n    \"Ġriot\": 13069,\n    \"Ġsettlements\": 13070,\n    \"Ġnorm\": 13071,\n    \"Ġaccelerated\": 13072,\n    \"ĠLok\": 13073,\n    \"Ġclever\": 13074,\n    \"Ġhyd\": 13075,\n    \"Ġstats\": 13076,\n    \"ĠHull\": 13077,\n    \"kers\": 13078,\n    \"Ġbuys\": 13079,\n    \"uter\": 13080,\n    \"Ġfue\": 13081,\n    \"https\": 13082,\n    \"UD\": 13083,\n    \"Ġisolation\": 13084,\n    \"Ġsuspend\": 13085,\n    \"ĠRules\": 13086,\n    \"ĠCircle\": 13087,\n    \"ĠHopefully\": 13088,\n    \"played\": 13089,\n    \"âĢ³\": 13090,\n    \"ĠPRE\": 13091,\n    \"sim\": 13092,\n    \"edd\": 13093,\n    \"ĠProperties\": 13094,\n    \"Ġbeans\": 13095,\n    \"Ġrevive\": 13096,\n    \"ĠBir\": 13097,\n    \"oug\": 13098,\n    \"Ġmob\": 13099,\n    \"Ġshowdown\": 13100,\n    \"iman\": 13101,\n    \"Ġpap\": 13102,\n    \"Ġvol\": 13103,\n    \"wu\": 13104,\n    \"Ġdiver\": 13105,\n    \"Ġpill\": 13106,\n    \"ĠMarlins\": 13107,\n    \"ĠLamar\": 13108,\n    \"Ġpersistent\": 13109,\n    \"Ġcondolences\": 13110,\n    \"ĠThor\": 13111,\n    \"Ab\": 13112,\n    \"Ġimpress\": 13113,\n    \"ĠRaptors\": 13114,\n    \"Ġreferences\": 13115,\n    \"Ġstiff\": 13116,\n    \"ĠBash\": 13117,\n    \"eding\": 13118,\n    \"Ġmurders\": 13119,\n    \"ĠGene\": 13120,\n    \"ĠManila\": 13121,\n    \"Ġbrokers\": 13122,\n    \"Ms\": 13123,\n    \"start\": 13124,\n    \"ĠDhabi\": 13125,\n    \"etz\": 13126,\n    \"Ġsubmission\": 13127,\n    \"ĠSchmidt\": 13128,\n    \"ĠPersonal\": 13129,\n    \"ĠBeverly\": 13130,\n    \"ĠMovie\": 13131,\n    \"ĠLamb\": 13132,\n    \"Ġplacement\": 13133,\n    \"Ġfolk\": 13134,\n    \"Ġfrequency\": 13135,\n    \"Ġplanted\": 13136,\n    \"Ġtwins\": 13137,\n    \"prov\": 13138,\n    \"rec\": 13139,\n    \"Ġpermanently\": 13140,\n    \"Ġcoordination\": 13141,\n    \"ĠCart\": 13142,\n    \"Ġobstacles\": 13143,\n    \"Ġliterature\": 13144,\n    \"Ġtu\": 13145,\n    \"Ġchill\": 13146,\n    \"ĠReserved\": 13147,\n    \"Ġlovers\": 13148,\n    \"ĠOutside\": 13149,\n    \"Ġslideshow\": 13150,\n    \"ĠGru\": 13151,\n    \"Ġty\": 13152,\n    \"Ġsalad\": 13153,\n    \"Ġlaboratory\": 13154,\n    \"ĠHolt\": 13155,\n    \"Ġ103\": 13156,\n    \"urb\": 13157,\n    \"ĠOrganisation\": 13158,\n    \"ĠAndrews\": 13159,\n    \"Ġrecipient\": 13160,\n    \"arch\": 13161,\n    \"Ġbleeding\": 13162,\n    \"ĠPand\": 13163,\n    \"Ġoverturned\": 13164,\n    \"Ġlistened\": 13165,\n    \"Ġclause\": 13166,\n    \"Ġnationalist\": 13167,\n    \"Ġresumed\": 13168,\n    \"ĠCout\": 13169,\n    \"ĠPride\": 13170,\n    \"Ġlayers\": 13171,\n    \"ĠBella\": 13172,\n    \"Ġreversed\": 13173,\n    \"Ġpriest\": 13174,\n    \"ĠFX\": 13175,\n    \"Ġalbeit\": 13176,\n    \"Ġhalfway\": 13177,\n    \"Ġcotton\": 13178,\n    \"ĠCarey\": 13179,\n    \"ĠTE\": 13180,\n    \"OCK\": 13181,\n    \"Ġbuck\": 13182,\n    \"ributes\": 13183,\n    \"ea\": 13184,\n    \"Ġfancy\": 13185,\n    \"ĠBuc\": 13186,\n    \"Ġbans\": 13187,\n    \"uters\": 13188,\n    \"Ġliabilities\": 13189,\n    \"ĠSou\": 13190,\n    \"ĠBernie\": 13191,\n    \"Ġintervene\": 13192,\n    \"food\": 13193,\n    \"ĠNDP\": 13194,\n    \"Ġinsist\": 13195,\n    \"Ġcontracted\": 13196,\n    \"hawk\": 13197,\n    \"),\\\"\": 13198,\n    \"ĠDawn\": 13199,\n    \"Ġmol\": 13200,\n    \"Ġcommissioners\": 13201,\n    \"Ġstranded\": 13202,\n    \"Ġoverwhelmed\": 13203,\n    \"Ġrecipes\": 13204,\n    \"Ġva\": 13205,\n    \"Ġrad\": 13206,\n    \"Ġscare\": 13207,\n    \"rez\": 13208,\n    \"Ġeliminating\": 13209,\n    \"Ġresc\": 13210,\n    \"ĠBreak\": 13211,\n    \"chn\": 13212,\n    \"Ġdelight\": 13213,\n    \"iot\": 13214,\n    \"Ġfreely\": 13215,\n    \"TI\": 13216,\n    \"ĠBluetooth\": 13217,\n    \"ĠMonth\": 13218,\n    \"ĠFlor\": 13219,\n    \"ĠFreddie\": 13220,\n    \"Ġtrailed\": 13221,\n    \"Ġinvestigative\": 13222,\n    \"Ġimposing\": 13223,\n    \"Ġattracting\": 13224,\n    \"awk\": 13225,\n    \"ĠSherman\": 13226,\n    \"Ġsucceeded\": 13227,\n    \"Ġvent\": 13228,\n    \"Ġreconciliation\": 13229,\n    \"ĠCel\": 13230,\n    \"ĠThroughout\": 13231,\n    \"ĠDowntown\": 13232,\n    \"ĠBrother\": 13233,\n    \"Ġtraditions\": 13234,\n    \"Ġmir\": 13235,\n    \"Ġstamp\": 13236,\n    \"tery\": 13237,\n    \"etti\": 13238,\n    \"isch\": 13239,\n    \"tic\": 13240,\n    \"Ġbanning\": 13241,\n    \"loss\": 13242,\n    \"ĠSpeedway\": 13243,\n    \"Ġstalled\": 13244,\n    \"ĠEN\": 13245,\n    \"ASH\": 13246,\n    \"thing\": 13247,\n    \"ĠAppeals\": 13248,\n    \"rac\": 13249,\n    \"Ġdistress\": 13250,\n    \"ĠConservatives\": 13251,\n    \"ĠPremium\": 13252,\n    \"usa\": 13253,\n    \"Ġslump\": 13254,\n    \"imm\": 13255,\n    \"ĠSupp\": 13256,\n    \"ĠWong\": 13257,\n    \"Ġdistant\": 13258,\n    \"Ġ104\": 13259,\n    \"Ġtide\": 13260,\n    \"ĠNorfolk\": 13261,\n    \"ĠYang\": 13262,\n    \"Ġsmashed\": 13263,\n    \"ĠBarrett\": 13264,\n    \"inho\": 13265,\n    \"Ġrobbed\": 13266,\n    \"ĠFarmers\": 13267,\n    \"filled\": 13268,\n    \"BT\": 13269,\n    \"Ġautumn\": 13270,\n    \"Ġtemple\": 13271,\n    \"ĠJacobs\": 13272,\n    \"Ġprecipitation\": 13273,\n    \"ĠHours\": 13274,\n    \"ĠFlight\": 13275,\n    \"Ġbeside\": 13276,\n    \"ĠOre\": 13277,\n    \"!)\": 13278,\n    \"ĠTurnbull\": 13279,\n    \"Ġpig\": 13280,\n    \"Ġcooling\": 13281,\n    \"Ġservers\": 13282,\n    \"oriented\": 13283,\n    \"Ġlocks\": 13284,\n    \"ĠSears\": 13285,\n    \"aving\": 13286,\n    \"ĠQuick\": 13287,\n    \"ĠGlob\": 13288,\n    \"ĠMining\": 13289,\n    \"Ġhorizon\": 13290,\n    \"arians\": 13291,\n    \"ĠOm\": 13292,\n    \"writing\": 13293,\n    \"Ġbelieving\": 13294,\n    \"Ġbon\": 13295,\n    \"Ġmounted\": 13296,\n    \"Ġpunt\": 13297,\n    \"ucci\": 13298,\n    \"uzz\": 13299,\n    \"cul\": 13300,\n    \"Ġkiss\": 13301,\n    \"ĠOnt\": 13302,\n    \"ĠCyprus\": 13303,\n    \"Ġrelying\": 13304,\n    \"Ġpiano\": 13305,\n    \"Ġcure\": 13306,\n    \"Ġcontinuously\": 13307,\n    \"ĠNobody\": 13308,\n    \"ĠBund\": 13309,\n    \"osis\": 13310,\n    \"ĠAurora\": 13311,\n    \"ĠBach\": 13312,\n    \"ĠKendall\": 13313,\n    \"Ġechoed\": 13314,\n    \"iable\": 13315,\n    \"Ġconscious\": 13316,\n    \"Ġmonster\": 13317,\n    \"omo\": 13318,\n    \"proof\": 13319,\n    \"ĠNate\": 13320,\n    \"Ġfilmmaker\": 13321,\n    \"ĠNaj\": 13322,\n    \"Ġvendor\": 13323,\n    \"ĠFoot\": 13324,\n    \"ĠChang\": 13325,\n    \"ĠFest\": 13326,\n    \"Ġselfie\": 13327,\n    \"Ġenters\": 13328,\n    \"ĠConor\": 13329,\n    \"ĠMosul\": 13330,\n    \"ĠWHAT\": 13331,\n    \"Ġwa\": 13332,\n    \"ĠGamb\": 13333,\n    \"osta\": 13334,\n    \"Ġcautioned\": 13335,\n    \"ĠTucker\": 13336,\n    \"ĠAirways\": 13337,\n    \"Ġvisitor\": 13338,\n    \"ĠÂ·\": 13339,\n    \"ĠRevolution\": 13340,\n    \"aching\": 13341,\n    \"Ġearliest\": 13342,\n    \"ĠQuality\": 13343,\n    \"Ġshorts\": 13344,\n    \"ube\": 13345,\n    \"ĠOperation\": 13346,\n    \"ĠSabha\": 13347,\n    \"Ġstrengths\": 13348,\n    \"ikes\": 13349,\n    \"Ġsexy\": 13350,\n    \"Ġrot\": 13351,\n    \"ibles\": 13352,\n    \"Ġcolours\": 13353,\n    \"THE\": 13354,\n    \"ailed\": 13355,\n    \"Ġwoke\": 13356,\n    \"ĠEmbassy\": 13357,\n    \"Ġinfamous\": 13358,\n    \"rov\": 13359,\n    \"State\": 13360,\n    \"âĢ¦.\": 13361,\n    \"Ġpond\": 13362,\n    \"Ġcapt\": 13363,\n    \"fore\": 13364,\n    \"De\": 13365,\n    \"Ġedited\": 13366,\n    \"self\": 13367,\n    \"Hey\": 13368,\n    \"Ġportrait\": 13369,\n    \"ĠManufact\": 13370,\n    \"ĠStand\": 13371,\n    \"Ġcontenders\": 13372,\n    \"':\": 13373,\n    \"acker\": 13374,\n    \"Ġwithdrawn\": 13375,\n    \"ĠBraves\": 13376,\n    \"ĠHosp\": 13377,\n    \"changing\": 13378,\n    \"ĠBag\": 13379,\n    \"Ġadjustment\": 13380,\n    \"ĠCousins\": 13381,\n    \"ĠAAP\": 13382,\n    \"Ġfi\": 13383,\n    \"Ġoutdoors\": 13384,\n    \"Ġlacked\": 13385,\n    \"BM\": 13386,\n    \"ĠWHO\": 13387,\n    \"ĠPST\": 13388,\n    \"ĠLuck\": 13389,\n    \"Ġassisting\": 13390,\n    \"ĠGround\": 13391,\n    \"ĠTeen\": 13392,\n    \"ĠOle\": 13393,\n    \"Ġembarrassing\": 13394,\n    \"ĠWalt\": 13395,\n    \"ĠVision\": 13396,\n    \"ĠFal\": 13397,\n    \"ĠZoo\": 13398,\n    \"ĠWorth\": 13399,\n    \"ĠFloyd\": 13400,\n    \"ĠGujarat\": 13401,\n    \"Ġtipped\": 13402,\n    \"Ġfam\": 13403,\n    \"ĠDad\": 13404,\n    \"Ġworship\": 13405,\n    \"Ġtyre\": 13406,\n    \"Ġrebuilding\": 13407,\n    \"Ġqualities\": 13408,\n    \"ĠLives\": 13409,\n    \"Ġbeats\": 13410,\n    \"Ġ450\": 13411,\n    \"Ġexisted\": 13412,\n    \"ĠGeorg\": 13413,\n    \"Ġpoured\": 13414,\n    \"rows\": 13415,\n    \"ĠOx\": 13416,\n    \"ĠSid\": 13417,\n    \"Ġmac\": 13418,\n    \"Ġteaches\": 13419,\n    \"ĠEli\": 13420,\n    \"alla\": 13421,\n    \"Ġdownside\": 13422,\n    \"ĠBend\": 13423,\n    \"non\": 13424,\n    \"ĠArmenia\": 13425,\n    \"Ġcultures\": 13426,\n    \"ĠMae\": 13427,\n    \"Ġduration\": 13428,\n    \"ĠAthletics\": 13429,\n    \"Ġjuvenile\": 13430,\n    \"Ġlid\": 13431,\n    \"Ġbankers\": 13432,\n    \"Ġoverview\": 13433,\n    \"wy\": 13434,\n    \"Ġorbit\": 13435,\n    \"Vs\": 13436,\n    \"because\": 13437,\n    \"Ps\": 13438,\n    \"ĠFran\": 13439,\n    \"Ġtouring\": 13440,\n    \"Ġwary\": 13441,\n    \"Ġ106\": 13442,\n    \"Ġlaser\": 13443,\n    \"ĠVij\": 13444,\n    \"âĦ¢\": 13445,\n    \"Ġsurrender\": 13446,\n    \"press\": 13447,\n    \"rees\": 13448,\n    \"NO\": 13449,\n    \"ĠShortly\": 13450,\n    \"ĠKor\": 13451,\n    \"edu\": 13452,\n    \"Ġhatred\": 13453,\n    \"Ġtee\": 13454,\n    \"Ġfamously\": 13455,\n    \"Ġkeeper\": 13456,\n    \"ND\": 13457,\n    \"Ġreduces\": 13458,\n    \"HC\": 13459,\n    \"Ġhay\": 13460,\n    \"Ġunnamed\": 13461,\n    \"ĠTes\": 13462,\n    \"Ġattackers\": 13463,\n    \"ĠFew\": 13464,\n    \"ĠRichards\": 13465,\n    \"Ġ1968\": 13466,\n    \"Ġspeeches\": 13467,\n    \"Ġcybersecurity\": 13468,\n    \"ĠInfrastructure\": 13469,\n    \"Ġ07\": 13470,\n    \"ENCE\": 13471,\n    \"uties\": 13472,\n    \"Ġanxious\": 13473,\n    \"ĠGang\": 13474,\n    \"Ġannouncements\": 13475,\n    \"lette\": 13476,\n    \"oret\": 13477,\n    \"ĠRockies\": 13478,\n    \"ĠEmployees\": 13479,\n    \"ĠThrones\": 13480,\n    \"Ġhugely\": 13481,\n    \"Ġclin\": 13482,\n    \"ĠHob\": 13483,\n    \"Ġfraction\": 13484,\n    \"ĠOfficial\": 13485,\n    \"ĠMariners\": 13486,\n    \"ĠElse\": 13487,\n    \"Ġsanctuary\": 13488,\n    \"ĠPhotograph\": 13489,\n    \"Ġreopen\": 13490,\n    \"lf\": 13491,\n    \"hm\": 13492,\n    \"vest\": 13493,\n    \"Ġspeeding\": 13494,\n    \"Ġtooth\": 13495,\n    \"ĠShi\": 13496,\n    \"ĠTitle\": 13497,\n    \"ĠMes\": 13498,\n    \"ĠJobs\": 13499,\n    \"fair\": 13500,\n    \"ĠDanish\": 13501,\n    \"ĠMalik\": 13502,\n    \"Ġlaughed\": 13503,\n    \"Ġnavy\": 13504,\n    \"ĠActress\": 13505,\n    \"ĠWilliamson\": 13506,\n    \"overs\": 13507,\n    \"Ġreckless\": 13508,\n    \"Ġjo\": 13509,\n    \"otic\": 13510,\n    \"Ġassaulting\": 13511,\n    \"Ġpri\": 13512,\n    \"ĠPi\": 13513,\n    \"Ġlesser\": 13514,\n    \"Ġtit\": 13515,\n    \"Ġdat\": 13516,\n    \"Ġnail\": 13517,\n    \"ĠMarathon\": 13518,\n    \"ĠGren\": 13519,\n    \"ĠDol\": 13520,\n    \"Ġjointly\": 13521,\n    \"Ġamended\": 13522,\n    \"mine\": 13523,\n    \"ĠBashar\": 13524,\n    \"ĠHyundai\": 13525,\n    \"Ġuncovered\": 13526,\n    \"Ġeducated\": 13527,\n    \"atti\": 13528,\n    \"pres\": 13529,\n    \"ĠBRE\": 13530,\n    \"Ġya\": 13531,\n    \"Bank\": 13532,\n    \"odd\": 13533,\n    \"lit\": 13534,\n    \"ĠLinks\": 13535,\n    \"Ġswitching\": 13536,\n    \"itte\": 13537,\n    \"ĠSind\": 13538,\n    \"erved\": 13539,\n    \"Ġ**\": 13540,\n    \"Ġpositively\": 13541,\n    \"Ġfrankly\": 13542,\n    \"Ġrevenge\": 13543,\n    \"ĠTrinity\": 13544,\n    \"ĠCDC\": 13545,\n    \"Ġthreatens\": 13546,\n    \"Ġhammer\": 13547,\n    \"NET\": 13548,\n    \"ĠMut\": 13549,\n    \"Ġsy\": 13550,\n    \"Ġunidentified\": 13551,\n    \"icken\": 13552,\n    \"Ġdrills\": 13553,\n    \"Ġtense\": 13554,\n    \"Ġforeigners\": 13555,\n    \"OST\": 13556,\n    \"Ġethical\": 13557,\n    \"ĠDurham\": 13558,\n    \"ĠQual\": 13559,\n    \"Ġterritories\": 13560,\n    \"Ġid\": 13561,\n    \"hor\": 13562,\n    \"enders\": 13563,\n    \"Mc\": 13564,\n    \"OV\": 13565,\n    \"percent\": 13566,\n    \"Ġdom\": 13567,\n    \"Ġupward\": 13568,\n    \"Ġamb\": 13569,\n    \"Ġvisas\": 13570,\n    \"zan\": 13571,\n    \"Ãĥ\": 13572,\n    \"Ġundocumented\": 13573,\n    \"Ġsuburbs\": 13574,\n    \"Ġhydro\": 13575,\n    \"ĠJob\": 13576,\n    \"ĠAdelaide\": 13577,\n    \"oya\": 13578,\n    \"ĠSR\": 13579,\n    \"ĠMick\": 13580,\n    \"Ġconsolidation\": 13581,\n    \"Ġemotionally\": 13582,\n    \"ĠHop\": 13583,\n    \"Her\": 13584,\n    \"Ġloses\": 13585,\n    \"ĠMoto\": 13586,\n    \"eled\": 13587,\n    \"Ġregulated\": 13588,\n    \"ental\": 13589,\n    \"Ġencountered\": 13590,\n    \"Ġhop\": 13591,\n    \"ĠTrafford\": 13592,\n    \"Ġsticks\": 13593,\n    \"Ġveto\": 13594,\n    \"Ġexpose\": 13595,\n    \"Ġstretched\": 13596,\n    \"fin\": 13597,\n    \"inance\": 13598,\n    \"chair\": 13599,\n    \"ĠGareth\": 13600,\n    \"ĠPil\": 13601,\n    \"ĠHammond\": 13602,\n    \"Ġserial\": 13603,\n    \"omy\": 13604,\n    \"Ġcellphone\": 13605,\n    \"ĠClara\": 13606,\n    \"Ġreacted\": 13607,\n    \"ĠNic\": 13608,\n    \"ĠHomes\": 13609,\n    \"ĠBroadcasting\": 13610,\n    \"ĠFut\": 13611,\n    \"ĠSupply\": 13612,\n    \"assing\": 13613,\n    \"ĠNewman\": 13614,\n    \"Ġcharitable\": 13615,\n    \"ĠClayton\": 13616,\n    \"Ġsovereignty\": 13617,\n    \"Ġconvincing\": 13618,\n    \"ĠPrincipal\": 13619,\n    \"ĠHigher\": 13620,\n    \"ĠCut\": 13621,\n    \"ĠCarrie\": 13622,\n    \"ĠSpot\": 13623,\n    \"Sometimes\": 13624,\n    \"ĠJar\": 13625,\n    \"ĠConsider\": 13626,\n    \"ieu\": 13627,\n    \"Ġrefinery\": 13628,\n    \"Ġbloody\": 13629,\n    \"wheel\": 13630,\n    \"Ġcryptocurrencies\": 13631,\n    \"Fund\": 13632,\n    \"ĠSunderland\": 13633,\n    \"ĠEvents\": 13634,\n    \"âĢĭ\": 13635,\n    \"Ġaccidentally\": 13636,\n    \"deep\": 13637,\n    \"Ġfranc\": 13638,\n    \"bec\": 13639,\n    \"ĠHartford\": 13640,\n    \"Ġstellar\": 13641,\n    \"wright\": 13642,\n    \"kick\": 13643,\n    \"UG\": 13644,\n    \"ĠBeast\": 13645,\n    \"Ġrefusal\": 13646,\n    \"ĠRoberto\": 13647,\n    \"ĠDixon\": 13648,\n    \"ĠDiane\": 13649,\n    \"name\": 13650,\n    \"asts\": 13651,\n    \"ĠCharter\": 13652,\n    \"Ġfueled\": 13653,\n    \"Ġcontents\": 13654,\n    \"Ġaccessing\": 13655,\n    \"Ġtroubles\": 13656,\n    \"Ġtops\": 13657,\n    \"Ġdebuted\": 13658,\n    \"icating\": 13659,\n    \"Ġinvestigator\": 13660,\n    \"Ġsubscribing\": 13661,\n    \"Ġcoordinated\": 13662,\n    \"ĠFil\": 13663,\n    \"six\": 13664,\n    \"teen\": 13665,\n    \"Ġwithdrew\": 13666,\n    \"ĠGilbert\": 13667,\n    \"Ġ1983\": 13668,\n    \"arsity\": 13669,\n    \"Ġimagination\": 13670,\n    \"Ġhandgun\": 13671,\n    \"ĠAlibaba\": 13672,\n    \"Ġbug\": 13673,\n    \"Ġ107\": 13674,\n    \"ĠCOMP\": 13675,\n    \"ĠSomething\": 13676,\n    \"Ġreliability\": 13677,\n    \"ĠFCC\": 13678,\n    \"ĠFowler\": 13679,\n    \"Ġsingled\": 13680,\n    \"nom\": 13681,\n    \"Ġknocking\": 13682,\n    \"Ġmeddling\": 13683,\n    \"Ġdetermining\": 13684,\n    \"reports\": 13685,\n    \"Ġshade\": 13686,\n    \"ĠSN\": 13687,\n    \"anto\": 13688,\n    \"Ġcomplaining\": 13689,\n    \"ĠNan\": 13690,\n    \"WS\": 13691,\n    \"Ġyoungsters\": 13692,\n    \"Il\": 13693,\n    \"ĠKaw\": 13694,\n    \"ĠProp\": 13695,\n    \"ĠCell\": 13696,\n    \"ĠHurricanes\": 13697,\n    \"Ġpublicity\": 13698,\n    \"ĠXin\": 13699,\n    \"rial\": 13700,\n    \"ICO\": 13701,\n    \"Ġsupervision\": 13702,\n    \"ĠSpotify\": 13703,\n    \"ĠNewport\": 13704,\n    \"Ġprince\": 13705,\n    \"anche\": 13706,\n    \"Ġsubscriber\": 13707,\n    \"ĠVic\": 13708,\n    \"ACT\": 13709,\n    \"ĠRaf\": 13710,\n    \"ĠActing\": 13711,\n    \"Ġcollusion\": 13712,\n    \"pet\": 13713,\n    \"isl\": 13714,\n    \"Ġcommerce\": 13715,\n    \"Health\": 13716,\n    \"ĠAbraham\": 13717,\n    \"pri\": 13718,\n    \"Ġlightweight\": 13719,\n    \"Ġinsurer\": 13720,\n    \"Like\": 13721,\n    \"Ġhelmet\": 13722,\n    \"Ġevac\": 13723,\n    \"look\": 13724,\n    \"ĠNaval\": 13725,\n    \"160\": 13726,\n    \"ĠFleet\": 13727,\n    \"vol\": 13728,\n    \"Ġexpired\": 13729,\n    \"ĠKlein\": 13730,\n    \"ĠEmmy\": 13731,\n    \"ABLE\": 13732,\n    \"ĠMorocco\": 13733,\n    \"ĠTrip\": 13734,\n    \"uted\": 13735,\n    \"Ġnos\": 13736,\n    \"ĠVista\": 13737,\n    \"mas\": 13738,\n    \"ĠRocky\": 13739,\n    \"ĠFlint\": 13740,\n    \"enberg\": 13741,\n    \"ĠBrow\": 13742,\n    \"Ġsignatures\": 13743,\n    \"Ġpolar\": 13744,\n    \"ajo\": 13745,\n    \"Ġendorsement\": 13746,\n    \"Ġreservations\": 13747,\n    \"LIN\": 13748,\n    \"anny\": 13749,\n    \"elli\": 13750,\n    \"last\": 13751,\n    \"Ġoversee\": 13752,\n    \"cm\": 13753,\n    \"ĠOilers\": 13754,\n    \"Are\": 13755,\n    \"Ġjudiciary\": 13756,\n    \"onte\": 13757,\n    \"ĠTrack\": 13758,\n    \"Ġsupervisor\": 13759,\n    \"erk\": 13760,\n    \"isher\": 13761,\n    \"Ġintact\": 13762,\n    \"Ġslid\": 13763,\n    \"icals\": 13764,\n    \"paid\": 13765,\n    \"ĠMAR\": 13766,\n    \"lement\": 13767,\n    \"ĠLiu\": 13768,\n    \"ĠLarge\": 13769,\n    \"ĠWings\": 13770,\n    \"pect\": 13771,\n    \"ĠRum\": 13772,\n    \"Ġanalyzed\": 13773,\n    \"Ġemploys\": 13774,\n    \"arte\": 13775,\n    \"ims\": 13776,\n    \"ĠEventually\": 13777,\n    \"Ġaffiliated\": 13778,\n    \"Ġhospitality\": 13779,\n    \"ĠSprint\": 13780,\n    \"Ġresolutions\": 13781,\n    \"Ġliquor\": 13782,\n    \"ĠNAFTA\": 13783,\n    \"ANY\": 13784,\n    \"Ġradiation\": 13785,\n    \"ĠProv\": 13786,\n    \"Ġpause\": 13787,\n    \"ĠTMZ\": 13788,\n    \"Ġelbow\": 13789,\n    \"Ġresilience\": 13790,\n    \"ĠParents\": 13791,\n    \"mus\": 13792,\n    \"ĠSafe\": 13793,\n    \"Ġinterpretation\": 13794,\n    \"Ġraced\": 13795,\n    \"IND\": 13796,\n    \"KR\": 13797,\n    \"Ġhinted\": 13798,\n    \"ĠErin\": 13799,\n    \"ĠBahrain\": 13800,\n    \"Ġcredentials\": 13801,\n    \"eless\": 13802,\n    \"Ġprocurement\": 13803,\n    \"ĠWebb\": 13804,\n    \"ĠLowe\": 13805,\n    \"ĠNak\": 13806,\n    \"ĠLearning\": 13807,\n    \"zh\": 13808,\n    \"Ġdipped\": 13809,\n    \"ĠSuite\": 13810,\n    \"Ġmisdemeanor\": 13811,\n    \"ALE\": 13812,\n    \"Ġstrengthened\": 13813,\n    \"ĠSophie\": 13814,\n    \"Ġconfirms\": 13815,\n    \"Ġrac\": 13816,\n    \"gey\": 13817,\n    \"Ġshootout\": 13818,\n    \"Ġble\": 13819,\n    \"Ġcircles\": 13820,\n    \"ĠChef\": 13821,\n    \"Ġcomprised\": 13822,\n    \"ĠSantiago\": 13823,\n    \"Ġfeud\": 13824,\n    \"beat\": 13825,\n    \"Ġstaffers\": 13826,\n    \"Ġacute\": 13827,\n    \"ski\": 13828,\n    \"Ġpolled\": 13829,\n    \"ĠKur\": 13830,\n    \"ĠJen\": 13831,\n    \"ĠUltimately\": 13832,\n    \"anded\": 13833,\n    \"ĠHoney\": 13834,\n    \"Ġannounces\": 13835,\n    \"Ġamateur\": 13836,\n    \"around\": 13837,\n    \"Ġfunctioning\": 13838,\n    \"group\": 13839,\n    \"ĠSqu\": 13840,\n    \"Where\": 13841,\n    \"Ġvoid\": 13842,\n    \"ĠSandra\": 13843,\n    \"isers\": 13844,\n    \"Ġhelicopters\": 13845,\n    \"ĠGym\": 13846,\n    \"ĠWol\": 13847,\n    \"mouth\": 13848,\n    \"Ġsubjected\": 13849,\n    \"ici\": 13850,\n    \"ually\": 13851,\n    \"ĠWash\": 13852,\n    \"ĠLindsay\": 13853,\n    \"ĠVers\": 13854,\n    \"Ġjumps\": 13855,\n    \"Ġneglect\": 13856,\n    \"ĠKuwait\": 13857,\n    \"fund\": 13858,\n    \"ĭ\": 13859,\n    \"ather\": 13860,\n    \"lly\": 13861,\n    \"ei\": 13862,\n    \"Although\": 13863,\n    \".''\": 13864,\n    \"Ġunhappy\": 13865,\n    \"Ġpills\": 13866,\n    \"Ġmagical\": 13867,\n    \"Ġdro\": 13868,\n    \"Ġinviting\": 13869,\n    \"ĠJohnston\": 13870,\n    \"oving\": 13871,\n    \"450\": 13872,\n    \"ĠMerc\": 13873,\n    \"Ġadmitting\": 13874,\n    \"Ġinsisting\": 13875,\n    \"ĠCru\": 13876,\n    \"ĠResource\": 13877,\n    \"oir\": 13878,\n    \"Ġcomplexity\": 13879,\n    \"ĠRoth\": 13880,\n    \"ĠCher\": 13881,\n    \"July\": 13882,\n    \"raf\": 13883,\n    \"Ġaggregate\": 13884,\n    \"Ġhelm\": 13885,\n    \"uclear\": 13886,\n    \"olan\": 13887,\n    \"Ġoffenses\": 13888,\n    \"ĠWolves\": 13889,\n    \"ĠFu\": 13890,\n    \"ĠPierce\": 13891,\n    \"Ġemailed\": 13892,\n    \"ĠStra\": 13893,\n    \"Ġpedestrians\": 13894,\n    \"ĠER\": 13895,\n    \"ĠConway\": 13896,\n    \"Ġblowing\": 13897,\n    \"CLOSE\": 13898,\n    \"hab\": 13899,\n    \"ĠGreene\": 13900,\n    \"Ġconfessed\": 13901,\n    \"ĠTorres\": 13902,\n    \"ĠHolocaust\": 13903,\n    \"Ġrepay\": 13904,\n    \"Ġdemonstrates\": 13905,\n    \"ĠPool\": 13906,\n    \"gent\": 13907,\n    \"Ġdeleted\": 13908,\n    \"Ġ$$\": 13909,\n    \"ĠSO\": 13910,\n    \"Ġdri\": 13911,\n    \"ĠNeg\": 13912,\n    \"ĠVP\": 13913,\n    \"ĠPF\": 13914,\n    \"ĠPrep\": 13915,\n    \"Ġorganizing\": 13916,\n    \"icker\": 13917,\n    \"Ġmanufactured\": 13918,\n    \"enson\": 13919,\n    \"adas\": 13920,\n    \"Ġwines\": 13921,\n    \"Ġmachinery\": 13922,\n    \"Ġspecialists\": 13923,\n    \"ĠDetective\": 13924,\n    \"ĠDL\": 13925,\n    \"Op\": 13926,\n    \"Ġquicker\": 13927,\n    \"ĠPenguins\": 13928,\n    \"Engine\": 13929,\n    \"zone\": 13930,\n    \"Ġsequence\": 13931,\n    \"ĠLost\": 13932,\n    \"Ġwarmer\": 13933,\n    \"ĠEthiopia\": 13934,\n    \"Ġaffirmed\": 13935,\n    \"fest\": 13936,\n    \"resses\": 13937,\n    \"Ġsoap\": 13938,\n    \"Ġbooth\": 13939,\n    \"Ġnotorious\": 13940,\n    \"amin\": 13941,\n    \"Ġpursued\": 13942,\n    \"ĠCer\": 13943,\n    \"ĠSB\": 13944,\n    \"Ġlivestock\": 13945,\n    \"Ġtrace\": 13946,\n    \"Ġrespects\": 13947,\n    \"arden\": 13948,\n    \"April\": 13949,\n    \"Ġ128\": 13950,\n    \"ĠSaid\": 13951,\n    \"ennial\": 13952,\n    \"Ġnamely\": 13953,\n    \"ĠBot\": 13954,\n    \"Ġ108\": 13955,\n    \"ĠLem\": 13956,\n    \"nell\": 13957,\n    \"Ġconfirming\": 13958,\n    \"Ġlogged\": 13959,\n    \"Ġprofound\": 13960,\n    \"elo\": 13961,\n    \"ĠChambers\": 13962,\n    \"RT\": 13963,\n    \"Ġnewer\": 13964,\n    \"Ġsideline\": 13965,\n    \"ĠCardinal\": 13966,\n    \"este\": 13967,\n    \"Ġnarrowly\": 13968,\n    \"Ġcompromised\": 13969,\n    \"Ġpolicing\": 13970,\n    \"Ġporn\": 13971,\n    \"Ġarc\": 13972,\n    \"Ġlearnt\": 13973,\n    \"INE\": 13974,\n    \"step\": 13975,\n    \"ĠDomin\": 13976,\n    \"Ġwaist\": 13977,\n    \"Ġboycott\": 13978,\n    \"mitted\": 13979,\n    \"iffs\": 13980,\n    \"ground\": 13981,\n    \"ĠMaterials\": 13982,\n    \"Ġceasefire\": 13983,\n    \"Right\": 13984,\n    \"ĠZen\": 13985,\n    \"estyle\": 13986,\n    \"Thank\": 13987,\n    \"ĠOnePlus\": 13988,\n    \"ĠMLS\": 13989,\n    \"Ġconstituents\": 13990,\n    \"oster\": 13991,\n    \"ĠProsecutor\": 13992,\n    \"Ġpriorit\": 13993,\n    \"ĠDebbie\": 13994,\n    \"ĠExpand\": 13995,\n    \"uv\": 13996,\n    \"Ġintegrate\": 13997,\n    \"Ġimmun\": 13998,\n    \"Ġdisciplinary\": 13999,\n    \"ĠImm\": 14000,\n    \"Ġja\": 14001,\n    \"Ġgardens\": 14002,\n    \"ĠHim\": 14003,\n    \"obe\": 14004,\n    \"Ġhitter\": 14005,\n    \"Ġbullets\": 14006,\n    \"Ġevolving\": 14007,\n    \"ĠScientists\": 14008,\n    \"Michael\": 14009,\n    \"ĠDO\": 14010,\n    \"Ġunbelievable\": 14011,\n    \"Ġlooming\": 14012,\n    \"Ġdownturn\": 14013,\n    \"Ġmentality\": 14014,\n    \"Ġreopened\": 14015,\n    \"Ġash\": 14016,\n    \"ĠChapman\": 14017,\n    \"Ġloop\": 14018,\n    \"ĠUT\": 14019,\n    \"ĠTier\": 14020,\n    \"Ġunaware\": 14021,\n    \"Ġgratitude\": 14022,\n    \"Ġperforms\": 14023,\n    \"olk\": 14024,\n    \"Ġ\\\"(\": 14025,\n    \"Ġlacks\": 14026,\n    \"Ġinstructed\": 14027,\n    \"ĠRecreation\": 14028,\n    \"sample\": 14029,\n    \"Ġrequesting\": 14030,\n    \"Canada\": 14031,\n    \"Ġsupposedly\": 14032,\n    \"ĠHardy\": 14033,\n    \"Ġholder\": 14034,\n    \"change\": 14035,\n    \"ĠDominic\": 14036,\n    \"ĠXavier\": 14037,\n    \"Ġlig\": 14038,\n    \"Ġcandid\": 14039,\n    \"ĠRab\": 14040,\n    \"Ġconferences\": 14041,\n    \"ĠBurton\": 14042,\n    \"Dr\": 14043,\n    \"Ġmunicipalities\": 14044,\n    \"Ġcrushed\": 14045,\n    \"Ġseekers\": 14046,\n    \"ĠCitizens\": 14047,\n    \"Ġheightened\": 14048,\n    \"ĠCasino\": 14049,\n    \"Ġdesktop\": 14050,\n    \"Ġwhoever\": 14051,\n    \"ĠImpact\": 14052,\n    \"Ġcocktail\": 14053,\n    \"Ġphilanthrop\": 14054,\n    \"ĠSAN\": 14055,\n    \"ĠPreston\": 14056,\n    \"Ġobesity\": 14057,\n    \"Ġrestrict\": 14058,\n    \"ĠKab\": 14059,\n    \"ĠProvidence\": 14060,\n    \"Ġscar\": 14061,\n    \"ĠChart\": 14062,\n    \"Ġbosses\": 14063,\n    \"ĠRate\": 14064,\n    \"Ġsav\": 14065,\n    \"pay\": 14066,\n    \"Ġtransplant\": 14067,\n    \"ĠNoble\": 14068,\n    \"child\": 14069,\n    \"Ġconclusions\": 14070,\n    \"FI\": 14071,\n    \"Ġsack\": 14072,\n    \"Ġexperimental\": 14073,\n    \"holder\": 14074,\n    \"oca\": 14075,\n    \"herty\": 14076,\n    \"ĠMT\": 14077,\n    \"Ġcatcher\": 14078,\n    \"LY\": 14079,\n    \"Ġgrams\": 14080,\n    \"reet\": 14081,\n    \"Ġadaptation\": 14082,\n    \"Ġhumble\": 14083,\n    \"Ġbot\": 14084,\n    \"Ġidentical\": 14085,\n    \"ication\": 14086,\n    \"ifer\": 14087,\n    \"ĠCrow\": 14088,\n    \"Ġregain\": 14089,\n    \"ĠLightning\": 14090,\n    \"Ġkg\": 14091,\n    \"Ġcomposed\": 14092,\n    \"Ġcorrespondent\": 14093,\n    \"Ġreunion\": 14094,\n    \"Ġobserve\": 14095,\n    \"Ġcomprising\": 14096,\n    \"Ġimpeachment\": 14097,\n    \"Ġresh\": 14098,\n    \"Ġlemon\": 14099,\n    \"ĠSnap\": 14100,\n    \"Ġproprietary\": 14101,\n    \"een\": 14102,\n    \"ourt\": 14103,\n    \"Ġdetective\": 14104,\n    \"Ġlabels\": 14105,\n    \"Ġcorridor\": 14106,\n    \"ĠClinic\": 14107,\n    \"Ġarra\": 14108,\n    \"ĠPearl\": 14109,\n    \"Ġinformal\": 14110,\n    \"ĠUnd\": 14111,\n    \"ĠVenezuelan\": 14112,\n    \"Ġpeninsula\": 14113,\n    \"Ġdefeating\": 14114,\n    \"Ġsyndrome\": 14115,\n    \"iere\": 14116,\n    \"Ġspite\": 14117,\n    \"bag\": 14118,\n    \"aran\": 14119,\n    \"Ġspecialized\": 14120,\n    \"ĠAA\": 14121,\n    \"ĠLyn\": 14122,\n    \"Ġinstrumental\": 14123,\n    \"Smith\": 14124,\n    \"Ġpivotal\": 14125,\n    \"Ġnightclub\": 14126,\n    \"ĠCob\": 14127,\n    \"Ġcolorful\": 14128,\n    \"Ġartwork\": 14129,\n    \"Ġ1981\": 14130,\n    \"Ġdawn\": 14131,\n    \"erville\": 14132,\n    \"uated\": 14133,\n    \"ief\": 14134,\n    \"Ġlinking\": 14135,\n    \"ĠOw\": 14136,\n    \"Ġappreci\": 14137,\n    \"Ġreductions\": 14138,\n    \"elling\": 14139,\n    \"Ġsalmon\": 14140,\n    \"bb\": 14141,\n    \"ĠPhillip\": 14142,\n    \"yle\": 14143,\n    \"Ġassure\": 14144,\n    \"Ġdiscretion\": 14145,\n    \"Ġefficiently\": 14146,\n    \"ĠMau\": 14147,\n    \"abil\": 14148,\n    \"Ġintentionally\": 14149,\n    \"Ġactivated\": 14150,\n    \"Ġimmense\": 14151,\n    \"ĠStrategic\": 14152,\n    \"Ġcheating\": 14153,\n    \"ĠTrend\": 14154,\n    \"ĠSamantha\": 14155,\n    \"Ġcomple\": 14156,\n    \"Ġhack\": 14157,\n    \"ĠSerie\": 14158,\n    \"ĠText\": 14159,\n    \"Ġstylish\": 14160,\n    \"ĠFaith\": 14161,\n    \"ĠGST\": 14162,\n    \"Ġexterior\": 14163,\n    \"Ġblessing\": 14164,\n    \"Ġblanket\": 14165,\n    \"Ġcooked\": 14166,\n    \"Ġretaliation\": 14167,\n    \"Ġtro\": 14168,\n    \"Ġshelves\": 14169,\n    \"rose\": 14170,\n    \"ĠGram\": 14171,\n    \"Ġsho\": 14172,\n    \"ĠArgentine\": 14173,\n    \"Ġclerk\": 14174,\n    \"specific\": 14175,\n    \"Ġagreeing\": 14176,\n    \"Ġstandout\": 14177,\n    \"black\": 14178,\n    \"Ġtrending\": 14179,\n    \"Ġviolate\": 14180,\n    \"Get\": 14181,\n    \"Ã±o\": 14182,\n    \"ĠOpt\": 14183,\n    \"ĠFrankfurt\": 14184,\n    \"ĠFranco\": 14185,\n    \"eness\": 14186,\n    \"Ġlining\": 14187,\n    \"Ġzoo\": 14188,\n    \"oil\": 14189,\n    \"lia\": 14190,\n    \"rab\": 14191,\n    \"Ġorganize\": 14192,\n    \"Ġwoods\": 14193,\n    \"Ġscan\": 14194,\n    \"Ġurgency\": 14195,\n    \"Ġoccurring\": 14196,\n    \"Ġreliance\": 14197,\n    \"Ġconcepts\": 14198,\n    \"Ġeligibility\": 14199,\n    \"0000\": 14200,\n    \"ĠBrief\": 14201,\n    \"Ġabusive\": 14202,\n    \"ĠBench\": 14203,\n    \"Ġrub\": 14204,\n    \"ĠDil\": 14205,\n    \"Ġmount\": 14206,\n    \"Ġmaturity\": 14207,\n    \"ĠNut\": 14208,\n    \"nee\": 14209,\n    \"enc\": 14210,\n    \"Ġgunfire\": 14211,\n    \"ĠKill\": 14212,\n    \"Ġgates\": 14213,\n    \"Ġflower\": 14214,\n    \"iol\": 14215,\n    \"Ġshaped\": 14216,\n    \"Ġundoubtedly\": 14217,\n    \"Ġbackgrounds\": 14218,\n    \"ĠComplex\": 14219,\n    \"\\\":{\\\"\": 14220,\n    \"Ġnaming\": 14221,\n    \"Ġmonument\": 14222,\n    \"Ġoh\": 14223,\n    \"Ġembedded\": 14224,\n    \"Ġbang\": 14225,\n    \"ĠKro\": 14226,\n    \"Ġaggression\": 14227,\n    \"ĠMits\": 14228,\n    \"During\": 14229,\n    \"ĠEp\": 14230,\n    \"iners\": 14231,\n    \"ĠAnaheim\": 14232,\n    \"Ġrom\": 14233,\n    \"Ġoutgoing\": 14234,\n    \"Ġfulfill\": 14235,\n    \"Ġreminds\": 14236,\n    \"Ġren\": 14237,\n    \"à¤\": 14238,\n    \"ĠSue\": 14239,\n    \"Ġrefresh\": 14240,\n    \"Ġlif\": 14241,\n    \"Ġfil\": 14242,\n    \"ĠLead\": 14243,\n    \"Ġregulate\": 14244,\n    \"ĠTeachers\": 14245,\n    \"Ġclarify\": 14246,\n    \"obs\": 14247,\n    \"Ġblasted\": 14248,\n    \"ĠAx\": 14249,\n    \"Ġflavors\": 14250,\n    \"Ġmega\": 14251,\n    \"Ġhurdles\": 14252,\n    \"Ġinspector\": 14253,\n    \"ĠSalvador\": 14254,\n    \"Ġprescribed\": 14255,\n    \"Ġrenovation\": 14256,\n    \"OUR\": 14257,\n    \"Ġutil\": 14258,\n    \"ĠBradford\": 14259,\n    \"Ġwasted\": 14260,\n    \"Ġlineman\": 14261,\n    \"Ġpalm\": 14262,\n    \"icate\": 14263,\n    \"Ġoverseeing\": 14264,\n    \"otted\": 14265,\n    \"ĠRapids\": 14266,\n    \"Ġjustified\": 14267,\n    \"aby\": 14268,\n    \"Ġextends\": 14269,\n    \"Ġoath\": 14270,\n    \"bow\": 14271,\n    \"ĠRivera\": 14272,\n    \"Jan\": 14273,\n    \"ĠImran\": 14274,\n    \"Ġforests\": 14275,\n    \"ĠShel\": 14276,\n    \"ĠBrun\": 14277,\n    \"Ġaerial\": 14278,\n    \"ĠNOW\": 14279,\n    \"PAR\": 14280,\n    \"Ġbeverages\": 14281,\n    \"ettel\": 14282,\n    \"Ġfragile\": 14283,\n    \"Ġcodes\": 14284,\n    \"Į\": 14285,\n    \"abel\": 14286,\n    \"Watch\": 14287,\n    \"road\": 14288,\n    \"Ġdismissal\": 14289,\n    \"ĠRosa\": 14290,\n    \"Ġcrunch\": 14291,\n    \"²\": 14292,\n    \"Ġinnovations\": 14293,\n    \"Ġhabitat\": 14294,\n    \"Ġforefront\": 14295,\n    \"ĠKoch\": 14296,\n    \"ĠChevrolet\": 14297,\n    \"Ġwheelchair\": 14298,\n    \"Ġconsiderably\": 14299,\n    \"Ġexpenditures\": 14300,\n    \"Ġtexts\": 14301,\n    \"Ġprompt\": 14302,\n    \"Ġskating\": 14303,\n    \"Ġpetroleum\": 14304,\n    \"ĠICC\": 14305,\n    \"Ġvit\": 14306,\n    \"fit\": 14307,\n    \"Ġprolonged\": 14308,\n    \"ĠLucy\": 14309,\n    \"Ġcho\": 14310,\n    \"Ġrocked\": 14311,\n    \"ĠBrom\": 14312,\n    \"Ġfreed\": 14313,\n    \"Ġyours\": 14314,\n    \"ĠEden\": 14315,\n    \"Ġmonitored\": 14316,\n    \"asted\": 14317,\n    \"Ġoversees\": 14318,\n    \"ieri\": 14319,\n    \"Ġideology\": 14320,\n    \"ĠFine\": 14321,\n    \"tering\": 14322,\n    \"Top\": 14323,\n    \"Ġdamp\": 14324,\n    \"uta\": 14325,\n    \"Ġlethal\": 14326,\n    \"Ġpurple\": 14327,\n    \"udge\": 14328,\n    \"ĠChemical\": 14329,\n    \"ĠPetersburg\": 14330,\n    \"Ġwarns\": 14331,\n    \"Ġcollectively\": 14332,\n    \"Ġâ\": 14333,\n    \"Ġplaintiffs\": 14334,\n    \"ĠBoris\": 14335,\n    \"Ġsheep\": 14336,\n    \"oves\": 14337,\n    \"ĠAuthor\": 14338,\n    \"Ġcampuses\": 14339,\n    \"Ġdestroying\": 14340,\n    \"Ġgloves\": 14341,\n    \"Ġcease\": 14342,\n    \"Ġdelegates\": 14343,\n    \"Ġpreceded\": 14344,\n    \"realDonaldTrump\": 14345,\n    \"Ġforwards\": 14346,\n    \"erton\": 14347,\n    \"ĠBuzzFeed\": 14348,\n    \"Ġoccupation\": 14349,\n    \"ĠLegion\": 14350,\n    \"Ġstir\": 14351,\n    \"Ġshale\": 14352,\n    \"Ġterrific\": 14353,\n    \"Ġnewborn\": 14354,\n    \"Ġstandoff\": 14355,\n    \"OWN\": 14356,\n    \"Ġmuscles\": 14357,\n    \"ĠHerman\": 14358,\n    \"ĠLiz\": 14359,\n    \"ĠExperience\": 14360,\n    \"ĠSuccess\": 14361,\n    \"ĠHispanic\": 14362,\n    \"ĠCCTV\": 14363,\n    \"Ġcomplement\": 14364,\n    \"ĠBing\": 14365,\n    \"Ġprem\": 14366,\n    \"ĠJohannes\": 14367,\n    \"Ġdent\": 14368,\n    \"itar\": 14369,\n    \"ĠHein\": 14370,\n    \"ĠNicola\": 14371,\n    \"Ġconcludes\": 14372,\n    \"ĠKhal\": 14373,\n    \"Ġparish\": 14374,\n    \"Ġshaking\": 14375,\n    \"ĠSchw\": 14376,\n    \"mod\": 14377,\n    \"ĠLil\": 14378,\n    \"Ã±a\": 14379,\n    \"ĠBog\": 14380,\n    \"ĠFight\": 14381,\n    \"Ġgre\": 14382,\n    \"Ġfel\": 14383,\n    \"Ġheal\": 14384,\n    \"err\": 14385,\n    \"TM\": 14386,\n    \"airo\": 14387,\n    \"health\": 14388,\n    \"Ġswings\": 14389,\n    \"Ġtier\": 14390,\n    \"anka\": 14391,\n    \"ribune\": 14392,\n    \"emouth\": 14393,\n    \"ĠBloom\": 14394,\n    \"Ġowing\": 14395,\n    \"Tech\": 14396,\n    \"Ġdough\": 14397,\n    \"Ġbatch\": 14398,\n    \"ĠLion\": 14399,\n    \"ĠZamb\": 14400,\n    \"Ġcrashing\": 14401,\n    \"ĠXL\": 14402,\n    \"ppers\": 14403,\n    \"ĠDoctors\": 14404,\n    \"ĠSor\": 14405,\n    \"video\": 14406,\n    \"Ġcigarettes\": 14407,\n    \"ĠBoxing\": 14408,\n    \"Ġconstitute\": 14409,\n    \"Ġconcentrate\": 14410,\n    \"ĠArmenian\": 14411,\n    \"Ġsemester\": 14412,\n    \"position\": 14413,\n    \"emic\": 14414,\n    \"ĠNYC\": 14415,\n    \"ĠCampus\": 14416,\n    \"Ġalternate\": 14417,\n    \"Ġexped\": 14418,\n    \"Ġpublishers\": 14419,\n    \"2015\": 14420,\n    \"Ġunanimous\": 14421,\n    \"ĠPrevious\": 14422,\n    \"Ġwellness\": 14423,\n    \"ĠCreative\": 14424,\n    \"edy\": 14425,\n    \"AGE\": 14426,\n    \"ĠCavs\": 14427,\n    \"Ġ1978\": 14428,\n    \"Ġfu\": 14429,\n    \"ĠTata\": 14430,\n    \"ĠChoice\": 14431,\n    \"Ġwoes\": 14432,\n    \"ĠCable\": 14433,\n    \"Ġ~\": 14434,\n    \"ĠGem\": 14435,\n    \"Ġconsolidated\": 14436,\n    \"ĠManitoba\": 14437,\n    \"Cloud\": 14438,\n    \"Ġrounded\": 14439,\n    \"ĠVentura\": 14440,\n    \"Ġshark\": 14441,\n    \"Ġdresses\": 14442,\n    \"Ġtraction\": 14443,\n    \"eda\": 14444,\n    \"Ġdiv\": 14445,\n    \"Ġdental\": 14446,\n    \"Wh\": 14447,\n    \"ĠGig\": 14448,\n    \"ĠBoyd\": 14449,\n    \"ĠTransit\": 14450,\n    \"Ġtelevised\": 14451,\n    \"SON\": 14452,\n    \"ĠVince\": 14453,\n    \"Ġcloses\": 14454,\n    \"apt\": 14455,\n    \"ĠWheeler\": 14456,\n    \"ĠTyson\": 14457,\n    \"Ġforensic\": 14458,\n    \"Ġpunished\": 14459,\n    \"Ġseas\": 14460,\n    \"Ġnavigation\": 14461,\n    \"Ġprecedent\": 14462,\n    \"Ġextremist\": 14463,\n    \"Ġcomposite\": 14464,\n    \"PO\": 14465,\n    \"Ġsurvivor\": 14466,\n    \"ĠVale\": 14467,\n    \"gars\": 14468,\n    \"HT\": 14469,\n    \"ĠRiyadh\": 14470,\n    \"Ġrevival\": 14471,\n    \"ĠPayne\": 14472,\n    \"Ġcollaborative\": 14473,\n    \"ĠCustomers\": 14474,\n    \"ĠPf\": 14475,\n    \"Ġproves\": 14476,\n    \"erve\": 14477,\n    \"Ġelev\": 14478,\n    \"ĠPaper\": 14479,\n    \"Ġchore\": 14480,\n    \"Ġthriller\": 14481,\n    \"Ġstraw\": 14482,\n    \"cock\": 14483,\n    \"Gu\": 14484,\n    \"Ġaligned\": 14485,\n    \"ĠChronicle\": 14486,\n    \"Ġshouting\": 14487,\n    \"Ġ1976\": 14488,\n    \"Ġlightning\": 14489,\n    \"Ġworlds\": 14490,\n    \"ĠOpening\": 14491,\n    \"enton\": 14492,\n    \"ĠAna\": 14493,\n    \"ĠGol\": 14494,\n    \"ĠTechn\": 14495,\n    \"lis\": 14496,\n    \"Ġorientation\": 14497,\n    \"ĠArri\": 14498,\n    \"ĠPG\": 14499,\n    \"ross\": 14500,\n    \"Ġsank\": 14501,\n    \"LOS\": 14502,\n    \"ĠAllison\": 14503,\n    \"Ġsmiles\": 14504,\n    \"USD\": 14505,\n    \"Ġkits\": 14506,\n    \"Bar\": 14507,\n    \"ĠBri\": 14508,\n    \"Ġounces\": 14509,\n    \"ĠNielsen\": 14510,\n    \"eno\": 14511,\n    \"Ġ109\": 14512,\n    \"Ġnorms\": 14513,\n    \"Ġskip\": 14514,\n    \"180\": 14515,\n    \"Ġmonitors\": 14516,\n    \"2012\": 14517,\n    \"Ġincorporate\": 14518,\n    \"Ġmechanisms\": 14519,\n    \"ĠHack\": 14520,\n    \"ĠBomb\": 14521,\n    \"ĠGavin\": 14522,\n    \"ĠNatalie\": 14523,\n    \"Ġdiscusses\": 14524,\n    \"Ġassembled\": 14525,\n    \"Ġcognitive\": 14526,\n    \"owner\": 14527,\n    \"Ġgenuinely\": 14528,\n    \"Ġdisappear\": 14529,\n    \"ĠAK\": 14530,\n    \"Ġstal\": 14531,\n    \"Ġsoup\": 14532,\n    \"ĠFinn\": 14533,\n    \"Ġcares\": 14534,\n    \"Ġfinest\": 14535,\n    \"Ġtuned\": 14536,\n    \"ende\": 14537,\n    \"ĠStefan\": 14538,\n    \"Ġaccompanying\": 14539,\n    \"Ã®\": 14540,\n    \"Maybe\": 14541,\n    \"Ġoffender\": 14542,\n    \"TT\": 14543,\n    \"Ġ212\": 14544,\n    \"Ġvolleyball\": 14545,\n    \"needed\": 14546,\n    \"Ġquo\": 14547,\n    \"Ġdim\": 14548,\n    \"ĠHistorical\": 14549,\n    \"ĠLance\": 14550,\n    \"gmail\": 14551,\n    \"ĠGate\": 14552,\n    \"Ġdemonstrators\": 14553,\n    \"Ġdy\": 14554,\n    \"cia\": 14555,\n    \"ĠSteele\": 14556,\n    \"ĠJoan\": 14557,\n    \"ĠKerala\": 14558,\n    \"KA\": 14559,\n    \"ĠElectoral\": 14560,\n    \"Ġpaths\": 14561,\n    \"Ã¸\": 14562,\n    \"Ne\": 14563,\n    \"Ġaccepts\": 14564,\n    \"Ġlowering\": 14565,\n    \"Ġportions\": 14566,\n    \"ĠValencia\": 14567,\n    \"Ġfestivals\": 14568,\n    \"Ġgeneric\": 14569,\n    \"usk\": 14570,\n    \"ĠVernon\": 14571,\n    \"ĠOrioles\": 14572,\n    \"Ġrenewal\": 14573,\n    \"Ġbelonged\": 14574,\n    \"Ġbreathe\": 14575,\n    \"Ġ220\": 14576,\n    \"Ġrecruited\": 14577,\n    \"Ġlogic\": 14578,\n    \"Ġrecreation\": 14579,\n    \"Ġverbal\": 14580,\n    \"ĠHaz\": 14581,\n    \"double\": 14582,\n    \"Ġfavourites\": 14583,\n    \"Ġfundamentals\": 14584,\n    \"ĠSoc\": 14585,\n    \"360\": 14586,\n    \"SO\": 14587,\n    \"Ġalerted\": 14588,\n    \"Ġbriefed\": 14589,\n    \"ĠBruno\": 14590,\n    \"Ġseating\": 14591,\n    \"Ġfreight\": 14592,\n    \"ĠAmer\": 14593,\n    \"Ġwished\": 14594,\n    \"table\": 14595,\n    \"growth\": 14596,\n    \"ĠWent\": 14597,\n    \"Ġhilarious\": 14598,\n    \"Ġthroat\": 14599,\n    \"bet\": 14600,\n    \"gon\": 14601,\n    \"Ġample\": 14602,\n    \"hee\": 14603,\n    \"ĠHood\": 14604,\n    \"ĠIceland\": 14605,\n    \"ĠAnkara\": 14606,\n    \"iang\": 14607,\n    \"Ġpracticing\": 14608,\n    \"azer\": 14609,\n    \"Ġleaf\": 14610,\n    \"Ġhottest\": 14611,\n    \"Ġmarginal\": 14612,\n    \"Ġrevelations\": 14613,\n    \"ĠPrices\": 14614,\n    \"ĠLar\": 14615,\n    \"times\": 14616,\n    \"Ġhandles\": 14617,\n    \"ĠNaz\": 14618,\n    \"Ġinstitute\": 14619,\n    \"Ġtranslate\": 14620,\n    \"ĠJP\": 14621,\n    \"Ġsoared\": 14622,\n    \"Ġconsume\": 14623,\n    \"ĠTap\": 14624,\n    \"ĠCelebrity\": 14625,\n    \"ĠMayweather\": 14626,\n    \"ĠOracle\": 14627,\n    \"Ġmor\": 14628,\n    \"ANA\": 14629,\n    \"Ġpaperwork\": 14630,\n    \"aste\": 14631,\n    \"Ġdil\": 14632,\n    \"Ġdecorated\": 14633,\n    \"Ġpromotional\": 14634,\n    \"ĠMerrill\": 14635,\n    \"Ġappliances\": 14636,\n    \"ĠCOP\": 14637,\n    \"Ġlips\": 14638,\n    \"ĠBrennan\": 14639,\n    \"ĠMile\": 14640,\n    \"ĠNetworks\": 14641,\n    \"ĠComment\": 14642,\n    \"ĠIb\": 14643,\n    \"ĠAgg\": 14644,\n    \"IDE\": 14645,\n    \"Ġinitiate\": 14646,\n    \"Ġknockout\": 14647,\n    \"Ġbargain\": 14648,\n    \"Ġaccordingly\": 14649,\n    \"bee\": 14650,\n    \"ĠGerald\": 14651,\n    \"Ġproblematic\": 14652,\n    \"Ġtrap\": 14653,\n    \"Ġfinalists\": 14654,\n    \"addy\": 14655,\n    \"would\": 14656,\n    \"Ġstrictly\": 14657,\n    \"ĠRamsey\": 14658,\n    \"Ġdownward\": 14659,\n    \"Ġextract\": 14660,\n    \"Ġfamed\": 14661,\n    \"ĠOUT\": 14662,\n    \"Ġinduct\": 14663,\n    \"ĠAuckland\": 14664,\n    \"Ġpoetry\": 14665,\n    \"mos\": 14666,\n    \"ĠGuinea\": 14667,\n    \"management\": 14668,\n    \"ohan\": 14669,\n    \"ĠGuide\": 14670,\n    \"aily\": 14671,\n    \"umping\": 14672,\n    \"Ġenacted\": 14673,\n    \"ĠEye\": 14674,\n    \"vision\": 14675,\n    \"umi\": 14676,\n    \"aped\": 14677,\n    \"Ġbicycle\": 14678,\n    \"ĠHouth\": 14679,\n    \"ĠNAS\": 14680,\n    \"Ġtapped\": 14681,\n    \"wer\": 14682,\n    \"otti\": 14683,\n    \"EA\": 14684,\n    \"Ġsurprises\": 14685,\n    \"ĠUpdate\": 14686,\n    \"ĠPun\": 14687,\n    \"ĠMiz\": 14688,\n    \"ĠOro\": 14689,\n    \"Ġcostumes\": 14690,\n    \"title\": 14691,\n    \"Ġsurviving\": 14692,\n    \"According\": 14693,\n    \"themed\": 14694,\n    \"ĠPeoples\": 14695,\n    \"Se\": 14696,\n    \"Ġassociations\": 14697,\n    \"hett\": 14698,\n    \"Time\": 14699,\n    \"Ġessay\": 14700,\n    \"Ġmu\": 14701,\n    \"ĠScore\": 14702,\n    \"ĠSpani\": 14703,\n    \"ĠSEE\": 14704,\n    \"Ġmales\": 14705,\n    \"Ġrage\": 14706,\n    \"EU\": 14707,\n    \"ĠYellow\": 14708,\n    \"rupt\": 14709,\n    \"Ġapparel\": 14710,\n    \"Ġsweat\": 14711,\n    \"Ġnearest\": 14712,\n    \"zman\": 14713,\n    \"Ġanticipation\": 14714,\n    \"Ġinjuring\": 14715,\n    \"Ġousted\": 14716,\n    \"chan\": 14717,\n    \"ĠAlert\": 14718,\n    \"Ġber\": 14719,\n    \"atal\": 14720,\n    \"Com\": 14721,\n    \"Ġ04\": 14722,\n    \"Ġafterward\": 14723,\n    \"edge\": 14724,\n    \"ĠBooker\": 14725,\n    \"lex\": 14726,\n    \"ĠWhole\": 14727,\n    \"Ġtoughest\": 14728,\n    \"ĠMaharashtra\": 14729,\n    \"lier\": 14730,\n    \"ĠTennis\": 14731,\n    \"Ġhandy\": 14732,\n    \"ĠMetal\": 14733,\n    \"ĠiTunes\": 14734,\n    \"ĠDiscovery\": 14735,\n    \"Ġcompassion\": 14736,\n    \"ĠLIVE\": 14737,\n    \"Ġeconomically\": 14738,\n    \"Ġendangered\": 14739,\n    \"GO\": 14740,\n    \"Ġmound\": 14741,\n    \"word\": 14742,\n    \"ĠTouch\": 14743,\n    \"ogo\": 14744,\n    \"Ġincomes\": 14745,\n    \"when\": 14746,\n    \"ĠAside\": 14747,\n    \"Ġscandals\": 14748,\n    \"Ġfunctionality\": 14749,\n    \"ĠAer\": 14750,\n    \"Ġcouncils\": 14751,\n    \"Ġdenial\": 14752,\n    \"140\": 14753,\n    \"Ġimplied\": 14754,\n    \"Ġoutfits\": 14755,\n    \"Ġsuited\": 14756,\n    \"Ġ1973\": 14757,\n    \"ĠPizza\": 14758,\n    \"Ġdebates\": 14759,\n    \"record\": 14760,\n    \"Ġhype\": 14761,\n    \"ĠRus\": 14762,\n    \"ĠRobbie\": 14763,\n    \"Ġtouted\": 14764,\n    \"ĠSharp\": 14765,\n    \"Ġbeings\": 14766,\n    \"Ġslavery\": 14767,\n    \"encies\": 14768,\n    \"ĠRooney\": 14769,\n    \"Ġnan\": 14770,\n    \"Ġraids\": 14771,\n    \"Ġinstructor\": 14772,\n    \"Market\": 14773,\n    \"Ġshook\": 14774,\n    \"Ġdeliberate\": 14775,\n    \"ĠNorthwestern\": 14776,\n    \"ĠEss\": 14777,\n    \"Ġwhatsoever\": 14778,\n    \"ĠConfederate\": 14779,\n    \"YS\": 14780,\n    \"ĠCameroon\": 14781,\n    \"ĠFlip\": 14782,\n    \"Yeah\": 14783,\n    \"Ġwashing\": 14784,\n    \"mand\": 14785,\n    \"ĠLex\": 14786,\n    \"Ġissuance\": 14787,\n    \"Ġniche\": 14788,\n    \"Ġfold\": 14789,\n    \"ĠWendy\": 14790,\n    \"Ġhy\": 14791,\n    \"Ġbucket\": 14792,\n    \"ĠVW\": 14793,\n    \"ĠCairo\": 14794,\n    \"ĠSK\": 14795,\n    \"ĠKang\": 14796,\n    \"Ġintake\": 14797,\n    \"Ġhills\": 14798,\n    \"anz\": 14799,\n    \"Â©\": 14800,\n    \"ugu\": 14801,\n    \"ĠFortunately\": 14802,\n    \"ĠMarqu\": 14803,\n    \"Ġimprisonment\": 14804,\n    \"oking\": 14805,\n    \"Ġdistributors\": 14806,\n    \"zie\": 14807,\n    \"Ġstip\": 14808,\n    \"ĠWire\": 14809,\n    \"Ġcouncillors\": 14810,\n    \"Ġsue\": 14811,\n    \"ĠRegardless\": 14812,\n    \"ĠEnc\": 14813,\n    \"Ġbaking\": 14814,\n    \"ĠVenture\": 14815,\n    \"Ġintriguing\": 14816,\n    \"Ġupheld\": 14817,\n    \"ĠActive\": 14818,\n    \"Ġgenes\": 14819,\n    \"ĠDawson\": 14820,\n    \"ĠPreviously\": 14821,\n    \"ĠRac\": 14822,\n    \"Ġmetric\": 14823,\n    \"Files\": 14824,\n    \"ĠiPhones\": 14825,\n    \"ĠWelcome\": 14826,\n    \"Ġburns\": 14827,\n    \"ĠScreen\": 14828,\n    \"ashes\": 14829,\n    \"ĠApr\": 14830,\n    \"Ġtheories\": 14831,\n    \"san\": 14832,\n    \"ĠRenault\": 14833,\n    \"ĠSinger\": 14834,\n    \"Ġfounders\": 14835,\n    \"Russian\": 14836,\n    \"ĠBelfast\": 14837,\n    \"Ġimagined\": 14838,\n    \"ĠPlanet\": 14839,\n    \"ĠCatalan\": 14840,\n    \"ĠRochester\": 14841,\n    \"Ġevolve\": 14842,\n    \"ĠOT\": 14843,\n    \"Ġpassword\": 14844,\n    \"Ġhomelessness\": 14845,\n    \"Ġbacklog\": 14846,\n    \"Ġpresenter\": 14847,\n    \"Ġfal\": 14848,\n    \"ISH\": 14849,\n    \"ĠEM\": 14850,\n    \"icked\": 14851,\n    \"Ġunlock\": 14852,\n    \"city\": 14853,\n    \"Ġnegotiation\": 14854,\n    \"Ġdancers\": 14855,\n    \"dan\": 14856,\n    \"ĠCOL\": 14857,\n    \"VC\": 14858,\n    \"boat\": 14859,\n    \"Ġoverly\": 14860,\n    \"deal\": 14861,\n    \"lander\": 14862,\n    \"Ġdiss\": 14863,\n    \"ICS\": 14864,\n    \"Ġfifty\": 14865,\n    \"Ġowe\": 14866,\n    \"Ġprisons\": 14867,\n    \"ifications\": 14868,\n    \"wo\": 14869,\n    \"ĠAu\": 14870,\n    \"Ġapiece\": 14871,\n    \"ĠCourtney\": 14872,\n    \"Ġ1975\": 14873,\n    \"Ġsurpass\": 14874,\n    \"Ġidentities\": 14875,\n    \"Ġintegral\": 14876,\n    \"Ġdocumentation\": 14877,\n    \"Ġelegant\": 14878,\n    \"ĠIg\": 14879,\n    \"Ġdear\": 14880,\n    \"Ġ113\": 14881,\n    \"ĠGupta\": 14882,\n    \"Ġcontentious\": 14883,\n    \"rish\": 14884,\n    \"Ġclues\": 14885,\n    \"Ġadditions\": 14886,\n    \"Ġep\": 14887,\n    \"rus\": 14888,\n    \"Ġcentered\": 14889,\n    \"ĠPhillies\": 14890,\n    \"father\": 14891,\n    \"Ġborough\": 14892,\n    \"Ġbuttons\": 14893,\n    \"Ġdeported\": 14894,\n    \"ĠREC\": 14895,\n    \"ĠAlready\": 14896,\n    \"eh\": 14897,\n    \"hur\": 14898,\n    \"Ġupbeat\": 14899,\n    \"omen\": 14900,\n    \"Ġdetailing\": 14901,\n    \"Ġwr\": 14902,\n    \"Ġvaried\": 14903,\n    \"ĠEconomics\": 14904,\n    \"Ġensures\": 14905,\n    \"ĠCivic\": 14906,\n    \"Ġunpaid\": 14907,\n    \"sold\": 14908,\n    \"ĠHil\": 14909,\n    \"ĠMult\": 14910,\n    \"ĠRising\": 14911,\n    \"ĠMini\": 14912,\n    \"Ġneuro\": 14913,\n    \"Ġpenal\": 14914,\n    \"Ġneighbour\": 14915,\n    \"ĠChavez\": 14916,\n    \"Ġjew\": 14917,\n    \"ĠVIP\": 14918,\n    \"Connor\": 14919,\n    \"ĠTalking\": 14920,\n    \"Ġcorrection\": 14921,\n    \"Ġstandpoint\": 14922,\n    \"roads\": 14923,\n    \"ĠWool\": 14924,\n    \"Ġverification\": 14925,\n    \"Ġmic\": 14926,\n    \"olf\": 14927,\n    \"Ġexemption\": 14928,\n    \"Ġfilter\": 14929,\n    \"Ġballoon\": 14930,\n    \"leases\": 14931,\n    \"ician\": 14932,\n    \"ĠSpr\": 14933,\n    \"Ġtoe\": 14934,\n    \"Ġunconstitutional\": 14935,\n    \"Ġmanslaughter\": 14936,\n    \"Ġtossed\": 14937,\n    \"ĠMeg\": 14938,\n    \"ATIONS\": 14939,\n    \"ACK\": 14940,\n    \"ĠRouge\": 14941,\n    \"ĠHansen\": 14942,\n    \"ĠHook\": 14943,\n    \"Out\": 14944,\n    \"ĠHorse\": 14945,\n    \"ĠBath\": 14946,\n    \"ĠAlways\": 14947,\n    \"Ġincorporated\": 14948,\n    \"Ġconjunction\": 14949,\n    \"ĠFit\": 14950,\n    \"Ġexamining\": 14951,\n    \"Ġwallet\": 14952,\n    \"Ġensured\": 14953,\n    \"Ġacclaimed\": 14954,\n    \"ippers\": 14955,\n    \"Ġbeneficiaries\": 14956,\n    \"Ġunexpectedly\": 14957,\n    \"Ġexploit\": 14958,\n    \"ĠWillie\": 14959,\n    \"Ġcomb\": 14960,\n    \"ĠWalton\": 14961,\n    \"rica\": 14962,\n    \"icky\": 14963,\n    \"Ġate\": 14964,\n    \"ĠPadres\": 14965,\n    \"Ġrib\": 14966,\n    \"Ġsnacks\": 14967,\n    \"ĠFernandez\": 14968,\n    \"ĠMachine\": 14969,\n    \"ction\": 14970,\n    \"Ġillnesses\": 14971,\n    \"ĠHoffman\": 14972,\n    \"ĠSpaceX\": 14973,\n    \"Ġju\": 14974,\n    \"Ġswift\": 14975,\n    \"Ġembark\": 14976,\n    \"ĠRailway\": 14977,\n    \"Ġmeasuring\": 14978,\n    \"agers\": 14979,\n    \"arsh\": 14980,\n    \"Ġessence\": 14981,\n    \"angle\": 14982,\n    \"Ġolive\": 14983,\n    \"ĠCommander\": 14984,\n    \"iggs\": 14985,\n    \"Ġrewarded\": 14986,\n    \"Ġdispatched\": 14987,\n    \"Ġplayground\": 14988,\n    \"Â½\": 14989,\n    \"ĠProgramme\": 14990,\n    \"Ġstudios\": 14991,\n    \"Ġskeptical\": 14992,\n    \"ĠOlymp\": 14993,\n    \"ĠKeys\": 14994,\n    \"ĠSunshine\": 14995,\n    \"amba\": 14996,\n    \"ĠDonna\": 14997,\n    \"Ġlightly\": 14998,\n    \"Ġobtaining\": 14999,\n    \"Ġpoisoning\": 15000,\n    \"Ġaz\": 15001,\n    \"Ġ1972\": 15002,\n    \"Ġunconscious\": 15003,\n    \"ECT\": 15004,\n    \"Ġlied\": 15005,\n    \"ĠKaz\": 15006,\n    \"Ġ06\": 15007,\n    \"ĠMoving\": 15008,\n    \"Ġnum\": 15009,\n    \"oral\": 15010,\n    \"Ġassessments\": 15011,\n    \"Ġscholarships\": 15012,\n    \"Ġevacuate\": 15013,\n    \"ĠSunni\": 15014,\n    \"Ġquake\": 15015,\n    \"Ġfort\": 15016,\n    \"ques\": 15017,\n    \"ĠAlonso\": 15018,\n    \"Ġthread\": 15019,\n    \"Ġsqueeze\": 15020,\n    \"arat\": 15021,\n    \"oly\": 15022,\n    \"ĠAlphabet\": 15023,\n    \"uting\": 15024,\n    \"icio\": 15025,\n    \"ĠRetirement\": 15026,\n    \"ither\": 15027,\n    \"Ġasleep\": 15028,\n    \"Ġpairs\": 15029,\n    \"Ġmanufacture\": 15030,\n    \"ĠHazard\": 15031,\n    \"Ġsidewalk\": 15032,\n    \"Ġwears\": 15033,\n    \"ĠCraft\": 15034,\n    \"emen\": 15035,\n    \"ieth\": 15036,\n    \"Ġbypass\": 15037,\n    \"ĠLancaster\": 15038,\n    \"Ġflour\": 15039,\n    \"charge\": 15040,\n    \"ĠCLICK\": 15041,\n    \"Ġpotatoes\": 15042,\n    \"ĠKarachi\": 15043,\n    \"Ġvalley\": 15044,\n    \"Ġsights\": 15045,\n    \"Ġfallout\": 15046,\n    \"ords\": 15047,\n    \"BN\": 15048,\n    \"Ġsunshine\": 15049,\n    \"Ġundertaken\": 15050,\n    \"Ġcontestants\": 15051,\n    \"Ġaccomplishments\": 15052,\n    \"Ġconditioning\": 15053,\n    \"Ġcel\": 15054,\n    \"ĠHalifax\": 15055,\n    \"Ġaccent\": 15056,\n    \"***\": 15057,\n    \"Ġpitchers\": 15058,\n    \"Ġadopting\": 15059,\n    \"Ġjustices\": 15060,\n    \"Ġrip\": 15061,\n    \"ince\": 15062,\n    \"Ġelimination\": 15063,\n    \"Ġaerospace\": 15064,\n    \"ĠBeer\": 15065,\n    \"ĠBasin\": 15066,\n    \"Ġunwanted\": 15067,\n    \"goers\": 15068,\n    \"isco\": 15069,\n    \"ĠTwin\": 15070,\n    \"ĠDesert\": 15071,\n    \"rix\": 15072,\n    \"Ġdarkness\": 15073,\n    \"ĠDunn\": 15074,\n    \"City\": 15075,\n    \"pop\": 15076,\n    \"Ġ1969\": 15077,\n    \"ataka\": 15078,\n    \"Ġtal\": 15079,\n    \"Ġautism\": 15080,\n    \"ĠMcLaren\": 15081,\n    \"ĠUEFA\": 15082,\n    \"Ġclassrooms\": 15083,\n    \"ĠLeave\": 15084,\n    \"Americans\": 15085,\n    \"las\": 15086,\n    \"Ġqui\": 15087,\n    \"Ġundefeated\": 15088,\n    \"otto\": 15089,\n    \"ĠNRA\": 15090,\n    \"ĠPorsche\": 15091,\n    \"Ġnuts\": 15092,\n    \"oys\": 15093,\n    \"ĠMethodist\": 15094,\n    \"Ġatt\": 15095,\n    \"Ġtweeting\": 15096,\n    \"children\": 15097,\n    \"eller\": 15098,\n    \"Ġinquiries\": 15099,\n    \"Ġmillennials\": 15100,\n    \"ĠWembley\": 15101,\n    \"INS\": 15102,\n    \"Ġautopsy\": 15103,\n    \"ĠElon\": 15104,\n    \"ĠHicks\": 15105,\n    \"ugg\": 15106,\n    \"Ġwreck\": 15107,\n    \"ĠComcast\": 15108,\n    \"Ġstones\": 15109,\n    \"public\": 15110,\n    \"ĠKem\": 15111,\n    \"bedroom\": 15112,\n    \"ļ\": 15113,\n    \"itated\": 15114,\n    \"Ġsemic\": 15115,\n    \"uman\": 15116,\n    \"Cal\": 15117,\n    \"ANN\": 15118,\n    \"ĠGaz\": 15119,\n    \"Ġundisclosed\": 15120,\n    \"ĠPlanned\": 15121,\n    \"ĠYale\": 15122,\n    \"ĠIST\": 15123,\n    \"lies\": 15124,\n    \"ĠStanding\": 15125,\n    \"Ġrelieved\": 15126,\n    \"EO\": 15127,\n    \"Ġgraduating\": 15128,\n    \"park\": 15129,\n    \"ĠâĢķ\": 15130,\n    \"Ġpensions\": 15131,\n    \"rave\": 15132,\n    \"ĠWonder\": 15133,\n    \"AZ\": 15134,\n    \"Ġcosting\": 15135,\n    \"Ġeditors\": 15136,\n    \"Ġtotaled\": 15137,\n    \"Ġspacecraft\": 15138,\n    \"meter\": 15139,\n    \"Ġ02\": 15140,\n    \"ĠNikki\": 15141,\n    \"sworth\": 15142,\n    \"ĠCrit\": 15143,\n    \"asha\": 15144,\n    \"Ġknees\": 15145,\n    \"Ġhats\": 15146,\n    \"uity\": 15147,\n    \"ĠPanther\": 15148,\n    \"Ġtan\": 15149,\n    \"ĠBuzz\": 15150,\n    \"ĠGlad\": 15151,\n    \"ĠPleasant\": 15152,\n    \"SM\": 15153,\n    \"Ġtricks\": 15154,\n    \"Ġplac\": 15155,\n    \"ĠDanielle\": 15156,\n    \"Ġours\": 15157,\n    \"Ġwashed\": 15158,\n    \"haven\": 15159,\n    \"Ġdrain\": 15160,\n    \"ĠUttar\": 15161,\n    \"Ġapple\": 15162,\n    \"Ġjunk\": 15163,\n    \"Ġturkey\": 15164,\n    \"ĠDug\": 15165,\n    \"Ġdiplomacy\": 15166,\n    \"Ġempire\": 15167,\n    \"Ġpinch\": 15168,\n    \"Ġferry\": 15169,\n    \"ĠDustin\": 15170,\n    \"Ġ03\": 15171,\n    \"Ġelder\": 15172,\n    \"Everything\": 15173,\n    \"ĠProgressive\": 15174,\n    \"ution\": 15175,\n    \"VI\": 15176,\n    \"dam\": 15177,\n    \"Ġlever\": 15178,\n    \"ĠAustralians\": 15179,\n    \"Ġconsequence\": 15180,\n    \"itan\": 15181,\n    \"Ġcondemn\": 15182,\n    \"Ġneg\": 15183,\n    \"ĠOverview\": 15184,\n    \"Ġsuccesses\": 15185,\n    \"Ġprobable\": 15186,\n    \"ĠMirror\": 15187,\n    \"mor\": 15188,\n    \"verse\": 15189,\n    \"Ġevaluating\": 15190,\n    \"ĠBes\": 15191,\n    \"Ġimm\": 15192,\n    \"Ġharness\": 15193,\n    \"Ġresilient\": 15194,\n    \"ĠBuild\": 15195,\n    \"Ġstraightforward\": 15196,\n    \"ADE\": 15197,\n    \"Ġgrandparents\": 15198,\n    \"Ġmarched\": 15199,\n    \"ĠKiev\": 15200,\n    \"Ġchiefs\": 15201,\n    \"oha\": 15202,\n    \"Ġvest\": 15203,\n    \"kn\": 15204,\n    \"enda\": 15205,\n    \"ĠSev\": 15206,\n    \"Ġbatters\": 15207,\n    \"ĠJos\": 15208,\n    \"ĠQue\": 15209,\n    \"ĠCourse\": 15210,\n    \"ĠCorner\": 15211,\n    \"ĠMess\": 15212,\n    \"Ġmourn\": 15213,\n    \"keepers\": 15214,\n    \"ĠRegina\": 15215,\n    \"Everybody\": 15216,\n    \"Ġtrajectory\": 15217,\n    \"Ġdefenseman\": 15218,\n    \"ĠArticles\": 15219,\n    \"Ġspur\": 15220,\n    \"ĠPhD\": 15221,\n    \"Ġpipes\": 15222,\n    \"Ġduck\": 15223,\n    \"Ġcombining\": 15224,\n    \"ĠHit\": 15225,\n    \"ĠGeorgetown\": 15226,\n    \"ĠBee\": 15227,\n    \"Cor\": 15228,\n    \"Ġcomposition\": 15229,\n    \"Ġconnects\": 15230,\n    \"ĠMARK\": 15231,\n    \"taker\": 15232,\n    \"Ġcertainty\": 15233,\n    \"Ġhefty\": 15234,\n    \"ĠHezbollah\": 15235,\n    \"ĠShip\": 15236,\n    \"Ġmalicious\": 15237,\n    \"AI\": 15238,\n    \"Ġbits\": 15239,\n    \"Ġstyl\": 15240,\n    \"Ġimpaired\": 15241,\n    \"ĠCBI\": 15242,\n    \"Despite\": 15243,\n    \"othe\": 15244,\n    \"ĠRyder\": 15245,\n    \"ĠAlf\": 15246,\n    \"ifa\": 15247,\n    \"Ind\": 15248,\n    \"Ġblaming\": 15249,\n    \"ĠToledo\": 15250,\n    \"EW\": 15251,\n    \"ĠEssex\": 15252,\n    \"iated\": 15253,\n    \"ĠAberdeen\": 15254,\n    \"ANCE\": 15255,\n    \"Ġpossess\": 15256,\n    \"Ġsuperhero\": 15257,\n    \"Ġoverhead\": 15258,\n    \"quet\": 15259,\n    \"ĠRicky\": 15260,\n    \"Ġdock\": 15261,\n    \"ĠTelecom\": 15262,\n    \"Ġshelf\": 15263,\n    \"³\": 15264,\n    \"Ġmaritime\": 15265,\n    \"Ġportrayed\": 15266,\n    \"ĠYesterday\": 15267,\n    \"Ġcollided\": 15268,\n    \"Ġcookies\": 15269,\n    \"ĠCul\": 15270,\n    \"Ġindexes\": 15271,\n    \"Ġnaval\": 15272,\n    \"oval\": 15273,\n    \"105\": 15274,\n    \"ĠWeber\": 15275,\n    \"chief\": 15276,\n    \"arma\": 15277,\n    \"ĠRey\": 15278,\n    \"Ġauditor\": 15279,\n    \"ĠMarion\": 15280,\n    \"ĠMartha\": 15281,\n    \"ĠSally\": 15282,\n    \"Ġsedan\": 15283,\n    \"ĠAlison\": 15284,\n    \"nce\": 15285,\n    \"Es\": 15286,\n    \"ĠParade\": 15287,\n    \"Ġpharmacy\": 15288,\n    \"ĠKre\": 15289,\n    \"loe\": 15290,\n    \"cks\": 15291,\n    \"Ġmitigate\": 15292,\n    \"Ġdesigning\": 15293,\n    \"Ġ2024\": 15294,\n    \"Ġportable\": 15295,\n    \"Ġimproves\": 15296,\n    \"ĠAMD\": 15297,\n    \"Ġexcluded\": 15298,\n    \"CON\": 15299,\n    \"ĠOscars\": 15300,\n    \"Ġfixtures\": 15301,\n    \"comb\": 15302,\n    \"ĠBerg\": 15303,\n    \"Ġbother\": 15304,\n    \"Ġboring\": 15305,\n    \"Ġobservation\": 15306,\n    \"ĠCad\": 15307,\n    \"Ġrecordings\": 15308,\n    \"ĠCultural\": 15309,\n    \"Ġweaken\": 15310,\n    \"Ġaccuse\": 15311,\n    \"ĠAbd\": 15312,\n    \"abor\": 15313,\n    \"115\": 15314,\n    \"uffle\": 15315,\n    \"Ġhighways\": 15316,\n    \"atham\": 15317,\n    \"empt\": 15318,\n    \"ĠDeer\": 15319,\n    \"ĠEDT\": 15320,\n    \"ĠWait\": 15321,\n    \"athan\": 15322,\n    \"Ġaccumulated\": 15323,\n    \"Ġguilt\": 15324,\n    \"Ġexempt\": 15325,\n    \"Ġdiluted\": 15326,\n    \"ĠJamal\": 15327,\n    \"Ġshit\": 15328,\n    \"cross\": 15329,\n    \"Ġeve\": 15330,\n    \"Ġshirts\": 15331,\n    \"Ġsatisfy\": 15332,\n    \"ĠPaulo\": 15333,\n    \"AH\": 15334,\n    \"sic\": 15335,\n    \"ĠChloe\": 15336,\n    \"ĠCities\": 15337,\n    \"ĠSwansea\": 15338,\n    \"Ġprecision\": 15339,\n    \"ĠTracy\": 15340,\n    \"ping\": 15341,\n    \"Ġcontinually\": 15342,\n    \"Ġdemographic\": 15343,\n    \"Ġcliff\": 15344,\n    \"Ġjaw\": 15345,\n    \"isted\": 15346,\n    \"ĠDevelop\": 15347,\n    \"ĠAJ\": 15348,\n    \"Ġaisle\": 15349,\n    \"ĠLionel\": 15350,\n    \"Ġpredominantly\": 15351,\n    \"Ġmel\": 15352,\n    \"Ġlifelong\": 15353,\n    \"hs\": 15354,\n    \"Ġshouted\": 15355,\n    \"lad\": 15356,\n    \"Ġdest\": 15357,\n    \"Ġpacks\": 15358,\n    \"ĠKath\": 15359,\n    \"ĠCruise\": 15360,\n    \"fired\": 15361,\n    \"oder\": 15362,\n    \"hua\": 15363,\n    \"Ġgoodbye\": 15364,\n    \"Ġinterfere\": 15365,\n    \"eca\": 15366,\n    \"ĠrÃ©\": 15367,\n    \"atum\": 15368,\n    \"itas\": 15369,\n    \"ĠLodge\": 15370,\n    \"ĠWald\": 15371,\n    \"Ġmidday\": 15372,\n    \"umble\": 15373,\n    \"asting\": 15374,\n    \"©\": 15375,\n    \"ĠLeg\": 15376,\n    \"ĠNepal\": 15377,\n    \"Ġchased\": 15378,\n    \"idge\": 15379,\n    \"Ġconv\": 15380,\n    \"Ġfraudulent\": 15381,\n    \"Ġopera\": 15382,\n    \"Ġshr\": 15383,\n    \"ĠUniverse\": 15384,\n    \"ĠJerome\": 15385,\n    \"Ġ1977\": 15386,\n    \"ĠDancing\": 15387,\n    \"ĠRS\": 15388,\n    \"±\": 15389,\n    \"eks\": 15390,\n    \"Ġchic\": 15391,\n    \"Ġpunish\": 15392,\n    \"Ġpropose\": 15393,\n    \"arin\": 15394,\n    \"ĠChop\": 15395,\n    \"ĠAhead\": 15396,\n    \"ĠGallagher\": 15397,\n    \"ĠBangkok\": 15398,\n    \"ĠShelby\": 15399,\n    \"ĠNS\": 15400,\n    \"Ġcheek\": 15401,\n    \"onia\": 15402,\n    \"Ġrelegation\": 15403,\n    \"ĠHind\": 15404,\n    \"ĠCory\": 15405,\n    \"Ġfingerprint\": 15406,\n    \"Ġstrive\": 15407,\n    \"Ġmm\": 15408,\n    \"igs\": 15409,\n    \"Ġholy\": 15410,\n    \"Ġfavored\": 15411,\n    \"ĠSomeone\": 15412,\n    \"ĠLatino\": 15413,\n    \"ĠPatt\": 15414,\n    \"Ġchallenger\": 15415,\n    \"ĠCotton\": 15416,\n    \"Sw\": 15417,\n    \"itten\": 15418,\n    \"ĠXI\": 15419,\n    \"ĠStat\": 15420,\n    \"ĠDIS\": 15421,\n    \"Ġautomakers\": 15422,\n    \"Ġevaluated\": 15423,\n    \"ĠArc\": 15424,\n    \"Ġpersuade\": 15425,\n    \"Af\": 15426,\n    \"Ġreunited\": 15427,\n    \"Ġabs\": 15428,\n    \"Ġbride\": 15429,\n    \"Ġpurely\": 15430,\n    \"uce\": 15431,\n    \"uded\": 15432,\n    \"Ġsettling\": 15433,\n    \"Ġlodged\": 15434,\n    \"Ġfixing\": 15435,\n    \"Ġsuccession\": 15436,\n    \"ĠAlfred\": 15437,\n    \"ĠAlvarez\": 15438,\n    \"mac\": 15439,\n    \"ĠFont\": 15440,\n    \"Ġcontra\": 15441,\n    \"affle\": 15442,\n    \"Ġcopied\": 15443,\n    \"Ġmasses\": 15444,\n    \"ĠElections\": 15445,\n    \"ĠThan\": 15446,\n    \"Ġsoaring\": 15447,\n    \"jay\": 15448,\n    \"Ġsuing\": 15449,\n    \"Ġconcentrated\": 15450,\n    \"Ġconvey\": 15451,\n    \"Ġ240\": 15452,\n    \"gs\": 15453,\n    \"ĠNeal\": 15454,\n    \"Ġnasty\": 15455,\n    \"ĠLB\": 15456,\n    \"odi\": 15457,\n    \"ĠSergei\": 15458,\n    \"Ġthumb\": 15459,\n    \"Ġservants\": 15460,\n    \"Ġrevelation\": 15461,\n    \"Ġdischarge\": 15462,\n    \"ĠBright\": 15463,\n    \"ĠBent\": 15464,\n    \"ĠChrysler\": 15465,\n    \"mill\": 15466,\n    \"ĠImagine\": 15467,\n    \"Ġreceptions\": 15468,\n    \"Ġpersonalities\": 15469,\n    \"Ġsilly\": 15470,\n    \"ĠLoc\": 15471,\n    \"ĠZero\": 15472,\n    \"HI\": 15473,\n    \"rice\": 15474,\n    \"Ġgar\": 15475,\n    \"far\": 15476,\n    \"enh\": 15477,\n    \"ĠBiden\": 15478,\n    \"ĠEntreprene\": 15479,\n    \"Ġassumption\": 15480,\n    \"Ġnicely\": 15481,\n    \"ĠEither\": 15482,\n    \"|\": 15483,\n    \"ĠNW\": 15484,\n    \"ĠKens\": 15485,\n    \"ĠNolan\": 15486,\n    \"Ġowning\": 15487,\n    \"atures\": 15488,\n    \"ĠPastor\": 15489,\n    \"ĠRegistration\": 15490,\n    \"Ġexperiments\": 15491,\n    \"Ġassurance\": 15492,\n    \"Ġhashtag\": 15493,\n    \"oint\": 15494,\n    \"ĠBin\": 15495,\n    \"Ġqualification\": 15496,\n    \"center\": 15497,\n    \"Ġausterity\": 15498,\n    \"ĠPers\": 15499,\n    \"Ġscoop\": 15500,\n    \"Ġpros\": 15501,\n    \"ĠFields\": 15502,\n    \"Ġfur\": 15503,\n    \"ĠJas\": 15504,\n    \"Ġplanting\": 15505,\n    \"security\": 15506,\n    \"ĠTrain\": 15507,\n    \"ĠKathy\": 15508,\n    \"demand\": 15509,\n    \"ĠLev\": 15510,\n    \"Ġtut\": 15511,\n    \"tier\": 15512,\n    \"QU\": 15513,\n    \"Ġexploitation\": 15514,\n    \"Ġignoring\": 15515,\n    \"ĠSex\": 15516,\n    \"Ġadapted\": 15517,\n    \"Ġdisastrous\": 15518,\n    \"Ġempower\": 15519,\n    \"Ġcreators\": 15520,\n    \"ĠLay\": 15521,\n    \"ĠDragon\": 15522,\n    \"ĠWyn\": 15523,\n    \"Ġ1974\": 15524,\n    \"acious\": 15525,\n    \"performance\": 15526,\n    \"ĠTiffany\": 15527,\n    \"isting\": 15528,\n    \"Ġindividually\": 15529,\n    \"ĠLeading\": 15530,\n    \"ĠSask\": 15531,\n    \"Ġcatastrophic\": 15532,\n    \"Ġpunched\": 15533,\n    \"ĠVienna\": 15534,\n    \"Ġsurgical\": 15535,\n    \"Gr\": 15536,\n    \"odo\": 15537,\n    \"Ġgem\": 15538,\n    \"ĠMinority\": 15539,\n    \"Ġmice\": 15540,\n    \"ĠHistoric\": 15541,\n    \"ĠKot\": 15542,\n    \"caster\": 15543,\n    \"Ġsuff\": 15544,\n    \"journal\": 15545,\n    \"Ġpresumably\": 15546,\n    \"ĠBit\": 15547,\n    \"inary\": 15548,\n    \"Ġbre\": 15549,\n    \"Ġenhancing\": 15550,\n    \"Ġgru\": 15551,\n    \"ĠRunning\": 15552,\n    \"hardt\": 15553,\n    \"Ġtroubling\": 15554,\n    \"Ġpumps\": 15555,\n    \"ĠProspect\": 15556,\n    \"etic\": 15557,\n    \"Ġmartial\": 15558,\n    \"Ġcouncillor\": 15559,\n    \"atra\": 15560,\n    \"ths\": 15561,\n    \"ĠSark\": 15562,\n    \"ĠChamp\": 15563,\n    \"scoring\": 15564,\n    \"ĠWel\": 15565,\n    \"rup\": 15566,\n    \"Ġterrifying\": 15567,\n    \"ĠCatch\": 15568,\n    \"Ġinspections\": 15569,\n    \"Ġpornography\": 15570,\n    \"bra\": 15571,\n    \"ĠKeeping\": 15572,\n    \"Ġbanker\": 15573,\n    \"angers\": 15574,\n    \"ĠCrimea\": 15575,\n    \"ĠDisclosure\": 15576,\n    \"iba\": 15577,\n    \"Ġturf\": 15578,\n    \"Ġschedules\": 15579,\n    \"ĠJorge\": 15580,\n    \"ĠAcross\": 15581,\n    \"Ġsolving\": 15582,\n    \"Ġsensation\": 15583,\n    \"ĠWW\": 15584,\n    \"cial\": 15585,\n    \"atz\": 15586,\n    \"Ġlion\": 15587,\n    \"Ġcertificates\": 15588,\n    \"itive\": 15589,\n    \"ĠWes\": 15590,\n    \"ĠPrison\": 15591,\n    \"ĠPlayStation\": 15592,\n    \"duty\": 15593,\n    \"Ġvariable\": 15594,\n    \"Ġstrangers\": 15595,\n    \"istrates\": 15596,\n    \"vs\": 15597,\n    \"Ġreigning\": 15598,\n    \"Ġsliding\": 15599,\n    \"ĠShin\": 15600,\n    \"Ġtelecommunications\": 15601,\n    \"Ġinstalling\": 15602,\n    \"Ġrecogn\": 15603,\n    \"Ġsubway\": 15604,\n    \"too\": 15605,\n    \"ĠMcKin\": 15606,\n    \"ĠStoke\": 15607,\n    \"Ġsensitivity\": 15608,\n    \"bas\": 15609,\n    \"Ġsan\": 15610,\n    \"Ġ(-\": 15611,\n    \"ĠSuarez\": 15612,\n    \"Ġaverages\": 15613,\n    \"ammu\": 15614,\n    \"ĠFen\": 15615,\n    \"Ġrefined\": 15616,\n    \"outh\": 15617,\n    \"Ġcob\": 15618,\n    \"ĠLaz\": 15619,\n    \"essa\": 15620,\n    \"Ġpositioning\": 15621,\n    \"Three\": 15622,\n    \"Ġoils\": 15623,\n    \"Ġassaults\": 15624,\n    \"Ġcompanion\": 15625,\n    \"ĠFlash\": 15626,\n    \"ĠMam\": 15627,\n    \"ĠTill\": 15628,\n    \"Ġblues\": 15629,\n    \"ĠJae\": 15630,\n    \"ĠPier\": 15631,\n    \"Ġbedrooms\": 15632,\n    \"ĠHawkins\": 15633,\n    \"ĠCornell\": 15634,\n    \"Ġanswering\": 15635,\n    \"Ġsec\": 15636,\n    \"Ġrecognizes\": 15637,\n    \"Red\": 15638,\n    \"ĠJamaica\": 15639,\n    \"Ġinsurgents\": 15640,\n    \"Ġbrace\": 15641,\n    \"Ġra\": 15642,\n    \"ĠTai\": 15643,\n    \"ocation\": 15644,\n    \"ignment\": 15645,\n    \"Ġreasonably\": 15646,\n    \"inating\": 15647,\n    \"Ġbonuses\": 15648,\n    \"Ġsandwich\": 15649,\n    \"Ġinadequate\": 15650,\n    \"Ġdelicate\": 15651,\n    \"Ġadorable\": 15652,\n    \"Ġpalace\": 15653,\n    \"Ġsmallest\": 15654,\n    \"Ġpractically\": 15655,\n    \"ĠCrosby\": 15656,\n    \"Ġlevy\": 15657,\n    \"Ġlend\": 15658,\n    \"boards\": 15659,\n    \"shaped\": 15660,\n    \"Ġvulnerability\": 15661,\n    \"ĠKelley\": 15662,\n    \"Ġsponsorship\": 15663,\n    \"ract\": 15664,\n    \"Ġslew\": 15665,\n    \"Ġfederation\": 15666,\n    \"ĠLal\": 15667,\n    \"acies\": 15668,\n    \"ĠFamilies\": 15669,\n    \"Ġproposing\": 15670,\n    \"Ġhyp\": 15671,\n    \"elected\": 15672,\n    \"inkle\": 15673,\n    \"ĠSays\": 15674,\n    \"ĠApollo\": 15675,\n    \"ĠWis\": 15676,\n    \"imer\": 15677,\n    \"Ġcombines\": 15678,\n    \"Ġtim\": 15679,\n    \"ĠQuestion\": 15680,\n    \"Ġborrowers\": 15681,\n    \"Ġswiftly\": 15682,\n    \"ĠMagn\": 15683,\n    \"Ġheadphones\": 15684,\n    \"Russia\": 15685,\n    \"Ġtongue\": 15686,\n    \"Ġbye\": 15687,\n    \"nn\": 15688,\n    \"Ġseller\": 15689,\n    \"ĠWord\": 15690,\n    \"Tom\": 15691,\n    \"ĠDevin\": 15692,\n    \"ĠSurrey\": 15693,\n    \"Ġquad\": 15694,\n    \"Ġcourthouse\": 15695,\n    \"gi\": 15696,\n    \"ĠGrill\": 15697,\n    \">\": 15698,\n    \"Ġrational\": 15699,\n    \"ĠFlames\": 15700,\n    \"ĠCham\": 15701,\n    \"Ġvacuum\": 15702,\n    \"ĠRays\": 15703,\n    \"Ġescalating\": 15704,\n    \"Ġouter\": 15705,\n    \"Ġstretches\": 15706,\n    \"ĠSpeed\": 15707,\n    \"Ġnegatively\": 15708,\n    \"Ġabsorb\": 15709,\n    \"ĠAustrian\": 15710,\n    \"Ġslice\": 15711,\n    \"ĠDiet\": 15712,\n    \"Ġbun\": 15713,\n    \"Ġtactical\": 15714,\n    \"ĠCBD\": 15715,\n    \"Ġedges\": 15716,\n    \"Ġnest\": 15717,\n    \"Ġstrained\": 15718,\n    \"ulates\": 15719,\n    \"ĠTina\": 15720,\n    \"Net\": 15721,\n    \"ķ\": 15722,\n    \"ĠGos\": 15723,\n    \"God\": 15724,\n    \"White\": 15725,\n    \"Ġproudly\": 15726,\n    \"usion\": 15727,\n    \"ĠArlington\": 15728,\n    \"ĠNear\": 15729,\n    \"ĠMaxwell\": 15730,\n    \"Ġbomber\": 15731,\n    \"Ġcared\": 15732,\n    \"Ġapprovals\": 15733,\n    \"Ġexams\": 15734,\n    \"ĠEconomy\": 15735,\n    \"Ġposters\": 15736,\n    \"ĠHampton\": 15737,\n    \"ĠPere\": 15738,\n    \"ĠContract\": 15739,\n    \"Ġhoused\": 15740,\n    \"Ġinstruction\": 15741,\n    \"ĠJess\": 15742,\n    \"Ġacre\": 15743,\n    \"Ġcongestion\": 15744,\n    \"ĠGener\": 15745,\n    \"Ġdioxide\": 15746,\n    \"Ġvar\": 15747,\n    \"ĠAlexandria\": 15748,\n    \"ĠSpider\": 15749,\n    \"Ġcoins\": 15750,\n    \"Ġ225\": 15751,\n    \"Ġterritorial\": 15752,\n    \"ĠSPD\": 15753,\n    \"Ġfloat\": 15754,\n    \"null\": 15755,\n    \"Ġcalculate\": 15756,\n    \"ĠDin\": 15757,\n    \"eto\": 15758,\n    \"Ġcows\": 15759,\n    \"Ġpunct\": 15760,\n    \"Ġexpire\": 15761,\n    \"Ġkidnapped\": 15762,\n    \"Ġcou\": 15763,\n    \"Ġattitudes\": 15764,\n    \"ĠLeh\": 15765,\n    \"ĠHero\": 15766,\n    \"ĠKabul\": 15767,\n    \"Ġcubic\": 15768,\n    \"Ġdigits\": 15769,\n    \"ĠRES\": 15770,\n    \"Ġpipelines\": 15771,\n    \"icide\": 15772,\n    \"ĠSingle\": 15773,\n    \"Ġhurts\": 15774,\n    \"ĠMaz\": 15775,\n    \"ĠPak\": 15776,\n    \"Ġslate\": 15777,\n    \"Ġmultimedia\": 15778,\n    \"ADA\": 15779,\n    \"Mexico\": 15780,\n    \"ĠRelease\": 15781,\n    \"chard\": 15782,\n    \"Ġgarlic\": 15783,\n    \"ĠFletcher\": 15784,\n    \"Ġaforementioned\": 15785,\n    \"Ġ05\": 15786,\n    \"ĠParkway\": 15787,\n    \"Ġfirefighter\": 15788,\n    \"Ġcounseling\": 15789,\n    \"utions\": 15790,\n    \"Cap\": 15791,\n    \"Ġconsultants\": 15792,\n    \"ĠMeh\": 15793,\n    \"ouring\": 15794,\n    \"ĠDI\": 15795,\n    \"mic\": 15796,\n    \"phones\": 15797,\n    \"Ġencounters\": 15798,\n    \"ĠHapp\": 15799,\n    \"Ġcartoon\": 15800,\n    \"flight\": 15801,\n    \"Ġundertake\": 15802,\n    \"ĠHans\": 15803,\n    \"Ġplunge\": 15804,\n    \"ĠParenthood\": 15805,\n    \"Ġkickoff\": 15806,\n    \"ĠCelsius\": 15807,\n    \"ĠRas\": 15808,\n    \"ĠDund\": 15809,\n    \"ounce\": 15810,\n    \"Ġpurse\": 15811,\n    \"Ġmortality\": 15812,\n    \"Ġbrains\": 15813,\n    \"Ġconglomerate\": 15814,\n    \"ĠObserver\": 15815,\n    \"ĠSector\": 15816,\n    \"ĠApparently\": 15817,\n    \"Ġblank\": 15818,\n    \"iston\": 15819,\n    \"Ġweighs\": 15820,\n    \"gro\": 15821,\n    \"ĠPaw\": 15822,\n    \"ĠCOM\": 15823,\n    \"ĠPurdue\": 15824,\n    \"Ġnetted\": 15825,\n    \"ĠLinux\": 15826,\n    \"Mike\": 15827,\n    \"Ġfaithful\": 15828,\n    \"Ġmagazines\": 15829,\n    \"Ġheadquartered\": 15830,\n    \"ĠIps\": 15831,\n    \"Ġindications\": 15832,\n    \"Look\": 15833,\n    \"ĠElite\": 15834,\n    \"Ġsupreme\": 15835,\n    \"Ġchunk\": 15836,\n    \"ĠSz\": 15837,\n    \"ĠVine\": 15838,\n    \"rise\": 15839,\n    \"ĠYas\": 15840,\n    \"general\": 15841,\n    \"ĠOpera\": 15842,\n    \"Ġpriests\": 15843,\n    \"Assad\": 15844,\n    \"Ġaunt\": 15845,\n    \"Ġwhopping\": 15846,\n    \"enzie\": 15847,\n    \"Ġvegan\": 15848,\n    \"Ġinflux\": 15849,\n    \"ĠConsult\": 15850,\n    \"Ġwaiver\": 15851,\n    \"Having\": 15852,\n    \"inning\": 15853,\n    \"Ġproximity\": 15854,\n    \"Ġclassical\": 15855,\n    \"ĠIslanders\": 15856,\n    \"Ġadvertisers\": 15857,\n    \"ĠCe\": 15858,\n    \"ĠSochi\": 15859,\n    \"Ġmemoir\": 15860,\n    \"ĠPlaying\": 15861,\n    \"yers\": 15862,\n    \"Ġstud\": 15863,\n    \"Ġobservations\": 15864,\n    \"Ġadmire\": 15865,\n    \"Ġhiking\": 15866,\n    \"Ġbatter\": 15867,\n    \"Ġconfusing\": 15868,\n    \"Ġprecaution\": 15869,\n    \"kil\": 15870,\n    \"clusive\": 15871,\n    \"opoulos\": 15872,\n    \"ĠWestbrook\": 15873,\n    \"ĠTanzania\": 15874,\n    \"ĠCedar\": 15875,\n    \"usted\": 15876,\n    \"Ġdestructive\": 15877,\n    \"ĠIndies\": 15878,\n    \"osi\": 15879,\n    \"ĠAmid\": 15880,\n    \"Ġintercepted\": 15881,\n    \"Ġpartnering\": 15882,\n    \"Ġsubstances\": 15883,\n    \"ĠSuns\": 15884,\n    \"Ġpromotes\": 15885,\n    \"bird\": 15886,\n    \"Gen\": 15887,\n    \"aper\": 15888,\n    \"ĠEy\": 15889,\n    \"Ġterrain\": 15890,\n    \"Ġ1930\": 15891,\n    \"zon\": 15892,\n    \"Ġbreed\": 15893,\n    \"broken\": 15894,\n    \"uchin\": 15895,\n    \"ĠPrim\": 15896,\n    \"ĠRoland\": 15897,\n    \"Ġfitted\": 15898,\n    \"Ġprotects\": 15899,\n    \"Ġ114\": 15900,\n    \"RP\": 15901,\n    \"Ġdisrupted\": 15902,\n    \"ĠBaylor\": 15903,\n    \"oren\": 15904,\n    \"ĠKeen\": 15905,\n    \"Ġmansion\": 15906,\n    \"Ġgrassroots\": 15907,\n    \"ĠVictory\": 15908,\n    \"Ġbarn\": 15909,\n    \"Ġdepreciation\": 15910,\n    \"oped\": 15911,\n    \"immer\": 15912,\n    \"Ġgarnered\": 15913,\n    \"ĠLip\": 15914,\n    \"ĠTob\": 15915,\n    \"Ġcreatures\": 15916,\n    \"ooter\": 15917,\n    \"Ġconsortium\": 15918,\n    \"obi\": 15919,\n    \"ĠMonster\": 15920,\n    \"arks\": 15921,\n    \"turn\": 15922,\n    \"Ġsketch\": 15923,\n    \"Ġpredicting\": 15924,\n    \"Ġminimize\": 15925,\n    \"ĠEthan\": 15926,\n    \"anson\": 15927,\n    \"ĠAdjusted\": 15928,\n    \"ĠHornets\": 15929,\n    \"ĠNZ\": 15930,\n    \"ĠKathleen\": 15931,\n    \"ĠKier\": 15932,\n    \"ĠMercury\": 15933,\n    \"Ġghost\": 15934,\n    \"Ġhaw\": 15935,\n    \"ĠDemand\": 15936,\n    \"ĠCollection\": 15937,\n    \"ĠFortune\": 15938,\n    \"Ġcruel\": 15939,\n    \"Ġfurious\": 15940,\n    \"ĠKun\": 15941,\n    \"ĠSalem\": 15942,\n    \"Ġunsuccessful\": 15943,\n    \"ĠLomb\": 15944,\n    \"ĠFury\": 15945,\n    \"ahi\": 15946,\n    \"Ġenthusiastic\": 15947,\n    \"Ġsurgeries\": 15948,\n    \"ACE\": 15949,\n    \"Ġroller\": 15950,\n    \"ĠStamford\": 15951,\n    \"Being\": 15952,\n    \"Dec\": 15953,\n    \"check\": 15954,\n    \"Ġaffection\": 15955,\n    \"Ġgifted\": 15956,\n    \"Ġenerg\": 15957,\n    \"Ġvarying\": 15958,\n    \"ĠCharl\": 15959,\n    \"Ġsolved\": 15960,\n    \"ĠNV\": 15961,\n    \"Ġlaptops\": 15962,\n    \"Ġkindness\": 15963,\n    \"mart\": 15964,\n    \"ĠPenny\": 15965,\n    \"Ġ116\": 15966,\n    \"ĠFeder\": 15967,\n    \"ĠCisco\": 15968,\n    \"Ġeducators\": 15969,\n    \"Ġminim\": 15970,\n    \"Ġgangs\": 15971,\n    \"Ġfestivities\": 15972,\n    \"ĠOriginal\": 15973,\n    \"yre\": 15974,\n    \"rying\": 15975,\n    \"Ġtighter\": 15976,\n    \"ĠMalta\": 15977,\n    \"Ġshield\": 15978,\n    \"interest\": 15979,\n    \"Ġbuoy\": 15980,\n    \"Ġsupplement\": 15981,\n    \"ĠSof\": 15982,\n    \"Ġok\": 15983,\n    \"Ġprosecuted\": 15984,\n    \"Ġinterventions\": 15985,\n    \"Ġseize\": 15986,\n    \"Ġcaravan\": 15987,\n    \"ĠCarlson\": 15988,\n    \"ĠEnterprises\": 15989,\n    \"ĠChristina\": 15990,\n    \"ĠWellington\": 15991,\n    \"Ġaltered\": 15992,\n    \"TP\": 15993,\n    \"Ġexpresses\": 15994,\n    \"Ġcomfortably\": 15995,\n    \"Ġstaffing\": 15996,\n    \"afa\": 15997,\n    \"itu\": 15998,\n    \"saving\": 15999,\n    \"Ġinflammation\": 16000,\n    \"hatt\": 16001,\n    \"ĠMiranda\": 16002,\n    \"icious\": 16003,\n    \"Ġgrabbing\": 16004,\n    \"ĠANY\": 16005,\n    \"Ġobjections\": 16006,\n    \"Ġdot\": 16007,\n    \"cle\": 16008,\n    \"Ġrelates\": 16009,\n    \"Ġtribe\": 16010,\n    \"Ġboarding\": 16011,\n    \"ĠEpisode\": 16012,\n    \"ĠEnjoy\": 16013,\n    \"arding\": 16014,\n    \"Ġathletics\": 16015,\n    \"Ġflies\": 16016,\n    \"Ġmortgages\": 16017,\n    \"ruct\": 16018,\n    \"Ġink\": 16019,\n    \"ĠKC\": 16020,\n    \"ĠSecondary\": 16021,\n    \"Ġfer\": 16022,\n    \"ĠQaeda\": 16023,\n    \"OA\": 16024,\n    \"Frank\": 16025,\n    \"track\": 16026,\n    \"ĠChandler\": 16027,\n    \"Ġenv\": 16028,\n    \"ĠLeaders\": 16029,\n    \"ĠKemp\": 16030,\n    \"Ġunsafe\": 16031,\n    \"sponsored\": 16032,\n    \"San\": 16033,\n    \"ĠUsers\": 16034,\n    \"PE\": 16035,\n    \"ĠAccount\": 16036,\n    \"otta\": 16037,\n    \"ĠMix\": 16038,\n    \"ĠCindy\": 16039,\n    \"En\": 16040,\n    \"Ġ175\": 16041,\n    \"Ġoverlooked\": 16042,\n    \"Ġpublications\": 16043,\n    \"Ġrewarding\": 16044,\n    \"Ġexplicit\": 16045,\n    \"Ġnotch\": 16046,\n    \"Ġspecifics\": 16047,\n    \"Ġdesignation\": 16048,\n    \"ĠAppeal\": 16049,\n    \"Ġcontingent\": 16050,\n    \"Ġcage\": 16051,\n    \"ĠKol\": 16052,\n    \"ĠJohns\": 16053,\n    \"ĠReach\": 16054,\n    \"ĠTin\": 16055,\n    \"ĠAfricans\": 16056,\n    \"Ġprec\": 16057,\n    \"ĠRural\": 16058,\n    \"ĠDw\": 16059,\n    \"Ġuphold\": 16060,\n    \"Ġsuffers\": 16061,\n    \"Ġweed\": 16062,\n    \"inst\": 16063,\n    \"Ġcancellation\": 16064,\n    \"ĠShaun\": 16065,\n    \"Ġleve\": 16066,\n    \"Ġdivisive\": 16067,\n    \"Ġhel\": 16068,\n    \"Ġfatigue\": 16069,\n    \"ĠSchwartz\": 16070,\n    \"ĠKirst\": 16071,\n    \"Ġarise\": 16072,\n    \"Ġgrandson\": 16073,\n    \"ĠLawson\": 16074,\n    \"Ġcollaborate\": 16075,\n    \"Ġparticipant\": 16076,\n    \"ĠBryce\": 16077,\n    \"Ġinfield\": 16078,\n    \"mid\": 16079,\n    \"Ġut\": 16080,\n    \"Ġnotices\": 16081,\n    \"Ġsneak\": 16082,\n    \"ĠPAR\": 16083,\n    \"Chris\": 16084,\n    \"Ġutilize\": 16085,\n    \"ĠByron\": 16086,\n    \"ĠZhang\": 16087,\n    \"PF\": 16088,\n    \"Ġoverwhelmingly\": 16089,\n    \"Ġvegetable\": 16090,\n    \"Ġabsurd\": 16091,\n    \"ĠChem\": 16092,\n    \"etime\": 16093,\n    \"Ġenvoy\": 16094,\n    \"Ġlover\": 16095,\n    \"length\": 16096,\n    \"Ġrevolutionary\": 16097,\n    \"ĠYam\": 16098,\n    \"Ġshutting\": 16099,\n    \"mt\": 16100,\n    \"super\": 16101,\n    \"ĠToby\": 16102,\n    \"ĠCoca\": 16103,\n    \"Ġproposition\": 16104,\n    \"Ġembracing\": 16105,\n    \"Ġversatile\": 16106,\n    \"ĠWalking\": 16107,\n    \"Ġillicit\": 16108,\n    \"Ġnude\": 16109,\n    \"Ġunpredictable\": 16110,\n    \"take\": 16111,\n    \"Ġgotta\": 16112,\n    \"ĠXiaomi\": 16113,\n    \"Ġinstit\": 16114,\n    \"ĠPep\": 16115,\n    \"ĠPearson\": 16116,\n    \"Ġrejection\": 16117,\n    \"stead\": 16118,\n    \"Ġmut\": 16119,\n    \"Ġoutspoken\": 16120,\n    \"ĠBaghdad\": 16121,\n    \"ĠFly\": 16122,\n    \"Ġwholly\": 16123,\n    \"ĠRM\": 16124,\n    \"ĠFa\": 16125,\n    \"Ġcleaner\": 16126,\n    \"frey\": 16127,\n    \"ĠHab\": 16128,\n    \"ĠLiber\": 16129,\n    \"Ġwhereabouts\": 16130,\n    \"Ġchefs\": 16131,\n    \"Ġalumni\": 16132,\n    \"Ġstopp\": 16133,\n    \"dd\": 16134,\n    \"forward\": 16135,\n    \"rast\": 16136,\n    \"ĠNash\": 16137,\n    \"ĠCort\": 16138,\n    \"Ġpotent\": 16139,\n    \"Ġmold\": 16140,\n    \"Ġdistinctive\": 16141,\n    \"chip\": 16142,\n    \"ĠBrunswick\": 16143,\n    \"Ġpopulist\": 16144,\n    \"Ġplagued\": 16145,\n    \"eka\": 16146,\n    \"ĠIOC\": 16147,\n    \"ugs\": 16148,\n    \"ĠDob\": 16149,\n    \"Ġmagn\": 16150,\n    \"asser\": 16151,\n    \"hew\": 16152,\n    \"Ġcapturing\": 16153,\n    \"oos\": 16154,\n    \"Ġcrystal\": 16155,\n    \"Ġalarming\": 16156,\n    \"Ġ135\": 16157,\n    \"iating\": 16158,\n    \"Ġnap\": 16159,\n    \"umar\": 16160,\n    \"ĠExpl\": 16161,\n    \"Ġupgrading\": 16162,\n    \"Ġdecl\": 16163,\n    \"Ġoverturn\": 16164,\n    \"ARK\": 16165,\n    \"linked\": 16166,\n    \"ĠContinued\": 16167,\n    \"Ġslumped\": 16168,\n    \"ĠGaga\": 16169,\n    \"iful\": 16170,\n    \"ĠPosted\": 16171,\n    \"ĠRecommended\": 16172,\n    \"Ġsnake\": 16173,\n    \"Ġexplosives\": 16174,\n    \"Ġhind\": 16175,\n    \"Ġcontempt\": 16176,\n    \"Ġmock\": 16177,\n    \"NBA\": 16178,\n    \"Ġstall\": 16179,\n    \"Ġorganisers\": 16180,\n    \"Ġingredient\": 16181,\n    \"Ġblockbuster\": 16182,\n    \"ĠStream\": 16183,\n    \"ĠLeah\": 16184,\n    \"Pic\": 16185,\n    \"Ġventures\": 16186,\n    \"oman\": 16187,\n    \"Ġweakening\": 16188,\n    \"Ġmaximize\": 16189,\n    \"Ġdigging\": 16190,\n    \"uez\": 16191,\n    \"Ġdistinction\": 16192,\n    \"ĠMali\": 16193,\n    \"Ġcontaminated\": 16194,\n    \"Ġhij\": 16195,\n    \"Ġcrafts\": 16196,\n    \"Fl\": 16197,\n    \"Ġcloset\": 16198,\n    \"ĠRapp\": 16199,\n    \"Ġtowers\": 16200,\n    \"Ġamenities\": 16201,\n    \"Ġopioids\": 16202,\n    \"Ġcontend\": 16203,\n    \"load\": 16204,\n    \"ĠJol\": 16205,\n    \"ĠBooks\": 16206,\n    \"Ġsim\": 16207,\n    \"Ġthrilling\": 16208,\n    \"Ġmeter\": 16209,\n    \"ĠMultiple\": 16210,\n    \"Ġarbitration\": 16211,\n    \"Ġcracked\": 16212,\n    \"Pl\": 16213,\n    \"Ġphotographers\": 16214,\n    \"Te\": 16215,\n    \"ĠSidd\": 16216,\n    \"Ġexplored\": 16217,\n    \"170\": 16218,\n    \"Ġpleasant\": 16219,\n    \"ĠCapitals\": 16220,\n    \"ĠRi\": 16221,\n    \"ĠRandall\": 16222,\n    \"overed\": 16223,\n    \"Ġchar\": 16224,\n    \"ĠEverybody\": 16225,\n    \"ĠPolitics\": 16226,\n    \"Ġmoisture\": 16227,\n    \"Ġthriving\": 16228,\n    \"ĠScotia\": 16229,\n    \"arded\": 16230,\n    \"imb\": 16231,\n    \"ĠFantasy\": 16232,\n    \"Ġcemetery\": 16233,\n    \"ĠPath\": 16234,\n    \"eur\": 16235,\n    \"ĠSec\": 16236,\n    \"ĠPlatform\": 16237,\n    \"Ġdeparted\": 16238,\n    \"ĠVIDEO\": 16239,\n    \"ĠPant\": 16240,\n    \"ĠSyn\": 16241,\n    \"Ġ230\": 16242,\n    \"bleacher\": 16243,\n    \"live\": 16244,\n    \"Ġprob\": 16245,\n    \"Ġgymn\": 16246,\n    \"Ġjudged\": 16247,\n    \"orns\": 16248,\n    \"Ġstemming\": 16249,\n    \"umbling\": 16250,\n    \"ĠHew\": 16251,\n    \"ĠCheryl\": 16252,\n    \"Ġconsciousness\": 16253,\n    \"cos\": 16254,\n    \"ĠTate\": 16255,\n    \"CNN\": 16256,\n    \"Ġrecognizing\": 16257,\n    \"meg\": 16258,\n    \"Ġpant\": 16259,\n    \"ulk\": 16260,\n    \"MM\": 16261,\n    \"ĠPrescott\": 16262,\n    \"ĠMarcel\": 16263,\n    \"anas\": 16264,\n    \"Ġhappier\": 16265,\n    \"mag\": 16266,\n    \"ĠLov\": 16267,\n    \"Ġspreads\": 16268,\n    \"ĠSample\": 16269,\n    \"Ġpopped\": 16270,\n    \"HR\": 16271,\n    \"ĠMitt\": 16272,\n    \"Ġ00\": 16273,\n    \"Ġlabeled\": 16274,\n    \"Ġaspirations\": 16275,\n    \"?)\": 16276,\n    \"Ġloads\": 16277,\n    \"ĠBritt\": 16278,\n    \"hurst\": 16279,\n    \"ĠTeams\": 16280,\n    \"Ġextremists\": 16281,\n    \"ĠClement\": 16282,\n    \"lings\": 16283,\n    \"shirts\": 16284,\n    \"cheon\": 16285,\n    \"ĠDEL\": 16286,\n    \"ĠLocation\": 16287,\n    \"Ġpresentations\": 16288,\n    \"ĠFalcon\": 16289,\n    \"Ġtoddler\": 16290,\n    \"kl\": 16291,\n    \"Ġprone\": 16292,\n    \"Ġcommemor\": 16293,\n    \"ĠStanton\": 16294,\n    \"201\": 16295,\n    \"Ġranges\": 16296,\n    \"Ġfielder\": 16297,\n    \"Ġattends\": 16298,\n    \"rade\": 16299,\n    \"Ġproactive\": 16300,\n    \"Ġhostage\": 16301,\n    \"ĠGriffith\": 16302,\n    \"ockey\": 16303,\n    \"ĠAdding\": 16304,\n    \"ĠAFL\": 16305,\n    \"gas\": 16306,\n    \"istics\": 16307,\n    \"Ġsurgeon\": 16308,\n    \"Ġtsunami\": 16309,\n    \"2014\": 16310,\n    \"Ġconstraints\": 16311,\n    \"cu\": 16312,\n    \"Ġsurrendered\": 16313,\n    \"azed\": 16314,\n    \"ĠAirbnb\": 16315,\n    \"650\": 16316,\n    \"zed\": 16317,\n    \"Ġinjustice\": 16318,\n    \"dog\": 16319,\n    \"full\": 16320,\n    \"ĠHear\": 16321,\n    \"Ġsprawling\": 16322,\n    \"Ġhomeland\": 16323,\n    \"ĠSG\": 16324,\n    \"anced\": 16325,\n    \"Ġpools\": 16326,\n    \"ĠCE\": 16327,\n    \"Ġbeers\": 16328,\n    \"AE\": 16329,\n    \"ĠJac\": 16330,\n    \"Ġrecurring\": 16331,\n    \"Writing\": 16332,\n    \"Ġgenius\": 16333,\n    \"ĠFrost\": 16334,\n    \"Ġgrounded\": 16335,\n    \"Ġallege\": 16336,\n    \"lessness\": 16337,\n    \"Ġjumper\": 16338,\n    \"Ġvicious\": 16339,\n    \"Ġsecretly\": 16340,\n    \"Ġhacked\": 16341,\n    \"ĠAmsterdam\": 16342,\n    \"ibu\": 16343,\n    \"Ġ1971\": 16344,\n    \"ĠRosenstein\": 16345,\n    \"nick\": 16346,\n    \"arge\": 16347,\n    \"Ġladder\": 16348,\n    \"elled\": 16349,\n    \"Ġsatellites\": 16350,\n    \"Ġassassination\": 16351,\n    \"ĠDepot\": 16352,\n    \"built\": 16353,\n    \"Ġunrelated\": 16354,\n    \"maid\": 16355,\n    \"ĠDod\": 16356,\n    \"ĠVanderbilt\": 16357,\n    \"Ġboundary\": 16358,\n    \"ĠStafford\": 16359,\n    \"ĠBry\": 16360,\n    \"Ġtribunal\": 16361,\n    \"Ġoutings\": 16362,\n    \"Ġquantity\": 16363,\n    \"imming\": 16364,\n    \"ĠBlacks\": 16365,\n    \"Br\": 16366,\n    \"eri\": 16367,\n    \"uffed\": 16368,\n    \"Ġexplicitly\": 16369,\n    \"ĠBieber\": 16370,\n    \"AKING\": 16371,\n    \"Ġphotographed\": 16372,\n    \"ĠPolit\": 16373,\n    \"Ġpremature\": 16374,\n    \"hered\": 16375,\n    \"ĠVi\": 16376,\n    \"Ġmarsh\": 16377,\n    \"casters\": 16378,\n    \"ĠKra\": 16379,\n    \"Ġdried\": 16380,\n    \"Ġcafe\": 16381,\n    \"eting\": 16382,\n    \"Ġshaping\": 16383,\n    \"aram\": 16384,\n    \"orf\": 16385,\n    \"Ġrichest\": 16386,\n    \"Ġhurricanes\": 16387,\n    \"Ġcommands\": 16388,\n    \"Gl\": 16389,\n    \"anth\": 16390,\n    \"Ġstunt\": 16391,\n    \"Ġyearly\": 16392,\n    \"Ġdefeats\": 16393,\n    \"Ġconsultancy\": 16394,\n    \"call\": 16395,\n    \"Ġlag\": 16396,\n    \"adh\": 16397,\n    \"ĠPalestine\": 16398,\n    \"Ġcustomized\": 16399,\n    \"ĠScar\": 16400,\n    \"ĠWesley\": 16401,\n    \"ready\": 16402,\n    \"Ġpersist\": 16403,\n    \"Ġpacking\": 16404,\n    \"ono\": 16405,\n    \"Ġdischarged\": 16406,\n    \"Ġpouring\": 16407,\n    \"sburg\": 16408,\n    \"Ġreconsider\": 16409,\n    \"ĠMethod\": 16410,\n    \"enez\": 16411,\n    \"cill\": 16412,\n    \"Ġsecular\": 16413,\n    \"pers\": 16414,\n    \"Ġple\": 16415,\n    \"ELS\": 16416,\n    \"ĠMine\": 16417,\n    \"Ġpushes\": 16418,\n    \"Us\": 16419,\n    \"Ġframes\": 16420,\n    \"ĠNets\": 16421,\n    \"ĠSiem\": 16422,\n    \"ĠHitler\": 16423,\n    \"kill\": 16424,\n    \"Ġrented\": 16425,\n    \"Ġcharm\": 16426,\n    \"Ġpulls\": 16427,\n    \"ĠTide\": 16428,\n    \"Ġinsufficient\": 16429,\n    \"itted\": 16430,\n    \"Care\": 16431,\n    \"iera\": 16432,\n    \"Ġcouch\": 16433,\n    \"aders\": 16434,\n    \"ext\": 16435,\n    \"ĠCitizen\": 16436,\n    \"Ġlogical\": 16437,\n    \"ĠMeadows\": 16438,\n    \"ĠDenis\": 16439,\n    \"ĠDrivers\": 16440,\n    \"Ġrepublic\": 16441,\n    \"Ġadvising\": 16442,\n    \"Ġparamedics\": 16443,\n    \"insky\": 16444,\n    \"illard\": 16445,\n    \"encia\": 16446,\n    \"Ġkh\": 16447,\n    \"Ġrh\": 16448,\n    \"Ġfinalized\": 16449,\n    \"Ġreins\": 16450,\n    \"ĠFarrell\": 16451,\n    \"Ġsteer\": 16452,\n    \"Ġproxy\": 16453,\n    \"unes\": 16454,\n    \"ĠSoul\": 16455,\n    \"ĠCopper\": 16456,\n    \"ĠKenyan\": 16457,\n    \"amped\": 16458,\n    \"conference\": 16459,\n    \"sted\": 16460,\n    \"ĠLon\": 16461,\n    \"Ġreplay\": 16462,\n    \"ĠBle\": 16463,\n    \"Ġvibe\": 16464,\n    \"Ġportfolios\": 16465,\n    \"sea\": 16466,\n    \"Ġbeautifully\": 16467,\n    \"Ġairs\": 16468,\n    \"ĠRap\": 16469,\n    \"ĠKatrina\": 16470,\n    \"Ġberth\": 16471,\n    \"gold\": 16472,\n    \"ĠIsaiah\": 16473,\n    \"iques\": 16474,\n    \"elson\": 16475,\n    \"Ġrelentless\": 16476,\n    \"ĠHighland\": 16477,\n    \"ĠPhilippe\": 16478,\n    \"ĠFol\": 16479,\n    \"Ġenduring\": 16480,\n    \"enz\": 16481,\n    \"Ġaer\": 16482,\n    \"icing\": 16483,\n    \"ĠHTC\": 16484,\n    \"Ġdoping\": 16485,\n    \"ĠAlb\": 16486,\n    \"Ġsom\": 16487,\n    \"icia\": 16488,\n    \"Ġcoroner\": 16489,\n    \"Ġdamn\": 16490,\n    \"Ġ119\": 16491,\n    \"Ġwiped\": 16492,\n    \"ĠAuditor\": 16493,\n    \"hern\": 16494,\n    \"ĠJew\": 16495,\n    \"endra\": 16496,\n    \"osp\": 16497,\n    \"ĠRory\": 16498,\n    \"Ġshapes\": 16499,\n    \"ĠPablo\": 16500,\n    \"Ġforemost\": 16501,\n    \"ĠHos\": 16502,\n    \"ĠCunningham\": 16503,\n    \"145\": 16504,\n    \"ĠRecovery\": 16505,\n    \"!!!\": 16506,\n    \"western\": 16507,\n    \"Ġimaging\": 16508,\n    \"ĠRookie\": 16509,\n    \"ĠMTV\": 16510,\n    \"Ġunc\": 16511,\n    \"ĠSporting\": 16512,\n    \"Ġpatrons\": 16513,\n    \"ĠCoverage\": 16514,\n    \"ĠObservatory\": 16515,\n    \"Ġfishermen\": 16516,\n    \"ĠProvince\": 16517,\n    \"ĠAston\": 16518,\n    \"ĠOsh\": 16519,\n    \"ĠWeekend\": 16520,\n    \"Ġrecruits\": 16521,\n    \"Ġdensity\": 16522,\n    \"FM\": 16523,\n    \"ĠGorsuch\": 16524,\n    \"ĠErie\": 16525,\n    \"lining\": 16526,\n    \"Ġshowcased\": 16527,\n    \"ĠRubio\": 16528,\n    \"Ġchaotic\": 16529,\n    \"Ġattractions\": 16530,\n    \"Ġhug\": 16531,\n    \"ĠHerbert\": 16532,\n    \"ĠRespond\": 16533,\n    \"Ġhappily\": 16534,\n    \"Ġtor\": 16535,\n    \"ĠOTHER\": 16536,\n    \"runner\": 16537,\n    \"ĠShakespeare\": 16538,\n    \"Ġstretching\": 16539,\n    \"ĠJudy\": 16540,\n    \"wyn\": 16541,\n    \"ĠCafe\": 16542,\n    \"Ġgreens\": 16543,\n    \"ĠHend\": 16544,\n    \"Ġglam\": 16545,\n    \"iation\": 16546,\n    \"ĠKingston\": 16547,\n    \"Ġincremental\": 16548,\n    \"Live\": 16549,\n    \"ĠBraun\": 16550,\n    \"USS\": 16551,\n    \"reb\": 16552,\n    \"Ġimperative\": 16553,\n    \"Ġsympathy\": 16554,\n    \"Ġrefuge\": 16555,\n    \"Ġadministered\": 16556,\n    \"rance\": 16557,\n    \"ĠLiberia\": 16558,\n    \"Ġmobil\": 16559,\n    \"heads\": 16560,\n    \"Ġinevitably\": 16561,\n    \"ĠEugene\": 16562,\n    \"ĠBerkshire\": 16563,\n    \"ĠHarbour\": 16564,\n    \"ĠTrends\": 16565,\n    \"TB\": 16566,\n    \"Ġdeficits\": 16567,\n    \"Ġlistings\": 16568,\n    \"Ġreadings\": 16569,\n    \"Ġtumor\": 16570,\n    \"Ġoffic\": 16571,\n    \"opy\": 16572,\n    \"Ġdistracted\": 16573,\n    \"Ġappropriately\": 16574,\n    \"ĠWillis\": 16575,\n    \"Ġskirt\": 16576,\n    \"ĠTea\": 16577,\n    \"Ġshades\": 16578,\n    \"Ġbargaining\": 16579,\n    \"Ġretention\": 16580,\n    \"ĠConcert\": 16581,\n    \"ĠMeteor\": 16582,\n    \"ĠCustom\": 16583,\n    \"Ġinputs\": 16584,\n    \"ĠSah\": 16585,\n    \"enta\": 16586,\n    \"Love\": 16587,\n    \"ĠBurg\": 16588,\n    \"ĠCynthia\": 16589,\n    \"ĠMoses\": 16590,\n    \"ubb\": 16591,\n    \"Ġpeoples\": 16592,\n    \"dh\": 16593,\n    \"ĠFro\": 16594,\n    \"bean\": 16595,\n    \"Ġcigarette\": 16596,\n    \"tta\": 16597,\n    \"umm\": 16598,\n    \"Ġphenomenal\": 16599,\n    \"Ġyelling\": 16600,\n    \"Ġinaug\": 16601,\n    \"Ġconven\": 16602,\n    \"ĠGore\": 16603,\n    \"request\": 16604,\n    \"Ġcolonial\": 16605,\n    \"ĠAleppo\": 16606,\n    \"Ġdemolition\": 16607,\n    \"Ġamounted\": 16608,\n    \"Ġstaggering\": 16609,\n    \"Ġclips\": 16610,\n    \"Ġinconsistent\": 16611,\n    \"ĠMilton\": 16612,\n    \"ĠWireless\": 16613,\n    \"ĠReno\": 16614,\n    \"ĠPerkins\": 16615,\n    \"Ġunusually\": 16616,\n    \"Ġmemor\": 16617,\n    \"Ġhectares\": 16618,\n    \"Ġlat\": 16619,\n    \"central\": 16620,\n    \"ĠDig\": 16621,\n    \"ĠMarina\": 16622,\n    \"ĠPartner\": 16623,\n    \"daily\": 16624,\n    \"your\": 16625,\n    \"Reilly\": 16626,\n    \"Ġpope\": 16627,\n    \"phy\": 16628,\n    \"Ġassessing\": 16629,\n    \"ĠRodrigo\": 16630,\n    \"wi\": 16631,\n    \"Ġcompatible\": 16632,\n    \"imate\": 16633,\n    \"Ġgentle\": 16634,\n    \"ĠRhodes\": 16635,\n    \"Brexit\": 16636,\n    \"ieve\": 16637,\n    \"Ġbreaches\": 16638,\n    \"Ġchopped\": 16639,\n    \"Ġcancers\": 16640,\n    \"VEL\": 16641,\n    \"Ġsluggish\": 16642,\n    \"ĠUltra\": 16643,\n    \"ĠUl\": 16644,\n    \"Ġcrises\": 16645,\n    \"ONE\": 16646,\n    \"ĠEquipment\": 16647,\n    \"Ġcater\": 16648,\n    \"Ġadjourn\": 16649,\n    \"Ġreadily\": 16650,\n    \"ĠRolling\": 16651,\n    \"ĠBott\": 16652,\n    \"inel\": 16653,\n    \"ĠRule\": 16654,\n    \"Ġgrind\": 16655,\n    \"ĠHussain\": 16656,\n    \"ussie\": 16657,\n    \"Ġdepressed\": 16658,\n    \"ĠImperial\": 16659,\n    \"ongo\": 16660,\n    \"Ġuniforms\": 16661,\n    \"Ġ117\": 16662,\n    \"Ġchambers\": 16663,\n    \"ĠDum\": 16664,\n    \"ifi\": 16665,\n    \"ĠBetty\": 16666,\n    \"ĠTA\": 16667,\n    \"Ġpromotions\": 16668,\n    \"itary\": 16669,\n    \"Ġcried\": 16670,\n    \"Ġbranding\": 16671,\n    \"ĠBahamas\": 16672,\n    \"ĠDat\": 16673,\n    \"Ġantibiotics\": 16674,\n    \"ĠAus\": 16675,\n    \"Ġumbrella\": 16676,\n    \"Ġgradual\": 16677,\n    \"Ġaltercation\": 16678,\n    \"Ġlure\": 16679,\n    \"ĠJakarta\": 16680,\n    \"Ġunified\": 16681,\n    \"chin\": 16682,\n    \"ettes\": 16683,\n    \"ĠRwanda\": 16684,\n    \"ulations\": 16685,\n    \"Ġbrink\": 16686,\n    \"Ġbroadcasting\": 16687,\n    \"ĠArtist\": 16688,\n    \"Ġrecon\": 16689,\n    \"Ġaqu\": 16690,\n    \"ĠServ\": 16691,\n    \"999\": 16692,\n    \"ĠParticipants\": 16693,\n    \"ĠVentures\": 16694,\n    \"fight\": 16695,\n    \"Ġactivism\": 16696,\n    \"Ġstructured\": 16697,\n    \"Ġportal\": 16698,\n    \"Ġtendency\": 16699,\n    \"ĠAssociate\": 16700,\n    \"Ġcalf\": 16701,\n    \"ĠOrd\": 16702,\n    \"ĠTi\": 16703,\n    \"ĠFrancois\": 16704,\n    \"uary\": 16705,\n    \"ĠVik\": 16706,\n    \"urchase\": 16707,\n    \"Ġfried\": 16708,\n    \"Ġbooming\": 16709,\n    \"Ġparticles\": 16710,\n    \"amas\": 16711,\n    \"INA\": 16712,\n    \"Super\": 16713,\n    \"supp\": 16714,\n    \"urring\": 16715,\n    \"ĠWatts\": 16716,\n    \"affer\": 16717,\n    \"ĠDEC\": 16718,\n    \"Ġroadway\": 16719,\n    \"border\": 16720,\n    \"Ġsequ\": 16721,\n    \"entially\": 16722,\n    \"ieg\": 16723,\n    \"Ġcamping\": 16724,\n    \"Ġ750\": 16725,\n    \"Ġcycles\": 16726,\n    \"ĠReese\": 16727,\n    \"ĠFellow\": 16728,\n    \"isters\": 16729,\n    \"ĠVehicle\": 16730,\n    \"kies\": 16731,\n    \"ĠJonas\": 16732,\n    \"Ġfoundations\": 16733,\n    \"ĠNigel\": 16734,\n    \"Ġstab\": 16735,\n    \"Ġcongressman\": 16736,\n    \"ĠWichita\": 16737,\n    \"antes\": 16738,\n    \"Ġprogression\": 16739,\n    \"Ġditch\": 16740,\n    \"lik\": 16741,\n    \"Ġsid\": 16742,\n    \"Ġele\": 16743,\n    \"ĠMund\": 16744,\n    \"Ġstairs\": 16745,\n    \"lete\": 16746,\n    \"Ġlingering\": 16747,\n    \"Ġsadly\": 16748,\n    \"Ġay\": 16749,\n    \"Em\": 16750,\n    \"Ġdeadliest\": 16751,\n    \"soon\": 16752,\n    \"Ġtangible\": 16753,\n    \"Ġabusing\": 16754,\n    \"Ġcomprises\": 16755,\n    \"vil\": 16756,\n    \"ĠBun\": 16757,\n    \"Ġdoubling\": 16758,\n    \"Ġcommun\": 16759,\n    \"Ġslogan\": 16760,\n    \"Ġloading\": 16761,\n    \"Ġshallow\": 16762,\n    \"Ġattributes\": 16763,\n    \"Che\": 16764,\n    \"Ġcheering\": 16765,\n    \"Ġrefuses\": 16766,\n    \"cam\": 16767,\n    \"bes\": 16768,\n    \"hon\": 16769,\n    \"ĠSpartans\": 16770,\n    \"cept\": 16771,\n    \"ĠComputer\": 16772,\n    \"ĠCanberra\": 16773,\n    \"ĠWARNING\": 16774,\n    \"Ġstuffed\": 16775,\n    \"block\": 16776,\n    \"ĠJennings\": 16777,\n    \"ĠAU\": 16778,\n    \"atin\": 16779,\n    \"Ġom\": 16780,\n    \"Ġbachelor\": 16781,\n    \"Ġprediction\": 16782,\n    \"ĠWinner\": 16783,\n    \"agne\": 16784,\n    \"Ġrob\": 16785,\n    \"ĠKatherine\": 16786,\n    \"Ġli\": 16787,\n    \"ĠHumph\": 16788,\n    \"ĠPEOPLE\": 16789,\n    \"IRO\": 16790,\n    \"Cola\": 16791,\n    \"Ġguitarist\": 16792,\n    \"isen\": 16793,\n    \"ĠHighlights\": 16794,\n    \"Ġwelcomes\": 16795,\n    \"Ġprisoner\": 16796,\n    \"Ġpsychology\": 16797,\n    \"Ġextradition\": 16798,\n    \"Ġrou\": 16799,\n    \"ĠLund\": 16800,\n    \"Ġthoughtful\": 16801,\n    \"RY\": 16802,\n    \"orman\": 16803,\n    \"Alex\": 16804,\n    \"Ġlaughter\": 16805,\n    \"Ġfumble\": 16806,\n    \"Ġsynthetic\": 16807,\n    \"Ġdigit\": 16808,\n    \"ĠRoc\": 16809,\n    \"ĠFactory\": 16810,\n    \"ellery\": 16811,\n    \"ishment\": 16812,\n    \"ilar\": 16813,\n    \"ĠEarl\": 16814,\n    \"ĠSutton\": 16815,\n    \"ĠJur\": 16816,\n    \"ĠAllan\": 16817,\n    \"ĠKoreans\": 16818,\n    \"uki\": 16819,\n    \"Ġculinary\": 16820,\n    \"PU\": 16821,\n    \"Stock\": 16822,\n    \"stars\": 16823,\n    \"ĠDayton\": 16824,\n    \"beck\": 16825,\n    \"Ġinstability\": 16826,\n    \"ĠBring\": 16827,\n    \"Ġbreeding\": 16828,\n    \"Ġmiracle\": 16829,\n    \"bons\": 16830,\n    \"Ġdonating\": 16831,\n    \"ĠKick\": 16832,\n    \"ĠSag\": 16833,\n    \"afi\": 16834,\n    \"Ġharassed\": 16835,\n    \"asm\": 16836,\n    \"Their\": 16837,\n    \"inity\": 16838,\n    \"Ġacademics\": 16839,\n    \"Ġstatute\": 16840,\n    \"ĠAmit\": 16841,\n    \"Ġpressured\": 16842,\n    \"east\": 16843,\n    \"\\\"),\": 16844,\n    \"iso\": 16845,\n    \"220\": 16846,\n    \"Ġairplane\": 16847,\n    \"ĠMcCabe\": 16848,\n    \"ctions\": 16849,\n    \"ĠMesa\": 16850,\n    \"Ġsensational\": 16851,\n    \"ĠFE\": 16852,\n    \"ĠNeigh\": 16853,\n    \"Ġbribery\": 16854,\n    \"Ġflaws\": 16855,\n    \"Ġfemales\": 16856,\n    \"Ġmisses\": 16857,\n    \"ĠColor\": 16858,\n    \"ĠVietnamese\": 16859,\n    \"ĠMental\": 16860,\n    \"Unfortunately\": 16861,\n    \"ĠPont\": 16862,\n    \"Ġ1940\": 16863,\n    \"dry\": 16864,\n    \"ĠGazette\": 16865,\n    \"ĠAns\": 16866,\n    \"Ġwhistle\": 16867,\n    \"Ġsymbolic\": 16868,\n    \"Ġpossessions\": 16869,\n    \"ĠDriver\": 16870,\n    \"Ġbracket\": 16871,\n    \"ĠReign\": 16872,\n    \"oji\": 16873,\n    \"Ġoct\": 16874,\n    \"Ġtube\": 16875,\n    \"ĠFelix\": 16876,\n    \"Ġtranslated\": 16877,\n    \"Ġpromptly\": 16878,\n    \"ĠErnest\": 16879,\n    \"arth\": 16880,\n    \"Ġdumb\": 16881,\n    \"Ġinfluences\": 16882,\n    \"taking\": 16883,\n    \"Ġprivat\": 16884,\n    \"erers\": 16885,\n    \"Ġmalware\": 16886,\n    \"Ġpredictable\": 16887,\n    \"Ġtighten\": 16888,\n    \"Ġheights\": 16889,\n    \"Ġfairness\": 16890,\n    \"facing\": 16891,\n    \"Ġrematch\": 16892,\n    \"Ġpoet\": 16893,\n    \"Ġfundamentally\": 16894,\n    \"Ġcoveted\": 16895,\n    \"Ġlivelihood\": 16896,\n    \"ĠABOUT\": 16897,\n    \"Ġsourced\": 16898,\n    \"Ġdeferred\": 16899,\n    \"Ġslashed\": 16900,\n    \"ĠSchultz\": 16901,\n    \"Ġtriggering\": 16902,\n    \"ĠShiv\": 16903,\n    \"Ġlithium\": 16904,\n    \"ahead\": 16905,\n    \"Ġleisure\": 16906,\n    \"Ġbackpack\": 16907,\n    \"ilateral\": 16908,\n    \"ĠNuclear\": 16909,\n    \"ĠLeone\": 16910,\n    \"ĠNice\": 16911,\n    \"Ġenthusiasts\": 16912,\n    \"September\": 16913,\n    \"Ġenroll\": 16914,\n    \"ĠWear\": 16915,\n    \"erey\": 16916,\n    \"angs\": 16917,\n    \"such\": 16918,\n    \"Ġunpopular\": 16919,\n    \"Ġdisciplined\": 16920,\n    \"Ġshrinking\": 16921,\n    \"ĠBrewing\": 16922,\n    \"ĠReally\": 16923,\n    \"Ġdirective\": 16924,\n    \"175\": 16925,\n    \"Ġnotifications\": 16926,\n    \"Ġfortunes\": 16927,\n    \"ĠHour\": 16928,\n    \"ĠGan\": 16929,\n    \"ĠChurchill\": 16930,\n    \"ĠDodge\": 16931,\n    \"ĠJeep\": 16932,\n    \"Ġsour\": 16933,\n    \"Ġderived\": 16934,\n    \"Ġft\": 16935,\n    \"riv\": 16936,\n    \"Ġlaundry\": 16937,\n    \"Ġfentanyl\": 16938,\n    \"ĠSioux\": 16939,\n    \"achi\": 16940,\n    \"workers\": 16941,\n    \"Ġworkload\": 16942,\n    \"rooms\": 16943,\n    \"ĠQU\": 16944,\n    \"ĠTruth\": 16945,\n    \"Ġdefenses\": 16946,\n    \"Ġdunk\": 16947,\n    \"Ĳ\": 16948,\n    \"Ġderby\": 16949,\n    \"ĠMotion\": 16950,\n    \"ĠMayo\": 16951,\n    \"ĠIke\": 16952,\n    \"Ġpreferences\": 16953,\n    \"Ġped\": 16954,\n    \"elman\": 16955,\n    \"moon\": 16956,\n    \"Ġshoots\": 16957,\n    \"ĠNoel\": 16958,\n    \"Ġmilit\": 16959,\n    \"ĠCambodia\": 16960,\n    \"ĠMLA\": 16961,\n    \"Ġhonoured\": 16962,\n    \"fast\": 16963,\n    \"Ġalgorithms\": 16964,\n    \"Ġstormed\": 16965,\n    \"NT\": 16966,\n    \"Benz\": 16967,\n    \"Ġvaccines\": 16968,\n    \"Ġmarching\": 16969,\n    \"Ġ118\": 16970,\n    \"ĠWilmington\": 16971,\n    \"GM\": 16972,\n    \"coin\": 16973,\n    \"Ġunderwater\": 16974,\n    \"ĠClearly\": 16975,\n    \"Ġorgans\": 16976,\n    \"mir\": 16977,\n    \"Ġdenounced\": 16978,\n    \"pless\": 16979,\n    \"imal\": 16980,\n    \"ĠKom\": 16981,\n    \"Ġfatalities\": 16982,\n    \"Ġyoungster\": 16983,\n    \"Ġthirty\": 16984,\n    \"Ġinternally\": 16985,\n    \"222\": 16986,\n    \"Ġdemonstrating\": 16987,\n    \"Ġbusiest\": 16988,\n    \"Ġperpetrators\": 16989,\n    \"Ġstun\": 16990,\n    \"Both\": 16991,\n    \"ĠMcCoy\": 16992,\n    \"gn\": 16993,\n    \"ĠDalton\": 16994,\n    \"ĠDAY\": 16995,\n    \"Ġsacred\": 16996,\n    \"Ġconsuming\": 16997,\n    \"Ġ(+\": 16998,\n    \"ĠPioneer\": 16999,\n    \"ĠApplications\": 17000,\n    \"ĠBolt\": 17001,\n    \"ĠBarkley\": 17002,\n    \"ĠExpo\": 17003,\n    \"ĠLore\": 17004,\n    \"ĠPrivacy\": 17005,\n    \"ĠHarley\": 17006,\n    \"Ġtractor\": 17007,\n    \"Ġtenth\": 17008,\n    \"ĠHaiti\": 17009,\n    \"ÃŃn\": 17010,\n    \"ĠTVs\": 17011,\n    \"ĠCathedral\": 17012,\n    \"Ġunite\": 17013,\n    \"Ġbinding\": 17014,\n    \"oks\": 17015,\n    \"ĠJenny\": 17016,\n    \"Ġcaller\": 17017,\n    \"ĠIngram\": 17018,\n    \"ĠPrairie\": 17019,\n    \"Ġrunoff\": 17020,\n    \"Ġasserted\": 17021,\n    \"icit\": 17022,\n    \"ĠSie\": 17023,\n    \"102\": 17024,\n    \"ĠMB\": 17025,\n    \"Ġobstruction\": 17026,\n    \"Ġgroom\": 17027,\n    \"Ġtolerate\": 17028,\n    \"Ġcans\": 17029,\n    \"forth\": 17030,\n    \"Ġvillain\": 17031,\n    \"Ġdefining\": 17032,\n    \"ĠFrenchman\": 17033,\n    \"otte\": 17034,\n    \"Ġcontr\": 17035,\n    \"clock\": 17036,\n    \"onder\": 17037,\n    \"Ġprolific\": 17038,\n    \"ĠElectronic\": 17039,\n    \"ĠSak\": 17040,\n    \"annie\": 17041,\n    \"ASS\": 17042,\n    \"Ġmultinational\": 17043,\n    \"Associated\": 17044,\n    \"IZ\": 17045,\n    \"ĠBelle\": 17046,\n    \"Ġmand\": 17047,\n    \"asis\": 17048,\n    \"Mac\": 17049,\n    \"Ġpretend\": 17050,\n    \"ĠCommunication\": 17051,\n    \"Ġheartbreaking\": 17052,\n    \"ĠShepherd\": 17053,\n    \"ĠBIG\": 17054,\n    \"mph\": 17055,\n    \"ĠShield\": 17056,\n    \"ĠLiv\": 17057,\n    \"ĠStatus\": 17058,\n    \"Ġbikini\": 17059,\n    \"Ġranch\": 17060,\n    \"Ġpeacefully\": 17061,\n    \"ITCH\": 17062,\n    \"bourne\": 17063,\n    \"ĠVariety\": 17064,\n    \"Ġstationed\": 17065,\n    \"Ġhed\": 17066,\n    \"Ġexhausted\": 17067,\n    \"Ġsurpassed\": 17068,\n    \"Ġcatalyst\": 17069,\n    \"Ġsmuggling\": 17070,\n    \"uating\": 17071,\n    \"Ġ123\": 17072,\n    \"Ġdup\": 17073,\n    \"ĠSul\": 17074,\n    \"conf\": 17075,\n    \"jit\": 17076,\n    \"Ġmaiden\": 17077,\n    \"asta\": 17078,\n    \"ĠCalvin\": 17079,\n    \"borne\": 17080,\n    \"Ġgrim\": 17081,\n    \"Ġtort\": 17082,\n    \"cott\": 17083,\n    \"olas\": 17084,\n    \"NR\": 17085,\n    \"Ġbreakout\": 17086,\n    \"ĠHun\": 17087,\n    \"ĠGuatemala\": 17088,\n    \"Ġhistorian\": 17089,\n    \"ĠLawyers\": 17090,\n    \"ĠDisplay\": 17091,\n    \"Ġobstruct\": 17092,\n    \"ĠOsborne\": 17093,\n    \"Ġtherapies\": 17094,\n    \"ĠAub\": 17095,\n    \"Ġinjunction\": 17096,\n    \"stroke\": 17097,\n    \"Ġseafood\": 17098,\n    \"Ġhazardous\": 17099,\n    \"ĠWolver\": 17100,\n    \"ĠViolence\": 17101,\n    \"ĠBillion\": 17102,\n    \"ĠLetter\": 17103,\n    \"ĠWorldwide\": 17104,\n    \"Real\": 17105,\n    \"Ġexpires\": 17106,\n    \"Ġflawed\": 17107,\n    \"European\": 17108,\n    \"Ġrigorous\": 17109,\n    \"ĠSimilar\": 17110,\n    \"ĠSurface\": 17111,\n    \"ĠEF\": 17112,\n    \"mys\": 17113,\n    \"ĠFunds\": 17114,\n    \"ographer\": 17115,\n    \"Ġtribes\": 17116,\n    \"Ġspouse\": 17117,\n    \"Ġunsure\": 17118,\n    \"aways\": 17119,\n    \"Ġtrainers\": 17120,\n    \"arie\": 17121,\n    \"ĠZar\": 17122,\n    \"ĠComedy\": 17123,\n    \"ĠLit\": 17124,\n    \"ĠNoon\": 17125,\n    \"Ġgallon\": 17126,\n    \"Ġconsulate\": 17127,\n    \"ĠBras\": 17128,\n    \"iology\": 17129,\n    \"onies\": 17130,\n    \"ĠBelichick\": 17131,\n    \"ĠRoot\": 17132,\n    \"ĠLux\": 17133,\n    \"ĠSed\": 17134,\n    \"ĠTos\": 17135,\n    \"Ġinherited\": 17136,\n    \"tw\": 17137,\n    \"Ġdeaf\": 17138,\n    \"Ġdriveway\": 17139,\n    \"jah\": 17140,\n    \"ĠScientific\": 17141,\n    \"ĠNottingham\": 17142,\n    \"both\": 17143,\n    \"awan\": 17144,\n    \"Ġnut\": 17145,\n    \"ĠLebanese\": 17146,\n    \"ĠAAA\": 17147,\n    \"ĠSuzuki\": 17148,\n    \"ĠBU\": 17149,\n    \"ells\": 17150,\n    \"Ġspecify\": 17151,\n    \"ĠNotes\": 17152,\n    \"Ġvoluntarily\": 17153,\n    \"ĠMolly\": 17154,\n    \"Ġoutskirts\": 17155,\n    \"Ġbehaviors\": 17156,\n    \"Ġmilitia\": 17157,\n    \"Ġsplash\": 17158,\n    \"Ġpersonalized\": 17159,\n    \"ĠFiat\": 17160,\n    \"ĠKind\": 17161,\n    \"ĠTruck\": 17162,\n    \"py\": 17163,\n    \"ĠWIN\": 17164,\n    \"dist\": 17165,\n    \"itational\": 17166,\n    \"APP\": 17167,\n    \"ĠPelicans\": 17168,\n    \"ĠGam\": 17169,\n    \"mel\": 17170,\n    \"Ġmandated\": 17171,\n    \"Ġbalances\": 17172,\n    \"ĠWizards\": 17173,\n    \"iary\": 17174,\n    \"ĠAvailable\": 17175,\n    \"Ġkay\": 17176,\n    \"jin\": 17177,\n    \"eyed\": 17178,\n    \"Ġsterling\": 17179,\n    \"Ġconcealed\": 17180,\n    \"ĠFedEx\": 17181,\n    \"ĠPO\": 17182,\n    \"ĠJacqu\": 17183,\n    \"anted\": 17184,\n    \"eme\": 17185,\n    \"ĠDefensive\": 17186,\n    \"manship\": 17187,\n    \"Ġreliever\": 17188,\n    \"Ġshortstop\": 17189,\n    \"Ġphot\": 17190,\n    \"ĠGain\": 17191,\n    \"ĠConcern\": 17192,\n    \"due\": 17193,\n    \"Ġalgorithm\": 17194,\n    \"fell\": 17195,\n    \"ĠMountains\": 17196,\n    \"icians\": 17197,\n    \"Ġhonoring\": 17198,\n    \"Ġuploaded\": 17199,\n    \"Ġtore\": 17200,\n    \"GH\": 17201,\n    \"orde\": 17202,\n    \"ĠCoin\": 17203,\n    \"ĠAven\": 17204,\n    \"Ġliterary\": 17205,\n    \"Before\": 17206,\n    \"Ġtactic\": 17207,\n    \"Ġsocially\": 17208,\n    \"ĠSik\": 17209,\n    \"Ġthermal\": 17210,\n    \"Ġhor\": 17211,\n    \"price\": 17212,\n    \"Ġrooted\": 17213,\n    \"arrow\": 17214,\n    \"Ġcirculating\": 17215,\n    \"Ġlaughs\": 17216,\n    \"ĠLines\": 17217,\n    \"lig\": 17218,\n    \"Ġjudgement\": 17219,\n    \"....\": 17220,\n    \"Ġsewer\": 17221,\n    \"Ġdancer\": 17222,\n    \"ĠPens\": 17223,\n    \"Ġsig\": 17224,\n    \"ische\": 17225,\n    \"wives\": 17226,\n    \"Ġgran\": 17227,\n    \"ĠBron\": 17228,\n    \"ĠHyde\": 17229,\n    \"yards\": 17230,\n    \"Ġcandidacy\": 17231,\n    \"Ġhey\": 17232,\n    \"Ġcontributors\": 17233,\n    \"ĠUpdated\": 17234,\n    \"Ġ190\": 17235,\n    \"Ġhalls\": 17236,\n    \"Ġemphas\": 17237,\n    \"ĠCherry\": 17238,\n    \"Ġrim\": 17239,\n    \"Ġbilled\": 17240,\n    \"Ġbaked\": 17241,\n    \"ĠPopular\": 17242,\n    \"lb\": 17243,\n    \"Ġgravity\": 17244,\n    \"Under\": 17245,\n    \"Ġreservation\": 17246,\n    \"organ\": 17247,\n    \"ĠPict\": 17248,\n    \"ĠWhitney\": 17249,\n    \"Ġonboard\": 17250,\n    \"NEY\": 17251,\n    \"ĠBreaking\": 17252,\n    \"Ġflagged\": 17253,\n    \"rar\": 17254,\n    \"ĠBasic\": 17255,\n    \"ĠDomestic\": 17256,\n    \"ĠPent\": 17257,\n    \"Ġvigilant\": 17258,\n    \"Ġzoning\": 17259,\n    \"Fire\": 17260,\n    \"Ġcorrected\": 17261,\n    \"isbury\": 17262,\n    \"ĠLaure\": 17263,\n    \"ĠDevon\": 17264,\n    \"print\": 17265,\n    \"ĠTopics\": 17266,\n    \"ĠFuel\": 17267,\n    \"Ġcirculation\": 17268,\n    \"ĠPratt\": 17269,\n    \"Ġskiing\": 17270,\n    \"Ġtornado\": 17271,\n    \"dep\": 17272,\n    \"ĠUnless\": 17273,\n    \"ifting\": 17274,\n    \"Ġfool\": 17275,\n    \"should\": 17276,\n    \"Ġinspectors\": 17277,\n    \"Ġprotested\": 17278,\n    \"Ġba\": 17279,\n    \"ussia\": 17280,\n    \"Ġspun\": 17281,\n    \"grass\": 17282,\n    \"phone\": 17283,\n    \"Ġpotato\": 17284,\n    \"ĠBehind\": 17285,\n    \"cil\": 17286,\n    \"Ġconcession\": 17287,\n    \"Ġapplause\": 17288,\n    \"ĠChin\": 17289,\n    \"Ġceremonies\": 17290,\n    \"pit\": 17291,\n    \"Ġtraumatic\": 17292,\n    \"Ġbasics\": 17293,\n    \"Ġparameters\": 17294,\n    \"ĠMoz\": 17295,\n    \"ĠAIDS\": 17296,\n    \"Ph\": 17297,\n    \"Ġjudging\": 17298,\n    \"Ġlecture\": 17299,\n    \"Ġmunicipality\": 17300,\n    \"Ġcardiac\": 17301,\n    \"ogan\": 17302,\n    \"pir\": 17303,\n    \"could\": 17304,\n    \"Channel\": 17305,\n    \"Ġshattered\": 17306,\n    \"ĠAV\": 17307,\n    \"continental\": 17308,\n    \"chie\": 17309,\n    \"ibi\": 17310,\n    \"ĠOy\": 17311,\n    \"Mon\": 17312,\n    \"ĠCN\": 17313,\n    \"WC\": 17314,\n    \"Ġdistributor\": 17315,\n    \"ĠSavannah\": 17316,\n    \"Ġcleaned\": 17317,\n    \"ĠFlores\": 17318,\n    \"Ġembarrassed\": 17319,\n    \"Ġclay\": 17320,\n    \"Ġvolcano\": 17321,\n    \"Ġstressful\": 17322,\n    \"Ġsummoned\": 17323,\n    \"ĠSeg\": 17324,\n    \"Ġstatistical\": 17325,\n    \"ĠShak\": 17326,\n    \"Ġadequately\": 17327,\n    \"worthy\": 17328,\n    \"fighting\": 17329,\n    \"alan\": 17330,\n    \"Ġnecessity\": 17331,\n    \"Ġresidency\": 17332,\n    \"Ġsober\": 17333,\n    \"arius\": 17334,\n    \"ĠTaj\": 17335,\n    \"mount\": 17336,\n    \"wards\": 17337,\n    \"Ġaesthetic\": 17338,\n    \"Coin\": 17339,\n    \"ĠDew\": 17340,\n    \"were\": 17341,\n    \"SK\": 17342,\n    \"Ġpowerhouse\": 17343,\n    \"Ġcleanup\": 17344,\n    \"ĠWITH\": 17345,\n    \"ĠHers\": 17346,\n    \"ĠRao\": 17347,\n    \"ĠFlyers\": 17348,\n    \"Ġdominating\": 17349,\n    \"issued\": 17350,\n    \"ĠMcGr\": 17351,\n    \"Ġinsurgency\": 17352,\n    \"Ġburial\": 17353,\n    \"ĠPlains\": 17354,\n    \"ensive\": 17355,\n    \"ĠPresent\": 17356,\n    \"Mo\": 17357,\n    \"Ġnerves\": 17358,\n    \"Ġsmoothly\": 17359,\n    \"staff\": 17360,\n    \"Ġrestoring\": 17361,\n    \"ĠGeneration\": 17362,\n    \"Ġcommuters\": 17363,\n    \"ĠLegend\": 17364,\n    \"ĠGad\": 17365,\n    \"lied\": 17366,\n    \"Ġissuer\": 17367,\n    \"ĠDozens\": 17368,\n    \"Ġphases\": 17369,\n    \"ĠWu\": 17370,\n    \"ĠTunisia\": 17371,\n    \"ĠPacers\": 17372,\n    \"Ġdur\": 17373,\n    \"ĠIG\": 17374,\n    \"annon\": 17375,\n    \"sided\": 17376,\n    \"Ġvo\": 17377,\n    \"ĠNI\": 17378,\n    \"Ġvitamin\": 17379,\n    \"Ġsoc\": 17380,\n    \"Ġimmunity\": 17381,\n    \"Ġgenerates\": 17382,\n    \"ĠMcGu\": 17383,\n    \"Ġexplores\": 17384,\n    \"Ġassistants\": 17385,\n    \"Ġstems\": 17386,\n    \"ushed\": 17387,\n    \"ĠZak\": 17388,\n    \"ĠOwners\": 17389,\n    \"Ġvariant\": 17390,\n    \"ardy\": 17391,\n    \"ĠNewark\": 17392,\n    \"ĠCatalonia\": 17393,\n    \"Ġautonomy\": 17394,\n    \"Ġgreet\": 17395,\n    \"Ġawait\": 17396,\n    \"ĠLuckily\": 17397,\n    \"ĠTicket\": 17398,\n    \"ĠSTOR\": 17399,\n    \"asy\": 17400,\n    \"Ġincorrect\": 17401,\n    \"Ġconsisting\": 17402,\n    \"Ġperspectives\": 17403,\n    \"ĠQuint\": 17404,\n    \"Ġtotaling\": 17405,\n    \"Ġnortheastern\": 17406,\n    \"Ġcharacterized\": 17407,\n    \"Ġsurfaces\": 17408,\n    \"nation\": 17409,\n    \"Ġprevents\": 17410,\n    \"ĠSho\": 17411,\n    \"Ġelectorate\": 17412,\n    \"Ġshortfall\": 17413,\n    \"chy\": 17414,\n    \"aws\": 17415,\n    \"ĠAddress\": 17416,\n    \"Ġdefensively\": 17417,\n    \"quel\": 17418,\n    \"chester\": 17419,\n    \"Ġterr\": 17420,\n    \"ahu\": 17421,\n    \"lined\": 17422,\n    \"ĠNev\": 17423,\n    \"unn\": 17424,\n    \"Def\": 17425,\n    \"pc\": 17426,\n    \"ĠSig\": 17427,\n    \"Ġnonetheless\": 17428,\n    \"ĠSundays\": 17429,\n    \"ĠBAS\": 17430,\n    \"Ġpolicemen\": 17431,\n    \"ĠGoal\": 17432,\n    \"apa\": 17433,\n    \"Ġrope\": 17434,\n    \"Ġoutage\": 17435,\n    \"ĠPaso\": 17436,\n    \"Ġsadness\": 17437,\n    \"ĠGrowing\": 17438,\n    \"ĠKyr\": 17439,\n    \"Ġale\": 17440,\n    \"ĠBreitbart\": 17441,\n    \"ĠVia\": 17442,\n    \"ĠBrig\": 17443,\n    \"idence\": 17444,\n    \"Ġ145\": 17445,\n    \"quire\": 17446,\n    \"Ġdistraction\": 17447,\n    \"ĠOdd\": 17448,\n    \"ĠSimply\": 17449,\n    \"ĠNin\": 17450,\n    \"Ġcompetent\": 17451,\n    \"ded\": 17452,\n    \"iper\": 17453,\n    \"ĠKaty\": 17454,\n    \"ĠSolomon\": 17455,\n    \"Ġfeeds\": 17456,\n    \"ĠMort\": 17457,\n    \"ĠRica\": 17458,\n    \"affe\": 17459,\n    \"Ġcooperating\": 17460,\n    \"Ġarrivals\": 17461,\n    \"Ġdelete\": 17462,\n    \"ĠAth\": 17463,\n    \"Ġtrustees\": 17464,\n    \"Ġtub\": 17465,\n    \"Ġsaga\": 17466,\n    \"otes\": 17467,\n    \"ĠCJ\": 17468,\n    \"Ġexited\": 17469,\n    \"stakes\": 17470,\n    \"Ġinflu\": 17471,\n    \"2000\": 17472,\n    \"ĠDonovan\": 17473,\n    \"ĠNur\": 17474,\n    \"Ġoutline\": 17475,\n    \"Ġaudition\": 17476,\n    \"oked\": 17477,\n    \"ĠJag\": 17478,\n    \"money\": 17479,\n    \"Ġcardiovascular\": 17480,\n    \"song\": 17481,\n    \"ĠOften\": 17482,\n    \"ĠGoff\": 17483,\n    \"ĠOaks\": 17484,\n    \"Will\": 17485,\n    \"acon\": 17486,\n    \"Ġ?\": 17487,\n    \"Har\": 17488,\n    \"ĠLambert\": 17489,\n    \"atoon\": 17490,\n    \"ĠAF\": 17491,\n    \"ĠMavericks\": 17492,\n    \"nia\": 17493,\n    \"ĠChennai\": 17494,\n    \"\\\"},\\\"\": 17495,\n    \"Ġpairing\": 17496,\n    \"mad\": 17497,\n    \"ause\": 17498,\n    \"ĠRide\": 17499,\n    \"111\": 17500,\n    \"ĠFallon\": 17501,\n    \"ĠHyder\": 17502,\n    \"ĠPiper\": 17503,\n    \"Ġfilmmakers\": 17504,\n    \"icon\": 17505,\n    \"ĠBeau\": 17506,\n    \"Ġbutt\": 17507,\n    \"lot\": 17508,\n    \"Ġrifles\": 17509,\n    \"Ġsunglasses\": 17510,\n    \"ĠTRA\": 17511,\n    \"Ġmagnetic\": 17512,\n    \"arty\": 17513,\n    \"ĠYo\": 17514,\n    \"ĠWeight\": 17515,\n    \"?!\": 17516,\n    \"ether\": 17517,\n    \"Ġaspir\": 17518,\n    \"Ġhunters\": 17519,\n    \"Ġcontamination\": 17520,\n    \"Ben\": 17521,\n    \"political\": 17522,\n    \"],\\\"\": 17523,\n    \"ĠBever\": 17524,\n    \"Ġmonuments\": 17525,\n    \"won\": 17526,\n    \"auc\": 17527,\n    \"Ġexpressions\": 17528,\n    \"Ġlakes\": 17529,\n    \"iao\": 17530,\n    \"abin\": 17531,\n    \"Ġpleading\": 17532,\n    \"Ġdiscounted\": 17533,\n    \"Ġdisappoint\": 17534,\n    \"ĠTW\": 17535,\n    \"craft\": 17536,\n    \"Ġsocieties\": 17537,\n    \"ĠAugusta\": 17538,\n    \"Ġbott\": 17539,\n    \"Ġmarker\": 17540,\n    \"ĠWrestling\": 17541,\n    \"CBC\": 17542,\n    \"athy\": 17543,\n    \"ĠAZ\": 17544,\n    \"Ġfabulous\": 17545,\n    \"valued\": 17546,\n    \"Ġoptical\": 17547,\n    \"Ġshaken\": 17548,\n    \"OSS\": 17549,\n    \"ĠImp\": 17550,\n    \"ĠAUD\": 17551,\n    \"inals\": 17552,\n    \"Ġrevital\": 17553,\n    \"Ġcontroller\": 17554,\n    \"Ġgrasp\": 17555,\n    \"uling\": 17556,\n    \"ĠFrederick\": 17557,\n    \"ague\": 17558,\n    \"bull\": 17559,\n    \"ĠLadies\": 17560,\n    \"Ġdisruptive\": 17561,\n    \"Ġbenefiting\": 17562,\n    \"Ġverge\": 17563,\n    \"ĠDak\": 17564,\n    \"Ġgrabs\": 17565,\n    \"ĠPAC\": 17566,\n    \"GN\": 17567,\n    \"ĠMcMahon\": 17568,\n    \"rob\": 17569,\n    \"ĠEspecially\": 17570,\n    \"ĠChrome\": 17571,\n    \"ĠBundesliga\": 17572,\n    \"104\": 17573,\n    \"Ġliberty\": 17574,\n    \"ĠSF\": 17575,\n    \"Ġvarieties\": 17576,\n    \"East\": 17577,\n    \"Ġgrowers\": 17578,\n    \"Ġsocialist\": 17579,\n    \"Ġunemployed\": 17580,\n    \"AMI\": 17581,\n    \"Ġtotals\": 17582,\n    \"ĠGib\": 17583,\n    \"Ġdefect\": 17584,\n    \"ĠOrtiz\": 17585,\n    \"ĠPerfect\": 17586,\n    \"Ġpraying\": 17587,\n    \"ISS\": 17588,\n    \"Ġul\": 17589,\n    \"Ġthrust\": 17590,\n    \"osc\": 17591,\n    \"ĠOtherwise\": 17592,\n    \"Ġobsessed\": 17593,\n    \"Ġ650\": 17594,\n    \"ĠWebsite\": 17595,\n    \"Ġspectators\": 17596,\n    \"ĠScout\": 17597,\n    \"ĠBoone\": 17598,\n    \"ĠDillon\": 17599,\n    \"Ġabortions\": 17600,\n    \"lect\": 17601,\n    \"utz\": 17602,\n    \"Ġvillagers\": 17603,\n    \"Ġaccelerating\": 17604,\n    \"Ġslap\": 17605,\n    \"Ġvague\": 17606,\n    \"Ġjurisdictions\": 17607,\n    \"League\": 17608,\n    \"ĠUruguay\": 17609,\n    \"Ġobstacle\": 17610,\n    \"Ġmanufactures\": 17611,\n    \"Ġcampaigned\": 17612,\n    \"ĠAdvance\": 17613,\n    \"ĠNort\": 17614,\n    \"emer\": 17615,\n    \"Ġ1964\": 17616,\n    \"Ġirre\": 17617,\n    \"Ġprog\": 17618,\n    \"ĠFeatured\": 17619,\n    \"Ġcommute\": 17620,\n    \"Ġhandset\": 17621,\n    \"akis\": 17622,\n    \"ĠArs\": 17623,\n    \"tail\": 17624,\n    \"iker\": 17625,\n    \"Ġcrafted\": 17626,\n    \"Ġupl\": 17627,\n    \"ĠMarcos\": 17628,\n    \"Looking\": 17629,\n    \"Ġseated\": 17630,\n    \"ĠBoat\": 17631,\n    \"Ġreadiness\": 17632,\n    \"ĠLLP\": 17633,\n    \"otechnology\": 17634,\n    \"facebook\": 17635,\n    \"ĠScouts\": 17636,\n    \"ĠEar\": 17637,\n    \"ĠAdv\": 17638,\n    \"ĠDemocracy\": 17639,\n    \"NI\": 17640,\n    \"oci\": 17641,\n    \"ĠSnapdragon\": 17642,\n    \"Saturday\": 17643,\n    \"ĠPra\": 17644,\n    \"ĠCoastal\": 17645,\n    \"ĠVoters\": 17646,\n    \"ĠLeigh\": 17647,\n    \"ohn\": 17648,\n    \"orry\": 17649,\n    \"Ġtechnicians\": 17650,\n    \"armed\": 17651,\n    \"Ġshrink\": 17652,\n    \"Ġspinning\": 17653,\n    \"agram\": 17654,\n    \"320\": 17655,\n    \"liner\": 17656,\n    \"ĠContest\": 17657,\n    \"ĠCountries\": 17658,\n    \"Ġfarewell\": 17659,\n    \"ĠCW\": 17660,\n    \"aris\": 17661,\n    \"Ġstorytelling\": 17662,\n    \"Ġpasser\": 17663,\n    \"Ġsailing\": 17664,\n    \"control\": 17665,\n    \"Ġdissent\": 17666,\n    \"ĠRih\": 17667,\n    \"Ġedit\": 17668,\n    \"Ġspoilers\": 17669,\n    \"itched\": 17670,\n    \"ĠBentley\": 17671,\n    \"Ġcant\": 17672,\n    \"mn\": 17673,\n    \"ĠMacy\": 17674,\n    \"Ġindefinitely\": 17675,\n    \"Ġvill\": 17676,\n    \"Ġmeth\": 17677,\n    \"ĠEL\": 17678,\n    \"Ġoptional\": 17679,\n    \"Ġremark\": 17680,\n    \"ĠVanessa\": 17681,\n    \"Ã£\": 17682,\n    \"Ġmasks\": 17683,\n    \"ĠProvincial\": 17684,\n    \"Ġculprit\": 17685,\n    \"ĠTol\": 17686,\n    \"Ġsnack\": 17687,\n    \"ĠInfinity\": 17688,\n    \"ĠPub\": 17689,\n    \"Ġbrakes\": 17690,\n    \"Ġclar\": 17691,\n    \"Ġinception\": 17692,\n    \"love\": 17693,\n    \"Ġwonders\": 17694,\n    \"Ġforged\": 17695,\n    \"ĠCEOs\": 17696,\n    \"Ġspecifications\": 17697,\n    \"irst\": 17698,\n    \"ension\": 17699,\n    \"ĠMarin\": 17700,\n    \"det\": 17701,\n    \"Ġordeal\": 17702,\n    \"ĠFeed\": 17703,\n    \"December\": 17704,\n    \"Ġstrokes\": 17705,\n    \"fect\": 17706,\n    \"orial\": 17707,\n    \"Ġshowcasing\": 17708,\n    \"Ġstack\": 17709,\n    \"UAL\": 17710,\n    \"ĠAlexandra\": 17711,\n    \"Ġpoison\": 17712,\n    \"ĠFry\": 17713,\n    \"ĠCars\": 17714,\n    \"Ġprototype\": 17715,\n    \"ĠUSDA\": 17716,\n    \"ĠIF\": 17717,\n    \"flows\": 17718,\n    \"Ġtailored\": 17719,\n    \"ĠGear\": 17720,\n    \"Ġmyth\": 17721,\n    \"Ġplatinum\": 17722,\n    \"seven\": 17723,\n    \"founded\": 17724,\n    \"encing\": 17725,\n    \"ĠTip\": 17726,\n    \"ĠMald\": 17727,\n    \"Ġgeopolitical\": 17728,\n    \"112\": 17729,\n    \"Ġenqu\": 17730,\n    \"ĠNR\": 17731,\n    \"ĠNadu\": 17732,\n    \"leen\": 17733,\n    \"ĠTat\": 17734,\n    \"Ġcolon\": 17735,\n    \"ĠSize\": 17736,\n    \"Ġvis\": 17737,\n    \"Ġbere\": 17738,\n    \"ĠAnnie\": 17739,\n    \"ĠWatkins\": 17740,\n    \"Ġpumping\": 17741,\n    \"cur\": 17742,\n    \"ĠBates\": 17743,\n    \"Ġslug\": 17744,\n    \"miss\": 17745,\n    \"Ġforecasting\": 17746,\n    \"source\": 17747,\n    \"Ġacknowledges\": 17748,\n    \"Ġprosecute\": 17749,\n    \"Ġtestament\": 17750,\n    \"Ġcum\": 17751,\n    \"ems\": 17752,\n    \"Ġsocks\": 17753,\n    \"ĠSame\": 17754,\n    \"Ġcompetitiveness\": 17755,\n    \"Ġdefinitive\": 17756,\n    \"Ġintensified\": 17757,\n    \"Ġsatisfying\": 17758,\n    \"Ġphysics\": 17759,\n    \"ĠHarden\": 17760,\n    \"Ġsubsidy\": 17761,\n    \"Men\": 17762,\n    \"ĠPaddock\": 17763,\n    \"Ġworkouts\": 17764,\n    \"ĠSaw\": 17765,\n    \"Ġcrisp\": 17766,\n    \"ĠBezos\": 17767,\n    \"ĠVote\": 17768,\n    \"Ġguiding\": 17769,\n    \"anged\": 17770,\n    \"Ġstaple\": 17771,\n    \"ŀ\": 17772,\n    \"ules\": 17773,\n    \"ĠAvengers\": 17774,\n    \"Ġoptim\": 17775,\n    \"ĠBuffett\": 17776,\n    \"Ġtimetable\": 17777,\n    \"oust\": 17778,\n    \"HE\": 17779,\n    \"ĠGrab\": 17780,\n    \"Have\": 17781,\n    \"cca\": 17782,\n    \"Ġwaived\": 17783,\n    \"Ġretaining\": 17784,\n    \"Ġaber\": 17785,\n    \"Ġoffline\": 17786,\n    \"Ġvigil\": 17787,\n    \"books\": 17788,\n    \"ĠRein\": 17789,\n    \"Ġacknowledging\": 17790,\n    \"ĠDoyle\": 17791,\n    \"Ġproteins\": 17792,\n    \"Ġmixing\": 17793,\n    \"ĠAlcohol\": 17794,\n    \"ĠJD\": 17795,\n    \"Ġsyn\": 17796,\n    \"Ġthieves\": 17797,\n    \"Ġhomemade\": 17798,\n    \"Ġfeminist\": 17799,\n    \"ĠRoosevelt\": 17800,\n    \"ĠCoal\": 17801,\n    \"Ġwishing\": 17802,\n    \"ĠSIGN\": 17803,\n    \"ĠLad\": 17804,\n    \"Ġempathy\": 17805,\n    \"ĠBrooke\": 17806,\n    \"ĠMash\": 17807,\n    \"inations\": 17808,\n    \"''\": 17809,\n    \"ulators\": 17810,\n    \"Ġdrastically\": 17811,\n    \"Ġfloral\": 17812,\n    \"ĠGuild\": 17813,\n    \"Ġundercover\": 17814,\n    \"ĠLaboratory\": 17815,\n    \"ĠRank\": 17816,\n    \"Ġrestraining\": 17817,\n    \"Ġparagraph\": 17818,\n    \"Ġpersona\": 17819,\n    \"ĠEmployment\": 17820,\n    \"ogs\": 17821,\n    \"ĠGw\": 17822,\n    \"ĠMedal\": 17823,\n    \"Ġwildly\": 17824,\n    \"fare\": 17825,\n    \"ĠCNBC\": 17826,\n    \"photo\": 17827,\n    \"Ġtransforming\": 17828,\n    \"Ġtermination\": 17829,\n    \"still\": 17830,\n    \"INT\": 17831,\n    \"Ġbal\": 17832,\n    \"ĠEconom\": 17833,\n    \"ĠLarson\": 17834,\n    \"Ġheck\": 17835,\n    \"Ġquantitative\": 17836,\n    \"Ġemergence\": 17837,\n    \"esta\": 17838,\n    \"Ġknot\": 17839,\n    \"Ġwhale\": 17840,\n    \"ĠðŁĺ\": 17841,\n    \"Ġperimeter\": 17842,\n    \"Ġempowerment\": 17843,\n    \"Ġmg\": 17844,\n    \"Ġrents\": 17845,\n    \"Ġrefreshing\": 17846,\n    \"Ġleasing\": 17847,\n    \"Ġpatents\": 17848,\n    \"andi\": 17849,\n    \"Ġfathers\": 17850,\n    \"Ġunse\": 17851,\n    \"Ġprocessors\": 17852,\n    \"Down\": 17853,\n    \"Ġreversal\": 17854,\n    \"veh\": 17855,\n    \"andal\": 17856,\n    \"ĠKov\": 17857,\n    \"Blue\": 17858,\n    \"Ġspecializes\": 17859,\n    \"Link\": 17860,\n    \"ĠConsidering\": 17861,\n    \"ĠEdmund\": 17862,\n    \"Ġneo\": 17863,\n    \"agger\": 17864,\n    \"rg\": 17865,\n    \"Ġseverity\": 17866,\n    \"Ġcour\": 17867,\n    \"RL\": 17868,\n    \"ĠTeresa\": 17869,\n    \"Ġgallons\": 17870,\n    \"Ġacquitted\": 17871,\n    \"Ġaccompl\": 17872,\n    \"Ġcracks\": 17873,\n    \"Ġsciences\": 17874,\n    \"Club\": 17875,\n    \"Ġpredicts\": 17876,\n    \"ĠVu\": 17877,\n    \"Ġhints\": 17878,\n    \"ĠZack\": 17879,\n    \"Ġrefurb\": 17880,\n    \"Ġdestabil\": 17881,\n    \"ĠSamar\": 17882,\n    \"ĠInfo\": 17883,\n    \"fs\": 17884,\n    \"Ġratios\": 17885,\n    \"Ġinherent\": 17886,\n    \"ĠContinental\": 17887,\n    \"Ġtreasure\": 17888,\n    \"Ġcaucus\": 17889,\n    \"Ġenact\": 17890,\n    \"orporated\": 17891,\n    \"ineries\": 17892,\n    \"Ġtastes\": 17893,\n    \"main\": 17894,\n    \"Ġsq\": 17895,\n    \"ickson\": 17896,\n    \"corruption\": 17897,\n    \"ulture\": 17898,\n    \"ĠGoodman\": 17899,\n    \"ĠLing\": 17900,\n    \"ĠSup\": 17901,\n    \"Ġexposing\": 17902,\n    \"immers\": 17903,\n    \"Ġresponds\": 17904,\n    \"heimer\": 17905,\n    \"Air\": 17906,\n    \"ĠFigures\": 17907,\n    \"Ġlongstanding\": 17908,\n    \"ĠAnalytics\": 17909,\n    \"Ġenforced\": 17910,\n    \"Ġnickname\": 17911,\n    \"Ġclinch\": 17912,\n    \"ĠCarpenter\": 17913,\n    \"ĠPharma\": 17914,\n    \"Ġconstructive\": 17915,\n    \"Ġgel\": 17916,\n    \"ĠSham\": 17917,\n    \"ĠTOP\": 17918,\n    \"ĠDerrick\": 17919,\n    \"Ã¶r\": 17920,\n    \"birds\": 17921,\n    \"ĠTong\": 17922,\n    \"ĠBatman\": 17923,\n    \"ĠRouhani\": 17924,\n    \"ĠOlive\": 17925,\n    \"ĠRiv\": 17926,\n    \"Ġdessert\": 17927,\n    \"Ġguides\": 17928,\n    \"Ġsag\": 17929,\n    \"Ġchemotherapy\": 17930,\n    \"Ġslept\": 17931,\n    \"ĠFranc\": 17932,\n    \"ĠDunk\": 17933,\n    \"writers\": 17934,\n    \"ĠÃĹ\": 17935,\n    \"Ġ401\": 17936,\n    \"Ġoutfielder\": 17937,\n    \"ĠHamburg\": 17938,\n    \"izu\": 17939,\n    \"Ġscr\": 17940,\n    \"Ġcomparisons\": 17941,\n    \"Ġwhites\": 17942,\n    \"Ġtraits\": 17943,\n    \"Ġcollateral\": 17944,\n    \"LEY\": 17945,\n    \"ideshow\": 17946,\n    \"Ġstatutory\": 17947,\n    \"Ġruin\": 17948,\n    \"Ġsituated\": 17949,\n    \"tem\": 17950,\n    \"Ġinject\": 17951,\n    \"rage\": 17952,\n    \"550\": 17953,\n    \"Ġfactions\": 17954,\n    \"ĠNaomi\": 17955,\n    \"cutting\": 17956,\n    \"Ġcommunicating\": 17957,\n    \"Ġrailroad\": 17958,\n    \"Ġsparking\": 17959,\n    \"Ġrespiratory\": 17960,\n    \"ĠWebster\": 17961,\n    \"ĠCarbon\": 17962,\n    \"Ġundertaking\": 17963,\n    \"Ġcomposer\": 17964,\n    \"ĠFigure\": 17965,\n    \"Ġspecified\": 17966,\n    \"Video\": 17967,\n    \"uber\": 17968,\n    \"Ġsexuality\": 17969,\n    \"lected\": 17970,\n    \"ĠBurger\": 17971,\n    \"ĠCards\": 17972,\n    \"SR\": 17973,\n    \"ĠLie\": 17974,\n    \"Ġrecount\": 17975,\n    \"Ġexceeding\": 17976,\n    \"Ġquoting\": 17977,\n    \"ĠJama\": 17978,\n    \"ĠVictorian\": 17979,\n    \"Ġsway\": 17980,\n    \"ĠGes\": 17981,\n    \"ĠSI\": 17982,\n    \"ĠKazakhstan\": 17983,\n    \"Ġaccusation\": 17984,\n    \"etr\": 17985,\n    \"Ah\": 17986,\n    \"Ġproc\": 17987,\n    \"Ġlamb\": 17988,\n    \"ĠMorales\": 17989,\n    \"ĠLily\": 17990,\n    \"Ġderail\": 17991,\n    \"Ġcontributes\": 17992,\n    \"iddle\": 17993,\n    \"ĠConcord\": 17994,\n    \"Ġelectr\": 17995,\n    \"Ġequip\": 17996,\n    \"Ġquantum\": 17997,\n    \"Ġthereafter\": 17998,\n    \"Ġarrange\": 17999,\n    \"Ġraided\": 18000,\n    \"ĠMove\": 18001,\n    \"ĠSang\": 18002,\n    \"ĠGaming\": 18003,\n    \"Ġbiology\": 18004,\n    \"ĠAmnesty\": 18005,\n    \"Ġdemise\": 18006,\n    \"ĠBarton\": 18007,\n    \"Ġqualifier\": 18008,\n    \"ANI\": 18009,\n    \"Ġundersc\": 18010,\n    \"Ġroyalty\": 18011,\n    \"ĠINC\": 18012,\n    \"Ġsne\": 18013,\n    \"ariat\": 18014,\n    \"ĠWan\": 18015,\n    \"Ġcluster\": 18016,\n    \"quin\": 18017,\n    \"Ġwhales\": 18018,\n    \"ĠFear\": 18019,\n    \"ĠBrew\": 18020,\n    \"Ġdeport\": 18021,\n    \"airs\": 18022,\n    \"Ġcensus\": 18023,\n    \"OUS\": 18024,\n    \"Ġrespectful\": 18025,\n    \"bone\": 18026,\n    \"Ġwaivers\": 18027,\n    \"friend\": 18028,\n    \"Ġsystemic\": 18029,\n    \"ĠDion\": 18030,\n    \"James\": 18031,\n    \"ĠAdmission\": 18032,\n    \"Ġstigma\": 18033,\n    \"ĠTIME\": 18034,\n    \"Ġunderpin\": 18035,\n    \"ĠWitnesses\": 18036,\n    \"Ġdigs\": 18037,\n    \"Ġgenocide\": 18038,\n    \"Ġstaging\": 18039,\n    \"rolled\": 18040,\n    \"Ġspecially\": 18041,\n    \"oop\": 18042,\n    \"Ġbaseline\": 18043,\n    \"ĠRF\": 18044,\n    \"avis\": 18045,\n    \"Ġvocals\": 18046,\n    \"COL\": 18047,\n    \"LD\": 18048,\n    \"Ġimpending\": 18049,\n    \"ĠCaldwell\": 18050,\n    \"Ġaluminium\": 18051,\n    \"Ġstra\": 18052,\n    \"ĠTayyip\": 18053,\n    \"Ġadmissions\": 18054,\n    \"falls\": 18055,\n    \"Ġrealizing\": 18056,\n    \"oen\": 18057,\n    \"ĠRV\": 18058,\n    \"ĠMog\": 18059,\n    \"Ġadvocating\": 18060,\n    \"ĠPepper\": 18061,\n    \"lived\": 18062,\n    \"ĠWick\": 18063,\n    \"Facebook\": 18064,\n    \"ĠSpect\": 18065,\n    \"Ġshout\": 18066,\n    \"Ġfractured\": 18067,\n    \"vet\": 18068,\n    \"Ġ1966\": 18069,\n    \"Ġcompensate\": 18070,\n    \"ĠVolume\": 18071,\n    \"Ġcategor\": 18072,\n    \"ĠHuntington\": 18073,\n    \"Free\": 18074,\n    \"OUGH\": 18075,\n    \"local\": 18076,\n    \"Sch\": 18077,\n    \"uti\": 18078,\n    \"Ġburger\": 18079,\n    \"Ġbush\": 18080,\n    \"Ġimpacting\": 18081,\n    \"Ġfrost\": 18082,\n    \"tti\": 18083,\n    \"ĠFresno\": 18084,\n    \"onz\": 18085,\n    \"shaw\": 18086,\n    \"ĠLibyan\": 18087,\n    \"Ġassert\": 18088,\n    \"ĠLegacy\": 18089,\n    \"ĠIE\": 18090,\n    \"ĠKinder\": 18091,\n    \"ĠHorizon\": 18092,\n    \"Ġtum\": 18093,\n    \"Ġsignaled\": 18094,\n    \"ĠFors\": 18095,\n    \"Ġspeedy\": 18096,\n    \"rang\": 18097,\n    \"ĠFT\": 18098,\n    \"Ġselecting\": 18099,\n    \"Ġpale\": 18100,\n    \"WD\": 18101,\n    \"Ġprobability\": 18102,\n    \"OUND\": 18103,\n    \"istrate\": 18104,\n    \"Ġsens\": 18105,\n    \"ocating\": 18106,\n    \"Ġinterpret\": 18107,\n    \"Ġpuzzle\": 18108,\n    \"Ġinland\": 18109,\n    \"Ġmanipulation\": 18110,\n    \"Sal\": 18111,\n    \"Ġfulfilling\": 18112,\n    \"ĠMcMaster\": 18113,\n    \"Make\": 18114,\n    \"jun\": 18115,\n    \"giving\": 18116,\n    \"ĠNiagara\": 18117,\n    \"Ġscholars\": 18118,\n    \"ALT\": 18119,\n    \"ĠSteam\": 18120,\n    \"omin\": 18121,\n    \"ĠSau\": 18122,\n    \"ĠDowning\": 18123,\n    \"Ġgy\": 18124,\n    \"ĠTit\": 18125,\n    \"ĠLav\": 18126,\n    \"ĠPepsi\": 18127,\n    \"Ġdumping\": 18128,\n    \"ĠDetect\": 18129,\n    \"ĠTDs\": 18130,\n    \"ĠKob\": 18131,\n    \"ĠSY\": 18132,\n    \"Ġpioneer\": 18133,\n    \"Ġ_\": 18134,\n    \"Ġclarified\": 18135,\n    \"ĠTests\": 18136,\n    \"opic\": 18137,\n    \"ĠMN\": 18138,\n    \"ĠBowman\": 18139,\n    \"umin\": 18140,\n    \"Ġwidow\": 18141,\n    \"Ġrallying\": 18142,\n    \"ĠPull\": 18143,\n    \"Ġprojection\": 18144,\n    \"Ġescalation\": 18145,\n    \"Ġlibraries\": 18146,\n    \"ĠFounder\": 18147,\n    \"ĠHugo\": 18148,\n    \"ĠStyle\": 18149,\n    \"Ġfreelance\": 18150,\n    \"Ġlisteners\": 18151,\n    \"Ġdiscovering\": 18152,\n    \"ĠPlans\": 18153,\n    \"Ġfranchises\": 18154,\n    \"ĠPam\": 18155,\n    \"Ġfarther\": 18156,\n    \"UI\": 18157,\n    \"opers\": 18158,\n    \"103\": 18159,\n    \"ublished\": 18160,\n    \"keys\": 18161,\n    \"aky\": 18162,\n    \"Ġinnov\": 18163,\n    \"¦\": 18164,\n    \"ĠDrum\": 18165,\n    \"Ġwraps\": 18166,\n    \"ĠCongressman\": 18167,\n    \"ĠVenus\": 18168,\n    \"fake\": 18169,\n    \"ĠBronx\": 18170,\n    \"ĠDinner\": 18171,\n    \"faced\": 18172,\n    \"Ġbackward\": 18173,\n    \"inge\": 18174,\n    \"Ġarsenal\": 18175,\n    \"ĠAce\": 18176,\n    \"uden\": 18177,\n    \"fre\": 18178,\n    \"Ġspa\": 18179,\n    \"ĠSaunders\": 18180,\n    \"ĠMatter\": 18181,\n    \"ĠSpons\": 18182,\n    \"Ġconsultations\": 18183,\n    \"ĠRuss\": 18184,\n    \"Ġsculpture\": 18185,\n    \"Ġuncommon\": 18186,\n    \"Nov\": 18187,\n    \"pg\": 18188,\n    \"otherapy\": 18189,\n    \"Ġgol\": 18190,\n    \"ĠBlazers\": 18191,\n    \"Ġadvises\": 18192,\n    \"ĠRegulatory\": 18193,\n    \"ĠBoyle\": 18194,\n    \"Äģ\": 18195,\n    \"Ġcuisine\": 18196,\n    \"Ġencouragement\": 18197,\n    \"yp\": 18198,\n    \"eny\": 18199,\n    \"ĠOrchestra\": 18200,\n    \"ĠChicken\": 18201,\n    \"Ġ1965\": 18202,\n    \"ĠPret\": 18203,\n    \"ĠCooperation\": 18204,\n    \"ĠDevices\": 18205,\n    \"ĠRodney\": 18206,\n    \"ĠHonduras\": 18207,\n    \"ĠEgg\": 18208,\n    \"Ġchurn\": 18209,\n    \"Ġclutch\": 18210,\n    \"ĠBernstein\": 18211,\n    \"Ġain\": 18212,\n    \"Ġformidable\": 18213,\n    \"ĠFacility\": 18214,\n    \"Ġpag\": 18215,\n    \"mons\": 18216,\n    \"bol\": 18217,\n    \"Ġliteracy\": 18218,\n    \"Ġsubmissions\": 18219,\n    \"ĠHulu\": 18220,\n    \"ĠConstitutional\": 18221,\n    \"ĠIsh\": 18222,\n    \"ĠPaula\": 18223,\n    \"olve\": 18224,\n    \"Ġabundance\": 18225,\n    \"ĠAla\": 18226,\n    \"ĠEcuador\": 18227,\n    \"Ġreconstruction\": 18228,\n    \"Ġcrush\": 18229,\n    \"reek\": 18230,\n    \"ĠÂŃ\": 18231,\n    \"ibo\": 18232,\n    \"Ġpracticed\": 18233,\n    \"Ġpac\": 18234,\n    \"rett\": 18235,\n    \"Ġpasta\": 18236,\n    \"Ġresp\": 18237,\n    \"ĠFlag\": 18238,\n    \"pal\": 18239,\n    \"Ġcommenting\": 18240,\n    \"Ġrecap\": 18241,\n    \"âĢĶâĢĶ\": 18242,\n    \"ĠToy\": 18243,\n    \"ĠMeredith\": 18244,\n    \"Ġreceipt\": 18245,\n    \"Ġseparating\": 18246,\n    \"ĠMap\": 18247,\n    \"Ġmogul\": 18248,\n    \"ĠBurlington\": 18249,\n    \"Ġger\": 18250,\n    \"Ġcoordinate\": 18251,\n    \"grad\": 18252,\n    \"Ġescalated\": 18253,\n    \"Ġproceeded\": 18254,\n    \"turned\": 18255,\n    \"Ġupt\": 18256,\n    \"hum\": 18257,\n    \"ĠWere\": 18258,\n    \"Whether\": 18259,\n    \"Ġenjoyable\": 18260,\n    \"energy\": 18261,\n    \"Ġprohibit\": 18262,\n    \"Ġhurdle\": 18263,\n    \"Ġdivorced\": 18264,\n    \"Ġcommentator\": 18265,\n    \"GT\": 18266,\n    \"ATH\": 18267,\n    \"Ġtravellers\": 18268,\n    \"Ġpopulated\": 18269,\n    \"ĠVo\": 18270,\n    \"ĠRebels\": 18271,\n    \"Ġspurred\": 18272,\n    \"Ġideological\": 18273,\n    \"Ġelephant\": 18274,\n    \"keyes\": 18275,\n    \"Pat\": 18276,\n    \"Ġlinger\": 18277,\n    \"Ġreps\": 18278,\n    \"Ġcocktails\": 18279,\n    \"ĠKristen\": 18280,\n    \"istically\": 18281,\n    \"Ġgunmen\": 18282,\n    \"Ġ1920\": 18283,\n    \"Ġquart\": 18284,\n    \"National\": 18285,\n    \"Ġexceptions\": 18286,\n    \"kat\": 18287,\n    \"priced\": 18288,\n    \"ĠHarold\": 18289,\n    \"ĠPistons\": 18290,\n    \"Ġcompounds\": 18291,\n    \"Ġmouse\": 18292,\n    \"Ġexhibits\": 18293,\n    \"ĠBurk\": 18294,\n    \"Ġclassmates\": 18295,\n    \"Ġcirculated\": 18296,\n    \"Ġattributable\": 18297,\n    \"ĠBaton\": 18298,\n    \"Ġorganizer\": 18299,\n    \"Ġdurable\": 18300,\n    \"Ġsingers\": 18301,\n    \"ĠOman\": 18302,\n    \"Ġhydrogen\": 18303,\n    \"Ġslash\": 18304,\n    \"Ġaccidental\": 18305,\n    \"ĠAbrams\": 18306,\n    \"KS\": 18307,\n    \"itty\": 18308,\n    \"Ġrust\": 18309,\n    \"Ġselections\": 18310,\n    \"porting\": 18311,\n    \"ĠEmanuel\": 18312,\n    \"XX\": 18313,\n    \"ĠThornton\": 18314,\n    \"Ġcolumns\": 18315,\n    \"Ġsentiments\": 18316,\n    \"fun\": 18317,\n    \"Ġplight\": 18318,\n    \"ĠSister\": 18319,\n    \"ĠMaggie\": 18320,\n    \"hya\": 18321,\n    \"Daniel\": 18322,\n    \"Ġplung\": 18323,\n    \"orio\": 18324,\n    \"ĠYorker\": 18325,\n    \"ĠSaturdays\": 18326,\n    \"Ġloc\": 18327,\n    \"aye\": 18328,\n    \"illon\": 18329,\n    \"ĠConsulting\": 18330,\n    \"pled\": 18331,\n    \"ĠZin\": 18332,\n    \"ĠFarms\": 18333,\n    \"ĠGiuliani\": 18334,\n    \"ĠMIN\": 18335,\n    \"ĠHanson\": 18336,\n    \"ĠComplete\": 18337,\n    \"ourke\": 18338,\n    \"oche\": 18339,\n    \"ĠJord\": 18340,\n    \"Ġprofessors\": 18341,\n    \"ĠWILL\": 18342,\n    \"ĠCron\": 18343,\n    \"Ġdorm\": 18344,\n    \"Ġcracking\": 18345,\n    \"tur\": 18346,\n    \"ORS\": 18347,\n    \"Ant\": 18348,\n    \"Ġdeduction\": 18349,\n    \"ĠSIM\": 18350,\n    \"igue\": 18351,\n    \"ĠValent\": 18352,\n    \"ĠEthereum\": 18353,\n    \"ĠSunny\": 18354,\n    \"ĠExtra\": 18355,\n    \"ivan\": 18356,\n    \"ĠFo\": 18357,\n    \"Ġleases\": 18358,\n    \"ibe\": 18359,\n    \"Ġ1800\": 18360,\n    \"Ġslapped\": 18361,\n    \"emaker\": 18362,\n    \"Ġfa\": 18363,\n    \"rien\": 18364,\n    \"ĠPeriod\": 18365,\n    \"ĠES\": 18366,\n    \"ĠBlu\": 18367,\n    \"Ġpreserving\": 18368,\n    \"Ġsmarter\": 18369,\n    \"mans\": 18370,\n    \"Ġgest\": 18371,\n    \"zu\": 18372,\n    \"nu\": 18373,\n    \"Ġdivest\": 18374,\n    \"roc\": 18375,\n    \"ĠFlood\": 18376,\n    \"Given\": 18377,\n    \"ĠNorton\": 18378,\n    \"Ġgranting\": 18379,\n    \"Ġdealings\": 18380,\n    \"Ġgeographic\": 18381,\n    \"esa\": 18382,\n    \"Ġcub\": 18383,\n    \"Ġcriticizing\": 18384,\n    \"ĠCub\": 18385,\n    \"Ġsurroundings\": 18386,\n    \"ĠInternal\": 18387,\n    \"Ġsle\": 18388,\n    \"Ġcrushing\": 18389,\n    \"ĠPP\": 18390,\n    \"izations\": 18391,\n    \"ĠAbdel\": 18392,\n    \"Joe\": 18393,\n    \"ĠVisitors\": 18394,\n    \"ĠCarly\": 18395,\n    \"INGTON\": 18396,\n    \"ĠGC\": 18397,\n    \"ĠWB\": 18398,\n    \"Ġgently\": 18399,\n    \"·\": 18400,\n    \"though\": 18401,\n    \"ĠAlto\": 18402,\n    \"Ġresting\": 18403,\n    \"ĠPerson\": 18404,\n    \"ĠTon\": 18405,\n    \"Ġbore\": 18406,\n    \"ĠClar\": 18407,\n    \"Ġmot\": 18408,\n    \"Ġbathrooms\": 18409,\n    \"ĠTypically\": 18410,\n    \"Ġdisconnect\": 18411,\n    \"Ġtightly\": 18412,\n    \"ĠHarvest\": 18413,\n    \"ĠHed\": 18414,\n    \"ĠGermans\": 18415,\n    \"atar\": 18416,\n    \"Ġkeynote\": 18417,\n    \"Ġimproper\": 18418,\n    \"fil\": 18419,\n    \"Ġintens\": 18420,\n    \"iev\": 18421,\n    \"Ġmedi\": 18422,\n    \"Ġtenant\": 18423,\n    \"Ġfootsteps\": 18424,\n    \"uli\": 18425,\n    \"Ġlegalization\": 18426,\n    \"106\": 18427,\n    \"ĠLexington\": 18428,\n    \"folio\": 18429,\n    \"ĠÂ½\": 18430,\n    \"ĠRita\": 18431,\n    \"Ġbattered\": 18432,\n    \"inka\": 18433,\n    \"ĠJavaScript\": 18434,\n    \"ĠMusical\": 18435,\n    \"ĠTalent\": 18436,\n    \"Ġlounge\": 18437,\n    \"Ġintimidation\": 18438,\n    \"ikh\": 18439,\n    \"ĠFam\": 18440,\n    \"Ġtherapeutic\": 18441,\n    \"Ġbalancing\": 18442,\n    \"Ġrocky\": 18443,\n    \"liners\": 18444,\n    \"ĠPredators\": 18445,\n    \"Ġregistering\": 18446,\n    \"Ġdiligence\": 18447,\n    \"ĠRover\": 18448,\n    \"ĠDot\": 18449,\n    \"Ġterminated\": 18450,\n    \"ĠEdu\": 18451,\n    \"Ġcharming\": 18452,\n    \"ĠPLAY\": 18453,\n    \"ĠFact\": 18454,\n    \"ĠCi\": 18455,\n    \").\\\"\": 18456,\n    \"ĠWrestle\": 18457,\n    \"hun\": 18458,\n    \"Ġopenings\": 18459,\n    \"Ġfou\": 18460,\n    \"Ġ126\": 18461,\n    \"spe\": 18462,\n    \"ĠAW\": 18463,\n    \"Ġbud\": 18464,\n    \"ĠTemper\": 18465,\n    \"ĠOrthodox\": 18466,\n    \"Ġprogressed\": 18467,\n    \"tre\": 18468,\n    \"Ġtasting\": 18469,\n    \"Ġscrutin\": 18470,\n    \"ĠLima\": 18471,\n    \"Ġlayout\": 18472,\n    \"Ġlitter\": 18473,\n    \"ijk\": 18474,\n    \"ĠParkinson\": 18475,\n    \"ĠAnfield\": 18476,\n    \"Ġdevelopmental\": 18477,\n    \"Ġheaven\": 18478,\n    \"ĠWoodward\": 18479,\n    \"index\": 18480,\n    \"Ġpistol\": 18481,\n    \"Ġreson\": 18482,\n    \"ĠWS\": 18483,\n    \"Ġemb\": 18484,\n    \"ĠLap\": 18485,\n    \"ĠPle\": 18486,\n    \"lington\": 18487,\n    \"ĠSit\": 18488,\n    \"Ġabruptly\": 18489,\n    \"ĠSenegal\": 18490,\n    \"ĠYates\": 18491,\n    \"aceutical\": 18492,\n    \"ĠJak\": 18493,\n    \"ĠHastings\": 18494,\n    \"iste\": 18495,\n    \"ĠDB\": 18496,\n    \"ĠAgent\": 18497,\n    \"Ġpreservation\": 18498,\n    \"ĠLank\": 18499,\n    \"ĠSuffolk\": 18500,\n    \"Ġboo\": 18501,\n    \"essed\": 18502,\n    \"Ġempowering\": 18503,\n    \"enne\": 18504,\n    \"Ġrecycled\": 18505,\n    \"Ġstrateg\": 18506,\n    \"Ġbrake\": 18507,\n    \"135\": 18508,\n    \"ĠStef\": 18509,\n    \"ĠFlake\": 18510,\n    \"ĠGregg\": 18511,\n    \"ĠRent\": 18512,\n    \"Ġinstallment\": 18513,\n    \"FW\": 18514,\n    \"ĠCran\": 18515,\n    \"obo\": 18516,\n    \"ml\": 18517,\n    \"ĠJade\": 18518,\n    \"Ġaccuses\": 18519,\n    \"ĠNvidia\": 18520,\n    \"Ġburg\": 18521,\n    \"High\": 18522,\n    \"Ġbothered\": 18523,\n    \"ĠBenn\": 18524,\n    \"Ġinterrupted\": 18525,\n    \"Ġtrek\": 18526,\n    \"Ġserv\": 18527,\n    \"Ġpatron\": 18528,\n    \"Ġdictator\": 18529,\n    \"owa\": 18530,\n    \"jad\": 18531,\n    \"ĠTulsa\": 18532,\n    \"Ġboil\": 18533,\n    \"Ġdisplaying\": 18534,\n    \"Ġcinem\": 18535,\n    \"awaited\": 18536,\n    \"¸\": 18537,\n    \"Ġreacts\": 18538,\n    \"ĠDee\": 18539,\n    \"ĠGron\": 18540,\n    \"igation\": 18541,\n    \"Ġservic\": 18542,\n    \"capt\": 18543,\n    \"Ġinsane\": 18544,\n    \"ĠVeteran\": 18545,\n    \"umen\": 18546,\n    \"End\": 18547,\n    \"ĠCream\": 18548,\n    \"Ġextremism\": 18549,\n    \"ĠMalone\": 18550,\n    \"Col\": 18551,\n    \"Ġsafeguard\": 18552,\n    \"Ġtomatoes\": 18553,\n    \"die\": 18554,\n    \"Ġchamp\": 18555,\n    \"zero\": 18556,\n    \"ĠPRES\": 18557,\n    \"Ġchoir\": 18558,\n    \"Ġpediatric\": 18559,\n    \"Ġprivileged\": 18560,\n    \"Ġdownstream\": 18561,\n    \"Business\": 18562,\n    \"ĠFighting\": 18563,\n    \"atable\": 18564,\n    \"Ġsums\": 18565,\n    \"Ġinsult\": 18566,\n    \"arten\": 18567,\n    \"ĠWikiLeaks\": 18568,\n    \"Ġpads\": 18569,\n    \"Ġretali\": 18570,\n    \"ĠHunts\": 18571,\n    \"Ġindie\": 18572,\n    \"ĠShields\": 18573,\n    \"ĠMortgage\": 18574,\n    \"oses\": 18575,\n    \"ampton\": 18576,\n    \"ĠVideos\": 18577,\n    \"ĠPER\": 18578,\n    \"itionally\": 18579,\n    \"ĠKimmel\": 18580,\n    \"sum\": 18581,\n    \"trade\": 18582,\n    \"acity\": 18583,\n    \"marked\": 18584,\n    \"ĠAngus\": 18585,\n    \"Ġtemper\": 18586,\n    \"Ġseizure\": 18587,\n    \"Ġfictional\": 18588,\n    \"utton\": 18589,\n    \"eva\": 18590,\n    \"Rs\": 18591,\n    \"Ġintra\": 18592,\n    \"ĠRequest\": 18593,\n    \"ppe\": 18594,\n    \"ĠeBay\": 18595,\n    \"ĠUSS\": 18596,\n    \"Ġ1500\": 18597,\n    \"Ġpossessing\": 18598,\n    \"Ġbacon\": 18599,\n    \"ĠSexual\": 18600,\n    \"ĠBuff\": 18601,\n    \"Ġslaughter\": 18602,\n    \"Ġjur\": 18603,\n    \"zhou\": 18604,\n    \"suit\": 18605,\n    \"ĠCha\": 18606,\n    \"ĠBuk\": 18607,\n    \"crime\": 18608,\n    \"ĠEasy\": 18609,\n    \"ĠChain\": 18610,\n    \"aq\": 18611,\n    \"ĠPall\": 18612,\n    \"flation\": 18613,\n    \"225\": 18614,\n    \"oup\": 18615,\n    \"109\": 18616,\n    \"ĠMcKenzie\": 18617,\n    \"Ġclearer\": 18618,\n    \"ĠDogs\": 18619,\n    \"oration\": 18620,\n    \"Ġsubs\": 18621,\n    \"Follow\": 18622,\n    \"ĠShirley\": 18623,\n    \"Ġadjusting\": 18624,\n    \"ĠEFF\": 18625,\n    \"Ġflipped\": 18626,\n    \"Ġconform\": 18627,\n    \"ĠLaurent\": 18628,\n    \"Ġcircular\": 18629,\n    \"ĠNOR\": 18630,\n    \"Ġmort\": 18631,\n    \"Ġtexture\": 18632,\n    \"avour\": 18633,\n    \"Ġflex\": 18634,\n    \"ĠHedge\": 18635,\n    \"ðŁĺ\": 18636,\n    \"Ġtrophies\": 18637,\n    \"ĠINV\": 18638,\n    \"Ġboast\": 18639,\n    \"ĠTyr\": 18640,\n    \"ĠNichols\": 18641,\n    \"ĠSpa\": 18642,\n    \"Ġcheered\": 18643,\n    \"Ġprey\": 18644,\n    \"reach\": 18645,\n    \"Ġbreached\": 18646,\n    \"ĠRegions\": 18647,\n    \"ĠLyft\": 18648,\n    \"ĠTul\": 18649,\n    \"ĠKore\": 18650,\n    \"Ġendure\": 18651,\n    \"ĠCover\": 18652,\n    \"\\\").\": 18653,\n    \"ĠSavage\": 18654,\n    \"Ã¨re\": 18655,\n    \"reens\": 18656,\n    \"Ġnic\": 18657,\n    \"sector\": 18658,\n    \"Ġweaknesses\": 18659,\n    \"Ġreboot\": 18660,\n    \"Ġ210\": 18661,\n    \"Ġimagery\": 18662,\n    \"ĠFrem\": 18663,\n    \"Ġclue\": 18664,\n    \"ĠLars\": 18665,\n    \"Ġfaction\": 18666,\n    \"hetic\": 18667,\n    \"Ġallied\": 18668,\n    \"ĠMarvin\": 18669,\n    \"Ġmethodology\": 18670,\n    \"ĠTN\": 18671,\n    \"Ġutter\": 18672,\n    \"Ġ270\": 18673,\n    \"ĠVolvo\": 18674,\n    \"oline\": 18675,\n    \"ĠACLU\": 18676,\n    \"Ġindirect\": 18677,\n    \"Ġminer\": 18678,\n    \"ĠBale\": 18679,\n    \"ĠStrange\": 18680,\n    \"ĠFuller\": 18681,\n    \"Ġexpelled\": 18682,\n    \"ĠTropical\": 18683,\n    \"Ġremotely\": 18684,\n    \"ĠTIM\": 18685,\n    \"Ġinnocence\": 18686,\n    \"Ġconfined\": 18687,\n    \"Ġfares\": 18688,\n    \"Ġprevalent\": 18689,\n    \"Ġdesp\": 18690,\n    \"House\": 18691,\n    \"azar\": 18692,\n    \"Ġgestures\": 18693,\n    \"ĠCES\": 18694,\n    \"ĠDM\": 18695,\n    \"eal\": 18696,\n    \"ĠÐ\": 18697,\n    \"Ġburnt\": 18698,\n    \"Ġframed\": 18699,\n    \"ĠDani\": 18700,\n    \"Ġhol\": 18701,\n    \"ĠCannes\": 18702,\n    \"ĠHayden\": 18703,\n    \"Ġwardrobe\": 18704,\n    \"ĠAssange\": 18705,\n    \"ĠSamp\": 18706,\n    \"bay\": 18707,\n    \"sky\": 18708,\n    \"ĠHence\": 18709,\n    \"ĠGrizzlies\": 18710,\n    \"rates\": 18711,\n    \"laws\": 18712,\n    \"ĠMandela\": 18713,\n    \"ĠHoover\": 18714,\n    \"rics\": 18715,\n    \"charged\": 18716,\n    \"Ġexclude\": 18717,\n    \"Ġpassive\": 18718,\n    \"Ġcontinuation\": 18719,\n    \"Ġblunt\": 18720,\n    \"Ġvac\": 18721,\n    \"ĠEmerging\": 18722,\n    \"rench\": 18723,\n    \"tv\": 18724,\n    \"ĠHollow\": 18725,\n    \"ĠOC\": 18726,\n    \"Ġadvisors\": 18727,\n    \"Ġrendered\": 18728,\n    \"ĠBernardino\": 18729,\n    \"ĠSupporters\": 18730,\n    \"ronic\": 18731,\n    \"Ġchancellor\": 18732,\n    \"Ġ1963\": 18733,\n    \"Ġuranium\": 18734,\n    \"Ġak\": 18735,\n    \"ĠOptions\": 18736,\n    \"ermott\": 18737,\n    \"ĠBerger\": 18738,\n    \"ibia\": 18739,\n    \"Ġexplosions\": 18740,\n    \"Ġimpairment\": 18741,\n    \"Ġhail\": 18742,\n    \"Ġalley\": 18743,\n    \"Ġcruelty\": 18744,\n    \"ĠClarence\": 18745,\n    \"Ġvariations\": 18746,\n    \"Ġrealm\": 18747,\n    \"Ġrenovations\": 18748,\n    \"ĠNorwich\": 18749,\n    \"Ġbelongings\": 18750,\n    \"Ġmerchants\": 18751,\n    \"ĠMinisters\": 18752,\n    \"ĠDodd\": 18753,\n    \"Ġviewer\": 18754,\n    \"Ġneutrality\": 18755,\n    \"quer\": 18756,\n    \"ĠPrinceton\": 18757,\n    \"dead\": 18758,\n    \"arest\": 18759,\n    \"GET\": 18760,\n    \"ĠCanadiens\": 18761,\n    \"ĠIgn\": 18762,\n    \"clear\": 18763,\n    \"Mal\": 18764,\n    \"ĠBridges\": 18765,\n    \"ĠHayward\": 18766,\n    \"Ġremarked\": 18767,\n    \"ingle\": 18768,\n    \"Ġsob\": 18769,\n    \"Ġdepart\": 18770,\n    \"beans\": 18771,\n    \"Ġpreserved\": 18772,\n    \"ĠFairfax\": 18773,\n    \"Ġforgot\": 18774,\n    \"ĠBeh\": 18775,\n    \"Rob\": 18776,\n    \"Ġcooperative\": 18777,\n    \"ullah\": 18778,\n    \"Ġmates\": 18779,\n    \"Ġrang\": 18780,\n    \"Ġthigh\": 18781,\n    \"Ġabducted\": 18782,\n    \"Ġchaired\": 18783,\n    \"ĠHearts\": 18784,\n    \"Ġidentifies\": 18785,\n    \"ĠBuckingham\": 18786,\n    \"ijn\": 18787,\n    \"ĠJab\": 18788,\n    \"Ġclashed\": 18789,\n    \"feed\": 18790,\n    \"sites\": 18791,\n    \"ĠCareer\": 18792,\n    \"exp\": 18793,\n    \"ĠBuccaneers\": 18794,\n    \"scape\": 18795,\n    \"Ġupdating\": 18796,\n    \"Ġintentional\": 18797,\n    \"ĠGuam\": 18798,\n    \"ĠBreakfast\": 18799,\n    \"ĠHag\": 18800,\n    \"Media\": 18801,\n    \"Ġtapping\": 18802,\n    \"Ġpics\": 18803,\n    \"Ġeaten\": 18804,\n    \"Ġpremise\": 18805,\n    \"Kim\": 18806,\n    \"ĠStorage\": 18807,\n    \"Ġextensively\": 18808,\n    \"Ġoutrageous\": 18809,\n    \"ĠSadly\": 18810,\n    \"Global\": 18811,\n    \"Â¢\": 18812,\n    \"leaning\": 18813,\n    \"CM\": 18814,\n    \"Ġeasiest\": 18815,\n    \"ument\": 18816,\n    \"Ġ122\": 18817,\n    \"Ġdaunting\": 18818,\n    \"ISE\": 18819,\n    \"Ġsunset\": 18820,\n    \"Ġreset\": 18821,\n    \"Ġbent\": 18822,\n    \"Trust\": 18823,\n    \"ĠCaleb\": 18824,\n    \"ĠRut\": 18825,\n    \"ĠBast\": 18826,\n    \"ETS\": 18827,\n    \"iencies\": 18828,\n    \"Ġpu\": 18829,\n    \"ature\": 18830,\n    \"Ġrealities\": 18831,\n    \"omi\": 18832,\n    \"Ġsoda\": 18833,\n    \"Ġunveil\": 18834,\n    \"ĠGoldberg\": 18835,\n    \"opes\": 18836,\n    \"Ġuprising\": 18837,\n    \"ĠMR\": 18838,\n    \"Ġendorse\": 18839,\n    \"Ġsail\": 18840,\n    \"Ġconverting\": 18841,\n    \"Ġglamorous\": 18842,\n    \"ĠHollande\": 18843,\n    \"108\": 18844,\n    \"isky\": 18845,\n    \"Ġcushion\": 18846,\n    \"240\": 18847,\n    \"Ġadventures\": 18848,\n    \"Ġantitrust\": 18849,\n    \"ĠStockholm\": 18850,\n    \"pace\": 18851,\n    \"ĠVald\": 18852,\n    \"ĠTransfer\": 18853,\n    \"ERT\": 18854,\n    \"ĠMcInt\": 18855,\n    \"Ġsurging\": 18856,\n    \"ogn\": 18857,\n    \"Ġlauded\": 18858,\n    \"ĠZam\": 18859,\n    \"ĠRough\": 18860,\n    \"TOR\": 18861,\n    \"Ġwed\": 18862,\n    \"Ġorigins\": 18863,\n    \"ĠEld\": 18864,\n    \"oso\": 18865,\n    \"Ġsupplying\": 18866,\n    \"ĠPetty\": 18867,\n    \"ĠTwe\": 18868,\n    \"ĠDenise\": 18869,\n    \"ĠBec\": 18870,\n    \"Ġbehave\": 18871,\n    \"Ġ121\": 18872,\n    \"estone\": 18873,\n    \"ĠBoulder\": 18874,\n    \"ĠBlackhawks\": 18875,\n    \"ĠWyatt\": 18876,\n    \"Ġfiguring\": 18877,\n    \"ĠDeborah\": 18878,\n    \"agi\": 18879,\n    \"significant\": 18880,\n    \"Ġasthma\": 18881,\n    \"Ġmessy\": 18882,\n    \"mpire\": 18883,\n    \"Ġax\": 18884,\n    \"Ġaspiring\": 18885,\n    \"ĠNH\": 18886,\n    \"ĠGina\": 18887,\n    \"heavy\": 18888,\n    \"ĠVick\": 18889,\n    \"ÃŃs\": 18890,\n    \"something\": 18891,\n    \"Ġbodily\": 18892,\n    \"Ġunauthorized\": 18893,\n    \"ĠActually\": 18894,\n    \"ĠOH\": 18895,\n    \"Ġmicrophone\": 18896,\n    \"allah\": 18897,\n    \"Ġrampant\": 18898,\n    \"Ġrelocated\": 18899,\n    \"Ġwidening\": 18900,\n    \"ĠCait\": 18901,\n    \"nel\": 18902,\n    \"ĠBlackBerry\": 18903,\n    \"Ġprofessionally\": 18904,\n    \"ĠInterestingly\": 18905,\n    \"Ġbarbecue\": 18906,\n    \"Ġresisting\": 18907,\n    \"ĠNunes\": 18908,\n    \"disc\": 18909,\n    \"Ġgroundbreaking\": 18910,\n    \"orable\": 18911,\n    \"ĠRegulation\": 18912,\n    \"Ġborrowed\": 18913,\n    \"Ġleaking\": 18914,\n    \"Ġlengths\": 18915,\n    \"Ġunveiling\": 18916,\n    \"houses\": 18917,\n    \"Ġ155\": 18918,\n    \"ĠBillboard\": 18919,\n    \"icion\": 18920,\n    \"Times\": 18921,\n    \"ĠZoe\": 18922,\n    \"ĠAbby\": 18923,\n    \"bus\": 18924,\n    \"ĠMinutes\": 18925,\n    \"ributed\": 18926,\n    \"Ġparap\": 18927,\n    \"Ġfertil\": 18928,\n    \"ABC\": 18929,\n    \"ĠIsle\": 18930,\n    \"Ġtherapist\": 18931,\n    \"Ġgubernatorial\": 18932,\n    \"ĠAust\": 18933,\n    \"ĠLoan\": 18934,\n    \"Bo\": 18935,\n    \"ĠNRL\": 18936,\n    \"rag\": 18937,\n    \"Clear\": 18938,\n    \"Ġrevision\": 18939,\n    \"Ġflesh\": 18940,\n    \"BD\": 18941,\n    \"iji\": 18942,\n    \"Ġproductions\": 18943,\n    \"Ġcoconut\": 18944,\n    \"ĠMcCorm\": 18945,\n    \"ĠDash\": 18946,\n    \"Ġgeography\": 18947,\n    \"hearted\": 18948,\n    \"Ġarson\": 18949,\n    \"Ġgoaltender\": 18950,\n    \"Ġbelly\": 18951,\n    \"Ġqualifications\": 18952,\n    \"ĠActiv\": 18953,\n    \"Ġhooked\": 18954,\n    \"ĠHungarian\": 18955,\n    \"Ġprotocols\": 18956,\n    \"inking\": 18957,\n    \"Ġfronts\": 18958,\n    \"ĠKuala\": 18959,\n    \"ĠToys\": 18960,\n    \"ĠFitness\": 18961,\n    \"Ġwarfare\": 18962,\n    \"Ġoutp\": 18963,\n    \"ĠQuestions\": 18964,\n    \"Ġwel\": 18965,\n    \"ĠShan\": 18966,\n    \"ĠMorton\": 18967,\n    \"ĠRomero\": 18968,\n    \"Ġglance\": 18969,\n    \"ĠTay\": 18970,\n    \"Ġsneakers\": 18971,\n    \"ĠSymphony\": 18972,\n    \"Ġinspect\": 18973,\n    \"enna\": 18974,\n    \"Nobody\": 18975,\n    \"Ġscrapped\": 18976,\n    \"ĠDeVos\": 18977,\n    \"ĠDominican\": 18978,\n    \"Ġplanets\": 18979,\n    \"anova\": 18980,\n    \"Ġnotify\": 18981,\n    \"Ġincurred\": 18982,\n    \"Ġunders\": 18983,\n    \"Ġdetainees\": 18984,\n    \"ĠMarriott\": 18985,\n    \"electric\": 18986,\n    \"ĠKes\": 18987,\n    \"union\": 18988,\n    \"ĠWatt\": 18989,\n    \"ATING\": 18990,\n    \"Ġslipping\": 18991,\n    \"Ġraft\": 18992,\n    \"Ġresisted\": 18993,\n    \"Ġcred\": 18994,\n    \"tern\": 18995,\n    \"Ġflurry\": 18996,\n    \"Line\": 18997,\n    \"Ġconsulted\": 18998,\n    \"Ġanalyzing\": 18999,\n    \"107\": 19000,\n    \"ĠWide\": 19001,\n    \"¶\": 19002,\n    \"human\": 19003,\n    \"ĠFEMA\": 19004,\n    \"Ġsmash\": 19005,\n    \"Ġcorps\": 19006,\n    \"Ġbarric\": 19007,\n    \"Ġcollar\": 19008,\n    \"ĠTB\": 19009,\n    \"without\": 19010,\n    \"ĠCanucks\": 19011,\n    \"Ġneedle\": 19012,\n    \"ĠSidney\": 19013,\n    \"ĠLauderdale\": 19014,\n    \"Ġglove\": 19015,\n    \"ilee\": 19016,\n    \"pic\": 19017,\n    \"Ġbenef\": 19018,\n    \"ĠHydro\": 19019,\n    \"ĠDisc\": 19020,\n    \"ĠArg\": 19021,\n    \"Ġtermin\": 19022,\n    \"Ġsympath\": 19023,\n    \"Ġpest\": 19024,\n    \"ĠCoff\": 19025,\n    \"Ġadvancement\": 19026,\n    \"social\": 19027,\n    \"pol\": 19028,\n    \"ĠEmails\": 19029,\n    \"Ġstacked\": 19030,\n    \"ibly\": 19031,\n    \"ĠAlbion\": 19032,\n    \"Ġfist\": 19033,\n    \"hero\": 19034,\n    \"ĠMarian\": 19035,\n    \"asia\": 19036,\n    \"Ġtownship\": 19037,\n    \"Ġslick\": 19038,\n    \"Ġmodeling\": 19039,\n    \"achers\": 19040,\n    \"ĠArgent\": 19041,\n    \"ĠSUN\": 19042,\n    \"arde\": 19043,\n    \"Ġpinned\": 19044,\n    \"Ġhitters\": 19045,\n    \"Ġdare\": 19046,\n    \"ictions\": 19047,\n    \"arily\": 19048,\n    \"Ġsting\": 19049,\n    \"Ġprimaries\": 19050,\n    \"appointed\": 19051,\n    \"Ġformats\": 19052,\n    \"Ġglitter\": 19053,\n    \"Ġpatches\": 19054,\n    \"Ġstrategically\": 19055,\n    \"Ġaka\": 19056,\n    \"Ġyielded\": 19057,\n    \"BY\": 19058,\n    \"Ġjeopard\": 19059,\n    \"ĠVand\": 19060,\n    \"Ġcrowned\": 19061,\n    \"Ġoccupants\": 19062,\n    \"Ġtanker\": 19063,\n    \"ĠVisa\": 19064,\n    \"Great\": 19065,\n    \"Ġseasoned\": 19066,\n    \"ĠAviv\": 19067,\n    \"Ġfiery\": 19068,\n    \"Ġderivatives\": 19069,\n    \"Ġdiverted\": 19070,\n    \"Ġacqu\": 19071,\n    \"Ġsandwiches\": 19072,\n    \"ĠLorenzo\": 19073,\n    \"Ġpardon\": 19074,\n    \"ĠBarber\": 19075,\n    \"ĠAgricultural\": 19076,\n    \"ĠPhilly\": 19077,\n    \"Ġregrets\": 19078,\n    \"ĠMillions\": 19079,\n    \"ĠFrazier\": 19080,\n    \"Ġtreasury\": 19081,\n    \"ĠKenn\": 19082,\n    \"Ġdestined\": 19083,\n    \"olved\": 19084,\n    \"Back\": 19085,\n    \"leader\": 19086,\n    \"lyss\": 19087,\n    \"ĠReyes\": 19088,\n    \"001\": 19089,\n    \"bags\": 19090,\n    \"ĠStandards\": 19091,\n    \"ĠExcellence\": 19092,\n    \"ĠMaid\": 19093,\n    \"ĠAnthem\": 19094,\n    \"FIELD\": 19095,\n    \"Ġrevived\": 19096,\n    \"ĠQuad\": 19097,\n    \"Ġdistinguished\": 19098,\n    \"Ġweighted\": 19099,\n    \"Ġritual\": 19100,\n    \"Ġinvites\": 19101,\n    \"wana\": 19102,\n    \"iture\": 19103,\n    \"ĠCI\": 19104,\n    \"ĠMAY\": 19105,\n    \"Ġunfairly\": 19106,\n    \"ĠKP\": 19107,\n    \"ĠMidlands\": 19108,\n    \"Ġmint\": 19109,\n    \"uers\": 19110,\n    \"Ġcatalog\": 19111,\n    \"arant\": 19112,\n    \"Ġlosers\": 19113,\n    \"Ġscheduling\": 19114,\n    \"esar\": 19115,\n    \"Ġtransferring\": 19116,\n    \"Ġbankrupt\": 19117,\n    \"Ġmethamphetamine\": 19118,\n    \"ĠEsk\": 19119,\n    \"ĠTreatment\": 19120,\n    \"ĠResponse\": 19121,\n    \"Ġhomework\": 19122,\n    \"ĠBald\": 19123,\n    \"Ġembarrassment\": 19124,\n    \"Ġpoorest\": 19125,\n    \"ĠPlatinum\": 19126,\n    \"ĠFac\": 19127,\n    \"Ġunleashed\": 19128,\n    \"Ġbrighter\": 19129,\n    \"002\": 19130,\n    \"Ġdisl\": 19131,\n    \"ĠLowry\": 19132,\n    \"ived\": 19133,\n    \"ĠDemon\": 19134,\n    \"ĠNonetheless\": 19135,\n    \"arro\": 19136,\n    \"ĠCONT\": 19137,\n    \"ifted\": 19138,\n    \"ĠFreder\": 19139,\n    \"isson\": 19140,\n    \"Ġrout\": 19141,\n    \"ARA\": 19142,\n    \"Ġswinging\": 19143,\n    \"Oct\": 19144,\n    \"Ġliable\": 19145,\n    \"Ġleaning\": 19146,\n    \"Ġlungs\": 19147,\n    \"380\": 19148,\n    \"ĠProcess\": 19149,\n    \"ĠCov\": 19150,\n    \"terrorism\": 19151,\n    \"Ġresistant\": 19152,\n    \"Ġpumped\": 19153,\n    \"Ġtripled\": 19154,\n    \"Semitism\": 19155,\n    \"ĠMia\": 19156,\n    \"Ġpenetration\": 19157,\n    \"ĠLutheran\": 19158,\n    \"BU\": 19159,\n    \"odes\": 19160,\n    \"Ġspanning\": 19161,\n    \"utch\": 19162,\n    \"Trans\": 19163,\n    \"ĠVolunteers\": 19164,\n    \"Ġpathway\": 19165,\n    \"Ġinfectious\": 19166,\n    \"Ġdrastic\": 19167,\n    \"ĠEngineers\": 19168,\n    \"Ġprincess\": 19169,\n    \"acts\": 19170,\n    \"usting\": 19171,\n    \"utive\": 19172,\n    \"achel\": 19173,\n    \"DO\": 19174,\n    \"Ġpave\": 19175,\n    \"ĠHerrera\": 19176,\n    \"Ġnearing\": 19177,\n    \"help\": 19178,\n    \"Ġembarked\": 19179,\n    \"Ġmodes\": 19180,\n    \"ĠDriving\": 19181,\n    \"Ġopting\": 19182,\n    \"Best\": 19183,\n    \"Ġbehavioral\": 19184,\n    \"Ġcables\": 19185,\n    \"App\": 19186,\n    \"otion\": 19187,\n    \"ĠExt\": 19188,\n    \"ĠSinclair\": 19189,\n    \"ĠInsp\": 19190,\n    \"Ġsinking\": 19191,\n    \"Next\": 19192,\n    \"ĠLumpur\": 19193,\n    \"ĠShadow\": 19194,\n    \"Donald\": 19195,\n    \"itals\": 19196,\n    \"Ġmentions\": 19197,\n    \"floor\": 19198,\n    \"Ġconsiderations\": 19199,\n    \"ĠSquad\": 19200,\n    \"ĠPlate\": 19201,\n    \"dos\": 19202,\n    \"Friday\": 19203,\n    \"Hopefully\": 19204,\n    \"arre\": 19205,\n    \"Ġalum\": 19206,\n    \"\\\":\\\"/\": 19207,\n    \"Ġfet\": 19208,\n    \"anza\": 19209,\n    \"Ġdign\": 19210,\n    \"ĠNguyen\": 19211,\n    \"ĠRutgers\": 19212,\n    \"ĠSew\": 19213,\n    \"Ġfilters\": 19214,\n    \"ofi\": 19215,\n    \"Ġunavailable\": 19216,\n    \"ranking\": 19217,\n    \"Ġrefining\": 19218,\n    \"ĠUNC\": 19219,\n    \"Ġmax\": 19220,\n    \"yll\": 19221,\n    \"Ġhandsome\": 19222,\n    \"Ġutterly\": 19223,\n    \"See\": 19224,\n    \"ĠStores\": 19225,\n    \"Ke\": 19226,\n    \"ĠAdvoc\": 19227,\n    \"ordon\": 19228,\n    \"umbles\": 19229,\n    \"Ġbugs\": 19230,\n    \"olar\": 19231,\n    \"ĠCork\": 19232,\n    \"Ġtoken\": 19233,\n    \"Ġauthorization\": 19234,\n    \"Ġconscience\": 19235,\n    \"Ġrepl\": 19236,\n    \"edi\": 19237,\n    \"owitz\": 19238,\n    \"iven\": 19239,\n    \"Ġlieu\": 19240,\n    \"Ġlifts\": 19241,\n    \"Lean\": 19242,\n    \"Ġmagnificent\": 19243,\n    \"ĠFilms\": 19244,\n    \"onents\": 19245,\n    \"Ġ***\": 19246,\n    \"Green\": 19247,\n    \"ĠAdvocate\": 19248,\n    \"ĠArrow\": 19249,\n    \"Ġblows\": 19250,\n    \"Ġexploited\": 19251,\n    \"fly\": 19252,\n    \"ĠAmar\": 19253,\n    \"ĠNOTICE\": 19254,\n    \"Ġsincere\": 19255,\n    \"found\": 19256,\n    \"ĠRud\": 19257,\n    \"Ġcy\": 19258,\n    \"ĠHeidi\": 19259,\n    \"Ġempowered\": 19260,\n    \"Ġweakest\": 19261,\n    \"ĠKru\": 19262,\n    \"Credit\": 19263,\n    \"aunted\": 19264,\n    \"Ġexotic\": 19265,\n    \"aning\": 19266,\n    \"Ġaw\": 19267,\n    \"ĠMulti\": 19268,\n    \"Ġanimation\": 19269,\n    \"850\": 19270,\n    \"ĠCounter\": 19271,\n    \"ĠNit\": 19272,\n    \"alli\": 19273,\n    \"Ġcapitalize\": 19274,\n    \"Ġexecuting\": 19275,\n    \"Ġdescent\": 19276,\n    \"ovi\": 19277,\n    \"ĠKimberly\": 19278,\n    \"headed\": 19279,\n    \"Ġmentioning\": 19280,\n    \")-\": 19281,\n    \"ĠSpecifically\": 19282,\n    \"ayette\": 19283,\n    \"ihad\": 19284,\n    \"ĠIss\": 19285,\n    \"Ġdisagreed\": 19286,\n    \"ĠKum\": 19287,\n    \"Ġurges\": 19288,\n    \"Ġpermitting\": 19289,\n    \"Ġpy\": 19290,\n    \"isp\": 19291,\n    \"Ġhygiene\": 19292,\n    \"Ġmourning\": 19293,\n    \"Ġcyclists\": 19294,\n    \"cats\": 19295,\n    \"FER\": 19296,\n    \"cycl\": 19297,\n    \"Ġnewcomers\": 19298,\n    \"Ġplead\": 19299,\n    \"Ġmend\": 19300,\n    \"secret\": 19301,\n    \"fan\": 19302,\n    \"Ġtranslates\": 19303,\n    \"unit\": 19304,\n    \"ĠTank\": 19305,\n    \"drive\": 19306,\n    \"ĠSite\": 19307,\n    \"Ġacceleration\": 19308,\n    \"ĠEnrique\": 19309,\n    \"ĠElaine\": 19310,\n    \"Ġstaring\": 19311,\n    \"Ġbackwards\": 19312,\n    \"Ġot\": 19313,\n    \"Ġvot\": 19314,\n    \"ĠHK\": 19315,\n    \"Ġfian\": 19316,\n    \"ĠLockheed\": 19317,\n    \"Ġmanifest\": 19318,\n    \"ĠZurich\": 19319,\n    \"pad\": 19320,\n    \"ĠRav\": 19321,\n    \"flow\": 19322,\n    \"Ġmoms\": 19323,\n    \"ĠSolid\": 19324,\n    \"ĠReady\": 19325,\n    \"aughlin\": 19326,\n    \"Ġreminding\": 19327,\n    \"ĠCOR\": 19328,\n    \"Ġoptimal\": 19329,\n    \"ĠCrisis\": 19330,\n    \"Ġcholesterol\": 19331,\n    \"ĠGerard\": 19332,\n    \"Ġfest\": 19333,\n    \"Ġsanction\": 19334,\n    \"Ġdragging\": 19335,\n    \"inent\": 19336,\n    \"ĠBravo\": 19337,\n    \"Ġamend\": 19338,\n    \"aval\": 19339,\n    \"Ġpoem\": 19340,\n    \"Ġinvasive\": 19341,\n    \"Ġlandsc\": 19342,\n    \"leigh\": 19343,\n    \"Ġheadache\": 19344,\n    \"ĠMuse\": 19345,\n    \"ĠTurning\": 19346,\n    \"girl\": 19347,\n    \"cess\": 19348,\n    \"Ġfalsely\": 19349,\n    \"Ġplaintiff\": 19350,\n    \"Ġheavier\": 19351,\n    \"Ġrumored\": 19352,\n    \"Ġeleven\": 19353,\n    \"ĠConsumers\": 19354,\n    \"ĠOriginally\": 19355,\n    \"ĠStatement\": 19356,\n    \"bors\": 19357,\n    \"Ġrevoked\": 19358,\n    \"ĠOmaha\": 19359,\n    \"Fox\": 19360,\n    \"ĠKle\": 19361,\n    \"Ġvault\": 19362,\n    \"Ġoutdated\": 19363,\n    \"umes\": 19364,\n    \"ĠArk\": 19365,\n    \"Ġapologised\": 19366,\n    \"Ġrockets\": 19367,\n    \"ĠMarines\": 19368,\n    \"Ġcaptures\": 19369,\n    \"ĠMW\": 19370,\n    \"ĠWalters\": 19371,\n    \"ĠFactor\": 19372,\n    \"Ġensuing\": 19373,\n    \"ĠSession\": 19374,\n    \"oons\": 19375,\n    \"Ġ132\": 19376,\n    \"gt\": 19377,\n    \"ĠPoints\": 19378,\n    \"Ġexhaust\": 19379,\n    \"ĠOsaka\": 19380,\n    \"heed\": 19381,\n    \"Ġhandic\": 19382,\n    \"amber\": 19383,\n    \"inging\": 19384,\n    \"Ġll\": 19385,\n    \"Ġescorted\": 19386,\n    \"Ġfloated\": 19387,\n    \"Ġmerge\": 19388,\n    \"Ġcompliment\": 19389,\n    \"ĠVC\": 19390,\n    \"Ġinsulin\": 19391,\n    \"ĠDebt\": 19392,\n    \"Ã§a\": 19393,\n    \"Ġpens\": 19394,\n    \"Ġassertion\": 19395,\n    \"Ġredevelopment\": 19396,\n    \"moderate\": 19397,\n    \"Ġleftist\": 19398,\n    \"ĠBA\": 19399,\n    \"Ġherd\": 19400,\n    \"Ġinsecurity\": 19401,\n    \"liter\": 19402,\n    \"Ġcommence\": 19403,\n    \"ĠCaucus\": 19404,\n    \"Ġnovels\": 19405,\n    \"ĠChevron\": 19406,\n    \"Ġerosion\": 19407,\n    \"ĠNicholson\": 19408,\n    \"ĠRoof\": 19409,\n    \"ĠVolunteer\": 19410,\n    \"Ġcompelled\": 19411,\n    \"Ġcongratulated\": 19412,\n    \"ĠPanel\": 19413,\n    \"Ġov\": 19414,\n    \"idelity\": 19415,\n    \"Ġspect\": 19416,\n    \"Ġbee\": 19417,\n    \"ĠAssistance\": 19418,\n    \"Ġterrified\": 19419,\n    \"iew\": 19420,\n    \"Ġweekday\": 19421,\n    \"ĠHiggins\": 19422,\n    \"special\": 19423,\n    \"ubs\": 19424,\n    \"anton\": 19425,\n    \"Ġbribes\": 19426,\n    \"Ġneat\": 19427,\n    \"ĠCliff\": 19428,\n    \"Ġdisqualified\": 19429,\n    \"ĠND\": 19430,\n    \"Ġvers\": 19431,\n    \"andra\": 19432,\n    \"Ġgraft\": 19433,\n    \"value\": 19434,\n    \"Ġportray\": 19435,\n    \"Ġdaytime\": 19436,\n    \"ksh\": 19437,\n    \"Ġconsist\": 19438,\n    \"Ġhonesty\": 19439,\n    \"ĠTimber\": 19440,\n    \"ĠNich\": 19441,\n    \"Ġinvented\": 19442,\n    \"ĠBuch\": 19443,\n    \"Ġskull\": 19444,\n    \"Ġtags\": 19445,\n    \"Ġ124\": 19446,\n    \"ighth\": 19447,\n    \"Ġrelaxing\": 19448,\n    \"Online\": 19449,\n    \"Ġsanctioned\": 19450,\n    \"Sport\": 19451,\n    \"ĠCove\": 19452,\n    \"Ġcomics\": 19453,\n    \"MW\": 19454,\n    \"AMA\": 19455,\n    \"mother\": 19456,\n    \"Home\": 19457,\n    \"ĠCustomer\": 19458,\n    \"Ġstrides\": 19459,\n    \"ĠWins\": 19460,\n    \"Ġrollout\": 19461,\n    \"ĠWeaver\": 19462,\n    \"Ġshuttle\": 19463,\n    \"Ġsteak\": 19464,\n    \"Ġglorious\": 19465,\n    \"ĠToll\": 19466,\n    \"Ġtrustee\": 19467,\n    \"Ġinstallations\": 19468,\n    \"ĠOpportunity\": 19469,\n    \"Ġoper\": 19470,\n    \"horse\": 19471,\n    \"Ġaided\": 19472,\n    \"irus\": 19473,\n    \"Ġsleek\": 19474,\n    \"Ġyelled\": 19475,\n    \"ĠSocialist\": 19476,\n    \"Ġapplaud\": 19477,\n    \"ĠWah\": 19478,\n    \"Ġdevote\": 19479,\n    \"Ġdh\": 19480,\n    \"Ġarchitectural\": 19481,\n    \"ĠMAC\": 19482,\n    \"centric\": 19483,\n    \"ĠSense\": 19484,\n    \"illas\": 19485,\n    \"ĠArchbishop\": 19486,\n    \"glass\": 19487,\n    \"Ġallowance\": 19488,\n    \"Ġbundle\": 19489,\n    \"andon\": 19490,\n    \"eight\": 19491,\n    \"ĠKare\": 19492,\n    \"haus\": 19493,\n    \"ĠAndreas\": 19494,\n    \"Ġdoll\": 19495,\n    \"RAM\": 19496,\n    \"Ġvolunteering\": 19497,\n    \"ĠRaleigh\": 19498,\n    \"Ġbees\": 19499,\n    \"Ġnickel\": 19500,\n    \"Ġgenerosity\": 19501,\n    \"Ġhomeowner\": 19502,\n    \"ĠLieutenant\": 19503,\n    \"Ġlandfall\": 19504,\n    \"ĠRenew\": 19505,\n    \"ĠGiving\": 19506,\n    \"ĠContribut\": 19507,\n    \"aret\": 19508,\n    \"ulf\": 19509,\n    \"Ġreinforce\": 19510,\n    \"ĠSalv\": 19511,\n    \"ĠVenice\": 19512,\n    \"Ġfreedoms\": 19513,\n    \"ĠTools\": 19514,\n    \"Ġ1962\": 19515,\n    \"ĠWarm\": 19516,\n    \"majority\": 19517,\n    \"Ġpleas\": 19518,\n    \"oding\": 19519,\n    \"plant\": 19520,\n    \"Ġtow\": 19521,\n    \"ĠBlanc\": 19522,\n    \"ĠPipeline\": 19523,\n    \"ĠMoor\": 19524,\n    \"Ġrefrain\": 19525,\n    \"ĠExplore\": 19526,\n    \"language\": 19527,\n    \"cers\": 19528,\n    \"ĠWT\": 19529,\n    \"sent\": 19530,\n    \"ĠNun\": 19531,\n    \"Ġplastics\": 19532,\n    \"acas\": 19533,\n    \"Ġdisruptions\": 19534,\n    \"Ġdiscomfort\": 19535,\n    \"enko\": 19536,\n    \"Ġimprisoned\": 19537,\n    \"Copyright\": 19538,\n    \"Ġmyriad\": 19539,\n    \"Ġparenting\": 19540,\n    \"Ġspree\": 19541,\n    \"NBC\": 19542,\n    \"Ġonion\": 19543,\n    \"ĠIsraelis\": 19544,\n    \"ĠRA\": 19545,\n    \"Ġrelocate\": 19546,\n    \"113\": 19547,\n    \"ĠHir\": 19548,\n    \"ĠDre\": 19549,\n    \"ĠDry\": 19550,\n    \"ĠONE\": 19551,\n    \"ĠAdministrator\": 19552,\n    \"Ġprints\": 19553,\n    \"ĠGret\": 19554,\n    \"Ġundergraduate\": 19555,\n    \"ĠLif\": 19556,\n    \"avers\": 19557,\n    \"ĠCarney\": 19558,\n    \"Ġapex\": 19559,\n    \"Ġlenses\": 19560,\n    \"Ġliberals\": 19561,\n    \"gb\": 19562,\n    \"ĠWhereas\": 19563,\n    \"Ġcountryside\": 19564,\n    \"amine\": 19565,\n    \"ĠTerminal\": 19566,\n    \"Ġintr\": 19567,\n    \"ĠTrey\": 19568,\n    \"ALS\": 19569,\n    \"Ġcontinental\": 19570,\n    \"Ġselfies\": 19571,\n    \"FILE\": 19572,\n    \"ĠUnity\": 19573,\n    \"Ġauthoritarian\": 19574,\n    \"Ġoriginated\": 19575,\n    \"ĠExcept\": 19576,\n    \"yna\": 19577,\n    \"Ġmonet\": 19578,\n    \"Ġundermining\": 19579,\n    \"ĠGS\": 19580,\n    \"pi\": 19581,\n    \"iq\": 19582,\n    \"Ġslides\": 19583,\n    \"ĠSummary\": 19584,\n    \"Ġpains\": 19585,\n    \"cluding\": 19586,\n    \"Ġequation\": 19587,\n    \"locked\": 19588,\n    \"Ġfraternity\": 19589,\n    \"Ġwithstand\": 19590,\n    \"Ġdevastation\": 19591,\n    \"Ġdemo\": 19592,\n    \"late\": 19593,\n    \"Ġpunches\": 19594,\n    \"Ġgeared\": 19595,\n    \"nen\": 19596,\n    \"ĠBowie\": 19597,\n    \"attle\": 19598,\n    \"Ġpolitic\": 19599,\n    \"ĠGle\": 19600,\n    \"mented\": 19601,\n    \"ĠCoordinator\": 19602,\n    \"Ġupwards\": 19603,\n    \"ĠMega\": 19604,\n    \"angled\": 19605,\n    \"Ġengineered\": 19606,\n    \"Ġluggage\": 19607,\n    \"ĠWen\": 19608,\n    \"ĠSergeant\": 19609,\n    \"Ġkindergarten\": 19610,\n    \"ĠPortsmouth\": 19611,\n    \"uddin\": 19612,\n    \"ket\": 19613,\n    \"oba\": 19614,\n    \"Ġoscill\": 19615,\n    \"esse\": 19616,\n    \"ĠOlson\": 19617,\n    \"ĠBorough\": 19618,\n    \"Ġsupplements\": 19619,\n    \"ĠEvening\": 19620,\n    \"ANE\": 19621,\n    \"Ġlava\": 19622,\n    \"Ġgearing\": 19623,\n    \"setting\": 19624,\n    \"urgical\": 19625,\n    \"asty\": 19626,\n    \"ĠDaytona\": 19627,\n    \"Ġbrewery\": 19628,\n    \"Ġpledges\": 19629,\n    \"rounder\": 19630,\n    \"ulous\": 19631,\n    \"ĠHancock\": 19632,\n    \"rex\": 19633,\n    \"Ġram\": 19634,\n    \"Ġproceeding\": 19635,\n    \"ĠMurdoch\": 19636,\n    \"Ġdowngrade\": 19637,\n    \"Ġstatues\": 19638,\n    \"Ġdebated\": 19639,\n    \"ĠSleep\": 19640,\n    \"Ġ144\": 19641,\n    \"ĠRuby\": 19642,\n    \"ĠFi\": 19643,\n    \"123\": 19644,\n    \"ĠArabic\": 19645,\n    \"Ġlasts\": 19646,\n    \"ĠIvy\": 19647,\n    \"ĠWid\": 19648,\n    \"rown\": 19649,\n    \"stick\": 19650,\n    \"?'\\\"\": 19651,\n    \"ĠSTEM\": 19652,\n    \"Ġsensible\": 19653,\n    \"htar\": 19654,\n    \"Ġharbor\": 19655,\n    \"Ġcra\": 19656,\n    \"ĠAlbum\": 19657,\n    \"ĠCarnival\": 19658,\n    \"Ġimplies\": 19659,\n    \"agement\": 19660,\n    \"ĠInitially\": 19661,\n    \"Ġchooses\": 19662,\n    \"Jeff\": 19663,\n    \"ĠHig\": 19664,\n    \"Ġtam\": 19665,\n    \"Ġlump\": 19666,\n    \"ucks\": 19667,\n    \"Ġrepatri\": 19668,\n    \"ĠMercy\": 19669,\n    \"zza\": 19670,\n    \"Ġ365\": 19671,\n    \"ĠRicardo\": 19672,\n    \"ogram\": 19673,\n    \"Ġundergone\": 19674,\n    \"system\": 19675,\n    \"Ġtel\": 19676,\n    \"ĠKee\": 19677,\n    \"ully\": 19678,\n    \"istas\": 19679,\n    \"Ġgrains\": 19680,\n    \"ĠTomorrow\": 19681,\n    \"ĠRC\": 19682,\n    \"ĠTurk\": 19683,\n    \"Ġfreshmen\": 19684,\n    \"ĠAway\": 19685,\n    \"ĠSach\": 19686,\n    \"ĠUltimate\": 19687,\n    \"Ġoffensively\": 19688,\n    \"ismo\": 19689,\n    \"Ġteaser\": 19690,\n    \"ĠJud\": 19691,\n    \"Ġlegitimacy\": 19692,\n    \"opt\": 19693,\n    \"ĠCobb\": 19694,\n    \"Ġrejecting\": 19695,\n    \"ĠSolo\": 19696,\n    \"ĠArcher\": 19697,\n    \"Ġsoutheastern\": 19698,\n    \"ĠPlain\": 19699,\n    \"ĠLoss\": 19700,\n    \"Ġminerals\": 19701,\n    \"ĠMari\": 19702,\n    \"Ġscrambling\": 19703,\n    \"ĠPeak\": 19704,\n    \"Ġhavoc\": 19705,\n    \"rings\": 19706,\n    \"Ġunofficial\": 19707,\n    \"ĠHaj\": 19708,\n    \"director\": 19709,\n    \"ĠCanal\": 19710,\n    \"ĠNSA\": 19711,\n    \"ĠEaton\": 19712,\n    \"ĠPART\": 19713,\n    \"ĠCommissioners\": 19714,\n    \"Ġwellbeing\": 19715,\n    \"resa\": 19716,\n    \"Ġunderstandable\": 19717,\n    \"dates\": 19718,\n    \"ĠSorry\": 19719,\n    \"Ġastonishing\": 19720,\n    \"Ġrevise\": 19721,\n    \"ĠEc\": 19722,\n    \"ĠLack\": 19723,\n    \"endi\": 19724,\n    \"endale\": 19725,\n    \"also\": 19726,\n    \"Ġcolder\": 19727,\n    \"Ġheel\": 19728,\n    \"Ġcellular\": 19729,\n    \"Conn\": 19730,\n    \"ĠThur\": 19731,\n    \"Ġmassage\": 19732,\n    \"olla\": 19733,\n    \"clus\": 19734,\n    \"Ġtoilets\": 19735,\n    \"ĠCelebr\": 19736,\n    \"Ġtackled\": 19737,\n    \"Ġchorus\": 19738,\n    \"ETA\": 19739,\n    \"anca\": 19740,\n    \"ĠOLED\": 19741,\n    \"Ġpunk\": 19742,\n    \"ĠBrain\": 19743,\n    \"ĠNuggets\": 19744,\n    \"Ġseamless\": 19745,\n    \"make\": 19746,\n    \"atted\": 19747,\n    \"ĠRog\": 19748,\n    \"ĠPatch\": 19749,\n    \"Ġruined\": 19750,\n    \"Ins\": 19751,\n    \"Ġconsolidate\": 19752,\n    \"Ġgospel\": 19753,\n    \"ĠCaption\": 19754,\n    \"Ġoverweight\": 19755,\n    \"Ġscreened\": 19756,\n    \"ĠKraft\": 19757,\n    \"ĠBain\": 19758,\n    \"breaker\": 19759,\n    \"ĠFeinstein\": 19760,\n    \"ĠDoc\": 19761,\n    \"Ġdeepest\": 19762,\n    \"ĠOL\": 19763,\n    \"Ġtunes\": 19764,\n    \"Ġrightly\": 19765,\n    \"ĠLanc\": 19766,\n    \"ĠBrotherhood\": 19767,\n    \"Ġpoultry\": 19768,\n    \"ĠPure\": 19769,\n    \"Ġstimulate\": 19770,\n    \"Ġdiscourse\": 19771,\n    \"ĠStark\": 19772,\n    \"Ġmuseums\": 19773,\n    \"ention\": 19774,\n    \"Ġtaxation\": 19775,\n    \"ĠAkron\": 19776,\n    \"ayer\": 19777,\n    \"ĠKirby\": 19778,\n    \"farm\": 19779,\n    \"oser\": 19780,\n    \"Ġcommend\": 19781,\n    \"Ġunarmed\": 19782,\n    \"ensions\": 19783,\n    \"Ġsuperst\": 19784,\n    \"Ġoceans\": 19785,\n    \"Ġmisuse\": 19786,\n    \"LO\": 19787,\n    \"ĠByrne\": 19788,\n    \"ĠMaritime\": 19789,\n    \"Ġdense\": 19790,\n    \"Ġexcuses\": 19791,\n    \"Ġsuppose\": 19792,\n    \"ĠMarks\": 19793,\n    \"Ġrainy\": 19794,\n    \"Ġreplicate\": 19795,\n    \"Ġboutique\": 19796,\n    \"ĠRenaissance\": 19797,\n    \"jas\": 19798,\n    \"icted\": 19799,\n    \"Ġreferenced\": 19800,\n    \"ĠTir\": 19801,\n    \"ĠHatch\": 19802,\n    \"ĠCry\": 19803,\n    \"ĠPayPal\": 19804,\n    \"Ġfulfil\": 19805,\n    \"ĠHawaiian\": 19806,\n    \"come\": 19807,\n    \"ĠThirty\": 19808,\n    \"Ġ260\": 19809,\n    \"ĠYak\": 19810,\n    \"Ġangles\": 19811,\n    \"Ġlandlord\": 19812,\n    \"Ġlavish\": 19813,\n    \"Women\": 19814,\n    \"ĠNT\": 19815,\n    \"Ġreinforced\": 19816,\n    \"Ġprevail\": 19817,\n    \"ĠCommunities\": 19818,\n    \"Ġfootwear\": 19819,\n    \"Ġassurances\": 19820,\n    \"Ġlb\": 19821,\n    \"Ġairing\": 19822,\n    \"Ġresorts\": 19823,\n    \"ĠFiji\": 19824,\n    \"ĠShay\": 19825,\n    \"Ġprevailing\": 19826,\n    \"many\": 19827,\n    \"Ġimpe\": 19828,\n    \"ĠDul\": 19829,\n    \"Ġsymbols\": 19830,\n    \"zb\": 19831,\n    \"ĠCere\": 19832,\n    \"Ġapplauded\": 19833,\n    \"Ġsoundtrack\": 19834,\n    \"Ġdrunken\": 19835,\n    \"ĠEuropeans\": 19836,\n    \"Ġherds\": 19837,\n    \"moving\": 19838,\n    \"WR\": 19839,\n    \"ĠHindi\": 19840,\n    \"Ġwaking\": 19841,\n    \"Jo\": 19842,\n    \"Andrew\": 19843,\n    \"rosse\": 19844,\n    \"ĠLegislative\": 19845,\n    \"Ġdisgrace\": 19846,\n    \"Nothing\": 19847,\n    \"ĠBulgaria\": 19848,\n    \"Ġhumidity\": 19849,\n    \"Ġtranslation\": 19850,\n    \"Ġmeasurements\": 19851,\n    \"Ġvying\": 19852,\n    \"ĠBrid\": 19853,\n    \"Max\": 19854,\n    \"Ġdir\": 19855,\n    \"unci\": 19856,\n    \"Ġdefines\": 19857,\n    \"Ġperfection\": 19858,\n    \"ancers\": 19859,\n    \"Matt\": 19860,\n    \"ĠShinzo\": 19861,\n    \"ĠPresidents\": 19862,\n    \"Ġginger\": 19863,\n    \"onna\": 19864,\n    \"existing\": 19865,\n    \"rika\": 19866,\n    \"enced\": 19867,\n    \"ĠBray\": 19868,\n    \"Ġgall\": 19869,\n    \"Ġdisrespect\": 19870,\n    \"ĠCumber\": 19871,\n    \"Ġcontestant\": 19872,\n    \"ucky\": 19873,\n    \"anticipated\": 19874,\n    \"abled\": 19875,\n    \"LLOW\": 19876,\n    \"Bel\": 19877,\n    \"ĠKear\": 19878,\n    \"Ġstoryline\": 19879,\n    \"Ġrigs\": 19880,\n    \"ĠScots\": 19881,\n    \"ĠChap\": 19882,\n    \"ĠThankfully\": 19883,\n    \"Ġcommunist\": 19884,\n    \"ĠAdviser\": 19885,\n    \"Ġregist\": 19886,\n    \"Ġannoying\": 19887,\n    \"ĠDVD\": 19888,\n    \"Ġethic\": 19889,\n    \"ĠFilipino\": 19890,\n    \"ĠAdidas\": 19891,\n    \"Ġbilling\": 19892,\n    \"Ġalleviate\": 19893,\n    \"Ġsmoked\": 19894,\n    \"Ġhazard\": 19895,\n    \"EV\": 19896,\n    \"Ag\": 19897,\n    \"baum\": 19898,\n    \"Ġdoses\": 19899,\n    \"Ġoutcry\": 19900,\n    \"Ġinclined\": 19901,\n    \"Ġpsychologist\": 19902,\n    \"itzer\": 19903,\n    \"January\": 19904,\n    \"Ġmornings\": 19905,\n    \"aught\": 19906,\n    \"Ġsurreal\": 19907,\n    \"ĠCannon\": 19908,\n    \"avy\": 19909,\n    \"ĠCris\": 19910,\n    \"cf\": 19911,\n    \"Ġinterpreted\": 19912,\n    \"Ġpersecution\": 19913,\n    \"vation\": 19914,\n    \"Ġupfront\": 19915,\n    \"ĠWaste\": 19916,\n    \"Ġmills\": 19917,\n    \"Ġbombings\": 19918,\n    \"ĠHeaven\": 19919,\n    \"ĠFlat\": 19920,\n    \"Ġboxer\": 19921,\n    \"Ġavenues\": 19922,\n    \"Invest\": 19923,\n    \"ĠZika\": 19924,\n    \"Ġbackstage\": 19925,\n    \"idas\": 19926,\n    \"eston\": 19927,\n    \"ead\": 19928,\n    \"Ġbishops\": 19929,\n    \"Ġrender\": 19930,\n    \"Ġfootballer\": 19931,\n    \"Ġspilled\": 19932,\n    \"Only\": 19933,\n    \"Ġsaddened\": 19934,\n    \"ĠAbove\": 19935,\n    \"inator\": 19936,\n    \"tro\": 19937,\n    \"onen\": 19938,\n    \"ĠAMC\": 19939,\n    \"Ġstringent\": 19940,\n    \"Ġfooting\": 19941,\n    \"ĠGhost\": 19942,\n    \"Ġtexting\": 19943,\n    \"ĠCPI\": 19944,\n    \"ĠUW\": 19945,\n    \"Ġaccol\": 19946,\n    \"iries\": 19947,\n    \"ĠFlex\": 19948,\n    \"ĠCarolyn\": 19949,\n    \"Andre\": 19950,\n    \"Ġsiege\": 19951,\n    \"Muslim\": 19952,\n    \"Ġautomobile\": 19953,\n    \"reci\": 19954,\n    \"Ġdean\": 19955,\n    \"atre\": 19956,\n    \"Ġwax\": 19957,\n    \"Ġwo\": 19958,\n    \"ĠDuffy\": 19959,\n    \"Ġfiance\": 19960,\n    \"Ġfib\": 19961,\n    \"Ġeagle\": 19962,\n    \"ĠCatal\": 19963,\n    \"Ġinfants\": 19964,\n    \"Ġsubmitting\": 19965,\n    \"Ġdownhill\": 19966,\n    \"Ġstaffer\": 19967,\n    \"ĠLights\": 19968,\n    \"Ġeater\": 19969,\n    \"ĠCaliforn\": 19970,\n    \"Ġsupervisors\": 19971,\n    \"ĠPy\": 19972,\n    \"Ġcondemnation\": 19973,\n    \"Ġsci\": 19974,\n    \"Ġhated\": 19975,\n    \"Ġtil\": 19976,\n    \"ĠLavrov\": 19977,\n    \"Ġsab\": 19978,\n    \"Ġmotors\": 19979,\n    \"Ġlogging\": 19980,\n    \"ĠOwn\": 19981,\n    \"Ġpi\": 19982,\n    \"Ġrepeating\": 19983,\n    \"ĠDOJ\": 19984,\n    \"enary\": 19985,\n    \"ĠChow\": 19986,\n    \"fat\": 19987,\n    \"Ġbalcony\": 19988,\n    \"orie\": 19989,\n    \"NING\": 19990,\n    \"ĠUnified\": 19991,\n    \"Neil\": 19992,\n    \"Bill\": 19993,\n    \"ĠSims\": 19994,\n    \"uten\": 19995,\n    \"LV\": 19996,\n    \"ĠEMS\": 19997,\n    \"Ġsip\": 19998,\n    \"Ġreplaces\": 19999,\n    \"ichi\": 20000,\n    \"ĠFig\": 20001,\n    \"ĠCharity\": 20002,\n    \"Ġpeek\": 20003,\n    \"Ġrack\": 20004,\n    \"Ġcousins\": 20005,\n    \"Ġresolving\": 20006,\n    \"Ġthrone\": 20007,\n    \"ĠEngine\": 20008,\n    \"ĠChak\": 20009,\n    \"Ġlamented\": 20010,\n    \"Ġwipe\": 20011,\n    \"Ġnutrients\": 20012,\n    \"ĠChat\": 20013,\n    \"AMP\": 20014,\n    \"ĠOprah\": 20015,\n    \"uming\": 20016,\n    \"serving\": 20017,\n    \"Ġfir\": 20018,\n    \"Ġlandlords\": 20019,\n    \"neck\": 20020,\n    \"Ġupload\": 20021,\n    \"Ġunspecified\": 20022,\n    \"Ġicy\": 20023,\n    \"´\": 20024,\n    \"Ġze\": 20025,\n    \"Ġprohibits\": 20026,\n    \"ĠFI\": 20027,\n    \"Res\": 20028,\n    \"ĠEff\": 20029,\n    \"hell\": 20030,\n    \"umbo\": 20031,\n    \"Ġreceipts\": 20032,\n    \"Ġoperatives\": 20033,\n    \"stant\": 20034,\n    \"Ġwives\": 20035,\n    \"ĠCinema\": 20036,\n    \"Ġnegligence\": 20037,\n    \"Ġgases\": 20038,\n    \"ĠLau\": 20039,\n    \"Ġbrew\": 20040,\n    \"August\": 20041,\n    \"never\": 20042,\n    \"Ġpenned\": 20043,\n    \"Ġincomplete\": 20044,\n    \"ĠZh\": 20045,\n    \"esi\": 20046,\n    \"Ġranged\": 20047,\n    \"apolis\": 20048,\n    \"Ġwithdrawing\": 20049,\n    \"ĠLevi\": 20050,\n    \"ĠLevy\": 20051,\n    \"ĠDaly\": 20052,\n    \"Ġdelaying\": 20053,\n    \"ĠMSNBC\": 20054,\n    \"ĠCyrus\": 20055,\n    \"ĠNutrition\": 20056,\n    \"NN\": 20057,\n    \"Ġwinding\": 20058,\n    \"Ġglow\": 20059,\n    \"ĠMY\": 20060,\n    \"Ġgoodwill\": 20061,\n    \"ĠMON\": 20062,\n    \"Ġslots\": 20063,\n    \"ĠNina\": 20064,\n    \"ĠFIR\": 20065,\n    \"ĠLTE\": 20066,\n    \"ĠInnov\": 20067,\n    \"dev\": 20068,\n    \"ctic\": 20069,\n    \"Ġanalyses\": 20070,\n    \"ĠBangalore\": 20071,\n    \"Ġtales\": 20072,\n    \"Ġovercame\": 20073,\n    \"ĠThurs\": 20074,\n    \"Ġcherry\": 20075,\n    \"ĠNou\": 20076,\n    \"ĠFlowers\": 20077,\n    \"1000\": 20078,\n    \"updated\": 20079,\n    \"rieve\": 20080,\n    \"ĠBeautiful\": 20081,\n    \"iak\": 20082,\n    \"Ġplayback\": 20083,\n    \"Ġheadset\": 20084,\n    \"Ġashamed\": 20085,\n    \"Min\": 20086,\n    \"Ġadm\": 20087,\n    \"ĠLucky\": 20088,\n    \"ĠTucson\": 20089,\n    \"Ġentirety\": 20090,\n    \"ranging\": 20091,\n    \"ĠVance\": 20092,\n    \"kered\": 20093,\n    \"image\": 20094,\n    \"ĠGord\": 20095,\n    \"War\": 20096,\n    \"Ġsimilarities\": 20097,\n    \"dig\": 20098,\n    \"ĠJude\": 20099,\n    \"Ġlonely\": 20100,\n    \"hra\": 20101,\n    \"ĠStaples\": 20102,\n    \"ĠACA\": 20103,\n    \"Ġmeasurement\": 20104,\n    \"Ġcooper\": 20105,\n    \"ATER\": 20106,\n    \"ĠMeng\": 20107,\n    \"Ġbarring\": 20108,\n    \"190\": 20109,\n    \"ĠBatt\": 20110,\n    \"Ġreproductive\": 20111,\n    \"ĠRowe\": 20112,\n    \"Ġsubsid\": 20113,\n    \"Ġslogans\": 20114,\n    \"ugar\": 20115,\n    \"ĠKeller\": 20116,\n    \"ingham\": 20117,\n    \"fuel\": 20118,\n    \"Ġhid\": 20119,\n    \"afe\": 20120,\n    \"Ġindul\": 20121,\n    \"cash\": 20122,\n    \"Ġstressing\": 20123,\n    \"ĠMIT\": 20124,\n    \"Ġtrump\": 20125,\n    \"ancer\": 20126,\n    \"ĠPes\": 20127,\n    \"ĠMint\": 20128,\n    \"Ġcrossover\": 20129,\n    \"ĠWeiss\": 20130,\n    \"ĠElvis\": 20131,\n    \"ĠPermanent\": 20132,\n    \"ĠKhalid\": 20133,\n    \"Ġunjust\": 20134,\n    \"Ġexceptionally\": 20135,\n    \"Ġfut\": 20136,\n    \"Ġavid\": 20137,\n    \"ĠEthics\": 20138,\n    \"Ġutilized\": 20139,\n    \"Ġfeasibility\": 20140,\n    \"Ġcatering\": 20141,\n    \"Press\": 20142,\n    \"wayne\": 20143,\n    \"October\": 20144,\n    \"Ġfavors\": 20145,\n    \"Ġobsession\": 20146,\n    \"Ġmelt\": 20147,\n    \"Ġmug\": 20148,\n    \"ĠMK\": 20149,\n    \"Ġapples\": 20150,\n    \"Ġvine\": 20151,\n    \"cliffe\": 20152,\n    \"Ġgrat\": 20153,\n    \"Ġspells\": 20154,\n    \"ounced\": 20155,\n    \"Ġdecree\": 20156,\n    \"issy\": 20157,\n    \"Team\": 20158,\n    \"Ġdeploying\": 20159,\n    \"Feb\": 20160,\n    \"Ġmiserable\": 20161,\n    \"Ġwat\": 20162,\n    \"ĠBust\": 20163,\n    \"ĠNorris\": 20164,\n    \"ĠTimberwolves\": 20165,\n    \"Ġangered\": 20166,\n    \"ĠArn\": 20167,\n    \"oft\": 20168,\n    \"rome\": 20169,\n    \"Ġadvertisements\": 20170,\n    \"onal\": 20171,\n    \"Ġnun\": 20172,\n    \"Ġtorque\": 20173,\n    \"Ġslave\": 20174,\n    \"Ġnonsense\": 20175,\n    \"Ġcoy\": 20176,\n    \"Ġcites\": 20177,\n    \"Game\": 20178,\n    \"Ġarchitects\": 20179,\n    \"playing\": 20180,\n    \"Ġgener\": 20181,\n    \"Ġsocio\": 20182,\n    \"Ġmeditation\": 20183,\n    \"Ġforgive\": 20184,\n    \"Ġsmiled\": 20185,\n    \"%),\": 20186,\n    \"Ġpers\": 20187,\n    \"ĠSoph\": 20188,\n    \"Ġoccupy\": 20189,\n    \"atton\": 20190,\n    \"Ġwitnessing\": 20191,\n    \"Ġapologise\": 20192,\n    \"Ġpredecessors\": 20193,\n    \"ĠCassidy\": 20194,\n    \"Ġtallied\": 20195,\n    \"NER\": 20196,\n    \"Ġtract\": 20197,\n    \"ĠHolder\": 20198,\n    \"ĠPav\": 20199,\n    \"Ġjackets\": 20200,\n    \"Mel\": 20201,\n    \"raud\": 20202,\n    \"Ġexercising\": 20203,\n    \"ĠChung\": 20204,\n    \"ĠAmin\": 20205,\n    \"athi\": 20206,\n    \"ĠMem\": 20207,\n    \"Ġracked\": 20208,\n    \"Ġcarved\": 20209,\n    \"ĠMickey\": 20210,\n    \"ĠLafayette\": 20211,\n    \"Ġgrill\": 20212,\n    \"ĠINFORMATION\": 20213,\n    \"usc\": 20214,\n    \"ĠPromotion\": 20215,\n    \"yson\": 20216,\n    \"istry\": 20217,\n    \"Ġfulfilled\": 20218,\n    \"Ġrestraint\": 20219,\n    \"Ġpopping\": 20220,\n    \"ĠSlater\": 20221,\n    \"Ġmercy\": 20222,\n    \"aden\": 20223,\n    \"Ġsubmarine\": 20224,\n    \"ĠBowling\": 20225,\n    \"dogs\": 20226,\n    \"ĠSwe\": 20227,\n    \"Ġnoticeable\": 20228,\n    \"Ġbis\": 20229,\n    \"ĠPremiership\": 20230,\n    \"Ġspat\": 20231,\n    \"ĠTow\": 20232,\n    \"ĠWand\": 20233,\n    \"Ġmechanics\": 20234,\n    \"while\": 20235,\n    \"ĠBenson\": 20236,\n    \"Ġmolecules\": 20237,\n    \"Ġcrosses\": 20238,\n    \"Ġrecalling\": 20239,\n    \"ĠCertainly\": 20240,\n    \"HAM\": 20241,\n    \"Ġsever\": 20242,\n    \"ĠRudy\": 20243,\n    \"ĠDUI\": 20244,\n    \"OLD\": 20245,\n    \"ĠTobacco\": 20246,\n    \"Ġsubdued\": 20247,\n    \"Ġquota\": 20248,\n    \"TF\": 20249,\n    \"Ġflats\": 20250,\n    \"Ġemphasize\": 20251,\n    \"Ġbelts\": 20252,\n    \"ĠOpinion\": 20253,\n    \"Ġpiled\": 20254,\n    \"ĠSpark\": 20255,\n    \"ĠElias\": 20256,\n    \"Ġclassification\": 20257,\n    \"ĠHands\": 20258,\n    \"ĠCV\": 20259,\n    \"Ġtoast\": 20260,\n    \"Ġcandle\": 20261,\n    \"atching\": 20262,\n    \"short\": 20263,\n    \"ĠDup\": 20264,\n    \"Ġult\": 20265,\n    \"bats\": 20266,\n    \"Ġmarketers\": 20267,\n    \"ĠAvery\": 20268,\n    \"ĠColbert\": 20269,\n    \"ĠIk\": 20270,\n    \"ĠVac\": 20271,\n    \"ĠJackets\": 20272,\n    \"Ġmerits\": 20273,\n    \"eli\": 20274,\n    \"PORT\": 20275,\n    \"Ġelevator\": 20276,\n    \"irming\": 20277,\n    \"effective\": 20278,\n    \"Ġgroceries\": 20279,\n    \"Ġhi\": 20280,\n    \"ĠINTER\": 20281,\n    \"ĠSAP\": 20282,\n    \"ĠNYPD\": 20283,\n    \"ĠKY\": 20284,\n    \"Ġangel\": 20285,\n    \"Ġspectacle\": 20286,\n    \"rÃ©\": 20287,\n    \"ĠRoche\": 20288,\n    \"Ġinsects\": 20289,\n    \"Ġcommenced\": 20290,\n    \"ĠFoley\": 20291,\n    \"Ġdarker\": 20292,\n    \"ĠUg\": 20293,\n    \"ĠMostly\": 20294,\n    \"Ġtermed\": 20295,\n    \"uci\": 20296,\n    \"ĠExec\": 20297,\n    \"ĠBrittany\": 20298,\n    \"Ġharmony\": 20299,\n    \"Ġadvocated\": 20300,\n    \"Ġparcel\": 20301,\n    \"ĠHots\": 20302,\n    \"Ġmonarch\": 20303,\n    \"ĠSiri\": 20304,\n    \"odge\": 20305,\n    \"ĠPag\": 20306,\n    \"Ġprogressing\": 20307,\n    \"grounds\": 20308,\n    \"Ġonstage\": 20309,\n    \"Ġwarmth\": 20310,\n    \"ĠWon\": 20311,\n    \"Ġviolates\": 20312,\n    \"ĠSaudis\": 20313,\n    \"Ġbumper\": 20314,\n    \"Ġpatrols\": 20315,\n    \"ĠBarron\": 20316,\n    \"Ġindoors\": 20317,\n    \"Ġtar\": 20318,\n    \"Each\": 20319,\n    \"Val\": 20320,\n    \"Ġapplicant\": 20321,\n    \"ĠCater\": 20322,\n    \"Ġclassics\": 20323,\n    \"ĠThreat\": 20324,\n    \"Ġwrapping\": 20325,\n    \"ĠIdlib\": 20326,\n    \"anking\": 20327,\n    \"Did\": 20328,\n    \"adia\": 20329,\n    \"ĠRig\": 20330,\n    \"ĠBram\": 20331,\n    \"ĠLaurie\": 20332,\n    \"ĠHair\": 20333,\n    \"ĠCannabis\": 20334,\n    \"Ġdaylight\": 20335,\n    \"ĠNorm\": 20336,\n    \"ĠRip\": 20337,\n    \"sin\": 20338,\n    \"unta\": 20339,\n    \"Pass\": 20340,\n    \"ĠAcad\": 20341,\n    \"ĠCummings\": 20342,\n    \"Ġtheirs\": 20343,\n    \"ĠDistribution\": 20344,\n    \"especially\": 20345,\n    \"Ġgrilled\": 20346,\n    \"Ġaffiliates\": 20347,\n    \"ĠVander\": 20348,\n    \"ĠCath\": 20349,\n    \"ĠProductions\": 20350,\n    \"ĠTrek\": 20351,\n    \"230\": 20352,\n    \"Ġcasinos\": 20353,\n    \"ĠCain\": 20354,\n    \"atu\": 20355,\n    \"idget\": 20356,\n    \"ĠWinds\": 20357,\n    \"Ġunanswered\": 20358,\n    \"Ġintercept\": 20359,\n    \"ĠMarty\": 20360,\n    \"Ġrefin\": 20361,\n    \"Ġlieutenant\": 20362,\n    \"cas\": 20363,\n    \"Chief\": 20364,\n    \"average\": 20365,\n    \"ilot\": 20366,\n    \"Ġscrimmage\": 20367,\n    \"ĠMud\": 20368,\n    \"speaking\": 20369,\n    \"ĠFranken\": 20370,\n    \"ĠTories\": 20371,\n    \"Ġabstract\": 20372,\n    \"awar\": 20373,\n    \"ĠTerms\": 20374,\n    \"dal\": 20375,\n    \"ĠFur\": 20376,\n    \"Ġhumour\": 20377,\n    \"rh\": 20378,\n    \"Ġsitu\": 20379,\n    \"aed\": 20380,\n    \"ĠFIN\": 20381,\n    \"Ġtranscripts\": 20382,\n    \"approved\": 20383,\n    \"ĠParsons\": 20384,\n    \"Ġpigs\": 20385,\n    \"Ġrepayment\": 20386,\n    \"ĠARM\": 20387,\n    \"ĠElliot\": 20388,\n    \"ĠLevine\": 20389,\n    \"Ġtagged\": 20390,\n    \"pun\": 20391,\n    \"ĠDwight\": 20392,\n    \"Ġconfiguration\": 20393,\n    \"sis\": 20394,\n    \"ĠAdult\": 20395,\n    \"Ġearthquakes\": 20396,\n    \"Ġcreature\": 20397,\n    \"ĠMRI\": 20398,\n    \"Ġmach\": 20399,\n    \"Ġprescriptions\": 20400,\n    \"cover\": 20401,\n    \"Ġministries\": 20402,\n    \"Ġinaccurate\": 20403,\n    \"ĠLabs\": 20404,\n    \"ĠMGM\": 20405,\n    \"Ġtomato\": 20406,\n    \"Ġeng\": 20407,\n    \"Ġopposes\": 20408,\n    \"owan\": 20409,\n    \"Ġmapping\": 20410,\n    \"Ġconsum\": 20411,\n    \"online\": 20412,\n    \"eters\": 20413,\n    \"code\": 20414,\n    \"Aug\": 20415,\n    \"Point\": 20416,\n    \"branded\": 20417,\n    \"pling\": 20418,\n    \"ĠCalder\": 20419,\n    \"Oper\": 20420,\n    \"ĠMiddles\": 20421,\n    \"Ġchampagne\": 20422,\n    \"ĠTues\": 20423,\n    \"Ġsampling\": 20424,\n    \"Ġenergetic\": 20425,\n    \"rano\": 20426,\n    \"ĠStyles\": 20427,\n    \"Ġneglected\": 20428,\n    \"ĠDamon\": 20429,\n    \"Ġendanger\": 20430,\n    \"Ġsouthwestern\": 20431,\n    \"ĠATM\": 20432,\n    \"ĠDuck\": 20433,\n    \"engers\": 20434,\n    \"Ġdan\": 20435,\n    \"yth\": 20436,\n    \"Ġbou\": 20437,\n    \"ĠDecl\": 20438,\n    \"Gold\": 20439,\n    \"Ġprojecting\": 20440,\n    \"Google\": 20441,\n    \"ĠHussein\": 20442,\n    \"Ġaccomplishment\": 20443,\n    \"itarian\": 20444,\n    \"Ġgossip\": 20445,\n    \"ĠRai\": 20446,\n    \"ril\": 20447,\n    \"ĠSke\": 20448,\n    \"Ġpsychiatric\": 20449,\n    \"ĠMacBook\": 20450,\n    \"ĠAdobe\": 20451,\n    \"ĠHodg\": 20452,\n    \"Ġaccompany\": 20453,\n    \"Ġadvertised\": 20454,\n    \"Ġreminiscent\": 20455,\n    \"Ġgeographical\": 20456,\n    \"Ġconvertible\": 20457,\n    \"IK\": 20458,\n    \"CTV\": 20459,\n    \"Ġcommunal\": 20460,\n    \"Ġchim\": 20461,\n    \"Ġselfish\": 20462,\n    \"Ġdrilled\": 20463,\n    \"Ġtortured\": 20464,\n    \"Ġblacks\": 20465,\n    \"noon\": 20466,\n    \"Ġmanifesto\": 20467,\n    \"ĠRichie\": 20468,\n    \"acco\": 20469,\n    \"Im\": 20470,\n    \"Ġdebit\": 20471,\n    \"ĠSNP\": 20472,\n    \"perfect\": 20473,\n    \"gard\": 20474,\n    \"ĠRatio\": 20475,\n    \"Ġstubborn\": 20476,\n    \"Ġaccumulation\": 20477,\n    \"Ġcongregation\": 20478,\n    \"Ġkissing\": 20479,\n    \"Ġkillers\": 20480,\n    \"ĠAbbey\": 20481,\n    \"von\": 20482,\n    \"ĠFuj\": 20483,\n    \"ĠIsabel\": 20484,\n    \"NB\": 20485,\n    \"ĠNish\": 20486,\n    \"ĠJulius\": 20487,\n    \"ĠZimmer\": 20488,\n    \"Ġuncover\": 20489,\n    \"dar\": 20490,\n    \"isle\": 20491,\n    \"ĠCompar\": 20492,\n    \"Ġcounselor\": 20493,\n    \"ĠSok\": 20494,\n    \"ĠCumm\": 20495,\n    \"ĠHip\": 20496,\n    \"Ġurgently\": 20497,\n    \"Ġrentals\": 20498,\n    \"Ġapproving\": 20499,\n    \"Ġirrigation\": 20500,\n    \"Ġprostate\": 20501,\n    \"ĠJudicial\": 20502,\n    \"ĠSubmit\": 20503,\n    \"ĠTanner\": 20504,\n    \"attack\": 20505,\n    \"emb\": 20506,\n    \"Ġreclaim\": 20507,\n    \"Ġec\": 20508,\n    \"Ġbrutality\": 20509,\n    \"Ġcommanding\": 20510,\n    \"Ġreasoning\": 20511,\n    \"Roy\": 20512,\n    \"ĠElect\": 20513,\n    \"ĠMobil\": 20514,\n    \"anding\": 20515,\n    \"Ġmirrors\": 20516,\n    \"Israel\": 20517,\n    \"Ġpavement\": 20518,\n    \"Ġoverdue\": 20519,\n    \"ĠMd\": 20520,\n    \"street\": 20521,\n    \"Ġthrill\": 20522,\n    \"pora\": 20523,\n    \"azon\": 20524,\n    \"Ġbrewing\": 20525,\n    \"enge\": 20526,\n    \"ĠDisaster\": 20527,\n    \"Ġbuilder\": 20528,\n    \"ods\": 20529,\n    \"utsch\": 20530,\n    \"Ġterminals\": 20531,\n    \"ĠBaird\": 20532,\n    \"enburg\": 20533,\n    \"Ġhast\": 20534,\n    \"Ġbrass\": 20535,\n    \"Ġparental\": 20536,\n    \"enture\": 20537,\n    \"ĠConduct\": 20538,\n    \"Ġexpands\": 20539,\n    \"luck\": 20540,\n    \"mur\": 20541,\n    \"ĠBj\": 20542,\n    \"Ġadministrations\": 20543,\n    \"ĠOlivier\": 20544,\n    \"oux\": 20545,\n    \"Ġnarrowed\": 20546,\n    \"winner\": 20547,\n    \"Ġmakeshift\": 20548,\n    \"ĠVAT\": 20549,\n    \"ĠJavier\": 20550,\n    \"-,\": 20551,\n    \"Ġsystematic\": 20552,\n    \"Ġenforcing\": 20553,\n    \"emin\": 20554,\n    \"ĠAudio\": 20555,\n    \"United\": 20556,\n    \"gener\": 20557,\n    \"ĠKara\": 20558,\n    \"ivas\": 20559,\n    \"ĠPretty\": 20560,\n    \"ĠLob\": 20561,\n    \"Ġpetitions\": 20562,\n    \"ĠMercer\": 20563,\n    \"ampa\": 20564,\n    \"product\": 20565,\n    \"Ġdistributing\": 20566,\n    \"Ġtunnels\": 20567,\n    \"Ġcondo\": 20568,\n    \"ĠRSS\": 20569,\n    \"ĠCarlo\": 20570,\n    \"Ġpumpkin\": 20571,\n    \"Ġsto\": 20572,\n    \"Ġassumes\": 20573,\n    \"oway\": 20574,\n    \"hiba\": 20575,\n    \"lection\": 20576,\n    \"Ġgam\": 20577,\n    \"ĠAires\": 20578,\n    \"Ġtransmitted\": 20579,\n    \"Ġtrousers\": 20580,\n    \"Ġcheers\": 20581,\n    \"ĠJensen\": 20582,\n    \"Ġemer\": 20583,\n    \"Ġsimpler\": 20584,\n    \"Ġcolored\": 20585,\n    \"ĠSustainable\": 20586,\n    \"Ġinstruct\": 20587,\n    \"Ġpoles\": 20588,\n    \"Ġsupervised\": 20589,\n    \"Ġinteg\": 20590,\n    \"ĠMoreno\": 20591,\n    \"boarding\": 20592,\n    \"igrant\": 20593,\n    \"ĠYoga\": 20594,\n    \"Ġenvironmentally\": 20595,\n    \"Ġsacrifices\": 20596,\n    \"Ġshores\": 20597,\n    \"Ġ127\": 20598,\n    \"Ġestranged\": 20599,\n    \"Ġintoxicated\": 20600,\n    \"Ġemergencies\": 20601,\n    \"ĠKosovo\": 20602,\n    \"yang\": 20603,\n    \"Ġfastball\": 20604,\n    \"Ġpackaged\": 20605,\n    \"LAN\": 20606,\n    \"Ġhurry\": 20607,\n    \"ĠManny\": 20608,\n    \"Ġporch\": 20609,\n    \"Ġcuriosity\": 20610,\n    \"ĠKend\": 20611,\n    \"thouse\": 20612,\n    \"ĠTou\": 20613,\n    \"mun\": 20614,\n    \"Ġwaving\": 20615,\n    \"Ġpasswords\": 20616,\n    \"ĠSwan\": 20617,\n    \"Ġprefers\": 20618,\n    \"ĠCorrections\": 20619,\n    \"aic\": 20620,\n    \"Ġejected\": 20621,\n    \"Ġdossier\": 20622,\n    \"ĠChal\": 20623,\n    \"Ġfacto\": 20624,\n    \"Ġspine\": 20625,\n    \"leck\": 20626,\n    \"Ġrestriction\": 20627,\n    \"Ġdisagreement\": 20628,\n    \"grown\": 20629,\n    \"ĠEdgar\": 20630,\n    \"Ġquantities\": 20631,\n    \"ĠRapid\": 20632,\n    \"Ġpals\": 20633,\n    \"Ġspared\": 20634,\n    \"Ġremarkably\": 20635,\n    \"ructure\": 20636,\n    \"Ġbackers\": 20637,\n    \"ĠGoals\": 20638,\n    \"cles\": 20639,\n    \"rolling\": 20640,\n    \"ĠBlasio\": 20641,\n    \"Ġorchestra\": 20642,\n    \"ologies\": 20643,\n    \"ĠRise\": 20644,\n    \"Power\": 20645,\n    \"Ġuptick\": 20646,\n    \"atha\": 20647,\n    \"ĠMob\": 20648,\n    \"Ġshotgun\": 20649,\n    \"downs\": 20650,\n    \"ĠBorg\": 20651,\n    \"Ġmorale\": 20652,\n    \"Call\": 20653,\n    \"wave\": 20654,\n    \"ĠDuc\": 20655,\n    \"Ġunwilling\": 20656,\n    \"oad\": 20657,\n    \"Ġbusinessmen\": 20658,\n    \"Ġrefriger\": 20659,\n    \"Ġgamers\": 20660,\n    \"Ġcele\": 20661,\n    \"Ġprecip\": 20662,\n    \"Ġrenegoti\": 20663,\n    \"OY\": 20664,\n    \"ĠPharm\": 20665,\n    \"Ġresponsive\": 20666,\n    \"Ġservant\": 20667,\n    \"eye\": 20668,\n    \"Ġraping\": 20669,\n    \"vas\": 20670,\n    \"Ġgroin\": 20671,\n    \"ĠMelvin\": 20672,\n    \"ĠKurds\": 20673,\n    \"Ġstricter\": 20674,\n    \"ĠMum\": 20675,\n    \"ients\": 20676,\n    \"Ġstandalone\": 20677,\n    \"Ġforums\": 20678,\n    \"Ġcommemorate\": 20679,\n    \"Far\": 20680,\n    \"ĠTelegram\": 20681,\n    \"Ġscreenings\": 20682,\n    \"ĠLeonardo\": 20683,\n    \"ighton\": 20684,\n    \"ĠDOWN\": 20685,\n    \"Ġmodule\": 20686,\n    \"Ġremedy\": 20687,\n    \"Ġ280\": 20688,\n    \"Su\": 20689,\n    \"ĠBecker\": 20690,\n    \"ĠGast\": 20691,\n    \"prem\": 20692,\n    \"ĠInto\": 20693,\n    \"oyle\": 20694,\n    \"114\": 20695,\n    \"Ġadhere\": 20696,\n    \"Report\": 20697,\n    \"ĠJaneiro\": 20698,\n    \"ĠKry\": 20699,\n    \"Pakistan\": 20700,\n    \"Ġrobotic\": 20701,\n    \"ande\": 20702,\n    \"Ġoverlooking\": 20703,\n    \"ĠTreaty\": 20704,\n    \"Ġrect\": 20705,\n    \"yne\": 20706,\n    \"Ġbattlefield\": 20707,\n    \"ĠGeoff\": 20708,\n    \"Ġearns\": 20709,\n    \"ĠMiner\": 20710,\n    \"Ġteased\": 20711,\n    \"Ġexemptions\": 20712,\n    \"Ġvacancy\": 20713,\n    \"oku\": 20714,\n    \"Ġvulnerabilities\": 20715,\n    \"ĠRou\": 20716,\n    \"Ġobserv\": 20717,\n    \"Ġoverlook\": 20718,\n    \"Ġcorrespond\": 20719,\n    \"Ġtheatrical\": 20720,\n    \"Ġrobotics\": 20721,\n    \"ĠCompl\": 20722,\n    \"ĠPasadena\": 20723,\n    \"laden\": 20724,\n    \"Ġvastly\": 20725,\n    \"olit\": 20726,\n    \"Ġjustification\": 20727,\n    \"Ġtampering\": 20728,\n    \"ĠSutherland\": 20729,\n    \"ĠMens\": 20730,\n    \"Ġinvisible\": 20731,\n    \"uren\": 20732,\n    \"ĠAshton\": 20733,\n    \"owl\": 20734,\n    \"Ġdisqual\": 20735,\n    \"ĠEva\": 20736,\n    \"Ġfriction\": 20737,\n    \"ĠIrvine\": 20738,\n    \"Ġaliens\": 20739,\n    \"ĠPension\": 20740,\n    \"ĠAssets\": 20741,\n    \"ĠBenedict\": 20742,\n    \"ittal\": 20743,\n    \"Ġsword\": 20744,\n    \"Ġunderwear\": 20745,\n    \"ĠFarmer\": 20746,\n    \"Ġtimber\": 20747,\n    \"Ġdependence\": 20748,\n    \"ĠTang\": 20749,\n    \"Ġ165\": 20750,\n    \"ĠNazis\": 20751,\n    \"Ġpunching\": 20752,\n    \"ĠGloria\": 20753,\n    \"usat\": 20754,\n    \"Ġluxurious\": 20755,\n    \"chuk\": 20756,\n    \"ĠCot\": 20757,\n    \"Ġregained\": 20758,\n    \"Ġreassure\": 20759,\n    \"Ġhello\": 20760,\n    \"Ġante\": 20761,\n    \"Ġnegotiators\": 20762,\n    \"Add\": 20763,\n    \"paced\": 20764,\n    \"Ã©r\": 20765,\n    \"Ġdemolished\": 20766,\n    \"Ann\": 20767,\n    \"joy\": 20768,\n    \"ĠJenna\": 20769,\n    \"Apple\": 20770,\n    \"Ġdisturbance\": 20771,\n    \"Ġcommissions\": 20772,\n    \"ĠPolitico\": 20773,\n    \"along\": 20774,\n    \"Ġnem\": 20775,\n    \"Ġauctions\": 20776,\n    \"ruck\": 20777,\n    \"ĠOD\": 20778,\n    \"ofer\": 20779,\n    \"Play\": 20780,\n    \"Ġcarn\": 20781,\n    \"vez\": 20782,\n    \"Ġtents\": 20783,\n    \"Ġcongratulate\": 20784,\n    \"ĠLiquid\": 20785,\n    \"ĠCoyotes\": 20786,\n    \"uku\": 20787,\n    \"ĠAllah\": 20788,\n    \"Ġbend\": 20789,\n    \"Ġcanvas\": 20790,\n    \"ĠClifford\": 20791,\n    \"Ġvolunteered\": 20792,\n    \"Luc\": 20793,\n    \"bp\": 20794,\n    \"ĠCensus\": 20795,\n    \"ĠShot\": 20796,\n    \"Ġanonymously\": 20797,\n    \"ĠAnglo\": 20798,\n    \"ĠBayer\": 20799,\n    \"ĠAber\": 20800,\n    \"ĠCorrectional\": 20801,\n    \"Ġhardship\": 20802,\n    \"ĠBuenos\": 20803,\n    \"ĠDaw\": 20804,\n    \"Ġbaskets\": 20805,\n    \"Ġupstairs\": 20806,\n    \"Ġmindful\": 20807,\n    \"ĠLCD\": 20808,\n    \"ĠBlackburn\": 20809,\n    \"ĠHale\": 20810,\n    \"477\": 20811,\n    \"Ġcircus\": 20812,\n    \"ĠDragons\": 20813,\n    \"Ġrubble\": 20814,\n    \"rb\": 20815,\n    \"Ġheadaches\": 20816,\n    \"aunt\": 20817,\n    \"itus\": 20818,\n    \"Ġscaled\": 20819,\n    \"ĠComic\": 20820,\n    \"asio\": 20821,\n    \"ĠNordic\": 20822,\n    \"Per\": 20823,\n    \"Ġbombers\": 20824,\n    \"ilitation\": 20825,\n    \"Ġindirectly\": 20826,\n    \"ĠHod\": 20827,\n    \"andan\": 20828,\n    \"operation\": 20829,\n    \"Ġpuppy\": 20830,\n    \"ĠMats\": 20831,\n    \"Ġstewards\": 20832,\n    \"roup\": 20833,\n    \"Ġmemorandum\": 20834,\n    \"Ġpatio\": 20835,\n    \"const\": 20836,\n    \"ĠBold\": 20837,\n    \"ĠKaiser\": 20838,\n    \"Following\": 20839,\n    \"Ġcompat\": 20840,\n    \"Ġsidewalks\": 20841,\n    \"ĠFitzpatrick\": 20842,\n    \"Ġsunlight\": 20843,\n    \"ĠLever\": 20844,\n    \"ĠBecky\": 20845,\n    \"icles\": 20846,\n    \"ĠProbably\": 20847,\n    \"Ġgarner\": 20848,\n    \"ĠTomas\": 20849,\n    \"Ġblankets\": 20850,\n    \"uga\": 20851,\n    \"jiang\": 20852,\n    \"Ġrevel\": 20853,\n    \"ĠHutch\": 20854,\n    \"llers\": 20855,\n    \"Ġtrimmed\": 20856,\n    \"ĠSTR\": 20857,\n    \"ĠKR\": 20858,\n    \"ĠPike\": 20859,\n    \"ĠASS\": 20860,\n    \"Bay\": 20861,\n    \"Ġdiagnostic\": 20862,\n    \"ĠSteph\": 20863,\n    \"Ġtoured\": 20864,\n    \"ĠAvoid\": 20865,\n    \"vic\": 20866,\n    \"Without\": 20867,\n    \"ĠClinical\": 20868,\n    \"Ġblo\": 20869,\n    \"undo\": 20870,\n    \"ĠBoise\": 20871,\n    \"Ġspeculated\": 20872,\n    \"ĠProt\": 20873,\n    \"vention\": 20874,\n    \"Ġscholar\": 20875,\n    \"ĠSta\": 20876,\n    \"Featured\": 20877,\n    \"ĠPrev\": 20878,\n    \"Ġpenny\": 20879,\n    \"ĠHath\": 20880,\n    \"rawn\": 20881,\n    \"Ġrenovated\": 20882,\n    \"ĠFried\": 20883,\n    \"itol\": 20884,\n    \"uddle\": 20885,\n    \"Ġinquest\": 20886,\n    \"Ġmetropolitan\": 20887,\n    \"lights\": 20888,\n    \"Ġtempo\": 20889,\n    \"onom\": 20890,\n    \"ĠImport\": 20891,\n    \"Asia\": 20892,\n    \"Ġowes\": 20893,\n    \"Ġmagistrate\": 20894,\n    \"ĠFriedman\": 20895,\n    \"Ġcontacting\": 20896,\n    \"Ġstrains\": 20897,\n    \"Ġhomage\": 20898,\n    \"Ġlent\": 20899,\n    \"ception\": 20900,\n    \"git\": 20901,\n    \"Ġlively\": 20902,\n    \"Ġscra\": 20903,\n    \"WW\": 20904,\n    \"Ã¶n\": 20905,\n    \"rill\": 20906,\n    \"Jack\": 20907,\n    \"ĠShank\": 20908,\n    \"iani\": 20909,\n    \"Ġdecreasing\": 20910,\n    \"MON\": 20911,\n    \"ĠSupervisor\": 20912,\n    \"ĠCats\": 20913,\n    \"ĠFusion\": 20914,\n    \"Ġracially\": 20915,\n    \"ĠTara\": 20916,\n    \"ĠPurchase\": 20917,\n    \"ĠRally\": 20918,\n    \"ĠGraph\": 20919,\n    \"ĠHello\": 20920,\n    \"hest\": 20921,\n    \"ĠVarg\": 20922,\n    \"Ġdrowned\": 20923,\n    \"ĠThu\": 20924,\n    \"ĠWet\": 20925,\n    \"ĠEug\": 20926,\n    \"Ġrainbow\": 20927,\n    \"Ġtelev\": 20928,\n    \"ĠAmir\": 20929,\n    \"Based\": 20930,\n    \"Ġcookie\": 20931,\n    \"uding\": 20932,\n    \"Ġcontracting\": 20933,\n    \"Ġobjected\": 20934,\n    \"Ġfork\": 20935,\n    \"acent\": 20936,\n    \"ĠTil\": 20937,\n    \"ĠLilly\": 20938,\n    \"ĠEur\": 20939,\n    \"Ġhormone\": 20940,\n    \"Ġnails\": 20941,\n    \"ĠFischer\": 20942,\n    \"Ġpier\": 20943,\n    \"EMENT\": 20944,\n    \"Ġeruption\": 20945,\n    \"visory\": 20946,\n    \"Ġspeculate\": 20947,\n    \"apan\": 20948,\n    \"ĠJub\": 20949,\n    \"ĠHuckabee\": 20950,\n    \"string\": 20951,\n    \"stay\": 20952,\n    \"Ġsustaining\": 20953,\n    \"VM\": 20954,\n    \"Ġpriv\": 20955,\n    \"Ġclos\": 20956,\n    \"Ġdownloaded\": 20957,\n    \"ĠIv\": 20958,\n    \"Ġfinanced\": 20959,\n    \"ĠSao\": 20960,\n    \"ĠEverett\": 20961,\n    \"rene\": 20962,\n    \"ĠWo\": 20963,\n    \"ĠPiet\": 20964,\n    \"Ġengulfed\": 20965,\n    \"Ġexiting\": 20966,\n    \"uni\": 20967,\n    \"horn\": 20968,\n    \"Ġgrav\": 20969,\n    \"ection\": 20970,\n    \"Ġdrainage\": 20971,\n    \"Ġfuelled\": 20972,\n    \"Ġorganizational\": 20973,\n    \"bike\": 20974,\n    \"ĠAreas\": 20975,\n    \"Ġpoliceman\": 20976,\n    \"ĠFirm\": 20977,\n    \"ĠSlide\": 20978,\n    \"Ġrand\": 20979,\n    \"ĠJedi\": 20980,\n    \"Ge\": 20981,\n    \"really\": 20982,\n    \"Manchester\": 20983,\n    \"ĠWise\": 20984,\n    \"parent\": 20985,\n    \"Ġlad\": 20986,\n    \"Ġurine\": 20987,\n    \"ĠColombian\": 20988,\n    \"geon\": 20989,\n    \"Ġ1961\": 20990,\n    \"Mania\": 20991,\n    \"Ġgraph\": 20992,\n    \"Ġcod\": 20993,\n    \"fred\": 20994,\n    \"Ġeffic\": 20995,\n    \"ĠGateway\": 20996,\n    \"asket\": 20997,\n    \"Ġdiminished\": 20998,\n    \"Mass\": 20999,\n    \"Ġ205\": 21000,\n    \"Long\": 21001,\n    \"Ġgranddaughter\": 21002,\n    \"Ġshining\": 21003,\n    \"Semitic\": 21004,\n    \"Ġarising\": 21005,\n    \"Ġ330\": 21006,\n    \"ĠDU\": 21007,\n    \"ĠZah\": 21008,\n    \"Ġexclusion\": 21009,\n    \"ĠClaus\": 21010,\n    \"Ġven\": 21011,\n    \"oine\": 21012,\n    \"ĠAPI\": 21013,\n    \"reve\": 21014,\n    \"Ġmilitias\": 21015,\n    \"Ġfro\": 21016,\n    \"Ġwaved\": 21017,\n    \"ĠLuxembourg\": 21018,\n    \"Ġdiamonds\": 21019,\n    \"Ġstabilize\": 21020,\n    \"Ġqueue\": 21021,\n    \"ĠSponsor\": 21022,\n    \"Ġeldest\": 21023,\n    \"ĠLud\": 21024,\n    \"Ġwasting\": 21025,\n    \"Ġdimension\": 21026,\n    \"Ġmotorcycles\": 21027,\n    \"ucker\": 21028,\n    \"ĠTav\": 21029,\n    \"Ġsupremacy\": 21030,\n    \"Take\": 21031,\n    \"ĠCPU\": 21032,\n    \"cup\": 21033,\n    \"Ġdisregard\": 21034,\n    \"Ġenvelope\": 21035,\n    \"ĠCah\": 21036,\n    \"Ġproposes\": 21037,\n    \"ĠMaurice\": 21038,\n    \"Ġhobby\": 21039,\n    \"Ġharmon\": 21040,\n    \"Ġribbon\": 21041,\n    \"ĠOrigin\": 21042,\n    \"Ġbuilders\": 21043,\n    \"Ġconj\": 21044,\n    \"Ġcert\": 21045,\n    \"eat\": 21046,\n    \"ĠStern\": 21047,\n    \"ulia\": 21048,\n    \"vals\": 21049,\n    \"cling\": 21050,\n    \"Ġprovocative\": 21051,\n    \"Ġsofter\": 21052,\n    \"Ġ1948\": 21053,\n    \"Ġremod\": 21054,\n    \"ĠSob\": 21055,\n    \"Ġmaxim\": 21056,\n    \"Ġblueprint\": 21057,\n    \"oit\": 21058,\n    \"ĠGarner\": 21059,\n    \"Ġfibre\": 21060,\n    \"search\": 21061,\n    \"ĠWrite\": 21062,\n    \"270\": 21063,\n    \"Ġclergy\": 21064,\n    \"ĠPalo\": 21065,\n    \"obile\": 21066,\n    \"Mad\": 21067,\n    \"Ġclown\": 21068,\n    \"Ġtraced\": 21069,\n    \"280\": 21070,\n    \"ĠAlberto\": 21071,\n    \"Ġdrums\": 21072,\n    \"ĠFridays\": 21073,\n    \"ĠStrat\": 21074,\n    \"stated\": 21075,\n    \"ĠStevenson\": 21076,\n    \"Pr\": 21077,\n    \"Ġboasted\": 21078,\n    \"ĠBrees\": 21079,\n    \"ĠDonn\": 21080,\n    \"ĠMaya\": 21081,\n    \"Ġrelieve\": 21082,\n    \"Ġ1080\": 21083,\n    \"Ġcheapest\": 21084,\n    \"Ġuniquely\": 21085,\n    \"Ġjungle\": 21086,\n    \"Ġprevalence\": 21087,\n    \"Ġoutfield\": 21088,\n    \"ĠMaps\": 21089,\n    \"Ġaccustomed\": 21090,\n    \"pac\": 21091,\n    \"Ġcombinations\": 21092,\n    \"ĠSoros\": 21093,\n    \"stad\": 21094,\n    \"Ġket\": 21095,\n    \"Ġdisgusting\": 21096,\n    \"ĠOFF\": 21097,\n    \"irs\": 21098,\n    \"Ġbiased\": 21099,\n    \"Ġpaved\": 21100,\n    \"iked\": 21101,\n    \"utterstock\": 21102,\n    \"ocal\": 21103,\n    \"Ġsurround\": 21104,\n    \"ĠGuang\": 21105,\n    \"Ġspear\": 21106,\n    \"ĠBellev\": 21107,\n    \"ortun\": 21108,\n    \"Rec\": 21109,\n    \"acho\": 21110,\n    \"Ġfrightening\": 21111,\n    \"Ġtyres\": 21112,\n    \"normal\": 21113,\n    \"ĠYan\": 21114,\n    \"ĠWarsaw\": 21115,\n    \"ĠBod\": 21116,\n    \"ourse\": 21117,\n    \"199\": 21118,\n    \"Ver\": 21119,\n    \"erent\": 21120,\n    \"Ġsparkling\": 21121,\n    \"Ġchanting\": 21122,\n    \"Ġ1945\": 21123,\n    \"Ġturbo\": 21124,\n    \"Ġhazards\": 21125,\n    \"IRE\": 21126,\n    \"ĠRonnie\": 21127,\n    \"Ġsplitting\": 21128,\n    \"ĠMatte\": 21129,\n    \"roph\": 21130,\n    \"Ġtended\": 21131,\n    \"Ġvandalism\": 21132,\n    \"alis\": 21133,\n    \"SY\": 21134,\n    \"Ġoversaw\": 21135,\n    \"Happy\": 21136,\n    \"ĠTC\": 21137,\n    \"275\": 21138,\n    \"Ġeco\": 21139,\n    \"ĠKers\": 21140,\n    \"Ġextensions\": 21141,\n    \"ĠFlan\": 21142,\n    \"ĠCena\": 21143,\n    \"ĠDowns\": 21144,\n    \"Ġdrummer\": 21145,\n    \"Ġawaited\": 21146,\n    \"ĠACL\": 21147,\n    \"Ġlegends\": 21148,\n    \"ĠRollins\": 21149,\n    \"hend\": 21150,\n    \"Ġdeparting\": 21151,\n    \"Ġtha\": 21152,\n    \"Ġunre\": 21153,\n    \".(\": 21154,\n    \"Ġfaded\": 21155,\n    \"Ġretirees\": 21156,\n    \"vid\": 21157,\n    \"Ġentrants\": 21158,\n    \"ĠStella\": 21159,\n    \"arer\": 21160,\n    \"Ġteaspoon\": 21161,\n    \"ĠSheridan\": 21162,\n    \"irc\": 21163,\n    \"ĠRelief\": 21164,\n    \"ĠButt\": 21165,\n    \"Ġris\": 21166,\n    \"Ġundermined\": 21167,\n    \"Ġsunk\": 21168,\n    \"Sam\": 21169,\n    \"kamp\": 21170,\n    \"riot\": 21171,\n    \"rating\": 21172,\n    \"Ġclubhouse\": 21173,\n    \"Ġpeaked\": 21174,\n    \"ĠSki\": 21175,\n    \"Ġairstrikes\": 21176,\n    \"Ġconce\": 21177,\n    \"ĠCPR\": 21178,\n    \"Ġesp\": 21179,\n    \"ĠWave\": 21180,\n    \"ĠColiseum\": 21181,\n    \"outheastern\": 21182,\n    \"Ġtrou\": 21183,\n    \"Ġfeather\": 21184,\n    \"ĠSoy\": 21185,\n    \"ĠBihar\": 21186,\n    \"Ġintervened\": 21187,\n    \"mits\": 21188,\n    \"colored\": 21189,\n    \"330\": 21190,\n    \"Ġprocession\": 21191,\n    \"apeake\": 21192,\n    \"itÃ©\": 21193,\n    \"riel\": 21194,\n    \"Ġmart\": 21195,\n    \"afer\": 21196,\n    \"ĠGuests\": 21197,\n    \"ĠPie\": 21198,\n    \"Ġshiny\": 21199,\n    \"ĠSixers\": 21200,\n    \"ĠRoads\": 21201,\n    \"Ġkicker\": 21202,\n    \"ĠCrimes\": 21203,\n    \"Ġfrontier\": 21204,\n    \"ansen\": 21205,\n    \"November\": 21206,\n    \"smith\": 21207,\n    \"ĠLaun\": 21208,\n    \"fried\": 21209,\n    \"weet\": 21210,\n    \"ĠGrass\": 21211,\n    \"Ġsanitation\": 21212,\n    \"ĠEat\": 21213,\n    \"ĠParts\": 21214,\n    \"ĠTun\": 21215,\n    \"amar\": 21216,\n    \"ĠJupiter\": 21217,\n    \"ĠFS\": 21218,\n    \"Ġunsc\": 21219,\n    \"ĠDone\": 21220,\n    \"Ġleveraging\": 21221,\n    \"Ġtucked\": 21222,\n    \"Ġineffective\": 21223,\n    \"Ġriots\": 21224,\n    \"wei\": 21225,\n    \"ĠAttend\": 21226,\n    \"Ġpertaining\": 21227,\n    \"amen\": 21228,\n    \"monds\": 21229,\n    \"Ġmism\": 21230,\n    \"serious\": 21231,\n    \"ĠViol\": 21232,\n    \"rous\": 21233,\n    \"Ġ129\": 21234,\n    \"uebl\": 21235,\n    \"umption\": 21236,\n    \"tri\": 21237,\n    \"ĠWedding\": 21238,\n    \"Ġtroopers\": 21239,\n    \"ĠTHR\": 21240,\n    \"olving\": 21241,\n    \"leys\": 21242,\n    \"Med\": 21243,\n    \"Ġseparatists\": 21244,\n    \"Ġimper\": 21245,\n    \"ĠFrontier\": 21246,\n    \"Ġwhit\": 21247,\n    \"ĠMutual\": 21248,\n    \"Ġrested\": 21249,\n    \"Ġunhealthy\": 21250,\n    \"gang\": 21251,\n    \"Ġresearching\": 21252,\n    \"ĠColonel\": 21253,\n    \"Ġaffordability\": 21254,\n    \"ĠRegarding\": 21255,\n    \"ĠWend\": 21256,\n    \"ĠMellon\": 21257,\n    \"Ġplots\": 21258,\n    \"Ġcanal\": 21259,\n    \"PER\": 21260,\n    \"ĠShopping\": 21261,\n    \"etry\": 21262,\n    \"Ġoccurrence\": 21263,\n    \"Ġgraves\": 21264,\n    \"BF\": 21265,\n    \"ĠKau\": 21266,\n    \"indust\": 21267,\n    \"Ġbeard\": 21268,\n    \"uate\": 21269,\n    \"ĠProdu\": 21270,\n    \"ĠSomali\": 21271,\n    \"ishers\": 21272,\n    \"ĠFell\": 21273,\n    \"ĠHutchinson\": 21274,\n    \"Ġhust\": 21275,\n    \"Ġillustration\": 21276,\n    \"Ġ//\": 21277,\n    \"Ġsharks\": 21278,\n    \"Ġcoincidence\": 21279,\n    \"Ġremake\": 21280,\n    \"Ġmural\": 21281,\n    \"course\": 21282,\n    \"ĠSultan\": 21283,\n    \"arse\": 21284,\n    \"Ġwhip\": 21285,\n    \"ĠPodcast\": 21286,\n    \"Ġtightened\": 21287,\n    \"Ġdenim\": 21288,\n    \"Ġlandfill\": 21289,\n    \"future\": 21290,\n    \"Ġsuperv\": 21291,\n    \"Hand\": 21292,\n    \"Ġpraising\": 21293,\n    \"ĠEly\": 21294,\n    \"ĠGust\": 21295,\n    \"ĠMayer\": 21296,\n    \"Ġorphan\": 21297,\n    \"Ġrepaired\": 21298,\n    \"ĠPir\": 21299,\n    \"Ġspiral\": 21300,\n    \"husband\": 21301,\n    \"ienne\": 21302,\n    \"iatric\": 21303,\n    \"Ġmarriages\": 21304,\n    \"Ġhorn\": 21305,\n    \"plain\": 21306,\n    \"ĠLum\": 21307,\n    \"ession\": 21308,\n    \"ĠFeatures\": 21309,\n    \"Ġbreakup\": 21310,\n    \"Ġentrepreneurship\": 21311,\n    \"rina\": 21312,\n    \"Ġembargo\": 21313,\n    \"Ġcapitalism\": 21314,\n    \"ĠMinor\": 21315,\n    \"Ġpromo\": 21316,\n    \"Ġexcel\": 21317,\n    \"Japan\": 21318,\n    \"Ġworsening\": 21319,\n    \"Ġstumbled\": 21320,\n    \"Ġpins\": 21321,\n    \"Ġswipe\": 21322,\n    \"Ġexile\": 21323,\n    \"Ġseparatist\": 21324,\n    \"ĠBian\": 21325,\n    \"Ġrelocation\": 21326,\n    \"Ġcommanders\": 21327,\n    \"Ġdowned\": 21328,\n    \"Ġblogger\": 21329,\n    \"packed\": 21330,\n    \"ĠSchn\": 21331,\n    \"Ġwaterfront\": 21332,\n    \"ĠYus\": 21333,\n    \"Ġnegotiator\": 21334,\n    \"Ġfavourable\": 21335,\n    \"Iran\": 21336,\n    \"oulder\": 21337,\n    \"Ġcance\": 21338,\n    \"Ġvind\": 21339,\n    \"angel\": 21340,\n    \"Ġauthenticity\": 21341,\n    \"Ġtowel\": 21342,\n    \"bul\": 21343,\n    \"ĠNeville\": 21344,\n    \"ĠBuddhist\": 21345,\n    \"fields\": 21346,\n    \"uly\": 21347,\n    \"Ġniece\": 21348,\n    \"Ġcorrections\": 21349,\n    \"Ġassignments\": 21350,\n    \"ĠSchl\": 21351,\n    \"Ġharmed\": 21352,\n    \"375\": 21353,\n    \"Ġwounding\": 21354,\n    \"ĠPosition\": 21355,\n    \"Ġsupermarkets\": 21356,\n    \"Ġdisclosures\": 21357,\n    \"Ġ185\": 21358,\n    \"esp\": 21359,\n    \"ĠMcCull\": 21360,\n    \"ĠMale\": 21361,\n    \"Ġsailors\": 21362,\n    \"mis\": 21363,\n    \"ĠSophia\": 21364,\n    \"Ġunfolded\": 21365,\n    \"owell\": 21366,\n    \"ĠScarborough\": 21367,\n    \"Ġentrepreneurial\": 21368,\n    \"118\": 21369,\n    \"ogy\": 21370,\n    \"ĠLikewise\": 21371,\n    \"Ġswung\": 21372,\n    \"Ġdrawings\": 21373,\n    \"Ġdrafting\": 21374,\n    \"ĠSimple\": 21375,\n    \"ĠFilip\": 21376,\n    \"arf\": 21377,\n    \"Ġfade\": 21378,\n    \"Ġmerged\": 21379,\n    \"ĠLeaf\": 21380,\n    \"sun\": 21381,\n    \"Ġflame\": 21382,\n    \"Ġindices\": 21383,\n    \"ĠCreate\": 21384,\n    \"ittle\": 21385,\n    \"ĠWer\": 21386,\n    \"ĠMond\": 21387,\n    \"Ġoz\": 21388,\n    \"ĠSmoke\": 21389,\n    \"Ġreplies\": 21390,\n    \"ĠDH\": 21391,\n    \"Ġjud\": 21392,\n    \"ĠFalk\": 21393,\n    \"Ġ---\": 21394,\n    \"Ġconstitutes\": 21395,\n    \"Ġtheat\": 21396,\n    \"119\": 21397,\n    \"Ġintermediate\": 21398,\n    \"vill\": 21399,\n    \"ĠGow\": 21400,\n    \"ĠHut\": 21401,\n    \"ł\": 21402,\n    \"155\": 21403,\n    \"ĠLocated\": 21404,\n    \"ĠDoor\": 21405,\n    \"Ġsliced\": 21406,\n    \"aru\": 21407,\n    \"Ġtearing\": 21408,\n    \"defense\": 21409,\n    \"oyer\": 21410,\n    \"Ġprodu\": 21411,\n    \"Ġseminar\": 21412,\n    \"asso\": 21413,\n    \"Ġpeaks\": 21414,\n    \"Ġconceal\": 21415,\n    \"Ġcrypto\": 21416,\n    \"Ġsetbacks\": 21417,\n    \"ĠAlicia\": 21418,\n    \"ĠFAA\": 21419,\n    \"Ġcontinuity\": 21420,\n    \"Ġcatastrophe\": 21421,\n    \"Ġbeg\": 21422,\n    \"Ġscales\": 21423,\n    \"apixel\": 21424,\n    \"Ġsalon\": 21425,\n    \"Ste\": 21426,\n    \"Ġlesbian\": 21427,\n    \"Ġanticip\": 21428,\n    \"Ġutilization\": 21429,\n    \"Ġchickens\": 21430,\n    \"Ġspinal\": 21431,\n    \"ĠJuliet\": 21432,\n    \"ĠFas\": 21433,\n    \"prising\": 21434,\n    \"ĠSalvation\": 21435,\n    \"Ġ138\": 21436,\n    \"Ġutilizing\": 21437,\n    \"âĢ¢\": 21438,\n    \"ĠMessenger\": 21439,\n    \"Ġrebellion\": 21440,\n    \"ĠAlexand\": 21441,\n    \"Ġinsect\": 21442,\n    \"Ġribs\": 21443,\n    \"ĠBild\": 21444,\n    \"Ġmonopoly\": 21445,\n    \"Queen\": 21446,\n    \"ĠNaples\": 21447,\n    \"Ġ133\": 21448,\n    \"Ġhourly\": 21449,\n    \"Ġego\": 21450,\n    \"Ġpencil\": 21451,\n    \"ĠPew\": 21452,\n    \"Ġdesirable\": 21453,\n    \"vant\": 21454,\n    \"ĠLAT\": 21455,\n    \"Ġperpet\": 21456,\n    \"lish\": 21457,\n    \"Ġ201\": 21458,\n    \"Ġdistances\": 21459,\n    \"Ġdistressed\": 21460,\n    \"Work\": 21461,\n    \"Ġtattoos\": 21462,\n    \"Ġstereotypes\": 21463,\n    \"istent\": 21464,\n    \"ĠCoral\": 21465,\n    \"fo\": 21466,\n    \"Ġpayable\": 21467,\n    \"Ġakin\": 21468,\n    \"ĠLis\": 21469,\n    \"ĠFinding\": 21470,\n    \"Ġsusceptible\": 21471,\n    \"ĠKiw\": 21472,\n    \"Ġforgiveness\": 21473,\n    \"ĠMoment\": 21474,\n    \"ĠDmitry\": 21475,\n    \"Ġrenov\": 21476,\n    \"Ġquint\": 21477,\n    \"ĠWaterloo\": 21478,\n    \"ĠReality\": 21479,\n    \"Ġstray\": 21480,\n    \"ĠBeaver\": 21481,\n    \"Ġbites\": 21482,\n    \"Ġelusive\": 21483,\n    \"Ġvirtue\": 21484,\n    \"Ġgadgets\": 21485,\n    \"Ġlandslide\": 21486,\n    \"ĠHealthy\": 21487,\n    \"Ġpits\": 21488,\n    \"Donnell\": 21489,\n    \"Ġirony\": 21490,\n    \"uct\": 21491,\n    \"Ġpractitioners\": 21492,\n    \"Ġreck\": 21493,\n    \"governmental\": 21494,\n    \"Ġatomic\": 21495,\n    \"Ġmotiv\": 21496,\n    \"Ġpolic\": 21497,\n    \"Ġcommunicated\": 21498,\n    \"ĠHS\": 21499,\n    \"Ġcriticize\": 21500,\n    \"Ġsynerg\": 21501,\n    \"Del\": 21502,\n    \"ĠRoe\": 21503,\n    \"Ġinspirational\": 21504,\n    \"ĠWarning\": 21505,\n    \"pel\": 21506,\n    \"Ġnevertheless\": 21507,\n    \"Ġdespair\": 21508,\n    \"Ġ(.\": 21509,\n    \"Ġfearing\": 21510,\n    \"Ġgrop\": 21511,\n    \"tree\": 21512,\n    \"Ġtrusts\": 21513,\n    \"Ġinterviewing\": 21514,\n    \"amic\": 21515,\n    \"Ġscor\": 21516,\n    \"ject\": 21517,\n    \"Another\": 21518,\n    \"pose\": 21519,\n    \"Ġdepicted\": 21520,\n    \"ĠPhotography\": 21521,\n    \"ĠLenovo\": 21522,\n    \"ĠEpic\": 21523,\n    \"ĠBoot\": 21524,\n    \"GI\": 21525,\n    \"enses\": 21526,\n    \"Class\": 21527,\n    \"arity\": 21528,\n    \"Ġservicing\": 21529,\n    \"ĠHann\": 21530,\n    \"Ġawe\": 21531,\n    \"Ġoverdoses\": 21532,\n    \"ĠFinnish\": 21533,\n    \"Ġpav\": 21534,\n    \"ĠPCs\": 21535,\n    \"SEC\": 21536,\n    \"ĠStro\": 21537,\n    \"Ġattracts\": 21538,\n    \"Ġapprehended\": 21539,\n    \"128\": 21540,\n    \"Ġunstable\": 21541,\n    \"ĠOutdoor\": 21542,\n    \"Ġcloth\": 21543,\n    \"ĠUlster\": 21544,\n    \"Ġvisually\": 21545,\n    \"Ġsculpt\": 21546,\n    \"Ġsufficiently\": 21547,\n    \"ĠKendrick\": 21548,\n    \"Ġengages\": 21549,\n    \"Ġknives\": 21550,\n    \"ĠGut\": 21551,\n    \"Ġarbit\": 21552,\n    \"osition\": 21553,\n    \"Ġemoji\": 21554,\n    \"Ġpinpoint\": 21555,\n    \"Ġremembering\": 21556,\n    \"rence\": 21557,\n    \"ĠVish\": 21558,\n    \"Ġimproperly\": 21559,\n    \"Ġranc\": 21560,\n    \"Ġupstream\": 21561,\n    \"Ġcheckpoint\": 21562,\n    \"Ġrash\": 21563,\n    \"eson\": 21564,\n    \"Ġtoes\": 21565,\n    \"260\": 21566,\n    \"Ġinvalid\": 21567,\n    \"Ġonions\": 21568,\n    \"Ġlashed\": 21569,\n    \"ĠDong\": 21570,\n    \"Ġprovisional\": 21571,\n    \"ĠFern\": 21572,\n    \"Ġirresponsible\": 21573,\n    \"actively\": 21574,\n    \"ĠKnown\": 21575,\n    \"Ġben\": 21576,\n    \"ĠBlank\": 21577,\n    \"Ġactresses\": 21578,\n    \"paying\": 21579,\n    \"Ġsyrup\": 21580,\n    \"isman\": 21581,\n    \"Ġeducating\": 21582,\n    \"Sunday\": 21583,\n    \"ifiable\": 21584,\n    \"Post\": 21585,\n    \"Ġcalculation\": 21586,\n    \"Ġhesitate\": 21587,\n    \"ĠIncreasing\": 21588,\n    \"Ġreeling\": 21589,\n    \"ĠDairy\": 21590,\n    \"ensing\": 21591,\n    \"Ġmaternity\": 21592,\n    \"Ø\": 21593,\n    \"./\": 21594,\n    \"ĠElm\": 21595,\n    \"Ġweddings\": 21596,\n    \"ĠYard\": 21597,\n    \"117\": 21598,\n    \"ĠRocket\": 21599,\n    \"OF\": 21600,\n    \"Ġtreasurer\": 21601,\n    \"Ġrattled\": 21602,\n    \"ĠDrop\": 21603,\n    \"arel\": 21604,\n    \"ĠFulton\": 21605,\n    \"ĠGiant\": 21606,\n    \"ĠFloor\": 21607,\n    \"Jet\": 21608,\n    \"ikk\": 21609,\n    \"ĠBucs\": 21610,\n    \"ostics\": 21611,\n    \"reme\": 21612,\n    \"ĠRouse\": 21613,\n    \"Ġdeliber\": 21614,\n    \"ĠEle\": 21615,\n    \"Ġconducts\": 21616,\n    \"ĠBlog\": 21617,\n    \"connected\": 21618,\n    \"Ġprayed\": 21619,\n    \"Ġcolourful\": 21620,\n    \"Ġaugmented\": 21621,\n    \"Ġbatted\": 21622,\n    \"Ġrelevance\": 21623,\n    \"ĠRomanian\": 21624,\n    \"acqu\": 21625,\n    \"ĠChel\": 21626,\n    \"ĠClo\": 21627,\n    \"ĠGraves\": 21628,\n    \"Ġchees\": 21629,\n    \"ĠGibbs\": 21630,\n    \"CLE\": 21631,\n    \"Ġfertility\": 21632,\n    \"Ġambul\": 21633,\n    \"Ġspecs\": 21634,\n    \"ĠIRA\": 21635,\n    \"ĠBooth\": 21636,\n    \"ithe\": 21637,\n    \"ĠPlayoff\": 21638,\n    \"ammed\": 21639,\n    \"Ġcollaborating\": 21640,\n    \"Ġlunar\": 21641,\n    \"Ġconfronting\": 21642,\n    \"Ġattribute\": 21643,\n    \"King\": 21644,\n    \"riz\": 21645,\n    \"Ġcasualty\": 21646,\n    \"acia\": 21647,\n    \"waters\": 21648,\n    \"Ġpaving\": 21649,\n    \"Ġcaregivers\": 21650,\n    \"nor\": 21651,\n    \"Ġreacting\": 21652,\n    \"ĠHash\": 21653,\n    \"Ġsqueezed\": 21654,\n    \"Ġexert\": 21655,\n    \"ĠMichele\": 21656,\n    \"ĠConc\": 21657,\n    \"ĠHep\": 21658,\n    \"Ġsewage\": 21659,\n    \"wart\": 21660,\n    \"GY\": 21661,\n    \"Ġdiscourage\": 21662,\n    \"ĠFir\": 21663,\n    \"Ġtextile\": 21664,\n    \"ĠSpice\": 21665,\n    \"ĠFah\": 21666,\n    \"Ġcomplainant\": 21667,\n    \"Ġinstinct\": 21668,\n    \"camp\": 21669,\n    \"ĠEdison\": 21670,\n    \"ĠVIDEOS\": 21671,\n    \"LM\": 21672,\n    \"ĠSands\": 21673,\n    \"About\": 21674,\n    \"Ġdisk\": 21675,\n    \"brid\": 21676,\n    \"Ġmuted\": 21677,\n    \"ACC\": 21678,\n    \"Ġwre\": 21679,\n    \"event\": 21680,\n    \"Ġicons\": 21681,\n    \"Express\": 21682,\n    \"udes\": 21683,\n    \"ĠBeatles\": 21684,\n    \"color\": 21685,\n    \"ĠHaas\": 21686,\n    \"ĠWolfe\": 21687,\n    \"ĠYOUR\": 21688,\n    \"Ġaccessibility\": 21689,\n    \"ĠCornwall\": 21690,\n    \"Ġing\": 21691,\n    \"Ġatrocities\": 21692,\n    \"weather\": 21693,\n    \"ĠDominion\": 21694,\n    \"ĠMIL\": 21695,\n    \"ĠLara\": 21696,\n    \"Ġunravel\": 21697,\n    \"Ġmaneuver\": 21698,\n    \"Ġfoam\": 21699,\n    \"ribe\": 21700,\n    \"CI\": 21701,\n    \"Ġcandles\": 21702,\n    \"acs\": 21703,\n    \")(\": 21704,\n    \"coon\": 21705,\n    \"ĠPurple\": 21706,\n    \"ĠGovernors\": 21707,\n    \"ĠKeystone\": 21708,\n    \"ĠYuk\": 21709,\n    \"file\": 21710,\n    \"Ġviol\": 21711,\n    \"gery\": 21712,\n    \"370\": 21713,\n    \"train\": 21714,\n    \"Ġgunshots\": 21715,\n    \"olin\": 21716,\n    \"Ġviruses\": 21717,\n    \"ĠTex\": 21718,\n    \"hours\": 21719,\n    \"Ġprev\": 21720,\n    \"ĠRid\": 21721,\n    \"ected\": 21722,\n    \"ĠVog\": 21723,\n    \"riers\": 21724,\n    \"Ġmurdering\": 21725,\n    \"ĠIz\": 21726,\n    \"Ġdeliberations\": 21727,\n    \"arming\": 21728,\n    \"unda\": 21729,\n    \"Ġrink\": 21730,\n    \"ĠDrugs\": 21731,\n    \"idered\": 21732,\n    \"Ġforge\": 21733,\n    \"Ġexpansive\": 21734,\n    \"VIEW\": 21735,\n    \"ĠBots\": 21736,\n    \"Ġswitches\": 21737,\n    \"KO\": 21738,\n    \"atten\": 21739,\n    \"Ġvariants\": 21740,\n    \"ĠVirtual\": 21741,\n    \"ĠCoch\": 21742,\n    \"yon\": 21743,\n    \"ĠKai\": 21744,\n    \"Ġbullied\": 21745,\n    \"iday\": 21746,\n    \"version\": 21747,\n    \"Ġlib\": 21748,\n    \"ĠCec\": 21749,\n    \"igated\": 21750,\n    \"ĠTRUMP\": 21751,\n    \"ĠPod\": 21752,\n    \"Ġtoppled\": 21753,\n    \"Ġeyeing\": 21754,\n    \"ĠPatients\": 21755,\n    \"techn\": 21756,\n    \"Ġhampered\": 21757,\n    \"Ġavert\": 21758,\n    \"ĠScheme\": 21759,\n    \"ĠCorm\": 21760,\n    \"Ġpony\": 21761,\n    \"Ġzoom\": 21762,\n    \"abo\": 21763,\n    \"Ġsleeves\": 21764,\n    \"lane\": 21765,\n    \"ĠLester\": 21766,\n    \"ĠDane\": 21767,\n    \"Ġcough\": 21768,\n    \"Ġsignings\": 21769,\n    \"HER\": 21770,\n    \"Ġsibling\": 21771,\n    \"Ġredemption\": 21772,\n    \"Ġstockp\": 21773,\n    \"ĠAlgeria\": 21774,\n    \"Ġpadd\": 21775,\n    \"ĠBrenda\": 21776,\n    \"uchi\": 21777,\n    \"Ġtransporting\": 21778,\n    \"Ġspeculative\": 21779,\n    \"ĠSek\": 21780,\n    \"abal\": 21781,\n    \"Ġshipment\": 21782,\n    \"oker\": 21783,\n    \"Ġwarranty\": 21784,\n    \"atan\": 21785,\n    \"Ġblister\": 21786,\n    \"ĠCelebration\": 21787,\n    \"Ġwal\": 21788,\n    \"Ġlac\": 21789,\n    \"Ġprioritize\": 21790,\n    \"ression\": 21791,\n    \"BP\": 21792,\n    \"Ġcollaborated\": 21793,\n    \"ĠNewsletter\": 21794,\n    \"ĠDamian\": 21795,\n    \"ĠResidential\": 21796,\n    \"Ġgra\": 21797,\n    \"Ġfeasible\": 21798,\n    \"ĠCrest\": 21799,\n    \"ĠBean\": 21800,\n    \"ĠSturgeon\": 21801,\n    \"ĠTale\": 21802,\n    \"ĠContin\": 21803,\n    \"ĠMush\": 21804,\n    \"Ġrocking\": 21805,\n    \"ĠMane\": 21806,\n    \"ĠHumane\": 21807,\n    \"resistant\": 21808,\n    \"ĠFra\": 21809,\n    \"highest\": 21810,\n    \"fts\": 21811,\n    \"Ġamassed\": 21812,\n    \"ĠPavilion\": 21813,\n    \"ĠSkin\": 21814,\n    \"Ġunfold\": 21815,\n    \"Ġresur\": 21816,\n    \"ĠPET\": 21817,\n    \"model\": 21818,\n    \"Ġemploying\": 21819,\n    \"Ġrude\": 21820,\n    \"Ġirrelevant\": 21821,\n    \"angu\": 21822,\n    \"Page\": 21823,\n    \"PN\": 21824,\n    \"igator\": 21825,\n    \"ĠReb\": 21826,\n    \"ĠArrest\": 21827,\n    \"ĠGund\": 21828,\n    \"Ġmalls\": 21829,\n    \"zhen\": 21830,\n    \"wed\": 21831,\n    \"Ġdaring\": 21832,\n    \"Ġfactual\": 21833,\n    \"ĠGent\": 21834,\n    \"Ġinforming\": 21835,\n    \"ĠStri\": 21836,\n    \"ĠLounge\": 21837,\n    \".]\": 21838,\n    \"ĠTribunal\": 21839,\n    \"ĠMoines\": 21840,\n    \"Ġshadows\": 21841,\n    \"generated\": 21842,\n    \"fulness\": 21843,\n    \"Ġheartfelt\": 21844,\n    \"ĠLivingston\": 21845,\n    \"ĠClerk\": 21846,\n    \"Ġnationalism\": 21847,\n    \"ĠMiche\": 21848,\n    \"balls\": 21849,\n    \"anos\": 21850,\n    \"agle\": 21851,\n    \"Ġprejudice\": 21852,\n    \"Ġevenly\": 21853,\n    \"Ġswearing\": 21854,\n    \"Ġexits\": 21855,\n    \"Ġcondemning\": 21856,\n    \"Ġvanilla\": 21857,\n    \"club\": 21858,\n    \"ĠFunding\": 21859,\n    \"ĠDover\": 21860,\n    \"Ġhots\": 21861,\n    \"Ġfres\": 21862,\n    \"Ġgoodness\": 21863,\n    \"ĠMcKay\": 21864,\n    \"Ġbulls\": 21865,\n    \"avia\": 21866,\n    \"129\": 21867,\n    \"Ġ1947\": 21868,\n    \"Ġdefamation\": 21869,\n    \"ĠMoran\": 21870,\n    \"irms\": 21871,\n    \"ĠFitz\": 21872,\n    \"ĠRossi\": 21873,\n    \"urated\": 21874,\n    \"Ġvariation\": 21875,\n    \"ĠBauer\": 21876,\n    \"ĠSchro\": 21877,\n    \"Ġcolony\": 21878,\n    \"ĠParliamentary\": 21879,\n    \"ikan\": 21880,\n    \"Ġstirring\": 21881,\n    \"ĠSheldon\": 21882,\n    \"Ġaccessory\": 21883,\n    \"ĠUtilities\": 21884,\n    \"Ġnab\": 21885,\n    \"Ġpract\": 21886,\n    \"Ġherein\": 21887,\n    \"ĠRole\": 21888,\n    \"ĠMant\": 21889,\n    \"Ġpharm\": 21890,\n    \"Ġ215\": 21891,\n    \"ĠNGO\": 21892,\n    \"ĠAnything\": 21893,\n    \"ĠMacedonia\": 21894,\n    \"Ġbree\": 21895,\n    \"ĠWTO\": 21896,\n    \"Chicago\": 21897,\n    \"ĠProtect\": 21898,\n    \"quarters\": 21899,\n    \"ĠGrassley\": 21900,\n    \"ĠInteractive\": 21901,\n    \"ĠInterview\": 21902,\n    \"Ġ550\": 21903,\n    \"Ġastronauts\": 21904,\n    \"Ġfreak\": 21905,\n    \"ĠIntegrated\": 21906,\n    \"Ġindict\": 21907,\n    \"Ġgenerators\": 21908,\n    \"acio\": 21909,\n    \"Kevin\": 21910,\n    \"Ġvaccination\": 21911,\n    \"Ġblockade\": 21912,\n    \"ĠSons\": 21913,\n    \"Ġcapita\": 21914,\n    \"ĠAnita\": 21915,\n    \"ĠExport\": 21916,\n    \"ĠNex\": 21917,\n    \"ĠAram\": 21918,\n    \"Ġzinc\": 21919,\n    \"Ġrevamped\": 21920,\n    \"Ġselective\": 21921,\n    \"Ġmanipulate\": 21922,\n    \"ĠBedford\": 21923,\n    \"ĠBattery\": 21924,\n    \"Ġqualifiers\": 21925,\n    \"lean\": 21926,\n    \"Ġscrew\": 21927,\n    \"film\": 21928,\n    \"ror\": 21929,\n    \"ĠEllison\": 21930,\n    \"ombo\": 21931,\n    \"ĠOst\": 21932,\n    \"165\": 21933,\n    \"Ġslaves\": 21934,\n    \"ĠPayton\": 21935,\n    \"Ġbarg\": 21936,\n    \"Ġrugged\": 21937,\n    \"ĠWinn\": 21938,\n    \"ĠHammer\": 21939,\n    \"ĠUPS\": 21940,\n    \"Euro\": 21941,\n    \"Ġunfamiliar\": 21942,\n    \"Ġdistract\": 21943,\n    \"Ġbuffer\": 21944,\n    \"ledge\": 21945,\n    \"Ġtrunk\": 21946,\n    \"Ġ320\": 21947,\n    \"122\": 21948,\n    \"Ġdilemma\": 21949,\n    \"Ġpra\": 21950,\n    \"Ġutmost\": 21951,\n    \"Ġcampaigners\": 21952,\n    \"icular\": 21953,\n    \"eful\": 21954,\n    \"ï¿½\": 21955,\n    \"ĠHQ\": 21956,\n    \"neau\": 21957,\n    \"Ġsir\": 21958,\n    \"test\": 21959,\n    \"Company\": 21960,\n    \"Ġrescind\": 21961,\n    \"ardon\": 21962,\n    \"MG\": 21963,\n    \"Gov\": 21964,\n    \"ĠRaz\": 21965,\n    \"Ġrod\": 21966,\n    \"fed\": 21967,\n    \"Ġpsych\": 21968,\n    \"Ġunin\": 21969,\n    \"ĠArbor\": 21970,\n    \"Ġnewcomer\": 21971,\n    \"ĠEdwin\": 21972,\n    \"raising\": 21973,\n    \"quist\": 21974,\n    \"Ġdiscoveries\": 21975,\n    \"Steve\": 21976,\n    \"Ġscramble\": 21977,\n    \"js\": 21978,\n    \"Ġacoustic\": 21979,\n    \"Ġdeterioration\": 21980,\n    \"Ġobserving\": 21981,\n    \"ĠWinning\": 21982,\n    \"ĠSaban\": 21983,\n    \"idy\": 21984,\n    \"Ġoverd\": 21985,\n    \"Ġscouting\": 21986,\n    \"Ġpunitive\": 21987,\n    \"ĠShelter\": 21988,\n    \"Ġmocked\": 21989,\n    \"Ġdreamed\": 21990,\n    \"Ġinvaluable\": 21991,\n    \"LP\": 21992,\n    \"standard\": 21993,\n    \"Ġrecounted\": 21994,\n    \"ĠSabres\": 21995,\n    \"points\": 21996,\n    \"Ġfringe\": 21997,\n    \"ĠBarker\": 21998,\n    \"alian\": 21999,\n    \"ĠPROV\": 22000,\n    \"Ġcartel\": 22001,\n    \"Ġovercrowd\": 22002,\n    \"tain\": 22003,\n    \"Year\": 22004,\n    \"ĠWelfare\": 22005,\n    \"ĠChr\": 22006,\n    \"Ġintroduces\": 22007,\n    \"ĠDoing\": 22008,\n    \"ĠGlover\": 22009,\n    \"Ġdeteriorating\": 22010,\n    \"Par\": 22011,\n    \"Ġattendant\": 22012,\n    \"ĠMold\": 22013,\n    \"ĠFlying\": 22014,\n    \"ovan\": 22015,\n    \"Ġoptimize\": 22016,\n    \"Ġchapters\": 22017,\n    \"Ġdull\": 22018,\n    \"gay\": 22019,\n    \"ĠATP\": 22020,\n    \"ĠKah\": 22021,\n    \"ainer\": 22022,\n    \"feet\": 22023,\n    \"Ġjoking\": 22024,\n    \"Ġdisadvantage\": 22025,\n    \"Rep\": 22026,\n    \"Ġtwisted\": 22027,\n    \"Ġslain\": 22028,\n    \"Ġcomprise\": 22029,\n    \"Ġrestricting\": 22030,\n    \"Ġdispos\": 22031,\n    \"Ġshaky\": 22032,\n    \"Ġembattled\": 22033,\n    \"owe\": 22034,\n    \"conscious\": 22035,\n    \"oken\": 22036,\n    \"Ġmistaken\": 22037,\n    \"ĠDra\": 22038,\n    \"Ġreservoir\": 22039,\n    \"Ġspate\": 22040,\n    \"Scott\": 22041,\n    \"avor\": 22042,\n    \"Ġqual\": 22043,\n    \"amel\": 22044,\n    \"hunt\": 22045,\n    \"ĠChevy\": 22046,\n    \"Ġclaw\": 22047,\n    \"Ġwitch\": 22048,\n    \"ĠZimmerman\": 22049,\n    \"arium\": 22050,\n    \"Ġrubbish\": 22051,\n    \"Ġstrings\": 22052,\n    \"Ġdoc\": 22053,\n    \"Ġplaque\": 22054,\n    \"ĠCyr\": 22055,\n    \"Ġflourish\": 22056,\n    \"Ġworthwhile\": 22057,\n    \"Ġbanners\": 22058,\n    \"ĠLemon\": 22059,\n    \"ĠRainbow\": 22060,\n    \"Ġconsisted\": 22061,\n    \"ĠHOW\": 22062,\n    \"Ñ\": 22063,\n    \"Ġblogs\": 22064,\n    \"CLUS\": 22065,\n    \"eely\": 22066,\n    \"Ġbeast\": 22067,\n    \"ĠMai\": 22068,\n    \"Ġhostility\": 22069,\n    \"eros\": 22070,\n    \"Ġforeseeable\": 22071,\n    \"ĠCorker\": 22072,\n    \"ĠWEEK\": 22073,\n    \"visors\": 22074,\n    \"ressive\": 22075,\n    \"ĠViktor\": 22076,\n    \"Ġbureaucracy\": 22077,\n    \"Ġ256\": 22078,\n    \"ĠFeel\": 22079,\n    \"ĠAdventure\": 22080,\n    \"Ġefficacy\": 22081,\n    \"ĠInstitution\": 22082,\n    \"ĠHarbaugh\": 22083,\n    \"ĠPractice\": 22084,\n    \"ĠChristianity\": 22085,\n    \"Thanks\": 22086,\n    \"Ġfridge\": 22087,\n    \"idel\": 22088,\n    \"Ġeff\": 22089,\n    \"Ġvein\": 22090,\n    \"terms\": 22091,\n    \"Ġignorance\": 22092,\n    \"Ġscream\": 22093,\n    \"Ġwit\": 22094,\n    \"ĠRousse\": 22095,\n    \"ĠWillow\": 22096,\n    \"Ġhallway\": 22097,\n    \"former\": 22098,\n    \"Ġshooters\": 22099,\n    \"ĠReporting\": 22100,\n    \"Ġgal\": 22101,\n    \"Ġsavvy\": 22102,\n    \"rand\": 22103,\n    \"Ġremed\": 22104,\n    \"ĠBaron\": 22105,\n    \"inar\": 22106,\n    \"Ġseizures\": 22107,\n    \"ĠThorn\": 22108,\n    \"ĠProtesters\": 22109,\n    \"ĠRevolutionary\": 22110,\n    \"think\": 22111,\n    \"ĠCabrera\": 22112,\n    \"Four\": 22113,\n    \"ĠRudd\": 22114,\n    \"Ġprost\": 22115,\n    \"ĠBottom\": 22116,\n    \"Port\": 22117,\n    \"nas\": 22118,\n    \"ifax\": 22119,\n    \"Wire\": 22120,\n    \"Ġtokens\": 22121,\n    \"antis\": 22122,\n    \"ĠSOU\": 22123,\n    \"ĠMilk\": 22124,\n    \"asters\": 22125,\n    \"Ġshrimp\": 22126,\n    \"Ġcakes\": 22127,\n    \"blue\": 22128,\n    \"ifty\": 22129,\n    \"View\": 22130,\n    \"adium\": 22131,\n    \"fen\": 22132,\n    \"zyk\": 22133,\n    \"ĠEmil\": 22134,\n    \"Ġdismay\": 22135,\n    \"Ġtilt\": 22136,\n    \"aska\": 22137,\n    \"Young\": 22138,\n    \"Ġpredators\": 22139,\n    \"Ġovershadowed\": 22140,\n    \"mitt\": 22141,\n    \"ĠSemin\": 22142,\n    \"ĠSchiff\": 22143,\n    \"ĠClarkson\": 22144,\n    \"212\": 22145,\n    \"210\": 22146,\n    \"Ġvanished\": 22147,\n    \"Ġmesh\": 22148,\n    \"ĠBurnett\": 22149,\n    \"ĠMent\": 22150,\n    \"ĠBlind\": 22151,\n    \"ĠPatriot\": 22152,\n    \"ĠVil\": 22153,\n    \"Ġflick\": 22154,\n    \"ĠTowns\": 22155,\n    \"ĠWhites\": 22156,\n    \"Ġspice\": 22157,\n    \"ĠMode\": 22158,\n    \"Ġnominate\": 22159,\n    \"Ġwrest\": 22160,\n    \"ĠAshes\": 22161,\n    \"Ġrows\": 22162,\n    \"ĠClint\": 22163,\n    \"Ġgentleman\": 22164,\n    \"utan\": 22165,\n    \"athlon\": 22166,\n    \"ĠIntermediate\": 22167,\n    \"hews\": 22168,\n    \"Ġoffended\": 22169,\n    \"ĠPaige\": 22170,\n    \"ĠFinch\": 22171,\n    \"ĠAboriginal\": 22172,\n    \"positive\": 22173,\n    \"Stop\": 22174,\n    \"Ġrenting\": 22175,\n    \"Ġ[âĢ¦]\": 22176,\n    \"ĠHert\": 22177,\n    \"Ġvegetation\": 22178,\n    \"apes\": 22179,\n    \"ĠCanon\": 22180,\n    \"appa\": 22181,\n    \"Ġabst\": 22182,\n    \"ĠKatz\": 22183,\n    \"Ġsurfing\": 22184,\n    \"aghan\": 22185,\n    \"ĠPresidency\": 22186,\n    \"Ġscaling\": 22187,\n    \"ĠSas\": 22188,\n    \"Ġpeanut\": 22189,\n    \"Ġrecommending\": 22190,\n    \"cious\": 22191,\n    \"endez\": 22192,\n    \"eker\": 22193,\n    \"ĠKamp\": 22194,\n    \"Ġsitcom\": 22195,\n    \"Ġcrust\": 22196,\n    \"women\": 22197,\n    \"ĠJes\": 22198,\n    \"ĠWhe\": 22199,\n    \"ĠWarwick\": 22200,\n    \"Ġepit\": 22201,\n    \"ĠAlc\": 22202,\n    \"Ġdictate\": 22203,\n    \"ĠSPORTS\": 22204,\n    \"ĠLanguage\": 22205,\n    \"Ġindicative\": 22206,\n    \"ĠMacDonald\": 22207,\n    \"Ġreorgan\": 22208,\n    \"Ġ`\": 22209,\n    \"ARS\": 22210,\n    \"Ġliberation\": 22211,\n    \"Ġbless\": 22212,\n    \"Ġreflective\": 22213,\n    \"Ġà¤\": 22214,\n    \"Ġdesires\": 22215,\n    \"ĠHank\": 22216,\n    \"ĠLaunch\": 22217,\n    \"Ġrotating\": 22218,\n    \"ĠStones\": 22219,\n    \"Ġcoordinating\": 22220,\n    \"ĠZeit\": 22221,\n    \"Ġskepticism\": 22222,\n    \"ĠAlam\": 22223,\n    \"ĠTrout\": 22224,\n    \"ĠSMS\": 22225,\n    \"ĠCrescent\": 22226,\n    \"ĠTeacher\": 22227,\n    \"Ġfury\": 22228,\n    \"Ġeyebrows\": 22229,\n    \"onga\": 22230,\n    \"ĠPilot\": 22231,\n    \"ĠRutherford\": 22232,\n    \"Ġinterstate\": 22233,\n    \"established\": 22234,\n    \"Ġbaggage\": 22235,\n    \"Ġ131\": 22236,\n    \"riks\": 22237,\n    \"mil\": 22238,\n    \"Ġneon\": 22239,\n    \"Ġqueer\": 22240,\n    \"ourced\": 22241,\n    \"ĠKash\": 22242,\n    \"ĠEleven\": 22243,\n    \"illes\": 22244,\n    \"ĠOpportun\": 22245,\n    \"Ġstre\": 22246,\n    \"Washington\": 22247,\n    \"ĠDifferent\": 22248,\n    \"Ġexempl\": 22249,\n    \"Ġboarded\": 22250,\n    \"Ġrogue\": 22251,\n    \"ĠDNC\": 22252,\n    \"rone\": 22253,\n    \"Ġreversing\": 22254,\n    \"nine\": 22255,\n    \"ĠIvory\": 22256,\n    \"itating\": 22257,\n    \"uve\": 22258,\n    \"Ġfracture\": 22259,\n    \"255\": 22260,\n    \"ĠAssessment\": 22261,\n    \"Ġsubjective\": 22262,\n    \"Ġfluct\": 22263,\n    \"ĠJaguar\": 22264,\n    \"Ġstride\": 22265,\n    \"Ġreapp\": 22266,\n    \"ĠGrow\": 22267,\n    \"against\": 22268,\n    \"ĠMedina\": 22269,\n    \"scenes\": 22270,\n    \"ĠNieto\": 22271,\n    \"Ġsou\": 22272,\n    \"ĠFleming\": 22273,\n    \"Ġnarcotics\": 22274,\n    \"ĠBere\": 22275,\n    \"ĠBub\": 22276,\n    \"ĠAck\": 22277,\n    \"Ġvinyl\": 22278,\n    \"ĠCopy\": 22279,\n    \"ĠGarland\": 22280,\n    \"ĠDuty\": 22281,\n    \"Ġinn\": 22282,\n    \"Ġmerchant\": 22283,\n    \"Ġactivate\": 22284,\n    \"Ġglowing\": 22285,\n    \"ettle\": 22286,\n    \"ĠBran\": 22287,\n    \"Ġsilk\": 22288,\n    \"anco\": 22289,\n    \"TL\": 22290,\n    \"ĠFurn\": 22291,\n    \"Ġwithheld\": 22292,\n    \"Ġpulse\": 22293,\n    \"ĠGU\": 22294,\n    \"BUS\": 22295,\n    \"ĠHyper\": 22296,\n    \"Ġpicnic\": 22297,\n    \"Ġpositives\": 22298,\n    \"ĠParamount\": 22299,\n    \"Ġ737\": 22300,\n    \"Ġenlisted\": 22301,\n    \"ĠValerie\": 22302,\n    \"false\": 22303,\n    \"ĠChocolate\": 22304,\n    \"ĠSTAR\": 22305,\n    \"Ġdescended\": 22306,\n    \"Ġtasty\": 22307,\n    \"ĠDaesh\": 22308,\n    \"ĠNed\": 22309,\n    \"Ġcomplimentary\": 22310,\n    \"Ġdepicting\": 22311,\n    \"ĠHavana\": 22312,\n    \"college\": 22313,\n    \"Ġtraces\": 22314,\n    \"Ġundue\": 22315,\n    \"ĠSisters\": 22316,\n    \"aum\": 22317,\n    \"ĠCourier\": 22318,\n    \"ĠOng\": 22319,\n    \"ĠSparks\": 22320,\n    \"ongs\": 22321,\n    \"ĠYong\": 22322,\n    \"URR\": 22323,\n    \"los\": 22324,\n    \"Ġhorsepower\": 22325,\n    \"confidence\": 22326,\n    \"ĠPett\": 22327,\n    \"ĠMeasure\": 22328,\n    \"Ġmarches\": 22329,\n    \"zig\": 22330,\n    \"ĠTOR\": 22331,\n    \"Ġexported\": 22332,\n    \"ĠRak\": 22333,\n    \"ĠInvestigations\": 22334,\n    \"Ġterminate\": 22335,\n    \"ĠTian\": 22336,\n    \"Ġmasters\": 22337,\n    \"ĠDS\": 22338,\n    \"Ġoutraged\": 22339,\n    \"ĠCups\": 22340,\n    \"ĠWeir\": 22341,\n    \"exec\": 22342,\n    \"Ġjourneys\": 22343,\n    \"Ġabide\": 22344,\n    \"Ġavail\": 22345,\n    \"ĠStreets\": 22346,\n    \"Ġfixes\": 22347,\n    \"Ġcocoa\": 22348,\n    \"Ġabundant\": 22349,\n    \"Ġhubs\": 22350,\n    \"mort\": 22351,\n    \"Ġrobberies\": 22352,\n    \"ĠBark\": 22353,\n    \"Ġprecautions\": 22354,\n    \"Ġhammered\": 22355,\n    \"ometric\": 22356,\n    \"mith\": 22357,\n    \"ĠMcCann\": 22358,\n    \"ĠJaw\": 22359,\n    \"ĠQuest\": 22360,\n    \"ĠMcF\": 22361,\n    \"Ġlob\": 22362,\n    \"Ġlegalized\": 22363,\n    \"Ġquirky\": 22364,\n    \"Ġtrailers\": 22365,\n    \"ĠIndividual\": 22366,\n    \"Ġcumulative\": 22367,\n    \"Ġenlarge\": 22368,\n    \"Ġconvoy\": 22369,\n    \"olen\": 22370,\n    \"got\": 22371,\n    \"landers\": 22372,\n    \"Ġscanner\": 22373,\n    \"Ġscans\": 22374,\n    \"ĠEg\": 22375,\n    \"prof\": 22376,\n    \"Ġhosp\": 22377,\n    \"ĠColo\": 22378,\n    \"Ġerr\": 22379,\n    \"Ġdeval\": 22380,\n    \"ĠUsually\": 22381,\n    \"Ġbul\": 22382,\n    \"ummy\": 22383,\n    \"Ġtandem\": 22384,\n    \"occupied\": 22385,\n    \"Ġmandates\": 22386,\n    \"ĠSwim\": 22387,\n    \"121\": 22388,\n    \"ussed\": 22389,\n    \"EF\": 22390,\n    \"Ġfries\": 22391,\n    \"Until\": 22392,\n    \"rc\": 22393,\n    \"Ġbadge\": 22394,\n    \"Ġstrips\": 22395,\n    \"Ġmagnet\": 22396,\n    \"Ġarchive\": 22397,\n    \"stan\": 22398,\n    \"ĠDeadline\": 22399,\n    \"Ġdisposable\": 22400,\n    \"Ġbob\": 22401,\n    \"Ġnorthwestern\": 22402,\n    \"Jul\": 22403,\n    \"ĠSAL\": 22404,\n    \"Ġinfluencing\": 22405,\n    \"Ġdevil\": 22406,\n    \"ĠEllie\": 22407,\n    \"cms\": 22408,\n    \"ingo\": 22409,\n    \"888\": 22410,\n    \"Ġcosmetic\": 22411,\n    \"Also\": 22412,\n    \"Ġyacht\": 22413,\n    \"Ġlazy\": 22414,\n    \"Ġmerc\": 22415,\n    \"Ġabsorbed\": 22416,\n    \"harm\": 22417,\n    \"116\": 22418,\n    \"Ġsubpoena\": 22419,\n    \"Ġcounters\": 22420,\n    \"ĠLori\": 22421,\n    \"Ġrandomly\": 22422,\n    \"nea\": 22423,\n    \"waves\": 22424,\n    \"Ġrelie\": 22425,\n    \"ĠKiss\": 22426,\n    \"Ġchassis\": 22427,\n    \"Ġbakery\": 22428,\n    \"Images\": 22429,\n    \"ĠHolden\": 22430,\n    \"Ġamazed\": 22431,\n    \"Ġalignment\": 22432,\n    \"ĠPowers\": 22433,\n    \"Ġlabelled\": 22434,\n    \"Ġstaunch\": 22435,\n    \"Ġsignaling\": 22436,\n    \"Ġsenate\": 22437,\n    \"Ġunconventional\": 22438,\n    \"ĠAlternative\": 22439,\n    \"Ġambassadors\": 22440,\n    \"ĠVPN\": 22441,\n    \"atics\": 22442,\n    \"Ġmosquito\": 22443,\n    \"ĠScholarship\": 22444,\n    \"Ġhelpless\": 22445,\n    \"alone\": 22446,\n    \"ZA\": 22447,\n    \"chel\": 22448,\n    \"Ġconstituencies\": 22449,\n    \"ĠCafÃ©\": 22450,\n    \"Ġhatch\": 22451,\n    \"ĠRupert\": 22452,\n    \"Ġrendering\": 22453,\n    \"Ġreinstated\": 22454,\n    \"Ġinterval\": 22455,\n    \"Texas\": 22456,\n    \"ĠAHL\": 22457,\n    \"February\": 22458,\n    \"review\": 22459,\n    \"Ġgle\": 22460,\n    \"Ġfals\": 22461,\n    \"Ġmarkers\": 22462,\n    \"Ġgovernmental\": 22463,\n    \"ĠPos\": 22464,\n    \"Ġarose\": 22465,\n    \"every\": 22466,\n    \"Ġrulings\": 22467,\n    \"obar\": 22468,\n    \"Govern\": 22469,\n    \"gren\": 22470,\n    \"isan\": 22471,\n    \"Ġmarketed\": 22472,\n    \"Click\": 22473,\n    \"Ġord\": 22474,\n    \"Ġballoons\": 22475,\n    \"asers\": 22476,\n    \"ĠHorton\": 22477,\n    \"pub\": 22478,\n    \"ĠAerospace\": 22479,\n    \"Ġflank\": 22480,\n    \"Ġmolecular\": 22481,\n    \"bour\": 22482,\n    \"nuts\": 22483,\n    \"Ġalliances\": 22484,\n    \"Ġbenchmarks\": 22485,\n    \"ocate\": 22486,\n    \"stadt\": 22487,\n    \"ĠGoodwin\": 22488,\n    \"lap\": 22489,\n    \"ĠFactors\": 22490,\n    \"Never\": 22491,\n    \"ĠNem\": 22492,\n    \"Ġroadside\": 22493,\n    \"orth\": 22494,\n    \"Ġexhibited\": 22495,\n    \"ĠPearce\": 22496,\n    \"ĠOlsen\": 22497,\n    \"Ġpostal\": 22498,\n    \"ĠLiberation\": 22499,\n    \"reen\": 22500,\n    \"mary\": 22501,\n    \"Ġropes\": 22502,\n    \"Ġlarg\": 22503,\n    \"Ġgob\": 22504,\n    \"boys\": 22505,\n    \"ĠSax\": 22506,\n    \"Ġreimbursement\": 22507,\n    \"ĠVie\": 22508,\n    \"ĠCatholics\": 22509,\n    \"ĠMartial\": 22510,\n    \"Ġpremiered\": 22511,\n    \"Ġawaits\": 22512,\n    \"ĠUnderstanding\": 22513,\n    \"ĠBelarus\": 22514,\n    \"ĠVor\": 22515,\n    \"ogi\": 22516,\n    \"iaz\": 22517,\n    \"Ġvictorious\": 22518,\n    \"Ġancestors\": 22519,\n    \"Ġwreckage\": 22520,\n    \"Ġoppression\": 22521,\n    \"ĠChildhood\": 22522,\n    \"Ġwidth\": 22523,\n    \"ĠPlymouth\": 22524,\n    \"ĠFifty\": 22525,\n    \"Ġoccupancy\": 22526,\n    \"etts\": 22527,\n    \"ĠFiscal\": 22528,\n    \"lifting\": 22529,\n    \"ĠTraditional\": 22530,\n    \"Ġnostalgia\": 22531,\n    \"Law\": 22532,\n    \"Ġlays\": 22533,\n    \"Ġarresting\": 22534,\n    \"Ġanticipating\": 22535,\n    \"Ġinsults\": 22536,\n    \"ĠExtension\": 22537,\n    \"Ġgenerator\": 22538,\n    \"ummer\": 22539,\n    \"Ġageing\": 22540,\n    \"Ġbouncing\": 22541,\n    \"ember\": 22542,\n    \"ĠWAR\": 22543,\n    \"ĠNico\": 22544,\n    \"ĠWow\": 22545,\n    \"ĠRaven\": 22546,\n    \"flower\": 22547,\n    \"ĠCrim\": 22548,\n    \"bh\": 22549,\n    \"Ġundo\": 22550,\n    \"Ġburgers\": 22551,\n    \"roud\": 22552,\n    \"ĠAtkinson\": 22553,\n    \"ĠYEAR\": 22554,\n    \"Ġpoorer\": 22555,\n    \"ICA\": 22556,\n    \"ĠSchedule\": 22557,\n    \"Ġstronghold\": 22558,\n    \"ĠMillennium\": 22559,\n    \"Ġ###\": 22560,\n    \"ilda\": 22561,\n    \"ĠGH\": 22562,\n    \"Ġupscale\": 22563,\n    \"aldi\": 22564,\n    \"ĠResolution\": 22565,\n    \"Ġswelling\": 22566,\n    \"Ġgrieving\": 22567,\n    \"ĠNile\": 22568,\n    \"ĠTig\": 22569,\n    \"ERY\": 22570,\n    \"ooth\": 22571,\n    \"BALL\": 22572,\n    \"Ġballet\": 22573,\n    \"Ġbucks\": 22574,\n    \"ĠUV\": 22575,\n    \"akin\": 22576,\n    \"Ġchilling\": 22577,\n    \"Ġdatabases\": 22578,\n    \"ĠGD\": 22579,\n    \"section\": 22580,\n    \"Ġhires\": 22581,\n    \"Ġmul\": 22582,\n    \"Ġsen\": 22583,\n    \"ĠTownsend\": 22584,\n    \"Ġinspected\": 22585,\n    \"ilic\": 22586,\n    \"Ġdiscriminatory\": 22587,\n    \"fol\": 22588,\n    \"Ġalcoholic\": 22589,\n    \"ĠHoff\": 22590,\n    \"Carl\": 22591,\n    \"Ġvicinity\": 22592,\n    \"lein\": 22593,\n    \"ĠEco\": 22594,\n    \"ĠGovern\": 22595,\n    \"Ġsecrecy\": 22596,\n    \"aned\": 22597,\n    \"ĠDUP\": 22598,\n    \"Ġ570\": 22599,\n    \"Ġsow\": 22600,\n    \"Ġstalls\": 22601,\n    \"Ġinsulting\": 22602,\n    \"ĠDT\": 22603,\n    \"Ġinforms\": 22604,\n    \"fitting\": 22605,\n    \"ĠDepending\": 22606,\n    \"ĠMelanie\": 22607,\n    \"ĠThom\": 22608,\n    \"path\": 22609,\n    \"Ġadmired\": 22610,\n    \"Peter\": 22611,\n    \"idents\": 22612,\n    \"ielding\": 22613,\n    \"ĠShanahan\": 22614,\n    \"TD\": 22615,\n    \"Things\": 22616,\n    \"sn\": 22617,\n    \"Ġconstituted\": 22618,\n    \"Ġ137\": 22619,\n    \"Ġderailed\": 22620,\n    \"ĠBonnie\": 22621,\n    \"Ġgraffiti\": 22622,\n    \"Ġearnest\": 22623,\n    \"Ġcompliant\": 22624,\n    \"blown\": 22625,\n    \"Ġalle\": 22626,\n    \"prise\": 22627,\n    \"Ġfocal\": 22628,\n    \"Ġgentlemen\": 22629,\n    \"ĠTalks\": 22630,\n    \"Ġpassports\": 22631,\n    \"Ġdeprived\": 22632,\n    \"Ġdude\": 22633,\n    \"ĠNath\": 22634,\n    \"Ġgoverned\": 22635,\n    \"Ġsac\": 22636,\n    \"Ġcastle\": 22637,\n    \"qv\": 22638,\n    \"Ġtolerated\": 22639,\n    \"ĠSci\": 22640,\n    \"close\": 22641,\n    \"ĠDynamics\": 22642,\n    \"Ġflashing\": 22643,\n    \"yk\": 22644,\n    \"ĠConsolid\": 22645,\n    \"Ġinherently\": 22646,\n    \"ĠForrest\": 22647,\n    \"Gene\": 22648,\n    \"Public\": 22649,\n    \"Ġloser\": 22650,\n    \"runners\": 22651,\n    \"Ġprudent\": 22652,\n    \"Ġpioneering\": 22653,\n    \"ĠHowe\": 22654,\n    \"ĠButter\": 22655,\n    \"ĠArabian\": 22656,\n    \"acha\": 22657,\n    \"ĠBBQ\": 22658,\n    \"ĠMineral\": 22659,\n    \"Ġdestiny\": 22660,\n    \"Ġretrieve\": 22661,\n    \"ĠBav\": 22662,\n    \"reth\": 22663,\n    \"oby\": 22664,\n    \"ĠGrid\": 22665,\n    \"Ġgrievances\": 22666,\n    \"ĠTips\": 22667,\n    \"Ġadamant\": 22668,\n    \"Ġdiets\": 22669,\n    \"Ġmilestones\": 22670,\n    \"Ġcollects\": 22671,\n    \"ĠLaboratories\": 22672,\n    \"ĠWC\": 22673,\n    \"Ġpostp\": 22674,\n    \"Ġdams\": 22675,\n    \"ĠOEM\": 22676,\n    \"Ġrumor\": 22677,\n    \"Ġlocking\": 22678,\n    \"Ġemission\": 22679,\n    \"Ġqueries\": 22680,\n    \"Jones\": 22681,\n    \"Ġlang\": 22682,\n    \"ĠAcqu\": 22683,\n    \"ĠMedium\": 22684,\n    \"ĠTreasurer\": 22685,\n    \"Sept\": 22686,\n    \"FB\": 22687,\n    \"Ġintegrating\": 22688,\n    \"Ġbolstered\": 22689,\n    \"Ġincorporating\": 22690,\n    \"encers\": 22691,\n    \"Ġirregularities\": 22692,\n    \"Ġnom\": 22693,\n    \"iod\": 22694,\n    \"ĠAi\": 22695,\n    \"Ġsor\": 22696,\n    \"anked\": 22697,\n    \"Ġrehears\": 22698,\n    \"fig\": 22699,\n    \"ĠBug\": 22700,\n    \"hoff\": 22701,\n    \"Ġtrooper\": 22702,\n    \"Ġgalaxy\": 22703,\n    \"amon\": 22704,\n    \"ĠAtlas\": 22705,\n    \"Ġsolicit\": 22706,\n    \"Ġsings\": 22707,\n    \"ĠInstructions\": 22708,\n    \"ĠMig\": 22709,\n    \"thinking\": 22710,\n    \"ĠCostco\": 22711,\n    \"Ġbreasts\": 22712,\n    \"Ġportraits\": 22713,\n    \"ĠCock\": 22714,\n    \"Ġsubscriptions\": 22715,\n    \"Ġpine\": 22716,\n    \"Ġhaunted\": 22717,\n    \"ĠMED\": 22718,\n    \"eer\": 22719,\n    \"ega\": 22720,\n    \"ĠZa\": 22721,\n    \"ENN\": 22722,\n    \"ĠWinners\": 22723,\n    \"aith\": 22724,\n    \"safe\": 22725,\n    \"Ġ143\": 22726,\n    \"ĠWeston\": 22727,\n    \"ĠLansing\": 22728,\n    \"ĠLaurel\": 22729,\n    \"ocrat\": 22730,\n    \"ograph\": 22731,\n    \"Ġmatchups\": 22732,\n    \"ĠFriend\": 22733,\n    \"Ġdigest\": 22734,\n    \"Ġdimensions\": 22735,\n    \"azing\": 22736,\n    \"Ġtipping\": 22737,\n    \"Ġenrich\": 22738,\n    \"gart\": 22739,\n    \"argo\": 22740,\n    \"Ġoutbreaks\": 22741,\n    \"Ġsalvage\": 22742,\n    \"ĠErica\": 22743,\n    \"Ġmodules\": 22744,\n    \"ĠPDF\": 22745,\n    \"ĠGoods\": 22746,\n    \"oots\": 22747,\n    \"2011\": 22748,\n    \"Ġinterrupt\": 22749,\n    \"Ġradi\": 22750,\n    \"ĠSimone\": 22751,\n    \"vell\": 22752,\n    \"ĠSV\": 22753,\n    \"extremely\": 22754,\n    \"Ġstadiums\": 22755,\n    \"ĠRox\": 22756,\n    \"Ġconflicting\": 22757,\n    \"Ġyouthful\": 22758,\n    \"ĠUM\": 22759,\n    \"series\": 22760,\n    \"Ġded\": 22761,\n    \"Ġfielding\": 22762,\n    \"Pre\": 22763,\n    \"itled\": 22764,\n    \"Ġstreamed\": 22765,\n    \"Ġapprentices\": 22766,\n    \"ĠAlec\": 22767,\n    \"ĠGap\": 22768,\n    \"ĠPrem\": 22769,\n    \"Ġleased\": 22770,\n    \"Ġdeepening\": 22771,\n    \"Ġbounds\": 22772,\n    \"Ġrethink\": 22773,\n    \"ĠVoting\": 22774,\n    \"ĠScha\": 22775,\n    \"blood\": 22776,\n    \"ĠReeves\": 22777,\n    \"Ġbells\": 22778,\n    \"Ġcollector\": 22779,\n    \"ĠCrimson\": 22780,\n    \"ĠWheat\": 22781,\n    \"207\": 22782,\n    \"ĠHB\": 22783,\n    \"ĠBCC\": 22784,\n    \"Ġsync\": 22785,\n    \"ĠAnders\": 22786,\n    \"Ġthanking\": 22787,\n    \"Ġlayoffs\": 22788,\n    \"Ġfoolish\": 22789,\n    \"Ġcustod\": 22790,\n    \"Ġelephants\": 22791,\n    \"Ġcorrelation\": 22792,\n    \"ĠHarding\": 22793,\n    \"ĠGPU\": 22794,\n    \"ĠBarnett\": 22795,\n    \"Ġol\": 22796,\n    \"Ġalarms\": 22797,\n    \"Ġfluctuations\": 22798,\n    \"shop\": 22799,\n    \"Ġcommentators\": 22800,\n    \"ĠAlpine\": 22801,\n    \"Ġmur\": 22802,\n    \"Ġbiotech\": 22803,\n    \"Ġunlocked\": 22804,\n    \"ouri\": 22805,\n    \"roe\": 22806,\n    \"ĠPayment\": 22807,\n    \"ĠPOL\": 22808,\n    \"ĠGuest\": 22809,\n    \"Ġphrases\": 22810,\n    \"ĠBuilt\": 22811,\n    \"erves\": 22812,\n    \"Ġnutritional\": 22813,\n    \"205\": 22814,\n    \"ourage\": 22815,\n    \"Related\": 22816,\n    \"Come\": 22817,\n    \"ĠSAT\": 22818,\n    \"Ġgatherings\": 22819,\n    \"Ġsquads\": 22820,\n    \"Ġorganising\": 22821,\n    \"Ġministerial\": 22822,\n    \"Ġkilomet\": 22823,\n    \"ĠJump\": 22824,\n    \"ĠStrength\": 22825,\n    \"ĠFerr\": 22826,\n    \"Ġillustrated\": 22827,\n    \"ĠOber\": 22828,\n    \"Ġextrad\": 22829,\n    \"Ġlimitation\": 22830,\n    \"idis\": 22831,\n    \"ĠMonths\": 22832,\n    \"ifts\": 22833,\n    \"Ġmotives\": 22834,\n    \"Ġmaternal\": 22835,\n    \"Ġbait\": 22836,\n    \"Ġadversity\": 22837,\n    \"Twitter\": 22838,\n    \"ĠUni\": 22839,\n    \"Ġgrappling\": 22840,\n    \"Ġbowls\": 22841,\n    \"ĠHib\": 22842,\n    \"ĠCopenhagen\": 22843,\n    \"Ġsergeant\": 22844,\n    \"Ġintro\": 22845,\n    \"Ġscrambled\": 22846,\n    \"ĠExc\": 22847,\n    \"Ġshowcases\": 22848,\n    \"Ġplotting\": 22849,\n    \"Ġsym\": 22850,\n    \"ĠNah\": 22851,\n    \"berries\": 22852,\n    \"itching\": 22853,\n    \"conn\": 22854,\n    \"istle\": 22855,\n    \"ĠBeginning\": 22856,\n    \"asley\": 22857,\n    \"ĠMeadow\": 22858,\n    \"ĠCra\": 22859,\n    \"Ġsupremacist\": 22860,\n    \"Ġsweats\": 22861,\n    \"production\": 22862,\n    \"innon\": 22863,\n    \"ovo\": 22864,\n    \"Ġscept\": 22865,\n    \"Ġdrowning\": 22866,\n    \"ĠEh\": 22867,\n    \"Ġdecorations\": 22868,\n    \"Ġsympathetic\": 22869,\n    \"raction\": 22870,\n    \"Ġ195\": 22871,\n    \"ripp\": 22872,\n    \"ĠNotice\": 22873,\n    \"charging\": 22874,\n    \"ĠDIY\": 22875,\n    \"ĠJin\": 22876,\n    \"Ġskinny\": 22877,\n    \"Ġmaj\": 22878,\n    \"Ġwhisk\": 22879,\n    \"Ġcongreg\": 22880,\n    \"RAL\": 22881,\n    \"Ġvolley\": 22882,\n    \"Ġestablishments\": 22883,\n    \"Ġcite\": 22884,\n    \"Miss\": 22885,\n    \"Int\": 22886,\n    \"iola\": 22887,\n    \"ĠBare\": 22888,\n    \"KING\": 22889,\n    \"ools\": 22890,\n    \"private\": 22891,\n    \"Ġflaw\": 22892,\n    \"Ġwires\": 22893,\n    \"Ġideals\": 22894,\n    \"oub\": 22895,\n    \"Ġ\\\"'\": 22896,\n    \"ĠCompet\": 22897,\n    \"ĠStatements\": 22898,\n    \"ĠHDR\": 22899,\n    \"rm\": 22900,\n    \"Ġbegging\": 22901,\n    \"uffs\": 22902,\n    \"Ġdispatch\": 22903,\n    \"Ġskipped\": 22904,\n    \"Ġlabs\": 22905,\n    \"hawks\": 22906,\n    \"Ġexpl\": 22907,\n    \"Ġpatriotic\": 22908,\n    \"ussions\": 22909,\n    \"Ġportrayal\": 22910,\n    \"ĠBudapest\": 22911,\n    \"ĠCod\": 22912,\n    \"Ġextingu\": 22913,\n    \"smart\": 22914,\n    \"Ġburdens\": 22915,\n    \"ĠDrama\": 22916,\n    \"Ġaltitude\": 22917,\n    \"Ġpursuant\": 22918,\n    \"à¥\": 22919,\n    \"atari\": 22920,\n    \"cot\": 22921,\n    \"Ġhotline\": 22922,\n    \"ooters\": 22923,\n    \"ĠRolls\": 22924,\n    \"Ġjeopardy\": 22925,\n    \"oids\": 22926,\n    \"Ġpageant\": 22927,\n    \"149\": 22928,\n    \"Ġdistinguish\": 22929,\n    \"support\": 22930,\n    \"ĠHighlands\": 22931,\n    \"ĠErnst\": 22932,\n    \"ĠHole\": 22933,\n    \"pering\": 22934,\n    \"ĠHasan\": 22935,\n    \"Ġrece\": 22936,\n    \"Ġirregular\": 22937,\n    \"Ġdisturbed\": 22938,\n    \"Ġcoupon\": 22939,\n    \"ĠElijah\": 22940,\n    \"oise\": 22941,\n    \"Ġfriendships\": 22942,\n    \"girlfriend\": 22943,\n    \"Ġrampage\": 22944,\n    \"arers\": 22945,\n    \"Ġdispens\": 22946,\n    \"assion\": 22947,\n    \"Ġtentative\": 22948,\n    \"ĠExploration\": 22949,\n    \"fashioned\": 22950,\n    \"ĠInstit\": 22951,\n    \"Ġthemed\": 22952,\n    \"ĠKurdistan\": 22953,\n    \"ĠCAL\": 22954,\n    \"ĠSweeney\": 22955,\n    \"Ġransom\": 22956,\n    \"Ġstamps\": 22957,\n    \"ĠSchwe\": 22958,\n    \"ĠLucia\": 22959,\n    \"124\": 22960,\n    \"omore\": 22961,\n    \"Ġmotivate\": 22962,\n    \"ĠWorcester\": 22963,\n    \"wald\": 22964,\n    \"CAR\": 22965,\n    \"iken\": 22966,\n    \"andro\": 22967,\n    \"ffic\": 22968,\n    \"ĠRehab\": 22969,\n    \"Ġgrou\": 22970,\n    \"Ġcontrollers\": 22971,\n    \"ĠHai\": 22972,\n    \"nz\": 22973,\n    \"Ġartillery\": 22974,\n    \"ĠMish\": 22975,\n    \"Ġregistry\": 22976,\n    \"Ġfrontman\": 22977,\n    \"ĠCharg\": 22978,\n    \"orneys\": 22979,\n    \"ĠPRESS\": 22980,\n    \"Ġperceptions\": 22981,\n    \"ĠMcGee\": 22982,\n    \"AU\": 22983,\n    \"mg\": 22984,\n    \"Off\": 22985,\n    \"ĠNGOs\": 22986,\n    \"chemical\": 22987,\n    \"Ġbrun\": 22988,\n    \"ĠHav\": 22989,\n    \"Ġlace\": 22990,\n    \"Ġ202\": 22991,\n    \"Ġdefer\": 22992,\n    \"Ġinjected\": 22993,\n    \"Ġgluten\": 22994,\n    \"ĠRin\": 22995,\n    \"ĠAvalanche\": 22996,\n    \"Ġcorpor\": 22997,\n    \"ĠPamela\": 22998,\n    \"Ġfills\": 22999,\n    \"ĠReve\": 23000,\n    \"ĠMonument\": 23001,\n    \"Ġnationalists\": 23002,\n    \"ĠIQ\": 23003,\n    \"adden\": 23004,\n    \"ĠLoop\": 23005,\n    \"Ġ134\": 23006,\n    \"Reg\": 23007,\n    \"click\": 23008,\n    \"bush\": 23009,\n    \"ĠKub\": 23010,\n    \"ipes\": 23011,\n    \"Ġtoggle\": 23012,\n    \"ĠRae\": 23013,\n    \"Ġburgl\": 23014,\n    \"Ġholistic\": 23015,\n    \"ronics\": 23016,\n    \"Ġprominence\": 23017,\n    \"jack\": 23018,\n    \"Ġfinan\": 23019,\n    \"icates\": 23020,\n    \"Ġvel\": 23021,\n    \"important\": 23022,\n    \"Thursday\": 23023,\n    \"chet\": 23024,\n    \"Ġrefunds\": 23025,\n    \"ĠElder\": 23026,\n    \"ĠOwner\": 23027,\n    \"Ġtakeaway\": 23028,\n    \"Pe\": 23029,\n    \"ĠToro\": 23030,\n    \"Tim\": 23031,\n    \"fix\": 23032,\n    \"before\": 23033,\n    \"ĠMotorola\": 23034,\n    \"Ġlev\": 23035,\n    \"Term\": 23036,\n    \"ĠSne\": 23037,\n    \"Ġmisinformation\": 23038,\n    \"ĠSinai\": 23039,\n    \"Ġnitrogen\": 23040,\n    \"Ġ203\": 23041,\n    \"Ġescaping\": 23042,\n    \"Ġjunction\": 23043,\n    \"ĠSantana\": 23044,\n    \"ĠYemeni\": 23045,\n    \"Ġwhipped\": 23046,\n    \"ĠStephenson\": 23047,\n    \"Ġattire\": 23048,\n    \"ĠBard\": 23049,\n    \"atically\": 23050,\n    \"ĠFaul\": 23051,\n    \"ĠSym\": 23052,\n    \"resh\": 23053,\n    \"ĠMG\": 23054,\n    \"Sub\": 23055,\n    \"ĠCarmen\": 23056,\n    \"Ġig\": 23057,\n    \"ĠSanford\": 23058,\n    \"ĠYa\": 23059,\n    \"cycle\": 23060,\n    \"Ġencryption\": 23061,\n    \"ĠScal\": 23062,\n    \"ĠChest\": 23063,\n    \"ĠMadonna\": 23064,\n    \"agin\": 23065,\n    \"ĠDHS\": 23066,\n    \"ĠCed\": 23067,\n    \"YR\": 23068,\n    \"Ġtruce\": 23069,\n    \"ĠBike\": 23070,\n    \"Ġfoes\": 23071,\n    \"ĠSlovakia\": 23072,\n    \"adal\": 23073,\n    \"Rain\": 23074,\n    \"OPE\": 23075,\n    \"Ġlockdown\": 23076,\n    \"Ġunilateral\": 23077,\n    \"Ġoverseen\": 23078,\n    \"Ġblames\": 23079,\n    \"Ġbarrage\": 23080,\n    \"aan\": 23081,\n    \"uds\": 23082,\n    \"ĠRust\": 23083,\n    \"ĠHC\": 23084,\n    \"cox\": 23085,\n    \"ĠAllied\": 23086,\n    \"ĠJosÃ©\": 23087,\n    \"pected\": 23088,\n    \"Ġunp\": 23089,\n    \"Ġsomeday\": 23090,\n    \"Ġdeductions\": 23091,\n    \"icial\": 23092,\n    \"ĠPRO\": 23093,\n    \"ĠIntern\": 23094,\n    \"Ġhemp\": 23095,\n    \"Ġkilograms\": 23096,\n    \"Ġnets\": 23097,\n    \"ĠBACK\": 23098,\n    \"early\": 23099,\n    \"outed\": 23100,\n    \"Ġrelegated\": 23101,\n    \"Ġ1958\": 23102,\n    \"ĠMustang\": 23103,\n    \"Ġgamble\": 23104,\n    \"Ġprostitution\": 23105,\n    \"ĠPapa\": 23106,\n    \"Ġinexpensive\": 23107,\n    \"GHz\": 23108,\n    \"Ġjerseys\": 23109,\n    \"Ġmisery\": 23110,\n    \"VIS\": 23111,\n    \"ĠRAW\": 23112,\n    \"Ġthri\": 23113,\n    \"Ġaffiliation\": 23114,\n    \"small\": 23115,\n    \"Ġflashed\": 23116,\n    \"Ġcoastline\": 23117,\n    \"Ġgard\": 23118,\n    \"Ġsv\": 23119,\n    \"Ġwaits\": 23120,\n    \"itton\": 23121,\n    \"London\": 23122,\n    \"Ġaccus\": 23123,\n    \"ĠCharge\": 23124,\n    \"Ġincub\": 23125,\n    \"Ġwanna\": 23126,\n    \"ĠAwareness\": 23127,\n    \"abies\": 23128,\n    \"ĠUh\": 23129,\n    \"Ġpersuaded\": 23130,\n    \"ĠThames\": 23131,\n    \"Ġcurated\": 23132,\n    \"Ī\": 23133,\n    \"Ġbrutally\": 23134,\n    \"Ġrooftop\": 23135,\n    \"Ġoy\": 23136,\n    \"Ġ1900\": 23137,\n    \"bery\": 23138,\n    \"Ġuphill\": 23139,\n    \"Ġinteracting\": 23140,\n    \"Ġchilly\": 23141,\n    \"ERE\": 23142,\n    \"Ġcapsule\": 23143,\n    \"ĠSaul\": 23144,\n    \"ocker\": 23145,\n    \"Ġdeserving\": 23146,\n    \"ĠBowen\": 23147,\n    \"ĠReaders\": 23148,\n    \"ĠWriters\": 23149,\n    \"Ġartifacts\": 23150,\n    \"ĠRanger\": 23151,\n    \"reau\": 23152,\n    \"Ġimperson\": 23153,\n    \"Ġhears\": 23154,\n    \"ĠMaher\": 23155,\n    \"neg\": 23156,\n    \"Ġmantra\": 23157,\n    \"Ġmull\": 23158,\n    \"Ġelders\": 23159,\n    \"ĠAmtrak\": 23160,\n    \"Ġspouses\": 23161,\n    \"ĠHak\": 23162,\n    \"Ġopenness\": 23163,\n    \"Ġprevailed\": 23164,\n    \"Ġfortnight\": 23165,\n    \"Pal\": 23166,\n    \"ride\": 23167,\n    \"Ġillustrate\": 23168,\n    \"dominated\": 23169,\n    \"trust\": 23170,\n    \"ī\": 23171,\n    \"ĠFemale\": 23172,\n    \"ĠSlim\": 23173,\n    \"Ġdesc\": 23174,\n    \"ĠKathryn\": 23175,\n    \"Ġdeepen\": 23176,\n    \"TAIN\": 23177,\n    \"eredith\": 23178,\n    \"Ġchanted\": 23179,\n    \"ĠHector\": 23180,\n    \"bread\": 23181,\n    \"ĠIsa\": 23182,\n    \"Ġvolcanic\": 23183,\n    \"Ġah\": 23184,\n    \"owners\": 23185,\n    \"aquin\": 23186,\n    \"Ġmelting\": 23187,\n    \"Ġpreschool\": 23188,\n    \"ocus\": 23189,\n    \"ĠMast\": 23190,\n    \"ĠMyr\": 23191,\n    \"Ġsuppress\": 23192,\n    \"Ġversatility\": 23193,\n    \"ĠNEC\": 23194,\n    \"Ġhoax\": 23195,\n    \"Ġmutually\": 23196,\n    \"ĠNeb\": 23197,\n    \"ĠWheel\": 23198,\n    \"kit\": 23199,\n    \"abl\": 23200,\n    \"again\": 23201,\n    \"ĠSonny\": 23202,\n    \"rift\": 23203,\n    \"Ġsweater\": 23204,\n    \"Ġinund\": 23205,\n    \"ĠTaco\": 23206,\n    \"ĠBout\": 23207,\n    \"Ġnonprofits\": 23208,\n    \"Ġmodify\": 23209,\n    \"Ġprofessionalism\": 23210,\n    \"ĠGould\": 23211,\n    \"ĠGuerrero\": 23212,\n    \"Ġterribly\": 23213,\n    \"ĠBenz\": 23214,\n    \"Ġcountered\": 23215,\n    \"Ġbean\": 23216,\n    \"ĠPhelps\": 23217,\n    \"Ġprowess\": 23218,\n    \"bc\": 23219,\n    \"Ġfeast\": 23220,\n    \"Ġ5000\": 23221,\n    \"Ġrevisit\": 23222,\n    \"Ġchin\": 23223,\n    \"agent\": 23224,\n    \"Ġtones\": 23225,\n    \"Ġextraction\": 23226,\n    \"ĠPosts\": 23227,\n    \"oin\": 23228,\n    \"Ġattain\": 23229,\n    \"Ġgardening\": 23230,\n    \"earned\": 23231,\n    \"ĠOtto\": 23232,\n    \"player\": 23233,\n    \"Ġscams\": 23234,\n    \"ĠHonolulu\": 23235,\n    \"ĠAppro\": 23236,\n    \"ĠHIGH\": 23237,\n    \"Ġdwell\": 23238,\n    \"Islam\": 23239,\n    \"leaders\": 23240,\n    \"Ġlegisl\": 23241,\n    \"expl\": 23242,\n    \"ĠChoi\": 23243,\n    \"Ġfrenzy\": 23244,\n    \"Ġcommercially\": 23245,\n    \"Ġlbs\": 23246,\n    \"Ġgateway\": 23247,\n    \"ĠAndersen\": 23248,\n    \"emia\": 23249,\n    \"lez\": 23250,\n    \"Ġresidences\": 23251,\n    \"office\": 23252,\n    \"ĠHelsinki\": 23253,\n    \"olia\": 23254,\n    \"Ġwolf\": 23255,\n    \"Ġstyling\": 23256,\n    \"ĠJunction\": 23257,\n    \"ĠPeyton\": 23258,\n    \"udo\": 23259,\n    \"ĠDorothy\": 23260,\n    \"Ġfreshly\": 23261,\n    \"ĠJulio\": 23262,\n    \"ĠSunset\": 23263,\n    \"ĠMadden\": 23264,\n    \"Ġissu\": 23265,\n    \"Ġsounding\": 23266,\n    \"sports\": 23267,\n    \"Ġmassively\": 23268,\n    \"ĠRahman\": 23269,\n    \"Ġpresided\": 23270,\n    \"Instead\": 23271,\n    \"Ġ136\": 23272,\n    \"ĠHowell\": 23273,\n    \"beit\": 23274,\n    \"Ġprosperous\": 23275,\n    \"Ġwrongly\": 23276,\n    \"ĠRaqqa\": 23277,\n    \"ĠCes\": 23278,\n    \"Ġbuddy\": 23279,\n    \"Ġchatting\": 23280,\n    \"Ġfencing\": 23281,\n    \"Ġtant\": 23282,\n    \"ocated\": 23283,\n    \"ALK\": 23284,\n    \"Ġsnapping\": 23285,\n    \"euro\": 23286,\n    \"Ryan\": 23287,\n    \"ĠRecogn\": 23288,\n    \"ucked\": 23289,\n    \"Ġpurported\": 23290,\n    \"ĠCann\": 23291,\n    \"Ġintimidating\": 23292,\n    \"Ġrulers\": 23293,\n    \"ĠMarse\": 23294,\n    \"Art\": 23295,\n    \"ĠAadhaar\": 23296,\n    \"Ġvows\": 23297,\n    \"Ġhunter\": 23298,\n    \"ourmet\": 23299,\n    \"ĠVarious\": 23300,\n    \"2009\": 23301,\n    \"anie\": 23302,\n    \"Ġcompassionate\": 23303,\n    \"ĠParking\": 23304,\n    \"Ġmalaria\": 23305,\n    \"Ġamnesty\": 23306,\n    \"Ġworsened\": 23307,\n    \"ĠTitan\": 23308,\n    \"Ġcrossings\": 23309,\n    \"drug\": 23310,\n    \"Ġaddicted\": 23311,\n    \"Ġremorse\": 23312,\n    \"ĠDestiny\": 23313,\n    \"Dear\": 23314,\n    \"Ġhur\": 23315,\n    \"Ġimplicated\": 23316,\n    \"Ġplayful\": 23317,\n    \"Ġripe\": 23318,\n    \"Ġsizable\": 23319,\n    \"Ġcrab\": 23320,\n    \"Ġliqu\": 23321,\n    \"Ġdrib\": 23322,\n    \"Ġcontraction\": 23323,\n    \"cro\": 23324,\n    \"ĠGus\": 23325,\n    \"Ġdoomed\": 23326,\n    \"Ġmog\": 23327,\n    \"ĠMonitor\": 23328,\n    \"Count\": 23329,\n    \"Ġsadd\": 23330,\n    \"Ġwrestler\": 23331,\n    \"Ġrestraints\": 23332,\n    \"Ġraging\": 23333,\n    \"185\": 23334,\n    \"Ġtapes\": 23335,\n    \"Ġmitigation\": 23336,\n    \"ocratic\": 23337,\n    \"Ġvib\": 23338,\n    \"ĠSnowden\": 23339,\n    \"aldo\": 23340,\n    \"Ġweights\": 23341,\n    \"Ġ1959\": 23342,\n    \"ucc\": 23343,\n    \"ĠCoc\": 23344,\n    \"Log\": 23345,\n    \"ĠStev\": 23346,\n    \"Ġdealership\": 23347,\n    \"Ġtrademarks\": 23348,\n    \"iru\": 23349,\n    \"Ġbeneficiary\": 23350,\n    \"Ġlegislator\": 23351,\n    \"Ġdeadlines\": 23352,\n    \"Ġcosmetics\": 23353,\n    \"ĠTammy\": 23354,\n    \"ĠCombined\": 23355,\n    \"Ġeducator\": 23356,\n    \"athon\": 23357,\n    \"Ġcombo\": 23358,\n    \"fu\": 23359,\n    \"appropriate\": 23360,\n    \"nington\": 23361,\n    \"ĠLiberties\": 23362,\n    \"missions\": 23363,\n    \"opard\": 23364,\n    \"ĠMondays\": 23365,\n    \"Ġfetch\": 23366,\n    \"Ġhers\": 23367,\n    \"jon\": 23368,\n    \"ukes\": 23369,\n    \"zek\": 23370,\n    \"Ġvetting\": 23371,\n    \"yet\": 23372,\n    \"Ġfacilitating\": 23373,\n    \"ĠStras\": 23374,\n    \"character\": 23375,\n    \"ĠHeads\": 23376,\n    \"Ġclim\": 23377,\n    \"ĠAlbuquerque\": 23378,\n    \"Ġbind\": 23379,\n    \"Ġconcluding\": 23380,\n    \"ĠBasically\": 23381,\n    \"rail\": 23382,\n    \"ĠTCU\": 23383,\n    \"ĠDepression\": 23384,\n    \"Ġhem\": 23385,\n    \"ĠHue\": 23386,\n    \"Ġpand\": 23387,\n    \"Ġscoreboard\": 23388,\n    \"Av\": 23389,\n    \"Ġidol\": 23390,\n    \"compl\": 23391,\n    \"Ġredesign\": 23392,\n    \"ĠJarrett\": 23393,\n    \"Ġfavoured\": 23394,\n    \"ĠINS\": 23395,\n    \"Ġpropelled\": 23396,\n    \"Ġevasion\": 23397,\n    \"Ġwidened\": 23398,\n    \"Ġwastewater\": 23399,\n    \"nard\": 23400,\n    \"responsive\": 23401,\n    \"Ġdemographics\": 23402,\n    \"engine\": 23403,\n    \"ĠBrewer\": 23404,\n    \"ĠBaxter\": 23405,\n    \"ront\": 23406,\n    \"ĠColon\": 23407,\n    \"Ġpromoter\": 23408,\n    \"Ġgenres\": 23409,\n    \"ovsky\": 23410,\n    \"build\": 23411,\n    \"urate\": 23412,\n    \"ĠCohn\": 23413,\n    \"design\": 23414,\n    \"Ġturbulent\": 23415,\n    \"Ġcurtain\": 23416,\n    \"310\": 23417,\n    \"ĠLamp\": 23418,\n    \"ĠBonds\": 23419,\n    \"church\": 23420,\n    \"Ġdeterrent\": 23421,\n    \"Ġdictatorship\": 23422,\n    \"acement\": 23423,\n    \"haul\": 23424,\n    \"Ġspir\": 23425,\n    \"Ġconceived\": 23426,\n    \"Ġstern\": 23427,\n    \"sit\": 23428,\n    \"Ġsingular\": 23429,\n    \"ĠYog\": 23430,\n    \"Ġconditional\": 23431,\n    \"Ġide\": 23432,\n    \"lund\": 23433,\n    \"Ġautop\": 23434,\n    \"ĠBEST\": 23435,\n    \"ĠJed\": 23436,\n    \"Ġrationale\": 23437,\n    \"Ġalarmed\": 23438,\n    \"Ġshovel\": 23439,\n    \"ĠProb\": 23440,\n    \"ĠMao\": 23441,\n    \"ĠBurgess\": 23442,\n    \"Ġ1953\": 23443,\n    \"above\": 23444,\n    \"ĠManson\": 23445,\n    \"Ġdismal\": 23446,\n    \"ĠFrankie\": 23447,\n    \"Ġtempted\": 23448,\n    \"Ġunderdog\": 23449,\n    \"ribing\": 23450,\n    \"ENCY\": 23451,\n    \"ĠDele\": 23452,\n    \"Las\": 23453,\n    \"places\": 23454,\n    \"Ġnotoriously\": 23455,\n    \"ĠAkin\": 23456,\n    \"Ġglut\": 23457,\n    \"Ġseamlessly\": 23458,\n    \"Ġrecess\": 23459,\n    \"written\": 23460,\n    \"ĠTJ\": 23461,\n    \"occ\": 23462,\n    \"ĠTerritory\": 23463,\n    \"ĠAIR\": 23464,\n    \"ĠDiagn\": 23465,\n    \"Ġvacancies\": 23466,\n    \"Ġcultivation\": 23467,\n    \"ĠAless\": 23468,\n    \"Ġrenamed\": 23469,\n    \"ĠMahmoud\": 23470,\n    \"bright\": 23471,\n    \"Ġvisibly\": 23472,\n    \"Ġnas\": 23473,\n    \"erred\": 23474,\n    \"ĠCarn\": 23475,\n    \"Ġtriggers\": 23476,\n    \"Ġpunishing\": 23477,\n    \"Ġluc\": 23478,\n    \"ĠBett\": 23479,\n    \"Ġbeam\": 23480,\n    \"ĠCheng\": 23481,\n    \"aina\": 23482,\n    \"Ġdetermines\": 23483,\n    \"ĠGerry\": 23484,\n    \"Ġshocks\": 23485,\n    \"Ġstainless\": 23486,\n    \"Ġdefects\": 23487,\n    \"ĠCinem\": 23488,\n    \"Ġtorrent\": 23489,\n    \"Ġresurgence\": 23490,\n    \"Ġcoral\": 23491,\n    \"Ġblitz\": 23492,\n    \"ĠGel\": 23493,\n    \"Ġstemmed\": 23494,\n    \"gur\": 23495,\n    \"Ġlymph\": 23496,\n    \"zzo\": 23497,\n    \"Ġspearheaded\": 23498,\n    \"Ġlicences\": 23499,\n    \"';\": 23500,\n    \"Ġarbitrary\": 23501,\n    \"ĠUzbek\": 23502,\n    \"Ġthief\": 23503,\n    \"reaching\": 23504,\n    \"Ġcand\": 23505,\n    \"ĠEA\": 23506,\n    \"ĠParaly\": 23507,\n    \"ĠEmerson\": 23508,\n    \"ĠSergey\": 23509,\n    \"ĠScher\": 23510,\n    \"ĠWr\": 23511,\n    \"rowing\": 23512,\n    \"Ġ3000\": 23513,\n    \"Ġmighty\": 23514,\n    \"elight\": 23515,\n    \"mAh\": 23516,\n    \"Ġcelebr\": 23517,\n    \"ĠConclusion\": 23518,\n    \"ĠCathy\": 23519,\n    \"Ġpolished\": 23520,\n    \"uddled\": 23521,\n    \"ewski\": 23522,\n    \"Ġfucking\": 23523,\n    \"Ġinterfering\": 23524,\n    \"Ġlandscapes\": 23525,\n    \"Ġfearful\": 23526,\n    \"ĠDetention\": 23527,\n    \"%).\": 23528,\n    \"ĠTT\": 23529,\n    \"Ġbleak\": 23530,\n    \"Ġindebted\": 23531,\n    \"Ġcheat\": 23532,\n    \"Ġconsolation\": 23533,\n    \"ĠPace\": 23534,\n    \"raine\": 23535,\n    \"Ġhonorary\": 23536,\n    \"420\": 23537,\n    \"Ġtechnician\": 23538,\n    \"ĠComprehensive\": 23539,\n    \"Ġfences\": 23540,\n    \"Ġwearable\": 23541,\n    \"ĠMarilyn\": 23542,\n    \"stru\": 23543,\n    \"Ġdrained\": 23544,\n    \"ĠGibraltar\": 23545,\n    \"lag\": 23546,\n    \"Ġdisorderly\": 23547,\n    \"Ġproclaimed\": 23548,\n    \"Ġcapacities\": 23549,\n    \"Ġretains\": 23550,\n    \"ĠVid\": 23551,\n    \"oshi\": 23552,\n    \"ĠEid\": 23553,\n    \"Ġanalytical\": 23554,\n    \"ominium\": 23555,\n    \"ĠExaminer\": 23556,\n    \"ĠNAACP\": 23557,\n    \"ocol\": 23558,\n    \"rev\": 23559,\n    \"ĠRim\": 23560,\n    \"ĠWoody\": 23561,\n    \"ĠMcKenna\": 23562,\n    \"ĠLennon\": 23563,\n    \"ĠEmploy\": 23564,\n    \"Fort\": 23565,\n    \"psy\": 23566,\n    \"Ġsphere\": 23567,\n    \"oday\": 23568,\n    \"ĠChick\": 23569,\n    \"ĠCompared\": 23570,\n    \"ĠIranians\": 23571,\n    \"ĠAccountability\": 23572,\n    \"itchie\": 23573,\n    \"ĠDickinson\": 23574,\n    \"Ġflock\": 23575,\n    \"Ġeclips\": 23576,\n    \"Ġnat\": 23577,\n    \"anke\": 23578,\n    \"ĠNeighborhood\": 23579,\n    \"Ġ141\": 23580,\n    \"Ġscarce\": 23581,\n    \"Ġcreations\": 23582,\n    \"lists\": 23583,\n    \"Ġuseless\": 23584,\n    \"Ġcriticisms\": 23585,\n    \"Ġruler\": 23586,\n    \"ĠHick\": 23587,\n    \"arya\": 23588,\n    \"worker\": 23589,\n    \"alam\": 23590,\n    \"Angelo\": 23591,\n    \"otle\": 23592,\n    \"Ġnewsletters\": 23593,\n    \"Ġerected\": 23594,\n    \"Ġzip\": 23595,\n    \"ĠBirthday\": 23596,\n    \"Ġdogged\": 23597,\n    \"Ġdanced\": 23598,\n    \"Ġconfession\": 23599,\n    \"Ġvomiting\": 23600,\n    \"ickers\": 23601,\n    \"Ġfox\": 23602,\n    \"Ġdeduct\": 23603,\n    \"Ġstresses\": 23604,\n    \"poll\": 23605,\n    \"ĠRadar\": 23606,\n    \"Ġengagements\": 23607,\n    \"Ġexaminer\": 23608,\n    \"Ġopportun\": 23609,\n    \"Ġlongevity\": 23610,\n    \"Ġbanana\": 23611,\n    \"carbon\": 23612,\n    \"uo\": 23613,\n    \"ĠLT\": 23614,\n    \"Ġsynagogue\": 23615,\n    \"Ġblackmail\": 23616,\n    \"INK\": 23617,\n    \"Ġfle\": 23618,\n    \"ĠGutierrez\": 23619,\n    \"Ġracket\": 23620,\n    \"Ġevenings\": 23621,\n    \"Ġdietary\": 23622,\n    \"ĠKok\": 23623,\n    \"Ġfaulty\": 23624,\n    \"Ġabandoning\": 23625,\n    \"ĠFlow\": 23626,\n    \"quest\": 23627,\n    \"estead\": 23628,\n    \"Ġbir\": 23629,\n    \"Ġsuicidal\": 23630,\n    \"ĠGift\": 23631,\n    \"ĠMissing\": 23632,\n    \"ĠMazda\": 23633,\n    \"ĠRib\": 23634,\n    \"ĠJourney\": 23635,\n    \"Ġconcede\": 23636,\n    \"Ġbrushed\": 23637,\n    \"Tw\": 23638,\n    \"andowski\": 23639,\n    \"ĠYun\": 23640,\n    \"Bride\": 23641,\n    \"zai\": 23642,\n    \"awatts\": 23643,\n    \"Ġcha\": 23644,\n    \"Ġspans\": 23645,\n    \"SF\": 23646,\n    \"Ġshells\": 23647,\n    \"planned\": 23648,\n    \"ĠGeographic\": 23649,\n    \"ĠVent\": 23650,\n    \"Ġfav\": 23651,\n    \"Ġinterrogation\": 23652,\n    \"Ġvaries\": 23653,\n    \"ĠPlat\": 23654,\n    \"operative\": 23655,\n    \"avid\": 23656,\n    \"Ġgreatness\": 23657,\n    \"ĠStrait\": 23658,\n    \"ĠSelling\": 23659,\n    \"Ġlawful\": 23660,\n    \"Ġlyn\": 23661,\n    \"Ġfunnel\": 23662,\n    \"Ġpundits\": 23663,\n    \"ties\": 23664,\n    \"Ġpneumonia\": 23665,\n    \"Ġcommencement\": 23666,\n    \"Ġbrisk\": 23667,\n    \"fires\": 23668,\n    \"ĠHTML\": 23669,\n    \"ĠSevent\": 23670,\n    \"Ġhistor\": 23671,\n    \"Ġ147\": 23672,\n    \"olls\": 23673,\n    \"Ġpian\": 23674,\n    \"Little\": 23675,\n    \"Ġcommercials\": 23676,\n    \"Ġdeteriorated\": 23677,\n    \"Ġbasin\": 23678,\n    \"Ġprohibition\": 23679,\n    \"Ġrestrictive\": 23680,\n    \"Ġtom\": 23681,\n    \"ĠPulse\": 23682,\n    \"vale\": 23683,\n    \"Ġmim\": 23684,\n    \"ĠLyons\": 23685,\n    \"ĠTrinidad\": 23686,\n    \"data\": 23687,\n    \"195\": 23688,\n    \"ĠPain\": 23689,\n    \"vor\": 23690,\n    \"ĠDirectorate\": 23691,\n    \"Wow\": 23692,\n    \"essential\": 23693,\n    \"Ġemerges\": 23694,\n    \"ĠDoors\": 23695,\n    \"Ġunde\": 23696,\n    \"Ġarchives\": 23697,\n    \"ĠIX\": 23698,\n    \"ĠAman\": 23699,\n    \"oric\": 23700,\n    \"ĠOper\": 23701,\n    \"nothing\": 23702,\n    \"Ġ142\": 23703,\n    \"igr\": 23704,\n    \"rust\": 23705,\n    \"ĠBYU\": 23706,\n    \"ĠBom\": 23707,\n    \"Ġrift\": 23708,\n    \"ĠAbs\": 23709,\n    \"ĠJenn\": 23710,\n    \"Ġrookies\": 23711,\n    \"hoe\": 23712,\n    \"Ġunderage\": 23713,\n    \"eden\": 23714,\n    \"Ġroasted\": 23715,\n    \"Ġenrol\": 23716,\n    \"Ġerased\": 23717,\n    \"Ġfreeway\": 23718,\n    \"Sil\": 23719,\n    \"Ġplanner\": 23720,\n    \"Ġconfess\": 23721,\n    \"ĠDual\": 23722,\n    \"ĠHeadquarters\": 23723,\n    \"bottom\": 23724,\n    \"Ġstatistic\": 23725,\n    \"ĠPush\": 23726,\n    \"Ġanim\": 23727,\n    \"ITT\": 23728,\n    \"Ġexecutions\": 23729,\n    \"Hub\": 23730,\n    \"ĠStick\": 23731,\n    \"Ġobscure\": 23732,\n    \"oven\": 23733,\n    \"Ġcoats\": 23734,\n    \"unc\": 23735,\n    \"Morning\": 23736,\n    \"Ġnit\": 23737,\n    \"mie\": 23738,\n    \"Ġcurves\": 23739,\n    \"gew\": 23740,\n    \"ĠAnniversary\": 23741,\n    \"members\": 23742,\n    \"ĠAbsolutely\": 23743,\n    \"Ġapt\": 23744,\n    \"otional\": 23745,\n    \"ĠGin\": 23746,\n    \"izo\": 23747,\n    \"Ġpretending\": 23748,\n    \"arak\": 23749,\n    \"Ġorganise\": 23750,\n    \"Ġroyalties\": 23751,\n    \"ĠCamden\": 23752,\n    \"Ġsausage\": 23753,\n    \"Inst\": 23754,\n    \"Ġchalk\": 23755,\n    \"ĠSurf\": 23756,\n    \"ĠSunrise\": 23757,\n    \"Ġmoder\": 23758,\n    \"aido\": 23759,\n    \"loving\": 23760,\n    \"lus\": 23761,\n    \"Ġoblig\": 23762,\n    \"Ġmotions\": 23763,\n    \"Ġclarification\": 23764,\n    \"ĠOM\": 23765,\n    \"Ġbishop\": 23766,\n    \"Ġexhibitions\": 23767,\n    \"ĠRifle\": 23768,\n    \"ĠPhot\": 23769,\n    \"ĠHM\": 23770,\n    \"ATIONAL\": 23771,\n    \"Ġwid\": 23772,\n    \"Ġreside\": 23773,\n    \"ĠPV\": 23774,\n    \"OOK\": 23775,\n    \"ĠTue\": 23776,\n    \"Ġ1200\": 23777,\n    \"Ġ1957\": 23778,\n    \"Ġespionage\": 23779,\n    \"ĠAPPLIC\": 23780,\n    \"Ġblasts\": 23781,\n    \"fter\": 23782,\n    \"Ġimmensely\": 23783,\n    \"ĠLots\": 23784,\n    \"Ġinflammatory\": 23785,\n    \"anging\": 23786,\n    \"Ġtumultuous\": 23787,\n    \"identified\": 23788,\n    \"Ġstead\": 23789,\n    \"ĠAch\": 23790,\n    \"Ãī\": 23791,\n    \"Ġbub\": 23792,\n    \"hler\": 23793,\n    \"olution\": 23794,\n    \"Ġshun\": 23795,\n    \"Ġnull\": 23796,\n    \"Ġunused\": 23797,\n    \"ĠObs\": 23798,\n    \"Ġinsol\": 23799,\n    \"ĠAttack\": 23800,\n    \"ertain\": 23801,\n    \"Ġdefiant\": 23802,\n    \"Through\": 23803,\n    \"ĠArmour\": 23804,\n    \"Ġsimulation\": 23805,\n    \"UCK\": 23806,\n    \"Ġinfluenza\": 23807,\n    \"Ġonset\": 23808,\n    \"Ġbored\": 23809,\n    \"Ġsouls\": 23810,\n    \"Ġreferees\": 23811,\n    \"Ġcollaborations\": 23812,\n    \"ĠLer\": 23813,\n    \"Ġcreepy\": 23814,\n    \"Ġanaly\": 23815,\n    \"ĠEffect\": 23816,\n    \"orting\": 23817,\n    \"Card\": 23818,\n    \"Ġdice\": 23819,\n    \"Ġharvesting\": 23820,\n    \"235\": 23821,\n    \"sty\": 23822,\n    \"ĠMcCartney\": 23823,\n    \"Ġsalute\": 23824,\n    \"UMP\": 23825,\n    \"Ġherb\": 23826,\n    \"ĠAbuse\": 23827,\n    \"ĠRamadan\": 23828,\n    \"Ġsuck\": 23829,\n    \"trained\": 23830,\n    \"ĠPhysical\": 23831,\n    \"iren\": 23832,\n    \"anches\": 23833,\n    \"erie\": 23834,\n    \"Ġhangs\": 23835,\n    \"Ġcataly\": 23836,\n    \"Ġintuitive\": 23837,\n    \"assi\": 23838,\n    \"Ġtechn\": 23839,\n    \"Ġjugg\": 23840,\n    \"Ġgameplay\": 23841,\n    \"Ġapolog\": 23842,\n    \"Ġfifteen\": 23843,\n    \"Ġgalleries\": 23844,\n    \"Ġoutlines\": 23845,\n    \"patient\": 23846,\n    \"ĠPotential\": 23847,\n    \"Ġethnicity\": 23848,\n    \"Ġharbour\": 23849,\n    \"Ġoverthrow\": 23850,\n    \"ĠLung\": 23851,\n    \"Ġwarehouses\": 23852,\n    \"ĠMonitoring\": 23853,\n    \"Ġmentors\": 23854,\n    \"Ġsized\": 23855,\n    \"Ġenvisioned\": 23856,\n    \"Ġgin\": 23857,\n    \"DT\": 23858,\n    \"Ġpropel\": 23859,\n    \"ĠKul\": 23860,\n    \"ference\": 23861,\n    \"estic\": 23862,\n    \"ĠLego\": 23863,\n    \"Ġdinners\": 23864,\n    \"ĠMoe\": 23865,\n    \"designed\": 23866,\n    \"ĠSusp\": 23867,\n    \"ĠBrick\": 23868,\n    \"qua\": 23869,\n    \"IDS\": 23870,\n    \"ĠBam\": 23871,\n    \"athe\": 23872,\n    \"Ġslices\": 23873,\n    \"Ġbottled\": 23874,\n    \"thy\": 23875,\n    \"producing\": 23876,\n    \"ĠTerror\": 23877,\n    \"professional\": 23878,\n    \"ĠKis\": 23879,\n    \"erto\": 23880,\n    \"ĠVehicles\": 23881,\n    \"Ġbeforehand\": 23882,\n    \"Ġdetrimental\": 23883,\n    \"weights\": 23884,\n    \"Ġallowances\": 23885,\n    \"Williams\": 23886,\n    \"ĠSyrians\": 23887,\n    \"ĠSto\": 23888,\n    \"Ġcozy\": 23889,\n    \"reditation\": 23890,\n    \"ensen\": 23891,\n    \"ĠSard\": 23892,\n    \"Ġroy\": 23893,\n    \"ooting\": 23894,\n    \"ĠReserv\": 23895,\n    \"ominated\": 23896,\n    \"emate\": 23897,\n    \"ĠTot\": 23898,\n    \"ĠCarnegie\": 23899,\n    \"ĠThib\": 23900,\n    \"ĠMarshal\": 23901,\n    \"Ġ152\": 23902,\n    \"Ġmayors\": 23903,\n    \"inery\": 23904,\n    \"ĠFiona\": 23905,\n    \"ĠCadillac\": 23906,\n    \"ivated\": 23907,\n    \"Ġeagerly\": 23908,\n    \"ĠOffensive\": 23909,\n    \"Ġastronaut\": 23910,\n    \"ĠVital\": 23911,\n    \"Ġcane\": 23912,\n    \"Ġquitting\": 23913,\n    \"ĠLone\": 23914,\n    \"Ġcensorship\": 23915,\n    \"ĠWelch\": 23916,\n    \"ĠUd\": 23917,\n    \"Ġmarquee\": 23918,\n    \"ĠDip\": 23919,\n    \"Ġwhereby\": 23920,\n    \"Ġtiger\": 23921,\n    \"gem\": 23922,\n    \"Ġconserv\": 23923,\n    \"Ġpresumed\": 23924,\n    \"ĠEntry\": 23925,\n    \"ffer\": 23926,\n    \"ĠProceed\": 23927,\n    \"Ġbrawl\": 23928,\n    \"ĠJaime\": 23929,\n    \"Ġecho\": 23930,\n    \"Ġadvancements\": 23931,\n    \"Ġtransitional\": 23932,\n    \"erick\": 23933,\n    \"Ġbully\": 23934,\n    \"anan\": 23935,\n    \"Ġreinvent\": 23936,\n    \"ĠLetters\": 23937,\n    \"Ġbricks\": 23938,\n    \"ĠSmy\": 23939,\n    \"Ġtowering\": 23940,\n    \"gging\": 23941,\n    \"299\": 23942,\n    \"orian\": 23943,\n    \"dimensional\": 23944,\n    \"ĠForty\": 23945,\n    \"ĠSinn\": 23946,\n    \"ushi\": 23947,\n    \"ĠSurveillance\": 23948,\n    \"enabled\": 23949,\n    \"ĠMous\": 23950,\n    \"ĠVive\": 23951,\n    \"Marcus\": 23952,\n    \"Ġvom\": 23953,\n    \"Ġcreek\": 23954,\n    \"Ġlime\": 23955,\n    \"Ġseismic\": 23956,\n    \"ĠFork\": 23957,\n    \"Ġembroiled\": 23958,\n    \"marks\": 23959,\n    \"Ġherald\": 23960,\n    \"ĠSonia\": 23961,\n    \"âĢ¦\\\"\": 23962,\n    \"wired\": 23963,\n    \"Ġobliged\": 23964,\n    \"ĠProjects\": 23965,\n    \"lde\": 23966,\n    \"ĠRiders\": 23967,\n    \"Ġovercoming\": 23968,\n    \"Mail\": 23969,\n    \"ĠLawn\": 23970,\n    \"ĠHawk\": 23971,\n    \"figure\": 23972,\n    \"ĠWritten\": 23973,\n    \"Ġens\": 23974,\n    \"Ġspacious\": 23975,\n    \"target\": 23976,\n    \"ĠRecep\": 23977,\n    \"ĠSAM\": 23978,\n    \"Ġentertained\": 23979,\n    \"Ġignited\": 23980,\n    \"ĠCENT\": 23981,\n    \"ogenic\": 23982,\n    \"Ġunatt\": 23983,\n    \"Ġexceeds\": 23984,\n    \"Ġ--------------------------------\": 23985,\n    \"Ġpillars\": 23986,\n    \"ĠBorders\": 23987,\n    \"ickey\": 23988,\n    \"Ġextinction\": 23989,\n    \"Ġviability\": 23990,\n    \"Ġtumors\": 23991,\n    \"ĠWilkinson\": 23992,\n    \"ĠKEY\": 23993,\n    \"Ġbins\": 23994,\n    \"ĠReported\": 23995,\n    \"Sm\": 23996,\n    \"ĠExclusive\": 23997,\n    \"ĠChilean\": 23998,\n    \"info\": 23999,\n    \"Ġwilderness\": 24000,\n    \"did\": 24001,\n    \"absolutely\": 24002,\n    \"pillar\": 24003,\n    \"Ġelites\": 24004,\n    \"ĠPreview\": 24005,\n    \"ixie\": 24006,\n    \"Mont\": 24007,\n    \"ribut\": 24008,\n    \"dream\": 24009,\n    \"Ġplanners\": 24010,\n    \"ĠSomerset\": 24011,\n    \"Ġenvis\": 24012,\n    \"ĠStall\": 24013,\n    \"Ġelevate\": 24014,\n    \"ographies\": 24015,\n    \"rama\": 24016,\n    \"Ha\": 24017,\n    \"Ġamidst\": 24018,\n    \"oho\": 24019,\n    \"Ġrejects\": 24020,\n    \"Jim\": 24021,\n    \"Ġmarginally\": 24022,\n    \"Ġusher\": 24023,\n    \"arez\": 24024,\n    \"ĠHawth\": 24025,\n    \"Ġsprink\": 24026,\n    \"ĠOffer\": 24027,\n    \"Ġanchored\": 24028,\n    \"ucking\": 24029,\n    \"ĠGarn\": 24030,\n    \"ĠConserv\": 24031,\n    \"Ġsocietal\": 24032,\n    \"Ġbrowsing\": 24033,\n    \"Ġbidder\": 24034,\n    \"burgh\": 24035,\n    \"ĠRunner\": 24036,\n    \"Ġtrendy\": 24037,\n    \"verts\": 24038,\n    \"imposed\": 24039,\n    \"ĠPatton\": 24040,\n    \"lements\": 24041,\n    \"Ġspicy\": 24042,\n    \"Ġswe\": 24043,\n    \"ĠStrike\": 24044,\n    \"Ġclam\": 24045,\n    \"ĠYankee\": 24046,\n    \"ĠKT\": 24047,\n    \"ĠGreenwood\": 24048,\n    \"ĠWays\": 24049,\n    \"Ġ2050\": 24050,\n    \"Ġattach\": 24051,\n    \"ĠShim\": 24052,\n    \"Ġmeltdown\": 24053,\n    \"Ġassemble\": 24054,\n    \"ĠUPDATE\": 24055,\n    \"Ġscout\": 24056,\n    \"Brown\": 24057,\n    \"ĠKobe\": 24058,\n    \"Ġpostpone\": 24059,\n    \"liness\": 24060,\n    \"allo\": 24061,\n    \"rief\": 24062,\n    \"ĠGerm\": 24063,\n    \"ĠFD\": 24064,\n    \"ĠReggie\": 24065,\n    \"ĠUnivers\": 24066,\n    \"ĠShepard\": 24067,\n    \"Ġcancell\": 24068,\n    \"ĠRomeo\": 24069,\n    \"ĠWarrior\": 24070,\n    \"ench\": 24071,\n    \"ifier\": 24072,\n    \"Ġprivileges\": 24073,\n    \"Ġsenses\": 24074,\n    \"Ġimpoverished\": 24075,\n    \"ĠPostal\": 24076,\n    \"encer\": 24077,\n    \"ĠConrad\": 24078,\n    \"Ġprinter\": 24079,\n    \"Ġinflicted\": 24080,\n    \"ĠGamble\": 24081,\n    \"ĠHeroes\": 24082,\n    \"132\": 24083,\n    \"Ġrevisions\": 24084,\n    \"Ġunsuccessfully\": 24085,\n    \"ĠHeisman\": 24086,\n    \"Ġstamped\": 24087,\n    \"inding\": 24088,\n    \"ĠLuna\": 24089,\n    \"Ġreinvest\": 24090,\n    \"ducers\": 24091,\n    \"ĠPassword\": 24092,\n    \"Leod\": 24093,\n    \"Ġcompounded\": 24094,\n    \"',\\\"\": 24095,\n    \"ogging\": 24096,\n    \"Ġprobing\": 24097,\n    \"ĠPBS\": 24098,\n    \"ĠMU\": 24099,\n    \"ĠWhenever\": 24100,\n    \"Ġsped\": 24101,\n    \"ĠCompetitive\": 24102,\n    \"isans\": 24103,\n    \"opa\": 24104,\n    \"Ġcleric\": 24105,\n    \"Ġvivid\": 24106,\n    \"à¸\": 24107,\n    \"126\": 24108,\n    \"Ġinconvenience\": 24109,\n    \"udi\": 24110,\n    \"Ġimmersive\": 24111,\n    \"Ġdiversion\": 24112,\n    \"Ġlogs\": 24113,\n    \"Ġspying\": 24114,\n    \"inct\": 24115,\n    \"Ġlitres\": 24116,\n    \"Ġmetallic\": 24117,\n    \"identally\": 24118,\n    \"FX\": 24119,\n    \"Ġloudly\": 24120,\n    \"Ġnursery\": 24121,\n    \"Ġcollectors\": 24122,\n    \"ĠKart\": 24123,\n    \"Ġescalate\": 24124,\n    \"Ġringing\": 24125,\n    \"Ġprocedural\": 24126,\n    \"Ġdisrupting\": 24127,\n    \"ĠEthiopian\": 24128,\n    \"ĠCFL\": 24129,\n    \"Ġillustrates\": 24130,\n    \"Ġperks\": 24131,\n    \"official\": 24132,\n    \"325\": 24133,\n    \"Ġmillennial\": 24134,\n    \"Ġbreadth\": 24135,\n    \"Ġmelted\": 24136,\n    \"Ġ850\": 24137,\n    \"ĠBake\": 24138,\n    \"donald\": 24139,\n    \"ĠGrac\": 24140,\n    \"Ġseeded\": 24141,\n    \"ĠDiscount\": 24142,\n    \"idates\": 24143,\n    \"Ġdrift\": 24144,\n    \"Ġcaptive\": 24145,\n    \"Ġseriousness\": 24146,\n    \"Ġrepercussions\": 24147,\n    \"Ġdisciplines\": 24148,\n    \"Ġthesis\": 24149,\n    \"Ġsleeve\": 24150,\n    \"ses\": 24151,\n    \"Monday\": 24152,\n    \"Ġthwart\": 24153,\n    \"ĠLic\": 24154,\n    \"Ġquadru\": 24155,\n    \"ĠPresbyterian\": 24156,\n    \"Ġreactors\": 24157,\n    \"ĠSuzanne\": 24158,\n    \"ewater\": 24159,\n    \"Ġlam\": 24160,\n    \"Ġbreastfeeding\": 24161,\n    \"Ġrats\": 24162,\n    \"ĠArtists\": 24163,\n    \"Ġdomestically\": 24164,\n    \"Ġdecom\": 24165,\n    \"ĠArms\": 24166,\n    \"basketball\": 24167,\n    \"Ġscrub\": 24168,\n    \"ĠTeddy\": 24169,\n    \"beh\": 24170,\n    \"ĠBetsy\": 24171,\n    \"ĠNursing\": 24172,\n    \"Ġdescriptions\": 24173,\n    \"127\": 24174,\n    \"gil\": 24175,\n    \"itional\": 24176,\n    \"Ġchampioned\": 24177,\n    \"ĠCalling\": 24178,\n    \"Ġrealization\": 24179,\n    \"ĠBuddy\": 24180,\n    \"hou\": 24181,\n    \"ĠDire\": 24182,\n    \"ĠHuff\": 24183,\n    \"Ġlipstick\": 24184,\n    \"Ray\": 24185,\n    \"Ġflare\": 24186,\n    \"belt\": 24187,\n    \"Ġbrightest\": 24188,\n    \"Ġmalfunction\": 24189,\n    \"ĠManor\": 24190,\n    \"Ġsaturated\": 24191,\n    \"rays\": 24192,\n    \"ĠDW\": 24193,\n    \"ixed\": 24194,\n    \"ĠSlovenia\": 24195,\n    \"seen\": 24196,\n    \"ĠCause\": 24197,\n    \"arios\": 24198,\n    \"ASE\": 24199,\n    \"Ġrend\": 24200,\n    \"ĠTBA\": 24201,\n    \"Ġlecturer\": 24202,\n    \"attering\": 24203,\n    \"Ġaffluent\": 24204,\n    \"CEO\": 24205,\n    \"Ġbreathtaking\": 24206,\n    \"ĠGiles\": 24207,\n    \"irth\": 24208,\n    \"ĠPhilips\": 24209,\n    \"Ġposture\": 24210,\n    \"ĠTSA\": 24211,\n    \"heit\": 24212,\n    \"Ġmenace\": 24213,\n    \"ricks\": 24214,\n    \"ĠAden\": 24215,\n    \"ĠReich\": 24216,\n    \"iggle\": 24217,\n    \"ĠShutterstock\": 24218,\n    \"Ġcourageous\": 24219,\n    \"edia\": 24220,\n    \"Staff\": 24221,\n    \"Ġdivert\": 24222,\n    \"ĠCir\": 24223,\n    \"Ġguessing\": 24224,\n    \"apers\": 24225,\n    \"ĠBritons\": 24226,\n    \"lÃ©\": 24227,\n    \"Ġconvened\": 24228,\n    \"ĠSerbian\": 24229,\n    \"Ġricher\": 24230,\n    \"Ġcock\": 24231,\n    \"Ġdeposited\": 24232,\n    \"company\": 24233,\n    \"Ġdelic\": 24234,\n    \"sensitive\": 24235,\n    \"tank\": 24236,\n    \"ĠPatty\": 24237,\n    \"mia\": 24238,\n    \"onomous\": 24239,\n    \"cn\": 24240,\n    \"Ġclamp\": 24241,\n    \"ĠAcademic\": 24242,\n    \"Ġprosecuting\": 24243,\n    \"ĠTransparency\": 24244,\n    \"Ġdeflation\": 24245,\n    \"Ġdashboard\": 24246,\n    \"ĠDress\": 24247,\n    \"Ġlin\": 24248,\n    \"mu\": 24249,\n    \"ĠGoodell\": 24250,\n    \"Ġlav\": 24251,\n    \"ĠTwelve\": 24252,\n    \"Ġflavour\": 24253,\n    \"Ġfiercely\": 24254,\n    \"Ġbloom\": 24255,\n    \"ĠHaf\": 24256,\n    \"ĠGrad\": 24257,\n    \"LET\": 24258,\n    \"ĠSeeing\": 24259,\n    \"oxide\": 24260,\n    \"Ġmenus\": 24261,\n    \"char\": 24262,\n    \"adoes\": 24263,\n    \"combe\": 24264,\n    \"Street\": 24265,\n    \"ĠRidley\": 24266,\n    \"Ġdepicts\": 24267,\n    \"ĠPred\": 24268,\n    \"ÑĢ\": 24269,\n    \"British\": 24270,\n    \"Ġbumps\": 24271,\n    \"Ġlamp\": 24272,\n    \"ĠDesmond\": 24273,\n    \"ĠPB\": 24274,\n    \"Ġfrag\": 24275,\n    \"tin\": 24276,\n    \"ĠSharing\": 24277,\n    \"Ġdesperation\": 24278,\n    \"Ġcommuter\": 24279,\n    \"igrants\": 24280,\n    \"ĠShapiro\": 24281,\n    \"Ġkinda\": 24282,\n    \"Ġimpartial\": 24283,\n    \"ĠJewel\": 24284,\n    \"Ġcongratulations\": 24285,\n    \"Ġcompost\": 24286,\n    \"Ġadmiration\": 24287,\n    \"Ġpaycheck\": 24288,\n    \"ĠAnonymous\": 24289,\n    \"enger\": 24290,\n    \"Mer\": 24291,\n    \"ĠGospel\": 24292,\n    \"ĠEth\": 24293,\n    \"ĠMH\": 24294,\n    \"Ġfem\": 24295,\n    \"ĠTrial\": 24296,\n    \"Ġdepths\": 24297,\n    \"ĠApplied\": 24298,\n    \"Ġgrit\": 24299,\n    \"Ġerase\": 24300,\n    \"sid\": 24301,\n    \"comm\": 24302,\n    \"}\": 24303,\n    \"Ġretreated\": 24304,\n    \"Ġanalysed\": 24305,\n    \"ĠRegular\": 24306,\n    \"ĠPesh\": 24307,\n    \"ICAL\": 24308,\n    \"pei\": 24309,\n    \"ĠReilly\": 24310,\n    \"ĠTrib\": 24311,\n    \"Ġbooths\": 24312,\n    \"Ġdrank\": 24313,\n    \"Ġcoma\": 24314,\n    \"Ġharvested\": 24315,\n    \"ĠCHAR\": 24316,\n    \"Ġbutterfly\": 24317,\n    \"Ġsailed\": 24318,\n    \"ĠDrink\": 24319,\n    \"eping\": 24320,\n    \"ATCH\": 24321,\n    \"ĠLegends\": 24322,\n    \"Ġinsured\": 24323,\n    \"Ġwholes\": 24324,\n    \"ĠBis\": 24325,\n    \"ĠShea\": 24326,\n    \"ighter\": 24327,\n    \"Ġsnakes\": 24328,\n    \"ĠGunn\": 24329,\n    \"ĠPoss\": 24330,\n    \"Ġdispar\": 24331,\n    \"Ġbombshell\": 24332,\n    \"Ġscanning\": 24333,\n    \"340\": 24334,\n    \"choice\": 24335,\n    \"cool\": 24336,\n    \"\\\"âĢĶ\": 24337,\n    \"ĠTheo\": 24338,\n    \"rine\": 24339,\n    \"ĠJacques\": 24340,\n    \"Ġdisadvantaged\": 24341,\n    \"Ġparamount\": 24342,\n    \"igate\": 24343,\n    \"stat\": 24344,\n    \"anski\": 24345,\n    \"Ġoutsourcing\": 24346,\n    \"Ġpopulous\": 24347,\n    \"Ġbinge\": 24348,\n    \"ĠOrganic\": 24349,\n    \"urban\": 24350,\n    \"Ġyogurt\": 24351,\n    \"Ġretweet\": 24352,\n    \"osen\": 24353,\n    \"cially\": 24354,\n    \"215\": 24355,\n    \"Ġeditions\": 24356,\n    \"Ġburgeoning\": 24357,\n    \"efully\": 24358,\n    \"ĠThousand\": 24359,\n    \"Ġreplacements\": 24360,\n    \"ĠAmazing\": 24361,\n    \"rator\": 24362,\n    \"icy\": 24363,\n    \"Ġintensify\": 24364,\n    \"Sen\": 24365,\n    \"ĠQuincy\": 24366,\n    \"powers\": 24367,\n    \"ĠAur\": 24368,\n    \"ĠZion\": 24369,\n    \"stal\": 24370,\n    \"Ġpillar\": 24371,\n    \"ĠErit\": 24372,\n    \"ĠPerform\": 24373,\n    \"aston\": 24374,\n    \"Eric\": 24375,\n    \"Ġunh\": 24376,\n    \"IFF\": 24377,\n    \"950\": 24378,\n    \"ĠEngineer\": 24379,\n    \"ĠLands\": 24380,\n    \"Ġdubious\": 24381,\n    \"fy\": 24382,\n    \"ĠWI\": 24383,\n    \"ĠSv\": 24384,\n    \"ĠHendricks\": 24385,\n    \"ĠKod\": 24386,\n    \"Ġoutlining\": 24387,\n    \"ĠCorrespond\": 24388,\n    \"amus\": 24389,\n    \"worst\": 24390,\n    \"arter\": 24391,\n    \"coni\": 24392,\n    \"Ġhierarchy\": 24393,\n    \"ĠTHAT\": 24394,\n    \"Ġexce\": 24395,\n    \"Ġrailways\": 24396,\n    \"Ġmasked\": 24397,\n    \"lene\": 24398,\n    \"Ġoutset\": 24399,\n    \"Ġavalanche\": 24400,\n    \"Ġnicknamed\": 24401,\n    \"Ġ702\": 24402,\n    \"Lee\": 24403,\n    \"Ġ139\": 24404,\n    \"ĠSixth\": 24405,\n    \"365\": 24406,\n    \"nda\": 24407,\n    \"Ġaccountant\": 24408,\n    \"Ġobese\": 24409,\n    \"Ġgrape\": 24410,\n    \"Ġimpunity\": 24411,\n    \"ĠYorkers\": 24412,\n    \"Ġguardian\": 24413,\n    \"icity\": 24414,\n    \"Ġcentrist\": 24415,\n    \"Ġwaterways\": 24416,\n    \"ursed\": 24417,\n    \"Ġhopeless\": 24418,\n    \"header\": 24419,\n    \"Ġtack\": 24420,\n    \"Ġric\": 24421,\n    \"umn\": 24422,\n    \"Ġvalve\": 24423,\n    \"Ġtread\": 24424,\n    \"ĠCST\": 24425,\n    \"Ġhepatitis\": 24426,\n    \"ctor\": 24427,\n    \"ĠRED\": 24428,\n    \"Ġsolitary\": 24429,\n    \"NW\": 24430,\n    \"Ġceremonial\": 24431,\n    \"Ġfoe\": 24432,\n    \"Ġling\": 24433,\n    \"Jason\": 24434,\n    \"ĠLisbon\": 24435,\n    \"Ġ1955\": 24436,\n    \"ĠHeller\": 24437,\n    \"Ġkin\": 24438,\n    \"essen\": 24439,\n    \"Ġturbines\": 24440,\n    \"shi\": 24441,\n    \"Ġlodge\": 24442,\n    \"Ġveterinary\": 24443,\n    \"ĠBoll\": 24444,\n    \"ĠConfederation\": 24445,\n    \"ĠJournalists\": 24446,\n    \"Ġtug\": 24447,\n    \"ĠStarr\": 24448,\n    \"Ġpiles\": 24449,\n    \"Way\": 24450,\n    \"adel\": 24451,\n    \"orean\": 24452,\n    \"Ġoft\": 24453,\n    \"Ġshortcomings\": 24454,\n    \"ĠSheila\": 24455,\n    \"Ġbackbone\": 24456,\n    \"III\": 24457,\n    \"ĠDarwin\": 24458,\n    \"ĠTunis\": 24459,\n    \"Ġsuspicions\": 24460,\n    \"Ġdisagreements\": 24461,\n    \"Ġ247\": 24462,\n    \"illery\": 24463,\n    \"'\\\"\": 24464,\n    \"Ġsegregation\": 24465,\n    \"ohl\": 24466,\n    \"Ġinstincts\": 24467,\n    \"ĠPoo\": 24468,\n    \"nih\": 24469,\n    \"parency\": 24470,\n    \"uddy\": 24471,\n    \"esting\": 24472,\n    \"asses\": 24473,\n    \"ĠIntroduction\": 24474,\n    \"ĠSirius\": 24475,\n    \"Local\": 24476,\n    \"orous\": 24477,\n    \"Ġrehearsal\": 24478,\n    \"Ġdemol\": 24479,\n    \"Ġtraffickers\": 24480,\n    \"Ġupsetting\": 24481,\n    \"Ġheir\": 24482,\n    \"death\": 24483,\n    \"ĠMoments\": 24484,\n    \"Los\": 24485,\n    \"Ġatmospheric\": 24486,\n    \"aints\": 24487,\n    \"ĠDianne\": 24488,\n    \"Ġlikewise\": 24489,\n    \"ĠMing\": 24490,\n    \"auga\": 24491,\n    \"Ġfirsthand\": 24492,\n    \"Ġnarratives\": 24493,\n    \"ĠAstron\": 24494,\n    \"ĠExtreme\": 24495,\n    \"Ġhorns\": 24496,\n    \"ĠSana\": 24497,\n    \"Ġrecapt\": 24498,\n    \"ĠMist\": 24499,\n    \"ĠRandolph\": 24500,\n    \"connect\": 24501,\n    \"Ġindecent\": 24502,\n    \"Ġforty\": 24503,\n    \"Ġjihadists\": 24504,\n    \"azes\": 24505,\n    \"Ġdread\": 24506,\n    \"Ġgrapes\": 24507,\n    \"Ġremoves\": 24508,\n    \"Ġscreamed\": 24509,\n    \"ĠCrus\": 24510,\n    \"ikers\": 24511,\n    \"Ġsnapshot\": 24512,\n    \"ĠCalls\": 24513,\n    \"Cons\": 24514,\n    \"Ġlettuce\": 24515,\n    \"ĠPig\": 24516,\n    \"urable\": 24517,\n    \"jured\": 24518,\n    \"ILY\": 24519,\n    \"ĠJessie\": 24520,\n    \".).\": 24521,\n    \"Pay\": 24522,\n    \"Tra\": 24523,\n    \"----------------\": 24524,\n    \"ĠUnits\": 24525,\n    \"ĠPlayboy\": 24526,\n    \"Ġarthritis\": 24527,\n    \"Ġafforded\": 24528,\n    \"insk\": 24529,\n    \"ĠFake\": 24530,\n    \"ĠLies\": 24531,\n    \"ĠBaltic\": 24532,\n    \"oyal\": 24533,\n    \"ĠVest\": 24534,\n    \"Ġrusher\": 24535,\n    \"Ġincorporates\": 24536,\n    \"ĠMM\": 24537,\n    \"ĠDru\": 24538,\n    \"ĠWare\": 24539,\n    \"ĠSammy\": 24540,\n    \"ĠGob\": 24541,\n    \"ĠRuk\": 24542,\n    \"Ġ146\": 24543,\n    \"ĠCrowd\": 24544,\n    \"Ġduel\": 24545,\n    \"irts\": 24546,\n    \"Ġsourcing\": 24547,\n    \"hp\": 24548,\n    \"ĠJava\": 24549,\n    \"bred\": 24550,\n    \"ĠRefer\": 24551,\n    \"Ġuninsured\": 24552,\n    \"Ġslope\": 24553,\n    \"256\": 24554,\n    \"Ġregulating\": 24555,\n    \"Ġfundra\": 24556,\n    \"Ġinserted\": 24557,\n    \"ĠNickel\": 24558,\n    \"ĠConsumption\": 24559,\n    \"ĠRomo\": 24560,\n    \"Atlantic\": 24561,\n    \"Ġenclave\": 24562,\n    \"Ġpegged\": 24563,\n    \"Ġdirects\": 24564,\n    \"mbudsman\": 24565,\n    \"ĠDES\": 24566,\n    \"Ob\": 24567,\n    \"Ġlimbs\": 24568,\n    \"Ġbury\": 24569,\n    \"ILA\": 24570,\n    \"Ġstew\": 24571,\n    \"Ġbreeze\": 24572,\n    \"Ġabrupt\": 24573,\n    \"ĠGott\": 24574,\n    \"ĠClaude\": 24575,\n    \"Ġgenetically\": 24576,\n    \"Ġrigid\": 24577,\n    \"ĠDudley\": 24578,\n    \"ĠNer\": 24579,\n    \"registered\": 24580,\n    \"Ġentrenched\": 24581,\n    \"Ġextortion\": 24582,\n    \"ĠNurs\": 24583,\n    \"Ġcontingency\": 24584,\n    \"etter\": 24585,\n    \"Ġrejo\": 24586,\n    \"Ġprotagonist\": 24587,\n    \"Ġcounselling\": 24588,\n    \"ĠVit\": 24589,\n    \"aware\": 24590,\n    \"ĠMonsanto\": 24591,\n    \"GG\": 24592,\n    \"Ġincarcerated\": 24593,\n    \"Ġabduction\": 24594,\n    \"Ġreferencing\": 24595,\n    \"Germany\": 24596,\n    \"uates\": 24597,\n    \"reck\": 24598,\n    \"Ġtram\": 24599,\n    \"Ġchron\": 24600,\n    \"Ġmish\": 24601,\n    \"ĠVes\": 24602,\n    \"ĠTire\": 24603,\n    \"Ġvandal\": 24604,\n    \"ĠCrazy\": 24605,\n    \"ĠLifetime\": 24606,\n    \"ĠSpectrum\": 24607,\n    \"celer\": 24608,\n    \"Ġmotto\": 24609,\n    \"hang\": 24610,\n    \"Ġblade\": 24611,\n    \"gel\": 24612,\n    \"Ġbiography\": 24613,\n    \"Ġallegiance\": 24614,\n    \"hod\": 24615,\n    \"hap\": 24616,\n    \"ptic\": 24617,\n    \"acle\": 24618,\n    \"ĠBlade\": 24619,\n    \"ĠBoh\": 24620,\n    \"Ġ149\": 24621,\n    \"Ġchang\": 24622,\n    \"Ġcanned\": 24623,\n    \"Ġfacilitated\": 24624,\n    \"actor\": 24625,\n    \"iologist\": 24626,\n    \"Ġrebuilt\": 24627,\n    \"Ġawake\": 24628,\n    \"Ġmayoral\": 24629,\n    \"ĠEuros\": 24630,\n    \"Ġdangerously\": 24631,\n    \"MK\": 24632,\n    \"Ġreplica\": 24633,\n    \"Ġcoinc\": 24634,\n    \"blog\": 24635,\n    \"ĠEra\": 24636,\n    \"Ġrelinqu\": 24637,\n    \"quite\": 24638,\n    \"ondon\": 24639,\n    \"rosso\": 24640,\n    \"tun\": 24641,\n    \"Ġtouchscreen\": 24642,\n    \"Ġpops\": 24643,\n    \"ousing\": 24644,\n    \"efficient\": 24645,\n    \"Ġ148\": 24646,\n    \"Ġconced\": 24647,\n    \"although\": 24648,\n    \"Ġ1956\": 24649,\n    \"Ġmortar\": 24650,\n    \"ĠCave\": 24651,\n    \"ĠJung\": 24652,\n    \"urer\": 24653,\n    \"Ġillusion\": 24654,\n    \"ĠBerman\": 24655,\n    \"intend\": 24656,\n    \"Ġcoping\": 24657,\n    \"Dem\": 24658,\n    \"tion\": 24659,\n    \"estation\": 24660,\n    \"ĠSounds\": 24661,\n    \"Ġnavigating\": 24662,\n    \"Ġsperm\": 24663,\n    \"Ġreligions\": 24664,\n    \"Ġfol\": 24665,\n    \"Ġheroic\": 24666,\n    \"FD\": 24667,\n    \"Ġhesitant\": 24668,\n    \"asure\": 24669,\n    \"Ġredeem\": 24670,\n    \"Adam\": 24671,\n    \"Ġfireplace\": 24672,\n    \"vertis\": 24673,\n    \"ĠSung\": 24674,\n    \"290\": 24675,\n    \"iland\": 24676,\n    \"ĠUpdates\": 24677,\n    \"OTUS\": 24678,\n    \"ĠPTSD\": 24679,\n    \"Ġhelmets\": 24680,\n    \"\\\"?\": 24681,\n    \"Ġslashing\": 24682,\n    \"Ġscouts\": 24683,\n    \"Ġspelling\": 24684,\n    \"ĠInitial\": 24685,\n    \"draw\": 24686,\n    \"Ġchallengers\": 24687,\n    \"Ġsupremacists\": 24688,\n    \"Ġpilgrims\": 24689,\n    \"Ġasc\": 24690,\n    \"ĠFill\": 24691,\n    \"ĠPau\": 24692,\n    \"Ġjewel\": 24693,\n    \"ĠMalt\": 24694,\n    \"icip\": 24695,\n    \"Ġinhabitants\": 24696,\n    \"Ġmetre\": 24697,\n    \"ahar\": 24698,\n    \"Comp\": 24699,\n    \"atches\": 24700,\n    \"inv\": 24701,\n    \"Ġcyclist\": 24702,\n    \"ĠQC\": 24703,\n    \"Ġmanually\": 24704,\n    \"ĠAnchorage\": 24705,\n    \"Ġdiscarded\": 24706,\n    \"Ġconsolid\": 24707,\n    \"Ġnavig\": 24708,\n    \"ĠAnimals\": 24709,\n    \"ĠPole\": 24710,\n    \"esson\": 24711,\n    \"Ġ1954\": 24712,\n    \"Ġsorted\": 24713,\n    \"Ġmadness\": 24714,\n    \"ĠBrigade\": 24715,\n    \"ĠGenesis\": 24716,\n    \"Ġdismissing\": 24717,\n    \"ĠPanasonic\": 24718,\n    \"Ġdizz\": 24719,\n    \"ĠEducational\": 24720,\n    \"ĠKO\": 24721,\n    \"ĠPill\": 24722,\n    \"ĠGIF\": 24723,\n    \"Ġbol\": 24724,\n    \"Ġwards\": 24725,\n    \"Ġcontroversies\": 24726,\n    \"Chinese\": 24727,\n    \"Ġantics\": 24728,\n    \"Ġreliant\": 24729,\n    \"ĠMoff\": 24730,\n    \"Ġethanol\": 24731,\n    \"Ġtorch\": 24732,\n    \"rights\": 24733,\n    \"ĠHabit\": 24734,\n    \"arton\": 24735,\n    \"rera\": 24736,\n    \"ĠSasha\": 24737,\n    \"abella\": 24738,\n    \"Ġproliferation\": 24739,\n    \"Ġsincerely\": 24740,\n    \"communication\": 24741,\n    \"ĠNay\": 24742,\n    \"ĠChattanooga\": 24743,\n    \"ounces\": 24744,\n    \"ĠNXT\": 24745,\n    \"ĠEmir\": 24746,\n    \"Ġmanipulated\": 24747,\n    \"Ġharassing\": 24748,\n    \"wat\": 24749,\n    \"Ġbouts\": 24750,\n    \"Book\": 24751,\n    \"Ġhovering\": 24752,\n    \"ĠScan\": 24753,\n    \"ship\": 24754,\n    \"ĠAngola\": 24755,\n    \"ĠLC\": 24756,\n    \"Ġruins\": 24757,\n    \"Ġsexist\": 24758,\n    \"zar\": 24759,\n    \"Ġpledging\": 24760,\n    \"ober\": 24761,\n    \"Ġembold\": 24762,\n    \"Ġobjection\": 24763,\n    \"Ġboasting\": 24764,\n    \"MIN\": 24765,\n    \"Ġherbs\": 24766,\n    \"Ġgears\": 24767,\n    \"ĠIc\": 24768,\n    \"stre\": 24769,\n    \"him\": 24770,\n    \"Ġhomicides\": 24771,\n    \"cki\": 24772,\n    \"castle\": 24773,\n    \"counter\": 24774,\n    \"ĠCAS\": 24775,\n    \"ĠReasons\": 24776,\n    \"ĠDeclaration\": 24777,\n    \"Ġsimplify\": 24778,\n    \"Ġfared\": 24779,\n    \"Ġescort\": 24780,\n    \"Ġkidn\": 24781,\n    \"ĠHamm\": 24782,\n    \"Ġnailed\": 24783,\n    \"Ġaccommodations\": 24784,\n    \"Ġmodifications\": 24785,\n    \"rible\": 24786,\n    \"Ġwool\": 24787,\n    \"EDIT\": 24788,\n    \"2010\": 24789,\n    \"Ġauthentication\": 24790,\n    \"Ġgoat\": 24791,\n    \"hom\": 24792,\n    \"Ġfederally\": 24793,\n    \"ĠRath\": 24794,\n    \"Ġspiked\": 24795,\n    \"Ġmisrepresent\": 24796,\n    \"Ġavenue\": 24797,\n    \"Ġbroadcasts\": 24798,\n    \"ĠEstonia\": 24799,\n    \"ennes\": 24800,\n    \"ĠMare\": 24801,\n    \"ption\": 24802,\n    \"ĠKag\": 24803,\n    \"Ġcircumstance\": 24804,\n    \"orrow\": 24805,\n    \"isons\": 24806,\n    \"ĠCollabor\": 24807,\n    \"Ġstroll\": 24808,\n    \"ĠCPS\": 24809,\n    \"soft\": 24810,\n    \"iral\": 24811,\n    \"apo\": 24812,\n    \"usky\": 24813,\n    \"poke\": 24814,\n    \"Ġwoo\": 24815,\n    \"ĠElena\": 24816,\n    \"ĠLastly\": 24817,\n    \"Ġlinemen\": 24818,\n    \"Canadian\": 24819,\n    \"ĠAnyway\": 24820,\n    \"Ġsubstantive\": 24821,\n    \"ĠCurt\": 24822,\n    \"Ġard\": 24823,\n    \"ĠYosh\": 24824,\n    \"ĠBuchanan\": 24825,\n    \"Ġrevolving\": 24826,\n    \"Ġspecials\": 24827,\n    \"Ġshrine\": 24828,\n    \"Ġlumber\": 24829,\n    \"Ġorchestrated\": 24830,\n    \"kie\": 24831,\n    \"azy\": 24832,\n    \"Ġexpiration\": 24833,\n    \"ĠDaryl\": 24834,\n    \"ĠPatri\": 24835,\n    \"better\": 24836,\n    \"2020\": 24837,\n    \"ĠFav\": 24838,\n    \"ĠOP\": 24839,\n    \"OTT\": 24840,\n    \"Ġflush\": 24841,\n    \"ĠSikh\": 24842,\n    \"Ġecosystems\": 24843,\n    \"ĠBET\": 24844,\n    \"eared\": 24845,\n    \"audio\": 24846,\n    \"ĠFahrenheit\": 24847,\n    \"police\": 24848,\n    \"Ġincarceration\": 24849,\n    \"Ġerupt\": 24850,\n    \"ĠDamien\": 24851,\n    \"ĠHague\": 24852,\n    \"ulz\": 24853,\n    \"ĠAgents\": 24854,\n    \"ĠBanner\": 24855,\n    \"Ġconductor\": 24856,\n    \"ĠAjax\": 24857,\n    \"arson\": 24858,\n    \"Ġrests\": 24859,\n    \"Ġeurozone\": 24860,\n    \"Ġfelon\": 24861,\n    \"Ġcurator\": 24862,\n    \"morning\": 24863,\n    \"Ġevidenced\": 24864,\n    \"ĠNeh\": 24865,\n    \"Ġmattress\": 24866,\n    \"Ġtast\": 24867,\n    \"Ġfueling\": 24868,\n    \"ĠOccup\": 24869,\n    \"Ġbake\": 24870,\n    \"ĠZac\": 24871,\n    \"meaning\": 24872,\n    \"Ill\": 24873,\n    \"ĠHau\": 24874,\n    \"ĠLaden\": 24875,\n    \"Ġbald\": 24876,\n    \"Mary\": 24877,\n    \"oky\": 24878,\n    \"atri\": 24879,\n    \"Ġtracker\": 24880,\n    \"OTA\": 24881,\n    \"catching\": 24882,\n    \"ĠUnderground\": 24883,\n    \"ĠHuffPost\": 24884,\n    \"ĠAtkins\": 24885,\n    \"oglu\": 24886,\n    \"Ġauthorised\": 24887,\n    \"Ġroutines\": 24888,\n    \"ĠHof\": 24889,\n    \"veland\": 24890,\n    \"Ġlangu\": 24891,\n    \"Ġprot\": 24892,\n    \"ĠHyd\": 24893,\n    \"integ\": 24894,\n    \"Ġbravery\": 24895,\n    \"Ġviolin\": 24896,\n    \"Ġdelightful\": 24897,\n    \"Ġticks\": 24898,\n    \"iton\": 24899,\n    \"Ġreap\": 24900,\n    \"Ġoversized\": 24901,\n    \"ĠPitch\": 24902,\n    \"Ġprized\": 24903,\n    \"Ġfusion\": 24904,\n    \"fact\": 24905,\n    \"acting\": 24906,\n    \"Ġfullback\": 24907,\n    \"Ġpolite\": 24908,\n    \"Ġswear\": 24909,\n    \"Ġconfiscated\": 24910,\n    \"ĠStud\": 24911,\n    \"Ġfielded\": 24912,\n    \"rito\": 24913,\n    \"covered\": 24914,\n    \"financial\": 24915,\n    \"bill\": 24916,\n    \"HK\": 24917,\n    \"OTOS\": 24918,\n    \"loaded\": 24919,\n    \"Ġmarble\": 24920,\n    \"ĠDiplom\": 24921,\n    \".âĢĶ\": 24922,\n    \"Ġeats\": 24923,\n    \"Ġbackfield\": 24924,\n    \"Ġtimeframe\": 24925,\n    \"Ġvegetarian\": 24926,\n    \"Ġswaps\": 24927,\n    \"ĠMines\": 24928,\n    \"igor\": 24929,\n    \"ĠLenn\": 24930,\n    \"ĠDP\": 24931,\n    \"ordered\": 24932,\n    \"ĠShark\": 24933,\n    \"Ġquant\": 24934,\n    \"erence\": 24935,\n    \"Ġashes\": 24936,\n    \"ĠBuckley\": 24937,\n    \"ophobia\": 24938,\n    \"Ġwarranted\": 24939,\n    \"Rose\": 24940,\n    \"Ġunreasonable\": 24941,\n    \"ĠJav\": 24942,\n    \"Ġpalette\": 24943,\n    \"Ġjoints\": 24944,\n    \"Ġadvent\": 24945,\n    \"Ġnoteworthy\": 24946,\n    \"ĠNicol\": 24947,\n    \"ĠChristensen\": 24948,\n    \"Ġplummeted\": 24949,\n    \"ayers\": 24950,\n    \"Ġdefends\": 24951,\n    \"Ġcontended\": 24952,\n    \"ĠCongratulations\": 24953,\n    \"kish\": 24954,\n    \"ĠHannity\": 24955,\n    \"Ġgroundwater\": 24956,\n    \"ĠKramer\": 24957,\n    \"Ġerect\": 24958,\n    \"Ġappet\": 24959,\n    \"ĠKardash\": 24960,\n    \"Ġexacerbated\": 24961,\n    \"Ġexplanations\": 24962,\n    \"vious\": 24963,\n    \"eport\": 24964,\n    \"---\": 24965,\n    \"icism\": 24966,\n    \"ĠNatasha\": 24967,\n    \"ĠGeoffrey\": 24968,\n    \"estro\": 24969,\n    \"Article\": 24970,\n    \"Ġincidence\": 24971,\n    \"Ġprovoked\": 24972,\n    \"elf\": 24973,\n    \"Ġinsistence\": 24974,\n    \"ĠOUR\": 24975,\n    \"Ġfertilizer\": 24976,\n    \"Ġstickers\": 24977,\n    \"ĠGators\": 24978,\n    \"ĠLanding\": 24979,\n    \"ĠDON\": 24980,\n    \"sta\": 24981,\n    \"ĠRobbins\": 24982,\n    \"Ġpixels\": 24983,\n    \"ĠHoy\": 24984,\n    \"imated\": 24985,\n    \"ĠÃī\": 24986,\n    \"â\": 24987,\n    \"Ġsimpl\": 24988,\n    \"Other\": 24989,\n    \"245\": 24990,\n    \"Ġforcibly\": 24991,\n    \"'.\\\"\": 24992,\n    \"Ġsmashing\": 24993,\n    \"Ġmosquitoes\": 24994,\n    \"Ġpaints\": 24995,\n    \"Ġdebating\": 24996,\n    \"enty\": 24997,\n    \"ĠIB\": 24998,\n    \"leaf\": 24999,\n    \"ĠDah\": 25000,\n    \"Ġreferral\": 25001,\n    \"pired\": 25002,\n    \"Ġbrunch\": 25003,\n    \"gie\": 25004,\n    \"Ġvict\": 25005,\n    \"ribute\": 25006,\n    \"Ġbloggers\": 25007,\n    \"Ġgum\": 25008,\n    \"ĠAdmiral\": 25009,\n    \"France\": 25010,\n    \"ĠPK\": 25011,\n    \"ĠSaturn\": 25012,\n    \"Ġinflated\": 25013,\n    \"WAR\": 25014,\n    \"Ġscenic\": 25015,\n    \"usal\": 25016,\n    \"their\": 25017,\n    \"Ġcontends\": 25018,\n    \"Ġpathways\": 25019,\n    \"inis\": 25020,\n    \"Ġawarding\": 25021,\n    \"Ġmisled\": 25022,\n    \"Ġeternal\": 25023,\n    \"Ġexaminations\": 25024,\n    \"Ġpoker\": 25025,\n    \"Ġsafest\": 25026,\n    \"Ġchildcare\": 25027,\n    \"aday\": 25028,\n    \"Ġpreceding\": 25029,\n    \"ĠCollective\": 25030,\n    \"Ġrespectable\": 25031,\n    \"ographical\": 25032,\n    \"Ġoak\": 25033,\n    \"00000\": 25034,\n    \"ĠCorridor\": 25035,\n    \"oran\": 25036,\n    \"133\": 25037,\n    \"Ġmushrooms\": 25038,\n    \"gaard\": 25039,\n    \"ĠOmega\": 25040,\n    \"ĠNaturally\": 25041,\n    \"anim\": 25042,\n    \"Ġcaptains\": 25043,\n    \"Ġtang\": 25044,\n    \"Ġlobbyists\": 25045,\n    \"ĠSug\": 25046,\n    \"Ġsucc\": 25047,\n    \"249\": 25048,\n    \"ENG\": 25049,\n    \"134\": 25050,\n    \"Ġsolic\": 25051,\n    \"ĠAdded\": 25052,\n    \"ĠSuicide\": 25053,\n    \"ĠFULL\": 25054,\n    \"ĠStrauss\": 25055,\n    \"ĠDiesel\": 25056,\n    \"Ġtempting\": 25057,\n    \"acist\": 25058,\n    \"ĠDelivery\": 25059,\n    \"Ġquiz\": 25060,\n    \"ĠPARK\": 25061,\n    \"Ġcollisions\": 25062,\n    \"Ġrestrained\": 25063,\n    \"purpose\": 25064,\n    \"ĠChanges\": 25065,\n    \"Ġabsentee\": 25066,\n    \"Ġprobes\": 25067,\n    \"hib\": 25068,\n    \"Ġcul\": 25069,\n    \"Ġpetty\": 25070,\n    \"Ġnecess\": 25071,\n    \"Ġcues\": 25072,\n    \"OME\": 25073,\n    \"Ġinadvertently\": 25074,\n    \"urity\": 25075,\n    \"ĠStuff\": 25076,\n    \"FG\": 25077,\n    \"Ġwrestlers\": 25078,\n    \"Ġpaste\": 25079,\n    \"ĠRoku\": 25080,\n    \"Ġcardboard\": 25081,\n    \"aires\": 25082,\n    \"Ġvariables\": 25083,\n    \"ĠSaras\": 25084,\n    \"ĠFif\": 25085,\n    \"Ġinvests\": 25086,\n    \"ĠDiscover\": 25087,\n    \"ĠFix\": 25088,\n    \"Thomas\": 25089,\n    \"ĠLunch\": 25090,\n    \"lv\": 25091,\n    \"camera\": 25092,\n    \"Step\": 25093,\n    \"Ġresumes\": 25094,\n    \"ĠSacred\": 25095,\n    \"ĠShooting\": 25096,\n    \"Ġnoble\": 25097,\n    \"Ġslopes\": 25098,\n    \"Ġont\": 25099,\n    \"Ġtwists\": 25100,\n    \"Very\": 25101,\n    \"Ġbigotry\": 25102,\n    \"ĠTib\": 25103,\n    \"Ġmos\": 25104,\n    \"Ġwarrior\": 25105,\n    \"Ġbroadcasters\": 25106,\n    \"Ġubiquitous\": 25107,\n    \"ameda\": 25108,\n    \"Ġchess\": 25109,\n    \"Special\": 25110,\n    \"Ġconver\": 25111,\n    \"Ġdeleg\": 25112,\n    \"endant\": 25113,\n    \"Ġfoil\": 25114,\n    \"Ġlush\": 25115,\n    \"Ġtaxed\": 25116,\n    \"Mag\": 25117,\n    \"ahs\": 25118,\n    \"Ġtablespoons\": 25119,\n    \"scription\": 25120,\n    \"clamation\": 25121,\n    \"ĠCertain\": 25122,\n    \"ĠDiversity\": 25123,\n    \"Ġhairst\": 25124,\n    \"ĠBrewery\": 25125,\n    \"Ġshedding\": 25126,\n    \"Cla\": 25127,\n    \"Ġpenis\": 25128,\n    \"ĠMurder\": 25129,\n    \"Park\": 25130,\n    \"uner\": 25131,\n    \"iments\": 25132,\n    \"ĠOVER\": 25133,\n    \"hus\": 25134,\n    \"Ġtabloid\": 25135,\n    \"Chart\": 25136,\n    \"Ġvouchers\": 25137,\n    \"ĠCoord\": 25138,\n    \"Ġmethane\": 25139,\n    \"ĠFisheries\": 25140,\n    \"ĠKham\": 25141,\n    \"includes\": 25142,\n    \"ĠSuperman\": 25143,\n    \"ensed\": 25144,\n    \"isure\": 25145,\n    \"Amazon\": 25146,\n    \"Ġvacated\": 25147,\n    \"heet\": 25148,\n    \"Ġroast\": 25149,\n    \"Ġlegalize\": 25150,\n    \"ĠTut\": 25151,\n    \"Ġsignage\": 25152,\n    \"init\": 25153,\n    \"Ġthefts\": 25154,\n    \"202\": 25155,\n    \"Ġstatic\": 25156,\n    \"Ġchants\": 25157,\n    \"Bob\": 25158,\n    \"Ġdiscretionary\": 25159,\n    \"Ġendurance\": 25160,\n    \"Ġcollegiate\": 25161,\n    \"Ġcorridors\": 25162,\n    \"Ġslack\": 25163,\n    \"ĠLash\": 25164,\n    \"Az\": 25165,\n    \"Series\": 25166,\n    \"Ġnonpartisan\": 25167,\n    \"ĠMcGill\": 25168,\n    \"Ġuneven\": 25169,\n    \"ulsive\": 25170,\n    \"eu\": 25171,\n    \"Ġpil\": 25172,\n    \"Ġfisheries\": 25173,\n    \"Ġonslaught\": 25174,\n    \"fiction\": 25175,\n    \"holding\": 25176,\n    \"Ġcheated\": 25177,\n    \"Ġtraumat\": 25178,\n    \"lasting\": 25179,\n    \"Ġmultitude\": 25180,\n    \"ĠThr\": 25181,\n    \"ĠBreast\": 25182,\n    \"Ġ1600\": 25183,\n    \"ĠMatth\": 25184,\n    \"Ġdiminish\": 25185,\n    \"ĠFTC\": 25186,\n    \"Ġgram\": 25187,\n    \"ĠResident\": 25188,\n    \"Ġfading\": 25189,\n    \"Ġmarginalized\": 25190,\n    \"ĠLite\": 25191,\n    \"ĠCarlton\": 25192,\n    \"Ġerad\": 25193,\n    \"Welcome\": 25194,\n    \"ĠFaw\": 25195,\n    \"iddy\": 25196,\n    \"Ġparticip\": 25197,\n    \"Ġcz\": 25198,\n    \"Ġtexted\": 25199,\n    \"Ġsuites\": 25200,\n    \"ĠForever\": 25201,\n    \"Ġrendition\": 25202,\n    \"rait\": 25203,\n    \"ĠPrague\": 25204,\n    \"Ġsponsoring\": 25205,\n    \"Ġcompos\": 25206,\n    \"ĠBeacon\": 25207,\n    \"144\": 25208,\n    \"Ġpupil\": 25209,\n    \"Ġintricate\": 25210,\n    \"Ġathleticism\": 25211,\n    \"Ġoptimization\": 25212,\n    \"Ġloot\": 25213,\n    \"polit\": 25214,\n    \"ĠOtt\": 25215,\n    \"Whatever\": 25216,\n    \"uno\": 25217,\n    \"ĠConstable\": 25218,\n    \"esville\": 25219,\n    \"Ġlookout\": 25220,\n    \"ĠAircraft\": 25221,\n    \"Ġspo\": 25222,\n    \"Ġcorrobor\": 25223,\n    \"Ġhiatus\": 25224,\n    \"ĠKnowing\": 25225,\n    \"ĠHamp\": 25226,\n    \"Ġspe\": 25227,\n    \"Ġstoring\": 25228,\n    \"Ġshakes\": 25229,\n    \"uran\": 25230,\n    \"Ġsickness\": 25231,\n    \"Ġliber\": 25232,\n    \"ĠAdministrative\": 25233,\n    \"Ġpleasing\": 25234,\n    \"ĠEqual\": 25235,\n    \"ĠConversation\": 25236,\n    \"Ġalgae\": 25237,\n    \"Ġlobbyist\": 25238,\n    \"ĠHelena\": 25239,\n    \"ptions\": 25240,\n    \"Ġfaire\": 25241,\n    \"ĠGone\": 25242,\n    \"ĠWiggins\": 25243,\n    \"Robert\": 25244,\n    \"Ġlistens\": 25245,\n    \"ĠDaisy\": 25246,\n    \"Ġsticky\": 25247,\n    \"sale\": 25248,\n    \"ĠMarijuana\": 25249,\n    \"ĠSSD\": 25250,\n    \"ĠTool\": 25251,\n    \"once\": 25252,\n    \"ĠHarmon\": 25253,\n    \"mobile\": 25254,\n    \"Ġdetain\": 25255,\n    \"Money\": 25256,\n    \"Ġflawless\": 25257,\n    \"forced\": 25258,\n    \"Ġguru\": 25259,\n    \"Ġairspace\": 25260,\n    \"ĠArchie\": 25261,\n    \"ĠGender\": 25262,\n    \"ĠMeat\": 25263,\n    \"abilities\": 25264,\n    \"ĠBD\": 25265,\n    \"Open\": 25266,\n    \"Ġoutsider\": 25267,\n    \"issue\": 25268,\n    \"Ġlearns\": 25269,\n    \"natural\": 25270,\n    \"Ġvinegar\": 25271,\n    \"ĠSUB\": 25272,\n    \"ĠRecon\": 25273,\n    \"blers\": 25274,\n    \"Ġsniff\": 25275,\n    \"Ġsuppression\": 25276,\n    \"Ġsaf\": 25277,\n    \"urger\": 25278,\n    \"Ġbunker\": 25279,\n    \"asaki\": 25280,\n    \"ĠSpartan\": 25281,\n    \"ĠTok\": 25282,\n    \"Ġrav\": 25283,\n    \"Ġfoc\": 25284,\n    \"Sean\": 25285,\n    \"etric\": 25286,\n    \"Ġballpark\": 25287,\n    \"ĠHerb\": 25288,\n    \"ĠBM\": 25289,\n    \"ĠPublishing\": 25290,\n    \"Ġroadmap\": 25291,\n    \"pered\": 25292,\n    \"Ġpredator\": 25293,\n    \"ĠBlockchain\": 25294,\n    \"Ġvalidity\": 25295,\n    \"ĠGlou\": 25296,\n    \"ĠYamaha\": 25297,\n    \"Ġadop\": 25298,\n    \"Ġswamp\": 25299,\n    \"Ġcomplied\": 25300,\n    \"Ky\": 25301,\n    \"Greg\": 25302,\n    \"casts\": 25303,\n    \"john\": 25304,\n    \"ĠBosnia\": 25305,\n    \"Ġcinematic\": 25306,\n    \"ĠTavern\": 25307,\n    \"Ġfrustrations\": 25308,\n    \"eryl\": 25309,\n    \"Ġfairy\": 25310,\n    \"UNCH\": 25311,\n    \"ĠTus\": 25312,\n    \"Corp\": 25313,\n    \"ĠNug\": 25314,\n    \"closed\": 25315,\n    \"Ġexercised\": 25316,\n    \"urden\": 25317,\n    \"Ġdigitally\": 25318,\n    \"137\": 25319,\n    \"ĠVictims\": 25320,\n    \"Ġreluctance\": 25321,\n    \"ELL\": 25322,\n    \"ĠTribe\": 25323,\n    \"chall\": 25324,\n    \"Ġwhiskey\": 25325,\n    \"ogl\": 25326,\n    \"Ġmater\": 25327,\n    \"ĠBac\": 25328,\n    \"Ġapartheid\": 25329,\n    \"ĠMBA\": 25330,\n    \"mot\": 25331,\n    \"ĠIre\": 25332,\n    \"Â®,\": 25333,\n    \"ĠChic\": 25334,\n    \"Ġtimed\": 25335,\n    \"ĠDome\": 25336,\n    \"efer\": 25337,\n    \"Ġobserver\": 25338,\n    \"unky\": 25339,\n    \"ĠKant\": 25340,\n    \"Ġundrafted\": 25341,\n    \"Ġsimplicity\": 25342,\n    \"onds\": 25343,\n    \"Ġstoked\": 25344,\n    \"Ġ1949\": 25345,\n    \"Ġransomware\": 25346,\n    \"ĠPow\": 25347,\n    \"ĠAngelo\": 25348,\n    \"ĠAmbrose\": 25349,\n    \"adjusted\": 25350,\n    \"Guard\": 25351,\n    \"138\": 25352,\n    \"ĠKaplan\": 25353,\n    \"stri\": 25354,\n    \"Ġcries\": 25355,\n    \"NF\": 25356,\n    \"atro\": 25357,\n    \"Ġavocado\": 25358,\n    \"illian\": 25359,\n    \"Ġsculptures\": 25360,\n    \"Ġelevation\": 25361,\n    \"Ġinspires\": 25362,\n    \"Ġgenerals\": 25363,\n    \"arb\": 25364,\n    \"chell\": 25365,\n    \"ĠJournalism\": 25366,\n    \"ĠHybrid\": 25367,\n    \"ĠCaller\": 25368,\n    \"vec\": 25369,\n    \"Lu\": 25370,\n    \"Ġresemble\": 25371,\n    \"bys\": 25372,\n    \"erving\": 25373,\n    \"antz\": 25374,\n    \"Ġwiden\": 25375,\n    \"vised\": 25376,\n    \"Ev\": 25377,\n    \"Ġdiagn\": 25378,\n    \"ĠMakes\": 25379,\n    \"Ġcer\": 25380,\n    \"ĠPats\": 25381,\n    \"single\": 25382,\n    \"sche\": 25383,\n    \"struct\": 25384,\n    \"Ġdissolved\": 25385,\n    \"Ġtimeout\": 25386,\n    \"Ġenhancement\": 25387,\n    \"CF\": 25388,\n    \"Ġindust\": 25389,\n    \"ĠDed\": 25390,\n    \"ĠZo\": 25391,\n    \"CB\": 25392,\n    \"Ġpesticides\": 25393,\n    \"ĠRubin\": 25394,\n    \"George\": 25395,\n    \"opal\": 25396,\n    \"Ġmotel\": 25397,\n    \"critical\": 25398,\n    \"Ġcollapsing\": 25399,\n    \"ĠShal\": 25400,\n    \"tex\": 25401,\n    \"Ġcomplementary\": 25402,\n    \"Ġoust\": 25403,\n    \"ĠFlu\": 25404,\n    \"Ġexporting\": 25405,\n    \"Ġdifferential\": 25406,\n    \"north\": 25407,\n    \"ĠFG\": 25408,\n    \"Ġspoon\": 25409,\n    \"sha\": 25410,\n    \"Ġdismantle\": 25411,\n    \"elta\": 25412,\n    \"Ġjar\": 25413,\n    \"space\": 25414,\n    \"Smart\": 25415,\n    \"mere\": 25416,\n    \"Ð\": 25417,\n    \"ĠGillespie\": 25418,\n    \"Lo\": 25419,\n    \"ĠMead\": 25420,\n    \"capacity\": 25421,\n    \"ĠIssue\": 25422,\n    \"050\": 25423,\n    \"ĠVall\": 25424,\n    \"Ġdisgr\": 25425,\n    \"Ġmeme\": 25426,\n    \"Ġpard\": 25427,\n    \"Ġcompensated\": 25428,\n    \"ĠKet\": 25429,\n    \"major\": 25430,\n    \"ĠBren\": 25431,\n    \"Ġheed\": 25432,\n    \"131\": 25433,\n    \"Ġcm\": 25434,\n    \"Ġdazzling\": 25435,\n    \"ĠCheese\": 25436,\n    \"Ġmonumental\": 25437,\n    \"Ġyielding\": 25438,\n    \"Read\": 25439,\n    \"Ġgrinding\": 25440,\n    \"Ang\": 25441,\n    \"Ġdefiance\": 25442,\n    \"Ġintimidated\": 25443,\n    \"Ġ310\": 25444,\n    \"Ġoutsiders\": 25445,\n    \"houn\": 25446,\n    \"Ma\": 25447,\n    \"ĸ\": 25448,\n    \"ĠForget\": 25449,\n    \"ĠSans\": 25450,\n    \"Ġunfolding\": 25451,\n    \"ĠSap\": 25452,\n    \"ĠLak\": 25453,\n    \"Ġsectarian\": 25454,\n    \"ĠDaddy\": 25455,\n    \"oxy\": 25456,\n    \"hitting\": 25457,\n    \"Ġdetectors\": 25458,\n    \"ĠRee\": 25459,\n    \"Ġbroaden\": 25460,\n    \"Ġslaying\": 25461,\n    \"Ġsuspending\": 25462,\n    \"Ġinvestig\": 25463,\n    \"Tuesday\": 25464,\n    \"Ġantibiotic\": 25465,\n    \"ĠShiite\": 25466,\n    \"igi\": 25467,\n    \"ĠExternal\": 25468,\n    \"ĠPhotographer\": 25469,\n    \"Ġerratic\": 25470,\n    \"NJ\": 25471,\n    \"ĠDock\": 25472,\n    \"Ġoutweigh\": 25473,\n    \"rants\": 25474,\n    \"Ġlobster\": 25475,\n    \"Ġreactor\": 25476,\n    \"Ġunrealistic\": 25477,\n    \"ĠAudrey\": 25478,\n    \"ĠYor\": 25479,\n    \"Anyone\": 25480,\n    \"Ġfraught\": 25481,\n    \"Ðµ\": 25482,\n    \"ĠWester\": 25483,\n    \"fc\": 25484,\n    \"ĠDunham\": 25485,\n    \"ĠLug\": 25486,\n    \"allow\": 25487,\n    \"139\": 25488,\n    \"Ġparity\": 25489,\n    \"Ġhorizontal\": 25490,\n    \"ijuana\": 25491,\n    \"Ġcivilization\": 25492,\n    \"ĠGins\": 25493,\n    \"Ġsmokers\": 25494,\n    \"ĠDiabetes\": 25495,\n    \"Five\": 25496,\n    \"ĠDG\": 25497,\n    \"Ġunderscores\": 25498,\n    \"Ġelabor\": 25499,\n    \"ĠLub\": 25500,\n    \"ĠDevil\": 25501,\n    \"Ġ154\": 25502,\n    \"ĠGuarant\": 25503,\n    \"ĠPandora\": 25504,\n    \"Ġexcav\": 25505,\n    \"Ġaccuser\": 25506,\n    \"Ġrevolt\": 25507,\n    \"Ġinstructors\": 25508,\n    \"Ġire\": 25509,\n    \"ographic\": 25510,\n    \"ĠCLE\": 25511,\n    \"Ġexpedition\": 25512,\n    \"ould\": 25513,\n    \"Ġstriving\": 25514,\n    \"south\": 25515,\n    \"onis\": 25516,\n    \"ĠSwed\": 25517,\n    \"MY\": 25518,\n    \"ĠLevin\": 25519,\n    \"Ġcarp\": 25520,\n    \"ĠArchitects\": 25521,\n    \"Ġ{\": 25522,\n    \"Ġcovert\": 25523,\n    \"Ġcooled\": 25524,\n    \"ĠStaten\": 25525,\n    \"Ġspecializing\": 25526,\n    \"ĠHazel\": 25527,\n    \"Ġlen\": 25528,\n    \"ighty\": 25529,\n    \"Ġbrilliantly\": 25530,\n    \"Phil\": 25531,\n    \"Ġlament\": 25532,\n    \"Australia\": 25533,\n    \"203\": 25534,\n    \"Ġticking\": 25535,\n    \"Ġadjud\": 25536,\n    \"Ġroommate\": 25537,\n    \"ĠSheet\": 25538,\n    \"capital\": 25539,\n    \"167\": 25540,\n    \"Ġendeavor\": 25541,\n    \"Ġaver\": 25542,\n    \"Ġdues\": 25543,\n    \"ĠCycl\": 25544,\n    \"oried\": 25545,\n    \"Va\": 25546,\n    \"loading\": 25547,\n    \"Ġpremie\": 25548,\n    \"Ġregimes\": 25549,\n    \"ĠAly\": 25550,\n    \"Ġperennial\": 25551,\n    \"Ġconsoles\": 25552,\n    \"Ġironic\": 25553,\n    \"ichael\": 25554,\n    \"Ġvigorously\": 25555,\n    \"Ġtransmit\": 25556,\n    \"gary\": 25557,\n    \"eking\": 25558,\n    \"Ġjails\": 25559,\n    \"ĠEpiscopal\": 25560,\n    \"eddy\": 25561,\n    \"Ġidle\": 25562,\n    \"Ġsafeguards\": 25563,\n    \"Ġdwindling\": 25564,\n    \"NOR\": 25565,\n    \"torn\": 25566,\n    \"ĠEvangel\": 25567,\n    \"ĠPlastic\": 25568,\n    \"ĠTerm\": 25569,\n    \"Ġforwarded\": 25570,\n    \"avage\": 25571,\n    \"Ġrefrigerator\": 25572,\n    \"arna\": 25573,\n    \"ĠGuinness\": 25574,\n    \"ĠCandy\": 25575,\n    \"Ġbotched\": 25576,\n    \"seller\": 25577,\n    \"Ġpul\": 25578,\n    \"grades\": 25579,\n    \"oshenko\": 25580,\n    \"earth\": 25581,\n    \"nette\": 25582,\n    \"Ġtraps\": 25583,\n    \"Ġtarn\": 25584,\n    \"Ġmilitar\": 25585,\n    \"ĠAriel\": 25586,\n    \"Ġtubes\": 25587,\n    \"ulo\": 25588,\n    \"Water\": 25589,\n    \"edin\": 25590,\n    \"Ġmarvel\": 25591,\n    \"chenko\": 25592,\n    \"ĠElk\": 25593,\n    \"spect\": 25594,\n    \"coe\": 25595,\n    \"ĠIllustrated\": 25596,\n    \"Ġruthless\": 25597,\n    \"etermined\": 25598,\n    \"Ġdys\": 25599,\n    \"Ġbreaching\": 25600,\n    \"gee\": 25601,\n    \"Nick\": 25602,\n    \"Ġcruiser\": 25603,\n    \"Ġciv\": 25604,\n    \"Ġdou\": 25605,\n    \"Ġ;\": 25606,\n    \"deb\": 25607,\n    \"ĠAsheville\": 25608,\n    \"Ġbiting\": 25609,\n    \"Ġyo\": 25610,\n    \"Courtesy\": 25611,\n    \"Ġroses\": 25612,\n    \"ĠConsequently\": 25613,\n    \"Ġrevis\": 25614,\n    \"Ġconfinement\": 25615,\n    \"next\": 25616,\n    \"produced\": 25617,\n    \"Ġmoratorium\": 25618,\n    \"Ġkne\": 25619,\n    \"eties\": 25620,\n    \"Ġplethora\": 25621,\n    \"Ġceleb\": 25622,\n    \"FIN\": 25623,\n    \"Ġdepartures\": 25624,\n    \"ĠWynne\": 25625,\n    \"abilia\": 25626,\n    \"ĠCourts\": 25627,\n    \"olis\": 25628,\n    \"Ġcereal\": 25629,\n    \"Ġblended\": 25630,\n    \"333\": 25631,\n    \"ĠLun\": 25632,\n    \"Ġrepe\": 25633,\n    \"Ġmathematics\": 25634,\n    \"Ġpharmacies\": 25635,\n    \"Center\": 25636,\n    \"Ġwhist\": 25637,\n    \"pine\": 25638,\n    \"Ġperm\": 25639,\n    \"Ġcustomary\": 25640,\n    \"Ġhormones\": 25641,\n    \"Ġcleansing\": 25642,\n    \"Ġconfidentiality\": 25643,\n    \"Ġmascot\": 25644,\n    \"Ġslippery\": 25645,\n    \"Ġmediation\": 25646,\n    \"Ġpodcasts\": 25647,\n    \"Ġcoating\": 25648,\n    \"Ġconveyed\": 25649,\n    \"Ġgir\": 25650,\n    \"ĠNurse\": 25651,\n    \"DM\": 25652,\n    \"Ġlured\": 25653,\n    \"orted\": 25654,\n    \"Ġolig\": 25655,\n    \"ritz\": 25656,\n    \"ĠINF\": 25657,\n    \"Ġtirelessly\": 25658,\n    \"Ġdoorstep\": 25659,\n    \"Ġtomb\": 25660,\n    \"Ġwithholding\": 25661,\n    \"irling\": 25662,\n    \"Ġhog\": 25663,\n    \"Ġ156\": 25664,\n    \"Ġgau\": 25665,\n    \"chem\": 25666,\n    \"raid\": 25667,\n    \"Ġtrolls\": 25668,\n    \"Ġ182\": 25669,\n    \"ĠColumb\": 25670,\n    \"Ġtissues\": 25671,\n    \"Ġnaive\": 25672,\n    \"Ġlect\": 25673,\n    \"Central\": 25674,\n    \"Sign\": 25675,\n    \"168\": 25676,\n    \"Ġbribe\": 25677,\n    \"ĠDoll\": 25678,\n    \"ĠTripoli\": 25679,\n    \"Ġfunk\": 25680,\n    \"Ġplaza\": 25681,\n    \"Ġmechanic\": 25682,\n    \"mem\": 25683,\n    \"Ġmonkey\": 25684,\n    \"grid\": 25685,\n    \"Ġtainted\": 25686,\n    \"ĠNicaragua\": 25687,\n    \"pelling\": 25688,\n    \"ĠXia\": 25689,\n    \"ammers\": 25690,\n    \"Ġorth\": 25691,\n    \"ICAN\": 25692,\n    \"Ġrant\": 25693,\n    \"Ġdiary\": 25694,\n    \"ĠHarrington\": 25695,\n    \"Ġimply\": 25696,\n    \"Qaeda\": 25697,\n    \"Ġworsen\": 25698,\n    \"Ġcrafting\": 25699,\n    \"ĠShir\": 25700,\n    \"Ġcoincided\": 25701,\n    \"Ġsnatched\": 25702,\n    \"ileen\": 25703,\n    \"sei\": 25704,\n    \"Ġsurgeons\": 25705,\n    \"directed\": 25706,\n    \"Ġcompulsory\": 25707,\n    \"Ġnowadays\": 25708,\n    \"ĠLI\": 25709,\n    \"ĠRebel\": 25710,\n    \"Ġlions\": 25711,\n    \"ĠJR\": 25712,\n    \"scar\": 25713,\n    \"ĠRespons\": 25714,\n    \"Ġscroll\": 25715,\n    \"ĠErd\": 25716,\n    \"iety\": 25717,\n    \"\\\";\": 25718,\n    \"ĠBone\": 25719,\n    \"ĠRumble\": 25720,\n    \"ĠKS\": 25721,\n    \"ĠLaur\": 25722,\n    \"kell\": 25723,\n    \"ĠBirds\": 25724,\n    \"agic\": 25725,\n    \"Ġsimmer\": 25726,\n    \"Ġrunaway\": 25727,\n    \"Ġ162\": 25728,\n    \"auna\": 25729,\n    \"Ġdialog\": 25730,\n    \"Ġlouder\": 25731,\n    \"esque\": 25732,\n    \"RR\": 25733,\n    \"Ġbloss\": 25734,\n    \"Ġcaliber\": 25735,\n    \"nery\": 25736,\n    \"Ġhauled\": 25737,\n    \"Ġbacterial\": 25738,\n    \"ĠVanity\": 25739,\n    \"ĠPrograms\": 25740,\n    \"omew\": 25741,\n    \"ĠMama\": 25742,\n    \"Ġarr\": 25743,\n    \"Ġdod\": 25744,\n    \"ĠJarvis\": 25745,\n    \"ĠFIRST\": 25746,\n    \"Ġinjections\": 25747,\n    \"ĠBallard\": 25748,\n    \"Ġmedically\": 25749,\n    \"angan\": 25750,\n    \"ĠNewfoundland\": 25751,\n    \"Ġfracking\": 25752,\n    \"Ġbast\": 25753,\n    \"outing\": 25754,\n    \"Ġmercury\": 25755,\n    \"Ġwatershed\": 25756,\n    \"ĠAmateur\": 25757,\n    \"Ġ153\": 25758,\n    \"escal\": 25759,\n    \"Ġpainter\": 25760,\n    \"creat\": 25761,\n    \"Ġperceive\": 25762,\n    \"Ġgent\": 25763,\n    \"attacks\": 25764,\n    \"worked\": 25765,\n    \"Ġimporting\": 25766,\n    \"Indian\": 25767,\n    \"Ġconvict\": 25768,\n    \"clad\": 25769,\n    \"Ġbudding\": 25770,\n    \"Ġambient\": 25771,\n    \"ĠWitness\": 25772,\n    \"letes\": 25773,\n    \"Ġbuffet\": 25774,\n    \"Ġneedles\": 25775,\n    \"Ġcoding\": 25776,\n    \"Ġchoke\": 25777,\n    \"Ġcorrespondence\": 25778,\n    \"Ġgods\": 25779,\n    \"Ġdances\": 25780,\n    \"Ġsteadfast\": 25781,\n    \"cert\": 25782,\n    \"Ġroaming\": 25783,\n    \"between\": 25784,\n    \"weak\": 25785,\n    \"Jer\": 25786,\n    \"jandro\": 25787,\n    \"Ġdiscouraged\": 25788,\n    \"Ġfruition\": 25789,\n    \"ĠØ\": 25790,\n    \"ĠKop\": 25791,\n    \"ULL\": 25792,\n    \"efe\": 25793,\n    \"imble\": 25794,\n    \"obb\": 25795,\n    \"ulla\": 25796,\n    \"Ġaccredited\": 25797,\n    \"Ġlectures\": 25798,\n    \"bil\": 25799,\n    \"why\": 25800,\n    \"Ġgreeting\": 25801,\n    \"ĠBoost\": 25802,\n    \"Ġmailed\": 25803,\n    \"Ġtroop\": 25804,\n    \"Ġfrig\": 25805,\n    \"Ġrese\": 25806,\n    \"Ġscratched\": 25807,\n    \"Stars\": 25808,\n    \"ĠRailroad\": 25809,\n    \"ĠIdol\": 25810,\n    \"Ġsuccumbed\": 25811,\n    \"ĠWeeks\": 25812,\n    \"ffe\": 25813,\n    \"Ġjihadist\": 25814,\n    \"ITION\": 25815,\n    \"Ġthreads\": 25816,\n    \"ĠGenerally\": 25817,\n    \"Ġmedieval\": 25818,\n    \"Ġquotas\": 25819,\n    \"ĠFerry\": 25820,\n    \"rique\": 25821,\n    \"Ġprod\": 25822,\n    \"ĠEduc\": 25823,\n    \"rive\": 25824,\n    \"Ġensued\": 25825,\n    \"Cy\": 25826,\n    \"Ġinfring\": 25827,\n    \"Ġprank\": 25828,\n    \"Ġfrontline\": 25829,\n    \"Ġcompletes\": 25830,\n    \"upe\": 25831,\n    \"Ġmanageable\": 25832,\n    \"Ġpoems\": 25833,\n    \"otten\": 25834,\n    \"igne\": 25835,\n    \"threat\": 25836,\n    \"ĠDri\": 25837,\n    \"ĠLINK\": 25838,\n    \"Calif\": 25839,\n    \"ĠDos\": 25840,\n    \"ulent\": 25841,\n    \"Ġaids\": 25842,\n    \"Ġslips\": 25843,\n    \"umped\": 25844,\n    \"Ġstyled\": 25845,\n    \"Ġdisproportionately\": 25846,\n    \"ĠDish\": 25847,\n    \"ĠUncle\": 25848,\n    \"andel\": 25849,\n    \"Ġrecharge\": 25850,\n    \"rators\": 25851,\n    \"ĠSPR\": 25852,\n    \"Ġguarded\": 25853,\n    \"ĠGreatest\": 25854,\n    \"ĠSkills\": 25855,\n    \"ĠNob\": 25856,\n    \"ĠDesk\": 25857,\n    \"ĠCros\": 25858,\n    \"Ġwrit\": 25859,\n    \"Ġquery\": 25860,\n    \"ORTS\": 25861,\n    \"Ġbundled\": 25862,\n    \"Ġgib\": 25863,\n    \"Ġeth\": 25864,\n    \"iesta\": 25865,\n    \"Ġevade\": 25866,\n    \"dict\": 25867,\n    \"straight\": 25868,\n    \"Met\": 25869,\n    \"present\": 25870,\n    \"Ġdiff\": 25871,\n    \"Ġdere\": 25872,\n    \"ĠSpl\": 25873,\n    \"Ġrepr\": 25874,\n    \"ĠBeard\": 25875,\n    \"Ġvain\": 25876,\n    \"Ġappointing\": 25877,\n    \"ĠVisual\": 25878,\n    \"caps\": 25879,\n    \"gado\": 25880,\n    \"ĠRican\": 25881,\n    \"ĠPose\": 25882,\n    \"endor\": 25883,\n    \"Ġ222\": 25884,\n    \"ĠLear\": 25885,\n    \"Ġconstructing\": 25886,\n    \"Dan\": 25887,\n    \"ĠSpears\": 25888,\n    \"ĠTherapy\": 25889,\n    \"pta\": 25890,\n    \"Ġrehabilit\": 25891,\n    \"Ġrisked\": 25892,\n    \"ĠGuer\": 25893,\n    \"HF\": 25894,\n    \"Ġ301\": 25895,\n    \"Ġliking\": 25896,\n    \"Ġmodular\": 25897,\n    \"eree\": 25898,\n    \"ĠMAT\": 25899,\n    \"ĠHomeless\": 25900,\n    \"Ġstove\": 25901,\n    \"erd\": 25902,\n    \"hash\": 25903,\n    \"ĠAchilles\": 25904,\n    \"ĠBeta\": 25905,\n    \"Ġincl\": 25906,\n    \"Ġgunned\": 25907,\n    \"ĠCrab\": 25908,\n    \"ĠMara\": 25909,\n    \"Ġinvaded\": 25910,\n    \"ulatory\": 25911,\n    \"ATA\": 25912,\n    \"angering\": 25913,\n    \"onso\": 25914,\n    \"Ġallocate\": 25915,\n    \"Ġgarment\": 25916,\n    \"itudes\": 25917,\n    \"ĠHuang\": 25918,\n    \"Ġstaples\": 25919,\n    \"ĠAlban\": 25920,\n    \"Ġtrough\": 25921,\n    \"Ġupright\": 25922,\n    \"tie\": 25923,\n    \"Ġexploits\": 25924,\n    \"ĠVaughan\": 25925,\n    \"ĠDarrell\": 25926,\n    \"Ġassortment\": 25927,\n    \"ĠChill\": 25928,\n    \"Ġlearners\": 25929,\n    \"aqu\": 25930,\n    \"Ġexplode\": 25931,\n    \"ĠChong\": 25932,\n    \"bt\": 25933,\n    \"opl\": 25934,\n    \"Ġaltern\": 25935,\n    \"Ġ151\": 25936,\n    \"fur\": 25937,\n    \"ULT\": 25938,\n    \"HOU\": 25939,\n    \"ĠMemory\": 25940,\n    \"Ġboosts\": 25941,\n    \"ynes\": 25942,\n    \"priv\": 25943,\n    \"Ġtimeless\": 25944,\n    \"Ġcurtail\": 25945,\n    \"ĠCary\": 25946,\n    \"ĠHud\": 25947,\n    \"Ġexclus\": 25948,\n    \"Ġ275\": 25949,\n    \"Ġfry\": 25950,\n    \"ĠVera\": 25951,\n    \"Ġdefied\": 25952,\n    \"ĠDust\": 25953,\n    \"Ġenvision\": 25954,\n    \"ĠPhilipp\": 25955,\n    \"Ġenhancements\": 25956,\n    \"ĠLIB\": 25957,\n    \"ggy\": 25958,\n    \"ĠAzure\": 25959,\n    \"esis\": 25960,\n    \"Ġcharismatic\": 25961,\n    \"Ġcoincide\": 25962,\n    \"inged\": 25963,\n    \"ĠChoose\": 25964,\n    \"Ġsizeable\": 25965,\n    \"136\": 25966,\n    \"Ġpronounce\": 25967,\n    \"ĠPositive\": 25968,\n    \"Ġideally\": 25969,\n    \"Ġechoes\": 25970,\n    \"Ġcottage\": 25971,\n    \"Ġencrypted\": 25972,\n    \"Prime\": 25973,\n    \"Ġá\": 25974,\n    \"Ġflashes\": 25975,\n    \"Group\": 25976,\n    \"Ġ501\": 25977,\n    \"heat\": 25978,\n    \"atility\": 25979,\n    \"ĠTesting\": 25980,\n    \"pex\": 25981,\n    \"WT\": 25982,\n    \"154\": 25983,\n    \"annah\": 25984,\n    \"Ġcompromising\": 25985,\n    \"Ġinactive\": 25986,\n    \"Ġdisparity\": 25987,\n    \"Ġgruesome\": 25988,\n    \"ĠFeather\": 25989,\n    \"ĠMandal\": 25990,\n    \"Ġthereof\": 25991,\n    \"ĠProducer\": 25992,\n    \"Ġprofiling\": 25993,\n    \"Ġlogistical\": 25994,\n    \"Ġcornerstone\": 25995,\n    \"ĠClaudia\": 25996,\n    \"Congress\": 25997,\n    \"ĠDill\": 25998,\n    \"ophone\": 25999,\n    \"Ġcameo\": 26000,\n    \"ĠCutler\": 26001,\n    \"Ġcraz\": 26002,\n    \"throw\": 26003,\n    \"ĠKasich\": 26004,\n    \"Ġexploiting\": 26005,\n    \"ĠSeas\": 26006,\n    \"agles\": 26007,\n    \"ĠGeological\": 26008,\n    \"ĠStub\": 26009,\n    \"ĠUps\": 26010,\n    \"MER\": 26011,\n    \"Ġmem\": 26012,\n    \"itution\": 26013,\n    \"Ġunderstandably\": 26014,\n    \"Ġcontractual\": 26015,\n    \"warming\": 26016,\n    \"qi\": 26017,\n    \"Sky\": 26018,\n    \"whelming\": 26019,\n    \"Ġcurse\": 26020,\n    \"ĠAren\": 26021,\n    \"Ġ265\": 26022,\n    \"ĠGree\": 26023,\n    \"Ġpresiding\": 26024,\n    \"Works\": 26025,\n    \"stones\": 26026,\n    \"Ġappalling\": 26027,\n    \"plex\": 26028,\n    \"dj\": 26029,\n    \"aunting\": 26030,\n    \"Ġimag\": 26031,\n    \"Ġsexism\": 26032,\n    \"ĠVert\": 26033,\n    \"ĠRag\": 26034,\n    \"ĠBliss\": 26035,\n    \"posium\": 26036,\n    \"div\": 26037,\n    \"Ġexperimenting\": 26038,\n    \"Ass\": 26039,\n    \"Lago\": 26040,\n    \"worthiness\": 26041,\n    \"ĠBerk\": 26042,\n    \"ĠDisneyland\": 26043,\n    \"Ġexaggerated\": 26044,\n    \"iliation\": 26045,\n    \"ĠFP\": 26046,\n    \"Ġprincipals\": 26047,\n    \"Miami\": 26048,\n    \"ropri\": 26049,\n    \"PLE\": 26050,\n    \"iona\": 26051,\n    \"ĠPokemon\": 26052,\n    \"apse\": 26053,\n    \"Ġbubbles\": 26054,\n    \"INC\": 26055,\n    \"ĠCaps\": 26056,\n    \"ĠBrowne\": 26057,\n    \"sing\": 26058,\n    \"ĠcafÃ©\": 26059,\n    \"Ġceilings\": 26060,\n    \"frame\": 26061,\n    \"ĠIrwin\": 26062,\n    \"ATS\": 26063,\n    \"dated\": 26064,\n    \"Ġprotester\": 26065,\n    \"Ġtaps\": 26066,\n    \"ĠOslo\": 26067,\n    \"Ù\": 26068,\n    \"Ġconcentrations\": 26069,\n    \"Ġdistributions\": 26070,\n    \"Ġglucose\": 26071,\n    \"ĠRudolph\": 26072,\n    \"Ġtowels\": 26073,\n    \"Ġâĸº\": 26074,\n    \"Ġneighbourhoods\": 26075,\n    \"Ġinduction\": 26076,\n    \"Ġglaring\": 26077,\n    \"Ġannexation\": 26078,\n    \"Ġunsustainable\": 26079,\n    \"ĠTend\": 26080,\n    \"Ġthumbs\": 26081,\n    \"iegel\": 26082,\n    \"cript\": 26083,\n    \"gor\": 26084,\n    \"closure\": 26085,\n    \"thought\": 26086,\n    \"Ġpaddle\": 26087,\n    \"Ġemulate\": 26088,\n    \"Ġdiameter\": 26089,\n    \"Ġtailor\": 26090,\n    \"ĠCorpor\": 26091,\n    \"icable\": 26092,\n    \"ĠPrin\": 26093,\n    \"Ġadminister\": 26094,\n    \"ĠJudd\": 26095,\n    \"ĠColleg\": 26096,\n    \"aund\": 26097,\n    \"ĠPond\": 26098,\n    \"ĠNOTE\": 26099,\n    \"Ġcombating\": 26100,\n    \"Ġinvention\": 26101,\n    \"ĠOculus\": 26102,\n    \"ĠRepl\": 26103,\n    \"iscal\": 26104,\n    \"Ġtrilogy\": 26105,\n    \"anian\": 26106,\n    \"ATT\": 26107,\n    \"ĠCoke\": 26108,\n    \"DL\": 26109,\n    \"ĠLup\": 26110,\n    \"living\": 26111,\n    \"Ġadvertise\": 26112,\n    \"ĠConnie\": 26113,\n    \"amping\": 26114,\n    \"Ġsung\": 26115,\n    \"ORY\": 26116,\n    \"ĠTet\": 26117,\n    \"Ġsplits\": 26118,\n    \"Ġreconnect\": 26119,\n    \"Ġlou\": 26120,\n    \"mut\": 26121,\n    \"ulator\": 26122,\n    \"Ġstrap\": 26123,\n    \"Ġswallow\": 26124,\n    \"rote\": 26125,\n    \"Ġexec\": 26126,\n    \"ffen\": 26127,\n    \"ĠCombine\": 26128,\n    \"ĠTreat\": 26129,\n    \"Ġsorrow\": 26130,\n    \"ĠNotably\": 26131,\n    \"ĠSever\": 26132,\n    \"rette\": 26133,\n    \"Ġwherein\": 26134,\n    \"Ġtransitioning\": 26135,\n    \"Ġtrout\": 26136,\n    \"Ġcockpit\": 26137,\n    \"Ġcrawl\": 26138,\n    \"Ġferv\": 26139,\n    \"Ġliquids\": 26140,\n    \"Ġtsp\": 26141,\n    \"atell\": 26142,\n    \"Ġmeasles\": 26143,\n    \"Ġjug\": 26144,\n    \"Ac\": 26145,\n    \"ĠKD\": 26146,\n    \"ĠMoose\": 26147,\n    \"Ġvans\": 26148,\n    \"chain\": 26149,\n    \"ĠPapua\": 26150,\n    \"plet\": 26151,\n    \"Wednesday\": 26152,\n    \"lynn\": 26153,\n    \"chery\": 26154,\n    \"budget\": 26155,\n    \"Tony\": 26156,\n    \"ĠBacon\": 26157,\n    \"Ġstirred\": 26158,\n    \"ĠSpecialist\": 26159,\n    \"Ġcounterfeit\": 26160,\n    \"Ð°\": 26161,\n    \"Ġdifferentiate\": 26162,\n    \"Ġmuscular\": 26163,\n    \"ĠTheodore\": 26164,\n    \"Ġlooms\": 26165,\n    \"ĠXX\": 26166,\n    \"ottage\": 26167,\n    \"Ġbenches\": 26168,\n    \"ĠMunicip\": 26169,\n    \"Po\": 26170,\n    \"ĠHeck\": 26171,\n    \"Ġscars\": 26172,\n    \"ĠNim\": 26173,\n    \"ÙĬ\": 26174,\n    \"ĠIngredients\": 26175,\n    \"Ġecological\": 26176,\n    \"ĠAWS\": 26177,\n    \"Ġdispose\": 26178,\n    \"Ġmattered\": 26179,\n    \"Ġ720\": 26180,\n    \"Ġpatriotism\": 26181,\n    \"ĠGrind\": 26182,\n    \"Ġcurved\": 26183,\n    \"opia\": 26184,\n    \"ĠLiqu\": 26185,\n    \"Ġevangelical\": 26186,\n    \"tto\": 26187,\n    \"ĠMaterial\": 26188,\n    \"ĠShowtime\": 26189,\n    \"ĠBS\": 26190,\n    \"Ġcheckpoints\": 26191,\n    \"Ġcrippling\": 26192,\n    \"ĠBalance\": 26193,\n    \"stress\": 26194,\n    \"bearing\": 26195,\n    \"Ġ216\": 26196,\n    \"ĠGuards\": 26197,\n    \"Ġlinebackers\": 26198,\n    \"Ġoffending\": 26199,\n    \"Ġsands\": 26200,\n    \"umbnail\": 26201,\n    \"atorial\": 26202,\n    \"Ġliberties\": 26203,\n    \"ĠGW\": 26204,\n    \"ĠPulitzer\": 26205,\n    \"ĠAlvin\": 26206,\n    \"ĠFAC\": 26207,\n    \"ĠStrategies\": 26208,\n    \"Ġreiter\": 26209,\n    \"ĠRestaur\": 26210,\n    \"ĠLithuania\": 26211,\n    \"ĠSwanson\": 26212,\n    \"terror\": 26213,\n    \"ĠMaurit\": 26214,\n    \"Ġparadise\": 26215,\n    \"zzle\": 26216,\n    \"owment\": 26217,\n    \"ĠWP\": 26218,\n    \"Ġsodium\": 26219,\n    \"Ġfuturistic\": 26220,\n    \"Ġdots\": 26221,\n    \"Anthony\": 26222,\n    \"Though\": 26223,\n    \"Ġstripes\": 26224,\n    \"Ġorig\": 26225,\n    \"ultz\": 26226,\n    \"Ġ340\": 26227,\n    \"KK\": 26228,\n    \"umer\": 26229,\n    \"ivery\": 26230,\n    \"Ġplacebo\": 26231,\n    \"Ġdemocrat\": 26232,\n    \"Ġsubmerged\": 26233,\n    \"ĠHidden\": 26234,\n    \"pieces\": 26235,\n    \"Ġasteroid\": 26236,\n    \"ĠGraphic\": 26237,\n    \"Ġadvert\": 26238,\n    \"sil\": 26239,\n    \"Ġdreaming\": 26240,\n    \"Ġnationality\": 26241,\n    \"Ġfostering\": 26242,\n    \"daughter\": 26243,\n    \"ĠSavings\": 26244,\n    \"Ġmischief\": 26245,\n    \"ĠClair\": 26246,\n    \"ĠBundy\": 26247,\n    \"Ġblatant\": 26248,\n    \"Ġtabs\": 26249,\n    \"qa\": 26250,\n    \"severe\": 26251,\n    \"attered\": 26252,\n    \"Ġgreed\": 26253,\n    \"Ġresembles\": 26254,\n    \"Ġnominal\": 26255,\n    \"Ġineligible\": 26256,\n    \"wealth\": 26257,\n    \"fax\": 26258,\n    \"payers\": 26259,\n    \"Ġdisplacement\": 26260,\n    \"itute\": 26261,\n    \"Ġunpleasant\": 26262,\n    \"ĠPom\": 26263,\n    \"lif\": 26264,\n    \"edo\": 26265,\n    \"ĠNP\": 26266,\n    \"Inter\": 26267,\n    \"Ġcohort\": 26268,\n    \"ĠStacy\": 26269,\n    \"ĠDai\": 26270,\n    \"Ġhistories\": 26271,\n    \"alin\": 26272,\n    \"273\": 26273,\n    \"Ġdram\": 26274,\n    \"ĠKand\": 26275,\n    \"Ġexpectancy\": 26276,\n    \"ansson\": 26277,\n    \"Ġlimbo\": 26278,\n    \"ĠPolar\": 26279,\n    \"Ġdivine\": 26280,\n    \"oused\": 26281,\n    \"Ġshel\": 26282,\n    \"ĠProblem\": 26283,\n    \"achment\": 26284,\n    \"Ġâĸł\": 26285,\n    \"shoot\": 26286,\n    \"antam\": 26287,\n    \"ĠHerz\": 26288,\n    \"Ġ157\": 26289,\n    \"Ġpreventive\": 26290,\n    \"keye\": 26291,\n    \"Sing\": 26292,\n    \"Ġcharacteristic\": 26293,\n    \"Ġcasually\": 26294,\n    \"ĠTaiwanese\": 26295,\n    \"md\": 26296,\n    \"ĠHubbard\": 26297,\n    \"imon\": 26298,\n    \"Ġsect\": 26299,\n    \"148\": 26300,\n    \"Ġmartyr\": 26301,\n    \"stud\": 26302,\n    \"Ġcongrat\": 26303,\n    \"ĠSWAT\": 26304,\n    \"ĠTheory\": 26305,\n    \"INAL\": 26306,\n    \"opping\": 26307,\n    \"ply\": 26308,\n    \"ĠKindle\": 26309,\n    \"uu\": 26310,\n    \"ĠLith\": 26311,\n    \"kaya\": 26312,\n    \"ĠActivity\": 26313,\n    \"uously\": 26314,\n    \"ĠJeb\": 26315,\n    \"tell\": 26316,\n    \"ĠSpin\": 26317,\n    \"ĠExplorer\": 26318,\n    \"Ġfolded\": 26319,\n    \"ĠCanterbury\": 26320,\n    \"ĠStur\": 26321,\n    \"Ġminiature\": 26322,\n    \"Ġmultif\": 26323,\n    \"ĠPressure\": 26324,\n    \"angling\": 26325,\n    \"ĠOverse\": 26326,\n    \"Ġresides\": 26327,\n    \"Ġimpressions\": 26328,\n    \"Ġauthored\": 26329,\n    \"265\": 26330,\n    \"Ġallergies\": 26331,\n    \"143\": 26332,\n    \"ĠJi\": 26333,\n    \"Ġsticker\": 26334,\n    \"ĠAccord\": 26335,\n    \"Ġcaste\": 26336,\n    \"Ġseparates\": 26337,\n    \"ĠFein\": 26338,\n    \"Daily\": 26339,\n    \"179\": 26340,\n    \"ĠScores\": 26341,\n    \"ĠAuction\": 26342,\n    \"hea\": 26343,\n    \"Ġdisclosing\": 26344,\n    \"ĠTacoma\": 26345,\n    \"Ġverse\": 26346,\n    \"ĠBeg\": 26347,\n    \"Ġfabrics\": 26348,\n    \"aez\": 26349,\n    \"Ġattachment\": 26350,\n    \"isy\": 26351,\n    \"Christ\": 26352,\n    \"Ġaddictive\": 26353,\n    \"Ġvir\": 26354,\n    \"Week\": 26355,\n    \"ĠPlum\": 26356,\n    \"croft\": 26357,\n    \"itivity\": 26358,\n    \"ĠExhibition\": 26359,\n    \"Ġbruised\": 26360,\n    \"Ġmimic\": 26361,\n    \"rers\": 26362,\n    \"Ġanal\": 26363,\n    \"Ġunintended\": 26364,\n    \"Ġpall\": 26365,\n    \"atts\": 26366,\n    \"ĠWarn\": 26367,\n    \"Ġslows\": 26368,\n    \"WH\": 26369,\n    \"Ġembro\": 26370,\n    \"nec\": 26371,\n    \"Ġ168\": 26372,\n    \"285\": 26373,\n    \"ologic\": 26374,\n    \"Ġhob\": 26375,\n    \"ĠPeel\": 26376,\n    \"Mill\": 26377,\n    \"eps\": 26378,\n    \"Ġrobbers\": 26379,\n    \"ĠDahl\": 26380,\n    \"semble\": 26381,\n    \"omics\": 26382,\n    \"toe\": 26383,\n    \"ĠLoch\": 26384,\n    \"Ġreproduction\": 26385,\n    \"ĠCullen\": 26386,\n    \"Ġimplants\": 26387,\n    \"Ġwow\": 26388,\n    \"ĠSTATE\": 26389,\n    \"vt\": 26390,\n    \"Ġdepleted\": 26391,\n    \"Ġbreweries\": 26392,\n    \"Ġhateful\": 26393,\n    \"Ġgast\": 26394,\n    \"Ġhollow\": 26395,\n    \"Ġradically\": 26396,\n    \"ographed\": 26397,\n    \"ĠFog\": 26398,\n    \"onian\": 26399,\n    \"ĠSequ\": 26400,\n    \"Ġdisrespectful\": 26401,\n    \"Dis\": 26402,\n    \"ĠExper\": 26403,\n    \"pron\": 26404,\n    \"ĠAmelia\": 26405,\n    \"ĠSage\": 26406,\n    \"bath\": 26407,\n    \"Ġtransformative\": 26408,\n    \"Ġtremendously\": 26409,\n    \"Ġpillow\": 26410,\n    \"ĠNormal\": 26411,\n    \"Cont\": 26412,\n    \"ĠMedic\": 26413,\n    \"educated\": 26414,\n    \"Ġredesigned\": 26415,\n    \"Ġkneeling\": 26416,\n    \"Ġinh\": 26417,\n    \"Ġroofs\": 26418,\n    \"Ġhandmade\": 26419,\n    \"Ġprotracted\": 26420,\n    \"ĠIsn\": 26421,\n    \"ĠCapacity\": 26422,\n    \"Ġsquash\": 26423,\n    \"ĠVega\": 26424,\n    \"Ġfats\": 26425,\n    \"ĠCertified\": 26426,\n    \"ointed\": 26427,\n    \"Ġpricey\": 26428,\n    \"ĠBasil\": 26429,\n    \"Ġfreezer\": 26430,\n    \"Ġscent\": 26431,\n    \"Ġpizz\": 26432,\n    \"ĠArd\": 26433,\n    \"Ġdistractions\": 26434,\n    \"Ġviolently\": 26435,\n    \"ĠHess\": 26436,\n    \"Ġfunc\": 26437,\n    \"Ġundert\": 26438,\n    \"Ġrejuven\": 26439,\n    \"Ġdisbelief\": 26440,\n    \"cluded\": 26441,\n    \"named\": 26442,\n    \"ĠFailure\": 26443,\n    \"kus\": 26444,\n    \"Ġhostages\": 26445,\n    \"ĠSahara\": 26446,\n    \"Ġ1944\": 26447,\n    \"Leary\": 26448,\n    \"ĠPrel\": 26449,\n    \"enza\": 26450,\n    \"ĠAlly\": 26451,\n    \"ĠKak\": 26452,\n    \"Ġcounselors\": 26453,\n    \"ĠGale\": 26454,\n    \"ĠHok\": 26455,\n    \"ĠSold\": 26456,\n    \"Ġhacker\": 26457,\n    \"Ġhun\": 26458,\n    \"Ġbung\": 26459,\n    \"Ġdeclares\": 26460,\n    \"Ġinfringement\": 26461,\n    \"OOD\": 26462,\n    \"Ġdoub\": 26463,\n    \"jam\": 26464,\n    \"Ġallergy\": 26465,\n    \"ĠShipping\": 26466,\n    \"Ġmedic\": 26467,\n    \"Ġaccommod\": 26468,\n    \"Ġdocumenting\": 26469,\n    \"Ġcompanions\": 26470,\n    \"Ġmodelling\": 26471,\n    \"Ġcarriage\": 26472,\n    \"ĠCherokee\": 26473,\n    \"Ġtresp\": 26474,\n    \"Ġtaxable\": 26475,\n    \"ĠActivities\": 26476,\n    \"ĠCrane\": 26477,\n    \"bots\": 26478,\n    \"ĠRusso\": 26479,\n    \"Ġstocked\": 26480,\n    \"ervation\": 26481,\n    \"Ġcoffin\": 26482,\n    \"aign\": 26483,\n    \"guards\": 26484,\n    \"Ġonwards\": 26485,\n    \"Ġfrank\": 26486,\n    \".*\": 26487,\n    \"unic\": 26488,\n    \"Ġcens\": 26489,\n    \"enic\": 26490,\n    \"ruit\": 26491,\n    \"rained\": 26492,\n    \"Ġadapting\": 26493,\n    \"aments\": 26494,\n    \"Ġstagnant\": 26495,\n    \"azaar\": 26496,\n    \"ĠHarlem\": 26497,\n    \"Ġ158\": 26498,\n    \"ysis\": 26499,\n    \"Ġbraking\": 26500,\n    \"Ġdipping\": 26501,\n    \"Ġclan\": 26502,\n    \"ĠShu\": 26503,\n    \"Ġprops\": 26504,\n    \"qualified\": 26505,\n    \"Ġmistakenly\": 26506,\n    \"ĠStalin\": 26507,\n    \"Ġaddicts\": 26508,\n    \"ĠCALL\": 26509,\n    \"ropolis\": 26510,\n    \"aten\": 26511,\n    \"pec\": 26512,\n    \"ĠDro\": 26513,\n    \"ĠFellowship\": 26514,\n    \"ĠSupporting\": 26515,\n    \"loc\": 26516,\n    \"uben\": 26517,\n    \"499\": 26518,\n    \"Bro\": 26519,\n    \"Ġpots\": 26520,\n    \"Ġchunks\": 26521,\n    \"wr\": 26522,\n    \"ĠColonial\": 26523,\n    \"ĠArchitecture\": 26524,\n    \"Ġconstrained\": 26525,\n    \"Ġenvelop\": 26526,\n    \"ĠIronically\": 26527,\n    \"aban\": 26528,\n    \"Ġapparatus\": 26529,\n    \"Ġcue\": 26530,\n    \"Ġborne\": 26531,\n    \"ĠRoz\": 26532,\n    \"ilton\": 26533,\n    \"Ġtheoretical\": 26534,\n    \"ĠWatching\": 26535,\n    \"Ġfuck\": 26536,\n    \"ĠSilk\": 26537,\n    \"ĠSTE\": 26538,\n    \"bler\": 26539,\n    \"ĠPOST\": 26540,\n    \"ĠUpton\": 26541,\n    \"Ġsummons\": 26542,\n    \"ĠCum\": 26543,\n    \"ĠKL\": 26544,\n    \"Ġrelaxation\": 26545,\n    \"ĠDuff\": 26546,\n    \"Ġincumb\": 26547,\n    \"ĠRedd\": 26548,\n    \"Ġstature\": 26549,\n    \"Ġcanv\": 26550,\n    \"added\": 26551,\n    \"Ġremedies\": 26552,\n    \"ĠISO\": 26553,\n    \"ĠDecker\": 26554,\n    \"Ġafloat\": 26555,\n    \"Ġstartling\": 26556,\n    \"ĠBethlehem\": 26557,\n    \"Ġrealizes\": 26558,\n    \"find\": 26559,\n    \"ĠAra\": 26560,\n    \"Ġphased\": 26561,\n    \"arov\": 26562,\n    \"Ġhalting\": 26563,\n    \"ĠWindow\": 26564,\n    \"Ġdentist\": 26565,\n    \"Ġtumble\": 26566,\n    \"Ġvalidation\": 26567,\n    \"Ġcarve\": 26568,\n    \"ĠIPS\": 26569,\n    \"Ġirrit\": 26570,\n    \"ĠEssential\": 26571,\n    \"Ġfluids\": 26572,\n    \"rons\": 26573,\n    \"Ġimplant\": 26574,\n    \"Ġnuisance\": 26575,\n    \"ĠShelley\": 26576,\n    \"ĠGemini\": 26577,\n    \"Ġpharmac\": 26578,\n    \"iction\": 26579,\n    \"Ġtaped\": 26580,\n    \"ĠGovernments\": 26581,\n    \"ruly\": 26582,\n    \"Ġscant\": 26583,\n    \"Ġprominently\": 26584,\n    \"Ġreim\": 26585,\n    \"unning\": 26586,\n    \"arted\": 26587,\n    \"ĠMatters\": 26588,\n    \"Ġ1918\": 26589,\n    \"ĠPros\": 26590,\n    \"atel\": 26591,\n    \"ĠBattalion\": 26592,\n    \"onduct\": 26593,\n    \"talk\": 26594,\n    \"ĠTinder\": 26595,\n    \"ĠInstant\": 26596,\n    \"ĠKern\": 26597,\n    \"Ġbuckets\": 26598,\n    \"ĠGroups\": 26599,\n    \"Ġmetaphor\": 26600,\n    \"cloud\": 26601,\n    \"ĠString\": 26602,\n    \"Ohio\": 26603,\n    \"Ġcaffeine\": 26604,\n    \"Old\": 26605,\n    \"Ġdefinite\": 26606,\n    \"ĠNikola\": 26607,\n    \"ĠLords\": 26608,\n    \"icol\": 26609,\n    \")?\": 26610,\n    \"Ġenjoyment\": 26611,\n    \"Ġfamine\": 26612,\n    \"Ġdefinitions\": 26613,\n    \"ĠJem\": 26614,\n    \"Check\": 26615,\n    \"Ġaiding\": 26616,\n    \"ĠMÃ©\": 26617,\n    \"Ġrenewables\": 26618,\n    \"Ġsightings\": 26619,\n    \"footed\": 26620,\n    \"Box\": 26621,\n    \"Ġgoats\": 26622,\n    \"Ġshack\": 26623,\n    \"AX\": 26624,\n    \"ĠMonk\": 26625,\n    \"ĠGraduate\": 26626,\n    \"Ġmeats\": 26627,\n    \"handle\": 26628,\n    \"147\": 26629,\n    \"rys\": 26630,\n    \"Ġunsub\": 26631,\n    \"Pont\": 26632,\n    \"uble\": 26633,\n    \"440\": 26634,\n    \"Ġeyel\": 26635,\n    \"thro\": 26636,\n    \"Ġcreep\": 26637,\n    \"^^^^\": 26638,\n    \"Ġpopcorn\": 26639,\n    \"Ġcompression\": 26640,\n    \"sal\": 26641,\n    \"ouf\": 26642,\n    \"Ġrepairing\": 26643,\n    \"Think\": 26644,\n    \"Ġdoubtful\": 26645,\n    \"ĠLooks\": 26646,\n    \"Ġtaller\": 26647,\n    \"Ġsul\": 26648,\n    \"sf\": 26649,\n    \"give\": 26650,\n    \"ĠGau\": 26651,\n    \"Ġrevered\": 26652,\n    \"EMBER\": 26653,\n    \"Ġsloppy\": 26654,\n    \"ersen\": 26655,\n    \"Ġvitamins\": 26656,\n    \"ĠImprovement\": 26657,\n    \"Ġprogresses\": 26658,\n    \"Ġdiploma\": 26659,\n    \"semb\": 26660,\n    \"ustain\": 26661,\n    \"Ġchant\": 26662,\n    \"Ġbumped\": 26663,\n    \"Ġsabotage\": 26664,\n    \"nant\": 26665,\n    \"Ġrabbit\": 26666,\n    \"Ġdividing\": 26667,\n    \"ĠDefender\": 26668,\n    \"Ġlik\": 26669,\n    \"Ġirrespective\": 26670,\n    \"cade\": 26671,\n    \"ĠSter\": 26672,\n    \"touch\": 26673,\n    \"EMA\": 26674,\n    \"Ġparted\": 26675,\n    \"ĠBAR\": 26676,\n    \"hung\": 26677,\n    \"Ġannoyed\": 26678,\n    \"Ġhinder\": 26679,\n    \"Ġexamines\": 26680,\n    \"oan\": 26681,\n    \"ĠBoe\": 26682,\n    \"Ġaggreg\": 26683,\n    \"ĠChu\": 26684,\n    \"ĠUCS\": 26685,\n    \"IGHTS\": 26686,\n    \"pez\": 26687,\n    \"ĠUNESCO\": 26688,\n    \"Ġwindshield\": 26689,\n    \"Martin\": 26690,\n    \"Ġwithhold\": 26691,\n    \"does\": 26692,\n    \"Ġbruising\": 26693,\n    \"Ġdeterior\": 26694,\n    \"bourg\": 26695,\n    \"ĠTowers\": 26696,\n    \"JD\": 26697,\n    \"England\": 26698,\n    \"Ġequivalents\": 26699,\n    \"Ġrazor\": 26700,\n    \"Ġreassuring\": 26701,\n    \"Ġident\": 26702,\n    \"Ġ208\": 26703,\n    \"reath\": 26704,\n    \"ceans\": 26705,\n    \"Ġpatrolling\": 26706,\n    \"eve\": 26707,\n    \"pots\": 26708,\n    \"itative\": 26709,\n    \"Ġsided\": 26710,\n    \"Ġsofa\": 26711,\n    \"Ġunborn\": 26712,\n    \"Ġaug\": 26713,\n    \"Ġperpetual\": 26714,\n    \"effect\": 26715,\n    \"represented\": 26716,\n    \"Ġrails\": 26717,\n    \"ĠSummers\": 26718,\n    \"ĠMOR\": 26719,\n    \"ĠSlow\": 26720,\n    \"ĠExpert\": 26721,\n    \"Ġshameful\": 26722,\n    \"Ġaudits\": 26723,\n    \"Sl\": 26724,\n    \"ĠBurr\": 26725,\n    \"adow\": 26726,\n    \"ĠWAY\": 26727,\n    \"anic\": 26728,\n    \"ĠIslamists\": 26729,\n    \"ĠStranger\": 26730,\n    \"pse\": 26731,\n    \"amaz\": 26732,\n    \"ĠPeggy\": 26733,\n    \"ĠSeventh\": 26734,\n    \"Ġscreenplay\": 26735,\n    \"ĠGriff\": 26736,\n    \"Ireland\": 26737,\n    \"142\": 26738,\n    \"Ġneural\": 26739,\n    \"ĠFernand\": 26740,\n    \"ainment\": 26741,\n    \"ĠMigration\": 26742,\n    \"ureen\": 26743,\n    \"ĠSCH\": 26744,\n    \"Sullivan\": 26745,\n    \"ĠWag\": 26746,\n    \"ĠREG\": 26747,\n    \"Ġ420\": 26748,\n    \"inky\": 26749,\n    \"ĠNewspaper\": 26750,\n    \"School\": 26751,\n    \"Ok\": 26752,\n    \"ĠKrishna\": 26753,\n    \"Ġ480\": 26754,\n    \"erald\": 26755,\n    \"Ġskipping\": 26756,\n    \"Ġharrowing\": 26757,\n    \"158\": 26758,\n    \"rogen\": 26759,\n    \"Ġbetrayal\": 26760,\n    \"Ġculmination\": 26761,\n    \"ĠCirc\": 26762,\n    \"Ġ211\": 26763,\n    \"stro\": 26764,\n    \"ĠTrace\": 26765,\n    \"Ġheaviest\": 26766,\n    \"td\": 26767,\n    \"ĠHenri\": 26768,\n    \"epend\": 26769,\n    \"RB\": 26770,\n    \"arella\": 26771,\n    \"umbai\": 26772,\n    \"Ġcrem\": 26773,\n    \"ĠDistribut\": 26774,\n    \"ruff\": 26775,\n    \"Ġscreams\": 26776,\n    \"Ġscathing\": 26777,\n    \"girls\": 26778,\n    \"Ġtiles\": 26779,\n    \"ĠEvil\": 26780,\n    \"usp\": 26781,\n    \"Ġknowledgeable\": 26782,\n    \"Ġrestitution\": 26783,\n    \"ĠWiFi\": 26784,\n    \"Ġitiner\": 26785,\n    \"exper\": 26786,\n    \"oris\": 26787,\n    \"ĠPokÃ©mon\": 26788,\n    \"iane\": 26789,\n    \"produ\": 26790,\n    \"ĠAchievement\": 26791,\n    \"Ġbrunt\": 26792,\n    \"ĠSurgery\": 26793,\n    \"Ġpragmatic\": 26794,\n    \"Ber\": 26795,\n    \"ĠKejriwal\": 26796,\n    \"cus\": 26797,\n    \"Ġconsensual\": 26798,\n    \"acet\": 26799,\n    \"ĠSecondly\": 26800,\n    \"Ġdivul\": 26801,\n    \"uca\": 26802,\n    \"Ġbusted\": 26803,\n    \"emies\": 26804,\n    \"ĠMou\": 26805,\n    \"Ġ217\": 26806,\n    \"Ġexcludes\": 26807,\n    \"ĠSamoa\": 26808,\n    \"Ġlofty\": 26809,\n    \"ĠSic\": 26810,\n    \"ĠRemem\": 26811,\n    \"dn\": 26812,\n    \"Ġeradicate\": 26813,\n    \"Ġpies\": 26814,\n    \"Ġscenery\": 26815,\n    \"ATTLE\": 26816,\n    \"ĠWAS\": 26817,\n    \"Ġinnovate\": 26818,\n    \"ĠEverest\": 26819,\n    \"Ġsynonymous\": 26820,\n    \"izen\": 26821,\n    \"Ġeuth\": 26822,\n    \"ĠFIA\": 26823,\n    \"ITIES\": 26824,\n    \"ĠSuddenly\": 26825,\n    \"Ġforay\": 26826,\n    \"pell\": 26827,\n    \"ÄŁ\": 26828,\n    \"licensed\": 26829,\n    \"Ġfra\": 26830,\n    \"Ġblasting\": 26831,\n    \"autical\": 26832,\n    \"ĠBlizzard\": 26833,\n    \"orer\": 26834,\n    \"Ġchili\": 26835,\n    \"ĠSylvia\": 26836,\n    \"except\": 26837,\n    \"tec\": 26838,\n    \"ĠResistance\": 26839,\n    \"young\": 26840,\n    \"usions\": 26841,\n    \"iotic\": 26842,\n    \"ĠDreams\": 26843,\n    \"ĠArchives\": 26844,\n    \"Ġunleash\": 26845,\n    \"ĠPract\": 26846,\n    \"Ġlikened\": 26847,\n    \"Ġga\": 26848,\n    \"Ġdisappearing\": 26849,\n    \"Ġunnoticed\": 26850,\n    \"Ġfrightened\": 26851,\n    \"arms\": 26852,\n    \"ĠCAD\": 26853,\n    \"Ġcoloured\": 26854,\n    \"ĠSigns\": 26855,\n    \"oing\": 26856,\n    \"Ġvodka\": 26857,\n    \"ruption\": 26858,\n    \"otions\": 26859,\n    \"isal\": 26860,\n    \"ĠBecome\": 26861,\n    \"Ġswoop\": 26862,\n    \"reating\": 26863,\n    \"Ġchoking\": 26864,\n    \"Ġunforgettable\": 26865,\n    \"258\": 26866,\n    \"packs\": 26867,\n    \"345\": 26868,\n    \"ĠAutumn\": 26869,\n    \"Ġther\": 26870,\n    \"399\": 26871,\n    \"ĠFaculty\": 26872,\n    \"Ġ1933\": 26873,\n    \"ĠNormally\": 26874,\n    \"orge\": 26875,\n    \"ĠTess\": 26876,\n    \"ĠChrom\": 26877,\n    \"Ġscripts\": 26878,\n    \"Ġbiking\": 26879,\n    \"Act\": 26880,\n    \"Ġgrazing\": 26881,\n    \"ĠLabrador\": 26882,\n    \"ĠLey\": 26883,\n    \"Ġwandering\": 26884,\n    \"Ġfend\": 26885,\n    \"ĠPolk\": 26886,\n    \"ĠKeane\": 26887,\n    \"ĠBeef\": 26888,\n    \"elope\": 26889,\n    \"ĠApproximately\": 26890,\n    \"Ġ1952\": 26891,\n    \"personal\": 26892,\n    \"Ġhistorians\": 26893,\n    \"ĠMcDonnell\": 26894,\n    \"must\": 26895,\n    \"LES\": 26896,\n    \"iking\": 26897,\n    \"Ġtherm\": 26898,\n    \"Ġhumane\": 26899,\n    \"Ġcrowdfunding\": 26900,\n    \"ĠBenefits\": 26901,\n    \"Land\": 26902,\n    \"Ġanalog\": 26903,\n    \"agency\": 26904,\n    \"ĠCrowley\": 26905,\n    \"Ġbirths\": 26906,\n    \"Ġobj\": 26907,\n    \"Ġfren\": 26908,\n    \"ĠSalmon\": 26909,\n    \"bies\": 26910,\n    \"Ġreve\": 26911,\n    \"216\": 26912,\n    \"Ġbetrayed\": 26913,\n    \"Ġinduced\": 26914,\n    \"acles\": 26915,\n    \"Ġtrad\": 26916,\n    \"Ġforgiven\": 26917,\n    \"Ġearners\": 26918,\n    \"208\": 26919,\n    \"Ġxen\": 26920,\n    \"Ġunle\": 26921,\n    \"Ġnecklace\": 26922,\n    \"Ġgravel\": 26923,\n    \"Ġsalads\": 26924,\n    \"Ġgrooming\": 26925,\n    \"California\": 26926,\n    \"Ġpossessed\": 26927,\n    \"Ġproclamation\": 26928,\n    \"Ġsequences\": 26929,\n    \"ream\": 26930,\n    \"FOX\": 26931,\n    \"arkin\": 26932,\n    \"ĠTRAN\": 26933,\n    \"Ġpurs\": 26934,\n    \"ĠLoans\": 26935,\n    \"Ġsacrificed\": 26936,\n    \"Ġiceberg\": 26937,\n    \"Phill\": 26938,\n    \"Ġgalvan\": 26939,\n    \"Ġsmugglers\": 26940,\n    \"formation\": 26941,\n    \"onson\": 26942,\n    \"ĠVaughn\": 26943,\n    \"Ġdoctrine\": 26944,\n    \"ĠEyes\": 26945,\n    \"Ġunmanned\": 26946,\n    \"states\": 26947,\n    \"Ġdetermin\": 26948,\n    \"almost\": 26949,\n    \"Ġeviction\": 26950,\n    \"Ġtid\": 26951,\n    \"ARR\": 26952,\n    \"Ġcooks\": 26953,\n    \"Bad\": 26954,\n    \"ĠCamb\": 26955,\n    \"Ġlinear\": 26956,\n    \"229\": 26957,\n    \"ĠCooke\": 26958,\n    \"ĠPurch\": 26959,\n    \"join\": 26960,\n    \"ĠCult\": 26961,\n    \"ĠRefugee\": 26962,\n    \"Ġslamming\": 26963,\n    \"ĠðŁĳ\": 26964,\n    \"Ġpedal\": 26965,\n    \"ĠVeronica\": 26966,\n    \"Ġlandowners\": 26967,\n    \"ĠYel\": 26968,\n    \"ĠWorkshop\": 26969,\n    \"antic\": 26970,\n    \"Ġdysfunction\": 26971,\n    \"Ġ229\": 26972,\n    \"Ġculturally\": 26973,\n    \"Ġinfuri\": 26974,\n    \"ĠEck\": 26975,\n    \"sem\": 26976,\n    \"Ġwired\": 26977,\n    \"ĠWerner\": 26978,\n    \"lov\": 26979,\n    \"ĠJasper\": 26980,\n    \"Ġvehemently\": 26981,\n    \"ĠSpy\": 26982,\n    \"lift\": 26983,\n    \"ĠNab\": 26984,\n    \"ĠPound\": 26985,\n    \"ĠHanna\": 26986,\n    \"Ġleveled\": 26987,\n    \"WOOD\": 26988,\n    \"tm\": 26989,\n    \"ĠKitt\": 26990,\n    \"Ġconve\": 26991,\n    \"nat\": 26992,\n    \"Ġjog\": 26993,\n    \"IVER\": 26994,\n    \"Ġmemes\": 26995,\n    \"Ġseaw\": 26996,\n    \"ector\": 26997,\n    \"Ġsprayed\": 26998,\n    \"Ġvaccinated\": 26999,\n    \"Europe\": 27000,\n    \"Ġmustard\": 27001,\n    \"ĠMahm\": 27002,\n    \"Ġ214\": 27003,\n    \"Research\": 27004,\n    \"iminary\": 27005,\n    \"Ġconcerted\": 27006,\n    \"Detroit\": 27007,\n    \"Ġkios\": 27008,\n    \"Ġplummet\": 27009,\n    \"Ġvisuals\": 27010,\n    \"247\": 27011,\n    \"Ġ228\": 27012,\n    \"development\": 27013,\n    \"ĠPascal\": 27014,\n    \"acial\": 27015,\n    \"ĠSeasons\": 27016,\n    \"ĠTL\": 27017,\n    \"480\": 27018,\n    \"ĠReader\": 27019,\n    \"Ġexpulsion\": 27020,\n    \"Ġchoked\": 27021,\n    \"Ġdevotion\": 27022,\n    \"ĠSTAT\": 27023,\n    \"urred\": 27024,\n    \"Ġfascinated\": 27025,\n    \"Ġstealth\": 27026,\n    \"NL\": 27027,\n    \"Ġbooster\": 27028,\n    \"Kat\": 27029,\n    \"ĠPriebus\": 27030,\n    \"Ġaux\": 27031,\n    \"ĠHate\": 27032,\n    \"ĠThing\": 27033,\n    \"Ġabnormal\": 27034,\n    \"Ġcalmly\": 27035,\n    \"Ġdedicate\": 27036,\n    \"cause\": 27037,\n    \"Ġisolate\": 27038,\n    \"ĠPai\": 27039,\n    \"Ġsuspensions\": 27040,\n    \"Ġpoisoned\": 27041,\n    \"ission\": 27042,\n    \"Ġprohibiting\": 27043,\n    \"353\": 27044,\n    \"banks\": 27045,\n    \"Ġkissed\": 27046,\n    \"ĠBegin\": 27047,\n    \"atis\": 27048,\n    \"LI\": 27049,\n    \"Ġshaft\": 27050,\n    \"ĠGuth\": 27051,\n    \"ĠBoo\": 27052,\n    \"Ġcinnamon\": 27053,\n    \"Ġverbally\": 27054,\n    \"ĠRabbi\": 27055,\n    \"Ġmonsters\": 27056,\n    \"done\": 27057,\n    \"ĠClyde\": 27058,\n    \"Ġspar\": 27059,\n    \"ĠCage\": 27060,\n    \"ĠPersons\": 27061,\n    \"305\": 27062,\n    \"ĠMons\": 27063,\n    \"Ġjealous\": 27064,\n    \"Ġswirling\": 27065,\n    \"know\": 27066,\n    \"Ġprote\": 27067,\n    \"Ġcruising\": 27068,\n    \"Ġduly\": 27069,\n    \"Ġchapel\": 27070,\n    \"Ġgroove\": 27071,\n    \"bps\": 27072,\n    \"ĠKelvin\": 27073,\n    \"iom\": 27074,\n    \"aer\": 27075,\n    \"bomb\": 27076,\n    \"Christian\": 27077,\n    \"Ġgigs\": 27078,\n    \"+.\": 27079,\n    \"ĠWei\": 27080,\n    \"Ġfarmland\": 27081,\n    \"otally\": 27082,\n    \"Ġequitable\": 27083,\n    \"ĠCBO\": 27084,\n    \"chool\": 27085,\n    \"amara\": 27086,\n    \"Ġwealthiest\": 27087,\n    \"ĠMeans\": 27088,\n    \"Ġ235\": 27089,\n    \"ĠUk\": 27090,\n    \"steps\": 27091,\n    \"raham\": 27092,\n    \"nerg\": 27093,\n    \"Ġclad\": 27094,\n    \"Ġsled\": 27095,\n    \"ĠMorrow\": 27096,\n    \"152\": 27097,\n    \"ĠRece\": 27098,\n    \"Ġplausible\": 27099,\n    \"Ġbisexual\": 27100,\n    \"artments\": 27101,\n    \"Ġveh\": 27102,\n    \"ĠLoft\": 27103,\n    \"bly\": 27104,\n    \"ĠCONC\": 27105,\n    \"automatic\": 27106,\n    \"Ġmasterpiece\": 27107,\n    \"ĠSpringer\": 27108,\n    \"Ġtendencies\": 27109,\n    \"Ro\": 27110,\n    \"Ġresentment\": 27111,\n    \"Ġadversely\": 27112,\n    \"Ġbandwidth\": 27113,\n    \"ĠDAV\": 27114,\n    \"Ġtun\": 27115,\n    \"Ġpuppies\": 27116,\n    \"ĠBundes\": 27117,\n    \"ĠHort\": 27118,\n    \"ĠGarfield\": 27119,\n    \"Ġenlist\": 27120,\n    \"Ġmont\": 27121,\n    \"gd\": 27122,\n    \"Ġrooting\": 27123,\n    \"Dream\": 27124,\n    \"Ġfulfillment\": 27125,\n    \"chal\": 27126,\n    \"182\": 27127,\n    \"prop\": 27128,\n    \"159\": 27129,\n    \"Ġcourtyard\": 27130,\n    \"iard\": 27131,\n    \"ĠSle\": 27132,\n    \"Ġoperative\": 27133,\n    \"Ġpublishes\": 27134,\n    \"ĠProposition\": 27135,\n    \"Ġcritique\": 27136,\n    \"Ġredist\": 27137,\n    \"wang\": 27138,\n    \"ĠNep\": 27139,\n    \"DD\": 27140,\n    \"Ġbonding\": 27141,\n    \"141\": 27142,\n    \"ĠAssault\": 27143,\n    \"-'\": 27144,\n    \"Ġlodging\": 27145,\n    \"itters\": 27146,\n    \"cigarettes\": 27147,\n    \"Ġ__\": 27148,\n    \"ĠLaf\": 27149,\n    \"GF\": 27150,\n    \"ĠAnat\": 27151,\n    \"ĠStephan\": 27152,\n    \"214\": 27153,\n    \"ĠKass\": 27154,\n    \"Ġviz\": 27155,\n    \"Ġpiling\": 27156,\n    \"Ġfugitive\": 27157,\n    \"ĠCurrency\": 27158,\n    \"ĠCrypto\": 27159,\n    \"Ġfaux\": 27160,\n    \"ĠPing\": 27161,\n    \"ĠLia\": 27162,\n    \"igl\": 27163,\n    \"Ġadversaries\": 27164,\n    \"ĠYPG\": 27165,\n    \"ĠComb\": 27166,\n    \"ĠYar\": 27167,\n    \"heny\": 27168,\n    \"Ġoverhe\": 27169,\n    \"Fest\": 27170,\n    \"emy\": 27171,\n    \"Ever\": 27172,\n    \"Ġ370\": 27173,\n    \"Ġsecretive\": 27174,\n    \"ĠSEN\": 27175,\n    \"ĠMEM\": 27176,\n    \"PRESS\": 27177,\n    \"ĠBirth\": 27178,\n    \"kos\": 27179,\n    \"Ġprecarious\": 27180,\n    \"irting\": 27181,\n    \"ĠUI\": 27182,\n    \"Ġoccupying\": 27183,\n    \"olute\": 27184,\n    \"Ġperiodic\": 27185,\n    \"eon\": 27186,\n    \"iens\": 27187,\n    \"ĠRH\": 27188,\n    \"Win\": 27189,\n    \"Ġplaybook\": 27190,\n    \"Ġexodus\": 27191,\n    \"ĠSkinner\": 27192,\n    \"Ġorderly\": 27193,\n    \"ĠVed\": 27194,\n    \"ouses\": 27195,\n    \"Ġescal\": 27196,\n    \"Ġbenign\": 27197,\n    \"Ġbots\": 27198,\n    \"ĠWhis\": 27199,\n    \"Ġappra\": 27200,\n    \"FOR\": 27201,\n    \"ĠChromebook\": 27202,\n    \"_____\": 27203,\n    \"990\": 27204,\n    \"athed\": 27205,\n    \"Ġspirited\": 27206,\n    \"illi\": 27207,\n    \"Ġbicycles\": 27208,\n    \"orse\": 27209,\n    \"ifestyle\": 27210,\n    \"orno\": 27211,\n    \"ĠDept\": 27212,\n    \"JA\": 27213,\n    \"Ġnausea\": 27214,\n    \"Ġpervasive\": 27215,\n    \"velop\": 27216,\n    \"commun\": 27217,\n    \"ĠUniversities\": 27218,\n    \"Ġremnants\": 27219,\n    \"Ġdisarm\": 27220,\n    \"ĠBoots\": 27221,\n    \"Ġprin\": 27222,\n    \"...\\\"\": 27223,\n    \"quila\": 27224,\n    \"Ġcautiously\": 27225,\n    \"uper\": 27226,\n    \"onto\": 27227,\n    \"din\": 27228,\n    \"Ġvelocity\": 27229,\n    \"Ġconspiring\": 27230,\n    \"ĠMX\": 27231,\n    \"Ġemphasizing\": 27232,\n    \"Ġâĸ\": 27233,\n    \"ĠStam\": 27234,\n    \"Ġspices\": 27235,\n    \"Ġairplanes\": 27236,\n    \"uty\": 27237,\n    \"culture\": 27238,\n    \"ĠPetr\": 27239,\n    \"Ġglor\": 27240,\n    \"ĠExcel\": 27241,\n    \"ĠSpeech\": 27242,\n    \"Ġharmless\": 27243,\n    \"ĠPend\": 27244,\n    \"ĠCrossing\": 27245,\n    \"ĠDocument\": 27246,\n    \"Ġramifications\": 27247,\n    \"ĠCroatian\": 27248,\n    \"ĠKiller\": 27249,\n    \"Ġmultim\": 27250,\n    \"Ġdiscontinued\": 27251,\n    \"Ġcherished\": 27252,\n    \"ĠMaker\": 27253,\n    \"aspers\": 27254,\n    \"ĠBlooming\": 27255,\n    \"ĠMata\": 27256,\n    \"offic\": 27257,\n    \"Ġsettlers\": 27258,\n    \"ĠPlenty\": 27259,\n    \"ĠInstitutes\": 27260,\n    \"ĠArpaio\": 27261,\n    \"Pool\": 27262,\n    \"ĠSubst\": 27263,\n    \"Ġ380\": 27264,\n    \"Ġdecidedly\": 27265,\n    \"ollah\": 27266,\n    \"Den\": 27267,\n    \"ĠJiang\": 27268,\n    \"ĠAmos\": 27269,\n    \"Grand\": 27270,\n    \"ĠTurns\": 27271,\n    \"meyer\": 27272,\n    \"Ġconducive\": 27273,\n    \"Ġpoignant\": 27274,\n    \"abortion\": 27275,\n    \"Ġnotebook\": 27276,\n    \"Ġshelling\": 27277,\n    \"common\": 27278,\n    \"ĠPavel\": 27279,\n    \"Ġhumid\": 27280,\n    \"Ġinappropriately\": 27281,\n    \"????\": 27282,\n    \"Ġsoar\": 27283,\n    \"Ġdynasty\": 27284,\n    \"Ġresearched\": 27285,\n    \"ĠYon\": 27286,\n    \"Ġmaple\": 27287,\n    \"Ġwedge\": 27288,\n    \"mass\": 27289,\n    \"ĠTM\": 27290,\n    \"USE\": 27291,\n    \"eln\": 27292,\n    \"Ġgloss\": 27293,\n    \"rigan\": 27294,\n    \"steen\": 27295,\n    \"ĠDeV\": 27296,\n    \"Ġdebacle\": 27297,\n    \"Christmas\": 27298,\n    \"Ġtweaks\": 27299,\n    \"grab\": 27300,\n    \"Ġprofoundly\": 27301,\n    \"Ġcampaigner\": 27302,\n    \"ĠSeal\": 27303,\n    \"Ġiteration\": 27304,\n    \"Ġsigh\": 27305,\n    \"Ġunfounded\": 27306,\n    \"Ġframing\": 27307,\n    \"Ġrecognizable\": 27308,\n    \"Ġseizing\": 27309,\n    \"legal\": 27310,\n    \"Ġproportions\": 27311,\n    \"omers\": 27312,\n    \"rek\": 27313,\n    \"Ġscreenshot\": 27314,\n    \"itsu\": 27315,\n    \"ĠOG\": 27316,\n    \"ĠYing\": 27317,\n    \"ĠMississ\": 27318,\n    \"295\": 27319,\n    \"Ġlandsl\": 27320,\n    \"Ġpsychiatrist\": 27321,\n    \"sov\": 27322,\n    \"arine\": 27323,\n    \"Ju\": 27324,\n    \"Ġflo\": 27325,\n    \"apple\": 27326,\n    \"hof\": 27327,\n    \"wig\": 27328,\n    \"ĠENT\": 27329,\n    \"Ġenthusiast\": 27330,\n    \"Such\": 27331,\n    \"ĠArtificial\": 27332,\n    \"happy\": 27333,\n    \"oton\": 27334,\n    \"ĠFram\": 27335,\n    \"ĠRemove\": 27336,\n    \"Ġsmear\": 27337,\n    \"Ġjer\": 27338,\n    \"Ġtopp\": 27339,\n    \"Ġimbalance\": 27340,\n    \"ĠWords\": 27341,\n    \"Ġcoffers\": 27342,\n    \"olina\": 27343,\n    \"Ġrigged\": 27344,\n    \"uction\": 27345,\n    \"idding\": 27346,\n    \"Ġdispensaries\": 27347,\n    \"Ġdermat\": 27348,\n    \"Ġshutter\": 27349,\n    \"idental\": 27350,\n    \"Ġcontinu\": 27351,\n    \"Ġhumility\": 27352,\n    \"Ġbulbs\": 27353,\n    \"Ġ207\": 27354,\n    \"lass\": 27355,\n    \"ĠBeirut\": 27356,\n    \"ĠUlt\": 27357,\n    \"urry\": 27358,\n    \"NEWS\": 27359,\n    \"Ġfeminine\": 27360,\n    \"Ġsimulated\": 27361,\n    \"Ġcharger\": 27362,\n    \"mom\": 27363,\n    \"ĠCreed\": 27364,\n    \"Ġwolves\": 27365,\n    \"essions\": 27366,\n    \"created\": 27367,\n    \"ifiers\": 27368,\n    \"Ġdissemin\": 27369,\n    \"ĠDarling\": 27370,\n    \"umann\": 27371,\n    \"Ġmarrying\": 27372,\n    \"Ġshred\": 27373,\n    \"avin\": 27374,\n    \"Ġbudgetary\": 27375,\n    \"Ġmedicinal\": 27376,\n    \"ulin\": 27377,\n    \"seys\": 27378,\n    \"agues\": 27379,\n    \"Ġextracted\": 27380,\n    \"ĠFlower\": 27381,\n    \"Ġcontinents\": 27382,\n    \"ĠWish\": 27383,\n    \"Ġdivides\": 27384,\n    \"ĠDing\": 27385,\n    \"Ġinsulation\": 27386,\n    \"respect\": 27387,\n    \"ĠABS\": 27388,\n    \"Ġreconcile\": 27389,\n    \"keep\": 27390,\n    \"ILD\": 27391,\n    \"Ġgenome\": 27392,\n    \"Ġ410\": 27393,\n    \"ĠSweep\": 27394,\n    \"Ġharass\": 27395,\n    \"Ġfrantic\": 27396,\n    \"ĠEE\": 27397,\n    \"dad\": 27398,\n    \"Ġaperture\": 27399,\n    \"rought\": 27400,\n    \"Ġhugs\": 27401,\n    \"Ġdrying\": 27402,\n    \"Ġoverrun\": 27403,\n    \"Space\": 27404,\n    \"Ġperiodically\": 27405,\n    \"Ġbrightness\": 27406,\n    \"atched\": 27407,\n    \"kee\": 27408,\n    \"ĠITS\": 27409,\n    \"ĠSpokane\": 27410,\n    \"ĠSeaf\": 27411,\n    \"Ġdesks\": 27412,\n    \"ĠEisen\": 27413,\n    \"ĠOPS\": 27414,\n    \"Ġcider\": 27415,\n    \"Ġacceler\": 27416,\n    \"ĠAthlet\": 27417,\n    \"2008\": 27418,\n    \"ĠGuid\": 27419,\n    \"ĠManip\": 27420,\n    \"Ġmould\": 27421,\n    \"Ġmisguided\": 27422,\n    \"Ġbrow\": 27423,\n    \"Ġmanagerial\": 27424,\n    \"Ġhugged\": 27425,\n    \"Ġfurnish\": 27426,\n    \"ĠHarmony\": 27427,\n    \"ĠHebrew\": 27428,\n    \"Ġtyph\": 27429,\n    \"Ġdecreases\": 27430,\n    \"Ġimpetus\": 27431,\n    \"Ġcontagious\": 27432,\n    \"Ġunch\": 27433,\n    \"209\": 27434,\n    \"Ġswell\": 27435,\n    \"ĠHuffington\": 27436,\n    \"Ġpubs\": 27437,\n    \"Ġadequ\": 27438,\n    \"amoto\": 27439,\n    \"rir\": 27440,\n    \"Ġpristine\": 27441,\n    \"Ġanx\": 27442,\n    \"ĠSecure\": 27443,\n    \"Ġenrichment\": 27444,\n    \"ĠVAL\": 27445,\n    \"Ġsummed\": 27446,\n    \"Ġconfidently\": 27447,\n    \"ĠProfit\": 27448,\n    \"ĠFrog\": 27449,\n    \"ĠLena\": 27450,\n    \"ĠFUN\": 27451,\n    \"Ġbruises\": 27452,\n    \"Ġuproar\": 27453,\n    \"coll\": 27454,\n    \"ĠImpro\": 27455,\n    \"Ġflair\": 27456,\n    \"146\": 27457,\n    \"ĠBrend\": 27458,\n    \"Ġ166\": 27459,\n    \"Ġenhances\": 27460,\n    \"ĠDent\": 27461,\n    \"Ġdegener\": 27462,\n    \"Ġproponents\": 27463,\n    \"ĠInspired\": 27464,\n    \"Ġramps\": 27465,\n    \"Ġwisely\": 27466,\n    \"Western\": 27467,\n    \"Ġtart\": 27468,\n    \"Ġsteered\": 27469,\n    \"Ġtreason\": 27470,\n    \"dropping\": 27471,\n    \"Ġtransc\": 27472,\n    \"ĠScarlett\": 27473,\n    \"ĠEzekiel\": 27474,\n    \"Ġpivot\": 27475,\n    \"esame\": 27476,\n    \"Show\": 27477,\n    \"Ġdiscontent\": 27478,\n    \"ĠJudith\": 27479,\n    \"ĠPutting\": 27480,\n    \"Ġblessings\": 27481,\n    \"Ġhardcore\": 27482,\n    \"Ġtray\": 27483,\n    \"Ġdiscern\": 27484,\n    \"oley\": 27485,\n    \"ouk\": 27486,\n    \"Ġwil\": 27487,\n    \"Ġintolerance\": 27488,\n    \"157\": 27489,\n    \"ĠRelative\": 27490,\n    \"ĠLynd\": 27491,\n    \"Ġwhistleblower\": 27492,\n    \"Ġincon\": 27493,\n    \"ĠTao\": 27494,\n    \"Ġindefinite\": 27495,\n    \"Ġguardians\": 27496,\n    \"Ġagon\": 27497,\n    \"ĠInstruments\": 27498,\n    \"Ġexistential\": 27499,\n    \"AAF\": 27500,\n    \"vind\": 27501,\n    \"Ġbrazen\": 27502,\n    \"condition\": 27503,\n    \"Ġratified\": 27504,\n    \"fam\": 27505,\n    \"ĠHin\": 27506,\n    \"ĠMichaels\": 27507,\n    \"204\": 27508,\n    \"ĠKats\": 27509,\n    \"ITS\": 27510,\n    \"ISON\": 27511,\n    \"prone\": 27512,\n    \"Ġboiling\": 27513,\n    \"Ġprolong\": 27514,\n    \"Ġnoticing\": 27515,\n    \"resident\": 27516,\n    \"brance\": 27517,\n    \"ĠFolk\": 27518,\n    \"Ġdesserts\": 27519,\n    \"uton\": 27520,\n    \"Web\": 27521,\n    \"ĠLongh\": 27522,\n    \"ĠReef\": 27523,\n    \"Going\": 27524,\n    \"ĠCarb\": 27525,\n    \"Sur\": 27526,\n    \"complete\": 27527,\n    \"ĠSloan\": 27528,\n    \"ĠClubs\": 27529,\n    \"ĠSadd\": 27530,\n    \"Ġshrugged\": 27531,\n    \"Ġedible\": 27532,\n    \"ĠTyp\": 27533,\n    \"thal\": 27534,\n    \"ĠRocks\": 27535,\n    \"ĠClive\": 27536,\n    \"Ġkidding\": 27537,\n    \"ĠCrom\": 27538,\n    \"ĠTurks\": 27539,\n    \"ĠWak\": 27540,\n    \"Ġeyewitness\": 27541,\n    \"ĠHass\": 27542,\n    \"collar\": 27543,\n    \"Ġsucceeding\": 27544,\n    \"Ġinsert\": 27545,\n    \"Ġ224\": 27546,\n    \"ĠBret\": 27547,\n    \"Ġneurological\": 27548,\n    \"Ġrewrite\": 27549,\n    \"imil\": 27550,\n    \"ultimate\": 27551,\n    \"ĠJeremiah\": 27552,\n    \"Ġliaison\": 27553,\n    \"Ġpedd\": 27554,\n    \"direct\": 27555,\n    \"ĠYi\": 27556,\n    \"ĠMAD\": 27557,\n    \"ĠOrion\": 27558,\n    \"oyd\": 27559,\n    \"ĠLOC\": 27560,\n    \"release\": 27561,\n    \"Ġinvestigates\": 27562,\n    \"ĠApache\": 27563,\n    \"Ã»\": 27564,\n    \"ĠVend\": 27565,\n    \"Ġcynical\": 27566,\n    \"ĠHelm\": 27567,\n    \"ĠMovies\": 27568,\n    \"tops\": 27569,\n    \"Ġsinister\": 27570,\n    \"Ġunparalleled\": 27571,\n    \"Ġspikes\": 27572,\n    \"Ġoverlap\": 27573,\n    \"enstein\": 27574,\n    \"Ġhypocrisy\": 27575,\n    \"Plus\": 27576,\n    \"Ġexpansions\": 27577,\n    \"Ġvow\": 27578,\n    \"Ġdetonated\": 27579,\n    \"Ġfellowship\": 27580,\n    \"Ġsolicitor\": 27581,\n    \"ĠNewtown\": 27582,\n    \"mony\": 27583,\n    \"ĠLod\": 27584,\n    \"ĠDevelopers\": 27585,\n    \"ateg\": 27586,\n    \"ibus\": 27587,\n    \"Ġcrumbling\": 27588,\n    \"ĠWein\": 27589,\n    \"ĠKlan\": 27590,\n    \"gio\": 27591,\n    \"ĠPhys\": 27592,\n    \"ĠAntarctica\": 27593,\n    \"368\": 27594,\n    \"Ġseam\": 27595,\n    \"Ġautomobiles\": 27596,\n    \"ĠTEAM\": 27597,\n    \"bern\": 27598,\n    \"Ġmanic\": 27599,\n    \"Ġsanct\": 27600,\n    \"Ġequals\": 27601,\n    \"Est\": 27602,\n    \"Ġincentiv\": 27603,\n    \"ĠHawking\": 27604,\n    \"nin\": 27605,\n    \"Ġresonate\": 27606,\n    \"bid\": 27607,\n    \"Ġtelescope\": 27608,\n    \"endon\": 27609,\n    \"ĠVacc\": 27610,\n    \"Ġregretted\": 27611,\n    \"Ġ1300\": 27612,\n    \"ĠForestry\": 27613,\n    \"BOOK\": 27614,\n    \"Ġgroundwork\": 27615,\n    \"Ġessays\": 27616,\n    \"ĠIndo\": 27617,\n    \"Pierre\": 27618,\n    \"ĠChau\": 27619,\n    \"Ġapologies\": 27620,\n    \"killers\": 27621,\n    \"ĠMoroccan\": 27622,\n    \"0001\": 27623,\n    \"336\": 27624,\n    \"Ra\": 27625,\n    \"Ġparcels\": 27626,\n    \"Ġleaned\": 27627,\n    \"Ġthankfully\": 27628,\n    \"ĠSplit\": 27629,\n    \"Ġlobbied\": 27630,\n    \"ĠDegree\": 27631,\n    \"Ġrisking\": 27632,\n    \"assy\": 27633,\n    \"Ġsupplemental\": 27634,\n    \"little\": 27635,\n    \"Ġeclectic\": 27636,\n    \"Ġ206\": 27637,\n    \"ealing\": 27638,\n    \"206\": 27639,\n    \"Ġrepo\": 27640,\n    \"Ġhose\": 27641,\n    \"ayn\": 27642,\n    \"lux\": 27643,\n    \"Ġbeliever\": 27644,\n    \"')\": 27645,\n    \"ĠHide\": 27646,\n    \"vance\": 27647,\n    \"ĠEinstein\": 27648,\n    \"Ġdepos\": 27649,\n    \"Ġfray\": 27650,\n    \"Ġki\": 27651,\n    \"Ġinternship\": 27652,\n    \"ĠHou\": 27653,\n    \"Vis\": 27654,\n    \"Ġstare\": 27655,\n    \"ĠBreed\": 27656,\n    \"option\": 27657,\n    \"Ġvisionary\": 27658,\n    \"Ġmins\": 27659,\n    \"Ġbitten\": 27660,\n    \"ancies\": 27661,\n    \"ĠShake\": 27662,\n    \"Ġtemplate\": 27663,\n    \"Ġliner\": 27664,\n    \"Ġmuster\": 27665,\n    \"appro\": 27666,\n    \"ĠMubarak\": 27667,\n    \"esty\": 27668,\n    \"mong\": 27669,\n    \"actory\": 27670,\n    \"Ġheadphone\": 27671,\n    \"ĠPrec\": 27672,\n    \"Ġwaive\": 27673,\n    \"Ron\": 27674,\n    \"ĠHearing\": 27675,\n    \"Ġimperfect\": 27676,\n    \"Ġsealing\": 27677,\n    \"Ġlocating\": 27678,\n    \"Ġculminated\": 27679,\n    \"chio\": 27680,\n    \"channel\": 27681,\n    \"lust\": 27682,\n    \"ĠLowell\": 27683,\n    \"woods\": 27684,\n    \"Ġsoak\": 27685,\n    \"Ġforbidden\": 27686,\n    \"Ġdetached\": 27687,\n    \"unct\": 27688,\n    \"ĠHunger\": 27689,\n    \"ĠPatient\": 27690,\n    \"ĠPolo\": 27691,\n    \"Saharan\": 27692,\n    \"Jon\": 27693,\n    \"athered\": 27694,\n    \"ĠSignal\": 27695,\n    \"Six\": 27696,\n    \"Ġstatistically\": 27697,\n    \"ITH\": 27698,\n    \"artment\": 27699,\n    \"ĠCU\": 27700,\n    \"Ġhates\": 27701,\n    \"qual\": 27702,\n    \"Ġcapitalist\": 27703,\n    \"ATES\": 27704,\n    \"ĠDesc\": 27705,\n    \"Ġhandcuffed\": 27706,\n    \"Ġindulge\": 27707,\n    \"ĠReligious\": 27708,\n    \"German\": 27709,\n    \"housing\": 27710,\n    \"Ġdismantling\": 27711,\n    \"Ġconventions\": 27712,\n    \"dain\": 27713,\n    \"chairs\": 27714,\n    \"Ġloos\": 27715,\n    \"Ġknowingly\": 27716,\n    \"Var\": 27717,\n    \"Ġhusbands\": 27718,\n    \"eez\": 27719,\n    \"asion\": 27720,\n    \"ĠIssa\": 27721,\n    \"Ġswollen\": 27722,\n    \"Ġ1946\": 27723,\n    \"Ġheadlined\": 27724,\n    \"Chelsea\": 27725,\n    \"Ġignorant\": 27726,\n    \"Ġperipheral\": 27727,\n    \"Note\": 27728,\n    \"Ġaxe\": 27729,\n    \"Ġnicotine\": 27730,\n    \"ĠSanctuary\": 27731,\n    \"Ġ1917\": 27732,\n    \"Ġwithdrawals\": 27733,\n    \"uits\": 27734,\n    \"Hot\": 27735,\n    \"Ġreimburse\": 27736,\n    \"probably\": 27737,\n    \"ĠAdapt\": 27738,\n    \"industrial\": 27739,\n    \"answer\": 27740,\n    \"orus\": 27741,\n    \"ĠMell\": 27742,\n    \"Talk\": 27743,\n    \"Ġcontemplating\": 27744,\n    \"omas\": 27745,\n    \"Ġtaxis\": 27746,\n    \"Ġencompasses\": 27747,\n    \"rations\": 27748,\n    \"ĠLatvia\": 27749,\n    \"Ġhumiliating\": 27750,\n    \"Ġloft\": 27751,\n    \"tight\": 27752,\n    \"rium\": 27753,\n    \"Ġlogin\": 27754,\n    \"ĠBulletin\": 27755,\n    \"Ġturtles\": 27756,\n    \"EAR\": 27757,\n    \"349\": 27758,\n    \"Radio\": 27759,\n    \"ĠBord\": 27760,\n    \"151\": 27761,\n    \"kk\": 27762,\n    \"pocket\": 27763,\n    \"Ġdove\": 27764,\n    \"348\": 27765,\n    \"Ġtemptation\": 27766,\n    \"ĠCoy\": 27767,\n    \"those\": 27768,\n    \"ĠDest\": 27769,\n    \"ishly\": 27770,\n    \"rn\": 27771,\n    \"Ġmammals\": 27772,\n    \"ĠTub\": 27773,\n    \"arial\": 27774,\n    \"ĠPersian\": 27775,\n    \"Ġdaddy\": 27776,\n    \"Zen\": 27777,\n    \"Ġps\": 27778,\n    \"Ġ]\": 27779,\n    \"Field\": 27780,\n    \"adiq\": 27781,\n    \"Ġmeaningless\": 27782,\n    \"Ġprimer\": 27783,\n    \"Ġ1942\": 27784,\n    \"Ġ!\": 27785,\n    \"625\": 27786,\n    \"Ġfashionable\": 27787,\n    \"ĠTheft\": 27788,\n    \"ĠHAVE\": 27789,\n    \"christ\": 27790,\n    \"Ġperil\": 27791,\n    \"Ġrepealing\": 27792,\n    \"Ġbuff\": 27793,\n    \"Ġodor\": 27794,\n    \"Ġstalking\": 27795,\n    \"ĠDems\": 27796,\n    \"iences\": 27797,\n    \"Ġunilaterally\": 27798,\n    \"odies\": 27799,\n    \"ĠQuite\": 27800,\n    \"Ġbloodshed\": 27801,\n    \"Ġinfect\": 27802,\n    \"Ġreminders\": 27803,\n    \"Ġchop\": 27804,\n    \"Ġevapor\": 27805,\n    \"877\": 27806,\n    \"Ġhorrified\": 27807,\n    \"ĠFruit\": 27808,\n    \"rams\": 27809,\n    \"Ġinsecure\": 27810,\n    \"cester\": 27811,\n    \"ĠNationwide\": 27812,\n    \"Ġmocking\": 27813,\n    \"Ret\": 27814,\n    \"Ġcomplying\": 27815,\n    \"sav\": 27816,\n    \"Ġali\": 27817,\n    \"Family\": 27818,\n    \"Ĩ\": 27819,\n    \"Ġdishonest\": 27820,\n    \"Ġincorrectly\": 27821,\n    \"LOAD\": 27822,\n    \"ĠGand\": 27823,\n    \"ourcing\": 27824,\n    \"obby\": 27825,\n    \"ĠPetersen\": 27826,\n    \"Something\": 27827,\n    \"Ġravaged\": 27828,\n    \"limited\": 27829,\n    \"Ġrituals\": 27830,\n    \"ĠKnowledge\": 27831,\n    \"ĠUtility\": 27832,\n    \"Ġdoom\": 27833,\n    \"Ġsheds\": 27834,\n    \"ĠGael\": 27835,\n    \"ĠMillennials\": 27836,\n    \"ĠMonthly\": 27837,\n    \"Ġdomination\": 27838,\n    \"Ġrapport\": 27839,\n    \"spot\": 27840,\n    \"ĠPrest\": 27841,\n    \"ĠHA\": 27842,\n    \"ushes\": 27843,\n    \"Ġtact\": 27844,\n    \"Richard\": 27845,\n    \"Ġgritty\": 27846,\n    \"Does\": 27847,\n    \"ĠTNT\": 27848,\n    \"Ġdownfall\": 27849,\n    \"Wood\": 27850,\n    \"ĠPrediction\": 27851,\n    \"ĠPour\": 27852,\n    \"ĠFraud\": 27853,\n    \"ĠSyndrome\": 27854,\n    \"166\": 27855,\n    \"Ġliteral\": 27856,\n    \"Ġaddict\": 27857,\n    \"ĠLoud\": 27858,\n    \"hens\": 27859,\n    \"ĠAccounts\": 27860,\n    \"distance\": 27861,\n    \"Ġclassmate\": 27862,\n    \"Ġsalv\": 27863,\n    \"Ġunlucky\": 27864,\n    \"Ġpartying\": 27865,\n    \"ĠKou\": 27866,\n    \"ĠSNAP\": 27867,\n    \"%-\": 27868,\n    \"Ġdelegate\": 27869,\n    \"Ġstrikers\": 27870,\n    \"ĠSlate\": 27871,\n    \"Ġarticulate\": 27872,\n    \"390\": 27873,\n    \"Ġinqu\": 27874,\n    \"Ġdiscredit\": 27875,\n    \"ĠPriv\": 27876,\n    \"ploy\": 27877,\n    \"ĠMarketplace\": 27878,\n    \"ĠTune\": 27879,\n    \"visor\": 27880,\n    \"Ġwrestle\": 27881,\n    \"Ġkindly\": 27882,\n    \"ĠCollect\": 27883,\n    \"Ġcirc\": 27884,\n    \"ĠRemain\": 27885,\n    \"Ġ192\": 27886,\n    \"contin\": 27887,\n    \"Ġ325\": 27888,\n    \"Ġsevered\": 27889,\n    \"isations\": 27890,\n    \"Ġmuddy\": 27891,\n    \"Ġtaxing\": 27892,\n    \"ĠRepresent\": 27893,\n    \"ĠSty\": 27894,\n    \"rology\": 27895,\n    \"ĠJudges\": 27896,\n    \"ĠBronze\": 27897,\n    \"ĠApplic\": 27898,\n    \"Ġarrow\": 27899,\n    \"consuming\": 27900,\n    \"ĠFeaturing\": 27901,\n    \"Ġspies\": 27902,\n    \"Ġnoises\": 27903,\n    \"ĠColony\": 27904,\n    \"lost\": 27905,\n    \"Ġopp\": 27906,\n    \"Ġdeem\": 27907,\n    \"ĠGarc\": 27908,\n    \"icent\": 27909,\n    \"ptroller\": 27910,\n    \"liest\": 27911,\n    \"Ġoutward\": 27912,\n    \"ĠUser\": 27913,\n    \"Ġintimidate\": 27914,\n    \"156\": 27915,\n    \"Ġjab\": 27916,\n    \"ANGE\": 27917,\n    \"Jay\": 27918,\n    \"ĠPoverty\": 27919,\n    \"ACA\": 27920,\n    \"Ġrife\": 27921,\n    \"Ġfaint\": 27922,\n    \"ĠAcceler\": 27923,\n    \"tall\": 27924,\n    \"ĠUNITED\": 27925,\n    \"ĠFighter\": 27926,\n    \"ĠGilmore\": 27927,\n    \"Ġsod\": 27928,\n    \"amura\": 27929,\n    \"Ġpredictive\": 27930,\n    \"Ġpolish\": 27931,\n    \"ĠDD\": 27932,\n    \"Ġfabricated\": 27933,\n    \"ĠDag\": 27934,\n    \"Ġfatty\": 27935,\n    \"Ġplague\": 27936,\n    \"Ġexhib\": 27937,\n    \"ĠAdvent\": 27938,\n    \"Ġ1941\": 27939,\n    \"ERSON\": 27940,\n    \"initely\": 27941,\n    \"Ġloneliness\": 27942,\n    \"ĠEquality\": 27943,\n    \"Ġuntrue\": 27944,\n    \"Ġonlook\": 27945,\n    \"Ġfragmented\": 27946,\n    \"ruce\": 27947,\n    \"Ġdistrust\": 27948,\n    \"Ġscal\": 27949,\n    \"ĠCors\": 27950,\n    \"Ġrobbing\": 27951,\n    \"cultural\": 27952,\n    \"clusion\": 27953,\n    \"ĠObi\": 27954,\n    \"sels\": 27955,\n    \"ĠEvidence\": 27956,\n    \"ĠSac\": 27957,\n    \"Ġfragments\": 27958,\n    \"Ġflipping\": 27959,\n    \"ĠRabbit\": 27960,\n    \"Ġdisproportionate\": 27961,\n    \"ĠCreat\": 27962,\n    \"Ġlabeling\": 27963,\n    \"ĠGri\": 27964,\n    \"Ġ161\": 27965,\n    \"ĠEditors\": 27966,\n    \"holm\": 27967,\n    \"adr\": 27968,\n    \"Ĭ\": 27969,\n    \"tailed\": 27970,\n    \"Ġrenters\": 27971,\n    \"Ġnoodles\": 27972,\n    \"Ġcompetence\": 27973,\n    \"Ġpanc\": 27974,\n    \"uration\": 27975,\n    \"Ġacids\": 27976,\n    \"Ġconfid\": 27977,\n    \"rival\": 27978,\n    \"AAA\": 27979,\n    \"kson\": 27980,\n    \"Ġrecreate\": 27981,\n    \"153\": 27982,\n    \"Ġ164\": 27983,\n    \"ĠOlympia\": 27984,\n    \"ĠUnlimited\": 27985,\n    \"ĠShock\": 27986,\n    \"ĠTeaching\": 27987,\n    \"ĠHouses\": 27988,\n    \"resso\": 27989,\n    \"ĠMaw\": 27990,\n    \"Ġreplen\": 27991,\n    \"Ġprotestors\": 27992,\n    \"bey\": 27993,\n    \"Ġsurve\": 27994,\n    \"Ġemphasizes\": 27995,\n    \"223\": 27996,\n    \"ĠEsther\": 27997,\n    \"ĠNikol\": 27998,\n    \"Ġprosecutions\": 27999,\n    \"ĠFreed\": 28000,\n    \"Ġposs\": 28001,\n    \"OTE\": 28002,\n    \"ĠPrayer\": 28003,\n    \"Ġsquarely\": 28004,\n    \"Ġtir\": 28005,\n    \"adv\": 28006,\n    \"Ġbogus\": 28007,\n    \"Ġwrongful\": 28008,\n    \"Ġembell\": 28009,\n    \"Ġseldom\": 28010,\n    \"Ġpossesses\": 28011,\n    \"Er\": 28012,\n    \"ĠAlternatively\": 28013,\n    \"Ġinstituted\": 28014,\n    \"rr\": 28015,\n    \"Ġvocational\": 28016,\n    \"eval\": 28017,\n    \"ĠComics\": 28018,\n    \"Ġstumbling\": 28019,\n    \"335\": 28020,\n    \"Ġdragon\": 28021,\n    \"vine\": 28022,\n    \"services\": 28023,\n    \"Ġcrit\": 28024,\n    \"irens\": 28025,\n    \"Ġlayered\": 28026,\n    \"orb\": 28027,\n    \"Ġdominates\": 28028,\n    \"ĠMarx\": 28029,\n    \"period\": 28030,\n    \"avering\": 28031,\n    \"Ġbrigade\": 28032,\n    \"Ġchem\": 28033,\n    \"ĠEvolution\": 28034,\n    \"ĠSuk\": 28035,\n    \"Ġ209\": 28036,\n    \"ĠMalk\": 28037,\n    \"Ġtallest\": 28038,\n    \"recogn\": 28039,\n    \"ĠCraw\": 28040,\n    \"Ġell\": 28041,\n    \"ĠCaesar\": 28042,\n    \"php\": 28043,\n    \"ĠSurvivors\": 28044,\n    \"sd\": 28045,\n    \"itsch\": 28046,\n    \"ambo\": 28047,\n    \"Ġashore\": 28048,\n    \"acular\": 28049,\n    \"rost\": 28050,\n    \"Ġmurderer\": 28051,\n    \"Ġcasts\": 28052,\n    \"ĠEconomist\": 28053,\n    \"ĠWeapons\": 28054,\n    \"Ġnostalgic\": 28055,\n    \"Skip\": 28056,\n    \"REAM\": 28057,\n    \"Pa\": 28058,\n    \"Ġjournals\": 28059,\n    \"ĠSitting\": 28060,\n    \"Union\": 28061,\n    \"Att\": 28062,\n    \"ĠMaxim\": 28063,\n    \"Ġpurportedly\": 28064,\n    \"Ġrespecting\": 28065,\n    \"ĠMAX\": 28066,\n    \"seed\": 28067,\n    \"Ġjuicy\": 28068,\n    \"ĠGallup\": 28069,\n    \"Ġmileage\": 28070,\n    \"adier\": 28071,\n    \"Ġbod\": 28072,\n    \"DER\": 28073,\n    \"Ġsummers\": 28074,\n    \"icult\": 28075,\n    \"ipl\": 28076,\n    \"ĠDeng\": 28077,\n    \"Ġsmells\": 28078,\n    \"Ġivory\": 28079,\n    \"Ġ255\": 28080,\n    \"Id\": 28081,\n    \"DEN\": 28082,\n    \"Ġ159\": 28083,\n    \"Due\": 28084,\n    \"ĠLighting\": 28085,\n    \"ĠSurely\": 28086,\n    \"Ġsund\": 28087,\n    \"ĠKessler\": 28088,\n    \"immigrant\": 28089,\n    \"Ġtragedies\": 28090,\n    \"ĠOxy\": 28091,\n    \"ĠFixed\": 28092,\n    \"ĠBalk\": 28093,\n    \"Ġoriented\": 28094,\n    \"pher\": 28095,\n    \"Ġkitchens\": 28096,\n    \"Ġhips\": 28097,\n    \"Ġtweak\": 28098,\n    \"Ġtuna\": 28099,\n    \"ĠCla\": 28100,\n    \"Ġdislike\": 28101,\n    \"ussy\": 28102,\n    \"Ġoutnumbered\": 28103,\n    \"Ġplumbing\": 28104,\n    \"Ġcogn\": 28105,\n    \"ĠThrow\": 28106,\n    \"ĠTER\": 28107,\n    \"urally\": 28108,\n    \"ĠMurd\": 28109,\n    \"Ġcreamy\": 28110,\n    \"Ġresiding\": 28111,\n    \"otics\": 28112,\n    \"Ġfingerprints\": 28113,\n    \"!,\": 28114,\n    \"Ġpaused\": 28115,\n    \"ĠMilo\": 28116,\n    \"Ġhomosexuality\": 28117,\n    \"Ġresponsibly\": 28118,\n    \"iop\": 28119,\n    \"UCT\": 28120,\n    \"Ġsucceeds\": 28121,\n    \"ĠCRE\": 28122,\n    \"ĠThatcher\": 28123,\n    \"Ġcurrents\": 28124,\n    \"Ġarises\": 28125,\n    \"Ġwaterproof\": 28126,\n    \"Ġamp\": 28127,\n    \"ĠClaims\": 28128,\n    \"177\": 28129,\n    \"Ġsubpoen\": 28130,\n    \"Ġvig\": 28131,\n    \"ĠNeuro\": 28132,\n    \"Ġblur\": 28133,\n    \"ĠPaint\": 28134,\n    \"campus\": 28135,\n    \"Ġtoughness\": 28136,\n    \"ĠButton\": 28137,\n    \"Neal\": 28138,\n    \"ĠDEN\": 28139,\n    \"ĠNir\": 28140,\n    \"ĠAxel\": 28141,\n    \"EEP\": 28142,\n    \"Ġpint\": 28143,\n    \"Ġagile\": 28144,\n    \"odor\": 28145,\n    \"Ġessentials\": 28146,\n    \"ĠMov\": 28147,\n    \"ĠVenezuel\": 28148,\n    \"Ġexchanging\": 28149,\n    \"ĠNegative\": 28150,\n    \"Mil\": 28151,\n    \"Key\": 28152,\n    \"Ġbuzzing\": 28153,\n    \"ĠStew\": 28154,\n    \"Ġrebuke\": 28155,\n    \"Ġdepl\": 28156,\n    \"ĠKoz\": 28157,\n    \"Ġ163\": 28158,\n    \"Ġshines\": 28159,\n    \"NZ\": 28160,\n    \"Ġcarnage\": 28161,\n    \"cases\": 28162,\n    \"Ġwarmed\": 28163,\n    \"ĠGreenwich\": 28164,\n    \"College\": 28165,\n    \"Ġneedy\": 28166,\n    \"301\": 28167,\n    \"ĠMÃ¼\": 28168,\n    \"culation\": 28169,\n    \"Ġ440\": 28170,\n    \"425\": 28171,\n    \"atories\": 28172,\n    \"Ġsatisfactory\": 28173,\n    \"ĠFib\": 28174,\n    \"ĠElim\": 28175,\n    \"developed\": 28176,\n    \"Ġvacations\": 28177,\n    \"Ġpeculiar\": 28178,\n    \"Ġvets\": 28179,\n    \"onest\": 28180,\n    \"ĠPug\": 28181,\n    \"Ġlifestyles\": 28182,\n    \"zzi\": 28183,\n    \"Ġprovoke\": 28184,\n    \"bah\": 28185,\n    \"arger\": 28186,\n    \"ĠVirt\": 28187,\n    \"Sales\": 28188,\n    \"annel\": 28189,\n    \"ĠMeth\": 28190,\n    \"ivating\": 28191,\n    \"Ġrevoke\": 28192,\n    \"ĠAgenda\": 28193,\n    \"ĠIch\": 28194,\n    \"Ġsensit\": 28195,\n    \"ĠAzerbai\": 28196,\n    \"ĠBombay\": 28197,\n    \"Ġuncon\": 28198,\n    \"river\": 28199,\n    \"Ġapr\": 28200,\n    \"actic\": 28201,\n    \"ĠSubaru\": 28202,\n    \"Ġbanquet\": 28203,\n    \"Ġcontradict\": 28204,\n    \"tek\": 28205,\n    \"Football\": 28206,\n    \"igent\": 28207,\n    \"Ġreintrodu\": 28208,\n    \"ĠInsight\": 28209,\n    \"Ġsystematically\": 28210,\n    \"Ġboun\": 28211,\n    \"ĠFishing\": 28212,\n    \"Ġstri\": 28213,\n    \"ĠOB\": 28214,\n    \"Ġstair\": 28215,\n    \"Wall\": 28216,\n    \"ĠAllow\": 28217,\n    \"Ġcaramel\": 28218,\n    \"169\": 28219,\n    \"Ġcafes\": 28220,\n    \"Ġcalcium\": 28221,\n    \"Ġ169\": 28222,\n    \"Ġportraying\": 28223,\n    \"Ġdiscriminate\": 28224,\n    \"Ġunrestricted\": 28225,\n    \"Ġmant\": 28226,\n    \"Ġscarcity\": 28227,\n    \"Ġfeminism\": 28228,\n    \"ĠJJ\": 28229,\n    \"ĠOversight\": 28230,\n    \"ĠCue\": 28231,\n    \"Ġinexperienced\": 28232,\n    \"Ġdrafts\": 28233,\n    \"Ġ1939\": 28234,\n    \"nm\": 28235,\n    \"forest\": 28236,\n    \"ĠHonour\": 28237,\n    \"Ġceramic\": 28238,\n    \"Ġdownstairs\": 28239,\n    \"Ġboon\": 28240,\n    \"Ġmorality\": 28241,\n    \"Ġhorrifying\": 28242,\n    \"Rad\": 28243,\n    \"justice\": 28244,\n    \"Ġmosques\": 28245,\n    \"Ġcurfew\": 28246,\n    \"Ġsurrogate\": 28247,\n    \"Ġreimb\": 28248,\n    \"enth\": 28249,\n    \"pressure\": 28250,\n    \"beam\": 28251,\n    \"Ġwhirlwind\": 28252,\n    \"ĠRecession\": 28253,\n    \"ĠTours\": 28254,\n    \"Ġclusters\": 28255,\n    \"ĠQuant\": 28256,\n    \"Jonathan\": 28257,\n    \"project\": 28258,\n    \"Ġ777\": 28259,\n    \"ĠNOAA\": 28260,\n    \"abis\": 28261,\n    \"Ġdeficiencies\": 28262,\n    \"Ġsuicides\": 28263,\n    \"Ġfoothold\": 28264,\n    \"ĠYah\": 28265,\n    \"imeter\": 28266,\n    \"URN\": 28267,\n    \"Ġcultivate\": 28268,\n    \"Ġnoisy\": 28269,\n    \"Ġ1951\": 28270,\n    \"Ġpressuring\": 28271,\n    \"ĠDeals\": 28272,\n    \"ĠProphet\": 28273,\n    \"ĠWikipedia\": 28274,\n    \"INESS\": 28275,\n    \"ĠShine\": 28276,\n    \"ĠCalled\": 28277,\n    \"ĠSole\": 28278,\n    \"ĠZhou\": 28279,\n    \"Ġasphalt\": 28280,\n    \"armac\": 28281,\n    \"ĠScorp\": 28282,\n    \"ĠUnknown\": 28283,\n    \"ĠPAT\": 28284,\n    \"Heart\": 28285,\n    \"Ġguessed\": 28286,\n    \"Ġsushi\": 28287,\n    \"Ġheartbeat\": 28288,\n    \"Ġconcent\": 28289,\n    \"eret\": 28290,\n    \"plin\": 28291,\n    \"Ġweeds\": 28292,\n    \"Ġbombed\": 28293,\n    \"ĠTerrorism\": 28294,\n    \"Rich\": 28295,\n    \"Ġblades\": 28296,\n    \"Ġhaunt\": 28297,\n    \"Ġstorefront\": 28298,\n    \"Ġthwarted\": 28299,\n    \"access\": 28300,\n    \"ĠLydia\": 28301,\n    \"LINE\": 28302,\n    \"Ġpregnancies\": 28303,\n    \"Ġripping\": 28304,\n    \"ĠBelieve\": 28305,\n    \"spoken\": 28306,\n    \"inian\": 28307,\n    \"sed\": 28308,\n    \"ĠBrass\": 28309,\n    \"econom\": 28310,\n    \"current\": 28311,\n    \"Ġvoc\": 28312,\n    \"Ġmodeled\": 28313,\n    \"Ġpeppers\": 28314,\n    \"otech\": 28315,\n    \"ĠOption\": 28316,\n    \"Connell\": 28317,\n    \"isel\": 28318,\n    \"Ġcompel\": 28319,\n    \"Ġjuveniles\": 28320,\n    \"ĠNET\": 28321,\n    \"ĠEXP\": 28322,\n    \"Ġparadigm\": 28323,\n    \"Des\": 28324,\n    \"Ġ204\": 28325,\n    \"employed\": 28326,\n    \"Ġdurability\": 28327,\n    \"Ġ245\": 28328,\n    \"Ġbillionaires\": 28329,\n    \"violent\": 28330,\n    \"ĠCooperative\": 28331,\n    \"TOP\": 28332,\n    \"ĠGarry\": 28333,\n    \"ĠSoldiers\": 28334,\n    \"Ġdared\": 28335,\n    \"Ġvoucher\": 28336,\n    \"Ġblends\": 28337,\n    \"gue\": 28338,\n    \"Ġadventurous\": 28339,\n    \"Ġorganisms\": 28340,\n    \"Ġgaze\": 28341,\n    \"Ġcrap\": 28342,\n    \"Coach\": 28343,\n    \"omon\": 28344,\n    \"ĠWheels\": 28345,\n    \"ĠGrayson\": 28346,\n    \"Ġrecy\": 28347,\n    \"grave\": 28348,\n    \"Ġallergic\": 28349,\n    \"Ġreef\": 28350,\n    \"Ġbeginnings\": 28351,\n    \"ĠRuff\": 28352,\n    \"Ġclout\": 28353,\n    \"structed\": 28354,\n    \"315\": 28355,\n    \"ĠGeorgian\": 28356,\n    \"say\": 28357,\n    \"Ġsprings\": 28358,\n    \"ĠAsus\": 28359,\n    \"Ġrepaid\": 28360,\n    \"ĠGuys\": 28361,\n    \"ticket\": 28362,\n    \"Ġunb\": 28363,\n    \"ĠCertificate\": 28364,\n    \"ĠSTORY\": 28365,\n    \"cin\": 28366,\n    \"Ġpassions\": 28367,\n    \"Ġmediocre\": 28368,\n    \"Ġlackluster\": 28369,\n    \"vernight\": 28370,\n    \"kids\": 28371,\n    \"ĠWife\": 28372,\n    \"politics\": 28373,\n    \"ĠHimal\": 28374,\n    \"oddy\": 28375,\n    \"ensus\": 28376,\n    \"ĠGustav\": 28377,\n    \"binding\": 28378,\n    \"ĠIndividuals\": 28379,\n    \"Ġmaize\": 28380,\n    \"Ġhoop\": 28381,\n    \"ĠChanging\": 28382,\n    \"Ġlessen\": 28383,\n    \"Ġarranging\": 28384,\n    \"ĠFukushima\": 28385,\n    \"ĠTrying\": 28386,\n    \"ĠMage\": 28387,\n    \"Ġskeleton\": 28388,\n    \"ĠTec\": 28389,\n    \"289\": 28390,\n    \"Ġrecl\": 28391,\n    \"ĠFIL\": 28392,\n    \"Gs\": 28393,\n    \"ĠOdyssey\": 28394,\n    \"ĠProcessing\": 28395,\n    \"ilion\": 28396,\n    \"Ġsubsidized\": 28397,\n    \"Ġabdomen\": 28398,\n    \"Ġanalyse\": 28399,\n    \"music\": 28400,\n    \"clean\": 28401,\n    \"Ġunfinished\": 28402,\n    \"Ġdownloads\": 28403,\n    \"Ġmorally\": 28404,\n    \"Ġ218\": 28405,\n    \"Ġtrib\": 28406,\n    \"Keep\": 28407,\n    \"ĠSER\": 28408,\n    \"FY\": 28409,\n    \"Ġaust\": 28410,\n    \"Ġdiscovers\": 28411,\n    \"ĠGROUP\": 28412,\n    \"ĠMachines\": 28413,\n    \"Ġeroded\": 28414,\n    \"Ġominous\": 28415,\n    \"Ġbrightly\": 28416,\n    \"IME\": 28417,\n    \"Ġwicked\": 28418,\n    \"ĠTrou\": 28419,\n    \"Ġvisions\": 28420,\n    \"Kay\": 28421,\n    \"reported\": 28422,\n    \"Ġbog\": 28423,\n    \"ĠQuin\": 28424,\n    \"ĠSigma\": 28425,\n    \"urned\": 28426,\n    \"ixon\": 28427,\n    \"Ġharming\": 28428,\n    \"Ġcheckout\": 28429,\n    \"inet\": 28430,\n    \"much\": 28431,\n    \"Ġcherish\": 28432,\n    \"ĠByrd\": 28433,\n    \"ĠSamson\": 28434,\n    \"WP\": 28435,\n    \"orders\": 28436,\n    \"boa\": 28437,\n    \"Ġbron\": 28438,\n    \"oki\": 28439,\n    \"ĠRR\": 28440,\n    \"Ġsuitcase\": 28441,\n    \"Ġfeathers\": 28442,\n    \"ĠChristy\": 28443,\n    \"Islamic\": 28444,\n    \"Ġamusement\": 28445,\n    \"ĠISS\": 28446,\n    \"intensive\": 28447,\n    \"Qaida\": 28448,\n    \"Ġneurons\": 28449,\n    \"Ġwagon\": 28450,\n    \"ĠTek\": 28451,\n    \"Ġdolls\": 28452,\n    \"ĠShoot\": 28453,\n    \"Ġunderestimate\": 28454,\n    \"Ġstreamlined\": 28455,\n    \"Ġfractures\": 28456,\n    \"Ġcathedral\": 28457,\n    \"Ġeliminates\": 28458,\n    \"helle\": 28459,\n    \"Ġcitrus\": 28460,\n    \"risis\": 28461,\n    \"Ġimpecc\": 28462,\n    \"istries\": 28463,\n    \"ĠHog\": 28464,\n    \"vote\": 28465,\n    \"pas\": 28466,\n    \"Ġassign\": 28467,\n    \"ĠSongs\": 28468,\n    \"ĠMiracle\": 28469,\n    \"kas\": 28470,\n    \"zynski\": 28471,\n    \"Ġcrane\": 28472,\n    \"Ġadulthood\": 28473,\n    \"ĠBenefit\": 28474,\n    \"ĠGrimes\": 28475,\n    \"Ġpayday\": 28476,\n    \"ablished\": 28477,\n    \"Ġcenterpiece\": 28478,\n    \"Ġhassle\": 28479,\n    \"ĠAppalachian\": 28480,\n    \"follow\": 28481,\n    \"Ġ290\": 28482,\n    \"ĠRL\": 28483,\n    \"ĠDoe\": 28484,\n    \"Ġacclaim\": 28485,\n    \"Ġlevied\": 28486,\n    \"Ġtossing\": 28487,\n    \"Ġcarrots\": 28488,\n    \"ĠDarius\": 28489,\n    \"161\": 28490,\n    \"Ġoffspring\": 28491,\n    \"ĠJury\": 28492,\n    \"ĠTPP\": 28493,\n    \"CAP\": 28494,\n    \"Ġenvironmentalists\": 28495,\n    \"Ġrays\": 28496,\n    \"267\": 28497,\n    \"Ser\": 28498,\n    \"Ġcaptivity\": 28499,\n    \"Ġappellate\": 28500,\n    \"ĠElectricity\": 28501,\n    \"ĠEnough\": 28502,\n    \"232\": 28503,\n    \"Ġfisher\": 28504,\n    \"Ġbrilliance\": 28505,\n    \"Ġpraises\": 28506,\n    \"aunch\": 28507,\n    \"Ġsolicitation\": 28508,\n    \"Ġadolescent\": 28509,\n    \"Ġinferior\": 28510,\n    \"checks\": 28511,\n    \"Set\": 28512,\n    \"Ġmutations\": 28513,\n    \"ĠLatinos\": 28514,\n    \"ĠLicense\": 28515,\n    \"ĠAme\": 28516,\n    \"hirt\": 28517,\n    \"ĠChun\": 28518,\n    \"Ġdeeds\": 28519,\n    \"ldon\": 28520,\n    \"Ġmammoth\": 28521,\n    \"Ġturtle\": 28522,\n    \"rule\": 28523,\n    \"Ken\": 28524,\n    \"Ġvoyage\": 28525,\n    \"gram\": 28526,\n    \"Ġconquer\": 28527,\n    \"Ġretaliate\": 28528,\n    \"ĠPJ\": 28529,\n    \"ĠViking\": 28530,\n    \"Ġsafegu\": 28531,\n    \"ordinary\": 28532,\n    \"ĠArbit\": 28533,\n    \"ĠDigest\": 28534,\n    \"Die\": 28535,\n    \"Ġbureaucratic\": 28536,\n    \"Ġhonorable\": 28537,\n    \"Ġcafeteria\": 28538,\n    \"ĠRAF\": 28539,\n    \"ĠPlaces\": 28540,\n    \"ĠKlu\": 28541,\n    \"Cam\": 28542,\n    \"ĠBiology\": 28543,\n    \"ĠCycling\": 28544,\n    \"imore\": 28545,\n    \"Ġstripping\": 28546,\n    \"Ġwarriors\": 28547,\n    \"Ġbursting\": 28548,\n    \"Ġlapse\": 28549,\n    \"Ġversa\": 28550,\n    \"Ġclicked\": 28551,\n    \"ogh\": 28552,\n    \"Ġ\\\"âĢ¦\": 28553,\n    \"Ġdiligently\": 28554,\n    \"ĠMiy\": 28555,\n    \"ĠCorpus\": 28556,\n    \"Ġredef\": 28557,\n    \"Ġ176\": 28558,\n    \"ĠInstrument\": 28559,\n    \"ĠOECD\": 28560,\n    \"Ġstro\": 28561,\n    \"Ġmicrowave\": 28562,\n    \"Santa\": 28563,\n    \"Ġpars\": 28564,\n    \"Social\": 28565,\n    \"iffe\": 28566,\n    \"itability\": 28567,\n    \"Equ\": 28568,\n    \"Ġnud\": 28569,\n    \"legged\": 28570,\n    \"ĠTud\": 28571,\n    \"lav\": 28572,\n    \"Ġinterpreter\": 28573,\n    \"alcohol\": 28574,\n    \"Ġimposition\": 28575,\n    \"Ġdwelling\": 28576,\n    \"Ġ1400\": 28577,\n    \"].\\\"\": 28578,\n    \"ĠIw\": 28579,\n    \"RM\": 28580,\n    \"Ġ555\": 28581,\n    \"Ġparalyzed\": 28582,\n    \"mind\": 28583,\n    \"rans\": 28584,\n    \"adin\": 28585,\n    \"French\": 28586,\n    \"Ġliar\": 28587,\n    \"Represent\": 28588,\n    \"Ġstrapped\": 28589,\n    \"orate\": 28590,\n    \"Ġrigging\": 28591,\n    \"Ġinterrog\": 28592,\n    \"Ġsparse\": 28593,\n    \"ento\": 28594,\n    \"ĠThem\": 28595,\n    \"Ġbaseless\": 28596,\n    \"Ġbuildup\": 28597,\n    \"Ġundecided\": 28598,\n    \"isms\": 28599,\n    \"Ġabduct\": 28600,\n    \"Ġflowed\": 28601,\n    \"Ġprestige\": 28602,\n    \"Ġhacks\": 28603,\n    \"Ġpanicked\": 28604,\n    \"Cast\": 28605,\n    \"ĠKrish\": 28606,\n    \"umat\": 28607,\n    \"Ġantique\": 28608,\n    \"Ġbitters\": 28609,\n    \"Ġentitlement\": 28610,\n    \"Ġstandby\": 28611,\n    \"Ten\": 28612,\n    \"said\": 28613,\n    \"ĠConditions\": 28614,\n    \"events\": 28615,\n    \"Ġobey\": 28616,\n    \"Ġshortest\": 28617,\n    \"etting\": 28618,\n    \"Ġconcentrating\": 28619,\n    \"ĠNeeds\": 28620,\n    \"234\": 28621,\n    \"Ġintrigued\": 28622,\n    \"enting\": 28623,\n    \"ĠXen\": 28624,\n    \"ĠAlger\": 28625,\n    \"seekers\": 28626,\n    \"anish\": 28627,\n    \"Ġ172\": 28628,\n    \"âĢĳ\": 28629,\n    \"Ġsilicon\": 28630,\n    \"Ġstandardized\": 28631,\n    \"ĠFountain\": 28632,\n    \"essel\": 28633,\n    \"Ġapproves\": 28634,\n    \"Ġsucked\": 28635,\n    \"gone\": 28636,\n    \"ĠBriggs\": 28637,\n    \"brother\": 28638,\n    \"Ġartisan\": 28639,\n    \"ĠContinuing\": 28640,\n    \"vir\": 28641,\n    \"Ġsubmarines\": 28642,\n    \"ĠInk\": 28643,\n    \"program\": 28644,\n    \"ĠNexus\": 28645,\n    \"ĠCoco\": 28646,\n    \"Ġconceptual\": 28647,\n    \"Ġmatt\": 28648,\n    \"aughters\": 28649,\n    \"Ġbaths\": 28650,\n    \"Ġbeaut\": 28651,\n    \"ĠEmerald\": 28652,\n    \"ĠParties\": 28653,\n    \"248\": 28654,\n    \"completely\": 28655,\n    \"esan\": 28656,\n    \"Ġdiarrhea\": 28657,\n    \"Ġ1100\": 28658,\n    \"borg\": 28659,\n    \"ĠBroken\": 28660,\n    \"Ġreiterate\": 28661,\n    \"Ġsorting\": 28662,\n    \"ONS\": 28663,\n    \"Ġ177\": 28664,\n    \"Ġadmin\": 28665,\n    \"ĠMandatory\": 28666,\n    \"Ġsymptom\": 28667,\n    \"Ġpaced\": 28668,\n    \"Remember\": 28669,\n    \"Ġabdominal\": 28670,\n    \"Ġswapped\": 28671,\n    \"Ġtransitions\": 28672,\n    \"IFA\": 28673,\n    \"pretty\": 28674,\n    \"ĠJC\": 28675,\n    \"Ġallotted\": 28676,\n    \"ĠShows\": 28677,\n    \"Arthur\": 28678,\n    \"Ġsoften\": 28679,\n    \"dozen\": 28680,\n    \"Mah\": 28681,\n    \"Ġextinguished\": 28682,\n    \"Ġreelection\": 28683,\n    \"Ġdeployments\": 28684,\n    \"Ġsturdy\": 28685,\n    \"Ġdownright\": 28686,\n    \"Ġjams\": 28687,\n    \"ĠOptim\": 28688,\n    \"Ġhumiliation\": 28689,\n    \"cd\": 28690,\n    \"Ġbunk\": 28691,\n    \"sie\": 28692,\n    \"NAT\": 28693,\n    \"ilies\": 28694,\n    \"Ġimplying\": 28695,\n    \"Ġ<\": 28696,\n    \"Ġhomepage\": 28697,\n    \"242\": 28698,\n    \"Ġey\": 28699,\n    \"Ġdict\": 28700,\n    \"Ġslender\": 28701,\n    \"Ġforehead\": 28702,\n    \"ĠCecil\": 28703,\n    \"Ġshrunk\": 28704,\n    \"ĠExit\": 28705,\n    \"Ġexpressly\": 28706,\n    \"Ġseals\": 28707,\n    \"ĠThiel\": 28708,\n    \"umni\": 28709,\n    \"Ġdamning\": 28710,\n    \"ĠVS\": 28711,\n    \"ulum\": 28712,\n    \"BBC\": 28713,\n    \"URES\": 28714,\n    \"Ġinhal\": 28715,\n    \"Ġfont\": 28716,\n    \"Ġworkplaces\": 28717,\n    \"ĠPUBLIC\": 28718,\n    \"ĠHorror\": 28719,\n    \"Bs\": 28720,\n    \"arta\": 28721,\n    \"ĠBread\": 28722,\n    \"Ġstret\": 28723,\n    \"Ġethos\": 28724,\n    \"Ġstabilized\": 28725,\n    \"Ġconvers\": 28726,\n    \"ĠInqu\": 28727,\n    \"Ġjudgments\": 28728,\n    \"ĠContemporary\": 28729,\n    \"221\": 28730,\n    \"Ġzombie\": 28731,\n    \"VD\": 28732,\n    \"Ġmisunderstanding\": 28733,\n    \"Ġspam\": 28734,\n    \"ĠPapers\": 28735,\n    \"Ġcrocod\": 28736,\n    \"ENA\": 28737,\n    \"ĠJuven\": 28738,\n    \"ĠAbram\": 28739,\n    \"Ġbursts\": 28740,\n    \"atto\": 28741,\n    \"Ġturbulence\": 28742,\n    \"tty\": 28743,\n    \"sexual\": 28744,\n    \"Ġwaning\": 28745,\n    \"community\": 28746,\n    \"Government\": 28747,\n    \"Ġtranspl\": 28748,\n    \"??\": 28749,\n    \"Getting\": 28750,\n    \"ĠRare\": 28751,\n    \"prime\": 28752,\n    \"Ġlooting\": 28753,\n    \"Ġvalidate\": 28754,\n    \"ĠCreating\": 28755,\n    \"ĠCorruption\": 28756,\n    \"Ġspit\": 28757,\n    \"ĠFavorite\": 28758,\n    \"Kar\": 28759,\n    \"Ġadaptive\": 28760,\n    \"ĠART\": 28761,\n    \"Ġtorso\": 28762,\n    \"ĠIdent\": 28763,\n    \"Ġsubdivision\": 28764,\n    \"azo\": 28765,\n    \"Ġconsequently\": 28766,\n    \"Ġrotate\": 28767,\n    \"ĠWit\": 28768,\n    \"Ġestab\": 28769,\n    \"managed\": 28770,\n    \"ĠBound\": 28771,\n    \"Ġskim\": 28772,\n    \"198\": 28773,\n    \"ĠCorona\": 28774,\n    \"ĠâĿ\": 28775,\n    \"Ġwording\": 28776,\n    \"buck\": 28777,\n    \"iph\": 28778,\n    \"patrick\": 28779,\n    \"Help\": 28780,\n    \"flying\": 28781,\n    \"Ġracer\": 28782,\n    \"Ġfisherman\": 28783,\n    \"____\": 28784,\n    \"ackers\": 28785,\n    \"Ġpersisted\": 28786,\n    \"Ġmyths\": 28787,\n    \"Ġgarn\": 28788,\n    \"ologue\": 28789,\n    \"ĠApprentice\": 28790,\n    \"Ġhereby\": 28791,\n    \"Ġvulgar\": 28792,\n    \"ĠGinger\": 28793,\n    \"Ġtrait\": 28794,\n    \"ĠIdea\": 28795,\n    \"Ġfigur\": 28796,\n    \"ĠSchwarzenegger\": 28797,\n    \"ĠSafari\": 28798,\n    \"178\": 28799,\n    \"ĠAsians\": 28800,\n    \"775\": 28801,\n    \"ĠTriangle\": 28802,\n    \"Ġdemons\": 28803,\n    \"ĠOv\": 28804,\n    \"Ġanime\": 28805,\n    \"Broad\": 28806,\n    \"Ġmolecule\": 28807,\n    \"Ġdeposition\": 28808,\n    \"Ġbiodiversity\": 28809,\n    \"modern\": 28810,\n    \"Ġwallets\": 28811,\n    \"NH\": 28812,\n    \"planes\": 28813,\n    \"rats\": 28814,\n    \"ĠSeed\": 28815,\n    \"Ġ174\": 28816,\n    \"umed\": 28817,\n    \"Ġtouting\": 28818,\n    \"gre\": 28819,\n    \"ĠSEAL\": 28820,\n    \"Ġperpetrator\": 28821,\n    \"ĠGerrard\": 28822,\n    \"Ġallocations\": 28823,\n    \"Ġworsh\": 28824,\n    \"payment\": 28825,\n    \"bett\": 28826,\n    \"ĠIssues\": 28827,\n    \"ennis\": 28828,\n    \"eering\": 28829,\n    \"ĠMV\": 28830,\n    \"yi\": 28831,\n    \"hak\": 28832,\n    \"Ġ167\": 28833,\n    \"Ġorchestr\": 28834,\n    \"224\": 28835,\n    \"Ġsup\": 28836,\n    \"Ġleukemia\": 28837,\n    \"osures\": 28838,\n    \"575\": 28839,\n    \"Ġnoticeably\": 28840,\n    \"Ġparamilitary\": 28841,\n    \"ĠTHERE\": 28842,\n    \"Ġwaged\": 28843,\n    \"igrated\": 28844,\n    \"Ġdocumentaries\": 28845,\n    \"Ġsenseless\": 28846,\n    \"Ġbark\": 28847,\n    \"Ġgenetics\": 28848,\n    \"ĠAlbania\": 28849,\n    \"ĠCrypt\": 28850,\n    \"ĠSEO\": 28851,\n    \"Ġnightly\": 28852,\n    \"Ġfaults\": 28853,\n    \"279\": 28854,\n    \"ĠFerdinand\": 28855,\n    \"ĠSylv\": 28856,\n    \"Ġcalam\": 28857,\n    \"ĠMuller\": 28858,\n    \"ĠSpielberg\": 28859,\n    \"Boy\": 28860,\n    \"ĠUrs\": 28861,\n    \"Ġrug\": 28862,\n    \"Ġcolonies\": 28863,\n    \"ĠFunk\": 28864,\n    \"Ġlyric\": 28865,\n    \"ĠATT\": 28866,\n    \"anni\": 28867,\n    \"ĠNB\": 28868,\n    \"Ġthorn\": 28869,\n    \"Ġpertinent\": 28870,\n    \"188\": 28871,\n    \"Ġpartic\": 28872,\n    \"Head\": 28873,\n    \"Pad\": 28874,\n    \"Palestinian\": 28875,\n    \"ĠBarg\": 28876,\n    \"anical\": 28877,\n    \"beaut\": 28878,\n    \"onge\": 28879,\n    \"Ġgigantic\": 28880,\n    \"travel\": 28881,\n    \"Ġdownloading\": 28882,\n    \"Contin\": 28883,\n    \"whe\": 28884,\n    \"plane\": 28885,\n    \"Wil\": 28886,\n    \"IDA\": 28887,\n    \"Ele\": 28888,\n    \"ĠPAL\": 28889,\n    \"Ġbeams\": 28890,\n    \"ĠProud\": 28891,\n    \"ramer\": 28892,\n    \"Ġindependents\": 28893,\n    \"Ġtranslator\": 28894,\n    \"ĠBrah\": 28895,\n    \"ĠTrooper\": 28896,\n    \"aylor\": 28897,\n    \"pson\": 28898,\n    \"Ġguise\": 28899,\n    \"Ġdiffering\": 28900,\n    \"Ġtopple\": 28901,\n    \"ichen\": 28902,\n    \"ĠSeymour\": 28903,\n    \"deg\": 28904,\n    \"ĠMixed\": 28905,\n    \"Ġinvoluntary\": 28906,\n    \"Ġcountdown\": 28907,\n    \"ĠNarc\": 28908,\n    \"ĠAdults\": 28909,\n    \"Ġcoaster\": 28910,\n    \"Ġ342\": 28911,\n    \"ĠAcquisition\": 28912,\n    \"mone\": 28913,\n    \"Ġpenchant\": 28914,\n    \"Brian\": 28915,\n    \"Gh\": 28916,\n    \"Pres\": 28917,\n    \"enei\": 28918,\n    \"Ġreefs\": 28919,\n    \"ĠMaver\": 28920,\n    \"Ġdevised\": 28921,\n    \"ĠIMP\": 28922,\n    \"vict\": 28923,\n    \"Ġagility\": 28924,\n    \"ĠPayments\": 28925,\n    \"respected\": 28926,\n    \"Ġtuning\": 28927,\n    \"ĠFACE\": 28928,\n    \"actions\": 28929,\n    \"Ġyell\": 28930,\n    \"ĠLeaving\": 28931,\n    \"Ġsnowy\": 28932,\n    \"Saudi\": 28933,\n    \"Ġformations\": 28934,\n    \"Ġairborne\": 28935,\n    \"Ġdeed\": 28936,\n    \"ooks\": 28937,\n    \"Ġnamesake\": 28938,\n    \"Ġpunishable\": 28939,\n    \"Ġagg\": 28940,\n    \"oths\": 28941,\n    \"ĠFamous\": 28942,\n    \"ĠDeposit\": 28943,\n    \"Ġinduce\": 28944,\n    \"189\": 28945,\n    \"Ġhesitation\": 28946,\n    \"ĠBrowse\": 28947,\n    \"ople\": 28948,\n    \"reys\": 28949,\n    \"henko\": 28950,\n    \"Ġsecretaries\": 28951,\n    \"Ġintersections\": 28952,\n    \"Ġdiminishing\": 28953,\n    \"ints\": 28954,\n    \"Ġ1934\": 28955,\n    \"ĠInvestigative\": 28956,\n    \"ĠMexicans\": 28957,\n    \"ĠMahar\": 28958,\n    \"ibur\": 28959,\n    \"Ġstocking\": 28960,\n    \"gross\": 28961,\n    \"Ġasbestos\": 28962,\n    \"Ġagitation\": 28963,\n    \"ĠBST\": 28964,\n    \"Overall\": 28965,\n    \"Ġheats\": 28966,\n    \"ĠSpan\": 28967,\n    \"Ġimped\": 28968,\n    \"Ġtrusting\": 28969,\n    \"Pet\": 28970,\n    \"Ġegregious\": 28971,\n    \"Ġcomedians\": 28972,\n    \"zin\": 28973,\n    \"WIN\": 28974,\n    \"Ġchats\": 28975,\n    \"Ġexploding\": 28976,\n    \"ĠTort\": 28977,\n    \"Ġembraces\": 28978,\n    \"Ġneut\": 28979,\n    \"verson\": 28980,\n    \"ouncing\": 28981,\n    \"ĠFiber\": 28982,\n    \"Ġbaker\": 28983,\n    \"Ġunstoppable\": 28984,\n    \"ĠDial\": 28985,\n    \"cars\": 28986,\n    \"Marc\": 28987,\n    \"164\": 28988,\n    \"volt\": 28989,\n    \"Ġceased\": 28990,\n    \"EFF\": 28991,\n    \"Ġpromoters\": 28992,\n    \"Ġcircuits\": 28993,\n    \"Ġexcise\": 28994,\n    \"Ġseminars\": 28995,\n    \"ĠTiny\": 28996,\n    \"ĠImportant\": 28997,\n    \"ĠTup\": 28998,\n    \"Ġoutburst\": 28999,\n    \"ĠSOC\": 29000,\n    \"ĠWWII\": 29001,\n    \"Ġmerging\": 29002,\n    \"highly\": 29003,\n    \"ĠGmail\": 29004,\n    \"ozy\": 29005,\n    \"ĠKB\": 29006,\n    \"Ġlaboratories\": 29007,\n    \"knit\": 29008,\n    \"ĠClosed\": 29009,\n    \"Ġsurrounds\": 29010,\n    \"ĠVet\": 29011,\n    \"Ġcere\": 29012,\n    \"vard\": 29013,\n    \"ĠDeadpool\": 29014,\n    \"text\": 29015,\n    \"Ġinfusion\": 29016,\n    \"Ġcuc\": 29017,\n    \"ĠAtl\": 29018,\n    \"Ġbustling\": 29019,\n    \"ĠSettings\": 29020,\n    \"Ġ193\": 29021,\n    \"ryan\": 29022,\n    \"184\": 29023,\n    \"186\": 29024,\n    \"Ġswat\": 29025,\n    \"rane\": 29026,\n    \"Ġepidem\": 29027,\n    \"lando\": 29028,\n    \"Ġtestifying\": 29029,\n    \"Ġmoistur\": 29030,\n    \"ĠTens\": 29031,\n    \"Ġexemplary\": 29032,\n    \"ĠPump\": 29033,\n    \"Ġforcefully\": 29034,\n    \"ĠFare\": 29035,\n    \"Ġcomplicate\": 29036,\n    \"Fe\": 29037,\n    \"Di\": 29038,\n    \"ĠThy\": 29039,\n    \"Ġcompartment\": 29040,\n    \"ĠFiesta\": 29041,\n    \"Would\": 29042,\n    \"fitted\": 29043,\n    \"Ġcull\": 29044,\n    \"Ġcomedic\": 29045,\n    \"cyl\": 29046,\n    \"Ġwhichever\": 29047,\n    \"stic\": 29048,\n    \"Ġ213\": 29049,\n    \"Ġspills\": 29050,\n    \"Ġplasma\": 29051,\n    \"Ġdisguise\": 29052,\n    \"ĠCompass\": 29053,\n    \"ĠImmun\": 29054,\n    \"Ġscarf\": 29055,\n    \"Ġdisperse\": 29056,\n    \"Ġreckon\": 29057,\n    \"ĠTaste\": 29058,\n    \"root\": 29059,\n    \"ĠGAME\": 29060,\n    \"xx\": 29061,\n    \"Ġhomophobic\": 29062,\n    \"Ġdimin\": 29063,\n    \"/#\": 29064,\n    \"Ġ178\": 29065,\n    \"Ġgems\": 29066,\n    \"lio\": 29067,\n    \"informed\": 29068,\n    \"ample\": 29069,\n    \"XT\": 29070,\n    \"Ġrepression\": 29071,\n    \"ĠTakes\": 29072,\n    \"Ġhabitats\": 29073,\n    \"Ġmountainous\": 29074,\n    \"ĠMcH\": 29075,\n    \"ENC\": 29076,\n    \"Mobil\": 29077,\n    \"Ġreel\": 29078,\n    \"ĠTI\": 29079,\n    \"Ġauthorize\": 29080,\n    \"ĠAccept\": 29081,\n    \"ĠMetall\": 29082,\n    \"CCC\": 29083,\n    \"Ġwetlands\": 29084,\n    \"ĠWitch\": 29085,\n    \"heading\": 29086,\n    \"Ġintervals\": 29087,\n    \"ĠWitt\": 29088,\n    \"hene\": 29089,\n    \"Ġcomforting\": 29090,\n    \"ollen\": 29091,\n    \"ERN\": 29092,\n    \"ooky\": 29093,\n    \"etch\": 29094,\n    \"Ġassailant\": 29095,\n    \"announced\": 29096,\n    \"elin\": 29097,\n    \"plate\": 29098,\n    \"920\": 29099,\n    \"eating\": 29100,\n    \"induced\": 29101,\n    \"ĠIgor\": 29102,\n    \"ĠAmph\": 29103,\n    \"Ġpatented\": 29104,\n    \"posing\": 29105,\n    \"Ġextraordinarily\": 29106,\n    \"Ġfearless\": 29107,\n    \"mortem\": 29108,\n    \"ĠDraw\": 29109,\n    \"ĠRend\": 29110,\n    \"Son\": 29111,\n    \"ridden\": 29112,\n    \"ĠAdvantage\": 29113,\n    \"Ġ305\": 29114,\n    \"Ġroared\": 29115,\n    \"Str\": 29116,\n    \"Ġradioactive\": 29117,\n    \"Ġslur\": 29118,\n    \"ĠRear\": 29119,\n    \"affles\": 29120,\n    \"ĠPon\": 29121,\n    \"Ġost\": 29122,\n    \"umbs\": 29123,\n    \"ĠSlack\": 29124,\n    \"athom\": 29125,\n    \"baby\": 29126,\n    \"213\": 29127,\n    \"ĠSpending\": 29128,\n    \"ĠAccordingly\": 29129,\n    \"Ġclocks\": 29130,\n    \"archs\": 29131,\n    \"Ġsmugg\": 29132,\n    \"Ġmastermind\": 29133,\n    \"ĠKlaus\": 29134,\n    \"alpha\": 29135,\n    \"Ġspoiled\": 29136,\n    \"264\": 29137,\n    \"Pod\": 29138,\n    \"Ġflared\": 29139,\n    \"Ġcomposure\": 29140,\n    \"ĠCAM\": 29141,\n    \"Ġrestruct\": 29142,\n    \"Ġtasted\": 29143,\n    \"ĠKimber\": 29144,\n    \"Ġupheaval\": 29145,\n    \"CHAR\": 29146,\n    \"ĠGeo\": 29147,\n    \"itations\": 29148,\n    \"Ġbegged\": 29149,\n    \"UX\": 29150,\n    \"Authorities\": 29151,\n    \"ĠEngel\": 29152,\n    \"ĠHOME\": 29153,\n    \"Ġratt\": 29154,\n    \"Ġquickest\": 29155,\n    \"475\": 29156,\n    \"ĠSting\": 29157,\n    \"ĠICO\": 29158,\n    \"yu\": 29159,\n    \"Ġdefy\": 29160,\n    \"Prince\": 29161,\n    \"cards\": 29162,\n    \"Ġovertake\": 29163,\n    \"Ġretrieved\": 29164,\n    \"ĠNavajo\": 29165,\n    \"Ġpastry\": 29166,\n    \"ĠLange\": 29167,\n    \"Ġentrusted\": 29168,\n    \"ĠCull\": 29169,\n    \"aler\": 29170,\n    \"Ġdinosaurs\": 29171,\n    \"Ġbragging\": 29172,\n    \"ĠAlley\": 29173,\n    \"meier\": 29174,\n    \"ĠAssuming\": 29175,\n    \"Ġana\": 29176,\n    \"omatic\": 29177,\n    \"Brend\": 29178,\n    \"acted\": 29179,\n    \"Ġexhaustive\": 29180,\n    \"Ġunfit\": 29181,\n    \"Several\": 29182,\n    \"gap\": 29183,\n    \"Ġtet\": 29184,\n    \"228\": 29185,\n    \"Sk\": 29186,\n    \"302\": 29187,\n    \"Ġdeflect\": 29188,\n    \"Ġ179\": 29189,\n    \"226\": 29190,\n    \"Ġadorned\": 29191,\n    \"ĠSpread\": 29192,\n    \"Ġthirds\": 29193,\n    \"ĠSemi\": 29194,\n    \"Ġdescend\": 29195,\n    \"Ġaccumulate\": 29196,\n    \"Ġflavours\": 29197,\n    \"Ġinvoked\": 29198,\n    \"ĠAnge\": 29199,\n    \"Ġprofess\": 29200,\n    \"unks\": 29201,\n    \"ĠKickstarter\": 29202,\n    \"ENTS\": 29203,\n    \"ĠRw\": 29204,\n    \"Ġchatter\": 29205,\n    \"ĠPOS\": 29206,\n    \"Ġcollaborators\": 29207,\n    \"ĠEW\": 29208,\n    \"ĠMarkus\": 29209,\n    \"Ġimpair\": 29210,\n    \"Ġbolt\": 29211,\n    \"Ġglue\": 29212,\n    \"Ġloosely\": 29213,\n    \"ĠSUM\": 29214,\n    \"Ġhydraulic\": 29215,\n    \"Ġpredatory\": 29216,\n    \"Charles\": 29217,\n    \"cond\": 29218,\n    \"Ġspawned\": 29219,\n    \"Fr\": 29220,\n    \"174\": 29221,\n    \"Ġtame\": 29222,\n    \"Ġaggrav\": 29223,\n    \"Ġchrist\": 29224,\n    \"true\": 29225,\n    \"ivable\": 29226,\n    \"Ġhen\": 29227,\n    \"ĠKut\": 29228,\n    \"Ġskyrocket\": 29229,\n    \"Ġeg\": 29230,\n    \"Ġveterinarian\": 29231,\n    \"ĠStats\": 29232,\n    \"Kit\": 29233,\n    \"Ġbiologist\": 29234,\n    \"Spe\": 29235,\n    \"Ġantenna\": 29236,\n    \"Ġsust\": 29237,\n    \"fill\": 29238,\n    \"Ġpayload\": 29239,\n    \"227\": 29240,\n    \"Ġlivestream\": 29241,\n    \"ORN\": 29242,\n    \"ĠAbel\": 29243,\n    \"Ġdeception\": 29244,\n    \"ussen\": 29245,\n    \"Britain\": 29246,\n    \"partisan\": 29247,\n    \"Ġbrowse\": 29248,\n    \"Ġmelan\": 29249,\n    \"172\": 29250,\n    \"ĠNumerous\": 29251,\n    \"ĠMansion\": 29252,\n    \"Ġassailants\": 29253,\n    \"Â£\": 29254,\n    \"olerance\": 29255,\n    \"Ġdirectives\": 29256,\n    \"ĠInteg\": 29257,\n    \"zers\": 29258,\n    \"Ġduct\": 29259,\n    \"ĠHonestly\": 29260,\n    \"ĠImmediately\": 29261,\n    \"ixty\": 29262,\n    \"Ġdiagnose\": 29263,\n    \"Ġimplication\": 29264,\n    \"ĠiPads\": 29265,\n    \"testers\": 29266,\n    \"riots\": 29267,\n    \"Ġrespons\": 29268,\n    \"XP\": 29269,\n    \"pes\": 29270,\n    \"875\": 29271,\n    \"Ġ199\": 29272,\n    \"ĠPoe\": 29273,\n    \"303\": 29274,\n    \"Ġailments\": 29275,\n    \"ĠCarrier\": 29276,\n    \"Ġeject\": 29277,\n    \"Ġrestroom\": 29278,\n    \"Drive\": 29279,\n    \"manufact\": 29280,\n    \"Ġcompens\": 29281,\n    \"Ġglossy\": 29282,\n    \"Ġrecovers\": 29283,\n    \"Ġthinner\": 29284,\n    \"Ġdescendants\": 29285,\n    \"antle\": 29286,\n    \"Beaut\": 29287,\n    \"competitive\": 29288,\n    \"ĠRobotics\": 29289,\n    \"Ġpretext\": 29290,\n    \"233\": 29291,\n    \"Ġflanked\": 29292,\n    \"ĠâĻ\": 29293,\n    \"Ġguts\": 29294,\n    \"Ġwee\": 29295,\n    \"Ġaccents\": 29296,\n    \"mc\": 29297,\n    \"Ġgrapp\": 29298,\n    \"ĠNathaniel\": 29299,\n    \"ĠMikhail\": 29300,\n    \"Ġobligated\": 29301,\n    \"Ġmanoeuv\": 29302,\n    \"Ġechoing\": 29303,\n    \"Ġ189\": 29304,\n    \"ĠDevice\": 29305,\n    \"isd\": 29306,\n    \"Ġloopholes\": 29307,\n    \"Ġbehold\": 29308,\n    \"ĠMerry\": 29309,\n    \"Ġfunn\": 29310,\n    \"Ġnuanced\": 29311,\n    \"667\": 29312,\n    \"ELY\": 29313,\n    \"ĠTasmania\": 29314,\n    \"ĠSaddam\": 29315,\n    \"Ġquizz\": 29316,\n    \"military\": 29317,\n    \"cient\": 29318,\n    \"Ġoutlaw\": 29319,\n    \"ĠAudit\": 29320,\n    \"ĠBoom\": 29321,\n    \"Ġcrim\": 29322,\n    \"asured\": 29323,\n    \"ĠApps\": 29324,\n    \"ĠKush\": 29325,\n    \"onica\": 29326,\n    \"Ġamput\": 29327,\n    \"signed\": 29328,\n    \"ĠMEN\": 29329,\n    \"ĠRosenberg\": 29330,\n    \"Ġvide\": 29331,\n    \"ĠDirection\": 29332,\n    \"Ġfountain\": 29333,\n    \"TW\": 29334,\n    \"ĠCARE\": 29335,\n    \"Ġreassured\": 29336,\n    \"Food\": 29337,\n    \"Ġdepressing\": 29338,\n    \"ĠWhilst\": 29339,\n    \"reatment\": 29340,\n    \"Ġspelled\": 29341,\n    \"Ġhipp\": 29342,\n    \"ĠPeach\": 29343,\n    \"hound\": 29344,\n    \"Harry\": 29345,\n    \"Ġcatalogue\": 29346,\n    \"ĠCommun\": 29347,\n    \"Ġnurture\": 29348,\n    \"rush\": 29349,\n    \"ĠPopulation\": 29350,\n    \"ĠNTS\": 29351,\n    \"ĠElectrical\": 29352,\n    \"rounded\": 29353,\n    \"Ġblending\": 29354,\n    \"Ġ223\": 29355,\n    \"alities\": 29356,\n    \"ilation\": 29357,\n    \"eas\": 29358,\n    \"estate\": 29359,\n    \"Ġnarrowing\": 29360,\n    \"ĠTreasure\": 29361,\n    \"192\": 29362,\n    \"Ġwhims\": 29363,\n    \"Ġrobber\": 29364,\n    \"Ġsoaked\": 29365,\n    \"nian\": 29366,\n    \"Ġcongest\": 29367,\n    \"ĠYosemite\": 29368,\n    \"notes\": 29369,\n    \"icer\": 29370,\n    \"ĠGuardians\": 29371,\n    \"ĠFrozen\": 29372,\n    \"Ġ187\": 29373,\n    \"Ġhandcuffs\": 29374,\n    \"Someone\": 29375,\n    \"Ġenshr\": 29376,\n    \"gency\": 29377,\n    \"ĠCube\": 29378,\n    \"Ġprinters\": 29379,\n    \"Ġundercut\": 29380,\n    \"ĠSolution\": 29381,\n    \"rosis\": 29382,\n    \"ĠHumanity\": 29383,\n    \"Ġsucks\": 29384,\n    \"ĠSick\": 29385,\n    \"Tax\": 29386,\n    \"Ġtablespoon\": 29387,\n    \"ĠTrin\": 29388,\n    \"ĠArchive\": 29389,\n    \"Mom\": 29390,\n    \"ĠSAY\": 29391,\n    \"Ġdrifting\": 29392,\n    \"ĠFarage\": 29393,\n    \"Ġforging\": 29394,\n    \"WM\": 29395,\n    \"ĠEleanor\": 29396,\n    \"USH\": 29397,\n    \"Ġemph\": 29398,\n    \"Ġcareless\": 29399,\n    \"Ġspew\": 29400,\n    \"Ġinsensitive\": 29401,\n    \"Ġawhile\": 29402,\n    \"Ġcit\": 29403,\n    \"opened\": 29404,\n    \"ĠFem\": 29405,\n    \"Ġvapor\": 29406,\n    \"Ġdownt\": 29407,\n    \"ylene\": 29408,\n    \"Ġclut\": 29409,\n    \"Ġculp\": 29410,\n    \"1990\": 29411,\n    \"Ġdisgruntled\": 29412,\n    \"Students\": 29413,\n    \"uttering\": 29414,\n    \"gyn\": 29415,\n    \"vre\": 29416,\n    \"Ġrapes\": 29417,\n    \"division\": 29418,\n    \"ĠCalendar\": 29419,\n    \"tal\": 29420,\n    \"icts\": 29421,\n    \"caliber\": 29422,\n    \"ĠFighters\": 29423,\n    \"ĠUnc\": 29424,\n    \"163\": 29425,\n    \"ĠRogue\": 29426,\n    \"Ġregistrations\": 29427,\n    \"Ġundermines\": 29428,\n    \"ĠPunch\": 29429,\n    \"Ġdramas\": 29430,\n    \"176\": 29431,\n    \"Ġslider\": 29432,\n    \"ĠFlore\": 29433,\n    \"Ø±\": 29434,\n    \"Ġbru\": 29435,\n    \"inelli\": 29436,\n    \"Ġdisparities\": 29437,\n    \"Ø§\": 29438,\n    \"Ġreferrals\": 29439,\n    \"ĠCharges\": 29440,\n    \"Ġbreeds\": 29441,\n    \"ĠMEP\": 29442,\n    \"288\": 29443,\n    \"Ġmouths\": 29444,\n    \"Ġsideways\": 29445,\n    \"Ġbelievers\": 29446,\n    \"ppard\": 29447,\n    \"Ġhotter\": 29448,\n    \"Ġunderestimated\": 29449,\n    \"Ġjelly\": 29450,\n    \"525\": 29451,\n    \"ĠCMS\": 29452,\n    \"ĠWeiner\": 29453,\n    \"Ġguarding\": 29454,\n    \"Ġampl\": 29455,\n    \"ĠKidd\": 29456,\n    \"UF\": 29457,\n    \"orient\": 29458,\n    \"max\": 29459,\n    \"Ash\": 29460,\n    \"Ġwander\": 29461,\n    \"Ġ..........\": 29462,\n    \"ĠDempsey\": 29463,\n    \"ĠToken\": 29464,\n    \"chat\": 29465,\n    \"Justin\": 29466,\n    \"equipped\": 29467,\n    \"ĠBI\": 29468,\n    \"Ġsins\": 29469,\n    \"Ġnond\": 29470,\n    \"ursion\": 29471,\n    \"Ġcoc\": 29472,\n    \"Ġmailing\": 29473,\n    \"ĠArchitect\": 29474,\n    \"Ġhaunting\": 29475,\n    \"Ġpont\": 29476,\n    \"Ġascertain\": 29477,\n    \"Ġwig\": 29478,\n    \"Ġskysc\": 29479,\n    \"Ġarg\": 29480,\n    \"ĠItalians\": 29481,\n    \"/?\": 29482,\n    \"Ġ----------------------------------------------------------------\": 29483,\n    \"ĠPrecision\": 29484,\n    \"EPA\": 29485,\n    \"Ġhotly\": 29486,\n    \"Ġcircumvent\": 29487,\n    \"ĠEcc\": 29488,\n    \"Ġmerch\": 29489,\n    \"akov\": 29490,\n    \"Ġunab\": 29491,\n    \"heres\": 29492,\n    \"Ġsubcommittee\": 29493,\n    \"ĠDiscuss\": 29494,\n    \"ĠChallenger\": 29495,\n    \"crafted\": 29496,\n    \"Ġcanine\": 29497,\n    \"osphere\": 29498,\n    \"Ġspider\": 29499,\n    \"Ġteachings\": 29500,\n    \"atos\": 29501,\n    \"Ġuniversally\": 29502,\n    \"Ġturbine\": 29503,\n    \"ĠLO\": 29504,\n    \"ĠMAG\": 29505,\n    \"Ġpassers\": 29506,\n    \"Ġroundup\": 29507,\n    \"Ġdenounce\": 29508,\n    \"ĠSpiegel\": 29509,\n    \"until\": 29510,\n    \"Ġshaved\": 29511,\n    \"Ġdisdain\": 29512,\n    \"Nazi\": 29513,\n    \"Ġnewfound\": 29514,\n    \"Ġspontaneous\": 29515,\n    \"Ġmash\": 29516,\n    \"ĠDispatch\": 29517,\n    \"Ġsunrise\": 29518,\n    \"ogged\": 29519,\n    \"Ġfuss\": 29520,\n    \"Ġeas\": 29521,\n    \"acci\": 29522,\n    \"ĠTarg\": 29523,\n    \"Ġhash\": 29524,\n    \"lict\": 29525,\n    \"Ġmisc\": 29526,\n    \"ĠSched\": 29527,\n    \"guy\": 29528,\n    \"linger\": 29529,\n    \"warm\": 29530,\n    \"ipel\": 29531,\n    \"ĠGork\": 29532,\n    \"Ġdispatcher\": 29533,\n    \"Ġ315\": 29534,\n    \"Ġfinely\": 29535,\n    \"Ġreliably\": 29536,\n    \"Ġrupt\": 29537,\n    \"Ġnegligent\": 29538,\n    \"Ġendorsements\": 29539,\n    \"ĠOrient\": 29540,\n    \"Ġelectro\": 29541,\n    \"haired\": 29542,\n    \"Ġphysique\": 29543,\n    \"wine\": 29544,\n    \"Ġadolescents\": 29545,\n    \"Ġ184\": 29546,\n    \"alth\": 29547,\n    \"Ġvalidated\": 29548,\n    \"izzard\": 29549,\n    \"ĠPeck\": 29550,\n    \"Ġemblem\": 29551,\n    \"status\": 29552,\n    \"ĠJungle\": 29553,\n    \"orius\": 29554,\n    \"Ġeccentric\": 29555,\n    \"Ġfolding\": 29556,\n    \"poor\": 29557,\n    \"ĠTHC\": 29558,\n    \"appers\": 29559,\n    \"Ġscripted\": 29560,\n    \"239\": 29561,\n    \"ĠPreferred\": 29562,\n    \"digital\": 29563,\n    \"Ġsharper\": 29564,\n    \"Ġportrays\": 29565,\n    \"rative\": 29566,\n    \"238\": 29567,\n    \"Ġ183\": 29568,\n    \"Ġuneasy\": 29569,\n    \"ĠRI\": 29570,\n    \"Ġvil\": 29571,\n    \"171\": 29572,\n    \"Ġspoil\": 29573,\n    \"ĠPricing\": 29574,\n    \"ĠHardware\": 29575,\n    \"Ġ188\": 29576,\n    \"Ġhorrendous\": 29577,\n    \"Ġostensibly\": 29578,\n    \"nah\": 29579,\n    \"Ġgadget\": 29580,\n    \"ADS\": 29581,\n    \"coat\": 29582,\n    \"Ġexhausting\": 29583,\n    \"Ġdraining\": 29584,\n    \"arate\": 29585,\n    \"ĠBulgarian\": 29586,\n    \"emo\": 29587,\n    \"Ġhier\": 29588,\n    \"Ġguitars\": 29589,\n    \"ieties\": 29590,\n    \"assed\": 29591,\n    \"ĠYaz\": 29592,\n    \"Ġaggress\": 29593,\n    \"ĠBG\": 29594,\n    \"vik\": 29595,\n    \"Ġneatly\": 29596,\n    \"Ġpixel\": 29597,\n    \"Ġintimacy\": 29598,\n    \"ĠRug\": 29599,\n    \"Ġ512\": 29600,\n    \"Ġnarrated\": 29601,\n    \"Ġmast\": 29602,\n    \"ĠNos\": 29603,\n    \"ĠHung\": 29604,\n    \"reciation\": 29605,\n    \"ĠChandra\": 29606,\n    \"Ġbios\": 29607,\n    \"ĠEnded\": 29608,\n    \"lique\": 29609,\n    \"ĠCambod\": 29610,\n    \"Ġworrisome\": 29611,\n    \"ĠEQ\": 29612,\n    \"Ġnovelist\": 29613,\n    \"ĠDynamic\": 29614,\n    \"ĠMIC\": 29615,\n    \"Ġdisposed\": 29616,\n    \"Ġbrackets\": 29617,\n    \"Ġhaircut\": 29618,\n    \"ĠLana\": 29619,\n    \"Ġlull\": 29620,\n    \"Ġbillboard\": 29621,\n    \"ĠReverend\": 29622,\n    \"ĠNAV\": 29623,\n    \"borgh\": 29624,\n    \"Ġadrenaline\": 29625,\n    \"Ġseeming\": 29626,\n    \"ĠPCB\": 29627,\n    \"ĠBridgewater\": 29628,\n    \"Ġsquirrel\": 29629,\n    \"262\": 29630,\n    \"write\": 29631,\n    \"Ġstabilization\": 29632,\n    \"wild\": 29633,\n    \"Ġsecession\": 29634,\n    \"Ġpacket\": 29635,\n    \"AMES\": 29636,\n    \"licted\": 29637,\n    \"Ġmalnutrition\": 29638,\n    \"claimed\": 29639,\n    \"Ġcharred\": 29640,\n    \"Ġtragically\": 29641,\n    \"Published\": 29642,\n    \"Ġrepealed\": 29643,\n    \"ĠSawyer\": 29644,\n    \"ĠMormon\": 29645,\n    \"resolution\": 29646,\n    \"ĠSaud\": 29647,\n    \"Henry\": 29648,\n    \"Ġdiscontin\": 29649,\n    \"Ġsnag\": 29650,\n    \"danger\": 29651,\n    \"Ġmixes\": 29652,\n    \"Ġupbringing\": 29653,\n    \"Ġlimb\": 29654,\n    \"ĠFantastic\": 29655,\n    \"Sim\": 29656,\n    \"ĠAugustine\": 29657,\n    \"ĠGreeks\": 29658,\n    \"cod\": 29659,\n    \"ĠHistorically\": 29660,\n    \"mire\": 29661,\n    \"register\": 29662,\n    \"ĠKund\": 29663,\n    \"Ġdebilitating\": 29664,\n    \"Chat\": 29665,\n    \"ĠTau\": 29666,\n    \"Ã¯\": 29667,\n    \"lower\": 29668,\n    \"pie\": 29669,\n    \"Ġ430\": 29670,\n    \"Ġnascent\": 29671,\n    \"Ġ375\": 29672,\n    \"Ġbum\": 29673,\n    \"WI\": 29674,\n    \"Netflix\": 29675,\n    \"whether\": 29676,\n    \"Ġdearly\": 29677,\n    \"eff\": 29678,\n    \"PRES\": 29679,\n    \"Ġlandmarks\": 29680,\n    \"Ġculminating\": 29681,\n    \"Ġmigrate\": 29682,\n    \"balanced\": 29683,\n    \"Ġregulars\": 29684,\n    \"Ġmodification\": 29685,\n    \"Ġdips\": 29686,\n    \"ĠRedmond\": 29687,\n    \"ationally\": 29688,\n    \"atsu\": 29689,\n    \"Ġphilosophical\": 29690,\n    \"Ġtyping\": 29691,\n    \"Ġunreal\": 29692,\n    \"Ġboiled\": 29693,\n    \"Ġblight\": 29694,\n    \"Ġdru\": 29695,\n    \"ĠGaddafi\": 29696,\n    \"Ġnour\": 29697,\n    \"Ġsequential\": 29698,\n    \"Ġaugment\": 29699,\n    \"ĠEuras\": 29700,\n    \"ĠWiley\": 29701,\n    \"endar\": 29702,\n    \"Ġacronym\": 29703,\n    \"esteem\": 29704,\n    \"ĠMajesty\": 29705,\n    \"Ġgrips\": 29706,\n    \"Ġobsolete\": 29707,\n    \"nos\": 29708,\n    \"Made\": 29709,\n    \"ogie\": 29710,\n    \"ĠLiver\": 29711,\n    \"ĠDonetsk\": 29712,\n    \"Ġdynam\": 29713,\n    \"tel\": 29714,\n    \"bring\": 29715,\n    \"Ġknit\": 29716,\n    \"Ġfirepower\": 29717,\n    \"Ġprepaid\": 29718,\n    \"ĠRaphael\": 29719,\n    \"Ġsensing\": 29720,\n    \"720\": 29721,\n    \"WN\": 29722,\n    \"Nor\": 29723,\n    \"puted\": 29724,\n    \"Ġbureaucrats\": 29725,\n    \"ĠAdjust\": 29726,\n    \"Ġintensely\": 29727,\n    \"Ġsunscreen\": 29728,\n    \"Ho\": 29729,\n    \"ĠYelp\": 29730,\n    \"ĠPU\": 29731,\n    \"ĠSerge\": 29732,\n    \"ĠCyp\": 29733,\n    \"ELF\": 29734,\n    \"ĠGuns\": 29735,\n    \"Ġteamwork\": 29736,\n    \"ĠBib\": 29737,\n    \"ĠMaintenance\": 29738,\n    \"perate\": 29739,\n    \"Ġwiping\": 29740,\n    \"Ġcharcoal\": 29741,\n    \"ordan\": 29742,\n    \"International\": 29743,\n    \"Ġbehaving\": 29744,\n    \"Ġsoftened\": 29745,\n    \"ĠIncreased\": 29746,\n    \"Ġunfl\": 29747,\n    \"470\": 29748,\n    \"Ġinformative\": 29749,\n    \"Ġnovelty\": 29750,\n    \"Ġavoidance\": 29751,\n    \"Ġteasing\": 29752,\n    \"matic\": 29753,\n    \"Ġmaid\": 29754,\n    \"ĠPell\": 29755,\n    \"Ġcounterterrorism\": 29756,\n    \"ĠGabe\": 29757,\n    \"ications\": 29758,\n    \"ĠConnection\": 29759,\n    \"ĠInquiry\": 29760,\n    \"isin\": 29761,\n    \"orama\": 29762,\n    \"Ġcorpse\": 29763,\n    \"Ġpractitioner\": 29764,\n    \"itto\": 29765,\n    \"UA\": 29766,\n    \"Ġforestry\": 29767,\n    \"Ġlic\": 29768,\n    \"Ġrevolves\": 29769,\n    \"Ġcalculating\": 29770,\n    \"Ġpuppet\": 29771,\n    \"ulously\": 29772,\n    \"ĠPebble\": 29773,\n    \"Dep\": 29774,\n    \"Ġupholding\": 29775,\n    \"Ġcarving\": 29776,\n    \"Ġwartime\": 29777,\n    \"Ġenvy\": 29778,\n    \"Ġencro\": 29779,\n    \"ĠPunk\": 29780,\n    \"ĠAdminist\": 29781,\n    \"ucha\": 29782,\n    \"Ġbattleground\": 29783,\n    \"Ġlol\": 29784,\n    \"uable\": 29785,\n    \"Ġunheard\": 29786,\n    \"ĠSpur\": 29787,\n    \"phony\": 29788,\n    \"Ġcarc\": 29789,\n    \"ĠSut\": 29790,\n    \"Ġpollutants\": 29791,\n    \"Cr\": 29792,\n    \"Ġvigorous\": 29793,\n    \"355\": 29794,\n    \"ĠMarriage\": 29795,\n    \"Ġstaffed\": 29796,\n    \"fecture\": 29797,\n    \"ĠArabs\": 29798,\n    \"supported\": 29799,\n    \"Ġmanpower\": 29800,\n    \"ĠSatellite\": 29801,\n    \"None\": 29802,\n    \"Ġqueues\": 29803,\n    \"Ġinsightful\": 29804,\n    \"Ġinterchange\": 29805,\n    \"Rel\": 29806,\n    \"Ġsolemn\": 29807,\n    \"Ġsmuggled\": 29808,\n    \"upt\": 29809,\n    \"Ġ171\": 29810,\n    \"Ġparallels\": 29811,\n    \"intelligence\": 29812,\n    \"punk\": 29813,\n    \"Ġrecycle\": 29814,\n    \"Ġdecorative\": 29815,\n    \"Ġshar\": 29816,\n    \"arrell\": 29817,\n    \"iances\": 29818,\n    \"ĠBolivia\": 29819,\n    \"Ġstrengthens\": 29820,\n    \"430\": 29821,\n    \"Ġhardships\": 29822,\n    \"Ġsignalling\": 29823,\n    \"Ġunthinkable\": 29824,\n    \"READ\": 29825,\n    \"Ġtad\": 29826,\n    \"picked\": 29827,\n    \"Ġarmor\": 29828,\n    \"Ġcores\": 29829,\n    \"ĠMatrix\": 29830,\n    \"Ġdj\": 29831,\n    \"Ġevolutionary\": 29832,\n    \"ĠBermuda\": 29833,\n    \"OE\": 29834,\n    \"organized\": 29835,\n    \"Ġrelentlessly\": 29836,\n    \"sol\": 29837,\n    \"ĠMamm\": 29838,\n    \"Ġpounding\": 29839,\n    \"Weather\": 29840,\n    \"Ġrab\": 29841,\n    \"Ġsweets\": 29842,\n    \"funding\": 29843,\n    \"ĠHUD\": 29844,\n    \"ĠSoldier\": 29845,\n    \"reed\": 29846,\n    \"released\": 29847,\n    \"Ġcontainment\": 29848,\n    \"alid\": 29849,\n    \"ĠNikon\": 29850,\n    \"Ġcervical\": 29851,\n    \"Ġign\": 29852,\n    \"Ġalias\": 29853,\n    \"Ġoptimized\": 29854,\n    \"Ġasserting\": 29855,\n    \"ĠAFTER\": 29856,\n    \"Ġflatt\": 29857,\n    \"Ġdinosaur\": 29858,\n    \"ĠRefugees\": 29859,\n    \"ĠAnch\": 29860,\n    \"Ġadjustable\": 29861,\n    \"Ġroaring\": 29862,\n    \"Ġpilgrimage\": 29863,\n    \"Ġcowboy\": 29864,\n    \"Ġentails\": 29865,\n    \"ractions\": 29866,\n    \"EY\": 29867,\n    \"undy\": 29868,\n    \"ĠKuh\": 29869,\n    \"inges\": 29870,\n    \"ĠTerra\": 29871,\n    \"ĠEscape\": 29872,\n    \"Ġrundown\": 29873,\n    \"Ġstriped\": 29874,\n    \"KN\": 29875,\n    \"ocations\": 29876,\n    \"IDENT\": 29877,\n    \"IGH\": 29878,\n    \"Ġavoids\": 29879,\n    \"Moh\": 29880,\n    \"ĠLS\": 29881,\n    \"lbs\": 29882,\n    \"ĠAttempt\": 29883,\n    \"Ġtriangle\": 29884,\n    \"Ġclimax\": 29885,\n    \"Ġhp\": 29886,\n    \"Ġallot\": 29887,\n    \"learning\": 29888,\n    \"ĠJFK\": 29889,\n    \"Justice\": 29890,\n    \"OUT\": 29891,\n    \"ĠHER\": 29892,\n    \"ĠLect\": 29893,\n    \"Ġtrench\": 29894,\n    \"edar\": 29895,\n    \"Ġreservoirs\": 29896,\n    \"uid\": 29897,\n    \"rf\": 29898,\n    \"162\": 29899,\n    \"Ġinterfered\": 29900,\n    \"Ġemit\": 29901,\n    \"these\": 29902,\n    \"444\": 29903,\n    \"ĠLeather\": 29904,\n    \"essing\": 29905,\n    \"ĠEighth\": 29906,\n    \"uckle\": 29907,\n    \"Breaking\": 29908,\n    \"Ġunresolved\": 29909,\n    \"Ġgoose\": 29910,\n    \"252\": 29911,\n    \"platform\": 29912,\n    \"atus\": 29913,\n    \"Ġcomplexion\": 29914,\n    \"ĠBUS\": 29915,\n    \"Ġstruct\": 29916,\n    \"middle\": 29917,\n    \"Sat\": 29918,\n    \"ĠWHERE\": 29919,\n    \"LB\": 29920,\n    \"redible\": 29921,\n    \"vered\": 29922,\n    \"Louis\": 29923,\n    \"ĠBaz\": 29924,\n    \"Eye\": 29925,\n    \"safety\": 29926,\n    \"Ġhypothetical\": 29927,\n    \"Ġbowel\": 29928,\n    \"Ġuntouched\": 29929,\n    \"312\": 29930,\n    \"ĠPric\": 29931,\n    \"Ġastounding\": 29932,\n    \"meet\": 29933,\n    \"Aaron\": 29934,\n    \"ĠWoo\": 29935,\n    \"236\": 29936,\n    \"ĠShape\": 29937,\n    \"Ġdrifted\": 29938,\n    \"Ġtile\": 29939,\n    \"ĠGrim\": 29940,\n    \"Ġundeniable\": 29941,\n    \"Ġ..\": 29942,\n    \"Ġradius\": 29943,\n    \"Ġovarian\": 29944,\n    \"ĠSeriously\": 29945,\n    \"verning\": 29946,\n    \"Ġassertions\": 29947,\n    \"oxic\": 29948,\n    \"231\": 29949,\n    \"ĠViz\": 29950,\n    \"Jackson\": 29951,\n    \"ĠSno\": 29952,\n    \"Ġboycot\": 29953,\n    \"okingly\": 29954,\n    \"ousse\": 29955,\n    \"proclaimed\": 29956,\n    \"Ġblazing\": 29957,\n    \"Ġinefficient\": 29958,\n    \"Ġfig\": 29959,\n    \"Ġbooze\": 29960,\n    \"259\": 29961,\n    \"agus\": 29962,\n    \"statement\": 29963,\n    \"Ġlocom\": 29964,\n    \"Ġtacos\": 29965,\n    \"Ġmemos\": 29966,\n    \"gender\": 29967,\n    \"ĠOrt\": 29968,\n    \"263\": 29969,\n    \"Ġintervening\": 29970,\n    \"Soc\": 29971,\n    \"University\": 29972,\n    \"ĠPis\": 29973,\n    \"ĠReturns\": 29974,\n    \"ĠPAN\": 29975,\n    \"Ġultrasound\": 29976,\n    \"Ġcoherent\": 29977,\n    \"tracking\": 29978,\n    \"rieved\": 29979,\n    \"383\": 29980,\n    \"Ġqualitative\": 29981,\n    \"uld\": 29982,\n    \"ĠGiovanni\": 29983,\n    \"Ġstorylines\": 29984,\n    \"Ġdarkest\": 29985,\n    \"Ġvelvet\": 29986,\n    \"RIP\": 29987,\n    \"Ġcompatibility\": 29988,\n    \"Ġtroll\": 29989,\n    \"CN\": 29990,\n    \"Found\": 29991,\n    \"ĠOu\": 29992,\n    \"Ġtease\": 29993,\n    \"Ġvested\": 29994,\n    \"Ġprovocation\": 29995,\n    \"Ġimprovised\": 29996,\n    \"Ġactivation\": 29997,\n    \"unte\": 29998,\n    \"ĠMonteneg\": 29999,\n    \"ĠJOHN\": 30000,\n    \"ĠReact\": 30001,\n    \"Ġpolluted\": 30002,\n    \"217\": 30003,\n    \"Ġmushroom\": 30004,\n    \"Ġdisconnected\": 30005,\n    \"ĠVoices\": 30006,\n    \"asu\": 30007,\n    \"Ġsensory\": 30008,\n    \"REE\": 30009,\n    \"Ġmonarchy\": 30010,\n    \"Ġ173\": 30011,\n    \"doing\": 30012,\n    \"involved\": 30013,\n    \"ĠJonah\": 30014,\n    \"Ġtoxins\": 30015,\n    \"Ġtv\": 30016,\n    \"Ġacademia\": 30017,\n    \"IQ\": 30018,\n    \"Mor\": 30019,\n    \"ĠStraight\": 30020,\n    \"ĠRN\": 30021,\n    \"ĠâĹı\": 30022,\n    \"Ġpear\": 30023,\n    \"187\": 30024,\n    \"Ġendeavors\": 30025,\n    \"ĠTurbo\": 30026,\n    \"Ġducks\": 30027,\n    \"ĠRamsay\": 30028,\n    \"Ġoutpatient\": 30029,\n    \"Ġcomprehend\": 30030,\n    \"UNE\": 30031,\n    \"Ġbriefings\": 30032,\n    \"total\": 30033,\n    \"Ġmigr\": 30034,\n    \"always\": 30035,\n    \"Ġmoot\": 30036,\n    \"ĠRider\": 30037,\n    \"Ġbiblical\": 30038,\n    \"Form\": 30039,\n    \"Ġcurry\": 30040,\n    \"Ġexquisite\": 30041,\n    \"385\": 30042,\n    \"244\": 30043,\n    \"Ġattendants\": 30044,\n    \"Ġcabinets\": 30045,\n    \"nton\": 30046,\n    \"Baby\": 30047,\n    \"Honestly\": 30048,\n    \"ĠFIRE\": 30049,\n    \"211\": 30050,\n    \"itech\": 30051,\n    \"ĠProsper\": 30052,\n    \"Ġchops\": 30053,\n    \"odic\": 30054,\n    \"Rod\": 30055,\n    \"job\": 30056,\n    \"orset\": 30057,\n    \"ĠAry\": 30058,\n    \"obic\": 30059,\n    \"ĠNil\": 30060,\n    \"isable\": 30061,\n    \"Ġorche\": 30062,\n    \"Ġtrivial\": 30063,\n    \"ĠZy\": 30064,\n    \"ĠXP\": 30065,\n    \"Ġendorsing\": 30066,\n    \"ĠLIM\": 30067,\n    \"adish\": 30068,\n    \"237\": 30069,\n    \"ĠLaws\": 30070,\n    \"heid\": 30071,\n    \"ĠSignature\": 30072,\n    \"ĠVern\": 30073,\n    \"ĠBland\": 30074,\n    \"ansk\": 30075,\n    \"Ġrepository\": 30076,\n    \"ĠPetra\": 30077,\n    \"Enter\": 30078,\n    \"Ġtruths\": 30079,\n    \"Ġbordering\": 30080,\n    \"Ġpenn\": 30081,\n    \"Ġsimplified\": 30082,\n    \"zn\": 30083,\n    \"ĠCree\": 30084,\n    \"Ġ181\": 30085,\n    \"Hi\": 30086,\n    \"ĠGreenberg\": 30087,\n    \"Ġprematurely\": 30088,\n    \"ĠSass\": 30089,\n    \"Ġwrecked\": 30090,\n    \"Ġheinous\": 30091,\n    \"415\": 30092,\n    \"Turn\": 30093,\n    \"zl\": 30094,\n    \"amental\": 30095,\n    \"ĠBraz\": 30096,\n    \"fing\": 30097,\n    \"ĠAngle\": 30098,\n    \"ĠPhantom\": 30099,\n    \"agra\": 30100,\n    \"ĠShack\": 30101,\n    \"Ġhomegrown\": 30102,\n    \"Ġalright\": 30103,\n    \"AME\": 30104,\n    \"ĠKN\": 30105,\n    \"Ġclicks\": 30106,\n    \"Ġmanned\": 30107,\n    \"ĠScope\": 30108,\n    \"Ġextras\": 30109,\n    \"Ġclinicians\": 30110,\n    \"321\": 30111,\n    \"African\": 30112,\n    \"Ġjuices\": 30113,\n    \"Ġrefere\": 30114,\n    \"****\": 30115,\n    \"ambling\": 30116,\n    \"since\": 30117,\n    \"Ġvoic\": 30118,\n    \"QB\": 30119,\n    \"ĠAtmospheric\": 30120,\n    \"Mat\": 30121,\n    \"Ġperpetrated\": 30122,\n    \"ĠSteps\": 30123,\n    \"Fit\": 30124,\n    \"Ġsilenced\": 30125,\n    \"Ġbonded\": 30126,\n    \"Ġquantify\": 30127,\n    \"Houston\": 30128,\n    \"ocracy\": 30129,\n    \"Ġfreeing\": 30130,\n    \"pipe\": 30131,\n    \"corn\": 30132,\n    \"rones\": 30133,\n    \"ooked\": 30134,\n    \"ĠSuz\": 30135,\n    \"Ġunaccount\": 30136,\n    \"196\": 30137,\n    \"Ġlogos\": 30138,\n    \"ĠFurious\": 30139,\n    \"ĠSpart\": 30140,\n    \"urst\": 30141,\n    \"itri\": 30142,\n    \"ĠZub\": 30143,\n    \"ĠActual\": 30144,\n    \"Ġslee\": 30145,\n    \"Ġgag\": 30146,\n    \"Ġmetabolism\": 30147,\n    \"ĠDesigned\": 30148,\n    \"Ġpedigree\": 30149,\n    \"Ġcoolest\": 30150,\n    \"âĿ\": 30151,\n    \"iuses\": 30152,\n    \"ĠYellowstone\": 30153,\n    \"Ġinformant\": 30154,\n    \"Ġushered\": 30155,\n    \"ĠGarg\": 30156,\n    \"thel\": 30157,\n    \"Hop\": 30158,\n    \"Ġrepetitive\": 30159,\n    \"flag\": 30160,\n    \"Ġunmarked\": 30161,\n    \"ĠBrave\": 30162,\n    \"Ġincur\": 30163,\n    \"reading\": 30164,\n    \"ppel\": 30165,\n    \"lah\": 30166,\n    \"ateurs\": 30167,\n    \"286\": 30168,\n    \"ĠAtomic\": 30169,\n    \"Ġappliance\": 30170,\n    \")'\": 30171,\n    \"traditional\": 30172,\n    \"Ġdads\": 30173,\n    \"Ġregimen\": 30174,\n    \"Ġinfrared\": 30175,\n    \"Ġdotted\": 30176,\n    \"Ġtails\": 30177,\n    \"Ġhorrors\": 30178,\n    \"uments\": 30179,\n    \"Ġdub\": 30180,\n    \"lighting\": 30181,\n    \"Ġunearthed\": 30182,\n    \"assisted\": 30183,\n    \"ĠSpiel\": 30184,\n    \"trial\": 30185,\n    \"Ġpersever\": 30186,\n    \"MAX\": 30187,\n    \"Ġicing\": 30188,\n    \"Energy\": 30189,\n    \"Ġ1943\": 30190,\n    \"move\": 30191,\n    \"Error\": 30192,\n    \"Ġliter\": 30193,\n    \"ĠCly\": 30194,\n    \"Ari\": 30195,\n    \"Ġgranite\": 30196,\n    \"Ġcropped\": 30197,\n    \"ĠRD\": 30198,\n    \"ĠREM\": 30199,\n    \"TX\": 30200,\n    \"Ġdispleasure\": 30201,\n    \"ĠComfort\": 30202,\n    \"Ġunsettling\": 30203,\n    \"Ġscratching\": 30204,\n    \"866\": 30205,\n    \"eton\": 30206,\n    \"560\": 30207,\n    \"Ġcommonplace\": 30208,\n    \"Ġreproduced\": 30209,\n    \"ggie\": 30210,\n    \"Ġschooling\": 30211,\n    \"Ġreprim\": 30212,\n    \"Ġdarling\": 30213,\n    \"huge\": 30214,\n    \"ĠDante\": 30215,\n    \"cp\": 30216,\n    \"heastern\": 30217,\n    \"Ġeduc\": 30218,\n    \"Digital\": 30219,\n    \"Ġwrath\": 30220,\n    \"Ġwatering\": 30221,\n    \"ĠTail\": 30222,\n    \"Ġdegradation\": 30223,\n    \"530\": 30224,\n    \"usive\": 30225,\n    \"ĠXu\": 30226,\n    \"ĠAH\": 30227,\n    \"Ġclassy\": 30228,\n    \"ĠSET\": 30229,\n    \"Ġcriminally\": 30230,\n    \"dependent\": 30231,\n    \"ĠAlps\": 30232,\n    \"Ġnotwithstanding\": 30233,\n    \"Ġfamiliarity\": 30234,\n    \"ĠAPP\": 30235,\n    \"aurus\": 30236,\n    \"gments\": 30237,\n    \"Mid\": 30238,\n    \"Ġepilepsy\": 30239,\n    \"Ġresemblance\": 30240,\n    \"brush\": 30241,\n    \"Ġ333\": 30242,\n    \"Ġliberated\": 30243,\n    \"ĠBeng\": 30244,\n    \"ĠLans\": 30245,\n    \"Ġtraff\": 30246,\n    \"ihu\": 30247,\n    \"establish\": 30248,\n    \"Ġcort\": 30249,\n    \"Rick\": 30250,\n    \"Ġplugged\": 30251,\n    \"onement\": 30252,\n    \"ĠAccounting\": 30253,\n    \"Ġreconstruct\": 30254,\n    \"Pop\": 30255,\n    \"Ġincapable\": 30256,\n    \"aho\": 30257,\n    \"ĠDexter\": 30258,\n    \"Ġpitted\": 30259,\n    \"Ġbathing\": 30260,\n    \"Ġdun\": 30261,\n    \"Ġexplor\": 30262,\n    \"ĠMidnight\": 30263,\n    \"Ġactiv\": 30264,\n    \"iann\": 30265,\n    \"likely\": 30266,\n    \"acons\": 30267,\n    \"owicz\": 30268,\n    \"Ġnegativity\": 30269,\n    \"Ġfreel\": 30270,\n    \"ewitness\": 30271,\n    \"Ġinj\": 30272,\n    \"Stephen\": 30273,\n    \"Ġshredded\": 30274,\n    \"Ġprepar\": 30275,\n    \"Script\": 30276,\n    \"Ġcorrectional\": 30277,\n    \"Ġcommits\": 30278,\n    \"hai\": 30279,\n    \"activity\": 30280,\n    \"Imp\": 30281,\n    \"Ġstumble\": 30282,\n    \"Ġcache\": 30283,\n    \"ĠPromise\": 30284,\n    \"Ġprecinct\": 30285,\n    \"Ġmulticultural\": 30286,\n    \"Ġsubstitutes\": 30287,\n    \"Ġshortened\": 30288,\n    \"ovable\": 30289,\n    \"Ġfasting\": 30290,\n    \"Ġinfused\": 30291,\n    \"Ġbulldo\": 30292,\n    \"alm\": 30293,\n    \"Ġadjoining\": 30294,\n    \"Ġmultiplayer\": 30295,\n    \"ĠAlien\": 30296,\n    \"Ġpund\": 30297,\n    \"ethyl\": 30298,\n    \"Ġbliss\": 30299,\n    \"ĠDecision\": 30300,\n    \"Ġbab\": 30301,\n    \"Ġangrily\": 30302,\n    \"another\": 30303,\n    \"oled\": 30304,\n    \"ainted\": 30305,\n    \"ĠPriest\": 30306,\n    \"Ġdraped\": 30307,\n    \"ĠPersonally\": 30308,\n    \"Ġstomp\": 30309,\n    \"ĠWolfgang\": 30310,\n    \"Ġoste\": 30311,\n    \"itches\": 30312,\n    \"Ġhoops\": 30313,\n    \"ĠJO\": 30314,\n    \"Ġsche\": 30315,\n    \"ĠZan\": 30316,\n    \"Ġcleans\": 30317,\n    \"Ġclimbs\": 30318,\n    \"Ġelectronically\": 30319,\n    \"243\": 30320,\n    \"ocy\": 30321,\n    \"gall\": 30322,\n    \"ĠREAL\": 30323,\n    \"Ġmurky\": 30324,\n    \"Ġmodernization\": 30325,\n    \"tub\": 30326,\n    \"Really\": 30327,\n    \"Ġlax\": 30328,\n    \"Ġdoubted\": 30329,\n    \"yden\": 30330,\n    \"ĠPrevent\": 30331,\n    \"UTERS\": 30332,\n    \"Ġoverride\": 30333,\n    \"ĠSAF\": 30334,\n    \"Ġcoun\": 30335,\n    \"Ġexcerpts\": 30336,\n    \"Ġmotivations\": 30337,\n    \"Ġdecency\": 30338,\n    \"Ġastronomers\": 30339,\n    \"orical\": 30340,\n    \"Ġaltering\": 30341,\n    \"Ġ232\": 30342,\n    \"described\": 30343,\n    \"omic\": 30344,\n    \"Ġexh\": 30345,\n    \"Ġknocks\": 30346,\n    \"ĠRiot\": 30347,\n    \"ĠPurs\": 30348,\n    \"equal\": 30349,\n    \"pleting\": 30350,\n    \"llan\": 30351,\n    \"ĠSOL\": 30352,\n    \"iator\": 30353,\n    \"ILE\": 30354,\n    \"ĠWM\": 30355,\n    \"Ġdefences\": 30356,\n    \"Ġforearm\": 30357,\n    \"Toronto\": 30358,\n    \"526\": 30359,\n    \"Ġacne\": 30360,\n    \"Ġthirteen\": 30361,\n    \"itiz\": 30362,\n    \"akable\": 30363,\n    \"charges\": 30364,\n    \"Ġinaction\": 30365,\n    \"Ġbred\": 30366,\n    \"Ġdeficiency\": 30367,\n    \"Ġintrigue\": 30368,\n    \"opoly\": 30369,\n    \"ĠCamer\": 30370,\n    \"ĠMelt\": 30371,\n    \"Ġunlawfully\": 30372,\n    \"Ġpenetrate\": 30373,\n    \"ĠUsed\": 30374,\n    \"ĠDirty\": 30375,\n    \"Ġexcerpt\": 30376,\n    \"ĠYen\": 30377,\n    \"ĠCARD\": 30378,\n    \"Ġcher\": 30379,\n    \"ĠChallenges\": 30380,\n    \"ieves\": 30381,\n    \"Ġambush\": 30382,\n    \"Data\": 30383,\n    \"eeks\": 30384,\n    \"Ġgiveaway\": 30385,\n    \"Ġpawn\": 30386,\n    \"Ġtransf\": 30387,\n    \"renched\": 30388,\n    \"Ġmoderately\": 30389,\n    \"Ġnumbered\": 30390,\n    \"ĠIntegrity\": 30391,\n    \"ĠHOU\": 30392,\n    \"ĠHDMI\": 30393,\n    \"Royal\": 30394,\n    \"LT\": 30395,\n    \"ĠDirk\": 30396,\n    \"izon\": 30397,\n    \"Ġ227\": 30398,\n    \"Ġdisagrees\": 30399,\n    \"ĠNinth\": 30400,\n    \"Ġincrement\": 30401,\n    \"ĠGlory\": 30402,\n    \"suff\": 30403,\n    \"Ġartery\": 30404,\n    \"ĠEmployee\": 30405,\n    \"bum\": 30406,\n    \"ĠEditorial\": 30407,\n    \"Kh\": 30408,\n    \"ĠPremiere\": 30409,\n    \"ĠWeld\": 30410,\n    \"ĠIncluded\": 30411,\n    \"Ġmathematical\": 30412,\n    \"Ġexponentially\": 30413,\n    \"Ġhandwritten\": 30414,\n    \"ĠMAS\": 30415,\n    \"Ġindiscrim\": 30416,\n    \"Ġnutrient\": 30417,\n    \"ĠSelection\": 30418,\n    \"Ġ219\": 30419,\n    \"hyd\": 30420,\n    \"Ġdeton\": 30421,\n    \"Ã¦\": 30422,\n    \"dark\": 30423,\n    \"ĠFidel\": 30424,\n    \"Ġmonkeys\": 30425,\n    \"Ġnutritious\": 30426,\n    \"Ġheadlights\": 30427,\n    \"oller\": 30428,\n    \"piring\": 30429,\n    \"ĠDefenders\": 30430,\n    \"Ġdrown\": 30431,\n    \"elong\": 30432,\n    \"Ġfloats\": 30433,\n    \"graduate\": 30434,\n    \"Ġprosper\": 30435,\n    \"ĠNamed\": 30436,\n    \"ĠEating\": 30437,\n    \"ECK\": 30438,\n    \"establishment\": 30439,\n    \"XM\": 30440,\n    \"Ġsoaking\": 30441,\n    \"278\": 30442,\n    \"Ġlistener\": 30443,\n    \"Ġsimultaneous\": 30444,\n    \"olutions\": 30445,\n    \"payer\": 30446,\n    \"Ġcustomize\": 30447,\n    \"ĠROCK\": 30448,\n    \"Ġaltar\": 30449,\n    \"ĠExercise\": 30450,\n    \"anky\": 30451,\n    \"ĠProfession\": 30452,\n    \"sever\": 30453,\n    \"ĠMerchant\": 30454,\n    \"RF\": 30455,\n    \"ĠCombat\": 30456,\n    \"Ġlegality\": 30457,\n    \"fledged\": 30458,\n    \"Ġdiapers\": 30459,\n    \"lves\": 30460,\n    \"Ġlur\": 30461,\n    \"Ġignores\": 30462,\n    \"ĠProtocol\": 30463,\n    \"Ġrepresentations\": 30464,\n    \"ĠBlumenthal\": 30465,\n    \"ĠLime\": 30466,\n    \"romptu\": 30467,\n    \"Ġbesieged\": 30468,\n    \"dl\": 30469,\n    \"Ġsighting\": 30470,\n    \"ĠParm\": 30471,\n    \"ĠServer\": 30472,\n    \"ĠBenghazi\": 30473,\n    \"estival\": 30474,\n    \"Ġplaylist\": 30475,\n    \"ĠUng\": 30476,\n    \"ĠQuantum\": 30477,\n    \"Ġcompromises\": 30478,\n    \"ĠSurvivor\": 30479,\n    \"ĠMobility\": 30480,\n    \"Ġbounty\": 30481,\n    \"ophers\": 30482,\n    \"ISA\": 30483,\n    \"need\": 30484,\n    \"uese\": 30485,\n    \"Ġorn\": 30486,\n    \"218\": 30487,\n    \"Ġ530\": 30488,\n    \"Ġbuddies\": 30489,\n    \"Ġagendas\": 30490,\n    \"ĠFeldman\": 30491,\n    \"ĠÃĸ\": 30492,\n    \"ĠBMC\": 30493,\n    \"ĠServe\": 30494,\n    \"Ent\": 30495,\n    \"ĠKH\": 30496,\n    \"ĠINT\": 30497,\n    \"Ġlittered\": 30498,\n    \"Ġvisitation\": 30499,\n    \"mist\": 30500,\n    \"Ġdupl\": 30501,\n    \"Ġrouted\": 30502,\n    \"ĠAmount\": 30503,\n    \"Dev\": 30504,\n    \"ĠConv\": 30505,\n    \"Ġslams\": 30506,\n    \"ĠVeterinary\": 30507,\n    \"bold\": 30508,\n    \"Ġ186\": 30509,\n    \"ĠDOT\": 30510,\n    \"builder\": 30511,\n    \"Ġdecay\": 30512,\n    \"ĠHemp\": 30513,\n    \"pelled\": 30514,\n    \"Ġmankind\": 30515,\n    \"Tonight\": 30516,\n    \"Ġeffortlessly\": 30517,\n    \"ĠBUT\": 30518,\n    \"Ġhostilities\": 30519,\n    \"formerly\": 30520,\n    \"alon\": 30521,\n    \"ĠCrash\": 30522,\n    \"humane\": 30523,\n    \"Ġmayhem\": 30524,\n    \"ĠBudd\": 30525,\n    \"Ġdisinformation\": 30526,\n    \"Ġ226\": 30527,\n    \"Ġprototypes\": 30528,\n    \"__\": 30529,\n    \"IVERS\": 30530,\n    \"izzy\": 30531,\n    \"ĠMight\": 30532,\n    \"ĠPip\": 30533,\n    \"pour\": 30534,\n    \"INO\": 30535,\n    \"ĠLL\": 30536,\n    \"Ġwiret\": 30537,\n    \"Ġresorted\": 30538,\n    \"ĠTanaka\": 30539,\n    \"ĠDOES\": 30540,\n    \"Earlier\": 30541,\n    \"HO\": 30542,\n    \"Ġmoniker\": 30543,\n    \"ĠFang\": 30544,\n    \"ĠHua\": 30545,\n    \"bered\": 30546,\n    \"adding\": 30547,\n    \"194\": 30548,\n    \"STR\": 30549,\n    \".\\\")\": 30550,\n    \"cop\": 30551,\n    \"ĠFlags\": 30552,\n    \"ĠColleges\": 30553,\n    \"ĠUz\": 30554,\n    \"Ġsparks\": 30555,\n    \"Ġparadox\": 30556,\n    \"Marie\": 30557,\n    \"Strong\": 30558,\n    \"Ġstrawberry\": 30559,\n    \"Ġnurturing\": 30560,\n    \"Ġfax\": 30561,\n    \"Tor\": 30562,\n    \"killer\": 30563,\n    \"burse\": 30564,\n    \"Ġattachments\": 30565,\n    \"Ġpup\": 30566,\n    \"Ġexhaustion\": 30567,\n    \"Ġwhisky\": 30568,\n    \"isu\": 30569,\n    \"ologically\": 30570,\n    \"iership\": 30571,\n    \"Ġlamps\": 30572,\n    \"Ġshuff\": 30573,\n    \"Ġcentralized\": 30574,\n    \"ĠNeedless\": 30575,\n    \"Ġgrenade\": 30576,\n    \"Ġrouter\": 30577,\n    \"Ġoptics\": 30578,\n    \"ivering\": 30579,\n    \"Ġpioneers\": 30580,\n    \"ĠHug\": 30581,\n    \"Ġhandguns\": 30582,\n    \"010\": 30583,\n    \"Ġbailed\": 30584,\n    \"uana\": 30585,\n    \"197\": 30586,\n    \"Ġdistorted\": 30587,\n    \"ĠEssentially\": 30588,\n    \"ĠSilent\": 30589,\n    \"Ġcomparative\": 30590,\n    \"Music\": 30591,\n    \"ĠMUS\": 30592,\n    \"Bur\": 30593,\n    \"ĠComet\": 30594,\n    \"ĠWinchester\": 30595,\n    \"IGN\": 30596,\n    \"Mod\": 30597,\n    \"ĠCandidate\": 30598,\n    \"Ġdysfunctional\": 30599,\n    \"ĠCeleb\": 30600,\n    \"Ġhitch\": 30601,\n    \"api\": 30602,\n    \"Ġidiot\": 30603,\n    \"Ġunsupported\": 30604,\n    \"gat\": 30605,\n    \"inker\": 30606,\n    \"Ġredevelop\": 30607,\n    \"Ġdwind\": 30608,\n    \"Ġforgetting\": 30609,\n    \"ĠRost\": 30610,\n    \"Ġremembrance\": 30611,\n    \"Na\": 30612,\n    \"mopolitan\": 30613,\n    \"Ġberries\": 30614,\n    \"Ġmarital\": 30615,\n    \"Vol\": 30616,\n    \"ĠClosing\": 30617,\n    \"ĠHindus\": 30618,\n    \"itism\": 30619,\n    \"Ġrover\": 30620,\n    \"Ġmysteries\": 30621,\n    \"ĠNig\": 30622,\n    \"ucing\": 30623,\n    \"Ġfabrication\": 30624,\n    \"Ġgarments\": 30625,\n    \"Ġwield\": 30626,\n    \"ĠCompton\": 30627,\n    \"357\": 30628,\n    \"Ġoxide\": 30629,\n    \"chron\": 30630,\n    \"ĠThought\": 30631,\n    \"Ġcomed\": 30632,\n    \"ĠEpstein\": 30633,\n    \"ĠBART\": 30634,\n    \"orative\": 30635,\n    \"ĠKahn\": 30636,\n    \"adan\": 30637,\n    \"APH\": 30638,\n    \"cum\": 30639,\n    \"Ġloophole\": 30640,\n    \"ĠGoPro\": 30641,\n    \"osit\": 30642,\n    \"Ġspecification\": 30643,\n    \"ĠAPR\": 30644,\n    \"Ġdrains\": 30645,\n    \"Ġconserve\": 30646,\n    \"ĠMorse\": 30647,\n    \"Ġcalorie\": 30648,\n    \"ĠCheney\": 30649,\n    \"station\": 30650,\n    \"Ġevangel\": 30651,\n    \"Ġspraying\": 30652,\n    \"lections\": 30653,\n    \"Ġenclosure\": 30654,\n    \"Ġcommanded\": 30655,\n    \"ĠOrganizations\": 30656,\n    \"Ġimb\": 30657,\n    \"mins\": 30658,\n    \"ĠTobias\": 30659,\n    \"Ve\": 30660,\n    \"ĠNau\": 30661,\n    \"183\": 30662,\n    \"ĠGuantanamo\": 30663,\n    \"173\": 30664,\n    \"Ġrequisite\": 30665,\n    \"Ġderivative\": 30666,\n    \"Ġpopulism\": 30667,\n    \"Ġcultivated\": 30668,\n    \"lord\": 30669,\n    \"uler\": 30670,\n    \"ĠDEA\": 30671,\n    \"inally\": 30672,\n    \"Ġdemonstr\": 30673,\n    \"trip\": 30674,\n    \"ĠFirefox\": 30675,\n    \"246\": 30676,\n    \"confirmed\": 30677,\n    \"Anne\": 30678,\n    \"Ġtamp\": 30679,\n    \"ĠHousehold\": 30680,\n    \"amous\": 30681,\n    \"Meet\": 30682,\n    \"Ġdashed\": 30683,\n    \"pire\": 30684,\n    \"Ġinex\": 30685,\n    \"Ġloosen\": 30686,\n    \"272\": 30687,\n    \"famous\": 30688,\n    \"ĠHeard\": 30689,\n    \"Ġhindsight\": 30690,\n    \"Ġdepot\": 30691,\n    \"ĠCutting\": 30692,\n    \"ĠMouse\": 30693,\n    \"Ġgeological\": 30694,\n    \"number\": 30695,\n    \"OUN\": 30696,\n    \".,\\\"\": 30697,\n    \"Ġmoderation\": 30698,\n    \"ĠUNHCR\": 30699,\n    \"Ġdomains\": 30700,\n    \"eco\": 30701,\n    \"Ġcrater\": 30702,\n    \"Ġ510\": 30703,\n    \"kid\": 30704,\n    \"Ġcylinders\": 30705,\n    \"ĠClasses\": 30706,\n    \"Kn\": 30707,\n    \"Ġcarcin\": 30708,\n    \"ĠHunting\": 30709,\n    \"irit\": 30710,\n    \"ARP\": 30711,\n    \"anting\": 30712,\n    \"ĠMarino\": 30713,\n    \"ĠRESP\": 30714,\n    \"ifle\": 30715,\n    \"Ġ239\": 30716,\n    \"fman\": 30717,\n    \"Ġtheoretically\": 30718,\n    \"Ġdistraught\": 30719,\n    \"Ġstaircase\": 30720,\n    \"Ġexpel\": 30721,\n    \"Ġlord\": 30722,\n    \"Ġbehaviours\": 30723,\n    \"Ġprescribing\": 30724,\n    \"ographs\": 30725,\n    \"ĠNewly\": 30726,\n    \"Ġpatiently\": 30727,\n    \"Ġskyline\": 30728,\n    \"udos\": 30729,\n    \"Ġrepertoire\": 30730,\n    \"Ġhover\": 30731,\n    \"mint\": 30732,\n    \"Ġclears\": 30733,\n    \"Ġkale\": 30734,\n    \"ĠSco\": 30735,\n    \"ĠCoulter\": 30736,\n    \"Ġpancreat\": 30737,\n    \"pu\": 30738,\n    \"995\": 30739,\n    \"Ġincompetent\": 30740,\n    \"2007\": 30741,\n    \"Ġgripping\": 30742,\n    \"enable\": 30743,\n    \"Ġreinforcing\": 30744,\n    \"ĠFee\": 30745,\n    \"education\": 30746,\n    \"ĠKuro\": 30747,\n    \"Ġbowed\": 30748,\n    \"Ġshave\": 30749,\n    \"ĠMean\": 30750,\n    \"xi\": 30751,\n    \"Ġinciting\": 30752,\n    \"atters\": 30753,\n    \"Ġecstatic\": 30754,\n    \"hog\": 30755,\n    \"Ġclauses\": 30756,\n    \"Ġsubt\": 30757,\n    \"Ġbehaved\": 30758,\n    \"tains\": 30759,\n    \"Liverpool\": 30760,\n    \"Ġstrives\": 30761,\n    \"ĠKev\": 30762,\n    \"ĠFramework\": 30763,\n    \"defined\": 30764,\n    \"Ġrecounts\": 30765,\n    \"array\": 30766,\n    \"tips\": 30767,\n    \"Ġartificially\": 30768,\n    \"fits\": 30769,\n    \"Clearly\": 30770,\n    \"mediate\": 30771,\n    \"Ġunseen\": 30772,\n    \"Ġthugs\": 30773,\n    \"ĠLent\": 30774,\n    \"Ġ1938\": 30775,\n    \"Ġgenital\": 30776,\n    \"ĠSonic\": 30777,\n    \"ĠWarehouse\": 30778,\n    \"pler\": 30779,\n    \"Ġunm\": 30780,\n    \"Ġpackets\": 30781,\n    \"ĠMET\": 30782,\n    \"ealous\": 30783,\n    \"ographers\": 30784,\n    \"Ġlabou\": 30785,\n    \"Core\": 30786,\n    \"+,\": 30787,\n    \"parable\": 30788,\n    \"Ġstrat\": 30789,\n    \"Ġinvitations\": 30790,\n    \"Ġsouven\": 30791,\n    \"Ġbillboards\": 30792,\n    \"ĠRegulations\": 30793,\n    \"Ġdwarf\": 30794,\n    \"Ġtoler\": 30795,\n    \"Ġprose\": 30796,\n    \"Ġestates\": 30797,\n    \"Ġmetabolic\": 30798,\n    \"ĠSuff\": 30799,\n    \"ĠFirstly\": 30800,\n    \"Ġpolio\": 30801,\n    \"Ġchick\": 30802,\n    \"ĠDaughter\": 30803,\n    \"Ġsubstant\": 30804,\n    \"ĠIdentity\": 30805,\n    \"umbers\": 30806,\n    \"ĠFacts\": 30807,\n    \"Ġfrust\": 30808,\n    \"Ġdissip\": 30809,\n    \"ĠDeck\": 30810,\n    \"Hy\": 30811,\n    \"ĠBirch\": 30812,\n    \"Ġhurled\": 30813,\n    \"democracy\": 30814,\n    \"nered\": 30815,\n    \"eper\": 30816,\n    \"Ġcerebral\": 30817,\n    \"181\": 30818,\n    \"Ġhalves\": 30819,\n    \"abit\": 30820,\n    \"balance\": 30821,\n    \"ĠTibet\": 30822,\n    \"Ġhandheld\": 30823,\n    \"ĠDough\": 30824,\n    \"Ġprogrammed\": 30825,\n    \"hw\": 30826,\n    \"Ġoutlawed\": 30827,\n    \"ĠSerious\": 30828,\n    \"Ġironically\": 30829,\n    \"Ġmanipulating\": 30830,\n    \")\\\"\": 30831,\n    \"juries\": 30832,\n    \"Ġfragrance\": 30833,\n    \"crete\": 30834,\n    \"ĠHHS\": 30835,\n    \"cience\": 30836,\n    \"Ġcosmic\": 30837,\n    \"Ġforeclosure\": 30838,\n    \"Ġpercentages\": 30839,\n    \"Bus\": 30840,\n    \"Ġenticing\": 30841,\n    \"extra\": 30842,\n    \"ĠShy\": 30843,\n    \"ĠÂ¥\": 30844,\n    \"Ġheadsets\": 30845,\n    \"imensional\": 30846,\n    \"Ġlux\": 30847,\n    \"Ġresidual\": 30848,\n    \"Ġmantle\": 30849,\n    \"ĠSJ\": 30850,\n    \"ĠPeaks\": 30851,\n    \"ĠFinger\": 30852,\n    \"Ġunfolds\": 30853,\n    \"anity\": 30854,\n    \"Ġresettlement\": 30855,\n    \"ĠWeak\": 30856,\n    \"ĠBeen\": 30857,\n    \"Ġ198\": 30858,\n    \"Ġangels\": 30859,\n    \"ĠFarn\": 30860,\n    \"peace\": 30861,\n    \"Ġcapac\": 30862,\n    \"Ġhue\": 30863,\n    \"Ġlust\": 30864,\n    \"traumatic\": 30865,\n    \"laun\": 30866,\n    \"Ġstrawberries\": 30867,\n    \"Ġherbal\": 30868,\n    \"Ġconversions\": 30869,\n    \"ĠHeld\": 30870,\n    \"Ġprescribe\": 30871,\n    \"Its\": 30872,\n    \"ĠDartmouth\": 30873,\n    \"Ġfashioned\": 30874,\n    \"460\": 30875,\n    \"BLE\": 30876,\n    \"international\": 30877,\n    \"Ġlumin\": 30878,\n    \"Ġplantation\": 30879,\n    \"ilde\": 30880,\n    \"490\": 30881,\n    \"Ġeuph\": 30882,\n    \"Ġdisgust\": 30883,\n    \"Ġaspire\": 30884,\n    \"medical\": 30885,\n    \"Ġsocialism\": 30886,\n    \"Ġdissolve\": 30887,\n    \"Wal\": 30888,\n    \"Ġadmittedly\": 30889,\n    \"Ġsewing\": 30890,\n    \"ĠAcer\": 30891,\n    \"Ġtul\": 30892,\n    \"Ġfacilit\": 30893,\n    \"Ġgrandma\": 30894,\n    \"ĠFeeling\": 30895,\n    \"Ġobst\": 30896,\n    \"ĠFranz\": 30897,\n    \"ĠPalin\": 30898,\n    \"ĠIncrease\": 30899,\n    \"gets\": 30900,\n    \"ĠImam\": 30901,\n    \"âĢİ\": 30902,\n    \"Ġcoincides\": 30903,\n    \"urrence\": 30904,\n    \"Ġlifes\": 30905,\n    \"Lab\": 30906,\n    \"Ham\": 30907,\n    \"angelo\": 30908,\n    \"Wild\": 30909,\n    \"Ġvetoed\": 30910,\n    \"Ġventilation\": 30911,\n    \"olid\": 30912,\n    \"Summer\": 30913,\n    \"Ġfacade\": 30914,\n    \"neys\": 30915,\n    \"ĠWOM\": 30916,\n    \"ĠBenny\": 30917,\n    \"ĠMarried\": 30918,\n    \"squ\": 30919,\n    \"ĠReflect\": 30920,\n    \"return\": 30921,\n    \"elia\": 30922,\n    \"olding\": 30923,\n    \"Ġrefine\": 30924,\n    \"ĠMadness\": 30925,\n    \"innacle\": 30926,\n    \"posts\": 30927,\n    \"287\": 30928,\n    \"fruit\": 30929,\n    \"274\": 30930,\n    \"icator\": 30931,\n    \"ĠVoy\": 30932,\n    \"Ġunsett\": 30933,\n    \"Ġfant\": 30934,\n    \"Ġtreaties\": 30935,\n    \"Ġcrystals\": 30936,\n    \"Ġhijacked\": 30937,\n    \"words\": 30938,\n    \"ĠReleased\": 30939,\n    \"Save\": 30940,\n    \"Ġcannon\": 30941,\n    \"Ġanomaly\": 30942,\n    \"Ġbeacon\": 30943,\n    \"Ġcrippled\": 30944,\n    \"Ġbundles\": 30945,\n    \"Ġuntreated\": 30946,\n    \"Ġhappiest\": 30947,\n    \"Ġgalaxies\": 30948,\n    \"Ġoccupational\": 30949,\n    \"416\": 30950,\n    \"Dar\": 30951,\n    \"Ġcrank\": 30952,\n    \"Ġappropriation\": 30953,\n    \"asking\": 30954,\n    \"mens\": 30955,\n    \"Ġdetector\": 30956,\n    \"Ġskewed\": 30957,\n    \"Ġpoke\": 30958,\n    \"254\": 30959,\n    \"Ġhypertension\": 30960,\n    \"apolog\": 30961,\n    \"Ġevaluations\": 30962,\n    \"blocks\": 30963,\n    \"Ġpow\": 30964,\n    \"GEN\": 30965,\n    \"Ġscalp\": 30966,\n    \"Ġarrogant\": 30967,\n    \"AIDS\": 30968,\n    \"ority\": 30969,\n    \"Ġredirect\": 30970,\n    \"Ġderogatory\": 30971,\n    \"Ġlateral\": 30972,\n    \"495\": 30973,\n    \"rolley\": 30974,\n    \"brew\": 30975,\n    \"Ġbabys\": 30976,\n    \"Ġmuff\": 30977,\n    \"ĠRequ\": 30978,\n    \"Ġdime\": 30979,\n    \"Ġwonderfully\": 30980,\n    \"Ġtreasures\": 30981,\n    \"ĠNES\": 30982,\n    \"Ġponds\": 30983,\n    \"Ġimpulse\": 30984,\n    \"Ġdetecting\": 30985,\n    \"Ġgrin\": 30986,\n    \"Ġbrid\": 30987,\n    \"Ġshoved\": 30988,\n    \"Ġpurge\": 30989,\n    \"irteen\": 30990,\n    \"OTHER\": 30991,\n    \"ÙĦ\": 30992,\n    \"irsch\": 30993,\n    \"ĠOcc\": 30994,\n    \"193\": 30995,\n    \"Ġfodder\": 30996,\n    \"wrote\": 30997,\n    \"meric\": 30998,\n    \"posal\": 30999,\n    \"Ġwinters\": 31000,\n    \"ĠJuice\": 31001,\n    \"hub\": 31002,\n    \"Ġcontrasting\": 31003,\n    \"Brazil\": 31004,\n    \"Ġflashy\": 31005,\n    \"uffer\": 31006,\n    \"technology\": 31007,\n    \"Children\": 31008,\n    \"Ġcatapult\": 31009,\n    \"owsky\": 31010,\n    \"ĠEclipse\": 31011,\n    \"abeth\": 31012,\n    \"ĠParticip\": 31013,\n    \"Ġlaud\": 31014,\n    \"ĠQuiet\": 31015,\n    \"Ġsimulations\": 31016,\n    \"Ġsacrificing\": 31017,\n    \"Ġpreaching\": 31018,\n    \"Ġvoicing\": 31019,\n    \"itizen\": 31020,\n    \"Ġgn\": 31021,\n    \"Ġsans\": 31022,\n    \"Ġ285\": 31023,\n    \"ĠRobot\": 31024,\n    \"Ġ1936\": 31025,\n    \"Ġsham\": 31026,\n    \"ĠKislyak\": 31027,\n    \"ĠGCC\": 31028,\n    \"tale\": 31029,\n    \"ĠShades\": 31030,\n    \"Ġsediment\": 31031,\n    \"Ġconveniently\": 31032,\n    \"Give\": 31033,\n    \"mounted\": 31034,\n    \"Ġpeel\": 31035,\n    \"Jun\": 31036,\n    \"ĠEisenhower\": 31037,\n    \"Ġdiplom\": 31038,\n    \"ĠPreservation\": 31039,\n    \"Ġaffirm\": 31040,\n    \"Ġtaboo\": 31041,\n    \"ĠGarr\": 31042,\n    \"ĠApply\": 31043,\n    \"prim\": 31044,\n    \"Ġausp\": 31045,\n    \"Ġtextbook\": 31046,\n    \"Ġforfeit\": 31047,\n    \"icides\": 31048,\n    \"Ġundis\": 31049,\n    \"DJ\": 31050,\n    \"Ġ\\\"...\": 31051,\n    \"ĠXperia\": 31052,\n    \"Ġfurry\": 31053,\n    \"Australian\": 31054,\n    \"Ġpreach\": 31055,\n    \"Ġparamed\": 31056,\n    \"Ġ196\": 31057,\n    \"agos\": 31058,\n    \"ĠRIP\": 31059,\n    \"Ġ408\": 31060,\n    \"ĠQuarterly\": 31061,\n    \"ĠQuentin\": 31062,\n    \"Ġdeft\": 31063,\n    \"ĠVlad\": 31064,\n    \"massive\": 31065,\n    \"apore\": 31066,\n    \"Ġquestionnaire\": 31067,\n    \"secution\": 31068,\n    \"ĠTunnel\": 31069,\n    \"ĠAssist\": 31070,\n    \"BILITY\": 31071,\n    \"everything\": 31072,\n    \"vich\": 31073,\n    \"Ġcomparatively\": 31074,\n    \"heng\": 31075,\n    \"ETH\": 31076,\n    \"ĠiPod\": 31077,\n    \"Ġinsurgent\": 31078,\n    \"Ġtestosterone\": 31079,\n    \"191\": 31080,\n    \"Ġmoons\": 31081,\n    \"Ġgripped\": 31082,\n    \"Ġstrang\": 31083,\n    \"pects\": 31084,\n    \"ĠSERVICE\": 31085,\n    \"Ġnumb\": 31086,\n    \"Ġmeasurable\": 31087,\n    \"Ġdismantled\": 31088,\n    \"Ġdepict\": 31089,\n    \"Ġretake\": 31090,\n    \"Light\": 31091,\n    \"Ġaquatic\": 31092,\n    \"useum\": 31093,\n    \"judicial\": 31094,\n    \"Ġ****\": 31095,\n    \"Ġrosters\": 31096,\n    \"certain\": 31097,\n    \"Ġhypothesis\": 31098,\n    \"2002\": 31099,\n    \"Snow\": 31100,\n    \"Ġpounded\": 31101,\n    \"ĠZel\": 31102,\n    \"ĠTrem\": 31103,\n    \"iversity\": 31104,\n    \"219\": 31105,\n    \"Jen\": 31106,\n    \"ĠAdventures\": 31107,\n    \"Ġcylinder\": 31108,\n    \"Ġbanging\": 31109,\n    \"Ġbalk\": 31110,\n    \"analy\": 31111,\n    \"ĠHust\": 31112,\n    \"ookie\": 31113,\n    \"ĠReturning\": 31114,\n    \"Ġpods\": 31115,\n    \"analysis\": 31116,\n    \"ĠTruman\": 31117,\n    \"Ġorg\": 31118,\n    \"Ġsar\": 31119,\n    \"Ġdred\": 31120,\n    \"ĠTelecommunications\": 31121,\n    \"ĠSven\": 31122,\n    \"carry\": 31123,\n    \"ĠLOVE\": 31124,\n    \"Ġparting\": 31125,\n    \"asar\": 31126,\n    \"utations\": 31127,\n    \"itic\": 31128,\n    \"Ġactu\": 31129,\n    \"Ġbananas\": 31130,\n    \"ĠNights\": 31131,\n    \"410\": 31132,\n    \"Still\": 31133,\n    \"Ġtweaked\": 31134,\n    \"went\": 31135,\n    \"Ġtoddlers\": 31136,\n    \"irted\": 31137,\n    \"Ġpaed\": 31138,\n    \"ĠWink\": 31139,\n    \"Ġviewpoint\": 31140,\n    \"ĠHelic\": 31141,\n    \"Ġhandshake\": 31142,\n    \"Ġpoaching\": 31143,\n    \"Ġrounding\": 31144,\n    \"268\": 31145,\n    \"ĠNVIDIA\": 31146,\n    \"Ġsquat\": 31147,\n    \"Ġtowed\": 31148,\n    \"Ġhandler\": 31149,\n    \"Ġconspir\": 31150,\n    \"Ġadditionally\": 31151,\n    \"CENT\": 31152,\n    \"ĠÃľ\": 31153,\n    \"article\": 31154,\n    \"ĠTough\": 31155,\n    \"NM\": 31156,\n    \"Rem\": 31157,\n    \"Ġstunts\": 31158,\n    \"ILS\": 31159,\n    \"ĠLM\": 31160,\n    \"Connect\": 31161,\n    \"ĠParagu\": 31162,\n    \"Ġcomplexities\": 31163,\n    \"Ġhugging\": 31164,\n    \"Ġabolish\": 31165,\n    \"ricting\": 31166,\n    \"ĠItems\": 31167,\n    \"Ġtemples\": 31168,\n    \"ĠSeat\": 31169,\n    \"ĠRubber\": 31170,\n    \"Ġindic\": 31171,\n    \"ĠVitamin\": 31172,\n    \"Ġcitations\": 31173,\n    \"Ġarmored\": 31174,\n    \"---------------\": 31175,\n    \"ĠNeo\": 31176,\n    \"ippy\": 31177,\n    \"Que\": 31178,\n    \"Ġrag\": 31179,\n    \"Ġlov\": 31180,\n    \"630\": 31181,\n    \"Ġadept\": 31182,\n    \"orbit\": 31183,\n    \"253\": 31184,\n    \"412\": 31185,\n    \"Ġbutterflies\": 31186,\n    \"Ġoutl\": 31187,\n    \"ĠCycle\": 31188,\n    \"Ġaesthetics\": 31189,\n    \"ĠTwitch\": 31190,\n    \"405\": 31191,\n    \"factor\": 31192,\n    \"ðŁĳ\": 31193,\n    \"ĠCircus\": 31194,\n    \"Posted\": 31195,\n    \"Ġintroductory\": 31196,\n    \"ĠStack\": 31197,\n    \"atoes\": 31198,\n    \"Ġfurn\": 31199,\n    \"ĠHond\": 31200,\n    \"Ġbipolar\": 31201,\n    \"ĠAging\": 31202,\n    \"inches\": 31203,\n    \"Ġincompetence\": 31204,\n    \"Ġaloud\": 31205,\n    \"Imagine\": 31206,\n    \"Ġsepar\": 31207,\n    \"Ġmanip\": 31208,\n    \"ophobic\": 31209,\n    \"inion\": 31210,\n    \"bek\": 31211,\n    \"Ġquer\": 31212,\n    \"ĠArmen\": 31213,\n    \"Ġhumorous\": 31214,\n    \"Ġmundane\": 31215,\n    \"Ġapologizing\": 31216,\n    \"Ġpioneered\": 31217,\n    \"Ġ303\": 31218,\n    \"282\": 31219,\n    \"Ġcalming\": 31220,\n    \"orious\": 31221,\n    \"760\": 31222,\n    \"Ġstitches\": 31223,\n    \"Ġthrottle\": 31224,\n    \"Ġspinach\": 31225,\n    \"urities\": 31226,\n    \"ĠCologne\": 31227,\n    \"Ġripple\": 31228,\n    \"Cs\": 31229,\n    \"Cent\": 31230,\n    \"Should\": 31231,\n    \"Ġaffinity\": 31232,\n    \"amount\": 31233,\n    \"ĠMISS\": 31234,\n    \"Ġsage\": 31235,\n    \"Ġamusing\": 31236,\n    \"Ġsnatch\": 31237,\n    \"clair\": 31238,\n    \"ĠGuess\": 31239,\n    \"bench\": 31240,\n    \"ĠMoj\": 31241,\n    \"nuclear\": 31242,\n    \"Ġfid\": 31243,\n    \"ĠVM\": 31244,\n    \"ĠGN\": 31245,\n    \"brainer\": 31246,\n    \"Ġcurled\": 31247,\n    \"Ġbushes\": 31248,\n    \"icably\": 31249,\n    \"Ġcreeping\": 31250,\n    \"Ġveil\": 31251,\n    \"ĠALS\": 31252,\n    \"ESPN\": 31253,\n    \"ulsion\": 31254,\n    \"ĠGTX\": 31255,\n    \"ĠANN\": 31256,\n    \"Ġcomplicit\": 31257,\n    \"assault\": 31258,\n    \"IOR\": 31259,\n    \"Ġpolymer\": 31260,\n    \"Ġestimating\": 31261,\n    \"277\": 31262,\n    \"alog\": 31263,\n    \"Ġglimps\": 31264,\n    \"Ġreinforces\": 31265,\n    \"Ġtextbooks\": 31266,\n    \"Ġdictated\": 31267,\n    \"ĠReyn\": 31268,\n    \"latable\": 31269,\n    \"ĠOrth\": 31270,\n    \"520\": 31271,\n    \"Ġtrickle\": 31272,\n    \"ĠWrong\": 31273,\n    \".[\": 31274,\n    \"ĠDesigner\": 31275,\n    \"304\": 31276,\n    \"ĠInner\": 31277,\n    \"Ġrave\": 31278,\n    \"ppa\": 31279,\n    \"ĠGim\": 31280,\n    \"Ġswath\": 31281,\n    \"Ġcarts\": 31282,\n    \"atlantic\": 31283,\n    \"Ġpersists\": 31284,\n    \"ĠDeveloper\": 31285,\n    \"Ġgoodies\": 31286,\n    \"isive\": 31287,\n    \"Inf\": 31288,\n    \"ĠSaving\": 31289,\n    \"loop\": 31290,\n    \"tions\": 31291,\n    \"Ġabusers\": 31292,\n    \"Ġclot\": 31293,\n    \"Ġmesmer\": 31294,\n    \"Ġdeg\": 31295,\n    \"Ġskirts\": 31296,\n    \"257\": 31297,\n    \"Ġunreliable\": 31298,\n    \"ĠCOMM\": 31299,\n    \"Ġ194\": 31300,\n    \"Ġfledgling\": 31301,\n    \"administ\": 31302,\n    \"Israeli\": 31303,\n    \"ĠBarbie\": 31304,\n    \"ĠJeanne\": 31305,\n    \"Ġgenerously\": 31306,\n    \"ĠStruct\": 31307,\n    \"ĠZap\": 31308,\n    \"Ġvetted\": 31309,\n    \"ĠViolet\": 31310,\n    \"Ġ),\": 31311,\n    \"Ġembarrass\": 31312,\n    \"bang\": 31313,\n    \"ĠProvider\": 31314,\n    \"getting\": 31315,\n    \"alg\": 31316,\n    \"Ġunconditional\": 31317,\n    \"ĠHulk\": 31318,\n    \"ĠWad\": 31319,\n    \"utation\": 31320,\n    \"Ġpointless\": 31321,\n    \"Ġdeprivation\": 31322,\n    \"Ġstarving\": 31323,\n    \"ĠImpossible\": 31324,\n    \"ĠStir\": 31325,\n    \"Ġknack\": 31326,\n    \"anse\": 31327,\n    \"Ġsecurely\": 31328,\n    \"Ġply\": 31329,\n    \"395\": 31330,\n    \"Pack\": 31331,\n    \"liv\": 31332,\n    \"Ġridden\": 31333,\n    \"alks\": 31334,\n    \"308\": 31335,\n    \"male\": 31336,\n    \"Ġbitterly\": 31337,\n    \"Ġirrational\": 31338,\n    \"Members\": 31339,\n    \"ported\": 31340,\n    \"qq\": 31341,\n    \"ractor\": 31342,\n    \"Ġinflict\": 31343,\n    \"ĠBoehner\": 31344,\n    \"Ġthickness\": 31345,\n    \"Ġdome\": 31346,\n    \"ĠInflu\": 31347,\n    \"Ġheap\": 31348,\n    \"Ġmirrored\": 31349,\n    \"Ġconstituent\": 31350,\n    \"Ġfertile\": 31351,\n    \"Ġvaping\": 31352,\n    \"266\": 31353,\n    \"riages\": 31354,\n    \"Ġembassies\": 31355,\n    \"Ġpersu\": 31356,\n    \"ĠMacArthur\": 31357,\n    \"issions\": 31358,\n    \"Main\": 31359,\n    \"aths\": 31360,\n    \"onne\": 31361,\n    \"circ\": 31362,\n    \"Ġsweating\": 31363,\n    \"quartered\": 31364,\n    \"Ġsax\": 31365,\n    \"Ġ540\": 31366,\n    \"Ġreputable\": 31367,\n    \"Ġsatire\": 31368,\n    \"Ġpastors\": 31369,\n    \"ventional\": 31370,\n    \"Mic\": 31371,\n    \"female\": 31372,\n    \"Ġpity\": 31373,\n    \"appropri\": 31374,\n    \"voc\": 31375,\n    \"hei\": 31376,\n    \"Ġimperial\": 31377,\n    \"Ġcorrective\": 31378,\n    \"Ġresent\": 31379,\n    \"Ġtempered\": 31380,\n    \"Ġdiffers\": 31381,\n    \"Hamilton\": 31382,\n    \"Ġsaddle\": 31383,\n    \"Ġgrenades\": 31384,\n    \"ĠQuart\": 31385,\n    \"onymous\": 31386,\n    \"til\": 31387,\n    \"Ġdepiction\": 31388,\n    \"Ġdisreg\": 31389,\n    \"Ġpetitioner\": 31390,\n    \"Ġfret\": 31391,\n    \"ĠEns\": 31392,\n    \"Emer\": 31393,\n    \"540\": 31394,\n    \"opathy\": 31395,\n    \"vertisements\": 31396,\n    \"Ġsketches\": 31397,\n    \"venth\": 31398,\n    \"Ġautomate\": 31399,\n    \"Ġjihad\": 31400,\n    \"iping\": 31401,\n    \"Ġtert\": 31402,\n    \"ĠSop\": 31403,\n    \"ships\": 31404,\n    \"Ġdeceptive\": 31405,\n    \"ĠPryor\": 31406,\n    \"ĠGorge\": 31407,\n    \"ĠMeridian\": 31408,\n    \"rero\": 31409,\n    \"affected\": 31410,\n    \"Ġlame\": 31411,\n    \"660\": 31412,\n    \"rub\": 31413,\n    \"Hello\": 31414,\n    \"ĠNumbers\": 31415,\n    \"269\": 31416,\n    \"Ġmarg\": 31417,\n    \"Fran\": 31418,\n    \"640\": 31419,\n    \"Ġcath\": 31420,\n    \"winter\": 31421,\n    \"ĠMosque\": 31422,\n    \"Ġreckoning\": 31423,\n    \"ĠImaging\": 31424,\n    \"Ġmutation\": 31425,\n    \"ĠMild\": 31426,\n    \"Ġkidnap\": 31427,\n    \"Ġnav\": 31428,\n    \"Ġferocious\": 31429,\n    \"Ġdusty\": 31430,\n    \"Cele\": 31431,\n    \"ĠFoss\": 31432,\n    \"Ġregrett\": 31433,\n    \"lymp\": 31434,\n    \"Ġcoli\": 31435,\n    \"Ġstereo\": 31436,\n    \"Ġforesee\": 31437,\n    \"alties\": 31438,\n    \"Ġresusc\": 31439,\n    \"Full\": 31440,\n    \"wash\": 31441,\n    \"ĠINST\": 31442,\n    \"ĠPars\": 31443,\n    \"Ġcoated\": 31444,\n    \"ĠHT\": 31445,\n    \"Ġdiscord\": 31446,\n    \"Ġreforming\": 31447,\n    \"CAN\": 31448,\n    \"Ġblink\": 31449,\n    \"Ġlubric\": 31450,\n    \"Ġmishand\": 31451,\n    \"ensible\": 31452,\n    \"existent\": 31453,\n    \"secondary\": 31454,\n    \"ĠDoesn\": 31455,\n    \"terrorist\": 31456,\n    \"Ġriff\": 31457,\n    \"custom\": 31458,\n    \"ĠDET\": 31459,\n    \"Ġreusable\": 31460,\n    \"ĠCRA\": 31461,\n    \"ĠScalia\": 31462,\n    \"Ġaccelerator\": 31463,\n    \"Ġpropag\": 31464,\n    \"ĠMID\": 31465,\n    \"ework\": 31466,\n    \"Ġlooted\": 31467,\n    \"oscope\": 31468,\n    \"eners\": 31469,\n    \"ruction\": 31470,\n    \"Ġbarr\": 31471,\n    \"Ġviewership\": 31472,\n    \"Ġlends\": 31473,\n    \"obil\": 31474,\n    \"ĠRoots\": 31475,\n    \"ĠCame\": 31476,\n    \"ibel\": 31477,\n    \"Ġglobalization\": 31478,\n    \"lab\": 31479,\n    \"information\": 31480,\n    \"Ġcoordin\": 31481,\n    \"Ġglitch\": 31482,\n    \"Ġworms\": 31483,\n    \"Ġslurs\": 31484,\n    \"Ġcontemplated\": 31485,\n    \"ĠPenal\": 31486,\n    \"Ġ191\": 31487,\n    \"Ġ221\": 31488,\n    \"Ġexposes\": 31489,\n    \"Ġ248\": 31490,\n    \"ĠASP\": 31491,\n    \"Ġdependency\": 31492,\n    \"urga\": 31493,\n    \"pdf\": 31494,\n    \"Ġvibr\": 31495,\n    \"clone\": 31496,\n    \"ossible\": 31497,\n    \"ĠUtt\": 31498,\n    \"serv\": 31499,\n    \"ĠLevant\": 31500,\n    \"maybe\": 31501,\n    \"MU\": 31502,\n    \"ĠLunar\": 31503,\n    \"Ġbystanders\": 31504,\n    \"Ġcapitals\": 31505,\n    \"Ġpreacher\": 31506,\n    \"thin\": 31507,\n    \"Ġunderscore\": 31508,\n    \"Ġ('\": 31509,\n    \"Ġmedd\": 31510,\n    \"Ġautobiography\": 31511,\n    \"Ġpersistence\": 31512,\n    \"Ġarming\": 31513,\n    \"Ġappalled\": 31514,\n    \"Ġcontradictory\": 31515,\n    \"Ġreciproc\": 31516,\n    \"Ġtakedown\": 31517,\n    \"tan\": 31518,\n    \"Ġnecessities\": 31519,\n    \"itans\": 31520,\n    \"ĠAlas\": 31521,\n    \"Ġsegregated\": 31522,\n    \"ĠResponsibility\": 31523,\n    \"ĠSHOW\": 31524,\n    \"ISIS\": 31525,\n    \"Ġpengu\": 31526,\n    \"Ġumb\": 31527,\n    \"ĠHO\": 31528,\n    \"HB\": 31529,\n    \"ĠChou\": 31530,\n    \"Ġalluded\": 31531,\n    \"Ġharms\": 31532,\n    \"bara\": 31533,\n    \"ĠWOR\": 31534,\n    \"Sorry\": 31535,\n    \"Ġstarvation\": 31536,\n    \"Ġspilling\": 31537,\n    \"Ġcarb\": 31538,\n    \"annis\": 31539,\n    \"ĠGarrison\": 31540,\n    \"Ġmillionaire\": 31541,\n    \"ifling\": 31542,\n    \"ĠCancel\": 31543,\n    \"Ġimprint\": 31544,\n    \"Ġborrower\": 31545,\n    \"455\": 31546,\n    \"ĠCic\": 31547,\n    \"Ġexposures\": 31548,\n    \"dest\": 31549,\n    \"Ġunn\": 31550,\n    \"Ġ802\": 31551,\n    \"Ġadherence\": 31552,\n    \"prints\": 31553,\n    \"Ġweary\": 31554,\n    \"Ġwaging\": 31555,\n    \"Ġ1937\": 31556,\n    \"ĠKepler\": 31557,\n    \"%;\": 31558,\n    \"Ġdefective\": 31559,\n    \"ĠReps\": 31560,\n    \"ĠGranted\": 31561,\n    \"Ġdisco\": 31562,\n    \"ĠRanking\": 31563,\n    \"erno\": 31564,\n    \"Ġarchaeological\": 31565,\n    \"sq\": 31566,\n    \"Ġcapit\": 31567,\n    \"Ġfleets\": 31568,\n    \"Ġinventor\": 31569,\n    \"iffin\": 31570,\n    \"Ġspotting\": 31571,\n    \"ĠSHARES\": 31572,\n    \"309\": 31573,\n    \"Hard\": 31574,\n    \"save\": 31575,\n    \"241\": 31576,\n    \"ĠThinking\": 31577,\n    \"XY\": 31578,\n    \"Ġhavens\": 31579,\n    \"Ġmessed\": 31580,\n    \"crop\": 31581,\n    \"Ġperme\": 31582,\n    \"Ġtimelines\": 31583,\n    \"ĠGarage\": 31584,\n    \"Ġplateau\": 31585,\n    \"together\": 31586,\n    \"fox\": 31587,\n    \"Ġfailings\": 31588,\n    \"ĠTight\": 31589,\n    \"ĠPhysics\": 31590,\n    \"ĠScholars\": 31591,\n    \"Ġpans\": 31592,\n    \"Fall\": 31593,\n    \"Ġhull\": 31594,\n    \"GER\": 31595,\n    \"Ġbourbon\": 31596,\n    \"ceived\": 31597,\n    \"Ġsteroids\": 31598,\n    \"Ġhamb\": 31599,\n    \"Ġinterpretations\": 31600,\n    \"Ġcush\": 31601,\n    \"Chair\": 31602,\n    \"Ġinformational\": 31603,\n    \"aryn\": 31604,\n    \"Ġwoven\": 31605,\n    \"Ġamen\": 31606,\n    \"Bre\": 31607,\n    \"Ġrefreshed\": 31608,\n    \"York\": 31609,\n    \"ĠBlast\": 31610,\n    \"Editor\": 31611,\n    \"Ġmotivating\": 31612,\n    \"ĠReason\": 31613,\n    \"Florida\": 31614,\n    \"Ġdreaded\": 31615,\n    \"Ġstationary\": 31616,\n    \"Ġbil\": 31617,\n    \"doors\": 31618,\n    \"Ġslightest\": 31619,\n    \"Ġcombustion\": 31620,\n    \"Ġfascination\": 31621,\n    \"Ġstraps\": 31622,\n    \"scribed\": 31623,\n    \"Ġexhibiting\": 31624,\n    \"Ġsimplest\": 31625,\n    \"Gar\": 31626,\n    \"Ġprogressives\": 31627,\n    \"claim\": 31628,\n    \"ocket\": 31629,\n    \"Ġexoner\": 31630,\n    \"ĠNETWORK\": 31631,\n    \"Brad\": 31632,\n    \"Ġ197\": 31633,\n    \"Ġnightmares\": 31634,\n    \"Ġillust\": 31635,\n    \"among\": 31636,\n    \"ĠGreenpeace\": 31637,\n    \"Ġoval\": 31638,\n    \"Ġblocker\": 31639,\n    \"3000\": 31640,\n    \"ĠMemor\": 31641,\n    \"Ġmids\": 31642,\n    \"Ġconfuse\": 31643,\n    \"YN\": 31644,\n    \"cow\": 31645,\n    \"Ġdispensary\": 31646,\n    \"telling\": 31647,\n    \"Ġentail\": 31648,\n    \"Ġneurolog\": 31649,\n    \"Ġbroth\": 31650,\n    \"Ġpron\": 31651,\n    \"ĠAnswer\": 31652,\n    \"thank\": 31653,\n    \"Ġintersect\": 31654,\n    \"Ġclinging\": 31655,\n    \"ĠKilling\": 31656,\n    \"Ġcohesion\": 31657,\n    \"Ġcategorized\": 31658,\n    \"Ġtangled\": 31659,\n    \"ĠASC\": 31660,\n    \"Arsenal\": 31661,\n    \"ĠAutomatic\": 31662,\n    \"580\": 31663,\n    \"sac\": 31664,\n    \"Ġshady\": 31665,\n    \"consumer\": 31666,\n    \"hetically\": 31667,\n    \"NV\": 31668,\n    \"Ġoverl\": 31669,\n    \"holes\": 31670,\n    \"ĠDonation\": 31671,\n    \"tera\": 31672,\n    \"score\": 31673,\n    \"library\": 31674,\n    \"Ġsmoother\": 31675,\n    \"Ġcoasts\": 31676,\n    \"Ġintercourse\": 31677,\n    \"Ġunfavorable\": 31678,\n    \"erb\": 31679,\n    \"Hel\": 31680,\n    \"Ġbiases\": 31681,\n    \"Ġinheritance\": 31682,\n    \"Ġsuppressed\": 31683,\n    \"ĠRecommend\": 31684,\n    \"iculture\": 31685,\n    \"ighting\": 31686,\n    \"inguished\": 31687,\n    \"idences\": 31688,\n    \"operated\": 31689,\n    \"Ġhors\": 31690,\n    \"Ġshrug\": 31691,\n    \"aila\": 31692,\n    \"ĠConsortium\": 31693,\n    \"Ġveins\": 31694,\n    \"uria\": 31695,\n    \"ĠSmithsonian\": 31696,\n    \"ĠAX\": 31697,\n    \")âĢĶ\": 31698,\n    \"given\": 31699,\n    \"JC\": 31700,\n    \"Ġreneg\": 31701,\n    \"Ġprincip\": 31702,\n    \"Ġextinct\": 31703,\n    \"Golden\": 31704,\n    \"ASON\": 31705,\n    \"Ġstatutes\": 31706,\n    \"292\": 31707,\n    \"ĠGOOD\": 31708,\n    \"ĠGreenland\": 31709,\n    \"ĠRasmussen\": 31710,\n    \"ATHER\": 31711,\n    \"Ġdeserted\": 31712,\n    \"ĠHitchcock\": 31713,\n    \"Ġqualifies\": 31714,\n    \"Ġdreadful\": 31715,\n    \"Ġsupers\": 31716,\n    \"Ġtendon\": 31717,\n    \"oter\": 31718,\n    \"ĠFate\": 31719,\n    \"Ġrestrooms\": 31720,\n    \"igating\": 31721,\n    \"Sher\": 31722,\n    \"Name\": 31723,\n    \"orph\": 31724,\n    \"ĠCritical\": 31725,\n    \"rox\": 31726,\n    \"Ġdefunct\": 31727,\n    \"Ġcanoe\": 31728,\n    \"Ġbiscuits\": 31729,\n    \"Ġwomb\": 31730,\n    \"808\": 31731,\n    \"istar\": 31732,\n    \"Ġroar\": 31733,\n    \"aundering\": 31734,\n    \"iewicz\": 31735,\n    \"ĠNM\": 31736,\n    \"ĠChamberlain\": 31737,\n    \"Ġ233\": 31738,\n    \"ĠCoat\": 31739,\n    \"Ġ999\": 31740,\n    \"aft\": 31741,\n    \"Ġlurking\": 31742,\n    \"ĠPist\": 31743,\n    \"Ġfollower\": 31744,\n    \"Ġcareg\": 31745,\n    \"ÙĨ\": 31746,\n    \"ĠThin\": 31747,\n    \"ZZ\": 31748,\n    \"ĠGI\": 31749,\n    \"ĠVintage\": 31750,\n    \"Ġpainstaking\": 31751,\n    \"Ġgloom\": 31752,\n    \"Ġtbsp\": 31753,\n    \"Ġwhim\": 31754,\n    \"ĠMask\": 31755,\n    \"rugged\": 31756,\n    \"Ġwritings\": 31757,\n    \"stantial\": 31758,\n    \"luence\": 31759,\n    \"ordable\": 31760,\n    \"akia\": 31761,\n    \"Ġassassinated\": 31762,\n    \"Wind\": 31763,\n    \"Ġdemeanor\": 31764,\n    \"Night\": 31765,\n    \"rape\": 31766,\n    \"ĠBringing\": 31767,\n    \"Ġshields\": 31768,\n    \"ĠAntarctic\": 31769,\n    \"Ġfruitful\": 31770,\n    \"ĠBuster\": 31771,\n    \"ĠLois\": 31772,\n    \"Ġ302\": 31773,\n    \"Style\": 31774,\n    \"ĠRIS\": 31775,\n    \"Ġdissatisfaction\": 31776,\n    \"ulp\": 31777,\n    \"ĠLaser\": 31778,\n    \"Ġdisposition\": 31779,\n    \"ĠAnk\": 31780,\n    \"Ġabsorbing\": 31781,\n    \"276\": 31782,\n    \"Ġvolcan\": 31783,\n    \"Ġleftover\": 31784,\n    \"yah\": 31785,\n    \"ĠVaj\": 31786,\n    \"Ġunsolved\": 31787,\n    \"oland\": 31788,\n    \"Ġstained\": 31789,\n    \"Ġpathetic\": 31790,\n    \"ylan\": 31791,\n    \"Ġknots\": 31792,\n    \"immigration\": 31793,\n    \"ieving\": 31794,\n    \"Coming\": 31795,\n    \"Commerce\": 31796,\n    \"ĠHurt\": 31797,\n    \"drawn\": 31798,\n    \"Ġaxis\": 31799,\n    \"Ġdye\": 31800,\n    \"ĠNora\": 31801,\n    \"ĠPortal\": 31802,\n    \"Ġsuspense\": 31803,\n    \"ĠExactly\": 31804,\n    \"Ġpowering\": 31805,\n    \"ĠClock\": 31806,\n    \"Ġdrawer\": 31807,\n    \"ĠSpike\": 31808,\n    \"Ġhallmark\": 31809,\n    \"aber\": 31810,\n    \"ĠTrainer\": 31811,\n    \"UV\": 31812,\n    \"Ġredundant\": 31813,\n    \"Tour\": 31814,\n    \"Ġdesignate\": 31815,\n    \"Ġredress\": 31816,\n    \"ĠUb\": 31817,\n    \"cake\": 31818,\n    \"oded\": 31819,\n    \"Ġkings\": 31820,\n    \"iates\": 31821,\n    \"Ġcoupons\": 31822,\n    \"Ġextremes\": 31823,\n    \"Elect\": 31824,\n    \"Ġcitation\": 31825,\n    \"Ġdirectory\": 31826,\n    \"Ġtranspired\": 31827,\n    \"cele\": 31828,\n    \"gence\": 31829,\n    \"5000\": 31830,\n    \"ostic\": 31831,\n    \"Ġraining\": 31832,\n    \"ĠSight\": 31833,\n    \"videos\": 31834,\n    \"phthal\": 31835,\n    \"llor\": 31836,\n    \"Ġappraisal\": 31837,\n    \"Ġdetox\": 31838,\n    \"Ġelecting\": 31839,\n    \"Ġordinances\": 31840,\n    \"Ġlifespan\": 31841,\n    \"Ref\": 31842,\n    \"Ġilluminated\": 31843,\n    \"Ġforfe\": 31844,\n    \"Making\": 31845,\n    \"ĠWorst\": 31846,\n    \"ĠTP\": 31847,\n    \"Ġfullest\": 31848,\n    \"ĠISIL\": 31849,\n    \"ĠRates\": 31850,\n    \"Ġyeast\": 31851,\n    \"sett\": 31852,\n    \"ĠYok\": 31853,\n    \"innie\": 31854,\n    \"edition\": 31855,\n    \"ĠGoldstein\": 31856,\n    \"Ġunaff\": 31857,\n    \"god\": 31858,\n    \"Ġzo\": 31859,\n    \"rums\": 31860,\n    \"Ġopaque\": 31861,\n    \"ĠHist\": 31862,\n    \"Yesterday\": 31863,\n    \"AMS\": 31864,\n    \"aband\": 31865,\n    \"005\": 31866,\n    \"illary\": 31867,\n    \"ĠSplash\": 31868,\n    \"Ġaccrued\": 31869,\n    \"Ell\": 31870,\n    \"Ġnominating\": 31871,\n    \"ĠBroadcast\": 31872,\n    \"ĠWhip\": 31873,\n    \"ARM\": 31874,\n    \"Ġunnecessarily\": 31875,\n    \"brown\": 31876,\n    \"429\": 31877,\n    \"ansky\": 31878,\n    \"Ġextravagant\": 31879,\n    \"Malley\": 31880,\n    \"wage\": 31881,\n    \"Ġexempted\": 31882,\n    \"Ġtypo\": 31883,\n    \"Ġesports\": 31884,\n    \"ĠStru\": 31885,\n    \"ĠPython\": 31886,\n    \"Ġsaint\": 31887,\n    \"ĠCSI\": 31888,\n    \"ĠPowder\": 31889,\n    \"Ġdisguised\": 31890,\n    \"ĠSubway\": 31891,\n    \"Ġprecursor\": 31892,\n    \"ĠWizard\": 31893,\n    \"Johnson\": 31894,\n    \"icas\": 31895,\n    \"Ġdefaults\": 31896,\n    \"!).\": 31897,\n    \"ebra\": 31898,\n    \"jected\": 31899,\n    \"Ġunaccompanied\": 31900,\n    \"HH\": 31901,\n    \"Ġproced\": 31902,\n    \"clinical\": 31903,\n    \"Ġmitigating\": 31904,\n    \"ĠSoup\": 31905,\n    \"ĠFunny\": 31906,\n    \"344\": 31907,\n    \"Hall\": 31908,\n    \"Ġscalable\": 31909,\n    \"Ġshimmer\": 31910,\n    \"Ġunderstatement\": 31911,\n    \"zeb\": 31912,\n    \"icus\": 31913,\n    \"Ġretract\": 31914,\n    \"IDER\": 31915,\n    \"ieft\": 31916,\n    \"iii\": 31917,\n    \"ĠEmperor\": 31918,\n    \"Ġvoltage\": 31919,\n    \"343\": 31920,\n    \"Rest\": 31921,\n    \"ĠButcher\": 31922,\n    \"Ġlaced\": 31923,\n    \"Ġsalty\": 31924,\n    \"Ġfourteen\": 31925,\n    \"Ġoxy\": 31926,\n    \"Ġraged\": 31927,\n    \"Ġforg\": 31928,\n    \"Ġcaveat\": 31929,\n    \"Ġponder\": 31930,\n    \"process\": 31931,\n    \"Ġghosts\": 31932,\n    \"ĠGoose\": 31933,\n    \"didn\": 31934,\n    \"stood\": 31935,\n    \"amation\": 31936,\n    \"Ġvillains\": 31937,\n    \"contract\": 31938,\n    \"Ġbooted\": 31939,\n    \"ĠDidn\": 31940,\n    \"ĠSalon\": 31941,\n    \"Ġlewd\": 31942,\n    \"ĠFritz\": 31943,\n    \"Ġorganis\": 31944,\n    \"Ġpuzzles\": 31945,\n    \"ĠRX\": 31946,\n    \"Ġcurtains\": 31947,\n    \"ĠPackage\": 31948,\n    \"Ġrebate\": 31949,\n    \"Ġspokes\": 31950,\n    \"Ġoccupant\": 31951,\n    \"Ġfooled\": 31952,\n    \"appy\": 31953,\n    \"Ġyourselves\": 31954,\n    \"Ġmaths\": 31955,\n    \"Ġ630\": 31956,\n    \"bos\": 31957,\n    \"ĠHeb\": 31958,\n    \"APS\": 31959,\n    \"Ġbulletin\": 31960,\n    \"Ġpests\": 31961,\n    \"Ġlum\": 31962,\n    \"ĠHAS\": 31963,\n    \"users\": 31964,\n    \"idated\": 31965,\n    \"Ġpalpable\": 31966,\n    \"ĠFeature\": 31967,\n    \"ĠPKK\": 31968,\n    \"Ġdetriment\": 31969,\n    \"Ġbamboo\": 31970,\n    \"Ġimmersed\": 31971,\n    \"ĠDud\": 31972,\n    \"Ġion\": 31973,\n    \"icc\": 31974,\n    \"ĠIris\": 31975,\n    \"ĠBeats\": 31976,\n    \"Ġimprobable\": 31977,\n    \"Ġfuner\": 31978,\n    \"Ġsprung\": 31979,\n    \"ĠLieberman\": 31980,\n    \"ĠSTA\": 31981,\n    \"venge\": 31982,\n    \"Ġtreacherous\": 31983,\n    \"Ġpreced\": 31984,\n    \"Ġsniper\": 31985,\n    \"ĠGOLD\": 31986,\n    \"ĠSUR\": 31987,\n    \"Nic\": 31988,\n    \"ĠROB\": 31989,\n    \"Camp\": 31990,\n    \"Ġhooks\": 31991,\n    \"oling\": 31992,\n    \"Ġbolst\": 31993,\n    \"339\": 31994,\n    \"heter\": 31995,\n    \"Ġbracelet\": 31996,\n    \"Ġbreat\": 31997,\n    \"307\": 31998,\n    \"ĠTrader\": 31999,\n    \"ĠPixar\": 32000,\n    \"hist\": 32001,\n    \"Ġmenacing\": 32002,\n    \"Ġgrizz\": 32003,\n    \"294\": 32004,\n    \"Ġillustrious\": 32005,\n    \"Ġtransact\": 32006,\n    \"Ġspoiler\": 32007,\n    \"ĠWORK\": 32008,\n    \"Road\": 32009,\n    \"Ġblackout\": 32010,\n    \"Ġencomp\": 32011,\n    \"proven\": 32012,\n    \"ĠFriendship\": 32013,\n    \"Ġentrances\": 32014,\n    \"Ġprofessions\": 32015,\n    \"Ġinsin\": 32016,\n    \"Ġrecorder\": 32017,\n    \"Ġformulation\": 32018,\n    \"govern\": 32019,\n    \"Ġpainfully\": 32020,\n    \"ĠRepe\": 32021,\n    \"eeds\": 32022,\n    \"cru\": 32023,\n    \"ĠDir\": 32024,\n    \"Ġtriumphant\": 32025,\n    \"Ġignition\": 32026,\n    \"xy\": 32027,\n    \"Ġintrusion\": 32028,\n    \"ĠEAR\": 32029,\n    \"RES\": 32030,\n    \"Ġration\": 32031,\n    \"ĠTaken\": 32032,\n    \"Ġcages\": 32033,\n    \"Ġpeg\": 32034,\n    \"Ġcommem\": 32035,\n    \"680\": 32036,\n    \"ĠRite\": 32037,\n    \"Ġfolder\": 32038,\n    \"Ġvertically\": 32039,\n    \"Ġcheeks\": 32040,\n    \"pick\": 32041,\n    \"Ġcrispy\": 32042,\n    \"Ġsqueezing\": 32043,\n    \"ĠBene\": 32044,\n    \"ĠTrailer\": 32045,\n    \"ĠKM\": 32046,\n    \"acceptable\": 32047,\n    \"ĠSetting\": 32048,\n    \"Ġsupernatural\": 32049,\n    \"ĠEz\": 32050,\n    \"Ġvenom\": 32051,\n    \"ĠFrey\": 32052,\n    \"Ġpulp\": 32053,\n    \"Had\": 32054,\n    \"centered\": 32055,\n    \"metics\": 32056,\n    \"Kent\": 32057,\n    \"ĠDOI\": 32058,\n    \"kr\": 32059,\n    \"ĠWHEN\": 32060,\n    \"Ġtakeoff\": 32061,\n    \"isf\": 32062,\n    \"uko\": 32063,\n    \"Ġquasi\": 32064,\n    \"Ġveggies\": 32065,\n    \"Ġpesticide\": 32066,\n    \"Ġstimulating\": 32067,\n    \"Ġacknowledgement\": 32068,\n    \"Ġattained\": 32069,\n    \"ĠBackground\": 32070,\n    \"281\": 32071,\n    \"317\": 32072,\n    \"ĠTrees\": 32073,\n    \"Ġdetractors\": 32074,\n    \"Ġannouncer\": 32075,\n    \"Ġjoyful\": 32076,\n    \"ĠElf\": 32077,\n    \"istration\": 32078,\n    \"phi\": 32079,\n    \"Ġprogressively\": 32080,\n    \"mini\": 32081,\n    \"Ġcontraception\": 32082,\n    \"asca\": 32083,\n    \"ishops\": 32084,\n    \"Ġmisunderstood\": 32085,\n    \"Ġinitiating\": 32086,\n    \"ĠConversely\": 32087,\n    \"338\": 32088,\n    \"080\": 32089,\n    \"idation\": 32090,\n    \"ĠGoes\": 32091,\n    \"Ġimprov\": 32092,\n    \"Ġswapping\": 32093,\n    \"Vict\": 32094,\n    \"Ġdevoid\": 32095,\n    \"fighter\": 32096,\n    \"ĠMori\": 32097,\n    \"Ġvoy\": 32098,\n    \"ĠElev\": 32099,\n    \"ĠAim\": 32100,\n    \"Ġtrustworthy\": 32101,\n    \"Leg\": 32102,\n    \"675\": 32103,\n    \"ĠPossible\": 32104,\n    \"Crunch\": 32105,\n    \"ĠRings\": 32106,\n    \"Ġphony\": 32107,\n    \"Ġbladder\": 32108,\n    \"ĠChall\": 32109,\n    \"Spot\": 32110,\n    \"oak\": 32111,\n    \"Was\": 32112,\n    \"ĠFAM\": 32113,\n    \"ĠAGA\": 32114,\n    \"ĠFifa\": 32115,\n    \"Ġenclosed\": 32116,\n    \"Ġanthrop\": 32117,\n    \"faith\": 32118,\n    \"ĠAux\": 32119,\n    \"Ġgracious\": 32120,\n    \"roller\": 32121,\n    \"Ġdowntime\": 32122,\n    \"swing\": 32123,\n    \"Ġcamouflage\": 32124,\n    \"ĠCosts\": 32125,\n    \"Ġliv\": 32126,\n    \"ricular\": 32127,\n    \"ĠUran\": 32128,\n    \"Ġdisapproval\": 32129,\n    \"Ġpropriet\": 32130,\n    \"bits\": 32131,\n    \"Ġmafia\": 32132,\n    \"ĠSCHOOL\": 32133,\n    \"ĠPrepar\": 32134,\n    \"button\": 32135,\n    \"Almost\": 32136,\n    \"Ġpastoral\": 32137,\n    \"ĠDove\": 32138,\n    \"Hol\": 32139,\n    \"Ġimposes\": 32140,\n    \"ĠDram\": 32141,\n    \"lys\": 32142,\n    \"ĠSAS\": 32143,\n    \"Ġwiring\": 32144,\n    \"271\": 32145,\n    \"ĠModels\": 32146,\n    \"Ġoutpost\": 32147,\n    \"etics\": 32148,\n    \"Ġinsulted\": 32149,\n    \"ĠMongolia\": 32150,\n    \"Ġoverth\": 32151,\n    \"Haw\": 32152,\n    \"ĠHomer\": 32153,\n    \"itta\": 32154,\n    \"raining\": 32155,\n    \"Ġevidently\": 32156,\n    \"raphic\": 32157,\n    \"impact\": 32158,\n    \"Ġfranch\": 32159,\n    \"Ġ2100\": 32160,\n    \"Ġapproximate\": 32161,\n    \"Ġcartoons\": 32162,\n    \"Ġbackups\": 32163,\n    \"umbing\": 32164,\n    \"Ġforceful\": 32165,\n    \"ĠShad\": 32166,\n    \"Ġsurges\": 32167,\n    \"Ġperf\": 32168,\n    \"Ġdele\": 32169,\n    \"Ġquieter\": 32170,\n    \"ĠHorowitz\": 32171,\n    \"ĠDX\": 32172,\n    \"anners\": 32173,\n    \"ĠNinja\": 32174,\n    \"ĠScript\": 32175,\n    \"ĠElise\": 32176,\n    \"collect\": 32177,\n    \"Ġgrading\": 32178,\n    \"ĠBethesda\": 32179,\n    \"Kids\": 32180,\n    \"ĠTelephone\": 32181,\n    \"Ġpreferring\": 32182,\n    \"Ġreconcil\": 32183,\n    \"Ġmango\": 32184,\n    \"ĠHail\": 32185,\n    \"ĠCitizenship\": 32186,\n    \"Master\": 32187,\n    \"cular\": 32188,\n    \"Ġstuffing\": 32189,\n    \"ĠAlive\": 32190,\n    \"ALLY\": 32191,\n    \"Ġchi\": 32192,\n    \"ĠDynam\": 32193,\n    \"ĠRosenthal\": 32194,\n    \"Ġpurity\": 32195,\n    \"Ġtemp\": 32196,\n    \"ĠHAL\": 32197,\n    \"employ\": 32198,\n    \"Ġplentiful\": 32199,\n    \"ĠComed\": 32200,\n    \"Ġstacks\": 32201,\n    \"ĠHuge\": 32202,\n    \"ĠOlder\": 32203,\n    \"Ġsclerosis\": 32204,\n    \"ONY\": 32205,\n    \"Ġfilmmaking\": 32206,\n    \"chance\": 32207,\n    \"Cry\": 32208,\n    \"Ġworkflow\": 32209,\n    \"ĠPersonnel\": 32210,\n    \"awed\": 32211,\n    \"ĠColumn\": 32212,\n    \"Ġuncomp\": 32213,\n    \"Ġdiscriminated\": 32214,\n    \"Ġpts\": 32215,\n    \"Ġallev\": 32216,\n    \"ĠKinn\": 32217,\n    \"meal\": 32218,\n    \"Ġnovice\": 32219,\n    \"Ġcrest\": 32220,\n    \"Ġhearty\": 32221,\n    \"Ġlowers\": 32222,\n    \"inqu\": 32223,\n    \"ĠPlayoffs\": 32224,\n    \"ĠHyp\": 32225,\n    \"Ġautos\": 32226,\n    \"Ġindec\": 32227,\n    \"Ġnighttime\": 32228,\n    \"Ġreflex\": 32229,\n    \"306\": 32230,\n    \"disciplinary\": 32231,\n    \"ophe\": 32232,\n    \"contact\": 32233,\n    \"Ġachievable\": 32234,\n    \"Ġslab\": 32235,\n    \"ĠMessage\": 32236,\n    \"ĠVMware\": 32237,\n    \"ĠDia\": 32238,\n    \"REG\": 32239,\n    \"Ġconfisc\": 32240,\n    \"ĠMechan\": 32241,\n    \"Ġphenomena\": 32242,\n    \"Ġsequencing\": 32243,\n    \"Ġshaming\": 32244,\n    \"Ġcompilation\": 32245,\n    \"ĠAges\": 32246,\n    \"Ġmastered\": 32247,\n    \"Ġagony\": 32248,\n    \"Ġrestrain\": 32249,\n    \"ĠLyme\": 32250,\n    \"Which\": 32251,\n    \"ĠBarney\": 32252,\n    \"ĠConcept\": 32253,\n    \"Ġsuperheroes\": 32254,\n    \"ĠPsychology\": 32255,\n    \"Ġreminis\": 32256,\n    \"violence\": 32257,\n    \"Lead\": 32258,\n    \"Da\": 32259,\n    \"VEN\": 32260,\n    \"ERC\": 32261,\n    \"ĠVoter\": 32262,\n    \"Ġbetray\": 32263,\n    \"Ġsavage\": 32264,\n    \"driver\": 32265,\n    \"IFT\": 32266,\n    \"Chain\": 32267,\n    \"angler\": 32268,\n    \"'-\": 32269,\n    \"lain\": 32270,\n    \"ĠRatt\": 32271,\n    \"bis\": 32272,\n    \"iverse\": 32273,\n    \"Ġdensely\": 32274,\n    \"Ġuncom\": 32275,\n    \"Ġunsuspecting\": 32276,\n    \"Ġstimulation\": 32277,\n    \"diff\": 32278,\n    \"Ġskins\": 32279,\n    \"ĠRiding\": 32280,\n    \"ategic\": 32281,\n    \"ĠUnderstand\": 32282,\n    \"occup\": 32283,\n    \"ĠCooking\": 32284,\n    \"Ġschizophrenia\": 32285,\n    \"ĠKoen\": 32286,\n    \"Ġcomrades\": 32287,\n    \"HY\": 32288,\n    \"Ġfab\": 32289,\n    \"ĠRowling\": 32290,\n    \"Allen\": 32291,\n    \"ĠJUL\": 32292,\n    \"Ġembryos\": 32293,\n    \"UU\": 32294,\n    \"ĠCAT\": 32295,\n    \"Ġtidy\": 32296,\n    \"finger\": 32297,\n    \"ĠCake\": 32298,\n    \"Ġrightfully\": 32299,\n    \"religious\": 32300,\n    \"Ġ407\": 32301,\n    \"Gal\": 32302,\n    \"408\": 32303,\n    \"Ġgrievance\": 32304,\n    \"Ġswallowed\": 32305,\n    \"251\": 32306,\n    \"283\": 32307,\n    \"ĠBarcl\": 32308,\n    \"opter\": 32309,\n    \"Ġpedoph\": 32310,\n    \"Ġcured\": 32311,\n    \"Ġestablishes\": 32312,\n    \"increasing\": 32313,\n    \"tics\": 32314,\n    \"articles\": 32315,\n    \"Ġunethical\": 32316,\n    \"authored\": 32317,\n    \"Ġanchors\": 32318,\n    \"ĠContra\": 32319,\n    \"Ġventured\": 32320,\n    \"ĠCoh\": 32321,\n    \"Ġpuff\": 32322,\n    \"heddar\": 32323,\n    \"Ġomission\": 32324,\n    \"Ġdich\": 32325,\n    \"ceed\": 32326,\n    \"Ġscares\": 32327,\n    \"Ġdoctoral\": 32328,\n    \"293\": 32329,\n    \"ĠUnt\": 32330,\n    \"Ġdop\": 32331,\n    \"ĠInjury\": 32332,\n    \"ificantly\": 32333,\n    \"ĠRift\": 32334,\n    \"ĠOrders\": 32335,\n    \"Ġmobilize\": 32336,\n    \"particularly\": 32337,\n    \"Ġchilled\": 32338,\n    \"Reports\": 32339,\n    \"redibly\": 32340,\n    \"ĠGuru\": 32341,\n    \"Ġvalleys\": 32342,\n    \"Ġtextures\": 32343,\n    \"Ġreuse\": 32344,\n    \"roit\": 32345,\n    \"unts\": 32346,\n    \"Ġirreversible\": 32347,\n    \"Ġwarships\": 32348,\n    \"Ġpus\": 32349,\n    \"Ġpeeled\": 32350,\n    \"Ġthirst\": 32351,\n    \"Ġgrapple\": 32352,\n    \"busters\": 32353,\n    \"Ġnort\": 32354,\n    \"ĠDates\": 32355,\n    \"Safe\": 32356,\n    \"Ġbirthplace\": 32357,\n    \"hemoth\": 32358,\n    \"Ġvile\": 32359,\n    \"Ġ306\": 32360,\n    \"Ram\": 32361,\n    \"activated\": 32362,\n    \"ĠAero\": 32363,\n    \"Ġbutcher\": 32364,\n    \"ĠKnock\": 32365,\n    \"Ġdisturb\": 32366,\n    \"Ġtotality\": 32367,\n    \"tted\": 32368,\n    \"Ġlegit\": 32369,\n    \"cking\": 32370,\n    \"nikov\": 32371,\n    \"Ġfavoring\": 32372,\n    \"lang\": 32373,\n    \"Ġrightful\": 32374,\n    \"orum\": 32375,\n    \"!!!!\": 32376,\n    \"ĠMinute\": 32377,\n    \"Ġpostings\": 32378,\n    \"Java\": 32379,\n    \"510\": 32380,\n    \"Ġmicrobes\": 32381,\n    \"Ġsixteen\": 32382,\n    \"entimes\": 32383,\n    \"Ġbulb\": 32384,\n    \"Ġgoalt\": 32385,\n    \"Ġhumiliated\": 32386,\n    \"ansom\": 32387,\n    \"roach\": 32388,\n    \"Ġgrouping\": 32389,\n    \"hari\": 32390,\n    \"Ġcler\": 32391,\n    \"Ġstared\": 32392,\n    \"ĠSymptoms\": 32393,\n    \"Ġbasil\": 32394,\n    \"Whenever\": 32395,\n    \"ĠWhoever\": 32396,\n    \"Oil\": 32397,\n    \"ĠJericho\": 32398,\n    \"ĠAlm\": 32399,\n    \"Pol\": 32400,\n    \"Hur\": 32401,\n    \"Ġupro\": 32402,\n    \"ĠSpo\": 32403,\n    \"hammer\": 32404,\n    \"Mur\": 32405,\n    \"ĠTorch\": 32406,\n    \"Ġfrequencies\": 32407,\n    \"ĠExpansion\": 32408,\n    \"Ġparalysis\": 32409,\n    \"igon\": 32410,\n    \"ĠSail\": 32411,\n    \"Ġsilently\": 32412,\n    \"Ġrevolver\": 32413,\n    \"Ġstockpile\": 32414,\n    \"Ġpessimistic\": 32415,\n    \"ESA\": 32416,\n    \"Ġdisclaim\": 32417,\n    \"Ġdemocracies\": 32418,\n    \"ĠTales\": 32419,\n    \"ĠAngry\": 32420,\n    \"ĠWhitman\": 32421,\n    \"ĠOri\": 32422,\n    \"Ġtransitioned\": 32423,\n    \"behind\": 32424,\n    \"ĠLAN\": 32425,\n    \"Ġcav\": 32426,\n    \"ĠJazeera\": 32427,\n    \"KC\": 32428,\n    \"ĠInspect\": 32429,\n    \"irty\": 32430,\n    \"ĠAin\": 32431,\n    \"ĠOrig\": 32432,\n    \"Ġobscene\": 32433,\n    \"Ġdormant\": 32434,\n    \"Ġharb\": 32435,\n    \"ĠWiz\": 32436,\n    \"ĠAdolf\": 32437,\n    \"Ġvic\": 32438,\n    \"Ġdenouncing\": 32439,\n    \"Ġye\": 32440,\n    \"aques\": 32441,\n    \"Ġomn\": 32442,\n    \"Ġassemblies\": 32443,\n    \"nosis\": 32444,\n    \"Ġadmon\": 32445,\n    \"Ġanguish\": 32446,\n    \"Ġvag\": 32447,\n    \"YE\": 32448,\n    \"ĠMacro\": 32449,\n    \"Ġrubbing\": 32450,\n    \"Ġreplicated\": 32451,\n    \"Moon\": 32452,\n    \"ĠGuitar\": 32453,\n    \"Ġcentimeters\": 32454,\n    \"amily\": 32455,\n    \"ĠAmes\": 32456,\n    \"Ġchlorine\": 32457,\n    \"Perhaps\": 32458,\n    \"Ġpartisans\": 32459,\n    \"soc\": 32460,\n    \"Ġvagina\": 32461,\n    \"Ġtrove\": 32462,\n    \"ĠYES\": 32463,\n    \"Ġtherapists\": 32464,\n    \"Ġnods\": 32465,\n    \"Ġhanged\": 32466,\n    \"Ġridge\": 32467,\n    \"Ġhaz\": 32468,\n    \"ĠmacOS\": 32469,\n    \"Ġske\": 32470,\n    \"ĠShia\": 32471,\n    \"Ġsteril\": 32472,\n    \"Ġalmond\": 32473,\n    \"ĠRockefeller\": 32474,\n    \"Ġintrinsic\": 32475,\n    \"Certainly\": 32476,\n    \"Ġsublime\": 32477,\n    \"Earn\": 32478,\n    \"abet\": 32479,\n    \"Ġframeworks\": 32480,\n    \"ogical\": 32481,\n    \"ilst\": 32482,\n    \"ipal\": 32483,\n    \"Ġrescuing\": 32484,\n    \"ĠWatergate\": 32485,\n    \"Ġ231\": 32486,\n    \"ĠNano\": 32487,\n    \"ighthouse\": 32488,\n    \"olph\": 32489,\n    \"Ġ312\": 32490,\n    \"Ġhealed\": 32491,\n    \"ĠTomb\": 32492,\n    \"Ġsubst\": 32493,\n    \"Ġsulph\": 32494,\n    \"ĠNewsp\": 32495,\n    \"ĠLama\": 32496,\n    \"venue\": 32497,\n    \"387\": 32498,\n    \"productive\": 32499,\n    \"ĠNEED\": 32500,\n    \"minus\": 32501,\n    \"ĠPages\": 32502,\n    \"cand\": 32503,\n    \"ĠClover\": 32504,\n    \"ĠForensic\": 32505,\n    \"ryn\": 32506,\n    \"ogle\": 32507,\n    \"ocr\": 32508,\n    \"Ġvaccinations\": 32509,\n    \"cies\": 32510,\n    \"ĠMek\": 32511,\n    \"Ġunaffected\": 32512,\n    \"Ġfetal\": 32513,\n    \"ĠDino\": 32514,\n    \"Ġhemisphere\": 32515,\n    \"Ġfroze\": 32516,\n    \"ĠPeg\": 32517,\n    \"Ġmicroscope\": 32518,\n    \"Ġmoderates\": 32519,\n    \"ĠGEN\": 32520,\n    \"ĠHawai\": 32521,\n    \"Ġstagn\": 32522,\n    \"Absolutely\": 32523,\n    \"practice\": 32524,\n    \"IBLE\": 32525,\n    \"cture\": 32526,\n    \"ĠAshe\": 32527,\n    \"Ġcondoms\": 32528,\n    \"Ġpoked\": 32529,\n    \"training\": 32530,\n    \"Ġintermedi\": 32531,\n    \"347\": 32532,\n    \"Ġcardinal\": 32533,\n    \"ĠSpoon\": 32534,\n    \"Ġsupp\": 32535,\n    \"Ġpreviews\": 32536,\n    \"Service\": 32537,\n    \"ĠBeam\": 32538,\n    \"Ġtranscend\": 32539,\n    \"Fresh\": 32540,\n    \"Sure\": 32541,\n    \"Ġ4000\": 32542,\n    \"idential\": 32543,\n    \"ĠCoinbase\": 32544,\n    \"Ġworkings\": 32545,\n    \"ĠPI\": 32546,\n    \"Ġpassionately\": 32547,\n    \"Ġdecisively\": 32548,\n    \"ĠInspection\": 32549,\n    \"Ġinvoke\": 32550,\n    \"Ġstain\": 32551,\n    \"Ġcleaners\": 32552,\n    \"Ġregulates\": 32553,\n    \"Ġshone\": 32554,\n    \"ĠEVERY\": 32555,\n    \"istance\": 32556,\n    \"map\": 32557,\n    \"Ġredu\": 32558,\n    \"Ġoccupies\": 32559,\n    \"Ġprocure\": 32560,\n    \"acket\": 32561,\n    \"roman\": 32562,\n    \"Ġilleg\": 32563,\n    \"Ġleaps\": 32564,\n    \"yond\": 32565,\n    \"Ġyarn\": 32566,\n    \"ĠLTD\": 32567,\n    \"ĠCONTR\": 32568,\n    \"ĠRestoration\": 32569,\n    \"ĠCDs\": 32570,\n    \"Ġdrinkers\": 32571,\n    \"ĠJordanian\": 32572,\n    \"Ġabl\": 32573,\n    \"Ġdisparate\": 32574,\n    \"Ġprimed\": 32575,\n    \"ĠFirearms\": 32576,\n    \"artz\": 32577,\n    \"Ġindispensable\": 32578,\n    \"Ter\": 32579,\n    \"Ġfright\": 32580,\n    \"Ġmarkedly\": 32581,\n    \"Ġroam\": 32582,\n    \"ĠJurassic\": 32583,\n    \"Ġfeder\": 32584,\n    \"Ġpepp\": 32585,\n    \"ĠDV\": 32586,\n    \"Ġpancakes\": 32587,\n    \"sweet\": 32588,\n    \"Ġunmatched\": 32589,\n    \"Ġassembling\": 32590,\n    \"Ultimately\": 32591,\n    \"Ġendeavour\": 32592,\n    \"Ġluckily\": 32593,\n    \"Ġbitch\": 32594,\n    \"Ġelegance\": 32595,\n    \"eers\": 32596,\n    \"drop\": 32597,\n    \"credit\": 32598,\n    \"Ġscourge\": 32599,\n    \"ĠMinimum\": 32600,\n    \"Ġimpatient\": 32601,\n    \"Ġhunted\": 32602,\n    \"ĠGoddard\": 32603,\n    \"Kal\": 32604,\n    \"Ġmined\": 32605,\n    \"Ġcalves\": 32606,\n    \"Ġ234\": 32607,\n    \"Ġplank\": 32608,\n    \"Ġinjecting\": 32609,\n    \"ĠKaufman\": 32610,\n    \"ĠCompliance\": 32611,\n    \"tone\": 32612,\n    \"Ġ345\": 32613,\n    \"Ġdazz\": 32614,\n    \"ĠClarks\": 32615,\n    \"Ġcomprehens\": 32616,\n    \"Ġpist\": 32617,\n    \"Ġrhythms\": 32618,\n    \"Ġreserv\": 32619,\n    \"337\": 32620,\n    \"ĠIDF\": 32621,\n    \"Ġshouts\": 32622,\n    \"midt\": 32623,\n    \"323\": 32624,\n    \"Ġsoothing\": 32625,\n    \"Ġadministr\": 32626,\n    \"Ġgloomy\": 32627,\n    \"Ġfutile\": 32628,\n    \"ĠProhibition\": 32629,\n    \"upon\": 32630,\n    \"ĠAnglic\": 32631,\n    \"seeking\": 32632,\n    \"Ġdodge\": 32633,\n    \"Ds\": 32634,\n    \"ĠGrants\": 32635,\n    \"editor\": 32636,\n    \"ĠInquis\": 32637,\n    \"Ġ1929\": 32638,\n    \"decl\": 32639,\n    \"ĠPorts\": 32640,\n    \"ĠCure\": 32641,\n    \"ĠDPRK\": 32642,\n    \"oct\": 32643,\n    \"Ġvocabulary\": 32644,\n    \"Ġcling\": 32645,\n    \"298\": 32646,\n    \"Ġpeac\": 32647,\n    \"Ġantibodies\": 32648,\n    \"dor\": 32649,\n    \"ĠWorse\": 32650,\n    \"Ġsmelled\": 32651,\n    \"Ġleash\": 32652,\n    \"MED\": 32653,\n    \"Ġdisinteg\": 32654,\n    \"Ġtruthful\": 32655,\n    \"Ġsalesman\": 32656,\n    \"Ġsquares\": 32657,\n    \"susp\": 32658,\n    \"Ġcraving\": 32659,\n    \"Ġwizard\": 32660,\n    \"moral\": 32661,\n    \"ĠQuÃ©\": 32662,\n    \"Anything\": 32663,\n    \"Ġfalsehood\": 32664,\n    \"ARI\": 32665,\n    \"Ġcoworkers\": 32666,\n    \"Ġthy\": 32667,\n    \"outher\": 32668,\n    \"Ġbrushing\": 32669,\n    \"ĠProtest\": 32670,\n    \"ĠMF\": 32671,\n    \"abba\": 32672,\n    \"lead\": 32673,\n    \"ĠExhibit\": 32674,\n    \"Ga\": 32675,\n    \"ĠFranks\": 32676,\n    \"Ġdictates\": 32677,\n    \"illegal\": 32678,\n    \"Ġrelayed\": 32679,\n    \"Ġploy\": 32680,\n    \"ĠØ§ÙĦ\": 32681,\n    \"ĠDocuments\": 32682,\n    \"Ġtint\": 32683,\n    \"ĠYuan\": 32684,\n    \"Ġdepended\": 32685,\n    \"Mir\": 32686,\n    \"ĠIntrodu\": 32687,\n    \"Ġrecourse\": 32688,\n    \"oqu\": 32689,\n    \"ĠTED\": 32690,\n    \"Ġdifferentiated\": 32691,\n    \"ĠWalls\": 32692,\n    \"Ġsentimental\": 32693,\n    \"Ġantis\": 32694,\n    \"retion\": 32695,\n    \"comes\": 32696,\n    \"ĠWORLD\": 32697,\n    \"Ġcoax\": 32698,\n    \"ĠTatt\": 32699,\n    \"ĠGingrich\": 32700,\n    \"2006\": 32701,\n    \"ĠBrut\": 32702,\n    \"Second\": 32703,\n    \"posed\": 32704,\n    \"shots\": 32705,\n    \"Ġ313\": 32706,\n    \"idian\": 32707,\n    \"alking\": 32708,\n    \"Ġdens\": 32709,\n    \"Ġgif\": 32710,\n    \"akings\": 32711,\n    \"Ġkeywords\": 32712,\n    \"Ġchast\": 32713,\n    \"Ġadversary\": 32714,\n    \"Ġnick\": 32715,\n    \"iasis\": 32716,\n    \"ĠLegisl\": 32717,\n    \"Ġcoff\": 32718,\n    \"ĠOriental\": 32719,\n    \"ĠMorg\": 32720,\n    \"ĠHAR\": 32721,\n    \"Ġlegalizing\": 32722,\n    \"Ġbanter\": 32723,\n    \"ĠTart\": 32724,\n    \"ĠTRI\": 32725,\n    \"Ġantagon\": 32726,\n    \"ĠGF\": 32727,\n    \"oler\": 32728,\n    \"ĠUFO\": 32729,\n    \"Therefore\": 32730,\n    \"ĠOsama\": 32731,\n    \"ĠStructure\": 32732,\n    \"apps\": 32733,\n    \"Ġpee\": 32734,\n    \"ĠSomehow\": 32735,\n    \"ĠOverwatch\": 32736,\n    \"ĠCasual\": 32737,\n    \"Ġdishon\": 32738,\n    \"SEE\": 32739,\n    \"ctive\": 32740,\n    \"andering\": 32741,\n    \"ĠTransformation\": 32742,\n    \"Andy\": 32743,\n    \"ĠFever\": 32744,\n    \"Ġspectator\": 32745,\n    \"Ġlash\": 32746,\n    \"Ġprotector\": 32747,\n    \"apy\": 32748,\n    \"Ġexhilar\": 32749,\n    \"aroo\": 32750,\n    \"Ġmamm\": 32751,\n    \"Ġbystand\": 32752,\n    \"acky\": 32753,\n    \"Ġdigestive\": 32754,\n    \"Ġamplified\": 32755,\n    \"Ġalpha\": 32756,\n    \"continue\": 32757,\n    \"Low\": 32758,\n    \"Ġdisgusted\": 32759,\n    \"356\": 32760,\n    \"script\": 32761,\n    \"Ġgenerational\": 32762,\n    \"ĠPassenger\": 32763,\n    \"sight\": 32764,\n    \"Ġcout\": 32765,\n    \"Ġhone\": 32766,\n    \"ulse\": 32767,\n    \"Ġignite\": 32768,\n    \"284\": 32769,\n    \"gow\": 32770,\n    \"Ġbinary\": 32771,\n    \"Ġincess\": 32772,\n    \"Review\": 32773,\n    \"607\": 32774,\n    \"ĠSurprise\": 32775,\n    \"Ġirritation\": 32776,\n    \"ĠBarth\": 32777,\n    \"ĠGum\": 32778,\n    \"Ġvideot\": 32779,\n    \"ĠFres\": 32780,\n    \"asons\": 32781,\n    \"Ġcollaborator\": 32782,\n    \"fal\": 32783,\n    \"ĠGon\": 32784,\n    \"Ġsettles\": 32785,\n    \"regular\": 32786,\n    \"Ġmiscarriage\": 32787,\n    \"cube\": 32788,\n    \"Ġsubord\": 32789,\n    \"ĠRegistered\": 32790,\n    \"Ġnotions\": 32791,\n    \"zzy\": 32792,\n    \"Ġrevert\": 32793,\n    \"OFF\": 32794,\n    \"Ġhasht\": 32795,\n    \"ĠPNG\": 32796,\n    \"Ġunimaginable\": 32797,\n    \"builders\": 32798,\n    \"Taylor\": 32799,\n    \"ĠPAY\": 32800,\n    \"Ġ).\": 32801,\n    \"Ġ238\": 32802,\n    \"ĠLAST\": 32803,\n    \"MAS\": 32804,\n    \"Ġillustrations\": 32805,\n    \"Ġparody\": 32806,\n    \"Ġdispersed\": 32807,\n    \"ĠRoses\": 32808,\n    \"Ġestimation\": 32809,\n    \"ĠGets\": 32810,\n    \"Patrick\": 32811,\n    \"CHA\": 32812,\n    \"Ġmisdem\": 32813,\n    \"agate\": 32814,\n    \"alter\": 32815,\n    \"Ġgeo\": 32816,\n    \"Ġenormously\": 32817,\n    \"Ġarrogance\": 32818,\n    \"Ġpert\": 32819,\n    \"Ġmeta\": 32820,\n    \"ĠJuno\": 32821,\n    \"iov\": 32822,\n    \"imov\": 32823,\n    \"Ġchores\": 32824,\n    \"acan\": 32825,\n    \"Paris\": 32826,\n    \"313\": 32827,\n    \"Lewis\": 32828,\n    \"Ġwillingly\": 32829,\n    \"ERA\": 32830,\n    \"Ġencaps\": 32831,\n    \"ilk\": 32832,\n    \"Ġnodes\": 32833,\n    \"Ġenzyme\": 32834,\n    \"want\": 32835,\n    \"Ġtolerant\": 32836,\n    \"Ġcondos\": 32837,\n    \"Ġasserts\": 32838,\n    \"Ġcanon\": 32839,\n    \"Ġscanned\": 32840,\n    \"bishop\": 32841,\n    \"Ġperched\": 32842,\n    \"util\": 32843,\n    \"ĠBonus\": 32844,\n    \"create\": 32845,\n    \"ĠFuk\": 32846,\n    \"Ġmotif\": 32847,\n    \"Ġcontemplate\": 32848,\n    \"ĠBEN\": 32849,\n    \"imir\": 32850,\n    \"Ġacadem\": 32851,\n    \"uvian\": 32852,\n    \"ĠIdeas\": 32853,\n    \"ĠCY\": 32854,\n    \"Ġants\": 32855,\n    \"Ġprostitutes\": 32856,\n    \"2005\": 32857,\n    \"Spring\": 32858,\n    \"ĠBarrel\": 32859,\n    \"ĠAunt\": 32860,\n    \"ĠLudwig\": 32861,\n    \"ĠHerm\": 32862,\n    \"PRO\": 32863,\n    \"obiles\": 32864,\n    \"rack\": 32865,\n    \"STER\": 32866,\n    \"ucket\": 32867,\n    \"Ġmun\": 32868,\n    \"Ġ419\": 32869,\n    \"ICES\": 32870,\n    \"Ġcardio\": 32871,\n    \"Ġtrenches\": 32872,\n    \"Nation\": 32873,\n    \"yahoo\": 32874,\n    \"Ġburd\": 32875,\n    \"Ġnost\": 32876,\n    \"Ġappropriations\": 32877,\n    \"ĠChili\": 32878,\n    \"Josh\": 32879,\n    \"GW\": 32880,\n    \"Ġoppressed\": 32881,\n    \"ĠBEFORE\": 32882,\n    \"Ġmurderous\": 32883,\n    \"Pen\": 32884,\n    \"achable\": 32885,\n    \"Ġrive\": 32886,\n    \"Ġculmin\": 32887,\n    \"Ġdefin\": 32888,\n    \"ĠMord\": 32889,\n    \"idate\": 32890,\n    \"ĠChim\": 32891,\n    \"ource\": 32892,\n    \"ĠElectro\": 32893,\n    \"orthy\": 32894,\n    \"Ġcalendars\": 32895,\n    \"regation\": 32896,\n    \"Ġretrospect\": 32897,\n    \"ĠTribal\": 32898,\n    \"ĠHes\": 32899,\n    \"Ġcran\": 32900,\n    \"Ġcreditor\": 32901,\n    \"Ġfibers\": 32902,\n    \"note\": 32903,\n    \"idays\": 32904,\n    \"ĠSebast\": 32905,\n    \"ĠKitty\": 32906,\n    \"Ġplainly\": 32907,\n    \"ĠLAPD\": 32908,\n    \"Ġtrumpet\": 32909,\n    \"ĠAppropriations\": 32910,\n    \"Hill\": 32911,\n    \"ĠVeget\": 32912,\n    \"296\": 32913,\n    \"lated\": 32914,\n    \"othes\": 32915,\n    \"ibrarian\": 32916,\n    \"Listen\": 32917,\n    \"nex\": 32918,\n    \"WHO\": 32919,\n    \"Ġshampoo\": 32920,\n    \"Ġclaimants\": 32921,\n    \"Ġisol\": 32922,\n    \"Ġunchecked\": 32923,\n    \"Ġmov\": 32924,\n    \"umo\": 32925,\n    \"ĠLens\": 32926,\n    \"Ġdiscreet\": 32927,\n    \"Ġrespectfully\": 32928,\n    \"Ġreclaimed\": 32929,\n    \"ĠHatt\": 32930,\n    \"thus\": 32931,\n    \"ĠFlo\": 32932,\n    \"Ġsumm\": 32933,\n    \"phas\": 32934,\n    \"ĠHaitian\": 32935,\n    \"Ġstrife\": 32936,\n    \"Ġabound\": 32937,\n    \"verted\": 32938,\n    \"Ġpatronage\": 32939,\n    \"449\": 32940,\n    \"Ġprelim\": 32941,\n    \"ĠZhu\": 32942,\n    \"ĠRevel\": 32943,\n    \"adic\": 32944,\n    \"Ġminded\": 32945,\n    \"ĠStability\": 32946,\n    \"Ġresembling\": 32947,\n    \"Ġvending\": 32948,\n    \"ischer\": 32949,\n    \"Ġkisses\": 32950,\n    \"Ġsuperiority\": 32951,\n    \"Ġinfinite\": 32952,\n    \"ISC\": 32953,\n    \"880\": 32954,\n    \"Ġappease\": 32955,\n    \"VO\": 32956,\n    \"404\": 32957,\n    \"ECH\": 32958,\n    \"gam\": 32959,\n    \"River\": 32960,\n    \"metal\": 32961,\n    \"determination\": 32962,\n    \"Cook\": 32963,\n    \"Ġbuds\": 32964,\n    \"Ġ(%)\": 32965,\n    \"ĠCreated\": 32966,\n    \"Ġstrut\": 32967,\n    \"Ġ425\": 32968,\n    \"Ġverte\": 32969,\n    \"ĠOrb\": 32970,\n    \"Ġweaving\": 32971,\n    \"261\": 32972,\n    \"Ġflyers\": 32973,\n    \"spons\": 32974,\n    \"ĠCovenant\": 32975,\n    \"570\": 32976,\n    \"Ġintangible\": 32977,\n    \"ĠBJ\": 32978,\n    \"ĠStead\": 32979,\n    \"ĠBrune\": 32980,\n    \"pain\": 32981,\n    \"independent\": 32982,\n    \"Ball\": 32983,\n    \"witch\": 32984,\n    \"ĠIon\": 32985,\n    \"Ġpupp\": 32986,\n    \"Cash\": 32987,\n    \"ĠConvert\": 32988,\n    \"Ġimpede\": 32989,\n    \"broad\": 32990,\n    \"onew\": 32991,\n    \"Ġsynergy\": 32992,\n    \"Ġcoined\": 32993,\n    \"620\": 32994,\n    \"ivalent\": 32995,\n    \"ĠInfect\": 32996,\n    \"ĠAqua\": 32997,\n    \"Together\": 32998,\n    \"ĠChemistry\": 32999,\n    \"ĠURL\": 33000,\n    \"ampion\": 33001,\n    \"Ġdeclarations\": 33002,\n    \"Ġaffirmative\": 33003,\n    \"umper\": 33004,\n    \"ĠTarant\": 33005,\n    \"Ġstereotype\": 33006,\n    \"Ġbookstore\": 33007,\n    \"incre\": 33008,\n    \"Ġchipset\": 33009,\n    \"Ġangst\": 33010,\n    \"Jose\": 33011,\n    \"laus\": 33012,\n    \"Ġheater\": 33013,\n    \"ipers\": 33014,\n    \"Ġeminent\": 33015,\n    \"hook\": 33016,\n    \"sticks\": 33017,\n    \"ĠCoul\": 33018,\n    \"Ġmildly\": 33019,\n    \"SG\": 33020,\n    \"Ġworm\": 33021,\n    \"Ġdisable\": 33022,\n    \"Ġperfume\": 33023,\n    \"ISTER\": 33024,\n    \"Ġgathers\": 33025,\n    \"ĠLotus\": 33026,\n    \"hyp\": 33027,\n    \"actus\": 33028,\n    \"Ġdistinctly\": 33029,\n    \"fifth\": 33030,\n    \"!),\": 33031,\n    \"ĠCrunch\": 33032,\n    \"Ġcohesive\": 33033,\n    \"Ġfortunately\": 33034,\n    \"Ġninety\": 33035,\n    \"Ġcartels\": 33036,\n    \"empl\": 33037,\n    \"Direct\": 33038,\n    \"Ġcommuting\": 33039,\n    \"ĠSX\": 33040,\n    \"ractive\": 33041,\n    \"Ġtranslating\": 33042,\n    \"ĠAQ\": 33043,\n    \"Ġslay\": 33044,\n    \"abuse\": 33045,\n    \"ĠProc\": 33046,\n    \"ĠCantor\": 33047,\n    \"ĠTas\": 33048,\n    \"Sir\": 33049,\n    \"Thom\": 33050,\n    \"ĠCHRIST\": 33051,\n    \"Ġreceptive\": 33052,\n    \"ĠCornel\": 33053,\n    \"Arab\": 33054,\n    \"Ġgrammar\": 33055,\n    \"Ġhandlers\": 33056,\n    \"Ġalloy\": 33057,\n    \"Ġthinly\": 33058,\n    \"adem\": 33059,\n    \"Ġproponent\": 33060,\n    \"ĠPVC\": 33061,\n    \"Ġstump\": 33062,\n    \"tom\": 33063,\n    \"rets\": 33064,\n    \"iciency\": 33065,\n    \"780\": 33066,\n    \"Ġ311\": 33067,\n    \"ĠClapper\": 33068,\n    \"ITAL\": 33069,\n    \"Ùħ\": 33070,\n    \"Ġnarrator\": 33071,\n    \"Ġblond\": 33072,\n    \"Ġintermittent\": 33073,\n    \"Ġcollabor\": 33074,\n    \"646\": 33075,\n    \"Ġmetast\": 33076,\n    \"Ġregeneration\": 33077,\n    \"ĠLegendary\": 33078,\n    \"Ġgenitals\": 33079,\n    \"Ġbartender\": 33080,\n    \"atson\": 33081,\n    \"Okay\": 33082,\n    \"Ġpassages\": 33083,\n    \"Ġsubstituted\": 33084,\n    \"orr\": 33085,\n    \"ALTH\": 33086,\n    \"Ġartic\": 33087,\n    \"Ġascent\": 33088,\n    \"Ġmatured\": 33089,\n    \"Ġterminology\": 33090,\n    \"served\": 33091,\n    \"ĠDeliver\": 33092,\n    \"Ġattic\": 33093,\n    \"anges\": 33094,\n    \"Ġrenaissance\": 33095,\n    \"Ġbleed\": 33096,\n    \"claimer\": 33097,\n    \"onse\": 33098,\n    \"Sec\": 33099,\n    \"Ġparticle\": 33100,\n    \"aneous\": 33101,\n    \"ateur\": 33102,\n    \"Ġzeal\": 33103,\n    \"ĠPets\": 33104,\n    \"Working\": 33105,\n    \"ĠRespect\": 33106,\n    \"Ġsermon\": 33107,\n    \"ĠProvided\": 33108,\n    \"Ġfilibuster\": 33109,\n    \"Ġabolished\": 33110,\n    \"reviewed\": 33111,\n    \"cription\": 33112,\n    \"Ġrevers\": 33113,\n    \"atered\": 33114,\n    \"435\": 33115,\n    \"Ġwhe\": 33116,\n    \"ometown\": 33117,\n    \"UFC\": 33118,\n    \"products\": 33119,\n    \"Winter\": 33120,\n    \"Ġ304\": 33121,\n    \"Ġsporadic\": 33122,\n    \"orough\": 33123,\n    \"EB\": 33124,\n    \"ĠAgric\": 33125,\n    \"ĠMTA\": 33126,\n    \"wic\": 33127,\n    \"Ġpowerless\": 33128,\n    \"Ġcarrot\": 33129,\n    \"ww\": 33130,\n    \"Ġabsorption\": 33131,\n    \"ĠTyphoon\": 33132,\n    \"Turkey\": 33133,\n    \"Ġproclaim\": 33134,\n    \"Ġhikers\": 33135,\n    \"Ġpractise\": 33136,\n    \"/$\": 33137,\n    \"Ġfingertips\": 33138,\n    \"Ġbaff\": 33139,\n    \"vu\": 33140,\n    \"Ġans\": 33141,\n    \"plug\": 33142,\n    \"Ġacquaintance\": 33143,\n    \"itement\": 33144,\n    \"ihar\": 33145,\n    \"Ġreluctantly\": 33146,\n    \"Ġforc\": 33147,\n    \"Ġguarant\": 33148,\n    \"ĠWanted\": 33149,\n    \"Walk\": 33150,\n    \"addle\": 33151,\n    \"unders\": 33152,\n    \"Fred\": 33153,\n    \"Ġtides\": 33154,\n    \"ĠBai\": 33155,\n    \"Ġcountering\": 33156,\n    \"raper\": 33157,\n    \"ursions\": 33158,\n    \"ĠFlav\": 33159,\n    \"pared\": 33160,\n    \"raised\": 33161,\n    \"Ñı\": 33162,\n    \"ĠDiff\": 33163,\n    \"Ġreload\": 33164,\n    \"ourses\": 33165,\n    \"ĠBurning\": 33166,\n    \"Ġwand\": 33167,\n    \"Ġledger\": 33168,\n    \"Ġcoughing\": 33169,\n    \"ĠLoren\": 33170,\n    \"Nazis\": 33171,\n    \"Ġcompile\": 33172,\n    \"Eight\": 33173,\n    \"icultural\": 33174,\n    \"yy\": 33175,\n    \"Ġ1932\": 33176,\n    \"Run\": 33177,\n    \"AIN\": 33178,\n    \"Ġattractiveness\": 33179,\n    \"ĠOmn\": 33180,\n    \"Ġconfer\": 33181,\n    \"compliance\": 33182,\n    \"Ġembed\": 33183,\n    \"Steven\": 33184,\n    \"2001\": 33185,\n    \"Ġdecre\": 33186,\n    \"Ġprompts\": 33187,\n    \"ĠHare\": 33188,\n    \"Ġleaping\": 33189,\n    \"Ġslaughtered\": 33190,\n    \"Ġforfeiture\": 33191,\n    \"342\": 33192,\n    \"Charl\": 33193,\n    \"CDC\": 33194,\n    \"ographically\": 33195,\n    \"Ġduplicate\": 33196,\n    \"Ġdistracting\": 33197,\n    \"examination\": 33198,\n    \"Ġpeas\": 33199,\n    \"Ġcatchy\": 33200,\n    \"Ġdives\": 33201,\n    \"ĠAda\": 33202,\n    \"Hay\": 33203,\n    \"Ġenthusiastically\": 33204,\n    \"Ġfunky\": 33205,\n    \"kay\": 33206,\n    \"EVA\": 33207,\n    \"Ġpsychologists\": 33208,\n    \"Ġancestry\": 33209,\n    \"iyah\": 33210,\n    \"ifter\": 33211,\n    \"nob\": 33212,\n    \"518\": 33213,\n    \"rouse\": 33214,\n    \"Ġchord\": 33215,\n    \"Ġcone\": 33216,\n    \"Ġbarracks\": 33217,\n    \"ĠRoyale\": 33218,\n    \"ĠIntegration\": 33219,\n    \"Ġtrolling\": 33220,\n    \"ĠSynt\": 33221,\n    \"andals\": 33222,\n    \"ĠGrain\": 33223,\n    \"ĠNeck\": 33224,\n    \"618\": 33225,\n    \"Ġrapist\": 33226,\n    \"pins\": 33227,\n    \"Ġwitty\": 33228,\n    \"Ġdehydration\": 33229,\n    \"arlane\": 33230,\n    \"Ġimmoral\": 33231,\n    \"Ġaccum\": 33232,\n    \"ĠMcAuliffe\": 33233,\n    \"slow\": 33234,\n    \"Ġinjust\": 33235,\n    \"Ġ1700\": 33236,\n    \"Ġcarbs\": 33237,\n    \"Ġintel\": 33238,\n    \"Non\": 33239,\n    \"isks\": 33240,\n    \"Tre\": 33241,\n    \"Ġinterviewer\": 33242,\n    \"sam\": 33243,\n    \"Ġdelve\": 33244,\n    \"Ġadmirable\": 33245,\n    \"ĠROM\": 33246,\n    \"ĠHispanics\": 33247,\n    \"Ġimpart\": 33248,\n    \"Ġunderrated\": 33249,\n    \"Ġvictimized\": 33250,\n    \"ĠPsych\": 33251,\n    \"ppings\": 33252,\n    \"Ġ610\": 33253,\n    \"pole\": 33254,\n    \"Ġdiner\": 33255,\n    \"ĠScale\": 33256,\n    \"Ġunforeseen\": 33257,\n    \"surprisingly\": 33258,\n    \"opus\": 33259,\n    \"ĠCOURT\": 33260,\n    \"Ġjuggling\": 33261,\n    \"ĠFacilities\": 33262,\n    \"Aid\": 33263,\n    \"ĠHPV\": 33264,\n    \"Ġcrawling\": 33265,\n    \"flu\": 33266,\n    \"etary\": 33267,\n    \"ĠHarriet\": 33268,\n    \"329\": 33269,\n    \"ĠSod\": 33270,\n    \"ĠBiological\": 33271,\n    \"birth\": 33272,\n    \"ribed\": 33273,\n    \"Ġpulses\": 33274,\n    \"396\": 33275,\n    \"eways\": 33276,\n    \"ĠAlma\": 33277,\n    \"nov\": 33278,\n    \"015\": 33279,\n    \"ricane\": 33280,\n    \"agna\": 33281,\n    \"Ak\": 33282,\n    \"ĠClaim\": 33283,\n    \"Ġpref\": 33284,\n    \"Ġinterfaces\": 33285,\n    \"ĠADHD\": 33286,\n    \"604\": 33287,\n    \"ZE\": 33288,\n    \"venture\": 33289,\n    \"Ġascend\": 33290,\n    \"ĠGou\": 33291,\n    \"Ġpriceless\": 33292,\n    \"redo\": 33293,\n    \"kw\": 33294,\n    \"Conf\": 33295,\n    \"Ġmah\": 33296,\n    \"Ġpoets\": 33297,\n    \"Ġstalk\": 33298,\n    \"Ġencamp\": 33299,\n    \"Ġhopped\": 33300,\n    \"Ġmelody\": 33301,\n    \"JECT\": 33302,\n    \"eming\": 33303,\n    \"Ġbewild\": 33304,\n    \"aternal\": 33305,\n    \"uchs\": 33306,\n    \"dit\": 33307,\n    \"ĠTransmission\": 33308,\n    \"Lake\": 33309,\n    \"Ġatoms\": 33310,\n    \"ĠThoughts\": 33311,\n    \"ilts\": 33312,\n    \"volume\": 33313,\n    \"Ġsocioeconomic\": 33314,\n    \"atisf\": 33315,\n    \"Ġnarr\": 33316,\n    \"zinski\": 33317,\n    \"ymes\": 33318,\n    \"episode\": 33319,\n    \"Ġinherit\": 33320,\n    \"Ġintending\": 33321,\n    \"Ġarenas\": 33322,\n    \"uras\": 33323,\n    \"burning\": 33324,\n    \"334\": 33325,\n    \"teenth\": 33326,\n    \"Ġsophistication\": 33327,\n    \"Ġscreenshots\": 33328,\n    \"Ġautistic\": 33329,\n    \"lip\": 33330,\n    \"paper\": 33331,\n    \"Ġmonopol\": 33332,\n    \"799\": 33333,\n    \"forms\": 33334,\n    \"ocrats\": 33335,\n    \"Ġpineapple\": 33336,\n    \"Ġbegs\": 33337,\n    \"Ġpersecuted\": 33338,\n    \"Ġsubscribed\": 33339,\n    \"Ġelic\": 33340,\n    \"ĠPRESIDENT\": 33341,\n    \"297\": 33342,\n    \"Ġpreferential\": 33343,\n    \"Ġpyramid\": 33344,\n    \"Ġconvergence\": 33345,\n    \"Ġwob\": 33346,\n    \"Project\": 33347,\n    \"ĠAluminum\": 33348,\n    \"ĠJPM\": 33349,\n    \"ĠBAT\": 33350,\n    \"Ġdolphins\": 33351,\n    \"018\": 33352,\n    \"healthy\": 33353,\n    \"ĠCG\": 33354,\n    \"ĠEffective\": 33355,\n    \"worm\": 33356,\n    \"ĠEas\": 33357,\n    \"olicited\": 33358,\n    \"ĠUSE\": 33359,\n    \"ĠCaval\": 33360,\n    \"Ġswirl\": 33361,\n    \"Ġspaghetti\": 33362,\n    \"Ġinward\": 33363,\n    \"Republican\": 33364,\n    \"Ġpublicized\": 33365,\n    \"Ġeconomical\": 33366,\n    \"Ġsalsa\": 33367,\n    \"ĠTitanic\": 33368,\n    \"dot\": 33369,\n    \"Ġcontro\": 33370,\n    \"ĠBangl\": 33371,\n    \"iban\": 33372,\n    \"ĠKlux\": 33373,\n    \"Ġhinges\": 33374,\n    \"610\": 33375,\n    \"Ġvalves\": 33376,\n    \"profits\": 33377,\n    \"Wonder\": 33378,\n    \"Ġorient\": 33379,\n    \"Ġsque\": 33380,\n    \"Ġprivatization\": 33381,\n    \"Obama\": 33382,\n    \"Thousands\": 33383,\n    \"ĠTasman\": 33384,\n    \"Ġmaze\": 33385,\n    \"eem\": 33386,\n    \"Ġsurvives\": 33387,\n    \"istant\": 33388,\n    \"Ġenriched\": 33389,\n    \"Ġencl\": 33390,\n    \"Ġcompliments\": 33391,\n    \"ĠShoes\": 33392,\n    \"Ġinsanity\": 33393,\n    \"consider\": 33394,\n    \"agog\": 33395,\n    \"Ġbaffled\": 33396,\n    \"ĠÂ°\": 33397,\n    \"ĠWordPress\": 33398,\n    \"qus\": 33399,\n    \"usual\": 33400,\n    \"stall\": 33401,\n    \"Deb\": 33402,\n    \"ĠRothschild\": 33403,\n    \"Ġesche\": 33404,\n    \"Ġsoph\": 33405,\n    \"Ġambiguous\": 33406,\n    \"negative\": 33407,\n    \"Ġdiscouraging\": 33408,\n    \"Alexander\": 33409,\n    \"319\": 33410,\n    \"Ġsummon\": 33411,\n    \"ipation\": 33412,\n    \"000000\": 33413,\n    \"Ġminimalist\": 33414,\n    \"Ġenraged\": 33415,\n    \"777\": 33416,\n    \"Ġplanetary\": 33417,\n    \"Ġthroughput\": 33418,\n    \"Ġtemperament\": 33419,\n    \"ĠNIC\": 33420,\n    \"ileged\": 33421,\n    \"minster\": 33422,\n    \"ĠPLEASE\": 33423,\n    \"Ġexagger\": 33424,\n    \"ĠDescription\": 33425,\n    \"Ġagitated\": 33426,\n    \"Ġimmortal\": 33427,\n    \"Ġrenders\": 33428,\n    \"Ġcharisma\": 33429,\n    \"sequ\": 33430,\n    \"Ġmajorities\": 33431,\n    \"Ġfreaking\": 33432,\n    \"ĠAdvice\": 33433,\n    \"Ġembodies\": 33434,\n    \"stable\": 33435,\n    \"Ġcustomization\": 33436,\n    \"started\": 33437,\n    \"ĠAutism\": 33438,\n    \"Ġparticipates\": 33439,\n    \"ĠUTC\": 33440,\n    \"Marco\": 33441,\n    \"Ġoddly\": 33442,\n    \"Ġantiqu\": 33443,\n    \"ĠPear\": 33444,\n    \"ĠFey\": 33445,\n    \"Ġcertify\": 33446,\n    \"Ġdisillusion\": 33447,\n    \"ĠPhysicians\": 33448,\n    \"obl\": 33449,\n    \"855\": 33450,\n    \"Ġelim\": 33451,\n    \"Ġ335\": 33452,\n    \"Ol\": 33453,\n    \"ĠSear\": 33454,\n    \"Ġnuances\": 33455,\n    \"past\": 33456,\n    \"Sa\": 33457,\n    \"ĠSlov\": 33458,\n    \"Ġfiltered\": 33459,\n    \"Ġanalogy\": 33460,\n    \"Ġformulate\": 33461,\n    \"Ġarmies\": 33462,\n    \"Ġpuls\": 33463,\n    \"fters\": 33464,\n    \"ilipp\": 33465,\n    \"ĠHOT\": 33466,\n    \"485\": 33467,\n    \"ĠAfghans\": 33468,\n    \"Ġtopical\": 33469,\n    \"ĠBunny\": 33470,\n    \"seeing\": 33471,\n    \"Ġeloqu\": 33472,\n    \"Ġkidneys\": 33473,\n    \"ĠDEM\": 33474,\n    \"pent\": 33475,\n    \"Ġhus\": 33476,\n    \"stores\": 33477,\n    \"ĠProtestant\": 33478,\n    \"Comm\": 33479,\n    \"label\": 33480,\n    \"Kings\": 33481,\n    \"ĠPurpose\": 33482,\n    \"âĢ¦..\": 33483,\n    \"Ġaccumulating\": 33484,\n    \"calling\": 33485,\n    \"Ġgiveaways\": 33486,\n    \"Ġpredicament\": 33487,\n    \"Ġtyp\": 33488,\n    \"Ġtraveler\": 33489,\n    \"003\": 33490,\n    \"impro\": 33491,\n    \"fac\": 33492,\n    \"Ġmapped\": 33493,\n    \"itious\": 33494,\n    \"Ġmasculinity\": 33495,\n    \"Ġtantal\": 33496,\n    \"ĠDJs\": 33497,\n    \"Ġviewpoints\": 33498,\n    \"Burn\": 33499,\n    \"ĠWii\": 33500,\n    \"pak\": 33501,\n    \"ĠEB\": 33502,\n    \"Ġhinge\": 33503,\n    \"Ġfacets\": 33504,\n    \"Ġphotographic\": 33505,\n    \"Ġcompiling\": 33506,\n    \"Ġdecks\": 33507,\n    \"Ġarticulated\": 33508,\n    \"Federal\": 33509,\n    \"crim\": 33510,\n    \"llah\": 33511,\n    \"Ġfiasco\": 33512,\n    \"ĠLIST\": 33513,\n    \"oute\": 33514,\n    \"ĠDraper\": 33515,\n    \"ĠLaos\": 33516,\n    \"Ġclimbers\": 33517,\n    \"raph\": 33518,\n    \"ĠDek\": 33519,\n    \"WAY\": 33520,\n    \"Ġgreets\": 33521,\n    \"Ġoppressive\": 33522,\n    \"otor\": 33523,\n    \"otiation\": 33524,\n    \"\\\":[\": 33525,\n    \"Record\": 33526,\n    \"mining\": 33527,\n    \"Town\": 33528,\n    \"Ġfavorably\": 33529,\n    \"ĠYoutube\": 33530,\n    \"William\": 33531,\n    \"Ġlan\": 33532,\n    \"âĢ²\": 33533,\n    \"ĠSpec\": 33534,\n    \"Ġtranquil\": 33535,\n    \"ĠClient\": 33536,\n    \"oln\": 33537,\n    \"celona\": 33538,\n    \"Ġrealistically\": 33539,\n    \"Ġmisplaced\": 33540,\n    \"ĠBie\": 33541,\n    \"bye\": 33542,\n    \"Yo\": 33543,\n    \"465\": 33544,\n    \"ĠMadagascar\": 33545,\n    \"oplan\": 33546,\n    \"arist\": 33547,\n    \"Ġconfines\": 33548,\n    \"Ġï\": 33549,\n    \"awks\": 33550,\n    \"Ġpiracy\": 33551,\n    \"Ġunwelcome\": 33552,\n    \"Intel\": 33553,\n    \"Ġparanoid\": 33554,\n    \"CLAIM\": 33555,\n    \"Ġblush\": 33556,\n    \"united\": 33557,\n    \"Ġmotivational\": 33558,\n    \"ĠVII\": 33559,\n    \"Ġdiabetic\": 33560,\n    \"Ġantiv\": 33561,\n    \"Ġdissect\": 33562,\n    \"Ġbestselling\": 33563,\n    \"Ġfluffy\": 33564,\n    \"ĠRemote\": 33565,\n    \"Ġvert\": 33566,\n    \"Correct\": 33567,\n    \"Ġcolossal\": 33568,\n    \"Ġcontrasts\": 33569,\n    \"Ġcirca\": 33570,\n    \"ĠDamage\": 33571,\n    \"Ġunrel\": 33572,\n    \"Ġdiscrepancy\": 33573,\n    \"ĠCIS\": 33574,\n    \"ĠCLASS\": 33575,\n    \"ilty\": 33576,\n    \"Ġsynopsis\": 33577,\n    \"emed\": 33578,\n    \"cakes\": 33579,\n    \"ibal\": 33580,\n    \"inea\": 33581,\n    \"ienced\": 33582,\n    \"Ġimplicit\": 33583,\n    \"ĠLOOK\": 33584,\n    \"Ġsilhouette\": 33585,\n    \"affiliated\": 33586,\n    \"ĠHalo\": 33587,\n    \"377\": 33588,\n    \"Ġlyr\": 33589,\n    \"ĠVide\": 33590,\n    \"herent\": 33591,\n    \"Ġbadges\": 33592,\n    \"plays\": 33593,\n    \"orea\": 33594,\n    \"Ġjammed\": 33595,\n    \"cancer\": 33596,\n    \"ĠYep\": 33597,\n    \"racted\": 33598,\n    \"ĠDisability\": 33599,\n    \"Ġfooth\": 33600,\n    \"friends\": 33601,\n    \"Ġbloated\": 33602,\n    \"Bet\": 33603,\n    \"ĠAntioch\": 33604,\n    \"Ġintrodu\": 33605,\n    \"Ġannexed\": 33606,\n    \"ivism\": 33607,\n    \"ĠFlickr\": 33608,\n    \"pants\": 33609,\n    \"Ġinterruption\": 33610,\n    \"645\": 33611,\n    \"ĠIly\": 33612,\n    \"ĠOss\": 33613,\n    \"ĠAMA\": 33614,\n    \"Ġpolitely\": 33615,\n    \"Ġnatives\": 33616,\n    \"Ġrushes\": 33617,\n    \"enges\": 33618,\n    \"ĠHarm\": 33619,\n    \"Ġdestroyer\": 33620,\n    \"ĠEstimates\": 33621,\n    \"Ġtransforms\": 33622,\n    \"Ġinvariably\": 33623,\n    \"Ġcac\": 33624,\n    \"iency\": 33625,\n    \"599\": 33626,\n    \"Ġconstitutionally\": 33627,\n    \"Ġrappers\": 33628,\n    \"ĠSettlement\": 33629,\n    \"icz\": 33630,\n    \"Ġhardened\": 33631,\n    \"citizens\": 33632,\n    \"Ġcircling\": 33633,\n    \"Ġtrapping\": 33634,\n    \"Ġguaranteeing\": 33635,\n    \"690\": 33636,\n    \"agher\": 33637,\n    \"Ġarcade\": 33638,\n    \"Ġfanc\": 33639,\n    \"Ġslapping\": 33640,\n    \"OPS\": 33641,\n    \"Ġmasse\": 33642,\n    \"Ġpudding\": 33643,\n    \"Jac\": 33644,\n    \"ĠGraphics\": 33645,\n    \"Ġuptake\": 33646,\n    \"?,\": 33647,\n    \"Fair\": 33648,\n    \"ĠSatan\": 33649,\n    \"uffy\": 33650,\n    \"ĠGuatem\": 33651,\n    \"ĠTransaction\": 33652,\n    \"Ġunlocking\": 33653,\n    \"ĠLINE\": 33654,\n    \"Ġapprehens\": 33655,\n    \"Ġglean\": 33656,\n    \"291\": 33657,\n    \"Ġexacerbate\": 33658,\n    \"ĠTrave\": 33659,\n    \"ĠTrop\": 33660,\n    \"Supp\": 33661,\n    \"Ġqueens\": 33662,\n    \"cart\": 33663,\n    \"Ġscrolling\": 33664,\n    \"Ġox\": 33665,\n    \"cone\": 33666,\n    \"Matthew\": 33667,\n    \"ĠDIRECT\": 33668,\n    \"Ġbacker\": 33669,\n    \"Ġthyroid\": 33670,\n    \"Sarah\": 33671,\n    \"ĠEDIT\": 33672,\n    \"ĠActivision\": 33673,\n    \"352\": 33674,\n    \"Ġreinforcements\": 33675,\n    \"Ġding\": 33676,\n    \"Ġplush\": 33677,\n    \"Ġpeanuts\": 33678,\n    \"ĠFant\": 33679,\n    \"ĠPediatrics\": 33680,\n    \"Ġaccommodating\": 33681,\n    \"ĠPractices\": 33682,\n    \"Answer\": 33683,\n    \"racial\": 33684,\n    \"ĠConstant\": 33685,\n    \"740\": 33686,\n    \"strength\": 33687,\n    \"apist\": 33688,\n    \"Ġsynthes\": 33689,\n    \"ĠLeap\": 33690,\n    \"ĠFabric\": 33691,\n    \"Ġbrainstorm\": 33692,\n    \"obia\": 33693,\n    \"Ġconception\": 33694,\n    \"Ġtuberculosis\": 33695,\n    \"Ġmajestic\": 33696,\n    \"ĠTitus\": 33697,\n    \"ĠTee\": 33698,\n    \"Ġlikeness\": 33699,\n    \"ĠSEA\": 33700,\n    \"lite\": 33701,\n    \"Ġ950\": 33702,\n    \"sufficient\": 33703,\n    \"Ġtrem\": 33704,\n    \"Ġharshly\": 33705,\n    \"Ġredacted\": 33706,\n    \"Ġwelding\": 33707,\n    \"Ġperplex\": 33708,\n    \"Ġpoetic\": 33709,\n    \"Ġinsignificant\": 33710,\n    \"Ġware\": 33711,\n    \"Ġwandered\": 33712,\n    \"Ġmete\": 33713,\n    \"ĠSTART\": 33714,\n    \"Ġweaponry\": 33715,\n    \"opsy\": 33716,\n    \"shadow\": 33717,\n    \"Ġobsc\": 33718,\n    \"hare\": 33719,\n    \"ĠOPEN\": 33720,\n    \"Ġdiligent\": 33721,\n    \"Girls\": 33722,\n    \"Ġinitials\": 33723,\n    \"Start\": 33724,\n    \"ĠBrookings\": 33725,\n    \"ombs\": 33726,\n    \"Ġlashes\": 33727,\n    \"essor\": 33728,\n    \"Ġgravy\": 33729,\n    \"ĠUbuntu\": 33730,\n    \"Tree\": 33731,\n    \"Ġ435\": 33732,\n    \"Ġcellar\": 33733,\n    \"Ġaquarium\": 33734,\n    \"ĠPodesta\": 33735,\n    \"361\": 33736,\n    \"ĠController\": 33737,\n    \"Ġeru\": 33738,\n    \"reasonable\": 33739,\n    \"Ġpermissions\": 33740,\n    \"725\": 33741,\n    \"Ġadministering\": 33742,\n    \"Ġflirt\": 33743,\n    \"Ġfleeting\": 33744,\n    \"asive\": 33745,\n    \"Ġsubcontract\": 33746,\n    \"Ġfascist\": 33747,\n    \"Ġcabbage\": 33748,\n    \"science\": 33749,\n    \"Ġboiler\": 33750,\n    \"ioned\": 33751,\n    \"Ġintegrates\": 33752,\n    \"Ġresidue\": 33753,\n    \"KEY\": 33754,\n    \"Ġwi\": 33755,\n    \"Ġsquared\": 33756,\n    \"Unless\": 33757,\n    \"Ġmute\": 33758,\n    \"ĠTuc\": 33759,\n    \"Ġverb\": 33760,\n    \"Gary\": 33761,\n    \"Ġexperimentation\": 33762,\n    \"fee\": 33763,\n    \"chini\": 33764,\n    \"Ġmarrow\": 33765,\n    \"ĠBalt\": 33766,\n    \"Ġnodded\": 33767,\n    \"tn\": 33768,\n    \"Ġmissionary\": 33769,\n    \"OTO\": 33770,\n    \"Ġoptimum\": 33771,\n    \"555\": 33772,\n    \"Ġwhipping\": 33773,\n    \"aunts\": 33774,\n    \"ĠScene\": 33775,\n    \"Ġcharacterize\": 33776,\n    \"Ġretrospective\": 33777,\n    \"Ġutilizes\": 33778,\n    \"Ġhastily\": 33779,\n    \"older\": 33780,\n    \"ĠPW\": 33781,\n    \"Ġsleepy\": 33782,\n    \"020\": 33783,\n    \"ĠAcid\": 33784,\n    \"Ġridiculously\": 33785,\n    \"Ġgigg\": 33786,\n    \"649\": 33787,\n    \"Ġcrus\": 33788,\n    \"ĠShame\": 33789,\n    \"ĠTorn\": 33790,\n    \"finding\": 33791,\n    \"IPS\": 33792,\n    \"Ġplat\": 33793,\n    \"ometers\": 33794,\n    \"Ġamphib\": 33795,\n    \"ellow\": 33796,\n    \"ĠSpecies\": 33797,\n    \"commercial\": 33798,\n    \"Ġvirgin\": 33799,\n    \"Ġdarn\": 33800,\n    \"Ġsorely\": 33801,\n    \"Ġrespondent\": 33802,\n    \"Ġray\": 33803,\n    \"ĠCONS\": 33804,\n    \"Ġunequivocally\": 33805,\n    \"server\": 33806,\n    \"Ġdrip\": 33807,\n    \"ĠRazor\": 33808,\n    \"Ban\": 33809,\n    \"ĠHMS\": 33810,\n    \"Ġhijab\": 33811,\n    \"ĠMuss\": 33812,\n    \"Ġsandy\": 33813,\n    \"Ġaversion\": 33814,\n    \"Ġoverarching\": 33815,\n    \"Ġultr\": 33816,\n    \"ĠIraqis\": 33817,\n    \"Ġuninterrupted\": 33818,\n    \"Ġrouting\": 33819,\n    \"Ġundone\": 33820,\n    \"independence\": 33821,\n    \"gra\": 33822,\n    \"ysics\": 33823,\n    \"inflammatory\": 33824,\n    \"cussion\": 33825,\n    \"ĠDefinitely\": 33826,\n    \"Ġelastic\": 33827,\n    \"peer\": 33828,\n    \"ĠGiov\": 33829,\n    \"ĠMandarin\": 33830,\n    \"Ġscratches\": 33831,\n    \"Ġphysicist\": 33832,\n    \"Ġbestowed\": 33833,\n    \"usually\": 33834,\n    \"OULD\": 33835,\n    \"igration\": 33836,\n    \"Human\": 33837,\n    \"Dead\": 33838,\n    \"osph\": 33839,\n    \"bott\": 33840,\n    \"doctoral\": 33841,\n    \"Ġbending\": 33842,\n    \"Ġconfigurations\": 33843,\n    \"psych\": 33844,\n    \"db\": 33845,\n    \"ĠUD\": 33846,\n    \"Ġarteries\": 33847,\n    \"orically\": 33848,\n    \"Ġblasphemy\": 33849,\n    \"jj\": 33850,\n    \"checking\": 33851,\n    \"adian\": 33852,\n    \"IRD\": 33853,\n    \"ĠDialogue\": 33854,\n    \"Ġshielded\": 33855,\n    \"ĠVox\": 33856,\n    \"Dave\": 33857,\n    \"Ġturb\": 33858,\n    \"ĠMassive\": 33859,\n    \"ĠBMI\": 33860,\n    \"ĠNF\": 33861,\n    \"uced\": 33862,\n    \"ickle\": 33863,\n    \"ishable\": 33864,\n    \"Ġembody\": 33865,\n    \"ÙĪ\": 33866,\n    \"Senior\": 33867,\n    \"ĠResult\": 33868,\n    \"try\": 33869,\n    \"egu\": 33870,\n    \"401\": 33871,\n    \"ĠLoyal\": 33872,\n    \"Ġperilous\": 33873,\n    \"Ġdissu\": 33874,\n    \"Ġmythology\": 33875,\n    \"ĠWax\": 33876,\n    \"Jesus\": 33877,\n    \"ĠMotorsport\": 33878,\n    \"Ġadvis\": 33879,\n    \"ĠAki\": 33880,\n    \"ISM\": 33881,\n    \"tested\": 33882,\n    \"Ġplag\": 33883,\n    \"Ġriches\": 33884,\n    \"ĠOCT\": 33885,\n    \"ĠLocke\": 33886,\n    \"BG\": 33887,\n    \"Ġ460\": 33888,\n    \"rawl\": 33889,\n    \"ĠTermin\": 33890,\n    \"Ġ295\": 33891,\n    \"Ġchopping\": 33892,\n    \"KT\": 33893,\n    \"Ġconverts\": 33894,\n    \"Ask\": 33895,\n    \"alse\": 33896,\n    \"ĠKeynes\": 33897,\n    \"Ġrefuted\": 33898,\n    \"Ġrabbits\": 33899,\n    \"Ġbilingual\": 33900,\n    \"urse\": 33901,\n    \"ĠSalad\": 33902,\n    \"odiac\": 33903,\n    \"Ġsolidly\": 33904,\n    \"Dam\": 33905,\n    \"Ġpp\": 33906,\n    \"rities\": 33907,\n    \"Rah\": 33908,\n    \"itness\": 33909,\n    \"Ġsixty\": 33910,\n    \"332\": 33911,\n    \"cold\": 33912,\n    \"Ġhindered\": 33913,\n    \"Ġclipped\": 33914,\n    \"Ġreceptor\": 33915,\n    \"ĠHoms\": 33916,\n    \"Ġdusk\": 33917,\n    \"Ġarchae\": 33918,\n    \"LR\": 33919,\n    \"Ġrods\": 33920,\n    \"Ġ257\": 33921,\n    \"ĠSith\": 33922,\n    \"ĠPumpkin\": 33923,\n    \"ellation\": 33924,\n    \"ĠWD\": 33925,\n    \"Ġdecriminal\": 33926,\n    \"Ġusable\": 33927,\n    \"Ġcheerful\": 33928,\n    \"ĠInform\": 33929,\n    \"Ġbrushes\": 33930,\n    \"vier\": 33931,\n    \"ĠBrush\": 33932,\n    \"590\": 33933,\n    \"boost\": 33934,\n    \"guided\": 33935,\n    \"ĠMJ\": 33936,\n    \"Ġsatirical\": 33937,\n    \"ortion\": 33938,\n    \"efficiency\": 33939,\n    \"Ġstrands\": 33940,\n    \"ĠWilde\": 33941,\n    \"Ġreproduce\": 33942,\n    \"verage\": 33943,\n    \"Ġlug\": 33944,\n    \"Ġhist\": 33945,\n    \"offer\": 33946,\n    \"Ġcollapses\": 33947,\n    \"Ġclerks\": 33948,\n    \"Ġairstrike\": 33949,\n    \"IPP\": 33950,\n    \"iscover\": 33951,\n    \"Ġnefarious\": 33952,\n    \"Ġstripe\": 33953,\n    \"Ġbona\": 33954,\n    \"ocon\": 33955,\n    \"Ġpunishments\": 33956,\n    \"ITED\": 33957,\n    \"ĠAltern\": 33958,\n    \"testing\": 33959,\n    \"Ġeerie\": 33960,\n    \"erous\": 33961,\n    \"Ġcaves\": 33962,\n    \"Ġcondemns\": 33963,\n    \"ĠDropbox\": 33964,\n    \"inese\": 33965,\n    \"axis\": 33966,\n    \"ĠRegistry\": 33967,\n    \"ĠMong\": 33968,\n    \"Ġbullies\": 33969,\n    \"Ġdocks\": 33970,\n    \"ĠAlter\": 33971,\n    \"rella\": 33972,\n    \"446\": 33973,\n    \"ĠDare\": 33974,\n    \"Ġvirtues\": 33975,\n    \"Ġdont\": 33976,\n    \"Value\": 33977,\n    \"ENE\": 33978,\n    \"received\": 33979,\n    \"Ġseaf\": 33980,\n    \"476\": 33981,\n    \"ilon\": 33982,\n    \"ĠKits\": 33983,\n    \"Ġrarity\": 33984,\n    \"Ġnurt\": 33985,\n    \"skin\": 33986,\n    \"ĠUL\": 33987,\n    \"ĠRegiment\": 33988,\n    \"terior\": 33989,\n    \"hate\": 33990,\n    \"ĠEstimated\": 33991,\n    \"ĠSilence\": 33992,\n    \"Ġorganism\": 33993,\n    \"ĠSigned\": 33994,\n    \"ĠIA\": 33995,\n    \"bite\": 33996,\n    \"Ġthicker\": 33997,\n    \"Ġeyeb\": 33998,\n    \"Ġjournalistic\": 33999,\n    \"ĠDisp\": 34000,\n    \"margin\": 34001,\n    \"Dri\": 34002,\n    \"Ġcomplexes\": 34003,\n    \"Ġimaginary\": 34004,\n    \"Ġrefuel\": 34005,\n    \"Ġmeticulous\": 34006,\n    \"Dub\": 34007,\n    \"Ġhaze\": 34008,\n    \"860\": 34009,\n    \"Ġproverbial\": 34010,\n    \"Ġozone\": 34011,\n    \"cale\": 34012,\n    \"resent\": 34013,\n    \"Ġdiscrete\": 34014,\n    \"boats\": 34015,\n    \"Ġ343\": 34016,\n    \"ĠRET\": 34017,\n    \"Ġsailor\": 34018,\n    \"hair\": 34019,\n    \"gear\": 34020,\n    \"Ġmalt\": 34021,\n    \"Ġpeach\": 34022,\n    \"ĠRabb\": 34023,\n    \"699\": 34024,\n    \"318\": 34025,\n    \"ĠVerge\": 34026,\n    \"Fin\": 34027,\n    \"ĠMighty\": 34028,\n    \"ierce\": 34029,\n    \"403\": 34030,\n    \"Ġdisenfranch\": 34031,\n    \"bass\": 34032,\n    \"nice\": 34033,\n    \"Ġsinks\": 34034,\n    \"ĠLaugh\": 34035,\n    \"367\": 34036,\n    \"ĠZur\": 34037,\n    \"Ġtravers\": 34038,\n    \"ĠMystery\": 34039,\n    \"onsense\": 34040,\n    \"ĠMonarch\": 34041,\n    \"Ġleapt\": 34042,\n    \"ergy\": 34043,\n    \"porate\": 34044,\n    \"display\": 34045,\n    \"ilet\": 34046,\n    \"Ġendemic\": 34047,\n    \"Bern\": 34048,\n    \"Ġpulmonary\": 34049,\n    \"Ġbroch\": 34050,\n    \"ĠManziel\": 34051,\n    \"Lyn\": 34052,\n    \"Repe\": 34053,\n    \"lda\": 34054,\n    \"hands\": 34055,\n    \"Ġtroublesome\": 34056,\n    \"Jordan\": 34057,\n    \"UTION\": 34058,\n    \"ĠALP\": 34059,\n    \"ĠLEG\": 34060,\n    \"Ġreconnaissance\": 34061,\n    \"ĠRNA\": 34062,\n    \"letters\": 34063,\n    \"ĠYounger\": 34064,\n    \"ĠLW\": 34065,\n    \"ĠSensor\": 34066,\n    \"388\": 34067,\n    \"Ġwielding\": 34068,\n    \"spr\": 34069,\n    \"Ġancestral\": 34070,\n    \"331\": 34071,\n    \"OTH\": 34072,\n    \"ĠAxis\": 34073,\n    \"irement\": 34074,\n    \"ĠCompact\": 34075,\n    \"voice\": 34076,\n    \"Ġpercussion\": 34077,\n    \"Ġendeav\": 34078,\n    \"Kate\": 34079,\n    \"ĠJACK\": 34080,\n    \"ĠMagnus\": 34081,\n    \"Ġinterconnected\": 34082,\n    \"ĠTraff\": 34083,\n    \"demon\": 34084,\n    \"Ġardent\": 34085,\n    \"ĠSomers\": 34086,\n    \"andum\": 34087,\n    \"346\": 34088,\n    \"heartedly\": 34089,\n    \"ayne\": 34090,\n    \"Design\": 34091,\n    \"melon\": 34092,\n    \"ĠCarib\": 34093,\n    \"Ġ1935\": 34094,\n    \"intention\": 34095,\n    \"cape\": 34096,\n    \"cend\": 34097,\n    \"organic\": 34098,\n    \"373\": 34099,\n    \"ĠRevival\": 34100,\n    \"ĠBLACK\": 34101,\n    \"Ġaspiration\": 34102,\n    \"yellow\": 34103,\n    \"bodied\": 34104,\n    \"Ġcrave\": 34105,\n    \"ĠIntelligent\": 34106,\n    \"ĠUnique\": 34107,\n    \"tab\": 34108,\n    \"386\": 34109,\n    \"ĠNess\": 34110,\n    \"Official\": 34111,\n    \"Stay\": 34112,\n    \"Ġcreat\": 34113,\n    \"iliary\": 34114,\n    \"rified\": 34115,\n    \"ĠPok\": 34116,\n    \"Ġabolition\": 34117,\n    \"Ka\": 34118,\n    \"ĠCourage\": 34119,\n    \"ĠDickens\": 34120,\n    \"rophic\": 34121,\n    \"ĠFAR\": 34122,\n    \"Ġfurnished\": 34123,\n    \".âĢĵ\": 34124,\n    \"rete\": 34125,\n    \"Ġvaginal\": 34126,\n    \"hner\": 34127,\n    \"ĠLONG\": 34128,\n    \"imates\": 34129,\n    \"ĠLiter\": 34130,\n    \"ĠMeasures\": 34131,\n    \"ĠBelg\": 34132,\n    \"\\\"-\": 34133,\n    \"ĠRaider\": 34134,\n    \"enario\": 34135,\n    \"rification\": 34136,\n    \"ĠFISA\": 34137,\n    \"ĠStab\": 34138,\n    \"Ġnar\": 34139,\n    \"mund\": 34140,\n    \"Tenn\": 34141,\n    \"Ġwakes\": 34142,\n    \"Ġcharg\": 34143,\n    \"okers\": 34144,\n    \"assment\": 34145,\n    \"Ġsiph\": 34146,\n    \"Ġludicrous\": 34147,\n    \"670\": 34148,\n    \"Ġcompositions\": 34149,\n    \"Ġpinnacle\": 34150,\n    \"ĠRankings\": 34151,\n    \"ĠTelescope\": 34152,\n    \"secure\": 34153,\n    \"Ġib\": 34154,\n    \"Ġaptly\": 34155,\n    \"paste\": 34156,\n    \"ĠJUST\": 34157,\n    \"RD\": 34158,\n    \"herry\": 34159,\n    \"sung\": 34160,\n    \"Ġmig\": 34161,\n    \"naires\": 34162,\n    \"Ġmigrated\": 34163,\n    \"Base\": 34164,\n    \"Ġamazingly\": 34165,\n    \"Ġunregulated\": 34166,\n    \"published\": 34167,\n    \"ĠPIT\": 34168,\n    \"ĠMissile\": 34169,\n    \"extreme\": 34170,\n    \"ĠAlone\": 34171,\n    \"skilled\": 34172,\n    \"ĠRamp\": 34173,\n    \"Ġcamer\": 34174,\n    \"Ġflyer\": 34175,\n    \"Ġbrewers\": 34176,\n    \"ĠReference\": 34177,\n    \"ĠMOV\": 34178,\n    \"ĠLep\": 34179,\n    \"Ġentitle\": 34180,\n    \"ivals\": 34181,\n    \"ĠPIN\": 34182,\n    \"Ġbatches\": 34183,\n    \"Ġunexplained\": 34184,\n    \"Ġenergies\": 34185,\n    \"Ġblurred\": 34186,\n    \"enged\": 34187,\n    \"orig\": 34188,\n    \"WF\": 34189,\n    \"olves\": 34190,\n    \"ĠPicks\": 34191,\n    \"ĠTwice\": 34192,\n    \"arranted\": 34193,\n    \"Ġmembrane\": 34194,\n    \"ĠMoonlight\": 34195,\n    \"Ġsulfur\": 34196,\n    \"Ġpurposely\": 34197,\n    \"Ġfumes\": 34198,\n    \"Ġ(#\": 34199,\n    \"onics\": 34200,\n    \"ivities\": 34201,\n    \"rollers\": 34202,\n    \"Ġflattering\": 34203,\n    \"felt\": 34204,\n    \"Ġintoxication\": 34205,\n    \"Bridge\": 34206,\n    \"ĠFallout\": 34207,\n    \"Ġcreatively\": 34208,\n    \"Ġpsychologically\": 34209,\n    \"Ġdespicable\": 34210,\n    \"gae\": 34211,\n    \"820\": 34212,\n    \"VERS\": 34213,\n    \"Ġtidal\": 34214,\n    \"Ġcarbohydrates\": 34215,\n    \"strip\": 34216,\n    \"Ġgravitational\": 34217,\n    \"Ġfeds\": 34218,\n    \"ĠZhao\": 34219,\n    \"legates\": 34220,\n    \"Ġ307\": 34221,\n    \"String\": 34222,\n    \"ĠRepair\": 34223,\n    \"Ġ1928\": 34224,\n    \"orses\": 34225,\n    \"atography\": 34226,\n    \"Boston\": 34227,\n    \"Ġasymm\": 34228,\n    \"ĠSomebody\": 34229,\n    \"Van\": 34230,\n    \"ĠSovereign\": 34231,\n    \"Ġnotoriety\": 34232,\n    \"Ġsimulate\": 34233,\n    \"ĠDiscussion\": 34234,\n    \"ĠTransition\": 34235,\n    \"Ġcopying\": 34236,\n    \"antage\": 34237,\n    \"ĠRodrig\": 34238,\n    \"Ġindifference\": 34239,\n    \"Ġ580\": 34240,\n    \"Ġastronomical\": 34241,\n    \"Ġscrews\": 34242,\n    \"840\": 34243,\n    \"inates\": 34244,\n    \"ĠStreaming\": 34245,\n    \"Ġentit\": 34246,\n    \"ĠLiterature\": 34247,\n    \"369\": 34248,\n    \"805\": 34249,\n    \"OTS\": 34250,\n    \"Ð¾\": 34251,\n    \"img\": 34252,\n    \"inness\": 34253,\n    \"Ġreverber\": 34254,\n    \"Ġpartition\": 34255,\n    \"Short\": 34256,\n    \"Ġmoist\": 34257,\n    \"Ġspoof\": 34258,\n    \"ĠDesire\": 34259,\n    \"orce\": 34260,\n    \"Ġcrammed\": 34261,\n    \"Ġunfor\": 34262,\n    \"Pan\": 34263,\n    \"ingen\": 34264,\n    \"Ġrelat\": 34265,\n    \"Mother\": 34266,\n    \"ĠGn\": 34267,\n    \"altern\": 34268,\n    \"Ġresurg\": 34269,\n    \"Ġcramped\": 34270,\n    \"ĠCitadel\": 34271,\n    \"Ġlaureate\": 34272,\n    \"Ġanalys\": 34273,\n    \"Ġnuns\": 34274,\n    \"ĠTie\": 34275,\n    \"activ\": 34276,\n    \"ĠSurprisingly\": 34277,\n    \"ĠProtective\": 34278,\n    \"ĠRedemption\": 34279,\n    \"Ġendlessly\": 34280,\n    \"Ġfists\": 34281,\n    \"spl\": 34282,\n    \"ĠKron\": 34283,\n    \"ĠExamples\": 34284,\n    \"Especially\": 34285,\n    \"Ġprejud\": 34286,\n    \"ĠSchwar\": 34287,\n    \"Ġ237\": 34288,\n    \"ĠPlants\": 34289,\n    \"ĠUNDER\": 34290,\n    \"Ġlasers\": 34291,\n    \"Ġsher\": 34292,\n    \"Ġgoddess\": 34293,\n    \"Ġwipes\": 34294,\n    \"409\": 34295,\n    \"ĠGTA\": 34296,\n    \"Ġhybrids\": 34297,\n    \"rowd\": 34298,\n    \"ĠMILL\": 34299,\n    \"ĠNUM\": 34300,\n    \"ĠGeek\": 34301,\n    \"ĠTWO\": 34302,\n    \"ĠTimbers\": 34303,\n    \"Ġresembled\": 34304,\n    \"ĠGRE\": 34305,\n    \"Bring\": 34306,\n    \"Ġcompressed\": 34307,\n    \"ĠOral\": 34308,\n    \"379\": 34309,\n    \"Ġwrench\": 34310,\n    \"LCS\": 34311,\n    \"Ġhomosexual\": 34312,\n    \"Kelly\": 34313,\n    \"Ġhump\": 34314,\n    \"ĠSicily\": 34315,\n    \"Ġperished\": 34316,\n    \"aos\": 34317,\n    \"doesn\": 34318,\n    \"scrib\": 34319,\n    \"Charlie\": 34320,\n    \"Ġshuffle\": 34321,\n    \"372\": 34322,\n    \"cedented\": 34323,\n    \"402\": 34324,\n    \"Ġtiers\": 34325,\n    \"Ġinteracted\": 34326,\n    \"ĠHG\": 34327,\n    \"ĠJere\": 34328,\n    \"ĠBRA\": 34329,\n    \"ĠDOC\": 34330,\n    \"things\": 34331,\n    \"Ġfaiths\": 34332,\n    \"Ġgirlfriends\": 34333,\n    \"Ġfortified\": 34334,\n    \"develop\": 34335,\n    \"ĠKus\": 34336,\n    \"iability\": 34337,\n    \"rase\": 34338,\n    \"iotics\": 34339,\n    \"ĠChern\": 34340,\n    \"boxes\": 34341,\n    \"abol\": 34342,\n    \"idan\": 34343,\n    \"emon\": 34344,\n    \"ĠJudaism\": 34345,\n    \"ĠSituation\": 34346,\n    \"ĠGrimm\": 34347,\n    \"Ġgou\": 34348,\n    \"ĠVictim\": 34349,\n    \"backer\": 34350,\n    \"Ġanimosity\": 34351,\n    \"ĠHorizons\": 34352,\n    \"ĠKazakh\": 34353,\n    \"Ġgrossly\": 34354,\n    \"ĠTac\": 34355,\n    \"yg\": 34356,\n    \"366\": 34357,\n    \"Ġcheaply\": 34358,\n    \"Ġformulated\": 34359,\n    \"ĠDangerous\": 34360,\n    \"offensive\": 34361,\n    \"Ġsauces\": 34362,\n    \"Ġkeyboards\": 34363,\n    \"666\": 34364,\n    \"Ġcanopy\": 34365,\n    \"Inc\": 34366,\n    \"astered\": 34367,\n    \"iesel\": 34368,\n    \"Ġadv\": 34369,\n    \"currency\": 34370,\n    \"Ġscapego\": 34371,\n    \"plings\": 34372,\n    \"ĠBDS\": 34373,\n    \"Ġstrangely\": 34374,\n    \"today\": 34375,\n    \"ĠEgyptians\": 34376,\n    \"Ġcoron\": 34377,\n    \"often\": 34378,\n    \"ĠTransformers\": 34379,\n    \"ĠAfterwards\": 34380,\n    \"reated\": 34381,\n    \"Ġpoisonous\": 34382,\n    \"Ġgeographically\": 34383,\n    \"Ġmell\": 34384,\n    \"Cross\": 34385,\n    \"Ġdeductible\": 34386,\n    \"ĠZionist\": 34387,\n    \"Ġcutter\": 34388,\n    \"ĠRP\": 34389,\n    \"ĠImag\": 34390,\n    \"Ġoverflow\": 34391,\n    \"358\": 34392,\n    \"ĠADD\": 34393,\n    \"bones\": 34394,\n    \"Ġflattened\": 34395,\n    \"ĠGREEN\": 34396,\n    \"Ġlaure\": 34397,\n    \"haps\": 34398,\n    \"ĠCellular\": 34399,\n    \"kens\": 34400,\n    \"363\": 34401,\n    \"ĠSmash\": 34402,\n    \"ĠSpeak\": 34403,\n    \"ĠMaiden\": 34404,\n    \"Ġgreedy\": 34405,\n    \"ĠManit\": 34406,\n    \"Ġfacet\": 34407,\n    \"ĠGPA\": 34408,\n    \"Ġracks\": 34409,\n    \"popular\": 34410,\n    \"322\": 34411,\n    \"ĠBars\": 34412,\n    \"avement\": 34413,\n    \"359\": 34414,\n    \"Ġpomp\": 34415,\n    \"Ġregisters\": 34416,\n    \"Fs\": 34417,\n    \"ĠLoving\": 34418,\n    \"ĠTaxi\": 34419,\n    \"concert\": 34420,\n    \"ĠArchae\": 34421,\n    \"Ġcurls\": 34422,\n    \"ĠSpit\": 34423,\n    \"ĠLIFE\": 34424,\n    \"Ġinvade\": 34425,\n    \"rolog\": 34426,\n    \"wreck\": 34427,\n    \"Ġconflicted\": 34428,\n    \"Ġ970\": 34429,\n    \"Ġexiled\": 34430,\n    \"Ġchew\": 34431,\n    \"udging\": 34432,\n    \"Ġexper\": 34433,\n    \"ĠFt\": 34434,\n    \"rius\": 34435,\n    \"ĠXer\": 34436,\n    \"~\": 34437,\n    \"Ġbandwagon\": 34438,\n    \"Fore\": 34439,\n    \"Cat\": 34440,\n    \"Ġoverflowing\": 34441,\n    \"Ġradios\": 34442,\n    \"Much\": 34443,\n    \"Ġfacilitates\": 34444,\n    \"ĠCaf\": 34445,\n    \"ĠQing\": 34446,\n    \"Use\": 34447,\n    \"Ġmang\": 34448,\n    \"Ġpissed\": 34449,\n    \"ĠOuter\": 34450,\n    \"within\": 34451,\n    \"ĠSchr\": 34452,\n    \"ĠSherlock\": 34453,\n    \"Ġ336\": 34454,\n    \"Ġcasc\": 34455,\n    \"chens\": 34456,\n    \"incent\": 34457,\n    \"Ġcultivating\": 34458,\n    \"ampions\": 34459,\n    \"Ġwasteful\": 34460,\n    \"adays\": 34461,\n    \"sets\": 34462,\n    \"ĠLF\": 34463,\n    \"watching\": 34464,\n    \"Ġabandonment\": 34465,\n    \"ĠJesuit\": 34466,\n    \"Ġlegislatures\": 34467,\n    \"regnancy\": 34468,\n    \"ĠColt\": 34469,\n    \"Ġinterns\": 34470,\n    \"Ġundertook\": 34471,\n    \"ĠIPA\": 34472,\n    \"ĠInstall\": 34473,\n    \"nsics\": 34474,\n    \"washer\": 34475,\n    \"Ġbeginners\": 34476,\n    \"ĠDiseases\": 34477,\n    \"Ġlimp\": 34478,\n    \"ĠESA\": 34479,\n    \"Basically\": 34480,\n    \"Ġprud\": 34481,\n    \"LED\": 34482,\n    \"Ġgrease\": 34483,\n    \"ousel\": 34484,\n    \"Ġrotten\": 34485,\n    \"ĠCele\": 34486,\n    \"facts\": 34487,\n    \"ĠLouie\": 34488,\n    \"ĠISI\": 34489,\n    \"481\": 34490,\n    \"Ġsett\": 34491,\n    \"Ġtoug\": 34492,\n    \"ĠReck\": 34493,\n    \"OUNT\": 34494,\n    \"ĠFou\": 34495,\n    \"Ġinhibitor\": 34496,\n    \"gru\": 34497,\n    \"bane\": 34498,\n    \"1980\": 34499,\n    \"ĠPanc\": 34500,\n    \"Ġsuperficial\": 34501,\n    \"Ġauthoritative\": 34502,\n    \"ĠVOL\": 34503,\n    \"790\": 34504,\n    \"Ġcrusade\": 34505,\n    \"airy\": 34506,\n    \"Ġemphatically\": 34507,\n    \"Ġflourishing\": 34508,\n    \"Ġ416\": 34509,\n    \"Ġheroine\": 34510,\n    \"inx\": 34511,\n    \"Ġanch\": 34512,\n    \"stretched\": 34513,\n    \"ĠRegener\": 34514,\n    \"ĠAncient\": 34515,\n    \"evaluate\": 34516,\n    \"Ġantibody\": 34517,\n    \"ĠEston\": 34518,\n    \"ĠAeg\": 34519,\n    \"Ġboldly\": 34520,\n    \"TN\": 34521,\n    \"ĠPercentage\": 34522,\n    \"Ġ747\": 34523,\n    \"Ġrapt\": 34524,\n    \"ĠEdited\": 34525,\n    \"Earth\": 34526,\n    \"phal\": 34527,\n    \"ĠXXX\": 34528,\n    \"arling\": 34529,\n    \"ĠReligion\": 34530,\n    \"Ġ503\": 34531,\n    \"forces\": 34532,\n    \"Ġendpoint\": 34533,\n    \"Miller\": 34534,\n    \"Ba\": 34535,\n    \"Ġdisappears\": 34536,\n    \"andre\": 34537,\n    \"Ġconnector\": 34538,\n    \"407\": 34539,\n    \"ĠTOUR\": 34540,\n    \"aura\": 34541,\n    \"ĠRazer\": 34542,\n    \"UPDATE\": 34543,\n    \"Ġcalib\": 34544,\n    \"original\": 34545,\n    \"ĠMonkey\": 34546,\n    \"Ir\": 34547,\n    \"Ġexacerb\": 34548,\n    \"killing\": 34549,\n    \"Ġforb\": 34550,\n    \"native\": 34551,\n    \"Ġpoking\": 34552,\n    \"Ġveiled\": 34553,\n    \"mails\": 34554,\n    \"Ġalphabet\": 34555,\n    \"Ġawkwardly\": 34556,\n    \"ĠNames\": 34557,\n    \"Ġspiders\": 34558,\n    \"ĠParam\": 34559,\n    \"ĠColour\": 34560,\n    \"Ġunification\": 34561,\n    \"ĠPione\": 34562,\n    \"Ġoffend\": 34563,\n    \"Ġscoff\": 34564,\n    \"ĠSAR\": 34565,\n    \"ĠBuildings\": 34566,\n    \"edes\": 34567,\n    \"ĠAke\": 34568,\n    \"Ġfirmware\": 34569,\n    \"Madison\": 34570,\n    \"policy\": 34571,\n    \"ĠComputing\": 34572,\n    \"ĠRW\": 34573,\n    \"Ġfluent\": 34574,\n    \"Ġdece\": 34575,\n    \"Ġswore\": 34576,\n    \"Ġrestaur\": 34577,\n    \"Ġpresses\": 34578,\n    \"ophon\": 34579,\n    \"Ġphilosopher\": 34580,\n    \"ften\": 34581,\n    \"Ġintruder\": 34582,\n    \"Ġleng\": 34583,\n    \"ĠCowboy\": 34584,\n    \"cled\": 34585,\n    \"Ġmeticulously\": 34586,\n    \"ĠPair\": 34587,\n    \"ĠEND\": 34588,\n    \"Ġcapsules\": 34589,\n    \"Ġauxiliary\": 34590,\n    \"Ġverses\": 34591,\n    \"Ġsheltered\": 34592,\n    \"Ġexplorer\": 34593,\n    \"ĠWolverine\": 34594,\n    \"auts\": 34595,\n    \"Ġinhibitors\": 34596,\n    \"ĠPeng\": 34597,\n    \"ĠValve\": 34598,\n    \"imar\": 34599,\n    \"Ġchuck\": 34600,\n    \"ĠRecording\": 34601,\n    \"Ġardu\": 34602,\n    \"Test\": 34603,\n    \"Ġinterven\": 34604,\n    \"Ġchrome\": 34605,\n    \"months\": 34606,\n    \"tap\": 34607,\n    \"ĠManz\": 34608,\n    \"format\": 34609,\n    \"ĠBalkans\": 34610,\n    \"Ġannex\": 34611,\n    \"uder\": 34612,\n    \"ĠAAC\": 34613,\n    \"Ġdisturbances\": 34614,\n    \"354\": 34615,\n    \"asms\": 34616,\n    \"ĠTad\": 34617,\n    \"puting\": 34618,\n    \"Ġfateful\": 34619,\n    \"imen\": 34620,\n    \"Ġaudi\": 34621,\n    \"ĠNewsweek\": 34622,\n    \"Around\": 34623,\n    \"Ġretribution\": 34624,\n    \"Ġsugars\": 34625,\n    \"Ġescapes\": 34626,\n    \"Ġlegitim\": 34627,\n    \"ĠProof\": 34628,\n    \"Ġmisogyn\": 34629,\n    \"cit\": 34630,\n    \"Ġclutching\": 34631,\n    \"exist\": 34632,\n    \"Ġrevol\": 34633,\n    \"Ġdiscs\": 34634,\n    \"discrimination\": 34635,\n    \"Ġstout\": 34636,\n    \"aline\": 34637,\n    \"ĠRandom\": 34638,\n    \"364\": 34639,\n    \"Ġapprehension\": 34640,\n    \"Ġmockery\": 34641,\n    \"Ġfossils\": 34642,\n    \"ĠStress\": 34643,\n    \"Ġbenefic\": 34644,\n    \"exc\": 34645,\n    \"lude\": 34646,\n    \"Small\": 34647,\n    \"Ġgh\": 34648,\n    \"Ġobserves\": 34649,\n    \"ĠSUP\": 34650,\n    \"Ġbrewer\": 34651,\n    \"ĠESP\": 34652,\n    \"Ġomitted\": 34653,\n    \"multiple\": 34654,\n    \"Ġminimizing\": 34655,\n    \"Ġtaco\": 34656,\n    \"Ġindifferent\": 34657,\n    \"medi\": 34658,\n    \"available\": 34659,\n    \"Ġ252\": 34660,\n    \"Ġsanity\": 34661,\n    \"ĠCookie\": 34662,\n    \"mostly\": 34663,\n    \"near\": 34664,\n    \"NASA\": 34665,\n    \"Ġlowly\": 34666,\n    \"seless\": 34667,\n    \"Ġobsess\": 34668,\n    \"itous\": 34669,\n    \"Dispatch\": 34670,\n    \"Ġcanyon\": 34671,\n    \"Ġbriefs\": 34672,\n    \"Say\": 34673,\n    \"ĠNato\": 34674,\n    \"ĠSpend\": 34675,\n    \"Ġ242\": 34676,\n    \"ĠEthernet\": 34677,\n    \"Ġmatte\": 34678,\n    \"ĠStim\": 34679,\n    \"hetics\": 34680,\n    \"Ġflourished\": 34681,\n    \"389\": 34682,\n    \"ĠMcA\": 34683,\n    \"695\": 34684,\n    \"Ġoverr\": 34685,\n    \"Ġtorment\": 34686,\n    \"Ġpirate\": 34687,\n    \"ĠJohann\": 34688,\n    \"roversial\": 34689,\n    \"ĠUnemployment\": 34690,\n    \"breakers\": 34691,\n    \"ĠMessages\": 34692,\n    \"tones\": 34693,\n    \"Ġtagging\": 34694,\n    \"Ġfrog\": 34695,\n    \"Jewish\": 34696,\n    \"Ġmessenger\": 34697,\n    \"Ġexasper\": 34698,\n    \"ernaut\": 34699,\n    \"Ġnarrower\": 34700,\n    \"ĠCatalyst\": 34701,\n    \"ĠSecrets\": 34702,\n    \"Ġadj\": 34703,\n    \"ĠFug\": 34704,\n    \"Ġaura\": 34705,\n    \"Ġtherape\": 34706,\n    \"mber\": 34707,\n    \"Ġcaliphate\": 34708,\n    \"Ġretreating\": 34709,\n    \"ĠComput\": 34710,\n    \"Ġburying\": 34711,\n    \"Ġail\": 34712,\n    \"Ġgriev\": 34713,\n    \"lins\": 34714,\n    \"825\": 34715,\n    \"tten\": 34716,\n    \"ifully\": 34717,\n    \"ĠTrials\": 34718,\n    \"igma\": 34719,\n    \"Ġ1914\": 34720,\n    \"Ġcoordinates\": 34721,\n    \"ocusing\": 34722,\n    \"ĠFeng\": 34723,\n    \"ĠWhale\": 34724,\n    \"Ġshorten\": 34725,\n    \"Ġcorrectness\": 34726,\n    \"evil\": 34727,\n    \"network\": 34728,\n    \"Ġreactive\": 34729,\n    \"assuming\": 34730,\n    \"ĠLaksh\": 34731,\n    \"games\": 34732,\n    \"Ġruining\": 34733,\n    \"excluding\": 34734,\n    \"annels\": 34735,\n    \"Âº\": 34736,\n    \"Ġrubbed\": 34737,\n    \"aleb\": 34738,\n    \"flex\": 34739,\n    \"iped\": 34740,\n    \"ĠLimit\": 34741,\n    \"allowed\": 34742,\n    \"ĠDMV\": 34743,\n    \"ĠLD\": 34744,\n    \"Ġstamina\": 34745,\n    \"conduct\": 34746,\n    \"Ġmislead\": 34747,\n    \"lib\": 34748,\n    \"ĠEminem\": 34749,\n    \"Ġpayoff\": 34750,\n    \"Ġkernel\": 34751,\n    \"Ġsweeps\": 34752,\n    \"Ġsonic\": 34753,\n    \"ĠKodi\": 34754,\n    \"unique\": 34755,\n    \"Ġsurrog\": 34756,\n    \"Michigan\": 34757,\n    \"Ġattest\": 34758,\n    \"Ġdummy\": 34759,\n    \"ĠStellar\": 34760,\n    \"ĠSquadron\": 34761,\n    \"ĠHait\": 34762,\n    \"ĠSpirits\": 34763,\n    \"605\": 34764,\n    \"ĠHemisphere\": 34765,\n    \"legram\": 34766,\n    \"ĠRack\": 34767,\n    \"opol\": 34768,\n    \"Ġfreshwater\": 34769,\n    \"cession\": 34770,\n    \"Ġabort\": 34771,\n    \"ĠLOG\": 34772,\n    \"Ġfuzzy\": 34773,\n    \"Ġcrystall\": 34774,\n    \"illation\": 34775,\n    \"ĠFreddy\": 34776,\n    \"Ġsalvation\": 34777,\n    \"Ġjuxtap\": 34778,\n    \"weekly\": 34779,\n    \"usha\": 34780,\n    \"456\": 34781,\n    \"Ġ660\": 34782,\n    \"ĠGlacier\": 34783,\n    \"Ġnegatives\": 34784,\n    \"Ġillegitimate\": 34785,\n    \"ĠProtein\": 34786,\n    \"Moore\": 34787,\n    \"Der\": 34788,\n    \"Ġinfancy\": 34789,\n    \"Again\": 34790,\n    \"ALD\": 34791,\n    \"Leon\": 34792,\n    \"ĠIdeally\": 34793,\n    \"fresh\": 34794,\n    \"730\": 34795,\n    \"Ġgamb\": 34796,\n    \"Ġscrewed\": 34797,\n    \"wow\": 34798,\n    \"Ġembodied\": 34799,\n    \"ĠCinderella\": 34800,\n    \"341\": 34801,\n    \"ĠPiano\": 34802,\n    \"Ġbroccoli\": 34803,\n    \"Ġmats\": 34804,\n    \"ĠZheng\": 34805,\n    \"cream\": 34806,\n    \"anut\": 34807,\n    \"ĠZig\": 34808,\n    \"Columb\": 34809,\n    \"ĠTibetan\": 34810,\n    \"Death\": 34811,\n    \"Ġstren\": 34812,\n    \"ĠVertical\": 34813,\n    \"Ġratification\": 34814,\n    \"Ġprincipally\": 34815,\n    \"ELD\": 34816,\n    \"Ġforbid\": 34817,\n    \"Ġamalg\": 34818,\n    \"blind\": 34819,\n    \"auri\": 34820,\n    \"stery\": 34821,\n    \"Ġbarley\": 34822,\n    \"FBI\": 34823,\n    \"ĠHex\": 34824,\n    \"925\": 34825,\n    \"Domin\": 34826,\n    \"oat\": 34827,\n    \"Ġswayed\": 34828,\n    \"ĠKKK\": 34829,\n    \"ĠTaxes\": 34830,\n    \"Ġker\": 34831,\n    \"eeper\": 34832,\n    \"ĠAwakens\": 34833,\n    \"ĠPix\": 34834,\n    \"ĠKING\": 34835,\n    \"dc\": 34836,\n    \"Ren\": 34837,\n    \"Ġlegitimately\": 34838,\n    \"ĠTriumph\": 34839,\n    \"ĠSites\": 34840,\n    \"ĠSai\": 34841,\n    \"tl\": 34842,\n    \"painted\": 34843,\n    \"ĠWaiting\": 34844,\n    \"starting\": 34845,\n    \"parents\": 34846,\n    \"ĠDuo\": 34847,\n    \"eele\": 34848,\n    \"upper\": 34849,\n    \"ĠInvestig\": 34850,\n    \"Ġeighteen\": 34851,\n    \"Ġcorrelated\": 34852,\n    \"ĠCascade\": 34853,\n    \"acca\": 34854,\n    \"ĠAlph\": 34855,\n    \"ĠPolic\": 34856,\n    \"ĠEVs\": 34857,\n    \"Ġworthless\": 34858,\n    \"ĠIndust\": 34859,\n    \"auld\": 34860,\n    \"ĠYiannopoulos\": 34861,\n    \"ĠEzra\": 34862,\n    \"Ġmorphed\": 34863,\n    \"Ġoriginating\": 34864,\n    \"mania\": 34865,\n    \"Ġsparing\": 34866,\n    \"Ġextrem\": 34867,\n    \"cre\": 34868,\n    \"ults\": 34869,\n    \"mare\": 34870,\n    \"classified\": 34871,\n    \"Ġparachute\": 34872,\n    \"Ġmistrust\": 34873,\n    \"ONT\": 34874,\n    \"Mind\": 34875,\n    \"Ġthru\": 34876,\n    \"707\": 34877,\n    \"ĠTwain\": 34878,\n    \"Ġmelodies\": 34879,\n    \"ĠDanger\": 34880,\n    \"ĠDPS\": 34881,\n    \"Ġderive\": 34882,\n    \"Ġdissolution\": 34883,\n    \"Ġchildbirth\": 34884,\n    \"Ġ415\": 34885,\n    \"fork\": 34886,\n    \"solid\": 34887,\n    \"loads\": 34888,\n    \"ĠCGI\": 34889,\n    \"378\": 34890,\n    \"ĠShed\": 34891,\n    \"Face\": 34892,\n    \"Ġcomet\": 34893,\n    \"iceps\": 34894,\n    \"ĠReduction\": 34895,\n    \"Fly\": 34896,\n    \"jp\": 34897,\n    \"ĠAnimation\": 34898,\n    \"Luke\": 34899,\n    \"Ġabiding\": 34900,\n    \"Ġdevise\": 34901,\n    \"ĠAe\": 34902,\n    \"Ġflux\": 34903,\n    \"Ġbras\": 34904,\n    \"Ġfracturing\": 34905,\n    \"Ġinventive\": 34906,\n    \"ĠGranger\": 34907,\n    \"Ġsap\": 34908,\n    \"inducing\": 34909,\n    \"Ġreviewers\": 34910,\n    \"Officers\": 34911,\n    \"ĠWHY\": 34912,\n    \"Ġamplify\": 34913,\n    \"Ġentr\": 34914,\n    \"Ġslit\": 34915,\n    \"457\": 34916,\n    \"Ġreformed\": 34917,\n    \"ĠPhi\": 34918,\n    \"Ġtempt\": 34919,\n    \"Ġcontradiction\": 34920,\n    \"585\": 34921,\n    \"ĠMaced\": 34922,\n    \"371\": 34923,\n    \"kinson\": 34924,\n    \"robe\": 34925,\n    \"ĠHunters\": 34926,\n    \"astern\": 34927,\n    \"criminal\": 34928,\n    \"jew\": 34929,\n    \"Ġdecentralized\": 34930,\n    \"bands\": 34931,\n    \"Ġavatar\": 34932,\n    \"ĠBarrier\": 34933,\n    \"Ġcharacterization\": 34934,\n    \"student\": 34935,\n    \"Ġgays\": 34936,\n    \"Ġspecialize\": 34937,\n    \"ĠJudging\": 34938,\n    \"Ġinitiation\": 34939,\n    \"Ġshove\": 34940,\n    \"Ġpirates\": 34941,\n    \"Ġfictitious\": 34942,\n    \"ĠPoker\": 34943,\n    \"ĠElsa\": 34944,\n    \"ĠTECH\": 34945,\n    \"handedly\": 34946,\n    \"Ġglued\": 34947,\n    \"Ġclinically\": 34948,\n    \"Ġinaccessible\": 34949,\n    \"Ġderegulation\": 34950,\n    \"Ġprohib\": 34951,\n    \"Ġdangling\": 34952,\n    \"Ġnoses\": 34953,\n    \"Ġstash\": 34954,\n    \"Ø§Ø\": 34955,\n    \"ESH\": 34956,\n    \"Ġmonstrous\": 34957,\n    \"Ġcrept\": 34958,\n    \"ĠCharm\": 34959,\n    \"Ġbeh\": 34960,\n    \"Ġshuts\": 34961,\n    \"Ġ236\": 34962,\n    \"imedia\": 34963,\n    \"445\": 34964,\n    \"Du\": 34965,\n    \"Ġafar\": 34966,\n    \"ĠRout\": 34967,\n    \"Ġflares\": 34968,\n    \"Utah\": 34969,\n    \"Ġ808\": 34970,\n    \"Ġjewels\": 34971,\n    \"2004\": 34972,\n    \"Ġrecal\": 34973,\n    \"Gas\": 34974,\n    \"ĠExcellent\": 34975,\n    \"Ġpitfalls\": 34976,\n    \"ĠDrawing\": 34977,\n    \"viously\": 34978,\n    \"angered\": 34979,\n    \"changes\": 34980,\n    \"Ġpasture\": 34981,\n    \"talking\": 34982,\n    \"Ġinequ\": 34983,\n    \"Ġbicycl\": 34984,\n    \"Cost\": 34985,\n    \"423\": 34986,\n    \"bard\": 34987,\n    \"Ġanterior\": 34988,\n    \"ecast\": 34989,\n    \"CHR\": 34990,\n    \"397\": 34991,\n    \"masters\": 34992,\n    \"706\": 34993,\n    \"ĠFinish\": 34994,\n    \"Yet\": 34995,\n    \"study\": 34996,\n    \"ĠCogn\": 34997,\n    \"Ġloaf\": 34998,\n    \"Ġspatial\": 34999,\n    \"ĠParad\": 35000,\n    \"batch\": 35001,\n    \"Ġvents\": 35002,\n    \"Ġspins\": 35003,\n    \"ĠAddiction\": 35004,\n    \"Ġcondone\": 35005,\n    \"Ġproble\": 35006,\n    \"English\": 35007,\n    \"ĠRomans\": 35008,\n    \"ĠSaying\": 35009,\n    \"ĠKling\": 35010,\n    \"Universal\": 35011,\n    \"ivist\": 35012,\n    \"Ġskirm\": 35013,\n    \"Ġ2500\": 35014,\n    \"Ġ263\": 35015,\n    \"aired\": 35016,\n    \"ĠMartian\": 35017,\n    \"ĠCompensation\": 35018,\n    \"lation\": 35019,\n    \"ĠSalam\": 35020,\n    \"LGBT\": 35021,\n    \"ĠDart\": 35022,\n    \"strike\": 35023,\n    \"vasive\": 35024,\n    \"ILLE\": 35025,\n    \"Ġimaginative\": 35026,\n    \"ĠEuph\": 35027,\n    \"Financial\": 35028,\n    \"Ġholog\": 35029,\n    \"orah\": 35030,\n    \"crit\": 35031,\n    \"ĠOswald\": 35032,\n    \"512\": 35033,\n    \"ĠUri\": 35034,\n    \"Ġdiscrepancies\": 35035,\n    \"Ġbeads\": 35036,\n    \"ĠShots\": 35037,\n    \"Mem\": 35038,\n    \"Ġhunts\": 35039,\n    \"Ġsubtly\": 35040,\n    \"Ġ470\": 35041,\n    \"ĠVigil\": 35042,\n    \"Ġsew\": 35043,\n    \"ĠBurma\": 35044,\n    \"igm\": 35045,\n    \"ighed\": 35046,\n    \"swe\": 35047,\n    \"Ġ251\": 35048,\n    \"Ġdeceit\": 35049,\n    \"Ġphysi\": 35050,\n    \"iflower\": 35051,\n    \"ĠCert\": 35052,\n    \"Ġchewing\": 35053,\n    \"rax\": 35054,\n    \"ĠMER\": 35055,\n    \"icient\": 35056,\n    \"Les\": 35057,\n    \"Ġ390\": 35058,\n    \"Ġperjury\": 35059,\n    \"Ġfiltering\": 35060,\n    \"770\": 35061,\n    \"Ġpoppy\": 35062,\n    \"Ġbland\": 35063,\n    \"ĠNasa\": 35064,\n    \"Ġorbiting\": 35065,\n    \"ĠRipple\": 35066,\n    \"otal\": 35067,\n    \"ĠRyu\": 35068,\n    \"ĠShap\": 35069,\n    \"ĠJian\": 35070,\n    \"Ġpiv\": 35071,\n    \"ĠNeptune\": 35072,\n    \"rary\": 35073,\n    \"Ġunavoidable\": 35074,\n    \"Ġguideline\": 35075,\n    \"Ġwaterfall\": 35076,\n    \"inators\": 35077,\n    \"ĠLogic\": 35078,\n    \"ĠPlug\": 35079,\n    \"role\": 35080,\n    \"Ġalterations\": 35081,\n    \"ĠSett\": 35082,\n    \"ĠFeld\": 35083,\n    \"Ġfreezes\": 35084,\n    \"Ġbedrock\": 35085,\n    \"ĠVIEW\": 35086,\n    \"ovation\": 35087,\n    \"Ġneedless\": 35088,\n    \"ĠIU\": 35089,\n    \"ignant\": 35090,\n    \"ĠConfeder\": 35091,\n    \"316\": 35092,\n    \"fine\": 35093,\n    \"Ġjars\": 35094,\n    \"gotten\": 35095,\n    \"Bron\": 35096,\n    \"Ġmindfulness\": 35097,\n    \"imating\": 35098,\n    \"Ġhysteria\": 35099,\n    \"Ġhurried\": 35100,\n    \"Ġinfantry\": 35101,\n    \"ĠNYU\": 35102,\n    \"tags\": 35103,\n    \"Penn\": 35104,\n    \"Ġtracing\": 35105,\n    \"ĠSwing\": 35106,\n    \"ĠIo\": 35107,\n    \"Ġreckoned\": 35108,\n    \"ĠRecall\": 35109,\n    \"ĠVersion\": 35110,\n    \"314\": 35111,\n    \"Ġecology\": 35112,\n    \"Ġarmoured\": 35113,\n    \"Ġresonance\": 35114,\n    \"970\": 35115,\n    \"Ġvigilance\": 35116,\n    \"Ġrede\": 35117,\n    \"ĠBohem\": 35118,\n    \"Ġchau\": 35119,\n    \"ĠDevi\": 35120,\n    \"Ġtru\": 35121,\n    \"))\": 35122,\n    \"Put\": 35123,\n    \"Ġflavored\": 35124,\n    \"ĠClown\": 35125,\n    \"Senate\": 35126,\n    \"ĠScandinavian\": 35127,\n    \"mable\": 35128,\n    \"Residents\": 35129,\n    \"ĠFranchise\": 35130,\n    \"Ġprecincts\": 35131,\n    \"Prem\": 35132,\n    \"ĠNeutral\": 35133,\n    \"coal\": 35134,\n    \"Ġdelinqu\": 35135,\n    \"Mus\": 35136,\n    \"UME\": 35137,\n    \"Ġtedious\": 35138,\n    \"roots\": 35139,\n    \"ĠCondition\": 35140,\n    \"ĠIntercept\": 35141,\n    \"017\": 35142,\n    \"itives\": 35143,\n    \"Ġdefinitively\": 35144,\n    \"Ġobliter\": 35145,\n    \"Ġclandestine\": 35146,\n    \"Ġstagnation\": 35147,\n    \"Ġblindness\": 35148,\n    \"abiding\": 35149,\n    \"Ġremix\": 35150,\n    \"feeding\": 35151,\n    \"Ġunrecogn\": 35152,\n    \"2003\": 35153,\n    \"960\": 35154,\n    \"381\": 35155,\n    \"Ġbulky\": 35156,\n    \"xia\": 35157,\n    \"ivered\": 35158,\n    \"inic\": 35159,\n    \"ĠSoci\": 35160,\n    \"ĠYards\": 35161,\n    \"Ġhides\": 35162,\n    \"Film\": 35163,\n    \"Ġtestim\": 35164,\n    \"Ġblacklist\": 35165,\n    \"Deep\": 35166,\n    \"Standard\": 35167,\n    \"ĠClash\": 35168,\n    \"Ġriddled\": 35169,\n    \"Ġdiseng\": 35170,\n    \"ĠTRE\": 35171,\n    \"ĠIDs\": 35172,\n    \"Ġmigrating\": 35173,\n    \"protect\": 35174,\n    \"Ġgraded\": 35175,\n    \"Ġvaguely\": 35176,\n    \"ĠCharacter\": 35177,\n    \"382\": 35178,\n    \"ĠMOD\": 35179,\n    \"Eng\": 35180,\n    \"Ġmobilized\": 35181,\n    \"Ġsincerity\": 35182,\n    \"Ġ317\": 35183,\n    \"sighted\": 35184,\n    \"ownt\": 35185,\n    \"ĠâĢİ\": 35186,\n    \"umpy\": 35187,\n    \"Ġitching\": 35188,\n    \"ĠVerd\": 35189,\n    \"cook\": 35190,\n    \"Ġsimulator\": 35191,\n    \"players\": 35192,\n    \"Early\": 35193,\n    \"infeld\": 35194,\n    \"Ġmaximizing\": 35195,\n    \"Philipp\": 35196,\n    \"ĠPhotoshop\": 35197,\n    \"Ġdestroys\": 35198,\n    \"Ġbefriend\": 35199,\n    \"Ġfilthy\": 35200,\n    \"ĠIncident\": 35201,\n    \"gha\": 35202,\n    \"Ġcomplicity\": 35203,\n    \"Ġmessing\": 35204,\n    \"YA\": 35205,\n    \"ĠNegro\": 35206,\n    \"adows\": 35207,\n    \"374\": 35208,\n    \"Ġpip\": 35209,\n    \"cean\": 35210,\n    \"Ġ1924\": 35211,\n    \"Sent\": 35212,\n    \"represent\": 35213,\n    \"Ġdeems\": 35214,\n    \"ĠRue\": 35215,\n    \"Ġtitanium\": 35216,\n    \"Ġmanners\": 35217,\n    \"âĢ¦âĢ¦\": 35218,\n    \"bare\": 35219,\n    \"Ġusur\": 35220,\n    \"mma\": 35221,\n    \"ĠPanda\": 35222,\n    \"ulus\": 35223,\n    \"ĠSlav\": 35224,\n    \"324\": 35225,\n    \"ĠMole\": 35226,\n    \"^\": 35227,\n    \"micro\": 35228,\n    \"foreign\": 35229,\n    \"lest\": 35230,\n    \"ocular\": 35231,\n    \"ĠUniv\": 35232,\n    \"ĠFrag\": 35233,\n    \"Ġshepherd\": 35234,\n    \"Ġelectron\": 35235,\n    \"ĠFSA\": 35236,\n    \"Ġunl\": 35237,\n    \"dose\": 35238,\n    \"Ġimmersion\": 35239,\n    \"ĠDeL\": 35240,\n    \"Ġbiomedical\": 35241,\n    \"Anna\": 35242,\n    \"Ġskillet\": 35243,\n    \"Ġrecre\": 35244,\n    \"Ġtrillions\": 35245,\n    \"voy\": 35246,\n    \"Ġnormalized\": 35247,\n    \"radio\": 35248,\n    \"cue\": 35249,\n    \"urbed\": 35250,\n    \"Ġthinkers\": 35251,\n    \"328\": 35252,\n    \"327\": 35253,\n    \"ĠForge\": 35254,\n    \"505\": 35255,\n    \"Ġunbearable\": 35256,\n    \"olini\": 35257,\n    \"Ġdisinfect\": 35258,\n    \"Ġshaving\": 35259,\n    \"Ġtoxicity\": 35260,\n    \"453\": 35261,\n    \"Ġheterosexual\": 35262,\n    \"Baltimore\": 35263,\n    \"Ġstool\": 35264,\n    \"lr\": 35265,\n    \"ĠMk\": 35266,\n    \"Ġantidote\": 35267,\n    \"Dark\": 35268,\n    \"810\": 35269,\n    \"Ġirritated\": 35270,\n    \"ĠSUPPORT\": 35271,\n    \"Chance\": 35272,\n    \"bent\": 35273,\n    \"ĠZelda\": 35274,\n    \"ĠPenguin\": 35275,\n    \"ifled\": 35276,\n    \"Ġarte\": 35277,\n    \"705\": 35278,\n    \"Ġcondol\": 35279,\n    \"izza\": 35280,\n    \"ĠCK\": 35281,\n    \"Ġprojector\": 35282,\n    \"ravings\": 35283,\n    \"Ġ1919\": 35284,\n    \"Ġburner\": 35285,\n    \"ĠSchwarz\": 35286,\n    \"Oregon\": 35287,\n    \"Ġridicule\": 35288,\n    \"Ġinstructional\": 35289,\n    \"Ġ\\\"#\": 35290,\n    \"ĠDign\": 35291,\n    \"Ġkitten\": 35292,\n    \"Ġconstit\": 35293,\n    \"iration\": 35294,\n    \"Speed\": 35295,\n    \"ecycle\": 35296,\n    \"ĠFalse\": 35297,\n    \"ĠDealer\": 35298,\n    \"Could\": 35299,\n    \"655\": 35300,\n    \"outside\": 35301,\n    \"Ġworldview\": 35302,\n    \"Ġ246\": 35303,\n    \"Ġspitting\": 35304,\n    \"595\": 35305,\n    \"MN\": 35306,\n    \"ĠComes\": 35307,\n    \"ingu\": 35308,\n    \"Ġenzymes\": 35309,\n    \"Ġcompass\": 35310,\n    \"Ġexclaimed\": 35311,\n    \"ĠMalays\": 35312,\n    \"Ġ1916\": 35313,\n    \"Ġcoloring\": 35314,\n    \"Ġrepeats\": 35315,\n    \"Ġsoils\": 35316,\n    \"Ġtrivia\": 35317,\n    \"ĠIsles\": 35318,\n    \"Const\": 35319,\n    \"ĠFiction\": 35320,\n    \"665\": 35321,\n    \"Ġcriminality\": 35322,\n    \"ĠZi\": 35323,\n    \"384\": 35324,\n    \"ĠWilderness\": 35325,\n    \"ĠCanary\": 35326,\n    \"ĠVs\": 35327,\n    \"Ð¸\": 35328,\n    \"ĠAPIs\": 35329,\n    \"Ġbehest\": 35330,\n    \"Ġeb\": 35331,\n    \"ĠHipp\": 35332,\n    \"Ġpreempt\": 35333,\n    \"Ġevoke\": 35334,\n    \"Ġinept\": 35335,\n    \"tele\": 35336,\n    \"447\": 35337,\n    \"ĠGarmin\": 35338,\n    \"Ġpursuits\": 35339,\n    \"351\": 35340,\n    \"ĠclichÃ©\": 35341,\n    \"ĠJihad\": 35342,\n    \"Ġ308\": 35343,\n    \"ĠSnake\": 35344,\n    \"ĠAnnounce\": 35345,\n    \"Nearly\": 35346,\n    \"!'\\\"\": 35347,\n    \"Ġ1927\": 35348,\n    \"saw\": 35349,\n    \"Ġabhor\": 35350,\n    \"Plan\": 35351,\n    \"rawled\": 35352,\n    \"ĠRiy\": 35353,\n    \"ensor\": 35354,\n    \"Fal\": 35355,\n    \"quick\": 35356,\n    \"odynamic\": 35357,\n    \"Ġsubstitution\": 35358,\n    \"Ġprovoking\": 35359,\n    \"Operation\": 35360,\n    \"rupulous\": 35361,\n    \"Ġsweetness\": 35362,\n    \"folk\": 35363,\n    \"ĠDefault\": 35364,\n    \"Ġstarved\": 35365,\n    \"ĠPrinting\": 35366,\n    \"urious\": 35367,\n    \"ĠTracker\": 35368,\n    \"them\": 35369,\n    \"Ġleth\": 35370,\n    \"Ġemptied\": 35371,\n    \"Ġfootprints\": 35372,\n    \"ilian\": 35373,\n    \"Ġbattalion\": 35374,\n    \"Ġprophet\": 35375,\n    \"Ġrailing\": 35376,\n    \"Ġhect\": 35377,\n    \"rouch\": 35378,\n    \"lees\": 35379,\n    \"Ġideologies\": 35380,\n    \"Ġ254\": 35381,\n    \"ĠGods\": 35382,\n    \"ĠAvalon\": 35383,\n    \"Ġfrontrunner\": 35384,\n    \"ĠPork\": 35385,\n    \"ĠPipe\": 35386,\n    \"Ġscaven\": 35387,\n    \"Ġming\": 35388,\n    \"Ġerg\": 35389,\n    \"Ġ520\": 35390,\n    \"Ġhatched\": 35391,\n    \"asant\": 35392,\n    \"ĠHI\": 35393,\n    \"Ġpend\": 35394,\n    \"Ġ288\": 35395,\n    \"Prom\": 35396,\n    \"achev\": 35397,\n    \"ĠEcology\": 35398,\n    \"enforcement\": 35399,\n    \"467\": 35400,\n    \"dule\": 35401,\n    \"Ġrealism\": 35402,\n    \"ĠTypes\": 35403,\n    \"USB\": 35404,\n    \"utra\": 35405,\n    \"ĠHiroshima\": 35406,\n    \"Ġcontradicted\": 35407,\n    \"393\": 35408,\n    \"ĠDSL\": 35409,\n    \"Ġtherein\": 35410,\n    \"ĠReconstruction\": 35411,\n    \"Ġ243\": 35412,\n    \"irled\": 35413,\n    \"479\": 35414,\n    \"ĠWhats\": 35415,\n    \"Currently\": 35416,\n    \"ĠPOWER\": 35417,\n    \"ĠHiro\": 35418,\n    \"ĠBreath\": 35419,\n    \"ĠYourself\": 35420,\n    \"Ġlantern\": 35421,\n    \"376\": 35422,\n    \"É\": 35423,\n    \"ĠHumans\": 35424,\n    \"Lady\": 35425,\n    \"Ġdissemination\": 35426,\n    \"ecake\": 35427,\n    \"ĠChao\": 35428,\n    \"flat\": 35429,\n    \"Ġinspecting\": 35430,\n    \"stration\": 35431,\n    \"Ġidentifiable\": 35432,\n    \"CV\": 35433,\n    \"ĠLobby\": 35434,\n    \"function\": 35435,\n    \"Roll\": 35436,\n    \"DIV\": 35437,\n    \"Tell\": 35438,\n    \"Ġfasc\": 35439,\n    \"ĠAOL\": 35440,\n    \"HM\": 35441,\n    \"Keefe\": 35442,\n    \"Ġporous\": 35443,\n    \"Ġsmoot\": 35444,\n    \"existence\": 35445,\n    \"ĠDeg\": 35446,\n    \"Ġdivor\": 35447,\n    \"isner\": 35448,\n    \"allas\": 35449,\n    \"Bloomberg\": 35450,\n    \"Ġdictators\": 35451,\n    \"ĠGeh\": 35452,\n    \"Ġsilicone\": 35453,\n    \"Ġdab\": 35454,\n    \"Ġmashed\": 35455,\n    \"Ġpric\": 35456,\n    \"might\": 35457,\n    \"ĠBLM\": 35458,\n    \"Ġpatriarch\": 35459,\n    \"Microsoft\": 35460,\n    \"ĠAds\": 35461,\n    \"Ġcoronary\": 35462,\n    \"ĠContrary\": 35463,\n    \"Ġdra\": 35464,\n    \"ĠStarted\": 35465,\n    \"Ġbuckle\": 35466,\n    \"lear\": 35467,\n    \"accept\": 35468,\n    \"Within\": 35469,\n    \"bd\": 35470,\n    \"interested\": 35471,\n    \"bia\": 35472,\n    \"POR\": 35473,\n    \"motion\": 35474,\n    \"ĠFounders\": 35475,\n    \"ĠCassandra\": 35476,\n    \"ĠPassion\": 35477,\n    \"Ġbehavioural\": 35478,\n    \"ĠHealing\": 35479,\n    \"Ġmarkings\": 35480,\n    \"Ġsnowball\": 35481,\n    \"Ġridiculed\": 35482,\n    \"phase\": 35483,\n    \"Ġunto\": 35484,\n    \"aque\": 35485,\n    \"uggets\": 35486,\n    \"Ġfrantically\": 35487,\n    \"Ġcoward\": 35488,\n    \"Ġinconvenient\": 35489,\n    \"Taking\": 35490,\n    \"Afee\": 35491,\n    \"Ġtwisting\": 35492,\n    \"930\": 35493,\n    \"ĠSieg\": 35494,\n    \"ĠGit\": 35495,\n    \"Ġcurs\": 35496,\n    \"ĠGlas\": 35497,\n    \"ĠSignificant\": 35498,\n    \"Ġachieves\": 35499,\n    \"Ġpreferably\": 35500,\n    \"Ġcondensed\": 35501,\n    \"Ġfetus\": 35502,\n    \"Ġunivers\": 35503,\n    \"Ġpse\": 35504,\n    \"Access\": 35505,\n    \"Ġintertwined\": 35506,\n    \"been\": 35507,\n    \"quit\": 35508,\n    \"ĠLEGO\": 35509,\n    \"Ġimagining\": 35510,\n    \"454\": 35511,\n    \"Ġplains\": 35512,\n    \"sequently\": 35513,\n    \"pull\": 35514,\n    \"Fast\": 35515,\n    \"Pot\": 35516,\n    \"yles\": 35517,\n    \"AIR\": 35518,\n    \"Ġblatantly\": 35519,\n    \"eki\": 35520,\n    \"ilated\": 35521,\n    \"ĠMembership\": 35522,\n    \"Ġ262\": 35523,\n    \"Ġ}\": 35524,\n    \"Ġexcavation\": 35525,\n    \"Ġethn\": 35526,\n    \"addin\": 35527,\n    \"Ġfoundational\": 35528,\n    \"ceptions\": 35529,\n    \"ĠViet\": 35530,\n    \"exempt\": 35531,\n    \"Ġmicrophones\": 35532,\n    \"Ġ244\": 35533,\n    \"778\": 35534,\n    \"Ġdwar\": 35535,\n    \"attery\": 35536,\n    \"502\": 35537,\n    \"ĠKik\": 35538,\n    \"Ġinspir\": 35539,\n    \"ĠMaximum\": 35540,\n    \"Ġvengeance\": 35541,\n    \"Ġetched\": 35542,\n    \"outine\": 35543,\n    \"552\": 35544,\n    \"Ġunicorn\": 35545,\n    \"gged\": 35546,\n    \".ï¿½\": 35547,\n    \"ĠBlackwell\": 35548,\n    \"ĠStatue\": 35549,\n    \"Ġdissidents\": 35550,\n    \"ĠKaine\": 35551,\n    \"Ġdeforestation\": 35552,\n    \"ĠScholar\": 35553,\n    \"Ġpleasantly\": 35554,\n    \"ÑĤ\": 35555,\n    \"398\": 35556,\n    \"ĠRUN\": 35557,\n    \"arent\": 35558,\n    \"Ġundeniably\": 35559,\n    \"Ġtechnologically\": 35560,\n    \"Ġconsciously\": 35561,\n    \"ĠEther\": 35562,\n    \"Ġproportional\": 35563,\n    \"Ġlaund\": 35564,\n    \"ĠRye\": 35565,\n    \"Ġambiguity\": 35566,\n    \"Ġunmist\": 35567,\n    \"Terror\": 35568,\n    \"ciplinary\": 35569,\n    \"ĠImproved\": 35570,\n    \"hesis\": 35571,\n    \"Ġcooker\": 35572,\n    \"elsen\": 35573,\n    \"Ġguerrilla\": 35574,\n    \"opped\": 35575,\n    \"ATURE\": 35576,\n    \"Ġrequ\": 35577,\n    \"Ġunprepared\": 35578,\n    \"Ġcamel\": 35579,\n    \"Ġfitt\": 35580,\n    \"Sex\": 35581,\n    \"edged\": 35582,\n    \"Ġrecurrent\": 35583,\n    \"ctuary\": 35584,\n    \"ĠCompare\": 35585,\n    \"ĠServing\": 35586,\n    \"Tri\": 35587,\n    \"Ġtransient\": 35588,\n    \"ĠBees\": 35589,\n    \"Ġcovenant\": 35590,\n    \"Ġfantasies\": 35591,\n    \"Ġespresso\": 35592,\n    \"draft\": 35593,\n    \"baugh\": 35594,\n    \"Ġdemocratically\": 35595,\n    \"ĠBans\": 35596,\n    \"ĠManual\": 35597,\n    \"ĠTurtle\": 35598,\n    \"ennett\": 35599,\n    \"achy\": 35600,\n    \"ĠClim\": 35601,\n    \"Ġdescending\": 35602,\n    \"Ġprow\": 35603,\n    \"Ġinconsistencies\": 35604,\n    \"Player\": 35605,\n    \"Ġoblivious\": 35606,\n    \"ĠWonderland\": 35607,\n    \"nav\": 35608,\n    \"aughter\": 35609,\n    \"Ġlod\": 35610,\n    \"Ġ403\": 35611,\n    \"ĠPolaris\": 35612,\n    \"ĠLeia\": 35613,\n    \"ĠInfantry\": 35614,\n    \"Sy\": 35615,\n    \"ĠMeter\": 35616,\n    \"Ġautoimmune\": 35617,\n    \"Ġdiagnoses\": 35618,\n    \"Ġtrespass\": 35619,\n    \"011\": 35620,\n    \"wrong\": 35621,\n    \"ĠGREAT\": 35622,\n    \"Ġtelescopes\": 35623,\n    \"shows\": 35624,\n    \"Pac\": 35625,\n    \"olation\": 35626,\n    \"Ġclerics\": 35627,\n    \"Ġdissenting\": 35628,\n    \"406\": 35629,\n    \"Ġetiquette\": 35630,\n    \"Ġdeterrence\": 35631,\n    \"765\": 35632,\n    \"Ġove\": 35633,\n    \"Has\": 35634,\n    \"Pak\": 35635,\n    \"à¤¾\": 35636,\n    \"ĠNec\": 35637,\n    \"Ġsociology\": 35638,\n    \"witz\": 35639,\n    \"Ġkittens\": 35640,\n    \"Ġcontinual\": 35641,\n    \"Ġoverlapping\": 35642,\n    \"Ġmonks\": 35643,\n    \"ĠMechanical\": 35644,\n    \"Captain\": 35645,\n    \"ocial\": 35646,\n    \"ĠFalling\": 35647,\n    \"ĠCorrection\": 35648,\n    \"ĠTrouble\": 35649,\n    \"Ġslog\": 35650,\n    \"Ġ253\": 35651,\n    \"Ġemanating\": 35652,\n    \"Ġwidest\": 35653,\n    \"PROV\": 35654,\n    \"Japanese\": 35655,\n    \"urat\": 35656,\n    \"Ġboxed\": 35657,\n    \"ĠCases\": 35658,\n    \"Ġjarring\": 35659,\n    \"Fix\": 35660,\n    \"'?\": 35661,\n    \"ĠStrateg\": 35662,\n    \"Republic\": 35663,\n    \"ovy\": 35664,\n    \"362\": 35665,\n    \"ĠMothers\": 35666,\n    \"Ġstreaks\": 35667,\n    \"Ġlocalized\": 35668,\n    \"ĠONLY\": 35669,\n    \"Ġeh\": 35670,\n    \"ĠObject\": 35671,\n    \"Ġstub\": 35672,\n    \"Fre\": 35673,\n    \"ĠScarlet\": 35674,\n    \"Ġmultip\": 35675,\n    \"ĠMaul\": 35676,\n    \"ĠProblems\": 35677,\n    \"cest\": 35678,\n    \"Ġmortal\": 35679,\n    \"Ġarche\": 35680,\n    \"ulet\": 35681,\n    \"Ġfuller\": 35682,\n    \"ĠGER\": 35683,\n    \"Si\": 35684,\n    \"mr\": 35685,\n    \"ĠPowerful\": 35686,\n    \"boxing\": 35687,\n    \"ĠPeer\": 35688,\n    \"Jean\": 35689,\n    \"ĠTF\": 35690,\n    \"Ġplural\": 35691,\n    \"optim\": 35692,\n    \"Jimmy\": 35693,\n    \"ĠFriendly\": 35694,\n    \"Mex\": 35695,\n    \"Ġdepri\": 35696,\n    \"PK\": 35697,\n    \"Ġwaitress\": 35698,\n    \"eph\": 35699,\n    \"arrass\": 35700,\n    \"ikawa\": 35701,\n    \"feel\": 35702,\n    \"Finally\": 35703,\n    \"fourth\": 35704,\n    \"394\": 35705,\n    \"conom\": 35706,\n    \"VT\": 35707,\n    \"Ġeleg\": 35708,\n    \"ivot\": 35709,\n    \"Ġharsher\": 35710,\n    \"ĠPepe\": 35711,\n    \"ĠImpl\": 35712,\n    \"Ġankles\": 35713,\n    \"idity\": 35714,\n    \"ĠPrepare\": 35715,\n    \"Rather\": 35716,\n    \"Ġconservatism\": 35717,\n    \"Ġunquestion\": 35718,\n    \"ribution\": 35719,\n    \"ĠPatent\": 35720,\n    \"ĠDeluxe\": 35721,\n    \"ĠAE\": 35722,\n    \"007\": 35723,\n    \"Ġprag\": 35724,\n    \"bg\": 35725,\n    \"Ġpalate\": 35726,\n    \"Ġintric\": 35727,\n    \"ossom\": 35728,\n    \"Ġspac\": 35729,\n    \"ĠSpotlight\": 35730,\n    \"Seven\": 35731,\n    \"amacare\": 35732,\n    \"ĠGotham\": 35733,\n    \"Ġencompass\": 35734,\n    \"Ġnicer\": 35735,\n    \"ĠLauder\": 35736,\n    \"Ġscaff\": 35737,\n    \"worn\": 35738,\n    \"442\": 35739,\n    \"Ġpropri\": 35740,\n    \"443\": 35741,\n    \"ĠCompos\": 35742,\n    \"ĠIniti\": 35743,\n    \"inth\": 35744,\n    \"Ġrehe\": 35745,\n    \"Prov\": 35746,\n    \"Ġgri\": 35747,\n    \"ossip\": 35748,\n    \"ĠModest\": 35749,\n    \"quiet\": 35750,\n    \"Ġwealthier\": 35751,\n    \"Ġ241\": 35752,\n    \"icum\": 35753,\n    \"Ġcommunism\": 35754,\n    \"Ġhelpers\": 35755,\n    \"Ġbellig\": 35756,\n    \"Ġ405\": 35757,\n    \"uttered\": 35758,\n    \"Ġbitterness\": 35759,\n    \"nl\": 35760,\n    \"474\": 35761,\n    \"Ġvitality\": 35762,\n    \"blank\": 35763,\n    \"ĠLeth\": 35764,\n    \"PAC\": 35765,\n    \"326\": 35766,\n    \"ĠNapoleon\": 35767,\n    \"Ġ299\": 35768,\n    \"ĠReviews\": 35769,\n    \"ĠSect\": 35770,\n    \"Ġstrongh\": 35771,\n    \"ĠTube\": 35772,\n    \"Ġwoodland\": 35773,\n    \"Ġhumming\": 35774,\n    \"411\": 35775,\n    \"Alpha\": 35776,\n    \"Ġundet\": 35777,\n    \"Ġmounts\": 35778,\n    \"Officials\": 35779,\n    \"igning\": 35780,\n    \"830\": 35781,\n    \"ĠStamp\": 35782,\n    \"ubby\": 35783,\n    \"424\": 35784,\n    \"Ġoutlandish\": 35785,\n    \"Ġjerk\": 35786,\n    \"Ġradiant\": 35787,\n    \"Ġcubes\": 35788,\n    \"Director\": 35789,\n    \"Ġatro\": 35790,\n    \"vous\": 35791,\n    \"Sab\": 35792,\n    \"Ġpretended\": 35793,\n    \"Ġ620\": 35794,\n    \"975\": 35795,\n    \"Sham\": 35796,\n    \"Ġpotassium\": 35797,\n    \"ĠAttention\": 35798,\n    \"gly\": 35799,\n    \"opens\": 35800,\n    \"ĠWorker\": 35801,\n    \"porter\": 35802,\n    \"Ġsplendid\": 35803,\n    \"embed\": 35804,\n    \"Je\": 35805,\n    \"ĠMeal\": 35806,\n    \"Ġsurname\": 35807,\n    \"Usually\": 35808,\n    \"Ġtimer\": 35809,\n    \"Ġweave\": 35810,\n    \"irin\": 35811,\n    \"ĠGenetics\": 35812,\n    \"ensual\": 35813,\n    \"Ġmerry\": 35814,\n    \"Ġapprehend\": 35815,\n    \"utsche\": 35816,\n    \"strate\": 35817,\n    \"Ġsupplementary\": 35818,\n    \"ĠRoundup\": 35819,\n    \"upid\": 35820,\n    \"Ġmiraculous\": 35821,\n    \"ĠHUN\": 35822,\n    \"Ġglaciers\": 35823,\n    \"weed\": 35824,\n    \"ĠSuggest\": 35825,\n    \"XL\": 35826,\n    \"authors\": 35827,\n    \"Ġbarking\": 35828,\n    \"ĠUKIP\": 35829,\n    \"leased\": 35830,\n    \"ĠRAD\": 35831,\n    \"Ġfide\": 35832,\n    \"Ġphen\": 35833,\n    \"Ġscanners\": 35834,\n    \"Parents\": 35835,\n    \"ĠBlaze\": 35836,\n    \"Ġtweaking\": 35837,\n    \"Ġelaborated\": 35838,\n    \"Ġsusp\": 35839,\n    \"iscovered\": 35840,\n    \"Ġthighs\": 35841,\n    \"Ġradicals\": 35842,\n    \"ULTS\": 35843,\n    \"aggressive\": 35844,\n    \"endants\": 35845,\n    \"Hon\": 35846,\n    \"Ġcorrecting\": 35847,\n    \"391\": 35848,\n    \"pps\": 35849,\n    \"ĠTerritories\": 35850,\n    \"Ġconferred\": 35851,\n    \"crazy\": 35852,\n    \"utor\": 35853,\n    \"ĠSurvival\": 35854,\n    \"Ġbrowsers\": 35855,\n    \"ĠConflict\": 35856,\n    \"pn\": 35857,\n    \"Ġdeprive\": 35858,\n    \"riage\": 35859,\n    \"ilan\": 35860,\n    \"à¦\": 35861,\n    \"949\": 35862,\n    \"Congratulations\": 35863,\n    \"radical\": 35864,\n    \"ĠHits\": 35865,\n    \"powerful\": 35866,\n    \"Ġcrypt\": 35867,\n    \"745\": 35868,\n    \"ĠRegistrar\": 35869,\n    \"ophile\": 35870,\n    \"ĠElement\": 35871,\n    \"cooked\": 35872,\n    \"ĠTwilight\": 35873,\n    \"Ġdemos\": 35874,\n    \"IER\": 35875,\n    \"Ġstricken\": 35876,\n    \"Magic\": 35877,\n    \"abby\": 35878,\n    \"ĠSack\": 35879,\n    \"ĠShrine\": 35880,\n    \"Nev\": 35881,\n    \"Probably\": 35882,\n    \"ĠWisdom\": 35883,\n    \"ulpt\": 35884,\n    \"opher\": 35885,\n    \"Ġcolonel\": 35886,\n    \"atl\": 35887,\n    \"Tem\": 35888,\n    \"kun\": 35889,\n    \"ĠIndie\": 35890,\n    \"Putin\": 35891,\n    \"jection\": 35892,\n    \"areth\": 35893,\n    \"ĠBullet\": 35894,\n    \"Ġsmartest\": 35895,\n    \"ĠEsper\": 35896,\n    \"Ġproficiency\": 35897,\n    \"Ġcessation\": 35898,\n    \"Ġmars\": 35899,\n    \"ĠDATA\": 35900,\n    \"sup\": 35901,\n    \"Ġostr\": 35902,\n    \"Jane\": 35903,\n    \"Ġpathogens\": 35904,\n    \"hd\": 35905,\n    \"ĠNK\": 35906,\n    \"Ġhorribly\": 35907,\n    \"regulated\": 35908,\n    \"Ġesteemed\": 35909,\n    \"ĠChinatown\": 35910,\n    \"Ġvibration\": 35911,\n    \"Ġoverboard\": 35912,\n    \"ĠRhod\": 35913,\n    \"Ġfeces\": 35914,\n    \"otation\": 35915,\n    \"Ġcryptic\": 35916,\n    \"Bal\": 35917,\n    \"OPER\": 35918,\n    \"Ġaffirmation\": 35919,\n    \"Ġmenstrual\": 35920,\n    \"Ġuntold\": 35921,\n    \"Ġanecdotes\": 35922,\n    \"ĠHOUSE\": 35923,\n    \"Ġcape\": 35924,\n    \"311\": 35925,\n    \"ittance\": 35926,\n    \"ĠRemy\": 35927,\n    \"ĠWaves\": 35928,\n    \"ĠCOVER\": 35929,\n    \"ordinate\": 35930,\n    \"Ġrestricts\": 35931,\n    \"Samsung\": 35932,\n    \"Ġplantations\": 35933,\n    \"olver\": 35934,\n    \"Better\": 35935,\n    \"ĠExplos\": 35936,\n    \"Ġnasal\": 35937,\n    \"ĠSyri\": 35938,\n    \"ĠPerl\": 35939,\n    \"Ġlatency\": 35940,\n    \"othermal\": 35941,\n    \"Sweet\": 35942,\n    \"ĠRyzen\": 35943,\n    \"ĠYuri\": 35944,\n    \"Ġsmack\": 35945,\n    \"Ġcrow\": 35946,\n    \"aniel\": 35947,\n    \"iological\": 35948,\n    \"Ġmonk\": 35949,\n    \"Ġtutorial\": 35950,\n    \"ĠAure\": 35951,\n    \"Ġcliffs\": 35952,\n    \"ameron\": 35953,\n    \"umers\": 35954,\n    \"ĠMour\": 35955,\n    \"Ġunorthodox\": 35956,\n    \"Ġgulf\": 35957,\n    \"Ġintrusive\": 35958,\n    \"ĠVIII\": 35959,\n    \"ĠFF\": 35960,\n    \"Ġenlarged\": 35961,\n    \"Ġspheres\": 35962,\n    \"ĠCheap\": 35963,\n    \"ĠAmend\": 35964,\n    \"Ġ::\": 35965,\n    \"Ġpacing\": 35966,\n    \"ĠStartup\": 35967,\n    \"ĠDating\": 35968,\n    \"racist\": 35969,\n    \"ĠDivine\": 35970,\n    \"Ġpollen\": 35971,\n    \"ĠMeaning\": 35972,\n    \"ĠLei\": 35973,\n    \"ĠMOT\": 35974,\n    \"ĠARC\": 35975,\n    \"legate\": 35976,\n    \"Ġbrav\": 35977,\n    \"Ross\": 35978,\n    \"redit\": 35979,\n    \"414\": 35980,\n    \"ringe\": 35981,\n    \"perhaps\": 35982,\n    \"SPA\": 35983,\n    \"Southern\": 35984,\n    \"Front\": 35985,\n    \"undrum\": 35986,\n    \"Ġassorted\": 35987,\n    \"ĠDawkins\": 35988,\n    \"ĠWrap\": 35989,\n    \"Ġconsequential\": 35990,\n    \"ĠFuji\": 35991,\n    \"458\": 35992,\n    \"Ġunst\": 35993,\n    \"Bon\": 35994,\n    \"acter\": 35995,\n    \"Trade\": 35996,\n    \"ingers\": 35997,\n    \"ĠClin\": 35998,\n    \"Ġstimul\": 35999,\n    \"arah\": 36000,\n    \"inois\": 36001,\n    \"urdy\": 36002,\n    \"Ġobsessive\": 36003,\n    \"Zone\": 36004,\n    \"Ġprimitive\": 36005,\n    \"unctions\": 36006,\n    \"Ġadapter\": 36007,\n    \"Ġassures\": 36008,\n    \"Daddy\": 36009,\n    \"Ġunsatisf\": 36010,\n    \"441\": 36011,\n    \"Ġ1910\": 36012,\n    \"Ġsecondly\": 36013,\n    \"truth\": 36014,\n    \"RED\": 36015,\n    \"040\": 36016,\n    \"Pope\": 36017,\n    \"venants\": 36018,\n    \"Ġestim\": 36019,\n    \"Ġhemorrh\": 36020,\n    \"Ġexcruciating\": 36021,\n    \"459\": 36022,\n    \"Ġboils\": 36023,\n    \"ieved\": 36024,\n    \"Storm\": 36025,\n    \"Ġmanifestation\": 36026,\n    \"Ġinsulated\": 36027,\n    \"fb\": 36028,\n    \"Ġclassify\": 36029,\n    \"Mbps\": 36030,\n    \"Ġinclination\": 36031,\n    \"Ġaur\": 36032,\n    \"Ġpolarized\": 36033,\n    \"Ġoccupations\": 36034,\n    \"Secretary\": 36035,\n    \"Ġcustomizable\": 36036,\n    \"scribe\": 36037,\n    \"Ġadjunct\": 36038,\n    \"Ġ1922\": 36039,\n    \"rived\": 36040,\n    \"ocative\": 36041,\n    \"Friends\": 36042,\n    \"Oak\": 36043,\n    \"Ġpsyche\": 36044,\n    \"Ġwrinkles\": 36045,\n    \"anthrop\": 36046,\n    \"Ġcoercion\": 36047,\n    \"enos\": 36048,\n    \"Ġvariability\": 36049,\n    \"hma\": 36050,\n    \"phot\": 36051,\n    \"ĠXander\": 36052,\n    \"ĠDiss\": 36053,\n    \"Ġtigers\": 36054,\n    \"ahoo\": 36055,\n    \"focus\": 36056,\n    \"rical\": 36057,\n    \"grow\": 36058,\n    \"Ġseminal\": 36059,\n    \"Ġdisciples\": 36060,\n    \"Cas\": 36061,\n    \"Hundreds\": 36062,\n    \"Ġscissors\": 36063,\n    \"correct\": 36064,\n    \"Ġfascism\": 36065,\n    \"imoto\": 36066,\n    \"Ġnudity\": 36067,\n    \"charg\": 36068,\n    \"Ġrusty\": 36069,\n    \"ĠLyndon\": 36070,\n    \"Ġanomalies\": 36071,\n    \"onial\": 36072,\n    \"ĠiCloud\": 36073,\n    \"Ġannoy\": 36074,\n    \"Ġdistortion\": 36075,\n    \"Lou\": 36076,\n    \"ĠGiul\": 36077,\n    \"eyes\": 36078,\n    \"870\": 36079,\n    \"uum\": 36080,\n    \"ĠUltr\": 36081,\n    \"Action\": 36082,\n    \"cigarette\": 36083,\n    \"igators\": 36084,\n    \"kj\": 36085,\n    \"Ġ323\": 36086,\n    \"uine\": 36087,\n    \"Score\": 36088,\n    \"Ġmans\": 36089,\n    \"Security\": 36090,\n    \"Ġarom\": 36091,\n    \"ĠBoards\": 36092,\n    \"Ġwrists\": 36093,\n    \"602\": 36094,\n    \"Ġastronomy\": 36095,\n    \"Ġresin\": 36096,\n    \"width\": 36097,\n    \")/\": 36098,\n    \"Ġconcurrent\": 36099,\n    \"unless\": 36100,\n    \"606\": 36101,\n    \"ĠMagnet\": 36102,\n    \"Ġauthorizing\": 36103,\n    \"ĠJunk\": 36104,\n    \"atical\": 36105,\n    \"Ġauthent\": 36106,\n    \"zac\": 36107,\n    \"413\": 36108,\n    \"ĠGrape\": 36109,\n    \"Ġcircled\": 36110,\n    \"Ġooz\": 36111,\n    \"Ġvisceral\": 36112,\n    \"ointment\": 36113,\n    \"Ġincendiary\": 36114,\n    \"ĠBourbon\": 36115,\n    \"Ġgimmick\": 36116,\n    \"vette\": 36117,\n    \"Stan\": 36118,\n    \"Ġdetachment\": 36119,\n    \"488\": 36120,\n    \"Ġmisogyny\": 36121,\n    \"Ġenlight\": 36122,\n    \"utic\": 36123,\n    \"Ġinquire\": 36124,\n    \"ĠBEL\": 36125,\n    \"ascular\": 36126,\n    \"ĠWasserman\": 36127,\n    \"Dallas\": 36128,\n    \"Ġconstellation\": 36129,\n    \"Ġdystopian\": 36130,\n    \"504\": 36131,\n    \"ĠOptical\": 36132,\n    \"Ġsilhou\": 36133,\n    \"Girl\": 36134,\n    \"ĠGong\": 36135,\n    \"ĠHighest\": 36136,\n    \"????????\": 36137,\n    \"Sav\": 36138,\n    \"ocity\": 36139,\n    \"leted\": 36140,\n    \"Ġattrition\": 36141,\n    \"ĠExpedition\": 36142,\n    \"ĠKilled\": 36143,\n    \"501\": 36144,\n    \"ONES\": 36145,\n    \"dat\": 36146,\n    \"Ġglyphosate\": 36147,\n    \"Ġplugs\": 36148,\n    \"Ġlact\": 36149,\n    \"Fla\": 36150,\n    \"fps\": 36151,\n    \"riger\": 36152,\n    \"Ġparagraphs\": 36153,\n    \"Ġinnate\": 36154,\n    \"ĠFoo\": 36155,\n    \"aternity\": 36156,\n    \"ĠGry\": 36157,\n    \"Ġoneself\": 36158,\n    \"642\": 36159,\n    \"Iowa\": 36160,\n    \"oodle\": 36161,\n    \"ĠCoconut\": 36162,\n    \"ĠChess\": 36163,\n    \"ommel\": 36164,\n    \"Ġmagnesium\": 36165,\n    \"Ġairliner\": 36166,\n    \"Ġexceedingly\": 36167,\n    \"ĠCreator\": 36168,\n    \"YouTube\": 36169,\n    \"Ġsleeper\": 36170,\n    \"Ġlonging\": 36171,\n    \"ĠPercy\": 36172,\n    \"Ġmatrix\": 36173,\n    \"Ġâľ\": 36174,\n    \"Ġbarren\": 36175,\n    \"Mrs\": 36176,\n    \"Ġinvading\": 36177,\n    \"Ġincom\": 36178,\n    \"Ġemperor\": 36179,\n    \"Ġip\": 36180,\n    \"irie\": 36181,\n    \"Ġpredictably\": 36182,\n    \"ĠBless\": 36183,\n    \"Ġsuperpower\": 36184,\n    \":-\": 36185,\n    \"Ġpropensity\": 36186,\n    \"easy\": 36187,\n    \"educ\": 36188,\n    \"ĠPolly\": 36189,\n    \"Ġcumbersome\": 36190,\n    \"Ġcollide\": 36191,\n    \"016\": 36192,\n    \"Ġtransports\": 36193,\n    \"Ġscraps\": 36194,\n    \"below\": 36195,\n    \"Ġhairs\": 36196,\n    \"mentation\": 36197,\n    \"Ġevolves\": 36198,\n    \"ĠFallen\": 36199,\n    \"Ġunsurprisingly\": 36200,\n    \"Ġcuff\": 36201,\n    \"Ġ249\": 36202,\n    \"mental\": 36203,\n    \"ĠCamel\": 36204,\n    \"Ġ337\": 36205,\n    \"Clinton\": 36206,\n    \"Ġdecad\": 36207,\n    \"ĠSTEP\": 36208,\n    \"ĠTestament\": 36209,\n    \"Ġirresistible\": 36210,\n    \"ĠACE\": 36211,\n    \"Ġhamm\": 36212,\n    \"ĠTerr\": 36213,\n    \"Ġcaul\": 36214,\n    \"iggins\": 36215,\n    \"Ġproficient\": 36216,\n    \"resp\": 36217,\n    \"Ġheirs\": 36218,\n    \"Ġ321\": 36219,\n    \"dress\": 36220,\n    \"ĠClothing\": 36221,\n    \"Ġ560\": 36222,\n    \"Ġ264\": 36223,\n    \"ĠRobb\": 36224,\n    \"Ġfrail\": 36225,\n    \"Ġoptimizing\": 36226,\n    \"615\": 36227,\n    \"ĠRefuge\": 36228,\n    \"rowth\": 36229,\n    \"washing\": 36230,\n    \"Ġgenders\": 36231,\n    \"indu\": 36232,\n    \"ĠNAT\": 36233,\n    \"Ġleans\": 36234,\n    \"Ġeyed\": 36235,\n    \"Ġhilar\": 36236,\n    \"vice\": 36237,\n    \"wolf\": 36238,\n    \"Ġfatig\": 36239,\n    \"ococ\": 36240,\n    \"ĠCarry\": 36241,\n    \"Community\": 36242,\n    \"Clark\": 36243,\n    \"itably\": 36244,\n    \"sv\": 36245,\n    \"448\": 36246,\n    \"Ġnumer\": 36247,\n    \"Ġ1925\": 36248,\n    \"ĠBehavioral\": 36249,\n    \"ĠScream\": 36250,\n    \"Ġgeek\": 36251,\n    \"rake\": 36252,\n    \"ĠTTC\": 36253,\n    \"Ġadditives\": 36254,\n    \"ĠBye\": 36255,\n    \"ylon\": 36256,\n    \"Ġfoliage\": 36257,\n    \"ateral\": 36258,\n    \"rapnel\": 36259,\n    \"Science\": 36260,\n    \"Ġrecollection\": 36261,\n    \"thening\": 36262,\n    \"ĠUbisoft\": 36263,\n    \"ĠLur\": 36264,\n    \"ĠOkinawa\": 36265,\n    \"ĠProvision\": 36266,\n    \"ferred\": 36267,\n    \"ĠGrounds\": 36268,\n    \"Ġhops\": 36269,\n    \"aterial\": 36270,\n    \"Ġacad\": 36271,\n    \"Ġengulf\": 36272,\n    \"ĠApex\": 36273,\n    \"frequency\": 36274,\n    \"relations\": 36275,\n    \"ĠCorvette\": 36276,\n    \"ĠRepeat\": 36277,\n    \"Ġanew\": 36278,\n    \"Ġhes\": 36279,\n    \"ĠLair\": 36280,\n    \"ĠPSP\": 36281,\n    \"foundation\": 36282,\n    \"Band\": 36283,\n    \"ĠPublisher\": 36284,\n    \"Ġreciprocal\": 36285,\n    \"Ġ287\": 36286,\n    \"Ġpir\": 36287,\n    \"Adams\": 36288,\n    \"Ġprostitute\": 36289,\n    \"ĠMecca\": 36290,\n    \"ectomy\": 36291,\n    \"Ġskew\": 36292,\n    \"ĠLol\": 36293,\n    \"Voice\": 36294,\n    \"ĠCalais\": 36295,\n    \"ISION\": 36296,\n    \"rue\": 36297,\n    \"Ġgaping\": 36298,\n    \"prot\": 36299,\n    \"Ġ6000\": 36300,\n    \"Ġtilted\": 36301,\n    \"Ġgoofy\": 36302,\n    \"Stand\": 36303,\n    \"Ġfellows\": 36304,\n    \"Ġcurly\": 36305,\n    \"ĠPOW\": 36306,\n    \"Ġlore\": 36307,\n    \"Ġinhabited\": 36308,\n    \"ĠIdentification\": 36309,\n    \"Metro\": 36310,\n    \"Ġdispel\": 36311,\n    \"Ġinvoking\": 36312,\n    \"Ġdeleting\": 36313,\n    \"Ġstigmat\": 36314,\n    \"ĠDalai\": 36315,\n    \"Ġequate\": 36316,\n    \"Ġmascara\": 36317,\n    \"endered\": 36318,\n    \"ĠNYT\": 36319,\n    \"ĠCommittees\": 36320,\n    \"rians\": 36321,\n    \"ĠOlympus\": 36322,\n    \"ĠQR\": 36323,\n    \"ĠDrinking\": 36324,\n    \"Ġbatt\": 36325,\n    \"andr\": 36326,\n    \"computer\": 36327,\n    \"Senator\": 36328,\n    \"ĠTwist\": 36329,\n    \"ĠNoise\": 36330,\n    \"Ġcheesy\": 36331,\n    \"Ġ1931\": 36332,\n    \"Ġtyranny\": 36333,\n    \"Ġnegligible\": 36334,\n    \"ĠBok\": 36335,\n    \"Ġwebpage\": 36336,\n    \"ĠHEAD\": 36337,\n    \"ĠNovel\": 36338,\n    \"Ġquarry\": 36339,\n    \"Ġexpressive\": 36340,\n    \"Ġforgiving\": 36341,\n    \"Among\": 36342,\n    \"asin\": 36343,\n    \"ĠSuc\": 36344,\n    \"Democrats\": 36345,\n    \"795\": 36346,\n    \"Ġaback\": 36347,\n    \"Â¨\": 36348,\n    \"ĠNeon\": 36349,\n    \"392\": 36350,\n    \"ĠRNC\": 36351,\n    \"ĠPROC\": 36352,\n    \"sein\": 36353,\n    \"Ros\": 36354,\n    \"Ġemot\": 36355,\n    \"ĠASA\": 36356,\n    \"ĠSeb\": 36357,\n    \"ĠExtended\": 36358,\n    \"atern\": 36359,\n    \"Ġpsychedelic\": 36360,\n    \"Fil\": 36361,\n    \"ĠOrwell\": 36362,\n    \"ĠSOS\": 36363,\n    \"Ġconceive\": 36364,\n    \"Ġhobbies\": 36365,\n    \"Ġspecimens\": 36366,\n    \"ĠTEXT\": 36367,\n    \"sometimes\": 36368,\n    \"Mario\": 36369,\n    \"orpor\": 36370,\n    \"ĠTemporary\": 36371,\n    \"Ġapocalypse\": 36372,\n    \"Ġcounterproductive\": 36373,\n    \"ĠQUEST\": 36374,\n    \"ĠCargo\": 36375,\n    \"Amb\": 36376,\n    \"Ġoptic\": 36377,\n    \"groups\": 36378,\n    \"Ġparanoia\": 36379,\n    \".?\": 36380,\n    \"sounding\": 36381,\n    \"mediately\": 36382,\n    \"System\": 36383,\n    \"ubi\": 36384,\n    \"Ġuttered\": 36385,\n    \"Ġgraphs\": 36386,\n    \"âĢĭâĢĭ\": 36387,\n    \"Ġscientifically\": 36388,\n    \"Ġbluntly\": 36389,\n    \"Ġhopping\": 36390,\n    \"Fun\": 36391,\n    \"ĠSUPER\": 36392,\n    \"Ġrobe\": 36393,\n    \"VB\": 36394,\n    \"ĠQuote\": 36395,\n    \"Ġincarnation\": 36396,\n    \"Ġtreadmill\": 36397,\n    \"Ġ1915\": 36398,\n    \"Ġbart\": 36399,\n    \"669\": 36400,\n    \"Ġhoc\": 36401,\n    \"Ġ309\": 36402,\n    \"Ġimprovis\": 36403,\n    \"Ġhut\": 36404,\n    \"Ġmixer\": 36405,\n    \"ĠCt\": 36406,\n    \"span\": 36407,\n    \"Ġwatered\": 36408,\n    \"Ġpatriot\": 36409,\n    \"Ġdehyd\": 36410,\n    \"laughs\": 36411,\n    \"ĠFancy\": 36412,\n    \"ĠVoc\": 36413,\n    \"Ġintellect\": 36414,\n    \"ĠTid\": 36415,\n    \"Ġnesting\": 36416,\n    \"Tel\": 36417,\n    \"Ġ()\": 36418,\n    \"letter\": 36419,\n    \"ĠSeems\": 36420,\n    \"Ops\": 36421,\n    \"ĠContents\": 36422,\n    \"ript\": 36423,\n    \"hani\": 36424,\n    \"Ġrecru\": 36425,\n    \"Ġpickups\": 36426,\n    \"repair\": 36427,\n    \"Throughout\": 36428,\n    \"bear\": 36429,\n    \"Ġconquered\": 36430,\n    \"656\": 36431,\n    \"Ġmalf\": 36432,\n    \"Ġordained\": 36433,\n    \"755\": 36434,\n    \"ĠReprodu\": 36435,\n    \"brain\": 36436,\n    \"ĠOuts\": 36437,\n    \"ĠWage\": 36438,\n    \"Ru\": 36439,\n    \"________\": 36440,\n    \"ĠLAW\": 36441,\n    \"ĠWass\": 36442,\n    \"Ġcomplication\": 36443,\n    \"Fri\": 36444,\n    \"Ġregener\": 36445,\n    \"Wait\": 36446,\n    \"577\": 36447,\n    \"Ġmisconception\": 36448,\n    \"Ġbombardment\": 36449,\n    \"Ġunloaded\": 36450,\n    \"Ġdictionary\": 36451,\n    \"IU\": 36452,\n    \"025\": 36453,\n    \"etically\": 36454,\n    \"ĠNarr\": 36455,\n    \"repe\": 36456,\n    \"Ġassigning\": 36457,\n    \"Rail\": 36458,\n    \"Ġnotebooks\": 36459,\n    \"Ġingest\": 36460,\n    \"Ġrpm\": 36461,\n    \"Ġalienated\": 36462,\n    \"ĠCredits\": 36463,\n    \"Ġindis\": 36464,\n    \"ĠGathering\": 36465,\n    \"aration\": 36466,\n    \"-+-+-+-+\": 36467,\n    \"Ġori\": 36468,\n    \"Ġsr\": 36469,\n    \"ndra\": 36470,\n    \"Ġlibertarian\": 36471,\n    \"Ġcoerced\": 36472,\n    \"ording\": 36473,\n    \"Ġtranqu\": 36474,\n    \"Ġelbows\": 36475,\n    \"549\": 36476,\n    \"Ġping\": 36477,\n    \"ĠRELE\": 36478,\n    \"ĠYanuk\": 36479,\n    \"Ġmaneuvers\": 36480,\n    \"ĠTrojan\": 36481,\n    \"IFIED\": 36482,\n    \"ĠViolent\": 36483,\n    \"è\": 36484,\n    \"Ġlest\": 36485,\n    \"Ġarrows\": 36486,\n    \"frog\": 36487,\n    \"anty\": 36488,\n    \"WB\": 36489,\n    \"ĠSeen\": 36490,\n    \"648\": 36491,\n    \"Ġclutter\": 36492,\n    \"ĠBender\": 36493,\n    \"Ġpessim\": 36494,\n    \"ĠTeg\": 36495,\n    \"Asian\": 36496,\n    \"IFIC\": 36497,\n    \"Ġexponential\": 36498,\n    \"Ġsponge\": 36499,\n    \"rite\": 36500,\n    \"ĠDAM\": 36501,\n    \"Ġtacit\": 36502,\n    \"ĠZoom\": 36503,\n    \"Ġolds\": 36504,\n    \"Ġonward\": 36505,\n    \"ĠSandwich\": 36506,\n    \"missible\": 36507,\n    \"isol\": 36508,\n    \"940\": 36509,\n    \"Ġinciner\": 36510,\n    \"ĠTrick\": 36511,\n    \"Ġawakening\": 36512,\n    \"Ġdart\": 36513,\n    \"ĠCouch\": 36514,\n    \"respons\": 36515,\n    \"ĠElephant\": 36516,\n    \"ĠPluto\": 36517,\n    \"ĠTags\": 36518,\n    \"itcher\": 36519,\n    \"644\": 36520,\n    \"702\": 36521,\n    \"Ġelectrons\": 36522,\n    \"ĠMyth\": 36523,\n    \"ĠAad\": 36524,\n    \"Danny\": 36525,\n    \"Ġcraw\": 36526,\n    \"ĠCertification\": 36527,\n    \"Ġtending\": 36528,\n    \"Ġpellets\": 36529,\n    \"Ġamused\": 36530,\n    \"ĠAuschwitz\": 36531,\n    \"ĠAppl\": 36532,\n    \"iris\": 36533,\n    \"ashion\": 36534,\n    \"walking\": 36535,\n    \"Ġabnorm\": 36536,\n    \"Cro\": 36537,\n    \"?:\": 36538,\n    \"ĠIcelandic\": 36539,\n    \"ĠAvailability\": 36540,\n    \"Ġcann\": 36541,\n    \"Opt\": 36542,\n    \"buster\": 36543,\n    \"ĠQuartz\": 36544,\n    \"Executive\": 36545,\n    \"tracks\": 36546,\n    \"igel\": 36547,\n    \"MIT\": 36548,\n    \"ĠTracking\": 36549,\n    \"Ġconditioned\": 36550,\n    \"Ġsampled\": 36551,\n    \"ĠGenius\": 36552,\n    \"Ġsubstit\": 36553,\n    \"ĠSiberia\": 36554,\n    \"Ġfrequ\": 36555,\n    \"historic\": 36556,\n    \"okin\": 36557,\n    \"OWS\": 36558,\n    \"1500\": 36559,\n    \"warts\": 36560,\n    \"ĠEtsy\": 36561,\n    \"licks\": 36562,\n    \"ĠSmooth\": 36563,\n    \"unity\": 36564,\n    \"515\": 36565,\n    \"Ġperk\": 36566,\n    \"aida\": 36567,\n    \"forts\": 36568,\n    \"ĠUA\": 36569,\n    \"RIC\": 36570,\n    \"Spain\": 36571,\n    \"ĠWired\": 36572,\n    \"cuts\": 36573,\n    \"Ġfurnace\": 36574,\n    \"ĠTOTAL\": 36575,\n    \"ĠTables\": 36576,\n    \"662\": 36577,\n    \"Fab\": 36578,\n    \"Ġquaint\": 36579,\n    \"ĠWorlds\": 36580,\n    \"ĠCabin\": 36581,\n    \"atche\": 36582,\n    \"List\": 36583,\n    \"ĠVO\": 36584,\n    \"Ġkeyword\": 36585,\n    \"Ġ258\": 36586,\n    \"Farm\": 36587,\n    \"timer\": 36588,\n    \"ĠVolt\": 36589,\n    \"Build\": 36590,\n    \"pressed\": 36591,\n    \"*,\": 36592,\n    \"Ġ324\": 36593,\n    \"aiman\": 36594,\n    \"TING\": 36595,\n    \"Ġsneaking\": 36596,\n    \"cery\": 36597,\n    \"Ġcrib\": 36598,\n    \"ĠIllust\": 36599,\n    \"later\": 36600,\n    \"Ġcompar\": 36601,\n    \"Ġpropulsion\": 36602,\n    \"647\": 36603,\n    \"ĠTrails\": 36604,\n    \"Ġperiphery\": 36605,\n    \"steel\": 36606,\n    \"Ġvividly\": 36607,\n    \"ĠConver\": 36608,\n    \"eatured\": 36609,\n    \"427\": 36610,\n    \"463\": 36611,\n    \"Ġapprox\": 36612,\n    \"spin\": 36613,\n    \"Ġconfigured\": 36614,\n    \"inside\": 36615,\n    \"razy\": 36616,\n    \"account\": 36617,\n    \"anye\": 36618,\n    \"riend\": 36619,\n    \"Ġbows\": 36620,\n    \"809\": 36621,\n    \"ĠDEF\": 36622,\n    \"ĠRez\": 36623,\n    \"Fans\": 36624,\n    \"ĠDF\": 36625,\n    \"Ġstains\": 36626,\n    \"ĠAtom\": 36627,\n    \"ĠConce\": 36628,\n    \"ĠTOM\": 36629,\n    \"ĠELECT\": 36630,\n    \"Ġdisappro\": 36631,\n    \"019\": 36632,\n    \"afia\": 36633,\n    \"ĠTemperature\": 36634,\n    \"Ġextracts\": 36635,\n    \"fab\": 36636,\n    \"Ġunsur\": 36637,\n    \"Ġseasoning\": 36638,\n    \"Ty\": 36639,\n    \"KB\": 36640,\n    \"Ġposit\": 36641,\n    \"Ġlocality\": 36642,\n    \"1200\": 36643,\n    \"cour\": 36644,\n    \"izons\": 36645,\n    \"hh\": 36646,\n    \"506\": 36647,\n    \"ĠDLC\": 36648,\n    \"iago\": 36649,\n    \"Ġcorpses\": 36650,\n    \"iddling\": 36651,\n    \"Mayor\": 36652,\n    \"Ġsimplistic\": 36653,\n    \"Ġlibel\": 36654,\n    \"Ġalmonds\": 36655,\n    \"Ġswast\": 36656,\n    \"Change\": 36657,\n    \"ĠJoker\": 36658,\n    \"MAR\": 36659,\n    \"ĠScully\": 36660,\n    \"Ġmailbox\": 36661,\n    \"VIDEO\": 36662,\n    \"ĠKyoto\": 36663,\n    \"esley\": 36664,\n    \"ĠIncredible\": 36665,\n    \"youtube\": 36666,\n    \"Ġinequalities\": 36667,\n    \"Ġbolts\": 36668,\n    \"Ġbothering\": 36669,\n    \"Ġattentive\": 36670,\n    \"ĠSparrow\": 36671,\n    \"Ġdiaper\": 36672,\n    \"Ġfanbase\": 36673,\n    \"Ġuncont\": 36674,\n    \"Ap\": 36675,\n    \"ĠQi\": 36676,\n    \"Price\": 36677,\n    \"471\": 36678,\n    \"Ġpearl\": 36679,\n    \"wid\": 36680,\n    \"899\": 36681,\n    \"ĠPony\": 36682,\n    \"casting\": 36683,\n    \"Ġinhabit\": 36684,\n    \"Ġunve\": 36685,\n    \"Ġinsur\": 36686,\n    \"ĠWee\": 36687,\n    \"658\": 36688,\n    \"Ġeffected\": 36689,\n    \"gger\": 36690,\n    \"Ġinstallments\": 36691,\n    \"imilar\": 36692,\n    \"FU\": 36693,\n    \"Ġinfertility\": 36694,\n    \"climate\": 36695,\n    \"HEAD\": 36696,\n    \"fashion\": 36697,\n    \"ĠTHEY\": 36698,\n    \"jc\": 36699,\n    \"Ġsatisf\": 36700,\n    \"ĠGuidelines\": 36701,\n    \"Ġinsure\": 36702,\n    \"ĠRSA\": 36703,\n    \"Ġvirt\": 36704,\n    \"Ġinterpre\": 36705,\n    \"Joshua\": 36706,\n    \"ĠShut\": 36707,\n    \"Ġtestimonies\": 36708,\n    \"Ñģ\": 36709,\n    \"untary\": 36710,\n    \"417\": 36711,\n    \"Ġbeck\": 36712,\n    \"ĠMilky\": 36713,\n    \"ç\": 36714,\n    \"Ġsequels\": 36715,\n    \"Ġ281\": 36716,\n    \"ĠRibbon\": 36717,\n    \"Ġroomm\": 36718,\n    \"Ġsynchron\": 36719,\n    \"452\": 36720,\n    \"Ġ1926\": 36721,\n    \"Ġhawk\": 36722,\n    \"ĠDisorder\": 36723,\n    \"Ġbackstory\": 36724,\n    \"ĠNum\": 36725,\n    \"Ġoverheard\": 36726,\n    \"technical\": 36727,\n    \"Jud\": 36728,\n    \"aii\": 36729,\n    \"Ġdecon\": 36730,\n    \"ĠRape\": 36731,\n    \"ĠWarrant\": 36732,\n    \"Ġpoop\": 36733,\n    \"spir\": 36734,\n    \"Country\": 36735,\n    \"Ġweld\": 36736,\n    \"Ġabuser\": 36737,\n    \"Ġ------\": 36738,\n    \"material\": 36739,\n    \"Ġpreserves\": 36740,\n    \"spring\": 36741,\n    \"Ġpuzzled\": 36742,\n    \"ĠDebate\": 36743,\n    \"Joseph\": 36744,\n    \"Ġ272\": 36745,\n    \"Blood\": 36746,\n    \"antry\": 36747,\n    \"Ġconverge\": 36748,\n    \"Ġimaginable\": 36749,\n    \"oward\": 36750,\n    \"545\": 36751,\n    \"Ġfug\": 36752,\n    \"Vision\": 36753,\n    \"075\": 36754,\n    \"Ġadoptive\": 36755,\n    \"Ġunknow\": 36756,\n    \"Stream\": 36757,\n    \"Ġaffili\": 36758,\n    \"ĠPUR\": 36759,\n    \"ĠWally\": 36760,\n    \"Ġgamer\": 36761,\n    \"Ġfart\": 36762,\n    \"stice\": 36763,\n    \"Ġcongen\": 36764,\n    \"Ð½\": 36765,\n    \"685\": 36766,\n    \"orst\": 36767,\n    \"ĠATF\": 36768,\n    \"Ġml\": 36769,\n    \"ĠMozilla\": 36770,\n    \"Ġcalmed\": 36771,\n    \"bage\": 36772,\n    \"ĠVault\": 36773,\n    \"arkable\": 36774,\n    \"ĠGuan\": 36775,\n    \"Ġclueless\": 36776,\n    \"umatic\": 36777,\n    \"Ġshameless\": 36778,\n    \"Ġpreached\": 36779,\n    \"Ġmisconceptions\": 36780,\n    \"Ġanthology\": 36781,\n    \"Ġbiomass\": 36782,\n    \"ĠPs\": 36783,\n    \"tails\": 36784,\n    \"Ġexcessively\": 36785,\n    \"Ġextr\": 36786,\n    \"Davis\": 36787,\n    \"Ġgrounding\": 36788,\n    \"Ġshortcuts\": 36789,\n    \"ĠShift\": 36790,\n    \"ĠRew\": 36791,\n    \"ĠIllum\": 36792,\n    \"Ġincite\": 36793,\n    \"sense\": 36794,\n    \"ĠScouting\": 36795,\n    \"otos\": 36796,\n    \"respond\": 36797,\n    \"Ġbeware\": 36798,\n    \"gran\": 36799,\n    \"ĠXV\": 36800,\n    \"JM\": 36801,\n    \"ĠSounders\": 36802,\n    \"Ġ276\": 36803,\n    \"Ġshockingly\": 36804,\n    \"Ġgastrointestinal\": 36805,\n    \"erences\": 36806,\n    \"df\": 36807,\n    \"ĠNG\": 36808,\n    \"Ġdiscredited\": 36809,\n    \"Ġdemoral\": 36810,\n    \"Ġgladly\": 36811,\n    \"Tal\": 36812,\n    \"ĠPredator\": 36813,\n    \"708\": 36814,\n    \"Ġdoi\": 36815,\n    \"Ġdecentral\": 36816,\n    \"illin\": 36817,\n    \"printed\": 36818,\n    \"Ġinflicting\": 36819,\n    \"ribes\": 36820,\n    \"Ġsupper\": 36821,\n    \"abc\": 36822,\n    \"Ġgraz\": 36823,\n    \"980\": 36824,\n    \"Bull\": 36825,\n    \"Ġmillionaires\": 36826,\n    \"Ġvanity\": 36827,\n    \"imony\": 36828,\n    \"Ġbiologists\": 36829,\n    \"Ġalternating\": 36830,\n    \"Ġsleeps\": 36831,\n    \"Force\": 36832,\n    \"ĠPrinc\": 36833,\n    \"ĠTransgender\": 36834,\n    \"Ġ314\": 36835,\n    \"ĠProvide\": 36836,\n    \"enthal\": 36837,\n    \"Ġplum\": 36838,\n    \"Ġresurrect\": 36839,\n    \"CW\": 36840,\n    \"Ġinjure\": 36841,\n    \"ĠPerspective\": 36842,\n    \"ĠBei\": 36843,\n    \"Ġrestless\": 36844,\n    \"aciously\": 36845,\n    \"Ġchlor\": 36846,\n    \"catch\": 36847,\n    \"ĠLuigi\": 36848,\n    \"Ġinconsistency\": 36849,\n    \"Ġwhiff\": 36850,\n    \"Arizona\": 36851,\n    \"ustration\": 36852,\n    \"ĠRaid\": 36853,\n    \"ĠDemons\": 36854,\n    \"ĠVita\": 36855,\n    \":\\\"\": 36856,\n    \"Ġmigraine\": 36857,\n    \"ĠHamb\": 36858,\n    \"Ġwidget\": 36859,\n    \"451\": 36860,\n    \"Ġrandomized\": 36861,\n    \"etchup\": 36862,\n    \"ĠParticularly\": 36863,\n    \"Ġdiced\": 36864,\n    \"Ġperfected\": 36865,\n    \"roid\": 36866,\n    \"710\": 36867,\n    \"Ġreflections\": 36868,\n    \"Ġantioxidants\": 36869,\n    \"ĠLabel\": 36870,\n    \"Ġ326\": 36871,\n    \"igious\": 36872,\n    \"ĠEucl\": 36873,\n    \"608\": 36874,\n    \"Ġstrand\": 36875,\n    \"ĠDirt\": 36876,\n    \"ĠLift\": 36877,\n    \"suits\": 36878,\n    \"ĠControls\": 36879,\n    \"RAW\": 36880,\n    \"Ġcowardly\": 36881,\n    \"ĠUmb\": 36882,\n    \"Growing\": 36883,\n    \"mington\": 36884,\n    \"Ġ339\": 36885,\n    \"ĠCommit\": 36886,\n    \"Ġnonviolent\": 36887,\n    \"Ġcontaminants\": 36888,\n    \"Ġacrylic\": 36889,\n    \"ĠMAP\": 36890,\n    \"Ġ269\": 36891,\n    \"Ġdegrading\": 36892,\n    \"Ġmiracles\": 36893,\n    \"ĠEstablishment\": 36894,\n    \"despite\": 36895,\n    \"cry\": 36896,\n    \"Ġpauses\": 36897,\n    \"Ġmythical\": 36898,\n    \"Ġtwenties\": 36899,\n    \"Actually\": 36900,\n    \"phan\": 36901,\n    \"recorded\": 36902,\n    \"Ġunwillingness\": 36903,\n    \"engineering\": 36904,\n    \"avored\": 36905,\n    \"Ġdevout\": 36906,\n    \"item\": 36907,\n    \"Ġbunny\": 36908,\n    \"ĠMerchants\": 36909,\n    \"Ġconsumes\": 36910,\n    \"508\": 36911,\n    \"Ġlex\": 36912,\n    \"ĠClause\": 36913,\n    \"Ġchecklist\": 36914,\n    \"Sus\": 36915,\n    \"uther\": 36916,\n    \".#\": 36917,\n    \"Bit\": 36918,\n    \"uay\": 36919,\n    \"bf\": 36920,\n    \"Ġpopulace\": 36921,\n    \"Ġ316\": 36922,\n    \"Ġcombust\": 36923,\n    \"Ġnano\": 36924,\n    \"Ġpopul\": 36925,\n    \"Indust\": 36926,\n    \"Ġcapitalists\": 36927,\n    \"ĠFiles\": 36928,\n    \"Bang\": 36929,\n    \"Ġkosher\": 36930,\n    \"atile\": 36931,\n    \"Ġincrim\": 36932,\n    \"OVER\": 36933,\n    \"Ġmelee\": 36934,\n    \"ymph\": 36935,\n    \"ĠPupp\": 36936,\n    \"evin\": 36937,\n    \"ĠMolecular\": 36938,\n    \"Ġmisinterpret\": 36939,\n    \"vc\": 36940,\n    \"olithic\": 36941,\n    \"ĠSimpsons\": 36942,\n    \"Ġshrew\": 36943,\n    \"Ġselectively\": 36944,\n    \"ĠDrain\": 36945,\n    \"mittedly\": 36946,\n    \"conservative\": 36947,\n    \"True\": 36948,\n    \"Using\": 36949,\n    \"562\": 36950,\n    \"apon\": 36951,\n    \"Ġapprentice\": 36952,\n    \"Mas\": 36953,\n    \"ĠBattlefield\": 36954,\n    \"Ġfing\": 36955,\n    \"Ġconcoct\": 36956,\n    \"ĠVIS\": 36957,\n    \"ĠHuss\": 36958,\n    \"Ġdetects\": 36959,\n    \"ĠFriedrich\": 36960,\n    \"Ġlatitude\": 36961,\n    \"Custom\": 36962,\n    \"ĠÙ\": 36963,\n    \"ĠBones\": 36964,\n    \"whose\": 36965,\n    \"Ġredirected\": 36966,\n    \"aligned\": 36967,\n    \"ĠNeighbor\": 36968,\n    \"ĠAmen\": 36969,\n    \"ĠMarble\": 36970,\n    \"Beyond\": 36971,\n    \"Ġbiomark\": 36972,\n    \"Ġerroneous\": 36973,\n    \"Atlanta\": 36974,\n    \"Ġmasturb\": 36975,\n    \"ĠAssoci\": 36976,\n    \"Albert\": 36977,\n    \"Ġcigar\": 36978,\n    \"ĠFraz\": 36979,\n    \"ethe\": 36980,\n    \"skinned\": 36981,\n    \"Ford\": 36982,\n    \"throp\": 36983,\n    \"Acc\": 36984,\n    \"Ġtricked\": 36985,\n    \"Ġoverwhelm\": 36986,\n    \"Ġimplements\": 36987,\n    \"ĠGeForce\": 36988,\n    \"Ġbounces\": 36989,\n    \"Ġmoderator\": 36990,\n    \"910\": 36991,\n    \"ĠButterfly\": 36992,\n    \"ĠIllegal\": 36993,\n    \"ĠSubject\": 36994,\n    \"RET\": 36995,\n    \"ĠFreeze\": 36996,\n    \"ĠNewt\": 36997,\n    \"Ġuterus\": 36998,\n    \"696\": 36999,\n    \"Ġ267\": 37000,\n    \"tk\": 37001,\n    \"Ġdodged\": 37002,\n    \"liam\": 37003,\n    \"Ġparasite\": 37004,\n    \"obal\": 37005,\n    \"ĠHubble\": 37006,\n    \"Ġtheology\": 37007,\n    \"âĢĶ\\\"\": 37008,\n    \"height\": 37009,\n    \"Ale\": 37010,\n    \"employment\": 37011,\n    \"ĠWallet\": 37012,\n    \"cessive\": 37013,\n    \"Ġ404\": 37014,\n    \"Ġsimilarity\": 37015,\n    \"zens\": 37016,\n    \"Ġdumps\": 37017,\n    \"Ġdepress\": 37018,\n    \"Ġlifeless\": 37019,\n    \"535\": 37020,\n    \"oard\": 37021,\n    \"Scotland\": 37022,\n    \"Ġbelievable\": 37023,\n    \"Ġcalculator\": 37024,\n    \"ĠNaked\": 37025,\n    \"Ġremission\": 37026,\n    \"Ġoranges\": 37027,\n    \"ĠSections\": 37028,\n    \"Ġentangled\": 37029,\n    \"Ġuncanny\": 37030,\n    \"Ġteaspoons\": 37031,\n    \"vr\": 37032,\n    \"ĠPorn\": 37033,\n    \"Organ\": 37034,\n    \"Ġbund\": 37035,\n    \"Doug\": 37036,\n    \"ĠGHz\": 37037,\n    \"Major\": 37038,\n    \"abus\": 37039,\n    \"Bell\": 37040,\n    \"avier\": 37041,\n    \"Ġimplanted\": 37042,\n    \"RON\": 37043,\n    \"Fle\": 37044,\n    \"462\": 37045,\n    \"509\": 37046,\n    \"Ġgoggles\": 37047,\n    \"Ġmanuscript\": 37048,\n    \"NOT\": 37049,\n    \"ĠCanaveral\": 37050,\n    \"ĠDID\": 37051,\n    \"Season\": 37052,\n    \"HAEL\": 37053,\n    \"Edge\": 37054,\n    \"appiness\": 37055,\n    \"DIS\": 37056,\n    \"Ġplotted\": 37057,\n    \"Ġwrought\": 37058,\n    \"Ġquarantine\": 37059,\n    \"Ġrearr\": 37060,\n    \"itage\": 37061,\n    \"Ġsocket\": 37062,\n    \"Ġbrig\": 37063,\n    \"Ġunbelievably\": 37064,\n    \"abytes\": 37065,\n    \"TG\": 37066,\n    \"Ġ444\": 37067,\n    \"ĠOffic\": 37068,\n    \"Ġacquaintances\": 37069,\n    \"ĠComparison\": 37070,\n    \"Nine\": 37071,\n    \"ĠFeast\": 37072,\n    \"758\": 37073,\n    \"YC\": 37074,\n    \"Ġfiner\": 37075,\n    \"ĠStrawberry\": 37076,\n    \"Ġeternity\": 37077,\n    \"liament\": 37078,\n    \"urrency\": 37079,\n    \"ĠCortana\": 37080,\n    \"ĠSabbath\": 37081,\n    \"Ġsprinkle\": 37082,\n    \"unker\": 37083,\n    \"ĠUE\": 37084,\n    \"flies\": 37085,\n    \"Ġblender\": 37086,\n    \"Ġacutely\": 37087,\n    \"emark\": 37088,\n    \"ĠAffect\": 37089,\n    \"Politics\": 37090,\n    \"Ġsane\": 37091,\n    \"Ġcorrosion\": 37092,\n    \"Ġspirituality\": 37093,\n    \"Ġredeemed\": 37094,\n    \"Ġingrained\": 37095,\n    \"manager\": 37096,\n    \"joined\": 37097,\n    \"ĠDumb\": 37098,\n    \"ĠHeight\": 37099,\n    \"Ġseventeen\": 37100,\n    \"Ġ640\": 37101,\n    \"Ġreviewer\": 37102,\n    \"Ġwallpaper\": 37103,\n    \"Ġnurs\": 37104,\n    \"Ġsubset\": 37105,\n    \"703\": 37106,\n    \"Ġsymbolism\": 37107,\n    \"Ġdudes\": 37108,\n    \"Ġmismatch\": 37109,\n    \"gans\": 37110,\n    \"please\": 37111,\n    \"ĠKE\": 37112,\n    \"Ġatom\": 37113,\n    \"004\": 37114,\n    \"ionic\": 37115,\n    \"Ġservings\": 37116,\n    \"Ġproxies\": 37117,\n    \"Ġtranscription\": 37118,\n    \"yx\": 37119,\n    \"bowl\": 37120,\n    \"iscovery\": 37121,\n    \"ĠScotch\": 37122,\n    \"brace\": 37123,\n    \"riter\": 37124,\n    \"ĠDesktop\": 37125,\n    \"Ġlimestone\": 37126,\n    \"æ\": 37127,\n    \"Neg\": 37128,\n    \"013\": 37129,\n    \"Ġformulas\": 37130,\n    \"Ġeval\": 37131,\n    \"Ġzombies\": 37132,\n    \"GU\": 37133,\n    \"ĠHermes\": 37134,\n    \"Ġbrist\": 37135,\n    \"Mand\": 37136,\n    \"Ġmastery\": 37137,\n    \"Ġgoverns\": 37138,\n    \"Ġconstrued\": 37139,\n    \"region\": 37140,\n    \"Ġemitted\": 37141,\n    \"Vice\": 37142,\n    \"060\": 37143,\n    \"Jennifer\": 37144,\n    \"mol\": 37145,\n    \"Ġjealousy\": 37146,\n    \"Ġingenuity\": 37147,\n    \"bug\": 37148,\n    \"olitical\": 37149,\n    \"Ġperce\": 37150,\n    \"ĠSapp\": 37151,\n    \"dim\": 37152,\n    \"utral\": 37153,\n    \"Ġinterrogated\": 37154,\n    \"Gate\": 37155,\n    \"Ġamber\": 37156,\n    \"911\": 37157,\n    \"ĠEveryday\": 37158,\n    \"ĠDDR\": 37159,\n    \"ĠBlades\": 37160,\n    \"Ġnifty\": 37161,\n    \"Ġmurderers\": 37162,\n    \"Ġpresumption\": 37163,\n    \"Pitt\": 37164,\n    \"Div\": 37165,\n    \"ĠDestination\": 37166,\n    \"having\": 37167,\n    \"Ġprolifer\": 37168,\n    \"Ġbreaker\": 37169,\n    \"ĠBW\": 37170,\n    \"Ġcourier\": 37171,\n    \"Try\": 37172,\n    \"ĠBUR\": 37173,\n    \"itized\": 37174,\n    \"Ġcompress\": 37175,\n    \"Ġrepetition\": 37176,\n    \"ĠTik\": 37177,\n    \"Ġdivergence\": 37178,\n    \"Ġcube\": 37179,\n    \"everyone\": 37180,\n    \"ĠPoles\": 37181,\n    \"418\": 37182,\n    \"ĠHighly\": 37183,\n    \"468\": 37184,\n    \"Jeremy\": 37185,\n    \"Ġcontradictions\": 37186,\n    \"Ġmanure\": 37187,\n    \"Sad\": 37188,\n    \"pletion\": 37189,\n    \"626\": 37190,\n    \"Ġ279\": 37191,\n    \"Ġfrivolous\": 37192,\n    \"ĠCanaan\": 37193,\n    \"olor\": 37194,\n    \"Ġincapac\": 37195,\n    \"ĠGentle\": 37196,\n    \"Ġinsomnia\": 37197,\n    \"ĠJing\": 37198,\n    \"688\": 37199,\n    \"ĠViews\": 37200,\n    \"Ġsyll\": 37201,\n    \"486\": 37202,\n    \"antom\": 37203,\n    \"Ġcog\": 37204,\n    \"aintain\": 37205,\n    \"ĠDVDs\": 37206,\n    \"Ġ318\": 37207,\n    \"archy\": 37208,\n    \"Ġreprodu\": 37209,\n    \"Ġconcedes\": 37210,\n    \"Brook\": 37211,\n    \"Ġinterpreting\": 37212,\n    \"Ġextracting\": 37213,\n    \"Ġess\": 37214,\n    \"uning\": 37215,\n    \"ĠMathematics\": 37216,\n    \"iably\": 37217,\n    \"Ġmultit\": 37218,\n    \"ĠActs\": 37219,\n    \"iliated\": 37220,\n    \"Foreign\": 37221,\n    \"Ġflaming\": 37222,\n    \"ĠCoup\": 37223,\n    \"Ġglitches\": 37224,\n    \"Ġdifferentiation\": 37225,\n    \"ihadi\": 37226,\n    \"ĠDrone\": 37227,\n    \"Ġincompatible\": 37228,\n    \"asher\": 37229,\n    \"documented\": 37230,\n    \"agons\": 37231,\n    \"wark\": 37232,\n    \"Ġshielding\": 37233,\n    \"ĠCorrect\": 37234,\n    \"romising\": 37235,\n    \"uned\": 37236,\n    \"Ġconduit\": 37237,\n    \"ĠDiablo\": 37238,\n    \"Ġbeginner\": 37239,\n    \"Ġarchived\": 37240,\n    \"smanship\": 37241,\n    \"ĠTBD\": 37242,\n    \"digy\": 37243,\n    \"Ġ322\": 37244,\n    \"Ġ268\": 37245,\n    \"ĠTears\": 37246,\n    \"ĠPriority\": 37247,\n    \"Italy\": 37248,\n    \"Ġ^\": 37249,\n    \"annot\": 37250,\n    \"different\": 37251,\n    \"Joy\": 37252,\n    \"Ġbreathed\": 37253,\n    \"heon\": 37254,\n    \"Ġracists\": 37255,\n    \"Ġvascular\": 37256,\n    \"Between\": 37257,\n    \"etition\": 37258,\n    \"ĠLikely\": 37259,\n    \"icans\": 37260,\n    \"529\": 37261,\n    \"ĠMonsters\": 37262,\n    \"agy\": 37263,\n    \"Orange\": 37264,\n    \"hide\": 37265,\n    \"SIM\": 37266,\n    \"Ġdeceive\": 37267,\n    \"ĠDAR\": 37268,\n    \"Ġshattering\": 37269,\n    \"Ġow\": 37270,\n    \"peak\": 37271,\n    \"Ġpreferable\": 37272,\n    \"Ġpiping\": 37273,\n    \"ĠLEDs\": 37274,\n    \"ĠCOMMUN\": 37275,\n    \"ĠConstruct\": 37276,\n    \"008\": 37277,\n    \"Ġdissatisfied\": 37278,\n    \"ĠKNOW\": 37279,\n    \"ĠFrame\": 37280,\n    \"ĠToast\": 37281,\n    \"Ġadore\": 37282,\n    \"history\": 37283,\n    \"Soviet\": 37284,\n    \"reporting\": 37285,\n    \"Ġ266\": 37286,\n    \"pract\": 37287,\n    \"ĠSauce\": 37288,\n    \"686\": 37289,\n    \"ievers\": 37290,\n    \"ĠDomain\": 37291,\n    \"ousand\": 37292,\n    \"768\": 37293,\n    \"Cos\": 37294,\n    \"609\": 37295,\n    \"432\": 37296,\n    \"Ġtransl\": 37297,\n    \"oof\": 37298,\n    \"Ġ292\": 37299,\n    \"Turkish\": 37300,\n    \"ĠPOLIT\": 37301,\n    \"Harris\": 37302,\n    \"bj\": 37303,\n    \"Ġrodents\": 37304,\n    \"556\": 37305,\n    \"Ġintellectuals\": 37306,\n    \"Ġinteroper\": 37307,\n    \"ixt\": 37308,\n    \"Ġunbiased\": 37309,\n    \"itia\": 37310,\n    \"Ġ504\": 37311,\n    \"Ġbuttocks\": 37312,\n    \"ĠFlam\": 37313,\n    \"Ġchrom\": 37314,\n    \"Ġ259\": 37315,\n    \"shock\": 37316,\n    \"ĠRJ\": 37317,\n    \"ĠLich\": 37318,\n    \"422\": 37319,\n    \"Ġcondom\": 37320,\n    \"phen\": 37321,\n    \"Ġvigilante\": 37322,\n    \"Ġowl\": 37323,\n    \"Ġdwellings\": 37324,\n    \"Ġarchaeologists\": 37325,\n    \"Ġ680\": 37326,\n    \"RAY\": 37327,\n    \"Ġ1921\": 37328,\n    \"Ġ625\": 37329,\n    \"ĠPLAN\": 37330,\n    \"alde\": 37331,\n    \"030\": 37332,\n    \"abbling\": 37333,\n    \"Wave\": 37334,\n    \"Ni\": 37335,\n    \"Ġfurthe\": 37336,\n    \"JS\": 37337,\n    \"Ġpsycho\": 37338,\n    \"ĠFranÃ§ois\": 37339,\n    \"Ġundergrad\": 37340,\n    \"Ġsuccessors\": 37341,\n    \"Ġpadded\": 37342,\n    \"introdu\": 37343,\n    \"Ġreasoned\": 37344,\n    \"Ġvas\": 37345,\n    \"creen\": 37346,\n    \"onsequ\": 37347,\n    \"starter\": 37348,\n    \"Court\": 37349,\n    \"ĠHIS\": 37350,\n    \"Ġplaster\": 37351,\n    \"Ġranger\": 37352,\n    \"Ġ298\": 37353,\n    \"esters\": 37354,\n    \"Ġglare\": 37355,\n    \"ype\": 37356,\n    \"Ġcompute\": 37357,\n    \"Ali\": 37358,\n    \"mallow\": 37359,\n    \"Ġmasculine\": 37360,\n    \"ĠExamination\": 37361,\n    \"improve\": 37362,\n    \"Ġdeclass\": 37363,\n    \"Ġdecoration\": 37364,\n    \"ĠFIG\": 37365,\n    \"abre\": 37366,\n    \"Ġstale\": 37367,\n    \"abling\": 37368,\n    \"ĠRusty\": 37369,\n    \"ĠASAP\": 37370,\n    \"Ġadjusts\": 37371,\n    \"Ġbluff\": 37372,\n    \"density\": 37373,\n    \"Ġdisse\": 37374,\n    \"Ġcensor\": 37375,\n    \"ervatives\": 37376,\n    \"Ġkettle\": 37377,\n    \"Ġskeptics\": 37378,\n    \"fd\": 37379,\n    \"Imm\": 37380,\n    \"461\": 37381,\n    \"Ġadvantageous\": 37382,\n    \"419\": 37383,\n    \"ĠPresents\": 37384,\n    \"482\": 37385,\n    \"ĠRewards\": 37386,\n    \"Ġovershadow\": 37387,\n    \"Alabama\": 37388,\n    \"ĠCPC\": 37389,\n    \"Ġsock\": 37390,\n    \"ĠChurches\": 37391,\n    \"hidden\": 37392,\n    \"Ġcringe\": 37393,\n    \"ĠHOR\": 37394,\n    \"PB\": 37395,\n    \"Pretty\": 37396,\n    \"Hong\": 37397,\n    \"?),\": 37398,\n    \"687\": 37399,\n    \"Ġgrocer\": 37400,\n    \"472\": 37401,\n    \"565\": 37402,\n    \"itent\": 37403,\n    \"Ġpartake\": 37404,\n    \"wait\": 37405,\n    \"usters\": 37406,\n    \"Ġcones\": 37407,\n    \"Ġconcurrently\": 37408,\n    \"Ġlevers\": 37409,\n    \"Ġaroma\": 37410,\n    \"ĠDrill\": 37411,\n    \"498\": 37412,\n    \"804\": 37413,\n    \"ithering\": 37414,\n    \"Ġ355\": 37415,\n    \"Ġlegion\": 37416,\n    \"Ġvitri\": 37417,\n    \"Ġcondu\": 37418,\n    \"Angel\": 37419,\n    \"OWER\": 37420,\n    \"Ġ{*\": 37421,\n    \"Simon\": 37422,\n    \"Ġsynthesis\": 37423,\n    \"ĠContainer\": 37424,\n    \"sheet\": 37425,\n    \"Bi\": 37426,\n    \"ĠRaspberry\": 37427,\n    \"Ġ328\": 37428,\n    \"anders\": 37429,\n    \"ĠBlossom\": 37430,\n    \"ĠFINAL\": 37431,\n    \"acid\": 37432,\n    \"Ġborderline\": 37433,\n    \"Aut\": 37434,\n    \"Ġoriginate\": 37435,\n    \"Ġtransm\": 37436,\n    \"Ġbuffalo\": 37437,\n    \"atial\": 37438,\n    \"ĠCraigslist\": 37439,\n    \"Ġcredential\": 37440,\n    \"Ġdisbanded\": 37441,\n    \"Ġunprotected\": 37442,\n    \"ĠZer\": 37443,\n    \"waukee\": 37444,\n    \"diagn\": 37445,\n    \"1999\": 37446,\n    \"doc\": 37447,\n    \"ellig\": 37448,\n    \"Ġwarheads\": 37449,\n    \"ĠADS\": 37450,\n    \"verified\": 37451,\n    \"ĠHAM\": 37452,\n    \"785\": 37453,\n    \"Cu\": 37454,\n    \"Ġenorm\": 37455,\n    \"ĠSkill\": 37456,\n    \"\\\\\": 37457,\n    \"Ġbashing\": 37458,\n    \"Ġloudspe\": 37459,\n    \"during\": 37460,\n    \"Ġdebunked\": 37461,\n    \"adequ\": 37462,\n    \"Ġuh\": 37463,\n    \"Feed\": 37464,\n    \"ificial\": 37465,\n    \"pred\": 37466,\n    \"ĠPassing\": 37467,\n    \"Kyle\": 37468,\n    \"enance\": 37469,\n    \"ĠMex\": 37470,\n    \"itect\": 37471,\n    \"Ġcavern\": 37472,\n    \"Ġtrop\": 37473,\n    \"ĠEliot\": 37474,\n    \"753\": 37475,\n    \"Ġencountering\": 37476,\n    \"Ġsulf\": 37477,\n    \"Always\": 37478,\n    \"ĠGest\": 37479,\n    \"Ġadditive\": 37480,\n    \"Ġ278\": 37481,\n    \"Ġloops\": 37482,\n    \"liberal\": 37483,\n    \"urion\": 37484,\n    \"ĠRefresh\": 37485,\n    \"ĠDynasty\": 37486,\n    \"Ġsweaty\": 37487,\n    \"Ġsails\": 37488,\n    \"protection\": 37489,\n    \"ĠRooms\": 37490,\n    \"ĠEXT\": 37491,\n    \"few\": 37492,\n    \"ĠPaid\": 37493,\n    \"Ġ377\": 37494,\n    \"Ġcolonialism\": 37495,\n    \"Ġchuckle\": 37496,\n    \"Ġarmour\": 37497,\n    \"Ġsoftly\": 37498,\n    \"661\": 37499,\n    \"Building\": 37500,\n    \"ĠAMER\": 37501,\n    \"Ġbabe\": 37502,\n    \"Ġshif\": 37503,\n    \"Sem\": 37504,\n    \"Ġdisembark\": 37505,\n    \"ĠSubstance\": 37506,\n    \"Stone\": 37507,\n    \"Ġdialect\": 37508,\n    \"ĠAph\": 37509,\n    \"Ġspreadsheet\": 37510,\n    \"ierra\": 37511,\n    \"Ġlineage\": 37512,\n    \"ĠCust\": 37513,\n    \"ĠBabe\": 37514,\n    \"Ġwra\": 37515,\n    \"ĠMafia\": 37516,\n    \"Ġflakes\": 37517,\n    \"ĠEVER\": 37518,\n    \"cong\": 37519,\n    \"ĠCreation\": 37520,\n    \"loo\": 37521,\n    \"ĠAmpl\": 37522,\n    \"ĠSpectre\": 37523,\n    \"012\": 37524,\n    \"geons\": 37525,\n    \"Ġswarm\": 37526,\n    \"ĠPale\": 37527,\n    \"ĠSeek\": 37528,\n    \"itures\": 37529,\n    \"Ġarri\": 37530,\n    \"Ġredistribution\": 37531,\n    \"campaign\": 37532,\n    \"ĠAbility\": 37533,\n    \"579\": 37534,\n    \"ournament\": 37535,\n    \"locks\": 37536,\n    \"Ġnests\": 37537,\n    \"ĠConstantine\": 37538,\n    \"Ġwhisper\": 37539,\n    \"Ġshrouded\": 37540,\n    \"changed\": 37541,\n    \"ĠEnhanced\": 37542,\n    \"Ġ920\": 37543,\n    \"Ġglob\": 37544,\n    \"Tam\": 37545,\n    \"Ġoutwe\": 37546,\n    \"Ġilliter\": 37547,\n    \"Ġsurg\": 37548,\n    \"Nap\": 37549,\n    \"ĠAerial\": 37550,\n    \"iferation\": 37551,\n    \"Egypt\": 37552,\n    \"ERO\": 37553,\n    \"Ġantip\": 37554,\n    \"environment\": 37555,\n    \"machine\": 37556,\n    \"Ġrupture\": 37557,\n    \"treatment\": 37558,\n    \"internal\": 37559,\n    \"Ġinfiltrate\": 37560,\n    \"Ġgratification\": 37561,\n    \"Uber\": 37562,\n    \"Ġunequal\": 37563,\n    \"Ġflav\": 37564,\n    \"Lord\": 37565,\n    \"tein\": 37566,\n    \"ĠLOT\": 37567,\n    \"Ġbullshit\": 37568,\n    \"Ġoriginals\": 37569,\n    \"Ġminced\": 37570,\n    \"Ġmultiply\": 37571,\n    \"ayson\": 37572,\n    \"Ġrecomm\": 37573,\n    \"Ġreceptors\": 37574,\n    \"Ġflashlight\": 37575,\n    \"Ġinhuman\": 37576,\n    \"Future\": 37577,\n    \"Ġpuzzling\": 37578,\n    \"Ġrouters\": 37579,\n    \"Ġuncontroll\": 37580,\n    \"responsible\": 37581,\n    \"Ġcellul\": 37582,\n    \"ĠTablet\": 37583,\n    \"Ġbolted\": 37584,\n    \"Ġpermissible\": 37585,\n    \"adra\": 37586,\n    \"picture\": 37587,\n    \"ODY\": 37588,\n    \"BRE\": 37589,\n    \"Iraq\": 37590,\n    \"Total\": 37591,\n    \"rising\": 37592,\n    \"Ġ273\": 37593,\n    \"nv\": 37594,\n    \"Ġ327\": 37595,\n    \"alysed\": 37596,\n    \"infect\": 37597,\n    \"Ġ1912\": 37598,\n    \"ĠVT\": 37599,\n    \"ĠLazarus\": 37600,\n    \"ictive\": 37601,\n    \"Bu\": 37602,\n    \"ĠNEVER\": 37603,\n    \"ĠCODE\": 37604,\n    \"ĠModified\": 37605,\n    \"fetched\": 37606,\n    \"ĠTrap\": 37607,\n    \"mob\": 37608,\n    \"Ġupkeep\": 37609,\n    \"WARD\": 37610,\n    \"Ġbrewed\": 37611,\n    \"Ġsaliva\": 37612,\n    \"Ġ1923\": 37613,\n    \"Ġsteroid\": 37614,\n    \"rather\": 37615,\n    \"ĠVER\": 37616,\n    \"Ġcontextual\": 37617,\n    \"Ont\": 37618,\n    \"ĠLSD\": 37619,\n    \"agine\": 37620,\n    \"Ġaudible\": 37621,\n    \"ĠMeta\": 37622,\n    \"erek\": 37623,\n    \"aults\": 37624,\n    \"ĠOttoman\": 37625,\n    \"ĠIncludes\": 37626,\n    \"Ġocc\": 37627,\n    \"678\": 37628,\n    \"ipple\": 37629,\n    \"Ġcontrasted\": 37630,\n    \"014\": 37631,\n    \"ĠLenin\": 37632,\n    \"Ġomega\": 37633,\n    \"885\": 37634,\n    \"civil\": 37635,\n    \"Ġoverload\": 37636,\n    \"},\\\"\": 37637,\n    \"Ġprogrammers\": 37638,\n    \"Ġgeometry\": 37639,\n    \"?).\": 37640,\n    \"shift\": 37641,\n    \"ĠClancy\": 37642,\n    \"nr\": 37643,\n    \"verb\": 37644,\n    \"Ġ760\": 37645,\n    \"Ġstaggered\": 37646,\n    \"Playing\": 37647,\n    \"ĠSmile\": 37648,\n    \"Ġcomplains\": 37649,\n    \"ĠSloven\": 37650,\n    \"Ġdisobedience\": 37651,\n    \"creator\": 37652,\n    \"Ġly\": 37653,\n    \"incoln\": 37654,\n    \"emp\": 37655,\n    \"Ġcrate\": 37656,\n    \"ĠPledge\": 37657,\n    \"ĠGPUs\": 37658,\n    \"protected\": 37659,\n    \"Vo\": 37660,\n    \"medium\": 37661,\n    \"Ġacet\": 37662,\n    \"603\": 37663,\n    \"478\": 37664,\n    \"469\": 37665,\n    \"Further\": 37666,\n    \"Ġsensed\": 37667,\n    \"Lock\": 37668,\n    \"Ġcrabs\": 37669,\n    \"ĠChains\": 37670,\n    \"ĠNEO\": 37671,\n    \"Ġexperimented\": 37672,\n    \"ĠRhythm\": 37673,\n    \"802\": 37674,\n    \"Ġhormonal\": 37675,\n    \"491\": 37676,\n    \"ĠMedian\": 37677,\n    \"Ġevaluates\": 37678,\n    \"ippi\": 37679,\n    \"Ġremovable\": 37680,\n    \"Ġvector\": 37681,\n    \"ilant\": 37682,\n    \"TERN\": 37683,\n    \"Ġpurch\": 37684,\n    \"ĠBind\": 37685,\n    \"athering\": 37686,\n    \"Ġcords\": 37687,\n    \"Lib\": 37688,\n    \"Ġdamned\": 37689,\n    \"orc\": 37690,\n    \"ĠEverywhere\": 37691,\n    \"Ġgorilla\": 37692,\n    \"ystem\": 37693,\n    \"fail\": 37694,\n    \"Ġecstasy\": 37695,\n    \"allion\": 37696,\n    \"Sea\": 37697,\n    \"Ġuploading\": 37698,\n    \"ĠSpecific\": 37699,\n    \"Ġreinforcement\": 37700,\n    \"cerned\": 37701,\n    \"ĠDollars\": 37702,\n    \"Twenty\": 37703,\n    \"OX\": 37704,\n    \"ADD\": 37705,\n    \"Ġbraces\": 37706,\n    \"Ġraven\": 37707,\n    \"Ġ1890\": 37708,\n    \"Ġcirculate\": 37709,\n    \"udden\": 37710,\n    \"Disney\": 37711,\n    \"ĠNope\": 37712,\n    \"ĠBagg\": 37713,\n    \"ĠBuddha\": 37714,\n    \"rael\": 37715,\n    \"urus\": 37716,\n    \"ĠKarma\": 37717,\n    \"Ġcurl\": 37718,\n    \"Ġflips\": 37719,\n    \"Ġbearer\": 37720,\n    \"Ġmisunderstand\": 37721,\n    \"Ġabras\": 37722,\n    \"ĠAssassin\": 37723,\n    \"Fact\": 37724,\n    \"Ġinterf\": 37725,\n    \"Ġvantage\": 37726,\n    \"ĠGenocide\": 37727,\n    \"Ġdeducted\": 37728,\n    \"Sep\": 37729,\n    \"McC\": 37730,\n    \"Jessica\": 37731,\n    \"ĠBackup\": 37732,\n    \"Ian\": 37733,\n    \"urnal\": 37734,\n    \"Ġlaborers\": 37735,\n    \"438\": 37736,\n    \"ĠContinuous\": 37737,\n    \"ĠNBN\": 37738,\n    \"Cool\": 37739,\n    \"mitting\": 37740,\n    \"ĠNormandy\": 37741,\n    \"Ġpurchaser\": 37742,\n    \"Ġacquainted\": 37743,\n    \"Ġblogging\": 37744,\n    \"route\": 37745,\n    \"marine\": 37746,\n    \"Ġstartled\": 37747,\n    \"6000\": 37748,\n    \"ĠRadical\": 37749,\n    \"kiss\": 37750,\n    \"ĠBlitz\": 37751,\n    \"express\": 37752,\n    \"Ġ601\": 37753,\n    \"hent\": 37754,\n    \"Ġtink\": 37755,\n    \"pires\": 37756,\n    \"launch\": 37757,\n    \"sg\": 37758,\n    \"ĠEffects\": 37759,\n    \"Ġstiffness\": 37760,\n    \"ĠAllies\": 37761,\n    \"Ġthirsty\": 37762,\n    \"Ġmyst\": 37763,\n    \"Ġlogger\": 37764,\n    \"Ġstances\": 37765,\n    \"ĠEvaluation\": 37766,\n    \"090\": 37767,\n    \"Ġproclaiming\": 37768,\n    \"Ġhypocritical\": 37769,\n    \"496\": 37770,\n    \"Ġcaus\": 37771,\n    \"ĠKappa\": 37772,\n    \"ĠLann\": 37773,\n    \"ĠScientist\": 37774,\n    \"Ġempath\": 37775,\n    \"etrical\": 37776,\n    \"lege\": 37777,\n    \"Hom\": 37778,\n    \"Aud\": 37779,\n    \"ĠColors\": 37780,\n    \"ĠStraw\": 37781,\n    \"each\": 37782,\n    \"ĠPatron\": 37783,\n    \"Ġnuance\": 37784,\n    \"send\": 37785,\n    \"ourney\": 37786,\n    \"ĠPhen\": 37787,\n    \"Ġamino\": 37788,\n    \"ĠSeconds\": 37789,\n    \"Sn\": 37790,\n    \"ĠCiv\": 37791,\n    \"Ġconglomer\": 37792,\n    \"Ġ411\": 37793,\n    \"versely\": 37794,\n    \"487\": 37795,\n    \"prises\": 37796,\n    \"Ġ277\": 37797,\n    \"necessary\": 37798,\n    \"Ġdope\": 37799,\n    \"Late\": 37800,\n    \"Ġrake\": 37801,\n    \"ĠBrigham\": 37802,\n    \"ogun\": 37803,\n    \"ĠSTATES\": 37804,\n    \"ĠGaal\": 37805,\n    \"Ġintellig\": 37806,\n    \"Ġglacier\": 37807,\n    \"destruct\": 37808,\n    \"ĠZucker\": 37809,\n    \"484\": 37810,\n    \"Ġ332\": 37811,\n    \"ĠArist\": 37812,\n    \"Ġprotagonists\": 37813,\n    \"Ġgraveyard\": 37814,\n    \"names\": 37815,\n    \"ĠPax\": 37816,\n    \"Ġthresholds\": 37817,\n    \"Seeing\": 37818,\n    \"Ġmunitions\": 37819,\n    \"Ġcontradicts\": 37820,\n    \"684\": 37821,\n    \"Ġ529\": 37822,\n    \"ĠConcent\": 37823,\n    \"ĠBlessed\": 37824,\n    \"Hz\": 37825,\n    \"Ġinhibit\": 37826,\n    \"Ġshenanigans\": 37827,\n    \"ĠSpear\": 37828,\n    \"Ġoverlay\": 37829,\n    \"ritis\": 37830,\n    \"ilus\": 37831,\n    \"Ġvariance\": 37832,\n    \"Ġoverpower\": 37833,\n    \"viol\": 37834,\n    \"erning\": 37835,\n    \"Ġpolarization\": 37836,\n    \"aito\": 37837,\n    \"GV\": 37838,\n    \"493\": 37839,\n    \"Keeping\": 37840,\n    \"Ġpaternity\": 37841,\n    \"ĠHappiness\": 37842,\n    \"oops\": 37843,\n    \"sb\": 37844,\n    \"xit\": 37845,\n    \"ophysical\": 37846,\n    \"Ġconclusive\": 37847,\n    \"Arch\": 37848,\n    \"Ġmiser\": 37849,\n    \"Ġsuffice\": 37850,\n    \"ĠStout\": 37851,\n    \"Ġhrs\": 37852,\n    \"643\": 37853,\n    \"Ġprincipled\": 37854,\n    \"azine\": 37855,\n    \"atorium\": 37856,\n    \"ĠFairy\": 37857,\n    \"Ġinfiltrated\": 37858,\n    \"ĠHier\": 37859,\n    \"ĠMIA\": 37860,\n    \"inders\": 37861,\n    \"Ġrebutt\": 37862,\n    \"Ġxx\": 37863,\n    \"Ġfeats\": 37864,\n    \"izzle\": 37865,\n    \"Ġ780\": 37866,\n    \"668\": 37867,\n    \"Ġrepressive\": 37868,\n    \"ĠYugoslavia\": 37869,\n    \"sole\": 37870,\n    \"704\": 37871,\n    \"ĠRPG\": 37872,\n    \"ĠTroll\": 37873,\n    \"packing\": 37874,\n    \"ĠDatabase\": 37875,\n    \"ĠVelvet\": 37876,\n    \"ĠRELEASE\": 37877,\n    \"ablish\": 37878,\n    \"smoking\": 37879,\n    \"ĠBottle\": 37880,\n    \"ĠFully\": 37881,\n    \"ĠLean\": 37882,\n    \"Ġobjectively\": 37883,\n    \"ĠFounding\": 37884,\n    \"ĠClassics\": 37885,\n    \"Ġmosaic\": 37886,\n    \"473\": 37887,\n    \"Ġrooft\": 37888,\n    \"Ġcentrally\": 37889,\n    \"Ġdismissive\": 37890,\n    \"Ġparasites\": 37891,\n    \"009\": 37892,\n    \"Ġcursed\": 37893,\n    \"Ġvex\": 37894,\n    \"Ġeconom\": 37895,\n    \"ĠBore\": 37896,\n    \"enery\": 37897,\n    \"ĠFundamental\": 37898,\n    \"ĠOmni\": 37899,\n    \"489\": 37900,\n    \"714\": 37901,\n    \"Ġforegoing\": 37902,\n    \"Ġfragment\": 37903,\n    \"oros\": 37904,\n    \"070\": 37905,\n    \"ĠFaust\": 37906,\n    \"Ġsucking\": 37907,\n    \"Ġnode\": 37908,\n    \"Ġrighteous\": 37909,\n    \"ĠPowered\": 37910,\n    \"426\": 37911,\n    \"HQ\": 37912,\n    \"Ġchronically\": 37913,\n    \"ĠBAL\": 37914,\n    \"Ġprest\": 37915,\n    \"Ġrapists\": 37916,\n    \"ĠRelationship\": 37917,\n    \"ĠCHR\": 37918,\n    \"Ġlinen\": 37919,\n    \"Ġnumerical\": 37920,\n    \"oters\": 37921,\n    \"Ġiterations\": 37922,\n    \"ttes\": 37923,\n    \"ĠENTER\": 37924,\n    \"Ġrabbi\": 37925,\n    \"Ġhoard\": 37926,\n    \"Ġmerciless\": 37927,\n    \"Ġrobes\": 37928,\n    \"ĠSpray\": 37929,\n    \"Ġadvers\": 37930,\n    \"ilantro\": 37931,\n    \"483\": 37932,\n    \"Ġfungus\": 37933,\n    \"Ġalcoholism\": 37934,\n    \"anasia\": 37935,\n    \"ĠCruiser\": 37936,\n    \"Ġmorals\": 37937,\n    \"cision\": 37938,\n    \"measures\": 37939,\n    \"Ġsabot\": 37940,\n    \"Ġrecol\": 37941,\n    \"ĠSaur\": 37942,\n    \"ĠError\": 37943,\n    \"Ġmysteriously\": 37944,\n    \"sle\": 37945,\n    \"Ġfeminists\": 37946,\n    \"Ð´\": 37947,\n    \"ackle\": 37948,\n    \"ĠMarxist\": 37949,\n    \"Ġselves\": 37950,\n    \"Ġdoorway\": 37951,\n    \"Ġdiscard\": 37952,\n    \"Ġbandits\": 37953,\n    \"ĠDive\": 37954,\n    \"ameless\": 37955,\n    \"TRY\": 37956,\n    \"Ġgull\": 37957,\n    \"Ġrepublican\": 37958,\n    \"sr\": 37959,\n    \"ĠDynamo\": 37960,\n    \"Ġembryo\": 37961,\n    \"MENTS\": 37962,\n    \"ĠLOW\": 37963,\n    \"Ġ319\": 37964,\n    \"Ġgly\": 37965,\n    \"Ġcowork\": 37966,\n    \"Coll\": 37967,\n    \"Ġcris\": 37968,\n    \"ĠBanana\": 37969,\n    \"reality\": 37970,\n    \"Ġmobilization\": 37971,\n    \"unal\": 37972,\n    \"Updated\": 37973,\n    \"Crew\": 37974,\n    \"ĠGideon\": 37975,\n    \"Ġvines\": 37976,\n    \"Ġknitting\": 37977,\n    \"Ġdag\": 37978,\n    \"ĠSurv\": 37979,\n    \"Ġvacc\": 37980,\n    \"Ġimpulses\": 37981,\n    \"Northern\": 37982,\n    \"Ġnanop\": 37983,\n    \"allows\": 37984,\n    \"UTH\": 37985,\n    \"Ġflashbacks\": 37986,\n    \"alsa\": 37987,\n    \"Ġ282\": 37988,\n    \"Ġtransmissions\": 37989,\n    \"ĠAlmighty\": 37990,\n    \"Office\": 37991,\n    \"ĠBride\": 37992,\n    \"ĠBeasts\": 37993,\n    \"othy\": 37994,\n    \"ĠClouds\": 37995,\n    \"ĠDyn\": 37996,\n    \"ĠJolly\": 37997,\n    \"District\": 37998,\n    \"Ġveget\": 37999,\n    \"Ġantit\": 38000,\n    \"ĠSmoking\": 38001,\n    \"hess\": 38002,\n    \"Ġcompose\": 38003,\n    \"Ġreligiously\": 38004,\n    \"ĠHY\": 38005,\n    \"Ġfluorescent\": 38006,\n    \"rame\": 38007,\n    \"ĠMeier\": 38008,\n    \"ĠSQ\": 38009,\n    \"benefit\": 38010,\n    \"Thirty\": 38011,\n    \"559\": 38012,\n    \"ĠCance\": 38013,\n    \"586\": 38014,\n    \"Ġgrouped\": 38015,\n    \"Ġphys\": 38016,\n    \"Ġrebellious\": 38017,\n    \"ĠBASE\": 38018,\n    \"chid\": 38019,\n    \"582\": 38020,\n    \"ĠLessons\": 38021,\n    \"ĠWonderful\": 38022,\n    \"ODE\": 38023,\n    \"uctions\": 38024,\n    \"Ġbarbaric\": 38025,\n    \"rahim\": 38026,\n    \"635\": 38027,\n    \"Ġcloves\": 38028,\n    \"ĠNIH\": 38029,\n    \"ossession\": 38030,\n    \"Employ\": 38031,\n    \"Ġliberate\": 38032,\n    \"Gro\": 38033,\n    \"Ġmagician\": 38034,\n    \"ountain\": 38035,\n    \"FORM\": 38036,\n    \"533\": 38037,\n    \"Ġunpredict\": 38038,\n    \"rity\": 38039,\n    \"Ġfaked\": 38040,\n    \"plets\": 38041,\n    \"ppelin\": 38042,\n    \"Living\": 38043,\n    \"Ġnearer\": 38044,\n    \"Ġsuperiors\": 38045,\n    \"Ur\": 38046,\n    \"Ġheroism\": 38047,\n    \"Ġbearded\": 38048,\n    \"006\": 38049,\n    \"Cole\": 38050,\n    \"1970\": 38051,\n    \"Ġsill\": 38052,\n    \"ĠReduce\": 38053,\n    \"OLOG\": 38054,\n    \"onel\": 38055,\n    \"Billy\": 38056,\n    \"ĠPainter\": 38057,\n    \"ansas\": 38058,\n    \"Ġintermediary\": 38059,\n    \"trump\": 38060,\n    \"ĠMith\": 38061,\n    \"otom\": 38062,\n    \"434\": 38063,\n    \"Ġterrit\": 38064,\n    \"Wa\": 38065,\n    \"Ġsuprem\": 38066,\n    \"Rh\": 38067,\n    \"liction\": 38068,\n    \"ĠDEAD\": 38069,\n    \"Ġbothers\": 38070,\n    \"503\": 38071,\n    \"Ġfrogs\": 38072,\n    \"Ġsprinkled\": 38073,\n    \"Ġnil\": 38074,\n    \"628\": 38075,\n    \"Private\": 38076,\n    \"ĠKGB\": 38077,\n    \"Ġoverriding\": 38078,\n    \"Ġdeceived\": 38079,\n    \"698\": 38080,\n    \"idium\": 38081,\n    \"Ġseeker\": 38082,\n    \"Final\": 38083,\n    \"Ġsubconscious\": 38084,\n    \"Ġwom\": 38085,\n    \"Ġcass\": 38086,\n    \"Ġchicks\": 38087,\n    \"Ġverifying\": 38088,\n    \"ective\": 38089,\n    \"inia\": 38090,\n    \"ĠDetection\": 38091,\n    \"MH\": 38092,\n    \"fortable\": 38093,\n    \"ĠISPs\": 38094,\n    \"Ġcrumble\": 38095,\n    \"ĠRecap\": 38096,\n    \"598\": 38097,\n    \"ummies\": 38098,\n    \"export\": 38099,\n    \"Irish\": 38100,\n    \"Ġlil\": 38101,\n    \"ĠRapt\": 38102,\n    \"ĠRIGHT\": 38103,\n    \"Ġanecdotal\": 38104,\n    \"Ġpiercing\": 38105,\n    \"deck\": 38106,\n    \"Liber\": 38107,\n    \"Books\": 38108,\n    \"Ġassassin\": 38109,\n    \"Tur\": 38110,\n    \"revolution\": 38111,\n    \"ĠSheep\": 38112,\n    \"ĠPublishers\": 38113,\n    \"EMS\": 38114,\n    \"iosis\": 38115,\n    \"finder\": 38116,\n    \"ĠCuriosity\": 38117,\n    \"ARB\": 38118,\n    \"ĠConvers\": 38119,\n    \"IVES\": 38120,\n    \"clave\": 38121,\n    \"ĠChaos\": 38122,\n    \"ĠMim\": 38123,\n    \"ĠCostume\": 38124,\n    \"Ġtwe\": 38125,\n    \"Ġintim\": 38126,\n    \"757\": 38127,\n    \"berto\": 38128,\n    \"Ġ261\": 38129,\n    \"VPN\": 38130,\n    \"cribed\": 38131,\n    \"ĠVerb\": 38132,\n    \"cb\": 38133,\n    \"Ġaxle\": 38134,\n    \"Ġsandwic\": 38135,\n    \"Ice\": 38136,\n    \"ĠThermal\": 38137,\n    \"654\": 38138,\n    \"709\": 38139,\n    \"ĠPact\": 38140,\n    \"ĠEnsure\": 38141,\n    \"izable\": 38142,\n    \"497\": 38143,\n    \"Ġbloodstream\": 38144,\n    \"Aw\": 38145,\n    \"Ġleakage\": 38146,\n    \"Ġalleg\": 38147,\n    \"ĠMelody\": 38148,\n    \"681\": 38149,\n    \"Austin\": 38150,\n    \"428\": 38151,\n    \"Ġsummarized\": 38152,\n    \"ĠDefendants\": 38153,\n    \"ĠVader\": 38154,\n    \"Ê\": 38155,\n    \"Ġ1880\": 38156,\n    \"Ġassemb\": 38157,\n    \"YOU\": 38158,\n    \"GREEN\": 38159,\n    \"jury\": 38160,\n    \"4000\": 38161,\n    \"Ġvenerable\": 38162,\n    \"Ġcomputational\": 38163,\n    \"Ġperpetuate\": 38164,\n    \"Ġtorpedo\": 38165,\n    \"Ġaborted\": 38166,\n    \"Ġrhetorical\": 38167,\n    \"ĠOvert\": 38168,\n    \"Ġacknowledgment\": 38169,\n    \"essment\": 38170,\n    \"ĠIGN\": 38171,\n    \"ĠSheen\": 38172,\n    \"571\": 38173,\n    \"Ġcontag\": 38174,\n    \"Ġcultiv\": 38175,\n    \"Ġspawn\": 38176,\n    \"mess\": 38177,\n    \"Dur\": 38178,\n    \"Ġvortex\": 38179,\n    \"ixties\": 38180,\n    \"ĠBlow\": 38181,\n    \"Sum\": 38182,\n    \"Åį\": 38183,\n    \"Rom\": 38184,\n    \"ĠRadeon\": 38185,\n    \"Fed\": 38186,\n    \"Ġameric\": 38187,\n    \"ĠAnth\": 38188,\n    \"Ġantic\": 38189,\n    \"Ġfortress\": 38190,\n    \"Cold\": 38191,\n    \"ĠPredict\": 38192,\n    \"Fake\": 38193,\n    \"Ġilluminate\": 38194,\n    \"Find\": 38195,\n    \"Ġintellectually\": 38196,\n    \"Ġgon\": 38197,\n    \"alker\": 38198,\n    \"Ġinvoice\": 38199,\n    \"IELD\": 38200,\n    \"Ġfools\": 38201,\n    \"ĠEnding\": 38202,\n    \"-(\": 38203,\n    \"Ġalk\": 38204,\n    \"ĠControlled\": 38205,\n    \"Ġpurposefully\": 38206,\n    \"ĠChronic\": 38207,\n    \"Ġrele\": 38208,\n    \"ĠOps\": 38209,\n    \"Party\": 38210,\n    \"ethnic\": 38211,\n    \"ĠSpecifications\": 38212,\n    \"ffee\": 38213,\n    \"ĠTeach\": 38214,\n    \"ulas\": 38215,\n    \"Ġenslaved\": 38216,\n    \"onomy\": 38217,\n    \"Ġtenets\": 38218,\n    \"Ġammonia\": 38219,\n    \"Ġ1913\": 38220,\n    \"Ġdripping\": 38221,\n    \"612\": 38222,\n    \"659\": 38223,\n    \"ĠSagan\": 38224,\n    \"Ġinaccur\": 38225,\n    \"Ġabol\": 38226,\n    \"ĠLIKE\": 38227,\n    \"Ġvisualization\": 38228,\n    \"learn\": 38229,\n    \"anon\": 38230,\n    \"cipline\": 38231,\n    \"Ġadaptations\": 38232,\n    \"Ġwaiter\": 38233,\n    \"nergy\": 38234,\n    \"507\": 38235,\n    \"ĠDK\": 38236,\n    \"YD\": 38237,\n    \"Ġpedest\": 38238,\n    \"Sense\": 38239,\n    \"ĠObst\": 38240,\n    \"Ġresurrection\": 38241,\n    \"ĠSPECIAL\": 38242,\n    \"Unlike\": 38243,\n    \"Ġlia\": 38244,\n    \"Ġpersuasive\": 38245,\n    \"iatrics\": 38246,\n    \"ONEY\": 38247,\n    \"esthetic\": 38248,\n    \"494\": 38249,\n    \"zik\": 38250,\n    \"Ġfract\": 38251,\n    \"ĠOutput\": 38252,\n    \"ĠBers\": 38253,\n    \"rozen\": 38254,\n    \"ĠRevis\": 38255,\n    \"Ġdraconian\": 38256,\n    \"Words\": 38257,\n    \"asions\": 38258,\n    \"ĠClintons\": 38259,\n    \"CU\": 38260,\n    \"History\": 38261,\n    \"Ġtwilight\": 38262,\n    \"iform\": 38263,\n    \"Ġdispl\": 38264,\n    \"progress\": 38265,\n    \"ĠIO\": 38266,\n    \"Ġcannibal\": 38267,\n    \"Michelle\": 38268,\n    \"Ġnerv\": 38269,\n    \"Ġcontexts\": 38270,\n    \"ĠHorses\": 38271,\n    \"Ġanatomy\": 38272,\n    \"ĠLegislation\": 38273,\n    \"ĠBloody\": 38274,\n    \"Ġunwittingly\": 38275,\n    \"Ġinquired\": 38276,\n    \"ĠZip\": 38277,\n    \"ĠDesigns\": 38278,\n    \"Ġirritating\": 38279,\n    \"Ġunison\": 38280,\n    \"ĠRG\": 38281,\n    \"aviour\": 38282,\n    \"Ġpseudo\": 38283,\n    \"ĠVenom\": 38284,\n    \"Ġobscured\": 38285,\n    \"Ġner\": 38286,\n    \"uked\": 38287,\n    \"ORGE\": 38288,\n    \"Ġmomentarily\": 38289,\n    \"olyn\": 38290,\n    \"Syrian\": 38291,\n    \"Ġmicroscopic\": 38292,\n    \"Ġmistress\": 38293,\n    \"Less\": 38294,\n    \"Ġawoke\": 38295,\n    \"Ġtutor\": 38296,\n    \"esome\": 38297,\n    \"ollar\": 38298,\n    \"egg\": 38299,\n    \"UTE\": 38300,\n    \"Buzz\": 38301,\n    \"Ġattainment\": 38302,\n    \"Ġdiscriminating\": 38303,\n    \"::\": 38304,\n    \"Ġ525\": 38305,\n    \"azard\": 38306,\n    \"ĠBrist\": 38307,\n    \"oras\": 38308,\n    \"Ġveterin\": 38309,\n    \"jing\": 38310,\n    \"idon\": 38311,\n    \"ĠAustral\": 38312,\n    \"arious\": 38313,\n    \"ĠGrav\": 38314,\n    \"anol\": 38315,\n    \"ĠQuran\": 38316,\n    \"Ġbleach\": 38317,\n    \"588\": 38318,\n    \"ĠOsw\": 38319,\n    \"Ġdiffered\": 38320,\n    \"typ\": 38321,\n    \"ĠSIL\": 38322,\n    \"failed\": 38323,\n    \"436\": 38324,\n    \"Ġpalms\": 38325,\n    \"ĠFail\": 38326,\n    \"idespread\": 38327,\n    \"Ġchap\": 38328,\n    \"ĠIMAGES\": 38329,\n    \"ACP\": 38330,\n    \"matched\": 38331,\n    \"Ġjaws\": 38332,\n    \"MHz\": 38333,\n    \"Nik\": 38334,\n    \"ĠHume\": 38335,\n    \"OSH\": 38336,\n    \"Ġpresume\": 38337,\n    \"secut\": 38338,\n    \"ĠDied\": 38339,\n    \"ĠBreat\": 38340,\n    \"gins\": 38341,\n    \"prison\": 38342,\n    \"ĠUR\": 38343,\n    \"ĠROS\": 38344,\n    \"isitions\": 38345,\n    \"Ġpelvic\": 38346,\n    \"exclusive\": 38347,\n    \"522\": 38348,\n    \"689\": 38349,\n    \"FN\": 38350,\n    \"Ġener\": 38351,\n    \"Ġdispers\": 38352,\n    \"Ġcohorts\": 38353,\n    \"shut\": 38354,\n    \"ĠLoad\": 38355,\n    \"needs\": 38356,\n    \"azaki\": 38357,\n    \"inoa\": 38358,\n    \"Inside\": 38359,\n    \"usra\": 38360,\n    \"ighters\": 38361,\n    \"Ġ271\": 38362,\n    \"Ġsubordinate\": 38363,\n    \"ĠHOL\": 38364,\n    \"ĠGlow\": 38365,\n    \"Ġincred\": 38366,\n    \"ĠMadame\": 38367,\n    \"Ġoats\": 38368,\n    \"Ġdeviation\": 38369,\n    \"ĠApproach\": 38370,\n    \"Ġnarc\": 38371,\n    \"bart\": 38372,\n    \"bole\": 38373,\n    \"ĠSHE\": 38374,\n    \"effects\": 38375,\n    \"ĠADA\": 38376,\n    \"Ġmuse\": 38377,\n    \"Squ\": 38378,\n    \"Ġneuroscience\": 38379,\n    \"ĠValues\": 38380,\n    \"engu\": 38381,\n    \"Ġdosage\": 38382,\n    \"Ġwhispers\": 38383,\n    \"Ġnaughty\": 38384,\n    \"ĠFarming\": 38385,\n    \"Recently\": 38386,\n    \"Ġrelapse\": 38387,\n    \"rentice\": 38388,\n    \"UGH\": 38389,\n    \"Ġdarkened\": 38390,\n    \"appings\": 38391,\n    \"ĠSlaughter\": 38392,\n    \"ĠAnim\": 38393,\n    \"Ġovertly\": 38394,\n    \"poses\": 38395,\n    \"Ġdeficient\": 38396,\n    \"Ġnecks\": 38397,\n    \"Iron\": 38398,\n    \"Ġphysiological\": 38399,\n    \"ĠLiang\": 38400,\n    \"Ġlear\": 38401,\n    \"Ġcelestial\": 38402,\n    \"Ġpistols\": 38403,\n    \"Ġeyebrow\": 38404,\n    \"915\": 38405,\n    \"ratch\": 38406,\n    \"cephal\": 38407,\n    \"ĠPSU\": 38408,\n    \"Ġphotograp\": 38409,\n    \"ĠGaul\": 38410,\n    \"Ġuncontrolled\": 38411,\n    \"ĠJoined\": 38412,\n    \"652\": 38413,\n    \"itory\": 38414,\n    \"Ġ274\": 38415,\n    \"GAN\": 38416,\n    \"imester\": 38417,\n    \"essional\": 38418,\n    \"Ø©\": 38419,\n    \"Ġuncons\": 38420,\n    \"THER\": 38421,\n    \"Ġpaternal\": 38422,\n    \"Zero\": 38423,\n    \"ugen\": 38424,\n    \"538\": 38425,\n    \"Ġende\": 38426,\n    \"Ġ505\": 38427,\n    \"movie\": 38428,\n    \"Lind\": 38429,\n    \"Ġscorn\": 38430,\n    \"ulty\": 38431,\n    \"Ġpesky\": 38432,\n    \"Ġ8000\": 38433,\n    \"677\": 38434,\n    \"Ġhomophobia\": 38435,\n    \"ranch\": 38436,\n    \"Ġnarciss\": 38437,\n    \"ĠVoyager\": 38438,\n    \"ĠHELP\": 38439,\n    \"528\": 38440,\n    \"edly\": 38441,\n    \"Ġdetract\": 38442,\n    \"Hope\": 38443,\n    \"787\": 38444,\n    \"ĠMerlin\": 38445,\n    \"Ġgrids\": 38446,\n    \"KI\": 38447,\n    \"Mu\": 38448,\n    \"ĠSelected\": 38449,\n    \"select\": 38450,\n    \"ĠModer\": 38451,\n    \"ĠFeet\": 38452,\n    \"Ġrename\": 38453,\n    \"intensity\": 38454,\n    \"Wilson\": 38455,\n    \"Ġ414\": 38456,\n    \"leave\": 38457,\n    \"Ready\": 38458,\n    \"intuitive\": 38459,\n    \"Ġmeager\": 38460,\n    \"Franc\": 38461,\n    \"DH\": 38462,\n    \"Ġrhy\": 38463,\n    \"ĠPillar\": 38464,\n    \"ĠDOE\": 38465,\n    \"minist\": 38466,\n    \"ĠGrave\": 38467,\n    \"isible\": 38468,\n    \"Ess\": 38469,\n    \"Ġempt\": 38470,\n    \"Ġpatched\": 38471,\n    \"ĠAbortion\": 38472,\n    \"rals\": 38473,\n    \"Ġdow\": 38474,\n    \"Ġcrawled\": 38475,\n    \"igrate\": 38476,\n    \"Virginia\": 38477,\n    \"Ġconting\": 38478,\n    \"Ġorphans\": 38479,\n    \"ĠCrimean\": 38480,\n    \"Ġdyn\": 38481,\n    \"Ġshadowy\": 38482,\n    \"sound\": 38483,\n    \"ailable\": 38484,\n    \"Ġ293\": 38485,\n    \"vm\": 38486,\n    \"Ġaccompanies\": 38487,\n    \"Meanwhile\": 38488,\n    \"JR\": 38489,\n    \"ĠDirections\": 38490,\n    \"Ġadolescence\": 38491,\n    \"Ġpenetrated\": 38492,\n    \"bars\": 38493,\n    \"Rev\": 38494,\n    \"Ta\": 38495,\n    \"ĠSkywalker\": 38496,\n    \"ĠFires\": 38497,\n    \"concept\": 38498,\n    \"ĠSIG\": 38499,\n    \"554\": 38500,\n    \"currently\": 38501,\n    \"Ġ----------------\": 38502,\n    \"ĠWHITE\": 38503,\n    \"767\": 38504,\n    \"rors\": 38505,\n    \"PDF\": 38506,\n    \"Ġcasing\": 38507,\n    \"673\": 38508,\n    \"Ġdisapprove\": 38509,\n    \"1800\": 38510,\n    \"ĠWeed\": 38511,\n    \"Ġinhib\": 38512,\n    \"Ġmorbid\": 38513,\n    \"433\": 38514,\n    \"Ġawfully\": 38515,\n    \"Ts\": 38516,\n    \"Maria\": 38517,\n    \"Ġillusions\": 38518,\n    \"Ġtotalitarian\": 38519,\n    \"ollo\": 38520,\n    \"Ġsuppl\": 38521,\n    \"Ġsarc\": 38522,\n    \"ĠRGB\": 38523,\n    \"Ġlauncher\": 38524,\n    \"Ġbadass\": 38525,\n    \"ĠSyd\": 38526,\n    \"Ġscrape\": 38527,\n    \"ĠCLA\": 38528,\n    \"Ġcircum\": 38529,\n    \"657\": 38530,\n    \"Ġnucleus\": 38531,\n    \"ĠUkip\": 38532,\n    \"Ġmodem\": 38533,\n    \"ĠJou\": 38534,\n    \"adders\": 38535,\n    \"Ġwiser\": 38536,\n    \"thereal\": 38537,\n    \"Ġdemocr\": 38538,\n    \"ĠInvalid\": 38539,\n    \"Mine\": 38540,\n    \"Ġmanifested\": 38541,\n    \"meat\": 38542,\n    \"MORE\": 38543,\n    \"Larry\": 38544,\n    \"acements\": 38545,\n    \"Ġspecimen\": 38546,\n    \"results\": 38547,\n    \"Ġswallowing\": 38548,\n    \"Ġpigeon\": 38549,\n    \"tons\": 38550,\n    \"ĠLose\": 38551,\n    \"Ġquartz\": 38552,\n    \"Ġintraven\": 38553,\n    \"Ġ412\": 38554,\n    \"alyst\": 38555,\n    \"Ġengraved\": 38556,\n    \"client\": 38557,\n    \"ĠADV\": 38558,\n    \"ĠShared\": 38559,\n    \"Ġrites\": 38560,\n    \"Ġhysterical\": 38561,\n    \"ĠHUM\": 38562,\n    \"Cow\": 38563,\n    \"orously\": 38564,\n    \"Ġpleasures\": 38565,\n    \"democratic\": 38566,\n    \"Ġamph\": 38567,\n    \"Ġnib\": 38568,\n    \"rieg\": 38569,\n    \"Ġcalculates\": 38570,\n    \"Ġfrying\": 38571,\n    \"favorite\": 38572,\n    \"Ġantim\": 38573,\n    \"ĠDoom\": 38574,\n    \"monitor\": 38575,\n    \"Want\": 38576,\n    \"Ġtemplates\": 38577,\n    \"558\": 38578,\n    \"iever\": 38579,\n    \"Photos\": 38580,\n    \",,\": 38581,\n    \"ĠSync\": 38582,\n    \"Ġconfronts\": 38583,\n    \"kept\": 38584,\n    \"dt\": 38585,\n    \"ĠERROR\": 38586,\n    \"ETF\": 38587,\n    \"578\": 38588,\n    \"Ġspor\": 38589,\n    \"718\": 38590,\n    \"ivation\": 38591,\n    \"ĠHaskell\": 38592,\n    \"Ca\": 38593,\n    \"Ġdick\": 38594,\n    \"Ġcivilized\": 38595,\n    \"Ġblah\": 38596,\n    \"enough\": 38597,\n    \"Ġoccup\": 38598,\n    \"Ġ334\": 38599,\n    \"antically\": 38600,\n    \"584\": 38601,\n    \"ĠDolphin\": 38602,\n    \"ĠStarts\": 38603,\n    \"Ġfanatic\": 38604,\n    \"Øª\": 38605,\n    \"imag\": 38606,\n    \"Ġmicrobial\": 38607,\n    \"freedom\": 38608,\n    \"cult\": 38609,\n    \"wra\": 38610,\n    \"Ġ423\": 38611,\n    \"RIPT\": 38612,\n    \"601\": 38613,\n    \"BTC\": 38614,\n    \"atmeal\": 38615,\n    \"653\": 38616,\n    \"agogue\": 38617,\n    \"Ġderives\": 38618,\n    \"Wolf\": 38619,\n    \"466\": 38620,\n    \"Susan\": 38621,\n    \"ĠPassage\": 38622,\n    \"ARDS\": 38623,\n    \"Guy\": 38624,\n    \"Council\": 38625,\n    \"Ġerotic\": 38626,\n    \"pure\": 38627,\n    \"ĠMemories\": 38628,\n    \"ĠWikileaks\": 38629,\n    \"elines\": 38630,\n    \"Ġanth\": 38631,\n    \"Capital\": 38632,\n    \"807\": 38633,\n    \"ĠEggs\": 38634,\n    \"cv\": 38635,\n    \"ctors\": 38636,\n    \"Ġshatter\": 38637,\n    \"Ġesteem\": 38638,\n    \"vity\": 38639,\n    \"ĠVulcan\": 38640,\n    \"effic\": 38641,\n    \"ĠBELOW\": 38642,\n    \"Ġplatoon\": 38643,\n    \"Commun\": 38644,\n    \"oustic\": 38645,\n    \"Amy\": 38646,\n    \"Freedom\": 38647,\n    \"ppo\": 38648,\n    \"Ja\": 38649,\n    \"ĠConan\": 38650,\n    \"Ġinsepar\": 38651,\n    \"scene\": 38652,\n    \"Ġurinary\": 38653,\n    \"gain\": 38654,\n    \"Hillary\": 38655,\n    \"ĠTAM\": 38656,\n    \"Hist\": 38657,\n    \"Ġmechan\": 38658,\n    \"ĠRobots\": 38659,\n    \"Leader\": 38660,\n    \"Ġcartridges\": 38661,\n    \"Ġwhistleblowers\": 38662,\n    \"ĠSPL\": 38663,\n    \"Labour\": 38664,\n    \"unction\": 38665,\n    \"Ġfaithfully\": 38666,\n    \"Ġcoarse\": 38667,\n    \"Ġsynth\": 38668,\n    \"ĠLV\": 38669,\n    \"Ġjustifying\": 38670,\n    \"439\": 38671,\n    \"Victoria\": 38672,\n    \"ĠProceedings\": 38673,\n    \"alogy\": 38674,\n    \"Ġmorph\": 38675,\n    \"Ġcove\": 38676,\n    \"Ġlaughable\": 38677,\n    \"ECA\": 38678,\n    \"Ġ670\": 38679,\n    \"aturated\": 38680,\n    \"ĠSouls\": 38681,\n    \"ĠSleeping\": 38682,\n    \"Ly\": 38683,\n    \"ĠRetro\": 38684,\n    \"Ġastroph\": 38685,\n    \"Ġseism\": 38686,\n    \"atherine\": 38687,\n    \"ĠHercules\": 38688,\n    \"Ġfuse\": 38689,\n    \"ĠHL\": 38690,\n    \"Ġunintentionally\": 38691,\n    \"ĠRÃ©\": 38692,\n    \"iery\": 38693,\n    \"Ġconco\": 38694,\n    \"Ġeras\": 38695,\n    \"recent\": 38696,\n    \"Ġlaunchers\": 38697,\n    \"ĠVolcano\": 38698,\n    \"ĠJace\": 38699,\n    \"Ġterminating\": 38700,\n    \"ĠIde\": 38701,\n    \"zee\": 38702,\n    \"asonic\": 38703,\n    \"itone\": 38704,\n    \"Ġnutshell\": 38705,\n    \"Ġbip\": 38706,\n    \"dies\": 38707,\n    \"Ġ286\": 38708,\n    \"Ġnood\": 38709,\n    \"ĠFathers\": 38710,\n    \"alys\": 38711,\n    \"Ġtheor\": 38712,\n    \"???\": 38713,\n    \"548\": 38714,\n    \"674\": 38715,\n    \"efined\": 38716,\n    \"806\": 38717,\n    \"âĻ\": 38718,\n    \"697\": 38719,\n    \"Ġdecap\": 38720,\n    \"ĠFN\": 38721,\n    \"Ġbureaucr\": 38722,\n    \"ĠGoat\": 38723,\n    \"ĠShang\": 38724,\n    \"Ġsemin\": 38725,\n    \"Ġthroats\": 38726,\n    \"Ġmoth\": 38727,\n    \"herer\": 38728,\n    \"Democratic\": 38729,\n    \"ixtures\": 38730,\n    \"impl\": 38731,\n    \"ĠLogo\": 38732,\n    \"ortunate\": 38733,\n    \"Ġclumsy\": 38734,\n    \"Ġinnocuous\": 38735,\n    \"ĠBlend\": 38736,\n    \"abulary\": 38737,\n    \"ĠFaces\": 38738,\n    \"Ġpornographic\": 38739,\n    \"px\": 38740,\n    \"Information\": 38741,\n    \"Ġfluoride\": 38742,\n    \"Ġatroc\": 38743,\n    \"Ġdelta\": 38744,\n    \"whatever\": 38745,\n    \"ossier\": 38746,\n    \"ĠNoir\": 38747,\n    \"ĠYao\": 38748,\n    \"551\": 38749,\n    \"undred\": 38750,\n    \"Ġmillennium\": 38751,\n    \"Ġferal\": 38752,\n    \"Ġconvinc\": 38753,\n    \"cano\": 38754,\n    \"imsy\": 38755,\n    \"angles\": 38756,\n    \"Ġsterile\": 38757,\n    \"ĠMenu\": 38758,\n    \"779\": 38759,\n    \"ĠCrack\": 38760,\n    \"Ġabundantly\": 38761,\n    \"ĠmL\": 38762,\n    \"Ġinfiltration\": 38763,\n    \"ĠDefinition\": 38764,\n    \"733\": 38765,\n    \"oubt\": 38766,\n    \"Ġorbital\": 38767,\n    \"Ġpiss\": 38768,\n    \"Ġbeet\": 38769,\n    \"679\": 38770,\n    \"Ġcounteract\": 38771,\n    \"ĠALE\": 38772,\n    \"ulative\": 38773,\n    \"crew\": 38774,\n    \"Ġliberating\": 38775,\n    \"ĠDull\": 38776,\n    \"Speaking\": 38777,\n    \"Sadly\": 38778,\n    \"Ġmisfortune\": 38779,\n    \"Ġdolphin\": 38780,\n    \"557\": 38781,\n    \"Ġbould\": 38782,\n    \"ĠTorah\": 38783,\n    \"ĠConfederacy\": 38784,\n    \"421\": 38785,\n    \"Ġorbits\": 38786,\n    \"ocused\": 38787,\n    \"beer\": 38788,\n    \"Rand\": 38789,\n    \"ĠORIG\": 38790,\n    \"Ġmuc\": 38791,\n    \"LER\": 38792,\n    \"ĠMisty\": 38793,\n    \"Ġinexpl\": 38794,\n    \"Ġreptiles\": 38795,\n    \"Ġaven\": 38796,\n    \"blocking\": 38797,\n    \"ĠPASS\": 38798,\n    \"Ġarisen\": 38799,\n    \"ĠMock\": 38800,\n    \"Ġops\": 38801,\n    \"Ġshin\": 38802,\n    \"524\": 38803,\n    \"Ġdigestion\": 38804,\n    \"Soft\": 38805,\n    \"irect\": 38806,\n    \"POL\": 38807,\n    \"ĠSpell\": 38808,\n    \"Level\": 38809,\n    \"Ġhex\": 38810,\n    \"Ġbitcoins\": 38811,\n    \"ĠHungry\": 38812,\n    \"VL\": 38813,\n    \"ĠRealm\": 38814,\n    \"RELATED\": 38815,\n    \"Delta\": 38816,\n    \"Pri\": 38817,\n    \"Ġrejoice\": 38818,\n    \"ĠLatter\": 38819,\n    \"LG\": 38820,\n    \"Ġstupidity\": 38821,\n    \"Ġdonkey\": 38822,\n    \"nova\": 38823,\n    \"Vill\": 38824,\n    \"Ġdecomp\": 38825,\n    \"Ġexternally\": 38826,\n    \"Ġsequest\": 38827,\n    \"815\": 38828,\n    \"Ġshortcut\": 38829,\n    \"riminal\": 38830,\n    \"Hun\": 38831,\n    \"EH\": 38832,\n    \"Ġregiment\": 38833,\n    \"Case\": 38834,\n    \"definition\": 38835,\n    \"Ġappendix\": 38836,\n    \"ĠPlayed\": 38837,\n    \"associated\": 38838,\n    \"izens\": 38839,\n    \"ĠVag\": 38840,\n    \"Ġflung\": 38841,\n    \"Ġfru\": 38842,\n    \"Ġcoil\": 38843,\n    \"________________________\": 38844,\n    \"Ġselects\": 38845,\n    \"Ġsolves\": 38846,\n    \"aea\": 38847,\n    \"985\": 38848,\n    \"Tomorrow\": 38849,\n    \"Ġsear\": 38850,\n    \"APE\": 38851,\n    \"492\": 38852,\n    \"Ġenlightened\": 38853,\n    \"Ġnonexistent\": 38854,\n    \"ĠPotato\": 38855,\n    \"Ghost\": 38856,\n    \"Ġrichness\": 38857,\n    \"ĠKarin\": 38858,\n    \"Ġfamilial\": 38859,\n    \"ĠJA\": 38860,\n    \"Regardless\": 38861,\n    \"Ġepis\": 38862,\n    \"GD\": 38863,\n    \"Ġinsanely\": 38864,\n    \"ĠPhill\": 38865,\n    \"Block\": 38866,\n    \"Finding\": 38867,\n    \"omal\": 38868,\n    \"Ġdecipher\": 38869,\n    \"ĠSwap\": 38870,\n    \"derived\": 38871,\n    \"ĠOFFIC\": 38872,\n    \"Support\": 38873,\n    \"Ġnylon\": 38874,\n    \"Ġexaggeration\": 38875,\n    \"Ġevangelicals\": 38876,\n    \"Ġbearings\": 38877,\n    \"587\": 38878,\n    \"Ġlocale\": 38879,\n    \"Ġpowerfully\": 38880,\n    \"Ġappropriated\": 38881,\n    \"itates\": 38882,\n    \"irlfriend\": 38883,\n    \"cule\": 38884,\n    \"ĠSomewhere\": 38885,\n    \"747\": 38886,\n    \"ĠInteresting\": 38887,\n    \"464\": 38888,\n    \"Ġelong\": 38889,\n    \"Ġdegrade\": 38890,\n    \"rafted\": 38891,\n    \"Ġtutorials\": 38892,\n    \"905\": 38893,\n    \"ĠIntervention\": 38894,\n    \"Ġuniqueness\": 38895,\n    \"Ġ284\": 38896,\n    \"Ġexplorers\": 38897,\n    \"Ġnucle\": 38898,\n    \"ĠMillenn\": 38899,\n    \"511\": 38900,\n    \"ĠReneg\": 38901,\n    \"Ġexecut\": 38902,\n    \"urai\": 38903,\n    \"leon\": 38904,\n    \"Ġdeserts\": 38905,\n    \"ĠCig\": 38906,\n    \"Ġsuggestive\": 38907,\n    \"instead\": 38908,\n    \"Ġlousy\": 38909,\n    \"Ġenigmatic\": 38910,\n    \"594\": 38911,\n    \"Know\": 38912,\n    \"rollment\": 38913,\n    \"ipher\": 38914,\n    \"Ġhumanities\": 38915,\n    \"Ġmodifying\": 38916,\n    \".....\": 38917,\n    \"Ġdegraded\": 38918,\n    \"Ġsuppressing\": 38919,\n    \"Ġeman\": 38920,\n    \"abouts\": 38921,\n    \"functional\": 38922,\n    \"ĠOU\": 38923,\n    \"ĠRelax\": 38924,\n    \"786\": 38925,\n    \"esses\": 38926,\n    \"ĠLogin\": 38927,\n    \"spec\": 38928,\n    \"ĠWWF\": 38929,\n    \"Ġ364\": 38930,\n    \"ĠIsis\": 38931,\n    \"Wisconsin\": 38932,\n    \"Ġequival\": 38933,\n    \"ĠCollector\": 38934,\n    \"ibilities\": 38935,\n    \"malink\": 38936,\n    \"acea\": 38937,\n    \"Ġchained\": 38938,\n    \"Ġarist\": 38939,\n    \"Ġdisadvantages\": 38940,\n    \"ĠBrus\": 38941,\n    \"limits\": 38942,\n    \"ĠDmit\": 38943,\n    \"544\": 38944,\n    \"ĠRecipe\": 38945,\n    \"Ġhabitual\": 38946,\n    \".):\": 38947,\n    \"ĠPRODUCT\": 38948,\n    \"772\": 38949,\n    \"Ġrept\": 38950,\n    \"Ġpathology\": 38951,\n    \"Ġresurrected\": 38952,\n    \"uders\": 38953,\n    \"Ġlingu\": 38954,\n    \"Ġdenomination\": 38955,\n    \"Ġfirewall\": 38956,\n    \"scient\": 38957,\n    \"Ġvaliant\": 38958,\n    \"Kansas\": 38959,\n    \"516\": 38960,\n    \"Ġcontemporaries\": 38961,\n    \"Roman\": 38962,\n    \"Ġaccompan\": 38963,\n    \"Ġantennas\": 38964,\n    \"ĠXan\": 38965,\n    \"Ġelectromagnetic\": 38966,\n    \"ĠNek\": 38967,\n    \"alien\": 38968,\n    \"indle\": 38969,\n    \"Ġgraphene\": 38970,\n    \"Ġgraceful\": 38971,\n    \"syn\": 38972,\n    \"ĠBosh\": 38973,\n    \"Ġ1908\": 38974,\n    \"Ġsuccumb\": 38975,\n    \"Technology\": 38976,\n    \"Ġtoxin\": 38977,\n    \"myra\": 38978,\n    \"essert\": 38979,\n    \"Hell\": 38980,\n    \"Gil\": 38981,\n    \"Ġdiarr\": 38982,\n    \"imeters\": 38983,\n    \"Ġexplo\": 38984,\n    \"Ġgeometric\": 38985,\n    \"ĠNavigation\": 38986,\n    \"cern\": 38987,\n    \"Ġprogrammer\": 38988,\n    \"oÄŁan\": 38989,\n    \"Ġdodging\": 38990,\n    \"ĠLU\": 38991,\n    \"573\": 38992,\n    \"inters\": 38993,\n    \"Ġserum\": 38994,\n    \"Ġuber\": 38995,\n    \"Ġmanga\": 38996,\n    \"762\": 38997,\n    \"ĠOccasionally\": 38998,\n    \"437\": 38999,\n    \"ĠTheme\": 39000,\n    \"Ġimmature\": 39001,\n    \"Ġactivating\": 39002,\n    \"ĠTruly\": 39003,\n    \"Ø¯\": 39004,\n    \"osion\": 39005,\n    \"Age\": 39006,\n    \"TIME\": 39007,\n    \"Silver\": 39008,\n    \"sand\": 39009,\n    \"ulnerable\": 39010,\n    \"Ġcram\": 39011,\n    \"Large\": 39012,\n    \"ĠAnger\": 39013,\n    \"icators\": 39014,\n    \"431\": 39015,\n    \"ĠHonest\": 39016,\n    \"zip\": 39017,\n    \"Ġdism\": 39018,\n    \"Ġfades\": 39019,\n    \"ĠPik\": 39020,\n    \"Ast\": 39021,\n    \"sequent\": 39022,\n    \"Ġunsigned\": 39023,\n    \"xious\": 39024,\n    \"creation\": 39025,\n    \"Ġ395\": 39026,\n    \"ottenham\": 39027,\n    \"Ġundesirable\": 39028,\n    \"ugal\": 39029,\n    \"ĠDivide\": 39030,\n    \"lp\": 39031,\n    \"563\": 39032,\n    \"ĠPOP\": 39033,\n    \"ĠCET\": 39034,\n    \"session\": 39035,\n    \"Ġoccurrences\": 39036,\n    \"chu\": 39037,\n    \"ĠACS\": 39038,\n    \"ĠProsecut\": 39039,\n    \"Ġhypnot\": 39040,\n    \"rely\": 39041,\n    \"ERG\": 39042,\n    \"Ven\": 39043,\n    \"Republicans\": 39044,\n    \"inez\": 39045,\n    \"ĠImplementation\": 39046,\n    \"Ġsprang\": 39047,\n    \"Ġobs\": 39048,\n    \"Defense\": 39049,\n    \"Ġunexpl\": 39050,\n    \"ĠPAGE\": 39051,\n    \"ĠTent\": 39052,\n    \"ĠNeurolog\": 39053,\n    \"Ġintuition\": 39054,\n    \"759\": 39055,\n    \"Ġterrestrial\": 39056,\n    \"Ġmorphine\": 39057,\n    \"Ġ.\\\"\": 39058,\n    \"ĠHydra\": 39059,\n    \"651\": 39060,\n    \"Ġneoliberal\": 39061,\n    \"683\": 39062,\n    \"Ġabnormalities\": 39063,\n    \"quant\": 39064,\n    \"Ġmonastery\": 39065,\n    \"jac\": 39066,\n    \"ĠReaction\": 39067,\n    \"Ġcontraceptive\": 39068,\n    \"ĠBalls\": 39069,\n    \"Ġapost\": 39070,\n    \"676\": 39071,\n    \"ĠHELL\": 39072,\n    \"approximately\": 39073,\n    \"Ġvibrations\": 39074,\n    \"COR\": 39075,\n    \"ĠCPUs\": 39076,\n    \"Ġcontin\": 39077,\n    \"Ġsemblance\": 39078,\n    \"Ġshorth\": 39079,\n    \"tip\": 39080,\n    \"ĠChips\": 39081,\n    \"makes\": 39082,\n    \"Ġprett\": 39083,\n    \"Ġconspicuous\": 39084,\n    \"ĠAmp\": 39085,\n    \"Ġvisualize\": 39086,\n    \"Hu\": 39087,\n    \"sorry\": 39088,\n    \"nai\": 39089,\n    \"ĠArcade\": 39090,\n    \"rimination\": 39091,\n    \"obin\": 39092,\n    \"Ġvampire\": 39093,\n    \"773\": 39094,\n    \"ĠCaucasus\": 39095,\n    \"Medic\": 39096,\n    \"ĠGitHub\": 39097,\n    \"ĠWicked\": 39098,\n    \"ĠFet\": 39099,\n    \"Krist\": 39100,\n    \"998\": 39101,\n    \"Ġfrontal\": 39102,\n    \"Ġ283\": 39103,\n    \"ndum\": 39104,\n    \"Ġidols\": 39105,\n    \"ĠMSG\": 39106,\n    \"ĠShuttle\": 39107,\n    \"ĠTowards\": 39108,\n    \"Ġsaturation\": 39109,\n    \"ĠÂ®\": 39110,\n    \"Ġcradle\": 39111,\n    \"eteen\": 39112,\n    \"Ġprejudices\": 39113,\n    \"separ\": 39114,\n    \"ĠSoda\": 39115,\n    \"ynam\": 39116,\n    \"Ġnause\": 39117,\n    \"Ġpenetrating\": 39118,\n    \"ĠVampire\": 39119,\n    \"Ġmole\": 39120,\n    \"Ġgoogle\": 39121,\n    \"earance\": 39122,\n    \"583\": 39123,\n    \"Ġdomin\": 39124,\n    \"727\": 39125,\n    \"Kind\": 39126,\n    \"Ġcust\": 39127,\n    \"manuel\": 39128,\n    \"ĠAstro\": 39129,\n    \"Roger\": 39130,\n    \"JO\": 39131,\n    \"killed\": 39132,\n    \"ĠDisapp\": 39133,\n    \"833\": 39134,\n    \"ĠEQU\": 39135,\n    \"Ġprecedence\": 39136,\n    \"mberg\": 39137,\n    \"641\": 39138,\n    \"ĠRoller\": 39139,\n    \"Ġspecifying\": 39140,\n    \"035\": 39141,\n    \"phil\": 39142,\n    \"Ġpowdered\": 39143,\n    \"Ġblot\": 39144,\n    \"Ġdeline\": 39145,\n    \"Bruce\": 39146,\n    \"536\": 39147,\n    \"Ġpim\": 39148,\n    \"leasing\": 39149,\n    \"vacc\": 39150,\n    \"RN\": 39151,\n    \"Ġspacing\": 39152,\n    \"Ġhangar\": 39153,\n    \"ĠPlot\": 39154,\n    \"537\": 39155,\n    \"legraph\": 39156,\n    \"596\": 39157,\n    \"Ġpolyg\": 39158,\n    \"doi\": 39159,\n    \"ĠNerd\": 39160,\n    \"installed\": 39161,\n    \"ĠSeeds\": 39162,\n    \"ĠPlays\": 39163,\n    \"ĠRomance\": 39164,\n    \"layer\": 39165,\n    \"Ġunsu\": 39166,\n    \"Ġcurric\": 39167,\n    \"Mi\": 39168,\n    \"restrial\": 39169,\n    \"ĠNiÃ±o\": 39170,\n    \"ĠProper\": 39171,\n    \"Ġpores\": 39172,\n    \"Giving\": 39173,\n    \"aeus\": 39174,\n    \"Middle\": 39175,\n    \"liber\": 39176,\n    \"Ġcombatants\": 39177,\n    \"ĠBulk\": 39178,\n    \"Ġ502\": 39179,\n    \"Ġstru\": 39180,\n    \"ĠLonely\": 39181,\n    \"Companies\": 39182,\n    \"inence\": 39183,\n    \"Autom\": 39184,\n    \"Ġfearsome\": 39185,\n    \"Ġsummar\": 39186,\n    \"Ġrotated\": 39187,\n    \"ĠPLA\": 39188,\n    \"ĠFAT\": 39189,\n    \"572\": 39190,\n    \"ĠSkies\": 39191,\n    \"iour\": 39192,\n    \"Ġintimately\": 39193,\n    \"amera\": 39194,\n    \"Ġ475\": 39195,\n    \"623\": 39196,\n    \"Ġirrig\": 39197,\n    \"Ġboosters\": 39198,\n    \"Ġtransmitting\": 39199,\n    \"DOWN\": 39200,\n    \"ĠAble\": 39201,\n    \"Ġfuriously\": 39202,\n    \"spirit\": 39203,\n    \"Ġgrun\": 39204,\n    \"Ġbible\": 39205,\n    \"ĠAdmir\": 39206,\n    \"ĠÂ§\": 39207,\n    \"ĠRaise\": 39208,\n    \"Ġflowering\": 39209,\n    \"uxe\": 39210,\n    \"ravis\": 39211,\n    \"urther\": 39212,\n    \"ĠScientology\": 39213,\n    \"pathy\": 39214,\n    \"Ġruth\": 39215,\n    \"Ġtempor\": 39216,\n    \"Ġwhispered\": 39217,\n    \"ogly\": 39218,\n    \"coord\": 39219,\n    \"chlor\": 39220,\n    \"processing\": 39221,\n    \"iott\": 39222,\n    \"ĠTY\": 39223,\n    \"wik\": 39224,\n    \"abolic\": 39225,\n    \"ĠUnable\": 39226,\n    \"ĠLiterary\": 39227,\n    \"ĠpH\": 39228,\n    \"Eastern\": 39229,\n    \"Craig\": 39230,\n    \"Fear\": 39231,\n    \"Ġinventions\": 39232,\n    \"ĠNost\": 39233,\n    \"Ġafflicted\": 39234,\n    \"ĠSwamp\": 39235,\n    \"INST\": 39236,\n    \"Jerry\": 39237,\n    \"Ġprope\": 39238,\n    \"ĠLancet\": 39239,\n    \"Ġrefres\": 39240,\n    \"ĠPrinciples\": 39241,\n    \"ĠLys\": 39242,\n    \"ERAL\": 39243,\n    \"addock\": 39244,\n    \"Ġcynicism\": 39245,\n    \"Ġmassacres\": 39246,\n    \"roo\": 39247,\n    \"Ġcollagen\": 39248,\n    \"Johnny\": 39249,\n    \"Keith\": 39250,\n    \"Italian\": 39251,\n    \"553\": 39252,\n    \"Dad\": 39253,\n    \"Neither\": 39254,\n    \"cler\": 39255,\n    \"ilers\": 39256,\n    \"Ġassass\": 39257,\n    \"Travel\": 39258,\n    \"672\": 39259,\n    \"Ġeaves\": 39260,\n    \"ATOR\": 39261,\n    \"Ġoily\": 39262,\n    \"581\": 39263,\n    \"ateful\": 39264,\n    \"728\": 39265,\n    \"Ġchiefly\": 39266,\n    \"tical\": 39267,\n    \"enes\": 39268,\n    \"ĠWouldn\": 39269,\n    \"ĠJacket\": 39270,\n    \"ĠSuit\": 39271,\n    \"Ġindustrialized\": 39272,\n    \"ĠNose\": 39273,\n    \"ĠSECTION\": 39274,\n    \"Ġredd\": 39275,\n    \"Ġcavity\": 39276,\n    \"Ġconn\": 39277,\n    \"Shield\": 39278,\n    \"Ġtongues\": 39279,\n    \"Ġsuccinct\": 39280,\n    \"views\": 39281,\n    \"ĠMUST\": 39282,\n    \"oliath\": 39283,\n    \"Ġlimitless\": 39284,\n    \"Ġapocalyptic\": 39285,\n    \"ĠAtlantis\": 39286,\n    \"DNA\": 39287,\n    \"ilded\": 39288,\n    \"ĠDresden\": 39289,\n    \"nit\": 39290,\n    \"Ġsubdiv\": 39291,\n    \"gressive\": 39292,\n    \"701\": 39293,\n    \"hops\": 39294,\n    \"alist\": 39295,\n    \"Ġunintentional\": 39296,\n    \"Ġpsychic\": 39297,\n    \"Ġcontrovers\": 39298,\n    \"Ġforeground\": 39299,\n    \"ĠnaÃ¯ve\": 39300,\n    \"Ġfolders\": 39301,\n    \"icist\": 39302,\n    \"Ġdrawbacks\": 39303,\n    \"ĠToxic\": 39304,\n    \"ophy\": 39305,\n    \"ĠMasonic\": 39306,\n    \"Ġcis\": 39307,\n    \"olated\": 39308,\n    \"Ġdepletion\": 39309,\n    \"Rap\": 39310,\n    \"692\": 39311,\n    \"Ġinver\": 39312,\n    \"ĠFAQ\": 39313,\n    \"Ġmeanings\": 39314,\n    \"Ġbisc\": 39315,\n    \"ĠRage\": 39316,\n    \"Ġresear\": 39317,\n    \"Ep\": 39318,\n    \"Ġunbeat\": 39319,\n    \"ĠComponents\": 39320,\n    \"bub\": 39321,\n    \"ĠInterface\": 39322,\n    \"Isa\": 39323,\n    \"ĠArgon\": 39324,\n    \"Ġdenomin\": 39325,\n    \"Ġmammal\": 39326,\n    \"519\": 39327,\n    \"Ġsizing\": 39328,\n    \"imbabwe\": 39329,\n    \"ĠReplacement\": 39330,\n    \"Georgia\": 39331,\n    \"ĠParticipation\": 39332,\n    \"Ġmelts\": 39333,\n    \"Ġfemin\": 39334,\n    \"514\": 39335,\n    \"Ġseams\": 39336,\n    \"513\": 39337,\n    \"ĠGaw\": 39338,\n    \"Ġbrood\": 39339,\n    \"Mit\": 39340,\n    \"Ġannoyance\": 39341,\n    \"Ġequilibrium\": 39342,\n    \"Ġpatri\": 39343,\n    \"Ġ338\": 39344,\n    \"561\": 39345,\n    \"mentioned\": 39346,\n    \"ĠVotes\": 39347,\n    \"Ġintoler\": 39348,\n    \"Ġstrikingly\": 39349,\n    \"Ġ352\": 39350,\n    \"Ġskeletal\": 39351,\n    \"616\": 39352,\n    \"isition\": 39353,\n    \"Ġfluor\": 39354,\n    \"provided\": 39355,\n    \"517\": 39356,\n    \"Ġclimates\": 39357,\n    \"Ġsensibilities\": 39358,\n    \"ĠFrequ\": 39359,\n    \"onite\": 39360,\n    \"Kenn\": 39361,\n    \"Ġmagnets\": 39362,\n    \"assis\": 39363,\n    \"Ġprerequisite\": 39364,\n    \"Ġ>>>\": 39365,\n    \"Ġscree\": 39366,\n    \"google\": 39367,\n    \"ĠMirage\": 39368,\n    \"Ġevict\": 39369,\n    \"Peace\": 39370,\n    \"Ġmissionaries\": 39371,\n    \"617\": 39372,\n    \"748\": 39373,\n    \"rient\": 39374,\n    \"ĠSTATS\": 39375,\n    \"Bird\": 39376,\n    \"ĠShiva\": 39377,\n    \"ĠBlessing\": 39378,\n    \"Ġredundancy\": 39379,\n    \"Ġphotoc\": 39380,\n    \"ĠOnes\": 39381,\n    \"754\": 39382,\n    \"alert\": 39383,\n    \"urous\": 39384,\n    \"Ġfolklore\": 39385,\n    \"ĠIdeal\": 39386,\n    \"sheets\": 39387,\n    \"according\": 39388,\n    \"Hor\": 39389,\n    \"Cle\": 39390,\n    \"ĠEdit\": 39391,\n    \"671\": 39392,\n    \"olitics\": 39393,\n    \"ĠESC\": 39394,\n    \"Ġparaly\": 39395,\n    \"Ġorgasm\": 39396,\n    \"speak\": 39397,\n    \"Ã°\": 39398,\n    \"Ġsneaky\": 39399,\n    \"Ġswords\": 39400,\n    \"Ġfandom\": 39401,\n    \"776\": 39402,\n    \"ĠScandinav\": 39403,\n    \"Ġdarts\": 39404,\n    \"546\": 39405,\n    \"cerpt\": 39406,\n    \"ĠGifts\": 39407,\n    \"Ġmagically\": 39408,\n    \"phys\": 39409,\n    \"Laughs\": 39410,\n    \"ĠSour\": 39411,\n    \"ources\": 39412,\n    \"789\": 39413,\n    \"ĠEps\": 39414,\n    \"ository\": 39415,\n    \"uality\": 39416,\n    \"literally\": 39417,\n    \"Ġheavens\": 39418,\n    \"FUL\": 39419,\n    \"Ġie\": 39420,\n    \"ĠISP\": 39421,\n    \"Ġwink\": 39422,\n    \"Ġweeping\": 39423,\n    \"Ġdocking\": 39424,\n    \"ACY\": 39425,\n    \"iece\": 39426,\n    \"Ġsignifies\": 39427,\n    \"guns\": 39428,\n    \"Sac\": 39429,\n    \"Leave\": 39430,\n    \"imation\": 39431,\n    \"Ġunex\": 39432,\n    \"uctive\": 39433,\n    \"ĠFees\": 39434,\n    \"ĠPortable\": 39435,\n    \"ĠInvestigator\": 39436,\n    \"pill\": 39437,\n    \"rehensible\": 39438,\n    \"Ġpotency\": 39439,\n    \"803\": 39440,\n    \"Ġembodiment\": 39441,\n    \"overty\": 39442,\n    \"shine\": 39443,\n    \"REL\": 39444,\n    \"ĠMPH\": 39445,\n    \"ĠPatriarch\": 39446,\n    \"Ġaspirin\": 39447,\n    \"Ġrinse\": 39448,\n    \"Ġinher\": 39449,\n    \"ograms\": 39450,\n    \"ĠTHREE\": 39451,\n    \"qt\": 39452,\n    \"ipples\": 39453,\n    \"Ġdehuman\": 39454,\n    \"Ġslander\": 39455,\n    \"Ġflora\": 39456,\n    \"brow\": 39457,\n    \"Ġblindly\": 39458,\n    \"ectar\": 39459,\n    \"endish\": 39460,\n    \"Ġpigment\": 39461,\n    \"cellent\": 39462,\n    \"Ġyells\": 39463,\n    \"ĠLust\": 39464,\n    \"ĠAttacks\": 39465,\n    \"ĠSyndicate\": 39466,\n    \"otin\": 39467,\n    \"gress\": 39468,\n    \"reenshot\": 39469,\n    \"picking\": 39470,\n    \"Ġacupuncture\": 39471,\n    \"images\": 39472,\n    \"glas\": 39473,\n    \"ĠPolicies\": 39474,\n    \"Ġintestinal\": 39475,\n    \"1998\": 39476,\n    \"ULE\": 39477,\n    \"runs\": 39478,\n    \"ĠNing\": 39479,\n    \"ĠAsuka\": 39480,\n    \"ĠSkull\": 39481,\n    \"Motor\": 39482,\n    \"Ġdefund\": 39483,\n    \"Ġattaching\": 39484,\n    \"ĠBAD\": 39485,\n    \"Ġquarrel\": 39486,\n    \"Child\": 39487,\n    \"Dog\": 39488,\n    \"issan\": 39489,\n    \"irmation\": 39490,\n    \"Ġinline\": 39491,\n    \"ĠLover\": 39492,\n    \"Ġcyan\": 39493,\n    \"entary\": 39494,\n    \"awareness\": 39495,\n    \"Ġtraveller\": 39496,\n    \"âĢĲ\": 39497,\n    \"Ġbeasts\": 39498,\n    \"Ġboobs\": 39499,\n    \"ĠDeadly\": 39500,\n    \"Ġplutonium\": 39501,\n    \"ĠIntellectual\": 39502,\n    \"Jam\": 39503,\n    \"Ġconsec\": 39504,\n    \"663\": 39505,\n    \"ĠVegan\": 39506,\n    \"Ġ331\": 39507,\n    \"uron\": 39508,\n    \"ĠHEL\": 39509,\n    \"reements\": 39510,\n    \"Ġclone\": 39511,\n    \"Ġoutputs\": 39512,\n    \"oult\": 39513,\n    \"ĠDOM\": 39514,\n    \"ĠNX\": 39515,\n    \"Ze\": 39516,\n    \"909\": 39517,\n    \"brate\": 39518,\n    \"arations\": 39519,\n    \"ĠJindal\": 39520,\n    \"Ġbooklet\": 39521,\n    \"amide\": 39522,\n    \"Ġscraping\": 39523,\n    \"Sol\": 39524,\n    \"Date\": 39525,\n    \"796\": 39526,\n    \"Ġfulf\": 39527,\n    \"Ġskeletons\": 39528,\n    \"Ġsaints\": 39529,\n    \"ĠCurious\": 39530,\n    \"Han\": 39531,\n    \"Ġrepud\": 39532,\n    \"osity\": 39533,\n    \"ĠGravity\": 39534,\n    \"Ġmetadata\": 39535,\n    \"Focus\": 39536,\n    \"Ġthrott\": 39537,\n    \"ĠProgramming\": 39538,\n    \"Break\": 39539,\n    \"erver\": 39540,\n    \"Ġknight\": 39541,\n    \"yrs\": 39542,\n    \"Ġ376\": 39543,\n    \"sat\": 39544,\n    \"auto\": 39545,\n    \"Ġbroom\": 39546,\n    \"Ġnerd\": 39547,\n    \"Political\": 39548,\n    \"022\": 39549,\n    \"-------------\": 39550,\n    \"oulos\": 39551,\n    \"Ġrelic\": 39552,\n    \"Ġenactment\": 39553,\n    \"rious\": 39554,\n    \"ĠUniform\": 39555,\n    \"Teen\": 39556,\n    \"Colorado\": 39557,\n    \"055\": 39558,\n    \"Ġangled\": 39559,\n    \"bolt\": 39560,\n    \"ĠNeander\": 39561,\n    \"ĠDism\": 39562,\n    \"thanks\": 39563,\n    \"Polit\": 39564,\n    \"ersion\": 39565,\n    \"dro\": 39566,\n    \"install\": 39567,\n    \"Jake\": 39568,\n    \"hz\": 39569,\n    \"Ġ770\": 39570,\n    \"ĠCommodore\": 39571,\n    \"lahoma\": 39572,\n    \"Ġshri\": 39573,\n    \"Ġ....\": 39574,\n    \"Ġ7000\": 39575,\n    \"scope\": 39576,\n    \"Ġgenesis\": 39577,\n    \"Ġresided\": 39578,\n    \"ĠRivals\": 39579,\n    \"Ġsarcastic\": 39580,\n    \"Ġelicit\": 39581,\n    \"Ġmultiplied\": 39582,\n    \"uitous\": 39583,\n    \"Ġoppress\": 39584,\n    \"ĠPROT\": 39585,\n    \"Ġperpetually\": 39586,\n    \"ĠAdds\": 39587,\n    \"Ġbuffers\": 39588,\n    \"Ġmush\": 39589,\n    \"Ġ354\": 39590,\n    \"Ġpresc\": 39591,\n    \"ĠKung\": 39592,\n    \"682\": 39593,\n    \"Education\": 39594,\n    \"Ġpled\": 39595,\n    \"bsp\": 39596,\n    \"Ġconfessions\": 39597,\n    \"Ġrevocation\": 39598,\n    \"Micro\": 39599,\n    \"ĠHobby\": 39600,\n    \"ĠFatal\": 39601,\n    \"STAR\": 39602,\n    \"Ġworkspace\": 39603,\n    \"Ġtransformations\": 39604,\n    \"Ġportals\": 39605,\n    \"orned\": 39606,\n    \"figured\": 39607,\n    \"Ġlinguistic\": 39608,\n    \"pperc\": 39609,\n    \"ergus\": 39610,\n    \"Fel\": 39611,\n    \"ĠIntent\": 39612,\n    \"Ġ289\": 39613,\n    \"Ġdelinquent\": 39614,\n    \"Ġhandwriting\": 39615,\n    \"Ġvap\": 39616,\n    \"576\": 39617,\n    \"redited\": 39618,\n    \"736\": 39619,\n    \"Ġpsychiatry\": 39620,\n    \"GMT\": 39621,\n    \"Ġdisingen\": 39622,\n    \"Ġcrou\": 39623,\n    \"801\": 39624,\n    \"Ġmalice\": 39625,\n    \"itutes\": 39626,\n    \"ĠTiff\": 39627,\n    \"Ġstink\": 39628,\n    \"574\": 39629,\n    \"Story\": 39630,\n    \"Modern\": 39631,\n    \"ĠGly\": 39632,\n    \"Jamie\": 39633,\n    \"Ġadvertis\": 39634,\n    \"Ġhiber\": 39635,\n    \"Ġinfiltr\": 39636,\n    \"Ġelector\": 39637,\n    \"rovers\": 39638,\n    \"ĠFist\": 39639,\n    \"peed\": 39640,\n    \"ĠClassical\": 39641,\n    \"592\": 39642,\n    \"Ġconscientious\": 39643,\n    \"Surv\": 39644,\n    \"Text\": 39645,\n    \"ĠDrunk\": 39646,\n    \"Ġsupplemented\": 39647,\n    \"THIS\": 39648,\n    \"Ġtimid\": 39649,\n    \"Ġstacking\": 39650,\n    \"rites\": 39651,\n    \"Ġrebirth\": 39652,\n    \"Ġbalcon\": 39653,\n    \"Ġyawn\": 39654,\n    \"rosc\": 39655,\n    \"axy\": 39656,\n    \"Hart\": 39657,\n    \"ĠOPER\": 39658,\n    \"996\": 39659,\n    \"Ġrabid\": 39660,\n    \"ĠTick\": 39661,\n    \"Ġgrinning\": 39662,\n    \"elfth\": 39663,\n    \"045\": 39664,\n    \"Ġjustifies\": 39665,\n    \"ĠPirate\": 39666,\n    \"ĠSalary\": 39667,\n    \"Ġmirac\": 39668,\n    \"613\": 39669,\n    \"inately\": 39670,\n    \"ĠLIN\": 39671,\n    \"Ġinadequ\": 39672,\n    \"NPR\": 39673,\n    \"iddled\": 39674,\n    \"storage\": 39675,\n    \"Ġseventy\": 39676,\n    \"onet\": 39677,\n    \"Ġgastro\": 39678,\n    \"FIR\": 39679,\n    \"Ġrodent\": 39680,\n    \"629\": 39681,\n    \"ĠInclude\": 39682,\n    \"ĠCategories\": 39683,\n    \"ĠLiterally\": 39684,\n    \"Ġpree\": 39685,\n    \"aunder\": 39686,\n    \"ĠLOL\": 39687,\n    \"694\": 39688,\n    \"Ġindef\": 39689,\n    \"Ped\": 39690,\n    \"Ġmenstru\": 39691,\n    \"Ġcensored\": 39692,\n    \"Ġconfigure\": 39693,\n    \"Ġoverest\": 39694,\n    \"igenous\": 39695,\n    \"Ġrectangular\": 39696,\n    \"ĠMIS\": 39697,\n    \"ĠMub\": 39698,\n    \"Ġwitches\": 39699,\n    \"izards\": 39700,\n    \"Ġobnoxious\": 39701,\n    \"ĠLoll\": 39702,\n    \"ĠSEM\": 39703,\n    \"Ġspiritually\": 39704,\n    \"Ġcoer\": 39705,\n    \"Ġmodesty\": 39706,\n    \"butt\": 39707,\n    \"Ġedits\": 39708,\n    \"ĠShall\": 39709,\n    \"sburgh\": 39710,\n    \"Ġ1911\": 39711,\n    \"Rex\": 39712,\n    \"manent\": 39713,\n    \"ĠLithuan\": 39714,\n    \"Ġpointers\": 39715,\n    \"ativity\": 39716,\n    \"retch\": 39717,\n    \"Ġcascade\": 39718,\n    \"ĠRagnarok\": 39719,\n    \"ĠPainting\": 39720,\n    \"ĠATL\": 39721,\n    \"Born\": 39722,\n    \"Ġpadding\": 39723,\n    \"whel\": 39724,\n    \"Ġgrotesque\": 39725,\n    \"Ġtheorists\": 39726,\n    \"forcer\": 39727,\n    \"ĠJinn\": 39728,\n    \"Ġrenal\": 39729,\n    \"jamin\": 39730,\n    \"ĠFEC\": 39731,\n    \".\\\"\\\"\": 39732,\n    \"redict\": 39733,\n    \"Ġoppos\": 39734,\n    \"opted\": 39735,\n    \"Sel\": 39736,\n    \"ipment\": 39737,\n    \"752\": 39738,\n    \"792\": 39739,\n    \"Pur\": 39740,\n    \"Ġvolt\": 39741,\n    \"Ġflap\": 39742,\n    \"ĠCASE\": 39743,\n    \"Ġdyed\": 39744,\n    \"orers\": 39745,\n    \"becca\": 39746,\n    \",.\": 39747,\n    \"ifice\": 39748,\n    \"ubes\": 39749,\n    \"Ġyr\": 39750,\n    \"DW\": 39751,\n    \"Ġalteration\": 39752,\n    \"ĠSimpl\": 39753,\n    \"Ġunequiv\": 39754,\n    \"756\": 39755,\n    \"Dou\": 39756,\n    \"Ġplunder\": 39757,\n    \"Ġcommons\": 39758,\n    \"Ġstag\": 39759,\n    \"ĠZeal\": 39760,\n    \"avanaugh\": 39761,\n    \"Self\": 39762,\n    \"none\": 39763,\n    \"EGIN\": 39764,\n    \"Ġflashback\": 39765,\n    \"VAL\": 39766,\n    \"Gab\": 39767,\n    \"ĠCapture\": 39768,\n    \"ĠBrilliant\": 39769,\n    \"ĠDisk\": 39770,\n    \"ĠMood\": 39771,\n    \"Ġhaun\": 39772,\n    \"Ġrotting\": 39773,\n    \"ĠCobra\": 39774,\n    \"Ġpsychopath\": 39775,\n    \"Ġhelper\": 39776,\n    \"Starting\": 39777,\n    \"ĠOrbit\": 39778,\n    \"Ġcaf\": 39779,\n    \"Half\": 39780,\n    \"Volume\": 39781,\n    \"aptop\": 39782,\n    \"ĠSaga\": 39783,\n    \"azor\": 39784,\n    \"593\": 39785,\n    \"774\": 39786,\n    \"ĠCaucasian\": 39787,\n    \"compan\": 39788,\n    \"ĠVERY\": 39789,\n    \"GES\": 39790,\n    \"Ġvomit\": 39791,\n    \"Ġdispro\": 39792,\n    \"ĠMechanics\": 39793,\n    \"Ġ385\": 39794,\n    \"Ġmystical\": 39795,\n    \"AFTA\": 39796,\n    \"Ġbacter\": 39797,\n    \"availability\": 39798,\n    \"Ġhairc\": 39799,\n    \"ĠVec\": 39800,\n    \"rypt\": 39801,\n    \"Ġmanipulative\": 39802,\n    \"shell\": 39803,\n    \"ĠWeird\": 39804,\n    \"jab\": 39805,\n    \"ĠByr\": 39806,\n    \"Bow\": 39807,\n    \"uin\": 39808,\n    \"Ġquot\": 39809,\n    \"MX\": 39810,\n    \"Ġ960\": 39811,\n    \"ĠSharia\": 39812,\n    \"ĠWeapon\": 39813,\n    \"ĠPowerPoint\": 39814,\n    \"Ġstitching\": 39815,\n    \"Ġconstraint\": 39816,\n    \"âľ\": 39817,\n    \"ulic\": 39818,\n    \"597\": 39819,\n    \"omedical\": 39820,\n    \"ĠSupplemental\": 39821,\n    \"ĠSurve\": 39822,\n    \"ĠSubcommittee\": 39823,\n    \"ĠDarkness\": 39824,\n    \"Ġpython\": 39825,\n    \"LU\": 39826,\n    \"Ġ402\": 39827,\n    \"ĠQuan\": 39828,\n    \"ĠModerate\": 39829,\n    \"clusively\": 39830,\n    \"Ġextrap\": 39831,\n    \"Ġlatt\": 39832,\n    \"ĠSTUD\": 39833,\n    \"oslav\": 39834,\n    \"Ġsymb\": 39835,\n    \"battle\": 39836,\n    \"flash\": 39837,\n    \"ĠDeploy\": 39838,\n    \"Ġmicrobiome\": 39839,\n    \"Ġingested\": 39840,\n    \"Ġdistort\": 39841,\n    \"Ġassimil\": 39842,\n    \"Ġmobs\": 39843,\n    \"illet\": 39844,\n    \"Gre\": 39845,\n    \"Ġ294\": 39846,\n    \"Ġforbids\": 39847,\n    \"ĠEfficiency\": 39848,\n    \"ĠClan\": 39849,\n    \"763\": 39850,\n    \"Ġdragons\": 39851,\n    \"States\": 39852,\n    \"ĠMAKE\": 39853,\n    \"ĠBOOK\": 39854,\n    \"ĠRuns\": 39855,\n    \"ĠUX\": 39856,\n    \"EED\": 39857,\n    \"Whoever\": 39858,\n    \"ionics\": 39859,\n    \"worldly\": 39860,\n    \"ĠMermaid\": 39861,\n    \"Ġbenz\": 39862,\n    \"Info\": 39863,\n    \"523\": 39864,\n    \"Ġbiod\": 39865,\n    \"ĠPoison\": 39866,\n    \"ceivable\": 39867,\n    \"Services\": 39868,\n    \"ATIVE\": 39869,\n    \"ĠItem\": 39870,\n    \"Ġdisav\": 39871,\n    \"Ġheter\": 39872,\n    \"Ġasteroids\": 39873,\n    \"ĠWooden\": 39874,\n    \"Ġelectroly\": 39875,\n    \"assadors\": 39876,\n    \"nance\": 39877,\n    \"reflect\": 39878,\n    \"Ġattent\": 39879,\n    \"iphany\": 39880,\n    \"Ġspaceship\": 39881,\n    \"Ġbegg\": 39882,\n    \"algia\": 39883,\n    \"Ax\": 39884,\n    \"Ġidiosyncr\": 39885,\n    \"Ġinserting\": 39886,\n    \"ĠCSS\": 39887,\n    \"ĠLET\": 39888,\n    \"ĠStrikes\": 39889,\n    \"ossibly\": 39890,\n    \"Exp\": 39891,\n    \"Opp\": 39892,\n    \"dden\": 39893,\n    \"Ġplayable\": 39894,\n    \"ĠJM\": 39895,\n    \"Ġlawfully\": 39896,\n    \"ĠBlink\": 39897,\n    \"Ġ413\": 39898,\n    \"Ġoverpowered\": 39899,\n    \"Ġcommenter\": 39900,\n    \"Track\": 39901,\n    \"Ġmethyl\": 39902,\n    \"Ġfermented\": 39903,\n    \"Ġinvaders\": 39904,\n    \"ĠMoves\": 39905,\n    \"Ġcommunicates\": 39906,\n    \"rint\": 39907,\n    \"ĠTray\": 39908,\n    \"jug\": 39909,\n    \"Ġsuperf\": 39910,\n    \"ochet\": 39911,\n    \"ĠJelly\": 39912,\n    \"Ġestrogen\": 39913,\n    \"Dom\": 39914,\n    \"mix\": 39915,\n    \"Gun\": 39916,\n    \"ochemistry\": 39917,\n    \"952\": 39918,\n    \"Ġovere\": 39919,\n    \"ĠPlaintiff\": 39920,\n    \"ĠPilgrim\": 39921,\n    \"ĠSERVICES\": 39922,\n    \"ĠExpend\": 39923,\n    \"ĠFRE\": 39924,\n    \"Ġsmelling\": 39925,\n    \"ĠSpaces\": 39926,\n    \"bris\": 39927,\n    \"Mission\": 39928,\n    \"Ġarter\": 39929,\n    \"Ġautonom\": 39930,\n    \"Lisa\": 39931,\n    \"ĠPercent\": 39932,\n    \"NK\": 39933,\n    \"ĠLimits\": 39934,\n    \"Ġ356\": 39935,\n    \"Recent\": 39936,\n    \"ĠSiberian\": 39937,\n    \"etermin\": 39938,\n    \"nets\": 39939,\n    \"ĠSword\": 39940,\n    \"essee\": 39941,\n    \"Ùĩ\": 39942,\n    \"icycle\": 39943,\n    \"Ġparas\": 39944,\n    \"Ġrud\": 39945,\n    \"Ġscrib\": 39946,\n    \"Ġ1860\": 39947,\n    \"Shop\": 39948,\n    \"orld\": 39949,\n    \"Ġpept\": 39950,\n    \"ENSE\": 39951,\n    \"Ġanimations\": 39952,\n    \"ership\": 39953,\n    \"Search\": 39954,\n    \"ĠUSSR\": 39955,\n    \"washed\": 39956,\n    \"Ġpromulg\": 39957,\n    \"Ġdetainee\": 39958,\n    \"Ġunderest\": 39959,\n    \"ĠAppropri\": 39960,\n    \"Left\": 39961,\n    \"Update\": 39962,\n    \"Wallet\": 39963,\n    \"idently\": 39964,\n    \"ĠBicycle\": 39965,\n    \"Ġgorge\": 39966,\n    \"abyte\": 39967,\n    \"ĠMinecraft\": 39968,\n    \"rike\": 39969,\n    \"997\": 39970,\n    \"Tesla\": 39971,\n    \"Often\": 39972,\n    \"ĠTHESE\": 39973,\n    \"Ġregression\": 39974,\n    \"Hen\": 39975,\n    \"Ġsnippets\": 39976,\n    \"irds\": 39977,\n    \"Ġprinces\": 39978,\n    \"Ġwastes\": 39979,\n    \"ĠWond\": 39980,\n    \"itimate\": 39981,\n    \"ĠMongol\": 39982,\n    \"ĠkW\": 39983,\n    \"Ġidiots\": 39984,\n    \"Ġforeigner\": 39985,\n    \"Upon\": 39986,\n    \"Ġbackdoor\": 39987,\n    \"umph\": 39988,\n    \"ĠSquirrel\": 39989,\n    \"Ġtyped\": 39990,\n    \"Ġblockers\": 39991,\n    \"Vote\": 39992,\n    \"ĠPossibly\": 39993,\n    \"geist\": 39994,\n    \"ĠTRANS\": 39995,\n    \"Ġtitan\": 39996,\n    \"VG\": 39997,\n    \"Ġmicrobi\": 39998,\n    \"Ġinteracts\": 39999,\n    \"Ġmasc\": 40000,\n    \"Ġfinite\": 40001,\n    \"Ġcutoff\": 40002,\n    \"ornings\": 40003,\n    \"Ġprototyp\": 40004,\n    \"Ġcompan\": 40005,\n    \"mology\": 40006,\n    \"ĠBOX\": 40007,\n    \"Cre\": 40008,\n    \"Bot\": 40009,\n    \"grading\": 40010,\n    \"PET\": 40011,\n    \"Ġinsidious\": 40012,\n    \"ĠFranch\": 40013,\n    \"orians\": 40014,\n    \"ĠAUT\": 40015,\n    \"ĠCrush\": 40016,\n    \"589\": 40017,\n    \"question\": 40018,\n    \"anguard\": 40019,\n    \"Ġabsurdity\": 40020,\n    \"?\\\",\": 40021,\n    \"Hum\": 40022,\n    \"Ġliberalism\": 40023,\n    \"Ġpostwar\": 40024,\n    \"Gener\": 40025,\n    \"Personally\": 40026,\n    \"889\": 40027,\n    \"Bul\": 40028,\n    \"Ġlighthouse\": 40029,\n    \"Ġ291\": 40030,\n    \"VK\": 40031,\n    \"ĠExposure\": 40032,\n    \"Ġsubtract\": 40033,\n    \"ometime\": 40034,\n    \"arbon\": 40035,\n    \"ĠThieves\": 40036,\n    \"anus\": 40037,\n    \"ĠLibertarian\": 40038,\n    \"Raw\": 40039,\n    \"Ġsolvent\": 40040,\n    \"Ġcorros\": 40041,\n    \"Ġsignific\": 40042,\n    \"Ġscholarly\": 40043,\n    \"024\": 40044,\n    \"Ġfetish\": 40045,\n    \"Ġlarvae\": 40046,\n    \"Ġcatast\": 40047,\n    \"Ġtraitor\": 40048,\n    \"ijing\": 40049,\n    \"Demand\": 40050,\n    \"math\": 40051,\n    \"Ġconceivable\": 40052,\n    \"either\": 40053,\n    \"acl\": 40054,\n    \"ĠArrows\": 40055,\n    \"627\": 40056,\n    \"ĠFrankenstein\": 40057,\n    \"entious\": 40058,\n    \"Ġimitation\": 40059,\n    \"amn\": 40060,\n    \"ĠSTOP\": 40061,\n    \"Ġcripp\": 40062,\n    \"zag\": 40063,\n    \"ĠZed\": 40064,\n    \"797\": 40065,\n    \"Along\": 40066,\n    \"Ġwont\": 40067,\n    \"Ġfolds\": 40068,\n    \"Shar\": 40069,\n    \"ĠCommentary\": 40070,\n    \"ĠLibraries\": 40071,\n    \"ĠThunderbolt\": 40072,\n    \"itud\": 40073,\n    \"Toy\": 40074,\n    \"Ġincidentally\": 40075,\n    \"ĠResp\": 40076,\n    \"Ġordinarily\": 40077,\n    \"Ġvanish\": 40078,\n    \"acterial\": 40079,\n    \"Minnesota\": 40080,\n    \"rank\": 40081,\n    \"614\": 40082,\n    \"ĠExam\": 40083,\n    \"Got\": 40084,\n    \"Ġsnipers\": 40085,\n    \"ETHOD\": 40086,\n    \"dirty\": 40087,\n    \"igsaw\": 40088,\n    \"Obs\": 40089,\n    \"ĠAuthors\": 40090,\n    \"Ġillustrating\": 40091,\n    \"782\": 40092,\n    \"864\": 40093,\n    \"Ġblinded\": 40094,\n    \"transfer\": 40095,\n    \"Ġspawning\": 40096,\n    \"ĠDiary\": 40097,\n    \"ĠDNS\": 40098,\n    \"CG\": 40099,\n    \"someone\": 40100,\n    \"Ġcruc\": 40101,\n    \"Morgan\": 40102,\n    \"Learn\": 40103,\n    \"API\": 40104,\n    \"toc\": 40105,\n    \"STAT\": 40106,\n    \"ĠFlame\": 40107,\n    \"aganda\": 40108,\n    \"ĠBenef\": 40109,\n    \"stuff\": 40110,\n    \"SEA\": 40111,\n    \"Ġincest\": 40112,\n    \"Normally\": 40113,\n    \"ĠRU\": 40114,\n    \"Ġarsenic\": 40115,\n    \"isine\": 40116,\n    \"ĠTG\": 40117,\n    \"Type\": 40118,\n    \"regn\": 40119,\n    \"Cass\": 40120,\n    \"Touch\": 40121,\n    \"Site\": 40122,\n    \"Ġpict\": 40123,\n    \"Ġcorrupted\": 40124,\n    \"729\": 40125,\n    \"Ġnineteen\": 40126,\n    \"Ġparaph\": 40127,\n    \"Ġtavern\": 40128,\n    \"Ġretard\": 40129,\n    \"ĠKaf\": 40130,\n    \"Ġcolleg\": 40131,\n    \"bucks\": 40132,\n    \"imum\": 40133,\n    \"ĠCandle\": 40134,\n    \"ĠMisc\": 40135,\n    \"ĠAwesome\": 40136,\n    \"edited\": 40137,\n    \"ĠDN\": 40138,\n    \"otomy\": 40139,\n    \"Ġdisclaimer\": 40140,\n    \"798\": 40141,\n    \"ĠGoodbye\": 40142,\n    \"ucle\": 40143,\n    \"atom\": 40144,\n    \"Judge\": 40145,\n    \"cipl\": 40146,\n    \"Ġinexplicable\": 40147,\n    \"iddler\": 40148,\n    \"781\": 40149,\n    \"Ġempirical\": 40150,\n    \"Veter\": 40151,\n    \"Ġascert\": 40152,\n    \"Ġaest\": 40153,\n    \"Ġlaz\": 40154,\n    \"binary\": 40155,\n    \"Ġ358\": 40156,\n    \"contained\": 40157,\n    \"Ġmultipl\": 40158,\n    \"ocado\": 40159,\n    \"Ġdelusional\": 40160,\n    \"Ġaeros\": 40161,\n    \"udence\": 40162,\n    \"Ġjargon\": 40163,\n    \"estine\": 40164,\n    \"Ġarbitrarily\": 40165,\n    \"Ġprick\": 40166,\n    \"BACK\": 40167,\n    \"amines\": 40168,\n    \"Mess\": 40169,\n    \"Knowing\": 40170,\n    \"ublic\": 40171,\n    \"ĠWarfare\": 40172,\n    \"Ġsignify\": 40173,\n    \"Ġfragmentation\": 40174,\n    \"Tex\": 40175,\n    \"Ġnin\": 40176,\n    \"Ġdise\": 40177,\n    \"882\": 40178,\n    \"hospital\": 40179,\n    \"volent\": 40180,\n    \"Need\": 40181,\n    \"Ġinfer\": 40182,\n    \"Sony\": 40183,\n    \"783\": 40184,\n    \"YING\": 40185,\n    \"Ġinfinity\": 40186,\n    \"ĠFortress\": 40187,\n    \"Ġmustache\": 40188,\n    \"Ġcorresponds\": 40189,\n    \"DX\": 40190,\n    \"Ġunmarried\": 40191,\n    \"ĠCruel\": 40192,\n    \"Ġ1901\": 40193,\n    \"Ġappropri\": 40194,\n    \"ZI\": 40195,\n    \"Ġphosph\": 40196,\n    \"901\": 40197,\n    \"IFE\": 40198,\n    \"Ġ347\": 40199,\n    \"Ġconvoluted\": 40200,\n    \"ĠApost\": 40201,\n    \"htm\": 40202,\n    \"Ġilluminating\": 40203,\n    \"568\": 40204,\n    \"Ġassassinate\": 40205,\n    \"Ġparam\": 40206,\n    \"Ġimpractical\": 40207,\n    \"cedes\": 40208,\n    \"ĠProcedure\": 40209,\n    \"ĠMouth\": 40210,\n    \"Battle\": 40211,\n    \"Ġ451\": 40212,\n    \"Sand\": 40213,\n    \"Ġcontamin\": 40214,\n    \"Hour\": 40215,\n    \"Cell\": 40216,\n    \"BIL\": 40217,\n    \"Ġprecon\": 40218,\n    \"ĠScor\": 40219,\n    \"Ġconfig\": 40220,\n    \"ĠMuscle\": 40221,\n    \"Ġhive\": 40222,\n    \"Ġunderworld\": 40223,\n    \"plement\": 40224,\n    \"Ġpostage\": 40225,\n    \"Ġinterpersonal\": 40226,\n    \"Ġpierced\": 40227,\n    \"Ġcharms\": 40228,\n    \"oscopic\": 40229,\n    \"ASC\": 40230,\n    \"ĠDex\": 40231,\n    \"render\": 40232,\n    \"png\": 40233,\n    \"Ġcritiques\": 40234,\n    \"992\": 40235,\n    \"ĠVinyl\": 40236,\n    \"Bear\": 40237,\n    \"idia\": 40238,\n    \"ĠTemp\": 40239,\n    \"Ġcyn\": 40240,\n    \"ĠBCE\": 40241,\n    \"Ġpatriarchal\": 40242,\n    \"Ġantagonist\": 40243,\n    \"ĠGMO\": 40244,\n    \"Ġunnatural\": 40245,\n    \"Race\": 40246,\n    \"imeo\": 40247,\n    \"ĠUkrainians\": 40248,\n    \"Train\": 40249,\n    \"Ġ329\": 40250,\n    \"ritten\": 40251,\n    \"igil\": 40252,\n    \"Lin\": 40253,\n    \"alus\": 40254,\n    \"*****\": 40255,\n    \"olded\": 40256,\n    \"ĠPegasus\": 40257,\n    \"Bas\": 40258,\n    \"photos\": 40259,\n    \"Ġ820\": 40260,\n    \"Ġsquadron\": 40261,\n    \"ESE\": 40262,\n    \"Ġ373\": 40263,\n    \"Uk\": 40264,\n    \"Lost\": 40265,\n    \"Store\": 40266,\n    \"ĠScenes\": 40267,\n    \"JJ\": 40268,\n    \"Ġlick\": 40269,\n    \"Tyler\": 40270,\n    \"cius\": 40271,\n    \"lishing\": 40272,\n    \"ocl\": 40273,\n    \"Ġassoci\": 40274,\n    \"ensitivity\": 40275,\n    \"entanyl\": 40276,\n    \"Rum\": 40277,\n    \"Ġ443\": 40278,\n    \"onding\": 40279,\n    \"Ġpedals\": 40280,\n    \"ĠPsychological\": 40281,\n    \"Ġthro\": 40282,\n    \"Network\": 40283,\n    \"591\": 40284,\n    \"Pick\": 40285,\n    \"Ġchords\": 40286,\n    \"ĠHound\": 40287,\n    \"entials\": 40288,\n    \"faces\": 40289,\n    \"ĠYin\": 40290,\n    \"ugi\": 40291,\n    \"bows\": 40292,\n    \"ĠForms\": 40293,\n    \"886\": 40294,\n    \"Ox\": 40295,\n    \"Ġ351\": 40296,\n    \"Ġmating\": 40297,\n    \"Ġchirop\": 40298,\n    \"916\": 40299,\n    \"Ġexpend\": 40300,\n    \"Ġusefulness\": 40301,\n    \"Marvel\": 40302,\n    \"ĠStretch\": 40303,\n    \"omez\": 40304,\n    \"ĠJS\": 40305,\n    \"Hal\": 40306,\n    \"fle\": 40307,\n    \"ĠCountdown\": 40308,\n    \"ĠLH\": 40309,\n    \"assian\": 40310,\n    \"vd\": 40311,\n    \"ĠTranscript\": 40312,\n    \"ĠExtrem\": 40313,\n    \"idine\": 40314,\n    \"ustainable\": 40315,\n    \"ederal\": 40316,\n    \"ĠOwl\": 40317,\n    \"Ġcreed\": 40318,\n    \"ĠGrateful\": 40319,\n    \"Ġprenatal\": 40320,\n    \"________________________________\": 40321,\n    \"ĠElements\": 40322,\n    \"âĢ¦)\": 40323,\n    \"nesia\": 40324,\n    \"ARGET\": 40325,\n    \"Ġboredom\": 40326,\n    \"Ġdepictions\": 40327,\n    \"verbal\": 40328,\n    \"ĠeSports\": 40329,\n    \"Laura\": 40330,\n    \"ilage\": 40331,\n    \"ĠGalactic\": 40332,\n    \"Investigators\": 40333,\n    \"Ġscattering\": 40334,\n    \"instein\": 40335,\n    \"ĠExperiment\": 40336,\n    \"ĠRecre\": 40337,\n    \"Ġregul\": 40338,\n    \"Ġrelent\": 40339,\n    \"STE\": 40340,\n    \"Ġslicing\": 40341,\n    \"igans\": 40342,\n    \"raped\": 40343,\n    \"ĠDeter\": 40344,\n    \"Ġsmoker\": 40345,\n    \"ĠWikimedia\": 40346,\n    \"pages\": 40347,\n    \"Ted\": 40348,\n    \"713\": 40349,\n    \"Ġpuberty\": 40350,\n    \"Ġhars\": 40351,\n    \"ĠStarter\": 40352,\n    \"patch\": 40353,\n    \"leeve\": 40354,\n    \"Ġ346\": 40355,\n    \"ĠAccessories\": 40356,\n    \"ventions\": 40357,\n    \"ĠSTAND\": 40358,\n    \"ĠUrug\": 40359,\n    \"ĠOccupy\": 40360,\n    \"Ġbinds\": 40361,\n    \"ĠBubble\": 40362,\n    \"Ġincorporation\": 40363,\n    \"Ġstereotypical\": 40364,\n    \"Ġgor\": 40365,\n    \"987\": 40366,\n    \"Ġevils\": 40367,\n    \"tower\": 40368,\n    \"Ġastronomer\": 40369,\n    \"Ble\": 40370,\n    \"ĠNid\": 40371,\n    \"ĠWidow\": 40372,\n    \"Ġpaw\": 40373,\n    \"Ġinnoc\": 40374,\n    \"ĠOWN\": 40375,\n    \"Ġtofu\": 40376,\n    \"drops\": 40377,\n    \"ĠEval\": 40378,\n    \"693\": 40379,\n    \"Collins\": 40380,\n    \"penter\": 40381,\n    \"ĠNib\": 40382,\n    \"Ġsmokes\": 40383,\n    \"Ġ1850\": 40384,\n    \"Ġtechno\": 40385,\n    \"oooo\": 40386,\n    \"ĠUnic\": 40387,\n    \"ĠKirin\": 40388,\n    \"\\\":[\\\"\": 40389,\n    \"Ġincrements\": 40390,\n    \"989\": 40391,\n    \"oodoo\": 40392,\n    \"ĠCyborg\": 40393,\n    \"Ġcures\": 40394,\n    \"ĠOW\": 40395,\n    \"ĠAnnex\": 40396,\n    \"behavior\": 40397,\n    \"/-\": 40398,\n    \"Ġbuggy\": 40399,\n    \"onent\": 40400,\n    \"Bey\": 40401,\n    \"Ġsummarize\": 40402,\n    \"putable\": 40403,\n    \"Ġfri\": 40404,\n    \"Gi\": 40405,\n    \"urances\": 40406,\n    \"ĠAppalach\": 40407,\n    \"Ġhegemony\": 40408,\n    \"ĠOrigins\": 40409,\n    \"Ġconnectors\": 40410,\n    \"ĠAST\": 40411,\n    \"object\": 40412,\n    \"ĠSlay\": 40413,\n    \"Arm\": 40414,\n    \"oston\": 40415,\n    \"ĠEVEN\": 40416,\n    \"Ġprophecy\": 40417,\n    \"Bright\": 40418,\n    \"ĠVector\": 40419,\n    \"Marg\": 40420,\n    \"omical\": 40421,\n    \"Holy\": 40422,\n    \"ĠRPM\": 40423,\n    \"ĠReceiver\": 40424,\n    \"Ġtracts\": 40425,\n    \"boss\": 40426,\n    \"Ġblurry\": 40427,\n    \"aspx\": 40428,\n    \"DES\": 40429,\n    \"Ġcess\": 40430,\n    \"ĠAster\": 40431,\n    \"anything\": 40432,\n    \"levard\": 40433,\n    \"unciation\": 40434,\n    \"jong\": 40435,\n    \"Ġiv\": 40436,\n    \"Common\": 40437,\n    \"ĠDistance\": 40438,\n    \"imus\": 40439,\n    \"outheast\": 40440,\n    \"Ġcir\": 40441,\n    \"ĠCato\": 40442,\n    \"Ġinscribed\": 40443,\n    \"ersed\": 40444,\n    \"Ġanarchy\": 40445,\n    \"Ġplagiar\": 40446,\n    \"Ġthug\": 40447,\n    \"Actor\": 40448,\n    \"ĠTant\": 40449,\n    \"Researchers\": 40450,\n    \"remember\": 40451,\n    \"Ġitch\": 40452,\n    \"Ġrefill\": 40453,\n    \"Ġsucker\": 40454,\n    \"ĠWANT\": 40455,\n    \"RAG\": 40456,\n    \"rencies\": 40457,\n    \"ĠTape\": 40458,\n    \"Ġattaches\": 40459,\n    \"nb\": 40460,\n    \"Tan\": 40461,\n    \"Ġappend\": 40462,\n    \"Ġalas\": 40463,\n    \"951\": 40464,\n    \"panel\": 40465,\n    \"Climate\": 40466,\n    \"icrobial\": 40467,\n    \"Brandon\": 40468,\n    \"ĠFreud\": 40469,\n    \"Ġfungi\": 40470,\n    \"Ġcommenters\": 40471,\n    \"ĠDelicious\": 40472,\n    \"Ġhitherto\": 40473,\n    \"conv\": 40474,\n    \"Ġchemist\": 40475,\n    \"Ġdenominations\": 40476,\n    \"ĠBehavior\": 40477,\n    \"comed\": 40478,\n    \"ĠLantern\": 40479,\n    \"ĠFloating\": 40480,\n    \"magic\": 40481,\n    \"ĠBarbar\": 40482,\n    \"bender\": 40483,\n    \"iliar\": 40484,\n    \"unny\": 40485,\n    \"Ġretracted\": 40486,\n    \"atars\": 40487,\n    \"ĠLovely\": 40488,\n    \"Ġinfinitely\": 40489,\n    \"Ġhumili\": 40490,\n    \"Ġinterestingly\": 40491,\n    \"Ġmunicip\": 40492,\n    \"ĠPanic\": 40493,\n    \"Ġcomprehension\": 40494,\n    \"ĠMassacre\": 40495,\n    \"Ġpersuasion\": 40496,\n    \"enf\": 40497,\n    \"Ġcoded\": 40498,\n    \"higher\": 40499,\n    \"chart\": 40500,\n    \"umbered\": 40501,\n    \"ĠIndigo\": 40502,\n    \"Ġthinker\": 40503,\n    \"Ġgoof\": 40504,\n    \"ĠPetition\": 40505,\n    \"fascist\": 40506,\n    \"absor\": 40507,\n    \"Ġassay\": 40508,\n    \"ĠClassification\": 40509,\n    \"Ġhalluc\": 40510,\n    \"speech\": 40511,\n    \"issues\": 40512,\n    \"Ġinexper\": 40513,\n    \"ĠLibre\": 40514,\n    \"Ġsling\": 40515,\n    \"zech\": 40516,\n    \"Ġpouch\": 40517,\n    \"ĠOffense\": 40518,\n    \"ĠHF\": 40519,\n    \"Fight\": 40520,\n    \"026\": 40521,\n    \"ĠTrident\": 40522,\n    \"fm\": 40523,\n    \"Ġintox\": 40524,\n    \"Ġ465\": 40525,\n    \"colonial\": 40526,\n    \"ovies\": 40527,\n    \"794\": 40528,\n    \"Techn\": 40529,\n    \"undreds\": 40530,\n    \"Ġchildish\": 40531,\n    \"arenthood\": 40532,\n    \"ĠShade\": 40533,\n    \"Host\": 40534,\n    \"Ġdirectional\": 40535,\n    \"reader\": 40536,\n    \"rimp\": 40537,\n    \"ĠEater\": 40538,\n    \"prep\": 40539,\n    \"Ġmeas\": 40540,\n    \"Ġlatch\": 40541,\n    \"inant\": 40542,\n    \"nels\": 40543,\n    \"finished\": 40544,\n    \"application\": 40545,\n    \"Board\": 40546,\n    \"Ġfiller\": 40547,\n    \"ivably\": 40548,\n    \"CAST\": 40549,\n    \"Ġstereotyp\": 40550,\n    \"Ġwarranties\": 40551,\n    \"ĠProbe\": 40552,\n    \"Ġspontaneously\": 40553,\n    \"Ġtropes\": 40554,\n    \"Meg\": 40555,\n    \"ĠHandling\": 40556,\n    \"hemer\": 40557,\n    \"986\": 40558,\n    \"ĠSly\": 40559,\n    \"plates\": 40560,\n    \"Ġmolten\": 40561,\n    \"ĠHIT\": 40562,\n    \"strings\": 40563,\n    \"Ġcentrif\": 40564,\n    \"ĠENG\": 40565,\n    \"Indeed\": 40566,\n    \"Ġ429\": 40567,\n    \"Ġsly\": 40568,\n    \"Ġ490\": 40569,\n    \"Ġhordes\": 40570,\n    \"boot\": 40571,\n    \"691\": 40572,\n    \"ihara\": 40573,\n    \"Ġsubversive\": 40574,\n    \"Russell\": 40575,\n    \"aceous\": 40576,\n    \"wk\": 40577,\n    \"Ġreverence\": 40578,\n    \"Ġingenious\": 40579,\n    \"holiday\": 40580,\n    \"eligible\": 40581,\n    \"ĠTactical\": 40582,\n    \"978\": 40583,\n    \"herence\": 40584,\n    \"Ġgimm\": 40585,\n    \"Ġarchaic\": 40586,\n    \"Ġadam\": 40587,\n    \"Ġ297\": 40588,\n    \"Father\": 40589,\n    \"ĠLerner\": 40590,\n    \"Ġhesitated\": 40591,\n    \"Safety\": 40592,\n    \"Ġawakened\": 40593,\n    \"ueller\": 40594,\n    \"Ġextrater\": 40595,\n    \"Ġmummy\": 40596,\n    \"ĠBuddhism\": 40597,\n    \"Ġ359\": 40598,\n    \"Ġlegions\": 40599,\n    \"Ġprehistoric\": 40600,\n    \"ancouver\": 40601,\n    \"Ġmelancholy\": 40602,\n    \"ĠEnemy\": 40603,\n    \"ĠSyl\": 40604,\n    \"ĠRobo\": 40605,\n    \"verting\": 40606,\n    \"ĠBullets\": 40607,\n    \"essler\": 40608,\n    \"Ġmarvelous\": 40609,\n    \"ĠBened\": 40610,\n    \"Ġsavior\": 40611,\n    \"omever\": 40612,\n    \"Bee\": 40613,\n    \"Ġrapp\": 40614,\n    \"Ġpredomin\": 40615,\n    \"ĠScripture\": 40616,\n    \"Ġsnapshots\": 40617,\n    \"Ġunrem\": 40618,\n    \"Ġsquid\": 40619,\n    \"ĠBuddh\": 40620,\n    \"ĠSantorum\": 40621,\n    \"Internet\": 40622,\n    \"avoid\": 40623,\n    \"Ġunamb\": 40624,\n    \"Ġ296\": 40625,\n    \"Ġnexus\": 40626,\n    \"Ġinterchangeable\": 40627,\n    \"ockets\": 40628,\n    \"Ġfoll\": 40629,\n    \"ĠOPT\": 40630,\n    \"023\": 40631,\n    \"Â²\": 40632,\n    \"Ġhereditary\": 40633,\n    \"Ġvape\": 40634,\n    \"=\\\"\": 40635,\n    \"1996\": 40636,\n    \"Ø³\": 40637,\n    \"Emergency\": 40638,\n    \"Ġneb\": 40639,\n    \"Ġisot\": 40640,\n    \"Ġdiam\": 40641,\n    \"stairs\": 40642,\n    \"ĠAppendix\": 40643,\n    \"venient\": 40644,\n    \"Ġinvol\": 40645,\n    \"Ġtheorist\": 40646,\n    \"Ġconqu\": 40647,\n    \"Mich\": 40648,\n    \"ĠSort\": 40649,\n    \"antasy\": 40650,\n    \"dating\": 40651,\n    \"771\": 40652,\n    \"Ġape\": 40653,\n    \"Ġindemn\": 40654,\n    \"ween\": 40655,\n    \"Games\": 40656,\n    \"ascal\": 40657,\n    \"Muslims\": 40658,\n    \"Ġleaflets\": 40659,\n    \"Ġtraverse\": 40660,\n    \"Ġtransgress\": 40661,\n    \"Ġflushed\": 40662,\n    \"893\": 40663,\n    \"lasses\": 40664,\n    \"obos\": 40665,\n    \"ooming\": 40666,\n    \"Ġtou\": 40667,\n    \"mast\": 40668,\n    \"âģ\": 40669,\n    \"751\": 40670,\n    \"Either\": 40671,\n    \"Ġgrate\": 40672,\n    \"urgy\": 40673,\n    \"Ġendowed\": 40674,\n    \"ĠRasm\": 40675,\n    \"Nat\": 40676,\n    \"odka\": 40677,\n    \"olon\": 40678,\n    \"iants\": 40679,\n    \"Ġsensations\": 40680,\n    \"Ġsituational\": 40681,\n    \"pox\": 40682,\n    \"Figure\": 40683,\n    \"Ġslime\": 40684,\n    \"Ġ421\": 40685,\n    \"ollow\": 40686,\n    \"Ġanesthesia\": 40687,\n    \"adult\": 40688,\n    \"ĠPiece\": 40689,\n    \"994\": 40690,\n    \"ĠAnalog\": 40691,\n    \"Iv\": 40692,\n    \"flo\": 40693,\n    \"Ġdomest\": 40694,\n    \"Ġcabal\": 40695,\n    \"Ġgarg\": 40696,\n    \"Ġrabb\": 40697,\n    \"REC\": 40698,\n    \"ISTORY\": 40699,\n    \"Friend\": 40700,\n    \"Ġancestor\": 40701,\n    \"ĠLets\": 40702,\n    \"Ġelf\": 40703,\n    \"Ġlobb\": 40704,\n    \"ĠAdren\": 40705,\n    \"silver\": 40706,\n    \"astical\": 40707,\n    \"Ġstitch\": 40708,\n    \"028\": 40709,\n    \"Hug\": 40710,\n    \"Ġmoss\": 40711,\n    \"ompl\": 40712,\n    \"Ġunob\": 40713,\n    \"883\": 40714,\n    \"Ġcortex\": 40715,\n    \"olutely\": 40716,\n    \"052\": 40717,\n    \"Seattle\": 40718,\n    \"restling\": 40719,\n    \"endment\": 40720,\n    \"Ġ366\": 40721,\n    \"ventus\": 40722,\n    \"ĠRated\": 40723,\n    \"ĠClever\": 40724,\n    \"Ġcloak\": 40725,\n    \"phrase\": 40726,\n    \"flake\": 40727,\n    \"Ġphilosophies\": 40728,\n    \"784\": 40729,\n    \"Ġskulls\": 40730,\n    \"wake\": 40731,\n    \"oru\": 40732,\n    \"ĠACTION\": 40733,\n    \"Ġcomprom\": 40734,\n    \"ĠManufacturer\": 40735,\n    \"ĠImprove\": 40736,\n    \"Ns\": 40737,\n    \"ĠRevenge\": 40738,\n    \"lords\": 40739,\n    \"Ġ417\": 40740,\n    \"iddles\": 40741,\n    \"Ġcondesc\": 40742,\n    \"tiny\": 40743,\n    \"Ġchloride\": 40744,\n    \"greg\": 40745,\n    \"ĠREST\": 40746,\n    \"subject\": 40747,\n    \"Ġundes\": 40748,\n    \"ftime\": 40749,\n    \"Ġbottleneck\": 40750,\n    \"ĠZombie\": 40751,\n    \"Ġhabitable\": 40752,\n    \"Ġcigars\": 40753,\n    \"Ġenlarg\": 40754,\n    \"icester\": 40755,\n    \"ðĿ\": 40756,\n    \"regulation\": 40757,\n    \"arters\": 40758,\n    \"Ġformulations\": 40759,\n    \"Ġadhesive\": 40760,\n    \"Ġ344\": 40761,\n    \"pod\": 40762,\n    \"etitive\": 40763,\n    \"Ġcontinuum\": 40764,\n    \"aghd\": 40765,\n    \"Ġ701\": 40766,\n    \"Ġdisband\": 40767,\n    \"Tu\": 40768,\n    \"Ġcivilisation\": 40769,\n    \"ĠPCI\": 40770,\n    \"Ġcrooked\": 40771,\n    \"ammy\": 40772,\n    \"Ġbrim\": 40773,\n    \"Jr\": 40774,\n    \"ĠBunker\": 40775,\n    \"plot\": 40776,\n    \"Ġwielded\": 40777,\n    \"Ġcaricature\": 40778,\n    \"ĠInfinite\": 40779,\n    \"piracy\": 40780,\n    \"aretz\": 40781,\n    \"Ġstares\": 40782,\n    \"incinnati\": 40783,\n    \"agents\": 40784,\n    \"ĠObamaCare\": 40785,\n    \"asuring\": 40786,\n    \"ansion\": 40787,\n    \"Ġastonished\": 40788,\n    \"iovascular\": 40789,\n    \"Bio\": 40790,\n    \"Ġadvisable\": 40791,\n    \"Ġsender\": 40792,\n    \"887\": 40793,\n    \"Led\": 40794,\n    \"DN\": 40795,\n    \"Ġaggregation\": 40796,\n    \"ĠInnocent\": 40797,\n    \"ĠTransactions\": 40798,\n    \"worms\": 40799,\n    \"ĠWorm\": 40800,\n    \"Ġ363\": 40801,\n    \"ĠBiblical\": 40802,\n    \"rared\": 40803,\n    \"Ġgazing\": 40804,\n    \"chant\": 40805,\n    \"Ġsubordinates\": 40806,\n    \"1600\": 40807,\n    \"actually\": 40808,\n    \"olition\": 40809,\n    \"ĠRTX\": 40810,\n    \"ĠPyramid\": 40811,\n    \"alph\": 40812,\n    \"ĠFPS\": 40813,\n    \"Ġerrone\": 40814,\n    \"ĠLR\": 40815,\n    \"Scientists\": 40816,\n    \"Ġincons\": 40817,\n    \"Ġbrittle\": 40818,\n    \"027\": 40819,\n    \"ĠBowser\": 40820,\n    \"Rub\": 40821,\n    \"links\": 40822,\n    \"ĠWik\": 40823,\n    \"ussion\": 40824,\n    \"Marsh\": 40825,\n    \"resents\": 40826,\n    \"Clean\": 40827,\n    \"Ġbrute\": 40828,\n    \"ĠInventory\": 40829,\n    \"1100\": 40830,\n    \"ĠATK\": 40831,\n    \"793\": 40832,\n    \"Ġcaveats\": 40833,\n    \"ĠKnot\": 40834,\n    \"IRT\": 40835,\n    \"ĠCanad\": 40836,\n    \"isma\": 40837,\n    \"entin\": 40838,\n    \"Own\": 40839,\n    \"Ġ455\": 40840,\n    \"Ġlesions\": 40841,\n    \"ĠAres\": 40842,\n    \"ĠKali\": 40843,\n    \"Ġpaws\": 40844,\n    \"Auto\": 40845,\n    \"Ġdiscrim\": 40846,\n    \"044\": 40847,\n    \"ĠCOUN\": 40848,\n    \"Ġ1905\": 40849,\n    \"Ġexperien\": 40850,\n    \"Ġ406\": 40851,\n    \"achelor\": 40852,\n    \"Ġscarcely\": 40853,\n    \"Ġsynchronized\": 40854,\n    \"Rat\": 40855,\n    \"Blake\": 40856,\n    \"Ġrewriting\": 40857,\n    \"Ġcannons\": 40858,\n    \"stem\": 40859,\n    \"Apparently\": 40860,\n    \"Ġleveling\": 40861,\n    \"?]\": 40862,\n    \"Ġfins\": 40863,\n    \"ĠTone\": 40864,\n    \"ogether\": 40865,\n    \"Sound\": 40866,\n    \"Ġmicrosc\": 40867,\n    \"ĠAsylum\": 40868,\n    \"Ġindividuality\": 40869,\n    \"Ġ432\": 40870,\n    \"lease\": 40871,\n    \"Chuck\": 40872,\n    \"Ġhating\": 40873,\n    \"Ġleftists\": 40874,\n    \"ĠPersonality\": 40875,\n    \"ĠBundle\": 40876,\n    \"Dutch\": 40877,\n    \"Ġtransformer\": 40878,\n    \"iami\": 40879,\n    \"ĠTradition\": 40880,\n    \"ĠRecipes\": 40881,\n    \"Ġdiscour\": 40882,\n    \"Viol\": 40883,\n    \"Ext\": 40884,\n    \"ĠOliv\": 40885,\n    \"ashington\": 40886,\n    \"Ġmillennia\": 40887,\n    \"Ġpsychiatrists\": 40888,\n    \"ĠTrilogy\": 40889,\n    \"inction\": 40890,\n    \"Ġdisliked\": 40891,\n    \"088\": 40892,\n    \"954\": 40893,\n    \"Ġoverloaded\": 40894,\n    \"Ġopium\": 40895,\n    \"acus\": 40896,\n    \"resources\": 40897,\n    \"mud\": 40898,\n    \"ometry\": 40899,\n    \"Hit\": 40900,\n    \"Ġguild\": 40901,\n    \"Ġabyss\": 40902,\n    \"884\": 40903,\n    \"ensity\": 40904,\n    \"ĠDifference\": 40905,\n    \"Electric\": 40906,\n    \"authent\": 40907,\n    \"Ġdownloadable\": 40908,\n    \"ellar\": 40909,\n    \"ĠSavior\": 40910,\n    \"ĠFRI\": 40911,\n    \"Ġ445\": 40912,\n    \"Ġincidental\": 40913,\n    \"Ġanalogue\": 40914,\n    \"ounters\": 40915,\n    \"ĠBuilder\": 40916,\n    \"Ġnarration\": 40917,\n    \"ategor\": 40918,\n    \"raise\": 40919,\n    \"Ġindoctr\": 40920,\n    \"Aren\": 40921,\n    \"Ġbaptism\": 40922,\n    \"Ġobe\": 40923,\n    \"Ġtubing\": 40924,\n    \"apsed\": 40925,\n    \"Fortunately\": 40926,\n    \"gered\": 40927,\n    \"Pict\": 40928,\n    \"Ġmastering\": 40929,\n    \"ĠHIM\": 40930,\n    \"ĠObesity\": 40931,\n    \"Ġornament\": 40932,\n    \"advant\": 40933,\n    \"ĠCous\": 40934,\n    \"032\": 40935,\n    \"cells\": 40936,\n    \"Ġpreclude\": 40937,\n    \"Ġanecdote\": 40938,\n    \"Ġpatriarchy\": 40939,\n    \"ĠSending\": 40940,\n    \"Pie\": 40941,\n    \"Ġdepressive\": 40942,\n    \"ĠEnds\": 40943,\n    \"712\": 40944,\n    \"zos\": 40945,\n    \"icka\": 40946,\n    \"Ġ1906\": 40947,\n    \"Anti\": 40948,\n    \"vana\": 40949,\n    \"ĠRestrict\": 40950,\n    \"Ġprotr\": 40951,\n    \"Ġusername\": 40952,\n    \"Ġparach\": 40953,\n    \"1997\": 40954,\n    \"imental\": 40955,\n    \"rower\": 40956,\n    \"carb\": 40957,\n    \"033\": 40958,\n    \"Ġobligatory\": 40959,\n    \"Ġwillful\": 40960,\n    \"Ġsnail\": 40961,\n    \"json\": 40962,\n    \"izarre\": 40963,\n    \"Ġmiscar\": 40964,\n    \"Ġdopamine\": 40965,\n    \"Ð»\": 40966,\n    \"Ġapplic\": 40967,\n    \"Ġnervously\": 40968,\n    \"YY\": 40969,\n    \"alez\": 40970,\n    \"ĠSoviets\": 40971,\n    \"ĠMister\": 40972,\n    \"Ġcrates\": 40973,\n    \"Ġheavenly\": 40974,\n    \"Ġdoct\": 40975,\n    \"048\": 40976,\n    \"Ġ2400\": 40977,\n    \"ivia\": 40978,\n    \"adies\": 40979,\n    \"Phone\": 40980,\n    \"asks\": 40981,\n    \"Ġperenn\": 40982,\n    \"Ġcomposing\": 40983,\n    \"Ġraiding\": 40984,\n    \"requent\": 40985,\n    \"ibli\": 40986,\n    \"ĠFeedback\": 40987,\n    \"cellaneous\": 40988,\n    \"ĠContracts\": 40989,\n    \"ĠCasting\": 40990,\n    \"vim\": 40991,\n    \"Cut\": 40992,\n    \"Ġabbrevi\": 40993,\n    \"Ġintest\": 40994,\n    \"ricted\": 40995,\n    \"969\": 40996,\n    \"nostic\": 40997,\n    \"Ġinverted\": 40998,\n    \"ĠEG\": 40999,\n    \"aiden\": 41000,\n    \"ĠClaud\": 41001,\n    \"ĠiP\": 41002,\n    \"urized\": 41003,\n    \"Emily\": 41004,\n    \"Ġ353\": 41005,\n    \"Ġ((\": 41006,\n    \"ammad\": 41007,\n    \"Reb\": 41008,\n    \"plom\": 41009,\n    \"YES\": 41010,\n    \"connection\": 41011,\n    \"ĠWra\": 41012,\n    \"ĠMerch\": 41013,\n    \"Ġether\": 41014,\n    \"Elizabeth\": 41015,\n    \"Chip\": 41016,\n    \"relevant\": 41017,\n    \"URA\": 41018,\n    \"Ġantioxidant\": 41019,\n    \"ĠChron\": 41020,\n    \"Ġtheological\": 41021,\n    \"HCR\": 41022,\n    \"ruits\": 41023,\n    \"Body\": 41024,\n    \"enezuel\": 41025,\n    \"Few\": 41026,\n    \"adder\": 41027,\n    \"Ġinducing\": 41028,\n    \"ĠDarth\": 41029,\n    \"Ġimplicitly\": 41030,\n    \"Ġoverfl\": 41031,\n    \"Ġrelics\": 41032,\n    \"Must\": 41033,\n    \"ĠAnswers\": 41034,\n    \"Ġretina\": 41035,\n    \"ĠSlowly\": 41036,\n    \"ĠShib\": 41037,\n    \"software\": 41038,\n    \"Ġ\\\"\\\"\": 41039,\n    \"hack\": 41040,\n    \"Apart\": 41041,\n    \"told\": 41042,\n    \"Ger\": 41043,\n    \"Civil\": 41044,\n    \"problem\": 41045,\n    \"Ġslang\": 41046,\n    \"Ġtactile\": 41047,\n    \"Ġtabl\": 41048,\n    \"ĠAscension\": 41049,\n    \"Ġhumankind\": 41050,\n    \"Howard\": 41051,\n    \"rescent\": 41052,\n    \"ĠReleases\": 41053,\n    \"arijuana\": 41054,\n    \"Christopher\": 41055,\n    \"ĠWarden\": 41056,\n    \"blogspot\": 41057,\n    \"ĠVari\": 41058,\n    \"idency\": 41059,\n    \"ĠHandler\": 41060,\n    \"Round\": 41061,\n    \"MJ\": 41062,\n    \"Ġrhyth\": 41063,\n    \"Tai\": 41064,\n    \"terson\": 41065,\n    \"Ġ,\\\"\": 41066,\n    \"portation\": 41067,\n    \"ĠOrbital\": 41068,\n    \"Ġfantas\": 41069,\n    \"Ġattribut\": 41070,\n    \"Ġdiagram\": 41071,\n    \"atech\": 41072,\n    \"1992\": 41073,\n    \"ibl\": 41074,\n    \"Woman\": 41075,\n    \"ternally\": 41076,\n    \"Days\": 41077,\n    \"Ġdebunk\": 41078,\n    \"ĠPhant\": 41079,\n    \"ĠOath\": 41080,\n    \"sharp\": 41081,\n    \"Ġclaws\": 41082,\n    \"Lots\": 41083,\n    \"Incre\": 41084,\n    \"Aff\": 41085,\n    \"hooting\": 41086,\n    \"rect\": 41087,\n    \"Ġaltru\": 41088,\n    \"Ġwors\": 41089,\n    \"Ġtho\": 41090,\n    \"Ġ349\": 41091,\n    \"clusions\": 41092,\n    \"Ġpseudonym\": 41093,\n    \"Bec\": 41094,\n    \"Ġphosphorus\": 41095,\n    \"ivic\": 41096,\n    \"Ġ348\": 41097,\n    \"otent\": 41098,\n    \"Ġub\": 41099,\n    \"Ġcoales\": 41100,\n    \"regate\": 41101,\n    \"Ġ1870\": 41102,\n    \"Ġglide\": 41103,\n    \"treated\": 41104,\n    \"ĠSymb\": 41105,\n    \"Ġenchant\": 41106,\n    \"Besides\": 41107,\n    \"stocks\": 41108,\n    \"Ġ388\": 41109,\n    \"--------------\": 41110,\n    \"interpret\": 41111,\n    \"ouple\": 41112,\n    \"Ġdrawback\": 41113,\n    \"ĠRevised\": 41114,\n    \"Ġanat\": 41115,\n    \"Ġpsychosis\": 41116,\n    \"Ø¨\": 41117,\n    \"Ġdiffuse\": 41118,\n    \"Ġaffidav\": 41119,\n    \"elve\": 41120,\n    \"amination\": 41121,\n    \"ĠTackle\": 41122,\n    \"hunter\": 41123,\n    \"env\": 41124,\n    \"Ġchests\": 41125,\n    \"Ġsubter\": 41126,\n    \"Ġconquest\": 41127,\n    \"Ġfidelity\": 41128,\n    \"Ġinfringing\": 41129,\n    \"opathic\": 41130,\n    \"ĠGrip\": 41131,\n    \"ĠKeyboard\": 41132,\n    \"Ġobjectionable\": 41133,\n    \"Ġmetabol\": 41134,\n    \"ĠGÃ¶\": 41135,\n    \"Room\": 41136,\n    \"...)\": 41137,\n    \"KEN\": 41138,\n    \"assic\": 41139,\n    \"Ġgeop\": 41140,\n    \"Tro\": 41141,\n    \"Ġcursing\": 41142,\n    \"Ġdile\": 41143,\n    \"Ġultraviolet\": 41144,\n    \"inarily\": 41145,\n    \"Ġdistilled\": 41146,\n    \"sect\": 41147,\n    \"ĠShooter\": 41148,\n    \"uckles\": 41149,\n    \"Ġdistortions\": 41150,\n    \"Map\": 41151,\n    \"Doctor\": 41152,\n    \"Ġinstalls\": 41153,\n    \"oire\": 41154,\n    \"Ġstarch\": 41155,\n    \"ociation\": 41156,\n    \"Lev\": 41157,\n    \"Ġscripture\": 41158,\n    \"Ġsalient\": 41159,\n    \"ilitating\": 41160,\n    \"wb\": 41161,\n    \"ĠSov\": 41162,\n    \"ĠDamn\": 41163,\n    \"Grey\": 41164,\n    \"Ġ980\": 41165,\n    \"Ġjung\": 41166,\n    \"Ġlicking\": 41167,\n    \"029\": 41168,\n    \"ĠDian\": 41169,\n    \"ĠBabylon\": 41170,\n    \"Ðº\": 41171,\n    \"ĠRomantic\": 41172,\n    \"Ġguesses\": 41173,\n    \"ĠFren\": 41174,\n    \"Generally\": 41175,\n    \"ultural\": 41176,\n    \"istence\": 41177,\n    \"Ġiniti\": 41178,\n    \"Ġ341\": 41179,\n    \"ĠSlave\": 41180,\n    \"ultan\": 41181,\n    \"ĠTrash\": 41182,\n    \"ĠEmpty\": 41183,\n    \"ĠHundred\": 41184,\n    \"ĠDirective\": 41185,\n    \"Anderson\": 41186,\n    \"Advertisement\": 41187,\n    \"RH\": 41188,\n    \"ĠOo\": 41189,\n    \"ĠHik\": 41190,\n    \"peg\": 41191,\n    \"Sup\": 41192,\n    \"ĠXT\": 41193,\n    \"Ġencrypt\": 41194,\n    \"selage\": 41195,\n    \"ĠThrone\": 41196,\n    \"Ġconsecut\": 41197,\n    \"Li\": 41198,\n    \"ĠVirus\": 41199,\n    \"ĠCookies\": 41200,\n    \"SHIP\": 41201,\n    \"Ġflavorful\": 41202,\n    \"odynamics\": 41203,\n    \"animal\": 41204,\n    \"spread\": 41205,\n    \"ĠIPCC\": 41206,\n    \"jobs\": 41207,\n    \"ernand\": 41208,\n    \"ĠHaunted\": 41209,\n    \"Ġintolerable\": 41210,\n    \"ĠLAR\": 41211,\n    \"ixtape\": 41212,\n    \"Ġneur\": 41213,\n    \"Ġcausal\": 41214,\n    \"ĠPsychiatry\": 41215,\n    \"ĠVim\": 41216,\n    \"Ġgenomic\": 41217,\n    \"duration\": 41218,\n    \"ĠUsername\": 41219,\n    \"ategy\": 41220,\n    \"Ġunic\": 41221,\n    \"ĠKILL\": 41222,\n    \"blooded\": 41223,\n    \"Ġcaucuses\": 41224,\n    \"ĠPOLITICO\": 41225,\n    \"Spanish\": 41226,\n    \"Ġobedience\": 41227,\n    \"Ġinconven\": 41228,\n    \"MAT\": 41229,\n    \"Ġbends\": 41230,\n    \"ĠImprovements\": 41231,\n    \"Ġrelig\": 41232,\n    \"ĠForth\": 41233,\n    \"ĠLumia\": 41234,\n    \"uces\": 41235,\n    \"Ġunim\": 41236,\n    \"ĠStatistical\": 41237,\n    \"kb\": 41238,\n    \"auntlet\": 41239,\n    \"ĠDisco\": 41240,\n    \"ĠInstruction\": 41241,\n    \"ooo\": 41242,\n    \"ĠDictionary\": 41243,\n    \"culated\": 41244,\n    \"Adv\": 41245,\n    \"ĠAvatar\": 41246,\n    \"ictional\": 41247,\n    \"Ġcentr\": 41248,\n    \"ifles\": 41249,\n    \"orks\": 41250,\n    \"skill\": 41251,\n    \"Ġlatex\": 41252,\n    \"ĠPagan\": 41253,\n    \"Ġdevast\": 41254,\n    \"Ġprol\": 41255,\n    \"896\": 41256,\n    \"Product\": 41257,\n    \"968\": 41258,\n    \"Ġfrench\": 41259,\n    \"083\": 41260,\n    \"ĠCluster\": 41261,\n    \"cloth\": 41262,\n    \"ĠFilter\": 41263,\n    \"ĠDisorders\": 41264,\n    \"etimes\": 41265,\n    \"Ġinstinctively\": 41266,\n    \"ĠBritann\": 41267,\n    \"Ġaft\": 41268,\n    \"ĠVict\": 41269,\n    \"Ġâĺħ\": 41270,\n    \"Ġperverse\": 41271,\n    \"Ġcontraceptives\": 41272,\n    \"ĠHannibal\": 41273,\n    \"escap\": 41274,\n    \"ĠApostle\": 41275,\n    \"ĠXiao\": 41276,\n    \"ĠMagnum\": 41277,\n    \"Ġphosphate\": 41278,\n    \"Ġ399\": 41279,\n    \"utable\": 41280,\n    \"Ġsten\": 41281,\n    \"Ġwearer\": 41282,\n    \"Ġsmug\": 41283,\n    \"ĠInfluence\": 41284,\n    \"Ġ384\": 41285,\n    \"Truth\": 41286,\n    \"struction\": 41287,\n    \"Ġmaniac\": 41288,\n    \"ĠMagnetic\": 41289,\n    \"ousands\": 41290,\n    \"Ġsemen\": 41291,\n    \"dir\": 41292,\n    \"ĠTornado\": 41293,\n    \"Ġexplos\": 41294,\n    \"1995\": 41295,\n    \"Xi\": 41296,\n    \"Steel\": 41297,\n    \"057\": 41298,\n    \"Barn\": 41299,\n    \"Fan\": 41300,\n    \"ĠChatt\": 41301,\n    \"Chem\": 41302,\n    \"ĠFold\": 41303,\n    \"bees\": 41304,\n    \"1080\": 41305,\n    \"ĠMaze\": 41306,\n    \"ierre\": 41307,\n    \"oeuv\": 41308,\n    \"Cand\": 41309,\n    \"odium\": 41310,\n    \"mmm\": 41311,\n    \"ereo\": 41312,\n    \"Ġreactionary\": 41313,\n    \"Ġacidic\": 41314,\n    \"ĠRemoval\": 41315,\n    \"Ġnont\": 41316,\n    \"031\": 41317,\n    \"ĠTerminator\": 41318,\n    \"ĠVendor\": 41319,\n    \"enemy\": 41320,\n    \"Ġreconstructed\": 41321,\n    \"ĠGalileo\": 41322,\n    \"Ġtesters\": 41323,\n    \"albeit\": 41324,\n    \"uminium\": 41325,\n    \"Ġrite\": 41326,\n    \"ĠInput\": 41327,\n    \"committee\": 41328,\n    \"Ġjour\": 41329,\n    \"gements\": 41330,\n    \"Ġgerm\": 41331,\n    \"Dick\": 41332,\n    \"ĠRequirements\": 41333,\n    \"omsday\": 41334,\n    \"Î\": 41335,\n    \"ISSION\": 41336,\n    \"Ġmolded\": 41337,\n    \"Ġrye\": 41338,\n    \"Attorney\": 41339,\n    \"population\": 41340,\n    \"Ġrepet\": 41341,\n    \"Sync\": 41342,\n    \"breaks\": 41343,\n    \"Ġbanished\": 41344,\n    \"Ġraspberry\": 41345,\n    \"Ġammo\": 41346,\n    \"Ġorthodox\": 41347,\n    \"Ġwebcam\": 41348,\n    \"ĠAsc\": 41349,\n    \"vl\": 41350,\n    \"1989\": 41351,\n    \"Ġdiscipl\": 41352,\n    \"Ġmoreover\": 41353,\n    \"Ġexplodes\": 41354,\n    \"1960\": 41355,\n    \"Ġpropositions\": 41356,\n    \"Protect\": 41357,\n    \"Ġsexes\": 41358,\n    \"physical\": 41359,\n    \"ĠAthena\": 41360,\n    \"ocent\": 41361,\n    \"ĠGothic\": 41362,\n    \"ĠRacial\": 41363,\n    \"istani\": 41364,\n    \"Ġhelium\": 41365,\n    \"ĠPresumably\": 41366,\n    \"Ġperman\": 41367,\n    \"becue\": 41368,\n    \"ĠHW\": 41369,\n    \"rued\": 41370,\n    \"ĠCNS\": 41371,\n    \"DEP\": 41372,\n    \"ĠManifest\": 41373,\n    \"2500\": 41374,\n    \"ĠMyst\": 41375,\n    \"Economic\": 41376,\n    \"Prot\": 41377,\n    \"Ġledge\": 41378,\n    \"Ġimitate\": 41379,\n    \"ĠTotally\": 41380,\n    \"ĠBeaut\": 41381,\n    \"OIL\": 41382,\n    \"Ġ1440\": 41383,\n    \"Moscow\": 41384,\n    \"ĠSets\": 41385,\n    \"merga\": 41386,\n    \"Ġlesbians\": 41387,\n    \"Walker\": 41388,\n    \"Move\": 41389,\n    \"ĠSOM\": 41390,\n    \"ĠPsy\": 41391,\n    \"strument\": 41392,\n    \"Ġiter\": 41393,\n    \"ĠTosh\": 41394,\n    \"oola\": 41395,\n    \"ĠAntiqu\": 41396,\n    \"ĠShining\": 41397,\n    \"Ġobservational\": 41398,\n    \"VW\": 41399,\n    \"rophe\": 41400,\n    \"034\": 41401,\n    \"Ġcontiguous\": 41402,\n    \"Ġstarve\": 41403,\n    \"sure\": 41404,\n    \"Ġnegate\": 41405,\n    \"Ġmindless\": 41406,\n    \"tf\": 41407,\n    \"Ġdownwards\": 41408,\n    \"046\": 41409,\n    \"riors\": 41410,\n    \"Ġreverted\": 41411,\n    \"ĠAthe\": 41412,\n    \"Bra\": 41413,\n    \"eah\": 41414,\n    \"Rachel\": 41415,\n    \"Hung\": 41416,\n    \"Join\": 41417,\n    \"ĠRaces\": 41418,\n    \"Ġmutant\": 41419,\n    \"Ġuncond\": 41420,\n    \"Ġusability\": 41421,\n    \"NESS\": 41422,\n    \"haust\": 41423,\n    \"036\": 41424,\n    \"Ġobscurity\": 41425,\n    \"Ġimperialism\": 41426,\n    \"Ġemitting\": 41427,\n    \"Ġideologically\": 41428,\n    \"ĠIro\": 41429,\n    \"erva\": 41430,\n    \"ĠIzzy\": 41431,\n    \"ĠLevels\": 41432,\n    \"onym\": 41433,\n    \"ĠConspiracy\": 41434,\n    \"ĠSapphire\": 41435,\n    \"Ul\": 41436,\n    \"Ġhuh\": 41437,\n    \"ochem\": 41438,\n    \"Ġbehaves\": 41439,\n    \"ĠMesh\": 41440,\n    \"Ark\": 41441,\n    \"Ġvec\": 41442,\n    \"ĠActions\": 41443,\n    \"Ġdistinguishing\": 41444,\n    \"ĠTsarnaev\": 41445,\n    \"ĠEndurance\": 41446,\n    \"ederation\": 41447,\n    \"itant\": 41448,\n    \"Ġstreetcar\": 41449,\n    \"041\": 41450,\n    \"ĠAval\": 41451,\n    \"ĠCompanion\": 41452,\n    \"ĠCartoon\": 41453,\n    \"Ġcalculus\": 41454,\n    \"993\": 41455,\n    \"eq\": 41456,\n    \"ĠVanilla\": 41457,\n    \"MAC\": 41458,\n    \"wolves\": 41459,\n    \"fg\": 41460,\n    \"Ġfermentation\": 41461,\n    \"Ġinformants\": 41462,\n    \"Ġsudo\": 41463,\n    \"Ġperipher\": 41464,\n    \"Ġindign\": 41465,\n    \"parts\": 41466,\n    \"detail\": 41467,\n    \"femin\": 41468,\n    \"blade\": 41469,\n    \"Ġinserts\": 41470,\n    \"Ġoffsets\": 41471,\n    \"Ġantidepressants\": 41472,\n    \"Ġphr\": 41473,\n    \"Ġresultant\": 41474,\n    \"biology\": 41475,\n    \"Ġacquies\": 41476,\n    \"UFF\": 41477,\n    \"****************\": 41478,\n    \"ĠPenalty\": 41479,\n    \"Ġrever\": 41480,\n    \"heric\": 41481,\n    \"ĠShadows\": 41482,\n    \"command\": 41483,\n    \"Ġreprint\": 41484,\n    \"089\": 41485,\n    \"empty\": 41486,\n    \"ĠTAG\": 41487,\n    \"stim\": 41488,\n    \"FK\": 41489,\n    \"Ġkins\": 41490,\n    \"uggle\": 41491,\n    \"imura\": 41492,\n    \"wit\": 41493,\n    \"Kill\": 41494,\n    \"Beck\": 41495,\n    \"Ocean\": 41496,\n    \"Ġlabyrinth\": 41497,\n    \"ĠNorse\": 41498,\n    \"IENCE\": 41499,\n    \"Ġ+++\": 41500,\n    \"DoS\": 41501,\n    \"gm\": 41502,\n    \"Ġbarbar\": 41503,\n    \"ĠCeres\": 41504,\n    \"Ġhashing\": 41505,\n    \"eworthy\": 41506,\n    \"Ġrecite\": 41507,\n    \"Ġelectrodes\": 41508,\n    \"Ġconformity\": 41509,\n    \"response\": 41510,\n    \"olate\": 41511,\n    \"Ġ357\": 41512,\n    \"Snap\": 41513,\n    \"Crime\": 41514,\n    \"Ġpointer\": 41515,\n    \"ĠTIT\": 41516,\n    \"Ġdistinctions\": 41517,\n    \"Ġ427\": 41518,\n    \"ĠÙĪ\": 41519,\n    \"abases\": 41520,\n    \"Mars\": 41521,\n    \"ĠSpiritual\": 41522,\n    \"Ġimpuls\": 41523,\n    \"Philadelphia\": 41524,\n    \"1994\": 41525,\n    \"Ġcunning\": 41526,\n    \"Ġfram\": 41527,\n    \"Ġinco\": 41528,\n    \"Ġomnip\": 41529,\n    \"imize\": 41530,\n    \"ervative\": 41531,\n    \"Gy\": 41532,\n    \"Drug\": 41533,\n    \"Ġcarniv\": 41534,\n    \"ĠSailor\": 41535,\n    \"download\": 41536,\n    \"ĠBeetle\": 41537,\n    \"ĠEarthqu\": 41538,\n    \"izontal\": 41539,\n    \"Alan\": 41540,\n    \"Nice\": 41541,\n    \"Prior\": 41542,\n    \"MAG\": 41543,\n    \"Ġautobi\": 41544,\n    \"ĠBrill\": 41545,\n    \"Ġpredominant\": 41546,\n    \"ĠMessiah\": 41547,\n    \"REM\": 41548,\n    \"ĠSlip\": 41549,\n    \"ĠWebs\": 41550,\n    \"ademic\": 41551,\n    \"<\": 41552,\n    \"ĠVessel\": 41553,\n    \"vari\": 41554,\n    \"Code\": 41555,\n    \"Ġbeetle\": 41556,\n    \"projects\": 41557,\n    \"BAT\": 41558,\n    \"Ġpsychotic\": 41559,\n    \"Ġunderside\": 41560,\n    \"Ġrefute\": 41561,\n    \"Considering\": 41562,\n    \"kees\": 41563,\n    \"wd\": 41564,\n    \"priority\": 41565,\n    \"Ġtwentieth\": 41566,\n    \"Ġatheist\": 41567,\n    \"amina\": 41568,\n    \"Ġeuphem\": 41569,\n    \"Ġtripod\": 41570,\n    \"ĠTrayvon\": 41571,\n    \"ĠNON\": 41572,\n    \"2200\": 41573,\n    \"ĠNPC\": 41574,\n    \"ependence\": 41575,\n    \"ĠMHz\": 41576,\n    \"ĠBung\": 41577,\n    \"Ġpane\": 41578,\n    \"Ġaboriginal\": 41579,\n    \"ĠPLUS\": 41580,\n    \"igers\": 41581,\n    \"ĠSexy\": 41582,\n    \"MF\": 41583,\n    \"Chall\": 41584,\n    \"Ay\": 41585,\n    \"ilingual\": 41586,\n    \"adj\": 41587,\n    \"Ġfrown\": 41588,\n    \"successful\": 41589,\n    \"stack\": 41590,\n    \"Ġic\": 41591,\n    \"ĠSeah\": 41592,\n    \"Ġconsequ\": 41593,\n    \"bugs\": 41594,\n    \"ĠScand\": 41595,\n    \"ĠCurve\": 41596,\n    \"Nob\": 41597,\n    \"ĠHoo\": 41598,\n    \"ĠKissinger\": 41599,\n    \"ĠTimeline\": 41600,\n    \"Ġmt\": 41601,\n    \"Description\": 41602,\n    \"YP\": 41603,\n    \"ĠInstallation\": 41604,\n    \"levision\": 41605,\n    \"Ġanthropology\": 41606,\n    \"itzerland\": 41607,\n    \"iaries\": 41608,\n    \"kward\": 41609,\n    \"robat\": 41610,\n    \"Ġcarbohydrate\": 41611,\n    \"Phot\": 41612,\n    \"Ð¾Ð\": 41613,\n    \"ĠSQL\": 41614,\n    \"Disc\": 41615,\n    \"Ġdataset\": 41616,\n    \"ynski\": 41617,\n    \"Ġfiat\": 41618,\n    \"ĠDres\": 41619,\n    \"ĠFavor\": 41620,\n    \"ĠHalls\": 41621,\n    \"Alt\": 41622,\n    \"PART\": 41623,\n    \"Spider\": 41624,\n    \"Ġdisabling\": 41625,\n    \"RG\": 41626,\n    \"Ward\": 41627,\n    \"aturation\": 41628,\n    \"Ġwillfully\": 41629,\n    \"Ġlockout\": 41630,\n    \"ĠShutdown\": 41631,\n    \"956\": 41632,\n    \"Ġcommunists\": 41633,\n    \"Against\": 41634,\n    \"Ore\": 41635,\n    \"ĠRik\": 41636,\n    \"ĠASD\": 41637,\n    \"ĠOnion\": 41638,\n    \"Ġparticulars\": 41639,\n    \"Analy\": 41640,\n    \"checked\": 41641,\n    \"selected\": 41642,\n    \"romy\": 41643,\n    \"ĠAkira\": 41644,\n    \"Ġcongr\": 41645,\n    \"Choice\": 41646,\n    \"Ġbos\": 41647,\n    \"organisms\": 41648,\n    \"Ġfrowned\": 41649,\n    \"Tok\": 41650,\n    \"Bir\": 41651,\n    \"ĠScrib\": 41652,\n    \"Ġrealms\": 41653,\n    \"Ġcoercive\": 41654,\n    \"1993\": 41655,\n    \"021\": 41656,\n    \"âĢĵâĢĵ\": 41657,\n    \"athetic\": 41658,\n    \"rior\": 41659,\n    \"Ġfolly\": 41660,\n    \"ĠAMERICA\": 41661,\n    \"Ġcassette\": 41662,\n    \"953\": 41663,\n    \"Ġabsorbs\": 41664,\n    \"043\": 41665,\n    \"quad\": 41666,\n    \"''.\": 41667,\n    \"ĠExtract\": 41668,\n    \"Ġ424\": 41669,\n    \"Whit\": 41670,\n    \"Dun\": 41671,\n    \"Ġexerted\": 41672,\n    \"Ġbrethren\": 41673,\n    \"ĠChronicles\": 41674,\n    \"eric\": 41675,\n    \"Mot\": 41676,\n    \"Ġendings\": 41677,\n    \"piration\": 41678,\n    \"Ġpredetermined\": 41679,\n    \"ĠAirl\": 41680,\n    \"Ġgasp\": 41681,\n    \"Ġ367\": 41682,\n    \"Ġexclaim\": 41683,\n    \"cation\": 41684,\n    \"sort\": 41685,\n    \"idden\": 41686,\n    \"missive\": 41687,\n    \"Ø¹\": 41688,\n    \"oice\": 41689,\n    \"same\": 41690,\n    \"Ott\": 41691,\n    \"Ġscatter\": 41692,\n    \"Flight\": 41693,\n    \"ĠTOD\": 41694,\n    \"Stra\": 41695,\n    \"amia\": 41696,\n    \"IZE\": 41697,\n    \"Ġcompressor\": 41698,\n    \"ixels\": 41699,\n    \"lethal\": 41700,\n    \"ĠExperimental\": 41701,\n    \"Ing\": 41702,\n    \"knife\": 41703,\n    \"Ġvanishing\": 41704,\n    \"ĠRequired\": 41705,\n    \"Stat\": 41706,\n    \"ĠPlex\": 41707,\n    \"spection\": 41708,\n    \"ĠBakr\": 41709,\n    \"Amazing\": 41710,\n    \"Ġbreaths\": 41711,\n    \"rots\": 41712,\n    \"OSP\": 41713,\n    \"Ġ840\": 41714,\n    \"Wars\": 41715,\n    \"OGR\": 41716,\n    \"Ġ372\": 41717,\n    \"ĠKhe\": 41718,\n    \"inous\": 41719,\n    \"lightly\": 41720,\n    \"ĠRounds\": 41721,\n    \"Ġrefinement\": 41722,\n    \"property\": 41723,\n    \"Ġmetaph\": 41724,\n    \"oultry\": 41725,\n    \"istor\": 41726,\n    \"Ġintestine\": 41727,\n    \"eus\": 41728,\n    \"ĠWilhelm\": 41729,\n    \"ĠBane\": 41730,\n    \"emption\": 41731,\n    \"oubtedly\": 41732,\n    \"ĠVirtue\": 41733,\n    \"'),\": 41734,\n    \"Ħ¢\": 41735,\n    \"Ġappar\": 41736,\n    \"ĠTranslation\": 41737,\n    \"Quite\": 41738,\n    \"Ġphysicists\": 41739,\n    \"Ġpriesthood\": 41740,\n    \"Ġallowable\": 41741,\n    \"Saint\": 41742,\n    \"OSED\": 41743,\n    \"bind\": 41744,\n    \"Ġtorches\": 41745,\n    \"osexual\": 41746,\n    \"Cruz\": 41747,\n    \"ertility\": 41748,\n    \"ĠAES\": 41749,\n    \"Ġascended\": 41750,\n    \"Ġmuzzle\": 41751,\n    \"Ġelectors\": 41752,\n    \"ĠKrug\": 41753,\n    \"Ġcc\": 41754,\n    \"classic\": 41755,\n    \"ĠMace\": 41756,\n    \"Å«\": 41757,\n    \"ĠâĢ¦\\\"\": 41758,\n    \"ĠTEST\": 41759,\n    \"gomery\": 41760,\n    \"Person\": 41761,\n    \"Ġtranslations\": 41762,\n    \"ĠDys\": 41763,\n    \"ĠConsent\": 41764,\n    \"Ġ361\": 41765,\n    \"alos\": 41766,\n    \"Ġallerg\": 41767,\n    \"ĠWast\": 41768,\n    \"ĠChecks\": 41769,\n    \"cerning\": 41770,\n    \"Ġlizard\": 41771,\n    \"Ġrevolutions\": 41772,\n    \"Ġtether\": 41773,\n    \"Ġminimized\": 41774,\n    \"ĠReverse\": 41775,\n    \"itely\": 41776,\n    \"iguous\": 41777,\n    \"athing\": 41778,\n    \"Flow\": 41779,\n    \"Moving\": 41780,\n    \"Ġ409\": 41781,\n    \"047\": 41782,\n    \"Ġsnug\": 41783,\n    \"Nich\": 41784,\n    \"Ġcartridge\": 41785,\n    \"YL\": 41786,\n    \"Ġforwarding\": 41787,\n    \"umerous\": 41788,\n    \"ĠAbedin\": 41789,\n    \"iolet\": 41790,\n    \"tick\": 41791,\n    \"ĠTransform\": 41792,\n    \"Grant\": 41793,\n    \"Ġsubtitles\": 41794,\n    \"ĠEmin\": 41795,\n    \"ghost\": 41796,\n    \"ĠKurd\": 41797,\n    \"Ġfireball\": 41798,\n    \"compatible\": 41799,\n    \"Ġprojectiles\": 41800,\n    \"amorph\": 41801,\n    \"ĠSatisf\": 41802,\n    \"Ġquirks\": 41803,\n    \"Ġrecept\": 41804,\n    \"spective\": 41805,\n    \"Ġgraphical\": 41806,\n    \"ĠPicard\": 41807,\n    \"ĠAuthent\": 41808,\n    \"ĠSponge\": 41809,\n    \"Army\": 41810,\n    \"ĠLumin\": 41811,\n    \"ĠSOME\": 41812,\n    \"Ġsolitude\": 41813,\n    \"ĠSHOULD\": 41814,\n    \"ĠFasc\": 41815,\n    \"opez\": 41816,\n    \"types\": 41817,\n    \"gallery\": 41818,\n    \"OLOGY\": 41819,\n    \"shake\": 41820,\n    \"Ġ369\": 41821,\n    \"Ġreused\": 41822,\n    \"Ġ378\": 41823,\n    \"Ġexorc\": 41824,\n    \"Ġdocs\": 41825,\n    \"Yu\": 41826,\n    \"ĠGOD\": 41827,\n    \"ocrine\": 41828,\n    \"location\": 41829,\n    \"fif\": 41830,\n    \"Grid\": 41831,\n    \"Ġpowd\": 41832,\n    \"Ġ'[\": 41833,\n    \"Ġposterior\": 41834,\n    \"Thompson\": 41835,\n    \"Table\": 41836,\n    \"oslov\": 41837,\n    \"ĠGoddess\": 41838,\n    \"odon\": 41839,\n    \"ĠSTD\": 41840,\n    \"Ġresponsiveness\": 41841,\n    \"stab\": 41842,\n    \"absolute\": 41843,\n    \"Enough\": 41844,\n    \"ĠEssence\": 41845,\n    \"ĠUpgrade\": 41846,\n    \"hematically\": 41847,\n    \"Subscribe\": 41848,\n    \"alsh\": 41849,\n    \"repl\": 41850,\n    \"Ġselector\": 41851,\n    \"ĠLength\": 41852,\n    \"Ġtemporal\": 41853,\n    \"Tele\": 41854,\n    \"ocalyptic\": 41855,\n    \"ĠDeaths\": 41856,\n    \"rl\": 41857,\n    \"Target\": 41858,\n    \"ĠOrn\": 41859,\n    \"ongh\": 41860,\n    \"Ġ1909\": 41861,\n    \"Quest\": 41862,\n    \"Place\": 41863,\n    \"ĠDisabled\": 41864,\n    \"Ġascending\": 41865,\n    \"giene\": 41866,\n    \"ĠMSI\": 41867,\n    \"ivil\": 41868,\n    \"Ġcaval\": 41869,\n    \"Ġintermitt\": 41870,\n    \"Ġsalts\": 41871,\n    \"Apr\": 41872,\n    \"059\": 41873,\n    \"ĠKeeper\": 41874,\n    \"emis\": 41875,\n    \"ĠEternal\": 41876,\n    \"SER\": 41877,\n    \"estones\": 41878,\n    \"Ġrudimentary\": 41879,\n    \"Ġpooled\": 41880,\n    \"ĠAlright\": 41881,\n    \"Ġdiagrams\": 41882,\n    \"ydia\": 41883,\n    \"Jacob\": 41884,\n    \"Ġarchitectures\": 41885,\n    \"ĠUSPS\": 41886,\n    \"Ġfootnote\": 41887,\n    \"ĠBrav\": 41888,\n    \"ĠLeopard\": 41889,\n    \"Ġvirtuous\": 41890,\n    \"ploma\": 41891,\n    \"ĠHIP\": 41892,\n    \"Ġhorizontally\": 41893,\n    \"olith\": 41894,\n    \"Prop\": 41895,\n    \"ĠApocalypse\": 41896,\n    \"Syria\": 41897,\n    \"ĠShowdown\": 41898,\n    \"constitutional\": 41899,\n    \"Independent\": 41900,\n    \"ĠMiliband\": 41901,\n    \"ĠTracks\": 41902,\n    \"adle\": 41903,\n    \"ĠESL\": 41904,\n    \"ĠFIGHT\": 41905,\n    \"Ġjohn\": 41906,\n    \"é\": 41907,\n    \"benef\": 41908,\n    \"eware\": 41909,\n    \"ĠTABLE\": 41910,\n    \"ĠVeg\": 41911,\n    \"ainers\": 41912,\n    \"Ġresolves\": 41913,\n    \"Warren\": 41914,\n    \"ĠRanked\": 41915,\n    \"possibly\": 41916,\n    \"bian\": 41917,\n    \"simple\": 41918,\n    \"Ġuniformly\": 41919,\n    \"ĠSlash\": 41920,\n    \"otton\": 41921,\n    \"ĠAbsent\": 41922,\n    \"agically\": 41923,\n    \"ĠPieces\": 41924,\n    \"Station\": 41925,\n    \"ĠBeware\": 41926,\n    \"ĠDiscrimination\": 41927,\n    \"Ġponies\": 41928,\n    \"Import\": 41929,\n    \"utory\": 41930,\n    \"ĠParas\": 41931,\n    \"Phoenix\": 41932,\n    \"Lat\": 41933,\n    \"UTC\": 41934,\n    \"push\": 41935,\n    \"astically\": 41936,\n    \"urrent\": 41937,\n    \"untarily\": 41938,\n    \"Ġparanormal\": 41939,\n    \"Ġglanced\": 41940,\n    \"Ġmanifestations\": 41941,\n    \"ĠNeuroscience\": 41942,\n    \"irgin\": 41943,\n    \"ROM\": 41944,\n    \"Ġ($)\": 41945,\n    \"Ġ379\": 41946,\n    \"missing\": 41947,\n    \"Ġmercenaries\": 41948,\n    \"Ġenumer\": 41949,\n    \"ĠShant\": 41950,\n    \"Ws\": 41951,\n    \"wered\": 41952,\n    \"Ġbuffs\": 41953,\n    \"ultane\": 41954,\n    \"ĠRohing\": 41955,\n    \"igger\": 41956,\n    \"Ring\": 41957,\n    \"Ġmanifests\": 41958,\n    \"Fat\": 41959,\n    \"ĠReduced\": 41960,\n    \"ĠMinerva\": 41961,\n    \"uart\": 41962,\n    \"ĠArmory\": 41963,\n    \"orange\": 41964,\n    \"igible\": 41965,\n    \"Ġphysiology\": 41966,\n    \"Ut\": 41967,\n    \"Ġparchment\": 41968,\n    \"ĠFired\": 41969,\n    \"trap\": 41970,\n    \"oggle\": 41971,\n    \"mson\": 41972,\n    \"ĠPoster\": 41973,\n    \"Ġbount\": 41974,\n    \"import\": 41975,\n    \"maximum\": 41976,\n    \"Ġ422\": 41977,\n    \"ĠFemin\": 41978,\n    \"Ġnodding\": 41979,\n    \"Ġinscription\": 41980,\n    \"Results\": 41981,\n    \"GRE\": 41982,\n    \"icative\": 41983,\n    \"Ġcognition\": 41984,\n    \"Ġions\": 41985,\n    \"ĠBite\": 41986,\n    \"Ġneutron\": 41987,\n    \"Ġduplication\": 41988,\n    \"ĠZIP\": 41989,\n    \"ĠQuit\": 41990,\n    \"Ġgrasping\": 41991,\n    \"ĠDaylight\": 41992,\n    \"Ġlayouts\": 41993,\n    \"CLA\": 41994,\n    \"reason\": 41995,\n    \"ĠHuh\": 41996,\n    \"Ġpige\": 41997,\n    \"ĠBomber\": 41998,\n    \"Produ\": 41999,\n    \"Ġgland\": 42000,\n    \"ĠAbsolute\": 42001,\n    \"writ\": 42002,\n    \"Ġmassac\": 42003,\n    \"Ġfixation\": 42004,\n    \"device\": 42005,\n    \"yz\": 42006,\n    \"ĠGOT\": 42007,\n    \"ĠDying\": 42008,\n    \"adjust\": 42009,\n    \"grain\": 42010,\n    \"Ġdeform\": 42011,\n    \"Ġtypew\": 42012,\n    \"Ġdagger\": 42013,\n    \"ĠTuring\": 42014,\n    \"ĠBucc\": 42015,\n    \"Heavy\": 42016,\n    \"Ġcommod\": 42017,\n    \"files\": 42018,\n    \"ogeneous\": 42019,\n    \"roth\": 42020,\n    \"Buff\": 42021,\n    \"Ġbookmark\": 42022,\n    \"porary\": 42023,\n    \"Medical\": 42024,\n    \"Um\": 42025,\n    \"Ġtranslucent\": 42026,\n    \"ĠAnxiety\": 42027,\n    \"ĠCorinthians\": 42028,\n    \"optional\": 42029,\n    \"PUT\": 42030,\n    \"Ġcrucifix\": 42031,\n    \"alloween\": 42032,\n    \"ĠVK\": 42033,\n    \"Ġblu\": 42034,\n    \"ĠCorinth\": 42035,\n    \"Mount\": 42036,\n    \"Ġmembranes\": 42037,\n    \"particip\": 42038,\n    \"Ġextraord\": 42039,\n    \"Ġstimulated\": 42040,\n    \"leneck\": 42041,\n    \"Ġspecifies\": 42042,\n    \"Sin\": 42043,\n    \"lash\": 42044,\n    \"Edited\": 42045,\n    \"Ġfused\": 42046,\n    \"Nin\": 42047,\n    \"ĠBungie\": 42048,\n    \"ĠTooth\": 42049,\n    \"WATCH\": 42050,\n    \"Nav\": 42051,\n    \"Initially\": 42052,\n    \"+)\": 42053,\n    \"ĠAncest\": 42054,\n    \"Ġtransmitter\": 42055,\n    \"ĠVolks\": 42056,\n    \"ezvous\": 42057,\n    \"ĠNirvana\": 42058,\n    \"ĠCald\": 42059,\n    \"font\": 42060,\n    \"Und\": 42061,\n    \"remlin\": 42062,\n    \"ichever\": 42063,\n    \"ĠHeal\": 42064,\n    \"shall\": 42065,\n    \"Ġattribution\": 42066,\n    \"authorized\": 42067,\n    \"ĠINTO\": 42068,\n    \"acteria\": 42069,\n    \"ĠTsu\": 42070,\n    \"ĠPlane\": 42071,\n    \"iphate\": 42072,\n    \"igraph\": 42073,\n    \"chev\": 42074,\n    \"Ġinverse\": 42075,\n    \"ifest\": 42076,\n    \"Players\": 42077,\n    \"!!\\\"\": 42078,\n    \"ĠContrast\": 42079,\n    \"1984\": 42080,\n    \"Ġsevent\": 42081,\n    \"colour\": 42082,\n    \"ĠRational\": 42083,\n    \"virtual\": 42084,\n    \"Ġfec\": 42085,\n    \"ĠETH\": 42086,\n    \"ĠPru\": 42087,\n    \"Õ\": 42088,\n    \"asma\": 42089,\n    \"Cur\": 42090,\n    \"Ġassigns\": 42091,\n    \"Ġridic\": 42092,\n    \"Todd\": 42093,\n    \"ulton\": 42094,\n    \"ĠDefendant\": 42095,\n    \"opsis\": 42096,\n    \"Ġpercentile\": 42097,\n    \"shr\": 42098,\n    \"wagen\": 42099,\n    \"Ġ368\": 42100,\n    \"SIGN\": 42101,\n    \"Screen\": 42102,\n    \"reprene\": 42103,\n    \"Ġerection\": 42104,\n    \"ĠFreak\": 42105,\n    \"ĠStard\": 42106,\n    \"stained\": 42107,\n    \"Ġcla\": 42108,\n    \"fet\": 42109,\n    \"ramids\": 42110,\n    \"QL\": 42111,\n    \"avorable\": 42112,\n    \"ĠTCP\": 42113,\n    \"nown\": 42114,\n    \"ulence\": 42115,\n    \"similar\": 42116,\n    \"Ġlinkage\": 42117,\n    \"ercise\": 42118,\n    \"Path\": 42119,\n    \"LECT\": 42120,\n    \"ĠCollections\": 42121,\n    \"ĠModule\": 42122,\n    \"Ġcs\": 42123,\n    \"Current\": 42124,\n    \"Ġmono\": 42125,\n    \"ĠAlv\": 42126,\n    \"ĠDude\": 42127,\n    \"Ġhypers\": 42128,\n    \"Ġ2600\": 42129,\n    \"surface\": 42130,\n    \"Ġpredictor\": 42131,\n    \"ĠColomb\": 42132,\n    \"Prof\": 42133,\n    \"anqu\": 42134,\n    \"natal\": 42135,\n    \"Ġadultery\": 42136,\n    \"ĠGenerations\": 42137,\n    \"clerosis\": 42138,\n    \"Ġ371\": 42139,\n    \"Ġenlightenment\": 42140,\n    \"onomic\": 42141,\n    \"Ġsatir\": 42142,\n    \"ĠBasics\": 42143,\n    \"Graham\": 42144,\n    \"ĠRove\": 42145,\n    \"Ġadul\": 42146,\n    \"Shut\": 42147,\n    \"ocious\": 42148,\n    \"Ġhandc\": 42149,\n    \"BW\": 42150,\n    \"ĠCognitive\": 42151,\n    \"visible\": 42152,\n    \"Ġinev\": 42153,\n    \"Ġ978\": 42154,\n    \"ĠSupported\": 42155,\n    \"Ġarrays\": 42156,\n    \"Ġalienation\": 42157,\n    \"Weight\": 42158,\n    \"ĠkWh\": 42159,\n    \"Ġwarped\": 42160,\n    \"Ġ386\": 42161,\n    \"lance\": 42162,\n    \"Ġherpes\": 42163,\n    \"ĠPHP\": 42164,\n    \"Ġclaimant\": 42165,\n    \"uitive\": 42166,\n    \"Ġpussy\": 42167,\n    \"Ġcorpus\": 42168,\n    \"ĠAo\": 42169,\n    \"Qual\": 42170,\n    \"ĠXVI\": 42171,\n    \"requ\": 42172,\n    \"Ġsympt\": 42173,\n    \"mination\": 42174,\n    \"Ġhairy\": 42175,\n    \"ĠBattles\": 42176,\n    \"owntown\": 42177,\n    \"Roberts\": 42178,\n    \"Ġnec\": 42179,\n    \"ablo\": 42180,\n    \"AMD\": 42181,\n    \"internet\": 42182,\n    \"Tar\": 42183,\n    \"direction\": 42184,\n    \"ouston\": 42185,\n    \"ĠGlock\": 42186,\n    \"ĠYanukovych\": 42187,\n    \"ogens\": 42188,\n    \"rogram\": 42189,\n    \"otype\": 42190,\n    \"ĠPt\": 42191,\n    \"tenance\": 42192,\n    \"Ġaromatic\": 42193,\n    \"oxin\": 42194,\n    \"Vert\": 42195,\n    \"Ġsociop\": 42196,\n    \"cible\": 42197,\n    \"Db\": 42198,\n    \"________________\": 42199,\n    \"Third\": 42200,\n    \"ĠShips\": 42201,\n    \"!.\": 42202,\n    \"expensive\": 42203,\n    \"WOR\": 42204,\n    \"primary\": 42205,\n    \"Ġ666\": 42206,\n    \"Ġdecaying\": 42207,\n    \"Ġclustered\": 42208,\n    \"Ġbeetles\": 42209,\n    \"ĠHogwarts\": 42210,\n    \"Ġheaders\": 42211,\n    \"ĠJudah\": 42212,\n    \"Ġscen\": 42213,\n    \"Ġcosmos\": 42214,\n    \"ĠGenetic\": 42215,\n    \"blems\": 42216,\n    \"Ġfeeble\": 42217,\n    \"NOW\": 42218,\n    \"NSA\": 42219,\n    \"Ġadminist\": 42220,\n    \"ĠDocker\": 42221,\n    \"portion\": 42222,\n    \"gression\": 42223,\n    \"Ġ1904\": 42224,\n    \"heard\": 42225,\n    \"Ġinhab\": 42226,\n    \"ĠLeaves\": 42227,\n    \"Ġcortisol\": 42228,\n    \"atinum\": 42229,\n    \"unknown\": 42230,\n    \"ĠObserv\": 42231,\n    \"ĠPhilosophy\": 42232,\n    \"Ide\": 42233,\n    \"Ġcopyrighted\": 42234,\n    \"surv\": 42235,\n    \"ĠLocations\": 42236,\n    \"Ġglands\": 42237,\n    \"ĠKnife\": 42238,\n    \"ĠEmber\": 42239,\n    \"ĠUnicorn\": 42240,\n    \"Ġhaste\": 42241,\n    \"Ġkinderg\": 42242,\n    \"ĠTerrit\": 42243,\n    \"ĠKoran\": 42244,\n    \"Ġaval\": 42245,\n    \"addon\": 42246,\n    \"ĠNero\": 42247,\n    \"\\\"]\": 42248,\n    \"Ġ392\": 42249,\n    \"comfort\": 42250,\n    \"Ġclothed\": 42251,\n    \"ashtra\": 42252,\n    \"mode\": 42253,\n    \"Ġ??\": 42254,\n    \"!\\\",\": 42255,\n    \"Ġknob\": 42256,\n    \"EMP\": 42257,\n    \"norm\": 42258,\n    \"ĠAgo\": 42259,\n    \"RECT\": 42260,\n    \"Denver\": 42261,\n    \"Ġ1907\": 42262,\n    \"ĠBombs\": 42263,\n    \"Sche\": 42264,\n    \"Ġtriangular\": 42265,\n    \"Ġperv\": 42266,\n    \"rises\": 42267,\n    \"Jes\": 42268,\n    \"Ġcalibration\": 42269,\n    \"Ġts\": 42270,\n    \"Same\": 42271,\n    \"ĠAxe\": 42272,\n    \"ĠMei\": 42273,\n    \"multi\": 42274,\n    \"Ġexerc\": 42275,\n    \"orney\": 42276,\n    \"Ware\": 42277,\n    \"abul\": 42278,\n    \"ĠFior\": 42279,\n    \"Eventually\": 42280,\n    \"ĠGrizz\": 42281,\n    \"Past\": 42282,\n    \"married\": 42283,\n    \"Ġscram\": 42284,\n    \"ĠCache\": 42285,\n    \"posure\": 42286,\n    \"Ġheav\": 42287,\n    \"ĠShirt\": 42288,\n    \"powder\": 42289,\n    \"complex\": 42290,\n    \"Doc\": 42291,\n    \"arus\": 42292,\n    \"Pi\": 42293,\n    \"Ġcurv\": 42294,\n    \"ĠTopic\": 42295,\n    \"Ġ.)\": 42296,\n    \"Ġwills\": 42297,\n    \"philis\": 42298,\n    \"gui\": 42299,\n    \"leground\": 42300,\n    \"Eth\": 42301,\n    \"Strike\": 42302,\n    \"Kid\": 42303,\n    \"Ġdelegated\": 42304,\n    \"Soon\": 42305,\n    \"Ġwast\": 42306,\n    \"gage\": 42307,\n    \"Ġprosecut\": 42308,\n    \"Ġ374\": 42309,\n    \"opolis\": 42310,\n    \"chest\": 42311,\n    \"ensation\": 42312,\n    \"Ġredes\": 42313,\n    \"Ġpresum\": 42314,\n    \"Portland\": 42315,\n    \"Ġannihil\": 42316,\n    \"yssey\": 42317,\n    \"Ġforks\": 42318,\n    \"Ġvitro\": 42319,\n    \"walker\": 42320,\n    \"ĠPsal\": 42321,\n    \"ĠStealth\": 42322,\n    \"Quick\": 42323,\n    \"ĠBaghd\": 42324,\n    \"ĠDrift\": 42325,\n    \"//\": 42326,\n    \"Ġinvincible\": 42327,\n    \"ĠGAM\": 42328,\n    \"Ġcastles\": 42329,\n    \"Ġbondage\": 42330,\n    \"ĠBalloon\": 42331,\n    \"Amid\": 42332,\n    \"individual\": 42333,\n    \"tis\": 42334,\n    \"ĠGuides\": 42335,\n    \"xe\": 42336,\n    \"Cong\": 42337,\n    \"URI\": 42338,\n    \"ĠHH\": 42339,\n    \"PHOTOS\": 42340,\n    \"ĠASIC\": 42341,\n    \"burst\": 42342,\n    \"ahon\": 42343,\n    \"ĠFIX\": 42344,\n    \"ilib\": 42345,\n    \"Ġ457\": 42346,\n    \"ĠLogged\": 42347,\n    \"à¹\": 42348,\n    \"Creat\": 42349,\n    \"inatory\": 42350,\n    \"column\": 42351,\n    \"ĠAugustus\": 42352,\n    \"suggest\": 42353,\n    \"pret\": 42354,\n    \"ĠParan\": 42355,\n    \"Ġsubsistence\": 42356,\n    \"wx\": 42357,\n    \"×\": 42358,\n    \"aleigh\": 42359,\n    \"dash\": 42360,\n    \"ĠMana\": 42361,\n    \"Ko\": 42362,\n    \"opausal\": 42363,\n    \"Ġbene\": 42364,\n    \"ĠSabb\": 42365,\n    \"ĠGhosts\": 42366,\n    \"Ġ1830\": 42367,\n    \"ĠHats\": 42368,\n    \"ĠHive\": 42369,\n    \"Perfect\": 42370,\n    \"Ġsocialists\": 42371,\n    \"Ġtumult\": 42372,\n    \"EGA\": 42373,\n    \"ĠNAME\": 42374,\n    \"Android\": 42375,\n    \"assembled\": 42376,\n    \"phis\": 42377,\n    \"Stage\": 42378,\n    \"Char\": 42379,\n    \"Double\": 42380,\n    \"Ġinsign\": 42381,\n    \"IED\": 42382,\n    \"perial\": 42383,\n    \"ĠEMP\": 42384,\n    \"mx\": 42385,\n    \"Ġskept\": 42386,\n    \"Ġwifi\": 42387,\n    \"Ġparad\": 42388,\n    \"ĠFrequency\": 42389,\n    \"Dist\": 42390,\n    \"nil\": 42391,\n    \"iots\": 42392,\n    \"å\": 42393,\n    \"Message\": 42394,\n    \"Furthermore\": 42395,\n    \"Ġhideous\": 42396,\n    \"ĠLDL\": 42397,\n    \"ĠFault\": 42398,\n    \"ĠDimensions\": 42399,\n    \"ĠImplement\": 42400,\n    \"fram\": 42401,\n    \"Ġamaz\": 42402,\n    \"ĠIndones\": 42403,\n    \"ĠTile\": 42404,\n    \"Ġlar\": 42405,\n    \"gc\": 42406,\n    \"Ġcorrelate\": 42407,\n    \"Ġensl\": 42408,\n    \"mite\": 42409,\n    \"Ġhomosexuals\": 42410,\n    \"Ġagric\": 42411,\n    \"8000\": 42412,\n    \"Ġcuring\": 42413,\n    \"rament\": 42414,\n    \"Ġrecons\": 42415,\n    \"ocene\": 42416,\n    \"ENTION\": 42417,\n    \"Ġcommunion\": 42418,\n    \"ĠFunction\": 42419,\n    \"iple\": 42420,\n    \"Ġredund\": 42421,\n    \"Ġcalibrated\": 42422,\n    \"Ġcontribut\": 42423,\n    \"ĠHuck\": 42424,\n    \"limit\": 42425,\n    \"ĠFedora\": 42426,\n    \"ĠTsuk\": 42427,\n    \"brates\": 42428,\n    \"Ġ1903\": 42429,\n    \"ozo\": 42430,\n    \"visual\": 42431,\n    \"ĠDiscipline\": 42432,\n    \"chains\": 42433,\n    \"ĠOCD\": 42434,\n    \"Ġexpended\": 42435,\n    \"0002\": 42436,\n    \"Ġsty\": 42437,\n    \"ĠNightmare\": 42438,\n    \"ĠReplace\": 42439,\n    \"ounty\": 42440,\n    \"fn\": 42441,\n    \"1900\": 42442,\n    \"ĠEpidem\": 42443,\n    \"ĠFW\": 42444,\n    \"Ġgul\": 42445,\n    \"ĠTomato\": 42446,\n    \"ĠPerse\": 42447,\n    \"wl\": 42448,\n    \"ĠFormation\": 42449,\n    \"Scan\": 42450,\n    \"cosystem\": 42451,\n    \"Brand\": 42452,\n    \"Ġ398\": 42453,\n    \"Ġcaptives\": 42454,\n    \"Ġ×\": 42455,\n    \"ESCO\": 42456,\n    \"ĠEnder\": 42457,\n    \"lesh\": 42458,\n    \"ĠAscend\": 42459,\n    \"poly\": 42460,\n    \"eous\": 42461,\n    \"Ġhyster\": 42462,\n    \"Murray\": 42463,\n    \"phe\": 42464,\n    \"Ġradiator\": 42465,\n    \"esthes\": 42466,\n    \"Ġopin\": 42467,\n    \"Ġconspic\": 42468,\n    \"intosh\": 42469,\n    \"Ġwitchcraft\": 42470,\n    \"ĠCFR\": 42471,\n    \"ussian\": 42472,\n    \"escent\": 42473,\n    \"locking\": 42474,\n    \"Ġnonsensical\": 42475,\n    \"uala\": 42476,\n    \"ĠSerial\": 42477,\n    \"1991\": 42478,\n    \"ĠCalm\": 42479,\n    \"containing\": 42480,\n    \"Ġstimulates\": 42481,\n    \"Ġ448\": 42482,\n    \"Pir\": 42483,\n    \"ĠâĨĴ\": 42484,\n    \"ĠDiver\": 42485,\n    \"Ġmanuscripts\": 42486,\n    \"ĠGaia\": 42487,\n    \"Ñĥ\": 42488,\n    \"Learning\": 42489,\n    \"Ġnipple\": 42490,\n    \"reads\": 42491,\n    \"Ġandroid\": 42492,\n    \"ĠMeditation\": 42493,\n    \"Ġincomprehensible\": 42494,\n    \"edded\": 42495,\n    \"Ġdescendant\": 42496,\n    \"ĠMorty\": 42497,\n    \"Luckily\": 42498,\n    \"ARCH\": 42499,\n    \"ausible\": 42500,\n    \"Dig\": 42501,\n    \"shared\": 42502,\n    \"ĠClip\": 42503,\n    \"Ġtrope\": 42504,\n    \"Ġnarcissistic\": 42505,\n    \"ventures\": 42506,\n    \"Ġcuriously\": 42507,\n    \"ĠCosmos\": 42508,\n    \"Aust\": 42509,\n    \"Lay\": 42510,\n    \"ĠShard\": 42511,\n    \"ĠRecorded\": 42512,\n    \"Ġ458\": 42513,\n    \"........\": 42514,\n    \"Ġperish\": 42515,\n    \"ĠExample\": 42516,\n    \"luent\": 42517,\n    \"Ġapes\": 42518,\n    \"ĠHitch\": 42519,\n    \"Ġholiest\": 42520,\n    \"Ġamplifier\": 42521,\n    \"minent\": 42522,\n    \"xxxxxxxx\": 42523,\n    \"inite\": 42524,\n    \"Ġgenomes\": 42525,\n    \"ĠGuilty\": 42526,\n    \"mult\": 42527,\n    \"Ġorc\": 42528,\n    \"Ġnipples\": 42529,\n    \"Side\": 42530,\n    \"Ġlogically\": 42531,\n    \"Ġdatasets\": 42532,\n    \"ĠTitanium\": 42533,\n    \"Ġrotor\": 42534,\n    \"undle\": 42535,\n    \"handled\": 42536,\n    \"nexpected\": 42537,\n    \"Ġdw\": 42538,\n    \"Ġdiagonal\": 42539,\n    \"ĠAnimated\": 42540,\n    \"Ġnumbering\": 42541,\n    \"Forest\": 42542,\n    \"ĠâĨ\": 42543,\n    \"Prin\": 42544,\n    \"Ġchemically\": 42545,\n    \"ĠGithub\": 42546,\n    \"Ġaph\": 42547,\n    \"ĠFaster\": 42548,\n    \"ĠTinker\": 42549,\n    \"ikini\": 42550,\n    \"Dest\": 42551,\n    \"dri\": 42552,\n    \"Manufact\": 42553,\n    \"isance\": 42554,\n    \"Return\": 42555,\n    \"Alert\": 42556,\n    \"elcome\": 42557,\n    \"ĠMMR\": 42558,\n    \"Ġresid\": 42559,\n    \"ĠLIC\": 42560,\n    \"Ġspecificity\": 42561,\n    \"zanne\": 42562,\n    \"Ġanyways\": 42563,\n    \"Ġ426\": 42564,\n    \"Scot\": 42565,\n    \"astery\": 42566,\n    \"Via\": 42567,\n    \"ĠBlocks\": 42568,\n    \"Ġactivates\": 42569,\n    \"Ġabstinence\": 42570,\n    \"Ġchronological\": 42571,\n    \"Soul\": 42572,\n    \"ĠSchne\": 42573,\n    \"Ġwatts\": 42574,\n    \"AUT\": 42575,\n    \"Ġcalcul\": 42576,\n    \"Simply\": 42577,\n    \"Emb\": 42578,\n    \"ceptive\": 42579,\n    \"ĠCatholicism\": 42580,\n    \"obook\": 42581,\n    \"ĠBits\": 42582,\n    \"ĠMbps\": 42583,\n    \"Ġindignation\": 42584,\n    \"Ġshorthand\": 42585,\n    \"Active\": 42586,\n    \"ĠLimbaugh\": 42587,\n    \"ĠCapcom\": 42588,\n    \"adesh\": 42589,\n    \"Ġclipping\": 42590,\n    \"ĠInstructor\": 42591,\n    \"Secret\": 42592,\n    \"___\": 42593,\n    \"Fer\": 42594,\n    \"rawling\": 42595,\n    \"ĠReward\": 42596,\n    \"Ġweep\": 42597,\n    \"Ġmotherboard\": 42598,\n    \"Above\": 42599,\n    \"metry\": 42600,\n    \"ĠPTS\": 42601,\n    \"Ġbombard\": 42602,\n    \"abetes\": 42603,\n    \".--\": 42604,\n    \"Lens\": 42605,\n    \"Comb\": 42606,\n    \"basic\": 42607,\n    \"ĠREALLY\": 42608,\n    \"Later\": 42609,\n    \"Ġ383\": 42610,\n    \"Ġpositional\": 42611,\n    \"olesc\": 42612,\n    \"Ġcrotch\": 42613,\n    \"ĠMDMA\": 42614,\n    \"requently\": 42615,\n    \"ĠPants\": 42616,\n    \"Ġ433\": 42617,\n    \"uctor\": 42618,\n    \"Ġillumination\": 42619,\n    \"ĠÙħ\": 42620,\n    \"ocrin\": 42621,\n    \"Ġpamph\": 42622,\n    \"atio\": 42623,\n    \"etc\": 42624,\n    \"Ġrestores\": 42625,\n    \"ĠProtector\": 42626,\n    \"Develop\": 42627,\n    \"ĠMew\": 42628,\n    \"trop\": 42629,\n    \"ĠSlayer\": 42630,\n    \"Ti\": 42631,\n    \"ĠNotwithstanding\": 42632,\n    \"Match\": 42633,\n    \"LIST\": 42634,\n    \"IDES\": 42635,\n    \"ĠThick\": 42636,\n    \"Ġdisks\": 42637,\n    \"Kin\": 42638,\n    \"Ġghetto\": 42639,\n    \"ĠObjects\": 42640,\n    \"Ġprism\": 42641,\n    \"ĠNether\": 42642,\n    \"Ġvul\": 42643,\n    \"iky\": 42644,\n    \"]:\": 42645,\n    \"ĠDetail\": 42646,\n    \"Ġfucked\": 42647,\n    \"!?\": 42648,\n    \"anium\": 42649,\n    \"Ġlords\": 42650,\n    \"ilities\": 42651,\n    \"ĠEthnic\": 42652,\n    \"static\": 42653,\n    \"$$\": 42654,\n    \"evidence\": 42655,\n    \"Ġmainline\": 42656,\n    \"Ġpeasant\": 42657,\n    \"ĠEnhance\": 42658,\n    \"ĠForced\": 42659,\n    \"virt\": 42660,\n    \"Ġii\": 42661,\n    \"Ġsymm\": 42662,\n    \"Ġconverter\": 42663,\n    \"ularity\": 42664,\n    \"Ġrepent\": 42665,\n    \"num\": 42666,\n    \"ĠScrew\": 42667,\n    \"ĠFTA\": 42668,\n    \"Ġmarines\": 42669,\n    \"hetto\": 42670,\n    \"blow\": 42671,\n    \"Ġado\": 42672,\n    \"ĠTypical\": 42673,\n    \"Ġoverw\": 42674,\n    \"ĠBerm\": 42675,\n    \"keley\": 42676,\n    \"Song\": 42677,\n    \"hao\": 42678,\n    \"valid\": 42679,\n    \"EXT\": 42680,\n    \"ĠProvides\": 42681,\n    \"âĺħâĺħ\": 42682,\n    \"ĠOdin\": 42683,\n    \"Shot\": 42684,\n    \"Ġgamma\": 42685,\n    \"Princ\": 42686,\n    \"asonry\": 42687,\n    \"ĠAccuracy\": 42688,\n    \"Ġcriterion\": 42689,\n    \"Ġdescriptive\": 42690,\n    \"Gall\": 42691,\n    \"gray\": 42692,\n    \"ĠCalcul\": 42693,\n    \"Ġaxes\": 42694,\n    \"ĠCommunists\": 42695,\n    \"ĠRebellion\": 42696,\n    \"Success\": 42697,\n    \"tg\": 42698,\n    \"Ġâĺ\": 42699,\n    \"Ġmultiplier\": 42700,\n    \"ravity\": 42701,\n    \"Thus\": 42702,\n    \"URL\": 42703,\n    \"Ġalternatively\": 42704,\n    \"duction\": 42705,\n    \"Ġsarcast\": 42706,\n    \"ĠCarth\": 42707,\n    \"ĠUSL\": 42708,\n    \"ĠInvisible\": 42709,\n    \"larg\": 42710,\n    \"pleted\": 42711,\n    \"pathic\": 42712,\n    \"Additionally\": 42713,\n    \"ĠCao\": 42714,\n    \"Ġlatent\": 42715,\n    \"ĠSurge\": 42716,\n    \"MEN\": 42717,\n    \"communications\": 42718,\n    \"ĠArray\": 42719,\n    \"Pink\": 42720,\n    \"commit\": 42721,\n    \"isodes\": 42722,\n    \"earcher\": 42723,\n    \"Ukraine\": 42724,\n    \"ĠAnthrop\": 42725,\n    \"incial\": 42726,\n    \"Ġquotations\": 42727,\n    \"adena\": 42728,\n    \"Ġwhining\": 42729,\n    \"Ġretri\": 42730,\n    \"ĠAssass\": 42731,\n    \"elligent\": 42732,\n    \"ĠPERSON\": 42733,\n    \"Py\": 42734,\n    \"Send\": 42735,\n    \"ĠâĪĴ\": 42736,\n    \"DON\": 42737,\n    \"Ġwatt\": 42738,\n    \"description\": 42739,\n    \"POS\": 42740,\n    \"Ġrepro\": 42741,\n    \"destroy\": 42742,\n    \"icidal\": 42743,\n    \"Ġmidrange\": 42744,\n    \"Ġinfographic\": 42745,\n    \"interesting\": 42746,\n    \"category\": 42747,\n    \"Flash\": 42748,\n    \"ĠInvasion\": 42749,\n    \"ĠExodus\": 42750,\n    \"restricted\": 42751,\n    \"Ġinference\": 42752,\n    \"dding\": 42753,\n    \"mingham\": 42754,\n    \"Ġcircumst\": 42755,\n    \"Wi\": 42756,\n    \"ĠHast\": 42757,\n    \"Ġsubjug\": 42758,\n    \"Ġwhispering\": 42759,\n    \"-.\": 42760,\n    \"Ġadren\": 42761,\n    \"ĠPattern\": 42762,\n    \"BOX\": 42763,\n    \"ĠEnhancement\": 42764,\n    \"Exc\": 42765,\n    \"ĠBucket\": 42766,\n    \"ĠGUN\": 42767,\n    \"deen\": 42768,\n    \"ĠHomo\": 42769,\n    \"1985\": 42770,\n    \"Ġclo\": 42771,\n    \"Ġsnippet\": 42772,\n    \"Ġ1896\": 42773,\n    \"TPP\": 42774,\n    \"Seg\": 42775,\n    \"success\": 42776,\n    \";\\\"\": 42777,\n    \"ĠMUCH\": 42778,\n    \"Author\": 42779,\n    \"Ġreplication\": 42780,\n    \"Ġhallucinations\": 42781,\n    \"Inv\": 42782,\n    \"ĠAware\": 42783,\n    \"ĠViper\": 42784,\n    \"kai\": 42785,\n    \"frames\": 42786,\n    \"ĠTHANK\": 42787,\n    \"ĠSHA\": 42788,\n    \"wordpress\": 42789,\n    \"Ġbc\": 42790,\n    \"CIA\": 42791,\n    \"arrison\": 42792,\n    \"Ġalloc\": 42793,\n    \"ĠAlz\": 42794,\n    \"letcher\": 42795,\n    \"ĠDaredevil\": 42796,\n    \"iversary\": 42797,\n    \"Ġmanuals\": 42798,\n    \"Catholic\": 42799,\n    \"feat\": 42800,\n    \"Ġkinetic\": 42801,\n    \"JB\": 42802,\n    \"yeah\": 42803,\n    \"ĠLDS\": 42804,\n    \"Ġppm\": 42805,\n    \"ĠADC\": 42806,\n    \"pring\": 42807,\n    \"cence\": 42808,\n    \"Ġclasp\": 42809,\n    \"Ġsetups\": 42810,\n    \"Ġdeity\": 42811,\n    \"ĠIndra\": 42812,\n    \"ĠWander\": 42813,\n    \"Ġantib\": 42814,\n    \"Otherwise\": 42815,\n    \"ombie\": 42816,\n    \"Bitcoin\": 42817,\n    \"ipop\": 42818,\n    \"expression\": 42819,\n    \"Animal\": 42820,\n    \"ĠResurrection\": 42821,\n    \"ĠMoral\": 42822,\n    \"ĠSDK\": 42823,\n    \"Ġwretched\": 42824,\n    \"ogenous\": 42825,\n    \"species\": 42826,\n    \"Ġchuckled\": 42827,\n    \"Thor\": 42828,\n    \"Ġ428\": 42829,\n    \"avery\": 42830,\n    \"ĠPry\": 42831,\n    \"asures\": 42832,\n    \"ĠErn\": 42833,\n    \"apor\": 42834,\n    \"Ġinnumerable\": 42835,\n    \"Ġbaptized\": 42836,\n    \"ĠExplosive\": 42837,\n    \"Ġelves\": 42838,\n    \"idges\": 42839,\n    \"ĠParadox\": 42840,\n    \"Close\": 42841,\n    \"aldehyde\": 42842,\n    \"construct\": 42843,\n    \"Ġvirginity\": 42844,\n    \"Poll\": 42845,\n    \"assin\": 42846,\n    \"Doctors\": 42847,\n    \"Pos\": 42848,\n    \"NECT\": 42849,\n    \"Moreover\": 42850,\n    \"Commercial\": 42851,\n    \"cknowled\": 42852,\n    \"1988\": 42853,\n    \"Ġquotation\": 42854,\n    \"marriage\": 42855,\n    \"ĠBapt\": 42856,\n    \"ĠSina\": 42857,\n    \"ĠGloves\": 42858,\n    \"gian\": 42859,\n    \"Ġconfounding\": 42860,\n    \"URRENT\": 42861,\n    \"Dean\": 42862,\n    \"Brew\": 42863,\n    \"thur\": 42864,\n    \"pty\": 42865,\n    \"immune\": 42866,\n    \"ĠSQU\": 42867,\n    \"Ġcounterfe\": 42868,\n    \"rider\": 42869,\n    \"Ġinferred\": 42870,\n    \"ĠDimension\": 42871,\n    \"ĠToad\": 42872,\n    \"Ġafterlife\": 42873,\n    \"ĠHERO\": 42874,\n    \"Indiana\": 42875,\n    \"seek\": 42876,\n    \"Ġdistinguishes\": 42877,\n    \"ĠQur\": 42878,\n    \"ĠMethods\": 42879,\n    \"combat\": 42880,\n    \"Ġcateg\": 42881,\n    \"ĠStruggle\": 42882,\n    \"teness\": 42883,\n    \"liquid\": 42884,\n    \"Ġblinking\": 42885,\n    \"ĠCONTIN\": 42886,\n    \"iae\": 42887,\n    \"Ġaerobic\": 42888,\n    \"Ġstrugg\": 42889,\n    \"Ġegalitarian\": 42890,\n    \"hello\": 42891,\n    \"orrect\": 42892,\n    \"ĠAbandon\": 42893,\n    \"Ġferment\": 42894,\n    \"Area\": 42895,\n    \"idem\": 42896,\n    \"ĠMania\": 42897,\n    \"Ġjs\": 42898,\n    \"ĠBALL\": 42899,\n    \"Running\": 42900,\n    \"Ġregenerate\": 42901,\n    \"iquid\": 42902,\n    \"Uh\": 42903,\n    \"Crystal\": 42904,\n    \"ĠItal\": 42905,\n    \"ĠHeavenly\": 42906,\n    \"Ð²\": 42907,\n    \"CRIPTION\": 42908,\n    \"Consumer\": 42909,\n    \"dust\": 42910,\n    \"amiliar\": 42911,\n    \"ĠRhino\": 42912,\n    \"Rocket\": 42913,\n    \"Ġreversible\": 42914,\n    \"kok\": 42915,\n    \"ĠSketch\": 42916,\n    \"Ġshotguns\": 42917,\n    \"apses\": 42918,\n    \"Ġdetach\": 42919,\n    \"ĠCells\": 42920,\n    \"artist\": 42921,\n    \"rily\": 42922,\n    \"ĠRestore\": 42923,\n    \"Scar\": 42924,\n    \"Ġevid\": 42925,\n    \"Ġspaced\": 42926,\n    \"ĠContributions\": 42927,\n    \"Ġ418\": 42928,\n    \"ĠMystic\": 42929,\n    \"Ġobfusc\": 42930,\n    \"Russ\": 42931,\n    \"wings\": 42932,\n    \"Pear\": 42933,\n    \"osite\": 42934,\n    \"Nusra\": 42935,\n    \"urations\": 42936,\n    \"ovie\": 42937,\n    \"icago\": 42938,\n    \"ĠConcepts\": 42939,\n    \"Ġstimuli\": 42940,\n    \"Ġaroused\": 42941,\n    \"aughty\": 42942,\n    \"Talking\": 42943,\n    \"ĠPrompt\": 42944,\n    \"Across\": 42945,\n    \"ĠPlaint\": 42946,\n    \"Ġbranching\": 42947,\n    \"Thankfully\": 42948,\n    \"Original\": 42949,\n    \"Esc\": 42950,\n    \"ĠTechnician\": 42951,\n    \"fleet\": 42952,\n    \"usher\": 42953,\n    \"Mos\": 42954,\n    \"livion\": 42955,\n    \"oenix\": 42956,\n    \"Ġhr\": 42957,\n    \"ibble\": 42958,\n    \"Ġindent\": 42959,\n    \"ĠFinished\": 42960,\n    \"Department\": 42961,\n    \"ĠINFO\": 42962,\n    \"Movie\": 42963,\n    \"++\": 42964,\n    \"THING\": 42965,\n    \"Ġtimers\": 42966,\n    \"rocket\": 42967,\n    \"Natural\": 42968,\n    \"lime\": 42969,\n    \"Ġangular\": 42970,\n    \"osure\": 42971,\n    \"Ġdynamically\": 42972,\n    \"Ġpacif\": 42973,\n    \"ĠProcessor\": 42974,\n    \"Ġdisgu\": 42975,\n    \"Ġmoderators\": 42976,\n    \"Ġceases\": 42977,\n    \"Ġinertia\": 42978,\n    \"Ġpaperback\": 42979,\n    \"yton\": 42980,\n    \"ĠHuma\": 42981,\n    \"Ġprohibitions\": 42982,\n    \"Ġgestation\": 42983,\n    \"Bomb\": 42984,\n    \"termin\": 42985,\n    \"Ġcaric\": 42986,\n    \"oS\": 42987,\n    \"tc\": 42988,\n    \"Cop\": 42989,\n    \"raved\": 42990,\n    \"Ġeighty\": 42991,\n    \"ĠEnable\": 42992,\n    \"Ġimplementations\": 42993,\n    \"Ġconquering\": 42994,\n    \"ĠFinder\": 42995,\n    \"window\": 42996,\n    \"Gra\": 42997,\n    \"Ġfonts\": 42998,\n    \"laughter\": 42999,\n    \"Ġcolonization\": 43000,\n    \"ĠDOD\": 43001,\n    \")!\": 43002,\n    \",)\": 43003,\n    \"ĠGeral\": 43004,\n    \"ĠSpoiler\": 43005,\n    \"ĠComponent\": 43006,\n    \"Ġgist\": 43007,\n    \"hiro\": 43008,\n    \"Ġlicens\": 43009,\n    \"nesses\": 43010,\n    \"Ġkarma\": 43011,\n    \"?\\\".\": 43012,\n    \"OPA\": 43013,\n    \"Ġsquats\": 43014,\n    \"ĠRAND\": 43015,\n    \"Ġorally\": 43016,\n    \"document\": 43017,\n    \"olars\": 43018,\n    \"Ġpresumptive\": 43019,\n    \"Pers\": 43020,\n    \"OAD\": 43021,\n    \"ufficient\": 43022,\n    \"LESS\": 43023,\n    \"Hidden\": 43024,\n    \"ORK\": 43025,\n    \"xs\": 43026,\n    \"Ġmathematician\": 43027,\n    \"ĠGloss\": 43028,\n    \"Ġannihilation\": 43029,\n    \"Ġmanifold\": 43030,\n    \"Ry\": 43031,\n    \"Thunder\": 43032,\n    \"Yan\": 43033,\n    \"Activ\": 43034,\n    \"Ġworldly\": 43035,\n    \"TED\": 43036,\n    \"marg\": 43037,\n    \"ĠStun\": 43038,\n    \"ryce\": 43039,\n    \"ĠVG\": 43040,\n    \"Isn\": 43041,\n    \"ĠCyn\": 43042,\n    \"Expl\": 43043,\n    \"IRED\": 43044,\n    \"Ġcompr\": 43045,\n    \"Ġindisc\": 43046,\n    \"Boss\": 43047,\n    \"()\": 43048,\n    \"berman\": 43049,\n    \"ĠBegins\": 43050,\n    \"ujah\": 43051,\n    \"ornia\": 43052,\n    \"hetical\": 43053,\n    \"Ġcivilizations\": 43054,\n    \"Ġfundamentalist\": 43055,\n    \"strap\": 43056,\n    \"Forward\": 43057,\n    \"ettlement\": 43058,\n    \"Ġprophetic\": 43059,\n    \"glers\": 43060,\n    \"bending\": 43061,\n    \"Terry\": 43062,\n    \"Ġidi\": 43063,\n    \"Ġtrunc\": 43064,\n    \"Ġcreeps\": 43065,\n    \"intel\": 43066,\n    \"switch\": 43067,\n    \"ailand\": 43068,\n    \"Ġinstaller\": 43069,\n    \"GOP\": 43070,\n    \"Ġ499\": 43071,\n    \"ĠParallel\": 43072,\n    \"Cru\": 43073,\n    \"Ġ\\\"@\": 43074,\n    \"Ġ396\": 43075,\n    \"ĠUnlock\": 43076,\n    \"Raven\": 43077,\n    \"Corn\": 43078,\n    \"Ġcircadian\": 43079,\n    \"Ġ********************************\": 43080,\n    \"iliate\": 43081,\n    \"ĠFunctional\": 43082,\n    \"Ġpronouns\": 43083,\n    \"ĠSatoshi\": 43084,\n    \"Ġstim\": 43085,\n    \"Gay\": 43086,\n    \"Iss\": 43087,\n    \"ĠThief\": 43088,\n    \"atellite\": 43089,\n    \"Ġshards\": 43090,\n    \"Ġphil\": 43091,\n    \"protein\": 43092,\n    \"Ġalters\": 43093,\n    \"Poor\": 43094,\n    \"Typically\": 43095,\n    \"KER\": 43096,\n    \"ociate\": 43097,\n    \"Ġemits\": 43098,\n    \"recy\": 43099,\n    \"Ġmechanically\": 43100,\n    \"Ġ...\\\"\": 43101,\n    \"nature\": 43102,\n    \"sys\": 43103,\n    \"ysc\": 43104,\n    \"Ġwavelengths\": 43105,\n    \"pattern\": 43106,\n    \"insured\": 43107,\n    \"Ġparasitic\": 43108,\n    \"ĠLCS\": 43109,\n    \"ĠPACs\": 43110,\n    \"Ġheals\": 43111,\n    \"ĠCCP\": 43112,\n    \"ĠHacker\": 43113,\n    \"Ġpsy\": 43114,\n    \"ĠBeans\": 43115,\n    \"Ġdemonic\": 43116,\n    \"JV\": 43117,\n    \"Ġatmosp\": 43118,\n    \"equality\": 43119,\n    \"Ġairst\": 43120,\n    \"Ġincarn\": 43121,\n    \"ynthesis\": 43122,\n    \"Ġequations\": 43123,\n    \"tch\": 43124,\n    \"ĠHUGE\": 43125,\n    \"ĠChanged\": 43126,\n    \"itatively\": 43127,\n    \"Job\": 43128,\n    \"gaming\": 43129,\n    \"Ġ1899\": 43130,\n    \"ĠMorsi\": 43131,\n    \"Ġconjecture\": 43132,\n    \"riad\": 43133,\n    \"Ġprimates\": 43134,\n    \"ĠArtemis\": 43135,\n    \"ĠThro\": 43136,\n    \"Ġbiologically\": 43137,\n    \"Church\": 43138,\n    \"topia\": 43139,\n    \"recomm\": 43140,\n    \"Ġgradient\": 43141,\n    \"Ġful\": 43142,\n    \"Ġbastard\": 43143,\n    \"CHO\": 43144,\n    \"IUM\": 43145,\n    \"sleep\": 43146,\n    \"Construction\": 43147,\n    \"raints\": 43148,\n    \"vable\": 43149,\n    \"ionage\": 43150,\n    \"Ġcomrade\": 43151,\n    \"Ġpopulate\": 43152,\n    \"Ġnerds\": 43153,\n    \"ĠXie\": 43154,\n    \"result\": 43155,\n    \"ĠImper\": 43156,\n    \"Ġpamphlet\": 43157,\n    \"Ku\": 43158,\n    \"Ġbackend\": 43159,\n    \"ificent\": 43160,\n    \"etus\": 43161,\n    \"Ġdisson\": 43162,\n    \"config\": 43163,\n    \"Ġsuc\": 43164,\n    \"Ġwavelength\": 43165,\n    \"external\": 43166,\n    \"owder\": 43167,\n    \"Ġpredis\": 43168,\n    \"eenth\": 43169,\n    \"Det\": 43170,\n    \"andem\": 43171,\n    \"Ġ1865\": 43172,\n    \"ĠDefeat\": 43173,\n    \"Individual\": 43174,\n    \"Ġretrieving\": 43175,\n    \"stories\": 43176,\n    \"Ġdesolate\": 43177,\n    \"Ġlett\": 43178,\n    \"Ġunpublished\": 43179,\n    \"Ġpassively\": 43180,\n    \"Ġdissertation\": 43181,\n    \"raits\": 43182,\n    \"abee\": 43183,\n    \"ĠResist\": 43184,\n    \"Robin\": 43185,\n    \"Ġbenevolent\": 43186,\n    \"blast\": 43187,\n    \"Offic\": 43188,\n    \"snap\": 43189,\n    \"vernment\": 43190,\n    \"Ġextermin\": 43191,\n    \"wt\": 43192,\n    \"bitious\": 43193,\n    \"hibited\": 43194,\n    \"Insp\": 43195,\n    \"posted\": 43196,\n    \"ĠYugoslav\": 43197,\n    \"rational\": 43198,\n    \"adapt\": 43199,\n    \"ĠAtari\": 43200,\n    \"Ġplugin\": 43201,\n    \"oglobin\": 43202,\n    \"efeated\": 43203,\n    \"ĠHRC\": 43204,\n    \"cko\": 43205,\n    \"ilver\": 43206,\n    \"ĠDestruction\": 43207,\n    \"gewater\": 43208,\n    \"ĠRadiation\": 43209,\n    \"Ġimprison\": 43210,\n    \"origin\": 43211,\n    \"antine\": 43212,\n    \"ĠPublication\": 43213,\n    \"Ġhealer\": 43214,\n    \"istered\": 43215,\n    \"ĠTHEIR\": 43216,\n    \"hazard\": 43217,\n    \"Contract\": 43218,\n    \"Ġmediated\": 43219,\n    \"Ġindexed\": 43220,\n    \"ĠSYSTEM\": 43221,\n    \"Labor\": 43222,\n    \"Blade\": 43223,\n    \"Ġyog\": 43224,\n    \"Champ\": 43225,\n    \"Gordon\": 43226,\n    \"IAS\": 43227,\n    \"Ġnineteenth\": 43228,\n    \"animous\": 43229,\n    \"begin\": 43230,\n    \"ĠHolo\": 43231,\n    \"Planet\": 43232,\n    \"udding\": 43233,\n    \"default\": 43234,\n    \"ĠOMG\": 43235,\n    \"Ġwond\": 43236,\n    \"wm\": 43237,\n    \"pend\": 43238,\n    \"Extreme\": 43239,\n    \"Ġinterstellar\": 43240,\n    \"ASED\": 43241,\n    \"ĠBerks\": 43242,\n    \"Ġprimal\": 43243,\n    \"Foot\": 43244,\n    \"Ġinadvert\": 43245,\n    \"amboo\": 43246,\n    \"ĠLeica\": 43247,\n    \"Events\": 43248,\n    \"ĠPigs\": 43249,\n    \"RAFT\": 43250,\n    \"ï\": 43251,\n    \"ĠGentleman\": 43252,\n    \"Multiple\": 43253,\n    \"ĠPsychiatric\": 43254,\n    \"Ġdespise\": 43255,\n    \"ĠZionism\": 43256,\n    \"ĠSSL\": 43257,\n    \"shit\": 43258,\n    \"Ġthreaded\": 43259,\n    \"Ġartifact\": 43260,\n    \"Ġmitochondrial\": 43261,\n    \"ĠLayer\": 43262,\n    \"inus\": 43263,\n    \"podcast\": 43264,\n    \"Ġawaken\": 43265,\n    \"Management\": 43266,\n    \"Ġdelusions\": 43267,\n    \"grey\": 43268,\n    \"Ġpseud\": 43269,\n    \"agonal\": 43270,\n    \"ĠHirosh\": 43271,\n    \"Georg\": 43272,\n    \"Dragon\": 43273,\n    \"Stack\": 43274,\n    \"ohm\": 43275,\n    \"Ġvener\": 43276,\n    \"Row\": 43277,\n    \"Ġsandbox\": 43278,\n    \"Ġblinding\": 43279,\n    \"razen\": 43280,\n    \"Ġ389\": 43281,\n    \"Ġcrappy\": 43282,\n    \"Ġlith\": 43283,\n    \"antha\": 43284,\n    \"Ġplurality\": 43285,\n    \"ĠDAC\": 43286,\n    \"inently\": 43287,\n    \"intage\": 43288,\n    \"Ġ1902\": 43289,\n    \"ĠDepend\": 43290,\n    \"Ġelapsed\": 43291,\n    \"==\": 43292,\n    \"ĠGenie\": 43293,\n    \"Bush\": 43294,\n    \"ĠPlanetary\": 43295,\n    \"Bah\": 43296,\n    \"ĠKira\": 43297,\n    \"emn\": 43298,\n    \"Month\": 43299,\n    \"allic\": 43300,\n    \"coded\": 43301,\n    \"VOL\": 43302,\n    \"Ġ[...]\": 43303,\n    \"ĠRampage\": 43304,\n    \"Ġ(*\": 43305,\n    \"Production\": 43306,\n    \"licts\": 43307,\n    \"Ġinoc\": 43308,\n    \"Cour\": 43309,\n    \"Ġspurious\": 43310,\n    \"Ġultras\": 43311,\n    \"ggles\": 43312,\n    \"Ġdelusion\": 43313,\n    \"ĠRacer\": 43314,\n    \"ĠPrism\": 43315,\n    \"FH\": 43316,\n    \"uppet\": 43317,\n    \"Ġcultured\": 43318,\n    \"Ġ436\": 43319,\n    \"aneously\": 43320,\n    \"Ø§ÙĦ\": 43321,\n    \"ĠMissions\": 43322,\n    \"monton\": 43323,\n    \"criptions\": 43324,\n    \"ificate\": 43325,\n    \"Cause\": 43326,\n    \"Ġ1898\": 43327,\n    \"ocaust\": 43328,\n    \"Ġbri\": 43329,\n    \"ĠShoals\": 43330,\n    \"ommod\": 43331,\n    \"alted\": 43332,\n    \"ogenesis\": 43333,\n    \"warn\": 43334,\n    \"illus\": 43335,\n    \"vv\": 43336,\n    \"Ġcontam\": 43337,\n    \"ĠLesbian\": 43338,\n    \"Ġcavalry\": 43339,\n    \"ĠPresence\": 43340,\n    \"rehens\": 43341,\n    \"tool\": 43342,\n    \"accessible\": 43343,\n    \"Ġ(~\": 43344,\n    \"ĠLicensed\": 43345,\n    \"Ġprophets\": 43346,\n    \"Ġboulder\": 43347,\n    \"mean\": 43348,\n    \"akura\": 43349,\n    \"Ġunres\": 43350,\n    \"ĠCinnamon\": 43351,\n    \"Leaks\": 43352,\n    \"........................\": 43353,\n    \"Contact\": 43354,\n    \"Ġassassins\": 43355,\n    \"ĠGreenwald\": 43356,\n    \"dk\": 43357,\n    \"amazon\": 43358,\n    \"Ġagreeable\": 43359,\n    \"ernandez\": 43360,\n    \"Easy\": 43361,\n    \"PLA\": 43362,\n    \"ĠBigfoot\": 43363,\n    \"Ġconvent\": 43364,\n    \"Ġempires\": 43365,\n    \"Ġ387\": 43366,\n    \"Ġgrasped\": 43367,\n    \"Ġruby\": 43368,\n    \"Ġreconc\": 43369,\n    \"Warning\": 43370,\n    \"atem\": 43371,\n    \"Ġretrieval\": 43372,\n    \"ĠFDR\": 43373,\n    \"ĠReaper\": 43374,\n    \"orem\": 43375,\n    \"ĠLuo\": 43376,\n    \"hig\": 43377,\n    \"ĠArmor\": 43378,\n    \"tp\": 43379,\n    \"ĠInterpret\": 43380,\n    \"Conservative\": 43381,\n    \"ĠSodium\": 43382,\n    \"Ġbead\": 43383,\n    \"Ġpropagate\": 43384,\n    \"claw\": 43385,\n    \"href\": 43386,\n    \"ĠPaste\": 43387,\n    \"Ġomit\": 43388,\n    \"Boost\": 43389,\n    \"Diamond\": 43390,\n    \"goo\": 43391,\n    \"Ġanomal\": 43392,\n    \"ĠDISTRICT\": 43393,\n    \"Greek\": 43394,\n    \"warning\": 43395,\n    \"Ġdespised\": 43396,\n    \"Karl\": 43397,\n    \"AGES\": 43398,\n    \"Ġserotonin\": 43399,\n    \"ESSION\": 43400,\n    \"_______\": 43401,\n    \"ĠCollider\": 43402,\n    \"auldron\": 43403,\n    \"Ġsquee\": 43404,\n    \"Control\": 43405,\n    \"ffield\": 43406,\n    \"cycles\": 43407,\n    \"Legal\": 43408,\n    \"xa\": 43409,\n    \"minimum\": 43410,\n    \"ĠGeneric\": 43411,\n    \"Circ\": 43412,\n    \"Â·\": 43413,\n    \"Behind\": 43414,\n    \"guide\": 43415,\n    \"Ground\": 43416,\n    \"roying\": 43417,\n    \"ĠGrail\": 43418,\n    \"Ġthee\": 43419,\n    \"Ġ9000\": 43420,\n    \"Batman\": 43421,\n    \"Brother\": 43422,\n    \"Ġnons\": 43423,\n    \"RW\": 43424,\n    \"saf\": 43425,\n    \"ĠCroat\": 43426,\n    \"tainment\": 43427,\n    \"sci\": 43428,\n    \"Ye\": 43429,\n    \"Range\": 43430,\n    \"Ey\": 43431,\n    \"perature\": 43432,\n    \"ĠDracula\": 43433,\n    \"oreal\": 43434,\n    \"Fighting\": 43435,\n    \"Ġreleg\": 43436,\n    \"Ġcoupling\": 43437,\n    \"Tracker\": 43438,\n    \"tyard\": 43439,\n    \"Mut\": 43440,\n    \"Military\": 43441,\n    \"lamm\": 43442,\n    \"ittens\": 43443,\n    \"ĠCRC\": 43444,\n    \"ĠXiang\": 43445,\n    \"Ġorthodoxy\": 43446,\n    \"ĠGoth\": 43447,\n    \"Ġalgorith\": 43448,\n    \"ĠAthen\": 43449,\n    \"Ġtyrann\": 43450,\n    \"ĠTorrent\": 43451,\n    \"IDs\": 43452,\n    \"ĠGENERAL\": 43453,\n    \"ĠASUS\": 43454,\n    \"rastructure\": 43455,\n    \"Faith\": 43456,\n    \"models\": 43457,\n    \"rentices\": 43458,\n    \"ĠCurse\": 43459,\n    \"Ġcalibr\": 43460,\n    \"attled\": 43461,\n    \"monary\": 43462,\n    \"Ġpenet\": 43463,\n    \"aclysm\": 43464,\n    \"album\": 43465,\n    \"Ġremnant\": 43466,\n    \"Ġfung\": 43467,\n    \"itiveness\": 43468,\n    \"thodox\": 43469,\n    \"Ġunlocks\": 43470,\n    \"Ġprobabilities\": 43471,\n    \"Ġster\": 43472,\n    \"Ġscrim\": 43473,\n    \"Ġanalytic\": 43474,\n    \"Urban\": 43475,\n    \"âĢĶâĢĶâĢĶâĢĶ\": 43476,\n    \"Craft\": 43477,\n    \"Ġbrut\": 43478,\n    \"1986\": 43479,\n    \"Section\": 43480,\n    \"raged\": 43481,\n    \"arij\": 43482,\n    \"Hero\": 43483,\n    \"ĠHebdo\": 43484,\n    \"ĠEmpress\": 43485,\n    \"Ġvivo\": 43486,\n    \"ĠPublications\": 43487,\n    \"Ġcannabinoids\": 43488,\n    \"arrett\": 43489,\n    \"Ġbounded\": 43490,\n    \"Ġquests\": 43491,\n    \"Ġomin\": 43492,\n    \"ĠRuler\": 43493,\n    \"ĠYue\": 43494,\n    \"ridges\": 43495,\n    \"Ġpeasants\": 43496,\n    \"ĠAlloy\": 43497,\n    \"Desk\": 43498,\n    \"ULAR\": 43499,\n    \"Ġthor\": 43500,\n    \"ĠOvers\": 43501,\n    \"ĠTome\": 43502,\n    \"mk\": 43503,\n    \"Ġ1050\": 43504,\n    \"Ġshroud\": 43505,\n    \"Ġdistribut\": 43506,\n    \"weapons\": 43507,\n    \"ĠAuthorization\": 43508,\n    \"ĠPoke\": 43509,\n    \"ĠAlternate\": 43510,\n    \"scan\": 43511,\n    \"artisan\": 43512,\n    \"ĠGems\": 43513,\n    \"ĠForums\": 43514,\n    \"atonin\": 43515,\n    \"viron\": 43516,\n    \"Rog\": 43517,\n    \"duct\": 43518,\n    \"Ġtabletop\": 43519,\n    \"crow\": 43520,\n    \"/)\": 43521,\n    \"ĠStainless\": 43522,\n    \"ottest\": 43523,\n    \"Ġreborn\": 43524,\n    \"anchez\": 43525,\n    \"cium\": 43526,\n    \"ĠNicarag\": 43527,\n    \"elfare\": 43528,\n    \"Ġupd\": 43529,\n    \"ritic\": 43530,\n    \"bm\": 43531,\n    \"Ġ608\": 43532,\n    \"ĠSlightly\": 43533,\n    \"ĠDrops\": 43534,\n    \"ISO\": 43535,\n    \"ĠiT\": 43536,\n    \"xiety\": 43537,\n    \"ĠGawker\": 43538,\n    \"omination\": 43539,\n    \"ĠReached\": 43540,\n    \"Student\": 43541,\n    \"Drop\": 43542,\n    \"MET\": 43543,\n    \"ĠKubrick\": 43544,\n    \"1950\": 43545,\n    \"ĠTuls\": 43546,\n    \"Ġcomputed\": 43547,\n    \"depending\": 43548,\n    \"ĠCosmetic\": 43549,\n    \"udget\": 43550,\n    \"Lex\": 43551,\n    \"icut\": 43552,\n    \"ĠDepth\": 43553,\n    \"Ġ1893\": 43554,\n    \"ahah\": 43555,\n    \"Ġath\": 43556,\n    \"fights\": 43557,\n    \"thia\": 43558,\n    \"Ġoccult\": 43559,\n    \"Wheel\": 43560,\n    \"ĠSega\": 43561,\n    \"Ġtheolog\": 43562,\n    \"reement\": 43563,\n    \")--\": 43564,\n    \"Ġunus\": 43565,\n    \"ĠGamma\": 43566,\n    \"Looks\": 43567,\n    \"Ġellipt\": 43568,\n    \"Ġairflow\": 43569,\n    \"ĠHimself\": 43570,\n    \"Ġpagan\": 43571,\n    \"ĠRei\": 43572,\n    \"Ġpilgr\": 43573,\n    \"ĠSubmission\": 43574,\n    \"Region\": 43575,\n    \"Ġinsertion\": 43576,\n    \"Ġsket\": 43577,\n    \"Ġsatisfies\": 43578,\n    \"ĠPixie\": 43579,\n    \"Ġcontempl\": 43580,\n    \"abbit\": 43581,\n    \"ĠReplay\": 43582,\n    \"ĠGalile\": 43583,\n    \"ĠGodzilla\": 43584,\n    \"Ġarithmetic\": 43585,\n    \"iasm\": 43586,\n    \"1987\": 43587,\n    \"ĠFeminist\": 43588,\n    \"Liter\": 43589,\n    \"ĠDisable\": 43590,\n    \"ouble\": 43591,\n    \"essors\": 43592,\n    \"Ġfors\": 43593,\n    \"Ġensu\": 43594,\n    \"Putting\": 43595,\n    \"ĠMSM\": 43596,\n    \"Cond\": 43597,\n    \"emade\": 43598,\n    \"Ġindistinguishable\": 43599,\n    \"Magn\": 43600,\n    \"Ġms\": 43601,\n    \"MAL\": 43602,\n    \"ĠBF\": 43603,\n    \"dm\": 43604,\n    \"iltration\": 43605,\n    \"irection\": 43606,\n    \"ĠSpir\": 43607,\n    \"Gb\": 43608,\n    \"ĠIbn\": 43609,\n    \"Abs\": 43610,\n    \"imens\": 43611,\n    \"RNA\": 43612,\n    \"============\": 43613,\n    \"Ġ655\": 43614,\n    \"ĠConversion\": 43615,\n    \"imilation\": 43616,\n    \"igion\": 43617,\n    \"ĠSomew\": 43618,\n    \"mL\": 43619,\n    \"Border\": 43620,\n    \"Ë\": 43621,\n    \"Factor\": 43622,\n    \"Number\": 43623,\n    \"Ġejac\": 43624,\n    \"Cho\": 43625,\n    \"Ġrighteousness\": 43626,\n    \"ĠPATH\": 43627,\n    \"ĠElys\": 43628,\n    \"ouched\": 43629,\n    \"Ġmultic\": 43630,\n    \"Ġfaculties\": 43631,\n    \"ĠEarthquake\": 43632,\n    \"ĠReferences\": 43633,\n    \"ensitive\": 43634,\n    \"Ġimpat\": 43635,\n    \"Ġ................\": 43636,\n    \"buff\": 43637,\n    \"Ġ1895\": 43638,\n    \"colo\": 43639,\n    \"Vi\": 43640,\n    \"Ġubiqu\": 43641,\n    \"ĠChev\": 43642,\n    \"Fish\": 43643,\n    \"ĠBlueprint\": 43644,\n    \"CHQ\": 43645,\n    \"Ġlinem\": 43646,\n    \"ĠFlavor\": 43647,\n    \"Ġcrimson\": 43648,\n    \"ĠAbstract\": 43649,\n    \"arette\": 43650,\n    \"plete\": 43651,\n    \"ranean\": 43652,\n    \"Dash\": 43653,\n    \"Ġdimensional\": 43654,\n    \"Cub\": 43655,\n    \"ttle\": 43656,\n    \"ĠDSM\": 43657,\n    \"Ġinstantaneous\": 43658,\n    \"esy\": 43659,\n    \"Ġepoch\": 43660,\n    \"Brit\": 43661,\n    \"ĠÎ\": 43662,\n    \"ECD\": 43663,\n    \"Ġwarp\": 43664,\n    \"obyl\": 43665,\n    \"ubric\": 43666,\n    \"Ġutilitarian\": 43667,\n    \"Ġsummarizes\": 43668,\n    \"letal\": 43669,\n    \"Ord\": 43670,\n    \"opath\": 43671,\n    \"tained\": 43672,\n    \"ghai\": 43673,\n    \"Ġwhis\": 43674,\n    \"insert\": 43675,\n    \"Ġphon\": 43676,\n    \"rils\": 43677,\n    \"Ġearthly\": 43678,\n    \"ĠAlic\": 43679,\n    \"ĠPCIe\": 43680,\n    \"Ġfurthermore\": 43681,\n    \"ocard\": 43682,\n    \"Ġuter\": 43683,\n    \"ĠAdmin\": 43684,\n    \"ographics\": 43685,\n    \"ĠConstantin\": 43686,\n    \"gravity\": 43687,\n    \"iPhone\": 43688,\n    \"Ġwasteland\": 43689,\n    \"Ġfps\": 43690,\n    \"Tip\": 43691,\n    \"Ġmurm\": 43692,\n    \"paces\": 43693,\n    \"ĠSamurai\": 43694,\n    \"ĠFOIA\": 43695,\n    \"ĠRadiant\": 43696,\n    \"ĠUnreal\": 43697,\n    \"Ġmicrow\": 43698,\n    \"usterity\": 43699,\n    \"zyme\": 43700,\n    \"itbart\": 43701,\n    \"metadata\": 43702,\n    \"Dat\": 43703,\n    \"ĠMoons\": 43704,\n    \"ĠProtestants\": 43705,\n    \"ungle\": 43706,\n    \"Ġvideog\": 43707,\n    \"pid\": 43708,\n    \"Ġdisple\": 43709,\n    \"aucus\": 43710,\n    \"Ġcoils\": 43711,\n    \"ĠDwar\": 43712,\n    \"fixed\": 43713,\n    \"Alice\": 43714,\n    \"Ġgarrison\": 43715,\n    \"ĠVelocity\": 43716,\n    \"ĠJehovah\": 43717,\n    \"Ġfascists\": 43718,\n    \"ĠCHO\": 43719,\n    \"jl\": 43720,\n    \"Ġmetaphors\": 43721,\n    \"ĠSiege\": 43722,\n    \"scientific\": 43723,\n    \"Ä«\": 43724,\n    \"Slow\": 43725,\n    \"hex\": 43726,\n    \"ĠBlaz\": 43727,\n    \"mediated\": 43728,\n    \"esthesia\": 43729,\n    \"ĠAvg\": 43730,\n    \"Ġbelie\": 43731,\n    \"Carter\": 43732,\n    \"Ġexposition\": 43733,\n    \"azeera\": 43734,\n    \"dial\": 43735,\n    \"Ġbask\": 43736,\n    \"Scale\": 43737,\n    \"Ġdisob\": 43738,\n    \"Ġgore\": 43739,\n    \"Ġhypocr\": 43740,\n    \"Ġphantom\": 43741,\n    \"ĠSynd\": 43742,\n    \"BLIC\": 43743,\n    \"pter\": 43744,\n    \"ĠScorpion\": 43745,\n    \"eor\": 43746,\n    \"ĠRecover\": 43747,\n    \"Ġsummoning\": 43748,\n    \"Ġorb\": 43749,\n    \"jump\": 43750,\n    \"Ġ768\": 43751,\n    \"ĠEnix\": 43752,\n    \"Spons\": 43753,\n    \",...\": 43754,\n    \"Wide\": 43755,\n    \"Ġparse\": 43756,\n    \"Ġdebtor\": 43757,\n    \"Ġpathological\": 43758,\n    \"Ġserpent\": 43759,\n    \"ĠFranÃ§\": 43760,\n    \"reetings\": 43761,\n    \"Ġdeletion\": 43762,\n    \"Ġvolunt\": 43763,\n    \"ĠNotification\": 43764,\n    \"liga\": 43765,\n    \"Disk\": 43766,\n    \"Account\": 43767,\n    \"1979\": 43768,\n    \"Ġsymmetry\": 43769,\n    \"ĠBearing\": 43770,\n    \"ĠABV\": 43771,\n    \"ĠORDER\": 43772,\n    \"rpm\": 43773,\n    \"ĠFuck\": 43774,\n    \"?!\\\"\": 43775,\n    \"mask\": 43776,\n    \"Grade\": 43777,\n    \"neath\": 43778,\n    \"ocom\": 43779,\n    \"Detect\": 43780,\n    \"ryption\": 43781,\n    \"ĠAura\": 43782,\n    \"Ġinert\": 43783,\n    \"PLAY\": 43784,\n    \"gres\": 43785,\n    \"INTON\": 43786,\n    \"Deal\": 43787,\n    \"fficient\": 43788,\n    \"ĠVoid\": 43789,\n    \"gement\": 43790,\n    \"Ġscorp\": 43791,\n    \"Ġreincarn\": 43792,\n    \"ĠVapor\": 43793,\n    \"Ġ1840\": 43794,\n    \"Yellow\": 43795,\n    \"......\": 43796,\n    \"Ġparameter\": 43797,\n    \"ĠDISTR\": 43798,\n    \"ĠForgotten\": 43799,\n    \"Eat\": 43800,\n    \"izational\": 43801,\n    \"Witness\": 43802,\n    \"ĠDupl\": 43803,\n    \"Ġdogma\": 43804,\n    \"Ġzipper\": 43805,\n    \"ĠZeus\": 43806,\n    \"mage\": 43807,\n    \"ormal\": 43808,\n    \"Ġ\\\".\": 43809,\n    \"Ġecc\": 43810,\n    \"ĠSlot\": 43811,\n    \"ĠRegist\": 43812,\n    \"Others\": 43813,\n    \"VID\": 43814,\n    \"Windows\": 43815,\n    \"Ġshitty\": 43816,\n    \"ĠLethal\": 43817,\n    \"Monster\": 43818,\n    \"ĠExpression\": 43819,\n    \"tx\": 43820,\n    \"ythm\": 43821,\n    \"Were\": 43822,\n    \"ivalry\": 43823,\n    \"atcher\": 43824,\n    \"ĠFormat\": 43825,\n    \"ĠPlasma\": 43826,\n    \"Phys\": 43827,\n    \"laugh\": 43828,\n    \"Fu\": 43829,\n    \"java\": 43830,\n    \"roma\": 43831,\n    \"ĠIncreases\": 43832,\n    \"Ġlicensee\": 43833,\n    \"Ġmystic\": 43834,\n    \"Ġproto\": 43835,\n    \"ĠLoki\": 43836,\n    \"forcing\": 43837,\n    \"hots\": 43838,\n    \"Ġ->\": 43839,\n    \"Outside\": 43840,\n    \"ĠEndless\": 43841,\n    \"Ġachie\": 43842,\n    \"ĠTurtles\": 43843,\n    \"Ġconvin\": 43844,\n    \"JUST\": 43845,\n    \"Ġimmobil\": 43846,\n    \"ĠCauses\": 43847,\n    \"Ġclich\": 43848,\n    \"xes\": 43849,\n    \"ffiti\": 43850,\n    \"Ġhypot\": 43851,\n    \"Bat\": 43852,\n    \"Ġbigot\": 43853,\n    \"Personal\": 43854,\n    \"ĠPharmac\": 43855,\n    \"Lot\": 43856,\n    \"VERT\": 43857,\n    \"Ġbapt\": 43858,\n    \"idelines\": 43859,\n    \"Ġprox\": 43860,\n    \"MAP\": 43861,\n    \"Spirit\": 43862,\n    \"ĠSlug\": 43863,\n    \"Ġebook\": 43864,\n    \"eches\": 43865,\n    \"ĠAndromeda\": 43866,\n    \"Ġceremon\": 43867,\n    \"1975\": 43868,\n    \"PRE\": 43869,\n    \"Ġasshole\": 43870,\n    \"linear\": 43871,\n    \"Nevertheless\": 43872,\n    \"Ġwillpower\": 43873,\n    \"azel\": 43874,\n    \"Fif\": 43875,\n    \"andise\": 43876,\n    \"Ġextravag\": 43877,\n    \"ĠBuffy\": 43878,\n    \"Ġcorrelations\": 43879,\n    \"ptr\": 43880,\n    \"Progress\": 43881,\n    \"shape\": 43882,\n    \"ĠSymbol\": 43883,\n    \"arag\": 43884,\n    \"ĠContext\": 43885,\n    \"ucer\": 43886,\n    \"1983\": 43887,\n    \"ĠMyster\": 43888,\n    \"Pain\": 43889,\n    \"Login\": 43890,\n    \"mbol\": 43891,\n    \"codes\": 43892,\n    \"RANT\": 43893,\n    \"Ġoverse\": 43894,\n    \"opot\": 43895,\n    \"STEM\": 43896,\n    \"enser\": 43897,\n    \"ĠCosmic\": 43898,\n    \"Spl\": 43899,\n    \"ritional\": 43900,\n    \"ĠPharaoh\": 43901,\n    \"ĠRemix\": 43902,\n    \"xon\": 43903,\n    \"ĠXII\": 43904,\n    \"Ġunman\": 43905,\n    \"Ġimmedi\": 43906,\n    \"Ġmonog\": 43907,\n    \"ĠLX\": 43908,\n    \"Ġabstraction\": 43909,\n    \"ocolate\": 43910,\n    \"ĠDonkey\": 43911,\n    \"Ġ!!\": 43912,\n    \"ĠLIA\": 43913,\n    \"shed\": 43914,\n    \"rules\": 43915,\n    \"Ġcalc\": 43916,\n    \"ĠAutob\": 43917,\n    \"anmar\": 43918,\n    \"eworks\": 43919,\n    \"notations\": 43920,\n    \"Ġtenancy\": 43921,\n    \"ĠPetraeus\": 43922,\n    \"dp\": 43923,\n    \"amphetamine\": 43924,\n    \"ĠCortex\": 43925,\n    \"rw\": 43926,\n    \"Ġprojectile\": 43927,\n    \"Ġintrinsically\": 43928,\n    \"Route\": 43929,\n    \"Ġnegoti\": 43930,\n    \"anuts\": 43931,\n    \"Analysis\": 43932,\n    \"redits\": 43933,\n    \"ĠGG\": 43934,\n    \"thread\": 43935,\n    \"ĠChosen\": 43936,\n    \"Years\": 43937,\n    \"otyp\": 43938,\n    \"ĠNCT\": 43939,\n    \"udic\": 43940,\n    \"ochemical\": 43941,\n    \"Neigh\": 43942,\n    \"Ġfishes\": 43943,\n    \"ĠFloat\": 43944,\n    \"Print\": 43945,\n    \"okia\": 43946,\n    \"Ġbarb\": 43947,\n    \"quote\": 43948,\n    \"Lew\": 43949,\n    \"Ġannoun\": 43950,\n    \"istors\": 43951,\n    \"Reading\": 43952,\n    \"ACTION\": 43953,\n    \"Ġintakes\": 43954,\n    \"ĠBeet\": 43955,\n    \"matter\": 43956,\n    \"Swe\": 43957,\n    \"Ther\": 43958,\n    \"Ġtyrant\": 43959,\n    \"ĠPsycho\": 43960,\n    \"ĠDestroy\": 43961,\n    \"Ġesoteric\": 43962,\n    \"Ġbiom\": 43963,\n    \"idious\": 43964,\n    \"Merc\": 43965,\n    \"hran\": 43966,\n    \"ĠBaal\": 43967,\n    \"seconds\": 43968,\n    \"Ġsuperhuman\": 43969,\n    \"ancel\": 43970,\n    \"Ġworshipped\": 43971,\n    \"Ġwebs\": 43972,\n    \"Ġviolet\": 43973,\n    \"ĠMetallic\": 43974,\n    \"eday\": 43975,\n    \"ordering\": 43976,\n    \"Nut\": 43977,\n    \"Ġconstructs\": 43978,\n    \"olescent\": 43979,\n    \"Unit\": 43980,\n    \"otypes\": 43981,\n    \"Ġembryonic\": 43982,\n    \"perm\": 43983,\n    \"Nature\": 43984,\n    \"ĠDecre\": 43985,\n    \"levant\": 43986,\n    \"Ġss\": 43987,\n    \"+(\": 43988,\n    \"ĠDoctrine\": 43989,\n    \"puters\": 43990,\n    \"Ġsaline\": 43991,\n    \"orsche\": 43992,\n    \"1111\": 43993,\n    \"values\": 43994,\n    \"Ġutopian\": 43995,\n    \"ĠBooster\": 43996,\n    \"Technical\": 43997,\n    \"ì\": 43998,\n    \"ĠLIMITED\": 43999,\n    \"nir\": 44000,\n    \"Ġclones\": 44001,\n    \"Performance\": 44002,\n    \"aple\": 44003,\n    \"Ġshudder\": 44004,\n    \"Ġcontempor\": 44005,\n    \"lator\": 44006,\n    \"ĠOops\": 44007,\n    \"Ġammon\": 44008,\n    \"Ġdavid\": 44009,\n    \"Ġbom\": 44010,\n    \"bish\": 44011,\n    \"Ġdetectable\": 44012,\n    \"Ġmultiplying\": 44013,\n    \"Ġreddit\": 44014,\n    \"Prim\": 44015,\n    \"Ġmedial\": 44016,\n    \"Ġsubstrate\": 44017,\n    \"ĠSanskrit\": 44018,\n    \"Spect\": 44019,\n    \"ĠMagical\": 44020,\n    \"Ġarcane\": 44021,\n    \"align\": 44022,\n    \"Ġ1861\": 44023,\n    \"Ġneocons\": 44024,\n    \"Ì\": 44025,\n    \"ĠBounty\": 44026,\n    \"ĠContinent\": 44027,\n    \"Ġhurd\": 44028,\n    \"alions\": 44029,\n    \"Ġgeneralized\": 44030,\n    \"ĠInsect\": 44031,\n    \"Ġsimul\": 44032,\n    \"actual\": 44033,\n    \"advert\": 44034,\n    \"ukong\": 44035,\n    \"Resp\": 44036,\n    \"ĠWarcraft\": 44037,\n    \"Hunter\": 44038,\n    \"hyper\": 44039,\n    \"ĠBreach\": 44040,\n    \"ught\": 44041,\n    \"Ġcomputation\": 44042,\n    \"react\": 44043,\n    \"Feel\": 44044,\n    \"ĠCheong\": 44045,\n    \"Ġslut\": 44046,\n    \"Ġgalactic\": 44047,\n    \"Ġtaunt\": 44048,\n    \"Enjoy\": 44049,\n    \"Ġreprinted\": 44050,\n    \"Word\": 44051,\n    \"ĠHandbook\": 44052,\n    \"amins\": 44053,\n    \"exit\": 44054,\n    \"Wo\": 44055,\n    \"Ġadherents\": 44056,\n    \"Counter\": 44057,\n    \"ĠNode\": 44058,\n    \"ĠTwisted\": 44059,\n    \"Ġgrinned\": 44060,\n    \"universal\": 44061,\n    \"ĠAmon\": 44062,\n    \"Ġaster\": 44063,\n    \"ĠEquip\": 44064,\n    \"!\\\".\": 44065,\n    \"Ġanalogous\": 44066,\n    \"rients\": 44067,\n    \"alky\": 44068,\n    \"ĠQian\": 44069,\n    \"Ġspont\": 44070,\n    \"docs\": 44071,\n    \"Ġcontemplation\": 44072,\n    \"Ġrevolutionaries\": 44073,\n    \"Ġpreset\": 44074,\n    \"ĠAmendments\": 44075,\n    \"Ġexecutes\": 44076,\n    \"ĠDuration\": 44077,\n    \"Ġcompulsion\": 44078,\n    \"Ġstagger\": 44079,\n    \"ynamic\": 44080,\n    \"blem\": 44081,\n    \"];\": 44082,\n    \"Higher\": 44083,\n    \"Balt\": 44084,\n    \"heast\": 44085,\n    \"Ġcorp\": 44086,\n    \"awei\": 44087,\n    \"Motion\": 44088,\n    \"Mis\": 44089,\n    \"Ġadventurer\": 44090,\n    \"eger\": 44091,\n    \"Ġarsen\": 44092,\n    \"ĠVoltage\": 44093,\n    \"ĠEVENTS\": 44094,\n    \"Salt\": 44095,\n    \"issance\": 44096,\n    \"DK\": 44097,\n    \"Ship\": 44098,\n    \"Ġunwitting\": 44099,\n    \"Ton\": 44100,\n    \"ĠPROGRAM\": 44101,\n    \"Ġtentacles\": 44102,\n    \"erness\": 44103,\n    \"thirst\": 44104,\n    \"Fig\": 44105,\n    \"fty\": 44106,\n    \"ĠTolkien\": 44107,\n    \"Sleep\": 44108,\n    \"ĠExplain\": 44109,\n    \"Pub\": 44110,\n    \"ĠBounce\": 44111,\n    \"ĠDemo\": 44112,\n    \"Ġ1897\": 44113,\n    \"ĠSPI\": 44114,\n    \"intern\": 44115,\n    \"********\": 44116,\n    \"ĠKills\": 44117,\n    \"ĠZombies\": 44118,\n    \"Single\": 44119,\n    \"ratom\": 44120,\n    \"ĠClaw\": 44121,\n    \"hid\": 44122,\n    \"asel\": 44123,\n    \"Shock\": 44124,\n    \"erential\": 44125,\n    \"Ġupgr\": 44126,\n    \"holy\": 44127,\n    \"Ġ\\\\\": 44128,\n    \"aghetti\": 44129,\n    \"Ġthence\": 44130,\n    \"genic\": 44131,\n    \"papers\": 44132,\n    \"1982\": 44133,\n    \"ravel\": 44134,\n    \"ĠUNIVERS\": 44135,\n    \"Charge\": 44136,\n    \"ĠDelay\": 44137,\n    \"ibrary\": 44138,\n    \"ĠHDD\": 44139,\n    \"olson\": 44140,\n    \"Ġenchanted\": 44141,\n    \"Wr\": 44142,\n    \"graph\": 44143,\n    \"Ġcorro\": 44144,\n    \"ept\": 44145,\n    \"etsu\": 44146,\n    \"ĠQin\": 44147,\n    \"Û\": 44148,\n    \"Ġantidepressant\": 44149,\n    \"ĠCerberus\": 44150,\n    \"Ġappe\": 44151,\n    \"ĠDEFENSE\": 44152,\n    \"Ġdysph\": 44153,\n    \"split\": 44154,\n    \"zilla\": 44155,\n    \"attr\": 44156,\n    \"Clar\": 44157,\n    \"Äĵ\": 44158,\n    \"hov\": 44159,\n    \"IRC\": 44160,\n    \"hibition\": 44161,\n    \"'/\": 44162,\n    \"ĠURLs\": 44163,\n    \"Draft\": 44164,\n    \"Prep\": 44165,\n    \"ĠLanguages\": 44166,\n    \"ĠTravels\": 44167,\n    \"ceiver\": 44168,\n    \"aturally\": 44169,\n    \"pair\": 44170,\n    \"ĠALWAYS\": 44171,\n    \"aaaa\": 44172,\n    \"ĠTenth\": 44173,\n    \"ĠNAD\": 44174,\n    \"Serv\": 44175,\n    \"ĠUID\": 44176,\n    \"cens\": 44177,\n    \"ĠLearned\": 44178,\n    \"Ġtraject\": 44179,\n    \"Ġmoaning\": 44180,\n    \"ĠNare\": 44181,\n    \"Ġingen\": 44182,\n    \"Ġsurn\": 44183,\n    \"Ġfloppy\": 44184,\n    \"breeding\": 44185,\n    \"uph\": 44186,\n    \"rossover\": 44187,\n    \"Understanding\": 44188,\n    \"Glass\": 44189,\n    \"Ġruntime\": 44190,\n    \"gp\": 44191,\n    \"Ġâľĵ\": 44192,\n    \"Ġcyt\": 44193,\n    \"bley\": 44194,\n    \"agall\": 44195,\n    \"Ġunworthy\": 44196,\n    \"otine\": 44197,\n    \"Ġchromosome\": 44198,\n    \"utters\": 44199,\n    \"ĠÂµ\": 44200,\n    \"Ġexpans\": 44201,\n    \"Ġdement\": 44202,\n    \"Ġinsurrection\": 44203,\n    \"Ġsurviv\": 44204,\n    \"genre\": 44205,\n    \"ospital\": 44206,\n    \"ĠPlato\": 44207,\n    \"ĠTrigger\": 44208,\n    \"selection\": 44209,\n    \"ilege\": 44210,\n    \"Ġsegreg\": 44211,\n    \"itizens\": 44212,\n    \"ĠRAID\": 44213,\n    \"Pure\": 44214,\n    \"hetti\": 44215,\n    \"ĠFailed\": 44216,\n    \"ĠCharacters\": 44217,\n    \"ĠCreep\": 44218,\n    \"akra\": 44219,\n    \"Ec\": 44220,\n    \"ĠAristotle\": 44221,\n    \"Lim\": 44222,\n    \"error\": 44223,\n    \"yrus\": 44224,\n    \"umably\": 44225,\n    \">>\": 44226,\n    \"Ġtsun\": 44227,\n    \"knowledge\": 44228,\n    \"Cert\": 44229,\n    \"bable\": 44230,\n    \"hesion\": 44231,\n    \"ĠProcedures\": 44232,\n    \"Ġmarkup\": 44233,\n    \"ideo\": 44234,\n    \"Ġrhet\": 44235,\n    \"ĠChapters\": 44236,\n    \"ĠChecking\": 44237,\n    \"mega\": 44238,\n    \"Ġphotons\": 44239,\n    \"required\": 44240,\n    \"Unknown\": 44241,\n    \"ĠDrawn\": 44242,\n    \"Ġvari\": 44243,\n    \"EEK\": 44244,\n    \"Ġcompuls\": 44245,\n    \"Ġcloning\": 44246,\n    \"ccoli\": 44247,\n    \"Ġ1070\": 44248,\n    \"Ġkindred\": 44249,\n    \"Ġdiscl\": 44250,\n    \"ĠCind\": 44251,\n    \"Collect\": 44252,\n    \"Ġchromosomes\": 44253,\n    \"phant\": 44254,\n    \"ĠKafka\": 44255,\n    \"Ġeverlasting\": 44256,\n    \"Ġmercenary\": 44257,\n    \"ĠHmm\": 44258,\n    \"----\": 44259,\n    \"riber\": 44260,\n    \"Ġdoubtless\": 44261,\n    \"Ġsusceptibility\": 44262,\n    \"beta\": 44263,\n    \"notice\": 44264,\n    \"Ġcrochet\": 44265,\n    \"Ġrespir\": 44266,\n    \"Ġphilosophers\": 44267,\n    \"ĠExtras\": 44268,\n    \"Ġseparat\": 44269,\n    \"shown\": 44270,\n    \"iblings\": 44271,\n    \"Hispanic\": 44272,\n    \"copy\": 44273,\n    \"Tang\": 44274,\n    \"Knight\": 44275,\n    \"Ġpursu\": 44276,\n    \"ĠAnime\": 44277,\n    \"Ġlipid\": 44278,\n    \"ggies\": 44279,\n    \"levels\": 44280,\n    \"phalt\": 44281,\n    \"ĠCompleted\": 44282,\n    \"bral\": 44283,\n    \"Ġcerv\": 44284,\n    \"ĠAfric\": 44285,\n    \"ĠPhar\": 44286,\n    \"Color\": 44287,\n    \"ogene\": 44288,\n    \"ĠCompan\": 44289,\n    \"memory\": 44290,\n    \"Dust\": 44291,\n    \"ĠXIV\": 44292,\n    \"ĠConsole\": 44293,\n    \"').\": 44294,\n    \"Ġ1888\": 44295,\n    \"byn\": 44296,\n    \"Ġpolygamy\": 44297,\n    \"Auth\": 44298,\n    \"BUT\": 44299,\n    \"istine\": 44300,\n    \"Ġsacr\": 44301,\n    \"Ġabsor\": 44302,\n    \"ijah\": 44303,\n    \"ĠNeural\": 44304,\n    \"olester\": 44305,\n    \"ql\": 44306,\n    \"Already\": 44307,\n    \"Creating\": 44308,\n    \"ĠStarg\": 44309,\n    \"ĠPhilos\": 44310,\n    \"Consider\": 44311,\n    \"Ġrepositories\": 44312,\n    \"cludes\": 44313,\n    \"ĠBuffer\": 44314,\n    \"ĠPerspect\": 44315,\n    \"Ġcomput\": 44316,\n    \"Stew\": 44317,\n    \"iamond\": 44318,\n    \"ĠJudgment\": 44319,\n    \"OVA\": 44320,\n    \"angible\": 44321,\n    \"Ġoxid\": 44322,\n    \"Ġepigen\": 44323,\n    \"Ġsidel\": 44324,\n    \"ĠEag\": 44325,\n    \"devices\": 44326,\n    \"icone\": 44327,\n    \"1920\": 44328,\n    \"atism\": 44329,\n    \"beard\": 44330,\n    \"ĠGujar\": 44331,\n    \"ĠPlaystation\": 44332,\n    \"Ġglances\": 44333,\n    \"ĠCOMPLE\": 44334,\n    \"VERTIS\": 44335,\n    \"ukemia\": 44336,\n    \"Edit\": 44337,\n    \"Tickets\": 44338,\n    \"Square\": 44339,\n    \"ĠSerpent\": 44340,\n    \"Ġtransporter\": 44341,\n    \"MQ\": 44342,\n    \"ĠMongo\": 44343,\n    \"1967\": 44344,\n    \"ibaba\": 44345,\n    \"Ġtimet\": 44346,\n    \"sylvania\": 44347,\n    \"Latin\": 44348,\n    \"osaurs\": 44349,\n    \"Ġhumanoid\": 44350,\n    \"Ġcannabinoid\": 44351,\n    \"Ġdisciple\": 44352,\n    \"Psych\": 44353,\n    \"Ġimpro\": 44354,\n    \"Ġmc\": 44355,\n    \"Raid\": 44356,\n    \"Letter\": 44357,\n    \"ificant\": 44358,\n    \"ĠPortug\": 44359,\n    \"ĠFreem\": 44360,\n    \"Ġappell\": 44361,\n    \"ĠMushroom\": 44362,\n    \"Ġclans\": 44363,\n    \"Ġsinful\": 44364,\n    \"Ġingestion\": 44365,\n    \"ĠDirectory\": 44366,\n    \"abetic\": 44367,\n    \"Ġantigen\": 44368,\n    \"Ġimagin\": 44369,\n    \"mitter\": 44370,\n    \"!!!!!\": 44371,\n    \"ĠDPR\": 44372,\n    \"leness\": 44373,\n    \"\\\":\\\"\\\",\\\"\": 44374,\n    \"ĠAUTHOR\": 44375,\n    \"Ġgrunt\": 44376,\n    \"Ġflickering\": 44377,\n    \"Cath\": 44378,\n    \"asury\": 44379,\n    \"Ġnozzle\": 44380,\n    \"Secure\": 44381,\n    \"Stre\": 44382,\n    \"ĠBIT\": 44383,\n    \"Ġdeviations\": 44384,\n    \"Professor\": 44385,\n    \"bilt\": 44386,\n    \"ĠConscious\": 44387,\n    \"Ġinterrupts\": 44388,\n    \"ĠMormons\": 44389,\n    \"ĠCutter\": 44390,\n    \"Bed\": 44391,\n    \"ipient\": 44392,\n    \"ĠGhostbusters\": 44393,\n    \"Cart\": 44394,\n    \"endas\": 44395,\n    \"ĠExecution\": 44396,\n    \"ycle\": 44397,\n    \"Ġwedd\": 44398,\n    \"Sold\": 44399,\n    \"Ġvanquished\": 44400,\n    \"Regarding\": 44401,\n    \"Depending\": 44402,\n    \"']\": 44403,\n    \"atron\": 44404,\n    \"oidal\": 44405,\n    \"Cube\": 44406,\n    \"Studio\": 44407,\n    \":/\": 44408,\n    \"ĠExplosion\": 44409,\n    \"activate\": 44410,\n    \"pport\": 44411,\n    \"fuck\": 44412,\n    \"Whe\": 44413,\n    \"Ġsmir\": 44414,\n    \"Ġwidgets\": 44415,\n    \"urses\": 44416,\n    \"izard\": 44417,\n    \")*\": 44418,\n    \"icho\": 44419,\n    \"ĠVersus\": 44420,\n    \"ĠIntroduced\": 44421,\n    \"osaurus\": 44422,\n    \"1977\": 44423,\n    \"forum\": 44424,\n    \"Gray\": 44425,\n    \"Program\": 44426,\n    \"righteous\": 44427,\n    \"endum\": 44428,\n    \"ĠScare\": 44429,\n    \"Ġresists\": 44430,\n    \"*)\": 44431,\n    \"ĠCombo\": 44432,\n    \"Ġsockets\": 44433,\n    \"Ġaston\": 44434,\n    \"LAB\": 44435,\n    \"Ġmutated\": 44436,\n    \"eworld\": 44437,\n    \"DEF\": 44438,\n    \"Trend\": 44439,\n    \"âĢĶ-\": 44440,\n    \"Ġpropagation\": 44441,\n    \"Ġemancipation\": 44442,\n    \"collection\": 44443,\n    \"ĠDifferences\": 44444,\n    \"Tweet\": 44445,\n    \"Ġmajesty\": 44446,\n    \")...\": 44447,\n    \"sylv\": 44448,\n    \"Ġadapters\": 44449,\n    \"Ġmilliseconds\": 44450,\n    \"Jews\": 44451,\n    \"ĠPatreon\": 44452,\n    \"phasis\": 44453,\n    \"ĠHTTP\": 44454,\n    \"onnaissance\": 44455,\n    \"ENDED\": 44456,\n    \"ĠIntro\": 44457,\n    \"qs\": 44458,\n    \"Ġsuperflu\": 44459,\n    \"*.\": 44460,\n    \"Ġminions\": 44461,\n    \"ĠStupid\": 44462,\n    \"Ġspecialization\": 44463,\n    \"ĠPikachu\": 44464,\n    \"Ġappellant\": 44465,\n    \"Training\": 44466,\n    \"circle\": 44467,\n    \"Interest\": 44468,\n    \"Ġfallacy\": 44469,\n    \"ĠDinosaur\": 44470,\n    \"ĠTHEM\": 44471,\n    \"Ġdirectories\": 44472,\n    \"Ġmasturbation\": 44473,\n    \"ĠStain\": 44474,\n    \"1978\": 44475,\n    \"odied\": 44476,\n    \"Ġexqu\": 44477,\n    \"ĠRats\": 44478,\n    \"swick\": 44479,\n    \"Ġemptiness\": 44480,\n    \"ĠXeon\": 44481,\n    \"Ġthereto\": 44482,\n    \"ĠEngels\": 44483,\n    \"ĠSupplement\": 44484,\n    \"Chan\": 44485,\n    \"Ġundead\": 44486,\n    \"ĠNoct\": 44487,\n    \"erest\": 44488,\n    \"ĠQuery\": 44489,\n    \"ĠSOLD\": 44490,\n    \"thritis\": 44491,\n    \"ĠEncounter\": 44492,\n    \"Ġvectors\": 44493,\n    \"Econom\": 44494,\n    \"Rogue\": 44495,\n    \"Ġgelatin\": 44496,\n    \"Rot\": 44497,\n    \"Flickr\": 44498,\n    \"Ġcaching\": 44499,\n    \"Ġloader\": 44500,\n    \"ĠELE\": 44501,\n    \"Ġcamoufl\": 44502,\n    \"Commission\": 44503,\n    \"Ġ1886\": 44504,\n    \"Ġcombos\": 44505,\n    \"ĠAwakening\": 44506,\n    \"Ġfeudal\": 44507,\n    \"Ġasses\": 44508,\n    \"ASY\": 44509,\n    \"atalie\": 44510,\n    \"Ġpanties\": 44511,\n    \"ĠMono\": 44512,\n    \"selves\": 44513,\n    \"Download\": 44514,\n    \"Ġvampires\": 44515,\n    \"------\": 44516,\n    \"ishop\": 44517,\n    \"User\": 44518,\n    \"Ġimperialist\": 44519,\n    \"ĠGOODMAN\": 44520,\n    \"1973\": 44521,\n    \"Vel\": 44522,\n    \"Struct\": 44523,\n    \"ĠUFOs\": 44524,\n    \"drivers\": 44525,\n    \"ĠOptional\": 44526,\n    \"uably\": 44527,\n    \"ĠPrinciple\": 44528,\n    \"verett\": 44529,\n    \"taining\": 44530,\n    \"Ġ1889\": 44531,\n    \"ĠCommunism\": 44532,\n    \"auder\": 44533,\n    \"Keys\": 44534,\n    \"lore\": 44535,\n    \"ĠMedieval\": 44536,\n    \"Hyd\": 44537,\n    \"weapon\": 44538,\n    \"Register\": 44539,\n    \"ĠHighlander\": 44540,\n    \"ĠRFC\": 44541,\n    \"Demon\": 44542,\n    \"ardless\": 44543,\n    \"ĠOrche\": 44544,\n    \"Kick\": 44545,\n    \"pixel\": 44546,\n    \"address\": 44547,\n    \"OUP\": 44548,\n    \"Brain\": 44549,\n    \"ĠMorph\": 44550,\n    \"bash\": 44551,\n    \"ĠANG\": 44552,\n    \"ĠIdle\": 44553,\n    \"ĠLucifer\": 44554,\n    \"Ġcorrelates\": 44555,\n    \"Ġgazed\": 44556,\n    \"colm\": 44557,\n    \"ĠKard\": 44558,\n    \"Solar\": 44559,\n    \"ĠVariable\": 44560,\n    \"ĠPACK\": 44561,\n    \"Ġfuzz\": 44562,\n    \"Ġanonym\": 44563,\n    \"ĠECO\": 44564,\n    \"feature\": 44565,\n    \"ĠEsports\": 44566,\n    \"ĠAnthropology\": 44567,\n    \"cise\": 44568,\n    \"manac\": 44569,\n    \"ĠSupports\": 44570,\n    \"rists\": 44571,\n    \"Quant\": 44572,\n    \"istical\": 44573,\n    \"çļĦ\": 44574,\n    \"Ġdexterity\": 44575,\n    \"monster\": 44576,\n    \"ordial\": 44577,\n    \"Mob\": 44578,\n    \"DEC\": 44579,\n    \"ĠConj\": 44580,\n    \"entric\": 44581,\n    \"1981\": 44582,\n    \"ECTION\": 44583,\n    \"ietal\": 44584,\n    \"ĠUses\": 44585,\n    \"ĠArmageddon\": 44586,\n    \"ĠCapitalism\": 44587,\n    \"Ub\": 44588,\n    \"iazep\": 44589,\n    \"helps\": 44590,\n    \"ouls\": 44591,\n    \"grim\": 44592,\n    \"ĠEthiop\": 44593,\n    \"tesy\": 44594,\n    \"Ġclipboard\": 44595,\n    \"Ġchimpanzees\": 44596,\n    \"PLIC\": 44597,\n    \"Sexual\": 44598,\n    \"wallet\": 44599,\n    \"ĠRect\": 44600,\n    \"ocytes\": 44601,\n    \"ĠHels\": 44602,\n    \"lace\": 44603,\n    \"Damn\": 44604,\n    \"Ġblasp\": 44605,\n    \"ildo\": 44606,\n    \"ĠRober\": 44607,\n    \"APD\": 44608,\n    \"ĠWCS\": 44609,\n    \"ippery\": 44610,\n    \"ellectual\": 44611,\n    \"Ġ$(\": 44612,\n    \"Ġuniverses\": 44613,\n    \"Ġholster\": 44614,\n    \"Ġshading\": 44615,\n    \"Ġinflic\": 44616,\n    \"else\": 44617,\n    \"ĠShiny\": 44618,\n    \"ĠAVG\": 44619,\n    \"Lower\": 44620,\n    \"ĠMayhem\": 44621,\n    \"Originally\": 44622,\n    \"Crypt\": 44623,\n    \"SHARE\": 44624,\n    \"ĠBeir\": 44625,\n    \"!:\": 44626,\n    \"Ġrepentance\": 44627,\n    \"WHAT\": 44628,\n    \".......\": 44629,\n    \"Ġauditory\": 44630,\n    \"aaa\": 44631,\n    \"ĠLoot\": 44632,\n    \"ciples\": 44633,\n    \"Ġcontem\": 44634,\n    \"Ġphoton\": 44635,\n    \"æľ\": 44636,\n    \"omach\": 44637,\n    \"ĠWhedon\": 44638,\n    \"ĠValid\": 44639,\n    \"asonable\": 44640,\n    \"pha\": 44641,\n    \"assad\": 44642,\n    \"ĠPse\": 44643,\n    \"Heat\": 44644,\n    \"Ġplugins\": 44645,\n    \"Ġclenched\": 44646,\n    \"ĠAmeric\": 44647,\n    \"transform\": 44648,\n    \"ĠEnh\": 44649,\n    \"agnetic\": 44650,\n    \"usalem\": 44651,\n    \"sych\": 44652,\n    \"Wed\": 44653,\n    \"replace\": 44654,\n    \"ĠKinect\": 44655,\n    \"shield\": 44656,\n    \"Sax\": 44657,\n    \"ividually\": 44658,\n    \"Ġfunctionally\": 44659,\n    \"Ġ:)\": 44660,\n    \"typically\": 44661,\n    \"Opening\": 44662,\n    \"Fa\": 44663,\n    \"ĠSELECT\": 44664,\n    \"Ġsamurai\": 44665,\n    \"Ġhorde\": 44666,\n    \"entle\": 44667,\n    \"sth\": 44668,\n    \"Changes\": 44669,\n    \"Pin\": 44670,\n    \"ithing\": 44671,\n    \"illance\": 44672,\n    \"ĠEmblem\": 44673,\n    \"ĠMicha\": 44674,\n    \"crypt\": 44675,\n    \"ĠObjective\": 44676,\n    \"ophys\": 44677,\n    \"Ġavg\": 44678,\n    \"poon\": 44679,\n    \"Ġreadable\": 44680,\n    \"ĠRx\": 44681,\n    \"allel\": 44682,\n    \"Sit\": 44683,\n    \"gom\": 44684,\n    \"ureau\": 44685,\n    \"ĠDoodle\": 44686,\n    \"Ġdungeon\": 44687,\n    \"($\": 44688,\n    \"Nintendo\": 44689,\n    \"\\\"],\\\"\": 44690,\n    \"Notes\": 44691,\n    \"Grab\": 44692,\n    \"Prosecutors\": 44693,\n    \"Advanced\": 44694,\n    \"Ġ1862\": 44695,\n    \"ĠVeter\": 44696,\n    \"Ġjurisd\": 44697,\n    \"ĠLauncher\": 44698,\n    \"Catal\": 44699,\n    \"udder\": 44700,\n    \"Ġresidues\": 44701,\n    \"Ġregress\": 44702,\n    \"ĠConquer\": 44703,\n    \"osal\": 44704,\n    \"ĠDice\": 44705,\n    \"************\": 44706,\n    \"braska\": 44707,\n    \"ipolar\": 44708,\n    \"Ġathe\": 44709,\n    \"bringing\": 44710,\n    \"Suddenly\": 44711,\n    \"ĠIEEE\": 44712,\n    \"verbs\": 44713,\n    \"Ġdelet\": 44714,\n    \"ipeg\": 44715,\n    \"Previous\": 44716,\n    \"]\\\"\": 44717,\n    \"Ġsidebar\": 44718,\n    \"illac\": 44719,\n    \"Property\": 44720,\n    \"Î±\": 44721,\n    \"REP\": 44722,\n    \"Ġauthenticated\": 44723,\n    \"gypt\": 44724,\n    \"uilding\": 44725,\n    \"ĠGing\": 44726,\n    \"Ġwart\": 44727,\n    \"Birth\": 44728,\n    \"Ġobedient\": 44729,\n    \"ĠXuan\": 44730,\n    \"ĠTYPE\": 44731,\n    \"Ġinhibits\": 44732,\n    \"1972\": 44733,\n    \"humans\": 44734,\n    \"IENT\": 44735,\n    \"Ġyoutube\": 44736,\n    \"Shortly\": 44737,\n    \"ophen\": 44738,\n    \"ĠWinc\": 44739,\n    \"ĠWrit\": 44740,\n    \"AUD\": 44741,\n    \"ĠHobbit\": 44742,\n    \"emphasis\": 44743,\n    \"ĠWonders\": 44744,\n    \"Ġtwitch\": 44745,\n    \"ĠProphe\": 44746,\n    \"Berry\": 44747,\n    \"ĠGinny\": 44748,\n    \"ĠBurst\": 44749,\n    \"ĠGenerator\": 44750,\n    \"Ġepile\": 44751,\n    \"ĠBalanced\": 44752,\n    \"GPU\": 44753,\n    \"maps\": 44754,\n    \"Ġneurotrans\": 44755,\n    \"ĠIRC\": 44756,\n    \"Ġ\\\"$\": 44757,\n    \"Create\": 44758,\n    \"Particip\": 44759,\n    \"ĠMarxism\": 44760,\n    \"Ġthou\": 44761,\n    \"ĠMortal\": 44762,\n    \"Ġï¿½\": 44763,\n    \"Ġninja\": 44764,\n    \"inburgh\": 44765,\n    \"Ġappro\": 44766,\n    \"ĠPistol\": 44767,\n    \"Jar\": 44768,\n    \"Ġprophes\": 44769,\n    \"classes\": 44770,\n    \"Ġanarchist\": 44771,\n    \"Ġextant\": 44772,\n    \"message\": 44773,\n    \"itaire\": 44774,\n    \"Ġ1863\": 44775,\n    \"ĠProl\": 44776,\n    \"Ġpropell\": 44777,\n    \"Ġimpossibility\": 44778,\n    \"Ġpropos\": 44779,\n    \"itamin\": 44780,\n    \"Rating\": 44781,\n    \"olphin\": 44782,\n    \"Ġmitochond\": 44783,\n    \"versions\": 44784,\n    \"Liberal\": 44785,\n    \"ishy\": 44786,\n    \"Ġspherical\": 44787,\n    \"ĠSurvive\": 44788,\n    \"FREE\": 44789,\n    \"rawler\": 44790,\n    \"Metal\": 44791,\n    \"ĠStarship\": 44792,\n    \"Ġ=================================================================\": 44793,\n    \"ĠDharma\": 44794,\n    \"ĠSeller\": 44795,\n    \"Ġwrapper\": 44796,\n    \"Experience\": 44797,\n    \"Integ\": 44798,\n    \"Customer\": 44799,\n    \"hammad\": 44800,\n    \"Ġunanim\": 44801,\n    \"Jenn\": 44802,\n    \"Ġschizophren\": 44803,\n    \"agree\": 44804,\n    \"ĠEVENT\": 44805,\n    \"Shell\": 44806,\n    \"Ġfractions\": 44807,\n    \"1968\": 44808,\n    \"Ġextermination\": 44809,\n    \"ĠSniper\": 44810,\n    \"Ġpronoun\": 44811,\n    \"ĠHitman\": 44812,\n    \"xp\": 44813,\n    \"resource\": 44814,\n    \"WIND\": 44815,\n    \"Ġhierarchical\": 44816,\n    \"Ġted\": 44817,\n    \"Changing\": 44818,\n    \"Ġplaus\": 44819,\n    \"Transform\": 44820,\n    \"Ġbicy\": 44821,\n    \"imentary\": 44822,\n    \"Fuck\": 44823,\n    \"Mini\": 44824,\n    \"Ġoverc\": 44825,\n    \"ĠOptimus\": 44826,\n    \"outer\": 44827,\n    \"helial\": 44828,\n    \"akening\": 44829,\n    \"fx\": 44830,\n    \"Ġnig\": 44831,\n    \"Ġ+/-\": 44832,\n    \"ĠVICE\": 44833,\n    \"Ġnm\": 44834,\n    \"1976\": 44835,\n    \"ĠRitual\": 44836,\n    \"ĠTyrann\": 44837,\n    \"Ġscriptures\": 44838,\n    \"inical\": 44839,\n    \"ĠNull\": 44840,\n    \"ourgeois\": 44841,\n    \"dra\": 44842,\n    \"Ġpious\": 44843,\n    \"Ġneuron\": 44844,\n    \"Ġcolonists\": 44845,\n    \"ĠNebula\": 44846,\n    \"apply\": 44847,\n    \"Sah\": 44848,\n    \"Marx\": 44849,\n    \"Ġhypotheses\": 44850,\n    \"notation\": 44851,\n    \"acists\": 44852,\n    \"Math\": 44853,\n    \"Manager\": 44854,\n    \"Library\": 44855,\n    \"audi\": 44856,\n    \"Ġmp\": 44857,\n    \"ergic\": 44858,\n    \"Ġwizards\": 44859,\n    \"fw\": 44860,\n    \"DVD\": 44861,\n    \"ĠScala\": 44862,\n    \"Different\": 44863,\n    \"ampoo\": 44864,\n    \"ĠDread\": 44865,\n    \"abbage\": 44866,\n    \"Rus\": 44867,\n    \"ĠDumbledore\": 44868,\n    \"keleton\": 44869,\n    \"elsh\": 44870,\n    \"esian\": 44871,\n    \"ĠCorsair\": 44872,\n    \"Tier\": 44873,\n    \"ĠCelest\": 44874,\n    \"Ġnoun\": 44875,\n    \"Ġlucid\": 44876,\n    \"requisites\": 44877,\n    \"Ġgenus\": 44878,\n    \"Event\": 44879,\n    \"1974\": 44880,\n    \"ĠSatanic\": 44881,\n    \"iox\": 44882,\n    \"ĠHandle\": 44883,\n    \"ĠDestroyer\": 44884,\n    \"Ġinvocation\": 44885,\n    \"ĠXD\": 44886,\n    \"modified\": 44887,\n    \"Gam\": 44888,\n    \"ĠRPC\": 44889,\n    \"Ġsubsystem\": 44890,\n    \"Compared\": 44891,\n    \"odan\": 44892,\n    \"ĠPassive\": 44893,\n    \"ĠHelmet\": 44894,\n    \"nutrition\": 44895,\n    \"riction\": 44896,\n    \"HOW\": 44897,\n    \"Jess\": 44898,\n    \"Ġpiston\": 44899,\n    \"imately\": 44900,\n    \"Ġhypoc\": 44901,\n    \"ĠCelestial\": 44902,\n    \"MRI\": 44903,\n    \"Ġcompiler\": 44904,\n    \"ĠBadge\": 44905,\n    \"ĠRevelation\": 44906,\n    \"Ġintrig\": 44907,\n    \"Grad\": 44908,\n    \"ĠSPACE\": 44909,\n    \"Poly\": 44910,\n    \"ĠVul\": 44911,\n    \"Ġtrembling\": 44912,\n    \"Ġindepend\": 44913,\n    \"doctor\": 44914,\n    \"Certain\": 44915,\n    \"emet\": 44916,\n    \"Password\": 44917,\n    \"Ġgasped\": 44918,\n    \"Ġpronunciation\": 44919,\n    \"Fuel\": 44920,\n    \"ĠSPEC\": 44921,\n    \"assets\": 44922,\n    \"Extra\": 44923,\n    \"Ġformatting\": 44924,\n    \"Ġmods\": 44925,\n    \"\\\"!\": 44926,\n    \"akedown\": 44927,\n    \"Ġcircuitry\": 44928,\n    \"ĠTRUE\": 44929,\n    \"ĠVeil\": 44930,\n    \"Ġsighed\": 44931,\n    \"Charg\": 44932,\n    \"eals\": 44933,\n    \"Ġworkaround\": 44934,\n    \"Ġank\": 44935,\n    \"ĠScrolls\": 44936,\n    \"Ġdiffusion\": 44937,\n    \"Ġamps\": 44938,\n    \"ĠTempest\": 44939,\n    \"adata\": 44940,\n    \"Ġphenomen\": 44941,\n    \"Ġ???\": 44942,\n    \"Ġpopup\": 44943,\n    \"Ġinhibition\": 44944,\n    \"Ġaliases\": 44945,\n    \"erity\": 44946,\n    \"agraph\": 44947,\n    \"Jew\": 44948,\n    \"Ġbec\": 44949,\n    \"Classic\": 44950,\n    \"comment\": 44951,\n    \"usable\": 44952,\n    \"rodu\": 44953,\n    \"ĠEnlightenment\": 44954,\n    \"Ġinvis\": 44955,\n    \"Ġbiochemical\": 44956,\n    \"latest\": 44957,\n    \"ĠGMOs\": 44958,\n    \"ĠSocialism\": 44959,\n    \"Ġpollut\": 44960,\n    \"Ġeluc\": 44961,\n    \"Js\": 44962,\n    \"orthern\": 44963,\n    \"PDATED\": 44964,\n    \"alyses\": 44965,\n    \"Experts\": 44966,\n    \"Blog\": 44967,\n    \"ĠDemocr\": 44968,\n    \"etooth\": 44969,\n    \"pause\": 44970,\n    \"âĢ¢âĢ¢\": 44971,\n    \"ĠShinji\": 44972,\n    \"Ġdystop\": 44973,\n    \"Sources\": 44974,\n    \"ĠBrach\": 44975,\n    \"np\": 44976,\n    \"ĠXY\": 44977,\n    \"Ġneurot\": 44978,\n    \"assembly\": 44979,\n    \"Ġbourgeois\": 44980,\n    \"ĠReson\": 44981,\n    \"ĠIDE\": 44982,\n    \"Ġrecoil\": 44983,\n    \"raq\": 44984,\n    \"ĠAvenger\": 44985,\n    \"Paper\": 44986,\n    \"UTF\": 44987,\n    \"ĠWrest\": 44988,\n    \"ĠSimulation\": 44989,\n    \"elaide\": 44990,\n    \"ĠDMCA\": 44991,\n    \"utm\": 44992,\n    \"1963\": 44993,\n    \"Ġarcs\": 44994,\n    \"Ġmaximal\": 44995,\n    \"Ġcyl\": 44996,\n    \"Ġphilosoph\": 44997,\n    \"enium\": 44998,\n    \"Ġrelativity\": 44999,\n    \"ĠMacintosh\": 45000,\n    \"Ġpneum\": 45001,\n    \"LOC\": 45002,\n    \"Ġgoddamn\": 45003,\n    \"SHA\": 45004,\n    \"Ġlocalization\": 45005,\n    \"ĠPHI\": 45006,\n    \"Ġhierarch\": 45007,\n    \"Ġatheists\": 45008,\n    \"Â±\": 45009,\n    \"Luck\": 45010,\n    \"ĠJugg\": 45011,\n    \"options\": 45012,\n    \"alore\": 45013,\n    \"Edward\": 45014,\n    \"Monitor\": 45015,\n    \"Ġneoc\": 45016,\n    \"numbered\": 45017,\n    \"Arc\": 45018,\n    \"ĠCodes\": 45019,\n    \"ĠHallow\": 45020,\n    \"olitan\": 45021,\n    \"sections\": 45022,\n    \"ĠEzek\": 45023,\n    \"Ġamy\": 45024,\n    \"task\": 45025,\n    \"ĠCLS\": 45026,\n    \"ĠValkyrie\": 45027,\n    \"Ġcircumference\": 45028,\n    \"amac\": 45029,\n    \"ĠNotting\": 45030,\n    \"Ġproverb\": 45031,\n    \"Spec\": 45032,\n    \"Ġelemental\": 45033,\n    \"ĠBitcoins\": 45034,\n    \"Except\": 45035,\n    \"Release\": 45036,\n    \"ADVERTISEMENT\": 45037,\n    \"Complete\": 45038,\n    \"phrine\": 45039,\n    \"Ġspores\": 45040,\n    \"random\": 45041,\n    \"neum\": 45042,\n    \"trigger\": 45043,\n    \"ocide\": 45044,\n    \"Ġlongitudinal\": 45045,\n    \"isec\": 45046,\n    \"peat\": 45047,\n    \"Ġprecept\": 45048,\n    \"Wing\": 45049,\n    \"ĠâĹ\": 45050,\n    \"otropic\": 45051,\n    \"mouse\": 45052,\n    \"ĠWitcher\": 45053,\n    \"ĠAppearance\": 45054,\n    \"ROR\": 45055,\n    \"Ġ||\": 45056,\n    \"aird\": 45057,\n    \"Blu\": 45058,\n    \"Ġincomp\": 45059,\n    \"ĠFirefly\": 45060,\n    \"update\": 45061,\n    \"Loc\": 45062,\n    \"Ġnihil\": 45063,\n    \"hesive\": 45064,\n    \"Quality\": 45065,\n    \"youtu\": 45066,\n    \"Seriously\": 45067,\n    \"Ġannot\": 45068,\n    \"ĠCoins\": 45069,\n    \"Visit\": 45070,\n    \"lc\": 45071,\n    \"----------\": 45072,\n    \"Ġdiction\": 45073,\n    \"Ġafore\": 45074,\n    \"Ġimmortality\": 45075,\n    \"ĠForbidden\": 45076,\n    \"Allah\": 45077,\n    \"ĠPartial\": 45078,\n    \"ĠGears\": 45079,\n    \"Ġtrance\": 45080,\n    \"Hat\": 45081,\n    \"irez\": 45082,\n    \"ĠSATA\": 45083,\n    \"Ġelectrode\": 45084,\n    \"ĠLinear\": 45085,\n    \"rikes\": 45086,\n    \"Ġderiv\": 45087,\n    \"ĠXue\": 45088,\n    \"Fine\": 45089,\n    \"ĠIgnore\": 45090,\n    \"desc\": 45091,\n    \"DOM\": 45092,\n    \"Simple\": 45093,\n    \"orescence\": 45094,\n    \"Previously\": 45095,\n    \"Ġcircumcision\": 45096,\n    \"Sphere\": 45097,\n    \"Ġrenown\": 45098,\n    \"SET\": 45099,\n    \"ilight\": 45100,\n    \"ĠByzantine\": 45101,\n    \"EXP\": 45102,\n    \"Ġwhine\": 45103,\n    \"Missing\": 45104,\n    \"Lt\": 45105,\n    \"Guide\": 45106,\n    \"Ġhippocampus\": 45107,\n    \"Ġwip\": 45108,\n    \"yrights\": 45109,\n    \"Ġsubmer\": 45110,\n    \"Maker\": 45111,\n    \"Switch\": 45112,\n    \"Ġspectral\": 45113,\n    \"nect\": 45114,\n    \"Ãį\": 45115,\n    \"Ġreven\": 45116,\n    \"WER\": 45117,\n    \"Adding\": 45118,\n    \"ĠCONTROL\": 45119,\n    \"asper\": 45120,\n    \"0000000\": 45121,\n    \"ynt\": 45122,\n    \"annabin\": 45123,\n    \"ĠAliens\": 45124,\n    \"ĠPCR\": 45125,\n    \"asketball\": 45126,\n    \"ricia\": 45127,\n    \"ĠUnch\": 45128,\n    \"Tap\": 45129,\n    \"Ġpracticable\": 45130,\n    \"ĠUsage\": 45131,\n    \"Ġsoluble\": 45132,\n    \"Scroll\": 45133,\n    \"Random\": 45134,\n    \"Ġmoan\": 45135,\n    \"ĠPuppet\": 45136,\n    \"Dim\": 45137,\n    \"Attack\": 45138,\n    \"Ġspears\": 45139,\n    \"Ġrectangle\": 45140,\n    \"Ġamuse\": 45141,\n    \"ĠDoct\": 45142,\n    \"reon\": 45143,\n    \"ĠReset\": 45144,\n    \"vag\": 45145,\n    \"unin\": 45146,\n    \"ĠBris\": 45147,\n    \"ĠSwarm\": 45148,\n    \"Model\": 45149,\n    \"Standing\": 45150,\n    \"Ġdenotes\": 45151,\n    \"{\": 45152,\n    \"ĠLizard\": 45153,\n    \"nesty\": 45154,\n    \"Ġwor\": 45155,\n    \"Ġamplification\": 45156,\n    \"ĠInferno\": 45157,\n    \"Cover\": 45158,\n    \"SAM\": 45159,\n    \"respective\": 45160,\n    \"Shift\": 45161,\n    \"Ġlibertarians\": 45162,\n    \"Runner\": 45163,\n    \"ĠRevelations\": 45164,\n    \"Spr\": 45165,\n    \"ĠCrusader\": 45166,\n    \"Ġcaffe\": 45167,\n    \"Patch\": 45168,\n    \"stros\": 45169,\n    \"ĠImmortal\": 45170,\n    \"Ġinsofar\": 45171,\n    \"itance\": 45172,\n    \"ĠValhalla\": 45173,\n    \"Ġradial\": 45174,\n    \"Beast\": 45175,\n    \"sync\": 45176,\n    \"Ġ--------\": 45177,\n    \"ĠPathfinder\": 45178,\n    \"iless\": 45179,\n    \"operator\": 45180,\n    \"Choose\": 45181,\n    \"Ġdecode\": 45182,\n    \"Ġvou\": 45183,\n    \"ĠMutant\": 45184,\n    \"ĠCVE\": 45185,\n    \"Female\": 45186,\n    \"Ġoxidation\": 45187,\n    \"inational\": 45188,\n    \"dB\": 45189,\n    \"Scope\": 45190,\n    \"Wan\": 45191,\n    \"ĠBought\": 45192,\n    \"ĠDietary\": 45193,\n    \"rotein\": 45194,\n    \"Present\": 45195,\n    \"aukee\": 45196,\n    \"Ġtotem\": 45197,\n    \"Ġsatur\": 45198,\n    \"wagon\": 45199,\n    \"Builder\": 45200,\n    \"ĠBulg\": 45201,\n    \"Ġsects\": 45202,\n    \"Flo\": 45203,\n    \"ombat\": 45204,\n    \"ĠHermione\": 45205,\n    \"aughs\": 45206,\n    \"Ġhydra\": 45207,\n    \"paren\": 45208,\n    \"ë\": 45209,\n    \"Whereas\": 45210,\n    \"tsky\": 45211,\n    \"Ġchall\": 45212,\n    \"WORK\": 45213,\n    \"opian\": 45214,\n    \"rican\": 45215,\n    \"vati\": 45216,\n    \"ĠHTTPS\": 45217,\n    \"Ġwrink\": 45218,\n    \"Ġthrob\": 45219,\n    \"habi\": 45220,\n    \"Ġiodine\": 45221,\n    \"omorph\": 45222,\n    \"ĠScion\": 45223,\n    \"Hunt\": 45224,\n    \"Written\": 45225,\n    \"iosity\": 45226,\n    \"ĠBrowser\": 45227,\n    \"Ġsinners\": 45228,\n    \"culosis\": 45229,\n    \"Ġunconsciously\": 45230,\n    \"0100\": 45231,\n    \"Ġanarchists\": 45232,\n    \"Pull\": 45233,\n    \"FFER\": 45234,\n    \"Ġpandemonium\": 45235,\n    \"matically\": 45236,\n    \"Rush\": 45237,\n    \"Ġpurified\": 45238,\n    \"ĠCyan\": 45239,\n    \"ĠDifficulty\": 45240,\n    \"Â«\": 45241,\n    \"Aside\": 45242,\n    \"oggles\": 45243,\n    \"untu\": 45244,\n    \"iege\": 45245,\n    \"iberal\": 45246,\n    \"ĠCOUR\": 45247,\n    \"eteenth\": 45248,\n    \"weeney\": 45249,\n    \"biased\": 45250,\n    \"ĠDecay\": 45251,\n    \"quart\": 45252,\n    \"alysis\": 45253,\n    \"Ġstere\": 45254,\n    \"ellect\": 45255,\n    \"Ġkernels\": 45256,\n    \"juven\": 45257,\n    \"ĠJPEG\": 45258,\n    \"indal\": 45259,\n    \"topic\": 45260,\n    \"Ġidentifier\": 45261,\n    \"åı\": 45262,\n    \"Ġepid\": 45263,\n    \"1969\": 45264,\n    \"Ġpoisons\": 45265,\n    \"sym\": 45266,\n    \"mop\": 45267,\n    \"LOCK\": 45268,\n    \"axe\": 45269,\n    \"cohol\": 45270,\n    \"ctory\": 45271,\n    \"Ġadject\": 45272,\n    \"Skin\": 45273,\n    \"ĠFract\": 45274,\n    \"ĠSHAR\": 45275,\n    \"echo\": 45276,\n    \"thood\": 45277,\n    \"Ġencoding\": 45278,\n    \"Ġrelational\": 45279,\n    \"Len\": 45280,\n    \"Bone\": 45281,\n    \"agara\": 45282,\n    \"uggish\": 45283,\n    \"ĠTanks\": 45284,\n    \"Stats\": 45285,\n    \"lihood\": 45286,\n    \"Mult\": 45287,\n    \"Graph\": 45288,\n    \"ĠCannot\": 45289,\n    \"ĠSpac\": 45290,\n    \"handler\": 45291,\n    \"ĠShit\": 45292,\n    \"Ġmorp\": 45293,\n    \"controller\": 45294,\n    \"udeau\": 45295,\n    \"Screenshot\": 45296,\n    \"Development\": 45297,\n    \"Gear\": 45298,\n    \"Ġtong\": 45299,\n    \"ĠColossus\": 45300,\n    \"rylic\": 45301,\n    \"STRUCT\": 45302,\n    \"capitalist\": 45303,\n    \"Ġsupplementation\": 45304,\n    \"Parts\": 45305,\n    \"pb\": 45306,\n    \"oppy\": 45307,\n    \"pite\": 45308,\n    \"processor\": 45309,\n    \"Ġexplanatory\": 45310,\n    \"Environmental\": 45311,\n    \"Compl\": 45312,\n    \"Gaming\": 45313,\n    \"arently\": 45314,\n    \"Ġconcess\": 45315,\n    \"Ġathlet\": 45316,\n    \"forestation\": 45317,\n    \"orsi\": 45318,\n    \"igmat\": 45319,\n    \"Ġencoded\": 45320,\n    \"misc\": 45321,\n    \"Ġproofs\": 45322,\n    \"ĠRevision\": 45323,\n    \"Ġmathematic\": 45324,\n    \"Ġconstitu\": 45325,\n    \"fficiency\": 45326,\n    \"Ġlightsaber\": 45327,\n    \"gz\": 45328,\n    \"erate\": 45329,\n    \"ournals\": 45330,\n    \"Comment\": 45331,\n    \"Ġpercept\": 45332,\n    \".\\\"[\": 45333,\n    \"ĠTechniques\": 45334,\n    \"coins\": 45335,\n    \"Shape\": 45336,\n    \"venant\": 45337,\n    \"ĠPrinted\": 45338,\n    \"Native\": 45339,\n    \"ĠGors\": 45340,\n    \"pecting\": 45341,\n    \"ĠDuel\": 45342,\n    \"Ġadmins\": 45343,\n    \"Flor\": 45344,\n    \"ĠDeus\": 45345,\n    \"cham\": 45346,\n    \"ĠRails\": 45347,\n    \"ceptor\": 45348,\n    \"naire\": 45349,\n    \"ĠSquid\": 45350,\n    \"ĠWarranty\": 45351,\n    \"SPEC\": 45352,\n    \"ensis\": 45353,\n    \"FUN\": 45354,\n    \"stellar\": 45355,\n    \"Select\": 45356,\n    \"llular\": 45357,\n    \"arget\": 45358,\n    \"ĠUncharted\": 45359,\n    \"Details\": 45360,\n    \"rison\": 45361,\n    \"Ġsyntax\": 45362,\n    \"chanted\": 45363,\n    \"Ġ-----\": 45364,\n    \"Ġthats\": 45365,\n    \"Registration\": 45366,\n    \"ĠSaber\": 45367,\n    \"ethical\": 45368,\n    \"Ġcryptography\": 45369,\n    \"atown\": 45370,\n    \"Ġdependencies\": 45371,\n    \"nw\": 45372,\n    \"Ġvehement\": 45373,\n    \"Ġrationality\": 45374,\n    \"ĠThou\": 45375,\n    \"Ġ----\": 45376,\n    \"rador\": 45377,\n    \"Ġenh\": 45378,\n    \"ĠCrate\": 45379,\n    \"STATE\": 45380,\n    \"/(\": 45381,\n    \"Ġdelim\": 45382,\n    \"CEPT\": 45383,\n    \"monkey\": 45384,\n    \"pai\": 45385,\n    \"uracy\": 45386,\n    \"Ġmortals\": 45387,\n    \"Sanders\": 45388,\n    \"ĠSeraph\": 45389,\n    \"-\\\"\": 45390,\n    \"1945\": 45391,\n    \"endix\": 45392,\n    \":'\": 45393,\n    \"ĠLegs\": 45394,\n    \"Exper\": 45395,\n    \"ĠKrypt\": 45396,\n    \"clinton\": 45397,\n    \"Ġuphe\": 45398,\n    \"Vers\": 45399,\n    \"Similarly\": 45400,\n    \"ressor\": 45401,\n    \"leans\": 45402,\n    \"LOG\": 45403,\n    \"cific\": 45404,\n    \"Ġ].\": 45405,\n    \"-)\": 45406,\n    \"resist\": 45407,\n    \"Pred\": 45408,\n    \"Latest\": 45409,\n    \"ilyn\": 45410,\n    \"Ġblob\": 45411,\n    \"Ġdevils\": 45412,\n    \"ĠIllusion\": 45413,\n    \"erella\": 45414,\n    \"Ġyak\": 45415,\n    \"method\": 45416,\n    \"Ġ698\": 45417,\n    \"Shadow\": 45418,\n    \"velt\": 45419,\n    \"Ġsomet\": 45420,\n    \"xc\": 45421,\n    \"Ġtriangles\": 45422,\n    \"netic\": 45423,\n    \"Calling\": 45424,\n    \"ĠDRM\": 45425,\n    \"Ġtriglycer\": 45426,\n    \"Ġinhibited\": 45427,\n    \"Ġnep\": 45428,\n    \"Ġalgebra\": 45429,\n    \"ascar\": 45430,\n    \"laim\": 45431,\n    \"Ġappl\": 45432,\n    \"1971\": 45433,\n    \"Bernie\": 45434,\n    \"Eh\": 45435,\n    \"Ġundefined\": 45436,\n    \"âĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶ\": 45437,\n    \"Sys\": 45438,\n    \"ournaments\": 45439,\n    \"Solid\": 45440,\n    \"Ġhep\": 45441,\n    \"ĠMales\": 45442,\n    \"Agent\": 45443,\n    \"Ġpsychedel\": 45444,\n    \"Wik\": 45445,\n    \"Ġdoctrines\": 45446,\n    \"rection\": 45447,\n    \"Compare\": 45448,\n    \"âĺ\": 45449,\n    \"Ġcertific\": 45450,\n    \"Ġsubstr\": 45451,\n    \"ĠCitation\": 45452,\n    \"ĠAFB\": 45453,\n    \"ĠBecame\": 45454,\n    \"Ġaristocracy\": 45455,\n    \"aryl\": 45456,\n    \"Ġanatomical\": 45457,\n    \"ocumented\": 45458,\n    \"ĠAssy\": 45459,\n    \"ĠFORM\": 45460,\n    \"Traditional\": 45461,\n    \"azines\": 45462,\n    \"Content\": 45463,\n    \"furt\": 45464,\n    \"Ġscripting\": 45465,\n    \"Ġcloaked\": 45466,\n    \"Ġunint\": 45467,\n    \"ĠCivilization\": 45468,\n    \"Desktop\": 45469,\n    \"ĠRagnar\": 45470,\n    \"Ġcurses\": 45471,\n    \"Ġobservable\": 45472,\n    \"ĠSpock\": 45473,\n    \"ĠPyr\": 45474,\n    \"Ġelectrom\": 45475,\n    \"ĠLump\": 45476,\n    \"oresc\": 45477,\n    \"ĠAttribution\": 45478,\n    \"egal\": 45479,\n    \"achusetts\": 45480,\n    \"Ġmarqu\": 45481,\n    \"âĻ¦\": 45482,\n    \"Ġcursor\": 45483,\n    \"ascist\": 45484,\n    \"1966\": 45485,\n    \"edit\": 45486,\n    \"lisher\": 45487,\n    \"ocyte\": 45488,\n    \"Writer\": 45489,\n    \"BILITIES\": 45490,\n    \"ĠUpload\": 45491,\n    \"Ġtreacher\": 45492,\n    \"Ġrecomb\": 45493,\n    \"Ġknights\": 45494,\n    \"Ġimmutable\": 45495,\n    \"ĠPly\": 45496,\n    \"Ġatten\": 45497,\n    \"ĠPassed\": 45498,\n    \"Flying\": 45499,\n    \"icipated\": 45500,\n    \"querade\": 45501,\n    \"ĠZot\": 45502,\n    \"CRE\": 45503,\n    \"ĠCursed\": 45504,\n    \"ickr\": 45505,\n    \"ĠDroid\": 45506,\n    \"thereum\": 45507,\n    \"Ġadjective\": 45508,\n    \"DIT\": 45509,\n    \"Ġtob\": 45510,\n    \"Ġinit\": 45511,\n    \"ĠPenet\": 45512,\n    \"Ġignor\": 45513,\n    \"Ġexalted\": 45514,\n    \"ĠDwell\": 45515,\n    \"assemb\": 45516,\n    \"Ġsentient\": 45517,\n    \"Ġ``\": 45518,\n    \"ĠGoo\": 45519,\n    \"Professional\": 45520,\n    \"othing\": 45521,\n    \"rupted\": 45522,\n    \"olics\": 45523,\n    \"ĠSetup\": 45524,\n    \"Thu\": 45525,\n    \"Campaign\": 45526,\n    \"Secondly\": 45527,\n    \"clipse\": 45528,\n    \"hibit\": 45529,\n    \"amate\": 45530,\n    \"SUP\": 45531,\n    \"ĠSuppose\": 45532,\n    \"submit\": 45533,\n    \"ĠDebian\": 45534,\n    \"Ġantid\": 45535,\n    \"Ġentert\": 45536,\n    \"ysical\": 45537,\n    \"ĠGladiator\": 45538,\n    \"ĠSTL\": 45539,\n    \"ĠBugs\": 45540,\n    \"ĠMech\": 45541,\n    \"ĠCoffin\": 45542,\n    \"itored\": 45543,\n    \"ICLE\": 45544,\n    \"Mist\": 45545,\n    \"Ġinfall\": 45546,\n    \"votes\": 45547,\n    \"actly\": 45548,\n    \"Occ\": 45549,\n    \"ĠConquest\": 45550,\n    \"alach\": 45551,\n    \"Ġintertw\": 45552,\n    \"reverse\": 45553,\n    \"amiya\": 45554,\n    \"icularly\": 45555,\n    \"edom\": 45556,\n    \"ĠLuxem\": 45557,\n    \"Fra\": 45558,\n    \"urrencies\": 45559,\n    \"Ġnobility\": 45560,\n    \"Tab\": 45561,\n    \"Beer\": 45562,\n    \"Ġ10000\": 45563,\n    \"Ġincor\": 45564,\n    \"Ġmelanch\": 45565,\n    \"Depth\": 45566,\n    \"Firstly\": 45567,\n    \"usr\": 45568,\n    \"ĠWiki\": 45569,\n    \"hhhh\": 45570,\n    \"ĠProxy\": 45571,\n    \"Ġantagonists\": 45572,\n    \"Ġtransistor\": 45573,\n    \"ĠRelic\": 45574,\n    \"ĠPrometheus\": 45575,\n    \"Ġ1280\": 45576,\n    \"Coun\": 45577,\n    \"ĠMedals\": 45578,\n    \"stats\": 45579,\n    \"Assembly\": 45580,\n    \"inished\": 45581,\n    \"cemic\": 45582,\n    \"Ġadventurers\": 45583,\n    \"Ġcd\": 45584,\n    \"Supporters\": 45585,\n    \"ĠYs\": 45586,\n    \"])\": 45587,\n    \"Ġneglig\": 45588,\n    \"Request\": 45589,\n    \"Ġwhore\": 45590,\n    \"Ġovercl\": 45591,\n    \"_-\": 45592,\n    \"partial\": 45593,\n    \"amd\": 45594,\n    \"Ġfructose\": 45595,\n    \"Ġdivid\": 45596,\n    \"Administ\": 45597,\n    \"amples\": 45598,\n    \"Boo\": 45599,\n    \"akery\": 45600,\n    \"owered\": 45601,\n    \"hester\": 45602,\n    \"Links\": 45603,\n    \"GROUND\": 45604,\n    \"ethy\": 45605,\n    \"Ġincarcer\": 45606,\n    \"Ġincap\": 45607,\n    \"Drag\": 45608,\n    \"ĠElastic\": 45609,\n    \"âĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶâĢĶ\": 45610,\n    \"Ultra\": 45611,\n    \"AAAA\": 45612,\n    \"Order\": 45613,\n    \"ĠMysteries\": 45614,\n    \"Ġcanonical\": 45615,\n    \"Ign\": 45616,\n    \"Ġanimate\": 45617,\n    \"wegian\": 45618,\n    \"ggle\": 45619,\n    \"Hash\": 45620,\n    \"Arg\": 45621,\n    \"verty\": 45622,\n    \"Ġanalges\": 45623,\n    \"ouver\": 45624,\n    \"ittees\": 45625,\n    \"ĠAsgard\": 45626,\n    \"______\": 45627,\n    \"Mix\": 45628,\n    \"1964\": 45629,\n    \"Rate\": 45630,\n    \"Ġarousal\": 45631,\n    \"pheus\": 45632,\n    \"undai\": 45633,\n    \"hetamine\": 45634,\n    \"ĠMysterious\": 45635,\n    \"Alright\": 45636,\n    \"ĠHerod\": 45637,\n    \"riott\": 45638,\n    \"ĠAnarchy\": 45639,\n    \"ĠArche\": 45640,\n    \"Question\": 45641,\n    \"Chapter\": 45642,\n    \"Token\": 45643,\n    \"ĠSphere\": 45644,\n    \"Ġinduces\": 45645,\n    \"Audio\": 45646,\n    \"Normal\": 45647,\n    \"Ġprophe\": 45648,\n    \"ĠValiant\": 45649,\n    \"Tag\": 45650,\n    \"Relations\": 45651,\n    \"Ġblinked\": 45652,\n    \"onyms\": 45653,\n    \"ĠVortex\": 45654,\n    \"Ġdb\": 45655,\n    \"emonic\": 45656,\n    \"Phase\": 45657,\n    \"Ġkingdoms\": 45658,\n    \"Twe\": 45659,\n    \"ĠLORD\": 45660,\n    \"plementation\": 45661,\n    \"ĠConstantinople\": 45662,\n    \"helm\": 45663,\n    \"ĠFlesh\": 45664,\n    \"Ġthumbnail\": 45665,\n    \"ledged\": 45666,\n    \"ĠPROG\": 45667,\n    \"Ġdisbel\": 45668,\n    \"ĠLikes\": 45669,\n    \"ĠGamer\": 45670,\n    \"renches\": 45671,\n    \"hattan\": 45672,\n    \"Index\": 45673,\n    \"pecially\": 45674,\n    \"ĠJiu\": 45675,\n    \"Ġwhats\": 45676,\n    \"erion\": 45677,\n    \"xf\": 45678,\n    \"ĠPerception\": 45679,\n    \"Alien\": 45680,\n    \"Capt\": 45681,\n    \"ãĢĤ\": 45682,\n    \"joining\": 45683,\n    \"nesium\": 45684,\n    \"ĠSocrates\": 45685,\n    \"Icon\": 45686,\n    \"animate\": 45687,\n    \"ocalypse\": 45688,\n    \"ĠTactics\": 45689,\n    \"assador\": 45690,\n    \"Veh\": 45691,\n    \"src\": 45692,\n    \",-\": 45693,\n    \"Ġvisc\": 45694,\n    \"ĠDiscord\": 45695,\n    \"initial\": 45696,\n    \"atana\": 45697,\n    \"Size\": 45698,\n    \"Claim\": 45699,\n    \"ffect\": 45700,\n    \"iciary\": 45701,\n    \"Ġturret\": 45702,\n    \"reset\": 45703,\n    \"Ï\": 45704,\n    \"wrap\": 45705,\n    \"ulnerability\": 45706,\n    \"ĠInsert\": 45707,\n    \"Ġirrad\": 45708,\n    \"ognitive\": 45709,\n    \"clips\": 45710,\n    \"uncle\": 45711,\n    \"chemy\": 45712,\n    \"ottesville\": 45713,\n    \"Write\": 45714,\n    \"earances\": 45715,\n    \"1965\": 45716,\n    \"MIC\": 45717,\n    \"Ġmanag\": 45718,\n    \"Ġtelesc\": 45719,\n    \"Termin\": 45720,\n    \"Guest\": 45721,\n    \"Ġdenote\": 45722,\n    \"Failure\": 45723,\n    \"ograp\": 45724,\n    \"âĢķ\": 45725,\n    \"Ġscrolls\": 45726,\n    \"ĠArmored\": 45727,\n    \"Ġrecomp\": 45728,\n    \"Ġplaceholder\": 45729,\n    \"ĠISBN\": 45730,\n    \"ĠBelief\": 45731,\n    \"emporary\": 45732,\n    \"Asset\": 45733,\n    \"arcer\": 45734,\n    \"haar\": 45735,\n    \"assium\": 45736,\n    \"%:\": 45737,\n    \"ernal\": 45738,\n    \"ĠLv\": 45739,\n    \"atible\": 45740,\n    \"Pand\": 45741,\n    \"oubted\": 45742,\n    \"Lie\": 45743,\n    \"bial\": 45744,\n    \"STEP\": 45745,\n    \"Ġpresets\": 45746,\n    \"Ġstatist\": 45747,\n    \"Sund\": 45748,\n    \"reshold\": 45749,\n    \"endium\": 45750,\n    \"\\\");\": 45751,\n    \"Software\": 45752,\n    \"Ġbasal\": 45753,\n    \"ĠYose\": 45754,\n    \"Ġmortg\": 45755,\n    \"ocry\": 45756,\n    \"Ġsubreddit\": 45757,\n    \"omorphic\": 45758,\n    \"ĠLoaded\": 45759,\n    \"berra\": 45760,\n    \"vg\": 45761,\n    \"orkshire\": 45762,\n    \"ĠChrys\": 45763,\n    \"Repeat\": 45764,\n    \"ĠSimulator\": 45765,\n    \"rx\": 45766,\n    \"gex\": 45767,\n    \"Linux\": 45768,\n    \"ĠInstruct\": 45769,\n    \"irable\": 45770,\n    \"Ġmosquit\": 45771,\n    \"ĠManga\": 45772,\n    \"iOS\": 45773,\n    \"Ġsynt\": 45774,\n    \"Ġclitor\": 45775,\n    \"Ġlobe\": 45776,\n    \"ĠDelete\": 45777,\n    \"CVE\": 45778,\n    \"fortunately\": 45779,\n    \"Enc\": 45780,\n    \"vertising\": 45781,\n    \"Ġanten\": 45782,\n    \"Ġfif\": 45783,\n    \"Study\": 45784,\n    \"prev\": 45785,\n    \"ossus\": 45786,\n    \"Nar\": 45787,\n    \"Decl\": 45788,\n    \"erala\": 45789,\n    \"ĠPrototype\": 45790,\n    \"UGE\": 45791,\n    \"1001\": 45792,\n    \"Ġ---------\": 45793,\n    \"deals\": 45794,\n    \"odcast\": 45795,\n    \"TPS\": 45796,\n    \"Ġcodec\": 45797,\n    \"ittee\": 45798,\n    \"isexual\": 45799,\n    \"ĠBreaker\": 45800,\n    \"menu\": 45801,\n    \"ĠURI\": 45802,\n    \"('\": 45803,\n    \"ĠFiorina\": 45804,\n    \"ĠApostles\": 45805,\n    \"ĠWitches\": 45806,\n    \"raint\": 45807,\n    \"addafi\": 45808,\n    \"ersive\": 45809,\n    \"yrim\": 45810,\n    \"Ġmosa\": 45811,\n    \"Ġrog\": 45812,\n    \"Ear\": 45813,\n    \"âĺħ\": 45814,\n    \"Ġcaloric\": 45815,\n    \"matical\": 45816,\n    \"yrics\": 45817,\n    \"ĠKrugman\": 45818,\n    \"axter\": 45819,\n    \"1016\": 45820,\n    \"Ġsep\": 45821,\n    \"ĠExtend\": 45822,\n    \"ropolitan\": 45823,\n    \"thren\": 45824,\n    \"ologne\": 45825,\n    \"atomic\": 45826,\n    \"Naturally\": 45827,\n    \"Pros\": 45828,\n    \"gencies\": 45829,\n    \"akens\": 45830,\n    \"Male\": 45831,\n    \"Ġcausation\": 45832,\n    \"omnia\": 45833,\n    \"Comments\": 45834,\n    \"eeee\": 45835,\n    \"iquette\": 45836,\n    \"Ġcytok\": 45837,\n    \"ename\": 45838,\n    \"details\": 45839,\n    \"Ġdestruct\": 45840,\n    \"leep\": 45841,\n    \"ĠCavern\": 45842,\n    \"ĠInvention\": 45843,\n    \"ueless\": 45844,\n    \"Ġsubsection\": 45845,\n    \"outhern\": 45846,\n    \"metic\": 45847,\n    \"blogs\": 45848,\n    \"ĠPacks\": 45849,\n    \"ĠArduino\": 45850,\n    \"hhh\": 45851,\n    \"elligence\": 45852,\n    \"imity\": 45853,\n    \"ĠUltron\": 45854,\n    \"astrous\": 45855,\n    \"Ġbiome\": 45856,\n    \"ĠHover\": 45857,\n    \"Ġprivile\": 45858,\n    \"igham\": 45859,\n    \"apest\": 45860,\n    \"ĠYoshi\": 45861,\n    \"Artist\": 45862,\n    \".\\\",\": 45863,\n    \"gamer\": 45864,\n    \"Virgin\": 45865,\n    \"Tea\": 45866,\n    \"ĠDoomsday\": 45867,\n    \"ĠðŁĻĤ\": 45868,\n    \"terday\": 45869,\n    \"ĠCommando\": 45870,\n    \"ĠAchieve\": 45871,\n    \"chrom\": 45872,\n    \"Ġcryptographic\": 45873,\n    \"Ġrebell\": 45874,\n    \"Specifically\": 45875,\n    \"âĢ¦âĢ¦âĢ¦âĢ¦\": 45876,\n    \"ĠEternity\": 45877,\n    \"Ġemulation\": 45878,\n    \"ĠSERV\": 45879,\n    \"ĠMiscellaneous\": 45880,\n    \"ĠParticipant\": 45881,\n    \"duc\": 45882,\n    \"vp\": 45883,\n    \"ĠSparkle\": 45884,\n    \"ategories\": 45885,\n    \"Ġdecrypt\": 45886,\n    \"ĠGNOME\": 45887,\n    \"activation\": 45888,\n    \"Ġanarch\": 45889,\n    \"owler\": 45890,\n    \"adiator\": 45891,\n    \"itars\": 45892,\n    \"ĠTHEN\": 45893,\n    \")\\\",\": 45894,\n    \"åħ\": 45895,\n    \"Ġembod\": 45896,\n    \"vae\": 45897,\n    \"âĺĨ\": 45898,\n    \"Member\": 45899,\n    \"Ġrm\": 45900,\n    \"nyder\": 45901,\n    \"ĠLeviathan\": 45902,\n    \"Gaza\": 45903,\n    \"erenn\": 45904,\n    \"Chicken\": 45905,\n    \"ĠDefinitive\": 45906,\n    \"ĠBolshe\": 45907,\n    \"ĠJagu\": 45908,\n    \"gorith\": 45909,\n    \"loader\": 45910,\n    \"exe\": 45911,\n    \".........\": 45912,\n    \"ĠReceived\": 45913,\n    \"ĠProto\": 45914,\n    \"ĠLocked\": 45915,\n    \"Posts\": 45916,\n    \"ankind\": 45917,\n    \"Clock\": 45918,\n    \"ĠCLI\": 45919,\n    \"Throw\": 45920,\n    \"dL\": 45921,\n    \"epad\": 45922,\n    \"ĠAtmosp\": 45923,\n    \"Ġmk\": 45924,\n    \"ĠSteal\": 45925,\n    \"uple\": 45926,\n    \"reference\": 45927,\n    \"ĠGNU\": 45928,\n    \"adelphia\": 45929,\n    \"scripts\": 45930,\n    \"ilaterally\": 45931,\n    \"ĠMods\": 45932,\n    \"odus\": 45933,\n    \"ignty\": 45934,\n    \"REF\": 45935,\n    \"Ġhypothesized\": 45936,\n    \"issors\": 45937,\n    \"Ġanus\": 45938,\n    \"HUD\": 45939,\n    \"rices\": 45940,\n    \"Draw\": 45941,\n    \"Computer\": 45942,\n    \"Below\": 45943,\n    \"uthor\": 45944,\n    \"ĠTact\": 45945,\n    \"=$\": 45946,\n    \"00000000\": 45947,\n    \"Ġcaut\": 45948,\n    \"Sharp\": 45949,\n    \"depend\": 45950,\n    \"Ġtatt\": 45951,\n    \"Goal\": 45952,\n    \"Sounds\": 45953,\n    \"zona\": 45954,\n    \"anyon\": 45955,\n    \"ricanes\": 45956,\n    \"ĠUSAF\": 45957,\n    \"Jump\": 45958,\n    \"Bottom\": 45959,\n    \"etermination\": 45960,\n    \"ĠPles\": 45961,\n    \"Ġhypothes\": 45962,\n    \"Reference\": 45963,\n    \"Ġswall\": 45964,\n    \"Ġmaneu\": 45965,\n    \"rifice\": 45966,\n    \"ĠVeh\": 45967,\n    \"Ġtex\": 45968,\n    \"geoning\": 45969,\n    \"ĠâľĶ\": 45970,\n    \"Mach\": 45971,\n    \"eanor\": 45972,\n    \"%);\": 45973,\n    \"archives\": 45974,\n    \"Ġencyclopedia\": 45975,\n    \"ĠPreferences\": 45976,\n    \"damage\": 45977,\n    \"Done\": 45978,\n    \"Ġcoefficient\": 45979,\n    \"ĠCreatures\": 45980,\n    \"Ġital\": 45981,\n    \"ivari\": 45982,\n    \"Revolution\": 45983,\n    \"Ġnob\": 45984,\n    \"Diff\": 45985,\n    \"Ġabbre\": 45986,\n    \"Writ\": 45987,\n    \"ĠDOS\": 45988,\n    \"redd\": 45989,\n    \"Ġsplend\": 45990,\n    \"orest\": 45991,\n    \"flame\": 45992,\n    \"Ġdevs\": 45993,\n    \"Ġ==\": 45994,\n    \"ĠPuzzle\": 45995,\n    \"Ġgit\": 45996,\n    \"MOD\": 45997,\n    \"ĠArgument\": 45998,\n    \"ĠAbyss\": 45999,\n    \"Studies\": 46000,\n    \"ophob\": 46001,\n    \"uild\": 46002,\n    \"scill\": 46003,\n    \"fp\": 46004,\n    \"Ġplur\": 46005,\n    \"Delete\": 46006,\n    \"ĠFALSE\": 46007,\n    \"FIL\": 46008,\n    \"Ġmicrobiota\": 46009,\n    \"ĠIPv\": 46010,\n    \"Stud\": 46011,\n    \"ortal\": 46012,\n    \"ĠDivinity\": 46013,\n    \"ounter\": 46014,\n    \"ä¸\": 46015,\n    \"Naz\": 46016,\n    \"stals\": 46017,\n    \"ihilation\": 46018,\n    \"Ġpersecut\": 46019,\n    \"ĠPlanes\": 46020,\n    \"viation\": 46021,\n    \"Driver\": 46022,\n    \"ĠEEG\": 46023,\n    \"Unity\": 46024,\n    \"Premium\": 46025,\n    \"ĠSiren\": 46026,\n    \"ĠPaleo\": 46027,\n    \"earchers\": 46028,\n    \"Pract\": 46029,\n    \"Ö\": 46030,\n    \"VII\": 46031,\n    \"mosp\": 46032,\n    \"Ġidentifiers\": 46033,\n    \"Near\": 46034,\n    \"achu\": 46035,\n    \"Apps\": 46036,\n    \"tackle\": 46037,\n    \"COLOR\": 46038,\n    \"Ġperpendicular\": 46039,\n    \"viks\": 46040,\n    \"ecided\": 46041,\n    \"ĠDota\": 46042,\n    \"icons\": 46043,\n    \"Ġpsi\": 46044,\n    \"Brave\": 46045,\n    \"Ġunimagin\": 46046,\n    \"ĠATI\": 46047,\n    \"OOL\": 46048,\n    \"Gender\": 46049,\n    \"ĠSwords\": 46050,\n    \"oples\": 46051,\n    \"Rank\": 46052,\n    \"olphins\": 46053,\n    \"Ġdeities\": 46054,\n    \"ĠXIII\": 46055,\n    \"Ð¼\": 46056,\n    \"ĠKraken\": 46057,\n    \"ĠLEVEL\": 46058,\n    \"stasy\": 46059,\n    \"ĠBabel\": 46060,\n    \"Hours\": 46061,\n    \"Avoid\": 46062,\n    \"Mech\": 46063,\n    \"Multi\": 46064,\n    \"Ġect\": 46065,\n    \"Occup\": 46066,\n    \"panic\": 46067,\n    \"Ġmutants\": 46068,\n    \"Evidence\": 46069,\n    \"Tips\": 46070,\n    \"Ġvolts\": 46071,\n    \"Exit\": 46072,\n    \"xb\": 46073,\n    \"planet\": 46074,\n    \"avez\": 46075,\n    \"features\": 46076,\n    \")]\": 46077,\n    \"lol\": 46078,\n    \"ĠNeph\": 46079,\n    \"ĠSanct\": 46080,\n    \"Ġimpover\": 46081,\n    \"................................\": 46082,\n    \"Sty\": 46083,\n    \"Email\": 46084,\n    \"Torrent\": 46085,\n    \"Ġgluc\": 46086,\n    \"ĠSins\": 46087,\n    \"ĠIncarn\": 46088,\n    \"ĠWITHOUT\": 46089,\n    \"ĠPanzer\": 46090,\n    \"ĠAssignment\": 46091,\n    \"versible\": 46092,\n    \"Strange\": 46093,\n    \"ITNESS\": 46094,\n    \"incible\": 46095,\n    \"ZX\": 46096,\n    \"ĠMySQL\": 46097,\n    \"Ġconson\": 46098,\n    \"Ġoxidative\": 46099,\n    \"Machine\": 46100,\n    \"Impro\": 46101,\n    \"Parent\": 46102,\n    \"ĠMetroid\": 46103,\n    \"Educ\": 46104,\n    \"Ġdismant\": 46105,\n    \"dx\": 46106,\n    \"ĠPersona\": 46107,\n    \"ĠHDL\": 46108,\n    \"Americ\": 46109,\n    \"Users\": 46110,\n    \"Ġeighteenth\": 46111,\n    \"WARNING\": 46112,\n    \"ĠLists\": 46113,\n    \"ĠCanter\": 46114,\n    \"ĠTrotsky\": 46115,\n    \"Ġhaha\": 46116,\n    \"]'\": 46117,\n    \"ĠEncyclopedia\": 46118,\n    \"admin\": 46119,\n    \"ĠACTIONS\": 46120,\n    \"idav\": 46121,\n    \"Î¿\": 46122,\n    \"ĠFTP\": 46123,\n    \"Ġquar\": 46124,\n    \"ongyang\": 46125,\n    \"âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦âĢ¦\": 46126,\n    \"Ġsynchronization\": 46127,\n    \"DEM\": 46128,\n    \"riched\": 46129,\n    \"Ġnegro\": 46130,\n    \"Bench\": 46131,\n    \"Ġfilament\": 46132,\n    \"Ġdecoding\": 46133,\n    \"obj\": 46134,\n    \"Ġjoystick\": 46135,\n    \"Decre\": 46136,\n    \"ĠBolshevik\": 46137,\n    \"Virtual\": 46138,\n    \"ĠSacrament\": 46139,\n    \"xd\": 46140,\n    \"BILL\": 46141,\n    \"-+-+\": 46142,\n    \"Â¶\": 46143,\n    \"anchester\": 46144,\n    \"Pokemon\": 46145,\n    \"Ġslic\": 46146,\n    \"iameter\": 46147,\n    \"errilla\": 46148,\n    \"Exactly\": 46149,\n    \"\\\"'\": 46150,\n    \"getic\": 46151,\n    \"3333\": 46152,\n    \"solete\": 46153,\n    \"Ġincorpor\": 46154,\n    \"Ġio\": 46155,\n    \"------------\": 46156,\n    \"Ġantiquity\": 46157,\n    \"ATURES\": 46158,\n    \"Policy\": 46159,\n    \"oppable\": 46160,\n    \"Ġ=>\": 46161,\n    \"ODUCT\": 46162,\n    \"otide\": 46163,\n    \"Ú\": 46164,\n    \"Ġnormative\": 46165,\n    \"Fac\": 46166,\n    \"Ġshaman\": 46167,\n    \"element\": 46168,\n    \"Plex\": 46169,\n    \"INTER\": 46170,\n    \"etsk\": 46171,\n    \"ĠGauntlet\": 46172,\n    \"ĠBIOS\": 46173,\n    \"×ķ\": 46174,\n    \"riet\": 46175,\n    \"Rew\": 46176,\n    \"uristic\": 46177,\n    \"urches\": 46178,\n    \"ĠChomsky\": 46179,\n    \"ixir\": 46180,\n    \"package\": 46181,\n    \"Owner\": 46182,\n    \"Ġschematic\": 46183,\n    \"Assistant\": 46184,\n    \"Ġemanc\": 46185,\n    \"Ġarchetype\": 46186,\n    \"Initial\": 46187,\n    \"intent\": 46188,\n    \"Ġfilib\": 46189,\n    \"ispers\": 46190,\n    \"Flag\": 46191,\n    \"Tank\": 46192,\n    \"Ġinsurg\": 46193,\n    \"Ġapproximation\": 46194,\n    \"Ġsemantic\": 46195,\n    \"Ġsubtitle\": 46196,\n    \"Font\": 46197,\n    \"Ġintimid\": 46198,\n    \"Ġhath\": 46199,\n    \"tools\": 46200,\n    \"gob\": 46201,\n    \"Process\": 46202,\n    \"slave\": 46203,\n    \"ĠJUSTICE\": 46204,\n    \"âĻ¥\": 46205,\n    \"ĠHardcore\": 46206,\n    \"Discover\": 46207,\n    \"Ġexch\": 46208,\n    \"ptive\": 46209,\n    \"units\": 46210,\n    \"ĠDjango\": 46211,\n    \"itudinal\": 46212,\n    \"Ġpc\": 46213,\n    \"akespeare\": 46214,\n    \"ospace\": 46215,\n    \"Ġhorny\": 46216,\n    \"auth\": 46217,\n    \"ĠSkyrim\": 46218,\n    \"ENGTH\": 46219,\n    \"perors\": 46220,\n    \"ĠVulkan\": 46221,\n    \"Ġchimpan\": 46222,\n    \"Ġremem\": 46223,\n    \"Ġopacity\": 46224,\n    \"Ġ:(\": 46225,\n    \"ushima\": 46226,\n    \"Ġawoken\": 46227,\n    \"Ġsacrament\": 46228,\n    \"Beginning\": 46229,\n    \"escape\": 46230,\n    \"Anim\": 46231,\n    \"Ġadvant\": 46232,\n    \"ĠRequires\": 46233,\n    \"output\": 46234,\n    \"Ġdroid\": 46235,\n    \"Yep\": 46236,\n    \"rieving\": 46237,\n    \"Ġpt\": 46238,\n    \"ĠShotgun\": 46239,\n    \"ĠOsiris\": 46240,\n    \"disabled\": 46241,\n    \"ĠRadius\": 46242,\n    \"Medium\": 46243,\n    \"ĠScient\": 46244,\n    \"ĠRept\": 46245,\n    \"ymm\": 46246,\n    \"Ġcp\": 46247,\n    \"ĠLabyrinth\": 46248,\n    \"poral\": 46249,\n    \"Ġ'(\": 46250,\n    \"Hack\": 46251,\n    \"ĠTechnique\": 46252,\n    \"/,\": 46253,\n    \"Ġambig\": 46254,\n    \"Basic\": 46255,\n    \"Ġretrie\": 46256,\n    \"VICE\": 46257,\n    \"BIP\": 46258,\n    \"ragon\": 46259,\n    \"phies\": 46260,\n    \"uminum\": 46261,\n    \"ĠFei\": 46262,\n    \"lesi\": 46263,\n    \"Ġsemantics\": 46264,\n    \"ĠHz\": 46265,\n    \"ĠUnderworld\": 46266,\n    \"Ġendot\": 46267,\n    \"olesterol\": 46268,\n    \"ourning\": 46269,\n    \"Ġcaches\": 46270,\n    \"ĠYug\": 46271,\n    \"Legendary\": 46272,\n    \"ĠDocumentation\": 46273,\n    \"ĠSpiral\": 46274,\n    \"ĠClone\": 46275,\n    \"bnb\": 46276,\n    \"ĠâĶ\": 46277,\n    \"ustom\": 46278,\n    \"Mp\": 46279,\n    \"gettable\": 46280,\n    \"agonist\": 46281,\n    \"Ġneuronal\": 46282,\n    \"culus\": 46283,\n    \"enum\": 46284,\n    \"cules\": 46285,\n    \"Ġmuttered\": 46286,\n    \"ctica\": 46287,\n    \"necess\": 46288,\n    \"ĠSubtle\": 46289,\n    \"Ġsolder\": 46290,\n    \"Environment\": 46291,\n    \"oneliness\": 46292,\n    \"orage\": 46293,\n    \"âĢ¦.\\\"\": 46294,\n    \"nesota\": 46295,\n    \"agements\": 46296,\n    \"Ùİ\": 46297,\n    \"WHERE\": 46298,\n    \"ĠGDDR\": 46299,\n    \"Scient\": 46300,\n    \"ĠMulcair\": 46301,\n    \"ĠRena\": 46302,\n    \"________________________________________________________________\": 46303,\n    \"antics\": 46304,\n    \"Ġtorped\": 46305,\n    \"Brow\": 46306,\n    \"ossal\": 46307,\n    \"Category\": 46308,\n    \"Regular\": 46309,\n    \"remote\": 46310,\n    \"ãģ\": 46311,\n    \"ĠCoil\": 46312,\n    \"ritch\": 46313,\n    \"specified\": 46314,\n    \"Average\": 46315,\n    \"Ġfingert\": 46316,\n    \"entity\": 46317,\n    \"atibility\": 46318,\n    \"ampunk\": 46319,\n    \"ĠScriptures\": 46320,\n    \"Ġunequ\": 46321,\n    \"arettes\": 46322,\n    \"arching\": 46323,\n    \"Ġastron\": 46324,\n    \"Ġnumeric\": 46325,\n    \"ĠeBook\": 46326,\n    \"remove\": 46327,\n    \"onday\": 46328,\n    \"Ġmetaphysical\": 46329,\n    \"ĠGoku\": 46330,\n    \"Element\": 46331,\n    \"ĠRuin\": 46332,\n    \"Norm\": 46333,\n    \"Ġtox\": 46334,\n    \"puff\": 46335,\n    \"Ġharmonic\": 46336,\n    \"ĠAgility\": 46337,\n    \"ĠHearthstone\": 46338,\n    \"Ġmana\": 46339,\n    \"Points\": 46340,\n    \"Ġconduc\": 46341,\n    \"ĠPersia\": 46342,\n    \"-----\": 46343,\n    \"license\": 46344,\n    \"Application\": 46345,\n    \"assert\": 46346,\n    \"Reader\": 46347,\n    \"ĠSacrifice\": 46348,\n    \"float\": 46349,\n    \"inctions\": 46350,\n    \"byter\": 46351,\n    \"Ġfundament\": 46352,\n    \"\\\"âĢ¦\": 46353,\n    \"Fourth\": 46354,\n    \"Effective\": 46355,\n    \"ĠMeow\": 46356,\n    \"ĠErrors\": 46357,\n    \"ĠIcar\": 46358,\n    \"ĠMMO\": 46359,\n    \"Ġapostles\": 46360,\n    \"Ġfaintly\": 46361,\n    \"component\": 46362,\n    \"bably\": 46363,\n    \"uggage\": 46364,\n    \"ĠMPG\": 46365,\n    \"krit\": 46366,\n    \"container\": 46367,\n    \"ixture\": 46368,\n    \"ĠPOV\": 46369,\n    \"izabeth\": 46370,\n    \"onut\": 46371,\n    \"isdom\": 46372,\n    \"trace\": 46373,\n    \"ĠSDL\": 46374,\n    \"Interestingly\": 46375,\n    \"ĠExplan\": 46376,\n    \"lesiastical\": 46377,\n    \"ternal\": 46378,\n    \"Bug\": 46379,\n    \"Ġmetabolites\": 46380,\n    \"geries\": 46381,\n    \"Ġsupra\": 46382,\n    \"ĠMakoto\": 46383,\n    \"orget\": 46384,\n    \"racuse\": 46385,\n    \"][\": 46386,\n    \"ĠPrelude\": 46387,\n    \"peria\": 46388,\n    \"tube\": 46389,\n    \"ĠCatalog\": 46390,\n    \"ĠGoblin\": 46391,\n    \"QUEST\": 46392,\n    \"ĠINCLUD\": 46393,\n    \"ĠVERS\": 46394,\n    \"erguson\": 46395,\n    \"Ġcommandments\": 46396,\n    \"ĠUDP\": 46397,\n    \"itle\": 46398,\n    \"Î¹\": 46399,\n    \"domain\": 46400,\n    \"roximately\": 46401,\n    \"ĠTLS\": 46402,\n    \"ongevity\": 46403,\n    \"Ġmodulation\": 46404,\n    \"Ġdidnt\": 46405,\n    \"ĠCalories\": 46406,\n    \"Applications\": 46407,\n    \"ormon\": 46408,\n    \"Ġsd\": 46409,\n    \"dullah\": 46410,\n    \"Ġcous\": 46411,\n    \"ĠDARK\": 46412,\n    \"clip\": 46413,\n    \"ĠPsychiat\": 46414,\n    \"ĠTanz\": 46415,\n    \"ĠCharisma\": 46416,\n    \"ĠMerge\": 46417,\n    \"ĠKDE\": 46418,\n    \"requires\": 46419,\n    \"urdue\": 46420,\n    \"Ġdecimal\": 46421,\n    \"Ġâī¥\": 46422,\n    \"ĠAuth\": 46423,\n    \"ebted\": 46424,\n    \"ĠTempl\": 46425,\n    \"ĠâĢº\": 46426,\n    \"Ultimate\": 46427,\n    \"Ġmammalian\": 46428,\n    \"advertising\": 46429,\n    \"Ġdominion\": 46430,\n    \"Ġacron\": 46431,\n    \"ĠWem\": 46432,\n    \"ĠHeist\": 46433,\n    \"oiler\": 46434,\n    \"FLAG\": 46435,\n    \"ovember\": 46436,\n    \"Syn\": 46437,\n    \"Ġgodd\": 46438,\n    \"ĠPyth\": 46439,\n    \"Ġglyc\": 46440,\n    \"ĠHelpful\": 46441,\n    \"Ġgad\": 46442,\n    \"chedel\": 46443,\n    \"Similar\": 46444,\n    \"ĠÂ¶\": 46445,\n    \"Ġnp\": 46446,\n    \"ĠREPL\": 46447,\n    \"Fill\": 46448,\n    \"ĠSunder\": 46449,\n    \"etsy\": 46450,\n    \"ĠPAX\": 46451,\n    \"ĠFemales\": 46452,\n    \"ĠKingdoms\": 46453,\n    \"Ġwhistlebl\": 46454,\n    \"Hide\": 46455,\n    \"serial\": 46456,\n    \"ĠEnemies\": 46457,\n    \"ĠPeb\": 46458,\n    \"Ġpiety\": 46459,\n    \"ifact\": 46460,\n    \"esity\": 46461,\n    \"bsite\": 46462,\n    \"esides\": 46463,\n    \"Ġported\": 46464,\n    \"Ġamygdala\": 46465,\n    \"ĠGerr\": 46466,\n    \"afety\": 46467,\n    \"Ġadip\": 46468,\n    \"(\\\"\": 46469,\n    \"Ġcf\": 46470,\n    \"Ġurl\": 46471,\n    \"unia\": 46472,\n    \"icro\": 46473,\n    \"Austral\": 46474,\n    \"ĠConfig\": 46475,\n    \"accompanied\": 46476,\n    \"isite\": 46477,\n    \"Ġtextual\": 46478,\n    \"\\\">\": 46479,\n    \"Ġanecd\": 46480,\n    \"Ġ\\\",\": 46481,\n    \"angular\": 46482,\n    \"ĠUnicode\": 46483,\n    \"Proof\": 46484,\n    \"Ġmultiplication\": 46485,\n    \"Address\": 46486,\n    \"Ġbytes\": 46487,\n    \"lems\": 46488,\n    \"uterte\": 46489,\n    \"Episode\": 46490,\n    \"oshop\": 46491,\n    \"ritical\": 46492,\n    \"Adjust\": 46493,\n    \"argument\": 46494,\n    \"\\\\'\": 46495,\n    \"Rober\": 46496,\n    \"pection\": 46497,\n    \"Agg\": 46498,\n    \"äº\": 46499,\n    \"interrupted\": 46500,\n    \"ĠDebor\": 46501,\n    \"Ġlair\": 46502,\n    \"Various\": 46503,\n    \"isively\": 46504,\n    \"ĠStatic\": 46505,\n    \"ohyd\": 46506,\n    \"ĠEchoes\": 46507,\n    \"UID\": 46508,\n    \"raught\": 46509,\n    \"Bott\": 46510,\n    \"Ġapostle\": 46511,\n    \"ĠCentauri\": 46512,\n    \"oxicity\": 46513,\n    \"ibling\": 46514,\n    \"Ġparalle\": 46515,\n    \"inav\": 46516,\n    \"Crit\": 46517,\n    \"ĠTyph\": 46518,\n    \"Ġhig\": 46519,\n    \"ĠEDITION\": 46520,\n    \"Ġcoord\": 46521,\n    \"uish\": 46522,\n    \"sectional\": 46523,\n    \"inki\": 46524,\n    \"Title\": 46525,\n    \"anyahu\": 46526,\n    \"osterone\": 46527,\n    \"Ġdesper\": 46528,\n    \"ribly\": 46529,\n    \"Legend\": 46530,\n    \"afort\": 46531,\n    \"Org\": 46532,\n    \"Ġempir\": 46533,\n    \"ĠQuake\": 46534,\n    \"SSL\": 46535,\n    \"ioxide\": 46536,\n    \"åľ\": 46537,\n    \"Ġenz\": 46538,\n    \"urtle\": 46539,\n    \"BSD\": 46540,\n    \"Rust\": 46541,\n    \"ospels\": 46542,\n    \"Rare\": 46543,\n    \"Ġpartitions\": 46544,\n    \"Ġheresy\": 46545,\n    \"overy\": 46546,\n    \"Ġmonop\": 46547,\n    \"Pixel\": 46548,\n    \"odder\": 46549,\n    \"Option\": 46550,\n    \"withstanding\": 46551,\n    \"Transfer\": 46552,\n    \"Ġarrog\": 46553,\n    \"skip\": 46554,\n    \"ĠSSH\": 46555,\n    \"ĠSph\": 46556,\n    \"Ġcallback\": 46557,\n    \"PIN\": 46558,\n    \"Ġpdf\": 46559,\n    \"Ġplaint\": 46560,\n    \"cipled\": 46561,\n    \"reenshots\": 46562,\n    \"Ġparsing\": 46563,\n    \"::::::::\": 46564,\n    \"ioxid\": 46565,\n    \"Ġhereafter\": 46566,\n    \"ĠFunctions\": 46567,\n    \"ĠBulgar\": 46568,\n    \"Ġintu\": 46569,\n    \"DOC\": 46570,\n    \"Location\": 46571,\n    \"Hyper\": 46572,\n    \"ageddon\": 46573,\n    \"Evil\": 46574,\n    \"illions\": 46575,\n    \"Introduction\": 46576,\n    \"Physical\": 46577,\n    \"ĠLayout\": 46578,\n    \"âķ\": 46579,\n    \"------------------------\": 46580,\n    \"ĠRodham\": 46581,\n    \"ĠPatterns\": 46582,\n    \"Delivery\": 46583,\n    \"Ġdistur\": 46584,\n    \"ĠVolunte\": 46585,\n    \"ĠGUI\": 46586,\n    \"Ġclen\": 46587,\n    \"Ġinacc\": 46588,\n    \"ĠBallistic\": 46589,\n    \"ĠSprite\": 46590,\n    \"Privacy\": 46591,\n    \"theme\": 46592,\n    \"dump\": 46593,\n    \"ĠByte\": 46594,\n    \"ĠIncre\": 46595,\n    \"apult\": 46596,\n    \"ĠWrath\": 46597,\n    \"ensibly\": 46598,\n    \"NOTE\": 46599,\n    \"ounge\": 46600,\n    \"ustomed\": 46601,\n    \"ochond\": 46602,\n    \"ĠQt\": 46603,\n    \"Primary\": 46604,\n    \"Ġsidew\": 46605,\n    \"Root\": 46606,\n    \"gregation\": 46607,\n    \"SQL\": 46608,\n    \"ĠSOFTWARE\": 46609,\n    \"Gallery\": 46610,\n    \"ĠDungeon\": 46611,\n    \"ĠVengeance\": 46612,\n    \"->\": 46613,\n    \"steam\": 46614,\n    \"Ġfrivol\": 46615,\n    \"Ġpid\": 46616,\n    \"filter\": 46617,\n    \"Ġfacult\": 46618,\n    \"doms\": 46619,\n    \"Tool\": 46620,\n    \"1959\": 46621,\n    \"Ġprefix\": 46622,\n    \"Ġcomma\": 46623,\n    \"relative\": 46624,\n    \"Ġformatted\": 46625,\n    \"appropriately\": 46626,\n    \"Ġmd\": 46627,\n    \"xxx\": 46628,\n    \"ĠAuthentication\": 46629,\n    \"ĠWTC\": 46630,\n    \"Ġvulner\": 46631,\n    \"reditary\": 46632,\n    \"Steam\": 46633,\n    \"Tx\": 46634,\n    \"ĠGHC\": 46635,\n    \"Increased\": 46636,\n    \"forcement\": 46637,\n    \"ĠGuant\": 46638,\n    \"bernatorial\": 46639,\n    \"Entry\": 46640,\n    \"ĠWarp\": 46641,\n    \"ĠCreature\": 46642,\n    \"ĠAmmunition\": 46643,\n    \"Ġclust\": 46644,\n    \"ĠInher\": 46645,\n    \"Ġunbel\": 46646,\n    \"RGB\": 46647,\n    \"ĠMankind\": 46648,\n    \"ĠPlague\": 46649,\n    \"Ġ=================================\": 46650,\n    \"psc\": 46651,\n    \"Intern\": 46652,\n    \"tml\": 46653,\n    \"ĠCrusade\": 46654,\n    \"inflamm\": 46655,\n    \"Storage\": 46656,\n    \"token\": 46657,\n    \"inse\": 46658,\n    \"False\": 46659,\n    \"Adult\": 46660,\n    \"PokÃ©mon\": 46661,\n    \"PLIED\": 46662,\n    \"Ġglac\": 46663,\n    \"ĠDwarf\": 46664,\n    \"sequence\": 46665,\n    \"Ġmagnification\": 46666,\n    \"ĠIlluminati\": 46667,\n    \"hedral\": 46668,\n    \"param\": 46669,\n    \"regon\": 46670,\n    \".\\\",\\\"\": 46671,\n    \"Eva\": 46672,\n    \"igree\": 46673,\n    \"Object\": 46674,\n    \"Ġoptimizations\": 46675,\n    \"uador\": 46676,\n    \"mmmm\": 46677,\n    \"ullivan\": 46678,\n    \"Ġ[\\\"\": 46679,\n    \"ĠDusk\": 46680,\n    \"Ġtrig\": 46681,\n    \"Ġiss\": 46682,\n    \"Ġhypert\": 46683,\n    \"Ġperspect\": 46684,\n    \"Ġassum\": 46685,\n    \":,\": 46686,\n    \"Ġinterpol\": 46687,\n    \"Asked\": 46688,\n    \"Boot\": 46689,\n    \"LIB\": 46690,\n    \"Loading\": 46691,\n    \"Ident\": 46692,\n    \"upuncture\": 46693,\n    \"ioch\": 46694,\n    \"Ġprefrontal\": 46695,\n    \"delay\": 46696,\n    \"ĠPokÃ©\": 46697,\n    \"bestos\": 46698,\n    \"overe\": 46699,\n    \"Elf\": 46700,\n    \"eteria\": 46701,\n    \"ĠSneak\": 46702,\n    \"bians\": 46703,\n    \"ĠARTICLE\": 46704,\n    \"Xbox\": 46705,\n    \"encrypted\": 46706,\n    \"ync\": 46707,\n    \"ĠNietzsche\": 46708,\n    \"Nonetheless\": 46709,\n    \"ĠÂ±\": 46710,\n    \"ĠPrimal\": 46711,\n    \"ĠFlare\": 46712,\n    \"Ġconflic\": 46713,\n    \"ĠRune\": 46714,\n    \"Tes\": 46715,\n    \"cellence\": 46716,\n    \"Mega\": 46717,\n    \"ĠEntity\": 46718,\n    \"chrome\": 46719,\n    \"iatures\": 46720,\n    \"Ġuninstall\": 46721,\n    \"Winner\": 46722,\n    \"aimon\": 46723,\n    \"Ġhomebrew\": 46724,\n    \"Ruby\": 46725,\n    \"araoh\": 46726,\n    \"itime\": 46727,\n    \"Ġpotion\": 46728,\n    \"ĠAllows\": 46729,\n    \"ogyn\": 46730,\n    \"osuke\": 46731,\n    \"Limited\": 46732,\n    \"Ġmacros\": 46733,\n    \"ERROR\": 46734,\n    \"gling\": 46735,\n    \"Ġtodd\": 46736,\n    \"repre\": 46737,\n    \"ĠSakura\": 46738,\n    \"erker\": 46739,\n    \"items\": 46740,\n    \"FIG\": 46741,\n    \"ĠUnle\": 46742,\n    \"Ġhardness\": 46743,\n    \"Split\": 46744,\n    \"Ġarous\": 46745,\n    \"ocally\": 46746,\n    \"Ġì\": 46747,\n    \"ĠEVE\": 46748,\n    \"pleasant\": 46749,\n    \"ihil\": 46750,\n    \"ĠRouter\": 46751,\n    \"ĠLucius\": 46752,\n    \"readable\": 46753,\n    \"Ġtremb\": 46754,\n    \"Dro\": 46755,\n    \"Ġblaster\": 46756,\n    \"Ġbourgeoisie\": 46757,\n    \"NUM\": 46758,\n    \"Alternative\": 46759,\n    \"flags\": 46760,\n    \"GAME\": 46761,\n    \"ebook\": 46762,\n    \"ĠIPM\": 46763,\n    \"Ġcorrel\": 46764,\n    \"Setting\": 46765,\n    \"Frame\": 46766,\n    \"Ġatheism\": 46767,\n    \"Interested\": 46768,\n    \"Liquid\": 46769,\n    \"stanbul\": 46770,\n    \"Lv\": 46771,\n    \"Ġtits\": 46772,\n    \"Ġdc\": 46773,\n    \"×Ļ×\": 46774,\n    \"Ġdoctr\": 46775,\n    \"background\": 46776,\n    \"tsy\": 46777,\n    \"ĠCtrl\": 46778,\n    \"ĠCompatibility\": 46779,\n    \"idae\": 46780,\n    \"example\": 46781,\n    \"perture\": 46782,\n    \"Ġguid\": 46783,\n    \"ĠWinged\": 46784,\n    \"Command\": 46785,\n    \"ridor\": 46786,\n    \"bool\": 46787,\n    \"comments\": 46788,\n    \"ĠImmunity\": 46789,\n    \"Nit\": 46790,\n    \"Statement\": 46791,\n    \"Ġmanif\": 46792,\n    \"ĠIntake\": 46793,\n    \"Bloom\": 46794,\n    \"txt\": 46795,\n    \"context\": 46796,\n    \"input\": 46797,\n    \"achus\": 46798,\n    \"proc\": 46799,\n    \"Ñĭ\": 46800,\n    \"Ġdisemb\": 46801,\n    \"ospons\": 46802,\n    \"utical\": 46803,\n    \"ĠRender\": 46804,\n    \"Ironically\": 46805,\n    \"ursday\": 46806,\n    \"ĠExile\": 46807,\n    \"lishes\": 46808,\n    \"iets\": 46809,\n    \"orescent\": 46810,\n    \"cair\": 46811,\n    \"ĠSubjects\": 46812,\n    \"ĠDungeons\": 46813,\n    \"Ġiii\": 46814,\n    \"neapolis\": 46815,\n    \"ĠBlaster\": 46816,\n    \"Ġphp\": 46817,\n    \"ORED\": 46818,\n    \"ĠSLI\": 46819,\n    \"Ġelig\": 46820,\n    \"ĠIdentified\": 46821,\n    \"ĠBrawl\": 46822,\n    \"bytes\": 46823,\n    \"ĠCTR\": 46824,\n    \"Ġsched\": 46825,\n    \"Assuming\": 46826,\n    \"Bound\": 46827,\n    \"ĠMathemat\": 46828,\n    \"razil\": 46829,\n    \"ĠAstral\": 46830,\n    \"mble\": 46831,\n    \"untled\": 46832,\n    \"Ġmech\": 46833,\n    \"ĠDagger\": 46834,\n    \"ĠUseful\": 46835,\n    \"nesday\": 46836,\n    \"tarians\": 46837,\n    \"AMY\": 46838,\n    \"Camera\": 46839,\n    \"node\": 46840,\n    \"pict\": 46841,\n    \"ginx\": 46842,\n    \"Ġyea\": 46843,\n    \">>>>>>>>\": 46844,\n    \"paragraph\": 46845,\n    \"ĠSupplementary\": 46846,\n    \"9999\": 46847,\n    \"ĠAlchemist\": 46848,\n    \"uzzle\": 46849,\n    \"igun\": 46850,\n    \"ĠCalculator\": 46851,\n    \"ĠApplicant\": 46852,\n    \"hift\": 46853,\n    \"ĠGPL\": 46854,\n    \"Ġencode\": 46855,\n    \"Crash\": 46856,\n    \"ĠNutr\": 46857,\n    \"kHz\": 46858,\n    \"TABLE\": 46859,\n    \"intestinal\": 46860,\n    \"andom\": 46861,\n    \"archive\": 46862,\n    \"Ëľ\": 46863,\n    \"Registered\": 46864,\n    \"Questions\": 46865,\n    \"Remote\": 46866,\n    \"ethyst\": 46867,\n    \"Ġgren\": 46868,\n    \"ĠTexture\": 46869,\n    \"Ġseiz\": 46870,\n    \"Anyway\": 46871,\n    \"ĠVariant\": 46872,\n    \"ê\": 46873,\n    \"Adapt\": 46874,\n    \"ittered\": 46875,\n    \"meta\": 46876,\n    \"ambers\": 46877,\n    \"ĠRuins\": 46878,\n    \"ĠChimera\": 46879,\n    \"password\": 46880,\n    \"ĠReboot\": 46881,\n    \"Ġcaster\": 46882,\n    \"Ġamplitude\": 46883,\n    \"Position\": 46884,\n    \"Ġnotation\": 46885,\n    \"Ġsecretion\": 46886,\n    \"Excellent\": 46887,\n    \"delete\": 46888,\n    \"aminer\": 46889,\n    \"ä»\": 46890,\n    \"Exec\": 46891,\n    \"ĠKenobi\": 46892,\n    \"Interview\": 46893,\n    \"ontent\": 46894,\n    \"ospel\": 46895,\n    \"Ġtuber\": 46896,\n    \"CONT\": 46897,\n    \"roups\": 46898,\n    \"Ġemulator\": 46899,\n    \"Ġjava\": 46900,\n    \"0200\": 46901,\n    \"Ġnested\": 46902,\n    \"Ġfert\": 46903,\n    \")).\": 46904,\n    \"Dex\": 46905,\n    \"ĠSora\": 46906,\n    \"Ġpotions\": 46907,\n    \"ĠAnon\": 46908,\n    \"aah\": 46909,\n    \"Ġdunno\": 46910,\n    \"ĠÎ¼\": 46911,\n    \"Ġmethodological\": 46912,\n    \"itles\": 46913,\n    \"phia\": 46914,\n    \"Beg\": 46915,\n    \"Rules\": 46916,\n    \"ĠXML\": 46917,\n    \"Ġflask\": 46918,\n    \"ĠShogun\": 46919,\n    \"Ġ2048\": 46920,\n    \"atchewan\": 46921,\n    \"Ġfuckin\": 46922,\n    \"Built\": 46923,\n    \"Ġbour\": 46924,\n    \"Ġdisag\": 46925,\n    \"yss\": 46926,\n    \"ĠÏ\": 46927,\n    \"Spoiler\": 46928,\n    \"Wiki\": 46929,\n    \"Ġmorphology\": 46930,\n    \"Ġendors\": 46931,\n    \"Ġdungeons\": 46932,\n    \"dragon\": 46933,\n    \")),\": 46934,\n    \"Ġhous\": 46935,\n    \"Ġoverwhel\": 46936,\n    \"SAY\": 46937,\n    \"abwe\": 46938,\n    \"--------------------------------\": 46939,\n    \"Ġepist\": 46940,\n    \"Ġpalp\": 46941,\n    \"ĠExtensions\": 46942,\n    \"ĠMistress\": 46943,\n    \"ĠUkrain\": 46944,\n    \"================\": 46945,\n    \"edience\": 46946,\n    \"abama\": 46947,\n    \"ĠLua\": 46948,\n    \"ĠOffline\": 46949,\n    \"ĠKonami\": 46950,\n    \"unicip\": 46951,\n    \"ĠMachina\": 46952,\n    \"Specific\": 46953,\n    \"Ġpresupp\": 46954,\n    \"ĠGEAR\": 46955,\n    \"rition\": 46956,\n    \"rences\": 46957,\n    \"successfully\": 46958,\n    \"Ġ1024\": 46959,\n    \"Platform\": 46960,\n    \"}}\": 46961,\n    \"clude\": 46962,\n    \"roxy\": 46963,\n    \"Ġpromot\": 46964,\n    \"ĠAdapter\": 46965,\n    \"rocal\": 46966,\n    \"ĠMasquerade\": 46967,\n    \"Panel\": 46968,\n    \"Language\": 46969,\n    \"elsius\": 46970,\n    \"Push\": 46971,\n    \"abase\": 46972,\n    \"ĠdB\": 46973,\n    \"argon\": 46974,\n    \"ĠRemoved\": 46975,\n    \"amph\": 46976,\n    \"ĠWyr\": 46977,\n    \"Ġindisp\": 46978,\n    \"ĠOkin\": 46979,\n    \"aepernick\": 46980,\n    \"moil\": 46981,\n    \"Continue\": 46982,\n    \"00007\": 46983,\n    \"ĠJournals\": 46984,\n    \"TAG\": 46985,\n    \"ĠRemastered\": 46986,\n    \"Ġsymp\": 46987,\n    \"methyl\": 46988,\n    \"Overview\": 46989,\n    \"umeric\": 46990,\n    \"ĠCodex\": 46991,\n    \".$\": 46992,\n    \"ranged\": 46993,\n    \"Sym\": 46994,\n    \"ĠVerse\": 46995,\n    \"ĠEnabled\": 46996,\n    \"ĠFUCK\": 46997,\n    \"ĠHearth\": 46998,\n    \"Ġbrill\": 46999,\n    \"ĠChaser\": 47000,\n    \"Beh\": 47001,\n    \"ĠAlchemy\": 47002,\n    \"Oracle\": 47003,\n    \"roleum\": 47004,\n    \"ĠVoldemort\": 47005,\n    \"();\": 47006,\n    \"Ġcollaps\": 47007,\n    \"Visual\": 47008,\n    \"ĠAngular\": 47009,\n    \"ĠOsc\": 47010,\n    \"ichita\": 47011,\n    \"Ġcig\": 47012,\n    \"Ġtoolbar\": 47013,\n    \"ĠEnlight\": 47014,\n    \"ÑĮ\": 47015,\n    \"Îµ\": 47016,\n    \"aliation\": 47017,\n    \"ĠLovecraft\": 47018,\n    \"jri\": 47019,\n    \"ĠInterstellar\": 47020,\n    \"Ġdebugging\": 47021,\n    \"Ġparentheses\": 47022,\n    \"ĠInit\": 47023,\n    \"Located\": 47024,\n    \"Weak\": 47025,\n    \"ĠPvP\": 47026,\n    \"ĠCloak\": 47027,\n    \"uture\": 47028,\n    \"iths\": 47029,\n    \"asionally\": 47030,\n    \"FACE\": 47031,\n    \"Introdu\": 47032,\n    \"');\": 47033,\n    \"slot\": 47034,\n    \"aturday\": 47035,\n    \"ĠNiet\": 47036,\n    \"Ġpuzz\": 47037,\n    \"!!!!!!!!\": 47038,\n    \"folios\": 47039,\n    \"Ç\": 47040,\n    \"Ġverbs\": 47041,\n    \"ĠFrames\": 47042,\n    \"ĠAmbro\": 47043,\n    \"Ġmillisec\": 47044,\n    \"ĠRebell\": 47045,\n    \"ylum\": 47046,\n    \"PASS\": 47047,\n    \"ĠConfiguration\": 47048,\n    \"Î¼\": 47049,\n    \"brids\": 47050,\n    \"vantage\": 47051,\n    \"Ġ['\": 47052,\n    \"ĠScy\": 47053,\n    \"Benef\": 47054,\n    \"gradation\": 47055,\n    \"ĠOrc\": 47056,\n    \"Resources\": 47057,\n    \"Awesome\": 47058,\n    \"ĠMilitia\": 47059,\n    \"POST\": 47060,\n    \"Ġbinaries\": 47061,\n    \"Mode\": 47062,\n    \"Ġkb\": 47063,\n    \"ĠWARRANT\": 47064,\n    \"hemy\": 47065,\n    \"Desc\": 47066,\n    \"alion\": 47067,\n    \"Ġwiki\": 47068,\n    \"Ġcommer\": 47069,\n    \"Serial\": 47070,\n    \"ĠUncommon\": 47071,\n    \"ignore\": 47072,\n    \"Ġconstructor\": 47073,\n    \"ctl\": 47074,\n    \"Ġ):\": 47075,\n    \"ĠVerify\": 47076,\n    \"Notice\": 47077,\n    \"ĠRPGs\": 47078,\n    \"uckland\": 47079,\n    \"Ġincre\": 47080,\n    \"Pinterest\": 47081,\n    \"ĠDefinitions\": 47082,\n    \"iband\": 47083,\n    \"Ġtd\": 47084,\n    \"Ġsubscrib\": 47085,\n    \"Shin\": 47086,\n    \"ĠGadget\": 47087,\n    \"Document\": 47088,\n    \"å®\": 47089,\n    \"Requ\": 47090,\n    \"QUIRE\": 47091,\n    \"ĠQuadro\": 47092,\n    \"ĠUnix\": 47093,\n    \"Enlarge\": 47094,\n    \"thens\": 47095,\n    \"\\\"...\": 47096,\n    \"gebra\": 47097,\n    \"pload\": 47098,\n    \"alogue\": 47099,\n    \"vironments\": 47100,\n    \"Strength\": 47101,\n    \"ĠPID\": 47102,\n    \"ĠInvaders\": 47103,\n    \"HOME\": 47104,\n    \"Atl\": 47105,\n    \"ĠBlizz\": 47106,\n    \"ĠWidth\": 47107,\n    \"ĠOpenGL\": 47108,\n    \"zx\": 47109,\n    \"$,\": 47110,\n    \"Ġå\": 47111,\n    \"cig\": 47112,\n    \"lectic\": 47113,\n    \"relation\": 47114,\n    \"Ġfeas\": 47115,\n    \"undown\": 47116,\n    \"Said\": 47117,\n    \"Î½\": 47118,\n    \"ï¿½ï¿½\": 47119,\n    \"english\": 47120,\n    \"ĠTokens\": 47121,\n    \"ĠALEC\": 47122,\n    \"OOOO\": 47123,\n    \"isconsin\": 47124,\n    \"Ġconstants\": 47125,\n    \"ĠTemplar\": 47126,\n    \"Accept\": 47127,\n    \"Ġmascul\": 47128,\n    \"enegger\": 47129,\n    \"ampires\": 47130,\n    \"Rated\": 47131,\n    \"lua\": 47132,\n    \"ucl\": 47133,\n    \"ĠSequence\": 47134,\n    \"ĠNRS\": 47135,\n    \"STD\": 47136,\n    \"Cra\": 47137,\n    \"autions\": 47138,\n    \"ĠKernel\": 47139,\n    \"oleon\": 47140,\n    \"htaking\": 47141,\n    \"ancial\": 47142,\n    \"Pages\": 47143,\n    \"orthodox\": 47144,\n    \"ropy\": 47145,\n    \"EEE\": 47146,\n    \"Ġtranssexual\": 47147,\n    \"?????\": 47148,\n    \"Ġsurpr\": 47149,\n    \"arthy\": 47150,\n    \"ĠPsychic\": 47151,\n    \"Ġdorsal\": 47152,\n    \"cember\": 47153,\n    \"joice\": 47154,\n    \"/+\": 47155,\n    \"verend\": 47156,\n    \"uint\": 47157,\n    \"Ġderog\": 47158,\n    \"Subject\": 47159,\n    \"hemat\": 47160,\n    \"!]\": 47161,\n    \"Ġ);\": 47162,\n    \"Ġmeshes\": 47163,\n    \"Ġreperc\": 47164,\n    \"ĠTerran\": 47165,\n    \"åĪ\": 47166,\n    \"Load\": 47167,\n    \"å¹\": 47168,\n    \"ikarp\": 47169,\n    \"rompt\": 47170,\n    \"Ġgoblins\": 47171,\n    \"ĠShattered\": 47172,\n    \"tests\": 47173,\n    \"Spread\": 47174,\n    \"ĠNaruto\": 47175,\n    \"Ġpredic\": 47176,\n    \"Hyp\": 47177,\n    \"ĠArkham\": 47178,\n    \"ĠNASL\": 47179,\n    \"Material\": 47180,\n    \"Rule\": 47181,\n    \"raviolet\": 47182,\n    \"ĠKlingon\": 47183,\n    \"Memory\": 47184,\n    \"acers\": 47185,\n    \"Known\": 47186,\n    \"Important\": 47187,\n    \"ĠÎ±\": 47188,\n    \"Ġtraged\": 47189,\n    \"Ġshalt\": 47190,\n    \"Ġiso\": 47191,\n    \"ĠJSON\": 47192,\n    \"Instant\": 47193,\n    \"Ġpg\": 47194,\n    \"Ġexponent\": 47195,\n    \"formance\": 47196,\n    \"bitcoin\": 47197,\n    \"DOS\": 47198,\n    \"cheat\": 47199,\n    \"Ġrook\": 47200,\n    \"ĠBiol\": 47201,\n    \"noticed\": 47202,\n    \"Ġtwent\": 47203,\n    \"ĠRedux\": 47204,\n    \"ĠBorderlands\": 47205,\n    \"Supported\": 47206,\n    \"TRUMP\": 47207,\n    \"Ġturrets\": 47208,\n    \"include\": 47209,\n    \"Effect\": 47210,\n    \"Ġdisg\": 47211,\n    \"ophical\": 47212,\n    \"ĠFaction\": 47213,\n    \"wiki\": 47214,\n    \"Ġsrc\": 47215,\n    \"Laun\": 47216,\n    \"TIT\": 47217,\n    \"Ġorbs\": 47218,\n    \"Ġincompet\": 47219,\n    \"Ġdescriptor\": 47220,\n    \"ĠTrog\": 47221,\n    \"Contribut\": 47222,\n    \"ĠGodd\": 47223,\n    \"inances\": 47224,\n    \"Ult\": 47225,\n    \"lyak\": 47226,\n    \"âĢ¢âĢ¢âĢ¢âĢ¢\": 47227,\n    \"stitial\": 47228,\n    \"essim\": 47229,\n    \"Graphics\": 47230,\n    \"ubis\": 47231,\n    \"Ġegreg\": 47232,\n    \"DEV\": 47233,\n    \"Ġannotations\": 47234,\n    \"Yang\": 47235,\n    \"ĠDruid\": 47236,\n    \"ĠInquisition\": 47237,\n    \"ohydrate\": 47238,\n    \"Critical\": 47239,\n    \"æĸ\": 47240,\n    \"Sample\": 47241,\n    \"ĠPref\": 47242,\n    \"ĠUnleashed\": 47243,\n    \"ĠAccessed\": 47244,\n    \"Ġconceptions\": 47245,\n    \"Minor\": 47246,\n    \"pard\": 47247,\n    \"prus\": 47248,\n    \"Factory\": 47249,\n    \"thinkable\": 47250,\n    \"Ġexecutable\": 47251,\n    \"chapter\": 47252,\n    \"inyl\": 47253,\n    \"Display\": 47254,\n    \"ilater\": 47255,\n    \"Released\": 47256,\n    \"ĠDirectX\": 47257,\n    \"aneers\": 47258,\n    \"Ġ______\": 47259,\n    \"ĠHilbert\": 47260,\n    \"Options\": 47261,\n    \"Ġsorcery\": 47262,\n    \"esm\": 47263,\n    \"ÏĦ\": 47264,\n    \"Ġdescript\": 47265,\n    \"ĠTycoon\": 47266,\n    \"psons\": 47267,\n    \"Ġcov\": 47268,\n    \"Launch\": 47269,\n    \"ogeneity\": 47270,\n    \"Ġsacrific\": 47271,\n    \"ADRA\": 47272,\n    \"netflix\": 47273,\n    \"flix\": 47274,\n    \"usage\": 47275,\n    \"properties\": 47276,\n    \"attach\": 47277,\n    \"req\": 47278,\n    \"Resource\": 47279,\n    \"requisite\": 47280,\n    \"1007\": 47281,\n    \"ĠMIDI\": 47282,\n    \"ĠZoro\": 47283,\n    \"Tue\": 47284,\n    \"hower\": 47285,\n    \"dds\": 47286,\n    \"ynasty\": 47287,\n    \"headers\": 47288,\n    \"Ġdisproportion\": 47289,\n    \"omaly\": 47290,\n    \"Ġvim\": 47291,\n    \"inces\": 47292,\n    \"edient\": 47293,\n    \"ĠWraith\": 47294,\n    \"ilibrium\": 47295,\n    \"Hig\": 47296,\n    \"ĠFrie\": 47297,\n    \"Meat\": 47298,\n    \"ldom\": 47299,\n    \"KNOWN\": 47300,\n    \"orgetown\": 47301,\n    \"Improve\": 47302,\n    \"10000\": 47303,\n    \"Ġretarded\": 47304,\n    \"Disclaimer\": 47305,\n    \"Ġunfocused\": 47306,\n    \"ĠUnsure\": 47307,\n    \"ĠElixir\": 47308,\n    \"idth\": 47309,\n    \"atural\": 47310,\n    \"ĠErr\": 47311,\n    \"Critics\": 47312,\n    \"ĠBows\": 47313,\n    \"ifferent\": 47314,\n    \"proxy\": 47315,\n    \"Lic\": 47316,\n    \"aucas\": 47317,\n    \"rolet\": 47318,\n    \"ĠCoC\": 47319,\n    \"Ġdoesnt\": 47320,\n    \"phabet\": 47321,\n    \"Version\": 47322,\n    \"Ġhepat\": 47323,\n    \"gif\": 47324,\n    \"izophren\": 47325,\n    \"ãĥ»\": 47326,\n    \"ĠGutenberg\": 47327,\n    \"Î²\": 47328,\n    \"phans\": 47329,\n    \"Scene\": 47330,\n    \"Ġaccomp\": 47331,\n    \"ilings\": 47332,\n    \"rypted\": 47333,\n    \"aceae\": 47334,\n    \"arantine\": 47335,\n    \"heses\": 47336,\n    \"iasco\": 47337,\n    \"lopp\": 47338,\n    \"ĠGSL\": 47339,\n    \"disk\": 47340,\n    \"ãĢģ\": 47341,\n    \"0010\": 47342,\n    \"ĠOutbreak\": 47343,\n    \"Column\": 47344,\n    \"odox\": 47345,\n    \"atform\": 47346,\n    \"ĠThrust\": 47347,\n    \"ĠSVG\": 47348,\n    \"Enhanced\": 47349,\n    \"Â¯\": 47350,\n    \"Tools\": 47351,\n    \"rogens\": 47352,\n    \"xus\": 47353,\n    \"Available\": 47354,\n    \"zbollah\": 47355,\n    \"è¡\": 47356,\n    \"osate\": 47357,\n    \"usb\": 47358,\n    \"ordes\": 47359,\n    \"Matrix\": 47360,\n    \"ĠBlazing\": 47361,\n    \"ascus\": 47362,\n    \"ĠSovere\": 47363,\n    \"hement\": 47364,\n    \"*:\": 47365,\n    \"amaru\": 47366,\n    \"Ġparsed\": 47367,\n    \"Bonus\": 47368,\n    \"otrop\": 47369,\n    \"spell\": 47370,\n    \"ancock\": 47371,\n    \"ĠEnchant\": 47372,\n    \"vP\": 47373,\n    \"ĠReferred\": 47374,\n    \"Ġalot\": 47375,\n    \"ĠRuntime\": 47376,\n    \"ĠFn\": 47377,\n    \"CPU\": 47378,\n    \"ĠNicotine\": 47379,\n    \"External\": 47380,\n    \"ĠNightmares\": 47381,\n    \"Ġentropy\": 47382,\n    \"kB\": 47383,\n    \"ĠRealms\": 47384,\n    \"Ġ##\": 47385,\n    \"Ġsubmar\": 47386,\n    \"ĠSlime\": 47387,\n    \"itual\": 47388,\n    \"ĠBastard\": 47389,\n    \"Ġacknowled\": 47390,\n    \"Magazine\": 47391,\n    \"rendered\": 47392,\n    \"ircraft\": 47393,\n    \"CSS\": 47394,\n    \"Numbers\": 47395,\n    \"Pg\": 47396,\n    \"utenant\": 47397,\n    \"ĠPalest\": 47398,\n    \"ĠRoose\": 47399,\n    \"udicrous\": 47400,\n    \"anooga\": 47401,\n    \"Unt\": 47402,\n    \"Ġcapacitor\": 47403,\n    \"Ġschema\": 47404,\n    \"hematic\": 47405,\n    \"ĠPinball\": 47406,\n    \"endars\": 47407,\n    \"Ġ===\": 47408,\n    \"nsic\": 47409,\n    \"ipedia\": 47410,\n    \"Ġchromos\": 47411,\n    \"ĠmRNA\": 47412,\n    \"Ct\": 47413,\n    \"ĠPaladin\": 47414,\n    \"sonian\": 47415,\n    \"Ġæ\": 47416,\n    \"ajor\": 47417,\n    \"repeat\": 47418,\n    \"ortex\": 47419,\n    \"ĠHeroic\": 47420,\n    \"ĠHera\": 47421,\n    \"ociated\": 47422,\n    \"Ġdebug\": 47423,\n    \"osher\": 47424,\n    \"upiter\": 47425,\n    \"_.\": 47426,\n    \"Ġsys\": 47427,\n    \"ĠDownloads\": 47428,\n    \"','\": 47429,\n    \"Adventure\": 47430,\n    \"FORE\": 47431,\n    \"ocument\": 47432,\n    \"arning\": 47433,\n    \"Ġmiscon\": 47434,\n    \"vidia\": 47435,\n    \"Cod\": 47436,\n    \"ibraries\": 47437,\n    \"buffer\": 47438,\n    \"cdn\": 47439,\n    \"ĠModes\": 47440,\n    \"tarian\": 47441,\n    \"ĠPyro\": 47442,\n    \"ĠFixes\": 47443,\n    \"ĠâĪ\": 47444,\n    \"ĠCf\": 47445,\n    \"Testing\": 47446,\n    \"Byte\": 47447,\n    \"nants\": 47448,\n    \"oufl\": 47449,\n    \"ĠCipher\": 47450,\n    \"Aim\": 47451,\n    \"ĠAfgh\": 47452,\n    \"ĠStarCraft\": 47453,\n    \"intendent\": 47454,\n    \"akespe\": 47455,\n    \"Apply\": 47456,\n    \">>>\": 47457,\n    \"Lenin\": 47458,\n    \"ĠShaman\": 47459,\n    \"%\\\"\": 47460,\n    \"ĠFrenzy\": 47461,\n    \"illusion\": 47462,\n    \"===\": 47463,\n    \"Website\": 47464,\n    \"Allow\": 47465,\n    \"ĠBinary\": 47466,\n    \"ensable\": 47467,\n    \"ĠEmpires\": 47468,\n    \"Ġpromul\": 47469,\n    \"ormonal\": 47470,\n    \"ileaks\": 47471,\n    \"ĠAmmo\": 47472,\n    \"assies\": 47473,\n    \"atican\": 47474,\n    \"avior\": 47475,\n    \"ĠIter\": 47476,\n    \"1024\": 47477,\n    \"uesday\": 47478,\n    \"ĠAppears\": 47479,\n    \"achine\": 47480,\n    \"Problem\": 47481,\n    \"ousy\": 47482,\n    \"ramid\": 47483,\n    \"nox\": 47484,\n    \"Â·Â·\": 47485,\n    \"omething\": 47486,\n    \"ĠPurg\": 47487,\n    \"artney\": 47488,\n    \"Ġ0000\": 47489,\n    \"psey\": 47490,\n    \"Ġglutamate\": 47491,\n    \"ĠActivate\": 47492,\n    \"Repl\": 47493,\n    \"Priv\": 47494,\n    \"cyclop\": 47495,\n    \"ĠHispan\": 47496,\n    \"atsuki\": 47497,\n    \"Likewise\": 47498,\n    \"JOHN\": 47499,\n    \"POSE\": 47500,\n    \"pherd\": 47501,\n    \"schild\": 47502,\n    \"Ġsuffix\": 47503,\n    \"åĲ\": 47504,\n    \"Ġoptionally\": 47505,\n    \"ĠRecomm\": 47506,\n    \"ĠSpawn\": 47507,\n    \"ARDIS\": 47508,\n    \"Ġinconsist\": 47509,\n    \"Ġenglish\": 47510,\n    \"Beta\": 47511,\n    \"ĠContains\": 47512,\n    \"uddenly\": 47513,\n    \"Ġls\": 47514,\n    \"Dynamic\": 47515,\n    \"åĽ\": 47516,\n    \"Ġ{{\": 47517,\n    \"dq\": 47518,\n    \"Hmm\": 47519,\n    \"oliberal\": 47520,\n    \"ĠCarnage\": 47521,\n    \"ĠRebirth\": 47522,\n    \"incerity\": 47523,\n    \"Ġproletariat\": 47524,\n    \"ĠCrafting\": 47525,\n    \"Explore\": 47526,\n    \"Ġeld\": 47527,\n    \"ĠAnarch\": 47528,\n    \"Ġ(>\": 47529,\n    \"ĠClockwork\": 47530,\n    \"ĠProced\": 47531,\n    \"APTER\": 47532,\n    \"ĠSorcerer\": 47533,\n    \"âĶ\": 47534,\n    \"ĠSnape\": 47535,\n    \"elist\": 47536,\n    \"Balance\": 47537,\n    \"Tube\": 47538,\n    \"Ġ--------------------\": 47539,\n    \"Ġnostalg\": 47540,\n    \"ACTED\": 47541,\n    \"ĠVID\": 47542,\n    \"soever\": 47543,\n    \"ignt\": 47544,\n    \"Ġhypothal\": 47545,\n    \"ĠObj\": 47546,\n    \"igure\": 47547,\n    \"ĠElves\": 47548,\n    \"gorithm\": 47549,\n    \"Romney\": 47550,\n    \"idable\": 47551,\n    \"renheit\": 47552,\n    \"aptic\": 47553,\n    \"Ġnonex\": 47554,\n    \"Profile\": 47555,\n    \"Ġscient\": 47556,\n    \"ĠAchievements\": 47557,\n    \"ĠReload\": 47558,\n    \"Products\": 47559,\n    \"ampire\": 47560,\n    \"pread\": 47561,\n    \"ĠYamato\": 47562,\n    \"Thread\": 47563,\n    \"ĠFML\": 47564,\n    \"ĠForsaken\": 47565,\n    \"Statistics\": 47566,\n    \"Ġ([\": 47567,\n    \"utsu\": 47568,\n    \"nces\": 47569,\n    \"...?\": 47570,\n    \"upload\": 47571,\n    \"Typ\": 47572,\n    \"ĠReflex\": 47573,\n    \"Dial\": 47574,\n    \"Ġspawns\": 47575,\n    \"Server\": 47576,\n    \"Ġacquaint\": 47577,\n    \"iterranean\": 47578,\n    \"='\": 47579,\n    \"Device\": 47580,\n    \"×¨\": 47581,\n    \"ocaly\": 47582,\n    \"Remove\": 47583,\n    \"Ġ=====\": 47584,\n    \"Ġabdom\": 47585,\n    \"ideos\": 47586,\n    \"Dual\": 47587,\n    \"Fax\": 47588,\n    \"Ġbesie\": 47589,\n    \"ĠAdin\": 47590,\n    \"Ġdescrib\": 47591,\n    \"Ġiod\": 47592,\n    \"Limit\": 47593,\n    \"aunders\": 47594,\n    \"ĠAssassins\": 47595,\n    \"xxxx\": 47596,\n    \"ulner\": 47597,\n    \"Shipping\": 47598,\n    \"Item\": 47599,\n    \"fortune\": 47600,\n    \"Ġcipher\": 47601,\n    \"mA\": 47602,\n    \"acerb\": 47603,\n    \"ebus\": 47604,\n    \"Ġmodifiers\": 47605,\n    \"Added\": 47606,\n    \"prisingly\": 47607,\n    \"Dir\": 47608,\n    \"ĠArchangel\": 47609,\n    \"umbnails\": 47610,\n    \"Huh\": 47611,\n    \"ĠWARN\": 47612,\n    \"Role\": 47613,\n    \"usional\": 47614,\n    \"Ġcortical\": 47615,\n    \"ĠSCP\": 47616,\n    \"ĠException\": 47617,\n    \"ĠWarhammer\": 47618,\n    \")))\": 47619,\n    \"](\": 47620,\n    \"Ġsynaptic\": 47621,\n    \"Ġcached\": 47622,\n    \"archment\": 47623,\n    \"Ġtarg\": 47624,\n    \"Filter\": 47625,\n    \"ĠHades\": 47626,\n    \"Ġprinc\": 47627,\n    \"halla\": 47628,\n    \"ptoms\": 47629,\n    \"Ïģ\": 47630,\n    \"ructose\": 47631,\n    \"termination\": 47632,\n    \"Ġcompe\": 47633,\n    \"define\": 47634,\n    \"Ġprosec\": 47635,\n    \"require\": 47636,\n    \"ĠCorpse\": 47637,\n    \"Abstract\": 47638,\n    \"********************************\": 47639,\n    \"Used\": 47640,\n    \"ĠIbid\": 47641,\n    \"trak\": 47642,\n    \"ä¸Ń\": 47643,\n    \"ĠGABA\": 47644,\n    \"åĬ\": 47645,\n    \"ĠHegel\": 47646,\n    \"Jere\": 47647,\n    \"odore\": 47648,\n    \"í\": 47649,\n    \"namese\": 47650,\n    \"Origin\": 47651,\n    \"ĠMastery\": 47652,\n    \"gerald\": 47653,\n    \"Charges\": 47654,\n    \"--------------------\": 47655,\n    \"Forge\": 47656,\n    \"comings\": 47657,\n    \"åį\": 47658,\n    \"Ġ(&\": 47659,\n    \"Ġgrap\": 47660,\n    \"Mask\": 47661,\n    \"ĠGundam\": 47662,\n    \"generic\": 47663,\n    \"ĠMalf\": 47664,\n    \"raphics\": 47665,\n    \"Internal\": 47666,\n    \"ourge\": 47667,\n    \"Ġirresist\": 47668,\n    \"sterdam\": 47669,\n    \"Ġendogenous\": 47670,\n    \"Export\": 47671,\n    \"Ġë\": 47672,\n    \"poons\": 47673,\n    \"Ġabund\": 47674,\n    \"ĠQuantity\": 47675,\n    \"Issue\": 47676,\n    \"âĪĴ\": 47677,\n    \"cknow\": 47678,\n    \"Anonymous\": 47679,\n    \"ĠDRAG\": 47680,\n    \"Wikipedia\": 47681,\n    \"Ġsubdu\": 47682,\n    \"iverpool\": 47683,\n    \"apesh\": 47684,\n    \"Ability\": 47685,\n    \"ĠCentOS\": 47686,\n    \"iseum\": 47687,\n    \"lycer\": 47688,\n    \"Untitled\": 47689,\n    \"Ġlineback\": 47690,\n    \"Ġtomat\": 47691,\n    \"byte\": 47692,\n    \"tile\": 47693,\n    \"linux\": 47694,\n    \"Palest\": 47695,\n    \"canon\": 47696,\n    \"FAULT\": 47697,\n    \"ĠkHz\": 47698,\n    \"Ġhelic\": 47699,\n    \"ĠIGF\": 47700,\n    \"WARE\": 47701,\n    \"Feature\": 47702,\n    \"ĠGraveyard\": 47703,\n    \"ĠNemesis\": 47704,\n    \"akuya\": 47705,\n    \"inement\": 47706,\n    \"Ġwhence\": 47707,\n    \"ractical\": 47708,\n    \"Ping\": 47709,\n    \"tesque\": 47710,\n    \"scroll\": 47711,\n    \"espie\": 47712,\n    \"Ġasynchronous\": 47713,\n    \"ocre\": 47714,\n    \"Measure\": 47715,\n    \"morph\": 47716,\n    \"std\": 47717,\n    \"Settings\": 47718,\n    \"Course\": 47719,\n    \"Ġ],\": 47720,\n    \"Ïĥ\": 47721,\n    \"Documents\": 47722,\n    \"estern\": 47723,\n    \"Ġtf\": 47724,\n    \"Ġcircumcised\": 47725,\n    \"geant\": 47726,\n    \"Ġconject\": 47727,\n    \"ĠFolder\": 47728,\n    \"outube\": 47729,\n    \"ĠMedline\": 47730,\n    \"Status\": 47731,\n    \"ctr\": 47732,\n    \"anoia\": 47733,\n    \"ĠPowerShell\": 47734,\n    \"Chel\": 47735,\n    \"Loop\": 47736,\n    \"Ġresize\": 47737,\n    \"aphael\": 47738,\n    \"workshop\": 47739,\n    \"velength\": 47740,\n    \"hover\": 47741,\n    \"flush\": 47742,\n    \"ĠÎ²\": 47743,\n    \"Task\": 47744,\n    \"pedia\": 47745,\n    \"ptin\": 47746,\n    \"bidden\": 47747,\n    \"windows\": 47748,\n    \"ĠCaucas\": 47749,\n    \"aml\": 47750,\n    \"isoft\": 47751,\n    \"Ġrs\": 47752,\n    \"cgi\": 47753,\n    \"urrection\": 47754,\n    \"miah\": 47755,\n    \"ÏĤ\": 47756,\n    \"Ġplaythrough\": 47757,\n    \"Reddit\": 47758,\n    \"×ľ\": 47759,\n    \"Ġannotation\": 47760,\n    \"Ġnobles\": 47761,\n    \"seq\": 47762,\n    \"mares\": 47763,\n    \"Ġwik\": 47764,\n    \"foreseen\": 47765,\n    \"RPG\": 47766,\n    \"Ġreper\": 47767,\n    \"aredevil\": 47768,\n    \"arcity\": 47769,\n    \"/\\\"\": 47770,\n    \"Ġ});\": 47771,\n    \"Ġdiscont\": 47772,\n    \"ĠBinding\": 47773,\n    \"answered\": 47774,\n    \"Mesh\": 47775,\n    \"ĠMPEG\": 47776,\n    \"Ġperceptual\": 47777,\n    \"OTAL\": 47778,\n    \"ursive\": 47779,\n    \"ãģĦ\": 47780,\n    \"Ġplun\": 47781,\n    \"onential\": 47782,\n    \"ãĤ\": 47783,\n    \"ĠReloaded\": 47784,\n    \"iscopal\": 47785,\n    \"ĠDespair\": 47786,\n    \"FIX\": 47787,\n    \"Ġheterogeneity\": 47788,\n    \",[\": 47789,\n    \"ichick\": 47790,\n    \"DCS\": 47791,\n    \"Ġcooldown\": 47792,\n    \"................\": 47793,\n    \"Ġsomew\": 47794,\n    \"Battery\": 47795,\n    \"stract\": 47796,\n    \"Attempt\": 47797,\n    \"allery\": 47798,\n    \"ĠNept\": 47799,\n    \"Ġtac\": 47800,\n    \"ĠElemental\": 47801,\n    \"Function\": 47802,\n    \"Ġbindings\": 47803,\n    \"versive\": 47804,\n    \"ĠWarlock\": 47805,\n    \"Response\": 47806,\n    \"ĠNPCs\": 47807,\n    \"ollower\": 47808,\n    \"ĠReborn\": 47809,\n    \"Ġphenotype\": 47810,\n    \"uscript\": 47811,\n    \"Ġpecul\": 47812,\n    \"!/\": 47813,\n    \"Unique\": 47814,\n    \"ĠFreeBSD\": 47815,\n    \"ĠChero\": 47816,\n    \"Ġcolle\": 47817,\n    \"gently\": 47818,\n    \"Empty\": 47819,\n    \"rss\": 47820,\n    \"Ġdd\": 47821,\n    \"forge\": 47822,\n    \"ĠTraps\": 47823,\n    \"×Ķ\": 47824,\n    \"iblical\": 47825,\n    \"---------\": 47826,\n    \"uminati\": 47827,\n    \"login\": 47828,\n    \"asus\": 47829,\n    \"xual\": 47830,\n    \"ĠMiko\": 47831,\n    \"ĠDrac\": 47832,\n    \"ssh\": 47833,\n    \"Submit\": 47834,\n    \"ĠMultiplayer\": 47835,\n    \"leanor\": 47836,\n    \"Orig\": 47837,\n    \"anism\": 47838,\n    \"peror\": 47839,\n    \"ĠESV\": 47840,\n    \"Ġencour\": 47841,\n    \"å°\": 47842,\n    \"ĠPLoS\": 47843,\n    \"ĠCrusher\": 47844,\n    \"ocrates\": 47845,\n    \"ynchronous\": 47846,\n    \"Â§\": 47847,\n    \"ĠLuffy\": 47848,\n    \"Lastly\": 47849,\n    \"Ġdiffere\": 47850,\n    \"okane\": 47851,\n    \"Enh\": 47852,\n    \"ursor\": 47853,\n    \"Ġapopt\": 47854,\n    \"ĠTotem\": 47855,\n    \"ä½\": 47856,\n    \"Honest\": 47857,\n    \"xml\": 47858,\n    \"Created\": 47859,\n    \"Ġteleport\": 47860,\n    \"NRS\": 47861,\n    \"ccess\": 47862,\n    \"ilitary\": 47863,\n    \"ackets\": 47864,\n    \"Ġenchantment\": 47865,\n    \"ĠCunning\": 47866,\n    \"ortmund\": 47867,\n    \"Altern\": 47868,\n    \"Alternatively\": 47869,\n    \"ĠLuthor\": 47870,\n    \"Publisher\": 47871,\n    \"GBT\": 47872,\n    \"çĶ\": 47873,\n    \"Activity\": 47874,\n    \"Ġleptin\": 47875,\n    \"æĪ\": 47876,\n    \"ĠStarfleet\": 47877,\n    \"å¸\": 47878,\n    \"oooooooo\": 47879,\n    \"Ġlawy\": 47880,\n    \"Frag\": 47881,\n    \"×ª\": 47882,\n    \"yright\": 47883,\n    \"cookie\": 47884,\n    \"Finish\": 47885,\n    \"wikipedia\": 47886,\n    \"ĠAbilities\": 47887,\n    \"interface\": 47888,\n    \"Ġglared\": 47889,\n    \"Engineers\": 47890,\n    \"ĠAtk\": 47891,\n    \"oteric\": 47892,\n    \"Ġbyte\": 47893,\n    \"ossibility\": 47894,\n    \"Label\": 47895,\n    \"ĠCSV\": 47896,\n    \"Ġè\": 47897,\n    \"ĠOblivion\": 47898,\n    \"android\": 47899,\n    \"rehensive\": 47900,\n    \"ĠCommands\": 47901,\n    \"clud\": 47902,\n    \"ĠTutorial\": 47903,\n    \"retched\": 47904,\n    \"irlwind\": 47905,\n    \"conserv\": 47906,\n    \"ministic\": 47907,\n    \"void\": 47908,\n    \"ernels\": 47909,\n    \"alias\": 47910,\n    \"ĠDraco\": 47911,\n    \"desktop\": 47912,\n    \"ĠMormonism\": 47913,\n    \"oÄŁ\": 47914,\n    \"kef\": 47915,\n    \"Ġtimestamp\": 47916,\n    \"WAYS\": 47917,\n    \"ãģĹ\": 47918,\n    \"\\\"(\": 47919,\n    \"eneg\": 47920,\n    \"CHAT\": 47921,\n    \"Ġnpm\": 47922,\n    \"ĠGrenade\": 47923,\n    \"rongh\": 47924,\n    \"dinand\": 47925,\n    \"Definition\": 47926,\n    \"ĠInteger\": 47927,\n    \"Ġmodifier\": 47928,\n    \"Ġdex\": 47929,\n    \"ĠParameters\": 47930,\n    \"andestine\": 47931,\n    \"ĠSHALL\": 47932,\n    \"Purchase\": 47933,\n    \"enaries\": 47934,\n    \"Ġstarship\": 47935,\n    \"Armor\": 47936,\n    \"Skill\": 47937,\n    \"Ġlookup\": 47938,\n    \"verages\": 47939,\n    \"Minimum\": 47940,\n    \"ĠBleach\": 47941,\n    \"Ġdf\": 47942,\n    \"inosaur\": 47943,\n    \"ixel\": 47944,\n    \"Zip\": 47945,\n    \"temp\": 47946,\n    \"ruby\": 47947,\n    \"Fram\": 47948,\n    \"sword\": 47949,\n    \"Minecraft\": 47950,\n    \"strous\": 47951,\n    \"Client\": 47952,\n    \"ĠBarbarian\": 47953,\n    \"æĹ\": 47954,\n    \"USER\": 47955,\n    \"ĠMehran\": 47956,\n    \"axies\": 47957,\n    \"ermanent\": 47958,\n    \"ĠHeader\": 47959,\n    \"ablishment\": 47960,\n    \"hyde\": 47961,\n    \"Snake\": 47962,\n    \"ĠTelesc\": 47963,\n    \"Pocket\": 47964,\n    \"Ġ........\": 47965,\n    \"Destroy\": 47966,\n    \"Method\": 47967,\n    \"ĠZup\": 47968,\n    \"olulu\": 47969,\n    \"Ġunemploy\": 47970,\n    \"Temp\": 47971,\n    \"ĠExplicit\": 47972,\n    \"äºº\": 47973,\n    \"cache\": 47974,\n    \"innamon\": 47975,\n    \"Ġunavoid\": 47976,\n    \"Summary\": 47977,\n    \"Ġappre\": 47978,\n    \"Ġtaxp\": 47979,\n    \"XXX\": 47980,\n    \"ieval\": 47981,\n    \"ĠSummon\": 47982,\n    \"å¤\": 47983,\n    \"Lear\": 47984,\n    \"ibliography\": 47985,\n    \"CLASS\": 47986,\n    \"dimension\": 47987,\n    \"ĠHorde\": 47988,\n    \"Ġfilesystem\": 47989,\n    \"ĠQiao\": 47990,\n    \"obbies\": 47991,\n    \"DIR\": 47992,\n    \"Ġimpedance\": 47993,\n    \"éĩ\": 47994,\n    \"Names\": 47995,\n    \"ĠDrupal\": 47996,\n    \"Applic\": 47997,\n    \"imei\": 47998,\n    \"ynchron\": 47999,\n    \"Ire\": 48000,\n    \"ĠMinion\": 48001,\n    \"ĠHaste\": 48002,\n    \"ä¿\": 48003,\n    \"Ġ(=\": 48004,\n    \"LinkedIn\": 48005,\n    \"Maps\": 48006,\n    \"ifacts\": 48007,\n    \"Damage\": 48008,\n    \"odynam\": 48009,\n    \"ĠShroud\": 48010,\n    \"Ancient\": 48011,\n    \"enhagen\": 48012,\n    \"Tact\": 48013,\n    \"anship\": 48014,\n    \"aturdays\": 48015,\n    \"ãģ«\": 48016,\n    \"ikhail\": 48017,\n    \"ãģ®\": 48018,\n    \"framework\": 48019,\n    \"lication\": 48020,\n    \"âĢ¦]\": 48021,\n    \"Plug\": 48022,\n    \"ĠLilith\": 48023,\n    \"browser\": 48024,\n    \"offset\": 48025,\n    \"ĠJuda\": 48026,\n    \"ciating\": 48027,\n    \"console\": 48028,\n    \"Ġ=================\": 48029,\n    \"._\": 48030,\n    \"ĠPuzz\": 48031,\n    \"OPLE\": 48032,\n    \"erial\": 48033,\n    \"OHN\": 48034,\n    \"ĠGolem\": 48035,\n    \"ierrez\": 48036,\n    \"Ġ},\": 48037,\n    \"inition\": 48038,\n    \"insula\": 48039,\n    \"ĠEntered\": 48040,\n    \"greSQL\": 48041,\n    \"ĠFlask\": 48042,\n    \"ĠXCOM\": 48043,\n    \"fixes\": 48044,\n    \"ĠWeasley\": 48045,\n    \"arser\": 48046,\n    \"Ġrc\": 48047,\n    \"microsoft\": 48048,\n    \"HHHH\": 48049,\n    \"INFO\": 48050,\n    \"rehend\": 48051,\n    \"Ġpolymorph\": 48052,\n    \"Button\": 48053,\n    \"âī\": 48054,\n    \"QUI\": 48055,\n    \"twitch\": 48056,\n    \"jriwal\": 48057,\n    \"ĠSaiyan\": 48058,\n    \"Ġadherent\": 48059,\n    \"acters\": 48060,\n    \"arthed\": 48061,\n    \"âĢł\": 48062,\n    \"Ġfoss\": 48063,\n    \"ã\": 48064,\n    \"Quote\": 48065,\n    \"ependent\": 48066,\n    \"Ġhorr\": 48067,\n    \"UGC\": 48068,\n    \"Weiss\": 48069,\n    \"styles\": 48070,\n    \"advertisement\": 48071,\n    \"Credits\": 48072,\n    \"Lua\": 48073,\n    \"ĠUCH\": 48074,\n    \"Ġhorrend\": 48075,\n    \"Ġminion\": 48076,\n    \">,\": 48077,\n    \"ãĥ³\": 48078,\n    \"Ġinclud\": 48079,\n    \"Compar\": 48080,\n    \"Ġ[]\": 48081,\n    \"Ġ(<\": 48082,\n    \"Phones\": 48083,\n    \"paralleled\": 48084,\n    \"HTML\": 48085,\n    \"Ġ(%\": 48086,\n    \"raltar\": 48087,\n    \"Ġamd\": 48088,\n    \"Maximum\": 48089,\n    \"ĠSolitaire\": 48090,\n    \"SCP\": 48091,\n    \"ĠVaugh\": 48092,\n    \"ĠCLR\": 48093,\n    \"database\": 48094,\n    \"module\": 48095,\n    \"Ì¶\": 48096,\n    \"Capture\": 48097,\n    \"Window\": 48098,\n    \"ubuntu\": 48099,\n    \"Includes\": 48100,\n    \"ĠUriel\": 48101,\n    \"ORPG\": 48102,\n    \"Îº\": 48103,\n    \"âĪ\": 48104,\n    \"ä¸Ģ\": 48105,\n    \"Ġdexter\": 48106,\n    \"ĠGlac\": 48107,\n    \"slice\": 48108,\n    \"HAHAHAHA\": 48109,\n    \"\\\\\\\"\": 48110,\n    \"lations\": 48111,\n    \"ÙĲ\": 48112,\n    \"ĠAUTH\": 48113,\n    \"earch\": 48114,\n    \"ĠSocket\": 48115,\n    \"Character\": 48116,\n    \"Sort\": 48117,\n    \"Ġindist\": 48118,\n    \"/_\": 48119,\n    \"ĠAntar\": 48120,\n    \"ifix\": 48121,\n    \"Ġlich\": 48122,\n    \"variable\": 48123,\n    \"_(\": 48124,\n    \"Ġgui\": 48125,\n    \"Herm\": 48126,\n    \"elvet\": 48127,\n    \"è¯\": 48128,\n    \"Developer\": 48129,\n    \"Ġkcal\": 48130,\n    \"ciation\": 48131,\n    \"Transaction\": 48132,\n    \"Ġdocker\": 48133,\n    \"###\": 48134,\n    \"ĠVegeta\": 48135,\n    \"Result\": 48136,\n    \"ocamp\": 48137,\n    \"aughtered\": 48138,\n    \"Increase\": 48139,\n    \"aples\": 48140,\n    \"iannopoulos\": 48141,\n    \"zbek\": 48142,\n    \"estyles\": 48143,\n    \"emonium\": 48144,\n    \"è¿\": 48145,\n    \"ĠFANT\": 48146,\n    \"Reason\": 48147,\n    \"Elsewhere\": 48148,\n    \"\\\"\\\"\": 48149,\n    \"ĠArtifact\": 48150,\n    \"Authent\": 48151,\n    \"herical\": 48152,\n    \"Ġmembr\": 48153,\n    \"socket\": 48154,\n    \"Elsa\": 48155,\n    \"Condition\": 48156,\n    \"Ġlapt\": 48157,\n    \"Ġsorcerer\": 48158,\n    \"Layer\": 48159,\n    \"apters\": 48160,\n    \"Ġveter\": 48161,\n    \"Myth\": 48162,\n    \"ensical\": 48163,\n    \"ÏĢ\": 48164,\n    \"noxious\": 48165,\n    \"Ġunpre\": 48166,\n    \"Flags\": 48167,\n    \"OOOOOOOO\": 48168,\n    \"Ġincent\": 48169,\n    \"Combat\": 48170,\n    \"Session\": 48171,\n    \"Ġteleportation\": 48172,\n    \"éĢ\": 48173,\n    \"ortment\": 48174,\n    \"Admin\": 48175,\n    \"Fixed\": 48176,\n    \"×Ļ\": 48177,\n    \"Ġconfir\": 48178,\n    \"ãģŁ\": 48179,\n    \"morrow\": 48180,\n    \"osponsors\": 48181,\n    \"\\\\/\": 48182,\n    \"ictionary\": 48183,\n    \"Num\": 48184,\n    \"Ġquir\": 48185,\n    \"åº\": 48186,\n    \"à¨\": 48187,\n    \"Ġ<<\": 48188,\n    \"Attempts\": 48189,\n    \"ãģ§\": 48190,\n    \"Î»\": 48191,\n    \"Features\": 48192,\n    \"XXXX\": 48193,\n    \"Ġinflamm\": 48194,\n    \"VERSION\": 48195,\n    \"ortality\": 48196,\n    \"spawn\": 48197,\n    \"ratulations\": 48198,\n    \"Ġcharism\": 48199,\n    \"Ġ&&\": 48200,\n    \"Dialogue\": 48201,\n    \"luster\": 48202,\n    \"<<\": 48203,\n    \"args\": 48204,\n    \"redients\": 48205,\n    \"Ġpredicate\": 48206,\n    \"qqa\": 48207,\n    \"etheus\": 48208,\n    \"Ġ(!\": 48209,\n    \"Ġshowc\": 48210,\n    \"cmd\": 48211,\n    \"bringer\": 48212,\n    \"Ġcoh\": 48213,\n    \"Input\": 48214,\n    \"ĠFANTASY\": 48215,\n    \"Ġfict\": 48216,\n    \"Blocks\": 48217,\n    \"Install\": 48218,\n    \"vector\": 48219,\n    \"umblr\": 48220,\n    \"agnar\": 48221,\n    \"Array\": 48222,\n    \"Ġembry\": 48223,\n    \"Ġtheoret\": 48224,\n    \"Ġhref\": 48225,\n    \"irrel\": 48226,\n    \"irements\": 48227,\n    \"iations\": 48228,\n    \"Ġ(/\": 48229,\n    \"Thumbnail\": 48230,\n    \"Ġhashes\": 48231,\n    \"^^\": 48232,\n    \"Copy\": 48233,\n    \"Ġeq\": 48234,\n    \"translation\": 48235,\n    \"Favorite\": 48236,\n    \"Fail\": 48237,\n    \"Ġogre\": 48238,\n    \"isites\": 48239,\n    \"Merit\": 48240,\n    \"ãģ¦\": 48241,\n    \"DATA\": 48242,\n    \"rarily\": 48243,\n    \"igmatic\": 48244,\n    \"Sequ\": 48245,\n    \"Els\": 48246,\n    \"ãģª\": 48247,\n    \"lehem\": 48248,\n    \"requency\": 48249,\n    \"aughed\": 48250,\n    \"Ġdistingu\": 48251,\n    \"Ġartific\": 48252,\n    \"Ġdwarves\": 48253,\n    \"Í\": 48254,\n    \"resy\": 48255,\n    \"~~\": 48256,\n    \"sofar\": 48257,\n    \"ideon\": 48258,\n    \"ozyg\": 48259,\n    \"EEEE\": 48260,\n    \"ĠMelee\": 48261,\n    \"å¤§\": 48262,\n    \"tumblr\": 48263,\n    \"ssl\": 48264,\n    \"Wra\": 48265,\n    \"ONSORED\": 48266,\n    \"Ġvowel\": 48267,\n    \"},\": 48268,\n    \"Vari\": 48269,\n    \"cientious\": 48270,\n    \"Node\": 48271,\n    \"Ġsorce\": 48272,\n    \"========\": 48273,\n    \"perse\": 48274,\n    \"Detailed\": 48275,\n    \"isphere\": 48276,\n    \"Background\": 48277,\n    \"ĺħ\": 48278,\n    \"Redd\": 48279,\n    \"ìĿ\": 48280,\n    \"ãģ¨\": 48281,\n    \"ĠCTRL\": 48282,\n    \"Ġç\": 48283,\n    \"iculty\": 48284,\n    \"ername\": 48285,\n    \"Ġns\": 48286,\n    \"Deploy\": 48287,\n    \"Ġhapp\": 48288,\n    \"Ġ///\": 48289,\n    \"Begin\": 48290,\n    \"Ġgp\": 48291,\n    \"$.\": 48292,\n    \"Output\": 48293,\n    \"Suggest\": 48294,\n    \"×Ĳ\": 48295,\n    \"ĠToggle\": 48296,\n    \"Ġnutrit\": 48297,\n    \"Ġ\\\\\\\"\": 48298,\n    \"Ġpreval\": 48299,\n    \"Ġsubreddits\": 48300,\n    \"Menu\": 48301,\n    \"Amount\": 48302,\n    \"ĠWasteland\": 48303,\n    \"Ġsprites\": 48304,\n    \"Ġshader\": 48305,\n    \"Ġ;)\": 48306,\n    \"NAME\": 48307,\n    \"CLUD\": 48308,\n    \"Ġgoblin\": 48309,\n    \"Refer\": 48310,\n    \"ÙĴ\": 48311,\n    \"á¹\": 48312,\n    \"Improved\": 48313,\n    \"endiary\": 48314,\n    \"Ġassail\": 48315,\n    \"chieve\": 48316,\n    \"reply\": 48317,\n    \"Ġcontrad\": 48318,\n    \"cients\": 48319,\n    \"GROUP\": 48320,\n    \"Controller\": 48321,\n    \"omsky\": 48322,\n    \"chemist\": 48323,\n    \"packages\": 48324,\n    \"ombies\": 48325,\n    \"scl\": 48326,\n    \"Ġibn\": 48327,\n    \"çĽ\": 48328,\n    \":(\": 48329,\n    \"ĠMinotaur\": 48330,\n    \"niper\": 48331,\n    \"====\": 48332,\n    \"Ġsubsc\": 48333,\n    \"è¦\": 48334,\n    \"Ġinteger\": 48335,\n    \"Ġ\\\"-\": 48336,\n    \"Ġtheorem\": 48337,\n    \"utenberg\": 48338,\n    \"Trigger\": 48339,\n    \"github\": 48340,\n    \"ä¼\": 48341,\n    \"##\": 48342,\n    \"xtap\": 48343,\n    \"okÃ©\": 48344,\n    \"ilial\": 48345,\n    \"idepress\": 48346,\n    \":\\\\\": 48347,\n    \"Param\": 48348,\n    \"Correction\": 48349,\n    \"Ã¯ve\": 48350,\n    \"Chest\": 48351,\n    \"×©\": 48352,\n    \"ĠÏĦ\": 48353,\n    \"Ġrespawn\": 48354,\n    \"Ġrall\": 48355,\n    \"Ġcreatine\": 48356,\n    \"umsy\": 48357,\n    \"ĠTemplate\": 48358,\n    \"foo\": 48359,\n    \"query\": 48360,\n    \"Ġmanufact\": 48361,\n    \"Hardware\": 48362,\n    \"iframe\": 48363,\n    \"Ġ-------\": 48364,\n    \"Ġrecip\": 48365,\n    \"ĠAttributes\": 48366,\n    \"Ġforeskin\": 48367,\n    \"ãĤĭ\": 48368,\n    \"ãĥĦ\": 48369,\n    \"uania\": 48370,\n    \"................................................................\": 48371,\n    \"Ġphylogen\": 48372,\n    \"eaturing\": 48373,\n    \"Ġsprite\": 48374,\n    \"Ġinvari\": 48375,\n    \"DonaldTrump\": 48376,\n    \"({\": 48377,\n    \"ĠMalfoy\": 48378,\n    \"Gamer\": 48379,\n    \"ĠPlugin\": 48380,\n    \"Î³\": 48381,\n    \"Query\": 48382,\n    \"ĠPuzzles\": 48383,\n    \"inventory\": 48384,\n    \"trl\": 48385,\n    \"Insert\": 48386,\n    \"Ġawa\": 48387,\n    \"ĠWerewolf\": 48388,\n    \"Ġhorizont\": 48389,\n    \"×ŀ\": 48390,\n    \"Ġcunt\": 48391,\n    \"]]\": 48392,\n    \"ĠByz\": 48393,\n    \"Mouse\": 48394,\n    \"Ġ[[\": 48395,\n    \"ĠCthulhu\": 48396,\n    \"ĠDRAGON\": 48397,\n    \"Default\": 48398,\n    \"ĠPresbyter\": 48399,\n    \"Ġff\": 48400,\n    \"Ġorcs\": 48401,\n    \"Construct\": 48402,\n    \"ĠDebug\": 48403,\n    \"Ġ*/\": 48404,\n    \"×ĳ\": 48405,\n    \"Ġembr\": 48406,\n    \"License\": 48407,\n    \"css\": 48408,\n    \"incinn\": 48409,\n    \"Prosecut\": 48410,\n    \"Ġsugg\": 48411,\n    \"å¾\": 48412,\n    \"ĠUndead\": 48413,\n    \"æĿ\": 48414,\n    \"Ġfs\": 48415,\n    \"Ġthw\": 48416,\n    \"Vector\": 48417,\n    \"åĮ\": 48418,\n    \"settings\": 48419,\n    \"å¯\": 48420,\n    \"Ġssh\": 48421,\n    \"ĠConverted\": 48422,\n    \"ãĤĴ\": 48423,\n    \"risome\": 48424,\n    \"Ġagre\": 48425,\n    \"Collection\": 48426,\n    \"cmp\": 48427,\n    \"puter\": 48428,\n    \"alloc\": 48429,\n    \"Ġé\": 48430,\n    \"ascade\": 48431,\n    \"ĠSpells\": 48432,\n    \"Ġ:-)\": 48433,\n    \"Haunted\": 48434,\n    \"Ġadolesc\": 48435,\n    \"FORMATION\": 48436,\n    \"ĠImperium\": 48437,\n    \"ãĥ¼\": 48438,\n    \"Supplement\": 48439,\n    \"Render\": 48440,\n    \"Theme\": 48441,\n    \"ĠTorment\": 48442,\n    \"([\": 48443,\n    \"ëĭ\": 48444,\n    \"Ġhtml\": 48445,\n    \"Ġjuven\": 48446,\n    \"ĠSiber\": 48447,\n    \"Ġdaemon\": 48448,\n    \"ivariate\": 48449,\n    \"objects\": 48450,\n    \"negie\": 48451,\n    \"Ġindu\": 48452,\n    \"landish\": 48453,\n    \"Meta\": 48454,\n    \"Impl\": 48455,\n    \"Ġglyph\": 48456,\n    \"Ġ-->\": 48457,\n    \"Ġstreng\": 48458,\n    \"agascar\": 48459,\n    \"guyen\": 48460,\n    \"((\": 48461,\n    \")[\": 48462,\n    \"ĠNorn\": 48463,\n    \"Ġhippocamp\": 48464,\n    \"ĠÂ¯\": 48465,\n    \"îĢ\": 48466,\n    \"Connection\": 48467,\n    \"PATH\": 48468,\n    \"mbuds\": 48469,\n    \"ĠShards\": 48470,\n    \"Ġadvoc\": 48471,\n    \"Ġsimulac\": 48472,\n    \"âĸĳ\": 48473,\n    \"!?\\\"\": 48474,\n    \"ĠPotion\": 48475,\n    \"Ġamulet\": 48476,\n    \"ĠFnatic\": 48477,\n    \"Ġcryptoc\": 48478,\n    \"wav\": 48479,\n    \"radius\": 48480,\n    \"pkg\": 48481,\n    \"ĠMFT\": 48482,\n    \"æĢ\": 48483,\n    \"Ġtoile\": 48484,\n    \"Items\": 48485,\n    \"ifference\": 48486,\n    \"errors\": 48487,\n    \"ĠCelt\": 48488,\n    \"Ġunpop\": 48489,\n    \"ilogy\": 48490,\n    \"6666\": 48491,\n    \"hesda\": 48492,\n    \"Instruct\": 48493,\n    \"å·\": 48494,\n    \"Materials\": 48495,\n    \"ettings\": 48496,\n    \"Percent\": 48497,\n    \"Ġresistor\": 48498,\n    \"tymology\": 48499,\n    \"Ġdeprecated\": 48500,\n    \"Ġgrep\": 48501,\n    \"ĠWRITE\": 48502,\n    \"Ġtriv\": 48503,\n    \"Ġscrut\": 48504,\n    \"[/\": 48505,\n    \"anyl\": 48506,\n    \"skirts\": 48507,\n    \"MSN\": 48508,\n    \"ĠCodec\": 48509,\n    \"ecd\": 48510,\n    \"Anth\": 48511,\n    \"){\": 48512,\n    \"%]\": 48513,\n    \"veyard\": 48514,\n    \"aspberry\": 48515,\n    \"ãĢ\": 48516,\n    \"Reward\": 48517,\n    \"rha\": 48518,\n    \"Stretch\": 48519,\n    \"]-\": 48520,\n    \"Prev\": 48521,\n    \"Context\": 48522,\n    \"Ġlinux\": 48523,\n    \"HAHA\": 48524,\n    \"perties\": 48525,\n    \"ĠVIDE\": 48526,\n    \"Domain\": 48527,\n    \"Ġmurd\": 48528,\n    \"ĠLegions\": 48529,\n    \"apache\": 48530,\n    \"æŃ\": 48531,\n    \"Pause\": 48532,\n    \"Temperature\": 48533,\n    \"ufact\": 48534,\n    \"igslist\": 48535,\n    \"ĠRetrieved\": 48536,\n    \"èª\": 48537,\n    \"ãģĮ\": 48538,\n    \"Ingredients\": 48539,\n    \"ruary\": 48540,\n    \"dyl\": 48541,\n    \"Alias\": 48542,\n    \"ĠÎĶ\": 48543,\n    \"Ġinval\": 48544,\n    \"amsung\": 48545,\n    \"!--\": 48546,\n    \"olean\": 48547,\n    \"æī\": 48548,\n    \"ãģ¯\": 48549,\n    \"Ġcoefficients\": 48550,\n    \"ĠDHCP\": 48551,\n    \"âĨĴ\": 48552,\n    \"utonium\": 48553,\n    \":[\": 48554,\n    \"âĹ\": 48555,\n    \"cli\": 48556,\n    \"Container\": 48557,\n    \"å¼\": 48558,\n    \"nexus\": 48559,\n    \"SOURCE\": 48560,\n    \"Ò\": 48561,\n    \"=/\": 48562,\n    \"Ġmysql\": 48563,\n    \"ĠGained\": 48564,\n    \"Ġ/*\": 48565,\n    \"uncture\": 48566,\n    \"Ġstatically\": 48567,\n    \"âĸł\": 48568,\n    \"æĺ¯\": 48569,\n    \"æ°\": 48570,\n    \"estamp\": 48571,\n    \"Cache\": 48572,\n    \"ulkan\": 48573,\n    \"staking\": 48574,\n    \"apter\": 48575,\n    \"ãģ¾\": 48576,\n    \"ĠÎ¼g\": 48577,\n    \"Ġtremend\": 48578,\n    \"ĠPiercing\": 48579,\n    \"naissance\": 48580,\n    \"ĠHealer\": 48581,\n    \"Enabled\": 48582,\n    \"éģ\": 48583,\n    \"âĸ\": 48584,\n    \"ĠThumbnails\": 48585,\n    \"Ġhither\": 48586,\n    \"Format\": 48587,\n    \"utherland\": 48588,\n    \"íķ\": 48589,\n    \"Ġdestro\": 48590,\n    \"fff\": 48591,\n    \"execute\": 48592,\n    \"msg\": 48593,\n    \"romancer\": 48594,\n    \"ĠCanaver\": 48595,\n    \"ĠVaults\": 48596,\n    \"oided\": 48597,\n    \"iage\": 48598,\n    \"Ġimg\": 48599,\n    \"summary\": 48600,\n    \"]);\": 48601,\n    \"ĠABE\": 48602,\n    \"ĠGamergate\": 48603,\n    \"utherford\": 48604,\n    \"Ġoverwrite\": 48605,\n    \"enment\": 48606,\n    \"æķ\": 48607,\n    \"Ġsystemd\": 48608,\n    \"tif\": 48609,\n    \"]).\": 48610,\n    \"ãĤ¤\": 48611,\n    \"Widget\": 48612,\n    \"======\": 48613,\n    \"(-\": 48614,\n    \"Ġ\\\"+\": 48615,\n    \"ĠIncarnation\": 48616,\n    \"æĥ\": 48617,\n    \"ï¿½ï¿½ï¿½\": 48618,\n    \"GUI\": 48619,\n    \"èĥ\": 48620,\n    \"forums\": 48621,\n    \"Ġrunes\": 48622,\n    \"Ġâī¤\": 48623,\n    \"Ġdefic\": 48624,\n    \"Distance\": 48625,\n    \"directory\": 48626,\n    \"ĠHorus\": 48627,\n    \"iltr\": 48628,\n    \"ortium\": 48629,\n    \"Ġ./\": 48630,\n    \"bda\": 48631,\n    \"owship\": 48632,\n    \"ĠâĨĳ\": 48633,\n    \"}.\": 48634,\n    \"åĩ\": 48635,\n    \"1027\": 48636,\n    \"Weapons\": 48637,\n    \"lucent\": 48638,\n    \"Ġauth\": 48639,\n    \";;\": 48640,\n    \"Recommended\": 48641,\n    \"Ġsurv\": 48642,\n    \"Ġvm\": 48643,\n    \"ĠStronghold\": 48644,\n    \"Ġparan\": 48645,\n    \"ĠTrance\": 48646,\n    \"æĺ\": 48647,\n    \"Ġsovere\": 48648,\n    \"Ġcorrid\": 48649,\n    \"ĠPwr\": 48650,\n    \"Ġ[/\": 48651,\n    \"Ġseq\": 48652,\n    \"Population\": 48653,\n    \"Ġ[];\": 48654,\n    \"Ġreferen\": 48655,\n    \"ĠInstr\": 48656,\n    \"ĠStamina\": 48657,\n    \"kernel\": 48658,\n    \"Python\": 48659,\n    \"-+\": 48660,\n    \"Ġallele\": 48661,\n    \"éĽ\": 48662,\n    \"isode\": 48663,\n    \"ä¸į\": 48664,\n    \"otonin\": 48665,\n    \"modules\": 48666,\n    \"Notable\": 48667,\n    \"Spell\": 48668,\n    \"\\\\\\\\\": 48669,\n    \"Pref\": 48670,\n    \"Ġdatas\": 48671,\n    \"setup\": 48672,\n    \"Ġhapl\": 48673,\n    \"Height\": 48674,\n    \"åĭ\": 48675,\n    \"ãģ£\": 48676,\n    \"]),\": 48677,\n    \"Handle\": 48678,\n    \"umenthal\": 48679,\n    \"Package\": 48680,\n    \"Ġenthus\": 48681,\n    \"Ġunsus\": 48682,\n    \"Narr\": 48683,\n    \"Examples\": 48684,\n    \"FAQ\": 48685,\n    \"REDACTED\": 48686,\n    \"Ġnotor\": 48687,\n    \"Enable\": 48688,\n    \"Pattern\": 48689,\n    \"aeda\": 48690,\n    \">.\": 48691,\n    \"CHECK\": 48692,\n    \"Ġï¿½ï¿½ï¿½ï¿½\": 48693,\n    \"Ġ'.\": 48694,\n    \"Ġãĥ\": 48695,\n    \"append\": 48696,\n    \"ï¿½ï¿½ï¿½ï¿½\": 48697,\n    \"gemony\": 48698,\n    \"terness\": 48699,\n    \"ĠHaku\": 48700,\n    \"NVIDIA\": 48701,\n    \"queue\": 48702,\n    \"Bind\": 48703,\n    \"Ġneigh\": 48704,\n    \"armor\": 48705,\n    \"retty\": 48706,\n    \"LOD\": 48707,\n    \"plugins\": 48708,\n    \"Ġ/>\": 48709,\n    \"TYPE\": 48710,\n    \"Ġ4096\": 48711,\n    \"-------\": 48712,\n    \"Preview\": 48713,\n    \"FML\": 48714,\n    \"Ġproletarian\": 48715,\n    \"zees\": 48716,\n    \"enfranch\": 48717,\n    \"ãģĨ\": 48718,\n    \"Ctrl\": 48719,\n    \"Module\": 48720,\n    \"ĠSurviv\": 48721,\n    \"ĠStarcraft\": 48722,\n    \"rored\": 48723,\n    \"reddit\": 48724,\n    \"Ġrul\": 48725,\n    \"Ġtx\": 48726,\n    \"Ġmage\": 48727,\n    \"Sword\": 48728,\n    \"Ġ~/\": 48729,\n    \"Effects\": 48730,\n    \"éļ\": 48731,\n    \"ä¹\": 48732,\n    \"Sensor\": 48733,\n    \"Solution\": 48734,\n    \"ãģĻ\": 48735,\n    \"Arcade\": 48736,\n    \"Ġpredec\": 48737,\n    \"Values\": 48738,\n    \"Length\": 48739,\n    \"Ġfortun\": 48740,\n    \"ttp\": 48741,\n    \"\\\"[\": 48742,\n    \"tmp\": 48743,\n    \"ĠBerserker\": 48744,\n    \"åĨ\": 48745,\n    \"ositories\": 48746,\n    \"Ġcouncill\": 48747,\n    \"ffff\": 48748,\n    \"));\": 48749,\n    \"Recipe\": 48750,\n    \"ĠASCII\": 48751,\n    \"âĦ¢:\": 48752,\n    \"ä\": 48753,\n    \"Ġhorm\": 48754,\n    \"=>\": 48755,\n    \"sers\": 48756,\n    \"ãģĭ\": 48757,\n    \"Recommend\": 48758,\n    \"['\": 48759,\n    \"agame\": 48760,\n    \"Animation\": 48761,\n    \"aucuses\": 48762,\n    \"Discussion\": 48763,\n    \"Ġhelicop\": 48764,\n    \"å¿\": 48765,\n    \"Float\": 48766,\n    \"Component\": 48767,\n    \"instance\": 48768,\n    \"Ġfoo\": 48769,\n    \"localhost\": 48770,\n    \"=-\": 48771,\n    \"Offset\": 48772,\n    \"Psy\": 48773,\n    \"ĠGohan\": 48774,\n    \"buquerque\": 48775,\n    \"Ġdefe\": 48776,\n    \"chwitz\": 48777,\n    \"parse\": 48778,\n    \"Ġdors\": 48779,\n    \"Ġspons\": 48780,\n    \"Ġasync\": 48781,\n    \"agonists\": 48782,\n    \"Ġindo\": 48783,\n    \".>>\": 48784,\n    \"ĠDisciple\": 48785,\n    \"Ġfilename\": 48786,\n    \"rency\": 48787,\n    \"ĠDise\": 48788,\n    \"Ġ\\\"/\": 48789,\n    \"template\": 48790,\n    \"ãĤ¹\": 48791,\n    \"swers\": 48792,\n    \"Ġ++\": 48793,\n    \"Ġ[(\": 48794,\n    \"thora\": 48795,\n    \"ĠDepths\": 48796,\n    \"livious\": 48797,\n    \"Ġdisadvant\": 48798,\n    \"foundland\": 48799,\n    \"Upload\": 48800,\n    \"ĠÂ§Â§\": 48801,\n    \"Ġsophistic\": 48802,\n    \";}\": 48803,\n    \"izont\": 48804,\n    \"\\\"}\": 48805,\n    \"estial\": 48806,\n    \"Ranked\": 48807,\n    \"ĠOccupations\": 48808,\n    \"LEASE\": 48809,\n    \"ĠOgre\": 48810,\n    \"folder\": 48811,\n    \"Plot\": 48812,\n    \"farious\": 48813,\n    \"Ġsuscept\": 48814,\n    \"Types\": 48815,\n    \"Discuss\": 48816,\n    \"Ġ'/\": 48817,\n    \"æµ\": 48818,\n    \"earable\": 48819,\n    \"æ³\": 48820,\n    \"Tile\": 48821,\n    \"iatus\": 48822,\n    \"åŃ\": 48823,\n    \"Ġreperto\": 48824,\n    \"Helper\": 48825,\n    \"Returns\": 48826,\n    \"ä¸Ĭ\": 48827,\n    \"imaru\": 48828,\n    \"Ġreq\": 48829,\n    \"Ġdissatisf\": 48830,\n    \"multipl\": 48831,\n    \"}{\": 48832,\n    \"-[\": 48833,\n    \"itial\": 48834,\n    \"*/\": 48835,\n    \"Config\": 48836,\n    \"Example\": 48837,\n    \"ĠjQuery\": 48838,\n    \"Mods\": 48839,\n    \"ĠGPIO\": 48840,\n    \"Ġlaun\": 48841,\n    \"layout\": 48842,\n    \"cised\": 48843,\n    \"Ġ......\": 48844,\n    \"+++\": 48845,\n    \"prototype\": 48846,\n    \"Exception\": 48847,\n    \"Ġsubsections\": 48848,\n    \"Ġresemb\": 48849,\n    \"Ġâĩ\": 48850,\n    \"ĠPubMed\": 48851,\n    \"username\": 48852,\n    \"Ġaggro\": 48853,\n    \"éĥ\": 48854,\n    \"Ġ};\": 48855,\n    \"ĠMages\": 48856,\n    \"ryu\": 48857,\n    \"apons\": 48858,\n    \"Optional\": 48859,\n    \"ĠAncients\": 48860,\n    \"ãĤĬ\": 48861,\n    \"Quotes\": 48862,\n    \"oaded\": 48863,\n    \"Ġsuspic\": 48864,\n    \"inline\": 48865,\n    \"omial\": 48866,\n    \"ĠMahjong\": 48867,\n    \"auntlets\": 48868,\n    \"Ġanarchism\": 48869,\n    \"Ġsubclass\": 48870,\n    \"ĠMLG\": 48871,\n    \"...]\": 48872,\n    \"Dialog\": 48873,\n    \"uphem\": 48874,\n    \"Ġrecursive\": 48875,\n    \"7601\": 48876,\n    \"frac\": 48877,\n    \"Else\": 48878,\n    \"ĠSeverus\": 48879,\n    \"},{\\\"\": 48880,\n    \"ĠCLIENT\": 48881,\n    \"Ġjavascript\": 48882,\n    \"sama\": 48883,\n    \"ĠLearns\": 48884,\n    \"ãĤĤ\": 48885,\n    \"Upgrade\": 48886,\n    \"Listener\": 48887,\n    \"Ġsnipp\": 48888,\n    \"Ġrune\": 48889,\n    \"ĠTTL\": 48890,\n    \"ertation\": 48891,\n    \"olicy\": 48892,\n    \"=\\\"\\\"\": 48893,\n    \"«ĺ\": 48894,\n    \"Ġexpr\": 48895,\n    \"ovych\": 48896,\n    \"Ġãģ\": 48897,\n    \"_-_\": 48898,\n    \"munition\": 48899,\n    \"////\": 48900,\n    \"func\": 48901,\n    \">>>>\": 48902,\n    \"Provider\": 48903,\n    \"Ïī\": 48904,\n    \"BUG\": 48905,\n    \"Ġ[-\": 48906,\n    \"Ġarrang\": 48907,\n    \"merce\": 48908,\n    \"ãĥ\": 48909,\n    \"incarn\": 48910,\n    \"Valid\": 48911,\n    \"ĠAether\": 48912,\n    \"ãĤĵ\": 48913,\n    \"ĠUTF\": 48914,\n    \"ĠMonstrous\": 48915,\n    \"ãĤĮ\": 48916,\n    \"hedon\": 48917,\n    \"áµ\": 48918,\n    \":#\": 48919,\n    \"ĠFrieza\": 48920,\n    \"padding\": 48921,\n    \"Reviewer\": 48922,\n    \"Ġpsychiat\": 48923,\n    \"yrinth\": 48924,\n    \"ĠâĶĤ\": 48925,\n    \"hillary\": 48926,\n    \"Static\": 48927,\n    \"Newsletter\": 48928,\n    \"Avg\": 48929,\n    \"Ġfn\": 48930,\n    \"Topic\": 48931,\n    \"choes\": 48932,\n    \"Ġnewsp\": 48933,\n    \"á¸\": 48934,\n    \"Ġ[+\": 48935,\n    \"~~~~~~~~~~~~~~~~\": 48936,\n    \":]\": 48937,\n    \"apego\": 48938,\n    \"buf\": 48939,\n    \"Translation\": 48940,\n    \"ById\": 48941,\n    \"Ġmmol\": 48942,\n    \"ãĥ¼ãĥ\": 48943,\n    \"å½\": 48944,\n    \"ãĤī\": 48945,\n    \"Ġparser\": 48946,\n    \"ãĥª\": 48947,\n    \"`,\": 48948,\n    \"Lair\": 48949,\n    \")}\": 48950,\n    \"ypes\": 48951,\n    \"adobe\": 48952,\n    \"Ġancest\": 48953,\n    \"ernel\": 48954,\n    \"ĠNULL\": 48955,\n    \"ç«\": 48956,\n    \"anguages\": 48957,\n    \"Increases\": 48958,\n    \"æĦ\": 48959,\n    \"utorial\": 48960,\n    \"ithmetic\": 48961,\n    \"dll\": 48962,\n    \"ĠArcane\": 48963,\n    \"çī\": 48964,\n    \"Ġtc\": 48965,\n    \"urtles\": 48966,\n    \"èĪ\": 48967,\n    \"Bytes\": 48968,\n    \"Slot\": 48969,\n    \"ĠBahÃ¡\": 48970,\n    \"Weapon\": 48971,\n    \"widget\": 48972,\n    \"querque\": 48973,\n    \"Ġembodiments\": 48974,\n    \"å¥\": 48975,\n    \"WARN\": 48976,\n    \"swer\": 48977,\n    \"thumbnails\": 48978,\n    \"FFFF\": 48979,\n    \"inguishable\": 48980,\n    \"Ġâī\": 48981,\n    \"Ġ${\": 48982,\n    \"AAAAAAAA\": 48983,\n    \"Conclusion\": 48984,\n    \"ĻĤ\": 48985,\n    \"disable\": 48986,\n    \"Rect\": 48987,\n    \"Ġsubp\": 48988,\n    \"Ġ().\": 48989,\n    \"ĠDetected\": 48990,\n    \"èĢ\": 48991,\n    \"[]\": 48992,\n    \"Ġcoerc\": 48993,\n    \"ĠmM\": 48994,\n    \"recated\": 48995,\n    \"fusc\": 48996,\n    \"ĠSorce\": 48997,\n    \"çĶŁ\": 48998,\n    \").[\": 48999,\n    \"Ġ})\": 49000,\n    \"mobi\": 49001,\n    \"yip\": 49002,\n    \"Acknowled\": 49003,\n    \"ternity\": 49004,\n    \"iqueness\": 49005,\n    \"ython\": 49006,\n    \"><\": 49007,\n    \"Ġstd\": 49008,\n    \"Url\": 49009,\n    \"Ġnamespace\": 49010,\n    \"Ġtion\": 49011,\n    \"oother\": 49012,\n    \"Ó\": 49013,\n    \"Ġhemor\": 49014,\n    \"Ġrg\": 49015,\n    \"ventory\": 49016,\n    \"ãĤ¢\": 49017,\n    \"anamo\": 49018,\n    \"Socket\": 49019,\n    \"Topics\": 49020,\n    \"apeshifter\": 49021,\n    \"gnu\": 49022,\n    \"Ġdetrim\": 49023,\n    \"`.\": 49024,\n    \"romeda\": 49025,\n    \"çĲ\": 49026,\n    \"Ġlambda\": 49027,\n    \"Compan\": 49028,\n    \"Variable\": 49029,\n    \"Ġusb\": 49030,\n    \"ĠAdamant\": 49031,\n    \"ournal\": 49032,\n    \"Ġcovari\": 49033,\n    \"ãĥ©\": 49034,\n    \"éĸ\": 49035,\n    \"åİ\": 49036,\n    \"otaur\": 49037,\n    \"Ġ(),\": 49038,\n    \"Marginal\": 49039,\n    \"ãģı\": 49040,\n    \"Ġphysic\": 49041,\n    \"adeon\": 49042,\n    \"RESULTS\": 49043,\n    \"200000\": 49044,\n    \"ãģį\": 49045,\n    \"udeb\": 49046,\n    \"ãģĵ\": 49047,\n    \"COMPLE\": 49048,\n    \"Ġmsg\": 49049,\n    \"ghazi\": 49050,\n    \"/*\": 49051,\n    \"ĠDeity\": 49052,\n    \"Ġdisapp\": 49053,\n    \"Availability\": 49054,\n    \"Ġillum\": 49055,\n    \"à©\": 49056,\n    \"ptives\": 49057,\n    \",âĢĶ\": 49058,\n    \"chnology\": 49059,\n    \"Ġaccur\": 49060,\n    \"Ġapi\": 49061,\n    \"Obj\": 49062,\n    \"ãĤ«\": 49063,\n    \"ãĤ¸\": 49064,\n    \"ä¹ĭ\": 49065,\n    \"ËĪ\": 49066,\n    \"Ġtcp\": 49067,\n    \"Required\": 49068,\n    \".<\": 49069,\n    \"\\\".[\": 49070,\n    \"Ġ~/.\": 49071,\n    \"Ġobser\": 49072,\n    \"RFC\": 49073,\n    \"Ġintegers\": 49074,\n    \"åī\": 49075,\n    \"Installation\": 49076,\n    \"Ô\": 49077,\n    \"ó\": 49078,\n    \"csv\": 49079,\n    \"ãĥ«\": 49080,\n    \"ĠNoticed\": 49081,\n    \"âĸĵ\": 49082,\n    \"Tumblr\": 49083,\n    \"Reply\": 49084,\n    \"||\": 49085,\n    \"Ġconclud\": 49086,\n    \"Ġ))\": 49087,\n    \"ebin\": 49088,\n    \"sql\": 49089,\n    \"Closure\": 49090,\n    \"++++\": 49091,\n    \"],[\": 49092,\n    \"âĹı\": 49093,\n    \"Ġprolet\": 49094,\n    \"Ġ>=\": 49095,\n    \"estinal\": 49096,\n    \"Ġ[*\": 49097,\n    \"ĠInquisitor\": 49098,\n    \"Ġcmd\": 49099,\n    \"FINE\": 49100,\n    \"CRIP\": 49101,\n    \"Ġvertex\": 49102,\n    \"TeX\": 49103,\n    \"///\": 49104,\n    \"Ö¼\": 49105,\n    \"iscons\": 49106,\n    \"Ġmyster\": 49107,\n    \"Changed\": 49108,\n    \"timeout\": 49109,\n    \"irtual\": 49110,\n    \"Methods\": 49111,\n    \"Ġcerts\": 49112,\n    \"texture\": 49113,\n    \"Roaming\": 49114,\n    \"Proxy\": 49115,\n    \"Override\": 49116,\n    \"éĹ\": 49117,\n    \"utf\": 49118,\n    \"python\": 49119,\n    \"ĠRarity\": 49120,\n    \"ilitarian\": 49121,\n    \"çľ\": 49122,\n    \"().\": 49123,\n    \"æł\": 49124,\n    \"Ġbuf\": 49125,\n    \"åĳ\": 49126,\n    \"çķ\": 49127,\n    \"Ġ*.\": 49128,\n    \"umerable\": 49129,\n    \"~~~~\": 49130,\n    \"å¦\": 49131,\n    \"Ġsimultane\": 49132,\n    \"Ġjson\": 49133,\n    \"Requires\": 49134,\n    \"Ġperl\": 49135,\n    \"Interface\": 49136,\n    \"rupal\": 49137,\n    \"</\": 49138,\n    \"uilt\": 49139,\n    \"mercial\": 49140,\n    \"ĠPalestin\": 49141,\n    \"theless\": 49142,\n    \")=\": 49143,\n    \"Generic\": 49144,\n    \"&&\": 49145,\n    \"ALSE\": 49146,\n    \"Ġdebugger\": 49147,\n    \"paralle\": 49148,\n    \"acly\": 49149,\n    \"ĠScourge\": 49150,\n    \")].\": 49151,\n    \"Ġinstr\": 49152,\n    \"Ġ{}\": 49153,\n    \"]+\": 49154,\n    \"Ġdilig\": 49155,\n    \"åŃĲ\": 49156,\n    \"Ġcaptcha\": 49157,\n    \"kefeller\": 49158,\n    \"iosyncr\": 49159,\n    \"Ġchars\": 49160,\n    \"Ġinitialize\": 49161,\n    \"Width\": 49162,\n    \"Ġgithub\": 49163,\n    \"Ġinitialization\": 49164,\n    \"ĠGamerGate\": 49165,\n    \"ĠÃ¾\": 49166,\n    \"drm\": 49167,\n    \"slaught\": 49168,\n    \"Ġtiss\": 49169,\n    \".............\": 49170,\n    \"Ĥ¬\": 49171,\n    \"Ġplent\": 49172,\n    \"ãģķ\": 49173,\n    \"cfg\": 49174,\n    \"âĨ\": 49175,\n    \"Ġpokemon\": 49176,\n    \"\\\"],\": 49177,\n    \"Ġtyr\": 49178,\n    \"SELECT\": 49179,\n    \"othal\": 49180,\n    \"Tags\": 49181,\n    \"ĠMarketable\": 49182,\n    \"-----------\": 49183,\n    \"icter\": 49184,\n    \"irlf\": 49185,\n    \"ormons\": 49186,\n    \"Database\": 49187,\n    \"ĠãĤ\": 49188,\n    \"Ġ{\\\"\": 49189,\n    \"î\": 49190,\n    \"Handler\": 49191,\n    \"âĶĢ\": 49192,\n    \"$$$$\": 49193,\n    \"ĠJaune\": 49194,\n    \"ãĤ³\": 49195,\n    \"(),\": 49196,\n    \")+\": 49197,\n    \"--------\": 49198,\n    \"Ġshenan\": 49199,\n    \"Ġwelf\": 49200,\n    \"Ġ',\": 49201,\n    \"attribute\": 49202,\n    \"Uncommon\": 49203,\n    \"maxwell\": 49204,\n    \"Browser\": 49205,\n    \"ĠPastebin\": 49206,\n    \"uberty\": 49207,\n    \"debug\": 49208,\n    \"Ġmosqu\": 49209,\n    \"ĠBoolean\": 49210,\n    \"wcs\": 49211,\n    \"é£\": 49212,\n    \"/âĢĭ\": 49213,\n    \"çĦ\": 49214,\n    \"(){\": 49215,\n    \"////////////////////////////////\": 49216,\n    \"ĠGleaming\": 49217,\n    \"regor\": 49218,\n    \"ĠMercenary\": 49219,\n    \"ensional\": 49220,\n    \"mpeg\": 49221,\n    \"sudo\": 49222,\n    \"ãģ®å\": 49223,\n    \"iggurat\": 49224,\n    \"vironment\": 49225,\n    \"Directory\": 49226,\n    \"ĠDecoder\": 49227,\n    \"SPONSORED\": 49228,\n    \"intendo\": 49229,\n    \"Ġ<=\": 49230,\n    \"btn\": 49231,\n    \"ï¸\": 49232,\n    \"ä½ľ\": 49233,\n    \"paio\": 49234,\n    \"Tokens\": 49235,\n    \"ãĢį\": 49236,\n    \"params\": 49237,\n    \"Offline\": 49238,\n    \"Ġmetab\": 49239,\n    \"ĠLisp\": 49240,\n    \"anwhile\": 49241,\n    \">:\": 49242,\n    \"itialized\": 49243,\n    \"HTTP\": 49244,\n    \"Trivia\": 49245,\n    \"Sov\": 49246,\n    \"wrapper\": 49247,\n    \"={\": 49248,\n    \"ĠAzerb\": 49249,\n    \"aeper\": 49250,\n    \"Ġneighb\": 49251,\n    \"initions\": 49252,\n    \"Ġsts\": 49253,\n    \"ĠSasuke\": 49254,\n    \"#$\": 49255,\n    \"uliffe\": 49256,\n    \"æĸ¹\": 49257,\n    \"++++++++++++++++\": 49258,\n    \"ĠElven\": 49259,\n    \"ãģĤ\": 49260,\n    \"Ġartif\": 49261,\n    \"Folder\": 49262,\n    \"Ġà¨\": 49263,\n    \"åĤ\": 49264,\n    \"Ġphyl\": 49265,\n    \"uggest\": 49266,\n    \"blance\": 49267,\n    \"ãģł\": 49268,\n    \"Requirements\": 49269,\n    \"Usage\": 49270,\n    \"Ġinitialized\": 49271,\n    \"ãģ®æ\": 49272,\n    \"conservancy\": 49273,\n    \"ĠReincarn\": 49274,\n    \")|\": 49275,\n    \"Ġantioxid\": 49276,\n    \"ĠClicker\": 49277,\n    \"Ġunlaw\": 49278,\n    \"Ġ\\\\(\": 49279,\n    \"ãĥĪ\": 49280,\n    \"Ġ[*]\": 49281,\n    \"Characters\": 49282,\n    \"////////\": 49283,\n    \"ãĢĲ\": 49284,\n    \"ãĤ·\": 49285,\n    \"webkit\": 49286,\n    \"ãĢĳ\": 49287,\n    \"Ġxp\": 49288,\n    \"alkyrie\": 49289,\n    \"Console\": 49290,\n    \"());\": 49291,\n    \"ĠKorra\": 49292,\n    \"\\\"))\": 49293,\n    \"oooooooooooooooo\": 49294,\n    \"Timer\": 49295,\n    \"////////////////\": 49296,\n    \"yout\": 49297,\n    \"engeance\": 49298,\n    \"emetery\": 49299,\n    \"Ġmages\": 49300,\n    \"mods\": 49301,\n    \"Null\": 49302,\n    \"Ġphilos\": 49303,\n    \"ascript\": 49304,\n    \"Ġaddon\": 49305,\n    \"ĠâĸĪ\": 49306,\n    \"emale\": 49307,\n    \"----------------------------------------------------------------\": 49308,\n    \"Ġ\\\\\\\\\": 49309,\n    \"=[\": 49310,\n    \"ĠParables\": 49311,\n    \"ãĥĨ\": 49312,\n    \"VALUE\": 49313,\n    \"Ġ@@\": 49314,\n    \"Ġuint\": 49315,\n    \"${\": 49316,\n    \"cpp\": 49317,\n    \"%%\": 49318,\n    \"Ġ(âĪĴ\": 49319,\n    \"utils\": 49320,\n    \"prefix\": 49321,\n    \"å°Ĩ\": 49322,\n    \"ãĥŃ\": 49323,\n    \"Completed\": 49324,\n    \"Ġgoto\": 49325,\n    \"ãĤ¯\": 49326,\n    \"Winged\": 49327,\n    \"perty\": 49328,\n    \"[\\\"\": 49329,\n    \"ãĥİ\": 49330,\n    \"ĠScythe\": 49331,\n    \"Ġæľ\": 49332,\n    \"Ġ!=\": 49333,\n    \"Buffer\": 49334,\n    \"docker\": 49335,\n    \"ĠWATCHED\": 49336,\n    \"èĢħ\": 49337,\n    \"())\": 49338,\n    \"Ġdst\": 49339,\n    \"SIZE\": 49340,\n    \"ĠDemonic\": 49341,\n    \"Ġresil\": 49342,\n    \"ãĤ¿\": 49343,\n    \"Ġpione\": 49344,\n    \"cpu\": 49345,\n    \"++)\": 49346,\n    \"TEXT\": 49347,\n    \"Ġdiscrep\": 49348,\n    \"debian\": 49349,\n    \"quished\": 49350,\n    \"Ġacknow\": 49351,\n    \"Ġtrave\": 49352,\n    \"Ġgcc\": 49353,\n    \"Catalog\": 49354,\n    \"ctrl\": 49355,\n    \"ĠMoroc\": 49356,\n    \"Ġcpu\": 49357,\n    \"Ġ];\": 49358,\n    \"ĠSorceress\": 49359,\n    \"Introduced\": 49360,\n    \"Frames\": 49361,\n    \"Ġcondem\": 49362,\n    \"¶æ\": 49363,\n    \"~~~~~~~~\": 49364,\n    \"ĠEmacs\": 49365,\n    \"][/\": 49366,\n    \"Ġglim\": 49367,\n    \"Init\": 49368,\n    \"ĠPrimordial\": 49369,\n    \"ãĥĥ\": 49370,\n    \"Ġ+=\": 49371,\n    \"Ġblat\": 49372,\n    \"à¼\": 49373,\n    \"------------------------------------------------\": 49374,\n    \"gpu\": 49375,\n    \"ãĥĥãĥĪ\": 49376,\n    \"Ġxml\": 49377,\n    \"Ġboolean\": 49378,\n    \"References\": 49379,\n    \"Ġ?)\": 49380,\n    \"Ġsatell\": 49381,\n    \"Queue\": 49382,\n    \"Ġpestic\": 49383,\n    \"Ġ}}\": 49384,\n    \"Attribute\": 49385,\n    \"Ġdx\": 49386,\n    \"ĠDefin\": 49387,\n    \"Synopsis\": 49388,\n    \"..................\": 49389,\n    \"ãĥ¬\": 49390,\n    \"plugin\": 49391,\n    \"Disable\": 49392,\n    \"0000000000000000\": 49393,\n    \")\\\\\": 49394,\n    \"ĠIchigo\": 49395,\n    \"println\": 49396,\n    \"rontal\": 49397,\n    \"Setup\": 49398,\n    \"Ġï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½\": 49399,\n    \"å§\": 49400,\n    \"âĸº\": 49401,\n    \"ĠPengu\": 49402,\n    \"ailability\": 49403,\n    \"Duration\": 49404,\n    \"Timeout\": 49405,\n    \"ãĢĮ\": 49406,\n    \"Ġbehav\": 49407,\n    \"Reviewed\": 49408,\n    \"Ġtoget\": 49409,\n    \"\\\\.\": 49410,\n    \"lished\": 49411,\n    \"Ġthous\": 49412,\n    \"Ġperpend\": 49413,\n    \"ecause\": 49414,\n    \"Layout\": 49415,\n    \"è»\": 49416,\n    \"ĠDexterity\": 49417,\n    \"unsigned\": 49418,\n    \"+=\": 49419,\n    \"[[\": 49420,\n    \"ĠRunes\": 49421,\n    \"ãĤ¦\": 49422,\n    \"};\": 49423,\n    \"})\": 49424,\n    \"FTWARE\": 49425,\n    \"ength\": 49426,\n    \"milo\": 49427,\n    \"duino\": 49428,\n    \"å¤©\": 49429,\n    \"ĠClojure\": 49430,\n    \"ļé\": 49431,\n    \"ãĥ¥\": 49432,\n    \"gradient\": 49433,\n    \"Ġ\\\"\\\"\\\"\": 49434,\n    \"âĨĳ\": 49435,\n    \"@#\": 49436,\n    \"JSON\": 49437,\n    \"Ġproport\": 49438,\n    \"addr\": 49439,\n    \"});\": 49440,\n    \"ãĥĲ\": 49441,\n    \"ä¸ī\": 49442,\n    \"Ġtmp\": 49443,\n    \"å£\": 49444,\n    \"../\": 49445,\n    \"zsche\": 49446,\n    \"ĠâĪ¼\": 49447,\n    \"Entity\": 49448,\n    \"æ©Ł\": 49449,\n    \"ĠâĶľâĶĢâĶĢ\": 49450,\n    \"filename\": 49451,\n    \"{{\": 49452,\n    \"@@\": 49453,\n    \"ĠSeym\": 49454,\n    \"Ġ/**\": 49455,\n    \"ĠSummoner\": 49456,\n    \"Quantity\": 49457,\n    \"ç·\": 49458,\n    \"Attach\": 49459,\n    \"Ġbool\": 49460,\n    \"Texture\": 49461,\n    \"Ġopio\": 49462,\n    \".}\": 49463,\n    \"ãĥĭ\": 49464,\n    \"integer\": 49465,\n    \"Ġregex\": 49466,\n    \"Ġnomine\": 49467,\n    \"ription\": 49468,\n    \"ãģ®ç\": 49469,\n    \"ãĥķ\": 49470,\n    \"Ġsubparagraph\": 49471,\n    \"GGGG\": 49472,\n    \"Ġexplan\": 49473,\n    \"Header\": 49474,\n    \"Spawn\": 49475,\n    \"toggle\": 49476,\n    \"²¾\": 49477,\n    \"Abyss\": 49478,\n    \"expr\": 49479,\n    \"ĠZerg\": 49480,\n    \"ĠGrimoire\": 49481,\n    \"Contents\": 49482,\n    \"Instance\": 49483,\n    \"cyclopedia\": 49484,\n    \"ãĥĹ\": 49485,\n    \"ĠTakeru\": 49486,\n    \"=(\": 49487,\n    \"ä»£\": 49488,\n    \"\\\\)\": 49489,\n    \"Ġrgb\": 49490,\n    \"htt\": 49491,\n    \"bryce\": 49492,\n    \"Ġlivest\": 49493,\n    \"ĠAnnotations\": 49494,\n    \"âĶĢâĶĢâĶĢâĶĢâĶĢâĶĢâĶĢâĶĢ\": 49495,\n    \"berus\": 49496,\n    \"ntil\": 49497,\n    \"Ġskelet\": 49498,\n    \"callback\": 49499,\n    \"åħī\": 49500,\n    \"Joined\": 49501,\n    \"ãĤª\": 49502,\n    \"Ġargs\": 49503,\n    \"artifacts\": 49504,\n    \"Ġå¤\": 49505,\n    \"ÃĽ\": 49506,\n    \"ãĥŀ\": 49507,\n    \"Streamer\": 49508,\n    \"}\\\"\": 49509,\n    \"Ġunden\": 49510,\n    \"ãĥģ\": 49511,\n    \"Īè\": 49512,\n    \"ãĥ£\": 49513,\n    \"Ġ0004\": 49514,\n    \"Ġ\\\\'\": 49515,\n    \"ãĤ°\": 49516,\n    \"ĠCONFIG\": 49517,\n    \"Ġ#####\": 49518,\n    \"``\": 49519,\n    \"anguage\": 49520,\n    \"Ġ*)\": 49521,\n    \"Template\": 49522,\n    \"MODE\": 49523,\n    \"Ġ00000000\": 49524,\n    \"'';\": 49525,\n    \"></\": 49526,\n    \"å£«\": 49527,\n    \"essage\": 49528,\n    \"ntax\": 49529,\n    \"Cmd\": 49530,\n    \"ividual\": 49531,\n    \"Unix\": 49532,\n    \"è£\": 49533,\n    \"çĭ\": 49534,\n    \"ä½¿\": 49535,\n    \"():\": 49536,\n    \"ãĥī\": 49537,\n    \"gdala\": 49538,\n    \"etheless\": 49539,\n    \"ktop\": 49540,\n    \"ĠACPI\": 49541,\n    \"ãĥĸ\": 49542,\n    \"Ġsshd\": 49543,\n    \"Ġ000000\": 49544,\n    \"Ġchalleng\": 49545,\n    \"âĶĢâĶĢ\": 49546,\n    \"ĠFlavoring\": 49547,\n    \"çİĭ\": 49548,\n    \"Http\": 49549,\n    \"Ĭ±\": 49550,\n    \"Accessory\": 49551,\n    \"oldemort\": 49552,\n    \"ĠIzan\": 49553,\n    \"galitarian\": 49554,\n    \"ĠChocobo\": 49555,\n    \"edIn\": 49556,\n    \"++++++++\": 49557,\n    \"Ġprintf\": 49558,\n    \"çīĪ\": 49559,\n    \"izoph\": 49560,\n    \"ruciating\": 49561,\n    \"Ġenum\": 49562,\n    \",,,,\": 49563,\n    \"Ġpregn\": 49564,\n    \"sembly\": 49565,\n    \"Ġtherap\": 49566,\n    \"Ġingred\": 49567,\n    \"ãĤµ\": 49568,\n    \"Ġsql\": 49569,\n    \"(*\": 49570,\n    \"Appearance\": 49571,\n    \"ngth\": 49572,\n    \"invoke\": 49573,\n    \"ãĥĥãĤ¯\": 49574,\n    \"ctx\": 49575,\n    \"Ġdmg\": 49576,\n    \"Plugin\": 49577,\n    \"ãĥ¡\": 49578,\n    \"ulhu\": 49579,\n    \"ãĤ§\": 49580,\n    \"Ġwarr\": 49581,\n    \"Ġmetic\": 49582,\n    \"å¥³\": 49583,\n    \"Ġoun\": 49584,\n    \"ð\": 49585,\n    \"Ġtooltip\": 49586,\n    \"ãĤŃ\": 49587,\n    \"Ġvolunte\": 49588,\n    \"imgur\": 49589,\n    \"accompan\": 49590,\n    \"aterasu\": 49591,\n    \"olkien\": 49592,\n    \"ãĤº\": 49593,\n    \"Ġnodd\": 49594,\n    \"ĠMetatron\": 49595,\n    \"javascript\": 49596,\n    \"umbledore\": 49597,\n    \"ãĥł\": 49598,\n    \"--------------------------------------------------------\": 49599,\n    \"runtime\": 49600,\n    \"ĠLeban\": 49601,\n    \"Configuration\": 49602,\n    \"emort\": 49603,\n    \"(_\": 49604,\n    \"Connector\": 49605,\n    \"iosyn\": 49606,\n    \"reddits\": 49607,\n    \"Ġ\\\"%\": 49608,\n    \"Ġ[&\": 49609,\n    \"ĠSwordsman\": 49610,\n    \"ĠAwoken\": 49611,\n    \"Ġ;;\": 49612,\n    \"ãĥ¼ãĥ«\": 49613,\n    \"Ġ:=\": 49614,\n    \"ãĤ¹ãĥĪ\": 49615,\n    \"Ġcomr\": 49616,\n    \"Adapter\": 49617,\n    \"sbm\": 49618,\n    \"âķĲâķĲ\": 49619,\n    \"çļ\": 49620,\n    \"Loader\": 49621,\n    \"ãĥĵ\": 49622,\n    \"okemon\": 49623,\n    \"ãģ®é\": 49624,\n    \"-->\": 49625,\n    \"Ġlvl\": 49626,\n    \"Footnote\": 49627,\n    \"Iter\": 49628,\n    \"####\": 49629,\n    \"ãĥĳ\": 49630,\n    \"ĠCarbuncle\": 49631,\n    \"Ġ[+]\": 49632,\n    \"Ġmathemat\": 49633,\n    \"Allows\": 49634,\n    \"Ġ4090\": 49635,\n    \"Async\": 49636,\n    \"ģ«\": 49637,\n    \"Ļ½\": 49638,\n    \"))))\": 49639,\n    \"á½\": 49640,\n    \"Ġcx\": 49641,\n    \"Ġansw\": 49642,\n    \"{\\\"\": 49643,\n    \"ãĥŁ\": 49644,\n    \"addons\": 49645,\n    \"Filename\": 49646,\n    \"Appearances\": 49647,\n    \"ĠãĢĮ\": 49648,\n    \"Ġaddr\": 49649,\n    \"Ġcharact\": 49650,\n    \"glomer\": 49651,\n    \"Advertisements\": 49652,\n    \"Ġdracon\": 49653,\n    \"ĠFenrir\": 49654,\n    \"Ġ();\": 49655,\n    \"ĠCitiz\": 49656,\n    \"acebook\": 49657,\n    \"Ġparams\": 49658,\n    \"]=\": 49659,\n    \"Ġsubscript\": 49660,\n    \"Ġentreprene\": 49661,\n    \"tnc\": 49662,\n    \"iversal\": 49663,\n    \"Ġmillenn\": 49664,\n    \"ithub\": 49665,\n    \"/>\": 49666,\n    \"Ġ\\\"{\": 49667,\n    \"Frameworks\": 49668,\n    \"avorite\": 49669,\n    \"Ġ])\": 49670,\n    \"Constructed\": 49671,\n    \"fml\": 49672,\n    \"ãĥį\": 49673,\n    \"################################\": 49674,\n    \"-|\": 49675,\n    \"¥ŀ\": 49676,\n    \"Ġwithd\": 49677,\n    \"ĠCth\": 49678,\n    \"AppData\": 49679,\n    \"Msg\": 49680,\n    \":{\": 49681,\n    \"ãĤ¨\": 49682,\n    \"Ġtuple\": 49683,\n    \"ç¥ŀ\": 49684,\n    \"Ġintrins\": 49685,\n    \"ĠCooldown\": 49686,\n    \"ategory\": 49687,\n    \"^{\": 49688,\n    \"ãĥĬ\": 49689,\n    \"''''\": 49690,\n    \"çĶ°\": 49691,\n    \"ĠDEBUG\": 49692,\n    \"Ġcannabin\": 49693,\n    \"ocobo\": 49694,\n    \"Invalid\": 49695,\n    \"ãĥĢ\": 49696,\n    \"Compat\": 49697,\n    \"Ġ({\": 49698,\n    \"Removed\": 49699,\n    \"Ġconvol\": 49700,\n    \"}:\": 49701,\n    \"interstitial\": 49702,\n    \"Ġ</\": 49703,\n    \"Ġcontrace\": 49704,\n    \"uyomi\": 49705,\n    \"Callback\": 49706,\n    \"Parser\": 49707,\n    \"äºĶ\": 49708,\n    \"Versions\": 49709,\n    \"::::\": 49710,\n    \"Recomm\": 49711,\n    \"}\\\\\": 49712,\n    \"Ġ\\\"_\": 49713,\n    \"Debug\": 49714,\n    \"ĠAoE\": 49715,\n    \"atever\": 49716,\n    \"ĠTradable\": 49717,\n    \"Reloaded\": 49718,\n    \"ĠReincarnated\": 49719,\n    \"ĠStrongh\": 49720,\n    \">\\\"\": 49721,\n    \"initialized\": 49722,\n    \"Ġexting\": 49723,\n    \"PokÃ©\": 49724,\n    \"Parameters\": 49725,\n    \"¶ħ\": 49726,\n    \"########\": 49727,\n    \"NULL\": 49728,\n    \"ãĥĩ\": 49729,\n    \"groupon\": 49730,\n    \"\\\\-\": 49731,\n    \"ãĥı\": 49732,\n    \"ãĤ±\": 49733,\n    \"Ġsubsequ\": 49734,\n    \"ccording\": 49735,\n    \"ĠMODULE\": 49736,\n    \"ĠProtoss\": 49737,\n    \"\\\"},{\\\"\": 49738,\n    \"Ġ..............\": 49739,\n    \"Integer\": 49740,\n    \"endif\": 49741,\n    \"ãĥĻ\": 49742,\n    \"parser\": 49743,\n    \"lambda\": 49744,\n    \"Ġcarbohyd\": 49745,\n    \"ĠUnloaded\": 49746,\n    \"_{\": 49747,\n    \"âĸ¬âĸ¬\": 49748,\n    \"Ġdebian\": 49749,\n    \"]}\": 49750,\n    \"ãĤ¶\": 49751,\n    \"Parameter\": 49752,\n    \"ãĤ£\": 49753,\n    \"ãĤ»\": 49754,\n    \"Ġ$_\": 49755,\n    \"İĭ\": 49756,\n    \"Ġiterator\": 49757,\n    \"ãĤ¬\": 49758,\n    \"WINDOWS\": 49759,\n    \"CONCLUS\": 49760,\n    \"Ġ\\\"\\\\\": 49761,\n    \"umbn\": 49762,\n    \"(&\": 49763,\n    \"ãĥ©ãĥ³\": 49764,\n    \"usercontent\": 49765,\n    \"ometimes\": 49766,\n    \"METHOD\": 49767,\n    \"ãĥ¢\": 49768,\n    \"potion\": 49769,\n    \"ãĥ¯\": 49770,\n    \"everal\": 49771,\n    \"Ġweap\": 49772,\n    \"minecraft\": 49773,\n    \"================================\": 49774,\n    \"printf\": 49775,\n    \"ĠShinra\": 49776,\n    \"Ġreluct\": 49777,\n    \"\\\\\\\",\": 49778,\n    \"Runtime\": 49779,\n    \"xff\": 49780,\n    \"ĠAbyssal\": 49781,\n    \"akeru\": 49782,\n    \"Ġ\\\\(\\\\\": 49783,\n    \"\\\"/>\": 49784,\n    \"efficients\": 49785,\n    \"Ü\": 49786,\n    \"avascript\": 49787,\n    \"Ġbehavi\": 49788,\n    \"++;\": 49789,\n    \"=#\": 49790,\n    \"Attributes\": 49791,\n    \"âĵĺ\": 49792,\n    \"lvl\": 49793,\n    \"¬¼\": 49794,\n    \"/**\": 49795,\n    \"Gameplay\": 49796,\n    \"ĠLeilan\": 49797,\n    \">)\": 49798,\n    \"=\\\"/\": 49799,\n    \"Ġ));\": 49800,\n    \"ãĥĨãĤ£\": 49801,\n    \"ġ\": 49802,\n    \".</\": 49803,\n    \"Ġantidepress\": 49804,\n    \"Ġhtt\": 49805,\n    \"################\": 49806,\n    \"arnaev\": 49807,\n    \"ãĤ½\": 49808,\n    \"DERR\": 49809,\n    \"¥µ\": 49810,\n    \"âĸĪ\": 49811,\n    \"Ġ|--\": 49812,\n    \"Ġundermin\": 49813,\n    \"Ġ)))\": 49814,\n    \"ãĥĩãĤ£\": 49815,\n    \"awaru\": 49816,\n    \"\\\":[{\\\"\": 49817,\n    \"aution\": 49818,\n    \"ãĤ¤ãĥĪ\": 49819,\n    \"ô\": 49820,\n    \"ĠILCS\": 49821,\n    \"dfx\": 49822,\n    \"ĨĴ\": 49823,\n    \"âĸĴ\": 49824,\n    \"Ġcitiz\": 49825,\n    \"Ġ-=\": 49826,\n    \"ĠAllaah\": 49827,\n    \"Ġ(_\": 49828,\n    \"ĸļ\": 49829,\n    \"Ġ{\\\\\": 49830,\n    \"Ġsrf\": 49831,\n    \"ãĤ´\": 49832,\n    \"æŃ¦\": 49833,\n    \"»Ĵ\": 49834,\n    \"Ptr\": 49835,\n    \"'>\": 49836,\n    \"DEBUG\": 49837,\n    \"âĶģ\": 49838,\n    \"ãĢı\": 49839,\n    \"WithNo\": 49840,\n    \"Redditor\": 49841,\n    \"ĠâĶľ\": 49842,\n    \"Ġfmt\": 49843,\n    \"ãĢİ\": 49844,\n    \"Ġmsec\": 49845,\n    \"ĪĴ\": 49846,\n    \"eatures\": 49847,\n    \"itially\": 49848,\n    \"\\\"\\\"\\\"\": 49849,\n    \"ãĥ¼ãĤ¯\": 49850,\n    \"Textures\": 49851,\n    \"\\\"},\": 49852,\n    \"\\\"></\": 49853,\n    \"Ġenthusi\": 49854,\n    \"CHAPTER\": 49855,\n    \"Ġunbeliev\": 49856,\n    \"Ġearthqu\": 49857,\n    \"Ġ><\": 49858,\n    \"||||\": 49859,\n    \"ß\": 49860,\n    \"iterator\": 49861,\n    \"è£ħ\": 49862,\n    \"Ĥª\": 49863,\n    \"ojure\": 49864,\n    \"ãħĭãħĭ\": 49865,\n    \"ãĥ¼ãĥ³\": 49866,\n    \"Ġprintln\": 49867,\n    \"Ġ][\": 49868,\n    \"âĸĪâĸĪ\": 49869,\n    \"âķĲ\": 49870,\n    \"\\\\\\\":\": 49871,\n    \"senal\": 49872,\n    \"é¾į\": 49873,\n    \"é¾\": 49874,\n    \"Ġcryst\": 49875,\n    \"ãĥķãĤ¡\": 49876,\n    \"ĠCosponsors\": 49877,\n    \"ãĤ·ãĥ£\": 49878,\n    \"Magikarp\": 49879,\n    \"ĠMagicka\": 49880,\n    \"âĸĪâĸĪâĸĪâĸĪ\": 49881,\n    \",,,,,,,,\": 49882,\n    \"vertisement\": 49883,\n    \"âĶĢâĶĢâĶĢâĶĢ\": 49884,\n    \"ãĥķãĤ©\": 49885,\n    \"luaj\": 49886,\n    \"CLASSIFIED\": 49887,\n    \".''.\": 49888,\n    \"byss\": 49889,\n    \"Ġ{:\": 49890,\n    \"ĠNanto\": 49891,\n    \"Ġptr\": 49892,\n    \"Ġ%%\": 49893,\n    \"Ġteasp\": 49894,\n    \"[_\": 49895,\n    \"ãĥ¤\": 49896,\n    \"ħĭ\": 49897,\n    \"ŃĶ\": 49898,\n    \"Ġpci\": 49899,\n    \"Ġ\\\"<\": 49900,\n    \"GGGGGGGG\": 49901,\n    \"æĪ¦\": 49902,\n    \"--+\": 49903,\n    \"ãĤ®\": 49904,\n    \"Ġ())\": 49905,\n    \"âĸ¬\": 49906,\n    \"Ġsizeof\": 49907,\n    \"}}}\": 49908,\n    \";;;;;;;;\": 49909,\n    \">]\": 49910,\n    \"âĸĪâĸĪâĸĪâĸĪâĸĪâĸĪâĸĪâĸĪ\": 49911,\n    \"Vaults\": 49912,\n    \"Ġistg\": 49913,\n    \"Ġnewcom\": 49914,\n    \"=]\": 49915,\n    \"¿½\": 49916,\n    \"ĵĺ\": 49917,\n    \"{\\\\\": 49918,\n    \"Args\": 49919,\n    \"Ġexha\": 49920,\n    \"(\\\\\": 49921,\n    \"Ġunnecess\": 49922,\n    \"\\\"}],\\\"\": 49923,\n    \"ĠUNCLASSIFIED\": 49924,\n    \">(\": 49925,\n    \"ãĤ¢ãĥ«\": 49926,\n    \"æ©\": 49927,\n    \"70710\": 49928,\n    \"Ń·\": 49929,\n    \"ãĥ¼ãĥĨãĤ£\": 49930,\n    \"ĠSakuya\": 49931,\n    \"ãĥĥãĥī\": 49932,\n    \"ĠPyrrha\": 49933,\n    \"escription\": 49934,\n    \"VIDIA\": 49935,\n    \"================================================================\": 49936,\n    \"Ġlooph\": 49937,\n    \"=~\": 49938,\n    \"Ġcumbers\": 49939,\n    \"Ġ)]\": 49940,\n    \"govtrack\": 49941,\n    \"ĠãĤµ\": 49942,\n    \"Ġsubur\": 49943,\n    \"Þ\": 49944,\n    \"Ġâī¡\": 49945,\n    \"Interstitial\": 49946,\n    \"ãĥ¼ãĥĨ\": 49947,\n    \"Ġgobl\": 49948,\n    \"ãĥīãĥ©\": 49949,\n    \"oldown\": 49950,\n    \"ģĸ\": 49951,\n    \"Depths\": 49952,\n    \"Ġ());\": 49953,\n    \"Ġ._\": 49954,\n    \"20439\": 49955,\n    \"Ġç¥ŀ\": 49956,\n    \"ãģ®å®\": 49957,\n    \"ãĤ¼\": 49958,\n    \"Ġ$\\\\\": 49959,\n    \"âĹ¼\": 49960,\n    \"Ġencount\": 49961,\n    \"Ġ<!--\": 49962,\n    \"Ġeleph\": 49963,\n    \"\\\\\\\\\\\\\\\\\": 49964,\n    \"Ġmisunder\": 49965,\n    \"ahime\": 49966,\n    \"Ġattm\": 49967,\n    \"ĠCrossref\": 49968,\n    \"@@@@\": 49969,\n    \"ãħĭ\": 49970,\n    \"£ı\": 49971,\n    \"````\": 49972,\n    \"dylib\": 49973,\n    \"Ĥİ\": 49974,\n    \"Ġoccas\": 49975,\n    \"ãĥ´\": 49976,\n    \"ãĥĺ\": 49977,\n    \"ãĥ³ãĤ¸\": 49978,\n    \"Ġ+#\": 49979,\n    \"FINEST\": 49980,\n    \"Iterator\": 49981,\n    \"_>\": 49982,\n    \"hovah\": 49983,\n    \"éŃĶ\": 49984,\n    \"ãĤ¦ãĤ¹\": 49985,\n    \"aditional\": 49986,\n    \"@@@@@@@@\": 49987,\n    \"?ãĢį\": 49988,\n    \"âĸĢ\": 49989,\n    \"natureconservancy\": 49990,\n    \"=\\\"#\": 49991,\n    \"ĠCrossRef\": 49992,\n    \"ãĤ¡\": 49993,\n    \"ĠArchdemon\": 49994,\n    \"\\\"><\": 49995,\n    \"ãĥ¯ãĥ³\": 49996,\n    \"Ġendif\": 49997,\n    \"Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯\": 49998,\n    \"Ġtradem\": 49999,\n    \"\\\":-\": 50000,\n    \"ĠCLSID\": 50001,\n    \"ãĤ©\": 50002,\n    \"=\\\\\\\"\": 50003,\n    \"\\\\/\\\\/\": 50004,\n    \"Ġunintention\": 50005,\n    \"PDATE\": 50006,\n    \"Ġ``(\": 50007,\n    \"shapeshifter\": 50008,\n    \"Ġpractition\": 50009,\n    \"ikuman\": 50010,\n    \"Ý\": 50011,\n    \";;;;\": 50012,\n    \"ĠKinnikuman\": 50013,\n    \"Ġ(?,\": 50014,\n    \"@#&\": 50015,\n    \")=(\": 50016,\n    \")</\": 50017,\n    \"Ġ//[\": 50018,\n    \"=-=-\": 50019,\n    \"\\\":\\\"\\\"},{\\\"\": 50020,\n    \"é»Ĵ\": 50021,\n    \"\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\": 50022,\n    \"steamapps\": 50023,\n    \"=-=-=-=-=-=-=-=-\": 50024,\n    \">[\": 50025,\n    \"Initialized\": 50026,\n    \"ãĥīãĥ©ãĤ´ãĥ³\": 50027,\n    \"=-=-=-=-\": 50028,\n    \"ĠTsukuyomi\": 50029,\n    \"ertodd\": 50030,\n    \"Ġ+---\": 50031,\n    \"é¾įå\": 50032,\n    \"ãĥ´ãĤ¡\": 50033,\n    \"ortunately\": 50034,\n    \"TextColor\": 50035,\n    \"66666666\": 50036,\n    \"%%%%\": 50037,\n    \"ãĤ¨ãĥ«\": 50038,\n    \"taboola\": 50039,\n    \"ĠSkydragon\": 50040,\n    \"userc\": 50041,\n    \"Cooldown\": 50042,\n    \"Ġsidx\": 50043,\n    \"éĹĺ\": 50044,\n    \"FontSize\": 50045,\n    \"©¶æ\": 50046,\n    \"å§«\": 50047,\n    \"ÃĥÃĤ\": 50048,\n    \"âĸĦ\": 50049,\n    \"00200000\": 50050,\n    \"Â¯Â¯\": 50051,\n    \"âĸĳâĸĳ\": 50052,\n    \"\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\": 50053,\n    \"STDOUT\": 50054,\n    \"Buyable\": 50055,\n    \"Ġâĵĺ\": 50056,\n    \"SourceFile\": 50057,\n    \"Â¯Â¯Â¯Â¯Â¯Â¯Â¯Â¯\": 50058,\n    \"ãģ®éŃĶ\": 50059,\n    \"ãĤ´ãĥ³\": 50060,\n    \"?????-\": 50061,\n    \"pmwiki\": 50062,\n    \"Â¯Â¯Â¯Â¯\": 50063,\n    \"TEXTURE\": 50064,\n    \"#$#$\": 50065,\n    \"ÃįÃį\": 50066,\n    \"EMOTE\": 50067,\n    \"\\\\<\": 50068,\n    \"dayName\": 50069,\n    \"Nitrome\": 50070,\n    \"ĠPsyNet\": 50071,\n    \";;;;;;;;;;;;\": 50072,\n    \"Ġè£ı\": 50073,\n    \"ĠisEnabled\": 50074,\n    \"76561\": 50075,\n    \"iHUD\": 50076,\n    \"ãĥĺãĥ©\": 50077,\n    \"*/(\": 50078,\n    \"Ġè£ıç\": 50079,\n    \"ÃĥÃĤÃĥÃĤ\": 50080,\n    \"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\": 50081,\n    \"ThumbnailImage\": 50082,\n    \"©¶æ¥µ\": 50083,\n    \"Ġ[|\": 50084,\n    \"displayText\": 50085,\n    \"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\": 50086,\n    \"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\": 50087,\n    \".ãĢį\": 50088,\n    \"ModLoader\": 50089,\n    \"oreAnd\": 50090,\n    \"ĠSmartstocks\": 50091,\n    \"cffff\": 50092,\n    \"À\": 50093,\n    \"Á\": 50094,\n    \"ñ\": 50095,\n    \"ò\": 50096,\n    \"õ\": 50097,\n    \"ö\": 50098,\n    \"÷\": 50099,\n    \"ø\": 50100,\n    \"ù\": 50101,\n    \"ú\": 50102,\n    \"û\": 50103,\n    \"ü\": 50104,\n    \"ý\": 50105,\n    \"þ\": 50106,\n    \"ÿ\": 50107,\n    \"Ā\": 50108,\n    \"ā\": 50109,\n    \"Ă\": 50110,\n    \"ă\": 50111,\n    \"Ą\": 50112,\n    \"ą\": 50113,\n    \"Ć\": 50114,\n    \"ć\": 50115,\n    \"Ĉ\": 50116,\n    \"ĉ\": 50117,\n    \"Ċ\": 50118,\n    \"ċ\": 50119,\n    \"Č\": 50120,\n    \"č\": 50121,\n    \"Ď\": 50122,\n    \"ď\": 50123,\n    \"Đ\": 50124,\n    \"đ\": 50125,\n    \"Ē\": 50126,\n    \"ē\": 50127,\n    \"Ĕ\": 50128,\n    \"ĕ\": 50129,\n    \"Ė\": 50130,\n    \"ė\": 50131,\n    \"Ę\": 50132,\n    \"ę\": 50133,\n    \"Ě\": 50134,\n    \"ě\": 50135,\n    \"Ĝ\": 50136,\n    \"ĝ\": 50137,\n    \"Ğ\": 50138,\n    \"ğ\": 50139,\n    \"ĊĊ\": 50140,\n    \"Âł\": 50141,\n    \"ÂłÂł\": 50142,\n    \"ĠÂł\": 50143,\n    \"ÂłÂłÂłÂł\": 50144,\n    \"ĠÂłĠÂł\": 50145,\n    \"wcsstore\": 50146,\n    \"ÂłÂłÂłÂłÂłÂłÂłÂł\": 50147,\n    \"ĠDragonbound\": 50148,\n    \"ĠguiActive\": 50149,\n    \"ĠÂłĠÂłĠÂłĠÂł\": 50150,\n    \"ļéĨĴ\": 50151,\n    \"Ġdavidjl\": 50152,\n    \"è¦ļéĨĴ\": 50153,\n    \"\\\"]=>\": 50154,\n    \"Ġ<-\": 50155,\n    \"ForgeModLoader\": 50156,\n    \"NetMessage\": 50157,\n    \"ItemImage\": 50158,\n    \"Ġè£ıè¦ļéĨĴ\": 50159,\n    \"PsyNetMessage\": 50160,\n    \"Ġ<[\": 50161,\n    \"ĠguiActiveUn\": 50162,\n    \"ĠguiName\": 50163,\n    \"ĠexternalTo\": 50164,\n    \"ĠunfocusedRange\": 50165,\n    \"ĠguiActiveUnfocused\": 50166,\n    \"ĠguiIcon\": 50167,\n    \"ĠexternalToEVA\": 50168,\n    \"ĠexternalToEVAOnly\": 50169,\n    \"reportprint\": 50170,\n    \"embedreportprint\": 50171,\n    \"cloneembedreportprint\": 50172,\n    \"rawdownload\": 50173,\n    \"rawdownloadcloneembedreportprint\": 50174,\n    \"SpaceEngineers\": 50175,\n    \"actionDate\": 50176,\n    \"ActionCode\": 50177,\n    \"externalActionCode\": 50178,\n    \"?????-?????-\": 50179,\n    \"MpServer\": 50180,\n    \"ĠBaseType\": 50181,\n    \"Ġgmaxwell\": 50182,\n    \"cffffcc\": 50183,\n    \"Ġ\\\"$:/\": 50184,\n    \"Ġ<@\": 50185,\n    \"ĸļå£«\": 50186,\n    \"é¾įåĸļå£«\": 50187,\n    \"ÂłÂłÂł\": 50188,\n    \"=~=~\": 50189,\n    \"ĠactionGroup\": 50190,\n    \"ĠItemLevel\": 50191,\n    \"Ġè£ıè\": 50192,\n    \">>\\\\\": 50193,\n    \"ĠattRot\": 50194,\n    \"ÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤÃĥÃĤ\": 50195,\n    \"ĠMechdragon\": 50196,\n    \"ĠRandomRedditor\": 50197,\n    \"ĠRandomRedditorWithNo\": 50198,\n    \"Ġdstg\": 50199,\n    \"Ġsqor\": 50200,\n    \"Ġpetertodd\": 50201,\n    \"StreamerBot\": 50202,\n    \"TPPStreamerBot\": 50203,\n    \"FactoryReloaded\": 50204,\n    \"ĠpartName\": 50205,\n    \"\\\\\\\">\": 50206,\n    \"catentry\": 50207,\n    \"ÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂłÂł\": 50208,\n    \"ItemThumbnailImage\": 50209,\n    \"ĠUCHIJ\": 50210,\n    \"ĳå£«\": 50211,\n    \"ĠSetFontSize\": 50212,\n    \"Orderable\": 50213,\n    \"isSpecial\": 50214,\n    \"DeliveryDate\": 50215,\n    \"quickShip\": 50216,\n    \"quickShipAvailable\": 50217,\n    \"isSpecialOrderable\": 50218,\n    \"inventoryQuantity\": 50219,\n    \"channelAvailability\": 50220,\n    \"soType\": 50221,\n    \"soDeliveryDate\": 50222,\n    \"é¾įå¥\": 50223,\n    \"é¾įå¥ĳå£«\": 50224,\n    \"EStream\": 50225,\n    \"oreAndOnline\": 50226,\n    \"InstoreAndOnline\": 50227,\n    \"BuyableInstoreAndOnline\": 50228,\n    \"ĠTAMADRA\": 50229,\n    \"assetsadobe\": 50230,\n    \"Downloadha\": 50231,\n    \"ĠTheNitrome\": 50232,\n    \"ĠTheNitromeFan\": 50233,\n    \"GoldMagikarp\": 50234,\n    \"DragonMagazine\": 50235,\n    \"Ġ<+\": 50236,\n    \"ĠsrfN\": 50237,\n    \"ĠlargeDownload\": 50238,\n    \"ĠOkawaru\": 50239,\n    \"ĠsrfAttach\": 50240,\n    \"EStreamFrame\": 50241,\n    \"ãĤ¼ãĤ¦ãĤ¹\": 50242,\n    \"ĠSolidGoldMagikarp\": 50243,\n    \"ĊÂł\": 50244,\n    \"ĠSetTextColor\": 50245,\n    \"Ġfixme\": 50246,\n    \"ĠãĤµãĥ¼ãĥĨãĤ£\": 50247,\n    \"ĠãĤµãĥ¼ãĥĨãĤ£ãĥ¯ãĥ³\": 50248,\n    \"ĠÂłĠÂłĠÂłĠÂłĠÂłĠÂłĠÂłĠÂł\": 50249,\n    \"ĠAdinida\": 50250,\n    \"ItemTracker\": 50251,\n    \"ĠDevOnline\": 50252,\n    \"ĠÂłÂł\": 50253,\n    \"<?\": 50254,\n    \"*=-\": 50255,\n    \"ÃĽÃĽ\": 50256,\n    \"ĠEntityItem\": 50257,\n    \"EngineDebug\": 50258,\n    \"ĠstrutConnector\": 50259,\n    \"<|endoftext|>\": 50260,\n    \"madeupword0000\": 50261,\n    \"madeupword0001\": 50262,\n    \"madeupword0002\": 50263,\n    \"<mask>\": 50264\n}"
  },
  {
    "path": "eval/grounded_sam/grounded_sam2_florence2_autolabel_pipeline.py",
    "content": "import os\nimport cv2\nimport torch\nimport argparse\nimport numpy as np\nimport supervision as sv\nfrom PIL import Image\nimport gc\nimport sys\n\nfrom eval.grounded_sam.florence2.modeling_florence2 import Florence2ForConditionalGeneration\nfrom eval.grounded_sam.florence2.processing_florence2 import Florence2Processor\nfrom eval.grounded_sam.sam2.build_sam import build_sam2\nfrom eval.grounded_sam.sam2.sam2_image_predictor import SAM2ImagePredictor\n\n\nclass FlorenceSAM:\n\n    # official usage: https://huggingface.co/microsoft/Florence-2-large/blob/main/sample_inference.ipynb\n    TASK_PROMPT = {\n        \"original\": \"<GIVEN>\",\n        \"caption\": \"<CAPTION>\",\n        \"detailed_caption\": \"<DETAILED_CAPTION>\",\n        \"more_detailed_caption\": \"<MORE_DETAILED_CAPTION>\",\n        \"object_detection\": \"<OD>\",\n        \"dense_region_caption\": \"<DENSE_REGION_CAPTION>\",\n        \"region_proposal\": \"<REGION_PROPOSAL>\",\n        \"phrase_grounding\": \"<CAPTION_TO_PHRASE_GROUNDING>\",\n        \"referring_expression_segmentation\": \"<REFERRING_EXPRESSION_SEGMENTATION>\",\n        \"region_to_segmentation\": \"<REGION_TO_SEGMENTATION>\",\n        \"open_vocabulary_detection\": \"<OPEN_VOCABULARY_DETECTION>\",\n        \"region_to_category\": \"<REGION_TO_CATEGORY>\",\n        \"region_to_description\": \"<REGION_TO_DESCRIPTION>\",\n        \"ocr\": \"<OCR>\",\n        \"ocr_with_region\": \"<OCR_WITH_REGION>\",\n    }\n\n\n    def __init__(self, device):\n        \"\"\"\n        Init Florence-2 and SAM 2 Model\n        \"\"\"\n        print(f\"[{self}] init on device {device}\")\n        self.device = torch.device(device)\n\n        # with torch.autocast(device_type=\"cuda\", dtype=torch.float32).__enter__()\n        # self.torch_dtype = torch.float32\n        # self.torch_dtype = torch.float16\n        self.torch_dtype = torch.bfloat16\n\n        try:\n            if torch.cuda.get_device_properties(0).major >= 8:\n                # turn on tfloat32 for Ampere GPUs (https://pytorch.org/docs/stable/notes/cuda.html#tensorfloat-32-tf32-on-ampere-devices)\n                torch.backends.cuda.matmul.allow_tf32 = True\n                torch.backends.cudnn.allow_tf32 = True\n                # self.torch_dtype = torch.bfloat16\n            # else:\n                # self.torch_dtype = torch.float16\n        except:\n            self.torch_dtype = torch.bfloat16\n            \n        FLORENCE2_MODEL_ID = os.getenv('FLORENCE2_MODEL_PATH', \"microsoft/Florence-2-large\")\n        SAM2_CHECKPOINT = os.getenv('SAM2_MODEL_PATH')\n        SAM2_CONFIG = \"configs/sam2.1/sam2.1_hiera_l.yaml\"\n\n        self.florence2_model = Florence2ForConditionalGeneration.from_pretrained(\n            FLORENCE2_MODEL_ID, \n            torch_dtype=self.torch_dtype,\n        ).eval().to(self.device)\n        self.florence2_processor = Florence2Processor.from_pretrained(\n            FLORENCE2_MODEL_ID, \n        )\n        self.sam2_model = build_sam2(SAM2_CONFIG, SAM2_CHECKPOINT, device=self.device)\n        self.sam2_predictor = SAM2ImagePredictor(self.sam2_model)\n\n    def __str__(self):\n        return \"FlorenceSAM\"\n\n\n    @torch.no_grad()\n    def run_florence2(self, task_prompt, text_input, image):\n        model = self.florence2_model\n        processor = self.florence2_processor\n        device = self.device\n        assert model is not None, \"You should pass the init florence-2 model here\"\n        assert processor is not None, \"You should set florence-2 processor here\"\n\n        with torch.autocast(device_type=\"cuda\", dtype=torch.float32):\n            if text_input is None:\n                prompt = task_prompt\n            else:\n                prompt = task_prompt + text_input\n            \n            inputs = processor(\n                text=prompt, images=image, \n                max_length=1024,\n                truncation=True,\n                return_tensors=\"pt\",\n            ).to(device, self.torch_dtype)\n            # inputs = processor(text=prompt, images=image, return_tensors=\"pt\").to(device, self.torch_dtype)\n            generated_ids = model.generate(\n                input_ids=inputs[\"input_ids\"].to(device),\n                pixel_values=inputs[\"pixel_values\"].to(device),\n                # max_new_tokens=1024,\n                max_new_tokens=768,\n                early_stopping=False,\n                do_sample=False,\n                num_beams=3,\n            )\n            generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0]\n            parsed_answer = processor.post_process_generation(\n                generated_text, \n                task=task_prompt, \n                image_size=(image.width, image.height)\n            )\n            return parsed_answer\n\n\n\n    def caption(self, image, caption_task_prompt='<CAPTION>'):\n        assert caption_task_prompt in [\"<CAPTION>\", \"<DETAILED_CAPTION>\", \"<MORE_DETAILED_CAPTION>\"]\n        caption_results = self.run_florence2(caption_task_prompt, None, image)\n        text_input = caption_results[caption_task_prompt]\n        caption = text_input\n        return caption\n\n\n    def segmentation(self, image, input_boxes, seg_model=\"sam\"):\n        if seg_model == \"sam\":\n            with torch.inference_mode(), torch.autocast(\"cuda\", dtype=torch.float32):\n                sam2_predictor = self.sam2_predictor\n                sam2_predictor.set_image(np.array(image))\n                masks, scores, logits = sam2_predictor.predict(\n                    point_coords=None,\n                    point_labels=None,\n                    box=input_boxes,\n                    multimask_output=False,\n                )\n                if masks.ndim == 4:\n                    masks = masks.squeeze(1)\n                if scores.ndim == 2:\n                    scores = scores.squeeze(1)\n        else:\n            raise NotImplementedError()\n\n        return masks, scores\n\n    def post_process_results(self, image, caption, labels, detections, output_dir=None):\n        result_dict = {\n            \"caption\": caption,\n            \"instance_images\": [],\n            \"instance_labels\": [],\n            \"instance_bboxes\": [],\n            \"instance_mask_scores\": [],\n        }\n        \n        if detections is None:\n            return detections, result_dict\n\n        if output_dir is not None:\n            os.makedirs(output_dir, exist_ok=True)\n        \n        cv_image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)\n\n        box_annotator = sv.BoxAnnotator()\n        annotated_frame = box_annotator.annotate(scene=cv_image.copy(), detections=detections)\n        \n        label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)\n        annotated_frame = label_annotator.annotate(scene=annotated_frame, detections=detections, labels=labels)\n        if output_dir is not None: \n            cv2.imwrite(os.path.join(output_dir, \"detections.jpg\"), annotated_frame)\n        \n        mask_annotator = sv.MaskAnnotator()\n        annotated_frame = mask_annotator.annotate(scene=annotated_frame, detections=detections)\n        if output_dir is not None: \n            cv2.imwrite(os.path.join(output_dir, \"masks.jpg\"), annotated_frame)\n\n        for detection in detections:\n            xyxy, mask, confidence, class_id, tracker_id, data = detection\n\n            label = labels[class_id]\n            cropped_img = sv.crop_image(image=cv_image, xyxy=xyxy)\n            if output_dir is not None: \n                cv2.imwrite(os.path.join(output_dir, f\"cropped_image_{label}.jpg\"), cropped_img)\n\n            if mask is None:\n                result_dict[\"instance_mask_scores\"].append(0)\n                result_dict[\"instance_images\"].append(cropped_img)\n            else:\n                mask = np.repeat(mask[..., np.newaxis], 3, axis=-1)\n                masked_img = np.where(mask, cv_image, 255)\n                cropped_masked_img = sv.crop_image(image=masked_img, xyxy=xyxy)\n                result_dict[\"instance_mask_scores\"].append(confidence.item())\n                result_dict[\"instance_images\"].append(cropped_masked_img)\n                \n            result_dict[\"instance_labels\"].append(label)\n            result_dict[\"instance_bboxes\"].append(xyxy)\n            if output_dir is not None: \n                cv2.imwrite(os.path.join(output_dir, f\"masked_image_{label}.jpg\"), cropped_masked_img)\n\n        torch.cuda.empty_cache()\n        gc.collect()  \n        return detections, result_dict\n\n    def caption_phrase_grounding_and_segmentation(\n        self,\n        image,\n        seg_model=\"sam\",\n        caption_task_prompt='<CAPTION>',\n        original_caption=None,\n        output_dir=None\n    ):\n        \n        assert caption_task_prompt in [\"<CAPTION>\", \"<DETAILED_CAPTION>\", \"<MORE_DETAILED_CAPTION>\", \"<GIVEN>\", \"<OPEN_VOCABULARY_DETECTION>\"]\n        assert seg_model in [\"sam\", \"florence2\"]\n        \n        # image caption\n        if caption_task_prompt in [\"<GIVEN>\", \"<OPEN_VOCABULARY_DETECTION>\"]:\n            assert original_caption is not None\n            caption = original_caption\n        else:\n            caption_results = self.run_florence2(caption_task_prompt, None, image)\n            text_input = caption_results[caption_task_prompt]\n            caption = text_input\n        \n        # phrase grounding\n        grounding_results = self.run_florence2('<CAPTION_TO_PHRASE_GROUNDING>', caption, image)['<CAPTION_TO_PHRASE_GROUNDING>']\n        input_boxes = np.array(grounding_results[\"bboxes\"])\n        class_names = grounding_results[\"labels\"]\n        class_ids = np.array(list(range(len(class_names))))\n        \n        # segmentation\n        masks, scores = self.segmentation(image, input_boxes, seg_model)\n        \n        labels = [f\"{class_name}\" for class_name in class_names]\n        detections = sv.Detections(\n            xyxy=input_boxes,\n            mask=masks.astype(bool),\n            class_id=class_ids,\n            confidence=scores,\n        )\n\n        return self.post_process_results(image, caption, labels, detections, output_dir)\n\n    def od_grounding_and_segmentation(\n        self,\n        image,\n        text_input,\n        seg_model=\"sam\",\n        output_dir=None\n    ):\n        assert seg_model in [\"sam\", \"florence2\"]\n        \n        # od grounding\n        grounding_results = self.run_florence2('<OPEN_VOCABULARY_DETECTION>', text_input, image)['<OPEN_VOCABULARY_DETECTION>']\n        if len(grounding_results[\"bboxes\"]) == 0:\n            detections = None\n            labels = []\n        else:\n            input_boxes = np.array(grounding_results[\"bboxes\"])\n            class_names = grounding_results[\"bboxes_labels\"]\n            class_ids = np.array(list(range(len(class_names))))\n\n            # segmentation\n            masks, scores = self.segmentation(image, input_boxes, seg_model)\n            \n            labels = [f\"{class_name}\" for class_name in class_names]\n            detections = sv.Detections(\n                xyxy=input_boxes,\n                mask=masks.astype(bool),\n                class_id=class_ids,\n                confidence=scores,\n            )\n\n        return self.post_process_results(image, text_input, labels, detections, output_dir)\n    \n    def od_grounding(\n        self,\n        image,\n        text_input,\n        output_dir=None\n    ):\n        \n        # od grounding\n        grounding_results = self.run_florence2('<OPEN_VOCABULARY_DETECTION>', text_input, image)['<OPEN_VOCABULARY_DETECTION>']\n        if len(grounding_results[\"bboxes\"]) == 0:\n            detections = None\n            labels = []\n        else:\n            input_boxes = np.array(grounding_results[\"bboxes\"])\n            class_names = grounding_results[\"bboxes_labels\"]\n            class_ids = np.array(list(range(len(class_names))))\n\n            labels = [f\"{class_name}\" for class_name in class_names]\n            detections = sv.Detections(\n                xyxy=input_boxes,\n                class_id=class_ids,\n            )\n\n        return self.post_process_results(image, text_input, labels, detections, output_dir)\n\n    def phrase_grounding_and_segmentation(\n        self,\n        image,\n        text_input,\n        seg_model=\"sam\",\n        output_dir=None\n    ):\n        assert seg_model in [\"sam\", \"florence2\"]\n\n        # phrase grounding\n        grounding_results = self.run_florence2('<CAPTION_TO_PHRASE_GROUNDING>', text_input, image)['<CAPTION_TO_PHRASE_GROUNDING>']\n        input_boxes = np.array(grounding_results[\"bboxes\"])\n        class_names = grounding_results[\"labels\"]\n        # print(f\"[phrase_grounding_and_segmentation] input_label={text_input}, output_label={class_names}\")\n        class_ids = np.array(list(range(len(class_names))))\n\n        # segmentation\n        masks, scores = self.segmentation(image, input_boxes, seg_model)\n        \n        labels = [f\"{class_name}\" for class_name in class_names]\n        detections = sv.Detections(\n            xyxy=input_boxes,\n            mask=masks.astype(bool),\n            class_id=class_ids,\n            confidence=scores,\n        )\n\n        return self.post_process_results(image, text_input, labels, detections, output_dir)\n\n\nif __name__ == \"__main__\":\n\n    parser = argparse.ArgumentParser(\"Grounded SAM 2 Florence-2 Demos\", add_help=True)\n    parser.add_argument(\"--image_path\", type=str, default=\"./notebooks/images/cars.jpg\", required=True, help=\"path to image file\")\n    parser.add_argument(\"--caption_type\", type=str, default=\"caption\", required=False, help=\"granularity of caption\")\n    args = parser.parse_args()\n\n\n\n    # IMAGE_PATH = args.image_path\n    PIPELINE = \"caption_to_phrase_grounding\"\n    CAPTION_TYPE = args.caption_type\n    assert CAPTION_TYPE in [\"caption\", \"detailed_caption\", \"more_detailed_caption\", \"original\"]\n    \n    print(f\"Running pipeline: {PIPELINE} now.\")\n\n    pipeline = FlorenceSAM(\"cuda:0\")\n\n    from glob import glob\n    from tqdm import tqdm\n    for image_path in tqdm(glob(\"/mnt/bn/lq-prompt-alignment/personal/chenbowen/code/IPVerse/prompt_alignment/Grounded-SAM-2/notebooks/images/*\") * 3):\n    # for image_path in tqdm(glob(\"/mnt/bn/lq-prompt-alignment/personal/chenbowen/code/IPVerse/prompt_alignment/Grounded-SAM-2/outputs/gcg_pipeline/00001.tar_debug/*.png\")):\n        print(pipeline.TASK_PROMPT, CAPTION_TYPE)\n        image = Image.open(image_path).convert(\"RGB\")\n        pipeline.caption_phrase_grounding_and_segmentation(\n            image=image,\n            seg_model=\"sam\",\n            caption_task_prompt=pipeline.TASK_PROMPT[CAPTION_TYPE],\n            output_dir=f\"./outputs/{os.path.basename(image_path)}\"\n        )"
  },
  {
    "path": "eval/grounded_sam/sam2/__init__.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom hydra import initialize_config_module\nfrom hydra.core.global_hydra import GlobalHydra\n\nif not GlobalHydra.instance().is_initialized():\n    initialize_config_module(\"sam2\", version_base=\"1.2\")\n"
  },
  {
    "path": "eval/grounded_sam/sam2/automatic_mask_generator.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\n# Adapted from https://github.com/facebookresearch/segment-anything/blob/main/segment_anything/automatic_mask_generator.py\nfrom typing import Any, Dict, List, Optional, Tuple\n\nimport numpy as np\nimport torch\nfrom torchvision.ops.boxes import batched_nms, box_area  # type: ignore\n\nfrom sam2.modeling.sam2_base import SAM2Base\nfrom sam2.sam2_image_predictor import SAM2ImagePredictor\nfrom sam2.utils.amg import (\n    area_from_rle,\n    batch_iterator,\n    batched_mask_to_box,\n    box_xyxy_to_xywh,\n    build_all_layer_point_grids,\n    calculate_stability_score,\n    coco_encode_rle,\n    generate_crop_boxes,\n    is_box_near_crop_edge,\n    mask_to_rle_pytorch,\n    MaskData,\n    remove_small_regions,\n    rle_to_mask,\n    uncrop_boxes_xyxy,\n    uncrop_masks,\n    uncrop_points,\n)\n\n\nclass SAM2AutomaticMaskGenerator:\n    def __init__(\n        self,\n        model: SAM2Base,\n        points_per_side: Optional[int] = 32,\n        points_per_batch: int = 64,\n        pred_iou_thresh: float = 0.8,\n        stability_score_thresh: float = 0.95,\n        stability_score_offset: float = 1.0,\n        mask_threshold: float = 0.0,\n        box_nms_thresh: float = 0.7,\n        crop_n_layers: int = 0,\n        crop_nms_thresh: float = 0.7,\n        crop_overlap_ratio: float = 512 / 1500,\n        crop_n_points_downscale_factor: int = 1,\n        point_grids: Optional[List[np.ndarray]] = None,\n        min_mask_region_area: int = 0,\n        output_mode: str = \"binary_mask\",\n        use_m2m: bool = False,\n        multimask_output: bool = True,\n        **kwargs,\n    ) -> None:\n        \"\"\"\n        Using a SAM 2 model, generates masks for the entire image.\n        Generates a grid of point prompts over the image, then filters\n        low quality and duplicate masks. The default settings are chosen\n        for SAM 2 with a HieraL backbone.\n\n        Arguments:\n          model (Sam): The SAM 2 model to use for mask prediction.\n          points_per_side (int or None): The number of points to be sampled\n            along one side of the image. The total number of points is\n            points_per_side**2. If None, 'point_grids' must provide explicit\n            point sampling.\n          points_per_batch (int): Sets the number of points run simultaneously\n            by the model. Higher numbers may be faster but use more GPU memory.\n          pred_iou_thresh (float): A filtering threshold in [0,1], using the\n            model's predicted mask quality.\n          stability_score_thresh (float): A filtering threshold in [0,1], using\n            the stability of the mask under changes to the cutoff used to binarize\n            the model's mask predictions.\n          stability_score_offset (float): The amount to shift the cutoff when\n            calculated the stability score.\n          mask_threshold (float): Threshold for binarizing the mask logits\n          box_nms_thresh (float): The box IoU cutoff used by non-maximal\n            suppression to filter duplicate masks.\n          crop_n_layers (int): If >0, mask prediction will be run again on\n            crops of the image. Sets the number of layers to run, where each\n            layer has 2**i_layer number of image crops.\n          crop_nms_thresh (float): The box IoU cutoff used by non-maximal\n            suppression to filter duplicate masks between different crops.\n          crop_overlap_ratio (float): Sets the degree to which crops overlap.\n            In the first crop layer, crops will overlap by this fraction of\n            the image length. Later layers with more crops scale down this overlap.\n          crop_n_points_downscale_factor (int): The number of points-per-side\n            sampled in layer n is scaled down by crop_n_points_downscale_factor**n.\n          point_grids (list(np.ndarray) or None): A list over explicit grids\n            of points used for sampling, normalized to [0,1]. The nth grid in the\n            list is used in the nth crop layer. Exclusive with points_per_side.\n          min_mask_region_area (int): If >0, postprocessing will be applied\n            to remove disconnected regions and holes in masks with area smaller\n            than min_mask_region_area. Requires opencv.\n          output_mode (str): The form masks are returned in. Can be 'binary_mask',\n            'uncompressed_rle', or 'coco_rle'. 'coco_rle' requires pycocotools.\n            For large resolutions, 'binary_mask' may consume large amounts of\n            memory.\n          use_m2m (bool): Whether to add a one step refinement using previous mask predictions.\n          multimask_output (bool): Whether to output multimask at each point of the grid.\n        \"\"\"\n\n        assert (points_per_side is None) != (\n            point_grids is None\n        ), \"Exactly one of points_per_side or point_grid must be provided.\"\n        if points_per_side is not None:\n            self.point_grids = build_all_layer_point_grids(\n                points_per_side,\n                crop_n_layers,\n                crop_n_points_downscale_factor,\n            )\n        elif point_grids is not None:\n            self.point_grids = point_grids\n        else:\n            raise ValueError(\"Can't have both points_per_side and point_grid be None.\")\n\n        assert output_mode in [\n            \"binary_mask\",\n            \"uncompressed_rle\",\n            \"coco_rle\",\n        ], f\"Unknown output_mode {output_mode}.\"\n        if output_mode == \"coco_rle\":\n            try:\n                from pycocotools import mask as mask_utils  # type: ignore  # noqa: F401\n            except ImportError as e:\n                print(\"Please install pycocotools\")\n                raise e\n\n        self.predictor = SAM2ImagePredictor(\n            model,\n            max_hole_area=min_mask_region_area,\n            max_sprinkle_area=min_mask_region_area,\n        )\n        self.points_per_batch = points_per_batch\n        self.pred_iou_thresh = pred_iou_thresh\n        self.stability_score_thresh = stability_score_thresh\n        self.stability_score_offset = stability_score_offset\n        self.mask_threshold = mask_threshold\n        self.box_nms_thresh = box_nms_thresh\n        self.crop_n_layers = crop_n_layers\n        self.crop_nms_thresh = crop_nms_thresh\n        self.crop_overlap_ratio = crop_overlap_ratio\n        self.crop_n_points_downscale_factor = crop_n_points_downscale_factor\n        self.min_mask_region_area = min_mask_region_area\n        self.output_mode = output_mode\n        self.use_m2m = use_m2m\n        self.multimask_output = multimask_output\n\n    @classmethod\n    def from_pretrained(cls, model_id: str, **kwargs) -> \"SAM2AutomaticMaskGenerator\":\n        \"\"\"\n        Load a pretrained model from the Hugging Face hub.\n\n        Arguments:\n          model_id (str): The Hugging Face repository ID.\n          **kwargs: Additional arguments to pass to the model constructor.\n\n        Returns:\n          (SAM2AutomaticMaskGenerator): The loaded model.\n        \"\"\"\n        from sam2.build_sam import build_sam2_hf\n\n        sam_model = build_sam2_hf(model_id, **kwargs)\n        return cls(sam_model, **kwargs)\n\n    @torch.no_grad()\n    def generate(self, image: np.ndarray) -> List[Dict[str, Any]]:\n        \"\"\"\n        Generates masks for the given image.\n\n        Arguments:\n          image (np.ndarray): The image to generate masks for, in HWC uint8 format.\n\n        Returns:\n           list(dict(str, any)): A list over records for masks. Each record is\n             a dict containing the following keys:\n               segmentation (dict(str, any) or np.ndarray): The mask. If\n                 output_mode='binary_mask', is an array of shape HW. Otherwise,\n                 is a dictionary containing the RLE.\n               bbox (list(float)): The box around the mask, in XYWH format.\n               area (int): The area in pixels of the mask.\n               predicted_iou (float): The model's own prediction of the mask's\n                 quality. This is filtered by the pred_iou_thresh parameter.\n               point_coords (list(list(float))): The point coordinates input\n                 to the model to generate this mask.\n               stability_score (float): A measure of the mask's quality. This\n                 is filtered on using the stability_score_thresh parameter.\n               crop_box (list(float)): The crop of the image used to generate\n                 the mask, given in XYWH format.\n        \"\"\"\n\n        # Generate masks\n        mask_data = self._generate_masks(image)\n\n        # Encode masks\n        if self.output_mode == \"coco_rle\":\n            mask_data[\"segmentations\"] = [\n                coco_encode_rle(rle) for rle in mask_data[\"rles\"]\n            ]\n        elif self.output_mode == \"binary_mask\":\n            mask_data[\"segmentations\"] = [rle_to_mask(rle) for rle in mask_data[\"rles\"]]\n        else:\n            mask_data[\"segmentations\"] = mask_data[\"rles\"]\n\n        # Write mask records\n        curr_anns = []\n        for idx in range(len(mask_data[\"segmentations\"])):\n            ann = {\n                \"segmentation\": mask_data[\"segmentations\"][idx],\n                \"area\": area_from_rle(mask_data[\"rles\"][idx]),\n                \"bbox\": box_xyxy_to_xywh(mask_data[\"boxes\"][idx]).tolist(),\n                \"predicted_iou\": mask_data[\"iou_preds\"][idx].item(),\n                \"point_coords\": [mask_data[\"points\"][idx].tolist()],\n                \"stability_score\": mask_data[\"stability_score\"][idx].item(),\n                \"crop_box\": box_xyxy_to_xywh(mask_data[\"crop_boxes\"][idx]).tolist(),\n            }\n            curr_anns.append(ann)\n\n        return curr_anns\n\n    def _generate_masks(self, image: np.ndarray) -> MaskData:\n        orig_size = image.shape[:2]\n        crop_boxes, layer_idxs = generate_crop_boxes(\n            orig_size, self.crop_n_layers, self.crop_overlap_ratio\n        )\n\n        # Iterate over image crops\n        data = MaskData()\n        for crop_box, layer_idx in zip(crop_boxes, layer_idxs):\n            crop_data = self._process_crop(image, crop_box, layer_idx, orig_size)\n            data.cat(crop_data)\n\n        # Remove duplicate masks between crops\n        if len(crop_boxes) > 1:\n            # Prefer masks from smaller crops\n            scores = 1 / box_area(data[\"crop_boxes\"])\n            scores = scores.to(data[\"boxes\"].device)\n            keep_by_nms = batched_nms(\n                data[\"boxes\"].float(),\n                scores,\n                torch.zeros_like(data[\"boxes\"][:, 0]),  # categories\n                iou_threshold=self.crop_nms_thresh,\n            )\n            data.filter(keep_by_nms)\n        data.to_numpy()\n        return data\n\n    def _process_crop(\n        self,\n        image: np.ndarray,\n        crop_box: List[int],\n        crop_layer_idx: int,\n        orig_size: Tuple[int, ...],\n    ) -> MaskData:\n        # Crop the image and calculate embeddings\n        x0, y0, x1, y1 = crop_box\n        cropped_im = image[y0:y1, x0:x1, :]\n        cropped_im_size = cropped_im.shape[:2]\n        self.predictor.set_image(cropped_im)\n\n        # Get points for this crop\n        points_scale = np.array(cropped_im_size)[None, ::-1]\n        points_for_image = self.point_grids[crop_layer_idx] * points_scale\n\n        # Generate masks for this crop in batches\n        data = MaskData()\n        for (points,) in batch_iterator(self.points_per_batch, points_for_image):\n            batch_data = self._process_batch(\n                points, cropped_im_size, crop_box, orig_size, normalize=True\n            )\n            data.cat(batch_data)\n            del batch_data\n        self.predictor.reset_predictor()\n\n        # Remove duplicates within this crop.\n        keep_by_nms = batched_nms(\n            data[\"boxes\"].float(),\n            data[\"iou_preds\"],\n            torch.zeros_like(data[\"boxes\"][:, 0]),  # categories\n            iou_threshold=self.box_nms_thresh,\n        )\n        data.filter(keep_by_nms)\n\n        # Return to the original image frame\n        data[\"boxes\"] = uncrop_boxes_xyxy(data[\"boxes\"], crop_box)\n        data[\"points\"] = uncrop_points(data[\"points\"], crop_box)\n        data[\"crop_boxes\"] = torch.tensor([crop_box for _ in range(len(data[\"rles\"]))])\n\n        return data\n\n    def _process_batch(\n        self,\n        points: np.ndarray,\n        im_size: Tuple[int, ...],\n        crop_box: List[int],\n        orig_size: Tuple[int, ...],\n        normalize=False,\n    ) -> MaskData:\n        orig_h, orig_w = orig_size\n\n        # Run model on this batch\n        points = torch.as_tensor(\n            points, dtype=torch.float32, device=self.predictor.device\n        )\n        in_points = self.predictor._transforms.transform_coords(\n            points, normalize=normalize, orig_hw=im_size\n        )\n        in_labels = torch.ones(\n            in_points.shape[0], dtype=torch.int, device=in_points.device\n        )\n        masks, iou_preds, low_res_masks = self.predictor._predict(\n            in_points[:, None, :],\n            in_labels[:, None],\n            multimask_output=self.multimask_output,\n            return_logits=True,\n        )\n\n        # Serialize predictions and store in MaskData\n        data = MaskData(\n            masks=masks.flatten(0, 1),\n            iou_preds=iou_preds.flatten(0, 1),\n            points=points.repeat_interleave(masks.shape[1], dim=0),\n            low_res_masks=low_res_masks.flatten(0, 1),\n        )\n        del masks\n\n        if not self.use_m2m:\n            # Filter by predicted IoU\n            if self.pred_iou_thresh > 0.0:\n                keep_mask = data[\"iou_preds\"] > self.pred_iou_thresh\n                data.filter(keep_mask)\n\n            # Calculate and filter by stability score\n            data[\"stability_score\"] = calculate_stability_score(\n                data[\"masks\"], self.mask_threshold, self.stability_score_offset\n            )\n            if self.stability_score_thresh > 0.0:\n                keep_mask = data[\"stability_score\"] >= self.stability_score_thresh\n                data.filter(keep_mask)\n        else:\n            # One step refinement using previous mask predictions\n            in_points = self.predictor._transforms.transform_coords(\n                data[\"points\"], normalize=normalize, orig_hw=im_size\n            )\n            labels = torch.ones(\n                in_points.shape[0], dtype=torch.int, device=in_points.device\n            )\n            masks, ious = self.refine_with_m2m(\n                in_points, labels, data[\"low_res_masks\"], self.points_per_batch\n            )\n            data[\"masks\"] = masks.squeeze(1)\n            data[\"iou_preds\"] = ious.squeeze(1)\n\n            if self.pred_iou_thresh > 0.0:\n                keep_mask = data[\"iou_preds\"] > self.pred_iou_thresh\n                data.filter(keep_mask)\n\n            data[\"stability_score\"] = calculate_stability_score(\n                data[\"masks\"], self.mask_threshold, self.stability_score_offset\n            )\n            if self.stability_score_thresh > 0.0:\n                keep_mask = data[\"stability_score\"] >= self.stability_score_thresh\n                data.filter(keep_mask)\n\n        # Threshold masks and calculate boxes\n        data[\"masks\"] = data[\"masks\"] > self.mask_threshold\n        data[\"boxes\"] = batched_mask_to_box(data[\"masks\"])\n\n        # Filter boxes that touch crop boundaries\n        keep_mask = ~is_box_near_crop_edge(\n            data[\"boxes\"], crop_box, [0, 0, orig_w, orig_h]\n        )\n        if not torch.all(keep_mask):\n            data.filter(keep_mask)\n\n        # Compress to RLE\n        data[\"masks\"] = uncrop_masks(data[\"masks\"], crop_box, orig_h, orig_w)\n        data[\"rles\"] = mask_to_rle_pytorch(data[\"masks\"])\n        del data[\"masks\"]\n\n        return data\n\n    @staticmethod\n    def postprocess_small_regions(\n        mask_data: MaskData, min_area: int, nms_thresh: float\n    ) -> MaskData:\n        \"\"\"\n        Removes small disconnected regions and holes in masks, then reruns\n        box NMS to remove any new duplicates.\n\n        Edits mask_data in place.\n\n        Requires open-cv as a dependency.\n        \"\"\"\n        if len(mask_data[\"rles\"]) == 0:\n            return mask_data\n\n        # Filter small disconnected regions and holes\n        new_masks = []\n        scores = []\n        for rle in mask_data[\"rles\"]:\n            mask = rle_to_mask(rle)\n\n            mask, changed = remove_small_regions(mask, min_area, mode=\"holes\")\n            unchanged = not changed\n            mask, changed = remove_small_regions(mask, min_area, mode=\"islands\")\n            unchanged = unchanged and not changed\n\n            new_masks.append(torch.as_tensor(mask).unsqueeze(0))\n            # Give score=0 to changed masks and score=1 to unchanged masks\n            # so NMS will prefer ones that didn't need postprocessing\n            scores.append(float(unchanged))\n\n        # Recalculate boxes and remove any new duplicates\n        masks = torch.cat(new_masks, dim=0)\n        boxes = batched_mask_to_box(masks)\n        keep_by_nms = batched_nms(\n            boxes.float(),\n            torch.as_tensor(scores),\n            torch.zeros_like(boxes[:, 0]),  # categories\n            iou_threshold=nms_thresh,\n        )\n\n        # Only recalculate RLEs for masks that have changed\n        for i_mask in keep_by_nms:\n            if scores[i_mask] == 0.0:\n                mask_torch = masks[i_mask].unsqueeze(0)\n                mask_data[\"rles\"][i_mask] = mask_to_rle_pytorch(mask_torch)[0]\n                mask_data[\"boxes\"][i_mask] = boxes[i_mask]  # update res directly\n        mask_data.filter(keep_by_nms)\n\n        return mask_data\n\n    def refine_with_m2m(self, points, point_labels, low_res_masks, points_per_batch):\n        new_masks = []\n        new_iou_preds = []\n\n        for cur_points, cur_point_labels, low_res_mask in batch_iterator(\n            points_per_batch, points, point_labels, low_res_masks\n        ):\n            best_masks, best_iou_preds, _ = self.predictor._predict(\n                cur_points[:, None, :],\n                cur_point_labels[:, None],\n                mask_input=low_res_mask[:, None, :],\n                multimask_output=False,\n                return_logits=True,\n            )\n            new_masks.append(best_masks)\n            new_iou_preds.append(best_iou_preds)\n        masks = torch.cat(new_masks, dim=0)\n        return masks, torch.cat(new_iou_preds, dim=0)\n"
  },
  {
    "path": "eval/grounded_sam/sam2/build_sam.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport logging\nimport os\nimport sys\nimport torch\nfrom hydra import compose\nfrom hydra.utils import instantiate\nfrom omegaconf import OmegaConf\n\nfrom pathlib import Path\ncurrent_dir = str(Path(os.path.abspath('')))\nsam_dir = os.path.join(current_dir, \"eval/grounded_sam\")\nsys.path.append(sam_dir)\n\nimport sam2\n\n# # Check if the user is running Python from the parent directory of the sam2 repo\n# # (i.e. the directory where this repo is cloned into) -- this is not supported since\n# # it could shadow the sam2 package and cause issues.\n# if os.path.isdir(os.path.join(sam2.__path__[0], \"sam2\")):\n#     # If the user has \"sam2/sam2\" in their path, they are likey importing the repo itself\n#     # as \"sam2\" rather than importing the \"sam2\" python package (i.e. \"sam2/sam2\" directory).\n#     # This typically happens because the user is running Python from the parent directory\n#     # that contains the sam2 repo they cloned.\n#     raise RuntimeError(\n#         \"You're likely running Python from the parent directory of the sam2 repository \"\n#         \"(i.e. the directory where https://github.com/facebookresearch/sam2 is cloned into). \"\n#         \"This is not supported since the `sam2` Python package could be shadowed by the \"\n#         \"repository name (the repository is also named `sam2` and contains the Python package \"\n#         \"in `sam2/sam2`). Please run Python from another directory (e.g. from the repo dir \"\n#         \"rather than its parent dir, or from your home directory) after installing SAM 2.\"\n#     )\n\n\nHF_MODEL_ID_TO_FILENAMES = {\n    \"facebook/sam2-hiera-tiny\": (\n        \"configs/sam2/sam2_hiera_t.yaml\",\n        \"sam2_hiera_tiny.pt\",\n    ),\n    \"facebook/sam2-hiera-small\": (\n        \"configs/sam2/sam2_hiera_s.yaml\",\n        \"sam2_hiera_small.pt\",\n    ),\n    \"facebook/sam2-hiera-base-plus\": (\n        \"configs/sam2/sam2_hiera_b+.yaml\",\n        \"sam2_hiera_base_plus.pt\",\n    ),\n    \"facebook/sam2-hiera-large\": (\n        \"configs/sam2/sam2_hiera_l.yaml\",\n        \"sam2_hiera_large.pt\",\n    ),\n    \"facebook/sam2.1-hiera-tiny\": (\n        \"configs/sam2.1/sam2.1_hiera_t.yaml\",\n        \"sam2.1_hiera_tiny.pt\",\n    ),\n    \"facebook/sam2.1-hiera-small\": (\n        \"configs/sam2.1/sam2.1_hiera_s.yaml\",\n        \"sam2.1_hiera_small.pt\",\n    ),\n    \"facebook/sam2.1-hiera-base-plus\": (\n        \"configs/sam2.1/sam2.1_hiera_b+.yaml\",\n        \"sam2.1_hiera_base_plus.pt\",\n    ),\n    \"facebook/sam2.1-hiera-large\": (\n        \"configs/sam2.1/sam2.1_hiera_l.yaml\",\n        \"sam2.1_hiera_large.pt\",\n    ),\n}\n\n\ndef build_sam2(\n    config_file,\n    ckpt_path=None,\n    device=\"cuda\",\n    mode=\"eval\",\n    hydra_overrides_extra=[],\n    apply_postprocessing=True,\n    **kwargs,\n):\n\n    if apply_postprocessing:\n        hydra_overrides_extra = hydra_overrides_extra.copy()\n        hydra_overrides_extra += [\n            # dynamically fall back to multi-mask if the single mask is not stable\n            \"++model.sam_mask_decoder_extra_args.dynamic_multimask_via_stability=true\",\n            \"++model.sam_mask_decoder_extra_args.dynamic_multimask_stability_delta=0.05\",\n            \"++model.sam_mask_decoder_extra_args.dynamic_multimask_stability_thresh=0.98\",\n        ]\n    # Read config and init model\n    cfg = compose(config_name=config_file, overrides=hydra_overrides_extra)\n    OmegaConf.resolve(cfg)\n    model = instantiate(cfg.model, _recursive_=True)\n    _load_checkpoint(model, ckpt_path)\n    model = model.to(device)\n    if mode == \"eval\":\n        model.eval()\n    return model\n\n\ndef build_sam2_video_predictor(\n    config_file,\n    ckpt_path=None,\n    device=\"cuda\",\n    mode=\"eval\",\n    hydra_overrides_extra=[],\n    apply_postprocessing=True,\n    **kwargs,\n):\n    hydra_overrides = [\n        \"++model._target_=sam2.sam2_video_predictor.SAM2VideoPredictor\",\n    ]\n    if apply_postprocessing:\n        hydra_overrides_extra = hydra_overrides_extra.copy()\n        hydra_overrides_extra += [\n            # dynamically fall back to multi-mask if the single mask is not stable\n            \"++model.sam_mask_decoder_extra_args.dynamic_multimask_via_stability=true\",\n            \"++model.sam_mask_decoder_extra_args.dynamic_multimask_stability_delta=0.05\",\n            \"++model.sam_mask_decoder_extra_args.dynamic_multimask_stability_thresh=0.98\",\n            # the sigmoid mask logits on interacted frames with clicks in the memory encoder so that the encoded masks are exactly as what users see from clicking\n            \"++model.binarize_mask_from_pts_for_mem_enc=true\",\n            # fill small holes in the low-res masks up to `fill_hole_area` (before resizing them to the original video resolution)\n            \"++model.fill_hole_area=8\",\n        ]\n    hydra_overrides.extend(hydra_overrides_extra)\n\n    # Read config and init model\n    cfg = compose(config_name=config_file, overrides=hydra_overrides)\n    OmegaConf.resolve(cfg)\n    model = instantiate(cfg.model, _recursive_=True)\n    _load_checkpoint(model, ckpt_path)\n    model = model.to(device)\n    if mode == \"eval\":\n        model.eval()\n    return model\n\n\ndef _hf_download(model_id):\n    from huggingface_hub import hf_hub_download\n\n    config_name, checkpoint_name = HF_MODEL_ID_TO_FILENAMES[model_id]\n    ckpt_path = hf_hub_download(repo_id=model_id, filename=checkpoint_name)\n    return config_name, ckpt_path\n\n\ndef build_sam2_hf(model_id, **kwargs):\n    config_name, ckpt_path = _hf_download(model_id)\n    return build_sam2(config_file=config_name, ckpt_path=ckpt_path, **kwargs)\n\n\ndef build_sam2_video_predictor_hf(model_id, **kwargs):\n    config_name, ckpt_path = _hf_download(model_id)\n    return build_sam2_video_predictor(\n        config_file=config_name, ckpt_path=ckpt_path, **kwargs\n    )\n\n\ndef _load_checkpoint(model, ckpt_path):\n    if ckpt_path is not None:\n        sd = torch.load(ckpt_path, map_location=\"cpu\", weights_only=True)[\"model\"]\n        missing_keys, unexpected_keys = model.load_state_dict(sd)\n        if missing_keys:\n            logging.error(missing_keys)\n            raise RuntimeError()\n        if unexpected_keys:\n            logging.error(unexpected_keys)\n            raise RuntimeError()\n        logging.info(\"Loaded checkpoint sucessfully\")\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2/sam2_hiera_b+.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 112\n      num_heads: 2\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [896, 448, 224, 112]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2/sam2_hiera_l.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 144\n      num_heads: 2\n      stages: [2, 6, 36, 4]\n      global_att_blocks: [23, 33, 43]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n      window_spec: [8, 4, 16, 8]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [1152, 576, 288, 144]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2/sam2_hiera_s.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 96\n      num_heads: 1\n      stages: [1, 2, 11, 2]\n      global_att_blocks: [7, 10, 13]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [768, 384, 192, 96]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2/sam2_hiera_t.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 96\n      num_heads: 1\n      stages: [1, 2, 7, 2]\n      global_att_blocks: [5, 7, 9]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [768, 384, 192, 96]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  # SAM decoder\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  # HieraT does not currently support compilation, should always be set to False\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2.1/sam2.1_hiera_b+.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 112\n      num_heads: 2\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [896, 448, 224, 112]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  no_obj_embed_spatial: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: true\n  proj_tpos_enc_in_obj_ptrs: true\n  use_signed_tpos_enc_to_obj_ptrs: true\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2.1/sam2.1_hiera_l.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 144\n      num_heads: 2\n      stages: [2, 6, 36, 4]\n      global_att_blocks: [23, 33, 43]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n      window_spec: [8, 4, 16, 8]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [1152, 576, 288, 144]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  no_obj_embed_spatial: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: true\n  proj_tpos_enc_in_obj_ptrs: true\n  use_signed_tpos_enc_to_obj_ptrs: true\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2.1/sam2.1_hiera_s.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 96\n      num_heads: 1\n      stages: [1, 2, 11, 2]\n      global_att_blocks: [7, 10, 13]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [768, 384, 192, 96]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  no_obj_embed_spatial: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: true\n  proj_tpos_enc_in_obj_ptrs: true\n  use_signed_tpos_enc_to_obj_ptrs: true\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2.1/sam2.1_hiera_t.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 96\n      num_heads: 1\n      stages: [1, 2, 7, 2]\n      global_att_blocks: [5, 7, 9]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [768, 384, 192, 96]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  # SAM decoder\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  no_obj_embed_spatial: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: true\n  proj_tpos_enc_in_obj_ptrs: true\n  use_signed_tpos_enc_to_obj_ptrs: true\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  # HieraT does not currently support compilation, should always be set to False\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/configs/sam2.1_training/sam2.1_hiera_b+_MOSE_finetune.yaml",
    "content": "# @package _global_\n\nscratch:\n  resolution: 1024\n  train_batch_size: 1\n  num_train_workers: 10\n  num_frames: 8\n  max_num_objects: 3\n  base_lr: 5.0e-6\n  vision_lr: 3.0e-06\n  phases_per_epoch: 1\n  num_epochs: 40\n\ndataset:\n  # PATHS to Dataset\n  img_folder: null # PATH to MOSE JPEGImages folder\n  gt_folder: null  # PATH to MOSE Annotations folder\n  file_list_txt: training/assets/MOSE_sample_train_list.txt # Optional PATH to filelist containing a subset of videos to be used for training\n  multiplier: 2\n\n# Video transforms\nvos:\n  train_transforms:\n    - _target_: training.dataset.transforms.ComposeAPI\n      transforms:\n        - _target_: training.dataset.transforms.RandomHorizontalFlip\n          consistent_transform: True\n        - _target_: training.dataset.transforms.RandomAffine\n          degrees: 25\n          shear: 20\n          image_interpolation: bilinear\n          consistent_transform: True\n        - _target_: training.dataset.transforms.RandomResizeAPI\n          sizes: ${scratch.resolution}\n          square: true\n          consistent_transform: True\n        - _target_: training.dataset.transforms.ColorJitter\n          consistent_transform: True\n          brightness: 0.1\n          contrast: 0.03\n          saturation: 0.03\n          hue: null\n        - _target_: training.dataset.transforms.RandomGrayscale\n          p: 0.05\n          consistent_transform: True\n        - _target_: training.dataset.transforms.ColorJitter\n          consistent_transform: False\n          brightness: 0.1\n          contrast: 0.05\n          saturation: 0.05\n          hue: null\n        - _target_: training.dataset.transforms.ToTensorAPI\n        - _target_: training.dataset.transforms.NormalizeAPI\n          mean: [0.485, 0.456, 0.406]\n          std: [0.229, 0.224, 0.225]\n\ntrainer:\n  _target_: training.trainer.Trainer\n  mode: train_only\n  max_epochs: ${times:${scratch.num_epochs},${scratch.phases_per_epoch}}\n  accelerator: cuda\n  seed_value: 123\n\n  model:\n    _target_: training.model.sam2.SAM2Train\n    image_encoder:\n      _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n      scalp: 1\n      trunk:\n        _target_: sam2.modeling.backbones.hieradet.Hiera\n        embed_dim: 112\n        num_heads: 2\n        drop_path_rate: 0.1\n      neck:\n        _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n        position_encoding:\n          _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n          num_pos_feats: 256\n          normalize: true\n          scale: null\n          temperature: 10000\n        d_model: 256\n        backbone_channel_list: [896, 448, 224, 112]\n        fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n        fpn_interp_model: nearest\n\n    memory_attention:\n      _target_: sam2.modeling.memory_attention.MemoryAttention\n      d_model: 256\n      pos_enc_at_input: true\n      layer:\n        _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n        activation: relu\n        dim_feedforward: 2048\n        dropout: 0.1\n        pos_enc_at_attn: false\n        self_attention:\n          _target_: sam2.modeling.sam.transformer.RoPEAttention\n          rope_theta: 10000.0\n          feat_sizes: [32, 32]\n          embedding_dim: 256\n          num_heads: 1\n          downsample_rate: 1\n          dropout: 0.1\n        d_model: 256\n        pos_enc_at_cross_attn_keys: true\n        pos_enc_at_cross_attn_queries: false\n        cross_attention:\n          _target_: sam2.modeling.sam.transformer.RoPEAttention\n          rope_theta: 10000.0\n          feat_sizes: [32, 32]\n          rope_k_repeat: True\n          embedding_dim: 256\n          num_heads: 1\n          downsample_rate: 1\n          dropout: 0.1\n          kv_in_dim: 64\n      num_layers: 4\n\n    memory_encoder:\n        _target_: sam2.modeling.memory_encoder.MemoryEncoder\n        out_dim: 64\n        position_encoding:\n          _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n          num_pos_feats: 64\n          normalize: true\n          scale: null\n          temperature: 10000\n        mask_downsampler:\n          _target_: sam2.modeling.memory_encoder.MaskDownSampler\n          kernel_size: 3\n          stride: 2\n          padding: 1\n        fuser:\n          _target_: sam2.modeling.memory_encoder.Fuser\n          layer:\n            _target_: sam2.modeling.memory_encoder.CXBlock\n            dim: 256\n            kernel_size: 7\n            padding: 3\n            layer_scale_init_value: 1e-6\n            use_dwconv: True  # depth-wise convs\n          num_layers: 2\n\n    num_maskmem: 7\n    image_size: ${scratch.resolution}\n    # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n    sigmoid_scale_for_mem_enc: 20.0\n    sigmoid_bias_for_mem_enc: -10.0\n    use_mask_input_as_output_without_sam: true\n    # Memory\n    directly_add_no_mem_embed: true\n    no_obj_embed_spatial: true\n    # use high-resolution feature map in the SAM mask decoder\n    use_high_res_features_in_sam: true\n    # output 3 masks on the first click on initial conditioning frames\n    multimask_output_in_sam: true\n    # SAM heads\n    iou_prediction_use_sigmoid: True\n    # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n    use_obj_ptrs_in_encoder: true\n    add_tpos_enc_to_obj_ptrs: true\n    proj_tpos_enc_in_obj_ptrs: true\n    use_signed_tpos_enc_to_obj_ptrs: true\n    only_obj_ptrs_in_the_past_for_eval: true\n    # object occlusion prediction\n    pred_obj_scores: true\n    pred_obj_scores_mlp: true\n    fixed_no_obj_ptr: true\n    # multimask tracking settings\n    multimask_output_for_tracking: true\n    use_multimask_token_for_obj_ptr: true\n    multimask_min_pt_num: 0\n    multimask_max_pt_num: 1\n    use_mlp_for_obj_ptr_proj: true\n    # Compilation flag\n    # compile_image_encoder: False\n\n    ####### Training specific params #######\n    # box/point input and corrections\n    prob_to_use_pt_input_for_train: 0.5\n    prob_to_use_pt_input_for_eval: 0.0\n    prob_to_use_box_input_for_train: 0.5  # 0.5*0.5 = 0.25 prob to use box instead of points\n    prob_to_use_box_input_for_eval: 0.0\n    prob_to_sample_from_gt_for_train: 0.1  # with a small prob, sampling correction points from GT mask instead of prediction errors\n    num_frames_to_correct_for_train: 2  # iteratively sample on random 1~2 frames (always include the first frame)\n    num_frames_to_correct_for_eval: 1  # only iteratively sample on first frame\n    rand_frames_to_correct_for_train: True  # random #init-cond-frame ~ 2\n    add_all_frames_to_correct_as_cond: True  # when a frame receives a correction click, it becomes a conditioning frame (even if it's not initially a conditioning frame)\n    # maximum 2 initial conditioning frames\n    num_init_cond_frames_for_train: 2\n    rand_init_cond_frames_for_train: True  # random 1~2\n    num_correction_pt_per_frame: 7\n    use_act_ckpt_iterative_pt_sampling: false\n    \n\n    \n    num_init_cond_frames_for_eval: 1  # only mask on the first frame\n    forward_backbone_per_frame_for_eval: True\n    \n\n  data:\n    train:\n      _target_: training.dataset.sam2_datasets.TorchTrainMixedDataset\n      phases_per_epoch: ${scratch.phases_per_epoch}\n      batch_sizes:\n        - ${scratch.train_batch_size}\n\n      datasets:\n        - _target_: training.dataset.utils.RepeatFactorWrapper\n          dataset:\n            _target_: training.dataset.utils.ConcatDataset\n            datasets:\n            - _target_: training.dataset.vos_dataset.VOSDataset\n              transforms: ${vos.train_transforms}\n              training: true\n              video_dataset:\n                _target_: training.dataset.vos_raw_dataset.PNGRawDataset\n                img_folder: ${dataset.img_folder}\n                gt_folder: ${dataset.gt_folder}\n                file_list_txt: ${dataset.file_list_txt}\n              sampler:\n                _target_: training.dataset.vos_sampler.RandomUniformSampler\n                num_frames: ${scratch.num_frames}\n                max_num_objects: ${scratch.max_num_objects}\n              multiplier: ${dataset.multiplier}\n      shuffle: True\n      num_workers: ${scratch.num_train_workers}\n      pin_memory: True\n      drop_last: True\n      collate_fn:\n        _target_: training.utils.data_utils.collate_fn\n        _partial_: true\n        dict_key: all\n\n  optim:\n    amp:\n      enabled: True\n      amp_dtype: bfloat16\n\n    optimizer:\n      _target_: torch.optim.AdamW\n\n    gradient_clip:\n      _target_: training.optimizer.GradientClipper\n      max_norm: 0.1\n      norm_type: 2\n\n    param_group_modifiers:\n      - _target_: training.optimizer.layer_decay_param_modifier\n        _partial_: True\n        layer_decay_value: 0.9\n        apply_to: 'image_encoder.trunk'\n        overrides:\n          - pattern: '*pos_embed*'\n            value: 1.0\n\n    options:\n      lr:\n        - scheduler:\n            _target_: fvcore.common.param_scheduler.CosineParamScheduler\n            start_value: ${scratch.base_lr}\n            end_value: ${divide:${scratch.base_lr},10}\n        - scheduler:\n            _target_: fvcore.common.param_scheduler.CosineParamScheduler\n            start_value: ${scratch.vision_lr}\n            end_value: ${divide:${scratch.vision_lr},10}\n          param_names:\n            - 'image_encoder.*'\n      weight_decay:\n        - scheduler:\n            _target_: fvcore.common.param_scheduler.ConstantParamScheduler\n            value: 0.1\n        - scheduler:\n            _target_: fvcore.common.param_scheduler.ConstantParamScheduler\n            value: 0.0\n          param_names:\n            - '*bias*'\n          module_cls_names: ['torch.nn.LayerNorm']\n\n  loss:\n    all:\n      _target_: training.loss_fns.MultiStepMultiMasksAndIous\n      weight_dict:\n        loss_mask: 20\n        loss_dice: 1\n        loss_iou: 1\n        loss_class: 1\n      supervise_all_iou: true\n      iou_use_l1_loss: true\n      pred_obj_scores: true\n      focal_gamma_obj_score: 0.0\n      focal_alpha_obj_score: -1.0\n\n  distributed:\n    backend: nccl\n    find_unused_parameters: True\n\n  logging:\n    tensorboard_writer:\n      _target_: training.utils.logger.make_tensorboard_logger\n      log_dir:  ${launcher.experiment_log_dir}/tensorboard\n      flush_secs: 120\n      should_log: True\n    log_dir: ${launcher.experiment_log_dir}/logs\n    log_freq: 10\n\n  # initialize from a SAM 2 checkpoint\n  checkpoint:\n    save_dir: ${launcher.experiment_log_dir}/checkpoints\n    save_freq: 0 # 0 only last checkpoint is saved.\n    model_weight_initializer:\n      _partial_: True\n      _target_: training.utils.checkpoint_utils.load_state_dict_into_model\n      strict: True\n      ignore_unexpected_keys: null\n      ignore_missing_keys: null\n\n      state_dict:\n        _target_: training.utils.checkpoint_utils.load_checkpoint_and_apply_kernels\n        checkpoint_path: ./checkpoints/sam2.1_hiera_base_plus.pt # PATH to SAM 2.1 checkpoint\n        ckpt_state_dict_keys: ['model']\n\nlauncher:\n  num_nodes: 1\n  gpus_per_node: 8\n  experiment_log_dir: null # Path to log directory, defaults to ./sam2_logs/${config_name}\n\n# SLURM args if running on a cluster\nsubmitit:\n  partition: null\n  account: null\n  qos: null\n  cpus_per_task: 10\n  use_cluster: false\n  timeout_hour: 24\n  name: null\n  port_range: [10000, 65000]\n\n"
  },
  {
    "path": "eval/grounded_sam/sam2/csrc/connected_components.cu",
    "content": "// Copyright (c) Meta Platforms, Inc. and affiliates.\n// All rights reserved.\n\n// This source code is licensed under the license found in the\n// LICENSE file in the root directory of this source tree.\n\n// adapted from https://github.com/zsef123/Connected_components_PyTorch\n// with license found in the LICENSE_cctorch file in the root directory.\n#include <ATen/cuda/CUDAContext.h>\n#include <cuda.h>\n#include <cuda_runtime.h>\n#include <torch/extension.h>\n#include <torch/script.h>\n#include <vector>\n\n// 2d\n#define BLOCK_ROWS 16\n#define BLOCK_COLS 16\n\nnamespace cc2d {\n\ntemplate <typename T>\n__device__ __forceinline__ unsigned char hasBit(T bitmap, unsigned char pos) {\n  return (bitmap >> pos) & 1;\n}\n\n__device__ int32_t find(const int32_t* s_buf, int32_t n) {\n  while (s_buf[n] != n)\n    n = s_buf[n];\n  return n;\n}\n\n__device__ int32_t find_n_compress(int32_t* s_buf, int32_t n) {\n  const int32_t id = n;\n  while (s_buf[n] != n) {\n    n = s_buf[n];\n    s_buf[id] = n;\n  }\n  return n;\n}\n\n__device__ void union_(int32_t* s_buf, int32_t a, int32_t b) {\n  bool done;\n  do {\n    a = find(s_buf, a);\n    b = find(s_buf, b);\n\n    if (a < b) {\n      int32_t old = atomicMin(s_buf + b, a);\n      done = (old == b);\n      b = old;\n    } else if (b < a) {\n      int32_t old = atomicMin(s_buf + a, b);\n      done = (old == a);\n      a = old;\n    } else\n      done = true;\n\n  } while (!done);\n}\n\n__global__ void\ninit_labeling(int32_t* label, const uint32_t W, const uint32_t H) {\n  const uint32_t row = (blockIdx.y * blockDim.y + threadIdx.y) * 2;\n  const uint32_t col = (blockIdx.x * blockDim.x + threadIdx.x) * 2;\n  const uint32_t idx = row * W + col;\n\n  if (row < H && col < W)\n    label[idx] = idx;\n}\n\n__global__ void\nmerge(uint8_t* img, int32_t* label, const uint32_t W, const uint32_t H) {\n  const uint32_t row = (blockIdx.y * blockDim.y + threadIdx.y) * 2;\n  const uint32_t col = (blockIdx.x * blockDim.x + threadIdx.x) * 2;\n  const uint32_t idx = row * W + col;\n\n  if (row >= H || col >= W)\n    return;\n\n  uint32_t P = 0;\n\n  if (img[idx])\n    P |= 0x777;\n  if (row + 1 < H && img[idx + W])\n    P |= 0x777 << 4;\n  if (col + 1 < W && img[idx + 1])\n    P |= 0x777 << 1;\n\n  if (col == 0)\n    P &= 0xEEEE;\n  if (col + 1 >= W)\n    P &= 0x3333;\n  else if (col + 2 >= W)\n    P &= 0x7777;\n\n  if (row == 0)\n    P &= 0xFFF0;\n  if (row + 1 >= H)\n    P &= 0xFF;\n\n  if (P > 0) {\n    // If need check about top-left pixel(if flag the first bit) and hit the\n    // top-left pixel\n    if (hasBit(P, 0) && img[idx - W - 1]) {\n      union_(label, idx, idx - 2 * W - 2); // top left block\n    }\n\n    if ((hasBit(P, 1) && img[idx - W]) || (hasBit(P, 2) && img[idx - W + 1]))\n      union_(label, idx, idx - 2 * W); // top bottom block\n\n    if (hasBit(P, 3) && img[idx + 2 - W])\n      union_(label, idx, idx - 2 * W + 2); // top right block\n\n    if ((hasBit(P, 4) && img[idx - 1]) || (hasBit(P, 8) && img[idx + W - 1]))\n      union_(label, idx, idx - 2); // just left block\n  }\n}\n\n__global__ void compression(int32_t* label, const int32_t W, const int32_t H) {\n  const uint32_t row = (blockIdx.y * blockDim.y + threadIdx.y) * 2;\n  const uint32_t col = (blockIdx.x * blockDim.x + threadIdx.x) * 2;\n  const uint32_t idx = row * W + col;\n\n  if (row < H && col < W)\n    find_n_compress(label, idx);\n}\n\n__global__ void final_labeling(\n    const uint8_t* img,\n    int32_t* label,\n    const int32_t W,\n    const int32_t H) {\n  const uint32_t row = (blockIdx.y * blockDim.y + threadIdx.y) * 2;\n  const uint32_t col = (blockIdx.x * blockDim.x + threadIdx.x) * 2;\n  const uint32_t idx = row * W + col;\n\n  if (row >= H || col >= W)\n    return;\n\n  int32_t y = label[idx] + 1;\n\n  if (img[idx])\n    label[idx] = y;\n  else\n    label[idx] = 0;\n\n  if (col + 1 < W) {\n    if (img[idx + 1])\n      label[idx + 1] = y;\n    else\n      label[idx + 1] = 0;\n\n    if (row + 1 < H) {\n      if (img[idx + W + 1])\n        label[idx + W + 1] = y;\n      else\n        label[idx + W + 1] = 0;\n    }\n  }\n\n  if (row + 1 < H) {\n    if (img[idx + W])\n      label[idx + W] = y;\n    else\n      label[idx + W] = 0;\n  }\n}\n\n__global__ void init_counting(\n    const int32_t* label,\n    int32_t* count_init,\n    const int32_t W,\n    const int32_t H) {\n  const uint32_t row = (blockIdx.y * blockDim.y + threadIdx.y);\n  const uint32_t col = (blockIdx.x * blockDim.x + threadIdx.x);\n  const uint32_t idx = row * W + col;\n\n  if (row >= H || col >= W)\n    return;\n\n  int32_t y = label[idx];\n  if (y > 0) {\n    int32_t count_idx = y - 1;\n    atomicAdd(count_init + count_idx, 1);\n  }\n}\n\n__global__ void final_counting(\n    const int32_t* label,\n    const int32_t* count_init,\n    int32_t* count_final,\n    const int32_t W,\n    const int32_t H) {\n  const uint32_t row = (blockIdx.y * blockDim.y + threadIdx.y);\n  const uint32_t col = (blockIdx.x * blockDim.x + threadIdx.x);\n  const uint32_t idx = row * W + col;\n\n  if (row >= H || col >= W)\n    return;\n\n  int32_t y = label[idx];\n  if (y > 0) {\n    int32_t count_idx = y - 1;\n    count_final[idx] = count_init[count_idx];\n  } else {\n    count_final[idx] = 0;\n  }\n}\n\n} // namespace cc2d\n\nstd::vector<torch::Tensor> get_connected_componnets(\n    const torch::Tensor& inputs) {\n  AT_ASSERTM(inputs.is_cuda(), \"inputs must be a CUDA tensor\");\n  AT_ASSERTM(inputs.ndimension() == 4, \"inputs must be [N, 1, H, W] shape\");\n  AT_ASSERTM(\n      inputs.scalar_type() == torch::kUInt8, \"inputs must be a uint8 type\");\n\n  const uint32_t N = inputs.size(0);\n  const uint32_t C = inputs.size(1);\n  const uint32_t H = inputs.size(2);\n  const uint32_t W = inputs.size(3);\n\n  AT_ASSERTM(C == 1, \"inputs must be [N, 1, H, W] shape\");\n  AT_ASSERTM((H % 2) == 0, \"height must be an even number\");\n  AT_ASSERTM((W % 2) == 0, \"width must be an even number\");\n\n  // label must be uint32_t\n  auto label_options =\n      torch::TensorOptions().dtype(torch::kInt32).device(inputs.device());\n  torch::Tensor labels = torch::zeros({N, C, H, W}, label_options);\n  torch::Tensor counts_init = torch::zeros({N, C, H, W}, label_options);\n  torch::Tensor counts_final = torch::zeros({N, C, H, W}, label_options);\n\n  dim3 grid = dim3(\n      ((W + 1) / 2 + BLOCK_COLS - 1) / BLOCK_COLS,\n      ((H + 1) / 2 + BLOCK_ROWS - 1) / BLOCK_ROWS);\n  dim3 block = dim3(BLOCK_COLS, BLOCK_ROWS);\n  dim3 grid_count =\n      dim3((W + BLOCK_COLS) / BLOCK_COLS, (H + BLOCK_ROWS) / BLOCK_ROWS);\n  dim3 block_count = dim3(BLOCK_COLS, BLOCK_ROWS);\n  cudaStream_t stream = at::cuda::getCurrentCUDAStream();\n\n  for (int n = 0; n < N; n++) {\n    uint32_t offset = n * H * W;\n\n    cc2d::init_labeling<<<grid, block, 0, stream>>>(\n        labels.data_ptr<int32_t>() + offset, W, H);\n    cc2d::merge<<<grid, block, 0, stream>>>(\n        inputs.data_ptr<uint8_t>() + offset,\n        labels.data_ptr<int32_t>() + offset,\n        W,\n        H);\n    cc2d::compression<<<grid, block, 0, stream>>>(\n        labels.data_ptr<int32_t>() + offset, W, H);\n    cc2d::final_labeling<<<grid, block, 0, stream>>>(\n        inputs.data_ptr<uint8_t>() + offset,\n        labels.data_ptr<int32_t>() + offset,\n        W,\n        H);\n\n    // get the counting of each pixel\n    cc2d::init_counting<<<grid_count, block_count, 0, stream>>>(\n        labels.data_ptr<int32_t>() + offset,\n        counts_init.data_ptr<int32_t>() + offset,\n        W,\n        H);\n    cc2d::final_counting<<<grid_count, block_count, 0, stream>>>(\n        labels.data_ptr<int32_t>() + offset,\n        counts_init.data_ptr<int32_t>() + offset,\n        counts_final.data_ptr<int32_t>() + offset,\n        W,\n        H);\n  }\n\n  // returned values are [labels, counts]\n  std::vector<torch::Tensor> outputs;\n  outputs.push_back(labels);\n  outputs.push_back(counts_final);\n  return outputs;\n}\n\nPYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {\n  m.def(\n      \"get_connected_componnets\",\n      &get_connected_componnets,\n      \"get_connected_componnets\");\n}\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/__init__.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/backbones/__init__.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/backbones/hieradet.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport logging\nfrom functools import partial\nfrom typing import List, Tuple, Union\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom iopath.common.file_io import g_pathmgr\n\nfrom sam2.modeling.backbones.utils import (\n    PatchEmbed,\n    window_partition,\n    window_unpartition,\n)\n\nfrom sam2.modeling.sam2_utils import DropPath, MLP\n\n\ndef do_pool(x: torch.Tensor, pool: nn.Module, norm: nn.Module = None) -> torch.Tensor:\n    if pool is None:\n        return x\n    # (B, H, W, C) -> (B, C, H, W)\n    x = x.permute(0, 3, 1, 2)\n    x = pool(x)\n    # (B, C, H', W') -> (B, H', W', C)\n    x = x.permute(0, 2, 3, 1)\n    if norm:\n        x = norm(x)\n\n    return x\n\n\nclass MultiScaleAttention(nn.Module):\n    def __init__(\n        self,\n        dim: int,\n        dim_out: int,\n        num_heads: int,\n        q_pool: nn.Module = None,\n    ):\n        super().__init__()\n\n        self.dim = dim\n        self.dim_out = dim_out\n        self.num_heads = num_heads\n        self.q_pool = q_pool\n        self.qkv = nn.Linear(dim, dim_out * 3)\n        self.proj = nn.Linear(dim_out, dim_out)\n\n    def forward(self, x: torch.Tensor) -> torch.Tensor:\n        B, H, W, _ = x.shape\n        # qkv with shape (B, H * W, 3, nHead, C)\n        qkv = self.qkv(x).reshape(B, H * W, 3, self.num_heads, -1)\n        # q, k, v with shape (B, H * W, nheads, C)\n        q, k, v = torch.unbind(qkv, 2)\n\n        # Q pooling (for downsample at stage changes)\n        if self.q_pool:\n            q = do_pool(q.reshape(B, H, W, -1), self.q_pool)\n            H, W = q.shape[1:3]  # downsampled shape\n            q = q.reshape(B, H * W, self.num_heads, -1)\n\n        # Torch's SDPA expects [B, nheads, H*W, C] so we transpose\n        x = F.scaled_dot_product_attention(\n            q.transpose(1, 2),\n            k.transpose(1, 2),\n            v.transpose(1, 2),\n        )\n        # Transpose back\n        x = x.transpose(1, 2)\n        x = x.reshape(B, H, W, -1)\n\n        x = self.proj(x)\n\n        return x\n\n\nclass MultiScaleBlock(nn.Module):\n    def __init__(\n        self,\n        dim: int,\n        dim_out: int,\n        num_heads: int,\n        mlp_ratio: float = 4.0,\n        drop_path: float = 0.0,\n        norm_layer: Union[nn.Module, str] = \"LayerNorm\",\n        q_stride: Tuple[int, int] = None,\n        act_layer: nn.Module = nn.GELU,\n        window_size: int = 0,\n    ):\n        super().__init__()\n\n        if isinstance(norm_layer, str):\n            norm_layer = partial(getattr(nn, norm_layer), eps=1e-6)\n\n        self.dim = dim\n        self.dim_out = dim_out\n        self.norm1 = norm_layer(dim)\n\n        self.window_size = window_size\n\n        self.pool, self.q_stride = None, q_stride\n        if self.q_stride:\n            self.pool = nn.MaxPool2d(\n                kernel_size=q_stride, stride=q_stride, ceil_mode=False\n            )\n\n        self.attn = MultiScaleAttention(\n            dim,\n            dim_out,\n            num_heads=num_heads,\n            q_pool=self.pool,\n        )\n        self.drop_path = DropPath(drop_path) if drop_path > 0.0 else nn.Identity()\n\n        self.norm2 = norm_layer(dim_out)\n        self.mlp = MLP(\n            dim_out,\n            int(dim_out * mlp_ratio),\n            dim_out,\n            num_layers=2,\n            activation=act_layer,\n        )\n\n        if dim != dim_out:\n            self.proj = nn.Linear(dim, dim_out)\n\n    def forward(self, x: torch.Tensor) -> torch.Tensor:\n        shortcut = x  # B, H, W, C\n        x = self.norm1(x)\n\n        # Skip connection\n        if self.dim != self.dim_out:\n            shortcut = do_pool(self.proj(x), self.pool)\n\n        # Window partition\n        window_size = self.window_size\n        if window_size > 0:\n            H, W = x.shape[1], x.shape[2]\n            x, pad_hw = window_partition(x, window_size)\n\n        # Window Attention + Q Pooling (if stage change)\n        x = self.attn(x)\n        if self.q_stride:\n            # Shapes have changed due to Q pooling\n            window_size = self.window_size // self.q_stride[0]\n            H, W = shortcut.shape[1:3]\n\n            pad_h = (window_size - H % window_size) % window_size\n            pad_w = (window_size - W % window_size) % window_size\n            pad_hw = (H + pad_h, W + pad_w)\n\n        # Reverse window partition\n        if self.window_size > 0:\n            x = window_unpartition(x, window_size, pad_hw, (H, W))\n\n        x = shortcut + self.drop_path(x)\n        # MLP\n        x = x + self.drop_path(self.mlp(self.norm2(x)))\n        return x\n\n\nclass Hiera(nn.Module):\n    \"\"\"\n    Reference: https://arxiv.org/abs/2306.00989\n    \"\"\"\n\n    def __init__(\n        self,\n        embed_dim: int = 96,  # initial embed dim\n        num_heads: int = 1,  # initial number of heads\n        drop_path_rate: float = 0.0,  # stochastic depth\n        q_pool: int = 3,  # number of q_pool stages\n        q_stride: Tuple[int, int] = (2, 2),  # downsample stride bet. stages\n        stages: Tuple[int, ...] = (2, 3, 16, 3),  # blocks per stage\n        dim_mul: float = 2.0,  # dim_mul factor at stage shift\n        head_mul: float = 2.0,  # head_mul factor at stage shift\n        window_pos_embed_bkg_spatial_size: Tuple[int, int] = (14, 14),\n        # window size per stage, when not using global att.\n        window_spec: Tuple[int, ...] = (\n            8,\n            4,\n            14,\n            7,\n        ),\n        # global attn in these blocks\n        global_att_blocks: Tuple[int, ...] = (\n            12,\n            16,\n            20,\n        ),\n        weights_path=None,\n        return_interm_layers=True,  # return feats from every stage\n    ):\n        super().__init__()\n\n        assert len(stages) == len(window_spec)\n        self.window_spec = window_spec\n\n        depth = sum(stages)\n        self.q_stride = q_stride\n        self.stage_ends = [sum(stages[:i]) - 1 for i in range(1, len(stages) + 1)]\n        assert 0 <= q_pool <= len(self.stage_ends[:-1])\n        self.q_pool_blocks = [x + 1 for x in self.stage_ends[:-1]][:q_pool]\n        self.return_interm_layers = return_interm_layers\n\n        self.patch_embed = PatchEmbed(\n            embed_dim=embed_dim,\n        )\n        # Which blocks have global att?\n        self.global_att_blocks = global_att_blocks\n\n        # Windowed positional embedding (https://arxiv.org/abs/2311.05613)\n        self.window_pos_embed_bkg_spatial_size = window_pos_embed_bkg_spatial_size\n        self.pos_embed = nn.Parameter(\n            torch.zeros(1, embed_dim, *self.window_pos_embed_bkg_spatial_size)\n        )\n        self.pos_embed_window = nn.Parameter(\n            torch.zeros(1, embed_dim, self.window_spec[0], self.window_spec[0])\n        )\n\n        dpr = [\n            x.item() for x in torch.linspace(0, drop_path_rate, depth)\n        ]  # stochastic depth decay rule\n\n        cur_stage = 1\n        self.blocks = nn.ModuleList()\n\n        for i in range(depth):\n            dim_out = embed_dim\n            # lags by a block, so first block of\n            # next stage uses an initial window size\n            # of previous stage and final window size of current stage\n            window_size = self.window_spec[cur_stage - 1]\n\n            if self.global_att_blocks is not None:\n                window_size = 0 if i in self.global_att_blocks else window_size\n\n            if i - 1 in self.stage_ends:\n                dim_out = int(embed_dim * dim_mul)\n                num_heads = int(num_heads * head_mul)\n                cur_stage += 1\n\n            block = MultiScaleBlock(\n                dim=embed_dim,\n                dim_out=dim_out,\n                num_heads=num_heads,\n                drop_path=dpr[i],\n                q_stride=self.q_stride if i in self.q_pool_blocks else None,\n                window_size=window_size,\n            )\n\n            embed_dim = dim_out\n            self.blocks.append(block)\n\n        self.channel_list = (\n            [self.blocks[i].dim_out for i in self.stage_ends[::-1]]\n            if return_interm_layers\n            else [self.blocks[-1].dim_out]\n        )\n\n        if weights_path is not None:\n            with g_pathmgr.open(weights_path, \"rb\") as f:\n                chkpt = torch.load(f, map_location=\"cpu\")\n            logging.info(\"loading Hiera\", self.load_state_dict(chkpt, strict=False))\n\n    def _get_pos_embed(self, hw: Tuple[int, int]) -> torch.Tensor:\n        h, w = hw\n        window_embed = self.pos_embed_window\n        pos_embed = F.interpolate(self.pos_embed, size=(h, w), mode=\"bicubic\")\n        pos_embed = pos_embed + window_embed.tile(\n            [x // y for x, y in zip(pos_embed.shape, window_embed.shape)]\n        )\n        pos_embed = pos_embed.permute(0, 2, 3, 1)\n        return pos_embed\n\n    def forward(self, x: torch.Tensor) -> List[torch.Tensor]:\n        x = self.patch_embed(x)\n        # x: (B, H, W, C)\n\n        # Add pos embed\n        x = x + self._get_pos_embed(x.shape[1:3])\n\n        outputs = []\n        for i, blk in enumerate(self.blocks):\n            x = blk(x)\n            if (i == self.stage_ends[-1]) or (\n                i in self.stage_ends and self.return_interm_layers\n            ):\n                feats = x.permute(0, 3, 1, 2)\n                outputs.append(feats)\n\n        return outputs\n\n    def get_layer_id(self, layer_name):\n        # https://github.com/microsoft/unilm/blob/master/beit/optim_factory.py#L33\n        num_layers = self.get_num_layers()\n\n        if layer_name.find(\"rel_pos\") != -1:\n            return num_layers + 1\n        elif layer_name.find(\"pos_embed\") != -1:\n            return 0\n        elif layer_name.find(\"patch_embed\") != -1:\n            return 0\n        elif layer_name.find(\"blocks\") != -1:\n            return int(layer_name.split(\"blocks\")[1].split(\".\")[1]) + 1\n        else:\n            return num_layers + 1\n\n    def get_num_layers(self) -> int:\n        return len(self.blocks)\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/backbones/image_encoder.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom typing import List, Optional\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass ImageEncoder(nn.Module):\n    def __init__(\n        self,\n        trunk: nn.Module,\n        neck: nn.Module,\n        scalp: int = 0,\n    ):\n        super().__init__()\n        self.trunk = trunk\n        self.neck = neck\n        self.scalp = scalp\n        assert (\n            self.trunk.channel_list == self.neck.backbone_channel_list\n        ), f\"Channel dims of trunk and neck do not match. Trunk: {self.trunk.channel_list}, neck: {self.neck.backbone_channel_list}\"\n\n    def forward(self, sample: torch.Tensor):\n        # Forward through backbone\n        features, pos = self.neck(self.trunk(sample))\n        if self.scalp > 0:\n            # Discard the lowest resolution features\n            features, pos = features[: -self.scalp], pos[: -self.scalp]\n\n        src = features[-1]\n        output = {\n            \"vision_features\": src,\n            \"vision_pos_enc\": pos,\n            \"backbone_fpn\": features,\n        }\n        return output\n\n\nclass FpnNeck(nn.Module):\n    \"\"\"\n    A modified variant of Feature Pyramid Network (FPN) neck\n    (we remove output conv and also do bicubic interpolation similar to ViT\n    pos embed interpolation)\n    \"\"\"\n\n    def __init__(\n        self,\n        position_encoding: nn.Module,\n        d_model: int,\n        backbone_channel_list: List[int],\n        kernel_size: int = 1,\n        stride: int = 1,\n        padding: int = 0,\n        fpn_interp_model: str = \"bilinear\",\n        fuse_type: str = \"sum\",\n        fpn_top_down_levels: Optional[List[int]] = None,\n    ):\n        \"\"\"Initialize the neck\n        :param trunk: the backbone\n        :param position_encoding: the positional encoding to use\n        :param d_model: the dimension of the model\n        :param neck_norm: the normalization to use\n        \"\"\"\n        super().__init__()\n        self.position_encoding = position_encoding\n        self.convs = nn.ModuleList()\n        self.backbone_channel_list = backbone_channel_list\n        self.d_model = d_model\n        for dim in backbone_channel_list:\n            current = nn.Sequential()\n            current.add_module(\n                \"conv\",\n                nn.Conv2d(\n                    in_channels=dim,\n                    out_channels=d_model,\n                    kernel_size=kernel_size,\n                    stride=stride,\n                    padding=padding,\n                ),\n            )\n\n            self.convs.append(current)\n        self.fpn_interp_model = fpn_interp_model\n        assert fuse_type in [\"sum\", \"avg\"]\n        self.fuse_type = fuse_type\n\n        # levels to have top-down features in its outputs\n        # e.g. if fpn_top_down_levels is [2, 3], then only outputs of level 2 and 3\n        # have top-down propagation, while outputs of level 0 and level 1 have only\n        # lateral features from the same backbone level.\n        if fpn_top_down_levels is None:\n            # default is to have top-down features on all levels\n            fpn_top_down_levels = range(len(self.convs))\n        self.fpn_top_down_levels = list(fpn_top_down_levels)\n\n    def forward(self, xs: List[torch.Tensor]):\n\n        out = [None] * len(self.convs)\n        pos = [None] * len(self.convs)\n        assert len(xs) == len(self.convs)\n        # fpn forward pass\n        # see https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/backbone/fpn.py\n        prev_features = None\n        # forward in top-down order (from low to high resolution)\n        n = len(self.convs) - 1\n        for i in range(n, -1, -1):\n            x = xs[i]\n            lateral_features = self.convs[n - i](x)\n            if i in self.fpn_top_down_levels and prev_features is not None:\n                top_down_features = F.interpolate(\n                    prev_features.to(dtype=torch.float32),\n                    scale_factor=2.0,\n                    mode=self.fpn_interp_model,\n                    align_corners=(\n                        None if self.fpn_interp_model == \"nearest\" else False\n                    ),\n                    antialias=False,\n                )\n                prev_features = lateral_features + top_down_features\n                if self.fuse_type == \"avg\":\n                    prev_features /= 2\n            else:\n                prev_features = lateral_features\n            x_out = prev_features\n            out[i] = x_out\n            pos[i] = self.position_encoding(x_out).to(x_out.dtype)\n\n        return out, pos\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/backbones/utils.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\n\"\"\"Some utilities for backbones, in particular for windowing\"\"\"\n\nfrom typing import Tuple\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef window_partition(x, window_size):\n    \"\"\"\n    Partition into non-overlapping windows with padding if needed.\n    Args:\n        x (tensor): input tokens with [B, H, W, C].\n        window_size (int): window size.\n    Returns:\n        windows: windows after partition with [B * num_windows, window_size, window_size, C].\n        (Hp, Wp): padded height and width before partition\n    \"\"\"\n    B, H, W, C = x.shape\n\n    pad_h = (window_size - H % window_size) % window_size\n    pad_w = (window_size - W % window_size) % window_size\n    if pad_h > 0 or pad_w > 0:\n        x = F.pad(x, (0, 0, 0, pad_w, 0, pad_h))\n    Hp, Wp = H + pad_h, W + pad_w\n\n    x = x.view(B, Hp // window_size, window_size, Wp // window_size, window_size, C)\n    windows = (\n        x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, window_size, window_size, C)\n    )\n    return windows, (Hp, Wp)\n\n\ndef window_unpartition(windows, window_size, pad_hw, hw):\n    \"\"\"\n    Window unpartition into original sequences and removing padding.\n    Args:\n        x (tensor): input tokens with [B * num_windows, window_size, window_size, C].\n        window_size (int): window size.\n        pad_hw (Tuple): padded height and width (Hp, Wp).\n        hw (Tuple): original height and width (H, W) before padding.\n    Returns:\n        x: unpartitioned sequences with [B, H, W, C].\n    \"\"\"\n    Hp, Wp = pad_hw\n    H, W = hw\n    B = windows.shape[0] // (Hp * Wp // window_size // window_size)\n    x = windows.view(\n        B, Hp // window_size, Wp // window_size, window_size, window_size, -1\n    )\n    x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, Hp, Wp, -1)\n\n    if Hp > H or Wp > W:\n        x = x[:, :H, :W, :].contiguous()\n    return x\n\n\nclass PatchEmbed(nn.Module):\n    \"\"\"\n    Image to Patch Embedding.\n    \"\"\"\n\n    def __init__(\n        self,\n        kernel_size: Tuple[int, ...] = (7, 7),\n        stride: Tuple[int, ...] = (4, 4),\n        padding: Tuple[int, ...] = (3, 3),\n        in_chans: int = 3,\n        embed_dim: int = 768,\n    ):\n        \"\"\"\n        Args:\n            kernel_size (Tuple): kernel size of the projection layer.\n            stride (Tuple): stride of the projection layer.\n            padding (Tuple): padding size of the projection layer.\n            in_chans (int): Number of input image channels.\n            embed_dim (int):  embed_dim (int): Patch embedding dimension.\n        \"\"\"\n        super().__init__()\n        self.proj = nn.Conv2d(\n            in_chans, embed_dim, kernel_size=kernel_size, stride=stride, padding=padding\n        )\n\n    def forward(self, x: torch.Tensor) -> torch.Tensor:\n        x = self.proj(x)\n        # B C H W -> B H W C\n        x = x.permute(0, 2, 3, 1)\n        return x\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/memory_attention.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom typing import Optional\n\nimport torch\nfrom torch import nn, Tensor\n\nfrom sam2.modeling.sam.transformer import RoPEAttention\n\nfrom sam2.modeling.sam2_utils import get_activation_fn, get_clones\n\n\nclass MemoryAttentionLayer(nn.Module):\n\n    def __init__(\n        self,\n        activation: str,\n        cross_attention: nn.Module,\n        d_model: int,\n        dim_feedforward: int,\n        dropout: float,\n        pos_enc_at_attn: bool,\n        pos_enc_at_cross_attn_keys: bool,\n        pos_enc_at_cross_attn_queries: bool,\n        self_attention: nn.Module,\n    ):\n        super().__init__()\n        self.d_model = d_model\n        self.dim_feedforward = dim_feedforward\n        self.dropout_value = dropout\n        self.self_attn = self_attention\n        self.cross_attn_image = cross_attention\n\n        # Implementation of Feedforward model\n        self.linear1 = nn.Linear(d_model, dim_feedforward)\n        self.dropout = nn.Dropout(dropout)\n        self.linear2 = nn.Linear(dim_feedforward, d_model)\n\n        self.norm1 = nn.LayerNorm(d_model)\n        self.norm2 = nn.LayerNorm(d_model)\n        self.norm3 = nn.LayerNorm(d_model)\n        self.dropout1 = nn.Dropout(dropout)\n        self.dropout2 = nn.Dropout(dropout)\n        self.dropout3 = nn.Dropout(dropout)\n\n        self.activation_str = activation\n        self.activation = get_activation_fn(activation)\n\n        # Where to add pos enc\n        self.pos_enc_at_attn = pos_enc_at_attn\n        self.pos_enc_at_cross_attn_queries = pos_enc_at_cross_attn_queries\n        self.pos_enc_at_cross_attn_keys = pos_enc_at_cross_attn_keys\n\n    def _forward_sa(self, tgt, query_pos):\n        # Self-Attention\n        tgt2 = self.norm1(tgt)\n        q = k = tgt2 + query_pos if self.pos_enc_at_attn else tgt2\n        tgt2 = self.self_attn(q, k, v=tgt2)\n        tgt = tgt + self.dropout1(tgt2)\n        return tgt\n\n    def _forward_ca(self, tgt, memory, query_pos, pos, num_k_exclude_rope=0):\n        kwds = {}\n        if num_k_exclude_rope > 0:\n            assert isinstance(self.cross_attn_image, RoPEAttention)\n            kwds = {\"num_k_exclude_rope\": num_k_exclude_rope}\n\n        # Cross-Attention\n        tgt2 = self.norm2(tgt)\n        tgt2 = self.cross_attn_image(\n            q=tgt2 + query_pos if self.pos_enc_at_cross_attn_queries else tgt2,\n            k=memory + pos if self.pos_enc_at_cross_attn_keys else memory,\n            v=memory,\n            **kwds,\n        )\n        tgt = tgt + self.dropout2(tgt2)\n        return tgt\n\n    def forward(\n        self,\n        tgt,\n        memory,\n        pos: Optional[Tensor] = None,\n        query_pos: Optional[Tensor] = None,\n        num_k_exclude_rope: int = 0,\n    ) -> torch.Tensor:\n\n        # Self-Attn, Cross-Attn\n        tgt = self._forward_sa(tgt, query_pos)\n        tgt = self._forward_ca(tgt, memory, query_pos, pos, num_k_exclude_rope)\n        # MLP\n        tgt2 = self.norm3(tgt)\n        tgt2 = self.linear2(self.dropout(self.activation(self.linear1(tgt2))))\n        tgt = tgt + self.dropout3(tgt2)\n        return tgt\n\n\nclass MemoryAttention(nn.Module):\n    def __init__(\n        self,\n        d_model: int,\n        pos_enc_at_input: bool,\n        layer: nn.Module,\n        num_layers: int,\n        batch_first: bool = True,  # Do layers expect batch first input?\n    ):\n        super().__init__()\n        self.d_model = d_model\n        self.layers = get_clones(layer, num_layers)\n        self.num_layers = num_layers\n        self.norm = nn.LayerNorm(d_model)\n        self.pos_enc_at_input = pos_enc_at_input\n        self.batch_first = batch_first\n\n    def forward(\n        self,\n        curr: torch.Tensor,  # self-attention inputs\n        memory: torch.Tensor,  # cross-attention inputs\n        curr_pos: Optional[Tensor] = None,  # pos_enc for self-attention inputs\n        memory_pos: Optional[Tensor] = None,  # pos_enc for cross-attention inputs\n        num_obj_ptr_tokens: int = 0,  # number of object pointer *tokens*\n    ):\n        if isinstance(curr, list):\n            assert isinstance(curr_pos, list)\n            assert len(curr) == len(curr_pos) == 1\n            curr, curr_pos = (\n                curr[0],\n                curr_pos[0],\n            )\n\n        assert (\n            curr.shape[1] == memory.shape[1]\n        ), \"Batch size must be the same for curr and memory\"\n\n        output = curr\n        if self.pos_enc_at_input and curr_pos is not None:\n            output = output + 0.1 * curr_pos\n\n        if self.batch_first:\n            # Convert to batch first\n            output = output.transpose(0, 1)\n            curr_pos = curr_pos.transpose(0, 1)\n            memory = memory.transpose(0, 1)\n            memory_pos = memory_pos.transpose(0, 1)\n\n        for layer in self.layers:\n            kwds = {}\n            if isinstance(layer.cross_attn_image, RoPEAttention):\n                kwds = {\"num_k_exclude_rope\": num_obj_ptr_tokens}\n\n            output = layer(\n                tgt=output,\n                memory=memory,\n                pos=memory_pos,\n                query_pos=curr_pos,\n                **kwds,\n            )\n        normed_output = self.norm(output)\n\n        if self.batch_first:\n            # Convert back to seq first\n            normed_output = normed_output.transpose(0, 1)\n            curr_pos = curr_pos.transpose(0, 1)\n\n        return normed_output\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/memory_encoder.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport math\nfrom typing import Tuple\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom sam2.modeling.sam2_utils import DropPath, get_clones, LayerNorm2d\n\n\nclass MaskDownSampler(nn.Module):\n    \"\"\"\n    Progressively downsample a mask by total_stride, each time by stride.\n    Note that LayerNorm is applied per *token*, like in ViT.\n\n    With each downsample (by a factor stride**2), channel capacity increases by the same factor.\n    In the end, we linearly project to embed_dim channels.\n    \"\"\"\n\n    def __init__(\n        self,\n        embed_dim=256,\n        kernel_size=4,\n        stride=4,\n        padding=0,\n        total_stride=16,\n        activation=nn.GELU,\n    ):\n        super().__init__()\n        num_layers = int(math.log2(total_stride) // math.log2(stride))\n        assert stride**num_layers == total_stride\n        self.encoder = nn.Sequential()\n        mask_in_chans, mask_out_chans = 1, 1\n        for _ in range(num_layers):\n            mask_out_chans = mask_in_chans * (stride**2)\n            self.encoder.append(\n                nn.Conv2d(\n                    mask_in_chans,\n                    mask_out_chans,\n                    kernel_size=kernel_size,\n                    stride=stride,\n                    padding=padding,\n                )\n            )\n            self.encoder.append(LayerNorm2d(mask_out_chans))\n            self.encoder.append(activation())\n            mask_in_chans = mask_out_chans\n\n        self.encoder.append(nn.Conv2d(mask_out_chans, embed_dim, kernel_size=1))\n\n    def forward(self, x):\n        return self.encoder(x)\n\n\n# Lightly adapted from ConvNext (https://github.com/facebookresearch/ConvNeXt)\nclass CXBlock(nn.Module):\n    r\"\"\"ConvNeXt Block. There are two equivalent implementations:\n    (1) DwConv -> LayerNorm (channels_first) -> 1x1 Conv -> GELU -> 1x1 Conv; all in (N, C, H, W)\n    (2) DwConv -> Permute to (N, H, W, C); LayerNorm (channels_last) -> Linear -> GELU -> Linear; Permute back\n    We use (2) as we find it slightly faster in PyTorch\n\n    Args:\n        dim (int): Number of input channels.\n        drop_path (float): Stochastic depth rate. Default: 0.0\n        layer_scale_init_value (float): Init value for Layer Scale. Default: 1e-6.\n    \"\"\"\n\n    def __init__(\n        self,\n        dim,\n        kernel_size=7,\n        padding=3,\n        drop_path=0.0,\n        layer_scale_init_value=1e-6,\n        use_dwconv=True,\n    ):\n        super().__init__()\n        self.dwconv = nn.Conv2d(\n            dim,\n            dim,\n            kernel_size=kernel_size,\n            padding=padding,\n            groups=dim if use_dwconv else 1,\n        )  # depthwise conv\n        self.norm = LayerNorm2d(dim, eps=1e-6)\n        self.pwconv1 = nn.Linear(\n            dim, 4 * dim\n        )  # pointwise/1x1 convs, implemented with linear layers\n        self.act = nn.GELU()\n        self.pwconv2 = nn.Linear(4 * dim, dim)\n        self.gamma = (\n            nn.Parameter(layer_scale_init_value * torch.ones((dim)), requires_grad=True)\n            if layer_scale_init_value > 0\n            else None\n        )\n        self.drop_path = DropPath(drop_path) if drop_path > 0.0 else nn.Identity()\n\n    def forward(self, x):\n        input = x\n        x = self.dwconv(x)\n        x = self.norm(x)\n        x = x.permute(0, 2, 3, 1)  # (N, C, H, W) -> (N, H, W, C)\n        x = self.pwconv1(x)\n        x = self.act(x)\n        x = self.pwconv2(x)\n        if self.gamma is not None:\n            x = self.gamma * x\n        x = x.permute(0, 3, 1, 2)  # (N, H, W, C) -> (N, C, H, W)\n\n        x = input + self.drop_path(x)\n        return x\n\n\nclass Fuser(nn.Module):\n    def __init__(self, layer, num_layers, dim=None, input_projection=False):\n        super().__init__()\n        self.proj = nn.Identity()\n        self.layers = get_clones(layer, num_layers)\n\n        if input_projection:\n            assert dim is not None\n            self.proj = nn.Conv2d(dim, dim, kernel_size=1)\n\n    def forward(self, x):\n        # normally x: (N, C, H, W)\n        x = self.proj(x)\n        for layer in self.layers:\n            x = layer(x)\n        return x\n\n\nclass MemoryEncoder(nn.Module):\n    def __init__(\n        self,\n        out_dim,\n        mask_downsampler,\n        fuser,\n        position_encoding,\n        in_dim=256,  # in_dim of pix_feats\n    ):\n        super().__init__()\n\n        self.mask_downsampler = mask_downsampler\n\n        self.pix_feat_proj = nn.Conv2d(in_dim, in_dim, kernel_size=1)\n        self.fuser = fuser\n        self.position_encoding = position_encoding\n        self.out_proj = nn.Identity()\n        if out_dim != in_dim:\n            self.out_proj = nn.Conv2d(in_dim, out_dim, kernel_size=1)\n\n    def forward(\n        self,\n        pix_feat: torch.Tensor,\n        masks: torch.Tensor,\n        skip_mask_sigmoid: bool = False,\n    ) -> Tuple[torch.Tensor, torch.Tensor]:\n        ## Process masks\n        # sigmoid, so that less domain shift from gt masks which are bool\n        if not skip_mask_sigmoid:\n            masks = F.sigmoid(masks)\n        masks = self.mask_downsampler(masks)\n\n        ## Fuse pix_feats and downsampled masks\n        # in case the visual features are on CPU, cast them to CUDA\n        pix_feat = pix_feat.to(masks.device)\n\n        x = self.pix_feat_proj(pix_feat)\n        x = x + masks\n        x = self.fuser(x)\n        x = self.out_proj(x)\n\n        pos = self.position_encoding(x).to(x.dtype)\n\n        return {\"vision_features\": x, \"vision_pos_enc\": [pos]}\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/position_encoding.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport math\nfrom typing import Any, Optional, Tuple\n\nimport numpy as np\n\nimport torch\nfrom torch import nn\n\n\nclass PositionEmbeddingSine(nn.Module):\n    \"\"\"\n    This is a more standard version of the position embedding, very similar to the one\n    used by the Attention Is All You Need paper, generalized to work on images.\n    \"\"\"\n\n    def __init__(\n        self,\n        num_pos_feats,\n        temperature: int = 10000,\n        normalize: bool = True,\n        scale: Optional[float] = None,\n    ):\n        super().__init__()\n        assert num_pos_feats % 2 == 0, \"Expecting even model width\"\n        self.num_pos_feats = num_pos_feats // 2\n        self.temperature = temperature\n        self.normalize = normalize\n        if scale is not None and normalize is False:\n            raise ValueError(\"normalize should be True if scale is passed\")\n        if scale is None:\n            scale = 2 * math.pi\n        self.scale = scale\n\n        self.cache = {}\n\n    def _encode_xy(self, x, y):\n        # The positions are expected to be normalized\n        assert len(x) == len(y) and x.ndim == y.ndim == 1\n        x_embed = x * self.scale\n        y_embed = y * self.scale\n\n        dim_t = torch.arange(self.num_pos_feats, dtype=torch.float32, device=x.device)\n        dim_t = self.temperature ** (2 * (dim_t // 2) / self.num_pos_feats)\n\n        pos_x = x_embed[:, None] / dim_t\n        pos_y = y_embed[:, None] / dim_t\n        pos_x = torch.stack(\n            (pos_x[:, 0::2].sin(), pos_x[:, 1::2].cos()), dim=2\n        ).flatten(1)\n        pos_y = torch.stack(\n            (pos_y[:, 0::2].sin(), pos_y[:, 1::2].cos()), dim=2\n        ).flatten(1)\n        return pos_x, pos_y\n\n    @torch.no_grad()\n    def encode_boxes(self, x, y, w, h):\n        pos_x, pos_y = self._encode_xy(x, y)\n        pos = torch.cat((pos_y, pos_x, h[:, None], w[:, None]), dim=1)\n        return pos\n\n    encode = encode_boxes  # Backwards compatibility\n\n    @torch.no_grad()\n    def encode_points(self, x, y, labels):\n        (bx, nx), (by, ny), (bl, nl) = x.shape, y.shape, labels.shape\n        assert bx == by and nx == ny and bx == bl and nx == nl\n        pos_x, pos_y = self._encode_xy(x.flatten(), y.flatten())\n        pos_x, pos_y = pos_x.reshape(bx, nx, -1), pos_y.reshape(by, ny, -1)\n        pos = torch.cat((pos_y, pos_x, labels[:, :, None]), dim=2)\n        return pos\n\n    @torch.no_grad()\n    def forward(self, x: torch.Tensor):\n        cache_key = (x.shape[-2], x.shape[-1])\n        if cache_key in self.cache:\n            return self.cache[cache_key][None].repeat(x.shape[0], 1, 1, 1)\n        y_embed = (\n            torch.arange(1, x.shape[-2] + 1, dtype=torch.float32, device=x.device)\n            .view(1, -1, 1)\n            .repeat(x.shape[0], 1, x.shape[-1])\n        )\n        x_embed = (\n            torch.arange(1, x.shape[-1] + 1, dtype=torch.float32, device=x.device)\n            .view(1, 1, -1)\n            .repeat(x.shape[0], x.shape[-2], 1)\n        )\n\n        if self.normalize:\n            eps = 1e-6\n            y_embed = y_embed / (y_embed[:, -1:, :] + eps) * self.scale\n            x_embed = x_embed / (x_embed[:, :, -1:] + eps) * self.scale\n\n        dim_t = torch.arange(self.num_pos_feats, dtype=torch.float32, device=x.device)\n        dim_t = self.temperature ** (2 * (dim_t // 2) / self.num_pos_feats)\n\n        pos_x = x_embed[:, :, :, None] / dim_t\n        pos_y = y_embed[:, :, :, None] / dim_t\n        pos_x = torch.stack(\n            (pos_x[:, :, :, 0::2].sin(), pos_x[:, :, :, 1::2].cos()), dim=4\n        ).flatten(3)\n        pos_y = torch.stack(\n            (pos_y[:, :, :, 0::2].sin(), pos_y[:, :, :, 1::2].cos()), dim=4\n        ).flatten(3)\n        pos = torch.cat((pos_y, pos_x), dim=3).permute(0, 3, 1, 2)\n        self.cache[cache_key] = pos[0]\n        return pos\n\n\nclass PositionEmbeddingRandom(nn.Module):\n    \"\"\"\n    Positional encoding using random spatial frequencies.\n    \"\"\"\n\n    def __init__(self, num_pos_feats: int = 64, scale: Optional[float] = None) -> None:\n        super().__init__()\n        if scale is None or scale <= 0.0:\n            scale = 1.0\n        self.register_buffer(\n            \"positional_encoding_gaussian_matrix\",\n            scale * torch.randn((2, num_pos_feats)),\n        )\n\n    def _pe_encoding(self, coords: torch.Tensor) -> torch.Tensor:\n        \"\"\"Positionally encode points that are normalized to [0,1].\"\"\"\n        # assuming coords are in [0, 1]^2 square and have d_1 x ... x d_n x 2 shape\n        coords = 2 * coords - 1\n        coords = coords @ self.positional_encoding_gaussian_matrix\n        coords = 2 * np.pi * coords\n        # outputs d_1 x ... x d_n x C shape\n        return torch.cat([torch.sin(coords), torch.cos(coords)], dim=-1)\n\n    def forward(self, size: Tuple[int, int]) -> torch.Tensor:\n        \"\"\"Generate positional encoding for a grid of the specified size.\"\"\"\n        h, w = size\n        device: Any = self.positional_encoding_gaussian_matrix.device\n        grid = torch.ones((h, w), device=device, dtype=torch.float32)\n        y_embed = grid.cumsum(dim=0) - 0.5\n        x_embed = grid.cumsum(dim=1) - 0.5\n        y_embed = y_embed / h\n        x_embed = x_embed / w\n\n        pe = self._pe_encoding(torch.stack([x_embed, y_embed], dim=-1))\n        return pe.permute(2, 0, 1)  # C x H x W\n\n    def forward_with_coords(\n        self, coords_input: torch.Tensor, image_size: Tuple[int, int]\n    ) -> torch.Tensor:\n        \"\"\"Positionally encode points that are not normalized to [0,1].\"\"\"\n        coords = coords_input.clone()\n        coords[:, :, 0] = coords[:, :, 0] / image_size[1]\n        coords[:, :, 1] = coords[:, :, 1] / image_size[0]\n        return self._pe_encoding(coords.to(torch.float))  # B x N x C\n\n\n# Rotary Positional Encoding, adapted from:\n# 1. https://github.com/meta-llama/codellama/blob/main/llama/model.py\n# 2. https://github.com/naver-ai/rope-vit\n# 3. https://github.com/lucidrains/rotary-embedding-torch\n\n\ndef init_t_xy(end_x: int, end_y: int):\n    t = torch.arange(end_x * end_y, dtype=torch.float32)\n    t_x = (t % end_x).float()\n    t_y = torch.div(t, end_x, rounding_mode=\"floor\").float()\n    return t_x, t_y\n\n\ndef compute_axial_cis(dim: int, end_x: int, end_y: int, theta: float = 10000.0):\n    freqs_x = 1.0 / (theta ** (torch.arange(0, dim, 4)[: (dim // 4)].float() / dim))\n    freqs_y = 1.0 / (theta ** (torch.arange(0, dim, 4)[: (dim // 4)].float() / dim))\n\n    t_x, t_y = init_t_xy(end_x, end_y)\n    freqs_x = torch.outer(t_x, freqs_x)\n    freqs_y = torch.outer(t_y, freqs_y)\n    freqs_cis_x = torch.polar(torch.ones_like(freqs_x), freqs_x)\n    freqs_cis_y = torch.polar(torch.ones_like(freqs_y), freqs_y)\n    return torch.cat([freqs_cis_x, freqs_cis_y], dim=-1)\n\n\ndef reshape_for_broadcast(freqs_cis: torch.Tensor, x: torch.Tensor):\n    ndim = x.ndim\n    assert 0 <= 1 < ndim\n    assert freqs_cis.shape == (x.shape[-2], x.shape[-1])\n    shape = [d if i >= ndim - 2 else 1 for i, d in enumerate(x.shape)]\n    return freqs_cis.view(*shape)\n\n\ndef apply_rotary_enc(\n    xq: torch.Tensor,\n    xk: torch.Tensor,\n    freqs_cis: torch.Tensor,\n    repeat_freqs_k: bool = False,\n):\n    xq_ = torch.view_as_complex(xq.float().reshape(*xq.shape[:-1], -1, 2))\n    xk_ = (\n        torch.view_as_complex(xk.float().reshape(*xk.shape[:-1], -1, 2))\n        if xk.shape[-2] != 0\n        else None\n    )\n    freqs_cis = reshape_for_broadcast(freqs_cis, xq_)\n    xq_out = torch.view_as_real(xq_ * freqs_cis).flatten(3)\n    if xk_ is None:\n        # no keys to rotate, due to dropout\n        return xq_out.type_as(xq).to(xq.device), xk\n    # repeat freqs along seq_len dim to match k seq_len\n    if repeat_freqs_k:\n        r = xk_.shape[-2] // xq_.shape[-2]\n        if freqs_cis.is_cuda:\n            freqs_cis = freqs_cis.repeat(*([1] * (freqs_cis.ndim - 2)), r, 1)\n        else:\n            # torch.repeat on complex numbers may not be supported on non-CUDA devices\n            # (freqs_cis has 4 dims and we repeat on dim 2) so we use expand + flatten\n            freqs_cis = freqs_cis.unsqueeze(2).expand(-1, -1, r, -1, -1).flatten(2, 3)\n    xk_out = torch.view_as_real(xk_ * freqs_cis).flatten(3)\n    return xq_out.type_as(xq).to(xq.device), xk_out.type_as(xk).to(xk.device)\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/sam/__init__.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/sam/mask_decoder.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom typing import List, Optional, Tuple, Type\n\nimport torch\nfrom torch import nn\n\nfrom sam2.modeling.sam2_utils import LayerNorm2d, MLP\n\n\nclass MaskDecoder(nn.Module):\n    def __init__(\n        self,\n        *,\n        transformer_dim: int,\n        transformer: nn.Module,\n        num_multimask_outputs: int = 3,\n        activation: Type[nn.Module] = nn.GELU,\n        iou_head_depth: int = 3,\n        iou_head_hidden_dim: int = 256,\n        use_high_res_features: bool = False,\n        iou_prediction_use_sigmoid=False,\n        dynamic_multimask_via_stability=False,\n        dynamic_multimask_stability_delta=0.05,\n        dynamic_multimask_stability_thresh=0.98,\n        pred_obj_scores: bool = False,\n        pred_obj_scores_mlp: bool = False,\n        use_multimask_token_for_obj_ptr: bool = False,\n    ) -> None:\n        \"\"\"\n        Predicts masks given an image and prompt embeddings, using a\n        transformer architecture.\n\n        Arguments:\n          transformer_dim (int): the channel dimension of the transformer\n          transformer (nn.Module): the transformer used to predict masks\n          num_multimask_outputs (int): the number of masks to predict\n            when disambiguating masks\n          activation (nn.Module): the type of activation to use when\n            upscaling masks\n          iou_head_depth (int): the depth of the MLP used to predict\n            mask quality\n          iou_head_hidden_dim (int): the hidden dimension of the MLP\n            used to predict mask quality\n        \"\"\"\n        super().__init__()\n        self.transformer_dim = transformer_dim\n        self.transformer = transformer\n\n        self.num_multimask_outputs = num_multimask_outputs\n\n        self.iou_token = nn.Embedding(1, transformer_dim)\n        self.num_mask_tokens = num_multimask_outputs + 1\n        self.mask_tokens = nn.Embedding(self.num_mask_tokens, transformer_dim)\n\n        self.pred_obj_scores = pred_obj_scores\n        if self.pred_obj_scores:\n            self.obj_score_token = nn.Embedding(1, transformer_dim)\n        self.use_multimask_token_for_obj_ptr = use_multimask_token_for_obj_ptr\n\n        self.output_upscaling = nn.Sequential(\n            nn.ConvTranspose2d(\n                transformer_dim, transformer_dim // 4, kernel_size=2, stride=2\n            ),\n            LayerNorm2d(transformer_dim // 4),\n            activation(),\n            nn.ConvTranspose2d(\n                transformer_dim // 4, transformer_dim // 8, kernel_size=2, stride=2\n            ),\n            activation(),\n        )\n        self.use_high_res_features = use_high_res_features\n        if use_high_res_features:\n            self.conv_s0 = nn.Conv2d(\n                transformer_dim, transformer_dim // 8, kernel_size=1, stride=1\n            )\n            self.conv_s1 = nn.Conv2d(\n                transformer_dim, transformer_dim // 4, kernel_size=1, stride=1\n            )\n\n        self.output_hypernetworks_mlps = nn.ModuleList(\n            [\n                MLP(transformer_dim, transformer_dim, transformer_dim // 8, 3)\n                for i in range(self.num_mask_tokens)\n            ]\n        )\n\n        self.iou_prediction_head = MLP(\n            transformer_dim,\n            iou_head_hidden_dim,\n            self.num_mask_tokens,\n            iou_head_depth,\n            sigmoid_output=iou_prediction_use_sigmoid,\n        )\n        if self.pred_obj_scores:\n            self.pred_obj_score_head = nn.Linear(transformer_dim, 1)\n            if pred_obj_scores_mlp:\n                self.pred_obj_score_head = MLP(transformer_dim, transformer_dim, 1, 3)\n\n        # When outputting a single mask, optionally we can dynamically fall back to the best\n        # multimask output token if the single mask output token gives low stability scores.\n        self.dynamic_multimask_via_stability = dynamic_multimask_via_stability\n        self.dynamic_multimask_stability_delta = dynamic_multimask_stability_delta\n        self.dynamic_multimask_stability_thresh = dynamic_multimask_stability_thresh\n\n    def forward(\n        self,\n        image_embeddings: torch.Tensor,\n        image_pe: torch.Tensor,\n        sparse_prompt_embeddings: torch.Tensor,\n        dense_prompt_embeddings: torch.Tensor,\n        multimask_output: bool,\n        repeat_image: bool,\n        high_res_features: Optional[List[torch.Tensor]] = None,\n    ) -> Tuple[torch.Tensor, torch.Tensor]:\n        \"\"\"\n        Predict masks given image and prompt embeddings.\n\n        Arguments:\n          image_embeddings (torch.Tensor): the embeddings from the image encoder\n          image_pe (torch.Tensor): positional encoding with the shape of image_embeddings\n          sparse_prompt_embeddings (torch.Tensor): the embeddings of the points and boxes\n          dense_prompt_embeddings (torch.Tensor): the embeddings of the mask inputs\n          multimask_output (bool): Whether to return multiple masks or a single\n            mask.\n\n        Returns:\n          torch.Tensor: batched predicted masks\n          torch.Tensor: batched predictions of mask quality\n          torch.Tensor: batched SAM token for mask output\n        \"\"\"\n        masks, iou_pred, mask_tokens_out, object_score_logits = self.predict_masks(\n            image_embeddings=image_embeddings,\n            image_pe=image_pe,\n            sparse_prompt_embeddings=sparse_prompt_embeddings,\n            dense_prompt_embeddings=dense_prompt_embeddings,\n            repeat_image=repeat_image,\n            high_res_features=high_res_features,\n        )\n\n        # Select the correct mask or masks for output\n        if multimask_output:\n            masks = masks[:, 1:, :, :]\n            iou_pred = iou_pred[:, 1:]\n        elif self.dynamic_multimask_via_stability and not self.training:\n            masks, iou_pred = self._dynamic_multimask_via_stability(masks, iou_pred)\n        else:\n            masks = masks[:, 0:1, :, :]\n            iou_pred = iou_pred[:, 0:1]\n\n        if multimask_output and self.use_multimask_token_for_obj_ptr:\n            sam_tokens_out = mask_tokens_out[:, 1:]  # [b, 3, c] shape\n        else:\n            # Take the mask output token. Here we *always* use the token for single mask output.\n            # At test time, even if we track after 1-click (and using multimask_output=True),\n            # we still take the single mask token here. The rationale is that we always track\n            # after multiple clicks during training, so the past tokens seen during training\n            # are always the single mask token (and we'll let it be the object-memory token).\n            sam_tokens_out = mask_tokens_out[:, 0:1]  # [b, 1, c] shape\n\n        # Prepare output\n        return masks, iou_pred, sam_tokens_out, object_score_logits\n\n    def predict_masks(\n        self,\n        image_embeddings: torch.Tensor,\n        image_pe: torch.Tensor,\n        sparse_prompt_embeddings: torch.Tensor,\n        dense_prompt_embeddings: torch.Tensor,\n        repeat_image: bool,\n        high_res_features: Optional[List[torch.Tensor]] = None,\n    ) -> Tuple[torch.Tensor, torch.Tensor]:\n        \"\"\"Predicts masks. See 'forward' for more details.\"\"\"\n        # Concatenate output tokens\n        s = 0\n        if self.pred_obj_scores:\n            output_tokens = torch.cat(\n                [\n                    self.obj_score_token.weight,\n                    self.iou_token.weight,\n                    self.mask_tokens.weight,\n                ],\n                dim=0,\n            )\n            s = 1\n        else:\n            output_tokens = torch.cat(\n                [self.iou_token.weight, self.mask_tokens.weight], dim=0\n            )\n        output_tokens = output_tokens.unsqueeze(0).expand(\n            sparse_prompt_embeddings.size(0), -1, -1\n        )\n        tokens = torch.cat((output_tokens, sparse_prompt_embeddings), dim=1)\n\n        # Expand per-image data in batch direction to be per-mask\n        if repeat_image:\n            src = torch.repeat_interleave(image_embeddings, tokens.shape[0], dim=0)\n        else:\n            assert image_embeddings.shape[0] == tokens.shape[0]\n            src = image_embeddings\n        src = src + dense_prompt_embeddings\n        assert (\n            image_pe.size(0) == 1\n        ), \"image_pe should have size 1 in batch dim (from `get_dense_pe()`)\"\n        pos_src = torch.repeat_interleave(image_pe, tokens.shape[0], dim=0)\n        b, c, h, w = src.shape\n\n        # Run the transformer\n        hs, src = self.transformer(src, pos_src, tokens)\n        iou_token_out = hs[:, s, :]\n        mask_tokens_out = hs[:, s + 1 : (s + 1 + self.num_mask_tokens), :]\n\n        # Upscale mask embeddings and predict masks using the mask tokens\n        src = src.transpose(1, 2).view(b, c, h, w)\n        if not self.use_high_res_features:\n            upscaled_embedding = self.output_upscaling(src)\n        else:\n            dc1, ln1, act1, dc2, act2 = self.output_upscaling\n            feat_s0, feat_s1 = high_res_features\n            upscaled_embedding = act1(ln1(dc1(src) + feat_s1))\n            upscaled_embedding = act2(dc2(upscaled_embedding) + feat_s0)\n\n        hyper_in_list: List[torch.Tensor] = []\n        for i in range(self.num_mask_tokens):\n            hyper_in_list.append(\n                self.output_hypernetworks_mlps[i](mask_tokens_out[:, i, :])\n            )\n        hyper_in = torch.stack(hyper_in_list, dim=1)\n        b, c, h, w = upscaled_embedding.shape\n        masks = (hyper_in @ upscaled_embedding.view(b, c, h * w)).view(b, -1, h, w)\n\n        # Generate mask quality predictions\n        iou_pred = self.iou_prediction_head(iou_token_out)\n        if self.pred_obj_scores:\n            assert s == 1\n            object_score_logits = self.pred_obj_score_head(hs[:, 0, :])\n        else:\n            # Obj scores logits - default to 10.0, i.e. assuming the object is present, sigmoid(10)=1\n            object_score_logits = 10.0 * iou_pred.new_ones(iou_pred.shape[0], 1)\n\n        return masks, iou_pred, mask_tokens_out, object_score_logits\n\n    def _get_stability_scores(self, mask_logits):\n        \"\"\"\n        Compute stability scores of the mask logits based on the IoU between upper and\n        lower thresholds.\n        \"\"\"\n        mask_logits = mask_logits.flatten(-2)\n        stability_delta = self.dynamic_multimask_stability_delta\n        area_i = torch.sum(mask_logits > stability_delta, dim=-1).float()\n        area_u = torch.sum(mask_logits > -stability_delta, dim=-1).float()\n        stability_scores = torch.where(area_u > 0, area_i / area_u, 1.0)\n        return stability_scores\n\n    def _dynamic_multimask_via_stability(self, all_mask_logits, all_iou_scores):\n        \"\"\"\n        When outputting a single mask, if the stability score from the current single-mask\n        output (based on output token 0) falls below a threshold, we instead select from\n        multi-mask outputs (based on output token 1~3) the mask with the highest predicted\n        IoU score. This is intended to ensure a valid mask for both clicking and tracking.\n        \"\"\"\n        # The best mask from multimask output tokens (1~3)\n        multimask_logits = all_mask_logits[:, 1:, :, :]\n        multimask_iou_scores = all_iou_scores[:, 1:]\n        best_scores_inds = torch.argmax(multimask_iou_scores, dim=-1)\n        batch_inds = torch.arange(\n            multimask_iou_scores.size(0), device=all_iou_scores.device\n        )\n        best_multimask_logits = multimask_logits[batch_inds, best_scores_inds]\n        best_multimask_logits = best_multimask_logits.unsqueeze(1)\n        best_multimask_iou_scores = multimask_iou_scores[batch_inds, best_scores_inds]\n        best_multimask_iou_scores = best_multimask_iou_scores.unsqueeze(1)\n\n        # The mask from singlemask output token 0 and its stability score\n        singlemask_logits = all_mask_logits[:, 0:1, :, :]\n        singlemask_iou_scores = all_iou_scores[:, 0:1]\n        stability_scores = self._get_stability_scores(singlemask_logits)\n        is_stable = stability_scores >= self.dynamic_multimask_stability_thresh\n\n        # Dynamically fall back to best multimask output upon low stability scores.\n        mask_logits_out = torch.where(\n            is_stable[..., None, None].expand_as(singlemask_logits),\n            singlemask_logits,\n            best_multimask_logits,\n        )\n        iou_scores_out = torch.where(\n            is_stable.expand_as(singlemask_iou_scores),\n            singlemask_iou_scores,\n            best_multimask_iou_scores,\n        )\n        return mask_logits_out, iou_scores_out\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/sam/prompt_encoder.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom typing import Optional, Tuple, Type\n\nimport torch\nfrom torch import nn\n\nfrom sam2.modeling.position_encoding import PositionEmbeddingRandom\n\nfrom sam2.modeling.sam2_utils import LayerNorm2d\n\n\nclass PromptEncoder(nn.Module):\n    def __init__(\n        self,\n        embed_dim: int,\n        image_embedding_size: Tuple[int, int],\n        input_image_size: Tuple[int, int],\n        mask_in_chans: int,\n        activation: Type[nn.Module] = nn.GELU,\n    ) -> None:\n        \"\"\"\n        Encodes prompts for input to SAM's mask decoder.\n\n        Arguments:\n          embed_dim (int): The prompts' embedding dimension\n          image_embedding_size (tuple(int, int)): The spatial size of the\n            image embedding, as (H, W).\n          input_image_size (int): The padded size of the image as input\n            to the image encoder, as (H, W).\n          mask_in_chans (int): The number of hidden channels used for\n            encoding input masks.\n          activation (nn.Module): The activation to use when encoding\n            input masks.\n        \"\"\"\n        super().__init__()\n        self.embed_dim = embed_dim\n        self.input_image_size = input_image_size\n        self.image_embedding_size = image_embedding_size\n        self.pe_layer = PositionEmbeddingRandom(embed_dim // 2)\n\n        self.num_point_embeddings: int = 4  # pos/neg point + 2 box corners\n        point_embeddings = [\n            nn.Embedding(1, embed_dim) for i in range(self.num_point_embeddings)\n        ]\n        self.point_embeddings = nn.ModuleList(point_embeddings)\n        self.not_a_point_embed = nn.Embedding(1, embed_dim)\n\n        self.mask_input_size = (\n            4 * image_embedding_size[0],\n            4 * image_embedding_size[1],\n        )\n        self.mask_downscaling = nn.Sequential(\n            nn.Conv2d(1, mask_in_chans // 4, kernel_size=2, stride=2),\n            LayerNorm2d(mask_in_chans // 4),\n            activation(),\n            nn.Conv2d(mask_in_chans // 4, mask_in_chans, kernel_size=2, stride=2),\n            LayerNorm2d(mask_in_chans),\n            activation(),\n            nn.Conv2d(mask_in_chans, embed_dim, kernel_size=1),\n        )\n        self.no_mask_embed = nn.Embedding(1, embed_dim)\n\n    def get_dense_pe(self) -> torch.Tensor:\n        \"\"\"\n        Returns the positional encoding used to encode point prompts,\n        applied to a dense set of points the shape of the image encoding.\n\n        Returns:\n          torch.Tensor: Positional encoding with shape\n            1x(embed_dim)x(embedding_h)x(embedding_w)\n        \"\"\"\n        return self.pe_layer(self.image_embedding_size).unsqueeze(0)\n\n    def _embed_points(\n        self,\n        points: torch.Tensor,\n        labels: torch.Tensor,\n        pad: bool,\n    ) -> torch.Tensor:\n        \"\"\"Embeds point prompts.\"\"\"\n        points = points + 0.5  # Shift to center of pixel\n        if pad:\n            padding_point = torch.zeros((points.shape[0], 1, 2), device=points.device)\n            padding_label = -torch.ones((labels.shape[0], 1), device=labels.device)\n            points = torch.cat([points, padding_point], dim=1)\n            labels = torch.cat([labels, padding_label], dim=1)\n        point_embedding = self.pe_layer.forward_with_coords(\n            points, self.input_image_size\n        )\n        point_embedding[labels == -1] = 0.0\n        point_embedding[labels == -1] += self.not_a_point_embed.weight\n        point_embedding[labels == 0] += self.point_embeddings[0].weight\n        point_embedding[labels == 1] += self.point_embeddings[1].weight\n        point_embedding[labels == 2] += self.point_embeddings[2].weight\n        point_embedding[labels == 3] += self.point_embeddings[3].weight\n        return point_embedding\n\n    def _embed_boxes(self, boxes: torch.Tensor) -> torch.Tensor:\n        \"\"\"Embeds box prompts.\"\"\"\n        boxes = boxes + 0.5  # Shift to center of pixel\n        coords = boxes.reshape(-1, 2, 2)\n        corner_embedding = self.pe_layer.forward_with_coords(\n            coords, self.input_image_size\n        )\n        corner_embedding[:, 0, :] += self.point_embeddings[2].weight\n        corner_embedding[:, 1, :] += self.point_embeddings[3].weight\n        return corner_embedding\n\n    def _embed_masks(self, masks: torch.Tensor) -> torch.Tensor:\n        \"\"\"Embeds mask inputs.\"\"\"\n        mask_embedding = self.mask_downscaling(masks)\n        return mask_embedding\n\n    def _get_batch_size(\n        self,\n        points: Optional[Tuple[torch.Tensor, torch.Tensor]],\n        boxes: Optional[torch.Tensor],\n        masks: Optional[torch.Tensor],\n    ) -> int:\n        \"\"\"\n        Gets the batch size of the output given the batch size of the input prompts.\n        \"\"\"\n        if points is not None:\n            return points[0].shape[0]\n        elif boxes is not None:\n            return boxes.shape[0]\n        elif masks is not None:\n            return masks.shape[0]\n        else:\n            return 1\n\n    def _get_device(self) -> torch.device:\n        return self.point_embeddings[0].weight.device\n\n    def forward(\n        self,\n        points: Optional[Tuple[torch.Tensor, torch.Tensor]],\n        boxes: Optional[torch.Tensor],\n        masks: Optional[torch.Tensor],\n    ) -> Tuple[torch.Tensor, torch.Tensor]:\n        \"\"\"\n        Embeds different types of prompts, returning both sparse and dense\n        embeddings.\n\n        Arguments:\n          points (tuple(torch.Tensor, torch.Tensor) or none): point coordinates\n            and labels to embed.\n          boxes (torch.Tensor or none): boxes to embed\n          masks (torch.Tensor or none): masks to embed\n\n        Returns:\n          torch.Tensor: sparse embeddings for the points and boxes, with shape\n            BxNx(embed_dim), where N is determined by the number of input points\n            and boxes.\n          torch.Tensor: dense embeddings for the masks, in the shape\n            Bx(embed_dim)x(embed_H)x(embed_W)\n        \"\"\"\n        bs = self._get_batch_size(points, boxes, masks)\n        sparse_embeddings = torch.empty(\n            (bs, 0, self.embed_dim), device=self._get_device()\n        )\n        if points is not None:\n            coords, labels = points\n            point_embeddings = self._embed_points(coords, labels, pad=(boxes is None))\n            sparse_embeddings = torch.cat([sparse_embeddings, point_embeddings], dim=1)\n        if boxes is not None:\n            box_embeddings = self._embed_boxes(boxes)\n            sparse_embeddings = torch.cat([sparse_embeddings, box_embeddings], dim=1)\n\n        if masks is not None:\n            dense_embeddings = self._embed_masks(masks)\n        else:\n            dense_embeddings = self.no_mask_embed.weight.reshape(1, -1, 1, 1).expand(\n                bs, -1, self.image_embedding_size[0], self.image_embedding_size[1]\n            )\n\n        return sparse_embeddings, dense_embeddings\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/sam/transformer.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport contextlib\nimport math\nimport warnings\nfrom functools import partial\nfrom typing import Tuple, Type\n\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn, Tensor\n\nfrom sam2.modeling.position_encoding import apply_rotary_enc, compute_axial_cis\nfrom sam2.modeling.sam2_utils import MLP\nfrom sam2.utils.misc import get_sdpa_settings\n\nwarnings.simplefilter(action=\"ignore\", category=FutureWarning)\n# Check whether Flash Attention is available (and use it by default)\nOLD_GPU, USE_FLASH_ATTN, MATH_KERNEL_ON = get_sdpa_settings()\n# A fallback setting to allow all available kernels if Flash Attention fails\nALLOW_ALL_KERNELS = False\n\n\ndef sdp_kernel_context(dropout_p):\n    \"\"\"\n    Get the context for the attention scaled dot-product kernel. We use Flash Attention\n    by default, but fall back to all available kernels if Flash Attention fails.\n    \"\"\"\n    if ALLOW_ALL_KERNELS:\n        return contextlib.nullcontext()\n\n    return torch.backends.cuda.sdp_kernel(\n        enable_flash=USE_FLASH_ATTN,\n        # if Flash attention kernel is off, then math kernel needs to be enabled\n        enable_math=(OLD_GPU and dropout_p > 0.0) or MATH_KERNEL_ON,\n        enable_mem_efficient=OLD_GPU,\n    )\n\n\nclass TwoWayTransformer(nn.Module):\n    def __init__(\n        self,\n        depth: int,\n        embedding_dim: int,\n        num_heads: int,\n        mlp_dim: int,\n        activation: Type[nn.Module] = nn.ReLU,\n        attention_downsample_rate: int = 2,\n    ) -> None:\n        \"\"\"\n        A transformer decoder that attends to an input image using\n        queries whose positional embedding is supplied.\n\n        Args:\n          depth (int): number of layers in the transformer\n          embedding_dim (int): the channel dimension for the input embeddings\n          num_heads (int): the number of heads for multihead attention. Must\n            divide embedding_dim\n          mlp_dim (int): the channel dimension internal to the MLP block\n          activation (nn.Module): the activation to use in the MLP block\n        \"\"\"\n        super().__init__()\n        self.depth = depth\n        self.embedding_dim = embedding_dim\n        self.num_heads = num_heads\n        self.mlp_dim = mlp_dim\n        self.layers = nn.ModuleList()\n\n        for i in range(depth):\n            self.layers.append(\n                TwoWayAttentionBlock(\n                    embedding_dim=embedding_dim,\n                    num_heads=num_heads,\n                    mlp_dim=mlp_dim,\n                    activation=activation,\n                    attention_downsample_rate=attention_downsample_rate,\n                    skip_first_layer_pe=(i == 0),\n                )\n            )\n\n        self.final_attn_token_to_image = Attention(\n            embedding_dim, num_heads, downsample_rate=attention_downsample_rate\n        )\n        self.norm_final_attn = nn.LayerNorm(embedding_dim)\n\n    def forward(\n        self,\n        image_embedding: Tensor,\n        image_pe: Tensor,\n        point_embedding: Tensor,\n    ) -> Tuple[Tensor, Tensor]:\n        \"\"\"\n        Args:\n          image_embedding (torch.Tensor): image to attend to. Should be shape\n            B x embedding_dim x h x w for any h and w.\n          image_pe (torch.Tensor): the positional encoding to add to the image. Must\n            have the same shape as image_embedding.\n          point_embedding (torch.Tensor): the embedding to add to the query points.\n            Must have shape B x N_points x embedding_dim for any N_points.\n\n        Returns:\n          torch.Tensor: the processed point_embedding\n          torch.Tensor: the processed image_embedding\n        \"\"\"\n        # BxCxHxW -> BxHWxC == B x N_image_tokens x C\n        bs, c, h, w = image_embedding.shape\n        image_embedding = image_embedding.flatten(2).permute(0, 2, 1)\n        image_pe = image_pe.flatten(2).permute(0, 2, 1)\n\n        # Prepare queries\n        queries = point_embedding\n        keys = image_embedding\n\n        # Apply transformer blocks and final layernorm\n        for layer in self.layers:\n            queries, keys = layer(\n                queries=queries,\n                keys=keys,\n                query_pe=point_embedding,\n                key_pe=image_pe,\n            )\n\n        # Apply the final attention layer from the points to the image\n        q = queries + point_embedding\n        k = keys + image_pe\n        attn_out = self.final_attn_token_to_image(q=q, k=k, v=keys)\n        queries = queries + attn_out\n        queries = self.norm_final_attn(queries)\n\n        return queries, keys\n\n\nclass TwoWayAttentionBlock(nn.Module):\n    def __init__(\n        self,\n        embedding_dim: int,\n        num_heads: int,\n        mlp_dim: int = 2048,\n        activation: Type[nn.Module] = nn.ReLU,\n        attention_downsample_rate: int = 2,\n        skip_first_layer_pe: bool = False,\n    ) -> None:\n        \"\"\"\n        A transformer block with four layers: (1) self-attention of sparse\n        inputs, (2) cross attention of sparse inputs to dense inputs, (3) mlp\n        block on sparse inputs, and (4) cross attention of dense inputs to sparse\n        inputs.\n\n        Arguments:\n          embedding_dim (int): the channel dimension of the embeddings\n          num_heads (int): the number of heads in the attention layers\n          mlp_dim (int): the hidden dimension of the mlp block\n          activation (nn.Module): the activation of the mlp block\n          skip_first_layer_pe (bool): skip the PE on the first layer\n        \"\"\"\n        super().__init__()\n        self.self_attn = Attention(embedding_dim, num_heads)\n        self.norm1 = nn.LayerNorm(embedding_dim)\n\n        self.cross_attn_token_to_image = Attention(\n            embedding_dim, num_heads, downsample_rate=attention_downsample_rate\n        )\n        self.norm2 = nn.LayerNorm(embedding_dim)\n\n        self.mlp = MLP(\n            embedding_dim, mlp_dim, embedding_dim, num_layers=2, activation=activation\n        )\n        self.norm3 = nn.LayerNorm(embedding_dim)\n\n        self.norm4 = nn.LayerNorm(embedding_dim)\n        self.cross_attn_image_to_token = Attention(\n            embedding_dim, num_heads, downsample_rate=attention_downsample_rate\n        )\n\n        self.skip_first_layer_pe = skip_first_layer_pe\n\n    def forward(\n        self, queries: Tensor, keys: Tensor, query_pe: Tensor, key_pe: Tensor\n    ) -> Tuple[Tensor, Tensor]:\n        # Self attention block\n        if self.skip_first_layer_pe:\n            queries = self.self_attn(q=queries, k=queries, v=queries)\n        else:\n            q = queries + query_pe\n            attn_out = self.self_attn(q=q, k=q, v=queries)\n            queries = queries + attn_out\n        queries = self.norm1(queries)\n\n        # Cross attention block, tokens attending to image embedding\n        q = queries + query_pe\n        k = keys + key_pe\n        attn_out = self.cross_attn_token_to_image(q=q, k=k, v=keys)\n        queries = queries + attn_out\n        queries = self.norm2(queries)\n\n        # MLP block\n        mlp_out = self.mlp(queries)\n        queries = queries + mlp_out\n        queries = self.norm3(queries)\n\n        # Cross attention block, image embedding attending to tokens\n        q = queries + query_pe\n        k = keys + key_pe\n        attn_out = self.cross_attn_image_to_token(q=k, k=q, v=queries)\n        keys = keys + attn_out\n        keys = self.norm4(keys)\n\n        return queries, keys\n\n\nclass Attention(nn.Module):\n    \"\"\"\n    An attention layer that allows for downscaling the size of the embedding\n    after projection to queries, keys, and values.\n    \"\"\"\n\n    def __init__(\n        self,\n        embedding_dim: int,\n        num_heads: int,\n        downsample_rate: int = 1,\n        dropout: float = 0.0,\n        kv_in_dim: int = None,\n    ) -> None:\n        super().__init__()\n        self.embedding_dim = embedding_dim\n        self.kv_in_dim = kv_in_dim if kv_in_dim is not None else embedding_dim\n        self.internal_dim = embedding_dim // downsample_rate\n        self.num_heads = num_heads\n        assert (\n            self.internal_dim % num_heads == 0\n        ), \"num_heads must divide embedding_dim.\"\n\n        self.q_proj = nn.Linear(embedding_dim, self.internal_dim)\n        self.k_proj = nn.Linear(self.kv_in_dim, self.internal_dim)\n        self.v_proj = nn.Linear(self.kv_in_dim, self.internal_dim)\n        self.out_proj = nn.Linear(self.internal_dim, embedding_dim)\n\n        self.dropout_p = dropout\n\n    def _separate_heads(self, x: Tensor, num_heads: int) -> Tensor:\n        b, n, c = x.shape\n        x = x.reshape(b, n, num_heads, c // num_heads)\n        return x.transpose(1, 2)  # B x N_heads x N_tokens x C_per_head\n\n    def _recombine_heads(self, x: Tensor) -> Tensor:\n        b, n_heads, n_tokens, c_per_head = x.shape\n        x = x.transpose(1, 2)\n        return x.reshape(b, n_tokens, n_heads * c_per_head)  # B x N_tokens x C\n\n    def forward(self, q: Tensor, k: Tensor, v: Tensor) -> Tensor:\n        # Input projections\n        q = self.q_proj(q)\n        k = self.k_proj(k)\n        v = self.v_proj(v)\n\n        # Separate into heads\n        q = self._separate_heads(q, self.num_heads)\n        k = self._separate_heads(k, self.num_heads)\n        v = self._separate_heads(v, self.num_heads)\n\n        dropout_p = self.dropout_p if self.training else 0.0\n        # Attention\n        try:\n            with sdp_kernel_context(dropout_p):\n                out = F.scaled_dot_product_attention(q, k, v, dropout_p=dropout_p)\n        except Exception as e:\n            # Fall back to all kernels if the Flash attention kernel fails\n            warnings.warn(\n                f\"Flash Attention kernel failed due to: {e}\\nFalling back to all available \"\n                f\"kernels for scaled_dot_product_attention (which may have a slower speed).\",\n                category=UserWarning,\n                stacklevel=2,\n            )\n            global ALLOW_ALL_KERNELS\n            ALLOW_ALL_KERNELS = True\n            out = F.scaled_dot_product_attention(q, k, v, dropout_p=dropout_p)\n\n        out = self._recombine_heads(out)\n        out = self.out_proj(out)\n\n        return out\n\n\nclass RoPEAttention(Attention):\n    \"\"\"Attention with rotary position encoding.\"\"\"\n\n    def __init__(\n        self,\n        *args,\n        rope_theta=10000.0,\n        # whether to repeat q rope to match k length\n        # this is needed for cross-attention to memories\n        rope_k_repeat=False,\n        feat_sizes=(32, 32),  # [w, h] for stride 16 feats at 512 resolution\n        **kwargs,\n    ):\n        super().__init__(*args, **kwargs)\n\n        self.compute_cis = partial(\n            compute_axial_cis, dim=self.internal_dim // self.num_heads, theta=rope_theta\n        )\n        freqs_cis = self.compute_cis(end_x=feat_sizes[0], end_y=feat_sizes[1])\n        self.freqs_cis = freqs_cis\n        self.rope_k_repeat = rope_k_repeat\n\n    def forward(\n        self, q: Tensor, k: Tensor, v: Tensor, num_k_exclude_rope: int = 0\n    ) -> Tensor:\n        # Input projections\n        q = self.q_proj(q)\n        k = self.k_proj(k)\n        v = self.v_proj(v)\n\n        # Separate into heads\n        q = self._separate_heads(q, self.num_heads)\n        k = self._separate_heads(k, self.num_heads)\n        v = self._separate_heads(v, self.num_heads)\n\n        # Apply rotary position encoding\n        w = h = math.sqrt(q.shape[-2])\n        self.freqs_cis = self.freqs_cis.to(q.device)\n        if self.freqs_cis.shape[0] != q.shape[-2]:\n            self.freqs_cis = self.compute_cis(end_x=w, end_y=h).to(q.device)\n        if q.shape[-2] != k.shape[-2]:\n            assert self.rope_k_repeat\n\n        num_k_rope = k.size(-2) - num_k_exclude_rope\n        q, k[:, :, :num_k_rope] = apply_rotary_enc(\n            q,\n            k[:, :, :num_k_rope],\n            freqs_cis=self.freqs_cis,\n            repeat_freqs_k=self.rope_k_repeat,\n        )\n\n        dropout_p = self.dropout_p if self.training else 0.0\n        # Attention\n        try:\n            with sdp_kernel_context(dropout_p):\n                out = F.scaled_dot_product_attention(q, k, v, dropout_p=dropout_p)\n        except Exception as e:\n            # Fall back to all kernels if the Flash attention kernel fails\n            warnings.warn(\n                f\"Flash Attention kernel failed due to: {e}\\nFalling back to all available \"\n                f\"kernels for scaled_dot_product_attention (which may have a slower speed).\",\n                category=UserWarning,\n                stacklevel=2,\n            )\n            global ALLOW_ALL_KERNELS\n            ALLOW_ALL_KERNELS = True\n            out = F.scaled_dot_product_attention(q, k, v, dropout_p=dropout_p)\n\n        out = self._recombine_heads(out)\n        out = self.out_proj(out)\n\n        return out\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/sam2_base.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport torch\nimport torch.distributed\nimport torch.nn.functional as F\n\nfrom torch.nn.init import trunc_normal_\n\nfrom sam2.modeling.sam.mask_decoder import MaskDecoder\nfrom sam2.modeling.sam.prompt_encoder import PromptEncoder\nfrom sam2.modeling.sam.transformer import TwoWayTransformer\nfrom sam2.modeling.sam2_utils import get_1d_sine_pe, MLP, select_closest_cond_frames\n\n# a large negative value as a placeholder score for missing objects\nNO_OBJ_SCORE = -1024.0\n\n\nclass SAM2Base(torch.nn.Module):\n    def __init__(\n        self,\n        image_encoder,\n        memory_attention,\n        memory_encoder,\n        num_maskmem=7,  # default 1 input frame + 6 previous frames\n        image_size=512,\n        backbone_stride=16,  # stride of the image backbone output\n        sigmoid_scale_for_mem_enc=1.0,  # scale factor for mask sigmoid prob\n        sigmoid_bias_for_mem_enc=0.0,  # bias factor for mask sigmoid prob\n        # During evaluation, whether to binarize the sigmoid mask logits on interacted frames with clicks\n        binarize_mask_from_pts_for_mem_enc=False,\n        use_mask_input_as_output_without_sam=False,  # on frames with mask input, whether to directly output the input mask without using a SAM prompt encoder + mask decoder\n        # The maximum number of conditioning frames to participate in the memory attention (-1 means no limit; if there are more conditioning frames than this limit,\n        # we only cross-attend to the temporally closest `max_cond_frames_in_attn` conditioning frames in the encoder when tracking each frame). This gives the model\n        # a temporal locality when handling a large number of annotated frames (since closer frames should be more important) and also avoids GPU OOM.\n        max_cond_frames_in_attn=-1,\n        # on the first frame, whether to directly add the no-memory embedding to the image feature\n        # (instead of using the transformer encoder)\n        directly_add_no_mem_embed=False,\n        # whether to use high-resolution feature maps in the SAM mask decoder\n        use_high_res_features_in_sam=False,\n        # whether to output multiple (3) masks for the first click on initial conditioning frames\n        multimask_output_in_sam=False,\n        # the minimum and maximum number of clicks to use multimask_output_in_sam (only relevant when `multimask_output_in_sam=True`;\n        # default is 1 for both, meaning that only the first click gives multimask output; also note that a box counts as two points)\n        multimask_min_pt_num=1,\n        multimask_max_pt_num=1,\n        # whether to also use multimask output for tracking (not just for the first click on initial conditioning frames; only relevant when `multimask_output_in_sam=True`)\n        multimask_output_for_tracking=False,\n        # Whether to use multimask tokens for obj ptr; Only relevant when both\n        # use_obj_ptrs_in_encoder=True and multimask_output_for_tracking=True\n        use_multimask_token_for_obj_ptr: bool = False,\n        # whether to use sigmoid to restrict ious prediction to [0-1]\n        iou_prediction_use_sigmoid=False,\n        # The memory bank's temporal stride during evaluation (i.e. the `r` parameter in XMem and Cutie; XMem and Cutie use r=5).\n        # For r>1, the (self.num_maskmem - 1) non-conditioning memory frames consist of\n        # (self.num_maskmem - 2) nearest frames from every r-th frames, plus the last frame.\n        memory_temporal_stride_for_eval=1,\n        # whether to apply non-overlapping constraints on the object masks in the memory encoder during evaluation (to avoid/alleviate superposing masks)\n        non_overlap_masks_for_mem_enc=False,\n        # whether to cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n        use_obj_ptrs_in_encoder=False,\n        # the maximum number of object pointers from other frames in encoder cross attention (only relevant when `use_obj_ptrs_in_encoder=True`)\n        max_obj_ptrs_in_encoder=16,\n        # whether to add temporal positional encoding to the object pointers in the encoder (only relevant when `use_obj_ptrs_in_encoder=True`)\n        add_tpos_enc_to_obj_ptrs=True,\n        # whether to add an extra linear projection layer for the temporal positional encoding in the object pointers to avoid potential interference\n        # with spatial positional encoding (only relevant when both `use_obj_ptrs_in_encoder=True` and `add_tpos_enc_to_obj_ptrs=True`)\n        proj_tpos_enc_in_obj_ptrs=False,\n        # whether to use signed distance (instead of unsigned absolute distance) in the temporal positional encoding in the object pointers\n        # (only relevant when both `use_obj_ptrs_in_encoder=True` and `add_tpos_enc_to_obj_ptrs=True`)\n        use_signed_tpos_enc_to_obj_ptrs=False,\n        # whether to only attend to object pointers in the past (before the current frame) in the encoder during evaluation\n        # (only relevant when `use_obj_ptrs_in_encoder=True`; this might avoid pointer information too far in the future to distract the initial tracking)\n        only_obj_ptrs_in_the_past_for_eval=False,\n        # Whether to predict if there is an object in the frame\n        pred_obj_scores: bool = False,\n        # Whether to use an MLP to predict object scores\n        pred_obj_scores_mlp: bool = False,\n        # Only relevant if pred_obj_scores=True and use_obj_ptrs_in_encoder=True;\n        # Whether to have a fixed no obj pointer when there is no object present\n        # or to use it as an additive embedding with obj_ptr produced by decoder\n        fixed_no_obj_ptr: bool = False,\n        # Soft no object, i.e. mix in no_obj_ptr softly,\n        # hope to make recovery easier if there is a mistake and mitigate accumulation of errors\n        soft_no_obj_ptr: bool = False,\n        use_mlp_for_obj_ptr_proj: bool = False,\n        # add no obj embedding to spatial frames\n        no_obj_embed_spatial: bool = False,\n        # extra arguments used to construct the SAM mask decoder; if not None, it should be a dict of kwargs to be passed into `MaskDecoder` class.\n        sam_mask_decoder_extra_args=None,\n        compile_image_encoder: bool = False,\n    ):\n        super().__init__()\n\n        # Part 1: the image backbone\n        self.image_encoder = image_encoder\n        # Use level 0, 1, 2 for high-res setting, or just level 2 for the default setting\n        self.use_high_res_features_in_sam = use_high_res_features_in_sam\n        self.num_feature_levels = 3 if use_high_res_features_in_sam else 1\n        self.use_obj_ptrs_in_encoder = use_obj_ptrs_in_encoder\n        self.max_obj_ptrs_in_encoder = max_obj_ptrs_in_encoder\n        if use_obj_ptrs_in_encoder:\n            # A conv layer to downsample the mask prompt to stride 4 (the same stride as\n            # low-res SAM mask logits) and to change its scales from 0~1 to SAM logit scale,\n            # so that it can be fed into the SAM mask decoder to generate a pointer.\n            self.mask_downsample = torch.nn.Conv2d(1, 1, kernel_size=4, stride=4)\n        self.add_tpos_enc_to_obj_ptrs = add_tpos_enc_to_obj_ptrs\n        if proj_tpos_enc_in_obj_ptrs:\n            assert add_tpos_enc_to_obj_ptrs  # these options need to be used together\n        self.proj_tpos_enc_in_obj_ptrs = proj_tpos_enc_in_obj_ptrs\n        self.use_signed_tpos_enc_to_obj_ptrs = use_signed_tpos_enc_to_obj_ptrs\n        self.only_obj_ptrs_in_the_past_for_eval = only_obj_ptrs_in_the_past_for_eval\n\n        # Part 2: memory attention to condition current frame's visual features\n        # with memories (and obj ptrs) from past frames\n        self.memory_attention = memory_attention\n        self.hidden_dim = image_encoder.neck.d_model\n\n        # Part 3: memory encoder for the previous frame's outputs\n        self.memory_encoder = memory_encoder\n        self.mem_dim = self.hidden_dim\n        if hasattr(self.memory_encoder, \"out_proj\") and hasattr(\n            self.memory_encoder.out_proj, \"weight\"\n        ):\n            # if there is compression of memories along channel dim\n            self.mem_dim = self.memory_encoder.out_proj.weight.shape[0]\n        self.num_maskmem = num_maskmem  # Number of memories accessible\n        # Temporal encoding of the memories\n        self.maskmem_tpos_enc = torch.nn.Parameter(\n            torch.zeros(num_maskmem, 1, 1, self.mem_dim)\n        )\n        trunc_normal_(self.maskmem_tpos_enc, std=0.02)\n        # a single token to indicate no memory embedding from previous frames\n        self.no_mem_embed = torch.nn.Parameter(torch.zeros(1, 1, self.hidden_dim))\n        self.no_mem_pos_enc = torch.nn.Parameter(torch.zeros(1, 1, self.hidden_dim))\n        trunc_normal_(self.no_mem_embed, std=0.02)\n        trunc_normal_(self.no_mem_pos_enc, std=0.02)\n        self.directly_add_no_mem_embed = directly_add_no_mem_embed\n        # Apply sigmoid to the output raw mask logits (to turn them from\n        # range (-inf, +inf) to range (0, 1)) before feeding them into the memory encoder\n        self.sigmoid_scale_for_mem_enc = sigmoid_scale_for_mem_enc\n        self.sigmoid_bias_for_mem_enc = sigmoid_bias_for_mem_enc\n        self.binarize_mask_from_pts_for_mem_enc = binarize_mask_from_pts_for_mem_enc\n        self.non_overlap_masks_for_mem_enc = non_overlap_masks_for_mem_enc\n        self.memory_temporal_stride_for_eval = memory_temporal_stride_for_eval\n        # On frames with mask input, whether to directly output the input mask without\n        # using a SAM prompt encoder + mask decoder\n        self.use_mask_input_as_output_without_sam = use_mask_input_as_output_without_sam\n        self.multimask_output_in_sam = multimask_output_in_sam\n        self.multimask_min_pt_num = multimask_min_pt_num\n        self.multimask_max_pt_num = multimask_max_pt_num\n        self.multimask_output_for_tracking = multimask_output_for_tracking\n        self.use_multimask_token_for_obj_ptr = use_multimask_token_for_obj_ptr\n        self.iou_prediction_use_sigmoid = iou_prediction_use_sigmoid\n\n        # Part 4: SAM-style prompt encoder (for both mask and point inputs)\n        # and SAM-style mask decoder for the final mask output\n        self.image_size = image_size\n        self.backbone_stride = backbone_stride\n        self.sam_mask_decoder_extra_args = sam_mask_decoder_extra_args\n        self.pred_obj_scores = pred_obj_scores\n        self.pred_obj_scores_mlp = pred_obj_scores_mlp\n        self.fixed_no_obj_ptr = fixed_no_obj_ptr\n        self.soft_no_obj_ptr = soft_no_obj_ptr\n        if self.fixed_no_obj_ptr:\n            assert self.pred_obj_scores\n            assert self.use_obj_ptrs_in_encoder\n        if self.pred_obj_scores and self.use_obj_ptrs_in_encoder:\n            self.no_obj_ptr = torch.nn.Parameter(torch.zeros(1, self.hidden_dim))\n            trunc_normal_(self.no_obj_ptr, std=0.02)\n        self.use_mlp_for_obj_ptr_proj = use_mlp_for_obj_ptr_proj\n        self.no_obj_embed_spatial = None\n        if no_obj_embed_spatial:\n            self.no_obj_embed_spatial = torch.nn.Parameter(torch.zeros(1, self.mem_dim))\n            trunc_normal_(self.no_obj_embed_spatial, std=0.02)\n\n        self._build_sam_heads()\n        self.max_cond_frames_in_attn = max_cond_frames_in_attn\n\n        # Model compilation\n        if compile_image_encoder:\n            # Compile the forward function (not the full module) to allow loading checkpoints.\n            print(\n                \"Image encoder compilation is enabled. First forward pass will be slow.\"\n            )\n            self.image_encoder.forward = torch.compile(\n                self.image_encoder.forward,\n                mode=\"max-autotune\",\n                fullgraph=True,\n                dynamic=False,\n            )\n\n    @property\n    def device(self):\n        return next(self.parameters()).device\n\n    def forward(self, *args, **kwargs):\n        raise NotImplementedError(\n            \"Please use the corresponding methods in SAM2VideoPredictor for inference or SAM2Train for training/fine-tuning\"\n            \"See notebooks/video_predictor_example.ipynb for an inference example.\"\n        )\n\n    def _build_sam_heads(self):\n        \"\"\"Build SAM-style prompt encoder and mask decoder.\"\"\"\n        self.sam_prompt_embed_dim = self.hidden_dim\n        self.sam_image_embedding_size = self.image_size // self.backbone_stride\n\n        # build PromptEncoder and MaskDecoder from SAM\n        # (their hyperparameters like `mask_in_chans=16` are from SAM code)\n        self.sam_prompt_encoder = PromptEncoder(\n            embed_dim=self.sam_prompt_embed_dim,\n            image_embedding_size=(\n                self.sam_image_embedding_size,\n                self.sam_image_embedding_size,\n            ),\n            input_image_size=(self.image_size, self.image_size),\n            mask_in_chans=16,\n        )\n        self.sam_mask_decoder = MaskDecoder(\n            num_multimask_outputs=3,\n            transformer=TwoWayTransformer(\n                depth=2,\n                embedding_dim=self.sam_prompt_embed_dim,\n                mlp_dim=2048,\n                num_heads=8,\n            ),\n            transformer_dim=self.sam_prompt_embed_dim,\n            iou_head_depth=3,\n            iou_head_hidden_dim=256,\n            use_high_res_features=self.use_high_res_features_in_sam,\n            iou_prediction_use_sigmoid=self.iou_prediction_use_sigmoid,\n            pred_obj_scores=self.pred_obj_scores,\n            pred_obj_scores_mlp=self.pred_obj_scores_mlp,\n            use_multimask_token_for_obj_ptr=self.use_multimask_token_for_obj_ptr,\n            **(self.sam_mask_decoder_extra_args or {}),\n        )\n        if self.use_obj_ptrs_in_encoder:\n            # a linear projection on SAM output tokens to turn them into object pointers\n            self.obj_ptr_proj = torch.nn.Linear(self.hidden_dim, self.hidden_dim)\n            if self.use_mlp_for_obj_ptr_proj:\n                self.obj_ptr_proj = MLP(\n                    self.hidden_dim, self.hidden_dim, self.hidden_dim, 3\n                )\n        else:\n            self.obj_ptr_proj = torch.nn.Identity()\n        if self.proj_tpos_enc_in_obj_ptrs:\n            # a linear projection on temporal positional encoding in object pointers to\n            # avoid potential interference with spatial positional encoding\n            self.obj_ptr_tpos_proj = torch.nn.Linear(self.hidden_dim, self.mem_dim)\n        else:\n            self.obj_ptr_tpos_proj = torch.nn.Identity()\n\n    def _forward_sam_heads(\n        self,\n        backbone_features,\n        point_inputs=None,\n        mask_inputs=None,\n        high_res_features=None,\n        multimask_output=False,\n    ):\n        \"\"\"\n        Forward SAM prompt encoders and mask heads.\n\n        Inputs:\n        - backbone_features: image features of [B, C, H, W] shape\n        - point_inputs: a dictionary with \"point_coords\" and \"point_labels\", where\n          1) \"point_coords\" has [B, P, 2] shape and float32 dtype and contains the\n             absolute pixel-unit coordinate in (x, y) format of the P input points\n          2) \"point_labels\" has shape [B, P] and int32 dtype, where 1 means\n             positive clicks, 0 means negative clicks, and -1 means padding\n        - mask_inputs: a mask of [B, 1, H*16, W*16] shape, float or bool, with the\n          same spatial size as the image.\n        - high_res_features: either 1) None or 2) or a list of length 2 containing\n          two feature maps of [B, C, 4*H, 4*W] and [B, C, 2*H, 2*W] shapes respectively,\n          which will be used as high-resolution feature maps for SAM decoder.\n        - multimask_output: if it's True, we output 3 candidate masks and their 3\n          corresponding IoU estimates, and if it's False, we output only 1 mask and\n          its corresponding IoU estimate.\n\n        Outputs:\n        - low_res_multimasks: [B, M, H*4, W*4] shape (where M = 3 if\n          `multimask_output=True` and M = 1 if `multimask_output=False`), the SAM\n          output mask logits (before sigmoid) for the low-resolution masks, with 4x\n          the resolution (1/4 stride) of the input backbone_features.\n        - high_res_multimasks: [B, M, H*16, W*16] shape (where M = 3\n          if `multimask_output=True` and M = 1 if `multimask_output=False`),\n          upsampled from the low-resolution masks, with shape size as the image\n          (stride is 1 pixel).\n        - ious, [B, M] shape, where (where M = 3 if `multimask_output=True` and M = 1\n          if `multimask_output=False`), the estimated IoU of each output mask.\n        - low_res_masks: [B, 1, H*4, W*4] shape, the best mask in `low_res_multimasks`.\n          If `multimask_output=True`, it's the mask with the highest IoU estimate.\n          If `multimask_output=False`, it's the same as `low_res_multimasks`.\n        - high_res_masks: [B, 1, H*16, W*16] shape, the best mask in `high_res_multimasks`.\n          If `multimask_output=True`, it's the mask with the highest IoU estimate.\n          If `multimask_output=False`, it's the same as `high_res_multimasks`.\n        - obj_ptr: [B, C] shape, the object pointer vector for the output mask, extracted\n          based on the output token from the SAM mask decoder.\n        \"\"\"\n        B = backbone_features.size(0)\n        device = backbone_features.device\n        assert backbone_features.size(1) == self.sam_prompt_embed_dim\n        assert backbone_features.size(2) == self.sam_image_embedding_size\n        assert backbone_features.size(3) == self.sam_image_embedding_size\n\n        # a) Handle point prompts\n        if point_inputs is not None:\n            sam_point_coords = point_inputs[\"point_coords\"]\n            sam_point_labels = point_inputs[\"point_labels\"]\n            assert sam_point_coords.size(0) == B and sam_point_labels.size(0) == B\n        else:\n            # If no points are provide, pad with an empty point (with label -1)\n            sam_point_coords = torch.zeros(B, 1, 2, device=device)\n            sam_point_labels = -torch.ones(B, 1, dtype=torch.int32, device=device)\n\n        # b) Handle mask prompts\n        if mask_inputs is not None:\n            # If mask_inputs is provided, downsize it into low-res mask input if needed\n            # and feed it as a dense mask prompt into the SAM mask encoder\n            assert len(mask_inputs.shape) == 4 and mask_inputs.shape[:2] == (B, 1)\n            if mask_inputs.shape[-2:] != self.sam_prompt_encoder.mask_input_size:\n                sam_mask_prompt = F.interpolate(\n                    mask_inputs.float(),\n                    size=self.sam_prompt_encoder.mask_input_size,\n                    align_corners=False,\n                    mode=\"bilinear\",\n                    antialias=True,  # use antialias for downsampling\n                )\n            else:\n                sam_mask_prompt = mask_inputs\n        else:\n            # Otherwise, simply feed None (and SAM's prompt encoder will add\n            # a learned `no_mask_embed` to indicate no mask input in this case).\n            sam_mask_prompt = None\n\n        sparse_embeddings, dense_embeddings = self.sam_prompt_encoder(\n            points=(sam_point_coords, sam_point_labels),\n            boxes=None,\n            masks=sam_mask_prompt,\n        )\n        (\n            low_res_multimasks,\n            ious,\n            sam_output_tokens,\n            object_score_logits,\n        ) = self.sam_mask_decoder(\n            image_embeddings=backbone_features,\n            image_pe=self.sam_prompt_encoder.get_dense_pe(),\n            sparse_prompt_embeddings=sparse_embeddings,\n            dense_prompt_embeddings=dense_embeddings,\n            multimask_output=multimask_output,\n            repeat_image=False,  # the image is already batched\n            high_res_features=high_res_features,\n        )\n        if self.pred_obj_scores:\n            is_obj_appearing = object_score_logits > 0\n\n            # Mask used for spatial memories is always a *hard* choice between obj and no obj,\n            # consistent with the actual mask prediction\n            low_res_multimasks = torch.where(\n                is_obj_appearing[:, None, None],\n                low_res_multimasks,\n                NO_OBJ_SCORE,\n            )\n\n        # convert masks from possibly bfloat16 (or float16) to float32\n        # (older PyTorch versions before 2.1 don't support `interpolate` on bf16)\n        low_res_multimasks = low_res_multimasks.float()\n        high_res_multimasks = F.interpolate(\n            low_res_multimasks,\n            size=(self.image_size, self.image_size),\n            mode=\"bilinear\",\n            align_corners=False,\n        )\n\n        sam_output_token = sam_output_tokens[:, 0]\n        if multimask_output:\n            # take the best mask prediction (with the highest IoU estimation)\n            best_iou_inds = torch.argmax(ious, dim=-1)\n            batch_inds = torch.arange(B, device=device)\n            low_res_masks = low_res_multimasks[batch_inds, best_iou_inds].unsqueeze(1)\n            high_res_masks = high_res_multimasks[batch_inds, best_iou_inds].unsqueeze(1)\n            if sam_output_tokens.size(1) > 1:\n                sam_output_token = sam_output_tokens[batch_inds, best_iou_inds]\n        else:\n            low_res_masks, high_res_masks = low_res_multimasks, high_res_multimasks\n\n        # Extract object pointer from the SAM output token (with occlusion handling)\n        obj_ptr = self.obj_ptr_proj(sam_output_token)\n        if self.pred_obj_scores:\n            # Allow *soft* no obj ptr, unlike for masks\n            if self.soft_no_obj_ptr:\n                lambda_is_obj_appearing = object_score_logits.sigmoid()\n            else:\n                lambda_is_obj_appearing = is_obj_appearing.float()\n\n            if self.fixed_no_obj_ptr:\n                obj_ptr = lambda_is_obj_appearing * obj_ptr\n            obj_ptr = obj_ptr + (1 - lambda_is_obj_appearing) * self.no_obj_ptr\n\n        return (\n            low_res_multimasks,\n            high_res_multimasks,\n            ious,\n            low_res_masks,\n            high_res_masks,\n            obj_ptr,\n            object_score_logits,\n        )\n\n    def _use_mask_as_output(self, backbone_features, high_res_features, mask_inputs):\n        \"\"\"\n        Directly turn binary `mask_inputs` into a output mask logits without using SAM.\n        (same input and output shapes as in _forward_sam_heads above).\n        \"\"\"\n        # Use -10/+10 as logits for neg/pos pixels (very close to 0/1 in prob after sigmoid).\n        out_scale, out_bias = 20.0, -10.0  # sigmoid(-10.0)=4.5398e-05\n        mask_inputs_float = mask_inputs.float()\n        high_res_masks = mask_inputs_float * out_scale + out_bias\n        low_res_masks = F.interpolate(\n            high_res_masks,\n            size=(high_res_masks.size(-2) // 4, high_res_masks.size(-1) // 4),\n            align_corners=False,\n            mode=\"bilinear\",\n            antialias=True,  # use antialias for downsampling\n        )\n        # a dummy IoU prediction of all 1's under mask input\n        ious = mask_inputs.new_ones(mask_inputs.size(0), 1).float()\n        if not self.use_obj_ptrs_in_encoder:\n            # all zeros as a dummy object pointer (of shape [B, C])\n            obj_ptr = torch.zeros(\n                mask_inputs.size(0), self.hidden_dim, device=mask_inputs.device\n            )\n        else:\n            # produce an object pointer using the SAM decoder from the mask input\n            _, _, _, _, _, obj_ptr, _ = self._forward_sam_heads(\n                backbone_features=backbone_features,\n                mask_inputs=self.mask_downsample(mask_inputs_float),\n                high_res_features=high_res_features,\n            )\n        # In this method, we are treating mask_input as output, e.g. using it directly to create spatial mem;\n        # Below, we follow the same design axiom to use mask_input to decide if obj appears or not instead of relying\n        # on the object_scores from the SAM decoder.\n        is_obj_appearing = torch.any(mask_inputs.flatten(1).float() > 0.0, dim=1)\n        is_obj_appearing = is_obj_appearing[..., None]\n        lambda_is_obj_appearing = is_obj_appearing.float()\n        object_score_logits = out_scale * lambda_is_obj_appearing + out_bias\n        if self.pred_obj_scores:\n            if self.fixed_no_obj_ptr:\n                obj_ptr = lambda_is_obj_appearing * obj_ptr\n            obj_ptr = obj_ptr + (1 - lambda_is_obj_appearing) * self.no_obj_ptr\n\n        return (\n            low_res_masks,\n            high_res_masks,\n            ious,\n            low_res_masks,\n            high_res_masks,\n            obj_ptr,\n            object_score_logits,\n        )\n\n    def forward_image(self, img_batch: torch.Tensor):\n        \"\"\"Get the image feature on the input batch.\"\"\"\n        backbone_out = self.image_encoder(img_batch)\n        # print(f\"[sam2_base.forward_image] backbone_out.dtype={backbone_out['vision_features'].dtype}\")\n        if self.use_high_res_features_in_sam:\n            # precompute projected level 0 and level 1 features in SAM decoder\n            # to avoid running it again on every SAM click\n            backbone_out[\"backbone_fpn\"][0] = self.sam_mask_decoder.conv_s0(\n                backbone_out[\"backbone_fpn\"][0]\n            )\n            backbone_out[\"backbone_fpn\"][1] = self.sam_mask_decoder.conv_s1(\n                backbone_out[\"backbone_fpn\"][1]\n            )\n        return backbone_out\n\n    def _prepare_backbone_features(self, backbone_out):\n        \"\"\"Prepare and flatten visual features.\"\"\"\n        backbone_out = backbone_out.copy()\n        assert len(backbone_out[\"backbone_fpn\"]) == len(backbone_out[\"vision_pos_enc\"])\n        assert len(backbone_out[\"backbone_fpn\"]) >= self.num_feature_levels\n\n        feature_maps = backbone_out[\"backbone_fpn\"][-self.num_feature_levels :]\n        vision_pos_embeds = backbone_out[\"vision_pos_enc\"][-self.num_feature_levels :]\n\n        feat_sizes = [(x.shape[-2], x.shape[-1]) for x in vision_pos_embeds]\n        # flatten NxCxHxW to HWxNxC\n        vision_feats = [x.flatten(2).permute(2, 0, 1) for x in feature_maps]\n        vision_pos_embeds = [x.flatten(2).permute(2, 0, 1) for x in vision_pos_embeds]\n\n        return backbone_out, vision_feats, vision_pos_embeds, feat_sizes\n\n    def _prepare_memory_conditioned_features(\n        self,\n        frame_idx,\n        is_init_cond_frame,\n        current_vision_feats,\n        current_vision_pos_embeds,\n        feat_sizes,\n        output_dict,\n        num_frames,\n        track_in_reverse=False,  # tracking in reverse time order (for demo usage)\n    ):\n        \"\"\"Fuse the current frame's visual feature map with previous memory.\"\"\"\n        B = current_vision_feats[-1].size(1)  # batch size on this frame\n        C = self.hidden_dim\n        H, W = feat_sizes[-1]  # top-level (lowest-resolution) feature size\n        device = current_vision_feats[-1].device\n        # The case of `self.num_maskmem == 0` below is primarily used for reproducing SAM on images.\n        # In this case, we skip the fusion with any memory.\n        if self.num_maskmem == 0:  # Disable memory and skip fusion\n            pix_feat = current_vision_feats[-1].permute(1, 2, 0).view(B, C, H, W)\n            return pix_feat\n\n        num_obj_ptr_tokens = 0\n        tpos_sign_mul = -1 if track_in_reverse else 1\n        # Step 1: condition the visual features of the current frame on previous memories\n        if not is_init_cond_frame:\n            # Retrieve the memories encoded with the maskmem backbone\n            to_cat_memory, to_cat_memory_pos_embed = [], []\n            # Add conditioning frames's output first (all cond frames have t_pos=0 for\n            # when getting temporal positional embedding below)\n            assert len(output_dict[\"cond_frame_outputs\"]) > 0\n            # Select a maximum number of temporally closest cond frames for cross attention\n            cond_outputs = output_dict[\"cond_frame_outputs\"]\n            selected_cond_outputs, unselected_cond_outputs = select_closest_cond_frames(\n                frame_idx, cond_outputs, self.max_cond_frames_in_attn\n            )\n            t_pos_and_prevs = [(0, out) for out in selected_cond_outputs.values()]\n            # Add last (self.num_maskmem - 1) frames before current frame for non-conditioning memory\n            # the earliest one has t_pos=1 and the latest one has t_pos=self.num_maskmem-1\n            # We also allow taking the memory frame non-consecutively (with stride>1), in which case\n            # we take (self.num_maskmem - 2) frames among every stride-th frames plus the last frame.\n            stride = 1 if self.training else self.memory_temporal_stride_for_eval\n            for t_pos in range(1, self.num_maskmem):\n                t_rel = self.num_maskmem - t_pos  # how many frames before current frame\n                if t_rel == 1:\n                    # for t_rel == 1, we take the last frame (regardless of r)\n                    if not track_in_reverse:\n                        # the frame immediately before this frame (i.e. frame_idx - 1)\n                        prev_frame_idx = frame_idx - t_rel\n                    else:\n                        # the frame immediately after this frame (i.e. frame_idx + 1)\n                        prev_frame_idx = frame_idx + t_rel\n                else:\n                    # for t_rel >= 2, we take the memory frame from every r-th frames\n                    if not track_in_reverse:\n                        # first find the nearest frame among every r-th frames before this frame\n                        # for r=1, this would be (frame_idx - 2)\n                        prev_frame_idx = ((frame_idx - 2) // stride) * stride\n                        # then seek further among every r-th frames\n                        prev_frame_idx = prev_frame_idx - (t_rel - 2) * stride\n                    else:\n                        # first find the nearest frame among every r-th frames after this frame\n                        # for r=1, this would be (frame_idx + 2)\n                        prev_frame_idx = -(-(frame_idx + 2) // stride) * stride\n                        # then seek further among every r-th frames\n                        prev_frame_idx = prev_frame_idx + (t_rel - 2) * stride\n                out = output_dict[\"non_cond_frame_outputs\"].get(prev_frame_idx, None)\n                if out is None:\n                    # If an unselected conditioning frame is among the last (self.num_maskmem - 1)\n                    # frames, we still attend to it as if it's a non-conditioning frame.\n                    out = unselected_cond_outputs.get(prev_frame_idx, None)\n                t_pos_and_prevs.append((t_pos, out))\n\n            for t_pos, prev in t_pos_and_prevs:\n                if prev is None:\n                    continue  # skip padding frames\n                # \"maskmem_features\" might have been offloaded to CPU in demo use cases,\n                # so we load it back to GPU (it's a no-op if it's already on GPU).\n                feats = prev[\"maskmem_features\"].to(device, non_blocking=True)\n                to_cat_memory.append(feats.flatten(2).permute(2, 0, 1))\n                # Spatial positional encoding (it might have been offloaded to CPU in eval)\n                maskmem_enc = prev[\"maskmem_pos_enc\"][-1].to(device)\n                maskmem_enc = maskmem_enc.flatten(2).permute(2, 0, 1)\n                # Temporal positional encoding\n                maskmem_enc = (\n                    maskmem_enc + self.maskmem_tpos_enc[self.num_maskmem - t_pos - 1]\n                )\n                to_cat_memory_pos_embed.append(maskmem_enc)\n\n            # Construct the list of past object pointers\n            if self.use_obj_ptrs_in_encoder:\n                max_obj_ptrs_in_encoder = min(num_frames, self.max_obj_ptrs_in_encoder)\n                # First add those object pointers from selected conditioning frames\n                # (optionally, only include object pointers in the past during evaluation)\n                if not self.training and self.only_obj_ptrs_in_the_past_for_eval:\n                    ptr_cond_outputs = {\n                        t: out\n                        for t, out in selected_cond_outputs.items()\n                        if (t >= frame_idx if track_in_reverse else t <= frame_idx)\n                    }\n                else:\n                    ptr_cond_outputs = selected_cond_outputs\n                pos_and_ptrs = [\n                    # Temporal pos encoding contains how far away each pointer is from current frame\n                    (\n                        (\n                            (frame_idx - t) * tpos_sign_mul\n                            if self.use_signed_tpos_enc_to_obj_ptrs\n                            else abs(frame_idx - t)\n                        ),\n                        out[\"obj_ptr\"],\n                    )\n                    for t, out in ptr_cond_outputs.items()\n                ]\n                # Add up to (max_obj_ptrs_in_encoder - 1) non-conditioning frames before current frame\n                for t_diff in range(1, max_obj_ptrs_in_encoder):\n                    t = frame_idx + t_diff if track_in_reverse else frame_idx - t_diff\n                    if t < 0 or (num_frames is not None and t >= num_frames):\n                        break\n                    out = output_dict[\"non_cond_frame_outputs\"].get(\n                        t, unselected_cond_outputs.get(t, None)\n                    )\n                    if out is not None:\n                        pos_and_ptrs.append((t_diff, out[\"obj_ptr\"]))\n                # If we have at least one object pointer, add them to the across attention\n                if len(pos_and_ptrs) > 0:\n                    pos_list, ptrs_list = zip(*pos_and_ptrs)\n                    # stack object pointers along dim=0 into [ptr_seq_len, B, C] shape\n                    obj_ptrs = torch.stack(ptrs_list, dim=0)\n                    # a temporal positional embedding based on how far each object pointer is from\n                    # the current frame (sine embedding normalized by the max pointer num).\n                    if self.add_tpos_enc_to_obj_ptrs:\n                        t_diff_max = max_obj_ptrs_in_encoder - 1\n                        tpos_dim = C if self.proj_tpos_enc_in_obj_ptrs else self.mem_dim\n                        obj_pos = torch.tensor(pos_list, device=device)\n                        obj_pos = get_1d_sine_pe(obj_pos / t_diff_max, dim=tpos_dim)\n                        obj_pos = self.obj_ptr_tpos_proj(obj_pos)\n                        obj_pos = obj_pos.unsqueeze(1).expand(-1, B, self.mem_dim)\n                    else:\n                        obj_pos = obj_ptrs.new_zeros(len(pos_list), B, self.mem_dim)\n                    if self.mem_dim < C:\n                        # split a pointer into (C // self.mem_dim) tokens for self.mem_dim < C\n                        obj_ptrs = obj_ptrs.reshape(\n                            -1, B, C // self.mem_dim, self.mem_dim\n                        )\n                        obj_ptrs = obj_ptrs.permute(0, 2, 1, 3).flatten(0, 1)\n                        obj_pos = obj_pos.repeat_interleave(C // self.mem_dim, dim=0)\n                    to_cat_memory.append(obj_ptrs)\n                    to_cat_memory_pos_embed.append(obj_pos)\n                    num_obj_ptr_tokens = obj_ptrs.shape[0]\n                else:\n                    num_obj_ptr_tokens = 0\n        else:\n            # for initial conditioning frames, encode them without using any previous memory\n            if self.directly_add_no_mem_embed:\n                # directly add no-mem embedding (instead of using the transformer encoder)\n                pix_feat_with_mem = current_vision_feats[-1] + self.no_mem_embed\n                pix_feat_with_mem = pix_feat_with_mem.permute(1, 2, 0).view(B, C, H, W)\n                return pix_feat_with_mem\n\n            # Use a dummy token on the first frame (to avoid empty memory input to tranformer encoder)\n            to_cat_memory = [self.no_mem_embed.expand(1, B, self.mem_dim)]\n            to_cat_memory_pos_embed = [self.no_mem_pos_enc.expand(1, B, self.mem_dim)]\n\n        # Step 2: Concatenate the memories and forward through the transformer encoder\n        memory = torch.cat(to_cat_memory, dim=0)\n        memory_pos_embed = torch.cat(to_cat_memory_pos_embed, dim=0)\n\n        pix_feat_with_mem = self.memory_attention(\n            curr=current_vision_feats,\n            curr_pos=current_vision_pos_embeds,\n            memory=memory,\n            memory_pos=memory_pos_embed,\n            num_obj_ptr_tokens=num_obj_ptr_tokens,\n        )\n        # reshape the output (HW)BC => BCHW\n        pix_feat_with_mem = pix_feat_with_mem.permute(1, 2, 0).view(B, C, H, W)\n        return pix_feat_with_mem\n\n    def _encode_new_memory(\n        self,\n        current_vision_feats,\n        feat_sizes,\n        pred_masks_high_res,\n        object_score_logits,\n        is_mask_from_pts,\n    ):\n        \"\"\"Encode the current image and its prediction into a memory feature.\"\"\"\n        B = current_vision_feats[-1].size(1)  # batch size on this frame\n        C = self.hidden_dim\n        H, W = feat_sizes[-1]  # top-level (lowest-resolution) feature size\n        # top-level feature, (HW)BC => BCHW\n        pix_feat = current_vision_feats[-1].permute(1, 2, 0).view(B, C, H, W)\n        if self.non_overlap_masks_for_mem_enc and not self.training:\n            # optionally, apply non-overlapping constraints to the masks (it's applied\n            # in the batch dimension and should only be used during eval, where all\n            # the objects come from the same video under batch size 1).\n            pred_masks_high_res = self._apply_non_overlapping_constraints(\n                pred_masks_high_res\n            )\n        # scale the raw mask logits with a temperature before applying sigmoid\n        binarize = self.binarize_mask_from_pts_for_mem_enc and is_mask_from_pts\n        if binarize and not self.training:\n            mask_for_mem = (pred_masks_high_res > 0).float()\n        else:\n            # apply sigmoid on the raw mask logits to turn them into range (0, 1)\n            mask_for_mem = torch.sigmoid(pred_masks_high_res)\n        # apply scale and bias terms to the sigmoid probabilities\n        if self.sigmoid_scale_for_mem_enc != 1.0:\n            mask_for_mem = mask_for_mem * self.sigmoid_scale_for_mem_enc\n        if self.sigmoid_bias_for_mem_enc != 0.0:\n            mask_for_mem = mask_for_mem + self.sigmoid_bias_for_mem_enc\n        maskmem_out = self.memory_encoder(\n            pix_feat, mask_for_mem, skip_mask_sigmoid=True  # sigmoid already applied\n        )\n        maskmem_features = maskmem_out[\"vision_features\"]\n        maskmem_pos_enc = maskmem_out[\"vision_pos_enc\"]\n        # add a no-object embedding to the spatial memory to indicate that the frame\n        # is predicted to be occluded (i.e. no object is appearing in the frame)\n        if self.no_obj_embed_spatial is not None:\n            is_obj_appearing = (object_score_logits > 0).float()\n            maskmem_features += (\n                1 - is_obj_appearing[..., None, None]\n            ) * self.no_obj_embed_spatial[..., None, None].expand(\n                *maskmem_features.shape\n            )\n\n        return maskmem_features, maskmem_pos_enc\n\n    def _track_step(\n        self,\n        frame_idx,\n        is_init_cond_frame,\n        current_vision_feats,\n        current_vision_pos_embeds,\n        feat_sizes,\n        point_inputs,\n        mask_inputs,\n        output_dict,\n        num_frames,\n        track_in_reverse,\n        prev_sam_mask_logits,\n    ):\n        current_out = {\"point_inputs\": point_inputs, \"mask_inputs\": mask_inputs}\n        # High-resolution feature maps for the SAM head, reshape (HW)BC => BCHW\n        if len(current_vision_feats) > 1:\n            high_res_features = [\n                x.permute(1, 2, 0).view(x.size(1), x.size(2), *s)\n                for x, s in zip(current_vision_feats[:-1], feat_sizes[:-1])\n            ]\n        else:\n            high_res_features = None\n        if mask_inputs is not None and self.use_mask_input_as_output_without_sam:\n            # When use_mask_input_as_output_without_sam=True, we directly output the mask input\n            # (see it as a GT mask) without using a SAM prompt encoder + mask decoder.\n            pix_feat = current_vision_feats[-1].permute(1, 2, 0)\n            pix_feat = pix_feat.view(-1, self.hidden_dim, *feat_sizes[-1])\n            sam_outputs = self._use_mask_as_output(\n                pix_feat, high_res_features, mask_inputs\n            )\n        else:\n            # fused the visual feature with previous memory features in the memory bank\n            pix_feat = self._prepare_memory_conditioned_features(\n                frame_idx=frame_idx,\n                is_init_cond_frame=is_init_cond_frame,\n                current_vision_feats=current_vision_feats[-1:],\n                current_vision_pos_embeds=current_vision_pos_embeds[-1:],\n                feat_sizes=feat_sizes[-1:],\n                output_dict=output_dict,\n                num_frames=num_frames,\n                track_in_reverse=track_in_reverse,\n            )\n            # apply SAM-style segmentation head\n            # here we might feed previously predicted low-res SAM mask logits into the SAM mask decoder,\n            # e.g. in demo where such logits come from earlier interaction instead of correction sampling\n            # (in this case, any `mask_inputs` shouldn't reach here as they are sent to _use_mask_as_output instead)\n            if prev_sam_mask_logits is not None:\n                assert point_inputs is not None and mask_inputs is None\n                mask_inputs = prev_sam_mask_logits\n            multimask_output = self._use_multimask(is_init_cond_frame, point_inputs)\n            sam_outputs = self._forward_sam_heads(\n                backbone_features=pix_feat,\n                point_inputs=point_inputs,\n                mask_inputs=mask_inputs,\n                high_res_features=high_res_features,\n                multimask_output=multimask_output,\n            )\n\n        return current_out, sam_outputs, high_res_features, pix_feat\n\n    def _encode_memory_in_output(\n        self,\n        current_vision_feats,\n        feat_sizes,\n        point_inputs,\n        run_mem_encoder,\n        high_res_masks,\n        object_score_logits,\n        current_out,\n    ):\n        if run_mem_encoder and self.num_maskmem > 0:\n            high_res_masks_for_mem_enc = high_res_masks\n            maskmem_features, maskmem_pos_enc = self._encode_new_memory(\n                current_vision_feats=current_vision_feats,\n                feat_sizes=feat_sizes,\n                pred_masks_high_res=high_res_masks_for_mem_enc,\n                object_score_logits=object_score_logits,\n                is_mask_from_pts=(point_inputs is not None),\n            )\n            current_out[\"maskmem_features\"] = maskmem_features\n            current_out[\"maskmem_pos_enc\"] = maskmem_pos_enc\n        else:\n            current_out[\"maskmem_features\"] = None\n            current_out[\"maskmem_pos_enc\"] = None\n\n    def track_step(\n        self,\n        frame_idx,\n        is_init_cond_frame,\n        current_vision_feats,\n        current_vision_pos_embeds,\n        feat_sizes,\n        point_inputs,\n        mask_inputs,\n        output_dict,\n        num_frames,\n        track_in_reverse=False,  # tracking in reverse time order (for demo usage)\n        # Whether to run the memory encoder on the predicted masks. Sometimes we might want\n        # to skip the memory encoder with `run_mem_encoder=False`. For example,\n        # in demo we might call `track_step` multiple times for each user click,\n        # and only encode the memory when the user finalizes their clicks. And in ablation\n        # settings like SAM training on static images, we don't need the memory encoder.\n        run_mem_encoder=True,\n        # The previously predicted SAM mask logits (which can be fed together with new clicks in demo).\n        prev_sam_mask_logits=None,\n    ):\n        current_out, sam_outputs, _, _ = self._track_step(\n            frame_idx,\n            is_init_cond_frame,\n            current_vision_feats,\n            current_vision_pos_embeds,\n            feat_sizes,\n            point_inputs,\n            mask_inputs,\n            output_dict,\n            num_frames,\n            track_in_reverse,\n            prev_sam_mask_logits,\n        )\n\n        (\n            _,\n            _,\n            _,\n            low_res_masks,\n            high_res_masks,\n            obj_ptr,\n            object_score_logits,\n        ) = sam_outputs\n\n        current_out[\"pred_masks\"] = low_res_masks\n        current_out[\"pred_masks_high_res\"] = high_res_masks\n        current_out[\"obj_ptr\"] = obj_ptr\n        if not self.training:\n            # Only add this in inference (to avoid unused param in activation checkpointing;\n            # it's mainly used in the demo to encode spatial memories w/ consolidated masks)\n            current_out[\"object_score_logits\"] = object_score_logits\n\n        # Finally run the memory encoder on the predicted mask to encode\n        # it into a new memory feature (that can be used in future frames)\n        self._encode_memory_in_output(\n            current_vision_feats,\n            feat_sizes,\n            point_inputs,\n            run_mem_encoder,\n            high_res_masks,\n            object_score_logits,\n            current_out,\n        )\n\n        return current_out\n\n    def _use_multimask(self, is_init_cond_frame, point_inputs):\n        \"\"\"Whether to use multimask output in the SAM head.\"\"\"\n        num_pts = 0 if point_inputs is None else point_inputs[\"point_labels\"].size(1)\n        multimask_output = (\n            self.multimask_output_in_sam\n            and (is_init_cond_frame or self.multimask_output_for_tracking)\n            and (self.multimask_min_pt_num <= num_pts <= self.multimask_max_pt_num)\n        )\n        return multimask_output\n\n    def _apply_non_overlapping_constraints(self, pred_masks):\n        \"\"\"\n        Apply non-overlapping constraints to the object scores in pred_masks. Here we\n        keep only the highest scoring object at each spatial location in pred_masks.\n        \"\"\"\n        batch_size = pred_masks.size(0)\n        if batch_size == 1:\n            return pred_masks\n\n        device = pred_masks.device\n        # \"max_obj_inds\": object index of the object with the highest score at each location\n        max_obj_inds = torch.argmax(pred_masks, dim=0, keepdim=True)\n        # \"batch_obj_inds\": object index of each object slice (along dim 0) in `pred_masks`\n        batch_obj_inds = torch.arange(batch_size, device=device)[:, None, None, None]\n        keep = max_obj_inds == batch_obj_inds\n        # suppress overlapping regions' scores below -10.0 so that the foreground regions\n        # don't overlap (here sigmoid(-10.0)=4.5398e-05)\n        pred_masks = torch.where(keep, pred_masks, torch.clamp(pred_masks, max=-10.0))\n        return pred_masks\n"
  },
  {
    "path": "eval/grounded_sam/sam2/modeling/sam2_utils.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\n\nimport copy\nfrom typing import Tuple\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom sam2.utils.misc import mask_to_box\n\n\ndef select_closest_cond_frames(frame_idx, cond_frame_outputs, max_cond_frame_num):\n    \"\"\"\n    Select up to `max_cond_frame_num` conditioning frames from `cond_frame_outputs`\n    that are temporally closest to the current frame at `frame_idx`. Here, we take\n    - a) the closest conditioning frame before `frame_idx` (if any);\n    - b) the closest conditioning frame after `frame_idx` (if any);\n    - c) any other temporally closest conditioning frames until reaching a total\n         of `max_cond_frame_num` conditioning frames.\n\n    Outputs:\n    - selected_outputs: selected items (keys & values) from `cond_frame_outputs`.\n    - unselected_outputs: items (keys & values) not selected in `cond_frame_outputs`.\n    \"\"\"\n    if max_cond_frame_num == -1 or len(cond_frame_outputs) <= max_cond_frame_num:\n        selected_outputs = cond_frame_outputs\n        unselected_outputs = {}\n    else:\n        assert max_cond_frame_num >= 2, \"we should allow using 2+ conditioning frames\"\n        selected_outputs = {}\n\n        # the closest conditioning frame before `frame_idx` (if any)\n        idx_before = max((t for t in cond_frame_outputs if t < frame_idx), default=None)\n        if idx_before is not None:\n            selected_outputs[idx_before] = cond_frame_outputs[idx_before]\n\n        # the closest conditioning frame after `frame_idx` (if any)\n        idx_after = min((t for t in cond_frame_outputs if t >= frame_idx), default=None)\n        if idx_after is not None:\n            selected_outputs[idx_after] = cond_frame_outputs[idx_after]\n\n        # add other temporally closest conditioning frames until reaching a total\n        # of `max_cond_frame_num` conditioning frames.\n        num_remain = max_cond_frame_num - len(selected_outputs)\n        inds_remain = sorted(\n            (t for t in cond_frame_outputs if t not in selected_outputs),\n            key=lambda x: abs(x - frame_idx),\n        )[:num_remain]\n        selected_outputs.update((t, cond_frame_outputs[t]) for t in inds_remain)\n        unselected_outputs = {\n            t: v for t, v in cond_frame_outputs.items() if t not in selected_outputs\n        }\n\n    return selected_outputs, unselected_outputs\n\n\ndef get_1d_sine_pe(pos_inds, dim, temperature=10000):\n    \"\"\"\n    Get 1D sine positional embedding as in the original Transformer paper.\n    \"\"\"\n    pe_dim = dim // 2\n    dim_t = torch.arange(pe_dim, dtype=torch.float32, device=pos_inds.device)\n    dim_t = temperature ** (2 * (dim_t // 2) / pe_dim)\n\n    pos_embed = pos_inds.unsqueeze(-1) / dim_t\n    pos_embed = torch.cat([pos_embed.sin(), pos_embed.cos()], dim=-1)\n    return pos_embed\n\n\ndef get_activation_fn(activation):\n    \"\"\"Return an activation function given a string\"\"\"\n    if activation == \"relu\":\n        return F.relu\n    if activation == \"gelu\":\n        return F.gelu\n    if activation == \"glu\":\n        return F.glu\n    raise RuntimeError(f\"activation should be relu/gelu, not {activation}.\")\n\n\ndef get_clones(module, N):\n    return nn.ModuleList([copy.deepcopy(module) for i in range(N)])\n\n\nclass DropPath(nn.Module):\n    # adapted from https://github.com/huggingface/pytorch-image-models/blob/main/timm/layers/drop.py\n    def __init__(self, drop_prob=0.0, scale_by_keep=True):\n        super(DropPath, self).__init__()\n        self.drop_prob = drop_prob\n        self.scale_by_keep = scale_by_keep\n\n    def forward(self, x):\n        if self.drop_prob == 0.0 or not self.training:\n            return x\n        keep_prob = 1 - self.drop_prob\n        shape = (x.shape[0],) + (1,) * (x.ndim - 1)\n        random_tensor = x.new_empty(shape).bernoulli_(keep_prob)\n        if keep_prob > 0.0 and self.scale_by_keep:\n            random_tensor.div_(keep_prob)\n        return x * random_tensor\n\n\n# Lightly adapted from\n# https://github.com/facebookresearch/MaskFormer/blob/main/mask_former/modeling/transformer/transformer_predictor.py # noqa\nclass MLP(nn.Module):\n    def __init__(\n        self,\n        input_dim: int,\n        hidden_dim: int,\n        output_dim: int,\n        num_layers: int,\n        activation: nn.Module = nn.ReLU,\n        sigmoid_output: bool = False,\n    ) -> None:\n        super().__init__()\n        self.num_layers = num_layers\n        h = [hidden_dim] * (num_layers - 1)\n        self.layers = nn.ModuleList(\n            nn.Linear(n, k) for n, k in zip([input_dim] + h, h + [output_dim])\n        )\n        self.sigmoid_output = sigmoid_output\n        self.act = activation()\n\n    def forward(self, x):\n        for i, layer in enumerate(self.layers):\n            x = self.act(layer(x)) if i < self.num_layers - 1 else layer(x)\n        if self.sigmoid_output:\n            x = F.sigmoid(x)\n        return x\n\n\n# From https://github.com/facebookresearch/detectron2/blob/main/detectron2/layers/batch_norm.py # noqa\n# Itself from https://github.com/facebookresearch/ConvNeXt/blob/d1fa8f6fef0a165b27399986cc2bdacc92777e40/models/convnext.py#L119  # noqa\nclass LayerNorm2d(nn.Module):\n    def __init__(self, num_channels: int, eps: float = 1e-6) -> None:\n        super().__init__()\n        self.weight = nn.Parameter(torch.ones(num_channels))\n        self.bias = nn.Parameter(torch.zeros(num_channels))\n        self.eps = eps\n\n    def forward(self, x: torch.Tensor) -> torch.Tensor:\n        u = x.mean(1, keepdim=True)\n        s = (x - u).pow(2).mean(1, keepdim=True)\n        x = (x - u) / torch.sqrt(s + self.eps)\n        x = self.weight[:, None, None] * x + self.bias[:, None, None]\n        return x\n\n\ndef sample_box_points(\n    masks: torch.Tensor,\n    noise: float = 0.1,  # SAM default\n    noise_bound: int = 20,  # SAM default\n    top_left_label: int = 2,\n    bottom_right_label: int = 3,\n) -> Tuple[np.array, np.array]:\n    \"\"\"\n    Sample a noised version of the top left and bottom right corners of a given `bbox`\n\n    Inputs:\n    - masks: [B, 1, H,W] boxes, dtype=torch.Tensor\n    - noise: noise as a fraction of box width and height, dtype=float\n    - noise_bound: maximum amount of noise (in pure pixesl), dtype=int\n\n    Returns:\n    - box_coords: [B, num_pt, 2], contains (x, y) coordinates of top left and bottom right box corners, dtype=torch.float\n    - box_labels: [B, num_pt], label 2 is reserverd for top left and 3 for bottom right corners, dtype=torch.int32\n    \"\"\"\n    device = masks.device\n    box_coords = mask_to_box(masks)\n    B, _, H, W = masks.shape\n    box_labels = torch.tensor(\n        [top_left_label, bottom_right_label], dtype=torch.int, device=device\n    ).repeat(B)\n    if noise > 0.0:\n        if not isinstance(noise_bound, torch.Tensor):\n            noise_bound = torch.tensor(noise_bound, device=device)\n        bbox_w = box_coords[..., 2] - box_coords[..., 0]\n        bbox_h = box_coords[..., 3] - box_coords[..., 1]\n        max_dx = torch.min(bbox_w * noise, noise_bound)\n        max_dy = torch.min(bbox_h * noise, noise_bound)\n        box_noise = 2 * torch.rand(B, 1, 4, device=device) - 1\n        box_noise = box_noise * torch.stack((max_dx, max_dy, max_dx, max_dy), dim=-1)\n\n        box_coords = box_coords + box_noise\n        img_bounds = (\n            torch.tensor([W, H, W, H], device=device) - 1\n        )  # uncentered pixel coords\n        box_coords.clamp_(torch.zeros_like(img_bounds), img_bounds)  # In place clamping\n\n    box_coords = box_coords.reshape(-1, 2, 2)  # always 2 points\n    box_labels = box_labels.reshape(-1, 2)\n    return box_coords, box_labels\n\n\ndef sample_random_points_from_errors(gt_masks, pred_masks, num_pt=1):\n    \"\"\"\n    Sample `num_pt` random points (along with their labels) independently from the error regions.\n\n    Inputs:\n    - gt_masks: [B, 1, H_im, W_im] masks, dtype=torch.bool\n    - pred_masks: [B, 1, H_im, W_im] masks, dtype=torch.bool or None\n    - num_pt: int, number of points to sample independently for each of the B error maps\n\n    Outputs:\n    - points: [B, num_pt, 2], dtype=torch.float, contains (x, y) coordinates of each sampled point\n    - labels: [B, num_pt], dtype=torch.int32, where 1 means positive clicks and 0 means\n      negative clicks\n    \"\"\"\n    if pred_masks is None:  # if pred_masks is not provided, treat it as empty\n        pred_masks = torch.zeros_like(gt_masks)\n    assert gt_masks.dtype == torch.bool and gt_masks.size(1) == 1\n    assert pred_masks.dtype == torch.bool and pred_masks.shape == gt_masks.shape\n    assert num_pt >= 0\n\n    B, _, H_im, W_im = gt_masks.shape\n    device = gt_masks.device\n\n    # false positive region, a new point sampled in this region should have\n    # negative label to correct the FP error\n    fp_masks = ~gt_masks & pred_masks\n    # false negative region, a new point sampled in this region should have\n    # positive label to correct the FN error\n    fn_masks = gt_masks & ~pred_masks\n    # whether the prediction completely match the ground-truth on each mask\n    all_correct = torch.all((gt_masks == pred_masks).flatten(2), dim=2)\n    all_correct = all_correct[..., None, None]\n\n    # channel 0 is FP map, while channel 1 is FN map\n    pts_noise = torch.rand(B, num_pt, H_im, W_im, 2, device=device)\n    # sample a negative new click from FP region or a positive new click\n    # from FN region, depend on where the maximum falls,\n    # and in case the predictions are all correct (no FP or FN), we just\n    # sample a negative click from the background region\n    pts_noise[..., 0] *= fp_masks | (all_correct & ~gt_masks)\n    pts_noise[..., 1] *= fn_masks\n    pts_idx = pts_noise.flatten(2).argmax(dim=2)\n    labels = (pts_idx % 2).to(torch.int32)\n    pts_idx = pts_idx // 2\n    pts_x = pts_idx % W_im\n    pts_y = pts_idx // W_im\n    points = torch.stack([pts_x, pts_y], dim=2).to(torch.float)\n    return points, labels\n\n\ndef sample_one_point_from_error_center(gt_masks, pred_masks, padding=True):\n    \"\"\"\n    Sample 1 random point (along with its label) from the center of each error region,\n    that is, the point with the largest distance to the boundary of each error region.\n    This is the RITM sampling method from https://github.com/saic-vul/ritm_interactive_segmentation/blob/master/isegm/inference/clicker.py\n\n    Inputs:\n    - gt_masks: [B, 1, H_im, W_im] masks, dtype=torch.bool\n    - pred_masks: [B, 1, H_im, W_im] masks, dtype=torch.bool or None\n    - padding: if True, pad with boundary of 1 px for distance transform\n\n    Outputs:\n    - points: [B, 1, 2], dtype=torch.float, contains (x, y) coordinates of each sampled point\n    - labels: [B, 1], dtype=torch.int32, where 1 means positive clicks and 0 means negative clicks\n    \"\"\"\n    import cv2\n\n    if pred_masks is None:\n        pred_masks = torch.zeros_like(gt_masks)\n    assert gt_masks.dtype == torch.bool and gt_masks.size(1) == 1\n    assert pred_masks.dtype == torch.bool and pred_masks.shape == gt_masks.shape\n\n    B, _, _, W_im = gt_masks.shape\n    device = gt_masks.device\n\n    # false positive region, a new point sampled in this region should have\n    # negative label to correct the FP error\n    fp_masks = ~gt_masks & pred_masks\n    # false negative region, a new point sampled in this region should have\n    # positive label to correct the FN error\n    fn_masks = gt_masks & ~pred_masks\n\n    fp_masks = fp_masks.cpu().numpy()\n    fn_masks = fn_masks.cpu().numpy()\n    points = torch.zeros(B, 1, 2, dtype=torch.float)\n    labels = torch.ones(B, 1, dtype=torch.int32)\n    for b in range(B):\n        fn_mask = fn_masks[b, 0]\n        fp_mask = fp_masks[b, 0]\n        if padding:\n            fn_mask = np.pad(fn_mask, ((1, 1), (1, 1)), \"constant\")\n            fp_mask = np.pad(fp_mask, ((1, 1), (1, 1)), \"constant\")\n        # compute the distance of each point in FN/FP region to its boundary\n        fn_mask_dt = cv2.distanceTransform(fn_mask.astype(np.uint8), cv2.DIST_L2, 0)\n        fp_mask_dt = cv2.distanceTransform(fp_mask.astype(np.uint8), cv2.DIST_L2, 0)\n        if padding:\n            fn_mask_dt = fn_mask_dt[1:-1, 1:-1]\n            fp_mask_dt = fp_mask_dt[1:-1, 1:-1]\n\n        # take the point in FN/FP region with the largest distance to its boundary\n        fn_mask_dt_flat = fn_mask_dt.reshape(-1)\n        fp_mask_dt_flat = fp_mask_dt.reshape(-1)\n        fn_argmax = np.argmax(fn_mask_dt_flat)\n        fp_argmax = np.argmax(fp_mask_dt_flat)\n        is_positive = fn_mask_dt_flat[fn_argmax] > fp_mask_dt_flat[fp_argmax]\n        pt_idx = fn_argmax if is_positive else fp_argmax\n        points[b, 0, 0] = pt_idx % W_im  # x\n        points[b, 0, 1] = pt_idx // W_im  # y\n        labels[b, 0] = int(is_positive)\n\n    points = points.to(device)\n    labels = labels.to(device)\n    return points, labels\n\n\ndef get_next_point(gt_masks, pred_masks, method):\n    if method == \"uniform\":\n        return sample_random_points_from_errors(gt_masks, pred_masks)\n    elif method == \"center\":\n        return sample_one_point_from_error_center(gt_masks, pred_masks)\n    else:\n        raise ValueError(f\"unknown sampling method {method}\")\n"
  },
  {
    "path": "eval/grounded_sam/sam2/sam2_hiera_b+.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 112\n      num_heads: 2\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [896, 448, 224, 112]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/sam2_hiera_l.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 144\n      num_heads: 2\n      stages: [2, 6, 36, 4]\n      global_att_blocks: [23, 33, 43]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n      window_spec: [8, 4, 16, 8]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [1152, 576, 288, 144]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/sam2_hiera_s.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 96\n      num_heads: 1\n      stages: [1, 2, 11, 2]\n      global_att_blocks: [7, 10, 13]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [768, 384, 192, 96]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/sam2_hiera_t.yaml",
    "content": "# @package _global_\n\n# Model\nmodel:\n  _target_: sam2.modeling.sam2_base.SAM2Base\n  image_encoder:\n    _target_: sam2.modeling.backbones.image_encoder.ImageEncoder\n    scalp: 1\n    trunk:\n      _target_: sam2.modeling.backbones.hieradet.Hiera\n      embed_dim: 96\n      num_heads: 1\n      stages: [1, 2, 7, 2]\n      global_att_blocks: [5, 7, 9]\n      window_pos_embed_bkg_spatial_size: [7, 7]\n    neck:\n      _target_: sam2.modeling.backbones.image_encoder.FpnNeck\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 256\n        normalize: true\n        scale: null\n        temperature: 10000\n      d_model: 256\n      backbone_channel_list: [768, 384, 192, 96]\n      fpn_top_down_levels: [2, 3]  # output level 0 and 1 directly use the backbone features\n      fpn_interp_model: nearest\n\n  memory_attention:\n    _target_: sam2.modeling.memory_attention.MemoryAttention\n    d_model: 256\n    pos_enc_at_input: true\n    layer:\n      _target_: sam2.modeling.memory_attention.MemoryAttentionLayer\n      activation: relu\n      dim_feedforward: 2048\n      dropout: 0.1\n      pos_enc_at_attn: false\n      self_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n      d_model: 256\n      pos_enc_at_cross_attn_keys: true\n      pos_enc_at_cross_attn_queries: false\n      cross_attention:\n        _target_: sam2.modeling.sam.transformer.RoPEAttention\n        rope_theta: 10000.0\n        feat_sizes: [32, 32]\n        rope_k_repeat: True\n        embedding_dim: 256\n        num_heads: 1\n        downsample_rate: 1\n        dropout: 0.1\n        kv_in_dim: 64\n    num_layers: 4\n\n  memory_encoder:\n      _target_: sam2.modeling.memory_encoder.MemoryEncoder\n      out_dim: 64\n      position_encoding:\n        _target_: sam2.modeling.position_encoding.PositionEmbeddingSine\n        num_pos_feats: 64\n        normalize: true\n        scale: null\n        temperature: 10000\n      mask_downsampler:\n        _target_: sam2.modeling.memory_encoder.MaskDownSampler\n        kernel_size: 3\n        stride: 2\n        padding: 1\n      fuser:\n        _target_: sam2.modeling.memory_encoder.Fuser\n        layer:\n          _target_: sam2.modeling.memory_encoder.CXBlock\n          dim: 256\n          kernel_size: 7\n          padding: 3\n          layer_scale_init_value: 1e-6\n          use_dwconv: True  # depth-wise convs\n        num_layers: 2\n\n  num_maskmem: 7\n  image_size: 1024\n  # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask\n  # SAM decoder\n  sigmoid_scale_for_mem_enc: 20.0\n  sigmoid_bias_for_mem_enc: -10.0\n  use_mask_input_as_output_without_sam: true\n  # Memory\n  directly_add_no_mem_embed: true\n  # use high-resolution feature map in the SAM mask decoder\n  use_high_res_features_in_sam: true\n  # output 3 masks on the first click on initial conditioning frames\n  multimask_output_in_sam: true\n  # SAM heads\n  iou_prediction_use_sigmoid: True\n  # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder\n  use_obj_ptrs_in_encoder: true\n  add_tpos_enc_to_obj_ptrs: false\n  only_obj_ptrs_in_the_past_for_eval: true\n  # object occlusion prediction\n  pred_obj_scores: true\n  pred_obj_scores_mlp: true\n  fixed_no_obj_ptr: true\n  # multimask tracking settings\n  multimask_output_for_tracking: true\n  use_multimask_token_for_obj_ptr: true\n  multimask_min_pt_num: 0\n  multimask_max_pt_num: 1\n  use_mlp_for_obj_ptr_proj: true\n  # Compilation flag\n  # HieraT does not currently support compilation, should always be set to False\n  compile_image_encoder: False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/sam2_image_predictor.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport logging\n\nfrom typing import List, Optional, Tuple, Union\n\nimport numpy as np\nimport torch\nfrom PIL.Image import Image\n\nfrom sam2.modeling.sam2_base import SAM2Base\nfrom sam2.utils.transforms import SAM2Transforms\n\n\nclass SAM2ImagePredictor:\n    def __init__(\n        self,\n        sam_model: SAM2Base,\n        mask_threshold=0.0,\n        max_hole_area=0.0,\n        max_sprinkle_area=0.0,\n        **kwargs,\n    ) -> None:\n        \"\"\"\n        Uses SAM-2 to calculate the image embedding for an image, and then\n        allow repeated, efficient mask prediction given prompts.\n\n        Arguments:\n          sam_model (Sam-2): The model to use for mask prediction.\n          mask_threshold (float): The threshold to use when converting mask logits\n            to binary masks. Masks are thresholded at 0 by default.\n          max_hole_area (int): If max_hole_area > 0, we fill small holes in up to\n            the maximum area of max_hole_area in low_res_masks.\n          max_sprinkle_area (int): If max_sprinkle_area > 0, we remove small sprinkles up to\n            the maximum area of max_sprinkle_area in low_res_masks.\n        \"\"\"\n        super().__init__()\n        self.model = sam_model\n        self._transforms = SAM2Transforms(\n            resolution=self.model.image_size,\n            mask_threshold=mask_threshold,\n            max_hole_area=max_hole_area,\n            max_sprinkle_area=max_sprinkle_area,\n        )\n\n        # Predictor state\n        self._is_image_set = False\n        self._features = None\n        self._orig_hw = None\n        # Whether the predictor is set for single image or a batch of images\n        self._is_batch = False\n\n        # Predictor config\n        self.mask_threshold = mask_threshold\n\n        # Spatial dim for backbone feature maps\n        self._bb_feat_sizes = [\n            (256, 256),\n            (128, 128),\n            (64, 64),\n        ]\n\n    @classmethod\n    def from_pretrained(cls, model_id: str, **kwargs) -> \"SAM2ImagePredictor\":\n        \"\"\"\n        Load a pretrained model from the Hugging Face hub.\n\n        Arguments:\n          model_id (str): The Hugging Face repository ID.\n          **kwargs: Additional arguments to pass to the model constructor.\n\n        Returns:\n          (SAM2ImagePredictor): The loaded model.\n        \"\"\"\n        from sam2.build_sam import build_sam2_hf\n\n        sam_model = build_sam2_hf(model_id, **kwargs)\n        return cls(sam_model, **kwargs)\n\n    @torch.no_grad()\n    def set_image(\n        self,\n        image: Union[np.ndarray, Image],\n    ) -> None:\n        \"\"\"\n        Calculates the image embeddings for the provided image, allowing\n        masks to be predicted with the 'predict' method.\n\n        Arguments:\n          image (np.ndarray or PIL Image): The input image to embed in RGB format. The image should be in HWC format if np.ndarray, or WHC format if PIL Image\n          with pixel values in [0, 255].\n          image_format (str): The color format of the image, in ['RGB', 'BGR'].\n        \"\"\"\n        self.reset_predictor()\n        # Transform the image to the form expected by the model\n        if isinstance(image, np.ndarray):\n            logging.info(\"For numpy array image, we assume (HxWxC) format\")\n            self._orig_hw = [image.shape[:2]]\n        elif isinstance(image, Image):\n            w, h = image.size\n            self._orig_hw = [(h, w)]\n        else:\n            raise NotImplementedError(\"Image format not supported\")\n\n        input_image = self._transforms(image)\n        input_image = input_image[None, ...].to(self.device)\n\n        assert (\n            len(input_image.shape) == 4 and input_image.shape[1] == 3\n        ), f\"input_image must be of size 1x3xHxW, got {input_image.shape}\"\n        logging.info(\"Computing image embeddings for the provided image...\")\n        backbone_out = self.model.forward_image(input_image)\n        _, vision_feats, _, _ = self.model._prepare_backbone_features(backbone_out)\n        # Add no_mem_embed, which is added to the lowest rest feat. map during training on videos\n        if self.model.directly_add_no_mem_embed:\n            vision_feats[-1] = vision_feats[-1] + self.model.no_mem_embed\n\n        feats = [\n            feat.permute(1, 2, 0).view(1, -1, *feat_size)\n            for feat, feat_size in zip(vision_feats[::-1], self._bb_feat_sizes[::-1])\n        ][::-1]\n        self._features = {\"image_embed\": feats[-1], \"high_res_feats\": feats[:-1]}\n        self._is_image_set = True\n        logging.info(\"Image embeddings computed.\")\n\n    @torch.no_grad()\n    def set_image_batch(\n        self,\n        image_list: List[Union[np.ndarray]],\n    ) -> None:\n        \"\"\"\n        Calculates the image embeddings for the provided image batch, allowing\n        masks to be predicted with the 'predict_batch' method.\n\n        Arguments:\n          image_list (List[np.ndarray]): The input images to embed in RGB format. The image should be in HWC format if np.ndarray\n          with pixel values in [0, 255].\n        \"\"\"\n        self.reset_predictor()\n        assert isinstance(image_list, list)\n        self._orig_hw = []\n        for image in image_list:\n            assert isinstance(\n                image, np.ndarray\n            ), \"Images are expected to be an np.ndarray in RGB format, and of shape  HWC\"\n            self._orig_hw.append(image.shape[:2])\n        # Transform the image to the form expected by the model\n        img_batch = self._transforms.forward_batch(image_list)\n        img_batch = img_batch.to(self.device)\n        batch_size = img_batch.shape[0]\n        assert (\n            len(img_batch.shape) == 4 and img_batch.shape[1] == 3\n        ), f\"img_batch must be of size Bx3xHxW, got {img_batch.shape}\"\n        logging.info(\"Computing image embeddings for the provided images...\")\n        backbone_out = self.model.forward_image(img_batch)\n        _, vision_feats, _, _ = self.model._prepare_backbone_features(backbone_out)\n        # Add no_mem_embed, which is added to the lowest rest feat. map during training on videos\n        if self.model.directly_add_no_mem_embed:\n            vision_feats[-1] = vision_feats[-1] + self.model.no_mem_embed\n\n        feats = [\n            feat.permute(1, 2, 0).view(batch_size, -1, *feat_size)\n            for feat, feat_size in zip(vision_feats[::-1], self._bb_feat_sizes[::-1])\n        ][::-1]\n        self._features = {\"image_embed\": feats[-1], \"high_res_feats\": feats[:-1]}\n        self._is_image_set = True\n        self._is_batch = True\n        logging.info(\"Image embeddings computed.\")\n\n    def predict_batch(\n        self,\n        point_coords_batch: List[np.ndarray] = None,\n        point_labels_batch: List[np.ndarray] = None,\n        box_batch: List[np.ndarray] = None,\n        mask_input_batch: List[np.ndarray] = None,\n        multimask_output: bool = True,\n        return_logits: bool = False,\n        normalize_coords=True,\n    ) -> Tuple[List[np.ndarray], List[np.ndarray], List[np.ndarray]]:\n        \"\"\"This function is very similar to predict(...), however it is used for batched mode, when the model is expected to generate predictions on multiple images.\n        It returns a tuple of lists of masks, ious, and low_res_masks_logits.\n        \"\"\"\n        assert self._is_batch, \"This function should only be used when in batched mode\"\n        if not self._is_image_set:\n            raise RuntimeError(\n                \"An image must be set with .set_image_batch(...) before mask prediction.\"\n            )\n        num_images = len(self._features[\"image_embed\"])\n        all_masks = []\n        all_ious = []\n        all_low_res_masks = []\n        for img_idx in range(num_images):\n            # Transform input prompts\n            point_coords = (\n                point_coords_batch[img_idx] if point_coords_batch is not None else None\n            )\n            point_labels = (\n                point_labels_batch[img_idx] if point_labels_batch is not None else None\n            )\n            box = box_batch[img_idx] if box_batch is not None else None\n            mask_input = (\n                mask_input_batch[img_idx] if mask_input_batch is not None else None\n            )\n            mask_input, unnorm_coords, labels, unnorm_box = self._prep_prompts(\n                point_coords,\n                point_labels,\n                box,\n                mask_input,\n                normalize_coords,\n                img_idx=img_idx,\n            )\n            masks, iou_predictions, low_res_masks = self._predict(\n                unnorm_coords,\n                labels,\n                unnorm_box,\n                mask_input,\n                multimask_output,\n                return_logits=return_logits,\n                img_idx=img_idx,\n            )\n            masks_np = masks.squeeze(0).float().detach().cpu().numpy()\n            iou_predictions_np = (\n                iou_predictions.squeeze(0).float().detach().cpu().numpy()\n            )\n            low_res_masks_np = low_res_masks.squeeze(0).float().detach().cpu().numpy()\n            all_masks.append(masks_np)\n            all_ious.append(iou_predictions_np)\n            all_low_res_masks.append(low_res_masks_np)\n\n        return all_masks, all_ious, all_low_res_masks\n\n    def predict(\n        self,\n        point_coords: Optional[np.ndarray] = None,\n        point_labels: Optional[np.ndarray] = None,\n        box: Optional[np.ndarray] = None,\n        mask_input: Optional[np.ndarray] = None,\n        multimask_output: bool = True,\n        return_logits: bool = False,\n        normalize_coords=True,\n    ) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:\n        \"\"\"\n        Predict masks for the given input prompts, using the currently set image.\n\n        Arguments:\n          point_coords (np.ndarray or None): A Nx2 array of point prompts to the\n            model. Each point is in (X,Y) in pixels.\n          point_labels (np.ndarray or None): A length N array of labels for the\n            point prompts. 1 indicates a foreground point and 0 indicates a\n            background point.\n          box (np.ndarray or None): A length 4 array given a box prompt to the\n            model, in XYXY format.\n          mask_input (np.ndarray): A low resolution mask input to the model, typically\n            coming from a previous prediction iteration. Has form 1xHxW, where\n            for SAM, H=W=256.\n          multimask_output (bool): If true, the model will return three masks.\n            For ambiguous input prompts (such as a single click), this will often\n            produce better masks than a single prediction. If only a single\n            mask is needed, the model's predicted quality score can be used\n            to select the best mask. For non-ambiguous prompts, such as multiple\n            input prompts, multimask_output=False can give better results.\n          return_logits (bool): If true, returns un-thresholded masks logits\n            instead of a binary mask.\n          normalize_coords (bool): If true, the point coordinates will be normalized to the range [0,1] and point_coords is expected to be wrt. image dimensions.\n\n        Returns:\n          (np.ndarray): The output masks in CxHxW format, where C is the\n            number of masks, and (H, W) is the original image size.\n          (np.ndarray): An array of length C containing the model's\n            predictions for the quality of each mask.\n          (np.ndarray): An array of shape CxHxW, where C is the number\n            of masks and H=W=256. These low resolution logits can be passed to\n            a subsequent iteration as mask input.\n        \"\"\"\n        if not self._is_image_set:\n            raise RuntimeError(\n                \"An image must be set with .set_image(...) before mask prediction.\"\n            )\n\n        # Transform input prompts\n\n        mask_input, unnorm_coords, labels, unnorm_box = self._prep_prompts(\n            point_coords, point_labels, box, mask_input, normalize_coords\n        )\n\n        masks, iou_predictions, low_res_masks = self._predict(\n            unnorm_coords,\n            labels,\n            unnorm_box,\n            mask_input,\n            multimask_output,\n            return_logits=return_logits,\n        )\n\n        masks_np = masks.squeeze(0).float().detach().cpu().numpy()\n        iou_predictions_np = iou_predictions.squeeze(0).float().detach().cpu().numpy()\n        low_res_masks_np = low_res_masks.squeeze(0).float().detach().cpu().numpy()\n        return masks_np, iou_predictions_np, low_res_masks_np\n\n    def _prep_prompts(\n        self, point_coords, point_labels, box, mask_logits, normalize_coords, img_idx=-1\n    ):\n\n        unnorm_coords, labels, unnorm_box, mask_input = None, None, None, None\n        if point_coords is not None:\n            assert (\n                point_labels is not None\n            ), \"point_labels must be supplied if point_coords is supplied.\"\n            point_coords = torch.as_tensor(\n                point_coords, dtype=torch.float, device=self.device\n            )\n            unnorm_coords = self._transforms.transform_coords(\n                point_coords, normalize=normalize_coords, orig_hw=self._orig_hw[img_idx]\n            )\n            labels = torch.as_tensor(point_labels, dtype=torch.int, device=self.device)\n            if len(unnorm_coords.shape) == 2:\n                unnorm_coords, labels = unnorm_coords[None, ...], labels[None, ...]\n        if box is not None:\n            box = torch.as_tensor(box, dtype=torch.float, device=self.device)\n            unnorm_box = self._transforms.transform_boxes(\n                box, normalize=normalize_coords, orig_hw=self._orig_hw[img_idx]\n            )  # Bx2x2\n        if mask_logits is not None:\n            mask_input = torch.as_tensor(\n                mask_logits, dtype=torch.float, device=self.device\n            )\n            if len(mask_input.shape) == 3:\n                mask_input = mask_input[None, :, :, :]\n        return mask_input, unnorm_coords, labels, unnorm_box\n\n    @torch.no_grad()\n    def _predict(\n        self,\n        point_coords: Optional[torch.Tensor],\n        point_labels: Optional[torch.Tensor],\n        boxes: Optional[torch.Tensor] = None,\n        mask_input: Optional[torch.Tensor] = None,\n        multimask_output: bool = True,\n        return_logits: bool = False,\n        img_idx: int = -1,\n    ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:\n        \"\"\"\n        Predict masks for the given input prompts, using the currently set image.\n        Input prompts are batched torch tensors and are expected to already be\n        transformed to the input frame using SAM2Transforms.\n\n        Arguments:\n          point_coords (torch.Tensor or None): A BxNx2 array of point prompts to the\n            model. Each point is in (X,Y) in pixels.\n          point_labels (torch.Tensor or None): A BxN array of labels for the\n            point prompts. 1 indicates a foreground point and 0 indicates a\n            background point.\n          boxes (np.ndarray or None): A Bx4 array given a box prompt to the\n            model, in XYXY format.\n          mask_input (np.ndarray): A low resolution mask input to the model, typically\n            coming from a previous prediction iteration. Has form Bx1xHxW, where\n            for SAM, H=W=256. Masks returned by a previous iteration of the\n            predict method do not need further transformation.\n          multimask_output (bool): If true, the model will return three masks.\n            For ambiguous input prompts (such as a single click), this will often\n            produce better masks than a single prediction. If only a single\n            mask is needed, the model's predicted quality score can be used\n            to select the best mask. For non-ambiguous prompts, such as multiple\n            input prompts, multimask_output=False can give better results.\n          return_logits (bool): If true, returns un-thresholded masks logits\n            instead of a binary mask.\n\n        Returns:\n          (torch.Tensor): The output masks in BxCxHxW format, where C is the\n            number of masks, and (H, W) is the original image size.\n          (torch.Tensor): An array of shape BxC containing the model's\n            predictions for the quality of each mask.\n          (torch.Tensor): An array of shape BxCxHxW, where C is the number\n            of masks and H=W=256. These low res logits can be passed to\n            a subsequent iteration as mask input.\n        \"\"\"\n        if not self._is_image_set:\n            raise RuntimeError(\n                \"An image must be set with .set_image(...) before mask prediction.\"\n            )\n\n        if point_coords is not None:\n            concat_points = (point_coords, point_labels)\n        else:\n            concat_points = None\n\n        # Embed prompts\n        if boxes is not None:\n            box_coords = boxes.reshape(-1, 2, 2)\n            box_labels = torch.tensor([[2, 3]], dtype=torch.int, device=boxes.device)\n            box_labels = box_labels.repeat(boxes.size(0), 1)\n            # we merge \"boxes\" and \"points\" into a single \"concat_points\" input (where\n            # boxes are added at the beginning) to sam_prompt_encoder\n            if concat_points is not None:\n                concat_coords = torch.cat([box_coords, concat_points[0]], dim=1)\n                concat_labels = torch.cat([box_labels, concat_points[1]], dim=1)\n                concat_points = (concat_coords, concat_labels)\n            else:\n                concat_points = (box_coords, box_labels)\n\n        sparse_embeddings, dense_embeddings = self.model.sam_prompt_encoder(\n            points=concat_points,\n            boxes=None,\n            masks=mask_input,\n        )\n\n        # Predict masks\n        batched_mode = (\n            concat_points is not None and concat_points[0].shape[0] > 1\n        )  # multi object prediction\n        high_res_features = [\n            feat_level[img_idx].unsqueeze(0)\n            for feat_level in self._features[\"high_res_feats\"]\n        ]\n        low_res_masks, iou_predictions, _, _ = self.model.sam_mask_decoder(\n            image_embeddings=self._features[\"image_embed\"][img_idx].unsqueeze(0),\n            image_pe=self.model.sam_prompt_encoder.get_dense_pe(),\n            sparse_prompt_embeddings=sparse_embeddings,\n            dense_prompt_embeddings=dense_embeddings,\n            multimask_output=multimask_output,\n            repeat_image=batched_mode,\n            high_res_features=high_res_features,\n        )\n\n        # Upscale the masks to the original image resolution\n        masks = self._transforms.postprocess_masks(\n            low_res_masks, self._orig_hw[img_idx]\n        )\n        low_res_masks = torch.clamp(low_res_masks, -32.0, 32.0)\n        if not return_logits:\n            masks = masks > self.mask_threshold\n\n        return masks, iou_predictions, low_res_masks\n\n    def get_image_embedding(self) -> torch.Tensor:\n        \"\"\"\n        Returns the image embeddings for the currently set image, with\n        shape 1xCxHxW, where C is the embedding dimension and (H,W) are\n        the embedding spatial dimension of SAM (typically C=256, H=W=64).\n        \"\"\"\n        if not self._is_image_set:\n            raise RuntimeError(\n                \"An image must be set with .set_image(...) to generate an embedding.\"\n            )\n        assert (\n            self._features is not None\n        ), \"Features must exist if an image has been set.\"\n        return self._features[\"image_embed\"]\n\n    @property\n    def device(self) -> torch.device:\n        return self.model.device\n\n    def reset_predictor(self) -> None:\n        \"\"\"\n        Resets the image embeddings and other state variables.\n        \"\"\"\n        self._is_image_set = False\n        self._features = None\n        self._orig_hw = None\n        self._is_batch = False\n"
  },
  {
    "path": "eval/grounded_sam/sam2/sam2_video_predictor.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport warnings\nfrom collections import OrderedDict\n\nimport torch\n\nfrom tqdm import tqdm\n\nfrom sam2.modeling.sam2_base import NO_OBJ_SCORE, SAM2Base\nfrom sam2.utils.misc import concat_points, fill_holes_in_mask_scores, load_video_frames\n\n\nclass SAM2VideoPredictor(SAM2Base):\n    \"\"\"The predictor class to handle user interactions and manage inference states.\"\"\"\n\n    def __init__(\n        self,\n        fill_hole_area=0,\n        # whether to apply non-overlapping constraints on the output object masks\n        non_overlap_masks=False,\n        # whether to clear non-conditioning memory of the surrounding frames (which may contain outdated information) after adding correction clicks;\n        # note that this would only apply to *single-object tracking* unless `clear_non_cond_mem_for_multi_obj` is also set to True)\n        clear_non_cond_mem_around_input=False,\n        # whether to also clear non-conditioning memory of the surrounding frames (only effective when `clear_non_cond_mem_around_input` is True).\n        clear_non_cond_mem_for_multi_obj=False,\n        # if `add_all_frames_to_correct_as_cond` is True, we also append to the conditioning frame list any frame that receives a later correction click\n        # if `add_all_frames_to_correct_as_cond` is False, we conditioning frame list to only use those initial conditioning frames\n        add_all_frames_to_correct_as_cond=False,\n        **kwargs,\n    ):\n        super().__init__(**kwargs)\n        self.fill_hole_area = fill_hole_area\n        self.non_overlap_masks = non_overlap_masks\n        self.clear_non_cond_mem_around_input = clear_non_cond_mem_around_input\n        self.clear_non_cond_mem_for_multi_obj = clear_non_cond_mem_for_multi_obj\n        self.add_all_frames_to_correct_as_cond = add_all_frames_to_correct_as_cond\n\n    @torch.inference_mode()\n    def init_state(\n        self,\n        video_path,\n        offload_video_to_cpu=False,\n        offload_state_to_cpu=False,\n        async_loading_frames=False,\n    ):\n        \"\"\"Initialize an inference state.\"\"\"\n        compute_device = self.device  # device of the model\n        images, video_height, video_width = load_video_frames(\n            video_path=video_path,\n            image_size=self.image_size,\n            offload_video_to_cpu=offload_video_to_cpu,\n            async_loading_frames=async_loading_frames,\n            compute_device=compute_device,\n        )\n        inference_state = {}\n        inference_state[\"images\"] = images\n        inference_state[\"num_frames\"] = len(images)\n        # whether to offload the video frames to CPU memory\n        # turning on this option saves the GPU memory with only a very small overhead\n        inference_state[\"offload_video_to_cpu\"] = offload_video_to_cpu\n        # whether to offload the inference state to CPU memory\n        # turning on this option saves the GPU memory at the cost of a lower tracking fps\n        # (e.g. in a test case of 768x768 model, fps dropped from 27 to 24 when tracking one object\n        # and from 24 to 21 when tracking two objects)\n        inference_state[\"offload_state_to_cpu\"] = offload_state_to_cpu\n        # the original video height and width, used for resizing final output scores\n        inference_state[\"video_height\"] = video_height\n        inference_state[\"video_width\"] = video_width\n        inference_state[\"device\"] = compute_device\n        if offload_state_to_cpu:\n            inference_state[\"storage_device\"] = torch.device(\"cpu\")\n        else:\n            inference_state[\"storage_device\"] = compute_device\n        # inputs on each frame\n        inference_state[\"point_inputs_per_obj\"] = {}\n        inference_state[\"mask_inputs_per_obj\"] = {}\n        # visual features on a small number of recently visited frames for quick interactions\n        inference_state[\"cached_features\"] = {}\n        # values that don't change across frames (so we only need to hold one copy of them)\n        inference_state[\"constants\"] = {}\n        # mapping between client-side object id and model-side object index\n        inference_state[\"obj_id_to_idx\"] = OrderedDict()\n        inference_state[\"obj_idx_to_id\"] = OrderedDict()\n        inference_state[\"obj_ids\"] = []\n        # A storage to hold the model's tracking results and states on each frame\n        inference_state[\"output_dict\"] = {\n            \"cond_frame_outputs\": {},  # dict containing {frame_idx: <out>}\n            \"non_cond_frame_outputs\": {},  # dict containing {frame_idx: <out>}\n        }\n        # Slice (view) of each object tracking results, sharing the same memory with \"output_dict\"\n        inference_state[\"output_dict_per_obj\"] = {}\n        # A temporary storage to hold new outputs when user interact with a frame\n        # to add clicks or mask (it's merged into \"output_dict\" before propagation starts)\n        inference_state[\"temp_output_dict_per_obj\"] = {}\n        # Frames that already holds consolidated outputs from click or mask inputs\n        # (we directly use their consolidated outputs during tracking)\n        inference_state[\"consolidated_frame_inds\"] = {\n            \"cond_frame_outputs\": set(),  # set containing frame indices\n            \"non_cond_frame_outputs\": set(),  # set containing frame indices\n        }\n        # metadata for each tracking frame (e.g. which direction it's tracked)\n        inference_state[\"tracking_has_started\"] = False\n        inference_state[\"frames_already_tracked\"] = {}\n        # Warm up the visual backbone and cache the image feature on frame 0\n        self._get_image_feature(inference_state, frame_idx=0, batch_size=1)\n        return inference_state\n\n    @classmethod\n    def from_pretrained(cls, model_id: str, **kwargs) -> \"SAM2VideoPredictor\":\n        \"\"\"\n        Load a pretrained model from the Hugging Face hub.\n\n        Arguments:\n          model_id (str): The Hugging Face repository ID.\n          **kwargs: Additional arguments to pass to the model constructor.\n\n        Returns:\n          (SAM2VideoPredictor): The loaded model.\n        \"\"\"\n        from sam2.build_sam import build_sam2_video_predictor_hf\n\n        sam_model = build_sam2_video_predictor_hf(model_id, **kwargs)\n        return sam_model\n\n    def _obj_id_to_idx(self, inference_state, obj_id):\n        \"\"\"Map client-side object id to model-side object index.\"\"\"\n        obj_idx = inference_state[\"obj_id_to_idx\"].get(obj_id, None)\n        if obj_idx is not None:\n            return obj_idx\n\n        # This is a new object id not sent to the server before. We only allow adding\n        # new objects *before* the tracking starts.\n        allow_new_object = not inference_state[\"tracking_has_started\"]\n        if allow_new_object:\n            # get the next object slot\n            obj_idx = len(inference_state[\"obj_id_to_idx\"])\n            inference_state[\"obj_id_to_idx\"][obj_id] = obj_idx\n            inference_state[\"obj_idx_to_id\"][obj_idx] = obj_id\n            inference_state[\"obj_ids\"] = list(inference_state[\"obj_id_to_idx\"])\n            # set up input and output structures for this object\n            inference_state[\"point_inputs_per_obj\"][obj_idx] = {}\n            inference_state[\"mask_inputs_per_obj\"][obj_idx] = {}\n            inference_state[\"output_dict_per_obj\"][obj_idx] = {\n                \"cond_frame_outputs\": {},  # dict containing {frame_idx: <out>}\n                \"non_cond_frame_outputs\": {},  # dict containing {frame_idx: <out>}\n            }\n            inference_state[\"temp_output_dict_per_obj\"][obj_idx] = {\n                \"cond_frame_outputs\": {},  # dict containing {frame_idx: <out>}\n                \"non_cond_frame_outputs\": {},  # dict containing {frame_idx: <out>}\n            }\n            return obj_idx\n        else:\n            raise RuntimeError(\n                f\"Cannot add new object id {obj_id} after tracking starts. \"\n                f\"All existing object ids: {inference_state['obj_ids']}. \"\n                f\"Please call 'reset_state' to restart from scratch.\"\n            )\n\n    def _obj_idx_to_id(self, inference_state, obj_idx):\n        \"\"\"Map model-side object index to client-side object id.\"\"\"\n        return inference_state[\"obj_idx_to_id\"][obj_idx]\n\n    def _get_obj_num(self, inference_state):\n        \"\"\"Get the total number of unique object ids received so far in this session.\"\"\"\n        return len(inference_state[\"obj_idx_to_id\"])\n\n    @torch.inference_mode()\n    def add_new_points_or_box(\n        self,\n        inference_state,\n        frame_idx,\n        obj_id,\n        points=None,\n        labels=None,\n        clear_old_points=True,\n        normalize_coords=True,\n        box=None,\n    ):\n        \"\"\"Add new points to a frame.\"\"\"\n        obj_idx = self._obj_id_to_idx(inference_state, obj_id)\n        point_inputs_per_frame = inference_state[\"point_inputs_per_obj\"][obj_idx]\n        mask_inputs_per_frame = inference_state[\"mask_inputs_per_obj\"][obj_idx]\n\n        if (points is not None) != (labels is not None):\n            raise ValueError(\"points and labels must be provided together\")\n        if points is None and box is None:\n            raise ValueError(\"at least one of points or box must be provided as input\")\n\n        if points is None:\n            points = torch.zeros(0, 2, dtype=torch.float32)\n        elif not isinstance(points, torch.Tensor):\n            points = torch.tensor(points, dtype=torch.float32)\n        if labels is None:\n            labels = torch.zeros(0, dtype=torch.int32)\n        elif not isinstance(labels, torch.Tensor):\n            labels = torch.tensor(labels, dtype=torch.int32)\n        if points.dim() == 2:\n            points = points.unsqueeze(0)  # add batch dimension\n        if labels.dim() == 1:\n            labels = labels.unsqueeze(0)  # add batch dimension\n\n        # If `box` is provided, we add it as the first two points with labels 2 and 3\n        # along with the user-provided points (consistent with how SAM 2 is trained).\n        if box is not None:\n            if not clear_old_points:\n                raise ValueError(\n                    \"cannot add box without clearing old points, since \"\n                    \"box prompt must be provided before any point prompt \"\n                    \"(please use clear_old_points=True instead)\"\n                )\n            if inference_state[\"tracking_has_started\"]:\n                warnings.warn(\n                    \"You are adding a box after tracking starts. SAM 2 may not always be \"\n                    \"able to incorporate a box prompt for *refinement*. If you intend to \"\n                    \"use box prompt as an *initial* input before tracking, please call \"\n                    \"'reset_state' on the inference state to restart from scratch.\",\n                    category=UserWarning,\n                    stacklevel=2,\n                )\n            if not isinstance(box, torch.Tensor):\n                box = torch.tensor(box, dtype=torch.float32, device=points.device)\n            box_coords = box.reshape(1, 2, 2)\n            box_labels = torch.tensor([2, 3], dtype=torch.int32, device=labels.device)\n            box_labels = box_labels.reshape(1, 2)\n            points = torch.cat([box_coords, points], dim=1)\n            labels = torch.cat([box_labels, labels], dim=1)\n\n        if normalize_coords:\n            video_H = inference_state[\"video_height\"]\n            video_W = inference_state[\"video_width\"]\n            points = points / torch.tensor([video_W, video_H]).to(points.device)\n        # scale the (normalized) coordinates by the model's internal image size\n        points = points * self.image_size\n        points = points.to(inference_state[\"device\"])\n        labels = labels.to(inference_state[\"device\"])\n\n        if not clear_old_points:\n            point_inputs = point_inputs_per_frame.get(frame_idx, None)\n        else:\n            point_inputs = None\n        point_inputs = concat_points(point_inputs, points, labels)\n\n        point_inputs_per_frame[frame_idx] = point_inputs\n        mask_inputs_per_frame.pop(frame_idx, None)\n        # If this frame hasn't been tracked before, we treat it as an initial conditioning\n        # frame, meaning that the inputs points are to generate segments on this frame without\n        # using any memory from other frames, like in SAM. Otherwise (if it has been tracked),\n        # the input points will be used to correct the already tracked masks.\n        is_init_cond_frame = frame_idx not in inference_state[\"frames_already_tracked\"]\n        # whether to track in reverse time order\n        if is_init_cond_frame:\n            reverse = False\n        else:\n            reverse = inference_state[\"frames_already_tracked\"][frame_idx][\"reverse\"]\n        obj_output_dict = inference_state[\"output_dict_per_obj\"][obj_idx]\n        obj_temp_output_dict = inference_state[\"temp_output_dict_per_obj\"][obj_idx]\n        # Add a frame to conditioning output if it's an initial conditioning frame or\n        # if the model sees all frames receiving clicks/mask as conditioning frames.\n        is_cond = is_init_cond_frame or self.add_all_frames_to_correct_as_cond\n        storage_key = \"cond_frame_outputs\" if is_cond else \"non_cond_frame_outputs\"\n\n        # Get any previously predicted mask logits on this object and feed it along with\n        # the new clicks into the SAM mask decoder.\n        prev_sam_mask_logits = None\n        # lookup temporary output dict first, which contains the most recent output\n        # (if not found, then lookup conditioning and non-conditioning frame output)\n        prev_out = obj_temp_output_dict[storage_key].get(frame_idx)\n        if prev_out is None:\n            prev_out = obj_output_dict[\"cond_frame_outputs\"].get(frame_idx)\n            if prev_out is None:\n                prev_out = obj_output_dict[\"non_cond_frame_outputs\"].get(frame_idx)\n\n        if prev_out is not None and prev_out[\"pred_masks\"] is not None:\n            device = inference_state[\"device\"]\n            prev_sam_mask_logits = prev_out[\"pred_masks\"].to(device, non_blocking=True)\n            # Clamp the scale of prev_sam_mask_logits to avoid rare numerical issues.\n            prev_sam_mask_logits = torch.clamp(prev_sam_mask_logits, -32.0, 32.0)\n        current_out, _ = self._run_single_frame_inference(\n            inference_state=inference_state,\n            output_dict=obj_output_dict,  # run on the slice of a single object\n            frame_idx=frame_idx,\n            batch_size=1,  # run on the slice of a single object\n            is_init_cond_frame=is_init_cond_frame,\n            point_inputs=point_inputs,\n            mask_inputs=None,\n            reverse=reverse,\n            # Skip the memory encoder when adding clicks or mask. We execute the memory encoder\n            # at the beginning of `propagate_in_video` (after user finalize their clicks). This\n            # allows us to enforce non-overlapping constraints on all objects before encoding\n            # them into memory.\n            run_mem_encoder=False,\n            prev_sam_mask_logits=prev_sam_mask_logits,\n        )\n        # Add the output to the output dict (to be used as future memory)\n        obj_temp_output_dict[storage_key][frame_idx] = current_out\n\n        # Resize the output mask to the original video resolution\n        obj_ids = inference_state[\"obj_ids\"]\n        consolidated_out = self._consolidate_temp_output_across_obj(\n            inference_state,\n            frame_idx,\n            is_cond=is_cond,\n            run_mem_encoder=False,\n            consolidate_at_video_res=True,\n        )\n        _, video_res_masks = self._get_orig_video_res_output(\n            inference_state, consolidated_out[\"pred_masks_video_res\"]\n        )\n        return frame_idx, obj_ids, video_res_masks\n\n    def add_new_points(self, *args, **kwargs):\n        \"\"\"Deprecated method. Please use `add_new_points_or_box` instead.\"\"\"\n        return self.add_new_points_or_box(*args, **kwargs)\n\n    @torch.inference_mode()\n    def add_new_mask(\n        self,\n        inference_state,\n        frame_idx,\n        obj_id,\n        mask,\n    ):\n        \"\"\"Add new mask to a frame.\"\"\"\n        obj_idx = self._obj_id_to_idx(inference_state, obj_id)\n        point_inputs_per_frame = inference_state[\"point_inputs_per_obj\"][obj_idx]\n        mask_inputs_per_frame = inference_state[\"mask_inputs_per_obj\"][obj_idx]\n\n        if not isinstance(mask, torch.Tensor):\n            mask = torch.tensor(mask, dtype=torch.bool)\n        assert mask.dim() == 2\n        mask_H, mask_W = mask.shape\n        mask_inputs_orig = mask[None, None]  # add batch and channel dimension\n        mask_inputs_orig = mask_inputs_orig.float().to(inference_state[\"device\"])\n\n        # resize the mask if it doesn't match the model's image size\n        if mask_H != self.image_size or mask_W != self.image_size:\n            mask_inputs = torch.nn.functional.interpolate(\n                mask_inputs_orig,\n                size=(self.image_size, self.image_size),\n                align_corners=False,\n                mode=\"bilinear\",\n                antialias=True,  # use antialias for downsampling\n            )\n            mask_inputs = (mask_inputs >= 0.5).float()\n        else:\n            mask_inputs = mask_inputs_orig\n\n        mask_inputs_per_frame[frame_idx] = mask_inputs\n        point_inputs_per_frame.pop(frame_idx, None)\n        # If this frame hasn't been tracked before, we treat it as an initial conditioning\n        # frame, meaning that the inputs points are to generate segments on this frame without\n        # using any memory from other frames, like in SAM. Otherwise (if it has been tracked),\n        # the input points will be used to correct the already tracked masks.\n        is_init_cond_frame = frame_idx not in inference_state[\"frames_already_tracked\"]\n        # whether to track in reverse time order\n        if is_init_cond_frame:\n            reverse = False\n        else:\n            reverse = inference_state[\"frames_already_tracked\"][frame_idx][\"reverse\"]\n        obj_output_dict = inference_state[\"output_dict_per_obj\"][obj_idx]\n        obj_temp_output_dict = inference_state[\"temp_output_dict_per_obj\"][obj_idx]\n        # Add a frame to conditioning output if it's an initial conditioning frame or\n        # if the model sees all frames receiving clicks/mask as conditioning frames.\n        is_cond = is_init_cond_frame or self.add_all_frames_to_correct_as_cond\n        storage_key = \"cond_frame_outputs\" if is_cond else \"non_cond_frame_outputs\"\n\n        current_out, _ = self._run_single_frame_inference(\n            inference_state=inference_state,\n            output_dict=obj_output_dict,  # run on the slice of a single object\n            frame_idx=frame_idx,\n            batch_size=1,  # run on the slice of a single object\n            is_init_cond_frame=is_init_cond_frame,\n            point_inputs=None,\n            mask_inputs=mask_inputs,\n            reverse=reverse,\n            # Skip the memory encoder when adding clicks or mask. We execute the memory encoder\n            # at the beginning of `propagate_in_video` (after user finalize their clicks). This\n            # allows us to enforce non-overlapping constraints on all objects before encoding\n            # them into memory.\n            run_mem_encoder=False,\n        )\n        # Add the output to the output dict (to be used as future memory)\n        obj_temp_output_dict[storage_key][frame_idx] = current_out\n\n        # Resize the output mask to the original video resolution\n        obj_ids = inference_state[\"obj_ids\"]\n        consolidated_out = self._consolidate_temp_output_across_obj(\n            inference_state,\n            frame_idx,\n            is_cond=is_cond,\n            run_mem_encoder=False,\n            consolidate_at_video_res=True,\n        )\n        _, video_res_masks = self._get_orig_video_res_output(\n            inference_state, consolidated_out[\"pred_masks_video_res\"]\n        )\n        return frame_idx, obj_ids, video_res_masks\n\n    def _get_orig_video_res_output(self, inference_state, any_res_masks):\n        \"\"\"\n        Resize the object scores to the original video resolution (video_res_masks)\n        and apply non-overlapping constraints for final output.\n        \"\"\"\n        device = inference_state[\"device\"]\n        video_H = inference_state[\"video_height\"]\n        video_W = inference_state[\"video_width\"]\n        any_res_masks = any_res_masks.to(device, non_blocking=True)\n        if any_res_masks.shape[-2:] == (video_H, video_W):\n            video_res_masks = any_res_masks\n        else:\n            video_res_masks = torch.nn.functional.interpolate(\n                any_res_masks,\n                size=(video_H, video_W),\n                mode=\"bilinear\",\n                align_corners=False,\n            )\n        if self.non_overlap_masks:\n            video_res_masks = self._apply_non_overlapping_constraints(video_res_masks)\n        return any_res_masks, video_res_masks\n\n    def _consolidate_temp_output_across_obj(\n        self,\n        inference_state,\n        frame_idx,\n        is_cond,\n        run_mem_encoder,\n        consolidate_at_video_res=False,\n    ):\n        \"\"\"\n        Consolidate the per-object temporary outputs in `temp_output_dict_per_obj` on\n        a frame into a single output for all objects, including\n        1) fill any missing objects either from `output_dict_per_obj` (if they exist in\n           `output_dict_per_obj` for this frame) or leave them as placeholder values\n           (if they don't exist in `output_dict_per_obj` for this frame);\n        2) if specified, rerun memory encoder after apply non-overlapping constraints\n           on the object scores.\n        \"\"\"\n        batch_size = self._get_obj_num(inference_state)\n        storage_key = \"cond_frame_outputs\" if is_cond else \"non_cond_frame_outputs\"\n        # Optionally, we allow consolidating the temporary outputs at the original\n        # video resolution (to provide a better editing experience for mask prompts).\n        if consolidate_at_video_res:\n            assert not run_mem_encoder, \"memory encoder cannot run at video resolution\"\n            consolidated_H = inference_state[\"video_height\"]\n            consolidated_W = inference_state[\"video_width\"]\n            consolidated_mask_key = \"pred_masks_video_res\"\n        else:\n            consolidated_H = consolidated_W = self.image_size // 4\n            consolidated_mask_key = \"pred_masks\"\n\n        # Initialize `consolidated_out`. Its \"maskmem_features\" and \"maskmem_pos_enc\"\n        # will be added when rerunning the memory encoder after applying non-overlapping\n        # constraints to object scores. Its \"pred_masks\" are prefilled with a large\n        # negative value (NO_OBJ_SCORE) to represent missing objects.\n        consolidated_out = {\n            \"maskmem_features\": None,\n            \"maskmem_pos_enc\": None,\n            consolidated_mask_key: torch.full(\n                size=(batch_size, 1, consolidated_H, consolidated_W),\n                fill_value=NO_OBJ_SCORE,\n                dtype=torch.float32,\n                device=inference_state[\"storage_device\"],\n            ),\n            \"obj_ptr\": torch.full(\n                size=(batch_size, self.hidden_dim),\n                fill_value=NO_OBJ_SCORE,\n                dtype=torch.float32,\n                device=inference_state[\"device\"],\n            ),\n            \"object_score_logits\": torch.full(\n                size=(batch_size, 1),\n                # default to 10.0 for object_score_logits, i.e. assuming the object is\n                # present as sigmoid(10)=1, same as in `predict_masks` of `MaskDecoder`\n                fill_value=10.0,\n                dtype=torch.float32,\n                device=inference_state[\"device\"],\n            ),\n        }\n        empty_mask_ptr = None\n        for obj_idx in range(batch_size):\n            obj_temp_output_dict = inference_state[\"temp_output_dict_per_obj\"][obj_idx]\n            obj_output_dict = inference_state[\"output_dict_per_obj\"][obj_idx]\n            out = obj_temp_output_dict[storage_key].get(frame_idx, None)\n            # If the object doesn't appear in \"temp_output_dict_per_obj\" on this frame,\n            # we fall back and look up its previous output in \"output_dict_per_obj\".\n            # We look up both \"cond_frame_outputs\" and \"non_cond_frame_outputs\" in\n            # \"output_dict_per_obj\" to find a previous output for this object.\n            if out is None:\n                out = obj_output_dict[\"cond_frame_outputs\"].get(frame_idx, None)\n            if out is None:\n                out = obj_output_dict[\"non_cond_frame_outputs\"].get(frame_idx, None)\n            # If the object doesn't appear in \"output_dict_per_obj\" either, we skip it\n            # and leave its mask scores to the default scores (i.e. the NO_OBJ_SCORE\n            # placeholder above) and set its object pointer to be a dummy pointer.\n            if out is None:\n                # Fill in dummy object pointers for those objects without any inputs or\n                # tracking outcomes on this frame (only do it under `run_mem_encoder=True`,\n                # i.e. when we need to build the memory for tracking).\n                if run_mem_encoder:\n                    if empty_mask_ptr is None:\n                        empty_mask_ptr = self._get_empty_mask_ptr(\n                            inference_state, frame_idx\n                        )\n                    # fill object pointer with a dummy pointer (based on an empty mask)\n                    consolidated_out[\"obj_ptr\"][obj_idx : obj_idx + 1] = empty_mask_ptr\n                continue\n            # Add the temporary object output mask to consolidated output mask\n            obj_mask = out[\"pred_masks\"]\n            consolidated_pred_masks = consolidated_out[consolidated_mask_key]\n            if obj_mask.shape[-2:] == consolidated_pred_masks.shape[-2:]:\n                consolidated_pred_masks[obj_idx : obj_idx + 1] = obj_mask\n            else:\n                # Resize first if temporary object mask has a different resolution\n                resized_obj_mask = torch.nn.functional.interpolate(\n                    obj_mask,\n                    size=consolidated_pred_masks.shape[-2:],\n                    mode=\"bilinear\",\n                    align_corners=False,\n                )\n                consolidated_pred_masks[obj_idx : obj_idx + 1] = resized_obj_mask\n            consolidated_out[\"obj_ptr\"][obj_idx : obj_idx + 1] = out[\"obj_ptr\"]\n            consolidated_out[\"object_score_logits\"][obj_idx : obj_idx + 1] = out[\n                \"object_score_logits\"\n            ]\n\n        # Optionally, apply non-overlapping constraints on the consolidated scores\n        # and rerun the memory encoder\n        if run_mem_encoder:\n            device = inference_state[\"device\"]\n            high_res_masks = torch.nn.functional.interpolate(\n                consolidated_out[\"pred_masks\"].to(device, non_blocking=True),\n                size=(self.image_size, self.image_size),\n                mode=\"bilinear\",\n                align_corners=False,\n            )\n            if self.non_overlap_masks_for_mem_enc:\n                high_res_masks = self._apply_non_overlapping_constraints(high_res_masks)\n            maskmem_features, maskmem_pos_enc = self._run_memory_encoder(\n                inference_state=inference_state,\n                frame_idx=frame_idx,\n                batch_size=batch_size,\n                high_res_masks=high_res_masks,\n                object_score_logits=consolidated_out[\"object_score_logits\"],\n                is_mask_from_pts=True,  # these frames are what the user interacted with\n            )\n            consolidated_out[\"maskmem_features\"] = maskmem_features\n            consolidated_out[\"maskmem_pos_enc\"] = maskmem_pos_enc\n\n        return consolidated_out\n\n    def _get_empty_mask_ptr(self, inference_state, frame_idx):\n        \"\"\"Get a dummy object pointer based on an empty mask on the current frame.\"\"\"\n        # A dummy (empty) mask with a single object\n        batch_size = 1\n        mask_inputs = torch.zeros(\n            (batch_size, 1, self.image_size, self.image_size),\n            dtype=torch.float32,\n            device=inference_state[\"device\"],\n        )\n\n        # Retrieve correct image features\n        (\n            _,\n            _,\n            current_vision_feats,\n            current_vision_pos_embeds,\n            feat_sizes,\n        ) = self._get_image_feature(inference_state, frame_idx, batch_size)\n\n        # Feed the empty mask and image feature above to get a dummy object pointer\n        current_out = self.track_step(\n            frame_idx=frame_idx,\n            is_init_cond_frame=True,\n            current_vision_feats=current_vision_feats,\n            current_vision_pos_embeds=current_vision_pos_embeds,\n            feat_sizes=feat_sizes,\n            point_inputs=None,\n            mask_inputs=mask_inputs,\n            output_dict={},\n            num_frames=inference_state[\"num_frames\"],\n            track_in_reverse=False,\n            run_mem_encoder=False,\n            prev_sam_mask_logits=None,\n        )\n        return current_out[\"obj_ptr\"]\n\n    @torch.inference_mode()\n    def propagate_in_video_preflight(self, inference_state):\n        \"\"\"Prepare inference_state and consolidate temporary outputs before tracking.\"\"\"\n        # Tracking has started and we don't allow adding new objects until session is reset.\n        inference_state[\"tracking_has_started\"] = True\n        batch_size = self._get_obj_num(inference_state)\n\n        # Consolidate per-object temporary outputs in \"temp_output_dict_per_obj\" and\n        # add them into \"output_dict\".\n        temp_output_dict_per_obj = inference_state[\"temp_output_dict_per_obj\"]\n        output_dict = inference_state[\"output_dict\"]\n        # \"consolidated_frame_inds\" contains indices of those frames where consolidated\n        # temporary outputs have been added (either in this call or any previous calls\n        # to `propagate_in_video_preflight`).\n        consolidated_frame_inds = inference_state[\"consolidated_frame_inds\"]\n        for is_cond in [False, True]:\n            # Separately consolidate conditioning and non-conditioning temp outputs\n            storage_key = \"cond_frame_outputs\" if is_cond else \"non_cond_frame_outputs\"\n            # Find all the frames that contain temporary outputs for any objects\n            # (these should be the frames that have just received clicks for mask inputs\n            # via `add_new_points_or_box` or `add_new_mask`)\n            temp_frame_inds = set()\n            for obj_temp_output_dict in temp_output_dict_per_obj.values():\n                temp_frame_inds.update(obj_temp_output_dict[storage_key].keys())\n            consolidated_frame_inds[storage_key].update(temp_frame_inds)\n            # consolidate the temporary output across all objects on this frame\n            for frame_idx in temp_frame_inds:\n                consolidated_out = self._consolidate_temp_output_across_obj(\n                    inference_state, frame_idx, is_cond=is_cond, run_mem_encoder=True\n                )\n                # merge them into \"output_dict\" and also create per-object slices\n                output_dict[storage_key][frame_idx] = consolidated_out\n                self._add_output_per_object(\n                    inference_state, frame_idx, consolidated_out, storage_key\n                )\n                clear_non_cond_mem = self.clear_non_cond_mem_around_input and (\n                    self.clear_non_cond_mem_for_multi_obj or batch_size <= 1\n                )\n                if clear_non_cond_mem:\n                    # clear non-conditioning memory of the surrounding frames\n                    self._clear_non_cond_mem_around_input(inference_state, frame_idx)\n\n            # clear temporary outputs in `temp_output_dict_per_obj`\n            for obj_temp_output_dict in temp_output_dict_per_obj.values():\n                obj_temp_output_dict[storage_key].clear()\n\n        # edge case: if an output is added to \"cond_frame_outputs\", we remove any prior\n        # output on the same frame in \"non_cond_frame_outputs\"\n        for frame_idx in output_dict[\"cond_frame_outputs\"]:\n            output_dict[\"non_cond_frame_outputs\"].pop(frame_idx, None)\n        for obj_output_dict in inference_state[\"output_dict_per_obj\"].values():\n            for frame_idx in obj_output_dict[\"cond_frame_outputs\"]:\n                obj_output_dict[\"non_cond_frame_outputs\"].pop(frame_idx, None)\n        for frame_idx in consolidated_frame_inds[\"cond_frame_outputs\"]:\n            assert frame_idx in output_dict[\"cond_frame_outputs\"]\n            consolidated_frame_inds[\"non_cond_frame_outputs\"].discard(frame_idx)\n\n        # Make sure that the frame indices in \"consolidated_frame_inds\" are exactly those frames\n        # with either points or mask inputs (which should be true under a correct workflow).\n        all_consolidated_frame_inds = (\n            consolidated_frame_inds[\"cond_frame_outputs\"]\n            | consolidated_frame_inds[\"non_cond_frame_outputs\"]\n        )\n        input_frames_inds = set()\n        for point_inputs_per_frame in inference_state[\"point_inputs_per_obj\"].values():\n            input_frames_inds.update(point_inputs_per_frame.keys())\n        for mask_inputs_per_frame in inference_state[\"mask_inputs_per_obj\"].values():\n            input_frames_inds.update(mask_inputs_per_frame.keys())\n        assert all_consolidated_frame_inds == input_frames_inds\n\n    @torch.inference_mode()\n    def propagate_in_video(\n        self,\n        inference_state,\n        start_frame_idx=None,\n        max_frame_num_to_track=None,\n        reverse=False,\n    ):\n        \"\"\"Propagate the input points across frames to track in the entire video.\"\"\"\n        self.propagate_in_video_preflight(inference_state)\n\n        output_dict = inference_state[\"output_dict\"]\n        consolidated_frame_inds = inference_state[\"consolidated_frame_inds\"]\n        obj_ids = inference_state[\"obj_ids\"]\n        num_frames = inference_state[\"num_frames\"]\n        batch_size = self._get_obj_num(inference_state)\n        if len(output_dict[\"cond_frame_outputs\"]) == 0:\n            raise RuntimeError(\"No points are provided; please add points first\")\n        clear_non_cond_mem = self.clear_non_cond_mem_around_input and (\n            self.clear_non_cond_mem_for_multi_obj or batch_size <= 1\n        )\n\n        # set start index, end index, and processing order\n        if start_frame_idx is None:\n            # default: start from the earliest frame with input points\n            start_frame_idx = min(output_dict[\"cond_frame_outputs\"])\n        if max_frame_num_to_track is None:\n            # default: track all the frames in the video\n            max_frame_num_to_track = num_frames\n        if reverse:\n            end_frame_idx = max(start_frame_idx - max_frame_num_to_track, 0)\n            if start_frame_idx > 0:\n                processing_order = range(start_frame_idx, end_frame_idx - 1, -1)\n            else:\n                processing_order = []  # skip reverse tracking if starting from frame 0\n        else:\n            end_frame_idx = min(\n                start_frame_idx + max_frame_num_to_track, num_frames - 1\n            )\n            processing_order = range(start_frame_idx, end_frame_idx + 1)\n\n        for frame_idx in tqdm(processing_order, desc=\"propagate in video\", disable=True):\n            # We skip those frames already in consolidated outputs (these are frames\n            # that received input clicks or mask). Note that we cannot directly run\n            # batched forward on them via `_run_single_frame_inference` because the\n            # number of clicks on each object might be different.\n            if frame_idx in consolidated_frame_inds[\"cond_frame_outputs\"]:\n                storage_key = \"cond_frame_outputs\"\n                current_out = output_dict[storage_key][frame_idx]\n                pred_masks = current_out[\"pred_masks\"]\n                if clear_non_cond_mem:\n                    # clear non-conditioning memory of the surrounding frames\n                    self._clear_non_cond_mem_around_input(inference_state, frame_idx)\n            elif frame_idx in consolidated_frame_inds[\"non_cond_frame_outputs\"]:\n                storage_key = \"non_cond_frame_outputs\"\n                current_out = output_dict[storage_key][frame_idx]\n                pred_masks = current_out[\"pred_masks\"]\n            else:\n                storage_key = \"non_cond_frame_outputs\"\n                current_out, pred_masks = self._run_single_frame_inference(\n                    inference_state=inference_state,\n                    output_dict=output_dict,\n                    frame_idx=frame_idx,\n                    batch_size=batch_size,\n                    is_init_cond_frame=False,\n                    point_inputs=None,\n                    mask_inputs=None,\n                    reverse=reverse,\n                    run_mem_encoder=True,\n                )\n                output_dict[storage_key][frame_idx] = current_out\n            # Create slices of per-object outputs for subsequent interaction with each\n            # individual object after tracking.\n            self._add_output_per_object(\n                inference_state, frame_idx, current_out, storage_key\n            )\n            inference_state[\"frames_already_tracked\"][frame_idx] = {\"reverse\": reverse}\n\n            # Resize the output mask to the original video resolution (we directly use\n            # the mask scores on GPU for output to avoid any CPU conversion in between)\n            _, video_res_masks = self._get_orig_video_res_output(\n                inference_state, pred_masks\n            )\n            yield frame_idx, obj_ids, video_res_masks\n\n    def _add_output_per_object(\n        self, inference_state, frame_idx, current_out, storage_key\n    ):\n        \"\"\"\n        Split a multi-object output into per-object output slices and add them into\n        `output_dict_per_obj`. The resulting slices share the same tensor storage.\n        \"\"\"\n        maskmem_features = current_out[\"maskmem_features\"]\n        assert maskmem_features is None or isinstance(maskmem_features, torch.Tensor)\n\n        maskmem_pos_enc = current_out[\"maskmem_pos_enc\"]\n        assert maskmem_pos_enc is None or isinstance(maskmem_pos_enc, list)\n\n        output_dict_per_obj = inference_state[\"output_dict_per_obj\"]\n        for obj_idx, obj_output_dict in output_dict_per_obj.items():\n            obj_slice = slice(obj_idx, obj_idx + 1)\n            obj_out = {\n                \"maskmem_features\": None,\n                \"maskmem_pos_enc\": None,\n                \"pred_masks\": current_out[\"pred_masks\"][obj_slice],\n                \"obj_ptr\": current_out[\"obj_ptr\"][obj_slice],\n                \"object_score_logits\": current_out[\"object_score_logits\"][obj_slice],\n            }\n            if maskmem_features is not None:\n                obj_out[\"maskmem_features\"] = maskmem_features[obj_slice]\n            if maskmem_pos_enc is not None:\n                obj_out[\"maskmem_pos_enc\"] = [x[obj_slice] for x in maskmem_pos_enc]\n            obj_output_dict[storage_key][frame_idx] = obj_out\n\n    @torch.inference_mode()\n    def clear_all_prompts_in_frame(\n        self, inference_state, frame_idx, obj_id, need_output=True\n    ):\n        \"\"\"Remove all input points or mask in a specific frame for a given object.\"\"\"\n        obj_idx = self._obj_id_to_idx(inference_state, obj_id)\n\n        # Clear the conditioning information on the given frame\n        inference_state[\"point_inputs_per_obj\"][obj_idx].pop(frame_idx, None)\n        inference_state[\"mask_inputs_per_obj\"][obj_idx].pop(frame_idx, None)\n\n        temp_output_dict_per_obj = inference_state[\"temp_output_dict_per_obj\"]\n        temp_output_dict_per_obj[obj_idx][\"cond_frame_outputs\"].pop(frame_idx, None)\n        temp_output_dict_per_obj[obj_idx][\"non_cond_frame_outputs\"].pop(frame_idx, None)\n\n        # Check and see if there are still any inputs left on this frame\n        batch_size = self._get_obj_num(inference_state)\n        frame_has_input = False\n        for obj_idx2 in range(batch_size):\n            if frame_idx in inference_state[\"point_inputs_per_obj\"][obj_idx2]:\n                frame_has_input = True\n                break\n            if frame_idx in inference_state[\"mask_inputs_per_obj\"][obj_idx2]:\n                frame_has_input = True\n                break\n\n        # If this frame has no remaining inputs for any objects, we further clear its\n        # conditioning frame status\n        if not frame_has_input:\n            output_dict = inference_state[\"output_dict\"]\n            consolidated_frame_inds = inference_state[\"consolidated_frame_inds\"]\n            consolidated_frame_inds[\"cond_frame_outputs\"].discard(frame_idx)\n            consolidated_frame_inds[\"non_cond_frame_outputs\"].discard(frame_idx)\n            # Remove the frame's conditioning output (possibly downgrading it to non-conditioning)\n            out = output_dict[\"cond_frame_outputs\"].pop(frame_idx, None)\n            if out is not None:\n                # The frame is not a conditioning frame anymore since it's not receiving inputs,\n                # so we \"downgrade\" its output (if exists) to a non-conditioning frame output.\n                output_dict[\"non_cond_frame_outputs\"][frame_idx] = out\n                inference_state[\"frames_already_tracked\"].pop(frame_idx, None)\n            # Similarly, do it for the sliced output on each object.\n            for obj_idx2 in range(batch_size):\n                obj_output_dict = inference_state[\"output_dict_per_obj\"][obj_idx2]\n                obj_out = obj_output_dict[\"cond_frame_outputs\"].pop(frame_idx, None)\n                if obj_out is not None:\n                    obj_output_dict[\"non_cond_frame_outputs\"][frame_idx] = obj_out\n\n            # If all the conditioning frames have been removed, we also clear the tracking outputs\n            if len(output_dict[\"cond_frame_outputs\"]) == 0:\n                self._reset_tracking_results(inference_state)\n\n        if not need_output:\n            return\n        # Finally, output updated masks per object (after removing the inputs above)\n        obj_ids = inference_state[\"obj_ids\"]\n        is_cond = any(\n            frame_idx in obj_temp_output_dict[\"cond_frame_outputs\"]\n            for obj_temp_output_dict in temp_output_dict_per_obj.values()\n        )\n        consolidated_out = self._consolidate_temp_output_across_obj(\n            inference_state,\n            frame_idx,\n            is_cond=is_cond,\n            run_mem_encoder=False,\n            consolidate_at_video_res=True,\n        )\n        _, video_res_masks = self._get_orig_video_res_output(\n            inference_state, consolidated_out[\"pred_masks_video_res\"]\n        )\n        return frame_idx, obj_ids, video_res_masks\n\n    @torch.inference_mode()\n    def reset_state(self, inference_state):\n        \"\"\"Remove all input points or mask in all frames throughout the video.\"\"\"\n        self._reset_tracking_results(inference_state)\n        # Remove all object ids\n        inference_state[\"obj_id_to_idx\"].clear()\n        inference_state[\"obj_idx_to_id\"].clear()\n        inference_state[\"obj_ids\"].clear()\n        inference_state[\"point_inputs_per_obj\"].clear()\n        inference_state[\"mask_inputs_per_obj\"].clear()\n        inference_state[\"output_dict_per_obj\"].clear()\n        inference_state[\"temp_output_dict_per_obj\"].clear()\n\n    def _reset_tracking_results(self, inference_state):\n        \"\"\"Reset all tracking inputs and results across the videos.\"\"\"\n        for v in inference_state[\"point_inputs_per_obj\"].values():\n            v.clear()\n        for v in inference_state[\"mask_inputs_per_obj\"].values():\n            v.clear()\n        for v in inference_state[\"output_dict_per_obj\"].values():\n            v[\"cond_frame_outputs\"].clear()\n            v[\"non_cond_frame_outputs\"].clear()\n        for v in inference_state[\"temp_output_dict_per_obj\"].values():\n            v[\"cond_frame_outputs\"].clear()\n            v[\"non_cond_frame_outputs\"].clear()\n        inference_state[\"output_dict\"][\"cond_frame_outputs\"].clear()\n        inference_state[\"output_dict\"][\"non_cond_frame_outputs\"].clear()\n        inference_state[\"consolidated_frame_inds\"][\"cond_frame_outputs\"].clear()\n        inference_state[\"consolidated_frame_inds\"][\"non_cond_frame_outputs\"].clear()\n        inference_state[\"tracking_has_started\"] = False\n        inference_state[\"frames_already_tracked\"].clear()\n\n    def _get_image_feature(self, inference_state, frame_idx, batch_size):\n        \"\"\"Compute the image features on a given frame.\"\"\"\n        # Look up in the cache first\n        image, backbone_out = inference_state[\"cached_features\"].get(\n            frame_idx, (None, None)\n        )\n        if backbone_out is None:\n            # Cache miss -- we will run inference on a single image\n            device = inference_state[\"device\"]\n            image = inference_state[\"images\"][frame_idx].to(device).float().unsqueeze(0)\n            backbone_out = self.forward_image(image)\n            # Cache the most recent frame's feature (for repeated interactions with\n            # a frame; we can use an LRU cache for more frames in the future).\n            inference_state[\"cached_features\"] = {frame_idx: (image, backbone_out)}\n\n        # expand the features to have the same dimension as the number of objects\n        expanded_image = image.expand(batch_size, -1, -1, -1)\n        expanded_backbone_out = {\n            \"backbone_fpn\": backbone_out[\"backbone_fpn\"].copy(),\n            \"vision_pos_enc\": backbone_out[\"vision_pos_enc\"].copy(),\n        }\n        for i, feat in enumerate(expanded_backbone_out[\"backbone_fpn\"]):\n            expanded_backbone_out[\"backbone_fpn\"][i] = feat.expand(\n                batch_size, -1, -1, -1\n            )\n        for i, pos in enumerate(expanded_backbone_out[\"vision_pos_enc\"]):\n            pos = pos.expand(batch_size, -1, -1, -1)\n            expanded_backbone_out[\"vision_pos_enc\"][i] = pos\n\n        features = self._prepare_backbone_features(expanded_backbone_out)\n        features = (expanded_image,) + features\n        return features\n\n    def _run_single_frame_inference(\n        self,\n        inference_state,\n        output_dict,\n        frame_idx,\n        batch_size,\n        is_init_cond_frame,\n        point_inputs,\n        mask_inputs,\n        reverse,\n        run_mem_encoder,\n        prev_sam_mask_logits=None,\n    ):\n        \"\"\"Run tracking on a single frame based on current inputs and previous memory.\"\"\"\n        # Retrieve correct image features\n        (\n            _,\n            _,\n            current_vision_feats,\n            current_vision_pos_embeds,\n            feat_sizes,\n        ) = self._get_image_feature(inference_state, frame_idx, batch_size)\n\n        # point and mask should not appear as input simultaneously on the same frame\n        assert point_inputs is None or mask_inputs is None\n        current_out = self.track_step(\n            frame_idx=frame_idx,\n            is_init_cond_frame=is_init_cond_frame,\n            current_vision_feats=current_vision_feats,\n            current_vision_pos_embeds=current_vision_pos_embeds,\n            feat_sizes=feat_sizes,\n            point_inputs=point_inputs,\n            mask_inputs=mask_inputs,\n            output_dict=output_dict,\n            num_frames=inference_state[\"num_frames\"],\n            track_in_reverse=reverse,\n            run_mem_encoder=run_mem_encoder,\n            prev_sam_mask_logits=prev_sam_mask_logits,\n        )\n\n        # optionally offload the output to CPU memory to save GPU space\n        storage_device = inference_state[\"storage_device\"]\n        maskmem_features = current_out[\"maskmem_features\"]\n        if maskmem_features is not None:\n            maskmem_features = maskmem_features.to(torch.bfloat16)\n            maskmem_features = maskmem_features.to(storage_device, non_blocking=True)\n        pred_masks_gpu = current_out[\"pred_masks\"]\n        # potentially fill holes in the predicted masks\n        if self.fill_hole_area > 0:\n            pred_masks_gpu = fill_holes_in_mask_scores(\n                pred_masks_gpu, self.fill_hole_area\n            )\n        pred_masks = pred_masks_gpu.to(storage_device, non_blocking=True)\n        # \"maskmem_pos_enc\" is the same across frames, so we only need to store one copy of it\n        maskmem_pos_enc = self._get_maskmem_pos_enc(inference_state, current_out)\n        # object pointer is a small tensor, so we always keep it on GPU memory for fast access\n        obj_ptr = current_out[\"obj_ptr\"]\n        object_score_logits = current_out[\"object_score_logits\"]\n        # make a compact version of this frame's output to reduce the state size\n        compact_current_out = {\n            \"maskmem_features\": maskmem_features,\n            \"maskmem_pos_enc\": maskmem_pos_enc,\n            \"pred_masks\": pred_masks,\n            \"obj_ptr\": obj_ptr,\n            \"object_score_logits\": object_score_logits,\n        }\n        return compact_current_out, pred_masks_gpu\n\n    def _run_memory_encoder(\n        self,\n        inference_state,\n        frame_idx,\n        batch_size,\n        high_res_masks,\n        object_score_logits,\n        is_mask_from_pts,\n    ):\n        \"\"\"\n        Run the memory encoder on `high_res_masks`. This is usually after applying\n        non-overlapping constraints to object scores. Since their scores changed, their\n        memory also need to be computed again with the memory encoder.\n        \"\"\"\n        # Retrieve correct image features\n        _, _, current_vision_feats, _, feat_sizes = self._get_image_feature(\n            inference_state, frame_idx, batch_size\n        )\n        maskmem_features, maskmem_pos_enc = self._encode_new_memory(\n            current_vision_feats=current_vision_feats,\n            feat_sizes=feat_sizes,\n            pred_masks_high_res=high_res_masks,\n            object_score_logits=object_score_logits,\n            is_mask_from_pts=is_mask_from_pts,\n        )\n\n        # optionally offload the output to CPU memory to save GPU space\n        storage_device = inference_state[\"storage_device\"]\n        maskmem_features = maskmem_features.to(torch.bfloat16)\n        maskmem_features = maskmem_features.to(storage_device, non_blocking=True)\n        # \"maskmem_pos_enc\" is the same across frames, so we only need to store one copy of it\n        maskmem_pos_enc = self._get_maskmem_pos_enc(\n            inference_state, {\"maskmem_pos_enc\": maskmem_pos_enc}\n        )\n        return maskmem_features, maskmem_pos_enc\n\n    def _get_maskmem_pos_enc(self, inference_state, current_out):\n        \"\"\"\n        `maskmem_pos_enc` is the same across frames and objects, so we cache it as\n        a constant in the inference session to reduce session storage size.\n        \"\"\"\n        model_constants = inference_state[\"constants\"]\n        # \"out_maskmem_pos_enc\" should be either a list of tensors or None\n        out_maskmem_pos_enc = current_out[\"maskmem_pos_enc\"]\n        if out_maskmem_pos_enc is not None:\n            if \"maskmem_pos_enc\" not in model_constants:\n                assert isinstance(out_maskmem_pos_enc, list)\n                # only take the slice for one object, since it's same across objects\n                maskmem_pos_enc = [x[0:1].clone() for x in out_maskmem_pos_enc]\n                model_constants[\"maskmem_pos_enc\"] = maskmem_pos_enc\n            else:\n                maskmem_pos_enc = model_constants[\"maskmem_pos_enc\"]\n            # expand the cached maskmem_pos_enc to the actual batch size\n            batch_size = out_maskmem_pos_enc[0].size(0)\n            expanded_maskmem_pos_enc = [\n                x.expand(batch_size, -1, -1, -1) for x in maskmem_pos_enc\n            ]\n        else:\n            expanded_maskmem_pos_enc = None\n        return expanded_maskmem_pos_enc\n\n    @torch.inference_mode()\n    def remove_object(self, inference_state, obj_id, strict=False, need_output=True):\n        \"\"\"\n        Remove an object id from the tracking state. If strict is True, we check whether\n        the object id actually exists and raise an error if it doesn't exist.\n        \"\"\"\n        old_obj_idx_to_rm = inference_state[\"obj_id_to_idx\"].get(obj_id, None)\n        updated_frames = []\n        # Check whether this object_id to remove actually exists and possibly raise an error.\n        if old_obj_idx_to_rm is None:\n            if not strict:\n                return inference_state[\"obj_ids\"], updated_frames\n            raise RuntimeError(\n                f\"Cannot remove object id {obj_id} as it doesn't exist. \"\n                f\"All existing object ids: {inference_state['obj_ids']}.\"\n            )\n\n        # If this is the only remaining object id, we simply reset the state.\n        if len(inference_state[\"obj_id_to_idx\"]) == 1:\n            self.reset_state(inference_state)\n            return inference_state[\"obj_ids\"], updated_frames\n\n        # There are still remaining objects after removing this object id. In this case,\n        # we need to delete the object storage from inference state tensors.\n        # Step 0: clear the input on those frames where this object id has point or mask input\n        # (note that this step is required as it might downgrade conditioning frames to\n        # non-conditioning ones)\n        obj_input_frames_inds = set()\n        obj_input_frames_inds.update(\n            inference_state[\"point_inputs_per_obj\"][old_obj_idx_to_rm]\n        )\n        obj_input_frames_inds.update(\n            inference_state[\"mask_inputs_per_obj\"][old_obj_idx_to_rm]\n        )\n        for frame_idx in obj_input_frames_inds:\n            self.clear_all_prompts_in_frame(\n                inference_state, frame_idx, obj_id, need_output=False\n            )\n\n        # Step 1: Update the object id mapping (note that it must be done after Step 0,\n        # since Step 0 still requires the old object id mappings in inference_state)\n        old_obj_ids = inference_state[\"obj_ids\"]\n        old_obj_inds = list(range(len(old_obj_ids)))\n        remain_old_obj_inds = old_obj_inds.copy()\n        remain_old_obj_inds.remove(old_obj_idx_to_rm)\n        new_obj_ids = [old_obj_ids[old_idx] for old_idx in remain_old_obj_inds]\n        new_obj_inds = list(range(len(new_obj_ids)))\n        # build new mappings\n        old_idx_to_new_idx = dict(zip(remain_old_obj_inds, new_obj_inds))\n        inference_state[\"obj_id_to_idx\"] = dict(zip(new_obj_ids, new_obj_inds))\n        inference_state[\"obj_idx_to_id\"] = dict(zip(new_obj_inds, new_obj_ids))\n        inference_state[\"obj_ids\"] = new_obj_ids\n\n        # Step 2: For per-object tensor storage, we shift their obj_idx in the dict keys.\n        # (note that \"consolidated_frame_inds\" doesn't need to be updated in this step as\n        # it's already handled in Step 0)\n        def _map_keys(container):\n            new_kvs = []\n            for k in old_obj_inds:\n                v = container.pop(k)\n                if k in old_idx_to_new_idx:\n                    new_kvs.append((old_idx_to_new_idx[k], v))\n            container.update(new_kvs)\n\n        _map_keys(inference_state[\"point_inputs_per_obj\"])\n        _map_keys(inference_state[\"mask_inputs_per_obj\"])\n        _map_keys(inference_state[\"output_dict_per_obj\"])\n        _map_keys(inference_state[\"temp_output_dict_per_obj\"])\n\n        # Step 3: For packed tensor storage, we index the remaining ids and rebuild the per-object slices.\n        def _slice_state(output_dict, storage_key):\n            for frame_idx, out in output_dict[storage_key].items():\n                out[\"maskmem_features\"] = out[\"maskmem_features\"][remain_old_obj_inds]\n                out[\"maskmem_pos_enc\"] = [\n                    x[remain_old_obj_inds] for x in out[\"maskmem_pos_enc\"]\n                ]\n                # \"maskmem_pos_enc\" is the same across frames, so we only need to store one copy of it\n                out[\"maskmem_pos_enc\"] = self._get_maskmem_pos_enc(inference_state, out)\n                out[\"pred_masks\"] = out[\"pred_masks\"][remain_old_obj_inds]\n                out[\"obj_ptr\"] = out[\"obj_ptr\"][remain_old_obj_inds]\n                out[\"object_score_logits\"] = out[\"object_score_logits\"][\n                    remain_old_obj_inds\n                ]\n                # also update the per-object slices\n                self._add_output_per_object(\n                    inference_state, frame_idx, out, storage_key\n                )\n\n        _slice_state(inference_state[\"output_dict\"], \"cond_frame_outputs\")\n        _slice_state(inference_state[\"output_dict\"], \"non_cond_frame_outputs\")\n\n        # Step 4: Further collect the outputs on those frames in `obj_input_frames_inds`, which\n        # could show an updated mask for objects previously occluded by the object being removed\n        if need_output:\n            temp_output_dict_per_obj = inference_state[\"temp_output_dict_per_obj\"]\n            for frame_idx in obj_input_frames_inds:\n                is_cond = any(\n                    frame_idx in obj_temp_output_dict[\"cond_frame_outputs\"]\n                    for obj_temp_output_dict in temp_output_dict_per_obj.values()\n                )\n                consolidated_out = self._consolidate_temp_output_across_obj(\n                    inference_state,\n                    frame_idx,\n                    is_cond=is_cond,\n                    run_mem_encoder=False,\n                    consolidate_at_video_res=True,\n                )\n                _, video_res_masks = self._get_orig_video_res_output(\n                    inference_state, consolidated_out[\"pred_masks_video_res\"]\n                )\n                updated_frames.append((frame_idx, video_res_masks))\n\n        return inference_state[\"obj_ids\"], updated_frames\n\n    def _clear_non_cond_mem_around_input(self, inference_state, frame_idx):\n        \"\"\"\n        Remove the non-conditioning memory around the input frame. When users provide\n        correction clicks, the surrounding frames' non-conditioning memories can still\n        contain outdated object appearance information and could confuse the model.\n\n        This method clears those non-conditioning memories surrounding the interacted\n        frame to avoid giving the model both old and new information about the object.\n        \"\"\"\n        r = self.memory_temporal_stride_for_eval\n        frame_idx_begin = frame_idx - r * self.num_maskmem\n        frame_idx_end = frame_idx + r * self.num_maskmem\n        output_dict = inference_state[\"output_dict\"]\n        non_cond_frame_outputs = output_dict[\"non_cond_frame_outputs\"]\n        for t in range(frame_idx_begin, frame_idx_end + 1):\n            non_cond_frame_outputs.pop(t, None)\n            for obj_output_dict in inference_state[\"output_dict_per_obj\"].values():\n                obj_output_dict[\"non_cond_frame_outputs\"].pop(t, None)\n"
  },
  {
    "path": "eval/grounded_sam/sam2/utils/__init__.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n"
  },
  {
    "path": "eval/grounded_sam/sam2/utils/amg.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport math\nfrom copy import deepcopy\nfrom itertools import product\nfrom typing import Any, Dict, Generator, ItemsView, List, Tuple\n\nimport numpy as np\nimport torch\n\n# Very lightly adapted from https://github.com/facebookresearch/segment-anything/blob/main/segment_anything/utils/amg.py\n\n\nclass MaskData:\n    \"\"\"\n    A structure for storing masks and their related data in batched format.\n    Implements basic filtering and concatenation.\n    \"\"\"\n\n    def __init__(self, **kwargs) -> None:\n        for v in kwargs.values():\n            assert isinstance(\n                v, (list, np.ndarray, torch.Tensor)\n            ), \"MaskData only supports list, numpy arrays, and torch tensors.\"\n        self._stats = dict(**kwargs)\n\n    def __setitem__(self, key: str, item: Any) -> None:\n        assert isinstance(\n            item, (list, np.ndarray, torch.Tensor)\n        ), \"MaskData only supports list, numpy arrays, and torch tensors.\"\n        self._stats[key] = item\n\n    def __delitem__(self, key: str) -> None:\n        del self._stats[key]\n\n    def __getitem__(self, key: str) -> Any:\n        return self._stats[key]\n\n    def items(self) -> ItemsView[str, Any]:\n        return self._stats.items()\n\n    def filter(self, keep: torch.Tensor) -> None:\n        for k, v in self._stats.items():\n            if v is None:\n                self._stats[k] = None\n            elif isinstance(v, torch.Tensor):\n                self._stats[k] = v[torch.as_tensor(keep, device=v.device)]\n            elif isinstance(v, np.ndarray):\n                self._stats[k] = v[keep.detach().cpu().numpy()]\n            elif isinstance(v, list) and keep.dtype == torch.bool:\n                self._stats[k] = [a for i, a in enumerate(v) if keep[i]]\n            elif isinstance(v, list):\n                self._stats[k] = [v[i] for i in keep]\n            else:\n                raise TypeError(f\"MaskData key {k} has an unsupported type {type(v)}.\")\n\n    def cat(self, new_stats: \"MaskData\") -> None:\n        for k, v in new_stats.items():\n            if k not in self._stats or self._stats[k] is None:\n                self._stats[k] = deepcopy(v)\n            elif isinstance(v, torch.Tensor):\n                self._stats[k] = torch.cat([self._stats[k], v], dim=0)\n            elif isinstance(v, np.ndarray):\n                self._stats[k] = np.concatenate([self._stats[k], v], axis=0)\n            elif isinstance(v, list):\n                self._stats[k] = self._stats[k] + deepcopy(v)\n            else:\n                raise TypeError(f\"MaskData key {k} has an unsupported type {type(v)}.\")\n\n    def to_numpy(self) -> None:\n        for k, v in self._stats.items():\n            if isinstance(v, torch.Tensor):\n                self._stats[k] = v.float().detach().cpu().numpy()\n\n\ndef is_box_near_crop_edge(\n    boxes: torch.Tensor, crop_box: List[int], orig_box: List[int], atol: float = 20.0\n) -> torch.Tensor:\n    \"\"\"Filter masks at the edge of a crop, but not at the edge of the original image.\"\"\"\n    crop_box_torch = torch.as_tensor(crop_box, dtype=torch.float, device=boxes.device)\n    orig_box_torch = torch.as_tensor(orig_box, dtype=torch.float, device=boxes.device)\n    boxes = uncrop_boxes_xyxy(boxes, crop_box).float()\n    near_crop_edge = torch.isclose(boxes, crop_box_torch[None, :], atol=atol, rtol=0)\n    near_image_edge = torch.isclose(boxes, orig_box_torch[None, :], atol=atol, rtol=0)\n    near_crop_edge = torch.logical_and(near_crop_edge, ~near_image_edge)\n    return torch.any(near_crop_edge, dim=1)\n\n\ndef box_xyxy_to_xywh(box_xyxy: torch.Tensor) -> torch.Tensor:\n    box_xywh = deepcopy(box_xyxy)\n    box_xywh[2] = box_xywh[2] - box_xywh[0]\n    box_xywh[3] = box_xywh[3] - box_xywh[1]\n    return box_xywh\n\n\ndef batch_iterator(batch_size: int, *args) -> Generator[List[Any], None, None]:\n    assert len(args) > 0 and all(\n        len(a) == len(args[0]) for a in args\n    ), \"Batched iteration must have inputs of all the same size.\"\n    n_batches = len(args[0]) // batch_size + int(len(args[0]) % batch_size != 0)\n    for b in range(n_batches):\n        yield [arg[b * batch_size : (b + 1) * batch_size] for arg in args]\n\n\ndef mask_to_rle_pytorch(tensor: torch.Tensor) -> List[Dict[str, Any]]:\n    \"\"\"\n    Encodes masks to an uncompressed RLE, in the format expected by\n    pycoco tools.\n    \"\"\"\n    # Put in fortran order and flatten h,w\n    b, h, w = tensor.shape\n    tensor = tensor.permute(0, 2, 1).flatten(1)\n\n    # Compute change indices\n    diff = tensor[:, 1:] ^ tensor[:, :-1]\n    change_indices = diff.nonzero()\n\n    # Encode run length\n    out = []\n    for i in range(b):\n        cur_idxs = change_indices[change_indices[:, 0] == i, 1]\n        cur_idxs = torch.cat(\n            [\n                torch.tensor([0], dtype=cur_idxs.dtype, device=cur_idxs.device),\n                cur_idxs + 1,\n                torch.tensor([h * w], dtype=cur_idxs.dtype, device=cur_idxs.device),\n            ]\n        )\n        btw_idxs = cur_idxs[1:] - cur_idxs[:-1]\n        counts = [] if tensor[i, 0] == 0 else [0]\n        counts.extend(btw_idxs.detach().cpu().tolist())\n        out.append({\"size\": [h, w], \"counts\": counts})\n    return out\n\n\ndef rle_to_mask(rle: Dict[str, Any]) -> np.ndarray:\n    \"\"\"Compute a binary mask from an uncompressed RLE.\"\"\"\n    h, w = rle[\"size\"]\n    mask = np.empty(h * w, dtype=bool)\n    idx = 0\n    parity = False\n    for count in rle[\"counts\"]:\n        mask[idx : idx + count] = parity\n        idx += count\n        parity ^= True\n    mask = mask.reshape(w, h)\n    return mask.transpose()  # Put in C order\n\n\ndef area_from_rle(rle: Dict[str, Any]) -> int:\n    return sum(rle[\"counts\"][1::2])\n\n\ndef calculate_stability_score(\n    masks: torch.Tensor, mask_threshold: float, threshold_offset: float\n) -> torch.Tensor:\n    \"\"\"\n    Computes the stability score for a batch of masks. The stability\n    score is the IoU between the binary masks obtained by thresholding\n    the predicted mask logits at high and low values.\n    \"\"\"\n    # One mask is always contained inside the other.\n    # Save memory by preventing unnecessary cast to torch.int64\n    intersections = (\n        (masks > (mask_threshold + threshold_offset))\n        .sum(-1, dtype=torch.int16)\n        .sum(-1, dtype=torch.int32)\n    )\n    unions = (\n        (masks > (mask_threshold - threshold_offset))\n        .sum(-1, dtype=torch.int16)\n        .sum(-1, dtype=torch.int32)\n    )\n    return intersections / unions\n\n\ndef build_point_grid(n_per_side: int) -> np.ndarray:\n    \"\"\"Generates a 2D grid of points evenly spaced in [0,1]x[0,1].\"\"\"\n    offset = 1 / (2 * n_per_side)\n    points_one_side = np.linspace(offset, 1 - offset, n_per_side)\n    points_x = np.tile(points_one_side[None, :], (n_per_side, 1))\n    points_y = np.tile(points_one_side[:, None], (1, n_per_side))\n    points = np.stack([points_x, points_y], axis=-1).reshape(-1, 2)\n    return points\n\n\ndef build_all_layer_point_grids(\n    n_per_side: int, n_layers: int, scale_per_layer: int\n) -> List[np.ndarray]:\n    \"\"\"Generates point grids for all crop layers.\"\"\"\n    points_by_layer = []\n    for i in range(n_layers + 1):\n        n_points = int(n_per_side / (scale_per_layer**i))\n        points_by_layer.append(build_point_grid(n_points))\n    return points_by_layer\n\n\ndef generate_crop_boxes(\n    im_size: Tuple[int, ...], n_layers: int, overlap_ratio: float\n) -> Tuple[List[List[int]], List[int]]:\n    \"\"\"\n    Generates a list of crop boxes of different sizes. Each layer\n    has (2**i)**2 boxes for the ith layer.\n    \"\"\"\n    crop_boxes, layer_idxs = [], []\n    im_h, im_w = im_size\n    short_side = min(im_h, im_w)\n\n    # Original image\n    crop_boxes.append([0, 0, im_w, im_h])\n    layer_idxs.append(0)\n\n    def crop_len(orig_len, n_crops, overlap):\n        return int(math.ceil((overlap * (n_crops - 1) + orig_len) / n_crops))\n\n    for i_layer in range(n_layers):\n        n_crops_per_side = 2 ** (i_layer + 1)\n        overlap = int(overlap_ratio * short_side * (2 / n_crops_per_side))\n\n        crop_w = crop_len(im_w, n_crops_per_side, overlap)\n        crop_h = crop_len(im_h, n_crops_per_side, overlap)\n\n        crop_box_x0 = [int((crop_w - overlap) * i) for i in range(n_crops_per_side)]\n        crop_box_y0 = [int((crop_h - overlap) * i) for i in range(n_crops_per_side)]\n\n        # Crops in XYWH format\n        for x0, y0 in product(crop_box_x0, crop_box_y0):\n            box = [x0, y0, min(x0 + crop_w, im_w), min(y0 + crop_h, im_h)]\n            crop_boxes.append(box)\n            layer_idxs.append(i_layer + 1)\n\n    return crop_boxes, layer_idxs\n\n\ndef uncrop_boxes_xyxy(boxes: torch.Tensor, crop_box: List[int]) -> torch.Tensor:\n    x0, y0, _, _ = crop_box\n    offset = torch.tensor([[x0, y0, x0, y0]], device=boxes.device)\n    # Check if boxes has a channel dimension\n    if len(boxes.shape) == 3:\n        offset = offset.unsqueeze(1)\n    return boxes + offset\n\n\ndef uncrop_points(points: torch.Tensor, crop_box: List[int]) -> torch.Tensor:\n    x0, y0, _, _ = crop_box\n    offset = torch.tensor([[x0, y0]], device=points.device)\n    # Check if points has a channel dimension\n    if len(points.shape) == 3:\n        offset = offset.unsqueeze(1)\n    return points + offset\n\n\ndef uncrop_masks(\n    masks: torch.Tensor, crop_box: List[int], orig_h: int, orig_w: int\n) -> torch.Tensor:\n    x0, y0, x1, y1 = crop_box\n    if x0 == 0 and y0 == 0 and x1 == orig_w and y1 == orig_h:\n        return masks\n    # Coordinate transform masks\n    pad_x, pad_y = orig_w - (x1 - x0), orig_h - (y1 - y0)\n    pad = (x0, pad_x - x0, y0, pad_y - y0)\n    return torch.nn.functional.pad(masks, pad, value=0)\n\n\ndef remove_small_regions(\n    mask: np.ndarray, area_thresh: float, mode: str\n) -> Tuple[np.ndarray, bool]:\n    \"\"\"\n    Removes small disconnected regions and holes in a mask. Returns the\n    mask and an indicator of if the mask has been modified.\n    \"\"\"\n    import cv2  # type: ignore\n\n    assert mode in [\"holes\", \"islands\"]\n    correct_holes = mode == \"holes\"\n    working_mask = (correct_holes ^ mask).astype(np.uint8)\n    n_labels, regions, stats, _ = cv2.connectedComponentsWithStats(working_mask, 8)\n    sizes = stats[:, -1][1:]  # Row 0 is background label\n    small_regions = [i + 1 for i, s in enumerate(sizes) if s < area_thresh]\n    if len(small_regions) == 0:\n        return mask, False\n    fill_labels = [0] + small_regions\n    if not correct_holes:\n        fill_labels = [i for i in range(n_labels) if i not in fill_labels]\n        # If every region is below threshold, keep largest\n        if len(fill_labels) == 0:\n            fill_labels = [int(np.argmax(sizes)) + 1]\n    mask = np.isin(regions, fill_labels)\n    return mask, True\n\n\ndef coco_encode_rle(uncompressed_rle: Dict[str, Any]) -> Dict[str, Any]:\n    from pycocotools import mask as mask_utils  # type: ignore\n\n    h, w = uncompressed_rle[\"size\"]\n    rle = mask_utils.frPyObjects(uncompressed_rle, h, w)\n    rle[\"counts\"] = rle[\"counts\"].decode(\"utf-8\")  # Necessary to serialize with json\n    return rle\n\n\ndef batched_mask_to_box(masks: torch.Tensor) -> torch.Tensor:\n    \"\"\"\n    Calculates boxes in XYXY format around masks. Return [0,0,0,0] for\n    an empty mask. For input shape C1xC2x...xHxW, the output shape is C1xC2x...x4.\n    \"\"\"\n    # torch.max below raises an error on empty inputs, just skip in this case\n    if torch.numel(masks) == 0:\n        return torch.zeros(*masks.shape[:-2], 4, device=masks.device)\n\n    # Normalize shape to CxHxW\n    shape = masks.shape\n    h, w = shape[-2:]\n    if len(shape) > 2:\n        masks = masks.flatten(0, -3)\n    else:\n        masks = masks.unsqueeze(0)\n\n    # Get top and bottom edges\n    in_height, _ = torch.max(masks, dim=-1)\n    in_height_coords = in_height * torch.arange(h, device=in_height.device)[None, :]\n    bottom_edges, _ = torch.max(in_height_coords, dim=-1)\n    in_height_coords = in_height_coords + h * (~in_height)\n    top_edges, _ = torch.min(in_height_coords, dim=-1)\n\n    # Get left and right edges\n    in_width, _ = torch.max(masks, dim=-2)\n    in_width_coords = in_width * torch.arange(w, device=in_width.device)[None, :]\n    right_edges, _ = torch.max(in_width_coords, dim=-1)\n    in_width_coords = in_width_coords + w * (~in_width)\n    left_edges, _ = torch.min(in_width_coords, dim=-1)\n\n    # If the mask is empty the right edge will be to the left of the left edge.\n    # Replace these boxes with [0, 0, 0, 0]\n    empty_filter = (right_edges < left_edges) | (bottom_edges < top_edges)\n    out = torch.stack([left_edges, top_edges, right_edges, bottom_edges], dim=-1)\n    out = out * (~empty_filter).unsqueeze(-1)\n\n    # Return to original shape\n    if len(shape) > 2:\n        out = out.reshape(*shape[:-2], 4)\n    else:\n        out = out[0]\n\n    return out\n"
  },
  {
    "path": "eval/grounded_sam/sam2/utils/misc.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport os\nimport warnings\nfrom threading import Thread\n\nimport numpy as np\nimport torch\nfrom PIL import Image\nfrom tqdm import tqdm\n\n\ndef get_sdpa_settings():\n    if torch.cuda.is_available():\n        old_gpu = torch.cuda.get_device_properties(0).major < 7\n        # only use Flash Attention on Ampere (8.0) or newer GPUs\n        use_flash_attn = torch.cuda.get_device_properties(0).major >= 8\n        if not use_flash_attn:\n            warnings.warn(\n                \"Flash Attention is disabled as it requires a GPU with Ampere (8.0) CUDA capability.\",\n                category=UserWarning,\n                stacklevel=2,\n            )\n        # keep math kernel for PyTorch versions before 2.2 (Flash Attention v2 is only\n        # available on PyTorch 2.2+, while Flash Attention v1 cannot handle all cases)\n        pytorch_version = tuple(int(v) for v in torch.__version__.split(\".\")[:2])\n        if pytorch_version < (2, 2):\n            warnings.warn(\n                f\"You are using PyTorch {torch.__version__} without Flash Attention v2 support. \"\n                \"Consider upgrading to PyTorch 2.2+ for Flash Attention v2 (which could be faster).\",\n                category=UserWarning,\n                stacklevel=2,\n            )\n        math_kernel_on = pytorch_version < (2, 2) or not use_flash_attn\n    else:\n        old_gpu = True\n        use_flash_attn = False\n        math_kernel_on = True\n\n    return old_gpu, use_flash_attn, math_kernel_on\n\n\ndef get_connected_components(mask):\n    \"\"\"\n    Get the connected components (8-connectivity) of binary masks of shape (N, 1, H, W).\n\n    Inputs:\n    - mask: A binary mask tensor of shape (N, 1, H, W), where 1 is foreground and 0 is\n            background.\n\n    Outputs:\n    - labels: A tensor of shape (N, 1, H, W) containing the connected component labels\n              for foreground pixels and 0 for background pixels.\n    - counts: A tensor of shape (N, 1, H, W) containing the area of the connected\n              components for foreground pixels and 0 for background pixels.\n    \"\"\"\n    from sam2 import _C\n\n    return _C.get_connected_componnets(mask.to(torch.uint8).contiguous())\n\n\ndef mask_to_box(masks: torch.Tensor):\n    \"\"\"\n    compute bounding box given an input mask\n\n    Inputs:\n    - masks: [B, 1, H, W] masks, dtype=torch.Tensor\n\n    Returns:\n    - box_coords: [B, 1, 4], contains (x, y) coordinates of top left and bottom right box corners, dtype=torch.Tensor\n    \"\"\"\n    B, _, h, w = masks.shape\n    device = masks.device\n    xs = torch.arange(w, device=device, dtype=torch.int32)\n    ys = torch.arange(h, device=device, dtype=torch.int32)\n    grid_xs, grid_ys = torch.meshgrid(xs, ys, indexing=\"xy\")\n    grid_xs = grid_xs[None, None, ...].expand(B, 1, h, w)\n    grid_ys = grid_ys[None, None, ...].expand(B, 1, h, w)\n    min_xs, _ = torch.min(torch.where(masks, grid_xs, w).flatten(-2), dim=-1)\n    max_xs, _ = torch.max(torch.where(masks, grid_xs, -1).flatten(-2), dim=-1)\n    min_ys, _ = torch.min(torch.where(masks, grid_ys, h).flatten(-2), dim=-1)\n    max_ys, _ = torch.max(torch.where(masks, grid_ys, -1).flatten(-2), dim=-1)\n    bbox_coords = torch.stack((min_xs, min_ys, max_xs, max_ys), dim=-1)\n\n    return bbox_coords\n\n\ndef _load_img_as_tensor(img_path, image_size):\n    img_pil = Image.open(img_path)\n    img_np = np.array(img_pil.convert(\"RGB\").resize((image_size, image_size)))\n    if img_np.dtype == np.uint8:  # np.uint8 is expected for JPEG images\n        img_np = img_np / 255.0\n    else:\n        raise RuntimeError(f\"Unknown image dtype: {img_np.dtype} on {img_path}\")\n    img = torch.from_numpy(img_np).permute(2, 0, 1)\n    video_width, video_height = img_pil.size  # the original video size\n    return img, video_height, video_width\n\n\nclass AsyncVideoFrameLoader:\n    \"\"\"\n    A list of video frames to be load asynchronously without blocking session start.\n    \"\"\"\n\n    def __init__(\n        self,\n        img_paths,\n        image_size,\n        offload_video_to_cpu,\n        img_mean,\n        img_std,\n        compute_device,\n    ):\n        self.img_paths = img_paths\n        self.image_size = image_size\n        self.offload_video_to_cpu = offload_video_to_cpu\n        self.img_mean = img_mean\n        self.img_std = img_std\n        # items in `self.images` will be loaded asynchronously\n        self.images = [None] * len(img_paths)\n        # catch and raise any exceptions in the async loading thread\n        self.exception = None\n        # video_height and video_width be filled when loading the first image\n        self.video_height = None\n        self.video_width = None\n        self.compute_device = compute_device\n\n        # load the first frame to fill video_height and video_width and also\n        # to cache it (since it's most likely where the user will click)\n        self.__getitem__(0)\n\n        # load the rest of frames asynchronously without blocking the session start\n        def _load_frames():\n            try:\n                for n in tqdm(range(len(self.images)), desc=\"frame loading (JPEG)\", disable=True):\n                    self.__getitem__(n)\n            except Exception as e:\n                self.exception = e\n\n        self.thread = Thread(target=_load_frames, daemon=True)\n        self.thread.start()\n\n    def __getitem__(self, index):\n        if self.exception is not None:\n            raise RuntimeError(\"Failure in frame loading thread\") from self.exception\n\n        img = self.images[index]\n        if img is not None:\n            return img\n\n        img, video_height, video_width = _load_img_as_tensor(\n            self.img_paths[index], self.image_size\n        )\n        self.video_height = video_height\n        self.video_width = video_width\n        # normalize by mean and std\n        img -= self.img_mean\n        img /= self.img_std\n        if not self.offload_video_to_cpu:\n            img = img.to(self.compute_device, non_blocking=True)\n        self.images[index] = img\n        return img\n\n    def __len__(self):\n        return len(self.images)\n\n\ndef load_video_frames(\n    video_path,\n    image_size,\n    offload_video_to_cpu,\n    img_mean=(0.485, 0.456, 0.406),\n    img_std=(0.229, 0.224, 0.225),\n    async_loading_frames=False,\n    compute_device=torch.device(\"cuda\"),\n):\n    \"\"\"\n    Load the video frames from video_path. The frames are resized to image_size as in\n    the model and are loaded to GPU if offload_video_to_cpu=False. This is used by the demo.\n    \"\"\"\n    is_bytes = isinstance(video_path, bytes)\n    is_str = isinstance(video_path, str)\n    is_mp4_path = is_str and os.path.splitext(video_path)[-1] in [\".mp4\", \".MP4\"]\n    if is_bytes or is_mp4_path:\n        return load_video_frames_from_video_file(\n            video_path=video_path,\n            image_size=image_size,\n            offload_video_to_cpu=offload_video_to_cpu,\n            img_mean=img_mean,\n            img_std=img_std,\n            compute_device=compute_device,\n        )\n    elif is_str and os.path.isdir(video_path):\n        return load_video_frames_from_jpg_images(\n            video_path=video_path,\n            image_size=image_size,\n            offload_video_to_cpu=offload_video_to_cpu,\n            img_mean=img_mean,\n            img_std=img_std,\n            async_loading_frames=async_loading_frames,\n            compute_device=compute_device,\n        )\n    else:\n        raise NotImplementedError(\n            \"Only MP4 video and JPEG folder are supported at this moment\"\n        )\n\n\ndef load_video_frames_from_jpg_images(\n    video_path,\n    image_size,\n    offload_video_to_cpu,\n    img_mean=(0.485, 0.456, 0.406),\n    img_std=(0.229, 0.224, 0.225),\n    async_loading_frames=False,\n    compute_device=torch.device(\"cuda\"),\n):\n    \"\"\"\n    Load the video frames from a directory of JPEG files (\"<frame_index>.jpg\" format).\n\n    The frames are resized to image_size x image_size and are loaded to GPU if\n    `offload_video_to_cpu` is `False` and to CPU if `offload_video_to_cpu` is `True`.\n\n    You can load a frame asynchronously by setting `async_loading_frames` to `True`.\n    \"\"\"\n    if isinstance(video_path, str) and os.path.isdir(video_path):\n        jpg_folder = video_path\n    else:\n        raise NotImplementedError(\n            \"Only JPEG frames are supported at this moment. For video files, you may use \"\n            \"ffmpeg (https://ffmpeg.org/) to extract frames into a folder of JPEG files, such as \\n\"\n            \"```\\n\"\n            \"ffmpeg -i <your_video>.mp4 -q:v 2 -start_number 0 <output_dir>/'%05d.jpg'\\n\"\n            \"```\\n\"\n            \"where `-q:v` generates high-quality JPEG frames and `-start_number 0` asks \"\n            \"ffmpeg to start the JPEG file from 00000.jpg.\"\n        )\n\n    frame_names = [\n        p\n        for p in os.listdir(jpg_folder)\n        if os.path.splitext(p)[-1] in [\".jpg\", \".jpeg\", \".JPG\", \".JPEG\"]\n    ]\n    frame_names.sort(key=lambda p: int(os.path.splitext(p)[0]))\n    num_frames = len(frame_names)\n    if num_frames == 0:\n        raise RuntimeError(f\"no images found in {jpg_folder}\")\n    img_paths = [os.path.join(jpg_folder, frame_name) for frame_name in frame_names]\n    img_mean = torch.tensor(img_mean, dtype=torch.float32)[:, None, None]\n    img_std = torch.tensor(img_std, dtype=torch.float32)[:, None, None]\n\n    if async_loading_frames:\n        lazy_images = AsyncVideoFrameLoader(\n            img_paths,\n            image_size,\n            offload_video_to_cpu,\n            img_mean,\n            img_std,\n            compute_device,\n        )\n        return lazy_images, lazy_images.video_height, lazy_images.video_width\n\n    images = torch.zeros(num_frames, 3, image_size, image_size, dtype=torch.float32)\n    for n, img_path in enumerate(tqdm(img_paths, desc=\"frame loading (JPEG)\", disable=True)):\n        images[n], video_height, video_width = _load_img_as_tensor(img_path, image_size)\n    if not offload_video_to_cpu:\n        images = images.to(compute_device)\n        img_mean = img_mean.to(compute_device)\n        img_std = img_std.to(compute_device)\n    # normalize by mean and std\n    images -= img_mean\n    images /= img_std\n    return images, video_height, video_width\n\n\ndef load_video_frames_from_video_file(\n    video_path,\n    image_size,\n    offload_video_to_cpu,\n    img_mean=(0.485, 0.456, 0.406),\n    img_std=(0.229, 0.224, 0.225),\n    compute_device=torch.device(\"cuda\"),\n):\n    \"\"\"Load the video frames from a video file.\"\"\"\n    import decord\n\n    img_mean = torch.tensor(img_mean, dtype=torch.float32)[:, None, None]\n    img_std = torch.tensor(img_std, dtype=torch.float32)[:, None, None]\n    # Get the original video height and width\n    decord.bridge.set_bridge(\"torch\")\n    video_height, video_width, _ = decord.VideoReader(video_path).next().shape\n    # Iterate over all frames in the video\n    images = []\n    for frame in decord.VideoReader(video_path, width=image_size, height=image_size):\n        images.append(frame.permute(2, 0, 1))\n\n    images = torch.stack(images, dim=0).float() / 255.0\n    if not offload_video_to_cpu:\n        images = images.to(compute_device)\n        img_mean = img_mean.to(compute_device)\n        img_std = img_std.to(compute_device)\n    # normalize by mean and std\n    images -= img_mean\n    images /= img_std\n    return images, video_height, video_width\n\n\ndef fill_holes_in_mask_scores(mask, max_area):\n    \"\"\"\n    A post processor to fill small holes in mask scores with area under `max_area`.\n    \"\"\"\n    # Holes are those connected components in background with area <= self.max_area\n    # (background regions are those with mask scores <= 0)\n    assert max_area > 0, \"max_area must be positive\"\n\n    input_mask = mask\n    try:\n        labels, areas = get_connected_components(mask <= 0)\n        is_hole = (labels > 0) & (areas <= max_area)\n        # We fill holes with a small positive mask score (0.1) to change them to foreground.\n        mask = torch.where(is_hole, 0.1, mask)\n    except Exception as e:\n        # Skip the post-processing step on removing small holes if the CUDA kernel fails\n        warnings.warn(\n            f\"{e}\\n\\nSkipping the post-processing step due to the error above. You can \"\n            \"still use SAM 2 and it's OK to ignore the error above, although some post-processing \"\n            \"functionality may be limited (which doesn't affect the results in most cases; see \"\n            \"https://github.com/facebookresearch/sam2/blob/main/INSTALL.md).\",\n            category=UserWarning,\n            stacklevel=2,\n        )\n        mask = input_mask\n\n    return mask\n\n\ndef concat_points(old_point_inputs, new_points, new_labels):\n    \"\"\"Add new points and labels to previous point inputs (add at the end).\"\"\"\n    if old_point_inputs is None:\n        points, labels = new_points, new_labels\n    else:\n        points = torch.cat([old_point_inputs[\"point_coords\"], new_points], dim=1)\n        labels = torch.cat([old_point_inputs[\"point_labels\"], new_labels], dim=1)\n\n    return {\"point_coords\": points, \"point_labels\": labels}\n"
  },
  {
    "path": "eval/grounded_sam/sam2/utils/transforms.py",
    "content": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport warnings\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torchvision.transforms import Normalize, Resize, ToTensor\n\n\nclass SAM2Transforms(nn.Module):\n    def __init__(\n        self, resolution, mask_threshold, max_hole_area=0.0, max_sprinkle_area=0.0\n    ):\n        \"\"\"\n        Transforms for SAM2.\n        \"\"\"\n        super().__init__()\n        self.resolution = resolution\n        self.mask_threshold = mask_threshold\n        self.max_hole_area = max_hole_area\n        self.max_sprinkle_area = max_sprinkle_area\n        self.mean = [0.485, 0.456, 0.406]\n        self.std = [0.229, 0.224, 0.225]\n        self.to_tensor = ToTensor()\n        self.transforms = torch.jit.script(\n            nn.Sequential(\n                Resize((self.resolution, self.resolution)),\n                Normalize(self.mean, self.std),\n            )\n        )\n\n    def __call__(self, x):\n        x = self.to_tensor(x)\n        return self.transforms(x)\n\n    def forward_batch(self, img_list):\n        img_batch = [self.transforms(self.to_tensor(img)) for img in img_list]\n        img_batch = torch.stack(img_batch, dim=0)\n        return img_batch\n\n    def transform_coords(\n        self, coords: torch.Tensor, normalize=False, orig_hw=None\n    ) -> torch.Tensor:\n        \"\"\"\n        Expects a torch tensor with length 2 in the last dimension. The coordinates can be in absolute image or normalized coordinates,\n        If the coords are in absolute image coordinates, normalize should be set to True and original image size is required.\n\n        Returns\n            Un-normalized coordinates in the range of [0, 1] which is expected by the SAM2 model.\n        \"\"\"\n        if normalize:\n            assert orig_hw is not None\n            h, w = orig_hw\n            coords = coords.clone()\n            coords[..., 0] = coords[..., 0] / w\n            coords[..., 1] = coords[..., 1] / h\n\n        coords = coords * self.resolution  # unnormalize coords\n        return coords\n\n    def transform_boxes(\n        self, boxes: torch.Tensor, normalize=False, orig_hw=None\n    ) -> torch.Tensor:\n        \"\"\"\n        Expects a tensor of shape Bx4. The coordinates can be in absolute image or normalized coordinates,\n        if the coords are in absolute image coordinates, normalize should be set to True and original image size is required.\n        \"\"\"\n        boxes = self.transform_coords(boxes.reshape(-1, 2, 2), normalize, orig_hw)\n        return boxes\n\n    def postprocess_masks(self, masks: torch.Tensor, orig_hw) -> torch.Tensor:\n        \"\"\"\n        Perform PostProcessing on output masks.\n        \"\"\"\n        from sam2.utils.misc import get_connected_components\n\n        masks = masks.float()\n        input_masks = masks\n        mask_flat = masks.flatten(0, 1).unsqueeze(1)  # flatten as 1-channel image\n        try:\n            if self.max_hole_area > 0:\n                # Holes are those connected components in background with area <= self.fill_hole_area\n                # (background regions are those with mask scores <= self.mask_threshold)\n                labels, areas = get_connected_components(\n                    mask_flat <= self.mask_threshold\n                )\n                is_hole = (labels > 0) & (areas <= self.max_hole_area)\n                is_hole = is_hole.reshape_as(masks)\n                # We fill holes with a small positive mask score (10.0) to change them to foreground.\n                masks = torch.where(is_hole, self.mask_threshold + 10.0, masks)\n\n            if self.max_sprinkle_area > 0:\n                labels, areas = get_connected_components(\n                    mask_flat > self.mask_threshold\n                )\n                is_hole = (labels > 0) & (areas <= self.max_sprinkle_area)\n                is_hole = is_hole.reshape_as(masks)\n                # We fill holes with negative mask score (-10.0) to change them to background.\n                masks = torch.where(is_hole, self.mask_threshold - 10.0, masks)\n        except Exception as e:\n            # Skip the post-processing step if the CUDA kernel fails\n            warnings.warn(\n                f\"{e}\\n\\nSkipping the post-processing step due to the error above. You can \"\n                \"still use SAM 2 and it's OK to ignore the error above, although some post-processing \"\n                \"functionality may be limited (which doesn't affect the results in most cases; see \"\n                \"https://github.com/facebookresearch/sam2/blob/main/INSTALL.md).\",\n                category=UserWarning,\n                stacklevel=2,\n            )\n            masks = input_masks\n        orig_dtype = masks.dtype\n        masks = F.interpolate(masks.float(), orig_hw, mode=\"bilinear\", align_corners=False)\n        masks = masks.to(orig_dtype)\n        return masks\n"
  },
  {
    "path": "eval/tools/XVerseBench_multi.json",
    "content": "[\n    {\n        \"index\": 0,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is riding a motorcycle.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/00_motorcycle.jpg\",\n                        \"caption\": \"a motorcycle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"motorcycle\",\n                        \"motorcycle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 1,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An anime Spider-Man is playing with a boy.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/00_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/71_anime Spider-Man.jpg\",\n                        \"caption\": \"an anime Spider-Man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"anime Spider-Man\",\n                        \"anime Spider-Man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 2,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man stands beside a vintage van.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/21_vintage van.jpg\",\n                        \"caption\": \"a vintage van\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"vintage van\",\n                        \"vintage van\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 3,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An old man meets a pixelated warrior.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/67_pixelated warrior.jpg\",\n                        \"caption\": \"a pixelated warrior\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        1,\n                        \"pixelated warrior\",\n                        \"pixelated warrior\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 4,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman stands in front of a hut.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/42_hut.jpg\",\n                        \"caption\": \"a hut\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"hut\",\n                        \"hut\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 5,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is playing a snare drum.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/60_snare drum.jpg\",\n                        \"caption\": \"a snare drum\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"snare drum\",\n                        \"snare drum\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 6,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is holding a leather handbag.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/57_leather handbag.jpg\",\n                        \"caption\": \"a leather handbag\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"leather handbag\",\n                        \"leather handbag\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 7,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is using a hair dryer.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/26_hair dryer.jpg\",\n                        \"caption\": \"a hair dryer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"hair dryer\",\n                        \"hair dryer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 8,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is sitting on a motorcycle.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/00_motorcycle.jpg\",\n                        \"caption\": \"a motorcycle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"motorcycle\",\n                        \"motorcycle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 9,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is holding a pineapple.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/43_pineapple.jpg\",\n                        \"caption\": \"a pineapple\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"pineapple\",\n                        \"pineapple\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 10,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is looking at a clock.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/56_clock.jpg\",\n                        \"caption\": \"a clock\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"clock\",\n                        \"clock\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 11,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and an anime man standing side by side\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/73_anime man.jpg\",\n                        \"caption\": \"an anime man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"anime man\",\n                        \"anime man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 12,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is holding a vase.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/30_vase.jpg\",\n                        \"caption\": \"a vase\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"vase\",\n                        \"vase\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 13,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is holding a vintage camera.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/23_vintage camera.jpg\",\n                        \"caption\": \"a vintage camera\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"vintage camera\",\n                        \"vintage camera\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 14,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is standing beside a classical bust.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/25_classical bust.jpg\",\n                        \"caption\": \"a classical bust\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"classical bust\",\n                        \"classical bust\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 15,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A curious boy discovered a ring in the forest.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/16_ring.jpg\",\n                        \"caption\": \"a ring\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"ring\",\n                        \"ring\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 16,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man stands beside a steam locomotive.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/19_steam locomotive.jpg\",\n                        \"caption\": \"a steam locomotive\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"steam locomotive\",\n                        \"steam locomotive\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 17,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man holding a Poke Ball.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/54_Poke Ball.jpg\",\n                        \"caption\": \"a Poke Ball\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"Poke Ball\",\n                        \"Poke Ball\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 18,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man standing among cherry blossoms.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/03_cherry blossoms.jpg\",\n                        \"caption\": \"a cherry blossoms\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"cherry blossoms\",\n                        \"cherry blossoms\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 19,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is standing next to a cactus.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/53_cactus.jpg\",\n                        \"caption\": \"a cactus\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"cactus\",\n                        \"cactus\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 20,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is standing beside another man.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 21,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is standing beside a man.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 22,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a boy are standing side by side.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"boy\",\n                        \"boy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 23,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and a girl standing side by side in a park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"girl\",\n                        \"girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 24,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman standing side by side in a park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 25,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An old man and a man standing together on the street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 26,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and a girl standing together in a park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"girl\",\n                        \"girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 27,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman standing side by side.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 28,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and another man standing side by side on a street, having a conversation.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 29,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman standing together in a park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 30,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl is walking hand-in-hand with a woman on a sunny street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 31,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman standing together on a sunny street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 32,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and another man standing side by side, having a conversation.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 33,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and a man standing side by side in a park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 34,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl is standing beside a man.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 35,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A girl is standing beside a woman, having a friendly chat.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"girl\",\n                        \"girl\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 36,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman standing together\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 37,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is standing beside another man.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 38,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl is standing beside a man.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 39,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman standing side by side in a park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 40,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is swimming with a sea turtle in the ocean.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/18_sea turtle.jpg\",\n                        \"caption\": \"a sea turtle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"sea turtle\",\n                        \"sea turtle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 41,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is playing with a dog.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/00_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/12_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"dog\",\n                        \"dog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 42,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is standing in the forest, facing a wolf.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"wolf\",\n                        \"wolf\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 43,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is playing with a hamster.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"hamster\",\n                        \"hamster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 44,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is standing beside a rooster.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/09_rooster.jpg\",\n                        \"caption\": \"a rooster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"rooster\",\n                        \"rooster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 45,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man standing face-to-face with a lion in the wild.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/30_lion.jpg\",\n                        \"caption\": \"a lion\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"lion\",\n                        \"lion\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 46,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is standing in front of a lion.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/30_lion.jpg\",\n                        \"caption\": \"a lion\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"lion\",\n                        \"lion\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 47,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is riding a horse.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/03_horse.jpg\",\n                        \"caption\": \"a horse\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"horse\",\n                        \"horse\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 48,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is observing a grasshopper.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/29_grasshopper.jpg\",\n                        \"caption\": \"a grasshopper\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"grasshopper\",\n                        \"grasshopper\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 49,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is looking at a frog.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/17_frog.jpg\",\n                        \"caption\": \"a frog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"frog\",\n                        \"frog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 50,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is playing with a corgi.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/00_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/22_corgi.jpg\",\n                        \"caption\": \"a corgi\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"corgi\",\n                        \"corgi\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 51,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is walking a corgi on a street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/22_corgi.jpg\",\n                        \"caption\": \"a corgi\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"corgi\",\n                        \"corgi\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 52,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is holding a Sphynx cat.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/25_Sphynx cat.jpg\",\n                        \"caption\": \"a Sphynx cat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"Sphynx cat\",\n                        \"Sphynx cat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 53,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is looking at a frog in a small pond.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/17_frog.jpg\",\n                        \"caption\": \"a frog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"frog\",\n                        \"frog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 54,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is walking with a dog on the street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/07_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"dog\",\n                        \"dog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 55,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is looking at a crab on the beach.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/04_crab.jpg\",\n                        \"caption\": \"a crab\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"crab\",\n                        \"crab\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 56,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is standing beside a flamingo.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/28_flamingo.jpg\",\n                        \"caption\": \"a flamingo\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"flamingo\",\n                        \"flamingo\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 57,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is interacting with a dolphin.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/39_dolphin.jpg\",\n                        \"caption\": \"a dolphin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"dolphin\",\n                        \"dolphin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 58,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl is playing with a puppy.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/42_puppy.jpg\",\n                        \"caption\": \"a puppy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"puppy\",\n                        \"puppy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 59,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is swimming with a dolphin in the sea.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/39_dolphin.jpg\",\n                        \"caption\": \"a dolphin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"dolphin\",\n                        \"dolphin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 60,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An elephant is carrying a backpack on its back.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/38_elephant.jpg\",\n                        \"caption\": \"an elephant\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/28_backpack.jpg\",\n                        \"caption\": \"a backpack\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"elephant\",\n                        \"elephant\"\n                    ],\n                    [\n                        1,\n                        \"backpack\",\n                        \"backpack\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 61,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A wolf is standing beside a teapot.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/52_teapot.jpg\",\n                        \"caption\": \"a teapot\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"wolf\",\n                        \"wolf\"\n                    ],\n                    [\n                        1,\n                        \"teapot\",\n                        \"teapot\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 62,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A deer standing beside a vintage van.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/31_deer.jpg\",\n                        \"caption\": \"a deer\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/21_vintage van.jpg\",\n                        \"caption\": \"a vintage van\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"deer\",\n                        \"deer\"\n                    ],\n                    [\n                        1,\n                        \"vintage van\",\n                        \"vintage van\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 63,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cotton-top tamarin is sitting under a street lamp.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/26_cotton-top tamarin.jpg\",\n                        \"caption\": \"a cotton-top tamarin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/15_street lamp.jpg\",\n                        \"caption\": \"a street lamp\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cotton-top tamarin\",\n                        \"cotton-top tamarin\"\n                    ],\n                    [\n                        1,\n                        \"street lamp\",\n                        \"street lamp\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 64,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"In the moonlit jungle, a white tiger prowls silently, its eye catching the glint of an old, abandoned watch nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/40_white tiger.jpg\",\n                        \"caption\": \"a white tiger\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/12_watch.jpg\",\n                        \"caption\": \"a watch\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"white tiger\",\n                        \"white tiger\"\n                    ],\n                    [\n                        1,\n                        \"watch\",\n                        \"watch\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 65,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A Corgi dog stands beside an anime samurai.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/32_Corgi dog.jpg\",\n                        \"caption\": \"a Corgi dog\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/69_anime samurai.jpg\",\n                        \"caption\": \"an anime samurai\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Corgi dog\",\n                        \"Corgi dog\"\n                    ],\n                    [\n                        1,\n                        \"anime samurai\",\n                        \"anime samurai\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 66,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A grasshopper is standing next to a Poke Ball.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/29_grasshopper.jpg\",\n                        \"caption\": \"a grasshopper\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/54_Poke Ball.jpg\",\n                        \"caption\": \"a Poke Ball\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"grasshopper\",\n                        \"grasshopper\"\n                    ],\n                    [\n                        1,\n                        \"Poke Ball\",\n                        \"Poke Ball\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 67,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A penguin is on a flamingo float in the water.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/05_penguin.jpg\",\n                        \"caption\": \"a penguin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/10_flamingo float.jpg\",\n                        \"caption\": \"a flamingo float\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"penguin\",\n                        \"penguin\"\n                    ],\n                    [\n                        1,\n                        \"flamingo float\",\n                        \"flamingo float\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 68,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A fox is standing under a street lamp.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/10_fox.jpg\",\n                        \"caption\": \"a fox\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/15_street lamp.jpg\",\n                        \"caption\": \"a street lamp\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"fox\",\n                        \"fox\"\n                    ],\n                    [\n                        1,\n                        \"street lamp\",\n                        \"street lamp\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 69,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cotton-top tamarin is curiously inspecting an Eevee figurine.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/26_cotton-top tamarin.jpg\",\n                        \"caption\": \"a cotton-top tamarin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/59_Eevee figurine.jpg\",\n                        \"caption\": \"an Eevee figurine\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cotton-top tamarin\",\n                        \"cotton-top tamarin\"\n                    ],\n                    [\n                        1,\n                        \"Eevee figurine\",\n                        \"Eevee figurine\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 70,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A llama wearing a hat\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/24_llama.jpg\",\n                        \"caption\": \"a llama\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/01_hat.jpg\",\n                        \"caption\": \"a hat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"llama\",\n                        \"llama\"\n                    ],\n                    [\n                        1,\n                        \"hat\",\n                        \"hat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 71,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cat is lying beside a teddy bear.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/44_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/13_teddy bear.jpg\",\n                        \"caption\": \"a teddy bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cat\",\n                        \"cat\"\n                    ],\n                    [\n                        1,\n                        \"teddy bear\",\n                        \"teddy bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 72,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cat sitting in front of a yellow taxi.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/44_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/44_yellow taxi.jpg\",\n                        \"caption\": \"a yellow taxi\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cat\",\n                        \"cat\"\n                    ],\n                    [\n                        1,\n                        \"yellow taxi\",\n                        \"yellow taxi\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 73,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cat is being dried by a hair dryer.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/44_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/26_hair dryer.jpg\",\n                        \"caption\": \"a hair dryer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cat\",\n                        \"cat\"\n                    ],\n                    [\n                        1,\n                        \"hair dryer\",\n                        \"hair dryer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 74,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A toucan is sitting in front of a vintage television.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/37_toucan.jpg\",\n                        \"caption\": \"a toucan\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/49_vintage television.jpg\",\n                        \"caption\": \"a vintage television\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"toucan\",\n                        \"toucan\"\n                    ],\n                    [\n                        1,\n                        \"vintage television\",\n                        \"vintage television\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 75,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A panda is using a hair dryer.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/33_panda.jpg\",\n                        \"caption\": \"a panda\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/26_hair dryer.jpg\",\n                        \"caption\": \"a hair dryer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"panda\",\n                        \"panda\"\n                    ],\n                    [\n                        1,\n                        \"hair dryer\",\n                        \"hair dryer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 76,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A lizard is sitting on a motorcycle.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/36_lizard.jpg\",\n                        \"caption\": \"a lizard\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/00_motorcycle.jpg\",\n                        \"caption\": \"a motorcycle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"lizard\",\n                        \"lizard\"\n                    ],\n                    [\n                        1,\n                        \"motorcycle\",\n                        \"motorcycle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 77,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A robin perches on a leather handbag.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/57_leather handbag.jpg\",\n                        \"caption\": \"a leather handbag\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"robin\",\n                        \"robin\"\n                    ],\n                    [\n                        1,\n                        \"leather handbag\",\n                        \"leather handbag\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 78,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cat is sitting beside a basketball shoe.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/34_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/07_basketball shoe.jpg\",\n                        \"caption\": \"a basketball shoe\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cat\",\n                        \"cat\"\n                    ],\n                    [\n                        1,\n                        \"basketball shoe\",\n                        \"basketball shoe\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 79,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A jellyfish floating near a tree on an otherworldly beach.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/16_jellyfish.jpg\",\n                        \"caption\": \"a jellyfish\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/08_tree.jpg\",\n                        \"caption\": \"a tree\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"jellyfish\",\n                        \"jellyfish\"\n                    ],\n                    [\n                        1,\n                        \"tree\",\n                        \"tree\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 80,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"In a dense jungle, a cotton-top tamarin curiously eyes a resting wolf, intrigued by the unfamiliar presence amid foliage.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/26_cotton-top tamarin.jpg\",\n                        \"caption\": \"a cotton-top tamarin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cotton-top tamarin\",\n                        \"cotton-top tamarin\"\n                    ],\n                    [\n                        1,\n                        \"wolf\",\n                        \"wolf\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 81,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A deer stands in a forest clearing while a robin perches on a nearby branch.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/31_deer.jpg\",\n                        \"caption\": \"a deer\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"deer\",\n                        \"deer\"\n                    ],\n                    [\n                        1,\n                        \"robin\",\n                        \"robin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 82,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A raccoon and a rooster are standing in a rural yard.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/08_raccoon.jpg\",\n                        \"caption\": \"a raccoon\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/09_rooster.jpg\",\n                        \"caption\": \"a rooster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"raccoon\",\n                        \"raccoon\"\n                    ],\n                    [\n                        1,\n                        \"rooster\",\n                        \"rooster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 83,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A dolphin and a penguin swimming in the ocean together.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/39_dolphin.jpg\",\n                        \"caption\": \"a dolphin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/05_penguin.jpg\",\n                        \"caption\": \"a penguin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"dolphin\",\n                        \"dolphin\"\n                    ],\n                    [\n                        1,\n                        \"penguin\",\n                        \"penguin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 84,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A playful panda and a curious cat frolic in a sunlit bamboo forest, surrounded by vibrant blossoms and fluttering butterflies.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/33_panda.jpg\",\n                        \"caption\": \"a panda\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/34_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"panda\",\n                        \"panda\"\n                    ],\n                    [\n                        1,\n                        \"cat\",\n                        \"cat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 85,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A grasshopper is jumping on the grass while a tiger is lurking nearby in the grassland.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/29_grasshopper.jpg\",\n                        \"caption\": \"a grasshopper\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/35_tiger.jpg\",\n                        \"caption\": \"a tiger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"grasshopper\",\n                        \"grasshopper\"\n                    ],\n                    [\n                        1,\n                        \"tiger\",\n                        \"tiger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 86,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A grasshopper is hopping on the grass while a wolf is prowling nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/29_grasshopper.jpg\",\n                        \"caption\": \"a grasshopper\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"grasshopper\",\n                        \"grasshopper\"\n                    ],\n                    [\n                        1,\n                        \"wolf\",\n                        \"wolf\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 87,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A polar bear and a hamster in a snowy landscape.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/13_polar bear.jpg\",\n                        \"caption\": \"a polar bear\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"polar bear\",\n                        \"polar bear\"\n                    ],\n                    [\n                        1,\n                        \"hamster\",\n                        \"hamster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 88,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A lion is lying under a tree while a robin is perched on a nearby branch.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/23_lion.jpg\",\n                        \"caption\": \"a lion\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"lion\",\n                        \"lion\"\n                    ],\n                    [\n                        1,\n                        \"robin\",\n                        \"robin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 89,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A dog is chasing a butterfly in the garden.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/15_butterfly.jpg\",\n                        \"caption\": \"a butterfly\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/07_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"butterfly\",\n                        \"butterfly\"\n                    ],\n                    [\n                        1,\n                        \"dog\",\n                        \"dog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 90,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A horse is standing near the seashore and looking at a crab on the beach.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/03_horse.jpg\",\n                        \"caption\": \"a horse\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/04_crab.jpg\",\n                        \"caption\": \"a crab\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"horse\",\n                        \"horse\"\n                    ],\n                    [\n                        1,\n                        \"crab\",\n                        \"crab\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 91,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A dog is looking up at an eagle soaring in the sky.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/07_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/14_eagle.jpg\",\n                        \"caption\": \"an eagle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"dog\",\n                        \"dog\"\n                    ],\n                    [\n                        1,\n                        \"eagle\",\n                        \"eagle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 92,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A heron is standing by a small pond in a forest, and a deer is drinking water at the edge of the pond.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/11_heron.jpg\",\n                        \"caption\": \"a heron\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/31_deer.jpg\",\n                        \"caption\": \"a deer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"heron\",\n                        \"heron\"\n                    ],\n                    [\n                        1,\n                        \"deer\",\n                        \"deer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 93,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A llama standing in a meadow with a robin flying nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/24_llama.jpg\",\n                        \"caption\": \"a llama\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"llama\",\n                        \"llama\"\n                    ],\n                    [\n                        1,\n                        \"robin\",\n                        \"robin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 94,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A French bulldog and a penguin standing side by side on an ice-floe under a sunny sky.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/43_French bulldog.jpg\",\n                        \"caption\": \"a French bulldog\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/05_penguin.jpg\",\n                        \"caption\": \"a penguin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"French bulldog\",\n                        \"French bulldog\"\n                    ],\n                    [\n                        1,\n                        \"penguin\",\n                        \"penguin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 95,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An eagle is soaring above the sea, and a shark is swimming in the water below.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/14_eagle.jpg\",\n                        \"caption\": \"an eagle\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/06_shark.jpg\",\n                        \"caption\": \"a shark\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"eagle\",\n                        \"eagle\"\n                    ],\n                    [\n                        1,\n                        \"shark\",\n                        \"shark\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 96,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A stork and a parrot are standing side by side on a branch.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/01_stork.jpg\",\n                        \"caption\": \"a stork\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/41_parrot.jpg\",\n                        \"caption\": \"a parrot\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"stork\",\n                        \"stork\"\n                    ],\n                    [\n                        1,\n                        \"parrot\",\n                        \"parrot\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 97,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A shark and an elephant co-existing in a fantasy underwater scene with the elephant floating gracefully among the shark.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/06_shark.jpg\",\n                        \"caption\": \"a shark\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/38_elephant.jpg\",\n                        \"caption\": \"an elephant\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"shark\",\n                        \"shark\"\n                    ],\n                    [\n                        1,\n                        \"elephant\",\n                        \"elephant\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 98,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A hamster is looking at a jellyfish floating in a fishbowl nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/16_jellyfish.jpg\",\n                        \"caption\": \"a jellyfish\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hamster\",\n                        \"hamster\"\n                    ],\n                    [\n                        1,\n                        \"jellyfish\",\n                        \"jellyfish\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 99,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A frog is floating on a small raft in the ocean, and a shark is swimming nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/17_frog.jpg\",\n                        \"caption\": \"a frog\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/06_shark.jpg\",\n                        \"caption\": \"a shark\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"frog\",\n                        \"frog\"\n                    ],\n                    [\n                        1,\n                        \"shark\",\n                        \"shark\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 100,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A piggy bank sits beside a Rolls-Royce hood ornament on a polished table.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/31_piggy bank.jpg\",\n                        \"caption\": \"a piggy bank\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/40_Rolls-Royce hood ornament.jpg\",\n                        \"caption\": \"a Rolls-Royce hood ornament\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"piggy bank\",\n                        \"piggy bank\"\n                    ],\n                    [\n                        1,\n                        \"Rolls-Royce hood ornament\",\n                        \"Rolls-Royce hood ornament\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 101,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cap is lying under a street lamp.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/15_street lamp.jpg\",\n                        \"caption\": \"a street lamp\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/32_cap.jpg\",\n                        \"caption\": \"a cap\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"street lamp\",\n                        \"street lamp\"\n                    ],\n                    [\n                        1,\n                        \"cap\",\n                        \"cap\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 102,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A basketball shoe sits in front of a vintage television.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/07_basketball shoe.jpg\",\n                        \"caption\": \"a basketball shoe\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/02_vintage television.jpg\",\n                        \"caption\": \"a vintage television\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"basketball shoe\",\n                        \"basketball shoe\"\n                    ],\n                    [\n                        1,\n                        \"vintage television\",\n                        \"vintage television\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 103,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An airplane is flying over a field with a cactus.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/37_airplane.jpg\",\n                        \"caption\": \"an airplane\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/53_cactus.jpg\",\n                        \"caption\": \"a cactus\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"airplane\",\n                        \"airplane\"\n                    ],\n                    [\n                        1,\n                        \"cactus\",\n                        \"cactus\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 104,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A mug is placed in front of a wooden house.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/45_wooden house.jpg\",\n                        \"caption\": \"a wooden house\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/27_mug.jpg\",\n                        \"caption\": \"a mug\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"wooden house\",\n                        \"wooden house\"\n                    ],\n                    [\n                        1,\n                        \"mug\",\n                        \"mug\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 105,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A rubber duck floating near a tree-like character by a small pond.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/50_rubber duck.jpg\",\n                        \"caption\": \"a rubber duck\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/34_tree-like character.jpg\",\n                        \"caption\": \"a tree-like character\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"rubber duck\",\n                        \"rubber duck\"\n                    ],\n                    [\n                        1,\n                        \"tree-like character\",\n                        \"tree-like character\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 106,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A vintage van parked next to a robot on an open ground.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/21_vintage van.jpg\",\n                        \"caption\": \"a vintage van\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/18_robot.jpg\",\n                        \"caption\": \"a robot\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"vintage van\",\n                        \"vintage van\"\n                    ],\n                    [\n                        1,\n                        \"robot\",\n                        \"robot\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 107,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A snare drum is placed beside a street lamp.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/60_snare drum.jpg\",\n                        \"caption\": \"a snare drum\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/15_street lamp.jpg\",\n                        \"caption\": \"a street lamp\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"snare drum\",\n                        \"snare drum\"\n                    ],\n                    [\n                        1,\n                        \"street lamp\",\n                        \"street lamp\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 108,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"The anime Spider-Man leaps across skyscrapers, clutching a roll of film, destined to unveil secrets hidden within the bustling city.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/71_anime Spider-Man.jpg\",\n                        \"caption\": \"an anime Spider-Man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/61_roll of film.jpg\",\n                        \"caption\": \"a roll of film\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"anime Spider-Man\",\n                        \"anime Spider-Man\"\n                    ],\n                    [\n                        1,\n                        \"roll of film\",\n                        \"roll of film\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 109,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A sneaker lies beside a beer can on the floor.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/22_sneaker.jpg\",\n                        \"caption\": \"a sneaker\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/04_beer can.jpg\",\n                        \"caption\": \"a beer can\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"sneaker\",\n                        \"sneaker\"\n                    ],\n                    [\n                        1,\n                        \"beer can\",\n                        \"beer can\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 110,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A tree-like character standing beside a stop sign.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/51_stop sign.jpg\",\n                        \"caption\": \"a stop sign\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/34_tree-like character.jpg\",\n                        \"caption\": \"a tree-like character\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"stop sign\",\n                        \"stop sign\"\n                    ],\n                    [\n                        1,\n                        \"tree-like character\",\n                        \"tree-like character\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 111,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A robot is standing beside an airplane.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/18_robot.jpg\",\n                        \"caption\": \"a robot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/37_airplane.jpg\",\n                        \"caption\": \"an airplane\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"robot\",\n                        \"robot\"\n                    ],\n                    [\n                        1,\n                        \"airplane\",\n                        \"airplane\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 112,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A hot air balloon floating in the sky above a sneaker lying on the ground.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/09_hot air balloon.jpg\",\n                        \"caption\": \"a hot air balloon\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/22_sneaker.jpg\",\n                        \"caption\": \"a sneaker\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hot air balloon\",\n                        \"hot air balloon\"\n                    ],\n                    [\n                        1,\n                        \"sneaker\",\n                        \"sneaker\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 113,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An Eevee figurine placed inside a leather handbag.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/59_Eevee figurine.jpg\",\n                        \"caption\": \"an Eevee figurine\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/57_leather handbag.jpg\",\n                        \"caption\": \"a leather handbag\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Eevee figurine\",\n                        \"Eevee figurine\"\n                    ],\n                    [\n                        1,\n                        \"leather handbag\",\n                        \"leather handbag\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 114,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A donut is placed beside a Rolls-Royce hood ornament.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/40_Rolls-Royce hood ornament.jpg\",\n                        \"caption\": \"a Rolls-Royce hood ornament\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/38_donut.jpg\",\n                        \"caption\": \"a donut\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Rolls-Royce hood ornament\",\n                        \"Rolls-Royce hood ornament\"\n                    ],\n                    [\n                        1,\n                        \"donut\",\n                        \"donut\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 115,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A roll of film lies beside a teddy bear.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/61_roll of film.jpg\",\n                        \"caption\": \"a roll of film\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/46_teddy bear.jpg\",\n                        \"caption\": \"a teddy bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"roll of film\",\n                        \"roll of film\"\n                    ],\n                    [\n                        1,\n                        \"teddy bear\",\n                        \"teddy bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 116,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A hot air balloon hovers above a flamingo float on the water.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/09_hot air balloon.jpg\",\n                        \"caption\": \"a hot air balloon\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/10_flamingo float.jpg\",\n                        \"caption\": \"a flamingo float\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hot air balloon\",\n                        \"hot air balloon\"\n                    ],\n                    [\n                        1,\n                        \"flamingo float\",\n                        \"flamingo float\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 117,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An Eevee figurine sitting beside a donut.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/59_Eevee figurine.jpg\",\n                        \"caption\": \"an Eevee figurine\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/38_donut.jpg\",\n                        \"caption\": \"a donut\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Eevee figurine\",\n                        \"Eevee figurine\"\n                    ],\n                    [\n                        1,\n                        \"donut\",\n                        \"donut\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 118,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An anime space ranger is riding a bicycle in space.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/17_bicycle.jpg\",\n                        \"caption\": \"a bicycle\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/65_anime space ranger.jpg\",\n                        \"caption\": \"an anime space ranger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"bicycle\",\n                        \"bicycle\"\n                    ],\n                    [\n                        1,\n                        \"anime space ranger\",\n                        \"anime space ranger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 119,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An Avatar standing beside a yellow taxi.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/72_Avatar.jpg\",\n                        \"caption\": \"an Avatar\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/44_yellow taxi.jpg\",\n                        \"caption\": \"a yellow taxi\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Avatar\",\n                        \"Avatar\"\n                    ],\n                    [\n                        1,\n                        \"yellow taxi\",\n                        \"yellow taxi\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 120,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is standing in front of his house, facing a wolf.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/14_house.jpg\",\n                        \"caption\": \"a house\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"house\",\n                        \"house\"\n                    ],\n                    [\n                        2,\n                        \"wolf\",\n                        \"wolf\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 121,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman with a cap playing with a puppy.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/32_cap.jpg\",\n                        \"caption\": \"a cap\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/42_puppy.jpg\",\n                        \"caption\": \"a puppy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"cap\",\n                        \"cap\"\n                    ],\n                    [\n                        2,\n                        \"puppy\",\n                        \"puppy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 122,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is holding a roll of film and looking at a deer in the forest.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/61_roll of film.jpg\",\n                        \"caption\": \"a roll of film\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/31_deer.jpg\",\n                        \"caption\": \"a deer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"roll of film\",\n                        \"roll of film\"\n                    ],\n                    [\n                        2,\n                        \"deer\",\n                        \"deer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 123,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is holding a pineapple while a robin is flying above him.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/43_pineapple.jpg\",\n                        \"caption\": \"a pineapple\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"pineapple\",\n                        \"pineapple\"\n                    ],\n                    [\n                        2,\n                        \"robin\",\n                        \"robin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 124,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is holding a Poke Ball and facing a fox.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/54_Poke Ball.jpg\",\n                        \"caption\": \"a Poke Ball\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/10_fox.jpg\",\n                        \"caption\": \"a fox\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"Poke Ball\",\n                        \"Poke Ball\"\n                    ],\n                    [\n                        2,\n                        \"fox\",\n                        \"fox\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 125,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is on a flamingo float while a lion watches nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/10_flamingo float.jpg\",\n                        \"caption\": \"a flamingo float\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/23_lion.jpg\",\n                        \"caption\": \"a lion\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"flamingo float\",\n                        \"flamingo float\"\n                    ],\n                    [\n                        2,\n                        \"lion\",\n                        \"lion\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 126,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An old man is lying on a flamingo float while a toucan perches nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/10_flamingo float.jpg\",\n                        \"caption\": \"a flamingo float\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/37_toucan.jpg\",\n                        \"caption\": \"a toucan\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        1,\n                        \"flamingo float\",\n                        \"flamingo float\"\n                    ],\n                    [\n                        2,\n                        \"toucan\",\n                        \"toucan\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 127,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is looking at his watch while a raccoon is nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/12_watch.jpg\",\n                        \"caption\": \"a watch\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/08_raccoon.jpg\",\n                        \"caption\": \"a raccoon\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"watch\",\n                        \"watch\"\n                    ],\n                    [\n                        2,\n                        \"raccoon\",\n                        \"raccoon\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 128,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is holding a leather handbag while standing in front of a white tiger.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/18_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/57_leather handbag.jpg\",\n                        \"caption\": \"a leather handbag\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/40_white tiger.jpg\",\n                        \"caption\": \"a white tiger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"leather handbag\",\n                        \"leather handbag\"\n                    ],\n                    [\n                        2,\n                        \"white tiger\",\n                        \"white tiger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 129,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is using a vintage camera to take a picture of a toucan.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/23_vintage camera.jpg\",\n                        \"caption\": \"a vintage camera\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/37_toucan.jpg\",\n                        \"caption\": \"a toucan\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"vintage camera\",\n                        \"vintage camera\"\n                    ],\n                    [\n                        2,\n                        \"toucan\",\n                        \"toucan\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 130,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is flying in a hot air balloon with a robot.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/09_hot air balloon.jpg\",\n                        \"caption\": \"a hot air balloon\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/18_robot.jpg\",\n                        \"caption\": \"a robot\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"hot air balloon\",\n                        \"hot air balloon\"\n                    ],\n                    [\n                        2,\n                        \"robot\",\n                        \"robot\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 131,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is sitting on a boat with a vintage computer.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/35_vintage computer.jpg\",\n                        \"caption\": \"a vintage computer\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/62_boat.jpg\",\n                        \"caption\": \"a boat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"vintage computer\",\n                        \"vintage computer\"\n                    ],\n                    [\n                        2,\n                        \"boat\",\n                        \"boat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 132,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is sitting in an armchair and looking at a UFO in the sky.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/11_armchair.jpg\",\n                        \"caption\": \"an armchair\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/47_UFO.jpg\",\n                        \"caption\": \"an UFO\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"armchair\",\n                        \"armchair\"\n                    ],\n                    [\n                        2,\n                        \"UFO\",\n                        \"UFO\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 133,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An old man is wearing headphones inside a hut.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/55_headphones.jpg\",\n                        \"caption\": \"a headphones\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/42_hut.jpg\",\n                        \"caption\": \"a hut\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        1,\n                        \"headphones\",\n                        \"headphones\"\n                    ],\n                    [\n                        2,\n                        \"hut\",\n                        \"hut\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 134,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is wearing headphones and a hat.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/55_headphones.jpg\",\n                        \"caption\": \"a headphones\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/01_hat.jpg\",\n                        \"caption\": \"a hat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"headphones\",\n                        \"headphones\"\n                    ],\n                    [\n                        2,\n                        \"hat\",\n                        \"hat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 135,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is sitting in front of a vintage television under a tree.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/49_vintage television.jpg\",\n                        \"caption\": \"a vintage television\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/08_tree.jpg\",\n                        \"caption\": \"a tree\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"vintage television\",\n                        \"vintage television\"\n                    ],\n                    [\n                        2,\n                        \"tree\",\n                        \"tree\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 136,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is inside a hut playing with a Magic Cube.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/42_hut.jpg\",\n                        \"caption\": \"a hut\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/20_Magic Cube.jpg\",\n                        \"caption\": \"a Magic Cube\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"hut\",\n                        \"hut\"\n                    ],\n                    [\n                        2,\n                        \"Magic Cube\",\n                        \"Magic Cube\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 137,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is standing beside a yellow taxi, looking at an anime space ranger.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/44_yellow taxi.jpg\",\n                        \"caption\": \"a yellow taxi\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/65_anime space ranger.jpg\",\n                        \"caption\": \"an anime space ranger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"yellow taxi\",\n                        \"yellow taxi\"\n                    ],\n                    [\n                        2,\n                        \"anime space ranger\",\n                        \"anime space ranger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 138,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is holding a vintage camera and a teddy bear.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/23_vintage camera.jpg\",\n                        \"caption\": \"a vintage camera\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/13_teddy bear.jpg\",\n                        \"caption\": \"a teddy bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"vintage camera\",\n                        \"vintage camera\"\n                    ],\n                    [\n                        2,\n                        \"teddy bear\",\n                        \"teddy bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 139,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"The old man gazed wistfully at the ancient clock, his fingers tracing the worn ring, memories echoing through time's passage.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/56_clock.jpg\",\n                        \"caption\": \"a clock\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/16_ring.jpg\",\n                        \"caption\": \"a ring\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        1,\n                        \"clock\",\n                        \"clock\"\n                    ],\n                    [\n                        2,\n                        \"ring\",\n                        \"ring\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 140,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is standing in an open field, with an eagle soaring in the sky above him and a dog sitting at his feet.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/14_eagle.jpg\",\n                        \"caption\": \"an eagle\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/07_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"eagle\",\n                        \"eagle\"\n                    ],\n                    [\n                        2,\n                        \"dog\",\n                        \"dog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 141,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is watching a robin flying around an elephant.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/38_elephant.jpg\",\n                        \"caption\": \"an elephant\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"robin\",\n                        \"robin\"\n                    ],\n                    [\n                        2,\n                        \"elephant\",\n                        \"elephant\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 142,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A curious boy gazes in wonder at a vibrant flamingo and a tiny lizard, marveling at nature's contrasts.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/00_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/36_lizard.jpg\",\n                        \"caption\": \"a lizard\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/28_flamingo.jpg\",\n                        \"caption\": \"a flamingo\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"lizard\",\n                        \"lizard\"\n                    ],\n                    [\n                        2,\n                        \"flamingo\",\n                        \"flamingo\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 143,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is watching a lizard and a cat in her garden.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/36_lizard.jpg\",\n                        \"caption\": \"a lizard\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/44_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"lizard\",\n                        \"lizard\"\n                    ],\n                    [\n                        2,\n                        \"cat\",\n                        \"cat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 144,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is playing with a parrot and a puppy in the yard.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/41_parrot.jpg\",\n                        \"caption\": \"a parrot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/42_puppy.jpg\",\n                        \"caption\": \"a puppy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"parrot\",\n                        \"parrot\"\n                    ],\n                    [\n                        2,\n                        \"puppy\",\n                        \"puppy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 145,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman is watching a cat while an eagle soars in the sky above.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/34_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/14_eagle.jpg\",\n                        \"caption\": \"an eagle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"cat\",\n                        \"cat\"\n                    ],\n                    [\n                        2,\n                        \"eagle\",\n                        \"eagle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 146,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A brave little girl stands wide-eyed, watching a majestic lion and tiger, feeling a mix of awe and excitement.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/30_lion.jpg\",\n                        \"caption\": \"a lion\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/35_tiger.jpg\",\n                        \"caption\": \"a tiger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"lion\",\n                        \"lion\"\n                    ],\n                    [\n                        2,\n                        \"tiger\",\n                        \"tiger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 147,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is watching a robin and a rooster in the yard.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/09_rooster.jpg\",\n                        \"caption\": \"a rooster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"robin\",\n                        \"robin\"\n                    ],\n                    [\n                        2,\n                        \"rooster\",\n                        \"rooster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 148,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"In a snow-clad forest, a man cautiously approaches a wolf while a majestic polar bear watches from a distance.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/13_polar bear.jpg\",\n                        \"caption\": \"a polar bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"wolf\",\n                        \"wolf\"\n                    ],\n                    [\n                        2,\n                        \"polar bear\",\n                        \"polar bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 149,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is standing between a cat and a tiger.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/44_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/35_tiger.jpg\",\n                        \"caption\": \"a tiger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"cat\",\n                        \"cat\"\n                    ],\n                    [\n                        2,\n                        \"tiger\",\n                        \"tiger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 150,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A Siamese cat is lying beside a sneaker and a t-shirt.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/21_Siamese cat.jpg\",\n                        \"caption\": \"a Siamese cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/22_sneaker.jpg\",\n                        \"caption\": \"a sneaker\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/41_t-shirt.jpg\",\n                        \"caption\": \"a t-shirt\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Siamese cat\",\n                        \"Siamese cat\"\n                    ],\n                    [\n                        1,\n                        \"sneaker\",\n                        \"sneaker\"\n                    ],\n                    [\n                        2,\n                        \"t-shirt\",\n                        \"t-shirt\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 151,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A wolf is standing beside a basketball shoe near a flamingo float.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/07_basketball shoe.jpg\",\n                        \"caption\": \"a basketball shoe\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/10_flamingo float.jpg\",\n                        \"caption\": \"a flamingo float\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"wolf\",\n                        \"wolf\"\n                    ],\n                    [\n                        1,\n                        \"basketball shoe\",\n                        \"basketball shoe\"\n                    ],\n                    [\n                        2,\n                        \"flamingo float\",\n                        \"flamingo float\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 152,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A parrot is standing on an anime samurai's shoulder while the samurai is in front of a vintage computer.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/41_parrot.jpg\",\n                        \"caption\": \"a parrot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/69_anime samurai.jpg\",\n                        \"caption\": \"an anime samurai\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/35_vintage computer.jpg\",\n                        \"caption\": \"a vintage computer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"parrot\",\n                        \"parrot\"\n                    ],\n                    [\n                        1,\n                        \"anime samurai\",\n                        \"anime samurai\"\n                    ],\n                    [\n                        2,\n                        \"vintage computer\",\n                        \"vintage computer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 153,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A dolphin is swimming beside a vintage van that has an anime space ranger sticker on it.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/39_dolphin.jpg\",\n                        \"caption\": \"a dolphin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/21_vintage van.jpg\",\n                        \"caption\": \"a vintage van\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/65_anime space ranger.jpg\",\n                        \"caption\": \"an anime space ranger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"dolphin\",\n                        \"dolphin\"\n                    ],\n                    [\n                        1,\n                        \"vintage van\",\n                        \"vintage van\"\n                    ],\n                    [\n                        2,\n                        \"anime space ranger\",\n                        \"anime space ranger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 154,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A Siamese cat is sitting beside a vintage camera and a cactus.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/21_Siamese cat.jpg\",\n                        \"caption\": \"a Siamese cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/24_vintage camera.jpg\",\n                        \"caption\": \"a vintage camera\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/53_cactus.jpg\",\n                        \"caption\": \"a cactus\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Siamese cat\",\n                        \"Siamese cat\"\n                    ],\n                    [\n                        1,\n                        \"vintage camera\",\n                        \"vintage camera\"\n                    ],\n                    [\n                        2,\n                        \"cactus\",\n                        \"cactus\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 155,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A grasshopper is near an Eevee figurine in front of a wooden house.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/29_grasshopper.jpg\",\n                        \"caption\": \"a grasshopper\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/59_Eevee figurine.jpg\",\n                        \"caption\": \"an Eevee figurine\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/45_wooden house.jpg\",\n                        \"caption\": \"a wooden house\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"grasshopper\",\n                        \"grasshopper\"\n                    ],\n                    [\n                        1,\n                        \"Eevee figurine\",\n                        \"Eevee figurine\"\n                    ],\n                    [\n                        2,\n                        \"wooden house\",\n                        \"wooden house\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 156,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A fox is standing beside an anime girl who is holding a rubber duck.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/10_fox.jpg\",\n                        \"caption\": \"a fox\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/68_anime girl.jpg\",\n                        \"caption\": \"an anime girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/50_rubber duck.jpg\",\n                        \"caption\": \"a rubber duck\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"fox\",\n                        \"fox\"\n                    ],\n                    [\n                        1,\n                        \"anime girl\",\n                        \"anime girl\"\n                    ],\n                    [\n                        2,\n                        \"rubber duck\",\n                        \"rubber duck\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 157,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A cat is standing beside a pixelated warrior who is holding a donut.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/44_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/67_pixelated warrior.jpg\",\n                        \"caption\": \"a pixelated warrior\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/38_donut.jpg\",\n                        \"caption\": \"a donut\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cat\",\n                        \"cat\"\n                    ],\n                    [\n                        1,\n                        \"pixelated warrior\",\n                        \"pixelated warrior\"\n                    ],\n                    [\n                        2,\n                        \"donut\",\n                        \"donut\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 158,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A white tiger is near a robot in front of a house.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/40_white tiger.jpg\",\n                        \"caption\": \"a white tiger\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/18_robot.jpg\",\n                        \"caption\": \"a robot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/14_house.jpg\",\n                        \"caption\": \"a house\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"white tiger\",\n                        \"white tiger\"\n                    ],\n                    [\n                        1,\n                        \"robot\",\n                        \"robot\"\n                    ],\n                    [\n                        2,\n                        \"house\",\n                        \"house\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 159,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A shark is swimming near the shore where cherry blossoms are floating on the water, and a steam locomotive is chugging along the nearby railway.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/06_shark.jpg\",\n                        \"caption\": \"a shark\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/03_cherry blossoms.jpg\",\n                        \"caption\": \"a cherry blossoms\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/19_steam locomotive.jpg\",\n                        \"caption\": \"a steam locomotive\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"shark\",\n                        \"shark\"\n                    ],\n                    [\n                        1,\n                        \"cherry blossoms\",\n                        \"cherry blossoms\"\n                    ],\n                    [\n                        2,\n                        \"steam locomotive\",\n                        \"steam locomotive\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 160,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl and a girl are admiring a Rolls-Royce hood ornament.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/40_Rolls-Royce hood ornament.jpg\",\n                        \"caption\": \"a Rolls-Royce hood ornament\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"girl\",\n                        \"girl\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"Rolls-Royce hood ornament\",\n                        \"Rolls-Royce hood ornament\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 161,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and another man are standing near a pineapple.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/43_pineapple.jpg\",\n                        \"caption\": \"a pineapple\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"pineapple\",\n                        \"pineapple\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 162,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy and a little girl are playing with a rubber duck.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/50_rubber duck.jpg\",\n                        \"caption\": \"a rubber duck\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        2,\n                        \"rubber duck\",\n                        \"rubber duck\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 163,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and a man are standing in front of a house.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/14_house.jpg\",\n                        \"caption\": \"a house\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"house\",\n                        \"house\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 164,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman, a man, and a pixelated warrior stand side by side.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/67_pixelated warrior.jpg\",\n                        \"caption\": \"a pixelated warrior\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"pixelated warrior\",\n                        \"pixelated warrior\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 165,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman are standing near a stop sign.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/51_stop sign.jpg\",\n                        \"caption\": \"a stop sign\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        2,\n                        \"stop sign\",\n                        \"stop sign\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 166,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman, an old man, and an anime girl are standing together in a park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/68_anime girl.jpg\",\n                        \"caption\": \"an anime girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        2,\n                        \"anime girl\",\n                        \"anime girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 167,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and an old man are sitting together, with a beer can on the table between them.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/04_beer can.jpg\",\n                        \"caption\": \"a beer can\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        2,\n                        \"beer can\",\n                        \"beer can\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 168,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl and a boy are on a boat.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/62_boat.jpg\",\n                        \"caption\": \"a boat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        2,\n                        \"boat\",\n                        \"boat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 169,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and another man are looking at an avocado together.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/18_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/06_avocado.jpg\",\n                        \"caption\": \"an avocado\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"avocado\",\n                        \"avocado\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 170,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl and a man are watching a cotton-top tamarin in a zoo.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/26_cotton-top tamarin.jpg\",\n                        \"caption\": \"a cotton-top tamarin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"cotton-top tamarin\",\n                        \"cotton-top tamarin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 171,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy and a man are watching a hamster play in a cage.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"hamster\",\n                        \"hamster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 172,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a man are looking at a parrot.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/18_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/41_parrot.jpg\",\n                        \"caption\": \"a parrot\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"parrot\",\n                        \"parrot\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 173,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman are playing with a puppy in the park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/18_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/42_puppy.jpg\",\n                        \"caption\": \"a puppy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        2,\n                        \"puppy\",\n                        \"puppy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 174,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man is watching a girl play with a hamster.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"girl\",\n                        \"girl\"\n                    ],\n                    [\n                        2,\n                        \"hamster\",\n                        \"hamster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 175,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a woman are looking at a panda in the zoo.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/33_panda.jpg\",\n                        \"caption\": \"a panda\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        2,\n                        \"panda\",\n                        \"panda\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 176,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and a girl are standing in the snow, facing a polar bear.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/13_polar bear.jpg\",\n                        \"caption\": \"a polar bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"girl\",\n                        \"girl\"\n                    ],\n                    [\n                        2,\n                        \"polar bear\",\n                        \"polar bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 177,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and a man are standing beside a llama.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/24_llama.jpg\",\n                        \"caption\": \"a llama\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"llama\",\n                        \"llama\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 178,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A woman and a man are observing a lizard in the garden.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/36_lizard.jpg\",\n                        \"caption\": \"a lizard\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"lizard\",\n                        \"lizard\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 179,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and another man are looking at an eagle soaring in the sky.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/14_eagle.jpg\",\n                        \"caption\": \"an eagle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"eagle\",\n                        \"eagle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 180,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man, a man, and a woman are standing in a park chatting.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 181,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man in blue, a man in black, and a man with sunglasses are standing together, chatting and laughing.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"man\",\n                        \"man\",\n                        3\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 182,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An old man, a man, and a woman are standing in a park chatting.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 183,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A girl, a man, and a woman are sitting together in a park, chatting and enjoying the sunny day.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/18_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"girl\",\n                        \"girl\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 184,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"Three men, a young man, an old man, and another man, are standing together chatting on the street corner.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        2,\n                        \"man\",\n                        \"man\",\n                        3\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 185,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A little girl is standing between a man and another man, having a conversation with them.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/18_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"man\",\n                        \"man\",\n                        2\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 186,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A boy is standing between a man and a woman, having a conversation.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        2,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 187,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man and another man are walking with a little girl in the park.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"little girl\",\n                        \"little girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 188,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A girl, an old man, and a woman are sitting on a park bench chatting.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"girl\",\n                        \"girl\"\n                    ],\n                    [\n                        1,\n                        \"old man\",\n                        \"old man\"\n                    ],\n                    [\n                        2,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 189,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A man, another man, and a boy are standing together in the park chatting.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ],\n                    [\n                        1,\n                        \"man\",\n                        \"man\",\n                        2\n                    ],\n                    [\n                        2,\n                        \"boy\",\n                        \"boy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 190,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"The vintage camera, vintage computer, and rubber duck together create a nostalgic and whimsical atmosphere in the sunlight.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/24_vintage camera.jpg\",\n                        \"caption\": \"a vintage camera\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/35_vintage computer.jpg\",\n                        \"caption\": \"a vintage computer\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/50_rubber duck.jpg\",\n                        \"caption\": \"a rubber duck\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"vintage camera\",\n                        \"vintage camera\"\n                    ],\n                    [\n                        1,\n                        \"vintage computer\",\n                        \"vintage computer\"\n                    ],\n                    [\n                        2,\n                        \"rubber duck\",\n                        \"rubber duck\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 191,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"In a sunlit meadow, an Avatar gracefully donned a cap, its hand delicately holding a glowing ring.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/72_Avatar.jpg\",\n                        \"caption\": \"an Avatar\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/16_ring.jpg\",\n                        \"caption\": \"a ring\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/32_cap.jpg\",\n                        \"caption\": \"a cap\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Avatar\",\n                        \"Avatar\"\n                    ],\n                    [\n                        1,\n                        \"ring\",\n                        \"ring\"\n                    ],\n                    [\n                        2,\n                        \"cap\",\n                        \"cap\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 192,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A vintage television is on, and there's a cocktail and a donut on the table beside it.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/63_cocktail.jpg\",\n                        \"caption\": \"a cocktail\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/38_donut.jpg\",\n                        \"caption\": \"a donut\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/49_vintage television.jpg\",\n                        \"caption\": \"a vintage television\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cocktail\",\n                        \"cocktail\"\n                    ],\n                    [\n                        1,\n                        \"donut\",\n                        \"donut\"\n                    ],\n                    [\n                        2,\n                        \"vintage television\",\n                        \"vintage television\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 193,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A street lamp illuminates an Eevee figurine placed next to a piggy bank on the sidewalk.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/59_Eevee figurine.jpg\",\n                        \"caption\": \"an Eevee figurine\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/31_piggy bank.jpg\",\n                        \"caption\": \"a piggy bank\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/15_street lamp.jpg\",\n                        \"caption\": \"a street lamp\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Eevee figurine\",\n                        \"Eevee figurine\"\n                    ],\n                    [\n                        1,\n                        \"piggy bank\",\n                        \"piggy bank\"\n                    ],\n                    [\n                        2,\n                        \"street lamp\",\n                        \"street lamp\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 194,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An anime girl is standing in front of a hut, holding an Eevee figurine.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/42_hut.jpg\",\n                        \"caption\": \"a hut\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/66_anime girl.jpg\",\n                        \"caption\": \"an anime girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/59_Eevee figurine.jpg\",\n                        \"caption\": \"an Eevee figurine\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hut\",\n                        \"hut\"\n                    ],\n                    [\n                        1,\n                        \"anime girl\",\n                        \"anime girl\"\n                    ],\n                    [\n                        2,\n                        \"Eevee figurine\",\n                        \"Eevee figurine\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 195,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A robot is carrying a backpack and standing next to a pineapple.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/43_pineapple.jpg\",\n                        \"caption\": \"a pineapple\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/64_robot.jpg\",\n                        \"caption\": \"a robot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/28_backpack.jpg\",\n                        \"caption\": \"a backpack\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"pineapple\",\n                        \"pineapple\"\n                    ],\n                    [\n                        1,\n                        \"robot\",\n                        \"robot\"\n                    ],\n                    [\n                        2,\n                        \"backpack\",\n                        \"backpack\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 196,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An anime girl is sitting next to a piggy bank, holding a mug in her hand.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/27_mug.jpg\",\n                        \"caption\": \"a mug\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/66_anime girl.jpg\",\n                        \"caption\": \"an anime girl\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/31_piggy bank.jpg\",\n                        \"caption\": \"a piggy bank\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"mug\",\n                        \"mug\"\n                    ],\n                    [\n                        1,\n                        \"anime girl\",\n                        \"anime girl\"\n                    ],\n                    [\n                        2,\n                        \"piggy bank\",\n                        \"piggy bank\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 197,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A UFO hovers in the sky while a pineapple lies on the ground nearby, and a vintage camera is placed beside the pineapple, ready to capture this strange scene.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/47_UFO.jpg\",\n                        \"caption\": \"an UFO\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/43_pineapple.jpg\",\n                        \"caption\": \"a pineapple\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/24_vintage camera.jpg\",\n                        \"caption\": \"a vintage camera\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"UFO\",\n                        \"UFO\"\n                    ],\n                    [\n                        1,\n                        \"pineapple\",\n                        \"pineapple\"\n                    ],\n                    [\n                        2,\n                        \"vintage camera\",\n                        \"vintage camera\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 198,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An anime Spider-Man stands near a stop sign, wearing a hat.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/01_hat.jpg\",\n                        \"caption\": \"a hat\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/51_stop sign.jpg\",\n                        \"caption\": \"a stop sign\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/71_anime Spider-Man.jpg\",\n                        \"caption\": \"an anime Spider-Man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hat\",\n                        \"hat\"\n                    ],\n                    [\n                        1,\n                        \"stop sign\",\n                        \"stop sign\"\n                    ],\n                    [\n                        2,\n                        \"anime Spider-Man\",\n                        \"anime Spider-Man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 199,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An anime space ranger is holding a Poke Ball while using a hair dryer in a cosmic setting.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/54_Poke Ball.jpg\",\n                        \"caption\": \"a Poke Ball\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/65_anime space ranger.jpg\",\n                        \"caption\": \"an anime space ranger\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/26_hair dryer.jpg\",\n                        \"caption\": \"a hair dryer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"Poke Ball\",\n                        \"Poke Ball\"\n                    ],\n                    [\n                        1,\n                        \"anime space ranger\",\n                        \"anime space ranger\"\n                    ],\n                    [\n                        2,\n                        \"hair dryer\",\n                        \"hair dryer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 200,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A parrot is perched on the saddle of a horse, while a kitten is playing at the horse's hooves.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/41_parrot.jpg\",\n                        \"caption\": \"a parrot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/03_horse.jpg\",\n                        \"caption\": \"a horse\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/00_kitten.jpg\",\n                        \"caption\": \"a kitten\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"parrot\",\n                        \"parrot\"\n                    ],\n                    [\n                        1,\n                        \"horse\",\n                        \"horse\"\n                    ],\n                    [\n                        2,\n                        \"kitten\",\n                        \"kitten\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 201,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A robin is perched on a branch above while a white tiger slowly approaches a curious kitten in a forest clearing.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/19_robin.jpg\",\n                        \"caption\": \"a robin\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/40_white tiger.jpg\",\n                        \"caption\": \"a white tiger\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/02_kitten.jpg\",\n                        \"caption\": \"a kitten\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"robin\",\n                        \"robin\"\n                    ],\n                    [\n                        1,\n                        \"white tiger\",\n                        \"white tiger\"\n                    ],\n                    [\n                        2,\n                        \"kitten\",\n                        \"kitten\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 202,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"An eagle soars in the sky above a grassy field where a horse is grazing, and a French bulldog is running around nearby.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/14_eagle.jpg\",\n                        \"caption\": \"an eagle\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/03_horse.jpg\",\n                        \"caption\": \"a horse\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/43_French bulldog.jpg\",\n                        \"caption\": \"a French bulldog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"eagle\",\n                        \"eagle\"\n                    ],\n                    [\n                        1,\n                        \"horse\",\n                        \"horse\"\n                    ],\n                    [\n                        2,\n                        \"French bulldog\",\n                        \"French bulldog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 203,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"In a sunlit oasis, a flamingo dances gracefully beside a lounging tiger and a curious, fluffy llama. Nature's harmony.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/28_flamingo.jpg\",\n                        \"caption\": \"a flamingo\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/35_tiger.jpg\",\n                        \"caption\": \"a tiger\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/24_llama.jpg\",\n                        \"caption\": \"a llama\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"flamingo\",\n                        \"flamingo\"\n                    ],\n                    [\n                        1,\n                        \"tiger\",\n                        \"tiger\"\n                    ],\n                    [\n                        2,\n                        \"llama\",\n                        \"llama\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 204,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A tiger is lurking in the tall grass, while a hamster scurries near a small burrow, and a llama stands calmly in the open space not far away.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/35_tiger.jpg\",\n                        \"caption\": \"a tiger\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/24_llama.jpg\",\n                        \"caption\": \"a llama\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"tiger\",\n                        \"tiger\"\n                    ],\n                    [\n                        1,\n                        \"hamster\",\n                        \"hamster\"\n                    ],\n                    [\n                        2,\n                        \"llama\",\n                        \"llama\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 205,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A parrot is perched on a branch, squawking, while a dog is running around barking nearby, and a crab is slowly crawling on the sandy shore.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/41_parrot.jpg\",\n                        \"caption\": \"a parrot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/12_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/04_crab.jpg\",\n                        \"caption\": \"a crab\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"parrot\",\n                        \"parrot\"\n                    ],\n                    [\n                        1,\n                        \"dog\",\n                        \"dog\"\n                    ],\n                    [\n                        2,\n                        \"crab\",\n                        \"crab\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 206,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A hamster, a llama and a tiger are in a large, wild-like enclosure. The hamster scurries around near some small burrows, the llama stands calmly chewing on some grass, and the tiger prowls around the perimeter, eyeing the other two animals. \",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/24_llama.jpg\",\n                        \"caption\": \"a llama\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/35_tiger.jpg\",\n                        \"caption\": \"a tiger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hamster\",\n                        \"hamster\"\n                    ],\n                    [\n                        1,\n                        \"llama\",\n                        \"llama\"\n                    ],\n                    [\n                        2,\n                        \"tiger\",\n                        \"tiger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 207,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"A corgi is standing on the shore, looking out at the ocean where jellyfish are floating. Suddenly, a wolf appears from the nearby forest and approaches the corgi.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/16_jellyfish.jpg\",\n                        \"caption\": \"a jellyfish\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/22_corgi.jpg\",\n                        \"caption\": \"a corgi\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"jellyfish\",\n                        \"jellyfish\"\n                    ],\n                    [\n                        1,\n                        \"corgi\",\n                        \"corgi\"\n                    ],\n                    [\n                        2,\n                        \"wolf\",\n                        \"wolf\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 208,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"Under a vibrant sunset, a flamingo wades in shimmering waters as a parrot sings atop a nearby graceful deer. Tranquility.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/28_flamingo.jpg\",\n                        \"caption\": \"a flamingo\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/41_parrot.jpg\",\n                        \"caption\": \"a parrot\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/31_deer.jpg\",\n                        \"caption\": \"a deer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"flamingo\",\n                        \"flamingo\"\n                    ],\n                    [\n                        1,\n                        \"parrot\",\n                        \"parrot\"\n                    ],\n                    [\n                        2,\n                        \"deer\",\n                        \"deer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 209,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"In a serene jungle glade, a panda munches bamboo, while a lion observes and a playful fox darts around. Bliss.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/33_panda.jpg\",\n                        \"caption\": \"a panda\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/30_lion.jpg\",\n                        \"caption\": \"a lion\"\n                    },\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/10_fox.jpg\",\n                        \"caption\": \"a fox\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"panda\",\n                        \"panda\"\n                    ],\n                    [\n                        1,\n                        \"lion\",\n                        \"lion\"\n                    ],\n                    [\n                        2,\n                        \"fox\",\n                        \"fox\"\n                    ]\n                ]\n            }\n        ]\n    }\n]"
  },
  {
    "path": "eval/tools/XVerseBench_multi_DSG.json",
    "content": "[\n    {\n        \"prompt\": \"A man is riding a motorcycle.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a motorcycle?\",\n            \"3\": \"Is the man riding the motorcycle?\"\n        }\n    },\n    {\n        \"prompt\": \"An anime Spider-Man is playing with a boy.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a Spider - Man?\",\n            \"2\": \"Is there a boy?\",\n            \"3\": \"Is the Spider - Man in anime style?\",\n            \"4\": \"Is the Spider - Man playing with the boy?\"\n        }\n    },\n    {\n        \"prompt\": \"A man stands beside a vintage van.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - type\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a van?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the van vintage?\",\n            \"5\": \"Is the man beside the van?\"\n        }\n    },\n    {\n        \"prompt\": \"An old man meets a pixelated warrior.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a warrior?\",\n            \"3\": \"Is the man old?\",\n            \"4\": \"Is the warrior pixelated?\",\n            \"5\": \"Is the man meeting the warrior?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman stands in front of a hut.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a hut?\",\n            \"3\": \"Is the woman standing?\",\n            \"4\": \"Is the woman in front of the hut?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is playing a snare drum.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a snare drum?\",\n            \"3\": \"Is the woman playing the snare drum?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is holding a leather handbag.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - material\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a handbag?\",\n            \"3\": \"Is the handbag made of leather?\",\n            \"4\": \"Is the man holding the handbag?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is using a hair dryer.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a hair dryer?\",\n            \"3\": \"Is the man using a hair dryer?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is sitting on a motorcycle.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a motorcycle?\",\n            \"3\": \"Is the woman sitting?\",\n            \"4\": \"Is the woman on the motorcycle?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is holding a pineapple.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a pineapple?\",\n            \"3\": \"Is the man holding the pineapple?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is looking at a clock.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a clock?\",\n            \"3\": \"Is the man looking at the clock?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and an anime man standing side by side\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is the man an anime man?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the man standing?\",\n            \"6\": \"Are the woman and the man standing side by side?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is holding a vase.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a vase?\",\n            \"3\": \"Is the woman holding the vase?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is holding a vintage camera.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a camera?\",\n            \"3\": \"Is the man holding the camera?\",\n            \"4\": \"Is the camera vintage?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is standing beside a classical bust.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - style\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a bust?\",\n            \"3\": \"Is the woman standing?\",\n            \"4\": \"Is the bust classical?\",\n            \"5\": \"Is the woman beside the bust?\"\n        }\n    },\n    {\n        \"prompt\": \"A curious boy discovered a ring in the forest.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a ring?\",\n            \"3\": \"Is there a forest?\",\n            \"4\": \"Is the boy curious?\",\n            \"5\": \"Did the boy discover the ring?\",\n            \"6\": \"Is the ring in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"A man stands beside a steam locomotive.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a steam locomotive?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man beside the steam locomotive?\"\n        }\n    },\n    {\n        \"prompt\": \"A man holding a Poke Ball.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a Poke Ball?\",\n            \"3\": \"Is the man holding a Poke Ball?\"\n        }\n    },\n    {\n        \"prompt\": \"A man standing among cherry blossoms.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Are there cherry blossoms?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man among the cherry blossoms?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is standing next to a cactus.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a cactus?\",\n            \"3\": \"Is the boy standing?\",\n            \"4\": \"Is the boy next to the cactus?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is standing beside another man.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there another man?\",\n            \"3\": \"Is the first man standing?\",\n            \"4\": \"Is the first man beside the second man?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is standing beside a man.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is the boy standing?\",\n            \"4\": \"Is the boy beside the man?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a boy are standing side by side.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a boy?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the boy standing?\",\n            \"5\": \"Are the man and the boy standing side by side?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and a girl standing side by side in a park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a girl?\",\n            \"3\": \"Is there a park?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the girl standing?\",\n            \"6\": \"Are the woman and the girl standing side by side?\",\n            \"7\": \"Is the woman in the park?\",\n            \"8\": \"Is the girl in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman standing side by side in a park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"attribute - type\",\n            \"6\": \"attribute - state\",\n            \"7\": \"attribute - state\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a park?\",\n            \"4\": \"Is the man male?\",\n            \"5\": \"Is the woman female?\",\n            \"6\": \"Is the man standing?\",\n            \"7\": \"Is the woman standing?\",\n            \"8\": \"Are the man and the woman standing side by side?\",\n            \"9\": \"Is the man in the park?\",\n            \"10\": \"Is the woman in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"An old man and a man standing together on the street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ],\n            \"8\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an old man?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a street?\",\n            \"4\": \"Is the old man old?\",\n            \"5\": \"Are the old man and the man together?\",\n            \"6\": \"Is the old man on the street?\",\n            \"7\": \"Is the man on the street?\",\n            \"8\": \"Are the man and the old man together?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and a girl standing together in a park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a girl?\",\n            \"3\": \"Is there a park?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the girl standing?\",\n            \"6\": \"Are the woman and the girl together?\",\n            \"7\": \"Is the woman in the park?\",\n            \"8\": \"Is the girl in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman standing side by side.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Are the man and the woman standing side by side?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and another man standing side by side on a street, having a conversation.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ],\n            \"9\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there another man?\",\n            \"3\": \"Is there a street?\",\n            \"4\": \"Is the first man standing?\",\n            \"5\": \"Is the second man standing?\",\n            \"6\": \"Are the two men standing side by side?\",\n            \"7\": \"Is the first man on the street?\",\n            \"8\": \"Is the second man on the street?\",\n            \"9\": \"Are the two men having a conversation?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman standing together in a park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a park?\",\n            \"4\": \"Is the man standing?\",\n            \"5\": \"Is the woman standing?\",\n            \"6\": \"Are the man and the woman together?\",\n            \"7\": \"Is the man in the park?\",\n            \"8\": \"Is the woman in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl is walking hand-in-hand with a woman on a sunny street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - scale\",\n            \"5\": \"attribute - state\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                3\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                1,\n                3\n            ],\n            \"9\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a street?\",\n            \"4\": \"Is the girl little?\",\n            \"5\": \"Is the street sunny?\",\n            \"6\": \"Is the girl walking?\",\n            \"7\": \"Is the girl walking hand - in - hand with the woman?\",\n            \"8\": \"Is the girl on the street?\",\n            \"9\": \"Is the woman on the street?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman standing together on a sunny street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ],\n            \"9\": [\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a street?\",\n            \"4\": \"Is the man standing?\",\n            \"5\": \"Is the woman standing?\",\n            \"6\": \"Are the man and the woman together?\",\n            \"7\": \"Is the man on the street?\",\n            \"8\": \"Is the woman on the street?\",\n            \"9\": \"Is the street sunny?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and another man standing side by side, having a conversation.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there another man?\",\n            \"3\": \"Is the first man standing?\",\n            \"4\": \"Is the second man standing?\",\n            \"5\": \"Are the two men standing side by side?\",\n            \"6\": \"Are the two men having a conversation?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and a man standing side by side in a park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a park?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the man standing?\",\n            \"6\": \"Are the woman and the man standing side by side?\",\n            \"7\": \"Is the woman in the park?\",\n            \"8\": \"Is the man in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl is standing beside a man.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - scale\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is the girl little?\",\n            \"4\": \"Is the girl standing?\",\n            \"5\": \"Is the girl beside the man?\"\n        }\n    },\n    {\n        \"prompt\": \"A girl is standing beside a woman, having a friendly chat.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - gender\",\n            \"5\": \"attribute - gender\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Are the girl and the woman having a friendly chat?\",\n            \"4\": \"Is the girl female?\",\n            \"5\": \"Is the woman female?\",\n            \"6\": \"Is the girl beside the woman?\",\n            \"7\": \"Is the girl standing?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman standing together\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - gender\",\n            \"4\": \"attribute - gender\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is the man male?\",\n            \"4\": \"Is the woman female?\",\n            \"5\": \"Is the man standing?\",\n            \"6\": \"Is the woman standing?\",\n            \"7\": \"Are the man and the woman standing together?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is standing beside another man.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there another man?\",\n            \"3\": \"Is the first man standing?\",\n            \"4\": \"Is the first man beside the second man?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl is standing beside a man.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - scale\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is the girl little?\",\n            \"4\": \"Is the girl standing?\",\n            \"5\": \"Is the girl beside the man?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman standing side by side in a park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"attribute - type\",\n            \"6\": \"attribute - state\",\n            \"7\": \"attribute - state\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a park?\",\n            \"4\": \"Is the man male?\",\n            \"5\": \"Is the woman female?\",\n            \"6\": \"Is the man standing?\",\n            \"7\": \"Is the woman standing?\",\n            \"8\": \"Are the man and the woman standing side by side?\",\n            \"9\": \"Is the man in the park?\",\n            \"10\": \"Is the woman in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is swimming with a sea turtle in the ocean.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                3\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a sea turtle?\",\n            \"3\": \"Is there an ocean?\",\n            \"4\": \"Is the man swimming in the ocean?\",\n            \"5\": \"Is the sea turtle swimming in the ocean?\",\n            \"6\": \"Is the man swimming with the sea turtle?\",\n            \"7\": \"Is the man in the ocean?\",\n            \"8\": \"Is the sea turtle in the ocean?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is playing with a dog.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a dog?\",\n            \"3\": \"Is the boy playing with the dog?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is standing in the forest, facing a wolf.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a forest?\",\n            \"3\": \"Is there a wolf?\",\n            \"4\": \"Is the man standing?\",\n            \"5\": \"Is the man in the forest?\",\n            \"6\": \"Is the man facing the wolf?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is playing with a hamster.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a hamster?\",\n            \"3\": \"Is the boy playing with the hamster?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is standing beside a rooster.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a rooster?\",\n            \"3\": \"Is the woman standing?\",\n            \"4\": \"Is the woman beside the rooster?\"\n        }\n    },\n    {\n        \"prompt\": \"A man standing face-to-face with a lion in the wild.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a lion?\",\n            \"3\": \"Is there a wild area?\",\n            \"4\": \"Is the man standing?\",\n            \"5\": \"Is the man face - to - face with the lion?\",\n            \"6\": \"Is the man in the wild?\",\n            \"7\": \"Is the lion in the wild?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is standing in front of a lion.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a lion?\",\n            \"3\": \"Is the woman standing?\",\n            \"4\": \"Is the woman in front of the lion?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is riding a horse.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a horse?\",\n            \"3\": \"Is the man riding the horse?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is observing a grasshopper.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a grasshopper?\",\n            \"3\": \"Is the man observing the grasshopper?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is looking at a frog.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a frog?\",\n            \"3\": \"Is the man looking at the frog?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is playing with a corgi.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a corgi?\",\n            \"3\": \"Is the boy playing with the corgi?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is walking a corgi on a street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a corgi?\",\n            \"3\": \"Is there a street?\",\n            \"4\": \"Is the woman walking the corgi?\",\n            \"5\": \"Is the woman on the street?\",\n            \"6\": \"Is the corgi on the street?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is holding a Sphynx cat.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a cat?\",\n            \"3\": \"Is the cat a Sphynx cat?\",\n            \"4\": \"Is the woman holding the cat?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is looking at a frog in a small pond.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"attribute - size\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a frog?\",\n            \"3\": \"Is there a pond?\",\n            \"4\": \"Is the man looking at the frog?\",\n            \"5\": \"Is the frog in the pond?\",\n            \"6\": \"Is the pond small?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is walking with a dog on the street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a dog?\",\n            \"3\": \"Is there a street?\",\n            \"4\": \"Is the man walking?\",\n            \"5\": \"Is the man with the dog?\",\n            \"6\": \"Is the man on the street?\",\n            \"7\": \"Is the dog on the street?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is looking at a crab on the beach.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a crab?\",\n            \"3\": \"Is there a beach?\",\n            \"4\": \"Is the woman looking at the crab?\",\n            \"5\": \"Is the crab on the beach?\",\n            \"6\": \"Is the woman on the beach?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is standing beside a flamingo.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a flamingo?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man beside the flamingo?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is interacting with a dolphin.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a dolphin?\",\n            \"3\": \"Is the woman interacting with the dolphin?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl is playing with a puppy.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - scale\",\n            \"4\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a puppy?\",\n            \"3\": \"Is the girl little?\",\n            \"4\": \"Is the girl playing with the puppy?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is swimming with a dolphin in the sea.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a dolphin?\",\n            \"3\": \"Is there a sea?\",\n            \"4\": \"Is the man swimming?\",\n            \"5\": \"Is the dolphin swimming?\",\n            \"6\": \"Is the man swimming with the dolphin?\",\n            \"7\": \"Is the man in the sea?\",\n            \"8\": \"Is the dolphin in the sea?\"\n        }\n    },\n    {\n        \"prompt\": \"An elephant is carrying a backpack on its back.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an elephant?\",\n            \"2\": \"Is there a backpack?\",\n            \"3\": \"Does the elephant have a back?\",\n            \"4\": \"Is the elephant carrying the backpack on its back?\"\n        }\n    },\n    {\n        \"prompt\": \"A wolf is standing beside a teapot.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a wolf?\",\n            \"2\": \"Is there a teapot?\",\n            \"3\": \"Is the wolf standing?\",\n            \"4\": \"Is the wolf beside the teapot?\"\n        }\n    },\n    {\n        \"prompt\": \"A deer standing beside a vintage van.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - type\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a deer?\",\n            \"2\": \"Is there a van?\",\n            \"3\": \"Is the deer standing?\",\n            \"4\": \"Is the van vintage?\",\n            \"5\": \"Is the deer beside the van?\"\n        }\n    },\n    {\n        \"prompt\": \"A cotton-top tamarin is sitting under a street lamp.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a tamarin?\",\n            \"2\": \"Is there a street lamp?\",\n            \"3\": \"Is the tamarin a cotton - top tamarin?\",\n            \"4\": \"Is the tamarin sitting?\",\n            \"5\": \"Is the tamarin under the street lamp?\"\n        }\n    },\n    {\n        \"prompt\": \"In the moonlit jungle, a white tiger prowls silently, its eye catching the glint of an old, abandoned watch nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - light source\",\n            \"5\": \"attribute - color\",\n            \"6\": \"action -\",\n            \"7\": \"attribute - state\",\n            \"8\": \"attribute - state\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                3\n            ],\n            \"8\": [\n                3\n            ],\n            \"9\": [\n                2,\n                3\n            ],\n            \"10\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a jungle?\",\n            \"2\": \"Is there a tiger?\",\n            \"3\": \"Is there a watch?\",\n            \"4\": \"Is the jungle lit by the moon?\",\n            \"5\": \"Is the tiger white?\",\n            \"6\": \"Is the tiger prowling silently?\",\n            \"7\": \"Is the watch old?\",\n            \"8\": \"Is the watch abandoned?\",\n            \"9\": \"Is the watch nearby the tiger?\",\n            \"10\": \"Is the tiger's eye catching the glint of the watch?\"\n        }\n    },\n    {\n        \"prompt\": \"A Corgi dog stands beside an anime samurai.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"attribute - type\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a Corgi dog?\",\n            \"2\": \"Is there an anime samurai?\",\n            \"3\": \"Is the dog a Corgi?\",\n            \"4\": \"Is the samurai an anime samurai?\",\n            \"5\": \"Is the Corgi dog standing?\",\n            \"6\": \"Is the Corgi dog beside the anime samurai?\"\n        }\n    },\n    {\n        \"prompt\": \"A grasshopper is standing next to a Poke Ball.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a grasshopper?\",\n            \"2\": \"Is there a Poke Ball?\",\n            \"3\": \"Is the grasshopper standing?\",\n            \"4\": \"Is the grasshopper next to the Poke Ball?\"\n        }\n    },\n    {\n        \"prompt\": \"A penguin is on a flamingo float in the water.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a penguin?\",\n            \"2\": \"Is there a flamingo float?\",\n            \"3\": \"Is there water?\",\n            \"4\": \"Is the penguin on the flamingo float?\",\n            \"5\": \"Is the flamingo float in the water?\",\n            \"6\": \"Is the penguin on the water via the flamingo float?\"\n        }\n    },\n    {\n        \"prompt\": \"A fox is standing under a street lamp.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a fox?\",\n            \"2\": \"Is there a street lamp?\",\n            \"3\": \"Is the fox standing?\",\n            \"4\": \"Is the fox under the street lamp?\"\n        }\n    },\n    {\n        \"prompt\": \"A cotton-top tamarin is curiously inspecting an Eevee figurine.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cotton - top tamarin?\",\n            \"2\": \"Is there an Eevee figurine?\",\n            \"3\": \"Is the cotton - top tamarin curious?\",\n            \"4\": \"Is the cotton - top tamarin inspecting the Eevee figurine?\"\n        }\n    },\n    {\n        \"prompt\": \"A llama wearing a hat\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a llama?\",\n            \"2\": \"Is there a hat?\",\n            \"3\": \"Is the llama wearing a hat?\"\n        }\n    },\n    {\n        \"prompt\": \"A cat is lying beside a teddy bear.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a teddy bear?\",\n            \"3\": \"Is the cat lying?\",\n            \"4\": \"Is the cat beside the teddy bear?\"\n        }\n    },\n    {\n        \"prompt\": \"A cat sitting in front of a yellow taxi.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - color\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a taxi?\",\n            \"3\": \"Is the taxi yellow?\",\n            \"4\": \"Is the cat sitting?\",\n            \"5\": \"Is the cat in front of the taxi?\"\n        }\n    },\n    {\n        \"prompt\": \"A cat is being dried by a hair dryer.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a hair dryer?\",\n            \"3\": \"Is the hair dryer drying the cat?\"\n        }\n    },\n    {\n        \"prompt\": \"A toucan is sitting in front of a vintage television.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a toucan?\",\n            \"2\": \"Is there a television?\",\n            \"3\": \"Is the television vintage?\",\n            \"4\": \"Is the toucan in front of the television?\",\n            \"5\": \"Is the toucan sitting?\"\n        }\n    },\n    {\n        \"prompt\": \"A panda is using a hair dryer.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a panda?\",\n            \"2\": \"Is there a hair dryer?\",\n            \"3\": \"Is the panda using a hair dryer?\"\n        }\n    },\n    {\n        \"prompt\": \"A lizard is sitting on a motorcycle.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a lizard?\",\n            \"2\": \"Is there a motorcycle?\",\n            \"3\": \"Is the lizard sitting?\",\n            \"4\": \"Is the lizard on the motorcycle?\"\n        }\n    },\n    {\n        \"prompt\": \"A robin perches on a leather handbag.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"attribute - material\",\n            \"5\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a robin?\",\n            \"2\": \"Is there a handbag?\",\n            \"3\": \"Is the handbag made of leather?\",\n            \"4\": \"Is the handbag made of leather?\",\n            \"5\": \"Is the robin perching on the handbag?\"\n        }\n    },\n    {\n        \"prompt\": \"A cat is sitting beside a basketball shoe.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a shoe?\",\n            \"3\": \"Is the shoe a basketball shoe?\",\n            \"4\": \"Is the cat sitting?\",\n            \"5\": \"Is the cat beside the shoe?\"\n        }\n    },\n    {\n        \"prompt\": \"A jellyfish floating near a tree on an otherworldly beach.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ],\n            \"8\": [\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a jellyfish?\",\n            \"2\": \"Is there a tree?\",\n            \"3\": \"Is there a beach?\",\n            \"4\": \"Is the jellyfish floating?\",\n            \"5\": \"Is the jellyfish near the tree?\",\n            \"6\": \"Is the jellyfish on the beach?\",\n            \"7\": \"Is the tree on the beach?\",\n            \"8\": \"Is the beach otherworldly?\"\n        }\n    },\n    {\n        \"prompt\": \"In a dense jungle, a cotton-top tamarin curiously eyes a resting wolf, intrigued by the unfamiliar presence amid foliage.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"action -\",\n            \"7\": \"attribute - state\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"attribute - state\",\n            \"14\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ],\n            \"9\": [\n                2,\n                4\n            ],\n            \"10\": [\n                3,\n                4\n            ],\n            \"11\": [\n                2,\n                1\n            ],\n            \"12\": [\n                3,\n                1\n            ],\n            \"13\": [\n                2\n            ],\n            \"14\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a jungle?\",\n            \"2\": \"Is there a cotton - top tamarin?\",\n            \"3\": \"Is there a wolf?\",\n            \"4\": \"Is there foliage?\",\n            \"5\": \"Is the jungle dense?\",\n            \"6\": \"Is the cotton - top tamarin curiously eyeing the wolf?\",\n            \"7\": \"Is the wolf resting?\",\n            \"8\": \"Are the cotton - top tamarin and the wolf in the same area?\",\n            \"9\": \"Is the cotton - top tamarin amid the foliage?\",\n            \"10\": \"Is the wolf amid the foliage?\",\n            \"11\": \"Is the cotton - top tamarin in the jungle?\",\n            \"12\": \"Is the wolf in the jungle?\",\n            \"13\": \"Is the cotton - top tamarin intrigued?\",\n            \"14\": \"Is the wolf an unfamiliar presence to the cotton - top tamarin?\"\n        }\n    },\n    {\n        \"prompt\": \"A deer stands in a forest clearing while a robin perches on a nearby branch.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"attribute - state\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                3\n            ],\n            \"8\": [\n                3,\n                4\n            ],\n            \"9\": [\n                4,\n                1\n            ],\n            \"10\": [\n                4,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a deer?\",\n            \"2\": \"Is there a forest clearing?\",\n            \"3\": \"Is there a robin?\",\n            \"4\": \"Is there a branch?\",\n            \"5\": \"Is the deer standing?\",\n            \"6\": \"Is the deer in the forest clearing?\",\n            \"7\": \"Is the robin perching?\",\n            \"8\": \"Is the robin on the branch?\",\n            \"9\": \"Is the branch nearby the deer?\",\n            \"10\": \"Is the branch in the forest clearing?\"\n        }\n    },\n    {\n        \"prompt\": \"A raccoon and a rooster are standing in a rural yard.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                3\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a raccoon?\",\n            \"2\": \"Is there a rooster?\",\n            \"3\": \"Is there a yard?\",\n            \"4\": \"Is the yard rural?\",\n            \"5\": \"Is the raccoon standing?\",\n            \"6\": \"Is the rooster standing?\",\n            \"7\": \"Is the raccoon in the yard?\",\n            \"8\": \"Is the rooster in the yard?\"\n        }\n    },\n    {\n        \"prompt\": \"A dolphin and a penguin swimming in the ocean together.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - togetherness\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                3\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a dolphin?\",\n            \"2\": \"Is there a penguin?\",\n            \"3\": \"Is there an ocean?\",\n            \"4\": \"Is the dolphin swimming in the ocean?\",\n            \"5\": \"Is the penguin swimming in the ocean?\",\n            \"6\": \"Are the dolphin and the penguin swimming together?\"\n        }\n    },\n    {\n        \"prompt\": \"A playful panda and a curious cat frolic in a sunlit bamboo forest, surrounded by vibrant blossoms and fluttering butterflies.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"attribute - state\",\n            \"7\": \"attribute - state\",\n            \"8\": \"attribute - state\",\n            \"9\": \"attribute - state\",\n            \"10\": \"attribute - state\",\n            \"11\": \"action -\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\",\n            \"15\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2\n            ],\n            \"8\": [\n                3\n            ],\n            \"9\": [\n                4\n            ],\n            \"10\": [\n                5\n            ],\n            \"11\": [\n                1,\n                2,\n                3\n            ],\n            \"12\": [\n                1,\n                4\n            ],\n            \"13\": [\n                1,\n                5\n            ],\n            \"14\": [\n                2,\n                4\n            ],\n            \"15\": [\n                2,\n                5\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a panda?\",\n            \"2\": \"Is there a cat?\",\n            \"3\": \"Is there a bamboo forest?\",\n            \"4\": \"Are there blossoms?\",\n            \"5\": \"Are there butterflies?\",\n            \"6\": \"Is the panda playful?\",\n            \"7\": \"Is the cat curious?\",\n            \"8\": \"Is the bamboo forest sunlit?\",\n            \"9\": \"Are the blossoms vibrant?\",\n            \"10\": \"Are the butterflies fluttering?\",\n            \"11\": \"Are the panda and the cat frolicking in the bamboo forest?\",\n            \"12\": \"Is the panda surrounded by blossoms?\",\n            \"13\": \"Is the panda surrounded by butterflies?\",\n            \"14\": \"Is the cat surrounded by blossoms?\",\n            \"15\": \"Is the cat surrounded by butterflies?\"\n        }\n    },\n    {\n        \"prompt\": \"A grasshopper is jumping on the grass while a tiger is lurking nearby in the grassland.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                2,\n                4\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a grasshopper?\",\n            \"2\": \"Is there grass?\",\n            \"3\": \"Is there a tiger?\",\n            \"4\": \"Is there a grassland?\",\n            \"5\": \"Is the grasshopper jumping on the grass?\",\n            \"6\": \"Is the tiger lurking?\",\n            \"7\": \"Is the grasshopper on the grass?\",\n            \"8\": \"Is the grass in the grassland?\",\n            \"9\": \"Is the tiger nearby the grasshopper?\",\n            \"10\": \"Is the tiger in the grassland?\"\n        }\n    },\n    {\n        \"prompt\": \"A grasshopper is hopping on the grass while a wolf is prowling nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                3\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a grasshopper?\",\n            \"2\": \"Is there grass?\",\n            \"3\": \"Is there a wolf?\",\n            \"4\": \"Is the grasshopper hopping on the grass?\",\n            \"5\": \"Is the wolf prowling?\",\n            \"6\": \"Is the grasshopper near the wolf?\",\n            \"7\": \"Is the wolf near the grasshopper?\",\n            \"8\": \"Is the grasshopper on the grass?\",\n            \"9\": \"Is the wolf near the grass?\"\n        }\n    },\n    {\n        \"prompt\": \"A polar bear and a hamster in a snowy landscape.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                3\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a polar bear?\",\n            \"2\": \"Is there a hamster?\",\n            \"3\": \"Is there a landscape?\",\n            \"4\": \"Is the bear a polar bear?\",\n            \"5\": \"Is the landscape snowy?\",\n            \"6\": \"Is the polar bear in the landscape?\",\n            \"7\": \"Is the hamster in the landscape?\"\n        }\n    },\n    {\n        \"prompt\": \"A lion is lying under a tree while a robin is perched on a nearby branch.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                3,\n                4\n            ],\n            \"9\": [\n                2,\n                4\n            ],\n            \"10\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a lion?\",\n            \"2\": \"Is there a tree?\",\n            \"3\": \"Is there a robin?\",\n            \"4\": \"Does the tree have a branch?\",\n            \"5\": \"Is the lion lying?\",\n            \"6\": \"Is the robin perching?\",\n            \"7\": \"Is the lion under the tree?\",\n            \"8\": \"Is the robin on the branch?\",\n            \"9\": \"Is the branch part of the tree?\",\n            \"10\": \"Is the robin near the lion?\"\n        }\n    },\n    {\n        \"prompt\": \"A dog is chasing a butterfly in the garden.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a dog?\",\n            \"2\": \"Is there a butterfly?\",\n            \"3\": \"Is there a garden?\",\n            \"4\": \"Is the dog chasing the butterfly?\",\n            \"5\": \"Is the dog in the garden?\",\n            \"6\": \"Is the butterfly in the garden?\"\n        }\n    },\n    {\n        \"prompt\": \"A horse is standing near the seashore and looking at a crab on the beach.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a horse?\",\n            \"2\": \"Is there a seashore?\",\n            \"3\": \"Is there a crab?\",\n            \"4\": \"Is there a beach?\",\n            \"5\": \"Is the horse standing?\",\n            \"6\": \"Is the horse near the seashore?\",\n            \"7\": \"Is the horse looking at the crab?\",\n            \"8\": \"Is the crab on the beach?\"\n        }\n    },\n    {\n        \"prompt\": \"A dog is looking up at an eagle soaring in the sky.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a dog?\",\n            \"2\": \"Is there an eagle?\",\n            \"3\": \"Is there a sky?\",\n            \"4\": \"Is the dog looking up at the eagle?\",\n            \"5\": \"Is the eagle soaring in the sky?\",\n            \"6\": \"Is the dog below the eagle?\",\n            \"7\": \"Is the eagle in the sky?\"\n        }\n    },\n    {\n        \"prompt\": \"A heron is standing by a small pond in a forest, and a deer is drinking water at the edge of the pond.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - size\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"action -\",\n            \"11\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ],\n            \"9\": [\n                2,\n                4\n            ],\n            \"10\": [\n                4\n            ],\n            \"11\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a heron?\",\n            \"2\": \"Is there a pond?\",\n            \"3\": \"Is there a forest?\",\n            \"4\": \"Is there a deer?\",\n            \"5\": \"Is the pond small?\",\n            \"6\": \"Is the heron next to the pond?\",\n            \"7\": \"Is the heron in the forest?\",\n            \"8\": \"Is the pond in the forest?\",\n            \"9\": \"Is the deer at the edge of the pond?\",\n            \"10\": \"Is the deer drinking water?\",\n            \"11\": \"Is the heron standing?\"\n        }\n    },\n    {\n        \"prompt\": \"A llama standing in a meadow with a robin flying nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a llama?\",\n            \"2\": \"Is there a meadow?\",\n            \"3\": \"Is there a robin?\",\n            \"4\": \"Is the llama standing?\",\n            \"5\": \"Is the llama in the meadow?\",\n            \"6\": \"Is the robin flying?\",\n            \"7\": \"Is the robin nearby the llama?\"\n        }\n    },\n    {\n        \"prompt\": \"A French bulldog and a penguin standing side by side on an ice-floe under a sunny sky.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - type\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"action -\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                4\n            ],\n            \"7\": [\n                1\n            ],\n            \"8\": [\n                2\n            ],\n            \"9\": [\n                1,\n                2\n            ],\n            \"10\": [\n                1,\n                3\n            ],\n            \"11\": [\n                2,\n                3\n            ],\n            \"12\": [\n                1,\n                4\n            ],\n            \"13\": [\n                2,\n                4\n            ],\n            \"14\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a French bulldog?\",\n            \"2\": \"Is there a penguin?\",\n            \"3\": \"Is there an ice - floe?\",\n            \"4\": \"Is there a sky?\",\n            \"5\": \"Is the bulldog French?\",\n            \"6\": \"Is the sky sunny?\",\n            \"7\": \"Is the French bulldog standing?\",\n            \"8\": \"Is the penguin standing?\",\n            \"9\": \"Are the French bulldog and the penguin standing side by side?\",\n            \"10\": \"Is the French bulldog on the ice - floe?\",\n            \"11\": \"Is the penguin on the ice - floe?\",\n            \"12\": \"Is the French bulldog under the sky?\",\n            \"13\": \"Is the penguin under the sky?\",\n            \"14\": \"Is the ice - floe under the sky?\"\n        }\n    },\n    {\n        \"prompt\": \"An eagle is soaring above the sea, and a shark is swimming in the water below.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"entity - part\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                3,\n                9\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                3,\n                1\n            ],\n            \"8\": [\n                3,\n                2\n            ],\n            \"9\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an eagle?\",\n            \"2\": \"Is there a sea?\",\n            \"3\": \"Is there a shark?\",\n            \"4\": \"Is the eagle soaring above the sea?\",\n            \"5\": \"Is the shark swimming in the water?\",\n            \"6\": \"Is the eagle above the shark?\",\n            \"7\": \"Is the shark below the eagle?\",\n            \"8\": \"Is the shark in the sea?\",\n            \"9\": \"Is there water in the sea?\"\n        }\n    },\n    {\n        \"prompt\": \"A stork and a parrot are standing side by side on a branch.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a stork?\",\n            \"2\": \"Is there a parrot?\",\n            \"3\": \"Is there a branch?\",\n            \"4\": \"Is the stork standing?\",\n            \"5\": \"Is the parrot standing?\",\n            \"6\": \"Are the stork and the parrot side by side?\",\n            \"7\": \"Is the stork on the branch?\",\n            \"8\": \"Is the parrot on the branch?\"\n        }\n    },\n    {\n        \"prompt\": \"A shark and an elephant co-existing in a fantasy underwater scene with the elephant floating gracefully among the shark.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"global -\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a shark?\",\n            \"2\": \"Is there an elephant?\",\n            \"3\": \"Is this a fantasy underwater scene?\",\n            \"4\": \"Are the shark and the elephant co - existing?\",\n            \"5\": \"Is the elephant among the shark?\",\n            \"6\": \"Is the elephant floating gracefully?\"\n        }\n    },\n    {\n        \"prompt\": \"A hamster is looking at a jellyfish floating in a fishbowl nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a hamster?\",\n            \"2\": \"Is there a jellyfish?\",\n            \"3\": \"Is there a fishbowl?\",\n            \"4\": \"Is the hamster looking at the jellyfish?\",\n            \"5\": \"Is the jellyfish floating in the fishbowl?\",\n            \"6\": \"Is the hamster nearby the jellyfish?\",\n            \"7\": \"Is the jellyfish in the fishbowl?\"\n        }\n    },\n    {\n        \"prompt\": \"A frog is floating on a small raft in the ocean, and a shark is swimming nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"action -\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                1,\n                3\n            ],\n            \"9\": [\n                2,\n                3\n            ],\n            \"10\": [\n                4\n            ],\n            \"11\": [\n                1,\n                4\n            ],\n            \"12\": [\n                2,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a frog?\",\n            \"2\": \"Is there a raft?\",\n            \"3\": \"Is there an ocean?\",\n            \"4\": \"Is there a shark?\",\n            \"5\": \"Is the raft small?\",\n            \"6\": \"Is the frog floating on the raft?\",\n            \"7\": \"Is the frog on the raft?\",\n            \"8\": \"Is the frog on the ocean (via the raft)?\",\n            \"9\": \"Is the raft in the ocean?\",\n            \"10\": \"Is the shark swimming?\",\n            \"11\": \"Is the shark nearby the frog?\",\n            \"12\": \"Is the shark nearby the raft?\"\n        }\n    },\n    {\n        \"prompt\": \"A piggy bank sits beside a Rolls-Royce hood ornament on a polished table.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"attribute - state\",\n            \"9\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ],\n            \"8\": [\n                3\n            ],\n            \"9\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a piggy bank?\",\n            \"2\": \"Is there a hood ornament?\",\n            \"3\": \"Is there a table?\",\n            \"4\": \"Is the hood ornament from a Rolls - Royce?\",\n            \"5\": \"Is the piggy bank beside the hood ornament?\",\n            \"6\": \"Is the piggy bank on the table?\",\n            \"7\": \"Is the hood ornament on the table?\",\n            \"8\": \"Is the table polished?\",\n            \"9\": \"Is the piggy bank sitting?\"\n        }\n    },\n    {\n        \"prompt\": \"A cap is lying under a street lamp.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cap?\",\n            \"2\": \"Is there a street lamp?\",\n            \"3\": \"Is the cap lying?\",\n            \"4\": \"Is the cap under the street lamp?\"\n        }\n    },\n    {\n        \"prompt\": \"A basketball shoe sits in front of a vintage television.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a shoe?\",\n            \"2\": \"Is there a television?\",\n            \"3\": \"Is the shoe a basketball shoe?\",\n            \"4\": \"Is the television vintage?\",\n            \"5\": \"Is the shoe in front of the television?\",\n            \"6\": \"Is the shoe sitting?\"\n        }\n    },\n    {\n        \"prompt\": \"An airplane is flying over a field with a cactus.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an airplane?\",\n            \"2\": \"Is there a field?\",\n            \"3\": \"Is there a cactus?\",\n            \"4\": \"Is the airplane flying?\",\n            \"5\": \"Is the airplane flying over the field?\",\n            \"6\": \"Is the cactus in the field?\"\n        }\n    },\n    {\n        \"prompt\": \"A mug is placed in front of a wooden house.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - material\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a mug?\",\n            \"2\": \"Is there a house?\",\n            \"3\": \"Is the house made of wood?\",\n            \"4\": \"Is the mug in front of the house?\",\n            \"5\": \"Is the mug placed?\"\n        }\n    },\n    {\n        \"prompt\": \"A rubber duck floating near a tree-like character by a small pond.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - material\",\n            \"5\": \"attribute - state\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                3\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                1,\n                3\n            ],\n            \"9\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a rubber duck?\",\n            \"2\": \"Is there a tree - like character?\",\n            \"3\": \"Is there a pond?\",\n            \"4\": \"Is the duck made of rubber?\",\n            \"5\": \"Is the pond small?\",\n            \"6\": \"Is the rubber duck floating?\",\n            \"7\": \"Is the rubber duck near the tree - like character?\",\n            \"8\": \"Is the rubber duck by the pond?\",\n            \"9\": \"Is the tree - like character by the pond?\"\n        }\n    },\n    {\n        \"prompt\": \"A vintage van parked next to a robot on an open ground.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - era\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a van?\",\n            \"2\": \"Is there a robot?\",\n            \"3\": \"Is there an open ground?\",\n            \"4\": \"Is the van vintage?\",\n            \"5\": \"Is the van parked?\",\n            \"6\": \"Is the van next to the robot?\",\n            \"7\": \"Is the van on the open ground?\",\n            \"8\": \"Is the robot on the open ground?\"\n        }\n    },\n    {\n        \"prompt\": \"A snare drum is placed beside a street lamp.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a snare drum?\",\n            \"2\": \"Is there a street lamp?\",\n            \"3\": \"Is the snare drum placed?\",\n            \"4\": \"Is the snare drum beside the street lamp?\"\n        }\n    },\n    {\n        \"prompt\": \"The anime Spider-Man leaps across skyscrapers, clutching a roll of film, destined to unveil secrets hidden within the bustling city.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - type\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"attribute - state\",\n            \"9\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                4\n            ],\n            \"9\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there Spider - Man?\",\n            \"2\": \"Are there skyscrapers?\",\n            \"3\": \"Is there a roll of film?\",\n            \"4\": \"Is there a city?\",\n            \"5\": \"Is the Spider - Man an anime version?\",\n            \"6\": \"Is the Spider - Man leaping across the skyscrapers?\",\n            \"7\": \"Is the Spider - Man clutching the roll of film?\",\n            \"8\": \"Is the city bustling?\",\n            \"9\": \"Is the roll of film going to unveil secrets in the city?\"\n        }\n    },\n    {\n        \"prompt\": \"A sneaker lies beside a beer can on the floor.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a sneaker?\",\n            \"2\": \"Is there a beer can?\",\n            \"3\": \"Is there a floor?\",\n            \"4\": \"Is the sneaker lying?\",\n            \"5\": \"Is the sneaker beside the beer can?\",\n            \"6\": \"Is the sneaker on the floor?\",\n            \"7\": \"Is the beer can on the floor?\"\n        }\n    },\n    {\n        \"prompt\": \"A tree-like character standing beside a stop sign.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - shape\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a character?\",\n            \"2\": \"Is there a stop sign?\",\n            \"3\": \"Is the character tree - like?\",\n            \"4\": \"Is the character standing?\",\n            \"5\": \"Is the character beside the stop sign?\"\n        }\n    },\n    {\n        \"prompt\": \"A robot is standing beside an airplane.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a robot?\",\n            \"2\": \"Is there an airplane?\",\n            \"3\": \"Is the robot standing?\",\n            \"4\": \"Is the robot beside the airplane?\"\n        }\n    },\n    {\n        \"prompt\": \"A hot air balloon floating in the sky above a sneaker lying on the ground.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                2,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a hot air balloon?\",\n            \"2\": \"Is there a sneaker?\",\n            \"3\": \"Is there a sky?\",\n            \"4\": \"Is there a ground?\",\n            \"5\": \"Is the hot air balloon floating in the sky?\",\n            \"6\": \"Is the hot air balloon above the sneaker?\",\n            \"7\": \"Is the sneaker on the ground?\"\n        }\n    },\n    {\n        \"prompt\": \"An Eevee figurine placed inside a leather handbag.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - material\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an Eevee figurine?\",\n            \"2\": \"Is there a handbag?\",\n            \"3\": \"Is the handbag made of leather?\",\n            \"4\": \"Is the Eevee figurine inside the handbag?\"\n        }\n    },\n    {\n        \"prompt\": \"A donut is placed beside a Rolls-Royce hood ornament.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a donut?\",\n            \"2\": \"Is there a Rolls - Royce hood ornament?\",\n            \"3\": \"Is the donut beside the Rolls - Royce hood ornament?\"\n        }\n    },\n    {\n        \"prompt\": \"A roll of film lies beside a teddy bear.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a roll of film?\",\n            \"2\": \"Is there a teddy bear?\",\n            \"3\": \"Is the roll of film beside the teddy bear?\",\n            \"4\": \"Is the roll of film lying?\"\n        }\n    },\n    {\n        \"prompt\": \"A hot air balloon hovers above a flamingo float on the water.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a hot air balloon?\",\n            \"2\": \"Is there a flamingo float?\",\n            \"3\": \"Is there water?\",\n            \"4\": \"Is the hot air balloon hovering?\",\n            \"5\": \"Is the hot air balloon above the flamingo float?\",\n            \"6\": \"Is the flamingo float on the water?\"\n        }\n    },\n    {\n        \"prompt\": \"An Eevee figurine sitting beside a donut.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an Eevee figurine?\",\n            \"2\": \"Is there a donut?\",\n            \"3\": \"Is the Eevee figurine sitting?\",\n            \"4\": \"Is the Eevee figurine beside the donut?\"\n        }\n    },\n    {\n        \"prompt\": \"An anime space ranger is riding a bicycle in space.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - style\",\n            \"5\": \"attribute - type\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a space ranger?\",\n            \"2\": \"Is there a bicycle?\",\n            \"3\": \"Is there space?\",\n            \"4\": \"Is the space ranger in anime style?\",\n            \"5\": \"Is the space ranger a space - themed ranger?\",\n            \"6\": \"Is the space ranger riding the bicycle?\",\n            \"7\": \"Is the space ranger in space?\",\n            \"8\": \"Is the bicycle in space?\"\n        }\n    },\n    {\n        \"prompt\": \"An Avatar standing beside a yellow taxi.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - color\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an Avatar?\",\n            \"2\": \"Is there a taxi?\",\n            \"3\": \"Is the taxi yellow?\",\n            \"4\": \"Is the Avatar beside the taxi?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is standing in front of his house, facing a wolf.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - relation\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a house?\",\n            \"3\": \"Is there a wolf?\",\n            \"4\": \"Is the house the man's?\",\n            \"5\": \"Is the man standing?\",\n            \"6\": \"Is the man in front of the house?\",\n            \"7\": \"Is the man facing the wolf?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman with a cap playing with a puppy.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2,\n                4\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a cap?\",\n            \"3\": \"Is there a puppy?\",\n            \"4\": \"Does the woman have a head?\",\n            \"5\": \"Is the cap on the woman's head?\",\n            \"6\": \"Is the woman playing with the puppy?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is holding a roll of film and looking at a deer in the forest.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                1,\n                4\n            ],\n            \"9\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a roll of film?\",\n            \"3\": \"Is there a deer?\",\n            \"4\": \"Is there a forest?\",\n            \"5\": \"Is the woman holding a roll of film?\",\n            \"6\": \"Is the woman looking at the deer?\",\n            \"7\": \"Is the woman in the same place as the deer?\",\n            \"8\": \"Is the woman in the forest?\",\n            \"9\": \"Is the deer in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is holding a pineapple while a robin is flying above him.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                3\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a pineapple?\",\n            \"3\": \"Is there a robin?\",\n            \"4\": \"Is the man holding a pineapple?\",\n            \"5\": \"Is the robin flying?\",\n            \"6\": \"Is the robin above the man?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is holding a Poke Ball and facing a fox.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a Poke Ball?\",\n            \"3\": \"Is there a fox?\",\n            \"4\": \"Is the boy holding a Poke Ball?\",\n            \"5\": \"Is the boy facing the fox?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is on a flamingo float while a lion watches nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                3\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a flamingo float?\",\n            \"3\": \"Is there a lion?\",\n            \"4\": \"Is the lion watching the man?\",\n            \"5\": \"Is the man on the flamingo float?\",\n            \"6\": \"Is the man near the lion?\",\n            \"7\": \"Is the flamingo float near the lion?\"\n        }\n    },\n    {\n        \"prompt\": \"An old man is lying on a flamingo float while a toucan perches nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - age\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a flamingo float?\",\n            \"3\": \"Is there a toucan?\",\n            \"4\": \"Is the man old?\",\n            \"5\": \"Is the man lying on the flamingo float?\",\n            \"6\": \"Is the toucan perching?\",\n            \"7\": \"Is the toucan nearby the man?\",\n            \"8\": \"Is the toucan nearby the flamingo float?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is looking at his watch while a raccoon is nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a watch?\",\n            \"3\": \"Is there a raccoon?\",\n            \"4\": \"Does the man have a watch?\",\n            \"5\": \"Is the man looking at his watch?\",\n            \"6\": \"Is the raccoon nearby the man?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is holding a leather handbag while standing in front of a white tiger.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"attribute - material\",\n            \"6\": \"attribute - color\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                2,\n                4\n            ],\n            \"8\": [\n                1,\n                3\n            ],\n            \"9\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a handbag?\",\n            \"3\": \"Is there a tiger?\",\n            \"4\": \"Does the man have hands?\",\n            \"5\": \"Is the handbag made of leather?\",\n            \"6\": \"Is the tiger white?\",\n            \"7\": \"Is the man holding the handbag?\",\n            \"8\": \"Is the man in front of the tiger?\",\n            \"9\": \"Is the man standing?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is using a vintage camera to take a picture of a toucan.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a camera?\",\n            \"3\": \"Is there a toucan?\",\n            \"4\": \"Is the camera vintage?\",\n            \"5\": \"Is the boy using the camera?\",\n            \"6\": \"Is the boy taking a picture of the toucan?\",\n            \"7\": \"Is the camera being used to take a picture of the toucan?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is flying in a hot air balloon with a robot.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a hot air balloon?\",\n            \"3\": \"Is there a robot?\",\n            \"4\": \"Is the man flying?\",\n            \"5\": \"Is the man in the hot air balloon?\",\n            \"6\": \"Is the man with the robot?\",\n            \"7\": \"Is the robot in the hot air balloon?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is sitting on a boat with a vintage computer.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"attribute - era\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a boat?\",\n            \"3\": \"Is there a computer?\",\n            \"4\": \"Is the woman sitting?\",\n            \"5\": \"Is the woman on the boat?\",\n            \"6\": \"Is the woman with the computer?\",\n            \"7\": \"Is the computer vintage?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is sitting in an armchair and looking at a UFO in the sky.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there an armchair?\",\n            \"3\": \"Is there a UFO?\",\n            \"4\": \"Is there a sky?\",\n            \"5\": \"Is the man sitting?\",\n            \"6\": \"Is the man in the armchair?\",\n            \"7\": \"Is the man looking at the UFO?\",\n            \"8\": \"Is the UFO in the sky?\"\n        }\n    },\n    {\n        \"prompt\": \"An old man is wearing headphones inside a hut.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - age\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Are there headphones?\",\n            \"3\": \"Is there a hut?\",\n            \"4\": \"Is the man old?\",\n            \"5\": \"Is the man wearing headphones?\",\n            \"6\": \"Is the man inside the hut?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is wearing headphones and a hat.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - part\",\n            \"3\": \"entity - part\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Are there headphones?\",\n            \"3\": \"Is there a hat?\",\n            \"4\": \"Is the woman wearing headphones?\",\n            \"5\": \"Is the woman wearing a hat?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is sitting in front of a vintage television under a tree.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a television?\",\n            \"3\": \"Is there a tree?\",\n            \"4\": \"Is the man sitting?\",\n            \"5\": \"Is the television vintage?\",\n            \"6\": \"Is the man in front of the television?\",\n            \"7\": \"Is the man under the tree?\",\n            \"8\": \"Is the television under the tree?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is inside a hut playing with a Magic Cube.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a hut?\",\n            \"3\": \"Is there a Magic Cube?\",\n            \"4\": \"Is the man inside the hut?\",\n            \"5\": \"Is the man playing with the Magic Cube?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is standing beside a yellow taxi, looking at an anime space ranger.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - color\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a taxi?\",\n            \"3\": \"Is there an anime space ranger?\",\n            \"4\": \"Is the boy standing?\",\n            \"5\": \"Is the taxi yellow?\",\n            \"6\": \"Is the boy beside the taxi?\",\n            \"7\": \"Is the boy looking at the anime space ranger?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is holding a vintage camera and a teddy bear.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a camera?\",\n            \"3\": \"Is there a teddy bear?\",\n            \"4\": \"Is the camera vintage?\",\n            \"5\": \"Is the man holding the camera?\",\n            \"6\": \"Is the man holding the teddy bear?\"\n        }\n    },\n    {\n        \"prompt\": \"The old man gazed wistfully at the ancient clock, his fingers tracing the worn ring, memories echoing through time's passage.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"attribute - state\",\n            \"9\": \"action -\",\n            \"10\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                1\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a clock?\",\n            \"3\": \"Is there a ring?\",\n            \"4\": \"Is the man old?\",\n            \"5\": \"Is the clock ancient?\",\n            \"6\": \"Is the ring worn?\",\n            \"7\": \"Is the man gazing at the clock?\",\n            \"8\": \"Is the man looking wistfully?\",\n            \"9\": \"Are the man's fingers tracing the ring?\",\n            \"10\": \"Are memories echoing through time's passage?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is standing in an open field, with an eagle soaring in the sky above him and a dog sitting at his feet.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"action -\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"action -\",\n            \"12\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                1\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                3,\n                5\n            ],\n            \"10\": [\n                1,\n                3\n            ],\n            \"11\": [\n                4\n            ],\n            \"12\": [\n                1,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a field?\",\n            \"3\": \"Is there an eagle?\",\n            \"4\": \"Is there a dog?\",\n            \"5\": \"Is there a sky?\",\n            \"6\": \"Is the field open?\",\n            \"7\": \"Is the boy standing?\",\n            \"8\": \"Is the boy in the field?\",\n            \"9\": \"Is the eagle soaring in the sky?\",\n            \"10\": \"Is the eagle above the boy?\",\n            \"11\": \"Is the dog sitting?\",\n            \"12\": \"Is the dog at the boy's feet?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is watching a robin flying around an elephant.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a robin?\",\n            \"3\": \"Is there an elephant?\",\n            \"4\": \"Is the woman watching the robin?\",\n            \"5\": \"Is the robin flying around the elephant?\"\n        }\n    },\n    {\n        \"prompt\": \"A curious boy gazes in wonder at a vibrant flamingo and a tiny lizard, marveling at nature's contrasts.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"entity - scale\",\n            \"8\": \"action -\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"entity - whole\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                3\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                1\n            ],\n            \"11\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a flamingo?\",\n            \"3\": \"Is there a lizard?\",\n            \"4\": \"Is the boy curious?\",\n            \"5\": \"Is the boy in a state of wonder?\",\n            \"6\": \"Is the flamingo vibrant?\",\n            \"7\": \"Is the lizard tiny?\",\n            \"8\": \"Is the boy gazing at the flamingo?\",\n            \"9\": \"Is the boy gazing at the lizard?\",\n            \"10\": \"Is the boy marveling at nature's contrasts?\",\n            \"11\": \"Are there nature's contrasts?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is watching a lizard and a cat in her garden.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - part\",\n            \"6\": \"action -\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                4\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                1,\n                4\n            ],\n            \"9\": [\n                2,\n                4\n            ],\n            \"10\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a lizard?\",\n            \"3\": \"Is there a cat?\",\n            \"4\": \"Is there a garden?\",\n            \"5\": \"Does the woman have a garden?\",\n            \"6\": \"Is the woman watching the lizard?\",\n            \"7\": \"Is the woman watching the cat?\",\n            \"8\": \"Is the woman in the garden?\",\n            \"9\": \"Is the lizard in the garden?\",\n            \"10\": \"Is the cat in the garden?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is playing with a parrot and a puppy in the yard.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                2,\n                4\n            ],\n            \"9\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a parrot?\",\n            \"3\": \"Is there a puppy?\",\n            \"4\": \"Is there a yard?\",\n            \"5\": \"Is the man playing with the parrot?\",\n            \"6\": \"Is the man playing with the puppy?\",\n            \"7\": \"Is the man in the yard?\",\n            \"8\": \"Is the parrot in the yard?\",\n            \"9\": \"Is the puppy in the yard?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman is watching a cat while an eagle soars in the sky above.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                3,\n                4\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a cat?\",\n            \"3\": \"Is there an eagle?\",\n            \"4\": \"Is there a sky?\",\n            \"5\": \"Is the woman watching the cat?\",\n            \"6\": \"Is the eagle soaring in the sky?\",\n            \"7\": \"Is the eagle above the woman?\",\n            \"8\": \"Is the eagle above the cat?\"\n        }\n    },\n    {\n        \"prompt\": \"A brave little girl stands wide-eyed, watching a majestic lion and tiger, feeling a mix of awe and excitement.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"entity - scale\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"attribute - state\",\n            \"9\": \"attribute - state\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                1,\n                2,\n                3\n            ],\n            \"8\": [\n                2\n            ],\n            \"9\": [\n                1\n            ],\n            \"10\": [\n                1,\n                2\n            ],\n            \"11\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a lion?\",\n            \"3\": \"Is there a tiger?\",\n            \"4\": \"Is the girl brave?\",\n            \"5\": \"Is the girl little?\",\n            \"6\": \"Is the girl wide - eyed?\",\n            \"7\": \"Is the girl watching a lion and a tiger?\",\n            \"8\": \"Is the lion majestic?\",\n            \"9\": \"Is the girl feeling a mix of awe and excitement?\",\n            \"10\": \"Is the girl watching the lion?\",\n            \"11\": \"Is the girl watching the tiger?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is watching a robin and a rooster in the yard.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                2,\n                4\n            ],\n            \"9\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a robin?\",\n            \"3\": \"Is there a rooster?\",\n            \"4\": \"Is there a yard?\",\n            \"5\": \"Is the man watching the robin?\",\n            \"6\": \"Is the man watching the rooster?\",\n            \"7\": \"Is the man in the yard?\",\n            \"8\": \"Is the robin in the yard?\",\n            \"9\": \"Is the rooster in the yard?\"\n        }\n    },\n    {\n        \"prompt\": \"In a snow-clad forest, a man cautiously approaches a wolf while a majestic polar bear watches from a distance.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"attribute - state\",\n            \"9\": \"action -\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\",\n            \"15\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                4\n            ],\n            \"7\": [\n                2,\n                3\n            ],\n            \"8\": [\n                2\n            ],\n            \"9\": [\n                4\n            ],\n            \"10\": [\n                2,\n                3\n            ],\n            \"11\": [\n                2,\n                4\n            ],\n            \"12\": [\n                3,\n                4\n            ],\n            \"13\": [\n                1,\n                2\n            ],\n            \"14\": [\n                1,\n                3\n            ],\n            \"15\": [\n                1,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a forest?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a wolf?\",\n            \"4\": \"Is there a polar bear?\",\n            \"5\": \"Is the forest snow - clad?\",\n            \"6\": \"Is the polar bear majestic?\",\n            \"7\": \"Is the man approaching the wolf?\",\n            \"8\": \"Is the man being cautious?\",\n            \"9\": \"Is the polar bear watching?\",\n            \"10\": \"Is the man approaching the wolf?\",\n            \"11\": \"Is the polar bear watching the man from a distance?\",\n            \"12\": \"Is the polar bear watching the wolf from a distance?\",\n            \"13\": \"Is the man in the forest?\",\n            \"14\": \"Is the wolf in the forest?\",\n            \"15\": \"Is the polar bear in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is standing between a cat and a tiger.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                1,\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a cat?\",\n            \"3\": \"Is there a tiger?\",\n            \"4\": \"Is the man standing?\",\n            \"5\": \"Is the man between the cat?\",\n            \"6\": \"Is the man between the tiger?\",\n            \"7\": \"Is the man between the cat and the tiger?\"\n        }\n    },\n    {\n        \"prompt\": \"A Siamese cat is lying beside a sneaker and a t-shirt.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a Siamese cat?\",\n            \"2\": \"Is there a sneaker?\",\n            \"3\": \"Is there a t-shirt?\",\n            \"4\": \"Is the cat a Siamese cat?\",\n            \"5\": \"Is the cat lying?\",\n            \"6\": \"Is the cat beside the sneaker?\",\n            \"7\": \"Is the cat beside the t-shirt?\"\n        }\n    },\n    {\n        \"prompt\": \"A wolf is standing beside a basketball shoe near a flamingo float.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a wolf?\",\n            \"2\": \"Is there a basketball shoe?\",\n            \"3\": \"Is there a flamingo float?\",\n            \"4\": \"Is the wolf standing?\",\n            \"5\": \"Is the wolf beside the basketball shoe?\",\n            \"6\": \"Is the wolf near the flamingo float?\",\n            \"7\": \"Is the basketball shoe near the flamingo float?\"\n        }\n    },\n    {\n        \"prompt\": \"A parrot is standing on an anime samurai's shoulder while the samurai is in front of a vintage computer.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"attribute - type\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a parrot?\",\n            \"2\": \"Is there a samurai?\",\n            \"3\": \"Is there a computer?\",\n            \"4\": \"Does the samurai have a shoulder?\",\n            \"5\": \"Is the samurai an anime samurai?\",\n            \"6\": \"Is the computer vintage?\",\n            \"7\": \"Is the parrot standing on the samurai's shoulder?\",\n            \"8\": \"Is the samurai in front of the computer?\"\n        }\n    },\n    {\n        \"prompt\": \"A dolphin is swimming beside a vintage van that has an anime space ranger sticker on it.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"action -\",\n            \"5\": \"attribute - type\",\n            \"6\": \"attribute - type\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a dolphin?\",\n            \"2\": \"Is there a van?\",\n            \"3\": \"Does the van have a sticker?\",\n            \"4\": \"Is the dolphin swimming?\",\n            \"5\": \"Is the van vintage?\",\n            \"6\": \"Is the sticker an anime space ranger sticker?\",\n            \"7\": \"Is the dolphin beside the van?\",\n            \"8\": \"Is the sticker on the van?\"\n        }\n    },\n    {\n        \"prompt\": \"A Siamese cat is sitting beside a vintage camera and a cactus.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a camera?\",\n            \"3\": \"Is there a cactus?\",\n            \"4\": \"Is the cat a Siamese cat?\",\n            \"5\": \"Is the camera vintage?\",\n            \"6\": \"Is the cat sitting?\",\n            \"7\": \"Is the cat beside the camera?\",\n            \"8\": \"Is the cat beside the cactus?\"\n        }\n    },\n    {\n        \"prompt\": \"A grasshopper is near an Eevee figurine in front of a wooden house.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - material\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                3\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a grasshopper?\",\n            \"2\": \"Is there an Eevee figurine?\",\n            \"3\": \"Is there a house?\",\n            \"4\": \"Is the house made of wood?\",\n            \"5\": \"Is the grasshopper near the Eevee figurine?\",\n            \"6\": \"Is the grasshopper in front of the house?\",\n            \"7\": \"Is the Eevee figurine in front of the house?\"\n        }\n    },\n    {\n        \"prompt\": \"A fox is standing beside an anime girl who is holding a rubber duck.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"attribute - type\",\n            \"8\": \"attribute - material\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                2\n            ],\n            \"8\": [\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a fox?\",\n            \"2\": \"Is there an anime girl?\",\n            \"3\": \"Is there a rubber duck?\",\n            \"4\": \"Is the fox standing?\",\n            \"5\": \"Is the fox beside the anime girl?\",\n            \"6\": \"Is the anime girl holding the rubber duck?\",\n            \"7\": \"Is the girl an anime girl?\",\n            \"8\": \"Is the duck made of rubber?\"\n        }\n    },\n    {\n        \"prompt\": \"A cat is standing beside a pixelated warrior who is holding a donut.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a warrior?\",\n            \"3\": \"Is there a donut?\",\n            \"4\": \"Is the cat standing?\",\n            \"5\": \"Is the warrior pixelated?\",\n            \"6\": \"Is the cat beside the warrior?\",\n            \"7\": \"Is the warrior holding a donut?\"\n        }\n    },\n    {\n        \"prompt\": \"A white tiger is near a robot in front of a house.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - color\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a tiger?\",\n            \"2\": \"Is there a robot?\",\n            \"3\": \"Is there a house?\",\n            \"4\": \"Is the tiger white?\",\n            \"5\": \"Is the tiger near the robot?\",\n            \"6\": \"Is the tiger in front of the house?\",\n            \"7\": \"Is the robot in front of the house?\"\n        }\n    },\n    {\n        \"prompt\": \"A shark is swimming near the shore where cherry blossoms are floating on the water, and a steam locomotive is chugging along the nearby railway.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"entity - whole\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"action -\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                0\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                3,\n                4\n            ],\n            \"10\": [\n                3,\n                2\n            ],\n            \"11\": [\n                5,\n                6\n            ],\n            \"12\": [\n                5,\n                2\n            ],\n            \"13\": [\n                6,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a shark?\",\n            \"2\": \"Is there a shore?\",\n            \"3\": \"Are there cherry blossoms?\",\n            \"4\": \"Is there water?\",\n            \"5\": \"Is there a steam locomotive?\",\n            \"6\": \"Is there a railway?\",\n            \"7\": \"Is the shark swimming in the water?\",\n            \"8\": \"Is the shark near the shore?\",\n            \"9\": \"Are the cherry blossoms floating on the water?\",\n            \"10\": \"Are the cherry blossoms near the shore?\",\n            \"11\": \"Is the steam locomotive chugging along the railway?\",\n            \"12\": \"Is the steam locomotive nearby the shore?\",\n            \"13\": \"Is the railway nearby the shore?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl and a girl are admiring a Rolls-Royce hood ornament.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - scale\",\n            \"5\": \"action -\",\n            \"6\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there another girl?\",\n            \"3\": \"Is there a Rolls - Royce hood ornament?\",\n            \"4\": \"Is the first girl little?\",\n            \"5\": \"Is the first girl admiring the Rolls - Royce hood ornament?\",\n            \"6\": \"Is the second girl admiring the Rolls - Royce hood ornament?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and another man are standing near a pineapple.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"other - count\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Are there men?\",\n            \"2\": \"Are there two men?\",\n            \"3\": \"Is there a pineapple?\",\n            \"4\": \"Are the men standing?\",\n            \"5\": \"Are the men near the pineapple?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy and a little girl are playing with a rubber duck.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - scale\",\n            \"5\": \"attribute - material\",\n            \"6\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                3\n            ],\n            \"6\": [\n                1,\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a girl?\",\n            \"3\": \"Is there a duck?\",\n            \"4\": \"Is the girl little?\",\n            \"5\": \"Is the duck made of rubber?\",\n            \"6\": \"Are the boy and the girl playing with the duck?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and a man are standing in front of a house.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a house?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the man standing?\",\n            \"6\": \"Is the woman in front of the house?\",\n            \"7\": \"Is the man in front of the house?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman, a man, and a pixelated warrior stand side by side.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                3\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a warrior?\",\n            \"4\": \"Is the warrior pixelated?\",\n            \"5\": \"Are the woman and the man standing side by side?\",\n            \"6\": \"Are the woman and the warrior standing side by side?\",\n            \"7\": \"Are the man and the warrior standing side by side?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman are standing near a stop sign.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a stop sign?\",\n            \"4\": \"Is the man standing?\",\n            \"5\": \"Is the woman standing?\",\n            \"6\": \"Is the man near the stop sign?\",\n            \"7\": \"Is the woman near the stop sign?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman, an old man, and an anime girl are standing together in a park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - age\",\n            \"6\": \"attribute - type\",\n            \"7\": \"attribute - state\",\n            \"8\": \"attribute - state\",\n            \"9\": \"attribute - state\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\",\n            \"15\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1\n            ],\n            \"8\": [\n                2\n            ],\n            \"9\": [\n                3\n            ],\n            \"10\": [\n                1,\n                2\n            ],\n            \"11\": [\n                1,\n                3\n            ],\n            \"12\": [\n                2,\n                3\n            ],\n            \"13\": [\n                1,\n                4\n            ],\n            \"14\": [\n                2,\n                4\n            ],\n            \"15\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there an anime girl?\",\n            \"4\": \"Is there a park?\",\n            \"5\": \"Is the man old?\",\n            \"6\": \"Is the girl an anime girl?\",\n            \"7\": \"Is the woman standing?\",\n            \"8\": \"Is the man standing?\",\n            \"9\": \"Is the anime girl standing?\",\n            \"10\": \"Are the woman and the man standing together?\",\n            \"11\": \"Are the woman and the anime girl standing together?\",\n            \"12\": \"Are the man and the anime girl standing together?\",\n            \"13\": \"Is the woman in the park?\",\n            \"14\": \"Is the man in the park?\",\n            \"15\": \"Is the anime girl in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and an old man are sitting together, with a beer can on the table between them.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"attribute - state\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                3,\n                4\n            ],\n            \"10\": [\n                1,\n                3\n            ],\n            \"11\": [\n                2,\n                3\n            ],\n            \"12\": [\n                1,\n                4\n            ],\n            \"13\": [\n                2,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a beer can?\",\n            \"4\": \"Is there a table?\",\n            \"5\": \"Is the man old?\",\n            \"6\": \"Is the woman sitting?\",\n            \"7\": \"Is the man sitting?\",\n            \"8\": \"Are the woman and the man sitting together?\",\n            \"9\": \"Is the beer can on the table?\",\n            \"10\": \"Is the beer can between the woman?\",\n            \"11\": \"Is the beer can between the man?\",\n            \"12\": \"Is the table between the woman?\",\n            \"13\": \"Is the table between the man?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl and a boy are on a boat.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - scale\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a boy?\",\n            \"3\": \"Is there a boat?\",\n            \"4\": \"Is the girl little?\",\n            \"5\": \"Is the girl on the boat?\",\n            \"6\": \"Is the boy on the boat?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and another man are looking at an avocado together.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - cooperation\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                3\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there another man?\",\n            \"3\": \"Is there an avocado?\",\n            \"4\": \"Is the first man looking at the avocado?\",\n            \"5\": \"Is the second man looking at the avocado?\",\n            \"6\": \"Are the two men looking at the avocado together?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl and a man are watching a cotton-top tamarin in a zoo.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - scale\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2,\n                3\n            ],\n            \"7\": [\n                1,\n                2,\n                4\n            ],\n            \"8\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a cotton - top tamarin?\",\n            \"4\": \"Is there a zoo?\",\n            \"5\": \"Is the girl little?\",\n            \"6\": \"Are the girl and the man watching the cotton - top tamarin?\",\n            \"7\": \"Are the girl and the man in the zoo?\",\n            \"8\": \"Is the cotton - top tamarin in the zoo?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy and a man are watching a hamster play in a cage.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                3,\n                4\n            ],\n            \"8\": [\n                3,\n                4\n            ],\n            \"9\": [\n                1,\n                4\n            ],\n            \"10\": [\n                2,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a hamster?\",\n            \"4\": \"Is there a cage?\",\n            \"5\": \"Is the boy watching the hamster?\",\n            \"6\": \"Is the man watching the hamster?\",\n            \"7\": \"Is the hamster playing in the cage?\",\n            \"8\": \"Is the hamster in the cage?\",\n            \"9\": \"Is the boy watching the cage from outside?\",\n            \"10\": \"Is the man watching the cage from outside?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a man are looking at a parrot.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"other - count\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Are there men?\",\n            \"2\": \"Are there two men?\",\n            \"3\": \"Is there a parrot?\",\n            \"4\": \"Are the men looking at the parrot?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman are playing with a puppy in the park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                2,\n                4\n            ],\n            \"9\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a puppy?\",\n            \"4\": \"Is there a park?\",\n            \"5\": \"Is the man playing with the puppy?\",\n            \"6\": \"Is the woman playing with the puppy?\",\n            \"7\": \"Is the man in the park?\",\n            \"8\": \"Is the woman in the park?\",\n            \"9\": \"Is the puppy in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A man is watching a girl play with a hamster.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a girl?\",\n            \"3\": \"Is there a hamster?\",\n            \"4\": \"Is the man watching?\",\n            \"5\": \"Is the girl playing with the hamster?\",\n            \"6\": \"Is the man watching the girl?\",\n            \"7\": \"Is the man watching the hamster?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a woman are looking at a panda in the zoo.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"attribute - gender\",\n            \"11\": \"attribute - gender\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                2,\n                4\n            ],\n            \"9\": [\n                3,\n                4\n            ],\n            \"10\": [\n                1\n            ],\n            \"11\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a panda?\",\n            \"4\": \"Is there a zoo?\",\n            \"5\": \"Is the man looking at the panda?\",\n            \"6\": \"Is the woman looking at the panda?\",\n            \"7\": \"Is the man in the zoo?\",\n            \"8\": \"Is the woman in the zoo?\",\n            \"9\": \"Is the panda in the zoo?\",\n            \"10\": \"Is the man male?\",\n            \"11\": \"Is the woman female?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and a girl are standing in the snow, facing a polar bear.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                2,\n                4\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a girl?\",\n            \"3\": \"Is there a polar bear?\",\n            \"4\": \"Is there snow?\",\n            \"5\": \"Is the man standing?\",\n            \"6\": \"Is the girl standing?\",\n            \"7\": \"Is the man in the snow?\",\n            \"8\": \"Is the girl in the snow?\",\n            \"9\": \"Is the man facing the polar bear?\",\n            \"10\": \"Is the girl facing the polar bear?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and a man are standing beside a llama.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a llama?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the man standing?\",\n            \"6\": \"Is the woman beside the llama?\",\n            \"7\": \"Is the man beside the llama?\"\n        }\n    },\n    {\n        \"prompt\": \"A woman and a man are observing a lizard in the garden.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                1,\n                4\n            ],\n            \"8\": [\n                2,\n                4\n            ],\n            \"9\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a lizard?\",\n            \"4\": \"Is there a garden?\",\n            \"5\": \"Is the woman observing the lizard?\",\n            \"6\": \"Is the man observing the lizard?\",\n            \"7\": \"Is the woman in the garden?\",\n            \"8\": \"Is the man in the garden?\",\n            \"9\": \"Is the lizard in the garden?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and another man are looking at an eagle soaring in the sky.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Are there men?\",\n            \"2\": \"Is there an eagle?\",\n            \"3\": \"Is there another man?\",\n            \"4\": \"Is the eagle soaring in the sky?\",\n            \"5\": \"Is one man looking at the eagle?\",\n            \"6\": \"Is the other man looking at the eagle?\"\n        }\n    },\n    {\n        \"prompt\": \"A man, a man, and a woman are standing in a park chatting.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"other - count\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"action -\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                1\n            ],\n            \"8\": [\n                2\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Are there men?\",\n            \"2\": \"Is there a woman?\",\n            \"3\": \"Is there a park?\",\n            \"4\": \"Are there two men?\",\n            \"5\": \"Are the men standing?\",\n            \"6\": \"Is the woman standing?\",\n            \"7\": \"Are the men chatting?\",\n            \"8\": \"Is the woman chatting?\",\n            \"9\": \"Are the men in the park?\",\n            \"10\": \"Is the woman in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A man in blue, a man in black, and a man with sunglasses are standing together, chatting and laughing.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"other - count\",\n            \"3\": \"entity - part\",\n            \"4\": \"entity - part\",\n            \"5\": \"entity - part\",\n            \"6\": \"attribute - color\",\n            \"7\": \"attribute - color\",\n            \"8\": \"action -\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                4\n            ],\n            \"8\": [\n                1\n            ],\n            \"9\": [\n                1\n            ],\n            \"10\": [\n                1\n            ],\n            \"11\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Are there men?\",\n            \"2\": \"Are there three men?\",\n            \"3\": \"Does one man have clothes?\",\n            \"4\": \"Does another man have clothes?\",\n            \"5\": \"Does one man have sunglasses?\",\n            \"6\": \"Are one man's clothes blue?\",\n            \"7\": \"Are another man's clothes black?\",\n            \"8\": \"Are the men standing?\",\n            \"9\": \"Are the men chatting?\",\n            \"10\": \"Are the men laughing?\",\n            \"11\": \"Are the men standing together?\"\n        }\n    },\n    {\n        \"prompt\": \"An old man, a man, and a woman are standing in a park chatting.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"attribute - state\",\n            \"8\": \"attribute - state\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"action -\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2\n            ],\n            \"8\": [\n                3\n            ],\n            \"9\": [\n                1\n            ],\n            \"10\": [\n                2\n            ],\n            \"11\": [\n                3\n            ],\n            \"12\": [\n                1,\n                4\n            ],\n            \"13\": [\n                2,\n                4\n            ],\n            \"14\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an old man?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a woman?\",\n            \"4\": \"Is there a park?\",\n            \"5\": \"Is the old man old?\",\n            \"6\": \"Is the old man standing?\",\n            \"7\": \"Is the man standing?\",\n            \"8\": \"Is the woman standing?\",\n            \"9\": \"Is the old man chatting?\",\n            \"10\": \"Is the man chatting?\",\n            \"11\": \"Is the woman chatting?\",\n            \"12\": \"Is the old man in the park?\",\n            \"13\": \"Is the man in the park?\",\n            \"14\": \"Is the woman in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A girl, a man, and a woman are sitting together in a park, chatting and enjoying the sunny day.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"action -\",\n            \"8\": \"action -\",\n            \"9\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2,\n                3,\n                4\n            ],\n            \"7\": [\n                1,\n                2,\n                3\n            ],\n            \"8\": [\n                1,\n                2,\n                3\n            ],\n            \"9\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a woman?\",\n            \"4\": \"Is there a park?\",\n            \"5\": \"Are the girl, man, and woman sitting together?\",\n            \"6\": \"Are the girl, man, and woman in the park?\",\n            \"7\": \"Are the girl, man, and woman chatting?\",\n            \"8\": \"Are the girl, man, and woman enjoying the sunny day?\",\n            \"9\": \"Is it a sunny day?\"\n        }\n    },\n    {\n        \"prompt\": \"Three men, a young man, an old man, and another man, are standing together chatting on the street corner.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"other - count\",\n            \"3\": \"entity - part\",\n            \"4\": \"entity - part\",\n            \"5\": \"entity - part\",\n            \"6\": \"entity - state\",\n            \"7\": \"entity - state\",\n            \"8\": \"entity - whole\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                4\n            ],\n            \"8\": [\n                0\n            ],\n            \"9\": [\n                1\n            ],\n            \"10\": [\n                1\n            ],\n            \"11\": [\n                1,\n                8\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Are there men?\",\n            \"2\": \"Are there three men?\",\n            \"3\": \"Is there a young man?\",\n            \"4\": \"Is there an old man?\",\n            \"5\": \"Is there another man?\",\n            \"6\": \"Is the young man young?\",\n            \"7\": \"Is the old man old?\",\n            \"8\": \"Is there a street corner?\",\n            \"9\": \"Are the men standing together?\",\n            \"10\": \"Are the men chatting?\",\n            \"11\": \"Are the men on the street corner?\"\n        }\n    },\n    {\n        \"prompt\": \"A little girl is standing between a man and another man, having a conversation with them.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - scale\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ],\n            \"8\": [\n                2,\n                3\n            ],\n            \"9\": [\n                1,\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there another man?\",\n            \"4\": \"Is the girl little?\",\n            \"5\": \"Is the girl standing?\",\n            \"6\": \"Is the girl between the first man?\",\n            \"7\": \"Is the girl between the second man?\",\n            \"8\": \"Is the girl standing between the two men?\",\n            \"9\": \"Is the girl having a conversation with the two men?\"\n        }\n    },\n    {\n        \"prompt\": \"A boy is standing between a man and a woman, having a conversation.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                1,\n                3\n            ],\n            \"9\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a man?\",\n            \"3\": \"Is there a woman?\",\n            \"4\": \"Is the boy having a conversation?\",\n            \"5\": \"Is the man having a conversation?\",\n            \"6\": \"Is the woman having a conversation?\",\n            \"7\": \"Is the boy between the man?\",\n            \"8\": \"Is the boy between the woman?\",\n            \"9\": \"Is the boy standing?\"\n        }\n    },\n    {\n        \"prompt\": \"A man and another man are walking with a little girl in the park.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"action -\",\n            \"8\": \"entity - scale\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                4\n            ],\n            \"6\": [\n                2,\n                4\n            ],\n            \"7\": [\n                3,\n                4\n            ],\n            \"8\": [\n                3\n            ],\n            \"9\": [\n                1,\n                2\n            ],\n            \"10\": [\n                1,\n                3\n            ],\n            \"11\": [\n                2,\n                3\n            ],\n            \"12\": [\n                1,\n                4\n            ],\n            \"13\": [\n                2,\n                4\n            ],\n            \"14\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there another man?\",\n            \"3\": \"Is there a girl?\",\n            \"4\": \"Is there a park?\",\n            \"5\": \"Is the first man walking in the park?\",\n            \"6\": \"Is the second man walking in the park?\",\n            \"7\": \"Is the girl walking in the park?\",\n            \"8\": \"Is the girl little?\",\n            \"9\": \"Are the two men walking together?\",\n            \"10\": \"Is the first man walking with the girl?\",\n            \"11\": \"Is the second man walking with the girl?\",\n            \"12\": \"Is the first man in the park?\",\n            \"13\": \"Is the second man in the park?\",\n            \"14\": \"Is the girl in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"A girl, an old man, and a woman are sitting on a park bench chatting.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"action -\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2,\n                3\n            ],\n            \"7\": [\n                1,\n                2,\n                3\n            ],\n            \"8\": [\n                1,\n                2,\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there an old man?\",\n            \"3\": \"Is there a woman?\",\n            \"4\": \"Is there a park bench?\",\n            \"5\": \"Is the man old?\",\n            \"6\": \"Are the girl, old man, and woman sitting?\",\n            \"7\": \"Are the girl, old man, and woman chatting?\",\n            \"8\": \"Are the girl, old man, and woman sitting on the park bench?\"\n        }\n    },\n    {\n        \"prompt\": \"A man, another man, and a boy are standing together in the park chatting.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2,\n                3\n            ],\n            \"6\": [\n                1,\n                2,\n                3\n            ],\n            \"7\": [\n                1,\n                2,\n                3\n            ],\n            \"8\": [\n                1,\n                2,\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there another man?\",\n            \"3\": \"Is there a boy?\",\n            \"4\": \"Is there a park?\",\n            \"5\": \"Are the man, another man, and the boy chatting?\",\n            \"6\": \"Are the man, another man, and the boy standing?\",\n            \"7\": \"Are the man, another man, and the boy together?\",\n            \"8\": \"Are the man, another man, and the boy in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"The vintage camera, vintage computer, and rubber duck together create a nostalgic and whimsical atmosphere in the sunlight.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - era\",\n            \"5\": \"attribute - era\",\n            \"6\": \"attribute - material\",\n            \"7\": \"action -\",\n            \"8\": \"attribute - state\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                1,\n                2,\n                3\n            ],\n            \"8\": [\n                7\n            ],\n            \"9\": [\n                1,\n                2,\n                3\n            ],\n            \"10\": [\n                1,\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a camera?\",\n            \"2\": \"Is there a computer?\",\n            \"3\": \"Is there a rubber duck?\",\n            \"4\": \"Is the camera vintage?\",\n            \"5\": \"Is the computer vintage?\",\n            \"6\": \"Is the duck made of rubber?\",\n            \"7\": \"Do the camera, computer, and rubber duck create something?\",\n            \"8\": \"Is the atmosphere nostalgic and whimsical?\",\n            \"9\": \"Are the camera, computer, and rubber duck together?\",\n            \"10\": \"Are the camera, computer, and rubber duck in the sunlight?\"\n        }\n    },\n    {\n        \"prompt\": \"In a sunlit meadow, an Avatar gracefully donned a cap, its hand delicately holding a glowing ring.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - part\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"action -\",\n            \"9\": \"attribute - state\",\n            \"10\": \"attribute - state\",\n            \"11\": \"attribute - state\",\n            \"12\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2,\n                3\n            ],\n            \"8\": [\n                4,\n                5\n            ],\n            \"9\": [\n                2\n            ],\n            \"10\": [\n                5\n            ],\n            \"11\": [\n                4\n            ],\n            \"12\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a meadow?\",\n            \"2\": \"Is there an Avatar?\",\n            \"3\": \"Is there a cap?\",\n            \"4\": \"Is there a ring?\",\n            \"5\": \"Does the Avatar have a hand?\",\n            \"6\": \"Is the meadow sunlit?\",\n            \"7\": \"Is the Avatar donning a cap?\",\n            \"8\": \"Is the Avatar's hand holding a ring?\",\n            \"9\": \"Is the Avatar graceful?\",\n            \"10\": \"Is the Avatar's hand delicate?\",\n            \"11\": \"Is the ring glowing?\",\n            \"12\": \"Is the Avatar in the meadow?\"\n        }\n    },\n    {\n        \"prompt\": \"A vintage television is on, and there's a cocktail and a donut on the table beside it.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2,\n                4\n            ],\n            \"8\": [\n                3,\n                4\n            ],\n            \"9\": [\n                1,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a television?\",\n            \"2\": \"Is there a cocktail?\",\n            \"3\": \"Is there a donut?\",\n            \"4\": \"Is there a table?\",\n            \"5\": \"Is the television vintage?\",\n            \"6\": \"Is the television on?\",\n            \"7\": \"Is the cocktail on the table?\",\n            \"8\": \"Is the donut on the table?\",\n            \"9\": \"Is the table beside the television?\"\n        }\n    },\n    {\n        \"prompt\": \"A street lamp illuminates an Eevee figurine placed next to a piggy bank on the sidewalk.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"attribute - type\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                2,\n                4\n            ],\n            \"8\": [\n                3,\n                4\n            ],\n            \"9\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a street lamp?\",\n            \"2\": \"Is there an Eevee figurine?\",\n            \"3\": \"Is there a piggy bank?\",\n            \"4\": \"Is there a sidewalk?\",\n            \"5\": \"Is the street lamp illuminating the Eevee figurine?\",\n            \"6\": \"Is the Eevee figurine next to the piggy bank?\",\n            \"7\": \"Is the Eevee figurine on the sidewalk?\",\n            \"8\": \"Is the piggy bank on the sidewalk?\",\n            \"9\": \"Is the figurine an Eevee figurine?\"\n        }\n    },\n    {\n        \"prompt\": \"An anime girl is standing in front of a hut, holding an Eevee figurine.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"action -\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an anime girl?\",\n            \"2\": \"Is there a hut?\",\n            \"3\": \"Is there an Eevee figurine?\",\n            \"4\": \"Is the girl an anime girl?\",\n            \"5\": \"Is the anime girl standing?\",\n            \"6\": \"Is the anime girl in front of the hut?\",\n            \"7\": \"Is the anime girl holding the Eevee figurine?\"\n        }\n    },\n    {\n        \"prompt\": \"A robot is carrying a backpack and standing next to a pineapple.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a robot?\",\n            \"2\": \"Is there a backpack?\",\n            \"3\": \"Is there a pineapple?\",\n            \"4\": \"Is the robot carrying a backpack?\",\n            \"5\": \"Is the robot next to the pineapple?\",\n            \"6\": \"Is the robot standing?\"\n        }\n    },\n    {\n        \"prompt\": \"An anime girl is sitting next to a piggy bank, holding a mug in her hand.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"attribute - type\",\n            \"6\": \"attribute - state\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                1,\n                2\n            ],\n            \"8\": [\n                1,\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a piggy bank?\",\n            \"3\": \"Is there a mug?\",\n            \"4\": \"Does the girl have a hand?\",\n            \"5\": \"Is the girl an anime girl?\",\n            \"6\": \"Is the girl sitting?\",\n            \"7\": \"Is the girl next to the piggy bank?\",\n            \"8\": \"Is the girl holding the mug in her hand?\"\n        }\n    },\n    {\n        \"prompt\": \"A UFO hovers in the sky while a pineapple lies on the ground nearby, and a vintage camera is placed beside the pineapple, ready to capture this strange scene.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"action -\",\n            \"7\": \"relation - spatial\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"attribute - state\",\n            \"11\": \"attribute - type\",\n            \"12\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                1,\n                4\n            ],\n            \"7\": [\n                2,\n                5\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                2,\n                3\n            ],\n            \"10\": [\n                3\n            ],\n            \"11\": [\n                3\n            ],\n            \"12\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a UFO?\",\n            \"2\": \"Is there a pineapple?\",\n            \"3\": \"Is there a camera?\",\n            \"4\": \"Is there a sky?\",\n            \"5\": \"Is there a ground?\",\n            \"6\": \"Is the UFO hovering in the sky?\",\n            \"7\": \"Is the pineapple on the ground?\",\n            \"8\": \"Is the UFO nearby the pineapple?\",\n            \"9\": \"Is the camera beside the pineapple?\",\n            \"10\": \"Is the camera ready to capture the scene?\",\n            \"11\": \"Is the camera vintage?\",\n            \"12\": \"Is the scene strange?\"\n        }\n    },\n    {\n        \"prompt\": \"An anime Spider-Man stands near a stop sign, wearing a hat.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"attribute - style\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a Spider - Man?\",\n            \"2\": \"Is there a stop sign?\",\n            \"3\": \"Does Spider - Man have a hat?\",\n            \"4\": \"Is the Spider - Man in anime style?\",\n            \"5\": \"Is the Spider - Man near the stop sign?\",\n            \"6\": \"Is the Spider - Man wearing a hat?\"\n        }\n    },\n    {\n        \"prompt\": \"An anime space ranger is holding a Poke Ball while using a hair dryer in a cosmic setting.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - type\",\n            \"5\": \"action -\",\n            \"6\": \"action -\",\n            \"7\": \"global -\",\n            \"8\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ],\n            \"7\": [\n                0\n            ],\n            \"8\": [\n                1,\n                7\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a space ranger?\",\n            \"2\": \"Is there a Poke Ball?\",\n            \"3\": \"Is there a hair dryer?\",\n            \"4\": \"Is the space ranger an anime character?\",\n            \"5\": \"Is the space ranger holding a Poke Ball?\",\n            \"6\": \"Is the space ranger using a hair dryer?\",\n            \"7\": \"Is this a cosmic setting?\",\n            \"8\": \"Is the space ranger in a cosmic setting?\"\n        }\n    },\n    {\n        \"prompt\": \"A parrot is perched on the saddle of a horse, while a kitten is playing at the horse's hooves.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - part\",\n            \"5\": \"entity - part\",\n            \"6\": \"action -\",\n            \"7\": \"action -\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                4\n            ],\n            \"7\": [\n                3,\n                5\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                3,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a parrot?\",\n            \"2\": \"Is there a horse?\",\n            \"3\": \"Is there a kitten?\",\n            \"4\": \"Does the horse have a saddle?\",\n            \"5\": \"Does the horse have hooves?\",\n            \"6\": \"Is the parrot perched on the horse's saddle?\",\n            \"7\": \"Is the kitten playing at the horse's hooves?\",\n            \"8\": \"Is the parrot on the horse's saddle?\",\n            \"9\": \"Is the kitten at the horse's hooves?\"\n        }\n    },\n    {\n        \"prompt\": \"A robin is perched on a branch above while a white tiger slowly approaches a curious kitten in a forest clearing.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"action -\",\n            \"7\": \"attribute - color\",\n            \"8\": \"attribute - state\",\n            \"9\": \"attribute - state\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                3\n            ],\n            \"8\": [\n                3\n            ],\n            \"9\": [\n                4\n            ],\n            \"10\": [\n                1,\n                2\n            ],\n            \"11\": [\n                3,\n                4\n            ],\n            \"12\": [\n                3,\n                5\n            ],\n            \"13\": [\n                4,\n                5\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a robin?\",\n            \"2\": \"Is there a branch?\",\n            \"3\": \"Is there a tiger?\",\n            \"4\": \"Is there a kitten?\",\n            \"5\": \"Is there a forest clearing?\",\n            \"6\": \"Is the robin perched on the branch?\",\n            \"7\": \"Is the tiger white?\",\n            \"8\": \"Is the tiger slowly approaching?\",\n            \"9\": \"Is the kitten curious?\",\n            \"10\": \"Is the robin above the branch?\",\n            \"11\": \"Is the tiger approaching the kitten?\",\n            \"12\": \"Is the tiger in the forest clearing?\",\n            \"13\": \"Is the kitten in the forest clearing?\"\n        }\n    },\n    {\n        \"prompt\": \"An eagle soars in the sky above a grassy field where a horse is grazing, and a French bulldog is running around nearby.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"attribute - texture\",\n            \"7\": \"attribute - type\",\n            \"8\": \"action -\",\n            \"9\": \"relation - spatial\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"action -\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                3\n            ],\n            \"7\": [\n                5\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                3,\n                4\n            ],\n            \"11\": [\n                3,\n                4\n            ],\n            \"12\": [\n                3,\n                5\n            ],\n            \"13\": [\n                5\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an eagle?\",\n            \"2\": \"Is there a sky?\",\n            \"3\": \"Is there a field?\",\n            \"4\": \"Is there a horse?\",\n            \"5\": \"Is there a French bulldog?\",\n            \"6\": \"Is the field grassy?\",\n            \"7\": \"Is the bulldog French?\",\n            \"8\": \"Is the eagle soaring in the sky?\",\n            \"9\": \"Is the eagle above the field?\",\n            \"10\": \"Is the horse on the field?\",\n            \"11\": \"Is the horse grazing on the field?\",\n            \"12\": \"Is the French bulldog nearby the field?\",\n            \"13\": \"Is the French bulldog running around?\"\n        }\n    },\n    {\n        \"prompt\": \"In a sunlit oasis, a flamingo dances gracefully beside a lounging tiger and a curious, fluffy llama. Nature's harmony.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"attribute - state\",\n            \"6\": \"action -\",\n            \"7\": \"attribute - state\",\n            \"8\": \"attribute - state\",\n            \"9\": \"attribute - state\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"global -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                2\n            ],\n            \"7\": [\n                3\n            ],\n            \"8\": [\n                4\n            ],\n            \"9\": [\n                4\n            ],\n            \"10\": [\n                2,\n                3\n            ],\n            \"11\": [\n                2,\n                4\n            ],\n            \"12\": [\n                3,\n                4\n            ],\n            \"13\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an oasis?\",\n            \"2\": \"Is there a flamingo?\",\n            \"3\": \"Is there a tiger?\",\n            \"4\": \"Is there a llama?\",\n            \"5\": \"Is the oasis sunlit?\",\n            \"6\": \"Is the flamingo dancing gracefully?\",\n            \"7\": \"Is the tiger lounging?\",\n            \"8\": \"Is the llama curious?\",\n            \"9\": \"Is the llama fluffy?\",\n            \"10\": \"Is the flamingo beside the tiger?\",\n            \"11\": \"Is the flamingo beside the llama?\",\n            \"12\": \"Is the tiger beside the llama?\",\n            \"13\": \"Does this scene show nature's harmony?\"\n        }\n    },\n    {\n        \"prompt\": \"A tiger is lurking in the tall grass, while a hamster scurries near a small burrow, and a llama stands calmly in the open space not far away.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"entity - whole\",\n            \"7\": \"attribute - state\",\n            \"8\": \"attribute - state\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"action -\",\n            \"12\": \"attribute - state\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\",\n            \"15\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                0\n            ],\n            \"7\": [\n                2\n            ],\n            \"8\": [\n                4\n            ],\n            \"9\": [\n                1,\n                2\n            ],\n            \"10\": [\n                3,\n                4\n            ],\n            \"11\": [\n                5,\n                6\n            ],\n            \"12\": [\n                5\n            ],\n            \"13\": [\n                1,\n                3\n            ],\n            \"14\": [\n                1,\n                5\n            ],\n            \"15\": [\n                3,\n                5\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a tiger?\",\n            \"2\": \"Is there grass?\",\n            \"3\": \"Is there a hamster?\",\n            \"4\": \"Is there a burrow?\",\n            \"5\": \"Is there a llama?\",\n            \"6\": \"Is there an open space?\",\n            \"7\": \"Is the grass tall?\",\n            \"8\": \"Is the burrow small?\",\n            \"9\": \"Is the tiger lurking in the grass?\",\n            \"10\": \"Is the hamster scurrying near the burrow?\",\n            \"11\": \"Is the llama standing in the open space?\",\n            \"12\": \"Is the llama calm?\",\n            \"13\": \"Is the tiger not far from the hamster?\",\n            \"14\": \"Is the tiger not far from the llama?\",\n            \"15\": \"Is the hamster not far from the llama?\"\n        }\n    },\n    {\n        \"prompt\": \"A parrot is perched on a branch, squawking, while a dog is running around barking nearby, and a crab is slowly crawling on the sandy shore.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"action -\",\n            \"7\": \"action -\",\n            \"8\": \"action -\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"attribute - texture\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\",\n            \"15\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                1,\n                2\n            ],\n            \"7\": [\n                1\n            ],\n            \"8\": [\n                3\n            ],\n            \"9\": [\n                3\n            ],\n            \"10\": [\n                4,\n                5\n            ],\n            \"11\": [\n                5\n            ],\n            \"12\": [\n                1,\n                3\n            ],\n            \"13\": [\n                3,\n                5\n            ],\n            \"14\": [\n                3,\n                4\n            ],\n            \"15\": [\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a parrot?\",\n            \"2\": \"Is there a branch?\",\n            \"3\": \"Is there a dog?\",\n            \"4\": \"Is there a crab?\",\n            \"5\": \"Is there a shore?\",\n            \"6\": \"Is the parrot perched on the branch?\",\n            \"7\": \"Is the parrot squawking?\",\n            \"8\": \"Is the dog running around?\",\n            \"9\": \"Is the dog barking?\",\n            \"10\": \"Is the crab crawling on the shore?\",\n            \"11\": \"Is the shore sandy?\",\n            \"12\": \"Is the dog nearby the parrot?\",\n            \"13\": \"Is the dog nearby the shore?\",\n            \"14\": \"Is the crab nearby the dog?\",\n            \"15\": \"Is the crab crawling slowly?\"\n        }\n    },\n    {\n        \"prompt\": \"A hamster, a llama and a tiger are in a large, wild-like enclosure. The hamster scurries around near some small burrows, the llama stands calmly chewing on some grass, and the tiger prowls around the perimeter, eyeing the other two animals. \",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"entity - whole\",\n            \"7\": \"attribute - size\",\n            \"8\": \"attribute - state\",\n            \"9\": \"attribute - size\",\n            \"10\": \"relation - spatial\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\",\n            \"15\": \"action -\",\n            \"16\": \"action -\",\n            \"17\": \"action -\",\n            \"18\": \"action -\",\n            \"19\": \"action -\",\n            \"20\": \"action -\",\n            \"21\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                0\n            ],\n            \"7\": [\n                4\n            ],\n            \"8\": [\n                4\n            ],\n            \"9\": [\n                5\n            ],\n            \"10\": [\n                1,\n                4\n            ],\n            \"11\": [\n                2,\n                4\n            ],\n            \"12\": [\n                3,\n                4\n            ],\n            \"13\": [\n                1,\n                5\n            ],\n            \"14\": [\n                2,\n                6\n            ],\n            \"15\": [\n                1\n            ],\n            \"16\": [\n                2\n            ],\n            \"17\": [\n                2,\n                6\n            ],\n            \"18\": [\n                3\n            ],\n            \"19\": [\n                3,\n                1\n            ],\n            \"20\": [\n                3,\n                2\n            ],\n            \"21\": [\n                3,\n                4\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a hamster?\",\n            \"2\": \"Is there a llama?\",\n            \"3\": \"Is there a tiger?\",\n            \"4\": \"Is there an enclosure?\",\n            \"5\": \"Are there burrows?\",\n            \"6\": \"Is there grass?\",\n            \"7\": \"Is the enclosure large?\",\n            \"8\": \"Is the enclosure wild - like?\",\n            \"9\": \"Are the burrows small?\",\n            \"10\": \"Is the hamster in the enclosure?\",\n            \"11\": \"Is the llama in the enclosure?\",\n            \"12\": \"Is the tiger in the enclosure?\",\n            \"13\": \"Is the hamster near the burrows?\",\n            \"14\": \"Is the llama on the grass?\",\n            \"15\": \"Is the hamster scurrying around?\",\n            \"16\": \"Is the llama standing calmly?\",\n            \"17\": \"Is the llama chewing on the grass?\",\n            \"18\": \"Is the tiger prowling around?\",\n            \"19\": \"Is the tiger eyeing the hamster?\",\n            \"20\": \"Is the tiger eyeing the llama?\",\n            \"21\": \"Is the tiger at the perimeter of the enclosure?\"\n        }\n    },\n    {\n        \"prompt\": \"A corgi is standing on the shore, looking out at the ocean where jellyfish are floating. Suddenly, a wolf appears from the nearby forest and approaches the corgi.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"entity - whole\",\n            \"7\": \"attribute - state\",\n            \"8\": \"relation - spatial\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"action -\",\n            \"13\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                0\n            ],\n            \"7\": [\n                1\n            ],\n            \"8\": [\n                1,\n                2\n            ],\n            \"9\": [\n                1,\n                3\n            ],\n            \"10\": [\n                3,\n                4\n            ],\n            \"11\": [\n                2,\n                6\n            ],\n            \"12\": [\n                5,\n                6\n            ],\n            \"13\": [\n                1,\n                5\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a corgi?\",\n            \"2\": \"Is there a shore?\",\n            \"3\": \"Is there an ocean?\",\n            \"4\": \"Are there jellyfish?\",\n            \"5\": \"Is there a wolf?\",\n            \"6\": \"Is there a forest?\",\n            \"7\": \"Is the corgi standing?\",\n            \"8\": \"Is the corgi on the shore?\",\n            \"9\": \"Is the corgi looking out at the ocean?\",\n            \"10\": \"Are the jellyfish floating in the ocean?\",\n            \"11\": \"Is the forest nearby the shore?\",\n            \"12\": \"Is the wolf appearing from the forest?\",\n            \"13\": \"Is the wolf approaching the corgi?\"\n        }\n    },\n    {\n        \"prompt\": \"Under a vibrant sunset, a flamingo wades in shimmering waters as a parrot sings atop a nearby graceful deer. Tranquility.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"attribute - state\",\n            \"7\": \"attribute - state\",\n            \"8\": \"attribute - state\",\n            \"9\": \"action -\",\n            \"10\": \"action -\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"relation - spatial\",\n            \"15\": \"global -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                3\n            ],\n            \"8\": [\n                5\n            ],\n            \"9\": [\n                2,\n                3\n            ],\n            \"10\": [\n                4\n            ],\n            \"11\": [\n                4,\n                5\n            ],\n            \"12\": [\n                4,\n                5\n            ],\n            \"13\": [\n                2,\n                1\n            ],\n            \"14\": [\n                4,\n                5\n            ],\n            \"15\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a sunset?\",\n            \"2\": \"Is there a flamingo?\",\n            \"3\": \"Are there waters?\",\n            \"4\": \"Is there a parrot?\",\n            \"5\": \"Is there a deer?\",\n            \"6\": \"Is the sunset vibrant?\",\n            \"7\": \"Are the waters shimmering?\",\n            \"8\": \"Is the deer graceful?\",\n            \"9\": \"Is the flamingo wading in the waters?\",\n            \"10\": \"Is the parrot singing?\",\n            \"11\": \"Is the parrot atop the deer?\",\n            \"12\": \"Is the deer below the parrot?\",\n            \"13\": \"Is the flamingo under the sunset?\",\n            \"14\": \"Is the deer nearby the parrot?\",\n            \"15\": \"Is there an atmosphere of tranquility?\"\n        }\n    },\n    {\n        \"prompt\": \"In a serene jungle glade, a panda munches bamboo, while a lion observes and a playful fox darts around. Bliss.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"entity - whole\",\n            \"5\": \"entity - whole\",\n            \"6\": \"attribute - state\",\n            \"7\": \"action -\",\n            \"8\": \"action -\",\n            \"9\": \"action -\",\n            \"10\": \"attribute - state\",\n            \"11\": \"relation - spatial\",\n            \"12\": \"relation - spatial\",\n            \"13\": \"relation - spatial\",\n            \"14\": \"global -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                0\n            ],\n            \"5\": [\n                0\n            ],\n            \"6\": [\n                1\n            ],\n            \"7\": [\n                2,\n                3\n            ],\n            \"8\": [\n                4\n            ],\n            \"9\": [\n                5\n            ],\n            \"10\": [\n                5\n            ],\n            \"11\": [\n                1,\n                2\n            ],\n            \"12\": [\n                1,\n                4\n            ],\n            \"13\": [\n                1,\n                5\n            ],\n            \"14\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a jungle glade?\",\n            \"2\": \"Is there a panda?\",\n            \"3\": \"Is there bamboo?\",\n            \"4\": \"Is there a lion?\",\n            \"5\": \"Is there a fox?\",\n            \"6\": \"Is the jungle glade serene?\",\n            \"7\": \"Is the panda munching bamboo?\",\n            \"8\": \"Is the lion observing?\",\n            \"9\": \"Is the fox darting around?\",\n            \"10\": \"Is the fox playful?\",\n            \"11\": \"Is the panda in the jungle glade?\",\n            \"12\": \"Is the lion in the jungle glade?\",\n            \"13\": \"Is the fox in the jungle glade?\",\n            \"14\": \"Is this a state of bliss?\"\n        }\n    }\n]"
  },
  {
    "path": "eval/tools/XVerseBench_single.json",
    "content": "\n[\n    {\n        \"index\": 0,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a polar bear standing on iceberg\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/13_polar bear.jpg\",\n                        \"caption\": \"a polar bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"polar bear\",\n                        \"polar bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 1,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a sea turtle swimming in the sea.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/18_sea turtle.jpg\",\n                        \"caption\": \"a sea turtle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"sea turtle\",\n                        \"sea turtle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 2,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a raccoon standing in a forest\\n\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/08_raccoon.jpg\",\n                        \"caption\": \"a raccoon\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"raccoon\",\n                        \"raccoon\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 3,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a dog wearing a red collar running\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/12_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"dog\",\n                        \"dog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 4,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a sphynx cat sitting on a sofa\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/25_Sphynx cat.jpg\",\n                        \"caption\": \"a sphynx cat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"sphynx cat\",\n                        \"sphynx cat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 5,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a colorful butterfly flying in the garden\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/15_butterfly.jpg\",\n                        \"caption\": \"a butterfly\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"butterfly\",\n                        \"butterfly\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 6,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a grasshopper jumping on the grass\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/29_grasshopper.jpg\",\n                        \"caption\": \"a grasshopper\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"grasshopper\",\n                        \"grasshopper\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 7,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a deer standing in a forest\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/31_deer.jpg\",\n                        \"caption\": \"a deer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"deer\",\n                        \"deer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 8,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a dolphin jumping out of the water\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/39_dolphin.jpg\",\n                        \"caption\": \"a dolphin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"dolphin\",\n                        \"dolphin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 9,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a cute kitten wearing a bowtie\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/02_kitten.jpg\",\n                        \"caption\": \"a kitten\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"kitten\",\n                        \"kitten\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 10,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"an elephant standing in the savannah\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/38_elephant.jpg\",\n                        \"caption\": \"an elephant\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"elephant\",\n                        \"elephant\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 11,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a shark swimming in the blue sea\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/06_shark.jpg\",\n                        \"caption\": \"a shark\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"shark\",\n                        \"shark\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 12,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"an eagle flying in the blue sky\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/14_eagle.jpg\",\n                        \"caption\": \"an eagle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"eagle\",\n                        \"eagle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 13,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a panda sitting on a bamboo mat\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/33_panda.jpg\",\n                        \"caption\": \"a panda\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"panda\",\n                        \"panda\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 14,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a rooster standing on a wooden fence\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/09_rooster.jpg\",\n                        \"caption\": \"a rooster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"rooster\",\n                        \"rooster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 15,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a cute kitten sitting on a mat.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/00_kitten.jpg\",\n                        \"caption\": \"a kitten\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"kitten\",\n                        \"kitten\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 16,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a lizard on a rocky background\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/36_lizard.jpg\",\n                        \"caption\": \"a lizard\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"lizard\",\n                        \"lizard\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 17,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a penguin standing on an iceberg\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/05_penguin.jpg\",\n                        \"caption\": \"a penguin\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"penguin\",\n                        \"penguin\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 18,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a white tiger standing in the grass.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/40_white tiger.jpg\",\n                        \"caption\": \"a white tiger\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"white tiger\",\n                        \"white tiger\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 19,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a french bulldog in a cozy sweater\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/43_French bulldog.jpg\",\n                        \"caption\": \"a french bulldog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"french bulldog\",\n                        \"french bulldog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 20,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a cute hamster wearing a tiny hat\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/20_hamster.jpg\",\n                        \"caption\": \"a hamster\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hamster\",\n                        \"hamster\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 21,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a crab walking on the sandy beach\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/04_crab.jpg\",\n                        \"caption\": \"a crab\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"crab\",\n                        \"crab\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 22,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a stork standing on a grassy field\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/01_stork.jpg\",\n                        \"caption\": \"a stork\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"stork\",\n                        \"stork\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 23,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a wolf howling in the forest\\n\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/27_wolf.jpg\",\n                        \"caption\": \"a wolf\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"wolf\",\n                        \"wolf\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 24,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a sly fox in a forest setting\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/10_fox.jpg\",\n                        \"caption\": \"a fox\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"fox\",\n                        \"fox\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 25,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a cute puppy in a red bow\\n\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/42_puppy.jpg\",\n                        \"caption\": \"a puppy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"puppy\",\n                        \"puppy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 26,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a cute cat sitting on a mat\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/44_cat.jpg\",\n                        \"caption\": \"a cat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cat\",\n                        \"cat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 27,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a cute dog in a red collar\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/07_dog.jpg\",\n                        \"caption\": \"a dog\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"dog\",\n                        \"dog\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 28,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a heron standing by a pond\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/animal/11_heron.jpg\",\n                        \"caption\": \"a heron\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"heron\",\n                        \"heron\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 29,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/05_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 30,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a woman smiling in a flower-filled garden\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/03_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 31,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a cute boy smiling in a crib.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/00_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 32,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a boy smiling in a sunny park\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/14_boy.jpg\",\n                        \"caption\": \"a boy\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boy\",\n                        \"boy\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 33,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/06_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 34,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a girl smiling in a flower-filled garden\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/19_girl.jpg\",\n                        \"caption\": \"a girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"girl\",\n                        \"girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 35,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a woman in a red dress smiling\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/09_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 36,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/07_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 37,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a woman standing in a park\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/13_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 38,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man wearing a hat standing in the forest\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/17_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 39,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/02_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 40,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a woman standing in a garden\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/15_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 41,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a woman standing in a flower-filled garden\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/12_woman.jpg\",\n                        \"caption\": \"a woman\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"woman\",\n                        \"woman\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 42,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/08_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 43,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/18_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 44,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/11_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 45,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/01_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 46,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man standing in a city street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/10_man.jpg\",\n                        \"caption\": \"a man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"man\",\n                        \"man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 47,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"an old man sitting on a bench.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/16_old man.jpg\",\n                        \"caption\": \"an old man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"old man\",\n                        \"old man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 48,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a little girl smiling in a garden.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/human/04_little girl.jpg\",\n                        \"caption\": \"a little girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"little girl\",\n                        \"little girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 49,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a man wearing a watch, standing. \",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/12_watch.jpg\",\n                        \"caption\": \"a watch\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"watch\",\n                        \"watch\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 50,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"anime spider-man in a city background\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/71_anime Spider-Man.jpg\",\n                        \"caption\": \"an anime spider-man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"anime spider-man\",\n                        \"anime spider-man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 51,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person wearing a cap smiling\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/32_cap.jpg\",\n                        \"caption\": \"a cap\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cap\",\n                        \"cap\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 52,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"anime girl in a cute pose\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/66_anime girl.jpg\",\n                        \"caption\": \"an anime girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"anime girl\",\n                        \"anime girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 53,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person holding a mug in the kitchen\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/27_mug.jpg\",\n                        \"caption\": \"a mug\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"mug\",\n                        \"mug\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 54,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person standing among cherry blossoms\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/03_cherry blossoms.jpg\",\n                        \"caption\": \"a cherry blossoms\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cherry blossoms\",\n                        \"cherry blossoms\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 55,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person rowing a boat on the lake\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/62_boat.jpg\",\n                        \"caption\": \"a boat\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"boat\",\n                        \"boat\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 56,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person standing by a stop sign\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/51_stop sign.jpg\",\n                        \"caption\": \"a stop sign\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"stop sign\",\n                        \"stop sign\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 57,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a guy playing guitar on the street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/39_guitar.jpg\",\n                        \"caption\": \"a guitar\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"guitar\",\n                        \"guitar\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 58,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person standing in front of a house\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/14_house.jpg\",\n                        \"caption\": \"a house\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"house\",\n                        \"house\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 59,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person standing in front of wooden house\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/45_wooden house.jpg\",\n                        \"caption\": \"a wooden house\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"wooden house\",\n                        \"wooden house\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 60,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person in a yellow taxi\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/44_yellow taxi.jpg\",\n                        \"caption\": \"a yellow taxi\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"yellow taxi\",\n                        \"yellow taxi\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 61,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"anime girl in a cute pose\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/70_anime girl.jpg\",\n                        \"caption\": \"an anime girl\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"anime girl\",\n                        \"anime girl\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 62,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person wearing a ring smiling\\n\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/16_ring.jpg\",\n                        \"caption\": \"a ring\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"ring\",\n                        \"ring\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 63,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person standing by an airplane\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/37_airplane.jpg\",\n                        \"caption\": \"an airplane\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"airplane\",\n                        \"airplane\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 64,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a teddy bear sitting on a cozy sofa\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/13_teddy bear.jpg\",\n                        \"caption\": \"a teddy bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"teddy bear\",\n                        \"teddy bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 65,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person wearing sunglasses casually\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/58_sunglasses.jpg\",\n                        \"caption\": \"a sunglasses\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"sunglasses\",\n                        \"sunglasses\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 66,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person looking at a clock on the wall\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/56_clock.jpg\",\n                        \"caption\": \"a clock\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"clock\",\n                        \"clock\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 67,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person holding a pineapple smiling\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/43_pineapple.jpg\",\n                        \"caption\": \"a pineapple\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"pineapple\",\n                        \"pineapple\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 68,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person sitting in front of a vintage television\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/49_vintage television.jpg\",\n                        \"caption\": \"a vintage television\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"vintage television\",\n                        \"vintage television\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 69,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person using a vintage computer\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/35_vintage computer.jpg\",\n                        \"caption\": \"a vintage computer\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"vintage computer\",\n                        \"vintage computer\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 70,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"anime man in a cool pose\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/73_anime man.jpg\",\n                        \"caption\": \"an anime man\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"anime man\",\n                        \"anime man\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 71,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person in a t-shirt smiling\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/41_t-shirt.jpg\",\n                        \"caption\": \"a t-shirt\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"t-shirt\",\n                        \"t-shirt\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 72,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a woman holding a teapot in the kitchen\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/52_teapot.jpg\",\n                        \"caption\": \"a teapot\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"teapot\",\n                        \"teapot\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 73,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a robot standing in a city street\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/18_robot.jpg\",\n                        \"caption\": \"a robot\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"robot\",\n                        \"robot\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 74,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person carrying a backpack walking\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/28_backpack.jpg\",\n                        \"caption\": \"a backpack\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"backpack\",\n                        \"backpack\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 75,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person holding a magic cube\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/20_Magic Cube.jpg\",\n                        \"caption\": \"a magic cube\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"magic cube\",\n                        \"magic cube\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 76,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person wearing headphones, standing\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/55_headphones.jpg\",\n                        \"caption\": \"a headphones\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"headphones\",\n                        \"headphones\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 77,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person riding a bicycle outdoors\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/17_bicycle.jpg\",\n                        \"caption\": \"a bicycle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"bicycle\",\n                        \"bicycle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 78,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a steam locomotive chugging on tracks\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/19_steam locomotive.jpg\",\n                        \"caption\": \"a steam locomotive\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"steam locomotive\",\n                        \"steam locomotive\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 79,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person sitting in an armchair\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/11_armchair.jpg\",\n                        \"caption\": \"an armchair\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"armchair\",\n                        \"armchair\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 80,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person eating a donut casually.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/38_donut.jpg\",\n                        \"caption\": \"a donut\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"donut\",\n                        \"donut\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 81,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a woman holds a leather handbag.\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/57_leather handbag.jpg\",\n                        \"caption\": \"a leather handbag\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"leather handbag\",\n                        \"leather handbag\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 82,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a rider on a motorcycle speeding\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/00_motorcycle.jpg\",\n                        \"caption\": \"a motorcycle\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"motorcycle\",\n                        \"motorcycle\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 83,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a teddy bear sitting on a sofa\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/46_teddy bear.jpg\",\n                        \"caption\": \"a teddy bear\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"teddy bear\",\n                        \"teddy bear\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 84,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"anime samurai in a traditional pose\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/69_anime samurai.jpg\",\n                        \"caption\": \"an anime samurai\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"anime samurai\",\n                        \"anime samurai\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 85,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person sipping a cocktail in bar\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/63_cocktail.jpg\",\n                        \"caption\": \"a cocktail\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"cocktail\",\n                        \"cocktail\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 86,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a classical bust on a pedestal\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/25_classical bust.jpg\",\n                        \"caption\": \"a classical bust\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"classical bust\",\n                        \"classical bust\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 87,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person in a hot air balloon flying\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/09_hot air balloon.jpg\",\n                        \"caption\": \"a hot air balloon\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hot air balloon\",\n                        \"hot air balloon\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 88,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"a person standing in front of a hut\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/42_hut.jpg\",\n                        \"caption\": \"a hut\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"hut\",\n                        \"hut\"\n                    ]\n                ]\n            }\n        ]\n    },\n    {\n        \"index\": 89,\n        \"input_images\": [],\n        \"position_delta\": [\n            0,\n            -32\n        ],\n        \"prompt\": \"pixelated warrior standing in a pixel world\",\n        \"modulation\": [\n            {\n                \"type\": \"adapter\",\n                \"src_inputs\": [\n                    {\n                        \"image_path\": \"assets/XVerseBench/object/67_pixelated warrior.jpg\",\n                        \"caption\": \"a pixelated warrior\"\n                    }\n                ],\n                \"use_words\": [\n                    [\n                        0,\n                        \"pixelated warrior\",\n                        \"pixelated warrior\"\n                    ]\n                ]\n            }\n        ]\n    }\n]"
  },
  {
    "path": "eval/tools/XVerseBench_single_DSG.json",
    "content": "[\n    {\n        \"prompt\": \"a polar bear standing on iceberg\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a polar bear?\",\n            \"2\": \"Is there an iceberg?\",\n            \"3\": \"Is the bear a polar bear?\",\n            \"4\": \"Is the polar bear standing?\",\n            \"5\": \"Is the polar bear on the iceberg?\"\n        }\n    },\n    {\n        \"prompt\": \"a sea turtle swimming in the sea.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - type\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a sea turtle?\",\n            \"2\": \"Is there a sea?\",\n            \"3\": \"Is the sea turtle swimming in the sea?\",\n            \"4\": \"Is the turtle a sea turtle?\"\n        }\n    },\n    {\n        \"prompt\": \"a raccoon standing in a forest\\n\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a raccoon?\",\n            \"2\": \"Is there a forest?\",\n            \"3\": \"Is the raccoon standing?\",\n            \"4\": \"Is the raccoon in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"a dog wearing a red collar running\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - part\",\n            \"3\": \"attribute - color\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a dog?\",\n            \"2\": \"Does the dog have a collar?\",\n            \"3\": \"Is the dog's collar red?\",\n            \"4\": \"Is the dog running?\",\n            \"5\": \"Is the dog wearing a collar?\"\n        }\n    },\n    {\n        \"prompt\": \"a sphynx cat sitting on a sofa\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a sofa?\",\n            \"3\": \"Is the cat a sphynx cat?\",\n            \"4\": \"Is the cat sitting?\",\n            \"5\": \"Is the cat on the sofa?\"\n        }\n    },\n    {\n        \"prompt\": \"a colorful butterfly flying in the garden\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a butterfly?\",\n            \"2\": \"Is there a garden?\",\n            \"3\": \"Is the butterfly colorful?\",\n            \"4\": \"Is the butterfly flying in the garden?\"\n        }\n    },\n    {\n        \"prompt\": \"a grasshopper jumping on the grass\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a grasshopper?\",\n            \"2\": \"Is there grass?\",\n            \"3\": \"Is the grasshopper jumping?\",\n            \"4\": \"Is the grasshopper on the grass?\"\n        }\n    },\n    {\n        \"prompt\": \"a deer standing in a forest\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a deer?\",\n            \"2\": \"Is there a forest?\",\n            \"3\": \"Is the deer standing?\",\n            \"4\": \"Is the deer in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"a dolphin jumping out of the water\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a dolphin?\",\n            \"2\": \"Is there water?\",\n            \"3\": \"Is the dolphin jumping out of the water?\"\n        }\n    },\n    {\n        \"prompt\": \"a cute kitten wearing a bowtie\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - part\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a kitten?\",\n            \"2\": \"Does the kitten have a bowtie?\",\n            \"3\": \"Is the kitten cute?\",\n            \"4\": \"Is the kitten wearing a bowtie?\"\n        }\n    },\n    {\n        \"prompt\": \"an elephant standing in the savannah\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an elephant?\",\n            \"2\": \"Is there a savannah?\",\n            \"3\": \"Is the elephant standing?\",\n            \"4\": \"Is the elephant in the savannah?\"\n        }\n    },\n    {\n        \"prompt\": \"a shark swimming in the blue sea\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - color\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a shark?\",\n            \"2\": \"Is there a sea?\",\n            \"3\": \"Is the shark swimming in the sea?\",\n            \"4\": \"Is the sea blue?\"\n        }\n    },\n    {\n        \"prompt\": \"an eagle flying in the blue sky\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - color\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there an eagle?\",\n            \"2\": \"Is there a sky?\",\n            \"3\": \"Is the eagle flying in the sky?\",\n            \"4\": \"Is the sky blue?\"\n        }\n    },\n    {\n        \"prompt\": \"a panda sitting on a bamboo mat\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a panda?\",\n            \"2\": \"Is there a bamboo mat?\",\n            \"3\": \"Is the panda sitting?\",\n            \"4\": \"Is the panda on the bamboo mat?\"\n        }\n    },\n    {\n        \"prompt\": \"a rooster standing on a wooden fence\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"attribute - material\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1\n            ],\n            \"6\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a rooster?\",\n            \"2\": \"Is there a fence?\",\n            \"3\": \"Does the rooster have legs?\",\n            \"4\": \"Is the fence made of wood?\",\n            \"5\": \"Is the rooster standing?\",\n            \"6\": \"Is the rooster on the fence?\"\n        }\n    },\n    {\n        \"prompt\": \"a cute kitten sitting on a mat.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a kitten?\",\n            \"2\": \"Is there a mat?\",\n            \"3\": \"Is the kitten cute?\",\n            \"4\": \"Is the kitten sitting?\",\n            \"5\": \"Is the kitten on the mat?\"\n        }\n    },\n    {\n        \"prompt\": \"a lizard on a rocky background\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - texture\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a lizard?\",\n            \"2\": \"Is there a background?\",\n            \"3\": \"Is the background rocky?\",\n            \"4\": \"Is the lizard on the background?\"\n        }\n    },\n    {\n        \"prompt\": \"a penguin standing on an iceberg\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a penguin?\",\n            \"2\": \"Is there an iceberg?\",\n            \"3\": \"Is the penguin standing?\",\n            \"4\": \"Is the penguin on the iceberg?\"\n        }\n    },\n    {\n        \"prompt\": \"a white tiger standing in the grass.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - color\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a tiger?\",\n            \"2\": \"Is there grass?\",\n            \"3\": \"Is the tiger white?\",\n            \"4\": \"Is the tiger standing?\",\n            \"5\": \"Is the tiger in the grass?\"\n        }\n    },\n    {\n        \"prompt\": \"a french bulldog in a cozy sweater\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a bulldog?\",\n            \"2\": \"Is there a sweater?\",\n            \"3\": \"Is the bulldog a French bulldog?\",\n            \"4\": \"Is the bulldog in the sweater?\",\n            \"5\": \"Is the sweater cozy?\"\n        }\n    },\n    {\n        \"prompt\": \"a cute hamster wearing a tiny hat\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - scale\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a hamster?\",\n            \"2\": \"Is there a hat?\",\n            \"3\": \"Is the hamster cute?\",\n            \"4\": \"Is the hat tiny?\",\n            \"5\": \"Is the hat on the hamster?\"\n        }\n    },\n    {\n        \"prompt\": \"a crab walking on the sandy beach\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"attribute - texture\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a crab?\",\n            \"2\": \"Is there a beach?\",\n            \"3\": \"Is the crab walking?\",\n            \"4\": \"Is the crab on the beach?\",\n            \"5\": \"Is the beach sandy?\"\n        }\n    },\n    {\n        \"prompt\": \"a stork standing on a grassy field\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - texture\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a stork?\",\n            \"2\": \"Is there a field?\",\n            \"3\": \"Is the stork standing?\",\n            \"4\": \"Is the field grassy?\",\n            \"5\": \"Is the stork on the field?\"\n        }\n    },\n    {\n        \"prompt\": \"a wolf howling in the forest\\n\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a wolf?\",\n            \"2\": \"Is there a forest?\",\n            \"3\": \"Is the wolf howling?\",\n            \"4\": \"Is the wolf in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"a sly fox in a forest setting\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a fox?\",\n            \"2\": \"Is there a forest?\",\n            \"3\": \"Is the fox sly?\",\n            \"4\": \"Is the fox in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"a cute puppy in a red bow\\n\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - color\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a puppy?\",\n            \"2\": \"Is there a bow?\",\n            \"3\": \"Is the puppy cute?\",\n            \"4\": \"Is the bow red?\",\n            \"5\": \"Is the puppy wearing the bow?\"\n        }\n    },\n    {\n        \"prompt\": \"a cute cat sitting on a mat\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a cat?\",\n            \"2\": \"Is there a mat?\",\n            \"3\": \"Is the cat cute?\",\n            \"4\": \"Is the cat sitting?\",\n            \"5\": \"Is the cat on the mat?\"\n        }\n    },\n    {\n        \"prompt\": \"a cute dog in a red collar\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - part\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - color\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a dog?\",\n            \"2\": \"Does the dog have a collar?\",\n            \"3\": \"Is the dog cute?\",\n            \"4\": \"Is the collar red?\",\n            \"5\": \"Is the dog wearing a red collar?\"\n        }\n    },\n    {\n        \"prompt\": \"a heron standing by a pond\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a heron?\",\n            \"2\": \"Is there a pond?\",\n            \"3\": \"Is the heron standing?\",\n            \"4\": \"Is the heron next to the pond?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a woman smiling in a flower-filled garden\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"attribute - state\",\n            \"5\": \"attribute - state\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                2\n            ],\n            \"6\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a garden?\",\n            \"3\": \"Are there flowers in the garden?\",\n            \"4\": \"Is the woman smiling?\",\n            \"5\": \"Is the garden filled with flowers?\",\n            \"6\": \"Is the woman in the garden?\"\n        }\n    },\n    {\n        \"prompt\": \"a cute boy smiling in a crib.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a crib?\",\n            \"3\": \"Is the boy cute?\",\n            \"4\": \"Is the boy smiling?\",\n            \"5\": \"Is the boy in the crib?\"\n        }\n    },\n    {\n        \"prompt\": \"a boy smiling in a sunny park\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a boy?\",\n            \"2\": \"Is there a park?\",\n            \"3\": \"Is the boy smiling?\",\n            \"4\": \"Is the park sunny?\",\n            \"5\": \"Is the boy in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a girl smiling in a flower-filled garden\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - part\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a garden?\",\n            \"3\": \"Are there flowers in the garden?\",\n            \"4\": \"Is the girl smiling?\",\n            \"5\": \"Is the girl in the garden?\",\n            \"6\": \"Is the garden filled with flowers?\"\n        }\n    },\n    {\n        \"prompt\": \"a woman in a red dress smiling\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - color\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a dress?\",\n            \"3\": \"Is the dress red?\",\n            \"4\": \"Is the woman in the dress?\",\n            \"5\": \"Is the woman smiling?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a woman standing in a park\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - gender\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a park?\",\n            \"3\": \"Is the woman female?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the woman in the park?\"\n        }\n    },\n    {\n        \"prompt\": \"a man wearing a hat standing in the forest\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - part\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Does the man have a hat?\",\n            \"3\": \"Is there a forest?\",\n            \"4\": \"Is the man standing?\",\n            \"5\": \"Is the man wearing a hat?\",\n            \"6\": \"Is the man in the forest?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a woman standing in a garden\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - gender\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a garden?\",\n            \"3\": \"Is the woman female?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the woman in the garden?\"\n        }\n    },\n    {\n        \"prompt\": \"a woman standing in a flower-filled garden\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a garden?\",\n            \"3\": \"Are there flowers?\",\n            \"4\": \"Is the woman standing?\",\n            \"5\": \"Is the woman in the garden?\",\n            \"6\": \"Are the flowers in the garden?\",\n            \"7\": \"Is the garden filled with flowers?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a man standing in a city street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"an old man sitting on a bench.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a bench?\",\n            \"3\": \"Is the man old?\",\n            \"4\": \"Is the man sitting?\",\n            \"5\": \"Is the man on the bench?\"\n        }\n    },\n    {\n        \"prompt\": \"a little girl smiling in a garden.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - scale\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is there a garden?\",\n            \"3\": \"Is the girl little?\",\n            \"4\": \"Is the girl smiling?\",\n            \"5\": \"Is the girl in the garden?\"\n        }\n    },\n    {\n        \"prompt\": \"a man wearing a watch, standing. \",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is there a watch?\",\n            \"3\": \"Is the man standing?\",\n            \"4\": \"Is the man wearing a watch?\"\n        }\n    },\n    {\n        \"prompt\": \"anime spider-man in a city background\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - style\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a Spider - Man?\",\n            \"2\": \"Is there a city?\",\n            \"3\": \"Is Spider - Man in anime style?\",\n            \"4\": \"Is Spider - Man in the city background?\"\n        }\n    },\n    {\n        \"prompt\": \"a person wearing a cap smiling\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a cap?\",\n            \"3\": \"Is the person wearing a cap?\",\n            \"4\": \"Is the person smiling?\"\n        }\n    },\n    {\n        \"prompt\": \"anime girl in a cute pose\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"attribute - type\",\n            \"3\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is the girl an anime girl?\",\n            \"3\": \"Is the girl in a cute pose?\"\n        }\n    },\n    {\n        \"prompt\": \"a person holding a mug in the kitchen\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"relation - spatial\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ],\n            \"6\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a mug?\",\n            \"3\": \"Is there a kitchen?\",\n            \"4\": \"Is the person holding the mug?\",\n            \"5\": \"Is the person in the kitchen?\",\n            \"6\": \"Is the mug in the kitchen?\"\n        }\n    },\n    {\n        \"prompt\": \"a person standing among cherry blossoms\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Are there cherry blossoms?\",\n            \"3\": \"Is the person standing?\",\n            \"4\": \"Is the person among the cherry blossoms?\"\n        }\n    },\n    {\n        \"prompt\": \"a person rowing a boat on the lake\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\",\n            \"6\": \"relation - spatial\",\n            \"7\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ],\n            \"6\": [\n                2,\n                3\n            ],\n            \"7\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a boat?\",\n            \"3\": \"Is there a lake?\",\n            \"4\": \"Is the person rowing the boat?\",\n            \"5\": \"Is the person on the boat?\",\n            \"6\": \"Is the boat on the lake?\",\n            \"7\": \"Is the person on the lake?\"\n        }\n    },\n    {\n        \"prompt\": \"a person standing by a stop sign\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a stop sign?\",\n            \"3\": \"Is the person standing?\",\n            \"4\": \"Is the person next to the stop sign?\"\n        }\n    },\n    {\n        \"prompt\": \"a guy playing guitar on the street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a guy?\",\n            \"2\": \"Is there a guitar?\",\n            \"3\": \"Is there a street?\",\n            \"4\": \"Is the guy playing the guitar?\",\n            \"5\": \"Is the guy on the street?\"\n        }\n    },\n    {\n        \"prompt\": \"a person standing in front of a house\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a house?\",\n            \"3\": \"Is the person standing?\",\n            \"4\": \"Is the person in front of the house?\"\n        }\n    },\n    {\n        \"prompt\": \"a person standing in front of wooden house\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - material\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a house?\",\n            \"3\": \"Is the person standing?\",\n            \"4\": \"Is the house made of wood?\",\n            \"5\": \"Is the person in front of the house?\"\n        }\n    },\n    {\n        \"prompt\": \"a person in a yellow taxi\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - color\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a taxi?\",\n            \"3\": \"Is the taxi yellow?\",\n            \"4\": \"Is the person in the taxi?\"\n        }\n    },\n    {\n        \"prompt\": \"anime girl in a cute pose\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"attribute - type\",\n            \"3\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a girl?\",\n            \"2\": \"Is the girl an anime girl?\",\n            \"3\": \"Is the girl in a cute pose?\"\n        }\n    },\n    {\n        \"prompt\": \"a person wearing a ring smiling\\n\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a ring?\",\n            \"3\": \"Is the person wearing a ring?\",\n            \"4\": \"Is the person smiling?\"\n        }\n    },\n    {\n        \"prompt\": \"a person standing by an airplane\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there an airplane?\",\n            \"3\": \"Is the person standing?\",\n            \"4\": \"Is the person by the airplane?\"\n        }\n    },\n    {\n        \"prompt\": \"a teddy bear sitting on a cozy sofa\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a teddy bear?\",\n            \"2\": \"Is there a sofa?\",\n            \"3\": \"Is the teddy bear sitting?\",\n            \"4\": \"Is the sofa cozy?\",\n            \"5\": \"Is the teddy bear on the sofa?\"\n        }\n    },\n    {\n        \"prompt\": \"a person wearing sunglasses casually\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Are there sunglasses?\",\n            \"3\": \"Is the person wearing sunglasses?\",\n            \"4\": \"Is the person being casual?\"\n        }\n    },\n    {\n        \"prompt\": \"a person looking at a clock on the wall\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                2,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a clock?\",\n            \"3\": \"Is there a wall?\",\n            \"4\": \"Is the person looking at the clock?\",\n            \"5\": \"Is the clock on the wall?\"\n        }\n    },\n    {\n        \"prompt\": \"a person holding a pineapple smiling\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a pineapple?\",\n            \"3\": \"Is the person holding a pineapple?\",\n            \"4\": \"Is the person smiling?\"\n        }\n    },\n    {\n        \"prompt\": \"a person sitting in front of a vintage television\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - era\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a television?\",\n            \"3\": \"Is the person sitting?\",\n            \"4\": \"Is the television vintage?\",\n            \"5\": \"Is the person in front of the television?\"\n        }\n    },\n    {\n        \"prompt\": \"a person using a vintage computer\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - age\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a computer?\",\n            \"3\": \"Is the person using the computer?\",\n            \"4\": \"Is the computer vintage?\"\n        }\n    },\n    {\n        \"prompt\": \"anime man in a cool pose\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"attribute - style\",\n            \"3\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a man?\",\n            \"2\": \"Is the man in anime style?\",\n            \"3\": \"Is the man in a cool pose?\"\n        }\n    },\n    {\n        \"prompt\": \"a person in a t-shirt smiling\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - part\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is the person wearing a t-shirt?\",\n            \"3\": \"Is the person smiling?\",\n            \"4\": \"Is the person in a t-shirt?\"\n        }\n    },\n    {\n        \"prompt\": \"a woman holding a teapot in the kitchen\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a teapot?\",\n            \"3\": \"Is there a kitchen?\",\n            \"4\": \"Is the woman holding the teapot?\",\n            \"5\": \"Is the woman in the kitchen?\"\n        }\n    },\n    {\n        \"prompt\": \"a robot standing in a city street\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a robot?\",\n            \"2\": \"Is there a city street?\",\n            \"3\": \"Is the robot standing?\",\n            \"4\": \"Is the robot in the city street?\"\n        }\n    },\n    {\n        \"prompt\": \"a person carrying a backpack walking\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a backpack?\",\n            \"3\": \"Is the person carrying a backpack?\",\n            \"4\": \"Is the person walking?\",\n            \"5\": \"Is the person carrying the backpack?\"\n        }\n    },\n    {\n        \"prompt\": \"a person holding a magic cube\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a magic cube?\",\n            \"3\": \"Is the person holding the magic cube?\"\n        }\n    },\n    {\n        \"prompt\": \"a person wearing headphones, standing\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - part\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Does the person have headphones?\",\n            \"3\": \"Is the person standing?\",\n            \"4\": \"Is the person wearing headphones?\"\n        }\n    },\n    {\n        \"prompt\": \"a person riding a bicycle outdoors\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"global -\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                0\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a bicycle?\",\n            \"3\": \"Is the person riding the bicycle?\",\n            \"4\": \"Is this outdoors?\"\n        }\n    },\n    {\n        \"prompt\": \"a steam locomotive chugging on tracks\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - type\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a steam locomotive?\",\n            \"2\": \"Are there tracks?\",\n            \"3\": \"Is the locomotive a steam locomotive?\",\n            \"4\": \"Is the steam locomotive chugging?\",\n            \"5\": \"Is the steam locomotive on the tracks?\"\n        }\n    },\n    {\n        \"prompt\": \"a person sitting in an armchair\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there an armchair?\",\n            \"3\": \"Is the person sitting?\",\n            \"4\": \"Is the person in the armchair?\"\n        }\n    },\n    {\n        \"prompt\": \"a person eating a donut casually.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a donut?\",\n            \"3\": \"Is the person eating the donut?\",\n            \"4\": \"Is the person eating casually?\"\n        }\n    },\n    {\n        \"prompt\": \"a woman holds a leather handbag.\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - material\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a woman?\",\n            \"2\": \"Is there a handbag?\",\n            \"3\": \"Is the handbag made of leather?\",\n            \"4\": \"Is the woman holding the handbag?\"\n        }\n    },\n    {\n        \"prompt\": \"a rider on a motorcycle speeding\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"relation - spatial\",\n            \"4\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1,\n                2\n            ],\n            \"4\": [\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a rider?\",\n            \"2\": \"Is there a motorcycle?\",\n            \"3\": \"Is the rider on the motorcycle?\",\n            \"4\": \"Is the motorcycle speeding?\"\n        }\n    },\n    {\n        \"prompt\": \"a teddy bear sitting on a sofa\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a teddy bear?\",\n            \"2\": \"Is there a sofa?\",\n            \"3\": \"Is the teddy bear sitting?\",\n            \"4\": \"Is the teddy bear on the sofa?\"\n        }\n    },\n    {\n        \"prompt\": \"anime samurai in a traditional pose\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"attribute - type\",\n            \"3\": \"attribute - state\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                1\n            ],\n            \"3\": [\n                1\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a samurai?\",\n            \"2\": \"Is the samurai an anime samurai?\",\n            \"3\": \"Is the samurai in a traditional pose?\"\n        }\n    },\n    {\n        \"prompt\": \"a person sipping a cocktail in bar\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"entity - whole\",\n            \"4\": \"action -\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                0\n            ],\n            \"4\": [\n                1,\n                2\n            ],\n            \"5\": [\n                1,\n                3\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a cocktail?\",\n            \"3\": \"Is there a bar?\",\n            \"4\": \"Is the person sipping the cocktail?\",\n            \"5\": \"Is the person in the bar?\"\n        }\n    },\n    {\n        \"prompt\": \"a classical bust on a pedestal\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - style\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a bust?\",\n            \"2\": \"Is there a pedestal?\",\n            \"3\": \"Is the bust classical?\",\n            \"4\": \"Is the bust on the pedestal?\"\n        }\n    },\n    {\n        \"prompt\": \"a person in a hot air balloon flying\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"action -\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                2\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a hot air balloon?\",\n            \"3\": \"Is the hot air balloon flying?\",\n            \"4\": \"Is the person in the hot air balloon?\"\n        }\n    },\n    {\n        \"prompt\": \"a person standing in front of a hut\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a person?\",\n            \"2\": \"Is there a hut?\",\n            \"3\": \"Is the person standing?\",\n            \"4\": \"Is the person in front of the hut?\"\n        }\n    },\n    {\n        \"prompt\": \"pixelated warrior standing in a pixel world\",\n        \"qid2tuple\": {\n            \"1\": \"entity - whole\",\n            \"2\": \"entity - whole\",\n            \"3\": \"attribute - state\",\n            \"4\": \"attribute - state\",\n            \"5\": \"relation - spatial\"\n        },\n        \"qid2dependency\": {\n            \"1\": [\n                0\n            ],\n            \"2\": [\n                0\n            ],\n            \"3\": [\n                1\n            ],\n            \"4\": [\n                2\n            ],\n            \"5\": [\n                1,\n                2\n            ]\n        },\n        \"qid2question\": {\n            \"1\": \"Is there a warrior?\",\n            \"2\": \"Is there a pixel world?\",\n            \"3\": \"Is the warrior pixelated?\",\n            \"4\": \"Is the world a pixel world?\",\n            \"5\": \"Is the warrior standing in the pixel world?\"\n        }\n    }\n]"
  },
  {
    "path": "eval/tools/dino.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom transformers import ViTImageProcessor, ViTModel\nfrom torch.nn import functional as F\nfrom PIL import Image\nimport requests\nfrom torchvision import transforms\nimport torch, os\n\nclass DINOScore:\n\n    def __init__(self, device, use_center_crop=True):\n        # https://github.com/facebookresearch/dino/issues/72#issuecomment-932874140\n        # https://github.com/facebookresearch/dino/blob/main/eval_linear.py\n        # https://gist.github.com/woctezuma/a30ee1de2e5efc1a3beff8e108795374\n        # according to this, we should use center crop with class token\n        self.device = torch.device(device)\n        self.use_center_crop = use_center_crop\n\n        if use_center_crop:\n            self.T = transforms.Compose([\n                transforms.Resize(256, interpolation=3),\n                transforms.CenterCrop(224),\n                transforms.ToTensor(),\n                transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225)),\n            ])\n        else:\n            self.T = transforms.Compose([\n                transforms.Resize(224, interpolation=3),\n                transforms.ToTensor(),\n                transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225)),\n            ])\n        self.model = ViTModel.from_pretrained(os.getenv(\"DINO_MODEL_PATH\", \"facebook/dino-vits16\")).to(self.device)\n\n    \n    def __call__(self, image_x, image_y, similarity_type=\"class\"):\n\n        inputs = torch.stack([self.T(x) for x in [image_x, image_y]]) # (2, 3, 224, 224). Batchsize = 2\n        outputs = self.model(inputs.to(self.device))\n        last_hidden_states = outputs.last_hidden_state\n        \n        assert similarity_type in [\"class\", \"avg\"]\n        if similarity_type == \"class\":\n            return self.cls_similarity(last_hidden_states[0], last_hidden_states[1])\n\n        return self.avg_similairty(last_hidden_states[0], last_hidden_states[1])\n\n\n    def avg_similairty(self, x, y):\n        return F.cosine_similarity(x.mean(dim=0), y.mean(dim=0), dim=0).item() * 100\n\n    def cls_similarity(self, x, y):\n        return F.cosine_similarity(x[0], y[0], dim=0).item() * 100\n\nif __name__ == \"__main__\":\n    # urls = [\n    #     'https://github.com/google/dreambooth/blob/main/dataset/rc_car/03.jpg?raw=true', # reference from Fig 11\n    #     'https://github.com/google/dreambooth/blob/main/dataset/rc_car/02.jpg?raw=true'# Real Sample from Fig 11\n    # ]\n    # images = [Image.open(requests.get(url, stream=True).raw) for url in urls]\n    urls = [\n        \"assets/idipbench_base/object/3_pinkbackpack.png\",\n        \"tmp/backpack_0.png\",\n    ]\n    images = [Image.open(url).convert(\"RGB\") for url in urls]\n\n    dino_score_model = DINOScore(\"cuda\", use_center_crop=True)\n    print(dino_score_model(images[0], images[1], \"class\"))\n    print(dino_score_model(images[0], images[1], \"avg\"))"
  },
  {
    "path": "eval/tools/dpg_score.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport torch\nfrom copy import deepcopy\nfrom collections import defaultdict\nimport numpy as np\nimport pandas as pd\nimport os\n\nclass MPLUG(torch.nn.Module):\n    def __init__(self, ckpt='damo/mplug_visual-question-answering_coco_large_en', device='gpu'):\n        super().__init__()\n        from modelscope.pipelines import pipeline\n        from modelscope.utils.constant import Tasks\n        self.pipeline_vqa = pipeline(Tasks.visual_question_answering, model=ckpt, device=device)\n\n    def vqa(self, image, question):\n        input_vqa = {'image': image, 'question': question}\n        result = self.pipeline_vqa(input_vqa)\n        return result['text']\n\n\nclass DPGScore:\n    def __init__(self, device):\n        self.device = device\n        ckpt = os.getenv('DPG_VQA_MODEL_PATH', \"xingjianleng/mplug_visual-question-answering_coco_large_en\")\n        self.vqa_model = MPLUG(ckpt, device=self.device)\n\n        \n    def __call__(self, image, q_dict):\n        VQA = self.vqa_model\n        qid2tuple, qid2dependency, qid2question = q_dict['qid2tuple'], q_dict['qid2dependency'], q_dict['qid2question']\n        qid2answer = {}\n        qid2scores = {}\n\n        for id, question in qid2question.items():\n            id = str(id)\n            answer = VQA.vqa(image, question)\n            qid2answer[id] = answer\n            qid2scores[id] = float(answer == 'yes')\n                \n        average_score_without_dep = sum(qid2scores.values()) / len(qid2scores)\n            \n        qid2validity = {}\n        qid2scores_after_filtering = deepcopy(qid2scores)\n\n        for id, parent_ids in qid2dependency.items():\n            id = str(id)\n            any_parent_answered_no = False\n            for parent_id in parent_ids:\n                parent_id = str(parent_id)\n                if int(parent_id) == 0:\n                    continue\n                if parent_id in qid2scores:\n                    if qid2scores[parent_id] == 0:\n                        any_parent_answered_no = True\n                        break\n            if any_parent_answered_no:\n                qid2scores_after_filtering[id] = 0.0\n                qid2validity[id] = False\n            else:\n                qid2validity[id] = True\n\n        average_score_with_dep = sum(qid2scores_after_filtering.values()) / len(qid2scores)\n        return {\n            'qid2tuple': qid2tuple,\n            'qid2dependency': qid2dependency,\n            'qid2question': qid2question,\n            'qid2answer': qid2answer,\n            'qid2scores': qid2scores,\n            'qid2validity': qid2validity,\n            'average_score_with_dependency': average_score_with_dep * 100.,\n            'average_score_without_dependency': average_score_without_dep * 100.\n        }\n\n\ndef prepare_dpg_data(csv_path):\n    previous_id = ''\n    current_id = ''\n    question_dict = dict()\n    category_count = defaultdict(int)\n    data = pd.read_csv(csv_path)\n    for i, line in data.iterrows():\n        if i == 0:\n            continue\n\n        current_id = line.item_id\n        qid = str(line.proposition_id)\n        dependency_list_str = line.dependency.split(',')\n        dependency_list_int = []\n        for d in dependency_list_str:\n            d_int = str(d.strip())\n            dependency_list_int.append(d_int)\n\n        if current_id == previous_id:\n            question_dict[current_id]['qid2tuple'][qid] = line.tuple\n            question_dict[current_id]['qid2dependency'][qid] = dependency_list_int\n            question_dict[current_id]['qid2question'][qid] = line.question_natural_language\n        else:\n            question_dict[current_id] = dict(\n                qid2tuple={qid: line.tuple},\n                qid2dependency={qid: dependency_list_int},\n                qid2question={qid: line.question_natural_language})\n        \n        category = line.question_natural_language.split('(')[0].strip()\n        category_count[category] += 1\n        \n        previous_id = current_id\n    return question_dict\n\n\n\nif __name__ == \"__main__\":\n    import os\n    import time\n    import shutil\n    import argparse\n    from PIL import Image\n    from tqdm import tqdm\n    from src.train.data.data_utils import split_grid, json_load, json_dump\n    from src.train.train_utils import get_train_config, get_rank_and_worldsize\n    from src.train.data.validation import *\n\n    def parse_args():\n        parser = argparse.ArgumentParser()\n        parser.add_argument(\"--image_dir\", type=str, default=\"\")\n        args = parser.parse_args()\n        return args\n\n    args = parse_args()\n\n    local_rank, global_rank, world_size = get_rank_and_worldsize()\n    print(f\"local_rank={local_rank}, global_rank={global_rank}, world_size={world_size}\")\n    is_local_main_process = local_rank == 0\n    is_main_process = global_rank == 0\n\n    images = sorted(glob(f\"{args.image_dir}/*.png\"))\n\n    if world_size > 1:\n        num_per_rank = round(len(images) / world_size)\n        images = images[global_rank*num_per_rank:(global_rank+1)*num_per_rank]\n        os.environ['CUDA_VISIBLE_DEVICES'] = str(local_rank % 8)\n        print(f\"[rank {global_rank}/{world_size}] has {len(images)} prompts to process, using device {torch.cuda.current_device()}\")\n\n    run_name = time.strftime(\"%Y%m%d-%H\")\n    temp_dir = os.path.join(args.image_dir, f\"eval_temp_{run_name}\")\n\n    if global_rank == 0:\n        if os.path.exists(temp_dir):\n            shutil.rmtree(temp_dir)\n        os.makedirs(temp_dir)\n\n    dpg_score_model = DPGScore(\"cuda\")\n    q_dicts = prepare_dpg_data(f\"eval/dpg/dpg_bench.csv\")\n\n    rank_json = {}\n    with torch.no_grad():\n        for image_path in tqdm(images):\n            prompt_name = os.path.splitext(os.path.basename(image_path))[0]\n            q_dict = q_dicts[prompt_name]\n            images = split_grid(Image.open(image_path))\n            rank_json[prompt_name] = []\n            for i, img in enumerate(images):\n                rank_json[prompt_name].append({})\n                result = dpg_score_model(img, q_dict)\n                for q_id, question in result[\"qid2question\"].items():\n                    answer = result[\"qid2answer\"][q_id]\n                    rank_json[prompt_name][i][question] = answer\n                rank_json[prompt_name][i]['average_score_with_dependency'] = result['average_score_with_dependency']\n                rank_json[prompt_name][i]['average_score_without_dependency'] = result['average_score_without_dependency']\n\n    rank_save_path = os.path.join(temp_dir, f\"scores_{global_rank}.json\")\n    json_dump(rank_json, rank_save_path, \"utf-8\")\n\n    if global_rank == 0:\n        while len(glob(os.path.join(temp_dir, f\"scores_*.json\"))) < world_size:\n            time.sleep(5)\n        time.sleep(5) # wait for the file writting to be finished\n        merged_json = {}\n        prompt_scores = {}\n        scores = []\n        for rank_path in glob(os.path.join(temp_dir, f\"scores_*.json\")):\n            rank_json = json_load(rank_path, \"utf-8\")\n            merged_json.update(rank_json)\n            for prompt_name in rank_json:\n                score_list = [x['average_score_with_dependency'] for x in rank_json[prompt_name]]\n                prompt_scores[prompt_name] = np.mean(score_list)\n                scores += score_list\n\n        json_dump(merged_json, os.path.join(args.image_dir, f\"dpg_scores_{run_name}.json\"), \"utf-8\")\n        dpg_score = np.mean(scores)\n        lines_to_write = [\n            f\"DPG Score: {dpg_score:.2f}\\n\"\n        ]\n        print(lines_to_write[0])\n        for prompt_name, score in prompt_scores.items():\n            lines_to_write.append(f\"{prompt_name}: {score:.2f}\\n\")\n\n        with open(os.path.join(args.image_dir, f\"dpg_scores_{run_name}.txt\"), \"w\") as f:\n            f.writelines(lines_to_write)\n\n        shutil.rmtree(temp_dir)"
  },
  {
    "path": "eval/tools/face_id.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport torch\nimport facer\nfrom PIL import Image\nfrom torchvision import transforms\nfrom eval.tools.face_utils.face import tight_warp_face\nfrom eval.tools.face_utils.face_recg import Backbone\nimport os\nfrom torch.nn import functional as F\nfrom src.utils.data_utils import pad_to_square, pad_to_target, json_dump, json_load, split_grid\n\n\ndef expand_bounding_box(x_min, y_min, x_max, y_max, factor=1.3):\n    # Calculate the center of the bounding box\n    x_center = (x_min + x_max) / 2\n    y_center = (y_min + y_max) / 2\n\n    # Calculate the width and height of the bounding box\n    width = x_max - x_min\n    height = y_max - y_min\n\n    # Calculate the new width and height\n    new_width = factor * width\n    new_height = factor * height\n\n    # Calculate the new bounding box coordinates\n    x_min_new = x_center - new_width / 2\n    x_max_new = x_center + new_width / 2\n    y_min_new = y_center - new_height / 2\n    y_max_new = y_center + new_height / 2\n\n    return x_min_new, y_min_new, x_max_new, y_max_new\n\nclass FaceID:\n    def __init__(self, device):\n        self.device = torch.device(device)\n        self.T = transforms.Compose([\n            transforms.ToTensor(),\n            transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])\n        ])\n        self.detector = facer.face_detector(\"retinaface/resnet50\", device=device)\n        face_model_path = os.getenv(\"FACE_ID_MODEL_PATH\")\n        self.model = Backbone(num_layers=50, drop_ratio=0.6, mode='ir_se')\n        self.model.load_state_dict(torch.load(face_model_path, map_location=device))\n        self.model.to(device)\n        self.model.eval()\n\n    def detect(self, image, expand_scale=1.3):\n        with torch.no_grad():\n            faces = self.detector(image.to(self.device))\n        bboxes = faces['rects'].detach().cpu().tolist()\n        bboxes = [expand_bounding_box(*x, expand_scale) for x in bboxes]\n        return bboxes\n\n    def __call__(self, image_x, image_y, normalize=False):\n        # NOTE: Only Support One Face Per Image\n        \n        try:\n            warp_x = tight_warp_face(image_x, self.detector)['cropped_face_masked']\n            warp_y = tight_warp_face(image_y, self.detector)['cropped_face_masked']\n        except:\n            # print(\"[Warning] No face detected!!\")\n            return 0\n\n        if warp_x is None or warp_y is None:\n            # print(\"[Warning] No face detected!!\")\n            return 0\n        \n        feature_x = self.model(self.T(warp_x).unsqueeze(0).to(self.device))[0] # [512]\n        feature_y = self.model(self.T(warp_y).unsqueeze(0).to(self.device))[0] # [512]\n        \n        \n        if normalize:\n            feature_x = feature_x / feature_x.norm(p=2, dim=-1, keepdim=True)\n            feature_y = feature_y / feature_y.norm(p=2, dim=-1, keepdim=True)\n\n        return F.cosine_similarity(feature_x, feature_y, dim=0).item() * 100\n    \n\n\nif __name__ == \"__main__\":\n    # online demo: https://dun.163.com/trial/face/compare\n    from src.train.data.data_utils import pil2tensor\n    import numpy as np\n\n\n    faceid = FaceID(\"cuda\")\n    real_image_path = \"assets/bengio_bengio.png\"\n\n    # gen_image_path = \"runs/0303-2034_flux100k_mod-t_oc-sblocks_multi-0.5_fs-lora8_cond192_res384_bs48_resume/eval/ckpt/40000/0304_cond192_tar512/1_A man is wearing green headphones standi.png\"\n    # gen_image_path = \"runs/0303-2034_flux100k_mod-t_oc-sblocks_multi-0.5_fs-lora8_cond192_res384_bs48_resume/eval/ckpt/40000/0304_cond192_tar512/7_A man is wearing green headphones standi.png\"\n    # gen_image_path = \"runs/0303-2034_flux100k_mod-t_oc-sblocks_multi-0.5_fs-lora8_cond192_res384_bs48_resume/eval/ckpt/40000/0304_cond192_tar512/198_A man wearing a black white suit and a w.png\"\n    gen_image_path = \"data/tmp/GCG/florence-sam_phrase-grounding_S3L-two-20k_v41_wds/00000/qwen10M_00000-00010_00000_000000008_vis.png\"\n    if \"eval/ckpt\" in gen_image_path:\n        gen_images = split_grid(Image.open(gen_image_path))\n    else:\n        gen_images = [Image.open(gen_image_path)]\n\n    for i, gen_img in enumerate(gen_images):\n        # img_tensor = torch.from_numpy(np.array(gen_img)).unsqueeze(0).permute(0, 3, 1, 2)\n        img_tensor = (pil2tensor(gen_img).unsqueeze(0) * 255).to(torch.uint8)\n        bboxes = faceid.detect(img_tensor)\n        for j, bbox in enumerate(bboxes):\n            face_img = gen_img.crop(bbox)\n            face_img.save(f\"tmp_{j}.png\")\n            print(faceid(real_image_path, face_img))\n        # print(faceid.detect(img_tensor))\n        # break\n        # print(faceid(real_image_path, gen_img))\n\n\n"
  },
  {
    "path": "eval/tools/face_utils/face.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\nimport argparse\n\nimport cv2\nimport torch\nimport torch.nn.functional as F\nfrom PIL import Image\nimport numpy as np\nimport facer\nimport facer.transform\nfrom copy import deepcopy\nimport PIL\n\n\ndef resize_image(image, max_size=1024):\n    height,width,_ = image.shape\n    if width > max_size or height > max_size:\n        if width > height:\n            new_width = max_size\n            new_height = int((height / width) * max_size)\n        else:\n            new_height = max_size\n            new_width = int((width / height) * max_size)\n        image = cv2.resize(image, (new_width, new_height))\n    return image \n\ndef open_and_resize_image(image_file, max_size=1024, return_type='numpy'):\n    if isinstance(image_file, str) or isinstance(image_file, PIL.Image.Image):\n        if isinstance(image_file, str):\n            img = Image.open(image_file)\n        else:\n            img = image_file\n        width, height = img.size\n        if width > height:\n            new_width = max_size\n            new_height = int((height / width) * max_size)\n        else:\n            new_height = max_size\n            new_width = int((width / height) * max_size)\n        img = img.resize((new_width, new_height))\n        if return_type == 'numpy':\n            return np.array(img.convert('RGB'))\n        else:\n            return img\n    elif isinstance(image_file, np.ndarray):\n        height,width,_ = image_file.shape\n        if width > height:\n            new_width = max_size\n            new_height = int((height / width) * max_size)\n        else:\n            new_height = max_size\n            new_width = int((width / height) * max_size)\n        img = cv2.resize(image_file, (new_width, new_height))\n        assert return_type == 'numpy'\n        return img\n    else:\n        raise TypeError(\"Do not support this img type\")\n\n\n@torch.no_grad()\ndef loose_warp_face(input_image, face_detector, face_target_shape=(512, 512), scale=1.3, face_parser=None, device=None, croped_face_scale=3, bg_value = 0, croped_face_y_offset=0.0):\n    \"\"\" Get the tight/loose warp of the face in the image, in which only one face is of concern.\n\n    Args:\n        input_image: Image path, or PIL.Image.Image, or np.ndarray (dtype=np.uint8).\n        face_detector: a facer.face_detector, for face detection.\n        face_target_shape: Output resolution.\n        scale: Scale of the output image w.r.t. the face it contains.\n\n    Returns:\n        PIL.Image.Image, single warped face.\n    \"\"\"\n    _normalized_face_target_pts = torch.tensor([\n    [38.2946, 51.6963],\n    [73.5318, 51.5014],\n    [56.0252, 71.7366],\n    [41.5493, 92.3655],\n    [70.729904, 92.2041]]) / 112.0\n    \n    target_pts = ((_normalized_face_target_pts -\n                   torch.tensor([0.5, 0.5])) / scale\n                  + torch.tensor([0.5, 0.5]))\n    if face_detector is not None:\n        device = next(face_detector.parameters()).device\n\n    if isinstance(input_image, str):\n        # image_tensor_hwc = facer.read_hwc(input_image)\n        np_img = open_and_resize_image(input_image)[:,:,:3]      # Downsample high-res images to avoid OOM.\n        img_height, img_width = np_img.shape[:2]\n        image_tensor_hwc = torch.from_numpy(np_img)\n    elif isinstance(input_image, Image.Image):\n        image_tensor_hwc = torch.from_numpy(np.array(input_image)[:,:,:3])\n        img_height, img_width = image_tensor_hwc.shape[:2]\n        assert image_tensor_hwc.dtype == torch.uint8\n    else:\n        assert isinstance(input_image, np.ndarray), 'Type %s of input_image is unsupported!' % type(input_image)\n        assert input_image.dtype == np.uint8, 'dtype %s of input np.ndarray is unsupported!' % input_image.dtype\n        input_image = cv2.cvtColor(input_image, cv2.COLOR_RGB2BGR)[:,:,:3]\n        input_image = resize_image(input_image)\n        image_tensor_hwc = torch.from_numpy(input_image)\n        img_height, img_width = image_tensor_hwc.shape[:2]\n    \n    image_pt_bchw_255 = facer.hwc2bchw(image_tensor_hwc).to(device)\n\n    res = {'cropped_face_masked': None, 'cropped_face': None, 'cropped_img': None, 'cropped_face_mask': None, 'align_face': None}\n\n    if face_detector is not None:\n        try:\n            face_data = face_detector(image_pt_bchw_255)\n        except:\n            import pdb;pdb.set_trace()\n        \n        if len(face_data) == 0:\n            return res\n        \n        if face_parser is not None:\n            with torch.inference_mode():\n                faces = face_parser(image_pt_bchw_255, face_data)\n            seg_logits = faces['seg']['logits']\n            seg_probs = seg_logits.softmax(dim=1)\n            seg_probs = seg_probs.argmax(dim=1).unsqueeze(1)[:1]\n\n        face_rects = face_data['rects'][:1]\n        face_rects = face_data['rects'][:1]\n        x1,y1,x2,y2 = face_rects[0][:4]\n        x1 = (int(x1.item()))\n        y1 = (int(y1.item()))\n        x2 = (int(x2.item()))\n        y2 = (int(y2.item()))\n        face_width = x2-x1\n        face_height = y2-y1\n        center_x = int(0.5*(x1+x2))\n        center_y = int(0.5*(y1+y2)) + croped_face_y_offset * face_height\n        croped_face_width = face_width*croped_face_scale\n        croped_face_height = face_height*croped_face_scale\n        \n        x1 = max(int(center_x-0.5*croped_face_width),0)\n        x2 = min(int(center_x+0.5*croped_face_width), img_width-1)\n        y1 = max(int(center_y-0.5*croped_face_height),0)\n        y2 = min(int(center_y+0.5*croped_face_height), img_height-1)\n        croped_face_height = y2-y1\n        croped_face_width = x2-x1\n        center_x = int(0.5*(x1+x2))\n        center_y = int(0.5*(y1+y2))\n        croped_face_len = min(croped_face_height, croped_face_width)\n        x1 = int(center_x - 0.5*croped_face_len)\n        y1 = int(center_y - 0.5*croped_face_len)\n        x2 = x1+croped_face_len\n        y2 = y1+croped_face_len\n        croped_image_pt_bchw_255 = image_pt_bchw_255[:, :, y1:y2, x1:x2]\n        face_points = face_data['points'][:1]\n        batch_inds = face_data['image_ids'][:1]\n        \n        matrix_align = facer.transform.get_face_align_matrix(\n            face_points, face_target_shape, \n            target_pts=(target_pts * torch.tensor(face_target_shape)))\n        \n        grid = facer.transform.make_tanh_warp_grid(\n            matrix_align, 0.0, face_target_shape, image_pt_bchw_255.shape[2:],)\n        image = F.grid_sample(\n            image_pt_bchw_255.float()[batch_inds], \n            grid, 'bilinear', align_corners=False)\n        image_align_raw = deepcopy(image)\n        image_align_raw = facer.bchw2hwc(image_align_raw).to(torch.uint8).cpu().numpy()\n        image_align_raw = Image.fromarray(image_align_raw)\n        image_croped = facer.bchw2hwc(croped_image_pt_bchw_255).to(torch.uint8).cpu().numpy()\n        image_croped = Image.fromarray(image_croped)\n        if face_parser is not None:\n            image_no_mask = deepcopy(image)\n            new_size = list(seg_probs.shape)\n            new_size[1] = image.shape[1]\n            seg_probs = seg_probs.expand(new_size)\n            assert seg_probs.shape[0] == 1 and image.shape[0] == 1, 'mask shape {}, != image shape {}'.format(seg_probs.shape, image.shape)\n            mask_img = F.grid_sample(seg_probs.float(), grid, 'bilinear', align_corners=False)\n            image[mask_img == 0] = bg_value\n            mask_img[mask_img!=0] = 1\n            assert mask_img.shape[0] == 1\n        else:\n            image_no_mask = image\n            mask_img = None\n    else:\n        image = image_pt_bchw_255\n        image_no_mask = image_pt_bchw_255\n        image_align_raw = None\n        image_croped = None\n\n    image = facer.bchw2hwc(image).to(torch.uint8).cpu().numpy()\n    image_no_mask = facer.bchw2hwc(image_no_mask).to(torch.uint8).cpu().numpy()\n    \n    res.update({'cropped_face_masked': Image.fromarray(image), 'cropped_face': Image.fromarray(image_no_mask), 'cropped_img':image_croped, 'cropped_face_mask': mask_img, 'align_face': image_align_raw})\n    return res\n\ndef tight_warp_face(input_image, face_detector, face_parser=None, device=None):\n    return loose_warp_face(input_image, face_detector, \n        face_target_shape=(112, 112), scale=1, face_parser=face_parser, device=device)\n"
  },
  {
    "path": "eval/tools/face_utils/face_recg.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom torch.nn import Linear, Conv2d, BatchNorm1d, BatchNorm2d, PReLU, ReLU, Sigmoid, Dropout2d, Dropout, AvgPool2d, MaxPool2d, AdaptiveAvgPool2d, Sequential, Module, Parameter\nimport torch.nn.functional as F\nimport torch\nfrom collections import namedtuple\nimport math\nimport pdb\n\nclass Flatten(Module):\n    def forward(self, input):\n        return input.view(input.size(0), -1)\n\ndef l2_norm(input,axis=1):\n    norm = torch.norm(input,2,axis,True)\n    output = torch.div(input, norm)\n    return output\n\nclass SEModule(Module):\n    def __init__(self, channels, reduction):\n        super(SEModule, self).__init__()\n        self.avg_pool = AdaptiveAvgPool2d(1)\n        self.fc1 = Conv2d(\n            channels, channels // reduction, kernel_size=1, padding=0 ,bias=False)\n        self.relu = ReLU(inplace=True)\n        self.fc2 = Conv2d(\n            channels // reduction, channels, kernel_size=1, padding=0 ,bias=False)\n        self.sigmoid = Sigmoid()\n\n    def forward(self, x):\n        module_input = x\n        x = self.avg_pool(x)\n        x = self.fc1(x)\n        x = self.relu(x)\n        x = self.fc2(x)\n        x = self.sigmoid(x)\n        return module_input * x\n\nclass bottleneck_IR(Module):\n    def __init__(self, in_channel, depth, stride):\n        super(bottleneck_IR, self).__init__()\n        if in_channel == depth:\n            self.shortcut_layer = MaxPool2d(1, stride)\n        else:\n            self.shortcut_layer = Sequential(\n                Conv2d(in_channel, depth, (1, 1), stride ,bias=False), BatchNorm2d(depth))\n        self.res_layer = Sequential(\n            BatchNorm2d(in_channel),\n            Conv2d(in_channel, depth, (3, 3), (1, 1), 1 ,bias=False), PReLU(depth),\n            Conv2d(depth, depth, (3, 3), stride, 1 ,bias=False), BatchNorm2d(depth))\n\n    def forward(self, x):\n        shortcut = self.shortcut_layer(x)\n        res = self.res_layer(x)\n        return res + shortcut\n\nclass bottleneck_IR_SE(Module):\n    def __init__(self, in_channel, depth, stride):\n        super(bottleneck_IR_SE, self).__init__()\n        if in_channel == depth:\n            self.shortcut_layer = MaxPool2d(1, stride)\n        else:\n            self.shortcut_layer = Sequential(\n                Conv2d(in_channel, depth, (1, 1), stride ,bias=False), \n                BatchNorm2d(depth))\n        self.res_layer = Sequential(\n            BatchNorm2d(in_channel),\n            Conv2d(in_channel, depth, (3,3), (1,1),1 ,bias=False),\n            PReLU(depth),\n            Conv2d(depth, depth, (3,3), stride, 1 ,bias=False),\n            BatchNorm2d(depth),\n            SEModule(depth,16)\n            )\n    def forward(self,x):\n        shortcut = self.shortcut_layer(x)\n        res = self.res_layer(x)\n        return res + shortcut\n\nclass Bottleneck(namedtuple('Block', ['in_channel', 'depth', 'stride'])):\n    '''A named tuple describing a ResNet block.'''\n    \ndef get_block(in_channel, depth, num_units, stride = 2):\n    return [Bottleneck(in_channel, depth, stride)] + [Bottleneck(depth, depth, 1) for i in range(num_units-1)]\n\ndef get_blocks(num_layers):\n    if num_layers == 50:\n        blocks = [\n            get_block(in_channel=64, depth=64, num_units = 3),\n            get_block(in_channel=64, depth=128, num_units=4),\n            get_block(in_channel=128, depth=256, num_units=14),\n            get_block(in_channel=256, depth=512, num_units=3)\n        ]\n    elif num_layers == 100:\n        blocks = [\n            get_block(in_channel=64, depth=64, num_units=3),\n            get_block(in_channel=64, depth=128, num_units=13),\n            get_block(in_channel=128, depth=256, num_units=30),\n            get_block(in_channel=256, depth=512, num_units=3)\n        ]\n    elif num_layers == 152:\n        blocks = [\n            get_block(in_channel=64, depth=64, num_units=3),\n            get_block(in_channel=64, depth=128, num_units=8),\n            get_block(in_channel=128, depth=256, num_units=36),\n            get_block(in_channel=256, depth=512, num_units=3)\n        ]\n    return blocks\n\nclass Backbone(Module):\n    def __init__(self, num_layers, drop_ratio, mode='ir'):\n        super(Backbone, self).__init__()\n        assert num_layers in [50, 100, 152], 'num_layers should be 50,100, or 152'\n        assert mode in ['ir', 'ir_se'], 'mode should be ir or ir_se'\n        blocks = get_blocks(num_layers)\n        if mode == 'ir':\n            unit_module = bottleneck_IR\n        elif mode == 'ir_se':\n            unit_module = bottleneck_IR_SE\n        self.input_layer = Sequential(Conv2d(3, 64, (3, 3), 1, 1 ,bias=False), \n                                      BatchNorm2d(64), \n                                      PReLU(64))\n        self.output_layer = Sequential(BatchNorm2d(512), \n                                       Dropout(drop_ratio),\n                                       Flatten(),\n                                       Linear(512 * 7 * 7, 512),\n                                       BatchNorm1d(512))\n        modules = []\n        for block in blocks:\n            for bottleneck in block:\n                modules.append(\n                    unit_module(bottleneck.in_channel,\n                                bottleneck.depth,\n                                bottleneck.stride))\n        self.body = Sequential(*modules)\n    \n    def forward(self,x):\n        x = self.input_layer(x)\n        x = self.body(x)\n        x = self.output_layer(x)\n        return l2_norm(x)\n"
  },
  {
    "path": "eval/tools/florence_sam.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\nimport sys\nimport torch\nimport cv2\nfrom PIL import Image\nfrom eval.grounded_sam.grounded_sam2_florence2_autolabel_pipeline import FlorenceSAM\n\nclass ObjectDetector:\n    def __init__(self, device):\n        self.device = torch.device(device)\n        self.detector = FlorenceSAM(device)\n    \n    def get_instances(self, gen_image, label, min_size=64):\n        _, instance_result_dict = \\\n            self.detector.od_grounding_and_segmentation(\n                image=gen_image, text_input=label,\n            )\n        instances = instance_result_dict[\"instance_images\"]\n        \n        filtered_instances = []\n        for img in instances:\n            width, height = img.shape[:2]\n            if width * height < min_size * min_size or min(width, height) < min_size // 4:\n                continue\n            \n            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n            img = Image.fromarray(img)\n            filtered_instances.append(img)\n\n        return filtered_instances\n    \n    def get_multiple_instances(self, gen_image, label, min_size=64):\n            # self.detector.phrase_grounding_and_segmentation(\n        _, instance_result_dict = \\\n            self.detector.od_grounding_and_segmentation(\n                image=gen_image, text_input=label,\n            )\n        \n        return instance_result_dict\n\n\nif __name__ == \"__main__\":\n    # online demo: https://dun.163.com/trial/face/compare\n    from glob import glob\n    from tqdm import tqdm\n    from src.train.data.data_utils import split_grid, pad_to_square\n    from eval.idip.dino import DINOScore\n\n    detector = ObjectDetector(\"cuda\")\n    dino_model = DINOScore(\"cuda\")\n\n    gen_image = Image.open(\"assets/tests/20250320-151038.jpeg\").convert(\"RGB\")\n    label = \"two people\"\n\n    save_dir = f\"tmp\"\n    os.makedirs(save_dir, exist_ok=True)\n\n    # for i, img in enumerate(split_grid(gen_image)):\n    for i, img in enumerate([gen_image]):\n        found_ips = detector.get_instances(img, label, min_size=img.size[0]//20)[:3]\n        found_ips = [pad_to_square(x) for x in found_ips]\n        for j, ip in enumerate(found_ips):\n            # score = dino_model(real_image, ip)\n            score = 1\n            pad_to_square(ip).save(f\"{save_dir}/{label}_{i}_{j}_{score}.png\")\n            \n        \n\n            \n\n\n"
  },
  {
    "path": "eval/tools/idip_aes_score.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom tqdm import tqdm\nfrom glob import glob\nimport argparse\nimport math\nimport random\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.distributed as dist\nfrom src.utils.data_utils import get_rank_and_worldsize, json_dump, json_load\nfrom aesthetic_predictor_v2_5 import convert_v2_5_from_siglip\nimport shutil\nfrom pathlib import Path\nimport os\nimport sys\nimport time\n\n\ndef parse_args():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--input_dir\", type=str, default=\"../examples\")\n    parser.add_argument(\"--test_list_name\", type=str, default=\"base_test_list_200\")\n    args = parser.parse_args()\n    \n    return args\n\ndef main():\n    args = parse_args()\n    print(args)\n    \n    local_rank, global_rank, world_size = get_rank_and_worldsize()\n    print(f\"local_rank={local_rank}, global_rank={global_rank}, world_size={world_size}\")\n    is_local_main_process = local_rank == 0\n    is_main_process = global_rank == 0\n    torch.cuda.set_device(local_rank)\n    \n    dtype = torch.bfloat16\n    device = \"cuda\"\n    \n    run_name = time.strftime(\"%m%d_$H\")\n    model, preprocessor = convert_v2_5_from_siglip(\n        low_cpu_mem_usage=True,\n        trust_remote_code=True,\n    )\n    model = model.to(torch.bfloat16).to(f\"cuda:{local_rank}\")\n    \n    test_list = json_load(f\"eval/tools/{args.test_list_name}.json\", 'utf-8')\n    images = list(glob(f\"{args.input_dir}/*.png\"))\n    \n    num_samples = min(len(test_list), len(images))\n    num_ranks = world_size\n    assert local_rank == global_rank\n    if world_size > 1:\n        num_per_rank = math.ceil(num_samples / num_ranks)\n        test_list_indices = list(range(num_samples))\n        random.seed(0)\n        random.shuffle(test_list_indices)\n        local_test_list_indices = test_list_indices[local_rank*num_per_rank:(local_rank+1)*num_per_rank]\n        os.environ['CUDA_VISIBLE_DEVICES'] = str(local_rank % 8)\n        print(f\"[worker {local_rank}] got {len(local_test_list_indices)} local samples\")\n\n    run_name = time.strftime(\"%Y%m%d-%H\")\n    temp_dir = os.path.join(args.input_dir, f\"eval_temp_{run_name}\")\n\n    if is_main_process:\n        if os.path.exists(temp_dir):\n            shutil.rmtree(temp_dir)\n        os.makedirs(temp_dir)\n\n    score_json = {}\n    with torch.no_grad():\n        for i in tqdm(local_test_list_indices):\n            test_sample = test_list[i]\n            image_path = list(filter(lambda x: x.split(\"/\")[-1].split(\"_\")[0] == str(i), images))[0]\n            \n            SAMPLE_IMAGE_PATH = Path(image_path)\n            image = Image.open(SAMPLE_IMAGE_PATH).convert(\"RGB\")\n            pixel_values = (\n                preprocessor(images=image, return_tensors=\"pt\")\n                .pixel_values.to(torch.bfloat16)\n                .to(f\"cuda:{local_rank}\")\n            )\n\n            with torch.inference_mode():\n                score = model(pixel_values).logits.squeeze().float().cpu().numpy()\n            \n            score_json[i] = float(score)*10\n\n    json_dump(score_json, f\"{temp_dir}/scores_{global_rank}.json\", \"utf-8\")\n\n    if is_main_process:\n        # 等待所有进程完成文件写入\n        all_files_written = False\n        max_retries = 10\n        retry_count = 0\n        while not all_files_written and retry_count < max_retries:\n            try:\n                if len(glob(f\"{temp_dir}/scores_*.json\")) == world_size:\n                    all_files_written = True\n                    time.sleep(5)  # 确保文件写入完成\n                else:\n                    time.sleep(5)\n                    retry_count += 1\n            except Exception as e:\n                print(f\"Error checking files: {e}\")\n                time.sleep(5)\n                retry_count += 1\n\n        if not all_files_written:\n            print(\"Not all score files were written within the timeout.\")\n            return\n\n        merged_json = {}\n        prompt_scores = {}\n        scores = []\n        for rank_path in glob(f\"{temp_dir}/scores_*.json\"):\n            try:\n                rank_json = json_load(rank_path, \"utf-8\")\n                merged_json.update(rank_json)\n                for i in rank_json:\n                    score = rank_json[i]\n                    prompt_scores[i] = score\n                    scores.append(score)\n            except Exception as e:\n                print(f\"Error loading file {rank_path}: {e}\")\n\n        json_dump(merged_json, f\"{args.input_dir}/aes_scores_{run_name}.json\", \"utf-8\")\n        if scores:\n            dpg_score = np.mean(scores)\n            lines_to_write = [\n                f\"AES Score: {dpg_score:.2f}\\n\"\n            ]\n            print(lines_to_write[0])\n            for i, score in prompt_scores.items():\n                lines_to_write.append(f\"{i}: {score:.2f}\\n\")\n\n            with open(f\"{args.input_dir}/aes_scores_{run_name}.txt\", \"w\") as f:\n                f.writelines(lines_to_write)\n        else:\n            print(\"No scores were collected.\")\n\n        shutil.rmtree(temp_dir)\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "eval/tools/idip_dpg_score.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\nimport sys\nimport time\nfrom tqdm import tqdm\nfrom glob import glob\nimport argparse\nimport math\nimport random\nimport numpy as np\nfrom PIL import Image\n\nimport torch\nimport torch.distributed as dist\n\nfrom src.flux.generate import seed_everything\nfrom src.utils.data_utils import get_train_config, get_rank_and_worldsize\nfrom src.utils.data_utils import pad_to_square, pad_to_target, json_dump, json_load, split_grid, image_grid\nimport shutil\nfrom eval.tools.dpg_score import DPGScore\n\n\ndef parse_args():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--input_dir\", type=str, default=\"../examples\")\n    parser.add_argument(\"--test_list_name\", type=str, default=\"base_test_list_200\")\n    args = parser.parse_args()\n    \n    return args\n\ndef main():\n    args = parse_args()\n    print(args)\n    \n    local_rank, global_rank, world_size = get_rank_and_worldsize()\n    print(f\"local_rank={local_rank}, global_rank={global_rank}, world_size={world_size}\")\n    is_local_main_process = local_rank == 0\n    is_main_process = global_rank == 0\n    torch.cuda.set_device(local_rank)\n    \n    dtype = torch.bfloat16\n    device = \"cuda\"\n    \n    run_name = time.strftime(\"%m%d_$H\")\n    dpg_score_model = DPGScore(f\"cuda:{local_rank}\")\n    \n    test_list = json_load(f\"eval/tools/{args.test_list_name}.json\", 'utf-8')\n    dsg_list = json_load(f\"eval/tools/{args.test_list_name}_DSG.json\", 'utf-8')\n    images = list(glob(f\"{args.input_dir}/*.png\"))\n    print(args.input_dir)\n    print(len(test_list), len(dsg_list), len(images))\n    assert len(test_list) == len(dsg_list)\n    \n    num_samples = min(len(test_list), len(images))\n    num_ranks = world_size\n    assert local_rank == global_rank\n    if world_size > 1:\n        num_per_rank = math.ceil(num_samples / num_ranks)\n        test_list_indices = list(range(num_samples))\n        random.seed(0)\n        random.shuffle(test_list_indices)\n        local_test_list_indices = test_list_indices[local_rank*num_per_rank:(local_rank+1)*num_per_rank]\n        os.environ['CUDA_VISIBLE_DEVICES'] = str(local_rank % 8)\n        print(f\"[worker {local_rank}] got {len(local_test_list_indices)} local samples\")\n\n    run_name = time.strftime(\"%Y%m%d-%H\")\n    temp_dir = os.path.join(args.input_dir, f\"eval_temp_{run_name}\")\n\n    if is_main_process:\n        if os.path.exists(temp_dir):\n            shutil.rmtree(temp_dir)\n        os.makedirs(temp_dir)\n\n    rank_json = {}\n    with torch.no_grad():\n        for i in tqdm(local_test_list_indices):\n            test_sample = test_list[i]\n            q_dict = dsg_list[i]\n            assert q_dict[\"prompt\"] == test_sample[\"prompt\"]\n            image_path = list(filter(lambda x: x.split(\"/\")[-1].split(\"_\")[0] == str(i), images))[0]\n            \n            rank_json[i] = []\n            for j, img in enumerate(split_grid(Image.open(image_path))):\n                rank_json[i].append({})\n                result = dpg_score_model(img, q_dict)\n                for q_id, question in result[\"qid2question\"].items():\n                    answer = result[\"qid2answer\"][q_id]\n                    rank_json[i][j][question] = answer\n                rank_json[i][j]['average_score_with_dependency'] = result['average_score_with_dependency']\n                rank_json[i][j]['average_score_without_dependency'] = result['average_score_without_dependency']\n\n    json_dump(rank_json, f\"{temp_dir}/scores_{global_rank}.json\", \"utf-8\")\n\n    if is_main_process:\n        while len(glob(f\"{temp_dir}/scores_*.json\")) < world_size:\n            time.sleep(5)\n        time.sleep(5) # wait for the file writting to be finished\n        merged_json = {}\n        prompt_scores = {}\n        scores = []\n        for rank_path in glob(f\"{temp_dir}/scores_*.json\"):\n            rank_json = json_load(rank_path, \"utf-8\")\n            merged_json.update(rank_json)\n            for i in rank_json:\n                score_list = [x['average_score_with_dependency'] for x in rank_json[i]]\n                prompt_scores[i] = np.mean(score_list)\n                scores += score_list\n\n        json_dump(merged_json, f\"{args.input_dir}/dpg_scores_{run_name}.json\", \"utf-8\")\n        dpg_score = np.mean(scores)\n        lines_to_write = [\n            f\"DPG Score: {dpg_score:.2f}\\n\"\n        ]\n        print(lines_to_write[0])\n        for i, score in prompt_scores.items():\n            lines_to_write.append(f\"{i}: {score:.2f}\\n\")\n\n        with open(f\"{args.input_dir}/dpg_scores_{run_name}.txt\", \"w\") as f:\n            f.writelines(lines_to_write)\n\n        shutil.rmtree(temp_dir)\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "eval/tools/idip_face_score.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\nimport sys\nimport time\nfrom tqdm import tqdm\nfrom glob import glob\nimport argparse\nimport math\nimport random\nimport numpy as np\nfrom PIL import Image\nfrom collections import defaultdict\n\nimport torch\nimport torch.distributed as dist\n\nfrom src.flux.generate import seed_everything\nfrom src.utils.data_utils import get_train_config, get_rank_and_worldsize\nfrom src.utils.data_utils import pad_to_square, pad_to_target, json_dump, json_load, split_grid, image_grid, pil2tensor\nimport shutil\nfrom eval.tools.face_id import FaceID\n\n\ndef parse_args():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--input_dir\", type=str, default=\"../examples\")\n    parser.add_argument(\"--test_list_name\", type=str, default=\"base_test_list_200\")\n    args = parser.parse_args()\n    \n    return args\n\ndef main():\n    args = parse_args()\n    print(args)\n    \n    local_rank, global_rank, world_size = get_rank_and_worldsize()\n    print(f\"local_rank={local_rank}, global_rank={global_rank}, world_size={world_size}\")\n    is_local_main_process = local_rank == 0\n    is_main_process = global_rank == 0\n    torch.cuda.set_device(local_rank)\n    \n    dtype = torch.bfloat16\n    device = \"cuda\"\n    \n    run_name = time.strftime(\"%m%d_$H\")\n    face_score_model = FaceID(device)\n    \n    test_list = json_load(f\"eval/tools/{args.test_list_name}.json\", 'utf-8')\n    images = list(glob(f\"{args.input_dir}/*.png\"))\n    print(len(test_list), len(images))\n    assert len(test_list) == len(images)\n    \n    num_samples = len(test_list)\n    num_ranks = world_size\n    assert local_rank == global_rank\n    if world_size > 1:\n        num_per_rank = math.ceil(num_samples / num_ranks)\n        test_list_indices = list(range(num_samples))\n        random.seed(0)\n        random.shuffle(test_list_indices)\n        local_test_list_indices = test_list_indices[local_rank*num_per_rank:(local_rank+1)*num_per_rank]\n        os.environ['CUDA_VISIBLE_DEVICES'] = str(local_rank % 8)\n        print(f\"[worker {local_rank}] got {len(local_test_list_indices)} local samples\")\n\n    run_name = time.strftime(\"%Y%m%d-%H\")\n    temp_dir = os.path.join(args.input_dir, f\"eval_id_temp_{run_name}\")\n\n    if is_main_process:\n        if os.path.exists(temp_dir):\n            shutil.rmtree(temp_dir)\n        os.makedirs(temp_dir)\n\n    rank_json = {}\n    with torch.no_grad():\n        for i in tqdm(local_test_list_indices):\n            test_sample = test_list[i]\n            real_paths, real_faces, real_names = [], [], []\n            for x in test_sample[\"modulation\"][0][\"src_inputs\"]:\n                img_path = x[\"image_path\"]\n                name = \"_\".join(img_path.split(\"/\")[-2:])\n                \n                if name.startswith(\"human\"):\n                    real_paths.append(img_path)\n                    try:\n                        real_faces.append(Image.open(img_path).convert(\"RGB\"))\n                        real_names.append(name)\n                    except Exception as e:\n                        print(f\"Failed to open image {img_path}, error message: {e}\")\n\n            gen_img_path = list(filter(lambda x: x.split(\"/\")[-1].split(\"_\")[0] == str(i), images))[0]\n            rank_json[i] = []\n            try:\n                for j, gen_img in enumerate(split_grid(Image.open(gen_img_path))):\n                    rank_json[i].append({})\n                    if len(real_names) > 0:\n                        gen_bboxes = face_score_model.detect(\n                            (pil2tensor(gen_img).unsqueeze(0) * 255).to(torch.uint8)\n                        )\n                        gen_faces = [gen_img.crop(bbox) for bbox in gen_bboxes]\n                        for k, (real_name, real_face) in enumerate(zip(real_names, real_faces)):\n                            if len(gen_faces) > 0:\n                                score = max([face_score_model(real_face, x) for x in gen_faces])\n                            else:\n                                score = 0\n                            rank_json[i][j][real_name] = score\n            except Exception as e:\n                print(f\"Failed to process image {gen_img_path}, error message: {e}\")\n                \n    json_dump(rank_json, f\"{temp_dir}/scores_{global_rank}.json\", \"utf-8\")\n\n    if is_main_process:\n        while len(glob(f\"{temp_dir}/scores_*.json\")) < world_size:\n            time.sleep(5)\n        time.sleep(5) # wait for the file writting to be finished\n        merged_json = {}\n        id_scores = defaultdict(list)\n        all_scores = []\n        for rank_path in glob(f\"{temp_dir}/scores_*.json\"):\n            rank_json = json_load(rank_path, \"utf-8\")\n            merged_json.update(rank_json)\n\n        for i, grid_json in merged_json.items():\n            for img_json in grid_json:\n                for id_name, id_score in img_json.items():\n                    id_scores[id_name].append(id_score)\n        \n        for id_name in id_scores:\n            all_scores += id_scores[id_name]\n            id_scores[id_name] = np.mean(id_scores[id_name])\n            print(id_name, id_scores[id_name])\n\n        json_dump(merged_json, f\"{args.input_dir}/id_scores_{run_name}.json\", \"utf-8\")\n        final_id_score = np.mean(all_scores)\n        lines_to_write = [\n            f\"ID Score: {final_id_score:.2f}\\n\"\n        ]\n        print(lines_to_write[0])\n        for id_name, score in id_scores.items():\n            lines_to_write.append(f\"{id_name}: {score:.2f}\\n\")\n\n        with open(f\"{args.input_dir}/id_scores_{run_name}.txt\", \"w\") as f:\n            f.writelines(lines_to_write)\n\n        shutil.rmtree(temp_dir)\n\nif __name__ == \"__main__\":\n    main()"
  },
  {
    "path": "eval/tools/idip_gen_split_idip.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\nimport sys\nimport time\nfrom tqdm import tqdm\nimport argparse\nimport math\nimport random\n\nimport torch\nimport torch.distributed as dist\n\nfrom src.flux.generate import generate, generate_from_test_sample, seed_everything\nfrom src.flux.pipeline_tools import CustomFluxPipeline, load_modulation_adapter, load_dit_lora\nfrom src.utils.data_utils import get_train_config, get_rank_and_worldsize\nfrom src.utils.data_utils import pad_to_square, pad_to_target, json_dump, json_load, image_grid\n\nimport shutil\n\ndef parse_args():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--config_name\", type=str, default=\"\")\n    parser.add_argument(\"--model_path\", type=str, default=\"\")\n    parser.add_argument(\"--target_size\", type=int, default=512)\n    parser.add_argument(\"--condition_size\", type=int, default=128)\n    parser.add_argument(\"--save_name\", type=str, default=\"../examples\")\n    parser.add_argument(\"--test_list_name\", type=str, default=\"base_test_list_200\")\n    args = parser.parse_args()\n    return args\n\ndef main():\n    args = parse_args()\n    print(args)\n    \n    local_rank, global_rank, world_size = get_rank_and_worldsize()\n    print(f\"local_rank={local_rank}, global_rank={global_rank}, world_size={world_size}\")\n    is_local_main_process = local_rank == 0\n    is_main_process = global_rank == 0\n    torch.cuda.set_device(local_rank)\n    \n    dtype = torch.bfloat16\n    device = \"cuda\"\n    config_path = args.config_name\n\n    config = get_train_config(config_path)\n    config[\"train\"][\"dataset\"][\"val_condition_size\"] = args.condition_size\n    config[\"train\"][\"dataset\"][\"val_target_size\"] = args.target_size\n    config[\"model\"][\"layer_control\"] = False\n            \n    run_name = time.strftime(\"%m%d\")\n    num_images = 4\n    ckpt_root = args.model_path\n    save_dir = args.save_name\n\n    model = CustomFluxPipeline(config, device, ckpt_root=ckpt_root, torch_dtype=dtype)\n    model.pipe.set_progress_bar_config(leave=False)\n    model.config = config\n    if \"py\" in args.test_list_name:\n        test_list = globals()[args.test_list_name.split(\"_py\")[0]]\n        test_list = test_list[5:11] + test_list[17:23] # TODO only for debug\n    else:\n        test_list = json_load(f\"eval/tools/{args.test_list_name}.json\", 'utf-8')\n    \n    num_samples = len(test_list)\n    num_ranks = world_size\n    assert local_rank == global_rank\n    if world_size > 1:\n        num_per_rank = math.ceil(num_samples / num_ranks)\n        test_list_indices = list(range(num_samples))\n        random.seed(0)\n        random.shuffle(test_list_indices)\n        local_test_list_indices = test_list_indices[local_rank*num_per_rank:(local_rank+1)*num_per_rank]\n        print(f\"[worker {local_rank}] got {len(local_test_list_indices)} local samples\")\n\n\n    model.clear_modulation_adapters()\n    model.pipe.transformer.unload_lora()\n\n    modulation_adapter = load_modulation_adapter(model, config, dtype, device, f\"{ckpt_root}/modulation_adapter\", is_training=False)\n    model.add_modulation_adapter(modulation_adapter)\n    if config[\"model\"][\"use_dit_lora\"]:\n        load_dit_lora(model, model.pipe, config, dtype, device, f\"{ckpt_root}\", is_training=False)\n\n    os.makedirs(save_dir, exist_ok=True)\n\n    # 复制配置文件到 save_dir\n    import shutil\n    config_dest_path = os.path.join(save_dir, os.path.basename(config_path))\n    shutil.copy(config_path, config_dest_path)\n    print(f\"已复制配置文件到 {config_dest_path}\")\n\n    for i in tqdm(local_test_list_indices):\n        test_sample = test_list[i]\n        prompt_name = test_sample['prompt'][:40].replace(\" \",\"_\")\n        save_path = f\"{save_dir}/{i}_{prompt_name}.png\"\n        if os.path.exists(save_path):\n            print(f\"文件 {save_path} 已存在，跳过保存\")\n            continue\n        image = generate_from_test_sample(test_sample, model.pipe, model.config, num_images=num_images, store_attn_map=False, use_idip=True)\n        if isinstance(image, list):\n            image = image_grid(image, len(image) // 2, 2)\n        # print(f\"{test_sample['prompt']}\")\n        image.save(save_path)\n        print(f\"save results {i} to: {save_path}\")\n        del image\n    del model\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "eval/tools/idip_sam-dino_score.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\nimport sys\nimport time\nfrom tqdm import tqdm\nfrom glob import glob\nimport argparse\nimport math\nimport random\nimport numpy as np\nfrom PIL import Image\nfrom collections import defaultdict\n\nimport torch\nimport torch.distributed as dist\n\nfrom src.flux.generate import seed_everything\nfrom src.utils.data_utils import get_train_config, get_rank_and_worldsize\nfrom src.utils.data_utils import pad_to_square, pad_to_target, json_dump, json_load, split_grid, image_grid, pil2tensor\nimport shutil\nfrom eval.tools.florence_sam import ObjectDetector\nfrom eval.tools.dino import DINOScore\n\ndef parse_args():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--input_dir\", type=str, default=\"../examples\")\n    parser.add_argument(\"--test_list_name\", type=str, default=\"base_test_list_200\")\n    args = parser.parse_args()\n    return args\n\ndef main():\n    args = parse_args()\n    print(args)\n    \n    local_rank, global_rank, world_size = get_rank_and_worldsize()\n    print(f\"local_rank={local_rank}, global_rank={global_rank}, world_size={world_size}\")\n    is_local_main_process = local_rank == 0\n    is_main_process = global_rank == 0\n    torch.cuda.set_device(local_rank)\n    \n    dtype = torch.bfloat16\n    device = \"cuda\"\n    \n    run_name = time.strftime(\"%m%d_$H\")\n    detector_model = ObjectDetector(device)\n    dino_model = DINOScore(device)\n    \n    test_list = json_load(f\"eval/tools/{args.test_list_name}.json\", 'utf-8')\n    images = list(glob(f\"{args.input_dir}/*.png\"))\n    print(len(test_list), len(images))\n    assert len(test_list) == len(images)\n    \n    num_samples = len(test_list)\n    num_ranks = world_size\n    assert local_rank == global_rank\n    if world_size > 1:\n        num_per_rank = math.ceil(num_samples / num_ranks)\n        test_list_indices = list(range(num_samples))\n        random.seed(0)\n        random.shuffle(test_list_indices)\n        local_test_list_indices = test_list_indices[local_rank*num_per_rank:(local_rank+1)*num_per_rank]\n        \n        os.environ['CUDA_VISIBLE_DEVICES'] = str(local_rank % 8)\n        print(f\"[worker {local_rank}] got {len(local_test_list_indices)} local samples\")\n\n    run_name = time.strftime(\"%Y%m%d-%H\")\n    temp_dir = os.path.join(args.input_dir, f\"eval_ip_temp_{run_name}\")\n\n    if is_main_process:\n        if os.path.exists(temp_dir):\n            shutil.rmtree(temp_dir)\n        os.makedirs(temp_dir)\n\n    rank_json = {}\n    with torch.no_grad():\n        for i in tqdm(local_test_list_indices):\n            test_sample = test_list[i]\n            real_paths, real_ips, real_names, real_labels = [], [], [], []\n            for j, x in enumerate(test_sample[\"modulation\"][0][\"src_inputs\"]):\n                img_path = x[\"image_path\"]\n                name = \"_\".join(img_path.split(\"/\")[-2:])\n                label = test_sample[\"modulation\"][0][\"use_words\"][j][1]\n                \n                if not name.startswith(\"human\"):\n                    real_paths.append(img_path)\n                    real_ips.append(Image.open(img_path).convert(\"RGB\"))\n                    real_names.append(name)\n                    real_labels.append(label)\n\n            gen_img_path = list(filter(lambda x: x.split(\"/\")[-1].split(\"_\")[0] == str(i), images))[0]\n            rank_json[i] = []\n            \n            for j, gen_img in enumerate(split_grid(Image.open(gen_img_path))):\n                rank_json[i].append({})\n                if len(real_names) > 0:\n                    \n                    for real_ip, real_name, real_label in zip(real_ips, real_names, real_labels):\n                        found_ips = detector_model.get_instances(gen_img, real_label, min_size=gen_img.size[0]//20)[:3]\n                        found_ips = [pad_to_square(x) for x in found_ips]\n                        score = 0\n                        if len(found_ips) > 0:\n                            score = max([dino_model(real_ip, ip) for ip in found_ips])\n                    \n                        rank_json[i][j][real_name] = score\n                    \n    json_dump(rank_json, f\"{temp_dir}/scores_{global_rank}.json\", \"utf-8\")\n\n    if is_main_process:\n        while len(glob(f\"{temp_dir}/scores_*.json\")) < world_size:\n            time.sleep(5)\n        time.sleep(5) # wait for the file writting to be finished\n        merged_json = {}\n        ip_scores = defaultdict(list)\n        all_scores = []\n        for rank_path in glob(f\"{temp_dir}/scores_*.json\"):\n            rank_json = json_load(rank_path, \"utf-8\")\n            merged_json.update(rank_json)\n            for i in rank_json:\n                grid_json = rank_json[i]\n                for img_json in grid_json:\n                    for ip_name, ip_score in img_json.items():\n                        ip_scores[ip_name].append(ip_score)\n        \n        for ip_name in ip_scores:\n            all_scores += ip_scores[ip_name]\n            ip_scores[ip_name] = np.mean(ip_scores[ip_name])\n            print(ip_name, ip_scores[ip_name])\n\n        json_dump(merged_json, f\"{args.input_dir}/ip_scores_{run_name}.json\", \"utf-8\")\n        final_ip_score = np.mean(all_scores)\n        lines_to_write = [\n            f\"IP Score: {final_ip_score:.2f}\\n\"\n        ]\n        print(lines_to_write[0])\n        for ip_name, score in ip_scores.items():\n            lines_to_write.append(f\"{ip_name}: {score:.2f}\\n\")\n\n        with open(f\"{args.input_dir}/ip_scores_{run_name}.txt\", \"w\") as f:\n            f.writelines(lines_to_write)\n\n        shutil.rmtree(temp_dir)\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "eval/tools/log_scores.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom PIL import Image\nimport os\nfrom glob import glob\nfrom tqdm import tqdm\nimport random\nimport argparse\nimport time\nfrom src.utils.data_utils import json_dump, json_load\n\n\ndef parse_args():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--input_dir\", type=str, default=\"../examples\")\n    parser.add_argument(\"--test_list_name\", type=str, default=\"base_test_list_200\")\n    args = parser.parse_args()\n    return args\n\ndef read_txt_first_line(file_path):\n    with open(file_path, \"r\") as f:\n        return f.readline().strip()\n\ndef read_txt_second_line(file_path):\n    with open(file_path, \"r\") as f:\n        f.readline()\n        return f.readline().strip()\n\nif __name__ == '__main__':\n    args = parse_args()\n    \n    final_score = {}\n\n    files = sorted(list(glob(f\"{args.input_dir}/dpg_scores_*.txt\")))\n    if len(files) > 0:\n        score = read_txt_first_line(files[-1]).split(\":\")[-1]\n        final_score[\"dpg\"] = score\n        \n    files = sorted(list(glob(f\"{args.input_dir}/id_scores_*.txt\")))\n    if len(files) > 0:\n        score = read_txt_first_line(files[-1]).split(\":\")[-1]\n        final_score[\"id\"] = score\n        \n    files = sorted(list(glob(f\"{args.input_dir}/ip_scores_*.txt\")))\n    if len(files) > 0:\n        score = read_txt_first_line(files[-1]).split(\":\")[-1]\n        final_score[\"ip\"] = score\n    \n    files = sorted(list(glob(f\"{args.input_dir}/clip_scores_*.txt\")))\n    if len(files) > 0:\n        score_i = read_txt_first_line(files[-1]).split(\":\")[-1]\n        score_t = read_txt_second_line(files[-1]).split(\":\")[-1]\n        final_score[\"clip_i\"] = score_i\n        final_score[\"clip_t\"] = score_t\n    \n    files = sorted(list(glob(f\"{args.input_dir}/aes_scores_*.txt\")))\n    if len(files) > 0:\n        score = read_txt_first_line(files[-1]).split(\":\")[-1]\n        final_score[\"aes\"] = score\n    \n    if \"dpg\" in final_score and \"id\" in final_score and \"ip\" in final_score and \"aes\" in final_score:\n        score = (float(final_score[\"dpg\"]) + float(final_score[\"id\"]) + float(final_score[\"ip\"]) + float(final_score[\"aes\"])) / 4\n        final_score[\"avg\"] = score\n    \n    run_name = time.strftime(\"%Y%m%d-%H%m\")\n    json_dump(final_score, f\"{args.input_dir}/idip_all_scores_{run_name}.json\", \"utf-8\")\n    print(final_score)\n        \n\n"
  },
  {
    "path": "inference_single_sample.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport tempfile\nfrom PIL import Image\nimport subprocess\n\nimport torch\nimport gradio as gr\nimport string\nimport random, time, os, math   \n\nfrom src.flux.generate import generate_from_test_sample, seed_everything\nfrom src.flux.pipeline_tools import CustomFluxPipeline, load_modulation_adapter, load_dit_lora\nfrom src.utils.gpu_momory_utils import ForwardHookManager\nfrom src.utils.data_utils import get_train_config, image_grid, pil2tensor, json_dump, pad_to_square, cv2pil, merge_bboxes\nfrom eval.tools.face_id import FaceID\nfrom eval.tools.florence_sam import ObjectDetector\nimport shutil\nimport yaml\nimport numpy as np\n\nimport argparse\nimport time\n\n\nconfig_path = \"train/config/XVerse_config_demo.yaml\"\nstore_attn_map = False\n\ndef generate_image(model, prompt, cond_size, target_height, target_width, seed, vae_skip_iter, control_weight_lambda, latent_dblora_scale_str, latent_sblora_scale_str, vae_lora_scale_str,\n                   indexs, num_images, device, forward_hook_manager, num_inference_steps, *args):  # 新增 num_images 参数\n    torch.cuda.empty_cache()\n    # 使用传入的 num_images\n    # num_images = 4\n\n    # 从 args 中提取 images, captions, idips_checkboxes\n    images = list(args[:len(indexs)])\n    captions = list(args[len(indexs):2*len(indexs)])\n    idips_checkboxes = list(args[2*len(indexs):3*len(indexs)])\n\n    print(f\"Length of images: {len(images)}\")\n    print(f\"Length of captions: {len(captions)}\")\n    print(f\"Indexs: {indexs}\")\n    \n    print(f\"Control weight lambda: {control_weight_lambda}\")\n    if control_weight_lambda != \"no\":\n        parts = control_weight_lambda.split(',')\n        new_parts = []\n        for part in parts:\n            if ':' in part:\n                left, right = part.split(':')\n                values = right.split('/')\n                # 保存整体值\n                global_value = values[0]\n                id_value = values[1]\n                ip_value = values[2]\n                new_values = [global_value]\n                for is_id in idips_checkboxes:\n                    if is_id:\n                        new_values.append(id_value)\n                    else:\n                        new_values.append(ip_value)\n                new_part = f\"{left}:{('/'.join(new_values))}\"\n                new_parts.append(new_part)\n            else:\n                new_parts.append(part)\n        control_weight_lambda = ','.join(new_parts)\n    \n    print(f\"Control weight lambda: {control_weight_lambda}\")\n\n    src_inputs = []\n    use_words = []\n    for i, (image_path, caption) in enumerate(zip(images, captions)):\n        if image_path:\n            if caption.startswith(\"a \") or caption.startswith(\"A \"):\n                word = caption[2:]\n            else:\n                word = caption\n            \n            if f\"ENT{i+1}\" in prompt:\n                prompt = prompt.replace(f\"ENT{i+1}\", caption)\n            \n            # 移除图片调整大小和保存操作\n            input_image_path = image_path\n\n            src_inputs.append(\n                {\n                    \"image_path\": input_image_path,\n                    \"caption\": caption\n                }\n            )\n            use_words.append((i, word, word))\n\n\n    test_sample = dict(\n        input_images=[], position_delta=[0, -32], \n        prompt=prompt,\n        target_height=target_height,\n        target_width=target_width,\n        seed=seed,\n        cond_size=cond_size,\n        vae_skip_iter=vae_skip_iter,\n        lora_scale=latent_dblora_scale_str,\n        control_weight_lambda=control_weight_lambda,\n        latent_sblora_scale=latent_sblora_scale_str,\n        condition_sblora_scale=vae_lora_scale_str,\n        double_attention=False,\n        single_attention=True,\n    )\n    if len(src_inputs) > 0:\n        test_sample[\"modulation\"] = [\n            dict(\n                type=\"adapter\",\n                src_inputs=src_inputs,\n                use_words=use_words,\n            ),\n        ]\n    \n    target_size = int(round((target_width * target_height) ** 0.5) // 16 * 16)\n    model.config[\"train\"][\"dataset\"][\"val_condition_size\"] = cond_size\n    model.config[\"train\"][\"dataset\"][\"val_target_size\"] = target_size\n    \n    if control_weight_lambda == \"no\":\n        control_weight_lambda = None\n    if vae_skip_iter == \"no\":\n        vae_skip_iter = None\n    use_condition_sblora_control = True\n    use_latent_sblora_control = True\n    image = generate_from_test_sample(\n        test_sample, model.pipe, model.config, \n        num_images=num_images,  # 使用传入的 num_images\n        target_height=target_height,\n        target_width=target_width,\n        seed=seed,\n        store_attn_map=store_attn_map, \n        vae_skip_iter=vae_skip_iter,  # 使用新的参数\n        control_weight_lambda=control_weight_lambda,  # 传递新的参数\n        double_attention=False,  # 新增参数\n        single_attention=True,  # 新增参数\n        latent_dblora_scale=latent_dblora_scale_str,\n        use_latent_sblora_control=use_latent_sblora_control,\n        latent_sblora_scale=latent_sblora_scale_str,\n        use_condition_sblora_control=use_condition_sblora_control,\n        condition_sblora_scale=vae_lora_scale_str,\n        device=device,\n        forward_hook_manager=forward_hook_manager,\n        num_inference_steps=num_inference_steps,  # 新增参数\n    )\n    if isinstance(image, list):\n        num_cols = 2\n        num_rows = int(math.ceil(num_images / num_cols))  # 使用传入的 num_images\n        image = image_grid(image, num_rows, num_cols)\n\n    return image\n\ndef main():\n    parser = argparse.ArgumentParser(description='XVerse Inference')\n    parser.add_argument('--prompt', type=str, required=True, help='Prompt for image generation')\n    parser.add_argument('--seed', type=int, default=42, help='Random seed')\n    parser.add_argument('--cond_size', type=int, default=256, help='Condition size')\n    parser.add_argument('--target_height', type=int, default=768, help='Generated image height')\n    parser.add_argument('--target_width', type=int, default=768, help='Generated image width')\n    parser.add_argument('--weight_id', type=float, default=3, help='Weight for ID')\n    parser.add_argument('--weight_ip', type=float, default=5, help='Weight for IP')\n    parser.add_argument('--latent_lora_scale', type=float, default=0.85, help='Latent lora scale')\n    parser.add_argument('--vae_lora_scale', type=float, default=1.3, help='VAE lora scale')\n    parser.add_argument('--vae_skip_iter_s1', type=float, default=0.05, help='VAE skip iter before')\n    parser.add_argument('--vae_skip_iter_s2', type=float, default=0.8, help='VAE skip iter after')\n    parser.add_argument('--images', nargs='+', help='List of image paths')\n    parser.add_argument('--captions', nargs='+', help='List of captions corresponding to images')\n    parser.add_argument('--idips', nargs='+', type=lambda x: (str(x).lower() == 'true'), help='List of ID/IP flags')\n    parser.add_argument('--save_path', type=str, default=\"generated_image.png\", help='Path to save the generated image')\n    parser.add_argument('--num_images', type=int, default=4, help='Number of images to generate')\n    parser.add_argument('--use_low_vram', type=bool, default=False, help='Use low vram')\n    parser.add_argument('--use_lower_vram', type=bool, default=False, help='Use lower vram in 16G gpu memory')\n    parser.add_argument('--num_inference_steps', type=int, default=28, help='Number of inference steps')\n    parser.add_argument('--dit_quant', type=str, default=\"int8-quanto\", help='Config for dit-quant')\n\n    args = parser.parse_args()\n\n    # size = 24 * 1024 * 1024 * 1024 // 4     \n    # big_tensor = torch.randn(size, dtype=torch.float32, device='cuda')\n\n    # 验证输入参数\n    if args.images and args.captions and len(args.images) != len(args.captions):\n        raise ValueError(\"Number of images and captions must be the same\")\n    if args.images and args.idips and len(args.images) != len(args.idips):\n        raise ValueError(\"Number of images and ID/IP flags must be the same\")\n\n    dtype = torch.bfloat16\n    if args.use_low_vram or args.use_lower_vram:\n        init_device = torch.device(\"cpu\")\n    else:\n        init_device = torch.device(\"cuda\")\n    do_device = torch.device(\"cuda\")\n    # init_device = torch.device(\"cuda\")\n\n    config = config_train = get_train_config(config_path)\n    config[\"model\"][\"dit_quant\"] = args.dit_quant\n    config[\"model\"][\"use_dit_lora\"] = False\n    model = CustomFluxPipeline(\n        config, init_device, torch_dtype=dtype,\n    )\n    model.pipe.set_progress_bar_config(leave=False)\n\n    # face_model = FaceID(init_device)\n    # detector = ObjectDetector(init_device)\n\n    config = get_train_config(config_path)\n    model.config = config\n\n    run_mode = \"mod_only\" # orig_only, mod_only, both\n    run_name = time.strftime(\"%m%d-%H%M\")\n\n    ckpt_root = \"./checkpoints/XVerse\"\n    model.clear_modulation_adapters()\n    model.pipe.unload_lora_weights()\n    if not os.path.exists(ckpt_root):\n        print(\"Checkpoint root does not exist.\")\n    modulation_adapter = load_modulation_adapter(model, config, dtype, init_device, f\"{ckpt_root}/modulation_adapter\", is_training=False)\n    model.add_modulation_adapter(modulation_adapter)\n    if config[\"model\"][\"use_dit_lora\"]:\n        load_dit_lora(model, model.pipe, config, dtype, init_device, f\"{ckpt_root}\", is_training=False)\n\n    # 计算 control_weight_lambda 和 vae_skip_iter\n    control_weight_lambda = f\"0-1:1/{args.weight_id}/{args.weight_ip}\"\n    vae_skip_iter = f\"0-{args.vae_skip_iter_s1}:1,{args.vae_skip_iter_s2}-1:1\"\n    latent_sblora_scale_str = f\"0-1:{args.latent_lora_scale}\"\n    latent_dblora_scale_str = f\"0-1:{args.latent_lora_scale}\"\n    vae_lora_scale_str = f\"0-1:{args.vae_lora_scale}\"\n\n    # 准备 indexs\n    indexs = list(range(len(args.images))) if args.images else []\n\n    if init_device.type == 'cpu' and (args.use_low_vram or args.use_lower_vram):\n        if args.use_lower_vram:\n            threshold_mem = 2 * 1024 * 1024 * 1024 \n        elif args.use_low_vram:\n            threshold_mem = 8 * 1024 * 1024 * 1024 \n        forward_hook_manager = ForwardHookManager(threshold_mem, args.use_lower_vram)\n        model.pipe.transformer = forward_hook_manager.register(model.pipe.transformer)\n        model.pipe.text_encoder = forward_hook_manager.register(model.pipe.text_encoder)\n        model.pipe.vae = forward_hook_manager.register(model.pipe.vae)\n        model.pipe.text_encoder_2 = forward_hook_manager.register(model.pipe.text_encoder_2)\n        model.pipe.clip_model = forward_hook_manager.register(model.pipe.clip_model)\n        for i in range(len(model.pipe.modulation_adapters)):\n            model.pipe.modulation_adapters[i] = forward_hook_manager.register(model.pipe.modulation_adapters[i])\n    else:\n        forward_hook_manager = None\n        model.pipe=model.pipe.to(\"cuda\")\n        for i in range(len(model.pipe.modulation_adapters)):\n            model.pipe.modulation_adapters[i] = model.pipe.modulation_adapters[i].to(\"cuda\")\n    \n    image = generate_image(\n        model,\n        args.prompt,\n        args.cond_size,\n        args.target_height,\n        args.target_width,\n        args.seed,\n        vae_skip_iter,\n        control_weight_lambda,\n        args.latent_lora_scale,\n        latent_sblora_scale_str,\n        vae_lora_scale_str,\n        indexs,\n        args.num_images,  # 传递 num_images 参数\n        do_device,\n        forward_hook_manager,\n        args.num_inference_steps,  # 新增参数\n        *args.images,\n        *args.captions,\n        *args.idips\n    )\n\n    # 使用命令行传入的路径保存生成的图像\n    image.save(args.save_path)\n    print(f\"Generated image saved to {args.save_path}\")\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "requirements.txt",
    "content": "aesthetic_predictor_v2_5==2024.12.18.1\ndecord==0.6.0\ndiffusers==0.32.2\neinops==0.8.1\ngradio==5.33.1\nhuggingface_hub==0.28.1\nhydra-core==1.3.2\niopath==0.1.10\nmodelscope==1.23.2\nomegaconf==2.3.0\nopencv_python==4.11.0.86\noptimum_quanto==0.2.6\npandas==1.5.3\npeft==0.14.0\nPillow==11.2.1\npreprocessing==0.1.13\npycocotools==2.0.8\npyfacer==0.0.5\nPyYAML==6.0.2\nPyYAML==6.0.2\nRequests==2.32.4\nsafetensors==0.5.3\nsupervision==0.25.1\ntimm==1.0.15\ntorchao==0.11.0\ntqdm==4.67.1\nwebdataset==0.2.111\npyfacer\ntransformers==4.49.0\nsentencepiece\nprotobuf\n"
  },
  {
    "path": "run_demo.sh",
    "content": "export FLORENCE2_MODEL_PATH=\"./checkpoints/Florence-2-large\"\nexport SAM2_MODEL_PATH=\"./checkpoints/sam2.1_hiera_large.pt\"\nexport FACE_ID_MODEL_PATH=\"./checkpoints/model_ir_se50.pth\"\nexport CLIP_MODEL_PATH=\"./checkpoints/clip-vit-large-patch14\"\nexport FLUX_MODEL_PATH=\"./checkpoints/FLUX.1-dev\"\n# export FLUX_MODEL_PATH=\"./checkpoints/FLUX.1-dev-bnb-4bit\"\n# export FLUX_TRANSFORMERS_PATH=\"./checkpoints/FLUX.1-dev-gguf/flux1-dev-Q3_K_S.gguf\"\n# export FLUX_MODEL_PATH=\"./checkpoints/FLUX.1-schnell\"\nexport DPG_VQA_MODEL_PATH=\"./checkpoints/mplug_visual-question-answering_coco_large_en\"\nexport DINO_MODEL_PATH=\"./checkpoints/dino-vits16\"\n\npython run_gradio.py"
  },
  {
    "path": "run_gradio.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport tempfile\nfrom PIL import Image\nimport subprocess\n\nimport torch\nimport gradio as gr\nimport string\nimport random, time, os, math   \nfrom src.utils.gpu_momory_utils import ForwardHookManager\n\nfrom src.flux.generate import generate_from_test_sample, seed_everything\nfrom src.flux.pipeline_tools import CustomFluxPipeline, load_modulation_adapter, load_dit_lora\nfrom src.utils.data_utils import get_train_config, image_grid, pil2tensor, json_dump, pad_to_square, cv2pil, merge_bboxes\nfrom eval.tools.face_id import FaceID\nfrom eval.tools.florence_sam import ObjectDetector\nimport shutil\nimport yaml, gc\nimport numpy as np\n\nimport argparse  # 导入 argparse 模块\n\n# 解析命令行参数\nparser = argparse.ArgumentParser(description='Run Gradio demo with configurable parameters')\nparser.add_argument('--server_name', type=str, default='0.0.0.0', help='Server name to bind to')\nparser.add_argument('--server_port', type=int, default=7680, help='Server port to listen on')\nparser.add_argument('--num_inference_steps', type=int, default=28, help='Number of inference steps')\nparser.add_argument('--dit_quant', type=str, default=\"int8-quanto\", help='Config for dit-quant')\nparser.add_argument('--use_low_vram', type=bool, default=False, help='Use low vram in 24G gpu memory')\nparser.add_argument('--use_lower_vram', type=bool, default=False, help='Use lower vram in 16G gpu memory')\nargs = parser.parse_args()\n\nuse_low_vram = args.use_low_vram\nuse_lower_vram = args.use_lower_vram\n\ndtype = torch.bfloat16\nnum_inputs = 6 #if not use_low_vram else 2\n\nif use_low_vram or use_lower_vram:\n    init_device = torch.device(\"cpu\")\nelse:\n    init_device = torch.device(\"cuda\")\ndo_device = torch.device(\"cuda\")\n\nconfig_path = \"train/config/XVerse_config_demo.yaml\"\n\nconfig = config_train = get_train_config(config_path)\nconfig[\"model\"][\"dit_quant\"] = args.dit_quant\nconfig[\"model\"][\"use_dit_lora\"] = False\nmodel = CustomFluxPipeline(\n    config, init_device, torch_dtype=dtype,\n)\nmodel.pipe.set_progress_bar_config(leave=False)\n\nface_model = FaceID(init_device)\ndetector = ObjectDetector(init_device)\n\nconfig = get_train_config(config_path)\nmodel.config = config\n\nrun_mode = \"mod_only\" # orig_only, mod_only, both\nstore_attn_map = False\nrun_name = time.strftime(\"%m%d-%H%M\")\n\nckpt_root = \"./checkpoints/XVerse\"\nmodel.clear_modulation_adapters()\nmodel.pipe.unload_lora_weights()\nif not os.path.exists(ckpt_root):\n    print(\"Checkpoint root does not exist.\")\n\nmodulation_adapter = load_modulation_adapter(model, config, dtype, init_device, f\"{ckpt_root}/modulation_adapter\", is_training=False)\nmodel.add_modulation_adapter(modulation_adapter)\nif config[\"model\"][\"use_dit_lora\"]:\n    load_dit_lora(model, model.pipe, config, dtype, init_device, f\"{ckpt_root}\", is_training=False)\n\nif init_device.type == 'cpu' and (args.use_low_vram or args.use_lower_vram):\n    if args.use_lower_vram:\n        threshold_mem = 2 * 1024 * 1024 * 1024 \n    elif args.use_low_vram:\n        threshold_mem = 8 * 1024 * 1024 * 1024 \n    forward_hook_manager = ForwardHookManager(threshold_mem, args.use_lower_vram)\n    model.pipe.transformer = forward_hook_manager.register(model.pipe.transformer)\n    model.pipe.text_encoder = forward_hook_manager.register(model.pipe.text_encoder)\n    model.pipe.vae = forward_hook_manager.register(model.pipe.vae)\n    model.pipe.text_encoder_2 = forward_hook_manager.register(model.pipe.text_encoder_2)\n    model.pipe.clip_model = forward_hook_manager.register(model.pipe.clip_model)\n    for i in range(len(model.pipe.modulation_adapters)):\n        model.pipe.modulation_adapters[i] = forward_hook_manager.register(model.pipe.modulation_adapters[i])\n    forward_hook_manager.register(face_model.detector)\n    forward_hook_manager.register(face_model.model)\n    forward_hook_manager.register(detector.detector.florence2_model)\n    forward_hook_manager.register(detector.detector.sam2_predictor.model)\nelse:\n    forward_hook_manager = None\n    model.pipe=model.pipe.to(\"cuda\")\n    for i in range(len(model.pipe.modulation_adapters)):\n        model.pipe.modulation_adapters[i] = model.pipe.modulation_adapters[i].to(\"cuda\")\n    model.pipe=model.pipe.to(\"cuda\")\n    face_model.detector.to(\"cuda\")\n    face_model.model.to(\"cuda\")\n    detector.detector.florence2_model.to(\"cuda\")\n    detector.detector.sam2_predictor.model.to(\"cuda\")\n\nvae_skip_iter = None\nattn_skip_iter = 0\n\n# 定义清空图像的函数，只返回四个 None\ndef clear_images():\n    return [None, ]*num_inputs\n\ndef det_seg_img(image, label):\n    if isinstance(image, str):\n        image = Image.open(image).convert(\"RGB\")\n    instance_result_dict = detector.get_multiple_instances(image, label, min_size=image.size[0]//20)\n    indices = list(range(len(instance_result_dict[\"instance_images\"])))\n    ins, bbox = merge_instances(image, indices, instance_result_dict[\"instance_bboxes\"], instance_result_dict[\"instance_images\"])\n    return ins\n\ndef crop_face_img(image):\n    if isinstance(image, str):\n        image = Image.open(image).convert(\"RGB\")\n\n    image = pad_to_square(image).resize((2048, 2048))\n    \n    face_bbox = face_model.detect(\n        (pil2tensor(image).unsqueeze(0) * 255).to(torch.uint8).to(do_device), 1.4\n    )[0]\n    face = image.crop(face_bbox)\n    return face\n\ndef vlm_img_caption(image):\n\n    # if forward_hook_manager is not None:\n    #     detector.detector.florence2_model = forward_hook_manager.model_to_cuda(detector.detector.florence2_model)\n\n    if isinstance(image, str):\n        image = Image.open(image).convert(\"RGB\")\n    \n    try:\n        caption = detector.detector.caption(image, \"<CAPTION>\").strip()\n        if caption.endswith(\".\"):\n            caption = caption[:-1]\n\n    except Exception as e:\n        print(e)\n        caption = \"\"\n    \n    caption = caption.lower()\n    return caption\n\n\ndef generate_random_string(length=4):\n    letters = string.ascii_letters  # 包含大小写字母的字符串\n    result_str = ''.join(random.choice(letters) for i in range(length))\n    return result_str\n\ndef resize_keep_aspect_ratio(pil_image, target_size=1024):\n    H, W = pil_image.height, pil_image.width\n    target_area = target_size * target_size\n    current_area = H * W\n    scaling_factor = (target_area / current_area) ** 0.5  # sqrt(target_area / current_area)\n    new_H = int(round(H * scaling_factor))\n    new_W = int(round(W * scaling_factor))\n    return pil_image.resize((new_W, new_H))\n\n# 使用循环生成六个图像输入\nimages = []\ncaptions = []\nface_btns = []\ndet_btns = []\nvlm_btns = []\naccordions = []\nidip_checkboxes = []\naccordion_states = []\n\ndef open_accordion_on_example_selection(*args):\n    print(\"enter open_accordion_on_example_selection\")\n    images = list(args[-18:-12])\n    outputs = []\n    for i, img in enumerate(images):\n        if img is not None:\n            print(f\"open accordions {i}\")\n            outputs.append(True)\n        else:\n            print(f\"close accordions {i}\")\n            outputs.append(False)\n    print(outputs)\n    return outputs\n\ndef generate_image(\n    prompt, \n    cond_size, target_height, target_width, \n    seed, \n    vae_skip_iter, control_weight_lambda,\n    double_attention,  # 新增参数\n    single_attention,  # 新增参数\n    latent_dblora_scale_str,\n    latent_sblora_scale_str, vae_lora_scale,\n    indexs,  # 新增参数\n    *images_captions_faces,  # Combine all unpacked arguments into one tuple\n):\n    torch.cuda.empty_cache()\n    num_images = 1\n\n    # Determine the number of images, captions, and faces based on the indexs length\n    images = list(images_captions_faces[:num_inputs])\n    captions = list(images_captions_faces[num_inputs:2 * num_inputs])\n    idips_checkboxes = list(images_captions_faces[2 * num_inputs:3 * num_inputs])\n    images = [images[i] for i in indexs]\n    captions = [captions[i] for i in indexs]\n    idips_checkboxes = [idips_checkboxes[i] for i in indexs]\n\n    print(f\"Length of images: {len(images)}\")\n    print(f\"Length of captions: {len(captions)}\")\n    print(f\"Indexs: {indexs}\")\n    \n    print(f\"Control weight lambda: {control_weight_lambda}\")\n    if control_weight_lambda != \"no\":\n        parts = control_weight_lambda.split(',')\n        new_parts = []\n        for part in parts:\n            if ':' in part:\n                left, right = part.split(':')\n                values = right.split('/')\n                # 保存整体值\n                global_value = values[0]\n                id_value = values[1]\n                ip_value = values[2]\n                new_values = [global_value]\n                for is_id in idips_checkboxes:\n                    if is_id:\n                        new_values.append(id_value)\n                    else:\n                        new_values.append(ip_value)\n                new_part = f\"{left}:{('/'.join(new_values))}\"\n                new_parts.append(new_part)\n            else:\n                new_parts.append(part)\n        control_weight_lambda = ','.join(new_parts)\n    \n    print(f\"Control weight lambda: {control_weight_lambda}\")\n\n    src_inputs = []\n    use_words = []\n    cur_run_time = time.strftime(\"%m%d-%H%M%S\")\n    tmp_dir_root = f\"tmp/gradio_demo/{run_name}\"\n    temp_dir = f\"{tmp_dir_root}/{cur_run_time}_{generate_random_string(4)}\"\n    os.makedirs(temp_dir, exist_ok=True)\n    print(f\"Temporary directory created: {temp_dir}\")\n    for i, (image_path, caption) in enumerate(zip(images, captions)):\n        if image_path:\n            if caption.startswith(\"a \") or caption.startswith(\"A \"):\n                word = caption[2:]\n            else:\n                word = caption\n            \n            if f\"ENT{i+1}\" in prompt:\n                prompt = prompt.replace(f\"ENT{i+1}\", caption)\n            \n            image = resize_keep_aspect_ratio(Image.open(image_path), 768)\n            save_path = f\"{temp_dir}/tmp_resized_input_{i}.png\"\n            image.save(save_path)\n            \n            input_image_path = save_path\n\n            src_inputs.append(\n                {\n                    \"image_path\": input_image_path,\n                    \"caption\": caption\n                }\n            )\n            use_words.append((i, word, word))\n\n\n    test_sample = dict(\n        input_images=[], position_delta=[0, -32], \n        prompt=prompt,\n        target_height=target_height,\n        target_width=target_width,\n        seed=seed,\n        cond_size=cond_size,\n        vae_skip_iter=vae_skip_iter,\n        lora_scale=latent_dblora_scale_str,\n        control_weight_lambda=control_weight_lambda,\n        latent_sblora_scale=latent_sblora_scale_str,\n        condition_sblora_scale=vae_lora_scale,\n        double_attention=double_attention,\n        single_attention=single_attention,\n    )\n    if len(src_inputs) > 0:\n        test_sample[\"modulation\"] = [\n            dict(\n                type=\"adapter\",\n                src_inputs=src_inputs,\n                use_words=use_words,\n            ),\n        ]\n    \n    json_dump(test_sample, f\"{temp_dir}/test_sample.json\", 'utf-8')\n    assert single_attention == True\n    target_size = int(round((target_width * target_height) ** 0.5) // 16 * 16)\n    print(test_sample)\n\n    model.config[\"train\"][\"dataset\"][\"val_condition_size\"] = cond_size\n    model.config[\"train\"][\"dataset\"][\"val_target_size\"] = target_size\n    \n    if control_weight_lambda == \"no\":\n        control_weight_lambda = None\n    if vae_skip_iter == \"no\":\n        vae_skip_iter = None\n    use_condition_sblora_control = True\n    use_latent_sblora_control = True\n    image = None\n    try:\n        image = generate_from_test_sample(\n            test_sample, model.pipe, model.config, \n            num_images=num_images, \n            target_height=target_height,\n            target_width=target_width,\n            seed=seed,\n            store_attn_map=store_attn_map, \n            vae_skip_iter=vae_skip_iter,  # 使用新的参数\n            control_weight_lambda=control_weight_lambda,  # 传递新的参数\n            double_attention=double_attention,  # 新增参数\n            single_attention=single_attention,  # 新增参数\n            ip_scale=latent_dblora_scale_str,\n            use_latent_sblora_control=use_latent_sblora_control,\n            latent_sblora_scale=latent_sblora_scale_str,\n            use_condition_sblora_control=use_condition_sblora_control,\n            condition_sblora_scale=vae_lora_scale,\n            device=do_device,\n            forward_hook_manager=forward_hook_manager,\n            num_inference_steps=args.num_inference_steps,\n        )\n        if isinstance(image, list):\n            num_cols = 2\n            num_rows = int(math.ceil(num_images / num_cols))\n            image = image_grid(image, num_rows, num_cols)\n\n        save_path = f\"{temp_dir}/tmp_result.png\"\n        image.save(save_path)\n    except torch.cuda.OutOfMemoryError:\n        gc.collect()\n        torch.cuda.synchronize()\n        torch.cuda.empty_cache()\n        raise torch.cuda.OutOfMemoryError\n    except Exception as e:\n        print(f\"Error: {e}\")\n        raise e\n    \n    return image\n\ndef create_image_input(index, open=True, indexs_state=None):\n    accordion_state = gr.State(open)\n    with gr.Column():\n        with gr.Accordion(f\"Input Image {index + 1}\", open=accordion_state.value) as accordion:\n            image = gr.Image(type=\"filepath\", label=f\"Image {index + 1}\")\n            caption = gr.Textbox(label=f\"Caption {index + 1}\", value=\"\")\n            id_ip_checkbox = gr.Checkbox(value=False, label=f\"ID or not {index + 1}\", visible=True)\n            with gr.Row():\n                vlm_btn = gr.Button(\"Auto Caption\")\n                det_btn = gr.Button(\"Det & Seg\")\n                face_btn = gr.Button(\"Crop Face\")\n            accordion.expand(\n                    inputs=[indexs_state],\n                    fn = lambda x: update_inputs(True, index, x), \n                    outputs=[indexs_state, accordion_state],\n                )\n            accordion.collapse(\n                    inputs=[indexs_state],\n                    fn = lambda x: update_inputs(False, index, x), \n                    outputs=[indexs_state, accordion_state],\n                )\n    return image, caption, face_btn, det_btn, vlm_btn, accordion_state, accordion, id_ip_checkbox\n\n\ndef merge_instances(orig_img, indices, ins_bboxes, ins_images):\n    orig_image_width, orig_image_height = orig_img.width, orig_img.height\n    final_img = Image.new(\"RGB\", (orig_image_width, orig_image_height), color=(255, 255, 255))\n    bboxes = []\n    for i in indices:\n        bbox = np.array(ins_bboxes[i], dtype=int).tolist()\n        bboxes.append(bbox)\n        \n        img = cv2pil(ins_images[i])\n        mask = (np.array(img)[..., :3] != 255).any(axis=-1)\n        mask = Image.fromarray(mask.astype(np.uint8) * 255, mode='L')\n        final_img.paste(img, (bbox[0], bbox[1]), mask)\n    \n    bbox = merge_bboxes(bboxes)\n    img = final_img.crop(bbox)\n    return img, bbox\n\n\ndef change_accordion(at: bool, index: int, state: list):\n    print(at, state)\n    indexs = state\n    if at:\n        if index not in indexs:\n            indexs.append(index)\n    else:\n        if index in indexs:\n            indexs.remove(index)\n    \n    # 确保 indexs 是有序的\n    indexs.sort()\n    print(indexs)\n    return gr.Accordion(open=at), indexs\n\ndef update_inputs(is_open, index, state: list):\n    indexs = state\n    if is_open:\n        if index not in indexs:\n            indexs.append(index)\n    else:\n        if index in indexs:\n            indexs.remove(index)\n    \n    # 确保 indexs 是有序的\n    indexs.sort()\n    print(indexs)\n    return indexs, is_open\n\nwith gr.Blocks() as demo:\n\n    indexs_state = gr.State([0, 1])  # 添加状态来存储 indexs\n    \n    gr.Markdown(\"### XVerse Demo\")\n    with gr.Row():\n        with gr.Column():\n            prompt = gr.Textbox(label=\"Prompt\", value=\"\")\n            # 使用 Row 和 Column 来布局四个图像和描述\n            with gr.Row():\n                target_height = gr.Slider(512, 1024, step=128, value=768, label=\"Generated Height\", info=\"\")\n                target_width = gr.Slider(512, 1024, step=128, value=768, label=\"Generated Width\", info=\"\")\n                cond_size = gr.Slider(256, 384, step=128, value=256, label=\"Condition Size\", info=\"\")\n            with gr.Row():\n                # 修改 weight_id_ip_str 为两个 Slider\n                weight_id = gr.Slider(0.1, 5, step=0.1, value=3, label=\"weight_id\")\n                weight_ip = gr.Slider(0.1, 5, step=0.1, value=5, label=\"weight_ip\")\n            with gr.Row():\n                # 修改 ip_scale_str 为 Slider，并添加 Textbox 显示转换后的格式\n                ip_scale_str = gr.Slider(0.5, 1.5, step=0.01, value=0.85, label=\"latent_lora_scale\")\n                vae_lora_scale = gr.Slider(0.5, 1.5, step=0.01, value=1.3, label=\"vae_lora_scale\")\n            with gr.Row():\n                # 修改 vae_skip_iter 为两个 Slider\n                vae_skip_iter_s1 = gr.Slider(0, 1, step=0.01, value=0.05, label=\"vae_skip_iter_before\")\n                vae_skip_iter_s2 = gr.Slider(0, 1, step=0.01, value=0.8, label=\"vae_skip_iter_after\")\n            \n    \n            with gr.Row():\n                weight_id_ip_str = gr.Textbox(\n                    value=\"0-1:1/3/5\",\n                    label=\"weight_id_ip_str\",\n                    interactive=False, visible=False\n                )\n                weight_id.change(\n                    lambda s1, s2: f\"0-1:1/{s1}/{s2}\",\n                    inputs=[weight_id, weight_ip],\n                    outputs=weight_id_ip_str\n                )\n                weight_ip.change(\n                    lambda s1, s2: f\"0-1:1/{s1}/{s2}\",\n                    inputs=[weight_id, weight_ip],\n                    outputs=weight_id_ip_str\n                )\n                vae_skip_iter = gr.Textbox(\n                    value=\"0-0.05:1,0.8-1:1\",\n                    label=\"vae_skip_iter\",\n                    interactive=False, visible=False\n                )\n                vae_skip_iter_s1.change(\n                    lambda s1, s2: f\"0-{s1}:1,{s2}-1:1\",\n                    inputs=[vae_skip_iter_s1, vae_skip_iter_s2],\n                    outputs=vae_skip_iter\n                )\n                vae_skip_iter_s2.change(\n                    lambda s1, s2: f\"0-{s1}:1,{s2}-1:1\",\n                    inputs=[vae_skip_iter_s1, vae_skip_iter_s2],\n                    outputs=vae_skip_iter\n                )\n                \n            \n            with gr.Row():\n                db_latent_lora_scale_str = gr.Textbox(\n                    value=\"0-1:0.85\",\n                    label=\"db_latent_lora_scale_str\",\n                    interactive=False, visible=False\n                )\n                sb_latent_lora_scale_str = gr.Textbox(\n                    value=\"0-1:0.85\",\n                    label=\"sb_latent_lora_scale_str\",\n                    interactive=False, visible=False\n                )\n                vae_lora_scale_str = gr.Textbox(\n                    value=\"0-1:1.3\",\n                    label=\"vae_lora_scale_str\",\n                    interactive=False, visible=False\n                )\n                vae_lora_scale.change(\n                        lambda s: f\"0-1:{s}\",\n                        inputs=vae_lora_scale,\n                        outputs=vae_lora_scale_str\n                    )\n                ip_scale_str.change(\n                        lambda s: [f\"0-1:{s}\", f\"0-1:{s}\"],\n                        inputs=ip_scale_str,\n                        outputs=[db_latent_lora_scale_str, sb_latent_lora_scale_str]\n                    )\n\n            with gr.Row():\n                double_attention = gr.Checkbox(value=False, label=\"Double Attention\", visible=False)\n                single_attention = gr.Checkbox(value=True, label=\"Single Attention\", visible=False)            \n\n            clear_btn = gr.Button(\"清空输入图像\")\n            with gr.Row():\n                for i in range(num_inputs):\n                    image, caption, face_btn, det_btn, vlm_btn, accordion_state, accordion, id_ip_checkbox = create_image_input(i, open=i<2, indexs_state=indexs_state)\n                    images.append(image)\n                    idip_checkboxes.append(id_ip_checkbox)\n                    captions.append(caption)\n                    face_btns.append(face_btn)\n                    det_btns.append(det_btn)\n                    vlm_btns.append(vlm_btn)\n                    accordion_states.append(accordion_state)\n                    \n                    accordions.append(accordion)\n        with gr.Column():\n            output = gr.Image(label=\"生成的图像\")\n            seed = gr.Number(value=42, label=\"Seed\", info=\"\")\n            gen_btn = gr.Button(\"生成图像\")\n\n    gr.Markdown(\"### Examples\")\n    gen_btn.click(\n        generate_image, \n        inputs=[\n            prompt, cond_size, target_height, target_width, seed,\n            vae_skip_iter, weight_id_ip_str,\n            double_attention, single_attention,\n            db_latent_lora_scale_str, sb_latent_lora_scale_str, vae_lora_scale_str,\n            indexs_state,  # 传递 indexs 状态\n            *images,  \n            *captions, \n            *idip_checkboxes,\n        ], \n        outputs=output\n    )\n\n    # 修改清空函数的输出参数\n    clear_btn.click(clear_images, outputs=images)\n\n    # 循环绑定 Det & Seg 和 Auto Caption 按钮的点击事件\n    for i in range(num_inputs):\n        face_btns[i].click(crop_face_img, inputs=[images[i]], outputs=[images[i]])\n        det_btns[i].click(det_seg_img, inputs=[images[i], captions[i]], outputs=[images[i]])\n        vlm_btns[i].click(vlm_img_caption, inputs=[images[i]], outputs=[captions[i]])\n        accordion_states[i].change(fn=lambda x, state, index=i: change_accordion(x, index, state), inputs=[accordion_states[i], indexs_state], outputs=[accordions[i], indexs_state])\n    \n    examples = gr.Examples(\n        examples=[\n            [\n                \"ENT1 wearing a tiny hat\", \n                42, 256, 768, 768,\n                3, 5,\n                0.85, 1.3,\n                0.05, 0.8,\n                \"sample/hamster.jpg\", None, None, None, None, None,\n                \"a hamster\", None, None, None, None, None,\n                False, False, False, False, False, False\n            ],\n            [\n                \"ENT1 in a red dress is smiling\", \n                42, 256, 768, 768,\n                3, 5,\n                0.85, 1.3,\n                0.05, 0.8,\n                \"sample/woman.jpg\", None, None, None, None, None,\n                \"a woman\", None, None, None, None, None,\n                True, False, False, False, False, False\n            ],\n            [\n                \"ENT1 and ENT2 standing together in a park.\", \n                42, 256, 768, 768,\n                2, 5,\n                0.85, 1.3,\n                0.05, 0.8,\n                \"sample/woman.jpg\", \"sample/girl.jpg\", None, None, None, None,\n                \"a woman\", \"a girl\", None, None, None, None,\n                True, True, False, False, False, False\n            ],\n            [\n                \"ENT1, ENT2, and ENT3 standing together in a park.\", \n                42, 256, 768, 768,\n                2.5, 5,\n                0.8, 1.2,\n                0.05, 0.8,\n                \"sample/woman.jpg\", \"sample/girl.jpg\", \"sample/old_man.jpg\", None, None, None,\n                \"a woman\", \"a girl\", \"an old man\", None, None, None,\n                True, True, True, False, False, False\n            ],\n        ],\n        inputs=[\n            prompt, seed, \n            cond_size,\n            target_height,\n            target_width,\n            weight_id,\n            weight_ip,\n            ip_scale_str,\n            vae_lora_scale,\n            vae_skip_iter_s1,\n            vae_skip_iter_s2,\n            *images,\n            *captions, \n            *idip_checkboxes\n        ],\n        outputs=accordion_states,\n        fn=open_accordion_on_example_selection,\n        run_on_click=True\n    )\n\n# size = 16 * 1024 * 1024 * 1024 // 4     \n# big_tensor = torch.randn(size, dtype=torch.float32, device='cuda')\n\ndemo.queue().launch(share=True, inbrowser=True, server_name=args.server_name, server_port=args.server_port)\n"
  },
  {
    "path": "src/adapters/__init__.py",
    "content": ""
  },
  {
    "path": "src/adapters/mod_adapters.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import Dict, List, Optional, Set, Tuple, Union\nfrom dataclasses import dataclass\nfrom inspect import isfunction\n\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom einops import rearrange, repeat\n\nfrom diffusers.models.modeling_utils import ModelMixin\nfrom diffusers.configuration_utils import ConfigMixin, register_to_config\nfrom diffusers.models.embeddings import TimestepEmbedding, Timesteps\n\nfrom src.utils.data_utils import pad_to_square, pad_to_target\n\nfrom transformers import CLIPProcessor, CLIPModel, CLIPVisionModelWithProjection, CLIPVisionModel\n\nfrom collections import OrderedDict\n\nclass SquaredReLU(nn.Module):\n    def forward(self, x: torch.Tensor):\n        return torch.square(torch.relu(x))\n\nclass AdaLayerNorm(nn.Module):\n    def __init__(self, embedding_dim: int, time_embedding_dim: Optional[int] = None, ln_bias=True):\n        super().__init__()\n\n        if time_embedding_dim is None:\n            time_embedding_dim = embedding_dim\n\n        self.silu = nn.SiLU()\n        self.linear = nn.Linear(time_embedding_dim, 2 * embedding_dim, bias=True)\n        nn.init.zeros_(self.linear.weight)\n        nn.init.zeros_(self.linear.bias)\n\n        self.norm = nn.LayerNorm(embedding_dim, elementwise_affine=False, eps=1e-6, bias=ln_bias)\n\n    def forward(\n        self, x: torch.Tensor, timestep_embedding: torch.Tensor\n    ) -> tuple[torch.Tensor, torch.Tensor]:\n        emb = self.linear(self.silu(timestep_embedding))\n        shift, scale = emb.view(len(x), 1, -1).chunk(2, dim=-1)\n        x = self.norm(x) * (1 + scale) + shift\n        return x\n\nclass PerceiverAttentionBlock(nn.Module):\n    def __init__(\n        self, d_model: int, n_heads: int, \n        time_embedding_dim: Optional[int] = None,\n        double_kv: Optional[bool] = True,\n    ):\n        super().__init__()\n        self.attn = nn.MultiheadAttention(d_model, n_heads, batch_first=True)\n        self.n_heads = n_heads\n\n        self.mlp = nn.Sequential(\n            OrderedDict(\n                [\n                    (\"c_fc\", nn.Linear(d_model, d_model * 4)),\n                    (\"sq_relu\", SquaredReLU()),\n                    (\"c_proj\", nn.Linear(d_model * 4, d_model)),\n                ]\n            )\n        )\n        self.double_kv = double_kv\n        self.ln_1 = AdaLayerNorm(d_model, time_embedding_dim)\n        self.ln_2 = AdaLayerNorm(d_model, time_embedding_dim)\n        self.ln_ff = AdaLayerNorm(d_model, time_embedding_dim)\n\n    def attention(self, q: torch.Tensor, kv: torch.Tensor, attn_mask: torch.Tensor = None):\n        attn_output, attn_output_weights = self.attn(q, kv, kv, need_weights=False, key_padding_mask=attn_mask)\n        return attn_output\n\n    def forward(\n        self,\n        x: torch.Tensor,\n        latents: torch.Tensor,\n        timestep_embedding: torch.Tensor = None,\n        attn_mask: torch.Tensor = None\n    ):\n        normed_latents = self.ln_1(latents, timestep_embedding)\n        normed_x = self.ln_2(x, timestep_embedding)\n        if self.double_kv:\n            kv = torch.cat([normed_latents, normed_x], dim=1)\n        else:\n            kv = normed_x\n        attn = self.attention(\n            q=normed_latents,\n            kv=kv,\n            attn_mask=attn_mask,\n        )\n        if attn_mask is not None:\n            query_padding_mask = attn_mask.chunk(2, -1)[0].unsqueeze(-1) # (B, 2S) -> (B, S, 1)\n            latents = latents + attn * (~query_padding_mask).to(attn)\n        else:\n            latents = latents + attn\n        latents = latents + self.mlp(self.ln_ff(latents, timestep_embedding))\n        return latents\n   \n\nclass CLIPModAdapter(ModelMixin, ConfigMixin):\n    @register_to_config\n    def __init__(\n        self, \n        out_dim=3072,\n        width=1024,\n        pblock_width=512,\n        layers=6,\n        pblock_layers=1,\n        heads=8,\n        input_text_dim=4096,\n        input_image_dim=1024,\n        pblock_single_blocks=0,\n    ):\n        super().__init__()\n        self.out_dim = out_dim\n\n        self.net = TextImageResampler(\n            width=width,\n            layers=layers,\n            heads=heads,\n            input_text_dim=input_text_dim,\n            input_image_dim=input_image_dim,\n            time_embedding_dim=64,\n            output_dim=out_dim,\n        )\n        self.net2 = TextImageResampler(\n            width=pblock_width,\n            layers=pblock_layers,\n            heads=heads,\n            input_text_dim=input_text_dim,\n            input_image_dim=input_image_dim,\n            time_embedding_dim=64,\n            output_dim=out_dim*(19+pblock_single_blocks),\n        )\n        \n    def enable_gradient_checkpointing(self):\n        self.gradient_checkpointing = True\n        self.net.enable_gradient_checkpointing()\n        self.net2.enable_gradient_checkpointing()\n\n\n    def forward(self, t_emb, llm_hidden_states, clip_outputs):\n        if len(llm_hidden_states.shape) > 3:\n            llm_hidden_states = llm_hidden_states[..., -1, :]\n        batch_size, seq_length = llm_hidden_states.shape[:2]\n\n        img_cls_feat = clip_outputs[\"image_embeds\"] # (B, 768)\n        img_last_feat = clip_outputs[\"last_hidden_state\"] # (B, 257, 1024)\n        img_layer_feats = clip_outputs[\"hidden_states\"] # [(B, 257, 1024) * 25]\n        img_second_last_feat = img_layer_feats[-2] # (B, 257, 1024)\n\n        img_hidden_states = img_second_last_feat # (B, 257, 1024)\n\n        x = self.net(llm_hidden_states, img_hidden_states) # (B, S, 3072)\n        x2 = self.net2(llm_hidden_states, img_hidden_states).view(batch_size, seq_length, -1, self.out_dim) # (B, S, N, 3072)\n        return x, x2\n\n\nclass TextImageResampler(nn.Module):\n    def __init__(\n        self,\n        width: int = 768,\n        layers: int = 6,\n        heads: int = 8,\n        output_dim: int = 3072,\n        input_text_dim: int = 4096,\n        input_image_dim: int = 1024,\n        time_embedding_dim: int = 64,\n    ):\n        super().__init__()\n        self.output_dim = output_dim\n        self.input_text_dim = input_text_dim\n        self.input_image_dim = input_image_dim\n        self.time_embedding_dim = time_embedding_dim\n\n        self.text_proj_in = nn.Linear(input_text_dim, width)\n        self.image_proj_in = nn.Linear(input_image_dim, width)\n\n        self.perceiver_blocks = nn.Sequential(\n            *[\n                PerceiverAttentionBlock(\n                    width, heads, time_embedding_dim=self.time_embedding_dim\n                )\n                for _ in range(layers)\n            ]\n        )\n\n        self.proj_out = nn.Sequential(\n            nn.Linear(width, output_dim), nn.LayerNorm(output_dim)\n        )\n        \n        self.gradient_checkpointing = False\n\n    def enable_gradient_checkpointing(self):\n        self.gradient_checkpointing = True\n        \n\n    def forward(\n        self, \n        text_hidden_states: torch.Tensor, \n        image_hidden_states: torch.Tensor,\n    ):\n        timestep_embedding = torch.zeros((text_hidden_states.shape[0], 1, self.time_embedding_dim)).to(text_hidden_states)\n\n        text_hidden_states = self.text_proj_in(text_hidden_states)\n        image_hidden_states = self.image_proj_in(image_hidden_states)\n\n        for p_block in self.perceiver_blocks:\n            if self.gradient_checkpointing:\n                def create_custom_forward(module):\n                    def custom_forward(*inputs):\n                        return module(*inputs)\n                    return custom_forward\n\n                text_hidden_states = torch.utils.checkpoint.checkpoint(\n                    create_custom_forward(p_block),\n                    image_hidden_states,\n                    text_hidden_states,\n                    timestep_embedding\n                )\n            else:\n                text_hidden_states = p_block(image_hidden_states, text_hidden_states, timestep_embedding=timestep_embedding)\n\n        text_hidden_states = self.proj_out(text_hidden_states)\n\n        return text_hidden_states\n"
  },
  {
    "path": "src/flux/block.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport torch\nfrom typing import List, Union, Optional, Tuple, Dict, Any, Callable\nfrom diffusers.models.attention_processor import Attention, F\nfrom .lora_controller import enable_lora\nfrom einops import rearrange\nimport math\nfrom diffusers.models.embeddings import apply_rotary_emb\n\n\ndef scaled_dot_product_attention(query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False, scale=None) -> torch.Tensor:\n    # Efficient implementation equivalent to the following:\n    L, S = query.size(-2), key.size(-2)\n    B = query.size(0)\n    scale_factor = 1 / math.sqrt(query.size(-1)) if scale is None else scale\n    attn_bias = torch.zeros(B, 1, L, S, dtype=query.dtype, device=query.device)\n    if is_causal:\n        assert attn_mask is None\n        assert False\n        temp_mask = torch.ones(L, S, dtype=torch.bool).tril(diagonal=0)\n        attn_bias.masked_fill_(temp_mask.logical_not(), float(\"-inf\"))\n        attn_bias.to(query.dtype)\n\n    if attn_mask is not None:\n        if attn_mask.dtype == torch.bool:\n            attn_bias.masked_fill_(attn_mask.logical_not(), float(\"-inf\"))\n        else:\n            attn_bias += attn_mask\n    attn_weight = query @ key.transpose(-2, -1) * scale_factor\n    attn_weight += attn_bias.to(attn_weight.device)\n    attn_weight = torch.softmax(attn_weight, dim=-1)\n\n    return torch.dropout(attn_weight, dropout_p, train=True) @ value, attn_weight\n\ndef attn_forward(\n    attn: Attention,\n    hidden_states: torch.FloatTensor,\n    encoder_hidden_states: torch.FloatTensor = None,\n    condition_latents: torch.FloatTensor = None,\n    text_cond_mask: Optional[torch.FloatTensor] = None,\n    attention_mask: Optional[torch.FloatTensor] = None,\n    image_rotary_emb: Optional[torch.Tensor] = None,\n    cond_rotary_emb: Optional[torch.Tensor] = None,\n    model_config: Optional[Dict[str, Any]] = {},\n    store_attn_map: bool = False,\n    latent_height: Optional[int] = None,\n    timestep: Optional[torch.Tensor] = None,\n    last_attn_map: Optional[torch.Tensor] = None,\n    condition_sblora_weight: Optional[float] = None,\n    latent_sblora_weight: Optional[float] = None,\n) -> torch.FloatTensor:\n    batch_size, _, _ = (\n        hidden_states.shape\n        if encoder_hidden_states is None\n        else encoder_hidden_states.shape\n    )\n    \n    is_sblock = encoder_hidden_states is None\n    is_dblock = not is_sblock\n    \n    with enable_lora(\n        (attn.to_q, attn.to_k, attn.to_v), \n        (is_dblock and model_config[\"latent_lora\"]) or (is_sblock and model_config[\"sblock_lora\"]), latent_sblora_weight=latent_sblora_weight\n    ):\n        query = attn.to_q(hidden_states)\n        key = attn.to_k(hidden_states)\n        value = attn.to_v(hidden_states)\n         \n    inner_dim = key.shape[-1]\n    head_dim = inner_dim // attn.heads\n\n    query = query.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n    key = key.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n    value = value.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n\n    if attn.norm_q is not None:\n        query = attn.norm_q(query)\n    if attn.norm_k is not None:\n        key = attn.norm_k(key)\n\n    # the attention in FluxSingleTransformerBlock does not use `encoder_hidden_states`\n    if encoder_hidden_states is not None:\n        # `context` projections.\n        with enable_lora((attn.add_q_proj, attn.add_k_proj, attn.add_v_proj), model_config[\"text_lora\"]):\n            encoder_hidden_states_query_proj = attn.add_q_proj(encoder_hidden_states)\n            encoder_hidden_states_key_proj = attn.add_k_proj(encoder_hidden_states)\n            encoder_hidden_states_value_proj = attn.add_v_proj(encoder_hidden_states)\n\n        encoder_hidden_states_query_proj = encoder_hidden_states_query_proj.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n        encoder_hidden_states_key_proj = encoder_hidden_states_key_proj.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n        encoder_hidden_states_value_proj = encoder_hidden_states_value_proj.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n\n        if attn.norm_added_q is not None:\n            encoder_hidden_states_query_proj = attn.norm_added_q(encoder_hidden_states_query_proj)\n        if attn.norm_added_k is not None:\n            encoder_hidden_states_key_proj = attn.norm_added_k(encoder_hidden_states_key_proj)\n\n        # attention\n        query = torch.cat([encoder_hidden_states_query_proj, query], dim=2)\n        key = torch.cat([encoder_hidden_states_key_proj, key], dim=2)\n        value = torch.cat([encoder_hidden_states_value_proj, value], dim=2)\n\n    if image_rotary_emb is not None:\n        query = apply_rotary_emb(query, image_rotary_emb)\n        key = apply_rotary_emb(key, image_rotary_emb)\n\n    if condition_latents is not None:\n        assert condition_latents.shape[0] == batch_size\n        cond_length = condition_latents.shape[1]\n\n        cond_lora_activate = (is_dblock and model_config[\"use_condition_dblock_lora\"]) or (is_sblock and model_config[\"use_condition_sblock_lora\"])\n        with enable_lora(\n            (attn.to_q, attn.to_k, attn.to_v), \n            dit_activated=not cond_lora_activate, cond_activated=cond_lora_activate, latent_sblora_weight=condition_sblora_weight  #TODO implementation for condition lora not share\n        ):\n            cond_query = attn.to_q(condition_latents)\n            cond_key = attn.to_k(condition_latents)\n            cond_value = attn.to_v(condition_latents)\n\n        cond_query = cond_query.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n        cond_key = cond_key.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n        cond_value = cond_value.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)\n        if attn.norm_q is not None:\n            cond_query = attn.norm_q(cond_query)\n        if attn.norm_k is not None:\n            cond_key = attn.norm_k(cond_key)\n\n        if cond_rotary_emb is not None:\n            cond_query = apply_rotary_emb(cond_query, cond_rotary_emb)\n            cond_key = apply_rotary_emb(cond_key, cond_rotary_emb)\n\n        if model_config.get(\"text_cond_attn\", False):\n            if encoder_hidden_states is not None:\n                assert text_cond_mask is not None\n                img_length = hidden_states.shape[1]\n                seq_length = encoder_hidden_states_query_proj.shape[2]\n                assert len(text_cond_mask.shape) == 2 or len(text_cond_mask.shape) == 3\n                if len(text_cond_mask.shape) == 2:\n                    text_cond_mask = text_cond_mask.unsqueeze(-1)\n                N = text_cond_mask.shape[-1] # num_condition\n            else:\n                raise NotImplementedError()\n\n            query = torch.cat([query, cond_query], dim=2) # (B, 24, S+HW+NC)\n            key = torch.cat([key, cond_key], dim=2)\n            value = torch.cat([value, cond_value], dim=2)\n            \n            assert query.shape[2] == key.shape[2]\n            assert query.shape[2] == cond_length + img_length + seq_length\n\n            attention_mask = torch.ones(batch_size, 1, query.shape[2], key.shape[2], device=query.device, dtype=torch.bool)\n            attention_mask[..., -cond_length:, :-cond_length] = False\n            attention_mask[..., :-cond_length, -cond_length:] = False\n\n            if encoder_hidden_states is not None:\n                tokens_per_cond = cond_length // N\n                for i in range(batch_size):\n                    for j in range(N):\n                        start = seq_length + img_length + tokens_per_cond * j\n                        attention_mask[i, 0, :seq_length, start:start+tokens_per_cond] = text_cond_mask[i, :, j].unsqueeze(-1)\n\n        elif model_config.get(\"union_cond_attn\", False):\n            query = torch.cat([query, cond_query], dim=2) # (B, 24, S+HW+NC)\n            key = torch.cat([key, cond_key], dim=2)\n            value = torch.cat([value, cond_value], dim=2)\n            \n            attention_mask = torch.ones(batch_size, 1, query.shape[2], key.shape[2], device=query.device, dtype=torch.bool)\n            cond_length = condition_latents.shape[1]\n            assert len(text_cond_mask.shape) == 2 or len(text_cond_mask.shape) == 3\n            if len(text_cond_mask.shape) == 2:\n                text_cond_mask = text_cond_mask.unsqueeze(-1)\n            N = text_cond_mask.shape[-1] # num_condition\n            tokens_per_cond = cond_length // N\n            \n            seq_length = 0\n            if encoder_hidden_states is not None:\n                seq_length = encoder_hidden_states_query_proj.shape[2]\n                img_length = hidden_states.shape[1]\n            else:\n                seq_length = 128 # TODO, pass it here\n                img_length = hidden_states.shape[1] - seq_length\n            \n            if not model_config.get(\"cond_cond_cross_attn\", True):\n                # no cross attention between different conds\n                cond_start = seq_length + img_length\n                attention_mask[:, :, cond_start:, cond_start:] = False\n                \n                for j in range(N):\n                    start = cond_start + tokens_per_cond * j\n                    end = cond_start + tokens_per_cond * (j + 1)\n                    attention_mask[..., start:end, start:end] = True\n            \n            # double block\n            if encoder_hidden_states is not None:\n                \n                # no cross attention\n                attention_mask[..., :-cond_length, -cond_length:] = False\n\n                if model_config.get(\"use_attention_double\", False) and last_attn_map is not None:\n                    attention_mask = torch.zeros(batch_size, 1, query.shape[2], key.shape[2], device=query.device, dtype=torch.bfloat16)\n                    last_attn_map = last_attn_map.to(query.device)\n                    attention_mask[..., seq_length:-cond_length, :seq_length] = torch.log(last_attn_map/last_attn_map.mean()*model_config[\"use_atten_lambda\"]).view(-1, seq_length)\n                \n            # single block\n            else:\n                # print(last_attn_map)\n                if model_config.get(\"use_attention_single\", False) and last_attn_map is not None:\n                    attention_mask = torch.zeros(batch_size, 1, query.shape[2], key.shape[2], device=query.device, dtype=torch.bfloat16)\n                    attention_mask[..., :seq_length, -cond_length:] = float('-inf')\n                    # 确保 use_atten_lambda 是列表\n                    use_atten_lambdas = model_config[\"use_atten_lambda\"] if len(model_config[\"use_atten_lambda\"])!=1 else model_config[\"use_atten_lambda\"] * (N+1)\n                    attention_mask[..., -cond_length:, seq_length:-cond_length] = math.log(use_atten_lambdas[0])\n                    last_attn_map = last_attn_map.to(query.device)\n                    \n                    cond2latents = []\n                    for i in range(batch_size):\n                        AM = last_attn_map[i] # (H, W, S)\n                        for j in range(N):\n                            start = seq_length + img_length + tokens_per_cond * j\n                            mask = text_cond_mask[i, :, j] # (S,)\n                            weighted_AM = AM * mask.unsqueeze(0).unsqueeze(0)  # 扩展 mask 维度以匹配 AM\n\n                            cond2latent = weighted_AM.mean(-1)\n                            if model_config.get(\"attention_norm\", \"mean\") == \"max\":\n                                cond2latent = cond2latent / cond2latent.max()  # 归一化\n                            else:\n                                cond2latent = cond2latent / cond2latent.mean()  # 归一化\n                            cond2latent = cond2latent.view(-1,) # (WH,)\n\n                            # 使用对应 condition 的 lambda 值\n                            current_lambda = use_atten_lambdas[j+1]\n                            # 将 cond2latent 复制到 attention_mask[i, 0, :seq_length, start:start+tokens_per_cond]\n                            attention_mask[i, 0, seq_length:-cond_length, start:start+tokens_per_cond] = torch.log(current_lambda * cond2latent.unsqueeze(-1))\n                            \n                            # 将 text_cond_mask[i, :, j].unsqueeze(-1) 为 true 的位置设置为当前 lambda 值\n                            cond = mask.unsqueeze(-1).expand(-1, tokens_per_cond)\n                            sub_mask = attention_mask[i, 0, :seq_length, start:start+tokens_per_cond]\n                            attention_mask[i, 0, :seq_length, start:start+tokens_per_cond] = torch.where(cond, math.log(current_lambda), sub_mask)\n                            cond2latents.append(\n                                cond2latent.reshape(latent_height, -1).detach().cpu()\n                            )\n                    if store_attn_map:\n                        if not hasattr(attn, \"cond2latents\"):\n                            attn.cond2latents = []\n                            attn.cond_timesteps = []\n                        attn.cond2latents.append(torch.stack(cond2latents, dim=0)) # (N, H, W)\n                        attn.cond_timesteps.append(timestep.cpu())\n\n                pass\n        else:\n            raise NotImplementedError()\n        if hasattr(attn, \"c_factor\"):\n            assert False\n            attention_mask = torch.zeros(\n                query.shape[2], key.shape[2], device=query.device, dtype=query.dtype\n            )\n            bias = torch.log(attn.c_factor[0])\n            attention_mask[-cond_length:, :-cond_length] = bias\n            attention_mask[:-cond_length, -cond_length:] = bias\n\n    ####################################################################################################\n    if store_attn_map and encoder_hidden_states is not None:\n        seq_length = encoder_hidden_states_query_proj.shape[2]\n        img_length = hidden_states.shape[1]\n        hidden_states, attention_probs = scaled_dot_product_attention(\n            query, key, value, attn_mask=attention_mask, dropout_p=0.0, is_causal=False\n        )\n        # (B, 24, S+HW, S+HW) -> (B, 24, HW, S)\n        t2i_attention_probs = attention_probs[:, :, seq_length:seq_length+img_length, :seq_length]\n        # (B, 24, S+HW, S+HW) -> (B, 24, S, HW) -> (B, 24, HW, S)\n        i2t_attention_probs = attention_probs[:, :, :seq_length, seq_length:seq_length+img_length].transpose(-1, -2)\n        \n        if not hasattr(attn, \"attn_maps\"):\n            attn.attn_maps = []\n            attn.timestep = []\n\n        attn.attn_maps.append(\n            (\n                rearrange(t2i_attention_probs, 'B attn_head (H W) attn_dim -> B attn_head H W attn_dim', H=latent_height),\n                rearrange(i2t_attention_probs, 'B attn_head (H W) attn_dim -> B attn_head H W attn_dim', H=latent_height),\n            )\n        )\n\n        attn.timestep.append(timestep.cpu())\n        has_nan = torch.isnan(hidden_states).any().item()\n        if has_nan:\n            print(\"[attn_forward] detect nan hidden_states in store_attn_map\")\n    else:\n        hidden_states = F.scaled_dot_product_attention(\n            query, key, value, attn_mask=attention_mask, dropout_p=0.0, is_causal=False\n        )\n        has_nan = torch.isnan(hidden_states).any().item()\n        if has_nan:\n            print(\"[attn_forward] detect nan hidden_states\")\n    ####################################################################################################\n    hidden_states = hidden_states.transpose(1, 2).reshape(batch_size, -1, attn.heads * head_dim).to(query.dtype)\n\n    if encoder_hidden_states is not None:\n        if condition_latents is not None:\n            encoder_hidden_states, hidden_states, condition_latents = (\n                hidden_states[:, : encoder_hidden_states.shape[1]],\n                hidden_states[\n                    :, encoder_hidden_states.shape[1] : -condition_latents.shape[1]\n                ],\n                hidden_states[:, -condition_latents.shape[1] :],\n            )\n            if model_config.get(\"latent_cond_by_text_attn\", False):\n                # hidden_states += add_latent # (B, HW, D)\n                hidden_states = new_hidden_states # (B, HW, D)\n            \n        else:\n            encoder_hidden_states, hidden_states = (\n                hidden_states[:, : encoder_hidden_states.shape[1]],\n                hidden_states[:, encoder_hidden_states.shape[1] :],\n            )\n\n\n        with enable_lora((attn.to_out[0],), model_config[\"latent_lora\"]):\n            hidden_states = attn.to_out[0](hidden_states) # linear proj\n            hidden_states = attn.to_out[1](hidden_states) # dropout\n        with enable_lora((attn.to_add_out,), model_config[\"text_lora\"]):\n            encoder_hidden_states = attn.to_add_out(encoder_hidden_states)\n\n        if condition_latents is not None:\n            cond_lora_activate = model_config[\"use_condition_dblock_lora\"]\n            with enable_lora(\n                (attn.to_out[0],), \n                dit_activated=not cond_lora_activate, cond_activated=cond_lora_activate,\n            ):\n                condition_latents = attn.to_out[0](condition_latents)\n                condition_latents = attn.to_out[1](condition_latents)\n\n\n        return (\n            (hidden_states, encoder_hidden_states, condition_latents)\n            if condition_latents is not None\n            else (hidden_states, encoder_hidden_states)\n        )\n    elif condition_latents is not None:\n        hidden_states, condition_latents = (\n            hidden_states[:, : -condition_latents.shape[1]],\n            hidden_states[:, -condition_latents.shape[1] :],\n        )\n        return hidden_states, condition_latents\n    else:\n        return hidden_states\n\n\ndef set_delta_by_start_end(\n    start_ends, \n    src_delta_emb, src_delta_emb_pblock, \n    delta_emb, delta_emb_pblock, delta_emb_mask, \n):\n    for (i, j, src_s, src_e, tar_s, tar_e) in start_ends:\n        if src_delta_emb is not None:\n            delta_emb[i, tar_s:tar_e] = src_delta_emb[j, src_s:src_e]\n        if src_delta_emb_pblock is not None:\n            delta_emb_pblock[i, tar_s:tar_e] = src_delta_emb_pblock[j, src_s:src_e]\n        delta_emb_mask[i, tar_s:tar_e] = True\n    return delta_emb, delta_emb_pblock, delta_emb_mask\n\ndef norm1_context_forward(\n    norm1_context,\n    x: torch.Tensor,\n    condition_latents: Optional[torch.Tensor] = None, \n    timestep: Optional[torch.Tensor] = None,\n    class_labels: Optional[torch.LongTensor] = None,\n    hidden_dtype: Optional[torch.dtype] = None,\n    emb: Optional[torch.Tensor] = None,\n    delta_emb: Optional[torch.Tensor] = None,\n    delta_emb_cblock: Optional[torch.Tensor] = None,\n    delta_emb_mask: Optional[torch.Tensor] = None,\n    delta_start_ends = None,\n    mod_adapter = None,\n) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:\n    batch_size, seq_length = x.shape[:2]\n    \n    if mod_adapter is not None:\n        assert False\n\n    if delta_emb is None:\n        emb = norm1_context.linear(norm1_context.silu(emb)) # (B, 3072) -> (B, 18432)\n        emb = emb.unsqueeze(1) # (B, 1, 18432)\n        shift_msa, scale_msa, gate_msa, shift_mlp, scale_mlp, gate_mlp = emb.chunk(6, dim=-1) # (B, 1, 3072)\n        x = norm1_context.norm(x) * (1 + scale_msa) + shift_msa # (B, 1, 3072)\n        return x, gate_msa, shift_mlp, scale_mlp, gate_mlp\n    else:\n        # (B, 3072) > (B, 18432) -> (B, S, 18432)\n        emb_orig = norm1_context.linear(norm1_context.silu(emb)).unsqueeze(1).expand((-1, seq_length, -1))\n        # (B, 3072) -> (B, 1, 3072) -> (B, S, 3072) -> (B, S, 18432)\n        if delta_emb_cblock is None:\n            emb_new = norm1_context.linear(norm1_context.silu(emb.unsqueeze(1) + delta_emb))\n        else:\n            emb_new = norm1_context.linear(norm1_context.silu(emb.unsqueeze(1) + delta_emb + delta_emb_cblock))\n        emb = torch.where(delta_emb_mask.unsqueeze(-1), emb_new, emb_orig) # (B, S, 18432)\n        shift_msa, scale_msa, gate_msa, shift_mlp, scale_mlp, gate_mlp = emb.chunk(6, dim=-1) # (B, S, 3072)\n        x = norm1_context.norm(x) * (1 + scale_msa) + shift_msa # (B, S, 3072)\n        return x, gate_msa, shift_mlp, scale_mlp, gate_mlp\n        \n\ndef norm1_forward(\n    norm1,\n    x: torch.Tensor,\n    timestep: Optional[torch.Tensor] = None,\n    class_labels: Optional[torch.LongTensor] = None,\n    hidden_dtype: Optional[torch.dtype] = None,\n    emb: Optional[torch.Tensor] = None,\n    delta_emb: Optional[torch.Tensor] = None,\n    delta_emb_cblock: Optional[torch.Tensor] = None,\n    delta_emb_mask: Optional[torch.Tensor] = None,\n    t2i_attn_map: Optional[torch.Tensor] = None,\n) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:\n    if delta_emb is None:\n        emb = norm1.linear(norm1.silu(emb)) # (B, 3072) -> (B, 18432)\n        emb = emb.unsqueeze(1) # (B, 1, 18432)\n        shift_msa, scale_msa, gate_msa, shift_mlp, scale_mlp, gate_mlp = emb.chunk(6, dim=-1) # (B, 1, 3072)\n        x = norm1.norm(x) * (1 + scale_msa) + shift_msa # (B, 1, 3072)\n        return x, gate_msa, shift_mlp, scale_mlp, gate_mlp\n    else:\n        raise NotImplementedError()\n        batch_size, HW = x.shape[:2]\n        seq_length = t2i_attn_map.shape[-1]\n        # (B, 3072) > (B, 18432) -> (B, S, 18432)\n        emb_orig = norm1.linear(norm1.silu(emb)).unsqueeze(1).expand((-1, seq_length, -1))\n        # (B, 3072) -> (B, 1, 3072) -> (B, S, 3072) -> (B, S, 18432)\n        if delta_emb_cblock is None:\n            emb_new = norm1.linear(norm1.silu(emb.unsqueeze(1) + delta_emb))\n        else:\n            emb_new = norm1.linear(norm1.silu(emb.unsqueeze(1) + delta_emb + delta_emb_cblock))\n        # attn_weight (B, HW, S)\n        emb = torch.where(delta_emb_mask.unsqueeze(-1), emb_new, emb_orig) # (B, S, 18432)\n        emb = t2i_attn_map @ emb    # (B, HW, 18432)\n        shift_msa, scale_msa, gate_msa, shift_mlp, scale_mlp, gate_mlp = emb.chunk(6, dim=-1) # (B, HW, 3072)\n        x = norm1.norm(x) * (1 + scale_msa) + shift_msa # (B, HW, 3072)\n        return x, gate_msa, shift_mlp, scale_mlp, gate_mlp\n\n\ndef block_forward(\n    block,\n    hidden_states: torch.FloatTensor,\n    encoder_hidden_states: torch.FloatTensor,\n    condition_latents: torch.FloatTensor,\n    temb: torch.FloatTensor,\n    cond_temb: torch.FloatTensor,\n    text_cond_mask: Optional[torch.FloatTensor] = None,\n    delta_emb: Optional[torch.FloatTensor] = None,\n    delta_emb_cblock: Optional[torch.FloatTensor] = None,\n    delta_emb_mask: Optional[torch.Tensor] = None,\n    delta_start_ends = None,\n    cond_rotary_emb=None,\n    image_rotary_emb=None,\n    model_config: Optional[Dict[str, Any]] = {},\n    store_attn_map: bool = False,\n    use_text_mod: bool = True,\n    use_img_mod: bool = False,\n    mod_adapter = None,\n    latent_height: Optional[int] = None,\n    timestep: Optional[torch.Tensor] = None,\n    last_attn_map: Optional[torch.Tensor] = None,\n):\n    batch_size = hidden_states.shape[0]\n    use_cond = condition_latents is not None\n\n    train_partial_latent_lora = model_config.get(\"train_partial_latent_lora\", False)\n    train_partial_text_lora = model_config.get(\"train_partial_text_lora\", False)\n    if train_partial_latent_lora:\n        train_partial_latent_lora_layers = model_config.get(\"train_partial_latent_lora_layers\", \"\")\n        activate_norm1 = activate_ff = True\n        if \"norm1\" not in train_partial_latent_lora_layers:\n            activate_norm1 = False\n        if \"ff\" not in train_partial_latent_lora_layers:\n            activate_ff = False\n    \n    if train_partial_text_lora:\n        train_partial_text_lora_layers = model_config.get(\"train_partial_text_lora_layers\", \"\")\n        activate_norm1_context = activate_ff_context = True\n        if \"norm1\" not in train_partial_text_lora_layers:\n            activate_norm1_context = False\n        if \"ff\" not in train_partial_text_lora_layers:\n            activate_ff_context = False\n    \n    if use_cond:\n        cond_lora_activate = model_config[\"use_condition_dblock_lora\"]\n        with enable_lora(\n            (block.norm1.linear,), \n            dit_activated=activate_norm1 if train_partial_latent_lora else not cond_lora_activate, cond_activated=cond_lora_activate,\n        ):\n            norm_condition_latents, cond_gate_msa, cond_shift_mlp, cond_scale_mlp, cond_gate_mlp = (\n                norm1_forward(\n                    block.norm1,\n                    condition_latents,\n                    emb=cond_temb, \n                )\n            )\n    delta_emb_img = delta_emb_img_cblock = None\n    if use_img_mod and use_text_mod:\n        if delta_emb is not None:\n            delta_emb_img, delta_emb = delta_emb.chunk(2, dim=-1)\n        if delta_emb_cblock is not None:\n            delta_emb_img_cblock, delta_emb_cblock = delta_emb_cblock.chunk(2, dim=-1)\n\n    with enable_lora((block.norm1.linear,), activate_norm1 if train_partial_latent_lora else model_config[\"latent_lora\"]):\n        if use_img_mod and encoder_hidden_states is not None:\n            with torch.no_grad():\n                attn = block.attn\n\n                norm_img = block.norm1(hidden_states, emb=temb)[0]\n                norm_text = block.norm1_context(encoder_hidden_states, emb=temb)[0]\n                \n                img_query = attn.to_q(norm_img)\n                img_key = attn.to_k(norm_img)\n                text_query = attn.add_q_proj(norm_text)\n                text_key = attn.add_k_proj(norm_text)\n\n                inner_dim = img_key.shape[-1]\n                head_dim = inner_dim // attn.heads\n\n                img_query = img_query.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)   # (B, N, HW, D)\n                img_key = img_key.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)       # (B, N, HW, D)\n                text_query = text_query.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2) # (B, N, S, D)\n                text_key = text_key.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)     # (B, N, S, D)\n\n                if attn.norm_q is not None:\n                    img_query = attn.norm_q(img_query)\n                if attn.norm_added_q is not None:\n                    text_query = attn.norm_added_q(text_query)\n                if attn.norm_k is not None:\n                    img_key = attn.norm_k(img_key)\n                if attn.norm_added_k is not None:\n                    text_key = attn.norm_added_k(text_key)\n                \n                query = torch.cat([text_query, img_query], dim=2) # (B, N, S+HW, D)\n                key = torch.cat([text_key, img_key], dim=2)       # (B, N, S+HW, D)\n                if image_rotary_emb is not None:\n                    query = apply_rotary_emb(query, image_rotary_emb)\n                    key = apply_rotary_emb(key, image_rotary_emb)\n\n                seq_length = text_query.shape[2]\n\n                scale_factor = 1 / math.sqrt(query.size(-1))\n                t2i_attn_map = query @ key.transpose(-2, -1) * scale_factor # (B, N, S+HW, S+HW)\n                t2i_attn_map = t2i_attn_map.mean(1)[:, seq_length:, :seq_length] # (B, S+HW, S+HW) -> (B, HW, S)\n                t2i_attn_map = torch.softmax(t2i_attn_map, dim=-1) # (B, HW, S)\n\n        else:\n            t2i_attn_map = None\n\n        norm_hidden_states, gate_msa, shift_mlp, scale_mlp, gate_mlp = (\n            norm1_forward(\n                block.norm1,\n                hidden_states,\n                emb=temb,\n                delta_emb=delta_emb_img,\n                delta_emb_cblock=delta_emb_img_cblock,\n                delta_emb_mask=delta_emb_mask,\n                t2i_attn_map=t2i_attn_map,\n            )\n        )\n    # Modulation for double block\n    with enable_lora((block.norm1_context.linear,), activate_norm1_context if train_partial_text_lora else model_config[\"text_lora\"]):\n        norm_encoder_hidden_states, c_gate_msa, c_shift_mlp, c_scale_mlp, c_gate_mlp = (\n            norm1_context_forward(\n                block.norm1_context, \n                encoder_hidden_states, \n                emb=temb, \n                delta_emb=delta_emb if use_text_mod else None,\n                delta_emb_cblock=delta_emb_cblock if use_text_mod else None,\n                delta_emb_mask=delta_emb_mask if use_text_mod else None,\n                delta_start_ends=delta_start_ends if use_text_mod else None,\n                mod_adapter=mod_adapter,\n                condition_latents=condition_latents,\n            )\n        )\n\n    # Attention.\n    result = attn_forward(\n        block.attn,\n        model_config=model_config,\n        hidden_states=norm_hidden_states,\n        encoder_hidden_states=norm_encoder_hidden_states,\n        condition_latents=norm_condition_latents if use_cond else None,\n        text_cond_mask=text_cond_mask if use_cond else None,\n        image_rotary_emb=image_rotary_emb,\n        cond_rotary_emb=cond_rotary_emb if use_cond else None,\n        store_attn_map=store_attn_map,\n        latent_height=latent_height,\n        timestep=timestep,\n        last_attn_map=last_attn_map,\n    )\n    attn_output, context_attn_output = result[:2]\n    cond_attn_output = result[2] if use_cond else None\n\n    # Process attention outputs for the `hidden_states`.\n    # 1. hidden_states\n    attn_output = gate_msa * attn_output # NOTE: changed by img mod\n    hidden_states = hidden_states + attn_output\n    # 2. encoder_hidden_states\n    context_attn_output = c_gate_msa * context_attn_output # NOTE: changed by delta_temb\n    encoder_hidden_states = encoder_hidden_states + context_attn_output\n    # 3. condition_latents\n    if use_cond:\n        cond_attn_output = cond_gate_msa * cond_attn_output  # NOTE: changed by img mod\n        condition_latents = condition_latents + cond_attn_output\n        if model_config.get(\"add_cond_attn\", False):\n            hidden_states += cond_attn_output\n\n    # LayerNorm + MLP.\n    # 1. hidden_states\n    norm_hidden_states = block.norm2(hidden_states)\n    norm_hidden_states = (\n        norm_hidden_states * (1 + scale_mlp) + shift_mlp  # NOTE: changed by img mod\n    )\n    # 2. encoder_hidden_states\n    norm_encoder_hidden_states = block.norm2_context(encoder_hidden_states)\n    norm_encoder_hidden_states = (\n        norm_encoder_hidden_states * (1 + c_scale_mlp) + c_shift_mlp  # NOTE: changed by delta_temb\n    )\n    # 3. condition_latents\n    if use_cond:\n        norm_condition_latents = block.norm2(condition_latents)\n        norm_condition_latents = (\n            norm_condition_latents * (1 + cond_scale_mlp) + cond_shift_mlp # NOTE: changed by img mod\n        )\n\n    # Feed-forward.\n    with enable_lora((block.ff.net[2],), activate_ff if train_partial_latent_lora else model_config[\"latent_lora\"]):\n        # 1. hidden_states\n        ff_output = block.ff(norm_hidden_states)\n        ff_output = gate_mlp * ff_output  # NOTE: changed by img mod\n    # 2. encoder_hidden_states\n    with enable_lora((block.ff_context.net[2],), activate_ff_context if train_partial_text_lora else model_config[\"text_lora\"]):\n        context_ff_output = block.ff_context(norm_encoder_hidden_states)\n        context_ff_output = c_gate_mlp * context_ff_output  # NOTE: changed by delta_temb\n    # 3. condition_latents\n    if use_cond:\n        cond_lora_activate = model_config[\"use_condition_dblock_lora\"]\n        with enable_lora(\n            (block.ff.net[2],), \n            dit_activated=activate_ff if train_partial_latent_lora else not cond_lora_activate, cond_activated=cond_lora_activate,\n        ):\n            cond_ff_output = block.ff(norm_condition_latents)\n            cond_ff_output = cond_gate_mlp * cond_ff_output  # NOTE: changed by img mod\n\n    # Process feed-forward outputs.\n    hidden_states = hidden_states + ff_output\n    encoder_hidden_states = encoder_hidden_states + context_ff_output\n    if use_cond:\n        condition_latents = condition_latents + cond_ff_output\n\n    # Clip to avoid overflow.\n    if encoder_hidden_states.dtype == torch.float16:\n        encoder_hidden_states = encoder_hidden_states.clip(-65504, 65504)\n\n    return encoder_hidden_states, hidden_states, condition_latents if use_cond else None\n\ndef single_norm_forward(\n    block,\n    x: torch.Tensor,\n    timestep: Optional[torch.Tensor] = None,\n    class_labels: Optional[torch.LongTensor] = None,\n    hidden_dtype: Optional[torch.dtype] = None,\n    emb: Optional[torch.Tensor] = None,\n    delta_emb: Optional[torch.Tensor] = None,\n    delta_emb_cblock: Optional[torch.Tensor] = None,\n    delta_emb_mask: Optional[torch.Tensor] = None,\n) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:\n    if delta_emb is None:\n        emb = block.linear(block.silu(emb)) # (B, 3072) -> (B, 9216)\n        emb = emb.unsqueeze(1) # (B, 1, 9216)\n        shift_msa, scale_msa, gate_msa = emb.chunk(3, dim=-1) # (B, 1, 3072)\n        x = block.norm(x) * (1 + scale_msa) + shift_msa # (B, S, 3072) * (B, 1, 3072)\n        return x, gate_msa\n    else:\n        img_text_seq_length = x.shape[1] # S+\n        text_seq_length = delta_emb_mask.shape[1] # S\n        # (B, 3072) -> (B, 9216) -> (B, S+, 9216)\n        emb_orig = block.linear(block.silu(emb)).unsqueeze(1).expand((-1, img_text_seq_length, -1))\n        # (B, 3072) -> (B, 1, 3072) -> (B, S, 3072) -> (B, S, 9216)\n        if delta_emb_cblock is None:\n            emb_new = block.linear(block.silu(emb.unsqueeze(1) + delta_emb))\n        else:\n            emb_new = block.linear(block.silu(emb.unsqueeze(1) + delta_emb + delta_emb_cblock))\n\n        emb_text = torch.where(delta_emb_mask.unsqueeze(-1), emb_new, emb_orig[:, :text_seq_length]) # (B, S, 9216)\n        emb_img = emb_orig[:, text_seq_length:] # (B, s, 9216)\n        emb = torch.cat([emb_text, emb_img], dim=1) # (B, S+, 9216)\n\n        shift_msa, scale_msa, gate_msa = emb.chunk(3, dim=-1) # (B, S+, 3072)\n        x = block.norm(x) * (1 + scale_msa) + shift_msa # (B, S+, 3072)\n        return x, gate_msa\n\n\ndef single_block_forward(\n    block,\n    hidden_states: torch.FloatTensor,\n    temb: torch.FloatTensor,\n    image_rotary_emb=None,\n    condition_latents: torch.FloatTensor = None,\n    text_cond_mask: torch.FloatTensor = None,\n    cond_temb: torch.FloatTensor = None,\n    delta_emb: Optional[torch.FloatTensor] = None,\n    delta_emb_cblock: Optional[torch.FloatTensor] = None,\n    delta_emb_mask: Optional[torch.Tensor] = None,\n    use_text_mod: bool = True,\n    use_img_mod: bool = False,\n    cond_rotary_emb=None,\n    latent_height: Optional[int] = None,\n    timestep: Optional[torch.Tensor] = None,\n    store_attn_map: bool = False,\n    model_config: Optional[Dict[str, Any]] = {},\n    last_attn_map: Optional[torch.Tensor] = None,\n    latent_sblora_weight=None,\n    condition_sblora_weight=None,\n):\n\n    using_cond = condition_latents is not None\n    residual = hidden_states\n    \n    train_partial_lora = model_config.get(\"train_partial_lora\", False)\n    if train_partial_lora:\n        train_partial_lora_layers = model_config.get(\"train_partial_lora_layers\", \"\")\n        activate_norm = activate_projmlp = activate_projout = True\n        \n        if \"norm\" not in train_partial_lora_layers:\n            activate_norm = False\n        if \"projmlp\" not in train_partial_lora_layers:\n            activate_projmlp = False\n        if \"projout\" not in train_partial_lora_layers:\n            activate_projout = False\n\n    with enable_lora((block.norm.linear,), activate_norm if train_partial_lora else model_config[\"sblock_lora\"], latent_sblora_weight=latent_sblora_weight):\n        # Modulation for single block\n        norm_hidden_states, gate = single_norm_forward(\n            block.norm, \n            hidden_states, \n            emb=temb,\n            delta_emb=delta_emb if use_text_mod else None,\n            delta_emb_cblock=delta_emb_cblock if use_text_mod else None,\n            delta_emb_mask=delta_emb_mask if use_text_mod else None,\n        )\n    with enable_lora((block.proj_mlp,), activate_projmlp if train_partial_lora else model_config[\"sblock_lora\"], latent_sblora_weight=latent_sblora_weight):\n        mlp_hidden_states = block.act_mlp(block.proj_mlp(norm_hidden_states))\n    if using_cond:\n        cond_lora_activate = model_config[\"use_condition_sblock_lora\"]\n        with enable_lora(\n            (block.norm.linear,), \n            dit_activated=activate_norm if train_partial_lora else not cond_lora_activate, cond_activated=cond_lora_activate, latent_sblora_weight=condition_sblora_weight\n        ):\n            residual_cond = condition_latents\n            norm_condition_latents, cond_gate = block.norm(condition_latents, emb=cond_temb)\n        with enable_lora(\n            (block.proj_mlp,), \n            dit_activated=activate_projmlp if train_partial_lora else not cond_lora_activate, cond_activated=cond_lora_activate, latent_sblora_weight=condition_sblora_weight\n        ):\n            mlp_cond_hidden_states = block.act_mlp(block.proj_mlp(norm_condition_latents))\n\n    attn_output = attn_forward(\n        block.attn,\n        model_config=model_config,\n        hidden_states=norm_hidden_states,\n        image_rotary_emb=image_rotary_emb,\n        last_attn_map=last_attn_map,\n        latent_height=latent_height,\n        store_attn_map=store_attn_map,\n        timestep=timestep,\n        latent_sblora_weight=latent_sblora_weight,\n        condition_sblora_weight=condition_sblora_weight,\n        **(\n            {\n                \"condition_latents\": norm_condition_latents,\n                \"cond_rotary_emb\": cond_rotary_emb if using_cond else None,\n                \"text_cond_mask\": text_cond_mask if using_cond else None,\n            }\n            if using_cond\n            else {}\n        ),\n    )\n    if using_cond:\n        attn_output, cond_attn_output = attn_output\n\n    with enable_lora((block.proj_out,), activate_projout if train_partial_lora else model_config[\"sblock_lora\"], latent_sblora_weight=latent_sblora_weight):\n        hidden_states = torch.cat([attn_output, mlp_hidden_states], dim=2)\n        # gate = (B, 1, 3072) or (B, S+, 3072)\n        hidden_states = gate * block.proj_out(hidden_states)\n        hidden_states = residual + hidden_states\n    if using_cond:\n        cond_lora_activate = model_config[\"use_condition_sblock_lora\"]\n        with enable_lora(\n            (block.proj_out,), \n            dit_activated=activate_projout if train_partial_lora else not cond_lora_activate, cond_activated=cond_lora_activate, latent_sblora_weight=condition_sblora_weight\n        ):\n            condition_latents = torch.cat([cond_attn_output, mlp_cond_hidden_states], dim=2)\n            cond_gate = cond_gate.unsqueeze(1)\n            condition_latents = cond_gate * block.proj_out(condition_latents)\n            condition_latents = residual_cond + condition_latents\n\n    if hidden_states.dtype == torch.float16:\n        hidden_states = hidden_states.clip(-65504, 65504)\n\n    return hidden_states if not using_cond else (hidden_states, condition_latents)\n"
  },
  {
    "path": "src/flux/condition.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport torch\nfrom typing import Optional, Union, List, Tuple\nfrom diffusers.pipelines import FluxPipeline\nfrom PIL import Image, ImageFilter\nimport numpy as np\nimport cv2\n\nfrom .pipeline_tools import encode_vae_images\n\ncondition_dict = {\n    \"depth\": 0,\n    \"canny\": 1,\n    \"subject\": 4,\n    \"coloring\": 6,\n    \"deblurring\": 7,\n    \"depth_pred\": 8,\n    \"fill\": 9,\n    \"sr\": 10,\n}\n\n\nclass Condition(object):\n    def __init__(\n        self,\n        condition_type: str,\n        raw_img: Union[Image.Image, torch.Tensor] = None,\n        condition: Union[Image.Image, torch.Tensor] = None,\n        mask=None,\n        position_delta=None,\n    ) -> None:\n        self.condition_type = condition_type\n        assert raw_img is not None or condition is not None\n        if raw_img is not None:\n            self.condition = self.get_condition(condition_type, raw_img)\n        else:\n            self.condition = condition\n        self.position_delta = position_delta\n        # TODO: Add mask support\n        assert mask is None, \"Mask not supported yet\"\n\n    def get_condition(\n        self, condition_type: str, raw_img: Union[Image.Image, torch.Tensor]\n    ) -> Union[Image.Image, torch.Tensor]:\n        \"\"\"\n        Returns the condition image.\n        \"\"\"\n        if condition_type == \"depth\":\n            from transformers import pipeline\n\n            depth_pipe = pipeline(\n                task=\"depth-estimation\",\n                model=\"LiheYoung/depth-anything-small-hf\",\n                device=\"cuda\",\n            )\n            source_image = raw_img.convert(\"RGB\")\n            condition_img = depth_pipe(source_image)[\"depth\"].convert(\"RGB\")\n            return condition_img\n        elif condition_type == \"canny\":\n            img = np.array(raw_img)\n            edges = cv2.Canny(img, 100, 200)\n            edges = Image.fromarray(edges).convert(\"RGB\")\n            return edges\n        elif condition_type == \"subject\":\n            return raw_img\n        elif condition_type == \"coloring\":\n            return raw_img.convert(\"L\").convert(\"RGB\")\n        elif condition_type == \"deblurring\":\n            condition_image = (\n                raw_img.convert(\"RGB\")\n                .filter(ImageFilter.GaussianBlur(10))\n                .convert(\"RGB\")\n            )\n            return condition_image\n        elif condition_type == \"fill\":\n            return raw_img.convert(\"RGB\")\n        return self.condition\n\n    @property\n    def type_id(self) -> int:\n        \"\"\"\n        Returns the type id of the condition.\n        \"\"\"\n        return condition_dict[self.condition_type]\n\n    @classmethod\n    def get_type_id(cls, condition_type: str) -> int:\n        \"\"\"\n        Returns the type id of the condition.\n        \"\"\"\n        return condition_dict[condition_type]\n\n    def encode(self, pipe: FluxPipeline) -> Tuple[torch.Tensor, torch.Tensor, int]:\n        \"\"\"\n        Encodes the condition into tokens, ids and type_id.\n        \"\"\"\n        if self.condition_type in [\n            \"depth\",\n            \"canny\",\n            \"subject\",\n            \"coloring\",\n            \"deblurring\",\n            \"depth_pred\",\n            \"fill\",\n            \"sr\",\n        ]:\n            tokens, ids = encode_vae_images(pipe, self.condition)\n        else:\n            raise NotImplementedError(\n                f\"Condition type {self.condition_type} not implemented\"\n            )\n        if self.position_delta is None and self.condition_type == \"subject\":\n            self.position_delta = [0, -self.condition.size[0] // 16]\n        if self.position_delta is not None:\n            ids[:, 1] += self.position_delta[0]\n            ids[:, 2] += self.position_delta[1]\n        print(f\"[Condition.encode] position_delta={self.position_delta}\")\n        type_id = torch.ones_like(ids[:, :1]) * self.type_id\n        return tokens, ids, type_id\n"
  },
  {
    "path": "src/flux/generate.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport torch\nimport yaml, os\nfrom PIL import Image\nfrom diffusers.pipelines import FluxPipeline\nfrom typing import List, Union, Optional, Dict, Any, Callable\nfrom src.flux.transformer import transformer_forward\nfrom src.flux.condition import Condition\n\nfrom diffusers.pipelines.flux.pipeline_flux import (\n    FluxPipelineOutput,\n    calculate_shift,\n    retrieve_timesteps,\n    np,\n)\nfrom src.flux.pipeline_tools import (\n    encode_prompt_with_clip_t5, tokenize_t5_prompt, clear_attn_maps, encode_vae_images\n)\n\nfrom src.flux.pipeline_tools import CustomFluxPipeline, load_modulation_adapter, decode_vae_images, \\\n    save_attention_maps, gather_attn_maps, clear_attn_maps, load_dit_lora, quantization\n\nfrom src.utils.data_utils import pad_to_square, pad_to_target, pil2tensor, get_closest_ratio, get_aspect_ratios\nfrom src.utils.modulation_utils import get_word_index, unpad_input_ids\n\ndef get_config(config_path: str = None):\n    config_path = config_path or os.environ.get(\"XFL_CONFIG\")\n    if not config_path:\n        return {}\n    with open(config_path, \"r\") as f:\n        config = yaml.safe_load(f)\n    return config\n\n\ndef prepare_params(\n    prompt: Union[str, List[str]] = None,\n    prompt_2: Optional[Union[str, List[str]]] = None,\n    height: Optional[int] = 512,\n    width: Optional[int] = 512,\n    num_inference_steps: int = 28,\n    timesteps: List[int] = None,\n    guidance_scale: float = 3.5,\n    num_images_per_prompt: Optional[int] = 1,\n    generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,\n    latents: Optional[torch.FloatTensor] = None,\n    prompt_embeds: Optional[torch.FloatTensor] = None,\n    pooled_prompt_embeds: Optional[torch.FloatTensor] = None,\n    output_type: Optional[str] = \"pil\",\n    return_dict: bool = True,\n    joint_attention_kwargs: Optional[Dict[str, Any]] = None,\n    callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None,\n    callback_on_step_end_tensor_inputs: List[str] = [\"latents\"],\n    max_sequence_length: int = 512,\n    verbose: bool = False,\n    **kwargs: dict,\n):\n    return (\n        prompt,\n        prompt_2,\n        height,\n        width,\n        num_inference_steps,\n        timesteps,\n        guidance_scale,\n        num_images_per_prompt,\n        generator,\n        latents,\n        prompt_embeds,\n        pooled_prompt_embeds,\n        output_type,\n        return_dict,\n        joint_attention_kwargs,\n        callback_on_step_end,\n        callback_on_step_end_tensor_inputs,\n        max_sequence_length,\n        verbose,\n    )\n\n\ndef seed_everything(seed: int = 42):\n    torch.backends.cudnn.deterministic = True\n    torch.manual_seed(seed)\n    np.random.seed(seed)\n\n\n@torch.no_grad()\ndef generate(\n    pipeline: FluxPipeline,\n    vae_conditions: List[Condition] = None,\n    config_path: str = None,\n    model_config: Optional[Dict[str, Any]] = {},\n    vae_condition_scale: float = 1.0,\n    default_lora: bool = False,\n    condition_pad_to: str = \"square\",\n    condition_size: int = 512,\n    text_cond_mask: Optional[torch.FloatTensor] = None,\n    delta_emb: Optional[torch.FloatTensor] = None,\n    delta_emb_pblock: Optional[torch.FloatTensor] = None,\n    delta_emb_mask: Optional[torch.FloatTensor] = None,\n    delta_start_ends = None,\n    condition_latents = None,\n    condition_ids = None,\n    mod_adapter = None,\n    store_attn_map: bool = False,\n    vae_skip_iter: str = None,\n    control_weight_lambda: str = None,\n    double_attention: bool = False,\n    single_attention: bool = False,\n    ip_scale: str = None,\n    use_latent_sblora_control: bool = False,\n    latent_sblora_scale: str = None,\n    use_condition_sblora_control: bool = False,\n    condition_sblora_scale: str = None,\n    idips = None,\n    device = torch.device('cuda'),\n    forward_hook_manager=None,\n    **params: dict,\n):\n    model_config = model_config or get_config(config_path).get(\"model\", {})\n\n    vae_skip_iter = model_config.get(\"vae_skip_iter\", vae_skip_iter)\n    double_attention = model_config.get(\"double_attention\", double_attention)\n    single_attention = model_config.get(\"single_attention\", single_attention)\n    control_weight_lambda = model_config.get(\"control_weight_lambda\", control_weight_lambda)\n    ip_scale = model_config.get(\"ip_scale\", ip_scale)\n    use_latent_sblora_control = model_config.get(\"use_latent_sblora_control\", use_latent_sblora_control)\n    use_condition_sblora_control = model_config.get(\"use_condition_sblora_control\", use_condition_sblora_control)\n\n    latent_sblora_scale = model_config.get(\"latent_sblora_scale\", latent_sblora_scale)\n    condition_sblora_scale = model_config.get(\"condition_sblora_scale\", condition_sblora_scale)\n\n    model_config[\"use_attention_double\"] = False\n    model_config[\"use_attention_single\"] = False\n    use_attention = False\n    \n    if idips is not None:\n        if control_weight_lambda != \"no\":\n            parts = control_weight_lambda.split(',')\n            new_parts = []\n            for part in parts:\n                if ':' in part:\n                    left, right = part.split(':')\n                    values = right.split('/')\n                    # 保存整体值\n                    global_value = values[0]\n                    id_value = values[1]\n                    ip_value = values[2]\n                    new_values = [global_value]\n                    for is_id in idips:\n                        if is_id:\n                            new_values.append(id_value)\n                        else:\n                            new_values.append(ip_value)\n                    new_part = f\"{left}:{('/'.join(new_values))}\"\n                    new_parts.append(new_part)\n                else:\n                    new_parts.append(part)\n            control_weight_lambda = ','.join(new_parts)\n\n    if vae_condition_scale != 1:\n        for name, module in pipeline.transformer.named_modules():\n            if not name.endswith(\".attn\"):\n                continue\n            module.c_factor = torch.ones(1, 1) * vae_condition_scale\n\n    # self = pipeline\n    (\n        prompt,\n        prompt_2,\n        height,\n        width,\n        num_inference_steps,\n        timesteps,\n        guidance_scale,\n        num_images_per_prompt,\n        generator,\n        latents,\n        prompt_embeds,\n        pooled_prompt_embeds,\n        output_type,\n        return_dict,\n        joint_attention_kwargs,\n        callback_on_step_end,\n        callback_on_step_end_tensor_inputs,\n        max_sequence_length,\n        verbose,\n    ) = prepare_params(**params)\n\n    height = height or pipeline.default_sample_size * pipeline.vae_scale_factor\n    width = width or pipeline.default_sample_size * pipeline.vae_scale_factor\n\n    # 1. Check inputs. Raise error if not correct\n    pipeline.check_inputs(\n        prompt,\n        prompt_2,\n        height,\n        width,\n        prompt_embeds=prompt_embeds,\n        pooled_prompt_embeds=pooled_prompt_embeds,\n        callback_on_step_end_tensor_inputs=callback_on_step_end_tensor_inputs,\n        max_sequence_length=max_sequence_length,\n    )\n\n    pipeline._guidance_scale = guidance_scale\n    pipeline._joint_attention_kwargs = joint_attention_kwargs\n    pipeline._interrupt = False\n\n    # 2. Define call parameters\n    if prompt is not None and isinstance(prompt, str):\n        batch_size = 1\n    elif prompt is not None and isinstance(prompt, list):\n        batch_size = len(prompt)\n    else:\n        batch_size = prompt_embeds.shape[0]\n\n    # device = self._execution_device\n\n    lora_scale = (\n        pipeline.joint_attention_kwargs.get(\"scale\", None)\n        if pipeline.joint_attention_kwargs is not None\n        else None\n    )\n    (\n        t5_prompt_embeds,\n        pooled_prompt_embeds,\n        text_ids,\n    ) = encode_prompt_with_clip_t5(\n        self=pipeline,\n        prompt=\"\" if pipeline.text_encoder_2 is None else prompt,\n        prompt_2=None,\n        prompt_embeds=prompt_embeds,\n        pooled_prompt_embeds=pooled_prompt_embeds,\n        device=device,\n        num_images_per_prompt=num_images_per_prompt,\n        max_sequence_length=max_sequence_length,\n        lora_scale=lora_scale,\n    )\n\n    # 4. Prepare latent variables\n    num_channels_latents = pipeline.transformer.config.in_channels // 4\n    latents, latent_image_ids = pipeline.prepare_latents(\n        batch_size * num_images_per_prompt,\n        num_channels_latents,\n        height,\n        width,\n        pooled_prompt_embeds.dtype,\n        device,\n        generator,\n        latents,\n    )\n\n    latent_height = height // 16\n\n    # 5. Prepare timesteps\n    sigmas = np.linspace(1.0, 1 / num_inference_steps, num_inference_steps)\n    image_seq_len = latents.shape[1]\n    mu = calculate_shift(\n        image_seq_len,\n        pipeline.scheduler.config.base_image_seq_len,\n        pipeline.scheduler.config.max_image_seq_len,\n        pipeline.scheduler.config.base_shift,\n        pipeline.scheduler.config.max_shift,\n    )\n    timesteps, num_inference_steps = retrieve_timesteps(\n        pipeline.scheduler,\n        num_inference_steps,\n        device,\n        timesteps,\n        sigmas,\n        mu=mu,\n    )\n    num_warmup_steps = max(\n        len(timesteps) - num_inference_steps * pipeline.scheduler.order, 0\n    )\n    pipeline._num_timesteps = len(timesteps)\n\n    attn_map = None\n\n    # 6. Denoising loop\n    with pipeline.progress_bar(total=num_inference_steps) as progress_bar:\n        totalsteps = timesteps[0]\n        if control_weight_lambda is not None:\n            print(\"control_weight_lambda\", control_weight_lambda)\n            control_weight_lambda_schedule = []\n            for scale_str in control_weight_lambda.split(','):\n                time_region, scale = scale_str.split(':')\n                start, end = time_region.split('-')\n                scales = [float(s) for s in scale.split('/')]\n                control_weight_lambda_schedule.append([(1-float(start))*totalsteps, (1-float(end))*totalsteps, scales])\n\n        if ip_scale is not None:\n            print(\"ip_scale\", ip_scale)\n            ip_scale_schedule = []\n            for scale_str in ip_scale.split(','):\n                time_region, scale = scale_str.split(':')\n                start, end = time_region.split('-')\n                ip_scale_schedule.append([(1-float(start))*totalsteps, (1-float(end))*totalsteps, float(scale)])\n\n        if use_latent_sblora_control:\n            if latent_sblora_scale is not None:\n                print(\"latent_sblora_scale\", latent_sblora_scale)\n                latent_sblora_scale_schedule = []\n                for scale_str in latent_sblora_scale.split(','):\n                    time_region, scale = scale_str.split(':')\n                    start, end = time_region.split('-')\n                    latent_sblora_scale_schedule.append([(1-float(start))*totalsteps, (1-float(end))*totalsteps, float(scale)])\n        \n        if use_condition_sblora_control:\n            if condition_sblora_scale is not None:\n                print(\"condition_sblora_scale\", condition_sblora_scale)\n                condition_sblora_scale_schedule = []\n                for scale_str in condition_sblora_scale.split(','):\n                    time_region, scale = scale_str.split(':')\n                    start, end = time_region.split('-')\n                    condition_sblora_scale_schedule.append([(1-float(start))*totalsteps, (1-float(end))*totalsteps, float(scale)])\n\n\n        if vae_skip_iter is not None:\n            print(\"vae_skip_iter\", vae_skip_iter)\n            vae_skip_iter_schedule = []\n            for scale_str in vae_skip_iter.split(','):\n                time_region, scale = scale_str.split(':')\n                start, end = time_region.split('-')\n                vae_skip_iter_schedule.append([(1-float(start))*totalsteps, (1-float(end))*totalsteps, float(scale)])\n\n        if control_weight_lambda is not None and attn_map is None:\n            batch_size = latents.shape[0]\n            latent_width = latents.shape[1]//latent_height\n            attn_map = torch.ones(batch_size, latent_height, latent_width, 128, device=latents.device, dtype=torch.bfloat16)\n            print(\"contol_weight_only\", attn_map.shape)\n\n        pipeline.scheduler.set_begin_index(0)\n        pipeline.scheduler._init_step_index(0)\n        for i, t in enumerate(timesteps):\n            \n            if control_weight_lambda is not None:\n                cur_control_weight_lambda = []\n                for start, end, scale in control_weight_lambda_schedule:\n                    if t <= start and t >= end:\n                        cur_control_weight_lambda = scale\n                        break\n                print(f\"timestep:{t}, cur_control_weight_lambda:{cur_control_weight_lambda}\")\n               \n                if cur_control_weight_lambda:\n                    model_config[\"use_attention_single\"] = True\n                    use_attention = True\n                    model_config[\"use_atten_lambda\"] = cur_control_weight_lambda  \n                else:\n                    model_config[\"use_attention_single\"] = False\n                    use_attention = False\n                     \n            if pipeline.interrupt:\n                continue\n\n            if isinstance(delta_emb, list):\n                cur_delta_emb = delta_emb[i]\n                cur_delta_emb_pblock = delta_emb_pblock[i]\n                cur_delta_emb_mask = delta_emb_mask[i]\n            else:\n                cur_delta_emb = delta_emb\n                cur_delta_emb_pblock = delta_emb_pblock\n                cur_delta_emb_mask = delta_emb_mask\n\n\n            # broadcast to batch dimension in a way that's compatible with ONNX/Core ML\n            timestep = t.expand(latents.shape[0]).to(latents.dtype) / 1000\n            prompt_embeds = t5_prompt_embeds\n            text_ids = torch.zeros(prompt_embeds.shape[1], 3).to(device=device, dtype=prompt_embeds.dtype)\n\n            # handle guidance\n            if pipeline.transformer.config.guidance_embeds:\n                guidance = torch.tensor([guidance_scale], device=device)\n                guidance = guidance.expand(latents.shape[0])\n            else:\n                guidance = None\n            pipeline.transformer.enable_lora()\n            \n            lora_weight  = 1\n            if ip_scale is not None:\n                lora_weight = 0\n                for start, end, scale in ip_scale_schedule:\n                    if t <= start and t >= end:\n                        lora_weight = scale\n                        break\n                if lora_weight != 1: print(f\"timestep:{t}, lora_weights:{lora_weight}\")\n            \n            latent_sblora_weight = None\n            if use_latent_sblora_control:\n                if latent_sblora_scale is not None:\n                    latent_sblora_weight = 0\n                    for start, end, scale in latent_sblora_scale_schedule:\n                        if t <= start and t >= end:\n                            latent_sblora_weight = scale\n                            break\n                    if latent_sblora_weight != 1: print(f\"timestep:{t}, latent_sblora_weight:{latent_sblora_weight}\")\n            \n            condition_sblora_weight = None\n            if use_condition_sblora_control:\n                if condition_sblora_scale is not None:\n                    condition_sblora_weight = 0\n                    for start, end, scale in condition_sblora_scale_schedule:\n                        if t <= start and t >= end:\n                            condition_sblora_weight = scale\n                            break\n                    if condition_sblora_weight !=1: print(f\"timestep:{t}, condition_sblora_weight:{condition_sblora_weight}\")\n\n            vae_skip_iter_t = False\n            if vae_skip_iter is not None:\n                for start, end, scale in vae_skip_iter_schedule:\n                    if t <= start and t >= end:\n                        vae_skip_iter_t = bool(scale)\n                        break\n                if vae_skip_iter_t:\n                    print(f\"timestep:{t}, skip vae:{vae_skip_iter_t}\")               \n\n            if forward_hook_manager is not None and forward_hook_manager.use_lower_vram is False:\n                pipeline.transformer = forward_hook_manager.model_to_cuda(pipeline.transformer)\n            noise_pred = transformer_forward(\n                pipeline.transformer,\n                model_config=model_config,\n                # Inputs of the condition (new feature)\n                text_cond_mask=text_cond_mask,\n                delta_emb=cur_delta_emb,\n                delta_emb_pblock=cur_delta_emb_pblock,\n                delta_emb_mask=cur_delta_emb_mask,\n                delta_start_ends=delta_start_ends,\n                condition_latents=None if vae_skip_iter_t else condition_latents,\n                condition_ids=None if vae_skip_iter_t else condition_ids,\n                condition_type_ids=None,\n                # Inputs to the original transformer\n                hidden_states=latents,\n                # YiYi notes: divide it by 1000 for now because we scale it by 1000 in the transforme rmodel (we should not keep it but I want to keep the inputs same for the model for testing)\n                timestep=timestep,\n                guidance=guidance,\n                pooled_projections=pooled_prompt_embeds,\n                encoder_hidden_states=prompt_embeds,\n                txt_ids=text_ids,\n                img_ids=latent_image_ids,\n                joint_attention_kwargs={'scale': lora_weight, \"latent_sblora_weight\": latent_sblora_weight, \"condition_sblora_weight\": condition_sblora_weight}, \n                store_attn_map=use_attention,\n                last_attn_map=attn_map if cur_control_weight_lambda else None,\n                use_text_mod=model_config[\"modulation\"][\"use_text_mod\"],\n                use_img_mod=model_config[\"modulation\"][\"use_img_mod\"],\n                mod_adapter=mod_adapter,\n                latent_height=latent_height,\n                return_dict=False,\n            )[0]\n\n            if use_attention:\n                attn_maps, _ = gather_attn_maps(pipeline.transformer, clear=True)\n\n            # compute the previous noisy sample x_t -> x_t-1\n            latents_dtype = latents.dtype\n            latents = pipeline.scheduler.step(noise_pred, t, latents, return_dict=False)[0]\n\n            if latents.dtype != latents_dtype:\n                if torch.backends.mps.is_available():\n                    # some platforms (eg. apple mps) misbehave due to a pytorch bug: https://github.com/pytorch/pytorch/pull/99272\n                    latents = latents.to(latents_dtype)\n\n            if callback_on_step_end is not None:\n                callback_kwargs = {}\n                for k in callback_on_step_end_tensor_inputs:\n                    callback_kwargs[k] = locals()[k]\n                callback_outputs = callback_on_step_end(pipeline, i, t, callback_kwargs)\n\n                latents = callback_outputs.pop(\"latents\", latents)\n                prompt_embeds = callback_outputs.pop(\"prompt_embeds\", prompt_embeds)\n\n            # call the callback, if provided\n            if i == len(timesteps) - 1 or (\n                (i + 1) > num_warmup_steps and (i + 1) % pipeline.scheduler.order == 0\n            ):\n                progress_bar.update()\n\n    if output_type == \"latent\":\n        image = latents\n\n    else:\n        latents = pipeline._unpack_latents(latents, height, width, pipeline.vae_scale_factor)\n        latents = (\n            latents / pipeline.vae.config.scaling_factor\n        ) + pipeline.vae.config.shift_factor\n        image = pipeline.vae.decode(latents, return_dict=False)[0]\n        image = pipeline.image_processor.postprocess(image, output_type=output_type)\n\n    # Offload all models\n    pipeline.maybe_free_model_hooks()\n\n    pipeline.transformer.enable_lora()\n\n    if vae_condition_scale != 1:\n        for name, module in pipeline.transformer.named_modules():\n            if not name.endswith(\".attn\"):\n                continue\n            del module.c_factor\n\n    if not return_dict:\n        return (image,)\n\n    return FluxPipelineOutput(images=image)\n\n\n@torch.no_grad()\ndef generate_from_test_sample(\n    test_sample, pipe, config, \n    num_images=1, \n    vae_skip_iter: str = None, \n    target_height: int = None,\n    target_width: int = None,\n    seed: int = 42,\n    control_weight_lambda: str = None,\n    double_attention: bool = False,\n    single_attention: bool = False,\n    ip_scale: str = None,\n    use_latent_sblora_control: bool = False,\n    latent_sblora_scale: str = None,\n    use_condition_sblora_control: bool = False,\n    condition_sblora_scale: str = None,\n    use_idip = False,\n    device = torch.device('cuda'),\n    forward_hook_manager=None,\n    num_inference_steps: int = 28,\n    **kargs\n):\n    target_size = config[\"train\"][\"dataset\"][\"val_target_size\"]\n    condition_size = config[\"train\"][\"dataset\"].get(\"val_condition_size\", target_size//2)\n    condition_pad_to = config[\"train\"][\"dataset\"][\"condition_pad_to\"]\n    pos_offset_type = config[\"model\"].get(\"pos_offset_type\", \"width\")\n    seed = config[\"model\"].get(\"seed\", seed)\n\n    # device = pipe._execution_device\n\n    condition_imgs = test_sample['input_images']\n    position_delta = test_sample['position_delta']\n    prompt = test_sample['prompt']\n    original_image = test_sample.get('original_image', None)\n    condition_type = test_sample.get('condition_type', \"subject\")\n    modulation_input = test_sample.get('modulation', None)\n\n    delta_start_ends = None\n    condition_latents = condition_ids = None\n    text_cond_mask = None\n    \n    delta_embs = None\n    delta_embs_pblock = None\n    delta_embs_mask = None\n\n    try:\n        max_length = config[\"model\"][\"modulation\"][\"max_text_len\"]\n    except Exception as e:\n        print(e)\n        max_length = 512\n\n    if modulation_input is None or len(modulation_input) == 0:\n        delta_emb = delta_emb_pblock = delta_emb_mask = None\n    else:\n        dtype = torch.bfloat16\n        batch_size = 1\n        N = config[\"model\"][\"modulation\"].get(\"per_block_adapter_single_blocks\", 0) + 19\n        guidance = torch.tensor([3.5]).to(device).expand(batch_size)\n        out_dim = config[\"model\"][\"modulation\"][\"out_dim\"]\n\n        tar_text_inputs = tokenize_t5_prompt(pipe, prompt, max_length)\n        tar_padding_mask = tar_text_inputs.attention_mask.to(device).bool()\n        tar_tokens = tar_text_inputs.input_ids.to(device)\n        if config[\"model\"][\"modulation\"][\"eos_exclude\"]:\n            tar_padding_mask[tar_tokens == 1] = False\n\n        def get_start_end_by_pompt_matching(src_prompts, tar_prompts):\n            text_cond_mask = torch.zeros(batch_size, max_length, device=device, dtype=torch.bool)\n            tar_prompt_input_ids = tokenize_t5_prompt(pipe, tar_prompts, max_length).input_ids\n            src_prompt_count = 1\n            start_ends = []\n            for i, (src_prompt, tar_prompt, tar_prompt_tokens) in enumerate(zip(src_prompts, tar_prompts, tar_prompt_input_ids)):\n                try:\n                    tar_start, tar_end = get_word_index(pipe, tar_prompt, tar_prompt_tokens, src_prompt, src_prompt_count, max_length, verbose=False)\n                    start_ends.append([tar_start, tar_end])\n                    text_cond_mask[i, tar_start:tar_end] = True\n                except Exception as e:\n                    print(e)\n            return start_ends, text_cond_mask\n\n        def encode_mod_image(pil_images):\n            if config[\"model\"][\"modulation\"][\"use_dit\"]:\n                raise NotImplementedError()\n            else:\n                pil_images = [pad_to_square(img).resize((224, 224)) for img in pil_images]\n                if config[\"model\"][\"modulation\"][\"use_vae\"]:\n                    raise NotImplementedError()\n                else:\n                    clip_pixel_values = pipe.clip_processor(\n                        text=None, images=pil_images, do_resize=False, do_center_crop=False, return_tensors=\"pt\",\n                    ).pixel_values.to(dtype=dtype, device=device)\n                    clip_outputs = pipe.clip_model(clip_pixel_values, output_hidden_states=True, interpolate_pos_encoding=True, return_dict=True)\n                    return clip_outputs\n\n        def rgba_to_white_background(input_path, background=(255,255,255)):\n            with Image.open(input_path).convert(\"RGBA\") as img:\n                img_np = np.array(img)\n                alpha = img_np[:, :, 3] / 255.0  # 归一化Alpha通道[3](@ref)\n                rgb = img_np[:, :, :3].astype(float)  # 提取RGB通道\n                \n                background_np = np.full_like(rgb, background, dtype=float)  # 根据参数生成背景[7](@ref)\n                \n                # 混合计算：前景色*alpha + 背景色*(1-alpha)\n                result_np = rgb * alpha[..., np.newaxis] + \\\n                            background_np * (1 - alpha[..., np.newaxis])\n                \n                result = Image.fromarray(result_np.astype(np.uint8), \"RGB\")\n                return result\n        def get_mod_emb(modulation_input, timestep):\n            delta_emb = torch.zeros((batch_size, max_length, out_dim), dtype=dtype, device=device)\n            delta_emb_pblock = torch.zeros((batch_size, max_length, N, out_dim), dtype=dtype, device=device)\n            delta_emb_mask = torch.zeros((batch_size, max_length), dtype=torch.bool, device=device)\n            delta_start_ends = None\n            condition_latents = condition_ids = None\n            text_cond_mask = None\n\n            if modulation_input[0][\"type\"] == \"adapter\":\n                num_inputs = len(modulation_input[0][\"src_inputs\"])\n                src_prompts = [x[\"caption\"] for x in modulation_input[0][\"src_inputs\"]]\n                src_text_inputs = tokenize_t5_prompt(pipe, src_prompts, max_length)\n                src_input_ids = unpad_input_ids(src_text_inputs.input_ids, src_text_inputs.attention_mask)\n                tar_input_ids = unpad_input_ids(tar_text_inputs.input_ids, tar_text_inputs.attention_mask)\n                src_prompt_embeds = pipe._get_t5_prompt_embeds(prompt=src_prompts, max_sequence_length=max_length, device=device) # (M, 512, 4096)\n                \n                pil_images = [rgba_to_white_background(x[\"image_path\"]) for x in modulation_input[0][\"src_inputs\"]]\n\n                src_ds_scales = [x.get(\"downsample_scale\", 1.0) for x in modulation_input[0][\"src_inputs\"]]\n                resized_pil_images = []\n                for img, ds_scale in zip(pil_images, src_ds_scales):\n                    img = pad_to_square(img)\n                    if ds_scale < 1.0:\n                        assert ds_scale > 0\n                        img = img.resize((int(224 * ds_scale), int(224 * ds_scale))).resize((224, 224))\n                    resized_pil_images.append(img)\n                pil_images = resized_pil_images\n                \n                img_encoded = encode_mod_image(pil_images)\n                delta_start_ends = []\n                text_cond_mask = torch.zeros(num_inputs, max_length, device=device, dtype=torch.bool)\n                if config[\"model\"][\"modulation\"][\"pass_vae\"]:\n                    pil_images = [pad_to_square(img).resize((condition_size, condition_size)) for img in pil_images]\n                    with torch.no_grad():\n                        batch_tensor = torch.stack([pil2tensor(x) for x in pil_images])\n                        x_0, img_ids = encode_vae_images(pipe, batch_tensor) # (N, 256, 64)\n\n                    condition_latents = x_0.clone().detach().reshape(1, -1, 64) # (1, N256, 64)\n                    condition_ids = img_ids.clone().detach()\n                    condition_ids = condition_ids.unsqueeze(0).repeat_interleave(num_inputs, dim=0) # (N, 256, 3)\n                    for i in range(num_inputs):\n                        condition_ids[i, :, 1] += 0 if pos_offset_type == \"width\" else -(batch_tensor.shape[-1]//16) * (i + 1)\n                        condition_ids[i, :, 2] += -(batch_tensor.shape[-1]//16) * (i + 1)\n                    condition_ids = condition_ids.reshape(-1, 3) # (N256, 3)\n\n                if config[\"model\"][\"modulation\"][\"use_dit\"]:\n                    raise NotImplementedError()\n                else:\n                    src_delta_embs = [] # [(512, 3072)]\n                    src_delta_emb_pblock = []\n                    for i in range(num_inputs):\n                        if isinstance(img_encoded, dict):\n                            _src_clip_outputs = {}\n                            for key in img_encoded:\n                                if torch.is_tensor(img_encoded[key]):\n                                    _src_clip_outputs[key] = img_encoded[key][i:i+1]\n                                else:\n                                    _src_clip_outputs[key] = [x[i:i+1] for x in img_encoded[key]]\n                            _img_encoded = _src_clip_outputs\n                        else:\n                            _img_encoded = img_encoded[i:i+1]\n                    \n                        x1, x2 = pipe.modulation_adapters[0](timestep, src_prompt_embeds[i:i+1], _img_encoded)\n                        src_delta_embs.append(x1[0]) # (512, 3072)\n                        src_delta_emb_pblock.append(x2[0]) # (512, N, 3072)\n\n                for input_args in modulation_input[0][\"use_words\"]:\n                    src_word_count = 1\n                    if len(input_args) == 3:\n                        src_input_index, src_word, tar_word = input_args\n                        tar_word_count = 1\n                    else:\n                        src_input_index, src_word, tar_word, tar_word_count = input_args[:4]\n                    src_prompt = src_prompts[src_input_index]\n                    tar_prompt = prompt\n\n                    src_start, src_end = get_word_index(pipe, src_prompt, src_input_ids[src_input_index], src_word, src_word_count, max_length, verbose=False)\n                    tar_start, tar_end = get_word_index(pipe, tar_prompt, tar_input_ids[0], tar_word, tar_word_count, max_length, verbose=False)\n                    if delta_emb is not None:\n                        delta_emb[:, tar_start:tar_end] = src_delta_embs[src_input_index][src_start:src_end] # (B, 512, 3072)\n                    if delta_emb_pblock is not None:\n                        delta_emb_pblock[:, tar_start:tar_end] = src_delta_emb_pblock[src_input_index][src_start:src_end] # (B, 512, N, 3072)\n                    delta_emb_mask[:, tar_start:tar_end] = True\n                    text_cond_mask[src_input_index, tar_start:tar_end] = True\n                    delta_start_ends.append([0, src_input_index, src_start, src_end, tar_start, tar_end])\n                text_cond_mask = text_cond_mask.transpose(0, 1).unsqueeze(0)\n\n            else:\n                raise NotImplementedError()\n            return delta_emb, delta_emb_pblock, delta_emb_mask, \\\n                text_cond_mask, delta_start_ends, condition_latents, condition_ids\n    \n    # num_inference_steps = 28 # FIXME: harcoded here\n    num_channels_latents = pipe.transformer.config.in_channels // 4\n\n    # set timesteps\n    sigmas = np.linspace(1.0, 1 / num_inference_steps, num_inference_steps)\n    mu = calculate_shift(\n        num_channels_latents,\n        pipe.scheduler.config.base_image_seq_len,\n        pipe.scheduler.config.max_image_seq_len,\n        pipe.scheduler.config.base_shift,\n        pipe.scheduler.config.max_shift,\n    )\n    timesteps, num_inference_steps = retrieve_timesteps(\n        pipe.scheduler,\n        num_inference_steps,\n        device,\n        None,\n        sigmas,\n        mu=mu,\n    )\n\n    if modulation_input is not None:\n        delta_embs = []\n        delta_embs_pblock = []\n        delta_embs_mask = []\n        for i, t in enumerate(timesteps):\n            t = t.expand(1).to(torch.bfloat16) / 1000\n            (\n                delta_emb, delta_emb_pblock, delta_emb_mask, \n                text_cond_mask, delta_start_ends, \n                condition_latents, condition_ids\n            ) = get_mod_emb(modulation_input, t)\n            delta_embs.append(delta_emb)\n            delta_embs_pblock.append(delta_emb_pblock)\n            delta_embs_mask.append(delta_emb_mask)\n\n    if original_image is not None:\n        raise NotImplementedError()\n        (target_height, target_width), closest_ratio = get_closest_ratio(original_image.height, original_image.width, train_aspect_ratios)\n    elif modulation_input is None or len(modulation_input) == 0:\n        delta_emb = delta_emb_pblock = delta_emb_mask = None\n    else:\n        for i, t in enumerate(timesteps):\n            t = t.expand(1).to(torch.bfloat16) / 1000\n            (\n                delta_emb, delta_emb_pblock, delta_emb_mask, \n                text_cond_mask, delta_start_ends, \n                condition_latents, condition_ids\n            ) = get_mod_emb(modulation_input, t)\n            delta_embs.append(delta_emb)\n            delta_embs_pblock.append(delta_emb_pblock)\n            delta_embs_mask.append(delta_emb_mask)\n\n    if target_height is None or target_width is None:\n        target_height = target_width = target_size\n\n    if condition_pad_to == \"square\":\n        condition_imgs = [pad_to_square(x) for x in condition_imgs]\n    elif condition_pad_to == \"target\":\n        condition_imgs = [pad_to_target(x, (target_size, target_size)) for x in condition_imgs]\n    condition_imgs = [x.resize((condition_size, condition_size)).convert(\"RGB\") for x in condition_imgs]\n    # TODO: fix position_delta\n    conditions = [\n        Condition(\n            condition_type=condition_type,\n            condition=x,\n            position_delta=position_delta,\n        ) for x in condition_imgs\n    ]\n    # vlm_images = condition_imgs if config[\"model\"][\"use_vlm\"] else []\n\n    use_perblock_adapter = False\n    try:\n        if config[\"model\"][\"modulation\"][\"use_perblock_adapter\"]:\n            use_perblock_adapter = True\n    except Exception as e:\n        pass\n\n    results = []\n    for i in range(num_images):\n        clear_attn_maps(pipe.transformer)\n        generator = torch.Generator(device=device)\n        generator.manual_seed(seed + i)\n        if modulation_input is None or len(modulation_input) == 0:\n            idips = None\n        else:\n            idips = [\"human\" in p[\"image_path\"] for p in modulation_input[0][\"src_inputs\"]]\n            if len(modulation_input[0][\"use_words\"][0])==5:\n                print(\"use idips in use_words\")\n                idips = [x[-1] for x in modulation_input[0][\"use_words\"]]\n        result_img = generate(\n            pipe,\n            prompt=prompt,\n            max_sequence_length=max_length,\n            vae_conditions=conditions,\n            generator=generator,\n            model_config=config[\"model\"],\n            height=target_height,\n            width=target_width,\n            condition_pad_to=condition_pad_to,\n            condition_size=condition_size,\n            text_cond_mask=text_cond_mask,\n            delta_emb=delta_embs,\n            delta_emb_pblock=delta_embs_pblock if use_perblock_adapter else None,\n            delta_emb_mask=delta_embs_mask,\n            delta_start_ends=delta_start_ends,\n            condition_latents=condition_latents,\n            condition_ids=condition_ids,\n            mod_adapter=pipe.modulation_adapters[0] if config[\"model\"][\"modulation\"][\"use_dit\"] else None,\n            vae_skip_iter=vae_skip_iter,\n            control_weight_lambda=control_weight_lambda,\n            double_attention=double_attention,\n            single_attention=single_attention,\n            ip_scale=ip_scale,\n            use_latent_sblora_control=use_latent_sblora_control,\n            latent_sblora_scale=latent_sblora_scale,\n            use_condition_sblora_control=use_condition_sblora_control,\n            condition_sblora_scale=condition_sblora_scale,\n            idips=idips if use_idip else None,\n            device=device,\n            forward_hook_manager=forward_hook_manager,\n            num_inference_steps=num_inference_steps,\n            **kargs,\n        ).images[0]\n\n        final_image = result_img\n        results.append(final_image)\n\n    if num_images == 1:\n        return results[0]\n    return results"
  },
  {
    "path": "src/flux/lora_controller.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom peft.tuners.tuners_utils import BaseTunerLayer\nfrom typing import List, Any, Optional, Type\n\n\nclass enable_lora:\n    def __init__(self, lora_modules: List[BaseTunerLayer], dit_activated: bool, cond_activated: bool=False, latent_sblora_weight: float=None, condition_sblora_weight: float=None) -> None:\n        self.dit_activated = dit_activated\n        self.cond_activated = cond_activated\n        self.latent_sblora_weight = latent_sblora_weight\n        self.condition_sblora_weight = condition_sblora_weight\n        # assert not (dit_activated and cond_activated)\n        \n        self.lora_modules: List[BaseTunerLayer] = [\n            each for each in lora_modules if isinstance(each, BaseTunerLayer)\n        ]\n\n        self.scales = [\n            {\n                active_adapter: lora_module.scaling[active_adapter] if active_adapter in lora_module.scaling else 1\n                for active_adapter in lora_module.active_adapters\n            } for lora_module in self.lora_modules\n        ]\n\n\n    def __enter__(self) -> None:\n        for i, lora_module in enumerate(self.lora_modules):\n            if not isinstance(lora_module, BaseTunerLayer):\n                continue\n            for active_adapter in lora_module.active_adapters:\n                if active_adapter == \"default\":\n                    if self.dit_activated:\n                        lora_module.scaling[active_adapter] = self.scales[0][\"default\"] if self.latent_sblora_weight is None else self.latent_sblora_weight\n                    else:\n                        lora_module.scaling[active_adapter] = 0\n                else:\n                    assert active_adapter == \"condition\"\n                    if self.cond_activated:\n                        lora_module.scaling[active_adapter] = self.scales[0][\"condition\"] if self.condition_sblora_weight is None else self.condition_sblora_weight\n                    else:\n                        lora_module.scaling[active_adapter] = 0\n\n    def __exit__(\n        self,\n        exc_type: Optional[Type[BaseException]],\n        exc_val: Optional[BaseException],\n        exc_tb: Optional[Any],\n    ) -> None:\n        for i, lora_module in enumerate(self.lora_modules):\n            if not isinstance(lora_module, BaseTunerLayer):\n                continue\n            for active_adapter in lora_module.active_adapters:\n                lora_module.scaling[active_adapter] = self.scales[i][active_adapter]\n        \nclass set_lora_scale:\n    def __init__(self, lora_modules: List[BaseTunerLayer], scale: float) -> None:\n        self.lora_modules: List[BaseTunerLayer] = [\n            each for each in lora_modules if isinstance(each, BaseTunerLayer)\n        ]\n        self.scales = [\n            {\n                active_adapter: lora_module.scaling[active_adapter]\n                for active_adapter in lora_module.active_adapters\n            }\n            for lora_module in self.lora_modules\n        ]\n        self.scale = scale\n\n    def __enter__(self) -> None:\n        for lora_module in self.lora_modules:\n            if not isinstance(lora_module, BaseTunerLayer):\n                continue\n            lora_module.scale_layer(self.scale)\n\n    def __exit__(\n        self,\n        exc_type: Optional[Type[BaseException]],\n        exc_val: Optional[BaseException],\n        exc_tb: Optional[Any],\n    ) -> None:\n        for i, lora_module in enumerate(self.lora_modules):\n            if not isinstance(lora_module, BaseTunerLayer):\n                continue\n            for active_adapter in lora_module.active_adapters:\n                lora_module.scaling[active_adapter] = self.scales[i][active_adapter]\n"
  },
  {
    "path": "src/flux/pipeline_tools.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport time\nimport inspect\nfrom typing import Any, Callable, Dict, List, Optional, Union\nimport os\nimport torch\nfrom torch import Tensor\nimport torch.nn.functional as F\nfrom diffusers.pipelines import FluxPipeline\nfrom diffusers.utils import logging\nfrom diffusers.loaders import TextualInversionLoaderMixin\nfrom diffusers.pipelines.flux.pipeline_flux import FluxLoraLoaderMixin\nfrom diffusers.models.transformers.transformer_flux import (\n    USE_PEFT_BACKEND,\n    scale_lora_layers,\n    unscale_lora_layers,\n    logger,\n)\nfrom diffusers import FluxTransformer2DModel, GGUFQuantizationConfig, BitsAndBytesConfig\nfrom torchvision.transforms import ToPILImage\nfrom peft.tuners.tuners_utils import BaseTunerLayer\nfrom optimum.quanto import (\n    freeze, quantize, QTensor, qfloat8, qint8, qint4, qint2,\n)\nimport re\nimport safetensors\nfrom src.adapters.mod_adapters import CLIPModAdapter\nfrom peft import LoraConfig, set_peft_model_state_dict\nfrom transformers import CLIPProcessor, CLIPModel, CLIPVisionModelWithProjection, CLIPVisionModel\n\nfrom safetensors.torch import load_file\n\nfrom diffusers.loaders.single_file_utils import (\n    create_diffusers_clip_model_from_ldm,\n    create_diffusers_t5_model_from_checkpoint,\n    convert_ldm_vae_checkpoint,\n)\n\nfrom transformers import T5EncoderModel, CLIPTextModel, AutoConfig, T5Config, AutoTokenizer, AutoModelForSeq2SeqLM\n\nimport json\n\ndef encode_vae_images(pipeline: FluxPipeline, images: Tensor):\n    images = pipeline.image_processor.preprocess(images)\n    images = images.to(pipeline.device).to(pipeline.dtype)\n    images = pipeline.vae.encode(images).latent_dist.sample()\n    images = (\n        images - pipeline.vae.config.shift_factor\n    ) * pipeline.vae.config.scaling_factor\n    images_tokens = pipeline._pack_latents(images, *images.shape)\n    images_ids = pipeline._prepare_latent_image_ids(\n        images.shape[0],\n        images.shape[2],\n        images.shape[3],\n        pipeline.device,\n        pipeline.dtype,\n    )\n    if images_tokens.shape[1] != images_ids.shape[0]:\n        images_ids = pipeline._prepare_latent_image_ids(\n            images.shape[0],\n            images.shape[2] // 2,\n            images.shape[3] // 2,\n            pipeline.device,\n            pipeline.dtype,\n        )\n    return images_tokens, images_ids\n\ndef decode_vae_images(pipeline: FluxPipeline, latents: Tensor, height, width, output_type: Optional[str] = \"pil\"):\n    latents = pipeline._unpack_latents(latents, height, width, pipeline.vae_scale_factor)\n    latents = (latents / pipeline.vae.config.scaling_factor) + pipeline.vae.config.shift_factor\n    image = pipeline.vae.decode(latents, return_dict=False)[0]\n    return pipeline.image_processor.postprocess(image, output_type=output_type)\n\n\ndef _get_clip_prompt_embeds(\n    self,\n    prompt: Union[str, List[str]],\n    num_images_per_prompt: int = 1,\n    device: Optional[torch.device] = None,\n):\n    device = device or self._execution_device\n\n    prompt = [prompt] if isinstance(prompt, str) else prompt\n    batch_size = len(prompt)\n\n    if isinstance(self, TextualInversionLoaderMixin):\n        prompt = self.maybe_convert_prompt(prompt, self.tokenizer)\n\n    text_inputs = self.tokenizer(\n        prompt,\n        padding=\"max_length\",\n        max_length=self.tokenizer_max_length,\n        truncation=True,\n        return_overflowing_tokens=False,\n        return_length=False,\n        return_tensors=\"pt\",\n    )\n\n    text_input_ids = text_inputs.input_ids\n\n    prompt_embeds = self.text_encoder(text_input_ids.to(device), output_hidden_states=False)\n\n    # Use pooled output of CLIPTextModel\n    prompt_embeds = prompt_embeds.pooler_output\n    prompt_embeds = prompt_embeds.to(dtype=self.text_encoder.dtype, device=device)\n\n    # duplicate text embeddings for each generation per prompt, using mps friendly method\n    prompt_embeds = prompt_embeds.repeat(1, num_images_per_prompt)\n    prompt_embeds = prompt_embeds.view(batch_size * num_images_per_prompt, -1)\n\n    return prompt_embeds\n\ndef encode_prompt_with_clip_t5(\n    self,\n    prompt: Union[str, List[str]],\n    prompt_2: Union[str, List[str]],\n    device: Optional[torch.device] = None,\n    num_images_per_prompt: int = 1,\n    prompt_embeds: Optional[torch.FloatTensor] = None,\n    pooled_prompt_embeds: Optional[torch.FloatTensor] = None,\n    max_sequence_length: int = 512,\n    lora_scale: Optional[float] = None,\n):\n    r\"\"\"\n\n    Args:\n        prompt (`str` or `List[str]`, *optional*):\n            prompt to be encoded\n        prompt_2 (`str` or `List[str]`, *optional*):\n            The prompt or prompts to be sent to the `tokenizer_2` and `text_encoder_2`. If not defined, `prompt` is\n            used in all text-encoders\n        device: (`torch.device`):\n            torch device\n        num_images_per_prompt (`int`):\n            number of images that should be generated per prompt\n        prompt_embeds (`torch.FloatTensor`, *optional*):\n            Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not\n            provided, text embeddings will be generated from `prompt` input argument.\n        pooled_prompt_embeds (`torch.FloatTensor`, *optional*):\n            Pre-generated pooled text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting.\n            If not provided, pooled text embeddings will be generated from `prompt` input argument.\n        lora_scale (`float`, *optional*):\n            A lora scale that will be applied to all LoRA layers of the text encoder if LoRA layers are loaded.\n    \"\"\"\n    device = device or self._execution_device\n\n    # set lora scale so that monkey patched LoRA\n    # function of text encoder can correctly access it\n    if lora_scale is not None and isinstance(self, FluxLoraLoaderMixin):\n        self._lora_scale = lora_scale\n\n        # dynamically adjust the LoRA scale\n        if self.text_encoder is not None and USE_PEFT_BACKEND:\n            scale_lora_layers(self.text_encoder, lora_scale)\n        if self.text_encoder_2 is not None and USE_PEFT_BACKEND:\n            scale_lora_layers(self.text_encoder_2, lora_scale)\n\n    prompt = [prompt] if isinstance(prompt, str) else prompt\n\n    if prompt_embeds is None:\n        prompt_2 = prompt_2 or prompt\n        prompt_2 = [prompt_2] if isinstance(prompt_2, str) else prompt_2\n\n        # We only use the pooled prompt output from the CLIPTextModel\n        pooled_prompt_embeds = _get_clip_prompt_embeds(\n            self=self,\n            prompt=prompt,\n            device=device,\n            num_images_per_prompt=num_images_per_prompt,\n        )\n        if self.text_encoder_2 is not None:\n            prompt_embeds = self._get_t5_prompt_embeds(\n                prompt=prompt_2,\n                num_images_per_prompt=num_images_per_prompt,\n                max_sequence_length=max_sequence_length,\n                device=device,\n            )\n            \n    if self.text_encoder is not None:\n        if isinstance(self, FluxLoraLoaderMixin) and USE_PEFT_BACKEND:\n            # Retrieve the original scale by scaling back the LoRA layers\n            unscale_lora_layers(self.text_encoder, lora_scale)\n\n    if self.text_encoder_2 is not None:\n        if isinstance(self, FluxLoraLoaderMixin) and USE_PEFT_BACKEND:\n            # Retrieve the original scale by scaling back the LoRA layers\n            unscale_lora_layers(self.text_encoder_2, lora_scale)\n\n    dtype = self.text_encoder.dtype if self.text_encoder is not None else self.transformer.dtype\n    if self.text_encoder_2 is not None:\n        text_ids = torch.zeros(prompt_embeds.shape[1], 3).to(device=device, dtype=dtype)\n    else:\n        text_ids = None\n\n    return prompt_embeds, pooled_prompt_embeds, text_ids\n\n\n\ndef prepare_text_input(\n    pipeline: FluxPipeline, \n    prompts, \n    max_sequence_length=512,\n):\n    # Turn off warnings (CLIP overflow)\n    logger.setLevel(logging.ERROR)\n    (\n        t5_prompt_embeds,\n        pooled_prompt_embeds,\n        text_ids,\n    ) = encode_prompt_with_clip_t5(\n        self=pipeline,\n        prompt=prompts,\n        prompt_2=None,\n        prompt_embeds=None,\n        pooled_prompt_embeds=None,\n        device=pipeline.device,\n        num_images_per_prompt=1,\n        max_sequence_length=max_sequence_length,\n        lora_scale=None,\n    )\n    # Turn on warnings\n    logger.setLevel(logging.WARNING)\n    return t5_prompt_embeds, pooled_prompt_embeds, text_ids\n\ndef prepare_t5_input(\n    pipeline: FluxPipeline, \n    prompts, \n    max_sequence_length=512,\n):\n    # Turn off warnings (CLIP overflow)\n    logger.setLevel(logging.ERROR)\n    (\n        t5_prompt_embeds,\n        pooled_prompt_embeds,\n        text_ids,\n    ) = encode_prompt_with_clip_t5(\n        self=pipeline,\n        prompt=prompts,\n        prompt_2=None,\n        prompt_embeds=None,\n        pooled_prompt_embeds=None,\n        device=pipeline.device,\n        num_images_per_prompt=1,\n        max_sequence_length=max_sequence_length,\n        lora_scale=None,\n    )\n    # Turn on warnings\n    logger.setLevel(logging.WARNING)\n    return t5_prompt_embeds, pooled_prompt_embeds, text_ids\n\ndef tokenize_t5_prompt(pipe, input_prompt, max_length, **kargs):\n    return pipe.tokenizer_2(\n        input_prompt,\n        padding=\"max_length\",\n        max_length=max_length,\n        truncation=True,\n        return_length=False,\n        return_overflowing_tokens=False,\n        return_tensors=\"pt\",\n        **kargs,\n    )\n\ndef clear_attn_maps(transformer):\n    for i, block in enumerate(transformer.transformer_blocks):\n        if hasattr(block.attn, \"attn_maps\"):\n            del block.attn.attn_maps\n            del block.attn.timestep\n    for i, block in enumerate(transformer.single_transformer_blocks):\n        if hasattr(block.attn, \"cond2latents\"):\n            del block.attn.cond2latents\n\ndef gather_attn_maps(transformer, clear=False):\n    t2i_attn_maps = {}\n    i2t_attn_maps = {}\n    for i, block in enumerate(transformer.transformer_blocks):\n        name = f\"block_{i}\"\n        if hasattr(block.attn, \"attn_maps\"):\n            attention_maps = block.attn.attn_maps\n            timesteps = block.attn.timestep # (B,)\n            for (timestep, (t2i_attn_map, i2t_attn_map)) in zip(timesteps, attention_maps):\n                timestep = str(timestep.item())\n\n                t2i_attn_maps[timestep] = t2i_attn_maps.get(timestep, dict())\n                t2i_attn_maps[timestep][name] = t2i_attn_maps[timestep].get(name, [])\n                t2i_attn_maps[timestep][name].append(t2i_attn_map.cpu())\n\n                i2t_attn_maps[timestep] = i2t_attn_maps.get(timestep, dict())\n                i2t_attn_maps[timestep][name] = i2t_attn_maps[timestep].get(name, [])\n                i2t_attn_maps[timestep][name].append(i2t_attn_map.cpu())\n\n        if clear:\n            del block.attn.attn_maps\n\n    for timestep in t2i_attn_maps:\n        for name in t2i_attn_maps[timestep]:\n            t2i_attn_maps[timestep][name] = torch.cat(t2i_attn_maps[timestep][name], dim=0)\n            i2t_attn_maps[timestep][name] = torch.cat(i2t_attn_maps[timestep][name], dim=0)\n\n    return t2i_attn_maps, i2t_attn_maps\n\ndef process_token(token, startofword):\n    if '</w>' in token:\n        token = token.replace('</w>', '')\n        if startofword:\n            token = '<' + token + '>'\n        else:\n            token = '-' + token + '>'\n            startofword = True\n    elif token not in ['<|startoftext|>', '<|endoftext|>']:\n        if startofword:\n            token = '<' + token + '-'\n            startofword = False\n        else:\n            token = '-' + token + '-'\n    return token, startofword\n\ndef save_attention_image(attn_map, tokens, batch_dir, to_pil):\n    startofword = True\n    for i, (token, a) in enumerate(zip(tokens, attn_map[:len(tokens)])):\n        token, startofword = process_token(token, startofword)\n        token = token.replace(\"/\", \"-\")\n        if token == '-<pad>-':\n            continue\n        a = a.to(torch.float32)\n        a = a / a.max() * 255 / 256\n        to_pil(a).save(os.path.join(batch_dir, f'{i}-{token}.png'))\n\ndef save_attention_maps(attn_maps, pipe, prompts, base_dir='attn_maps'):\n    to_pil = ToPILImage()\n    \n    token_ids = tokenize_t5_prompt(pipe, prompts, 512).input_ids # (B, 512)\n    token_ids = [x for x in token_ids]\n    total_tokens = [pipe.tokenizer_2.convert_ids_to_tokens(token_id) for token_id in token_ids]\n    \n    os.makedirs(base_dir, exist_ok=True)\n    \n    total_attn_map_shape = (256, 256)\n    total_attn_map_number = 0\n\n    # (B, 24, H, W, 512) -> (B, H, W, 512) -> (B, 512, H, W)\n    print(attn_maps.keys())\n    total_attn_map = list(list(attn_maps.values())[0].values())[0].sum(1)\n    total_attn_map = total_attn_map.permute(0, 3, 1, 2)\n    total_attn_map = torch.zeros_like(total_attn_map)\n    total_attn_map = F.interpolate(total_attn_map, size=total_attn_map_shape, mode='bilinear', align_corners=False)\n    \n    for timestep, layers in attn_maps.items():\n        timestep_dir = os.path.join(base_dir, f'{timestep}')\n        os.makedirs(timestep_dir, exist_ok=True)\n        \n        for layer, attn_map in layers.items():\n            layer_dir = os.path.join(timestep_dir, f'{layer}')\n            os.makedirs(layer_dir, exist_ok=True)\n            \n            attn_map = attn_map.sum(1).squeeze(1).permute(0, 3, 1, 2)\n\n            resized_attn_map = F.interpolate(attn_map, size=total_attn_map_shape, mode='bilinear', align_corners=False)\n            total_attn_map += resized_attn_map\n            total_attn_map_number += 1\n\n            for batch, (attn_map, tokens) in enumerate(zip(resized_attn_map, total_tokens)):\n                save_attention_image(attn_map, tokens, layer_dir, to_pil)\n            \n            # for batch, (tokens, attn) in enumerate(zip(total_tokens, attn_map)):\n            #     batch_dir = os.path.join(layer_dir, f'batch-{batch}')\n            #     os.makedirs(batch_dir, exist_ok=True)\n            #     save_attention_image(attn, tokens, batch_dir, to_pil)\n    \n    total_attn_map /= total_attn_map_number\n    for batch, (attn_map, tokens) in enumerate(zip(total_attn_map, total_tokens)):\n        batch_dir = os.path.join(base_dir, f'batch-{batch}')\n        os.makedirs(batch_dir, exist_ok=True)\n        save_attention_image(attn_map, tokens, batch_dir, to_pil)\n\ndef gather_cond2latents(transformer, clear=False):\n    c2l_attn_maps = {}\n    # for i, block in enumerate(transformer.transformer_blocks):\n    for i, block in enumerate(transformer.single_transformer_blocks):\n        name = f\"block_{i}\"\n        if hasattr(block.attn, \"cond2latents\"):\n            attention_maps = block.attn.cond2latents\n            timesteps = block.attn.cond_timesteps # (B,)\n            for (timestep, c2l_attn_map) in zip(timesteps, attention_maps):\n                timestep = str(timestep.item())\n\n                c2l_attn_maps[timestep] = c2l_attn_maps.get(timestep, dict())\n                c2l_attn_maps[timestep][name] = c2l_attn_maps[timestep].get(name, [])\n                c2l_attn_maps[timestep][name].append(c2l_attn_map.cpu())\n\n            if clear:\n                # del block.attn.attn_maps\n                del block.attn.cond2latents\n                del block.attn.cond_timesteps\n\n    for timestep in c2l_attn_maps:\n        for name in c2l_attn_maps[timestep]:\n            c2l_attn_maps[timestep][name] = torch.cat(c2l_attn_maps[timestep][name], dim=0)\n\n    return c2l_attn_maps\n\ndef save_cond2latent_image(attn_map, batch_dir, to_pil):\n    for i, a in enumerate(attn_map): # (N, H, W)\n        a = a.to(torch.float32)\n        a = a / a.max() * 255 / 256\n        to_pil(a).save(os.path.join(batch_dir, f'{i}.png'))\n\ndef save_cond2latent(attn_maps, base_dir='attn_maps'):\n    to_pil = ToPILImage()\n    \n    os.makedirs(base_dir, exist_ok=True)\n    \n    total_attn_map_shape = (256, 256)\n    total_attn_map_number = 0\n\n    # (N, H, W) -> (1, N, H, W)\n    total_attn_map = list(list(attn_maps.values())[0].values())[0].unsqueeze(0)\n    total_attn_map = torch.zeros_like(total_attn_map)\n    total_attn_map = F.interpolate(total_attn_map, size=total_attn_map_shape, mode='bilinear', align_corners=False)\n    \n    for timestep, layers in attn_maps.items():\n        cur_ts_attn_map = torch.zeros_like(total_attn_map)\n        cur_ts_attn_map_number = 0\n\n        timestep_dir = os.path.join(base_dir, f'{timestep}')\n        os.makedirs(timestep_dir, exist_ok=True)\n        \n        for layer, attn_map in layers.items():\n            # layer_dir = os.path.join(timestep_dir, f'{layer}')\n            # os.makedirs(layer_dir, exist_ok=True)\n            \n            attn_map = attn_map.unsqueeze(0) # (1, N, H, W)\n            resized_attn_map = F.interpolate(attn_map, size=total_attn_map_shape, mode='bilinear', align_corners=False)\n\n            cur_ts_attn_map += resized_attn_map\n            cur_ts_attn_map_number += 1\n\n        for batch, attn_map in enumerate(cur_ts_attn_map / cur_ts_attn_map_number):\n            save_cond2latent_image(attn_map, timestep_dir, to_pil)\n        \n        total_attn_map += cur_ts_attn_map\n        total_attn_map_number += cur_ts_attn_map_number\n            \n    total_attn_map /= total_attn_map_number\n    for batch, attn_map in enumerate(total_attn_map):\n        batch_dir = os.path.join(base_dir, f'batch-{batch}')\n        os.makedirs(batch_dir, exist_ok=True)\n        save_cond2latent_image(attn_map, batch_dir, to_pil)\n\ndef quantization(pipe, qtype, t5_only=False):\n    if qtype != \"None\" and qtype != \"\":\n        if qtype.endswith(\"quanto\"):\n            if qtype == \"int2-quanto\":\n                quant_level = qint2\n            elif qtype == \"int4-quanto\":\n                quant_level = qint4\n            elif qtype == \"int8-quanto\":\n                quant_level = qint8\n            elif qtype == \"fp8-quanto\":\n                quant_level = qfloat8\n            else:\n                raise ValueError(f\"Invalid quantisation level: {qtype}\")\n\n            extra_quanto_args = {}\n            extra_quanto_args[\"exclude\"] = [\n                \"*.norm\",\n                \"*.norm1\",\n                \"*.norm2\",\n                \"*.norm2_context\",\n                \"proj_out\",\n                \"x_embedder\",\n                \"norm_out\",\n                \"context_embedder\",\n            ]\n            try:\n                print(\"[Quantization] Start freezing\")\n                if not t5_only:\n                    quantize(pipe.transformer, weights=quant_level, **extra_quanto_args)\n                    freeze(pipe.transformer)\n                quantize(pipe.text_encoder_2, weights=quant_level, **extra_quanto_args)\n                freeze(pipe.text_encoder_2)\n                torch.cuda.empty_cache()\n                print(\"[Quantization] Finished\")\n            except Exception as e:\n                if \"out of memory\" in str(e).lower():\n                    print(\n                        \"GPU ran out of memory during quantisation. Use --quantize_via=cpu to use the slower CPU method.\"\n                    )\n                raise e\n        else:\n            assert qtype == \"fp8-ao\"\n            from torchao.float8 import convert_to_float8_training, Float8LinearConfig\n            def module_filter_fn(mod: torch.nn.Module, fqn: str):\n                # don't convert the output module\n                if fqn == \"proj_out\":\n                    return False\n                # don't convert linear modules with weight dimensions not divisible by 16\n                if isinstance(mod, torch.nn.Linear):\n                    if mod.in_features % 16 != 0 or mod.out_features % 16 != 0:\n                        return False\n                return True\n            convert_to_float8_training(\n                pipe.transformer, module_filter_fn=module_filter_fn, config=Float8LinearConfig(pad_inner_dim=True)\n            )\n\nclass CustomFluxPipeline:\n    def __init__(\n        self,\n        config,\n        device=torch.device(\"cuda\"),\n        ckpt_root=None,\n        ckpt_root_condition=None,\n        torch_dtype=torch.bfloat16,\n    ):\n\n        self.config = config\n        self.device = device\n        self.dtype = torch_dtype\n\n        model_path = os.getenv(\"FLUX_MODEL_PATH\", \"black-forest-labs/FLUX.1-dev\")\n\n        dit_quant = config[\"model\"].get(\"dit_quant\", \"None\")\n\n        if dit_quant == \"GGUF\":\n            # T5_path = os.getenv(\"FLUX_T5XXL_PATH\")\n            # tokenizer = AutoTokenizer.from_pretrained(T5_path, gguf_file=\"t5-v1_1-xxl-encoder-Q5_K_S.gguf\")\n            # text_encoder = T5EncoderModel.from_pretrained(\n            #     T5_path, gguf_file=\"t5-v1_1-xxl-encoder-Q3_K_S.gguf\", \n            #     torch_dtype=torch.bfloat16\n            # )\n            transformer_path = os.getenv(\"FLUX_TRANSFORMERS_PATH\")\n            transformer = FluxTransformer2DModel.from_single_file(\n                transformer_path,\n                quantization_config=GGUFQuantizationConfig(compute_dtype=torch.bfloat16),\n                torch_dtype=torch.bfloat16,\n            )\n            self.pipe = FluxPipeline.from_pretrained(\n                model_path,\n                transformer=transformer,\n                # tokenizer_2=tokenizer,\n                # text_encoder_2=text_encoder,\n                torch_dtype=torch.bfloat16,\n            )\n            quantization(self.pipe, \"int8-quanto\", t5_only=True)\n        else:\n            print(\"[CustomFluxPipeline] Loading FLUX Pipeline\")\n            self.pipe = FluxPipeline.from_pretrained(model_path, torch_dtype=torch_dtype)\n            if dit_quant != \"None\":\n                start = time.time()\n                quantization(self.pipe, dit_quant)\n                print(f\"Quantization time: {time.time() - start}\")\n\n        self.pipe = self.pipe.to(device)\n\n        self.modulation_adapters = []\n        self.pipe.modulation_adapters = []\n        \n        try:\n            if config[\"model\"][\"modulation\"][\"use_clip\"]:\n                load_clip(self, config, torch_dtype, device, None, is_training=False)\n        except Exception as e:\n            print(e)\n        \n        if config[\"model\"][\"use_dit_lora\"] or config[\"model\"][\"use_condition_dblock_lora\"] or config[\"model\"][\"use_condition_sblock_lora\"]:\n            if ckpt_root_condition is None and (config[\"model\"][\"use_condition_dblock_lora\"] or config[\"model\"][\"use_condition_sblock_lora\"]):\n                ckpt_root_condition = ckpt_root\n            load_dit_lora(self, self.pipe, config, torch_dtype, device, f\"{ckpt_root}\", f\"{ckpt_root_condition}\", is_training=False)\n        self.pipe.to(device)\n\n    def add_modulation_adapter(self, modulation_adapter):\n        self.modulation_adapters.append(modulation_adapter)\n        self.pipe.modulation_adapters.append(modulation_adapter)\n\n    def clear_modulation_adapters(self):\n        self.modulation_adapters = []\n        self.pipe.modulation_adapters = []\n        torch.cuda.empty_cache()\n\ndef load_clip(pipeline, config, torch_dtype, device, ckpt_dir=None, is_training=False):\n    model_path = os.getenv(\"CLIP_MODEL_PATH\", \"openai/clip-vit-large-patch14\")\n    clip_model = CLIPVisionModelWithProjection.from_pretrained(model_path).to(device, dtype=torch_dtype)\n    clip_processor = CLIPProcessor.from_pretrained(model_path)\n    pipeline.pipe.clip_model = clip_model\n    pipeline.pipe.clip_processor = clip_processor\n\ndef load_dit_lora(pipeline, pipe, config, torch_dtype, device, ckpt_dir=None, condition_ckpt_dir=None, is_training=False):\n\n    if not config[\"model\"][\"use_condition_dblock_lora\"] and not config[\"model\"][\"use_condition_sblock_lora\"] and not config[\"model\"][\"use_dit_lora\"]:\n        print(\"[load_dit_lora] no dit lora, no condition lora\")\n        return []\n    \n    adapter_names = [\"default\", \"condition\"]\n    \n    if condition_ckpt_dir is None:\n        condition_ckpt_dir = ckpt_dir\n    \n    if not config[\"model\"][\"use_condition_dblock_lora\"] and not config[\"model\"][\"use_condition_sblock_lora\"]:\n        print(\"[load_dit_lora] no condition lora\")\n        adapter_names.pop(1)\n    elif condition_ckpt_dir is not None and os.path.exists(os.path.join(condition_ckpt_dir, \"pytorch_lora_weights_condition.safetensors\")):\n        assert \"condition\" in adapter_names\n        print(f\"[load_dit_lora] load condition lora from {condition_ckpt_dir}\")\n        pipe.transformer.load_lora_adapter(condition_ckpt_dir, use_safetensors=True, adapter_name=\"condition\", weight_name=\"pytorch_lora_weights_condition.safetensors\") # TODO: check if they are trainable\n    else:\n        assert is_training\n        assert \"condition\" in adapter_names\n        print(\"[load_dit_lora] init new condition lora\")\n        pipe.transformer.add_adapter(LoraConfig(**config[\"model\"][\"condition_lora_config\"]), adapter_name=\"condition\")\n\n    if not config[\"model\"][\"use_dit_lora\"]:\n        print(\"[load_dit_lora] no dit lora\")\n        adapter_names.pop(0)\n    elif ckpt_dir is not None and os.path.exists(os.path.join(ckpt_dir, \"pytorch_lora_weights.safetensors\")):\n        assert \"default\" in adapter_names\n        print(f\"[load_dit_lora] load dit lora from {ckpt_dir}\")\n        lora_file = os.path.join(ckpt_dir, \"pytorch_lora_weights.safetensors\")\n        lora_state_dict = safetensors.torch.load_file(lora_file, device=\"cpu\")\n        \n        single_lora_pattern = \"(.*single_transformer_blocks\\\\.[0-9]+\\\\.norm\\\\.linear|.*single_transformer_blocks\\\\.[0-9]+\\\\.proj_mlp|.*single_transformer_blocks\\\\.[0-9]+\\\\.proj_out|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_k|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_q|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_v|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_out)\"\n        latent_lora_pattern = \"(.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.norm1\\\\.linear|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_k|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_q|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_v|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_out\\\\.0|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.ff\\\\.net\\\\.2)\"\n        use_pretrained_dit_single_lora = config[\"model\"].get(\"use_pretrained_dit_single_lora\", True)\n        use_pretrained_dit_latent_lora = config[\"model\"].get(\"use_pretrained_dit_latent_lora\", True)\n        if not use_pretrained_dit_single_lora or not use_pretrained_dit_latent_lora:\n            lora_state_dict_keys = list(lora_state_dict.keys())\n            for layer_name in lora_state_dict_keys:\n                if not use_pretrained_dit_single_lora:\n                    if re.search(single_lora_pattern, layer_name):\n                        del lora_state_dict[layer_name]\n                if not use_pretrained_dit_latent_lora:\n                    if re.search(latent_lora_pattern, layer_name):\n                        del lora_state_dict[layer_name]\n            pipe.transformer.add_adapter(LoraConfig(**config[\"model\"][\"dit_lora_config\"]), adapter_name=\"default\")\n            set_peft_model_state_dict(pipe.transformer, lora_state_dict, adapter_name=\"default\")\n        else:\n            pipe.transformer.load_lora_adapter(ckpt_dir, use_safetensors=True, adapter_name=\"default\", weight_name=\"pytorch_lora_weights.safetensors\") # TODO: check if they are trainable\n    else:\n        assert is_training\n        assert \"default\" in adapter_names\n        print(\"[load_dit_lora] init new dit lora\")\n        pipe.transformer.add_adapter(LoraConfig(**config[\"model\"][\"dit_lora_config\"]), adapter_name=\"default\")\n\n    assert len(adapter_names) <= 2 and len(adapter_names) > 0\n    for name, module in pipe.transformer.named_modules():\n        if isinstance(module, BaseTunerLayer):\n            module.set_adapter(adapter_names)\n    \n    if \"default\" in adapter_names: assert config[\"model\"][\"use_dit_lora\"]\n    if \"condition\" in adapter_names: assert config[\"model\"][\"use_condition_dblock_lora\"] or config[\"model\"][\"use_condition_sblock_lora\"]\n    \n    lora_layers = list(filter(\n        lambda p: p[1].requires_grad, pipe.transformer.named_parameters()\n    ))\n    \n    lora_layers = [l[1] for l in lora_layers]\n    return lora_layers\n\ndef load_modulation_adapter(pipeline, config, torch_dtype, device, ckpt_dir=None, is_training=False):\n    adapter_type = config[\"model\"][\"modulation\"][\"adapter_type\"]\n\n    if ckpt_dir is not None and os.path.exists(ckpt_dir):\n        print(f\"loading modulation adapter from {ckpt_dir}\")\n        modulation_adapter = CLIPModAdapter.from_pretrained(\n            ckpt_dir, subfolder=\"modulation_adapter\", strict=False, \n            low_cpu_mem_usage=False, device_map=None,\n        ).to(device)\n    else:\n        print(f\"Init new modulation adapter\")\n        adapter_layers = config[\"model\"][\"modulation\"][\"adapter_layers\"]\n        adapter_width = config[\"model\"][\"modulation\"][\"adapter_width\"]\n        pblock_adapter_layers = config[\"model\"][\"modulation\"][\"per_block_adapter_layers\"]\n        pblock_adapter_width = config[\"model\"][\"modulation\"][\"per_block_adapter_width\"]\n        pblock_adapter_single_blocks = config[\"model\"][\"modulation\"][\"per_block_adapter_single_blocks\"]\n        use_text_mod = config[\"model\"][\"modulation\"][\"use_text_mod\"]\n        use_img_mod = config[\"model\"][\"modulation\"][\"use_img_mod\"]\n        \n        out_dim = config[\"model\"][\"modulation\"][\"out_dim\"]\n        if adapter_type == \"clip_adapter\":\n            modulation_adapter = CLIPModAdapter(\n                out_dim=out_dim,\n                width=adapter_width,\n                pblock_width=pblock_adapter_width,\n                layers=adapter_layers,\n                pblock_layers=pblock_adapter_layers,\n                heads=8,\n                input_text_dim=4096,\n                input_image_dim=1024,\n                pblock_single_blocks=pblock_adapter_single_blocks,\n            )\n        else:\n            raise NotImplementedError()\n\n    if is_training:\n        modulation_adapter.train()\n        try:\n            modulation_adapter.enable_gradient_checkpointing()\n        except Exception as e:\n            print(e)\n        if not config[\"model\"][\"modulation\"][\"use_perblock_adapter\"]:\n            try:\n                modulation_adapter.net2.requires_grad_(False)\n            except Exception as e:\n                print(e)\n    else:\n        modulation_adapter.requires_grad_(False)\n    modulation_adapter.to(device, dtype=torch_dtype)\n    return modulation_adapter\n\n\ndef load_ckpt(pipeline, ckpt_dir, is_training=False):\n    if pipeline.config[\"model\"][\"use_dit_lora\"]:\n        pipeline.pipe.transformer.delete_adapters([\"subject\"])\n        lora_path = f\"{ckpt_dir}/pytorch_lora_weights.safetensors\"\n        print(f\"Loading DIT Lora from {lora_path}\")\n        pipeline.pipe.load_lora_weights(lora_path, adapter_name=\"subject\")\n\n        \n\n"
  },
  {
    "path": "src/flux/transformer.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright 2024 Black Forest Labs and The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport torch\nfrom diffusers.pipelines import FluxPipeline\nfrom typing import List, Union, Optional, Dict, Any, Callable\nfrom .block import block_forward, single_block_forward\nfrom .lora_controller import enable_lora\nfrom diffusers.models.transformers.transformer_flux import (\n    FluxTransformer2DModel,\n    Transformer2DModelOutput,\n    USE_PEFT_BACKEND,\n    is_torch_version,\n    scale_lora_layers,\n    unscale_lora_layers,\n    logger,\n)\nimport numpy as np\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef prepare_params(\n    hidden_states: torch.Tensor,\n    encoder_hidden_states: torch.Tensor = None,\n    pooled_projections: torch.Tensor = None,\n    timestep: torch.LongTensor = None,\n    img_ids: torch.Tensor = None,\n    txt_ids: torch.Tensor = None,\n    guidance: torch.Tensor = None,\n    joint_attention_kwargs: Optional[Dict[str, Any]] = None,\n    controlnet_block_samples=None,\n    controlnet_single_block_samples=None,\n    return_dict: bool = True,\n    **kwargs: dict,\n):\n    return (\n        hidden_states,\n        encoder_hidden_states,\n        pooled_projections,\n        timestep,\n        img_ids,\n        txt_ids,\n        guidance,\n        joint_attention_kwargs,\n        controlnet_block_samples,\n        controlnet_single_block_samples,\n        return_dict,\n    )\n\n\ndef transformer_forward(\n    transformer: FluxTransformer2DModel,\n    condition_latents: torch.Tensor,\n    condition_ids: torch.Tensor,\n    condition_type_ids: torch.Tensor,\n    model_config: Optional[Dict[str, Any]] = {},\n    c_t=0,\n    text_cond_mask: Optional[torch.FloatTensor] = None,\n    delta_emb: Optional[torch.FloatTensor] = None,\n    delta_emb_pblock: Optional[torch.FloatTensor] = None,\n    delta_emb_mask: Optional[torch.FloatTensor] = None,\n    delta_start_ends = None,\n    store_attn_map: bool = False,\n    use_text_mod: bool = True,\n    use_img_mod: bool = False,\n    mod_adapter = None,\n    latent_height: Optional[int] = None,\n    last_attn_map = None,\n    **params: dict,\n):\n    \n    use_condition = condition_latents is not None\n\n    (\n        hidden_states,\n        encoder_hidden_states,\n        pooled_projections,\n        timestep,\n        img_ids,\n        txt_ids,\n        guidance,\n        joint_attention_kwargs,\n        controlnet_block_samples,\n        controlnet_single_block_samples,\n        return_dict,\n    ) = prepare_params(**params)\n\n    if joint_attention_kwargs is not None:\n        joint_attention_kwargs = joint_attention_kwargs.copy()\n        lora_scale = joint_attention_kwargs.pop(\"scale\", 1.0)\n        latent_sblora_weight = joint_attention_kwargs.pop(\"latent_sblora_weight\", None)\n        condition_sblora_weight = joint_attention_kwargs.pop(\"condition_sblora_weight\", None)\n    else:\n        lora_scale = 1.0\n        latent_sblora_weight = None\n        condition_sblora_weight = None\n    if USE_PEFT_BACKEND:\n        # weight the lora layers by setting `lora_scale` for each PEFT layer\n        scale_lora_layers(transformer, lora_scale)\n    else:\n        if (\n            joint_attention_kwargs is not None\n            and joint_attention_kwargs.get(\"scale\", None) is not None\n        ):\n            logger.warning(\n                \"Passing `scale` via `joint_attention_kwargs` when not using the PEFT backend is ineffective.\"\n            )\n\n    train_partial_text_lora = model_config.get(\"train_partial_text_lora\", False)\n    train_partial_latent_lora = model_config.get(\"train_partial_latent_lora\", False)\n\n    if train_partial_text_lora or train_partial_latent_lora:\n        train_partial_text_lora_layers = model_config.get(\"train_partial_text_lora_layers\", \"\")\n        train_partial_latent_lora_layers = model_config.get(\"train_partial_latent_lora_layers\", \"\")\n        activate_x_embedder = True\n        if \"x_embedder\" not in train_partial_text_lora_layers or \"x_embedder\" not in train_partial_latent_lora_layers:\n            activate_x_embedder = False\n    if train_partial_text_lora or train_partial_latent_lora:\n        activate_x_embedder_ = activate_x_embedder\n    else:\n        activate_x_embedder_ = model_config[\"latent_lora\"] or model_config[\"text_lora\"]\n    \n    with enable_lora((transformer.x_embedder,), activate_x_embedder_):\n        hidden_states = transformer.x_embedder(hidden_states)\n    cond_lora_activate = model_config[\"use_condition_dblock_lora\"] or model_config[\"use_condition_sblock_lora\"]\n    with enable_lora(\n        (transformer.x_embedder,), \n        dit_activated=activate_x_embedder if train_partial_text_lora or train_partial_latent_lora else not cond_lora_activate, cond_activated=cond_lora_activate,\n    ):\n        condition_latents = transformer.x_embedder(condition_latents) if use_condition else None\n\n    timestep = timestep.to(hidden_states.dtype) * 1000\n\n    if guidance is not None:\n        guidance = guidance.to(hidden_states.dtype) * 1000\n    else:\n        guidance = None\n\n    temb = (\n        transformer.time_text_embed(timestep, pooled_projections)\n        if guidance is None\n        else transformer.time_text_embed(timestep, guidance, pooled_projections)\n    ) # (B, 3072)\n\n    cond_temb = (\n        transformer.time_text_embed(torch.ones_like(timestep) * c_t * 1000, pooled_projections)\n        if guidance is None\n        else transformer.time_text_embed(\n            torch.ones_like(timestep) * c_t * 1000, guidance, pooled_projections\n        )\n    )\n    encoder_hidden_states = transformer.context_embedder(encoder_hidden_states)\n\n    if txt_ids.ndim == 3:\n        logger.warning(\n            \"Passing `txt_ids` 3d torch.Tensor is deprecated.\"\n            \"Please remove the batch dimension and pass it as a 2d torch Tensor\"\n        )\n        txt_ids = txt_ids[0]\n    if img_ids.ndim == 3:\n        logger.warning(\n            \"Passing `img_ids` 3d torch.Tensor is deprecated.\"\n            \"Please remove the batch dimension and pass it as a 2d torch Tensor\"\n        )\n        img_ids = img_ids[0]\n\n    ids = torch.cat((txt_ids, img_ids), dim=0)\n    image_rotary_emb = transformer.pos_embed(ids)\n    if use_condition:\n        cond_rotary_emb = transformer.pos_embed(condition_ids)\n\n    for index_block, block in enumerate(transformer.transformer_blocks):\n        if delta_emb_pblock is None:\n            delta_emb_cblock = None\n        else:\n            delta_emb_cblock = delta_emb_pblock[:, :, index_block]\n        condition_pass_to_double = use_condition and (model_config[\"double_use_condition\"] or model_config[\"single_use_condition\"])\n        if transformer.training and transformer.gradient_checkpointing:\n            ckpt_kwargs: Dict[str, Any] = (\n                {\"use_reentrant\": False} if is_torch_version(\">=\", \"1.11.0\") else {}\n            )\n            \n            encoder_hidden_states, hidden_states, condition_latents = (\n                torch.utils.checkpoint.checkpoint(\n                    block_forward,\n                    block=block,\n                    model_config=model_config,\n                    hidden_states=hidden_states,\n                    encoder_hidden_states=encoder_hidden_states,\n                    condition_latents=condition_latents if condition_pass_to_double else None,\n                    cond_temb=cond_temb if condition_pass_to_double else None,\n                    cond_rotary_emb=cond_rotary_emb if condition_pass_to_double else None,\n                    temb=temb,\n                    text_cond_mask=text_cond_mask,\n                    delta_emb=delta_emb,\n                    delta_emb_cblock=delta_emb_cblock,\n                    delta_emb_mask=delta_emb_mask,\n                    delta_start_ends=delta_start_ends,\n                    image_rotary_emb=image_rotary_emb,\n                    store_attn_map=store_attn_map,\n                    use_text_mod=use_text_mod,\n                    use_img_mod=use_img_mod,\n                    mod_adapter=mod_adapter,\n                    latent_height=latent_height,\n                    timestep=timestep,\n                    last_attn_map=last_attn_map,\n                    **ckpt_kwargs,\n                )\n            )\n\n        else:\n            encoder_hidden_states, hidden_states, condition_latents = block_forward(\n                block,\n                model_config=model_config,\n                hidden_states=hidden_states,\n                encoder_hidden_states=encoder_hidden_states,\n                condition_latents=condition_latents if condition_pass_to_double else None,\n                cond_temb=cond_temb if condition_pass_to_double else None,\n                cond_rotary_emb=cond_rotary_emb if condition_pass_to_double else None,\n                temb=temb,\n                text_cond_mask=text_cond_mask,\n                delta_emb=delta_emb,\n                delta_emb_cblock=delta_emb_cblock,\n                delta_emb_mask=delta_emb_mask,\n                delta_start_ends=delta_start_ends,\n                image_rotary_emb=image_rotary_emb,\n                store_attn_map=store_attn_map,\n                use_text_mod=use_text_mod,\n                use_img_mod=use_img_mod,\n                mod_adapter=mod_adapter,\n                latent_height=latent_height,\n                timestep=timestep,\n                last_attn_map=last_attn_map,\n            )\n\n        # controlnet residual\n        if controlnet_block_samples is not None:\n            interval_control = len(transformer.transformer_blocks) / len(\n                controlnet_block_samples\n            )\n            interval_control = int(np.ceil(interval_control))\n            hidden_states = (\n                hidden_states\n                + controlnet_block_samples[index_block // interval_control]\n            )\n    hidden_states = torch.cat([encoder_hidden_states, hidden_states], dim=1)\n\n    for index_block, block in enumerate(transformer.single_transformer_blocks):\n        if delta_emb_pblock is not None and delta_emb_pblock.shape[2] > 19+index_block:\n            delta_emb_single = delta_emb\n            delta_emb_cblock = delta_emb_pblock[:, :, index_block+19]\n        else:\n            delta_emb_single = None\n            delta_emb_cblock = None\n        if transformer.training and transformer.gradient_checkpointing:\n            ckpt_kwargs: Dict[str, Any] = (\n                {\"use_reentrant\": False} if is_torch_version(\">=\", \"1.11.0\") else {}\n            )\n            result = torch.utils.checkpoint.checkpoint(\n                single_block_forward,\n                block=block,\n                model_config=model_config,\n                hidden_states=hidden_states,\n                temb=temb,\n                delta_emb=delta_emb_single,\n                delta_emb_cblock=delta_emb_cblock,\n                delta_emb_mask=delta_emb_mask,\n                use_text_mod=use_text_mod,\n                use_img_mod=use_img_mod,\n                image_rotary_emb=image_rotary_emb,\n                last_attn_map=last_attn_map,\n                latent_height=latent_height,\n                timestep=timestep,\n                store_attn_map=store_attn_map,\n                **(\n                    {\n                        \"condition_latents\": condition_latents,\n                        \"cond_temb\": cond_temb,\n                        \"cond_rotary_emb\": cond_rotary_emb,\n                        \"text_cond_mask\": text_cond_mask,\n                    }\n                    if use_condition and model_config[\"single_use_condition\"]\n                    else {}\n                ),\n                **ckpt_kwargs,\n            )\n\n        else:\n            result = single_block_forward(\n                block,\n                model_config=model_config,\n                hidden_states=hidden_states,\n                temb=temb,\n                delta_emb=delta_emb_single,\n                delta_emb_cblock=delta_emb_cblock,\n                delta_emb_mask=delta_emb_mask,\n                use_text_mod=use_text_mod,\n                use_img_mod=use_img_mod,\n                image_rotary_emb=image_rotary_emb,\n                last_attn_map=last_attn_map,\n                latent_height=latent_height,\n                timestep=timestep,\n                store_attn_map=store_attn_map,\n                latent_sblora_weight=latent_sblora_weight,\n                condition_sblora_weight=condition_sblora_weight,\n                **(\n                    {\n                        \"condition_latents\": condition_latents,\n                        \"cond_temb\": cond_temb,\n                        \"cond_rotary_emb\": cond_rotary_emb,\n                        \"text_cond_mask\": text_cond_mask,\n                    }\n                    if use_condition and model_config[\"single_use_condition\"]\n                    else {}\n                ),\n            )\n        if use_condition and model_config[\"single_use_condition\"]:\n            hidden_states, condition_latents = result\n        else:\n            hidden_states = result\n\n        # controlnet residual\n        if controlnet_single_block_samples is not None:\n            interval_control = len(transformer.single_transformer_blocks) / len(\n                controlnet_single_block_samples\n            )\n            interval_control = int(np.ceil(interval_control))\n            hidden_states[:, encoder_hidden_states.shape[1] :, ...] = (\n                hidden_states[:, encoder_hidden_states.shape[1] :, ...]\n                + controlnet_single_block_samples[index_block // interval_control]\n            )\n\n    hidden_states = hidden_states[:, encoder_hidden_states.shape[1] :, ...]\n\n    hidden_states = transformer.norm_out(hidden_states, temb)\n    output = transformer.proj_out(hidden_states)\n\n    if USE_PEFT_BACKEND:\n        # remove `lora_scale` from each PEFT layer\n        unscale_lora_layers(transformer, lora_scale)\n\n    if not return_dict:\n        return (output,)\n    return Transformer2DModelOutput(sample=output)\n\n"
  },
  {
    "path": "src/utils/data_utils.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport cv2\nimport json\nimport torch\nimport random\nimport base64\nimport numpy as np\nfrom PIL import Image, ImageDraw\nfrom glob import glob\nfrom torchvision import transforms as T\nimport os\nimport gc\nfrom webdataset.filters import default_collation_fn, pipelinefilter\nimport yaml\n\ndef get_rank_and_worldsize():\n    try:\n        local_rank = int(os.environ.get(\"LOCAL_RANK\"))\n        global_rank = int(os.environ.get(\"RANK\"))\n        world_size = int(os.getenv('WORLD_SIZE', 1))\n    except:\n        local_rank = 0\n        global_rank = 0\n        world_size = 1\n    return local_rank, global_rank, world_size\n\ndef get_train_config(config_path=None):\n    if config_path is None:\n        config_path = os.environ.get(\"XFL_CONFIG\")\n    assert config_path is not None, \"Please set the XFL_CONFIG environment variable\"\n    with open(config_path, \"r\") as f:\n        config = yaml.safe_load(f)\n    return config\n\ndef calculate_aspect_ratios(resolution):\n    ASPECT_RATIO = {\n        '0.25': [128.0, 512.0], '0.26': [128.0, 496.0], '0.27': [128.0, 480.0], '0.28': [128.0, 464.0],\n        '0.32': [144.0, 448.0], '0.33': [144.0, 432.0], '0.35': [144.0, 416.0], '0.4': [160.0, 400.0],\n        '0.42': [160.0, 384.0], '0.48': [176.0, 368.0], '0.5': [176.0, 352.0], '0.52': [176.0, 336.0],\n        '0.57': [192.0, 336.0], '0.6': [192.0, 320.0], '0.68': [208.0, 304.0], '0.72': [208.0, 288.0],\n        '0.78': [224.0, 288.0], '0.82': [224.0, 272.0], '0.88': [240.0, 272.0], '0.94': [240.0, 256.0],\n        '1.0': [256.0, 256.0], '1.07': [256.0, 240.0], '1.13': [272.0, 240.0], '1.21': [272.0, 224.0],\n        '1.29': [288.0, 224.0], '1.38': [288.0, 208.0], '1.46': [304.0, 208.0], '1.67': [320.0, 192.0],\n        '1.75': [336.0, 192.0], '2.0': [352.0, 176.0], '2.09': [368.0, 176.0], '2.4': [384.0, 160.0],\n        '2.5': [400.0, 160.0], '2.89': [416.0, 144.0], '3.0': [432.0, 144.0], '3.11': [448.0, 144.0],\n        '3.62': [464.0, 128.0], '3.75': [480.0, 128.0], '3.88': [496.0, 128.0], '4.0': [512.0, 128.0]\n    }\n    NEW_ASPECT_RATIO = {}\n    for ratio in ASPECT_RATIO:\n        height, width = ASPECT_RATIO[ratio]\n        width = round(width / 256 * resolution)\n        height = round(height / 256 * resolution)\n        if width % 8 != 0:\n            print(f\"skip train resolution {width}, {height}\")\n            continue\n        if height % 8 != 0:\n            print(f\"skip train resolution {width}, {height}\")\n            continue\n        NEW_ASPECT_RATIO[ratio] = [height, width]\n    return NEW_ASPECT_RATIO\n\nASPECT_RATIO_256 = calculate_aspect_ratios(256)\nASPECT_RATIO_384 = calculate_aspect_ratios(384)\nASPECT_RATIO_512 = calculate_aspect_ratios(512)\nASPECT_RATIO_768 = calculate_aspect_ratios(768)\nASPECT_RATIO_1024 = calculate_aspect_ratios(1024)\n\ndef get_closest_ratio(height: float, width: float, ratios: dict):\n    aspect_ratio = height / width\n    closest_ratio = min(ratios.keys(), key=lambda ratio: abs(float(ratio) - aspect_ratio))\n    return ratios[closest_ratio], closest_ratio\n\n\ndef _aspect_ratio_batched(\n    data,\n    batchsize=20,\n    aspect_ratios=ASPECT_RATIO_512,\n    batch_cross=False,\n    collation_fn=default_collation_fn,\n    partial=True,\n):\n    \"\"\"Create batches of the given size.\n\n    :param data: iterator\n    :param batchsize: target batch size\n    :param tensors: automatically batch lists of ndarrays into ndarrays\n    :param partial: return partial batches\n    :returns: iterator\n\n    \"\"\"\n    assert collation_fn is not None\n    buckets = {\n        ratio: {\"cross\": [], \"no_cross\": []} for ratio in aspect_ratios.keys()\n    }\n\n    def check(buckets):\n        for ratio in buckets:\n            for bucket_name in buckets[ratio]:\n                bucket = buckets[ratio][bucket_name]\n                assert len(bucket) < batchsize\n\n    for sample in data:\n        check(buckets)\n        height, width = sample['original_sizes']\n        (new_height, new_width), closest_ratio = get_closest_ratio(height, width, aspect_ratios)\n\n        bucket_name = \"cross\" if sample[\"has_cross\"] and batch_cross else \"no_cross\"\n        bucket = buckets[closest_ratio][bucket_name]\n        bucket.append(sample)\n\n        if len(bucket) >= batchsize:\n            try:\n                batch = collation_fn(bucket)\n                yield batch\n                del batch\n            except Exception as e:\n                print(f\"[aspect_ratio_batched] collation_fn batch failed due to error {e}\")\n                for sample in bucket:\n                    if \"__key__\" in sample:\n                        print(\"error sample key in batch:\", sample[\"__key__\"])\n                    if \"__url__\" in sample:\n                        print(\"error sample url in batch:\", sample[\"__url__\"])\n            buckets[closest_ratio][bucket_name] = []\n            del bucket\n            gc.collect()\n\n    # yield the rest data and reset the buckets\n    for ratio in buckets.keys():\n        for bucket_name in [\"cross\", \"no_cross\"]:\n            bucket = buckets[ratio][bucket_name]\n            if len(bucket) > 0:\n                if len(bucket) == batchsize or partial:\n                    batch = collation_fn(bucket)\n                    yield batch\n                    del batch\n                buckets[ratio][bucket_name] = []\n                del bucket\n\naspect_ratio_batched = pipelinefilter(_aspect_ratio_batched)\n\ndef apply_aspect_ratio_batched(dataset, batchsize, aspect_ratios, batch_cross, collation_fn, partial=True):\n    return dataset.compose(\n        aspect_ratio_batched(\n            batchsize, \n            aspect_ratios=aspect_ratios, \n            batch_cross=batch_cross,\n            collation_fn=collation_fn, \n            partial=partial\n        )\n    )\n\ndef get_aspect_ratios(enable_aspect_ratio, resolution):\n    if enable_aspect_ratio:\n        # print(\"[Dataset] Multi Aspect Ratio Training Enabled\")\n        if resolution == 256:\n            aspect_ratios = ASPECT_RATIO_256\n        elif resolution == 384:\n            aspect_ratios = ASPECT_RATIO_384\n        elif resolution == 512:\n            aspect_ratios = ASPECT_RATIO_512\n        elif resolution == 768:\n            aspect_ratios = ASPECT_RATIO_768\n        elif resolution == 1024:\n            aspect_ratios = ASPECT_RATIO_1024\n        else:\n            aspect_ratios = calculate_aspect_ratios(resolution)\n    else:\n        # print(\"[Dataset] Multi Aspect Ratio Training Disabled\")\n        aspect_ratios = {\n            '1.0': [resolution, resolution]\n        }\n    return aspect_ratios\n\ndef bbox_to_grid(bbox, image_size, output_size=(224, 224)):\n    \"\"\"\n    Convert bounding box to a grid of points.\n    Args:\n        bbox (list of float): [xmin, ymin, xmax, ymax]\n        output_size (tuple of int): (height, width) of the output grid\n        \n    Returns:\n        torch.Tensor: Grid of points with shape (output_height, output_width, 2)\n    \"\"\"\n    xmin, ymin, xmax, ymax = bbox\n    \n    # Create a meshgrid for the output grid\n    h, w = output_size\n    yy, xx = torch.meshgrid(\n        torch.linspace(ymin, ymax, h),\n        torch.linspace(xmin, xmax, w)\n    )\n    grid = torch.stack((xx, yy), -1)\n    \n    # Normalize grid to range [-1, 1]\n    H, W = image_size\n    grid[..., 0] = grid[..., 0] / (W - 1) * 2 - 1  # Normalize x to [-1, 1]\n    grid[..., 1] = grid[..., 1] / (H - 1) * 2 - 1  # Normalize y to [-1, 1]\n    \n    return grid\n\ndef random_crop_instance(instance, min_crop_ratio):\n    assert 0 < min_crop_ratio <= 1\n    crop_width_ratio = random.uniform(min_crop_ratio, 1)\n    crop_height_ratio = random.uniform(min_crop_ratio, 1)\n    \n    orig_width, orig_height = instance.size\n    \n    crop_width = int(orig_width * crop_width_ratio)\n    crop_height = int(orig_height * crop_height_ratio)\n    \n    crop_left = random.randint(0, orig_width - crop_width)\n    crop_top = random.randint(0, orig_height - crop_height)\n    \n    crop_box = (crop_left, crop_top, crop_left + crop_width, crop_top + crop_height) # (left, upper, right, lower)\n    return instance.crop(crop_box), crop_box\n\npil2tensor = T.ToTensor()\ntensor2pil = T.ToPILImage()\n\ncv2pil = lambda x: Image.fromarray(cv2.cvtColor(x, cv2.COLOR_BGR2RGB))\npil2cv2 = lambda x: cv2.cvtColor(np.array(x), cv2.COLOR_RGB2BGR)\n\ndef compute_psnr(x, y):\n    y = y.resize(x.size)\n    x = pil2tensor(x) * 255.\n    y = pil2tensor(y) * 255.\n    mse = torch.mean((x - y) ** 2)\n    return 20 * torch.log10(255.0 / torch.sqrt(mse)).item()\n\ndef replace_first_occurrence(sentence, word_or_phrase, replace_with):\n    # Escape special characters in word_or_phrase for exact matching\n    escaped_word_or_phrase = re.escape(word_or_phrase)\n    pattern = r'\\b' + escaped_word_or_phrase + r'\\b'\n    \n    # Finding the first match\n    match = next(re.finditer(pattern, sentence), None)\n    if match:\n        # Perform replacement\n        result = re.sub(pattern, replace_with, sentence, count=1)\n        replaced = True\n        index = match.start()\n    else:\n        # No match found\n        result = sentence\n        replaced = False\n        index = -1\n    \n    return result, replaced, index\n\n\ndef decode_base64_to_image(base64_str):\n    # Decode the base64 string to bytes\n    img_bytes = base64.b64decode(base64_str)\n    # Create a BytesIO buffer from the bytes\n    img_buffer = io.BytesIO(img_bytes)\n    # Open the image using Pillow\n    image = Image.open(img_buffer)\n    return image\n\ndef jpeg_compression(pil_image, quality):\n    buffer = io.BytesIO()\n    pil_image.save(buffer, format=\"JPEG\", quality=quality)\n    return Image.open(io.BytesIO(buffer.getvalue()))\n\ndef pad_to_square(pil_image):\n    new_size = max(pil_image.width, pil_image.height)\n    square_image = Image.new(\"RGB\", (new_size, new_size), \"white\")\n    left = (new_size - pil_image.width) // 2\n    top = (new_size - pil_image.height) // 2\n    square_image.paste(pil_image, (left, top))\n    return square_image\n\ndef pad_to_target(pil_image, target_size):\n    original_width, original_height = pil_image.size\n    target_width, target_height = target_size\n    \n    original_aspect_ratio = original_width / original_height\n    target_aspect_ratio = target_width / target_height\n    \n    # Pad the image to the target aspect ratio\n    if original_aspect_ratio > target_aspect_ratio:\n        new_width = original_width\n        new_height = int(new_width / target_aspect_ratio)\n    else:\n        new_height = original_height\n        new_width = int(new_height * target_aspect_ratio)\n    \n    pad_image = Image.new(\"RGB\", (new_width, new_height), \"white\")\n    left = (new_width - original_width) // 2\n    top = (new_height - original_height) // 2\n    pad_image.paste(pil_image, (left, top))\n    \n    # Resize the image to the target size\n    resized_image = pad_image.resize(target_size)\n    return resized_image\n\ndef image_grid(imgs, rows, cols):\n    # assert len(imgs) == rows * cols\n\n    w, h = imgs[0].size\n    if imgs[0].mode == 'L':\n        grid = Image.new('L', size=(cols * w, rows * h))\n    else:\n        grid = Image.new('RGB', size=(cols * w, rows * h))\n\n    for i, img in enumerate(imgs):\n        grid.paste(img, box=(i % cols * w, i // cols * h))\n    return grid\n\ndef split_grid(image):\n    width = image.width // 2\n    height = image.height // 2\n\n    crop_tuples_list = [\n        (0, 0, width, height),\n        (width, 0, width*2, height),\n        (0, height, width, height*2),\n        (width, height, width*2, height*2),\n    ]\n    def crop_image(input_image, crop_tuple=None):\n        if crop_tuple is None:\n            return input_image\n        return input_image.crop((crop_tuple[0], crop_tuple[1], crop_tuple[2], crop_tuple[3]))\n    \n    return [crop_image(image, crop_tuple) for crop_tuple in crop_tuples_list]\n\ndef add_border(img, border_color, border_thickness):\n    \"\"\"\n    Add a colored border to an image without changing its size.\n    \n    Parameters:\n        border_color (tuple): Border color in RGB (e.g., (255, 0, 0) for red).\n        border_thickness (int): Thickness of the border in pixels.\n    \"\"\"\n    width, height = img.size\n    img = img.copy()\n    draw = ImageDraw.Draw(img)\n    draw.rectangle((0, 0, width, border_thickness), fill=border_color)\n    draw.rectangle((0, height - border_thickness, width, height), fill=border_color)\n    draw.rectangle((0, 0, border_thickness, height), fill=border_color)\n    draw.rectangle((width - border_thickness, 0, width, height), fill=border_color)\n    return img\n\ndef merge_bboxes(bboxes):\n    if not bboxes:\n        return None  # Handle empty input\n    \n    # Extract all coordinates\n    x_mins = [b[0] for b in bboxes]\n    y_mins = [b[1] for b in bboxes]\n    x_maxs = [b[2] for b in bboxes]\n    y_maxs = [b[3] for b in bboxes]\n    \n    # Compute the merged box\n    merged_box = (\n        min(x_mins),  # x_min\n        min(y_mins),  # y_min\n        max(x_maxs),  # x_max\n        max(y_maxs)   # y_max\n    )\n    return merged_box\n\n\ndef flip_bbox_left_right(bbox, image_width):\n    \"\"\"\n    Flips the bounding box horizontally on an image.\n    \n    Parameters:\n    bbox (list of float): [x_min, y_min, x_max, y_max]\n    image_width (int): The width of the image\n    \n    Returns:\n    list of float: New bounding box after horizontal flip [x_min', y_min', x_max', y_max']\n    \"\"\"\n    x_min, y_min, x_max, y_max = bbox\n    new_x_min = image_width - x_max\n    new_x_max = image_width - x_min\n    new_bbox = [new_x_min, y_min, new_x_max, y_max]\n    return new_bbox\n\ndef json_load(path, encoding='ascii'):\n    with open(path, 'r', encoding=encoding) as file:\n        return json.load(file)\n\ndef json_dump(obj, path, encoding='ascii', indent=4, create_dir=True, verbose=True, **kwargs):\n    if create_dir and os.path.dirname(path) != '':\n        os.makedirs(os.path.dirname(path), exist_ok=True)\n    with open(path, 'w', encoding=encoding) as file:\n        json.dump(obj, file, indent=4, ensure_ascii=False, **kwargs)\n    if verbose:\n        print(type(obj), 'saved to', path)\n"
  },
  {
    "path": "src/utils/gpu_momory_utils.py",
    "content": "import torch\nfrom diffusers import AutoencoderKL, FluxTransformer2DModel\nimport time\n\nclass ForwardHookManager:\n    def __init__(self, threshold_mem = 8 * 1024 * 1024 * 1024, use_lower_vram = False):\n        self._registered_models = []\n        self._origin_states = {}\n        self._load_order = {}\n        self.threshold_mem = threshold_mem\n        self.use_lower_vram = use_lower_vram\n\n    def _get_available_memory(self):\n        total = torch.cuda.get_device_properties(0).total_memory\n        reserved = torch.cuda.memory_reserved(0)\n        return total - reserved\n\n    def _free_up_memory(self, required_mem, cache_model = None):\n\n        sorted_items = sorted(self._load_order.items(),\n                             key=lambda x: (x[1]['count'], x[1]['timestamp']))\n        for model, value in sorted_items:\n            if self._origin_states[model]['in_cuda']:\n                if model != cache_model:\n                    model.to(self._origin_states[model]['origin_device'])\n                    self._origin_states[model]['in_cuda'] = False\n                    del self._load_order[model]\n                torch.cuda.empty_cache()\n                if cache_model == None:\n                    if self._get_available_memory() - self.threshold_mem >= required_mem:\n                        return True\n                else:\n                    if self._get_available_memory() >= self.threshold_mem:\n                        return True\n        return False\n    \n    def model_to_cuda(self, model):\n        if torch.cuda.is_available():\n            origin_device = model.device if hasattr(model, 'device') else torch.device('cpu')\n            if model not in self._registered_models:\n                if torch.cuda.is_available():\n                    if origin_device.type == 'cuda':\n                        model.to('cpu')\n                    with torch.no_grad():\n                        ori_cuda_memory = torch.cuda.memory_allocated()\n                        model.to(\"cuda\")\n                        cuda_memory = torch.cuda.memory_allocated() - ori_cuda_memory\n                        model.to(origin_device)\n                        torch.cuda.empty_cache()\n                    \n                    self._origin_states[model] = {\n                        'origin_forward': model.forward,\n                        'origin_device': origin_device,\n                        'cuda_memory': cuda_memory,\n                        'in_cuda': False,\n                    }\n            available_mem = self._get_available_memory()\n            required_mem = self._origin_states[model]['cuda_memory']\n            # print(f\"required_mem: {required_mem}, available_mem: {available_mem}\")\n            if origin_device.type != 'cuda':\n                if available_mem - self.threshold_mem < required_mem:\n                    self._free_up_memory(required_mem)\n                        # raise RuntimeError(f\"Insufficient GPU memory. Required: {required_mem}, Available: {self._get_available_memory()}\")\n                \n                if model not in self._load_order:\n                    self._load_order[model] = {\n                        'count': 3,\n                        'timestamp': time.time(),\n                    }\n            else:\n                if available_mem < self.threshold_mem:\n                    self._free_up_memory(required_mem, model)\n                        # raise RuntimeError(f\"Insufficient GPU memory. Required: {required_mem}, Available: {self._get_available_memory()}\")\n            model.to('cuda')\n            self._load_order[model]['count'] += 1\n            self._load_order[model]['timestamp'] = time.time()\n\n            for other_model in self._load_order:\n                # if other_model != model:\n                #     self._load_order[other_model] = max(self._load_order[other_model], 0)\n                if other_model != model:\n                    self._load_order[other_model]['count'] = max(\n                        self._load_order[other_model]['count'] - 1, 0\n                    )\n            self._origin_states[model]['in_cuda'] = True\n        return model\n\n    def _register(self, model):\n        if model not in self._registered_models:\n            origin_device = model.device if hasattr(model, 'device') else torch.device('cpu')\n            if torch.cuda.is_available():\n                if origin_device.type == 'cuda':\n                    model.to('cpu')\n                with torch.no_grad():\n                    ori_cuda_memory = torch.cuda.memory_allocated()\n                    model.to(\"cuda\")\n                    cuda_memory = torch.cuda.memory_allocated() - ori_cuda_memory\n                    model.to(origin_device)\n                    torch.cuda.empty_cache()\n                \n                self._origin_states[model] = {\n                    'origin_forward': model.forward,\n                    'origin_device': origin_device,\n                    'cuda_memory': cuda_memory,\n                    'in_cuda': False,\n                }\n\n                def custom_forward(*args, **kwargs):      \n                    if torch.cuda.is_available():\n                        available_mem = self._get_available_memory()\n                        required_mem = self._origin_states[model]['cuda_memory']\n                        origin_device = model.device if hasattr(model, 'device') else self._origin_states[model]['origin_device']\n                        if origin_device.type != 'cuda':\n                            if available_mem - self.threshold_mem < required_mem:\n                                self._free_up_memory(required_mem)\n                            # model.to('cuda')\n                            \n                            if model not in self._load_order:\n                                self._load_order[model] = {\n                                    'count': 3,\n                                    'timestamp': time.time(),\n                                }\n                        else:\n                            if self._get_available_memory() < self.threshold_mem:\n                                self._free_up_memory(required_mem, model)\n                        \n                        for other_model in self._load_order:\n                            if other_model != model:\n                                self._load_order[other_model]['count'] = max(\n                                    self._load_order[other_model]['count'] - 1, 0\n                                )\n                        args = tuple(arg.cuda() if isinstance(arg, torch.Tensor) and arg.device != 'cuda' else arg     \n                                   for arg in args)\n                        kwargs = {k: v.cuda() if isinstance(v, torch.Tensor) and v.device != 'cuda' else v \n                                for k, v in kwargs.items()}\n                        model.to('cuda')\n                        self._origin_states[model]['in_cuda'] = True\n                        self._load_order[model]['count'] += 1\n                        self._load_order[model]['timestamp'] = time.time()\n\n                    result = self._origin_states[model]['origin_forward'](*args, **kwargs)\n                    return result\n\n                model.forward = custom_forward\n                self._registered_models.append(model)\n        return model\n    def replace_module_children(self, model, deep = 0):\n        if deep >= 0:\n            for name, child in model.named_children():\n                if isinstance(child, torch.nn.ModuleList):\n                    for index_block, block in enumerate(child):\n                        new_block = self._register(block)\n                        child[index_block] = new_block\n                        self.replace_module_children(new_block, 1)\n                    setattr(model, name, child)\n                elif isinstance(child, torch.nn.Module):\n                    new_child = self._register(child)\n                    setattr(model, name, new_child)\n                    self.replace_module_children(new_child, deep - 1)\n\n    def register(self, model):\n        if isinstance(model, torch.nn.Module):\n            if isinstance(model, AutoencoderKL):\n                model.encoder = self._register(model.encoder)\n                model.decoder = self._register(model.decoder)\n            elif isinstance(model, FluxTransformer2DModel) and self.use_lower_vram:\n                self.replace_module_children(model)\n            else:\n                model = self._register(model)\n        return model\n\n    def revert(self):\n        for model in self._registered_models:\n            if model in self._origin_states:\n                # model.forward = self._origin_states[model]['origin_forward']\n                model.to(self._origin_states[model]['origin_device'])\n        # self._registered_models.clear()\n        # self._origin_states.clear()\n        self._load_order.clear()\n    \n\n"
  },
  {
    "path": "src/utils/modulation_utils.py",
    "content": "# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates\n# Copyright (c) Facebook, Inc. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport torch\nfrom src.flux.pipeline_tools import tokenize_t5_prompt\n\ndef unpad_input_ids(input_ids, attention_mask):\n    return [input_ids[i][attention_mask[i].bool()][:-1] for i in range(input_ids.shape[0])]\n\ndef get_word_index(pipe, prompt, input_ids, word, word_count=1, max_length=512, verbose=True, reverse=False):\n    word_inputs = tokenize_t5_prompt(pipe, word, max_length)\n    word_ids = unpad_input_ids(word_inputs.input_ids, word_inputs.attention_mask)[0]\n    if word_ids[0] == 3:\n        word_ids = word_ids[1:] # remove prefix space\n\n    if verbose:\n        print(f\"Trying to find {word} {word_ids.tolist()} in {input_ids.tolist()} where\")\n        print([(i, pipe.tokenizer_2.decode(input_ids[i])) for i in range(input_ids.shape[0])])\n    \n    count = 0\n    if reverse:\n        for i in range(input_ids.shape[0] - word_ids.shape[0],-1,-1):\n            if torch.equal(input_ids[i:i+word_ids.shape[0]], word_ids):\n                count += 1\n                if count == word_count:\n                    if verbose:\n                        reconstructed_word = pipe.tokenizer_2.decode(input_ids[i:i+word_ids.shape[0]])\n                        assert reconstructed_word == word\n                        print(f\"[Reverse] Found index {i} to {i+word_ids.shape[0]} for '{word}' in prompt '{prompt}'\")\n                        print(\"Reconstructed word\", reconstructed_word)\n                    return i, i + word_ids.shape[0]\n    else:\n        for i in range(input_ids.shape[0] - word_ids.shape[0] + 1):\n            if torch.equal(input_ids[i:i+word_ids.shape[0]], word_ids):\n                count += 1\n                if count == word_count:\n                    if verbose:\n                        reconstructed_word = pipe.tokenizer_2.decode(input_ids[i:i+word_ids.shape[0]])\n                        assert reconstructed_word == word\n                        print(f\"Found index {i} to {i+word_ids.shape[0]} for '{word}' in prompt '{prompt}'\")\n                        print(\"Reconstructed word\", reconstructed_word)\n                    return i, i + word_ids.shape[0]\n    print(f\"[Error] Could not find '{word}' in prompt '{prompt}' with word_count {word_count}\")"
  },
  {
    "path": "train/config/XVerse_config_INF.yaml",
    "content": "dtype: \"bfloat16\"\n\nmodel:\n  text_cond_attn: false\n  add_cond_attn: false\n\n  union_cond_attn: true\n  double_use_condition: false\n  single_use_condition: true\n  cond_label_attn_only: false\n  cond_cond_cross_attn: true\n  train_partial_text_lora: false  # dblock txt lora \n  train_partial_text_lora_layers: \"qkv_toout\"\n  train_partial_latent_lora: false  # dblock latent lora \n  train_partial_latent_lora_layers: \"qkv_toout\"\n  train_partial_lora: true\n  train_partial_lora_layers: \"qkv_projout\"\n\n  vae_skip_iter: \"0-0.05:1,0.8-1:1\"\n  control_weight_lambda: \"0-1:1/3/5\"\n  condition_sblora_scale: \"0-1:1.3\"\n  latent_sblora_scale: \"0-1:0.85\"\n  ip_scale: \"0-1:0.85\"\n  use_condition_sblora_control: true\n  use_latent_sblora_control: true\n  \n  use_dit_lora: true\n  latent_lora: false\n  text_lora: true\n  sblock_lora: true\n  use_pretrained_dit_lora: true\n\n  use_condition_dblock_lora: false\n  use_condition_sblock_lora: false\n  use_pretrained_condition_lora: false  \n\n  freeze_mod_adapter: true\n  freeze_txt_lora: true\n  freeze_single_lora: false\n  use_pretrained_dit_single_lora: true  \n\n  pos_offset_type: \"diagonal\"\n\n  modulation:\n    use_clip: true\n    use_vae: false\n    use_dit: false\n    use_text_mod: true\n    use_img_mod: false\n    pass_vae: true\n    max_text_len: 128\n    adapter_type: \"clip_adapter\"\n    adapter_layers: 3\n    adapter_width: 3072\n    out_dim: 3072\n    use_perblock_adapter: true\n    per_block_adapter_layers: 3\n    per_block_adapter_width: 3072\n    per_block_adapter_single_blocks: 0\n    eos_exclude: false\n\n  dit_lora_config:\n    r: 128\n    lora_alpha: 128\n    init_lora_weights: \"gaussian\"\n    target_modules: \"(.*x_embedder|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.norm1\\\\.linear|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.norm1_context\\\\.linear|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_k|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_q|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_v|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.add_q_proj|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.add_k_proj|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.add_v_proj|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_add_out|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.ff_context\\\\.net\\\\.2|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_out\\\\.0|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.ff\\\\.net\\\\.2|.*single_transformer_blocks\\\\.[0-9]+\\\\.norm\\\\.linear|.*single_transformer_blocks\\\\.[0-9]+\\\\.proj_mlp|.*single_transformer_blocks\\\\.[0-9]+\\\\.proj_out|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_k|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_q|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_v|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_out)\"\n  \n  dit_quant: \"int8-quanto\"\n\ntrain:\n  dataset:\n    condition_pad_to: \"square\"\n    val_condition_size: 256\n    val_target_size: 512"
  },
  {
    "path": "train/config/XVerse_config_demo.yaml",
    "content": "dtype: \"bfloat16\"\n\nmodel:\n  text_cond_attn: false\n  add_cond_attn: false\n\n  union_cond_attn: true\n  double_use_condition: false\n  single_use_condition: true\n  cond_cond_cross_attn: true\n  train_partial_text_lora: false  # dblock txt lora \n  train_partial_text_lora_layers: \"qkv_toout\"\n  train_partial_latent_lora: false  # dblock latent lora \n  train_partial_latent_lora_layers: \"qkv_toout\"\n  train_partial_lora: true\n  train_partial_lora_layers: \"qkv_projout\"\n  \n  use_dit_lora: true\n  latent_lora: false\n  text_lora: true\n  sblock_lora: true\n  use_pretrained_dit_lora: true\n\n  use_condition_dblock_lora: false\n  use_condition_sblock_lora: false\n  use_pretrained_condition_lora: false  \n\n  freeze_mod_adapter: true\n  freeze_txt_lora: true\n  freeze_single_lora: false\n  use_pretrained_dit_single_lora: true  \n\n  pos_offset_type: \"diagonal\"\n\n  modulation:\n    use_clip: true\n    use_vae: false\n    use_dit: false\n    use_text_mod: true\n    use_img_mod: false\n    pass_vae: true\n    max_text_len: 128\n    adapter_type: \"clip_adapter\"\n    adapter_layers: 3\n    adapter_width: 3072\n    out_dim: 3072\n    use_perblock_adapter: true\n    per_block_adapter_layers: 3\n    per_block_adapter_width: 3072\n    per_block_adapter_single_blocks: 0\n    eos_exclude: false\n\n  dit_lora_config:\n    r: 128\n    lora_alpha: 128\n    init_lora_weights: \"gaussian\"\n    target_modules: \"(.*x_embedder|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.norm1\\\\.linear|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.norm1_context\\\\.linear|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_k|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_q|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_v|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.add_q_proj|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.add_k_proj|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.add_v_proj|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_add_out|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.ff_context\\\\.net\\\\.2|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.attn\\\\.to_out\\\\.0|.*(?<!single_)transformer_blocks\\\\.[0-9]+\\\\.ff\\\\.net\\\\.2|.*single_transformer_blocks\\\\.[0-9]+\\\\.norm\\\\.linear|.*single_transformer_blocks\\\\.[0-9]+\\\\.proj_mlp|.*single_transformer_blocks\\\\.[0-9]+\\\\.proj_out|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_k|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_q|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_v|.*single_transformer_blocks\\\\.[0-9]+\\\\.attn.to_out)\"\n  \n  dit_quant: \"int8-quanto\"\n\ntrain:\n  dataset:\n    condition_pad_to: \"square\"\n    val_condition_size: 256\n    val_target_size: 512"
  }
]