Showing preview only (8,414K chars total). Download the full file or copy to clipboard to get everything.
Repository: lllyasviel/Fooocus
Branch: main
Commit: ae05379cc97b
Files: 331
Total size: 8.0 MB
Directory structure:
gitextract____cmvti/
├── .dockerignore
├── .gitattributes
├── .github/
│ ├── CODEOWNERS
│ ├── ISSUE_TEMPLATE/
│ │ ├── bug_report.yml
│ │ ├── config.yml
│ │ └── feature_request.yml
│ ├── dependabot.yml
│ └── workflows/
│ └── build_container.yml
├── .gitignore
├── Dockerfile
├── LICENSE
├── args_manager.py
├── auth-example.json
├── build_launcher.py
├── css/
│ └── style.css
├── development.md
├── docker-compose.yml
├── docker.md
├── entry_with_update.py
├── entrypoint.sh
├── environment.yaml
├── experiments_expansion.py
├── experiments_face.py
├── experiments_interrogate.py
├── experiments_mask_generation.py
├── extras/
│ ├── BLIP/
│ │ ├── configs/
│ │ │ ├── bert_config.json
│ │ │ ├── caption_coco.yaml
│ │ │ ├── med_config.json
│ │ │ ├── nlvr.yaml
│ │ │ ├── nocaps.yaml
│ │ │ ├── pretrain.yaml
│ │ │ ├── retrieval_coco.yaml
│ │ │ ├── retrieval_flickr.yaml
│ │ │ ├── retrieval_msrvtt.yaml
│ │ │ └── vqa.yaml
│ │ └── models/
│ │ ├── bert_tokenizer/
│ │ │ ├── config.json
│ │ │ ├── tokenizer.json
│ │ │ ├── tokenizer_config.json
│ │ │ └── vocab.txt
│ │ ├── blip.py
│ │ ├── blip_itm.py
│ │ ├── blip_nlvr.py
│ │ ├── blip_pretrain.py
│ │ ├── blip_retrieval.py
│ │ ├── blip_vqa.py
│ │ ├── med.py
│ │ ├── nlvr_encoder.py
│ │ └── vit.py
│ ├── GroundingDINO/
│ │ ├── config/
│ │ │ └── GroundingDINO_SwinT_OGC.py
│ │ └── util/
│ │ └── inference.py
│ ├── censor.py
│ ├── expansion.py
│ ├── face_crop.py
│ ├── facexlib/
│ │ ├── detection/
│ │ │ ├── __init__.py
│ │ │ ├── align_trans.py
│ │ │ ├── matlab_cp2tform.py
│ │ │ ├── retinaface.py
│ │ │ ├── retinaface_net.py
│ │ │ └── retinaface_utils.py
│ │ ├── parsing/
│ │ │ ├── __init__.py
│ │ │ ├── bisenet.py
│ │ │ ├── parsenet.py
│ │ │ └── resnet.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── face_restoration_helper.py
│ │ ├── face_utils.py
│ │ └── misc.py
│ ├── inpaint_mask.py
│ ├── interrogate.py
│ ├── ip_adapter.py
│ ├── preprocessors.py
│ ├── resampler.py
│ ├── safety_checker/
│ │ ├── configs/
│ │ │ ├── config.json
│ │ │ └── preprocessor_config.json
│ │ └── models/
│ │ └── safety_checker.py
│ ├── sam/
│ │ └── predictor.py
│ ├── vae_interpose.py
│ └── wd14tagger.py
├── fooocus_colab.ipynb
├── fooocus_version.py
├── javascript/
│ ├── contextMenus.js
│ ├── edit-attention.js
│ ├── imageviewer.js
│ ├── localization.js
│ ├── script.js
│ ├── viewer.js
│ └── zoom.js
├── language/
│ ├── en.json
│ └── example.json
├── launch.py
├── ldm_patched/
│ ├── contrib/
│ │ ├── external.py
│ │ ├── external_align_your_steps.py
│ │ ├── external_canny.py
│ │ ├── external_clip_sdxl.py
│ │ ├── external_compositing.py
│ │ ├── external_custom_sampler.py
│ │ ├── external_freelunch.py
│ │ ├── external_hypernetwork.py
│ │ ├── external_hypertile.py
│ │ ├── external_images.py
│ │ ├── external_latent.py
│ │ ├── external_mask.py
│ │ ├── external_model_advanced.py
│ │ ├── external_model_downscale.py
│ │ ├── external_model_merging.py
│ │ ├── external_perpneg.py
│ │ ├── external_photomaker.py
│ │ ├── external_post_processing.py
│ │ ├── external_rebatch.py
│ │ ├── external_sag.py
│ │ ├── external_sdupscale.py
│ │ ├── external_stable3d.py
│ │ ├── external_tomesd.py
│ │ ├── external_upscale_model.py
│ │ └── external_video_model.py
│ ├── controlnet/
│ │ └── cldm.py
│ ├── k_diffusion/
│ │ ├── sampling.py
│ │ └── utils.py
│ ├── ldm/
│ │ ├── models/
│ │ │ └── autoencoder.py
│ │ ├── modules/
│ │ │ ├── attention.py
│ │ │ ├── diffusionmodules/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── model.py
│ │ │ │ ├── openaimodel.py
│ │ │ │ ├── upscaling.py
│ │ │ │ └── util.py
│ │ │ ├── distributions/
│ │ │ │ ├── __init__.py
│ │ │ │ └── distributions.py
│ │ │ ├── ema.py
│ │ │ ├── encoders/
│ │ │ │ ├── __init__.py
│ │ │ │ └── noise_aug_modules.py
│ │ │ ├── sub_quadratic_attention.py
│ │ │ └── temporal_ae.py
│ │ └── util.py
│ ├── licenses-3rd/
│ │ ├── chainer
│ │ ├── comfyui
│ │ ├── diffusers
│ │ ├── kdiffusion
│ │ ├── ldm
│ │ ├── taesd
│ │ └── transformers
│ ├── modules/
│ │ ├── args_parser.py
│ │ ├── checkpoint_pickle.py
│ │ ├── clip_config_bigg.json
│ │ ├── clip_model.py
│ │ ├── clip_vision.py
│ │ ├── clip_vision_config_g.json
│ │ ├── clip_vision_config_h.json
│ │ ├── clip_vision_config_vitl.json
│ │ ├── conds.py
│ │ ├── controlnet.py
│ │ ├── diffusers_convert.py
│ │ ├── diffusers_load.py
│ │ ├── gligen.py
│ │ ├── latent_formats.py
│ │ ├── lora.py
│ │ ├── model_base.py
│ │ ├── model_detection.py
│ │ ├── model_management.py
│ │ ├── model_patcher.py
│ │ ├── model_sampling.py
│ │ ├── ops.py
│ │ ├── options.py
│ │ ├── sample.py
│ │ ├── samplers.py
│ │ ├── sd.py
│ │ ├── sd1_clip.py
│ │ ├── sd1_clip_config.json
│ │ ├── sd1_tokenizer/
│ │ │ ├── merges.txt
│ │ │ ├── special_tokens_map.json
│ │ │ ├── tokenizer_config.json
│ │ │ └── vocab.json
│ │ ├── sd2_clip.py
│ │ ├── sd2_clip_config.json
│ │ ├── sdxl_clip.py
│ │ ├── supported_models.py
│ │ ├── supported_models_base.py
│ │ └── utils.py
│ ├── pfn/
│ │ ├── __init__.py
│ │ ├── architecture/
│ │ │ ├── DAT.py
│ │ │ ├── HAT.py
│ │ │ ├── LICENSE-DAT
│ │ │ ├── LICENSE-ESRGAN
│ │ │ ├── LICENSE-HAT
│ │ │ ├── LICENSE-RealESRGAN
│ │ │ ├── LICENSE-SCUNet
│ │ │ ├── LICENSE-SPSR
│ │ │ ├── LICENSE-SwiftSRGAN
│ │ │ ├── LICENSE-Swin2SR
│ │ │ ├── LICENSE-SwinIR
│ │ │ ├── LICENSE-lama
│ │ │ ├── LaMa.py
│ │ │ ├── OmniSR/
│ │ │ │ ├── ChannelAttention.py
│ │ │ │ ├── LICENSE
│ │ │ │ ├── OSA.py
│ │ │ │ ├── OSAG.py
│ │ │ │ ├── OmniSR.py
│ │ │ │ ├── esa.py
│ │ │ │ ├── layernorm.py
│ │ │ │ └── pixelshuffle.py
│ │ │ ├── RRDB.py
│ │ │ ├── SCUNet.py
│ │ │ ├── SPSR.py
│ │ │ ├── SRVGG.py
│ │ │ ├── SwiftSRGAN.py
│ │ │ ├── Swin2SR.py
│ │ │ ├── SwinIR.py
│ │ │ ├── __init__.py
│ │ │ ├── block.py
│ │ │ ├── face/
│ │ │ │ ├── LICENSE-GFPGAN
│ │ │ │ ├── LICENSE-RestoreFormer
│ │ │ │ ├── LICENSE-codeformer
│ │ │ │ ├── arcface_arch.py
│ │ │ │ ├── codeformer.py
│ │ │ │ ├── fused_act.py
│ │ │ │ ├── gfpgan_bilinear_arch.py
│ │ │ │ ├── gfpganv1_arch.py
│ │ │ │ ├── gfpganv1_clean_arch.py
│ │ │ │ ├── restoreformer_arch.py
│ │ │ │ ├── stylegan2_arch.py
│ │ │ │ ├── stylegan2_bilinear_arch.py
│ │ │ │ ├── stylegan2_clean_arch.py
│ │ │ │ └── upfirdn2d.py
│ │ │ └── timm/
│ │ │ ├── LICENSE
│ │ │ ├── drop.py
│ │ │ ├── helpers.py
│ │ │ └── weight_init.py
│ │ ├── model_loading.py
│ │ └── types.py
│ ├── t2ia/
│ │ └── adapter.py
│ ├── taesd/
│ │ └── taesd.py
│ ├── unipc/
│ │ └── uni_pc.py
│ └── utils/
│ ├── latent_visualization.py
│ └── path_utils.py
├── models/
│ ├── checkpoints/
│ │ └── put_checkpoints_here
│ ├── clip/
│ │ └── put_clip_or_text_encoder_models_here
│ ├── clip_vision/
│ │ ├── put_clip_vision_models_here
│ │ └── wd-v1-4-moat-tagger-v2.csv
│ ├── configs/
│ │ ├── anything_v3.yaml
│ │ ├── v1-inference.yaml
│ │ ├── v1-inference_clip_skip_2.yaml
│ │ ├── v1-inference_clip_skip_2_fp16.yaml
│ │ ├── v1-inference_fp16.yaml
│ │ ├── v1-inpainting-inference.yaml
│ │ ├── v2-inference-v.yaml
│ │ ├── v2-inference-v_fp32.yaml
│ │ ├── v2-inference.yaml
│ │ ├── v2-inference_fp32.yaml
│ │ └── v2-inpainting-inference.yaml
│ ├── controlnet/
│ │ └── put_controlnets_and_t2i_here
│ ├── diffusers/
│ │ └── put_diffusers_models_here
│ ├── embeddings/
│ │ └── put_embeddings_or_textual_inversion_concepts_here
│ ├── gligen/
│ │ └── put_gligen_models_here
│ ├── hypernetworks/
│ │ └── put_hypernetworks_here
│ ├── inpaint/
│ │ └── put_inpaint_here
│ ├── loras/
│ │ └── put_loras_here
│ ├── prompt_expansion/
│ │ ├── fooocus_expansion/
│ │ │ ├── config.json
│ │ │ ├── merges.txt
│ │ │ ├── positive.txt
│ │ │ ├── special_tokens_map.json
│ │ │ ├── tokenizer.json
│ │ │ ├── tokenizer_config.json
│ │ │ └── vocab.json
│ │ └── put_prompt_expansion_here
│ ├── safety_checker/
│ │ └── put_safety_checker_models_here
│ ├── style_models/
│ │ └── put_t2i_style_model_here
│ ├── unet/
│ │ └── put_unet_files_here
│ ├── upscale_models/
│ │ └── put_esrgan_and_other_upscale_models_here
│ ├── vae/
│ │ └── put_vae_here
│ └── vae_approx/
│ └── put_taesd_encoder_pth_and_taesd_decoder_pth_here
├── modules/
│ ├── __init__.py
│ ├── anisotropic.py
│ ├── async_worker.py
│ ├── auth.py
│ ├── config.py
│ ├── constants.py
│ ├── core.py
│ ├── default_pipeline.py
│ ├── extra_utils.py
│ ├── flags.py
│ ├── gradio_hijack.py
│ ├── hash_cache.py
│ ├── html.py
│ ├── inpaint_worker.py
│ ├── launch_util.py
│ ├── localization.py
│ ├── lora.py
│ ├── meta_parser.py
│ ├── model_loader.py
│ ├── ops.py
│ ├── patch.py
│ ├── patch_clip.py
│ ├── patch_precision.py
│ ├── private_logger.py
│ ├── sample_hijack.py
│ ├── sdxl_styles.py
│ ├── style_sorter.py
│ ├── ui_gradio_extensions.py
│ ├── upscaler.py
│ └── util.py
├── presets/
│ ├── .gitignore
│ ├── anime.json
│ ├── default.json
│ ├── lcm.json
│ ├── playground_v2.5.json
│ ├── pony_v6.json
│ ├── realistic.json
│ └── sai.json
├── readme.md
├── requirements_docker.txt
├── requirements_versions.txt
├── sdxl_styles/
│ ├── sdxl_styles_diva.json
│ ├── sdxl_styles_fooocus.json
│ ├── sdxl_styles_marc_k3nt3l.json
│ ├── sdxl_styles_mre.json
│ ├── sdxl_styles_sai.json
│ └── sdxl_styles_twri.json
├── shared.py
├── tests/
│ ├── __init__.py
│ ├── test_extra_utils.py
│ └── test_utils.py
├── troubleshoot.md
├── update_log.md
├── webui.py
└── wildcards/
├── .gitignore
├── animal.txt
├── artist.txt
├── color.txt
├── color_flower.txt
├── extended-color.txt
├── flower.txt
└── nationality.txt
================================================
FILE CONTENTS
================================================
================================================
FILE: .dockerignore
================================================
__pycache__
*.ckpt
*.safetensors
*.pth
*.pt
*.bin
*.patch
*.backup
*.corrupted
*.partial
*.onnx
sorted_styles.json
/input
/cache
/language/default.json
/test_imgs
config.txt
config_modification_tutorial.txt
user_path_config.txt
user_path_config-deprecated.txt
/modules/*.png
/repositories
/fooocus_env
/venv
/tmp
/ui-config.json
/outputs
/config.json
/log
/webui.settings.bat
/embeddings
/styles.csv
/params.txt
/styles.csv.bak
/webui-user.bat
/webui-user.sh
/interrogate
/user.css
/.idea
/notification.ogg
/notification.mp3
/SwinIR
/textual_inversion
.vscode
/extensions
/test/stdout.txt
/test/stderr.txt
/cache.json*
/config_states/
/node_modules
/package-lock.json
/.coverage*
/auth.json
.DS_Store
================================================
FILE: .gitattributes
================================================
# Ensure that shell scripts always use lf line endings, e.g. entrypoint.sh for docker
* text=auto
*.sh text eol=lf
================================================
FILE: .github/CODEOWNERS
================================================
* @lllyasviel
================================================
FILE: .github/ISSUE_TEMPLATE/bug_report.yml
================================================
name: Bug Report
description: You think something is broken in Fooocus
title: "[Bug]: "
labels: ["bug", "triage"]
body:
- type: markdown
attributes:
value: |
> The title of the bug report should be short and descriptive.
> Use relevant keywords for searchability.
> Do not leave it blank, but also do not put an entire error log in it.
- type: checkboxes
attributes:
label: Checklist
description: |
Please perform basic debugging to see if your configuration is the cause of the issue.
Basic debug procedure
1. Update Fooocus - sometimes things just need to be updated
2. Backup and remove your config.txt - check if the issue is caused by bad configuration
3. Try a fresh installation of Fooocus in a different directory - see if a clean installation solves the issue
Before making a issue report please, check that the issue hasn't been reported recently.
options:
- label: The issue has not been resolved by following the [troubleshooting guide](https://github.com/lllyasviel/Fooocus/blob/main/troubleshoot.md)
- label: The issue exists on a clean installation of Fooocus
- label: The issue exists in the current version of Fooocus
- label: The issue has not been reported before recently
- label: The issue has been reported before but has not been fixed yet
- type: markdown
attributes:
value: |
> Please fill this form with as much information as possible. Don't forget to add information about "What browsers" and provide screenshots if possible
- type: textarea
id: what-did
attributes:
label: What happened?
description: Tell us what happened in a very clear and simple way
placeholder: |
image generation is not working as intended.
validations:
required: true
- type: textarea
id: steps
attributes:
label: Steps to reproduce the problem
description: Please provide us with precise step by step instructions on how to reproduce the bug
placeholder: |
1. Go to ...
2. Press ...
3. ...
validations:
required: true
- type: textarea
id: what-should
attributes:
label: What should have happened?
description: Tell us what you think the normal behavior should be
placeholder: |
Fooocus should ...
validations:
required: true
- type: dropdown
id: browsers
attributes:
label: What browsers do you use to access Fooocus?
multiple: true
options:
- Mozilla Firefox
- Google Chrome
- Brave
- Apple Safari
- Microsoft Edge
- Android
- iOS
- Other
- type: dropdown
id: hosting
attributes:
label: Where are you running Fooocus?
multiple: false
options:
- Locally
- Locally with virtualization (e.g. Docker)
- Cloud (Google Colab)
- Cloud (other)
- type: input
id: operating-system
attributes:
label: What operating system are you using?
placeholder: |
Windows 10
- type: textarea
id: logs
attributes:
label: Console logs
description: Please provide **full** cmd/terminal logs from the moment you started UI to the end of it, after the bug occured. If it's very long, provide a link to pastebin or similar service.
render: Shell
validations:
required: true
- type: textarea
id: misc
attributes:
label: Additional information
description: |
Please provide us with any relevant additional info or context.
Examples:
I have updated my GPU driver recently.
================================================
FILE: .github/ISSUE_TEMPLATE/config.yml
================================================
blank_issues_enabled: false
contact_links:
- name: Ask a question
url: https://github.com/lllyasviel/Fooocus/discussions/new?category=q-a
about: Ask the community for help
================================================
FILE: .github/ISSUE_TEMPLATE/feature_request.yml
================================================
name: Feature request
description: Suggest an idea for this project
title: "[Feature Request]: "
labels: ["enhancement", "triage"]
body:
- type: checkboxes
attributes:
label: Is there an existing issue for this?
description: Please search to see if an issue already exists for the feature you want, and that it's not implemented in a recent build/commit.
options:
- label: I have searched the existing issues and checked the recent builds/commits
required: true
- type: markdown
attributes:
value: |
*Please fill this form with as much information as possible, provide screenshots and/or illustrations of the feature if possible*
- type: textarea
id: feature
attributes:
label: What would your feature do?
description: Tell us about your feature in a very clear and simple way, and what problem it would solve
validations:
required: true
- type: textarea
id: workflow
attributes:
label: Proposed workflow
description: Please provide us with step by step information on how you'd like the feature to be accessed and used
value: |
1. Go to ....
2. Press ....
3. ...
validations:
required: true
- type: textarea
id: misc
attributes:
label: Additional information
description: Add any other context or screenshots about the feature request here.
================================================
FILE: .github/dependabot.yml
================================================
version: 2
updates:
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "monthly"
================================================
FILE: .github/workflows/build_container.yml
================================================
name: Docker image build
on:
push:
branches:
- main
tags:
- v*
jobs:
build-and-push-image:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
steps:
- name: Checkout repository
uses: actions/checkout@v5
- name: Log in to the Container registry
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata (tags, labels) for Docker
id: meta
uses: docker/metadata-action@v5
with:
images: ghcr.io/${{ github.repository_owner }}/${{ github.event.repository.name }}
tags: |
type=semver,pattern={{version}}
type=semver,pattern={{major}}.{{minor}}
type=semver,pattern={{major}}
type=edge,branch=main
- name: Build and push Docker image
uses: docker/build-push-action@v6
with:
context: .
file: ./Dockerfile
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
================================================
FILE: .gitignore
================================================
__pycache__
*.ckpt
*.safetensors
*.pth
*.pt
*.bin
*.patch
*.backup
*.corrupted
*.partial
*.onnx
sorted_styles.json
hash_cache.txt
/input
/cache
/language/default.json
/test_imgs
config.txt
config_modification_tutorial.txt
user_path_config.txt
user_path_config-deprecated.txt
/modules/*.png
/repositories
/fooocus_env
/venv
/tmp
/ui-config.json
/outputs
/config.json
/log
/webui.settings.bat
/embeddings
/styles.csv
/params.txt
/styles.csv.bak
/webui-user.bat
/webui-user.sh
/interrogate
/user.css
/.idea
/notification.ogg
/notification.mp3
/SwinIR
/textual_inversion
.vscode
/extensions
/test/stdout.txt
/test/stderr.txt
/cache.json*
/config_states/
/node_modules
/package-lock.json
/.coverage*
/auth.json
.DS_Store
================================================
FILE: Dockerfile
================================================
FROM nvidia/cuda:12.4.1-base-ubuntu22.04
ENV DEBIAN_FRONTEND noninteractive
ENV CMDARGS --listen
RUN apt-get update -y && \
apt-get install -y curl libgl1 libglib2.0-0 python3-pip python-is-python3 git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
COPY requirements_docker.txt requirements_versions.txt /tmp/
RUN pip install --no-cache-dir -r /tmp/requirements_docker.txt -r /tmp/requirements_versions.txt && \
rm -f /tmp/requirements_docker.txt /tmp/requirements_versions.txt
RUN pip install --no-cache-dir xformers==0.0.23 --no-dependencies
RUN curl -fsL -o /usr/local/lib/python3.10/dist-packages/gradio/frpc_linux_amd64_v0.2 https://cdn-media.huggingface.co/frpc-gradio-0.2/frpc_linux_amd64 && \
chmod +x /usr/local/lib/python3.10/dist-packages/gradio/frpc_linux_amd64_v0.2
RUN adduser --disabled-password --gecos '' user && \
mkdir -p /content/app /content/data
COPY entrypoint.sh /content/
RUN chown -R user:user /content
WORKDIR /content
USER user
COPY --chown=user:user . /content/app
RUN mv /content/app/models /content/app/models.org
CMD [ "sh", "-c", "/content/entrypoint.sh ${CMDARGS}" ]
================================================
FILE: LICENSE
================================================
GNU GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The GNU General Public License is a free, copyleft license for
software and other kinds of works.
The licenses for most software and other practical works are designed
to take away your freedom to share and change the works. By contrast,
the GNU General Public License is intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free
software for all its users. We, the Free Software Foundation, use the
GNU General Public License for most of our software; it applies also to
any other work released this way by its authors. You can apply it to
your programs, too.
When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
them if you wish), that you receive source code or can get it if you
want it, that you can change the software or use pieces of it in new
free programs, and that you know you can do these things.
To protect your rights, we need to prevent others from denying you
these rights or asking you to surrender the rights. Therefore, you have
certain responsibilities if you distribute copies of the software, or if
you modify it: responsibilities to respect the freedom of others.
For example, if you distribute copies of such a program, whether
gratis or for a fee, you must pass on to the recipients the same
freedoms that you received. You must make sure that they, too, receive
or can get the source code. And you must show them these terms so they
know their rights.
Developers that use the GNU GPL protect your rights with two steps:
(1) assert copyright on the software, and (2) offer you this License
giving you legal permission to copy, distribute and/or modify it.
For the developers' and authors' protection, the GPL clearly explains
that there is no warranty for this free software. For both users' and
authors' sake, the GPL requires that modified versions be marked as
changed, so that their problems will not be attributed erroneously to
authors of previous versions.
Some devices are designed to deny users access to install or run
modified versions of the software inside them, although the manufacturer
can do so. This is fundamentally incompatible with the aim of
protecting users' freedom to change the software. The systematic
pattern of such abuse occurs in the area of products for individuals to
use, which is precisely where it is most unacceptable. Therefore, we
have designed this version of the GPL to prohibit the practice for those
products. If such problems arise substantially in other domains, we
stand ready to extend this provision to those domains in future versions
of the GPL, as needed to protect the freedom of users.
Finally, every program is threatened constantly by software patents.
States should not allow patents to restrict development and use of
software on general-purpose computers, but in those that do, we wish to
avoid the special danger that patents applied to a free program could
make it effectively proprietary. To prevent this, the GPL assures that
patents cannot be used to render the program non-free.
The precise terms and conditions for copying, distribution and
modification follow.
TERMS AND CONDITIONS
0. Definitions.
"This License" refers to version 3 of the GNU General Public License.
"Copyright" also means copyright-like laws that apply to other kinds of
works, such as semiconductor masks.
"The Program" refers to any copyrightable work licensed under this
License. Each licensee is addressed as "you". "Licensees" and
"recipients" may be individuals or organizations.
To "modify" a work means to copy from or adapt all or part of the work
in a fashion requiring copyright permission, other than the making of an
exact copy. The resulting work is called a "modified version" of the
earlier work or a work "based on" the earlier work.
A "covered work" means either the unmodified Program or a work based
on the Program.
To "propagate" a work means to do anything with it that, without
permission, would make you directly or secondarily liable for
infringement under applicable copyright law, except executing it on a
computer or modifying a private copy. Propagation includes copying,
distribution (with or without modification), making available to the
public, and in some countries other activities as well.
To "convey" a work means any kind of propagation that enables other
parties to make or receive copies. Mere interaction with a user through
a computer network, with no transfer of a copy, is not conveying.
An interactive user interface displays "Appropriate Legal Notices"
to the extent that it includes a convenient and prominently visible
feature that (1) displays an appropriate copyright notice, and (2)
tells the user that there is no warranty for the work (except to the
extent that warranties are provided), that licensees may convey the
work under this License, and how to view a copy of this License. If
the interface presents a list of user commands or options, such as a
menu, a prominent item in the list meets this criterion.
1. Source Code.
The "source code" for a work means the preferred form of the work
for making modifications to it. "Object code" means any non-source
form of a work.
A "Standard Interface" means an interface that either is an official
standard defined by a recognized standards body, or, in the case of
interfaces specified for a particular programming language, one that
is widely used among developers working in that language.
The "System Libraries" of an executable work include anything, other
than the work as a whole, that (a) is included in the normal form of
packaging a Major Component, but which is not part of that Major
Component, and (b) serves only to enable use of the work with that
Major Component, or to implement a Standard Interface for which an
implementation is available to the public in source code form. A
"Major Component", in this context, means a major essential component
(kernel, window system, and so on) of the specific operating system
(if any) on which the executable work runs, or a compiler used to
produce the work, or an object code interpreter used to run it.
The "Corresponding Source" for a work in object code form means all
the source code needed to generate, install, and (for an executable
work) run the object code and to modify the work, including scripts to
control those activities. However, it does not include the work's
System Libraries, or general-purpose tools or generally available free
programs which are used unmodified in performing those activities but
which are not part of the work. For example, Corresponding Source
includes interface definition files associated with source files for
the work, and the source code for shared libraries and dynamically
linked subprograms that the work is specifically designed to require,
such as by intimate data communication or control flow between those
subprograms and other parts of the work.
The Corresponding Source need not include anything that users
can regenerate automatically from other parts of the Corresponding
Source.
The Corresponding Source for a work in source code form is that
same work.
2. Basic Permissions.
All rights granted under this License are granted for the term of
copyright on the Program, and are irrevocable provided the stated
conditions are met. This License explicitly affirms your unlimited
permission to run the unmodified Program. The output from running a
covered work is covered by this License only if the output, given its
content, constitutes a covered work. This License acknowledges your
rights of fair use or other equivalent, as provided by copyright law.
You may make, run and propagate covered works that you do not
convey, without conditions so long as your license otherwise remains
in force. You may convey covered works to others for the sole purpose
of having them make modifications exclusively for you, or provide you
with facilities for running those works, provided that you comply with
the terms of this License in conveying all material for which you do
not control copyright. Those thus making or running the covered works
for you must do so exclusively on your behalf, under your direction
and control, on terms that prohibit them from making any copies of
your copyrighted material outside their relationship with you.
Conveying under any other circumstances is permitted solely under
the conditions stated below. Sublicensing is not allowed; section 10
makes it unnecessary.
3. Protecting Users' Legal Rights From Anti-Circumvention Law.
No covered work shall be deemed part of an effective technological
measure under any applicable law fulfilling obligations under article
11 of the WIPO copyright treaty adopted on 20 December 1996, or
similar laws prohibiting or restricting circumvention of such
measures.
When you convey a covered work, you waive any legal power to forbid
circumvention of technological measures to the extent such circumvention
is effected by exercising rights under this License with respect to
the covered work, and you disclaim any intention to limit operation or
modification of the work as a means of enforcing, against the work's
users, your or third parties' legal rights to forbid circumvention of
technological measures.
4. Conveying Verbatim Copies.
You may convey verbatim copies of the Program's source code as you
receive it, in any medium, provided that you conspicuously and
appropriately publish on each copy an appropriate copyright notice;
keep intact all notices stating that this License and any
non-permissive terms added in accord with section 7 apply to the code;
keep intact all notices of the absence of any warranty; and give all
recipients a copy of this License along with the Program.
You may charge any price or no price for each copy that you convey,
and you may offer support or warranty protection for a fee.
5. Conveying Modified Source Versions.
You may convey a work based on the Program, or the modifications to
produce it from the Program, in the form of source code under the
terms of section 4, provided that you also meet all of these conditions:
a) The work must carry prominent notices stating that you modified
it, and giving a relevant date.
b) The work must carry prominent notices stating that it is
released under this License and any conditions added under section
7. This requirement modifies the requirement in section 4 to
"keep intact all notices".
c) You must license the entire work, as a whole, under this
License to anyone who comes into possession of a copy. This
License will therefore apply, along with any applicable section 7
additional terms, to the whole of the work, and all its parts,
regardless of how they are packaged. This License gives no
permission to license the work in any other way, but it does not
invalidate such permission if you have separately received it.
d) If the work has interactive user interfaces, each must display
Appropriate Legal Notices; however, if the Program has interactive
interfaces that do not display Appropriate Legal Notices, your
work need not make them do so.
A compilation of a covered work with other separate and independent
works, which are not by their nature extensions of the covered work,
and which are not combined with it such as to form a larger program,
in or on a volume of a storage or distribution medium, is called an
"aggregate" if the compilation and its resulting copyright are not
used to limit the access or legal rights of the compilation's users
beyond what the individual works permit. Inclusion of a covered work
in an aggregate does not cause this License to apply to the other
parts of the aggregate.
6. Conveying Non-Source Forms.
You may convey a covered work in object code form under the terms
of sections 4 and 5, provided that you also convey the
machine-readable Corresponding Source under the terms of this License,
in one of these ways:
a) Convey the object code in, or embodied in, a physical product
(including a physical distribution medium), accompanied by the
Corresponding Source fixed on a durable physical medium
customarily used for software interchange.
b) Convey the object code in, or embodied in, a physical product
(including a physical distribution medium), accompanied by a
written offer, valid for at least three years and valid for as
long as you offer spare parts or customer support for that product
model, to give anyone who possesses the object code either (1) a
copy of the Corresponding Source for all the software in the
product that is covered by this License, on a durable physical
medium customarily used for software interchange, for a price no
more than your reasonable cost of physically performing this
conveying of source, or (2) access to copy the
Corresponding Source from a network server at no charge.
c) Convey individual copies of the object code with a copy of the
written offer to provide the Corresponding Source. This
alternative is allowed only occasionally and noncommercially, and
only if you received the object code with such an offer, in accord
with subsection 6b.
d) Convey the object code by offering access from a designated
place (gratis or for a charge), and offer equivalent access to the
Corresponding Source in the same way through the same place at no
further charge. You need not require recipients to copy the
Corresponding Source along with the object code. If the place to
copy the object code is a network server, the Corresponding Source
may be on a different server (operated by you or a third party)
that supports equivalent copying facilities, provided you maintain
clear directions next to the object code saying where to find the
Corresponding Source. Regardless of what server hosts the
Corresponding Source, you remain obligated to ensure that it is
available for as long as needed to satisfy these requirements.
e) Convey the object code using peer-to-peer transmission, provided
you inform other peers where the object code and Corresponding
Source of the work are being offered to the general public at no
charge under subsection 6d.
A separable portion of the object code, whose source code is excluded
from the Corresponding Source as a System Library, need not be
included in conveying the object code work.
A "User Product" is either (1) a "consumer product", which means any
tangible personal property which is normally used for personal, family,
or household purposes, or (2) anything designed or sold for incorporation
into a dwelling. In determining whether a product is a consumer product,
doubtful cases shall be resolved in favor of coverage. For a particular
product received by a particular user, "normally used" refers to a
typical or common use of that class of product, regardless of the status
of the particular user or of the way in which the particular user
actually uses, or expects or is expected to use, the product. A product
is a consumer product regardless of whether the product has substantial
commercial, industrial or non-consumer uses, unless such uses represent
the only significant mode of use of the product.
"Installation Information" for a User Product means any methods,
procedures, authorization keys, or other information required to install
and execute modified versions of a covered work in that User Product from
a modified version of its Corresponding Source. The information must
suffice to ensure that the continued functioning of the modified object
code is in no case prevented or interfered with solely because
modification has been made.
If you convey an object code work under this section in, or with, or
specifically for use in, a User Product, and the conveying occurs as
part of a transaction in which the right of possession and use of the
User Product is transferred to the recipient in perpetuity or for a
fixed term (regardless of how the transaction is characterized), the
Corresponding Source conveyed under this section must be accompanied
by the Installation Information. But this requirement does not apply
if neither you nor any third party retains the ability to install
modified object code on the User Product (for example, the work has
been installed in ROM).
The requirement to provide Installation Information does not include a
requirement to continue to provide support service, warranty, or updates
for a work that has been modified or installed by the recipient, or for
the User Product in which it has been modified or installed. Access to a
network may be denied when the modification itself materially and
adversely affects the operation of the network or violates the rules and
protocols for communication across the network.
Corresponding Source conveyed, and Installation Information provided,
in accord with this section must be in a format that is publicly
documented (and with an implementation available to the public in
source code form), and must require no special password or key for
unpacking, reading or copying.
7. Additional Terms.
"Additional permissions" are terms that supplement the terms of this
License by making exceptions from one or more of its conditions.
Additional permissions that are applicable to the entire Program shall
be treated as though they were included in this License, to the extent
that they are valid under applicable law. If additional permissions
apply only to part of the Program, that part may be used separately
under those permissions, but the entire Program remains governed by
this License without regard to the additional permissions.
When you convey a copy of a covered work, you may at your option
remove any additional permissions from that copy, or from any part of
it. (Additional permissions may be written to require their own
removal in certain cases when you modify the work.) You may place
additional permissions on material, added by you to a covered work,
for which you have or can give appropriate copyright permission.
Notwithstanding any other provision of this License, for material you
add to a covered work, you may (if authorized by the copyright holders of
that material) supplement the terms of this License with terms:
a) Disclaiming warranty or limiting liability differently from the
terms of sections 15 and 16 of this License; or
b) Requiring preservation of specified reasonable legal notices or
author attributions in that material or in the Appropriate Legal
Notices displayed by works containing it; or
c) Prohibiting misrepresentation of the origin of that material, or
requiring that modified versions of such material be marked in
reasonable ways as different from the original version; or
d) Limiting the use for publicity purposes of names of licensors or
authors of the material; or
e) Declining to grant rights under trademark law for use of some
trade names, trademarks, or service marks; or
f) Requiring indemnification of licensors and authors of that
material by anyone who conveys the material (or modified versions of
it) with contractual assumptions of liability to the recipient, for
any liability that these contractual assumptions directly impose on
those licensors and authors.
All other non-permissive additional terms are considered "further
restrictions" within the meaning of section 10. If the Program as you
received it, or any part of it, contains a notice stating that it is
governed by this License along with a term that is a further
restriction, you may remove that term. If a license document contains
a further restriction but permits relicensing or conveying under this
License, you may add to a covered work material governed by the terms
of that license document, provided that the further restriction does
not survive such relicensing or conveying.
If you add terms to a covered work in accord with this section, you
must place, in the relevant source files, a statement of the
additional terms that apply to those files, or a notice indicating
where to find the applicable terms.
Additional terms, permissive or non-permissive, may be stated in the
form of a separately written license, or stated as exceptions;
the above requirements apply either way.
8. Termination.
You may not propagate or modify a covered work except as expressly
provided under this License. Any attempt otherwise to propagate or
modify it is void, and will automatically terminate your rights under
this License (including any patent licenses granted under the third
paragraph of section 11).
However, if you cease all violation of this License, then your
license from a particular copyright holder is reinstated (a)
provisionally, unless and until the copyright holder explicitly and
finally terminates your license, and (b) permanently, if the copyright
holder fails to notify you of the violation by some reasonable means
prior to 60 days after the cessation.
Moreover, your license from a particular copyright holder is
reinstated permanently if the copyright holder notifies you of the
violation by some reasonable means, this is the first time you have
received notice of violation of this License (for any work) from that
copyright holder, and you cure the violation prior to 30 days after
your receipt of the notice.
Termination of your rights under this section does not terminate the
licenses of parties who have received copies or rights from you under
this License. If your rights have been terminated and not permanently
reinstated, you do not qualify to receive new licenses for the same
material under section 10.
9. Acceptance Not Required for Having Copies.
You are not required to accept this License in order to receive or
run a copy of the Program. Ancillary propagation of a covered work
occurring solely as a consequence of using peer-to-peer transmission
to receive a copy likewise does not require acceptance. However,
nothing other than this License grants you permission to propagate or
modify any covered work. These actions infringe copyright if you do
not accept this License. Therefore, by modifying or propagating a
covered work, you indicate your acceptance of this License to do so.
10. Automatic Licensing of Downstream Recipients.
Each time you convey a covered work, the recipient automatically
receives a license from the original licensors, to run, modify and
propagate that work, subject to this License. You are not responsible
for enforcing compliance by third parties with this License.
An "entity transaction" is a transaction transferring control of an
organization, or substantially all assets of one, or subdividing an
organization, or merging organizations. If propagation of a covered
work results from an entity transaction, each party to that
transaction who receives a copy of the work also receives whatever
licenses to the work the party's predecessor in interest had or could
give under the previous paragraph, plus a right to possession of the
Corresponding Source of the work from the predecessor in interest, if
the predecessor has it or can get it with reasonable efforts.
You may not impose any further restrictions on the exercise of the
rights granted or affirmed under this License. For example, you may
not impose a license fee, royalty, or other charge for exercise of
rights granted under this License, and you may not initiate litigation
(including a cross-claim or counterclaim in a lawsuit) alleging that
any patent claim is infringed by making, using, selling, offering for
sale, or importing the Program or any portion of it.
11. Patents.
A "contributor" is a copyright holder who authorizes use under this
License of the Program or a work on which the Program is based. The
work thus licensed is called the contributor's "contributor version".
A contributor's "essential patent claims" are all patent claims
owned or controlled by the contributor, whether already acquired or
hereafter acquired, that would be infringed by some manner, permitted
by this License, of making, using, or selling its contributor version,
but do not include claims that would be infringed only as a
consequence of further modification of the contributor version. For
purposes of this definition, "control" includes the right to grant
patent sublicenses in a manner consistent with the requirements of
this License.
Each contributor grants you a non-exclusive, worldwide, royalty-free
patent license under the contributor's essential patent claims, to
make, use, sell, offer for sale, import and otherwise run, modify and
propagate the contents of its contributor version.
In the following three paragraphs, a "patent license" is any express
agreement or commitment, however denominated, not to enforce a patent
(such as an express permission to practice a patent or covenant not to
sue for patent infringement). To "grant" such a patent license to a
party means to make such an agreement or commitment not to enforce a
patent against the party.
If you convey a covered work, knowingly relying on a patent license,
and the Corresponding Source of the work is not available for anyone
to copy, free of charge and under the terms of this License, through a
publicly available network server or other readily accessible means,
then you must either (1) cause the Corresponding Source to be so
available, or (2) arrange to deprive yourself of the benefit of the
patent license for this particular work, or (3) arrange, in a manner
consistent with the requirements of this License, to extend the patent
license to downstream recipients. "Knowingly relying" means you have
actual knowledge that, but for the patent license, your conveying the
covered work in a country, or your recipient's use of the covered work
in a country, would infringe one or more identifiable patents in that
country that you have reason to believe are valid.
If, pursuant to or in connection with a single transaction or
arrangement, you convey, or propagate by procuring conveyance of, a
covered work, and grant a patent license to some of the parties
receiving the covered work authorizing them to use, propagate, modify
or convey a specific copy of the covered work, then the patent license
you grant is automatically extended to all recipients of the covered
work and works based on it.
A patent license is "discriminatory" if it does not include within
the scope of its coverage, prohibits the exercise of, or is
conditioned on the non-exercise of one or more of the rights that are
specifically granted under this License. You may not convey a covered
work if you are a party to an arrangement with a third party that is
in the business of distributing software, under which you make payment
to the third party based on the extent of your activity of conveying
the work, and under which the third party grants, to any of the
parties who would receive the covered work from you, a discriminatory
patent license (a) in connection with copies of the covered work
conveyed by you (or copies made from those copies), or (b) primarily
for and in connection with specific products or compilations that
contain the covered work, unless you entered into that arrangement,
or that patent license was granted, prior to 28 March 2007.
Nothing in this License shall be construed as excluding or limiting
any implied license or other defenses to infringement that may
otherwise be available to you under applicable patent law.
12. No Surrender of Others' Freedom.
If conditions are imposed on you (whether by court order, agreement or
otherwise) that contradict the conditions of this License, they do not
excuse you from the conditions of this License. If you cannot convey a
covered work so as to satisfy simultaneously your obligations under this
License and any other pertinent obligations, then as a consequence you may
not convey it at all. For example, if you agree to terms that obligate you
to collect a royalty for further conveying from those to whom you convey
the Program, the only way you could satisfy both those terms and this
License would be to refrain entirely from conveying the Program.
13. Use with the GNU Affero General Public License.
Notwithstanding any other provision of this License, you have
permission to link or combine any covered work with a work licensed
under version 3 of the GNU Affero General Public License into a single
combined work, and to convey the resulting work. The terms of this
License will continue to apply to the part which is the covered work,
but the special requirements of the GNU Affero General Public License,
section 13, concerning interaction through a network will apply to the
combination as such.
14. Revised Versions of this License.
The Free Software Foundation may publish revised and/or new versions of
the GNU General Public License from time to time. Such new versions will
be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the
Program specifies that a certain numbered version of the GNU General
Public License "or any later version" applies to it, you have the
option of following the terms and conditions either of that numbered
version or of any later version published by the Free Software
Foundation. If the Program does not specify a version number of the
GNU General Public License, you may choose any version ever published
by the Free Software Foundation.
If the Program specifies that a proxy can decide which future
versions of the GNU General Public License can be used, that proxy's
public statement of acceptance of a version permanently authorizes you
to choose that version for the Program.
Later license versions may give you additional or different
permissions. However, no additional obligations are imposed on any
author or copyright holder as a result of your choosing to follow a
later version.
15. Disclaimer of Warranty.
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
<program> Copyright (C) <year> <name of author>
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
<https://www.gnu.org/licenses/>.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<https://www.gnu.org/licenses/why-not-lgpl.html>.
================================================
FILE: args_manager.py
================================================
import ldm_patched.modules.args_parser as args_parser
args_parser.parser.add_argument("--share", action='store_true', help="Set whether to share on Gradio.")
args_parser.parser.add_argument("--preset", type=str, default=None, help="Apply specified UI preset.")
args_parser.parser.add_argument("--disable-preset-selection", action='store_true',
help="Disables preset selection in Gradio.")
args_parser.parser.add_argument("--language", type=str, default='default',
help="Translate UI using json files in [language] folder. "
"For example, [--language example] will use [language/example.json] for translation.")
# For example, https://github.com/lllyasviel/Fooocus/issues/849
args_parser.parser.add_argument("--disable-offload-from-vram", action="store_true",
help="Force loading models to vram when the unload can be avoided. "
"Some Mac users may need this.")
args_parser.parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
args_parser.parser.add_argument("--disable-image-log", action='store_true',
help="Prevent writing images and logs to the outputs folder.")
args_parser.parser.add_argument("--disable-analytics", action='store_true',
help="Disables analytics for Gradio.")
args_parser.parser.add_argument("--disable-metadata", action='store_true',
help="Disables saving metadata to images.")
args_parser.parser.add_argument("--disable-preset-download", action='store_true',
help="Disables downloading models for presets", default=False)
args_parser.parser.add_argument("--disable-enhance-output-sorting", action='store_true',
help="Disables enhance output sorting for final image gallery.")
args_parser.parser.add_argument("--enable-auto-describe-image", action='store_true',
help="Enables automatic description of uov and enhance image when prompt is empty", default=False)
args_parser.parser.add_argument("--always-download-new-model", action='store_true',
help="Always download newer models", default=False)
args_parser.parser.add_argument("--rebuild-hash-cache", help="Generates missing model and LoRA hashes.",
type=int, nargs="?", metavar="CPU_NUM_THREADS", const=-1)
args_parser.parser.set_defaults(
disable_cuda_malloc=True,
in_browser=True,
port=None
)
args_parser.args = args_parser.parser.parse_args()
# (Disable by default because of issues like https://github.com/lllyasviel/Fooocus/issues/724)
args_parser.args.always_offload_from_vram = not args_parser.args.disable_offload_from_vram
if args_parser.args.disable_analytics:
import os
os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
if args_parser.args.disable_in_browser:
args_parser.args.in_browser = False
args = args_parser.args
================================================
FILE: auth-example.json
================================================
[
{
"user": "sitting-duck-1",
"pass": "very-bad-publicly-known-password-change-it"
}
]
================================================
FILE: build_launcher.py
================================================
import os
win32_root = os.path.dirname(os.path.dirname(__file__))
python_embeded_path = os.path.join(win32_root, 'python_embeded')
is_win32_standalone_build = os.path.exists(python_embeded_path) and os.path.isdir(python_embeded_path)
win32_cmd = '''
.\python_embeded\python.exe -s Fooocus\entry_with_update.py {cmds} %*
pause
'''
def build_launcher():
if not is_win32_standalone_build:
return
presets = [None, 'anime', 'realistic']
for preset in presets:
win32_cmd_preset = win32_cmd.replace('{cmds}', '' if preset is None else f'--preset {preset}')
bat_path = os.path.join(win32_root, 'run.bat' if preset is None else f'run_{preset}.bat')
if not os.path.exists(bat_path):
with open(bat_path, "w", encoding="utf-8") as f:
f.write(win32_cmd_preset)
return
================================================
FILE: css/style.css
================================================
/* based on https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/v1.6.0/style.css */
.loader-container {
display: flex; /* Use flex to align items horizontally */
align-items: center; /* Center items vertically within the container */
white-space: nowrap; /* Prevent line breaks within the container */
}
.loader {
border: 8px solid #f3f3f3; /* Light grey */
border-top: 8px solid #3498db; /* Blue */
border-radius: 50%;
width: 30px;
height: 30px;
animation: spin 2s linear infinite;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
/* Style the progress bar */
progress {
appearance: none; /* Remove default styling */
height: 20px; /* Set the height of the progress bar */
border-radius: 5px; /* Round the corners of the progress bar */
background-color: #f3f3f3; /* Light grey background */
width: 100%;
vertical-align: middle !important;
}
/* Style the progress bar container */
.progress-container {
margin-left: 20px;
margin-right: 20px;
flex-grow: 1; /* Allow the progress container to take up remaining space */
}
/* Set the color of the progress bar fill */
progress::-webkit-progress-value {
background-color: #3498db; /* Blue color for the fill */
}
progress::-moz-progress-bar {
background-color: #3498db; /* Blue color for the fill in Firefox */
}
/* Style the text on the progress bar */
progress::after {
content: attr(value '%'); /* Display the progress value followed by '%' */
position: absolute;
top: 50%;
left: 50%;
transform: translate(-50%, -50%);
color: white; /* Set text color */
font-size: 14px; /* Set font size */
}
/* Style other texts */
.loader-container > span {
margin-left: 5px; /* Add spacing between the progress bar and the text */
}
.progress-bar > .generating {
display: none !important;
}
.progress-bar{
height: 30px !important;
}
.progress-bar span {
text-align: right;
width: 215px;
}
div:has(> #positive_prompt) {
border: none;
}
#positive_prompt {
padding: 1px;
background: var(--background-fill-primary);
}
.type_row {
height: 84px !important;
}
.type_row_half {
height: 34px !important;
}
.refresh_button {
border: none !important;
background: none !important;
font-size: none !important;
box-shadow: none !important;
}
.advanced_check_row {
width: 330px !important;
}
.min_check {
min-width: min(1px, 100%) !important;
}
.resizable_area {
resize: vertical;
overflow: auto !important;
}
.performance_selection label {
width: 140px !important;
}
.aspect_ratios label {
flex: calc(50% - 5px) !important;
}
.aspect_ratios label span {
white-space: nowrap !important;
}
.aspect_ratios label input {
margin-left: -5px !important;
}
.lora_enable label {
height: 100%;
}
.lora_enable label input {
margin: auto;
}
.lora_enable label span {
display: none;
}
@-moz-document url-prefix() {
.lora_weight input[type=number] {
width: 80px;
}
}
#context-menu{
z-index:9999;
position:absolute;
display:block;
padding:0px 0;
border:2px solid #a55000;
border-radius:8px;
box-shadow:1px 1px 2px #CE6400;
width: 200px;
}
.context-menu-items{
list-style: none;
margin: 0;
padding: 0;
}
.context-menu-items a{
display:block;
padding:5px;
cursor:pointer;
}
.context-menu-items a:hover{
background: #a55000;
}
.canvas-tooltip-info {
position: absolute;
top: 28px;
left: 2px;
cursor: help;
background-color: rgba(0, 0, 0, 0.3);
width: 20px;
height: 20px;
border-radius: 50%;
display: flex;
align-items: center;
justify-content: center;
flex-direction: column;
z-index: 100;
}
.canvas-tooltip-info::after {
content: '';
display: block;
width: 2px;
height: 7px;
background-color: white;
margin-top: 2px;
}
.canvas-tooltip-info::before {
content: '';
display: block;
width: 2px;
height: 2px;
background-color: white;
}
.canvas-tooltip-content {
display: none;
background-color: #f9f9f9;
color: #333;
border: 1px solid #ddd;
padding: 15px;
position: absolute;
top: 40px;
left: 10px;
width: 250px;
font-size: 16px;
opacity: 0;
border-radius: 8px;
box-shadow: 0px 8px 16px 0px rgba(0,0,0,0.2);
z-index: 100;
}
.canvas-tooltip:hover .canvas-tooltip-content {
display: block;
animation: fadeIn 0.5s;
opacity: 1;
}
@keyframes fadeIn {
from {opacity: 0;}
to {opacity: 1;}
}
.styler {
overflow:inherit !important;
}
.gradio-container{
overflow: visible;
}
/* fullpage image viewer */
#lightboxModal{
display: none;
position: fixed;
z-index: 1001;
left: 0;
top: 0;
width: 100%;
height: 100%;
overflow: auto;
background-color: rgba(20, 20, 20, 0.95);
user-select: none;
-webkit-user-select: none;
flex-direction: column;
}
.modalControls {
display: flex;
position: absolute;
right: 0px;
left: 0px;
gap: 1em;
padding: 1em;
background-color:rgba(0,0,0,0);
z-index: 1;
transition: 0.2s ease background-color;
}
.modalControls:hover {
background-color:rgba(0,0,0,0.9);
}
.modalClose {
margin-left: auto;
}
.modalControls span{
color: white;
text-shadow: 0px 0px 0.25em black;
font-size: 35px;
font-weight: bold;
cursor: pointer;
width: 1em;
}
.modalControls span:hover, .modalControls span:focus{
color: #999;
text-decoration: none;
}
#lightboxModal > img {
display: block;
margin: auto;
width: auto;
}
#lightboxModal > img.modalImageFullscreen{
object-fit: contain;
height: 100%;
width: 100%;
min-height: 0;
}
.modalPrev,
.modalNext {
cursor: pointer;
position: absolute;
top: 50%;
width: auto;
padding: 16px;
margin-top: -50px;
color: white;
font-weight: bold;
font-size: 20px;
transition: 0.6s ease;
border-radius: 0 3px 3px 0;
user-select: none;
-webkit-user-select: none;
}
.modalNext {
right: 0;
border-radius: 3px 0 0 3px;
}
.modalPrev:hover,
.modalNext:hover {
background-color: rgba(0, 0, 0, 0.8);
}
#imageARPreview {
position: absolute;
top: 0px;
left: 0px;
border: 2px solid red;
background: rgba(255, 0, 0, 0.3);
z-index: 900;
pointer-events: none;
display: none;
}
#stylePreviewOverlay {
opacity: 0;
pointer-events: none;
width: 128px;
height: 128px;
position: fixed;
top: 0px;
left: 0px;
border: solid 1px lightgrey;
transform: translate(-140px, 20px);
background-size: cover;
background-position: center;
background-color: rgba(0, 0, 0, 0.3);
border-radius: 5px;
z-index: 100;
transition: transform 0.1s ease, opacity 0.3s ease;
}
#stylePreviewOverlay.lower-half {
transform: translate(-140px, -140px);
}
/* scrollable box for style selections */
.contain .tabs {
height: 100%;
}
.contain .tabs .tabitem.style_selections_tab {
height: 100%;
}
.contain .tabs .tabitem.style_selections_tab > div:first-child {
height: 100%;
}
.contain .tabs .tabitem.style_selections_tab .style_selections {
min-height: 200px;
height: 100%;
}
.contain .tabs .tabitem.style_selections_tab .style_selections .wrap[data-testid="checkbox-group"] {
position: absolute; /* remove this to disable scrolling within the checkbox-group */
overflow: auto;
padding-right: 2px;
max-height: 100%;
}
.contain .tabs .tabitem.style_selections_tab .style_selections .wrap[data-testid="checkbox-group"] label {
/* max-width: calc(35% - 15px) !important; */ /* add this to enable 3 columns layout */
flex: calc(50% - 5px) !important;
}
.contain .tabs .tabitem.style_selections_tab .style_selections .wrap[data-testid="checkbox-group"] label span {
/* white-space:nowrap; */ /* add this to disable text wrapping (better choice for 3 columns layout) */
overflow: hidden;
text-overflow: ellipsis;
}
/* styles preview tooltip */
.preview-tooltip {
background-color: #fff8;
font-family: monospace;
text-align: center;
border-radius: 5px 5px 0px 0px;
display: none; /* remove this to enable tooltip in preview image */
}
#inpaint_canvas .canvas-tooltip-info {
top: 2px;
}
#inpaint_brush_color input[type=color]{
background: none;
}
================================================
FILE: development.md
================================================
## Running unit tests
Native python:
```
python -m unittest tests/
```
Embedded python (Windows zip file installation method):
```
..\python_embeded\python.exe -m unittest
```
================================================
FILE: docker-compose.yml
================================================
volumes:
fooocus-data:
services:
app:
build: .
image: ghcr.io/lllyasviel/fooocus
ports:
- "7865:7865"
environment:
- CMDARGS=--listen # Arguments for launch.py.
- DATADIR=/content/data # Directory which stores models, outputs dir
- config_path=/content/data/config.txt
- config_example_path=/content/data/config_modification_tutorial.txt
- path_checkpoints=/content/data/models/checkpoints/
- path_loras=/content/data/models/loras/
- path_embeddings=/content/data/models/embeddings/
- path_vae_approx=/content/data/models/vae_approx/
- path_upscale_models=/content/data/models/upscale_models/
- path_inpaint=/content/data/models/inpaint/
- path_controlnet=/content/data/models/controlnet/
- path_clip_vision=/content/data/models/clip_vision/
- path_fooocus_expansion=/content/data/models/prompt_expansion/fooocus_expansion/
- path_outputs=/content/app/outputs/ # Warning: If it is not located under '/content/app', you can't see history log!
volumes:
- fooocus-data:/content/data
#- ./models:/import/models # Once you import files, you don't need to mount again.
#- ./outputs:/import/outputs # Once you import files, you don't need to mount again.
tty: true
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids: ['0']
capabilities: [compute, utility]
================================================
FILE: docker.md
================================================
# Fooocus on Docker
The docker image is based on NVIDIA CUDA 12.4 and PyTorch 2.1, see [Dockerfile](Dockerfile) and [requirements_docker.txt](requirements_docker.txt) for details.
## Requirements
- A computer with specs good enough to run Fooocus, and proprietary Nvidia drivers
- Docker, Docker Compose, or Podman
## Quick start
**More information in the [notes](#notes).**
### Running with Docker Compose
1. Clone this repository
2. Run the docker container with `docker compose up`.
### Running with Docker
```sh
docker run -p 7865:7865 -v fooocus-data:/content/data -it \
--gpus all \
-e CMDARGS=--listen \
-e DATADIR=/content/data \
-e config_path=/content/data/config.txt \
-e config_example_path=/content/data/config_modification_tutorial.txt \
-e path_checkpoints=/content/data/models/checkpoints/ \
-e path_loras=/content/data/models/loras/ \
-e path_embeddings=/content/data/models/embeddings/ \
-e path_vae_approx=/content/data/models/vae_approx/ \
-e path_upscale_models=/content/data/models/upscale_models/ \
-e path_inpaint=/content/data/models/inpaint/ \
-e path_controlnet=/content/data/models/controlnet/ \
-e path_clip_vision=/content/data/models/clip_vision/ \
-e path_fooocus_expansion=/content/data/models/prompt_expansion/fooocus_expansion/ \
-e path_outputs=/content/app/outputs/ \
ghcr.io/lllyasviel/fooocus
```
### Running with Podman
```sh
podman run -p 7865:7865 -v fooocus-data:/content/data -it \
--security-opt=no-new-privileges --cap-drop=ALL --security-opt label=type:nvidia_container_t --device=nvidia.com/gpu=all \
-e CMDARGS=--listen \
-e DATADIR=/content/data \
-e config_path=/content/data/config.txt \
-e config_example_path=/content/data/config_modification_tutorial.txt \
-e path_checkpoints=/content/data/models/checkpoints/ \
-e path_loras=/content/data/models/loras/ \
-e path_embeddings=/content/data/models/embeddings/ \
-e path_vae_approx=/content/data/models/vae_approx/ \
-e path_upscale_models=/content/data/models/upscale_models/ \
-e path_inpaint=/content/data/models/inpaint/ \
-e path_controlnet=/content/data/models/controlnet/ \
-e path_clip_vision=/content/data/models/clip_vision/ \
-e path_fooocus_expansion=/content/data/models/prompt_expansion/fooocus_expansion/ \
-e path_outputs=/content/app/outputs/ \
ghcr.io/lllyasviel/fooocus
```
When you see the message `Use the app with http://0.0.0.0:7865/` in the console, you can access the URL in your browser.
Your models and outputs are stored in the `fooocus-data` volume, which, depending on OS, is stored in `/var/lib/docker/volumes/` (or `~/.local/share/containers/storage/volumes/` when using `podman`).
## Building the container locally
Clone the repository first, and open a terminal in the folder.
Build with `docker`:
```sh
docker build . -t fooocus
```
Build with `podman`:
```sh
podman build . -t fooocus
```
## Details
### Update the container manually (`docker compose`)
When you are using `docker compose up` continuously, the container is not updated to the latest version of Fooocus automatically.
Run `git pull` before executing `docker compose build --no-cache` to build an image with the latest Fooocus version.
You can then start it with `docker compose up`
### Import models, outputs
If you want to import files from models or the outputs folder, you can add the following bind mounts in the [docker-compose.yml](docker-compose.yml) or your preferred method of running the container:
```
#- ./models:/import/models # Once you import files, you don't need to mount again.
#- ./outputs:/import/outputs # Once you import files, you don't need to mount again.
```
After running the container, your files will be copied into `/content/data/models` and `/content/data/outputs`
Since `/content/data` is a persistent volume folder, your files will be persisted even when you re-run the container without the above mounts.
### Paths inside the container
|Path|Details|
|-|-|
|/content/app|The application stored folder|
|/content/app/models.org|Original 'models' folder.<br> Files are copied to the '/content/app/models' which is symlinked to '/content/data/models' every time the container boots. (Existing files will not be overwritten.) |
|/content/data|Persistent volume mount point|
|/content/data/models|The folder is symlinked to '/content/app/models'|
|/content/data/outputs|The folder is symlinked to '/content/app/outputs'|
### Environments
You can change `config.txt` parameters by using environment variables.
**The priority of using the environments is higher than the values defined in `config.txt`, and they will be saved to the `config_modification_tutorial.txt`**
Docker specified environments are there. They are used by 'entrypoint.sh'
|Environment|Details|
|-|-|
|DATADIR|'/content/data' location.|
|CMDARGS|Arguments for [entry_with_update.py](entry_with_update.py) which is called by [entrypoint.sh](entrypoint.sh)|
|config_path|'config.txt' location|
|config_example_path|'config_modification_tutorial.txt' location|
|HF_MIRROR| huggingface mirror site domain|
You can also use the same json key names and values explained in the 'config_modification_tutorial.txt' as the environments.
See examples in the [docker-compose.yml](docker-compose.yml)
## Notes
- Please keep 'path_outputs' under '/content/app'. Otherwise, you may get an error when you open the history log.
- Docker on Mac/Windows still has issues in the form of slow volume access when you use "bind mount" volumes. Please refer to [this article](https://docs.docker.com/storage/volumes/#use-a-volume-with-docker-compose) for not using "bind mount".
- The MPS backend (Metal Performance Shaders, Apple Silicon M1/M2/etc.) is not yet supported in Docker, see https://github.com/pytorch/pytorch/issues/81224
- You can also use `docker compose up -d` to start the container detached and connect to the logs with `docker compose logs -f`. This way you can also close the terminal and keep the container running.
================================================
FILE: entry_with_update.py
================================================
import os
import sys
root = os.path.dirname(os.path.abspath(__file__))
sys.path.append(root)
os.chdir(root)
try:
import pygit2
pygit2.option(pygit2.GIT_OPT_SET_OWNER_VALIDATION, 0)
repo = pygit2.Repository(os.path.abspath(os.path.dirname(__file__)))
branch_name = repo.head.shorthand
remote_name = 'origin'
remote = repo.remotes[remote_name]
remote.fetch()
local_branch_ref = f'refs/heads/{branch_name}'
local_branch = repo.lookup_reference(local_branch_ref)
remote_reference = f'refs/remotes/{remote_name}/{branch_name}'
remote_commit = repo.revparse_single(remote_reference)
merge_result, _ = repo.merge_analysis(remote_commit.id)
if merge_result & pygit2.GIT_MERGE_ANALYSIS_UP_TO_DATE:
print("Already up-to-date")
elif merge_result & pygit2.GIT_MERGE_ANALYSIS_FASTFORWARD:
local_branch.set_target(remote_commit.id)
repo.head.set_target(remote_commit.id)
repo.checkout_tree(repo.get(remote_commit.id))
repo.reset(local_branch.target, pygit2.GIT_RESET_HARD)
print("Fast-forward merge")
elif merge_result & pygit2.GIT_MERGE_ANALYSIS_NORMAL:
print("Update failed - Did you modify any file?")
except Exception as e:
print('Update failed.')
print(str(e))
print('Update succeeded.')
from launch import *
================================================
FILE: entrypoint.sh
================================================
#!/bin/bash
ORIGINALDIR=/content/app
# Use predefined DATADIR if it is defined
[[ x"${DATADIR}" == "x" ]] && DATADIR=/content/data
# Make persistent dir from original dir
function mklink () {
mkdir -p $DATADIR/$1
ln -s $DATADIR/$1 $ORIGINALDIR
}
# Copy old files from import dir
function import () {
(test -d /import/$1 && cd /import/$1 && cp -Rpn . $DATADIR/$1/)
}
cd $ORIGINALDIR
# models
mklink models
# Copy original files
(cd $ORIGINALDIR/models.org && cp -Rpn . $ORIGINALDIR/models/)
# Import old files
import models
# outputs
mklink outputs
# Import old files
import outputs
# Start application
python launch.py $*
================================================
FILE: environment.yaml
================================================
name: fooocus
channels:
- defaults
dependencies:
- python=3.10
- pip=23.0
- packaging
================================================
FILE: experiments_expansion.py
================================================
from modules.expansion import FooocusExpansion
expansion = FooocusExpansion()
text = 'a handsome man'
for i in range(64):
print(expansion(text, seed=i))
================================================
FILE: experiments_face.py
================================================
import cv2
import extras.face_crop as cropper
img = cv2.imread('lena.png')
result = cropper.crop_image(img)
cv2.imwrite('lena_result.png', result)
================================================
FILE: experiments_interrogate.py
================================================
import cv2
from extras.interrogate import default_interrogator as default_interrogator_photo
from extras.wd14tagger import default_interrogator as default_interrogator_anime
img = cv2.imread('./test_imgs/red_box.jpg')[:, :, ::-1].copy()
print(default_interrogator_photo(img))
img = cv2.imread('./test_imgs/miku.jpg')[:, :, ::-1].copy()
print(default_interrogator_anime(img))
================================================
FILE: experiments_mask_generation.py
================================================
# https://github.com/sail-sg/EditAnything/blob/main/sam2groundingdino_edit.py
import numpy as np
from PIL import Image
from extras.inpaint_mask import SAMOptions, generate_mask_from_image
original_image = Image.open('cat.webp')
image = np.array(original_image, dtype=np.uint8)
sam_options = SAMOptions(
dino_prompt='eye',
dino_box_threshold=0.3,
dino_text_threshold=0.25,
dino_erode_or_dilate=0,
dino_debug=False,
max_detections=2,
model_type='vit_b'
)
mask_image, _, _, _ = generate_mask_from_image(image, sam_options=sam_options)
merged_masks_img = Image.fromarray(mask_image)
merged_masks_img.show()
================================================
FILE: extras/BLIP/configs/bert_config.json
================================================
{
"architectures": [
"BertModel"
],
"attention_probs_dropout_prob": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"type_vocab_size": 2,
"vocab_size": 30522,
"encoder_width": 768,
"add_cross_attention": true
}
================================================
FILE: extras/BLIP/configs/caption_coco.yaml
================================================
image_root: '/export/share/datasets/vision/coco/images/'
ann_root: 'annotation'
coco_gt_root: 'annotation/coco_gt'
# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_caption_capfilt_large.pth'
# size of vit model; base or large
vit: 'base'
vit_grad_ckpt: False
vit_ckpt_layer: 0
batch_size: 32
init_lr: 1e-5
# vit: 'large'
# vit_grad_ckpt: True
# vit_ckpt_layer: 5
# batch_size: 16
# init_lr: 2e-6
image_size: 384
# generation configs
max_length: 20
min_length: 5
num_beams: 3
prompt: 'a picture of '
# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 5
================================================
FILE: extras/BLIP/configs/med_config.json
================================================
{
"architectures": [
"BertModel"
],
"attention_probs_dropout_prob": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"type_vocab_size": 2,
"vocab_size": 30524,
"encoder_width": 768,
"add_cross_attention": true
}
================================================
FILE: extras/BLIP/configs/nlvr.yaml
================================================
image_root: '/export/share/datasets/vision/NLVR2/'
ann_root: 'annotation'
# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_nlvr.pth'
#size of vit model; base or large
vit: 'base'
batch_size_train: 16
batch_size_test: 64
vit_grad_ckpt: False
vit_ckpt_layer: 0
max_epoch: 15
image_size: 384
# optimizer
weight_decay: 0.05
init_lr: 3e-5
min_lr: 0
================================================
FILE: extras/BLIP/configs/nocaps.yaml
================================================
image_root: '/export/share/datasets/vision/nocaps/'
ann_root: 'annotation'
# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_caption_capfilt_large.pth'
vit: 'base'
batch_size: 32
image_size: 384
max_length: 20
min_length: 5
num_beams: 3
prompt: 'a picture of '
================================================
FILE: extras/BLIP/configs/pretrain.yaml
================================================
train_file: ['/export/share/junnan-li/VL_pretrain/annotation/coco_karpathy_train.json',
'/export/share/junnan-li/VL_pretrain/annotation/vg_caption.json',
]
laion_path: ''
# size of vit model; base or large
vit: 'base'
vit_grad_ckpt: False
vit_ckpt_layer: 0
image_size: 224
batch_size: 75
queue_size: 57600
alpha: 0.4
# optimizer
weight_decay: 0.05
init_lr: 3e-4
min_lr: 1e-6
warmup_lr: 1e-6
lr_decay_rate: 0.9
max_epoch: 20
warmup_steps: 3000
================================================
FILE: extras/BLIP/configs/retrieval_coco.yaml
================================================
image_root: '/export/share/datasets/vision/coco/images/'
ann_root: 'annotation'
dataset: 'coco'
# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_coco.pth'
# size of vit model; base or large
vit: 'base'
batch_size_train: 32
batch_size_test: 64
vit_grad_ckpt: True
vit_ckpt_layer: 4
init_lr: 1e-5
# vit: 'large'
# batch_size_train: 16
# batch_size_test: 32
# vit_grad_ckpt: True
# vit_ckpt_layer: 12
# init_lr: 5e-6
image_size: 384
queue_size: 57600
alpha: 0.4
k_test: 256
negative_all_rank: True
# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 6
================================================
FILE: extras/BLIP/configs/retrieval_flickr.yaml
================================================
image_root: '/export/share/datasets/vision/flickr30k/'
ann_root: 'annotation'
dataset: 'flickr'
# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_flickr.pth'
# size of vit model; base or large
vit: 'base'
batch_size_train: 32
batch_size_test: 64
vit_grad_ckpt: True
vit_ckpt_layer: 4
init_lr: 1e-5
# vit: 'large'
# batch_size_train: 16
# batch_size_test: 32
# vit_grad_ckpt: True
# vit_ckpt_layer: 10
# init_lr: 5e-6
image_size: 384
queue_size: 57600
alpha: 0.4
k_test: 128
negative_all_rank: False
# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 6
================================================
FILE: extras/BLIP/configs/retrieval_msrvtt.yaml
================================================
video_root: '/export/share/dongxuli/data/msrvtt_retrieval/videos'
ann_root: 'annotation'
# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_coco.pth'
# size of vit model; base or large
vit: 'base'
batch_size: 64
k_test: 128
image_size: 384
num_frm_test: 8
================================================
FILE: extras/BLIP/configs/vqa.yaml
================================================
vqa_root: '/export/share/datasets/vision/VQA/Images/mscoco/' #followed by train2014/
vg_root: '/export/share/datasets/vision/visual-genome/' #followed by image/
train_files: ['vqa_train','vqa_val','vg_qa']
ann_root: 'annotation'
# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_vqa_capfilt_large.pth'
# size of vit model; base or large
vit: 'base'
batch_size_train: 16
batch_size_test: 32
vit_grad_ckpt: False
vit_ckpt_layer: 0
init_lr: 2e-5
image_size: 480
k_test: 128
inference: 'rank'
# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 10
================================================
FILE: extras/BLIP/models/bert_tokenizer/config.json
================================================
{
"architectures": [
"BertForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"transformers_version": "4.6.0.dev0",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 30522
}
================================================
FILE: extras/BLIP/models/bert_tokenizer/tokenizer.json
================================================
{"version":"1.0","truncation":null,"padding":null,"added_tokens":[{"id":0,"special":true,"content":"[PAD]","single_word":false,"lstrip":false,"rstrip":false,"normalized":false},{"id":100,"special":true,"content":"[UNK]","single_word":false,"lstrip":false,"rstrip":false,"normalized":false},{"id":101,"special":true,"content":"[CLS]","single_word":false,"lstrip":false,"rstrip":false,"normalized":false},{"id":102,"special":true,"content":"[SEP]","single_word":false,"lstrip":false,"rstrip":false,"normalized":false},{"id":103,"special":true,"content":"[MASK]","single_word":false,"lstrip":false,"rstrip":false,"normalized":false}],"normalizer":{"type":"BertNormalizer","clean_text":true,"handle_chinese_chars":true,"strip_accents":null,"lowercase":true},"pre_tokenizer":{"type":"BertPreTokenizer"},"post_processor":{"type":"TemplateProcessing","single":[{"SpecialToken":{"id":"[CLS]","type_id":0}},{"Sequence":{"id":"A","type_id":0}},{"SpecialToken":{"id":"[SEP]","type_id":0}}],"pair":[{"SpecialToken":{"id":"[CLS]","type_id":0}},{"Sequence":{"id":"A","type_id":0}},{"SpecialToken":{"id":"[SEP]","type_id":0}},{"Sequence":{"id":"B","type_id":1}},{"SpecialToken":{"id":"[SEP]","type_id":1}}],"special_tokens":{"[CLS]":{"id":"[CLS]","ids":[101],"tokens":["[CLS]"]},"[SEP]":{"id":"[SEP]","ids":[102],"tokens":["[SEP]"]}}},"decoder":{"type":"WordPiece","prefix":"##","cleanup":true},"model":{"unk_token":"[UNK]","continuing_subword_prefix":"##","max_input_chars_per_word":100,"vocab":{"[PAD]":0,"[unused0]":1,"[unused1]":2,"[unused2]":3,"[unused3]":4,"[unused4]":5,"[unused5]":6,"[unused6]":7,"[unused7]":8,"[unused8]":9,"[unused9]":10,"[unused10]":11,"[unused11]":12,"[unused12]":13,"[unused13]":14,"[unused14]":15,"[unused15]":16,"[unused16]":17,"[unused17]":18,"[unused18]":19,"[unused19]":20,"[unused20]":21,"[unused21]":22,"[unused22]":23,"[unused23]":24,"[unused24]":25,"[unused25]":26,"[unused26]":27,"[unused27]":28,"[unused28]":29,"[unused29]":30,"[unused30]":31,"[unused31]":32,"[unused32]":33,"[unused33]":34,"[unused34]":35,"[unused35]":36,"[unused36]":37,"[unused37]":38,"[unused38]":39,"[unused39]":40,"[unused40]":41,"[unused41]":42,"[unused42]":43,"[unused43]":44,"[unused44]":45,"[unused45]":46,"[unused46]":47,"[unused47]":48,"[unused48]":49,"[unused49]":50,"[unused50]":51,"[unused51]":52,"[unused52]":53,"[unused53]":54,"[unused54]":55,"[unused55]":56,"[unused56]":57,"[unused57]":58,"[unused58]":59,"[unused59]":60,"[unused60]":61,"[unused61]":62,"[unused62]":63,"[unused63]":64,"[unused64]":65,"[unused65]":66,"[unused66]":67,"[unused67]":68,"[unused68]":69,"[unused69]":70,"[unused70]":71,"[unused71]":72,"[unused72]":73,"[unused73]":74,"[unused74]":75,"[unused75]":76,"[unused76]":77,"[unused77]":78,"[unused78]":79,"[unused79]":80,"[unused80]":81,"[unused81]":82,"[unused82]":83,"[unused83]":84,"[unused84]":85,"[unused85]":86,"[unused86]":87,"[unused87]":88,"[unused88]":89,"[unused89]":90,"[unused90]":91,"[unused91]":92,"[unused92]":93,"[unused93]":94,"[unused94]":95,"[unused95]":96,"[unused96]":97,"[unused97]":98,"[unused98]":99,"[UNK]":100,"[CLS]":101,"[SEP]":102,"[MASK]":103,"[unused99]":104,"[unused100]":105,"[unused101]":106,"[unused102]":107,"[unused103]":108,"[unused104]":109,"[unused105]":110,"[unused106]":111,"[unused107]":112,"[unused108]":113,"[unused109]":114,"[unused110]":115,"[unused111]":116,"[unused112]":117,"[unused113]":118,"[unused114]":119,"[unused115]":120,"[unused116]":121,"[unused117]":122,"[unused118]":123,"[unused119]":124,"[unused120]":125,"[unused121]":126,"[unused122]":127,"[unused123]":128,"[unused124]":129,"[unused125]":130,"[unused126]":131,"[unused127]":132,"[unused128]":133,"[unused129]":134,"[unused130]":135,"[unused131]":136,"[unused132]":137,"[unused133]":138,"[unused134]":139,"[unused135]":140,"[unused136]":141,"[unused137]":142,"[unused138]":143,"[unused139]":144,"[unused140]":145,"[unused141]":146,"[unused142]":147,"[unused143]":148,"[unused144]":149,"[unused145]":150,"[unused146]":151,"[unused147]":152,"[unused148]":153,"[unused149]":154,"[unused150]":155,"[unused151]":156,"[unused152]":157,"[unused153]":158,"[unused154]":159,"[unused155]":160,"[unused156]":161,"[unused157]":162,"[unused158]":163,"[unused159]":164,"[unused160]":165,"[unused161]":166,"[unused162]":167,"[unused163]":168,"[unused164]":169,"[unused165]":170,"[unused166]":171,"[unused167]":172,"[unused168]":173,"[unused169]":174,"[unused170]":175,"[unused171]":176,"[unused172]":177,"[unused173]":178,"[unused174]":179,"[unused175]":180,"[unused176]":181,"[unused177]":182,"[unused178]":183,"[unused179]":184,"[unused180]":185,"[unused181]":186,"[unused182]":187,"[unused183]":188,"[unused184]":189,"[unused185]":190,"[unused186]":191,"[unused187]":192,"[unused188]":193,"[unused189]":194,"[unused190]":195,"[unused191]":196,"[unused192]":197,"[unused193]":198,"[unused194]":199,"[unused195]":200,"[unused196]":201,"[unused197]":202,"[unused198]":203,"[unused199]":204,"[unused200]":205,"[unused201]":206,"[unused202]":207,"[unused203]":208,"[unused204]":209,"[unused205]":210,"[unused206]":211,"[unused207]":212,"[unused208]":213,"[unused209]":214,"[unused210]":215,"[unused211]":216,"[unused212]":217,"[unused213]":218,"[unused214]":219,"[unused215]":220,"[unused216]":221,"[unused217]":222,"[unused218]":223,"[unused219]":224,"[unused220]":225,"[unused221]":226,"[unused222]":227,"[unused223]":228,"[unused224]":229,"[unused225]":230,"[unused226]":231,"[unused227]":232,"[unused228]":233,"[unused229]":234,"[unused230]":235,"[unused231]":236,"[unused232]":237,"[unused233]":238,"[unused234]":239,"[unused235]":240,"[unused236]":241,"[unused237]":242,"[unused238]":243,"[unused239]":244,"[unused240]":245,"[unused241]":246,"[unused242]":247,"[unused243]":248,"[unused244]":249,"[unused245]":250,"[unused246]":251,"[unused247]":252,"[unused248]":253,"[unused249]":254,"[unused250]":255,"[unused251]":256,"[unused252]":257,"[unused253]":258,"[unused254]":259,"[unused255]":260,"[unused256]":261,"[unused257]":262,"[unused258]":263,"[unused259]":264,"[unused260]":265,"[unused261]":266,"[unused262]":267,"[unused263]":268,"[unused264]":269,"[unused265]":270,"[unused266]":271,"[unused267]":272,"[unused268]":273,"[unused269]":274,"[unused270]":275,"[unused271]":276,"[unused272]":277,"[unused273]":278,"[unused274]":279,"[unused275]":280,"[unused276]":281,"[unused277]":282,"[unused278]":283,"[unused279]":284,"[unused280]":285,"[unused281]":286,"[unused282]":287,"[unused283]":288,"[unused284]":289,"[unused285]":290,"[unused286]":291,"[unused287]":292,"[unused288]":293,"[unused289]":294,"[unused290]":295,"[unused291]":296,"[unused292]":297,"[unused293]":298,"[unused294]":299,"[unused295]":300,"[unused296]":301,"[unused297]":302,"[unused298]":303,"[unused299]":304,"[unused300]":305,"[unused301]":306,"[unused302]":307,"[unused303]":308,"[unused304]":309,"[unused305]":310,"[unused306]":311,"[unused307]":312,"[unused308]":313,"[unused309]":314,"[unused310]":315,"[unused311]":316,"[unused312]":317,"[unused313]":318,"[unused314]":319,"[unused315]":320,"[unused316]":321,"[unused317]":322,"[unused318]":323,"[unused319]":324,"[unused320]":325,"[unused321]":326,"[unused322]":327,"[unused323]":328,"[unused324]":329,"[unused325]":330,"[unused326]":331,"[unused327]":332,"[unused328]":333,"[unused329]":334,"[unused330]":335,"[unused331]":336,"[unused332]":337,"[unused333]":338,"[unused334]":339,"[unused335]":340,"[unused336]":341,"[unused337]":342,"[unused338]":343,"[unused339]":344,"[unused340]":345,"[unused341]":346,"[unused342]":347,"[unused343]":348,"[unused344]":349,"[unused345]":350,"[unused346]":351,"[unused347]":352,"[unused348]":353,"[unused349]":354,"[unused350]":355,"[unused351]":356,"[unused352]":357,"[unused353]":358,"[unused354]":359,"[unused355]":360,"[unused356]":361,"[unused357]":362,"[unused358]":363,"[unused359]":364,"[unused360]":365,"[unused361]":366,"[unused362]":367,"[unused363]":368,"[unused364]":369,"[unused365]":370,"[unused366]":371,"[unused367]":372,"[unused368]":373,"[unused369]":374,"[unused370]":375,"[unused371]":376,"[unused372]":377,"[unused373]":378,"[unused374]":379,"[unused375]":380,"[unused376]":381,"[unused377]":382,"[unused378]":383,"[unused379]":384,"[unused380]":385,"[unused381]":386,"[unused382]":387,"[unused383]":388,"[unused384]":389,"[unused385]":390,"[unused386]":391,"[unused387]":392,"[unused388]":393,"[unused389]":394,"[unused390]":395,"[unused391]":396,"[unused392]":397,"[unused393]":398,"[unused394]":399,"[unused395]":400,"[unused396]":401,"[unused397]":402,"[unused398]":403,"[unused399]":404,"[unused400]":405,"[unused401]":406,"[unused402]":407,"[unused403]":408,"[unused404]":409,"[unused405]":410,"[unused406]":411,"[unused407]":412,"[unused408]":413,"[unused409]":414,"[unused410]":415,"[unused411]":416,"[unused412]":417,"[unused413]":418,"[unused414]":419,"[unused415]":420,"[unused416]":421,"[unused417]":422,"[unused418]":423,"[unused419]":424,"[unused420]":425,"[unused421]":426,"[unused422]":427,"[unused423]":428,"[unused424]":429,"[unused425]":430,"[unused426]":431,"[unused427]":432,"[unused428]":433,"[unused429]":434,"[unused430]":435,"[unused431]":436,"[unused432]":437,"[unused433]":438,"[unused434]":439,"[unused435]":440,"[unused436]":441,"[unused437]":442,"[unused438]":443,"[unused439]":444,"[unused440]":445,"[unused441]":446,"[unused442]":447,"[unused443]":448,"[unused444]":449,"[unused445]":450,"[unused446]":451,"[unused447]":452,"[unused448]":453,"[unused449]":454,"[unused450]":455,"[unused451]":456,"[unused452]":457,"[unused453]":458,"[unused454]":459,"[unused455]":460,"[unused456]":461,"[unused457]":462,"[unused458]":463,"[unused459]":464,"[unused460]":465,"[unused461]":466,"[unused462]":467,"[unused463]":468,"[unused464]":469,"[unused465]":470,"[unused466]":471,"[unused467]":472,"[unused468]":473,"[unused469]":474,"[unused470]":475,"[unused471]":476,"[unused472]":477,"[unused473]":478,"[unused474]":479,"[unused475]":480,"[unused476]":481,"[unused477]":482,"[unused478]":483,"[unused479]":484,"[unused480]":485,"[unused481]":486,"[unused482]":487,"[unused483]":488,"[unused484]":489,"[unused485]":490,"[unused486]":491,"[unused487]":492,"[unused488]":493,"[unused489]":494,"[unused490]":495,"[unused491]":496,"[unused492]":497,"[unused493]":498,"[unused494]":499,"[unused495]":500,"[unused496]":501,"[unused497]":502,"[unused498]":503,"[unused499]":504,"[unused500]":505,"[unused501]":506,"[unused502]":507,"[unused503]":508,"[unused504]":509,"[unused505]":510,"[unused506]":511,"[unused507]":512,"[unused508]":513,"[unused509]":514,"[unused510]":515,"[unused511]":516,"[unused512]":517,"[unused513]":518,"[unused514]":519,"[unused515]":520,"[unused516]":521,"[unused517]":522,"[unused518]":523,"[unused519]":524,"[unused520]":525,"[unused521]":526,"[unused522]":527,"[unused523]":528,"[unused524]":529,"[unused525]":530,"[unused526]":531,"[unused527]":532,"[unused528]":533,"[unused529]":534,"[unused530]":535,"[unused531]":536,"[unused532]":537,"[unused533]":538,"[unused534]":539,"[unused535]":540,"[unused536]":541,"[unused537]":542,"[unused538]":543,"[unused539]":544,"[unused540]":545,"[unused541]":546,"[unused542]":547,"[unused543]":548,"[unused544]":549,"[unused545]":550,"[unused546]":551,"[unused547]":552,"[unused548]":553,"[unused549]":554,"[unused550]":555,"[unused551]":556,"[unused552]":557,"[unused553]":558,"[unused554]":559,"[unused555]":560,"[unused556]":561,"[unused557]":562,"[unused558]":563,"[unused559]":564,"[unused560]":565,"[unused561]":566,"[unused562]":567,"[unused563]":568,"[unused564]":569,"[unused565]":570,"[unused566]":571,"[unused567]":572,"[unused568]":573,"[unused569]":574,"[unused570]":575,"[unused571]":576,"[unused572]":577,"[unused573]":578,"[unused574]":579,"[unused575]":580,"[unused576]":581,"[unused577]":582,"[unused578]":583,"[unused579]":584,"[unused580]":585,"[unused581]":586,"[unused582]":587,"[unused583]":588,"[unused584]":589,"[unused585]":590,"[unused586]":591,"[unused587]":592,"[unused588]":593,"[unused589]":594,"[unused590]":595,"[unused591]":596,"[unused592]":597,"[unused593]":598,"[unused594]":599,"[unused595]":600,"[unused596]":601,"[unused597]":602,"[unused598]":603,"[unused599]":604,"[unused600]":605,"[unused601]":606,"[unused602]":607,"[unused603]":608,"[unused604]":609,"[unused605]":610,"[unused606]":611,"[unused607]":612,"[unused608]":613,"[unused609]":614,"[unused610]":615,"[unused611]":616,"[unused612]":617,"[unused613]":618,"[unused614]":619,"[unused615]":620,"[unused616]":621,"[unused617]":622,"[unused618]":623,"[unused619]":624,"[unused620]":625,"[unused621]":626,"[unused622]":627,"[unused623]":628,"[unused624]":629,"[unused625]":630,"[unused626]":631,"[unused627]":632,"[unused628]":633,"[unused629]":634,"[unused630]":635,"[unused631]":636,"[unused632]":637,"[unused633]":638,"[unused634]":639,"[unused635]":640,"[unused636]":641,"[unused637]":642,"[unused638]":643,"[unused639]":644,"[unused640]":645,"[unused641]":646,"[unused642]":647,"[unused643]":648,"[unused644]":649,"[unused645]":650,"[unused646]":651,"[unused647]":652,"[unused648]":653,"[unused649]":654,"[unused650]":655,"[unused651]":656,"[unused652]":657,"[unused653]":658,"[unused654]":659,"[unused655]":660,"[unused656]":661,"[unused657]":662,"[unused658]":663,"[unused659]":664,"[unused660]":665,"[unused661]":666,"[unused662]":667,"[unused663]":668,"[unused664]":669,"[unused665]":670,"[unused666]":671,"[unused667]":672,"[unused668]":673,"[unused669]":674,"[unused670]":675,"[unused671]":676,"[unused672]":677,"[unused673]":678,"[unused674]":679,"[unused675]":680,"[unused676]":681,"[unused677]":682,"[unused678]":683,"[unused679]":684,"[unused680]":685,"[unused681]":686,"[unused682]":687,"[unused683]":688,"[unused684]":689,"[unused685]":690,"[unused686]":691,"[unused687]":692,"[unused688]":693,"[unused689]":694,"[unused690]":695,"[unused691]":696,"[unused692]":697,"[unused693]":698,"[unused694]":699,"[unused695]":700,"[unused696]":701,"[unused697]":702,"[unused698]":703,"[unused699]":704,"[unused700]":705,"[unused701]":706,"[unused702]":707,"[unused703]":708,"[unused704]":709,"[unused705]":710,"[unused706]":711,"[unused707]":712,"[unused708]":713,"[unused709]":714,"[unused710]":715,"[unused711]":716,"[unused712]":717,"[unused713]":718,"[unused714]":719,"[unused715]":720,"[unused716]":721,"[unused717]":722,"[unused718]":723,"[unused719]":724,"[unused720]":725,"[unused721]":726,"[unused722]":727,"[unused723]":728,"[unused724]":729,"[unused725]":730,"[unused726]":731,"[unused727]":732,"[unused728]":733,"[unused729]":734,"[unused730]":735,"[unused731]":736,"[unused732]":737,"[unused733]":738,"[unused734]":739,"[unused735]":740,"[unused736]":741,"[unused737]":742,"[unused738]":743,"[unused739]":744,"[unused740]":745,"[unused741]":746,"[unused742]":747,"[unused743]":748,"[unused744]":749,"[unused745]":750,"[unused746]":751,"[unused747]":752,"[unused748]":753,"[unused749]":754,"[unused750]":755,"[unused751]":756,"[unused752]":757,"[unused753]":758,"[unused754]":759,"[unused755]":760,"[unused756]":761,"[unused757]":762,"[unused758]":763,"[unused759]":764,"[unused760]":765,"[unused761]":766,"[unused762]":767,"[unused763]":768,"[unused764]":769,"[unused765]":770,"[unused766]":771,"[unused767]":772,"[unused768]":773,"[unused769]":774,"[unused770]":775,"[unused771]":776,"[unused772]":777,"[unused773]":778,"[unused774]":779,"[unused775]":780,"[unused776]":781,"[unused777]":782,"[unused778]":783,"[unused779]":784,"[unused780]":785,"[unused781]":786,"[unused782]":787,"[unused783]":788,"[unused784]":789,"[unused785]":790,"[unused786]":791,"[unused787]":792,"[unused788]":793,"[unused789]":794,"[unused790]":795,"[unused791]":796,"[unused792]":797,"[unused793]":798,"[unused794]":799,"[unused795]":800,"[unused796]":801,"[unused797]":802,"[unused798]":803,"[unused799]":804,"[unused800]":805,"[unused801]":806,"[unused802]":807,"[unused803]":808,"[unused804]":809,"[unused805]":810,"[unused806]":811,"[unused807]":812,"[unused808]":813,"[unused809]":814,"[unused810]":815,"[unused811]":816,"[unused812]":817,"[unused813]":818,"[unused814]":819,"[unused815]":820,"[unused816]":821,"[unused817]":822,"[unused818]":823,"[unused819]":824,"[unused820]":825,"[unused821]":826,"[unused822]":827,"[unused823]":828,"[unused824]":829,"[unused825]":830,"[unused826]":831,"[unused827]":832,"[unused828]":833,"[unused829]":834,"[unused830]":835,"[unused831]":836,"[unused832]":837,"[unused833]":838,"[unused834]":839,"[unused835]":840,"[unused836]":841,"[unused837]":842,"[unused838]":843,"[unused839]":844,"[unused840]":845,"[unused841]":846,"[unused842]":847,"[unused843]":848,"[unused844]":849,"[unused845]":850,"[unused846]":851,"[unused847]":852,"[unused848]":853,"[unused849]":854,"[unused850]":855,"[unused851]":856,"[unused852]":857,"[unused853]":858,"[unused854]":859,"[unused855]":860,"[unused856]":861,"[unused857]":862,"[unused858]":863,"[unused859]":864,"[unused860]":865,"[unused861]":866,"[unused862]":867,"[unused863]":868,"[unused864]":869,"[unused865]":870,"[unused866]":871,"[unused867]":872,"[unused868]":873,"[unused869]":874,"[unused870]":875,"[unused871]":876,"[unused872]":877,"[unused873]":878,"[unused874]":879,"[unused875]":880,"[unused876]":881,"[unused877]":882,"[unused878]":883,"[unused879]":884,"[unused880]":885,"[unused881]":886,"[unused882]":887,"[unused883]":888,"[unused884]":889,"[unused885]":890,"[unused886]":891,"[unused887]":892,"[unused888]":893,"[unused889]":894,"[unused890]":895,"[unused891]":896,"[unused892]":897,"[unused893]":898,"[unused894]":899,"[unused895]":900,"[unused896]":901,"[unused897]":902,"[unused898]":903,"[unused899]":904,"[unused900]":905,"[unused901]":906,"[unused902]":907,"[unused903]":908,"[unused904]":909,"[unused905]":910,"[unused906]":911,"[unused907]":912,"[unused908]":913,"[unused909]":914,"[unused910]":915,"[unused911]":916,"[unused912]":917,"[unused913]":918,"[unused914]":919,"[unused915]":920,"[unused916]":921,"[unused917]":922,"[unused918]":923,"[unused919]":924,"[unused920]":925,"[unused921]":926,"[unused922]":927,"[unused923]":928,"[unused924]":929,"[unused925]":930,"[unused926]":931,"[unused927]":932,"[unused928]":933,"[unused929]":934,"[unused930]":935,"[unused931]":936,"[unused932]":937,"[unused933]":938,"[unused934]":939,"[unused935]":940,"[unused936]":941,"[unused937]":942,"[unused938]":943,"[unused939]":944,"[unused940]":945,"[unused941]":946,"[unused942]":947,"[unused943]":948,"[unused944]":949,"[unused945]":950,"[unused946]":951,"[unused947]":952,"[unused948]":953,"[unused949]":954,"[unused950]":955,"[unused951]":956,"[unused952]":957,"[unused953]":958,"[unused954]":959,"[unused955]":960,"[unused956]":961,"[unused957]":962,"[unused958]":963,"[unused959]":964,"[unused960]":965,"[unused961]":966,"[unused962]":967,"[unused963]":968,"[unused964]":969,"[unused965]":970,"[unused966]":971,"[unused967]":972,"[unused968]":973,"[unused969]":974,"[unused970]":975,"[unused971]":976,"[unused972]":977,"[unused973]":978,"[unused974]":979,"[unused975]":980,"[unused976]":981,"[unused977]":982,"[unused978]":983,"[unused979]":984,"[unused980]":985,"[unused981]":986,"[unused982]":987,"[unused983]":988,"[unused984]":989,"[unused985]":990,"[unused986]":991,"[unused987]":992,"[unused988]":993,"[unused989]":994,"[unused990]":995,"[unused991]":996,"[unused992]":997,"[unused993]":998,"!":999,"\"":1000,"#":1001,"$":1002,"%":1003,"&":1004,"'":1005,"(":1006,")":1007,"*":1008,"+":1009,",":1010,"-":1011,".":1012,"/":1013,"0":1014,"1":1015,"2":1016,"3":1017,"4":1018,"5":1019,"6":1020,"7":1021,"8":1022,"9":1023,":":1024,";":1025,"<":1026,"=":1027,">":1028,"?":1029,"@":1030,"[":1031,"\\":1032,"]":1033,"^":1034,"_":1035,"`":1036,"a":1037,"b":1038,"c":1039,"d":1040,"e":1041,"f":1042,"g":1043,"h":1044,"i":1045,"j":1046,"k":1047,"l":1048,"m":1049,"n":1050,"o":1051,"p":1052,"q":1053,"r":1054,"s":1055,"t":1056,"u":1057,"v":1058,"w":1059,"x":1060,"y":1061,"z":1062,"{":1063,"|":1064,"}":1065,"~":1066,"¡":1067,"¢":1068,"£":1069,"¤":1070,"¥":1071,"¦":1072,"§":1073,"¨":1074,"©":1075,"ª":1076,"«":1077,"¬":1078,"®":1079,"°":1080,"±":1081,"²":1082,"³":1083,"´":1084,"µ":1085,"¶":1086,"·":1087,"¹":1088,"º":1089,"»":1090,"¼":1091,"½":1092,"¾":1093,"¿":1094,"×":1095,"ß":1096,"æ":1097,"ð":1098,"÷":1099,"ø":1100,"þ":1101,"đ":1102,"ħ":1103,"ı":1104,"ł":1105,"ŋ":1106,"œ":1107,"ƒ":1108,"ɐ":1109,"ɑ":1110,"ɒ":1111,"ɔ":1112,"ɕ":1113,"ə":1114,"ɛ":1115,"ɡ":1116,"ɣ":1117,"ɨ":1118,"ɪ":1119,"ɫ":1120,"ɬ":1121,"ɯ":1122,"ɲ":1123,"ɴ":1124,"ɹ":1125,"ɾ":1126,"ʀ":1127,"ʁ":1128,"ʂ":1129,"ʃ":1130,"ʉ":1131,"ʊ":1132,"ʋ":1133,"ʌ":1134,"ʎ":1135,"ʐ":1136,"ʑ":1137,"ʒ":1138,"ʔ":1139,"ʰ":1140,"ʲ":1141,"ʳ":1142,"ʷ":1143,"ʸ":1144,"ʻ":1145,"ʼ":1146,"ʾ":1147,"ʿ":1148,"ˈ":1149,"ː":1150,"ˡ":1151,"ˢ":1152,"ˣ":1153,"ˤ":1154,"α":1155,"β":1156,"γ":1157,"δ":1158,"ε":1159,"ζ":1160,"η":1161,"θ":1162,"ι":1163,"κ":1164,"λ":1165,"μ":1166,"ν":1167,"ξ":1168,"ο":1169,"π":1170,"ρ":1171,"ς":1172,"σ":1173,"τ":1174,"υ":1175,"φ":1176,"χ":1177,"ψ":1178,"ω":1179,"а":1180,"б":1181,"в":1182,"г":1183,"д":1184,"е":1185,"ж":1186,"з":1187,"и":1188,"к":1189,"л":1190,"м":1191,"н":1192,"о":1193,"п":1194,"р":1195,"с":1196,"т":1197,"у":1198,"ф":1199,"х":1200,"ц":1201,"ч":1202,"ш":1203,"щ":1204,"ъ":1205,"ы":1206,"ь":1207,"э":1208,"ю":1209,"я":1210,"ђ":1211,"є":1212,"і":1213,"ј":1214,"љ":1215,"њ":1216,"ћ":1217,"ӏ":1218,"ա":1219,"բ":1220,"գ":1221,"դ":1222,"ե":1223,"թ":1224,"ի":1225,"լ":1226,"կ":1227,"հ":1228,"մ":1229,"յ":1230,"ն":1231,"ո":1232,"պ":1233,"ս":1234,"վ":1235,"տ":1236,"ր":1237,"ւ":1238,"ք":1239,"־":1240,"א":1241,"ב":1242,"ג":1243,"ד":1244,"ה":1245,"ו":1246,"ז":1247,"ח":1248,"ט":1249,"י":1250,"ך":1251,"כ":1252,"ל":1253,"ם":1254,"מ":1255,"ן":1256,"נ":1257,"ס":1258,"ע":1259,"ף":1260,"פ":1261,"ץ":1262,"צ":1263,"ק":1264,"ר":1265,"ש":1266,"ת":1267,"،":1268,"ء":1269,"ا":1270,"ب":1271,"ة":1272,"ت":1273,"ث":1274,"ج":1275,"ح":1276,"خ":1277,"د":1278,"ذ":1279,"ر":1280,"ز":1281,"س":1282,"ش":1283,"ص":1284,"ض":1285,"ط":1286,"ظ":1287,"ع":1288,"غ":1289,"ـ":1290,"ف":1291,"ق":1292,"ك":1293,"ل":1294,"م":1295,"ن":1296,"ه":1297,"و":1298,"ى":1299,"ي":1300,"ٹ":1301,"پ":1302,"چ":1303,"ک":1304,"گ":1305,"ں":1306,"ھ":1307,"ہ":1308,"ی":1309,"ے":1310,"अ":1311,"आ":1312,"उ":1313,"ए":1314,"क":1315,"ख":1316,"ग":1317,"च":1318,"ज":1319,"ट":1320,"ड":1321,"ण":1322,"त":1323,"थ":1324,"द":1325,"ध":1326,"न":1327,"प":1328,"ब":1329,"भ":1330,"म":1331,"य":1332,"र":1333,"ल":1334,"व":1335,"श":1336,"ष":1337,"स":1338,"ह":1339,"ा":1340,"ि":1341,"ी":1342,"ो":1343,"।":1344,"॥":1345,"ং":1346,"অ":1347,"আ":1348,"ই":1349,"উ":1350,"এ":1351,"ও":1352,"ক":1353,"খ":1354,"গ":1355,"চ":1356,"ছ":1357,"জ":1358,"ট":1359,"ড":1360,"ণ":1361,"ত":1362,"থ":1363,"দ":1364,"ধ":1365,"ন":1366,"প":1367,"ব":1368,"ভ":1369,"ম":1370,"য":1371,"র":1372,"ল":1373,"শ":1374,"ষ":1375,"স":1376,"হ":1377,"া":1378,"ি":1379,"ী":1380,"ে":1381,"க":1382,"ச":1383,"ட":1384,"த":1385,"ந":1386,"ன":1387,"ப":1388,"ம":1389,"ய":1390,"ர":1391,"ல":1392,"ள":1393,"வ":1394,"ா":1395,"ி":1396,"ு":1397,"ே":1398,"ை":1399,"ನ":1400,"ರ":1401,"ಾ":1402,"ක":1403,"ය":1404,"ර":1405,"ල":1406,"ව":1407,"ා":1408,"ก":1409,"ง":1410,"ต":1411,"ท":1412,"น":1413,"พ":1414,"ม":1415,"ย":1416,"ร":1417,"ล":1418,"ว":1419,"ส":1420,"อ":1421,"า":1422,"เ":1423,"་":1424,"།":1425,"ག":1426,"ང":1427,"ད":1428,"ན":1429,"པ":1430,"བ":1431,"མ":1432,"འ":1433,"ར":1434,"ལ":1435,"ས":1436,"မ":1437,"ა":1438,"ბ":1439,"გ":1440,"დ":1441,"ე":1442,"ვ":1443,"თ":1444,"ი":1445,"კ":1446,"ლ":1447,"მ":1448,"ნ":1449,"ო":1450,"რ":1451,"ს":1452,"ტ":1453,"უ":1454,"ᄀ":1455,"ᄂ":1456,"ᄃ":1457,"ᄅ":1458,"ᄆ":1459,"ᄇ":1460,"ᄉ":1461,"ᄊ":1462,"ᄋ":1463,"ᄌ":1464,"ᄎ":1465,"ᄏ":1466,"ᄐ":1467,"ᄑ":1468,"ᄒ":1469,"ᅡ":1470,"ᅢ":1471,"ᅥ":1472,"ᅦ":1473,"ᅧ":1474,"ᅩ":1475,"ᅪ":1476,"ᅭ":1477,"ᅮ":1478,"ᅯ":1479,"ᅲ":1480,"ᅳ":1481,"ᅴ":1482,"ᅵ":1483,"ᆨ":1484,"ᆫ":1485,"ᆯ":1486,"ᆷ":1487,"ᆸ":1488,"ᆼ":1489,"ᴬ":1490,"ᴮ":1491,"ᴰ":1492,"ᴵ":1493,"ᴺ":1494,"ᵀ":1495,"ᵃ":1496,"ᵇ":1497,"ᵈ":1498,"ᵉ":1499,"ᵍ":1500,"ᵏ":1501,"ᵐ":1502,"ᵒ":1503,"ᵖ":1504,"ᵗ":1505,"ᵘ":1506,"ᵢ":1507,"ᵣ":1508,"ᵤ":1509,"ᵥ":1510,"ᶜ":1511,"ᶠ":1512,"‐":1513,"‑":1514,"‒":1515,"–":1516,"—":1517,"―":1518,"‖":1519,"‘":1520,"’":1521,"‚":1522,"“":1523,"”":1524,"„":1525,"†":1526,"‡":1527,"•":1528,"…":1529,"‰":1530,"′":1531,"″":1532,"›":1533,"‿":1534,"⁄":1535,"⁰":1536,"ⁱ":1537,"⁴":1538,"⁵":1539,"⁶":1540,"⁷":1541,"⁸":1542,"⁹":1543,"⁺":1544,"⁻":1545,"ⁿ":1546,"₀":1547,"₁":1548,"₂":1549,"₃":1550,"₄":1551,"₅":1552,"₆":1553,"₇":1554,"₈":1555,"₉":1556,"₊":1557,"₍":1558,"₎":1559,"ₐ":1560,"ₑ":1561,"ₒ":1562,"ₓ":1563,"ₕ":1564,"ₖ":1565,"ₗ":1566,"ₘ":1567,"ₙ":1568,"ₚ":1569,"ₛ":1570,"ₜ":1571,"₤":1572,"₩":1573,"€":1574,"₱":1575,"₹":1576,"ℓ":1577,"№":1578,"ℝ":1579,"™":1580,"⅓":1581,"⅔":1582,"←":1583,"↑":1584,"→":1585,"↓":1586,"↔":1587,"↦":1588,"⇄":1589,"⇌":1590,"⇒":1591,"∂":1592,"∅":1593,"∆":1594,"∇":1595,"∈":1596,"−":1597,"∗":1598,"∘":1599,"√":1600,"∞":1601,"∧":1602,"∨":1603,"∩":1604,"∪":1605,"≈":1606,"≡":1607,"≤":1608,"≥":1609,"⊂":1610,"⊆":1611,"⊕":1612,"⊗":1613,"⋅":1614,"─":1615,"│":1616,"■":1617,"▪":1618,"●":1619,"★":1620,"☆":1621,"☉":1622,"♠":1623,"♣":1624,"♥":1625,"♦":1626,"♭":1627,"♯":1628,"⟨":1629,"⟩":1630,"ⱼ":1631,"⺩":1632,"⺼":1633,"⽥":1634,"、":1635,"。":1636,"〈":1637,"〉":1638,"《":1639,"》":1640,"「":1641,"」":1642,"『":1643,"』":1644,"〜":1645,"あ":1646,"い":1647,"う":1648,"え":1649,"お":1650,"か":1651,"き":1652,"く":1653,"け":1654,"こ":1655,"さ":1656,"し":1657,"す":1658,"せ":1659,"そ":1660,"た":1661,"ち":1662,"っ":1663,"つ":1664,"て":1665,"と":1666,"な":1667,"に":1668,"ぬ":1669,"ね":1670,"の":1671,"は":1672,"ひ":1673,"ふ":1674,"へ":1675,"ほ":1676,"ま":1677,"み":1678,"む":1679,"め":1680,"も":1681,"や":1682,"ゆ":1683,"よ":1684,"ら":1685,"り":1686,"る":1687,"れ":1688,"ろ":1689,"を":1690,"ん":1691,"ァ":1692,"ア":1693,"ィ":1694,"イ":1695,"ウ":1696,"ェ":1697,"エ":1698,"オ":1699,"カ":1700,"キ":1701,"ク":1702,"ケ":1703,"コ":1704,"サ":1705,"シ":1706,"ス":1707,"セ":1708,"タ":1709,"チ":1710,"ッ":1711,"ツ":1712,"テ":1713,"ト":1714,"ナ":1715,"ニ":1716,"ノ":1717,"ハ":1718,"ヒ":1719,"フ":1720,"ヘ":1721,"ホ":1722,"マ":1723,"ミ":1724,"ム":1725,"メ":1726,"モ":1727,"ャ":1728,"ュ":1729,"ョ":1730,"ラ":1731,"リ":1732,"ル":1733,"レ":1734,"ロ":1735,"ワ":1736,"ン":1737,"・":1738,"ー":1739,"一":1740,"三":1741,"上":1742,"下":1743,"不":1744,"世":1745,"中":1746,"主":1747,"久":1748,"之":1749,"也":1750,"事":1751,"二":1752,"五":1753,"井":1754,"京":1755,"人":1756,"亻":1757,"仁":1758,"介":1759,"代":1760,"仮":1761,"伊":1762,"会":1763,"佐":1764,"侍":1765,"保":1766,"信":1767,"健":1768,"元":1769,"光":1770,"八":1771,"公":1772,"内":1773,"出":1774,"分":1775,"前":1776,"劉":1777,"力":1778,"加":1779,"勝":1780,"北":1781,"区":1782,"十":1783,"千":1784,"南":1785,"博":1786,"原":1787,"口":1788,"古":1789,"史":1790,"司":1791,"合":1792,"吉":1793,"同":1794,"名":1795,"和":1796,"囗":1797,"四":1798,"国":1799,"國":1800,"土":1801,"地":1802,"坂":1803,"城":1804,"堂":1805,"場":1806,"士":1807,"夏":1808,"外":1809,"大":1810,"天":1811,"太":1812,"夫":1813,"奈":1814,"女":1815,"子":1816,"学":1817,"宀":1818,"宇":1819,"安":1820,"宗":1821,"定":1822,"宣":1823,"宮":1824,"家":1825,"宿":1826,"寺":1827,"將":1828,"小":1829,"尚":1830,"山":1831,"岡":1832,"島":1833,"崎":1834,"川":1835,"州":1836,"巿":1837,"帝":1838,"平":1839,"年":1840,"幸":1841,"广":1842,"弘":1843,"張":1844,"彳":1845,"後":1846,"御":1847,"德":1848,"心":1849,"忄":1850,"志":1851,"忠":1852,"愛":1853,"成":1854,"我":1855,"戦":1856,"戸":1857,"手":1858,"扌":1859,"政":1860,"文":1861,"新":1862,"方":1863,"日":1864,"明":1865,"星":1866,"春":1867,"昭":1868,"智":1869,"曲":1870,"書":1871,"月":1872,"有":1873,"朝":1874,"木":1875,"本":1876,"李":1877,"村":1878,"東":1879,"松":1880,"林":1881,"森":1882,"楊":1883,"樹":1884,"橋":1885,"歌":1886,"止":1887,"正":1888,"武":1889,"比":1890,"氏":1891,"民":1892,"水":1893,"氵":1894,"氷":1895,"永":1896,"江":1897,"沢":1898,"河":1899,"治":1900,"法":1901,"海":1902,"清":1903,"漢":1904,"瀬":1905,"火":1906,"版":1907,"犬":1908,"王":1909,"生":1910,"田":1911,"男":1912,"疒":1913,"発":1914,"白":1915,"的":1916,"皇":1917,"目":1918,"相":1919,"省":1920,"真":1921,"石":1922,"示":1923,"社":1924,"神":1925,"福":1926,"禾":1927,"秀":1928,"秋":1929,"空":1930,"立":1931,"章":1932,"竹":1933,"糹":1934,"美":1935,"義":1936,"耳":1937,"良":1938,"艹":1939,"花":1940,"英":1941,"華":1942,"葉":1943,"藤":1944,"行":1945,"街":1946,"西":1947,"見":1948,"訁":1949,"語":1950,"谷":1951,"貝":1952,"貴":1953,"車":1954,"軍":1955,"辶":1956,"道":1957,"郎":1958,"郡":1959,"部":1960,"都":1961,"里":1962,"野":1963,"金":1964,"鈴":1965,"镇":1966,"長":1967,"門":1968,"間":1969,"阝":1970,"阿":1971,"陳":1972,"陽":1973,"雄":1974,"青":1975,"面":1976,"風":1977,"食":1978,"香":1979,"馬":1980,"高":1981,"龍":1982,"龸":1983,"fi":1984,"fl":1985,"！":1986,"（":1987,"）":1988,"，":1989,"－":1990,"．":1991,"／":1992,"：":1993,"？":1994,"～":1995,"the":1996,"of":1997,"and":1998,"in":1999,"to":2000,"was":2001,"he":2002,"is":2003,"as":2004,"for":2005,"on":2006,"with":2007,"that":2008,"it":2009,"his":2010,"by":2011,"at":2012,"from":2013,"her":2014,"##s":2015,"she":2016,"you":2017,"had":2018,"an":2019,"were":2020,"but":2021,"be":2022,"this":2023,"are":2024,"not":2025,"my":2026,"they":2027,"one":2028,"which":2029,"or":2030,"have":2031,"him":2032,"me":2033,"first":2034,"all":2035,"also":2036,"their":2037,"has":2038,"up":2039,"who":2040,"out":2041,"been":2042,"when":2043,"after":2044,"there":2045,"into":2046,"new":2047,"two":2048,"its":2049,"##a":2050,"time":2051,"would":2052,"no":2053,"what":2054,"about":2055,"said":2056,"we":2057,"over":2058,"then":2059,"other":2060,"so":2061,"more":2062,"##e":2063,"can":2064,"if":2065,"like":2066,"back":2067,"them":2068,"only":2069,"some":2070,"could":2071,"##i":2072,"where":2073,"just":2074,"##ing":2075,"during":2076,"before":2077,"##n":2078,"do":2079,"##o":2080,"made":2081,"school":2082,"through":2083,"than":2084,"now":2085,"years":2086,"most":2087,"world":2088,"may":2089,"between":2090,"down":2091,"well":2092,"three":2093,"##d":2094,"year":2095,"while":2096,"will":2097,"##ed":2098,"##r":2099,"##y":2100,"later":2101,"##t":2102,"city":2103,"under":2104,"around":2105,"did":2106,"such":2107,"being":2108,"used":2109,"state":2110,"people":2111,"part":2112,"know":2113,"against":2114,"your":2115,"many":2116,"second":2117,"university":2118,"both":2119,"national":2120,"##er":2121,"these":2122,"don":2123,"known":2124,"off":2125,"way":2126,"until":2127,"re":2128,"how":2129,"even":2130,"get":2131,"head":2132,"...":2133,"didn":2134,"##ly":2135,"team":2136,"american":2137,"because":2138,"de":2139,"##l":2140,"born":2141,"united":2142,"film":2143,"since":2144,"still":2145,"long":2146,"work":2147,"south":2148,"us":2149,"became":2150,"any":2151,"high":2152,"again":2153,"day":2154,"family":2155,"see":2156,"right":2157,"man":2158,"eyes":2159,"house":2160,"season":2161,"war":2162,"states":2163,"including":2164,"took":2165,"life":2166,"north":2167,"same":2168,"each":2169,"called":2170,"name":2171,"much":2172,"place":2173,"however":2174,"go":2175,"four":2176,"group":2177,"another":2178,"found":2179,"won":2180,"area":2181,"here":2182,"going":2183,"10":2184,"away":2185,"series":2186,"left":2187,"home":2188,"music":2189,"best":2190,"make":2191,"hand":2192,"number":2193,"company":2194,"several":2195,"never":2196,"last":2197,"john":2198,"000":2199,"very":2200,"album":2201,"take":2202,"end":2203,"good":2204,"too":2205,"following":2206,"released":2207,"game":2208,"played":2209,"little":2210,"began":2211,"district":2212,"##m":2213,"old":2214,"want":2215,"those":2216,"side":2217,"held":2218,"own":2219,"early":2220,"county":2221,"ll":2222,"league":2223,"use":2224,"west":2225,"##u":2226,"face":2227,"think":2228,"##es":2229,"2010":2230,"government":2231,"##h":2232,"march":2233,"came":2234,"small":2235,"general":2236,"town":2237,"june":2238,"##on":2239,"line":2240,"based":2241,"something":2242,"##k":2243,"september":2244,"thought":2245,"looked":2246,"along":2247,"international":2248,"2011":2249,"air":2250,"july":2251,"club":2252,"went":2253,"january":2254,"october":2255,"our":2256,"august":2257,"april":2258,"york":2259,"12":2260,"few":2261,"2012":2262,"2008":2263,"east":2264,"show":2265,"member":2266,"college":2267,"2009":2268,"father":2269,"public":2270,"##us":2271,"come":2272,"men":2273,"five":2274,"set":2275,"station":2276,"church":2277,"##c":2278,"next":2279,"former":2280,"november":2281,"room":2282,"party":2283,"located":2284,"december":2285,"2013":2286,"age":2287,"got":2288,"2007":2289,"##g":2290,"system":2291,"let":2292,"love":2293,"2006":2294,"though":2295,"every":2296,"2014":2297,"look":2298,"song":2299,"water":2300,"century":2301,"without":2302,"body":2303,"black":2304,"night":2305,"within":2306,"great":2307,"women":2308,"single":2309,"ve":2310,"building":2311,"large":2312,"population":2313,"river":2314,"named":2315,"band":2316,"white":2317,"started":2318,"##an":2319,"once":2320,"15":2321,"20":2322,"should":2323,"18":2324,"2015":2325,"service":2326,"top":2327,"built":2328,"british":2329,"open":2330,"death":2331,"king":2332,"moved":2333,"local":2334,"times":2335,"children":2336,"february":2337,"book":2338,"why":2339,"11":2340,"door":2341,"need":2342,"president":2343,"order":2344,"final":2345,"road":2346,"wasn":2347,"although":2348,"due":2349,"major":2350,"died":2351,"village":2352,"third":2353,"knew":2354,"2016":2355,"asked":2356,"turned":2357,"st":2358,"wanted":2359,"say":2360,"##p":2361,"together":2362,"received":2363,"main":2364,"son":2365,"served":2366,"different":2367,"##en":2368,"behind":2369,"himself":2370,"felt":2371,"members":2372,"power":2373,"football":2374,"law":2375,"voice":2376,"play":2377,"##in":2378,"near":2379,"park":2380,"history":2381,"30":2382,"having":2383,"2005":2384,"16":2385,"##man":2386,"saw":2387,"mother":2388,"##al":2389,"army":2390,"point":2391,"front":2392,"help":2393,"english":2394,"street":2395,"art":2396,"late":2397,"hands":2398,"games":2399,"award":2400,"##ia":2401,"young":2402,"14":2403,"put":2404,"published":2405,"country":2406,"division":2407,"across":2408,"told":2409,"13":2410,"often":2411,"ever":2412,"french":2413,"london":2414,"center":2415,"six":2416,"red":2417,"2017":2418,"led":2419,"days":2420,"include":2421,"light":2422,"25":2423,"find":2424,"tell":2425,"among":2426,"species":2427,"really":2428,"according":2429,"central":2430,"half":2431,"2004":2432,"form":2433,"original":2434,"gave":2435,"office":2436,"making":2437,"enough":2438,"lost":2439,"full":2440,"opened":2441,"must":2442,"included":2443,"live":2444,"given":2445,"german":2446,"player":2447,"run":2448,"business":2449,"woman":2450,"community":2451,"cup":2452,"might":2453,"million":2454,"land":2455,"2000":2456,"court":2457,"development":2458,"17":2459,"short":2460,"round":2461,"ii":2462,"km":2463,"seen":2464,"class":2465,"story":2466,"always":2467,"become":2468,"sure":2469,"research":2470,"almost":2471,"director":2472,"council":2473,"la":2474,"##2":2475,"career":2476,"things":2477,"using":2478,"island":2479,"##z":2480,"couldn":2481,"car":2482,"##is":2483,"24":2484,"close":2485,"force":2486,"##1":2487,"better":2488,"free":2489,"support":2490,"control":2491,"field":2492,"students":2493,"2003":2494,"education":2495,"married":2496,"##b":2497,"nothing":2498,"worked":2499,"others":2500,"record":2501,"big":2502,"inside":2503,"level":2504,"anything":2505,"continued":2506,"give":2507,"james":2508,"##3":2509,"military":2510,"established":2511,"non":2512,"returned":2513,"feel":2514,"does":2515,"title":2516,"written":2517,"thing":2518,"feet":2519,"william":2520,"far":2521,"co":2522,"association":2523,"hard":2524,"already":2525,"2002":2526,"##ra":2527,"championship":2528,"human":2529,"western":2530,"100":2531,"##na":2532,"department":2533,"hall":2534,"role":2535,"various":2536,"production":2537,"21":2538,"19":2539,"heart":2540,"2001":2541,"living":2542,"fire":2543,"version":2544,"##ers":2545,"##f":2546,"television":2547,"royal":2548,"##4":2549,"produced":2550,"working":2551,"act":2552,"case":2553,"society":2554,"region":2555,"present":2556,"radio":2557,"period":2558,"looking":2559,"least":2560,"total":2561,"keep":2562,"england":2563,"wife":2564,"program":2565,"per":2566,"brother":2567,"mind":2568,"special":2569,"22":2570,"##le":2571,"am":2572,"works":2573,"soon":2574,"##6":2575,"political":2576,"george":2577,"services":2578,"taken":2579,"created":2580,"##7":2581,"further":2582,"able":2583,"reached":2584,"david":2585,"union":2586,"joined":2587,"upon":2588,"done":2589,"important":2590,"social":2591,"information":2592,"either":2593,"##ic":2594,"##x":2595,"appeared":2596,"position":2597,"ground":2598,"lead":2599,"rock":2600,"dark":2601,"election":2602,"23":2603,"board":2604,"france":2605,"hair":2606,"course":2607,"arms":2608,"site":2609,"police":2610,"girl":2611,"instead":2612,"real":2613,"sound":2614,"##v":2615,"words":2616,"moment":2617,"##te":2618,"someone":2619,"##8":2620,"summer":2621,"project":2622,"announced":2623,"san":2624,"less":2625,"wrote":2626,"past":2627,"followed":2628,"##5":2629,"blue":2630,"founded":2631,"al":2632,"finally":2633,"india":2634,"taking":2635,"records":2636,"america":2637,"##ne":2638,"1999":2639,"design":2640,"considered":2641,"northern":2642,"god":2643,"stop":2644,"battle":2645,"toward":2646,"european":2647,"outside":2648,"described":2649,"track":2650,"today":2651,"playing":2652,"language":2653,"28":2654,"call":2655,"26":2656,"heard":2657,"professional":2658,"low":2659,"australia":2660,"miles":2661,"california":2662,"win":2663,"yet":2664,"green":2665,"##ie":2666,"trying":2667,"blood":2668,"##ton":2669,"southern":2670,"science":2671,"maybe":2672,"everything":2673,"match":2674,"square":2675,"27":2676,"mouth":2677,"video":2678,"race":2679,"recorded":2680,"leave":2681,"above":2682,"##9":2683,"daughter":2684,"points":2685,"space":2686,"1998":2687,"museum":2688,"change":2689,"middle":2690,"common":2691,"##0":2692,"move":2693,"tv":2694,"post":2695,"##ta":2696,"lake":2697,"seven":2698,"tried":2699,"elected":2700,"closed":2701,"ten":2702,"paul":2703,"minister":2704,"##th":2705,"months":2706,"start":2707,"chief":2708,"return":2709,"canada":2710,"person":2711,"sea":2712,"release":2713,"similar":2714,"modern":2715,"brought":2716,"rest":2717,"hit":2718,"formed":2719,"mr":2720,"##la":2721,"1997":2722,"floor":2723,"event":2724,"doing":2725,"thomas":2726,"1996":2727,"robert":2728,"care":2729,"killed":2730,"training":2731,"star":2732,"week":2733,"needed":2734,"turn":2735,"finished":2736,"railway":2737,"rather":2738,"news":2739,"health":2740,"sent":2741,"example":2742,"ran":2743,"term":2744,"michael":2745,"coming":2746,"currently":2747,"yes":2748,"forces":2749,"despite":2750,"gold":2751,"areas":2752,"50":2753,"stage":2754,"fact":2755,"29":2756,"dead":2757,"says":2758,"popular":2759,"2018":2760,"originally":2761,"germany":2762,"probably":2763,"developed":2764,"result":2765,"pulled":2766,"friend":2767,"stood":2768,"money":2769,"running":2770,"mi":2771,"signed":2772,"word":2773,"songs":2774,"child":2775,"eventually":2776,"met":2777,"tour":2778,"average":2779,"teams":2780,"minutes":2781,"festival":2782,"current":2783,"deep":2784,"kind":2785,"1995":2786,"decided":2787,"usually":2788,"eastern":2789,"seemed":2790,"##ness":2791,"episode":2792,"bed":2793,"added":2794,"table":2795,"indian":2796,"private":2797,"charles":2798,"route":2799,"available":2800,"idea":2801,"throughout":2802,"centre":2803,"addition":2804,"appointed":2805,"style":2806,"1994":2807,"books":2808,"eight":2809,"construction":2810,"press":2811,"mean":2812,"wall":2813,"friends":2814,"remained":2815,"schools":2816,"study":2817,"##ch":2818,"##um":2819,"institute":2820,"oh":2821,"chinese":2822,"sometimes":2823,"events":2824,"possible":2825,"1992":2826,"australian":2827,"type":2828,"brown":2829,"forward":2830,"talk":2831,"process":2832,"food":2833,"debut":2834,"seat":2835,"performance":2836,"committee":2837,"features":2838,"character":2839,"arts":2840,"herself":2841,"else":2842,"lot":2843,"strong":2844,"russian":2845,"range":2846,"hours":2847,"peter":2848,"arm":2849,"##da":2850,"morning":2851,"dr":2852,"sold":2853,"##ry":2854,"quickly":2855,"directed":2856,"1993":2857,"guitar":2858,"china":2859,"##w":2860,"31":2861,"list":2862,"##ma":2863,"performed":2864,"media":2865,"uk":2866,"players":2867,"smile":2868,"##rs":2869,"myself":2870,"40":2871,"placed":2872,"coach":2873,"province":2874,"towards":2875,"wouldn":2876,"leading":2877,"whole":2878,"boy":2879,"official":2880,"designed":2881,"grand":2882,"census":2883,"##el":2884,"europe":2885,"attack":2886,"japanese":2887,"henry":2888,"1991":2889,"##re":2890,"##os":2891,"cross":2892,"getting":2893,"alone":2894,"action":2895,"lower":2896,"network":2897,"wide":2898,"washington":2899,"japan":2900,"1990":2901,"hospital":2902,"believe":2903,"changed":2904,"sister":2905,"##ar":2906,"hold":2907,"gone":2908,"sir":2909,"hadn":2910,"ship":2911,"##ka":2912,"studies":2913,"academy":2914,"shot":2915,"rights":2916,"below":2917,"base":2918,"bad":2919,"involved":2920,"kept":2921,"largest":2922,"##ist":2923,"bank":2924,"future":2925,"especially":2926,"beginning":2927,"mark":2928,"movement":2929,"section":2930,"female":2931,"magazine":2932,"plan":2933,"professor":2934,"lord":2935,"longer":2936,"##ian":2937,"sat":2938,"walked":2939,"hill":2940,"actually":2941,"civil":2942,"energy":2943,"model":2944,"families":2945,"size":2946,"thus":2947,"aircraft":2948,"completed":2949,"includes":2950,"data":2951,"captain":2952,"##or":2953,"fight":2954,"vocals":2955,"featured":2956,"richard":2957,"bridge":2958,"fourth":2959,"1989":2960,"officer":2961,"stone":2962,"hear":2963,"##ism":2964,"means":2965,"medical":2966,"groups":2967,"management":2968,"self":2969,"lips":2970,"competition":2971,"entire":2972,"lived":2973,"technology":2974,"leaving":2975,"federal":2976,"tournament":2977,"bit":2978,"passed":2979,"hot":2980,"independent":2981,"awards":2982,"kingdom":2983,"mary":2984,"spent":2985,"fine":2986,"doesn":2987,"reported":2988,"##ling":2989,"jack":2990,"fall":2991,"raised":2992,"itself":2993,"stay":2994,"true":2995,"studio":2996,"1988":2997,"sports":2998,"replaced":2999,"paris":3000,"systems":3001,"saint":3002,"leader":3003,"theatre":3004,"whose":3005,"market":3006,"capital":3007,"parents":3008,"spanish":3009,"canadian":3010,"earth":3011,"##ity":3012,"cut":3013,"degree":3014,"writing":3015,"bay":3016,"christian":3017,"awarded":3018,"natural":3019,"higher":3020,"bill":3021,"##as":3022,"coast":3023,"provided":3024,"previous":3025,"senior":3026,"ft":3027,"valley":3028,"organization":3029,"stopped":3030,"onto":3031,"countries":3032,"parts":3033,"conference":3034,"queen":3035,"security":3036,"interest":3037,"saying":3038,"allowed":3039,"master":3040,"earlier":3041,"phone":3042,"matter":3043,"smith":3044,"winning":3045,"try":3046,"happened":3047,"moving":3048,"campaign":3049,"los":3050,"##ley":3051,"breath":3052,"nearly":3053,"mid":3054,"1987":3055,"certain":3056,"girls":3057,"date":3058,"italian":3059,"african":3060,"standing":3061,"fell":3062,"artist":3063,"##ted":3064,"shows":3065,"deal":3066,"mine":3067,"industry":3068,"1986":3069,"##ng":3070,"everyone":3071,"republic":3072,"provide":3073,"collection":3074,"library":3075,"student":3076,"##ville":3077,"primary":3078,"owned":3079,"older":3080,"via":3081,"heavy":3082,"1st":3083,"makes":3084,"##able":3085,"attention":3086,"anyone":3087,"africa":3088,"##ri":3089,"stated":3090,"length":3091,"ended":3092,"fingers":3093,"command":3094,"staff":3095,"skin":3096,"foreign":3097,"opening":3098,"governor":3099,"okay":3100,"medal":3101,"kill":3102,"sun":3103,"cover":3104,"job":3105,"1985":3106,"introduced":3107,"chest":3108,"hell":3109,"feeling":3110,"##ies":3111,"success":3112,"meet":3113,"reason":3114,"standard":3115,"meeting":3116,"novel":3117,"1984":3118,"trade":3119,"source":3120,"buildings":3121,"##land":3122,"rose":3123,"guy":3124,"goal":3125,"##ur":3126,"chapter":3127,"native":3128,"husband":3129,"previously":3130,"unit":3131,"limited":3132,"entered":3133,"weeks":3134,"producer":3135,"operations":3136,"mountain":3137,"takes":3138,"covered":3139,"forced":3140,"related":3141,"roman":3142,"complete":3143,"successful":3144,"key":3145,"texas":3146,"cold":3147,"##ya":3148,"channel":3149,"1980":3150,"traditional":3151,"films":3152,"dance":3153,"clear":3154,"approximately":3155,"500":3156,"nine":3157,"van":3158,"prince":3159,"question":3160,"active":3161,"tracks":3162,"ireland":3163,"regional":3164,"silver":3165,"author":3166,"personal":3167,"sense":3168,"operation":3169,"##ine":3170,"economic":3171,"1983":3172,"holding":3173,"twenty":3174,"isbn":3175,"additional":3176,"speed":3177,"hour":3178,"edition":3179,"regular":3180,"historic":3181,"places":3182,"whom":3183,"shook":3184,"movie":3185,"km²":3186,"secretary":3187,"prior":3188,"report":3189,"chicago":3190,"read":3191,"foundation":3192,"view":3193,"engine":3194,"scored":3195,"1982":3196,"units":3197,"ask":3198,"airport":3199,"property":3200,"ready":3201,"immediately":3202,"lady":3203,"month":3204,"listed":3205,"contract":3206,"##de":3207,"manager":3208,"themselves":3209,"lines":3210,"##ki":3211,"navy":3212,"writer":3213,"meant":3214,"##ts":3215,"runs":3216,"##ro":3217,"practice":3218,"championships":3219,"singer":3220,"glass":3221,"commission":3222,"required":3223,"forest":3224,"starting":3225,"culture":3226,"generally":3227,"giving":3228,"access":3229,"attended":3230,"test":3231,"couple":3232,"stand":3233,"catholic":3234,"martin":3235,"caught":3236,"executive":3237,"##less":3238,"eye":3239,"##ey":3240,"thinking":3241,"chair":3242,"quite":3243,"shoulder":3244,"1979":3245,"hope":3246,"decision":3247,"plays":3248,"defeated":3249,"municipality":3250,"whether":3251,"structure":3252,"offered":3253,"slowly":3254,"pain":3255,"ice":3256,"direction":3257,"##ion":3258,"paper":3259,"mission":3260,"1981":3261,"mostly":3262,"200":3263,"noted":3264,"individual":3265,"managed":3266,"nature":3267,"lives":3268,"plant":3269,"##ha":3270,"helped":3271,"except":3272,"studied":3273,"computer":3274,"figure":3275,"relationship":3276,"issue":3277,"significant":3278,"loss":3279,"die":3280,"smiled":3281,"gun":3282,"ago":3283,"highest":3284,"1972":3285,"##am":3286,"male":3287,"bring":3288,"goals":3289,"mexico":3290,"problem":3291,"distance":3292,"commercial":3293,"completely":3294,"location":3295,"annual":3296,"famous":3297,"drive":3298,"1976":3299,"neck":3300,"1978":3301,"surface":3302,"caused":3303,"italy":3304,"understand":3305,"greek":3306,"highway":3307,"wrong":3308,"hotel":3309,"comes":3310,"appearance":3311,"joseph":3312,"double":3313,"issues":3314,"musical":3315,"companies":3316,"castle":3317,"income":3318,"review":3319,"assembly":3320,"bass":3321,"initially":3322,"parliament":3323,"artists":3324,"experience":3325,"1974":3326,"particular":3327,"walk":3328,"foot":3329,"engineering":3330,"talking":3331,"window":3332,"dropped":3333,"##ter":3334,"miss":3335,"baby":3336,"boys":3337,"break":3338,"1975":3339,"stars":3340,"edge":3341,"remember":3342,"policy":3343,"carried":3344,"train":3345,"stadium":3346,"bar":3347,"sex":3348,"angeles":3349,"evidence":3350,"##ge":3351,"becoming":3352,"assistant":3353,"soviet":3354,"1977":3355,"upper":3356,"step":3357,"wing":3358,"1970":3359,"youth":3360,"financial":3361,"reach":3362,"##ll":3363,"actor":3364,"numerous":3365,"##se":3366,"##st":3367,"nodded":3368,"arrived":3369,"##ation":3370,"minute":3371,"##nt":3372,"believed":3373,"sorry":3374,"complex":3375,"beautiful":3376,"victory":3377,"associated":3378,"temple":3379,"1968":3380,"1973":3381,"chance":3382,"perhaps":3383,"metal":3384,"##son":3385,"1945":3386,"bishop":3387,"##et":3388,"lee":3389,"launched":3390,"particularly":3391,"tree":3392,"le":3393,"retired":3394,"subject":3395,"prize":3396,"contains":3397,"yeah":3398,"theory":3399,"empire":3400,"##ce":3401,"suddenly":3402,"waiting":3403,"trust":3404,"recording":3405,"##to":3406,"happy":3407,"terms":3408,"camp":3409,"champion":3410,"1971":3411,"religious":3412,"pass":3413,"zealand":3414,"names":3415,"2nd":3416,"port":3417,"ancient":3418,"tom":3419,"corner":3420,"represented":3421,"watch":3422,"legal":3423,"anti":3424,"justice":3425,"cause":3426,"watched":3427,"brothers":3428,"45":3429,"material":3430,"changes":3431,"simply":3432,"response":3433,"louis":3434,"fast":3435,"##ting":3436,"answer":3437,"60":3438,"historical":3439,"1969":3440,"stories":3441,"straight":3442,"create":3443,"feature":3444,"increased":3445,"rate":3446,"administration":3447,"virginia":3448,"el":3449,"activities":3450,"cultural":3451,"overall":3452,"winner":3453,"programs":3454,"basketball":3455,"legs":3456,"guard":3457,"beyond":3458,"cast":3459,"doctor":3460,"mm":3461,"flight":3462,"results":3463,"remains":3464,"cost":3465,"effect":3466,"winter":3467,"##ble":3468,"larger":3469,"islands":3470,"problems":3471,"chairman":3472,"grew":3473,"commander":3474,"isn":3475,"1967":3476,"pay":3477,"failed":3478,"selected":3479,"hurt":3480,"fort":3481,"box":3482,"regiment":3483,"majority":3484,"journal":3485,"35":3486,"edward":3487,"plans":3488,"##ke":3489,"##ni":3490,"shown":3491,"pretty":3492,"irish":3493,"characters":3494,"directly":3495,"scene":3496,"likely":3497,"operated":3498,"allow":3499,"spring":3500,"##j":3501,"junior":3502,"matches":3503,"looks":3504,"mike":3505,"houses":3506,"fellow":3507,"##tion":3508,"beach":3509,"marriage":3510,"##ham":3511,"##ive":3512,"rules":3513,"oil":3514,"65":3515,"florida":3516,"expected":3517,"nearby":3518,"congress":3519,"sam":3520,"peace":3521,"recent":3522,"iii":3523,"wait":3524,"subsequently":3525,"cell":3526,"##do":3527,"variety":3528,"serving":3529,"agreed":3530,"please":3531,"poor":3532,"joe":3533,"pacific":3534,"attempt":3535,"wood":3536,"democratic":3537,"piece":3538,"prime":3539,"##ca":3540,"rural":3541,"mile":3542,"touch":3543,"appears":3544,"township":3545,"1964":3546,"1966":3547,"soldiers":3548,"##men":3549,"##ized":3550,"1965":3551,"pennsylvania":3552,"closer":3553,"fighting":3554,"claimed":3555,"score":3556,"jones":3557,"physical":3558,"editor":3559,"##ous":3560,"filled":3561,"genus":3562,"specific":3563,"sitting":3564,"super":3565,"mom":3566,"##va":3567,"therefore":3568,"supported":3569,"status":3570,"fear":3571,"cases":3572,"store":3573,"meaning":3574,"wales":3575,"minor":3576,"spain":3577,"tower":3578,"focus":3579,"vice":3580,"frank":3581,"follow":3582,"parish":3583,"separate":3584,"golden":3585,"horse":3586,"fifth":3587,"remaining":3588,"branch":3589,"32":3590,"presented":3591,"stared":3592,"##id":3593,"uses":3594,"secret":3595,"forms":3596,"##co":3597,"baseball":3598,"exactly":3599,"##ck":3600,"choice":3601,"note":3602,"discovered":3603,"travel":3604,"composed":3605,"truth":3606,"russia":3607,"ball":3608,"color":3609,"kiss":3610,"dad":3611,"wind":3612,"continue":3613,"ring":3614,"referred":3615,"numbers":3616,"digital":3617,"greater":3618,"##ns":3619,"metres":3620,"slightly":3621,"direct":3622,"increase":3623,"1960":3624,"responsible":3625,"crew":3626,"rule":3627,"trees":3628,"troops":3629,"##no":3630,"broke":3631,"goes":3632,"individuals":3633,"hundred":3634,"weight":3635,"creek":3636,"sleep":3637,"memory":3638,"defense":3639,"provides":3640,"ordered":3641,"code":3642,"value":3643,"jewish":3644,"windows":3645,"1944":3646,"safe":3647,"judge":3648,"whatever":3649,"corps":3650,"realized":3651,"growing":3652,"pre":3653,"##ga":3654,"cities":3655,"alexander":3656,"gaze":3657,"lies":3658,"spread":3659,"scott":3660,"letter":3661,"showed":3662,"situation":3663,"mayor":3664,"transport":3665,"watching":3666,"workers":3667,"extended":3668,"##li":3669,"expression":3670,"normal":3671,"##ment":3672,"chart":3673,"multiple":3674,"border":3675,"##ba":3676,"host":3677,"##ner":3678,"daily":3679,"mrs":3680,"walls":3681,"piano":3682,"##ko":3683,"heat":3684,"cannot":3685,"##ate":3686,"earned":3687,"products":3688,"drama":3689,"era":3690,"authority":3691,"seasons":3692,"join":3693,"grade":3694,"##io":3695,"sign":3696,"difficult":3697,"machine":3698,"1963":3699,"territory":3700,"mainly":3701,"##wood":3702,"stations":3703,"squadron":3704,"1962":3705,"stepped":3706,"iron":3707,"19th":3708,"##led":3709,"serve":3710,"appear":3711,"sky":3712,"speak":3713,"broken":3714,"charge":3715,"knowledge":3716,"kilometres":3717,"removed":3718,"ships":3719,"article":3720,"campus":3721,"simple":3722,"##ty":3723,"pushed":3724,"britain":3725,"##ve":3726,"leaves":3727,"recently":3728,"cd":3729,"soft":3730,"boston":3731,"latter":3732,"easy":3733,"acquired":3734,"poland":3735,"##sa":3736,"quality":3737,"officers":3738,"presence":3739,"planned":3740,"nations":3741,"mass":3742,"broadcast":3743,"jean":3744,"share":3745,"image":3746,"influence":3747,"wild":3748,"offer":3749,"emperor":3750,"electric":3751,"reading":3752,"headed":3753,"ability":3754,"promoted":3755,"yellow":3756,"ministry":3757,"1942":3758,"throat":3759,"smaller":3760,"politician":3761,"##by":3762,"latin":3763,"spoke":3764,"cars":3765,"williams":3766,"males":3767,"lack":3768,"pop":3769,"80":3770,"##ier":3771,"acting":3772,"seeing":3773,"consists":3774,"##ti":3775,"estate":3776,"1961":3777,"pressure":3778,"johnson":3779,"newspaper":3780,"jr":3781,"chris":3782,"olympics":3783,"online":3784,"conditions":3785,"beat":3786,"elements":3787,"walking":3788,"vote":3789,"##field":3790,"needs":3791,"carolina":3792,"text":3793,"featuring":3794,"global":3795,"block":3796,"shirt":3797,"levels":3798,"francisco":3799,"purpose":3800,"females":3801,"et":3802,"dutch":3803,"duke":3804,"ahead":3805,"gas":3806,"twice":3807,"safety":3808,"serious":3809,"turning":3810,"highly":3811,"lieutenant":3812,"firm":3813,"maria":3814,"amount":3815,"mixed":3816,"daniel":3817,"proposed":3818,"perfect":3819,"agreement":3820,"affairs":3821,"3rd":3822,"seconds":3823,"contemporary":3824,"paid":3825,"1943":3826,"prison":3827,"save":3828,"kitchen":3829,"label":3830,"administrative":3831,"intended":3832,"constructed":3833,"academic":3834,"nice":3835,"teacher":3836,"races":3837,"1956":3838,"formerly":3839,"corporation":3840,"ben":3841,"nation":3842,"issued":3843,"shut":3844,"1958":3845,"drums":3846,"housing":3847,"victoria":3848,"seems":3849,"opera":3850,"1959":3851,"graduated":3852,"function":3853,"von":3854,"mentioned":3855,"picked":3856,"build":3857,"recognized":3858,"shortly":3859,"protection":3860,"picture":3861,"notable":3862,"exchange":3863,"elections":3864,"1980s":3865,"loved":3866,"percent":3867,"racing":3868,"fish":3869,"elizabeth":3870,"garden":3871,"volume":3872,"hockey":3873,"1941":3874,"beside":3875,"settled":3876,"##ford":3877,"1940":3878,"competed":3879,"replied":3880,"drew":3881,"1948":3882,"actress":3883,"marine":3884,"scotland":3885,"steel":3886,"glanced":3887,"farm":3888,"steve":3889,"1957":3890,"risk":3891,"tonight":3892,"positive":3893,"magic":3894,"singles":3895,"effects":3896,"gray":3897,"screen":3898,"dog":3899,"##ja":3900,"residents":3901,"bus":3902,"sides":3903,"none":3904,"secondary":3905,"literature":3906,"polish":3907,"destroyed":3908,"flying":3909,"founder":3910,"households":3911,"1939":3912,"lay":3913,"reserve":3914,"usa":3915,"gallery":3916,"##ler":3917,"1946":3918,"industrial":3919,"younger":3920,"approach":3921,"appearances":3922,"urban":3923,"ones":3924,"1950":3925,"finish":3926,"avenue":3927,"powerful":3928,"fully":3929,"growth":3930,"page":3931,"honor":3932,"jersey":3933,"projects":3934,"advanced":3935,"revealed":3936,"basic":3937,"90":3938,"infantry":3939,"pair":3940,"equipment":3941,"visit":3942,"33":3943,"evening":3944,"search":3945,"grant":3946,"effort":3947,"solo":3948,"treatment":3949,"buried":3950,"republican":3951,"primarily":3952,"bottom":3953,"owner":3954,"1970s":3955,"israel":3956,"gives":3957,"jim":3958,"dream":3959,"bob":3960,"remain":3961,"spot":3962,"70":3963,"notes":3964,"produce":3965,"champions":3966,"contact":3967,"ed":3968,"soul":3969,"accepted":3970,"ways":3971,"del":3972,"##ally":3973,"losing":3974,"split":3975,"price":3976,"capacity":3977,"basis":3978,"trial":3979,"questions":3980,"##ina":3981,"1955":3982,"20th":3983,"guess":3984,"officially":3985,"memorial":3986,"naval":3987,"initial":3988,"##ization":3989,"whispered":3990,"median":3991,"engineer":3992,"##ful":3993,"sydney":3994,"##go":3995,"columbia":3996,"strength":3997,"300":3998,"1952":3999,"tears":4000,"senate":4001,"00":4002,"card":4003,"asian":4004,"agent":4005,"1947":4006,"software":4007,"44":4008,"draw":4009,"warm":4010,"supposed":4011,"com":4012,"pro":4013,"##il":4014,"transferred":4015,"leaned":4016,"##at":4017,"candidate":4018,"escape":4019,"mountains":4020,"asia":4021,"potential":4022,"activity":4023,"entertainment":4024,"seem":4025,"traffic":4026,"jackson":4027,"murder":4028,"36":4029,"slow":4030,"product":4031,"orchestra":4032,"haven":4033,"agency":4034,"bbc":4035,"taught":4036,"website":4037,"comedy":4038,"unable":4039,"storm":4040,"planning":4041,"albums":4042,"rugby":4043,"environment":4044,"scientific":4045,"grabbed":4046,"protect":4047,"##hi":4048,"boat":4049,"typically":4050,"1954":4051,"1953":4052,"damage":4053,"principal":4054,"divided":4055,"dedicated":4056,"mount":4057,"ohio":4058,"##berg":4059,"pick":4060,"fought":4061,"driver":4062,"##der":4063,"empty":4064,"shoulders":4065,"sort":4066,"thank":4067,"berlin":4068,"prominent":4069,"account":4070,"freedom":4071,"necessary":4072,"efforts":4073,"alex":4074,"headquarters":4075,"follows":4076,"alongside":4077,"des":4078,"simon":4079,"andrew":4080,"suggested":4081,"operating":4082,"learning":4083,"steps":4084,"1949":4085,"sweet":4086,"technical":4087,"begin":4088,"easily":4089,"34":4090,"teeth":4091,"speaking":4092,"settlement":4093,"scale":4094,"##sh":4095,"renamed":4096,"ray":4097,"max":4098,"enemy":4099,"semi":4100,"joint":4101,"compared":4102,"##rd":4103,"scottish":4104,"leadership":4105,"analysis":4106,"offers":4107,"georgia":4108,"pieces":4109,"captured":4110,"animal":4111,"deputy":4112,"guest":4113,"organized":4114,"##lin":4115,"tony":4116,"combined":4117,"method":4118,"challenge":4119,"1960s":4120,"huge":4121,"wants":4122,"battalion":4123,"sons":4124,"rise":4125,"crime":4126,"types":4127,"facilities":4128,"telling":4129,"path":4130,"1951":4131,"platform":4132,"sit":4133,"1990s":4134,"##lo":4135,"tells":4136,"assigned":4137,"rich":4138,"pull":4139,"##ot":4140,"commonly":4141,"alive":4142,"##za":4143,"letters":4144,"concept":4145,"conducted":4146,"wearing":4147,"happen":4148,"bought":4149,"becomes":4150,"holy":4151,"gets":4152,"ocean":4153,"defeat":4154,"languages":4155,"purchased":4156,"coffee":4157,"occurred":4158,"titled":4159,"##q":4160,"declared":4161,"applied":4162,"sciences":4163,"concert":4164,"sounds":4165,"jazz":4166,"brain":4167,"##me":4168,"painting":4169,"fleet":4170,"tax":4171,"nick":4172,"##ius":4173,"michigan":4174,"count":4175,"animals":4176,"leaders":4177,"episodes":4178,"##line":4179,"content":4180,"##den":4181,"birth":4182,"##it":4183,"clubs":4184,"64":4185,"palace":4186,"critical":4187,"refused":4188,"fair":4189,"leg":4190,"laughed":4191,"returning":4192,"surrounding":4193,"participated":4194,"formation":4195,"lifted":4196,"pointed":4197,"connected":4198,"rome":4199,"medicine":4200,"laid":4201,"taylor":4202,"santa":4203,"powers":4204,"adam":4205,"tall":4206,"shared":4207,"focused":4208,"knowing":4209,"yards":4210,"entrance":4211,"falls":4212,"##wa":4213,"calling":4214,"##ad":4215,"sources":4216,"chosen":4217,"beneath":4218,"resources":4219,"yard":4220,"##ite":4221,"nominated":4222,"silence":4223,"zone":4224,"defined":4225,"##que":4226,"gained":4227,"thirty":4228,"38":4229,"bodies":4230,"moon":4231,"##ard":4232,"adopted":4233,"christmas":4234,"widely":4235,"register":4236,"apart":4237,"iran":4238,"premier":4239,"serves":4240,"du":4241,"unknown":4242,"parties":4243,"##les":4244,"generation":4245,"##ff":4246,"continues":4247,"quick":4248,"fields":4249,"brigade":4250,"quiet":4251,"teaching":4252,"clothes":4253,"impact":4254,"weapons":4255,"partner":4256,"flat":4257,"theater":4258,"supreme":4259,"1938":4260,"37":4261,"relations":4262,"##tor":4263,"plants":4264,"suffered":4265,"1936":4266,"wilson":4267,"kids":4268,"begins":4269,"##age":4270,"1918":4271,"seats":4272,"armed":4273,"internet":4274,"models":4275,"worth":4276,"laws":4277,"400":4278,"communities":4279,"classes":4280,"background":4281,"knows":4282,"thanks":4283,"quarter":4284,"reaching":4285,"humans":4286,"carry":4287,"killing":4288,"format":4289,"kong":4290,"hong":4291,"setting":4292,"75":4293,"architecture":4294,"disease":4295,"railroad":4296,"inc":4297,"possibly":4298,"wish":4299,"arthur":4300,"thoughts":4301,"harry":4302,"doors":4303,"density":4304,"##di":4305,"crowd":4306,"illinois":4307,"stomach":4308,"tone":4309,"unique":4310,"reports":4311,"anyway":4312,"##ir":4313,"liberal":4314,"der":4315,"vehicle":4316,"thick":4317,"dry":4318,"drug":4319,"faced":4320,"largely":4321,"facility":4322,"theme":4323,"holds":4324,"creation":4325,"strange":4326,"colonel":4327,"##mi":4328,"revolution":4329,"bell":4330,"politics":4331,"turns":4332,"silent":4333,"rail":4334,"relief":4335,"independence":4336,"combat":4337,"shape":4338,"write":4339,"determined":4340,"sales":4341,"learned":4342,"4th":4343,"finger":4344,"oxford":4345,"providing":4346,"1937":4347,"heritage":4348,"fiction":4349,"situated":4350,"designated":4351,"allowing":4352,"distribution":4353,"hosted":4354,"##est":4355,"sight":4356,"interview":4357,"estimated":4358,"reduced":4359,"##ria":4360,"toronto":4361,"footballer":4362,"keeping":4363,"guys":4364,"damn":4365,"claim":4366,"motion":4367,"sport":4368,"sixth":4369,"stayed":4370,"##ze":4371,"en":4372,"rear":4373,"receive":4374,"handed":4375,"twelve":4376,"dress":4377,"audience":4378,"granted":4379,"brazil":4380,"##well":4381,"spirit":4382,"##ated":4383,"noticed":4384,"etc":4385,"olympic":4386,"representative":4387,"eric":4388,"tight":4389,"trouble":4390,"reviews":4391,"drink":4392,"vampire":4393,"missing":4394,"roles":4395,"ranked":4396,"newly":4397,"household":4398,"finals":4399,"wave":4400,"critics":4401,"##ee":4402,"phase":4403,"massachusetts":4404,"pilot":4405,"unlike":4406,"philadelphia":4407,"bright":4408,"guns":4409,"crown":4410,"organizations":4411,"roof":4412,"42":4413,"respectively":4414,"clearly":4415,"tongue":4416,"marked":4417,"circle":4418,"fox":4419,"korea":4420,"bronze":4421,"brian":4422,"expanded":4423,"sexual":4424,"supply":4425,"yourself":4426,"inspired":4427,"labour":4428,"fc":4429,"##ah":4430,"reference":4431,"vision":4432,"draft":4433,"connection":4434,"brand":4435,"reasons":4436,"1935":4437,"classic":4438,"driving":4439,"trip":4440,"jesus":4441,"cells":4442,"entry":4443,"1920":4444,"neither":4445,"trail":4446,"claims":4447,"atlantic":4448,"orders":4449,"labor":4450,"nose":4451,"afraid":4452,"identified":4453,"intelligence":4454,"calls":4455,"cancer":4456,"attacked":4457,"passing":4458,"stephen":4459,"positions":4460,"imperial":4461,"grey":4462,"jason":4463,"39":4464,"sunday":4465,"48":4466,"swedish":4467,"avoid":4468,"extra":4469,"uncle":4470,"message":4471,"covers":4472,"allows":4473,"surprise":4474,"materials":4475,"fame":4476,"hunter":4477,"##ji":4478,"1930":4479,"citizens":4480,"figures":4481,"davis":4482,"environmental":4483,"confirmed":4484,"shit":4485,"titles":4486,"di":4487,"performing":4488,"difference":4489,"acts":4490,"attacks":4491,"##ov":4492,"existing":4493,"votes":4494,"opportunity":4495,"nor":4496,"shop":4497,"entirely":4498,"trains":4499,"opposite":4500,"pakistan":4501,"##pa":4502,"develop":4503,"resulted":4504,"representatives":4505,"actions":4506,"reality":4507,"pressed":4508,"##ish":4509,"barely":4510,"wine":4511,"conversation":4512,"faculty":4513,"northwest":4514,"ends":4515,"documentary":4516,"nuclear":4517,"stock":4518,"grace":4519,"sets":4520,"eat":4521,"alternative":4522,"##ps":4523,"bag":4524,"resulting":4525,"creating":4526,"surprised":4527,"cemetery":4528,"1919":4529,"drop":4530,"finding":4531,"sarah":4532,"cricket":4533,"streets":4534,"tradition":4535,"ride":4536,"1933":4537,"exhibition":4538,"target":4539,"ear":4540,"explained":4541,"rain":4542,"composer":4543,"injury":4544,"apartment":4545,"municipal":4546,"educational":4547,"occupied":4548,"netherlands":4549,"clean":4550,"billion":4551,"constitution":4552,"learn":4553,"1914":4554,"maximum":4555,"classical":4556,"francis":4557,"lose":4558,"opposition":4559,"jose":4560,"ontario":4561,"bear":4562,"core":4563,"hills":4564,"rolled":4565,"ending":4566,"drawn":4567,"permanent":4568,"fun":4569,"##tes":4570,"##lla":4571,"lewis":4572,"sites":4573,"chamber":4574,"ryan":4575,"##way":4576,"scoring":4577,"height":4578,"1934":4579,"##house":4580,"lyrics":4581,"staring":4582,"55":4583,"officials":4584,"1917":4585,"snow":4586,"oldest":4587,"##tic":4588,"orange":4589,"##ger":4590,"qualified":4591,"interior":4592,"apparently":4593,"succeeded":4594,"thousand":4595,"dinner":4596,"lights":4597,"existence":4598,"fans":4599,"heavily":4600,"41":4601,"greatest":4602,"conservative":4603,"send":4604,"bowl":4605,"plus":4606,"enter":4607,"catch":4608,"##un":4609,"economy":4610,"duty":4611,"1929":4612,"speech":4613,"authorities":4614,"princess":4615,"performances":4616,"versions":4617,"shall":4618,"graduate":4619,"pictures":4620,"effective":4621,"remembered":4622,"poetry":4623,"desk":4624,"crossed":4625,"starring":4626,"starts":4627,"passenger":4628,"sharp":4629,"##ant":4630,"acres":4631,"ass":4632,"weather":4633,"falling":4634,"rank":4635,"fund":4636,"supporting":4637,"check":4638,"adult":4639,"publishing":4640,"heads":4641,"cm":4642,"southeast":4643,"lane":4644,"##burg":4645,"application":4646,"bc":4647,"##ura":4648,"les":4649,"condition":4650,"transfer":4651,"prevent":4652,"display":4653,"ex":4654,"regions":4655,"earl":4656,"federation":4657,"cool":4658,"relatively":4659,"answered":4660,"besides":4661,"1928":4662,"obtained":4663,"portion":4664,"##town":4665,"mix":4666,"##ding":4667,"reaction":4668,"liked":4669,"dean":4670,"express":4671,"peak":4672,"1932":4673,"##tte":4674,"counter":4675,"religion":4676,"chain":4677,"rare":4678,"miller":4679,"convention":4680,"aid":4681,"lie":4682,"vehicles":4683,"mobile":4684,"perform":4685,"squad":4686,"wonder":4687,"lying":4688,"crazy":4689,"sword":4690,"##ping":4691,"attempted":4692,"centuries":4693,"weren":4694,"philosophy":4695,"category":4696,"##ize":4697,"anna":4698,"interested":4699,"47":4700,"sweden":4701,"wolf":4702,"frequently":4703,"abandoned":4704,"kg":4705,"literary":4706,"alliance":4707,"task":4708,"entitled":4709,"##ay":4710,"threw":4711,"promotion":4712,"factory":4713,"tiny":4714,"soccer":4715,"visited":4716,"matt":4717,"fm":4718,"achieved":4719,"52":4720,"defence":4721,"internal":4722,"persian":4723,"43":4724,"methods":4725,"##ging":4726,"arrested":4727,"otherwise":4728,"cambridge":4729,"programming":4730,"villages":4731,"elementary":4732,"districts":4733,"rooms":4734,"criminal":4735,"conflict":4736,"worry":4737,"trained":4738,"1931":4739,"attempts":4740,"waited":4741,"signal":4742,"bird":4743,"truck":4744,"subsequent":4745,"programme":4746,"##ol":4747,"ad":4748,"49":4749,"communist":4750,"details":4751,"faith":4752,"sector":4753,"patrick":4754,"carrying":4755,"laugh":4756,"##ss":4757,"controlled":4758,"korean":4759,"showing":4760,"origin":4761,"fuel":4762,"evil":4763,"1927":4764,"##ent":4765,"brief":4766,"identity":4767,"darkness":4768,"address":4769,"pool":4770,"missed":4771,"publication":4772,"web":4773,"planet":4774,"ian":4775,"anne":4776,"wings":4777,"invited":4778,"##tt":4779,"briefly":4780,"standards":4781,"kissed":4782,"##be":4783,"ideas":4784,"climate":4785,"causing":4786,"walter":4787,"worse":4788,"albert":4789,"articles":4790,"winners":4791,"desire":4792,"aged":4793,"northeast":4794,"dangerous":4795,"gate":4796,"doubt":4797,"1922":4798,"wooden":4799,"multi":4800,"##ky":4801,"poet":4802,"rising":4803,"funding":4804,"46":4805,"communications":4806,"communication":4807,"violence":4808,"copies":4809,"prepared":4810,"ford":4811,"investigation":4812,"skills":4813,"1924":4814,"pulling":4815,"electronic":4816,"##ak":4817,"##ial":4818,"##han":4819,"containing":4820,"ultimately":4821,"offices":4822,"singing":4823,"understanding":4824,"restaurant":4825,"tomorrow":4826,"fashion":4827,"christ":4828,"ward":4829,"da":4830,"pope":4831,"stands":4832,"5th":4833,"flow":4834,"studios":4835,"aired":4836,"commissioned":4837,"contained":4838,"exist":4839,"fresh":4840,"americans":4841,"##per":4842,"wrestling":4843,"approved":4844,"kid":4845,"employed":4846,"respect":4847,"suit":4848,"1925":4849,"angel":4850,"asking":4851,"increasing":4852,"frame":4853,"angry":4854,"selling":4855,"1950s":4856,"thin":4857,"finds":4858,"##nd":4859,"temperature":4860,"statement":4861,"ali":4862,"explain":4863,"inhabitants":4864,"towns":4865,"extensive":4866,"narrow":4867,"51":4868,"jane":4869,"flowers":4870,"images":4871,"promise":4872,"somewhere":4873,"object":4874,"fly":4875,"closely":4876,"##ls":4877,"1912":4878,"bureau":4879,"cape":4880,"1926":4881,"weekly":4882,"presidential":4883,"legislative":4884,"1921":4885,"##ai":4886,"##au":4887,"launch":4888,"founding":4889,"##ny":4890,"978":4891,"##ring":4892,"artillery":4893,"strike":4894,"un":4895,"institutions":4896,"roll":4897,"writers":4898,"landing":4899,"chose":4900,"kevin":4901,"anymore":4902,"pp":4903,"##ut":4904,"attorney":4905,"fit":4906,"dan":4907,"billboard":4908,"receiving":4909,"agricultural":4910,"breaking":4911,"sought":4912,"dave":4913,"admitted":4914,"lands":4915,"mexican":4916,"##bury":4917,"charlie":4918,"specifically":4919,"hole":4920,"iv":4921,"howard":4922,"credit":4923,"moscow":4924,"roads":4925,"accident":4926,"1923":4927,"proved":4928,"wear":4929,"struck":4930,"hey":4931,"guards":4932,"stuff":4933,"slid":4934,"expansion":4935,"1915":4936,"cat":4937,"anthony":4938,"##kin":4939,"melbourne":4940,"opposed":4941,"sub":4942,"southwest":4943,"architect":4944,"failure":4945,"plane":4946,"1916":4947,"##ron":4948,"map":4949,"camera":4950,"tank":4951,"listen":4952,"regarding":4953,"wet":4954,"introduction":4955,"metropolitan":4956,"link":4957,"ep":4958,"fighter":4959,"inch":4960,"grown":4961,"gene":4962,"anger":4963,"fixed":4964,"buy":4965,"dvd":4966,"khan":4967,"domestic":4968,"worldwide":4969,"chapel":4970,"mill":4971,"functions":4972,"examples":4973,"##head":4974,"developing":4975,"1910":4976,"turkey":4977,"hits":4978,"pocket":4979,"antonio":4980,"papers":4981,"grow":4982,"unless":4983,"circuit":4984,"18th":4985,"concerned":4986,"attached":4987,"journalist":4988,"selection":4989,"journey":4990,"converted":4991,"provincial":4992,"painted":4993,"hearing":4994,"aren":4995,"bands":4996,"negative":4997,"aside":4998,"wondered":4999,"knight":5000,"lap":5001,"survey":5002,"ma":5003,"##ow":5004,"noise":5005,"billy":5006,"##ium":5007,"shooting":5008,"guide":5009,"bedroom":5010,"priest":5011,"resistance":5012,"motor":5013,"homes":5014,"sounded":5015,"giant":5016,"##mer":5017,"150":5018,"scenes":5019,"equal":5020,"comic":5021,"patients":5022,"hidden":5023,"solid":5024,"actual":5025,"bringing":5026,"afternoon":5027,"touched":5028,"funds":5029,"wedding":5030,"consisted":5031,"marie":5032,"canal":5033,"sr":5034,"kim":5035,"treaty":5036,"turkish":5037,"recognition":5038,"residence":5039,"cathedral":5040,"broad":5041,"knees":5042,"incident":5043,"shaped":5044,"fired":5045,"norwegian":5046,"handle":5047,"cheek":5048,"contest":5049,"represent":5050,"##pe":5051,"representing":5052,"beauty":5053,"##sen":5054,"birds":5055,"advantage":5056,"emergency":5057,"wrapped":5058,"drawing":5059,"notice":5060,"pink":5061,"broadcasting":5062,"##ong":5063,"somehow":5064,"bachelor":5065,"seventh":5066,"collected":5067,"registered":5068,"establishment":5069,"alan":5070,"assumed":5071,"chemical":5072,"personnel":5073,"roger":5074,"retirement":5075,"jeff":5076,"portuguese":5077,"wore":5078,"tied":5079,"device":5080,"threat":5081,"progress":5082,"advance":5083,"##ised":5084,"banks":5085,"hired":5086,"manchester":5087,"nfl":5088,"teachers":5089,"structures":5090,"forever":5091,"##bo":5092,"tennis":5093,"helping":5094,"saturday":5095,"sale":5096,"applications":5097,"junction":5098,"hip":5099,"incorporated":5100,"neighborhood":5101,"dressed":5102,"ceremony":5103,"##ds":5104,"influenced":5105,"hers":5106,"visual":5107,"stairs":5108,"decades":5109,"inner":5110,"kansas":5111,"hung":5112,"hoped":5113,"gain":5114,"scheduled":5115,"downtown":5116,"engaged":5117,"austria":5118,"clock":5119,"norway":5120,"certainly":5121,"pale":5122,"protected":5123,"1913":5124,"victor":5125,"employees":5126,"plate":5127,"putting":5128,"surrounded":5129,"##ists":5130,"finishing":5131,"blues":5132,"tropical":5133,"##ries":5134,"minnesota":5135,"consider":5136,"philippines":5137,"accept":5138,"54":5139,"retrieved":5140,"1900":5141,"concern":5142,"anderson":5143,"properties":5144,"institution":5145,"gordon":5146,"successfully":5147,"vietnam":5148,"##dy":5149,"backing":5150,"outstanding":5151,"muslim":5152,"crossing":5153,"folk":5154,"producing":5155,"usual":5156,"demand":5157,"occurs":5158,"observed":5159,"lawyer":5160,"educated":5161,"##ana":5162,"kelly":5163,"string":5164,"pleasure":5165,"budget":5166,"items":5167,"quietly":5168,"colorado":5169,"philip":5170,"typical":5171,"##worth":5172,"derived":5173,"600":5174,"survived":5175,"asks":5176,"mental":5177,"##ide":5178,"56":5179,"jake":5180,"jews":5181,"distinguished":5182,"ltd":5183,"1911":5184,"sri":5185,"extremely":5186,"53":5187,"athletic":5188,"loud":5189,"thousands":5190,"worried":5191,"shadow":5192,"transportation":5193,"horses":5194,"weapon":5195,"arena":5196,"importance":5197,"users":5198,"tim":5199,"objects":5200,"contributed":5201,"dragon":5202,"douglas":5203,"aware":5204,"senator":5205,"johnny":5206,"jordan":5207,"sisters":5208,"engines":5209,"flag":5210,"investment":5211,"samuel":5212,"shock":5213,"capable":5214,"clark":5215,"row":5216,"wheel":5217,"refers":5218,"session":5219,"familiar":5220,"biggest":5221,"wins":5222,"hate":5223,"maintained":5224,"drove":5225,"hamilton":5226,"request":5227,"expressed":5228,"injured":5229,"underground":5230,"churches":5231,"walker":5232,"wars":5233,"tunnel":5234,"passes":5235,"stupid":5236,"agriculture":5237,"softly":5238,"cabinet":5239,"regarded":5240,"joining":5241,"indiana":5242,"##ea":5243,"##ms":5244,"push":5245,"dates":5246,"spend":5247,"behavior":5248,"woods":5249,"protein":5250,"gently":5251,"chase":5252,"morgan":5253,"mention":5254,"burning":5255,"wake":5256,"combination":5257,"occur":5258,"mirror":5259,"leads":5260,"jimmy":5261,"indeed":5262,"impossible":5263,"singapore":5264,"paintings":5265,"covering":5266,"##nes":5267,"soldier":5268,"locations":5269,"attendance":5270,"sell":5271,"historian":5272,"wisconsin":5273,"invasion":5274,"argued":5275,"painter":5276,"diego":5277,"changing":5278,"egypt":5279,"##don":5280,"experienced":5281,"inches":5282,"##ku":5283,"missouri":5284,"vol":5285,"grounds":5286,"spoken":5287,"switzerland":5288,"##gan":5289,"reform":5290,"rolling":5291,"ha":5292,"forget":5293,"massive":5294,"resigned":5295,"burned":5296,"allen":5297,"tennessee":5298,"locked":5299,"values":5300,"improved":5301,"##mo":5302,"wounded":5303,"universe":5304,"sick":5305,"dating":5306,"facing":5307,"pack":5308,"purchase":5309,"user":5310,"##pur":5311,"moments":5312,"##ul":5313,"merged":5314,"anniversary":5315,"1908":5316,"coal":5317,"brick":5318,"understood":5319,"causes":5320,"dynasty":5321,"queensland":5322,"establish":5323,"stores":5324,"crisis":5325,"promote":5326,"hoping":5327,"views":5328,"cards":5329,"referee":5330,"extension":5331,"##si":5332,"raise":5333,"arizona":5334,"improve":5335,"colonial":5336,"formal":5337,"charged":5338,"##rt":5339,"palm":5340,"lucky":5341,"hide":5342,"rescue":5343,"faces":5344,"95":5345,"feelings":5346,"candidates":5347,"juan":5348,"##ell":5349,"goods":5350,"6th":5351,"courses":5352,"weekend":5353,"59":5354,"luke":5355,"cash":5356,"fallen":5357,"##om":5358,"delivered":5359,"affected":5360,"installed":5361,"carefully":5362,"tries":5363,"swiss":5364,"hollywood":5365,"costs":5366,"lincoln":5367,"responsibility":5368,"##he":5369,"shore":5370,"file":5371,"proper":5372,"normally":5373,"maryland":5374,"assistance":5375,"jump":5376,"constant":5377,"offering":5378,"friendly":5379,"waters":5380,"persons":5381,"realize":5382,"contain":5383,"trophy":5384,"800":5385,"partnership":5386,"factor":5387,"58":5388,"musicians":5389,"cry":5390,"bound":5391,"oregon":5392,"indicated":5393,"hero":5394,"houston":5395,"medium":5396,"##ure":5397,"consisting":5398,"somewhat":5399,"##ara":5400,"57":5401,"cycle":5402,"##che":5403,"beer":5404,"moore":5405,"frederick":5406,"gotten":5407,"eleven":5408,"worst":5409,"weak":5410,"approached":5411,"arranged":5412,"chin":5413,"loan":5414,"universal":5415,"bond":5416,"fifteen":5417,"pattern":5418,"disappeared":5419,"##ney":5420,"translated":5421,"##zed":5422,"lip":5423,"arab":5424,"capture":5425,"interests":5426,"insurance":5427,"##chi":5428,"shifted":5429,"cave":5430,"prix":5431,"warning":5432,"sections":5433,"courts":5434,"coat":5435,"plot":5436,"smell":5437,"feed":5438,"golf":5439,"favorite":5440,"maintain":5441,"knife":5442,"vs":5443,"voted":5444,"degrees":5445,"finance":5446,"quebec":5447,"opinion":5448,"translation":5449,"manner":5450,"ruled":5451,"operate":5452,"productions":5453,"choose":5454,"musician":5455,"discovery":5456,"confused":5457,"tired":5458,"separated":5459,"stream":5460,"techniques":5461,"committed":5462,"attend":5463,"ranking":5464,"kings":5465,"throw":5466,"passengers":5467,"measure":5468,"horror":5469,"fan":5470,"mining":5471,"sand":5472,"danger":5473,"salt":5474,"calm":5475,"decade":5476,"dam":5477,"require":5478,"runner":5479,"##ik":5480,"rush":5481,"associate":5482,"greece":5483,"##ker":5484,"rivers":5485,"consecutive":5486,"matthew":5487,"##ski":5488,"sighed":5489,"sq":5490,"documents":5491,"steam":5492,"edited":5493,"closing":5494,"tie":5495,"accused":5496,"1905":5497,"##ini":5498,"islamic":5499,"distributed":5500,"directors":5501,"organisation":5502,"bruce":5503,"7th":5504,"breathing":5505,"mad":5506,"lit":5507,"arrival":5508,"concrete":5509,"taste":5510,"08":5511,"composition":5512,"shaking":5513,"faster":5514,"amateur":5515,"adjacent":5516,"stating":5517,"1906":5518,"twin":5519,"flew":5520,"##ran":5521,"tokyo":5522,"publications":5523,"##tone":5524,"obviously":5525,"ridge":5526,"storage":5527,"1907":5528,"carl":5529,"pages":5530,"concluded":5531,"desert":5532,"driven":5533,"universities":5534,"ages":5535,"terminal":5536,"sequence":5537,"borough":5538,"250":5539,"constituency":5540,"creative":5541,"cousin":5542,"economics":5543,"dreams":5544,"margaret":5545,"notably":5546,"reduce":5547,"montreal":5548,"mode":5549,"17th":5550,"ears":5551,"saved":5552,"jan":5553,"vocal":5554,"##ica":5555,"1909":5556,"andy":5557,"##jo":5558,"riding":5559,"roughly":5560,"threatened":5561,"##ise":5562,"meters":5563,"meanwhile":5564,"landed":5565,"compete":5566,"repeated":5567,"grass":5568,"czech":5569,"regularly":5570,"charges":5571,"tea":5572,"sudden":5573,"appeal":5574,"##ung":5575,"solution":5576,"describes":5577,"pierre":5578,"classification":5579,"glad":5580,"parking":5581,"##ning":5582,"belt":5583,"physics":5584,"99":5585,"rachel":5586,"add":5587,"hungarian":5588,"participate":5589,"expedition":5590,"damaged":5591,"gift":5592,"childhood":5593,"85":5594,"fifty":5595,"##red":5596,"mathematics":5597,"jumped":5598,"letting":5599,"defensive":5600,"mph":5601,"##ux":5602,"##gh":5603,"testing":5604,"##hip":5605,"hundreds":5606,"shoot":5607,"owners":5608,"matters":5609,"smoke":5610,"israeli":5611,"kentucky":5612,"dancing":5613,"mounted":5614,"grandfather":5615,"emma":5616,"designs":5617,"profit":5618,"argentina":5619,"##gs":5620,"truly":5621,"li":5622,"lawrence":5623,"cole":5624,"begun":5625,"detroit":5626,"willing":5627,"branches":5628,"smiling":5629,"decide":5630,"miami":5631,"enjoyed":5632,"recordings":5633,"##dale":5634,"poverty":5635,"ethnic":5636,"gay":5637,"##bi":5638,"gary":5639,"arabic":5640,"09":5641,"accompanied":5642,"##one":5643,"##ons":5644,"fishing":5645,"determine":5646,"residential":5647,"acid":5648,"##ary":5649,"alice":5650,"returns":5651,"starred":5652,"mail":5653,"##ang":5654,"jonathan":5655,"strategy":5656,"##ue":5657,"net":5658,"forty":5659,"cook":5660,"businesses":5661,"equivalent":5662,"commonwealth":5663,"distinct":5664,"ill":5665,"##cy":5666,"seriously":5667,"##ors":5668,"##ped":5669,"shift":5670,"harris":5671,"replace":5672,"rio":5673,"imagine":5674,"formula":5675,"ensure":5676,"##ber":5677,"additionally":5678,"scheme":5679,"conservation":5680,"occasionally":5681,"purposes":5682,"feels":5683,"favor":5684,"##and":5685,"##ore":5686,"1930s":5687,"contrast":5688,"hanging":5689,"hunt":5690,"movies":5691,"1904":5692,"instruments":5693,"victims":5694,"danish":5695,"christopher":5696,"busy":5697,"demon":5698,"sugar":5699,"earliest":5700,"colony":5701,"studying":5702,"balance":5703,"duties":5704,"##ks":5705,"belgium":5706,"slipped":5707,"carter":5708,"05":5709,"visible":5710,"stages":5711,"iraq":5712,"fifa":5713,"##im":5714,"commune":5715,"forming":5716,"zero":5717,"07":5718,"continuing":5719,"talked":5720,"counties":5721,"legend":5722,"bathroom":5723,"option":5724,"tail":5725,"clay":5726,"daughters":5727,"afterwards":5728,"severe":5729,"jaw":5730,"visitors":5731,"##ded":5732,"devices":5733,"aviation":5734,"russell":5735,"kate":5736,"##vi":5737,"entering":5738,"subjects":5739,"##ino":5740,"temporary":5741,"swimming":5742,"forth":5743,"smooth":5744,"ghost":5745,"audio":5746,"bush":5747,"operates":5748,"rocks":5749,"movements":5750,"signs":5751,"eddie":5752,"##tz":5753,"ann":5754,"voices":5755,"honorary":5756,"06":5757,"memories":5758,"dallas":5759,"pure":5760,"measures":5761,"racial":5762,"promised":5763,"66":5764,"harvard":5765,"ceo":5766,"16th":5767,"parliamentary":5768,"indicate":5769,"benefit":5770,"flesh":5771,"dublin":5772,"louisiana":5773,"1902":5774,"1901":5775,"patient":5776,"sleeping":5777,"1903":5778,"membership":5779,"coastal":5780,"medieval":5781,"wanting":5782,"element":5783,"scholars":5784,"rice":5785,"62":5786,"limit":5787,"survive":5788,"makeup":5789,"rating":5790,"definitely":5791,"collaboration":5792,"obvious":5793,"##tan":5794,"boss":5795,"ms":5796,"baron":5797,"birthday":5798,"linked":5799,"soil":5800,"diocese":5801,"##lan":5802,"ncaa":5803,"##mann":5804,"offensive":5805,"shell":5806,"shouldn":5807,"waist":5808,"##tus":5809,"plain":5810,"ross":5811,"organ":5812,"resolution":5813,"manufacturing":5814,"adding":5815,"relative":5816,"kennedy":5817,"98":5818,"whilst":5819,"moth":5820,"marketing":5821,"gardens":5822,"crash":5823,"72":5824,"heading":5825,"partners":5826,"credited":5827,"carlos":5828,"moves":5829,"cable":5830,"##zi":5831,"marshall":5832,"##out":5833,"depending":5834,"bottle":5835,"represents":5836,"rejected":5837,"responded":5838,"existed":5839,"04":5840,"jobs":5841,"denmark":5842,"lock":5843,"##ating":5844,"treated":5845,"graham":5846,"routes":5847,"talent":5848,"commissioner":5849,"drugs":5850,"secure":5851,"tests":5852,"reign":5853,"restored":5854,"photography":5855,"##gi":5856,"contributions":5857,"oklahoma":5858,"designer":5859,"disc":5860,"grin":5861,"seattle":5862,"robin":5863,"paused":5864,"atlanta":5865,"unusual":5866,"##gate":5867,"praised":5868,"las":5869,"laughing":5870,"satellite":5871,"hungary":5872,"visiting":5873,"##sky":5874,"interesting":5875,"factors":5876,"deck":5877,"poems":5878,"norman":5879,"##water":5880,"stuck":5881,"speaker":5882,"rifle":5883,"domain":5884,"premiered":5885,"##her":5886,"dc":5887,"comics":5888,"actors":5889,"01":5890,"reputation":5891,"eliminated":5892,"8th":5893,"ceiling":5894,"prisoners":5895,"script":5896,"##nce":5897,"leather":5898,"austin":5899,"mississippi":5900,"rapidly":5901,"admiral":5902,"parallel":5903,"charlotte":5904,"guilty":5905,"tools":5906,"gender":5907,"divisions":5908,"fruit":5909,"##bs":5910,"laboratory":5911,"nelson":5912,"fantasy":5913,"marry":5914,"rapid":5915,"aunt":5916,"tribe":5917,"requirements":5918,"aspects":5919,"suicide":5920,"amongst":5921,"adams":5922,"bone":5923,"ukraine":5924,"abc":5925,"kick":5926,"sees":5927,"edinburgh":5928,"clothing":5929,"column":5930,"rough":5931,"gods":5932,"hunting":5933,"broadway":5934,"gathered":5935,"concerns":5936,"##ek":5937,"spending":5938,"ty":5939,"12th":5940,"snapped":5941,"requires":5942,"solar":5943,"bones":5944,"cavalry":5945,"##tta":5946,"iowa":5947,"drinking":5948,"waste":5949,"index":5950,"franklin":5951,"charity":5952,"thompson":5953,"stewart":5954,"tip":5955,"flash":5956,"landscape":5957,"friday":5958,"enjoy":5959,"singh":5960,"poem":5961,"listening":5962,"##back":5963,"eighth":5964,"fred":5965,"differences":5966,"adapted":5967,"bomb":5968,"ukrainian":5969,"surgery":5970,"corporate":5971,"masters":5972,"anywhere":5973,"##more":5974,"waves":5975,"odd":5976,"sean":5977,"portugal":5978,"orleans":5979,"dick":5980,"debate":5981,"kent":5982,"eating":5983,"puerto":5984,"cleared":5985,"96":5986,"expect":5987,"cinema":5988,"97":5989,"guitarist":5990,"blocks":5991,"electrical":5992,"agree":5993,"involving":5994,"depth":5995,"dying":5996,"panel":5997,"struggle":5998,"##ged":5999,"peninsula":6000,"adults":6001,"novels":6002,"emerged":6003,"vienna":6004,"metro":6005,"debuted":6006,"shoes":6007,"tamil":6008,"songwriter":6009,"meets":6010,"prove":6011,"beating":6012,"instance":6013,"heaven":6014,"scared":6015,"sending":6016,"marks":6017,"artistic":6018,"passage":6019,"superior":6020,"03":6021,"significantly":6022,"shopping":6023,"##tive":6024,"retained":6025,"##izing":6026,"malaysia":6027,"technique":6028,"cheeks":6029,"##ola":6030,"warren":6031,"maintenance":6032,"destroy":6033,"extreme":6034,"allied":6035,"120":6036,"appearing":6037,"##yn":6038,"fill":6039,"advice":6040,"alabama":6041,"qualifying":6042,"policies":6043,"cleveland":6044,"hat":6045,"battery":6046,"smart":6047,"authors":6048,"10th":6049,"soundtrack":6050,"acted":6051,"dated":6052,"lb":6053,"glance":6054,"equipped":6055,"coalition":6056,"funny":6057,"outer":6058,"ambassador":6059,"roy":6060,"possibility":6061,"couples":6062,"campbell":6063,"dna":6064,"loose":6065,"ethan":6066,"supplies":6067,"1898":6068,"gonna":6069,"88":6070,"monster":6071,"##res":6072,"shake":6073,"agents":6074,"frequency":6075,"springs":6076,"dogs":6077,"practices":6078,"61":6079,"gang":6080,"plastic":6081,"easier":6082,"suggests":6083,"gulf":6084,"blade":6085,"exposed":6086,"colors":6087,"industries":6088,"markets":6089,"pan":6090,"nervous":6091,"electoral":6092,"charts":6093,"legislation":6094,"ownership":6095,"##idae":6096,"mac":6097,"appointment":6098,"shield":6099,"copy":6100,"assault":6101,"socialist":6102,"abbey":6103,"monument":6104,"license":6105,"throne":6106,"employment":6107,"jay":6108,"93":6109,"replacement":6110,"charter":6111,"cloud":6112,"powered":6113,"suffering":6114,"accounts":6115,"oak":6116,"connecticut":6117,"strongly":6118,"wright":6119,"colour":6120,"crystal":6121,"13th":6122,"context":6123,"welsh":6124,"networks":6125,"voiced":6126,"gabriel":6127,"jerry":6128,"##cing":6129,"forehead":6130,"mp":6131,"##ens":6132,"manage":6133,"schedule":6134,"totally":6135,"remix":6136,"##ii":6137,"forests":6138,"occupation":6139,"print":6140,"nicholas":6141,"brazilian":6142,"strategic":6143,"vampires":6144,"engineers":6145,"76":6146,"roots":6147,"seek":6148,"correct":6149,"instrumental":6150,"und":6151,"alfred":6152,"backed":6153,"hop":6154,"##des":6155,"stanley":6156,"robinson":6157,"traveled":6158,"wayne":6159,"welcome":6160,"austrian":6161,"achieve":6162,"67":6163,"exit":6164,"rates":6165,"1899":6166,"strip":6167,"whereas":6168,"##cs":6169,"sing":6170,"deeply":6171,"adventure":6172,"bobby":6173,"rick":6174,"jamie":6175,"careful":6176,"components":6177,"cap":6178,"useful":6179,"personality":6180,"knee":6181,"##shi":6182,"pushing":6183,"hosts":6184,"02":6185,"protest":6186,"ca":6187,"ottoman":6188,"symphony":6189,"##sis":6190,"63":6191,"boundary":6192,"1890":6193,"processes":6194,"considering":6195,"considerable":6196,"tons":6197,"##work":6198,"##ft":6199,"##nia":6200,"cooper":6201,"trading":6202,"dear":6203,"conduct":6204,"91":6205,"illegal":6206,"apple":6207,"revolutionary":6208,"holiday":6209,"definition":6210,"harder":6211,"##van":6212,"jacob":6213,"circumstances":6214,"destruction":6215,"##lle":6216,"popularity":6217,"grip":6218,"classified":6219,"liverpool":6220,"donald":6221,"baltimore":6222,"flows":6223,"seeking":6224,"honour":6225,"approval":6226,"92":6227,"mechanical":6228,"till":6229,"happening":6230,"statue":6231,"critic":6232,"increasingly":6233,"immediate":6234,"describe":6235,"commerce":6236,"stare":6237,"##ster":6238,"indonesia":6239,"meat":6240,"rounds":6241,"boats":6242,"baker":6243,"orthodox":6244,"depression":6245,"formally":6246,"worn":6247,"naked":6248,"claire":6249,"muttered":6250,"sentence":6251,"11th":6252,"emily":6253,"document":6254,"77":6255,"criticism":6256,"wished":6257,"vessel":6258,"spiritual":6259,"bent":6260,"virgin":6261,"parker":6262,"minimum":6263,"murray":6264,"lunch":6265,"danny":6266,"printed":6267,"compilation":6268,"keyboards":6269,"false":6270,"blow":6271,"belonged":6272,"68":6273,"raising":6274,"78":6275,"cutting":6276,"##board":6277,"pittsburgh":6278,"##up":6279,"9th":6280,"shadows":6281,"81":6282,"hated":6283,"indigenous":6284,"jon":6285,"15th":6286,"barry":6287,"scholar":6288,"ah":6289,"##zer":6290,"oliver":6291,"##gy":6292,"stick":6293,"susan":6294,"meetings":6295,"attracted":6296,"spell":6297,"romantic":6298,"##ver":6299,"ye":6300,"1895":6301,"photo":6302,"demanded":6303,"customers":6304,"##ac":6305,"1896":6306,"logan":6307,"revival":6308,"keys":6309,"modified":6310,"commanded":6311,"jeans":6312,"##ious":6313,"upset":6314,"raw":6315,"phil":6316,"detective":6317,"hiding":6318,"resident":6319,"vincent":6320,"##bly":6321,"experiences":6322,"diamond":6323,"defeating":6324,"coverage":6325,"lucas":6326,"external":6327,"parks":6328,"franchise":6329,"helen":6330,"bible":6331,"successor":6332,"percussion":6333,"celebrated":6334,"il":6335,"lift":6336,"profile":6337,"clan":6338,"romania":6339,"##ied":6340,"mills":6341,"##su":6342,"nobody":6343,"achievement":6344,"shrugged":6345,"fault":6346,"1897":6347,"rhythm":6348,"initiative":6349,"breakfast":6350,"carbon":6351,"700":6352,"69":6353,"lasted":6354,"violent":6355,"74":6356,"wound":6357,"ken":6358,"killer":6359,"gradually":6360,"filmed":6361,"°c":6362,"dollars":6363,"processing":6364,"94":6365,"remove":6366,"criticized":6367,"guests":6368,"sang":6369,"chemistry":6370,"##vin":6371,"legislature":6372,"disney":6373,"##bridge":6374,"uniform":6375,"escaped":6376,"integrated":6377,"proposal":6378,"purple":6379,"denied":6380,"liquid":6381,"karl":6382,"influential":6383,"morris":6384,"nights":6385,"stones":6386,"intense":6387,"experimental":6388,"twisted":6389,"71":6390,"84":6391,"##ld":6392,"pace":6393,"nazi":6394,"mitchell":6395,"ny":6396,"blind":6397,"reporter":6398,"newspapers":6399,"14th":6400,"centers":6401,"burn":6402,"basin":6403,"forgotten":6404,"surviving":6405,"filed":6406,"collections":6407,"monastery":6408,"losses":6409,"manual":6410,"couch":6411,"description":6412,"appropriate":6413,"merely":6414,"tag":6415,"missions":6416,"sebastian":6417,"restoration":6418,"replacing":6419,"triple":6420,"73":6421,"elder":6422,"julia":6423,"warriors":6424,"benjamin":6425,"julian":6426,"convinced":6427,"stronger":6428,"amazing":6429,"declined":6430,"versus":6431,"merchant":6432,"happens":6433,"output":6434,"finland":6435,"bare":6436,"barbara":6437,"absence":6438,"ignored":6439,"dawn":6440,"injuries":6441,"##port":6442,"producers":6443,"##ram":6444,"82":6445,"luis":6446,"##ities":6447,"kw":6448,"admit":6449,"expensive":6450,"electricity":6451,"nba":6452,"exception":6453,"symbol":6454,"##ving":6455,"ladies":6456,"shower":6457,"sheriff":6458,"characteristics":6459,"##je":6460,"aimed":6461,"button":6462,"ratio":6463,"effectively":6464,"summit":6465,"angle":6466,"jury":6467,"bears":6468,"foster":6469,"vessels":6470,"pants":6471,"executed":6472,"evans":6473,"dozen":6474,"advertising":6475,"kicked":6476,"patrol":6477,"1889":6478,"competitions":6479,"lifetime":6480,"principles":6481,"athletics":6482,"##logy":6483,"birmingham":6484,"sponsored":6485,"89":6486,"rob":6487,"nomination":6488,"1893":6489,"acoustic":6490,"##sm":6491,"creature":6492,"longest":6493,"##tra":6494,"credits":6495,"harbor":6496,"dust":6497,"josh":6498,"##so":6499,"territories":6500,"milk":6501,"infrastructure":6502,"completion":6503,"thailand":6504,"indians":6505,"leon":6506,"archbishop":6507,"##sy":6508,"assist":6509,"pitch":6510,"blake":6511,"arrangement":6512,"girlfriend":6513,"serbian":6514,"operational":6515,"hence":6516,"sad":6517,"scent":6518,"fur":6519,"dj":6520,"sessions":6521,"hp":6522,"refer":6523,"rarely":6524,"##ora":6525,"exists":6526,"1892":6527,"##ten":6528,"scientists":6529,"dirty":6530,"penalty":6531,"burst":6532,"portrait":6533,"seed":6534,"79":6535,"pole":6536,"limits":6537,"rival":6538,"1894":6539,"stable":6540,"alpha":6541,"grave":6542,"constitutional":6543,"alcohol":6544,"arrest":6545,"flower":6546,"mystery":6547,"devil":6548,"architectural":6549,"relationships":6550,"greatly":6551,"habitat":6552,"##istic":6553,"larry":6554,"progressive":6555,"remote":6556,"cotton":6557,"##ics":6558,"##ok":6559,"preserved":6560,"reaches":6561,"##ming":6562,"cited":6563,"86":6564,"vast":6565,"scholarship":6566,"decisions":6567,"cbs":6568,"joy":6569,"teach":6570,"1885":6571,"editions":6572,"knocked":6573,"eve":6574,"searching":6575,"partly":6576,"participation":6577,"gap":6578,"animated":6579,"fate":6580,"excellent":6581,"##ett":6582,"na":6583,"87":6584,"alternate":6585,"saints":6586,"youngest":6587,"##ily":6588,"climbed":6589,"##ita":6590,"##tors":6591,"suggest":6592,"##ct":6593,"discussion":6594,"staying":6595,"choir":6596,"lakes":6597,"jacket":6598,"revenue":6599,"nevertheless":6600,"peaked":6601,"instrument":6602,"wondering":6603,"annually":6604,"managing":6605,"neil":6606,"1891":6607,"signing":6608,"terry":6609,"##ice":6610,"apply":6611,"clinical":6612,"brooklyn":6613,"aim":6614,"catherine":6615,"fuck":6616,"farmers":6617,"figured":6618,"ninth":6619,"pride":6620,"hugh":6621,"evolution":6622,"ordinary":6623,"involvement":6624,"comfortable":6625,"shouted":6626,"tech":6627,"encouraged":6628,"taiwan":6629,"representation":6630,"sharing":6631,"##lia":6632,"##em":6633,"panic":6634,"exact":6635,"cargo":6636,"competing":6637,"fat":6638,"cried":6639,"83":6640,"1920s":6641,"occasions":6642,"pa":6643,"cabin":6644,"borders":6645,"utah":6646,"marcus":6647,"##isation":6648,"badly":6649,"muscles":6650,"##ance":6651,"victorian":6652,"transition":6653,"warner":6654,"bet":6655,"permission":6656,"##rin":6657,"slave":6658,"terrible":6659,"similarly":6660,"shares":6661,"seth":6662,"uefa":6663,"possession":6664,"medals":6665,"benefits":6666,"colleges":6667,"lowered":6668,"perfectly":6669,"mall":6670,"transit":6671,"##ye":6672,"##kar":6673,"publisher":6674,"##ened":6675,"harrison":6676,"deaths":6677,"elevation":6678,"##ae":6679,"asleep":6680,"machines":6681,"sigh":6682,"ash":6683,"hardly":6684,"argument":6685,"occasion":6686,"parent":6687,"leo":6688,"decline":6689,"1888":6690,"contribution":6691,"##ua":6692,"concentration":6693,"1000":6694,"opportunities":6695,"hispanic":6696,"guardian":6697,"extent":6698,"emotions":6699,"hips":6700,"mason":6701,"volumes":6702,"bloody":6703,"controversy":6704,"diameter":6705,"steady":6706,"mistake":6707,"phoenix":6708,"identify":6709,"violin":6710,"##sk":6711,"departure":6712,"richmond":6713,"spin":6714,"funeral":6715,"enemies":6716,"1864":6717,"gear":6718,"literally":6719,"connor":6720,"random":6721,"sergeant":6722,"grab":6723,"confusion":6724,"1865":6725,"transmission":6726,"informed":6727,"op":6728,"leaning":6729,"sacred":6730,"suspended":6731,"thinks":6732,"gates":6733,"portland":6734,"luck":6735,"agencies":6736,"yours":6737,"hull":6738,"expert":6739,"muscle":6740,"layer":6741,"practical":6742,"sculpture":6743,"jerusalem":6744,"latest":6745,"lloyd":6746,"statistics":6747,"deeper":6748,"recommended":6749,"warrior":6750,"arkansas":6751,"mess":6752,"supports":6753,"greg":6754,"eagle":6755,"1880":6756,"recovered":6757,"rated":6758,"concerts":6759,"rushed":6760,"##ano":6761,"stops":6762,"eggs":6763,"files":6764,"premiere":6765,"keith":6766,"##vo":6767,"delhi":6768,"turner":6769,"pit":6770,"affair":6771,"belief":6772,"paint":6773,"##zing":6774,"mate":6775,"##ach":6776,"##ev":6777,"victim":6778,"##ology":6779,"withdrew":6780,"bonus":6781,"styles":6782,"fled":6783,"##ud":6784,"glasgow":6785,"technologies":6786,"funded":6787,"nbc":6788,"adaptation":6789,"##ata":6790,"portrayed":6791,"cooperation":6792,"supporters":6793,"judges":6794,"bernard":6795,"justin":6796,"hallway":6797,"ralph":6798,"##ick":6799,"graduating":6800,"controversial":6801,"distant":6802,"continental":6803,"spider":6804,"bite":6805,"##ho":6806,"recognize":6807,"intention":6808,"mixing":6809,"##ese":6810,"egyptian":6811,"bow":6812,"tourism":6813,"suppose":6814,"claiming":6815,"tiger":6816,"dominated":6817,"participants":6818,"vi":6819,"##ru":6820,"nurse":6821,"partially":6822,"tape":6823,"##rum":6824,"psychology":6825,"##rn":6826,"essential":6827,"touring":6828,"duo":6829,"voting":6830,"civilian":6831,"emotional":6832,"channels":6833,"##king":6834,"apparent":6835,"hebrew":6836,"1887":6837,"tommy":6838,"carrier":6839,"intersection":6840,"beast":6841,"hudson":6842,"##gar":6843,"##zo":6844,"lab":6845,"nova":6846,"bench":6847,"discuss":6848,"costa":6849,"##ered":6850,"detailed":6851,"behalf":6852,"drivers":6853,"unfortunately":6854,"obtain":6855,"##lis":6856,"rocky":6857,"##dae":6858,"siege":6859,"friendship":6860,"honey":6861,"##rian":6862,"1861":6863,"amy":6864,"hang":6865,"posted":6866,"governments":6867,"collins":6868,"respond":6869,"wildlife":6870,"preferred":6871,"operator":6872,"##po":6873,"laura":6874,"pregnant":6875,"videos":6876,"dennis":6877,"suspected":6878,"boots":6879,"instantly":6880,"weird":6881,"automatic":6882,"businessman":6883,"alleged":6884,"placing":6885,"throwing":6886,"ph":6887,"mood":6888,"1862":6889,"perry":6890,"venue":6891,"jet":6892,"remainder":6893,"##lli":6894,"##ci":6895,"passion":6896,"biological":6897,"boyfriend":6898,"1863":6899,"dirt":6900,"buffalo":6901,"ron":6902,"segment":6903,"fa":6904,"abuse":6905,"##era":6906,"genre":6907,"thrown":6908,"stroke":6909,"colored":6910,"stress":6911,"exercise":6912,"displayed":6913,"##gen":6914,"struggled":6915,"##tti":6916,"abroad":6917,"dramatic":6918,"wonderful":6919,"thereafter":6920,"madrid":6921,"component":6922,"widespread":6923,"##sed":6924,"tale":6925,"citizen":6926,"todd":6927,"monday":6928,"1886":6929,"vancouver":6930,"overseas":6931,"forcing":6932,"crying":6933,"descent":6934,"##ris":6935,"discussed":6936,"substantial":6937,"ranks":6938,"regime":6939,"1870":6940,"provinces":6941,"switch":6942,"drum":6943,"zane":6944,"ted":6945,"tribes":6946,"proof":6947,"lp":6948,"cream":6949,"researchers":6950,"volunteer":6951,"manor":6952,"silk":6953,"milan":6954,"donated":6955,"allies":6956,"venture":6957,"principle":6958,"delivery":6959,"enterprise":6960,"##ves":6961,"##ans":6962,"bars":6963,"traditionally":6964,"witch":6965,"reminded":6966,"copper":6967,"##uk":6968,"pete":6969,"inter":6970,"links":6971,"colin":6972,"grinned":6973,"elsewhere":6974,"competitive":6975,"frequent":6976,"##oy":6977,"scream":6978,"##hu":6979,"tension":6980,"texts":6981,"submarine":6982,"finnish":6983,"defending":6984,"defend":6985,"pat":6986,"detail":6987,"1884":6988,"affiliated":6989,"stuart":6990,"themes":6991,"villa":6992,"periods":6993,"tool":6994,"belgian":6995,"ruling":6996,"crimes":6997,"answers":6998,"folded":6999,"licensed":7000,"resort":7001,"demolished":7002,"hans":7003,"lucy":7004,"1881":7005,"lion":7006,"traded":7007,"photographs":7008,"writes":7009,"craig":7010,"##fa":7011,"trials":7012,"generated":7013,"beth":7014,"noble":7015,"debt":7016,"percentage":7017,"yorkshire":7018,"erected":7019,"ss":7020,"viewed":7021,"grades":7022,"confidence":7023,"ceased":7024,"islam":7025,"telephone":7026,"retail":7027,"##ible":7028,"chile":7029,"m²":7030,"roberts":7031,"sixteen":7032,"##ich":7033,"commented":7034,"hampshire":7035,"innocent":7036,"dual":7037,"pounds":7038,"checked":7039,"regulations":7040,"afghanistan":7041,"sung":7042,"rico":7043,"liberty":7044,"assets":7045,"bigger":7046,"options":7047,"angels":7048,"relegated":7049,"tribute":7050,"wells":7051,"attending":7052,"leaf":7053,"##yan":7054,"butler":7055,"romanian":7056,"forum":7057,"monthly":7058,"lisa":7059,"patterns":7060,"gmina":7061,"##tory":7062,"madison":7063,"hurricane":7064,"rev":7065,"##ians":7066,"bristol":7067,"##ula":7068,"elite":7069,"valuable":7070,"disaster":7071,"democracy":7072,"awareness":7073,"germans":7074,"freyja":7075,"##ins":7076,"loop":7077,"absolutely":7078,"paying":7079,"populations":7080,"maine":7081,"sole":7082,"prayer":7083,"spencer":7084,"releases":7085,"doorway":7086,"bull":7087,"##ani":7088,"lover":7089,"midnight":7090,"conclusion":7091,"##sson":7092,"thirteen":7093,"lily":7094,"mediterranean":7095,"##lt":7096,"nhl":7097,"proud":7098,"sample":7099,"##hill":7100,"drummer":7101,"guinea":7102,"##ova":7103,"murphy":7104,"climb":7105,"##ston":7106,"instant":7107,"attributed":7108,"horn":7109,"ain":7110,"railways":7111,"steven":7112,"##ao":7113,"autumn":7114,"ferry":7115,"opponent":7116,"root":7117,"traveling":7118,"secured":7119,"corridor":7120,"stretched":7121,"tales":7122,"sheet":7123,"trinity":7124,"cattle":7125,"helps":7126,"indicates":7127,"manhattan":7128,"murdered":7129,"fitted":7130,"1882":7131,"gentle":7132,"grandmother":7133,"mines":7134,"shocked":7135,"vegas":7136,"produces":7137,"##light":7138,"caribbean":7139,"##ou":7140,"belong":7141,"continuous":7142,"desperate":7143,"drunk":7144,"historically":7145,"trio":7146,"waved":7147,"raf":7148,"dealing":7149,"nathan":7150,"bat":7151,"murmured":7152,"interrupted":7153,"residing":7154,"scientist":7155,"pioneer":7156,"harold":7157,"aaron":7158,"##net":7159,"delta":7160,"attempting":7161,"minority":7162,"mini":7163,"believes":7164,"chorus":7165,"tend":7166,"lots":7167,"eyed":7168,"indoor":7169,"load":7170,"shots":7171,"updated":7172,"jail":7173,"##llo":7174,"concerning":7175,"connecting":7176,"wealth":7177,"##ved":7178,"slaves":7179,"arrive":7180,"rangers":7181,"sufficient":7182,"rebuilt":7183,"##wick":7184,"cardinal":7185,"flood":7186,"muhammad":7187,"whenever":7188,"relation":7189,"runners":7190,"moral":7191,"repair":7192,"viewers":7193,"arriving":7194,"revenge":7195,"punk":7196,"assisted":7197,"bath":7198,"fairly":7199,"breathe":7200,"lists":7201,"innings":7202,"illustrated":7203,"whisper":7204,"nearest":7205,"voters":7206,"clinton":7207,"ties":7208,"ultimate":7209,"screamed":7210,"beijing":7211,"lions":7212,"andre":7213,"fictional":7214,"gathering":7215,"comfort":7216,"radar":7217,"suitable":7218,"dismissed":7219,"hms":7220,"ban":7221,"pine":7222,"wrist":7223,"atmosphere":7224,"voivodeship":7225,"bid":7226,"timber":7227,"##ned":7228,"##nan":7229,"giants":7230,"##ane":7231,"cameron":7232,"recovery":7233,"uss":7234,"identical":7235,"categories":7236,"switched":7237,"serbia":7238,"laughter":7239,"noah":7240,"ensemble":7241,"therapy":7242,"peoples":7243,"touching":7244,"##off":7245,"locally":7246,"pearl":7247,"platforms":7248,"everywhere":7249,"ballet":7250,"tables":7251,"lanka":7252,"herbert":7253,"outdoor":7254,"toured":7255,"derek":7256,"1883":7257,"spaces":7258,"contested":7259,"swept":7260,"1878":7261,"exclusive":7262,"slight":7263,"connections":7264,"##dra":7265,"winds":7266,"prisoner":7267,"collective":7268,"bangladesh":7269,"tube":7270,"publicly":7271,"wealthy":7272,"thai":7273,"##ys":7274,"isolated":7275,"select":7276,"##ric":7277,"insisted":7278,"pen":7279,"fortune":7280,"ticket":7281,"spotted":7282,"reportedly":7283,"animation":7284,"enforcement":7285,"tanks":7286,"110":7287,"decides":7288,"wider":7289,"lowest":7290,"owen":7291,"##time":7292,"nod":7293,"hitting":7294,"##hn":7295,"gregory":7296,"furthermore":7297,"magazines":7298,"fighters":7299,"solutions":7300,"##ery":7301,"pointing":7302,"requested":7303,"peru":7304,"reed":7305,"chancellor":7306,"knights":7307,"mask":7308,"worker":7309,"eldest":7310,"flames":7311,"reduction":7312,"1860":7313,"volunteers":7314,"##tis":7315,"reporting":7316,"##hl":7317,"wire":7318,"advisory":7319,"endemic":7320,"origins":7321,"settlers":7322,"pursue":7323,"knock":7324,"consumer":7325,"1876":7326,"eu":7327,"compound":7328,"creatures":7329,"mansion":7330,"sentenced":7331,"ivan":7332,"deployed":7333,"guitars":7334,"frowned":7335,"involves":7336,"mechanism":7337,"kilometers":7338,"perspective":7339,"shops":7340,"maps":7341,"terminus":7342,"duncan":7343,"alien":7344,"fist":7345,"bridges":7346,"##pers":7347,"heroes":7348,"fed":7349,"derby":7350,"swallowed":7351,"##ros":7352,"patent":7353,"sara":7354,"illness":7355,"characterized":7356,"adventures":7357,"slide":7358,"hawaii":7359,"jurisdiction":7360,"##op":7361,"organised":7362,"##side":7363,"adelaide":7364,"walks":7365,"biology":7366,"se":7367,"##ties":7368,"rogers":7369,"swing":7370,"tightly":7371,"boundaries":7372,"##rie":7373,"prepare":7374,"implementation":7375,"stolen":7376,"##sha":7377,"certified":7378,"colombia":7379,"edwards":7380,"garage":7381,"##mm":7382,"recalled":7383,"##ball":7384,"rage":7385,"harm":7386,"nigeria":7387,"breast":7388,"##ren":7389,"furniture":7390,"pupils":7391,"settle":7392,"##lus":7393,"cuba":7394,"balls":7395,"client":7396,"alaska":7397,"21st":7398,"linear":7399,"thrust":7400,"celebration":7401,"latino":7402,"genetic":7403,"terror":7404,"##cia":7405,"##ening":7406,"lightning":7407,"fee":7408,"witness":7409,"lodge":7410,"establishing":7411,"skull":7412,"##ique":7413,"earning":7414,"hood":7415,"##ei":7416,"rebellion":7417,"wang":7418,"sporting":7419,"warned":7420,"missile":7421,"devoted":7422,"activist":7423,"porch":7424,"worship":7425,"fourteen":7426,"package":7427,"1871":7428,"decorated":7429,"##shire":7430,"housed":7431,"##ock":7432,"chess":7433,"sailed":7434,"doctors":7435,"oscar":7436,"joan":7437,"treat":7438,"garcia":7439,"harbour":7440,"jeremy":7441,"##ire":7442,"traditions":7443,"dominant":7444,"jacques":7445,"##gon":7446,"##wan":7447,"relocated":7448,"1879":7449,"amendment":7450,"sized":7451,"companion":7452,"simultaneously":7453,"volleyball":7454,"spun":7455,"acre":7456,"increases":7457,"stopping":7458,"loves":7459,"belongs":7460,"affect":7461,"drafted":7462,"tossed":7463,"scout":7464,"battles":7465,"1875":7466,"filming":7467,"shoved":7468,"munich":7469,"tenure":7470,"vertical":7471,"romance":7472,"pc":7473,"##cher":7474,"argue":7475,"##ical":7476,"craft":7477,"ranging":7478,"www":7479,"opens":7480,"honest":7481,"tyler":7482,"yesterday":7483,"virtual":7484,"##let":7485,"muslims":7486,"reveal":7487,"snake":7488,"immigrants":7489,"radical":7490,"screaming":7491,"speakers":7492,"firing":7493,"saving":7494,"belonging":7495,"ease":7496,"lighting":7497,"prefecture":7498,"blame":7499,"farmer":7500,"hungry":7501,"grows":7502,"rubbed":7503,"beam":7504,"sur":7505,"subsidiary":7506,"##cha":7507,"armenian":7508,"sao":7509,"dropping":7510,"conventional":7511,"##fer":7512,"microsoft":7513,"reply":7514,"qualify":7515,"spots":7516,"1867":7517,"sweat":7518,"festivals":7519,"##ken":7520,"immigration":7521,"physician":7522,"discover":7523,"exposure":7524,"sandy":7525,"explanation":7526,"isaac":7527,"implemented":7528,"##fish":7529,"hart":7530,"initiated":7531,"connect":7532,"stakes":7533,"presents":7534,"heights":7535,"householder":7536,"pleased":7537,"tourist":7538,"regardless":7539,"slip":7540,"closest":7541,"##ction":7542,"surely":7543,"sultan":7544,"brings":7545,"riley":7546,"preparation":7547,"aboard":7548,"slammed":7549,"baptist":7550,"experiment":7551,"ongoing":7552,"interstate":7553,"organic":7554,"playoffs":7555,"##ika":7556,"1877":7557,"130":7558,"##tar":7559,"hindu":7560,"error":7561,"tours":7562,"tier":7563,"plenty":7564,"arrangements":7565,"talks":7566,"trapped":7567,"excited":7568,"sank":7569,"ho":7570,"athens":7571,"1872":7572,"denver":7573,"welfare":7574,"suburb":7575,"athletes":7576,"trick":7577,"diverse":7578,"belly":7579,"exclusively":7580,"yelled":7581,"1868":7582,"##med":7583,"conversion":7584,"##ette":7585,"1874":7586,"internationally":7587,"computers":7588,"conductor":7589,"abilities":7590,"sensitive":7591,"hello":7592,"dispute":7593,"measured":7594,"globe":7595,"rocket":7596,"prices":7597,"amsterdam":7598,"flights":7599,"tigers":7600,"inn":7601,"municipalities":7602,"emotion":7603,"references":7604,"3d":7605,"##mus":7606,"explains":7607,"airlines":7608,"manufactured":7609,"pm":7610,"archaeological":7611,"1873":7612,"interpretation":7613,"devon":7614,"comment":7615,"##ites":7616,"settlements":7617,"kissing":7618,"absolute":7619,"improvement":7620,"suite":7621,"impressed":7622,"barcelona":7623,"sullivan":7624,"jefferson":7625,"towers":7626,"jesse":7627,"julie":7628,"##tin":7629,"##lu":7630,"grandson":7631,"hi":7632,"gauge":7633,"regard":7634,"rings":7635,"interviews":7636,"trace":7637,"raymond":7638,"thumb":7639,"departments":7640,"burns":7641,"serial":7642,"bulgarian":7643,"scores":7644,"demonstrated":7645,"##ix":7646,"1866":7647,"kyle":7648,"alberta":7649,"underneath":7650,"romanized":7651,"##ward":7652,"relieved":7653,"acquisition":7654,"phrase":7655,"cliff":7656,"reveals":7657,"han":7658,"cuts":7659,"merger":7660,"custom":7661,"##dar":7662,"nee":7663,"gilbert":7664,"graduation":7665,"##nts":7666,"assessment":7667,"cafe":7668,"difficulty":7669,"demands":7670,"swung":7671,"democrat":7672,"jennifer":7673,"commons":7674,"1940s":7675,"grove":7676,"##yo":7677,"completing":7678,"focuses":7679,"sum":7680,"substitute":7681,"bearing":7682,"stretch":7683,"reception":7684,"##py":7685,"reflected":7686,"essentially":7687,"destination":7688,"pairs":7689,"##ched":7690,"survival":7691,"resource":7692,"##bach":7693,"promoting":7694,"doubles":7695,"messages":7696,"tear":7697,"##down":7698,"##fully":7699,"parade":7700,"florence":7701,"harvey":7702,"incumbent":7703,"partial":7704,"framework":7705,"900":7706,"pedro":7707,"frozen":7708,"procedure":7709,"olivia":7710,"controls":7711,"##mic":7712,"shelter":7713,"personally":7714,"temperatures":7715,"##od":7716,"brisbane":7717,"tested":7718,"sits":7719,"marble":7720,"comprehensive":7721,"oxygen":7722,"leonard":7723,"##kov":7724,"inaugural":7725,"iranian":7726,"referring":7727,"quarters":7728,"attitude":7729,"##ivity":7730,"mainstream":7731,"lined":7732,"mars":7733,"dakota":7734,"norfolk":7735,"unsuccessful":7736,"##°":7737,"explosion":7738,"helicopter":7739,"congressional":7740,"##sing":7741,"inspector":7742,"bitch":7743,"seal":7744,"departed":7745,"divine":7746,"##ters":7747,"coaching":7748,"examination":7749,"punishment":7750,"manufacturer":7751,"sink":7752,"columns":7753,"unincorporated":7754,"signals":7755,"nevada":7756,"squeezed":7757,"dylan":7758,"dining":7759,"photos":7760,"martial":7761,"manuel":7762,"eighteen":7763,"elevator":7764,"brushed":7765,"plates":7766,"ministers":7767,"ivy":7768,"congregation":7769,"##len":7770,"slept":7771,"specialized":7772,"taxes":7773,"curve":7774,"restricted":7775,"negotiations":7776,"likes":7777,"statistical":7778,"arnold":7779,"inspiration":7780,"execution":7781,"bold":7782,"intermediate":7783,"significance":7784,"margin":7785,"ruler":7786,"wheels":7787,"gothic":7788,"intellectual":7789,"dependent":7790,"listened":7791,"eligible":7792,"buses":7793,"widow":7794,"syria":7795,"earn":7796,"cincinnati":7797,"collapsed":7798,"recipient":7799,"secrets":7800,"accessible":7801,"philippine":7802,"maritime":7803,"goddess":7804,"clerk":7805,"surrender":7806,"breaks":7807,"playoff":7808,"database":7809,"##ified":7810,"##lon":7811,"ideal":7812,"beetle":7813,"aspect":7814,"soap":7815,"regulation":7816,"strings":7817,"expand":7818,"anglo":7819,"shorter":7820,"crosses":7821,"retreat":7822,"tough":7823,"coins":7824,"wallace":7825,"directions":7826,"pressing":7827,"##oon":7828,"shipping":7829,"locomotives":7830,"comparison":7831,"topics":7832,"nephew":7833,"##mes":7834,"distinction":7835,"honors":7836,"travelled":7837,"sierra":7838,"ibn":7839,"##over":7840,"fortress":7841,"sa":7842,"recognised":7843,"carved":7844,"1869":7845,"clients":7846,"##dan":7847,"intent":7848,"##mar":7849,"coaches":7850,"describing":7851,"bread":7852,"##ington":7853,"beaten":7854,"northwestern":7855,"##ona":7856,"merit":7857,"youtube":7858,"collapse":7859,"challenges":7860,"em":7861,"historians":7862,"objective":7863,"submitted":7864,"virus":7865,"attacking":7866,"drake":7867,"assume":7868,"##ere":7869,"diseases":7870,"marc":7871,"stem":7872,"leeds":7873,"##cus":7874,"##ab":7875,"farming":7876,"glasses":7877,"##lock":7878,"visits":7879,"nowhere":7880,"fellowship":7881,"relevant":7882,"carries":7883,"restaurants":7884,"experiments":7885,"101":7886,"constantly":7887,"bases":7888,"targets":7889,"shah":7890,"tenth":7891,"opponents":7892,"verse":7893,"territorial":7894,"##ira":7895,"writings":7896,"corruption":7897,"##hs":7898,"instruction":7899,"inherited":7900,"reverse":7901,"emphasis":7902,"##vic":7903,"employee":7904,"arch":7905,"keeps":7906,"rabbi":7907,"watson":7908,"payment":7909,"uh":7910,"##ala":7911,"nancy":7912,"##tre":7913,"venice":7914,"fastest":7915,"sexy":7916,"banned":7917,"adrian":7918,"properly":7919,"ruth":7920,"touchdown":7921,"dollar":7922,"boards":7923,"metre":7924,"circles":7925,"edges":7926,"favour":7927,"comments":7928,"ok":7929,"travels":7930,"liberation":7931,"scattered":7932,"firmly":7933,"##ular":7934,"holland":7935,"permitted":7936,"diesel":7937,"kenya":7938,"den":7939,"originated":7940,"##ral":7941,"demons":7942,"resumed":7943,"dragged":7944,"rider":7945,"##rus":7946,"servant":7947,"blinked":7948,"extend":7949,"torn":7950,"##ias":7951,"##sey":7952,"input":7953,"meal":7954,"everybody":7955,"cylinder":7956,"kinds":7957,"camps":7958,"##fe":7959,"bullet":7960,"logic":7961,"##wn":7962,"croatian":7963,"evolved":7964,"healthy":7965,"fool":7966,"chocolate":7967,"wise":7968,"preserve":7969,"pradesh":7970,"##ess":7971,"respective":7972,"1850":7973,"##ew":7974,"chicken":7975,"artificial":7976,"gross":7977,"corresponding":7978,"convicted":7979,"cage":7980,"caroline":7981,"dialogue":7982,"##dor":7983,"narrative":7984,"stranger":7985,"mario":7986,"br":7987,"christianity":7988,"failing":7989,"trent":7990,"commanding":7991,"buddhist":7992,"1848":7993,"maurice":7994,"focusing":7995,"yale":7996,"bike":7997,"altitude":7998,"##ering":7999,"mouse":8000,"revised":8001,"##sley":8002,"veteran":8003,"##ig":8004,"pulls":8005,"theology":8006,"crashed":8007,"campaigns":8008,"legion":8009,"##ability":8010,"drag":8011,"excellence":8012,"customer":8013,"cancelled":8014,"intensity":8015,"excuse":8016,"##lar":8017,"liga":8018,"participating":8019,"contributing":8020,"printing":8021,"##burn":8022,"variable":8023,"##rk":8024,"curious":8025,"bin":8026,"legacy":8027,"renaissance":8028,"##my":8029,"symptoms":8030,"binding":8031,"vocalist":8032,"dancer":8033,"##nie":8034,"grammar":8035,"gospel":8036,"democrats":8037,"ya":8038,"enters":8039,"sc":8040,"diplomatic":8041,"hitler":8042,"##ser":8043,"clouds":8044,"mathematical":8045,"quit":8046,"defended":8047,"oriented":8048,"##heim":8049,"fundamental":8050,"hardware":8051,"impressive":8052,"equally":8053,"convince":8054,"confederate":8055,"guilt":8056,"chuck":8057,"sliding":8058,"##ware":8059,"magnetic":8060,"narrowed":8061,"petersburg":8062,"bulgaria":8063,"otto":8064,"phd":8065,"skill":8066,"##ama":8067,"reader":8068,"hopes":8069,"pitcher":8070,"reservoir":8071,"hearts":8072,"automatically":8073,"expecting":8074,"mysterious":8075,"bennett":8076,"extensively":8077,"imagined":8078,"seeds":8079,"monitor":8080,"fix":8081,"##ative":8082,"journalism":8083,"struggling":8084,"signature":8085,"ranch":8086,"encounter":8087,"photographer":8088,"observation":8089,"protests":8090,"##pin":8091,"influences":8092,"##hr":8093,"calendar":8094,"##all":8095,"cruz":8096,"croatia":8097,"locomotive":8098,"hughes":8099,"naturally":8100,"shakespeare":8101,"basement":8102,"hook":8103,"uncredited":8104,"faded":8105,"theories":8106,"approaches":8107,"dare":8108,"phillips":8109,"filling":8110,"fury":8111,"obama":8112,"##ain":8113,"efficient":8114,"arc":8115,"deliver":8116,"min":8117,"raid":8118,"breeding":8119,"inducted":8120,"leagues":8121,"efficiency":8122,"axis":8123,"montana":8124,"eagles":8125,"##ked":8126,"supplied":8127,"instructions":8128,"karen":8129,"picking":8130,"indicating":8131,"trap":8132,"anchor":8133,"practically":8134,"christians":8135,"tomb":8136,"vary":8137,"occasional":8138,"electronics":8139,"lords":8140,"readers":8141,"newcastle":8142,"faint":8143,"innovation":8144,"collect":8145,"situations":8146,"engagement":8147,"160":8148,"claude":8149,"mixture":8150,"##feld":8151,"peer":8152,"tissue":8153,"logo":8154,"lean":8155,"##ration":8156,"°f":8157,"floors":8158,"##ven":8159,"architects":8160,"reducing":8161,"##our":8162,"##ments":8163,"rope":8164,"1859":8165,"ottawa":8166,"##har":8167,"samples":8168,"banking":8169,"declaration":8170,"proteins":8171,"resignation":8172,"francois":8173,"saudi":8174,"advocate":8175,"exhibited":8176,"armor":8177,"twins":8178,"divorce":8179,"##ras":8180,"abraham":8181,"reviewed":8182,"jo":8183,"temporarily":8184,"matrix":8185,"physically":8186,"pulse":8187,"curled":8188,"##ena":8189,"difficulties":8190,"bengal":8191,"usage":8192,"##ban":8193,"annie":8194,"riders":8195,"certificate":8196,"##pi":8197,"holes":8198,"warsaw":8199,"distinctive":8200,"jessica":8201,"##mon":8202,"mutual":8203,"1857":8204,"customs":8205,"circular":8206,"eugene":8207,"removal":8208,"loaded":8209,"mere":8210,"vulnerable":8211,"depicted":8212,"generations":8213,"dame":8214,"heir":8215,"enormous":8216,"lightly":8217,"climbing":8218,"pitched":8219,"lessons":8220,"pilots":8221,"nepal":8222,"ram":8223,"google":8224,"preparing":8225,"brad":8226,"louise":8227,"renowned":8228,"##₂":8229,"liam":8230,"##ably":8231,"plaza":8232,"shaw":8233,"sophie":8234,"brilliant":8235,"bills":8236,"##bar":8237,"##nik":8238,"fucking":8239,"mainland":8240,"server":8241,"pleasant":8242,"seized":8243,"veterans":8244,"jerked":8245,"fail":8246,"beta":8247,"brush":8248,"radiation":8249,"stored":8250,"warmth":8251,"southeastern":8252,"nate":8253,"sin":8254,"raced":8255,"berkeley":8256,"joke":8257,"athlete":8258,"designation":8259,"trunk":8260,"##low":8261,"roland":8262,"qualification":8263,"archives":8264,"heels":8265,"artwork":8266,"receives":8267,"judicial":8268,"reserves":8269,"##bed":8270,"woke":8271,"installation":8272,"abu":8273,"floating":8274,"fake":8275,"lesser":8276,"excitement":8277,"interface":8278,"concentrated":8279,"addressed":8280,"characteristic":8281,"amanda":8282,"saxophone":8283,"monk":8284,"auto":8285,"##bus":8286,"releasing":8287,"egg":8288,"dies":8289,"interaction":8290,"defender":8291,"ce":8292,"outbreak":8293,"glory":8294,"loving":8295,"##bert":8296,"sequel":8297,"consciousness":8298,"http":8299,"awake":8300,"ski":8301,"enrolled":8302,"##ress":8303,"handling":8304,"rookie":8305,"brow":8306,"somebody":8307,"biography":8308,"warfare":8309,"amounts":8310,"contracts":8311,"presentation":8312,"fabric":8313,"dissolved":8314,"challenged":8315,"meter":8316,"psychological":8317,"lt":8318,"elevated":8319,"rally":8320,"accurate":8321,"##tha":8322,"hospitals":8323,"undergraduate":8324,"specialist":8325,"venezuela":8326,"exhibit":8327,"shed":8328,"nursing":8329,"protestant":8330,"fluid":8331,"structural":8332,"footage":8333,"jared":8334,"consistent":8335,"prey":8336,"##ska":8337,"succession":8338,"reflect":8339,"exile":8340,"lebanon":8341,"wiped":8342,"suspect":8343,"shanghai":8344,"resting":8345,"integration":8346,"preservation":8347,"marvel":8348,"variant":8349,"pirates":8350,"sheep":8351,"rounded":8352,"capita":8353,"sailing":8354,"colonies":8355,"manuscript":8356,"deemed":8357,"variations":8358,"clarke":8359,"functional":8360,"emerging":8361,"boxing":8362,"relaxed":8363,"curse":8364,"azerbaijan":8365,"heavyweight":8366,"nickname":8367,"editorial":8368,"rang":8369,"grid":8370,"tightened":8371,"earthquake":8372,"flashed":8373,"miguel":8374,"rushing":8375,"##ches":8376,"improvements":8377,"boxes":8378,"brooks":8379,"180":8380,"consumption":8381,"molecular":8382,"felix":8383,"societies":8384,"repeatedly":8385,"variation":8386,"aids":8387,"civic":8388,"graphics":8389,"professionals":8390,"realm":8391,"autonomous":8392,"receiver":8393,"delayed":8394,"workshop":8395,"militia":8396,"chairs":8397,"trump":8398,"canyon":8399,"##point":8400,"harsh":8401,"extending":8402,"lovely":8403,"happiness":8404,"##jan":8405,"stake":8406,"eyebrows":8407,"embassy":8408,"wellington":8409,"hannah":8410,"##ella":8411,"sony":8412,"corners":8413,"bishops":8414,"swear":8415,"cloth":8416,"contents":8417,"xi":8418,"namely":8419,"commenced":8420,"1854":8421,"stanford":8422,"nashville":8423,"courage":8424,"graphic":8425,"commitment":8426,"garrison":8427,"##bin":8428,"hamlet":8429,"clearing":8430,"rebels":8431,"attraction":8432,"literacy":8433,"cooking":8434,"ruins":8435,"temples":8436,"jenny":8437,"humanity":8438,"celebrate":8439,"hasn":8440,"freight":8441,"sixty":8442,"rebel":8443,"bastard":8444,"##art":8445,"newton":8446,"##ada":8447,"deer":8448,"##ges":8449,"##ching":8450,"smiles":8451,"delaware":8452,"singers":8453,"##ets":8454,"approaching":8455,"assists":8456,"flame":8457,"##ph":8458,"boulevard":8459,"barrel":8460,"planted":8461,"##ome":8462,"pursuit":8463,"##sia":8464,"consequences":8465,"posts":8466,"shallow":8467,"invitation":8468,"rode":8469,"depot":8470,"ernest":8471,"kane":8472,"rod":8473,"concepts":8474,"preston":8475,"topic":8476,"chambers":8477,"striking":8478,"blast":8479,"arrives":8480,"descendants":8481,"montgomery":8482,"ranges":8483,"worlds":8484,"##lay":8485,"##ari":8486,"span":8487,"chaos":8488,"praise":8489,"##ag":8490,"fewer":8491,"1855":8492,"sanctuary":8493,"mud":8494,"fbi":8495,"##ions":8496,"programmes":8497,"maintaining":8498,"unity":8499,"harper":8500,"bore":8501,"handsome":8502,"closure":8503,"tournaments":8504,"thunder":8505,"nebraska":8506,"linda":8507,"facade":8508,"puts":8509,"satisfied":8510,"argentine":8511,"dale":8512,"cork":8513,"dome":8514,"panama":8515,"##yl":8516,"1858":8517,"tasks":8518,"experts":8519,"##ates":8520,"feeding":8521,"equation":8522,"##las":8523,"##ida":8524,"##tu":8525,"engage":8526,"bryan":8527,"##ax":8528,"um":8529,"quartet":8530,"melody":8531,"disbanded":8532,"sheffield":8533,"blocked":8534,"gasped":8535,"delay":8536,"kisses":8537,"maggie":8538,"connects":8539,"##non":8540,"sts":8541,"poured":8542,"creator":8543,"publishers":8544,"##we":8545,"guided":8546,"ellis":8547,"extinct":8548,"hug":8549,"gaining":8550,"##ord":8551,"complicated":8552,"##bility":8553,"poll":8554,"clenched":8555,"investigate":8556,"##use":8557,"thereby":8558,"quantum":8559,"spine":8560,"cdp":8561,"humor":8562,"kills":8563,"administered":8564,"semifinals":8565,"##du":8566,"encountered":8567,"ignore":8568,"##bu":8569,"commentary":8570,"##maker":8571,"bother":8572,"roosevelt":8573,"140":8574,"plains":8575,"halfway":8576,"flowing":85
gitextract____cmvti/
├── .dockerignore
├── .gitattributes
├── .github/
│ ├── CODEOWNERS
│ ├── ISSUE_TEMPLATE/
│ │ ├── bug_report.yml
│ │ ├── config.yml
│ │ └── feature_request.yml
│ ├── dependabot.yml
│ └── workflows/
│ └── build_container.yml
├── .gitignore
├── Dockerfile
├── LICENSE
├── args_manager.py
├── auth-example.json
├── build_launcher.py
├── css/
│ └── style.css
├── development.md
├── docker-compose.yml
├── docker.md
├── entry_with_update.py
├── entrypoint.sh
├── environment.yaml
├── experiments_expansion.py
├── experiments_face.py
├── experiments_interrogate.py
├── experiments_mask_generation.py
├── extras/
│ ├── BLIP/
│ │ ├── configs/
│ │ │ ├── bert_config.json
│ │ │ ├── caption_coco.yaml
│ │ │ ├── med_config.json
│ │ │ ├── nlvr.yaml
│ │ │ ├── nocaps.yaml
│ │ │ ├── pretrain.yaml
│ │ │ ├── retrieval_coco.yaml
│ │ │ ├── retrieval_flickr.yaml
│ │ │ ├── retrieval_msrvtt.yaml
│ │ │ └── vqa.yaml
│ │ └── models/
│ │ ├── bert_tokenizer/
│ │ │ ├── config.json
│ │ │ ├── tokenizer.json
│ │ │ ├── tokenizer_config.json
│ │ │ └── vocab.txt
│ │ ├── blip.py
│ │ ├── blip_itm.py
│ │ ├── blip_nlvr.py
│ │ ├── blip_pretrain.py
│ │ ├── blip_retrieval.py
│ │ ├── blip_vqa.py
│ │ ├── med.py
│ │ ├── nlvr_encoder.py
│ │ └── vit.py
│ ├── GroundingDINO/
│ │ ├── config/
│ │ │ └── GroundingDINO_SwinT_OGC.py
│ │ └── util/
│ │ └── inference.py
│ ├── censor.py
│ ├── expansion.py
│ ├── face_crop.py
│ ├── facexlib/
│ │ ├── detection/
│ │ │ ├── __init__.py
│ │ │ ├── align_trans.py
│ │ │ ├── matlab_cp2tform.py
│ │ │ ├── retinaface.py
│ │ │ ├── retinaface_net.py
│ │ │ └── retinaface_utils.py
│ │ ├── parsing/
│ │ │ ├── __init__.py
│ │ │ ├── bisenet.py
│ │ │ ├── parsenet.py
│ │ │ └── resnet.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── face_restoration_helper.py
│ │ ├── face_utils.py
│ │ └── misc.py
│ ├── inpaint_mask.py
│ ├── interrogate.py
│ ├── ip_adapter.py
│ ├── preprocessors.py
│ ├── resampler.py
│ ├── safety_checker/
│ │ ├── configs/
│ │ │ ├── config.json
│ │ │ └── preprocessor_config.json
│ │ └── models/
│ │ └── safety_checker.py
│ ├── sam/
│ │ └── predictor.py
│ ├── vae_interpose.py
│ └── wd14tagger.py
├── fooocus_colab.ipynb
├── fooocus_version.py
├── javascript/
│ ├── contextMenus.js
│ ├── edit-attention.js
│ ├── imageviewer.js
│ ├── localization.js
│ ├── script.js
│ ├── viewer.js
│ └── zoom.js
├── language/
│ ├── en.json
│ └── example.json
├── launch.py
├── ldm_patched/
│ ├── contrib/
│ │ ├── external.py
│ │ ├── external_align_your_steps.py
│ │ ├── external_canny.py
│ │ ├── external_clip_sdxl.py
│ │ ├── external_compositing.py
│ │ ├── external_custom_sampler.py
│ │ ├── external_freelunch.py
│ │ ├── external_hypernetwork.py
│ │ ├── external_hypertile.py
│ │ ├── external_images.py
│ │ ├── external_latent.py
│ │ ├── external_mask.py
│ │ ├── external_model_advanced.py
│ │ ├── external_model_downscale.py
│ │ ├── external_model_merging.py
│ │ ├── external_perpneg.py
│ │ ├── external_photomaker.py
│ │ ├── external_post_processing.py
│ │ ├── external_rebatch.py
│ │ ├── external_sag.py
│ │ ├── external_sdupscale.py
│ │ ├── external_stable3d.py
│ │ ├── external_tomesd.py
│ │ ├── external_upscale_model.py
│ │ └── external_video_model.py
│ ├── controlnet/
│ │ └── cldm.py
│ ├── k_diffusion/
│ │ ├── sampling.py
│ │ └── utils.py
│ ├── ldm/
│ │ ├── models/
│ │ │ └── autoencoder.py
│ │ ├── modules/
│ │ │ ├── attention.py
│ │ │ ├── diffusionmodules/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── model.py
│ │ │ │ ├── openaimodel.py
│ │ │ │ ├── upscaling.py
│ │ │ │ └── util.py
│ │ │ ├── distributions/
│ │ │ │ ├── __init__.py
│ │ │ │ └── distributions.py
│ │ │ ├── ema.py
│ │ │ ├── encoders/
│ │ │ │ ├── __init__.py
│ │ │ │ └── noise_aug_modules.py
│ │ │ ├── sub_quadratic_attention.py
│ │ │ └── temporal_ae.py
│ │ └── util.py
│ ├── licenses-3rd/
│ │ ├── chainer
│ │ ├── comfyui
│ │ ├── diffusers
│ │ ├── kdiffusion
│ │ ├── ldm
│ │ ├── taesd
│ │ └── transformers
│ ├── modules/
│ │ ├── args_parser.py
│ │ ├── checkpoint_pickle.py
│ │ ├── clip_config_bigg.json
│ │ ├── clip_model.py
│ │ ├── clip_vision.py
│ │ ├── clip_vision_config_g.json
│ │ ├── clip_vision_config_h.json
│ │ ├── clip_vision_config_vitl.json
│ │ ├── conds.py
│ │ ├── controlnet.py
│ │ ├── diffusers_convert.py
│ │ ├── diffusers_load.py
│ │ ├── gligen.py
│ │ ├── latent_formats.py
│ │ ├── lora.py
│ │ ├── model_base.py
│ │ ├── model_detection.py
│ │ ├── model_management.py
│ │ ├── model_patcher.py
│ │ ├── model_sampling.py
│ │ ├── ops.py
│ │ ├── options.py
│ │ ├── sample.py
│ │ ├── samplers.py
│ │ ├── sd.py
│ │ ├── sd1_clip.py
│ │ ├── sd1_clip_config.json
│ │ ├── sd1_tokenizer/
│ │ │ ├── merges.txt
│ │ │ ├── special_tokens_map.json
│ │ │ ├── tokenizer_config.json
│ │ │ └── vocab.json
│ │ ├── sd2_clip.py
│ │ ├── sd2_clip_config.json
│ │ ├── sdxl_clip.py
│ │ ├── supported_models.py
│ │ ├── supported_models_base.py
│ │ └── utils.py
│ ├── pfn/
│ │ ├── __init__.py
│ │ ├── architecture/
│ │ │ ├── DAT.py
│ │ │ ├── HAT.py
│ │ │ ├── LICENSE-DAT
│ │ │ ├── LICENSE-ESRGAN
│ │ │ ├── LICENSE-HAT
│ │ │ ├── LICENSE-RealESRGAN
│ │ │ ├── LICENSE-SCUNet
│ │ │ ├── LICENSE-SPSR
│ │ │ ├── LICENSE-SwiftSRGAN
│ │ │ ├── LICENSE-Swin2SR
│ │ │ ├── LICENSE-SwinIR
│ │ │ ├── LICENSE-lama
│ │ │ ├── LaMa.py
│ │ │ ├── OmniSR/
│ │ │ │ ├── ChannelAttention.py
│ │ │ │ ├── LICENSE
│ │ │ │ ├── OSA.py
│ │ │ │ ├── OSAG.py
│ │ │ │ ├── OmniSR.py
│ │ │ │ ├── esa.py
│ │ │ │ ├── layernorm.py
│ │ │ │ └── pixelshuffle.py
│ │ │ ├── RRDB.py
│ │ │ ├── SCUNet.py
│ │ │ ├── SPSR.py
│ │ │ ├── SRVGG.py
│ │ │ ├── SwiftSRGAN.py
│ │ │ ├── Swin2SR.py
│ │ │ ├── SwinIR.py
│ │ │ ├── __init__.py
│ │ │ ├── block.py
│ │ │ ├── face/
│ │ │ │ ├── LICENSE-GFPGAN
│ │ │ │ ├── LICENSE-RestoreFormer
│ │ │ │ ├── LICENSE-codeformer
│ │ │ │ ├── arcface_arch.py
│ │ │ │ ├── codeformer.py
│ │ │ │ ├── fused_act.py
│ │ │ │ ├── gfpgan_bilinear_arch.py
│ │ │ │ ├── gfpganv1_arch.py
│ │ │ │ ├── gfpganv1_clean_arch.py
│ │ │ │ ├── restoreformer_arch.py
│ │ │ │ ├── stylegan2_arch.py
│ │ │ │ ├── stylegan2_bilinear_arch.py
│ │ │ │ ├── stylegan2_clean_arch.py
│ │ │ │ └── upfirdn2d.py
│ │ │ └── timm/
│ │ │ ├── LICENSE
│ │ │ ├── drop.py
│ │ │ ├── helpers.py
│ │ │ └── weight_init.py
│ │ ├── model_loading.py
│ │ └── types.py
│ ├── t2ia/
│ │ └── adapter.py
│ ├── taesd/
│ │ └── taesd.py
│ ├── unipc/
│ │ └── uni_pc.py
│ └── utils/
│ ├── latent_visualization.py
│ └── path_utils.py
├── models/
│ ├── checkpoints/
│ │ └── put_checkpoints_here
│ ├── clip/
│ │ └── put_clip_or_text_encoder_models_here
│ ├── clip_vision/
│ │ ├── put_clip_vision_models_here
│ │ └── wd-v1-4-moat-tagger-v2.csv
│ ├── configs/
│ │ ├── anything_v3.yaml
│ │ ├── v1-inference.yaml
│ │ ├── v1-inference_clip_skip_2.yaml
│ │ ├── v1-inference_clip_skip_2_fp16.yaml
│ │ ├── v1-inference_fp16.yaml
│ │ ├── v1-inpainting-inference.yaml
│ │ ├── v2-inference-v.yaml
│ │ ├── v2-inference-v_fp32.yaml
│ │ ├── v2-inference.yaml
│ │ ├── v2-inference_fp32.yaml
│ │ └── v2-inpainting-inference.yaml
│ ├── controlnet/
│ │ └── put_controlnets_and_t2i_here
│ ├── diffusers/
│ │ └── put_diffusers_models_here
│ ├── embeddings/
│ │ └── put_embeddings_or_textual_inversion_concepts_here
│ ├── gligen/
│ │ └── put_gligen_models_here
│ ├── hypernetworks/
│ │ └── put_hypernetworks_here
│ ├── inpaint/
│ │ └── put_inpaint_here
│ ├── loras/
│ │ └── put_loras_here
│ ├── prompt_expansion/
│ │ ├── fooocus_expansion/
│ │ │ ├── config.json
│ │ │ ├── merges.txt
│ │ │ ├── positive.txt
│ │ │ ├── special_tokens_map.json
│ │ │ ├── tokenizer.json
│ │ │ ├── tokenizer_config.json
│ │ │ └── vocab.json
│ │ └── put_prompt_expansion_here
│ ├── safety_checker/
│ │ └── put_safety_checker_models_here
│ ├── style_models/
│ │ └── put_t2i_style_model_here
│ ├── unet/
│ │ └── put_unet_files_here
│ ├── upscale_models/
│ │ └── put_esrgan_and_other_upscale_models_here
│ ├── vae/
│ │ └── put_vae_here
│ └── vae_approx/
│ └── put_taesd_encoder_pth_and_taesd_decoder_pth_here
├── modules/
│ ├── __init__.py
│ ├── anisotropic.py
│ ├── async_worker.py
│ ├── auth.py
│ ├── config.py
│ ├── constants.py
│ ├── core.py
│ ├── default_pipeline.py
│ ├── extra_utils.py
│ ├── flags.py
│ ├── gradio_hijack.py
│ ├── hash_cache.py
│ ├── html.py
│ ├── inpaint_worker.py
│ ├── launch_util.py
│ ├── localization.py
│ ├── lora.py
│ ├── meta_parser.py
│ ├── model_loader.py
│ ├── ops.py
│ ├── patch.py
│ ├── patch_clip.py
│ ├── patch_precision.py
│ ├── private_logger.py
│ ├── sample_hijack.py
│ ├── sdxl_styles.py
│ ├── style_sorter.py
│ ├── ui_gradio_extensions.py
│ ├── upscaler.py
│ └── util.py
├── presets/
│ ├── .gitignore
│ ├── anime.json
│ ├── default.json
│ ├── lcm.json
│ ├── playground_v2.5.json
│ ├── pony_v6.json
│ ├── realistic.json
│ └── sai.json
├── readme.md
├── requirements_docker.txt
├── requirements_versions.txt
├── sdxl_styles/
│ ├── sdxl_styles_diva.json
│ ├── sdxl_styles_fooocus.json
│ ├── sdxl_styles_marc_k3nt3l.json
│ ├── sdxl_styles_mre.json
│ ├── sdxl_styles_sai.json
│ └── sdxl_styles_twri.json
├── shared.py
├── tests/
│ ├── __init__.py
│ ├── test_extra_utils.py
│ └── test_utils.py
├── troubleshoot.md
├── update_log.md
├── webui.py
└── wildcards/
├── .gitignore
├── animal.txt
├── artist.txt
├── color.txt
├── color_flower.txt
├── extended-color.txt
├── flower.txt
└── nationality.txt
Showing preview only (219K chars total). Download the full file or copy to clipboard to get everything.
SYMBOL INDEX (2905 symbols across 181 files)
FILE: build_launcher.py
function build_launcher (line 14) | def build_launcher():
FILE: extras/BLIP/models/blip.py
class BLIP_Base (line 23) | class BLIP_Base(nn.Module):
method __init__ (line 24) | def __init__(self,
method forward (line 46) | def forward(self, image, caption, mode):
class BLIP_Decoder (line 78) | class BLIP_Decoder(nn.Module):
method __init__ (line 79) | def __init__(self,
method forward (line 105) | def forward(self, image, caption):
method generate (line 128) | def generate(self, image, sample=False, num_beams=3, max_length=30, mi...
function blip_decoder (line 172) | def blip_decoder(pretrained='',**kwargs):
function blip_feature_extractor (line 179) | def blip_feature_extractor(pretrained='',**kwargs):
function init_tokenizer (line 186) | def init_tokenizer():
function create_vit (line 195) | def create_vit(vit, image_size, use_grad_checkpointing=False, ckpt_layer...
function is_url (line 212) | def is_url(url_or_filename):
function load_checkpoint (line 216) | def load_checkpoint(model,url_or_filename):
FILE: extras/BLIP/models/blip_itm.py
class BLIP_ITM (line 10) | class BLIP_ITM(nn.Module):
method __init__ (line 11) | def __init__(self,
method forward (line 41) | def forward(self, image, caption, match_head='itm'):
function blip_itm (line 70) | def blip_itm(pretrained='',**kwargs):
FILE: extras/BLIP/models/blip_nlvr.py
class BLIP_NLVR (line 16) | class BLIP_NLVR(nn.Module):
method __init__ (line 17) | def __init__(self,
method forward (line 44) | def forward(self, image, text, targets, train=True):
function blip_nlvr (line 69) | def blip_nlvr(pretrained='',**kwargs):
function load_checkpoint (line 78) | def load_checkpoint(model,url_or_filename):
FILE: extras/BLIP/models/blip_pretrain.py
class BLIP_Pretrain (line 19) | class BLIP_Pretrain(nn.Module):
method __init__ (line 20) | def __init__(self,
method forward (line 97) | def forward(self, image, caption, alpha):
method copy_params (line 217) | def copy_params(self):
method _momentum_update (line 225) | def _momentum_update(self):
method _dequeue_and_enqueue (line 232) | def _dequeue_and_enqueue(self, image_feat, text_feat):
function blip_pretrain (line 250) | def blip_pretrain(**kwargs):
function concat_all_gather (line 256) | def concat_all_gather(tensor):
function tie_encoder_decoder_weights (line 270) | def tie_encoder_decoder_weights(encoder: nn.Module, decoder: nn.Module, ...
FILE: extras/BLIP/models/blip_retrieval.py
class BLIP_Retrieval (line 10) | class BLIP_Retrieval(nn.Module):
method __init__ (line 11) | def __init__(self,
method forward (line 72) | def forward(self, image, caption, alpha, idx):
method copy_params (line 229) | def copy_params(self):
method _momentum_update (line 237) | def _momentum_update(self):
method _dequeue_and_enqueue (line 244) | def _dequeue_and_enqueue(self, image_feat, text_feat, idxs):
function blip_retrieval (line 264) | def blip_retrieval(pretrained='',**kwargs):
function concat_all_gather (line 274) | def concat_all_gather(tensor):
class GatherLayer (line 287) | class GatherLayer(torch.autograd.Function):
method forward (line 294) | def forward(ctx, x):
method backward (line 300) | def backward(ctx, *grads):
function all_gather_with_grad (line 306) | def all_gather_with_grad(tensors):
FILE: extras/BLIP/models/blip_vqa.py
class BLIP_VQA (line 10) | class BLIP_VQA(nn.Module):
method __init__ (line 11) | def __init__(self,
method forward (line 37) | def forward(self, image, question, answer=None, n=None, weights=None, ...
method rank_answer (line 120) | def rank_answer(self, question_states, question_atts, answer_ids, answ...
function blip_vqa (line 170) | def blip_vqa(pretrained='',**kwargs):
function tile (line 178) | def tile(x, dim, n_tile):
FILE: extras/BLIP/models/med.py
class BertEmbeddings (line 52) | class BertEmbeddings(nn.Module):
method __init__ (line 55) | def __init__(self, config):
method forward (line 71) | def forward(
class BertSelfAttention (line 97) | class BertSelfAttention(nn.Module):
method __init__ (line 98) | def __init__(self, config, is_cross_attention):
method save_attn_gradients (line 126) | def save_attn_gradients(self, attn_gradients):
method get_attn_gradients (line 129) | def get_attn_gradients(self):
method save_attention_map (line 132) | def save_attention_map(self, attention_map):
method get_attention_map (line 135) | def get_attention_map(self):
method transpose_for_scores (line 138) | def transpose_for_scores(self, x):
method forward (line 143) | def forward(
class BertSelfOutput (line 228) | class BertSelfOutput(nn.Module):
method __init__ (line 229) | def __init__(self, config):
method forward (line 235) | def forward(self, hidden_states, input_tensor):
class BertAttention (line 242) | class BertAttention(nn.Module):
method __init__ (line 243) | def __init__(self, config, is_cross_attention=False):
method prune_heads (line 249) | def prune_heads(self, heads):
method forward (line 267) | def forward(
class BertIntermediate (line 291) | class BertIntermediate(nn.Module):
method __init__ (line 292) | def __init__(self, config):
method forward (line 300) | def forward(self, hidden_states):
class BertOutput (line 306) | class BertOutput(nn.Module):
method __init__ (line 307) | def __init__(self, config):
method forward (line 313) | def forward(self, hidden_states, input_tensor):
class BertLayer (line 320) | class BertLayer(nn.Module):
method __init__ (line 321) | def __init__(self, config, layer_num):
method forward (line 333) | def forward(
method feed_forward_chunk (line 380) | def feed_forward_chunk(self, attention_output):
class BertEncoder (line 386) | class BertEncoder(nn.Module):
method __init__ (line 387) | def __init__(self, config):
method forward (line 393) | def forward(
class BertPooler (line 486) | class BertPooler(nn.Module):
method __init__ (line 487) | def __init__(self, config):
method forward (line 492) | def forward(self, hidden_states):
class BertPredictionHeadTransform (line 501) | class BertPredictionHeadTransform(nn.Module):
method __init__ (line 502) | def __init__(self, config):
method forward (line 511) | def forward(self, hidden_states):
class BertLMPredictionHead (line 518) | class BertLMPredictionHead(nn.Module):
method __init__ (line 519) | def __init__(self, config):
method forward (line 532) | def forward(self, hidden_states):
class BertOnlyMLMHead (line 538) | class BertOnlyMLMHead(nn.Module):
method __init__ (line 539) | def __init__(self, config):
method forward (line 543) | def forward(self, sequence_output):
class BertPreTrainedModel (line 548) | class BertPreTrainedModel(PreTrainedModel):
method _init_weights (line 558) | def _init_weights(self, module):
class BertModel (line 571) | class BertModel(BertPreTrainedModel):
method __init__ (line 581) | def __init__(self, config, add_pooling_layer=True):
method get_input_embeddings (line 594) | def get_input_embeddings(self):
method set_input_embeddings (line 597) | def set_input_embeddings(self, value):
method _prune_heads (line 600) | def _prune_heads(self, heads_to_prune):
method get_extended_attention_mask (line 609) | def get_extended_attention_mask(self, attention_mask: Tensor, input_sh...
method forward (line 670) | def forward(
class BertLMHeadModel (line 811) | class BertLMHeadModel(BertPreTrainedModel):
method __init__ (line 816) | def __init__(self, config):
method get_output_embeddings (line 824) | def get_output_embeddings(self):
method set_output_embeddings (line 827) | def set_output_embeddings(self, new_embeddings):
method forward (line 830) | def forward(
method prepare_inputs_for_generation (line 932) | def prepare_inputs_for_generation(self, input_ids, past=None, attentio...
method _reorder_cache (line 951) | def _reorder_cache(self, past, beam_idx):
FILE: extras/BLIP/models/nlvr_encoder.py
class BertEmbeddings (line 42) | class BertEmbeddings(nn.Module):
method __init__ (line 45) | def __init__(self, config):
method forward (line 61) | def forward(
class BertSelfAttention (line 87) | class BertSelfAttention(nn.Module):
method __init__ (line 88) | def __init__(self, config, is_cross_attention):
method save_attn_gradients (line 116) | def save_attn_gradients(self, attn_gradients):
method get_attn_gradients (line 119) | def get_attn_gradients(self):
method save_attention_map (line 122) | def save_attention_map(self, attention_map):
method get_attention_map (line 125) | def get_attention_map(self):
method transpose_for_scores (line 128) | def transpose_for_scores(self, x):
method forward (line 133) | def forward(
class BertSelfOutput (line 218) | class BertSelfOutput(nn.Module):
method __init__ (line 219) | def __init__(self, config, twin=False, merge=False):
method forward (line 235) | def forward(self, hidden_states, input_tensor):
class BertAttention (line 251) | class BertAttention(nn.Module):
method __init__ (line 252) | def __init__(self, config, is_cross_attention=False, layer_num=-1):
method prune_heads (line 262) | def prune_heads(self, heads):
method forward (line 280) | def forward(
class BertIntermediate (line 327) | class BertIntermediate(nn.Module):
method __init__ (line 328) | def __init__(self, config):
method forward (line 336) | def forward(self, hidden_states):
class BertOutput (line 342) | class BertOutput(nn.Module):
method __init__ (line 343) | def __init__(self, config):
method forward (line 349) | def forward(self, hidden_states, input_tensor):
class BertLayer (line 356) | class BertLayer(nn.Module):
method __init__ (line 357) | def __init__(self, config, layer_num):
method forward (line 369) | def forward(
method feed_forward_chunk (line 415) | def feed_forward_chunk(self, attention_output):
class BertEncoder (line 421) | class BertEncoder(nn.Module):
method __init__ (line 422) | def __init__(self, config):
method forward (line 428) | def forward(
class BertPooler (line 521) | class BertPooler(nn.Module):
method __init__ (line 522) | def __init__(self, config):
method forward (line 527) | def forward(self, hidden_states):
class BertPredictionHeadTransform (line 536) | class BertPredictionHeadTransform(nn.Module):
method __init__ (line 537) | def __init__(self, config):
method forward (line 546) | def forward(self, hidden_states):
class BertLMPredictionHead (line 553) | class BertLMPredictionHead(nn.Module):
method __init__ (line 554) | def __init__(self, config):
method forward (line 567) | def forward(self, hidden_states):
class BertOnlyMLMHead (line 573) | class BertOnlyMLMHead(nn.Module):
method __init__ (line 574) | def __init__(self, config):
method forward (line 578) | def forward(self, sequence_output):
class BertPreTrainedModel (line 583) | class BertPreTrainedModel(PreTrainedModel):
method _init_weights (line 593) | def _init_weights(self, module):
class BertModel (line 606) | class BertModel(BertPreTrainedModel):
method __init__ (line 616) | def __init__(self, config, add_pooling_layer=True):
method get_input_embeddings (line 629) | def get_input_embeddings(self):
method set_input_embeddings (line 632) | def set_input_embeddings(self, value):
method _prune_heads (line 635) | def _prune_heads(self, heads_to_prune):
method get_extended_attention_mask (line 644) | def get_extended_attention_mask(self, attention_mask: Tensor, input_sh...
method forward (line 705) | def forward(
FILE: extras/BLIP/models/vit.py
function checkpoint_wrapper (line 22) | def checkpoint_wrapper(x):
class Mlp (line 26) | class Mlp(nn.Module):
method __init__ (line 29) | def __init__(self, in_features, hidden_features=None, out_features=Non...
method forward (line 38) | def forward(self, x):
class Attention (line 47) | class Attention(nn.Module):
method __init__ (line 48) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
method save_attn_gradients (line 61) | def save_attn_gradients(self, attn_gradients):
method get_attn_gradients (line 64) | def get_attn_gradients(self):
method save_attention_map (line 67) | def save_attention_map(self, attention_map):
method get_attention_map (line 70) | def get_attention_map(self):
method forward (line 73) | def forward(self, x, register_hook=False):
class Block (line 92) | class Block(nn.Module):
method __init__ (line 94) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
method forward (line 110) | def forward(self, x, register_hook=False):
class VisionTransformer (line 116) | class VisionTransformer(nn.Module):
method __init__ (line 121) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
method _init_weights (line 170) | def _init_weights(self, m):
method no_weight_decay (line 180) | def no_weight_decay(self):
method forward (line 183) | def forward(self, x, register_blk=-1):
method load_pretrained (line 200) | def load_pretrained(self, checkpoint_path, prefix=''):
function _load_weights (line 205) | def _load_weights(model: VisionTransformer, checkpoint_path: str, prefix...
function interpolate_pos_embed (line 284) | def interpolate_pos_embed(pos_embed_checkpoint, visual_encoder):
FILE: extras/GroundingDINO/util/inference.py
class GroundingDinoModel (line 15) | class GroundingDinoModel(Model):
method __init__ (line 16) | def __init__(self):
method predict_with_caption (line 24) | def predict_with_caption(
function predict (line 64) | def predict(
FILE: extras/censor.py
class Censor (line 17) | class Censor:
method __init__ (line 18) | def __init__(self):
method init (line 24) | def init(self):
method censor (line 39) | def censor(self, images: list | np.ndarray) -> list | np.ndarray:
FILE: extras/expansion.py
function safe_str (line 24) | def safe_str(x):
function remove_pattern (line 31) | def remove_pattern(x, pattern):
class FooocusExpansion (line 37) | class FooocusExpansion:
method __init__ (line 38) | def __init__(self):
method logits_processor (line 83) | def logits_processor(self, input_ids, scores):
method __call__ (line 95) | def __call__(self, prompt, seed):
FILE: extras/face_crop.py
function align_warp_face (line 9) | def align_warp_face(self, landmark, border_mode='constant'):
function crop_image (line 24) | def crop_image(img_rgb):
FILE: extras/facexlib/detection/__init__.py
function init_detection_model (line 8) | def init_detection_model(model_name, half=False, device='cuda', model_ro...
FILE: extras/facexlib/detection/align_trans.py
class FaceWarpException (line 13) | class FaceWarpException(Exception):
method __str__ (line 15) | def __str__(self):
function get_reference_facial_points (line 19) | def get_reference_facial_points(output_size=None, inner_padding_factor=0...
function get_affine_transform_matrix (line 112) | def get_affine_transform_matrix(src_pts, dst_pts):
function warp_and_crop_face (line 145) | def warp_and_crop_face(src_img, facial_pts, reference_pts=None, crop_siz...
FILE: extras/facexlib/detection/matlab_cp2tform.py
class MatlabCp2tormException (line 7) | class MatlabCp2tormException(Exception):
method __str__ (line 9) | def __str__(self):
function tformfwd (line 13) | def tformfwd(trans, uv):
function tforminv (line 37) | def tforminv(trans, uv):
function findNonreflectiveSimilarity (line 60) | def findNonreflectiveSimilarity(uv, xy, options=None):
function findSimilarity (line 94) | def findSimilarity(uv, xy, options=None):
function get_similarity_transform (line 130) | def get_similarity_transform(src_pts, dst_pts, reflective=True):
function cvt_tform_mat_for_cv2 (line 170) | def cvt_tform_mat_for_cv2(trans):
function get_similarity_transform_for_cv2 (line 198) | def get_similarity_transform_for_cv2(src_pts, dst_pts, reflective=True):
FILE: extras/facexlib/detection/retinaface.py
function generate_config (line 15) | def generate_config(network_name):
class RetinaFace (line 71) | class RetinaFace(nn.Module):
method __init__ (line 73) | def __init__(self, network_name='resnet50', half=False, phase='test', ...
method forward (line 120) | def forward(self, inputs):
method __detect_faces (line 145) | def __detect_faces(self, inputs):
method transform (line 165) | def transform(self, image, use_origin_size):
method detect_faces (line 192) | def detect_faces(
method __align_multi (line 235) | def __align_multi(self, image, boxes, landmarks, limit=None):
method align_multi (line 253) | def align_multi(self, img, conf_threshold=0.8, limit=None):
method batched_transform (line 261) | def batched_transform(self, frames, use_origin_size):
method batched_detect_faces (line 304) | def batched_detect_faces(self, frames, conf_threshold=0.8, nms_thresho...
FILE: extras/facexlib/detection/retinaface_net.py
function conv_bn (line 6) | def conv_bn(inp, oup, stride=1, leaky=0):
function conv_bn_no_relu (line 12) | def conv_bn_no_relu(inp, oup, stride):
function conv_bn1X1 (line 19) | def conv_bn1X1(inp, oup, stride, leaky=0):
function conv_dw (line 25) | def conv_dw(inp, oup, stride, leaky=0.1):
class SSH (line 36) | class SSH(nn.Module):
method __init__ (line 38) | def __init__(self, in_channel, out_channel):
method forward (line 52) | def forward(self, input):
class FPN (line 66) | class FPN(nn.Module):
method __init__ (line 68) | def __init__(self, in_channels_list, out_channels):
method forward (line 80) | def forward(self, input):
class MobileNetV1 (line 100) | class MobileNetV1(nn.Module):
method __init__ (line 102) | def __init__(self):
method forward (line 127) | def forward(self, x):
class ClassHead (line 138) | class ClassHead(nn.Module):
method __init__ (line 140) | def __init__(self, inchannels=512, num_anchors=3):
method forward (line 145) | def forward(self, x):
class BboxHead (line 152) | class BboxHead(nn.Module):
method __init__ (line 154) | def __init__(self, inchannels=512, num_anchors=3):
method forward (line 158) | def forward(self, x):
class LandmarkHead (line 165) | class LandmarkHead(nn.Module):
method __init__ (line 167) | def __init__(self, inchannels=512, num_anchors=3):
method forward (line 171) | def forward(self, x):
function make_class_head (line 178) | def make_class_head(fpn_num=3, inchannels=64, anchor_num=2):
function make_bbox_head (line 185) | def make_bbox_head(fpn_num=3, inchannels=64, anchor_num=2):
function make_landmark_head (line 192) | def make_landmark_head(fpn_num=3, inchannels=64, anchor_num=2):
FILE: extras/facexlib/detection/retinaface_utils.py
class PriorBox (line 8) | class PriorBox(object):
method __init__ (line 10) | def __init__(self, cfg, image_size=None, phase='train'):
method forward (line 19) | def forward(self):
function py_cpu_nms (line 39) | def py_cpu_nms(dets, thresh):
function point_form (line 50) | def point_form(boxes):
function center_size (line 65) | def center_size(boxes):
function intersect (line 79) | def intersect(box_a, box_b):
function jaccard (line 98) | def jaccard(box_a, box_b):
function matrix_iou (line 117) | def matrix_iou(a, b):
function matrix_iof (line 130) | def matrix_iof(a, b):
function match (line 142) | def match(threshold, truths, priors, variances, labels, landms, loc_t, c...
function encode (line 200) | def encode(matched, priors, variances):
function encode_landm (line 224) | def encode_landm(matched, priors, variances):
function decode (line 254) | def decode(loc, priors, variances):
function decode_landm (line 274) | def decode_landm(pre, priors, variances):
function batched_decode (line 297) | def batched_decode(b_loc, priors, variances):
function batched_decode_landm (line 320) | def batched_decode_landm(pre, priors, variances):
function log_sum_exp (line 343) | def log_sum_exp(x):
function nms (line 357) | def nms(boxes, scores, overlap=0.5, top_k=200):
FILE: extras/facexlib/parsing/__init__.py
function init_parsing_model (line 8) | def init_parsing_model(model_name='bisenet', half=False, device='cuda', ...
FILE: extras/facexlib/parsing/bisenet.py
class ConvBNReLU (line 8) | class ConvBNReLU(nn.Module):
method __init__ (line 10) | def __init__(self, in_chan, out_chan, ks=3, stride=1, padding=1):
method forward (line 15) | def forward(self, x):
class BiSeNetOutput (line 21) | class BiSeNetOutput(nn.Module):
method __init__ (line 23) | def __init__(self, in_chan, mid_chan, num_class):
method forward (line 28) | def forward(self, x):
class AttentionRefinementModule (line 34) | class AttentionRefinementModule(nn.Module):
method __init__ (line 36) | def __init__(self, in_chan, out_chan):
method forward (line 43) | def forward(self, x):
class ContextPath (line 53) | class ContextPath(nn.Module):
method __init__ (line 55) | def __init__(self):
method forward (line 64) | def forward(self, x):
class FeatureFusionModule (line 87) | class FeatureFusionModule(nn.Module):
method __init__ (line 89) | def __init__(self, in_chan, out_chan):
method forward (line 97) | def forward(self, fsp, fcp):
class BiSeNet (line 110) | class BiSeNet(nn.Module):
method __init__ (line 112) | def __init__(self, num_class):
method forward (line 120) | def forward(self, x, return_feat=False):
FILE: extras/facexlib/parsing/parsenet.py
class NormLayer (line 8) | class NormLayer(nn.Module):
method __init__ (line 16) | def __init__(self, channels, normalize_shape=None, norm_type='bn'):
method forward (line 35) | def forward(self, x, ref=None):
class ReluLayer (line 42) | class ReluLayer(nn.Module):
method __init__ (line 54) | def __init__(self, channels, relu_type='relu'):
method forward (line 70) | def forward(self, x):
class ConvLayer (line 74) | class ConvLayer(nn.Module):
method __init__ (line 76) | def __init__(self,
method forward (line 103) | def forward(self, x):
class ResidualBlock (line 113) | class ResidualBlock(nn.Module):
method __init__ (line 118) | def __init__(self, c_in, c_out, relu_type='prelu', norm_type='bn', sca...
method forward (line 132) | def forward(self, x):
class ParseNet (line 140) | class ParseNet(nn.Module):
method __init__ (line 142) | def __init__(self,
method forward (line 188) | def forward(self, x):
FILE: extras/facexlib/parsing/resnet.py
function conv3x3 (line 5) | def conv3x3(in_planes, out_planes, stride=1):
class BasicBlock (line 10) | class BasicBlock(nn.Module):
method __init__ (line 12) | def __init__(self, in_chan, out_chan, stride=1):
method forward (line 26) | def forward(self, x):
function create_layer_basic (line 41) | def create_layer_basic(in_chan, out_chan, bnum, stride=1):
class ResNet18 (line 48) | class ResNet18(nn.Module):
method __init__ (line 50) | def __init__(self):
method forward (line 60) | def forward(self, x):
FILE: extras/facexlib/utils/face_restoration_helper.py
function get_largest_face (line 12) | def get_largest_face(det_faces, h, w):
function get_center_face (line 34) | def get_center_face(det_faces, h=0, w=0, center=None):
class FaceRestoreHelper (line 48) | class FaceRestoreHelper(object):
method __init__ (line 51) | def __init__(self,
method set_upscale_factor (line 105) | def set_upscale_factor(self, upscale_factor):
method read_image (line 108) | def read_image(self, img):
method get_face_landmarks_5 (line 123) | def get_face_landmarks_5(self,
method align_warp_face (line 234) | def align_warp_face(self, save_cropped_path=None, border_mode='constan...
method get_inverse_affine (line 266) | def get_inverse_affine(self, save_inverse_affine_path=None):
method add_restored_face (line 278) | def add_restored_face(self, face):
method paste_faces_to_input_image (line 281) | def paste_faces_to_input_image(self, save_path=None, upsample_img=None):
method clean_all (line 367) | def clean_all(self):
FILE: extras/facexlib/utils/face_utils.py
function compute_increased_bbox (line 6) | def compute_increased_bbox(bbox, increase_area, preserve_aspect=True):
function get_valid_bboxes (line 23) | def get_valid_bboxes(bboxes, h, w):
function align_crop_face_landmarks (line 31) | def align_crop_face_landmarks(img,
function paste_face_back (line 190) | def paste_face_back(img, face, inverse_affine):
FILE: extras/facexlib/utils/misc.py
function imwrite (line 11) | def imwrite(img, file_path, params=None, auto_mkdir=True):
function img2tensor (line 30) | def img2tensor(imgs, bgr2rgb=True, float32=True):
function load_file_from_url (line 59) | def load_file_from_url(url, model_dir=None, progress=True, file_name=Non...
function scandir (line 81) | def scandir(dir_path, suffix=None, recursive=False, full_path=False):
FILE: extras/inpaint_mask.py
class SAMOptions (line 13) | class SAMOptions:
method __init__ (line 14) | def __init__(self,
function optimize_masks (line 35) | def optimize_masks(masks: torch.Tensor) -> torch.Tensor:
function generate_mask_from_image (line 46) | def generate_mask_from_image(image: np.ndarray, mask_model: str = 'sam',...
FILE: extras/interrogate.py
class Interrogator (line 17) | class Interrogator:
method __init__ (line 18) | def __init__(self):
method interrogate (line 26) | def interrogate(self, img_rgb):
FILE: extras/ip_adapter.py
function sdp (line 18) | def sdp(q, k, v, extra_options):
class ImageProjModel (line 22) | class ImageProjModel(torch.nn.Module):
method __init__ (line 23) | def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024,...
method forward (line 31) | def forward(self, image_embeds):
class To_KV (line 39) | class To_KV(torch.nn.Module):
method __init__ (line 40) | def __init__(self, cross_attention_dim):
method load_state_dict_ordered (line 47) | def load_state_dict_ordered(self, sd):
class IPAdapterModel (line 58) | class IPAdapterModel(torch.nn.Module):
method __init__ (line 59) | def __init__(self, state_dict, plus, cross_attention_dim=768, clip_emb...
function load_ip_adapter (line 91) | def load_ip_adapter(clip_vision_path, ip_negative_path, ip_adapter_path):
function clip_preprocess (line 153) | def clip_preprocess(image):
function preprocess (line 167) | def preprocess(img, ip_adapter_path):
function patch_model (line 204) | def patch_model(model, tasks):
FILE: extras/preprocessors.py
function centered_canny (line 5) | def centered_canny(x: np.ndarray, canny_low_threshold, canny_high_thresh...
function centered_canny_color (line 14) | def centered_canny_color(x: np.ndarray, canny_low_threshold, canny_high_...
function pyramid_canny_color (line 23) | def pyramid_canny_color(x: np.ndarray, canny_low_threshold, canny_high_t...
function norm255 (line 43) | def norm255(x, low=4, high=96):
function canny_pyramid (line 56) | def canny_pyramid(x, canny_low_threshold, canny_high_threshold):
function cpds (line 66) | def cpds(x):
FILE: extras/resampler.py
function FeedForward (line 9) | def FeedForward(dim, mult=4):
function reshape_tensor (line 19) | def reshape_tensor(x, heads):
class PerceiverAttention (line 30) | class PerceiverAttention(nn.Module):
method __init__ (line 31) | def __init__(self, *, dim, dim_head=64, heads=8):
method forward (line 46) | def forward(self, x, latents):
class Resampler (line 78) | class Resampler(nn.Module):
method __init__ (line 79) | def __init__(
method forward (line 110) | def forward(self, x):
FILE: extras/safety_checker/models/safety_checker.py
function cosine_distance (line 26) | def cosine_distance(image_embeds, text_embeds):
class StableDiffusionSafetyChecker (line 32) | class StableDiffusionSafetyChecker(PreTrainedModel):
method __init__ (line 38) | def __init__(self, config: CLIPConfig):
method forward (line 51) | def forward(self, clip_input, images):
method forward_onnx (line 103) | def forward_onnx(self, clip_input: torch.Tensor, images: torch.Tensor):
FILE: extras/sam/predictor.py
class SamPredictor (line 19) | class SamPredictor:
method __init__ (line 20) | def __init__(
method set_image (line 45) | def set_image(
method set_torch_image (line 74) | def set_torch_image(
method predict (line 104) | def predict(
method predict_torch (line 181) | def predict_torch(
method get_image_embedding (line 264) | def get_image_embedding(self) -> torch.Tensor:
method device (line 278) | def device(self) -> torch.device:
method reset_image (line 281) | def reset_image(self) -> None:
FILE: extras/vae_interpose.py
class ResBlock (line 14) | class ResBlock(nn.Module):
method __init__ (line 17) | def __init__(self, ch):
method forward (line 30) | def forward(self, x):
class ExtractBlock (line 35) | class ExtractBlock(nn.Module):
method __init__ (line 38) | def __init__(self, ch_in, ch_out):
method forward (line 51) | def forward(self, x):
class InterposerModel (line 55) | class InterposerModel(nn.Module):
method __init__ (line 58) | def __init__(self, ch_in=4, ch_out=4, ch_mid=64, scale=1.0, blocks=12):
method forward (line 75) | def forward(self, x):
function parse (line 85) | def parse(x):
FILE: extras/wd14tagger.py
function default_interrogator (line 27) | def default_interrogator(image_rgb, threshold=0.35, character_threshold=...
FILE: javascript/contextMenus.js
function showContextMenu (line 11) | function showContextMenu(event, element, menuEntries) {
function appendContextMenuOption (line 62) | function appendContextMenuOption(targetElementSelector, entryName, entry...
function removeContextMenuOption (line 81) | function removeContextMenuOption(uid) {
function addContextMenuEventListener (line 95) | function addContextMenuEventListener() {
FILE: javascript/edit-attention.js
function updateInput (line 1) | function updateInput(target) {
function keyupEditAttention (line 7) | function keyupEditAttention(event) {
FILE: javascript/imageviewer.js
function closeModal (line 3) | function closeModal() {
function showModal (line 7) | function showModal(event) {
function negmod (line 21) | function negmod(n, m) {
function updateOnBackgroundChange (line 25) | function updateOnBackgroundChange() {
function all_gallery_buttons (line 40) | function all_gallery_buttons() {
function selected_gallery_button (line 51) | function selected_gallery_button() {
function selected_gallery_index (line 55) | function selected_gallery_index() {
function modalImageSwitch (line 59) | function modalImageSwitch(offset) {
function saveImage (line 88) | function saveImage() {
function modalSaveImage (line 92) | function modalSaveImage(event) {
function modalNextImage (line 96) | function modalNextImage(event) {
function modalPrevImage (line 101) | function modalPrevImage(event) {
function modalKeyHandler (line 106) | function modalKeyHandler(event) {
function setupImageForLightbox (line 123) | function setupImageForLightbox(e) {
function modalZoomSet (line 154) | function modalZoomSet(modalImage, enable) {
function modalZoomToggle (line 158) | function modalZoomToggle(event) {
function modalTileImageToggle (line 164) | function modalTileImageToggle(event) {
FILE: javascript/localization.js
function hasLocalization (line 6) | function hasLocalization() {
function textNodesUnder (line 10) | function textNodesUnder(el) {
function canBeTranslated (line 16) | function canBeTranslated(node, text) {
function getTranslation (line 25) | function getTranslation(text) {
function processTextNode (line 40) | function processTextNode(node) {
function processNode (line 54) | function processNode(node) {
function refresh_style_localization (line 79) | function refresh_style_localization() {
function refresh_aspect_ratios_label (line 83) | function refresh_aspect_ratios_label(value) {
function localizeWholePage (line 92) | function localizeWholePage() {
FILE: javascript/script.js
function gradioApp (line 2) | function gradioApp() {
function get_uiCurrentTab (line 17) | function get_uiCurrentTab() {
function get_uiCurrentTabContent (line 24) | function get_uiCurrentTabContent() {
function onUiUpdate (line 40) | function onUiUpdate(callback) {
function onAfterUiUpdate (line 52) | function onAfterUiUpdate(callback) {
function onUiLoaded (line 60) | function onUiLoaded(callback) {
function onUiTabChange (line 68) | function onUiTabChange(callback) {
function onOptionsChanged (line 77) | function onOptionsChanged(callback) {
function executeCallbacks (line 81) | function executeCallbacks(queue, arg) {
function scheduleAfterUiUpdateCallbacks (line 97) | function scheduleAfterUiUpdateCallbacks() {
function addObserverIfDesiredNodeAvailable (line 136) | function addObserverIfDesiredNodeAvailable(querySelector, callback) {
function initStylePreviewOverlay (line 186) | function initStylePreviewOverlay() {
function uiElementIsVisible (line 229) | function uiElementIsVisible(el) {
function uiElementInSight (line 241) | function uiElementInSight(el) {
function playNotification (line 249) | function playNotification() {
function set_theme (line 253) | function set_theme(theme) {
function htmlDecode (line 260) | function htmlDecode(input) {
FILE: javascript/viewer.js
function refresh_grid (line 3) | function refresh_grid() {
function refresh_grid_delayed (line 15) | function refresh_grid_delayed() {
function resized (line 22) | function resized() {
function viewer_to_top (line 37) | function viewer_to_top(delay = 100) {
function viewer_to_bottom (line 41) | function viewer_to_bottom(delay = 100) {
function on_style_selection_blur (line 60) | function on_style_selection_blur() {
FILE: javascript/zoom.js
function hasHorizontalScrollbar (line 5) | function hasHorizontalScrollbar(element) {
function isModifierKey (line 10) | function isModifierKey(event, key) {
function createHotkeyConfig (line 24) | function createHotkeyConfig(defaultHotkeysConfig) {
function applyZoomAndPan (line 56) | function applyZoomAndPan(elemId) {
FILE: launch.py
function prepare_environment (line 29) | def prepare_environment():
function ini_args (line 70) | def ini_args():
function download_models (line 103) | def download_models(default_model, previous_default_models, checkpoint_d...
FILE: ldm_patched/contrib/external.py
function before_node_execution (line 39) | def before_node_execution():
function interrupt_processing (line 42) | def interrupt_processing(value=True):
class CLIPTextEncode (line 47) | class CLIPTextEncode:
method INPUT_TYPES (line 49) | def INPUT_TYPES(s):
method encode (line 56) | def encode(self, clip, text):
class ConditioningCombine (line 61) | class ConditioningCombine:
method INPUT_TYPES (line 63) | def INPUT_TYPES(s):
method combine (line 70) | def combine(self, conditioning_1, conditioning_2):
class ConditioningAverage (line 73) | class ConditioningAverage :
method INPUT_TYPES (line 75) | def INPUT_TYPES(s):
method addWeighted (line 84) | def addWeighted(self, conditioning_to, conditioning_from, conditioning...
class ConditioningConcat (line 111) | class ConditioningConcat:
method INPUT_TYPES (line 113) | def INPUT_TYPES(s):
method concat (line 123) | def concat(self, conditioning_to, conditioning_from):
class ConditioningSetArea (line 139) | class ConditioningSetArea:
method INPUT_TYPES (line 141) | def INPUT_TYPES(s):
method append (line 154) | def append(self, conditioning, width, height, x, y, strength):
class ConditioningSetAreaPercentage (line 164) | class ConditioningSetAreaPercentage:
method INPUT_TYPES (line 166) | def INPUT_TYPES(s):
method append (line 179) | def append(self, conditioning, width, height, x, y, strength):
class ConditioningSetMask (line 189) | class ConditioningSetMask:
method INPUT_TYPES (line 191) | def INPUT_TYPES(s):
method append (line 202) | def append(self, conditioning, mask, set_cond_area, strength):
class ConditioningZeroOut (line 218) | class ConditioningZeroOut:
method INPUT_TYPES (line 220) | def INPUT_TYPES(s):
method zero_out (line 227) | def zero_out(self, conditioning):
class ConditioningSetTimestepRange (line 237) | class ConditioningSetTimestepRange:
method INPUT_TYPES (line 239) | def INPUT_TYPES(s):
method set_range (line 249) | def set_range(self, conditioning, start, end):
class VAEDecode (line 259) | class VAEDecode:
method INPUT_TYPES (line 261) | def INPUT_TYPES(s):
method decode (line 268) | def decode(self, vae, samples):
class VAEDecodeTiled (line 271) | class VAEDecodeTiled:
method INPUT_TYPES (line 273) | def INPUT_TYPES(s):
method decode (line 282) | def decode(self, vae, samples, tile_size):
class VAEEncode (line 285) | class VAEEncode:
method INPUT_TYPES (line 287) | def INPUT_TYPES(s):
method vae_encode_crop_pixels (line 295) | def vae_encode_crop_pixels(pixels):
method encode (line 304) | def encode(self, vae, pixels):
class VAEEncodeTiled (line 309) | class VAEEncodeTiled:
method INPUT_TYPES (line 311) | def INPUT_TYPES(s):
method encode (line 320) | def encode(self, vae, pixels, tile_size):
class VAEEncodeForInpaint (line 325) | class VAEEncodeForInpaint:
method INPUT_TYPES (line 327) | def INPUT_TYPES(s):
method encode (line 334) | def encode(self, vae, pixels, mask, grow_mask_by=6):
class InpaintModelConditioning (line 365) | class InpaintModelConditioning:
method INPUT_TYPES (line 367) | def INPUT_TYPES(s):
method encode (line 381) | def encode(self, positive, negative, pixels, vae, mask):
class SaveLatent (line 420) | class SaveLatent:
method __init__ (line 421) | def __init__(self):
method INPUT_TYPES (line 425) | def INPUT_TYPES(s):
method save (line 437) | def save(self, samples, filename_prefix="ldm_patched", prompt=None, ex...
class LoadLatent (line 471) | class LoadLatent:
method INPUT_TYPES (line 473) | def INPUT_TYPES(s):
method load (line 483) | def load(self, latent):
method IS_CHANGED (line 493) | def IS_CHANGED(s, latent):
method VALIDATE_INPUTS (line 501) | def VALIDATE_INPUTS(s, latent):
class CheckpointLoader (line 507) | class CheckpointLoader:
method INPUT_TYPES (line 509) | def INPUT_TYPES(s):
method load_checkpoint (line 517) | def load_checkpoint(self, config_name, ckpt_name, output_vae=True, out...
class CheckpointLoaderSimple (line 522) | class CheckpointLoaderSimple:
method INPUT_TYPES (line 524) | def INPUT_TYPES(s):
method load_checkpoint (line 532) | def load_checkpoint(self, ckpt_name, output_vae=True, output_clip=True):
class DiffusersLoader (line 537) | class DiffusersLoader:
method INPUT_TYPES (line 539) | def INPUT_TYPES(cls):
method load_checkpoint (line 553) | def load_checkpoint(self, model_path, output_vae=True, output_clip=True):
class unCLIPCheckpointLoader (line 564) | class unCLIPCheckpointLoader:
method INPUT_TYPES (line 566) | def INPUT_TYPES(s):
method load_checkpoint (line 574) | def load_checkpoint(self, ckpt_name, output_vae=True, output_clip=True):
class CLIPSetLastLayer (line 579) | class CLIPSetLastLayer:
method INPUT_TYPES (line 581) | def INPUT_TYPES(s):
method set_last_layer (line 590) | def set_last_layer(self, clip, stop_at_clip_layer):
class LoraLoader (line 595) | class LoraLoader:
method __init__ (line 596) | def __init__(self):
method INPUT_TYPES (line 600) | def INPUT_TYPES(s):
method load_lora (line 612) | def load_lora(self, model, clip, lora_name, strength_model, strength_c...
class LoraLoaderModelOnly (line 633) | class LoraLoaderModelOnly(LoraLoader):
method INPUT_TYPES (line 635) | def INPUT_TYPES(s):
method load_lora_model_only (line 643) | def load_lora_model_only(self, model, lora_name, strength_model):
class VAELoader (line 646) | class VAELoader:
method vae_list (line 648) | def vae_list():
method load_taesd (line 672) | def load_taesd(name):
method INPUT_TYPES (line 694) | def INPUT_TYPES(s):
method load_vae (line 702) | def load_vae(self, vae_name):
class ControlNetLoader (line 711) | class ControlNetLoader:
method INPUT_TYPES (line 713) | def INPUT_TYPES(s):
method load_controlnet (line 721) | def load_controlnet(self, control_net_name):
class DiffControlNetLoader (line 726) | class DiffControlNetLoader:
method INPUT_TYPES (line 728) | def INPUT_TYPES(s):
method load_controlnet (line 737) | def load_controlnet(self, model, control_net_name):
class ControlNetApply (line 743) | class ControlNetApply:
method INPUT_TYPES (line 745) | def INPUT_TYPES(s):
method apply_controlnet (line 756) | def apply_controlnet(self, conditioning, control_net, image, strength):
class ControlNetApplyAdvanced (line 773) | class ControlNetApplyAdvanced:
method INPUT_TYPES (line 775) | def INPUT_TYPES(s):
method apply_controlnet (line 791) | def apply_controlnet(self, positive, negative, control_net, image, str...
class UNETLoader (line 820) | class UNETLoader:
method INPUT_TYPES (line 822) | def INPUT_TYPES(s):
method load_unet (line 830) | def load_unet(self, unet_name):
class CLIPLoader (line 835) | class CLIPLoader:
method INPUT_TYPES (line 837) | def INPUT_TYPES(s):
method load_clip (line 845) | def load_clip(self, clip_name):
class DualCLIPLoader (line 850) | class DualCLIPLoader:
method INPUT_TYPES (line 852) | def INPUT_TYPES(s):
method load_clip (line 860) | def load_clip(self, clip_name1, clip_name2):
class CLIPVisionLoader (line 866) | class CLIPVisionLoader:
method INPUT_TYPES (line 868) | def INPUT_TYPES(s):
method load_clip (line 876) | def load_clip(self, clip_name):
class CLIPVisionEncode (line 881) | class CLIPVisionEncode:
method INPUT_TYPES (line 883) | def INPUT_TYPES(s):
method encode (line 892) | def encode(self, clip_vision, image):
class StyleModelLoader (line 896) | class StyleModelLoader:
method INPUT_TYPES (line 898) | def INPUT_TYPES(s):
method load_style_model (line 906) | def load_style_model(self, style_model_name):
class StyleModelApply (line 912) | class StyleModelApply:
method INPUT_TYPES (line 914) | def INPUT_TYPES(s):
method apply_stylemodel (line 924) | def apply_stylemodel(self, clip_vision_output, style_model, conditioni...
class unCLIPConditioning (line 932) | class unCLIPConditioning:
method INPUT_TYPES (line 934) | def INPUT_TYPES(s):
method apply_adm (line 945) | def apply_adm(self, conditioning, clip_vision_output, strength, noise_...
class GLIGENLoader (line 961) | class GLIGENLoader:
method INPUT_TYPES (line 963) | def INPUT_TYPES(s):
method load_gligen (line 971) | def load_gligen(self, gligen_name):
class GLIGENTextBoxApply (line 976) | class GLIGENTextBoxApply:
method INPUT_TYPES (line 978) | def INPUT_TYPES(s):
method append (line 993) | def append(self, conditioning_to, clip, gligen_textbox_model, text, wi...
class EmptyLatentImage (line 1007) | class EmptyLatentImage:
method __init__ (line 1008) | def __init__(self):
method INPUT_TYPES (line 1012) | def INPUT_TYPES(s):
method generate (line 1021) | def generate(self, width, height, batch_size=1):
class LatentFromBatch (line 1026) | class LatentFromBatch:
method INPUT_TYPES (line 1028) | def INPUT_TYPES(s):
method frombatch (line 1038) | def frombatch(self, samples, batch_index, length):
class RepeatLatentBatch (line 1058) | class RepeatLatentBatch:
method INPUT_TYPES (line 1060) | def INPUT_TYPES(s):
method repeat (line 1069) | def repeat(self, samples, amount):
class LatentUpscale (line 1084) | class LatentUpscale:
method INPUT_TYPES (line 1089) | def INPUT_TYPES(s):
method upscale (line 1099) | def upscale(self, samples, upscale_method, width, height, crop):
class LatentUpscaleBy (line 1118) | class LatentUpscaleBy:
method INPUT_TYPES (line 1122) | def INPUT_TYPES(s):
method upscale (line 1130) | def upscale(self, samples, upscale_method, scale_by):
class LatentRotate (line 1137) | class LatentRotate:
method INPUT_TYPES (line 1139) | def INPUT_TYPES(s):
method rotate (line 1148) | def rotate(self, samples, rotation):
class LatentFlip (line 1161) | class LatentFlip:
method INPUT_TYPES (line 1163) | def INPUT_TYPES(s):
method flip (line 1172) | def flip(self, samples, flip_method):
class LatentComposite (line 1181) | class LatentComposite:
method INPUT_TYPES (line 1183) | def INPUT_TYPES(s):
method composite (line 1195) | def composite(self, samples_to, samples_from, x, y, composite_method="...
class LatentBlend (line 1223) | class LatentBlend:
method INPUT_TYPES (line 1225) | def INPUT_TYPES(s):
method blend (line 1242) | def blend(self, samples1, samples2, blend_factor:float, blend_mode: st...
method blend_mode (line 1258) | def blend_mode(self, img1, img2, mode):
class LatentCrop (line 1264) | class LatentCrop:
method INPUT_TYPES (line 1266) | def INPUT_TYPES(s):
method crop (line 1278) | def crop(self, samples, width, height, x, y):
class SetLatentNoiseMask (line 1297) | class SetLatentNoiseMask:
method INPUT_TYPES (line 1299) | def INPUT_TYPES(s):
method set_mask (line 1308) | def set_mask(self, samples, mask):
function common_ksampler (line 1313) | def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, po...
class KSampler (line 1334) | class KSampler:
method INPUT_TYPES (line 1336) | def INPUT_TYPES(s):
method sample (line 1356) | def sample(self, model, seed, steps, cfg, sampler_name, scheduler, pos...
class KSamplerAdvanced (line 1359) | class KSamplerAdvanced:
method INPUT_TYPES (line 1361) | def INPUT_TYPES(s):
method sample (line 1384) | def sample(self, model, add_noise, noise_seed, steps, cfg, sampler_nam...
class SaveImage (line 1393) | class SaveImage:
method __init__ (line 1394) | def __init__(self):
method INPUT_TYPES (line 1401) | def INPUT_TYPES(s):
method save_images (line 1415) | def save_images(self, images, filename_prefix="ldm_patched", prompt=No...
class PreviewImage (line 1442) | class PreviewImage(SaveImage):
method __init__ (line 1443) | def __init__(self):
method INPUT_TYPES (line 1450) | def INPUT_TYPES(s):
class LoadImage (line 1456) | class LoadImage:
method INPUT_TYPES (line 1458) | def INPUT_TYPES(s):
method load_image (line 1469) | def load_image(self, image):
method IS_CHANGED (line 1499) | def IS_CHANGED(s, image):
method VALIDATE_INPUTS (line 1507) | def VALIDATE_INPUTS(s, image):
class LoadImageMask (line 1513) | class LoadImageMask:
method INPUT_TYPES (line 1516) | def INPUT_TYPES(s):
method load_image (line 1528) | def load_image(self, image, channel):
method IS_CHANGED (line 1548) | def IS_CHANGED(s, image, channel):
method VALIDATE_INPUTS (line 1556) | def VALIDATE_INPUTS(s, image):
class ImageScale (line 1562) | class ImageScale:
method INPUT_TYPES (line 1567) | def INPUT_TYPES(s):
method upscale (line 1577) | def upscale(self, image, upscale_method, width, height, crop):
class ImageScaleBy (line 1592) | class ImageScaleBy:
method INPUT_TYPES (line 1596) | def INPUT_TYPES(s):
method upscale (line 1604) | def upscale(self, image, upscale_method, scale_by):
class ImageInvert (line 1612) | class ImageInvert:
method INPUT_TYPES (line 1615) | def INPUT_TYPES(s):
method invert (line 1623) | def invert(self, image):
class ImageBatch (line 1627) | class ImageBatch:
method INPUT_TYPES (line 1630) | def INPUT_TYPES(s):
method batch (line 1638) | def batch(self, image1, image2):
class EmptyImage (line 1644) | class EmptyImage:
method __init__ (line 1645) | def __init__(self, device="cpu"):
method INPUT_TYPES (line 1649) | def INPUT_TYPES(s):
method generate (line 1660) | def generate(self, width, height, batch_size=1, color=0):
class ImagePadForOutpaint (line 1666) | class ImagePadForOutpaint:
method INPUT_TYPES (line 1669) | def INPUT_TYPES(s):
method expand_image (line 1686) | def expand_image(self, image, left, top, right, bottom, feathering):
function load_custom_node (line 1859) | def load_custom_node(module_path, ignore=set()):
function load_custom_nodes (line 1896) | def load_custom_nodes():
function init_custom_nodes (line 1923) | def init_custom_nodes():
FILE: ldm_patched/contrib/external_align_your_steps.py
function loglinear_interp (line 7) | def loglinear_interp(t_steps, num_steps):
class AlignYourStepsScheduler (line 24) | class AlignYourStepsScheduler:
method INPUT_TYPES (line 26) | def INPUT_TYPES(s):
method get_sigmas (line 38) | def get_sigmas(self, model_type, steps, denoise):
FILE: ldm_patched/contrib/external_canny.py
function get_canny_nms_kernel (line 10) | def get_canny_nms_kernel(device=None, dtype=None):
function get_hysteresis_kernel (line 28) | def get_hysteresis_kernel(device=None, dtype=None):
function gaussian_blur_2d (line 45) | def gaussian_blur_2d(img, kernel_size, sigma):
function get_sobel_kernel2d (line 65) | def get_sobel_kernel2d(device=None, dtype=None):
function spatial_gradient (line 70) | def spatial_gradient(input, normalized: bool = True):
function rgb_to_grayscale (line 108) | def rgb_to_grayscale(image, rgb_weights = None):
function canny (line 155) | def canny(
class Canny (line 281) | class Canny:
method INPUT_TYPES (line 283) | def INPUT_TYPES(s):
method detect_edge (line 294) | def detect_edge(self, image, low_threshold, high_threshold):
FILE: ldm_patched/contrib/external_clip_sdxl.py
class CLIPTextEncodeSDXLRefiner (line 6) | class CLIPTextEncodeSDXLRefiner:
method INPUT_TYPES (line 8) | def INPUT_TYPES(s):
method encode (line 20) | def encode(self, clip, ascore, width, height, text):
class CLIPTextEncodeSDXL (line 25) | class CLIPTextEncodeSDXL:
method INPUT_TYPES (line 27) | def INPUT_TYPES(s):
method encode (line 43) | def encode(self, clip, width, height, crop_w, crop_h, target_width, ta...
FILE: ldm_patched/contrib/external_compositing.py
function resize_mask (line 8) | def resize_mask(mask, shape):
class PorterDuffMode (line 11) | class PorterDuffMode(Enum):
function porter_duff_composite (line 32) | def porter_duff_composite(src_image: torch.Tensor, src_alpha: torch.Tens...
class PorterDuffImageComposite (line 94) | class PorterDuffImageComposite:
method INPUT_TYPES (line 96) | def INPUT_TYPES(s):
method composite (line 111) | def composite(self, source: torch.Tensor, source_alpha: torch.Tensor, ...
class SplitImageWithAlpha (line 147) | class SplitImageWithAlpha:
method INPUT_TYPES (line 149) | def INPUT_TYPES(s):
method split_image_with_alpha (line 160) | def split_image_with_alpha(self, image: torch.Tensor):
class JoinImageWithAlpha (line 167) | class JoinImageWithAlpha:
method INPUT_TYPES (line 169) | def INPUT_TYPES(s):
method join_image_with_alpha (line 181) | def join_image_with_alpha(self, image: torch.Tensor, alpha: torch.Tens...
FILE: ldm_patched/contrib/external_custom_sampler.py
class BasicScheduler (line 11) | class BasicScheduler:
method INPUT_TYPES (line 13) | def INPUT_TYPES(s):
method get_sigmas (line 26) | def get_sigmas(self, model, scheduler, steps, denoise):
class KarrasScheduler (line 37) | class KarrasScheduler:
method INPUT_TYPES (line 39) | def INPUT_TYPES(s):
method get_sigmas (line 52) | def get_sigmas(self, steps, sigma_max, sigma_min, rho):
class ExponentialScheduler (line 56) | class ExponentialScheduler:
method INPUT_TYPES (line 58) | def INPUT_TYPES(s):
method get_sigmas (line 70) | def get_sigmas(self, steps, sigma_max, sigma_min):
class PolyexponentialScheduler (line 74) | class PolyexponentialScheduler:
method INPUT_TYPES (line 76) | def INPUT_TYPES(s):
method get_sigmas (line 89) | def get_sigmas(self, steps, sigma_max, sigma_min, rho):
class SDTurboScheduler (line 93) | class SDTurboScheduler:
method INPUT_TYPES (line 95) | def INPUT_TYPES(s):
method get_sigmas (line 107) | def get_sigmas(self, model, steps, denoise):
class VPScheduler (line 114) | class VPScheduler:
method INPUT_TYPES (line 116) | def INPUT_TYPES(s):
method get_sigmas (line 129) | def get_sigmas(self, steps, beta_d, beta_min, eps_s):
class SplitSigmas (line 133) | class SplitSigmas:
method INPUT_TYPES (line 135) | def INPUT_TYPES(s):
method get_sigmas (line 146) | def get_sigmas(self, sigmas, step):
class FlipSigmas (line 151) | class FlipSigmas:
method INPUT_TYPES (line 153) | def INPUT_TYPES(s):
method get_sigmas (line 163) | def get_sigmas(self, sigmas):
class KSamplerSelect (line 169) | class KSamplerSelect:
method INPUT_TYPES (line 171) | def INPUT_TYPES(s):
method get_sampler (line 181) | def get_sampler(self, sampler_name):
class SamplerDPMPP_2M_SDE (line 185) | class SamplerDPMPP_2M_SDE:
method INPUT_TYPES (line 187) | def INPUT_TYPES(s):
method get_sampler (line 200) | def get_sampler(self, solver_type, eta, s_noise, noise_device):
class SamplerDPMPP_SDE (line 209) | class SamplerDPMPP_SDE:
method INPUT_TYPES (line 211) | def INPUT_TYPES(s):
method get_sampler (line 224) | def get_sampler(self, eta, s_noise, r, noise_device):
class SamplerTCD (line 233) | class SamplerTCD:
method INPUT_TYPES (line 235) | def INPUT_TYPES(s):
method get_sampler (line 246) | def get_sampler(self, eta=0.3):
class SamplerCustom (line 251) | class SamplerCustom:
method INPUT_TYPES (line 253) | def INPUT_TYPES(s):
method sample (line 274) | def sample(self, model, add_noise, noise_seed, cfg, positive, negative...
FILE: ldm_patched/contrib/external_freelunch.py
function Fourier_filter (line 8) | def Fourier_filter(x, threshold, scale):
class FreeU (line 27) | class FreeU:
method INPUT_TYPES (line 29) | def INPUT_TYPES(s):
method patch (line 41) | def patch(self, model, b1, b2, s1, s2):
class FreeU_V2 (line 66) | class FreeU_V2:
method INPUT_TYPES (line 68) | def INPUT_TYPES(s):
method patch (line 80) | def patch(self, model, b1, b2, s1, s2):
FILE: ldm_patched/contrib/external_hypernetwork.py
function load_hypernetwork_patch (line 7) | def load_hypernetwork_patch(path, strength):
class HypernetworkLoader (line 98) | class HypernetworkLoader:
method INPUT_TYPES (line 100) | def INPUT_TYPES(s):
method load_hypernetwork (line 110) | def load_hypernetwork(self, model, hypernetwork_name, strength):
FILE: ldm_patched/contrib/external_hypertile.py
function random_divisor (line 10) | def random_divisor(value: int, min_value: int, /, max_options: int = 1) ...
class HyperTile (line 25) | class HyperTile:
method INPUT_TYPES (line 27) | def INPUT_TYPES(s):
method patch (line 39) | def patch(self, model, tile_size, swap_size, max_depth, scale_depth):
FILE: ldm_patched/contrib/external_images.py
class ImageCrop (line 16) | class ImageCrop:
method INPUT_TYPES (line 18) | def INPUT_TYPES(s):
method crop (line 30) | def crop(self, image, width, height, x, y):
class RepeatImageBatch (line 38) | class RepeatImageBatch:
method INPUT_TYPES (line 40) | def INPUT_TYPES(s):
method repeat (line 49) | def repeat(self, image, amount):
class SaveAnimatedWEBP (line 53) | class SaveAnimatedWEBP:
method __init__ (line 54) | def __init__(self):
method INPUT_TYPES (line 61) | def INPUT_TYPES(s):
method save_images (line 81) | def save_images(self, images, fps, filename_prefix, lossless, quality,...
class SaveAnimatedPNG (line 119) | class SaveAnimatedPNG:
method __init__ (line 120) | def __init__(self):
method INPUT_TYPES (line 126) | def INPUT_TYPES(s):
method save_images (line 143) | def save_images(self, images, fps, compress_level, filename_prefix="ld...
FILE: ldm_patched/contrib/external_latent.py
function reshape_latent_to (line 6) | def reshape_latent_to(target_shape, latent):
class LatentAdd (line 12) | class LatentAdd:
method INPUT_TYPES (line 14) | def INPUT_TYPES(s):
method op (line 22) | def op(self, samples1, samples2):
class LatentSubtract (line 32) | class LatentSubtract:
method INPUT_TYPES (line 34) | def INPUT_TYPES(s):
method op (line 42) | def op(self, samples1, samples2):
class LatentMultiply (line 52) | class LatentMultiply:
method INPUT_TYPES (line 54) | def INPUT_TYPES(s):
method op (line 64) | def op(self, samples, multiplier):
class LatentInterpolate (line 71) | class LatentInterpolate:
method INPUT_TYPES (line 73) | def INPUT_TYPES(s):
method op (line 84) | def op(self, samples1, samples2, ratio):
class LatentBatch (line 105) | class LatentBatch:
method INPUT_TYPES (line 107) | def INPUT_TYPES(s):
method batch (line 115) | def batch(self, samples1, samples2):
class LatentBatchSeedBehavior (line 127) | class LatentBatchSeedBehavior:
method INPUT_TYPES (line 129) | def INPUT_TYPES(s):
method op (line 138) | def op(self, samples, seed_behavior):
FILE: ldm_patched/contrib/external_mask.py
function composite (line 10) | def composite(destination, source, x, y, mask = None, multiplier = 8, re...
class LatentCompositeMasked (line 44) | class LatentCompositeMasked:
method INPUT_TYPES (line 46) | def INPUT_TYPES(s):
method composite (line 64) | def composite(self, destination, source, x, y, resize_source, mask = N...
class ImageCompositeMasked (line 71) | class ImageCompositeMasked:
method INPUT_TYPES (line 73) | def INPUT_TYPES(s):
method composite (line 91) | def composite(self, destination, source, x, y, resize_source, mask = N...
class MaskToImage (line 96) | class MaskToImage:
method INPUT_TYPES (line 98) | def INPUT_TYPES(s):
method mask_to_image (line 110) | def mask_to_image(self, mask):
class ImageToMask (line 114) | class ImageToMask:
method INPUT_TYPES (line 116) | def INPUT_TYPES(s):
method image_to_mask (line 129) | def image_to_mask(self, image, channel):
class ImageColorToMask (line 134) | class ImageColorToMask:
method INPUT_TYPES (line 136) | def INPUT_TYPES(s):
method image_to_mask (line 149) | def image_to_mask(self, image, color):
class SolidMask (line 155) | class SolidMask:
method INPUT_TYPES (line 157) | def INPUT_TYPES(cls):
method solid (line 172) | def solid(self, value, width, height):
class InvertMask (line 176) | class InvertMask:
method INPUT_TYPES (line 178) | def INPUT_TYPES(cls):
method invert (line 191) | def invert(self, mask):
class CropMask (line 195) | class CropMask:
method INPUT_TYPES (line 197) | def INPUT_TYPES(cls):
method crop (line 214) | def crop(self, mask, x, y, width, height):
class MaskComposite (line 219) | class MaskComposite:
method INPUT_TYPES (line 221) | def INPUT_TYPES(cls):
method combine (line 238) | def combine(self, destination, source, x, y, operation):
class FeatherMask (line 266) | class FeatherMask:
method INPUT_TYPES (line 268) | def INPUT_TYPES(cls):
method feather (line 285) | def feather(self, mask, left, top, right, bottom):
class GrowMask (line 311) | class GrowMask:
method INPUT_TYPES (line 313) | def INPUT_TYPES(cls):
method expand_mask (line 328) | def expand_mask(self, mask, expand, tapered_corners):
FILE: ldm_patched/contrib/external_model_advanced.py
class LCM (line 8) | class LCM(ldm_patched.modules.model_sampling.EPS):
method calculate_denoised (line 9) | def calculate_denoised(self, sigma, model_output, model_input):
class ModelSamplingDiscreteDistilled (line 22) | class ModelSamplingDiscreteDistilled(ldm_patched.modules.model_sampling....
method __init__ (line 25) | def __init__(self, model_config=None):
method timestep (line 36) | def timestep(self, sigma):
method sigma (line 41) | def sigma(self, timestep):
function rescale_zero_terminal_snr_sigmas (line 50) | def rescale_zero_terminal_snr_sigmas(sigmas):
class ModelSamplingDiscrete (line 69) | class ModelSamplingDiscrete:
method INPUT_TYPES (line 71) | def INPUT_TYPES(s):
method patch (line 82) | def patch(self, model, sampling, zsnr):
class ModelSamplingContinuousEDM (line 107) | class ModelSamplingContinuousEDM:
method INPUT_TYPES (line 109) | def INPUT_TYPES(s):
method patch (line 121) | def patch(self, model, sampling, sigma_max, sigma_min):
class RescaleCFG (line 145) | class RescaleCFG:
method INPUT_TYPES (line 147) | def INPUT_TYPES(s):
method patch (line 156) | def patch(self, model, multiplier):
FILE: ldm_patched/contrib/external_model_downscale.py
class PatchModelAddDownscale (line 6) | class PatchModelAddDownscale:
method INPUT_TYPES (line 9) | def INPUT_TYPES(s):
method patch (line 24) | def patch(self, model, block_number, downscale_factor, start_percent, ...
FILE: ldm_patched/contrib/external_model_merging.py
class ModelMergeSimple (line 14) | class ModelMergeSimple:
method INPUT_TYPES (line 16) | def INPUT_TYPES(s):
method merge (line 26) | def merge(self, model1, model2, ratio):
class ModelSubtract (line 33) | class ModelSubtract:
method INPUT_TYPES (line 35) | def INPUT_TYPES(s):
method merge (line 45) | def merge(self, model1, model2, multiplier):
class ModelAdd (line 52) | class ModelAdd:
method INPUT_TYPES (line 54) | def INPUT_TYPES(s):
method merge (line 63) | def merge(self, model1, model2):
class CLIPMergeSimple (line 71) | class CLIPMergeSimple:
method INPUT_TYPES (line 73) | def INPUT_TYPES(s):
method merge (line 83) | def merge(self, clip1, clip2, ratio):
class ModelMergeBlocks (line 92) | class ModelMergeBlocks:
method INPUT_TYPES (line 94) | def INPUT_TYPES(s):
method merge (line 106) | def merge(self, model1, model2, **kwargs):
function save_checkpoint (line 124) | def save_checkpoint(model, clip=None, vae=None, clip_vision=None, filena...
class CheckpointSave (line 166) | class CheckpointSave:
method __init__ (line 167) | def __init__(self):
method INPUT_TYPES (line 171) | def INPUT_TYPES(s):
method save (line 183) | def save(self, model, clip, vae, filename_prefix, prompt=None, extra_p...
class CLIPSave (line 187) | class CLIPSave:
method __init__ (line 188) | def __init__(self):
method INPUT_TYPES (line 192) | def INPUT_TYPES(s):
method save (line 202) | def save(self, clip, filename_prefix, prompt=None, extra_pnginfo=None):
class VAESave (line 243) | class VAESave:
method __init__ (line 244) | def __init__(self):
method INPUT_TYPES (line 248) | def INPUT_TYPES(s):
method save (line 258) | def save(self, vae, filename_prefix, prompt=None, extra_pnginfo=None):
FILE: ldm_patched/contrib/external_perpneg.py
class PerpNeg (line 10) | class PerpNeg:
method INPUT_TYPES (line 12) | def INPUT_TYPES(s):
method patch (line 22) | def patch(self, model, empty_conditioning, neg_scale):
FILE: ldm_patched/contrib/external_photomaker.py
class MLP (line 23) | class MLP(nn.Module):
method __init__ (line 24) | def __init__(self, in_dim, out_dim, hidden_dim, use_residual=True, ope...
method forward (line 34) | def forward(self, x):
class FuseModule (line 45) | class FuseModule(nn.Module):
method __init__ (line 46) | def __init__(self, embed_dim, operations):
method fuse_fn (line 52) | def fuse_fn(self, prompt_embeds, id_embeds):
method forward (line 59) | def forward(
class PhotoMakerIDEncoder (line 93) | class PhotoMakerIDEncoder(ldm_patched.modules.clip_model.CLIPVisionModel...
method __init__ (line 94) | def __init__(self):
method forward (line 103) | def forward(self, id_pixel_values, prompt_embeds, class_tokens_mask):
class PhotoMakerLoader (line 120) | class PhotoMakerLoader:
method INPUT_TYPES (line 122) | def INPUT_TYPES(s):
method load_photomaker_model (line 130) | def load_photomaker_model(self, photomaker_model_name):
class PhotoMakerEncode (line 140) | class PhotoMakerEncode:
method INPUT_TYPES (line 142) | def INPUT_TYPES(s):
method apply_photomaker (line 154) | def apply_photomaker(self, photomaker, image, clip, text):
FILE: ldm_patched/contrib/external_post_processing.py
class Blend (line 12) | class Blend:
method __init__ (line 13) | def __init__(self):
method INPUT_TYPES (line 17) | def INPUT_TYPES(s):
method blend_images (line 37) | def blend_images(self, image1: torch.Tensor, image2: torch.Tensor, ble...
method blend_mode (line 49) | def blend_mode(self, img1, img2, mode):
method g (line 65) | def g(self, x):
function gaussian_kernel (line 68) | def gaussian_kernel(kernel_size: int, sigma: float, device=None):
class Blur (line 74) | class Blur:
method __init__ (line 75) | def __init__(self):
method INPUT_TYPES (line 79) | def INPUT_TYPES(s):
method blur (line 103) | def blur(self, image: torch.Tensor, blur_radius: int, sigma: float):
class Quantize (line 119) | class Quantize:
method __init__ (line 120) | def __init__(self):
method INPUT_TYPES (line 124) | def INPUT_TYPES(s):
method bayer (line 143) | def bayer(im, pal_im, order):
method quantize (line 168) | def quantize(self, image: torch.Tensor, colors: int, dither: str):
class Sharpen (line 190) | class Sharpen:
method __init__ (line 191) | def __init__(self):
method INPUT_TYPES (line 195) | def INPUT_TYPES(s):
method sharpen (line 225) | def sharpen(self, image: torch.Tensor, sharpen_radius: int, sigma:floa...
class ImageScaleToTotalPixels (line 246) | class ImageScaleToTotalPixels:
method INPUT_TYPES (line 251) | def INPUT_TYPES(s):
method upscale (line 260) | def upscale(self, image, upscale_method, megapixels):
FILE: ldm_patched/contrib/external_rebatch.py
class LatentRebatch (line 5) | class LatentRebatch:
method INPUT_TYPES (line 7) | def INPUT_TYPES(s):
method get_batch (line 20) | def get_batch(latents, list_ind, offset):
method get_slices (line 36) | def get_slices(indexable, num, batch_size):
method slice_batch (line 47) | def slice_batch(batch, num, batch_size):
method cat_batch (line 52) | def cat_batch(batch1, batch2):
method rebatch (line 58) | def rebatch(self, latents, batch_size):
class ImageRebatch (line 104) | class ImageRebatch:
method INPUT_TYPES (line 106) | def INPUT_TYPES(s):
method rebatch (line 118) | def rebatch(self, images, batch_size):
FILE: ldm_patched/contrib/external_sag.py
function attention_basic_with_sim (line 15) | def attention_basic_with_sim(q, k, v, heads, mask=None):
function create_blur_map (line 56) | def create_blur_map(x0, attn, sigma=3.0, threshold=1.0):
function gaussian_blur_2d (line 79) | def gaussian_blur_2d(img, kernel_size, sigma):
class SelfAttentionGuidance (line 98) | class SelfAttentionGuidance:
method INPUT_TYPES (line 100) | def INPUT_TYPES(s):
method patch (line 110) | def patch(self, model, scale, blur_sigma):
FILE: ldm_patched/contrib/external_sdupscale.py
class SD_4XUpscale_Conditioning (line 7) | class SD_4XUpscale_Conditioning:
method INPUT_TYPES (line 9) | def INPUT_TYPES(s):
method encode (line 23) | def encode(self, images, positive, negative, scale_ratio, noise_augmen...
FILE: ldm_patched/contrib/external_stable3d.py
function camera_embeddings (line 7) | def camera_embeddings(elevation, azimuth):
class StableZero123_Conditioning (line 25) | class StableZero123_Conditioning:
method INPUT_TYPES (line 27) | def INPUT_TYPES(s):
method encode (line 44) | def encode(self, clip_vision, init_image, vae, width, height, batch_si...
class StableZero123_Conditioning_Batched (line 58) | class StableZero123_Conditioning_Batched:
method INPUT_TYPES (line 60) | def INPUT_TYPES(s):
method encode (line 79) | def encode(self, clip_vision, init_image, vae, width, height, batch_si...
FILE: ldm_patched/contrib/external_tomesd.py
function do_nothing (line 9) | def do_nothing(x: torch.Tensor, mode:str=None):
function mps_gather_workaround (line 13) | def mps_gather_workaround(input, dim, index):
function bipartite_soft_matching_random2d (line 24) | def bipartite_soft_matching_random2d(metric: torch.Tensor,
function get_functions (line 129) | def get_functions(x, ratio, original_shape):
class TomePatchModel (line 150) | class TomePatchModel:
method INPUT_TYPES (line 152) | def INPUT_TYPES(s):
method patch (line 161) | def patch(self, model, ratio):
FILE: ldm_patched/contrib/external_upscale_model.py
class UpscaleModelLoader (line 10) | class UpscaleModelLoader:
method INPUT_TYPES (line 12) | def INPUT_TYPES(s):
method load_model (line 20) | def load_model(self, model_name):
class ImageUpscaleWithModel (line 29) | class ImageUpscaleWithModel:
method INPUT_TYPES (line 31) | def INPUT_TYPES(s):
method upscale (line 40) | def upscale(self, upscale_model, image):
FILE: ldm_patched/contrib/external_video_model.py
class ImageOnlyCheckpointLoader (line 11) | class ImageOnlyCheckpointLoader:
method INPUT_TYPES (line 13) | def INPUT_TYPES(s):
method load_checkpoint (line 21) | def load_checkpoint(self, ckpt_name, output_vae=True, output_clip=True):
class SVD_img2vid_Conditioning (line 27) | class SVD_img2vid_Conditioning:
method INPUT_TYPES (line 29) | def INPUT_TYPES(s):
method encode (line 47) | def encode(self, clip_vision, init_image, vae, width, height, video_fr...
class VideoLinearCFGGuidance (line 60) | class VideoLinearCFGGuidance:
method INPUT_TYPES (line 62) | def INPUT_TYPES(s):
method patch (line 71) | def patch(self, model, min_cfg):
class ImageOnlyCheckpointSave (line 84) | class ImageOnlyCheckpointSave(ldm_patched.contrib.external_model_merging...
method INPUT_TYPES (line 88) | def INPUT_TYPES(s):
method save (line 95) | def save(self, model, clip_vision, vae, filename_prefix, prompt=None, ...
FILE: ldm_patched/controlnet/cldm.py
class ControlledUnetModel (line 18) | class ControlledUnetModel(UNetModel):
class ControlNet (line 22) | class ControlNet(nn.Module):
method __init__ (line 23) | def __init__(
method make_zero_conv (line 282) | def make_zero_conv(self, channels, operations=None, dtype=None, device...
method forward (line 285) | def forward(self, x, hint, timesteps, context, y=None, **kwargs):
FILE: ldm_patched/k_diffusion/sampling.py
function append_zero (line 12) | def append_zero(x):
function get_sigmas_karras (line 16) | def get_sigmas_karras(n, sigma_min, sigma_max, rho=7., device='cpu'):
function get_sigmas_exponential (line 25) | def get_sigmas_exponential(n, sigma_min, sigma_max, device='cpu'):
function get_sigmas_polyexponential (line 31) | def get_sigmas_polyexponential(n, sigma_min, sigma_max, rho=1., device='...
function get_sigmas_vp (line 38) | def get_sigmas_vp(n, beta_d=19.9, beta_min=0.1, eps_s=1e-3, device='cpu'):
function to_d (line 45) | def to_d(x, sigma, denoised):
function get_ancestral_step (line 50) | def get_ancestral_step(sigma_from, sigma_to, eta=1.):
function default_noise_sampler (line 60) | def default_noise_sampler(x):
class BatchedBrownianTree (line 64) | class BatchedBrownianTree:
method __init__ (line 67) | def __init__(self, x, t0, t1, seed=None, **kwargs):
method sort (line 88) | def sort(a, b):
method __call__ (line 91) | def __call__(self, t0, t1):
class BrownianTreeNoiseSampler (line 101) | class BrownianTreeNoiseSampler:
method __init__ (line 116) | def __init__(self, x, sigma_min, sigma_max, seed=None, transform=lambd...
method __call__ (line 121) | def __call__(self, sigma, sigma_next):
function sample_euler (line 127) | def sample_euler(model, x, sigmas, extra_args=None, callback=None, disab...
function sample_euler_ancestral (line 148) | def sample_euler_ancestral(model, x, sigmas, extra_args=None, callback=N...
function sample_heun (line 168) | def sample_heun(model, x, sigmas, extra_args=None, callback=None, disabl...
function sample_dpm_2 (line 197) | def sample_dpm_2(model, x, sigmas, extra_args=None, callback=None, disab...
function sample_dpm_2_ancestral (line 228) | def sample_dpm_2_ancestral(model, x, sigmas, extra_args=None, callback=N...
function linear_multistep_coeff (line 256) | def linear_multistep_coeff(order, t, i, j):
function sample_lms (line 270) | def sample_lms(model, x, sigmas, extra_args=None, callback=None, disable...
class PIDStepSizeController (line 289) | class PIDStepSizeController:
method __init__ (line 291) | def __init__(self, h, pcoeff, icoeff, dcoeff, order=1, accept_safety=0...
method limiter (line 300) | def limiter(self, x):
method propose_step (line 303) | def propose_step(self, error):
class DPMSolver (line 318) | class DPMSolver(nn.Module):
method __init__ (line 321) | def __init__(self, model, extra_args=None, eps_callback=None, info_cal...
method t (line 328) | def t(self, sigma):
method sigma (line 331) | def sigma(self, t):
method eps (line 334) | def eps(self, eps_cache, key, x, t, *args, **kwargs):
method dpm_solver_1_step (line 343) | def dpm_solver_1_step(self, x, t, t_next, eps_cache=None):
method dpm_solver_2_step (line 350) | def dpm_solver_2_step(self, x, t, t_next, r1=1 / 2, eps_cache=None):
method dpm_solver_3_step (line 360) | def dpm_solver_3_step(self, x, t, t_next, r1=1 / 3, r2=2 / 3, eps_cach...
method dpm_solver_fast (line 373) | def dpm_solver_fast(self, x, t_start, t_end, nfe, eta=0., s_noise=1., ...
method dpm_solver_adaptive (line 412) | def dpm_solver_adaptive(self, x, t_start, t_end, order=3, rtol=0.05, a...
function sample_dpm_fast (line 467) | def sample_dpm_fast(model, x, sigma_min, sigma_max, n, extra_args=None, ...
function sample_dpm_adaptive (line 479) | def sample_dpm_adaptive(model, x, sigma_min, sigma_max, extra_args=None,...
function sample_dpmpp_2s_ancestral (line 494) | def sample_dpmpp_2s_ancestral(model, x, sigmas, extra_args=None, callbac...
function sample_dpmpp_sde (line 528) | def sample_dpmpp_sde(model, x, sigmas, extra_args=None, callback=None, d...
function sample_dpmpp_2m (line 571) | def sample_dpmpp_2m(model, x, sigmas, extra_args=None, callback=None, di...
function sample_dpmpp_2m_sde (line 596) | def sample_dpmpp_2m_sde(model, x, sigmas, extra_args=None, callback=None...
function sample_dpmpp_3m_sde (line 642) | def sample_dpmpp_3m_sde(model, x, sigmas, extra_args=None, callback=None...
function sample_dpmpp_3m_sde_gpu (line 692) | def sample_dpmpp_3m_sde_gpu(model, x, sigmas, extra_args=None, callback=...
function sample_dpmpp_2m_sde_gpu (line 698) | def sample_dpmpp_2m_sde_gpu(model, x, sigmas, extra_args=None, callback=...
function sample_dpmpp_sde_gpu (line 704) | def sample_dpmpp_sde_gpu(model, x, sigmas, extra_args=None, callback=Non...
function DDPMSampler_step (line 710) | def DDPMSampler_step(x, sigma, sigma_prev, noise, noise_sampler):
function generic_step_sampler (line 720) | def generic_step_sampler(model, x, sigmas, extra_args=None, callback=Non...
function sample_ddpm (line 736) | def sample_ddpm(model, x, sigmas, extra_args=None, callback=None, disabl...
function sample_lcm (line 740) | def sample_lcm(model, x, sigmas, extra_args=None, callback=None, disable...
function sample_heunpp2 (line 756) | def sample_heunpp2(model, x, sigmas, extra_args=None, callback=None, dis...
function sample_tcd (line 813) | def sample_tcd(model, x, sigmas, extra_args=None, callback=None, disable...
function sample_restart (line 842) | def sample_restart(model, x, sigmas, extra_args=None, callback=None, dis...
FILE: ldm_patched/k_diffusion/utils.py
function hf_datasets_augs_helper (line 15) | def hf_datasets_augs_helper(examples, transform, image_key, mode='RGB'):
function append_dims (line 21) | def append_dims(x, target_dims):
function n_params (line 32) | def n_params(module):
function download_file (line 37) | def download_file(path, url, digest=None):
function train_mode (line 52) | def train_mode(model, mode=True):
function eval_mode (line 63) | def eval_mode(model):
function ema_update (line 70) | def ema_update(model, averaged_model, decay):
class EMAWarmup (line 88) | class EMAWarmup:
method __init__ (line 104) | def __init__(self, inv_gamma=1., power=1., min_value=0., max_value=1.,...
method state_dict (line 113) | def state_dict(self):
method load_state_dict (line 117) | def load_state_dict(self, state_dict):
method get_value (line 125) | def get_value(self):
method step (line 131) | def step(self):
class InverseLR (line 136) | class InverseLR(optim.lr_scheduler._LRScheduler):
method __init__ (line 153) | def __init__(self, optimizer, inv_gamma=1., power=1., warmup=0., min_l...
method get_lr (line 163) | def get_lr(self):
method _get_closed_form_lr (line 170) | def _get_closed_form_lr(self):
class ExponentialLR (line 177) | class ExponentialLR(optim.lr_scheduler._LRScheduler):
method __init__ (line 194) | def __init__(self, optimizer, num_steps, decay=0.5, warmup=0., min_lr=0.,
method get_lr (line 204) | def get_lr(self):
method _get_closed_form_lr (line 211) | def _get_closed_form_lr(self):
function rand_log_normal (line 218) | def rand_log_normal(shape, loc=0., scale=1., device='cpu', dtype=torch.f...
function rand_log_logistic (line 223) | def rand_log_logistic(shape, loc=0., scale=1., min_value=0., max_value=f...
function rand_log_uniform (line 233) | def rand_log_uniform(shape, min_value, max_value, device='cpu', dtype=to...
function rand_v_diffusion (line 240) | def rand_v_diffusion(shape, sigma_data=1., min_value=0., max_value=float...
function rand_split_log_normal (line 248) | def rand_split_log_normal(shape, loc, scale_1, scale_2, device='cpu', dt...
class FolderOfImages (line 258) | class FolderOfImages(data.Dataset):
method __init__ (line 264) | def __init__(self, root, transform=None):
method __repr__ (line 270) | def __repr__(self):
method __len__ (line 273) | def __len__(self):
method __getitem__ (line 276) | def __getitem__(self, key):
class CSVLogger (line 284) | class CSVLogger:
method __init__ (line 285) | def __init__(self, filename, columns):
method write (line 294) | def write(self, *args):
function tf32_mode (line 299) | def tf32_mode(cudnn=None, matmul=None):
FILE: ldm_patched/ldm/models/autoencoder.py
class DiagonalGaussianRegularizer (line 13) | class DiagonalGaussianRegularizer(torch.nn.Module):
method __init__ (line 14) | def __init__(self, sample: bool = True):
method get_trainable_parameters (line 18) | def get_trainable_parameters(self) -> Any:
method forward (line 21) | def forward(self, z: torch.Tensor) -> Tuple[torch.Tensor, dict]:
class AbstractAutoencoder (line 34) | class AbstractAutoencoder(torch.nn.Module):
method __init__ (line 41) | def __init__(
method get_input (line 59) | def get_input(self, batch) -> Any:
method on_train_batch_end (line 62) | def on_train_batch_end(self, *args, **kwargs):
method ema_scope (line 68) | def ema_scope(self, context=None):
method encode (line 82) | def encode(self, *args, **kwargs) -> torch.Tensor:
method decode (line 85) | def decode(self, *args, **kwargs) -> torch.Tensor:
method instantiate_optimizer_from_config (line 88) | def instantiate_optimizer_from_config(self, params, lr, cfg):
method configure_optimizers (line 94) | def configure_optimizers(self) -> Any:
class AutoencodingEngine (line 98) | class AutoencodingEngine(AbstractAutoencoder):
method __init__ (line 105) | def __init__(
method get_last_layer (line 121) | def get_last_layer(self):
method encode (line 124) | def encode(
method decode (line 138) | def decode(self, z: torch.Tensor, **kwargs) -> torch.Tensor:
method forward (line 142) | def forward(
class AutoencodingEngineLegacy (line 150) | class AutoencodingEngineLegacy(AutoencodingEngine):
method __init__ (line 151) | def __init__(self, embed_dim: int, **kwargs):
method get_autoencoder_params (line 173) | def get_autoencoder_params(self) -> list:
method encode (line 177) | def encode(
method decode (line 199) | def decode(self, z: torch.Tensor, **decoder_kwargs) -> torch.Tensor:
class AutoencoderKL (line 217) | class AutoencoderKL(AutoencodingEngineLegacy):
method __init__ (line 218) | def __init__(self, **kwargs):
FILE: ldm_patched/ldm/modules/attention.py
function exists (line 29) | def exists(val):
function uniq (line 33) | def uniq(arr):
function default (line 37) | def default(val, d):
function max_neg_value (line 43) | def max_neg_value(t):
function init_ (line 47) | def init_(tensor):
class GEGLU (line 55) | class GEGLU(nn.Module):
method __init__ (line 56) | def __init__(self, dim_in, dim_out, dtype=None, device=None, operation...
method forward (line 60) | def forward(self, x):
class FeedForward (line 65) | class FeedForward(nn.Module):
method __init__ (line 66) | def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0., d...
method forward (line 81) | def forward(self, x):
function Normalize (line 84) | def Normalize(in_channels, dtype=None, device=None):
function attention_basic (line 87) | def attention_basic(q, k, v, heads, mask=None):
function attention_sub_quad (line 132) | def attention_sub_quad(query, key, value, heads, mask=None):
function attention_split (line 185) | def attention_split(q, k, v, heads, mask=None):
function attention_xformers (line 285) | def attention_xformers(q, k, v, heads, mask=None):
function attention_pytorch (line 317) | def attention_pytorch(q, k, v, heads, mask=None):
function optimized_attention_for_device (line 350) | def optimized_attention_for_device(device, mask=False, small_input=False):
class CrossAttention (line 366) | class CrossAttention(nn.Module):
method __init__ (line 367) | def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, ...
method forward (line 381) | def forward(self, x, context=None, value=None, mask=None):
class BasicTransformerBlock (line 398) | class BasicTransformerBlock(nn.Module):
method __init__ (line 399) | def __init__(self, dim, n_heads, d_head, dropout=0., context_dim=None,...
method forward (line 439) | def forward(self, x, context=None, transformer_options={}):
method _forward (line 442) | def _forward(self, x, context=None, transformer_options={}):
class SpatialTransformer (line 557) | class SpatialTransformer(nn.Module):
method __init__ (line 566) | def __init__(self, in_channels, n_heads, d_head,
method forward (line 599) | def forward(self, x, context=None, transformer_options={}):
class SpatialVideoTransformer (line 622) | class SpatialVideoTransformer(SpatialTransformer):
method __init__ (line 623) | def __init__(
method forward (line 706) | def forward(
FILE: ldm_patched/ldm/modules/diffusionmodules/model.py
function get_timestep_embedding (line 17) | def get_timestep_embedding(timesteps, embedding_dim):
function nonlinearity (line 38) | def nonlinearity(x):
function Normalize (line 43) | def Normalize(in_channels, num_groups=32):
class Upsample (line 47) | class Upsample(nn.Module):
method __init__ (line 48) | def __init__(self, in_channels, with_conv):
method forward (line 58) | def forward(self, x):
class Downsample (line 76) | class Downsample(nn.Module):
method __init__ (line 77) | def __init__(self, in_channels, with_conv):
method forward (line 88) | def forward(self, x):
class ResnetBlock (line 98) | class ResnetBlock(nn.Module):
method __init__ (line 99) | def __init__(self, *, in_channels, out_channels=None, conv_shortcut=Fa...
method forward (line 138) | def forward(self, x, temb):
function slice_attention (line 160) | def slice_attention(q, k, v):
function normal_attention (line 197) | def normal_attention(q, k, v):
function xformers_attention (line 211) | def xformers_attention(q, k, v):
function pytorch_attention (line 226) | def pytorch_attention(q, k, v):
class AttnBlock (line 243) | class AttnBlock(nn.Module):
method __init__ (line 244) | def __init__(self, in_channels):
method forward (line 280) | def forward(self, x):
function make_attn (line 294) | def make_attn(in_channels, attn_type="vanilla", attn_kwargs=None):
class Model (line 298) | class Model(nn.Module):
method __init__ (line 299) | def __init__(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks,
method forward (line 398) | def forward(self, x, t=None, context=None):
method get_last_layer (line 446) | def get_last_layer(self):
class Encoder (line 450) | class Encoder(nn.Module):
method __init__ (line 451) | def __init__(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks,
method forward (line 516) | def forward(self, x):
class Decoder (line 541) | class Decoder(nn.Module):
method __init__ (line 542) | def __init__(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks,
method forward (line 617) | def forward(self, z, **kwargs):
FILE: ldm_patched/ldm/modules/diffusionmodules/openaimodel.py
class TimestepBlock (line 20) | class TimestepBlock(nn.Module):
method forward (line 26) | def forward(self, x, emb):
function forward_timestep_embed (line 32) | def forward_timestep_embed(ts, x, emb, context=None, transformer_options...
class TimestepEmbedSequential (line 52) | class TimestepEmbedSequential(nn.Sequential, TimestepBlock):
method forward (line 58) | def forward(self, *args, **kwargs):
class Upsample (line 61) | class Upsample(nn.Module):
method __init__ (line 70) | def __init__(self, channels, use_conv, dims=2, out_channels=None, padd...
method forward (line 79) | def forward(self, x, output_shape=None):
class Downsample (line 97) | class Downsample(nn.Module):
method __init__ (line 106) | def __init__(self, channels, use_conv, dims=2, out_channels=None, padd...
method forward (line 121) | def forward(self, x):
class ResBlock (line 126) | class ResBlock(TimestepBlock):
method __init__ (line 142) | def __init__(
method forward (line 222) | def forward(self, x, emb):
method _forward (line 234) | def _forward(self, x, emb):
class VideoResBlock (line 266) | class VideoResBlock(ResBlock):
method __init__ (line 267) | def __init__(
method forward (line 325) | def forward(
class Timestep (line 347) | class Timestep(nn.Module):
method __init__ (line 348) | def __init__(self, dim):
method forward (line 352) | def forward(self, t):
function apply_control (line 355) | def apply_control(h, control, name):
class UNetModel (line 365) | class UNetModel(nn.Module):
method __init__ (line 391) | def __init__(
method forward (line 816) | def forward(self, x, timesteps=None, context=None, y=None, control=Non...
FILE: ldm_patched/ldm/modules/diffusionmodules/upscaling.py
class AbstractLowScaleModel (line 10) | class AbstractLowScaleModel(nn.Module):
method __init__ (line 12) | def __init__(self, noise_schedule_config=None):
method register_schedule (line 17) | def register_schedule(self, beta_schedule="linear", timesteps=1000,
method q_sample (line 44) | def q_sample(self, x_start, t, noise=None, seed=None):
method forward (line 53) | def forward(self, x):
method decode (line 56) | def decode(self, x):
class SimpleImageConcat (line 60) | class SimpleImageConcat(AbstractLowScaleModel):
method __init__ (line 62) | def __init__(self):
method forward (line 66) | def forward(self, x):
class ImageConcatWithNoiseAugmentation (line 71) | class ImageConcatWithNoiseAugmentation(AbstractLowScaleModel):
method __init__ (line 72) | def __init__(self, noise_schedule_config, max_noise_level=1000, to_cud...
method forward (line 76) | def forward(self, x, noise_level=None, seed=None):
FILE: ldm_patched/ldm/modules/diffusionmodules/util.py
class AlphaBlender (line 20) | class AlphaBlender(nn.Module):
method __init__ (line 23) | def __init__(
method get_alpha (line 49) | def get_alpha(self, image_only_indicator: torch.Tensor) -> torch.Tensor:
method forward (line 73) | def forward(
function make_beta_schedule (line 87) | def make_beta_schedule(schedule, n_timestep, linear_start=1e-4, linear_e...
function make_ddim_timesteps (line 119) | def make_ddim_timesteps(ddim_discr_method, num_ddim_timesteps, num_ddpm_...
function make_ddim_sampling_parameters (line 136) | def make_ddim_sampling_parameters(alphacums, ddim_timesteps, eta, verbos...
function betas_for_alpha_bar (line 150) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
function extract_into_tensor (line 169) | def extract_into_tensor(a, t, x_shape):
function checkpoint (line 175) | def checkpoint(func, inputs, params, flag):
class CheckpointFunction (line 192) | class CheckpointFunction(torch.autograd.Function):
method forward (line 194) | def forward(ctx, run_function, length, *args):
method backward (line 206) | def backward(ctx, *output_grads):
function timestep_embedding (line 227) | def timestep_embedding(timesteps, dim, max_period=10000, repeat_only=Fal...
function zero_module (line 250) | def zero_module(module):
function scale_module (line 259) | def scale_module(module, scale):
function mean_flat (line 268) | def mean_flat(tensor):
function avg_pool_nd (line 275) | def avg_pool_nd(dims, *args, **kwargs):
class HybridConditioner (line 288) | class HybridConditioner(nn.Module):
method __init__ (line 290) | def __init__(self, c_concat_config, c_crossattn_config):
method forward (line 295) | def forward(self, c_concat, c_crossattn):
function noise_like (line 301) | def noise_like(shape, device, repeat=False):
FILE: ldm_patched/ldm/modules/distributions/distributions.py
class AbstractDistribution (line 5) | class AbstractDistribution:
method sample (line 6) | def sample(self):
method mode (line 9) | def mode(self):
class DiracDistribution (line 13) | class DiracDistribution(AbstractDistribution):
method __init__ (line 14) | def __init__(self, value):
method sample (line 17) | def sample(self):
method mode (line 20) | def mode(self):
class DiagonalGaussianDistribution (line 24) | class DiagonalGaussianDistribution(object):
method __init__ (line 25) | def __init__(self, parameters, deterministic=False):
method sample (line 35) | def sample(self):
method kl (line 39) | def kl(self, other=None):
method nll (line 53) | def nll(self, sample, dims=[1,2,3]):
method mode (line 61) | def mode(self):
function normal_kl (line 65) | def normal_kl(mean1, logvar1, mean2, logvar2):
FILE: ldm_patched/ldm/modules/ema.py
class LitEma (line 5) | class LitEma(nn.Module):
method __init__ (line 6) | def __init__(self, model, decay=0.9999, use_num_upates=True):
method reset_num_updates (line 25) | def reset_num_updates(self):
method forward (line 29) | def forward(self, model):
method copy_to (line 50) | def copy_to(self, model):
method store (line 59) | def store(self, parameters):
method restore (line 68) | def restore(self, parameters):
FILE: ldm_patched/ldm/modules/encoders/noise_aug_modules.py
class CLIPEmbeddingNoiseAugmentation (line 5) | class CLIPEmbeddingNoiseAugmentation(ImageConcatWithNoiseAugmentation):
method __init__ (line 6) | def __init__(self, *args, clip_stats_path=None, timestep_dim=256, **kw...
method scale (line 16) | def scale(self, x):
method unscale (line 21) | def unscale(self, x):
method forward (line 26) | def forward(self, x, noise_level=None, seed=None):
FILE: ldm_patched/ldm/modules/sub_quadratic_attention.py
function dynamic_slice (line 29) | def dynamic_slice(
class AttnChunk (line 37) | class AttnChunk(NamedTuple):
class SummarizeChunk (line 42) | class SummarizeChunk(Protocol):
method __call__ (line 44) | def __call__(
class ComputeQueryChunkAttn (line 50) | class ComputeQueryChunkAttn(Protocol):
method __call__ (line 52) | def __call__(
function _summarize_chunk (line 58) | def _summarize_chunk(
function _query_chunk_attention (line 96) | def _query_chunk_attention(
function _get_attention_scores_no_kv_chunking (line 139) | def _get_attention_scores_no_kv_chunking(
class ScannedChunk (line 183) | class ScannedChunk(NamedTuple):
function efficient_dot_product_attention (line 187) | def efficient_dot_product_attention(
FILE: ldm_patched/ldm/modules/temporal_ae.py
function partialclass (line 18) | def partialclass(cls, *args, **kwargs):
class VideoResBlock (line 25) | class VideoResBlock(ResnetBlock):
method __init__ (line 26) | def __init__(
method get_alpha (line 63) | def get_alpha(self, bs):
method forward (line 71) | def forward(self, x, temb, skip_video=False, timesteps=None):
class AE3DConv (line 92) | class AE3DConv(ops.Conv2d):
method __init__ (line 93) | def __init__(self, in_channels, out_channels, video_kernel_size=3, *ar...
method forward (line 107) | def forward(self, input, timesteps=None, skip_video=False):
class AttnVideoBlock (line 118) | class AttnVideoBlock(AttnBlock):
method __init__ (line 119) | def __init__(
method forward (line 149) | def forward(self, x, timesteps=None, skip_time_block=False):
method get_alpha (line 179) | def get_alpha(
function make_time_attn (line 191) | def make_time_attn(
class Conv2DWrapper (line 203) | class Conv2DWrapper(torch.nn.Conv2d):
method forward (line 204) | def forward(self, input: torch.Tensor, **kwargs) -> torch.Tensor:
class VideoDecoder (line 208) | class VideoDecoder(Decoder):
method __init__ (line 211) | def __init__(
method get_last_layer (line 237) | def get_last_layer(self, skip_time_mix=False, **kwargs):
FILE: ldm_patched/ldm/util.py
function log_txt_as_img (line 11) | def log_txt_as_img(wh, xc, size=10):
function ismap (line 35) | def ismap(x):
function isimage (line 41) | def isimage(x):
function exists (line 47) | def exists(x):
function default (line 51) | def default(val, d):
function mean_flat (line 57) | def mean_flat(tensor):
function count_params (line 65) | def count_params(model, verbose=False):
function instantiate_from_config (line 72) | def instantiate_from_config(config):
function get_obj_from_str (line 82) | def get_obj_from_str(string, reload=False):
class AdamWwithEMAandWings (line 90) | class AdamWwithEMAandWings(optim.Optimizer):
method __init__ (line 92) | def __init__(self, params, lr=1.e-3, betas=(0.9, 0.999), eps=1.e-8, #...
method __setstate__ (line 113) | def __setstate__(self, state):
method step (line 119) | def step(self, closure=None):
FILE: ldm_patched/modules/args_parser.py
class EnumAction (line 5) | class EnumAction(argparse.Action):
method __init__ (line 9) | def __init__(self, **kwargs):
method __call__ (line 28) | def __call__(self, parser, namespace, values, option_string=None):
class LatentPreviewMethod (line 83) | class LatentPreviewMethod(enum.Enum):
FILE: ldm_patched/modules/checkpoint_pickle.py
class Empty (line 5) | class Empty:
class Unpickler (line 8) | class Unpickler(pickle.Unpickler):
method find_class (line 9) | def find_class(self, module, name):
FILE: ldm_patched/modules/clip_model.py
class CLIPAttention (line 4) | class CLIPAttention(torch.nn.Module):
method __init__ (line 5) | def __init__(self, embed_dim, heads, dtype, device, operations):
method forward (line 15) | def forward(self, x, mask=None, optimized_attention=None):
class CLIPMLP (line 27) | class CLIPMLP(torch.nn.Module):
method __init__ (line 28) | def __init__(self, embed_dim, intermediate_size, activation, dtype, de...
method forward (line 34) | def forward(self, x):
class CLIPLayer (line 40) | class CLIPLayer(torch.nn.Module):
method __init__ (line 41) | def __init__(self, embed_dim, heads, intermediate_size, intermediate_a...
method forward (line 48) | def forward(self, x, mask=None, optimized_attention=None):
class CLIPEncoder (line 54) | class CLIPEncoder(torch.nn.Module):
method __init__ (line 55) | def __init__(self, num_layers, embed_dim, heads, intermediate_size, in...
method forward (line 59) | def forward(self, x, mask=None, intermediate_output=None):
class CLIPEmbeddings (line 73) | class CLIPEmbeddings(torch.nn.Module):
method __init__ (line 74) | def __init__(self, embed_dim, vocab_size=49408, num_positions=77, dtyp...
method forward (line 79) | def forward(self, input_tokens):
class CLIPTextModel_ (line 83) | class CLIPTextModel_(torch.nn.Module):
method __init__ (line 84) | def __init__(self, config_dict, dtype, device, operations):
method forward (line 96) | def forward(self, input_tokens, attention_mask=None, intermediate_outp...
class CLIPTextModel (line 117) | class CLIPTextModel(torch.nn.Module):
method __init__ (line 118) | def __init__(self, config_dict, dtype, device, operations):
method get_input_embeddings (line 124) | def get_input_embeddings(self):
method set_input_embeddings (line 127) | def set_input_embeddings(self, embeddings):
method forward (line 130) | def forward(self, *args, **kwargs):
class CLIPVisionEmbeddings (line 133) | class CLIPVisionEmbeddings(torch.nn.Module):
method __init__ (line 134) | def __init__(self, embed_dim, num_channels=3, patch_size=14, image_siz...
method forward (line 152) | def forward(self, pixel_values):
class CLIPVision (line 157) | class CLIPVision(torch.nn.Module):
method __init__ (line 158) | def __init__(self, config_dict, dtype, device, operations):
method forward (line 171) | def forward(self, pixel_values, attention_mask=None, intermediate_outp...
class CLIPVisionModelProjection (line 179) | class CLIPVisionModelProjection(torch.nn.Module):
method __init__ (line 180) | def __init__(self, config_dict, dtype, device, operations):
method forward (line 185) | def forward(self, *args, **kwargs):
FILE: ldm_patched/modules/clip_vision.py
class Output (line 12) | class Output:
method __getitem__ (line 13) | def __getitem__(self, key):
method __setitem__ (line 15) | def __setitem__(self, key, item):
function clip_preprocess (line 18) | def clip_preprocess(image, size=224):
class ClipVisionModel (line 31) | class ClipVisionModel():
method __init__ (line 32) | def __init__(self, json_config):
method load_sd (line 44) | def load_sd(self, sd):
method get_sd (line 47) | def get_sd(self):
method encode_image (line 50) | def encode_image(self, image):
function convert_to_transformers (line 61) | def convert_to_transformers(sd, prefix):
function load_clipvision_from_sd (line 87) | def load_clipvision_from_sd(sd, prefix="", convert_keys=False):
function load (line 111) | def load(ckpt_path):
FILE: ldm_patched/modules/conds.py
class CONDRegular (line 7) | class CONDRegular:
method __init__ (line 8) | def __init__(self, cond):
method _copy_with (line 11) | def _copy_with(self, cond):
method process_cond (line 14) | def process_cond(self, batch_size, device, **kwargs):
method can_concat (line 17) | def can_concat(self, other):
method concat (line 22) | def concat(self, others):
class CONDNoiseShape (line 28) | class CONDNoiseShape(CONDRegular):
method process_cond (line 29) | def process_cond(self, batch_size, device, area, **kwargs):
class CONDCrossAttn (line 34) | class CONDCrossAttn(CONDRegular):
method can_concat (line 35) | def can_concat(self, other):
method concat (line 48) | def concat(self, others):
class CONDConstant (line 63) | class CONDConstant(CONDRegular):
method __init__ (line 64) | def __init__(self, cond):
method process_cond (line 67) | def process_cond(self, batch_size, device, **kwargs):
method can_concat (line 70) | def can_concat(self, other):
method concat (line 75) | def concat(self, others):
FILE: ldm_patched/modules/controlnet.py
function broadcast_image_to (line 14) | def broadcast_image_to(tensor, target_batch_size, batched_number):
class ControlBase (line 32) | class ControlBase:
method __init__ (line 33) | def __init__(self, device=None):
method set_cond_hint (line 46) | def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_rang...
method pre_run (line 52) | def pre_run(self, model, percent_to_timestep_function):
method set_previous_controlnet (line 57) | def set_previous_controlnet(self, controlnet):
method cleanup (line 61) | def cleanup(self):
method get_models (line 69) | def get_models(self):
method copy_to (line 75) | def copy_to(self, c):
method inference_memory_requirements (line 81) | def inference_memory_requirements(self, dtype):
method control_merge (line 86) | def control_merge(self, control_input, control_output, control_prev, o...
class ControlNet (line 134) | class ControlNet(ControlBase):
method __init__ (line 135) | def __init__(self, control_model, global_average_pooling=False, device...
method get_control (line 144) | def get_control(self, x_noisy, t, cond, batched_number):
method copy (line 179) | def copy(self):
method get_models (line 184) | def get_models(self):
method pre_run (line 189) | def pre_run(self, model, percent_to_timestep_function):
method cleanup (line 193) | def cleanup(self):
class ControlLoraOps (line 197) | class ControlLoraOps:
class Linear (line 198) | class Linear(torch.nn.Module):
method __init__ (line 199) | def __init__(self, in_features: int, out_features: int, bias: bool =...
method forward (line 210) | def forward(self, input):
class Conv2d (line 217) | class Conv2d(torch.nn.Module):
method __init__ (line 218) | def __init__(
method forward (line 250) | def forward(self, input):
class ControlLora (line 258) | class ControlLora(ControlNet):
method __init__ (line 259) | def __init__(self, control_weights, global_average_pooling=False, devi...
method pre_run (line 264) | def pre_run(self, model, percent_to_timestep_function):
method copy (line 298) | def copy(self):
method cleanup (line 303) | def cleanup(self):
method get_models (line 308) | def get_models(self):
method inference_memory_requirements (line 312) | def inference_memory_requirements(self, dtype):
function load_controlnet (line 315) | def load_controlnet(ckpt_path, model=None):
class T2IAdapter (line 425) | class T2IAdapter(ControlBase):
method __init__ (line 426) | def __init__(self, t2i_model, channels_in, device=None):
method scale_image_to (line 432) | def scale_image_to(self, width, height):
method get_control (line 438) | def get_control(self, x_noisy, t, cond, batched_number):
method copy (line 474) | def copy(self):
function load_t2i_adapter (line 479) | def load_t2i_adapter(t2i_data):
FILE: ldm_patched/modules/diffusers_convert.py
function convert_unet_state_dict (line 85) | def convert_unet_state_dict(unet_state_dict):
function reshape_weight_for_sd (line 159) | def reshape_weight_for_sd(w):
function convert_vae_state_dict (line 164) | def convert_vae_state_dict(vae_state_dict):
function convert_text_enc_state_dict_v20 (line 209) | def convert_text_enc_state_dict_v20(text_enc_dict, prefix=""):
function convert_text_enc_state_dict (line 258) | def convert_text_enc_state_dict(text_enc_dict):
FILE: ldm_patched/modules/diffusers_load.py
function first_file (line 5) | def first_file(path, filenames):
function load_diffusers (line 12) | def load_diffusers(model_path, output_vae=True, output_clip=True, embedd...
FILE: ldm_patched/modules/gligen.py
function exists (line 7) | def exists(val):
function uniq (line 11) | def uniq(arr):
function default (line 15) | def default(val, d):
class GEGLU (line 22) | class GEGLU(nn.Module):
method __init__ (line 23) | def __init__(self, dim_in, dim_out):
method forward (line 27) | def forward(self, x):
class FeedForward (line 32) | class FeedForward(nn.Module):
method __init__ (line 33) | def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.):
method forward (line 48) | def forward(self, x):
class GatedCrossAttentionDense (line 52) | class GatedCrossAttentionDense(nn.Module):
method __init__ (line 53) | def __init__(self, query_dim, context_dim, n_heads, d_head):
method forward (line 74) | def forward(self, x, objs):
class GatedSelfAttentionDense (line 84) | class GatedSelfAttentionDense(nn.Module):
method __init__ (line 85) | def __init__(self, query_dim, context_dim, n_heads, d_head):
method forward (line 110) | def forward(self, x, objs):
class GatedSelfAttentionDense2 (line 123) | class GatedSelfAttentionDense2(nn.Module):
method __init__ (line 124) | def __init__(self, query_dim, context_dim, n_heads, d_head):
method forward (line 146) | def forward(self, x, objs):
class FourierEmbedder (line 177) | class FourierEmbedder():
method __init__ (line 178) | def __init__(self, num_freqs=64, temperature=100):
method __call__ (line 185) | def __call__(self, x, cat_dim=-1):
class PositionNet (line 194) | class PositionNet(nn.Module):
method __init__ (line 195) | def __init__(self, in_dim, out_dim, fourier_freqs=8):
method forward (line 216) | def forward(self, boxes, masks, positive_embeddings):
class Gligen (line 240) | class Gligen(nn.Module):
method __init__ (line 241) | def __init__(self, modules, position_net, key_dim):
method _set_position (line 249) | def _set_position(self, boxes, masks, positive_embeddings):
method set_position (line 257) | def set_position(self, latent_image_shape, position_params, device):
method set_empty (line 288) | def set_empty(self, latent_image_shape, device):
function load_gligen (line 301) | def load_gligen(sd):
FILE: ldm_patched/modules/latent_formats.py
class LatentFormat (line 3) | class LatentFormat:
method process_in (line 8) | def process_in(self, latent):
method process_out (line 11) | def process_out(self, latent):
class SD15 (line 14) | class SD15(LatentFormat):
method __init__ (line 15) | def __init__(self, scale_factor=0.18215):
class SDXL (line 26) | class SDXL(LatentFormat):
method __init__ (line 27) | def __init__(self):
class SDXL_Playground_2_5 (line 38) | class SDXL_Playground_2_5(LatentFormat):
method __init__ (line 39) | def __init__(self):
method process_in (line 53) | def process_in(self, latent):
method process_out (line 58) | def process_out(self, latent):
class SD_X4 (line 64) | class SD_X4(LatentFormat):
method __init__ (line 65) | def __init__(self):
class SC_Prior (line 74) | class SC_Prior(LatentFormat):
method __init__ (line 75) | def __init__(self):
class SC_B (line 96) | class SC_B(LatentFormat):
method __init__ (line 97) | def __init__(self):
FILE: ldm_patched/modules/lora.py
function load_lora (line 13) | def load_lora(lora, to_load):
function model_lora_keys_clip (line 162) | def model_lora_keys_clip(model, key_map={}):
function model_lora_keys_unet (line 203) | def model_lora_keys_unet(model, key_map={}):
FILE: ldm_patched/modules/model_base.py
class ModelType (line 11) | class ModelType(Enum):
function model_sampling (line 20) | def model_sampling(model_config, model_type):
class BaseModel (line 37) | class BaseModel(torch.nn.Module):
method __init__ (line 38) | def __init__(self, model_config, model_type=ModelType.EPS, device=None):
method apply_model (line 62) | def apply_model(self, x, t, c_concat=None, c_crossattn=None, control=N...
method get_dtype (line 88) | def get_dtype(self):
method is_adm (line 91) | def is_adm(self):
method encode_adm (line 94) | def encode_adm(self, **kwargs):
method extra_conds (line 97) | def extra_conds(self, **kwargs):
method load_model_weights (line 158) | def load_model_weights(self, sd, unet_prefix=""):
method process_latent_in (line 175) | def process_latent_in(self, latent):
method process_latent_out (line 178) | def process_latent_out(self, latent):
method state_dict_for_saving (line 181) | def state_dict_for_saving(self, clip_state_dict=None, vae_state_dict=N...
method set_inpaint (line 204) | def set_inpaint(self):
method memory_required (line 207) | def memory_required(self, input_shape):
function unclip_adm (line 221) | def unclip_adm(unclip_conditioning, device, noise_augmentor, noise_augme...
class SD21UNCLIP (line 245) | class SD21UNCLIP(BaseModel):
method __init__ (line 246) | def __init__(self, model_config, noise_aug_config, model_type=ModelTyp...
method encode_adm (line 250) | def encode_adm(self, **kwargs):
function sdxl_pooled (line 258) | def sdxl_pooled(args, noise_augmentor):
class SDXLRefiner (line 264) | class SDXLRefiner(BaseModel):
method __init__ (line 265) | def __init__(self, model_config, model_type=ModelType.EPS, device=None):
method encode_adm (line 270) | def encode_adm(self, **kwargs):
class SDXL (line 291) | class SDXL(BaseModel):
method __init__ (line 292) | def __init__(self, model_config, model_type=ModelType.EPS, device=None):
method encode_adm (line 297) | def encode_adm(self, **kwargs):
class SVD_img2vid (line 316) | class SVD_img2vid(BaseModel):
method __init__ (line 317) | def __init__(self, model_config, model_type=ModelType.V_PREDICTION_EDM...
method encode_adm (line 321) | def encode_adm(self, **kwargs):
method extra_conds (line 334) | def extra_conds(self, **kwargs):
class Stable_Zero123 (line 365) | class Stable_Zero123(BaseModel):
method __init__ (line 366) | def __init__(self, model_config, model_type=ModelType.EPS, device=None...
method extra_conds (line 372) | def extra_conds(self, **kwargs):
class SD_X4Upscaler (line 395) | class SD_X4Upscaler(BaseModel):
method __init__ (line 396) | def __init__(self, model_config, model_type=ModelType.V_PREDICTION, de...
method extra_conds (line 400) | def extra_conds(self, **kwargs):
FILE: ldm_patched/modules/model_detection.py
function count_blocks (line 4) | def count_blocks(state_dict_keys, prefix_string):
function calculate_transformer_depth (line 17) | def calculate_transformer_depth(prefix, state_dict_keys, state_dict):
function detect_unet_config (line 31) | def detect_unet_config(state_dict, key_prefix, dtype):
function model_config_from_unet_config (line 154) | def model_config_from_unet_config(unet_config):
function model_config_from_unet (line 162) | def model_config_from_unet(state_dict, unet_key_prefix, dtype, use_base_...
function convert_config (line 170) | def convert_config(unet_config):
function unet_config_from_diffusers_unet (line 209) | def unet_config_from_diffusers_unet(state_dict, dtype):
function model_config_from_diffusers_unet (line 316) | def model_config_from_diffusers_unet(state_dict, dtype):
FILE: ldm_patched/modules/model_management.py
class VRAMState (line 8) | class VRAMState(Enum):
class CPUState (line 16) | class CPUState(Enum):
function is_intel_xpu (line 68) | def is_intel_xpu():
function get_torch_device (line 76) | def get_torch_device():
function get_total_memory (line 92) | def get_total_memory(dev=None, torch_total_too=False):
function is_nvidia (line 161) | def is_nvidia():
function get_torch_device_name (line 244) | def get_torch_device_name(device):
function module_size (line 268) | def module_size(module):
class LoadedModel (line 276) | class LoadedModel:
method __init__ (line 277) | def __init__(self, model):
method model_memory (line 282) | def model_memory(self):
method model_memory_required (line 285) | def model_memory_required(self, device):
method model_load (line 291) | def model_load(self, lowvram_model_memory=0):
method model_unload (line 329) | def model_unload(self):
method __eq__ (line 341) | def __eq__(self, other):
function minimum_inference_memory (line 344) | def minimum_inference_memory():
function unload_model_clones (line 347) | def unload_model_clones(model):
function free_memory (line 357) | def free_memory(memory_required, device, keep_loaded=[]):
function load_models_gpu (line 379) | def load_models_gpu(models, memory_required=0):
function load_model_gpu (line 442) | def load_model_gpu(model):
function cleanup_models (line 445) | def cleanup_models():
function dtype_size (line 456) | def dtype_size(dtype):
function unet_offload_device (line 469) | def unet_offload_device():
function unet_inital_load_device (line 475) | def unet_inital_load_device(parameters, dtype):
function unet_dtype (line 493) | def unet_dtype(device=None, model_params=0):
function unet_manual_cast (line 507) | def unet_manual_cast(weight_dtype, inference_device):
function text_encoder_offload_device (line 520) | def text_encoder_offload_device():
function text_encoder_device (line 526) | def text_encoder_device():
function text_encoder_dtype (line 539) | def text_encoder_dtype(device=None):
function intermediate_device (line 557) | def intermediate_device():
function vae_device (line 563) | def vae_device():
function vae_offload_device (line 568) | def vae_offload_device():
function vae_dtype (line 574) | def vae_dtype():
function get_autocast_device (line 578) | def get_autocast_device(dev):
function supports_dtype (line 583) | def supports_dtype(device, dtype): #TODO
function device_supports_non_blocking (line 594) | def device_supports_non_blocking(device):
function cast_to_device (line 599) | def cast_to_device(tensor, device, dtype, copy=False):
function xformers_enabled (line 621) | def xformers_enabled():
function xformers_enabled_vae (line 633) | def xformers_enabled_vae():
function pytorch_attention_enabled (line 640) | def pytorch_attention_enabled():
function pytorch_attention_flash_attention (line 644) | def pytorch_attention_flash_attention():
function get_free_memory (line 652) | def get_free_memory(dev=None, torch_free_too=False):
function cpu_mode (line 684) | def cpu_mode():
function mps_mode (line 688) | def mps_mode():
function is_device_cpu (line 692) | def is_device_cpu(device):
function is_device_mps (line 698) | def is_device_mps(device):
function should_use_fp16 (line 704) | def should_use_fp16(device=None, model_params=0, prioritize_performance=...
function soft_empty_cache (line 762) | def soft_empty_cache(force=False):
function unload_all_models (line 773) | def unload_all_models():
function resolve_lowvram_weight (line 777) | def resolve_lowvram_weight(weight, model, key): #TODO: remove
class InterruptProcessingException (line 783) | class InterruptProcessingException(Exception):
function interrupt_current_processing (line 789) | def interrupt_current_processing(value=True):
function processing_interrupted (line 795) | def processing_interrupted():
function throw_exception_if_processing_interrupted (line 801) | def throw_exception_if_processing_interrupted():
FILE: ldm_patched/modules/model_patcher.py
class ModelPatcher (line 8) | class ModelPatcher:
method __init__ (line 9) | def __init__(self, model, load_device, offload_device, size=0, current...
method model_size (line 27) | def model_size(self):
method clone (line 35) | def clone(self):
method is_clone (line 46) | def is_clone(self, other):
method memory_required (line 51) | def memory_required(self, input_shape):
method set_model_sampler_cfg_function (line 54) | def set_model_sampler_cfg_function(self, sampler_cfg_function, disable...
method set_model_sampler_post_cfg_function (line 62) | def set_model_sampler_post_cfg_function(self, post_cfg_function, disab...
method set_model_unet_function_wrapper (line 67) | def set_model_unet_function_wrapper(self, unet_wrapper_function):
method set_model_patch (line 70) | def set_model_patch(self, patch, name):
method set_model_patch_replace (line 76) | def set_model_patch_replace(self, patch, name, block_name, number, tra...
method set_model_attn1_patch (line 88) | def set_model_attn1_patch(self, patch):
method set_model_attn2_patch (line 91) | def set_model_attn2_patch(self, patch):
method set_model_attn1_replace (line 94) | def set_model_attn1_replace(self, patch, block_name, number, transform...
method set_model_attn2_replace (line 97) | def set_model_attn2_replace(self, patch, block_name, number, transform...
method set_model_attn1_output_patch (line 100) | def set_model_attn1_output_patch(self, patch):
method set_model_attn2_output_patch (line 103) | def set_model_attn2_output_patch(self, patch):
method set_model_input_block_patch (line 106) | def set_model_input_block_patch(self, patch):
method set_model_input_block_patch_after_skip (line 109) | def set_model_input_block_patch_after_skip(self, patch):
method set_model_output_block_patch (line 112) | def set_model_output_block_patch(self, patch):
method add_object_patch (line 115) | def add_object_patch(self, name, obj):
method model_patches_to (line 118) | def model_patches_to(self, device):
method model_dtype (line 139) | def model_dtype(self):
method add_patches (line 143) | def add_patches(self, patches, strength_patch=1.0, strength_model=1.0):
method get_key_patches (line 154) | def get_key_patches(self, filter_prefix=None):
method model_state_dict (line 168) | def model_state_dict(self, filter_prefix=None):
method patch_model (line 177) | def patch_model(self, device_to=None, patch_weights=True):
method calculate_weight (line 215) | def calculate_weight(self, patches, weight, key):
method unpatch_model (line 337) | def unpatch_model(self, device_to=None):
FILE: ldm_patched/modules/model_sampling.py
class EPS (line 6) | class EPS:
method calculate_input (line 7) | def calculate_input(self, sigma, noise):
method calculate_denoised (line 11) | def calculate_denoised(self, sigma, model_output, model_input):
method noise_scaling (line 15) | def noise_scaling(self, sigma, noise, latent_image, max_denoise=False):
method inverse_noise_scaling (line 24) | def inverse_noise_scaling(self, sigma, latent):
class V_PREDICTION (line 27) | class V_PREDICTION(EPS):
method calculate_denoised (line 28) | def calculate_denoised(self, sigma, model_output, model_input):
class EDM (line 32) | class EDM(V_PREDICTION):
method calculate_denoised (line 33) | def calculate_denoised(self, sigma, model_output, model_input):
class ModelSamplingDiscrete (line 38) | class ModelSamplingDiscrete(torch.nn.Module):
method __init__ (line 39) | def __init__(self, model_config=None):
method _register_schedule (line 54) | def _register_schedule(self, given_betas=None, beta_schedule="linear",...
method set_sigmas (line 77) | def set_sigmas(self, sigmas):
method set_alphas_cumprod (line 81) | def set_alphas_cumprod(self, alphas_cumprod):
method sigma_min (line 85) | def sigma_min(self):
method sigma_max (line 89) | def sigma_max(self):
method timestep (line 92) | def timestep(self, sigma):
method sigma (line 97) | def sigma(self, timestep):
method percent_to_sigma (line 105) | def percent_to_sigma(self, percent):
class ModelSamplingContinuousEDM (line 114) | class ModelSamplingContinuousEDM(torch.nn.Module):
method __init__ (line 115) | def __init__(self, model_config=None):
method set_parameters (line 127) | def set_parameters(self, sigma_min, sigma_max, sigma_data):
method sigma_min (line 135) | def sigma_min(self):
method sigma_max (line 139) | def sigma_max(self):
method timestep (line 142) | def timestep(self, sigma):
method sigma (line 145) | def sigma(self, timestep):
method percent_to_sigma (line 148) | def percent_to_sigma(self, percent):
class StableCascadeSampling (line 158) | class StableCascadeSampling(ModelSamplingDiscrete):
method __init__ (line 159) | def __init__(self, model_config=None):
method set_parameters (line 169) | def set_parameters(self, shift=1.0, cosine_s=8e-3):
method sigma (line 183) | def sigma(self, timestep):
method timestep (line 195) | def timestep(self, sigma):
method percent_to_sigma (line 202) | def percent_to_sigma(self, percent):
FILE: ldm_patched/modules/ops.py
function cast_bias_weight (line 4) | def cast_bias_weight(s, input):
class disable_weight_init (line 13) | class disable_weight_init:
class Linear (line 14) | class Linear(torch.nn.Linear):
method reset_parameters (line 16) | def reset_parameters(self):
method forward_ldm_patched_cast_weights (line 19) | def forward_ldm_patched_cast_weights(self, input):
method forward (line 23) | def forward(self, *args, **kwargs):
class Conv2d (line 29) | class Conv2d(torch.nn.Conv2d):
method reset_parameters (line 31) | def reset_parameters(self):
method forward_ldm_patched_cast_weights (line 34) | def forward_ldm_patched_cast_weights(self, input):
method forward (line 38) | def forward(self, *args, **kwargs):
class Conv3d (line 44) | class Conv3d(torch.nn.Conv3d):
method reset_parameters (line 46) | def reset_parameters(self):
method forward_ldm_patched_cast_weights (line 49) | def forward_ldm_patched_cast_weights(self, input):
method forward (line 53) | def forward(self, *args, **kwargs):
class GroupNorm (line 59) | class GroupNorm(torch.nn.GroupNorm):
method reset_parameters (line 61) | def reset_parameters(self):
method forward_ldm_patched_cast_weights (line 64) | def forward_ldm_patched_cast_weights(self, input):
method forward (line 68) | def forward(self, *args, **kwargs):
class LayerNorm (line 75) | class LayerNorm(torch.nn.LayerNorm):
method reset_parameters (line 77) | def reset_parameters(self):
method forward_ldm_patched_cast_weights (line 80) | def forward_ldm_patched_cast_weights(self, input):
method forward (line 84) | def forward(self, *args, **kwargs):
method conv_nd (line 91) | def conv_nd(s, dims, *args, **kwargs):
class manual_cast (line 100) | class manual_cast(disable_weight_init):
class Linear (line 101) | class Linear(disable_weight_init.Linear):
class Conv2d (line 104) | class Conv2d(disable_weight_init.Conv2d):
class Conv3d (line 107) | class Conv3d(disable_weight_init.Conv3d):
class GroupNorm (line 110) | class GroupNorm(disable_weight_init.GroupNorm):
class LayerNorm (line 113) | class LayerNorm(disable_weight_init.LayerNorm):
FILE: ldm_patched/modules/options.py
function enable_args_parsing (line 4) | def enable_args_parsing(enable=True):
FILE: ldm_patched/modules/sample.py
function prepare_noise (line 9) | def prepare_noise(latent_image, seed, noise_inds=None):
function prepare_mask (line 28) | def prepare_mask(noise_mask, shape, device):
function get_models_from_cond (line 36) | def get_models_from_cond(cond, model_type):
function convert_cond (line 43) | def convert_cond(cond):
function get_additional_models (line 55) | def get_additional_models(positive, negative, dtype):
function cleanup_additional_models (line 70) | def cleanup_additional_models(models):
function prepare_sampling (line 76) | def prepare_sampling(model, noise_shape, positive, negative, noise_mask):
function sample (line 92) | def sample(model, noise, steps, cfg, sampler_name, scheduler, positive, ...
function sample_custom (line 107) | def sample_custom(model, noise, cfg, sampler, sigmas, positive, negative...
FILE: ldm_patched/modules/samplers.py
function get_area_and_mult (line 8) | def get_area_and_mult(conds, x_in, timestep_in):
function cond_equal_size (line 79) | def cond_equal_size(c1, c2):
function can_concat_cond (line 89) | def can_concat_cond(c1, c2):
function cond_cat (line 109) | def cond_cat(c_list):
function calc_cond_uncond_batch (line 129) | def calc_cond_uncond_batch(model, cond, uncond, x_in, timestep, model_op...
function sampling_function (line 242) | def sampling_function(model, x, timestep, uncond, cond, cond_scale, mode...
class CFGNoisePredictor (line 263) | class CFGNoisePredictor(torch.nn.Module):
method __init__ (line 264) | def __init__(self, model):
method apply_model (line 267) | def apply_model(self, x, timestep, cond, uncond, cond_scale, model_opt...
method forward (line 270) | def forward(self, *args, **kwargs):
class KSamplerX0Inpaint (line 273) | class KSamplerX0Inpaint(torch.nn.Module):
method __init__ (line 274) | def __init__(self, model):
method forward (line 277) | def forward(self, x, sigma, uncond, cond, cond_scale, denoise_mask, mo...
function simple_scheduler (line 286) | def simple_scheduler(model, steps):
function ddim_scheduler (line 295) | def ddim_scheduler(model, steps):
function normal_scheduler (line 307) | def normal_scheduler(model, steps, sgm=False, floor=False):
function get_mask_aabb (line 324) | def get_mask_aabb(masks):
function resolve_areas_and_cond_masks (line 347) | def resolve_areas_and_cond_masks(conditions, h, w, device):
function create_cond_with_same_area_if_none (line 387) | def create_cond_with_same_area_if_none(conds, c):
function calculate_start_end_timesteps (line 419) | def calculate_start_end_timesteps(model, conds):
function pre_run_control (line 439) | def pre_run_control(model, conds):
function apply_empty_x_to_equal_area (line 450) | def apply_empty_x_to_equal_area(conds, uncond, name, uncond_fill_func):
function encode_model_conds (line 485) | def encode_model_conds(model_function, conds, noise, device, prompt_type...
class Sampler (line 507) | class Sampler:
method sample (line 508) | def sample(self):
method max_denoise (line 511) | def max_denoise(self, model_wrap, sigmas):
class UNIPC (line 516) | class UNIPC(Sampler):
method sample (line 517) | def sample(self, model_wrap, sigmas, extra_args, callback, noise, late...
class UNIPCBH2 (line 520) | class UNIPCBH2(Sampler):
method sample (line 521) | def sample(self, model_wrap, sigmas, extra_args, callback, noise, late...
class KSAMPLER (line 528) | class KSAMPLER(Sampler):
method __init__ (line 529) | def __init__(self, sampler_function, extra_options={}, inpaint_options...
method sample (line 534) | def sample(self, model_wrap, sigmas, extra_args, callback, noise, late...
function ksampler (line 561) | def ksampler(sampler_name, extra_options={}, inpaint_options={}):
function wrap_model (line 582) | def wrap_model(model):
function sample (line 586) | def sample(model, noise, positive, negative, cfg, device, sampler, sigma...
function calculate_sigmas_scheduler (line 624) | def calculate_sigmas_scheduler(model, scheduler_name, steps):
function sampler_object (line 641) | def sampler_object(name):
class KSampler (line 652) | class KSampler:
method __init__ (line 656) | def __init__(self, model, steps, device, sampler=None, scheduler=None,...
method calculate_sigmas (line 669) | def calculate_sigmas(self, steps):
method set_steps (line 683) | def set_steps(self, steps, denoise=None):
method sample (line 692) | def sample(self, noise, positive, negative, cfg, latent_image=None, st...
FILE: ldm_patched/modules/sd.py
function load_model_weights (line 25) | def load_model_weights(model, sd):
function load_clip_weights (line 39) | def load_clip_weights(model, sd):
function load_lora_for_models (line 55) | def load_lora_for_models(model, clip, lora, strength_model, strength_clip):
class CLIP (line 85) | class CLIP:
method __init__ (line 86) | def __init__(self, target=None, embedding_directory=None, no_init=False):
method clone (line 104) | def clone(self):
method add_patches (line 112) | def add_patches(self, patches, strength_patch=1.0, strength_model=1.0):
method clip_layer (line 115) | def clip_layer(self, layer_idx):
method tokenize (line 118) | def tokenize(self, text, return_word_ids=False):
method encode_from_tokens (line 121) | def encode_from_tokens(self, tokens, return_pooled=False):
method encode (line 133) | def encode(self, text):
method load_sd (line 137) | def load_sd(self, sd):
method get_sd (line 140) | def get_sd(self):
method load_model (line 143) | def load_model(self):
method get_key_patches (line 147) | def get_key_patches(self):
class VAE (line 150) | class VAE:
method __init__ (line 151) | def __init__(self, sd=None, device=None, config=None, dtype=None):
method decode_tiled_ (line 203) | def decode_tiled_(self, samples, tile_x=64, tile_y=64, overlap = 16):
method encode_tiled_ (line 217) | def encode_tiled_(self, pixel_samples, tile_x=512, tile_y=512, overlap...
method decode (line 230) | def decode(self, samples_in):
method decode_tiled (line 249) | def decode_tiled(self, samples, tile_x=64, tile_y=64, overlap = 16):
method encode (line 254) | def encode(self, pixel_samples):
method encode_tiled (line 273) | def encode_tiled(self, pixel_samples, tile_x=512, tile_y=512, overlap ...
method get_sd (line 279) | def get_sd(self):
class StyleModel (line 282) | class StyleModel:
method __init__ (line 283) | def __init__(self, model, device="cpu"):
method get_cond (line 286) | def get_cond(self, input):
function load_style_model (line 290) | def load_style_model(ckpt_path):
function load_clip (line 301) | def load_clip(ckpt_paths, embedding_directory=None):
function load_gligen (line 339) | def load_gligen(ckpt_path):
function load_checkpoint (line 346) | def load_checkpoint(config_path=None, ckpt_path=None, output_vae=True, o...
function load_checkpoint_guess_config (line 430) | def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip...
function load_unet_state_dict (line 496) | def load_unet_state_dict(sd): #load unet in diffusers format
function load_unet (line 531) | def load_unet(unet_path):
function save_checkpoint (line 539) | def save_checkpoint(output_path, model, clip=None, vae=None, clip_vision...
FILE: ldm_patched/modules/sd1_clip.py
function gen_empty_tokens (line 12) | def gen_empty_tokens(special_tokens, length):
class ClipTokenWeightEncoder (line 24) | class ClipTokenWeightEncoder:
method encode_token_weights (line 25) | def encode_token_weights(self, token_weight_pairs):
class SDClipModel (line 61) | class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder):
method __init__ (line 68) | def __init__(self, version="openai/clip-vit-large-patch14", device="cp...
method freeze (line 100) | def freeze(self):
method clip_layer (line 106) | def clip_layer(self, layer_idx):
method reset_clip_layer (line 113) | def reset_clip_layer(self):
method set_up_textual_embeddings (line 117) | def set_up_textual_embeddings(self, tokens, current_embeds):
method forward (line 156) | def forward(self, tokens):
method encode (line 189) | def encode(self, tokens):
method load_sd (line 192) | def load_sd(self, sd):
function parse_parentheses (line 199) | def parse_parentheses(string):
function token_weights (line 227) | def token_weights(string, current_weight):
function escape_important (line 247) | def escape_important(text):
function unescape_important (line 252) | def unescape_important(text):
function safe_load_embed_zip (line 257) | def safe_load_embed_zip(embed_path):
function expand_directory_list (line 276) | def expand_directory_list(directories):
function load_embed (line 284) | def load_embed(embedding_name, embedding_directory, embedding_size, embe...
class SDTokenizer (line 356) | class SDTokenizer:
method __init__ (line 357) | def __init__(self, tokenizer_path=None, max_length=77, pad_with_end=Tr...
method _try_get_embedding (line 383) | def _try_get_embedding(self, embedding_name:str):
method tokenize_with_weights (line 397) | def tokenize_with_weights(self, text:str, return_word_ids=False):
method untokenize (line 480) | def untokenize(self, token_weight_pair):
class SD1Tokenizer (line 484) | class SD1Tokenizer:
method __init__ (line 485) | def __init__(self, embedding_directory=None, clip_name="l", tokenizer=...
method tokenize_with_weights (line 490) | def tokenize_with_weights(self, text:str, return_word_ids=False):
method untokenize (line 495) | def untokenize(self, token_weight_pair):
class SD1ClipModel (line 499) | class SD1ClipModel(torch.nn.Module):
method __init__ (line 500) | def __init__(self, device="cpu", dtype=None, clip_name="l", clip_model...
method clip_layer (line 506) | def clip_layer(self, layer_idx):
method reset_clip_layer (line 509) | def reset_clip_layer(self):
method encode_token_weights (line 512) | def encode_token_weights(self, token_weight_pairs):
method load_sd (line 517) | def load_sd(self, sd):
FILE: ldm_patched/modules/sd2_clip.py
class SD2ClipHModel (line 5) | class SD2ClipHModel(sd1_clip.SDClipModel):
method __init__ (line 6) | def __init__(self, arch="ViT-H-14", device="cpu", max_length=77, freez...
class SD2ClipHTokenizer (line 14) | class SD2ClipHTokenizer(sd1_clip.SDTokenizer):
method __init__ (line 15) | def __init__(self, tokenizer_path=None, embedding_directory=None):
class SD2Tokenizer (line 18) | class SD2Tokenizer(sd1_clip.SD1Tokenizer):
method __init__ (line 19) | def __init__(self, embedding_directory=None):
class SD2ClipModel (line 22) | class SD2ClipModel(sd1_clip.SD1ClipModel):
method __init__ (line 23) | def __init__(self, device="cpu", dtype=None, **kwargs):
FILE: ldm_patched/modules/sdxl_clip.py
class SDXLClipG (line 5) | class SDXLClipG(sd1_clip.SDClipModel):
method __init__ (line 6) | def __init__(self, device="cpu", max_length=77, freeze=True, layer="pe...
method load_sd (line 15) | def load_sd(self, sd):
class SDXLClipGTokenizer (line 18) | class SDXLClipGTokenizer(sd1_clip.SDTokenizer):
method __init__ (line 19) | def __init__(self, tokenizer_path=None, embedding_directory=None):
class SDXLTokenizer (line 23) | class SDXLTokenizer:
method __init__ (line 24) | def __init__(self, embedding_directory=None):
method tokenize_with_weights (line 28) | def tokenize_with_weights(self, text:str, return_word_ids=False):
method untokenize (line 34) | def untokenize(self, token_weight_pair):
class SDXLClipModel (line 37) | class SDXLClipModel(torch.nn.Module):
method __init__ (line 38) | def __init__(self, device="cpu", dtype=None):
method clip_layer (line 43) | def clip_layer(self, layer_idx):
method reset_clip_layer (line 47) | def reset_clip_layer(self):
method encode_token_weights (line 51) | def encode_token_weights(self, token_weight_pairs):
method load_sd (line 58) | def load_sd(self, sd):
class SDXLRefinerClipModel (line 64) | class SDXLRefinerClipModel(sd1_clip.SD1ClipModel):
method __init__ (line 65) | def __init__(self, device="cpu", dtype=None):
FILE: ldm_patched/modules/supported_models.py
class SD15 (line 14) | class SD15(supported_models_base.BASE):
method process_clip_state_dict (line 30) | def process_clip_state_dict(self, state_dict):
method process_clip_state_dict_for_saving (line 47) | def process_clip_state_dict_for_saving(self, state_dict):
method clip_target (line 51) | def clip_target(self):
class SD20 (line 54) | class SD20(supported_models_base.BASE):
method model_type (line 65) | def model_type(self, state_dict, prefix=""):
method process_clip_state_dict (line 73) | def process_clip_state_dict(self, state_dict):
method process_clip_state_dict_for_saving (line 81) | def process_clip_state_dict_for_saving(self, state_dict):
method clip_target (line 88) | def clip_target(self):
class SD21UnclipL (line 91) | class SD21UnclipL(SD20):
class SD21UnclipH (line 104) | class SD21UnclipH(SD20):
class SDXLRefiner (line 116) | class SDXLRefiner(supported_models_base.BASE):
method get_model (line 128) | def get_model(self, state_dict, prefix="", device=None):
method process_clip_state_dict (line 131) | def process_clip_state_dict(self, state_dict):
method process_clip_state_dict_for_saving (line 142) | def process_clip_state_dict_for_saving(self, state_dict):
method clip_target (line 151) | def clip_target(self):
class SDXL (line 154) | class SDXL(supported_models_base.BASE):
method model_type (line 166) | def model_type(self, state_dict, prefix=""):
method get_model (line 172) | def get_model(self, state_dict, prefix="", device=None):
method process_clip_state_dict (line 178) | def process_clip_state_dict(self, state_dict):
method process_clip_state_dict_for_saving (line 192) | def process_clip_state_dict_for_saving(self, state_dict):
method clip_target (line 207) | def clip_target(self):
class SSD1B (line 210) | class SSD1B(SDXL):
class Segmind_Vega (line 220) | class Segmind_Vega(SDXL):
class SVD_img2vid (line 230) | class SVD_img2vid(supported_models_base.BASE):
method get_model (line 248) | def get_model(self, state_dict, prefix="", device=None):
method clip_target (line 252) | def clip_target(self):
class Stable_Zero123 (line 255) | class Stable_Zero123(supported_models_base.BASE):
method get_model (line 274) | def get_model(self, state_dict, prefix="", device=None):
method clip_target (line 278) | def clip_target(self):
class SD_X4Upscaler (line 281) | class SD_X4Upscaler(SD20):
method get_model (line 305) | def get_model(self, state_dict, prefix="", device=None):
FILE: ldm_patched/modules/supported_models_base.py
class ClipTarget (line 6) | class ClipTarget:
method __init__ (line 7) | def __init__(self, tokenizer, clip):
class BASE (line 12) | class BASE:
method matches (line 28) | def matches(s, unet_config):
method model_type (line 34) | def model_type(self, state_dict, prefix=""):
method inpaint_model (line 37) | def inpaint_model(self):
method __init__ (line 40) | def __init__(self, unet_config):
method get_model (line 46) | def get_model(self, state_dict, prefix="", device=None):
method process_clip_state_dict (line 55) | def process_clip_state_dict(self, state_dict):
method process_unet_state_dict (line 58) | def process_unet_state_dict(self, state_dict):
method process_vae_state_dict (line 61) | def process_vae_state_dict(self, state_dict):
method process_clip_state_dict_for_saving (line 64) | def process_clip_state_dict_for_saving(self, state_dict):
method process_clip_vision_state_dict_for_saving (line 68) | def process_clip_vision_state_dict_for_saving(self, state_dict):
method process_unet_state_dict_for_saving (line 74) | def process_unet_state_dict_for_saving(self, state_dict):
method process_vae_state_dict_for_saving (line 78) | def process_vae_state_dict_for_saving(self, state_dict):
method set_manual_cast (line 82) | def set_manual_cast(self, manual_cast_dtype):
FILE: ldm_patched/modules/utils.py
function load_torch_file (line 9) | def load_torch_file(ckpt, safe_load=False, device=None):
function save_torch_file (line 31) | def save_torch_file(sd, ckpt, metadata=None):
function calculate_parameters (line 37) | def calculate_parameters(sd, prefix=""):
function state_dict_key_replace (line 44) | def state_dict_key_replace(state_dict, keys_to_replace):
function state_dict_prefix_replace (line 50) | def state_dict_prefix_replace(state_dict, replace_prefix, filter_keys=Fa...
function transformers_convert (line 63) | def transformers_convert(sd, prefix_from, prefix_to, number):
function unet_to_diffusers (line 171) | def unet_to_diffusers(unet_config):
function repeat_to_batch_size (line 235) | def repeat_to_batch_size(tensor, batch_size):
function resize_to_batch_size (line 242) | def resize_to_batch_size(tensor, batch_size):
function convert_sd_to (line 262) | def convert_sd_to(state_dict, dtype):
function safetensors_header (line 268) | def safetensors_header(safetensors_path, max_size=100*1024*1024):
function set_attr (line 276) | def set_attr(obj, attr, value):
function copy_to_param (line 284) | def copy_to_param(obj, attr, value):
function get_attr (line 292) | def get_attr(obj, attr):
function bislerp (line 298) | def bislerp(samples, width, height):
function lanczos (line 374) | def lanczos(samples, width, height):
function common_upscale (line 381) | def common_upscale(samples, width, height, upscale_method, crop):
function get_tiled_scale_steps (line 404) | def get_tiled_scale_steps(width, height, tile_x, tile_y, overlap):
function tiled_scale (line 408) | def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, up...
function set_progress_bar_enabled (line 435) | def set_progress_bar_enabled(enabled):
function set_progress_bar_global_hook (line 440) | def set_progress_bar_global_hook(function):
class ProgressBar (line 444) | class ProgressBar:
method __init__ (line 445) | def __init__(self, total):
method update_absolute (line 451) | def update_absolute(self, value, total=None, preview=None):
method update (line 460) | def update(self, value):
FILE: ldm_patched/pfn/architecture/DAT.py
function img2windows (line 18) | def img2windows(img, H_sp, W_sp):
function windows2img (line 31) | def windows2img(img_splits_hw, H_sp, W_sp, H, W):
class SpatialGate (line 43) | class SpatialGate(nn.Module):
method __init__ (line 49) | def __init__(self, dim):
method forward (line 56) | def forward(self, x, H, W):
class SGFN (line 70) | class SGFN(nn.Module):
method __init__ (line 80) | def __init__(
method forward (line 97) | def forward(self, x, H, W):
class DynamicPosBias (line 114) | class DynamicPosBias(nn.Module):
method __init__ (line 123) | def __init__(self, dim, num_heads, residual):
method forward (line 145) | def forward(self, biases):
class Spatial_Attention (line 156) | class Spatial_Attention(nn.Module):
method __init__ (line 171) | def __init__(
method im2win (line 228) | def im2win(self, x, H, W):
method forward (line 239) | def forward(self, qkv, H, W, mask=None):
class Adaptive_Spatial_Attention (line 293) | class Adaptive_Spatial_Attention(nn.Module):
method __init__ (line 309) | def __init__(
method calculate_mask (line 394) | def calculate_mask(self, H, W):
method forward (line 473) | def forward(self, x, H, W):
class Adaptive_Channel_Attention (line 578) | class Adaptive_Channel_Attention(nn.Module):
method __init__ (line 590) | def __init__(
method forward (line 627) | def forward(self, x, H, W):
class DATB (line 682) | class DATB(nn.Module):
method __init__ (line 683) | def __init__(
method forward (line 741) | def forward(self, x, x_size):
class ResidualGroup (line 753) | class ResidualGroup(nn.Module):
method __init__ (line 773) | def __init__(
method forward (line 830) | def forward(self, x, x_size):
class Upsample (line 850) | class Upsample(nn.Sequential):
method __init__ (line 857) | def __init__(self, scale, num_feat):
class UpsampleOneStep (line 873) | class UpsampleOneStep(nn.Sequential):
method __init__ (line 883) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
method flops (line 891) | def flops(self):
class DAT (line 897) | class DAT(nn.Module):
method __init__ (line 920) | def __init__(self, state_dict):
method _init_weights (line 1140) | def _init_weights(self, m):
method forward_features (line 1151) | def forward_features(self, x):
method forward (line 1162) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/HAT.py
function drop_path (line 15) | def drop_path(x, drop_prob: float = 0.0, training: bool = False):
class DropPath (line 31) | class DropPath(nn.Module):
method __init__ (line 36) | def __init__(self, drop_prob=None):
method forward (line 40) | def forward(self, x):
class ChannelAttention (line 44) | class ChannelAttention(nn.Module):
method __init__ (line 51) | def __init__(self, num_feat, squeeze_factor=16):
method forward (line 61) | def forward(self, x):
class CAB (line 66) | class CAB(nn.Module):
method __init__ (line 67) | def __init__(self, num_feat, compress_ratio=3, squeeze_factor=30):
method forward (line 77) | def forward(self, x):
class Mlp (line 81) | class Mlp(nn.Module):
method __init__ (line 82) | def __init__(
method forward (line 98) | def forward(self, x):
function window_partition (line 107) | def window_partition(x, window_size):
function window_reverse (line 123) | def window_reverse(windows, window_size, h, w):
class WindowAttention (line 141) | class WindowAttention(nn.Module):
method __init__ (line 154) | def __init__(
method forward (line 185) | def forward(self, x, rpi, mask=None):
class HAB (line 234) | class HAB(nn.Module):
method __init__ (line 252) | def __init__(
method forward (line 312) | def forward(self, x, x_size, rpi_sa, attn_mask):
class PatchMerging (line 366) | class PatchMerging(nn.Module):
method __init__ (line 374) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
method forward (line 381) | def forward(self, x):
class OCAB (line 405) | class OCAB(nn.Module):
method __init__ (line 408) | def __init__(
method forward (line 457) | def forward(self, x, x_size, rpi):
class AttenBlocks (line 539) | class AttenBlocks(nn.Module):
method __init__ (line 558) | def __init__(
method forward (line 632) | def forward(self, x, x_size, params):
class RHAG (line 643) | class RHAG(nn.Module):
method __init__ (line 665) | def __init__(
method forward (line 736) | def forward(self, x, x_size, params):
class PatchEmbed (line 747) | class PatchEmbed(nn.Module):
method __init__ (line 757) | def __init__(
method forward (line 780) | def forward(self, x):
class PatchUnEmbed (line 787) | class PatchUnEmbed(nn.Module):
method __init__ (line 797) | def __init__(
method forward (line 815) | def forward(self, x, x_size):
class Upsample (line 824) | class Upsample(nn.Sequential):
method __init__ (line 831) | def __init__(self, scale, num_feat):
class HAT (line 847) | class HAT(nn.Module):
method __init__ (line 875) | def __init__(
method _init_weights (line 1133) | def _init_weights(self, m):
method calculate_rpi_sa (line 1142) | def calculate_rpi_sa(self):
method calculate_rpi_oca (line 1160) | def calculate_rpi_oca(self):
method calculate_mask (line 1191) | def calculate_mask(self, x_size):
method no_weight_decay (line 1223) | def no_weight_decay(self):
method no_weight_decay_keywords (line 1227) | def no_weight_decay_keywords(self):
method check_image_size (line 1230) | def check_image_size(self, x):
method forward_features (line 1237) | def forward_features(self, x):
method forward (line 1262) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/LaMa.py
class LearnableSpatialTransformWrapper (line 18) | class LearnableSpatialTransformWrapper(nn.Module):
method __init__ (line 19) | def __init__(self, impl, pad_coef=0.5, angle_init_range=80, train_angl...
method forward (line 27) | def forward(self, x):
method transform (line 39) | def transform(self, x):
method inverse_transform (line 49) | def inverse_transform(self, y_padded_rotated, orig_x):
class SELayer (line 64) | class SELayer(nn.Module):
method __init__ (line 65) | def __init__(self, channel, reduction=16):
method forward (line 75) | def forward(self, x):
class FourierUnit (line 83) | class FourierUnit(nn.Module):
method __init__ (line 84) | def __init__(
method forward (line 126) | def forward(self, x):
class SpectralTransform (line 224) | class SpectralTransform(nn.Module):
method __init__ (line 225) | def __init__(
method forward (line 259) | def forward(self, x):
class FFC (line 282) | class FFC(nn.Module):
method __init__ (line 283) | def __init__(
method forward (line 368) | def forward(self, x):
class FFC_BN_ACT (line 391) | class FFC_BN_ACT(nn.Module):
method __init__ (line 392) | def __init__(
method forward (line 437) | def forward(self, x):
class FFCResnetBlock (line 444) | class FFCResnetBlock(nn.Module):
method __init__ (line 445) | def __init__(
method forward (line 488) | def forward(self, x):
class ConcatTupleLayer (line 509) | class ConcatTupleLayer(nn.Module):
method forward (line 510) | def forward(self, x):
class FFCResNetGenerator (line 519) | class FFCResNetGenerator(nn.Module):
method __init__ (line 520) | def __init__(
method forward (line 662) | def forward(self, image, mask):
class LaMa (line 666) | class LaMa(nn.Module):
method __init__ (line 667) | def __init__(self, state_dict) -> None:
method forward (line 690) | def forward(self, img, mask):
FILE: ldm_patched/pfn/architecture/OmniSR/ChannelAttention.py
class CA_layer (line 6) | class CA_layer(nn.Module):
method __init__ (line 7) | def __init__(self, channel, reduction=16):
method forward (line 18) | def forward(self, x):
class Simple_CA_layer (line 23) | class Simple_CA_layer(nn.Module):
method __init__ (line 24) | def __init__(self, channel):
method forward (line 37) | def forward(self, x):
class ECA_layer (line 41) | class ECA_layer(nn.Module):
method __init__ (line 48) | def __init__(self, channel):
method forward (line 61) | def forward(self, x):
class ECA_MaxPool_layer (line 77) | class ECA_MaxPool_layer(nn.Module):
method __init__ (line 84) | def __init__(self, channel):
method forward (line 97) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/OmniSR/OSA.py
function exists (line 24) | def exists(val):
function default (line 28) | def default(val, d):
function cast_tuple (line 32) | def cast_tuple(val, length=1):
class PreNormResidual (line 39) | class PreNormResidual(nn.Module):
method __init__ (line 40) | def __init__(self, dim, fn):
method forward (line 45) | def forward(self, x):
class Conv_PreNormResidual (line 49) | class Conv_PreNormResidual(nn.Module):
method __init__ (line 50) | def __init__(self, dim, fn):
method forward (line 55) | def forward(self, x):
class FeedForward (line 59) | class FeedForward(nn.Module):
method __init__ (line 60) | def __init__(self, dim, mult=2, dropout=0.0):
method forward (line 71) | def forward(self, x):
class Conv_FeedForward (line 75) | class Conv_FeedForward(nn.Module):
method __init__ (line 76) | def __init__(self, dim, mult=2, dropout=0.0):
method forward (line 87) | def forward(self, x):
class Gated_Conv_FeedForward (line 91) | class Gated_Conv_FeedForward(nn.Module):
method __init__ (line 92) | def __init__(self, dim, mult=1, bias=False, dropout=0.0):
method forward (line 111) | def forward(self, x):
class SqueezeExcitation (line 122) | class SqueezeExcitation(nn.Module):
method __init__ (line 123) | def __init__(self, dim, shrinkage_rate=0.25):
method forward (line 136) | def forward(self, x):
class MBConvResidual (line 140) | class MBConvResidual(nn.Module):
method __init__ (line 141) | def __init__(self, fn, dropout=0.0):
method forward (line 146) | def forward(self, x):
class Dropsample (line 152) | class Dropsample(nn.Module):
method __init__ (line 153) | def __init__(self, prob=0):
method forward (line 157) | def forward(self, x):
function MBConv (line 170) | def MBConv(
class Attention (line 197) | class Attention(nn.Module):
method __init__ (line 198) | def __init__(
method forward (line 240) | def forward(self, x):
class Block_Attention (line 292) | class Block_Attention(nn.Module):
method __init__ (line 293) | def __init__(
method forward (line 327) | def forward(self, x):
class Channel_Attention (line 377) | class Channel_Attention(nn.Module):
method __init__ (line 378) | def __init__(self, dim, heads, bias=False, dropout=0.0, window_size=7):
method forward (line 398) | def forward(self, x):
class Channel_Attention_grid (line 437) | class Channel_Attention_grid(nn.Module):
method __init__ (line 438) | def __init__(self, dim, heads, bias=False, dropout=0.0, window_size=7):
method forward (line 458) | def forward(self, x):
class OSA_Block (line 497) | class OSA_Block(nn.Module):
method __init__ (line 498) | def __init__(
method forward (line 575) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/OmniSR/OSAG.py
class OSAG (line 20) | class OSAG(nn.Module):
method __init__ (line 21) | def __init__(
method forward (line 57) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/OmniSR/OmniSR.py
class OmniSR (line 23) | class OmniSR(nn.Module):
method __init__ (line 24) | def __init__(
method check_image_size (line 122) | def check_image_size(self, x):
method forward (line 131) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/OmniSR/esa.py
function moment (line 20) | def moment(x, dim=(2, 3), k=2):
class ESA (line 27) | class ESA(nn.Module):
method __init__ (line 35) | def __init__(self, esa_channels, n_feats, conv=nn.Conv2d):
method forward (line 46) | def forward(self, x):
class LK_ESA (line 60) | class LK_ESA(nn.Module):
method __init__ (line 61) | def __init__(
method forward (line 111) | def forward(self, x):
class LK_ESA_LN (line 123) | class LK_ESA_LN(nn.Module):
method __init__ (line 124) | def __init__(
method forward (line 176) | def forward(self, x):
class AdaGuidedFilter (line 189) | class AdaGuidedFilter(nn.Module):
method __init__ (line 190) | def __init__(
method box_filter (line 208) | def box_filter(self, x, r):
method forward (line 218) | def forward(self, x):
class AdaConvGuidedFilter (line 241) | class AdaConvGuidedFilter(nn.Module):
method __init__ (line 242) | def __init__(
method forward (line 283) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/OmniSR/layernorm.py
class LayerNormFunction (line 17) | class LayerNormFunction(torch.autograd.Function):
method forward (line 19) | def forward(ctx, x, weight, bias, eps):
method backward (line 30) | def backward(ctx, grad_output):
class LayerNorm2d (line 48) | class LayerNorm2d(nn.Module):
method __init__ (line 49) | def __init__(self, channels, eps=1e-6):
method forward (line 55) | def forward(self, x):
class GRN (line 59) | class GRN(nn.Module):
method __init__ (line 62) | def __init__(self, dim):
method forward (line 67) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/OmniSR/pixelshuffle.py
function pixelshuffle_block (line 16) | def pixelshuffle_block(
FILE: ldm_patched/pfn/architecture/RRDB.py
class RRDBNet (line 18) | class RRDBNet(nn.Module):
method __init__ (line 19) | def __init__(
method new_to_old_arch (line 196) | def new_to_old_arch(self, state):
method get_scale (line 259) | def get_scale(self, min_part: int = 6) -> int:
method get_num_blocks (line 269) | def get_num_blocks(self) -> int:
method forward (line 283) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/SCUNet.py
class WMSA (line 19) | class WMSA(nn.Module):
method __init__ (line 22) | def __init__(self, input_dim, output_dim, head_dim, window_size, type):
method generate_mask (line 53) | def generate_mask(self, h, w, p, shift):
method forward (line 84) | def forward(self, x):
method relative_embedding (line 150) | def relative_embedding(self):
class Block (line 167) | class Block(nn.Module):
method __init__ (line 168) | def __init__(
method forward (line 197) | def forward(self, x):
class ConvTransBlock (line 203) | class ConvTransBlock(nn.Module):
method __init__ (line 204) | def __init__(
method forward (line 260) | def forward(self, x):
class SCUNet (line 274) | class SCUNet(nn.Module):
method __init__ (line 275) | def __init__(
method check_image_size (line 424) | def check_image_size(self, x):
method forward (line 431) | def forward(self, x0):
method _init_weights (line 448) | def _init_weights(self, m):
FILE: ldm_patched/pfn/architecture/SPSR.py
class Get_gradient_nopadding (line 13) | class Get_gradient_nopadding(nn.Module):
method __init__ (line 14) | def __init__(self):
method forward (line 24) | def forward(self, x):
class SPSRNet (line 38) | class SPSRNet(nn.Module):
method __init__ (line 39) | def __init__(
method get_scale (line 297) | def get_scale(self, min_part: int = 4) -> int:
method get_num_blocks (line 307) | def get_num_blocks(self) -> int:
method forward (line 316) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/SRVGG.py
class SRVGGNetCompact (line 10) | class SRVGGNetCompact(nn.Module):
method __init__ (line 23) | def __init__(
method get_num_conv (line 83) | def get_num_conv(self) -> int:
method get_num_feats (line 86) | def get_num_feats(self) -> int:
method get_in_nc (line 89) | def get_in_nc(self) -> int:
method get_scale (line 92) | def get_scale(self) -> int:
method forward (line 105) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/SwiftSRGAN.py
class SeperableConv2d (line 7) | class SeperableConv2d(nn.Module):
method __init__ (line 8) | def __init__(
method forward (line 23) | def forward(self, x):
class ConvBlock (line 27) | class ConvBlock(nn.Module):
method __init__ (line 28) | def __init__(
method forward (line 48) | def forward(self, x):
class UpsampleBlock (line 52) | class UpsampleBlock(nn.Module):
method __init__ (line 53) | def __init__(self, in_channels, scale_factor):
method forward (line 68) | def forward(self, x):
class ResidualBlock (line 72) | class ResidualBlock(nn.Module):
method __init__ (line 73) | def __init__(self, in_channels):
method forward (line 83) | def forward(self, x):
class Generator (line 89) | class Generator(nn.Module):
method __init__ (line 100) | def __init__(
method forward (line 156) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/Swin2SR.py
class Mlp (line 23) | class Mlp(nn.Module):
method __init__ (line 24) | def __init__(
method forward (line 40) | def forward(self, x):
function window_partition (line 49) | def window_partition(x, window_size):
function window_reverse (line 65) | def window_reverse(windows, window_size, H, W):
class WindowAttention (line 83) | class WindowAttention(nn.Module):
method __init__ (line 96) | def __init__(
method forward (line 178) | def forward(self, x, mask=None):
method extra_repr (line 235) | def extra_repr(self) -> str:
method flops (line 241) | def flops(self, N):
class SwinTransformerBlock (line 255) | class SwinTransformerBlock(nn.Module):
method __init__ (line 273) | def __init__(
method calculate_mask (line 332) | def calculate_mask(self, x_size):
method forward (line 363) | def forward(self, x, x_size):
method extra_repr (line 416) | def extra_repr(self) -> str:
method flops (line 422) | def flops(self):
class PatchMerging (line 437) | class PatchMerging(nn.Module):
method __init__ (line 445) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
method forward (line 452) | def forward(self, x):
method extra_repr (line 475) | def extra_repr(self) -> str:
method flops (line 478) | def flops(self):
class BasicLayer (line 485) | class BasicLayer(nn.Module):
method __init__ (line 504) | def __init__(
method forward (line 558) | def forward(self, x, x_size):
method extra_repr (line 568) | def extra_repr(self) -> str:
method flops (line 571) | def flops(self):
method _init_respostnorm (line 579) | def _init_respostnorm(self):
class PatchEmbed (line 587) | class PatchEmbed(nn.Module):
method __init__ (line 597) | def __init__(
method forward (line 620) | def forward(self, x):
method flops (line 630) | def flops(self):
class RSTB (line 638) | class RSTB(nn.Module):
method __init__ (line 660) | def __init__(
method forward (line 728) | def forward(self, x, x_size):
method flops (line 736) | def flops(self):
class PatchUnEmbed (line 747) | class PatchUnEmbed(nn.Module):
method __init__ (line 758) | def __init__(
method forward (line 773) | def forward(self, x, x_size):
method flops (line 778) | def flops(self):
class Upsample (line 783) | class Upsample(nn.Sequential):
method __init__ (line 791) | def __init__(self, scale, num_feat):
class Upsample_hf (line 807) | class Upsample_hf(nn.Sequential):
method __init__ (line 815) | def __init__(self, scale, num_feat):
class UpsampleOneStep (line 831) | class UpsampleOneStep(nn.Sequential):
method __init__ (line 841) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
method flops (line 849) | def flops(self):
class Swin2SR (line 855) | class Swin2SR(nn.Module):
method __init__ (line 882) | def __init__(
method _init_weights (line 1229) | def _init_weights(self, m):
method no_weight_decay (line 1239) | def no_weight_decay(self):
method no_weight_decay_keywords (line 1243) | def no_weight_decay_keywords(self):
method check_image_size (line 1246) | def check_image_size(self, x):
method forward_features (line 1253) | def forward_features(self, x):
method forward_features_hf (line 1268) | def forward_features_hf(self, x):
method forward (line 1283) | def forward(self, x):
method flops (line 1368) | def flops(self):
FILE: ldm_patched/pfn/architecture/SwinIR.py
class Mlp (line 21) | class Mlp(nn.Module):
method __init__ (line 22) | def __init__(
method forward (line 38) | def forward(self, x):
function window_partition (line 47) | def window_partition(x, window_size):
function window_reverse (line 64) | def window_reverse(windows, window_size, H, W):
class WindowAttention (line 83) | class WindowAttention(nn.Module):
method __init__ (line 97) | def __init__(
method forward (line 145) | def forward(self, x, mask=None):
method extra_repr (line 195) | def extra_repr(self) -> str:
method flops (line 198) | def flops(self, N):
class SwinTransformerBlock (line 212) | class SwinTransformerBlock(nn.Module):
method __init__ (line 231) | def __init__(
method calculate_mask (line 290) | def calculate_mask(self, x_size):
method forward (line 321) | def forward(self, x, x_size):
method extra_repr (line 375) | def extra_repr(self) -> str:
method flops (line 381) | def flops(self):
class PatchMerging (line 396) | class PatchMerging(nn.Module):
method __init__ (line 405) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
method forward (line 412) | def forward(self, x):
method extra_repr (line 435) | def extra_repr(self) -> str:
method flops (line 438) | def flops(self):
class BasicLayer (line 445) | class BasicLayer(nn.Module):
method __init__ (line 465) | def __init__(
method forward (line 519) | def forward(self, x, x_size):
method extra_repr (line 529) | def extra_repr(self) -> str:
method flops (line 532) | def flops(self):
class RSTB (line 541) | class RSTB(nn.Module):
method __init__ (line 564) | def __init__(
method forward (line 634) | def forward(self, x, x_size):
method flops (line 642) | def flops(self):
class PatchEmbed (line 653) | class PatchEmbed(nn.Module):
method __init__ (line 664) | def __init__(
method forward (line 687) | def forward(self, x):
method flops (line 693) | def flops(self):
class PatchUnEmbed (line 701) | class PatchUnEmbed(nn.Module):
method __init__ (line 712) | def __init__(
method forward (line 730) | def forward(self, x, x_size):
method flops (line 735) | def flops(self):
class Upsample (line 740) | class Upsample(nn.Sequential):
method __init__ (line 748) | def __init__(self, scale, num_feat):
class UpsampleOneStep (line 764) | class UpsampleOneStep(nn.Sequential):
method __init__ (line 774) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
method flops (line 782) | def flops(self):
class SwinIR (line 788) | class SwinIR(nn.Module):
method __init__ (line 816) | def __init__(
method _init_weights (line 1123) | def _init_weights(self, m):
method no_weight_decay (line 1133) | def no_weight_decay(self):
method no_weight_decay_keywords (line 1137) | def no_weight_decay_keywords(self):
method check_image_size (line 1140) | def check_image_size(self, x):
method forward_features (line 1147) | def forward_features(self, x):
method forward (line 1162) | def forward(self, x):
method flops (line 1215) | def flops(self):
FILE: ldm_patched/pfn/architecture/block.py
function act (line 20) | def act(act_type: str, inplace=True, neg_slope=0.2, n_prelu=1):
function norm (line 38) | def norm(norm_type: str, nc: int):
function pad (line 52) | def pad(pad_type: str, padding):
function get_valid_padding (line 69) | def get_valid_padding(kernel_size, dilation):
class ConcatBlock (line 75) | class ConcatBlock(nn.Module):
method __init__ (line 77) | def __init__(self, submodule):
method forward (line 81) | def forward(self, x):
method __repr__ (line 85) | def __repr__(self):
class ShortcutBlock (line 92) | class ShortcutBlock(nn.Module):
method __init__ (line 94) | def __init__(self, submodule):
method forward (line 98) | def forward(self, x):
method __repr__ (line 102) | def __repr__(self):
class ShortcutBlockSPSR (line 109) | class ShortcutBlockSPSR(nn.Module):
method __init__ (line 111) | def __init__(self, submodule):
method forward (line 115) | def forward(self, x):
method __repr__ (line 118) | def __repr__(self):
function sequential (line 125) | def sequential(*args):
function conv_block_2c2 (line 145) | def conv_block_2c2(
function conv_block (line 157) | def conv_block(
class ResNetBlock (line 217) | class ResNetBlock(nn.Module):
method __init__ (line 224) | def __init__(
method forward (line 281) | def forward(self, x):
class RRDB (line 286) | class RRDB(nn.Module):
method __init__ (line 292) | def __init__(
method forward (line 349) | def forward(self, x):
class ResidualDenseBlock_5C (line 356) | class ResidualDenseBlock_5C(nn.Module):
method __init__ (line 378) | def __init__(
method forward (line 463) | def forward(self, x):
function conv1x1 (line 477) | def conv1x1(in_planes, out_planes, stride=1):
function pixelshuffle_block (line 486) | def pixelshuffle_block(
function upconv_block (line 519) | def upconv_block(
FILE: ldm_patched/pfn/architecture/face/arcface_arch.py
function conv3x3 (line 4) | def conv3x3(inplanes, outplanes, stride=1):
class BasicBlock (line 17) | class BasicBlock(nn.Module):
method __init__ (line 29) | def __init__(self, inplanes, planes, stride=1, downsample=None):
method forward (line 39) | def forward(self, x):
class IRBlock (line 58) | class IRBlock(nn.Module):
method __init__ (line 71) | def __init__(self, inplanes, planes, stride=1, downsample=None, use_se...
method forward (line 85) | def forward(self, x):
class Bottleneck (line 106) | class Bottleneck(nn.Module):
method __init__ (line 118) | def __init__(self, inplanes, planes, stride=1, downsample=None):
method forward (line 134) | def forward(self, x):
class SEBlock (line 157) | class SEBlock(nn.Module):
method __init__ (line 165) | def __init__(self, channel, reduction=16):
method forward (line 177) | def forward(self, x):
class ResNetArcFace (line 184) | class ResNetArcFace(nn.Module):
method __init__ (line 195) | def __init__(self, block, layers, use_se=True):
method _make_layer (line 226) | def _make_layer(self, block, planes, num_blocks, stride=1):
method forward (line 249) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/face/codeformer.py
class VectorQuantizer (line 17) | class VectorQuantizer(nn.Module):
method __init__ (line 18) | def __init__(self, codebook_size, emb_dim, beta):
method forward (line 28) | def forward(self, z):
method get_codebook_feat (line 81) | def get_codebook_feat(self, indices, shape):
class GumbelQuantizer (line 96) | class GumbelQuantizer(nn.Module):
method __init__ (line 97) | def __init__(
method forward (line 117) | def forward(self, z):
class Downsample (line 137) | class Downsample(nn.Module):
method __init__ (line 138) | def __init__(self, in_channels):
method forward (line 144) | def forward(self, x):
class Upsample (line 151) | class Upsample(nn.Module):
method __init__ (line 152) | def __init__(self, in_channels):
method forward (line 158) | def forward(self, x):
class AttnBlock (line 165) | class AttnBlock(nn.Module):
method __init__ (line 166) | def __init__(self, in_channels):
method forward (line 184) | def forward(self, x):
class Encoder (line 211) | class Encoder(nn.Module):
method __init__ (line 212) | def __init__(
method forward (line 262) | def forward(self, x):
class Generator (line 269) | class Generator(nn.Module):
method __init__ (line 270) | def __init__(self, nf, ch_mult, res_blocks, img_size, attn_resolutions...
method forward (line 317) | def forward(self, x):
class VQAutoEncoder (line 324) | class VQAutoEncoder(nn.Module):
method __init__ (line 325) | def __init__(
method forward (line 394) | def forward(self, x):
function calc_mean_std (line 401) | def calc_mean_std(feat, eps=1e-5):
function adaptive_instance_normalization (line 417) | def adaptive_instance_normalization(content_feat, style_feat):
class PositionEmbeddingSine (line 434) | class PositionEmbeddingSine(nn.Module):
method __init__ (line 440) | def __init__(
method forward (line 453) | def forward(self, x, mask=None):
function _get_activation_fn (line 481) | def _get_activation_fn(activation):
class TransformerSALayer (line 492) | class TransformerSALayer(nn.Module):
method __init__ (line 493) | def __init__(
method with_pos_embed (line 510) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
method forward (line 513) | def forward(
function normalize (line 535) | def normalize(in_channels):
function swish (line 542) | def swish(x):
class ResBlock (line 546) | class ResBlock(nn.Module):
method __init__ (line 547) | def __init__(self, in_channels, out_channels=None):
method forward (line 564) | def forward(self, x_in):
class Fuse_sft_block (line 578) | class Fuse_sft_block(nn.Module):
method __init__ (line 579) | def __init__(self, in_ch, out_ch):
method forward (line 595) | def forward(self, enc_feat, dec_feat, w=1):
class CodeFormer (line 604) | class CodeFormer(VQAutoEncoder):
method __init__ (line 605) | def __init__(self, state_dict):
method _init_weights (line 716) | def _init_weights(self, module):
method forward (line 725) | def forward(self, x, weight=0.5, **kwargs):
FILE: ldm_patched/pfn/architecture/face/fused_act.py
class FusedLeakyReLUFunctionBackward (line 12) | class FusedLeakyReLUFunctionBackward(Function):
method forward (line 14) | def forward(ctx, grad_output, out, negative_slope, scale):
method backward (line 35) | def backward(ctx, gradgrad_input, gradgrad_bias):
class FusedLeakyReLUFunction (line 44) | class FusedLeakyReLUFunction(Function):
method forward (line 46) | def forward(ctx, input, bias, negative_slope, scale):
method backward (line 58) | def backward(ctx, grad_output):
class FusedLeakyReLU (line 68) | class FusedLeakyReLU(nn.Module):
method __init__ (line 69) | def __init__(self, channel, negative_slope=0.2, scale=2**0.5):
method forward (line 76) | def forward(self, input):
function fused_leaky_relu (line 80) | def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2**0.5):
FILE: ldm_patched/pfn/architecture/face/gfpgan_bilinear_arch.py
class StyleGAN2GeneratorBilinearSFT (line 20) | class StyleGAN2GeneratorBilinearSFT(StyleGAN2GeneratorBilinear):
method __init__ (line 34) | def __init__(
method forward (line 54) | def forward(
class GFPGANBilinear (line 152) | class GFPGANBilinear(nn.Module):
method __init__ (line 171) | def __init__(
method forward (line 340) | def forward(self, x, return_latents=False, return_rgb=True, randomize_...
FILE: ldm_patched/pfn/architecture/face/gfpganv1_arch.py
class StyleGAN2GeneratorSFT (line 21) | class StyleGAN2GeneratorSFT(StyleGAN2Generator):
method __init__ (line 35) | def __init__(
method forward (line 57) | def forward(
class ConvUpLayer (line 155) | class ConvUpLayer(nn.Module):
method __init__ (line 168) | def __init__(
method forward (line 206) | def forward(self, x):
class ResUpBlock (line 223) | class ResUpBlock(nn.Module):
method __init__ (line 230) | def __init__(self, in_channels, out_channels):
method forward (line 241) | def forward(self, x):
class GFPGANv1 (line 249) | class GFPGANv1(nn.Module):
method __init__ (line 268) | def __init__(
method forward (line 440) | def forward(
class FacialComponentDiscriminator (line 494) | class FacialComponentDiscriminator(nn.Module):
method __init__ (line 497) | def __init__(self):
method forward (line 547) | def forward(self, x, return_feats=False, **kwargs):
FILE: ldm_patched/pfn/architecture/face/gfpganv1_clean_arch.py
class StyleGAN2GeneratorCSFT (line 13) | class StyleGAN2GeneratorCSFT(StyleGAN2GeneratorClean):
method __init__ (line 25) | def __init__(
method forward (line 43) | def forward(
class ResBlock (line 141) | class ResBlock(nn.Module):
method __init__ (line 149) | def __init__(self, in_channels, out_channels, mode="down"):
method forward (line 160) | def forward(self, x):
class GFPGANv1Clean (line 176) | class GFPGANv1Clean(nn.Module):
method __init__ (line 193) | def __init__(
method forward (line 320) | def forward(
FILE: ldm_patched/pfn/architecture/face/restoreformer_arch.py
class VectorQuantizer (line 11) | class VectorQuantizer(nn.Module):
method __init__ (line 23) | def __init__(self, n_e, e_dim, beta):
method forward (line 32) | def forward(self, z):
method get_codebook_entry (line 96) | def get_codebook_entry(self, indices, shape):
function nonlinearity (line 115) | def nonlinearity(x):
function Normalize (line 120) | def Normalize(in_channels):
class Upsample (line 126) | class Upsample(nn.Module):
method __init__ (line 127) | def __init__(self, in_channels, with_conv):
method forward (line 135) | def forward(self, x):
class Downsample (line 142) | class Downsample(nn.Module):
method __init__ (line 143) | def __init__(self, in_channels, with_conv):
method forward (line 152) | def forward(self, x):
class ResnetBlock (line 162) | class ResnetBlock(nn.Module):
method __init__ (line 163) | def __init__(
method forward (line 199) | def forward(self, x, temb):
class MultiHeadAttnBlock (line 222) | class MultiHeadAttnBlock(nn.Module):
method __init__ (line 223) | def __init__(self, in_channels, head_size=1):
method forward (line 249) | def forward(self, x, y=None):
class MultiHeadEncoder (line 292) | class MultiHeadEncoder(nn.Module):
method __init__ (line 293) | def __init__(
method forward (line 379) | def forward(self, x):
class MultiHeadDecoder (line 417) | class MultiHeadDecoder(nn.Module):
method __init__ (line 418) | def __init__(
method forward (line 509) | def forward(self, z):
class MultiHeadDecoderTransformer (line 544) | class MultiHeadDecoderTransformer(nn.Module):
method __init__ (line 545) | def __init__(
method forward (line 636) | def forward(self, z, hs):
class RestoreFormer (line 674) | class RestoreFormer(nn.Module):
method __init__ (line 675) | def __init__(
method encode (line 760) | def encode(self, x):
method decode (line 766) | def decode(self, quant, hs):
method forward (line 772) | def forward(self, input, **kwargs):
FILE: ldm_patched/pfn/architecture/face/stylegan2_arch.py
class NormStyleCode (line 14) | class NormStyleCode(nn.Module):
method forward (line 15) | def forward(self, x):
function make_resample_kernel (line 27) | def make_resample_kernel(k):
class UpFirDnUpsample (line 44) | class UpFirDnUpsample(nn.Module):
method __init__ (line 57) | def __init__(self, resample_kernel, factor=2):
method forward (line 65) | def forward(self, x):
method __repr__ (line 69) | def __repr__(self):
class UpFirDnDownsample (line 73) | class UpFirDnDownsample(nn.Module):
method __init__ (line 82) | def __init__(self, resample_kernel, factor=2):
method forward (line 90) | def forward(self, x):
method __repr__ (line 94) | def __repr__(self):
class UpFirDnSmooth (line 98) | class UpFirDnSmooth(nn.Module):
method __init__ (line 109) | def __init__(
method forward (line 128) | def forward(self, x):
method __repr__ (line 132) | def __repr__(self):
class EqualLinear (line 139) | class EqualLinear(nn.Module):
method __init__ (line 153) | def __init__(
method forward (line 180) | def forward(self, x):
method __repr__ (line 192) | def __repr__(self):
class ModulatedConv2d (line 199) | class ModulatedConv2d(nn.Module):
method __init__ (line 219) | def __init__(
method forward (line 276) | def forward(self, x, style):
method __repr__ (line 324) | def __repr__(self):
class StyleConv (line 333) | class StyleConv(nn.Module):
method __init__ (line 348) | def __init__(
method forward (line 371) | def forward(self, x, style, noise=None):
class ToRGB (line 384) | class ToRGB(nn.Module):
method __init__ (line 395) | def __init__(
method forward (line 413) | def forward(self, x, style, skip=None):
class ConstantInput (line 433) | class ConstantInput(nn.Module):
method __init__ (line 441) | def __init__(self, num_channel, size):
method forward (line 445) | def forward(self, batch):
class StyleGAN2Generator (line 450) | class StyleGAN2Generator(nn.Module):
method __init__ (line 466) | def __init__(
method make_noise (line 572) | def make_noise(self):
method get_latent (line 583) | def get_latent(self, x):
method mean_latent (line 586) | def mean_latent(self, num_latent):
method forward (line 593) | def forward(
class ScaledLeakyReLU (line 683) | class ScaledLeakyReLU(nn.Module):
method __init__ (line 690) | def __init__(self, negative_slope=0.2):
method forward (line 694) | def forward(self, x):
class EqualConv2d (line 699) | class EqualConv2d(nn.Module):
method __init__ (line 714) | def __init__(
method forward (line 740) | def forward(self, x):
method __repr__ (line 751) | def __repr__(self):
class ConvLayer (line 761) | class ConvLayer(nn.Sequential):
method __init__ (line 778) | def __init__(
class ResBlock (line 825) | class ResBlock(nn.Module):
method __init__ (line 837) | def __init__(self, in_channels, out_channels, resample_kernel=(1, 3, 3...
method forward (line 860) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/face/stylegan2_bilinear_arch.py
class NormStyleCode (line 13) | class NormStyleCode(nn.Module):
method forward (line 14) | def forward(self, x):
class EqualLinear (line 24) | class EqualLinear(nn.Module):
method __init__ (line 37) | def __init__(
method forward (line 64) | def forward(self, x):
method __repr__ (line 76) | def __repr__(self):
class ModulatedConv2d (line 83) | class ModulatedConv2d(nn.Module):
method __init__ (line 99) | def __init__(
method forward (line 139) | def forward(self, x, style):
method __repr__ (line 184) | def __repr__(self):
class StyleConv (line 193) | class StyleConv(nn.Module):
method __init__ (line 205) | def __init__(
method forward (line 228) | def forward(self, x, style, noise=None):
class ToRGB (line 241) | class ToRGB(nn.Module):
method __init__ (line 249) | def __init__(
method forward (line 270) | def forward(self, x, style, skip=None):
class ConstantInput (line 293) | class ConstantInput(nn.Module):
method __init__ (line 300) | def __init__(self, num_channel, size):
method forward (line 304) | def forward(self, batch):
class StyleGAN2GeneratorBilinear (line 309) | class StyleGAN2GeneratorBilinear(nn.Module):
method __init__ (line 321) | def __init__(
method make_noise (line 427) | def make_noise(self):
method get_latent (line 438) | def get_latent(self, x):
method mean_latent (line 441) | def mean_latent(self, num_latent):
method forward (line 448) | def forward(
class ScaledLeakyReLU (line 537) | class ScaledLeakyReLU(nn.Module):
method __init__ (line 543) | def __init__(self, negative_slope=0.2):
method forward (line 547) | def forward(self, x):
class EqualConv2d (line 552) | class EqualConv2d(nn.Module):
method __init__ (line 566) | def __init__(
method forward (line 592) | def forward(self, x):
method __repr__ (line 603) | def __repr__(self):
class ConvLayer (line 613) | class ConvLayer(nn.Sequential):
method __init__ (line 625) | def __init__(
class ResBlock (line 674) | class ResBlock(nn.Module):
method __init__ (line 681) | def __init__(self, in_channels, out_channels, interpolation_mode="bili...
method forward (line 704) | def forward(self, x):
FILE: ldm_patched/pfn/architecture/face/stylegan2_clean_arch.py
function default_init_weights (line 13) | def default_init_weights(module_list, scale=1, bias_fill=0, **kwargs):
class NormStyleCode (line 42) | class NormStyleCode(nn.Module):
method forward (line 43) | def forward(self, x):
class ModulatedConv2d (line 53) | class ModulatedConv2d(nn.Module):
method __init__ (line 66) | def __init__(
method forward (line 102) | def forward(self, x, style):
method __repr__ (line 138) | def __repr__(self):
class StyleConv (line 145) | class StyleConv(nn.Module):
method __init__ (line 156) | def __init__(
method forward (line 178) | def forward(self, x, style, noise=None):
class ToRGB (line 193) | class ToRGB(nn.Module):
method __init__ (line 201) | def __init__(self, in_channels, num_style_feat, upsample=True):
method forward (line 214) | def forward(self, x, style, skip=None):
class ConstantInput (line 234) | class ConstantInput(nn.Module):
method __init__ (line 241) | def __init__(self, num_channel, size):
method forward (line 245) | def forward(self, batch):
class StyleGAN2GeneratorClean (line 250) | class StyleGAN2GeneratorClean(nn.Module):
method __init__ (line 260) | def __init__(
method make_noise (line 350) | def make_noise(self):
method get_latent (line 361) | def get_latent(self, x):
method mean_latent (line 364) | def mean_latent(self, num_latent):
method forward (line 371) | def forward(
FILE: ldm_patched/pfn/architecture/face/upfirdn2d.py
class UpFirDn2dBackward (line 14) | class UpFirDn2dBackward(Function):
method forward (line 16) | def forward(
method backward (line 57) | def backward(ctx, gradgrad_input):
class UpFirDn2d (line 83) | class UpFirDn2d(Function):
method forward (line 85) | def forward(ctx, input, kernel, up, down, pad):
method backward (line 122) | def backward(ctx, grad_output):
function upfirdn2d (line 140) | def upfirdn2d(input, kernel, up=1, down=1, pad=(0, 0)):
function upfirdn2d_native (line 153) | def upfirdn2d_native(
FILE: ldm_patched/pfn/architecture/timm/drop.py
function drop_block_2d (line 22) | def drop_block_2d(
function drop_block_fast_2d (line 91) | def drop_block_fast_2d(
class DropBlock2d (line 141) | class DropBlock2d(nn.Module):
method __init__ (line 144) | def __init__(
method forward (line 163) | def forward(self, x):
function drop_path (line 187) | def drop_path(
class DropPath (line 211) | class DropPath(nn.Module):
method __init__ (line 214) | def __init__(self, drop_prob: float = 0.0, scale_by_keep: bool = True):
method forward (line 219) | def forward(self, x):
method extra_repr (line 222) | def extra_repr(self):
FILE: ldm_patched/pfn/architecture/timm/helpers.py
function _ntuple (line 9) | def _ntuple(n):
function make_divisible (line 25) | def make_divisible(v, divisor=8, min_value=None, round_limit=0.9):
FILE: ldm_patched/pfn/architecture/timm/weight_init.py
function _no_grad_trunc_normal_ (line 8) | def _no_grad_trunc_normal_(tensor, mean, std, a, b):
function trunc_normal_ (line 46) | def trunc_normal_(
function trunc_normal_tf_ (line 73) | def trunc_normal_tf_(
function variance_scaling_ (line 103) | def variance_scaling_(tensor, scale=1.0, mode="fan_in", distribution="no...
function lecun_normal_ (line 127) | def lecun_normal_(tensor):
FILE: ldm_patched/pfn/model_loading.py
class UnsupportedModel (line 20) | class UnsupportedModel(Exception):
function load_state_dict (line 24) | def load_state_dict(state_dict) -> PyTorchModel:
FILE: ldm_patched/pfn/types.py
function is_pytorch_sr_model (line 44) | def is_pytorch_sr_model(model: object):
function is_pytorch_face_model (line 52) | def is_pytorch_face_model(model: object):
function is_pytorch_inpaint_model (line 60) | def is_pytorch_inpaint_model(model: object):
function is_pytorch_model (line 68) | def is_pytorch_model(model: object):
FILE: ldm_patched/t2ia/adapter.py
function conv_nd (line 7) | def conv_nd(dims, *args, **kwargs):
function avg_pool_nd (line 20) | def avg_pool_nd(dims, *args, **kwargs):
class Downsample (line 33) | class Downsample(nn.Module):
method __init__ (line 42) | def __init__(self, channels, use_conv, dims=2, out_channels=None, padd...
method forward (line 57) | def forward(self, x):
class ResnetBlock (line 67) | class ResnetBlock(nn.Module):
method __init__ (line 68) | def __init__(self, in_c, out_c, down, ksize=3, sk=False, use_conv=True):
method forward (line 88) | def forward(self, x):
class Adapter (line 103) | class Adapter(nn.Module):
method __init__ (line 104) | def __init__(self, channels=[320, 640, 1280, 1280], nums_rb=3, cin=64,...
method forward (line 134) | def forward(self, x):
class LayerNorm (line 159) | class LayerNorm(nn.LayerNorm):
method forward (line 162) | def forward(self, x: torch.Tensor):
class QuickGELU (line 168) | class QuickGELU(nn.Module):
method forward (line 170) | def forward(self, x: torch.Tensor):
class ResidualAttentionBlock (line 174) | class ResidualAttentionBlock(nn.Module):
method __init__ (line 176) | def __init__(self, d_model: int, n_head: int, attn_mask: torch.Tensor ...
method attention (line 187) | def attention(self, x: torch.Tensor):
method forward (line 191) | def forward(self, x: torch.Tensor):
class StyleAdapter (line 197) | class StyleAdapter(nn.Module):
method __init__ (line 199) | def __init__(self, width=1024, context_dim=768, num_head=8, n_layes=3,...
method forward (line 210) | def forward(self, x):
class ResnetBlock_light (line 226) | class ResnetBlock_light(nn.Module):
method __init__ (line 227) | def __init__(self, in_c):
method forward (line 233) | def forward(self, x):
class extractor (line 241) | class extractor(nn.Module):
method __init__ (line 242) | def __init__(self, in_c, inter_c, out_c, nums_rb, down=False):
method forward (line 254) | def forward(self, x):
class Adapter_light (line 264) | class Adapter_light(nn.Module):
method __init__ (line 265) | def __init__(self, channels=[320, 640, 1280, 1280], nums_rb=3, cin=64):
method forward (line 282) | def forward(self, x):
FILE: ldm_patched/taesd/taesd.py
function conv (line 12) | def conv(n_in, n_out, **kwargs):
class Clamp (line 15) | class Clamp(nn.Module):
method forward (line 16) | def forward(self, x):
class Block (line 19) | class Block(nn.Module):
method __init__ (line 20) | def __init__(self, n_in, n_out):
method forward (line 25) | def forward(self, x):
function Encoder (line 28) | def Encoder():
function Decoder (line 37) | def Decoder():
class TAESD (line 46) | class TAESD(nn.Module):
method __init__ (line 50) | def __init__(self, encoder_path=None, decoder_path=None):
method scale_latents (line 62) | def scale_latents(x):
method unscale_latents (line 67) | def unscale_latents(x):
method decode (line 71) | def decode(self, x):
method encode (line 76) | def encode(self, x):
FILE: ldm_patched/unipc/uni_pc.py
class NoiseScheduleVP (line 10) | class NoiseScheduleVP:
method __init__ (line 11) | def __init__(
method marginal_log_mean_coeff (line 129) | def marginal_log_mean_coeff(self, t):
method marginal_alpha (line 142) | def marginal_alpha(self, t):
method marginal_std (line 148) | def marginal_std(self, t):
method marginal_lambda (line 154) | def marginal_lambda(self, t):
method inverse_lambda (line 162) | def inverse_lambda(self, lamb):
function model_wrapper (line 181) | def model_wrapper(
class UniPC (line 352) | class UniPC:
method __init__ (line 353) | def __init__(
method dynamic_thresholding_fn (line 379) | def dynamic_thresholding_fn(self, x0, t=None):
method noise_prediction_fn (line 390) | def noise_prediction_fn(self, x, t):
method data_prediction_fn (line 399) | def data_prediction_fn(self, x, t):
method model_fn (line 416) | def model_fn(self, x, t):
method get_time_steps (line 425) | def get_time_steps(self, skip_type, t_T, t_0, N, device):
method get_orders_and_timesteps_for_singlestep_solver (line 442) | def get_orders_and_timesteps_for_singlestep_solver(self, steps, order,...
method denoise_to_zero_fn (line 473) | def denoise_to_zero_fn(self, x, s):
method multistep_uni_pc_update (line 479) | def multistep_uni_pc_update(self, x, model_prev_list, t_prev_list, t, ...
method multistep_uni_pc_vary_update (line 488) | def multistep_uni_pc_vary_update(self, x, model_prev_list, t_prev_list...
method multistep_uni_pc_bh_update (line 591) | def multistep_uni_pc_bh_update(self, x, model_prev_list, t_prev_list, ...
method sample (line 712) | def sample(self, x, timesteps, t_start=None, t_end=None, order=3, skip...
function interpolate_fn (line 781) | def interpolate_fn(x, xp, yp):
function expand_dims (line 823) | def expand_dims(v, dims):
class SigmaConvert (line 836) | class SigmaConvert:
method marginal_log_mean_coeff (line 838) | def marginal_log_mean_coeff(self, sigma):
method marginal_alpha (line 841) | def marginal_alpha(self, t):
method marginal_std (line 844) | def marginal_std(self, t):
method marginal_lambda (line 847) | def marginal_lambda(self, t):
function predict_eps_sigma (line 855) | def predict_eps_sigma(model, input, sigma_in, **kwargs):
function sample_unipc (line 861) | def sample_unipc(model, noise, image, sigmas, max_denoise, extra_args=No...
FILE: ldm_patched/utils/latent_visualization.py
class LatentPreviewer (line 12) | class LatentPreviewer:
method decode_latent_to_preview (line 13) | def decode_latent_to_preview(self, x0):
method decode_latent_to_preview_image (line 16) | def decode_latent_to_preview_image(self, preview_format, x0):
class TAESDPreviewerImpl (line 20) | class TAESDPreviewerImpl(LatentPreviewer):
method __init__ (line 21) | def __init__(self, taesd):
method decode_latent_to_preview (line 24) | def decode_latent_to_preview(self, x0):
class Latent2RGBPreviewer (line 34) | class Latent2RGBPreviewer(LatentPreviewer):
method __init__ (line 35) | def __init__(self, latent_rgb_factors):
method decode_latent_to_preview (line 38) | def decode_latent_to_preview(self, x0):
function get_previewer (line 49) | def get_previewer(device, latent_format):
function prepare_callback (line 80) | def prepare_callback(model, steps, x0_output_dict=None):
FILE: ldm_patched/utils/path_utils.py
function set_output_directory (line 49) | def set_output_directory(output_dir):
function set_temp_directory (line 53) | def set_temp_directory(temp_dir):
function set_input_directory (line 57) | def set_input_directory(input_dir):
function get_output_directory (line 61) | def get_output_directory():
function get_temp_directory (line 65) | def get_temp_directory():
function get_input_directory (line 69) | def get_input_directory():
function get_directory_by_type (line 75) | def get_directory_by_type(type_name):
function annotated_filepath (line 87) | def annotated_filepath(name):
function get_annotated_filepath (line 103) | def get_annotated_filepath(name, default_dir=None):
function exists_annotated_filepath (line 115) | def exists_annotated_filepath(name):
function add_model_folder_path (line 125) | def add_model_folder_path(folder_name, full_folder_path):
function get_folder_paths (line 132) | def get_folder_paths(folder_name):
function recursive_search (line 135) | def recursive_search(directory, excluded_dir_names=None):
function filter_files_extensions (line 166) | def filter_files_extensions(files, extensions):
function get_full_path (line 171) | def get_full_path(folder_name, filename):
function get_filename_list_ (line 184) | def get_filename_list_(folder_name):
function cached_filename_list_ (line 196) | def cached_filename_list_(folder_name):
function get_filename_list (line 217) | def get_filename_list(folder_name):
function get_save_image_path (line 225) | def get_save_image_path(filename_prefix, output_dir, image_width=0, imag...
FILE: modules/anisotropic.py
function _compute_zero_padding (line 10) | def _compute_zero_padding(kernel_size: tuple[int, int] | int) -> tuple[i...
function _unpack_2d_ks (line 15) | def _unpack_2d_ks(kernel_size: tuple[int, int] | int) -> tuple[int, int]:
function gaussian (line 27) | def gaussian(
function get_gaussian_kernel1d (line 43) | def get_gaussian_kernel1d(
function get_gaussian_kernel2d (line 55) | def get_gaussian_kernel2d(
function _bilateral_blur (line 75) | def _bilateral_blur(
function bilateral_blur (line 118) | def bilateral_blur(
function adaptive_anisotropic_filter (line 129) | def adaptive_anisotropic_filter(x, g=None):
function joint_bilateral_blur (line 144) | def joint_bilateral_blur(
class _BilateralBlur (line 156) | class _BilateralBlur(torch.nn.Module):
method __init__ (line 157) | def __init__(
method __repr__ (line 172) | def __repr__(self) -> str:
class BilateralBlur (line 183) | class BilateralBlur(_BilateralBlur):
method forward (line 184) | def forward(self, input: Tensor) -> Tensor:
class JointBilateralBlur (line 190) | class JointBilateralBlur(_BilateralBlur):
method forward (line 191) | def forward(self, input: Tensor, guidance: Tensor) -> Tensor:
FILE: modules/async_worker.py
class AsyncTask (line 10) | class AsyncTask:
method __init__ (line 11) | def __init__(self, args):
class EarlyReturnException (line 164) | class EarlyReturnException(BaseException):
function worker (line 168) | def worker():
FILE: modules/auth.py
function auth_list_to_dict (line 8) | def auth_list_to_dict(auth_list):
function load_auth_data (line 19) | def load_auth_data(filename=None):
function check_auth (line 37) | def check_auth(user, password):
FILE: modules/config.py
function get_config_path (line 16) | def get_config_path(key, default_value):
function try_load_deprecated_user_path_config (line 52) | def try_load_deprecated_user_path_config():
function get_presets (line 101) | def get_presets():
function update_presets (line 110) | def update_presets():
function try_get_preset_content (line 114) | def try_get_preset_content(preset):
function get_path_output (line 134) | def get_path_output() -> str:
function get_dir_or_set_default (line 146) | def get_dir_or_set_default(key, default_value, as_array=False, make_dire...
function get_config_item_or_set_default (line 207) | def get_config_item_or_set_default(key, default_value, validator, disabl...
function init_temp_path (line 236) | def init_temp_path(path: str | None, default_path: str) -> str:
function add_ratio (line 767) | def add_ratio(x):
function get_model_filenames (line 800) | def get_model_filenames(folder_paths, extensions=None, name_filter=None):
function update_files (line 813) | def update_files():
function downloading_inpaint_models (line 823) | def downloading_inpaint_models(v):
function downloading_sdxl_lcm_lora (line 861) | def downloading_sdxl_lcm_lora():
function downloading_sdxl_lightning_lora (line 870) | def downloading_sdxl_lightning_lora():
function downloading_sdxl_hyper_sd_lora (line 879) | def downloading_sdxl_hyper_sd_lora():
function downloading_controlnet_canny (line 888) | def downloading_controlnet_canny():
function downloading_controlnet_cpds (line 897) | def downloading_controlnet_cpds():
function downloading_ip_adapters (line 906) | def downloading_ip_adapters(v):
function downloading_upscale_model (line 944) | def downloading_upscale_model():
function downloading_safety_checker_model (line 952) | def downloading_safety_checker_model():
function download_sam_model (line 961) | def download_sam_model(sam_model: str) -> str:
function downloading_sam_vit_b (line 973) | def downloading_sam_vit_b():
function downloading_sam_vit_l (line 982) | def downloading_sam_vit_l():
function downloading_sam_vit_h (line 991) | def downloading_sam_vit_h():
FILE: modules/core.py
class StableDiffusionModel (line 37) | class StableDiffusionModel:
method __init__ (line 38) | def __init__(self, unet=None, vae=None, clip=None, clip_vision=None, f...
method refresh_loras (line 62) | def refresh_loras(self, loras):
function apply_freeu (line 127) | def apply_freeu(model, b1, b2, s1, s2):
function load_controlnet (line 133) | def load_controlnet(ckpt_filename):
function apply_controlnet (line 139) | def apply_controlnet(positive, negative, control_net, image, strength, s...
function load_model (line 146) | def load_model(ckpt_filename, vae_filename=None):
function generate_empty_latent (line 154) | def generate_empty_latent(width=1024, height=1024, batch_size=1):
function decode_vae (line 160) | def decode_vae(vae, latent_image, tiled=False):
function encode_vae (line 169) | def encode_vae(vae, pixels, tiled=False):
function encode_vae_inpaint (line 178) | def encode_vae_inpaint(vae, pixels, mask):
class VAEApprox (line 196) | class VAEApprox(torch.nn.Module):
method __init__ (line 197) | def __init__(self):
method forward (line 209) | def forward(self, x):
function get_previewer (line 224) | def get_previewer(model):
function ksampler (line 265) | def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg...
function pytorch_to_numpy (line 330) | def pytorch_to_numpy(x):
function numpy_to_pytorch (line 336) | def numpy_to_pytorch(x):
FILE: modules/default_pipeline.py
function refresh_controlnets (line 33) | def refresh_controlnets(model_paths):
function assert_model_integrity (line 48) | def assert_model_integrity():
function refresh_base_model (line 62) | def refresh_base_model(name, vae_name=None):
function refresh_refiner_model (line 82) | def refresh_refiner_model(name):
function synthesize_refiner_model (line 113) | def synthesize_refiner_m
Condensed preview — 331 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (9,222K chars).
[
{
"path": ".dockerignore",
"chars": 700,
"preview": "__pycache__\n*.ckpt\n*.safetensors\n*.pth\n*.pt\n*.bin\n*.patch\n*.backup\n*.corrupted\n*.partial\n*.onnx\nsorted_styles.json\n/inpu"
},
{
"path": ".gitattributes",
"chars": 114,
"preview": "# Ensure that shell scripts always use lf line endings, e.g. entrypoint.sh for docker\n* text=auto\n*.sh text eol=lf"
},
{
"path": ".github/CODEOWNERS",
"chars": 20,
"preview": "* @lllyasviel\n"
},
{
"path": ".github/ISSUE_TEMPLATE/bug_report.yml",
"chars": 3740,
"preview": "name: Bug Report\ndescription: You think something is broken in Fooocus\ntitle: \"[Bug]: \"\nlabels: [\"bug\", \"triage\"]\n\nbody:"
},
{
"path": ".github/ISSUE_TEMPLATE/config.yml",
"chars": 181,
"preview": "blank_issues_enabled: false\ncontact_links:\n - name: Ask a question\n url: https://github.com/lllyasviel/Fooocus/discu"
},
{
"path": ".github/ISSUE_TEMPLATE/feature_request.yml",
"chars": 1421,
"preview": "name: Feature request\ndescription: Suggest an idea for this project\ntitle: \"[Feature Request]: \"\nlabels: [\"enhancement\","
},
{
"path": ".github/dependabot.yml",
"chars": 118,
"preview": "version: 2\nupdates:\n - package-ecosystem: \"github-actions\"\n directory: \"/\"\n schedule:\n interval: \"monthly\""
},
{
"path": ".github/workflows/build_container.yml",
"chars": 1190,
"preview": "name: Docker image build\n\non:\n push:\n branches:\n - main\n tags:\n - v*\n\njobs:\n build-and-push-image:\n "
},
{
"path": ".gitignore",
"chars": 716,
"preview": "__pycache__\n*.ckpt\n*.safetensors\n*.pth\n*.pt\n*.bin\n*.patch\n*.backup\n*.corrupted\n*.partial\n*.onnx\nsorted_styles.json\nhash_"
},
{
"path": "Dockerfile",
"chars": 1119,
"preview": "FROM nvidia/cuda:12.4.1-base-ubuntu22.04\nENV DEBIAN_FRONTEND noninteractive\nENV CMDARGS --listen\n\nRUN apt-get update -y "
},
{
"path": "LICENSE",
"chars": 35149,
"preview": " GNU GENERAL PUBLIC LICENSE\n Version 3, 29 June 2007\n\n Copyright (C) 2007 Free "
},
{
"path": "args_manager.py",
"chars": 3117,
"preview": "import ldm_patched.modules.args_parser as args_parser\n\nargs_parser.parser.add_argument(\"--share\", action='store_true', h"
},
{
"path": "auth-example.json",
"chars": 111,
"preview": "[\n {\n \"user\": \"sitting-duck-1\",\n \"pass\": \"very-bad-publicly-known-password-change-it\"\n }\n]\n"
},
{
"path": "build_launcher.py",
"chars": 838,
"preview": "import os\n\nwin32_root = os.path.dirname(os.path.dirname(__file__))\npython_embeded_path = os.path.join(win32_root, 'pytho"
},
{
"path": "css/style.css",
"chars": 8224,
"preview": "/* based on https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/v1.6.0/style.css */\n\n.loader-container {\n disp"
},
{
"path": "development.md",
"chars": 178,
"preview": "## Running unit tests\n\nNative python:\n```\npython -m unittest tests/\n```\n\nEmbedded python (Windows zip file installation "
},
{
"path": "docker-compose.yml",
"chars": 1483,
"preview": "volumes:\n fooocus-data:\n\nservices:\n app:\n build: .\n image: ghcr.io/lllyasviel/fooocus\n ports:\n - \"7865:78"
},
{
"path": "docker.md",
"chars": 5949,
"preview": "# Fooocus on Docker\n\nThe docker image is based on NVIDIA CUDA 12.4 and PyTorch 2.1, see [Dockerfile](Dockerfile) and [re"
},
{
"path": "entry_with_update.py",
"chars": 1337,
"preview": "import os\nimport sys\n\n\nroot = os.path.dirname(os.path.abspath(__file__))\nsys.path.append(root)\nos.chdir(root)\n\n\ntry:\n "
},
{
"path": "entrypoint.sh",
"chars": 632,
"preview": "#!/bin/bash\n\nORIGINALDIR=/content/app\n# Use predefined DATADIR if it is defined\n[[ x\"${DATADIR}\" == \"x\" ]] && DATADIR=/c"
},
{
"path": "environment.yaml",
"chars": 94,
"preview": "name: fooocus\nchannels:\n - defaults\ndependencies:\n - python=3.10\n - pip=23.0\n - packaging\n"
},
{
"path": "experiments_expansion.py",
"chars": 160,
"preview": "from modules.expansion import FooocusExpansion\n\nexpansion = FooocusExpansion()\n\ntext = 'a handsome man'\n\nfor i in range("
},
{
"path": "experiments_face.py",
"chars": 149,
"preview": "import cv2\nimport extras.face_crop as cropper\n\n\nimg = cv2.imread('lena.png')\nresult = cropper.crop_image(img)\ncv2.imwrit"
},
{
"path": "experiments_interrogate.py",
"chars": 376,
"preview": "import cv2\nfrom extras.interrogate import default_interrogator as default_interrogator_photo\nfrom extras.wd14tagger impo"
},
{
"path": "experiments_mask_generation.py",
"chars": 637,
"preview": "# https://github.com/sail-sg/EditAnything/blob/main/sam2groundingdino_edit.py\n\nimport numpy as np\nfrom PIL import Image\n"
},
{
"path": "extras/BLIP/configs/bert_config.json",
"chars": 485,
"preview": "{\n \"architectures\": [\n \"BertModel\"\n ],\n \"attention_probs_dropout_prob\": 0.1,\n \"hidden_act\": \"gelu\",\n \"hidden_dro"
},
{
"path": "extras/BLIP/configs/caption_coco.yaml",
"chars": 651,
"preview": "image_root: '/export/share/datasets/vision/coco/images/'\nann_root: 'annotation'\ncoco_gt_root: 'annotation/coco_gt'\n\n# se"
},
{
"path": "extras/BLIP/configs/med_config.json",
"chars": 485,
"preview": "{\n \"architectures\": [\n \"BertModel\"\n ],\n \"attention_probs_dropout_prob\": 0.1,\n \"hidden_act\": \"gelu\",\n \"hidden_dro"
},
{
"path": "extras/BLIP/configs/nlvr.yaml",
"chars": 441,
"preview": "image_root: '/export/share/datasets/vision/NLVR2/' \nann_root: 'annotation'\n\n# set pretrained as a file path or an url\npr"
},
{
"path": "extras/BLIP/configs/nocaps.yaml",
"chars": 352,
"preview": "image_root: '/export/share/datasets/vision/nocaps/'\nann_root: 'annotation'\n\n# set pretrained as a file path or an url\npr"
},
{
"path": "extras/BLIP/configs/pretrain.yaml",
"chars": 479,
"preview": "train_file: ['/export/share/junnan-li/VL_pretrain/annotation/coco_karpathy_train.json',\n '/export/share/junn"
},
{
"path": "extras/BLIP/configs/retrieval_coco.yaml",
"chars": 655,
"preview": "image_root: '/export/share/datasets/vision/coco/images/'\nann_root: 'annotation'\ndataset: 'coco'\n\n# set pretrained as a f"
},
{
"path": "extras/BLIP/configs/retrieval_flickr.yaml",
"chars": 658,
"preview": "image_root: '/export/share/datasets/vision/flickr30k/'\nann_root: 'annotation'\ndataset: 'flickr'\n\n# set pretrained as a f"
},
{
"path": "extras/BLIP/configs/retrieval_msrvtt.yaml",
"chars": 354,
"preview": "video_root: '/export/share/dongxuli/data/msrvtt_retrieval/videos'\nann_root: 'annotation'\n\n# set pretrained as a file pat"
},
{
"path": "extras/BLIP/configs/vqa.yaml",
"chars": 639,
"preview": "vqa_root: '/export/share/datasets/vision/VQA/Images/mscoco/' #followed by train2014/\nvg_root: '/export/share/datasets/vi"
},
{
"path": "extras/BLIP/models/bert_tokenizer/config.json",
"chars": 570,
"preview": "{\n \"architectures\": [\n \"BertForMaskedLM\"\n ],\n \"attention_probs_dropout_prob\": 0.1,\n \"gradient_checkpointing\": fal"
},
{
"path": "extras/BLIP/models/bert_tokenizer/tokenizer.json",
"chars": 462763,
"preview": "{\"version\":\"1.0\",\"truncation\":null,\"padding\":null,\"added_tokens\":[{\"id\":0,\"special\":true,\"content\":\"[PAD]\",\"single_word\""
},
{
"path": "extras/BLIP/models/bert_tokenizer/tokenizer_config.json",
"chars": 28,
"preview": "{\n \"do_lower_case\": true\n}\n"
},
{
"path": "extras/BLIP/models/bert_tokenizer/vocab.txt",
"chars": 228209,
"preview": "[PAD]\n[unused0]\n[unused1]\n[unused2]\n[unused3]\n[unused4]\n[unused5]\n[unused6]\n[unused7]\n[unused8]\n[unused9]\n[unused10]\n[un"
},
{
"path": "extras/BLIP/models/blip.py",
"chars": 11100,
"preview": "'''\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
},
{
"path": "extras/BLIP/models/blip_itm.py",
"chars": 3184,
"preview": "from extras.BLIP.models.med import BertConfig, BertModel\nfrom transformers import BertTokenizer\n\nimport torch\nfrom torch"
},
{
"path": "extras/BLIP/models/blip_nlvr.py",
"chars": 4495,
"preview": "from extras.BLIP.models.med import BertConfig\nfrom extras.BLIP.models.nlvr_encoder import BertModel\nfrom extras.BLIP.mod"
},
{
"path": "extras/BLIP/models/blip_pretrain.py",
"chars": 16084,
"preview": "'''\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
},
{
"path": "extras/BLIP/models/blip_retrieval.py",
"chars": 13783,
"preview": "from extras.BLIP.models.med import BertConfig, BertModel\nfrom transformers import BertTokenizer\n\nimport torch\nfrom torch"
},
{
"path": "extras/BLIP/models/blip_vqa.py",
"chars": 8993,
"preview": "from extras.BLIP.models.med import BertConfig, BertModel, BertLMHeadModel\nfrom extras.BLIP.models.blip import create_vit"
},
{
"path": "extras/BLIP/models/med.py",
"chars": 41786,
"preview": "'''\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
},
{
"path": "extras/BLIP/models/nlvr_encoder.py",
"chars": 36738,
"preview": "import math\nimport os\nimport warnings\nfrom dataclasses import dataclass\nfrom typing import Optional, Tuple\n\nimport torch"
},
{
"path": "extras/BLIP/models/vit.py",
"chars": 14204,
"preview": "'''\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
},
{
"path": "extras/GroundingDINO/config/GroundingDINO_SwinT_OGC.py",
"chars": 1005,
"preview": "batch_size = 1\nmodelname = \"groundingdino\"\nbackbone = \"swin_T_224_1k\"\nposition_embedding = \"sine\"\npe_temperatureH = 20\np"
},
{
"path": "extras/GroundingDINO/util/inference.py",
"chars": 3594,
"preview": "from typing import Tuple, List\n\nimport ldm_patched.modules.model_management as model_management\nfrom ldm_patched.modules"
},
{
"path": "extras/censor.py",
"chars": 2535,
"preview": "import os\n\nimport numpy as np\nimport torch\nfrom transformers import CLIPConfig, CLIPImageProcessor\n\nimport ldm_patched.m"
},
{
"path": "extras/expansion.py",
"chars": 4675,
"preview": "# Fooocus GPT2 Expansion\n# Algorithm created by Lvmin Zhang at 2023, Stanford\n# If used inside Fooocus, any use is permi"
},
{
"path": "extras/face_crop.py",
"chars": 1683,
"preview": "import cv2\nimport numpy as np\nimport modules.config\n\n\nfaceRestoreHelper = None\n\n\ndef align_warp_face(self, landmark, bor"
},
{
"path": "extras/facexlib/detection/__init__.py",
"chars": 1346,
"preview": "import torch\nfrom copy import deepcopy\n\nfrom extras.facexlib.utils import load_file_from_url\nfrom .retinaface import Ret"
},
{
"path": "extras/facexlib/detection/align_trans.py",
"chars": 7941,
"preview": "import cv2\nimport numpy as np\n\nfrom .matlab_cp2tform import get_similarity_transform_for_cv2\n\n# reference facial points,"
},
{
"path": "extras/facexlib/detection/matlab_cp2tform.py",
"chars": 8109,
"preview": "import numpy as np\nfrom numpy.linalg import inv, lstsq\nfrom numpy.linalg import matrix_rank as rank\nfrom numpy.linalg im"
},
{
"path": "extras/facexlib/detection/retinaface.py",
"chars": 13365,
"preview": "import cv2\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom PIL import Image\nf"
},
{
"path": "extras/facexlib/detection/retinaface_net.py",
"chars": 6281,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef conv_bn(inp, oup, stride=1, leaky=0):\n retur"
},
{
"path": "extras/facexlib/detection/retinaface_utils.py",
"chars": 16362,
"preview": "import numpy as np\nimport torch\nimport torchvision\nfrom itertools import product as product\nfrom math import ceil\n\n\nclas"
},
{
"path": "extras/facexlib/parsing/__init__.py",
"chars": 1042,
"preview": "import torch\n\nfrom extras.facexlib.utils import load_file_from_url\nfrom .bisenet import BiSeNet\nfrom .parsenet import Pa"
},
{
"path": "extras/facexlib/parsing/bisenet.py",
"chars": 5190,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom .resnet import ResNet18\n\n\nclass ConvBNReLU(nn.M"
},
{
"path": "extras/facexlib/parsing/parsenet.py",
"chars": 6477,
"preview": "\"\"\"Modified from https://github.com/chaofengc/PSFRGAN\n\"\"\"\nimport numpy as np\nimport torch.nn as nn\nfrom torch.nn import "
},
{
"path": "extras/facexlib/parsing/resnet.py",
"chars": 2357,
"preview": "import torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef conv3x3(in_planes, out_planes, stride=1):\n \"\"\"3x3 convolu"
},
{
"path": "extras/facexlib/utils/__init__.py",
"chars": 330,
"preview": "from .face_utils import align_crop_face_landmarks, compute_increased_bbox, get_valid_bboxes, paste_face_back\nfrom .misc "
},
{
"path": "extras/facexlib/utils/face_restoration_helper.py",
"chars": 17303,
"preview": "import cv2\nimport numpy as np\nimport os\nimport torch\nfrom torchvision.transforms.functional import normalize\n\nfrom extra"
},
{
"path": "extras/facexlib/utils/face_utils.py",
"chars": 10213,
"preview": "import cv2\nimport numpy as np\nimport torch\n\n\ndef compute_increased_bbox(bbox, increase_area, preserve_aspect=True):\n "
},
{
"path": "extras/facexlib/utils/misc.py",
"chars": 4081,
"preview": "import cv2\nimport os\nimport os.path as osp\nimport torch\nfrom torch.hub import download_url_to_file, get_dir\nfrom urllib."
},
{
"path": "extras/inpaint_mask.py",
"chars": 4958,
"preview": "import sys\n\nimport modules.config\nimport numpy as np\nimport torch\nfrom extras.GroundingDINO.util.inference import defaul"
},
{
"path": "extras/interrogate.py",
"chars": 2443,
"preview": "import os\nimport torch\nimport ldm_patched.modules.model_management as model_management\n\nfrom torchvision import transfor"
},
{
"path": "extras/ip_adapter.py",
"chars": 10979,
"preview": "import torch\nimport ldm_patched.modules.clip_vision\nimport safetensors.torch as sf\nimport ldm_patched.modules.model_mana"
},
{
"path": "extras/preprocessors.py",
"chars": 2678,
"preview": "import cv2\nimport numpy as np\n\n\ndef centered_canny(x: np.ndarray, canny_low_threshold, canny_high_threshold):\n assert"
},
{
"path": "extras/resampler.py",
"chars": 3557,
"preview": "# modified from https://github.com/mlfoundations/open_flamingo/blob/main/open_flamingo/src/helpers.py\nimport math\n\nimpor"
},
{
"path": "extras/safety_checker/configs/config.json",
"chars": 4549,
"preview": "{\n \"_name_or_path\": \"clip-vit-large-patch14/\",\n \"architectures\": [\n \"SafetyChecker\"\n ],\n \"initializer_factor\": 1."
},
{
"path": "extras/safety_checker/configs/preprocessor_config.json",
"chars": 342,
"preview": "{\n \"crop_size\": 224,\n \"do_center_crop\": true,\n \"do_convert_rgb\": true,\n \"do_normalize\": true,\n \"do_resize\": true,\n "
},
{
"path": "extras/safety_checker/models/safety_checker.py",
"chars": 5885,
"preview": "# from https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/safety_checker.py\n\n# "
},
{
"path": "extras/sam/predictor.py",
"chars": 12634,
"preview": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the li"
},
{
"path": "extras/vae_interpose.py",
"chars": 3364,
"preview": "# https://github.com/city96/SD-Latent-Interposer/blob/main/interposer.py\n\nimport os\n\nimport safetensors.torch as sf\nimpo"
},
{
"path": "extras/wd14tagger.py",
"chars": 3451,
"preview": "# https://huggingface.co/spaces/SmilingWolf/wd-v1-4-tags\n# https://github.com/pythongosssss/ComfyUI-WD14-Tagger/blob/mai"
},
{
"path": "fooocus_colab.ipynb",
"chars": 639,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"id\": \"VjYy0F2gZIPR\"\n },\n "
},
{
"path": "fooocus_version.py",
"chars": 17,
"preview": "version = '2.5.5'"
},
{
"path": "javascript/contextMenus.js",
"chars": 5384,
"preview": "// based on https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/v1.6.0/javascript/contextMenus.js\n\nvar contextM"
},
{
"path": "javascript/edit-attention.js",
"chars": 4707,
"preview": "function updateInput(target) {\n let e = new Event(\"input\", {bubbles: true});\n Object.defineProperty(e, \"target\", {"
},
{
"path": "javascript/imageviewer.js",
"chars": 8255,
"preview": "// From A1111\n\nfunction closeModal() {\n gradioApp().getElementById(\"lightboxModal\").style.display = \"none\";\n}\n\nfuncti"
},
{
"path": "javascript/localization.js",
"chars": 4218,
"preview": "var re_num = /^[.\\d]+$/;\n\nvar original_lines = {};\nvar translated_lines = {};\n\nfunction hasLocalization() {\n return w"
},
{
"path": "javascript/script.js",
"chars": 8358,
"preview": "// based on https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/v1.6.0/script.js\nfunction gradioApp() {\n con"
},
{
"path": "javascript/viewer.js",
"chars": 2540,
"preview": "window.main_viewer_height = 512;\n\nfunction refresh_grid() {\n let gridContainer = document.querySelector('#final_galle"
},
{
"path": "javascript/zoom.js",
"chars": 23630,
"preview": "onUiLoaded(async() => {\n // Helper functions\n\n // Detect whether the element has a horizontal scroll bar\n funct"
},
{
"path": "language/en.json",
"chars": 25106,
"preview": "{\n \"Preview\": \"Preview\",\n \"Gallery\": \"Gallery\",\n \"Generate\": \"Generate\",\n \"Skip\": \"Skip\",\n \"Stop\": \"Stop\""
},
{
"path": "language/example.json",
"chars": 103,
"preview": "{\n \"Generate\": \"生成\",\n \"Input Image\": \"入力画像\",\n \"Advanced\": \"고급\",\n \"SAI 3D Model\": \"SAI 3D Modèle\"\n}\n"
},
{
"path": "launch.py",
"chars": 6428,
"preview": "import os\nimport ssl\nimport sys\n\nprint('[System ARGV] ' + str(sys.argv))\n\nroot = os.path.dirname(os.path.abspath(__file_"
},
{
"path": "ldm_patched/contrib/external.py",
"chars": 75043,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\n\nimport os\nimport sys\nimport json\nimport"
},
{
"path": "ldm_patched/contrib/external_align_your_steps.py",
"chars": 2087,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py\n\n#from: https://research.nvidia.com/labs/toronto-ai/Ali"
},
{
"path": "ldm_patched/contrib/external_canny.py",
"chars": 11564,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\n#From https://github.com/kornia/kornia\nimport math\n\ni"
},
{
"path": "ldm_patched/contrib/external_clip_sdxl.py",
"chars": 2763,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\nfrom ldm_patched.contrib.external import"
},
{
"path": "ldm_patched/contrib/external_compositing.py",
"chars": 8000,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport numpy as np\nimport torch\nimport ldm_patched.mo"
},
{
"path": "ldm_patched/contrib/external_custom_sampler.py",
"chars": 12105,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport ldm_patched.modules.samplers\nimport ldm_patche"
},
{
"path": "ldm_patched/contrib/external_freelunch.py",
"chars": 4890,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\n#code originally taken from: https://github.com/Cheny"
},
{
"path": "ldm_patched/contrib/external_hypernetwork.py",
"chars": 4682,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport ldm_patched.modules.utils\nimport ldm_patched.u"
},
{
"path": "ldm_patched/contrib/external_hypertile.py",
"chars": 3138,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\n#Taken from: https://github.com/tfernd/HyperTile/\n\nim"
},
{
"path": "ldm_patched/contrib/external_images.py",
"chars": 7066,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport ldm_patched.contrib.external\nimport ldm_patche"
},
{
"path": "ldm_patched/contrib/external_latent.py",
"chars": 4749,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport ldm_patched.modules.utils\nimport torch\n\ndef re"
},
{
"path": "ldm_patched/contrib/external_mask.py",
"chars": 12401,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport numpy as np\nimport scipy.ndimage\nimport torch\n"
},
{
"path": "ldm_patched/contrib/external_model_advanced.py",
"chars": 7436,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport ldm_patched.utils.path_utils\nimport ldm_patche"
},
{
"path": "ldm_patched/contrib/external_model_downscale.py",
"chars": 2623,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\nimport ldm_patched.modules.utils\n\nclass "
},
{
"path": "ldm_patched/contrib/external_model_merging.py",
"chars": 10691,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport ldm_patched.modules.sd\nimport ldm_patched.modu"
},
{
"path": "ldm_patched/contrib/external_perpneg.py",
"chars": 1945,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\nimport ldm_patched.modules.model_managem"
},
{
"path": "ldm_patched/contrib/external_photomaker.py",
"chars": 7750,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\nimport torch.nn as nn\nimport ldm_patched"
},
{
"path": "ldm_patched/contrib/external_post_processing.py",
"chars": 9751,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport numpy as np\nimport torch\nimport torch.nn.funct"
},
{
"path": "ldm_patched/contrib/external_rebatch.py",
"chars": 5282,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\n\nclass LatentRebatch:\n @classmethod\n "
},
{
"path": "ldm_patched/contrib/external_sag.py",
"chars": 6055,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\nfrom torch import einsum\nimport torch.nn"
},
{
"path": "ldm_patched/contrib/external_sdupscale.py",
"chars": 1851,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\nimport ldm_patched.contrib.external\nimpo"
},
{
"path": "ldm_patched/contrib/external_stable3d.py",
"chars": 5210,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport torch\nimport ldm_patched.contrib.external\nimpo"
},
{
"path": "ldm_patched/contrib/external_tomesd.py",
"chars": 6692,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\n#Taken from: https://github.com/dbolya/tomesd\n\nimport"
},
{
"path": "ldm_patched/contrib/external_upscale_model.py",
"chars": 2485,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport os\nfrom ldm_patched.pfn import model_loading\nf"
},
{
"path": "ldm_patched/contrib/external_video_model.py",
"chars": 5226,
"preview": "# https://github.com/comfyanonymous/ComfyUI/blob/master/nodes.py \n\nimport ldm_patched.contrib.external\nimport torch\nimpo"
},
{
"path": "ldm_patched/controlnet/cldm.py",
"chars": 13559,
"preview": "#taken from: https://github.com/lllyasviel/ControlNet\n#and modified\n\nimport torch\nimport torch as th\nimport torch.nn as "
},
{
"path": "ldm_patched/k_diffusion/sampling.py",
"chars": 40407,
"preview": "import math\n\nfrom scipy import integrate\nimport torch\nfrom torch import nn\nimport torchsde\nfrom tqdm.auto import trange,"
},
{
"path": "ldm_patched/k_diffusion/utils.py",
"chars": 12718,
"preview": "from contextlib import contextmanager\nimport hashlib\nimport math\nfrom pathlib import Path\nimport shutil\nimport urllib\nim"
},
{
"path": "ldm_patched/ldm/models/autoencoder.py",
"chars": 7802,
"preview": "import torch\n# import pytorch_lightning as pl\nimport torch.nn.functional as F\nfrom contextlib import contextmanager\nfrom"
},
{
"path": "ldm_patched/ldm/modules/attention.py",
"chars": 28133,
"preview": "import math\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn, einsum\nfrom einops import rearrange, repe"
},
{
"path": "ldm_patched/ldm/modules/diffusionmodules/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "ldm_patched/ldm/modules/diffusionmodules/model.py",
"chars": 24629,
"preview": "# pytorch_diffusion + derived encoder decoder\nimport math\nimport torch\nimport torch.nn as nn\nimport numpy as np\nfrom ein"
},
{
"path": "ldm_patched/ldm/modules/diffusionmodules/openaimodel.py",
"chars": 35904,
"preview": "from abc import abstractmethod\n\nimport torch as th\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom einops imp"
},
{
"path": "ldm_patched/ldm/modules/diffusionmodules/upscaling.py",
"chars": 3686,
"preview": "import torch\nimport torch.nn as nn\nimport numpy as np\nfrom functools import partial\n\nfrom .util import extract_into_tens"
},
{
"path": "ldm_patched/ldm/modules/diffusionmodules/util.py",
"chars": 11802,
"preview": "# adopted from\n# https://github.com/openai/improved-diffusion/blob/main/improved_diffusion/gaussian_diffusion.py\n# and\n#"
},
{
"path": "ldm_patched/ldm/modules/distributions/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "ldm_patched/ldm/modules/distributions/distributions.py",
"chars": 2970,
"preview": "import torch\nimport numpy as np\n\n\nclass AbstractDistribution:\n def sample(self):\n raise NotImplementedError()\n"
},
{
"path": "ldm_patched/ldm/modules/ema.py",
"chars": 3110,
"preview": "import torch\nfrom torch import nn\n\n\nclass LitEma(nn.Module):\n def __init__(self, model, decay=0.9999, use_num_upates="
},
{
"path": "ldm_patched/ldm/modules/encoders/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "ldm_patched/ldm/modules/encoders/noise_aug_modules.py",
"chars": 1567,
"preview": "from ..diffusionmodules.upscaling import ImageConcatWithNoiseAugmentation\nfrom ..diffusionmodules.openaimodel import Tim"
},
{
"path": "ldm_patched/ldm/modules/sub_quadratic_attention.py",
"chars": 9469,
"preview": "# original source:\n# https://github.com/AminRezaei0x443/memory-efficient-attention/blob/1bc0d9e6ac5f82ea43a375135c4e1d"
},
{
"path": "ldm_patched/ldm/modules/temporal_ae.py",
"chars": 7959,
"preview": "import functools\nfrom typing import Callable, Iterable, Union\n\nimport torch\nfrom einops import rearrange, repeat\n\nimport"
},
{
"path": "ldm_patched/ldm/util.py",
"chars": 7227,
"preview": "import importlib\n\nimport torch\nfrom torch import optim\nimport numpy as np\n\nfrom inspect import isfunction\nfrom PIL impor"
},
{
"path": "ldm_patched/licenses-3rd/chainer",
"chars": 1117,
"preview": "Copyright (c) 2015 Preferred Infrastructure, Inc.\nCopyright (c) 2015 Preferred Networks, Inc.\n\nPermission is hereby gran"
},
{
"path": "ldm_patched/licenses-3rd/comfyui",
"chars": 35148,
"preview": " GNU GENERAL PUBLIC LICENSE\n Version 3, 29 June 2007\n\n Copyright (C) 2007 Free "
},
{
"path": "ldm_patched/licenses-3rd/diffusers",
"chars": 11356,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/licenses-3rd/kdiffusion",
"chars": 1060,
"preview": "Copyright (c) 2022 Katherine Crowson\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof th"
},
{
"path": "ldm_patched/licenses-3rd/ldm",
"chars": 1101,
"preview": "MIT License\n\nCopyright (c) 2022 Machine Vision and Learning Group, LMU Munich\n\nPermission is hereby granted, free of cha"
},
{
"path": "ldm_patched/licenses-3rd/taesd",
"chars": 1072,
"preview": "MIT License\n\nCopyright (c) 2023 Ollin Boer Bohan\n\nPermission is hereby granted, free of charge, to any person obtaining "
},
{
"path": "ldm_patched/licenses-3rd/transformers",
"chars": 11417,
"preview": "Copyright 2018- The Hugging Face team. All rights reserved.\n\n Apache License\n "
},
{
"path": "ldm_patched/modules/args_parser.py",
"chars": 5253,
"preview": "import argparse\nimport enum\nimport ldm_patched.modules.options\n\nclass EnumAction(argparse.Action):\n \"\"\"\n Argparse "
},
{
"path": "ldm_patched/modules/checkpoint_pickle.py",
"chars": 286,
"preview": "import pickle\n\nload = pickle.load\n\nclass Empty:\n pass\n\nclass Unpickler(pickle.Unpickler):\n def find_class(self, mo"
},
{
"path": "ldm_patched/modules/clip_config_bigg.json",
"chars": 520,
"preview": "{\n \"architectures\": [\n \"CLIPTextModel\"\n ],\n \"attention_dropout\": 0.0,\n \"bos_token_id\": 0,\n \"dropout\": 0.0,\n \"eo"
},
{
"path": "ldm_patched/modules/clip_model.py",
"chars": 8920,
"preview": "import torch\nfrom ldm_patched.ldm.modules.attention import optimized_attention_for_device\n\nclass CLIPAttention(torch.nn."
},
{
"path": "ldm_patched/modules/clip_vision.py",
"chars": 5241,
"preview": "from .utils import load_torch_file, transformers_convert, state_dict_prefix_replace\nimport os\nimport torch\nimport json\n\n"
},
{
"path": "ldm_patched/modules/clip_vision_config_g.json",
"chars": 419,
"preview": "{\n \"attention_dropout\": 0.0,\n \"dropout\": 0.0,\n \"hidden_act\": \"gelu\",\n \"hidden_size\": 1664,\n \"image_size\": 224,\n \"i"
},
{
"path": "ldm_patched/modules/clip_vision_config_h.json",
"chars": 419,
"preview": "{\n \"attention_dropout\": 0.0,\n \"dropout\": 0.0,\n \"hidden_act\": \"gelu\",\n \"hidden_size\": 1280,\n \"image_size\": 224,\n \"i"
},
{
"path": "ldm_patched/modules/clip_vision_config_vitl.json",
"chars": 424,
"preview": "{\n \"attention_dropout\": 0.0,\n \"dropout\": 0.0,\n \"hidden_act\": \"quick_gelu\",\n \"hidden_size\": 1024,\n \"image_size\": 224"
},
{
"path": "ldm_patched/modules/conds.py",
"chars": 2353,
"preview": "import torch\nimport math\nimport ldm_patched.modules.utils\n\n\n\nclass CONDRegular:\n def __init__(self, cond):\n se"
},
{
"path": "ldm_patched/modules/controlnet.py",
"chars": 21905,
"preview": "import torch\nimport math\nimport os\nimport ldm_patched.modules.utils\nimport ldm_patched.modules.model_management\nimport l"
},
{
"path": "ldm_patched/modules/diffusers_convert.py",
"chars": 9852,
"preview": "import re\nimport torch\n\n# conversion code from https://github.com/huggingface/diffusers/blob/main/scripts/convert_diffus"
},
{
"path": "ldm_patched/modules/diffusers_load.py",
"chars": 1496,
"preview": "import os\n\nimport ldm_patched.modules.sd\n\ndef first_file(path, filenames):\n for f in filenames:\n p = os.path.j"
},
{
"path": "ldm_patched/modules/gligen.py",
"chars": 11685,
"preview": "import torch\nfrom torch import nn\nfrom ldm_patched.ldm.modules.attention import CrossAttention\nfrom inspect import isfun"
},
{
"path": "ldm_patched/modules/latent_formats.py",
"chars": 3675,
"preview": "import torch\n\nclass LatentFormat:\n scale_factor = 1.0\n latent_rgb_factors = None\n taesd_decoder_name = None\n\n "
},
{
"path": "ldm_patched/modules/lora.py",
"chars": 9109,
"preview": "import ldm_patched.modules.utils\n\nLORA_CLIP_MAP = {\n \"mlp.fc1\": \"mlp_fc1\",\n \"mlp.fc2\": \"mlp_fc2\",\n \"self_attn.k"
},
{
"path": "ldm_patched/modules/model_base.py",
"chars": 18585,
"preview": "import torch\nfrom ldm_patched.ldm.modules.diffusionmodules.openaimodel import UNetModel, Timestep\nfrom ldm_patched.ldm.m"
},
{
"path": "ldm_patched/modules/model_detection.py",
"chars": 17382,
"preview": "import ldm_patched.modules.supported_models\nimport ldm_patched.modules.supported_models_base\n\ndef count_blocks(state_dic"
},
{
"path": "ldm_patched/modules/model_management.py",
"chars": 25433,
"preview": "import psutil\nfrom enum import Enum\nfrom ldm_patched.modules.args_parser import args\nimport ldm_patched.modules.utils\nim"
},
{
"path": "ldm_patched/modules/model_patcher.py",
"chars": 16311,
"preview": "import torch\nimport copy\nimport inspect\n\nimport ldm_patched.modules.utils\nimport ldm_patched.modules.model_management\n\nc"
},
{
"path": "ldm_patched/modules/model_sampling.py",
"chars": 8017,
"preview": "import torch\nfrom ldm_patched.ldm.modules.diffusionmodules.util import make_beta_schedule\nimport math\nimport numpy as np"
},
{
"path": "ldm_patched/modules/ops.py",
"chars": 4116,
"preview": "import torch\nimport ldm_patched.modules.model_management\n\ndef cast_bias_weight(s, input):\n bias = None\n non_blocki"
},
{
"path": "ldm_patched/modules/options.py",
"chars": 111,
"preview": "\nargs_parsing = False\n\ndef enable_args_parsing(enable=True):\n global args_parsing\n args_parsing = enable\n"
},
{
"path": "ldm_patched/modules/sample.py",
"chars": 5785,
"preview": "import torch\nimport ldm_patched.modules.model_management\nimport ldm_patched.modules.samplers\nimport ldm_patched.modules."
},
{
"path": "ldm_patched/modules/samplers.py",
"chars": 27868,
"preview": "from ldm_patched.k_diffusion import sampling as k_diffusion_sampling\nfrom ldm_patched.unipc import uni_pc\nimport torch\ni"
},
{
"path": "ldm_patched/modules/sd.py",
"chars": 25123,
"preview": "import torch\n\nfrom ldm_patched.modules import model_management\nfrom ldm_patched.ldm.models.autoencoder import Autoencode"
},
{
"path": "ldm_patched/modules/sd1_clip.py",
"chars": 20413,
"preview": "import os\n\nfrom transformers import CLIPTokenizer\nimport ldm_patched.modules.ops\nimport torch\nimport traceback\nimport zi"
},
{
"path": "ldm_patched/modules/sd1_clip_config.json",
"chars": 612,
"preview": "{\n \"_name_or_path\": \"openai/clip-vit-large-patch14\",\n \"architectures\": [\n \"CLIPTextModel\"\n ],\n \"attention_dropout"
},
{
"path": "ldm_patched/modules/sd1_tokenizer/merges.txt",
"chars": 515308,
"preview": "#version: 0.2\ni n\nt h\na n\nr e\na r\ne r\nth e</w>\nin g</w>\no u\no n\ns t\no r\ne n\no n</w>\na l\na t\ne r</w>\ni t\ni n</w>\nt o</w>\n"
},
{
"path": "ldm_patched/modules/sd1_tokenizer/special_tokens_map.json",
"chars": 472,
"preview": "{\n \"bos_token\": {\n \"content\": \"<|startoftext|>\",\n \"lstrip\": false,\n \"normalized\": true,\n \"rstrip\": false,\n "
},
{
"path": "ldm_patched/modules/sd1_tokenizer/tokenizer_config.json",
"chars": 806,
"preview": "{\n \"add_prefix_space\": false,\n \"bos_token\": {\n \"__type\": \"AddedToken\",\n \"content\": \"<|startoftext|>\",\n \"lstri"
},
{
"path": "ldm_patched/modules/sd1_tokenizer/vocab.json",
"chars": 1050327,
"preview": "{\n \"!\": 0,\n \"!!\": 1443,\n \"!!!\": 11194,\n \"!!!!\": 4003,\n \"!!!!!!!!\": 11281,\n \"!!!!!!!!!!!!!!!!\": 30146,\n \"!!!!!!!!!"
},
{
"path": "ldm_patched/modules/sd2_clip.py",
"chars": 1300,
"preview": "from ldm_patched.modules import sd1_clip\nimport torch\nimport os\n\nclass SD2ClipHModel(sd1_clip.SDClipModel):\n def __in"
},
{
"path": "ldm_patched/modules/sd2_clip_config.json",
"chars": 520,
"preview": "{\n \"architectures\": [\n \"CLIPTextModel\"\n ],\n \"attention_dropout\": 0.0,\n \"bos_token_id\": 0,\n \"dropout\": 0.0,\n \"eo"
},
{
"path": "ldm_patched/modules/sdxl_clip.py",
"chars": 2926,
"preview": "from ldm_patched.modules import sd1_clip\nimport torch\nimport os\n\nclass SDXLClipG(sd1_clip.SDClipModel):\n def __init__"
},
{
"path": "ldm_patched/modules/supported_models.py",
"chars": 11558,
"preview": "import torch\nfrom . import model_base\nfrom . import utils\n\nfrom . import sd1_clip\nfrom . import sd2_clip\nfrom . import s"
},
{
"path": "ldm_patched/modules/supported_models_base.py",
"chars": 2752,
"preview": "import torch\nfrom . import model_base\nfrom . import utils\nfrom . import latent_formats\n\nclass ClipTarget:\n def __init"
},
{
"path": "ldm_patched/modules/utils.py",
"chars": 18699,
"preview": "import torch\nimport math\nimport struct\nimport ldm_patched.modules.checkpoint_pickle\nimport safetensors.torch\nimport nump"
},
{
"path": "ldm_patched/pfn/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "ldm_patched/pfn/architecture/DAT.py",
"chars": 40954,
"preview": "# pylint: skip-file\nimport math\nimport re\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.utils.chec"
},
{
"path": "ldm_patched/pfn/architecture/HAT.py",
"chars": 44835,
"preview": "# pylint: skip-file\n# HAT from https://github.com/XPixelGroup/HAT/blob/main/hat/archs/hat_arch.py\nimport math\nimport re\n"
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-DAT",
"chars": 11357,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-ESRGAN",
"chars": 11357,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-HAT",
"chars": 1069,
"preview": "MIT License\n\nCopyright (c) 2022 Xiangyu Chen\n\nPermission is hereby granted, free of charge, to any person obtaining a co"
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-RealESRGAN",
"chars": 1519,
"preview": "BSD 3-Clause License\n\nCopyright (c) 2021, Xintao Wang\nAll rights reserved.\n\nRedistribution and use in source and binary "
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-SCUNet",
"chars": 11409,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-SPSR",
"chars": 11350,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-SwiftSRGAN",
"chars": 7048,
"preview": "Creative Commons Legal Code\n\nCC0 1.0 Universal\n\n CREATIVE COMMONS CORPORATION IS NOT A LAW FIRM AND DOES NOT PROVIDE\n"
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-Swin2SR",
"chars": 11348,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-SwinIR",
"chars": 11348,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/LICENSE-lama",
"chars": 11348,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/LaMa.py",
"chars": 21411,
"preview": "# pylint: skip-file\n\"\"\"\nModel adapted from advimman's lama project: https://github.com/advimman/lama\n\"\"\"\n\n# Fast Fourier"
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/ChannelAttention.py",
"chars": 3179,
"preview": "import math\n\nimport torch.nn as nn\n\n\nclass CA_layer(nn.Module):\n def __init__(self, channel, reduction=16):\n s"
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/LICENSE",
"chars": 11357,
"preview": " Apache License\n Version 2.0, January 2004\n "
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/OSA.py",
"chars": 15187,
"preview": "#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n#############################################################\n# File: OSA."
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/OSAG.py",
"chars": 1828,
"preview": "#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n#############################################################\n# File: OSAG"
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/OmniSR.py",
"chars": 4570,
"preview": "#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n#############################################################\n# File: Omni"
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/esa.py",
"chars": 8420,
"preview": "#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n#############################################################\n# File: esa."
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/layernorm.py",
"chars": 2300,
"preview": "#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n#############################################################\n# File: laye"
},
{
"path": "ldm_patched/pfn/architecture/OmniSR/pixelshuffle.py",
"chars": 904,
"preview": "#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n#############################################################\n# File: pixe"
},
{
"path": "ldm_patched/pfn/architecture/RRDB.py",
"chars": 10570,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nimport functools\nimport math\nimport re\nfrom collections import OrderedDi"
}
]
// ... and 131 more files (download for full content)
About this extraction
This page contains the full source code of the lllyasviel/Fooocus GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 331 files (8.0 MB), approximately 2.1M tokens, and a symbol index with 2905 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.