Full Code of positive666/Prompt-Can-Anything for AI

gitextract__iw3ng36/

├── .gitignore
├── .gitmodules
├── LICENSE
├── README.md
├── README_zh.md
├── a2f.py
├── app.py
├── audio2face_pb2.py
├── audio2face_pb2_grpc.py
├── audio2face_streaming_utils.py
├── audio_segment.py
├── auto_label_demo.py
├── batch_clean_gpu.txt
├── crazy_functions/
│   ├── Langchain知识库.py
│   ├── Latex全文润色.py
│   ├── Latex全文翻译.py
│   ├── Latex输出PDF结果.py
│   ├── __init__.py
│   ├── chatglm微调工具.py
│   ├── crazy_functions_test.py
│   ├── crazy_utils.py
│   ├── latex_fns/
│   │   ├── latex_actions.py
│   │   └── latex_toolbox.py
│   ├── live_audio/
│   │   ├── aliyunASR.py
│   │   └── audio_io.py
│   ├── test_project/
│   │   ├── cpp/
│   │   │   ├── cppipc/
│   │   │   │   ├── buffer.cpp
│   │   │   │   ├── ipc.cpp
│   │   │   │   ├── policy.h
│   │   │   │   ├── pool_alloc.cpp
│   │   │   │   ├── prod_cons.h
│   │   │   │   ├── queue.h
│   │   │   │   ├── shm.cpp
│   │   │   │   ├── waiter.h
│   │   │   │   └── 来源
│   │   │   ├── libJPG/
│   │   │   │   ├── jpgd.cpp
│   │   │   │   ├── jpgd.h
│   │   │   │   ├── jpge.cpp
│   │   │   │   ├── jpge.h
│   │   │   │   └── 来源
│   │   │   └── longcode/
│   │   │       ├── jpgd.cpp
│   │   │       ├── jpge.cpp
│   │   │       └── prod_cons.h
│   │   ├── latex/
│   │   │   └── attention/
│   │   │       ├── background.tex
│   │   │       ├── introduction.tex
│   │   │       ├── model_architecture.tex
│   │   │       ├── parameter_attention.tex
│   │   │       └── 来源
│   │   ├── python/
│   │   │   └── dqn/
│   │   │       ├── __init__.py
│   │   │       ├── dqn.py
│   │   │       ├── policies.py
│   │   │       └── 来源
│   │   └── 其他测试
│   ├── 下载arxiv论文翻译摘要.py
│   ├── 交互功能函数模板.py
│   ├── 代码重写为全英文_多线程.py
│   ├── 图片生成.py
│   ├── 对话历史存档.py
│   ├── 总结word文档.py
│   ├── 总结音视频.py
│   ├── 批量Markdown翻译.py
│   ├── 批量总结PDF文档.py
│   ├── 批量总结PDF文档pdfminer.py
│   ├── 批量翻译PDF文档_多线程.py
│   ├── 数学动画生成manim.py
│   ├── 理解PDF文档内容.py
│   ├── 生成函数注释.py
│   ├── 联网的ChatGPT.py
│   ├── 联网的ChatGPT_bing版.py
│   ├── 虚空终端.py
│   ├── 解析JupyterNotebook.py
│   ├── 解析项目源代码.py
│   ├── 询问多个大语言模型.py
│   ├── 语音助手.py
│   ├── 读文章写摘要.py
│   ├── 谷歌检索小助手.py
│   ├── 辅助回答.py
│   └── 高级功能函数模板.py
├── gradio_demo.py
├── llm_cards/
│   ├── bridge_all.py
│   ├── bridge_chatglm.py
│   ├── bridge_chatgpt.py
│   ├── bridge_stackclaude.py
│   ├── core_functional.py
│   ├── crazy_functional.py
│   ├── requirements_chatglm.txt
│   └── requirements_slackclaude.txt
├── model_cards/
│   ├── Tag2Text/
│   │   ├── MANIFEST.in
│   │   ├── batch_inference.py
│   │   ├── datasets/
│   │   │   ├── openimages_common_214/
│   │   │   │   ├── imgs/
│   │   │   │   │   └── .gitkeep
│   │   │   │   ├── openimages_common_214_ram_annots.txt
│   │   │   │   ├── openimages_common_214_ram_taglist.txt
│   │   │   │   ├── openimages_common_214_tag2text_idannots.txt
│   │   │   │   └── openimages_common_214_tag2text_tagidlist.txt
│   │   │   └── openimages_rare_200/
│   │   │       ├── imgs/
│   │   │       │   └── .gitkeep
│   │   │       ├── openimages_rare_200_ram_annots.txt
│   │   │       └── openimages_rare_200_ram_taglist.txt
│   │   ├── inference_ram.py
│   │   ├── inference_ram_openset.py
│   │   ├── inference_tag2text.py
│   │   ├── ram/
│   │   │   ├── __init__.py
│   │   │   ├── configs/
│   │   │   │   ├── med_config.json
│   │   │   │   ├── q2l_config.json
│   │   │   │   └── swin/
│   │   │   │       ├── config_swinB_384.json
│   │   │   │       └── config_swinL_384.json
│   │   │   ├── data/
│   │   │   │   ├── ram_tag_list.txt
│   │   │   │   ├── ram_tag_list_chinese.txt
│   │   │   │   ├── ram_tag_list_threshold.txt
│   │   │   │   └── tag_list.txt
│   │   │   ├── inference.py
│   │   │   ├── models/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── bert.py
│   │   │   │   ├── ram.py
│   │   │   │   ├── swin_transformer.py
│   │   │   │   ├── tag2text.py
│   │   │   │   ├── utils.py
│   │   │   │   └── vit.py
│   │   │   ├── transform.py
│   │   │   └── utils/
│   │   │       ├── __init__.py
│   │   │       ├── metrics.py
│   │   │       └── openset_utils.py
│   │   ├── requirements_groundingDINO.txt
│   │   ├── setup.cfg
│   │   └── setup.py
│   ├── autoback.py
│   ├── groundingdino/
│   │   ├── __init__.py
│   │   ├── config/
│   │   │   ├── GroundingDINO_SwinB.cfg.py
│   │   │   └── GroundingDINO_SwinT_OGC.py
│   │   ├── datasets/
│   │   │   ├── __init__.py
│   │   │   └── transforms.py
│   │   ├── models/
│   │   │   ├── GroundingDINO/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── backbone/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── backbone.py
│   │   │   │   │   ├── position_encoding.py
│   │   │   │   │   └── swin_transformer.py
│   │   │   │   ├── bertwarper.py
│   │   │   │   ├── csrc/
│   │   │   │   │   ├── MsDeformAttn/
│   │   │   │   │   │   ├── ms_deform_attn.h
│   │   │   │   │   │   ├── ms_deform_attn_cpu.cpp
│   │   │   │   │   │   ├── ms_deform_attn_cpu.h
│   │   │   │   │   │   ├── ms_deform_attn_cuda.cu
│   │   │   │   │   │   ├── ms_deform_attn_cuda.h
│   │   │   │   │   │   └── ms_deform_im2col_cuda.cuh
│   │   │   │   │   ├── cuda_version.cu
│   │   │   │   │   └── vision.cpp
│   │   │   │   ├── fuse_modules.py
│   │   │   │   ├── groundingdino.py
│   │   │   │   ├── ms_deform_attn.py
│   │   │   │   ├── transformer.py
│   │   │   │   ├── transformer_vanilla.py
│   │   │   │   └── utils.py
│   │   │   ├── __init__.py
│   │   │   └── registry.py
│   │   ├── util/
│   │   │   ├── __init__.py
│   │   │   ├── box_ops.py
│   │   │   ├── get_tokenlizer.py
│   │   │   ├── inference.py
│   │   │   ├── logger.py
│   │   │   ├── misc.py
│   │   │   ├── slconfig.py
│   │   │   ├── slio.py
│   │   │   ├── time_counter.py
│   │   │   ├── utils.py
│   │   │   ├── visualizer.py
│   │   │   └── vl_utils.py
│   │   └── version.py
│   ├── lama/
│   │   ├── .gitignore
│   │   ├── LICENSE
│   │   ├── README.md
│   │   ├── bin/
│   │   │   ├── analyze_errors.py
│   │   │   ├── blur_predicts.py
│   │   │   ├── calc_dataset_stats.py
│   │   │   ├── debug/
│   │   │   │   └── analyze_overlapping_masks.sh
│   │   │   ├── evaluate_predicts.py
│   │   │   ├── evaluator_example.py
│   │   │   ├── extract_masks.py
│   │   │   ├── filter_sharded_dataset.py
│   │   │   ├── gen_debug_mask_dataset.py
│   │   │   ├── gen_mask_dataset.py
│   │   │   ├── gen_mask_dataset_hydra.py
│   │   │   ├── gen_outpainting_dataset.py
│   │   │   ├── make_checkpoint.py
│   │   │   ├── mask_example.py
│   │   │   ├── paper_runfiles/
│   │   │   │   ├── blur_tests.sh
│   │   │   │   ├── env.sh
│   │   │   │   ├── find_best_checkpoint.py
│   │   │   │   ├── generate_test_celeba-hq.sh
│   │   │   │   ├── generate_test_ffhq.sh
│   │   │   │   ├── generate_test_paris.sh
│   │   │   │   ├── generate_test_paris_256.sh
│   │   │   │   ├── generate_val_test.sh
│   │   │   │   ├── predict_inner_features.sh
│   │   │   │   └── update_test_data_stats.sh
│   │   │   ├── predict.py
│   │   │   ├── predict_inner_features.py
│   │   │   ├── report_from_tb.py
│   │   │   ├── sample_from_dataset.py
│   │   │   ├── side_by_side.py
│   │   │   ├── split_tar.py
│   │   │   ├── to_jit.py
│   │   │   └── train.py
│   │   ├── colab/
│   │   │   └── LaMa_inpainting.ipynb
│   │   ├── conda_env.yml
│   │   ├── configs/
│   │   │   ├── analyze_mask_errors.yaml
│   │   │   ├── data_gen/
│   │   │   │   ├── random_medium_256.yaml
│   │   │   │   ├── random_medium_512.yaml
│   │   │   │   ├── random_thick_256.yaml
│   │   │   │   ├── random_thick_512.yaml
│   │   │   │   ├── random_thin_256.yaml
│   │   │   │   └── random_thin_512.yaml
│   │   │   ├── debug_mask_gen.yaml
│   │   │   ├── eval1.yaml
│   │   │   ├── eval2.yaml
│   │   │   ├── eval2_cpu.yaml
│   │   │   ├── eval2_gpu.yaml
│   │   │   ├── eval2_jpg.yaml
│   │   │   ├── eval2_segm.yaml
│   │   │   ├── eval2_segm_test.yaml
│   │   │   ├── eval2_test.yaml
│   │   │   ├── places2-categories_157.txt
│   │   │   ├── prediction/
│   │   │   │   └── default.yaml
│   │   │   ├── test_large_30k.lst
│   │   │   └── training/
│   │   │       ├── ablv2_work.yaml
│   │   │       ├── ablv2_work_ffc075.yaml
│   │   │       ├── ablv2_work_md.yaml
│   │   │       ├── ablv2_work_no_fm.yaml
│   │   │       ├── ablv2_work_no_segmpl.yaml
│   │   │       ├── ablv2_work_no_segmpl_csdilirpl.yaml
│   │   │       ├── ablv2_work_no_segmpl_csdilirpl_celeba_csdilirpl1_new.yaml
│   │   │       ├── ablv2_work_no_segmpl_csirpl.yaml
│   │   │       ├── ablv2_work_no_segmpl_csirpl_celeba_csirpl03_new.yaml
│   │   │       ├── ablv2_work_no_segmpl_vgg.yaml
│   │   │       ├── ablv2_work_no_segmpl_vgg_celeba_l2_vgg003_new.yaml
│   │   │       ├── ablv2_work_nodil_segmpl.yaml
│   │   │       ├── ablv2_work_small_holes.yaml
│   │   │       ├── big-lama-celeba.yaml
│   │   │       ├── big-lama-regular-celeba.yaml
│   │   │       ├── big-lama-regular.yaml
│   │   │       ├── big-lama.yaml
│   │   │       ├── data/
│   │   │       │   ├── abl-02-thin-bb.yaml
│   │   │       │   ├── abl-04-256-mh-dist-celeba.yaml
│   │   │       │   ├── abl-04-256-mh-dist-web.yaml
│   │   │       │   └── abl-04-256-mh-dist.yaml
│   │   │       ├── discriminator/
│   │   │       │   └── pix2pixhd_nlayer.yaml
│   │   │       ├── evaluator/
│   │   │       │   └── default_inpainted.yaml
│   │   │       ├── generator/
│   │   │       │   ├── ffc_resnet_075.yaml
│   │   │       │   ├── pix2pixhd_global.yaml
│   │   │       │   ├── pix2pixhd_global_sigmoid.yaml
│   │   │       │   └── pix2pixhd_multidilated_catin_4dil_9b.yaml
│   │   │       ├── hydra/
│   │   │       │   ├── no_time.yaml
│   │   │       │   └── overrides.yaml
│   │   │       ├── lama-fourier-celeba.yaml
│   │   │       ├── lama-fourier.yaml
│   │   │       ├── lama-regular-celeba.yaml
│   │   │       ├── lama-regular.yaml
│   │   │       ├── lama_small_train_masks.yaml
│   │   │       ├── location/
│   │   │       │   ├── celeba_example.yaml
│   │   │       │   ├── docker.yaml
│   │   │       │   └── places_example.yaml
│   │   │       ├── optimizers/
│   │   │       │   └── default_optimizers.yaml
│   │   │       ├── trainer/
│   │   │       │   ├── any_gpu_large_ssim_ddp_final.yaml
│   │   │       │   ├── any_gpu_large_ssim_ddp_final_benchmark.yaml
│   │   │       │   └── any_gpu_large_ssim_ddp_final_celeba.yaml
│   │   │       └── visualizer/
│   │   │           └── directory.yaml
│   │   ├── docker/
│   │   │   ├── 1_generate_masks_from_raw_images.sh
│   │   │   ├── 2_predict.sh
│   │   │   ├── 3_evaluate.sh
│   │   │   ├── Dockerfile
│   │   │   ├── Dockerfile-cuda111
│   │   │   ├── build-cuda111.sh
│   │   │   ├── build.sh
│   │   │   └── entrypoint.sh
│   │   ├── fetch_data/
│   │   │   ├── celebahq_dataset_prepare.sh
│   │   │   ├── celebahq_gen_masks.sh
│   │   │   ├── eval_sampler.py
│   │   │   ├── places_challenge_train_download.sh
│   │   │   ├── places_standard_evaluation_prepare_data.sh
│   │   │   ├── places_standard_test_val_gen_masks.sh
│   │   │   ├── places_standard_test_val_prepare.sh
│   │   │   ├── places_standard_test_val_sample.sh
│   │   │   ├── places_standard_train_prepare.sh
│   │   │   ├── sampler.py
│   │   │   ├── train_shuffled.flist
│   │   │   └── val_shuffled.flist
│   │   ├── models/
│   │   │   └── ade20k/
│   │   │       ├── __init__.py
│   │   │       ├── base.py
│   │   │       ├── color150.mat
│   │   │       ├── mobilenet.py
│   │   │       ├── object150_info.csv
│   │   │       ├── resnet.py
│   │   │       ├── segm_lib/
│   │   │       │   ├── nn/
│   │   │       │   │   ├── __init__.py
│   │   │       │   │   ├── modules/
│   │   │       │   │   │   ├── __init__.py
│   │   │       │   │   │   ├── batchnorm.py
│   │   │       │   │   │   ├── comm.py
│   │   │       │   │   │   ├── replicate.py
│   │   │       │   │   │   ├── tests/
│   │   │       │   │   │   │   ├── test_numeric_batchnorm.py
│   │   │       │   │   │   │   └── test_sync_batchnorm.py
│   │   │       │   │   │   └── unittest.py
│   │   │       │   │   └── parallel/
│   │   │       │   │       ├── __init__.py
│   │   │       │   │       └── data_parallel.py
│   │   │       │   └── utils/
│   │   │       │       ├── __init__.py
│   │   │       │       ├── data/
│   │   │       │       │   ├── __init__.py
│   │   │       │       │   ├── dataloader.py
│   │   │       │       │   ├── dataset.py
│   │   │       │       │   ├── distributed.py
│   │   │       │       │   └── sampler.py
│   │   │       │       └── th.py
│   │   │       └── utils.py
│   │   ├── requirements.txt
│   │   └── saicinpainting/
│   │       ├── __init__.py
│   │       ├── evaluation/
│   │       │   ├── __init__.py
│   │       │   ├── data.py
│   │       │   ├── evaluator.py
│   │       │   ├── losses/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── base_loss.py
│   │       │   │   ├── fid/
│   │       │   │   │   ├── __init__.py
│   │       │   │   │   ├── fid_score.py
│   │       │   │   │   └── inception.py
│   │       │   │   ├── lpips.py
│   │       │   │   └── ssim.py
│   │       │   ├── masks/
│   │       │   │   ├── README.md
│   │       │   │   ├── __init__.py
│   │       │   │   ├── countless/
│   │       │   │   │   ├── .gitignore
│   │       │   │   │   ├── README.md
│   │       │   │   │   ├── __init__.py
│   │       │   │   │   ├── countless2d.py
│   │       │   │   │   ├── countless3d.py
│   │       │   │   │   ├── requirements.txt
│   │       │   │   │   └── test.py
│   │       │   │   └── mask.py
│   │       │   ├── refinement.py
│   │       │   ├── utils.py
│   │       │   └── vis.py
│   │       ├── training/
│   │       │   ├── __init__.py
│   │       │   ├── data/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── aug.py
│   │       │   │   ├── datasets.py
│   │       │   │   └── masks.py
│   │       │   ├── losses/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── adversarial.py
│   │       │   │   ├── constants.py
│   │       │   │   ├── distance_weighting.py
│   │       │   │   ├── feature_matching.py
│   │       │   │   ├── perceptual.py
│   │       │   │   ├── segmentation.py
│   │       │   │   └── style_loss.py
│   │       │   ├── modules/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── base.py
│   │       │   │   ├── depthwise_sep_conv.py
│   │       │   │   ├── fake_fakes.py
│   │       │   │   ├── ffc.py
│   │       │   │   ├── multidilated_conv.py
│   │       │   │   ├── multiscale.py
│   │       │   │   ├── pix2pixhd.py
│   │       │   │   ├── spatial_transform.py
│   │       │   │   └── squeeze_excitation.py
│   │       │   ├── trainers/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── base.py
│   │       │   │   └── default.py
│   │       │   └── visualizers/
│   │       │       ├── __init__.py
│   │       │       ├── base.py
│   │       │       ├── colors.py
│   │       │       ├── directory.py
│   │       │       └── noop.py
│   │       └── utils.py
│   ├── requirements.txt
│   ├── segment_anything/
│   │   ├── __init__.py
│   │   ├── automatic_mask_generator.py
│   │   ├── build_sam.py
│   │   ├── modeling/
│   │   │   ├── __init__.py
│   │   │   ├── common.py
│   │   │   ├── image_encoder.py
│   │   │   ├── mask_decoder.py
│   │   │   ├── prompt_encoder.py
│   │   │   ├── sam.py
│   │   │   └── transformer.py
│   │   ├── predictor.py
│   │   └── utils/
│   │       ├── __init__.py
│   │       ├── amg.py
│   │       ├── onnx.py
│   │       └── transforms.py
│   └── setup.py
├── requirements.txt
├── requirements_llm_extra.txt
├── themes/
│   ├── common.js
│   ├── default.css
│   ├── default.py
│   ├── green.css
│   ├── green.py
│   └── theme.py
└── utils/
    ├── AudioRecorder.py
    ├── AudioTrans.py
    ├── __init__.py
    ├── audio.py
    ├── check_proxy.py
    ├── colorful.py
    ├── conf.py
    ├── dataloads.py
    ├── downloads.py
    ├── ops.py
    ├── plot.py
    ├── text2speech.py
    ├── textsplitter/
    │   ├── __init__.py
    │   ├── ali_text_splitter.py
    │   ├── chinese_text_splitter.py
    │   └── zh_title_enhance.py
    ├── toolbox.py
    ├── torch_utils.py
    └── video.py

SYMBOL INDEX (2527 symbols across 220 files)

FILE: a2f.py
  function get_part_wav (line 31) | def get_part_wav(sound, start_time, end_time, part_wav_path):
  function crop_wav (line 41) | def crop_wav(path, crop_len):
  function process_chunk (line 62) | def process_chunk(model, chunk, detect_language):
  function speech_recognition (line 78) | def speech_recognition(inputs, model,stream_model=False,detect_language=...
  function mic_audio (line 130) | def mic_audio(record_file="record.wav"):
  function tts_send (line 163) | async def tts_send(text,onmiverse=False,send_file='voice_dir/send_a2f.wa...
  function tts_a2f (line 209) | async def tts_a2f(text):
  function push_stream (line 228) | def push_stream(url,player,dir="voice_dir/send_omniverse.wav"):
  function audio_synthesis (line 246) | def audio_synthesis(gpt_replying_buffer,url,player):
  function process_send_stream (line 250) | def process_send_stream(gpt_replying_buffer,url,player):
  function receive_max (line 258) | def receive_max(q,Text):
  function send_stream2 (line 281) | def send_stream2(q):
  function audio_chatbot (line 319) | def audio_chatbot(text):

FILE: app.py
  function toggle_operation (line 59) | def toggle_operation(flag):
  function sadtalker_demo (line 80) | async def sadtalker_demo(checkpoint_path,config_path,source_image,
  function train_visualGLM (line 104) | def train_visualGLM(name,model_size,mode,train_iters,resume_data,
  function start_finetuning_process (line 128) | def start_finetuning_process(gpt_option,model_args,method_type):
  function load_speech_model (line 186) | async def load_speech_model(asr_method,tts_method):
  function save_text2img_data (line 209) | def save_text2img_data(prompt,label,img_name,zh_select):
  function load_auto_backend_models (line 222) | async def load_auto_backend_models(lama, sam, det,tag2text,ram, trans_zh...
  function load_auto_backend_model (line 234) | def load_auto_backend_model(lama,sam,det,tag2text,ram,trans_zh,visual_gl...
  function Auto_run (line 304) | def Auto_run(
  function visual_chat (line 517) | def visual_chat(prompt_input, temperature, top_p, image_prompt, result_t...
  function clear_fn_image (line 534) | def clear_fn_image(value):
  function t2s (line 725) | def t2s(text,method):
  function s2t (line 734) | def s2t(speech_file,stream_mode=False):
  function fn_area_visibility (line 830) | def fn_area_visibility(a):
  function on_md_dropdown_changed (line 859) | def on_md_dropdown_changed(k):
  function on_dropdown_changed (line 900) | def on_dropdown_changed(k):
  function on_md_dropdown_changed (line 909) | def on_md_dropdown_changed(k):
  function route (line 913) | def route(request: gr.Request, k, *args, **kwargs):
  function auto_opentab_delay (line 937) | def auto_opentab_delay(port=7586):

FILE: audio2face_pb2_grpc.py
  class Audio2FaceStub (line 8) | class Audio2FaceStub(object):
    method __init__ (line 11) | def __init__(self, channel):
  class Audio2FaceServicer (line 29) | class Audio2FaceServicer(object):
    method PushAudio (line 32) | def PushAudio(self, request, context):
    method PushAudioStream (line 38) | def PushAudioStream(self, request_iterator, context):
  function add_Audio2FaceServicer_to_server (line 45) | def add_Audio2FaceServicer_to_server(servicer, server):
  class Audio2Face (line 63) | class Audio2Face(object):
    method PushAudio (line 67) | def PushAudio(
    method PushAudioStream (line 96) | def PushAudioStream(

FILE: audio2face_streaming_utils.py
  function push_audio_track (line 22) | def push_audio_track(url, audio_data, samplerate, instance_name):
  function push_audio_track_stream (line 50) | def push_audio_track_stream(url, audio_data, samplerate, instance_name):
  function push_stream (line 95) | def push_stream(url, audio_data, samplerate, instance_name):

FILE: audio_segment.py
  function crop_audio (line 8) | def crop_audio(file_path, start_time, end_time):
  function split_audio_file (line 19) | def split_audio_file(file_path, output_path, segment_time=3000):
  function audio_processing (line 37) | def audio_processing(file_path, output_path, label):

FILE: auto_label_demo.py
  function save_text2img_data (line 45) | def save_text2img_data(output_dir, prompt,label,img_name):
  function load_auto_backend_models (line 55) | def load_auto_backend_models(opt):
  function Auto_run (line 74) | def Auto_run(weights=ROOT / '',  # model.pt path(s)
  function run_do (line 262) | def run_do(shared_args,process_name=0):
  function parse_opt (line 266) | def parse_opt():
  function main (line 314) | def main(opt):

FILE: crazy_functions/Langchain知识库.py
  function 知识库问答 (line 7) | def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_promp...
  function 读取知识库作答 (line 77) | def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro...

FILE: crazy_functions/Latex全文润色.py
  class PaperFileGroup (line 5) | class PaperFileGroup():
    method __init__ (line 6) | def __init__(self):
    method run_file_split (line 19) | def run_file_split(self, max_token_limit=1900):
    method merge_result (line 37) | def merge_result(self):
    method write_result (line 42) | def write_result(self):
    method zip_result (line 50) | def zip_result(self):
  function 多文件润色 (line 57) | def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chat...
  function Latex英文润色 (line 136) | def Latex英文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p...
  function Latex中文润色 (line 174) | def Latex中文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p...
  function Latex英文纠错 (line 210) | def Latex英文纠错(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p...

FILE: crazy_functions/Latex全文翻译.py
  class PaperFileGroup (line 5) | class PaperFileGroup():
    method __init__ (line 6) | def __init__(self):
    method run_file_split (line 19) | def run_file_split(self, max_token_limit=1900):
  function 多文件翻译 (line 38) | def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chat...
  function Latex英译中 (line 108) | def Latex英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...
  function Latex中译英 (line 145) | def Latex中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...

FILE: crazy_functions/Latex输出PDF结果.py
  function switch_prompt (line 10) | def switch_prompt(pfg, mode, more_requirement):
  function desend_to_extracted_folder_if_exist (line 38) | def desend_to_extracted_folder_if_exist(project_folder):
  function move_project (line 53) | def move_project(project_folder, arxiv_id=None):
  function arxiv_download (line 82) | def arxiv_download(chatbot, history, txt):
  function Latex英文纠错加PDF对比 (line 145) | def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, history, sy...
  function Latex翻译中文并重新编译PDF (line 221) | def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, ...

FILE: crazy_functions/chatglm微调工具.py
  function fetch_items (line 5) | def fetch_items(list_of_items, batch_size):
  function string_to_options (line 9) | def string_to_options(arguments):
  function 微调数据集生成 (line 35) | def 微调数据集生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro...
  function 启动微调 (line 83) | def 启动微调(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt...

FILE: crazy_functions/crazy_functions_test.py
  function validate_path (line 9) | def validate_path():
  function silence_stdout (line 43) | def silence_stdout(func):
  class CLI_Printer (line 56) | class CLI_Printer():
    method __init__ (line 57) | def __init__(self) -> None:
    method print (line 60) | def print(self, buf):
  function test_解析一个Python项目 (line 78) | def test_解析一个Python项目():
  function test_解析一个Cpp项目 (line 84) | def test_解析一个Cpp项目():
  function test_Latex英文润色 (line 90) | def test_Latex英文润色():
  function test_Markdown中译英 (line 96) | def test_Markdown中译英():
  function test_批量翻译PDF文档 (line 102) | def test_批量翻译PDF文档():
  function test_谷歌检索小助手 (line 108) | def test_谷歌检索小助手():
  function test_总结word文档 (line 114) | def test_总结word文档():
  function test_下载arxiv论文并翻译摘要 (line 120) | def test_下载arxiv论文并翻译摘要():
  function test_联网回答问题 (line 126) | def test_联网回答问题():
  function test_解析ipynb文件 (line 139) | def test_解析ipynb文件():
  function test_数学动画生成manim (line 146) | def test_数学动画生成manim():
  function test_Markdown多语言 (line 154) | def test_Markdown多语言():
  function test_Langchain知识库 (line 163) | def test_Langchain知识库():
  function test_Langchain知识库读取 (line 176) | def test_Langchain知识库读取():
  function test_Latex (line 182) | def test_Latex():
  function test_chatglm_finetune (line 217) | def test_chatglm_finetune():

FILE: crazy_functions/crazy_utils.py
  function input_clipping (line 4) | def input_clipping(inputs, history, max_token_limit):
  function request_gpt_model_in_new_thread_with_ui_alive (line 38) | def request_gpt_model_in_new_thread_with_ui_alive(
  function can_multi_process (line 133) | def can_multi_process(llm):
  function request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency (line 139) | def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_effici...
  function breakdown_txt_to_satisfy_token_limit (line 306) | def breakdown_txt_to_satisfy_token_limit(txt, get_token_fn, limit):
  function force_breakdown (line 336) | def force_breakdown(txt, limit, get_token_fn):
  function breakdown_txt_to_satisfy_token_limit_for_pdf (line 345) | def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit):
  function read_and_clean_pdf_text (line 396) | def read_and_clean_pdf_text(fp):
  function get_files_from_everything (line 574) | def get_files_from_everything(txt, type): # type='.md'
  function Singleton (line 619) | def Singleton(cls):
  class knowledge_archive_interface (line 631) | class knowledge_archive_interface():
    method __init__ (line 632) | def __init__(self) -> None:
    method get_chinese_text2vec (line 639) | def get_chinese_text2vec(self):
    method feed_archive (line 651) | def feed_archive(self, file_manifest, id="default"):
    method get_current_archive_id (line 667) | def get_current_archive_id(self):
    method get_loaded_file (line 670) | def get_loaded_file(self):
    method answer_with_archive_by_id (line 673) | def answer_with_archive_by_id(self, txt, id):
  function try_install_deps (line 702) | def try_install_deps(deps):
  class construct_html (line 715) | class construct_html():
    method __init__ (line 716) | def __init__(self) -> None:
    method add_row (line 744) | def add_row(self, a, b):
    method save_file (line 757) | def save_file(self, file_name):

FILE: crazy_functions/latex_fns/latex_actions.py
  function split_subprocess (line 15) | def split_subprocess(txt, project_folder, return_dict, opts):
  class LatexPaperSplit (line 80) | class LatexPaperSplit():
    method __init__ (line 86) | def __init__(self) -> None:
    method merge_result (line 95) | def merge_result(self, arr, mode, msg, buggy_lines=[], buggy_line_surg...
    method split (line 135) | def split(self, txt, project_folder, opts):
  class LatexPaperFileGroup (line 156) | class LatexPaperFileGroup():
    method __init__ (line 160) | def __init__(self):
    method run_file_split (line 173) | def run_file_split(self, max_token_limit=1900):
    method merge_result (line 191) | def merge_result(self):
    method write_result (line 196) | def write_result(self):
  function Latex精细分解与转化 (line 205) | def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwarg...
  function remove_buggy_lines (line 299) | def remove_buggy_lines(file_path, log_path, tex_name, tex_name_pure, n_f...
  function 编译Latex (line 326) | def 编译Latex(chatbot, history, main_file_original, main_file_modified, wo...
  function write_html (line 422) | def write_html(sp_file_contents, sp_file_result, chatbot, project_folder):

FILE: crazy_functions/latex_fns/latex_toolbox.py
  class LinkedListNode (line 9) | class LinkedListNode():
    method __init__ (line 13) | def __init__(self, string, preserve=True) -> None:
  function convert_to_linklist (line 21) | def convert_to_linklist(text, mask):
  function post_process (line 34) | def post_process(root):
  function set_forbidden_text (line 127) | def set_forbidden_text(text, mask, pattern, flags=0):
  function reverse_forbidden_text (line 140) | def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=...
  function set_forbidden_text_careful_brace (line 158) | def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
  function reverse_forbidden_text_careful_brace (line 178) | def reverse_forbidden_text_careful_brace(text, mask, pattern, flags=0, f...
  function set_forbidden_text_begin_end (line 201) | def set_forbidden_text_begin_end(text, mask, pattern, flags=0, limit_n_l...
  function find_main_tex_file (line 230) | def find_main_tex_file(file_manifest, mode):
  function rm_comments (line 268) | def rm_comments(main_file):
  function find_tex_file_ignore_case (line 281) | def find_tex_file_ignore_case(fp):
  function merge_tex_files_ (line 293) | def merge_tex_files_(project_foler, main_file, mode):
  function merge_tex_files (line 310) | def merge_tex_files(project_foler, main_file, mode):
  function mod_inbraket (line 346) | def mod_inbraket(match):
  function fix_content (line 359) | def fix_content(final_tex, node_string):
  function compile_latex_with_timeout (line 407) | def compile_latex_with_timeout(command, cwd, timeout=60):
  function merge_pdfs (line 421) | def merge_pdfs(pdf1_path, pdf2_path, output_path):

FILE: crazy_functions/live_audio/aliyunASR.py
  class AliyunASR (line 4) | class AliyunASR():
    method test_on_sentence_begin (line 6) | def test_on_sentence_begin(self, message, *args):
    method test_on_sentence_end (line 10) | def test_on_sentence_end(self, message, *args):
    method test_on_start (line 17) | def test_on_start(self, message, *args):
    method test_on_error (line 21) | def test_on_error(self, message, *args):
    method test_on_close (line 25) | def test_on_close(self, *args):
    method test_on_result_chg (line 29) | def test_on_result_chg(self, message, *args):
    method test_on_completed (line 35) | def test_on_completed(self, message, *args):
    method audio_convertion_thread (line 40) | def audio_convertion_thread(self, uuid):
    method get_token (line 97) | def get_token(self):

FILE: crazy_functions/live_audio/audio_io.py
  function Singleton (line 4) | def Singleton(cls):
  class RealtimeAudioDistribution (line 16) | class RealtimeAudioDistribution():
    method __init__ (line 17) | def __init__(self) -> None:
    method clean_up (line 22) | def clean_up(self):
    method feed (line 25) | def feed(self, uuid, audio):
    method read (line 35) | def read(self, uuid):
  function change_sample_rate (line 43) | def change_sample_rate(audio, old_sr, new_sr):

FILE: crazy_functions/test_project/cpp/cppipc/buffer.cpp
  type ipc (line 6) | namespace ipc {
    class buffer::buffer_ (line 16) | class buffer::buffer_ : public pimpl<buffer_> {
      method buffer_ (line 23) | buffer_(void* p, std::size_t s, buffer::destructor_t d, void* a)
    function buffer (line 66) | buffer& buffer::operator=(buffer rhs) {

FILE: crazy_functions/test_project/cpp/cppipc/ipc.cpp
  type msg_t (line 37) | struct msg_t
    method msg_t (line 51) | msg_t() = default;
    method msg_t (line 52) | msg_t(msg_id_t cc_id, msg_id_t id, std::int32_t remain, void const * d...
  type msg_t<0, AlignSize> (line 40) | struct msg_t<0, AlignSize> {
  type msg_t (line 48) | struct msg_t : msg_t<0, AlignSize> {
    method msg_t (line 51) | msg_t() = default;
    method msg_t (line 52) | msg_t(msg_id_t cc_id, msg_id_t id, std::int32_t remain, void const * d...
  function make_cache (line 66) | ipc::buff_t make_cache(T& data, std::size_t size) {
  type cache_t (line 72) | struct cache_t {
    method cache_t (line 76) | cache_t(std::size_t f, ipc::buff_t && b)
    method append (line 80) | void append(void const * data, std::size_t size) {
  function cc_acc (line 88) | auto cc_acc() {
  function IPC_CONSTEXPR_ (line 93) | IPC_CONSTEXPR_ std::size_t align_chunk_size(std::size_t size) noexcept {
  function IPC_CONSTEXPR_ (line 97) | IPC_CONSTEXPR_ std::size_t calc_chunk_size(std::size_t size) noexcept {
  type chunk_t (line 102) | struct chunk_t {
  type chunk_info_t (line 113) | struct chunk_info_t {
  function chunk_t (line 125) | chunk_t *at(std::size_t chunk_size, ipc::storage_id_t id) noexcept {
  class chunk_handle_t (line 132) | class chunk_handle_t {
    method chunk_info_t (line 136) | chunk_info_t *get_info(std::size_t chunk_size) {
  function chunk_info_t (line 155) | chunk_info_t *chunk_storage_info(std::size_t chunk_size) {
  function acquire_storage (line 171) | std::pair<ipc::storage_id_t, void*> acquire_storage(std::size_t size, ip...
  function release_storage (line 199) | void release_storage(ipc::storage_id_t id, std::size_t size) {
  function sub_rc (line 213) | bool sub_rc(ipc::wr<Rp, Rc, ipc::trans::unicast>,
  function sub_rc (line 219) | bool sub_rc(ipc::wr<Rp, Rc, ipc::trans::broadcast>,
  function recycle_storage (line 232) | void recycle_storage(ipc::storage_id_t id, std::size_t size, ipc::circ::...
  function clear_message (line 253) | bool clear_message(void* p) {
  type conn_info_head (line 268) | struct conn_info_head {
    method conn_info_head (line 275) | conn_info_head(char const * name)
    method quit_waiting (line 284) | void quit_waiting() {
    method acc (line 290) | auto acc() {
  function wait_for (line 301) | bool wait_for(W& waiter, F&& pred, std::uint64_t tm) {
  type queue_generator (line 318) | struct queue_generator {
    type conn_info_t (line 322) | struct conn_info_t : conn_info_head {
      method conn_info_t (line 325) | conn_info_t(char const * name)
      method disconnect_receiver (line 332) | void disconnect_receiver() {
  type detail_impl (line 343) | struct detail_impl {
    method conn_info_t (line 350) | constexpr static conn_info_t* info_of(ipc::handle_t h) noexcept {
    method queue_t (line 354) | constexpr static queue_t* queue_of(ipc::handle_t h) noexcept {
    method disconnect (line 360) | static void disconnect(ipc::handle_t h) {
    method reconnect (line 370) | static bool reconnect(ipc::handle_t * ph, bool start_to_recv) {
    method connect (line 392) | static bool connect(ipc::handle_t * ph, char const * name, bool start_...
    method destroy (line 400) | static void destroy(ipc::handle_t h) {
    method recv_count (line 405) | static std::size_t recv_count(ipc::handle_t h) noexcept {
    method wait_for_recv (line 413) | static bool wait_for_recv(ipc::handle_t h, std::size_t r_count, std::u...
    method send (line 424) | static bool send(F&& gen_push, ipc::handle_t h, void const * data, std...
    method send (line 486) | static bool send(ipc::handle_t h, void const * data, std::size_t size,...
    method try_send (line 507) | static bool try_send(ipc::handle_t h, void const * data, std::size_t s...
    method recv (line 523) | static ipc::buff_t recv(ipc::handle_t h, std::uint64_t tm) {
    method try_recv (line 620) | static ipc::buff_t try_recv(ipc::handle_t h) {
  type ipc (line 631) | namespace ipc {
    function buff_t (line 681) | buff_t chan_impl<Flag>::recv(ipc::handle_t h, std::uint64_t tm) {
    function buff_t (line 691) | buff_t chan_impl<Flag>::try_recv(ipc::handle_t h) {
    type chan_impl<ipc::wr<relat::single, relat::single, trans::unicast  >> (line 695) | struct chan_impl<ipc::wr<relat::single, relat::single, trans::unicast  >>
    type chan_impl<ipc::wr<relat::single, relat::multi , trans::broadcast>> (line 698) | struct chan_impl<ipc::wr<relat::single, relat::multi , trans::broadcast>>
    type chan_impl<ipc::wr<relat::multi , relat::multi , trans::broadcast>> (line 699) | struct chan_impl<ipc::wr<relat::multi , relat::multi , trans::broadcast>>

FILE: crazy_functions/test_project/cpp/cppipc/policy.h
  function namespace (line 10) | namespace ipc {

FILE: crazy_functions/test_project/cpp/cppipc/pool_alloc.cpp
  type ipc (line 5) | namespace ipc {
    type mem (line 6) | namespace mem {

FILE: crazy_functions/test_project/cpp/cppipc/prod_cons.h
  function namespace (line 16) | namespace ipc {
  type elem_t (line 112) | struct elem_t {
  type rc_t (line 200) | enum : rc_t {
  type elem_t (line 206) | struct elem_t {
  function rc_t (line 212) | alignas(cache_line_size) rc_t epoch_ { 0 };             // only one writer
  type rc_t (line 298) | enum : rc_t {
  type elem_t (line 307) | struct elem_t {
  function std (line 314) | alignas(cache_line_size) std::atomic<rc_t> epoch_ { 0 };

FILE: crazy_functions/test_project/cpp/cppipc/queue.h
  function namespace (line 22) | namespace ipc {
  function pop (line 206) | bool pop(T& item) {

FILE: crazy_functions/test_project/cpp/cppipc/shm.cpp
  type ipc (line 10) | namespace ipc {
    type shm (line 11) | namespace shm {
      class handle::handle_ (line 13) | class handle::handle_ : public pimpl<handle_> {
      function handle (line 45) | handle& handle::operator=(handle rhs) {
      function id_t (line 93) | id_t handle::detach() {

FILE: crazy_functions/test_project/cpp/cppipc/waiter.h
  function IPC_UNUSED_ (line 56) | IPC_UNUSED_ std::lock_guard<ipc::sync::mutex> guard {lock_};
  function notify (line 66) | bool notify() noexcept {

FILE: crazy_functions/test_project/cpp/libJPG/jpgd.cpp
  type jpgd (line 34) | namespace jpgd {
    function jpgd_free (line 37) | static inline void jpgd_free(void *p) { FMemory::Free(p); }
    type ERGBFormatJPG (line 42) | enum ERGBFormatJPG
    type JPEG_MARKER (line 55) | enum JPEG_MARKER
    type JPEG_SUBSAMPLING (line 64) | enum JPEG_SUBSAMPLING { JPGD_GRAYSCALE = 0, JPGD_YH1V1, JPGD_YH2V1, JP...
    type Row (line 92) | struct Row
      method idct (line 94) | static void idct(int* pTemp, const jpgd_block_t* pSrc)
    type Row<0> (line 137) | struct Row<0>
      method idct (line 139) | static void idct(int* pTemp, const jpgd_block_t* pSrc)
    type Row<1> (line 148) | struct Row<1>
      method idct (line 150) | static void idct(int* pTemp, const jpgd_block_t* pSrc)
    type Col (line 167) | struct Col
      method idct (line 169) | static void idct(uint8* pDst_ptr, const int* pTemp)
    type Col<1> (line 228) | struct Col<1>
      method idct (line 230) | static void idct(uint8* pDst_ptr, const int* pTemp)
    function idct (line 259) | void idct(const jpgd_block_t* pSrc_ptr, uint8* pDst_ptr, int block_max...
    function idct_4x4 (line 328) | void idct_4x4(const jpgd_block_t* pSrc_ptr, uint8* pDst_ptr)
    function uint (line 351) | inline uint jpeg_decoder::get_char()
    function uint (line 378) | inline uint jpeg_decoder::get_char(bool *pPadding_flag)
    function uint8 (line 411) | inline uint8 jpeg_decoder::get_octet()
    function uint (line 442) | inline uint jpeg_decoder::get_bits(int num_bits)
    function uint (line 470) | inline uint jpeg_decoder::get_bits_no_markers(int num_bits)
    function uint8 (line 586) | inline uint8 jpeg_decoder::clamp(int i)
    type DCT_Upsample (line 594) | namespace DCT_Upsample
      type Matrix44 (line 596) | struct Matrix44
        method rows (line 603) | inline int rows() const { return NUM_ROWS; }
        method cols (line 604) | inline int cols() const { return NUM_COLS; }
        method Element_Type (line 606) | inline const Element_Type & at(int r, int c) const { return v[r][c...
        method Element_Type (line 607) | inline       Element_Type & at(int r, int c)       { return v[r][c...
        method Matrix44 (line 609) | inline Matrix44() { }
        method Matrix44 (line 611) | inline Matrix44& operator += (const Matrix44& a)
        method Matrix44 (line 623) | inline Matrix44& operator -= (const Matrix44& a)
        method Matrix44 (line 635) | inline Matrix44 operator + (const Matrix44& a, const Matrix44& b)
        method Matrix44 (line 648) | inline Matrix44 operator - (const Matrix44& a, const Matrix44& b)
        method add_and_store (line 661) | static inline void add_and_store(jpgd_block_t* pDst, const Matrix4...
        method sub_and_store (line 672) | static inline void sub_and_store(jpgd_block_t* pDst, const Matrix4...
      type P_Q (line 696) | struct P_Q
        method calc (line 698) | static void calc(Matrix44& P, Matrix44& Q, const jpgd_block_t* pSrc)
      type R_S (line 775) | struct R_S
        method calc (line 777) | static void calc(Matrix44& R, Matrix44& S, const jpgd_block_t* pSrc)
    function dequantize_ac (line 1775) | static inline int dequantize_ac(int c, int q) {	c *= q;	return c; }
    function jpgd_block_t (line 2683) | inline jpgd_block_t *jpeg_decoder::coeff_buf_getp(coeff_buf *cb, int b...

FILE: crazy_functions/test_project/cpp/libJPG/jpgd.h
  function namespace (line 10) | namespace jpgd

FILE: crazy_functions/test_project/cpp/libJPG/jpge.cpp
  type jpge (line 22) | namespace jpge {
    function jpge_free (line 25) | static inline void jpge_free(void *p) { FMemory::Free(p);; }
    function clear_obj (line 60) | inline void clear_obj(T &obj) { memset(&obj, 0, sizeof(obj)); }
    function uint8 (line 63) | static inline uint8 clamp(int i) { if (static_cast<uint>(i) > 255U) { ...
    function RGB_to_YCC (line 65) | static void RGB_to_YCC(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function RGB_to_Y (line 76) | static void RGB_to_Y(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function RGBA_to_YCC (line 82) | static void RGBA_to_YCC(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function RGBA_to_Y (line 93) | static void RGBA_to_Y(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function Y_to_YCC (line 99) | static void Y_to_YCC(uint8* pDst, const uint8* pSrc, int num_pixels)
    function DCT2D (line 125) | static void DCT2D(int32 *p)
    type sym_freq (line 144) | struct sym_freq { uint m_key, m_sym_index; }
    function sym_freq (line 147) | static inline sym_freq* radix_sort_syms(uint num_syms, sym_freq* pSyms...
    function calculate_minimum_redundancy (line 167) | static void calculate_minimum_redundancy(sym_freq *A, int n)
    function huffman_enforce_max_code_size (line 189) | static void huffman_enforce_max_code_size(int *pNum_codes, int code_li...
    class cfile_stream (line 904) | class cfile_stream : public output_stream
      method cfile_stream (line 913) | cfile_stream() : m_pFile(NULL), m_bStatus(false) { }
      method open (line 920) | bool open(const char *pFilename)
      method close (line 935) | bool close()
      method put_buf (line 948) | virtual bool put_buf(const void* pBuf, int64_t len)
      method uint (line 954) | uint get_size() const
    function compress_image_to_jpeg_file (line 961) | bool compress_image_to_jpeg_file(const char *pFilename, int64_t width,...
    class memory_stream (line 989) | class memory_stream : public output_stream
      method memory_stream (line 998) | memory_stream(void *pBuf, uint64_t buf_size) : m_pBuf(static_cast<ui...
      method put_buf (line 1002) | virtual bool put_buf(const void* pBuf, int64_t len)
      method get_size (line 1012) | uint64_t get_size() const
    function compress_image_to_jpeg_file_in_memory (line 1018) | bool compress_image_to_jpeg_file_in_memory(void *pDstBuf, int64_t &buf...

FILE: crazy_functions/test_project/cpp/libJPG/jpge.h
  function namespace (line 10) | namespace jpge
  function class (line 62) | class output_stream
  function class (line 71) | class jpeg_encoder

FILE: crazy_functions/test_project/cpp/longcode/jpgd.cpp
  type jpgd (line 34) | namespace jpgd {
    function jpgd_free (line 37) | static inline void jpgd_free(void *p) { FMemory::Free(p); }
    type ERGBFormatJPG (line 42) | enum ERGBFormatJPG
    type JPEG_MARKER (line 55) | enum JPEG_MARKER
    type JPEG_SUBSAMPLING (line 64) | enum JPEG_SUBSAMPLING { JPGD_GRAYSCALE = 0, JPGD_YH1V1, JPGD_YH2V1, JP...
    type Row (line 92) | struct Row
      method idct (line 94) | static void idct(int* pTemp, const jpgd_block_t* pSrc)
    type Row<0> (line 137) | struct Row<0>
      method idct (line 139) | static void idct(int* pTemp, const jpgd_block_t* pSrc)
    type Row<1> (line 148) | struct Row<1>
      method idct (line 150) | static void idct(int* pTemp, const jpgd_block_t* pSrc)
    type Col (line 167) | struct Col
      method idct (line 169) | static void idct(uint8* pDst_ptr, const int* pTemp)
    type Col<1> (line 228) | struct Col<1>
      method idct (line 230) | static void idct(uint8* pDst_ptr, const int* pTemp)
    function idct (line 259) | void idct(const jpgd_block_t* pSrc_ptr, uint8* pDst_ptr, int block_max...
    function idct_4x4 (line 328) | void idct_4x4(const jpgd_block_t* pSrc_ptr, uint8* pDst_ptr)
    function uint (line 351) | inline uint jpeg_decoder::get_char()
    function uint (line 378) | inline uint jpeg_decoder::get_char(bool *pPadding_flag)
    function uint8 (line 411) | inline uint8 jpeg_decoder::get_octet()
    function uint (line 442) | inline uint jpeg_decoder::get_bits(int num_bits)
    function uint (line 470) | inline uint jpeg_decoder::get_bits_no_markers(int num_bits)
    function uint8 (line 586) | inline uint8 jpeg_decoder::clamp(int i)
    type DCT_Upsample (line 594) | namespace DCT_Upsample
      type Matrix44 (line 596) | struct Matrix44
        method rows (line 603) | inline int rows() const { return NUM_ROWS; }
        method cols (line 604) | inline int cols() const { return NUM_COLS; }
        method Element_Type (line 606) | inline const Element_Type & at(int r, int c) const { return v[r][c...
        method Element_Type (line 607) | inline       Element_Type & at(int r, int c)       { return v[r][c...
        method Matrix44 (line 609) | inline Matrix44() { }
        method Matrix44 (line 611) | inline Matrix44& operator += (const Matrix44& a)
        method Matrix44 (line 623) | inline Matrix44& operator -= (const Matrix44& a)
        method Matrix44 (line 635) | inline Matrix44 operator + (const Matrix44& a, const Matrix44& b)
        method Matrix44 (line 648) | inline Matrix44 operator - (const Matrix44& a, const Matrix44& b)
        method add_and_store (line 661) | static inline void add_and_store(jpgd_block_t* pDst, const Matrix4...
        method sub_and_store (line 672) | static inline void sub_and_store(jpgd_block_t* pDst, const Matrix4...
      type P_Q (line 696) | struct P_Q
        method calc (line 698) | static void calc(Matrix44& P, Matrix44& Q, const jpgd_block_t* pSrc)
      type R_S (line 775) | struct R_S
        method calc (line 777) | static void calc(Matrix44& R, Matrix44& S, const jpgd_block_t* pSrc)
    function dequantize_ac (line 1775) | static inline int dequantize_ac(int c, int q) {	c *= q;	return c; }
    function jpgd_block_t (line 2683) | inline jpgd_block_t *jpeg_decoder::coeff_buf_getp(coeff_buf *cb, int b...

FILE: crazy_functions/test_project/cpp/longcode/jpge.cpp
  type jpge (line 22) | namespace jpge {
    function jpge_free (line 25) | static inline void jpge_free(void *p) { FMemory::Free(p);; }
    function clear_obj (line 60) | inline void clear_obj(T &obj) { memset(&obj, 0, sizeof(obj)); }
    function uint8 (line 63) | static inline uint8 clamp(int i) { if (static_cast<uint>(i) > 255U) { ...
    function RGB_to_YCC (line 65) | static void RGB_to_YCC(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function RGB_to_Y (line 76) | static void RGB_to_Y(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function RGBA_to_YCC (line 82) | static void RGBA_to_YCC(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function RGBA_to_Y (line 93) | static void RGBA_to_Y(uint8* pDst, const uint8 *pSrc, int num_pixels)
    function Y_to_YCC (line 99) | static void Y_to_YCC(uint8* pDst, const uint8* pSrc, int num_pixels)
    function DCT2D (line 125) | static void DCT2D(int32 *p)
    type sym_freq (line 144) | struct sym_freq { uint m_key, m_sym_index; }
    function sym_freq (line 147) | static inline sym_freq* radix_sort_syms(uint num_syms, sym_freq* pSyms...
    function calculate_minimum_redundancy (line 167) | static void calculate_minimum_redundancy(sym_freq *A, int n)
    function huffman_enforce_max_code_size (line 189) | static void huffman_enforce_max_code_size(int *pNum_codes, int code_li...
    class cfile_stream (line 904) | class cfile_stream : public output_stream
      method cfile_stream (line 913) | cfile_stream() : m_pFile(NULL), m_bStatus(false) { }
      method open (line 920) | bool open(const char *pFilename)
      method close (line 935) | bool close()
      method put_buf (line 948) | virtual bool put_buf(const void* pBuf, int64_t len)
      method uint (line 954) | uint get_size() const
    function compress_image_to_jpeg_file (line 961) | bool compress_image_to_jpeg_file(const char *pFilename, int64_t width,...
    class memory_stream (line 989) | class memory_stream : public output_stream
      method memory_stream (line 998) | memory_stream(void *pBuf, uint64_t buf_size) : m_pBuf(static_cast<ui...
      method put_buf (line 1002) | virtual bool put_buf(const void* pBuf, int64_t len)
      method get_size (line 1012) | uint64_t get_size() const
    function compress_image_to_jpeg_file_in_memory (line 1018) | bool compress_image_to_jpeg_file_in_memory(void *pDstBuf, int64_t &buf...

FILE: crazy_functions/test_project/cpp/longcode/prod_cons.h
  function namespace (line 16) | namespace ipc {
  type elem_t (line 112) | struct elem_t {
  type rc_t (line 200) | enum : rc_t {
  type elem_t (line 206) | struct elem_t {
  function rc_t (line 212) | alignas(cache_line_size) rc_t epoch_ { 0 };             // only one writer
  type rc_t (line 298) | enum : rc_t {
  type elem_t (line 307) | struct elem_t {
  function std (line 314) | alignas(cache_line_size) std::atomic<rc_t> epoch_ { 0 };

FILE: crazy_functions/test_project/python/dqn/dqn.py
  class DQN (line 16) | class DQN(OffPolicyAlgorithm):
    method __init__ (line 58) | def __init__(
    method _setup_model (line 123) | def _setup_model(self) -> None:
    method _create_aliases (line 130) | def _create_aliases(self) -> None:
    method _on_step (line 134) | def _on_step(self) -> None:
    method train (line 145) | def train(self, gradient_steps: int, batch_size: int = 100) -> None:
    method predict (line 187) | def predict(
    method learn (line 214) | def learn(
    method _excluded_save_params (line 239) | def _excluded_save_params(self) -> List[str]:
    method _get_torch_save_params (line 242) | def _get_torch_save_params(self) -> Tuple[List[str], List[str]]:

FILE: crazy_functions/test_project/python/dqn/policies.py
  class QNetwork (line 12) | class QNetwork(BasePolicy):
    method __init__ (line 24) | def __init__(
    method forward (line 53) | def forward(self, obs: th.Tensor) -> th.Tensor:
    method _predict (line 62) | def _predict(self, observation: th.Tensor, deterministic: bool = True)...
    method _get_constructor_parameters (line 68) | def _get_constructor_parameters(self) -> Dict[str, Any]:
  class DQNPolicy (line 82) | class DQNPolicy(BasePolicy):
    method __init__ (line 102) | def __init__(
    method _build (line 145) | def _build(self, lr_schedule: Schedule) -> None:
    method make_q_net (line 160) | def make_q_net(self) -> QNetwork:
    method forward (line 165) | def forward(self, obs: th.Tensor, deterministic: bool = True) -> th.Te...
    method _predict (line 168) | def _predict(self, obs: th.Tensor, deterministic: bool = True) -> th.T...
    method _get_constructor_parameters (line 171) | def _get_constructor_parameters(self) -> Dict[str, Any]:
  class CnnPolicy (line 191) | class CnnPolicy(DQNPolicy):
    method __init__ (line 209) | def __init__(

FILE: crazy_functions/下载arxiv论文翻译摘要.py
  function download_arxiv_ (line 5) | def download_arxiv_(url_pdf):
  function get_name (line 67) | def get_name(_url_):
  function 下载arxiv论文并翻译摘要 (line 135) | def 下载arxiv论文并翻译摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys...

FILE: crazy_functions/交互功能函数模板.py
  function 交互功能模板函数 (line 6) | def 交互功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...
  function get_image_page_by_keyword (line 52) | def get_image_page_by_keyword(keyword):

FILE: crazy_functions/代码重写为全英文_多线程.py
  function extract_code_block_carefully (line 7) | def extract_code_block_carefully(txt):
  function break_txt_into_half_at_some_linebreak (line 17) | def break_txt_into_half_at_some_linebreak(txt):
  function 全项目切换英文 (line 26) | def 全项目切换英文(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_prompt...

FILE: crazy_functions/图片生成.py
  function gen_image (line 6) | def gen_image(llm_kwargs, prompt, resolution="256x256"):
  function 图片生成 (line 47) | def 图片生成(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro...

FILE: crazy_functions/对话历史存档.py
  function write_chat_to_file (line 5) | def write_chat_to_file(chatbot, history=None, file_name=None):
  function gen_file_preview (line 35) | def gen_file_preview(file_name):
  function read_file_to_chat (line 50) | def read_file_to_chat(chatbot, history, file_name):
  function 对话历史存档 (line 71) | def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom...
  function hide_cwd (line 86) | def hide_cwd(str):
  function 载入对话历史存档 (line 93) | def 载入对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...
  function 删除所有本地对话历史记录 (line 123) | def 删除所有本地对话历史记录(txt, llm_kwargs, plugin_kwargs, chatbot, history, syste...

FILE: crazy_functions/总结word文档.py
  function 解析docx (line 7) | def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, cha...
  function 总结word文档 (line 84) | def 总结word文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...

FILE: crazy_functions/总结音视频.py
  function split_audio_file (line 4) | def split_audio_file(filename, split_duration=1000):
  function AnalyAudio (line 40) | def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
  function 总结音视频 (line 133) | def 总结音视频(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_promp...

FILE: crazy_functions/批量Markdown翻译.py
  class PaperFileGroup (line 7) | class PaperFileGroup():
    method __init__ (line 8) | def __init__(self):
    method run_file_split (line 21) | def run_file_split(self, max_token_limit=1900):
    method merge_result (line 39) | def merge_result(self):
    method write_result (line 44) | def write_result(self, language):
  function 多文件翻译 (line 53) | def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chat...
  function get_files_from_everything (line 115) | def get_files_from_everything(txt, preference=''):
  function Markdown英译中 (line 154) | def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system...
  function Markdown中译英 (line 194) | def Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system...
  function Markdown翻译指定语言 (line 227) | def Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys...

FILE: crazy_functions/批量总结PDF文档.py
  function 解析PDF (line 9) | def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chat...
  function 批量总结PDF文档 (line 108) | def 批量总结PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p...

FILE: crazy_functions/批量总结PDF文档pdfminer.py
  function readPdf (line 7) | def readPdf(pdfPath):
  function 解析Paper (line 65) | def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch...
  function 批量总结PDF文档pdfminer (line 125) | def 批量总结PDF文档pdfminer(txt, llm_kwargs, plugin_kwargs, chatbot, history, ...

FILE: crazy_functions/批量翻译PDF文档_多线程.py
  function 批量翻译PDF文档 (line 9) | def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_prom...
  function 解析PDF (line 59) | def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chat...
  class construct_html (line 162) | class construct_html():
    method __init__ (line 163) | def __init__(self) -> None:
    method add_row (line 191) | def add_row(self, a, b):
    method save_file (line 204) | def save_file(self, file_name):

FILE: crazy_functions/数学动画生成manim.py
  function inspect_dependency (line 5) | def inspect_dependency(chatbot, history):
  function eval_manim (line 15) | def eval_manim(code):
  function get_code_block (line 42) | def get_code_block(reply):
  function 动画生成 (line 51) | def 动画生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt...
  function examples_of_manim (line 100) | def examples_of_manim():

FILE: crazy_functions/理解PDF文档内容.py
  function 解析PDF (line 8) | def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system...
  function 理解PDF文档内容标准文件输入 (line 71) | def 理解PDF文档内容标准文件输入(txt, llm_kwargs, plugin_kwargs, chatbot, history, sy...

FILE: crazy_functions/生成函数注释.py
  function 生成函数注释 (line 6) | def 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, cha...
  function 批量生成函数注释 (line 37) | def 批量生成函数注释(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...

FILE: crazy_functions/联网的ChatGPT.py
  function google (line 7) | def google(query, proxies):
  function scrape_text (line 30) | def scrape_text(url, proxies) -> str:
  function 连接网络回答问题 (line 58) | def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...

FILE: crazy_functions/联网的ChatGPT_bing版.py
  function bing_search (line 8) | def bing_search(query, proxies=None):
  function scrape_text (line 30) | def scrape_text(url, proxies) -> str:
  function 连接bing搜索回答问题 (line 58) | def 连接bing搜索回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, syste...

FILE: crazy_functions/虚空终端.py
  function get_fn_lib (line 58) | def get_fn_lib():
  function inspect_dependency (line 67) | def inspect_dependency(chatbot, history):
  function eval_code (line 70) | def eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_...
  function get_code_block (line 90) | def get_code_block(reply):
  function 终端 (line 99) | def 终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, ...

FILE: crazy_functions/解析JupyterNotebook.py
  class PaperFileGroup (line 6) | class PaperFileGroup():
    method __init__ (line 7) | def __init__(self):
    method run_file_split (line 21) | def run_file_split(self, max_token_limit=1900):
  function parseNotebook (line 42) | def parseNotebook(filename, enable_markdown=1):
  function ipynb解释 (line 67) | def ipynb解释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch...
  function 解析ipynb文件 (line 118) | def 解析ipynb文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p...

FILE: crazy_functions/解析项目源代码.py
  function 解析源代码新 (line 5) | def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, cha...
  function 解析项目本身 (line 106) | def 解析项目本身(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom...
  function 解析一个Python项目 (line 120) | def 解析一个Python项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, syste...
  function 解析一个C项目的头文件 (line 139) | def 解析一个C项目的头文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system...
  function 解析一个C项目 (line 159) | def 解析一个C项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro...
  function 解析一个Java项目 (line 181) | def 解析一个Java项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_...
  function 解析一个前端项目 (line 203) | def 解析一个前端项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...
  function 解析一个Golang项目 (line 232) | def 解析一个Golang项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, syste...
  function 解析一个Rust项目 (line 253) | def 解析一个Rust项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_...
  function 解析一个Lua项目 (line 273) | def 解析一个Lua项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p...
  function 解析一个CSharp项目 (line 295) | def 解析一个CSharp项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, syste...
  function 解析任意code项目 (line 315) | def 解析任意code项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_...

FILE: crazy_functions/询问多个大语言模型.py
  function 同时问询 (line 5) | def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt...
  function 同时问询_指定模型 (line 34) | def 同时问询_指定模型(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p...

FILE: crazy_functions/语音助手.py
  class WatchDog (line 10) | class WatchDog():
    method __init__ (line 11) | def __init__(self, timeout, bark_fn, interval=3, msg="") -> None:
    method watch (line 19) | def watch(self):
    method begin_watch (line 28) | def begin_watch(self):
    method feed (line 34) | def feed(self):
  function chatbot2history (line 37) | def chatbot2history(chatbot):
  class AsyncGptTask (line 45) | class AsyncGptTask():
    method __init__ (line 46) | def __init__(self) -> None:
    method gpt_thread_worker (line 50) | def gpt_thread_worker(self, i_say, llm_kwargs, history, sys_prompt, ob...
    method add_async_gpt_task (line 61) | def add_async_gpt_task(self, i_say, chatbot_index, llm_kwargs, history...
    method update_chatbot (line 69) | def update_chatbot(self, chatbot):
  class InterviewAssistant (line 79) | class InterviewAssistant(AliyunASR):
    method __init__ (line 80) | def __init__(self):
    method __del__ (line 90) | def __del__(self):
    method init (line 96) | def init(self, chatbot):
    method no_audio_for_a_while (line 111) | def no_audio_for_a_while(self):
    method begin (line 117) | def begin(self, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...
  function 语音助手 (line 172) | def 语音助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt...

FILE: crazy_functions/读文章写摘要.py
  function 解析Paper (line 7) | def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch...
  function 读文章写摘要 (line 50) | def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom...

FILE: crazy_functions/谷歌检索小助手.py
  function get_meta_information (line 5) | def get_meta_information(url, chatbot, history):
  function 谷歌检索小助手 (line 67) | def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro...

FILE: crazy_functions/辅助回答.py
  function 猜你想问 (line 11) | def 猜你想问(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt...

FILE: crazy_functions/高级功能函数模板.py
  function 高阶功能模板函数 (line 5) | def 高阶功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr...

FILE: gradio_demo.py
  function auto_opentab_delay (line 41) | def auto_opentab_delay(port=7585):
  function load_auto_backend_models (line 50) | def load_auto_backend_models(lama,sam,det,tag2text,device):
  function Auto_run (line 85) | def Auto_run(
  function main (line 284) | def main(args):

FILE: llm_cards/bridge_all.py
  class LazyloadTiktoken (line 28) | class LazyloadTiktoken(object):
    method __init__ (line 29) | def __init__(self, model):
    method get_encoder (line 34) | def get_encoder(model):
    method encode (line 40) | def encode(self, *args, **kwargs):
    method decode (line 44) | def decode(self, *args, **kwargs):
  function LLM_CATCH_EXCEPTION (line 235) | def LLM_CATCH_EXCEPTION(f):
  function predict_no_ui_long_connection (line 249) | def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_promp...
  function predict_all (line 326) | def predict_all(inputs, llm_kwargs, *args, **kwargs):
  function talk_all (line 340) | def talk_all(inputs, llm_kwargs, *args, **kwargs):

FILE: llm_cards/bridge_chatglm.py
  class GetGLMHandle (line 13) | class GetGLMHandle(Process):
    method __init__ (line 14) | def __init__(self,quantize=None):
    method check_dependency (line 27) | def check_dependency(self):
    method ready (line 36) | def ready(self):
    method run (line 39) | def run(self):
    method stream_chat (line 95) | def stream_chat(self, **kwargs):
  function predict_no_ui_long_connection (line 111) | def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_pr...
  function asr_with_gpt (line 143) | def asr_with_gpt(transcriber,text_queue, llm_kwargs, plugin_kwargs, chat...
  function send_ui (line 171) | async def send_ui(text_queue,chatbot, history):
  function Talk_with_app (line 187) | def Talk_with_app(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[]...
  function predict (line 239) | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], syst...

FILE: llm_cards/bridge_chatgpt.py
  function get_full_error (line 31) | def get_full_error(chunk, stream_response):
  function predict_no_ui_long_connection (line 43) | def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_pr...
  function asr_with_gpt (line 111) | def asr_with_gpt(transcriber,text_queue, llm_kwargs, plugin_kwargs, chat...
  function Talk_with_app (line 138) | def Talk_with_app(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[]...
  function predict (line 191) | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], syst...
  function generate_payload (line 338) | def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):

FILE: llm_cards/bridge_stackclaude.py
  class SlackClient (line 23) | class SlackClient(AsyncWebClient):
    method open_channel (line 38) | async def open_channel(self):
    method chat (line 42) | async def chat(self, text):
    method get_slack_messages (line 49) | async def get_slack_messages(self):
    method get_reply (line 59) | async def get_reply(self):
  class ClaudeHandle (line 82) | class ClaudeHandle(Process):
    method __init__ (line 83) | def __init__(self):
    method check_dependency (line 95) | def check_dependency(self):
    method ready (line 105) | def ready(self):
    method async_run (line 108) | async def async_run(self):
    method run (line 140) | def run(self):
    method stream_chat (line 177) | def stream_chat(self, **kwargs):
  function predict_no_ui_long_connection (line 204) | def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_pr...
  function predict (line 234) | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], syst...

FILE: llm_cards/core_functional.py
  function get_core_functions (line 9) | def get_core_functions():
  function handle_core_functionality (line 81) | def handle_core_functionality(additional_fn, inputs, history, chatbot):

FILE: llm_cards/crazy_functional.py
  function get_crazy_functions (line 4) | def get_crazy_functions():

FILE: model_cards/Tag2Text/batch_inference.py
  function parse_args (line 20) | def parse_args():
  function load_dataset (line 94) | def load_dataset(
  function get_class_idxs (line 151) | def get_class_idxs(
  function load_thresholds (line 170) | def load_thresholds(
  function gen_pred_file (line 201) | def gen_pred_file(
  function load_ram (line 217) | def load_ram(
  function load_tag2text (line 236) | def load_tag2text(
  function forward_ram (line 250) | def forward_ram(model: Module, imgs: Tensor) -> Tensor:
  function forward_tag2text (line 267) | def forward_tag2text(
  function print_write (line 287) | def print_write(f: TextIO, s: str):

FILE: model_cards/Tag2Text/ram/inference.py
  function inference_tag2text (line 8) | def inference_tag2text(image, model, input_tag="None"):
  function inference_ram (line 33) | def inference_ram(image, model):
  function inference_ram_openset (line 42) | def inference_ram_openset(image, model):

FILE: model_cards/Tag2Text/ram/models/bert.py
  class BertEmbeddings_nopos (line 52) | class BertEmbeddings_nopos(nn.Module):
    method __init__ (line 55) | def __init__(self, config):
    method forward (line 71) | def forward(
  class BertEmbeddings (line 100) | class BertEmbeddings(nn.Module):
    method __init__ (line 103) | def __init__(self, config):
    method forward (line 119) | def forward(
  class BertSelfAttention (line 146) | class BertSelfAttention(nn.Module):
    method __init__ (line 147) | def __init__(self, config, is_cross_attention):
    method save_attn_gradients (line 175) | def save_attn_gradients(self, attn_gradients):
    method get_attn_gradients (line 178) | def get_attn_gradients(self):
    method save_attention_map (line 181) | def save_attention_map(self, attention_map):
    method get_attention_map (line 184) | def get_attention_map(self):
    method transpose_for_scores (line 187) | def transpose_for_scores(self, x):
    method forward (line 192) | def forward(
  class BertSelfOutput (line 284) | class BertSelfOutput(nn.Module):
    method __init__ (line 285) | def __init__(self, config):
    method forward (line 291) | def forward(self, hidden_states, input_tensor):
  class BertAttention (line 298) | class BertAttention(nn.Module):
    method __init__ (line 299) | def __init__(self, config, is_cross_attention=False):
    method prune_heads (line 305) | def prune_heads(self, heads):
    method forward (line 323) | def forward(
  class BertIntermediate (line 347) | class BertIntermediate(nn.Module):
    method __init__ (line 348) | def __init__(self, config):
    method forward (line 356) | def forward(self, hidden_states):
  class BertOutput (line 362) | class BertOutput(nn.Module):
    method __init__ (line 363) | def __init__(self, config):
    method forward (line 369) | def forward(self, hidden_states, input_tensor):
  class BertLayer (line 376) | class BertLayer(nn.Module):
    method __init__ (line 377) | def __init__(self, config, layer_num):
    method forward (line 389) | def forward(
    method feed_forward_chunk (line 455) | def feed_forward_chunk(self, attention_output):
  class BertEncoder (line 461) | class BertEncoder(nn.Module):
    method __init__ (line 462) | def __init__(self, config):
    method forward (line 468) | def forward(
  class BertPooler (line 561) | class BertPooler(nn.Module):
    method __init__ (line 562) | def __init__(self, config):
    method forward (line 567) | def forward(self, hidden_states):
  class BertPredictionHeadTransform (line 576) | class BertPredictionHeadTransform(nn.Module):
    method __init__ (line 577) | def __init__(self, config):
    method forward (line 586) | def forward(self, hidden_states):
  class BertLMPredictionHead (line 593) | class BertLMPredictionHead(nn.Module):
    method __init__ (line 594) | def __init__(self, config):
    method forward (line 607) | def forward(self, hidden_states):
  class BertOnlyMLMHead (line 613) | class BertOnlyMLMHead(nn.Module):
    method __init__ (line 614) | def __init__(self, config):
    method forward (line 618) | def forward(self, sequence_output):
  class BertPreTrainedModel (line 623) | class BertPreTrainedModel(PreTrainedModel):
    method _init_weights (line 633) | def _init_weights(self, module):
  class BertModel (line 646) | class BertModel(BertPreTrainedModel):
    method __init__ (line 656) | def __init__(self, config, add_pooling_layer=True):
    method get_input_embeddings (line 669) | def get_input_embeddings(self):
    method set_input_embeddings (line 672) | def set_input_embeddings(self, value):
    method _prune_heads (line 675) | def _prune_heads(self, heads_to_prune):
    method get_extended_attention_mask (line 684) | def get_extended_attention_mask(self, attention_mask: Tensor, input_sh...
    method forward (line 745) | def forward(
  class BertLMHeadModel (line 885) | class BertLMHeadModel(BertPreTrainedModel):
    method __init__ (line 890) | def __init__(self, config):
    method get_output_embeddings (line 898) | def get_output_embeddings(self):
    method set_output_embeddings (line 901) | def set_output_embeddings(self, new_embeddings):
    method forward (line 904) | def forward(
    method prepare_inputs_for_generation (line 1010) | def prepare_inputs_for_generation(self, input_ids, past=None, attentio...
    method _reorder_cache (line 1029) | def _reorder_cache(self, past, beam_idx):

FILE: model_cards/Tag2Text/ram/models/ram.py
  class RAM (line 20) | class RAM(nn.Module):
    method __init__ (line 21) | def __init__(self,
    method load_tag_list (line 158) | def load_tag_list(self, tag_list_file):
    method del_selfattention (line 165) | def del_selfattention(self):
    method generate_tag (line 170) | def generate_tag(self,
    method generate_tag_openset (line 217) | def generate_tag_openset(self,
  function ram (line 262) | def ram(pretrained='', **kwargs):

FILE: model_cards/Tag2Text/ram/models/swin_transformer.py
  class Mlp (line 17) | class Mlp(nn.Module):
    method __init__ (line 18) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 27) | def forward(self, x):
  function window_partition (line 36) | def window_partition(x, window_size):
  function window_reverse (line 51) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 68) | class WindowAttention(nn.Module):
    method __init__ (line 82) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 116) | def forward(self, x, mask=None):
    method extra_repr (line 149) | def extra_repr(self) -> str:
    method flops (line 152) | def flops(self, N):
  class SwinTransformerBlock (line 166) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 185) | def __init__(self, dim, input_resolution, num_heads, window_size=7, sh...
    method forward (line 236) | def forward(self, x):
    method extra_repr (line 275) | def extra_repr(self) -> str:
    method flops (line 279) | def flops(self):
  class PatchMerging (line 294) | class PatchMerging(nn.Module):
    method __init__ (line 303) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
    method forward (line 310) | def forward(self, x):
    method extra_repr (line 333) | def extra_repr(self) -> str:
    method flops (line 336) | def flops(self):
  class BasicLayer (line 343) | class BasicLayer(nn.Module):
    method __init__ (line 363) | def __init__(self, dim, input_resolution, depth, num_heads, window_size,
    method forward (line 391) | def forward(self, x):
    method extra_repr (line 401) | def extra_repr(self) -> str:
    method flops (line 404) | def flops(self):
  class PatchEmbed (line 413) | class PatchEmbed(nn.Module):
    method __init__ (line 424) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 443) | def forward(self, x):
    method flops (line 453) | def flops(self):
  class SwinTransformer (line 461) | class SwinTransformer(nn.Module):
    method __init__ (line 487) | def __init__(self, img_size=224, patch_size=4, in_chans=3, num_classes...
    method _init_weights (line 545) | def _init_weights(self, m):
    method no_weight_decay (line 555) | def no_weight_decay(self):
    method no_weight_decay_keywords (line 559) | def no_weight_decay_keywords(self):
    method forward (line 562) | def forward(self, x, idx_to_group_img=None, image_atts=None, **kwargs):
    method flops (line 586) | def flops(self):
  function interpolate_relative_pos_embed (line 596) | def interpolate_relative_pos_embed(rel_pos_bias, dst_num_pos, param_name...

FILE: model_cards/Tag2Text/ram/models/tag2text.py
  class Tag2Text (line 19) | class Tag2Text(nn.Module):
    method __init__ (line 21) | def __init__(self,
    method load_tag_list (line 128) | def load_tag_list(self, tag_list_file):
    method del_selfattention (line 135) | def del_selfattention(self):
    method forward (line 141) | def forward(self, image, caption, tag):
    method generate (line 231) | def generate(self,
  function tag2text (line 360) | def tag2text(pretrained='', **kwargs):

FILE: model_cards/Tag2Text/ram/models/utils.py
  function read_json (line 16) | def read_json(rpath):
  function tie_encoder_decoder_weights (line 21) | def tie_encoder_decoder_weights(encoder: nn.Module, decoder: nn.Module,
  class GroupWiseLinear (line 99) | class GroupWiseLinear(nn.Module):
    method __init__ (line 103) | def __init__(self, num_class, hidden_dim, bias=True):
    method reset_parameters (line 114) | def reset_parameters(self):
    method forward (line 122) | def forward(self, x):
  function init_tokenizer (line 130) | def init_tokenizer():
  function create_vit (line 138) | def create_vit(vit,
  function is_url (line 170) | def is_url(url_or_filename):
  function load_checkpoint (line 175) | def load_checkpoint(model, url_or_filename):
  function load_checkpoint_swinbase (line 203) | def load_checkpoint_swinbase(model, url_or_filename, kwargs):
  function load_checkpoint_swinlarge (line 241) | def load_checkpoint_swinlarge(model, url_or_filename, kwargs):
  class AsymmetricLoss (line 281) | class AsymmetricLoss(nn.Module):
    method __init__ (line 282) | def __init__(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-8, disa...
    method forward (line 291) | def forward(self, x, y):

FILE: model_cards/Tag2Text/ram/models/vit.py
  class Mlp (line 23) | class Mlp(nn.Module):
    method __init__ (line 26) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 35) | def forward(self, x):
  class Attention (line 44) | class Attention(nn.Module):
    method __init__ (line 45) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method save_attn_gradients (line 58) | def save_attn_gradients(self, attn_gradients):
    method get_attn_gradients (line 61) | def get_attn_gradients(self):
    method save_attention_map (line 64) | def save_attention_map(self, attention_map):
    method get_attention_map (line 67) | def get_attention_map(self):
    method forward (line 70) | def forward(self, x, register_hook=False):
  class Block (line 89) | class Block(nn.Module):
    method __init__ (line 91) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
    method forward (line 107) | def forward(self, x, register_hook=False):
  class VisionTransformer (line 113) | class VisionTransformer(nn.Module):
    method __init__ (line 118) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
    method _init_weights (line 167) | def _init_weights(self, m):
    method no_weight_decay (line 177) | def no_weight_decay(self):
    method forward (line 180) | def forward(self, x, register_blk=-1):
    method load_pretrained (line 197) | def load_pretrained(self, checkpoint_path, prefix=''):
  function _load_weights (line 202) | def _load_weights(model: VisionTransformer, checkpoint_path: str, prefix...
  function interpolate_pos_embed (line 281) | def interpolate_pos_embed(pos_embed_checkpoint, visual_encoder):

FILE: model_cards/Tag2Text/ram/transform.py
  function get_transform (line 4) | def get_transform(image_size=384):

FILE: model_cards/Tag2Text/ram/utils/metrics.py
  function get_mAP (line 7) | def get_mAP(
  function _average_precision (line 41) | def _average_precision(output: ndarray, target: ndarray) -> float:
  function get_PR (line 61) | def get_PR(

FILE: model_cards/Tag2Text/ram/utils/openset_utils.py
  function article (line 9) | def article(name):
  function processed_name (line 13) | def processed_name(name, rm_dot=False):
  function build_openset_label_embedding (line 293) | def build_openset_label_embedding(categories=None):

FILE: model_cards/autoback.py
  function preprocess_image (line 48) | def preprocess_image(img):
  class Ensemble (line 67) | class Ensemble(nn.ModuleList):
    method __init__ (line 69) | def __init__(self):
    method forward (line 72) | def forward(self, x, augment=False, profile=False, visualize=False):
  function torch_safe_load (line 77) | def torch_safe_load(weight):
  function is_similar_string (line 102) | def is_similar_string(string):
  function attempt_load (line 109) | def attempt_load(weights, device=None):
  class AutoBackend (line 124) | class AutoBackend(nn.Module):
    method __init__ (line 126) | def __init__(self, methods: str ,weights: None , device=torch.device('...
    method forward (line 253) | def forward(self, im, augment=False, visualize=False,prompt= None ,box...
    method gligen_inference (line 278) | def gligen_inference(config=None, starting_noise=None,negative_prompt=...
    method grounded_inference (line 281) | def grounded_inference(self,im,caption,box_threshold,text_threshold,io...
    method sam_inference (line 322) | def sam_inference(self,im,prompt):
    method tag2text_inference (line 334) | def tag2text_inference(self,im,prompt):
    method ram_inference (line 341) | def ram_inference(self,im):
    method lama_inference (line 347) | def lama_inference(self,im,mask) :
    method _model_type (line 376) | def _model_type(p='path/to/model.pt'):

FILE: model_cards/groundingdino/datasets/transforms.py
  function crop (line 17) | def crop(image, target, region):
  function hflip (line 68) | def hflip(image, target):
  function resize (line 87) | def resize(image, target, size, max_size=None):
  function pad (line 149) | def pad(image, target, padding):
  class ResizeDebug (line 162) | class ResizeDebug(object):
    method __init__ (line 163) | def __init__(self, size):
    method __call__ (line 166) | def __call__(self, img, target):
  class RandomCrop (line 170) | class RandomCrop(object):
    method __init__ (line 171) | def __init__(self, size):
    method __call__ (line 174) | def __call__(self, img, target):
  class RandomSizeCrop (line 179) | class RandomSizeCrop(object):
    method __init__ (line 180) | def __init__(self, min_size: int, max_size: int, respect_boxes: bool =...
    method __call__ (line 187) | def __call__(self, img: PIL.Image.Image, target: dict):
  class CenterCrop (line 204) | class CenterCrop(object):
    method __init__ (line 205) | def __init__(self, size):
    method __call__ (line 208) | def __call__(self, img, target):
  class RandomHorizontalFlip (line 216) | class RandomHorizontalFlip(object):
    method __init__ (line 217) | def __init__(self, p=0.5):
    method __call__ (line 220) | def __call__(self, img, target):
  class RandomResize (line 226) | class RandomResize(object):
    method __init__ (line 227) | def __init__(self, sizes, max_size=None):
    method __call__ (line 232) | def __call__(self, img, target=None):
  class RandomPad (line 237) | class RandomPad(object):
    method __init__ (line 238) | def __init__(self, max_pad):
    method __call__ (line 241) | def __call__(self, img, target):
  class RandomSelect (line 247) | class RandomSelect(object):
    method __init__ (line 253) | def __init__(self, transforms1, transforms2, p=0.5):
    method __call__ (line 258) | def __call__(self, img, target):
  class ToTensor (line 264) | class ToTensor(object):
    method __call__ (line 265) | def __call__(self, img, target):
  class RandomErasing (line 269) | class RandomErasing(object):
    method __init__ (line 270) | def __init__(self, *args, **kwargs):
    method __call__ (line 273) | def __call__(self, img, target):
  class Normalize (line 277) | class Normalize(object):
    method __init__ (line 278) | def __init__(self, mean, std):
    method __call__ (line 282) | def __call__(self, image, target=None):
  class Compose (line 296) | class Compose(object):
    method __init__ (line 297) | def __init__(self, transforms):
    method __call__ (line 300) | def __call__(self, image, target):
    method __repr__ (line 305) | def __repr__(self):

FILE: model_cards/groundingdino/models/GroundingDINO/backbone/backbone.py
  class FrozenBatchNorm2d (line 33) | class FrozenBatchNorm2d(torch.nn.Module):
    method __init__ (line 42) | def __init__(self, n):
    method _load_from_state_dict (line 49) | def _load_from_state_dict(
    method forward (line 60) | def forward(self, x):
  class BackboneBase (line 73) | class BackboneBase(nn.Module):
    method __init__ (line 74) | def __init__(
    method forward (line 107) | def forward(self, tensor_list: NestedTensor):
  class Backbone (line 119) | class Backbone(BackboneBase):
    method __init__ (line 122) | def __init__(
  class Joiner (line 146) | class Joiner(nn.Sequential):
    method __init__ (line 147) | def __init__(self, backbone, position_embedding):
    method forward (line 150) | def forward(self, tensor_list: NestedTensor):
  function build_backbone (line 162) | def build_backbone(args):

FILE: model_cards/groundingdino/models/GroundingDINO/backbone/position_encoding.py
  class PositionEmbeddingSine (line 30) | class PositionEmbeddingSine(nn.Module):
    method __init__ (line 36) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 47) | def forward(self, tensor_list: NestedTensor):
  class PositionEmbeddingSineHW (line 78) | class PositionEmbeddingSineHW(nn.Module):
    method __init__ (line 84) | def __init__(
    method forward (line 98) | def forward(self, tensor_list: NestedTensor):
  class PositionEmbeddingLearned (line 134) | class PositionEmbeddingLearned(nn.Module):
    method __init__ (line 139) | def __init__(self, num_pos_feats=256):
    method reset_parameters (line 145) | def reset_parameters(self):
    method forward (line 149) | def forward(self, tensor_list: NestedTensor):
  function build_position_encoding (line 171) | def build_position_encoding(args):

FILE: model_cards/groundingdino/models/GroundingDINO/backbone/swin_transformer.py
  class Mlp (line 24) | class Mlp(nn.Module):
    method __init__ (line 27) | 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 61) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 77) | class WindowAttention(nn.Module):
    method __init__ (line 90) | def __init__(
    method forward (line 134) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 177) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 194) | def __init__(
    method forward (line 238) | def forward(self, x, mask_matrix):
  class PatchMerging (line 301) | class PatchMerging(nn.Module):
    method __init__ (line 308) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 314) | def forward(self, x, H, W):
  class BasicLayer (line 343) | class BasicLayer(nn.Module):
    method __init__ (line 361) | def __init__(
    method forward (line 409) | def forward(self, x, H, W):
  class PatchEmbed (line 459) | class PatchEmbed(nn.Module):
    method __init__ (line 468) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 482) | def forward(self, x):
  class SwinTransformer (line 501) | class SwinTransformer(nn.Module):
    method __init__ (line 530) | def __init__(
    method _freeze_stages (line 636) | def _freeze_stages(self):
    method forward_raw (line 678) | def forward_raw(self, x):
    method forward (line 712) | def forward(self, tensor_list: NestedTensor):
    method train (line 756) | def train(self, mode=True):
  function build_swin_transformer (line 762) | def build_swin_transformer(modelname, pretrain_img_size, **kw):

FILE: model_cards/groundingdino/models/GroundingDINO/bertwarper.py
  class BertModelWarper (line 17) | class BertModelWarper(nn.Module):
    method __init__ (line 18) | def __init__(self, bert_model):
    method forward (line 31) | def forward(
  class TextEncoderShell (line 169) | class TextEncoderShell(nn.Module):
    method __init__ (line 170) | def __init__(self, text_encoder):
    method forward (line 175) | def forward(self, **kw):
  function generate_masks_with_special_tokens (line 180) | def generate_masks_with_special_tokens(tokenized, special_tokens_list, t...
  function generate_masks_with_special_tokens_and_transfer_map (line 224) | def generate_masks_with_special_tokens_and_transfer_map(tokenized, speci...

FILE: model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn.h
  function namespace (line 19) | namespace groundingdino {

FILE: model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cpu.cpp
  type groundingdino (line 16) | namespace groundingdino {
    function ms_deform_attn_cpu_forward (line 18) | at::Tensor
    function ms_deform_attn_cpu_backward (line 30) | std::vector<at::Tensor>

FILE: model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cpu.h
  function namespace (line 14) | namespace groundingdino {

FILE: model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cuda.h
  function namespace (line 14) | namespace groundingdino {

FILE: model_cards/groundingdino/models/GroundingDINO/csrc/vision.cpp
  type groundingdino (line 5) | namespace groundingdino {
    function get_cuda_version (line 11) | std::string get_cuda_version() {
    function get_compiler_version (line 32) | std::string get_compiler_version() {
    function PYBIND11_MODULE (line 53) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: model_cards/groundingdino/models/GroundingDINO/fuse_modules.py
  class FeatureResizer (line 14) | class FeatureResizer(nn.Module):
    method __init__ (line 20) | def __init__(self, input_feat_size, output_feat_size, dropout, do_ln=T...
    method forward (line 28) | def forward(self, encoder_features):
  function l1norm (line 36) | def l1norm(X, dim, eps=1e-8):
  function l2norm (line 43) | def l2norm(X, dim, eps=1e-8):
  function func_attention (line 50) | def func_attention(query, context, smooth=1, raw_feature_norm="softmax",...
  class BiMultiHeadAttention (line 99) | class BiMultiHeadAttention(nn.Module):
    method __init__ (line 100) | def __init__(self, v_dim, l_dim, embed_dim, num_heads, dropout=0.1, cf...
    method _shape (line 129) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method _reset_parameters (line 132) | def _reset_parameters(self):
    method forward (line 146) | def forward(self, v, l, attention_mask_v=None, attention_mask_l=None):
  class BiAttentionBlock (line 252) | class BiAttentionBlock(nn.Module):
    method __init__ (line 253) | def __init__(
    method forward (line 286) | def forward(self, v, l, attention_mask_v=None, attention_mask_l=None):

FILE: model_cards/groundingdino/models/GroundingDINO/groundingdino.py
  class GroundingDINO (line 52) | class GroundingDINO(nn.Module):
    method __init__ (line 55) | def __init__(
    method _reset_parameters (line 204) | def _reset_parameters(self):
    method init_ref_points (line 210) | def init_ref_points(self, use_num_queries):
    method forward (line 213) | def forward(self, samples: NestedTensor, targets: List = None, **kw):
    method _set_aux_loss (line 353) | def _set_aux_loss(self, outputs_class, outputs_coord):
  function build_groundingdino (line 364) | def build_groundingdino(args):

FILE: model_cards/groundingdino/models/GroundingDINO/ms_deform_attn.py
  function _is_power_of_2 (line 35) | def _is_power_of_2(n):
  class MultiScaleDeformableAttnFunction (line 41) | class MultiScaleDeformableAttnFunction(Function):
    method forward (line 43) | def forward(
    method backward (line 72) | def backward(ctx, grad_output):
  function multi_scale_deformable_attn_pytorch (line 93) | def multi_scale_deformable_attn_pytorch(
  class MultiScaleDeformableAttention (line 136) | class MultiScaleDeformableAttention(nn.Module):
    method __init__ (line 154) | def __init__(
    method _reset_parameters (line 194) | def _reset_parameters(self):
    method init_weights (line 197) | def init_weights(self):
    method freeze_sampling_offsets (line 222) | def freeze_sampling_offsets(self):
    method freeze_attention_weights (line 227) | def freeze_attention_weights(self):
    method forward (line 232) | def forward(
  function create_dummy_class (line 362) | def create_dummy_class(klass, dependency, message=""):
  function create_dummy_func (line 391) | def create_dummy_func(func, dependency, message=""):

FILE: model_cards/groundingdino/models/GroundingDINO/transformer.py
  class Transformer (line 40) | class Transformer(nn.Module):
    method __init__ (line 41) | def __init__(
    method _reset_parameters (line 189) | def _reset_parameters(self):
    method get_valid_ratio (line 199) | def get_valid_ratio(self, mask):
    method init_ref_points (line 208) | def init_ref_points(self, use_num_queries):
    method forward (line 211) | def forward(self, srcs, masks, refpoint_embed, pos_embeds, tgt, attn_m...
  class TransformerEncoder (line 406) | class TransformerEncoder(nn.Module):
    method __init__ (line 407) | def __init__(
    method get_reference_points (line 466) | def get_reference_points(spatial_shapes, valid_ratios, device):
    method forward (line 482) | def forward(
  class TransformerDecoder (line 598) | class TransformerDecoder(nn.Module):
    method __init__ (line 599) | def __init__(
    method forward (line 633) | def forward(
  class DeformableTransformerEncoderLayer (line 738) | class DeformableTransformerEncoderLayer(nn.Module):
    method __init__ (line 739) | def __init__(
    method with_pos_embed (line 771) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 774) | def forward_ffn(self, src):
    method forward (line 780) | def forward(
  class DeformableTransformerDecoderLayer (line 802) | class DeformableTransformerDecoderLayer(nn.Module):
    method __init__ (line 803) | def __init__(
    method rm_self_attn_modules (line 852) | def rm_self_attn_modules(self):
    method with_pos_embed (line 858) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 861) | def forward_ffn(self, tgt):
    method forward (line 868) | def forward(
  function build_transformer (line 930) | def build_transformer(args):

FILE: model_cards/groundingdino/models/GroundingDINO/transformer_vanilla.py
  class TextTransformer (line 33) | class TextTransformer(nn.Module):
    method __init__ (line 34) | def __init__(self, num_layers, d_model=256, nheads=8, dim_feedforward=...
    method forward (line 47) | def forward(self, memory_text: torch.Tensor, text_attention_mask: torc...
  class TransformerEncoderLayer (line 72) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 73) | def __init__(
    method with_pos_embed (line 98) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward (line 101) | def forward(

FILE: model_cards/groundingdino/models/GroundingDINO/utils.py
  function _get_clones (line 16) | def _get_clones(module, N, layer_share=False):
  function get_sine_pos_embed (line 24) | def get_sine_pos_embed(
  function gen_encoder_output_proposals (line 56) | def gen_encoder_output_proposals(
  class RandomBoxPerturber (line 119) | class RandomBoxPerturber:
    method __init__ (line 120) | def __init__(
    method __call__ (line 127) | def __call__(self, refanchors: Tensor) -> Tensor:
  function sigmoid_focal_loss (line 138) | def sigmoid_focal_loss(
  class MLP (line 171) | class MLP(nn.Module):
    method __init__ (line 174) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 182) | def forward(self, x):
  function _get_activation_fn (line 188) | def _get_activation_fn(activation, d_model=256, batch_dim=0):
  function gen_sineembed_for_position (line 204) | def gen_sineembed_for_position(pos_tensor):
  class ContrastiveEmbed (line 233) | class ContrastiveEmbed(nn.Module):
    method __init__ (line 234) | def __init__(self, max_text_len=256):
    method forward (line 242) | def forward(self, x, text_dict):

FILE: model_cards/groundingdino/models/__init__.py
  function build_model (line 11) | def build_model(args):

FILE: model_cards/groundingdino/models/registry.py
  class Registry (line 18) | class Registry(object):
    method __init__ (line 19) | def __init__(self, name):
    method __repr__ (line 23) | def __repr__(self):
    method __len__ (line 29) | def __len__(self):
    method name (line 33) | def name(self):
    method module_dict (line 37) | def module_dict(self):
    method get (line 40) | def get(self, key):
    method registe_with_name (line 43) | def registe_with_name(self, module_name=None, force=False):
    method register (line 46) | def register(self, module_build_function, module_name=None, force=False):

FILE: model_cards/groundingdino/util/box_ops.py
  function box_cxcywh_to_xyxy (line 9) | def box_cxcywh_to_xyxy(x):
  function box_xyxy_to_cxcywh (line 15) | def box_xyxy_to_cxcywh(x):
  function box_iou (line 22) | def box_iou(boxes1, boxes2):
  function generalized_box_iou (line 39) | def generalized_box_iou(boxes1, boxes2):
  function box_iou_pairwise (line 66) | def box_iou_pairwise(boxes1, boxes2):
  function generalized_box_iou_pairwise (line 82) | def generalized_box_iou_pairwise(boxes1, boxes2):
  function masks_to_boxes (line 107) | def masks_to_boxes(masks):

FILE: model_cards/groundingdino/util/get_tokenlizer.py
  function get_tokenlizer (line 4) | def get_tokenlizer(text_encoder_type):
  function get_pretrained_language_model (line 21) | def get_pretrained_language_model(text_encoder_type):

FILE: model_cards/groundingdino/util/inference.py
  function preprocess_caption (line 21) | def preprocess_caption(caption: str) -> str:
  function load_model (line 28) | def load_model(model_config_path: str, model_checkpoint_path: str, devic...
  function load_image (line 38) | def load_image(image_path: str) -> Tuple[np.array, torch.Tensor]:
  function predict (line 52) | def predict(
  function annotate (line 87) | def annotate(image_source: np.ndarray, boxes: torch.Tensor, logits: torc...
  class Model (line 110) | class Model:
    method __init__ (line 112) | def __init__(
    method predict_with_caption (line 125) | def predict_with_caption(
    method predict_with_classes (line 165) | def predict_with_classes(
    method preprocess_image (line 210) | def preprocess_image(image_bgr: np.ndarray) -> torch.Tensor:
    method post_process_result (line 223) | def post_process_result(
    method phrases2classes (line 235) | def phrases2classes(phrases: List[str], classes: List[str]) -> np.ndar...

FILE: model_cards/groundingdino/util/logger.py
  class _ColorfulFormatter (line 10) | class _ColorfulFormatter(logging.Formatter):
    method __init__ (line 11) | def __init__(self, *args, **kwargs):
    method formatMessage (line 18) | def formatMessage(self, record):
  function setup_logger (line 32) | def setup_logger(output=None, distributed_rank=0, *, color=True, name="i...
  function _cached_log_stream (line 92) | def _cached_log_stream(filename):

FILE: model_cards/groundingdino/util/misc.py
  class SmoothedValue (line 33) | class SmoothedValue(object):
    method __init__ (line 38) | def __init__(self, window_size=20, fmt=None):
    method update (line 46) | def update(self, value, n=1):
    method synchronize_between_processes (line 51) | def synchronize_between_processes(self):
    method median (line 65) | def median(self):
    method avg (line 72) | def avg(self):
    method global_avg (line 77) | def global_avg(self):
    method max (line 85) | def max(self):
    method value (line 89) | def value(self):
    method __str__ (line 92) | def __str__(self):
  function _get_global_gloo_group (line 103) | def _get_global_gloo_group():
  function all_gather_cpu (line 115) | def all_gather_cpu(data):
  function all_gather (line 173) | def all_gather(data):
  function reduce_dict (line 220) | def reduce_dict(input_dict, average=True):
  class MetricLogger (line 247) | class MetricLogger(object):
    method __init__ (line 248) | def __init__(self, delimiter="\t"):
    method update (line 252) | def update(self, **kwargs):
    method __getattr__ (line 259) | def __getattr__(self, attr):
    method __str__ (line 266) | def __str__(self):
    method synchronize_between_processes (line 275) | def synchronize_between_processes(self):
    method add_meter (line 279) | def add_meter(self, name, meter):
    method log_every (line 282) | def log_every(self, iterable, print_freq, header=None, logger=None):
  function get_sha (line 362) | def get_sha():
  function collate_fn (line 383) | def collate_fn(batch):
  function _max_by_axis (line 390) | def _max_by_axis(the_list):
  class NestedTensor (line 399) | class NestedTensor(object):
    method __init__ (line 400) | def __init__(self, tensors, mask: Optional[Tensor]):
    method imgsize (line 416) | def imgsize(self):
    method to (line 425) | def to(self, device):
    method to_img_list_single (line 436) | def to_img_list_single(self, tensor, mask):
    method to_img_list (line 443) | def to_img_list(self):
    method device (line 460) | def device(self):
    method decompose (line 463) | def decompose(self):
    method __repr__ (line 466) | def __repr__(self):
    method shape (line 470) | def shape(self):
  function nested_tensor_from_tensor_list (line 474) | def nested_tensor_from_tensor_list(tensor_list: List[Tensor]):
  function _onnx_nested_tensor_from_tensor_list (line 502) | def _onnx_nested_tensor_from_tensor_list(tensor_list: List[Tensor]) -> N...
  function setup_for_distributed (line 532) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 548) | def is_dist_avail_and_initialized():
  function get_world_size (line 556) | def get_world_size():
  function get_rank (line 562) | def get_rank():
  function is_main_process (line 568) | def is_main_process():
  function save_on_master (line 572) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 577) | def init_distributed_mode(args):
  function accuracy (line 638) | def accuracy(output, target, topk=(1,)):
  function accuracy_onehot (line 657) | def accuracy_onehot(pred, gt):
  function interpolate (line 669) | def interpolate(input, size=None, scale_factor=None, mode="nearest", ali...
  class color_sys (line 687) | class color_sys:
    method __init__ (line 688) | def __init__(self, num_colors) -> None:
    method __call__ (line 700) | def __call__(self, idx):
  function inverse_sigmoid (line 704) | def inverse_sigmoid(x, eps=1e-3):
  function clean_state_dict (line 711) | def clean_state_dict(state_dict):

FILE: model_cards/groundingdino/util/slconfig.py
  function check_file_exist (line 21) | def check_file_exist(filename, msg_tmpl='file "{}" does not exist'):
  class ConfigDict (line 26) | class ConfigDict(Dict):
    method __missing__ (line 27) | def __missing__(self, name):
    method __getattr__ (line 30) | def __getattr__(self, name):
  class SLConfig (line 42) | class SLConfig(object):
    method _validate_py_syntax (line 68) | def _validate_py_syntax(filename):
    method _file2dict (line 77) | def _file2dict(filename):
    method _merge_a_into_b (line 140) | def _merge_a_into_b(a, b):
    method fromfile (line 184) | def fromfile(filename):
    method __init__ (line 188) | def __init__(self, cfg_dict=None, cfg_text=None, filename=None):
    method filename (line 209) | def filename(self):
    method text (line 213) | def text(self):
    method pretty_text (line 217) | def pretty_text(self):
    method __repr__ (line 310) | def __repr__(self):
    method __len__ (line 313) | def __len__(self):
    method __getattr__ (line 316) | def __getattr__(self, name):
    method __getitem__ (line 329) | def __getitem__(self, name):
    method __setattr__ (line 332) | def __setattr__(self, name, value):
    method __setitem__ (line 337) | def __setitem__(self, name, value):
    method __iter__ (line 342) | def __iter__(self):
    method dump (line 345) | def dump(self, file=None):
    method merge_from_dict (line 353) | def merge_from_dict(self, options):
    method __setstate__ (line 386) | def __setstate__(self, state):
    method copy (line 389) | def copy(self):
    method deepcopy (line 392) | def deepcopy(self):
  class DictAction (line 396) | class DictAction(Action):
    method _parse_int_float_bool (line 404) | def _parse_int_float_bool(val):
    method __call__ (line 419) | def __call__(self, parser, namespace, values, option_string=None):

FILE: model_cards/groundingdino/util/slio.py
  class BaseFileHandler (line 23) | class BaseFileHandler(metaclass=ABCMeta):
    method load_from_fileobj (line 25) | def load_from_fileobj(self, file, **kwargs):
    method dump_to_fileobj (line 29) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_str (line 33) | def dump_to_str(self, obj, **kwargs):
    method load_from_path (line 36) | def load_from_path(self, filepath, mode="r", **kwargs):
    method dump_to_path (line 40) | def dump_to_path(self, obj, filepath, mode="w", **kwargs):
  class JsonHandler (line 45) | class JsonHandler(BaseFileHandler):
    method load_from_fileobj (line 46) | def load_from_fileobj(self, file):
    method dump_to_fileobj (line 49) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_str (line 52) | def dump_to_str(self, obj, **kwargs):
  class PickleHandler (line 56) | class PickleHandler(BaseFileHandler):
    method load_from_fileobj (line 57) | def load_from_fileobj(self, file, **kwargs):
    method load_from_path (line 60) | def load_from_path(self, filepath, **kwargs):
    method dump_to_str (line 63) | def dump_to_str(self, obj, **kwargs):
    method dump_to_fileobj (line 67) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_path (line 71) | def dump_to_path(self, obj, filepath, **kwargs):
  class YamlHandler (line 75) | class YamlHandler(BaseFileHandler):
    method load_from_fileobj (line 76) | def load_from_fileobj(self, file, **kwargs):
    method dump_to_fileobj (line 80) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_str (line 84) | def dump_to_str(self, obj, **kwargs):
  function is_str (line 102) | def is_str(x):
  function slload (line 110) | def slload(file, file_format=None, **kwargs):
  function sldump (line 143) | def sldump(obj, file=None, file_format=None, **kwargs):

FILE: model_cards/groundingdino/util/time_counter.py
  class TimeCounter (line 5) | class TimeCounter:
    method __init__ (line 6) | def __init__(self) -> None:
    method clear (line 9) | def clear(self):
    method timeit (line 13) | def timeit(self, name):
  class TimeHolder (line 19) | class TimeHolder:
    method __init__ (line 20) | def __init__(self) -> None:
    method update (line 23) | def update(self, _timedict: dict):
    method final_res (line 29) | def final_res(self):
    method __str__ (line 32) | def __str__(self):
  class AverageMeter (line 36) | class AverageMeter(object):
    method __init__ (line 39) | def __init__(self, name, fmt=":f", val_only=False):
    method reset (line 45) | def reset(self):
    method update (line 51) | def update(self, val, n=1):
    method __str__ (line 57) | def __str__(self):

FILE: model_cards/groundingdino/util/utils.py
  function slprint (line 15) | def slprint(x, name="x"):
  function clean_state_dict (line 29) | def clean_state_dict(state_dict):
  function renorm (line 38) | def renorm(
  class CocoClassMapper (line 66) | class CocoClassMapper:
    method __init__ (line 67) | def __init__(self) -> None:
    method origin2compact (line 153) | def origin2compact(self, idx):
    method compact2origin (line 156) | def compact2origin(self, idx):
  function to_device (line 160) | def to_device(item, device):
  function get_gaussian_mean (line 174) | def get_gaussian_mean(x, axis, other_axis, softmax=True):
  function get_expected_points_from_map (line 200) | def get_expected_points_from_map(hm, softmax=True):
  class Embedder (line 222) | class Embedder:
    method __init__ (line 223) | def __init__(self, **kwargs):
    method create_embedding_fn (line 227) | def create_embedding_fn(self):
    method embed (line 251) | def embed(self, inputs):
  function get_embedder (line 255) | def get_embedder(multires, i=0):
  class APOPMeter (line 275) | class APOPMeter:
    method __init__ (line 276) | def __init__(self) -> None:
    method update (line 282) | def update(self, pred, gt):
    method update_cm (line 293) | def update_cm(self, tp, fp, tn, fn):
  function inverse_sigmoid (line 300) | def inverse_sigmoid(x, eps=1e-5):
  function get_raw_dict (line 307) | def get_raw_dict(args):
  function stat_tensors (line 325) | def stat_tensors(tensor):
  class NiceRepr (line 340) | class NiceRepr:
    method __nice__ (line 374) | def __nice__(self):
    method __repr__ (line 384) | def __repr__(self):
    method __str__ (line 394) | def __str__(self):
  function ensure_rng (line 405) | def ensure_rng(rng=None):
  function random_boxes (line 436) | def random_boxes(num=1, scale=1, rng=None):
  class ModelEma (line 473) | class ModelEma(torch.nn.Module):
    method __init__ (line 474) | def __init__(self, model, decay=0.9997, device=None):
    method _update (line 487) | def _update(self, model, update_fn):
    method update (line 496) | def update(self, model):
    method set (line 499) | def set(self, model):
  class BestMetricSingle (line 503) | class BestMetricSingle:
    method __init__ (line 504) | def __init__(self, init_res=0.0, better="large") -> None:
    method isbetter (line 512) | def isbetter(self, new_res, old_res):
    method update (line 518) | def update(self, new_res, ep):
    method __str__ (line 525) | def __str__(self) -> str:
    method __repr__ (line 528) | def __repr__(self) -> str:
    method summary (line 531) | def summary(self) -> dict:
  class BestMetricHolder (line 538) | class BestMetricHolder:
    method __init__ (line 539) | def __init__(self, init_res=0.0, better="large", use_ema=False) -> None:
    method update (line 546) | def update(self, new_res, epoch, is_ema=False):
    method summary (line 560) | def summary(self):
    method __repr__ (line 570) | def __repr__(self) -> str:
    method __str__ (line 573) | def __str__(self) -> str:
  function targets_to (line 577) | def targets_to(targets: List[Dict[str, Any]], device):
  function get_phrases_from_posmap (line 599) | def get_phrases_from_posmap(

FILE: model_cards/groundingdino/util/visualizer.py
  function renorm (line 22) | def renorm(
  class ColorMap (line 50) | class ColorMap:
    method __init__ (line 51) | def __init__(self, basergb=[255, 255, 0]):
    method __call__ (line 54) | def __call__(self, attnmap):
  function rainbow_text (line 66) | def rainbow_text(x, y, ls, lc, **kw):
  class COCOVisualizer (line 95) | class COCOVisualizer:
    method __init__ (line 96) | def __init__(self, coco=None, tokenlizer=None) -> None:
    method visualize (line 99) | def visualize(self, img, tgt, caption=None, dpi=180, savedir="vis"):
    method addtgt (line 135) | def addtgt(self, tgt):
    method showAnns (line 225) | def showAnns(self, anns, draw_bbox=False):

FILE: model_cards/groundingdino/util/vl_utils.py
  function create_positive_map_from_span (line 8) | def create_positive_map_from_span(tokenized, token_span, max_text_len=256):
  function build_captions_and_token_span (line 49) | def build_captions_and_token_span(cat_list, force_lowercase):
  function build_id2posspan_and_caption (line 90) | def build_id2posspan_and_caption(category_dict: dict):

FILE: model_cards/lama/bin/analyze_errors.py
  function draw_score (line 18) | def draw_score(img, score):
  function save_global_samples (line 30) | def save_global_samples(global_mask_fnames, mask2real_fname, mask2fake_f...
  function save_samples_by_real (line 49) | def save_samples_by_real(worst_best_by_real, mask2fake_fname, fake_info,...
  function extract_overlapping_masks (line 85) | def extract_overlapping_masks(mask_fnames, cur_i, fake_scores_table, max...
  function main (line 103) | def main(args):

FILE: model_cards/lama/bin/blur_predicts.py
  function main (line 13) | def main(args):

FILE: model_cards/lama/bin/calc_dataset_stats.py
  function main (line 13) | def main(args):

FILE: model_cards/lama/bin/evaluate_predicts.py
  function main (line 14) | def main(args):

FILE: model_cards/lama/bin/evaluator_example.py
  class SimpleImageDataset (line 14) | class SimpleImageDataset(Dataset):
    method __init__ (line 15) | def __init__(self, root_dir, image_size=(400, 600)):
    method __getitem__ (line 20) | def __getitem__(self, index):
    method __len__ (line 27) | def __len__(self):
  function create_rectangle_mask (line 31) | def create_rectangle_mask(height, width):
  class Model (line 39) | class Model():
    method __call__ (line 40) | def __call__(self, img_batch, mask_batch):
  class SimpleImageSquareMaskDataset (line 46) | class SimpleImageSquareMaskDataset(Dataset):
    method __init__ (line 47) | def __init__(self, dataset):
    method __getitem__ (line 52) | def __getitem__(self, index):
    method __len__ (line 58) | def __len__(self):

FILE: model_cards/lama/bin/extract_masks.py
  function main (line 6) | def main(args):

FILE: model_cards/lama/bin/filter_sharded_dataset.py
  function is_good_key (line 13) | def is_good_key(key, cats):
  function main (line 17) | def main(args):

FILE: model_cards/lama/bin/gen_debug_mask_dataset.py
  function generate_masks_for_img (line 16) | def generate_masks_for_img(infile, outmask_pattern, mask_size=200, step=...
  function main (line 34) | def main(args):

FILE: model_cards/lama/bin/gen_mask_dataset.py
  class MakeManyMasksWrapper (line 17) | class MakeManyMasksWrapper:
    method __init__ (line 18) | def __init__(self, impl, variants_n=2):
    method get_masks (line 22) | def get_masks(self, img):
  function process_images (line 27) | def process_images(src_images, indir, outdir, config):
  function main (line 100) | def main(args):

FILE: model_cards/lama/bin/gen_mask_dataset_hydra.py
  class MakeManyMasksWrapper (line 19) | class MakeManyMasksWrapper:
    method __init__ (line 20) | def __init__(self, impl, variants_n=2):
    method get_masks (line 24) | def get_masks(self, img):
  function process_images (line 29) | def process_images(src_images, indir, outdir, config):
  function main (line 104) | def main(config: OmegaConf):

FILE: model_cards/lama/bin/gen_outpainting_dataset.py
  function main (line 34) | def main(args):

FILE: model_cards/lama/bin/make_checkpoint.py
  function get_checkpoint_files (line 9) | def get_checkpoint_files(s):
  function main (line 16) | def main(args):

FILE: model_cards/lama/bin/paper_runfiles/find_best_checkpoint.py
  function ssim_fid100_f1 (line 8) | def ssim_fid100_f1(metrics, fid_scale=100):
  function find_best_checkpoint (line 16) | def find_best_checkpoint(model_list, models_dir):

FILE: model_cards/lama/bin/predict.py
  function main (line 39) | def main(predict_config: OmegaConf):

FILE: model_cards/lama/bin/predict_inner_features.py
  function main (line 39) | def main(predict_config: OmegaConf):

FILE: model_cards/lama/bin/report_from_tb.py
  function need_drop (line 21) | def need_drop(tag):
  function get_group_and_title (line 28) | def get_group_and_title(tag):
  function main (line 37) | def main(args):

FILE: model_cards/lama/bin/sample_from_dataset.py
  function save_mask_for_sidebyside (line 13) | def save_mask_for_sidebyside(item, out_file):
  function save_img_for_sidebyside (line 20) | def save_img_for_sidebyside(item, out_file):
  function save_masked_img_for_sidebyside (line 25) | def save_masked_img_for_sidebyside(item, out_file):
  function main (line 35) | def main(args):

FILE: model_cards/lama/bin/side_by_side.py
  function main (line 13) | def main(args):

FILE: model_cards/lama/bin/split_tar.py
  function main (line 8) | def main(args):

FILE: model_cards/lama/bin/to_jit.py
  class JITWrapper (line 14) | class JITWrapper(nn.Module):
    method __init__ (line 15) | def __init__(self, model):
    method forward (line 19) | def forward(self, image, mask):
  function main (line 29) | def main(predict_config: OmegaConf):

FILE: model_cards/lama/bin/train.py
  function main (line 30) | def main(config: OmegaConf):

FILE: model_cards/lama/models/ade20k/base.py
  class NormalizeTensor (line 25) | class NormalizeTensor:
    method __init__ (line 26) | def __init__(self, mean, std, inplace=False):
    method __call__ (line 44) | def __call__(self, tensor):
  class ModelBuilder (line 56) | class ModelBuilder:
    method weights_init (line 59) | def weights_init(m):
    method build_encoder (line 68) | def build_encoder(arch='resnet50dilated', fc_dim=512, weights=''):
    method build_decoder (line 98) | def build_decoder(arch='ppm_deepsup',
    method get_decoder (line 125) | def get_decoder(weights_path, arch_encoder, arch_decoder, fc_dim, drop...
    method get_encoder (line 130) | def get_encoder(weights_path, arch_encoder, arch_decoder, fc_dim, segm...
  function conv3x3_bn_relu (line 139) | def conv3x3_bn_relu(in_planes, out_planes, stride=1):
  class SegmentationModule (line 147) | class SegmentationModule(nn.Module):
    method __init__ (line 148) | def __init__(self,
    method normalize_input (line 194) | def normalize_input(self, tensor):
    method feature_maps_channels (line 200) | def feature_maps_channels(self):
    method forward (line 203) | def forward(self, img_data, segSize=None):
    method multi_mask_from_multiclass (line 215) | def multi_mask_from_multiclass(self, pred, classes):
    method multi_mask_from_multiclass_probs (line 221) | def multi_mask_from_multiclass_probs(scores, classes):
    method predict (line 230) | def predict(self, tensor, imgSizes=(-1,),  # (300, 375, 450, 525, 600)
    method get_edges (line 277) | def get_edges(self, t):
  class PPMDeepsup (line 290) | class PPMDeepsup(nn.Module):
    method __init__ (line 291) | def __init__(self, num_class=NUM_CLASS, fc_dim=4096,
    method forward (line 320) | def forward(self, conv_out, segSize=None):
  class Resnet (line 355) | class Resnet(nn.Module):
    method __init__ (line 356) | def __init__(self, orig_resnet):
    method forward (line 375) | def forward(self, x, return_feature_maps=False):
  class ResnetDilated (line 393) | class ResnetDilated(nn.Module):
    method __init__ (line 394) | def __init__(self, orig_resnet, dilate_scale=8):
    method _nostride_dilate (line 423) | def _nostride_dilate(self, m, dilate):
    method forward (line 438) | def forward(self, x, return_feature_maps=False):
  class MobileNetV2Dilated (line 459) | class MobileNetV2Dilated(nn.Module):
    method __init__ (line 460) | def __init__(self, orig_net, dilate_scale=8):
    method _nostride_dilate (line 485) | def _nostride_dilate(self, m, dilate):
    method forward (line 500) | def forward(self, x, return_feature_maps=False):
  class C1DeepSup (line 515) | class C1DeepSup(nn.Module):
    method __init__ (line 516) | def __init__(self, num_class=150, fc_dim=2048, use_softmax=False, drop...
    method forward (line 528) | def forward(self, conv_out, segSize=None):
  class C1 (line 556) | class C1(nn.Module):
    method __init__ (line 557) | def __init__(self, num_class=150, fc_dim=2048, use_softmax=False):
    method forward (line 566) | def forward(self, conv_out, segSize=None):
  class PPM (line 582) | class PPM(nn.Module):
    method __init__ (line 583) | def __init__(self, num_class=150, fc_dim=4096,
    method forward (line 607) | def forward(self, conv_out, segSize=None):

FILE: model_cards/lama/models/ade20k/mobilenet.py
  function conv_bn (line 22) | def conv_bn(inp, oup, stride):
  function conv_1x1_bn (line 30) | def conv_1x1_bn(inp, oup):
  class InvertedResidual (line 38) | class InvertedResidual(nn.Module):
    method __init__ (line 39) | def __init__(self, inp, oup, stride, expand_ratio):
    method forward (line 72) | def forward(self, x):
  class MobileNetV2 (line 79) | class MobileNetV2(nn.Module):
    method __init__ (line 80) | def __init__(self, n_class=1000, input_size=224, width_mult=1.):
    method forward (line 123) | def forward(self, x):
    method _initialize_weights (line 129) | def _initialize_weights(self):
  function mobilenetv2 (line 145) | def mobilenetv2(pretrained=False, **kwargs):

FILE: model_cards/lama/models/ade20k/resnet.py
  function conv3x3 (line 18) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 24) | class BasicBlock(nn.Module):
    method __init__ (line 27) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 37) | def forward(self, x):
  class Bottleneck (line 56) | class Bottleneck(nn.Module):
    method __init__ (line 59) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 72) | def forward(self, x):
  class ResNet (line 95) | class ResNet(nn.Module):
    method __init__ (line 97) | def __init__(self, block, layers, num_classes=1000):
    method _make_layer (line 126) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 143) | def forward(self, x):
  function resnet50 (line 161) | def resnet50(pretrained=False, **kwargs):
  function resnet18 (line 173) | def resnet18(pretrained=False, **kwargs):

FILE: model_cards/lama/models/ade20k/segm_lib/nn/modules/batchnorm.py
  function _sum_ft (line 24) | def _sum_ft(tensor):
  function _unsqueeze_ft (line 29) | def _unsqueeze_ft(tensor):
  class _SynchronizedBatchNorm (line 38) | class _SynchronizedBatchNorm(_BatchNorm):
    method __init__ (line 39) | def __init__(self, num_features, eps=1e-5, momentum=0.001, affine=True):
    method forward (line 56) | def forward(self, input):
    method __data_parallel_replicate__ (line 88) | def __data_parallel_replicate__(self, ctx, copy_id):
    method _data_parallel_master (line 98) | def _data_parallel_master(self, intermediates):
    method _add_weighted (line 119) | def _add_weighted(self, dest, delta, alpha=1, beta=1, bias=0):
    method _compute_mean_std (line 123) | def _compute_mean_std(self, sum_, ssum, size):
  class SynchronizedBatchNorm1d (line 142) | class SynchronizedBatchNorm1d(_SynchronizedBatchNorm):
    method _check_input_dim (line 198) | def _check_input_dim(self, input):
  class SynchronizedBatchNorm2d (line 205) | class SynchronizedBatchNorm2d(_SynchronizedBatchNorm):
    method _check_input_dim (line 261) | def _check_input_dim(self, input):
  class SynchronizedBatchNorm3d (line 268) | class SynchronizedBatchNorm3d(_SynchronizedBatchNorm):
    method _check_input_dim (line 325) | def _check_input_dim(self, input):

FILE: model_cards/lama/models/ade20k/segm_lib/nn/modules/comm.py
  class FutureResult (line 18) | class FutureResult(object):
    method __init__ (line 21) | def __init__(self):
    method put (line 26) | def put(self, result):
    method get (line 32) | def get(self):
  class SlavePipe (line 46) | class SlavePipe(_SlavePipeBase):
    method run_slave (line 49) | def run_slave(self, msg):
  class SyncMaster (line 56) | class SyncMaster(object):
    method __init__ (line 67) | def __init__(self, master_callback):
    method register_slave (line 78) | def register_slave(self, identifier):
    method run_master (line 96) | def run_master(self, master_msg):
    method nr_slaves (line 130) | def nr_slaves(self):

FILE: model_cards/lama/models/ade20k/segm_lib/nn/modules/replicate.py
  class CallbackContext (line 23) | class CallbackContext(object):
  function execute_replication_callbacks (line 27) | def execute_replication_callbacks(modules):
  class DataParallelWithCallback (line 50) | class DataParallelWithCallback(DataParallel):
    method replicate (line 64) | def replicate(self, module, device_ids):
  function patch_replication_callback (line 70) | def patch_replication_callback(data_parallel):

FILE: model_cards/lama/models/ade20k/segm_lib/nn/modules/tests/test_numeric_batchnorm.py
  function handy_var (line 18) | def handy_var(a, unbias=True):
  class NumericTestCase (line 29) | class NumericTestCase(TorchTestCase):
    method testNumericBatchNorm (line 30) | def testNumericBatchNorm(self):

FILE: model_cards/lama/models/ade20k/segm_lib/nn/modules/tests/test_sync_batchnorm.py
  function handy_var (line 19) | def handy_var(a, unbias=True):
  function _find_bn (line 30) | def _find_bn(module):
  class SyncTestCase (line 36) | class SyncTestCase(TorchTestCase):
    method _syncParameters (line 37) | def _syncParameters(self, bn1, bn2):
    method _checkBatchNormResult (line 44) | def _checkBatchNormResult(self, bn1, bn2, input, is_train, cuda=False):
    method testSyncBatchNormNormalTrain (line 67) | def testSyncBatchNormNormalTrain(self):
    method testSyncBatchNormNormalEval (line 73) | def testSyncBatchNormNormalEval(self):
    method testSyncBatchNormSyncTrain (line 79) | def testSyncBatchNormSyncTrain(self):
    method testSyncBatchNormSyncEval (line 89) | def testSyncBatchNormSyncEval(self):
    method testSyncBatchNorm2DSyncTrain (line 99) | def testSyncBatchNorm2DSyncTrain(self):

FILE: model_cards/lama/models/ade20k/segm_lib/nn/modules/unittest.py
  function as_numpy (line 17) | def as_numpy(v):
  class TorchTestCase (line 23) | class TorchTestCase(unittest.TestCase):
    method assertTensorClose (line 24) | def assertTensorClose(self, a, b, atol=1e-3, rtol=1e-3):

FILE: model_cards/lama/models/ade20k/segm_lib/nn/parallel/data_parallel.py
  function async_copy_to (line 13) | def async_copy_to(obj, dev, main_stream=None):
  function dict_gather (line 27) | def dict_gather(outputs, target_device, dim=0):
  class DictGatherDataParallel (line 48) | class DictGatherDataParallel(nn.DataParallel):
    method gather (line 49) | def gather(self, outputs, output_device):
  class UserScatteredDataParallel (line 53) | class UserScatteredDataParallel(DictGatherDataParallel):
    method scatter (line 54) | def scatter(self, inputs, kwargs, device_ids):
  function user_scattered_collate (line 65) | def user_scattered_collate(batch):
  function _async_copy (line 69) | def _async_copy(inputs, device_ids):
  function _async_copy_stream (line 82) | def _async_copy_stream(inputs, device_ids):
  function _get_stream (line 104) | def _get_stream(device):

FILE: model_cards/lama/models/ade20k/segm_lib/utils/data/dataloader.py
  class ExceptionWrapper (line 25) | class ExceptionWrapper(object):
    method __init__ (line 28) | def __init__(self, exc_info):
  function _worker_loop (line 37) | def _worker_loop(dataset, index_queue, data_queue, collate_fn, seed, ini...
  function _worker_manager_loop (line 67) | def _worker_manager_loop(in_queue, out_queue, done_event, pin_memory, de...
  function default_collate (line 104) | def default_collate(batch):
  function pin_memory_batch (line 145) | def pin_memory_batch(batch):
  function _set_SIGCHLD_handler (line 163) | def _set_SIGCHLD_handler():
  class DataLoaderIter (line 188) | class DataLoaderIter(object):
    method __init__ (line 191) | def __init__(self, loader):
    method __len__ (line 249) | def __len__(self):
    method _get_batch (line 252) | def _get_batch(self):
    method __next__ (line 261) | def __next__(self):
    method __iter__ (line 290) | def __iter__(self):
    method _put_indices (line 293) | def _put_indices(self):
    method _process_next_batch (line 302) | def _process_next_batch(self, batch):
    method __getstate__ (line 309) | def __getstate__(self):
    method _shutdown_workers (line 317) | def _shutdown_workers(self):
    method __del__ (line 336) | def __del__(self):
  class DataLoader (line 341) | class DataLoader(object):
    method __init__ (line 383) | def __init__(self, dataset, batch_size=1, shuffle=False, sampler=None,...
    method __iter__ (line 421) | def __iter__(self):
    method __len__ (line 424) | def __len__(self):

FILE: model_cards/lama/models/ade20k/segm_lib/utils/data/dataset.py
  class Dataset (line 8) | class Dataset(object):
    method __getitem__ (line 16) | def __getitem__(self, index):
    method __len__ (line 19) | def __len__(self):
    method __add__ (line 22) | def __add__(self, other):
  class TensorDataset (line 26) | class TensorDataset(Dataset):
    method __init__ (line 37) | def __init__(self, data_tensor, target_tensor):
    method __getitem__ (line 42) | def __getitem__(self, index):
    method __len__ (line 45) | def __len__(self):
  class ConcatDataset (line 49) | class ConcatDataset(Dataset):
    method cumsum (line 61) | def cumsum(sequence):
    method __init__ (line 69) | def __init__(self, datasets):
    method __len__ (line 75) | def __len__(self):
    method __getitem__ (line 78) | def __getitem__(self, idx):
    method cummulative_sizes (line 87) | def cummulative_sizes(self):
  class Subset (line 93) | class Subset(Dataset):
    method __init__ (line 94) | def __init__(self, dataset, indices):
    method __getitem__ (line 98) | def __getitem__(self, idx):
    method __len__ (line 101) | def __len__(self):
  function random_split (line 105) | def random_split(dataset, lengths):

FILE: model_cards/lama/models/ade20k/segm_lib/utils/data/distributed.py
  class DistributedSampler (line 7) | class DistributedSampler(Sampler):
    method __init__ (line 25) | def __init__(self, dataset, num_replicas=None, rank=None):
    method __iter__ (line 37) | def __iter__(self):
    method __len__ (line 54) | def __len__(self):
    method set_epoch (line 57) | def set_epoch(self, epoch):

FILE: model_cards/lama/models/ade20k/segm_lib/utils/data/sampler.py
  class Sampler (line 4) | class Sampler(object):
    method __init__ (line 12) | def __init__(self, data_source):
    method __iter__ (line 15) | def __iter__(self):
    method __len__ (line 18) | def __len__(self):
  class SequentialSampler (line 22) | class SequentialSampler(Sampler):
    method __init__ (line 29) | def __init__(self, data_source):
    method __iter__ (line 32) | def __iter__(self):
    method __len__ (line 35) | def __len__(self):
  class RandomSampler (line 39) | class RandomSampler(Sampler):
    method __init__ (line 46) | def __init__(self, data_source):
    method __iter__ (line 49) | def __iter__(self):
    method __len__ (line 52) | def __len__(self):
  class SubsetRandomSampler (line 56) | class SubsetRandomSampler(Sampler):
    method __init__ (line 63) | def __init__(self, indices):
    method __iter__ (line 66) | def __iter__(self):
    method __len__ (line 69) | def __len__(self):
  class WeightedRandomSampler (line 73) | class WeightedRandomSampler(Sampler):
    method __init__ (line 84) | def __init__(self, weights, num_samples, replacement=True):
    method __iter__ (line 89) | def __iter__(self):
    method __len__ (line 92) | def __len__(self):
  class BatchSampler (line 96) | class BatchSampler(object):
    method __init__ (line 112) | def __init__(self, sampler, batch_size, drop_last):
    method __iter__ (line 117) | def __iter__(self):
    method __len__ (line 127) | def __len__(self):

FILE: model_cards/lama/models/ade20k/segm_lib/utils/th.py
  function as_variable (line 8) | def as_variable(obj):
  function as_numpy (line 18) | def as_numpy(obj):
  function mark_volatile (line 30) | def mark_volatile(obj):

FILE: model_cards/lama/models/ade20k/utils.py
  function load_url (line 15) | def load_url(url, model_dir='./pretrained', map_location=None):
  function color_encode (line 26) | def color_encode(labelmap, colors, mode='RGB'):

FILE: model_cards/lama/saicinpainting/evaluation/__init__.py
  function make_evaluator (line 9) | def make_evaluator(kind='default', ssim=True, lpips=True, fid=True, inte...

FILE: model_cards/lama/saicinpainting/evaluation/data.py
  function load_image (line 12) | def load_image(fname, mode='RGB', return_orig=False):
  function ceil_modulo (line 23) | def ceil_modulo(x, mod):
  function pad_img_to_modulo (line 29) | def pad_img_to_modulo(img, mod):
  function pad_tensor_to_modulo (line 36) | def pad_tensor_to_modulo(img, mod):
  function scale_image (line 43) | def scale_image(img, factor, interpolation=cv2.INTER_AREA):
  class InpaintingDataset (line 58) | class InpaintingDataset(Dataset):
    method __init__ (line 59) | def __init__(self, datadir, img_suffix='.jpg', pad_out_to_modulo=None,...
    method __len__ (line 66) | def __len__(self):
    method __getitem__ (line 69) | def __getitem__(self, i):
  class OurInpaintingDataset (line 85) | class OurInpaintingDataset(Dataset):
    method __init__ (line 86) | def __init__(self, datadir, img_suffix='.jpg', pad_out_to_modulo=None,...
    method __len__ (line 93) | def __len__(self):
    method __getitem__ (line 96) | def __getitem__(self, i):
  class PrecomputedInpaintingResultsDataset (line 110) | class PrecomputedInpaintingResultsDataset(InpaintingDataset):
    method __init__ (line 111) | def __init__(self, datadir, predictdir, inpainted_suffix='_inpainted.j...
    method __getitem__ (line 119) | def __getitem__(self, i):
  class OurPrecomputedInpaintingResultsDataset (line 126) | class OurPrecomputedInpaintingResultsDataset(OurInpaintingDataset):
    method __init__ (line 127) | def __init__(self, datadir, predictdir, inpainted_suffix="png", **kwar...
    method __getitem__ (line 137) | def __getitem__(self, i):
  class InpaintingEvalOnlineDataset (line 145) | class InpaintingEvalOnlineDataset(Dataset):
    method __init__ (line 146) | def __init__(self, indir, mask_generator, img_suffix='.jpg', pad_out_t...
    method __len__ (line 153) | def __len__(self):
    method __getitem__ (line 156) | def __getitem__(self, i):

FILE: model_cards/lama/saicinpainting/evaluation/evaluator.py
  class InpaintingEvaluator (line 16) | class InpaintingEvaluator():
    method __init__ (line 17) | def __init__(self, dataset, scores, area_grouping=True, bins=10, batch...
    method _get_bin_edges (line 42) | def _get_bin_edges(self):
    method evaluate (line 67) | def evaluate(self, model=None):
  function ssim_fid100_f1 (line 112) | def ssim_fid100_f1(metrics, fid_scale=100):
  function lpips_fid100_f1 (line 120) | def lpips_fid100_f1(metrics, fid_scale=100):
  class InpaintingEvaluatorOnline (line 129) | class InpaintingEvaluatorOnline(nn.Module):
    method __init__ (line 130) | def __init__(self, scores, bins=10, image_key='image', inpainted_key='...
    method _get_bins (line 162) | def _get_bins(self, mask_batch):
    method forward (line 168) | def forward(self, batch: Dict[str, torch.Tensor]):
    method process_batch (line 186) | def process_batch(self, batch: Dict[str, torch.Tensor]):
    method evaluation_end (line 189) | def evaluation_end(self, states=None):

FILE: model_cards/lama/saicinpainting/evaluation/losses/base_loss.py
  function get_groupings (line 21) | def get_groupings(groups):
  class EvaluatorScore (line 40) | class EvaluatorScore(nn.Module):
    method forward (line 42) | def forward(self, pred_batch, target_batch, mask):
    method get_value (line 46) | def get_value(self, groups=None, states=None):
    method reset (line 50) | def reset(self):
  class PairwiseScore (line 54) | class PairwiseScore(EvaluatorScore, ABC):
    method __init__ (line 55) | def __init__(self):
    method get_value (line 59) | def get_value(self, groups=None, states=None):
    method reset (line 88) | def reset(self):
  class SSIMScore (line 92) | class SSIMScore(PairwiseScore):
    method __init__ (line 93) | def __init__(self, window_size=11):
    method forward (line 98) | def forward(self, pred_batch, target_batch, mask=None):
  class LPIPSScore (line 106) | class LPIPSScore(PairwiseScore):
    method __init__ (line 107) | def __init__(self, model='net-lin', net='vgg', model_path=None, use_gp...
    method forward (line 113) | def forward(self, pred_batch, target_batch, mask=None):
  function fid_calculate_activation_statistics (line 121) | def fid_calculate_activation_statistics(act):
  function calculate_frechet_distance (line 127) | def calculate_frechet_distance(activations_pred, activations_target, eps...
  class FIDScore (line 156) | class FIDScore(EvaluatorScore):
    method __init__ (line 157) | def __init__(self, dims=2048, eps=1e-6):
    method forward (line 168) | def forward(self, pred_batch, target_batch, mask=None):
    method get_value (line 177) | def get_value(self, groups=None, states=None):
    method reset (line 207) | def reset(self):
    method _get_activations (line 211) | def _get_activations(self, batch):
  class SegmentationAwareScore (line 221) | class SegmentationAwareScore(EvaluatorScore):
    method __init__ (line 222) | def __init__(self, weights_path):
    method forward (line 229) | def forward(self, pred_batch, target_batch, mask):
    method reset (line 256) | def reset(self):
  function distribute_values_to_classes (line 263) | def distribute_values_to_classes(target_class_freq_by_image_mask, values...
  function get_segmentation_idx2name (line 271) | def get_segmentation_idx2name():
  class SegmentationAwarePairwiseScore (line 275) | class SegmentationAwarePairwiseScore(SegmentationAwareScore):
    method __init__ (line 276) | def __init__(self, *args, **kwargs):
    method forward (line 281) | def forward(self, pred_batch, target_batch, mask):
    method calc_score (line 288) | def calc_score(self, pred_batch, target_batch, mask):
    method get_value (line 291) | def get_value(self, groups=None, states=None):
    method reset (line 336) | def reset(self):
  class SegmentationClassStats (line 341) | class SegmentationClassStats(SegmentationAwarePairwiseScore):
    method calc_score (line 342) | def calc_score(self, pred_batch, target_batch, mask):
    method get_value (line 345) | def get_value(self, groups=None, states=None):
  class SegmentationAwareSSIM (line 420) | class SegmentationAwareSSIM(SegmentationAwarePairwiseScore):
    method __init__ (line 421) | def __init__(self, *args, window_size=11, **kwargs):
    method calc_score (line 425) | def calc_score(self, pred_batch, target_batch, mask):
  class SegmentationAwareLPIPS (line 429) | class SegmentationAwareLPIPS(SegmentationAwarePairwiseScore):
    method __init__ (line 430) | def __init__(self, *args, model='net-lin', net='vgg', model_path=None,...
    method calc_score (line 435) | def calc_score(self, pred_batch, target_batch, mask):
  function calculade_fid_no_img (line 439) | def calculade_fid_no_img(img_i, activations_pred, activations_target, ep...
  class SegmentationAwareFID (line 445) | class SegmentationAwareFID(SegmentationAwarePairwiseScore):
    method __init__ (line 446) | def __init__(self, *args, dims=2048, eps=1e-6, n_jobs=-1, **kwargs):
    method calc_score (line 455) | def calc_score(self, pred_batch, target_batch, mask):
    method get_value (line 460) | def get_value(self, groups=None, states=None):
    method distribute_fid_to_classes (line 513) | def distribute_fid_to_classes(self, class_freq, activations_pred, acti...
    method _get_activations (line 523) | def _get_activations(self, batch):

FILE: model_cards/lama/saicinpainting/evaluation/losses/fid/fid_score.py
  function tqdm (line 52) | def tqdm(x): return x
  function get_activations (line 76) | def get_activations(files, model, batch_size=50, dims=2048,
  function calculate_frechet_distance (line 160) | def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6):
  function calculate_activation_statistics (line 218) | def calculate_activation_statistics(files, model, batch_size=50,
  function _compute_statistics_of_path (line 243) | def _compute_statistics_of_path(path, model, batch_size, dims, cuda):
  function _compute_statistics_of_images (line 257) | def _compute_statistics_of_images(images, model, batch_size, dims, cuda,...
  function calculate_fid_given_paths (line 268) | def calculate_fid_given_paths(paths, batch_size, cuda, dims):
  function calculate_fid_given_images (line 289) | def calculate_fid_given_images(images, batch_size, cuda, dims, use_globa...

FILE: model_cards/lama/saicinpainting/evaluation/losses/fid/inception.py
  class InceptionV3 (line 21) | class InceptionV3(nn.Module):
    method __init__ (line 36) | def __init__(self,
    method forward (line 134) | def forward(self, inp):
  function fid_inception_v3 (line 171) | def fid_inception_v3():
  class FIDInceptionA (line 206) | class FIDInceptionA(models.inception.InceptionA):
    method __init__ (line 208) | def __init__(self, in_channels, pool_features):
    method forward (line 211) | def forward(self, x):
  class FIDInceptionC (line 231) | class FIDInceptionC(models.inception.InceptionC):
    method __init__ (line 233) | def __init__(self, in_channels, channels_7x7):
    method forward (line 236) | def forward(self, x):
  class FIDInceptionE_1 (line 259) | class FIDInceptionE_1(models.inception.InceptionE):
    method __init__ (line 261) | def __init__(self, in_channels):
    method forward (line 264) | def forward(self, x):
  class FIDInceptionE_2 (line 292) | class FIDInceptionE_2(models.inception.InceptionE):
    method __init__ (line 294) | def __init__(self, in_channels):
    method forward (line 297) | def forward(self, x):

FILE: model_cards/lama/saicinpainting/evaluation/losses/lpips.py
  class PerceptualLoss (line 18) | class PerceptualLoss(torch.nn.Module):
    method __init__ (line 19) | def __init__(self, model='net-lin', net='alex', colorspace='rgb', mode...
    method forward (line 29) | def forward(self, pred, target, normalize=True):
  function normalize_tensor (line 45) | def normalize_tensor(in_feat, eps=1e-10):
  function l2 (line 50) | def l2(p0, p1, range=255.):
  function psnr (line 54) | def psnr(p0, p1, peak=255.):
  function dssim (line 58) | def dssim(p0, p1, range=255.):
  function rgb2lab (line 62) | def rgb2lab(in_img, mean_cent=False):
  function tensor2np (line 70) | def tensor2np(tensor_obj):
  function np2tensor (line 75) | def np2tensor(np_obj):
  function tensor2tensorlab (line 80) | def tensor2tensorlab(image_tensor, to_norm=True, mc_only=False):
  function tensorlab2tensor (line 95) | def tensorlab2tensor(lab_tensor, return_inbnd=False):
  function rgb2lab (line 114) | def rgb2lab(input):
  function tensor2im (line 119) | def tensor2im(image_tensor, imtype=np.uint8, cent=1., factor=255. / 2.):
  function im2tensor (line 125) | def im2tensor(image, imtype=np.uint8, cent=1., factor=255. / 2.):
  function tensor2vec (line 130) | def tensor2vec(vector_tensor):
  function voc_ap (line 134) | def voc_ap(rec, prec, use_07_metric=False):
  function tensor2im (line 168) | def tensor2im(image_tensor, imtype=np.uint8, cent=1., factor=255. / 2.):
  function im2tensor (line 175) | def im2tensor(image, imtype=np.uint8, cent=1., factor=255. / 2.):
  class BaseModel (line 186) | class BaseModel(torch.nn.Module):
    method __init__ (line 187) | def __init__(self):
    method name (line 190) | def name(self):
    method initialize (line 193) | def initialize(self, use_gpu=True):
    method forward (line 196) | def forward(self):
    method get_image_paths (line 199) | def get_image_paths(self):
    method optimize_parameters (line 202) | def optimize_parameters(self):
    method get_current_visuals (line 205) | def get_current_visuals(self):
    method get_current_errors (line 208) | def get_current_errors(self):
    method save (line 211) | def save(self, label):
    method save_network (line 215) | def save_network(self, network, path, network_label, epoch_label):
    method load_network (line 221) | def load_network(self, network, network_label, epoch_label):
    method update_learning_rate (line 227) | def update_learning_rate():
    method get_image_paths (line 230) | def get_image_paths(self):
    method save_done (line 233) | def save_done(self, flag=False):
  class DistModel (line 248) | class DistModel(BaseModel):
    method name (line 249) | def name(self):
    method initialize (line 252) | def initialize(self, model='net-lin', net='alex', colorspace='Lab', pn...
    method forward (line 330) | def forward(self, in0, in1, retPerLayer=False):
    method optimize_parameters (line 341) | def optimize_parameters(self):
    method clamp_weights (line 348) | def clamp_weights(self):
    method set_input (line 353) | def set_input(self, data):
    method forward_train (line 369) | def forward_train(self):  # run forward pass
    method backward_train (line 385) | def backward_train(self):
    method compute_accuracy (line 388) | def compute_accuracy(self, d0, d1, judge):
    method get_current_errors (line 394) | def get_current_errors(self):
    method get_current_visuals (line 403) | def get_current_visuals(self):
    method save (line 418) | def save(self, path, label):
    method update_learning_rate (line 425) | def update_learning_rate(self, nepoch_decay):
  function score_2afc_dataset (line 436) | def score_2afc_dataset(data_loader, func, name=''):
  function score_jnd_dataset (line 472) | def score_jnd_dataset(data_loader, func, name=''):
  function spatial_average (line 521) | def spatial_average(in_tens, keepdim=True):
  function upsample (line 525) | def upsample(in_tens, out_H=64):  # assumes scale factor is same for H a...
  class PNetLin (line 533) | class PNetLin(nn.Module):
    method __init__ (line 534) | def __init__(self, pnet_type='vgg', pnet_rand=False, pnet_tune=False, ...
    method forward (line 571) | def forward(self, in0, in1, retPerLayer=False):
  class ScalingLayer (line 603) | class ScalingLayer(nn.Module):
    method __init__ (line 604) | def __init__(self):
    method forward (line 609) | def forward(self, inp):
  class NetLinLayer (line 613) | class NetLinLayer(nn.Module):
    method __init__ (line 616) | def __init__(self, chn_in, chn_out=1, use_dropout=False):
  class Dist2LogitLayer (line 624) | class Dist2LogitLayer(nn.Module):
    method __init__ (line 627) | def __init__(self, chn_mid=32, use_sigmoid=True):
    method forward (line 639) | def forward(self, d0, d1, eps=0.1):
  class BCERankingLoss (line 643) | class BCERankingLoss(nn.Module):
    method __init__ (line 644) | def __init__(self, chn_mid=32):
    method forward (line 650) | def forward(self, d0, d1, judge):
  class FakeNet (line 657) | class FakeNet(nn.Module):
    method __init__ (line 658) | def __init__(self, use_gpu=True, colorspace='Lab'):
  class L2 (line 664) | class L2(FakeNet):
    method forward (line 666) | def forward(self, in0, in1, retPerLayer=None):
  class DSSIM (line 683) | class DSSIM(FakeNet):
    method forward (line 685) | def forward(self, in0, in1, retPerLayer=None):
  function print_network (line 699) | def print_network(net):
  class squeezenet (line 716) | class squeezenet(torch.nn.Module):
    method __init__ (line 717) | def __init__(self, requires_grad=False, pretrained=True):
    method forward (line 746) | def forward(self, X):
  class alexnet (line 767) | class alexnet(torch.nn.Module):
    method __init__ (line 768) | def __init__(self, requires_grad=False, pretrained=True):
    method forward (line 791) | def forward(self, X):
  class vgg16 (line 808) | class vgg16(torch.nn.Module):
    method __init__ (line 809) | def __init__(self, requires_grad=False, pretrained=True):
    method forward (line 832) | def forward(self, X):
  class resnet (line 849) | class resnet(torch.nn.Module):
    method __init__ (line 850) | def __init__(self, requires_grad=False, pretrained=True, num=18):
    method forward (line 873) | def forward(self, X):

FILE: model_cards/lama/saicinpainting/evaluation/losses/ssim.py
  class SSIM (line 6) | class SSIM(torch.nn.Module):
    method __init__ (line 11) | def __init__(self, window_size=11, size_average=True):
    method forward (line 18) | def forward(self, img1, img2):
    method _gaussian (line 36) | def _gaussian(self, window_size, sigma):
    method _create_window (line 42) | def _create_window(self, window_size, channel):
    method _ssim (line 47) | def _ssim(self, img1, img2, window, window_size, channel, size_average...
    method _load_from_state_dict (line 73) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...

FILE: model_cards/lama/saicinpainting/evaluation/masks/countless/countless2d.py
  function simplest_countless (line 25) | def simplest_countless(data):
  function quick_countless (line 52) | def quick_countless(data):
  function quickest_countless (line 77) | def quickest_countless(data):
  function quick_countless_xor (line 100) | def quick_countless_xor(data):
  function stippled_countless (line 124) | def stippled_countless(data):
  function zero_corrected_countless (line 151) | def zero_corrected_countless(data):
  function countless_extreme (line 195) | def countless_extreme(data):
  function countless (line 212) | def countless(data):
  function upgrade_type (line 252) | def upgrade_type(arr):
  function downgrade_type (line 264) | def downgrade_type(arr):
  function odd_to_even (line 276) | def odd_to_even(image):
  function counting (line 310) | def counting(array):
  function ndzoom (line 340) | def ndzoom(array):
  function countless_if (line 347) | def countless_if(array):
  function downsample_with_averaging (line 376) | def downsample_with_averaging(array):
  function downsample_with_max_pooling (line 401) | def downsample_with_max_pooling(array):
  function striding (line 421) | def striding(array):
  function benchmark (line 431) | def benchmark():

FILE: model_cards/lama/saicinpainting/evaluation/masks/countless/countless3d.py
  function countless5 (line 17) | def countless5(a,b,c,d,e):
  function countless8 (line 50) | def countless8(a,b,c,d,e,f,g,h):
  function dynamic_countless3d (line 74) | def dynamic_countless3d(data):
  function countless3d (line 133) | def countless3d(data):
  function countless_generalized (line 169) | def countless_generalized(data, factor):
  function dynamic_countless_generalized (line 209) | def dynamic_countless_generalized(data, factor):
  function downsample_with_averaging (line 261) | def downsample_with_averaging(array):
  function downsample_with_max_pooling (line 282) | def downsample_with_max_pooling(array):
  function striding (line 299) | def striding(array):
  function benchmark (line 309) | def benchmark():

FILE: model_cards/lama/saicinpainting/evaluation/masks/countless/test.py
  function test_countless2d (line 8) | def test_countless2d():
  function test_stippled_countless2d (line 55) | def test_stippled_countless2d():
  function test_countless3d (line 113) | def test_countless3d():

FILE: model_cards/lama/saicinpainting/evaluation/masks/mask.py
  class ObjectMask (line 19) | class ObjectMask():
    method __init__ (line 20) | def __init__(self, mask):
    method _get_limits (line 26) | def _get_limits(mask):
    method _clean (line 40) | def _clean(self):
    method horizontal_flip (line 44) | def horizontal_flip(self, inplace=False):
    method vertical_flip (line 52) | def vertical_flip(self, inplace=False):
    method image_center (line 60) | def image_center(self):
    method rescale (line 65) | def rescale(self, scaling_factor, inplace=False):
    method crop_to_canvas (line 82) | def crop_to_canvas(self, vertical=True, horizontal=True, inplace=False):
    method restore_full_mask (line 114) | def restore_full_mask(self, allow_crop=False):
    method shift (line 120) | def shift(self, vertical=0, horizontal=0, inplace=False):
    method area (line 131) | def area(self):
  class RigidnessMode (line 135) | class RigidnessMode(enum.Enum):
  class SegmentationMask (line 140) | class SegmentationMask:
    method __init__ (line 141) | def __init__(self, confidence_threshold=0.5, rigidness_mode=RigidnessM...
    method get_segmentation (line 191) | def get_segmentation(self, img):
    method _is_power_of_two (line 197) | def _is_power_of_two(n):
    method identify_candidates (line 200) | def identify_candidates(self, panoptic_seg, segments_info):
    method downsample_mask (line 212) | def downsample_mask(self, mask):
    method _augmentation_params (line 230) | def _augmentation_params(self):
    method _get_intersection (line 244) | def _get_intersection(self, mask_array, mask_object):
    method _check_masks_intersection (line 250) | def _check_masks_intersection(self, aug_mask, total_mask_area, prev_ma...
    method _check_foreground_intersection (line 260) | def _check_foreground_intersection(self, aug_mask, foreground):
    method _move_mask (line 271) | def _move_mask(self, mask, foreground):
    method _prepare_mask (line 351) | def _prepare_mask(self, mask):
    method get_masks (line 358) | def get_masks(self, im, return_panoptic=False):
  function propose_random_square_crop (line 410) | def propose_random_square_crop(mask, min_overlap=0.5):

FILE: model_cards/lama/saicinpainting/evaluation/refinement.py
  function _pyrdown (line 19) | def _pyrdown(im : torch.Tensor, downsize : tuple=None):
  function _pyrdown_mask (line 28) | def _pyrdown_mask(mask : torch.Tensor, downsize : tuple=None, eps : floa...
  function _erode_mask (line 66) | def _erode_mask(mask : torch.Tensor, ekernel : torch.Tensor=None, eps : ...
  function _l1_loss (line 75) | def _l1_loss(
  function _infer (line 86) | def _infer(
  function _get_image_mask_pyramid (line 176) | def _get_image_mask_pyramid(batch : dict, min_side : int, max_scales : i...
  function refine_predict (line 228) | def refine_predict(

FILE: model_cards/lama/saicinpainting/evaluation/utils.py
  function load_yaml (line 9) | def load_yaml(path):
  function move_to_device (line 14) | def move_to_device(obj, device):
  class SmallMode (line 26) | class SmallMode(Enum):

FILE: model_cards/lama/saicinpainting/evaluation/vis.py
  function save_item_for_vis (line 6) | def save_item_for_vis(item, out_file):
  function save_mask_for_sidebyside (line 27) | def save_mask_for_sidebyside(item, out_file):
  function save_img_for_sidebyside (line 34) | def save_img_for_sidebyside(item, out_file):

FILE: model_cards/lama/saicinpainting/training/data/aug.py
  class IAAAffine2 (line 4) | class IAAAffine2(DualIAATransform):
    method __init__ (line 17) | def __init__(
    method processor (line 41) | def processor(self):
    method get_transform_init_args_names (line 53) | def get_transform_init_args_names(self):
  class IAAPerspective2 (line 57) | class IAAPerspective2(DualIAATransform):
    method __init__ (line 71) | def __init__(self, scale=(0.05, 0.1), keep_size=True, always_apply=Fal...
    method processor (line 80) | def processor(self):
    method get_transform_init_args_names (line 83) | def get_transform_init_args_names(self):

FILE: model_cards/lama/saicinpainting/training/data/datasets.py
  class InpaintingTrainDataset (line 25) | class InpaintingTrainDataset(Dataset):
    method __init__ (line 26) | def __init__(self, indir, mask_generator, transform):
    method __len__ (line 32) | def __len__(self):
    method __getitem__ (line 35) | def __getitem__(self, item):
  class InpaintingTrainWebDataset (line 48) | class InpaintingTrainWebDataset(IterableDataset):
    method __init__ (line 49) | def __init__(self, indir, mask_generator, transform, shuffle_buffer=200):
    method __iter__ (line 54) | def __iter__(self):
  class ImgSegmentationDataset (line 64) | class ImgSegmentationDataset(Dataset):
    method __init__ (line 65) | def __init__(self, indir, mask_generator, transform, out_size, segm_in...
    method __len__ (line 74) | def __len__(self):
    method __getitem__ (line 77) | def __getitem__(self, item):
    method load_semantic_segm (line 92) | def load_semantic_segm(self, img_path):
  function get_transforms (line 101) | def get_transforms(transform_variant, out_size):
  function make_default_train_dataloader (line 206) | def make_default_train_dataloader(indir, kind='default', out_size=512, m...
  function make_default_val_dataset (line 249) | def make_default_val_dataset(indir, kind='default', out_size=512, transf...
  function make_default_val_dataloader (line 283) | def make_default_val_dataloader(*args, dataloader_kwargs=None, **kwargs):
  function make_constant_area_crop_params (line 292) | def make_constant_area_crop_params(img_height, img_width, min_size=128, ...

FILE: model_cards/lama/saicinpainting/training/data/masks.py
  class DrawMethod (line 16) | class DrawMethod(Enum):
  function make_random_irregular_mask (line 22) | def make_random_irregular_mask(shape, max_angle=4, max_len=60, max_width...
  class RandomIrregularMaskGenerator (line 51) | class RandomIrregularMaskGenerator:
    method __init__ (line 52) | def __init__(self, max_angle=4, max_len=60, max_width=20, min_times=0,...
    method __call__ (line 62) | def __call__(self, img, iter_i=None, raw_image=None):
  function make_random_rectangle_mask (line 72) | def make_random_rectangle_mask(shape, margin=10, bbox_min_size=30, bbox_...
  class RandomRectangleMaskGenerator (line 86) | class RandomRectangleMaskGenerator:
    method __init__ (line 87) | def __init__(self, margin=10, bbox_min_size=30, bbox_max_size=100, min...
    method __call__ (line 95) | def __call__(self, img, iter_i=None, raw_image=None):
  class RandomSegmentationMaskGenerator (line 104) | class RandomSegmentationMaskGenerator:
    method __init__ (line 105) | def __init__(self, **kwargs):
    method __call__ (line 109) | def __call__(self, img, iter_i=None, raw_image=None):
  function make_random_superres_mask (line 118) | def make_random_superres_mask(shape, min_step=2, max_step=4, min_width=1...
  class RandomSuperresMaskGenerator (line 136) | class RandomSuperresMaskGenerator:
    method __init__ (line 137) | def __init__(self, **kwargs):
    method __call__ (line 140) | def __call__(self, img, iter_i=None):
  class DumbAreaMaskGenerator (line 144) | class DumbAreaMaskGenerator:
    method __init__ (line 149) | def __init__(self, is_training):
    method _random_vector (line 154) | def _random_vector(self, dimension):
    method __call__ (line 167) | def __call__(self, img, iter_i=None, raw_image=None):
  class OutpaintingMaskGenerator (line 176) | class OutpaintingMaskGenerator:
    method __init__ (line 177) | def __init__(self, min_padding_percent:float=0.04, max_padding_percent...
    method apply_padding (line 195) | def apply_padding(self, mask, coord):
    method get_padding (line 200) | def get_padding(self, size):
    method _img2rs (line 206) | def _img2rs(img):
    method __call__ (line 212) | def __call__(self, img, iter_i=None, raw_image=None):
  class MixedMaskGenerator (line 252) | class MixedMaskGenerator:
    method __init__ (line 253) | def __init__(self, irregular_proba=1/3, irregular_kwargs=None,
    method __call__ (line 309) | def __call__(self, img, iter_i=None, raw_image=None):
  function get_mask_generator (line 318) | def get_mask_generator(kind, kwargs):

FILE: model_cards/lama/saicinpainting/training/losses/adversarial.py
  class BaseAdversarialLoss (line 8) | class BaseAdversarialLoss:
    method pre_generator_step (line 9) | def pre_generator_step(self, real_batch: torch.Tensor, fake_batch: tor...
    method pre_discriminator_step (line 20) | def pre_discriminator_step(self, real_batch: torch.Tensor, fake_batch:...
    method generator_loss (line 31) | def generator_loss(self, real_batch: torch.Tensor, fake_batch: torch.T...
    method discriminator_loss (line 46) | def discriminator_loss(self, real_batch: torch.Tensor, fake_batch: tor...
    method interpolate_mask (line 61) | def interpolate_mask(self, mask, shape):
  function make_r1_gp (line 71) | def make_r1_gp(discr_real_pred, real_batch):
  class NonSaturatingWithR1 (line 81) | class NonSaturatingWithR1(BaseAdversarialLoss):
    method __init__ (line 82) | def __init__(self, gp_coef=5, weight=1, mask_as_fake_target=False, all...
    method generator_loss (line 101) | def generator_loss(self, real_batch: torch.Tensor, fake_batch: torch.T...
    method pre_discriminator_step (line 117) | def pre_discriminator_step(self, real_batch: torch.Tensor, fake_batch:...
    method discriminator_loss (line 121) | def discriminator_loss(self, real_batch: torch.Tensor, fake_batch: tor...
  class BCELoss (line 145) | class BCELoss(BaseAdversarialLoss):
    method __init__ (line 146) | def __init__(self, weight):
    method generator_loss (line 150) | def generator_loss(self, discr_fake_pred: torch.Tensor) -> Tuple[torch...
    method pre_discriminator_step (line 155) | def pre_discriminator_step(self, real_batch: torch.Tensor, fake_batch:...
    method discriminator_loss (line 159) | def discriminator_loss(self,
  function make_discrim_loss (line 172) | def make_discrim_loss(kind, **kwargs):

FILE: model_cards/lama/saicinpainting/training/losses/distance_weighting.py
  function dummy_distance_weighter (line 9) | def dummy_distance_weighter(real_img, pred_img, mask):
  function get_gauss_kernel (line 13) | def get_gauss_kernel(kernel_size, width_factor=1):
  class BlurMask (line 22) | class BlurMask(nn.Module):
    method __init__ (line 23) | def __init__(self, kernel_size=5, width_factor=1):
    method forward (line 28) | def forward(self, real_img, pred_img, mask):
  class EmulatedEDTMask (line 34) | class EmulatedEDTMask(nn.Module):
    method __init__ (line 35) | def __init__(self, dilate_kernel_size=5, blur_kernel_size=5, width_fac...
    method forward (line 43) | def forward(self, real_img, pred_img, mask):
  class PropagatePerceptualSim (line 51) | class PropagatePerceptualSim(nn.Module):
    method __init__ (line 52) | def __init__(self, level=2, max_iters=10, temperature=500, erode_mask_...
    method forward (line 82) | def forward(self, real_img, pred_img, mask):
  function make_mask_distance_weighter (line 117) | def make_mask_distance_weighter(kind='none', **kwargs):

FILE: model_cards/lama/saicinpainting/training/losses/feature_matching.py
  function masked_l2_loss (line 7) | def masked_l2_loss(pred, target, mask, weight_known, weight_missing):
  function masked_l1_loss (line 13) | def masked_l1_loss(pred, target, mask, weight_known, weight_missing):
  function feature_matching_loss (line 19) | def feature_matching_loss(fake_features: List[torch.Tensor], target_feat...

FILE: model_cards/lama/saicinpainting/training/losses/perceptual.py
  class PerceptualLoss (line 14) | class PerceptualLoss(nn.Module):
    method __init__ (line 15) | def __init__(self, normalize_inputs=True):
    method do_normalize_inputs (line 38) | def do_normalize_inputs(self, x):
    method partial_losses (line 41) | def partial_losses(self, input, target, mask=None):
    method forward (line 72) | def forward(self, input, target, mask=None):
    method get_global_features (line 76) | def get_global_features(self, input):
  class ResNetPL (line 88) | class ResNetPL(nn.Module):
    method __init__ (line 89) | def __init__(self, weight=1,
    method forward (line 103) | def forward(self, pred, target):

FILE: model_cards/lama/saicinpainting/training/losses/segmentation.py
  class CrossEntropy2d (line 8) | class CrossEntropy2d(nn.Module):
    method __init__ (line 9) | def __init__(self, reduction="mean", ignore_label=255, weights=None, *...
    method forward (line 22) | def forward(self, predict, target):

FILE: model_cards/lama/saicinpainting/training/losses/style_loss.py
  class PerceptualLoss (line 6) | class PerceptualLoss(nn.Module):
    method __init__ (line 13) | def __init__(self, weights=[1.0, 1.0, 1.0, 1.0, 1.0]):
    method __call__ (line 19) | def __call__(self, x, y):
  class VGG19 (line 34) | class VGG19(torch.nn.Module):
    method __init__ (line 35) | def __init__(self):
    method forward (line 111) | def forward(self, x):

FILE: model_cards/lama/saicinpainting/training/modules/__init__.py
  function make_generator (line 7) | def make_generator(config, kind, **kwargs):
  function make_discriminator (line 22) | def make_discriminator(kind, **kwargs):

FILE: model_cards/lama/saicinpainting/training/modules/base.py
  class BaseDiscriminator (line 11) | class BaseDiscriminator(nn.Module):
    method forward (line 13) | def forward(self, x: torch.Tensor) -> Tuple[torch.Tensor, List[torch.T...
  function get_conv_block_ctor (line 21) | def get_conv_block_ctor(kind='default'):
  function get_norm_layer (line 33) | def get_norm_layer(kind='bn'):
  function get_activation (line 43) | def get_activation(kind='tanh'):
  class SimpleMultiStepGenerator (line 53) | class SimpleMultiStepGenerator(nn.Module):
    method __init__ (line 54) | def __init__(self, steps: List[nn.Module]):
    method forward (line 58) | def forward(self, x):
  function deconv_factory (line 67) | def deconv_factory(kind, ngf, mult, norm_layer, activation, max_features):

FILE: model_cards/lama/saicinpainting/training/modules/depthwise_sep_conv.py
  class DepthWiseSeperableConv (line 4) | class DepthWiseSeperableConv(nn.Module):
    method __init__ (line 5) | def __init__(self, in_dim, out_dim, *args, **kwargs):
    method forward (line 14) | def forward(self, x):

FILE: model_cards/lama/saicinpainting/training/modules/fake_fakes.py
  class FakeFakesGenerator (line 6) | class FakeFakesGenerator:
    method __init__ (line 7) | def __init__(self, aug_proba=0.5, img_aug_degree=30, img_aug_translate...
    method __call__ (line 20) | def __call__(self, input_images, masks):
    method _make_blend_target (line 26) | def _make_blend_target(self, input_images):
    method _fill_masks_with_gradient (line 34) | def _fill_masks_with_gradient(self, masks):

FILE: model_cards/lama/saicinpainting/training/modules/ffc.py
  class FFCSE_block (line 16) | class FFCSE_block(nn.Module):
    method __init__ (line 18) | def __init__(self, channels, ratio_g):
    method forward (line 34) | def forward(self, x):
  class FourierUnit (line 49) | class FourierUnit(nn.Module):
    method __init__ (line 51) | def __init__(self, in_channels, out_channels, groups=1, spatial_scale_...
    method forward (line 76) | def forward(self, x):
  class SpectralTransform (line 116) | class SpectralTransform(nn.Module):
    method __init__ (line 118) | def __init__(self, in_channels, out_channels, stride=1, groups=1, enab...
    method forward (line 142) | def forward(self, x):
  class FFC (line 166) | class FFC(nn.Module):
    method __init__ (line 168) | def __init__(self, in_channels, out_channels, kernel_size,
    method forward (line 205) | def forward(self, x):
  class FFC_BN_ACT (line 228) | class FFC_BN_ACT(nn.Module):
    method __init__ (line 230) | def __init__(self, in_channels, out_channels,
    method forward (line 251) | def forward(self, x):
  class FFCResnetBlock (line 258) | class FFCResnetBlock(nn.Module):
    method __init__ (line 259) | def __init__(self, dim, padding_type, norm_layer, activation_layer=nn....
    method forward (line 277) | def forward(self, x):
  class ConcatTupleLayer (line 295) | class ConcatTupleLayer(nn.Module):
    method forward (line 296) | def forward(self, x):
  class FFCResNetGenerator (line 305) | class FFCResNetGenerator(nn.Module):
    method __init__ (line 306) | def __init__(self, input_nc, output_nc, ngf=64, n_downsampling=3, n_bl...
    method forward (line 366) | def forward(self, input):
  class FFCNLayerDiscriminator (line 370) | class FFCNLayerDiscriminator(BaseDiscriminator):
    method __init__ (line 371) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method get_all_activations (line 416) | def get_all_activations(self, x):
    method forward (line 423) | def forward(self, x):

FILE: model_cards/lama/saicinpainting/training/modules/multidilated_conv.py
  class MultidilatedConv (line 6) | class MultidilatedConv(nn.Module):
    method __init__ (line 7) | def __init__(self, in_dim, out_dim, kernel_size, dilation_num=3, comb_...
    method forward (line 73) | def forward(self, x):

FILE: model_cards/lama/saicinpainting/training/modules/multiscale.py
  class ResNetHead (line 11) | class ResNetHead(nn.Module):
    method __init__ (line 12) | def __init__(self, input_nc, ngf=64, n_downsampling=3, n_blocks=9, nor...
    method forward (line 40) | def forward(self, input):
  class ResNetTail (line 44) | class ResNetTail(nn.Module):
    method __init__ (line 45) | def __init__(self, output_nc, ngf=64, n_downsampling=3, n_blocks=9, no...
    method forward (line 86) | def forward(self, input, return_last_act=False):
  class MultiscaleResNet (line 95) | class MultiscaleResNet(nn.Module):
    method __init__ (line 96) | def __init__(self, input_nc, output_nc, ngf=64, n_downsampling=2, n_bl...
    method num_scales (line 120) | def num_scales(self):
    method forward (line 123) | def forward(self, ms_inputs: List[torch.Tensor], smallest_scales_num: ...
  class MultiscaleDiscriminatorSimple (line 173) | class MultiscaleDiscriminatorSimple(nn.Module):
    method __init__ (line 174) | def __init__(self, ms_impl):
    method num_scales (line 179) | def num_scales(self):
    method forward (line 182) | def forward(self, ms_inputs: List[torch.Tensor], smallest_scales_num: ...
  class SingleToMultiScaleInputMixin (line 199) | class SingleToMultiScaleInputMixin:
    method forward (line 200) | def forward(self, x: torch.Tensor) -> List:
  class GeneratorMultiToSingleOutputMixin (line 208) | class GeneratorMultiToSingleOutputMixin:
    method forward (line 209) | def forward(self, x):
  class DiscriminatorMultiToSingleOutputMixin (line 213) | class DiscriminatorMultiToSingleOutputMixin:
    method forward (line 214) | def forward(self, x):
  class DiscriminatorMultiToSingleOutputStackedMixin (line 219) | class DiscriminatorMultiToSingleOutputStackedMixin:
    method __init__ (line 220) | def __init__(self, *args, return_feats_only_levels=None, **kwargs):
    method forward (line 224) | def forward(self, x):
  class MultiscaleDiscrSingleInput (line 239) | class MultiscaleDiscrSingleInput(SingleToMultiScaleInputMixin, Discrimin...
  class MultiscaleResNetSingle (line 243) | class MultiscaleResNetSingle(GeneratorMultiToSingleOutputMixin, SingleTo...

FILE: model_cards/lama/saicinpainting/training/modules/pix2pixhd.py
  class DotDict (line 15) | class DotDict(defaultdict):
  class Identity (line 22) | class Identity(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 26) | def forward(self, x):
  class ResnetBlock (line 30) | class ResnetBlock(nn.Module):
    method __init__ (line 31) | def __init__(self, dim, padding_type, norm_layer, activation=nn.ReLU(T...
    method build_conv_block (line 47) | def build_conv_block(self, dim, padding_type, norm_layer, activation, ...
    method forward (line 85) | def forward(self, x):
  class ResnetBlock5x5 (line 92) | class ResnetBlock5x5(nn.Module):
    method __init__ (line 93) | def __init__(self, dim, padding_type, norm_layer, activation=nn.ReLU(T...
    method build_conv_block (line 109) | def build_conv_block(self, dim, padding_type, norm_layer, activation, ...
    method forward (line 147) | def forward(self, x):
  class MultidilatedResnetBlock (line 155) | class MultidilatedResnetBlock(nn.Module):
    method __init__ (line 156) | def __init__(self, dim, padding_type, conv_layer, norm_layer, activati...
    method build_conv_block (line 160) | def build_conv_block(self, dim, padding_type, conv_layer, norm_layer, ...
    method forward (line 173) | def forward(self, x):
  class MultiDilatedGlobalGenerator (line 178) | class MultiDilatedGlobalGenerator(nn.Module):
    method __init__ (line 179) | def __init__(self, input_nc, output_nc, ngf=64, n_downsampling=3,
    method forward (line 236) | def forward(self, input):
  class ConfigGlobalGenerator (line 239) | class ConfigGlobalGenerator(nn.Module):
    method __init__ (line 240) | def __init__(self, input_nc, output_nc, ngf=64, n_downsampling=3,
    method forward (line 325) | def forward(self, input):
  function make_dil_blocks (line 329) | def make_dil_blocks(dilated_blocks_n, dilation_block_kind, dilated_block...
  class GlobalGenerator (line 341) | class GlobalGenerator(nn.Module):
    method __init__ (line 342) | def __init__(self, input_nc, output_nc, ngf=64, n_downsampling=3, n_bl...
    method forward (line 435) | def forward(self, input):
  class GlobalGeneratorGated (line 439) | class GlobalGeneratorGated(GlobalGenerator):
    method __init__ (line 440) | def __init__(self, *args, **kwargs):
  class GlobalGeneratorFromSuperChannels (line 450) | class GlobalGeneratorFromSuperChannels(nn.Module):
    method __init__ (line 451) | def __init__(self, input_nc, output_nc, n_downsampling, n_blocks, supe...
    method convert_super_channels (line 517) | def convert_super_channels(self, super_channels):
    method forward (line 560) | def forward(self, input):
  class NLayerDiscriminator (line 565) | class NLayerDiscriminator(BaseDiscriminator):
    method __init__ (line 566) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method get_all_activations (line 604) | def get_all_activations(self, x):
    method forward (line 611) | def forward(self, x):
  class MultidilatedNLayerDiscriminator (line 616) | class MultidilatedNLayerDiscriminator(BaseDiscriminator):
    method __init__ (line 617) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method get_all_activations (line 655) | def get_all_activations(self, x):
    method forward (line 662) | def forward(self, x):
  class NLayerDiscriminatorAsGen (line 667) | class NLayerDiscriminatorAsGen(NLayerDiscriminator):
    method forward (line 668) | def forward(self, x):

FILE: model_cards/lama/saicinpainting/training/modules/spatial_transform.py
  class LearnableSpatialTransformWrapper (line 7) | class LearnableSpatialTransformWrapper(nn.Module):
    method __init__ (line 8) | def __init__(self, impl, pad_coef=0.5, angle_init_range=80, train_angl...
    method forward (line 16) | def forward(self, x):
    method transform (line 26) | def transform(self, x):
    method inverse_transform (line 33) | def inverse_transform(self, y_padded_rotated, orig_x):

FILE: model_cards/lama/saicinpainting/training/modules/squeeze_excitation.py
  class SELayer (line 4) | class SELayer(nn.Module):
    method __init__ (line 5) | def __init__(self, channel, reduction=16):
    method forward (line 15) | def forward(self, x):

FILE: model_cards/lama/saicinpainting/training/trainers/__init__.py
  function get_training_model_class (line 6) | def get_training_model_class(kind):
  function make_training_model (line 13) | def make_training_model(config):
  function load_checkpoint (line 25) | def load_checkpoint(train_config, path, map_location='cuda', strict=True):

FILE: model_cards/lama/saicinpainting/training/trainers/base.py
  function make_optimizer (line 24) | def make_optimizer(parameters, kind='adamw', **kwargs):
  function update_running_average (line 34) | def update_running_average(result: nn.Module, new_iterate_model: nn.Modu...
  function make_multiscale_noise (line 43) | def make_multiscale_noise(base_tensor, scales=6, scale_mode='bilinear'):
  class BaseInpaintingTrainingModule (line 57) | class BaseInpaintingTrainingModule(ptl.LightningModule):
    method __init__ (line 58) | def __init__(self, config, use_ddp, *args,  predict_only=False, visual...
    method configure_optimizers (line 117) | def configure_optimizers(self):
    method train_dataloader (line 124) | def train_dataloader(self):
    method val_dataloader (line 133) | def val_dataloader(self):
    method training_step (line 147) | def training_step(self, batch, batch_idx, optimizer_idx=None):
    method validation_step (line 151) | def validation_step(self, batch, batch_idx, dataloader_idx):
    method training_step_end (line 163) | def training_step_end(self, batch_parts_outputs):
    method validation_epoch_end (line 180) | def validation_epoch_end(self, outputs):
    method _do_step (line 224) | def _do_step(self, batch, batch_idx, mode='train', optimizer_idx=None,...
    method get_current_generator (line 267) | def get_current_generator(self, no_average=False):
    method forward (line 272) | def forward(self, batch: Dict[str, torch.Tensor]) -> Dict[str, torch.T...
    method generator_loss (line 276) | def generator_loss(self, batch) -> Tuple[torch.Tensor, Dict[str, torch...
    method discriminator_loss (line 279) | def discriminator_loss(self, batch) -> Tuple[torch.Tensor, Dict[str, t...
    method store_discr_outputs (line 282) | def store_discr_outputs(self, batch):
    method get_ddp_rank (line 290) | def get_ddp_rank(self):

FILE: model_cards/lama/saicinpainting/training/trainers/default.py
  function make_constant_area_crop_batch (line 17) | def make_constant_area_crop_batch(batch, **kwargs):
  class DefaultInpaintingTrainingModule (line 26) | class DefaultInpaintingTrainingModule(BaseInpaintingTrainingModule):
    method __init__ (line 27) | def __init__(self, *args, concat_mask=True, rescale_scheduler_kwargs=N...
    method forward (line 47) | def forward(self, batch):
    method generator_loss (line 88) | def generator_loss(self, batch):
    method discriminator_loss (line 140) | def discriminator_loss(self, batch):

FILE: model_cards/lama/saicinpainting/training/visualizers/__init__.py
  function make_visualizer (line 7) | def make_visualizer(kind, **kwargs):

FILE: model_cards/lama/saicinpainting/training/visualizers/base.py
  class BaseVisualizer (line 14) | class BaseVisualizer:
    method __call__ (line 16) | def __call__(self, epoch_i, batch_i, batch, suffix='', rank=None):
  function visualize_mask_and_images (line 23) | def visualize_mask_and_images(images_dict: Dict[str, np.ndarray], keys: ...
  function visualize_mask_and_images_batch (line 61) | def visualize_mask_and_images_batch(batch: Dict[str, torch.Tensor], keys...

FILE: model_cards/lama/saicinpainting/training/visualizers/colors.py
  function generate_colors (line 11) | def generate_colors(nlabels, type='bright', first_color_black=False, las...

FILE: model_cards/lama/saicinpainting/training/visualizers/directory.py
  class DirectoryVisualizer (line 10) | class DirectoryVisualizer(BaseVisualizer):
    method __init__ (line 13) | def __init__(self, outdir, key_order=DEFAULT_KEY_ORDER, max_items_in_b...
    method __call__ (line 22) | def __call__(self, epoch_i, batch_i, batch, suffix='', rank=None):

FILE: model_cards/lama/saicinpainting/training/visualizers/noop.py
  class NoopVisualizer (line 4) | class NoopVisualizer(BaseVisualizer):
    method __init__ (line 5) | def __init__(self, *args, **kwargs):
    method __call__ (line 8) | def __call__(self, epoch_i, batch_i, batch, suffix='', rank=None):

FILE: model_cards/lama/saicinpainting/utils.py
  function check_and_warn_input_range (line 20) | def check_and_warn_input_range(tensor, min_value, max_value, name):
  function sum_dict_with_prefix (line 27) | def sum_dict_with_prefix(target, cur_dict, prefix, default=0):
  function average_dicts (line 33) | def average_dicts(dict_list):
  function add_prefix_to_keys (line 44) | def add_prefix_to_keys(dct, prefix):
  function set_requires_grad (line 48) | def set_requires_grad(module, value):
  function flatten_dict (line 53) | def flatten_dict(dct):
  class LinearRamp (line 66) | class LinearRamp:
    method __init__ (line 67) | def __init__(self, start_value=0, end_value=1, start_iter=-1, end_iter...
    method __call__ (line 73) | def __call__(self, i):
  class LadderRamp (line 82) | class LadderRamp:
    method __init__ (line 83) | def __init__(self, start_iters, values):
    method __call__ (line 88) | def __call__(self, i):
  function get_ramp (line 93) | def get_ramp(kind='ladder', **kwargs):
  function print_traceback_handler (line 101) | def print_traceback_handler(sig, frame):
  function register_debug_signal_handlers (line 107) | def register_debug_signal_handlers(sig=signal.SIGUSR1, handler=print_tra...
  function handle_deterministic_config (line 112) | def handle_deterministic_config(config):
  function get_shape (line 121) | def get_shape(t):
  function get_has_ddp_rank (line 134) | def get_has_ddp_rank():
  function handle_ddp_subprocess (line 143) | def handle_ddp_subprocess():
  function handle_ddp_parent_process (line 168) | def handle_ddp_parent_process():

FILE: model_cards/segment_anything/automatic_mask_generator.py
  class SamAutomaticMaskGenerator (line 35) | class SamAutomaticMaskGenerator:
    method __init__ (line 36) | def __init__(
    method generate (line 137) | def generate(self, image: np.ndarray) -> List[Dict[str, Any]]:
    method _generate_masks (line 197) | def _generate_masks(self, image: np.ndarray) -> MaskData:
    method _process_crop (line 225) | def _process_crop(
    method _process_batch (line 266) | def _process_batch(
    method postprocess_small_regions (line 324) | def postprocess_small_regions(

FILE: model_cards/segment_anything/build_sam.py
  function build_sam_vit_h (line 14) | def build_sam_vit_h(checkpoint=None):
  function build_sam_vit_l (line 27) | def build_sam_vit_l(checkpoint=None):
  function build_sam_vit_b (line 37) | def build_sam_vit_b(checkpoint=None):
  function _build_sam (line 55) | def _build_sam(

FILE: model_cards/segment_anything/modeling/common.py
  class MLPBlock (line 13) | class MLPBlock(nn.Module):
    method __init__ (line 14) | def __init__(
    method forward (line 25) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class LayerNorm2d (line 31) | class LayerNorm2d(nn.Module):
    method __init__ (line 32) | def __init__(self, num_channels: int, eps: float = 1e-6) -> None:
    method forward (line 38) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: model_cards/segment_anything/modeling/image_encoder.py
  class ImageEncoderViT (line 17) | class ImageEncoderViT(nn.Module):
    method __init__ (line 18) | def __init__(
    method forward (line 106) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Block (line 119) | class Block(nn.Module):
    method __init__ (line 122) | def __init__(
    method forward (line 166) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Attention (line 185) | class Attention(nn.Module):
    method __init__ (line 188) | def __init__(
    method forward (line 224) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  function window_partition (line 243) | def window_partition(x: torch.Tensor, window_size: int) -> Tuple[torch.T...
  function window_unpartition (line 267) | def window_unpartition(
  function get_rel_pos (line 292) | def get_rel_pos(q_size: int, k_size: int, rel_pos: torch.Tensor) -> torc...
  function add_decomposed_rel_pos (line 325) | def add_decomposed_rel_pos(
  class PatchEmbed (line 364) | class PatchEmbed(nn.Module):
    method __init__ (line 369) | def __init__(
    method forward (line 391) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: model_cards/segment_anything/modeling/mask_decoder.py
  class MaskDecoder (line 16) | class MaskDecoder(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 71) | def forward(
    method predict_masks (line 112) | def predict_masks(
  class MLP (line 154) | class MLP(nn.Module):
    method __init__ (line 155) | def __init__(
    method forward (line 171) | def forward(self, x):

FILE: model_cards/segment_anything/modeling/prompt_encoder.py
  class PromptEncoder (line 16) | class PromptEncoder(nn.Module):
    method __init__ (line 17) | def __init__(
    method get_dense_pe (line 62) | def get_dense_pe(self) -> torch.Tensor:
    method _embed_points (line 73) | def _embed_points(
    method _embed_boxes (line 93) | def _embed_boxes(self, boxes: torch.Tensor) -> torch.Tensor:
    method _embed_masks (line 102) | def _embed_masks(self, masks: torch.Tensor) -> torch.Tensor:
    method _get_batch_size (line 107) | def _get_batch_size(
    method _get_device (line 125) | def _get_device(self) -> torch.device:
    method forward (line 128) | def forward(
  class PositionEmbeddingRandom (line 171) | class PositionEmbeddingRandom(nn.Module):
    method __init__ (line 176) | def __init__(self, num_pos_feats: int = 64, scale: Optional[float] = N...
    method _pe_encoding (line 185) | def _pe_encoding(self, coords: torch.Tensor) -> torch.Tensor:
    method forward (line 194) | def forward(self, size: Tuple[int, int]) -> torch.Tensor:
    method forward_with_coords (line 207) | def forward_with_coords(

FILE: model_cards/segment_anything/modeling/sam.py
  class Sam (line 18) | class Sam(nn.Module):
    method __init__ (line 22) | def __init__(
    method device (line 50) | def device(self) -> Any:
    method forward (line 54) | def forward(
    method postprocess_masks (line 133) | def postprocess_masks(
    method preprocess (line 164) | def preprocess(self, x: torch.Tensor) -> torch.Tensor:

FILE: model_cards/segment_anything/modeling/transformer.py
  class TwoWayTransformer (line 16) | class TwoWayTransformer(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 62) | def forward(
  class TwoWayAttentionBlock (line 109) | class TwoWayAttentionBlock(nn.Module):
    method __init__ (line 110) | def __init__(
    method forward (line 151) | def forward(
  class Attention (line 185) | class Attention(nn.Module):
    method __init__ (line 191) | def __init__(
    method _separate_heads (line 208) | def _separate_heads(self, x: Tensor, num_heads: int) -> Tensor:
    method _recombine_heads (line 213) | def _recombine_heads(self, x: Tensor) -> Tensor:
    method forward (line 218) | def forward(self, q: Tensor, k: Tensor, v: Tensor) -> Tensor:

FILE: model_cards/segment_anything/predictor.py
  class SamPredictor (line 17) | class SamPredictor:
    method __init__ (line 18) | def __init__(
    method set_image (line 34) | def set_image(
    method set_torch_image (line 63) | def set_torch_image(
    method predict (line 92) | def predict(
    method predict_torch (line 169) | def predict_torch(
    method get_image_embedding (line 245) | def get_image_embedding(self) -> torch.Tensor:
    method device (line 259) | def device(self) -> torch.device:
    method reset_image (line 262) | def reset_image(self) -> None:

FILE: model_cards/segment_anything/utils/amg.py
  class MaskData (line 16) | class MaskData:
    method __init__ (line 22) | def __init__(self, **kwargs) -> None:
    method __setitem__ (line 29) | def __setitem__(self, key: str, item: Any) -> None:
    method __delitem__ (line 35) | def __delitem__(self, key: str) -> None:
    method __getitem__ (line 38) | def __getitem__(self, key: str) -> Any:
    method items (line 41) | def items(self) -> ItemsView[str, Any]:
    method filter (line 44) | def filter(self, keep: torch.Tensor) -> None:
    method cat (line 59) | def cat(self, new_stats: "MaskData") -> None:
    method to_numpy (line 72) | def to_numpy(self) -> None:
  function is_box_near_crop_edge (line 78) | def is_box_near_crop_edge(
  function box_xyxy_to_xywh (line 91) | def box_xyxy_to_xywh(box_xyxy: torch.Tensor) -> torch.Tensor:
  function batch_iterator (line 98) | def batch_iterator(batch_size: int, *args) -> Generator[List[Any], None,...
  function mask_to_rle_pytorch (line 107) | def mask_to_rle_pytorch(tensor: torch.Tensor) -> List[Dict[str, Any]]:
  function rle_to_mask (line 138) | def rle_to_mask(rle: Dict[str, Any]) -> np.ndarray:
  function area_from_rle (line 152) | def area_from_rle(rle: Dict[str, Any]) -> int:
  function calculate_stability_score (line 156) | def calculate_stability_score(
  function build_point_grid (line 179) | def build_point_grid(n_per_side: int) -> np.ndarray:
  function build_all_layer_point_grids (line 189) | def build_all_layer_point_grids(
  function generate_crop_boxes (line 200) | def generate_crop_boxes(
  function uncrop_boxes_xyxy (line 237) | def uncrop_boxes_xyxy(boxes: torch.Tensor, crop_box: List[int]) -> torch...
  function uncrop_points (line 246) | def uncrop_points(points: torch.Tensor, crop_box: List[int]) -> torch.Te...
  function uncrop_masks (line 255) | def uncrop_masks(
  function remove_small_regions (line 267) | def remove_small_regions(
  function coco_encode_rle (line 294) | def coco_encode_rle(uncompressed_rle: Dict[str, Any]) -> Dict[str, Any]:
  function batched_mask_to_box (line 303) | def batched_mask_to_box(masks: torch.Tensor) -> torch.Tensor:

FILE: model_cards/segment_anything/utils/onnx.py
  class SamOnnxModel (line 17) | class SamOnnxModel(nn.Module):
    method __init__ (line 25) | def __init__(
    method resize_longest_image_size (line 42) | def resize_longest_image_size(
    method _embed_points (line 51) | def _embed_points(self, point_coords: torch.Tensor, point_labels: torc...
    method _embed_masks (line 69) | def _embed_masks(self, input_mask: torch.Tensor, has_mask_input: torch...
    method mask_postprocessing (line 76) | def mask_postprocessing(self, masks: torch.Tensor, orig_im_size: torch...
    method select_masks (line 92) | def select_masks(
    method forward (line 108) | def forward(

FILE: model_cards/segment_anything/utils/transforms.py
  class ResizeLongestSide (line 16) | class ResizeLongestSide:
    method __init__ (line 23) | def __init__(self, target_length: int) -> None:
    method apply_image (line 26) | def apply_image(self, image: np.ndarray) -> np.ndarray:
    method apply_coords (line 33) | def apply_coords(self, coords: np.ndarray, original_size: Tuple[int, ....
    method apply_boxes (line 47) | def apply_boxes(self, boxes: np.ndarray, original_size: Tuple[int, ......
    method apply_image_torch (line 55) | def apply_image_torch(self, image: torch.Tensor) -> torch.Tensor:
    method apply_coords_torch (line 67) | def apply_coords_torch(
    method apply_boxes_torch (line 83) | def apply_boxes_torch(
    method get_preprocess_shape (line 94) | def get_preprocess_shape(oldh: int, oldw: int, long_side_length: int) ...

FILE: model_cards/setup.py
  function write_version_file (line 44) | def write_version_file():
  function get_extensions (line 56) | def get_extensions():
  function parse_requirements (line 114) | def parse_requirements(fname="requirements.txt", with_version=True):

FILE: themes/common.js
  function ChatBotHeight (line 1) | function ChatBotHeight() {
  function get_elements (line 31) | function get_elements() {

FILE: themes/default.py
  function adjust_theme (line 5) | def adjust_theme():

FILE: themes/green.py
  function adjust_theme (line 5) | def adjust_theme():

FILE: utils/AudioRecorder.py
  class BaseRecorder (line 9) | class BaseRecorder:
    method __init__ (line 10) | def __init__(self, source, source_name):
    method adjust_for_noise (line 21) | def adjust_for_noise(self, device_name, msg):
    method record_into_queue (line 27) | def record_into_queue(self, audio_queue):
  class DefaultMicRecorder (line 34) | class DefaultMicRecorder(BaseRecorder):
    method __init__ (line 35) | def __init__(self):
  class DefaultSpeakerRecorder (line 39) | class DefaultSpeakerRecorder(BaseRecorder):
    method __init__ (line 40) | def __init__(self):

FILE: utils/AudioTrans.py
  class AudioTranscriber (line 18) | class AudioTranscriber:
    method __init__ (line 19) | def __init__(self, mic_source, speaker_source, model,two_ways=False):
    method transcribe_audio_queue (line 45) | def transcribe_audio_queue(self, audio_queue):
    method update_last_sample_and_phrase_status (line 73) | def update_last_sample_and_phrase_status(self, who_spoke, data, time_s...
    method process_mic_data (line 89) | def process_mic_data(self, data, temp_file_name):
    method process_speaker_data (line 95) | def process_speaker_data(self, data, temp_file_name):
    method update_transcript (line 103) | def update_transcript(self, who_spoke, text, time_spoken):
    method get_transcript (line 115) | def get_transcript(self):
    method clear_transcript_data (line 122) | def clear_transcript_data(self):

FILE: utils/__init__.py
  function set_logging (line 21) | def set_logging(name=None, verbose=VERBOSE):
  function write_categories (line 36) | def write_categories(cls_name, file_path):
  function threaded (line 45) | def threaded(func):
  class TryExcept (line 54) | class TryExcept(contextlib.ContextDecorator):
    method __init__ (line 56) | def __init__(self, msg='', verbose=True):
    method __enter__ (line 60) | def __enter__(self):
    method __exit__ (line 63) | def __exit__(self, exc_type, value, traceback):
  function check_suffix (line 68) | def check_suffix(file=None, suffix=('.pt',), msg=''):
  function is_online (line 78) | def is_online() -> bool:
  function url2file (line 92) | def url2file(url):
  function emojis (line 97) | def emojis(str=''):
  function clean_url (line 100) | def clean_url(url):
  function check_requirements (line 106) | def check_requirements(requirements=ROOT / 'requirements.txt', exclude=(...

FILE: utils/audio.py
  class SetupError (line 28) | class SetupError(Exception):
  class WaitTimeoutError (line 32) | class WaitTimeoutError(Exception):
  class RequestError (line 36) | class RequestError(Exception):
  class UnknownValueError (line 40) | class UnknownValueError(Exception):
  class TranscriptionNotReady (line 44) | class TranscriptionNotReady(Exception):
  class TranscriptionFailed (line 48) | class TranscriptionFailed(Exception):
  class PortableNamedTemporaryFile (line 51) | class PortableNamedTemporaryFile(object):
    method __init__ (line 53) | def __init__(self, mode="w+b"):
    method __enter__ (line 56) | def __enter__(self):
    method __exit__ (line 65) | def __exit__(self, exc_type, exc_value, traceback):
    method write (line 69) | def write(self, *args, **kwargs):
    method writelines (line 72) | def writelines(self, *args, **kwargs):
    method flush (line 75) | def flush(self, *args, **kwargs):
  class AudioSource (line 78) | class AudioSource(object):
    method __init__ (line 79) | def __init__(self):
    method __enter__ (line 82) | def __enter__(self):
    method __exit__ (line 85) | def __exit__(self, exc_type, exc_value, traceback):
  class Microphone (line 89) | class Microphone(AudioSource):
    method __init__ (line 105) | def __init__(self, device_index=None, sample_rate=None, chunk_size=102...
    method get_pyaudio (line 136) | def get_pyaudio():
    method list_microphone_names (line 150) | def list_microphone_names():
    method list_working_microphones (line 167) | def list_working_microphones():
    method __enter__ (line 206) | def __enter__(self):
    method __exit__ (line 234) | def __exit__(self, exc_type, exc_value, traceback):
    class MicrophoneStream (line 241) | class MicrophoneStream(object):
      method __init__ (line 242) | def __init__(self, pyaudio_stream):
      method read (line 245) | def read(self, size):
      method close (line 248) | def close(self):
  class AudioFile (line 257) | class AudioFile(AudioSource):
    method __init__ (line 272) | def __init__(self, filename_or_fileobject):
    method __enter__ (line 284) | def __enter__(self):
    method __exit__ (line 341) | def __exit__(self, exc_type, exc_value, traceback):
    class AudioFileStream (line 347) | class AudioFileStream(object):
      method __init__ (line 348) | def __init__(self, audio_reader, little_endian, samples_24_bit_prete...
      method read (line 353) | def read(self, size=-1):
  class Recognizer (line 373) | class Recognizer(AudioSource):
    method __init__ (line 374) | def __init__(self):
    method record (line 388) | def record(self, source, duration=None, offset=None):
    method adjust_for_ambient_noise (line 421) | def adjust_for_ambient_noise(self, source, duration=1):
    method snowboy_wait_for_hot_word (line 448) | def snowboy_wait_for_hot_word(self, snowboy_location, snowboy_hot_word...
    method listen (line 497) | def listen(self, source, timeout=None, phrase_time_limit=None, snowboy...
    method listen_in_background (line 594) | def listen_in_background(self, source, callback, phrase_time_limit=None):
    method recognize_sphinx (line 627) | def recognize_sphinx(self, audio_data, language="en-US", keyword_entri...
  class AudioData (line 719) | class AudioData(object):
    method __init__ (line 732) | def __init__(self, frame_data, sample_rate, sample_width):
    method get_segment (line 741) | def get_segment(self, start_ms=None, end_ms=None):
    method get_raw_data (line 771) | def get_raw_data(self, convert_rate=None, convert_width=None):
    method get_wav_data (line 843) | def get_wav_data(self, convert_rate=None, convert_width=None, nchannel...
    method get_aiff_data (line 874) | def get_aiff_data(self, convert_rate=None, convert_width=None):
    method get_flac_data (line 916) | def get_flac_data(self, convert_rate=None, convert_width=None):
  function get_flac_converter (line 968) | def get_flac_converter():
  function shutil_which (line 1018) | def shutil_which(pgm):

FILE: utils/check_proxy.py
  function check_proxy (line 2) | def check_proxy(proxies):
  function _check_with_backup_source (line 27) | def _check_with_backup_source(proxies):
  function backup_and_download (line 33) | def backup_and_download(current_version, remote_version):
  function patch_and_restart (line 65) | def patch_and_restart(path):
  function get_current_version (line 97) | def get_current_version():
  function auto_update (line 107) | def auto_update(raise_error=False):
  function warm_up_modules (line 156) | def warm_up_modules():

FILE: utils/colorful.py
  function print红 (line 11) | def print红(*kw,**kargs):
  function print绿 (line 13) | def print绿(*kw,**kargs):
  function print黄 (line 15) | def print黄(*kw,**kargs):
  function print蓝 (line 17) | def print蓝(*kw,**kargs):
  function print紫 (line 19) | def print紫(*kw,**kargs):
  function print靛 (line 21) | def print靛(*kw,**kargs):
  function print亮红 (line 24) | def print亮红(*kw,**kargs):
  function print亮绿 (line 26) | def print亮绿(*kw,**kargs):
  function print亮黄 (line 28) | def print亮黄(*kw,**kargs):
  function print亮蓝 (line 30) | def print亮蓝(*kw,**kargs):
  function print亮紫 (line 32) | def print亮紫(*kw,**kargs):
  function print亮靛 (line 34) | def print亮靛(*kw,**kargs):
  function sprint红 (line 38) | def sprint红(*kw):
  function sprint绿 (line 40) | def sprint绿(*kw):
  function sprint黄 (line 42) | def sprint黄(*kw):
  function sprint蓝 (line 44) | def sprint蓝(*kw):
  function sprint紫 (line 46) | def sprint紫(*kw):
  function sprint靛 (line 48) | def sprint靛(*kw):
  function sprint亮红 (line 50) | def sprint亮红(*kw):
  function sprint亮绿 (line 52) | def sprint亮绿(*kw):
  function sprint亮黄 (line 54) | def sprint亮黄(*kw):
  function sprint亮蓝 (line 56) | def sprint亮蓝(*kw):
  function sprint亮紫 (line 58) | def sprint亮紫(*kw):
  function sprint亮靛 (line 60) | def sprint亮靛(*kw):

FILE: utils/dataloads.py
  function get_hash (line 51) | def get_hash(paths):
  function exif_size (line 59) | def exif_size(img):
  function exif_transpose (line 69) | def exif_transpose(image):
  function seed_worker (line 94) | def seed_worker(worker_id):
  function create_dataloader (line 101) | def create_dataloader(path,
  function create_kpt_dataloader (line 160) | def create_kpt_dataloader(path, imgsz, batch_size, stride, opt, hyp=None...
  class InfiniteDataLoader (line 190) | class InfiniteDataLoader(dataloader.DataLoader):
    method __init__ (line 195) | def __init__(self, *args, **kwargs):
    method __len__ (line 200) | def __len__(self):
    method __iter__ (line 203) | def __iter__(self):
  class _RepeatSampler (line 208) | class _RepeatSampler:
    method __init__ (line 214) | def __init__(self, sampler):
    method __iter__ (line 217) | def __iter__(self):
  class LoadScreenshots (line 222) | class LoadScreenshots:
    method __init__ (line 224) | def __init__(self, source, img_size=640, stride=32, auto=True, transfo...
    method __iter__ (line 253) | def __iter__(self):
    method __next__ (line 256) | def __next__(self):
  class LoadImages (line 271) | class LoadImages:
    method __init__ (line 273) | def __init__(self, path, img_size=640, stride=32, auto=True, transform...
    method __iter__ (line 308) | def __iter__(self):
    method __next__ (line 312) | def __next__(self):
    method _new_video (line 352) | def _new_video(self, path):
    method _cv2_rotate (line 360) | def _cv2_rotate(self, im):
    method __len__ (line 370) | def __len__(self):
  class LoadWebcam (line 375) | class LoadWebcam:  # for inference
    method __init__ (line 377) | def __init__(self, pipe='0', img_size=640, stride=32):
    method __iter__ (line 384) | def __iter__(self):
    method __next__ (line 388) | def __next__(self):
    method __len__ (line 411) | def __len__(self):
  class LoadStreams (line 415) | class LoadStreams:
    method __init__ (line 417) | def __init__(self, sources='file.streams', img_size=640, stride=32, au...
    method update (line 460) | def update(self, i, cap, stream):
    method __iter__ (line 477) | def __iter__(self):
    method __next__ (line 481) | def __next__(self):
    method __len__ (line 497) | def __len__(self):
  function img2label_paths (line 501) | def img2label_paths(img_paths):
  class LoadImagesAndLabels (line 507) | class LoadImagesAndLabels(Dataset):
    method __init__ (line 512) | def __init__(self,
    method check_cache_ram (line 662) | def check_cache_ram(self, safety_margin=0.1, prefix=''):
    method cache_labels (line 679) | def cache_labels(self, path=Path('./labels.cache'), prefix=''):
    method __len__ (line 717) | def __len__(self):
    method __getitem__ (line 726) | def __getitem__(self, index):
    method load_image (line 812) | def load_image(self, i):
    method cache_images_to_disk (line 829) | def cache_images_to_disk(self, i):
    method load_mosaic (line 835) | def load_mosaic(self, index):
    method load_mosaic9 (line 893) | def load_mosaic9(self, index):
    method load_samples (line 970) | def load_samples(self, index):
    method collate_fn (line 1022) | def collate_fn(batch):
    method collate_fn_v8 (line 1029) | def collate_fn_v8(batch):
    method collate_fn4 (line 1045) | def collate_fn4(batch):
  function create_folder (line 1073) | def create_folder(path='./new'):
  function flatten_recursive (line 1080) | def flatten_recursive(path=DATASETS_DIR / 'coco128'):
  function extract_boxes (line 1088) | def extract_boxes(path=DATASETS_DIR / 'coco128'):  # from utils.datasets...
  function autosplit (line 1122) | def autosplit(path=DATASETS_DIR / 'coco128/images', weights=(0.9, 0.1, 0...
  function verify_image_label (line 1146) | def verify_image_label(args):

FILE: utils/downloads.py
  function is_url (line 24) | def is_url(url, check_online=True):
  function unzip_file (line 34) | def unzip_file(file, path=None, exclude=('.DS_Store', '__MACOSX')):
  function gsutil_getsize (line 49) | def gsutil_getsize(url=''):
  function url_getsize (line 54) | def url_getsize(url='https://ultralytics.com/images/bus.jpg'):
  function check_disk_space (line 59) | def check_disk_space(url=None, sf=1.5, hard=True):
  function safe_download (line 90) | def safe_download(url,
  function attempt_download (line 176) | def attempt_download(file, repo='positive666/Prompt-Can-Anything', relea...
  function download_model (line 225) | def download_model(model_url, save_directory):

FILE: utils/ops.py
  function write_xml (line 63) | def write_xml(filename, img_name, img_root,preds, width, height):
  function save_format (line 94) | def save_format(label_format: str ="xml",save_path :str ="runs/xmls" ,
  function dilate_mask (line 107) | def dilate_mask(mask, dilate_factor=15):
  function erode_mask (line 116) | def erode_mask(mask, dilate_factor=15):
  function torch_nms_box (line 125) | def torch_nms_box(bboxes, scores, iou_threshold=0.5):
  function check_class_names (line 171) | def check_class_names(names):
  function is_kaggle (line 187) | def is_kaggle():
  function is_writeable (line 192) | def is_writeable(dir, test=False):
  function set_logging (line 206) | def set_logging(name=None, verbose=VERBOSE):
  function set_logging (line 222) | def set_logging(name=LOGGING_NAME, verbose=True):
  function user_config_dir (line 250) | def user_config_dir(dir='positive666', env_var='YOLOV5_CONFIG_DIR'):
  class Profile (line 266) | class Profile(contextlib.ContextDecorator):
    method __init__ (line 268) | def __init__(self, t=0.0):
    method __enter__ (line 272) | def __enter__(self):
    method __exit__ (line 276) | def __exit__(self, type, value, traceback):
    method time (line 280) | def time(self):
  class Timeout (line 286) | class Timeout(contextlib.ContextDecorator):
    method __init__ (line 288) | def __init__(self, seconds, *, timeout_msg='', suppress_timeout_errors...
    method _timeout_handler (line 293) | def _timeout_handler(self, signum, frame):
    method __enter__ (line 296) | def __enter__(self):
    method __exit__ (line 301) | def __exit__(self, exc_type, exc_val, exc_tb):
  class WorkingDirectory (line 308) | class WorkingDirectory(contextlib.ContextDecorator):
    method __init__ (line 310) | def __init__(self, new_dir):
    method __enter__ (line 314) | def __enter__(self):
    method __exit__ (line 317) | def __exit__(self, exc_type, exc_val, exc_tb):
  function methods (line 322) | def methods(instance):
  function print_args (line 327) | def print_args(args: Optional[dict] = None, show_file=True, show_func=Fa...
  function init_seeds (line 342) | def init_seeds(seed=0, deterministic=False):
  function intersect_dicts (line 360) | def intersect_dicts(da, db, exclude=()):
  function get_default_args (line 364) | def get_default_args(func):
  function merge_bases (line 369) | def merge_bases(rois, coeffs, attn_r, num_b, location_to_inds=None):
  function get_latest_run (line 387) | def get_latest_run(search_dir='.'):
  function is_docker (line 393) | def is_docker():
  function is_colab (line 403) | def is_colab():
  function is_jupyter (line 408) | def is_jupyter():
  function is_pip (line 420) | def is_pip():
  function is_ascii (line 425) | def is_ascii(s=''):
  function is_chinese (line 431) | def is_chinese(s='人工智能'):
  function file_age (line 436) | def file_age(path=__file__):
  function file_date (line 442) | def file_date(path=__file__):
  function file_size (line 448) | def file_size(path):
  function check_online (line 460) | def check_online():
  function check_yolo (line 475) | def check_yolo(verbose=True):
  function git_describe (line 497) | def git_describe(path=ROOT):  # path must be a directory
  function check_git_status (line 508) | def check_git_status(repo='positive666/yolo_research', branch='master'):
  function check_git_info (line 535) | def check_git_info(path='.'):
  function check_python (line 551) | def check_python(minimum='3.7.0'):
  function check_version (line 556) | def check_version(current='0.0.0', minimum='0.0.0', name='version ', pin...
  function check_requirements (line 569) | def check_requirements(requirements=ROOT / 'requirements.txt', exclude=(...
  function check_img_size (line 605) | def check_img_size(imgsz, s=32, floor=0):
  function check_imshow (line 617) | def check_imshow(warn=False):
  function check_suffix (line 633) | def check_suffix(file='yolov5s.pt', suffix=('.pt',), msg=''):
  function check_yaml (line 644) | def check_yaml(file, suffix=('.yaml', '.yml')):
  function check_file (line 649) | def check_file(file, suffix=''):
  function check_dataset (line 673) | def check_dataset(data, autodownload=True):
  function yaml_load (line 735) | def yaml_load(file='data.yaml', append_filename=False):
  function yaml_save (line 754) | def yaml_save(file='data.yaml', data={}):
  function unzip_file (line 759) | def unzip_file(file, path=None, exclude=('.DS_Store', '__MACOSX')):
  function url2file (line 768) | def url2file(url):
  function download (line 774) | def download(url, dir='.', unzip=True, delete=True, curl=False, threads=...
  function make_divisible (line 822) | def make_divisible(x, divisor):
  function clean_str (line 829) | def clean_str(s):
  function one_cycle (line 834) | def one_cycle(y1=0.0, y2=1.0, steps=100):
  function colorstr (line 839) | def colorstr(*input):
  function labels_to_class_weights (line 865) | def labels_to_class_weights(labels, nc=80):
  function labels_to_image_weights (line 884) | def labels_to_image_weights(labels, nc=80, class_weights=np.ones(80)):
  function coco80_to_coco91_class (line 891) | def coco80_to_coco91_class():  # converts 80-index (val2014) to 91-index...
  function xyxy2xywh (line 903) | def xyxy2xywh(x):
  function xywh2xyxy (line 913) | def xywh2xyxy(x):
  function xywh2xyxy_export (line 923) | def xywh2xyxy_export(cx,cy,w,h):
  function xywhn2xyxy (line 935) | def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0,kpt_label=False):
  function xyxy2xywhn (line 955) | def xyxy2xywhn(x, w=640, h=640, clip=False, eps=0.0):
  function xyn2xy (line 967) | def xyn2xy(x, w=640, h=640, padw=0, padh=0):
  function segment2box (line 975) | def segment2box(segment, width=640, height=640):
  function segments2boxes (line 983) | def segments2boxes(segments):
  function resample_segments (line 992) | def resample_segments(segments, n=1000):
  function scale_boxes (line 1002) | def scale_boxes(img1_shape, boxes, img0_shape, ratio_pad=None,kpt_label=...
  function box_iou (line 1024) | def box_iou(box1, box2, eps=1e-7):
  function scale_segments (line 1044) | def scale_segments(img1_shape, segments, img0_shape, ratio_pad=None, nor...
  function clip_boxes (line 1063) | def clip_boxes(boxes, shape, step=None):
  function clip_segments (line 1080) | def clip_segments(boxes, shape):
  function scale_image (line 1089) | def scale_image(im1_shape, masks, im0_shape, ratio_pad=None):
  function clip_boxes (line 1121) | def clip_boxes(boxes, shape):
  function non_max_suppression (line 1138) | def non_max_suppression(prediction,
  function non_max_suppression_keypoint (line 1246) | def non_max_suppression_keypoint(prediction, conf_thres=0.25, iou_thres=...
  function increment_path (line 1346) | def increment_path(path, exist_ok=False, sep='', mkdir=False):
  function imread (line 1376) | def imread(path, flags=cv2.IMREAD_COLOR):
  function imwrite (line 1380) | def imwrite(path, im):
  function imshow (line 1388) | def imshow(path, im):
  function fitness (line 1396) | def fitness(x):
  function split_images_to_folders (line 1402) | def split_images_to_folders(folder_path, num_threads, num_folders):
  function merge_image_folders (line 1433) | def merge_image_folders(folder_path):

FILE: utils/plot.py
  function save_mask_data (line 33) | def save_mask_data(output_dir, caption, mask_list, box_list, label_list,...
  function scale_image (line 61) | def scale_image(im1_shape, masks, im0_shape, ratio_pad=None):
  function show_mask (line 88) | def show_mask(mask, ax, random_color=False,cls_color=None):
  function Draw_img (line 103) | def Draw_img(data,draw,mode='box',label=None,random_color=None):
  function show_box (line 132) | def show_box(box, ax, label):
  class Colors (line 138) | class Colors:
    method __init__ (line 140) | def __init__(self):
    method __call__ (line 147) | def __call__(self, i, bgr=False):
    method hex2rgb (line 152) | def hex2rgb(h):  # rgb order (PIL)
  function check_font (line 158) | def check_font(font=FONT, url="",progress=False):
  function check_pil_font (line 167) | def check_pil_font(font=FONT, size=10):
  class Annotator (line 183) | class Annotator:
    method __init__ (line 185) | def __init__(self, im, line_width=None, font_size=None, font='Arial.tt...
    method box_label (line 198) | def box_label(self, box, label='', color=(128, 128, 128), txt_color=(2...
    method masks (line 229) | def masks(self, masks, colors, im_gpu, alpha=0.5, retina_masks=False):
    method rectangle (line 259) | def rectangle(self, xy, fill=None, outline=None, width=1):
    method text (line 263) | def text(self, xy, text, txt_color=(255, 255, 255), anchor='top'):
    method fromarray (line 270) | def fromarray(self, im):
    method result (line 275) | def result(self):
  function feature_visualization (line 280) | def feature_visualization(x, module_type, stage, n=32, save_dir=Path('ru...
  function hist2d (line 308) | def hist2d(x, y, n=100):
  function butter_lowpass_filtfilt (line 317) | def butter_lowpass_filtfilt(data, cutoff=1500, fs=50000, order=5):
  function output_to_target (line 330) | def output_to_target(output, max_det=300):
  function plot_images (line 341) | def plot_images(images, targets, paths=None, fname='images.jpg', names=N...
  function plot_images_masks (line 405) | def plot_images_masks(images,
  function plot_lr_scheduler (line 510) | def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir=''):
  function plot_val_txt (line 527) | def plot_val_txt():  # from utils.plots import *; plot_val()
  function plot_targets_txt (line 544) | def plot_targets_txt():  # from utils.plots import *; plot_targets_txt()
  function plot_val_study (line 557) | def plot_val_study(file='', dir='', x=None):  # from utils.plots import ...
  function plot_labels (line 603) | def plot_labels(labels, names=(), save_dir=Path('')):
  function plot_evolve (line 678) | def plot_evolve(evolve_csv='path/to/evolve.csv'):  # from utils.plots im...
  function plot_results (line 705) | def plot_results(file='path/to/results.csv', dir=''):
  function profile_idetection (line 731) | def profile_idetection(start=0, stop=0, labels=(), save_dir=''):
  function save_one_box (line 762) | def save_one_box(xyxy, im, file=Path('im.jpg'), gain=1.02, pad=10, squar...
  function plot_one_box (line 780) | def plot_one_box(x, im, color=None, label=None, line_thickness=3, kpt_la...
  function plot_skeleton_kpts (line 800) | def plot_skeleton_kpts(im, kpts, steps, orig_shape=None):

FILE: utils/text2speech.py
  class T2S (line 7) | class T2S():
    method __init__ (line 8) | def __init__(self) -> None:
    method test (line 12) | def test(self, text, language='en'):

FILE: utils/textsplitter/ali_text_splitter.py
  class AliTextSplitter (line 6) | class AliTextSplitter(CharacterTextSplitter):
    method __init__ (line 7) | def __init__(self, pdf: bool = False, **kwargs):
    method split_text (line 11) | def split_text(self, text: str) -> List[str]:

FILE: utils/textsplitter/chinese_text_splitter.py
  class ChineseTextSplitter (line 7) | class ChineseTextSplitter(CharacterTextSplitter):
    method __init__ (line 8) | def __init__(self, pdf: bool = False, sentence_size: int = SENTENCE_SI...
    method split_text1 (line 13) | def split_text1(self, text: str) -> List[str]:
    method split_text (line 27) | def split_text(self, text: str) -> List[str]:   ##此处需要进一步优化逻辑

FILE: utils/textsplitter/zh_title_enhance.py
  function under_non_alpha_ratio (line 5) | def under_non_alpha_ratio(text: str, threshold: float = 0.5):
  function is_possible_title (line 30) | def is_possible_title(
  function zh_title_enhance (line 88) | def zh_title_enhance(docs: Document) -> Document:

FILE: utils/toolbox.py
  class ChatBotWithCookies (line 24) | class ChatBotWithCookies(list):
    method __init__ (line 25) | def __init__(self, cookie):
    method write_list (line 28) | def write_list(self, list):
    method get_list (line 32) | def get_list(self):
    method get_cookies (line 35) | def get_cookies(self):
  function ArgsGeneralWrapper (line 39) | def ArgsGeneralWrapper(f):
  function update_ui (line 73) | def update_ui(chatbot, history, msg='正常', **kwargs):  # 刷新界面
  function trimmed_format_exc (line 80) | def trimmed_format_exc():
  function CatchException (line 87) | def CatchException(f):
  function HotReload (line 110) | def HotReload(f):
  function get_reduce_token_percent (line 146) | def get_reduce_token_percent(text):
  function write_results_to_file (line 164) | def write_results_to_file(history, file_name=None):
  function write_history_to_file (line 195) | def write_history_to_file(history, file_basename=None, file_fullname=None):
  function regular_txt_to_markdown (line 225) | def regular_txt_to_markdown(text):
  function report_execption (line 237) | def report_execption(chatbot, history, a, b):
  function text_divide_paragraph (line 246) | def text_divide_paragraph(text):
  function markdown_convertion (line 262) | def markdown_convertion(txt):
  function close_up_code_segment_during_stream (line 338) | def close_up_code_segment_during_stream(gpt_reply):
  function format_io (line 364) | def format_io(self, y):
  function find_free_port (line 386) | def find_free_port():
  function extract_archive (line 398) | def extract_archive(file_path, dest_dir):
  function find_recent_files (line 443) | def find_recent_files(directory):
  function promote_file_to_downloadzone (line 466) | def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
  function disable_auto_promotion (line 481) | def disable_auto_promotion(chatbot):
  function on_file_uploaded (line 485) | def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
  function on_report_generated (line 523) | def on_report_generated(cookies, files, chatbot):
  function is_openai_api_key (line 539) | def is_openai_api_key(key):
  function is_api2d_key (line 544) | def is_api2d_key(key):
  function is_any_api_key (line 550) | def is_any_api_key(key):
  function what_keys (line 559) | def what_keys(keys):

[
  {
    "path": ".gitignore",
    "chars": 1980,
    "preview": "# Byte-compiled / optimized / DLL files\n__pycache__/\n*.py[cod]\n*$py.class\n\n# C extensions\n*.so\n\n# Distribution / packagi"
  },
  {
    "path": ".gitmodules",
    "chars": 104,
    "preview": "[submodule \"VisualGLM_6B\"]\n\tpath = VisualGLM_6B\n\turl = https://github.com/positive666/VisualGLM_6B.git\n\n"
  },
  {
    "path": "LICENSE",
    "chars": 35149,
    "preview": "                    GNU GENERAL PUBLIC LICENSE\n                       Version 3, 29 June 2007\n\n Copyright (C) 2007 Free "
  },
  {
    "path": "README.md",
    "chars": 15444,
    "preview": "# Prompt-Can-Anything\n\n<p align=\"center\"> English | <a href=\"README_zh.md\">中文</a></p>\n\nThis is a gradio  library and res"
  },
  {
    "path": "README_zh.md",
    "chars": 9303,
    "preview": "\n\n# Prompt-Can-Anything\n\n这是一个结合SOTA AI的应用web库以及研究的储备库，它能够帮你实现一切：你只需要提供提示！只需一次点击！通过SOTA模型的提示和创意，你可以做任何事情。\n\n**动机**\n\n当前：为工程"
  },
  {
    "path": "a2f.py",
    "chars": 12880,
    "preview": "import argparse\nimport functools\nimport os\nimport yaml\nimport numpy as np\nimport ffmpeg\nimport grpc\nimport grpc\nimport a"
  },
  {
    "path": "app.py",
    "chars": 59164,
    "preview": "from model_cards.autoback import AutoBackend\nimport argparse\nimport os\nimport platform\nimport sys\nfrom pathlib import Pa"
  },
  {
    "path": "audio2face_pb2.py",
    "chars": 16751,
    "preview": "# -*- coding: utf-8 -*-\n# Generated by the protocol buffer compiler.  DO NOT EDIT!\n# source: audio2face.proto\n\"\"\"Generat"
  },
  {
    "path": "audio2face_pb2_grpc.py",
    "chars": 4209,
    "preview": "# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!\n\"\"\"Client and server classes corresponding to prot"
  },
  {
    "path": "audio2face_streaming_utils.py",
    "chars": 6975,
    "preview": "\"\"\"\nThis demo script shows how to send audio data to Audio2Face Streaming Audio Player via gRPC requests.\nThere are two "
  },
  {
    "path": "audio_segment.py",
    "chars": 2665,
    "preview": "\n\nimport os\nimport gradio as gr\nfrom pydub import AudioSegment\n\n# function to crop audio according to the given start an"
  },
  {
    "path": "auto_label_demo.py",
    "chars": 19802,
    "preview": "from model_cards.autoback import AutoBackend\nimport argparse\nimport os\nimport platform\nimport sys\nfrom pathlib import Pa"
  },
  {
    "path": "batch_clean_gpu.txt",
    "chars": 85,
    "preview": "sudo fuser -v /dev/nvidia* |awk '{for(i=1;i<=NF;i++)print \"kill -9 \" $i;}' | sudo sh\n"
  },
  {
    "path": "crazy_functions/Langchain知识库.py",
    "chars": 5182,
    "preview": "from utils.toolbox import CatchException, update_ui, ProxyNetworkActivate\nfrom .crazy_utils import request_gpt_model_in_"
  },
  {
    "path": "crazy_functions/Latex全文润色.py",
    "chars": 10132,
    "preview": "from utils.toolbox import update_ui, trimmed_format_exc\nfrom utils.toolbox import CatchException, report_execption, writ"
  },
  {
    "path": "crazy_functions/Latex全文翻译.py",
    "chars": 7432,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file\nfa"
  },
  {
    "path": "crazy_functions/Latex输出PDF结果.py",
    "chars": 13975,
    "preview": "from utils.toolbox import update_ui, trimmed_format_exc, get_conf, objdump, objload, promote_file_to_downloadzone\nfrom u"
  },
  {
    "path": "crazy_functions/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "crazy_functions/chatglm微调工具.py",
    "chars": 5758,
    "preview": "from utils.toolbox import CatchException, update_ui, promote_file_to_downloadzone\nfrom .crazy_utils import request_gpt_m"
  },
  {
    "path": "crazy_functions/crazy_functions_test.py",
    "chars": 10204,
    "preview": "\"\"\"\n这是什么？\n    这个文件用于函数插件的单元测试\n    运行方法 python crazy_functions/crazy_functions_test.py\n\"\"\"\n    \n# ======================="
  },
  {
    "path": "crazy_functions/crazy_utils.py",
    "chars": 31908,
    "preview": "from utils.toolbox import update_ui, get_conf, trimmed_format_exc\nimport threading\n\ndef input_clipping(inputs, history, "
  },
  {
    "path": "crazy_functions/latex_fns/latex_actions.py",
    "chars": 23361,
    "preview": "from utils.toolbox import update_ui, update_ui_lastest_msg    # 刷新Gradio前端界面\nfrom utils.toolbox import zip_folder, objdu"
  },
  {
    "path": "crazy_functions/latex_fns/latex_toolbox.py",
    "chars": 17390,
    "preview": "import os, shutil\nimport re\nimport numpy as np\nPRESERVE = 0\nTRANSFORM = 1\n\npj = os.path.join\n\nclass LinkedListNode():\n  "
  },
  {
    "path": "crazy_functions/live_audio/aliyunASR.py",
    "chars": 4781,
    "preview": "import time, threading, json\n\n\nclass AliyunASR():\n\n    def test_on_sentence_begin(self, message, *args):\n        # print"
  },
  {
    "path": "crazy_functions/live_audio/audio_io.py",
    "chars": 1464,
    "preview": "import numpy as np\nfrom scipy import interpolate\n\ndef Singleton(cls):\n    _instance = {}\n \n    def _singleton(*args, **k"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/buffer.cpp",
    "chars": 1695,
    "preview": "#include \"libipc/buffer.h\"\n#include \"libipc/utility/pimpl.h\"\n\n#include <cstring>\n\nnamespace ipc {\n\nbool operator==(buffe"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/ipc.cpp",
    "chars": 23714,
    "preview": "\n#include <type_traits>\n#include <cstring>\n#include <algorithm>\n#include <utility>          // std::pair, std::move, std"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/policy.h",
    "chars": 539,
    "preview": "#pragma once\n\n#include <type_traits>\n\n#include \"libipc/def.h\"\n#include \"libipc/prod_cons.h\"\n\n#include \"libipc/circ/elem_"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/pool_alloc.cpp",
    "chars": 320,
    "preview": "#include \"libipc/pool_alloc.h\"\n\n#include \"libipc/memory/resource.h\"\n\nnamespace ipc {\nnamespace mem {\n\nvoid* pool_alloc::"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/prod_cons.h",
    "chars": 16667,
    "preview": "#pragma once\n\n#include <atomic>\n#include <utility>\n#include <cstring>\n#include <type_traits>\n#include <cstdint>\n\n#includ"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/queue.h",
    "chars": 5709,
    "preview": "#pragma once\n\n#include <type_traits>\n#include <new>\n#include <utility>  // [[since C++14]]: std::exchange\n#include <algo"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/shm.cpp",
    "chars": 1953,
    "preview": "\n#include <string>\n#include <utility>\n\n#include \"libipc/shm.h\"\n\n#include \"libipc/utility/pimpl.h\"\n#include \"libipc/memor"
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/waiter.h",
    "chars": 1927,
    "preview": "#pragma once\n\n#include <utility>\n#include <string>\n#include <mutex>\n#include <atomic>\n\n#include \"libipc/def.h\"\n#include "
  },
  {
    "path": "crazy_functions/test_project/cpp/cppipc/来源",
    "chars": 129,
    "preview": "https://github.com/mutouyun/cpp-ipc\n\nA high-performance inter-process communication library using shared memory on Linux"
  },
  {
    "path": "crazy_functions/test_project/cpp/libJPG/jpgd.cpp",
    "chars": 86773,
    "preview": "// jpgd.cpp - C++ class for JPEG decompression.\n// Public domain, Rich Geldreich <richgel99@gmail.com>\n// Last updated A"
  },
  {
    "path": "crazy_functions/test_project/cpp/libJPG/jpgd.h",
    "chars": 13766,
    "preview": "// jpgd.h - C++ class for JPEG decompression.\n// Public domain, Rich Geldreich <richgel99@gmail.com>\n#ifndef JPEG_DECODE"
  },
  {
    "path": "crazy_functions/test_project/cpp/libJPG/jpge.cpp",
    "chars": 35392,
    "preview": "// jpge.cpp - C++ class for JPEG compression.\n// Public domain, Rich Geldreich <richgel99@gmail.com>\n// v1.01, Dec. 18, "
  },
  {
    "path": "crazy_functions/test_project/cpp/libJPG/jpge.h",
    "chars": 6546,
    "preview": "\n// jpge.h - C++ class for JPEG compression.\n// Public domain, Rich Geldreich <richgel99@gmail.com>\n// Alex Evans: Added"
  },
  {
    "path": "crazy_functions/test_project/cpp/libJPG/来源",
    "chars": 149,
    "preview": "jpge.h - C++ class for JPEG compression.\nPublic domain, Rich Geldreich <richgel99@gmail.com>\nAlex Evans: Added RGBA supp"
  },
  {
    "path": "crazy_functions/test_project/cpp/longcode/jpgd.cpp",
    "chars": 86773,
    "preview": "// jpgd.cpp - C++ class for JPEG decompression.\n// Public domain, Rich Geldreich <richgel99@gmail.com>\n// Last updated A"
  },
  {
    "path": "crazy_functions/test_project/cpp/longcode/jpge.cpp",
    "chars": 35392,
    "preview": "// jpge.cpp - C++ class for JPEG compression.\n// Public domain, Rich Geldreich <richgel99@gmail.com>\n// v1.01, Dec. 18, "
  },
  {
    "path": "crazy_functions/test_project/cpp/longcode/prod_cons.h",
    "chars": 16667,
    "preview": "#pragma once\n\n#include <atomic>\n#include <utility>\n#include <cstring>\n#include <type_traits>\n#include <cstdint>\n\n#includ"
  },
  {
    "path": "crazy_functions/test_project/latex/attention/background.tex",
    "chars": 8376,
    "preview": "The goal of reducing sequential computation also forms the foundation of the Extended Neural GPU \\citep{extendedngpu}, B"
  },
  {
    "path": "crazy_functions/test_project/latex/attention/introduction.tex",
    "chars": 5300,
    "preview": "Recurrent neural networks, long short-term memory \\citep{hochreiter1997} and gated recurrent \\citep{gruEval14} neural ne"
  },
  {
    "path": "crazy_functions/test_project/latex/attention/model_architecture.tex",
    "chars": 17109,
    "preview": "\n\\begin{figure}\n  \\centering\n  \\includegraphics[scale=0.6]{Figures/ModalNet-21}\n  \\caption{The Transformer - model archi"
  },
  {
    "path": "crazy_functions/test_project/latex/attention/parameter_attention.tex",
    "chars": 3489,
    "preview": "\\pagebreak\n\\section*{Two Feed-Forward Layers = Attention over Parameters}\\label{sec:parameter_attention}\n\nIn addition to"
  },
  {
    "path": "crazy_functions/test_project/latex/attention/来源",
    "chars": 1340,
    "preview": "chatgpt的老祖宗《Attention is all you need》\n\nAshish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N"
  },
  {
    "path": "crazy_functions/test_project/python/dqn/__init__.py",
    "chars": 106,
    "preview": "from stable_baselines3.dqn.dqn import DQN\nfrom stable_baselines3.dqn.policies import CnnPolicy, MlpPolicy\n"
  },
  {
    "path": "crazy_functions/test_project/python/dqn/dqn.py",
    "chars": 10780,
    "preview": "from typing import Any, Dict, List, Optional, Tuple, Type, Union\n\nimport gym\nimport numpy as np\nimport torch as th\nfrom "
  },
  {
    "path": "crazy_functions/test_project/python/dqn/policies.py",
    "chars": 8564,
    "preview": "from typing import Any, Dict, List, Optional, Type\n\nimport gym\nimport torch as th\nfrom torch import nn\n\nfrom stable_base"
  },
  {
    "path": "crazy_functions/test_project/python/dqn/来源",
    "chars": 66,
    "preview": "github stablebaseline3\nhttps://github.com/DLR-RM/stable-baselines3"
  },
  {
    "path": "crazy_functions/test_project/其他测试",
    "chars": 957,
    "preview": "\"In practice, we found that a high-entropy initial state is more likely to increase the speed of training.\nThe entropy i"
  },
  {
    "path": "crazy_functions/下载arxiv论文翻译摘要.py",
    "chars": 6365,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file, g"
  },
  {
    "path": "crazy_functions/交互功能函数模板.py",
    "chars": 2778,
    "preview": "from utils.toolbox import CatchException, update_ui\nfrom .crazy_utils import request_gpt_model_in_new_thread_with_ui_ali"
  },
  {
    "path": "crazy_functions/代码重写为全英文_多线程.py",
    "chars": 5872,
    "preview": "import threading\nfrom llm_cards.bridge_all import predict_no_ui_long_connection\nfrom utils.toolbox import update_ui\nfrom"
  },
  {
    "path": "crazy_functions/图片生成.py",
    "chars": 2794,
    "preview": "from utils.toolbox import CatchException, update_ui, get_conf, select_api_key\nfrom .crazy_utils import request_gpt_model"
  },
  {
    "path": "crazy_functions/对话历史存档.py",
    "chars": 5955,
    "preview": "from utils.toolbox import CatchException, update_ui, promote_file_to_downloadzone\nfrom .crazy_utils import request_gpt_m"
  },
  {
    "path": "crazy_functions/总结word文档.py",
    "chars": 5107,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file\nfr"
  },
  {
    "path": "crazy_functions/总结音视频.py",
    "chars": 6700,
    "preview": "from utils.toolbox import CatchException, report_execption, select_api_key, update_ui, write_results_to_file, get_conf\nf"
  },
  {
    "path": "crazy_functions/批量Markdown翻译.py",
    "chars": 11185,
    "preview": "import glob, time, os, re\nfrom utils.toolbox import update_ui, trimmed_format_exc, gen_time_str, disable_auto_promotion\n"
  },
  {
    "path": "crazy_functions/批量总结PDF文档.py",
    "chars": 7937,
    "preview": "from utils.toolbox import update_ui, promote_file_to_downloadzone, gen_time_str\nfrom utils.toolbox import CatchException"
  },
  {
    "path": "crazy_functions/批量总结PDF文档pdfminer.py",
    "chars": 6495,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file\nfr"
  },
  {
    "path": "crazy_functions/批量翻译PDF文档_多线程.py",
    "chars": 8277,
    "preview": "from utils.toolbox import CatchException, report_execption, write_results_to_file\nfrom utils.toolbox import update_ui, p"
  },
  {
    "path": "crazy_functions/数学动画生成manim.py",
    "chars": 5821,
    "preview": "from utils.toolbox import CatchException, update_ui, gen_time_str\nfrom .crazy_utils import request_gpt_model_in_new_thre"
  },
  {
    "path": "crazy_functions/理解PDF文档内容.py",
    "chars": 5529,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption\nfrom .crazy_utils import "
  },
  {
    "path": "crazy_functions/生成函数注释.py",
    "chars": 2592,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file\nfr"
  },
  {
    "path": "crazy_functions/联网的ChatGPT.py",
    "chars": 4091,
    "preview": "from utils.toolbox import CatchException, update_ui\nfrom .crazy_utils import request_gpt_model_in_new_thread_with_ui_ali"
  },
  {
    "path": "crazy_functions/联网的ChatGPT_bing版.py",
    "chars": 4015,
    "preview": "from utils.toolbox import CatchException, update_ui\nfrom .crazy_utils import request_gpt_model_in_new_thread_with_ui_ali"
  },
  {
    "path": "crazy_functions/虚空终端.py",
    "chars": 4557,
    "preview": "from toolbox import CatchException, update_ui, gen_time_str\nfrom .crazy_utils import request_gpt_model_in_new_thread_wit"
  },
  {
    "path": "crazy_functions/解析JupyterNotebook.py",
    "chars": 5830,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file\nfa"
  },
  {
    "path": "crazy_functions/解析项目源代码.py",
    "chars": 18840,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file\nfr"
  },
  {
    "path": "crazy_functions/询问多个大语言模型.py",
    "chars": 2608,
    "preview": "from utils.toolbox import CatchException, update_ui\nfrom .crazy_utils import request_gpt_model_in_new_thread_with_ui_ali"
  },
  {
    "path": "crazy_functions/语音助手.py",
    "chars": 8047,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, get_conf, markdown_convertion\nfrom crazy_f"
  },
  {
    "path": "crazy_functions/读文章写摘要.py",
    "chars": 3417,
    "preview": "from utils.toolbox import update_ui\nfrom utils.toolbox import CatchException, report_execption, write_results_to_file\nfr"
  },
  {
    "path": "crazy_functions/谷歌检索小助手.py",
    "chars": 4401,
    "preview": "from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive\nfrom utils.toolbox import CatchException, report_"
  },
  {
    "path": "crazy_functions/辅助回答.py",
    "chars": 965,
    "preview": "# encoding: utf-8\n# @Time   : 2023/4/19\n# @Author : Spike\n# @Descr   :\nfrom utils.toolbox import update_ui\nfrom utils.to"
  },
  {
    "path": "crazy_functions/高级功能函数模板.py",
    "chars": 1684,
    "preview": "from utils.toolbox import CatchException, update_ui\nfrom .crazy_utils import request_gpt_model_in_new_thread_with_ui_ali"
  },
  {
    "path": "gradio_demo.py",
    "chars": 21944,
    "preview": "from model_cards.autoback import AutoBackend\nimport argparse\nimport os\nimport platform\nimport sys\nfrom pathlib import Pa"
  },
  {
    "path": "llm_cards/bridge_all.py",
    "chars": 11808,
    "preview": "\n\"\"\"\n    该文件中主要包含2个函数，是所有LLM的通用接口，它们会继续向下调用更底层的LLM模型，处理多模型并行等细节\n\n    不具备多线程能力的函数：正常对话时使用，具备完备的交互功能，不可多线程\n    1. predict("
  },
  {
    "path": "llm_cards/bridge_chatglm.py",
    "chars": 11742,
    "preview": "\nfrom transformers import AutoModel, AutoTokenizer\nimport time\nimport threading\nimport importlib\nfrom utils.toolbox impo"
  },
  {
    "path": "llm_cards/bridge_chatgpt.py",
    "chars": 18381,
    "preview": "# 借鉴了 https://github.com/GaiZhenbiao/ChuanhuChatGPT 项目\n\n\"\"\"\n    该文件中主要包含三个函数\n\n    不具备多线程能力的函数：\n    1. predict: 正常对话时使用，具"
  },
  {
    "path": "llm_cards/bridge_stackclaude.py",
    "chars": 10254,
    "preview": "#from llm_.bridge_newbing import preprocess_newbing_out, preprocess_newbing_out_simple\nfrom multiprocessing import Proce"
  },
  {
    "path": "llm_cards/core_functional.py",
    "chars": 4748,
    "preview": "# 'primary' 颜色对应 theme.py 中的 primary_hue\n# 'secondary' 颜色对应 theme.py 中的 neutral_hue\n# 'stop' 颜色对应 theme.py 中的 color_er\n#"
  },
  {
    "path": "llm_cards/crazy_functional.py",
    "chars": 15649,
    "preview": "from utils.toolbox import HotReload  # HotReload 的意思是热更新，修改函数插件后，不需要重启程序，代码直接生效\n\n\ndef get_crazy_functions():\n    #######"
  },
  {
    "path": "llm_cards/requirements_chatglm.txt",
    "chars": 78,
    "preview": "protobuf\ntransformers==4.27.1\ncpm_kernels\ntorch>=1.10\nmdtex2html\nsentencepiece"
  },
  {
    "path": "llm_cards/requirements_slackclaude.txt",
    "chars": 17,
    "preview": "slack-sdk==3.21.3"
  },
  {
    "path": "model_cards/Tag2Text/MANIFEST.in",
    "chars": 82,
    "preview": "include ram/configs/*.json\ninclude ram/configs/swin/*.json\ninclude ram/data/*.txt\n"
  },
  {
    "path": "model_cards/Tag2Text/batch_inference.py",
    "chars": 13685,
    "preview": "from argparse import ArgumentParser\nfrom pathlib import Path\nfrom typing import Dict, List, Optional, TextIO, Tuple\n\nimp"
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_common_214/imgs/.gitkeep",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_common_214/openimages_common_214_ram_annots.txt",
    "chars": 1652767,
    "preview": "test/0000c64e1253d68f,car\ntest/0002ab0af02e4a77,flower\ntest/000411001ff7dd4f,chicken\ntest/00045d609ca3f4eb,pumpkin,hallo"
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_common_214/openimages_common_214_ram_taglist.txt",
    "chars": 1685,
    "preview": "accident\naccordion\nplane\nairport\nantelope\napple\nart gallery\neggplant\nauditorium\nautumn\nbaboon\nbackpack\nbakery\nbamboo\nban"
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_common_214/openimages_common_214_tag2text_idannots.txt",
    "chars": 1584452,
    "preview": "test/0000c64e1253d68f,2317\ntest/0002ab0af02e4a77,1141\ntest/000411001ff7dd4f,147\ntest/00045d609ca3f4eb,2035,612\ntest/0007"
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_common_214/openimages_common_214_tag2text_tagidlist.txt",
    "chars": 987,
    "preview": "3\n8\n16\n19\n21\n33\n44\n50\n58\n61\n71\n77\n84\n96\n117\n139\n142\n147\n180\n200\n202\n206\n244\n267\n317\n321\n347\n361\n380\n387\n398\n407\n471\n486\n"
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_rare_200/imgs/.gitkeep",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_rare_200/openimages_rare_200_ram_annots.txt",
    "chars": 857206,
    "preview": "test/0000c64e1253d68f,Auto racing\ntest/0002cc8afaf1b611,Residential area\ntest/0003d84e0165d630,Lawn game\ntest/00045d609c"
  },
  {
    "path": "model_cards/Tag2Text/datasets/openimages_rare_200/openimages_rare_200_ram_taglist.txt",
    "chars": 2414,
    "preview": "Aerial photography\nAircraft engine\nAle\nAloe\nAmphibian\nAngling\nAnole\nAntique car\nArcade game\nArthropod\nAssault rifle\nAthl"
  },
  {
    "path": "model_cards/Tag2Text/inference_ram.py",
    "chars": 1486,
    "preview": "'''\n * The Recognize Anything Model (RAM)\n * Written by Xinyu Huang\n'''\nimport argparse\nimport numpy as np\nimport random"
  },
  {
    "path": "model_cards/Tag2Text/inference_ram_openset.py",
    "chars": 1989,
    "preview": "'''\n * The Recognize Anything Model (RAM) inference on unseen classes\n * Written by Xinyu Huang\n'''\nimport argparse\nimpo"
  },
  {
    "path": "model_cards/Tag2Text/inference_tag2text.py",
    "chars": 2213,
    "preview": "'''\n * The Tag2Text Model\n * Written by Xinyu Huang\n'''\nimport argparse\nimport numpy as np\nimport random\n\nimport torch\n\n"
  },
  {
    "path": "model_cards/Tag2Text/ram/__init__.py",
    "chars": 117,
    "preview": "from .inference import inference_tag2text, inference_ram, inference_ram_openset\nfrom .transform import get_transform\n"
  },
  {
    "path": "model_cards/Tag2Text/ram/configs/med_config.json",
    "chars": 524,
    "preview": "{\n    \"architectures\": [\n      \"BertModel\"\n    ],\n    \"attention_probs_dropout_prob\": 0.1,\n    \"hidden_act\": \"gelu\",\n   "
  },
  {
    "path": "model_cards/Tag2Text/ram/configs/q2l_config.json",
    "chars": 557,
    "preview": "{\n    \"architectures\": [\n      \"BertModel\"\n    ],\n    \"attention_probs_dropout_prob\": 0.1,\n    \"hidden_act\": \"gelu\",\n   "
  },
  {
    "path": "model_cards/Tag2Text/ram/configs/swin/config_swinB_384.json",
    "chars": 230,
    "preview": "{\n    \"ckpt\": \"pretrain_model/swin_base_patch4_window7_224_22k.pth\",\n    \"vision_width\": 1024,\n    \"image_res\": 384,\n   "
  },
  {
    "path": "model_cards/Tag2Text/ram/configs/swin/config_swinL_384.json",
    "chars": 233,
    "preview": "{\n    \"ckpt\": \"pretrain_model/swin_large_patch4_window12_384_22k.pth\",\n    \"vision_width\": 1536,\n    \"image_res\": 384,\n "
  },
  {
    "path": "model_cards/Tag2Text/ram/data/ram_tag_list.txt",
    "chars": 41904,
    "preview": "3D CG rendering\n3D glasses\nabacus\nabalone\nmonastery\nbelly\nacademy\naccessory\naccident\naccordion\nacorn\nacrylic paint\nact\na"
  },
  {
    "path": "model_cards/Tag2Text/ram/data/ram_tag_list_chinese.txt",
    "chars": 19597,
    "preview": "三维CG渲染 \n3d眼镜\n算盘 \n鲍鱼 \n修道院 \n肚子 \n学院 \n附件 \n事故 \n手风琴 \n橡子 \n丙烯颜料\n表演\n行动 \n动作电影 \n活动 \n演员 \n改编本\n添加 \n胶带 \n调整 \n成人 \n冒险 \n广告 \n天线 \n有氧运动 \n喷雾罐\n爆"
  },
  {
    "path": "model_cards/Tag2Text/ram/data/ram_tag_list_threshold.txt",
    "chars": 22016,
    "preview": "0.65\n0.65\n0.65\n0.65\n0.65\n0.65\n0.65\n0.8\n0.71\n0.75\n0.65\n0.65\n0.65\n0.8\n0.65\n0.8\n0.8\n0.65\n0.65\n0.65\n0.65\n0.8\n0.65\n0.8\n0.8\n0."
  },
  {
    "path": "model_cards/Tag2Text/ram/data/tag_list.txt",
    "chars": 29062,
    "preview": "tennis\nbear cub\nobservatory\nbicycle\nhillside\njudge\nwatercolor illustration\ngranite\nlobster\nlivery\nstone\nceramic\nranch\ncl"
  },
  {
    "path": "model_cards/Tag2Text/ram/inference.py",
    "chars": 1401,
    "preview": "'''\n * The Inference of RAM and Tag2Text Models\n * Written by Xinyu Huang\n'''\nimport torch\n\n\ndef inference_tag2text(imag"
  },
  {
    "path": "model_cards/Tag2Text/ram/models/__init__.py",
    "chars": 52,
    "preview": "from .ram import ram\nfrom .tag2text import tag2text\n"
  },
  {
    "path": "model_cards/Tag2Text/ram/models/bert.py",
    "chars": 45130,
    "preview": "'''\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
  },
  {
    "path": "model_cards/Tag2Text/ram/models/ram.py",
    "chars": 10865,
    "preview": "'''\n * The Recognize Anything Model (RAM)\n * Written by Xinyu Huang\n'''\nimport json\nimport warnings\n\nimport numpy as np\n"
  },
  {
    "path": "model_cards/Tag2Text/ram/models/swin_transformer.py",
    "chars": 26827,
    "preview": "# --------------------------------------------------------\n# Swin Transformer\n# Copyright (c) 2021 Microsoft\n# Licensed "
  },
  {
    "path": "model_cards/Tag2Text/ram/models/tag2text.py",
    "chars": 14787,
    "preview": "'''\n * The Tag2Text Model\n * Written by Xinyu Huang\n'''\nimport numpy as np\nimport json\nimport torch\nimport warnings\n\nfro"
  },
  {
    "path": "model_cards/Tag2Text/ram/models/utils.py",
    "chars": 12958,
    "preview": "import os\nimport json\nimport torch\nimport math\n\nfrom torch import nn\nfrom typing import List\nfrom transformers import Be"
  },
  {
    "path": "model_cards/Tag2Text/ram/models/vit.py",
    "chars": 14240,
    "preview": "'''\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
  },
  {
    "path": "model_cards/Tag2Text/ram/transform.py",
    "chars": 316,
    "preview": "from torchvision.transforms import Normalize, Compose, Resize, ToTensor\n\n\ndef get_transform(image_size=384):\n    return "
  },
  {
    "path": "model_cards/Tag2Text/ram/utils/__init__.py",
    "chars": 94,
    "preview": "from .metrics import get_mAP, get_PR\nfrom .openset_utils import build_openset_label_embedding\n"
  },
  {
    "path": "model_cards/Tag2Text/ram/utils/metrics.py",
    "chars": 3222,
    "preview": "from typing import List, Tuple\n\nimport numpy as np\nfrom numpy import ndarray\n\n\ndef get_mAP(\n    preds: ndarray,\n    gt_f"
  },
  {
    "path": "model_cards/Tag2Text/ram/utils/openset_utils.py",
    "chars": 6951,
    "preview": "\n\n\nimport torch\nimport torch.nn as nn\nfrom clip import clip\n\n\ndef article(name):\n    return \"an\" if name[0] in \"aeiou\" e"
  },
  {
    "path": "model_cards/Tag2Text/requirements_groundingDINO.txt",
    "chars": 135,
    "preview": "timm==0.4.12\ntransformers==4.15.0\nfairscale==0.4.4\npycocoevalcap\ntorch\ntorchvision\nPillow\nscipy\ngit+https://github.com/o"
  },
  {
    "path": "model_cards/Tag2Text/setup.cfg",
    "chars": 253,
    "preview": "[metadata]\nname = recognize-anything\nversion = 0.0.1\ndescription = Recognize Anything Model and Tag2Text Model\n\n[options"
  },
  {
    "path": "model_cards/Tag2Text/setup.py",
    "chars": 37,
    "preview": "import setuptools\nsetuptools.setup()\n"
  },
  {
    "path": "model_cards/autoback.py",
    "chars": 19182,
    "preview": "import torch\nimport json\nimport math\nimport platform\nimport warnings\nfrom collections import OrderedDict, namedtuple\nfro"
  },
  {
    "path": "model_cards/groundingdino/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "model_cards/groundingdino/config/GroundingDINO_SwinB.cfg.py",
    "chars": 1007,
    "preview": "batch_size = 1\nmodelname = \"groundingdino\"\nbackbone = \"swin_B_384_22k\"\nposition_embedding = \"sine\"\npe_temperatureH = 20\n"
  },
  {
    "path": "model_cards/groundingdino/config/GroundingDINO_SwinT_OGC.py",
    "chars": 1006,
    "preview": "batch_size = 1\nmodelname = \"groundingdino\"\nbackbone = \"swin_T_224_1k\"\nposition_embedding = \"sine\"\npe_temperatureH = 20\np"
  },
  {
    "path": "model_cards/groundingdino/datasets/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "model_cards/groundingdino/datasets/transforms.py",
    "chars": 9711,
    "preview": "# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\"\"\"\nTransforms and data augmentation for both ima"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/__init__.py",
    "chars": 823,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/backbone/__init__.py",
    "chars": 37,
    "preview": "from .backbone import build_backbone\n"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/backbone/backbone.py",
    "chars": 7972,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/backbone/position_encoding.py",
    "chars": 6866,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/backbone/swin_transformer.py",
    "chars": 29339,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/bertwarper.py",
    "chars": 12242,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn.h",
    "chars": 1883,
    "preview": "/*!\n**************************************************************************************************\n* Deformable DETR"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cpu.cpp",
    "chars": 1311,
    "preview": "/*!\n**************************************************************************************************\n* Deformable DETR"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cpu.h",
    "chars": 1194,
    "preview": "/*!\n**************************************************************************************************\n* Deformable DETR"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cuda.cu",
    "chars": 7367,
    "preview": "/*!\n**************************************************************************************************\n* Deformable DETR"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cuda.h",
    "chars": 1195,
    "preview": "/*!\n**************************************************************************************************\n* Deformable DETR"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_im2col_cuda.cuh",
    "chars": 54694,
    "preview": "/*!\n**************************************************************************\n* Deformable DETR\n* Copyright (c) 2020 Se"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/cuda_version.cu",
    "chars": 140,
    "preview": "#include <cuda_runtime_api.h>\n\nnamespace groundingdino {\nint get_cudart_version() {\n  return CUDART_VERSION;\n}\n} // name"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/csrc/vision.cpp",
    "chars": 1419,
    "preview": "// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\n#include \"MsDeformAttn/ms_deform_attn.h\"\n\nnames"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/fuse_modules.py",
    "chars": 11825,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/groundingdino.py",
    "chars": 16702,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/ms_deform_attn.py",
    "chars": 15482,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/transformer.py",
    "chars": 36805,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/transformer_vanilla.py",
    "chars": 4020,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/GroundingDINO/utils.py",
    "chars": 10087,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/__init__.py",
    "chars": 754,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/models/registry.py",
    "chars": 2143,
    "preview": "# ------------------------------------------------------------------------\n# Grounding DINO\n# url: https://github.com/ID"
  },
  {
    "path": "model_cards/groundingdino/util/__init__.py",
    "chars": 71,
    "preview": "# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n"
  },
  {
    "path": "model_cards/groundingdino/util/box_ops.py",
    "chars": 3905,
    "preview": "# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\"\"\"\nUtilities for bounding box manipulation and G"
  },
  {
    "path": "model_cards/groundingdino/util/get_tokenlizer.py",
    "chars": 1157,
    "preview": "from transformers import AutoTokenizer, BertModel, BertTokenizer, RobertaModel, RobertaTokenizerFast\n\n\ndef get_tokenlize"
  },
  {
    "path": "model_cards/groundingdino/util/inference.py",
    "chars": 7997,
    "preview": "from typing import Tuple, List\n\nimport cv2\nimport numpy as np\nimport supervision as sv\nimport torch\nfrom PIL import Imag"
  },
  {
    "path": "model_cards/groundingdino/util/logger.py",
    "chars": 3303,
    "preview": "# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport functools\nimport logging\nimport os\nimport "
  },
  {
    "path": "model_cards/groundingdino/util/misc.py",
    "chars": 23348,
    "preview": "# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\"\"\"\nMisc functions, including distributed helpers"
  },
  {
    "path": "model_cards/groundingdino/util/slconfig.py",
    "chars": 14380,
    "preview": "# ==========================================================\n# Modified from mmcv\n# ===================================="
  },
  {
    "path": "model_cards/groundingdino/util/slio.py",
    "chars": 5377,
    "preview": "# ==========================================================\n# Modified from mmcv\n# ===================================="
  },
  {
    "path": "model_cards/groundingdino/util/time_counter.py",
    "chars": 1567,
    "preview": "import json\nimport time\n\n\nclass TimeCounter:\n    def __init__(self) -> None:\n        pass\n\n    def clear(self):\n        "
  },
  {
    "path": "model_cards/groundingdino/util/utils.py",
    "chars": 17712,
    "preview": "import argparse\nimport json\nimport warnings\nfrom collections import OrderedDict\nfrom copy import deepcopy\nfrom typing im"
  },
  {
    "path": "model_cards/groundingdino/util/visualizer.py",
    "chars": 12047,
    "preview": "# -*- coding: utf-8 -*-\n\"\"\"\n@File    :   visualizer.py\n@Time    :   2022/04/05 11:39:33\n@Author  :   Shilong Liu \n@Conta"
  },
  {
    "path": "model_cards/groundingdino/util/vl_utils.py",
    "chars": 3489,
    "preview": "import os\nimport random\nfrom typing import List\n\nimport torch\n\n\ndef create_positive_map_from_span(tokenized, token_span,"
  },
  {
    "path": "model_cards/groundingdino/version.py",
    "chars": 22,
    "preview": "__version__ = '0.1.0'\n"
  },
  {
    "path": "model_cards/lama/.gitignore",
    "chars": 1865,
    "preview": "# Byte-compiled / optimized / DLL files\n__pycache__/\n*.py[cod]\n*$py.class\n\n# C extensions\n*.so\n\n# Distribution / packagi"
  },
  {
    "path": "model_cards/lama/LICENSE",
    "chars": 11348,
    "preview": "                                 Apache License\n                           Version 2.0, January 2004\n                   "
  },
  {
    "path": "model_cards/lama/README.md",
    "chars": 16548,
    "preview": "# 🦙 LaMa: Resolution-robust Large Mask Inpainting with Fourier Convolutions\n\nby Roman Suvorov, Elizaveta Logacheva, Anto"
  },
  {
    "path": "model_cards/lama/bin/analyze_errors.py",
    "chars": 17698,
    "preview": "#!/usr/bin/env python3\nimport cv2\nimport numpy as np\nimport sklearn\nimport torch\nimport os\nimport pickle\nimport pandas a"
  },
  {
    "path": "model_cards/lama/bin/blur_predicts.py",
    "chars": 2191,
    "preview": "#!/usr/bin/env python3\n\nimport os\n\nimport cv2\nimport numpy as np\nimport tqdm\n\nfrom saicinpainting.evaluation.data import"
  },
  {
    "path": "model_cards/lama/bin/calc_dataset_stats.py",
    "chars": 3627,
    "preview": "#!/usr/bin/env python3\n\nimport os\n\nimport numpy as np\nimport tqdm\nfrom scipy.ndimage.morphology import distance_transfor"
  },
  {
    "path": "model_cards/lama/bin/debug/analyze_overlapping_masks.sh",
    "chars": 1132,
    "preview": "#!/bin/bash\n\nBASEDIR=\"$(dirname $0)\"\n\n# paths are valid for mml7\n\n# select images\n#ls /data/inpainting/work/data/train |"
  },
  {
    "path": "model_cards/lama/bin/evaluate_predicts.py",
    "chars": 3530,
    "preview": "#!/usr/bin/env python3\n\nimport os\n\nimport pandas as pd\n\nfrom saicinpainting.evaluation.data import PrecomputedInpainting"
  },
  {
    "path": "model_cards/lama/bin/evaluator_example.py",
    "chars": 2359,
    "preview": "import os\n\nimport cv2\nimport numpy as np\nimport torch\nfrom skimage import io\nfrom skimage.transform import resize\nfrom t"
  },
  {
    "path": "model_cards/lama/bin/extract_masks.py",
    "chars": 1627,
    "preview": "import PIL.Image as Image\nimport numpy as np\nimport os\n\n\ndef main(args):\n    if not args.indir.endswith('/'):\n        ar"
  },
  {
    "path": "model_cards/lama/bin/filter_sharded_dataset.py",
    "chars": 2346,
    "preview": "#!/usr/bin/env python3\n\n\nimport math\nimport os\nimport random\n\nimport braceexpand\nimport webdataset as wds\n\nDEFAULT_CATS_"
  },
  {
    "path": "model_cards/lama/bin/gen_debug_mask_dataset.py",
    "chars": 1909,
    "preview": "#!/usr/bin/env python3\n\nimport glob\nimport os\n\nimport PIL.Image as Image\nimport cv2\nimport numpy as np\nimport tqdm\nimpor"
  },
  {
    "path": "model_cards/lama/bin/gen_mask_dataset.py",
    "chars": 5609,
    "preview": "#!/usr/bin/env python3\n\nimport glob\nimport os\nimport shutil\nimport traceback\n\nimport PIL.Image as Image\nimport numpy as "
  },
  {
    "path": "model_cards/lama/bin/gen_mask_dataset_hydra.py",
    "chars": 5340,
    "preview": "#!/usr/bin/env python3\n\nimport glob\nimport os\nimport shutil\nimport traceback\nimport hydra\nfrom omegaconf import OmegaCon"
  },
  {
    "path": "model_cards/lama/bin/gen_outpainting_dataset.py",
    "chars": 3226,
    "preview": "#!/usr/bin/env python3\nimport glob\nimport logging\nimport os\nimport shutil\nimport sys\nimport traceback\n\nfrom saicinpainti"
  },
  {
    "path": "model_cards/lama/bin/make_checkpoint.py",
    "chars": 3097,
    "preview": "#!/usr/bin/env python3\n\nimport os\nimport shutil\n\nimport torch\n\n\ndef get_checkpoint_files(s):\n    s = s.strip()\n    if ',"
  },
  {
    "path": "model_cards/lama/bin/mask_example.py",
    "chars": 466,
    "preview": "import matplotlib.pyplot as plt\nfrom skimage import io\nfrom skimage.transform import resize\n\nfrom saicinpainting.evaluat"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/blur_tests.sh",
    "chars": 1491,
    "preview": "##!/usr/bin/env bash\n#\n## !!! file set to make test_large_30k from the vanilla test_large: configs/test_large_30k.lst\n#\n"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/env.sh",
    "chars": 170,
    "preview": "DIRNAME=\"$(dirname $0)\"\nDIRNAME=\"$(realpath \"\"$DIRNAME\"\")\"\n\nBINDIR=\"$DIRNAME/..\"\nSRCDIR=\"$BINDIR/..\"\nCONFIGDIR=\"$SRCDIR/"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/find_best_checkpoint.py",
    "chars": 2075,
    "preview": "#!/usr/bin/env python3\n\n\nimport os\nfrom argparse import ArgumentParser\n\n\ndef ssim_fid100_f1(metrics, fid_scale=100):\n   "
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/generate_test_celeba-hq.sh",
    "chars": 603,
    "preview": "#!/usr/bin/env bash\n\n# paths to data are valid for mml-ws01\nOUT_DIR=\"/media/inpainting/paper_data/CelebA-HQ_val_test\"\n\ns"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/generate_test_ffhq.sh",
    "chars": 580,
    "preview": "#!/usr/bin/env bash\n\n# paths to data are valid for mml-ws01\nOUT_DIR=\"/media/inpainting/paper_data/FFHQ_val\"\n\nsource \"$(d"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/generate_test_paris.sh",
    "chars": 593,
    "preview": "#!/usr/bin/env bash\n\n# paths to data are valid for mml-ws01\nOUT_DIR=\"/media/inpainting/paper_data/Paris_StreetView_Datas"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/generate_test_paris_256.sh",
    "chars": 598,
    "preview": "#!/usr/bin/env bash\n\n# paths to data are valid for mml-ws01\nOUT_DIR=\"/media/inpainting/paper_data/Paris_StreetView_Datas"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/generate_val_test.sh",
    "chars": 1045,
    "preview": "#!/usr/bin/env bash\n\n# !!! file set to make test_large_30k from the vanilla test_large: configs/test_large_30k.lst\n\n# pa"
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/predict_inner_features.sh",
    "chars": 841,
    "preview": "#!/usr/bin/env bash\n\n# paths to data are valid for mml7\n\nsource \"$(dirname $0)/env.sh\"\n\n\"$BINDIR/predict_inner_features."
  },
  {
    "path": "model_cards/lama/bin/paper_runfiles/update_test_data_stats.sh",
    "chars": 927,
    "preview": "#!/usr/bin/env bash\n\n# paths to data are valid for mml7\n\nsource \"$(dirname $0)/env.sh\"\n\n#INDIR=\"/data/inpainting/paper_d"
  },
  {
    "path": "model_cards/lama/bin/predict.py",
    "chars": 4092,
    "preview": "#!/usr/bin/env python3\n\n# Example command:\n# ./bin/predict.py \\\n#       model.path=<path to checkpoint, prepared by make"
  },
  {
    "path": "model_cards/lama/bin/predict_inner_features.py",
    "chars": 4938,
    "preview": "#!/usr/bin/env python3\n\n# Example command:\n# ./bin/predict.py \\\n#       model.path=<path to checkpoint, prepared by make"
  },
  {
    "path": "model_cards/lama/bin/report_from_tb.py",
    "chars": 2588,
    "preview": "#!/usr/bin/env python3\n\nimport glob\nimport os\nimport re\n\nimport tensorflow as tf\nfrom torch.utils.tensorboard import Sum"
  },
  {
    "path": "model_cards/lama/bin/sample_from_dataset.py",
    "chars": 3044,
    "preview": "#!/usr/bin/env python3\n\nimport os\n\nimport numpy as np\nimport tqdm\nfrom skimage import io\nfrom skimage.segmentation impor"
  },
  {
    "path": "model_cards/lama/bin/side_by_side.py",
    "chars": 2826,
    "preview": "#!/usr/bin/env python3\nimport os\nimport random\n\nimport cv2\nimport numpy as np\n\nfrom saicinpainting.evaluation.data impor"
  },
  {
    "path": "model_cards/lama/bin/split_tar.py",
    "chars": 470,
    "preview": "#!/usr/bin/env python3\n\n\nimport tqdm\nimport webdataset as wds\n\n\ndef main(args):\n    input_dataset = wds.Dataset(args.inf"
  },
  {
    "path": "model_cards/lama/bin/to_jit.py",
    "chars": 2155,
    "preview": "import os\nfrom pathlib import Path\n\nimport hydra\nimport torch\nimport yaml\nfrom omegaconf import OmegaConf\nfrom torch imp"
  },
  {
    "path": "model_cards/lama/bin/train.py",
    "chars": 2609,
    "preview": "#!/usr/bin/env python3\n\nimport logging\nimport os\nimport sys\nimport traceback\n\nos.environ['OMP_NUM_THREADS'] = '1'\nos.env"
  },
  {
    "path": "model_cards/lama/colab/LaMa_inpainting.ipynb",
    "chars": 4656214,
    "preview": "{\n  \"cells\": [\n    {\n      \"cell_type\": \"markdown\",\n      \"metadata\": {\n        \"id\": \"_pRpIwnaOnb3\"\n      },\n      \"sou"
  }
]

// ... and 207 more files (download for full content)