Full Code of OpenGVLab/InternVL for AI

gitextract_i3i5r_p7/

├── .flake8
├── .github/
│   ├── CONTRIBUTING.md
│   └── ISSUE_TEMPLATE/
│       ├── 1-bug-report.yml
│       ├── 2-feature-request.yml
│       └── 3-documentation.yml
├── .gitignore
├── .isort.cfg
├── .pre-commit-config.yaml
├── INSTALLATION.md
├── LICENSE
├── README.md
├── README_zh.md
├── classification/
│   ├── README.md
│   ├── config.py
│   ├── configs/
│   │   ├── attn_pooling_probing/
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224_64gpu.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_a.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_r.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_real.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_sketch.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenetv2.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224to448_64gpu.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_a.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_r.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_real.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_sketch.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenetv2.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_a.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_r.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_real.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_sketch.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenetv2.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_a.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_r.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_real.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_sketch.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenetv2.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_a.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_r.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_real.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_sketch.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenetv2.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_a.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_r.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_real.yaml
│   │   │   ├── attn_pooling_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_sketch.yaml
│   │   │   └── attn_pooling_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenetv2.yaml
│   │   ├── intern_vit_6b_1k_224.yaml
│   │   ├── intern_vit_6b_1k_224_test_imagenet_a.yaml
│   │   ├── intern_vit_6b_1k_224_test_imagenet_r.yaml
│   │   ├── intern_vit_6b_1k_224_test_imagenet_real.yaml
│   │   ├── intern_vit_6b_1k_224_test_imagenet_sketch.yaml
│   │   ├── intern_vit_6b_1k_224_test_imagenetv2.yaml
│   │   └── linear_probing/
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224_64gpu.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_a.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_r.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_real.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_sketch.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenetv2.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224to448_64gpu.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_a.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_r.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_real.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenet_sketch.yaml
│   │       ├── linear_probing_intern_vit_6b_224px_in1k_224to448_64gpu_imagenetv2.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_a.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_r.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_real.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_sketch.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenetv2.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_a.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_r.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_real.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_sketch.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenetv2.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_a.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_r.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_real.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_sketch.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenetv2.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_a.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_r.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_real.yaml
│   │       ├── linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_sketch.yaml
│   │       └── linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenetv2.yaml
│   ├── dataset/
│   │   ├── __init__.py
│   │   ├── build.py
│   │   ├── cached_image_folder.py
│   │   ├── imagenet_a_r_indices.py
│   │   ├── imagenet_real.py
│   │   ├── imagenetv2.py
│   │   ├── samplers.py
│   │   └── zipreader.py
│   ├── ddp_hooks.py
│   ├── gflops.py
│   ├── hf2pytorch.py
│   ├── logger.py
│   ├── lr_scheduler.py
│   ├── main.py
│   ├── meta_data/
│   │   ├── 22k_class_to_idx.json
│   │   ├── imagenet_classes.json
│   │   ├── map22kto1k.txt
│   │   └── real.json
│   ├── models/
│   │   ├── __init__.py
│   │   ├── build.py
│   │   ├── clip_vit.py
│   │   ├── flash_attention.py
│   │   └── intern_vit_6b.py
│   ├── optimizer.py
│   ├── train_in1k.sh
│   ├── utils.py
│   └── work_dirs/
│       └── intern_vit_6b_1k_224/
│           └── log_rank0.txt
├── clip_benchmark/
│   ├── AUTHORS.rst
│   ├── CONTRIBUTING.rst
│   ├── HISTORY.rst
│   ├── LICENSE
│   ├── MANIFEST.in
│   ├── Makefile
│   ├── README.md
│   ├── benchmark/
│   │   ├── README.md
│   │   ├── benchmark.csv
│   │   ├── dataset_type.csv
│   │   ├── datasets.txt
│   │   ├── datasets_multilingual.txt
│   │   ├── models.txt
│   │   ├── results.ipynb
│   │   └── webdatasets.txt
│   ├── clip_benchmark/
│   │   ├── __init__.py
│   │   ├── cli.py
│   │   ├── datasets/
│   │   │   ├── __init__.py
│   │   │   ├── ar_classnames.json
│   │   │   ├── ar_zeroshot_classification_templates.json
│   │   │   ├── birdsnap.py
│   │   │   ├── builder.py
│   │   │   ├── caltech101.py
│   │   │   ├── cn_classnames.json
│   │   │   ├── cn_zeroshot_classification_templates.json
│   │   │   ├── cupl_prompts.json
│   │   │   ├── en_classnames.json
│   │   │   ├── en_zeroshot_classification_templates.json
│   │   │   ├── flickr.py
│   │   │   ├── imagenetv2.py
│   │   │   ├── it_classnames.json
│   │   │   ├── it_zeroshot_classification_templates.json
│   │   │   ├── jp_classnames.json
│   │   │   ├── jp_zeroshot_classification_templates.json
│   │   │   ├── kitti.py
│   │   │   ├── multilingual_mscoco.py
│   │   │   ├── objectnet.py
│   │   │   ├── tfds.py
│   │   │   ├── tools.py
│   │   │   └── voc2007.py
│   │   ├── metrics/
│   │   │   ├── __init__.py
│   │   │   ├── linear_probe.py
│   │   │   ├── mscoco_generative.py
│   │   │   ├── zeroshot_classification.py
│   │   │   └── zeroshot_retrieval.py
│   │   ├── model_collection.py
│   │   ├── models/
│   │   │   ├── __init__.py
│   │   │   ├── intern_vit_6b/
│   │   │   │   ├── configuration_intern_vit.py
│   │   │   │   ├── flash_attention.py
│   │   │   │   └── modeling_intern_vit.py
│   │   │   ├── internvl.py
│   │   │   ├── internvl_c_pytorch/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── chinese_alpaca_lora_7b/
│   │   │   │   │   ├── config.json
│   │   │   │   │   ├── generation_config.json
│   │   │   │   │   ├── pytorch_model.bin.index.json
│   │   │   │   │   ├── special_tokens_map.json
│   │   │   │   │   ├── tokenizer.model
│   │   │   │   │   └── tokenizer_config.json
│   │   │   │   ├── flash_attention.py
│   │   │   │   └── internvl_c.py
│   │   │   ├── internvl_huggingface/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── configuration_intern_vit.py
│   │   │   │   ├── configuration_internvl.py
│   │   │   │   ├── flash_attention.py
│   │   │   │   ├── modeling_intern_vit.py
│   │   │   │   ├── modeling_internvl.py
│   │   │   │   └── modeling_qllama.py
│   │   │   ├── japanese_clip.py
│   │   │   └── open_clip.py
│   │   └── webdataset_builder.py
│   ├── data/
│   │   ├── birdsnap/
│   │   │   └── test_images_valid.txt
│   │   ├── flickr30k/
│   │   │   └── flickr30k_cn_test.txt
│   │   └── mscoco_captions/
│   │       └── coco-cn_test.json
│   ├── probe_benchmark/
│   │   ├── PROBES.md
│   │   ├── build_df_scaling_experiments.py
│   │   ├── clip_table_2.csv
│   │   ├── generate_table.py
│   │   ├── laion5b_fewshot_experiments.py
│   │   ├── openclip_results.csv
│   │   ├── process_vtab.py
│   │   ├── scaling_experiment_data2.json
│   │   ├── scaling_experiment_data_vtab.json
│   │   ├── scaling_experiments.py
│   │   └── scaling_plot.ipynb
│   ├── requirements-test.txt
│   ├── requirements.txt
│   ├── setup.cfg
│   ├── setup.py
│   ├── test_internvl_c_classification.sh
│   ├── test_internvl_c_imagenet.sh
│   ├── test_internvl_c_retrieval.sh
│   ├── test_internvl_c_xtd.sh
│   ├── test_internvl_g_classification.sh
│   ├── test_internvl_g_imagenet.sh
│   ├── test_internvl_g_retrieval.sh
│   ├── test_internvl_g_retrieval_finetune.sh
│   ├── test_internvl_g_xtd.sh
│   ├── tests/
│   │   └── test_clip_benchmark.py
│   └── tox.ini
├── internvl_chat/
│   ├── README.md
│   ├── eval/
│   │   ├── README.md
│   │   ├── caption/
│   │   │   ├── README.md
│   │   │   └── evaluate_caption.py
│   │   ├── domain_specific/
│   │   │   ├── drivelm/
│   │   │   │   └── evaluate.py
│   │   │   ├── mme_rw/
│   │   │   │   └── evaluate.py
│   │   │   ├── rs_det/
│   │   │   │   ├── caculate.py
│   │   │   │   └── evaluate.py
│   │   │   └── rs_vqa/
│   │   │       ├── evaluate.py
│   │   │       └── score.py
│   │   ├── llava_bench/
│   │   │   ├── README.md
│   │   │   ├── eval_gpt_review_bench.py
│   │   │   ├── evaluate_llava_bench.py
│   │   │   ├── rule.json
│   │   │   └── summarize_gpt_review.py
│   │   ├── mantis_eval/
│   │   │   ├── README.md
│   │   │   └── evaluate_mantis.py
│   │   ├── mathvista/
│   │   │   ├── README.md
│   │   │   ├── calculate_score.py
│   │   │   ├── evaluate_mathvista.py
│   │   │   ├── extract_answer.py
│   │   │   ├── prompts/
│   │   │   │   └── ext_ans.py
│   │   │   └── utilities.py
│   │   ├── mirb/
│   │   │   ├── README.md
│   │   │   └── evaluate_mirb.py
│   │   ├── mmbench/
│   │   │   ├── README.md
│   │   │   └── evaluate_mmbench.py
│   │   ├── mme/
│   │   │   ├── README.md
│   │   │   ├── Your_Results/
│   │   │   │   ├── OCR.txt
│   │   │   │   ├── artwork.txt
│   │   │   │   ├── celebrity.txt
│   │   │   │   ├── code_reasoning.txt
│   │   │   │   ├── color.txt
│   │   │   │   ├── commonsense_reasoning.txt
│   │   │   │   ├── count.txt
│   │   │   │   ├── existence.txt
│   │   │   │   ├── landmark.txt
│   │   │   │   ├── numerical_calculation.txt
│   │   │   │   ├── position.txt
│   │   │   │   ├── posters.txt
│   │   │   │   ├── scene.txt
│   │   │   │   └── text_translation.txt
│   │   │   ├── calculation.py
│   │   │   └── eval.py
│   │   ├── mmhal/
│   │   │   ├── README.md
│   │   │   ├── eval_gpt_mmhal.py
│   │   │   └── evaluate_mmhal.py
│   │   ├── mmiu/
│   │   │   ├── README.md
│   │   │   ├── evaluate_mmiu.py
│   │   │   └── mmiu.jsonl
│   │   ├── mmmu/
│   │   │   ├── README.md
│   │   │   ├── answer_dict_val.json
│   │   │   ├── data_utils.py
│   │   │   ├── eval_utils.py
│   │   │   ├── evaluate_mmmu.py
│   │   │   └── main_eval_only.py
│   │   ├── mmmu_pro/
│   │   │   ├── README.md
│   │   │   ├── evaluate.py
│   │   │   ├── evaluate_mmmu_pro.py
│   │   │   └── prompts.yaml
│   │   ├── mmvet/
│   │   │   ├── README.md
│   │   │   └── evaluate_mmvet.py
│   │   ├── mmvetv2/
│   │   │   ├── README.md
│   │   │   └── evaluate_mmvet_v2.py
│   │   ├── mmvp/
│   │   │   ├── README.md
│   │   │   └── evaluate_mmvp.py
│   │   ├── mpdocvqa/
│   │   │   ├── README.md
│   │   │   ├── evaluate_vqa.py
│   │   │   └── infographicsvqa_eval.py
│   │   ├── mvbench/
│   │   │   ├── README.md
│   │   │   └── evaluate_mvbench.py
│   │   ├── pope/
│   │   │   ├── README.md
│   │   │   ├── eval_pope.py
│   │   │   └── evaluate_pope.py
│   │   ├── refcoco/
│   │   │   ├── README.md
│   │   │   └── evaluate_grounding.py
│   │   ├── scienceqa/
│   │   │   ├── README.md
│   │   │   └── evaluate_scienceqa.py
│   │   ├── seed/
│   │   │   ├── README.md
│   │   │   ├── calculation.py
│   │   │   └── evaluate_seed.py
│   │   ├── tiny_lvlm/
│   │   │   ├── README.md
│   │   │   ├── calculate_score.py
│   │   │   ├── evaluate_lvlm.py
│   │   │   └── tools.py
│   │   └── vqa/
│   │       ├── README.md
│   │       ├── convert_gqa_for_eval.py
│   │       ├── evaluate_vqa.py
│   │       ├── infographicsvqa_eval.py
│   │       └── textvqa_eval.py
│   ├── evaluate.sh
│   ├── internvl/
│   │   ├── conversation.py
│   │   ├── dist_utils.py
│   │   ├── model/
│   │   │   ├── __init__.py
│   │   │   ├── internlm2/
│   │   │   │   ├── configuration_internlm2.py
│   │   │   │   ├── modeling_internlm2.py
│   │   │   │   ├── tokenization_internlm2.py
│   │   │   │   └── tokenization_internlm2_fast.py
│   │   │   ├── internvl_chat/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── configuration_intern_vit.py
│   │   │   │   ├── configuration_internvl_chat.py
│   │   │   │   ├── modeling_intern_vit.py
│   │   │   │   └── modeling_internvl_chat.py
│   │   │   └── phi3/
│   │   │       ├── configuration_phi3.py
│   │   │       └── modeling_phi3.py
│   │   ├── patch/
│   │   │   ├── __init__.py
│   │   │   ├── internlm2_packed_training_patch.py
│   │   │   ├── internvit_liger_monkey_patch.py
│   │   │   ├── llama2_flash_attn_monkey_patch.py
│   │   │   ├── llama_flash_attn_monkey_patch.py
│   │   │   ├── llama_packed_training_patch.py
│   │   │   ├── llama_rmsnorm_monkey_patch.py
│   │   │   ├── pad_data_collator.py
│   │   │   ├── phi3_packed_training_patch.py
│   │   │   ├── qwen2_packed_training_patch.py
│   │   │   ├── train_dataloader_patch.py
│   │   │   └── train_sampler_patch.py
│   │   └── train/
│   │       ├── __init__.py
│   │       ├── constants.py
│   │       ├── dataset.py
│   │       ├── dataset_packed.py
│   │       ├── internvl_chat_finetune.py
│   │       ├── internvl_chat_mpo.py
│   │       ├── internvl_chat_pretrain.py
│   │       └── trainer_dpo.py
│   ├── pyproject.toml
│   ├── shell/
│   │   ├── data/
│   │   │   ├── coco_caption.json
│   │   │   ├── internvl_1_2_finetune.json
│   │   │   └── internvl_1_2_finetune_custom.json
│   │   ├── internvl1.2/
│   │   │   ├── 2nd_finetune/
│   │   │   │   ├── internvl_chat_v1_2_hermes2_yi34b_448_res_2nd_finetune_full.sh
│   │   │   │   └── internvl_chat_v1_2_hermes2_yi34b_448_res_2nd_finetune_lora.sh
│   │   │   └── hermes2_yi34b/
│   │   │       └── internvl_chat_v1_2_hermes2_yi34b_448_res_finetune.sh
│   │   ├── internvl1.5/
│   │   │   ├── 2nd_finetune/
│   │   │   │   ├── internvl_chat_v1_5_internlm2_1_8b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl_chat_v1_5_internlm2_1_8b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl_chat_v1_5_internlm2_20b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl_chat_v1_5_internlm2_20b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl_chat_v1_5_phi3_3_8b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   └── internvl_chat_v1_5_phi3_3_8b_dynamic_res_2nd_finetune_lora.sh
│   │   │   ├── hermes2_yi34b/
│   │   │   │   ├── internvl_chat_v1_5_hermes2_yi34b_dynamic_res_finetune.sh
│   │   │   │   └── internvl_chat_v1_5_hermes2_yi34b_dynamic_res_pretrain.sh
│   │   │   ├── internlm2_1_8b/
│   │   │   │   ├── internvl_chat_v1_5_internlm2_1_8b_dynamic_res_finetune.sh
│   │   │   │   └── internvl_chat_v1_5_internlm2_1_8b_dynamic_res_pretrain.sh
│   │   │   ├── internlm2_20b/
│   │   │   │   ├── internvl_chat_v1_5_internlm2_20b_dynamic_res_finetune.sh
│   │   │   │   └── internvl_chat_v1_5_internlm2_20b_dynamic_res_pretrain.sh
│   │   │   └── phi3_3_8b/
│   │   │       ├── internvl_chat_v1_5_phi3_3_8b_dynamic_res_finetune.sh
│   │   │       └── internvl_chat_v1_5_phi3_3_8b_dynamic_res_pretrain.sh
│   │   ├── internvl2.0/
│   │   │   └── 2nd_finetune/
│   │   │       ├── internvl2_1b_qwen2_0_5b_dynamic_res_2nd_finetune_full.sh
│   │   │       ├── internvl2_1b_qwen2_0_5b_dynamic_res_2nd_finetune_lora.sh
│   │   │       ├── internvl2_26b_internlm2_20b_dynamic_res_2nd_finetune_full.sh
│   │   │       ├── internvl2_26b_internlm2_20b_dynamic_res_2nd_finetune_lora.sh
│   │   │       ├── internvl2_2b_internlm2_1_8b_dynamic_res_2nd_finetune_full.sh
│   │   │       ├── internvl2_2b_internlm2_1_8b_dynamic_res_2nd_finetune_lora.sh
│   │   │       ├── internvl2_2b_internlm2_1_8b_dynamic_res_2nd_finetune_lora_coco.sh
│   │   │       ├── internvl2_40b_hermes2_yi_34b_dynamic_res_2nd_finetune_full.sh
│   │   │       ├── internvl2_40b_hermes2_yi_34b_dynamic_res_2nd_finetune_lora.sh
│   │   │       ├── internvl2_4b_phi3_3_8b_dynamic_res_2nd_finetune_full.sh
│   │   │       ├── internvl2_4b_phi3_3_8b_dynamic_res_2nd_finetune_lora.sh
│   │   │       ├── internvl2_76b_hermes2_llama3_70b_dynamic_res_2nd_finetune_full.sh
│   │   │       ├── internvl2_76b_hermes2_llama3_70b_dynamic_res_2nd_finetune_lora.sh
│   │   │       ├── internvl2_8b_internlm2_7b_dynamic_res_2nd_finetune_full.sh
│   │   │       └── internvl2_8b_internlm2_7b_dynamic_res_2nd_finetune_lora.sh
│   │   ├── internvl2.0_mpo/
│   │   │   ├── README.md
│   │   │   └── preference_optimization/
│   │   │       └── internvl2_8b_internlm2_7b_dynamic_res_mpo_full.sh
│   │   ├── internvl2.5/
│   │   │   ├── 2nd_finetune/
│   │   │   │   ├── internvl2_5_1b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl2_5_1b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl2_5_26b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl2_5_26b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl2_5_2b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl2_5_2b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl2_5_2b_dynamic_res_2nd_finetune_lora_coco.sh
│   │   │   │   ├── internvl2_5_38b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl2_5_38b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl2_5_4b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl2_5_4b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl2_5_78b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl2_5_78b_dynamic_res_2nd_finetune_lora.sh
│   │   │   │   ├── internvl2_5_8b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   └── internvl2_5_8b_dynamic_res_2nd_finetune_lora.sh
│   │   │   ├── stage1/
│   │   │   │   ├── internvl2_5_1b_qwen2_5_0_5b_dynamic_res_stage1.sh
│   │   │   │   ├── internvl2_5_26b_internlm2_5_20b_dynamic_res_stage1.sh
│   │   │   │   ├── internvl2_5_2b_internlm2_5_1_8b_dynamic_res_stage1.sh
│   │   │   │   ├── internvl2_5_38b_qwen2_5_32b_dynamic_res_stage1.sh
│   │   │   │   ├── internvl2_5_4b_qwen2_5_3b_dynamic_res_stage1.sh
│   │   │   │   ├── internvl2_5_78b_qwen2_5_72b_dynamic_res_stage1.sh
│   │   │   │   └── internvl2_5_8b_internlm2_5_7b_dynamic_res_stage1.sh
│   │   │   ├── stage1.5/
│   │   │   │   ├── internvl2_5_26b_internlm2_5_20b_dynamic_res_stage1_5.sh
│   │   │   │   └── internvl2_5_8b_internlm2_5_7b_dynamic_res_stage1_5.sh
│   │   │   └── stage2/
│   │   │       ├── internvl2_5_1b_qwen2_5_0_5b_dynamic_res_stage2.sh
│   │   │       ├── internvl2_5_26b_internlm2_5_20b_dynamic_res_stage2.sh
│   │   │       ├── internvl2_5_2b_internlm2_5_1_8b_dynamic_res_stage2.sh
│   │   │       ├── internvl2_5_38b_qwen2_5_32b_dynamic_res_stage2.sh
│   │   │       ├── internvl2_5_4b_qwen2_5_3b_dynamic_res_stage2.sh
│   │   │       ├── internvl2_5_78b_qwen2_5_72b_dynamic_res_stage2.sh
│   │   │       └── internvl2_5_8b_internlm2_5_7b_dynamic_res_stage2.sh
│   │   ├── internvl2.5_mpo/
│   │   │   └── preference_optimization/
│   │   │       ├── internvl2_5_1b_qwen2_5_0_5b_dynamic_res_mpo.sh
│   │   │       ├── internvl2_5_26b_internlm2_5_20b_dynamic_res_mpo.sh
│   │   │       ├── internvl2_5_2b_internlm2_5_1_8b_dynamic_res_mpo.sh
│   │   │       ├── internvl2_5_38b_qwen2_5_32b_dynamic_res_mpo.sh
│   │   │       ├── internvl2_5_4b_qwen2_5_3b_dynamic_res_mpo.sh
│   │   │       ├── internvl2_5_78b_qwen2_5_72b_dynamic_res_mpo.sh
│   │   │       └── internvl2_5_8b_internlm2_5_7b_dynamic_res_mpo.sh
│   │   ├── internvl3.0/
│   │   │   ├── 2nd_finetune/
│   │   │   │   ├── internvl3_14b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl3_1b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl3_2b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl3_38b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl3_78b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   ├── internvl3_8b_dynamic_res_2nd_finetune_full.sh
│   │   │   │   └── internvl3_9b_dynamic_res_2nd_finetune_full.sh
│   │   │   ├── mpo/
│   │   │   │   ├── internvl3_14b_mpo.sh
│   │   │   │   ├── internvl3_1b_mpo.sh
│   │   │   │   ├── internvl3_2b_mpo.sh
│   │   │   │   ├── internvl3_38b_mpo.sh
│   │   │   │   ├── internvl3_78b_mpo.sh
│   │   │   │   ├── internvl3_8b_mpo.sh
│   │   │   │   └── internvl3_9b_mpo.sh
│   │   │   ├── mpo_data_construction/
│   │   │   │   ├── correctness_build_data.sh
│   │   │   │   └── correctness_mmpr_8b.sh
│   │   │   └── visualprm_data_construction/
│   │   │       ├── visualprm_build_data.sh
│   │   │       └── visualprm_mmpr_8b.sh
│   │   └── mini_internvl/
│   │       ├── README.md
│   │       └── domain_adaptation/
│   │           ├── internvl2_1b_qwen2_0_5b_dynamic_res_finetune_bdd.sh
│   │           ├── internvl2_1b_qwen2_0_5b_dynamic_res_finetune_drivelm.sh
│   │           ├── internvl2_1b_qwen2_0_5b_dynamic_res_finetune_medical.sh
│   │           ├── internvl2_1b_qwen2_0_5b_dynamic_res_finetune_remote.sh
│   │           ├── internvl2_2b_internlm2_1_8b_dynamic_res_finetune_bdd.sh
│   │           ├── internvl2_2b_internlm2_1_8b_dynamic_res_finetune_drivelm.sh
│   │           ├── internvl2_2b_internlm2_1_8b_dynamic_res_finetune_medical.sh
│   │           ├── internvl2_2b_internlm2_1_8b_dynamic_res_finetune_remote.sh
│   │           ├── internvl2_4b_phi3_3_8b_dynamic_res_finetune_bdd.sh
│   │           ├── internvl2_4b_phi3_3_8b_dynamic_res_finetune_drivelm.sh
│   │           ├── internvl2_4b_phi3_3_8b_dynamic_res_finetune_medical.sh
│   │           └── internvl2_4b_phi3_3_8b_dynamic_res_finetune_remote.sh
│   ├── tools/
│   │   ├── README.md
│   │   ├── convert_to_int8.py
│   │   ├── extract_mlp.py
│   │   ├── extract_video_frames.py
│   │   ├── extract_vit.py
│   │   ├── images_stitching.py
│   │   ├── internvl_custom2hf.py
│   │   ├── internvl_hf2custom.py
│   │   ├── json2jsonl.py
│   │   ├── jsonl2jsonl.py
│   │   ├── merge_lora.py
│   │   ├── reasoning_data_pipeline/
│   │   │   ├── mmpr_data_pipeline_correctness.py
│   │   │   ├── mmpr_data_pipeline_correctness_postprocess.py
│   │   │   ├── mmpr_data_pipeline_dropout_ntp.py
│   │   │   ├── utils/
│   │   │   │   ├── accuracy_reward.py
│   │   │   │   ├── constants.py
│   │   │   │   └── utils.py
│   │   │   ├── visualprm_data_pieline.py
│   │   │   └── visualprm_data_pipeline_postprocess.py
│   │   ├── replace_llm.py
│   │   └── resize_pos_embed.py
│   ├── zero_stage1_config.json
│   ├── zero_stage2_config.json
│   ├── zero_stage3_config.json
│   ├── zero_stage3_config_100b.json
│   ├── zero_stage3_config_100b_1e7_offload.json
│   ├── zero_stage3_config_100b_1e8.json
│   ├── zero_stage3_config_34b.json
│   └── zero_stage3_config_70b.json
├── internvl_chat_gpt_oss/
│   ├── README.md
│   ├── internvl/
│   │   ├── dist_utils.py
│   │   ├── model/
│   │   │   └── internvl_chat/
│   │   │       ├── __init__.py
│   │   │       ├── configuration_intern_vit.py
│   │   │       ├── configuration_internvl_chat.py
│   │   │       ├── conversation.py
│   │   │       ├── modeling_intern_vit.py
│   │   │       └── modeling_internvl_chat.py
│   │   ├── patch/
│   │   │   ├── __init__.py
│   │   │   ├── flash_sink_attn/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── flash_attn_with_sink.py
│   │   │   │   ├── flash_sink_attn.py
│   │   │   │   ├── flash_sink_attn_gpt_oss.py
│   │   │   │   ├── flash_sink_varlen_attn_gpt_oss.py
│   │   │   │   └── sliding_cache.py
│   │   │   ├── flash_sink_attn_monkey_patch.py
│   │   │   ├── pad_data_collator.py
│   │   │   ├── qwen3_flash_monkey_patch.py
│   │   │   └── train_dataloader_patch.py
│   │   ├── train/
│   │   │   ├── constants.py
│   │   │   ├── dataset.py
│   │   │   ├── dataset_packed.py
│   │   │   ├── internvl_chat_finetune.py
│   │   │   ├── internvl_chat_mpo.py
│   │   │   └── trainer_dpo.py
│   │   └── utils/
│   │       ├── s3_config.py
│   │       ├── s3_exception.py
│   │       └── s3_fileio.py
│   ├── requirements.txt
│   ├── shell/
│   │   ├── data/
│   │   │   ├── debug_mpo.json
│   │   │   └── debug_sft.json
│   │   ├── internvl3_5_gpt_oss/
│   │   │   ├── internvl3_5_gpt_oss_20b_stage0_mlp_warmup.sh
│   │   │   ├── internvl3_5_gpt_oss_20b_stage1_pretrain.sh
│   │   │   ├── internvl3_5_gpt_oss_20b_stage2_sft.sh
│   │   │   └── internvl3_5_gpt_oss_20b_stage3_mpo.sh
│   │   └── internvl3_5_qwen3/
│   │       ├── internvl3_5_14b_mpo.sh
│   │       ├── internvl3_5_14b_sft.sh
│   │       ├── internvl3_5_1b_mpo.sh
│   │       ├── internvl3_5_1b_sft.sh
│   │       ├── internvl3_5_241b_mpo.sh
│   │       ├── internvl3_5_241b_sft.sh
│   │       ├── internvl3_5_2b_mpo.sh
│   │       ├── internvl3_5_2b_sft.sh
│   │       ├── internvl3_5_30b_mpo.sh
│   │       ├── internvl3_5_30b_sft.sh
│   │       ├── internvl3_5_38b_mpo.sh
│   │       ├── internvl3_5_38b_sft.sh
│   │       ├── internvl3_5_4b_mpo.sh
│   │       ├── internvl3_5_4b_sft.sh
│   │       ├── internvl3_5_8b_mpo.sh
│   │       └── internvl3_5_8b_sft.sh
│   ├── zero_stage1_config.json
│   └── zero_stage3_config.json
├── internvl_chat_llava/
│   ├── LICENSE
│   ├── README.md
│   ├── docs/
│   │   ├── Customize_Component.md
│   │   ├── Data.md
│   │   ├── Evaluation.md
│   │   ├── LLaVA_Bench.md
│   │   ├── LLaVA_from_LLaMA2.md
│   │   ├── LoRA.md
│   │   ├── MODEL_ZOO.md
│   │   └── ScienceQA.md
│   ├── llava/
│   │   ├── __init__.py
│   │   ├── constants.py
│   │   ├── conversation.py
│   │   ├── eval/
│   │   │   ├── eval_gpt_review.py
│   │   │   ├── eval_gpt_review_bench.py
│   │   │   ├── eval_gpt_review_visual.py
│   │   │   ├── eval_pope.py
│   │   │   ├── eval_science_qa.py
│   │   │   ├── eval_science_qa_gpt4.py
│   │   │   ├── eval_science_qa_gpt4_requery.py
│   │   │   ├── eval_textvqa.py
│   │   │   ├── generate_webpage_data_from_table.py
│   │   │   ├── m4c_evaluator.py
│   │   │   ├── model_qa.py
│   │   │   ├── model_vqa.py
│   │   │   ├── model_vqa_loader.py
│   │   │   ├── model_vqa_mmbench.py
│   │   │   ├── model_vqa_science.py
│   │   │   ├── qa_baseline_gpt35.py
│   │   │   ├── run_llava.py
│   │   │   ├── summarize_gpt_review.py
│   │   │   ├── table/
│   │   │   │   ├── answer/
│   │   │   │   │   ├── answer_alpaca-13b.jsonl
│   │   │   │   │   ├── answer_bard.jsonl
│   │   │   │   │   ├── answer_gpt35.jsonl
│   │   │   │   │   ├── answer_llama-13b.jsonl
│   │   │   │   │   └── answer_vicuna-13b.jsonl
│   │   │   │   ├── caps_boxes_coco2014_val_80.jsonl
│   │   │   │   ├── model.jsonl
│   │   │   │   ├── prompt.jsonl
│   │   │   │   ├── question.jsonl
│   │   │   │   ├── review/
│   │   │   │   │   ├── review_alpaca-13b_vicuna-13b.jsonl
│   │   │   │   │   ├── review_bard_vicuna-13b.jsonl
│   │   │   │   │   ├── review_gpt35_vicuna-13b.jsonl
│   │   │   │   │   └── review_llama-13b_vicuna-13b.jsonl
│   │   │   │   ├── reviewer.jsonl
│   │   │   │   └── rule.json
│   │   │   └── webpage/
│   │   │       ├── index.html
│   │   │       ├── script.js
│   │   │       └── styles.css
│   │   ├── mm_utils.py
│   │   ├── model/
│   │   │   ├── __init__.py
│   │   │   ├── apply_delta.py
│   │   │   ├── builder.py
│   │   │   ├── consolidate.py
│   │   │   ├── language_model/
│   │   │   │   ├── llava_llama.py
│   │   │   │   ├── llava_mpt.py
│   │   │   │   └── mpt/
│   │   │   │       ├── adapt_tokenizer.py
│   │   │   │       ├── attention.py
│   │   │   │       ├── blocks.py
│   │   │   │       ├── configuration_mpt.py
│   │   │   │       ├── custom_embedding.py
│   │   │   │       ├── flash_attn_triton.py
│   │   │   │       ├── hf_prefixlm_converter.py
│   │   │   │       ├── meta_init_context.py
│   │   │   │       ├── modeling_mpt.py
│   │   │   │       ├── norm.py
│   │   │   │       └── param_init_fns.py
│   │   │   ├── llava_arch.py
│   │   │   ├── make_delta.py
│   │   │   ├── multimodal_encoder/
│   │   │   │   ├── builder.py
│   │   │   │   ├── clip_encoder.py
│   │   │   │   ├── eva_clip/
│   │   │   │   │   ├── configuration_evaclip.py
│   │   │   │   │   └── modeling_evaclip.py
│   │   │   │   ├── intern_vit_6b/
│   │   │   │   │   ├── configuration_intern_vit.py
│   │   │   │   │   ├── flash_attention.py
│   │   │   │   │   └── modeling_intern_vit.py
│   │   │   │   └── internvl_14b/
│   │   │   │       ├── __init__.py
│   │   │   │       ├── configuration_intern_vit.py
│   │   │   │       ├── configuration_internvl.py
│   │   │   │       ├── flash_attention.py
│   │   │   │       ├── modeling_intern_vit.py
│   │   │   │       ├── modeling_internvl.py
│   │   │   │       └── modeling_qllama.py
│   │   │   ├── multimodal_projector/
│   │   │   │   └── builder.py
│   │   │   └── utils.py
│   │   ├── serve/
│   │   │   ├── __init__.py
│   │   │   ├── cli.py
│   │   │   ├── controller.py
│   │   │   ├── gradio_web_server.py
│   │   │   ├── model_worker.py
│   │   │   ├── register_worker.py
│   │   │   └── test_message.py
│   │   ├── train/
│   │   │   ├── dist_utils.py
│   │   │   ├── llama_flash_attn_monkey_patch.py
│   │   │   ├── llava_trainer.py
│   │   │   ├── train.py
│   │   │   ├── train_custom.py
│   │   │   ├── train_mem.py
│   │   │   └── train_mem_custom.py
│   │   └── utils.py
│   ├── pyproject.toml
│   ├── scripts/
│   │   ├── convert_gqa_for_eval.py
│   │   ├── convert_mmbench_for_submission.py
│   │   ├── convert_mmvet_for_eval.py
│   │   ├── convert_seed_for_submission.py
│   │   ├── convert_sqa_to_llava.py
│   │   ├── convert_sqa_to_llava_base_prompt.py
│   │   ├── convert_vizwiz_for_submission.py
│   │   ├── convert_vqav2_for_submission.py
│   │   ├── finetune.sh
│   │   ├── finetune_full_schedule.sh
│   │   ├── finetune_lora.sh
│   │   ├── finetune_qlora.sh
│   │   ├── finetune_sqa.sh
│   │   ├── merge_lora_weights.py
│   │   ├── pretrain.sh
│   │   ├── sqa_eval_batch.sh
│   │   ├── sqa_eval_gather.sh
│   │   ├── v1_5/
│   │   │   ├── eval/
│   │   │   │   ├── gqa.sh
│   │   │   │   ├── llavabench.sh
│   │   │   │   ├── mmbench.sh
│   │   │   │   ├── mmbench_cn.sh
│   │   │   │   ├── mme.sh
│   │   │   │   ├── mmvet.sh
│   │   │   │   ├── pope.sh
│   │   │   │   ├── seed.sh
│   │   │   │   ├── sqa.sh
│   │   │   │   ├── textvqa.sh
│   │   │   │   ├── vizwiz.sh
│   │   │   │   └── vqav2.sh
│   │   │   ├── finetune.sh
│   │   │   └── pretrain.sh
│   │   ├── zero1.json
│   │   ├── zero2.json
│   │   ├── zero3.json
│   │   └── zero3_offload.json
│   └── scripts_internvl/
│       ├── eval/
│       │   ├── gqa.sh
│       │   ├── llavabench.sh
│       │   ├── mmbench.sh
│       │   ├── mme.sh
│       │   ├── mmvet.sh
│       │   ├── pope.sh
│       │   ├── sqa.sh
│       │   ├── textvqa.sh
│       │   ├── vizwiz.sh
│       │   └── vqav2.sh
│       ├── finetune_internvit6b_224to336_vicuna13b.sh
│       ├── finetune_internvit6b_224to336_vicuna13b_custom_data.sh
│       ├── finetune_internvit6b_224to336_vicuna7b.sh
│       ├── finetune_internvit6b_448_v1_2_vicuna13b.sh
│       ├── finetune_internvit6b_448_v1_5_vicuna13b.sh
│       ├── finetune_internvit6b_448_vicuna13b.sh
│       ├── finetune_internvit6b_448_vicuna7b.sh
│       ├── meta/
│       │   └── custom_data.json
│       ├── pretrain_internvit6b_224to336_vicuna13b.sh
│       ├── pretrain_internvit6b_224to336_vicuna7b.sh
│       ├── pretrain_internvit6b_448_v1_2_vicuna13b.sh
│       ├── pretrain_internvit6b_448_v1_5_vicuna13b.sh
│       ├── pretrain_internvit6b_448_vicuna13b.sh
│       └── pretrain_internvit6b_448_vicuna7b.sh
├── internvl_g/
│   ├── README.md
│   ├── eval/
│   │   └── evaluate_caption.py
│   ├── evaluate.sh
│   ├── internvl/
│   │   ├── dist_utils.py
│   │   ├── model/
│   │   │   ├── __init__.py
│   │   │   ├── internvl_stage2/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── configuration_intern_vit.py
│   │   │   │   ├── configuration_internvl.py
│   │   │   │   ├── flash_attention.py
│   │   │   │   ├── modeling_intern_vit.py
│   │   │   │   ├── modeling_internvl.py
│   │   │   │   └── modeling_qllama.py
│   │   │   └── internvl_stage2_retrieval/
│   │   │       ├── __init__.py
│   │   │       ├── configuration_intern_vit.py
│   │   │       ├── configuration_internvl.py
│   │   │       ├── flash_attention.py
│   │   │       ├── modeling_intern_vit.py
│   │   │       ├── modeling_internvl.py
│   │   │       └── modeling_qllama.py
│   │   └── train/
│   │       ├── __init__.py
│   │       ├── dataset.py
│   │       ├── internvl_stage2_finetune.py
│   │       └── trainer_monkey_patch.py
│   ├── shell/
│   │   ├── finetune/
│   │   │   ├── internvl_stage2_finetune_coco_364_bs1024_ep5.sh
│   │   │   ├── internvl_stage2_finetune_flickr_364_bs1024_ep10.sh
│   │   │   └── internvl_stage2_finetune_flickrcn_364_bs1024_ep10.sh
│   │   ├── head_finetune/
│   │   │   ├── internvl_stage2_finetune_coco_224_bs1024_ep5_head_4gpu.sh
│   │   │   ├── internvl_stage2_finetune_flickr_224_bs1024_ep10_head_4gpu.sh
│   │   │   └── internvl_stage2_finetune_flickrcn_224_bs1024_ep10_head_4gpu.sh
│   │   └── lora_finetune/
│   │       ├── internvl_stage2_finetune_coco_224_bs1024_ep5_lora16_4gpu.sh
│   │       ├── internvl_stage2_finetune_flickr_224_bs1024_ep10_lora16_4gpu.sh
│   │       └── internvl_stage2_finetune_flickrcn_224_bs1024_ep10_lora16_4gpu.sh
│   ├── zero_stage1_config.json
│   ├── zero_stage2_config.json
│   └── zero_stage3_config.json
├── requirements/
│   ├── classification.txt
│   ├── clip_benchmark.txt
│   ├── internvl_chat.txt
│   ├── segmentation.txt
│   └── streamlit_demo.txt
├── requirements.txt
├── segmentation/
│   ├── README.md
│   ├── configs/
│   │   ├── _base_/
│   │   │   ├── datasets/
│   │   │   │   ├── ade20k.py
│   │   │   │   ├── ade20k_504x504.py
│   │   │   │   ├── ade20k_504x504_1of16.py
│   │   │   │   ├── ade20k_504x504_1of2.py
│   │   │   │   ├── ade20k_504x504_1of4.py
│   │   │   │   ├── ade20k_504x504_1of8.py
│   │   │   │   ├── ade20k_640x640.py
│   │   │   │   ├── ade20k_896x896.py
│   │   │   │   ├── chase_db1.py
│   │   │   │   ├── cityscapes.py
│   │   │   │   ├── cityscapes_1024x1024.py
│   │   │   │   ├── cityscapes_768x768.py
│   │   │   │   ├── cityscapes_769x769.py
│   │   │   │   ├── cityscapes_832x832.py
│   │   │   │   ├── coco-stuff10k.py
│   │   │   │   ├── coco-stuff164k.py
│   │   │   │   ├── coco-stuff164k_896x896.py
│   │   │   │   ├── drive.py
│   │   │   │   ├── hrf.py
│   │   │   │   ├── isaid.py
│   │   │   │   ├── loveda.py
│   │   │   │   ├── pascal_context.py
│   │   │   │   ├── pascal_context_59.py
│   │   │   │   ├── pascal_voc12.py
│   │   │   │   ├── pascal_voc12_aug.py
│   │   │   │   ├── potsdam.py
│   │   │   │   ├── stare.py
│   │   │   │   └── vaihingen.py
│   │   │   ├── default_runtime.py
│   │   │   ├── models/
│   │   │   │   ├── ann_r50-d8.py
│   │   │   │   ├── apcnet_r50-d8.py
│   │   │   │   ├── bisenetv1_r18-d32.py
│   │   │   │   ├── bisenetv2.py
│   │   │   │   ├── ccnet_r50-d8.py
│   │   │   │   ├── cgnet.py
│   │   │   │   ├── danet_r50-d8.py
│   │   │   │   ├── deeplabv3_r50-d8.py
│   │   │   │   ├── deeplabv3_unet_s5-d16.py
│   │   │   │   ├── deeplabv3plus_r50-d8.py
│   │   │   │   ├── dmnet_r50-d8.py
│   │   │   │   ├── dnl_r50-d8.py
│   │   │   │   ├── dpt_vit-b16.py
│   │   │   │   ├── emanet_r50-d8.py
│   │   │   │   ├── encnet_r50-d8.py
│   │   │   │   ├── erfnet_fcn.py
│   │   │   │   ├── fast_scnn.py
│   │   │   │   ├── fastfcn_r50-d32_jpu_psp.py
│   │   │   │   ├── fcn_hr18.py
│   │   │   │   ├── fcn_r50-d8.py
│   │   │   │   ├── fcn_unet_s5-d16.py
│   │   │   │   ├── fpn_r50.py
│   │   │   │   ├── gcnet_r50-d8.py
│   │   │   │   ├── icnet_r50-d8.py
│   │   │   │   ├── isanet_r50-d8.py
│   │   │   │   ├── lraspp_m-v3-d8.py
│   │   │   │   ├── mask2former_beit.py
│   │   │   │   ├── nonlocal_r50-d8.py
│   │   │   │   ├── ocrnet_hr18.py
│   │   │   │   ├── ocrnet_r50-d8.py
│   │   │   │   ├── pointrend_r50.py
│   │   │   │   ├── psanet_r50-d8.py
│   │   │   │   ├── pspnet_r50-d8.py
│   │   │   │   ├── pspnet_unet_s5-d16.py
│   │   │   │   ├── segformer_mit-b0.py
│   │   │   │   ├── segmenter_vit-b16_mask.py
│   │   │   │   ├── setr_mla.py
│   │   │   │   ├── setr_naive.py
│   │   │   │   ├── setr_pup.py
│   │   │   │   ├── stdc.py
│   │   │   │   ├── twins_pcpvt-s_fpn.py
│   │   │   │   ├── twins_pcpvt-s_upernet.py
│   │   │   │   ├── upernet_beit.py
│   │   │   │   ├── upernet_convnext.py
│   │   │   │   ├── upernet_mae.py
│   │   │   │   ├── upernet_r50.py
│   │   │   │   ├── upernet_swin.py
│   │   │   │   └── upernet_vit-b16_ln_mln.py
│   │   │   └── schedules/
│   │   │       ├── schedule_10k.py
│   │   │       ├── schedule_160k.py
│   │   │       ├── schedule_20k.py
│   │   │       ├── schedule_320k.py
│   │   │       ├── schedule_40k.py
│   │   │       ├── schedule_5k.py
│   │   │       └── schedule_80k.py
│   │   └── intern_vit_6b/
│   │       ├── few_shot/
│   │       │   ├── linear_intern_vit_6b_504_10k_ade20k_bs16_lr4e-5_1of8.py
│   │       │   ├── linear_intern_vit_6b_504_20k_ade20k_bs16_lr4e-5_1of4.py
│   │       │   ├── linear_intern_vit_6b_504_40k_ade20k_bs16_lr4e-5_1of2.py
│   │       │   ├── linear_intern_vit_6b_504_5k_ade20k_bs16_lr4e-5_1of16.py
│   │       │   └── linear_intern_vit_6b_504_80k_ade20k_bs16_lr4e-5_1of1.py
│   │       ├── full_tuning/
│   │       │   └── upernet_intern_vit_6b_504_80k_ade20k_bs16_lr4e-5.py
│   │       ├── head_tuning/
│   │       │   └── upernet_intern_vit_6b_504_80k_ade20k_bs16_lr4e-5_frozen.py
│   │       └── linear_probing/
│   │           └── linear_intern_vit_6b_504_80k_ade20k_bs16_lr4e-5_frozen.py
│   ├── dist_test.sh
│   ├── dist_train.sh
│   ├── mmcv_custom/
│   │   ├── __init__.py
│   │   ├── ddp_hooks.py
│   │   └── layer_decay_optimizer_constructor.py
│   ├── mmseg_custom/
│   │   ├── __init__.py
│   │   ├── datasets/
│   │   │   ├── __init__.py
│   │   │   ├── ade.py
│   │   │   └── pipelines/
│   │   │       ├── __init__.py
│   │   │       └── transform.py
│   │   └── models/
│   │       ├── __init__.py
│   │       ├── backbones/
│   │       │   ├── __init__.py
│   │       │   ├── flash_attention.py
│   │       │   └── intern_vit_6b.py
│   │       └── decode_heads/
│   │           ├── __init__.py
│   │           └── fcn_head.py
│   ├── release.py
│   ├── slurm_test.sh
│   ├── slurm_train.sh
│   ├── test.py
│   ├── train.py
│   └── zero_configs/
│       ├── adam_fp16.json
│       ├── adam_zero1_amp.json
│       ├── adam_zero1_bf16.json
│       ├── adam_zero1_fp16.json
│       ├── adam_zero2_bf16.json
│       ├── adam_zero2_fp16.json
│       └── adam_zero3_fp16.json
├── streamlit_demo/
│   ├── .streamlit/
│   │   └── config.toml
│   ├── api.py
│   ├── app.py
│   ├── constants.py
│   ├── controller.py
│   ├── library.py
│   ├── model_worker.py
│   ├── sd_worker.py
│   └── utils.py
└── video_retrieval/
    └── test_msrvtt.py

SYMBOL INDEX (2771 symbols across 274 files)

FILE: classification/config.py
  function _update_config_from_file (line 226) | def _update_config_from_file(config, cfg_file):
  function update_config (line 240) | def update_config(config, args):
  function get_config (line 292) | def get_config(args):

FILE: classification/dataset/build.py
  function _pil_interp (line 22) | def _pil_interp(method):
  class TTA (line 35) | class TTA(torch.nn.Module):
    method __init__ (line 37) | def __init__(self, size, scales=[1.0, 1.05, 1.1]):
    method forward (line 42) | def forward(self, img):
    method __repr__ (line 54) | def __repr__(self) -> str:
  function build_loader (line 58) | def build_loader(config):
  function build_loader2 (line 148) | def build_loader2(config):
  function build_dataset (line 199) | def build_dataset(split, config):
  function build_transform_for_linear_probe (line 266) | def build_transform_for_linear_probe(is_train, config):
  function build_transform (line 287) | def build_transform(is_train, config):

FILE: classification/dataset/cached_image_folder.py
  function has_file_allowed_extension (line 32) | def has_file_allowed_extension(filename, extensions):
  function find_classes (line 44) | def find_classes(dir):
  function make_dataset (line 53) | def make_dataset(dir, class_to_idx, extensions):
  function make_dataset_with_ann (line 70) | def make_dataset_with_ann(ann_file, img_prefix, extensions):
  class DatasetFolder (line 85) | class DatasetFolder(data.Dataset):
    method __init__ (line 107) | def __init__(self,
    method init_cache (line 146) | def init_cache(self):
    method __getitem__ (line 170) | def __getitem__(self, index):
    method __len__ (line 186) | def __len__(self):
    method __repr__ (line 189) | def __repr__(self):
  function pil_loader (line 209) | def pil_loader(path):
  function accimage_loader (line 224) | def accimage_loader(path):
  function default_img_loader (line 233) | def default_img_loader(path):
  class CachedImageFolder (line 241) | class CachedImageFolder(DatasetFolder):
    method __init__ (line 261) | def __init__(self,
    method __getitem__ (line 280) | def __getitem__(self, index):
  class ImageCephDataset (line 299) | class ImageCephDataset(data.Dataset):
    method __init__ (line 301) | def __init__(self,
    method __getitem__ (line 324) | def __getitem__(self, index):
    method __len__ (line 335) | def __len__(self):
    method filename (line 338) | def filename(self, index, basename=False, absolute=False):
    method filenames (line 341) | def filenames(self, basename=False, absolute=False):
  class Parser (line 345) | class Parser:
    method __init__ (line 347) | def __init__(self):
    method _filename (line 351) | def _filename(self, index, basename=False, absolute=False):
    method filename (line 354) | def filename(self, index, basename=False, absolute=False):
    method filenames (line 357) | def filenames(self, basename=False, absolute=False):
  class ParserCephImage (line 364) | class ParserCephImage(Parser):
    method __init__ (line 366) | def __init__(self,
    method load_onto_memory (line 412) | def load_onto_memory(self):
    method load_onto_memory_v2 (line 427) | def load_onto_memory_v2(self):
    method __getitem__ (line 456) | def __getitem__(self, index):
    method __len__ (line 492) | def __len__(self):
    method _filename (line 495) | def _filename(self, index, basename=False, absolute=False):
  function get_temporal_info (line 502) | def get_temporal_info(date, miss_hour=False):
  function get_spatial_info (line 534) | def get_spatial_info(latitude, longitude):

FILE: classification/dataset/imagenet_real.py
  class RealLabelsImagenet (line 20) | class RealLabelsImagenet:
    method __init__ (line 22) | def __init__(self, filenames, real_json='real.json', topk=(1, 5)):
    method add_result (line 33) | def add_result(self, output):
    method get_accuracy (line 46) | def get_accuracy(self, k=None):

FILE: classification/dataset/imagenetv2.py
  class ImageNetV2Dataset (line 26) | class ImageNetV2Dataset(Dataset):
    method __init__ (line 27) | def __init__(self, variant='matched-frequency', transform=None, locati...
    method __len__ (line 52) | def __len__(self):
    method __getitem__ (line 55) | def __getitem__(self, i):

FILE: classification/dataset/samplers.py
  class SubsetRandomSampler (line 16) | class SubsetRandomSampler(torch.utils.data.Sampler):
    method __init__ (line 24) | def __init__(self, indices):
    method __iter__ (line 28) | def __iter__(self):
    method __len__ (line 31) | def __len__(self):
    method set_epoch (line 34) | def set_epoch(self, epoch):
  class NodeDistributedSampler (line 38) | class NodeDistributedSampler(Sampler):
    method __init__ (line 53) | def __init__(self,
    method __iter__ (line 85) | def __iter__(self):
    method __len__ (line 112) | def __len__(self):
    method set_epoch (line 115) | def set_epoch(self, epoch):

FILE: classification/dataset/zipreader.py
  function is_zip_path (line 17) | def is_zip_path(img_or_path):
  class ZipReader (line 22) | class ZipReader(object):
    method __init__ (line 26) | def __init__(self):
    method get_zipfile (line 30) | def get_zipfile(path):
    method split_zip_style_path (line 38) | def split_zip_style_path(path):
    method list_folder (line 48) | def list_folder(path):
    method list_files (line 66) | def list_files(path, extension=None):
    method read (line 85) | def read(path):
    method imread (line 92) | def imread(path):

FILE: classification/ddp_hooks.py
  function _allreduce_fut (line 12) | def _allreduce_fut(process_group: dist.ProcessGroup,
  function allreduce_hook (line 25) | def allreduce_hook(
  function fp16_compress_hook (line 43) | def fp16_compress_hook(
  function bf16_compress_hook (line 77) | def bf16_compress_hook(
  function fp16_compress_wrapper (line 111) | def fp16_compress_wrapper(
  function bf16_compress_wrapper (line 147) | def bf16_compress_wrapper(

FILE: classification/gflops.py
  function sa_flops (line 60) | def sa_flops(h, w, dim):
  function get_flops (line 64) | def get_flops(model, input_shape):

FILE: classification/logger.py
  function create_logger (line 16) | def create_logger(output_dir, dist_rank=0, name=''):

FILE: classification/lr_scheduler.py
  function build_scheduler (line 13) | def build_scheduler(config, optimizer, n_iter_per_epoch):
  class LinearLRScheduler (line 53) | class LinearLRScheduler(Scheduler):
    method __init__ (line 55) | def __init__(
    method _get_lr (line 89) | def _get_lr(self, t):
    method get_epoch_values (line 101) | def get_epoch_values(self, epoch: int):
    method get_update_values (line 107) | def get_update_values(self, num_updates: int):

FILE: classification/main.py
  function obsolete_torch_version (line 51) | def obsolete_torch_version(torch_version, version_threshold):
  function parse_option (line 55) | def parse_option():
  function throughput (line 146) | def throughput(data_loader, model, logger):
  function main (line 167) | def main(config):
  function train_one_epoch (line 403) | def train_one_epoch(config,
  function validate_real (line 539) | def validate_real(config, data_loader, model, real_labels, amp_autocast=...
  function validate (line 605) | def validate(config, data_loader, model, epoch=None, amp_autocast=suppre...

FILE: classification/models/build.py
  function build_model (line 11) | def build_model(config):

FILE: classification/models/clip_vit.py
  function _freeze_params (line 15) | def _freeze_params(module):
  class CrossAttention (line 20) | class CrossAttention(nn.Module):
    method __init__ (line 21) | def __init__(
    method forward (line 52) | def forward(self, x, k=None, v=None):
  class AttentiveBlock (line 85) | class AttentiveBlock(nn.Module):
    method __init__ (line 87) | def __init__(self, dim, num_heads, qkv_bias=False, qk_scale=None, drop...
    method forward (line 100) | def forward(self, x_q, x_kv, pos_q, pos_k, bool_masked_pos, rel_pos_bi...
  class AttentionPoolingBlock (line 109) | class AttentionPoolingBlock(AttentiveBlock):
    method forward (line 111) | def forward(self, x):
  class CLIPViT (line 119) | class CLIPViT(nn.Module):
    method __init__ (line 121) | def __init__(self, patch_size=14, img_size=336, pretrain_size=336, emb...
    method dtype (line 159) | def dtype(self):
    method forward_features (line 162) | def forward_features(self, x):
    method forward (line 168) | def forward(self, x):
    method lr_decay_keywords (line 181) | def lr_decay_keywords(self, decay_ratio=0.95):

FILE: classification/models/flash_attention.py
  class FlashAttention (line 14) | class FlashAttention(nn.Module):
    method __init__ (line 25) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 30) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...

FILE: classification/models/intern_vit_6b.py
  function _freeze_params (line 23) | def _freeze_params(module):
  class CrossAttention (line 28) | class CrossAttention(nn.Module):
    method __init__ (line 29) | def __init__(
    method forward (line 60) | def forward(self, x, k=None, v=None):
  class AttentiveBlock (line 93) | class AttentiveBlock(nn.Module):
    method __init__ (line 95) | def __init__(self, dim, num_heads, qkv_bias=False, qk_scale=None, drop...
    method forward (line 108) | def forward(self, x_q, x_kv, pos_q, pos_k, bool_masked_pos, rel_pos_bi...
  class AttentionPoolingBlock (line 117) | class AttentionPoolingBlock(AttentiveBlock):
    method forward (line 119) | def forward(self, x):
  class RMSNorm (line 127) | class RMSNorm(nn.Module):
    method __init__ (line 128) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 133) | def forward(self, hidden_states):
  class LayerScale (line 155) | class LayerScale(nn.Module):
    method __init__ (line 156) | def __init__(self, dim, init_values=1e-5, inplace=False, force_fp32=Fa...
    method forward (line 163) | def forward(self, x):
  class Attention (line 173) | class Attention(nn.Module):
    method __init__ (line 174) | def __init__(self, dim, num_heads=8, qkv_bias=False, attn_drop=0., pro...
    method _naive_attn (line 196) | def _naive_attn(self, x):
    method _flash_attn (line 215) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 232) | def forward(self, x):
  class Mlp (line 237) | class Mlp(nn.Module):
    method __init__ (line 241) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 255) | def forward(self, x):
  class Block (line 264) | class Block(nn.Module):
    method __init__ (line 266) | def __init__(
    method forward (line 290) | def forward(self, x):
  class PatchEmbed (line 303) | class PatchEmbed(nn.Module):
    method __init__ (line 307) | def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=...
    method forward (line 321) | def forward(self, x, **kwargs):
  class InternViT6B (line 330) | class InternViT6B(nn.Module):
    method __init__ (line 332) | def __init__(self, in_chans=3, patch_size=14, img_size=224, pretrain_s...
    method init_weights (line 408) | def init_weights(self, pretrained=None):
    method dtype (line 438) | def dtype(self):
    method forward_features (line 441) | def forward_features(self, x):
    method forward (line 452) | def forward(self, x):
    method lr_decay_keywords (line 467) | def lr_decay_keywords(self, decay_ratio=0.95):

FILE: classification/optimizer.py
  function build_optimizer (line 11) | def build_optimizer(config, model):
  function check_keywords_in_name (line 90) | def check_keywords_in_name(name, keywords=()):
  function check_keywords_in_dict (line 98) | def check_keywords_in_dict(name, keywords_dict):
  function set_weight_decay_and_lr (line 105) | def set_weight_decay_and_lr(

FILE: classification/utils.py
  function load_ema_checkpoint (line 23) | def load_ema_checkpoint(config, model_ema, logger):
  function load_checkpoint (line 59) | def load_checkpoint(config, model, optimizer, lr_scheduler, scaler, logg...
  function load_pretrained (line 103) | def load_pretrained(config, model, logger):
  function convert_22k_head_to_1k (line 243) | def convert_22k_head_to_1k(model, logger):
  function save_checkpoint (line 263) | def save_checkpoint(config,
  function get_grad_norm (line 316) | def get_grad_norm(parameters, norm_type=2):
  function auto_resume_helper (line 329) | def auto_resume_helper(output_dir):
  function reduce_tensor (line 344) | def reduce_tensor(tensor):
  class NativeScalerWithGradNormCount (line 352) | class NativeScalerWithGradNormCount:
    method __init__ (line 355) | def __init__(self):
    method __call__ (line 358) | def __call__(self,
    method state_dict (line 380) | def state_dict(self):
    method load_state_dict (line 383) | def load_state_dict(self, state_dict):
  class MyAverageMeter (line 387) | class MyAverageMeter(object):
    method __init__ (line 390) | def __init__(self, max_len=-1):
    method update (line 398) | def update(self, val):

FILE: clip_benchmark/clip_benchmark/cli.py
  function get_parser_args (line 23) | def get_parser_args():
  function main (line 90) | def main():
  function main_build (line 98) | def main_build(base):
  function main_eval (line 119) | def main_eval(base):
  function _as_list (line 172) | def _as_list(l):
  function run (line 178) | def run(args):

FILE: clip_benchmark/clip_benchmark/datasets/birdsnap.py
  class Birdsnap (line 14) | class Birdsnap(torch.utils.data.Dataset):
    method __init__ (line 29) | def __init__(self, root, split='train', transform=None, target_transfo...
    method _check_integrity_of_metadata (line 44) | def _check_integrity_of_metadata(self, chunk_size=8192):
    method check_integrity (line 55) | def check_integrity(self):
    method download (line 69) | def download(self):
    method __len__ (line 86) | def __len__(self):
    method __getitem__ (line 90) | def __getitem__(self, index):
    method _parse_metadata (line 109) | def _parse_metadata(self):
    method _verify_image (line 127) | def _verify_image(self, idx):
    method scrape_images (line 137) | def scrape_images(self, missing_ids, chunk_size=8196):
    method _purge_missing_data (line 165) | def _purge_missing_data(self):
  class BirdsnapV2 (line 185) | class BirdsnapV2(torch.utils.data.Dataset):
    method __init__ (line 186) | def __init__(self, root, split='test', transform=None, target_transfor...
    method __len__ (line 209) | def __len__(self):
    method __getitem__ (line 213) | def __getitem__(self, index):

FILE: clip_benchmark/clip_benchmark/datasets/builder.py
  function _load_classnames_and_classification_templates (line 20) | def _load_classnames_and_classification_templates(dataset_name, current_...
  function build_dataset (line 43) | def build_dataset(dataset_name, root='root', transform=None, split='test...
  class Dummy (line 488) | class Dummy():
    method __init__ (line 490) | def __init__(self):
    method __getitem__ (line 493) | def __getitem__(self, i):
    method __len__ (line 496) | def __len__(self):
  function get_dataset_default_task (line 500) | def get_dataset_default_task(dataset):
  function get_dataset_collate_fn (line 507) | def get_dataset_collate_fn(dataset_name):
  function has_gdown (line 514) | def has_gdown():
  function has_kaggle (line 518) | def has_kaggle():
  function build_vtab_dataset (line 522) | def build_vtab_dataset(dataset_name, transform, download=True, split='te...
  function build_tfds_dataset (line 664) | def build_tfds_dataset(name, transform, download=True, split='test', dat...
  function build_wds_dataset (line 679) | def build_wds_dataset(dataset_name, transform, split='test', data_dir='r...
  function _extract_task (line 779) | def _extract_task(dataset_name):
  function image_captions_collate_fn (line 785) | def image_captions_collate_fn(batch):
  function get_dataset_collection_from_file (line 792) | def get_dataset_collection_from_file(path):

FILE: clip_benchmark/clip_benchmark/datasets/caltech101.py
  class Caltech101 (line 17) | class Caltech101(VisionDataset):
    method __init__ (line 41) | def __init__(
    method __getitem__ (line 82) | def __getitem__(self, index: int) -> Tuple[Any, Any]:
    method _check_integrity (line 125) | def _check_integrity(self) -> bool:
    method __len__ (line 129) | def __len__(self) -> int:
    method download (line 132) | def download(self) -> None:
    method extra_repr (line 150) | def extra_repr(self) -> str:
  class Caltech256 (line 154) | class Caltech256(VisionDataset):
    method __init__ (line 169) | def __init__(
    method __getitem__ (line 199) | def __getitem__(self, index: int) -> Tuple[Any, Any]:
    method _check_integrity (line 226) | def _check_integrity(self) -> bool:
    method __len__ (line 230) | def __len__(self) -> int:
    method download (line 233) | def download(self) -> None:

FILE: clip_benchmark/clip_benchmark/datasets/flickr.py
  class Flickr (line 13) | class Flickr(VisionDataset):
    method __init__ (line 15) | def __init__(
    method __getitem__ (line 36) | def __getitem__(self, index: int) -> Tuple[Any, Any]:
    method __len__ (line 58) | def __len__(self) -> int:

FILE: clip_benchmark/clip_benchmark/datasets/imagenetv2.py
  class ImageNetValDataset (line 29) | class ImageNetValDataset(Dataset):
    method __init__ (line 30) | def __init__(self, transform=None, location='.'):
    method __len__ (line 55) | def __len__(self):
    method __getitem__ (line 58) | def __getitem__(self, i):
  class ImageNetV2Dataset (line 65) | class ImageNetV2Dataset(Dataset):
    method __init__ (line 66) | def __init__(self, variant='matched-frequency', transform=None, locati...
    method __len__ (line 91) | def __len__(self):
    method __getitem__ (line 94) | def __getitem__(self, i):

FILE: clip_benchmark/clip_benchmark/datasets/kitti.py
  function _count_all_pp (line 26) | def _count_all_pp(x):
  function _count_vehicles_pp (line 34) | def _count_vehicles_pp(x):
  function _count_left_pp (line 44) | def _count_left_pp(x):
  function _count_far_pp (line 54) | def _count_far_pp(x):
  function _count_near_pp (line 65) | def _count_near_pp(x):
  function _closest_object_distance_pp (line 76) | def _closest_object_distance_pp(x):
  function _closest_vehicle_distance_pp (line 87) | def _closest_vehicle_distance_pp(x):
  function _closest_object_x_location_pp (line 103) | def _closest_object_x_location_pp(x):
  class KittiData (line 152) | class KittiData(base.ImageTfdsData):
    method __init__ (line 164) | def __init__(self, task, data_dir=None):

FILE: clip_benchmark/clip_benchmark/datasets/multilingual_mscoco.py
  class Multilingual_MSCOCO (line 21) | class Multilingual_MSCOCO(VisionDataset):
    method __init__ (line 23) | def __init__(self, root, ann_file, transform=None, target_transform=No...
    method __getitem__ (line 31) | def __getitem__(self, index):
    method __len__ (line 46) | def __len__(self) -> int:
  function _get_downloadable_file (line 50) | def _get_downloadable_file(filename, download_url, is_json=True):
  function create_annotation_file (line 60) | def create_annotation_file(root, lang_code):

FILE: clip_benchmark/clip_benchmark/datasets/objectnet.py
  function get_metadata (line 13) | def get_metadata(folder):
  class ObjectNetDataset (line 43) | class ObjectNetDataset(datasets.ImageFolder):
    method __init__ (line 45) | def __init__(self, root, transform):
    method __len__ (line 62) | def __len__(self):
    method __getitem__ (line 65) | def __getitem__(self, index):

FILE: clip_benchmark/clip_benchmark/datasets/tfds.py
  function download_tfds_dataset (line 5) | def download_tfds_dataset(name, data_dir=None):
  function disable_gpus_on_tensorflow (line 11) | def disable_gpus_on_tensorflow():
  class VTABIterableDataset (line 16) | class VTABIterableDataset(torch.utils.data.IterableDataset):
    method __init__ (line 18) | def __init__(self, tfds_dataset, split='test', input_name='image', lab...
    method __iter__ (line 33) | def __iter__(self):
    method __len__ (line 50) | def __len__(self):

FILE: clip_benchmark/clip_benchmark/datasets/tools.py
  function process_single_caption (line 4) | def process_single_caption(caption, max_words=50):
  function pre_caption (line 17) | def pre_caption(caption, max_words=50):

FILE: clip_benchmark/clip_benchmark/datasets/voc2007.py
  function download_url (line 35) | def download_url(url, path):
  function download_voc2007 (line 40) | def download_voc2007(root):
  function read_split (line 137) | def read_split(root, dataset, split):
  function read_bndbox (line 152) | def read_bndbox(root, dataset, paths):
  class PASCALVoc2007 (line 170) | class PASCALVoc2007(data.Dataset):
    method __init__ (line 177) | def __init__(self, root, set, transform=None, download=False, target_t...
    method __getitem__ (line 200) | def __getitem__(self, index):
    method __len__ (line 210) | def __len__(self):
  class PASCALVoc2007Cropped (line 214) | class PASCALVoc2007Cropped(data.Dataset):
    method __init__ (line 222) | def __init__(self, root, set, transform=None, download=False, target_t...
    method __getitem__ (line 240) | def __getitem__(self, index):
    method __len__ (line 250) | def __len__(self):

FILE: clip_benchmark/clip_benchmark/metrics/linear_probe.py
  function assign_learning_rate (line 15) | def assign_learning_rate(param_group, new_lr):
  function _warmup_lr (line 19) | def _warmup_lr(base_lr, warmup_length, step):
  function cosine_lr (line 23) | def cosine_lr(optimizer, base_lrs, warmup_length, steps):
  class Featurizer (line 41) | class Featurizer(torch.nn.Module):
    method __init__ (line 42) | def __init__(self, model):
    method forward (line 46) | def forward(self, input):
  class FeatureDataset (line 53) | class FeatureDataset(Dataset):
    method __init__ (line 54) | def __init__(self, features, targets):
    method __len__ (line 58) | def __len__(self):
    method __getitem__ (line 61) | def __getitem__(self, i):
  function evaluate (line 65) | def evaluate(model, train_dataloader, dataloader, fewshot_k, batch_size,...

FILE: clip_benchmark/clip_benchmark/metrics/mscoco_generative.py
  function evaluate (line 8) | def evaluate(model, dataloader, batch_size, device, transform, train_dat...

FILE: clip_benchmark/clip_benchmark/metrics/zeroshot_classification.py
  function zero_shot_classifier (line 13) | def zero_shot_classifier(model, tokenizer, classnames, templates, device...
  function accuracy (line 54) | def accuracy(output, target, topk=(1,)):
  function run_classification (line 79) | def run_classification(model, classifier, dataloader, device, amp=True):
  function average_precision_per_class (line 120) | def average_precision_per_class(scores, targets):
  function evaluate (line 161) | def evaluate(model, dataloader, tokenizer, classnames, templates, device...

FILE: clip_benchmark/clip_benchmark/metrics/zeroshot_retrieval.py
  function evaluate (line 8) | def evaluate(model, dataloader, tokenizer, device, amp=True, recall_k_li...
  function dataloader_with_indices (line 93) | def dataloader_with_indices(dataloader):
  function recall_at_k (line 102) | def recall_at_k(scores, positive_pairs, k):
  function batchify (line 126) | def batchify(func, X, Y, batch_size, device, *args, **kwargs):

FILE: clip_benchmark/clip_benchmark/model_collection.py
  function get_model_collection_from_file (line 4) | def get_model_collection_from_file(path):

FILE: clip_benchmark/clip_benchmark/models/__init__.py
  function load_clip (line 18) | def load_clip(

FILE: clip_benchmark/clip_benchmark/models/intern_vit_6b/configuration_intern_vit.py
  class InternVisionConfig (line 15) | class InternVisionConfig(PretrainedConfig):
    method __init__ (line 63) | def __init__(
    method from_pretrained (line 105) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....

FILE: clip_benchmark/clip_benchmark/models/intern_vit_6b/flash_attention.py
  class FlashAttention (line 14) | class FlashAttention(nn.Module):
    method __init__ (line 25) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 30) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...

FILE: clip_benchmark/clip_benchmark/models/intern_vit_6b/modeling_intern_vit.py
  class InternRMSNorm (line 33) | class InternRMSNorm(nn.Module):
    method __init__ (line 34) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 39) | def forward(self, hidden_states):
  class InternVisionEmbeddings (line 61) | class InternVisionEmbeddings(nn.Module):
    method __init__ (line 62) | def __init__(self, config: InternVisionConfig):
    method forward (line 82) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class InternAttention (line 93) | class InternAttention(nn.Module):
    method __init__ (line 96) | def __init__(self, config: InternVisionConfig):
    method _naive_attn (line 126) | def _naive_attn(self, x):
    method _flash_attn (line 145) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 162) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternMLP (line 167) | class InternMLP(nn.Module):
    method __init__ (line 168) | def __init__(self, config: InternVisionConfig):
    method forward (line 175) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternVisionEncoderLayer (line 182) | class InternVisionEncoderLayer(nn.Module):
    method __init__ (line 183) | def __init__(self, config: InternVisionConfig, drop_path_rate: float):
    method forward (line 198) | def forward(
  class InternVisionEncoder (line 213) | class InternVisionEncoder(nn.Module):
    method __init__ (line 223) | def __init__(self, config: InternVisionConfig):
    method forward (line 232) | def forward(
  class InternVisionModel (line 279) | class InternVisionModel(PreTrainedModel):
    method __init__ (line 283) | def __init__(self, config: InternVisionConfig):
    method resize_pos_embeddings (line 290) | def resize_pos_embeddings(self, old_size, new_size, patch_size):
    method get_input_embeddings (line 301) | def get_input_embeddings(self):
    method forward (line 304) | def forward(

FILE: clip_benchmark/clip_benchmark/models/internvl.py
  function load_internvl (line 12) | def load_internvl(model_name, pretrained, cache_dir, device):

FILE: clip_benchmark/clip_benchmark/models/internvl_c_pytorch/__init__.py
  class InternVLTokenizer (line 23) | class InternVLTokenizer(nn.Module):
    method __init__ (line 24) | def __init__(self, model_path):
    method forward (line 30) | def forward(self, text, prefix='summarize:'):
  function build_transform (line 39) | def build_transform(task, image_size=224, mean=[0.485, 0.456, 0.406], st...
  function get_model_and_transform (line 56) | def get_model_and_transform(task, image_size, device):
  function load_internvl_c_pytorch (line 65) | def load_internvl_c_pytorch(ckpt_path, device, task, image_size=224):

FILE: clip_benchmark/clip_benchmark/models/internvl_c_pytorch/flash_attention.py
  class FlashAttention (line 15) | class FlashAttention(nn.Module):
    method __init__ (line 26) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 31) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...

FILE: clip_benchmark/clip_benchmark/models/internvl_c_pytorch/internvl_c.py
  class CrossAttention (line 25) | class CrossAttention(nn.Module):
    method __init__ (line 26) | def __init__(
    method forward (line 57) | def forward(self, x, k=None, v=None):
  class AttentiveBlock (line 90) | class AttentiveBlock(nn.Module):
    method __init__ (line 92) | def __init__(self, dim, num_heads, qkv_bias=False, qk_scale=None, drop...
    method forward (line 105) | def forward(self, x_q, x_kv, pos_q, pos_k, bool_masked_pos, rel_pos_bi...
  class AttentionPoolingBlock (line 114) | class AttentionPoolingBlock(AttentiveBlock):
    method forward (line 116) | def forward(self, x):
  class RMSNorm (line 124) | class RMSNorm(nn.Module):
    method __init__ (line 125) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 130) | def forward(self, hidden_states):
  class LayerScale (line 152) | class LayerScale(nn.Module):
    method __init__ (line 153) | def __init__(self, dim, init_values=1e-5, inplace=False, force_fp32=Fa...
    method forward (line 160) | def forward(self, x):
  class Attention (line 170) | class Attention(nn.Module):
    method __init__ (line 171) | def __init__(self, dim, num_heads=8, qkv_bias=False, attn_drop=0., pro...
    method _naive_attn (line 193) | def _naive_attn(self, x):
    method _flash_attn (line 212) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 229) | def forward(self, x):
  class Mlp (line 234) | class Mlp(nn.Module):
    method __init__ (line 238) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 252) | def forward(self, x):
  class Block (line 261) | class Block(nn.Module):
    method __init__ (line 263) | def __init__(
    method forward (line 287) | def forward(self, x):
  class PatchEmbed (line 300) | class PatchEmbed(nn.Module):
    method __init__ (line 304) | def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=...
    method forward (line 318) | def forward(self, x, **kwargs):
  class InternVL_C (line 327) | class InternVL_C(nn.Module):
    method __init__ (line 328) | def __init__(self, in_chans=3, patch_size=14, img_size=224, qkv_bias=F...
    method dtype (line 377) | def dtype(self):
    method forward_features (line 380) | def forward_features(self, x):
    method encode_image (line 391) | def encode_image(self, image):
    method encode_text (line 396) | def encode_text(self, text):
    method forward (line 403) | def forward(self, image, text):

FILE: clip_benchmark/clip_benchmark/models/internvl_huggingface/__init__.py
  class InternVLTokenizer (line 23) | class InternVLTokenizer(nn.Module):
    method __init__ (line 24) | def __init__(self, model_path):
    method forward (line 30) | def forward(self, text, prefix='summarize:'):
  function build_transform (line 39) | def build_transform(task, image_size=224, mean=[0.485, 0.456, 0.406], st...
  function load_internvl_c_huggingface (line 56) | def load_internvl_c_huggingface(ckpt_path, device, task):
  function load_internvl_g_huggingface (line 73) | def load_internvl_g_huggingface(ckpt_path, device, task):

FILE: clip_benchmark/clip_benchmark/models/internvl_huggingface/configuration_intern_vit.py
  class InternVisionConfig (line 15) | class InternVisionConfig(PretrainedConfig):
    method __init__ (line 63) | def __init__(
    method from_pretrained (line 105) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....

FILE: clip_benchmark/clip_benchmark/models/internvl_huggingface/configuration_internvl.py
  class InternVLConfig (line 17) | class InternVLConfig(PretrainedConfig):
    method __init__ (line 57) | def __init__(
    method to_dict (line 97) | def to_dict(self):

FILE: clip_benchmark/clip_benchmark/models/internvl_huggingface/flash_attention.py
  class FlashAttention (line 15) | class FlashAttention(nn.Module):
    method __init__ (line 26) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 31) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...

FILE: clip_benchmark/clip_benchmark/models/internvl_huggingface/modeling_intern_vit.py
  class InternRMSNorm (line 33) | class InternRMSNorm(nn.Module):
    method __init__ (line 34) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 39) | def forward(self, hidden_states):
  class InternVisionEmbeddings (line 61) | class InternVisionEmbeddings(nn.Module):
    method __init__ (line 62) | def __init__(self, config: InternVisionConfig):
    method forward (line 82) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class InternAttention (line 93) | class InternAttention(nn.Module):
    method __init__ (line 96) | def __init__(self, config: InternVisionConfig):
    method _naive_attn (line 126) | def _naive_attn(self, x):
    method _flash_attn (line 145) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 162) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternMLP (line 167) | class InternMLP(nn.Module):
    method __init__ (line 168) | def __init__(self, config: InternVisionConfig):
    method forward (line 175) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternVisionEncoderLayer (line 182) | class InternVisionEncoderLayer(nn.Module):
    method __init__ (line 183) | def __init__(self, config: InternVisionConfig, drop_path_rate: float):
    method forward (line 198) | def forward(
  class InternVisionEncoder (line 213) | class InternVisionEncoder(nn.Module):
    method __init__ (line 223) | def __init__(self, config: InternVisionConfig):
    method forward (line 232) | def forward(
  class InternVisionModel (line 279) | class InternVisionModel(PreTrainedModel):
    method __init__ (line 283) | def __init__(self, config: InternVisionConfig):
    method resize_pos_embeddings (line 290) | def resize_pos_embeddings(self, old_size, new_size, patch_size):
    method get_input_embeddings (line 301) | def get_input_embeddings(self):
    method forward (line 304) | def forward(

FILE: clip_benchmark/clip_benchmark/models/internvl_huggingface/modeling_internvl.py
  class InternVLPreTrainedModel (line 33) | class InternVLPreTrainedModel(PreTrainedModel):
    method _init_weights (line 49) | def _init_weights(self, module):
    method _set_gradient_checkpointing (line 67) | def _set_gradient_checkpointing(self, module, value=False):
  class CrossAttention (line 74) | class CrossAttention(nn.Module):
    method __init__ (line 75) | def __init__(
    method forward (line 106) | def forward(self, x, k=None, v=None):
  class AttentiveBlock (line 139) | class AttentiveBlock(nn.Module):
    method __init__ (line 141) | def __init__(self, dim, num_heads, qkv_bias=False, qk_scale=None, drop...
    method forward (line 154) | def forward(self, x_q, x_kv, pos_q, pos_k, bool_masked_pos, rel_pos_bi...
  class AttentionPoolingBlock (line 163) | class AttentionPoolingBlock(AttentiveBlock):
    method forward (line 165) | def forward(self, x):
  class InternVLModel (line 173) | class InternVLModel(InternVLPreTrainedModel):
    method __init__ (line 177) | def __init__(self, config: InternVLConfig):
    method wrap_backbone_lora (line 219) | def wrap_backbone_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method wrap_qllama_lora (line 229) | def wrap_qllama_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method get_input_embeddings (line 240) | def get_input_embeddings(self):
    method set_input_embeddings (line 243) | def set_input_embeddings(self, value):
    method set_output_embeddings (line 246) | def set_output_embeddings(self, new_embeddings):
    method get_output_embeddings (line 249) | def get_output_embeddings(self) -> nn.Module:
    method generate (line 253) | def generate(
    method get_text_features (line 288) | def get_text_features(
    method get_image_features (line 337) | def get_image_features(
    method encode_image (line 383) | def encode_image(self, image, mode):
    method encode_text (line 407) | def encode_text(self, text):
    method forward (line 420) | def forward(self, image, text, mode='InternVL-C'):
  class InternVL_C (line 437) | class InternVL_C(InternVLModel):
    method encode_image (line 439) | def encode_image(self, image):
    method encode_text (line 448) | def encode_text(self, text):
    method forward (line 461) | def forward(self, image, text):
  class InternVL_G (line 477) | class InternVL_G(InternVLModel):
    method encode_image (line 479) | def encode_image(self, image):
    method encode_text (line 493) | def encode_text(self, text):
    method forward (line 506) | def forward(self, image, text):

FILE: clip_benchmark/clip_benchmark/models/internvl_huggingface/modeling_qllama.py
  function _make_causal_mask (line 42) | def _make_causal_mask(
  function _expand_mask (line 60) | def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Option...
  class LlamaRMSNorm (line 74) | class LlamaRMSNorm(nn.Module):
    method __init__ (line 75) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 83) | def forward(self, hidden_states):
  class LlamaRotaryEmbedding (line 109) | class LlamaRotaryEmbedding(torch.nn.Module):
    method __init__ (line 110) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method forward (line 124) | def forward(self, x, seq_len=None):
  class FixedLlamaRotaryEmbedding (line 141) | class FixedLlamaRotaryEmbedding(torch.nn.Module):
    method __init__ (line 142) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method _set_cos_sin_cache (line 155) | def _set_cos_sin_cache(self, seq_len, device, dtype):
    method forward (line 165) | def forward(self, x, seq_len=None):
  function rotate_half (line 179) | def rotate_half(x):
  function apply_rotary_pos_emb (line 186) | def apply_rotary_pos_emb(q, k, cos, sin, position_ids):
  class LlamaMLP (line 196) | class LlamaMLP(nn.Module):
    method __init__ (line 197) | def __init__(
    method forward (line 209) | def forward(self, x):
  class LlamaAttention (line 213) | class LlamaAttention(nn.Module):
    method __init__ (line 216) | def __init__(self, config: LlamaConfig):
    method _shape (line 235) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 238) | def forward(
  class LlamaCrossAttention (line 304) | class LlamaCrossAttention(nn.Module):
    method __init__ (line 307) | def __init__(self, config: LlamaConfig):
    method _shape (line 329) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 332) | def forward(
  class LlamaDecoderLayer (line 408) | class LlamaDecoderLayer(nn.Module):
    method __init__ (line 409) | def __init__(self, config: LlamaConfig, use_cross_attn: bool):
    method forward (line 423) | def forward(
  class LlamaPreTrainedModel (line 520) | class LlamaPreTrainedModel(PreTrainedModel):
    method _init_weights (line 527) | def _init_weights(self, module):
    method _set_gradient_checkpointing (line 538) | def _set_gradient_checkpointing(self, module, value=False):
  class LlamaModel (line 613) | class LlamaModel(LlamaPreTrainedModel):
    method __init__ (line 621) | def __init__(self, config: LlamaConfig):
    method get_input_embeddings (line 636) | def get_input_embeddings(self):
    method set_input_embeddings (line 639) | def set_input_embeddings(self, value):
    method _prepare_decoder_attention_mask (line 643) | def _prepare_decoder_attention_mask(self, attention_mask, input_shape,...
    method forward (line 667) | def forward(
    method forward_train (line 783) | def forward_train(
  class LlamaForCausalLM (line 915) | class LlamaForCausalLM(LlamaPreTrainedModel):
    method __init__ (line 916) | def __init__(self, config):
    method get_input_embeddings (line 925) | def get_input_embeddings(self):
    method set_input_embeddings (line 928) | def set_input_embeddings(self, value):
    method get_output_embeddings (line 931) | def get_output_embeddings(self):
    method set_output_embeddings (line 934) | def set_output_embeddings(self, new_embeddings):
    method set_decoder (line 937) | def set_decoder(self, decoder):
    method get_decoder (line 940) | def get_decoder(self):
    method forward (line 945) | def forward(
    method prepare_inputs_for_generation (line 1035) | def prepare_inputs_for_generation(
    method _reorder_cache (line 1069) | def _reorder_cache(past_key_values, beam_idx):

FILE: clip_benchmark/clip_benchmark/models/japanese_clip.py
  class DictTensor (line 6) | class DictTensor:
    method __init__ (line 11) | def __init__(self, d: Dict[str, torch.Tensor]):
    method to (line 14) | def to(self, device):
  class JaCLIPForBenchmark (line 18) | class JaCLIPForBenchmark:
    method __init__ (line 23) | def __init__(self, model):
    method encode_text (line 26) | def encode_text(self, dict_tensor):
    method encode_image (line 29) | def encode_image(self, image):
  function load_japanese_clip (line 33) | def load_japanese_clip(pretrained: str, device='cpu', **kwargs):

FILE: clip_benchmark/clip_benchmark/models/open_clip.py
  function load_open_clip (line 4) | def load_open_clip(model_name: str = 'ViT-B-32-quickgelu', pretrained: s...

FILE: clip_benchmark/clip_benchmark/webdataset_builder.py
  function get_parser_args (line 16) | def get_parser_args():
  function main (line 52) | def main():
  function run (line 57) | def run(args):
  function PIL_to_bytes (line 92) | def PIL_to_bytes(image_format):
  function path_to_bytes (line 107) | def path_to_bytes(filepath):
  function convert_dataset (line 112) | def convert_dataset(dataset, split, output_folder, *, transform=None,
  function convert_retrieval_dataset (line 213) | def convert_retrieval_dataset(dataset, split, output_folder, *, transfor...

FILE: clip_benchmark/probe_benchmark/build_df_scaling_experiments.py
  function get_us_dataset (line 70) | def get_us_dataset(pretrained):

FILE: clip_benchmark/setup.py
  function load_requirements (line 14) | def load_requirements(f):

FILE: clip_benchmark/tests/test_clip_benchmark.py
  class base_args (line 11) | class base_args:
  function test_base (line 38) | def test_base():

FILE: internvl_chat/eval/caption/evaluate_caption.py
  class CaptionDataset (line 40) | class CaptionDataset(torch.utils.data.Dataset):
    method __init__ (line 42) | def __init__(self, name, root, annotation, prompt, input_size=224, dyn...
    method __len__ (line 57) | def __len__(self):
    method __getitem__ (line 60) | def __getitem__(self, idx):
  function collate_fn (line 89) | def collate_fn(inputs, tokenizer):
  class InferenceSampler (line 98) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 100) | def __init__(self, size):
    method _get_local_indices (line 108) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 117) | def __iter__(self):
    method __len__ (line 120) | def __len__(self):
  function evaluate_chat_model (line 124) | def evaluate_chat_model():

FILE: internvl_chat/eval/domain_specific/drivelm/evaluate.py
  function post_process (line 27) | def post_process(pred):
  function collate_fn (line 68) | def collate_fn(batches, tokenizer):
  class DriveLMDataset (line 77) | class DriveLMDataset(torch.utils.data.Dataset):
    method __init__ (line 79) | def __init__(self, root, split, prompt, image_path, input_size=224, dy...
    method __len__ (line 94) | def __len__(self):
    method __getitem__ (line 97) | def __getitem__(self, idx):
  class InferenceSampler (line 128) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 130) | def __init__(self, size):
    method _get_local_indices (line 138) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 147) | def __iter__(self):
    method __len__ (line 150) | def __len__(self):
  function evaluate_chat_model (line 154) | def evaluate_chat_model():

FILE: internvl_chat/eval/domain_specific/mme_rw/evaluate.py
  function collate_fn (line 29) | def collate_fn(batches, tokenizer):
  class MMERealworldDataset (line 40) | class MMERealworldDataset(torch.utils.data.Dataset):
    method __init__ (line 42) | def __init__(self, root, prompt, language, subtask: Literal[
    method __len__ (line 59) | def __len__(self):
    method __getitem__ (line 62) | def __getitem__(self, idx):
  class InferenceSampler (line 100) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 102) | def __init__(self, size):
    method _get_local_indices (line 110) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 119) | def __iter__(self):
    method __len__ (line 122) | def __len__(self):
  function post_process (line 126) | def post_process(s, choices):
  function evaluate (line 152) | def evaluate(outputs):
  function evaluate_chat_model (line 190) | def evaluate_chat_model():

FILE: internvl_chat/eval/domain_specific/rs_det/caculate.py
  function calculate_iou (line 9) | def calculate_iou(box1, box2):
  function box_iou (line 32) | def box_iou(boxes1, boxes2):
  function transform_bbox (line 48) | def transform_bbox(bbox, image_size):
  function evaluation_metrics (line 59) | def evaluation_metrics(outputs):

FILE: internvl_chat/eval/domain_specific/rs_det/evaluate.py
  function collate_fn (line 26) | def collate_fn(batches, tokenizer):
  class GroundingDataset (line 35) | class GroundingDataset(torch.utils.data.Dataset):
    method __init__ (line 37) | def __init__(self, root, image_root, prompt='', input_size=224, dynami...
    method __len__ (line 50) | def __len__(self):
    method __getitem__ (line 53) | def __getitem__(self, idx):
  function calculate_iou (line 80) | def calculate_iou(box1, box2):
  class InferenceSampler (line 103) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 105) | def __init__(self, size):
    method _get_local_indices (line 113) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 122) | def __iter__(self):
    method __len__ (line 125) | def __len__(self):
  function evaluate_chat_model (line 129) | def evaluate_chat_model():

FILE: internvl_chat/eval/domain_specific/rs_vqa/evaluate.py
  function collate_fn (line 40) | def collate_fn(batches, tokenizer):
  class RSVQADataset (line 50) | class RSVQADataset(torch.utils.data.Dataset):
    method __init__ (line 52) | def __init__(self, root, prompt, image_root, input_size=224, dynamic_i...
    method __len__ (line 65) | def __len__(self):
    method __getitem__ (line 68) | def __getitem__(self, idx):
  function evaluation_metrics (line 96) | def evaluation_metrics(outputs):
  class InferenceSampler (line 121) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 123) | def __init__(self, size):
    method _get_local_indices (line 131) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 140) | def __iter__(self):
    method __len__ (line 143) | def __len__(self):
  function evaluate_chat_model (line 147) | def evaluate_chat_model():

FILE: internvl_chat/eval/domain_specific/rs_vqa/score.py
  function is_correct_count (line 5) | def is_correct_count(response, answer):
  function is_correct_area (line 23) | def is_correct_area(response, answer):
  function calculate_scores (line 32) | def calculate_scores(data):

FILE: internvl_chat/eval/llava_bench/eval_gpt_review_bench.py
  function get_eval (line 11) | def get_eval(content: str, max_tokens: int):
  function parse_score (line 34) | def parse_score(review):

FILE: internvl_chat/eval/llava_bench/evaluate_llava_bench.py
  class VQADataset (line 22) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 24) | def __init__(self, root, data, prompt, input_size=224, dynamic_image_s...
    method __len__ (line 35) | def __len__(self):
    method __getitem__ (line 38) | def __getitem__(self, idx):
  function evaluate_chat_model (line 57) | def evaluate_chat_model():

FILE: internvl_chat/eval/llava_bench/summarize_gpt_review.py
  function parse_args (line 9) | def parse_args():

FILE: internvl_chat/eval/mantis_eval/evaluate_mantis.py
  function collate_fn (line 26) | def collate_fn(batches, tokenizer):
  class MantisEvalDataset (line 36) | class MantisEvalDataset(torch.utils.data.Dataset):
    method __init__ (line 38) | def __init__(self, root, split, prompt, input_size=224, dynamic_image_...
    method __len__ (line 49) | def __len__(self):
    method __getitem__ (line 52) | def __getitem__(self, idx):
  class InferenceSampler (line 103) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 105) | def __init__(self, size):
    method _get_local_indices (line 113) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 122) | def __iter__(self):
    method __len__ (line 125) | def __len__(self):
  function evaluate_chat_model (line 129) | def evaluate_chat_model():

FILE: internvl_chat/eval/mathvista/calculate_score.py
  function get_most_similar (line 9) | def get_most_similar(prediction, choices):
  function normalize_extracted_answer (line 19) | def normalize_extracted_answer(extraction, choices, question_type, answe...
  function safe_equal (line 70) | def safe_equal(prediction, answer):
  function get_acc_with_contion (line 83) | def get_acc_with_contion(res_pd, key, value):

FILE: internvl_chat/eval/mathvista/evaluate_mathvista.py
  function collate_fn (line 42) | def collate_fn(batches, tokenizer):
  class MathVistaDataset (line 48) | class MathVistaDataset(torch.utils.data.Dataset):
    method __init__ (line 50) | def __init__(self, root, split, input_size=224, dynamic_image_size=False,
    method __len__ (line 60) | def __len__(self):
    method __getitem__ (line 63) | def __getitem__(self, idx):
  class InferenceSampler (line 83) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 85) | def __init__(self, size):
    method _get_local_indices (line 93) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 102) | def __iter__(self):
    method __len__ (line 105) | def __len__(self):
  function evaluate_chat_model (line 109) | def evaluate_chat_model():

FILE: internvl_chat/eval/mathvista/extract_answer.py
  function verify_extraction (line 21) | def verify_extraction(extraction):
  function create_test_prompt (line 28) | def create_test_prompt(demo_prompt, query, response):
  function _extract_answer (line 35) | def _extract_answer(text):
  function extract_answer (line 42) | def extract_answer(response, problem, quick_extract=False):

FILE: internvl_chat/eval/mathvista/utilities.py
  function create_dir (line 14) | def create_dir(output_dir):
  function read_csv (line 19) | def read_csv(file):
  function read_pandas_csv (line 27) | def read_pandas_csv(csv_path):
  function read_json (line 34) | def read_json(path):
  function read_jsonl (line 39) | def read_jsonl(file):
  function read_pickle (line 45) | def read_pickle(path):
  function save_json (line 50) | def save_json(data, path):
  function save_array_img (line 55) | def save_array_img(path, image):
  function contains_digit (line 59) | def contains_digit(text):
  function contains_number_word (line 66) | def contains_number_word(text):
  function contains_quantity_word (line 86) | def contains_quantity_word(text, special_keep_words=[]):
  function is_bool_word (line 115) | def is_bool_word(text):
  function is_digit_string (line 123) | def is_digit_string(text):
  function is_float_string (line 134) | def is_float_string(text):
  function copy_image (line 145) | def copy_image(image_path, output_image_path):
  function copy_dir (line 150) | def copy_dir(src_dir, dst_dir):
  function get_image_size (line 160) | def get_image_size(img_path):
  function get_chat_response (line 166) | def get_chat_response(promot, api_key, model='gpt-3.5-turbo', temperatur...

FILE: internvl_chat/eval/mirb/evaluate_mirb.py
  function eval_scores (line 42) | def eval_scores(results, dataset):
  function exact_yes_no (line 54) | def exact_yes_no(results):
  function exact_in_match (line 74) | def exact_in_match(results):
  function exact_match (line 107) | def exact_match(results, dataset):
  function collate_fn (line 139) | def collate_fn(batches, tokenizer):
  function get_task_instruction (line 151) | def get_task_instruction(dataset):
  class MIRBDataset (line 166) | class MIRBDataset(torch.utils.data.Dataset):
    method __init__ (line 168) | def __init__(self, root, split, input_size=224, dynamic_image_size=False,
    method __len__ (line 188) | def __len__(self):
    method __getitem__ (line 191) | def __getitem__(self, idx):
  class InferenceSampler (line 237) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 239) | def __init__(self, size):
    method _get_local_indices (line 247) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 256) | def __iter__(self):
    method __len__ (line 259) | def __len__(self):
  function evaluate_chat_model (line 263) | def evaluate_chat_model():

FILE: internvl_chat/eval/mmbench/evaluate_mmbench.py
  function collate_fn (line 64) | def collate_fn(batches, tokenizer):
  class MMBenchDataset (line 73) | class MMBenchDataset(torch.utils.data.Dataset):
    method __init__ (line 75) | def __init__(self, root, prompt, language, input_size=224, dynamic_ima...
    method __len__ (line 86) | def __len__(self):
    method __getitem__ (line 89) | def __getitem__(self, idx):
    method load_from_df (line 132) | def load_from_df(self, idx, key):
  class InferenceSampler (line 139) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 141) | def __init__(self, size):
    method _get_local_indices (line 149) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 158) | def __iter__(self):
    method __len__ (line 161) | def __len__(self):
  function post_process (line 165) | def post_process(pred, option):
  function evaluate_chat_model (line 180) | def evaluate_chat_model():

FILE: internvl_chat/eval/mme/calculation.py
  class calculate_metrics (line 16) | class calculate_metrics:
    method divide_chunks (line 17) | def divide_chunks(self, l, n=2):
    method parse_pred_ans (line 24) | def parse_pred_ans(self, pred_ans):
    method compute_metric (line 40) | def compute_metric(self, gts, preds):
    method process_result (line 84) | def process_result(self, results_dir):

FILE: internvl_chat/eval/mme/eval.py
  function load_image (line 12) | def load_image(image_file, input_size=224):
  function post_processing (line 26) | def post_processing(response):

FILE: internvl_chat/eval/mmhal/evaluate_mmhal.py
  function collate_fn (line 29) | def collate_fn(batches, tokenizer):
  class VQADataset (line 39) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 41) | def __init__(
    method __len__ (line 58) | def __len__(self):
    method __getitem__ (line 61) | def __getitem__(self, idx):
  class InferenceSampler (line 97) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 99) | def __init__(self, size):
    method _get_local_indices (line 107) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 116) | def __iter__(self):
    method __len__ (line 119) | def __len__(self):
  function evaluate_chat_model (line 123) | def evaluate_chat_model():

FILE: internvl_chat/eval/mmiu/evaluate_mmiu.py
  function collate_fn (line 25) | def collate_fn(batches, tokenizer):
  class MMIUDataset (line 35) | class MMIUDataset(torch.utils.data.Dataset):
    method __init__ (line 37) | def __init__(self, meta, input_size=224, dynamic_image_size=False,
    method __len__ (line 51) | def __len__(self):
    method __getitem__ (line 54) | def __getitem__(self, idx):
  class InferenceSampler (line 111) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 113) | def __init__(self, size):
    method _get_local_indices (line 121) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 130) | def __iter__(self):
    method __len__ (line 133) | def __len__(self):
  function post_process (line 137) | def post_process(pred, option):
  function evaluate_chat_model (line 152) | def evaluate_chat_model():

FILE: internvl_chat/eval/mmmu/data_utils.py
  function save_json (line 55) | def save_json(filename, ds):
  function get_multi_choice_info (line 60) | def get_multi_choice_info(options):
  function load_yaml (line 76) | def load_yaml(file_path):
  function parse_img_path (line 86) | def parse_img_path(text):
  function process_single_sample (line 91) | def process_single_sample(data):
  function save_json (line 105) | def save_json(filename, ds):
  function save_jsonl (line 110) | def save_jsonl(filename, data):
  function save_args (line 128) | def save_args(args, path_dir):
  function construct_prompt (line 138) | def construct_prompt(sample, config):

FILE: internvl_chat/eval/mmmu/eval_utils.py
  function parse_multi_choice_response (line 11) | def parse_multi_choice_response(response, all_choices, index2ans):
  function check_is_number (line 67) | def check_is_number(string):
  function normalize_str (line 79) | def normalize_str(string):
  function extract_numbers (line 104) | def extract_numbers(string):
  function parse_open_response (line 127) | def parse_open_response(response):
  function eval_multi_choice (line 183) | def eval_multi_choice(gold_i, pred_i):
  function eval_open (line 200) | def eval_open(gold_i, pred_i):
  function evaluate (line 229) | def evaluate(samples):
  function calculate_ins_level_acc (line 255) | def calculate_ins_level_acc(results: Dict):

FILE: internvl_chat/eval/mmmu/evaluate_mmmu.py
  function collate_fn (line 39) | def collate_fn(batches, tokenizer):
  class MMMUDataset (line 48) | class MMMUDataset(torch.utils.data.Dataset):
    method __init__ (line 50) | def __init__(self, root, split, prompt, input_size=224, dynamic_image_...
    method __len__ (line 67) | def __len__(self):
    method __getitem__ (line 70) | def __getitem__(self, idx):
  class InferenceSampler (line 119) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 121) | def __init__(self, size):
    method _get_local_indices (line 129) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 138) | def __iter__(self):
    method __len__ (line 141) | def __len__(self):
  function post_process (line 145) | def post_process(pred, option):
  function evaluate_chat_model (line 160) | def evaluate_chat_model():

FILE: internvl_chat/eval/mmmu_pro/evaluate.py
  function mmmu_process_results (line 16) | def mmmu_process_results(results):
  function extract_subset_name (line 40) | def extract_subset_name(input_string):
  function mmmu_aggregate_results (line 51) | def mmmu_aggregate_results(results):
  function calculate_ins_level_acc (line 94) | def calculate_ins_level_acc(results):
  function eval_multi_choice (line 143) | def eval_multi_choice(gold_i, pred_i):
  function eval_open (line 161) | def eval_open(gold_i, pred_i):
  function evaluate_mmmu (line 190) | def evaluate_mmmu(samples):
  function parse_multi_choice_responses (line 214) | def parse_multi_choice_responses(response):
  function parse_multi_choice_response (line 219) | def parse_multi_choice_response(response, all_choices, index2ans):
  function extract_numbers (line 296) | def extract_numbers(string):
  function check_is_number (line 320) | def check_is_number(string):
  function normalize_str (line 333) | def normalize_str(string):
  function parse_open_response (line 359) | def parse_open_response(response):
  function get_multi_choice_info (line 431) | def get_multi_choice_info(options):
  function check_files (line 451) | def check_files(input_dir):

FILE: internvl_chat/eval/mmmu_pro/evaluate_mmmu_pro.py
  function replace_images_tokens (line 34) | def replace_images_tokens(input_string):
  function parse_options (line 43) | def parse_options(options):
  function construct_prompt (line 49) | def construct_prompt(doc):
  function mmmu_doc_to_text (line 56) | def mmmu_doc_to_text(doc):
  function origin_mmmu_doc_to_visual (line 61) | def origin_mmmu_doc_to_visual(doc):
  function vision_mmmu_doc_to_visual (line 70) | def vision_mmmu_doc_to_visual(doc):
  function process_prompt (line 74) | def process_prompt(data):
  function run_and_save (line 84) | def run_and_save(pipe):

FILE: internvl_chat/eval/mmvet/evaluate_mmvet.py
  function collate_fn (line 24) | def collate_fn(batches, tokenizer):
  class VQADataset (line 33) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 35) | def __init__(self, root, data, prompt, input_size=224, dynamic_image_s...
    method __len__ (line 46) | def __len__(self):
    method __getitem__ (line 49) | def __getitem__(self, idx):
  function evaluate_chat_model (line 68) | def evaluate_chat_model():

FILE: internvl_chat/eval/mmvetv2/evaluate_mmvet_v2.py
  function collate_fn (line 26) | def collate_fn(batches, tokenizer):
  class VQADataset (line 35) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 37) | def __init__(self, root, data, prompt, input_size=224, dynamic_image_s...
    method __len__ (line 50) | def __len__(self):
    method __getitem__ (line 53) | def __getitem__(self, idx):
  class InferenceSampler (line 80) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 82) | def __init__(self, size):
    method _get_local_indices (line 90) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 99) | def __iter__(self):
    method __len__ (line 102) | def __len__(self):
  function evaluate_chat_model (line 106) | def evaluate_chat_model():

FILE: internvl_chat/eval/mmvp/evaluate_mmvp.py
  function collate_fn (line 25) | def collate_fn(batches, tokenizer):
  class MMVPDataset (line 34) | class MMVPDataset(torch.utils.data.Dataset):
    method __init__ (line 36) | def __init__(self, root, prompt, input_size=224, dynamic_image_size=Fa...
    method __len__ (line 53) | def __len__(self):
    method __getitem__ (line 56) | def __getitem__(self, idx):
  class InferenceSampler (line 98) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 100) | def __init__(self, size):
    method _get_local_indices (line 108) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 117) | def __iter__(self):
    method __len__ (line 120) | def __len__(self):
  function post_process (line 124) | def post_process(pred, option):
  function evaluate_chat_model (line 139) | def evaluate_chat_model():

FILE: internvl_chat/eval/mpdocvqa/evaluate_vqa.py
  function collate_fn (line 32) | def collate_fn(batches, tokenizer):
  class VQADataset (line 42) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 44) | def __init__(self, root, test, prompt, input_size=224, dynamic_image_s...
    method __len__ (line 56) | def __len__(self):
    method __getitem__ (line 59) | def __getitem__(self, idx):
  class InferenceSampler (line 101) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 103) | def __init__(self, size):
    method _get_local_indices (line 111) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 120) | def __iter__(self):
    method __len__ (line 123) | def __len__(self):
  function evaluate_chat_model (line 127) | def evaluate_chat_model():

FILE: internvl_chat/eval/mpdocvqa/infographicsvqa_eval.py
  function save_json (line 17) | def save_json(file_path, data):
  function levenshtein_distance (line 22) | def levenshtein_distance(s1, s2):
  function validate_data (line 38) | def validate_data(gtFilePath, submFilePath):
  function evaluate_method (line 91) | def evaluate_method(gtFilePath, submFilePath, evaluationParams):
  function display_results (line 204) | def display_results(results, show_answer_types):

FILE: internvl_chat/eval/mvbench/evaluate_mvbench.py
  function collate_fn (line 52) | def collate_fn(batches, tokenizer):
  class MVBenchDataset (line 61) | class MVBenchDataset(torch.utils.data.Dataset):
    method __init__ (line 63) | def __init__(self, data_dir, data_list, prompt, question_prompt, num_s...
    method __len__ (line 91) | def __len__(self):
    method __str__ (line 94) | def __str__(self):
    method get_index (line 116) | def get_index(self, bound, fps, max_frame, first_idx=0):
    method read_video (line 130) | def read_video(self, video_path, bound=None):
    method read_gif (line 143) | def read_gif(self, video_path, bound=None, fps=25):
    method read_frame (line 157) | def read_frame(self, video_path, bound=None, fps=3):
    method qa_template (line 167) | def qa_template(self, data):
    method __getitem__ (line 180) | def __getitem__(self, idx):
  class InferenceSampler (line 220) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 222) | def __init__(self, size):
    method _get_local_indices (line 230) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 239) | def __iter__(self):
    method __len__ (line 242) | def __len__(self):
  function check_ans (line 246) | def check_ans(pred, gt):
  function evaluate_chat_model (line 265) | def evaluate_chat_model():

FILE: internvl_chat/eval/pope/eval_pope.py
  function eval_pope (line 6) | def eval_pope(answers, label_file):

FILE: internvl_chat/eval/pope/evaluate_pope.py
  function extract_answer (line 38) | def extract_answer(text):
  function collate_fn (line 45) | def collate_fn(batches, tokenizer):
  class VQADataset (line 54) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 56) | def __init__(self, root, data, prompt, input_size=224, dynamic_image_s...
    method __len__ (line 67) | def __len__(self):
    method __getitem__ (line 70) | def __getitem__(self, idx):
  class InferenceSampler (line 98) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 100) | def __init__(self, size):
    method _get_local_indices (line 108) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 117) | def __iter__(self):
    method __len__ (line 120) | def __len__(self):
  function evaluate_chat_model (line 124) | def evaluate_chat_model():

FILE: internvl_chat/eval/refcoco/evaluate_grounding.py
  function box_iou (line 29) | def box_iou(boxes1, boxes2):
  function collate_fn (line 45) | def collate_fn(batches, tokenizer):
  class RefCOCODataset (line 53) | class RefCOCODataset(torch.utils.data.Dataset):
    method __init__ (line 55) | def __init__(self, test, prompt, input_size=224, dynamic_image_size=Fa...
    method __len__ (line 65) | def __len__(self):
    method __getitem__ (line 68) | def __getitem__(self, idx):
  class InferenceSampler (line 94) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 96) | def __init__(self, size):
    method _get_local_indices (line 104) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 113) | def __iter__(self):
    method __len__ (line 116) | def __len__(self):
  function evaluate_chat_model (line 120) | def evaluate_chat_model():

FILE: internvl_chat/eval/scienceqa/evaluate_scienceqa.py
  function extract_answer (line 41) | def extract_answer(text):
  function collate_fn (line 48) | def collate_fn(batches, tokenizer):
  class ScienceQADataset (line 57) | class ScienceQADataset(torch.utils.data.Dataset):
    method __init__ (line 59) | def __init__(self, root, prompt, input_size=224, dynamic_image_size=Fa...
    method __len__ (line 70) | def __len__(self):
    method __getitem__ (line 73) | def __getitem__(self, idx):
  class InferenceSampler (line 114) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 116) | def __init__(self, size):
    method _get_local_indices (line 124) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 133) | def __iter__(self):
    method __len__ (line 136) | def __len__(self):
  function post_process (line 140) | def post_process(pred, option):
  function evaluate_chat_model (line 161) | def evaluate_chat_model():

FILE: internvl_chat/eval/seed/calculation.py
  function is_integer_string (line 16) | def is_integer_string(s):
  function filter_questions (line 24) | def filter_questions(data, task='all'):

FILE: internvl_chat/eval/seed/evaluate_seed.py
  function collate_fn (line 25) | def collate_fn(batches, tokenizer):
  class MultipleChoiceDataset (line 33) | class MultipleChoiceDataset(torch.utils.data.Dataset):
    method __init__ (line 35) | def __init__(self, root, annotation, input_size=224, dynamic_image_siz...
    method __len__ (line 46) | def __len__(self):
    method __getitem__ (line 49) | def __getitem__(self, idx):
  class InferenceSampler (line 71) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 73) | def __init__(self, size):
    method _get_local_indices (line 81) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 90) | def __iter__(self):
    method __len__ (line 93) | def __len__(self):
  function post_process (line 97) | def post_process(pred, option):
  function evaluate_chat_model (line 112) | def evaluate_chat_model():

FILE: internvl_chat/eval/tiny_lvlm/calculate_score.py
  function parse_args (line 10) | def parse_args():
  function main (line 17) | def main(args):

FILE: internvl_chat/eval/tiny_lvlm/evaluate_lvlm.py
  function collate_fn (line 24) | def collate_fn(batches, tokenizer):
  class VQADataset (line 33) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 35) | def __init__(self, root, prompt, input_size=224, dynamic_image_size=Fa...
    method __len__ (line 56) | def __len__(self):
    method __getitem__ (line 59) | def __getitem__(self, idx):
  class InferenceSampler (line 82) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 84) | def __init__(self, size):
    method _get_local_indices (line 92) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 101) | def __iter__(self):
    method __len__ (line 104) | def __len__(self):
  function evaluate_chat_model (line 108) | def evaluate_chat_model():

FILE: internvl_chat/eval/tiny_lvlm/tools.py
  function remove_special_chars (line 5) | def remove_special_chars(s):
  function has_word (line 11) | def has_word(sentence, word):
  class VQAEval (line 20) | class VQAEval:
    method __init__ (line 21) | def __init__(self):
    method evaluate (line 186) | def evaluate(self, answer, gt_answers):
    method evaluate_MRR (line 213) | def evaluate_MRR(self, answer, gt_answers):
    method processPunctuation (line 231) | def processPunctuation(self, inText):
    method processDigitArticle (line 243) | def processDigitArticle(self, inText):

FILE: internvl_chat/eval/vqa/evaluate_vqa.py
  function relaxed_correctness (line 144) | def relaxed_correctness(target: str,
  function evaluate_relaxed_accuracy (line 186) | def evaluate_relaxed_accuracy(entries):
  function evaluate_exact_match_accuracy (line 199) | def evaluate_exact_match_accuracy(entries):
  function collate_fn (line 213) | def collate_fn(batches, tokenizer):
  class VQADataset (line 222) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 224) | def __init__(self, train, test, prompt, few_shot, input_size=224, dyna...
    method __len__ (line 237) | def __len__(self):
    method __getitem__ (line 240) | def __getitem__(self, idx):
  class InferenceSampler (line 273) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 275) | def __init__(self, size):
    method _get_local_indices (line 283) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 292) | def __iter__(self):
    method __len__ (line 295) | def __len__(self):
  function post_process (line 299) | def post_process(response):
  function evaluate_chat_model (line 318) | def evaluate_chat_model():

FILE: internvl_chat/eval/vqa/infographicsvqa_eval.py
  function save_json (line 17) | def save_json(file_path, data):
  function levenshtein_distance (line 22) | def levenshtein_distance(s1, s2):
  function validate_data (line 38) | def validate_data(gtFilePath, submFilePath):
  function evaluate_method (line 91) | def evaluate_method(gtFilePath, submFilePath, evaluationParams):
  function display_results (line 204) | def display_results(results, show_answer_types):

FILE: internvl_chat/eval/vqa/textvqa_eval.py
  class EvalAIAnswerProcessor (line 8) | class EvalAIAnswerProcessor:
    method __init__ (line 179) | def __init__(self, *args, **kwargs):
    method word_tokenize (line 182) | def word_tokenize(self, word):
    method process_punctuation (line 187) | def process_punctuation(self, in_text):
    method process_digit_article (line 199) | def process_digit_article(self, in_text):
    method __call__ (line 214) | def __call__(self, item):
  class TextVQAAccuracyEvaluator (line 222) | class TextVQAAccuracyEvaluator:
    method __init__ (line 223) | def __init__(self):
    method _compute_answer_scores (line 226) | def _compute_answer_scores(self, raw_answers):
    method eval_pred_list (line 249) | def eval_pred_list(self, pred_list, disable_tqdm=False):
  class STVQAAccuracyEvaluator (line 261) | class STVQAAccuracyEvaluator:
    method __init__ (line 262) | def __init__(self):
    method eval_pred_list (line 265) | def eval_pred_list(self, pred_list):
  class STVQAANLSEvaluator (line 277) | class STVQAANLSEvaluator:
    method __init__ (line 278) | def __init__(self):
    method get_anls (line 283) | def get_anls(self, s1, s2):
    method eval_pred_list (line 290) | def eval_pred_list(self, pred_list):
  class TextCapsBleu4Evaluator (line 302) | class TextCapsBleu4Evaluator:
    method __init__ (line 303) | def __init__(self):
    method eval_pred_list (line 322) | def eval_pred_list(self, pred_list):

FILE: internvl_chat/internvl/conversation.py
  class SeparatorStyle (line 13) | class SeparatorStyle(IntEnum):
  class Conversation (line 37) | class Conversation:
    method get_prompt (line 61) | def get_prompt(self) -> str:
    method set_system_message (line 251) | def set_system_message(self, system_message: str):
    method append_message (line 255) | def append_message(self, role: str, message: str):
    method update_last_message (line 259) | def update_last_message(self, message: str):
    method to_gradio_chatbot (line 267) | def to_gradio_chatbot(self):
    method to_openai_api_messages (line 277) | def to_openai_api_messages(self):
    method copy (line 289) | def copy(self):
    method dict (line 304) | def dict(self):
  function register_conv_template (line 318) | def register_conv_template(template: Conversation, override: bool = False):
  function get_conv_template (line 328) | def get_conv_template(name: str) -> Conversation:

FILE: internvl_chat/internvl/dist_utils.py
  function _find_free_port (line 14) | def _find_free_port():
  function _is_free_port (line 25) | def _is_free_port(port):
  function init_dist (line 32) | def init_dist(launcher, backend='nccl', **kwargs):
  function _init_dist_pytorch (line 45) | def _init_dist_pytorch(backend, **kwargs):
  function _init_dist_mpi (line 54) | def _init_dist_mpi(backend, **kwargs):
  function _init_dist_slurm (line 67) | def _init_dist_slurm(backend, port=None):

FILE: internvl_chat/internvl/model/__init__.py
  function split_model (line 14) | def split_model(num_layers, vit_alpha=0.5):
  function load_model_and_tokenizer (line 39) | def load_model_and_tokenizer(args):

FILE: internvl_chat/internvl/model/internlm2/configuration_internlm2.py
  class InternLM2Config (line 27) | class InternLM2Config(PretrainedConfig):
    method __init__ (line 77) | def __init__(  # pylint: disable=W0102
    method _rope_scaling_validation (line 131) | def _rope_scaling_validation(self):

FILE: internvl_chat/internvl/model/internlm2/modeling_internlm2.py
  function _import_flash_attn (line 65) | def _import_flash_attn():
  function _get_unpad_data (line 83) | def _get_unpad_data(attention_mask):
  function _make_causal_mask (line 96) | def _make_causal_mask(
  function _expand_mask (line 114) | def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Option...
  class InternLM2RMSNorm (line 129) | class InternLM2RMSNorm(nn.Module):
    method __init__ (line 130) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 138) | def forward(self, hidden_states):
  class InternLM2RotaryEmbedding (line 161) | class InternLM2RotaryEmbedding(nn.Module):
    method __init__ (line 162) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method _set_cos_sin_cache (line 176) | def _set_cos_sin_cache(self, seq_len, device, dtype):
    method forward (line 186) | def forward(self, x, seq_len=None):
  class InternLM2LinearScalingRotaryEmbedding (line 198) | class InternLM2LinearScalingRotaryEmbedding(InternLM2RotaryEmbedding):
    method __init__ (line 201) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method _set_cos_sin_cache (line 205) | def _set_cos_sin_cache(self, seq_len, device, dtype):
  class InternLM2DynamicNTKScalingRotaryEmbedding (line 218) | class InternLM2DynamicNTKScalingRotaryEmbedding(InternLM2RotaryEmbedding):
    method __init__ (line 223) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method _set_cos_sin_cache (line 227) | def _set_cos_sin_cache(self, seq_len, device, dtype):
  function rotate_half (line 247) | def rotate_half(x):
  function apply_rotary_pos_emb (line 255) | def apply_rotary_pos_emb(q, k, cos, sin, position_ids, unsqueeze_dim=1):
  class InternLM2MLP (line 264) | class InternLM2MLP(nn.Module):
    method __init__ (line 265) | def __init__(self, config):
    method forward (line 275) | def forward(self, x):
  function repeat_kv (line 282) | def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
  class InternLM2Attention (line 295) | class InternLM2Attention(nn.Module):
    method __init__ (line 298) | def __init__(self, config: InternLM2Config):
    method _init_rope (line 324) | def _init_rope(self):
    method _shape (line 352) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 355) | def forward(
  class InternLM2FlashAttention2 (line 444) | class InternLM2FlashAttention2(InternLM2Attention):
    method forward (line 451) | def forward(
    method _flash_attention_forward (line 523) | def _flash_attention_forward(
    method _unpad_input (line 577) | def _unpad_input(self, query_layer, key_layer, value_layer, attention_...
  class InternLM2DecoderLayer (line 624) | class InternLM2DecoderLayer(nn.Module):
    method __init__ (line 625) | def __init__(self, config: InternLM2Config):
    method forward (line 635) | def forward(
  class InternLM2PreTrainedModel (line 720) | class InternLM2PreTrainedModel(PreTrainedModel):
    method _init_weights (line 728) | def _init_weights(self, module):
  class InternLM2Model (line 810) | class InternLM2Model(InternLM2PreTrainedModel):
    method __init__ (line 820) | def __init__(self, config: InternLM2Config):
    method get_input_embeddings (line 838) | def get_input_embeddings(self):
    method set_input_embeddings (line 841) | def set_input_embeddings(self, value):
    method _prepare_decoder_attention_mask (line 844) | def _prepare_decoder_attention_mask(self, attention_mask, input_shape,...
    method forward (line 868) | def forward(
  class InternLM2ForCausalLM (line 1002) | class InternLM2ForCausalLM(InternLM2PreTrainedModel):
    method __init__ (line 1007) | def __init__(self, config):
    method get_input_embeddings (line 1016) | def get_input_embeddings(self):
    method set_input_embeddings (line 1019) | def set_input_embeddings(self, value):
    method get_output_embeddings (line 1022) | def get_output_embeddings(self):
    method set_output_embeddings (line 1025) | def set_output_embeddings(self, new_embeddings):
    method set_decoder (line 1028) | def set_decoder(self, decoder):
    method get_decoder (line 1031) | def get_decoder(self):
    method forward (line 1036) | def forward(
    method prepare_inputs_for_generation (line 1126) | def prepare_inputs_for_generation(
    method _reorder_cache (line 1166) | def _reorder_cache(past_key_values, beam_idx):
    method build_inputs (line 1174) | def build_inputs(self, tokenizer, query: str, history: List[Tuple[str,...
    method chat (line 1187) | def chat(
    method stream_chat (line 1223) | def stream_chat(
  class InternLM2ForSequenceClassification (line 1325) | class InternLM2ForSequenceClassification(InternLM2PreTrainedModel):
    method __init__ (line 1326) | def __init__(self, config):
    method get_input_embeddings (line 1335) | def get_input_embeddings(self):
    method set_input_embeddings (line 1338) | def set_input_embeddings(self, value):
    method forward (line 1342) | def forward(

FILE: internvl_chat/internvl/model/internlm2/tokenization_internlm2.py
  class InternLM2Tokenizer (line 34) | class InternLM2Tokenizer(PreTrainedTokenizer):
    method __init__ (line 48) | def __init__(
    method no_prefix_space_tokens (line 80) | def no_prefix_space_tokens(self):
    method vocab_size (line 87) | def vocab_size(self):
    method bos_token_id (line 92) | def bos_token_id(self) -> Optional[int]:
    method eos_token_id (line 96) | def eos_token_id(self) -> Optional[int]:
    method get_vocab (line 99) | def get_vocab(self):
    method _tokenize (line 105) | def _tokenize(self, text):
    method _convert_token_to_id (line 109) | def _convert_token_to_id(self, token):
    method _convert_id_to_token (line 113) | def _convert_id_to_token(self, index):
    method _maybe_add_prefix_space (line 118) | def _maybe_add_prefix_space(self, tokens, decoded):
    method convert_tokens_to_string (line 124) | def convert_tokens_to_string(self, tokens):
    method save_vocabulary (line 145) | def save_vocabulary(self, save_directory, filename_prefix: Optional[st...
    method build_inputs_with_special_tokens (line 172) | def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=No...
    method get_special_tokens_mask (line 188) | def get_special_tokens_mask(
    method create_token_type_ids_from_sequences (line 215) | def create_token_type_ids_from_sequences(

FILE: internvl_chat/internvl/model/internlm2/tokenization_internlm2_fast.py
  class InternLM2Converter (line 38) | class InternLM2Converter(SpmConverter):
    method vocab (line 41) | def vocab(self, proto):
    method unk_id (line 50) | def unk_id(self, proto):
    method decoder (line 54) | def decoder(self, replacement, add_prefix_space):
    method tokenizer (line 64) | def tokenizer(self, proto):
    method normalizer (line 92) | def normalizer(self, proto):
    method pre_tokenizer (line 99) | def pre_tokenizer(self, replacement, add_prefix_space):
  class InternLM2TokenizerFast (line 107) | class InternLM2TokenizerFast(PreTrainedTokenizerFast):
    method __init__ (line 114) | def __init__(
    method can_save_slow_tokenizer (line 147) | def can_save_slow_tokenizer(self) -> bool:
    method update_post_processor (line 150) | def update_post_processor(self):
    method add_eos_token (line 177) | def add_eos_token(self):
    method add_bos_token (line 181) | def add_bos_token(self):
    method add_eos_token (line 185) | def add_eos_token(self, value):
    method add_bos_token (line 190) | def add_bos_token(self, value):
    method save_vocabulary (line 194) | def save_vocabulary(self, save_directory: str, filename_prefix: Option...

FILE: internvl_chat/internvl/model/internvl_chat/configuration_intern_vit.py
  class InternVisionConfig (line 16) | class InternVisionConfig(PretrainedConfig):
    method __init__ (line 64) | def __init__(
    method from_pretrained (line 108) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....

FILE: internvl_chat/internvl/model/internvl_chat/configuration_internvl_chat.py
  class InternVLChatConfig (line 20) | class InternVLChatConfig(PretrainedConfig):
    method __init__ (line 24) | def __init__(
    method to_dict (line 86) | def to_dict(self):

FILE: internvl_chat/internvl/model/internvl_chat/modeling_intern_vit.py
  class FlashAttention (line 35) | class FlashAttention(nn.Module):
    method __init__ (line 46) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 51) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...
  class InternRMSNorm (line 99) | class InternRMSNorm(nn.Module):
    method __init__ (line 100) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 105) | def forward(self, hidden_states):
  class InternVisionEmbeddings (line 133) | class InternVisionEmbeddings(nn.Module):
    method __init__ (line 134) | def __init__(self, config: InternVisionConfig):
    method _get_pos_embed (line 154) | def _get_pos_embed(self, pos_embed, H, W):
    method forward (line 162) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class InternAttention (line 177) | class InternAttention(nn.Module):
    method __init__ (line 180) | def __init__(self, config: InternVisionConfig):
    method _naive_attn (line 210) | def _naive_attn(self, x):
    method _flash_attn (line 229) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 246) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternMLP (line 251) | class InternMLP(nn.Module):
    method __init__ (line 252) | def __init__(self, config: InternVisionConfig):
    method forward (line 259) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternVisionEncoderLayer (line 266) | class InternVisionEncoderLayer(nn.Module):
    method __init__ (line 267) | def __init__(self, config: InternVisionConfig, drop_path_rate: float):
    method forward (line 283) | def forward(
  class InternVisionEncoder (line 298) | class InternVisionEncoder(nn.Module):
    method __init__ (line 308) | def __init__(self, config: InternVisionConfig):
    method forward (line 317) | def forward(
  class InternVisionModel (line 364) | class InternVisionModel(PreTrainedModel):
    method __init__ (line 371) | def __init__(self, config: InternVisionConfig):
    method resize_pos_embeddings (line 378) | def resize_pos_embeddings(self, old_size, new_size, patch_size):
    method get_input_embeddings (line 390) | def get_input_embeddings(self):
    method forward (line 393) | def forward(

FILE: internvl_chat/internvl/model/internvl_chat/modeling_internvl_chat.py
  function version_cmp (line 31) | def version_cmp(v1, v2, op='eq'):
  class InternVLChatModel (line 39) | class InternVLChatModel(PreTrainedModel):
    method __init__ (line 48) | def __init__(self, config: InternVLChatConfig, vision_model=None, lang...
    method wrap_backbone_lora (line 111) | def wrap_backbone_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method wrap_llm_lora (line 121) | def wrap_llm_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method forward (line 143) | def forward(
    method pixel_shuffle (line 257) | def pixel_shuffle(self, x, scale_factor=0.5):
    method extract_feature (line 273) | def extract_feature(self, pixel_values):
    method batch_chat (line 293) | def batch_chat(self, tokenizer, pixel_values, questions, generation_co...
    method chat (line 343) | def chat(self, tokenizer, pixel_values, question, generation_config, h...
    method generate (line 401) | def generate(
    method lm_head (line 443) | def lm_head(self):
    method get_input_embeddings (line 446) | def get_input_embeddings(self):
    method get_output_embeddings (line 449) | def get_output_embeddings(self):

FILE: internvl_chat/internvl/model/phi3/configuration_phi3.py
  class Phi3Config (line 29) | class Phi3Config(PretrainedConfig):
    method __init__ (line 115) | def __init__(
    method _rope_scaling_validation (line 173) | def _rope_scaling_validation(self):

FILE: internvl_chat/internvl/model/phi3/modeling_phi3.py
  class Phi3RMSNorm (line 78) | class Phi3RMSNorm(nn.Module):
    method __init__ (line 79) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 87) | def forward(self, hidden_states):
  function _get_unpad_data (line 96) | def _get_unpad_data(attention_mask):
  class Phi3RotaryEmbedding (line 109) | class Phi3RotaryEmbedding(nn.Module):
    method __init__ (line 110) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method forward (line 119) | def forward(self, x, position_ids, seq_len=None):
  class Phi3SuScaledRotaryEmbedding (line 139) | class Phi3SuScaledRotaryEmbedding(Phi3RotaryEmbedding):
    method __init__ (line 140) | def __init__(self, dim, config, device=None):
    method forward (line 148) | def forward(self, x, position_ids, seq_len=None):
  class Phi3YarnScaledRotaryEmbedding (line 180) | class Phi3YarnScaledRotaryEmbedding(Phi3RotaryEmbedding):
    method __init__ (line 181) | def __init__(self, dim, config, device=None):
    method forward (line 189) | def forward(self, x, position_ids, seq_len=None):
  function rotate_half (line 222) | def rotate_half(x):
  function apply_rotary_pos_emb (line 230) | def apply_rotary_pos_emb(q, k, cos, sin, position_ids=None, unsqueeze_di...
  class Phi3MLP (line 257) | class Phi3MLP(nn.Module):
    method __init__ (line 258) | def __init__(self, config):
    method forward (line 267) | def forward(self, hidden_states: torch.FloatTensor) -> torch.FloatTensor:
  function repeat_kv (line 277) | def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
  class Phi3Attention (line 289) | class Phi3Attention(nn.Module):
    method __init__ (line 292) | def __init__(self, config: Phi3Config, layer_idx: Optional[int] = None):
    method _init_rope (line 326) | def _init_rope(self):
    method forward (line 342) | def forward(
  class Phi3FlashAttention2 (line 424) | class Phi3FlashAttention2(Phi3Attention):
    method __init__ (line 432) | def __init__(self, *args, **kwargs):
    method forward (line 440) | def forward(
    method _flash_attention_forward (line 589) | def _flash_attention_forward(
    method _upad_input (line 690) | def _upad_input(self, query_layer, key_layer, value_layer, attention_m...
  class Phi3SdpaAttention (line 735) | class Phi3SdpaAttention(Phi3Attention):
    method forward (line 743) | def forward(
  class Phi3DecoderLayer (line 831) | class Phi3DecoderLayer(nn.Module):
    method __init__ (line 832) | def __init__(self, config: Phi3Config, layer_idx: int):
    method forward (line 845) | def forward(
  class Phi3PreTrainedModel (line 930) | class Phi3PreTrainedModel(PreTrainedModel):
    method __init__ (line 942) | def __init__(self, config: Phi3Config):
    method _init_weights (line 948) | def _init_weights(self, module):
  class Phi3Model (line 1034) | class Phi3Model(Phi3PreTrainedModel):
    method __init__ (line 1042) | def __init__(self, config: Phi3Config):
    method get_input_embeddings (line 1060) | def get_input_embeddings(self):
    method set_input_embeddings (line 1063) | def set_input_embeddings(self, value):
    method forward (line 1067) | def forward(
  class Phi3ForCausalLM (line 1204) | class Phi3ForCausalLM(Phi3PreTrainedModel):
    method __init__ (line 1208) | def __init__(self, config):
    method get_input_embeddings (line 1218) | def get_input_embeddings(self):
    method set_input_embeddings (line 1222) | def set_input_embeddings(self, value):
    method get_output_embeddings (line 1226) | def get_output_embeddings(self):
    method set_output_embeddings (line 1230) | def set_output_embeddings(self, new_embeddings):
    method set_decoder (line 1234) | def set_decoder(self, decoder):
    method get_decoder (line 1238) | def get_decoder(self):
    method forward (line 1244) | def forward(
    method prepare_inputs_for_generation (line 1332) | def prepare_inputs_for_generation(
    method _reorder_cache (line 1390) | def _reorder_cache(past_key_values, beam_idx):
  class Phi3ForSequenceClassification (line 1415) | class Phi3ForSequenceClassification(Phi3PreTrainedModel):
    method __init__ (line 1416) | def __init__(self, config):
    method get_input_embeddings (line 1425) | def get_input_embeddings(self):
    method set_input_embeddings (line 1428) | def set_input_embeddings(self, value):
    method forward (line 1432) | def forward(
  class Phi3ForTokenClassification (line 1531) | class Phi3ForTokenClassification(Phi3PreTrainedModel):
    method __init__ (line 1532) | def __init__(self, config: Phi3Config):
    method forward (line 1555) | def forward(

FILE: internvl_chat/internvl/patch/internlm2_packed_training_patch.py
  class InternLM2FlashAttention2ForPackedTraining (line 15) | class InternLM2FlashAttention2ForPackedTraining(InternLM2FlashAttention2):
    method _flash_attention_forward (line 17) | def _flash_attention_forward(
  function replace_internlm2_attention_class (line 72) | def replace_internlm2_attention_class():

FILE: internvl_chat/internvl/patch/internvit_liger_monkey_patch.py
  function apply_liger_kernel_to_internvit (line 7) | def apply_liger_kernel_to_internvit() -> None:

FILE: internvl_chat/internvl/patch/llama2_flash_attn_monkey_patch.py
  function apply_rotary_pos_emb (line 17) | def apply_rotary_pos_emb(q, k, cos_sin, position_ids):
  function forward (line 31) | def forward(
  function _prepare_decoder_attention_mask (line 107) | def _prepare_decoder_attention_mask(
  function replace_llama2_attn_with_flash_attn (line 131) | def replace_llama2_attn_with_flash_attn():
  function test (line 143) | def test():

FILE: internvl_chat/internvl/patch/llama_flash_attn_monkey_patch.py
  function forward (line 17) | def forward(
  function _prepare_decoder_attention_mask (line 114) | def _prepare_decoder_attention_mask(
  function forward_2 (line 121) | def forward_2(
  function replace_llama_attn_with_flash_attn (line 215) | def replace_llama_attn_with_flash_attn():

FILE: internvl_chat/internvl/patch/llama_packed_training_patch.py
  class LlamaFlashAttention2ForPackedTraining (line 14) | class LlamaFlashAttention2ForPackedTraining(LlamaFlashAttention2):
    method _flash_attention_forward (line 16) | def _flash_attention_forward(
  function replace_llama_attention_class (line 104) | def replace_llama_attention_class():

FILE: internvl_chat/internvl/patch/llama_rmsnorm_monkey_patch.py
  function replace_llama_rmsnorm_with_fused_rmsnorm (line 10) | def replace_llama_rmsnorm_with_fused_rmsnorm():

FILE: internvl_chat/internvl/patch/pad_data_collator.py
  function pad_data_collator (line 13) | def pad_data_collator(features, pad_id=0):
  function concat_pad_data_collator (line 57) | def concat_pad_data_collator(features, max_item_length=None, pad_id=0):
  function dpo_concat_pad_data_collator (line 119) | def dpo_concat_pad_data_collator(features, pad_id=0):

FILE: internvl_chat/internvl/patch/phi3_packed_training_patch.py
  class Phi3FlashAttention2ForPackedTraining (line 13) | class Phi3FlashAttention2ForPackedTraining(Phi3FlashAttention2):
    method _flash_attention_forward (line 15) | def _flash_attention_forward(
  function replace_phi3_attention_class (line 103) | def replace_phi3_attention_class():

FILE: internvl_chat/internvl/patch/qwen2_packed_training_patch.py
  class Qwen2FlashAttention2ForPackedTraining (line 14) | class Qwen2FlashAttention2ForPackedTraining(Qwen2FlashAttention2):
    method _flash_attention_forward (line 16) | def _flash_attention_forward(
  function replace_qwen2_attention_class (line 104) | def replace_qwen2_attention_class():

FILE: internvl_chat/internvl/patch/train_dataloader_patch.py
  function get_train_dataloader (line 14) | def get_train_dataloader(self) -> DataLoader:
  function replace_train_dataloader (line 51) | def replace_train_dataloader():

FILE: internvl_chat/internvl/patch/train_sampler_patch.py
  function split_to_even_chunks (line 19) | def split_to_even_chunks(indices, lengths, num_chunks):
  function get_length_grouped_indices (line 42) | def get_length_grouped_indices(lengths, batch_size, world_size, generato...
  class LengthGroupedSampler (line 54) | class LengthGroupedSampler(Sampler):
    method __init__ (line 60) | def __init__(
    method __len__ (line 93) | def __len__(self):
    method __iter__ (line 96) | def __iter__(self):
  function _get_train_sampler (line 102) | def _get_train_sampler(self) -> Optional[torch.utils.data.Sampler]:
  function replace_train_sampler (line 123) | def replace_train_sampler():

FILE: internvl_chat/internvl/train/dataset.py
  function calculate_ngram_repetition (line 43) | def calculate_ngram_repetition(text, n):
  function check_conversations_repetition (line 52) | def check_conversations_repetition(conversations, repeat_threshold=0.4, ...
  function get_frame_indices (line 61) | def get_frame_indices(num_frames, vlen, sample='rand', fix_start=None, i...
  function read_frames_gif (line 102) | def read_frames_gif(
  function read_frames_decord (line 126) | def read_frames_decord(
  function extract_frame_number (line 158) | def extract_frame_number(filename):
  function sort_frames (line 164) | def sort_frames(frame_paths):
  function read_frames_folder (line 169) | def read_frames_folder(
  class WeightedConcatDataset (line 199) | class WeightedConcatDataset(ConcatDataset):
    method __init__ (line 200) | def __init__(self, datasets, weights):
    method __iter__ (line 206) | def __iter__(self):
    method __len__ (line 209) | def __len__(self):
  function pil_loader (line 213) | def pil_loader(img_str):
  class TCSLoader (line 219) | class TCSLoader(object):
    method __init__ (line 221) | def __init__(self, conf_path, sc_config_key='sensecore'):
    method __call__ (line 228) | def __call__(self, fn, image_type='image', max_num_frames=-1, min_num_...
  function expand2square (line 247) | def expand2square(pil_img, background_color):
  function simulate_jpeg_degradation (line 261) | def simulate_jpeg_degradation(quality):
  function build_transform (line 276) | def build_transform(is_train, input_size, pad2square=False, normalize_ty...
  function preprocess (line 313) | def preprocess(
  function preprocess_mpt (line 418) | def preprocess_mpt(
  function preprocess_phi3 (line 512) | def preprocess_phi3(
  function preprocess_internlm (line 621) | def preprocess_internlm(
  function preprocess_internvl2_5 (line 711) | def preprocess_internvl2_5(
  function find_closest_aspect_ratio (line 813) | def find_closest_aspect_ratio(aspect_ratio, target_ratios, width, height...
  function dynamic_preprocess (line 830) | def dynamic_preprocess(image, min_num=1, max_num=6, image_size=448, use_...

FILE: internvl_chat/internvl/train/dataset_packed.py
  function is_dist_avail_and_initialized (line 26) | def is_dist_avail_and_initialized():
  function get_world_size (line 34) | def get_world_size():
  function get_rank (line 40) | def get_rank():
  class PackedDataset (line 46) | class PackedDataset(IterableDataset):
    method __init__ (line 47) | def __init__(
    method load_state_dict (line 142) | def load_state_dict(self, state_dict, custom_infos=None):
    method _should_log (line 154) | def _should_log(self):
    method next_data (line 163) | def next_data(self, current_dataset_idx):
    method find_buffer (line 210) | def find_buffer(self, buffer_list, new_sample):
    method update_buffer (line 234) | def update_buffer(self, buffer, new_sample):
    method check_valid (line 247) | def check_valid(sample_to_check, min_active_tokens_ratio=1/256):
    method split_buffer (line 253) | def split_buffer(buffer, max_tokens, img_start_token_id, img_token_id,...
    method update_buffer_list (line 339) | def update_buffer_list(self, buffer_list, buffer_max_len_list, buffer):
    method pad_buffer (line 376) | def pad_buffer(self, buffer):
    method postprocess_buffer (line 392) | def postprocess_buffer(self, buffer, custom_infos=None):
    method print_log (line 399) | def print_log(self, iter_idx, buffer_list):
    method __iter__ (line 408) | def __iter__(self):
    method get_cu_seqlens_and_indexes (line 517) | def get_cu_seqlens_and_indexes(
  function packed_collate_fn (line 551) | def packed_collate_fn(

FILE: internvl_chat/internvl/train/internvl_chat_finetune.py
  class ModelArguments (line 88) | class ModelArguments:
  class DataTrainingArguments (line 163) | class DataTrainingArguments:
  class LazySupervisedDataset (line 269) | class LazySupervisedDataset(Dataset):
    method __init__ (line 272) | def __init__(
    method __len__ (line 384) | def __len__(self):
    method get_preprocess_function (line 387) | def get_preprocess_function(self):
    method load_image (line 401) | def load_image(self, image_path):
    method get_image_path (line 407) | def get_image_path(self, image_path):
    method get_transform (line 414) | def get_transform(self):
    method multi_modal_get_item (line 420) | def multi_modal_get_item(self, data_item):
    method multi_modal_multi_image_get_item (line 475) | def multi_modal_multi_image_get_item(self, data_item):
    method video_get_item (line 525) | def video_get_item(self, data_item):
    method pure_text_get_item (line 581) | def pure_text_get_item(self, data_item):
    method _enable_worker_distributed (line 624) | def _enable_worker_distributed(self):
    method __getitem__ (line 634) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
    method __iter__ (line 681) | def __iter__(self):
  function build_datasets (line 701) | def build_datasets(
  function len2weight (line 786) | def len2weight(x, loss_reduction):
  function main (line 798) | def main():

FILE: internvl_chat/internvl/train/internvl_chat_mpo.py
  class ModelArguments (line 89) | class ModelArguments:
  class DataTrainingArguments (line 164) | class DataTrainingArguments:
  class DPOConfig (line 238) | class DPOConfig(DPOConfigTRL):
  class LazySupervisedDataset (line 245) | class LazySupervisedDataset(Dataset):
    method __init__ (line 248) | def __init__(
    method __len__ (line 338) | def __len__(self):
    method get_preprocess_function (line 341) | def get_preprocess_function(self):
    method load_image (line 355) | def load_image(self, image_path):
    method get_image_path (line 361) | def get_image_path(self, image_path):
    method get_transform (line 368) | def get_transform(self):
    method get_longest_common_prefix_index (line 375) | def get_longest_common_prefix_index(tensor1, tensor2):
    method multi_modal_get_item (line 384) | def multi_modal_get_item(self, data_item):
    method multi_modal_multi_image_get_item (line 456) | def multi_modal_multi_image_get_item(self, data_item):
    method video_get_item (line 527) | def video_get_item(self, data_item):
    method pure_text_get_item (line 606) | def pure_text_get_item(self, data_item):
    method __getitem__ (line 670) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  function build_datasets (line 712) | def build_datasets(
  function main (line 772) | def main():

FILE: internvl_chat/internvl/train/internvl_chat_pretrain.py
  class ModelArguments (line 88) | class ModelArguments:
  class DataTrainingArguments (line 163) | class DataTrainingArguments:
  class LazySupervisedDataset (line 269) | class LazySupervisedDataset(Dataset):
    method __init__ (line 272) | def __init__(
    method __len__ (line 424) | def __len__(self):
    method get_preprocess_function (line 430) | def get_preprocess_function(self):
    method load_image (line 444) | def load_image(self, image_path):
    method get_image_path (line 450) | def get_image_path(self, image_path):
    method get_transform (line 457) | def get_transform(self):
    method multi_modal_get_item (line 463) | def multi_modal_get_item(self, data_item):
    method multi_modal_multi_image_get_item (line 518) | def multi_modal_multi_image_get_item(self, data_item):
    method video_get_item (line 568) | def video_get_item(self, data_item):
    method pure_text_get_item (line 624) | def pure_text_get_item(self, data_item):
    method _enable_worker_distributed (line 667) | def _enable_worker_distributed(self):
    method __getitem__ (line 678) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
    method __iter__ (line 725) | def __iter__(self):
  function build_datasets (line 745) | def build_datasets(
  function len2weight (line 830) | def len2weight(x, loss_reduction):
  function main (line 842) | def main():

FILE: internvl_chat/internvl/train/trainer_dpo.py
  function _map (line 18) | def _map(self, *args, **kwargs):
  class MultimodalDPOTrainer (line 25) | class MultimodalDPOTrainer(DPOTrainer):
    method __init__ (line 26) | def __init__(self, *args, **kwargs):
    method concatenated_inputs (line 33) | def concatenated_inputs(
    method concatenated_forward (line 99) | def concatenated_forward(
    method _prepare_deepspeed_orig (line 178) | def _prepare_deepspeed_orig(self, model):
    method _prepare_deepspeed (line 191) | def _prepare_deepspeed(self, model):
    method get_batch_loss_metrics (line 206) | def get_batch_loss_metrics(

FILE: internvl_chat/tools/extract_video_frames.py
  function transform_video (line 22) | def transform_video(buffer):
  function get_index (line 37) | def get_index(num_frames, num_segments):
  function fetch_images (line 52) | def fetch_images(qa_item):
  function fetch_images_parallel (line 99) | def fetch_images_parallel(qa_item):

FILE: internvl_chat/tools/images_stitching.py
  function custom_image (line 11) | def custom_image(img_paths, save_path, image_size=448):
  function get_images (line 54) | def get_images(ann_file):

FILE: internvl_chat/tools/internvl_custom2hf.py
  function compute_l2_distance (line 13) | def compute_l2_distance(model1, model2):
  function convert_keys_to_hf (line 41) | def convert_keys_to_hf(custom_state_dict):

FILE: internvl_chat/tools/internvl_hf2custom.py
  function compute_l2_distance (line 11) | def compute_l2_distance(model1, model2):
  function convert_keys_back (line 39) | def convert_keys_back(hf_state_dict):

FILE: internvl_chat/tools/reasoning_data_pipeline/mmpr_data_pipeline_correctness.py
  function collate_fn (line 49) | def collate_fn(batches):
  class VQADataset (line 67) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 68) | def __init__(
    method __len__ (line 86) | def __len__(self):
    method multi_modal_get_item (line 89) | def multi_modal_get_item(self, item):
    method pure_text_get_item (line 122) | def pure_text_get_item(self, item):
    method __getitem__ (line 136) | def __getitem__(self, idx):
  function evaluate_chat_model (line 143) | def evaluate_chat_model():

FILE: internvl_chat/tools/reasoning_data_pipeline/mmpr_data_pipeline_correctness_postprocess.py
  function _build_items_based_on_correctness (line 22) | def _build_items_based_on_correctness(lines, mode):
  function build_neg_based_on_correctness (line 70) | def build_neg_based_on_correctness(lines, mode):
  function _build_pair_based_on_pos_neg (line 96) | def _build_pair_based_on_pos_neg(item_pos, item_neg):
  function build_pairs_based_on_pos_neg (line 125) | def build_pairs_based_on_pos_neg(pos_id2item, neg_id2item, allow_entailm...
  function save_items (line 164) | def save_items(items, save_path, question_only=False, all_incorrect_keys...
  function save_pairs (line 202) | def save_pairs(pairs, save_path):
  function main (line 269) | def main(args):

FILE: internvl_chat/tools/reasoning_data_pipeline/mmpr_data_pipeline_dropout_ntp.py
  function collate_fn (line 46) | def collate_fn(batches):
  class VQADataset (line 61) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 62) | def __init__(
    method __len__ (line 80) | def __len__(self):
    method _truncate_prefix (line 83) | def _truncate_prefix(self, prefix):
    method __getitem__ (line 89) | def __getitem__(self, idx):
  function evaluate_chat_model (line 121) | def evaluate_chat_model():

FILE: internvl_chat/tools/reasoning_data_pipeline/utils/accuracy_reward.py
  class EvalAIAnswerProcessor (line 9) | class EvalAIAnswerProcessor:
    method __init__ (line 180) | def __init__(self, *args, **kwargs):
    method word_tokenize (line 183) | def word_tokenize(self, word):
    method process_punctuation (line 188) | def process_punctuation(self, in_text):
    method process_digit_article (line 200) | def process_digit_article(self, in_text):
    method __call__ (line 215) | def __call__(self, item):
  class TextVQAAccuracyEvaluator (line 223) | class TextVQAAccuracyEvaluator:
    method __init__ (line 224) | def __init__(self):
    method _compute_answer_scores (line 227) | def _compute_answer_scores(self, raw_answers):
    method eval_pred_list (line 250) | def eval_pred_list(self, pred_list, disable_tqdm=False):
  function isfloat (line 267) | def isfloat(x):
  function math_score (line 275) | def math_score(prediction: str, target: str, max_relative_change: float ...
  function relaxed_correctness (line 301) | def relaxed_correctness(target: str,
  function levenshtein_distance (line 347) | def levenshtein_distance(s1, s2):
  function multi_choice_score (line 363) | def multi_choice_score(answer_pred, answer_gt):
  function parse_answer (line 378) | def parse_answer(response, prompt_version):
  function extract_answer_from_mpo (line 395) | def extract_answer_from_mpo(response, version):
  function extract_answer_from_box (line 419) | def extract_answer_from_box(ans):
  function check_cot_format (line 446) | def check_cot_format(response: str):
  function check_r1_format (line 450) | def check_r1_format(response: str):
  function check_answer (line 467) | def check_answer(answer_pred, answer_gt, mode):
  function fix_answer (line 531) | def fix_answer(response, answer_pred, answer_gt):
  function contain_keywords (line 561) | def contain_keywords(ds_name, keywords):
  function post_process (line 568) | def post_process(pred):
  function get_mode (line 583) | def get_mode(ds_name):
  function use_latex_score (line 599) | def use_latex_score(x):
  function validate_latex (line 612) | def validate_latex(pred, gt, easy_mode=False):
  function latex_score (line 650) | def latex_score(prediction, target):

FILE: internvl_chat/tools/reasoning_data_pipeline/utils/utils.py
  function localtime (line 11) | def localtime():
  function init_distributed_mode (line 15) | def init_distributed_mode():
  function init_dist (line 51) | def init_dist(args):
  function get_global_min (line 90) | def get_global_min(value):
  function save_outputs (line 98) | def save_outputs(outputs, results_file):
  function load_outputs (line 120) | def load_outputs(results_file):
  class InferenceSampler (line 127) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 129) | def __init__(self, size):
    method _get_local_indices (line 137) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 146) | def __iter__(self):
    method __len__ (line 149) | def __len__(self):

FILE: internvl_chat/tools/reasoning_data_pipeline/visualprm_data_pieline.py
  function collate_fn (line 53) | def collate_fn(batches):
  class VQADataset (line 63) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 64) | def __init__(
    method __len__ (line 78) | def __len__(self):
    method __getitem__ (line 81) | def __getitem__(self, idx):
  function split_response (line 116) | def split_response(response, sep='\n\n', max_steps=None):
  function join_steps (line 129) | def join_steps(steps, sep='\n\n'):
  function build_responses (line 133) | def build_responses(inputs, num_return_sequences=1, prefixes=None):
  function build_mc_scores (line 174) | def build_mc_scores(inputs, response_list, items, num_return_sequences):
  function build_process_supervision (line 254) | def build_process_supervision(inputs, items, num_return_sequences):
  function print_process_supervision (line 272) | def print_process_supervision(output):
  function evaluate_chat_model (line 287) | def evaluate_chat_model():

FILE: internvl_chat/tools/reasoning_data_pipeline/visualprm_data_pipeline_postprocess.py
  function save_outputs (line 10) | def save_outputs(outputs, results_file):
  function item2conv_prm (line 20) | def item2conv_prm(item):
  function item2conv_orm (line 47) | def item2conv_orm(item):
  function main (line 74) | def main():

FILE: internvl_chat_gpt_oss/internvl/dist_utils.py
  function _find_free_port (line 14) | def _find_free_port():
  function _is_free_port (line 25) | def _is_free_port(port):
  function init_dist (line 32) | def init_dist(launcher, backend='nccl', **kwargs):
  function _init_dist_pytorch (line 45) | def _init_dist_pytorch(backend, **kwargs):
  function _init_dist_mpi (line 61) | def _init_dist_mpi(backend, **kwargs):
  function _init_dist_slurm (line 74) | def _init_dist_slurm(backend, port=None):

FILE: internvl_chat_gpt_oss/internvl/model/internvl_chat/configuration_intern_vit.py
  class InternVisionConfig (line 15) | class InternVisionConfig(PretrainedConfig):
    method __init__ (line 63) | def __init__(
    method from_pretrained (line 107) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....

FILE: internvl_chat_gpt_oss/internvl/model/internvl_chat/configuration_internvl_chat.py
  class InternVLChatConfig (line 18) | class InternVLChatConfig(PretrainedConfig):
    method __init__ (line 22) | def __init__(
    method to_dict (line 95) | def to_dict(self):

FILE: internvl_chat_gpt_oss/internvl/model/internvl_chat/conversation.py
  class SeparatorStyle (line 15) | class SeparatorStyle(IntEnum):
  class Conversation (line 40) | class Conversation:
    method get_prompt (line 64) | def get_prompt(self) -> str:
    method set_system_message (line 271) | def set_system_message(self, system_message: str):
    method append_message (line 275) | def append_message(self, role: str, message: str):
    method update_last_message (line 279) | def update_last_message(self, message: str):
    method to_gradio_chatbot (line 287) | def to_gradio_chatbot(self):
    method to_openai_api_messages (line 297) | def to_openai_api_messages(self):
    method copy (line 309) | def copy(self):
    method dict (line 324) | def dict(self):
  function register_conv_template (line 338) | def register_conv_template(template: Conversation, override: bool = False):
  function get_conv_template (line 348) | def get_conv_template(name: str) -> Conversation:

FILE: internvl_chat_gpt_oss/internvl/model/internvl_chat/modeling_intern_vit.py
  class FlashAttention (line 35) | class FlashAttention(nn.Module):
    method __init__ (line 46) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 51) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...
  class InternRMSNorm (line 99) | class InternRMSNorm(nn.Module):
    method __init__ (line 100) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 105) | def forward(self, hidden_states):
  class InternVisionEmbeddings (line 133) | class InternVisionEmbeddings(nn.Module):
    method __init__ (line 134) | def __init__(self, config: InternVisionConfig):
    method _get_pos_embed (line 154) | def _get_pos_embed(self, pos_embed, H, W):
    method forward (line 162) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class InternAttention (line 177) | class InternAttention(nn.Module):
    method __init__ (line 180) | def __init__(self, config: InternVisionConfig):
    method _naive_attn (line 210) | def _naive_attn(self, x):
    method _flash_attn (line 229) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 246) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternMLP (line 251) | class InternMLP(nn.Module):
    method __init__ (line 252) | def __init__(self, config: InternVisionConfig):
    method forward (line 259) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternVisionEncoderLayer (line 266) | class InternVisionEncoderLayer(nn.Module):
    method __init__ (line 267) | def __init__(self, config: InternVisionConfig, drop_path_rate: float):
    method forward (line 283) | def forward(
  class InternVisionEncoder (line 298) | class InternVisionEncoder(nn.Module):
    method __init__ (line 307) | def __init__(self, config: InternVisionConfig):
    method forward (line 316) | def forward(
  class InternVisionModel (line 363) | class InternVisionModel(PreTrainedModel):
    method __init__ (line 370) | def __init__(self, config: InternVisionConfig):
    method resize_pos_embeddings (line 377) | def resize_pos_embeddings(self, old_size, new_size, patch_size):
    method get_input_embeddings (line 389) | def get_input_embeddings(self):
    method forward (line 392) | def forward(

FILE: internvl_chat_gpt_oss/internvl/model/internvl_chat/modeling_internvl_chat.py
  function version_cmp (line 29) | def version_cmp(v1, v2, op='eq'):
  class InternVLChatModel (line 37) | class InternVLChatModel(PreTrainedModel):
    method __init__ (line 56) | def __init__(self, config: InternVLChatConfig, vision_model=None, lang...
    method forward (line 100) | def forward(
    method pixel_shuffle (line 278) | def pixel_shuffle(self, x, scale_factor=0.5):
    method extract_feature (line 294) | def extract_feature(self, pixel_values):
    method batch_chat (line 314) | def batch_chat(self, tokenizer, pixel_values, questions, generation_co...
    method chat (line 366) | def chat(self, tokenizer, pixel_values, question, generation_config, h...
    method generate (line 426) | def generate(
    method lm_head (line 468) | def lm_head(self):
    method get_output_embeddings (line 471) | def get_output_embeddings(self):
    method get_input_embeddings (line 474) | def get_input_embeddings(self):
    method set_input_embeddings (line 477) | def set_input_embeddings(self, value):
    method set_output_embeddings (line 480) | def set_output_embeddings(self, value):

FILE: internvl_chat_gpt_oss/internvl/patch/flash_sink_attn/flash_attn_with_sink.py
  class FlashAttentionWithSink (line 14) | class FlashAttentionWithSink(torch.autograd.Function):
    method forward (line 17) | def forward(
    method backward (line 77) | def backward(ctx, grad_output):
  function flash_attn_with_sink_func (line 186) | def flash_attn_with_sink_func(

FILE: internvl_chat_gpt_oss/internvl/patch/flash_sink_attn/flash_sink_attn.py
  function _bwd_preprocess_do_o_dot (line 19) | def _bwd_preprocess_do_o_dot(
  function init_to_zero (line 77) | def init_to_zero(name):
  function _fwd_kernel (line 82) | def _fwd_kernel(
  function _bwd_kernel (line 169) | def _bwd_kernel(
  function _flash_attn_forward (line 263) | def _flash_attn_forward(
  function _flash_attn_backward (line 314) | def _flash_attn_backward(
  class FlashSinkAttention (line 377) | class FlashSinkAttention(torch.autograd.Function):
    method forward (line 380) | def forward(
    method backward (line 404) | def backward(ctx, do):

FILE: internvl_chat_gpt_oss/internvl/patch/flash_sink_attn/flash_sink_attn_gpt_oss.py
  function _bwd_preprocess_do_o_dot (line 19) | def _bwd_preprocess_do_o_dot(
  function init_to_zero (line 77) | def init_to_zero(name):
  function _fwd_kernel (line 82) | def _fwd_kernel(
  function _bwd_kernel (line 200) | def _bwd_kernel(
  function _flash_attn_forward (line 333) | def _flash_attn_forward(
  function _flash_attn_backward (line 383) | def _flash_attn_backward(
  class FlashSinkAttention (line 446) | class FlashSinkAttention(torch.autograd.Function):
    method forward (line 449) | def forward(
    method backward (line 473) | def backward(ctx, do):

FILE: internvl_chat_gpt_oss/internvl/patch/flash_sink_attn/flash_sink_varlen_attn_gpt_oss.py
  function _bwd_preprocess_do_o_dot (line 18) | def _bwd_preprocess_do_o_dot(
  function init_to_zero (line 62) | def init_to_zero(name):
  function _fwd_kernel (line 67) | def _fwd_kernel(
  function _bwd_kernel (line 185) | def _bwd_kernel(
  function _flash_attn_forward (line 314) | def _flash_attn_forward(
  function _flash_attn_backward (line 363) | def _flash_attn_backward(
  class FlashSinkVarlenAttention (line 426) | class FlashSinkVarlenAttention(torch.autograd.Function):
    method forward (line 428) | def forward(
    method backward (line 454) | def backward(ctx, do):

FILE: internvl_chat_gpt_oss/internvl/patch/flash_sink_attn/sliding_cache.py
  class SlidingCacheManager (line 12) | class SlidingCacheManager:
    method __init__ (line 16) | def __init__(
    method reset (line 25) | def reset(self):
    method update (line 30) | def update(self, key, val):

FILE: internvl_chat_gpt_oss/internvl/patch/flash_sink_attn_monkey_patch.py
  function _forward_gpt_oss (line 17) | def _forward_gpt_oss(
  function _forward_gpt_oss_with_varlen (line 64) | def _forward_gpt_oss_with_varlen(
  function replace_gpt_oss_with_flash_sink_attn (line 125) | def replace_gpt_oss_with_flash_sink_attn(model, use_varlen=False):

FILE: internvl_chat_gpt_oss/internvl/patch/pad_data_collator.py
  function pad_data_collator (line 13) | def pad_data_collator(features, pad_id=0):
  function concat_pad_data_collator (line 57) | def concat_pad_data_collator(features, max_item_length=None, pad_id=0):
  function dpo_concat_pad_data_collator (line 119) | def dpo_concat_pad_data_collator(features, pad_id=0):

FILE: internvl_chat_gpt_oss/internvl/patch/qwen3_flash_monkey_patch.py
  function _forward_qwen3 (line 16) | def _forward_qwen3(
  function replace_qwen3_attention_class (line 91) | def replace_qwen3_attention_class(model):

FILE: internvl_chat_gpt_oss/internvl/patch/train_dataloader_patch.py
  function _get_dataloader (line 16) | def _get_dataloader(
  function replace_train_dataloader (line 67) | def replace_train_dataloader():

FILE: internvl_chat_gpt_oss/internvl/train/dataset.py
  function calculate_ngram_repetition (line 38) | def calculate_ngram_repetition(text, n):
  function check_conversations_repetition (line 47) | def check_conversations_repetition(conversations, repeat_threshold=0.4, ...
  function get_frame_indices (line 56) | def get_frame_indices(num_frames, vlen, sample='rand', fix_start=None, i...
  function read_frames_gif (line 97) | def read_frames_gif(
  function read_frames_decord (line 121) | def read_frames_decord(
  function extract_frame_number (line 153) | def extract_frame_number(filename):
  function sort_frames (line 159) | def sort_frames(frame_paths):
  function read_frames_folder (line 164) | def read_frames_folder(
  class WeightedConcatDataset (line 194) | class WeightedConcatDataset(ConcatDataset):
    method __init__ (line 195) | def __init__(self, datasets, weights):
    method __iter__ (line 201) | def __iter__(self):
    method __len__ (line 204) | def __len__(self):
  function pil_loader (line 208) | def pil_loader(img_str):
  class TCSLoader (line 214) | class TCSLoader(object):
    method __init__ (line 216) | def __init__(self, conf_path, sc_config_key='sensecore'):
    method __call__ (line 223) | def __call__(self, fn, image_type='image', max_num_frames=-1, min_num_...
  function expand2square (line 242) | def expand2square(pil_img, background_color):
  function simulate_jpeg_degradation (line 256) | def simulate_jpeg_degradation(quality):
  function build_transform (line 271) | def build_transform(is_train, input_size, pad2square=False, normalize_ty...
  function preprocess_pretrain (line 308) | def preprocess_pretrain(
  function preprocess_internvl2_5 (line 389) | def preprocess_internvl2_5(
  function preprocess_internvl3_5_gpt_oss (line 491) | def preprocess_internvl3_5_gpt_oss(
  function preprocess_internvl3_5_gpt_oss_with_think (line 597) | def preprocess_internvl3_5_gpt_oss_with_think(
  function find_closest_aspect_ratio (line 712) | def find_closest_aspect_ratio(aspect_ratio, target_ratios, width, height...
  function dynamic_preprocess (line 729) | def dynamic_preprocess(image, min_num=1, max_num=6, image_size=448, use_...

FILE: internvl_chat_gpt_oss/internvl/train/dataset_packed.py
  function is_dist_avail_and_initialized (line 26) | def is_dist_avail_and_initialized():
  function get_rank (line 34) | def get_rank():
  class PackedDataset (line 40) | class PackedDataset(IterableDataset):
    method __init__ (line 41) | def __init__(
    method load_state_dict (line 136) | def load_state_dict(self, state_dict, custom_infos=None):
    method _should_log (line 148) | def _should_log(self):
    method next_data (line 157) | def next_data(self, current_dataset_idx):
    method find_buffer (line 204) | def find_buffer(self, buffer_list, new_sample):
    method update_buffer (line 228) | def update_buffer(self, buffer, new_sample):
    method check_valid (line 241) | def check_valid(sample_to_check, min_active_tokens_ratio=1/256):
    method split_buffer (line 247) | def split_buffer(buffer, max_tokens, img_start_token_id, img_token_id,...
    method update_buffer_list (line 333) | def update_buffer_list(self, buffer_list, buffer_max_len_list, buffer):
    method pad_buffer (line 370) | def pad_buffer(self, buffer):
    method postprocess_buffer (line 386) | def postprocess_buffer(self, buffer, custom_infos=None):
    method print_log (line 393) | def print_log(self, iter_idx, buffer_list):
    method __iter__ (line 402) | def __iter__(self):
    method get_cu_seqlens_and_indexes (line 511) | def get_cu_seqlens_and_indexes(
  function packed_collate_fn (line 548) | def packed_collate_fn(

FILE: internvl_chat_gpt_oss/internvl/train/internvl_chat_finetune.py
  class ModelArguments (line 76) | class ModelArguments:
  class DataTrainingArguments (line 155) | class DataTrainingArguments:
  class LazySupervisedDataset (line 257) | class LazySupervisedDataset(Dataset):
    method __init__ (line 260) | def __init__(
    method __len__ (line 391) | def __len__(self):
    method get_preprocess_function (line 394) | def get_preprocess_function(self, use_pretrain=False):
    method load_image (line 407) | def load_image(self, image_path):
    method get_image_path (line 413) | def get_image_path(self, image_path):
    method get_transform (line 418) | def get_transform(self):
    method multi_modal_get_item (line 428) | def multi_modal_get_item(self, data_item):
    method multi_modal_multi_image_get_item (line 485) | def multi_modal_multi_image_get_item(self, data_item):
    method video_get_item (line 541) | def video_get_item(self, data_item):
    method pure_text_get_item (line 599) | def pure_text_get_item(self, data_item):
    method fake_data_get_item (line 642) | def fake_data_get_item(self):
    method _enable_worker_distributed (line 690) | def _enable_worker_distributed(self):
    method __getitem__ (line 700) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
    method __iter__ (line 749) | def __iter__(self):
  function build_datasets (line 769) | def build_datasets(
  function len2weight (line 849) | def len2weight(x, loss_reduction):
  function main (line 861) | def main():

FILE: internvl_chat_gpt_oss/internvl/train/internvl_chat_mpo.py
  class ModelArguments (line 95) | class ModelArguments:
  class DataTrainingArguments (line 162) | class DataTrainingArguments:
  class LazySupervisedDataset (line 236) | class LazySupervisedDataset(Dataset):
    method __init__ (line 239) | def __init__(
    method __len__ (line 343) | def __len__(self):
    method get_preprocess_function (line 346) | def get_preprocess_function(self, use_pretrain=False):
    method load_image (line 359) | def load_image(self, image_path):
    method get_image_path (line 365) | def get_image_path(self, image_path):
    method get_transform (line 370) | def get_transform(self):
    method multi_modal_get_item (line 380) | def multi_modal_get_item(self, data_item):
    method multi_modal_multi_image_get_item (line 483) | def multi_modal_multi_image_get_item(self, data_item):
    method video_get_item (line 585) | def video_get_item(self, data_item):
    method pure_text_get_item (line 696) | def pure_text_get_item(self, data_item):
    method __getitem__ (line 791) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  function build_datasets (line 837) | def build_datasets(
  function main (line 890) | def main():

FILE: internvl_chat_gpt_oss/internvl/train/trainer_dpo.py
  function _map (line 17) | def _map(self, *args, **kwargs):
  class InternVLDPOTrainer (line 25) | class InternVLDPOTrainer(DPOTrainer):
    method concatenated_inputs (line 27) | def concatenated_inputs(
    method concatenated_forward (line 37) | def concatenated_forward(

FILE: internvl_chat_gpt_oss/internvl/utils/s3_config.py
  function _value_to_str (line 30) | def _value_to_str(d):
  class GetterMixin (line 40) | class GetterMixin(object):
    method get (line 45) | def get(self, key, default=_UNSET):
    method has_option (line 54) | def has_option(self, key):
    method get_boolean (line 61) | def get_boolean(self, key, default=_UNSET):
    method get_int (line 68) | def get_int(self, key, default=_UNSET):
    method get_log_level (line 74) | def get_log_level(self, key, default=_UNSET):
  class _my_dict (line 81) | class _my_dict(configparser._default_dict):
  class Config (line 85) | class Config(GetterMixin):
    method __init__ (line 86) | def __init__(self, conf_path, *args, **kwargs):
    method __getitem__ (line 109) | def __getitem__(self, key):
    method update (line 115) | def update(self, other: dict):
    method default (line 119) | def default(self):
    method items (line 122) | def items(self):
  class Section (line 129) | class Section(GetterMixin):
    method __init__ (line 131) | def __init__(self, conf: dict):
    method __getitem__ (line 135) | def __getitem__(self, key):
    method update (line 141) | def update(self, other):

FILE: internvl_chat_gpt_oss/internvl/utils/s3_exception.py
  class Error (line 4) | class Error(Exception):
    method __str__ (line 7) | def __str__(self):
  class RetriableError (line 13) | class RetriableError(Error):
  class ConfigError (line 20) | class ConfigError(Error):
  class InvalidConfigError (line 24) | class InvalidConfigError(ConfigError):
  class ConfigFileNotFoundError (line 28) | class ConfigFileNotFoundError(ConfigError):
  class ConfigItemNotFoundError (line 32) | class ConfigItemNotFoundError(ConfigError):
  class ConfigKeyNotFoundError (line 36) | class ConfigKeyNotFoundError(ConfigItemNotFoundError):
  class ConfigSectionNotFoundError (line 40) | class ConfigSectionNotFoundError(ConfigItemNotFoundError):
  class ConfigKeyTypeError (line 44) | class ConfigKeyTypeError(ConfigError):
  class ConfigKeyValueError (line 48) | class ConfigKeyValueError(ConfigError):
  class UnSupprotAddressStyle (line 52) | class UnSupprotAddressStyle(ConfigError):
  class ClientError (line 59) | class ClientError(Error):
  class ContentTypeError (line 63) | class ContentTypeError(ClientError):
  class S3ClientError (line 67) | class S3ClientError(ClientError):
  class InvalidAccessKeyError (line 71) | class InvalidAccessKeyError(S3ClientError):
  class SignatureNotMatchError (line 75) | class SignatureNotMatchError(S3ClientError):
  class NetworkConnectionError (line 79) | class NetworkConnectionError(S3ClientError):
  class ResourceNotFoundError (line 83) | class ResourceNotFoundError(S3ClientError):
  class AccessDeniedError (line 87) | class AccessDeniedError(ClientError):
  class RangeError (line 91) | class RangeError(ClientError):
  class MultipartError (line 95) | class MultipartError(ClientError):
  class ObjectNotFoundError (line 99) | class ObjectNotFoundError(ClientError):
  class S3ObjectNotFoundError (line 103) | class S3ObjectNotFoundError(ObjectNotFoundError):
  class NoSuchBucketError (line 107) | class NoSuchBucketError(S3ObjectNotFoundError):
  class NoSuchKeyError (line 111) | class NoSuchKeyError(S3ObjectNotFoundError):
  class CacheError (line 118) | class CacheError(ClientError):
  class McClientError (line 122) | class McClientError(CacheError):
  class McObjectNotFoundError (line 126) | class McObjectNotFoundError(ObjectNotFoundError, McClientError):
  class McTimeoutOccur (line 130) | class McTimeoutOccur(McClientError, RetriableError):
  class McConnFailed (line 134) | class McConnFailed(McClientError, RetriableError):
  class McServerFailed (line 138) | class McServerFailed(McClientError, RetriableError):
  class McServerDisable (line 142) | class McServerDisable(McClientError):
  class McServerDead (line 146) | class McServerDead(McClientError):
  class McBadKeyProvided (line 150) | class McBadKeyProvided(McClientError):
  class McKeySizeExceed (line 154) | class McKeySizeExceed(McClientError):
  class McObjectSizeExceed (line 158) | class McObjectSizeExceed(McClientError):
  class InvalidUriError (line 165) | class InvalidUriError(Error):
  class InvalidS3UriError (line 169) | class InvalidS3UriError(InvalidUriError):
  class InvalidBucketUriError (line 173) | class InvalidBucketUriError(InvalidS3UriError):
  class InvalidDfsUriError (line 177) | class InvalidDfsUriError(InvalidUriError):
  class InvalidMcUriError (line 181) | class InvalidMcUriError(InvalidUriError):
  class InvalidClusterNameError (line 185) | class InvalidClusterNameError(InvalidUriError):
  class NoDefaultClusterNameError (line 189) | class NoDefaultClusterNameError(InvalidUriError):

FILE: internvl_chat_gpt_oss/internvl/utils/s3_fileio.py
  class S3Backend (line 26) | class S3Backend(BaseStorageBackend):
    method __init__ (line 45) | def __init__(self,
    method _map_path (line 76) | def _map_path(self, filepath: Union[str, Path]) -> str:
    method _format_path (line 89) | def _format_path(self, filepath: str) -> str:
    method _parse_path (line 102) | def _parse_path(self, filepath: Union[str, Path]) -> Tuple[str, str]:
    method _check_bucket (line 121) | def _check_bucket(self, bucket: str) -> bool:
    method _check_object (line 136) | def _check_object(self, bucket: str, obj_name: str) -> bool:
    method get (line 151) | def get(self, filepath: str) -> bytes:
    method get_text (line 170) | def get_text(self, filepath, encoding='utf-8') -> str:
    method put (line 188) | def put(self, obj: bytes, filepath: Union[str, Path]) -> None:
    method put_text (line 201) | def put_text(self,
    method remove (line 215) | def remove(self, filepath: Union[str, Path]) -> None:
    method exists (line 224) | def exists(self, filepath: Union[str, Path]) -> bool:
    method isdir (line 235) | def isdir(self, filepath: Union[str, Path]) -> bool:
    method isfile (line 251) | def isfile(self, filepath: Union[str, Path]) -> bool:
    method get_local_path (line 267) | def get_local_path(
    method list (line 297) | def list(self,
  class MixedClient (line 421) | class MixedClient(object):
    method __init__ (line 422) | def __init__(self, conf_path, **kwargs):
    method parse_uri (line 443) | def parse_uri(uri, ceph_dict, default_cluster=None):
    method get_with_info (line 470) | def get_with_info(self, uri, **kwargs):
    method list (line 480) | def list(self, uri, **kwargs):
  class Client (line 487) | class Client(object):
    method __init__ (line 489) | def __init__(self, conf_path='petreloss.conf', *args, **kwargs):
    method _get_local_client (line 497) | def _get_local_client(self):
    method get_with_info (line 513) | def get_with_info(self, uri, **kwargs):
    method get (line 516) | def get(self, *args, **kwargs):
    method list (line 520) | def list(self, *args, **kwargs):

FILE: internvl_chat_llava/llava/conversation.py
  class SeparatorStyle (line 6) | class SeparatorStyle(Enum):
  class Conversation (line 18) | class Conversation:
    method get_prompt (line 35) | def get_prompt(self):
    method append_message (line 133) | def append_message(self, role, message):
    method get_images (line 136) | def get_images(self, return_pil=False, return_org=False):
    method to_gradio_chatbot (line 197) | def to_gradio_chatbot(self):
    method copy (line 228) | def copy(self):
    method dict (line 242) | def dict(self):

FILE: internvl_chat_llava/llava/eval/eval_gpt_review.py
  function get_eval (line 13) | def get_eval(content: str, max_tokens: int):
  function parse_score (line 39) | def parse_score(review):

FILE: internvl_chat_llava/llava/eval/eval_gpt_review_bench.py
  function get_eval (line 11) | def get_eval(content: str, max_tokens: int):
  function parse_score (line 36) | def parse_score(review):

FILE: internvl_chat_llava/llava/eval/eval_gpt_review_visual.py
  function get_eval (line 11) | def get_eval(content: str, max_tokens: int):
  function parse_score (line 36) | def parse_score(review):

FILE: internvl_chat_llava/llava/eval/eval_pope.py
  function eval_pope (line 5) | def eval_pope(answers, label_file):

FILE: internvl_chat_llava/llava/eval/eval_science_qa.py
  function get_args (line 8) | def get_args():
  function convert_caps (line 19) | def convert_caps(results):
  function get_pred_idx (line 28) | def get_pred_idx(prediction, choices, options):

FILE: internvl_chat_llava/llava/eval/eval_science_qa_gpt4.py
  function get_args (line 9) | def get_args():
  function convert_caps (line 19) | def convert_caps(results):
  function get_pred_idx (line 28) | def get_pred_idx(prediction, choices, options):

FILE: internvl_chat_llava/llava/eval/eval_science_qa_gpt4_requery.py
  function get_args (line 9) | def get_args():
  function convert_caps (line 21) | def convert_caps(results):
  function get_pred_idx (line 30) | def get_pred_idx(prediction, choices, options):

FILE: internvl_chat_llava/llava/eval/eval_textvqa.py
  function get_args (line 9) | def get_args():
  function prompt_processor (line 17) | def prompt_processor(prompt):
  function eval_single (line 35) | def eval_single(annotation_file, result_file):

FILE: internvl_chat_llava/llava/eval/generate_webpage_data_from_table.py
  function read_jsonl (line 10) | def read_jsonl(path: str, key: str=None):
  function trim_hanging_lines (line 23) | def trim_hanging_lines(s: str, n: int) -> str:

FILE: internvl_chat_llava/llava/eval/m4c_evaluator.py
  class EvalAIAnswerProcessor (line 7) | class EvalAIAnswerProcessor:
    method __init__ (line 178) | def __init__(self, *args, **kwargs):
    method word_tokenize (line 181) | def word_tokenize(self, word):
    method process_punctuation (line 186) | def process_punctuation(self, in_text):
    method process_digit_article (line 198) | def process_digit_article(self, in_text):
    method __call__ (line 213) | def __call__(self, item):
  class TextVQAAccuracyEvaluator (line 221) | class TextVQAAccuracyEvaluator:
    method __init__ (line 222) | def __init__(self):
    method _compute_answer_scores (line 225) | def _compute_answer_scores(self, raw_answers):
    method eval_pred_list (line 248) | def eval_pred_list(self, pred_list):
  class STVQAAccuracyEvaluator (line 260) | class STVQAAccuracyEvaluator:
    method __init__ (line 261) | def __init__(self):
    method eval_pred_list (line 264) | def eval_pred_list(self, pred_list):
  class STVQAANLSEvaluator (line 276) | class STVQAANLSEvaluator:
    method __init__ (line 277) | def __init__(self):
    method get_anls (line 282) | def get_anls(self, s1, s2):
    method eval_pred_list (line 289) | def eval_pred_list(self, pred_list):
  class TextCapsBleu4Evaluator (line 301) | class TextCapsBleu4Evaluator:
    method __init__ (line 302) | def __init__(self):
    method eval_pred_list (line 321) | def eval_pred_list(self, pred_list):

FILE: internvl_chat_llava/llava/eval/model_qa.py
  class KeywordsStoppingCriteria (line 14) | class KeywordsStoppingCriteria(StoppingCriteria):
    method __init__ (line 15) | def __init__(self, keywords, tokenizer, input_ids):
    method __call__ (line 21) | def __call__(self, output_ids: torch.LongTensor, scores: torch.FloatTe...
  function eval_model (line 33) | def eval_model(model_name, questions_file, answers_file):

FILE: internvl_chat_llava/llava/eval/model_vqa.py
  function split_list (line 18) | def split_list(lst, n):
  function get_chunk (line 24) | def get_chunk(lst, n, k):
  function eval_model (line 29) | def eval_model(args):

FILE: internvl_chat_llava/llava/eval/model_vqa_loader.py
  function split_list (line 19) | def split_list(lst, n):
  function get_chunk (line 25) | def get_chunk(lst, n, k):
  class CustomDataset (line 31) | class CustomDataset(Dataset):
    method __init__ (line 32) | def __init__(self, questions, image_folder, tokenizer, image_processor...
    method __getitem__ (line 39) | def __getitem__(self, index):
    method __len__ (line 60) | def __len__(self):
  function create_data_loader (line 65) | def create_data_loader(questions, image_folder, tokenizer, image_process...
  function eval_model (line 72) | def eval_model(args):

FILE: internvl_chat_llava/llava/eval/model_vqa_mmbench.py
  function split_list (line 22) | def split_list(lst, n):
  function get_chunk (line 28) | def get_chunk(lst, n, k):
  function is_none (line 33) | def is_none(value):
  function get_options (line 44) | def get_options(row, options):
  function eval_model (line 54) | def eval_model(args):

FILE: internvl_chat_llava/llava/eval/model_vqa_science.py
  function split_list (line 18) | def split_list(lst, n):
  function get_chunk (line 24) | def get_chunk(lst, n, k):
  function eval_model (line 29) | def eval_model(args):

FILE: internvl_chat_llava/llava/eval/qa_baseline_gpt35.py
  function get_answer (line 16) | def get_answer(question_id: int, question: str, max_tokens: int):

FILE: internvl_chat_llava/llava/eval/run_llava.py
  function load_image (line 17) | def load_image(image_file):
  function eval_model (line 26) | def eval_model(args):

FILE: internvl_chat_llava/llava/eval/summarize_gpt_review.py
  function parse_args (line 9) | def parse_args():

FILE: internvl_chat_llava/llava/eval/webpage/script.js
  function text2Markdown (line 35) | function text2Markdown(text) {
  function capitalizeFirstChar (line 41) | function capitalizeFirstChar(str) {
  function updateQuestionSelect (line 48) | function updateQuestionSelect(question_id) {
  function updateModelSelect (line 64) | function updateModelSelect() {
  function populateModels (line 70) | function populateModels(models) {
  function populateQuestions (line 81) | function populateQuestions(questions) {
  function displayQuestion (line 110) | function displayQuestion(index) {
  function displayAnswers (line 116) | function displayAnswers(index) {
  function switchQuestionAndCategory (line 203) | function switchQuestionAndCategory() {
  function updateExpandButtonVisibility (line 226) | function updateExpandButtonVisibility(card) {

FILE: internvl_chat_llava/llava/mm_utils.py
  function load_image_from_base64 (line 10) | def load_image_from_base64(image):
  function expand2square (line 14) | def expand2square(pil_img, background_color):
  function process_images (line 28) | def process_images(images, image_processor, model_cfg):
  function tokenizer_image_token (line 43) | def tokenizer_image_token(prompt, tokenizer, image_token_index=IMAGE_TOK...
  function get_model_name_from_path (line 71) | def get_model_name_from_path(model_path):
  class KeywordsStoppingCriteria (line 82) | class KeywordsStoppingCriteria(StoppingCriteria):
    method __init__ (line 83) | def __init__(self, keywords, tokenizer, input_ids):
    method __call__ (line 97) | def __call__(self, output_ids: torch.LongTensor, scores: torch.FloatTe...

FILE: internvl_chat_llava/llava/model/apply_delta.py
  function apply_delta (line 13) | def apply_delta(base_model_path, target_model_path, delta_path):

FILE: internvl_chat_llava/llava/model/builder.py
  function load_pretrained_model (line 26) | def load_pretrained_model(model_path, model_base, model_name, load_8bit=...

FILE: internvl_chat_llava/llava/model/consolidate.py
  function consolidate_ckpt (line 13) | def consolidate_ckpt(src_path, dst_path):

FILE: internvl_chat_llava/llava/model/language_model/llava_llama.py
  class LlavaConfig (line 30) | class LlavaConfig(LlamaConfig):
  class LlavaLlamaModel (line 34) | class LlavaLlamaModel(LlavaMetaModel, LlamaModel):
    method __init__ (line 37) | def __init__(self, config: LlamaConfig):
  class LlavaLlamaForCausalLM (line 41) | class LlavaLlamaForCausalLM(LlamaForCausalLM, LlavaMetaForCausalLM):
    method __init__ (line 44) | def __init__(self, config):
    method get_model (line 53) | def get_model(self):
    method forward (line 56) | def forward(
    method prepare_inputs_for_generation (line 117) | def prepare_inputs_for_generation(

FILE: internvl_chat_llava/llava/model/language_model/llava_mpt.py
  class LlavaMptConfig (line 25) | class LlavaMptConfig(MptConfig):
  class LlavaMptModel (line 29) | class LlavaMptModel(LlavaMetaModel, MptModel):
    method __init__ (line 32) | def __init__(self, config: MptConfig):
    method embed_tokens (line 36) | def embed_tokens(self, x):
  class LlavaMptForCausalLM (line 40) | class LlavaMptForCausalLM(MptForCausalLM, LlavaMetaForCausalLM):
    method __init__ (line 44) | def __init__(self, config):
    method get_model (line 53) | def get_model(self):
    method _set_gradient_checkpointing (line 56) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 60) | def forward(
    method prepare_inputs_for_generation (line 87) | def prepare_inputs_for_generation(self, input_ids, past_key_values=Non...

FILE: internvl_chat_llava/llava/model/language_model/mpt/adapt_tokenizer.py
  function adapt_tokenizer_for_denoising (line 6) | def adapt_tokenizer_for_denoising(tokenizer: Tokenizer):
  class AutoTokenizerForMOD (line 25) | class AutoTokenizerForMOD(AutoTokenizer):
    method from_pretrained (line 37) | def from_pretrained(cls, *args, **kwargs):

FILE: internvl_chat_llava/llava/model/language_model/mpt/attention.py
  function _reset_is_causal (line 12) | def _reset_is_causal(num_query_tokens: int, num_key_tokens: int, origina...
  function scaled_multihead_dot_product_attention (line 20) | def scaled_multihead_dot_product_attention(query, key, value, n_heads, p...
  function check_valid_inputs (line 64) | def check_valid_inputs(*tensors, valid_dtypes=[torch.float16, torch.bflo...
  function flash_attn_fn (line 71) | def flash_attn_fn(query, key, value, n_heads, past_key_value=None, softm...
  function triton_flash_attn_fn (line 107) | def triton_flash_attn_fn(query, key, value, n_heads, past_key_value=None...
  class MultiheadAttention (line 151) | class MultiheadAttention(nn.Module):
    method __init__ (line 158) | def __init__(self, d_model: int, n_heads: int, attn_impl: str='triton'...
    method forward (line 191) | def forward(self, x, past_key_value=None, attn_bias=None, attention_ma...
  class MultiQueryAttention (line 204) | class MultiQueryAttention(nn.Module):
    method __init__ (line 211) | def __init__(self, d_model: int, n_heads: int, attn_impl: str='triton'...
    method forward (line 245) | def forward(self, x, past_key_value=None, attn_bias=None, attention_ma...
  function attn_bias_shape (line 258) | def attn_bias_shape(attn_impl, n_heads, seq_len, alibi, prefix_lm, causa...
  function build_attn_bias (line 272) | def build_attn_bias(attn_impl, attn_bias, n_heads, seq_len, causal=False...
  function gen_slopes (line 283) | def gen_slopes(n_heads, alibi_bias_max=8, device=None):
  function build_alibi_bias (line 292) | def build_alibi_bias(n_heads, seq_len, full=False, alibi_bias_max=8, dev...

FILE: internvl_chat_llava/llava/model/language_model/mpt/blocks.py
  class MPTMLP (line 8) | class MPTMLP(nn.Module):
    method __init__ (line 10) | def __init__(self, d_model: int, expansion_ratio: int, device: Optiona...
    method forward (line 17) | def forward(self, x):
  class MPTBlock (line 20) | class MPTBlock(nn.Module):
    method __init__ (line 22) | def __init__(self, d_model: int, n_heads: int, expansion_ratio: int, a...
    method forward (line 34) | def forward(self, x: torch.Tensor, past_key_value: Optional[Tuple[torc...

FILE: internvl_chat_llava/llava/model/language_model/mpt/configuration_mpt.py
  class MPTConfig (line 7) | class MPTConfig(PretrainedConfig):
    method __init__ (line 10) | def __init__(self, d_model: int=2048, n_heads: int=16, n_layers: int=2...
    method _set_config_defaults (line 90) | def _set_config_defaults(self, config, config_defaults):
    method _validate_config (line 96) | def _validate_config(self):

FILE: internvl_chat_llava/llava/model/language_model/mpt/custom_embedding.py
  class SharedEmbedding (line 6) | class SharedEmbedding(nn.Embedding):
    method forward (line 8) | def forward(self, input: Tensor, unembed: bool=False) -> Tensor:

FILE: internvl_chat_llava/llava/model/language_model/mpt/flash_attn_triton.py
  function _fwd_kernel (line 51) | def _fwd_kernel(Q, K, V, Bias, Out, Lse, TMP, softmax_scale, stride_qb, ...
  function _bwd_preprocess_do_o_dot (line 155) | def _bwd_preprocess_do_o_dot(Out, DO, Delta, stride_ob, stride_oh, strid...
  function _bwd_store_dk_dv (line 168) | def _bwd_store_dk_dv(dk_ptrs, dv_ptrs, dk, dv, offs_n, offs_d, seqlen_k,...
  function _bwd_kernel_one_col_block (line 184) | def _bwd_kernel_one_col_block(start_n, Q, K, V, Bias, DO, DQ, DK, DV, LS...
  function init_to_zero (line 300) | def init_to_zero(name):
  function _bwd_kernel (line 306) | def _bwd_kernel(Q, K, V, Bias, DO, DQ, DK, DV, LSE, D, softmax_scale, st...
  function _flash_attn_forward (line 329) | def _flash_attn_forward(q, k, v, bias=None, causal=False, softmax_scale=...
  function _flash_attn_backward (line 366) | def _flash_attn_backward(do, q, k, v, o, lse, dq, dk, dv, bias=None, cau...
  class FlashAttnQKVPackedFunc (line 401) | class FlashAttnQKVPackedFunc(torch.autograd.Function):
    method forward (line 404) | def forward(ctx, qkv, bias=None, causal=False, softmax_scale=None):
    method backward (line 419) | def backward(ctx, do):
  class FlashAttnKVPackedFunc (line 428) | class FlashAttnKVPackedFunc(torch.autograd.Function):
    method forward (line 431) | def forward(ctx, q, kv, bias=None, causal=False, softmax_scale=None):
    method backward (line 446) | def backward(ctx, do):
  class FlashAttnFunc (line 457) | class FlashAttnFunc(torch.autograd.Function):
    method forward (line 460) | def forward(ctx, q, k, v, bias=None, causal=False, softmax_scale=None):
    method backward (line 475) | def backward(ctx, do):

FILE: internvl_chat_llava/llava/model/language_model/mpt/hf_prefixlm_converter.py
  function _convert_gpt_causal_lm_to_prefix_lm (line 29) | def _convert_gpt_causal_lm_to_prefix_lm(model: CAUSAL_GPT_TYPES) -> CAUS...
  function _convert_bloom_causal_lm_to_prefix_lm (line 113) | def _convert_bloom_causal_lm_to_prefix_lm(model: BloomForCausalLM) -> Bl...
  function _convert_opt_causal_lm_to_prefix_lm (line 269) | def _convert_opt_causal_lm_to_prefix_lm(model: OPTForCausalLM) -> OPTFor...
  function convert_hf_causal_lm_to_prefix_lm (line 335) | def convert_hf_causal_lm_to_prefix_lm(model: CAUSAL_LM_TYPES) -> CAUSAL_...
  function add_bidirectional_mask_if_missing (line 401) | def add_bidirectional_mask_if_missing(batch: Dict[str, Any]):

FILE: internvl_chat_llava/llava/model/language_model/mpt/meta_init_context.py
  function init_empty_weights (line 6) | def init_empty_weights(include_buffers: bool=False):
  function init_on_device (line 37) | def init_on_device(device: torch.device, include_buffers: bool=False):

FILE: internvl_chat_llava/llava/model/language_model/mpt/modeling_mpt.py
  class MPTPreTrainedModel (line 28) | class MPTPreTrainedModel(PreTrainedModel):
  class MPTModel (line 33) | class MPTModel(MPTPreTrainedModel):
    method __init__ (line 35) | def __init__(self, config: MPTConfig):
    method get_input_embeddings (line 81) | def get_input_embeddings(self):
    method set_input_embeddings (line 84) | def set_input_embeddings(self, value):
    method _attn_bias (line 88) | def _attn_bias(self, device, dtype, attention_mask: Optional[torch.Byt...
    method _apply_prefix_mask (line 119) | def _apply_prefix_mask(self, attn_bias: torch.Tensor, prefix_mask: tor...
    method _apply_sequence_id (line 134) | def _apply_sequence_id(self, attn_bias: torch.Tensor, sequence_id: tor...
    method forward (line 144) | def forward(self, input_ids: torch.LongTensor, past_key_values: Option...
    method param_init_fn (line 222) | def param_init_fn(self, module):
    method fsdp_wrap_fn (line 226) | def fsdp_wrap_fn(self, module):
    method activation_checkpointing_fn (line 229) | def activation_checkpointing_fn(self, module):
  class MPTForCausalLM (line 232) | class MPTForCausalLM(MPTPreTrainedModel):
    method __init__ (line 234) | def __init__(self, config: MPTConfig):
    method get_input_embeddings (line 255) | def get_input_embeddings(self):
    method set_input_embeddings (line 258) | def set_input_embeddings(self, value):
    method get_output_embeddings (line 261) | def get_output_embeddings(self):
    method set_output_embeddings (line 264) | def set_output_embeddings(self, new_embeddings):
    method set_decoder (line 267) | def set_decoder(self, decoder):
    method get_decoder (line 270) | def get_decoder(self):
    method forward (line 273) | def forward(self, input_ids: torch.LongTensor, past_key_values: Option...
    method param_init_fn (line 291) | def param_init_fn(self, module):
    method fsdp_wrap_fn (line 295) | def fsdp_wrap_fn(self, module):
    method activation_checkpointing_fn (line 298) | def activation_checkpointing_fn(self, module):
    method prepare_inputs_for_generation (line 301) | def prepare_inputs_for_generation(self, input_ids, past_key_values=Non...
    method _reorder_cache (line 322) | def _reorder_cache(past_key_values, beam_idx):

FILE: internvl_chat_llava/llava/model/language_model/mpt/norm.py
  function _cast_if_autocast_enabled (line 3) | def _cast_if_autocast_enabled(tensor):
  class LPLayerNorm (line 14) | class LPLayerNorm(torch.nn.LayerNorm):
    method __init__ (line 16) | def __init__(self, normalized_shape, eps=1e-05, elementwise_affine=Tru...
    method forward (line 19) | def forward(self, x):
  function rms_norm (line 27) | def rms_norm(x, weight=None, eps=1e-05):
  class RMSNorm (line 33) | class RMSNorm(torch.nn.Module):
    method __init__ (line 35) | def __init__(self, normalized_shape, eps=1e-05, weight=True, dtype=Non...
    method forward (line 43) | def forward(self, x):
  class LPRMSNorm (line 46) | class LPRMSNorm(RMSNorm):
    method __init__ (line 48) | def __init__(self, normalized_shape, eps=1e-05, weight=True, dtype=Non...
    method forward (line 51) | def forward(self, x):

FILE: internvl_chat_llava/llava/model/language_model/mpt/param_init_fns.py
  function torch_default_param_init_fn_ (line 10) | def torch_default_param_init_fn_(module: nn.Module, verbose: int=0, **kw...
  function fused_init_helper_ (line 17) | def fused_init_helper_(module: nn.Module, init_fn_):
  function generic_param_init_fn_ (line 28) | def generic_param_init_fn_(module: nn.Module, init_fn_, n_layers: int, d...
  function _normal_init_ (line 121) | def _normal_init_(std, mean=0.0):
  function _normal_param_init_fn_ (line 124) | def _normal_param_init_fn_(module: nn.Module, std: float, n_layers: int,...
  function baseline_param_init_fn_ (line 131) | def baseline_param_init_fn_(module: nn.Module, init_std: float, n_layers...
  function small_param_init_fn_ (line 137) | def small_param_init_fn_(module: nn.Module, n_layers: int, d_model: int,...
  function neox_param_init_fn_ (line 142) | def neox_param_init_fn_(module: nn.Module, n_layers: int, d_model: int, ...
  function kaiming_uniform_param_init_fn_ (line 155) | def kaiming_uniform_param_init_fn_(module: nn.Module, n_layers: int, d_m...
  function kaiming_normal_param_init_fn_ (line 162) | def kaiming_normal_param_init_fn_(module: nn.Module, n_layers: int, d_mo...
  function xavier_uniform_param_init_fn_ (line 169) | def xavier_uniform_param_init_fn_(module: nn.Module, n_layers: int, d_mo...
  function xavier_normal_param_init_fn_ (line 176) | def xavier_normal_param_init_fn_(module: nn.Module, n_layers: int, d_mod...

FILE: internvl_chat_llava/llava/model/llava_arch.py
  class LlavaMetaModel (line 27) | class LlavaMetaModel:
    method __init__ (line 29) | def __init__(self, config):
    method get_vision_tower (line 36) | def get_vision_tower(self):
    method initialize_vision_modules (line 42) | def initialize_vision_modules(self, model_args, fsdp=None):
  class LlavaMetaForCausalLM (line 90) | class LlavaMetaForCausalLM(ABC):
    method get_model (line 93) | def get_model(self):
    method get_vision_tower (line 96) | def get_vision_tower(self):
    method encode_images (line 99) | def encode_images(self, images):
    method prepare_inputs_labels_for_multimodal (line 104) | def prepare_inputs_labels_for_multimodal(
    method initialize_vision_tokenizer (line 223) | def initialize_vision_tokenizer(self, model_args, tokenizer):

FILE: internvl_chat_llava/llava/model/make_delta.py
  function make_delta (line 13) | def make_delta(base_model_path, target_model_path, delta_path, hub_repo_...

FILE: internvl_chat_llava/llava/model/multimodal_encoder/builder.py
  function build_vision_tower (line 5) | def build_vision_tower(vision_tower_cfg, **kwargs):

FILE: internvl_chat_llava/llava/model/multimodal_encoder/clip_encoder.py
  function is_intern_vit_6b_model (line 15) | def is_intern_vit_6b_model(vision_tower_name):
  function is_internvl_14b_model (line 20) | def is_internvl_14b_model(vision_tower_name):
  class CLIPVisionTower (line 25) | class CLIPVisionTower(nn.Module):
    method __init__ (line 26) | def __init__(self, vision_tower, args, delay_load=False):
    method load_model (line 47) | def load_model(self):
    method feature_select (line 72) | def feature_select(self, image_forward_outs):
    method forward (line 83) | def forward(self, images):
    method dummy_feature (line 107) | def dummy_feature(self):
    method dtype (line 111) | def dtype(self):
    method device (line 115) | def device(self):
    method config (line 119) | def config(self):
    method hidden_size (line 126) | def hidden_size(self):
    method num_patches (line 130) | def num_patches(self):

FILE: internvl_chat_llava/llava/model/multimodal_encoder/eva_clip/configuration_evaclip.py
  class EvaCLIPTextConfig (line 36) | class EvaCLIPTextConfig(PretrainedConfig):
    method __init__ (line 90) | def __init__(
    method from_pretrained (line 133) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....
  class EvaCLIPVisionConfig (line 151) | class EvaCLIPVisionConfig(PretrainedConfig):
    method __init__ (line 204) | def __init__(
    method from_pretrained (line 246) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....
  class EvaCLIPConfig (line 264) | class EvaCLIPConfig(PretrainedConfig):
    method __init__ (line 313) | def __init__(
    method from_text_vision_configs (line 402) | def from_text_vision_configs(cls, text_config: EvaCLIPTextConfig, visi...
    method to_dict (line 413) | def to_dict(self):

FILE: internvl_chat_llava/llava/model/multimodal_encoder/eva_clip/modeling_evaclip.py
  function _expand_mask (line 48) | def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Option...
  function contrastive_loss (line 64) | def contrastive_loss(logits: torch.Tensor) -> torch.Tensor:
  function clip_loss (line 68) | def clip_loss(similarity: torch.Tensor) -> torch.Tensor:
  class EvaCLIPVisionModelOutput (line 75) | class EvaCLIPVisionModelOutput(ModelOutput):
  class EvaCLIPTextModelOutput (line 104) | class EvaCLIPTextModelOutput(ModelOutput):
  class EvaCLIPOutput (line 133) | class EvaCLIPOutput(ModelOutput):
    method to_tuple (line 162) | def to_tuple(self) -> Tuple[Any]:
  class EvaCLIPVisionEmbeddings (line 169) | class EvaCLIPVisionEmbeddings(nn.Module):
    method __init__ (line 170) | def __init__(self, config: EvaCLIPVisionConfig):
    method forward (line 192) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class EvaCLIPTextEmbeddings (line 203) | class EvaCLIPTextEmbeddings(nn.Module):
    method __init__ (line 204) | def __init__(self, config: EvaCLIPTextConfig):
    method forward (line 214) | def forward(
  class EvaCLIPAttention (line 234) | class EvaCLIPAttention(nn.Module):
    method __init__ (line 237) | def __init__(self, config):
    method _shape (line 255) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 258) | def forward(
  class EvaCLIPTextAttention (line 336) | class EvaCLIPTextAttention(nn.Module):
    method __init__ (line 339) | def __init__(self, config):
    method _shape (line 357) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 360) | def forward(
  class EvaCLIPMLP (line 438) | class EvaCLIPMLP(nn.Module):
    method __init__ (line 439) | def __init__(self, config):
    method forward (line 446) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class EvaCLIPEncoderLayer (line 453) | class EvaCLIPEncoderLayer(nn.Module):
    method __init__ (line 454) | def __init__(self, config: EvaCLIPConfig):
    method forward (line 464) | def forward(
  class EvaCLIPPreTrainedModel (line 510) | class EvaCLIPPreTrainedModel(PreTrainedModel):
    method _init_weights (line 521) | def _init_weights(self, module):
    method _set_gradient_checkpointing (line 574) | def _set_gradient_checkpointing(self, module, value=False):
  class EvaCLIPEncoder (line 679) | class EvaCLIPEncoder(nn.Module):
    method __init__ (line 688) | def __init__(self, config: EvaCLIPConfig):
    method forward (line 694) | def forward(
  class EvaCLIPTextTransformer (line 782) | class EvaCLIPTextTransformer(nn.Module):
    method __init__ (line 783) | def __init__(self, config: EvaCLIPTextConfig):
    method forward (line 793) | def forward(
    method _build_causal_attention_mask (line 861) | def _build_causal_attention_mask(self, bsz, seq_len, dtype):
  class EvaCLIPTextModel (line 875) | class EvaCLIPTextModel(EvaCLIPPreTrainedModel):
    method __init__ (line 880) | def __init__(self, config: EvaCLIPTextConfig):
    method get_input_embeddings (line 886) | def get_input_embeddings(self) -> nn.Module:
    method set_input_embeddings (line 889) | def set_input_embeddings(self, value):
    method forward (line 894) | def forward(
  class EvaCLIPVisionTransformer (line 932) | class EvaCLIPVisionTransformer(nn.Module):
    method __init__ (line 933) | def __init__(self, config: EvaCLIPVisionConfig):
    method forward (line 944) | def forward(
  class EvaCLIPVisionModel (line 992) | class EvaCLIPVisionModel(EvaCLIPPreTrainedModel):
    method __init__ (line 996) | def __init__(self, config: EvaCLIPVisionConfig):
    method get_input_embeddings (line 1002) | def get_input_embeddings(self) -> nn.Module:
    method forward (line 1007) | def forward(
  class EvaCLIPModel (line 1047) | class EvaCLIPModel(EvaCLIPPreTrainedModel):
    method __init__ (line 1050) | def __init__(self, config: EvaCLIPConfig):
    method get_text_features (line 1083) | def get_text_features(
    method get_image_features (line 1130) | def get_image_features(
    method forward (line 1180) | def forward(
  class EvaCLIPTextModelWithProjection (line 1278) | class EvaCLIPTextModelWithProjection(EvaCLIPPreTrainedModel):
    method __init__ (line 1283) | def __init__(self, config: EvaCLIPTextConfig):
    method get_input_embeddings (line 1293) | def get_input_embeddings(self) -> nn.Module:
    method set_input_embeddings (line 1296) | def set_input_embeddings(self, value):
    method forward (line 1301) | def forward(
  class EvaCLIPVisionModelWithProjection (line 1359) | class EvaCLIPVisionModelWithProjection(EvaCLIPPreTrainedModel):
    method __init__ (line 1363) | def __init__(self, config: EvaCLIPVisionConfig):
    method get_input_embeddings (line 1373) | def get_input_embeddings(self) -> nn.Module:
    method forward (line 1378) | def forward(

FILE: internvl_chat_llava/llava/model/multimodal_encoder/intern_vit_6b/configuration_intern_vit.py
  class InternVisionConfig (line 15) | class InternVisionConfig(PretrainedConfig):
    method __init__ (line 63) | def __init__(
    method from_pretrained (line 105) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....

FILE: internvl_chat_llava/llava/model/multimodal_encoder/intern_vit_6b/flash_attention.py
  class FlashAttention (line 14) | class FlashAttention(nn.Module):
    method __init__ (line 25) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 30) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...

FILE: internvl_chat_llava/llava/model/multimodal_encoder/intern_vit_6b/modeling_intern_vit.py
  class InternRMSNorm (line 33) | class InternRMSNorm(nn.Module):
    method __init__ (line 34) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 39) | def forward(self, hidden_states):
  class InternVisionEmbeddings (line 61) | class InternVisionEmbeddings(nn.Module):
    method __init__ (line 62) | def __init__(self, config: InternVisionConfig):
    method _get_pos_embed (line 82) | def _get_pos_embed(self, pos_embed, H, W):
    method forward (line 90) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class InternAttention (line 105) | class InternAttention(nn.Module):
    method __init__ (line 108) | def __init__(self, config: InternVisionConfig):
    method _naive_attn (line 138) | def _naive_attn(self, x):
    method _flash_attn (line 157) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 174) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternMLP (line 179) | class InternMLP(nn.Module):
    method __init__ (line 180) | def __init__(self, config: InternVisionConfig):
    method forward (line 187) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternVisionEncoderLayer (line 194) | class InternVisionEncoderLayer(nn.Module):
    method __init__ (line 195) | def __init__(self, config: InternVisionConfig, drop_path_rate: float):
    method forward (line 210) | def forward(
  class InternVisionEncoder (line 225) | class InternVisionEncoder(nn.Module):
    method __init__ (line 235) | def __init__(self, config: InternVisionConfig):
    method forward (line 244) | def forward(
  class InternVisionModel (line 291) | class InternVisionModel(PreTrainedModel):
    method __init__ (line 295) | def __init__(self, config: InternVisionConfig):
    method resize_pos_embeddings (line 302) | def resize_pos_embeddings(self, old_size, new_size, patch_size):
    method get_input_embeddings (line 313) | def get_input_embeddings(self):
    method forward (line 316) | def forward(

FILE: internvl_chat_llava/llava/model/multimodal_encoder/internvl_14b/__init__.py
  class InternVLTokenizer (line 23) | class InternVLTokenizer(nn.Module):
    method __init__ (line 24) | def __init__(self, model_path):
    method forward (line 30) | def forward(self, text, prefix='summarize:'):
  function build_transform (line 39) | def build_transform(task, image_size=224, mean=[0.485, 0.456, 0.406], st...
  function load_internvl_c_huggingface (line 56) | def load_internvl_c_huggingface(ckpt_path, device, task):
  function load_internvl_g_huggingface (line 73) | def load_internvl_g_huggingface(ckpt_path, device, task):

FILE: internvl_chat_llava/llava/model/multimodal_encoder/internvl_14b/configuration_intern_vit.py
  class InternVisionConfig (line 15) | class InternVisionConfig(PretrainedConfig):
    method __init__ (line 63) | def __init__(
    method from_pretrained (line 105) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....

FILE: internvl_chat_llava/llava/model/multimodal_encoder/internvl_14b/configuration_internvl.py
  class InternVLConfig (line 17) | class InternVLConfig(PretrainedConfig):
    method __init__ (line 57) | def __init__(
    method to_dict (line 97) | def to_dict(self):

FILE: internvl_chat_llava/llava/model/multimodal_encoder/internvl_14b/flash_attention.py
  class FlashAttention (line 15) | class FlashAttention(nn.Module):
    method __init__ (line 26) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 31) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...

FILE: internvl_chat_llava/llava/model/multimodal_encoder/internvl_14b/modeling_intern_vit.py
  class InternRMSNorm (line 33) | class InternRMSNorm(nn.Module):
    method __init__ (line 34) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 39) | def forward(self, hidden_states):
  class InternVisionEmbeddings (line 61) | class InternVisionEmbeddings(nn.Module):
    method __init__ (line 62) | def __init__(self, config: InternVisionConfig):
    method _get_pos_embed (line 82) | def _get_pos_embed(self, pos_embed, H, W):
    method forward (line 90) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class InternAttention (line 105) | class InternAttention(nn.Module):
    method __init__ (line 108) | def __init__(self, config: InternVisionConfig):
    method _naive_attn (line 138) | def _naive_attn(self, x):
    method _flash_attn (line 157) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 174) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternMLP (line 179) | class InternMLP(nn.Module):
    method __init__ (line 180) | def __init__(self, config: InternVisionConfig):
    method forward (line 187) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternVisionEncoderLayer (line 194) | class InternVisionEncoderLayer(nn.Module):
    method __init__ (line 195) | def __init__(self, config: InternVisionConfig, drop_path_rate: float):
    method forward (line 210) | def forward(
  class InternVisionEncoder (line 225) | class InternVisionEncoder(nn.Module):
    method __init__ (line 235) | def __init__(self, config: InternVisionConfig):
    method forward (line 244) | def forward(
  class InternVisionModel (line 291) | class InternVisionModel(PreTrainedModel):
    method __init__ (line 295) | def __init__(self, config: InternVisionConfig):
    method resize_pos_embeddings (line 302) | def resize_pos_embeddings(self, old_size, new_size, patch_size):
    method get_input_embeddings (line 313) | def get_input_embeddings(self):
    method forward (line 316) | def forward(

FILE: internvl_chat_llava/llava/model/multimodal_encoder/internvl_14b/modeling_internvl.py
  class InternVLPreTrainedModel (line 33) | class InternVLPreTrainedModel(PreTrainedModel):
    method _init_weights (line 49) | def _init_weights(self, module):
    method _set_gradient_checkpointing (line 67) | def _set_gradient_checkpointing(self, module, value=False):
  class CrossAttention (line 74) | class CrossAttention(nn.Module):
    method __init__ (line 75) | def __init__(
    method forward (line 106) | def forward(self, x, k=None, v=None):
  class AttentiveBlock (line 139) | class AttentiveBlock(nn.Module):
    method __init__ (line 141) | def __init__(self, dim, num_heads, qkv_bias=False, qk_scale=None, drop...
    method forward (line 154) | def forward(self, x_q, x_kv, pos_q, pos_k, bool_masked_pos, rel_pos_bi...
  class AttentionPoolingBlock (line 163) | class AttentionPoolingBlock(AttentiveBlock):
    method forward (line 165) | def forward(self, x):
  class InternVLModel (line 173) | class InternVLModel(InternVLPreTrainedModel):
    method __init__ (line 177) | def __init__(self, config: InternVLConfig):
    method wrap_backbone_lora (line 218) | def wrap_backbone_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method wrap_qllama_lora (line 228) | def wrap_qllama_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method get_input_embeddings (line 239) | def get_input_embeddings(self):
    method set_input_embeddings (line 242) | def set_input_embeddings(self, value):
    method set_output_embeddings (line 245) | def set_output_embeddings(self, new_embeddings):
    method get_output_embeddings (line 248) | def get_output_embeddings(self) -> nn.Module:
    method generate (line 252) | def generate(
    method get_text_features (line 287) | def get_text_features(
    method get_image_features (line 336) | def get_image_features(
    method encode_image (line 382) | def encode_image(self, image, mode):
    method encode_text (line 406) | def encode_text(self, text):
    method forward (line 419) | def forward(self, pixel_values: torch.FloatTensor,
  class InternVL_C (line 461) | class InternVL_C(InternVLModel):
    method encode_image (line 463) | def encode_image(self, image):
    method encode_text (line 472) | def encode_text(self, text):
    method forward (line 485) | def forward(self, image, text):
  class InternVL_G (line 501) | class InternVL_G(InternVLModel):
    method encode_image (line 503) | def encode_image(self, image):
    method encode_text (line 517) | def encode_text(self, text):
    method forward (line 530) | def forward(self, image, text):

FILE: internvl_chat_llava/llava/model/multimodal_encoder/internvl_14b/modeling_qllama.py
  function _make_causal_mask (line 42) | def _make_causal_mask(
  function _expand_mask (line 60) | def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Option...
  class LlamaRMSNorm (line 74) | class LlamaRMSNorm(nn.Module):
    method __init__ (line 75) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 83) | def forward(self, hidden_states):
  class LlamaRotaryEmbedding (line 109) | class LlamaRotaryEmbedding(torch.nn.Module):
    method __init__ (line 110) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method forward (line 124) | def forward(self, x, seq_len=None):
  class FixedLlamaRotaryEmbedding (line 141) | class FixedLlamaRotaryEmbedding(torch.nn.Module):
    method __init__ (line 142) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method _set_cos_sin_cache (line 155) | def _set_cos_sin_cache(self, seq_len, device, dtype):
    method forward (line 165) | def forward(self, x, seq_len=None):
  function rotate_half (line 179) | def rotate_half(x):
  function apply_rotary_pos_emb (line 186) | def apply_rotary_pos_emb(q, k, cos, sin, position_ids):
  class LlamaMLP (line 196) | class LlamaMLP(nn.Module):
    method __init__ (line 197) | def __init__(
    method forward (line 209) | def forward(self, x):
  class LlamaAttention (line 213) | class LlamaAttention(nn.Module):
    method __init__ (line 216) | def __init__(self, config: LlamaConfig):
    method _shape (line 235) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 238) | def forward(
  class LlamaCrossAttention (line 304) | class LlamaCrossAttention(nn.Module):
    method __init__ (line 307) | def __init__(self, config: LlamaConfig):
    method _shape (line 329) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method forward (line 332) | def forward(
  class LlamaDecoderLayer (line 408) | class LlamaDecoderLayer(nn.Module):
    method __init__ (line 409) | def __init__(self, config: LlamaConfig, use_cross_attn: bool):
    method forward (line 423) | def forward(
  class LlamaPreTrainedModel (line 520) | class LlamaPreTrainedModel(PreTrainedModel):
    method _init_weights (line 527) | def _init_weights(self, module):
    method _set_gradient_checkpointing (line 538) | def _set_gradient_checkpointing(self, module, value=False):
  class LlamaModel (line 613) | class LlamaModel(LlamaPreTrainedModel):
    method __init__ (line 621) | def __init__(self, config: LlamaConfig):
    method get_input_embeddings (line 636) | def get_input_embeddings(self):
    method set_input_embeddings (line 639) | def set_input_embeddings(self, value):
    method _prepare_decoder_attention_mask (line 643) | def _prepare_decoder_attention_mask(self, attention_mask, input_shape,...
    method forward (line 667) | def forward(
    method forward_train (line 783) | def forward_train(
  class LlamaForCausalLM (line 915) | class LlamaForCausalLM(LlamaPreTrainedModel):
    method __init__ (line 916) | def __init__(self, config):
    method get_input_embeddings (line 925) | def get_input_embeddings(self):
    method set_input_embeddings (line 928) | def set_input_embeddings(self, value):
    method get_output_embeddings (line 931) | def get_output_embeddings(self):
    method set_output_embeddings (line 934) | def set_output_embeddings(self, new_embeddings):
    method set_decoder (line 937) | def set_decoder(self, decoder):
    method get_decoder (line 940) | def get_decoder(self):
    method forward (line 945) | def forward(
    method prepare_inputs_for_generation (line 1035) | def prepare_inputs_for_generation(
    method _reorder_cache (line 1069) | def _reorder_cache(past_key_values, beam_idx):

FILE: internvl_chat_llava/llava/model/multimodal_projector/builder.py
  class IdentityMap (line 6) | class IdentityMap(nn.Module):
    method __init__ (line 7) | def __init__(self):
    method forward (line 10) | def forward(self, x, *args, **kwargs):
    method config (line 14) | def config(self):
  class SimpleResBlock (line 18) | class SimpleResBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, channels):
    method forward (line 28) | def forward(self, x):
  class TwoMLP (line 33) | class TwoMLP(nn.Module):
    method __init__ (line 34) | def __init__(self, config):
    method forward (line 48) | def forward(self, inputs):
  function build_vision_projector (line 58) | def build_vision_projector(config, delay_load=False, **kwargs):

FILE: internvl_chat_llava/llava/model/utils.py
  function auto_upgrade (line 4) | def auto_upgrade(config):

FILE: internvl_chat_llava/llava/serve/cli.py
  function load_image (line 18) | def load_image(image_file):
  function main (line 27) | def main(args):

FILE: internvl_chat_llava/llava/serve/controller.py
  class DispatchMethod (line 28) | class DispatchMethod(Enum):
    method from_str (line 33) | def from_str(cls, name):
  class WorkerInfo (line 43) | class WorkerInfo:
  function heart_beat_controller (line 51) | def heart_beat_controller(controller):
  class Controller (line 57) | class Controller:
    method __init__ (line 58) | def __init__(self, dispatch_method: str):
    method register_worker (line 69) | def register_worker(self, worker_name: str, check_heart_beat: bool,
    method get_worker_status (line 88) | def get_worker_status(self, worker_name: str):
    method remove_worker (line 101) | def remove_worker(self, worker_name: str):
    method refresh_all_workers (line 104) | def refresh_all_workers(self):
    method list_models (line 112) | def list_models(self):
    method get_worker_address (line 120) | def get_worker_address(self, model_name: str):
    method receive_heart_beat (line 173) | def receive_heart_beat(self, worker_name: str, queue_length: int):
    method remove_stable_workers_by_expiration (line 183) | def remove_stable_workers_by_expiration(self):
    method worker_api_generate_stream (line 193) | def worker_api_generate_stream(self, params):
    method worker_api_get_status (line 220) | def worker_api_get_status(self):
  function register_worker (line 243) | async def register_worker(request: Request):
  function refresh_all_workers (line 251) | async def refresh_all_workers():
  function list_models (line 256) | async def list_models():
  function get_worker_address (line 262) | async def get_worker_address(request: Request):
  function receive_heart_beat (line 269) | async def receive_heart_beat(request: Request):
  function worker_api_generate_stream (line 277) | async def worker_api_generate_stream(request: Request):
  function worker_api_get_status (line 284) | async def worker_api_get_status(request: Request):

FILE: internvl_chat_llava/llava/serve/gradio_web_server.py
  function get_conv_log_filename (line 32) | def get_conv_log_filename():
  function sort_models (line 38) | def sort_models(models):
  function get_model_list (line 58) | def get_model_list():
  function load_demo (line 79) | def load_demo(url_params, request: gr.Request):
  function load_demo_refresh_model_list (line 93) | def load_demo_refresh_model_list(request: gr.Request):
  function vote_last_response (line 104) | def vote_last_response(state, vote_type, model_selector, request: gr.Req...
  function upvote_last_response (line 116) | def upvote_last_response(state, model_selector, request: gr.Request):
  function downvote_last_response (line 122) | def downvote_last_response(state, model_selector, request: gr.Request):
  function flag_last_response (line 128) | def flag_last_response(state, model_selector, request: gr.Request):
  function regenerate (line 134) | def regenerate(state, image_process_mode, request: gr.Request):
  function clear_history (line 144) | def clear_history(request: gr.Request):
  function add_text (line 150) | def add_text(state, text, image, image_process_mode, request: gr.Request):
  function http_bot (line 174) | def http_bot(state, model_selector, temperature, top_p, max_new_tokens, ...
  function build_demo (line 344) | def build_demo(embed_mode):

FILE: internvl_chat_llava/llava/serve/model_worker.py
  function heart_beat_worker (line 37) | def heart_beat_worker(controller):
  class ModelWorker (line 44) | class ModelWorker:
    method __init__ (line 45) | def __init__(self, controller_addr, worker_addr,
    method register_to_controller (line 75) | def register_to_controller(self):
    method send_heart_beat (line 87) | def send_heart_beat(self):
    method get_queue_length (line 108) | def get_queue_length(self):
    method get_status (line 115) | def get_status(self):
    method generate_stream (line 123) | def generate_stream(self, params):
    method generate_stream_gate (line 194) | def generate_stream_gate(self, params):
  function release_model_semaphore (line 224) | def release_model_semaphore(fn=None):
  function generate_stream (line 231) | async def generate_stream(request: Request):
  function get_status (line 247) | async def get_status(request: Request):

FILE: internvl_chat_llava/llava/serve/test_message.py
  function main (line 9) | def main():

FILE: internvl_chat_llava/llava/train/dist_utils.py
  function _find_free_port (line 13) | def _find_free_port():
  function _is_free_port (line 24) | def _is_free_port(port):
  function init_dist (line 31) | def init_dist(launcher, backend='nccl', **kwargs):
  function _init_dist_pytorch (line 44) | def _init_dist_pytorch(backend, **kwargs):
  function _init_dist_mpi (line 52) | def _init_dist_mpi(backend, **kwargs):
  function _init_dist_slurm (line 65) | def _init_dist_slurm(backend, port=None):

FILE: internvl_chat_llava/llava/train/llama_flash_attn_monkey_patch.py
  function forward (line 16) | def forward(
  function _prepare_decoder_attention_mask (line 98) | def _prepare_decoder_attention_mask(
  function replace_llama_attn_with_flash_attn (line 105) | def replace_llama_attn_with_flash_attn():

FILE: internvl_chat_llava/llava/train/llava_trainer.py
  function maybe_zero_3 (line 13) | def maybe_zero_3(param, ignore_status=False, name=None):
  function get_mm_adapter_state_maybe_zero_3 (line 27) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function split_to_even_chunks (line 33) | def split_to_even_chunks(indices, lengths, num_chunks):
  function get_modality_length_grouped_indices (line 55) | def get_modality_length_grouped_indices(lengths, batch_size, world_size,...
  function get_length_grouped_indices (line 87) | def get_length_grouped_indices(lengths, batch_size, world_size, generato...
  class LengthGroupedSampler (line 98) | class LengthGroupedSampler(Sampler):
    method __init__ (line 104) | def __init__(
    method __len__ (line 121) | def __len__(self):
    method __iter__ (line 124) | def __iter__(self):
  class LLaVATrainer (line 132) | class LLaVATrainer(Trainer):
    method _get_train_sampler (line 134) | def _get_train_sampler(self) -> Optional[torch.utils.data.Sampler]:
    method _save_checkpoint (line 150) | def _save_checkpoint(self, model, trial, metrics=None):
    method _save (line 176) | def _save(self, output_dir: Optional[str] = None, state_dict=None):

FILE: internvl_chat_llava/llava/train/train.py
  function rank0_print (line 44) | def rank0_print(*args):
  class ModelArguments (line 50) | class ModelArguments:
  class DataArguments (line 66) | class DataArguments:
  class TrainingArguments (line 77) | class TrainingArguments(transformers.TrainingArguments):
  function maybe_zero_3 (line 112) | def maybe_zero_3(param, ignore_status=False, name=None):
  function get_peft_state_maybe_zero_3 (line 127) | def get_peft_state_maybe_zero_3(named_params, bias):
  function get_peft_state_non_lora_maybe_zero_3 (line 152) | def get_peft_state_non_lora_maybe_zero_3(named_params, require_grad_only...
  function get_mm_adapter_state_maybe_zero_3 (line 160) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function find_all_linear_names (line 166) | def find_all_linear_names(model):
  function safe_save_model_for_hf_trainer (line 180) | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer,
  function smart_tokenizer_and_embedding_resize (line 224) | def smart_tokenizer_and_embedding_resize(
  function _tokenize_fn (line 249) | def _tokenize_fn(strings: Sequence[str],
  function _mask_targets (line 276) | def _mask_targets(target, tokenized_lens, speakers):
  function _add_speaker_and_signal (line 287) | def _add_speaker_and_signal(header, source, get_conversation=True):
  function preprocess_multimodal (line 308) | def preprocess_multimodal(
  function preprocess_llama_2 (line 332) | def preprocess_llama_2(
  function preprocess_v1 (line 414) | def preprocess_v1(
  function preprocess_mpt (line 505) | def preprocess_mpt(
  function preprocess_plain (line 571) | def preprocess_plain(
  function preprocess (line 593) | def preprocess(
  class LazySupervisedDataset (line 641) | class LazySupervisedDataset(Dataset):
    method __init__ (line 644) | def __init__(self, data_path: str,
    method __len__ (line 655) | def __len__(self):
    method lengths (line 659) | def lengths(self):
    method modality_lengths (line 667) | def modality_lengths(self):
    method __getitem__ (line 675) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  class DataCollatorForSupervisedDataset (line 733) | class DataCollatorForSupervisedDataset(object):
    method __call__ (line 738) | def __call__(self, instances: Sequence[Dict]) -> Dict[str, torch.Tensor]:
  function make_supervised_data_module (line 766) | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokeni...
  function train (line 778) | def train(attn_implementation=None):

FILE: internvl_chat_llava/llava/train/train_custom.py
  function pil_loader (line 52) | def pil_loader(img_str):
  class TCSLoader (line 58) | class TCSLoader(object):
    method __init__ (line 60) | def __init__(self, conf_path):
    method __call__ (line 66) | def __call__(self, fn):
  function rank0_print (line 75) | def rank0_print(*args):
  class ModelArguments (line 81) | class ModelArguments:
  class DataArguments (line 97) | class DataArguments:
  class TrainingArguments (line 108) | class TrainingArguments(transformers.TrainingArguments):
  function maybe_zero_3 (line 143) | def maybe_zero_3(param, ignore_status=False, name=None):
  function get_peft_state_maybe_zero_3 (line 158) | def get_peft_state_maybe_zero_3(named_params, bias):
  function get_peft_state_non_lora_maybe_zero_3 (line 183) | def get_peft_state_non_lora_maybe_zero_3(named_params, require_grad_only...
  function get_mm_adapter_state_maybe_zero_3 (line 191) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function find_all_linear_names (line 197) | def find_all_linear_names(model):
  function safe_save_model_for_hf_trainer (line 211) | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer,
  function smart_tokenizer_and_embedding_resize (line 255) | def smart_tokenizer_and_embedding_resize(
  function _tokenize_fn (line 280) | def _tokenize_fn(strings: Sequence[str],
  function _mask_targets (line 307) | def _mask_targets(target, tokenized_lens, speakers):
  function _add_speaker_and_signal (line 318) | def _add_speaker_and_signal(header, source, get_conversation=True):
  function preprocess_multimodal (line 339) | def preprocess_multimodal(
  function preprocess_llama_2 (line 363) | def preprocess_llama_2(
  function preprocess_v1 (line 445) | def preprocess_v1(
  function preprocess_mpt (line 536) | def preprocess_mpt(
  function preprocess_plain (line 602) | def preprocess_plain(
  function preprocess (line 624) | def preprocess(
  class WeightedConcatDataset (line 675) | class WeightedConcatDataset(ConcatDataset):
    method __init__ (line 676) | def __init__(self, datasets, weights):
    method __iter__ (line 682) | def __iter__(self):
    method __len__ (line 685) | def __len__(self):
  class LazySupervisedDataset (line 689) | class LazySupervisedDataset(Dataset):
    method __init__ (line 692) | def __init__(self, meta,
    method __len__ (line 708) | def __len__(self):
    method lengths (line 712) | def lengths(self):
    method modality_lengths (line 720) | def modality_lengths(self):
    method __getitem__ (line 728) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  class DataCollatorForSupervisedDataset (line 788) | class DataCollatorForSupervisedDataset(object):
    method __call__ (line 793) | def __call__(self, instances: Sequence[Dict]) -> Dict[str, torch.Tensor]:
  function make_supervised_data_module (line 821) | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokeni...
  function train (line 850) | def train(attn_implementation=None):

FILE: internvl_chat_llava/llava/utils.py
  function build_logger (line 17) | def build_logger(logger_name, logger_filename):
  class StreamToLogger (line 60) | class StreamToLogger(object):
    method __init__ (line 64) | def __init__(self, logger, log_level=logging.INFO):
    method __getattr__ (line 70) | def __getattr__(self, attr):
    method write (line 73) | def write(self, buf):
    method flush (line 87) | def flush(self):
  function disable_torch_init (line 93) | def disable_torch_init():
  function violates_moderation (line 102) | def violates_moderation(text):
  function pretty_print_semaphore (line 123) | def pretty_print_semaphore(semaphore):

FILE: internvl_chat_llava/scripts/convert_mmbench_for_submission.py
  function get_args (line 6) | def get_args():

FILE: internvl_chat_llava/scripts/convert_seed_for_submission.py
  function get_args (line 6) | def get_args():
  function eval_single (line 14) | def eval_single(result_file, eval_only_type=None):

FILE: internvl_chat_llava/scripts/convert_sqa_to_llava.py
  function convert_to_llava (line 8) | def convert_to_llava(base_dir, split, prompt_format="QCM-LEA"):
  function convert_to_jsonl (line 49) | def convert_to_jsonl(base_dir, split, prompt_format="QCM-LEPA"):
  function main (line 83) | def main(task, **kwargs):

FILE: internvl_chat_llava/scripts/convert_sqa_to_llava_base_prompt.py
  function get_question_text (line 1) | def get_question_text(problem):
  function get_context_text (line 6) | def get_context_text(problem, use_caption):
  function get_choice_text (line 15) | def get_choice_text(probelm, options):
  function get_answer (line 25) | def get_answer(problem, options):
  function get_lecture_text (line 29) | def get_lecture_text(problem):
  function get_solution_text (line 35) | def get_solution_text(problem):
  function create_one_example_chatbot (line 41) | def create_one_example_chatbot(format, question, context, choice, answer...
  function create_one_example (line 106) | def create_one_example(format, question, context, choice, answer, lectur...
  function create_one_example_gpt4 (line 162) | def create_one_example_gpt4(format, question, context, choice, answer, l...
  function build_prompt_chatbot (line 221) | def build_prompt_chatbot(problems, shot_qids, prompt_format, use_caption...
  function build_prompt (line 244) | def build_prompt(problems, shot_qids, test_qid, args):
  function build_prompt_gpt4 (line 291) | def build_prompt_gpt4(problems, shot_qids, test_qid, args):

FILE: internvl_chat_llava/scripts/convert_vizwiz_for_submission.py
  function parse_args (line 8) | def parse_args():

FILE: internvl_chat_llava/scripts/convert_vqav2_for_submission.py
  function parse_args (line 8) | def parse_args():

FILE: internvl_chat_llava/scripts/merge_lora_weights.py
  function merge_lora (line 6) | def merge_lora(args):

FILE: internvl_g/eval/evaluate_caption.py
  class CaptionDataset (line 36) | class CaptionDataset(torch.utils.data.Dataset):
    method __init__ (line 38) | def __init__(self, name, root, annotation, prompt, input_size=224):
    method __len__ (line 53) | def __len__(self):
    method __getitem__ (line 56) | def __getitem__(self, idx):
  function collate_fn (line 76) | def collate_fn(inputs, tokenizer):
  class InferenceSampler (line 85) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 87) | def __init__(self, size):
    method _get_local_indices (line 95) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 104) | def __iter__(self):
    method __len__ (line 107) | def __len__(self):
  function evaluate_qllama_model (line 111) | def evaluate_qllama_model():

FILE: internvl_g/internvl/dist_utils.py
  function _find_free_port (line 13) | def _find_free_port():
  function _is_free_port (line 24) | def _is_free_port(port):
  function init_dist (line 31) | def init_dist(launcher, backend='nccl', **kwargs):
  function _init_dist_pytorch (line 44) | def _init_dist_pytorch(backend, **kwargs):
  function _init_dist_mpi (line 52) | def _init_dist_mpi(backend, **kwargs):
  function _init_dist_slurm (line 65) | def _init_dist_slurm(backend, port=None):

FILE: internvl_g/internvl/model/internvl_stage2/__init__.py
  class InternVLTokenizer (line 23) | class InternVLTokenizer(nn.Module):
    method __init__ (line 24) | def __init__(self, model_path):
    method forward (line 30) | def forward(self, text, prefix='summarize:'):
  function build_transform (line 39) | def build_transform(task, image_size=224, mean=[0.485, 0.456, 0.406], st...
  function load_internvl_c_huggingface (line 56) | def load_internvl_c_huggingface(ckpt_path, device, task):
  function load_internvl_g_huggingface (line 73) | def load_internvl_g_huggingface(ckpt_path, device, task):

FILE: internvl_g/internvl/model/internvl_stage2/configuration_intern_vit.py
  class InternVisionConfig (line 15) | class InternVisionConfig(PretrainedConfig):
    method __init__ (line 63) | def __init__(
    method from_pretrained (line 105) | def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os....

FILE: internvl_g/internvl/model/internvl_stage2/configuration_internvl.py
  class InternVLConfig (line 17) | class InternVLConfig(PretrainedConfig):
    method __init__ (line 57) | def __init__(
    method to_dict (line 97) | def to_dict(self):

FILE: internvl_g/internvl/model/internvl_stage2/flash_attention.py
  class FlashAttention (line 15) | class FlashAttention(nn.Module):
    method __init__ (line 26) | def __init__(self, softmax_scale=None, attention_dropout=0.0, device=N...
    method forward (line 31) | def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens...

FILE: internvl_g/internvl/model/internvl_stage2/modeling_intern_vit.py
  class InternRMSNorm (line 33) | class InternRMSNorm(nn.Module):
    method __init__ (line 34) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 39) | def forward(self, hidden_states):
  class InternVisionEmbeddings (line 61) | class InternVisionEmbeddings(nn.Module):
    method __init__ (line 62) | def __init__(self, config: InternVisionConfig):
    method forward (line 82) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class InternAttention (line 93) | class InternAttention(nn.Module):
    method __init__ (line 96) | def __init__(self, config: InternVisionConfig):
    method _naive_attn (line 126) | def _naive_attn(self, x):
    method _flash_attn (line 145) | def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
    method forward (line 162) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternMLP (line 167) | class InternMLP(nn.Module):
    method __init__ (line 168) | def __init__(self, config: InternVisionConfig):
    method forward (line 175) | def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
  class InternVisionEncoderLayer (line 182) | class InternVisionEncoderLayer(nn.Module):
    method __init__ (line 183) | def __init__(self, config: InternVisionConfig, drop_path_rate: float):
    method forward (line 198) | def forward(
  class InternVisionEncoder (line 213) | class InternVisionEncoder(nn.Module):
    method __init__ (line 223) | def __init__(self, config: InternVisionConfig):
    method forward (line 232) | def forward(
  class InternVisionModel (line 279) | class InternVisionModel(PreTrainedModel):
    method __init__ (line 283) | def __init__(self, config: InternVisionConfig):
    method resize_pos_embeddings (line 290) | def resize_pos_embeddings(self, old_size, new_size, patch_size):
    method get_input_embeddings (line 301) | def get_input_embeddings(self):
    method forward (line 304) | def forward(

FILE: internvl_g/internvl/model/internvl_stage2/modeling_internvl.py
  class InternVLPreTrainedModel (line 35) | class InternVLPreTrainedModel(PreTrainedModel):
    method _set_gradient_checkpointing (line 69) | def _set_gradient_checkpointing(self, module, value=False):
  class CrossAttention (line 76) | class CrossAttention(nn.Module):
    method __init__ (line 77) | def __init__(
    method forward (line 108) | def forward(self, x, k=None, v=None):
  class AttentiveBlock (line 141) | class AttentiveBlock(nn.Module):
    method __init__ (line 143) | def __init__(self, dim, num_heads, qkv_bias=False, qk_scale=None, drop...
    method forward (line 156) | def forward(self, x_q, x_kv, pos_q, pos_k, bool_masked_pos, rel_pos_bi...
  class AttentionPoolingBlock (line 165) | class AttentionPoolingBlock(AttentiveBlock):
    method forward (line 167) | def forward(self, x):
  class InternVLModelOutput (line 176) | class InternVLModelOutput(ModelOutput):
    method to_tuple (line 186) | def to_tuple(self) -> Tuple[Any]:
  class GatherLayer (line 195) | class GatherLayer(torch.autograd.Function):
    method forward (line 200) | def forward(ctx, input):
    method backward (line 207) | def backward(ctx, grads):
  class InternVLModel (line 215) | class InternVLModel(InternVLPreTrainedModel):
    method __init__ (line 219) | def __init__(self, config: InternVLConfig):
    method wrap_backbone_lora (line 261) | def wrap_backbone_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method wrap_qllama_lora (line 271) | def wrap_qllama_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
    method get_input_embeddings (line 282) | def get_input_embeddings(self):
    method set_input_embeddings (line 285) | def set_input_embeddings(self, value):
    method set_ou

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    "path": ".flake8",
    "chars": 218,
    "preview": "[flake8]\nignore = E501, F403, C901, W504, W605, E251, E122, E126, E127, E722, W503, E128, E741, E731, E701\nselect = E1, "
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  {
    "path": ".github/CONTRIBUTING.md",
    "chars": 11248,
    "preview": "## Contributing to InternLM\n\nWelcome to the InternLM community, all kinds of contributions are welcomed, including but n"
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  {
    "path": ".github/ISSUE_TEMPLATE/1-bug-report.yml",
    "chars": 2031,
    "preview": "name: 🐞 Bug report\ndescription: Create a report to help us reproduce and fix the bug\ntitle: \"[Bug] \"\nlabels: ['Bug']\n\nbo"
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    "path": ".github/ISSUE_TEMPLATE/2-feature-request.yml",
    "chars": 1172,
    "preview": "name: 🚀 Feature request\ndescription: Suggest an idea for this project\ntitle: \"[Feature] \"\n\nbody:\n- type: markdown\n  attr"
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    "path": ".github/ISSUE_TEMPLATE/3-documentation.yml",
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    "chars": 3242,
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  {
    "path": ".isort.cfg",
    "chars": 697,
    "preview": "[isort]\nline-length = 180\nmulti_line_output = 0\nextra_standard_library = setuptools\nknown_third_party = PIL,asynctest,ci"
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    "chars": 2167,
    "preview": "## 🛠️ Installation\n\n- Clone this repository:\n\n  ```bash\n  git clone https://github.com/OpenGVLab/InternVL.git\n  ```\n\n- C"
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    "path": "LICENSE",
    "chars": 1066,
    "preview": "MIT License\n\nCopyright (c) 2023 OpenGVLab\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\n"
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    "preview": "<div align=\"center\">\n\n# InternVL Family: Closing the Gap to Commercial Multimodal Models with Open-Source Suites —— A Pi"
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    "chars": 60886,
    "preview": "<div align=\"center\">\n\n# InternVL家族：通过开源组件缩小与商业多模态模型的差距 —— GPT-5的开源替代方案\n\n<div align=\"center\">\n  <img width=\"500\" alt=\"ima"
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  {
    "path": "classification/README.md",
    "chars": 10168,
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    "path": "classification/config.py",
    "chars": 10125,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2022 OpenGVLab\n# Licensed under Th"
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_224px_in1k_224_64gpu_imagenet_real.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v1_0_in1k_448_64gpu_imagenet_real.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v1_2_in1k_448_64gpu_imagenet_real.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenet_real.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v1_5_in1k_448_64gpu_imagenetv2.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_r.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_real.yaml",
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    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenet_sketch.yaml",
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  {
    "path": "classification/configs/linear_probing/linear_probing_intern_vit_6b_448px_v2_5_in1k_448_64gpu_imagenetv2.yaml",
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    "preview": "DATA:\n  IMG_ON_MEMORY: False\n  BATCH_SIZE: 16 # single GPU batch size\n  DATASET: 'imagenetv2'\n  TRANSFORM: 'build_transf"
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  {
    "path": "classification/dataset/__init__.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
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    "path": "classification/dataset/build.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
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    "path": "classification/dataset/cached_image_folder.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
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    "path": "classification/dataset/imagenet_a_r_indices.py",
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    "preview": "\"\"\"Code from https://github.com/baaivision/EVA/blob/master/EVA-02/asuka/imagenet_a_r_indices.py\nThanks to the authors of"
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  {
    "path": "classification/dataset/imagenet_real.py",
    "chars": 2025,
    "preview": "# --------------------------------------------------------\n# EVA: Exploring the Limits of Masked Visual Representation L"
  },
  {
    "path": "classification/dataset/imagenetv2.py",
    "chars": 2865,
    "preview": "\"\"\"Code from https://github.com/mlfoundations/wise-ft/blob/master/src/datasets/imagenetv2.py\nThanks to the authors of wi"
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  {
    "path": "classification/dataset/samplers.py",
    "chars": 3858,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "classification/dataset/zipreader.py",
    "chars": 3292,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "classification/ddp_hooks.py",
    "chars": 7618,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2022 OpenGVLab\n# Licensed under Th"
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    "path": "classification/gflops.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "classification/hf2pytorch.py",
    "chars": 2869,
    "preview": "import argparse\nimport os\n\nimport torch\nfrom safetensors.torch import load_file as safetensors_load_file\n\n# Parse comman"
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    "path": "classification/logger.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2022 OpenGVLab\n# Licensed under Th"
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    "path": "classification/lr_scheduler.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2022 OpenGVLab\n# Licensed under Th"
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  {
    "path": "classification/main.py",
    "chars": 30523,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
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  {
    "path": "classification/meta_data/22k_class_to_idx.json",
    "chars": 425711,
    "preview": "{\"n00004475\": 0, \"n00005787\": 1, \"n00006024\": 2, \"n00006484\": 3, \"n00007846\": 4, \"n00015388\": 5, \"n00017222\": 6, \"n00021"
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    "path": "classification/meta_data/imagenet_classes.json",
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    "path": "classification/meta_data/real.json",
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    "preview": "[[], [970, 795], [230, 231], [809], [516, 850], [57], [334], [700], [674], [332], [109], [286], [370], [757], [595], [14"
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  {
    "path": "classification/models/__init__.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
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    "path": "classification/models/build.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2024 OpenGVLab\n# Licensed under Th"
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  {
    "path": "classification/models/flash_attention.py",
    "chars": 3370,
    "preview": "import torch\nimport torch.nn as nn\nfrom einops import rearrange\n\ntry:  # v1\n    from flash_attn.flash_attn_interface imp"
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    "path": "classification/models/intern_vit_6b.py",
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    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
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    "path": "classification/optimizer.py",
    "chars": 5904,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2022 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "classification/train_in1k.sh",
    "chars": 613,
    "preview": "#!/usr/bin/env bash\n\nset -x\n\nPARTITION=$1\nJOB_NAME=$2\nCONFIG=$3\nGPUS=${GPUS:-8}\nGPUS_PER_NODE=${GPUS_PER_NODE:-8}\nCPUS_P"
  },
  {
    "path": "classification/utils.py",
    "chars": 15597,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2022 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "classification/work_dirs/intern_vit_6b_1k_224/log_rank0.txt",
    "chars": 535243,
    "preview": "[2023-11-09 22:22:39 intern_vit_6b_1k_224_cls_patch_sgd_lr0.1] (main.py 663): INFO Full config saved to work_dirs/intern"
  },
  {
    "path": "clip_benchmark/AUTHORS.rst",
    "chars": 122,
    "preview": "=======\nCredits\n=======\n\n* `Mehdi Cherti <https://github.com/mehdidc>`_\n* `Romain Beaumont <https://github.com/rom1504>`"
  },
  {
    "path": "clip_benchmark/CONTRIBUTING.rst",
    "chars": 3607,
    "preview": ".. highlight:: shell\n\n============\nContributing\n============\n\nContributions are welcome, and they are greatly appreciate"
  },
  {
    "path": "clip_benchmark/HISTORY.rst",
    "chars": 852,
    "preview": "## History\n\n### 1.4.0\n\n* Fix silent webdataset error-handling\n* Added support for wds/voc2007_multilabel\n* default to fl"
  },
  {
    "path": "clip_benchmark/LICENSE",
    "chars": 1070,
    "preview": "MIT License\n\nCopyright (c) 2022, Mehdi Cherti\n\nPermission is hereby granted, free of charge, to any person obtaining a c"
  },
  {
    "path": "clip_benchmark/MANIFEST.in",
    "chars": 289,
    "preview": "include AUTHORS.rst\ninclude CONTRIBUTING.rst\ninclude HISTORY.rst\ninclude LICENSE\ninclude README.rst\n\nrecursive-include t"
  },
  {
    "path": "clip_benchmark/Makefile",
    "chars": 2480,
    "preview": ".PHONY: clean clean-build clean-pyc clean-test coverage dist docs help install lint lint/flake8\n.DEFAULT_GOAL := help\n\nd"
  },
  {
    "path": "clip_benchmark/README.md",
    "chars": 58761,
    "preview": "# InternVL for Zero-Shot Image Classification & Image-Text Retrieval\n\nThis folder contains the implementation of InternV"
  },
  {
    "path": "clip_benchmark/benchmark/README.md",
    "chars": 1988,
    "preview": "# Benchmark\n\nthe benchmark results are available in [benchmark.csv](benchmark.csv).\nYou can visualize the results in the"
  },
  {
    "path": "clip_benchmark/benchmark/benchmark.csv",
    "chars": 68985,
    "preview": "acc1,acc5,mean_per_class_recall,dataset,model,pretrained,task,mean_average_precision,image_retrieval_recall@5,text_retri"
  },
  {
    "path": "clip_benchmark/benchmark/dataset_type.csv",
    "chars": 1026,
    "preview": "dataset,type\nimagenet1k,natural\nimagenetv2,natural\nimagenet-r,natural\nimagenet_sketch,specialized\nobjectnet,natural\nimag"
  },
  {
    "path": "clip_benchmark/benchmark/datasets.txt",
    "chars": 582,
    "preview": "mscoco_captions\nflickr8k\nflickr30k\nimagenet1k\nimagenetv2\nimagenet_sketch\nimagenet-a\nimagenet-r\nobjectnet\nfer2013\nvoc2007"
  },
  {
    "path": "clip_benchmark/benchmark/datasets_multilingual.txt",
    "chars": 326,
    "preview": "multilingual_mscoco_captions,es\nmultilingual_mscoco_captions,it\nmultilingual_mscoco_captions,ko\nmultilingual_mscoco_capt"
  },
  {
    "path": "clip_benchmark/benchmark/models.txt",
    "chars": 308,
    "preview": "ViT-B-32,openai\nViT-B-16,openai\nViT-L-14,openai\nViT-L-14-336,openai\nViT-B-32-quickgelu,laion400m_e32\nViT-B-32,laion2b_e1"
  },
  {
    "path": "clip_benchmark/benchmark/results.ipynb",
    "chars": 1892068,
    "preview": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"id\": \"b3edae65-ec1c-4318-b825-1ea20cea1f3c\",\n   \""
  },
  {
    "path": "clip_benchmark/benchmark/webdatasets.txt",
    "chars": 788,
    "preview": "wds/mscoco_captions\nwds/flickr8k\nwds/flickr30k\nwds/imagenet1k\nwds/imagenetv2\nwds/imagenet_sketch\nwds/imagenet-a\nwds/imag"
  },
  {
    "path": "clip_benchmark/clip_benchmark/__init__.py",
    "chars": 135,
    "preview": "\"\"\"Top-level package for CLIP Benchmark.\"\"\"\n\n__author__ = \"\"\"Mehdi Cherti\"\"\"\n__email__ = 'mehdicherti@gmail.com'\n__versi"
  },
  {
    "path": "clip_benchmark/clip_benchmark/cli.py",
    "chars": 16207,
    "preview": "\"\"\"Console script for clip_benchmark.\"\"\"\nimport argparse\nimport csv\nimport json\nimport os\nimport sys\nfrom copy import co"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/ar_classnames.json",
    "chars": 76069,
    "preview": "{\n  \"imagenet1k\": [\n    \"\\u0633\\u0645\\u0643 \\u0627\\u0644\\u062a\\u0646\\u0634\",\n    \"\\u0627\\u0644\\u0633\\u0645\\u0643\\u0629 \\"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/ar_zeroshot_classification_templates.json",
    "chars": 4623,
    "preview": "{\n  \"imagenet1k\": [\n    \"{c}\",\n    \"\\u0635\\u0648\\u0631\\u0629 \\u0633\\u064a\\u0626\\u0629 \\u0644\\u0640 {c}\",\n    \"\\u0635\\u06"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/birdsnap.py",
    "chars": 10006,
    "preview": "import concurrent.futures\nimport csv\nimport hashlib\nimport os\nfrom pathlib import Path\n\nimport torch\nfrom PIL import Ima"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/builder.py",
    "chars": 65146,
    "preview": "import json\nimport os\nimport sys\nimport warnings\nfrom subprocess import call\n\nimport torch\nfrom torch.utils.data import "
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/caltech101.py",
    "chars": 9151,
    "preview": "\"\"\"\nCode adapted from https://github.com/pytorch/vision/blob/main/torchvision/datasets/caltech.py\nModification of caltec"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/cn_classnames.json",
    "chars": 27709,
    "preview": "{\n  \"imagenet1k\": [\n    \"\\u4e01\\u9cb7\",\n    \"\\u91d1\\u9c7c\",\n    \"\\u5927\\u767d\\u9ca8\",\n    \"\\u864e\\u9ca8\",\n    \"\\u9524\\u5"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/cn_zeroshot_classification_templates.json",
    "chars": 3747,
    "preview": "{\n  \"imagenet1k\": [\n    \"{c}\\u7684\\u7167\\u7247\\u3002\",\n    \"\\u8d28\\u91cf\\u5dee\\u7684{c}\\u7684\\u7167\\u7247\\u3002\",\n    \"\\"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/cupl_prompts.json",
    "chars": 10172605,
    "preview": "{\n    \"imagenet1k\": {\n        \"tench\": [\n            \"A tench is a freshwater fish of the carp family.\",\n            \"A "
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/en_classnames.json",
    "chars": 32702,
    "preview": "{\n  \"flowers\": [\n    \"pink primrose\",\n    \"hard-leaved pocket orchid\",\n    \"canterbury bells\",\n    \"sweet pea\",\n    \"eng"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/en_zeroshot_classification_templates.json",
    "chars": 7927,
    "preview": "{\n  \"cifar10\": [\n    \"a photo of a {c}.\",\n    \"a blurry photo of a {c}.\",\n    \"a black and white photo of a {c}.\",\n    \""
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/flickr.py",
    "chars": 1820,
    "preview": "\"\"\"\nAdapted from https://github.com/pytorch/vision/blob/main/torchvision/datasets/flickr.py\nThanks to the authors of tor"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/imagenetv2.py",
    "chars": 4628,
    "preview": "\"\"\"\nCode from https://github.com/mlfoundations/wise-ft/blob/master/src/datasets/imagenetv2.py\nThanks to the authors of w"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/it_classnames.json",
    "chars": 23002,
    "preview": "{\n  \"imagenet1k\": [\n    \"una tinca\",\n    \"un pesce rosso\",\n    \"un grande squalo bianco\",\n    \"uno squalo tigre\",\n    \"u"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/it_zeroshot_classification_templates.json",
    "chars": 1479,
    "preview": "{\n  \"imagenet1k\": [\n    \"una brutta foto di {c}\",\n    \"una scultura di {c}\",\n    \"una foto di {c} difficilmente visibile"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/jp_classnames.json",
    "chars": 38852,
    "preview": "{\n  \"imagenet1k\": [\n    \"\\u30c6\\u30f3\\u30c1\",\n    \"\\u91d1\\u9b5a\",\n    \"\\u30db\\u30db\\u30b8\\u30ed\\u30b6\\u30e1\",\n    \"\\u30a"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/jp_zeroshot_classification_templates.json",
    "chars": 1714,
    "preview": "{\n  \"imagenet1k\": [\n    \"{c}\\u306e\\u60aa\\u3044\\u5199\\u771f\",\n    \"\\u591a\\u304f\\u306e{c}\\u306e\\u5199\\u771f\",\n    \"{c}\\u30"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/kitti.py",
    "chars": 7109,
    "preview": "# Copyright 2019 Google LLC.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this "
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/multilingual_mscoco.py",
    "chars": 3991,
    "preview": "import json\nimport os\nfrom subprocess import call\n\nfrom PIL import Image\nfrom torchvision.datasets import VisionDataset\n"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/objectnet.py",
    "chars": 2648,
    "preview": "\"\"\"\nCode adapted from https://github.com/mlfoundations/wise-ft/blob/master/src/datasets/objectnet.py\nThanks to the autho"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/tfds.py",
    "chars": 1939,
    "preview": "import torch\nfrom PIL import Image\n\n\ndef download_tfds_dataset(name, data_dir=None):\n    import tensorflow_datasets as t"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/tools.py",
    "chars": 651,
    "preview": "import re\n\n\ndef process_single_caption(caption, max_words=50):\n    caption = re.sub(r\"([.!\\\"()*#:;~])\", ' ', caption.low"
  },
  {
    "path": "clip_benchmark/clip_benchmark/datasets/voc2007.py",
    "chars": 8861,
    "preview": "# Code from https://github.com/SsnL/dataset-distillation/blob/master/datasets/pascal_voc.py , thanks to the authors\n\"\"\"D"
  },
  {
    "path": "clip_benchmark/clip_benchmark/metrics/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "clip_benchmark/clip_benchmark/metrics/linear_probe.py",
    "chars": 9494,
    "preview": "import os\nimport time\nfrom contextlib import suppress\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nf"
  },
  {
    "path": "clip_benchmark/clip_benchmark/metrics/mscoco_generative.py",
    "chars": 1261,
    "preview": "import json\n\nfrom open_clip.tokenizer import _tokenizer\nfrom pycocoevalcap.eval import COCOEvalCap\nfrom tqdm.auto import"
  },
  {
    "path": "clip_benchmark/clip_benchmark/metrics/zeroshot_classification.py",
    "chars": 7564,
    "preview": "\"\"\"\nCode adapated from https://github.com/mlfoundations/open_clip/blob/main/src/training/zero_shot.py\nThanks to the auth"
  },
  {
    "path": "clip_benchmark/clip_benchmark/metrics/zeroshot_retrieval.py",
    "chars": 5662,
    "preview": "from contextlib import suppress\n\nimport torch\nimport torch.nn.functional as F\nfrom tqdm import tqdm\n\n\ndef evaluate(model"
  },
  {
    "path": "clip_benchmark/clip_benchmark/model_collection.py",
    "chars": 935,
    "preview": "import open_clip\n\n\ndef get_model_collection_from_file(path):\n    return [l.strip().split(',') for l in open(path).readli"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/__init__.py",
    "chars": 761,
    "preview": "from typing import Union\n\nimport torch\n\nfrom .internvl import load_internvl\nfrom .japanese_clip import load_japanese_cli"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/intern_vit_6b/configuration_intern_vit.py",
    "chars": 5478,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/intern_vit_6b/flash_attention.py",
    "chars": 3370,
    "preview": "import torch\nimport torch.nn as nn\nfrom einops import rearrange\n\ntry:  # v1\n    from flash_attn.flash_attn_interface imp"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/intern_vit_6b/modeling_intern_vit.py",
    "chars": 13993,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl.py",
    "chars": 1238,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/__init__.py",
    "chars": 2769,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/chinese_alpaca_lora_7b/config.json",
    "chars": 538,
    "preview": "{\n  \"architectures\": [\n    \"LlamaForCausalLM\"\n  ],\n  \"bos_token_id\": 1,\n  \"eos_token_id\": 2,\n  \"hidden_act\": \"silu\",\n  \""
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/chinese_alpaca_lora_7b/generation_config.json",
    "chars": 137,
    "preview": "{\n  \"_from_model_config\": true,\n  \"bos_token_id\": 1,\n  \"eos_token_id\": 2,\n  \"pad_token_id\": 0,\n  \"transformers_version\":"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/chinese_alpaca_lora_7b/pytorch_model.bin.index.json",
    "chars": 26788,
    "preview": "{\n  \"metadata\": {\n    \"total_size\": 13770997760\n  },\n  \"weight_map\": {\n    \"lm_head.weight\": \"pytorch_model-00002-of-000"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/chinese_alpaca_lora_7b/special_tokens_map.json",
    "chars": 96,
    "preview": "{\n  \"bos_token\": \"<s>\",\n  \"eos_token\": \"</s>\",\n  \"pad_token\": \"[PAD]\",\n  \"unk_token\": \"<unk>\"\n}\n"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/chinese_alpaca_lora_7b/tokenizer_config.json",
    "chars": 806,
    "preview": "{\n  \"add_bos_token\": true,\n  \"add_eos_token\": false,\n  \"bos_token\": {\n    \"__type\": \"AddedToken\",\n    \"content\": \"<s>\",\n"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/flash_attention.py",
    "chars": 3459,
    "preview": "# https://github.com/Dao-AILab/flash-attention/blob/v0.2.8/flash_attn/flash_attention.py\nimport torch\nimport torch.nn as"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_c_pytorch/internvl_c.py",
    "chars": 16066,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_huggingface/__init__.py",
    "chars": 3596,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_huggingface/configuration_intern_vit.py",
    "chars": 5478,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_huggingface/configuration_internvl.py",
    "chars": 4802,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_huggingface/flash_attention.py",
    "chars": 3459,
    "preview": "# https://github.com/Dao-AILab/flash-attention/blob/v0.2.8/flash_attn/flash_attention.py\nimport torch\nimport torch.nn as"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_huggingface/modeling_intern_vit.py",
    "chars": 13993,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_huggingface/modeling_internvl.py",
    "chars": 21163,
    "preview": "# --------------------------------------------------------\n# InternVL\n# Copyright (c) 2023 OpenGVLab\n# Licensed under Th"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/internvl_huggingface/modeling_qllama.py",
    "chars": 48012,
    "preview": "# Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved.\n#\n# This code is based on EleutherAI's G"
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/japanese_clip.py",
    "chars": 1710,
    "preview": "from typing import Dict\n\nimport torch\n\n\nclass DictTensor:\n    \"\"\"\n    enable to do `tokenizer(texts).to(device)`\n    \"\"\""
  },
  {
    "path": "clip_benchmark/clip_benchmark/models/open_clip.py",
    "chars": 410,
    "preview": "import open_clip\n\n\ndef load_open_clip(model_name: str = 'ViT-B-32-quickgelu', pretrained: str = 'laion400m_e32', cache_d"
  },
  {
    "path": "clip_benchmark/clip_benchmark/webdataset_builder.py",
    "chars": 11155,
    "preview": "# Convert CLIP_benchmark datasets to webdataset format\n\nimport argparse\nimport io\nimport os\nimport sys\n\nimport torch\nimp"
  },
  {
    "path": "clip_benchmark/data/birdsnap/test_images_valid.txt",
    "chars": 51030,
    "preview": "path\nCoopers_Hawk/0561.jpg\nCoopers_Hawk/0629.jpg\nCoopers_Hawk/0717.jpg\nCoopers_Hawk/1847.jpg\nNorthern_Goshawk/2629.jpg\nN"
  },
  {
    "path": "clip_benchmark/data/flickr30k/flickr30k_cn_test.txt",
    "chars": 179306,
    "preview": "image,caption\n1009692167.jpg,在警车前，一条训练有素的警犬坐在它的警官身旁。\n1009692167.jpg,一名警察站着，身边有一只德国牧羊犬\n1009692167.jpg,一位安保人员带着他的狗正在寻找某些东西"
  },
  {
    "path": "clip_benchmark/data/mscoco_captions/coco-cn_test.json",
    "chars": 231071,
    "preview": "{\"images\": [{\"id\": 573854, \"file_name\": \"train2014/COCO_train2014_000000573854.jpg\"}, {\"id\": 412975, \"file_name\": \"val20"
  },
  {
    "path": "clip_benchmark/probe_benchmark/PROBES.md",
    "chars": 565,
    "preview": "Steps to run.\n\n1. Navigate to `CLIP_benchmark`.\n2. Run `export PYTHONPATH=$PWD`.\n3. (Optional) To re-run the experiments"
  },
  {
    "path": "clip_benchmark/probe_benchmark/build_df_scaling_experiments.py",
    "chars": 5292,
    "preview": "import json\nimport os\n\nimport pandas as pd\n\nif __name__ == '__main__':\n\n    compute_df = pd.read_csv('probe_benchmark/cl"
  },
  {
    "path": "clip_benchmark/probe_benchmark/clip_table_2.csv",
    "chars": 2063,
    "preview": "model,image_size,image_width,text_width,embed_dim,gmacs,macts,mparams,image_gmacs,image_macts,image_mparams,text_gmacs,t"
  },
  {
    "path": "clip_benchmark/probe_benchmark/generate_table.py",
    "chars": 2383,
    "preview": "import pandas as pd\n\n# make a new version of vtab\n\nif __name__ == '__main__':\n    df_full = pd.read_json('probe_benchmar"
  },
  {
    "path": "clip_benchmark/probe_benchmark/laion5b_fewshot_experiments.py",
    "chars": 2376,
    "preview": "import os\n\nfrom clip_benchmark.cli import get_parser_args, run\n\n# /private/home/mitchellw/miniconda3/envs/cb/bin/python "
  },
  {
    "path": "clip_benchmark/probe_benchmark/openclip_results.csv",
    "chars": 274304,
    "preview": "model_fullname,arch,samples_seen,gmacs_total,gmacs,upstream_dataset,downstream_dataset,acc1,acc5,mean_per_class_recall,i"
  },
  {
    "path": "clip_benchmark/probe_benchmark/process_vtab.py",
    "chars": 1440,
    "preview": "import json\n\nimport pandas as pd\n\n# make a new version of vtab\n\nif __name__ == '__main__':\n    df = pd.read_json('probe_"
  },
  {
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    "chars": 2818083,
    "preview": "[\n  {\n    \"k\": 10,\n    \"lr\": 0.1,\n    \"bs\": 256,\n    \"epochs\": 10,\n    \"model\": \"ViT-B-32\",\n    \"pretrained\": \"laion400m"
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    "path": "clip_benchmark/probe_benchmark/scaling_experiment_data_vtab.json",
    "chars": 3043,
    "preview": "[\n  {\n    \"dataset\": \"vtab\",\n    \"lp_acc1\": 0.7272385796110142,\n    \"fewshot_k\": -1,\n    \"model\": \"ViT-B-16\",\n    \"pretr"
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]

// ... and 664 more files (download for full content)