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Functions1,650 in github.com/VITA-MLLM/VITA

↓ 1 callersMethodload_pretrained_model
(self, model_path, load_8bit=False, load_4bit=False, revision='main')
VLMEvalKit/vlmeval/vlm/transcore_m.py:15
↓ 1 callersFunctionload_state_dict
( checkpoint_path: str, map_location: str = "cpu", model_key: str = "model|module|state_dict",
vita/model/multimodal_encoder/eva_clip/eva_vit.py:814
↓ 1 callersMethodload_vad
(self)
web_demo/wakeup_and_vad/wakeup_and_vad.py:151
↓ 1 callersMethodload_video
(self, video_path, num_segments=8, resolution=336)
VLMEvalKit/vlmeval/vlm/video_llm/pllava.py:49
↓ 1 callersMethodload_video
(self, video_path, max_frames_num)
VLMEvalKit/vlmeval/vlm/llava/llava.py:503
↓ 1 callersFunctionls
(dirname='.', match=[], mode='all', level=1)
VLMEvalKit/vlmeval/smp/file.py:211
↓ 1 callersFunctionmain
(args)
videomme/yt_video_inference_qa.py:260
↓ 1 callersFunctionmain
(args)
videomme/yt_video_inference_qa_imgs.py:160
↓ 1 callersFunctionmain
()
data_tools/mmco_collect.py:21
↓ 1 callersFunctionmain
()
VLMEvalKit/run.py:42
↓ 1 callersFunctionmain
(model_path)
web_demo/web_ability_demo.py:494
↓ 1 callersFunctionmake_pad_mask
Make mask tensor containing indices of padded part. See description of make_non_pad_mask. Args: lengths (torch.Tensor): Batch of len
vita/model/vita_tts/masks.py:125
↓ 1 callersFunctionmake_pad_mask
(lengths: torch.Tensor, max_len: int = 0)
vita/model/multimodal_encoder/whale/utils.py:78
↓ 1 callersFunctionmake_shared_position_ids
(cur_v_start_end, cur_len, shared_v_pid_stride)
vita/model/vita_arch.py:628
↓ 1 callersFunctionmake_supervised_data_module
Make dataset and collator for supervised fine-tuning.
vita/util/data_utils_video_audio_neg_patch.py:1475
↓ 1 callersFunctionmaybe_zero_3
(param, ignore_status=False, name=None)
vita/train/vita_trainer.py:17
↓ 1 callersFunctionmerge_chessboard
x: b * c * h * w Assuming x contains num_split**2 sub-squares concatenated along batch dimension, merge the sub-squares back to the original
vita/util/s2wrapper/utils.py:30
↓ 1 callersFunctionmerge_consecutive_tuples
(tuples_list)
vita/model/vita_arch.py:605
↓ 1 callersFunctionmerge_current_and_history
( global_history, current_request, skip_history_vision=False, move_image_token
web_demo/server.py:631
↓ 1 callersFunctionmerge_lora
(args)
script/merge_lora_weights.py:8
↓ 1 callersFunctionmerge_txt_files
(input_files, output_file)
data_tools/merge_txt.py:3
↓ 1 callersMethodmessage_to_prompt_embs
(self, message, dataset=None)
VLMEvalKit/vlmeval/vlm/xcomposer/xcomposer.py:81
↓ 1 callersMethodmessage_to_promptimg
(self, message, dataset=None)
VLMEvalKit/vlmeval/api/base.py:243
↓ 1 callersMethodmessage_to_promptimg
(self, message, dataset=None)
VLMEvalKit/vlmeval/api/sensechat_vision.py:157
↓ 1 callersFunctionmwlines
(lines, fname)
VLMEvalKit/vlmeval/smp/file.py:256
↓ 1 callersMethodoutput_process
(self, answer)
VLMEvalKit/vlmeval/vlm/mantis.py:127
↓ 1 callersMethodoutput_process
(self, answer)
VLMEvalKit/vlmeval/vlm/llava/llava.py:241
↓ 1 callersFunctionpadding_336
(b)
VLMEvalKit/vlmeval/vlm/xcomposer/xcomposer2_4KHD.py:14
↓ 1 callersFunctionpadding_560
(b)
VLMEvalKit/vlmeval/vlm/xcomposer/xcomposer2d5.py:16
↓ 1 callersFunctionparse_args
()
videomme/yt_video_inference_qa.py:71
↓ 1 callersFunctionparse_args
()
videomme/parse_answer.py:67
↓ 1 callersFunctionparse_args
()
videomme/yt_video_inference_qa_imgs.py:72
↓ 1 callersFunctionparse_args
()
VLMEvalKit/run.py:13
↓ 1 callersFunctionparse_args
()
VLMEvalKit/scripts/summarize.py:65
↓ 1 callersFunctionparse_line
Parse information from a line in a requirements text file.
VLMEvalKit/setup.py:24
↓ 1 callersFunctionparse_requirements
Parse the package dependencies listed in a requirements file but strips specific versioning information. Args: fname (str): path to r
VLMEvalKit/setup.py:7
↓ 1 callersFunctionparse_score
(review)
VLMEvalKit/vlmeval/dataset/utils/llavabench.py:16
↓ 1 callersMethodpixel_shuffle
(self, x, scale_factor=0.5)
vita/model/multimodal_encoder/internvit/internvit_encoder.py:41
↓ 1 callersMethodpixel_shuffle
(self, x, scale_factor=0.5)
web_demo/vllm_tools/vllm_file/qwen2.py:935
↓ 1 callersMethodpost_build
(self, dataset)
VLMEvalKit/vlmeval/dataset/image_base.py:139
↓ 1 callersMethodpost_build
(self, dataset)
VLMEvalKit/vlmeval/dataset/text_base.py:71
↓ 1 callersMethodpredict
(self, audio: torch.Tensor)
web_demo/wakeup_and_vad/wakeup_and_vad.py:175
↓ 1 callersFunctionprefetch_answer
(item)
VLMEvalKit/vlmeval/dataset/utils/multiple_choice.py:232
↓ 1 callersMethodprepare_dataset
(self, dataset)
VLMEvalKit/vlmeval/dataset/video_base.py:83
↓ 1 callersFunctionprepare_file
(file_name)
VLMEvalKit/scripts/mmb_eval_gradio.py:18
↓ 1 callersMethodprepare_inputs
(self, message)
VLMEvalKit/vlmeval/vlm/parrot.py:196
↓ 1 callersMethodprepare_inputs
(self, message)
VLMEvalKit/vlmeval/vlm/ovis.py:113
↓ 1 callersMethodprepare_inputs
(self, message)
VLMEvalKit/vlmeval/vlm/deepseek_vl.py:39
↓ 1 callersMethodprepare_inputs
(self, inputs)
VLMEvalKit/vlmeval/api/claude.py:71
↓ 1 callersMethodprepare_inputs
(self, inputs)
VLMEvalKit/vlmeval/api/hunyuan.py:87
↓ 1 callersMethodprepare_inputs
(self, inputs)
VLMEvalKit/vlmeval/api/gpt.py:153
↓ 1 callersMethodprepare_inputs
(self, inputs)
VLMEvalKit/vlmeval/api/cloudwalk.py:51
↓ 1 callersMethodprepare_inputs
(self, inputs)
VLMEvalKit/vlmeval/api/qwen_vl_api.py:56
↓ 1 callersMethodprepare_inputs_for_generation_original
( self, input_ids, past_key_values=None, attention_mask=None, inputs_e
vita/model/language_model/vita_mixtral.py:292
↓ 1 callersMethodprepare_texts
(self, texts, conv_temp)
VLMEvalKit/vlmeval/vlm/vxverse.py:122
↓ 1 callersMethodprepare_tsv
(self, url, file_md5=None)
VLMEvalKit/vlmeval/dataset/image_base.py:77
↓ 1 callersMethodprepare_tsv
(self, url, file_md5=None)
VLMEvalKit/vlmeval/dataset/text_base.py:29
↓ 1 callersMethodpreproc_image
(self, fname)
VLMEvalKit/vlmeval/vlm/mplug_owl3.py:77
↓ 1 callersFunctionpreprocess_mixtral_two
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_patch.py:136
↓ 1 callersFunctionpreprocess_mixtral_two
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_patch.py:270
↓ 1 callersFunctionpreprocess_mixtral_two
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_patch_fo.py:268
↓ 1 callersFunctionpreprocess_mixtral_two
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_patch_audio.py:145
↓ 1 callersFunctionpreprocess_mixtral_two
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_frameCat.py:261
↓ 1 callersFunctionpreprocess_mixtral_two
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_patch_sf.py:136
↓ 1 callersFunctionpreprocess_mixtral_zh
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_frameCat.py:135
↓ 1 callersFunctionpreprocess_mixtral_zh
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio.py:107
↓ 1 callersFunctionpreprocess_nemo
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_patch.py:265
↓ 1 callersFunctionpreprocess_nemo
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_patch.py:401
↓ 1 callersFunctionpreprocess_nemo
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_patch_fo.py:399
↓ 1 callersFunctionpreprocess_nemo
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_patch_audio.py:274
↓ 1 callersFunctionpreprocess_nemo
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_patch_sf.py:265
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
vita/util/data_utils_video_audio_patch.py:514
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
vita/util/data_utils_video_audio_neg_patch.py:655
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
vita/util/data_utils_video_audio_neg_patch_fo.py:653
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
vita/util/data_utils_video_patch_audio.py:522
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
vita/util/data_utils_video_audio_neg_frameCat.py:390
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
vita/util/data_utils_video_audio.py:226
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
vita/util/data_utils_video_audio_patch_sf.py:514
↓ 1 callersFunctionpreprocess_qwen2p5_instruct
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_patch.py:388
↓ 1 callersFunctionpreprocess_qwen2p5_instruct
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_patch.py:526
↓ 1 callersFunctionpreprocess_qwen2p5_instruct
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_neg_patch_fo.py:524
↓ 1 callersFunctionpreprocess_qwen2p5_instruct
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_patch_audio.py:397
↓ 1 callersFunctionpreprocess_qwen2p5_instruct
( sources, tokenizer: transformers.PreTrainedTokenizer, has_image: bool = False, has_audio: bo
vita/util/data_utils_video_audio_patch_sf.py:388
↓ 1 callersMethodqa_template
(self, data)
VLMEvalKit/vlmeval/dataset/mvbench.py:257
↓ 1 callersMethodqa_template
(self, data)
VLMEvalKit/vlmeval/dataset/mvbench.py:463
↓ 1 callersMethodqa_template
(self, data)
VLMEvalKit/vlmeval/vlm/video_llm/videochat2.py:353
↓ 1 callersFunctionrank0_print
(*args)
vita/train/train.py:39
↓ 1 callersMethodread_video
(self, video_path, bound=None)
VLMEvalKit/vlmeval/dataset/mvbench.py:484
↓ 1 callersFunctionread_video_pyav
(container, indices)
VLMEvalKit/vlmeval/vlm/video_llm/video_llava.py:11
↓ 1 callersMethodrecognize
( self, speech: torch.Tensor, speech_lengths: torch.Tensor, extra_inputs: Opti
vita/model/vita_tts/audioLLM.py:247
↓ 1 callersFunctionreformat_acc
(acc)
VLMEvalKit/scripts/mmb_eval_gradio.py:55
↓ 1 callersFunctionrelaxed_correctness
Calculates relaxed correctness. The correctness tolerates certain error ratio defined by max_relative_change. See https://arxiv.org/pdf/2203.
VLMEvalKit/vlmeval/dataset/utils/vqa_eval.py:172
↓ 1 callersFunctionremove_special_tokens
(input_str)
web_demo/server.py:468
↓ 1 callersFunctionrepeat
Repeat module N times. :param int N: repeat time :param function fn: function to generate module :return: repeated modules :rtype: Mu
vita/model/vita_tts/encoder/transformer.py:17
↓ 1 callersFunctionreplace_equation
(sentence)
web_demo/web_ability_demo.py:50
↓ 1 callersFunctionreplace_equation
(sentence)
web_demo/server.py:475
↓ 1 callersMethodreport_acc_by_groups
(self, df, group_column)
VLMEvalKit/vlmeval/dataset/image_mcq.py:390
↓ 1 callersFunctionrescale_img
(img, tgt=None)
VLMEvalKit/vlmeval/smp/vlm.py:15
↓ 1 callersMethodrobust_json_load
(s)
VLMEvalKit/vlmeval/dataset/mmbench_video.py:150
↓ 1 callersFunctionrough_filter
(answer_text)
VLMEvalKit/vlmeval/dataset/vcr.py:40
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