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Functions354 in github.com/TinyLLaVA/TinyLLaVA_Factory

⨍ Functions 354◇ Types & classes 78
↓ 16 callersMethod__init__
(self, config)
tinyllava/model/connector/qformer.py:13
↓ 16 callersMethodload
(self, model, model_args={})
tinyllava/training_recipe/base.py:137
↓ 10 callersMethodadd_message
(self, question, answer=None)
tinyllava/utils/message.py:14
↓ 9 callersMethodto_gradio_chatbot
(self)
tinyllava/utils/message.py:36
↓ 8 callersMethod__init__
(self, config: OpenELMConfig)
tinyllava/model/llm/openelm.py:831
↓ 8 callersMethodapply
(self, **kwargs)
tinyllava/data/template/formatter.py:13
↓ 8 callersFunctionload_pretrained_model
(model_name_or_path, load_type='hf', load_8bit=False, load_4bit=False, device_map="auto",
tinyllava/model/load_model.py:18
↓ 8 callersMethodtokenizer_image_token
(cls, prompt, tokenizer, image_token_index=IMAGE_TOKEN_INDEX, return_tensors=None)
tinyllava/data/template/base.py:137
↓ 7 callersFunctiondisable_torch_init
Disable the redundant torch default initialization to accelerate model creation.
tinyllava/utils/eval_utils.py:9
↓ 7 callersMethodgenerate
( self, inputs: Optional[torch.Tensor] = None, images: Optional[torch.Tensor] = None,
tinyllava/model/modeling_tinyllava.py:155
↓ 7 callersMethodtranspose_for_scores
(self, x)
tinyllava/model/connector/qformer.py:227
↓ 6 callersFunctionget_peft_state_non_lora_maybe_zero_3
(named_params, require_grad_only=True)
tinyllava/utils/train_utils.py:66
↓ 5 callersFunctionimport_modules
(models_dir, namespace)
tinyllava/utils/import_module.py:4
↓ 5 callersFunctionlog
(*args)
tinyllava/utils/logging.py:40
↓ 4 callersMethodencode
1. get list form messages(conversations:[{from:human, value:message}, {from:gpt, value:message}]) ===> human_list, value_list
tinyllava/data/template/base.py:22
↓ 3 callersMethodget_input_embeddings
(self)
tinyllava/model/modeling_tinyllava.py:78
↓ 3 callersFunctionget_length_grouped_indices
(lengths, batch_size, world_size, generator=None, merge=True)
tinyllava/train/tinyllava_trainer.py:75
↓ 3 callersFunctionget_state_maybe_zero_3
(named_params, keys_to_match=[''], require_grad_only=True)
tinyllava/utils/train_utils.py:74
↓ 3 callersFunctionget_value_from_kwargs
(kwargs, name)
tinyllava/model/modeling_tinyllava.py:18
↓ 3 callersFunctionload_base_ckp_for_lora
(ckp_path)
tinyllava/model/load_model.py:9
↓ 3 callersMethodload_connector
(self, **kwargs)
tinyllava/model/modeling_tinyllava.py:378
↓ 3 callersMethodload_vision_tower
(self, **kwargs)
tinyllava/model/modeling_tinyllava.py:373
↓ 3 callersFunctionmake_divisible
This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by the divisor It ca
tinyllava/model/llm/openelm.py:42
↓ 3 callersFunctionmaybe_zero_3
(param, ignore_status=False, name=None)
tinyllava/utils/train_utils.py:28
↓ 3 callersMethodsave
(self, model, trainer)
tinyllava/training_recipe/base.py:95
↓ 2 callersFunctionLLMFactory
(model_name_or_path)
tinyllava/model/llm/__init__.py:8
↓ 2 callersFunctionTrainingRecipeFactory
(training_recipe)
tinyllava/training_recipe/__init__.py:8
↓ 2 callersMethod__init__
(self, config)
tinyllava/model/connector/resampler.py:13
↓ 2 callersFunction_apply_rotary_pos_emb
(x: Tensor, pos_sin: Tensor, pos_cos: Tensor)
tinyllava/model/llm/openelm.py:416
↓ 2 callersMethod_compute_sin_cos_embeddings
Compute sine and cos embeddings. Args: key_len: Number of tokens in the key embeddings in the transformer model.
tinyllava/model/llm/openelm.py:453
↓ 2 callersMethod_load_text_config
(self, text_config=None)
tinyllava/model/configuration_tinyllava.py:96
↓ 2 callersMethod_load_vision_config
(self, vision_config=None)
tinyllava/model/configuration_tinyllava.py:110
↓ 2 callersFunctioncompute_heads
Compute the number of heads. Args: model_dim: Model dimension. head_dim: Head dimension. Returns: An integer denoting
tinyllava/model/llm/openelm.py:68
↓ 2 callersFunctioneval_model
(args)
tinyllava/eval/run_tiny_llava.py:37
↓ 2 callersFunctioneval_single
(annotation_file, result_file)
tinyllava/eval/eval_textvqa.py:35
↓ 2 callersMethodextra_repr
(self)
tinyllava/model/llm/openelm.py:379
↓ 2 callersFunctionfind_all_linear_names
(model, skip_keywords=['connector', 'vision_tower'])
tinyllava/utils/train_utils.py:82
↓ 2 callersMethodget_extended_attention_mask
Makes broadcastable attention and causal masks so that future and masked tokens are ignored. Arguments: attention_mask (
tinyllava/model/connector/qformer.py:779
↓ 2 callersFunctionget_peft_state_maybe_zero_3
(named_params, bias)
tinyllava/utils/train_utils.py:41
↓ 2 callersFunctionget_pred_idx
Get the index (e.g. 2) from the prediction (e.g. 'C')
tinyllava/eval/eval_science_qa.py:28
↓ 2 callersMethodload_llm
(self, **kwargs)
tinyllava/model/modeling_tinyllava.py:354
↓ 2 callersMethodload_model
(self, **kwargs)
tinyllava/model/connector/base.py:12
↓ 2 callersFunctionlog_trainable_params
(model)
tinyllava/utils/logging.py:49
↓ 2 callersFunctionlogger_setting
(save_dir=None)
tinyllava/utils/logging.py:15
↓ 2 callersFunctionmake_supervised_data_module
Make dataset and collator for supervised fine-tuning.
tinyllava/data/dataset.py:119
↓ 2 callersMethodprepare_inputs_labels_for_multimodal
( self, input_ids, position_ids, attention_mask, past_key_values, labels, images, image_sizes=
tinyllava/model/modeling_tinyllava.py:218
↓ 2 callersFunctionselect_best_resolution
Selects the best resolution from a list of possible resolutions based on the original size. Args: original_size (tuple): The origina
tinyllava/utils/data_utils.py:24
↓ 1 callersFunctionConnectorFactory
(connector_name)
tinyllava/model/connector/__init__.py:8
↓ 1 callersFunctionFeedForward
(dim, mult=4)
tinyllava/model/connector/resampler.py:58
↓ 1 callersFunctionTemplateFactory
(version)
tinyllava/data/template/__init__.py:10
↓ 1 callersFunctionVisionTowerFactory
(vision_tower_name)
tinyllava/model/vision_tower/__init__.py:8
↓ 1 callersMethod__init__
(self, config)
tinyllava/model/connector/mof_mlp.py:11
↓ 1 callersMethod__init__
(self, cfg)
tinyllava/model/vision_tower/mof.py:14
↓ 1 callersMethod__post_init__
(self)
tinyllava/model/llm/openelm.py:257
↓ 1 callersMethod_compute_answer_scores
compute the accuracy (soft score) of human answers
tinyllava/eval/m4c_evaluator.py:225
↓ 1 callersMethod_connector_tune_type_setting
(self, model)
tinyllava/training_recipe/base.py:78
↓ 1 callersMethod_get_list_from_message
messages ====> [{from:human, value:message}, {from:gpt, value:message}]
tinyllava/data/template/base.py:46
↓ 1 callersMethod_llm_tune_type_setting
(self, model)
tinyllava/training_recipe/base.py:40
↓ 1 callersFunction_load_connector_settings
(model_arguments)
tinyllava/train/train.py:43
↓ 1 callersFunction_load_llm_settings
(model_arguments)
tinyllava/train/train.py:29
↓ 1 callersMethod_load_model
(self, vision_tower_name, **kwargs)
tinyllava/model/vision_tower/base.py:30
↓ 1 callersFunction_load_vision_settings
(model_arguments)
tinyllava/train/train.py:36
↓ 1 callersMethod_make_masks
(self, labels, tokenizer, sep, eos_token_length, rounds)
tinyllava/data/template/base.py:120
↓ 1 callersMethod_norm
Apply the OpenELMRMSNorm normalization to the input tensor. Args: x (torch.Tensor): The input tensor. Returns:
tinyllava/model/llm/openelm.py:358
↓ 1 callersMethod_prompt
( self, question_list, answer_list, )
tinyllava/data/template/base.py:78
↓ 1 callersMethod_register
(self, llm_layers_index)
tinyllava_visualizer/tinyllava_visualizer.py:133
↓ 1 callersFunction_rotate_half
(x: Tensor)
tinyllava/model/llm/openelm.py:411
↓ 1 callersMethod_update_causal_mask
(self, attention_mask, input_tensor)
tinyllava/model/llm/openelm.py:1037
↓ 1 callersMethod_vision_tower_tune_type_setting
(self, model)
tinyllava/training_recipe/base.py:50
↓ 1 callersMethodadd_args
(self, model_args)
tinyllava/training_recipe/base.py:23
↓ 1 callersMethodadd_image
(self, image, index=0)
tinyllava/utils/message.py:22
↓ 1 callersFunctionbuild_demo
()
tinyllava/serve/app.py:206
↓ 1 callersMethodcall_for_batch
(self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs)
tinyllava/utils/eval_utils.py:31
↓ 1 callersFunctionconvert_legecy_config_to_tinyllavaconfig
(old_config_path)
tinyllava/model/convert_legecy_weights_to_tinyllavafactory.py:29
↓ 1 callersFunctionconvert_state_dict_to_tinyllavafactory
(old_state_dict_path)
tinyllava/model/convert_legecy_weights_to_tinyllavafactory.py:56
↓ 1 callersFunctioncreate_data_loader
(questions, image_folder, text_processor, image_processor, batch_size=1, num_workers=4)
tinyllava/eval/model_vqa_loader.py:68
↓ 1 callersFunctioncreate_data_loader
(questions, image_folder, text_processor, image_processor, batch_size=1, num_workers=4)
tinyllava/eval/model_vqa_pope.py:68
↓ 1 callersFunctiondivide_to_patches
Divides an image into patches of a specified size. Args: image (PIL.Image.Image): The input image. patch_size (int): The siz
tinyllava/utils/data_utils.py:54
↓ 1 callersMethodencode_images
(self, images)
tinyllava/model/modeling_tinyllava.py:194
↓ 1 callersFunctioneval_model
(args)
scripts/convert_answer_to_mmmu.py:6
↓ 1 callersFunctioneval_model
(args)
tinyllava/eval/model_vqa_loader.py:75
↓ 1 callersFunctioneval_model
(args)
tinyllava/eval/model_vqa_mmmu.py:84
↓ 1 callersFunctioneval_model
(args)
tinyllava/eval/model_vqa_science.py:27
↓ 1 callersFunctioneval_model
(args)
tinyllava/eval/model_vqa_pope.py:75
↓ 1 callersFunctioneval_model
(args)
tinyllava/eval/model_vqa.py:27
↓ 1 callersFunctioneval_pope
(answers, label_file)
tinyllava/eval/eval_pope.py:5
↓ 1 callersMethodeval_pred_list
(self, pred_list)
tinyllava/eval/m4c_evaluator.py:248
↓ 1 callersMethodexpand2square
(cls, pil_img, background_color)
tinyllava/data/image_preprocess.py:29
↓ 1 callersFunctionextract_max_values_and_indices
(tensor, k)
tinyllava_visualizer/tinyllava_visualizer.py:35
↓ 1 callersFunctiongenerate_square_subsequent_mask
(sz)
tinyllava_visualizer/tinyllava_visualizer.py:62
↓ 1 callersFunctiongenerate_word_images
(tokenizer, top_words_tensor, num, input_ids, embed_tokens, output_dir)
tinyllava_visualizer/tinyllava_visualizer.py:68
↓ 1 callersFunctiongenerate_word_images_before
(tokenizer, input_ids, tensor, num, top_words_tensor, output_dir)
tinyllava_visualizer/tinyllava_visualizer.py:86
↓ 1 callersMethodget_anls
(self, s1, s2)
tinyllava/eval/m4c_evaluator.py:282
↓ 1 callersFunctionget_args
()
tinyllava/eval/eval_textvqa.py:9
↓ 1 callersFunctionget_args
()
tinyllava/eval/eval_science_qa.py:8
↓ 1 callersFunctionget_chunk
(lst, n, k)
tinyllava/eval/model_vqa_loader.py:26
↓ 1 callersFunctionget_chunk
(lst, n, k)
tinyllava/eval/model_vqa_mmmu.py:24
↓ 1 callersFunctionget_chunk
(lst, n, k)
tinyllava/eval/model_vqa_science.py:22
↓ 1 callersFunctionget_chunk
(lst, n, k)
tinyllava/eval/model_vqa_pope.py:26
↓ 1 callersFunctionget_chunk
(lst, n, k)
tinyllava/eval/model_vqa.py:22
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