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Functions1,412 in github.com/Zhenhao-Zhang/OpenHOI

⨍ Functions 1,412◇ Types & classes 217↳ Endpoints 9
↓ 1 callersMethodget_visual_embs
(self, point)
HOIAffordanceMLLM/llava/model/language_model/affordancellm.py:777
↓ 1 callersFunctiongpt_get_average_score
(question, question_type, answer_model, answer_label, model="gpt-3.5-turbo", times=5)
HOIAffordanceMLLM/llava/eval/gpt_eval.py:78
↓ 1 callersMethodinfer_scope
Infer the scope of registry. The name of the package where registry is defined will be returned. Example: # in mmdet/model
HOIAffordanceMLLM/ReConV2/utils/registry.py:70
↓ 1 callersMethodinfer_scope
Infer the scope of registry. The name of the package where registry is defined will be returned. Example: # in mmdet/model
HOIAffordanceMLLM/llava/model/Uni3D/data/utils/registry.py:69
↓ 1 callersMethodinfo_nce_loss
(self, feat1, feat2, logit_scale=1, mask=None)
HOIAffordanceMLLM/ReConV2/models/ReCon.py:264
↓ 1 callersFunctioninit_distributed_device
(args)
HOIAffordanceMLLM/llava/model/Uni3D/utils/distributed.py:65
↓ 1 callersFunctioninit_model
(args)
HOIAffordanceMLLM/llava/eval/eval_objaverse.py:49
↓ 1 callersFunctioninit_model
(args)
HOIAffordanceMLLM/llava/eval/eval_modelnet_cls.py:47
↓ 1 callersFunctioninit_on_device
Device initialization context manager. A context manager under which models are initialized with all parameters on the specified device.
HOIAffordanceMLLM/llava/model/language_model/mpt/meta_init_context.py:37
↓ 1 callersMethodinpainting_loss
(self, ppx, pred_X0_lhand_uncond, pred_X0_rhand_uncond)
Affordance-DrivenHOIDiffusion/lib/networks/diffusion copy.py:328
↓ 1 callersFunctioninsert_separator
(X, sep)
HOIAffordanceMLLM/llava/mm_utils.py:166
↓ 1 callersFunctioninterpolate_point_cloud
(points, k)
HOIAffordanceMLLM/llava/mm_utils.py:10
↓ 1 callersFunctionintersectionAndUnionGPU
(output, target, K, ignore_index=255)
HOIAffordanceMLLM/utils/utils.py:116
↓ 1 callersFunctionis_dist_avail_and_initialized
()
HOIAffordanceMLLM/llava/model/Uni3D/utils/distributed.py:13
↓ 1 callersFunctionis_global_master
(args)
HOIAffordanceMLLM/llava/model/Uni3D/utils/distributed.py:25
↓ 1 callersFunctionis_local_master
(args)
HOIAffordanceMLLM/llava/model/Uni3D/utils/distributed.py:29
↓ 1 callersFunctionis_using_distributed
()
HOIAffordanceMLLM/llava/model/Uni3D/utils/distributed.py:37
↓ 1 callersFunctionis_valid
(value)
HOIAffordanceMLLM/llava/eval/gpt_eval.py:67
↓ 1 callersFunctionknn_point
Input: nsample: max sample number in local region xyz: all points, [B, N, C] new_xyz: query points, [B, S, C] Return:
HOIAffordanceMLLM/ReConV2/segmentation/knn.py:26
↓ 1 callersFunctionknn_point
Input: nsample: max sample number in local region xyz: all points, [B, N, C] new_xyz: query points, [B, S, C] Return:
HOIAffordanceMLLM/llava/model/Uni3D/models/point_encoder.py:17
↓ 1 callersFunctionload_dataset
(data_path, anno_path, pointnum, conversation_types, use_color)
HOIAffordanceMLLM/llava/eval/eval_objaverse.py:60
↓ 1 callersFunctionload_dataset
(config_path, split, subset_nums, use_color)
HOIAffordanceMLLM/llava/eval/eval_modelnet_cls.py:58
↓ 1 callersFunctionload_from_hf
(repo_id, filename, subfolder=None)
HOIAffordanceMLLM/llava/model/builder.py:63
↓ 1 callersMethodload_from_reconstruct
(self, path)
HOIAffordanceMLLM/ReConV2/tools/runner_pretrain.py:150
↓ 1 callersFunctionload_hydra_cfg
()
Affordance-DrivenHOIDiffusion/start/inference.py:96
↓ 1 callersMethodload_model_from_ckpt
(self, bert_ckpt_path)
HOIAffordanceMLLM/ReConV2/segmentation/models/pt.py:292
↓ 1 callersMethodload_pretrained_timm_weights
(self)
HOIAffordanceMLLM/ReConV2/models/transformer.py:509
↓ 1 callersFunctionlog_args_to_file
(args, pre='args', logger=None)
HOIAffordanceMLLM/ReConV2/utils/config.py:7
↓ 1 callersFunctionlog_config_to_file
(cfg, pre='cfg', logger=None)
HOIAffordanceMLLM/ReConV2/utils/config.py:12
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/train_ds.py:109
↓ 1 callersFunctionmain
()
HOIAffordanceMLLM/ReConV2/main.py:15
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/ReConV2/segmentation/main.py:71
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/llava/serve/cli.py:13
↓ 1 callersFunctionmain
()
HOIAffordanceMLLM/llava/serve/test_message.py:9
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/llava/model/Uni3D/main.py:54
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/llava/eval/eval_3dmmvet.py:9
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/llava/eval/eval_gapartnet.py:36
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/llava/eval/eval_objaverse.py:148
↓ 1 callersFunctionmain
(args)
HOIAffordanceMLLM/llava/eval/eval_modelnet_cls.py:144
↓ 1 callersFunctionmain
()
Affordance-DrivenHOIDiffusion/preprocessing_grab_object.py:9
↓ 1 callersFunctionmain
(config)
Affordance-DrivenHOIDiffusion/train/train_seq_cvae.py:26
↓ 1 callersFunctionmain
(config)
Affordance-DrivenHOIDiffusion/train/train_texthom.py:45
↓ 1 callersFunctionmain
(config)
Affordance-DrivenHOIDiffusion/train/train_contact_estimator.py:40
↓ 1 callersFunctionmain
(config)
Affordance-DrivenHOIDiffusion/train/train_refiner.py:49
↓ 1 callersFunctionmain
(config)
Affordance-DrivenHOIDiffusion/start/inference.py:104
↓ 1 callersFunctionmake_delta
(base_model_path, target_model_path, delta_path, hub_repo_id)
HOIAffordanceMLLM/llava/model/make_delta.py:13
↓ 1 callersFunctionmake_supervised_data_module
Make dataset and collator for supervised fine-tuning.
HOIAffordanceMLLM/llava/train/train.py:663
↓ 1 callersFunctionmake_supervised_data_module
Make dataset and collator for supervised fine-tuning.
HOIAffordanceMLLM/llava/train/inference.py:636
↓ 1 callersFunctionmaybe_zero_3
(param, ignore_status=False, name=None)
HOIAffordanceMLLM/llava/train/llava_trainer.py:18
↓ 1 callersFunctionmerge_lora
(args)
HOIAffordanceMLLM/scripts/merge_lora_weights.py:6
↓ 1 callersFunctionmerge_new_config
(config, new_config)
HOIAffordanceMLLM/ReConV2/utils/config.py:21
↓ 1 callersFunctionmerge_new_config
(config, new_config)
HOIAffordanceMLLM/llava/model/Uni3D/utils/utils.py:14
↓ 1 callersFunctionmerge_new_config
(config, new_config)
HOIAffordanceMLLM/llava/model/Uni3D/data/datasets.py:649
↓ 1 callersFunctionmerge_new_config
(config, new_config)
HOIAffordanceMLLM/llava/model/Uni3D/data/utils/config.py:18
↓ 1 callersFunctionmerge_new_config
(config, new_config)
HOIAffordanceMLLM/llava/model/Uni3D/data/utils/utils.py:14
↓ 1 callersFunctionmerge_new_config
(config, new_config)
HOIAffordanceMLLM/llava/eval/data/utils.py:250
↓ 1 callersMethodmodel_forward
( self, points:torch.FloatTensor, input_ids: torch.LongTensor, labels: torch.L
HOIAffordanceMLLM/llava/model/language_model/affordancellm.py:810
↓ 1 callersFunctionmy_augment_pool
()
HOIAffordanceMLLM/ReConV2/utils/randaugment.py:162
↓ 1 callersFunctionnormalize_point_cloud_to_2048
(points)
DataProcess/point_cloud_process.py:3
↓ 1 callersMethodparallel_evaluate
(self, num_workers=20)
HOIAffordanceMLLM/llava/eval/evaluator.py:742
↓ 1 callersMethodparallel_load_img
(self, index, max_workers)
HOIAffordanceMLLM/ReConV2/datasets/HybridDataset.py:70
↓ 1 callersMethodparallel_load_img
(self, sample, max_workers)
HOIAffordanceMLLM/ReConV2/datasets/ShapeNet55Dataset.py:96
↓ 1 callersMethodparallel_load_img
(self, index, max_workers)
HOIAffordanceMLLM/ReConV2/datasets/Cap3D.py:63
↓ 1 callersFunctionparse_args
(args)
HOIAffordanceMLLM/train_ds.py:24
↓ 1 callersFunctionparse_args
(args)
HOIAffordanceMLLM/llava/model/Uni3D/utils/params.py:13
↓ 1 callersFunctionparse_args
()
HOIAffordanceMLLM/scripts/extract_mm_projector.py:15
↓ 1 callersMethodparse_gpt_response_evaluate
(self, gpt_response)
HOIAffordanceMLLM/llava/eval/evaluator.py:173
↓ 1 callersMethodparse_gpt_response_evaluate
Argument: gpt_response: str, index#label#short_reason groud_truth: int
HOIAffordanceMLLM/llava/eval/evaluator.py:392
↓ 1 callersMethodparse_gpt_response_evaluate
Argument: gpt_response: str, index#label#short_reason groud_truth: int
HOIAffordanceMLLM/llava/eval/evaluator.py:643
↓ 1 callersFunctionpatch_tensor_constructor
(fn)
HOIAffordanceMLLM/llava/model/language_model/mpt/meta_init_context.py:76
↓ 1 callersFunctionpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/llava/mm_utils.py:130
↓ 1 callersFunctionpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/llava/eval/data/utils.py:152
↓ 1 callersMethodpc_norm
(self, pc)
HOIAffordanceMLLM/ReConV2/datasets/HybridDataset.py:46
↓ 1 callersMethodpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/ReConV2/datasets/HybridDataset.py:144
↓ 1 callersMethodpc_norm
(self, pc)
HOIAffordanceMLLM/ReConV2/datasets/ShapeNet55Dataset.py:75
↓ 1 callersMethodpc_norm
(self, pc)
HOIAffordanceMLLM/ReConV2/datasets/Cap3D.py:40
↓ 1 callersMethodpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/llava/model/Uni3D/data/datasets.py:231
↓ 1 callersMethodpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/llava/model/Uni3D/data/datasets.py:335
↓ 1 callersMethodpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/llava/model/Uni3D/data/datasets.py:521
↓ 1 callersMethodpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/llava/eval/data/object_point_dataset.py:152
↓ 1 callersMethodpc_norm
pc: NxC, return NxC
HOIAffordanceMLLM/llava/eval/data/modelnet.py:97
↓ 1 callersFunctionpc_normalize
(pc)
HOIAffordanceMLLM/ReConV2/datasets/ModelNetDatasetFewShot.py:19
↓ 1 callersFunctionpc_normalize
(pc)
HOIAffordanceMLLM/ReConV2/datasets/ModelNetDataset.py:20
↓ 1 callersFunctionpc_normalize
(pc)
HOIAffordanceMLLM/llava/model/Uni3D/data/datasets.py:29
↓ 1 callersFunctionpc_normalize
pc: Nx3 array This functions normalizes a point cloud to fit within a unit sphere. It first calculates the centroid of the point cloud an
HOIAffordanceMLLM/llava/eval/data/utils.py:236
↓ 1 callersFunctionpc_normalize
(pc)
HOIAffordanceMLLM/llava/train/aff_rea_dataset.py:74
↓ 1 callersMethodpoint_transform
:param points: [batch, num_points, 3] :param rot_mat: [batch, 3] :param rot_mat2: [batch, 3] :param translation: [bat
HOIAffordanceMLLM/ReConV2/datasets/pc_render.py:196
↓ 1 callersFunctionpoints2grid
Quantize each point cloud to a 3D grid. Args: points (torch.tensor): of size [B, _, 3] Returns: grid (torch.tensor): of size [
HOIAffordanceMLLM/ReConV2/datasets/pc_render.py:98
↓ 1 callersFunctionpreprocess
Given a list of sources, each is a conversation list. This transform: 1. Add signal '### ' at the beginning each sentence, with end signal '\
HOIAffordanceMLLM/llava/train/train.py:545
↓ 1 callersFunctionpreprocess
Given a list of sources, each is a conversation list. This transform: 1. Add signal '### ' at the beginning each sentence, with end signal '\
HOIAffordanceMLLM/llava/train/inference.py:524
↓ 1 callersFunctionpreprocess_multimodal
( sources: Sequence[str], data_args: DataArguments )
HOIAffordanceMLLM/llava/train/train.py:409
↓ 1 callersFunctionpreprocess_multimodal
( sources: Sequence[str], data_args: DataArguments )
HOIAffordanceMLLM/llava/train/inference.py:394
↓ 1 callersFunctionpreprocess_multimodal_point_cloud
( sources: Sequence[str], point_backbone_config: dict, point_indicator: str = "<point>
HOIAffordanceMLLM/llava/eval/data/utils.py:133
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
HOIAffordanceMLLM/llava/train/train.py:523
↓ 1 callersFunctionpreprocess_plain
( sources: Sequence[str], tokenizer: transformers.PreTrainedTokenizer, )
HOIAffordanceMLLM/llava/train/inference.py:502
↓ 1 callersFunctionpreprocess_v1
( sources, tokenizer: transformers.PreTrainedTokenizer, )
HOIAffordanceMLLM/llava/eval/data/utils.py:62
↓ 1 callersFunctionpreprocess_v1
( sources, tokenizer: transformers.PreTrainedTokenizer, has_point: bool = False )
HOIAffordanceMLLM/llava/train/train.py:431
↓ 1 callersFunctionpreprocess_v1
( sources, tokenizer: transformers.PreTrainedTokenizer, has_point: bool = False )
HOIAffordanceMLLM/llava/train/inference.py:416
↓ 1 callersFunctionpreprocessing_text
()
Affordance-DrivenHOIDiffusion/process_grab_text.py:36
↓ 1 callersFunctionpretty_print_semaphore
(semaphore)
HOIAffordanceMLLM/llava/utils.py:123
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