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Functions286 in github.com/Mark12Ding/Dispider

⨍ Functions 286◇ Types & classes 67 ↳ Endpoints 1

↓ 1 callersMethodprune_heads

dispider/model/multimodal_projector/modeling_sampler.py:281

↓ 1 callersMethodsave_attention_map

(self, attention_map)

dispider/model/multimodal_projector/modeling_sampler.py:139

↓ 1 callersFunctionsplit_list

Split a list into n (roughly) equal-sized chunks

dispider/eval/model_videomme_long.py:40

(self, input_ids: torch.LongTensor, scores: torch.FloatTensor)

inference.py:26

(self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs)

dispider/mm_utils.py:99

(self, input_ids: torch.LongTensor, scores: torch.FloatTensor)

dispider/eval/model_videomme_long.py:32

Method__getattr__

dispider/utils.py:70

(self, stops=[], encounters=1)

inference.py:22

(self, logger, log_level=logging.INFO)

dispider/utils.py:64

(self, keywords, tokenizer, input_ids)

dispider/mm_utils.py:73

(self, list_data_dict, tokenizer, conv)

dispider/conv_template.py:166

dispider/model/long_arch.py:29

dispider/model/llava_arch.py:30

dispider/model/language_model/stream_grounding_qwen.py:45

dispider/model/language_model/llava_qwen.py:46

dispider/model/language_model/grounding_qwen.py:45

(self, compressor)

dispider/model/language_model/builder.py:72

dispider/model/language_model/long_qwen.py:45

( self, vocab_size=151936, hidden_size=4096, intermediate_size=22016,

dispider/model/language_model/qwen_model/configuration_qwen.py:94

Qwen2RMSNorm is equivalent to T5LayerNorm

dispider/model/language_model/qwen_model/modeling_qwen.py:67

(self, dim, max_position_embeddings=2048, base=10000, device=None)

dispider/model/language_model/qwen_model/modeling_qwen.py:88

(self, config: Qwen2Config, layer_idx: Optional[int] = None)

dispider/model/language_model/qwen_model/modeling_qwen.py:194

(self, *args, **kwargs)

dispider/model/language_model/qwen_model/modeling_qwen.py:315

(self, config: Qwen2Config, layer_idx: int)

dispider/model/language_model/qwen_model/modeling_qwen.py:576

(self, config: Qwen2Config)

dispider/model/language_model/qwen_model/modeling_qwen.py:785

dispider/model/language_model/qwen_model/modeling_qwen.py:1020

dispider/model/language_model/qwen_model/modeling_qwen.py:2422

dispider/model/language_model/qwen_model/modeling_qwen.py:2538

dispider/model/multimodal_projector/modeling_sampler.py:40

(self, config, is_cross_attention)

dispider/model/multimodal_projector/modeling_sampler.py:98

dispider/model/multimodal_projector/modeling_sampler.py:260

(self, config, is_cross_attention=False)

dispider/model/multimodal_projector/modeling_sampler.py:275

dispider/model/multimodal_projector/modeling_sampler.py:331

dispider/model/multimodal_projector/modeling_sampler.py:346

dispider/model/multimodal_projector/modeling_sampler.py:467

dispider/model/multimodal_projector/modeling_sampler.py:569

dispider/model/multimodal_projector/modeling_sampler.py:584

dispider/model/multimodal_projector/modeling_sampler.py:602

dispider/model/multimodal_projector/modeling_sampler.py:624

(self, config, add_pooling_layer=False)

dispider/model/multimodal_projector/modeling_sampler.py:666

dispider/model/multimodal_projector/modeling_sampler.py:941

dispider/model/multimodal_projector/modeling_sampler.py:1115

dispider/model/multimodal_projector/builder.py:13

(self, channels)

dispider/model/multimodal_projector/builder.py:25

Builds the Slot Attention module. Args: iters: Number of iterations. num_slots: Number of slots. encoder_d

dispider/model/multimodal_projector/builder.py:42

(self, num_query_token, num_vision_features, out_size)

dispider/model/multimodal_projector/builder.py:115

(self, mlp, sa)

dispider/model/multimodal_projector/builder.py:164

( self, grid_size, embed_dim, num_heads, kv_dim=No

dispider/model/multimodal_projector/builder.py:346

(self, mlp, num_slot, embed_dim)

dispider/model/multimodal_projector/builder.py:418

(self, mlp, resolution, pool_num)

dispider/model/multimodal_projector/builder.py:448

dispider/model/multimodal_projector/builder.py:530

dispider/model/multimodal_projector/builder.py:562

(self, vision_tower, args=None, delay_load=False)

dispider/model/multimodal_encoder/clip_encoder.py:8

(self, stops=[], encounters=1)

dispider/eval/model_videomme_long.py:28

Function_compute_dynamic_ntk_parameters

Computes the inverse frequencies with NTK scaling. Credits to the Reddit users /u/bloc97 and /u/emozilla Args: config ([`~transformer

dispider/model/language_model/qwen_model/modeling_rope_utils.py:112

Function_compute_linear_scaling_rope_parameters

Computes the inverse frequencies with linear scaling. Credits to the Reddit user /u/kaiokendev Args: config ([`~transformers.Pretrain

dispider/model/language_model/qwen_model/modeling_rope_utils.py:71

Function_compute_llama3_parameters

Computes the inverse frequencies for llama 3.1. Args: config ([`~transformers.PretrainedConfig`]): The model configurati

dispider/model/language_model/qwen_model/modeling_rope_utils.py:310

Function_compute_longrope_parameters

Computes the inverse frequencies with LongRoPE scaling. Please refer to the [original implementation](https://github.com/microsoft/LongRoPE)

dispider/model/language_model/qwen_model/modeling_rope_utils.py:242

Function_compute_yarn_parameters

Computes the inverse frequencies with NTK scaling. Please refer to the [original paper](https://arxiv.org/abs/2309.00071) Args: c

dispider/model/language_model/qwen_model/modeling_rope_utils.py:163

Method_init_weights

dispider/model/language_model/qwen_model/modeling_qwen.py:687

Method_init_weights

Initialize the weights

dispider/model/multimodal_projector/modeling_sampler.py:643

Method_init_weights

dispider/model/multimodal_projector/builder.py:307

Method_init_weights

dispider/model/multimodal_projector/builder.py:383

Method_prune_heads

Prunes heads of the model. heads_to_prune: dict of {layer_num: list of heads to prune in this layer} See base class PreTrainedModel

dispider/model/multimodal_projector/modeling_sampler.py:684

Method_reorder_cache

(self, past, beam_idx)

dispider/model/multimodal_projector/modeling_sampler.py:1099

Method_set_gradient_checkpointing

(self, module, value=False)

dispider/model/language_model/stream_grounding_qwen.py:58

Method_set_gradient_checkpointing

(self, module, value=False)

dispider/model/language_model/llava_qwen.py:58

Method_set_gradient_checkpointing

(self, module, value=False)

dispider/model/language_model/grounding_qwen.py:57

Function_validate_default_rope_parameters

(config: PretrainedConfig, ignore_keys: Optional[set] = None)

dispider/model/language_model/qwen_model/modeling_rope_utils.py:395

Function_validate_dynamic_scaling_rope_parameters

(config: PretrainedConfig, ignore_keys: Optional[set] = None)

dispider/model/language_model/qwen_model/modeling_rope_utils.py:415

Function_validate_linear_scaling_rope_parameters

(config: PretrainedConfig, ignore_keys: Optional[set] = None)

dispider/model/language_model/qwen_model/modeling_rope_utils.py:403

Function_validate_llama3_parameters

(config: PretrainedConfig, ignore_keys: Optional[set] = None)

dispider/model/language_model/qwen_model/modeling_rope_utils.py:510

Function_validate_longrope_parameters

(config: PretrainedConfig, ignore_keys: Optional[set] = None)

dispider/model/language_model/qwen_model/modeling_rope_utils.py:460

Function_validate_yarn_parameters

(config: PretrainedConfig, ignore_keys: Optional[set] = None)

dispider/model/language_model/qwen_model/modeling_rope_utils.py:429

Functionbuild_logger

(logger_name, logger_filename)

dispider/utils.py:17

dispider/model/language_model/builder.py:153

dispider/model/multimodal_projector/builder.py:20

dispider/model/multimodal_encoder/clip_encoder.py:71

Methodcreate_custom_forward

dispider/model/multimodal_projector/modeling_sampler.py:512

Methodcustom_forward

dispider/model/multimodal_projector/modeling_sampler.py:513

dispider/model/language_model/builder.py:149

dispider/model/multimodal_encoder/clip_encoder.py:67

dispider/conversation.py:212

dispider/model/language_model/builder.py:145

dispider/model/multimodal_encoder/clip_encoder.py:63

Methoddummy_feature

dispider/model/language_model/builder.py:141

Methoddummy_feature

dispider/model/multimodal_encoder/clip_encoder.py:59

Methodexpand2square

(pil_img, background_color=(122, 116, 104))

dispider/conversation.py:130

Methodextra_repr

dispider/model/language_model/qwen_model/modeling_qwen.py:82

Methodfeed_forward_chunk

(self, attention_output)

dispider/model/multimodal_projector/modeling_sampler.py:455

Methodfeed_forward_chunk_query

(self, attention_output)

dispider/model/multimodal_projector/modeling_sampler.py:460

dispider/utils.py:87

( self, input_ids: torch.LongTensor = None, attention_mask: Optional[torch.Tensor] = N

dispider/model/language_model/stream_grounding_qwen.py:145

( self, input_ids: torch.LongTensor = None, attention_mask: Optional[torch.Tensor] = N

dispider/model/language_model/llava_qwen.py:133

( self, input_ids: torch.LongTensor = None, attention_mask: Optional[torch.Tensor] = N

dispider/model/language_model/grounding_qwen.py:128

(self, clips, clips_large, seqs, compress_mask, qs, qs_mask, time_labels)

dispider/model/language_model/builder.py:67

(self, clips, clips_large, seqs, compress_mask, qs, qs_mask, time_labels, ans_token, todo_token, insert_positi

dispider/model/language_model/builder.py:133

( self, input_ids: torch.LongTensor = None, attention_mask: Optional[torch.Tensor] = N

dispider/model/language_model/long_qwen.py:57

(self, hidden_states)

dispider/model/language_model/qwen_model/modeling_qwen.py:75

(self, x, seq_len=None)

dispider/model/language_model/qwen_model/modeling_qwen.py:112

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