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Functions316 in github.com/ToTheBeginning/PuLID

⨍ Functions 316◇ Types & classes 80

Functionadd_model_config

add model config path or file and update registry

eva_clip/factory.py:58

(ctx, grad_output)

eva_clip/utils.py:319

Functioncreate_model_from_pretrained

( model_name: str, pretrained: str, precision: str = 'fp32', device: Union[str

eva_clip/factory.py:469

Functioncreate_transforms

( model_name: str, pretrained: Optional[str] = None, precision: str = 'fp32',

eva_clip/factory.py:413

Functiondrop_seq_token

(seq, drop_rate=0.5)

pulid/utils.py:44

Methodextra_repr

eva_clip/eva_vit_model.py:43

( self, img: Tensor, img_ids: Tensor, txt: Tensor, txt_ids: Tensor,

flux/model.py:87

(self, ids: Tensor)

flux/modules/layers.py:18

(self, x: Tensor)

flux/modules/layers.py:59

(self, x: Tensor)

flux/modules/layers.py:68

(self, q: Tensor, k: Tensor, v: Tensor)

flux/modules/layers.py:81

(self, x: Tensor, pe: Tensor)

flux/modules/layers.py:97

(self, vec: Tensor)

flux/modules/layers.py:120

(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor)

flux/modules/layers.py:158

(self, x: Tensor, vec: Tensor, pe: Tensor)

flux/modules/layers.py:227

(self, x: Tensor, vec: Tensor)

flux/modules/layers.py:249

(self, text: list[str])

flux/modules/conditioner.py:21

(self, x: Tensor)

flux/modules/autoencoder.py:51

flux/modules/autoencoder.py:69

(self, x: Tensor)

flux/modules/autoencoder.py:91

(self, x: Tensor)

flux/modules/autoencoder.py:103

(self, x: Tensor)

flux/modules/autoencoder.py:159

(self, z: Tensor)

flux/modules/autoencoder.py:237

(self, z: Tensor)

flux/modules/autoencoder.py:268

(self, x: Tensor)

flux/modules/autoencoder.py:311

pulid/encoders.py:51

Args: x (torch.Tensor): image features shape (b, n1, D) latent (torch.Tensor): latent features

pulid/encoders_transformer.py:44

Args: x (torch.Tensor): image features shape (b, n1, D) latent (torch.Tensor): latent features

pulid/encoders_transformer.py:90

pulid/encoders_transformer.py:189

(self, image_features, text_features, logit_scale=1.)

eva_clip/loss.py:95

(self, t, start_index = 0)

eva_clip/rope.py:70

(self, t, patch_indices_keep=None)

eva_clip/rope.py:121

(ctx, tensor, rank, world_size)

eva_clip/utils.py:311

(self, x: torch.Tensor)

eva_clip/modified_resnet.py:42

eva_clip/modified_resnet.py:68

eva_clip/modified_resnet.py:173

eva_clip/transform.py:24

eva_clip/timm_model.py:119

(self, x:BaseModelOutput, attention_mask:TensorType)

eva_clip/hf_model.py:46

(self, x:BaseModelOutput, attention_mask:TensorType)

eva_clip/hf_model.py:53

(self, x:BaseModelOutput, attention_mask:TensorType)

eva_clip/hf_model.py:65

(self, x:TensorType)

eva_clip/hf_model.py:213

(self, x: torch.Tensor)

eva_clip/transformer.py:41

(self, x: torch.Tensor)

eva_clip/transformer.py:55

(self, x: torch.Tensor)

eva_clip/transformer.py:62

eva_clip/transformer.py:72

eva_clip/transformer.py:87

(self, x, attn_mask: Optional[torch.Tensor] = None)

eva_clip/transformer.py:195

(self, query: torch.Tensor, key: torch.Tensor, value: torch.Tensor, attn_mask: Optional[torch.Tensor] = None)

eva_clip/transformer.py:286

(self, q: torch.Tensor, k: torch.Tensor, v: torch.Tensor, attn_mask: Optional[torch.Tensor] = None)

eva_clip/transformer.py:384

(self, q: torch.Tensor, k: torch.Tensor = None, v: torch.Tensor = None, attn_mask: Optional[torch.Tensor] = No

eva_clip/transformer.py:432

(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor] = None)

eva_clip/transformer.py:480

(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor] = None)

eva_clip/transformer.py:511

(self, x: torch.Tensor, return_all_features: bool=False)

eva_clip/transformer.py:611

(self, text, return_all_features: bool=False)

eva_clip/transformer.py:722

eva_clip/eva_vit_model.py:40

eva_clip/eva_vit_model.py:70

eva_clip/eva_vit_model.py:97

(self, x, rel_pos_bias=None, attn_mask=None)

eva_clip/eva_vit_model.py:173

(self, x, rel_pos_bias=None, attn_mask=None)

eva_clip/eva_vit_model.py:287

(self, x, **kwargs)

eva_clip/eva_vit_model.py:320

eva_clip/eva_vit_model.py:358

(self, x, return_all_features=False, return_hidden=False, shuffle=False)

eva_clip/eva_vit_model.py:541

(self, image, text)

eva_clip/model.py:264

(self, image, text)

eva_clip/model.py:309

Methodforward_mlm

(self, input_ids, image_embeds, mlm_probability=0.25)

eva_clip/hf_model.py:177

Methodgenerate_image

( self, width, height, num_steps, start_step,

Methodget_cast_dtype

eva_clip/transformer.py:429

Methodget_cast_dtype

eva_clip/eva_vit_model.py:458

Methodget_classifier

eva_clip/eva_vit_model.py:486

Methodget_id_embedding

Args: image: numpy rgb image, range [0, 255]

pulid/pipeline_flux.py:120

Methodget_id_embedding

Args: image in image_list: numpy rgb image, range [0, 255]

pulid/pipeline_v1_1.py:171

Methodget_num_layers

eva_clip/hf_model.py:242

Methodget_num_layers

eva_clip/transformer.py:600

Methodget_num_layers

eva_clip/transformer.py:711

Methodget_num_layers

eva_clip/eva_vit_model.py:470

Functionget_tokenizer

eva_clip/factory.py:73

Functionimport_model_class_from_model_name_or_path

( pretrained_model_name_or_path: str, revision: str, subfolder: str = "text_encoder" )

pulid/utils.py:52

Methodinference

( self, prompt, size, prompt_n='', id_embedding=None, uncond_i

pulid/pipeline_v1_1.py:270

Methodinit_parameters

eva_clip/hf_model.py:247

Functioninstantiate_from_config

pulid/utils.py:28

Functionis_logging

eva_clip/utils.py:292

Functionis_master

(args, local=False)

eva_clip/utils.py:299

Functionlist_pretrained

returns list of pretrained models Returns a tuple (model_name, pretrain_tag) by default or 'name:tag' if as_str == True

eva_clip/pretrained.py:196

Methodload_pretrain

(self, pretrain_path=None, version='v0.9.0')

pulid/pipeline_flux.py:94

(self, unlocked_groups=0, freeze_bn_stats=False)

eva_clip/modified_resnet.py:154

(self, unlocked_layers:int=0, freeze_layer_norm:bool=True)

eva_clip/hf_model.py:220

(self, unlocked_groups=0, freeze_bn_stats=False)

eva_clip/transformer.py:567

(self, unlocked_groups=0, freeze_bn_stats=False)

eva_clip/eva_vit_model.py:473

Methodlock_image_tower

(self, unlocked_groups=0, freeze_bn_stats=False)

eva_clip/model.py:233

Methodlock_image_tower

(self, unlocked_groups=0, freeze_bn_stats=False)

eva_clip/model.py:285

Methodlock_text_tower

(self, unlocked_layers:int=0, freeze_layer_norm:bool=True)

eva_clip/model.py:289

Methodno_weight_decay

eva_clip/transformer.py:608

Methodno_weight_decay

eva_clip/transformer.py:707

Methodno_weight_decay

eva_clip/eva_vit_model.py:483

Methodno_weight_decay

eva_clip/model.py:243

Methodno_weight_decay

eva_clip/model.py:298

eva_clip/utils.py:278

Functionregister_pooler

Decorator registering pooler class

eva_clip/hf_model.py:37

(param, layer_id)

eva_clip/eva_vit_model.py:448

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