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Functions238 in github.com/Monalissaa/DisenDiff

⨍ Functions 238◇ Types & classes 39

↓ 1 callersFunctionmain

src/diffusers_training.py:594

↓ 1 callersFunctionmelk

(*args, **kwargs)

↓ 1 callersFunctionnondefault_trainer_args

↓ 1 callersFunctionparse_args

utils/clip_eval.py:126

↓ 1 callersFunctionparse_args

utils/clipscore/clipscore.py:30

↓ 1 callersFunctionparse_args

src/compress.py:57

↓ 1 callersFunctionparse_args

src/retrieve.py:77

↓ 1 callersFunctionparse_args

src/diffusers_sample.py:55

↓ 1 callersFunctionparse_args

src/composenW.py:268

↓ 1 callersFunctionparse_args

src/get_deltas.py:43

↓ 1 callersFunctionparse_args

src/diffusers_composenW.py:167

↓ 1 callersFunctionparse_args

(input_args=None)

src/diffusers_training.py:312

↓ 1 callersFunctionparse_args

src/convert.py:141

↓ 1 callersMethodprepare_data

↓ 1 callersFunctionprocess_flickr8k

utils/clipscore/flickr8k_example/download.py:19

↓ 1 callersFunctionpycoco_eval

scorer is assumed to have a compute_score function. refs is a list of lists of strings cands is a list of predictions

utils/clipscore/generation_eval_utils.py:58

↓ 1 callersFunctionreplace_chars

utils/clip_eval.py:8

↓ 1 callersMethodreset

src/attention_controllers.py:215

↓ 1 callersFunctionretrieve

(class_prompt, class_data_dir, num_class_images)

src/retrieve.py:25

↓ 1 callersFunctionsample

(ckpt, delta_ckpt, from_file, prompt, compress, batch_size, freeze_model)

src/diffusers_sample.py:18

↓ 1 callersMethodsetup

(self, stage=None)

↓ 1 callersFunctionshow_cross_attention

(prompts, tokenizer, save_path, base_count, attention_store: AttentionStore, res: int, from_where: List[str],

↓ 1 callersMethodstep_callback

src/attention_controllers.py:135

↓ 1 callersFunctiontokenize

(refs, cands, no_op=False)

utils/clipscore/generation_eval_utils.py:39

↓ 1 callersMethodtxt_to_img_similarity

(self, text, generated_images)

utils/clip_eval.py:60

↓ 1 callersFunctionwhitespace_clean

clip/simple_tokenizer.py:56

(self, attn, is_cross: bool = True, place_in_unet: str = None)

src/attention_controllers.py:16

(self, attn, is_cross: bool, place_in_unet: str)

src/attention_controllers.py:149

src/ptp_utils.py:213

( self, attn: CrossAttention, hidden_states, encoder_hidden_states=None,

src/diffusers_model_pipeline.py:278

(self, attn: CrossAttention, hidden_states, encoder_hidden_states=None, attention_mask=None)

src/diffusers_model_pipeline.py:325

Method__getitem__

Method__getitem__

Method__getitem__

utils/clipscore/clipscore.py:73

Method__getitem__

utils/clipscore/clipscore.py:97

Method__getitem__

utils/ldmm/data/personalized.py:180

Method__getitem__

src/diffusers_data_pipeline.py:268

Method__getitem__

src/diffusers_data_pipeline.py:336

Method__getitem__

src/finetune_data.py:190

(self, dataset)

(self, *datasets)

(self, batch_size, train=None, train2=None, validation=None, test=None, predict=None, wrap=Fa

(self, resume, now, logdir, ckptdir, cfgdir, config, lightning_config)

(self, device, clip_model='ViT-B/32')

utils/clip_eval.py:109

(self, data, prefix='A photo depicts')

utils/clipscore/clipscore.py:67

utils/clipscore/clipscore.py:83

(self, data_root, size=None, repeats=100,

utils/ldmm/data/personalized.py:133

(self, bpe_path: str = default_bpe())

clip/simple_tokenizer.py:63

(self, embed_dim, num_heads, dropout=0., bias=True, add_bias_kv=False, add_zero_attn=False, kdim=None, vdim=No

clip/auxilary.py:296

(self, inplanes, planes, stride=1)

clip/model.py:13

(self, spacial_dim: int, embed_dim: int, num_heads: int, output_dim: int = None)

clip/model.py:57

(self, layers, output_dim, heads, input_resolution=224, width=64)

clip/model.py:101

(self, d_model: int, n_head: int, attn_mask: torch.Tensor = None)

clip/model.py:168

(self, width: int, layers: int, heads: int, attn_mask: torch.Tensor = None)

clip/model.py:202

(self, input_resolution: int, patch_size: int, width: int, layers: int, heads: int, output_dim: int)

clip/model.py:213

src/attention_controllers.py:46

src/attention_controllers.py:170

(self, all_step_attention_store=False)

src/attention_controllers.py:220

(self, channels, kernel_size, sigma, dim=2)

src/gaussian_smoothing.py:21

(self, size, newtoken=1)

src/iterative_embedding.py:4

src/ptp_utils.py:216

(self, prompt, num_samples)

src/diffusers_data_pipeline.py:261

( self, concepts_list, tokenizer, size=512, center_crop=False,

src/diffusers_data_pipeline.py:281

(self, datapath, reg_datapath=None, caption=None,

src/finetune_data.py:116

(self, attention_op: Optional[Callable] = None)

src/diffusers_model_pipeline.py:322

( self, vae: AutoencoderKL, text_encoder: CLIPTextModel, tokenizer: CLIPTokeni

src/diffusers_model_pipeline.py:395

(self, modifier_token, version="openai/clip-vit-large-patch14", device="cuda", max_length=77)

src/custom_modules.py:227

(self, freeze_model='crossattn-kv', cond_stage_trainable=False,

src/model.py:123

utils/clipscore/clipscore.py:78

utils/clipscore/clipscore.py:103

utils/ldmm/data/personalized.py:177

src/diffusers_data_pipeline.py:265

src/diffusers_data_pipeline.py:333

src/finetune_data.py:182

Method__setstate__

clip/auxilary.py:351

Function_convert_weights_to_fp16

clip/model.py:384

Method_predict_dataloader

(self, shuffle=False)

Method_test_dataloader

(self, shuffle=False)

Method_testtube

(self, pl_module, images, batch_idx, split)

Method_train_dataloader

Method_val_dataloader

(self, shuffle=False)

Methodadd_token

(self, initializer_token)

src/diffusers_model_pipeline.py:421

Functionaggregate_attention

(prompts, attention_store: AttentionStore, res: int, from_where: List[str], is_cross: bool, select: int)

Methodapply_smoothing_and_filter

(mask, smoothing, self_filter=False, twice_filter=False)

src/model.py:433

Methodbetween_steps

src/attention_controllers.py:25

Methodcalculate_IoU

(mask1, mask2, smooth=1)

src/model.py:452

Methodcalculate_IoU_wo_detach

(mask1, mask2, smooth=1)

src/model.py:461

Methodchange_checkpoint

src/model.py:222

Methodchange_forward

src/model.py:268

Methodconfigure_optimizers

src/model.py:284

(*args, **kwargs)

clip/model.py:343

(self, text, t=None)

src/custom_modules.py:311

Functionforward

(x, context=None, mask=None)

src/ptp_utils.py:182

r""" Args: query, key, value: map a query and a set of key-value pairs to an output. See "Attention Is All You Need" for more

clip/auxilary.py:358

(self, x: torch.Tensor)

clip/model.py:40

clip/model.py:66

clip/model.py:135

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