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Functions543 in github.com/cientgu/VQ-Diffusion

⨍ Functions 543◇ Types & classes 107
↓ 1 callersMethodpreprocess
imgs: B x C x H x W, in the range 0-255
image_synthesis/modeling/codecs/image_codec/taming_gumbel_vqvae.py:254
↓ 1 callersMethodq_pred_one_timestep
(self, log_x_t, t)
image_synthesis/modeling/transformers/diffusion_transformer.py:151
↓ 1 callersMethodq_pred_one_timestep
(self, log_x_t, t)
image_synthesis/modeling/transformers/diffusion_transformer_amp.py:167
↓ 1 callersMethodremap_to_used
(self, inds)
image_synthesis/taming/modules/vqvae/quantize.py:147
↓ 1 callersMethodremap_to_used
(self, inds)
image_synthesis/taming/modules/vqvae/quantize.py:247
↓ 1 callersFunctionretrieve
Given a nested list or dict return the desired value at key expanding callable nodes if necessary and :attr:`expand` is ``True``. The expansion
image_synthesis/taming/util.py:62
↓ 1 callersMethodreverse
(self, output)
image_synthesis/taming/modules/util.py:71
↓ 1 callersMethodrun
(self,func,array,**kwargs)
image_synthesis/data/utils/manage.py:32
↓ 1 callersMethodsample
( self, batch, clip = None, temperature = 1., return_rec = True,
image_synthesis/modeling/models/unconditional_dalle.py:164
↓ 1 callersMethodsample
( self, batch, clip = None, temperature = 1., return_rec = True,
image_synthesis/modeling/models/conditional_dalle.py:193
↓ 1 callersMethodsample
(self, batch, phase='train', step_type='iteration')
image_synthesis/engine/solver.py:178
↓ 1 callersMethodsample_fast
( self, condition_token, condition_mask, condition_embed,
image_synthesis/modeling/transformers/diffusion_transformer.py:541
↓ 1 callersMethodsample_time
(self, b, device, method='uniform')
image_synthesis/modeling/transformers/diffusion_transformer.py:271
↓ 1 callersMethodsample_time
(self, b, device, method='uniform')
image_synthesis/modeling/transformers/diffusion_transformer_amp.py:276
↓ 1 callersMethodsave_config
(self, config)
image_synthesis/engine/logger.py:44
↓ 1 callersFunctionsave_config_to_yaml
(config, path)
image_synthesis/utils/io.py:12
↓ 1 callersMethodschedule
(self, n)
image_synthesis/taming/lr_scheduler.py:17
↓ 1 callersFunctionseed_everything
Function that sets seed for pseudo-random number generators in: pytorch, numpy, python.random Args: seed: the integer value
image_synthesis/utils/misc.py:9
↓ 1 callersFunctionspatial_average
(x, keepdim=True)
image_synthesis/taming/modules/losses/lpips.py:119
↓ 1 callersMethodsynchronize
Helper function to synchronize (barrier) among all processes when using distributed training
image_synthesis/data/utils/comm.py:59
↓ 1 callersMethodtemperature_scheduling
(self)
image_synthesis/taming/models/vqgan.py:200
↓ 1 callersFunctiontokenize
Returns the tokenized representation of given input string(s) Parameters ---------- texts : Union[str, List[str]] An input s
image_synthesis/modeling/modules/clip/clip.py:164
↓ 1 callersFunctiontop_k_logits
(logits, k)
image_synthesis/taming/modules/transformer/mingpt.py:285
↓ 1 callersMethodtrain_epoch
(self)
image_synthesis/engine/solver.py:402
↓ 1 callersMethodunmap_to_all
(self, inds)
image_synthesis/taming/modules/vqvae/quantize.py:161
↓ 1 callersMethodunmap_to_all
(self, inds)
image_synthesis/taming/modules/vqvae/quantize.py:261
↓ 1 callersMethodvalidate_epoch
(self)
image_synthesis/engine/solver.py:470
↓ 1 callersFunctionwhitespace_clean
(text)
image_synthesis/modeling/modules/clip/simple_tokenizer.py:56
↓ 1 callersFunctionwhitespace_clean
(text)
image_synthesis/modeling/modules/clip/clip_tokenizer.py:56
↓ 1 callersFunctionwrite_args
(args, path)
image_synthesis/utils/io.py:26
Method__call__
image: PIL.Image
image_synthesis/data/utils/image_preprocessor.py:24
Method__call__
image: PIL.Image
image_synthesis/data/utils/image_preprocessor.py:75
Method__call__
(self, parameters)
image_synthesis/engine/clip_grad_norm.py:16
Method__call__
(self, n)
image_synthesis/taming/lr_scheduler.py:32
Method__exit__
(self, exc_type, exc_value, traceback)
image_synthesis/data/utils/manage.py:213
Method__getitem__
(self, index)
image_synthesis/data/cub200_dataset.py:42
Method__getitem__
(self, index)
image_synthesis/data/ffhq_dataset.py:16
Method__getitem__
(self, index)
image_synthesis/data/imagenet_dataset.py:39
Method__getitem__
(self, index)
image_synthesis/data/mscoco_dataset.py:33
Method__init__
(self, config, path)
inference_VQ_Diffusion.py:24
Method__init__
(self, num_embed=1000, embed_dim=512, identity=False,
image_synthesis/modeling/embeddings/class_embedding.py:6
Method__init__
(self, num_embed=8192, spatial_size=[32, 32], # height and with
image_synthesis/modeling/embeddings/dalle_mask_image_embedding.py:6
Method__init__
(self, clip_name='ViT-B/32', num_embed=49408, normalize=Tr
image_synthesis/modeling/embeddings/clip_text_embedding.py:8
Method__init__
(self, end_idx=49152, bpe_path: str = default_bpe())
image_synthesis/modeling/modules/clip/simple_tokenizer.py:63
Method__init__
(self, end_idx=49152, bpe_path: str = default_bpe())
image_synthesis/modeling/modules/clip/clip_tokenizer.py:63
Method__init__
(self, inplanes, planes, stride=1)
image_synthesis/modeling/modules/clip/model.py:12
Method__init__
(self, spacial_dim: int, embed_dim: int, num_heads: int, output_dim: int = None)
image_synthesis/modeling/modules/clip/model.py:56
Method__init__
(self, layers, output_dim, heads, input_resolution=224, width=64)
image_synthesis/modeling/modules/clip/model.py:100
Method__init__
(self, d_model: int, n_head: int, attn_mask: torch.Tensor = None)
image_synthesis/modeling/modules/clip/model.py:167
Method__init__
(self, width: int, layers: int, heads: int, attn_mask: torch.Tensor = None)
image_synthesis/modeling/modules/clip/model.py:191
Method__init__
(self, input_resolution: int, patch_size: int, width: int, layers: int, heads: int, output_dim: int)
image_synthesis/modeling/modules/clip/model.py:202
Method__init__
( self, *, content_emb_config=None, condition_emb_config=None, transfo
image_synthesis/modeling/transformers/diffusion_transformer.py:69
Method__init__
( self, *, content_emb_config=None, condition_emb_config=None, transfo
image_synthesis/modeling/transformers/diffusion_transformer_amp.py:62
Method__init__
(self, n_embd, # the embed dim n_head, # the number of heads
image_synthesis/modeling/transformers/transformer_utils.py:23
Method__init__
(self, condition_seq_len, n_embd, # the embed dim condit
image_synthesis/modeling/transformers/transformer_utils.py:63
Method__init__
(self, num_steps, dim, rescale_steps=4000)
image_synthesis/modeling/transformers/transformer_utils.py:120
Method__init__
(self, n_embd, diffusion_step, emb_type="adalayernorm_abs")
image_synthesis/modeling/transformers/transformer_utils.py:137
Method__init__
(self, n_embd, diffusion_step, emb_type="adainsnorm_abs")
image_synthesis/modeling/transformers/transformer_utils.py:154
Method__init__
(self, class_type='adalayernorm', class_number=1000, con
image_synthesis/modeling/transformers/transformer_utils.py:172
Method__init__
(self, n_embd, mlp_hidden_times, act, resid_pdrop)
image_synthesis/modeling/transformers/transformer_utils.py:277
Method__init__
( self, condition_seq_len=77, n_layer=14, n_embd=1024, n_head=16,
image_synthesis/modeling/transformers/transformer_utils.py:292
Method__init__
( self, class_type='adalayernorm', class_number=1000, n_layer=24,
image_synthesis/modeling/transformers/transformer_utils.py:439
Method__init__
( self, class_type='adalayernorm', n_layer=24, n_embd=512, n_head
image_synthesis/modeling/transformers/transformer_utils.py:582
Method__init__
( self, *, content_info={'key': 'image'}, content_codec_config, diffus
image_synthesis/modeling/models/unconditional_dalle.py:20
Method__init__
( self, *, content_info={'key': 'image'}, condition_info={'key': 'label'},
image_synthesis/modeling/models/conditional_dalle.py:20
Method__init__
( self, *, content_info={'key': 'image'}, condition_info={'key': 'text'},
image_synthesis/modeling/models/dalle.py:20
Method__init__
(self, decoder, post_quant_conv, quantize, w=16, h=16)
image_synthesis/modeling/codecs/image_codec/taming_gumbel_vqvae.py:33
Method__init__
( self, trainable=False, token_shape=[16,16], config_path='OU
image_synthesis/modeling/codecs/image_codec/taming_gumbel_vqvae.py:51
Method__init__
( self, trainable=False, token_shape=[16,16], config_path='OU
image_synthesis/modeling/codecs/image_codec/taming_gumbel_vqvae.py:133
Method__init__
( self, trainable=False, token_shape=[32,32], config_path='OU
image_synthesis/modeling/codecs/image_codec/taming_gumbel_vqvae.py:211
Method__init__
This is a wrapper class for tokenize of texts. For CLIP and DALLE-pytorch tokenize, the default arguments are different:
image_synthesis/modeling/codecs/text_codec/tokenize.py:8
Method__init__
(self, data_root, phase = 'train', im_preprocessor_config=None)
image_synthesis/data/cub200_dataset.py:17
Method__init__
(self, data_root, im_preprocessor_config)
image_synthesis/data/ffhq_dataset.py:12
Method__init__
(self, data_root, input_file, phase = 'train', im_preprocessor_config=None)
image_synthesis/data/imagenet_dataset.py:15
Method__init__
(self, data_root, phase = 'train', im_preprocessor_config=None)
image_synthesis/data/mscoco_dataset.py:15
Method__init__
(self, size=256, phase='train', additional_targets=None)
image_synthesis/data/utils/image_preprocessor.py:10
Method__init__
(self, size=256, phase='train', additional_targets=None)
image_synthesis/data/utils/image_preprocessor.py:61
Method__init__
(self, local_rank=0)
image_synthesis/data/utils/comm.py:14
Method__init__
(self,n)
image_synthesis/data/utils/manage.py:28
Method__init__
(self, files: list)
image_synthesis/data/utils/manage.py:105
Method__init__
(self, db_path,data_type,prefix=None,load=True)
image_synthesis/data/utils/manage.py:112
Method__init__
(self, db_path,data_type,prefix=None,load=True)
image_synthesis/data/utils/manage.py:159
Method__init__
(self,db_path,data_type,prefix=None,load=True)
image_synthesis/data/utils/manage.py:220
Method__init__
(self, files: list, data_type,get_key=False,sync=True)
image_synthesis/data/utils/manage.py:283
Method__init__
(self, path, readonly=True, size=None)
image_synthesis/data/utils/manage.py:383
Method__init__
(self, config, args, model, dataloader, logger)
image_synthesis/engine/solver.py:37
Method__init__
(self, start_iteration=0, end_iteration=-1, # if negative, the norm will b
image_synthesis/engine/clip_grad_norm.py:5
Method__init__
(self, model, decay=0.99, update_interval=1,
image_synthesis/engine/ema.py:5
Method__init__
(self, args)
image_synthesis/engine/logger.py:19
Method__init__
(self, optimizer, mode='min', factor=0.1, patience=10, threshold=1e-4, threshold_mode='rel',
image_synthesis/engine/lr_scheduler.py:52
Method__init__
(self, optimizer, T_max, last_epoch=-1, verbose=False, min_lr=0, warmup_lr=None, warmup=0)
image_synthesis/engine/lr_scheduler.py:218
Method__init__
(self, warm_up_steps, lr_min, lr_max, lr_start, max_decay_steps, verbosity_interval=0)
image_synthesis/taming/lr_scheduler.py:8
Method__init__
(self, cause, keys=None, visited=None)
image_synthesis/taming/util.py:48
Method__init__
(self)
image_synthesis/taming/modules/util.py:96
Method__init__
(self, n_classes, quantize_interface=True)
image_synthesis/taming/modules/util.py:105
Method__init__
(self, sos_token, quantize_interface=True)
image_synthesis/taming/modules/util.py:119
Method__init__
(self, in_channels, with_conv)
image_synthesis/taming/modules/diffusionmodules/model.py:39
Method__init__
(self, in_channels, with_conv)
image_synthesis/taming/modules/diffusionmodules/model.py:57
Method__init__
(self, *, in_channels, out_channels=None, conv_shortcut=False, dropout, temb_channels=512)
image_synthesis/taming/modules/diffusionmodules/model.py:79
Method__init__
(self, in_channels)
image_synthesis/taming/modules/diffusionmodules/model.py:141
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