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Functions1,414 in github.com/ChenWu98/cycle-diffusion

⨍ Functions 1,414◇ Types & classes 263
↓ 51 callersMethodlog
(self, *args, level=INFO)
model/lib/ddpm_ddim/models/improved_ddpm/logger.py:332
↓ 39 callersMethodregister_buffer
(self, name, attr)
model/lib/stable_diffusion/ldm/models/diffusion/ddim.py:19
↓ 38 callersMethodregister_buffer
(self, name, attr)
model/lib/latentdiff/ldm/models/diffusion/ddim.py:18
↓ 31 callersFunctionextract
Extract coefficients from a based on t and reshape to make it broadcastable with x_shape.
model/lib/ddpm_ddim/utils/diffusion_utils.py:12
↓ 23 callersFunctioninstantiate_from_config
(config)
model/lib/latentdiff/ldm/util.py:71
↓ 22 callersFunctioninstantiate_from_config
(config)
model/lib/stable_diffusion/ldm/util.py:78
↓ 17 callersMethoddecode_first_stage
(self, z, predict_cids=False, force_not_quantize=False)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:698
↓ 17 callersMethodema_scope
(self, context=None)
model/lib/latentdiff/ldm/models/autoencoder.py:64
↓ 16 callersFunctionexists
(val)
model/lib/latentdiff/ldm/modules/x_transformer.py:54
↓ 16 callersFunctionexists
(val)
model/lib/stable_diffusion/ldm/modules/x_transformer.py:54
↓ 15 callersMethod__init__
(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks, attn_resolutions, dropout=0.0, resam
model/lib/latentdiff/ldm/modules/diffusionmodules/model.py:217
↓ 15 callersMethod__init__
(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks, attn_resolutions, dropout=0.0, resam
model/lib/stable_diffusion/ldm/modules/diffusionmodules/model.py:217
↓ 15 callersFunctionconv_nd
Create a 1D, 2D, or 3D convolution module.
model/lib/latentdiff/ldm/modules/diffusionmodules/util.py:219
↓ 15 callersFunctionconv_nd
Create a 1D, 2D, or 3D convolution module.
model/lib/stable_diffusion/ldm/modules/diffusionmodules/util.py:219
↓ 15 callersMethoddecode
(self, quant)
model/lib/latentdiff/ldm/models/autoencoder.py:107
↓ 15 callersFunctionextract_into_tensor
(a, t, x_shape)
model/lib/stable_diffusion/ldm/modules/diffusionmodules/util.py:97
↓ 14 callersMethoddevice
(self)
model/gan_wrapper/ddpm_ddim_wrapper.py:537
↓ 14 callersMethodq_sample
(self, x_start, t, noise=None)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:270
↓ 14 callersMethodq_sample
(self, x_start, t, noise=None)
model/lib/stable_diffusion/ldm/models/diffusion/ddpm.py:271
↓ 13 callersMethodapply_model
(self, x_noisy, t, cond, return_ids=False)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:882
↓ 13 callersMethodapply_model
(self, x_noisy, t, cond, return_ids=False)
model/lib/stable_diffusion/ldm/models/diffusion/ddpm.py:882
↓ 13 callersMethoddecode
(self, x_latent, cond, t_start, unconditional_guidance_scale=1.0, unconditional_conditioning=None,
model/lib/stable_diffusion/ldm/models/diffusion/ddim.py:663
↓ 13 callersFunctionextract_into_tensor
(a, t, x_shape)
model/lib/latentdiff/ldm/modules/diffusionmodules/util.py:97
↓ 13 callersMethodregister_buffer
(self, name, attr)
model/lib/latentdiff/ldm/models/diffusion/plms.py:18
↓ 13 callersMethodregister_buffer
(self, name, attr)
model/lib/stable_diffusion/ldm/models/diffusion/plms.py:18
↓ 12 callersMethod__init__
(self, value, fn)
model/lib/latentdiff/ldm/modules/x_transformer.py:118
↓ 12 callersMethod__init__
(self, value, fn)
model/lib/stable_diffusion/ldm/modules/x_transformer.py:118
↓ 12 callersFunctionconv_nd
Create a 1D, 2D, or 3D convolution module.
model/lib/ddpm_ddim/models/improved_ddpm/nn.py:22
↓ 12 callersMethodget_learned_conditioning
(self, c)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:545
↓ 12 callersMethodis_world_process_zero
Whether or not this process is the global main process (when training in a distributed fashion on several machines, this is only goin
trainer/trainer.py:361
↓ 10 callersMethoddecode_first_stage
(self, z, predict_cids=False, force_not_quantize=False)
model/lib/stable_diffusion/ldm/models/diffusion/ddpm.py:698
↓ 10 callersFunctionnonlinearity
(x)
model/lib/latentdiff/ldm/modules/diffusionmodules/model.py:33
↓ 10 callersFunctionnonlinearity
(x)
model/lib/stable_diffusion/ldm/modules/diffusionmodules/model.py:33
↓ 9 callersFunctionNormalize
(in_channels, num_groups=32)
model/lib/latentdiff/ldm/modules/diffusionmodules/model.py:38
↓ 9 callersFunctionNormalize
(in_channels, num_groups=32)
model/lib/stable_diffusion/ldm/modules/diffusionmodules/model.py:38
↓ 9 callersMethod__init__
(self, channels, use_conv, dims=2, out_channels=None, padding=1)
model/lib/latentdiff/ldm/modules/diffusionmodules/openaimodel.py:100
↓ 9 callersMethod__init__
(self, channels, use_conv, dims=2, out_channels=None, padding=1)
model/lib/stable_diffusion/ldm/modules/diffusionmodules/openaimodel.py:100
↓ 9 callersFunctionget_current
()
model/lib/ddpm_ddim/models/improved_ddpm/logger.py:281
↓ 8 callersMethod__init__
(self, n_embed, n_layer, vocab_size=30522, max_seq_len=77, device="cuda",use_tokenizer=True,
model/lib/stable_diffusion/ldm/modules/encoders/modules.py:81
↓ 8 callersMethodencode
(self, x)
model/lib/latentdiff/ldm/models/autoencoder.py:96
↓ 8 callersMethodlog
Log :obj:`logs` on the various objects watching training. Subclass and override this method to inject custom behavior. Args
trainer/trainer.py:332
↓ 8 callersFunctionnormalization
Make a standard normalization layer. :param channels: number of input channels. :return: an nn.Module for normalization.
model/lib/latentdiff/ldm/modules/diffusionmodules/util.py:200
↓ 8 callersFunctionnormalization
Make a standard normalization layer. :param channels: number of input channels. :return: an nn.Module for normalization.
model/lib/stable_diffusion/ldm/modules/diffusionmodules/util.py:200
↓ 7 callersMethod__init__
(self, channels, use_conv, dims=2, out_channels=None)
model/lib/ddpm_ddim/models/improved_ddpm/unet.py:96
↓ 7 callersMethodema_scope
(self, context=None)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:171
↓ 7 callersMethodema_scope
(self, context=None)
model/lib/stable_diffusion/ldm/models/diffusion/ddpm.py:172
↓ 7 callersFunctionmake_attn
(in_channels, attn_type="vanilla")
model/lib/latentdiff/ldm/modules/diffusionmodules/model.py:205
↓ 7 callersFunctionmake_attn
(in_channels, attn_type="vanilla")
model/lib/stable_diffusion/ldm/modules/diffusionmodules/model.py:205
↓ 7 callersMethodsample
(self)
model/lib/latentdiff/ldm/modules/distributions/distributions.py:17
↓ 7 callersMethodsample
(self)
model/lib/stable_diffusion/ldm/modules/distributions/distributions.py:17
↓ 6 callersMethod__init__
(self, dim_in, dim_out)
model/lib/latentdiff/ldm/modules/attention.py:38
↓ 6 callersMethod__init__
(self, txt_file, data_root, size=None, int
model/lib/latentdiff/ldm/data/lsun.py:10
↓ 6 callersMethod__init__
(self, dim_in, dim_out)
model/lib/stable_diffusion/ldm/modules/attention.py:38
↓ 6 callersMethod__init__
(self, txt_file, data_root, size=None, int
model/lib/stable_diffusion/ldm/data/lsun.py:10
↓ 6 callersFunctionadd_JPEG_noise
(img)
model/lib/latentdiff/ldm/modules/image_degradation/bsrgan.py:418
↓ 6 callersFunctionadd_JPEG_noise
(img)
model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan.py:418
↓ 6 callersFunctionadd_blur
(img, sf=4)
model/lib/latentdiff/ldm/modules/image_degradation/bsrgan.py:325
↓ 6 callersFunctionadd_blur
(img, sf=4)
model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan.py:325
↓ 6 callersFunctiondefault
(val, d)
model/lib/latentdiff/ldm/modules/x_transformer.py:58
↓ 6 callersFunctiondefault
(val, d)
model/lib/stable_diffusion/ldm/modules/x_transformer.py:58
↓ 6 callersMethodencode_first_stage
(self, x)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:817
↓ 6 callersMethodget_first_stage_encoding
(self, encoder_posterior)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:535
↓ 6 callersMethodget_learned_conditioning
(self, c)
model/lib/stable_diffusion/ldm/models/diffusion/ddpm.py:545
↓ 6 callersFunctionlog
Write the sequence of args, with no separators, to the console and output files (if you've configured an output file).
model/lib/ddpm_ddim/models/improved_ddpm/logger.py:203
↓ 6 callersMethodlogkv_mean
(self, key, val)
model/lib/ddpm_ddim/models/improved_ddpm/logger.py:306
↓ 6 callersMethodmeshgrid
(self, h, w)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:558
↓ 6 callersMethodmeshgrid
(self, h, w)
model/lib/stable_diffusion/ldm/models/diffusion/ddpm.py:558
↓ 6 callersMethodquantize
(self, x, *args, **kwargs)
model/lib/latentdiff/ldm/models/autoencoder.py:436
↓ 6 callersMethodquantize
(self, x, *args, **kwargs)
model/lib/stable_diffusion/ldm/models/autoencoder.py:436
↓ 5 callersMethod__init__
(self, n_embed, n_layer, vocab_size=30522, max_seq_len=77, device="cuda",use_tokenizer=True,
model/lib/latentdiff/ldm/modules/encoders/modules.py:77
↓ 5 callersMethodclose
(self)
model/lib/ddpm_ddim/models/improved_ddpm/logger.py:347
↓ 5 callersFunctiondefault
(val, d)
model/lib/latentdiff/ldm/util.py:50
↓ 5 callersFunctiondefault
(val, d)
model/lib/stable_diffusion/ldm/util.py:57
↓ 5 callersMethodencode
(self, x)
model/lib/stable_diffusion/ldm/models/autoencoder.py:96
↓ 5 callersMethodforward
(self, x)
model/lib/latentdiff/ldm/modules/diffusionmodules/util.py:211
↓ 5 callersMethodforward
(self, x)
model/lib/stable_diffusion/ldm/modules/diffusionmodules/util.py:211
↓ 5 callersMethodget_input
(self, batch, k)
model/lib/latentdiff/ldm/models/diffusion/ddpm.py:325
↓ 5 callersMethodget_input
(self, batch, k)
model/lib/stable_diffusion/ldm/models/diffusion/ddpm.py:326
↓ 5 callersFunctionlinear
Create a linear module.
model/lib/latentdiff/ldm/modules/diffusionmodules/util.py:232
↓ 5 callersFunctionlinear
Create a linear module.
model/lib/stable_diffusion/ldm/modules/diffusionmodules/util.py:232
↓ 5 callersFunctionnoise_like
(shape, device, repeat=False)
model/lib/latentdiff/ldm/modules/diffusionmodules/util.py:265
↓ 5 callersFunctionnoise_like
(shape, device, repeat=False)
model/lib/stable_diffusion/ldm/modules/diffusionmodules/util.py:265
↓ 5 callersFunctionnonlinearity
(x)
model/lib/ddpm_ddim/models/ddpm/diffusion.py:27
↓ 5 callersMethodsample
(self, S, batch_size, shape, conditioning=None,
model/lib/latentdiff/ldm/models/diffusion/ddim.py:56
↓ 5 callersMethodto_rgb
(self, x)
model/lib/latentdiff/ldm/models/autoencoder.py:255
↓ 5 callersMethodto_rgb
(self, x)
model/lib/stable_diffusion/ldm/models/autoencoder.py:255
↓ 4 callersFunctionNormalize
(in_channels)
model/lib/ddpm_ddim/models/ddpm/diffusion.py:32
↓ 4 callersMethod__init__
Imagenet Superresolution Dataloader Performs following ops in order: 1. crops a crop of size s from image either as random o
model/lib/latentdiff/ldm/data/imagenet.py:273
↓ 4 callersMethod__init__
Imagenet Superresolution Dataloader Performs following ops in order: 1. crops a crop of size s from image either as random o
model/lib/stable_diffusion/ldm/data/imagenet.py:273
↓ 4 callersMethod__init__
(self, config)
model/lib/ddpm_ddim/models/ddpm/diffusion.py:193
↓ 4 callersFunctionadd_Gaussian_noise
(img, noise_level1=2, noise_level2=25)
model/lib/latentdiff/ldm/modules/image_degradation/bsrgan.py:369
↓ 4 callersFunctionadd_Gaussian_noise
(img, noise_level1=2, noise_level2=25)
model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan.py:369
↓ 4 callersFunctionadd_JPEG_noise
(img)
model/lib/latentdiff/ldm/modules/image_degradation/bsrgan_light.py:422
↓ 4 callersFunctionadd_JPEG_noise
(img)
model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan_light.py:422
↓ 4 callersFunctionadopt_weight
(weight, global_step, threshold=0, value=0.)
model/lib/latentdiff/ldm/modules/losses/vqperceptual.py:20
↓ 4 callersFunctionadopt_weight
(weight, global_step, threshold=0, value=0.)
model/lib/stable_diffusion/ldm/modules/losses/vqperceptual.py:20
↓ 4 callersFunctioncalculate_weights_indices
(in_length, out_length, scale, kernel, kernel_width, antialiasing)
model/lib/latentdiff/ldm/modules/image_degradation/utils_image.py:708
↓ 4 callersFunctioncalculate_weights_indices
(in_length, out_length, scale, kernel, kernel_width, antialiasing)
model/lib/stable_diffusion/ldm/modules/image_degradation/utils_image.py:708
↓ 4 callersMethodcompute_top_k
(self, logits, labels, k, reduction="mean")
model/lib/latentdiff/ldm/models/diffusion/classifier.py:147
↓ 4 callersMethodcompute_top_k
(self, logits, labels, k, reduction="mean")
model/lib/stable_diffusion/ldm/models/diffusion/classifier.py:147
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