Functions — github.com/ChenWu98/cycle-diffusion

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

⨍ Functions 1,414◇ Types & classes 263

↓ 1 callersMethod_filter_relpaths

(self, relpaths)

model/lib/stable_diffusion/ldm/data/imagenet.py:48

↓ 1 callersFunction_get_paths_from_images

(path)

model/lib/latentdiff/ldm/modules/image_degradation/utils_image.py:74

↓ 1 callersFunction_get_paths_from_images

(path)

model/lib/stable_diffusion/ldm/modules/image_degradation/utils_image.py:74

↓ 1 callersMethod_load

(self)

model/lib/latentdiff/ldm/data/imagenet.py:93

↓ 1 callersMethod_load

(self)

model/lib/stable_diffusion/ldm/data/imagenet.py:93

↓ 1 callersMethod_load_state_dict_in_model

(self, state_dict)

trainer/trainer.py:368

↓ 1 callersMethod_maybe_log_save_evaluate

(self, weighted_loss, losses,

trainer/trainer.py:509

↓ 1 callersMethod_optimize_fp16

(self, opt: th.optim.Optimizer)

model/lib/ddpm_ddim/models/improved_ddpm/fp16_util.py:189

↓ 1 callersMethod_optimize_normal

(self, opt: th.optim.Optimizer)

model/lib/ddpm_ddim/models/improved_ddpm/fp16_util.py:209

↓ 1 callersMethod_prepare

(self)

model/lib/latentdiff/ldm/data/imagenet.py:45

↓ 1 callersMethod_prepare

(self)

model/lib/stable_diffusion/ldm/data/imagenet.py:45

↓ 1 callersMethod_prepare_human_to_integer_label

(self)

model/lib/latentdiff/ldm/data/imagenet.py:80

↓ 1 callersMethod_prepare_human_to_integer_label

(self)

model/lib/stable_diffusion/ldm/data/imagenet.py:80

↓ 1 callersMethod_prepare_idx_to_synset

(self)

model/lib/latentdiff/ldm/data/imagenet.py:74

↓ 1 callersMethod_prepare_idx_to_synset

(self)

model/lib/stable_diffusion/ldm/data/imagenet.py:74

↓ 1 callersMethod_prepare_synset_to_human

(self)

model/lib/latentdiff/ldm/data/imagenet.py:66

↓ 1 callersMethod_prepare_synset_to_human

(self)

model/lib/stable_diffusion/ldm/data/imagenet.py:66

↓ 1 callersMethod_refine

(self, refine_steps, cond, shape, ddim_use_original_steps=False, callback=None

model/lib/latentdiff/ldm/models/diffusion/ddim.py:337

↓ 1 callersMethod_refine

(self, refine_steps, cond, shape, ddim_use_original_steps=False, callback=None

model/lib/stable_diffusion/ldm/models/diffusion/ddim.py:339

↓ 1 callersMethod_rotate_checkpoints

(self, use_mtime=False, output_dir=None)

trainer/trainer.py:428

↓ 1 callersMethod_save_checkpoint

(self, metrics=None)

trainer/trainer.py:453

↓ 1 callersFunction_secs2timedelta

convert seconds to hh:mm:ss.msec, msecs rounded to 2 decimals

trainer/trainer.py:109

↓ 1 callersMethod_sorted_checkpoints

( self, output_dir=None, checkpoint_prefix=PREFIX_CHECKPOINT_DIR, use_mtime=False )

trainer/trainer.py:404

↓ 1 callersFunctionadd_sharpening

USM sharpening. borrowed from real-ESRGAN Input image: I; Blurry image: B. 1. K = I + weight * (I - B) 2. Mask = 1 if abs(I - B) > thresho

model/lib/latentdiff/ldm/modules/image_degradation/bsrgan.py:299

↓ 1 callersFunctionadd_sharpening

USM sharpening. borrowed from real-ESRGAN Input image: I; Blurry image: B. 1. K = I + weight * (I - B) 2. Mask = 1 if abs(I - B) > thresho

model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan.py:299

↓ 1 callersFunctionanisotropic_Gaussian

generate an anisotropic Gaussian kernel Args: ksize : e.g., 15, kernel size theta : [0, pi], rotation angle range l1

model/lib/latentdiff/ldm/modules/image_degradation/bsrgan_light.py:65

↓ 1 callersFunctionanisotropic_Gaussian

generate an anisotropic Gaussian kernel Args: ksize : e.g., 15, kernel size theta : [0, pi], rotation angle range l1

model/lib/latentdiff/ldm/modules/image_degradation/bsrgan.py:65

↓ 1 callersFunctionanisotropic_Gaussian

generate an anisotropic Gaussian kernel Args: ksize : e.g., 15, kernel size theta : [0, pi], rotation angle range l1

model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan_light.py:65

↓ 1 callersFunctionanisotropic_Gaussian

generate an anisotropic Gaussian kernel Args: ksize : e.g., 15, kernel size theta : [0, pi], rotation angle range l1

model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan.py:65

↓ 1 callersFunctionaugment_img

Kai Zhang (github: https://github.com/cszn)

model/lib/latentdiff/ldm/modules/image_degradation/utils_image.py:380

↓ 1 callersFunctionaugment_img

Kai Zhang (github: https://github.com/cszn)

model/lib/stable_diffusion/ldm/modules/image_degradation/utils_image.py:380

↓ 1 callersFunctionavg_pool_nd

Create a 1D, 2D, or 3D average pooling module.

model/lib/latentdiff/ldm/modules/diffusionmodules/util.py:239

↓ 1 callersFunctionavg_pool_nd

Create a 1D, 2D, or 3D average pooling module.

model/lib/stable_diffusion/ldm/modules/diffusionmodules/util.py:239

↓ 1 callersFunctionavg_pool_nd

Create a 1D, 2D, or 3D average pooling module.

model/lib/ddpm_ddim/models/improved_ddpm/nn.py:42

↓ 1 callersMethodbackward

(ctx, *output_grads)

model/lib/ddpm_ddim/models/improved_ddpm/nn.py:153

↓ 1 callersFunctionbgr2ycbcr

bgr version of rgb2ycbcr only_y: only return Y channel Input: uint8, [0, 255] float, [0, 1]

model/lib/latentdiff/ldm/modules/image_degradation/utils_image.py:573

↓ 1 callersFunctionbgr2ycbcr

bgr version of rgb2ycbcr only_y: only return Y channel Input: uint8, [0, 255] float, [0, 1]

model/lib/stable_diffusion/ldm/modules/image_degradation/utils_image.py:573

↓ 1 callersMethodcalculate_adaptive_weight

(self, nll_loss, g_loss, last_layer=None)

model/lib/latentdiff/ldm/modules/losses/vqperceptual.py:85

↓ 1 callersMethodcalculate_adaptive_weight

(self, nll_loss, g_loss, last_layer=None)

model/lib/latentdiff/ldm/modules/losses/contperceptual.py:32

↓ 1 callersMethodcalculate_adaptive_weight

(self, nll_loss, g_loss, last_layer=None)

model/lib/stable_diffusion/ldm/modules/losses/vqperceptual.py:85

↓ 1 callersMethodcalculate_adaptive_weight

(self, nll_loss, g_loss, last_layer=None)

model/lib/stable_diffusion/ldm/modules/losses/contperceptual.py:32

↓ 1 callersMethodcheck_frequency

(self, check_idx)

model/lib/latentdiff/main.py:372

↓ 1 callersMethodcheck_frequency

(self, check_idx)

model/lib/stable_diffusion/main.py:372

↓ 1 callersFunctioncheck_overflow

(value)

model/lib/ddpm_ddim/models/improved_ddpm/fp16_util.py:235

↓ 1 callersFunctionchunk

(it, size)

model/lib/stable_diffusion/txt2img.py:20

↓ 1 callersFunctioncompute_eps

(xt, xt_next, t, t_next, models, sampling_type, b, logvars, eta, learn_sigma)

model/gan_wrapper/ddpm_ddim_wrapper.py:230

↓ 1 callersMethodcompute_eps

(self, xt, xt_next, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,

model/lib/latentdiff/ldm/models/diffusion/ddim.py:543

↓ 1 callersMethodcompute_eps

(self, xt, xt_next, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,

model/lib/stable_diffusion/ldm/models/diffusion/ddim.py:545

↓ 1 callersMethodconvert_to_fp16

Convert the torso of the model to float16.

model/lib/ddpm_ddim/models/improved_ddpm/unet.py:623

↓ 1 callersFunctionconvsample

(model, shape, return_intermediates=True, verbose=True, make_prog_row=False)

model/lib/latentdiff/sample_diffusion.py:53

↓ 1 callersFunctionconvsample_ddim

(model, steps, shape, eta=1.0 )

model/lib/latentdiff/sample_diffusion.py:67

↓ 1 callersFunctionconvsample_ddim

(model, cond, steps, shape, eta=1.0, callback=None, normals_sequence=None, mask=None, x0=N

model/lib/latentdiff/notebook_helpers.py:187

↓ 1 callersFunctionconvsample_ddim

(model, cond, steps, shape, eta=1.0, callback=None, normals_sequence=None, mask=None, x0=N

model/lib/stable_diffusion/notebook_helpers.py:188

↓ 1 callersFunctionconvsample_ddim

(model, steps, shape, x_T, eta)

model/gan_wrapper/latentdiff_wrapper.py:87

↓ 1 callersFunctionconvsample_ddim

(model, steps, shape, x_T, eta, eps_list, refine_steps)

model/gan_wrapper/latentdiff_stochastic_wrapper.py:56

↓ 1 callersFunctionconvsample_ddim_conditional

(model, steps, shape, x_T, skip_steps, eta, eps_list, scale, text)

model/gan_wrapper/latentdiff_stochastic_text_wrapper.py:41

↓ 1 callersFunctionconvsample_ddim_conditional

(model, steps, shape, x_T, eta, scale, class_label)

model/gan_wrapper/latentdiff_wrapper.py:69

↓ 1 callersFunctionconvsample_ddim_conditional

(model, steps, shape, x_T, skip_steps, eta, eps_list, scale, text)

model/gan_wrapper/stable_diffusion_stochastic_text_wrapper.py:39

↓ 1 callersFunctionconvsample_ddim_conditional

(model, steps, shape, x_T, eta, eps_list, scale, class_label, refine_steps)

model/gan_wrapper/latentdiff_stochastic_wrapper.py:82

↓ 1 callersFunctionconvsample_ddim_forward

(model, steps, shape, x0)

model/gan_wrapper/latentdiff_wrapper.py:95

↓ 1 callersFunctionconvsample_ddim_forward_conditional

(model, steps, shape, x0, scale, class_label)

model/gan_wrapper/latentdiff_wrapper.py:104

↓ 1 callersFunctioncount_params

(model, verbose=False)

model/lib/latentdiff/ldm/util.py:64

↓ 1 callersMethodcreate_optimizer

Setup the optimizer. We provide a reasonable default that works well. If you want to use something else, you can pass a tuple in the

trainer/trainer.py:204

↓ 1 callersMethodcreate_scheduler

Setup the scheduler. The optimizer of the trainer must have been set up before this method is called. Args: num_training

trainer/trainer.py:190

↓ 1 callersMethodddim_sampling

(self, cond, shape, x_T=None, ddim_use_original_steps=False, callb

model/lib/latentdiff/ldm/models/diffusion/ddim.py:286

↓ 1 callersMethodddim_sampling

(self, cond, shape, x_T=None, ddim_use_original_steps=False, callb

model/lib/stable_diffusion/ldm/models/diffusion/ddim.py:288

↓ 1 callersMethodddim_sampling_with_eps

(self, cond, shape, eps_list, x_T=None, ddim_use_original_steps=False,

model/lib/latentdiff/ldm/models/diffusion/ddim.py:393

↓ 1 callersMethodddim_sampling_with_eps

(self, cond, shape, eps_list, x_T=None, ddim_use_original_steps=False,

model/lib/stable_diffusion/ldm/models/diffusion/ddim.py:395

↓ 1 callersFunctionddpm_ddim_encoding

(model, steps, shape, eta, white_box_steps, x0)

model/gan_wrapper/latentdiff_stochastic_wrapper.py:154

↓ 1 callersFunctionddpm_ddim_encoding_conditional

(model, steps, shape, eta, white_box_steps, skip_steps, x0, scale, text)

model/gan_wrapper/latentdiff_stochastic_text_wrapper.py:79

↓ 1 callersFunctionddpm_ddim_encoding_conditional

(model, steps, shape, eta, white_box_steps, skip_steps, x0, scale, text)

model/gan_wrapper/stable_diffusion_stochastic_text_wrapper.py:77

↓ 1 callersFunctionddpm_ddim_encoding_conditional

(model, steps, shape, eta, white_box_steps, x0, scale, class_label)

model/gan_wrapper/latentdiff_stochastic_wrapper.py:163

↓ 1 callersFunctiondenoising_step_with_eps

(xt, eps, t, t_next, *, models, logvars,

model/gan_wrapper/ddpm_ddim_wrapper.py:114

↓ 1 callersFunctiondict2namespace

(config)

model/gan_wrapper/ddpm_ddim_wrapper.py:103

↓ 1 callersFunctiondownload_models

(mode)

model/lib/latentdiff/notebook_helpers.py:19

↓ 1 callersFunctiondownload_models

(mode)

model/lib/stable_diffusion/notebook_helpers.py:19

↓ 1 callersMethoddumpkvs

(self)

model/lib/ddpm_ddim/models/improved_ddpm/logger.py:311

↓ 1 callersMethodencode

(self, text)

model/lib/latentdiff/ldm/modules/encoders/modules.py:96

↓ 1 callersMethodencode

(self, x)

model/lib/latentdiff/ldm/models/autoencoder.py:324

↓ 1 callersMethodencode

(self, text)

model/lib/stable_diffusion/ldm/modules/encoders/modules.py:100

↓ 1 callersMethodencode

(self, x)

model/lib/stable_diffusion/ldm/models/autoencoder.py:324

↓ 1 callersMethodencode_with_pretrained

(self,x)

model/lib/latentdiff/ldm/modules/diffusionmodules/model.py:815

↓ 1 callersMethodencode_with_pretrained

(self,x)

model/lib/stable_diffusion/ldm/modules/diffusionmodules/model.py:815

↓ 1 callersFunctionequals

(val)

model/lib/latentdiff/ldm/modules/x_transformer.py:76

↓ 1 callersFunctionequals

(val)

model/lib/stable_diffusion/ldm/modules/x_transformer.py:76

↓ 1 callersMethodforward

(self, x)

model/lib/ddpm_ddim/models/improved_ddpm/nn.py:13

↓ 1 callersMethodfreeze

(self)

model/lib/stable_diffusion/ldm/modules/encoders/modules.py:146

↓ 1 callersFunctionfspecial_gaussian

(hsize, sigma)

model/lib/latentdiff/ldm/modules/image_degradation/bsrgan_light.py:187

↓ 1 callersFunctionfspecial_gaussian

(hsize, sigma)

model/lib/latentdiff/ldm/modules/image_degradation/bsrgan.py:187

↓ 1 callersFunctionfspecial_gaussian

(hsize, sigma)

model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan_light.py:187

↓ 1 callersFunctionfspecial_gaussian

(hsize, sigma)

model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan.py:187

↓ 1 callersFunctionfspecial_laplacian

(alpha)

model/lib/latentdiff/ldm/modules/image_degradation/bsrgan_light.py:201

↓ 1 callersFunctionfspecial_laplacian

(alpha)

model/lib/latentdiff/ldm/modules/image_degradation/bsrgan.py:201

↓ 1 callersFunctionfspecial_laplacian

(alpha)

model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan_light.py:201

↓ 1 callersFunctionfspecial_laplacian

(alpha)

model/lib/stable_diffusion/ldm/modules/image_degradation/bsrgan.py:201

↓ 1 callersMethodgenerate

(self, z_ensemble, decode_text)

model/gan_wrapper/latentdiff_stochastic_text_wrapper.py:143

↓ 1 callersMethodgenerate

(self, z, class_label)

model/gan_wrapper/latentdiff_wrapper.py:205

↓ 1 callersMethodgenerate

(self, z_ensemble, decode_text)

model/gan_wrapper/stable_diffusion_stochastic_text_wrapper.py:142

↓ 1 callersMethodgenerate

(self, z, class_label)

model/gan_wrapper/latentdiff_stochastic_wrapper.py:236

↓ 1 callersMethodgenerate

(self, z, class_label)

model/gan_wrapper/ddpm_ddim_wrapper.py:392

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