Functions — github.com/DreamEditBenchTeam/DreamEdit

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Functions598 in github.com/DreamEditBenchTeam/DreamEdit

⨍ Functions 598◇ Types & classes 104

↓ 1 callersFunctionget_stable_diffusion_inpaint_pipeline

(device)

src/pipelines/inpainting_pipelines.py:40

↓ 1 callersFunctionget_timestamp

()

src/ldm/modules/image_degradation/utils_image.py:33

↓ 1 callersFunctionget_timestep_embedding

This matches the implementation in Denoising Diffusion Probabilistic Models: From Fairseq. Build sinusoidal embeddings. This matches

src/ldm/modules/diffusionmodules/model.py:12

↓ 1 callersMethodget_transform

(self)

src/metrics/dino_vit.py:11

↓ 1 callersMethodget_x_noisy

(self, x, t, noise=None)

src/ldm/models/diffusion/classifier.py:110

↓ 1 callersFunctiongm_blur_kernel

(mean, cov, size=15)

src/ldm/modules/image_degradation/bsrgan_light.py:86

↓ 1 callersFunctiongm_blur_kernel

(mean, cov, size=15)

src/ldm/modules/image_degradation/bsrgan.py:86

↓ 1 callersFunctionimread_uint

(path, n_channels=3)

src/ldm/modules/image_degradation/utils_image.py:185

↓ 1 callersFunctionimssave

imgs: list, N images of size WxHxC

src/ldm/modules/image_degradation/utils_image.py:112

↓ 1 callersMethodinit_

(self)

src/ldm/modules/x_transformer.py:31

↓ 1 callersMethodinit_

(self)

src/ldm/modules/x_transformer.py:595

↓ 1 callersMethodinit_from_ckpt

(self, path, ignore_keys=list())

src/ldm/models/autoencoder.py:78

↓ 1 callersMethodinit_from_ckpt

(self, path, ignore_keys=list())

src/ldm/models/autoencoder.py:313

↓ 1 callersMethodinit_from_ckpt

(self, path, ignore_keys=list(), only_model=False)

src/ldm/models/diffusion/classifier.py:70

↓ 1 callersFunctioninpaint_text_gligen

(pipe, prompt, background_path, bounding_box, gligen_phrase, config)

src/pipelines/inpainting_pipelines.py:17

↓ 1 callersMethodinstantiate_cond_stage

(self, config)

src/ldm/models/diffusion/ddpm.py:509

↓ 1 callersMethodinstantiate_first_stage

(self, config)

src/ldm/models/diffusion/ddpm.py:502

↓ 1 callersMethodinstantiate_pretrained

(self, config)

src/ldm/modules/diffusionmodules/model.py:807

↓ 1 callersFunctionis_image_file

(filename)

src/ldm/modules/image_degradation/utils_image.py:29

↓ 1 callersFunctionisimage

src/ldm/modules/distributions/distributions.py:39

↓ 1 callersMethodload_classifier

(self, ckpt_path, pool)

src/ldm/models/diffusion/classifier.py:95

↓ 1 callersMethodload_diffusion

(self)

src/ldm/models/diffusion/classifier.py:88

↓ 1 callersFunctionload_img

(path, W, H)

src/generate_new.py:80

↓ 1 callersMethodlog_images

(self, batch, N=8, n_row=2, sample=True, return_keys=None, **kwargs)

src/ldm/models/diffusion/ddpm.py:378

↓ 1 callersFunctionmain

(args)

src/clip_img_ret.py:55

↓ 1 callersFunctionmake_beta_schedule

(schedule, n_timestep, linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3)

src/ldm/modules/diffusionmodules/util.py:21

↓ 1 callersMethodmake_cond_schedule

(self, )

src/ldm/models/diffusion/ddpm.py:471

↓ 1 callersMethodmake_schedule

(self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0., verbose=True)

src/ldm/models/diffusion/ddim.py:25

↓ 1 callersMethodmake_schedule

(self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0., verbose=True)

src/ldm/models/diffusion/plms.py:24

↓ 1 callersFunctionmask_closing

param: mask in size [H, W] k = kernel number return: mask in size [H, W]

src/utils/mask_helper.py:70

↓ 1 callersFunctionmask_closing_half

param: mask in size [H, W] k = kernel number return: mask in size [H, W]

src/utils/mask_helper.py:85

↓ 1 callersFunctionmask_dilation

param: mask in size [H, W] k = kernel number return: mask in size [H, W]

src/utils/mask_helper.py:55

↓ 1 callersFunctionmax_neg_value

(tensor)

src/ldm/modules/x_transformer.py:82

↓ 1 callersFunctionmean_flat

Take the mean over all non-batch dimensions.

src/ldm/modules/diffusionmodules/util.py:192

↓ 1 callersFunctionmeasure_perplexity

(predicted_indices, n_embed)

src/ldm/modules/losses/vqperceptual.py:26

↓ 1 callersMethodmultistep_dpm_solver_second_update

Multistep solver DPM-Solver-2 from time `t_prev_list[-1]` to time `t`. Args: x: A pytorch tensor. The initial value at t

src/ldm/models/diffusion/dpm_solver/dpm_solver.py:755

↓ 1 callersMethodmultistep_dpm_solver_third_update

Multistep solver DPM-Solver-3 from time `t_prev_list[-1]` to time `t`. Args: x: A pytorch tensor. The initial value at t

src/ldm/models/diffusion/dpm_solver/dpm_solver.py:812

↓ 1 callersFunctionnormal_kl

source: https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/losses.py#L12 Compute the K

src/ldm/modules/distributions/distributions.py:65

↓ 1 callersFunctionnot_equals

(val)

src/ldm/modules/x_transformer.py:70

↓ 1 callersMethodp_losses

(self, x_start, t, noise=None)

src/ldm/models/diffusion/ddpm.py:294

↓ 1 callersMethodp_losses

(self, x_start, cond, t, noise=None)

src/ldm/models/diffusion/ddpm.py:1012

↓ 1 callersMethodp_mean_variance

(self, x, t, clip_denoised: bool)

src/ldm/models/diffusion/ddpm.py:231

↓ 1 callersMethodp_mean_variance

(self, x, c, t, clip_denoised: bool, return_codebook_ids=False, quantize_denoised=False,

src/ldm/models/diffusion/ddpm.py:1047

↓ 1 callersMethodp_sample

(self, x, t, clip_denoised=True, repeat_noise=False)

src/ldm/models/diffusion/ddpm.py:244

↓ 1 callersMethodp_sample_loop

(self, shape, return_intermediates=False)

src/ldm/models/diffusion/ddpm.py:253

↓ 1 callersMethodp_sample_loop

(self, cond, shape, return_intermediates=False, x_T=None, verbose=True, callback=None, t

src/ldm/models/diffusion/ddpm.py:1166

↓ 1 callersMethodp_sample_plms

(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,

src/ldm/models/diffusion/plms.py:173

↓ 1 callersFunctionparse_args

(input_args=None)

src/clip_img_ret.py:11

↓ 1 callersFunctionpatches_from_image

(img, p_size=512, p_overlap=64, p_max=800)

src/ldm/modules/image_degradation/utils_image.py:93

↓ 1 callersMethodplms_sampling

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

src/ldm/models/diffusion/plms.py:115

↓ 1 callersMethodpreprocess

(self, x)

src/ldm/modules/encoders/modules.py:216

↓ 1 callersMethodprogressive_denoising

(self, cond, shape, verbose=True, callback=None, quantize_denoised=False, img_ca

src/ldm/models/diffusion/ddpm.py:1110

↓ 1 callersMethodq_mean_variance

Get the distribution q(x_t | x_0). :param x_start: the [N x C x ...] tensor of noiseless inputs. :param t: the number of diff

src/ldm/models/diffusion/ddpm.py:204

↓ 1 callersFunctionrandom_crop

(lq, hq, sf=4, lq_patchsize=64)

src/ldm/modules/image_degradation/bsrgan_light.py:431

↓ 1 callersMethodregister_buffer

(self, name, attr)

src/ldm/models/diffusion/dpm_solver/sampler.py:15

↓ 1 callersFunctionreplace_background

( src_img, img_to_edit, obj_class, first_iter_obj_mask, lang_sam_model

src/iterate_generate.py:61

↓ 1 callersFunctionreplacement

( src_img_path, obj_img_path, # Useful only for copy-paste obj_class, lang_sa

src/iterate_generate.py:388

↓ 1 callersMethodreset_noise_accs

(self)

src/ldm/models/diffusion/classifier.py:202

↓ 1 callersMethodsample

(self, S, batch_size, shape, conditioning=None,

src/ldm/models/diffusion/ddim.py:57

↓ 1 callersMethodsample

(self, cond, batch_size=16, return_intermediates=False, x_T=None, verbose=True, timesteps=None,

src/ldm/models/diffusion/ddpm.py:1217

↓ 1 callersMethodschedule

(self, n, **kwargs)

src/ldm/lr_scheduler.py:17

↓ 1 callersMethodschedule

(self, n, **kwargs)

src/ldm/lr_scheduler.py:59

↓ 1 callersMethodstep

(self)

src/iterate_generate.py:48

↓ 1 callersFunctionsynset2idx

(path_to_yaml="data/index_synset.yaml")

src/ldm/data/imagenet.py:20

↓ 1 callersMethodwrite_logs

(self, loss, logits, targets)

src/ldm/models/diffusion/classifier.py:162

↓ 1 callersFunctionzero_module

Zero out the parameters of a module and return it.

src/ldm/modules/attention.py:67

Method__call__

(self, n, **kwargs)

src/ldm/lr_scheduler.py:32

Method__call__

(self, n, **kwargs)

src/ldm/lr_scheduler.py:77

Method__getitem__

(self, i)

src/ldm/data/imagenet.py:42

Method__getitem__

(self, i)

src/ldm/data/imagenet.py:339

Method__getitem__

(self, i)

src/ldm/data/lsun.py:39

Method__init__

(self, schedule_config, total_iterations)

src/iterate_generate.py:32

Method__init__

(self, device="cuda")

src/metrics/clip_vit.py:6

Method__init__

(self, device="cuda")

src/metrics/dino_vit.py:6

Method__init__

(self, device="cuda", processor_weights = "Salesforce/blip-image-captioning-base", conditional_generation_weig

src/pipelines/imagecaption_pipelines.py:7

Method__init__

(self, device="cuda")

src/pipelines/extract_object_pipeline.py:24

Method__init__

(self, warm_up_steps, lr_min, lr_max, lr_start, max_decay_steps, verbosity_interval=0)

src/ldm/lr_scheduler.py:8

Method__init__

(self, warm_up_steps, f_min, f_max, f_start, cycle_lengths, verbosity_interval=0)

src/ldm/lr_scheduler.py:41

Method__init__

(self, model, decay=0.9999, use_num_upates=True)

src/ldm/modules/ema.py:6

Method__init__

(self, dim, max_seq_len)

src/ldm/modules/x_transformer.py:26

Method__init__

(self, dim)

src/ldm/modules/x_transformer.py:40

Method__init__

(self, fn)

src/ldm/modules/x_transformer.py:129

Method__init__

(self, dim, eps=1e-5)

src/ldm/modules/x_transformer.py:140

Method__init__

(self, dim, eps=1e-8)

src/ldm/modules/x_transformer.py:152

Method__init__

(self, dim)

src/ldm/modules/x_transformer.py:169

Method__init__

(self, dim_in, dim_out)

src/ldm/modules/x_transformer.py:185

Method__init__

(self, dim, dim_out=None, mult=4, glu=False, dropout=0.)

src/ldm/modules/x_transformer.py:195

Method__init__

( self, dim, dim_head=DEFAULT_DIM_HEAD, heads=8, c

src/ldm/modules/x_transformer.py:216

Method__init__

( self, dim, depth, heads=8, causal=False,

src/ldm/modules/x_transformer.py:371

Method__init__

(self, **kwargs)

src/ldm/modules/x_transformer.py:542

Method__init__

( self, *, num_tokens, max_seq_len, attn_layers,

src/ldm/modules/x_transformer.py:549

Method__init__

(self, dim, dim_out=None, mult=4, glu=False, dropout=0.)

src/ldm/modules/attention.py:48

Method__init__

(self, dim, heads=4, dim_head=32)

src/ldm/modules/attention.py:81

Method__init__

(self, in_channels)

src/ldm/modules/attention.py:100

Method__init__

(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0.)

src/ldm/modules/attention.py:153

Method__init__

(self, dim, n_heads, d_head, dropout=0., context_dim=None, gated_ff=True, checkpoint=True)

src/ldm/modules/attention.py:197

Method__init__

(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None)

src/ldm/modules/attention.py:226

Method__init__

( self, spacial_dim: int, embed_dim: int, num_heads_channels: int, out

src/ldm/modules/diffusionmodules/openaimodel.py:37

Method__init__

(self, channels, out_channels=None, ks=5)

src/ldm/modules/diffusionmodules/openaimodel.py:123

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