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Functions1,626 in github.com/LuChengTHU/dpm-solver

Method__init__
(self, dir)
examples/ddpm_and_guided-diffusion/models/guided_diffusion/logger.py:155
Method__init__
(self, dir, output_formats, comm=None)
examples/ddpm_and_guided-diffusion/models/guided_diffusion/logger.py:337
Method__init__
(self, channels, use_conv, dims=2)
examples/ddpm_and_guided-diffusion/models/improved_ddpm/unet.py:91
Method__init__
( self, channels, emb_channels, dropout, out_channels=None, us
examples/ddpm_and_guided-diffusion/models/improved_ddpm/unet.py:122
Method__init__
(self, channels, num_heads=1, use_checkpoint=False)
examples/ddpm_and_guided-diffusion/models/improved_ddpm/unet.py:208
Method__init__
( self, in_channels, model_channels, out_channels, num_res_blocks,
examples/ddpm_and_guided-diffusion/models/improved_ddpm/unet.py:301
Method__init__
(self, in_channels, *args, **kwargs)
examples/ddpm_and_guided-diffusion/models/improved_ddpm/unet.py:534
Method__init__
Create a wrapper class for the forward SDE (VP type). *** Update: We support discrete-time diffusion models by implementing a picewis
examples/score_sde_pytorch/dpm_solver.py:7
Method__init__
Construct a DPM-Solver. We support both DPM-Solver (`algorithm_type="dpmsolver"`) and DPM-Solver++ (`algorithm_type="dpmsolver++"`).
examples/score_sde_pytorch/dpm_solver.py:346
Method__init__
(self)
examples/score_sde_pytorch/sde_lib.py:85
Method__init__
Construct a Variance Preserving SDE. Args: beta_min: value of beta(0) beta_max: value of beta(1) N: number of discretization st
examples/score_sde_pytorch/sde_lib.py:113
Method__init__
Construct the sub-VP SDE that excels at likelihoods. Args: beta_min: value of beta(0) beta_max: value of beta(1) N: number of d
examples/score_sde_pytorch/sde_lib.py:168
Method__init__
Construct a Variance Exploding SDE. Args: sigma_min: smallest sigma. sigma_max: largest sigma. N: number of discretization step
examples/score_sde_pytorch/sde_lib.py:208
Method__init__
(self, sde, score_fn, snr, n_steps)
examples/score_sde_pytorch/sampling.py:171
Method__init__
(self, sde, score_fn, probability_flow=False)
examples/score_sde_pytorch/sampling.py:195
Method__init__
(self, sde, score_fn, probability_flow=False)
examples/score_sde_pytorch/sampling.py:209
Method__init__
(self, sde, score_fn, probability_flow=False)
examples/score_sde_pytorch/sampling.py:224
Method__init__
(self, sde, score_fn, probability_flow=False)
examples/score_sde_pytorch/sampling.py:263
Method__init__
(self, sde, score_fn, snr, n_steps)
examples/score_sde_pytorch/sampling.py:272
Method__init__
(self, sde, score_fn, snr, n_steps)
examples/score_sde_pytorch/sampling.py:309
Method__init__
(self, sde, score_fn, snr, n_steps)
examples/score_sde_pytorch/sampling.py:343
Method__init__
(self, channel, negative_slope=0.2, scale=2 ** 0.5)
examples/score_sde_pytorch/op/fused_act.py:75
Method__init__
(self)
examples/score_sde_pytorch/models/layers.py:96
Method__init__
(self, features, n_stages, act=nn.ReLU(), maxpool=True)
examples/score_sde_pytorch/models/layers.py:134
Method__init__
(self, features, n_stages, num_classes, normalizer, act=nn.ReLU())
examples/score_sde_pytorch/models/layers.py:158
Method__init__
(self, features, n_blocks, n_stages, act=nn.ReLU())
examples/score_sde_pytorch/models/layers.py:184
Method__init__
(self, features, n_blocks, n_stages, num_classes, normalizer, act=nn.ReLU())
examples/score_sde_pytorch/models/layers.py:208
Method__init__
(self, in_planes, features)
examples/score_sde_pytorch/models/layers.py:235
Method__init__
(self, in_planes, features, num_classes, normalizer)
examples/score_sde_pytorch/models/layers.py:254
Method__init__
(self, in_planes, features, act=nn.ReLU(), start=False, end=False, maxpool=True)
examples/score_sde_pytorch/models/layers.py:278
Method__init__
(self, in_planes, features, num_classes, normalizer, act=nn.ReLU(), start=False, end=False)
examples/score_sde_pytorch/models/layers.py:314
Method__init__
(self, input_dim, output_dim, kernel_size=3, biases=True, adjust_padding=False)
examples/score_sde_pytorch/models/layers.py:352
Method__init__
(self, input_dim, output_dim, kernel_size=3, biases=True)
examples/score_sde_pytorch/models/layers.py:373
Method__init__
(self, input_dim, output_dim, kernel_size=3, biases=True)
examples/score_sde_pytorch/models/layers.py:385
Method__init__
(self, input_dim, output_dim, num_classes, resample=1, act=nn.ELU(), normalization=ConditionalI
examples/score_sde_pytorch/models/layers.py:398
Method__init__
(self, input_dim, output_dim, resample=None, act=nn.ELU(), normalization=nn.InstanceNorm2d, adj
examples/score_sde_pytorch/models/layers.py:454
Method__init__
(self, channels)
examples/score_sde_pytorch/models/layers.py:560
Method__init__
(self, channels, with_conv=False)
examples/score_sde_pytorch/models/layers.py:585
Method__init__
(self, channels, with_conv=False)
examples/score_sde_pytorch/models/layers.py:600
Method__init__
(self, act, in_ch, out_ch=None, temb_dim=None, conv_shortcut=False, dropout=0.1)
examples/score_sde_pytorch/models/layers.py:621
Method__init__
Args: parameters: Iterable of `torch.nn.Parameter`; usually the result of `model.parameters()`. decay: The exponential decay.
examples/score_sde_pytorch/models/ema.py:15
Method__init__
(self, config)
examples/score_sde_pytorch/models/ddpm.py:41
Method__init__
(self, config)
examples/score_sde_pytorch/models/ncsnpp.py:38
Method__init__
(self, embedding_size=256, scale=1.0)
examples/score_sde_pytorch/models/layerspp.py:35
Method__init__
(self, channels, skip_rescale=False, init_scale=0.)
examples/score_sde_pytorch/models/layerspp.py:65
Method__init__
(self, in_ch=None, out_ch=None, with_conv=False, fir=False, fir_kernel=(1, 3, 3, 1))
examples/score_sde_pytorch/models/layerspp.py:95
Method__init__
(self, in_ch=None, out_ch=None, with_conv=False, fir=False, fir_kernel=(1, 3, 3, 1))
examples/score_sde_pytorch/models/layerspp.py:130
Method__init__
(self, act, in_ch, out_ch=None, temb_dim=None, conv_shortcut=False, dropout=0.1, skip_rescale=F
examples/score_sde_pytorch/models/layerspp.py:169
Method__init__
(self, act, in_ch, out_ch=None, temb_dim=None, up=False, down=False, dropout=0.1, fir=False, fi
examples/score_sde_pytorch/models/layerspp.py:213
Method__init__
(self, config)
examples/score_sde_pytorch/models/ncsnv2.py:45
Method__init__
(self, config)
examples/score_sde_pytorch/models/ncsnv2.py:224
Method__init__
(self, config)
examples/score_sde_pytorch/models/ncsnv2.py:318
Method__init__
(self, num_features, num_classes, bias=True)
examples/score_sde_pytorch/models/normalization.py:44
Method__init__
(self, num_features, num_classes, bias=True)
examples/score_sde_pytorch/models/normalization.py:69
Method__init__
(self, num_features, num_classes, bias=False)
examples/score_sde_pytorch/models/normalization.py:94
Method__init__
(self, num_features, bias=False)
examples/score_sde_pytorch/models/normalization.py:111
Method__init__
(self, num_features, num_classes, bias=True)
examples/score_sde_pytorch/models/normalization.py:127
Method__init__
(self, num_features, bias=True)
examples/score_sde_pytorch/models/normalization.py:158
Method__init__
(self, num_features, num_classes, bias=True)
examples/score_sde_pytorch/models/normalization.py:187
Method__init__
(self, in_ch, out_ch, kernel, up=False, down=False, resample_kernel=(1, 3, 3, 1),
examples/score_sde_pytorch/models/up_or_down_sampling.py:26
Method__init__
(self, dataset)
examples/stable-diffusion/main.py:136
Method__init__
(self, batch_size, train=None, validation=None, test=None, predict=None, wrap=False, num_work
examples/stable-diffusion/main.py:163
Method__init__
(self, resume, now, logdir, ckptdir, cfgdir, config, lightning_config)
examples/stable-diffusion/main.py:241
Method__init__
(self, database, retriever_version='ViT-L/14')
examples/stable-diffusion/scripts/knn2img.py:62
Method__init__
(self, warm_up_steps, lr_min, lr_max, lr_start, max_decay_steps, verbosity_interval=0)
examples/stable-diffusion/ldm/lr_scheduler.py:8
Method__init__
(self, warm_up_steps, f_min, f_max, f_start, cycle_lengths, verbosity_interval=0)
examples/stable-diffusion/ldm/lr_scheduler.py:41
Method__init__
(self, model, decay=0.9999, use_num_upates=True)
examples/stable-diffusion/ldm/modules/ema.py:6
Method__init__
(self, dim, max_seq_len)
examples/stable-diffusion/ldm/modules/x_transformer.py:26
Method__init__
(self, dim)
examples/stable-diffusion/ldm/modules/x_transformer.py:40
Method__init__
(self, fn)
examples/stable-diffusion/ldm/modules/x_transformer.py:129
Method__init__
(self, dim, eps=1e-5)
examples/stable-diffusion/ldm/modules/x_transformer.py:140
Method__init__
(self, dim, eps=1e-8)
examples/stable-diffusion/ldm/modules/x_transformer.py:152
Method__init__
(self, dim)
examples/stable-diffusion/ldm/modules/x_transformer.py:169
Method__init__
(self, dim_in, dim_out)
examples/stable-diffusion/ldm/modules/x_transformer.py:185
Method__init__
(self, dim, dim_out=None, mult=4, glu=False, dropout=0.)
examples/stable-diffusion/ldm/modules/x_transformer.py:195
Method__init__
( self, dim, dim_head=DEFAULT_DIM_HEAD, heads=8, c
examples/stable-diffusion/ldm/modules/x_transformer.py:216
Method__init__
( self, dim, depth, heads=8, causal=False,
examples/stable-diffusion/ldm/modules/x_transformer.py:371
Method__init__
(self, **kwargs)
examples/stable-diffusion/ldm/modules/x_transformer.py:542
Method__init__
( self, *, num_tokens, max_seq_len, attn_layers,
examples/stable-diffusion/ldm/modules/x_transformer.py:549
Method__init__
(self, dim, dim_out=None, mult=4, glu=False, dropout=0.)
examples/stable-diffusion/ldm/modules/attention.py:48
Method__init__
(self, dim, heads=4, dim_head=32)
examples/stable-diffusion/ldm/modules/attention.py:81
Method__init__
(self, in_channels)
examples/stable-diffusion/ldm/modules/attention.py:100
Method__init__
(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0.)
examples/stable-diffusion/ldm/modules/attention.py:153
Method__init__
(self, dim, n_heads, d_head, dropout=0., context_dim=None, gated_ff=True, checkpoint=True)
examples/stable-diffusion/ldm/modules/attention.py:197
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None)
examples/stable-diffusion/ldm/modules/attention.py:226
Method__init__
( self, spacial_dim: int, embed_dim: int, num_heads_channels: int, out
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:37
Method__init__
(self, channels, out_channels=None, ks=5)
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:123
Method__init__
(self, channels, use_conv, dims=2, out_channels=None,padding=1)
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:143
Method__init__
( self, channels, emb_channels, dropout, out_channels=None, us
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:179
Method__init__
( self, channels, num_heads=1, num_head_channels=-1, use_checkpoint=Fa
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:285
Method__init__
(self, n_heads)
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:352
Method__init__
(self, n_heads)
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:384
Method__init__
( self, image_size, in_channels, model_channels, out_channels,
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:443
Method__init__
( self, image_size, in_channels, model_channels, out_channels,
examples/stable-diffusion/ldm/modules/diffusionmodules/openaimodel.py:751
Method__init__
(self, c_concat_config, c_crossattn_config)
examples/stable-diffusion/ldm/modules/diffusionmodules/util.py:253
Method__init__
(self, in_channels, with_conv)
examples/stable-diffusion/ldm/modules/diffusionmodules/model.py:43
Method__init__
(self, in_channels, with_conv)
examples/stable-diffusion/ldm/modules/diffusionmodules/model.py:61
Method__init__
(self, *, in_channels, out_channels=None, conv_shortcut=False, dropout, temb_channels=512)
examples/stable-diffusion/ldm/modules/diffusionmodules/model.py:83
Method__init__
(self, in_channels)
examples/stable-diffusion/ldm/modules/diffusionmodules/model.py:146
Method__init__
(self, in_channels)
examples/stable-diffusion/ldm/modules/diffusionmodules/model.py:151
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