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

⨍ Functions 1,626◇ Types & classes 286
↓ 5 callersFunctionddpm_conv3x3
3x3 convolution with DDPM initialization.
examples/score_sde_jax/models/layers.py:95
↓ 5 callersMethoddecode
(self, quant)
examples/stable-diffusion/ldm/models/autoencoder.py:107
↓ 5 callersFunctiondecouple
(inputs)
examples/score_sde_pytorch/controllable_generation.py:114
↓ 5 callersFunctiondecouple
(inputs)
examples/score_sde_jax/controllable_generation.py:131
↓ 5 callersFunctiondefault
(val, d)
examples/stable-diffusion/ldm/util.py:57
↓ 5 callersFunctiondownload
(url, local_path, chunk_size=1024)
examples/ddpm_and_guided-diffusion/functions/ckpt_util.py:37
↓ 5 callersMethodforward
(self, x)
examples/stable-diffusion/ldm/modules/diffusionmodules/util.py:210
↓ 5 callersMethodget_input
(self, batch, k)
examples/stable-diffusion/ldm/models/diffusion/ddpm.py:329
↓ 5 callersFunctionget_normalization
Obtain normalization modules from the config file.
examples/score_sde_jax/models/normalization.py:23
↓ 5 callersMethodget_time_steps
Compute the intermediate time steps for sampling. Args: skip_type: A `str`. The type for the spacing of the time steps. We suppor
dpm_solver_jax.py:409
↓ 5 callersMethodget_time_steps
Compute the intermediate time steps for sampling. Args: skip_type: A `str`. The type for the spacing of the time steps. We suppor
dpm_solver_pytorch.py:453
↓ 5 callersMethodget_time_steps
Compute the intermediate time steps for sampling. Args: skip_type: A `str`. The type for the spacing of the time steps. We suppor
examples/ddpm_and_guided-diffusion/dpm_solver/sampler.py:453
↓ 5 callersMethodget_time_steps
Compute the intermediate time steps for sampling. Args: skip_type: A `str`. The type for the spacing of the time steps. We suppor
examples/score_sde_pytorch/dpm_solver.py:461
↓ 5 callersMethodget_time_steps
Compute the intermediate time steps for sampling. Args: skip_type: A `str`. The type for the spacing of the time steps. We suppor
examples/stable-diffusion/ldm/models/diffusion/dpm_solver/dpm_solver.py:461
↓ 5 callersMethodget_time_steps
Compute the intermediate time steps for sampling. Args: skip_type: A `str`. The type for the spacing of the time steps. We suppor
examples/score_sde_jax/dpm_solver.py:409
↓ 5 callersMethodinverse_lambda
Compute the continuous-time label t in [0, T] of a given half-logSNR lambda_t.
dpm_solver_jax.py:159
↓ 5 callersMethodinverse_lambda
Compute the continuous-time label t in [0, T] of a given half-logSNR lambda_t.
dpm_solver_pytorch.py:156
↓ 5 callersMethodinverse_lambda
Compute the continuous-time label t in [0, T] of a given half-logSNR lambda_t.
examples/ddpm_and_guided-diffusion/dpm_solver/sampler.py:156
↓ 5 callersMethodinverse_lambda
Compute the continuous-time label t in [0, T] of a given half-logSNR lambda_t.
examples/score_sde_pytorch/dpm_solver.py:159
↓ 5 callersMethodinverse_lambda
Compute the continuous-time label t in [0, T] of a given half-logSNR lambda_t.
examples/stable-diffusion/ldm/models/diffusion/dpm_solver/dpm_solver.py:159
↓ 5 callersMethodinverse_lambda
Compute the continuous-time label t in [0, T] of a given half-logSNR lambda_t.
examples/score_sde_jax/dpm_solver.py:159
↓ 5 callersFunctionlinear
Create a linear module.
examples/ddpm_and_guided-diffusion/models/guided_diffusion/nn.py:35
↓ 5 callersFunctionlinear
Create a linear module.
examples/stable-diffusion/ldm/modules/diffusionmodules/util.py:231
↓ 5 callersFunctionmodel_fn
The noise predicition model function that is used for DPM-Solver.
examples/ddpm_and_guided-diffusion/dpm_solver/sampler.py:309
↓ 5 callersFunctionnonlinearity
(x)
examples/ddpm_and_guided-diffusion/models/diffusion.py:27
↓ 5 callersMethodprior_sampling
Generate one sample from the prior distribution, $p_T(x)$.
examples/score_sde_pytorch/sde_lib.py:35
↓ 5 callersMethodquantize
(self, x, *args, **kwargs)
examples/stable-diffusion/ldm/models/autoencoder.py:437
↓ 5 callersFunctionscore_fn
(x, t)
examples/score_sde_pytorch/models/utils.py:173
↓ 5 callersMethodsde
(self, x, t)
examples/score_sde_pytorch/sde_lib.py:26
↓ 5 callersMethodsde
(self, x, t)
examples/score_sde_jax/sde_lib.py:28
↓ 5 callersMethodto_rgb
(self, x)
examples/stable-diffusion/ldm/models/autoencoder.py:255
↓ 5 callersMethodtrain
(self)
examples/ddpm_and_guided-diffusion/runners/diffusion.py:159
↓ 5 callersMethodupdate
(self, module)
examples/ddpm_and_guided-diffusion/models/ema.py:16
↓ 4 callersFunctionNormalize
(in_channels)
examples/ddpm_and_guided-diffusion/models/diffusion.py:32
↓ 4 callersMethod__init__
Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return featur
examples/ddpm_and_guided-diffusion/evaluate/inception.py:31
↓ 4 callersMethod__init__
(self, config)
examples/ddpm_and_guided-diffusion/models/diffusion.py:193
↓ 4 callersMethod__init__
Imagenet Superresolution Dataloader Performs following ops in order: 1. crops a crop of size s from image either as random o
examples/stable-diffusion/ldm/data/imagenet.py:273
↓ 4 callersMethod_compute_cond_module
(self, module, x)
examples/score_sde_pytorch/models/ncsnv2.py:101
↓ 4 callersMethod_compute_cond_module
(self, module, x, y)
examples/score_sde_pytorch/models/ncsnv2.py:191
↓ 4 callersFunction_setup_kernel
(k)
examples/score_sde_pytorch/models/up_or_down_sampling.py:181
↓ 4 callersFunction_setup_kernel
(k)
examples/score_sde_jax/models/up_or_down_sampling.py:319
↓ 4 callersFunction_simple_upfirdn_2d
(x, k, up=1, down=1, pad0=0, pad1=0, data_format='NCHW')
examples/score_sde_jax/models/up_or_down_sampling.py:297
↓ 4 callersFunctionactivation
(x, train, apply_relu=True, name='')
examples/score_sde_jax/models/wideresnet_noise_conditional.py:199
↓ 4 callersFunctionadd_Gaussian_noise
(img, noise_level1=2, noise_level2=25)
examples/stable-diffusion/ldm/modules/image_degradation/bsrgan.py:369
↓ 4 callersFunctionadd_JPEG_noise
(img)
examples/stable-diffusion/ldm/modules/image_degradation/bsrgan_light.py:422
↓ 4 callersFunctionadopt_weight
(weight, global_step, threshold=0, value=0.)
examples/stable-diffusion/ldm/modules/losses/vqperceptual.py:20
↓ 4 callersFunctioncalculate_weights_indices
(in_length, out_length, scale, kernel, kernel_width, antialiasing)
examples/stable-diffusion/ldm/modules/image_degradation/utils_image.py:708
↓ 4 callersMethodcompute_top_k
(self, logits, labels, k, reduction="mean")
examples/stable-diffusion/ldm/models/diffusion/classifier.py:150
↓ 4 callersMethodencode
(self, S, x, encode_ratio, conditioning=None,
examples/stable-diffusion/ldm/models/diffusion/dpm_solver/sampler.py:99
↓ 4 callersFunctionexpand_dims
Expand the tensor `v` to the dim `dims`. Args: `v`: a PyTorch tensor with shape [N]. `dim`: a `int`. Returns: a
examples/ddpm_and_guided-diffusion/dpm_solver/sampler.py:1295
↓ 4 callersMethodget_fold_unfold
:param x: img of size (bs, c, h, w) :return: n img crops of size (n, bs, c, kernel_size[0], kernel_size[1])
examples/stable-diffusion/ldm/models/diffusion/ddpm.py:601
↓ 4 callersMethodget_input
(self, batch, k)
examples/stable-diffusion/ldm/models/autoencoder.py:124
↓ 4 callersMethodget_last_layer
(self)
examples/stable-diffusion/ldm/models/autoencoder.py:230
↓ 4 callersMethodget_last_layer
(self)
examples/stable-diffusion/ldm/models/autoencoder.py:397
↓ 4 callersFunctionget_normalization
Obtain normalization modules from the config file.
examples/score_sde_pytorch/models/normalization.py:22
↓ 4 callersFunctionget_sigmas
Get sigmas --- the set of noise levels for SMLD from config files. Args: config: A ConfigDict object parsed from the config file Returns:
examples/score_sde_jax/models/utils.py:69
↓ 4 callersMethodmarginal_alpha
Compute alpha_t of a given continuous-time label t in [0, T].
dpm_solver_pytorch.py:136
↓ 4 callersMethodmarginal_alpha
Compute alpha_t of a given continuous-time label t in [0, T].
examples/ddpm_and_guided-diffusion/dpm_solver/sampler.py:136
↓ 4 callersMethodmarginal_alpha
Compute alpha_t of a given continuous-time label t in [0, T].
examples/score_sde_pytorch/dpm_solver.py:139
↓ 4 callersMethodmarginal_alpha
Compute alpha_t of a given continuous-time label t in [0, T].
examples/stable-diffusion/ldm/models/diffusion/dpm_solver/dpm_solver.py:139
↓ 4 callersFunctionmodel_fn
Compute the output of the score-based model. Args: x: A mini-batch of input data. labels: A mini-batch of conditioning variables for
examples/score_sde_pytorch/models/utils.py:108
↓ 4 callersFunctionmodel_fn
Compute the output of the score-based model. Args: x: A mini-batch of input data. labels: A mini-batch of conditioning variables for
examples/score_sde_jax/models/utils.py:138
↓ 4 callersFunctionnoise_like
(shape, device, repeat=False)
examples/stable-diffusion/ldm/modules/diffusionmodules/util.py:264
↓ 4 callersFunctionnoise_pred_fn
(x, t_continuous, cond=None)
dpm_solver_jax.py:290
↓ 4 callersFunctionnoise_pred_fn
(x, t_continuous, cond=None)
dpm_solver_pytorch.py:282
↓ 4 callersFunctionnoise_pred_fn
(x, t_continuous, cond=None)
examples/ddpm_and_guided-diffusion/dpm_solver/sampler.py:282
↓ 4 callersFunctionnoise_pred_fn
(x, t_continuous, cond=None)
examples/score_sde_pytorch/dpm_solver.py:290
↓ 4 callersFunctionnoise_pred_fn
(x, t_continuous, cond=None)
examples/stable-diffusion/ldm/models/diffusion/dpm_solver/dpm_solver.py:290
↓ 4 callersFunctionnoise_pred_fn
(x, t_continuous, cond=None)
examples/score_sde_jax/dpm_solver.py:290
↓ 4 callersFunctionnormalization
Make a standard normalization layer. :param channels: number of input channels. :return: an nn.Module for normalization.
examples/ddpm_and_guided-diffusion/models/improved_ddpm/nn.py:92
↓ 4 callersFunctionrestore_checkpoint
(ckpt_dir, state, device)
examples/score_sde_pytorch/utils.py:7
↓ 4 callersMethodsample
(self, S, batch_size, shape, conditioning=None,
examples/stable-diffusion/ldm/models/diffusion/ddim.py:57
↓ 4 callersMethodsample_log
(self,cond,batch_size,ddim, ddim_steps,**kwargs)
examples/stable-diffusion/ldm/models/diffusion/ddpm.py:1235
↓ 4 callersMethodshared_step
(self, batch, t=None)
examples/stable-diffusion/ldm/models/diffusion/classifier.py:179
↓ 4 callersFunctionupfirdn2d
(input, kernel, up=1, down=1, pad=(0, 0))
examples/score_sde_pytorch/op/upfirdn2d.py:145
↓ 4 callersFunctionzero_module
Zero out the parameters of a module and return it.
examples/ddpm_and_guided-diffusion/models/guided_diffusion/nn.py:68
↓ 4 callersFunctionzero_module
Zero out the parameters of a module and return it.
examples/stable-diffusion/ldm/modules/diffusionmodules/util.py:174
↓ 3 callersMethod__init__
Construct an SDE. Args: N: number of discretization time steps.
examples/score_sde_pytorch/sde_lib.py:10
↓ 3 callersMethod__init__
(self, config)
examples/score_sde_pytorch/models/ncsnv2.py:137
↓ 3 callersMethod__init__
(self, ddconfig, lossconfig, n_embed, embe
examples/stable-diffusion/ldm/models/autoencoder.py:15
↓ 3 callersMethod__init__
(self, unet_config, timesteps=1000, beta_schedule="linear",
examples/stable-diffusion/ldm/models/diffusion/ddpm.py:46
↓ 3 callersMethod__init__
Construct an SDE. Args: N: number of discretization time steps.
examples/score_sde_jax/sde_lib.py:12
↓ 3 callersFunctionadd_blur
(img, sf=4)
examples/stable-diffusion/ldm/modules/image_degradation/bsrgan_light.py:325
↓ 3 callersFunctioncheck_integrity
(fpath, md5=None)
examples/ddpm_and_guided-diffusion/datasets/utils.py:20
↓ 3 callersFunctioncheckpoint
Evaluate a function without caching intermediate activations, allowing for reduced memory at the expense of extra compute in the backward pas
examples/stable-diffusion/ldm/modules/diffusionmodules/util.py:102
↓ 3 callersMethodcopy_to
Copy current parameters into given collection of parameters. Args: parameters: Iterable of `torch.nn.Parameter`; the parameters to be
examples/score_sde_pytorch/models/ema.py:53
↓ 3 callersFunctioncouple
(inputs)
examples/score_sde_pytorch/controllable_generation.py:118
↓ 3 callersFunctioncouple
(inputs)
examples/score_sde_jax/controllable_generation.py:135
↓ 3 callersFunctioncustom_to_pil
(x)
examples/stable-diffusion/scripts/sample_diffusion.py:15
↓ 3 callersFunctiondefault
(val, d)
examples/stable-diffusion/ldm/modules/attention.py:19
↓ 3 callersMethoddpm_solver_first_update
DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`. Args: x: A jnp.DeviceArray. The initial value at time `s`.
dpm_solver_jax.py:494
↓ 3 callersMethoddpm_solver_first_update
DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`. Args: x: A pytorch tensor. The initial value at time `s`.
dpm_solver_pytorch.py:547
↓ 3 callersMethoddpm_solver_first_update
DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`. Args: x: A pytorch tensor. The initial value at time `s`.
examples/ddpm_and_guided-diffusion/dpm_solver/sampler.py:547
↓ 3 callersMethoddpm_solver_first_update
DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`. Args: x: A pytorch tensor. The initial value at time `s`.
examples/score_sde_pytorch/dpm_solver.py:555
↓ 3 callersMethoddpm_solver_first_update
DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`. Args: x: A pytorch tensor. The initial value at time `s`.
examples/stable-diffusion/ldm/models/diffusion/dpm_solver/dpm_solver.py:555
↓ 3 callersMethoddpm_solver_first_update
DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`. Args: x: A jnp.DeviceArray. The initial value at time `s`.
examples/score_sde_jax/dpm_solver.py:494
↓ 3 callersMethodencode_first_stage
(self, x)
examples/stable-diffusion/ldm/models/diffusion/ddpm.py:826
↓ 3 callersFunctionexists
(val)
examples/stable-diffusion/ldm/modules/attention.py:11
↓ 3 callersFunctionexpand_dims
Expand the tensor `v` to the dim `dims`. Args: `v`: a PyTorch tensor with shape [N]. `dim`: a `int`. Returns: a
examples/score_sde_pytorch/dpm_solver.py:1303
↓ 3 callersFunctionexpand_dims
Expand the tensor `v` to the dim `dims`. Args: `v`: a PyTorch tensor with shape [N]. `dim`: a `int`. Returns: a
examples/stable-diffusion/ldm/models/diffusion/dpm_solver/dpm_solver.py:1303
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