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github.com/JiangkaiWu/Promptus
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Functions
645 in github.com/JiangkaiWu/Promptus
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Functions
645
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Types & classes
174
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Endpoints
3
Method
forward
(self, x, timesteps, skip_time_block=False)
sgm/modules/autoencoding/temporal_ae.py:212
Method
forward
(self, input: torch.Tensor, **kwargs)
sgm/modules/autoencoding/temporal_ae.py:289
Method
forward
(self, z: torch.Tensor)
sgm/modules/autoencoding/regularizers/base.py:13
Method
forward
(self, z: torch.Tensor)
sgm/modules/autoencoding/regularizers/base.py:22
Method
forward
(self, z: torch.Tensor)
sgm/modules/autoencoding/regularizers/__init__.py:21
Method
forward
( self, z: torch.Tensor, temp: Optional[float] = None, return_logits: bool = False )
sgm/modules/autoencoding/regularizers/quantize.py:119
Method
forward
( self, z: torch.Tensor, )
sgm/modules/autoencoding/regularizers/quantize.py:234
Method
forward
(self, z: torch.Tensor)
sgm/modules/autoencoding/regularizers/quantize.py:396
Method
forward
(self, z: torch.Tensor)
sgm/modules/autoencoding/regularizers/quantize.py:464
Method
forward
(self, input, reverse=False)
sgm/modules/autoencoding/lpips/util.py:79
Method
forward
Standard forward.
sgm/modules/autoencoding/lpips/model/model.py:86
Method
forward
(self, input, target)
sgm/modules/autoencoding/lpips/loss/lpips.py:46
Method
forward
(self, inp)
sgm/modules/autoencoding/lpips/loss/lpips.py:77
Method
forward
(self, X)
sgm/modules/autoencoding/lpips/loss/lpips.py:123
Method
forward
( self, inputs: torch.Tensor, reconstructions: torch.Tensor, *, # added becau
sgm/modules/autoencoding/losses/discriminator_loss.py:207
Method
forward
(self, latent_inputs, latent_predictions, image_inputs, split="train")
sgm/modules/autoencoding/losses/lpips.py:32
Method
forward
( self, batch: Dict, force_zero_embeddings: Optional[List] = None )
sgm/modules/encoders/modules.py:120
Method
forward
(self, x)
sgm/modules/encoders/modules.py:211
Method
forward
(self, c)
sgm/modules/encoders/modules.py:222
Method
forward
(self, batch, key=None, disable_dropout=False)
sgm/modules/encoders/modules.py:238
Method
forward
(self, text)
sgm/modules/encoders/modules.py:269
Method
forward
(self, text)
sgm/modules/encoders/modules.py:311
Method
forward
(self, text)
sgm/modules/encoders/modules.py:368
Method
forward
(self, text)
sgm/modules/encoders/modules.py:444
Method
forward
(self, text)
sgm/modules/encoders/modules.py:539
Method
forward
(self, image, no_dropout=False)
sgm/modules/encoders/modules.py:649
Method
forward
(self, text)
sgm/modules/encoders/modules.py:762
Method
forward
(self, x)
sgm/modules/encoders/modules.py:808
Method
forward
(self, x)
sgm/modules/encoders/modules.py:904
Method
forward
(self, x)
sgm/modules/encoders/modules.py:930
Method
forward
(self, x)
sgm/modules/encoders/modules.py:950
Method
forward
( self, vid: torch.Tensor )
sgm/modules/encoders/modules.py:993
Method
forward
(self, vid)
sgm/modules/encoders/modules.py:1050
Method
forward
(self, x, batch)
sgm/models/diffusion.py:152
Method
forward
( self, x: torch.Tensor, **additional_decode_kwargs )
sgm/models/autoencoder.py:214
Method
get_attention_layer
( ch, num_heads, dim_head, depth=1, context_dim=No
sgm/modules/diffusionmodules/video_model.py:198
Method
get_autoencoder_params
(self)
sgm/models/autoencoder.py:464
Method
get_codebook_entry
( self, indices: torch.Tensor, shape: Optional[Tuple[int, ...]] = None )
sgm/modules/autoencoding/regularizers/quantize.py:55
Method
get_codebook_entry
( self, indices: torch.Tensor, shape: Optional[Tuple[int, ...]] = None )
sgm/modules/autoencoding/regularizers/quantize.py:302
Function
get_configs_path
Get the `configs` directory. For a working copy, this is the one in the root of the repository, but for an installed copy, it's in the `s
sgm/util.py:233
Function
get_init_img
(batch_size=1, key=None)
scripts/demo/streamlit_helpers.py:472
Method
get_input
(self, batch)
sgm/models/autoencoder.py:61
Method
get_input
(self, x: Any)
sgm/models/autoencoder.py:555
Function
get_input_image_tensor
(image: Image.Image, device="cuda")
sgm/inference/helpers.py:230
Method
get_last_layer
(self)
sgm/modules/video_attention.py:142
Method
get_last_layer
(self)
sgm/modules/diffusionmodules/model.py:483
Method
get_last_layer
(self, **kwargs)
sgm/modules/diffusionmodules/model.py:712
Method
get_last_layer
(self, skip_time_mix=False, **kwargs)
sgm/modules/autoencoding/temporal_ae.py:314
Method
get_resblock
( merge_factor, merge_strategy, video_kernel_size, ch,
sgm/modules/diffusionmodules/video_model.py:227
Method
get_sigmas
(self, n, device="cpu")
sgm/modules/diffusionmodules/discretizer.py:34
Method
get_sigmas
(self, n, device="cpu")
sgm/modules/diffusionmodules/discretizer.py:58
Function
get_string_from_tuple
(s)
sgm/util.py:20
Method
get_trainable_parameters
(self)
sgm/modules/autoencoding/regularizers/base.py:25
Method
get_trainable_parameters
(self)
sgm/modules/autoencoding/regularizers/__init__.py:18
Method
get_trainable_parameters
(self)
sgm/modules/autoencoding/regularizers/quantize.py:60
Method
get_trainable_parameters
(self)
sgm/modules/autoencoding/losses/discriminator_loss.py:85
Method
get_unconditional_conditioning
( self, batch_c: Dict, batch_uc: Optional[Dict] = None, force_uc_zero_embeddin
sgm/modules/encoders/modules.py:166
Function
hinge_d_loss
(logits_real, logits_fake)
sgm/modules/autoencoding/lpips/vqperceptual.py:5
Method
image_to_image
( self, params: SamplingParams, image, prompt: str, negative_prom
sgm/inference/api.py:212
Function
increment_counter
()
scripts/demo/turbo.py:187
Function
init_
(tensor)
sgm/modules/attention.py:79
Function
init_embedder_options
(keys, init_dict, prompt=None, negative_prompt=None)
scripts/demo/streamlit_helpers.py:125
Method
input_key
(self)
sgm/modules/encoders/modules.py:43
Function
is_power_of_two
chat.openai.com/chat Return True if n is a power of 2, otherwise return False. The function is_power_of_two takes an integer n as input
sgm/util.py:36
Method
is_trainable
(self)
sgm/modules/encoders/modules.py:35
Function
isheatmap
(x)
sgm/util.py:124
Function
isimage
(x)
sgm/util.py:118
Function
ismap
(x)
sgm/util.py:112
Function
isneighbors
(x)
sgm/util.py:131
Function
load_partial_from_config
(config)
sgm/util.py:64
Method
log_images
( self, inputs: torch.Tensor, reconstructions: torch.Tensor )
sgm/modules/autoencoding/losses/discriminator_loss.py:94
Method
log_images
( self, batch: Dict, N: int = 8, sample: bool = True, ucg_keys: List[s
sgm/models/diffusion.py:294
Method
log_images
( self, batch: dict, additional_log_kwargs: Optional[Dict] = None, **kwargs )
sgm/models/autoencoder.py:395
Function
make_path_absolute
(path)
sgm/util.py:105
Function
make_time_attn
( in_channels, attn_type="vanilla", attn_kwargs=None, alpha: float = 0, merge_strategy: st
sgm/modules/autoencoding/temporal_ae.py:250
Method
map_name
(name)
tensorrt_acceleration/utilities.py:138
Function
max_neg_value
(t)
sgm/modules/attention.py:75
Function
mean_flat
https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/nn.py#L86 Take the mean over all no
sgm/util.py:153
Function
mean_flat
Take the mean over all non-batch dimensions.
sgm/modules/diffusionmodules/util.py:252
Function
mixed_checkpoint
Evaluate a function without caching intermediate activations, allowing for reduced memory at the expense of extra compute in the backward pas
sgm/modules/diffusionmodules/util.py:42
Method
mode
(self)
sgm/modules/distributions/distributions.py:9
Method
mode
(self)
sgm/modules/distributions/distributions.py:20
Method
nll
(self, sample, dims=[1, 2, 3])
sgm/modules/distributions/distributions.py:62
Function
normal_kl
source: https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/losses.py#L12 Compute the K
sgm/modules/distributions/distributions.py:75
Method
on_train_batch_end
(self, *args, **kwargs)
sgm/models/diffusion.py:193
Method
on_train_batch_end
(self, *args, **kwargs)
sgm/models/autoencoder.py:64
Method
on_train_start
(self, *args, **kwargs)
sgm/models/diffusion.py:189
Function
perform_save_locally
(save_path, samples)
sgm/inference/helpers.py:65
Method
possible_correction_step
( self, euler_step, x, d, dt, next_sigma, denoiser, cond, uc )
sgm/modules/diffusionmodules/sampling.py:212
Method
possibly_quantize_c_noise
(self, c_noise: torch.Tensor)
sgm/modules/diffusionmodules/denoiser.py:71
Method
possibly_quantize_sigma
(self, sigma: torch.Tensor)
sgm/modules/diffusionmodules/denoiser.py:68
Method
prepare_data
(self)
sgm/data/cifar10.py:42
Method
prepare_data
(self)
sgm/data/mnist.py:43
Method
prepare_inputs
(self, x, s, c, uc)
sgm/modules/diffusionmodules/guiders.py:33
Method
prepare_inputs
( self, x: torch.Tensor, s: float, c: Dict, uc: Dict )
sgm/modules/diffusionmodules/guiders.py:49
Method
prepare_inputs
( self, x: torch.Tensor, s: torch.Tensor, c: dict, uc: dict )
sgm/modules/diffusionmodules/guiders.py:88
Method
prepare_sampling_loop
(self, x, cond, uc=None, num_steps=None)
inversion.py:37
Method
prepare_sampling_loop
(self, x, cond, uc=None, num_steps=None)
generation.py:41
Method
prepare_sampling_loop
(self, x, cond, uc=None, num_steps=None)
scripts/demo/turbo.py:33
Method
prepare_sampling_loop
(self, x, cond, uc=None, num_steps=None)
scripts/demo/turbo_demo.py:41
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