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Functions645 in github.com/JiangkaiWu/Promptus

⨍ Functions 645◇ Types & classes 174↳ Endpoints 3
↓ 2 callersFunctioninit_save_locally
(_dir, init_value: bool = False)
scripts/demo/streamlit_helpers.py:209
↓ 2 callersMethodinitialize
(self, input)
sgm/modules/autoencoding/lpips/util.py:58
↓ 2 callersMethodinstantiate_optimizer_from_config
(self, params, lr, cfg)
sgm/models/autoencoder.py:92
↓ 2 callersFunctionload_img
(path)
inversion.py:95
↓ 2 callersFunctionload_img
(path)
generation.py:105
↓ 2 callersFunctionload_img
( display: bool = True, size: Union[None, int, Tuple[int, int]] = None, center_crop: bool = False,
scripts/demo/streamlit_helpers.py:445
↓ 2 callersFunctionload_model
( config: str, device: str, num_frames: int, num_steps: int, )
scripts/sampling/simple_video_sample.py:251
↓ 2 callersFunctionload_model_weights
(path: str)
scripts/util/detection/nsfw_and_watermark_dectection.py:20
↓ 2 callersFunctionmake_beta_schedule
( schedule, n_timestep, linear_start=1e-4, linear_end=2e-2, )
sgm/modules/diffusionmodules/util.py:20
↓ 2 callersFunctionmd5_hash
(path)
sgm/modules/autoencoding/lpips/util.py:28
↓ 2 callersMethodnormalization
(self, images_tensor, to_numpy=False)
realtime_demo.py:122
↓ 2 callersFunctionnormalize_tensor
(x, eps=1e-10)
sgm/modules/autoencoding/lpips/loss/lpips.py:141
↓ 2 callersFunctionpredict_proba
(X, weights, biases)
scripts/util/detection/nsfw_and_watermark_dectection.py:12
↓ 2 callersMethodprepare_inputs
( self, x: torch.Tensor, s: float, c: Dict, uc: Dict )
sgm/modules/diffusionmodules/guiders.py:18
↓ 2 callersMethodremap_to_used
(self, inds: torch.Tensor)
sgm/modules/autoencoding/regularizers/quantize.py:26
↓ 2 callersMethodrestore
Restore the parameters stored with the `store` method. Useful to validate the model with EMA parameters without affecting the
sgm/modules/ema.py:74
↓ 2 callersMethodsampler_step
(self, sigma, next_sigma, denoiser, x, cond, uc=None, gamma=0.0)
sgm/modules/diffusionmodules/sampling.py:93
↓ 2 callersFunctionseeded_randn
(shape, seed)
inversion.py:51
↓ 2 callersFunctionseeded_randn
(shape, seed)
generation.py:55
↓ 2 callersFunctionseeded_randn
(shape, seed)
scripts/demo/turbo.py:47
↓ 2 callersMethodsigma_to_idx
(self, sigma: torch.Tensor)
sgm/modules/diffusionmodules/denoiser.py:61
↓ 2 callersMethodstore
Save the current parameters for restoring later. Args: parameters: Iterable of `torch.nn.Parameter`; the parameters to be
sgm/modules/ema.py:65
↓ 2 callersMethodtext_transformer_forward
(self, x: torch.Tensor, attn_mask=None)
sgm/modules/encoders/modules.py:562
↓ 2 callersMethodunmap_to_all
(self, inds: torch.Tensor)
sgm/modules/autoencoding/regularizers/quantize.py:43
↓ 2 callersFunctionzero_module
Zero out the parameters of a module and return it.
sgm/modules/attention.py:116
↓ 1 callersMethod__init__
(self, seed)
inversion.py:58
↓ 1 callersMethod__init__
(self, seed)
generation.py:62
↓ 1 callersMethod__init__
(self, seed)
scripts/demo/turbo.py:54
↓ 1 callersMethod__init__
(self, seed)
scripts/demo/turbo_demo.py:62
↓ 1 callersMethod__init__
( self, dim, n_heads, d_head, dropout=0.0, context_dim=None,
sgm/modules/video_attention.py:21
↓ 1 callersMethod__init__
(self, sigma_min=0.002, sigma_max=80.0, rho=7.0)
sgm/modules/diffusionmodules/discretizer.py:29
↓ 1 callersMethod__init__
( self, in_channels: int, model_channels: int, out_channels: int, num_
sgm/modules/diffusionmodules/video_model.py:85
↓ 1 callersMethod__init__
(self, scaling_config: Dict)
sgm/modules/diffusionmodules/denoiser.py:12
↓ 1 callersMethod__init__
(self, batch_size, num_workers=0, shuffle=True)
sgm/data/cifar10.py:21
↓ 1 callersMethod__init__
(self, batch_size, num_workers=0, prefetch_factor=2, shuffle=True)
sgm/data/mnist.py:21
↓ 1 callersMethod_forward
(self, x, context=None, timesteps=None)
sgm/modules/video_attention.py:109
↓ 1 callersMethod_forward
( self, x, context=None, additional_tokens=None, n_times_crossframe_attn_in_self=0 )
sgm/modules/attention.py:551
↓ 1 callersMethod_forward
( self, network: nn.Module, denoiser: Denoiser, cond: Dict, input: tor
sgm/modules/diffusionmodules/loss.py:59
↓ 1 callersMethod_forward
(self, x: th.Tensor, emb: th.Tensor)
sgm/modules/diffusionmodules/openaimodel.py:328
↓ 1 callersMethod_init_first_stage
(self, config)
sgm/models/diffusion.py:105
↓ 1 callersMethod_load_model
(self, device="cuda", use_fp16=True)
sgm/inference/api.py:173
↓ 1 callersMethod_make_attn
(self)
sgm/modules/diffusionmodules/model.py:703
↓ 1 callersMethod_make_conv
(self)
sgm/modules/diffusionmodules/model.py:709
↓ 1 callersMethod_make_resblock
(self)
sgm/modules/diffusionmodules/model.py:706
↓ 1 callersMethodadd_noise
(self, prev_frame)
realtime_demo.py:136
↓ 1 callersFunctionappend_zero
(x)
sgm/util.py:188
↓ 1 callersFunctionapply_refiner
( input, state, sampler, num_samples, prompt, negative_prompt, filter=None, fi
scripts/demo/sampling.py:210
↓ 1 callersMethodattention
(self, h_: torch.Tensor)
sgm/modules/diffusionmodules/model.py:231
↓ 1 callersFunctionavg_pool_nd
Create a 1D, 2D, or 3D average pooling module.
sgm/modules/diffusionmodules/util.py:299
↓ 1 callersMethodbackward
(ctx, grad_output)
quantization.py:15
↓ 1 callersFunctionbenchmark_transformer_blocks
()
scripts/tests/attention.py:140
↓ 1 callersMethodbuild
( self, onnx_path, fp16, input_profile=None, enable_refit=False,
tensorrt_acceleration/utilities.py:204
↓ 1 callersFunctioncalcScaleZeroPoint
(min_val, max_val, num_bits=8)
quantization.py:18
↓ 1 callersMethodcalculate_adaptive_weight
( self, nll_loss: torch.Tensor, g_loss: torch.Tensor, last_layer: torch.Tensor )
sgm/modules/autoencoding/losses/discriminator_loss.py:196
↓ 1 callersFunctionclip_process_images
(images: torch.Tensor)
scripts/util/detection/nsfw_and_watermark_dectection.py:25
↓ 1 callersMethodcluster_size_ema_update
(self, new_cluster_size)
sgm/modules/autoencoding/regularizers/quantize.py:337
↓ 1 callersFunctiondecode
(samples_z)
scripts/demo/turbo_demo.py:197
↓ 1 callersMethoddecode
(self, cv2Image, method="dwtDct", **configs)
scripts/demo/detect.py:37
↓ 1 callersMethoddecode
(self, z: torch.Tensor, **kwargs)
sgm/models/autoencoder.py:210
↓ 1 callersMethoddecode
( self, inds: torch.Tensor, shape: Union[None, tuple, list] = None )
sgm/models/autoencoder.py:593
↓ 1 callersMethoddecoder_engine_build
(self)
realtime_demo.py:77
↓ 1 callersMethoddecoder_engine_load
(self)
realtime_demo.py:85
↓ 1 callersMethoddenoise_engine_build
(self)
realtime_demo.py:52
↓ 1 callersMethoddenoise_engine_load
(self)
realtime_demo.py:60
↓ 1 callersFunctiondo_sample
( model, sampler, value_dict, num_samples, H, W, C, F, force_uc_zero_embed
sgm/inference/helpers.py:101
↓ 1 callersFunctiondownload
(url, local_path, chunk_size=1024)
sgm/modules/autoencoding/lpips/util.py:16
↓ 1 callersMethodembed_avg_ema_update
(self, new_embed_avg)
sgm/modules/autoencoding/regularizers/quantize.py:342
↓ 1 callersMethodencode
( self, x: torch.Tensor, return_reg_log: bool = False, unregularized: bool = F
sgm/models/autoencoder.py:196
↓ 1 callersMethodencode_with_transformer
(self, text)
sgm/modules/encoders/modules.py:454
↓ 1 callersMethodencode_with_transformer
(self, text)
sgm/modules/encoders/modules.py:545
↓ 1 callersMethodencode_with_vision_transformer
(self, img)
sgm/modules/encoders/modules.py:702
↓ 1 callersFunctionexists
(x)
sgm/util.py:137
↓ 1 callersMethodforward
(self, x)
sgm/modules/diffusionmodules/util.py:270
↓ 1 callersMethodforward
( self, x: th.Tensor, timesteps: th.Tensor, context: Optional[th.Tensor] = Non
sgm/modules/diffusionmodules/video_model.py:442
↓ 1 callersMethodforward
(self, x, t=None, context=None)
sgm/modules/diffusionmodules/model.py:434
↓ 1 callersMethodforward
(self, embed_id)
sgm/modules/autoencoding/regularizers/quantize.py:334
↓ 1 callersMethodfreeze
(self)
sgm/modules/encoders/modules.py:263
↓ 1 callersMethodfreeze
(self)
sgm/modules/encoders/modules.py:305
↓ 1 callersMethodfreeze
(self)
sgm/modules/encoders/modules.py:361
↓ 1 callersMethodfreeze
(self)
sgm/modules/encoders/modules.py:438
↓ 1 callersMethodfreeze
(self)
sgm/modules/encoders/modules.py:534
↓ 1 callersMethodfreeze
(self)
sgm/modules/encoders/modules.py:643
↓ 1 callersFunctiongenerate_roughly_equally_spaced_steps
( num_substeps: int, max_step: int )
sgm/modules/diffusionmodules/discretizer.py:11
↓ 1 callersFunctiongeneration
( model, sampler, decoder, rank, interval, frame_path,
generation.py:70
↓ 1 callersMethodget_alpha
(self, image_only_indicator: torch.Tensor)
sgm/modules/diffusionmodules/util.py:341
↓ 1 callersMethodget_alpha
(self, bs)
sgm/modules/autoencoding/temporal_ae.py:56
↓ 1 callersMethodget_alpha
( self, )
sgm/modules/autoencoding/temporal_ae.py:169
↓ 1 callersMethodget_alpha
( self, )
sgm/modules/autoencoding/temporal_ae.py:239
↓ 1 callersMethodget_codebook_entry
(self, indices, shape)
sgm/modules/autoencoding/regularizers/quantize.py:158
↓ 1 callersFunctionget_discretization
(discretization, options, key=1)
scripts/demo/streamlit_helpers.py:335
↓ 1 callersFunctionget_discretization_config
(params: SamplingParams)
sgm/inference/api.py:306
↓ 1 callersMethodget_discriminator_params
(self)
sgm/models/autoencoder.py:186
↓ 1 callersFunctionget_guider
(options, key)
scripts/demo/streamlit_helpers.py:219
↓ 1 callersFunctionget_guider_config
(params: SamplingParams)
sgm/inference/api.py:280
↓ 1 callersMethodget_loss
(self, model_output, target, w)
sgm/modules/diffusionmodules/loss.py:92
↓ 1 callersMethodget_mult
(self, h, s, t, t_next)
sgm/modules/diffusionmodules/sampling.py:254
↓ 1 callersMethodget_mult
(self, h, r, t, t_next, previous_sigma)
sgm/modules/diffusionmodules/sampling.py:299
↓ 1 callersFunctionget_nested_attribute
Will return the result of a recursive get attribute call. E.g.: a.b.c = getattr(getattr(a, "b"), "c") = get_nested_at
sgm/util.py:251
↓ 1 callersMethodget_nll_loss
( self, rec_loss: torch.Tensor, weights: Optional[Union[float, torch.Tensor]] = None,
sgm/modules/autoencoding/losses/discriminator_loss.py:294
↓ 1 callersMethodget_noised_input
( self, sigmas_bc: torch.Tensor, noise: torch.Tensor, input: torch.Tensor )
sgm/modules/diffusionmodules/loss.py:42
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