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Functions645 in github.com/JiangkaiWu/Promptus

⨍ Functions 645◇ Types & classes 174↳ Endpoints 3
Method__init__
(self, batch=1, device='cuda:0')
realtime_demo.py:16
Method__init__
(self, num_bits=8)
quantization.py:55
Method__init__
(self, device)
lossbuilder.py:15
Method__init__
(self, weight)
lossbuilder.py:28
Method__init__
( self, engine_path, )
tensorrt_acceleration/utilities.py:83
Method__init__
(self, n_sample_steps=1, *args, **kwargs)
scripts/demo/turbo.py:28
Method__init__
(self, wm_type="bytes", length=0)
scripts/demo/detect.py:26
Method__init__
(self, watermark)
scripts/demo/detect.py:78
Method__init__
(self, discretization: Discretization, strength: float = 1.0)
scripts/demo/discretization.py:13
Method__init__
( self, discretization: Discretization, strength: float = 0.0, original_steps=None )
scripts/demo/discretization.py:37
Method__init__
(self, n_sample_steps=1, *args, **kwargs)
scripts/demo/turbo_demo.py:36
Method__init__
( self, verbose: bool = False, device: torch.device = torch.device("cpu") )
scripts/util/detection/nsfw_and_watermark_dectection.py:40
Method__init__
( self, warm_up_steps, lr_min, lr_max, lr_start, max_decay_ste
sgm/lr_scheduler.py:9
Method__init__
( self, warm_up_steps, f_min, f_max, f_start, cycle_lengths, verbosity_interval=0 )
sgm/lr_scheduler.py:57
Method__init__
( self, in_channels, n_heads, d_head, depth=1, dropout=0.0,
sgm/modules/video_attention.py:147
Method__init__
(self, model, decay=0.9999, use_num_upates=True)
sgm/modules/ema.py:6
Method__init__
(self, dim, dim_out=None, mult=4, glu=False, dropout=0.0)
sgm/modules/attention.py:98
Method__init__
(self, dim, heads=4, dim_head=32)
sgm/modules/attention.py:132
Method__init__
( self, dim: int, num_heads: int = 8, qkv_bias: bool = False, qk_scale
sgm/modules/attention.py:157
Method__init__
(self, in_channels)
sgm/modules/attention.py:211
Method__init__
( self, query_dim, context_dim=None, heads=8, dim_head=64, dro
sgm/modules/attention.py:256
Method__init__
( self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0.0, **kwargs )
sgm/modules/attention.py:349
Method__init__
( self, dim, n_heads, d_head, dropout=0.0, context_dim=None,
sgm/modules/attention.py:462
Method__init__
( self, dim, n_heads, d_head, dropout=0.0, context_dim=None,
sgm/modules/attention.py:582
Method__init__
( self, in_channels, n_heads, d_head, depth=1, dropout=0.0,
sgm/modules/attention.py:629
Method__init__
( self, dim: int, depth: int, heads: int, dim_head: int, conte
sgm/modules/attention.py:727
Method__init__
( self, sigma_sampler_config: dict, loss_weighting_config: dict, loss_type: st
sgm/modules/diffusionmodules/loss.py:13
Method__init__
(self, sigma_data: float = 0.5)
sgm/modules/diffusionmodules/loss_weighting.py:18
Method__init__
(self)
sgm/modules/diffusionmodules/loss_weighting.py:26
Method__init__
(self, sigma_data=0.5)
sgm/modules/diffusionmodules/denoiser_weighting.py:10
Method__init__
(self)
sgm/modules/diffusionmodules/denoiser_weighting.py:18
Method__init__
( self, spacial_dim: int, embed_dim: int, num_heads_channels: int, out
sgm/modules/diffusionmodules/openaimodel.py:27
Method__init__
( self, channels: int, use_conv: bool, dims: int = 2, out_channels: Op
sgm/modules/diffusionmodules/openaimodel.py:169
Method__init__
( self, channels: int, emb_channels: int, dropout: float, out_channels
sgm/modules/diffusionmodules/openaimodel.py:226
Method__init__
( self, channels: int, num_heads: int = 1, num_head_channels: int = -1,
sgm/modules/diffusionmodules/openaimodel.py:364
Method__init__
(self, n_heads: int)
sgm/modules/diffusionmodules/openaimodel.py:410
Method__init__
(self, n_heads: int)
sgm/modules/diffusionmodules/openaimodel.py:438
Method__init__
(self, dim: int)
sgm/modules/diffusionmodules/openaimodel.py:464
Method__init__
( self, in_channels: int, model_channels: int, out_channels: int, num_
sgm/modules/diffusionmodules/openaimodel.py:502
Method__init__
(self, sigma_data: float = 0.5)
sgm/modules/diffusionmodules/denoiser_scaling.py:16
Method__init__
( self, linear_start=0.00085, linear_end=0.0120, num_timesteps=1000, )
sgm/modules/diffusionmodules/discretizer.py:43
Method__init__
( self, discretization_config: Union[Dict, ListConfig, OmegaConf], num_steps: Union[in
sgm/modules/diffusionmodules/sampling.py:22
Method__init__
(self, eta=1.0, s_noise=1.0, *args, **kwargs)
sgm/modules/diffusionmodules/sampling.py:134
Method__init__
( self, order=4, *args, **kwargs, )
sgm/modules/diffusionmodules/sampling.py:174
Method__init__
( self, alpha: float, merge_strategy: str = "learned_with_images", rearrange_p
sgm/modules/diffusionmodules/util.py:315
Method__init__
(self, p_mean=-1.2, p_std=1.2)
sgm/modules/diffusionmodules/sigma_sampling.py:7
Method__init__
(self, discretization_config, num_idx, do_append_zero=False, flip=True)
sgm/modules/diffusionmodules/sigma_sampling.py:17
Method__init__
( self, channels: int, emb_channels: int, dropout: float, video_kernel
sgm/modules/diffusionmodules/video_model.py:13
Method__init__
( self, scaling_config: Dict, num_idx: int, discretization_config: Dict,
sgm/modules/diffusionmodules/denoiser.py:43
Method__init__
(self, diffusion_model, compile_model: bool = False)
sgm/modules/diffusionmodules/wrappers.py:9
Method__init__
(self, in_channels, with_conv)
sgm/modules/diffusionmodules/model.py:59
Method__init__
(self, in_channels, with_conv)
sgm/modules/diffusionmodules/model.py:75
Method__init__
( self, *, in_channels, out_channels=None, conv_shortcut=False,
sgm/modules/diffusionmodules/model.py:95
Method__init__
(self, in_channels)
sgm/modules/diffusionmodules/model.py:157
Method__init__
(self, in_channels)
sgm/modules/diffusionmodules/model.py:162
Method__init__
(self, in_channels)
sgm/modules/diffusionmodules/model.py:212
Method__init__
( self, *, ch, out_ch, ch_mult=(1, 2, 4, 8), num_res_blocks,
sgm/modules/diffusionmodules/model.py:488
Method__init__
( self, *, ch, out_ch, ch_mult=(1, 2, 4, 8), num_res_blocks,
sgm/modules/diffusionmodules/model.py:605
Method__init__
(self, scale: float)
sgm/modules/diffusionmodules/guiders.py:25
Method__init__
( self, max_scale: float, num_frames: int, min_scale: float = 1.0, add
sgm/modules/diffusionmodules/guiders.py:61
Method__init__
( self, out_channels, *args, dropout=0.0, video_kernel_size=3,
sgm/modules/autoencoding/temporal_ae.py:19
Method__init__
( self, in_channels: int, alpha: float = 0, merge_strategy: str = "learned" )
sgm/modules/autoencoding/temporal_ae.py:111
Method__init__
( self, in_channels: int, alpha: float = 0, merge_strategy: str = "learned" )
sgm/modules/autoencoding/temporal_ae.py:181
Method__init__
( self, *args, video_kernel_size: Union[int, list] = 3, alpha: float = 0.0,
sgm/modules/autoencoding/temporal_ae.py:296
Method__init__
(self)
sgm/modules/autoencoding/regularizers/base.py:10
Method__init__
(self, sample: bool = True)
sgm/modules/autoencoding/regularizers/__init__.py:14
Method__init__
(self)
sgm/modules/autoencoding/regularizers/quantize.py:18
Method__init__
( self, num_hiddens: int, embedding_dim: int, n_embed: int, straight_t
sgm/modules/autoencoding/regularizers/quantize.py:73
Method__init__
( self, n_e: int, e_dim: int, beta: float = 0.25, remap: Optional[str]
sgm/modules/autoencoding/regularizers/quantize.py:184
Method__init__
( self, n_embed: int, embedding_dim: int, beta: float, decay: float =
sgm/modules/autoencoding/regularizers/quantize.py:356
Method__init__
( self, input_dim: int, n_codes: int, codebook_dim: int, beta: float =
sgm/modules/autoencoding/regularizers/quantize.py:447
Method__init__
( self, num_features, logdet=False, affine=True, allow_reverse_init=False )
sgm/modules/autoencoding/lpips/util.py:46
Method__init__
Construct a PatchGAN discriminator Parameters: input_nc (int) -- the number of channels in input images ndf (int)
sgm/modules/autoencoding/lpips/model/model.py:22
Method__init__
(self)
sgm/modules/autoencoding/lpips/loss/lpips.py:68
Method__init__
(self, chn_in, chn_out=1, use_dropout=False)
sgm/modules/autoencoding/lpips/loss/lpips.py:84
Method__init__
(self, requires_grad=False, pretrained=True)
sgm/modules/autoencoding/lpips/loss/lpips.py:100
Method__init__
( self, disc_start: int, logvar_init: float = 0.0, disc_num_layers: int = 3,
sgm/modules/autoencoding/losses/discriminator_loss.py:18
Method__init__
( self, decoder_config, perceptual_weight=1.0, latent_weight=1.0, scal
sgm/modules/autoencoding/losses/lpips.py:9
Method__init__
(self, value)
sgm/modules/distributions/distributions.py:14
Method__init__
(self, parameters, deterministic=False)
sgm/modules/distributions/distributions.py:25
Method__init__
(self)
sgm/modules/encoders/modules.py:28
Method__init__
(self, emb_models: Union[List, ListConfig])
sgm/modules/encoders/modules.py:75
Method__init__
(self, embed_dim, n_classes=1000, add_sequence_dim=False)
sgm/modules/encoders/modules.py:216
Method__init__
( self, version="google/t5-v1_1-xxl", device="cuda", max_length=77, freeze=True )
sgm/modules/encoders/modules.py:252
Method__init__
( self, version="google/byt5-base", device="cuda", max_length=77, freeze=True )
sgm/modules/encoders/modules.py:294
Method__init__
( self, version="openai/clip-vit-large-patch14", device="cuda", max_length=77,
sgm/modules/encoders/modules.py:336
Method__init__
( self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", m
sgm/modules/encoders/modules.py:403
Method__init__
( self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", m
sgm/modules/encoders/modules.py:505
Method__init__
( self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", m
sgm/modules/encoders/modules.py:584
Method__init__
( self, clip_version="openai/clip-vit-large-patch14", t5_version="google/t5-v1_1-xl",
sgm/modules/encoders/modules.py:741
Method__init__
( self, n_stages=1, method="bilinear", multiplier=0.5, in_channels=3,
sgm/modules/encoders/modules.py:769
Method__init__
( self, model_config, linear_start, linear_end, timesteps=1000,
sgm/modules/encoders/modules.py:829
Method__init__
(self, outdim)
sgm/modules/encoders/modules.py:925
Method__init__
( self, weight: float = 1.0, flatten_output: bool = True, *args, **kwargs )
sgm/modules/encoders/modules.py:942
Method__init__
( self, n_cond_frames: int, n_copies: int, encoder_config: dict, sigma
sgm/modules/encoders/modules.py:961
Method__init__
( self, open_clip_embedding_config: Dict, n_cond_frames: int, n_copies: int,
sgm/modules/encoders/modules.py:1038
Method__init__
( self, train: DictConfig, validation: Optional[DictConfig] = None, test: Opti
sgm/data/dataset.py:21
Method__init__
(self, dset)
sgm/data/cifar10.py:8
Method__init__
(self, dset)
sgm/data/mnist.py:8
Method__init__
( self, model_id: ModelArchitecture, model_path="checkpoints", config_path
sgm/inference/api.py:156
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