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Functions274 in github.com/G-U-N/AnimateLCM

⨍ Functions 274◇ Types & classes 47
Methoddisable_vae_slicing
(self)
animatelcm_sd15/animatelcm/pipelines/pipeline_animation.py:131
Methoddo_classifier_free_guidance
(self)
animatelcm_svd/pipeline.py:318
Functiondownload_image
(url)
animatelcm_svd/train_svd_lcm.py:571
Methodenable_sequential_cpu_offload
(self, gpu_id=0)
animatelcm_sd15/animatelcm/pipelines/pipeline_animation.py:134
Methodenable_vae_slicing
(self)
animatelcm_sd15/animatelcm/pipelines/pipeline_animation.py:128
Methodextra_repr
(self)
animatelcm_sd15/animatelcm/models/motion_module.py:268
Methodextract_features
(self, x)
metrics/pytorch_i3d.py:351
Methodextract_features_multiscale
(self, x)
metrics/pytorch_i3d.py:365
Functionextract_into_tensor
(a, t, x_shape)
animatelcm_svd/animate_lcm_utils.py:101
Methodextract_pre_pool_features
(self, x)
metrics/pytorch_i3d.py:358
Methodfn_recursive_retrieve_slicable_dims
(module: torch.nn.Module)
animatelcm_sd15/animatelcm/models/unet.py:296
Methodfn_recursive_set_attention_slice
(module: torch.nn.Module, slice_size: List[int])
animatelcm_sd15/animatelcm/models/unet.py:336
Methodforward
r""" Args: sample (`torch.FloatTensor`): (batch, channel, height, width) noisy inputs tensor timestep (`torch.FloatTen
animatelcm_sd15/animatelcm/models/unet.py:351
Methodforward
(self, x)
animatelcm_sd15/animatelcm/models/adapter.py:81
Methodforward
(self, x)
animatelcm_sd15/animatelcm/models/adapter.py:127
Methodforward
(self, x)
animatelcm_sd15/animatelcm/models/adapter.py:168
Methodforward
(self, hidden_states, temb=None, encoder_hidden_states=None, attention_mask=None)
animatelcm_sd15/animatelcm/models/unet_blocks.py:315
Methodforward
(self, hidden_states, temb=None, encoder_hidden_states=None, attention_mask=None, img_feature=None)
animatelcm_sd15/animatelcm/models/unet_blocks.py:453
Methodforward
(self, hidden_states, temb=None, encoder_hidden_states=None, img_feature=None)
animatelcm_sd15/animatelcm/models/unet_blocks.py:587
Methodforward
( self, hidden_states, res_hidden_states_tuple, temb=None, encoder_hid
animatelcm_sd15/animatelcm/models/unet_blocks.py:747
Methodforward
(self, hidden_states, res_hidden_states_tuple, temb=None, upsample_size=None, encoder_hidden_states=None,)
animatelcm_sd15/animatelcm/models/unet_blocks.py:875
Methodforward
(self, hidden_states, encoder_hidden_states=None, timestep=None, return_dict: bool = True)
animatelcm_sd15/animatelcm/models/attention.py:92
Methodforward
(self, hidden_states, encoder_hidden_states=None, timestep=None, attention_mask=None, video_length=None)
animatelcm_sd15/animatelcm/models/attention.py:252
Methodforward
(self, sample, condition=None)
animatelcm_sd15/animatelcm/models/embeddings.py:92
Methodforward
(self, timesteps)
animatelcm_sd15/animatelcm/models/embeddings.py:111
Methodforward
(self, x)
animatelcm_sd15/animatelcm/models/embeddings.py:138
Methodforward
(self, index)
animatelcm_sd15/animatelcm/models/embeddings.py:193
Methodforward
(self, x)
animatelcm_sd15/animatelcm/models/resnet.py:12
Methodforward
(self, x)
animatelcm_sd15/animatelcm/models/resnet.py:23
Methodforward
(self, hidden_states, output_size=None)
animatelcm_sd15/animatelcm/models/resnet.py:49
Methodforward
(self, hidden_states)
animatelcm_sd15/animatelcm/models/resnet.py:103
Methodforward
(self, input_tensor, temb)
animatelcm_sd15/animatelcm/models/resnet.py:209
Methodforward
( self, x_spatial: torch.Tensor, x_temporal: torch.Tensor, image_only_indicato
animatelcm_sd15/animatelcm/models/resnet.py:302
Methodforward
(self, input_tensor, temb, encoder_hidden_states, attention_mask=None, anchor_frame_idx=None)
animatelcm_sd15/animatelcm/models/motion_module.py:75
Methodforward
(self, hidden_states, encoder_hidden_states=None, attention_mask=None)
animatelcm_sd15/animatelcm/models/motion_module.py:132
Methodforward
(self, hidden_states, encoder_hidden_states=None, attention_mask=None, video_length=None)
animatelcm_sd15/animatelcm/models/motion_module.py:211
Methodforward
(self, x)
animatelcm_sd15/animatelcm/models/motion_module.py:244
Methodforward
(self, hidden_states, encoder_hidden_states=None, attention_mask=None, video_length=None)
animatelcm_sd15/animatelcm/models/motion_module.py:271
Methodforward
(self, x)
metrics/pytorch_i3d.py:22
Methodforward
(self, x)
metrics/pytorch_i3d.py:145
Methodforward
(self, x)
metrics/pytorch_i3d.py:338
Functionget_clip_score
(image_pil,text, clip_model, clip_processor)
metrics/clip_score.py:8
Functionget_fvd_logits
(videos, i3d, device)
metrics/fvd.py:30
Methodget_scalings
(self, sigma)
animatelcm_svd/animatelcm_scheduler.py:282
Methodget_velocity
( self, sample: torch.FloatTensor, noise: torch.FloatTensor, timesteps: torch.IntTensor )
animatelcm_sd15/animatelcm/scheduler/lcm_scheduler.py:686
Methodguidance_scale
(self)
animatelcm_svd/pipeline.py:311
Functionguidance_scale_embedding
See https://github.com/google-research/vdm/blob/dc27b98a554f65cdc654b800da5aa1846545d41b/model_vdm.py#L298 Args: timesteps (`torch.T
animatelcm_sd15/animatelcm/utils/lcm_utils.py:6
Methodheun_solver
(self, model_output, sample, indices, indices_next, model_fn)
animatelcm_svd/animate_lcm_utils.py:87
Methodindex_for_timestep
(self, timestep, schedule_timesteps=None)
animatelcm_svd/animatelcm_scheduler.py:105
Functionload_clip
()
metrics/clip_score.py:3
Functionload_fvd_model
(device)
metrics/fvd.py:35
Functionload_model_hook
(models, input_dir)
animatelcm_svd/train_svd_lcm.py:754
Methodnum_timesteps
(self)
animatelcm_svd/pipeline.py:324
Functionpolynomial_mmd
(X, Y)
metrics/fvd.py:104
Functionpredicted_origin
(model_output, timesteps, sample, prediction_type, alphas, sigmas)
animatelcm_sd15/animatelcm/utils/lcm_utils.py:52
Methodprevious_timestep
(self, timestep)
animatelcm_sd15/animatelcm/scheduler/lcm_scheduler.py:711
Functionrand_cosine_interpolated
Draws samples from an interpolated cosine timestep distribution (from simple diffusion).
animatelcm_svd/train_svd_lcm.py:78
Methodreplace_logits
(self, num_classes)
metrics/pytorch_i3d.py:323
Functionresize_image
(image, output_size=(1024, 576))
animatelcm_svd/app.py:109
Functionsample
( image: Image, seed: Optional[int] = 42, randomize_seed: bool = False, motion_bucket_id: int
animatelcm_svd/app.py:66
Functionsave_model_hook
(models, weights, output_dir)
animatelcm_svd/train_svd_lcm.py:744
Functionscale_for_loss
(timesteps, sample, prediction_type, alphas, sigmas)
animatelcm_sd15/animatelcm/utils/lcm_utils.py:68
Functionscalings_for_boundary_conditions
(timestep, sigma_data=0.5, timestep_scaling=10.0)
animatelcm_sd15/animatelcm/utils/lcm_utils.py:45
Methodset_use_memory_efficient_attention_xformers
(self, use_memory_efficient_attention_xformers: bool)
animatelcm_sd15/animatelcm/models/attention.py:225
Functionstable_unclip_image_encoder
Returns the image processor and clip image encoder for the img2img unclip pipeline. We currently know of two types of stable unclip models w
animatelcm_sd15/animatelcm/utils/convert_from_ckpt.py:857
Functionstable_unclip_image_noising_components
Returns the noising components for the img2img and txt2img unclip pipelines. Converts the stability noise augmentor into 1. a `StableUnC
animatelcm_sd15/animatelcm/utils/convert_from_ckpt.py:890
Methodstep_index
(self)
animatelcm_sd15/animatelcm/scheduler/lcm_scheduler.py:333
Methodstep_index
The index counter for current timestep. It will increae 1 after each scheduler step.
animatelcm_svd/animatelcm_scheduler.py:113
Functionupdate_ema
Update target parameters to be closer to those of source parameters using an exponential moving average. :param target_params: the targe
animatelcm_sd15/animatelcm/utils/lcm_utils.py:129
Methodupdate_lora_model
(self, lora_model_dropdown)
animatelcm_sd15/app-i2v.py:141
Methodupdate_lora_model
(self, lora_model_dropdown)
animatelcm_sd15/app.py:141
Functionupdate_personalized_model
()
animatelcm_sd15/app-i2v.py:286
Functionupdate_personalized_model
()
animatelcm_sd15/app.py:284
Functionzero_rank_print
(s)
animatelcm_sd15/animatelcm/utils/util.py:63
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