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Functions480 in github.com/Francis-Rings/StableAnimator

⨍ Functions 480◇ Types & classes 92
Method__init__
(self, s=64.0, m=0.40)
animation/helper/losses.py:89
Method__init__
(self, optimizer, warmup_iters, total_iters=5, power=1.0, last_epoch=-1, verbose=False)
animation/helper/lr_scheduler.py:7
Method__init__
(self, num_features)
animation/helper/backbones/vit.py:26
Method__init__
(self, dim: int, num_heads: int = 8, qkv_bias: bool = False
animation/helper/backbones/vit.py:36
Method__init__
(self, dim: int, num_heads: int, num_patches: int,
animation/helper/backbones/vit.py:75
Method__init__
(self, img_size=108, patch_size=9, in_channels=3, embed_dim=768)
animation/helper/backbones/vit.py:115
Method__init__
(self, img_size: int = 112, patch_size: int = 16, in_channe
animation/helper/backbones/vit.py:139
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1)
animation/helper/backbones/iresnet.py:31
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1)
animation/helper/backbones/iresnet2060.py:34
Method__init__
(self, in_c, out_c, kernel=(1, 1), stride=(1, 1), padding=(0, 0), groups=1)
animation/helper/backbones/mobilefacenet.py:17
Method__init__
(self, in_c, out_c, kernel=(1, 1), stride=(1, 1), padding=(0, 0), groups=1)
animation/helper/backbones/mobilefacenet.py:30
Method__init__
(self, in_c, out_c, residual=False, kernel=(3, 3), stride=(2, 2), padding=(1, 1), groups=1)
animation/helper/backbones/mobilefacenet.py:42
Method__init__
(self, c, num_block, groups, kernel=(3, 3), stride=(1, 1), padding=(1, 1))
animation/helper/backbones/mobilefacenet.py:64
Method__init__
(self, fp16=False, num_features=512, blocks=(1, 4, 6, 2), scale=2)
animation/helper/backbones/mobilefacenet.py:89
Method__init__
(self)
animation/helper/utils/utils_logging.py:10
Method__init__
( self, dataset, num_replicas=None, # world_size rank=None, # local_rank
animation/helper/utils/utils_distributed_sampler.py:83
Method__init__
(self, val_targets, rec_prefix, summary_writer=None, image_size=(112, 112), wandb_logger=None)
animation/helper/utils/utils_callbacks.py:16
Method__init__
(self, frequent, total_step, batch_size, start_step=0,writer=None)
animation/helper/utils/utils_callbacks.py:69
Method__init__
(self, n_splits=2, shuffle=False)
animation/helper/eval/verification.py:42
Method__init__
(self)
DWPose/dwpose_utils/wholebody.py:9
Method__init__
(self)
DWPose/dwpose_utils/__init__.py:34
Method__init__
(self)
DWPose/dwpose_utils/__init__.py:76
Method__init__
(self, device='cpu')
DWPose/dwpose_utils/dwpose_detector.py:12
Method__iter__
(self)
animation/helper/dataset.py:103
Method__iter__
(self)
animation/helper/dataset.py:114
Method__iter__
(self)
animation/helper/utils/utils_distributed_sampler.py:102
Method__len__
(self)
animation/dataset/animation_dataset.py:40
Method__len__
(self)
animation/pipelines/euler_discrete_pro.py:812
Method__len__
(self)
animation/helper/onnx_ijbc.py:36
Method__len__
(self)
animation/helper/dataset.py:172
Method__len__
(self)
animation/helper/dataset.py:189
Method__next__
(self)
animation/helper/dataset.py:100
Method__next__
(self)
animation/helper/dataset.py:128
Method__next__
(self)
animation/helper/dataset.py:272
Method_get_closed_form_lr
(self)
animation/helper/lr_scheduler.py:31
Method_init_weights
(self, m)
animation/helper/backbones/vit.py:208
Method_set_gradient_checkpointing
(self, module, value=False)
animation/modules/refined_vae.py:228
Methodadd_noise
( self, original_samples: torch.Tensor, noise: torch.Tensor, timesteps: to
animation/pipelines/euler_discrete_pro.py:742
Methodattn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
animation/modules/unet.py:257
Methodattn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
animation/modules/refined_vae.py:234
Methodbackward
Args: loss_grad (torch.Tensor): gradient backward by last layer Returns: gradients for each input in forward
animation/helper/partial_fc_v2.py:199
Methodbegin_index
The index for the first timestep. It should be set from pipeline with `set_begin_index` method.
animation/pipelines/euler_discrete_pro.py:354
Functioncollate_fn
(data)
animation/helper/onnx_ijbc.py:61
Methodcreate_custom_forward
(module, return_dict=None)
animation/modules/unet_3d_blocks.py:1086
Methodcreate_custom_forward
(module)
animation/modules/unet_3d_blocks.py:1176
Methodcreate_custom_forward
(module, return_dict=None)
animation/modules/unet_3d_blocks.py:1289
Methodcreate_custom_forward
(module)
animation/modules/unet_3d_blocks.py:1391
Methodcreate_custom_forward
(module, return_dict=None)
animation/modules/unet_3d_blocks.py:1511
Methodcreate_custom_forward
(module)
animation/modules/refined_vae.py:89
Functioncreate_pipeline
create mimicmotion pipeline and load pretrained weight Args: infer_config (str): device (str or torch.device): "cpu" or "cuda:{d
animation/utils/loader.py:35
Methodcustom_forward
(*inputs)
animation/modules/unet_3d_blocks.py:1087
Methodcustom_forward
(*inputs)
animation/modules/unet_3d_blocks.py:1177
Methodcustom_forward
(*inputs)
animation/modules/unet_3d_blocks.py:1290
Methodcustom_forward
(*inputs)
animation/modules/unet_3d_blocks.py:1392
Methodcustom_forward
(*inputs)
animation/modules/unet_3d_blocks.py:1512
Methodcustom_forward
(*inputs)
animation/modules/refined_vae.py:90
Functiondecode_latents_scheduler
(latents, num_frames, decode_chunk_size=8, vae=None, device=None)
animation/pipelines/euler_discrete_pro.py:34
Functiondenormalize
(images: Union[np.ndarray, torch.Tensor])
animation/pipelines/euler_discrete_pro.py:20
FunctiondivideIntoNstrand
(listTemp, n)
animation/helper/eval_ijbc.py:113
Methoddo_classifier_free_guidance
(self)
animation/pipelines/inference_pipeline_animation.py:336
Methoddo_classifier_free_guidance
(self)
animation/pipelines/pipeline_animation.py:357
Methoddo_classifier_free_guidance
(self)
animation/pipelines/validation_pipeline_animation.py:364
Methoddo_classifier_free_guidance
(self)
animation/pipelines/inference_pipeline_animation_pro.py:339
Functiondownload_image
(url)
train.py:821
Functiondownload_image
(url)
train_single.py:832
Functiondraw_bodypose
(canvas, candidate, subset)
DWPose/dwpose_utils/util.py:68
Functiondraw_facepose
(canvas, all_lmks)
DWPose/dwpose_utils/util.py:140
Functiondraw_handpose
(canvas, all_hand_peaks)
DWPose/dwpose_utils/util.py:112
FunctiondumpR
(data_set, backbone, batch_size, name='', data_extra=None, l
animation/helper/eval/verification.py:277
Methodenable_forward_chunking
Sets the attention processor to use [feed forward chunking](https://huggingface.co/blog/reformer#2-chunked-feed-forward-layers).
animation/modules/unet.py:337
Functionexport_to_video
(video_frames, output_video_path, fps)
train.py:336
Functionexport_to_video
(video_frames, output_video_path, fps)
train_single.py:340
FunctionfaceDetect
(candidate, subset, oriImg)
DWPose/dwpose_utils/util.py:221
Functionfaceid_loss_compute
(vae, latents, target_images, num_frames, decode_chunk_size, image_processor, device, face_loss_model=None, fa
animation/utils/utils.py:86
Methodfn_recursive_add_processors
( name: str, module: torch.nn.Module, processors: Dict[str, At
animation/modules/unet.py:266
Methodfn_recursive_add_processors
(name: str, module: torch.nn.Module, processors: Dict[str, AttentionProcessor])
animation/modules/refined_vae.py:243
Methodfn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
animation/modules/unet.py:305
Methodfn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
animation/modules/refined_vae.py:279
Methodfn_recursive_feed_forward
(module: torch.nn.Module, chunk_size: int, dim: int)
animation/modules/unet.py:356
Functionforward
(self, hidden_states)
animation/utils/geglu_patch.py:6
Methodforward
r""" The [`UNetSpatioTemporalConditionModel`] forward method. Args: sample (`torch.FloatTensor`): The noi
animation/modules/unet.py:366
Methodforward
The [`TransformerTemporal`] forward method. Args: hidden_states (`torch.LongTensor` of shape `(batch size, num laten
animation/modules/transformer_temporal.py:121
Methodforward
Args: hidden_states (`torch.Tensor` of shape `(batch size, channel, height, width)`): Input hidden_states.
animation/modules/transformer_temporal.py:281
Methodforward
The [`TransformerTemporal`] forward method. Args: hidden_states (`torch.LongTensor` of shape `(batch size, num latent pi
animation/modules/attention.py:107
Methodforward
Args: hidden_states (`torch.FloatTensor` of shape `(batch size, channel, height, width)`): Input hidden_states.
animation/modules/attention.py:263
Methodforward
(self, x)
animation/modules/pose_net.py:57
Methodforward
( self, hidden_states: torch.Tensor, temb: Optional[torch.Tensor] = None,
animation/modules/unet_3d_blocks.py:379
Methodforward
( self, hidden_states: torch.Tensor, temb: Optional[torch.Tensor] = None,
animation/modules/unet_3d_blocks.py:512
Methodforward
( self, hidden_states: torch.Tensor, temb: Optional[torch.Tensor] = None,
animation/modules/unet_3d_blocks.py:619
Methodforward
( self, hidden_states: torch.Tensor, res_hidden_states_tuple: Tuple[torch.Tensor, .
animation/modules/unet_3d_blocks.py:737
Methodforward
( self, hidden_states: torch.Tensor, res_hidden_states_tuple: Tuple[torch.Tensor, .
animation/modules/unet_3d_blocks.py:859
Methodforward
( self, hidden_states: torch.Tensor, image_only_indicator: torch.Tensor, )
animation/modules/unet_3d_blocks.py:946
Methodforward
( self, hidden_states: torch.Tensor, image_only_indicator: torch.Tensor, )
animation/modules/unet_3d_blocks.py:997
Methodforward
( self, hidden_states: torch.Tensor, temb: Optional[torch.Tensor] = None,
animation/modules/unet_3d_blocks.py:1070
Methodforward
( self, hidden_states: torch.Tensor, temb: Optional[torch.Tensor] = None,
animation/modules/unet_3d_blocks.py:1166
Methodforward
( self, hidden_states: torch.Tensor, temb: Optional[torch.Tensor] = None,
animation/modules/unet_3d_blocks.py:1276
Methodforward
( self, hidden_states: torch.Tensor, res_hidden_states_tuple: Tuple[torch.Tensor, .
animation/modules/unet_3d_blocks.py:1375
Methodforward
( self, hidden_states: torch.Tensor, res_hidden_states_tuple: Tuple[torch.Tensor, .
animation/modules/unet_3d_blocks.py:1484
Methodforward
r"""The forward method of the `Decoder` class.
animation/modules/refined_vae.py:75
Methodforward
r""" Args: sample (`torch.Tensor`): Input sample. sample_posterior (`bool`, *optional*, defaults to `False`):
animation/modules/refined_vae.py:362
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