Functions — github.com/Francis-Rings/MotionFollower

↓ 43 callersMethodhead_to_batch_dim

r""" Reshape the tensor from `[batch_size, seq_len, dim]` to `[batch_size, seq_len, heads, dim // heads]` `heads` is the number of h

src/models/attn_process_diffuser.py:555

↓ 13 callersMethodnorm_encoder_hidden_states

r""" Normalize the encoder hidden states. Requires `self.norm_cross` to be specified when constructing the `Attention` class.

src/models/attn_process_diffuser.py:672

↓ 13 callersMethodprepare_attention_mask

r""" Prepare the attention mask for the attention computation. Args: attention_mask (`torch.Tensor`):

src/models/attn_process_diffuser.py:625

↓ 11 callersMethodbatch_to_head_dim

r""" Reshape the tensor from `[batch_size, seq_len, dim]` to `[batch_size // heads, seq_len, dim * heads]`. `heads` is the number of

src/models/attn_process_diffuser.py:538

↓ 10 callersMethod__init__

( self, query_dim: int, cross_attention_dim: Optional[int] = None, heads:

src/models/attn_process_diffuser.py:76

↓ 8 callersMethodset_processor

r""" Set the attention processor to use. Args: processor (`AttnProcessor`): The attention processor

src/models/attn_process_diffuser.py:360

↓ 7 callersMethodget_attention_scores

r""" Compute the attention scores. Args: query (`torch.Tensor`): The query tensor. key (`torch.Tensor`):

src/models/attn_process_diffuser.py:578

↓ 5 callersFunctionget_motion_module

(in_channels, motion_module_type: str, motion_module_kwargs: dict)

src/models/motion_module.py:33

↓ 4 callersMethod__init__

( self, in_channels: int, prev_output_channel: int, out_channels: int,

src/models/unet_3d_blocks.py:816

↓ 4 callersMethod__init__

(self, d_model, dropout=0.0, max_len=24)

src/models/motion_module.py:262

↓ 3 callersMethod_reshape

(hid_states, h)

src/models/attn_process_diffuser.py:2238

↓ 3 callersMethodget_noise_pred_single

(self, latents, t, context, normal_infer=False)

src/pipelines/null_text_optimization.py:54

↓ 2 callersMethod__init__

(self, channels, use_conv, dims=2, out_channels=None, padding=1)

src/models/appearance_net.py:102

↓ 2 callersMethod__init__

( self, channels, use_conv=False, use_conv_transpose=False, out_channe

src/models/resnet.py:30

↓ 2 callersMethodforward

(self, hidden_states)

src/models/resnet.py:244

↓ 2 callersMethodfrom_pretrained_2d

( cls, pretrained_model_path: PathLike, motion_module_path: PathLike, subf

src/models/estimator.py:649

↓ 2 callersFunctionget_down_block

( down_block_type, num_layers, in_channels, out_channels, temb_channels, add_downsampl

src/models/unet_3d_blocks.py:21

↓ 2 callersFunctionget_up_block

( up_block_type, num_layers, in_channels, out_channels, prev_output_channel, temb_chan

src/models/unet_3d_blocks.py:100

↓ 2 callersMethodnext_step

(self, model_output: Union[torch.FloatTensor, np.ndarray], timestep: int, sample: Union[tor

src/pipelines/null_text_optimization.py:42

↓ 2 callersFunctionordered_halving

(val)

src/pipelines/context.py:6

↓ 2 callersMethodprev_step

(self, model_output: Union[torch.FloatTensor, np.ndarray], timestep: int, sample: Union[tor

src/pipelines/null_text_optimization.py:30

↓ 2 callersFunctionsave_videos_grid

(videos: torch.Tensor, path: str, rescale=False, n_rows=6, fps=8)

src/utils/util.py:86

↓ 2 callersFunctionzero_module

(module)

src/models/motion_module.py:14

↓ 1 callersMethod__init__

(self, hidden_size)

src/models/transformer_3d.py:31

↓ 1 callersFunctionavg_pool_nd

(dims, *args, **kwargs)

src/models/appearance_net.py:23

↓ 1 callersFunctionconv_nd

(dims, in_channels, out_channels, kernel_size, **kwargs)

src/models/appearance_net.py:5

↓ 1 callersMethodddim_inversion

(self, latent)

src/pipelines/null_text_optimization.py:176

↓ 1 callersMethodddim_loop

(self, latent, ref_images_pil=None, pose_cond_fea=None)

src/utils/inversion.py:40

↓ 1 callersMethodddim_loop

(self, latent)

src/pipelines/null_text_optimization.py:157

↓ 1 callersMethoddecode_latents

(self, latents)

src/pipelines/motion_editor.py:110

↓ 1 callersMethoddecode_latents

(self, latents)

src/pipelines/pipeline_pose2vid_collection.py:104

↓ 1 callersMethodget_noise_pred

(self, latents, t, is_forward=True, context=None, normal_infer=False)

src/pipelines/null_text_optimization.py:58

↓ 1 callersMethodget_noise_pred_single

(self, latents, t, context, ref_images_pil=None, pose_cond_fea=None)

src/utils/inversion.py:26

↓ 1 callersMethodguidance_edit

( self, source_masks, target_masks, latent, l

src/pipelines/motion_editor.py:553

↓ 1 callersMethodinit_emb_img

(self, clip_emb_im=None)

src/utils/inversion.py:36

↓ 1 callersMethodinit_signals

(self, ref_images_list, ref_pose_list)

src/pipelines/null_text_optimization.py:117

↓ 1 callersFunctionmain

()

inference-sde.py:56

↓ 1 callersFunctionmodulate

(x, shift, scale)

src/models/transformer_3d.py:27

↓ 1 callersMethodnext_step

(self, model_output: Union[torch.FloatTensor, np.ndarray], timestep: int, sample: Union[tor

src/utils/inversion.py:14

↓ 1 callersMethodnull_optimization

(self, latents, null_inner_steps, epsilon)

src/pipelines/null_text_optimization.py:180

↓ 1 callersFunctionparse_args

()

inference-sde.py:29

↓ 1 callersMethodprepare_extra_step_kwargs

(self, generator, eta)

src/pipelines/motion_editor.py:125

↓ 1 callersMethodprepare_extra_step_kwargs

(self, generator, eta)

src/pipelines/pipeline_pose2vid_collection.py:119

↓ 1 callersMethodprepare_latents

( self, batch_size, num_channels_latents, width, height,

src/pipelines/pipeline_pose2vid_collection.py:140

↓ 1 callersFunctionsave_videos_from_pil

(pil_images, path, fps=8)

src/utils/util.py:51

↓ 1 callersFunctionseed_everything

(seed)

src/utils/util.py:16

↓ 1 callersMethodset_attention_slice

r""" Enable sliced attention computation. When this option is enabled, the attention module will split the input tensor in slices, to

src/models/unet_3d.py:282

↓ 1 callersMethodset_attention_slice

r""" Enable sliced attention computation. When this option is enabled, the attention module will split the input tensor in slices,

src/models/estimator.py:283

↓ 1 callersMethodset_attn_processor

r""" Sets the attention processor to use to compute attention. Parameters: processor (`dict` of `AttentionProcessor`

src/models/estimator.py:359

Method__call__

( self, ref_images, target_pose_images, width,

src/pipelines/motion_editor.py:291

Method__call__

( self, ref_images, pose_images, width, height, video_le

src/pipelines/pipeline_pose2vid_collection.py:285

Method__call__

( self, attn, hidden_states, encoder_hidden_states=None, attentio

src/models/attention_processor.py:23

Method__call__