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Functions380 in github.com/TencentARC/MotionCtrl

⨍ Functions 380◇ Types & classes 83

(self, ch_mult:list, in_channels, pretrained_model:nn.Module=None, reshape=F

lvdm/modules/networks/ae_modules.py:784

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

lvdm/modules/networks/openaimodel3d_next.py:60

( self, channels, emb_channels, dropout, out_channels=None, us

lvdm/modules/networks/openaimodel3d_next.py:126

(self, in_channels, out_channels=None, dropout=0.0, spatial_aware=False, use_image_dataset=False)

lvdm/modules/networks/openaimodel3d_next.py:242

(self, in_channels, model_channels, out_channels,

lvdm/modules/networks/openaimodel3d_next.py:314

lvdm/modules/encoders/condition2.py:14

(self, version="google/t5-v1_1-large", device="cuda", max_length=77, freeze=True)

lvdm/modules/encoders/condition2.py:63

(self, version="openai/clip-vit-large-patch14", device="cuda", max_length=77, freeze=True, la

lvdm/modules/encoders/condition2.py:100

( self, model, jit=False, device='cuda' if torch.cuda.is_avail

lvdm/modules/encoders/condition2.py:140

(self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", max_length=77, freeze=Tru

lvdm/modules/encoders/condition2.py:187

(self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", max_length=77, freeze=Tru

lvdm/modules/encoders/condition2.py:246

(self, clip_version="openai/clip-vit-large-patch14", t5_version="google/t5-v1_1-xl", device="cuda",

lvdm/modules/encoders/condition2.py:301

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

lvdm/modules/encoders/adapter.py:15

(self, in_c, out_c, down, ksize=3, sk=False, use_conv=True)

lvdm/modules/encoders/adapter.py:36

(self, first_stage_config, cond_stage_config, num_timesteps

lvdm/models/ddpm3d.py:426

(self, diff_model_config, conditioning_key)

lvdm/models/ddpm3d.py:1019

(self, *args, vq_interface=False, **kwargs)

lvdm/models/autoencoder.py:205

(self, model, schedule="linear", **kwargs)

lvdm/models/samplers/ddim.py:13

(self, x, context=None, temporal_context=None, mask=None, no_temporal_attn=None, )

lvdm/modules/attention_temporal.py:462

(self, x, context=None, mask=None)

lvdm/modules/attention.py:164

(self, x, emb, batch_size=None, is_imgbatch=False)

lvdm/modules/networks/openaimodel3d_next.py:212

Method_forward_no_temporal_attn

(self, x, context=None, temporal_context=None, )

lvdm/modules/attention_temporal.py:480

Method_forward_nocontext

(self, x, no_temporal_attn=None)

lvdm/modules/attention_temporal.py:501

Functionadd_camera_motion

(camera_motion, camera_mode)

gradio_utils/page_control.py:495

Functionadd_complex_camera_motion

(camera_motion)

gradio_utils/page_control.py:506

Functionadd_provided_traj

gradio_utils/page_control.py:577

Functionadd_traj_point

(evt: gr.SelectData, )

gradio_utils/page_control.py:571

Functionautocast

lvdm/common.py:19

for x in ctx.input_tensors: if isinstance(x, int): print('-----------------', ctx.run_function)

lvdm/common.py:120

Functionbetas_for_alpha_bar

Create a beta schedule that discretizes the given alpha_t_bar function, which defines the cumulative product of (1-beta) over time from t = [

lvdm/models/utils_diffusion.py:89

Functionchange_camera_mode

(combine_type, camera_mode)

gradio_utils/page_control.py:511

Functionchange_camera_speed

gradio_utils/page_control.py:566

Functioncheck_istarget

name: full name of source para para_list: partial name of target para

utils/utils.py:18

Methodconfigure_optimizers

lvdm/models/ddpm3d.py:415

Methodconfigure_optimizers

configure_optimizers for LatentDiffusion

lvdm/models/ddpm3d.py:960

Methodconfigure_optimizers

lvdm/models/autoencoder.py:165

Methodcount_flops

lvdm/modules/attention_temporal.py:911

(self, x, *args, **kwargs)

lvdm/models/autoencoder.py:212

Methoddifferentiable_decode_first_stage

same as decode_first_stage but without decorator

lvdm/models/ddpm3d.py:603

Functiondisabled_train

Overwrite model.train with this function to make sure train/eval mode does not change anymore.

lvdm/basics.py:20

Functiondisabled_train

Overwrite model.train with this function to make sure train/eval mode does not change anymore.

lvdm/modules/encoders/condition2.py:54

Functiondo_autocast

(*args, **kwargs)

lvdm/common.py:20

Methodefficient_forward

(self, x, context=None, mask=None)

lvdm/modules/attention_temporal.py:327

Methodefficient_forward

(self, x, context=None, mask=None)

lvdm/modules/attention.py:105

lvdm/modules/encoders/condition2.py:23

lvdm/modules/encoders/condition2.py:88

lvdm/modules/encoders/condition2.py:135

lvdm/modules/encoders/condition2.py:237

lvdm/modules/encoders/condition2.py:296

lvdm/modules/encoders/condition2.py:309

(self, x, *args, **kwargs)

lvdm/models/autoencoder.py:209

Functionfn_traj_droplast

gradio_utils/page_control.py:585

Functionfn_vis_camera

(info_mode, camera_args=None)

gradio_utils/page_control.py:596

Functionfn_vis_traj

gradio_utils/page_control.py:637

(ctx, run_function, length, *args)

lvdm/common.py:109

lvdm/basics.py:83

(self, c_concat, c_crossattn)

lvdm/basics.py:103

lvdm/modules/attention_temporal.py:57

(self, length_q, length_k)

lvdm/modules/attention_temporal.py:76

(self, x, context=None, mask=None)

lvdm/modules/attention_temporal.py:179

(self, x, context=None, mask=None)

lvdm/modules/attention_temporal.py:295

(self, x, context=None, mask=None)

lvdm/modules/attention_temporal.py:358

(self, x, context=None, temporal_context=None, no_temporal_attn=None, attn_mask=None, **kwargs)

lvdm/modules/attention_temporal.py:438

(self, x, context=None, temporal_context=None, **kwargs)

lvdm/modules/attention_temporal.py:755

(self, x, mask=None)

lvdm/modules/attention_temporal.py:842

Apply QKV attention. :param qkv: an [N x (H * 3 * C) x T] tensor of Qs, Ks, and Vs. :return: an [N x (H * C) x T] tensor aft

lvdm/modules/attention_temporal.py:889

Apply QKV attention. :param qkv: an [N x (3 * H * C) x T] tensor of Qs, Ks, and Vs. :return: an [N x (H * C) x T] tensor aft

lvdm/modules/attention_temporal.py:925

lvdm/modules/x_transformer.py:34

(self, x, seq_dim=1, offset=0)

lvdm/modules/x_transformer.py:45

(self, x, **kwargs)

lvdm/modules/x_transformer.py:123

(self, x, **kwargs)

lvdm/modules/x_transformer.py:134

lvdm/modules/x_transformer.py:146

lvdm/modules/x_transformer.py:158

(self, x, residual)

lvdm/modules/x_transformer.py:164

(self, x, residual)

lvdm/modules/x_transformer.py:173

lvdm/modules/x_transformer.py:189

lvdm/modules/x_transformer.py:210

( self, x, context=None, mask=None, context_mask=N

lvdm/modules/x_transformer.py:268

( self, x, context=None, mask=None, context_mask=N

lvdm/modules/x_transformer.py:481

( self, x, return_embeddings=False, mask=None, ret

lvdm/modules/x_transformer.py:598

(self, length_q, length_k)

lvdm/modules/attention.py:30

(self, x, context=None, mask=None)

lvdm/modules/attention.py:71

(self, x, context=None, mask=None)

lvdm/modules/attention.py:150

(self, x, context=None)

lvdm/modules/attention.py:209

(self, x, context=None, is_imgbatch=False)

lvdm/modules/attention.py:276

lvdm/modules/attention.py:334

lvdm/modules/attention.py:355

lvdm/modules/attention.py:367

lvdm/modules/attention.py:405

lvdm/modules/networks/ae_modules.py:55

lvdm/modules/networks/ae_modules.py:104

lvdm/modules/networks/ae_modules.py:125

(self, x, temb)

lvdm/modules/networks/ae_modules.py:192

(self, x, t=None, context=None)

lvdm/modules/networks/ae_modules.py:314

lvdm/modules/networks/ae_modules.py:432

lvdm/modules/networks/ae_modules.py:541

lvdm/modules/networks/ae_modules.py:606

lvdm/modules/networks/ae_modules.py:653

lvdm/modules/networks/ae_modules.py:692

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