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Functions214 in github.com/TMElyralab/MusePose

⨍ Functions 214◇ Types & classes 48
Functionget_up_block
( up_block_type, num_layers, in_channels, out_channels, prev_output_channel, temb_chan
musepose/models/unet_3d_blocks.py:94
Methodhacked_basic_transformer_inner_forward
( self, hidden_states: torch.FloatTensor, attention_mask: Optional[torch.F
musepose/models/mutual_self_attention.py:93
Functionimport_filename
(filename)
pose/script/tool.py:27
Functionlinear
(v1, v2, t)
musepose/pipelines/utils.py:15
Methodprepare_condition
( self, cond_image, width, height, device, dtype, do_c
musepose/pipelines/pipeline_pose2img.py:172
Functionsave_videos_grid
(videos: torch.Tensor, path: str, rescale=False, n_rows=6, fps=8)
pose/script/tool.py:88
Functionseed_everything
(seed)
pose/script/tool.py:16
Methodset_attn_processor
r""" Sets the attention processor to use to compute attention. Parameters: processor (`dict` of `AttentionProcessor` or o
musepose/models/unet_3d.py:359
Methodset_chunk_feed_forward
(self, chunk_size: Optional[int], dim: int = 0)
musepose/models/attention.py:173
Methodset_default_attn_processor
Disables custom attention processors and sets the default attention implementation.
musepose/models/unet_2d_condition.py:740
Functionset_tensor_interpolation_method
(is_slerp)
musepose/pipelines/utils.py:10
Methodset_use_memory_efficient_attention_xformers
( self, use_memory_efficient_attention_xformers: bool, attention_op: Optional[Callable
musepose/models/motion_module.py:309
Functionslerp
( v0: torch.Tensor, v1: torch.Tensor, t: float, DOT_THRESHOLD: float = 0.9995 )
musepose/pipelines/utils.py:19
Functionuniform
( step: int = ..., num_steps: Optional[int] = None, num_frames: int = ..., context_size: Optio
musepose/pipelines/context.py:15
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