class_docstr: A sequential module that passes timestep embeddings to the children that
  support it as an extra input.
class_docstr_tok: ["A","sequential","module","that","passes","timestep","embeddings","to","the","children","that","support","it","as","an","extra","input","."]
code: def forward(
      self,
      x: th.Tensor,
      emb: th.Tensor,
      context: Optional[th.Tensor] = None,
      image_only_indicator: Optional[th.Tensor] = None,
      time_context: Optional[int] = None,
      num_video_frames: Optional[int] = None,
  ):
      from ...modules.diffusionmodules.video_model import VideoResBlock
  
      for layer in self:
          module = layer
  
          if isinstance(module, TimestepBlock) and not isinstance(
              module, VideoResBlock
          ):
              x = layer(x, emb)
          elif isinstance(module, VideoResBlock):
              x = layer(x, emb, num_video_frames, image_only_indicator)
          elif isinstance(module, SpatialVideoTransformer):
              x = layer(
                  x,
                  context,
                  time_context,
                  num_video_frames,
                  image_only_indicator,
              )
          elif isinstance(module, SpatialTransformer):
              x = layer(x, context)
          else:
              x = layer(x)
      return x
  
imports: import logging
  import math
  from abc import abstractmethod
  from typing import Iterable, List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from einops import rearrange
  from torch.utils.checkpoint import checkpoint
  from ...modules.attention import SpatialTransformer
  from ...modules.diffusionmodules.util import avg_pool_nd, conv_nd, linear, normalization, timestep_embedding, zero_module
  from ...modules.video_attention import SpatialVideoTransformer
  from ...util import exists
label_desc: Use image node_id 1 for calling the TimestepEmbedSequential obj's underlying member method code with example usage: obj.forward(x, emb, context, image_only_indicator, time_context, num_video_frames) and returns: x