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, emb):
      for layer in self:
          if isinstance(layer, TimestepBlock):
              x = layer(x, emb)
          else:
              x = layer(x)
      return x
  
imports: from abc import abstractmethod
  import math
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from .fp16_util import convert_module_to_f16, convert_module_to_f32
  from .nn import checkpoint, conv_nd, linear, avg_pool_nd, zero_module, normalization, timestep_embedding
label_desc: Use image node_id 1 for calling the TimestepEmbedSequential obj's underlying member method code with example usage: obj.forward(x, emb) and returns: x