class_docstr: a custom module for concatenation of tensors
class_docstr_tok: ["a","custom","module","for","concatenation","of","tensors"]
code: def __init__(self, allow_broadcast=False):
      self.allow_broadcast = allow_broadcast
      super().__init__()
  
imports: from inspect import isclass
  import torch
  import torch.nn
  from pyro.distributions.util import broadcast_shape
label_desc: Use image node_id 1 to create a new ConcatModule object from inherited base classes: nn with example: obj = ConcatModule(allow_broadcast)