class_docstr: a custom module for exponentiation of tensors
class_docstr_tok: ["a","custom","module","for","exponentiation","of","tensors"]
code: def __init__(self):
      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 Exp object from inherited base classes: nn with example: obj = Exp()