class_docstr: a custom module for exponentiation of tensors
class_docstr_tok: ["a","custom","module","for","exponentiation","of","tensors"]
code: def forward(self, val):
      return torch.exp(val)
  
imports: from inspect import isclass
  import torch
  import torch.nn
  from pyro.distributions.util import broadcast_shape
label_desc: Use image node_id 2 for calling the Exp obj's underlying member method code with example usage: obj.forward(val) and returns: torch