class_docstr: Initialization class that has gain property
  
  Parameters
  ----------
  gain : float
      Scales variance of the distribution by this factor. Value ``2``
      is a suitable choice for layers that have Relu non-linearity.
      Defaults to ``1``.
  
  seed : None or int
      Random seed. Integer value will make results reproducible.
      Defaults to ``None``.
class_docstr_tok: ["Initialization","class","that","has","gain","property","Parameters","--","--","--","--","--","gain",":","float","Scales","variance","of","the","distribution","by","this","factor",".","Value","``","2","``","is","a","suitable","choice","for","layers","that","have","Relu","non-linearity",".","Defaults","to","``","1","``",".","seed",":","None","or","int","Random","seed",".","Integer","value","will","make","results","reproducible",".","Defaults","to","``","None","``","."]
code: def __repr__(self):
      return "{}(gain={})".format(classname(self), self.gain)
  
imports: import abc
  import six
  import numpy
  import tensorflow
  from neupy.core.docs import SharedDocsABCMeta
label_desc: Use image node_id 2 for calling the InitializerWithGain obj's underlying member method code with example usage: obj.__repr__() and returns: str