class_docstr: Normalize inputs by a fixed divisor.
docstr: Returns the normalized value.
  
  Arguments:
      x (Tensor or optree): Input value
  
  Returns:
      Tensor or optree: Output :math:`x / N`
docstr_tok: ["Returns","the","normalized","value",".","Arguments",":","x","(","Tensor","or","optree",")",":","Input","value","Returns",":","Tensor","or","optree",":","Output",":","math",":","`","x","\/","N","`"]
code: def __call__(self, x):
      """
      Returns the normalized value.
  
      Arguments:
          x (Tensor or optree): Input value
  
      Returns:
          Tensor or optree: Output :math:`x / N`
      """
      return x / self.divisor
  
imports: from __future__ import division
  from neon.transforms.transform import Transform
label_desc: Use image node_id 2 for calling the Normalizer obj's underlying member method code with example usage: obj.__call__(x) and returns: unknown