class_docstr: Normalize inputs by a fixed divisor.
docstr: Returns the derivative.
  
  Arguments:
      x (Tensor or optree): Input value
  
  Returns:
      Tensor or optree: Derivative
docstr_tok: ["Returns","the","derivative",".","Arguments",":","x","(","Tensor","or","optree",")",":","Input","value","Returns",":","Tensor","or","optree",":","Derivative"]
code: def bprop(self, x):
      """
      Returns the derivative.
  
      Arguments:
          x (Tensor or optree): Input value
  
      Returns:
          Tensor or optree: Derivative
      """
      return 1.0 / self.divisor
  
imports: from __future__ import division
  from neon.transforms.transform import Transform
label_desc: Use image node_id 3 for calling the Normalizer obj's underlying member method code with example usage: obj.bprop(x) and returns: unknown