class_docstr: Normalize inputs by a fixed divisor.
docstr: Class constructor.
  
  Arguments:
      divisor (float, optional): Normalization factor (default: 128)
      name (string, optional): Name (default: None)
docstr_tok: ["Class","constructor",".","Arguments",":","divisor","(","float",",","optional",")",":","Normalization","factor","(","default",":","128",")","name","(","string",",","optional",")",":","Name","(","default",":","None",")"]
code: def __init__(self, name=None, divisor=128.0):
      """
      Class constructor.
  
      Arguments:
          divisor (float, optional): Normalization factor (default: 128)
          name (string, optional): Name (default: None)
      """
      super(Normalizer, self).__init__(name)
      self.divisor = divisor
  
imports: from __future__ import division
  from neon.transforms.transform import Transform
label_desc: Use image node_id 1 to create a new Normalizer object from inherited base classes: Transform with example: obj = Normalizer(name, divisor)