class_docstr: The layers require a randomisation process, to randomly
  change some of the layer's states on the fly.
code: def __init__(self, name="randomised_op"):
      super(RandomisedLayer, self).__init__(name=name)
  
imports: from __future__ import absolute_import, print_function
  from abc import ABCMeta, abstractmethod
  import numpy
  import tensorflow
  from six import with_metaclass
  from niftynet.engine.application_variables import RESTORABLE
label_desc: Use image node_id 1 to create a new RandomisedLayer object from inherited base classes: Layer with example: obj = RandomisedLayer(name)