class_docstr: Extends the Layer object to have trainable parameters,
  adding initializers and regularizers.
code: def __init__(self, name="trainable_op"):
      super(TrainableLayer, self).__init__(name=name)
  
      self._initializers = None
      self._regularizers = None
  
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 TrainableLayer object from inherited base classes: Layer with example: obj = TrainableLayer(name)