class_docstr: Extends the Layer object to have trainable parameters,
  adding initializers and regularizers.
code: def regularizers(self, value):
      assert isinstance(value, dict)
      self._regularizers = value
  
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 10 for calling the TrainableLayer obj's underlying member method code with example usage: obj.regularizers(value) without return types