class_docstr: Interface for all classes that are configurable
  via a parameters dictionary.
  
  Args:
    params: A dictionary of parameters.
    mode: A value in tf.contrib.learn.ModeKeys
docstr: Logs parameter values
docstr_tok: ["Logs","parameter","values"]
code: def _print_params(self):
      """Logs parameter values"""
      classname = self.__class__.__name__
      tf.logging.info("Creating %s in mode=%s", classname, self._mode)
      tf.logging.info("\n%s", yaml.dump({classname: self._params}))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import copy
  from pydoc import locate
  import six
  import yaml
  import tensorflow
label_desc: Use image node_id 2 for calling the Configurable obj's underlying member method code with example usage: obj._print_params() without return types