class_docstr: Collect all tf.Tensor object, to be evaluated by tf.Session.run()
  These objects are grouped into::
  
      NETWORK_OUTPUT: to be decoded by an aggregator
      CONSOLE: to be printed on command line
      TF_SUMMARIES: to be added to tensorboard visualisation
docstr: get tf.Tensors to be evaluated by tf.Session().run()
  
  :param collection: in choices of
      [CONSOLE, TF_SUMMARIES, NETWORK_OUTPUT]
  :return: a variable dictionary
docstr_tok: ["get","tf.Tensors","to","be","evaluated","by","tf.Session","(",")",".run","(",")",":","param","collection",":","in","choices","of","[","CONSOLE",",","TF_SUMMARIES",",","NETWORK_OUTPUT","]",":","return",":","a","variable","dictionary"]
code: def variables(self, collection=CONSOLE):
      """
      get tf.Tensors to be evaluated by tf.Session().run()
  
      :param collection: in choices of
          [CONSOLE, TF_SUMMARIES, NETWORK_OUTPUT]
      :return: a variable dictionary
      """
      if collection == CONSOLE:
          return self.console_vars
      elif collection == TF_SUMMARIES:
          return self._merge_op if self._merge_op is not None else {}
      elif collection == NETWORK_OUTPUT:
          return self.output_vars
      else:
          tf.logging.fatal("unknown output %s", collection)
          raise ValueError
  
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from tensorflow.contrib.framework import list_variables
  from niftynet.io.misc_io import image3_axial, image3_coronal, image3_sagittal, resolve_checkpoint
  from niftynet.utilities import util_common
  from niftynet.utilities.restore_initializer import restore_initializer
label_desc: Use image node_id 4 for calling the OutputsCollector obj's underlying member method code with example usage: obj.variables(collection) and returns: self, unknown, self