class_docstr: This class consists of network variables and operations at each iteration.
  It is generated by the application engine but can be modified by the
  application as well.
class_docstr_tok: ["This","class","consists","of","network","variables","and","operations","at","each","iteration",".","It","is","generated","by","the","application","engine","but","can","be","modified","by","the","application","as","well","."]
docstr: A dictionary that maps graph elements to values
  to be fed into ``session.run(...)`` as feed_dict parameter
  
  :return: dictionary of operations
docstr_tok: ["A","dictionary","that","maps","graph","elements","to","values","to","be","fed","into","``","session.run","(","...",")","``","as","feed_dict","parameter",":","return",":","dictionary","of","operations"]
code: def data_feed_dict(self):
      """
      A dictionary that maps graph elements to values
      to be fed into ``session.run(...)`` as feed_dict parameter
  
      :return: dictionary of operations
      """
      if self._data_feed_dict is None:
          self._data_feed_dict = {}
      return self._data_feed_dict
  
imports: import itertools
  import time
  from niftynet.engine.application_variables import CONSOLE, TF_SUMMARIES
  from niftynet.engine.signal import TRAIN, VALID, INFER
  from niftynet.utilities.util_common import look_up_operations
label_desc: Use image node_id 5 for calling the IterationMessage obj's underlying member method code with example usage: obj.data_feed_dict() and returns: self