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.
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docstr: operations (tf graph elements) to be fed into
  ``session.run(...)``. This is currently mainly used
  for passing network gradient updates ops to ``session.run``.
  
  To modify the operations, assigns ``self.ops_to_run``
  
  :return: a copy of the operation dictionary
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code: def ops_to_run(self):
      """
      operations (tf graph elements) to be fed into
      ``session.run(...)``. This is currently mainly used
      for passing network gradient updates ops to ``session.run``.
  
      To modify the operations, assigns ``self.ops_to_run``
  
      :return: a copy of the operation dictionary
      """
      if self._ops_to_run is None:
          self._ops_to_run = {}
      assert isinstance(
          self._ops_to_run, dict
      ), "ops to run should be a dictionary"
      return self._ops_to_run
  
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 3 for calling the IterationMessage obj's underlying member method code with example usage: obj.ops_to_run() and returns: self