class_docstr: Request to an on-run-end callback.
  
  The callback is invoked immediately before the wrapped run() call ends.
class_docstr_tok: ["Request","to","an","on-run-end","callback",".","The","callback","is","invoked","immediately","before","the","wrapped","run","(",")","call","ends","."]
docstr: Constructor for `OnRunEndRequest`.
  
  Args:
    performed_action: (`OnRunStartAction`) Actually-performed action by the
      debug-wrapper session.
    run_metadata: run_metadata output from the run() call (if any).
    client_graph_def: (GraphDef) GraphDef from the client side, i.e., from
      the python front end of TensorFlow. Can be obtained with
      session.graph.as_graph_def().
    tf_error: (errors.OpError subtypes) TensorFlow OpError that occurred
      during the run (if any).
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code: def __init__(
      self,
      performed_action,
      run_metadata=None,
      client_graph_def=None,
      tf_error=None,
  ):
      """Constructor for `OnRunEndRequest`.
  
      Args:
        performed_action: (`OnRunStartAction`) Actually-performed action by the
          debug-wrapper session.
        run_metadata: run_metadata output from the run() call (if any).
        client_graph_def: (GraphDef) GraphDef from the client side, i.e., from
          the python front end of TensorFlow. Can be obtained with
          session.graph.as_graph_def().
        tf_error: (errors.OpError subtypes) TensorFlow OpError that occurred
          during the run (if any).
      """
  
      _check_type(performed_action, str)
      self.performed_action = performed_action
  
      if run_metadata is not None:
          _check_type(run_metadata, config_pb2.RunMetadata)
      self.run_metadata = run_metadata
      self.client_graph_def = client_graph_def
      self.tf_error = tf_error
  
imports: import abc
  import re
  import threading
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.debug.lib import debug_utils
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import stack
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import monitored_session
  from tensorflow.python.util import nest
  from tensorflow.python.util.compat import collections_abc
label_desc: Use image node_id 1 to create a new OnRunEndRequest object  with example: obj = OnRunEndRequest(performed_action, run_metadata, client_graph_def, tf_error)