class_docstr: The worker context class.
  
  This context object provides configuration information for each task. One
  context manager with a worker context object will be created per
  invocation to the `worker_fn` where `get_current_worker_context` can be called
  to access the worker context object.
docstr: Return whether the task is the chief worker.
docstr_tok: ["Return","whether","the","task","is","the","chief","worker","."]
code: def _is_chief(self):
      """Return whether the task is the chief worker."""
      if not self._cluster_spec or self._task_type in [
          _TaskType.CHIEF,
          _TaskType.EVALUATOR,
          None,
      ]:
          return True
  
      # If not local and chief not in the cluster_spec, use the first worker as
      # chief.
      if (
          _TaskType.CHIEF not in self._cluster_spec.jobs
          and self._task_type == _TaskType.WORKER
          and self._task_id == 0
      ):
          return True
      return False
  
imports: import copy
  import json
  import os
  import threading
  import time
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.distribute import distribute_coordinator_context
  from tensorflow.python.distribute import multi_worker_util
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import coordinator
  from tensorflow.python.training import monitored_session
  from tensorflow.python.training import server_lib
label_desc: Use image node_id 6 for calling the _WorkerContext obj's underlying member method code with example usage: obj._is_chief() and returns: False, True, True