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.
code: def __enter__(self):
      old_context = (
          distribute_coordinator_context.get_current_worker_context()
      )
      if old_context:
          raise ValueError(
              "You cannot run distribute coordinator in a `worker_fn`.\t"
              + self._debug_message()
          )
      # pylint: disable=protected-access
      distribute_coordinator_context._worker_context.current = self
  
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 3 for calling the _WorkerContext obj's underlying member method code with example usage: obj.__enter__() without return types