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.
class_docstr_tok: ["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: Returns the id or index of the corresponding task.
docstr_tok: ["Returns","the","id","or","index","of","the","corresponding","task","."]
code: def task_id(self):
      """Returns the id or index of the corresponding task."""
      return self._task_id
  
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 14 for calling the _WorkerContext obj's underlying member method code with example usage: obj.task_id() and returns: self