class_docstr: A reusable barrier class for worker synchronization.
docstr: Initializes the barrier object.
  
  Args:
    num_participants: an integer which is the expected number of calls of
      `wait` pass to through this barrier.
docstr_tok: ["Initializes","the","barrier","object",".","Args",":","num_participants",":","an","integer","which","is","the","expected","number","of","calls","of","`","wait","`","pass","to","through","this","barrier","."]
code: def __init__(self, num_participants):
      """Initializes the barrier object.
  
      Args:
        num_participants: an integer which is the expected number of calls of
          `wait` pass to through this barrier.
      """
      self._num_participants = num_participants
      self._counter = 0
      self._flag = False
      self._local_sense = threading.local()
      self._lock = threading.Lock()
      self._condition = threading.Condition()
  
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 1 to create a new _Barrier object from inherited base classes: object with example: obj = _Barrier(num_participants)