code: def mock_distribute(fn, num_workers=2, wait_for_chief=False):
      """Runs `fn` in multiple processes env vars for chief and clients.
  
      This function does not directly use any KerasTuner components, but only set
      up the corresponding environment variables for each of the threads. The
      environment variables are used by KerasTuner to check if the current thread
      is the chief or a client.
  
      All the exceptions, in the chief and all the clients, are collected raised
      in the main thread afterwards.
  
      Arguments:
          fn: Callable. The function to be called.
          num_workers: Int. The number of clients.
          wait_for_chief: Boolean. Default to False. Whether to wait for the chief
              thread to finish before ending the test.
      """
      port = str(portpicker.pick_unused_port())
      with mock.patch.object(os, "environ", MockEnvVars()):
  
          def chief_fn():
              # The IP address of the chief Oracle. Run in distributed mode when
              # present. Cloud oracle does not run in this mode because the Cloud
              # API coordinates workers itself.
              os.environ["KERASTUNER_ORACLE_IP"] = "127.0.0.1"
              # The port of the chief Oracle.
              os.environ["KERASTUNER_ORACLE_PORT"] = port
              # The ID of this process. 'chief' will run the OracleServicer
              # server.
              os.environ["KERASTUNER_TUNER_ID"] = "chief"
              fn()
  
          chief_thread = ExceptionStoringThread(target=chief_fn)
          chief_thread.daemon = True
          chief_thread.start()
  
          worker_threads = []
          for i in range(num_workers):
  
              def worker_fn():
                  os.environ["KERASTUNER_ORACLE_IP"] = "127.0.0.1"
                  os.environ["KERASTUNER_ORACLE_PORT"] = port
                  # Workers that are part of the same multi-worker
                  # DistributionStrategy should have the same TUNER_ID.
                  os.environ["KERASTUNER_TUNER_ID"] = f"worker{i}"
                  fn()
  
              worker_thread = ExceptionStoringThread(target=worker_fn)
              worker_thread.start()
              worker_threads.append(worker_thread)
  
          # Wait for chief and clients to finish
          for worker_thread in worker_threads:
              worker_thread.join()
          if wait_for_chief:
              chief_thread.join()
  
          # Re-raise exceptions from chief and clients.
          if chief_thread.raised_exception:
              six.reraise(*chief_thread.raised_exception)
          for worker_thread in worker_threads:
              if worker_thread.raised_exception is not None:
                  six.reraise(*worker_thread.raised_exception)
  
file_path: keras-tuner/keras_tuner/test_utils/mock_distribute.py
imports: import os
  import sys
  import threading
  from unittest import mock
  import portpicker
  import six
label_desc: Use image node_id 1 for calling a global function with example usage: mock_distribute(fn, num_workers, wait_for_chief) without return types