code: def has_thread(prefix, running_threads):
      """Returns whether any 'running_threads' is prefixed with 'prefix'.
  
      Args:
        prefix: The prefix of the expected thread name.
        running_threads: A collection of the running thread names.
      """
      for thread in running_threads:
          if thread.startswith(prefix):
              return True
      return False
  
imports: import collections
  import dataclasses
  import functools
  import io
  import itertools
  import threading
  from absl import app
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.distribute import collective_all_reduce_strategy
  from tensorflow.python.distribute import multi_process_runner
  from tensorflow.python.distribute import multi_worker_test_base
  from tensorflow.python.distribute import tpu_strategy
  from tensorflow.python.distribute import values
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.util import nest
label_desc: Use image node_id 12 for calling a global function with example usage: has_thread(prefix, running_threads) and returns: False, True