code: def should_run_distribute_coordinator(config):
      """Checks the config to see whether to run distribute coordinator."""
      # pylint: disable=protected-access
      if (
          not hasattr(config, "_distribute_coordinator_mode")
          or config._distribute_coordinator_mode is None
      ):
          logging.info("Not using Distribute Coordinator.")
          return False
      if not isinstance(
          config._distribute_coordinator_mode, six.string_types
      ) or config._distribute_coordinator_mode not in [
          dc.CoordinatorMode.STANDALONE_CLIENT,
          dc.CoordinatorMode.INDEPENDENT_WORKER,
      ]:
          logging.warning(
              "Unexpected distribute_coordinator_mode: %r",
              config._distribute_coordinator_mode,
          )
          return False
      if not config.cluster_spec:
          logging.warning(
              "Running `train_and_evaluate` locally, ignoring "
              "`experimental_distribute_coordinator_mode`."
          )
          return False
      return True
  
file_path: tensorflow/tensorflow/python/distribute/estimator_training.py
imports: import copy
  import six
  from tensorflow.python.distribute import distribute_coordinator
  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 server_lib
label_desc: Use image node_id 6 for calling a global function with example usage: should_run_distribute_coordinator(config) and returns: True, False, False, False