code: def test_worker_start_failure(ray_start_4_cpus):
      def init_hook():
          pass
  
      def init_hook_fail():
          ray.actor.exit_actor()
  
      class TestBackendExecutor(BackendExecutor):
          def __init__(self, *args, **kwargs):
              super().__init__(*args, **kwargs)
  
          def _restart(self):
              self._initialization_hook = init_hook
              super()._restart()
  
      config = BackendConfig()
  
      iterator = create_iterator(
          lambda x: 1,
          config,
          backend_executor_cls=TestBackendExecutor,
          init_hook=init_hook_fail,
      )
      assert len(iterator._backend_executor.get_worker_group()) == 2
  
imports: import functools
  import time
  from unittest.mock import patch
  import pytest
  import ray
  from ray import train
  from ray.air._internal.util import StartTraceback
  from ray.train import DataConfig
  from ray.train._internal.backend_executor import BackendExecutor
  from ray.train._internal.session import get_session, init_session
  from ray.train._internal.utils import construct_train_func
  from ray.train._internal.worker_group import WorkerGroup
  from ray.train.backend import BackendConfig
  from ray.train.examples.pytorch.torch_linear_example import train_func
  from ray.train.examples.tf.tensorflow_mnist_example import train_func
  from ray.train.tests.util import mock_storage_context
  from ray.train.trainer import TrainingIterator
label_desc: Use image node_id 11 for calling a global function with example usage: test_worker_start_failure(ray_start_4_cpus) without return types