class_docstr: Tests garbage collecting unused local worker tasks.
  
  The user typically creates an iterator in each epoch. This should delete the
  previous iterator and releases the resources of it.
code: def testMultipleEpochs_WorkerRestart(self, num_remote_workers):
      num_local_workers = 1
      cluster = multi_process_cluster.MultiProcessCluster(
          num_local_workers=num_local_workers,
          num_remote_workers=num_remote_workers,
      )
  
      num_steps = 10
      dataset = self._make_distributed_infinite_range_dataset(
          cluster, job_name="shared_job_name"
      )
  
      get_next = self.getNext(dataset)
      for i in range(num_steps):
          self.assertEqual(self.evaluate(get_next()), i)
  
      # Verifies the worker re-creates the task after the iterator is deleted and
      # the worker restarts.
      del get_next
      cluster.restart_local_workers()
  
      get_next = self.getNext(dataset)
      for i in range(num_steps):
          self.assertEqual(self.evaluate(get_next()), i)
  
imports: import multiprocessing
  from absl.testing import parameterized
  from tensorflow.python.data.experimental.kernel_tests.service import multi_process_cluster
  from tensorflow.python.data.experimental.kernel_tests.service import test_base
  from tensorflow.python.data.experimental.ops import data_service_ops
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
label_desc: Use image node_id 6 for calling the LocalTaskGarbageCollectTest obj's underlying member method code with example usage: obj.testMultipleEpochs_WorkerRestart(num_remote_workers) without return types