code: def testDistributedLoad(
      self, num_workers, repeated_load, sharding_policy
  ):
      cluster = data_service_test_base.TestCluster(
          num_workers=num_workers
      )
      dataset = dataset_ops.Dataset.range(10)
      self.evaluate(
          distributed_save_op.distributed_save(
              dataset, self._test_dir, cluster.dispatcher_address()
          )
      )
      _wait_for_snapshot(self._test_dir)
  
      dataset = dataset_ops.Dataset.load(self._test_dir)
      if repeated_load > 1:
          dataset = dataset.repeat(repeated_load)
      dataset = dataset.apply(
          data_service_ops.distribute(
              processing_mode=sharding_policy,
              service=cluster.dispatcher_address(),
          )
      )
  
      ignore_order = num_workers > 0
      expected = list(range(10)) * repeated_load
      if sharding_policy == data_service_ops.ShardingPolicy.OFF:
          expected *= num_workers
      self.assertDatasetProduces(
          dataset, expected, assert_items_equal=ignore_order
      )
  
imports: import os
  import shutil
  import tempfile
  import time
  from absl.testing import parameterized
  import numpy
  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.experimental.ops import distributed_save_op
  from tensorflow.python.data.experimental.service import _pywrap_snapshot_utils
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  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
  from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 8 for calling the DistributedSaveTest obj's underlying member method code with example usage: obj.testDistributedLoad(num_workers, repeated_load, sharding_policy) without return types