class_docstr: Tests auto-sharding datasets with tf.data service.
class_docstr_tok: ["Tests","auto-sharding","datasets","with","tf.data","service","."]
docstr: Makes sure shards from all workers form the complete dataset.
docstr_tok: ["Makes","sure","shards","from","all","workers","form","the","complete","dataset","."]
code: def testRangeDataset_OneWorker(self):
      """Makes sure shards from all workers form the complete dataset."""
      cluster = _make_service_cluster(
          num_workers=1, local_shard_index=0
      )
      dataset = dataset_ops.Dataset.range(20)
      dataset = self.make_distributed_dataset(
          dataset,
          cluster=cluster,
          processing_mode=data_service_ops.ShardingPolicy.FILE_OR_DATA,
      )
      self.assertDatasetProduces(dataset, list(range(20)))
  
imports: from absl.testing import parameterized
  from tensorflow.core.protobuf import data_service_pb2
  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.kernel_tests.service.multi_process_cluster import MultiProcessCluster
  from tensorflow.python.data.experimental.ops import data_service_ops
  from tensorflow.python.data.experimental.ops import distribute
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.kernel_tests import tf_record_test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import readers
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
label_desc: Use image node_id 9 for calling the AutoShardTest obj's underlying member method code with example usage: obj.testRangeDataset_OneWorker() without return types