code: def testTupleOutput(self):
      dataset = (
          dataset_ops.Dataset.range(1024)
          .map(lambda x: (x, x))
          .batch(32)
      )
      rebatched_dataset = distribute._LegacyRebatchDataset(
          dataset, num_replicas=4
      )
      expected_output = [
          (
              [
                  k for k in range(i, i + 8)
              ],  # pylint: disable=g-complex-comprehension
              [k for k in range(i, i + 8)],
          )
          for i in range(0, 1024, 8)
      ]
      self.assertDatasetProduces(rebatched_dataset, expected_output)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import distribute
  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.data.util import nest
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import image_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
label_desc: Use image node_id 6 for calling the LegacyRebatchDatasetTest obj's underlying member method code with example usage: obj.testTupleOutput() without return types