code: def testMultipleBatches(self):
      dataset = dataset_ops.Dataset.range(16).batch(2).batch(4)
      self.assertEqual([[None, None]], _flat_shapes(dataset))
  
      # Each element is a list of 4 elements where each element is a list of 2.
      expected_output = [
          [[0, 1], [2, 3], [4, 5], [6, 7]],
          [[8, 9], [10, 11], [12, 13], [14, 15]],
      ]
      self.assertDatasetProduces(dataset, expected_output)
  
      rebatched_dataset = distribute._LegacyRebatchDataset(dataset, 2)
      self.assertEqual([[None, None]], _flat_shapes(rebatched_dataset))
      # Each element is a list of 2 elements where each element is a list of 2.
      expected_output = [
          [[0, 1], [2, 3]],
          [[4, 5], [6, 7]],
          [[8, 9], [10, 11]],
          [[12, 13], [14, 15]],
      ]
      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 10 for calling the LegacyRebatchDatasetTest obj's underlying member method code with example usage: obj.testMultipleBatches() without return types