code: def testMapAndBatchYieldsPartialBatch(self):
      dataset = dataset_ops.Dataset.range(10).apply(
          batching.map_and_batch(
              lambda x: array_ops.reshape(x * x, [1]), 4
          )
      )
  
      self.assertEqual(
          [None, 1],
          dataset_ops.get_legacy_output_shapes(dataset).as_list(),
      )
      expected_output = [
          [[0], [1], [4], [9]],
          [[16], [25], [36], [49]],
          [[64], [81]],
      ]
      self.assertDatasetProduces(
          dataset, expected_output=expected_output
      )
  
imports: import math
  from absl.testing import parameterized
  import numpy
  from tensorflow.python import pywrap_sanitizers
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.checkpoint import checkpoint_management
  from tensorflow.python.data.experimental.ops import batching
  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.ops import options
  from tensorflow.python.eager import context
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the MapAndBatchTest obj's underlying member method code with example usage: obj.testMapAndBatchYieldsPartialBatch() without return types