code: def testSparse(self, verify_fn):
      def build_dataset():
          def map_fn(i):
              return sparse_tensor.SparseTensorValue(
                  indices=[[0]], values=(i * [1]), dense_shape=[1]
              )
  
          return dataset_ops.Dataset.range(10).apply(
              batching.map_and_batch(map_fn, 5)
          )
  
      verify_fn(self, build_dataset, num_outputs=2)
  
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 MapAndBatchCheckpointTest obj's underlying member method code with example usage: obj.testSparse(verify_fn) and returns: dataset_ops, sparse_tensor