code: def test(self, verify_fn, symbolic_checkpoint, num_parallel_calls):
      tensor_slice_len = 8
      batch_size = 2
      options = options_lib.Options()
      options.experimental_symbolic_checkpoint = symbolic_checkpoint
      num_outputs = tensor_slice_len // batch_size
      verify_fn(
          self,
          lambda: self._build_dataset(
              15.0,
              tensor_slice_len,
              batch_size,
              num_parallel_calls,
              options,
          ),
          num_outputs,
      )
  
imports: import time
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.checkpoint import checkpoint_management
  from tensorflow.python.data.experimental.ops import random_access
  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.data.util import nest
  from tensorflow.python.framework import combinations
  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 math_ops
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops.ragged import ragged_concat_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the BatchCheckpointTest obj's underlying member method code with example usage: obj.test(verify_fn, symbolic_checkpoint, num_parallel_calls) without return types