code: def test(self, verify_fn, symbolic_checkpoint):
      # Complicated way of saying range(start, start+25).
      def build_ds(start):
          def map_fn(x):
              return dataset_ops.Dataset.range(x, x + 5)
  
          dataset = dataset_ops.Dataset.range(start, start + 5 * 5, 5)
          dataset = dataset.flat_map(map_fn)
          options = options_lib.Options()
          options.experimental_symbolic_checkpoint = symbolic_checkpoint
          return dataset.with_options(options)
  
      verify_fn(self, lambda: build_ds(0), num_outputs=25)
  
imports: import random
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.client import session
  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.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 function
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops.ragged import ragged_conversion_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
  from tensorflow.python.training import server_lib
label_desc: Use image node_id 1 for calling the FlatMapCheckpointTest obj's underlying member method code with example usage: obj.test(verify_fn, symbolic_checkpoint) and returns: dataset, dataset_ops