code: def _build_dataset(self, num_elements, symbolic_checkpoint):
      dataset = dataset_ops.Dataset.from_tensors(1).repeat(num_elements)
      dataset = dataset.scan(
          initial_state=[0, 1],
          scan_func=lambda a, _: ([a[1], a[0] + a[1]], a[1]),
      )
      options = options_lib.Options()
      options.experimental_symbolic_checkpoint = symbolic_checkpoint
      return dataset.with_options(options)
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  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.ops import scan_op
  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 ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_v2_toggles
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the ScanCheckpointTest obj's underlying member method code with example usage: obj._build_dataset(num_elements, symbolic_checkpoint) and returns: dataset