code: def testMapThenFlatMap(self, verify_fn):
      def build_ds():
          def flat_map_fn(_):
              def map_fn(y):
                  return 10 * math_ops.cast(y, dtypes.int32)
  
              return dataset_ops.Dataset.range(100).map(map_fn)
  
          return dataset_ops.Dataset.range(5).flat_map(flat_map_fn)
  
      verify_fn(self, build_ds, num_outputs=500)
  
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 3 for calling the FlatMapCheckpointTest obj's underlying member method code with example usage: obj.testMapThenFlatMap(verify_fn) and returns: dataset_ops, dataset_ops, unknown