code: def testCapturedInputs(self, num_parallel_calls):
      a = constant_op.constant(3, dtype=dtypes.int64)
      b = constant_op.constant(4, dtype=dtypes.int64)
      some_tensor = math_ops.mul(a, b)
  
      dataset = dataset_ops.Dataset.range(1)
      # We currently do not support functions with captured inputs.
      if num_parallel_calls in [2, dataset_ops.AUTOTUNE]:
          dataset = dataset.apply(
              testing.assert_next(["ParallelMap", "ParallelMap"])
          )
      else:
          dataset = dataset.apply(testing.assert_next(["Map", "Map"]))
  
      dataset = dataset.map(
          lambda x: some_tensor, num_parallel_calls=num_parallel_calls
      ).map(lambda x: x, num_parallel_calls=num_parallel_calls)
  
      options = options_lib.Options()
      options.experimental_optimization.apply_default_optimizations = (
          False
      )
      options.experimental_optimization.map_fusion = True
      dataset = dataset.with_options(options)
      self.assertDatasetProduces(dataset, expected_output=[some_tensor])
  
imports: import functools
  from absl.testing import parameterized
  from tensorflow.python.data.experimental.ops import testing
  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 ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the MapFusionTest obj's underlying member method code with example usage: obj.testCapturedInputs(num_parallel_calls) without return types