code: def testMultiDeviceDataCapturedFunction(self, distribution):
      inputs = constant_op.constant([2.0, 3.0])
      dataset = lambda _: dataset_ops.Dataset.from_tensor_slices(
          inputs
      ).repeat(5)
      input_iterator = iter(
          distribution.distribute_datasets_from_function(dataset)
      )
      with distribution.scope():
          var = variables.Variable(1.0)
  
      @def_function.function
      def train_step(input_iterator):
          def func(inputs):
              return math_ops.square(inputs) + var
  
          per_replica_outputs = distribution.run(
              func, (next(input_iterator),)
          )
          mean = distribution.reduce(
              reduce_util.ReduceOp.MEAN, per_replica_outputs, axis=None
          )
          for _ in dataset_ops.Dataset.range(1):
              per_replica_outputs = distribution.run(
                  func, (next(input_iterator),)
              )
              mean = distribution.reduce(
                  reduce_util.ReduceOp.MEAN,
                  per_replica_outputs,
                  axis=None,
              )
          return mean
  
      with distribution.scope():
          if distribution.num_replicas_in_sync == 1:
              self.assertAlmostEqual(
                  10.0, self.evaluate(train_step(input_iterator))
              )
          else:
              self.assertAlmostEqual(
                  7.5, self.evaluate(train_step(input_iterator))
              )
  
imports: from absl.testing import parameterized
  from tensorflow.python import tf2
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute import strategy_combinations
  from tensorflow.python.distribute import test_util
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import test
  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 array_ops
  from tensorflow.python.ops import control_flow_assert
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.losses import losses
  from tensorflow.python.tpu import tpu
  from tensorflow.python.util import nest
label_desc: Use image node_id 37 for calling the InputIterationTest obj's underlying member method code with example usage: obj.testMultiDeviceDataCapturedFunction(distribution) and returns: mean, unknown