code: def testConstantNumpyInput(self, distribution):
      @def_function.function
      def run(x):
          def computation(x):
              return math_ops.square(x)
  
          outputs = distribution.experimental_local_results(
              distribution.run(computation, args=(x,))
          )
          return outputs
  
      self.assertAllEqual(
          constant_op.constant(
              4.0, shape=(distribution.num_replicas_in_sync)
          ),
          run(2.0),
      )
  
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 1 for calling the InputIterationTest obj's underlying member method code with example usage: obj.testConstantNumpyInput(distribution) and returns: outputs, math_ops