code: def testStatefulExperimentalRunAlwaysExecute(self, distribution):
      with distribution.scope():
          v = variables.Variable(
              0.0, aggregation=variables.VariableAggregation.MEAN
          )
  
      @def_function.function
      def train_step():
          def assign_add():
              v.assign_add(1.0)
  
          distribution.run(assign_add)
          return array_ops.zeros([])
  
      train_step()
      self.assertAllEqual(1.0, v.numpy())
  
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 2 for calling the InputIterationTest obj's underlying member method code with example usage: obj.testStatefulExperimentalRunAlwaysExecute(distribution) and returns: array_ops