code: def test_spmd_variable_update(self):
      batch_size = 1024
      num_feature_in = 256
  
      x = random_ops.random_uniform(
          (batch_size, num_feature_in), dtype=dtypes.float32
      )
      w_init = random_ops.random_uniform(
          (batch_size, num_feature_in), dtype=dtypes.float32
      )
  
      strategy, num_replicas = get_tpu_strategy(enable_spmd=True)
      with strategy.scope():
          w = variables.Variable(w_init, dtype=dtypes.float32)
  
      self.assertIsInstance(w, tpu_values.TPUMirroredVariable)
      self.assertTrue(w._is_replicated_or_sharded_to_logical_cores())
  
      def make_strategy_run(fn):
          def run(value):
              return strategy.run(fn, args=(value,))
  
          return def_function.function(run)
  
      result = make_strategy_run(w.assign)(x)
      self.assertAllClose(
          strategy.reduce("SUM", result, axis=None), x * num_replicas
      )
  
      delta = random_ops.random_uniform(
          (batch_size, num_feature_in), dtype=dtypes.float32
      )
      result = make_strategy_run(w.assign_sub)(delta)
      x -= delta
      self.assertAllClose(
          strategy.reduce("SUM", result, axis=None), x * num_replicas
      )
  
      delta = random_ops.random_uniform(
          (batch_size, num_feature_in), dtype=dtypes.float32
      )
      result = make_strategy_run(w.assign_add)(delta)
      x += delta
      self.assertAllClose(
          strategy.reduce("SUM", result, axis=None), x * num_replicas
      )
  
imports: import os
  from absl.testing import parameterized
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.checkpoint import checkpoint_management
  from tensorflow.python.compiler.xla.experimental import xla_sharding
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import packed_distributed_variable
  from tensorflow.python.distribute import strategy_test_lib
  from tensorflow.python.distribute import tpu_replicated_variable
  from tensorflow.python.distribute import tpu_strategy
  from tensorflow.python.distribute import tpu_values
  from tensorflow.python.distribute.cluster_resolver import tpu_cluster_resolver
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import remote
  from tensorflow.python.eager import test
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import summary_test_util
  from tensorflow.python.module import module
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import summary_ops_v2
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import flags
  from tensorflow.python.tpu import device_assignment
  from tensorflow.python.tpu import tpu_replication
label_desc: Use image node_id 8 for calling the TPUStrategyModelParallelismTest obj's underlying member method code with example usage: obj.test_spmd_variable_update() and returns: def_function, strategy