code: def test_spmd_variable_structure(self, enable_packing):
      strategy, num_replicas = get_tpu_strategy(enable_spmd=True)
  
      # pylint: disable=protected-access
      if enable_packing:
          self.assertTrue(
              strategy._enable_packed_variable_in_eager_mode,
              "packed variables should be enabled by default",
          )
      else:
          strategy._enable_packed_variable_in_eager_mode = False
      # pylint: enable=protected-access
  
      tensor = constant_op.constant([[0.0, 1.0], [2.0, 3.0]])
  
      # Test TPUMirroredVariable and TPUSyncOnReadVariable
      with strategy.scope():
          v = variables.Variable(
              tensor,
              name="v",
              synchronization=vs.VariableSynchronization.ON_READ,
          )
          w = variables.Variable(
              tensor,
              name="w",
              synchronization=vs.VariableSynchronization.ON_WRITE,
          )
  
      def test_read(x):
          @def_function.function
          def fn():
              return x.read_value()
  
          results = strategy.run(fn)
          results = strategy.experimental_local_results(results)
  
          for i in range(num_replicas):
              self.assertAllClose(results[i], tensor)
  
      def test_structure(values):
          for i, value in enumerate(values):
              self.assertIsInstance(
                  value, tpu_replicated_variable.TPUReplicatedVariable
              )
              packed_var = getattr(value, "_packed_var", None)
              if enable_packing:
                  if i == 0:
                      self.assertIsInstance(
                          packed_var, packed.PackedDistributedVariable
                      )
                  else:
                      self.assertIs(
                          packed_var,
                          values[
                              0
                          ]._packed_var,  # pylint: disable=protected-access
                          "all vals should share the same packed var instance",
                      )
              else:
                  self.assertIsNone(packed_var)
  
          if enable_packing:
              # pylint: disable=protected-access
              resources = sum((value._vars for value in values), [])
              dist_vars = packed_var._distributed_variables
              # pylint: enable=protected-access
              self.assertLen(resources, len(dist_vars))
              for dist_var, resource in zip(dist_vars, resources):
                  self.assertIs(dist_var, resource)
  
      test_read(v)
      test_structure(v.values)
      test_read(w)
      test_structure(w.values)
  
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 1 for calling the TPUStrategyModelParallelismTest obj's underlying member method code with example usage: obj.test_spmd_variable_structure(enable_packing) and returns: x