code: def test_checkpoint_restore_with_different_layout(self, shard_spec):
      tensor_a = stateless_random_ops.stateless_random_uniform(
          shape=[4, 8], seed=[0, 1]
      )
      tensor_b = stateless_random_ops.stateless_random_uniform(
          shape=[2, 4], seed=[0, 1]
      )
  
      layout = Layout(shard_spec, self.mesh)
  
      dvariable_a = d_variable.DVariable(
          numpy_util.pack_numpy(tensor_a, layout)
      )
      dvariable_b = d_variable.DVariable(
          numpy_util.pack_numpy(tensor_b, layout)
      )
  
      # Record a checkpoint with two dvariables.
      checkpoint_1 = checkpoint.Checkpoint(a=dvariable_a, b=dvariable_b)
  
      saved_path = checkpoint_1.save(self.get_temp_dir())
  
      new_layout = Layout([_MESH_DIM_X, _MESH_DIM_Y], self.mesh)
  
      # Create new Dvariables, zero'd out with different layouts
      # from the layouts we saved the tensors.
      dvariable_a = d_variable.DVariable(
          numpy_util.pack_numpy(
              array_ops.zeros([4, 8], dtype=dtypes.float32), new_layout
          )
      )
      dvariable_b = d_variable.DVariable(
          numpy_util.pack_numpy(
              array_ops.zeros([2, 4], dtype=dtypes.float32), new_layout
          )
      )
  
      checkpoint_2 = checkpoint.Checkpoint(a=dvariable_a, b=dvariable_b)
  
      checkpoint_2.restore(saved_path)
  
      self.assertDTensorEqual(
          tensor_a, new_layout, dvariable_a.read_value()
      )
      self.assertDTensorEqual(
          tensor_b, new_layout, dvariable_b.read_value()
      )
  
imports: import gc
  from absl.testing import parameterized
  import numpy
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import d_variable
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python import numpy_util
  from tensorflow.dtensor.python.tests import test_util
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.checkpoint import checkpoint_management
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.module import module
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the DTensorSaveRestoreV2Test obj's underlying member method code with example usage: obj.test_checkpoint_restore_with_different_layout(shard_spec) without return types