code: def test_mnist(self):
      def train():
          input_layout = d_layout.Layout.batch_sharded(
              self.mesh, _BATCH_DIM, rank=4
          )
          (n_w, n_b, n_k), (w, b, k) = init_var(self.mesh)
          for i in range(_STEPS):
              data = stateless_random_ops.stateless_random_normal(
                  [_BATCH_SIZE, 28, 28, 1], seed=[0, i]
              )
              g_nw, g_nb, n_loss = _run_step(
                  data.numpy(), n_w, n_b, n_k
              )
  
              input_image = d_api.copy_to_mesh(
                  data,
                  layout=d_layout.Layout.replicated(self.mesh, rank=4),
              )
              input_image = d_api.relayout(
                  input_image, layout=input_layout
              )
  
              with ops.device_v2(self.mesh.local_devices()[0]):
                  gw, gb, loss = _run_step(input_image, w, b, k)
  
          gw = d_api.relayout(
              gw, d_layout.Layout.replicated(self.mesh, rank=2)
          )
          w = d_api.relayout(
              w, d_layout.Layout.replicated(self.mesh, rank=2)
          )
          gb = d_api.relayout(
              gb, d_layout.Layout.replicated(self.mesh, rank=1)
          )
          b = d_api.relayout(
              b, d_layout.Layout.replicated(self.mesh, rank=1)
          )
  
          return (n_loss, g_nw, g_nb, n_w, n_b), (loss, gw, gb, w, b)
  
      (n_loss, g_nw, g_nb, n_w, n_b), (loss, gw, gb, w, b) = train()
  
      self.assertAllClose(n_loss, loss, atol=5e-4)
      self.assertAllClose(g_nw, gw, atol=1e-5)
      self.assertAllClose(g_nb, gb, atol=1e-5)
      self.assertAllClose(n_w, w, atol=1e-5)
      self.assertAllClose(n_b, b, atol=1e-5)
  
imports: import os
  from absl import flags
  import numpy
  from tensorflow.dtensor.python import accelerator_util
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import config
  from tensorflow.dtensor.python import d_variable
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python import mesh_util
  from tensorflow.dtensor.python.tests import multi_client_test_util
  from tensorflow.dtensor.python.tests import test_backend_util
  from tensorflow.dtensor.python.tests import test_util
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager.polymorphic_function import polymorphic_function
  from tensorflow.python.framework import config
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the DTensorMNISTTest obj's underlying member method code with example usage: obj.test_mnist() and returns: n_loss,  g_nw,  g_nb,  n_w,  n_b,  loss,  gw,  gb,  w,  b