code: def testTensorGotAfterWorkerFailure(self):
      with self.strategy.scope():
          v = variables.Variable(initial_value=0, dtype=dtypes.int32)
  
      @def_function.function
      def worker_fn():
          return v + 1, v - 1
  
      remote_value = self.cluster_coord.schedule(worker_fn)
  
      # Attempt to fetch before killing worker task should succeed.
      fetched = remote_value.get()[0]
      self.assertIsInstance(fetched, tensor.Tensor)
      self.assertEqual(
          fetched.device, "/job:chief/replica:0/task:0/device:CPU:0"
      )
      self.assertEqual((1, -1), remote_value.get())
      remote_value.get()[0].numpy()
  
      # As well as the remote tensors that point to worker0 or worker1.
      values = remote_value._values[0]
      self.assertIsInstance(values, tensor.Tensor)
      self.assertRegex(
          values.device, "/job:worker/replica:0/task:[0-1]/device:CPU:0"
      )
      self.assertEqual((1, -1), remote_value._values)
      remote_value._values[0].numpy()
  
      # Terminate the workers and wait a little so that they are indeed killed.
      for i in range(self.num_workers):
          self._cluster.kill_task("worker", i)
      time.sleep(5)
  
      # Attempt to fetch after killing worker tasks should succeed as well.
      remote_value.get()[0].numpy()
      self.assertEqual((1, -1), remote_value.get())
  
      # Attempting to copy the tensor from worker now should fail.
      with self.assertRaises(errors.UnavailableError) as cm:
          remote_value._values[0].numpy()
      self.assertIn(
          "failed to connect to all addresses", cm.exception.message
      )
      self.assertIn("/job:worker/replica:0/task:", cm.exception.message)
  
imports: import gc
  import os
  import sys
  import threading
  import time
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import multi_worker_test_base
  from tensorflow.python.distribute import parameter_server_strategy_v2
  from tensorflow.python.distribute import test_util
  from tensorflow.python.distribute.cluster_resolver.cluster_resolver import SimpleClusterResolver
  from tensorflow.python.distribute.coordinator import cluster_coordinator
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import coordinator
  from tensorflow.python.training import server_lib
label_desc: Use image node_id 20 for calling the BaseFaultToleranceTest obj's underlying member method code with example usage: obj.testTensorGotAfterWorkerFailure() and returns: unknown,  unknown