code: def testParameterServerMultiExecutors(self):
      context.update_server_def(server_def=self.server_def_s1_s2_s3_s4)
  
      with ops.device(self.device_t1):
          v1 = variables.Variable(initial_value=0.0)
      with ops.device(self.device_t2):
          v2 = variables.Variable(initial_value=10.0)
  
      @def_function.function
      def worker_fn():
          x1 = v1.read_value()
          x2 = v2.read_value()
          grad = (x1 + x2) * 0.1
          v1.assign_add(grad)
          v2.assign_sub(grad)
          return v1 + v2
  
      worker_fn.get_concrete_function()
  
      executor_t3 = executor.new_executor(enable_async=False)
      executor_t4 = executor.new_executor(enable_async=False)
  
      num_calls = 10
      self._coord = coordinator.Coordinator()
  
      def thread_fn(executor_obj, device, results):
          with self._coord.stop_on_exception():
              for i in range(num_calls):
                  with context.executor_scope(executor_obj):
                      with ops.device(device):
                          results[i] = worker_fn()
  
      def update_server_def_fn():
          with self._coord.stop_on_exception():
              for _ in range(30):
                  context.update_server_def(self.server_def_s1_s2_s3_s4)
  
      t3_results = [None] * num_calls
      t4_results = [None] * num_calls
      threads = []
      threads.append(
          threading.Thread(
              target=thread_fn,
              args=(executor_t3, self.device_t3, t3_results),
          )
      )
      threads.append(
          threading.Thread(
              target=thread_fn,
              args=(executor_t4, self.device_t4, t4_results),
          )
      )
      threads.append(threading.Thread(target=update_server_def_fn))
      for t in threads:
          t.start()
      self._coord.join(threads)
  
      # Cannot assert individual values since the results are non-deterministic.
      # By summing up the value we ensure that there are all reasonable and valid
      # numbers (not `None` or `NaN`).
      total = np.sum(t3_results + t4_results)
      self.assertGreater(total, 0)
  
imports: import os
  import threading
  from absl.testing import parameterized
  import numpy
  from tensorflow.core.distributed_runtime.preemption import gen_check_preemption_op
  from tensorflow.core.protobuf import cluster_pb2
  from tensorflow.core.protobuf import tensorflow_server_pb2
  from tensorflow.python import pywrap_tfe
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import executor
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import coordinator
  from tensorflow.python.training import server_lib
label_desc: Use image node_id 20 for calling the DynamicClusterTest obj's underlying member method code with example usage: obj.testParameterServerMultiExecutors() and returns: unknown