text: #   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import unittest
  
  import paddle.fluid as fluid
  import paddle.fluid.layers as layers
  import numpy
  from multiprocessing import Process
  import os, sys
  import time
  
  
  class TestRecvOp(unittest.TestCase):
      def no_test_send(self):
          # Run init_serv in a thread
          place = fluid.CPUPlace()
          p = Process(target=self.init_serv, args=(place, ))
          p.daemon = True
          p.start()
          time.sleep(1)
          self.init_client(place)
          # FIXME(typhoonzero): find a way to gracefully shutdown the server.
          os.system("kill -9 %d" % p.pid)
          p.join()
  
      def init_serv(self, place):
          main = fluid.Program()
          with fluid.program_guard(main):
              serv = layers.ListenAndServ(
                  "127.0.0.1:6174", ["X"], optimizer_mode=False)
              with serv.do():
                  x = layers.data(
                      shape=[32, 32],
                      dtype='float32',
                      name="X",
                      append_batch_size=False)
                  fluid.initializer.Constant(value=1.0)(x, main.global_block())
                  o = layers.scale(x=x, scale=10.0)
              main.global_block().create_var(
                  name=o.name, psersistable=False, dtype=o.dtype, shape=o.shape)
          exe = fluid.Executor(place)
          exe.run(main)
  
      def init_client(self, place):
          main = fluid.Program()
          with fluid.program_guard(main):
              x = layers.data(
                  shape=[32, 32],
                  dtype='float32',
                  name='X',
                  append_batch_size=False)
              fluid.initializer.Constant(value=1.0)(x, main.global_block())
              layers.Send("127.0.0.1:6174", [x], [x])
          exe = fluid.Executor(place)
          exe.run(main)
  
  
  if __name__ == "__main__":
      unittest.main()
  