# 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 os import time import unittest from multiprocessing import Process import signal import numpy import paddle.fluid as fluid import paddle.fluid.layers as layers from paddle.fluid.layers.io import ListenAndServ from paddle.fluid.layers.io import Recv from paddle.fluid.layers.io import Send from paddle.fluid import core RPC_OP_ROLE_ATTR_NAME = op_role_attr_name = core.op_proto_and_checker_maker.kOpRoleAttrName( ) RPC_OP_ROLE_ATTR_VALUE = core.op_proto_and_checker_maker.OpRole.RPC class TestSendOp(unittest.TestCase): def test_send(self): # Run init_serv in a thread place = fluid.CPUPlace() # NOTE: python thread will not work here due to GIL. p = Process(target=self.init_serv, args=(place, )) p.daemon = True p.start() self.ps_timeout = 5 self._wait_ps_ready(p.pid) with open("/tmp/paddle.%d.port" % p.pid, "r") as fn: selected_port = int(fn.readlines()[0]) self.init_client(place, selected_port) self.run_local(place) self.assertTrue(numpy.allclose(self.local_out, self.dist_out)) # FIXME(typhoonzero): find a way to gracefully shutdown the server. os.kill(p.pid, signal.SIGKILL) p.join() def _wait_ps_ready(self, pid): start_left_time = self.ps_timeout sleep_time = 0.5 while True: assert start_left_time >= 0, "wait ps ready failed" time.sleep(sleep_time) try: # the listen_and_serv_op would touch a file which contains the listen port # on the /tmp directory until it was ready to process all the RPC call. os.stat("/tmp/paddle.%d.port" % pid) return except os.error: start_left_time -= sleep_time def init_serv(self, place): main = fluid.Program() with fluid.program_guard(main): serv = ListenAndServ("127.0.0.1:0", ["X"], optimizer_mode=False) with serv.do(): out_var = main.global_block().create_var( name="scale_0.tmp_0", psersistable=True, dtype="float32", shape=[32, 32]) 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.scale(x=x, scale=10.0, out=out_var) self.server_exe = fluid.Executor(place) self.server_exe.run(main) def init_client(self, place, port): main = fluid.Program() with fluid.program_guard(main): main.global_block().append_op( type="fetch_barrier", inputs={}, outputs={}, attrs={ "endpoints": ["127.0.0.1:{0}".format(port)], RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE }) x = layers.data( shape=[32, 32], dtype='float32', name='X', append_batch_size=False) fluid.initializer.Constant(value=2.3)(x, main.global_block()) get_var = main.global_block().create_var( name="scale_0.tmp_0", # server side var dtype="float32", persistable=False, shape=[32, 32]) fluid.initializer.Constant(value=2.3)(get_var, main.global_block()) Send("127.0.0.1:%d" % port, [x]) o = Recv("127.0.0.1:%d" % port, [get_var]) exe = fluid.Executor(place) self.dist_out = exe.run(main, fetch_list=o) # o is a list def run_local(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=2.3)(x, main.global_block()) o = layers.scale(x=x, scale=10.0) exe = fluid.Executor(place) self.local_out = exe.run(main, fetch_list=[o]) if __name__ == "__main__": unittest.main()