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107 lines
3.6 KiB
107 lines
3.6 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import time
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import unittest
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from multiprocessing import Process
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import numpy
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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class TestSendOp(unittest.TestCase):
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@unittest.skip(
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"This test is buggy. We cannot use time.sleep to sync processes, the connection may fail in unittest."
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)
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def test_send(self):
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# Run init_serv in a thread
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place = fluid.CPUPlace()
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# NOTE: python thread will not work here due to GIL.
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p = Process(target=self.init_serv, args=(place, ))
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p.daemon = True
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p.start()
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time.sleep(10)
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with open("/tmp/paddle.%d.port" % p.pid, "r") as fn:
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selected_port = int(fn.readlines()[0])
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self.init_client(place, selected_port)
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self.run_local(place)
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self.assertTrue(numpy.allclose(self.local_out, self.dist_out))
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# FIXME(typhoonzero): find a way to gracefully shutdown the server.
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os.system("kill -9 %d" % p.pid)
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p.join()
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def init_serv(self, place):
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main = fluid.Program()
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with fluid.program_guard(main):
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serv = layers.ListenAndServ(
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"127.0.0.1:0", ["X"], optimizer_mode=False)
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with serv.do():
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out_var = main.global_block().create_var(
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name="scale_0.tmp_0",
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psersistable=True,
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dtype="float32",
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shape=[32, 32])
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x = layers.data(
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shape=[32, 32],
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dtype='float32',
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name="X",
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append_batch_size=False)
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fluid.initializer.Constant(value=1.0)(x, main.global_block())
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layers.scale(x=x, scale=10.0, out=out_var)
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self.server_exe = fluid.Executor(place)
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self.server_exe.run(main)
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def init_client(self, place, port):
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main = fluid.Program()
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with fluid.program_guard(main):
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x = layers.data(
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shape=[32, 32],
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dtype='float32',
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name='X',
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append_batch_size=False)
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fluid.initializer.Constant(value=2.3)(x, main.global_block())
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get_var = main.global_block().create_var(
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name="scale_0.tmp_0", # server side var
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dtype="float32",
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persistable=False,
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shape=[32, 32])
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o = layers.Send("127.0.0.1:%d" % port, [x], [get_var])
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exe = fluid.Executor(place)
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self.dist_out = exe.run(main, fetch_list=o) # o is a list
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def run_local(self, place):
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main = fluid.Program()
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with fluid.program_guard(main):
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x = layers.data(
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shape=[32, 32],
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dtype='float32',
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name='X',
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append_batch_size=False)
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fluid.initializer.Constant(value=2.3)(x, main.global_block())
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o = layers.scale(x=x, scale=10.0)
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exe = fluid.Executor(place)
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self.local_out = exe.run(main, fetch_list=[o])
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if __name__ == "__main__":
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unittest.main()
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