test_recv_op.py 2.5 KB
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#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
# 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.v2.fluid as fluid
import paddle.v2.fluid.layers as layers
import numpy
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from multiprocessing import Process
import os, sys
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class TestRecvOp(unittest.TestCase):
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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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        p = Process(target=self.init_serv, args=(place, ))
        p.daemon = True
        p.start()
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        self.init_client(place)
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        # FIXME(typhoonzero): find a way to gracefully shutdown the server.
        os.system("kill -9 %d" % p.pid)
        p.join()
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    def init_serv(self, place):
        main = fluid.Program()
        with fluid.program_guard(main):
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            x = layers.data(
                shape=[32, 32],
                dtype='float32',
                name="X",
                append_batch_size=False)
            fluid.initializer.Constant(value=1.0)(x, main.global_block())
            serv = layers.ListenAndServ("127.0.0.1:6174", optimizer_mode=False)
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            with serv.do():
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                o = layers.scale(x=x, scale=10.0)
            main.global_block().create_var(
                name=o.name, psersistable=False, dtype=o.dtype, shape=o.shape)
            print main
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        exe = fluid.Executor(place)
        exe.run(main)

    def init_client(self, place):
        main = fluid.Program()
        with fluid.program_guard(main):
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            x = layers.data(
                shape=[32, 32],
                dtype='float32',
                name='X',
                append_batch_size=False)
            fluid.initializer.Constant(value=1.0)(x, main.global_block())
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            layers.Send("127.0.0.1:6174", [x], [x])
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            print main
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        exe = fluid.Executor(place)
        exe.run(main)
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if __name__ == "__main__":
    unittest.main()
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    # test = TestRecvOp()
    # place = fluid.CPUPlace()
    # if sys.argv[1] == "server":
    #     test.init_serv(place)
    # else:
    #     test.init_client(place)