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146 lines
4.9 KiB
146 lines
4.9 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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from __future__ import print_function
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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 signal
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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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from paddle.fluid.layers.io import ListenAndServ
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from paddle.fluid.layers.io import Recv
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from paddle.fluid.layers.io import Send
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import paddle.fluid.layers.ops as ops
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from paddle.fluid import core
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RPC_OP_ROLE_ATTR_NAME = op_role_attr_name = core.op_proto_and_checker_maker.kOpRoleAttrName(
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)
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RPC_OP_ROLE_ATTR_VALUE = core.op_proto_and_checker_maker.OpRole.RPC
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class TestSendOp(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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# 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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self.ps_timeout = 5
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self._wait_ps_ready(p.pid)
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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.kill(p.pid, signal.SIGKILL)
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p.join()
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def _wait_ps_ready(self, pid):
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start_left_time = self.ps_timeout
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sleep_time = 0.5
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while True:
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assert start_left_time >= 0, "wait ps ready failed"
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time.sleep(sleep_time)
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try:
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# the listen_and_serv_op would touch a file which contains the listen port
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# on the /tmp directory until it was ready to process all the RPC call.
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os.stat("/tmp/paddle.%d.port" % pid)
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return
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except os.error:
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start_left_time -= sleep_time
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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 = ListenAndServ("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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ops._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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main.global_block().append_op(
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type="fetch_barrier",
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inputs={},
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outputs={"Out": []},
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attrs={
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"endpoints": ["127.0.0.1:{0}".format(port)],
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RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE
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})
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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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fluid.initializer.Constant(value=2.3)(get_var, main.global_block())
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Send("127.0.0.1:%d" % port, [x])
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o = Recv("127.0.0.1:%d" % port, [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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