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34cffe91
编写于
4月 16, 2018
作者:
T
typhoonzero
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python/paddle/fluid/tests/unittests/test_dist_train_op.py
python/paddle/fluid/tests/unittests/test_dist_train_op.py
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python/paddle/fluid/tests/unittests/test_dist_train_op.py
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# 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.core
as
core
import
paddle.fluid.layers
as
layers
import
numpy
from
multiprocessing
import
Process
from
threading
import
Thread
import
os
,
sys
import
time
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
()
time
.
sleep
(
8
)
with
open
(
"/tmp/paddle.selected_port"
,
"r"
)
as
fn
:
selected_port
=
int
(
fn
.
readlines
()[
0
])
self
.
init_client
(
place
,
selected_port
)
# FIXME(typhoonzero): find a way to gracefully shutdown the server.
os
.
system
(
"kill -9 %d"
%
p
.
pid
)
p
.
join
()
self
.
run_local
(
place
)
self
.
assertTrue
(
numpy
.
allclose
(
self
.
local_out
,
self
.
dist_out
))
def
init_serv
(
self
,
place
):
main
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main
):
serv
=
layers
.
ListenAndServ
(
"127.0.0.1:0"
,
[
"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
)
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
):
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
])
o
=
layers
.
Send
(
"127.0.0.1:%d"
%
port
,
[
x
],
[
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
()
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