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fd925943
编写于
11月 21, 2016
作者:
W
wangyang59
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差异文件
added test_ConvUnify
上级
98f4c761
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2
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2 changed file
with
140 addition
and
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+140
-0
paddle/gserver/tests/CMakeLists.txt
paddle/gserver/tests/CMakeLists.txt
+7
-0
paddle/gserver/tests/test_ConvUnify.cpp
paddle/gserver/tests/test_ConvUnify.cpp
+133
-0
未找到文件。
paddle/gserver/tests/CMakeLists.txt
浏览文件 @
fd925943
...
...
@@ -34,7 +34,14 @@ add_unittest_without_exec(test_ConvTrans
add_test
(
NAME test_ConvTrans
COMMAND test_ConvTrans
)
################# test_ConvUnify #######################
add_unittest_without_exec
(
test_ConvUnify
test_ConvUnify.cpp
LayerGradUtil.cpp
TestUtil.cpp
)
add_test
(
NAME test_ConvUnify
COMMAND test_ConvUnify
)
################## test_Evaluator #######################
add_unittest
(
test_Evaluator
test_Evaluator.cpp
...
...
paddle/gserver/tests/test_ConvUnify.cpp
0 → 100644
浏览文件 @
fd925943
/* Copyright (c) 2016 Baidu, Inc. 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. */
#include <gtest/gtest.h>
#include <vector>
#include <string>
#include "paddle/gserver/layers/DataLayer.h"
#include "ModelConfig.pb.h"
#include "paddle/trainer/Trainer.h"
#include "paddle/utils/GlobalConstants.h"
#include "paddle/gserver/layers/ExpandConvTransLayer.h"
#include "paddle/math/MathUtils.h"
#include "TestUtil.h"
#include "LayerGradUtil.h"
using
namespace
paddle
;
// NOLINT
using
namespace
std
;
// NOLINT
P_DECLARE_bool
(
use_gpu
);
P_DECLARE_int32
(
gpu_id
);
P_DECLARE_double
(
checkgrad_eps
);
P_DECLARE_bool
(
thread_local_rand_use_global_seed
);
P_DECLARE_bool
(
prev_batch_state
);
// Do one forward pass of convTrans layer and check to see if its output
// matches the given result
MatrixPtr
doOneConvTest
(
size_t
imgSize
,
size_t
output_x
,
size_t
stride
,
size_t
padding
,
size_t
filter_size
,
size_t
channel
,
size_t
numfilters
,
MatrixPtr
&
inputData
,
real
*
param
,
bool
useGpu
)
{
TestConfig
config
;
config
.
biasSize
=
numfilters
;
if
(
useGpu
)
{
config
.
layerConfig
.
set_type
(
"cudnn_conv"
);
}
else
{
config
.
layerConfig
.
set_type
(
"exconv"
);
}
config
.
layerConfig
.
set_num_filters
(
numfilters
);
config
.
layerConfig
.
set_partial_sum
(
1
);
config
.
layerConfig
.
set_shared_biases
(
true
);
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_0"
,
imgSize
*
imgSize
*
channel
,
channel
*
filter_size
*
filter_size
*
config
.
layerConfig
.
num_filters
()});
LayerInputConfig
*
input
=
config
.
layerConfig
.
add_inputs
();
ConvConfig
*
conv
=
input
->
mutable_conv_conf
();
conv
->
set_filter_size
(
filter_size
);
conv
->
set_filter_size_y
(
filter_size
);
conv
->
set_channels
(
channel
);
conv
->
set_padding
(
padding
);
conv
->
set_padding_y
(
padding
);
conv
->
set_stride
(
stride
);
conv
->
set_stride_y
(
stride
);
conv
->
set_groups
(
1
);
conv
->
set_filter_channels
(
channel
);
conv
->
set_img_size
(
imgSize
);
conv
->
set_output_x
(
output_x
);
config
.
layerConfig
.
set_size
(
conv
->
output_x
()
*
conv
->
output_x
()
*
config
.
layerConfig
.
num_filters
());
config
.
layerConfig
.
set_name
(
"conv"
);
std
::
vector
<
DataLayerPtr
>
dataLayers
;
LayerMap
layerMap
;
vector
<
Argument
>
datas
;
initDataLayer
(
config
,
&
dataLayers
,
&
datas
,
&
layerMap
,
"conv"
,
1
,
false
,
useGpu
);
dataLayers
[
0
]
->
getOutputValue
()
->
zeroMem
();
dataLayers
[
0
]
->
getOutputValue
()
->
copyFrom
(
*
inputData
);
// test layer initialize
std
::
vector
<
ParameterPtr
>
parameters
;
LayerPtr
convLayer
;
initTestLayer
(
config
,
&
layerMap
,
&
parameters
,
&
convLayer
);
convLayer
->
getBiasParameter
()
->
zeroMem
();
convLayer
->
getParameters
()[
0
]
->
zeroMem
();
convLayer
->
getParameters
()[
0
]
->
getBuf
(
PARAMETER_VALUE
)
->
copyFrom
(
param
,
18
);
convLayer
->
forward
(
PASS_GC
);
return
convLayer
->
getOutputValue
();
}
TEST
(
Layer
,
convTransLayerFwd2
)
{
MatrixPtr
input
,
resultCpu
,
resultGpu
;
input
=
Matrix
::
create
(
1
,
4
*
4
,
false
,
false
);
float
inputData
[]
=
{
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
,
11
,
12
,
13
,
14
,
15
,
16
};
float
param
[]
=
{
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
9
,
8
,
7
,
6
,
5
,
4
,
3
,
2
,
1
};
input
->
setData
(
inputData
);
resultCpu
=
doOneConvTest
(
/* imgSize */
4
,
/* output_x */
2
,
/* stride */
1
,
/* padding */
0
,
/* filter_size */
3
,
/*channel*/
1
,
/*numfilters*/
2
,
input
,
param
,
false
);
resultGpu
=
doOneConvTest
(
/* imgSize */
4
,
/* output_x */
2
,
/* stride */
1
,
/* padding */
0
,
/* filter_size */
3
,
/*channel*/
1
,
/*numfilters*/
2
,
input
,
param
,
true
);
checkMatrixEqual
(
resultCpu
,
resultGpu
);
}
int
main
(
int
argc
,
char
**
argv
)
{
testing
::
InitGoogleTest
(
&
argc
,
argv
);
initMain
(
argc
,
argv
);
FLAGS_thread_local_rand_use_global_seed
=
true
;
srand
(
1
);
return
RUN_ALL_TESTS
();
}
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